Interplanetary Alfvenic fluctuations: A stochastic model
Barnes, A.
1981-01-01
The strong alignment of the average directions of minimum magnetic variance and mean magnetic field in interplanetary Alfvenic fluctuations is inconsistent with the usual wave-propagation models. We investigate the concept of minimum variance for nonplanar Alfvenic fluctuations in which the field direction varies stochastically. It is found that the tendency of the minimum variance and mean field directions to be aligned may be purely a consequence of the randomness of the field direction. In particular, a well-defined direction of minimum variance does not imply that the fluctuations are necessarily planar. The fluctuation power spectrum is a power law for frequencies much higher than the inverse of the correlation time. The probability distribution of directions a randomly fluctuating field of constant magnitude is calculated. A new approach for observational studies of interplanetary fluctuations is suggested
Stochastic dark energy from inflationary quantum fluctuations
Glavan, Dražen; Prokopec, Tomislav; Starobinsky, Alexei A.
2018-05-01
We study the quantum backreaction from inflationary fluctuations of a very light, non-minimally coupled spectator scalar and show that it is a viable candidate for dark energy. The problem is solved by suitably adapting the formalism of stochastic inflation. This allows us to self-consistently account for the backreaction on the background expansion rate of the Universe where its effects are large. This framework is equivalent to that of semiclassical gravity in which matter vacuum fluctuations are included at the one loop level, but purely quantum gravitational fluctuations are neglected. Our results show that dark energy in our model can be characterized by a distinct effective equation of state parameter (as a function of redshift) which allows for testing of the model at the level of the background.
Stochastic thermodynamics, fluctuation theorems and molecular machines
Seifert, Udo
2012-01-01
Stochastic thermodynamics as reviewed here systematically provides a framework for extending the notions of classical thermodynamics such as work, heat and entropy production to the level of individual trajectories of well-defined non-equilibrium ensembles. It applies whenever a non-equilibrium process is still coupled to one (or several) heat bath(s) of constant temperature. Paradigmatic systems are single colloidal particles in time-dependent laser traps, polymers in external flow, enzymes and molecular motors in single molecule assays, small biochemical networks and thermoelectric devices involving single electron transport. For such systems, a first-law like energy balance can be identified along fluctuating trajectories. For a basic Markovian dynamics implemented either on the continuum level with Langevin equations or on a discrete set of states as a master equation, thermodynamic consistency imposes a local-detailed balance constraint on noise and rates, respectively. Various integral and detailed fluctuation theorems, which are derived here in a unifying approach from one master theorem, constrain the probability distributions for work, heat and entropy production depending on the nature of the system and the choice of non-equilibrium conditions. For non-equilibrium steady states, particularly strong results hold like a generalized fluctuation–dissipation theorem involving entropy production. Ramifications and applications of these concepts include optimal driving between specified states in finite time, the role of measurement-based feedback processes and the relation between dissipation and irreversibility. Efficiency and, in particular, efficiency at maximum power can be discussed systematically beyond the linear response regime for two classes of molecular machines, isothermal ones such as molecular motors, and heat engines such as thermoelectric devices, using a common framework based on a cycle decomposition of entropy production. (review article)
Polarized Radiative Transfer in Fluctuating Stochastic Media
Sallah, M.; Degheidy, A.R.; Selim, M.M.
2009-01-01
The problem of polarized radiative transfer in a planar cluttered atmospheric medium (like cloudy atmosphere) is proposed. The solution is presented for an arbitrary absorption and scattering cross sections. The extinction function of the medium is assumed to be a continuous random function of position, with fluctuations about the mean taken as Gaussian distributed. The joint probability distribution function of these Gaussian random variables is used to calculate the ensemble-averaged quantities, such as reflectivity, radiative energy and radiative flux, for an arbitrary correlation function. A modified Gaussian probability distribution function is also used to average the solution in order to exclude the probable negative values of the optical variable. The problem is considered in half space medium which has specular reflecting boundary exposed to unit external incident flux. Numerical results of the average reflectivity, average radiant energy and average net flux are obtained for both Gaussian and modified Gaussian probability density functions at different degrees of polarization
Stochastic approach and fluctuation theorem for charge transport in diodes
Gu, Jiayin; Gaspard, Pierre
2018-05-01
A stochastic approach for charge transport in diodes is developed in consistency with the laws of electricity, thermodynamics, and microreversibility. In this approach, the electron and hole densities are ruled by diffusion-reaction stochastic partial differential equations and the electric field generated by the charges is determined with the Poisson equation. These equations are discretized in space for the numerical simulations of the mean density profiles, the mean electric potential, and the current-voltage characteristics. Moreover, the full counting statistics of the carrier current and the measured total current including the contribution of the displacement current are investigated. On the basis of local detailed balance, the fluctuation theorem is shown to hold for both currents.
Stochastic motion of a particle in a model fluctuating medium
Moreau, M.; Gaveau, B.; Perera, A.; Frankowicz, M.
1993-01-01
We present several models of time fluctuating media with finite memory, consisting in one and two-dimensional lattices, the Modes of which fluctuate between two internal states according to a Poisson process. A particle moves on the lattice, the diffusion by the Modes depending on their internal state. Such models can be used for the microscopic theory of reaction constants in a dense phase, or for the study of diffusion or reactivity in a complex medium. In a number of cases, the transmission probability of the medium is computed exactly; it is shown that stochastic resonances can occur, an optimal transmission being obtained for a convenient choice of parameters. In more general situations, approximate solutions are given in the case of short and moderate memory of the obstacles. The diffusion in an infinite two-dimensional lattice is studied, and the memory is shown to affect the distribution of the particles rather than the diffusion law. (author). 25 refs, 5 figs
Stochastic fluctuations and the detectability limit of network communities.
Floretta, Lucio; Liechti, Jonas; Flammini, Alessandro; De Los Rios, Paolo
2013-12-01
We have analyzed the detectability limits of network communities in the framework of the popular Girvan and Newman benchmark. By carefully taking into account the inevitable stochastic fluctuations that affect the construction of each and every instance of the benchmark, we come to the conclusion that the native, putative partition of the network is completely lost even before the in-degree/out-degree ratio becomes equal to that of a structureless Erdös-Rényi network. We develop a simple iterative scheme, analytically well described by an infinite branching process, to provide an estimate of the true detectability limit. Using various algorithms based on modularity optimization, we show that all of them behave (semiquantitatively) in the same way, with the same functional form of the detectability threshold as a function of the network parameters. Because the same behavior has also been found by further modularity-optimization methods and for methods based on different heuristics implementations, we conclude that indeed a correct definition of the detectability limit must take into account the stochastic fluctuations of the network construction.
Nonlinear dynamics of mushy layers induced by external stochastic fluctuations.
Alexandrov, Dmitri V; Bashkirtseva, Irina A; Ryashko, Lev B
2018-02-28
The time-dependent process of directional crystallization in the presence of a mushy layer is considered with allowance for arbitrary fluctuations in the atmospheric temperature and friction velocity. A nonlinear set of mushy layer equations and boundary conditions is solved analytically when the heat and mass fluxes at the boundary between the mushy layer and liquid phase are induced by turbulent motion in the liquid and, as a result, have the corresponding convective form. Namely, the 'solid phase-mushy layer' and 'mushy layer-liquid phase' phase transition boundaries as well as the solid fraction, temperature and concentration (salinity) distributions are found. If the atmospheric temperature and friction velocity are constant, the analytical solution takes a parametric form. In the more common case when they represent arbitrary functions of time, the analytical solution is given by means of the standard Cauchy problem. The deterministic and stochastic behaviour of the phase transition process is analysed on the basis of the obtained analytical solutions. In the case of stochastic fluctuations in the atmospheric temperature and friction velocity, the phase transition interfaces (mushy layer boundaries) move faster than in the deterministic case. A cumulative effect of these noise contributions is revealed as well. In other words, when the atmospheric temperature and friction velocity fluctuate simultaneously due to the influence of different external processes and phenomena, the phase transition boundaries move even faster. This article is part of the theme issue 'From atomistic interfaces to dendritic patterns'.This article is part of the theme issue 'From atomistic interfaces to dendritic patterns'. © 2018 The Author(s).
Fractional Stochastic Differential Equations Satisfying Fluctuation-Dissipation Theorem
Li, Lei; Liu, Jian-Guo; Lu, Jianfeng
2017-10-01
We propose in this work a fractional stochastic differential equation (FSDE) model consistent with the over-damped limit of the generalized Langevin equation model. As a result of the `fluctuation-dissipation theorem', the differential equations driven by fractional Brownian noise to model memory effects should be paired with Caputo derivatives, and this FSDE model should be understood in an integral form. We establish the existence of strong solutions for such equations and discuss the ergodicity and convergence to Gibbs measure. In the linear forcing regime, we show rigorously the algebraic convergence to Gibbs measure when the `fluctuation-dissipation theorem' is satisfied, and this verifies that satisfying `fluctuation-dissipation theorem' indeed leads to the correct physical behavior. We further discuss possible approaches to analyze the ergodicity and convergence to Gibbs measure in the nonlinear forcing regime, while leave the rigorous analysis for future works. The FSDE model proposed is suitable for systems in contact with heat bath with power-law kernel and subdiffusion behaviors.
Effect of Stochastic Charge Fluctuations on Dust Dynamics
Matthews, Lorin; Shotorban, Babak; Hyde, Truell
2017-10-01
The charging of particles in a plasma environment occurs through the collection of electrons and ions on the particle surface. Depending on the particle size and the plasma density, the standard deviation of the number of collected elementary charges, which fluctuates due to the randomness in times of collisions with electrons or ions, may be a significant fraction of the equilibrium charge. We use a discrete stochastic charging model to simulate the variations in charge across the dust surface as well as in time. The resultant asymmetric particle potentials, even for spherical grains, has a significant impact on the particle coagulation rate as well as the structure of the resulting aggregates. We compare the effects on particle collisions and growth in typical laboratory and astrophysical plasma environments. This work was supported by the National Science Foundation under Grant PHY-1414523.
Stochastic amplification of fluctuations in cortical up-states.
Jorge Hidalgo
Full Text Available Cortical neurons are bistable; as a consequence their local field potentials can fluctuate between quiescent and active states, generating slow 0.5 2 Hz oscillations which are widely known as transitions between Up and Down States. Despite a large number of studies on Up-Down transitions, deciphering its nature, mechanisms and function are still today challenging tasks. In this paper we focus on recent experimental evidence, showing that a class of spontaneous oscillations can emerge within the Up states. In particular, a non-trivial peak around 20 Hz appears in their associated power-spectra, what produces an enhancement of the activity power for higher frequencies (in the 30-90 Hz band. Moreover, this rhythm within Ups seems to be an emergent or collective phenomenon given that individual neurons do not lock to it as they remain mostly unsynchronized. Remarkably, similar oscillations (and the concomitant peak in the spectrum do not appear in the Down states. Here we shed light on these findings by using different computational models for the dynamics of cortical networks in presence of different levels of physiological complexity. Our conclusion, supported by both theory and simulations, is that the collective phenomenon of "stochastic amplification of fluctuations"--previously described in other contexts such as Ecology and Epidemiology--explains in an elegant and parsimonious manner, beyond model-dependent details, this extra-rhythm emerging only in the Up states but not in the Downs.
Stochastic cooling of bunched beams from fluctuation and kinetic theory
Chattopadhyay, S.
1982-09-01
A theoretical formalism for stochastic phase-space cooling of bunched beams in storage rings is developed on the dual basis of classical fluctuation theory and kinetic theory of many-body systems in phase-space. The physics is that of a collection of three-dimensional oscillators coupled via retarded nonconservative interactions determined by an electronic feedback loop. At the heart of the formulation is the existence of several disparate time-scales characterizing the cooling process. Both theoretical approaches describe the cooling process in the form of a Fokker-Planck transport equation in phase-space valid up to second order in the strength and first order in the auto-correlation of the cooling signal. With neglect of the collective correlations induced by the feedback loop, identical expressions are obtained in both cases for the coherent damping and Schottky noise diffusion coefficients. These are expressed in terms of Fourier coefficients in a harmonic decomposition in angle of the generalized nonconservative cooling force written in canonical action-angle variables of the particles in six-dimensional phase-space. Comparison of analytic results to a numerical simulation study with 90 pseudo-particles in a model cooling system is presented
Nonstationary stochastic charge fluctuations of a dust particle in plasmas.
Shotorban, B
2011-06-01
Stochastic charge fluctuations of a dust particle that are due to discreteness of electrons and ions in plasmas can be described by a one-step process master equation [T. Matsoukas and M. Russell, J. Appl. Phys. 77, 4285 (1995)] with no exact solution. In the present work, using the system size expansion method of Van Kampen along with the linear noise approximation, a Fokker-Planck equation with an exact Gaussian solution is developed by expanding the master equation. The Gaussian solution has time-dependent mean and variance governed by two ordinary differential equations modeling the nonstationary process of dust particle charging. The model is tested via the comparison of its results to the results obtained by solving the master equation numerically. The electron and ion currents are calculated through the orbital motion limited theory. At various times of the nonstationary process of charging, the model results are in a very good agreement with the master equation results. The deviation is more significant when the standard deviation of the charge is comparable to the mean charge in magnitude.
Dreimann, Karsten; Linz, Stefan J.
2010-01-01
Graphical abstract: Deterministic surface pattern (left) and its stochastic counterpart (right) arising in a stochastic damped Kuramoto-Sivashinsky equation that serves as a model equation for ion-beam eroded surfaces and is systematically investigated. - Abstract: Using a recently proposed field equation for the surface evolution of ion-beam eroded semiconductor target materials under normal incidence, we systematically explore the impact of additive stochastic fluctuations that are permanently present during the erosion process. Specifically, we investigate the dependence of the surface roughness, the underlying pattern forming properties and the bifurcation behavior on the strength of the fluctuations.
Li, Dongxi; Xu, Wei; Sun, Chunyan; Wang, Liang
2012-01-01
We investigate the phenomenon that stochastic fluctuation induced the competition between tumor extinction and recurrence in the model of tumor growth derived from the catalytic Michaelis–Menten reaction. We analyze the probability transitions between the extinction state and the state of the stable tumor by the Mean First Extinction Time (MFET) and Mean First Return Time (MFRT). It is found that the positional fluctuations hinder the transition, but the environmental fluctuations, to a certain level, facilitate the tumor extinction. The observed behavior could be used as prior information for the treatment of cancer. -- Highlights: ► Stochastic fluctuation induced the competition between extinction and recurrence. ► The probability transitions are investigated. ► The positional fluctuations hinder the transition. ► The environmental fluctuations, to a certain level, facilitate the tumor extinction. ► The observed behavior can be used as prior information for the treatment of cancer.
Li Dongxi, E-mail: lidongxi@mail.nwpu.edu.c [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Xu Wei; Guo, Yongfeng; Xu Yong [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)
2011-01-31
We investigate a stochastic model of tumor growth derived from the catalytic Michaelis-Menten reaction with positional and environmental fluctuations under subthreshold periodic treatment. Firstly, the influences of environmental fluctuations on the treatable stage are analyzed numerically. Applying the standard theory of stochastic resonance derived from the two-state approach, we derive the signal-to-noise ratio (SNR) analytically, which is used to measure the stochastic resonance phenomenon. It is found that the weak environmental fluctuations could induce the extinction of tumor cells in the subthreshold periodic treatment. The positional stability is better in favor of the treatment of the tumor cells. Besides, the appropriate and feasible treatment intensity and the treatment cycle should be highlighted considered in the treatment of tumor cells.
Li Dongxi; Xu Wei; Guo, Yongfeng; Xu Yong
2011-01-01
We investigate a stochastic model of tumor growth derived from the catalytic Michaelis-Menten reaction with positional and environmental fluctuations under subthreshold periodic treatment. Firstly, the influences of environmental fluctuations on the treatable stage are analyzed numerically. Applying the standard theory of stochastic resonance derived from the two-state approach, we derive the signal-to-noise ratio (SNR) analytically, which is used to measure the stochastic resonance phenomenon. It is found that the weak environmental fluctuations could induce the extinction of tumor cells in the subthreshold periodic treatment. The positional stability is better in favor of the treatment of the tumor cells. Besides, the appropriate and feasible treatment intensity and the treatment cycle should be highlighted considered in the treatment of tumor cells.
Noise-sustained fluctuations in stochastic dynamics with a delay.
D'Odorico, Paolo; Laio, Francesco; Ridolfi, Luca
2012-04-01
Delayed responses to external drivers are ubiquitous in environmental, social, and biological processes. Delays may induce oscillations, Hopf bifurcations, and instabilities in deterministic systems even in the absence of nonlinearities. Despite recent advances in the study of delayed stochastic differential equations, the interaction of random drivers with delays remains poorly understood. In particular, it is unclear whether noise-induced behaviors may emerge from these interactions. Here we show that noise may enhance and sustain transient periodic oscillations inherent to deterministic delayed systems. We investigate the conditions conducive to the emergence and disappearance of these dynamics in a linear system in the presence of both additive and multiplicative noise.
Stochastic Eulerian Lagrangian methods for fluid-structure interactions with thermal fluctuations
Atzberger, Paul J.
2011-01-01
We present approaches for the study of fluid-structure interactions subject to thermal fluctuations. A mixed mechanical description is utilized combining Eulerian and Lagrangian reference frames. We establish general conditions for operators coupling these descriptions. Stochastic driving fields for the formalism are derived using principles from statistical mechanics. The stochastic differential equations of the formalism are found to exhibit significant stiffness in some physical regimes. To cope with this issue, we derive reduced stochastic differential equations for several physical regimes. We also present stochastic numerical methods for each regime to approximate the fluid-structure dynamics and to generate efficiently the required stochastic driving fields. To validate the methodology in each regime, we perform analysis of the invariant probability distribution of the stochastic dynamics of the fluid-structure formalism. We compare this analysis with results from statistical mechanics. To further demonstrate the applicability of the methodology, we perform computational studies for spherical particles having translational and rotational degrees of freedom. We compare these studies with results from fluid mechanics. The presented approach provides for fluid-structure systems a set of rather general computational methods for treating consistently structure mechanics, hydrodynamic coupling, and thermal fluctuations.
Emergence of dynamic cooperativity in the stochastic kinetics of fluctuating enzymes
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.
Emergence of dynamic cooperativity in the stochastic kinetics of fluctuating enzymes
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.
Emergence of dynamic cooperativity in the stochastic kinetics of fluctuating enzymes
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.
Giona, Massimiliano; Brasiello, Antonio; Crescitelli, Silvestro
2017-07-01
We analyze the thermodynamic properties of stochastic differential equations driven by smooth Poisson-Kac fluctuations, and their convergence, in the Kac limit, towards Wiener-driven Langevin equations. Using a Markovian embedding of the stochastic work variable, it is proved that the Kac-limit convergence implies a Stratonovich formulation of the limit Langevin equations, in accordance with the Wong-Zakai theorem. Exact moment analysis applied to the case of a purely frictional system shows the occurrence of different regimes and crossover phenomena in the parameter space.
Fluctuating chemohydrodynamics and the stochastic motion of self-diffusiophoretic particles
Gaspard, Pierre; Kapral, Raymond
2018-04-01
The propulsion of active particles by self-diffusiophoresis is driven by asymmetric catalytic reactions on the particle surface that generate a mechanochemical coupling between the fluid velocity and the concentration fields of fuel and product in the surrounding solution. Because of thermal and molecular fluctuations in the solution, the motion of micrometric or submicrometric active particles is stochastic. Coupled Langevin equations describing the translation, rotation, and reaction of such active particles are deduced from fluctuating chemohydrodynamics and fluctuating boundary conditions at the interface between the fluid and the particle. These equations are consistent with microreversibility and the Onsager-Casimir reciprocal relations between affinities and currents and provide a thermodynamically consistent basis for the investigation of the dynamics of active particles propelled by diffusiophoretic mechanisms.
Zhou, Shenggao, E-mail: sgzhou@suda.edu.cn, E-mail: bli@math.ucsd.edu [Department of Mathematics and Mathematical Center for Interdiscipline Research, Soochow University, 1 Shizi Street, Jiangsu, Suzhou 215006 (China); Sun, Hui; Cheng, Li-Tien [Department of Mathematics, University of California, San Diego, La Jolla, California 92093-0112 (United States); Dzubiella, Joachim [Soft Matter and Functional Materials, Helmholtz-Zentrum Berlin, 14109 Berlin, Germany and Institut für Physik, Humboldt-Universität zu Berlin, 12489 Berlin (Germany); Li, Bo, E-mail: sgzhou@suda.edu.cn, E-mail: bli@math.ucsd.edu [Department of Mathematics and Quantitative Biology Graduate Program, University of California, San Diego, La Jolla, California 92093-0112 (United States); McCammon, J. Andrew [Department of Chemistry and Biochemistry, Department of Pharmacology, Howard Hughes Medical Institute, University of California, San Diego, La Jolla, California 92093-0365 (United States)
2016-08-07
Recent years have seen the initial success of a variational implicit-solvent model (VISM), implemented with a robust level-set method, in capturing efficiently different hydration states and providing quantitatively good estimation of solvation free energies of biomolecules. The level-set minimization of the VISM solvation free-energy functional of all possible solute-solvent interfaces or dielectric boundaries predicts an equilibrium biomolecular conformation that is often close to an initial guess. In this work, we develop a theory in the form of Langevin geometrical flow to incorporate solute-solvent interfacial fluctuations into the VISM. Such fluctuations are crucial to biomolecular conformational changes and binding process. We also develop a stochastic level-set method to numerically implement such a theory. We describe the interfacial fluctuation through the “normal velocity” that is the solute-solvent interfacial force, derive the corresponding stochastic level-set equation in the sense of Stratonovich so that the surface representation is independent of the choice of implicit function, and develop numerical techniques for solving such an equation and processing the numerical data. We apply our computational method to study the dewetting transition in the system of two hydrophobic plates and a hydrophobic cavity of a synthetic host molecule cucurbit[7]uril. Numerical simulations demonstrate that our approach can describe an underlying system jumping out of a local minimum of the free-energy functional and can capture dewetting transitions of hydrophobic systems. In the case of two hydrophobic plates, we find that the wavelength of interfacial fluctuations has a strong influence to the dewetting transition. In addition, we find that the estimated energy barrier of the dewetting transition scales quadratically with the inter-plate distance, agreeing well with existing studies of molecular dynamics simulations. Our work is a first step toward the
Proistosescu, C.; Donohoe, A.; Armour, K.; Roe, G.; Stuecker, M. F.; Bitz, C. M.
2017-12-01
Joint observations of global surface temperature and energy imbalance provide for a unique opportunity to empirically constrain radiative feedbacks. However, the satellite record of Earth's radiative imbalance is relatively short and dominated by stochastic fluctuations. Estimates of radiative feedbacks obtained by regressing energy imbalance against surface temperature depend strongly on sampling choices and on assumptions about whether the stochastic fluctuations are primarily forced by atmospheric or oceanic variability (e.g. Murphy and Forster 2010, Dessler 2011, Spencer and Braswell 2011, Forster 2016). We develop a framework around a stochastic energy balance model that allows us to parse the different contributions of atmospheric and oceanic forcing based on their differing impacts on the covariance structure - or lagged regression - of temperature and radiative imbalance. We validate the framework in a hierarchy of general circulation models: the impact of atmospheric forcing is examined in unforced control simulations of fixed sea-surface temperature and slab ocean model versions; the impact of oceanic forcing is examined in coupled simulations with prescribed ENSO variability. With the impact of atmospheric and oceanic forcing constrained, we are able to predict the relationship between temperature and radiative imbalance in a fully coupled control simulation, finding that both forcing sources are needed to explain the structure of the lagged-regression. We further model the dependence of feedback estimates on sampling interval by considering the effects of a finite equilibration time for the atmosphere, and issues of smoothing and aliasing. Finally, we develop a method to fit the stochastic model to the short timeseries of temperature and radiative imbalance by performing a Bayesian inference based on a modified version of the spectral Whittle likelihood. We are thus able to place realistic joint uncertainty estimates on both stochastic forcing and
Mekkaoui, Abdessamad [IEK-4 Forschungszentrum Juelich 52428 (Germany)
2013-07-01
A method to derive stochastic differential equations for intermittent plasma density dynamics in magnetic fusion edge plasma is presented. It uses a measured first four moments (mean, variance, Skewness and Kurtosis) and the correlation time of turbulence to write a Pearson equation for the probability distribution function of fluctuations. The Fokker-Planck equation is then used to derive a Langevin equation for the plasma density fluctuations. A theoretical expectations are used as a constraints to fix the nonlinearity structure of the stochastic differential equation. In particular when the quadratically nonlinear dynamics is assumed, then it is shown that the plasma density is driven by a multiplicative Wiener process and evolves on the turbulence correlation time scale, while the linear growth is quadratically damped by the fluctuation level. Strong criteria for statistical discrimination of experimental time series are proposed as an alternative to the Kurtosis-Skewness scaling. This scaling is broadly used in contemporary literature to characterize edge turbulence, but it is inappropriate because a large family of distributions could share this scaling. Strong criteria allow us to focus on the relevant candidate distribution and approach a nonlinear structure of edge turbulence model.
Kobayashi, Tetsuya J.; Sughiyama, Yuki
2017-07-01
Adaptation in a fluctuating environment is a process of fueling environmental information to gain fitness. Living systems have gradually developed strategies for adaptation from random and passive diversification of the phenotype to more proactive decision making, in which environmental information is sensed and exploited more actively and effectively. Understanding the fundamental relation between fitness and information is therefore crucial to clarify the limits and universal properties of adaptation. In this work, we elucidate the underlying stochastic and information-thermodynamic structure in this process, by deriving causal fluctuation relations (FRs) of fitness and information. Combined with a duality between phenotypic and environmental dynamics, the FRs reveal the limit of fitness gain, the relation of time reversibility with the achievability of the limit, and the possibility and condition for gaining excess fitness due to environmental fluctuation. The loss of fitness due to causal constraints and the limited capacity of real organisms is shown to be the difference between time-forward and time-backward path probabilities of phenotypic and environmental dynamics. Furthermore, the FRs generalize the concept of the evolutionary stable state (ESS) for fluctuating environment by giving the probability that the optimal strategy on average can be invaded by a suboptimal one owing to rare environmental fluctuation. These results clarify the information-thermodynamic structures in adaptation and evolution.
Deng, De-Ming; Chang, Cheng-Hung [Institute of Physics, National Chiao Tung University, Hsinchu 300, Taiwan (China)
2015-05-14
Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.
Deng, De-Ming; Chang, Cheng-Hung
2015-05-14
Conventional studies of biomolecular behaviors rely largely on the construction of kinetic schemes. Since the selection of these networks is not unique, a concern is raised whether and under which conditions hierarchical schemes can reveal the same experimentally measured fluctuating behaviors and unique fluctuation related physical properties. To clarify these questions, we introduce stochasticity into the traditional lumping analysis, generalize it from rate equations to chemical master equations and stochastic differential equations, and extract the fluctuation relations between kinetically and thermodynamically equivalent networks under intrinsic and extrinsic noises. The results provide a theoretical basis for the legitimate use of low-dimensional models in the studies of macromolecular fluctuations and, more generally, for exploring stochastic features in different levels of contracted networks in chemical and biological kinetic systems.
Observation of fluctuations responsible for stochastic ion heating in a turbulent plasma
Amagishi, Y.; Iguchi, H.; Ito, Y.; Kawabe, T.
1977-10-01
Experiments are described in which the correlation time and fluctuation level of ion acoustic waves are measured under the condition of turbulent heating using twin capacitive probes. At the anomalously resistive time, the correlation time becomes shorter, typically several periods of ion waves, and the energy density of the waves is of the order of 10 -2 n sub(e)T sub(e). The ion heating rate previously reported is well explained by these results to be due to stochastic mechanism. (auth.)
QB1 - Stochastic Gene Regulation
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.
Stochastic dynamics of resistive switching: fluctuations lead to optimal particle number
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)
Stochastic dynamics of resistive switching: fluctuations lead to optimal particle number
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.
Fluctuating dynamics of nematic liquid crystals using the stochastic method of lines
Bhattacharjee, A. K.; Menon, Gautam I.; Adhikari, R.
2010-07-01
We construct Langevin equations describing the fluctuations of the tensor order parameter Qαβ in nematic liquid crystals by adding noise terms to time-dependent variational equations that follow from the Ginzburg-Landau-de Gennes free energy. The noise is required to preserve the symmetry and tracelessness of the tensor order parameter and must satisfy a fluctuation-dissipation relation at thermal equilibrium. We construct a noise with these properties in a basis of symmetric traceless matrices and show that the Langevin equations can be solved numerically in this basis using a stochastic version of the method of lines. The numerical method is validated by comparing equilibrium probability distributions, structure factors, and dynamic correlations obtained from these numerical solutions with analytic predictions. We demonstrate excellent agreement between numerics and theory. This methodology can be applied to the study of phenomena where fluctuations in both the magnitude and direction of nematic order are important, as for instance, in the nematic swarms which produce enhanced opalescence near the isotropic-nematic transition or the problem of nucleation of the nematic from the isotropic phase.
Proskurov, S.; Darbyshire, O. R.; Karabasov, S. A.
2017-12-01
The present work discusses modifications to the stochastic Fast Random Particle Mesh (FRPM) method featuring both tonal and broadband noise sources. The technique relies on the combination of incorporated vortex-shedding resolved flow available from Unsteady Reynolds-Averaged Navier-Stokes (URANS) simulation with the fine-scale turbulence FRPM solution generated via the stochastic velocity fluctuations in the context of vortex sound theory. In contrast to the existing literature, our method encompasses a unified treatment for broadband and tonal acoustic noise sources at the source level, thus, accounting for linear source interference as well as possible non-linear source interaction effects. When sound sources are determined, for the sound propagation, Acoustic Perturbation Equations (APE-4) are solved in the time-domain. Results of the method's application for two aerofoil benchmark cases, with both sharp and blunt trailing edges are presented. In each case, the importance of individual linear and non-linear noise sources was investigated. Several new key features related to the unsteady implementation of the method were tested and brought into the equation. Encouraging results have been obtained for benchmark test cases using the new technique which is believed to be potentially applicable to other airframe noise problems where both tonal and broadband parts are important.
A simple stochastic model for dipole moment fluctuations in numerical dynamo simulations
Domenico G. eMeduri
2016-04-01
Full Text Available Earth's axial dipole field changes in a complex fashion on many differenttime scales ranging from less than a year to tens of million years.Documenting, analysing, and replicating this intricate signalis a challenge for data acquisition, theoretical interpretation,and dynamo modelling alike. Here we explore whether axial dipole variationscan be described by the superposition of a slow deterministic driftand fast stochastic fluctuations, i.e. by a Langevin-type system.The drift term describes the time averaged behaviour of the axial dipole variations,whereas the stochastic part mimics complex flow interactions over convective time scales.The statistical behaviour of the system is described by a Fokker-Planck equation whichallows useful predictions, including the average rates of dipole reversals and excursions.We analyse several numerical dynamo simulations, most of which havebeen integrated particularly long in time, and also the palaeomagneticmodel PADM2M which covers the past 2 Myr.The results show that the Langevin description provides a viable statistical modelof the axial dipole variations on time scales longer than about 1 kyr.For example, the axial dipole probability distribution and the average reversalrate are successfully predicted.The exception is PADM2M where the stochastic model reversal rate seems too low.The dependence of the drift on the axial dipolemoment reveals the nonlinear interactions that establish thedynamo balance. A separate analysis of inductive and diffusive magnetic effectsin three dynamo simulations suggests that the classical quadraticquenching of induction predicted by mean-field theory seems at work.
The fluctuation-dissipation theorem for stochastic kinetics—Implications on genetic regulations
Yan, Ching-Cher Sanders [Institute of Chemistry, Academia Sinica, 128, Section 2, Academia Road, Nankang, Taipei 115, Taiwan (China); Hsu, Chao-Ping, E-mail: cherri@chem.sinica.edu.tw [Institute of Chemistry, Academia Sinica, 128, Section 2, Academia Road, Nankang, Taipei 115, Taiwan (China); Genome and Systems Biology Degree Program, National Taiwan University, 1, Section 4, Roosevelt Road, Taipei 106, Taiwan (China)
2013-12-14
The Fluctuation-Dissipation theorem (FDT) connects the “memory” in the fluctuation in equilibrium to the response of a system after a perturbation, which has been a fundamental ground in many branches of physics. When viewing a cell as a stochastic biochemical system, the cell's response under a perturbation is related to its intrinsic steady-state correlation functions via the FDT, a theorem we derived and present in this work. FDT allows us to use the noise to derive dynamic response and infer dynamic properties in the system. We tested FDT's validity with gene regulation models and found that it is limited to the linear response. For an indirect regulation pathway where unknown components may exist, FDT still works within the linear response region. Thus, FDT may be used for systems with partial knowledge, and it is potentially possible to identify the existence of unobserved components. With FDT, the dynamic response can be composed of steady-state measurements without the complete detailed knowledge for the regulation or kinetics. The response function derived can give important insights into the dynamics and time scales of the system.
A. W. Wernik
1996-01-01
Full Text Available Four data sets of density fluctuations measured in-situ by the Dynamics Explorer (DE 2 were analyzed in an attempt to study chaotic nature of the high-latitude turbulence and, in this way to complement the conventional spectral analysis. It has been found that the probability distribution function of density differences is far from Gaussian and similar to that observed in the intermittent fluid or MBD turbulence. This indicates that ionospheric density fluctuations are not stochastic but coherent to some extent. Wayland's and surrogate data tests for determinism in a time series of density data allowed us to differentiate between regions of intense shear and moderate shear. We observe that in the region of strong field aligned currents (FAC and intense shear, or along the convection in the collisional regime, ionospheric turbulence behaves like a random noise with non-Gaussian statistics implying that the underlying physical process is nondeterministic. On the other hand, when FACs are weak, and shear is moderate or observations made in the inertial regime the turbulence is chaotic. The attractor dimension is lowest (1.9 for 'old' convected irregularities. The dimension 3.2 is found for turbulence in the inertial regime and considerably smaller (2.4 in the collisional regime. It is suggested that a high dimension in the inertial regime may be caused by a complicated velocity structure in the shear instability region.
Astumian, R D
2018-01-11
In the absence of input energy, a chemical reaction in a closed system ineluctably relaxes toward an equilibrium state governed by a Boltzmann distribution. The addition of a catalyst to the system provides a way for more rapid equilibration toward this distribution, but the catalyst can never, in and of itself, drive the system away from equilibrium. In the presence of external fluctuations, however, a macromolecular catalyst (e.g., an enzyme) can absorb energy and drive the formation of a steady state between reactant and product that is not determined solely by their relative energies. Due to the ubiquity of non-equilibrium steady states in living systems, the development of a theory for the effects of external fluctuations on chemical systems has been a longstanding focus of non-equilibrium thermodynamics. The theory of stochastic pumping has provided insight into how a non-equilibrium steady-state can be formed and maintained in the presence of dissipation and kinetic asymmetry. This effort has been greatly enhanced by a confluence of experimental and theoretical work on synthetic molecular machines designed explicitly to harness external energy to drive non-equilibrium transport and self-assembly.
Modeling the response of a standard accretion disc to stochastic viscous fluctuations
Ahmad, Naveel; Misra, Ranjeev; Iqbal, Naseer; Maqbool, Bari; Hamid, Mubashir
2018-01-01
The observed variability of X-ray binaries over a wide range of time-scales can be understood in the framework of a stochastic propagation model, where viscous fluctuations at different radii induce accretion rate variability that propagate inwards to the X-ray producing region. The scenario successfully explains the power spectra, the linear rms-flux relation as well as the time-lag between different energy photons. The predictions of this model have been obtained using approximate analytical solutions or empirically motivated models which take into account the effect of these propagating variability on the radiative process of complex accretion flows. Here, we study the variation of the accretion rate due to such viscous fluctuations using a hydro-dynamical code for the standard geometrically thin, gas pressure dominated α-disc with a zero torque boundary condition. Our results confirm earlier findings that the time-lag between a perturbation and the resultant inner accretion rate variation depends on the frequency (or time-period) of the perturbation. Here we have quantified that the time-lag tlag ∝f-0.54 , for time-periods less than the viscous time-scale of the perturbation radius and is nearly constant otherwise. This, coupled with radiative process would produce the observed frequency dependent time-lag between different energy bands. We also confirm that if there are random Gaussian fluctuations of the α-parameter at different radii, the resultant inner accretion rate has a power spectrum which is a power-law.
Kaplani, E.; Kaplanis, S.
2012-01-01
Highlights: ► Solar radiation data for European cities follow the Extreme Value or Weibull distribution. ► Simulation model for the sizing of SAPV systems based on energy balance and stochastic analysis. ► Simulation of PV Generator-Loads-Battery Storage System performance for all months. ► Minimum peak power and battery capacity required for reliable SAPV sizing for various European cities. ► Peak power and battery capacity reduced by more than 30% for operation 95% success rate. -- Abstract: The large fluctuations observed in the daily solar radiation profiles affect highly the reliability of the PV system sizing. Increasing the reliability of the PV system requires higher installed peak power (P m ) and larger battery storage capacity (C L ). This leads to increased costs, and makes PV technology less competitive. This research paper presents a new stochastic simulation model for stand-alone PV systems, developed to determine the minimum installed P m and C L for the PV system to be energy independent. The stochastic simulation model developed, makes use of knowledge acquired from an in-depth statistical analysis of the solar radiation data for the site, and simulates the energy delivered, the excess energy burnt, the load profiles and the state of charge of the battery system for the month the sizing is applied, and the PV system performance for the entire year. The simulation model provides the user with values for the autonomy factor d, simulating PV performance in order to determine the minimum P m and C L depending on the requirements of the application, i.e. operation with critical or non-critical loads. The model makes use of NASA’s Surface meteorology and Solar Energy database for the years 1990–2004 for various cities in Europe with a different climate. The results obtained with this new methodology indicate a substantial reduction in installed peak power and battery capacity, both for critical and non-critical operation, when compared to
Fluctuations in protein synthesis from a single RNA template: stochastic kinetics of ribosomes.
Garai, Ashok; Chowdhury, Debashish; Ramakrishnan, T V
2009-01-01
Proteins are polymerized by cyclic machines called ribosomes, which use their messenger RNA (mRNA) track also as the corresponding template, and the process is called translation. We explore, in depth and detail, the stochastic nature of the translation. We compute various distributions associated with the translation process; one of them--namely, the dwell time distribution--has been measured in recent single-ribosome experiments. The form of the distribution, which fits best with our simulation data, is consistent with that extracted from the experimental data. For our computations, we use a model that captures both the mechanochemistry of each individual ribosome and their steric interactions. We also demonstrate the effects of the sequence inhomogeneities of real genes on the fluctuations and noise in translation. Finally, inspired by recent advances in the experimental techniques of manipulating single ribosomes, we make theoretical predictions on the force-velocity relation for individual ribosomes. In principle, all our predictions can be tested by carrying out in vitro experiments.
Krommes, J.A.
1999-01-01
Highly simplified models of random flows interacting with background microturbulence are analyzed. In the limit of very rapid velocity fluctuations, it is shown rigorously that the fluctuation level of a passively advected scalar is not controlled by the rms shear. In a model with random velocities dependent only on time, the level of cross-correlations between the flows and the background turbulence regulates the saturation level. This effect is illustrated by considering a simple stochastic-oscillator model, both exactly and with analysis and numerical solutions of the direct-interaction approximation. Implications for the understanding of self-consistent turbulence are discussed briefly
Marro, Massimo; Salizzoni, Pietro; Soulhac, Lionel; Cassiani, Massimo
2018-01-01
We analyze the reliability of the Lagrangian stochastic micromixing method in predicting higher-order statistics of the passive scalar concentration induced by an elevated source (of varying diameter) placed in a turbulent boundary layer. To that purpose we analyze two different modelling approaches by testing their results against the wind-tunnel measurements discussed in Part I (Nironi et al., Boundary-Layer Meteorology, 2015, Vol. 156, 415-446). The first is a probability density function (PDF) micromixing model that simulates the effects of the molecular diffusivity on the concentration fluctuations by taking into account the background particles. The second is a new model, named VPΓ, conceived in order to minimize the computational costs. This is based on the volumetric particle approach providing estimates of the first two concentration moments with no need for the simulation of the background particles. In this second approach, higher-order moments are computed based on the estimates of these two moments and under the assumption that the concentration PDF is a Gamma distribution. The comparisons concern the spatial distribution of the first four moments of the concentration and the evolution of the PDF along the plume centreline. The novelty of this work is twofold: (i) we perform a systematic comparison of the results of micro-mixing Lagrangian models against experiments providing profiles of the first four moments of the concentration within an inhomogeneous and anisotropic turbulent flow, and (ii) we show the reliability of the VPΓ model as an operational tool for the prediction of the PDF of the concentration.
Marro, Massimo; Salizzoni, Pietro; Soulhac, Lionel; Cassiani, Massimo
2018-06-01
We analyze the reliability of the Lagrangian stochastic micromixing method in predicting higher-order statistics of the passive scalar concentration induced by an elevated source (of varying diameter) placed in a turbulent boundary layer. To that purpose we analyze two different modelling approaches by testing their results against the wind-tunnel measurements discussed in Part I (Nironi et al., Boundary-Layer Meteorology, 2015, Vol. 156, 415-446). The first is a probability density function (PDF) micromixing model that simulates the effects of the molecular diffusivity on the concentration fluctuations by taking into account the background particles. The second is a new model, named VPΓ, conceived in order to minimize the computational costs. This is based on the volumetric particle approach providing estimates of the first two concentration moments with no need for the simulation of the background particles. In this second approach, higher-order moments are computed based on the estimates of these two moments and under the assumption that the concentration PDF is a Gamma distribution. The comparisons concern the spatial distribution of the first four moments of the concentration and the evolution of the PDF along the plume centreline. The novelty of this work is twofold: (i) we perform a systematic comparison of the results of micro-mixing Lagrangian models against experiments providing profiles of the first four moments of the concentration within an inhomogeneous and anisotropic turbulent flow, and (ii) we show the reliability of the VPΓ model as an operational tool for the prediction of the PDF of the concentration.
Kostic, Lj.
2003-01-01
The influence of the stochastically pulsed Poisson source to the statistical properties of the subcritical multiplying system is analyzed in the paper. It is shown a strong dependence on the pulse period and pulse width of the source (author)
Schmidt, Christian; Piel, Alexander
2015-10-01
The Brownian motion of a single particle in the plasma sheath is studied to separate the effect of stochastic heating by charge fluctuations from heating by collective effects. By measuring the particle velocities in the ballistic regime and by carefully determining the particle mass from the Epstein drag it is shown that for a pressure of 10 Pa, which is typical of many experiments, the proper kinetic temperature of the Brownian particle remains close to the gas temperature and rises only slightly with particle size. This weak effect is confirmed by a detailed model for charging and charge fluctuations in the sheath. A substantial temperature rise is found for decreasing pressure, which approximately shows the expected scaling with p-2. The system under study is an example for non-equilibrium Brownian motion under the influence of white noise without corresponding dissipation.
Garcia, O. E., E-mail: odd.erik.garcia@uit.no; Kube, R.; Theodorsen, A. [Department of Physics and Technology, UiT The Arctic University of Norway, N-9037 Tromsø (Norway); Pécseli, H. L. [Physics Department, University of Oslo, PO Box 1048 Blindern, N-0316 Oslo (Norway)
2016-05-15
A stochastic model is presented for intermittent fluctuations in the scrape-off layer of magnetically confined plasmas. The fluctuations in the plasma density are modeled by a super-position of uncorrelated pulses with fixed shape and duration, describing radial motion of blob-like structures. In the case of an exponential pulse shape and exponentially distributed pulse amplitudes, predictions are given for the lowest order moments, probability density function, auto-correlation function, level crossings, and average times for periods spent above and below a given threshold level. Also, the mean squared errors on estimators of sample mean and variance for realizations of the process by finite time series are obtained. These results are discussed in the context of single-point measurements of fluctuations in the scrape-off layer, broad density profiles, and implications for plasma–wall interactions due to the transient transport events in fusion grade plasmas. The results may also have wide applications for modelling fluctuations in other magnetized plasmas such as basic laboratory experiments and ionospheric irregularities.
Role of stochastic fluctuations in the charge on macroscopic particles in dusty plasmas
Vaulina, O.S.; Nefedov, A.P.; Petrov, O.F.; Khrapak, S.A.
1999-01-01
The currents which charge a macroscopic particle placed in a plasma consist of discrete charges; hence, the charge can undergo random fluctuations about its equilibrium value. These random fluctuations can be described by a simple model which, if the mechanisms for charging of macroscopic particles are known, makes it possible to determine the dependence of the temporal and amplitude characteristics of the fluctuations on the plasma parameters. This model can be used to study the effect of charge fluctuations on the dynamics of the macroscopic particles. The case of so-called plasma-dust crystals (i.e., highly ordered structures which develop because of strong interactions among macroscopic particles) in laboratory gaseous discharge plasmas is considered as an example. The molecular dynamics method shows that, under certain conditions, random fluctuations in the charge can effectively heat a system of macroscopic particles, thereby impeding the ordering process
EFT Beyond the Horizon: Stochastic Inflation and How Primordial Quantum Fluctuations Go Classical
Burgess, C P; Tasinato, G; Williams, M
2015-01-01
We identify the effective theory describing inflationary super-Hubble scales and show it to be a special case of effective field theories appropriate to open systems. Open systems allow information to be exchanged between the degrees of freedom of interest and those that are integrated out, such as for particles moving through a fluid. Strictly speaking they cannot in general be described by an effective lagrangian; rather the appropriate `low-energy' limit is instead a Lindblad equation describing the evolution of the density matrix of the slow degrees of freedom. We derive the equation relevant to super-Hubble modes of quantum fields in near-de Sitter spacetimes and derive two implications. We show the evolution of the diagonal density-matrix elements quickly approaches the Fokker-Planck equation of Starobinsky's stochastic inflationary picture. This provides an alternative first-principles derivation of this picture's stochastic noise and drift, as well as its leading corrections. (An application computes ...
Fluctuations and Noise in Stochastic Spread of Respiratory Infection Epidemics in Social Networks
Yulmetyev, Renat; Emelyanova, Natalya; Demin, Sergey; Gafarov, Fail; Hänggi, Peter; Yulmetyeva, Dinara
2003-05-01
For the analysis of epidemic and disease dynamics complexity, it is necessary to understand the basic principles and notions of its spreading in long-time memory media. Here we considering the problem from a theoretical and practical viewpoint, presenting the quantitative evidence confirming the existence of stochastic long-range memory and robust chaos in a real time series of respiratory infections of human upper respiratory track. In this work we present a new statistical method of analyzing the spread of grippe and acute respiratory track infections epidemic process of human upper respiratory track by means of the theory of discrete non-Markov stochastic processes. We use the results of our recent theory (Phys. Rev. E 65, 046107 (2002)) for the study of statistical effects of memory in real data series, describing the epidemic dynamics of human acute respiratory track infections and grippe. The obtained results testify to an opportunity of the strict quantitative description of the regular and stochastic components in epidemic dynamics of social networks with a view to time discreteness and effects of statistical memory.
Fang, Wen; Wang, Jun
2013-09-01
We develop a financial market model using an Ising spin system on a Sierpinski carpet lattice that breaks the equal status of each spin. To study the fluctuation behavior of the financial model, we present numerical research based on Monte Carlo simulation in conjunction with the statistical analysis and multifractal analysis of the financial time series. We extract the multifractal spectra by selecting various lattice size values of the Sierpinski carpet, and the inverse temperature of the Ising dynamic system. We also investigate the statistical fluctuation behavior, the time-varying volatility clustering, and the multifractality of returns for the indices SSE, SZSE, DJIA, IXIC, S&P500, HSI, N225, and for the simulation data derived from the Ising model on the Sierpinski carpet lattice. A numerical study of the model’s dynamical properties reveals that this financial model reproduces important features of the empirical data.
Wen, Xing-Chun; He, Ling-Yun
2015-08-01
There is a bitter controversy over what drives the housing price in China in the existing literature. In this paper, we investigate the underlying driving force behind housing price fluctuations in China, especially focusing on the role of housing demand shock with that of money supply shock in explaining housing price movements, by a new Keynesian dynamic stochastic general equilibrium model. Empirical results suggest that it is housing demand, instead of money supply, that mainly drives China's housing price movements. Relevant policy implication is further discussed, namely, whether to consider the housing price fluctuations in the conduct of monetary policy. By means of the policy simulations, we find that a real house price-augmented money supply rule is a better monetary policy for China's economy stabilization. 1. Investment refers to fixed capital investment. 2. Housing price refers to national average housing price. Quarterly data on housing price during the period of our work are not directly available. However, monthly data of the value of sales on housing and sale volume on housing can be directly obtained from National Bureau of Statistics of China. We add up the monthly data and calculate one quarter's housing price by dividing the value of housing sales by its sale volume in one quarter. 3. M2 means the broad money supply in China.
Bouzat, Sebastián
2016-01-01
One-dimensional models coupling a Langevin equation for the cargo position to stochastic stepping dynamics for the motors constitute a relevant framework for analyzing multiple-motor microtubule transport. In this work we explore the consistence of these models focusing on the effects of the thermal noise. We study how to define consistent stepping and detachment rates for the motors as functions of the local forces acting on them in such a way that the cargo velocity and run-time match previously specified functions of the external load, which are set on the base of experimental results. We show that due to the influence of the thermal fluctuations this is not a trivial problem, even for the single-motor case. As a solution, we propose a motor stepping dynamics which considers memory on the motor force. This model leads to better results for single-motor transport than the approaches previously considered in the literature. Moreover, it gives a much better prediction for the stall force of the two-motor case, highly compatible with the experimental findings. We also analyze the fast fluctuations of the cargo position and the influence of the viscosity, comparing the proposed model to the standard one, and we show how the differences on the single-motor dynamics propagate to the multiple motor situations. Finally, we find that the one-dimensional character of the models impede an appropriate description of the fast fluctuations of the cargo position at small loads. We show how this problem can be solved by considering two-dimensional models.
Absorptive and dispersive optical profiles in fluctuating environments: A stochastic model
Paz, J.L.; Mendoza-Garcia, A.; Mastrodomenico, A.
2011-01-01
In this study, we determined the absorptive and dispersive optical profiles of a molecular system coupled with a thermal bath. Solvent effects were explicitly considered by modelling the non-radiative interaction with the solute as a random variable. The optical stochastical Bloch equations (OSBE) were solved using a time-ordered cumulant expansion with white noise as a correlation function. We found a solution for the Fourier component of coherence at the third order of perturbation for the nonlinear Four-wave mixing signal and produced analytical expressions for the optical responses of the system. Finally, we examined the behaviour of these properties with respect to the noise parameter, frequency detuning of the dynamic perturbation, and relaxation times.
Stability of discrete memory states to stochastic fluctuations in neuronal systems
Miller, Paul; Wang, Xiao-Jing
2014-01-01
Noise can degrade memories by causing transitions from one memory state to another. For any biological memory system to be useful, the time scale of such noise-induced transitions must be much longer than the required duration for memory retention. Using biophysically-realistic modeling, we consider two types of memory in the brain: short-term memories maintained by reverberating neuronal activity for a few seconds, and long-term memories maintained by a molecular switch for years. Both systems require persistence of (neuronal or molecular) activity self-sustained by an autocatalytic process and, we argue, that both have limited memory lifetimes because of significant fluctuations. We will first discuss a strongly recurrent cortical network model endowed with feedback loops, for short-term memory. Fluctuations are due to highly irregular spike firing, a salient characteristic of cortical neurons. Then, we will analyze a model for long-term memory, based on an autophosphorylation mechanism of calcium/calmodulin-dependent protein kinase II (CaMKII) molecules. There, fluctuations arise from the fact that there are only a small number of CaMKII molecules at each postsynaptic density (putative synaptic memory unit). Our results are twofold. First, we demonstrate analytically and computationally the exponential dependence of stability on the number of neurons in a self-excitatory network, and on the number of CaMKII proteins in a molecular switch. Second, for each of the two systems, we implement graded memory consisting of a group of bistable switches. For the neuronal network we report interesting ramping temporal dynamics as a result of sequentially switching an increasing number of discrete, bistable, units. The general observation of an exponential increase in memory stability with the system size leads to a trade-off between the robustness of memories (which increases with the size of each bistable unit) and the total amount of information storage (which decreases
Stochastic fluctuations and distributed control of gene expression impact cellular memory.
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.
Proton and heavy ion acceleration by stochastic fluctuations in the Earth's magnetotail
Catapano, Filomena; Zimbardo, Gaetano; Perri, Silvia; Greco, Antonella [Calabria Univ., Rende (Italy). Dept. of Physics; Artemyev, Anton V. [Russian Academy of Science, Moscow (Russian Federation). Space Research Inst.; California Univ., Los Angeles, CA (United States). Dept. of Earth, Planetary, and Space Science and Inst. of Geophysics and Planetary Physics
2016-07-01
Spacecraft observations show that energetic ions are found in the Earth's magnetotail, with energies ranging from tens of keV to a few hundreds of keV. In this paper we carry out test particle simulations in which protons and other ion species are injected in the Vlasov magnetic field configurations obtained by Catapano et al. (2015). These configurations represent solutions of a generalized Harris model, which well describes the observed profiles in the magnetotail. In addition, three-dimensional time-dependent stochastic electromagnetic perturbations are included in the simulation box, so that the ion acceleration process is studied while varying the equilibrium magnetic field profile and the ion species. We find that proton energies of the order of 100 keV are reached with simulation parameters typical of the Earth's magnetotail. By changing the ion mass and charge, we can study the acceleration of heavy ions such as He{sup ++} and O{sup +}, and it is found that energies of the order of 100-200 keV are reached in a few seconds for He{sup ++}, and about 100 keV for O{sup +}.
Proton and heavy ion acceleration by stochastic fluctuations in the Earth's magnetotail
F. Catapano
2016-10-01
Full Text Available Spacecraft observations show that energetic ions are found in the Earth's magnetotail, with energies ranging from tens of keV to a few hundreds of keV. In this paper we carry out test particle simulations in which protons and other ion species are injected in the Vlasov magnetic field configurations obtained by Catapano et al. (2015. These configurations represent solutions of a generalized Harris model, which well describes the observed profiles in the magnetotail. In addition, three-dimensional time-dependent stochastic electromagnetic perturbations are included in the simulation box, so that the ion acceleration process is studied while varying the equilibrium magnetic field profile and the ion species. We find that proton energies of the order of 100 keV are reached with simulation parameters typical of the Earth's magnetotail. By changing the ion mass and charge, we can study the acceleration of heavy ions such as He+ + and O+, and it is found that energies of the order of 100–200 keV are reached in a few seconds for He+ + , and about 100 keV for O+.
Wetland Ecohydrology: stochastic description of water level fluctuations across the soil surface
Tamea, S.; Muneepeerakul, R.; Laio, F.; Ridolfi, L.; Rodriguez-Iturbe, I.
2009-12-01
Wetlands provide a suite of social and ecological critical functions such as being habitats of disease-carrying vectors, providing buffer zones against hurricanes, controlling sediment transport, filtering nutrients and contaminants, and a repository of great biological diversity. More recently, wetlands have also been recognized as crucial for carbon storage in the context of global climate change. Despite such importance, quantitative approaches to many aspects of wetlands are far from adequate. Therefore, improving our quantitative understanding of wetlands is necessary to our ability to maintain, manage, and restore these invaluable environments. In wetlands, hydrologic factors and ecosystem processes interplay and generate unique characteristics and a delicate balance between biotic and abiotic elements. The main hydrologic driver of wetland ecosystems is the position of the water level that, being above or below ground, determines the submergence or exposure of soil. When the water level is above the soil surface, soil saturation and lack of oxygen causes hypoxia, anaerobic functioning of microorganisms and anoxic stress in plants, that might lead to the death of non-adapted organisms. When the water level lies below the soil surface, the ecosystem becomes groundwater-dependent, and pedological and physiological aspects play their role in the soil water balance. We propose here a quantitative description of wetland ecohydrology, through a stochastic process-based water balance, driven by a marked compound Poisson noise representing rainfall events. The model includes processes such as rainfall infiltration, evapotranspiration, capillary rise, and the contribution of external water bodies, which are quantified in a simple yet realistic way. The semi-analytical steady-state probability distributions of water level spanning across the soil surface are validated with data from the Everglades (Florida, USA). The model and its results allow for a quantitative
Stochasticity in the yeast mating pathway
Hong-Li, Wang; Zheng-Ping, Fu; Xin-Hang, Xu; Qi, Ouyang
2009-01-01
We report stochastic simulations of the yeast mating signal transduction pathway. The effects of intrinsic and external noise, the influence of cell-to-cell difference in the pathway capacity, and noise propagation in the pathway have been examined. The stochastic temporal behaviour of the pathway is found to be robust to the influence of inherent fluctuations, and intrinsic noise propagates in the pathway in a uniform pattern when the yeasts are treated with pheromones of different stimulus strengths and of varied fluctuations. In agreement with recent experimental findings, extrinsic noise is found to play a more prominent role than intrinsic noise in the variability of proteins. The occurrence frequency for the reactions in the pathway are also examined and a more compact network is obtained by dropping most of the reactions of least occurrence
Shnoll S. E.
2006-04-01
Full Text Available This is a survey of the fine structure stochastic distributions in measurements obtained by me over 50 years. It is shown: (1 The forms of the histograms obtained at each geographic point (at each given moment of time are similar with high probability, even if we register phenomena of completely different nature --- from biochemical reactions to the noise in a gravitational antenna, or alpha-decay. (2 The forms of the histograms change with time. The iterations of the same form have the periods of the stellar day (1.436 min, the solar day (1.440 min, the calendar year (365 solar days, and the sidereal year (365 solar days plus 6 hours and 9 min. (3 At the same instants of the local time, at different geographic points, the forms of the histograms are the same, with high probability. (4 The forms of the histograms depend on the locations of the Moon and the Sun with respect to the horizon. (5 All the facts are proof of the dependance of the form of the histograms on the location of the measured objects with respect to stars, the Sun, and the Moon. (6 At the instants of New Moon and the maxima of solar eclipses there are specific forms of the histograms. (7 It is probable that the observed correlations are not connected to flow power changes (the changes of the gravity force --- we did not find the appropriate periods in changes in histogram form. (8 A sharp anisotropy of space was discovered, registered by alpha-decay detectors armed with collimators. Observations at 54 North (the collimator was pointed at the Pole Star showed no day-long periods, as was also the case for observations at 82 North, near the Pole. Histograms obtained by observations with an Easterly-directed collimator were determined every 718 minutes (half stellar day and with observations using a Westerly-directed collimator. (9 Collimators rotating counter-clockwise, in parallel with the celestial equator, gave the probability of changes in histograms as the number of the
Shnoll S. E.
2006-04-01
Full Text Available This is a survey of the fine structure stochastic distributions in measurements obtained by me over 50 years. It is shown: (1 The forms of the histograms obtained at each geographic point (at each given moment of time are similar with high probability, even if we register phenomena of completely different nature — from biochemical reactions to the noise in a gravitational antenna, or α-decay. (2 The forms of the histograms change with time. The iterations of the same form have the periods of the stellar day (1.436 min, the solar day (1.440 min, the calendar year (365 solar days, and the sidereal year (365 solar days plus 6 hours and 9 min. (3 At the same instants of the local time, at different geographic points, the forms of the histograms are the same, with high probability. (4 The forms of the histograms depend on the locations of the Moon and the Sun with respect to the horizon. (5 All the facts are proof of the dependance of the form of the histograms on the location of the measured objects with respect to stars, the Sun, and the Moon. (6 At the instants of New Moon and the maxima of solar eclipses there are specific forms of the histograms. (7 It is probable that the observed correlations are not connected to flow power changes (the changes of the gravity force — we did not find the appropriate periods in changes in histogram form. (8 A sharp anisotropy of space was discovered, registered by α-decay detectors armed with collimators. Observations at 54◦ North (the collimator was pointed at the Pole Star showed no day-long periods, as was also the case for observations at 82◦ North, near the Pole. Histograms obtained by observations with an Easterly-directed collimator were determined every 718 minutes (half stellar day and with observations using a Westerly-directed collimator. (9 Collimators rotating counter-clockwise, in parallel with the celestial equator, gave the probability of changes in histograms as the number of the
Lück, Anja; Klimmasch, Lukas; Großmann, Peter; Germerodt, Sebastian; Kaleta, Christoph
2018-01-10
Organisms need to adapt to changing environments and they do so by using a broad spectrum of strategies. These strategies include finding the right balance between expressing genes before or when they are needed, and adjusting the degree of noise inherent in gene expression. We investigated the interplay between different nutritional environments and the inhabiting organisms' metabolic and genetic adaptations by applying an evolutionary algorithm to an agent-based model of a concise bacterial metabolism. Our results show that constant environments and rapidly fluctuating environments produce similar adaptations in the organisms, making the predictability of the environment a major factor in determining optimal adaptation. We show that exploitation of expression noise occurs only in some types of fluctuating environment and is strongly dependent on the quality and availability of nutrients: stochasticity is generally detrimental in fluctuating environments and beneficial only at equal periods of nutrient availability and above a threshold environmental richness. Moreover, depending on the availability and nutritional value of nutrients, nutrient-dependent and stochastic expression are both strategies used to deal with environmental changes. Overall, we comprehensively characterize the interplay between the quality and periodicity of an environment and the resulting optimal deterministic and stochastic regulation strategies of nutrient-catabolizing pathways.
Modulating cell-to-cell variability and sensitivity to death ligands by co-drugging
Flusberg, Deborah A; Sorger, Peter K
2013-01-01
TRAIL (tumor necrosis factor-related apoptosis-inducing ligand) holds promise as an anti-cancer therapeutic but efficiently induces apoptosis in only a subset of tumor cell lines. Moreover, even in clonal populations of responsive lines, only a fraction of cells dies in response to TRAIL and individual cells exhibit cell-to-cell variability in the timing of cell death. Fractional killing in these cell populations appears to arise not from genetic differences among cells but rather from differences in gene expression states, fluctuations in protein levels and the extent to which TRAIL-induced death or survival pathways become activated. In this study, we ask how cell-to-cell variability manifests in cell types with different sensitivities to TRAIL, as well as how it changes when cells are exposed to combinations of drugs. We show that individual cells that survive treatment with TRAIL can regenerate the sensitivity and death-time distribution of the parental population, demonstrating that fractional killing is a stable property of cell populations. We also show that cell-to-cell variability in the timing and probability of apoptosis in response to treatment can be tuned using combinations of drugs that together increase apoptotic sensitivity compared to treatment with one drug alone. In the case of TRAIL, modulation of cell-to-cell variability by co-drugging appears to involve a reduction in the threshold for mitochondrial outer membrane permeabilization. (paper)
Weinberg, Seth H.; Smith, Gregory D.
2012-01-01
Cardiac myocyte calcium signaling is often modeled using deterministic ordinary differential equations (ODEs) and mass-action kinetics. However, spatially restricted “domains” associated with calcium influx are small enough (e.g., 10−17 liters) that local signaling may involve 1–100 calcium ions. Is it appropriate to model the dynamics of subspace calcium using deterministic ODEs or, alternatively, do we require stochastic descriptions that account for the fundamentally discrete nature of these local calcium signals? To address this question, we constructed a minimal Markov model of a calcium-regulated calcium channel and associated subspace. We compared the expected value of fluctuating subspace calcium concentration (a result that accounts for the small subspace volume) with the corresponding deterministic model (an approximation that assumes large system size). When subspace calcium did not regulate calcium influx, the deterministic and stochastic descriptions agreed. However, when calcium binding altered channel activity in the model, the continuous deterministic description often deviated significantly from the discrete stochastic model, unless the subspace volume is unrealistically large and/or the kinetics of the calcium binding are sufficiently fast. This principle was also demonstrated using a physiologically realistic model of calmodulin regulation of L-type calcium channels introduced by Yue and coworkers. PMID:23509597
Determinants of cell-to-cell variability in protein kinase signaling.
Jeschke, Matthias; Baumgärtner, Stephan; Legewie, Stefan
2013-01-01
Cells reliably sense environmental changes despite internal and external fluctuations, but the mechanisms underlying robustness remain unclear. We analyzed how fluctuations in signaling protein concentrations give rise to cell-to-cell variability in protein kinase signaling using analytical theory and numerical simulations. We characterized the dose-response behavior of signaling cascades by calculating the stimulus level at which a pathway responds ('pathway sensitivity') and the maximal activation level upon strong stimulation. Minimal kinase cascades with gradual dose-response behavior show strong variability, because the pathway sensitivity and the maximal activation level cannot be simultaneously invariant. Negative feedback regulation resolves this trade-off and coordinately reduces fluctuations in the pathway sensitivity and maximal activation. Feedbacks acting at different levels in the cascade control different aspects of the dose-response curve, thereby synergistically reducing the variability. We also investigated more complex, ultrasensitive signaling cascades capable of switch-like decision making, and found that these can be inherently robust to protein concentration fluctuations. We describe how the cell-to-cell variability of ultrasensitive signaling systems can be actively regulated, e.g., by altering the expression of phosphatase(s) or by feedback/feedforward loops. Our calculations reveal that slow transcriptional negative feedback loops allow for variability suppression while maintaining switch-like decision making. Taken together, we describe design principles of signaling cascades that promote robustness. Our results may explain why certain signaling cascades like the yeast pheromone pathway show switch-like decision making with little cell-to-cell variability.
Determinants of cell-to-cell variability in protein kinase signaling.
Matthias Jeschke
Full Text Available Cells reliably sense environmental changes despite internal and external fluctuations, but the mechanisms underlying robustness remain unclear. We analyzed how fluctuations in signaling protein concentrations give rise to cell-to-cell variability in protein kinase signaling using analytical theory and numerical simulations. We characterized the dose-response behavior of signaling cascades by calculating the stimulus level at which a pathway responds ('pathway sensitivity' and the maximal activation level upon strong stimulation. Minimal kinase cascades with gradual dose-response behavior show strong variability, because the pathway sensitivity and the maximal activation level cannot be simultaneously invariant. Negative feedback regulation resolves this trade-off and coordinately reduces fluctuations in the pathway sensitivity and maximal activation. Feedbacks acting at different levels in the cascade control different aspects of the dose-response curve, thereby synergistically reducing the variability. We also investigated more complex, ultrasensitive signaling cascades capable of switch-like decision making, and found that these can be inherently robust to protein concentration fluctuations. We describe how the cell-to-cell variability of ultrasensitive signaling systems can be actively regulated, e.g., by altering the expression of phosphatase(s or by feedback/feedforward loops. Our calculations reveal that slow transcriptional negative feedback loops allow for variability suppression while maintaining switch-like decision making. Taken together, we describe design principles of signaling cascades that promote robustness. Our results may explain why certain signaling cascades like the yeast pheromone pathway show switch-like decision making with little cell-to-cell variability.
Robustness of MEK-ERK Dynamics and Origins of Cell-to-Cell Variability in MAPK Signaling
Sarah Filippi
2016-06-01
Full Text Available Cellular signaling processes can exhibit pronounced cell-to-cell variability in genetically identical cells. This affects how individual cells respond differentially to the same environmental stimulus. However, the origins of cell-to-cell variability in cellular signaling systems remain poorly understood. Here, we measure the dynamics of phosphorylated MEK and ERK across cell populations and quantify the levels of population heterogeneity over time using high-throughput image cytometry. We use a statistical modeling framework to show that extrinsic noise, particularly that from upstream MEK, is the dominant factor causing cell-to-cell variability in ERK phosphorylation, rather than stochasticity in the phosphorylation/dephosphorylation of ERK. We furthermore show that without extrinsic noise in the core module, variable (including noisy signals would be faithfully reproduced downstream, but the within-module extrinsic variability distorts these signals and leads to a drastic reduction in the mutual information between incoming signal and ERK activity.
Neergaard, Jesper; Schieber, Jay D.
1999-01-01
A self-consistent reptation model that includes chain stretching, chain-length fluctuations, segment connectivity and constraint release is used to predict transient and steady flows. Quantitative comparisons are made with entangledsolution data. The model is able to capture quantitatively all...
Šolc, Milan
2002-01-01
Roč. 216, 07 (2002), s. 869-893 ISSN 0942-9352 R&D Projects: GA AV ČR IAA4032101 Institutional research plan: CEZ:AV0Z4032918 Keywords : stochastic kinetics * fluctuation * first-passage time Subject RIV: CF - Physical ; Theoretical Chemistry Impact factor: 0.854, year: 2002
Single cell Hi-C reveals cell-to-cell variability in chromosome structure
Schoenfelder, Stefan; Yaffe, Eitan; Dean, Wendy; Laue, Ernest D.; Tanay, Amos; Fraser, Peter
2013-01-01
Large-scale chromosome structure and spatial nuclear arrangement have been linked to control of gene expression and DNA replication and repair. Genomic techniques based on chromosome conformation capture assess contacts for millions of loci simultaneously, but do so by averaging chromosome conformations from millions of nuclei. Here we introduce single cell Hi-C, combined with genome-wide statistical analysis and structural modeling of single copy X chromosomes, to show that individual chromosomes maintain domain organisation at the megabase scale, but show variable cell-to-cell chromosome territory structures at larger scales. Despite this structural stochasticity, localisation of active gene domains to boundaries of territories is a hallmark of chromosomal conformation. Single cell Hi-C data bridge current gaps between genomics and microscopy studies of chromosomes, demonstrating how modular organisation underlies dynamic chromosome structure, and how this structure is probabilistically linked with genome activity patterns. PMID:24067610
Tetherin restricts productive HIV-1 cell-to-cell transmission.
Nicoletta Casartelli
2010-06-01
Full Text Available The IFN-inducible antiviral protein tetherin (or BST-2/CD317/HM1.24 impairs release of mature HIV-1 particles from infected cells. HIV-1 Vpu antagonizes the effect of tetherin. The fate of virions trapped at the cell surface remains poorly understood. Here, we asked whether tetherin impairs HIV cell-to-cell transmission, a major means of viral spread. Tetherin-positive or -negative cells, infected with wild-type or DeltaVpu HIV, were used as donor cells and cocultivated with target lymphocytes. We show that tetherin inhibits productive cell-to-cell transmission of DeltaVpu to targets and impairs that of WT HIV. Tetherin accumulates with Gag at the contact zone between infected and target cells, but does not prevent the formation of virological synapses. In the presence of tetherin, viruses are then mostly transferred to targets as abnormally large patches. These viral aggregates do not efficiently promote infection after transfer, because they accumulate at the surface of target cells and are impaired in their fusion capacities. Tetherin, by imprinting virions in donor cells, is the first example of a surface restriction factor limiting viral cell-to-cell spread.
Mechanisms for Cell-to-Cell Transmission of HIV-1
Bracq, Lucie; Xie, Maorong; Benichou, Serge; Bouchet, Jérôme
2018-01-01
While HIV-1 infection of target cells with cell-free viral particles has been largely documented, intercellular transmission through direct cell-to-cell contact may be a predominant mode of propagation in host. To spread, HIV-1 infects cells of the immune system and takes advantage of their specific particularities and functions. Subversion of intercellular communication allows to improve HIV-1 replication through a multiplicity of intercellular structures and membrane protrusions, like tunneling nanotubes, filopodia, or lamellipodia-like structures involved in the formation of the virological synapse. Other features of immune cells, like the immunological synapse or the phagocytosis of infected cells are hijacked by HIV-1 and used as gateways to infect target cells. Finally, HIV-1 reuses its fusogenic capacity to provoke fusion between infected donor cells and target cells, and to form infected syncytia with high capacity of viral production and improved capacities of motility or survival. All these modes of cell-to-cell transfer are now considered as viral mechanisms to escape immune system and antiretroviral therapies, and could be involved in the establishment of persistent virus reservoirs in different host tissues. PMID:29515578
Hainsworth, A. H.; Lee, S.; Patel, A.; Poon, W. W.; Knight, A. E.
2018-01-01
Aims The spatial resolution of light microscopy is limited by the wavelength of visible light (the ‘diffraction limit’, approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Methods Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8–32 nm) and for SOFI (effective pixel size 80 nm). Results In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Conclusions Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. PMID:28696566
Hainsworth, A H; Lee, S; Foot, P; Patel, A; Poon, W W; Knight, A E
2017-07-11
The spatial resolution of light microscopy is limited by the wavelength of visible light (the 'diffraction limit', approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8-32 nm) and for SOFI (effective pixel size 80 nm). In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. © 2017 British Neuropathological Society.
Vasdekis, A E; Silverman, A M; Stephanopoulos, G
2015-12-14
Bioprocess limitations imposed by microbial cell-to-cell phenotypic diversity remain poorly understood. To address this, we investigated the origins of such culture diversity during lipid production and assessed the impact of the fermentation microenvironment. We measured the single-cell lipid production dynamics in a time-invariant microfluidic environment and discovered that production is not monotonic, but rather sporadic with time. To characterize this, we introduce bioprocessing noise and identify its epigenetic origins. We linked such intracellular production fluctuations with cell-to-cell productivity diversity in culture. This unmasked the phenotypic diversity amplification by the culture microenvironment, a critical parameter in strain engineering as well as metabolic disease treatment.
Modeling PSA Problems - II: A Cell-to-Cell Transport Theory Approach
Labeau, P.E.; Izquierdo, J.M.
2005-01-01
In the first paper of this series, we presented an extension of the classical theory of dynamic reliability in which the actual occurrence of an event causing a change in the system dynamics is possibly delayed. The concept of stimulus activation, which triggers the realization of an event after a distributed time delay, was introduced. This gives a new understanding of competing events in the sequence delineation process.In the context of the level-2 probabilistic safety analysis (PSA), the information on stimulus activation mainly consists of regions of the process variables space where the activation can occur with a given probability. The evolution equations of the extended theory of probabilistic dynamics are therefore particularized to a transport process between discrete cells defined in phase-space on this basis. Doing so, an integrated and coherent approach to level-2 PSA problems is propounded. This amounts to including the stimulus concept and the associated stochastic delays discussed in the first paper in the frame of a cell-to-cell transport process.In addition, this discrete model provides a theoretical basis for the definition of appropriate numerical schemes for integrated level-2 PSA applications
Quantifying intrinsic and extrinsic variability in stochastic gene expression models.
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.
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
Gruel, Gaëtan; Villagrasa, Carmen; Voisin, Pascale; Clairand, Isabelle; Benderitter, Marc; Bottollier-Depois, Jean-François; Barquinero, Joan Francesc
2016-01-01
Most studies that aim to understand the interactions between different types of photon radiation and cellular DNA assume homogeneous cell irradiation, with all cells receiving the same amount of energy. The level of DNA damage is therefore generally determined by averaging it over the entire population of exposed cells. However, evaluating the molecular consequences of a stochastic phenomenon such as energy deposition of ionizing radiation by measuring only an average effect may not be sufficient for understanding some aspects of the cellular response to this radiation. The variance among the cells associated with this average effect may also be important for the behaviour of irradiated tissue. In this study, we accurately estimated the distribution of the number of radiation-induced γH2AX foci (RIF) per cell nucleus in a large population of endothelial cells exposed to 3 macroscopic doses of gamma rays from 60Co. The number of RIF varied significantly and reproducibly from cell to cell, with its relative standard deviation ranging from 36% to 18% depending on the macroscopic dose delivered. Interestingly, this relative cell-to-cell variability increased as the dose decreased, contrary to the mean RIF count per cell. This result shows that the dose effect, in terms of the number of DNA lesions indicated by RIF is not as simple as a purely proportional relation in which relative SD is constant with dose. To analyse the origins of this observed variability, we calculated the spread of the specific energy distribution for the different target volumes and subvolumes in which RIF can be generated. Variances, standard deviations and relative standard deviations all changed similarly from dose to dose for biological and calculated microdosimetric values. This similarity is an important argument that supports the hypothesis of the conservation of the association between the number of RIF per nucleus and the specific energy per DNA molecule. This comparison allowed us to
Gaëtan Gruel
Full Text Available Most studies that aim to understand the interactions between different types of photon radiation and cellular DNA assume homogeneous cell irradiation, with all cells receiving the same amount of energy. The level of DNA damage is therefore generally determined by averaging it over the entire population of exposed cells. However, evaluating the molecular consequences of a stochastic phenomenon such as energy deposition of ionizing radiation by measuring only an average effect may not be sufficient for understanding some aspects of the cellular response to this radiation. The variance among the cells associated with this average effect may also be important for the behaviour of irradiated tissue. In this study, we accurately estimated the distribution of the number of radiation-induced γH2AX foci (RIF per cell nucleus in a large population of endothelial cells exposed to 3 macroscopic doses of gamma rays from 60Co. The number of RIF varied significantly and reproducibly from cell to cell, with its relative standard deviation ranging from 36% to 18% depending on the macroscopic dose delivered. Interestingly, this relative cell-to-cell variability increased as the dose decreased, contrary to the mean RIF count per cell. This result shows that the dose effect, in terms of the number of DNA lesions indicated by RIF is not as simple as a purely proportional relation in which relative SD is constant with dose. To analyse the origins of this observed variability, we calculated the spread of the specific energy distribution for the different target volumes and subvolumes in which RIF can be generated. Variances, standard deviations and relative standard deviations all changed similarly from dose to dose for biological and calculated microdosimetric values. This similarity is an important argument that supports the hypothesis of the conservation of the association between the number of RIF per nucleus and the specific energy per DNA molecule. This
Dose-rate dependent stochastic effects in radiation cell-survival models
Sachs, R.K.; Hlatky, L.R.
1990-01-01
When cells are subjected to ionizing radiation the specific energy rate (microscopic analog of dose-rate) varies from cell to cell. Within one cell, this rate fluctuates during the course of time; a crossing of a sensitive cellular site by a high energy charged particle produces many ionizations almost simultaneously, but during the interval between events no ionizations occur. In any cell-survival model one can incorporate the effect of such fluctuations without changing the basic biological assumptions. Using stochastic differential equations and Monte Carlo methods to take into account stochastic effects we calculated the dose-survival rfelationships in a number of current cell survival models. Some of the models assume quadratic misrepair; others assume saturable repair enzyme systems. It was found that a significant effect of random fluctuations is to decrease the theoretically predicted amount of dose-rate sparing. In the limit of low dose-rates neglecting the stochastic nature of specific energy rates often leads to qualitatively misleading results by overestimating the surviving fraction drastically. In the opposite limit of acute irradiation, analyzing the fluctuations in rates merely amounts to analyzing fluctuations in total specific energy via the usual microdosimetric specific energy distribution function, and neglecting fluctuations usually underestimates the surviving fraction. The Monte Carlo methods interpolate systematically between the low dose-rate and high dose-rate limits. As in other approaches, the slope of the survival curve at low dose-rates is virtually independent of dose and equals the initial slope of the survival curve for acute radiation. (orig.)
Chen, Yong; Ge, Hao; Xiong, Jie; Xu, Lihu
2016-01-01
Fluctuation theorem is one of the major achievements in the field of nonequilibrium statistical mechanics during the past two decades. There exist very few results for steady-state fluctuation theorem of sample entropy production rate in terms of large deviation principle for diffusion processes due to the technical difficulties. Here we give a proof for the steady-state fluctuation theorem of a diffusion process in magnetic fields, with explicit expressions of the free energy function and rate function. The proof is based on the Karhunen-Loève expansion of complex-valued Ornstein-Uhlenbeck process.
Bierkens, M.F.P.; Bron, W.A.
2000-01-01
The VIDENTE program contains a decision support system (DSS) to choose between different models for stochastic modelling of water-table depths, and a graphical user interface to facilitate operating and running four implemented models: KALMAX, KALTFN,SSDS and EMERALD. In self-contained parts each of
Ahmet, Kara
2015-01-01
This paper presents a simple model of the provision of higher educational services that considers and exemplifies nonlinear, stochastic, and potentially chaotic processes. I use the methods of system dynamics to simulate these processes in the context of a particular sociologically interesting case, namely that of the Turkish higher education…
Listening to the Noise: Random Fluctuations Reveal Gene Network Parameters
Munsky, Brian; Trinh, Brooke; Khammash, Mustafa
2010-03-01
The cellular environment is abuzz with noise originating from the inherent random motion of reacting molecules in the living cell. In this noisy environment, clonal cell populations exhibit cell-to-cell variability that can manifest significant prototypical differences. Noise induced stochastic fluctuations in cellular constituents can be measured and their statistics quantified using flow cytometry, single molecule fluorescence in situ hybridization, time lapse fluorescence microscopy and other single cell and single molecule measurement techniques. We show that these random fluctuations carry within them valuable information about the underlying genetic network. Far from being a nuisance, the ever-present cellular noise acts as a rich source of excitation that, when processed through a gene network, carries its distinctive fingerprint that encodes a wealth of information about that network. We demonstrate that in some cases the analysis of these random fluctuations enables the full identification of network parameters, including those that may otherwise be difficult to measure. We use theoretical investigations to establish experimental guidelines for the identification of gene regulatory networks, and we apply these guideline to experimentally identify predictive models for different regulatory mechanisms in bacteria and yeast.
Stochastic TDHF and the Boltzman-Langevin equation
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
On the stochastic stability of MHD equilibria
Teichmann, J.
1979-07-01
The stochastic stability in the large of stationary equilibria of ideal and dissipative magnetohydrodynamics under the influence of stationary random fluctuations is studied using the direct Liapunov method. Sufficient and necessary conditions for stability of the linearized Euler-Lagrangian systems are given. The destabilizing effect of stochastic fluctuations is demonstrated. (orig.)
Gambling with Superconducting Fluctuations
Foltyn, Marek; Zgirski, Maciej
2015-08-01
Josephson junctions and superconducting nanowires, when biased close to superconducting critical current, can switch to a nonzero voltage state by thermal or quantum fluctuations. The process is understood as an escape of a Brownian particle from a metastable state. Since this effect is fully stochastic, we propose to use it for generating random numbers. We present protocol for obtaining random numbers and test the experimentally harvested data for their fidelity. Our work is prerequisite for using the Josephson junction as a tool for stochastic (probabilistic) determination of physical parameters such as magnetic flux, temperature, and current.
Obtaining the Wakefield Due to Cell-to-Cell Misalignments in a Linear Accelerator Structure
Bane, Karl L. F.; Li, Zenghai
2001-01-01
A linear accelerator structure, such as will be used in the linacs of the JLC/NLC collider, is composed of on the order of 100 cells. The cells are constructed as individual cups that are brazed together to form a structure. Fabrication error will result in slight cell-to-cell misalignments along the finished structure. In this report we derive an approximation to the transverse wakefield of a structure with cell-to-cell misalignments in terms of the eigenfunctions and eigenvalues of the erro...
Surface Transmission or Polarized Egress? Lessons Learned from HTLV Cell-to-Cell Transmission
Jin, Jing; Sherer, Nathan; Mothes, Walther
2010-01-01
Commentary on Pais-Correia, A.M.; Sachse, M.; Guadagnini, S.; Robbiati, V.; Lasserre, R.; Gessain, A.; Gout, O.; Alcover, A.; Thoulouze, M.I. Biofilm-like extracellular viral assemblies mediate HTLV-1 cell-to-cell transmission at virological synapses. Nat. Med. 2010, 16, 83–89. PMID:21994650
Inhibition of HSV cell-to-cell spread by lactoferrin and lactoferricin.
Jenssen, Håvard; Sandvik, Kjersti; Andersen, Jeanette H; Hancock, Robert E W; Gutteberg, Tore J
2008-09-01
The milk protein lactoferrin (Lf) has multiple functions, including immune stimulation and antiviral activity towards herpes simplex virus 1 and 2 (HSV-1 and HSV-2); antiviral activity has also been reported for the N-terminal pepsin-derived fragment lactoferricin (Lfcin). The anti-HSV mode of action of Lf and Lfcin is assumed to involve, in part, their interaction with the cell surface glycosaminoglycan heparan sulfate, thereby blocking of viral entry. In this study we investigated the ability of human and bovine Lf and Lfcin to inhibit viral cell-to-cell spread as well as the involvement of cell surface glycosaminoglycans during viral cell-to-cell spread. Lf and Lfcin from both human and bovine origin, inhibited cell-to-cell spread of both HSV-1 and HSV-2. Inhibition of cell-to-cell spread by bovine Lfcin involved cell surface chondroitin sulfate. Based on transmission electron microscopy studies, human Lfcin, like bovine Lfcin, was randomly distributed intracellularly, thus differences in their antiviral activity could not be explained by differences in their distribution. In contrast, the cellular localization of iron-saturated (holo)-Lf appeared to differ from that of apo-Lf, indicating that holo- and apo-Lf may exhibit different antiviral mechanisms.
Non-chemical and non-contact cell-to-cell communication: a short review
Scholkmann, F.; Fels, D.; Cifra, Michal
2013-01-01
Roč. 5, č. 6 (2013), s. 586-593 ISSN 1943-8141 R&D Projects: GA ČR GA13-29294S Institutional support: RVO:67985882 Keywords : Cell-to-cell communication * physical signaling Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 3.226, year: 2013
MEMS-based dynamic cell-to-cell culture platforms using electrochemical surface modifications
Chang, Jiyoung; Lin, Liwei; Yoon, Sang-Hee; Mofrad, Mohammad R K
2011-01-01
MEMS-based biological platforms with the capability of both spatial placements and time releases of living cells for cell-to-cell culture experiments have been designed and demonstrated utilizing electrochemical surface modification effects. The spatial placement is accomplished by electrochemical surface modification of substrate surfaces to be either adhesive or non-adhesive for living cells. The time control is achieved by the electrical activation of the selective indium tin oxide co-culture electrode to allow the migration of living cells onto the electrode to start the cell-to-cell culture studies. Prototype devices have a three-electrode design with an electrode size of 50 × 50 µm 2 and the separation gaps of 2 µm between them. An electrical voltage of −1.5 V has been used to activate the electrodes independently and sequentially to demonstrate the dynamic cell-to-cell culture experiments of NIH 3T3 fibroblast and Madin Darby canine kidney cells. As such, this MEMS platform could be a basic yet versatile tool to characterize transient cell-to-cell interactions
Stochastic volatility and stochastic leverage
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...
The Arabidopsis synaptotagmin SYTA regulates the cell-to-cell movement of diverse plant viruses
Asako eUchiyama
2014-11-01
Full Text Available Synaptotagmins are a large gene family in animals that have been extensively characterized due to their role as calcium sensors to regulate synaptic vesicle exocytosis and endocytosis in neurons, and dense core vesicle exocytosis for hormone secretion from neuroendocrine cells. Thought to be exclusive to animals, synaptotagmins have recently been characterized in Arabidopsis thaliana, in which they comprise a five gene family. Using infectivity and leaf-based functional assays, we have shown that Arabidopsis SYTA regulates endocytosis and marks an endosomal vesicle recycling pathway to regulate movement protein-mediated trafficking of the Begomovirus Cabbage leaf curl virus (CaLCuV and the Tobamovirus Tobacco mosaic virus (TMV through plasmodesmata (Lewis and Lazarowitz, 2010. To determine whether SYTA has a central role in regulating the cell-to-cell trafficking of a wider range of diverse plant viruses, we extended our studies here to examine the role of SYTA in the cell-to-cell movement of additional plant viruses that employ different modes of movement, namely the Potyvirus Turnip mosaic virus (TuMV, the Caulimovirus Cauliflower mosaic virus (CaMV and the Tobamovirus Turnip vein clearing virus (TVCV, which in contrast to TMV does efficiently infect Arabidopsis. We found that both TuMV and TVCV systemic infection, and the cell-to-cell trafficking of the their movement proteins, were delayed in the Arabidopsis Col-0 syta-1 knockdown mutant. In contrast, CaMV systemic infection was not inhibited in syta-1. Our studies show that SYTA is a key regulator of plant virus intercellular movement, being necessary for the ability of diverse cell-to-cell movement proteins encoded by Begomoviruses (CaLCuV MP, Tobamoviruses (TVCV and TMV 30K protein and Potyviruses (TuMV P3N-PIPO to alter PD and thereby mediate virus cell-to-cell spread.
Phase space fluctuations and dynamics of fluctuations of collective variables
Benhassine, B.; Farine, M.; Idier, D.; Remaud, B.; Sebille, F. (Lab. de Physique Nucleaire, IN2P3/CNRS, 44 - Nantes (France) Nantes Univ., 44 (France)); Hernandez, E.S. (Dept. de Fisica, Ciudad Universitaria, Buenos Aires (Argentina))
1992-08-03
Within the framework of theoretical approaches based on stochastic transport equation of one-body distribution function, a numerical treatment of the fluctuations of collective observables is studied and checked in comparison with analytical results either at equilibrium or close to it. (orig.).
Phase space fluctuations and dynamics of fluctuations of collective variables
Benhassine, B.; Farine, M.; Idier, D.; Remaud, B.; Sebille, F.; Hernandez, E.S.
1992-01-01
Within the framework of theoretical approaches based on stochastic transport equation of one-body distribution function, a numerical treatment of the fluctuations of collective observables is studied and checked in comparison with analytical results either at equilibrium or close to it. (orig.)
Stochastic theory of fatigue corrosion
Hu, Haiyun
1999-10-01
A stochastic theory of corrosion has been constructed. The stochastic equations are described giving the transportation corrosion rate and fluctuation corrosion coefficient. In addition the pit diameter distribution function, the average pit diameter and the most probable pit diameter including other related empirical formula have been derived. In order to clarify the effect of stress range on the initiation and growth behaviour of pitting corrosion, round smooth specimen were tested under cyclic loading in 3.5% NaCl solution.
Memory effects on stochastic resonance
Neiman, Alexander; Sung, Wokyung
1996-02-01
We study the phenomenon of stochastic resonance (SR) in a bistable system with internal colored noise. In this situation the system possesses time-dependent memory friction connected with noise via the fluctuation-dissipation theorem, so that in the absence of periodic driving the system approaches the thermodynamic equilibrium state. For this non-Markovian case we find that memory usually suppresses stochastic resonance. However, for a large memory time SR can be enhanced by the memory.
Stochastic approach to microphysics
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...).
Bacterial spread from cell to cell: beyond actin-based motility.
Kuehl, Carole J; Dragoi, Ana-Maria; Talman, Arthur; Agaisse, Hervé
2015-09-01
Several intracellular pathogens display the ability to propagate within host tissues by displaying actin-based motility in the cytosol of infected cells. As motile bacteria reach cell-cell contacts they form plasma membrane protrusions that project into adjacent cells and resolve into vacuoles from which the pathogen escapes, thereby achieving spread from cell to cell. Seminal studies have defined the bacterial and cellular factors that support actin-based motility. By contrast, the mechanisms supporting the formation of protrusions and their resolution into vacuoles have remained elusive. Here, we review recent advances in the field showing that Listeria monocytogenes and Shigella flexneri have evolved pathogen-specific mechanisms of bacterial spread from cell to cell. Copyright © 2015 Elsevier Ltd. All rights reserved.
Myosin-Va-dependent cell-to-cell transfer of RNA from Schwann cells to axons.
José R Sotelo
Full Text Available To better understand the role of protein synthesis in axons, we have identified the source of a portion of axonal RNA. We show that proximal segments of transected sciatic nerves accumulate newly-synthesized RNA in axons. This RNA is synthesized in Schwann cells because the RNA was labeled in the complete absence of neuronal cell bodies both in vitro and in vivo. We also demonstrate that the transfer is prevented by disruption of actin and that it fails to occur in the absence of myosin-Va. Our results demonstrate cell-to-cell transfer of RNA and identify part of the mechanism required for transfer. The induction of cell-to-cell RNA transfer by injury suggests that interventions following injury or degeneration, particularly gene therapy, may be accomplished by applying them to nearby glial cells (or implanted stem cells at the site of injury to promote regeneration.
Myosin-Va-dependent cell-to-cell transfer of RNA from Schwann cells to axons.
Sotelo, José R; Canclini, Lucía; Kun, Alejandra; Sotelo-Silveira, José R; Xu, Lei; Wallrabe, Horst; Calliari, Aldo; Rosso, Gonzalo; Cal, Karina; Mercer, John A
2013-01-01
To better understand the role of protein synthesis in axons, we have identified the source of a portion of axonal RNA. We show that proximal segments of transected sciatic nerves accumulate newly-synthesized RNA in axons. This RNA is synthesized in Schwann cells because the RNA was labeled in the complete absence of neuronal cell bodies both in vitro and in vivo. We also demonstrate that the transfer is prevented by disruption of actin and that it fails to occur in the absence of myosin-Va. Our results demonstrate cell-to-cell transfer of RNA and identify part of the mechanism required for transfer. The induction of cell-to-cell RNA transfer by injury suggests that interventions following injury or degeneration, particularly gene therapy, may be accomplished by applying them to nearby glial cells (or implanted stem cells) at the site of injury to promote regeneration.
Aging increases cell-to-cell transcriptional variability upon immune stimulation.
Martinez-Jimenez, Celia Pilar; Eling, Nils; Chen, Hung-Chang; Vallejos, Catalina A; Kolodziejczyk, Aleksandra A; Connor, Frances; Stojic, Lovorka; Rayner, Timothy F; Stubbington, Michael J T; Teichmann, Sarah A; de la Roche, Maike; Marioni, John C; Odom, Duncan T
2017-03-31
Aging is characterized by progressive loss of physiological and cellular functions, but the molecular basis of this decline remains unclear. We explored how aging affects transcriptional dynamics using single-cell RNA sequencing of unstimulated and stimulated naïve and effector memory CD4 + T cells from young and old mice from two divergent species. In young animals, immunological activation drives a conserved transcriptomic switch, resulting in tightly controlled gene expression characterized by a strong up-regulation of a core activation program, coupled with a decrease in cell-to-cell variability. Aging perturbed the activation of this core program and increased expression heterogeneity across populations of cells in both species. These discoveries suggest that increased cell-to-cell transcriptional variability will be a hallmark feature of aging across most, if not all, mammalian tissues. Copyright © 2017, American Association for the Advancement of Science.
Stochastic background of atmospheric cascades
Wilk, G.; Wlodarczyk, Z.
1993-01-01
Fluctuations in the atmospheric cascades developing during the propagation of very high energy cosmic rays through the atmosphere are investigated using stochastic branching model of pure birth process with immigration. In particular, we show that the multiplicity distributions of secondaries emerging from gamma families are much narrower than those resulting from hadronic families. We argue that the strong intermittent like behaviour found recently in atmospheric families results from the fluctuations in the cascades themselves and are insensitive to the details of elementary interactions
Stochastic deformation of a thermodynamic symplectic structure
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...
Bible, Amber N; Khalsa-Moyers, Gurusahai K; Mukherjee, Tanmoy; Green, Calvin S; Mishra, Priyanka; Purcell, Alicia; Aksenova, Anastasia; Hurst, Gregory B; Alexandre, Gladys
2015-12-01
The ability of bacteria to monitor their metabolism and adjust their behavior accordingly is critical to maintain competitiveness in the environment. The motile microaerophilic bacterium Azospirillum brasilense navigates oxygen gradients by aerotaxis in order to locate low oxygen concentrations that can support metabolism. When cells are exposed to elevated levels of oxygen in their surroundings, motile A. brasilense cells implement an alternative response to aerotaxis and form transient clumps by cell-to-cell interactions. Clumping was suggested to represent a behavior protecting motile cells from transiently elevated levels of aeration. Using the proteomics of wild-type and mutant strains affected in the extent of their clumping abilities, we show that cell-to-cell clumping represents a metabolic scavenging strategy that likely prepares the cells for further metabolic stresses. Analysis of mutants affected in carbon or nitrogen metabolism confirmed this assumption. The metabolic changes experienced as clumping progresses prime cells for flocculation, a morphological and metabolic shift of cells triggered under elevated-aeration conditions and nitrogen limitation. The analysis of various mutants during clumping and flocculation characterized an ordered set of changes in cell envelope properties accompanying the metabolic changes. These data also identify clumping and early flocculation to be behaviors compatible with the expression of nitrogen fixation genes, despite the elevated-aeration conditions. Cell-to-cell clumping may thus license diazotrophy to microaerophilic A. brasilense cells under elevated oxygen conditions and prime them for long-term survival via flocculation if metabolic stress persists. Copyright © 2015, American Society for Microbiology. All Rights Reserved.
Random Walk Model for Cell-To-Cell Misalignments in Accelerator Structures
Stupakov, Gennady
2000-01-01
Due to manufacturing and construction errors, cells in accelerator structures can be misaligned relative to each other. As a consequence, the beam generates a transverse wakefield even when it passes through the structure on axis. The most important effect is the long-range transverse wakefield that deflects the bunches and causes growth of the bunch train projected emittance. In this paper, the effect of the cell-to-cell misalignments is evaluated using a random walk model that assumes that each cell is shifted by a random step relative to the previous one. The model is compared with measurements of a few accelerator structures
Stochastic processes in mechanical engineering
Brouwers, J.J.H.
2006-01-01
Stochastic or random vibrations occur in a variety of applications of mechanicalengineering. Examples are: the dynamics of a vehicle on an irregular roadsurface; the variation in time of thermodynamic variables in municipal wasteincinerators due to fluctuations in heating value of the waste; the
Environmental Stochasticity and the Speed of Evolution
Danino, Matan; Kessler, David A.; Shnerb, Nadav M.
2018-03-01
Biological populations are subject to two types of noise: demographic stochasticity due to fluctuations in the reproductive success of individuals, and environmental variations that affect coherently the relative fitness of entire populations. The rate in which the average fitness of a community increases has been considered so far using models with pure demographic stochasticity; here we present some theoretical considerations and numerical results for the general case where environmental variations are taken into account. When the competition is pairwise, fitness fluctuations are shown to reduce the speed of evolution, while under global competition the speed increases due to environmental stochasticity.
Relation between radio-adaptive response and cell to cell communication
Keiichiro Ishii
1996-01-01
Ionizing radiation has been considered to cause severe damages to DNA and do harm to cells in proportion to the dose, however low it might be. In 1984, Wolff et al. showed that human peripheral lymphocytes adapted to the low-dose radiation from 3 H-TdR added in culture medium and became resistant to the subsequent irradiation with high-doses of X-rays. This response, which is called radio-adaptive response, is also induced by X-rays and gamma-rays in human lymphocytes and Chinese hamster V79 cells. However, the mechanisms of and conditions for adaptive responses to radiation have not been clarified. With an objective of clarifying the conditions for adaptive responses of cells to radiation, we examined how the cell to cell communication is involved in the adaptive responses. We irradiated normal human embryo-derived (HE) cells and cancer cells (HeLa) in culture at high density with low-dose X-ray and examined their radio-adaptive responses by measuring the changes in sensitivity to subsequent high-dose X-ray irradiation using the Trypan Blue dye-exclusion test method. We also conducted experiments to examine the effects of Ca 2+ ions and Phorbol 12-Myristate 13-Acetate (TPA) which are supposed to be involved in cell to cell communication. (author)
Jennifer S. Liu
2012-11-01
Full Text Available Variability in signaling pathway activation between neighboring epithelial cells can arise from local differences in the microenvironment, noisy gene expression, or acquired genetic changes. To investigate the consequences of this cell-to-cell variability in signaling pathway activation on coordinated multicellular processes such as morphogenesis, we use DNA-programmed assembly to construct three-dimensional MCF10A microtissues that are mosaic for low-level expression of activated H-Ras. We find two emergent behaviors in mosaic microtissues: cells with activated H-Ras are basally extruded or lead motile multicellular protrusions that direct the collective motility of their wild-type neighbors. Remarkably, these behaviors are not observed in homogeneous microtissues in which all cells express the activated Ras protein, indicating that heterogeneity in Ras activity, rather than the total amount of Ras activity, is critical for these processes. Our results directly demonstrate that cell-to-cell variability in pathway activation within local populations of epithelial cells can drive emergent behaviors during epithelial morphogenesis.
Stochasticity in materials structure, properties, and processing—A review
Hull, Robert; Keblinski, Pawel; Lewis, Dan; Maniatty, Antoinette; Meunier, Vincent; Oberai, Assad A.; Picu, Catalin R.; Samuel, Johnson; Shephard, Mark S.; Tomozawa, Minoru; Vashishth, Deepak; Zhang, Shengbai
2018-03-01
We review the concept of stochasticity—i.e., unpredictable or uncontrolled fluctuations in structure, chemistry, or kinetic processes—in materials. We first define six broad classes of stochasticity: equilibrium (thermodynamic) fluctuations; structural/compositional fluctuations; kinetic fluctuations; frustration and degeneracy; imprecision in measurements; and stochasticity in modeling and simulation. In this review, we focus on the first four classes that are inherent to materials phenomena. We next develop a mathematical framework for describing materials stochasticity and then show how it can be broadly applied to these four materials-related stochastic classes. In subsequent sections, we describe structural and compositional fluctuations at small length scales that modify material properties and behavior at larger length scales; systems with engineered fluctuations, concentrating primarily on composite materials; systems in which stochasticity is developed through nucleation and kinetic phenomena; and configurations in which constraints in a given system prevent it from attaining its ground state and cause it to attain several, equally likely (degenerate) states. We next describe how stochasticity in these processes results in variations in physical properties and how these variations are then accentuated by—or amplify—stochasticity in processing and manufacturing procedures. In summary, the origins of materials stochasticity, the degree to which it can be predicted and/or controlled, and the possibility of using stochastic descriptions of materials structure, properties, and processing as a new degree of freedom in materials design are described.
Turbulent response in a stochastic regime
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
Stochastic ice stream dynamics.
Mantelli, Elisa; Bertagni, Matteo Bernard; Ridolfi, Luca
2016-08-09
Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution.
Fractional Stochastic Field Theory
Honkonen, Juha
2018-02-01
Models describing evolution of physical, chemical, biological, social and financial processes are often formulated as differential equations with the understanding that they are large-scale equations for averages of quantities describing intrinsically random processes. Explicit account of randomness may lead to significant changes in the asymptotic behaviour (anomalous scaling) in such models especially in low spatial dimensions, which in many cases may be captured with the use of the renormalization group. Anomalous scaling and memory effects may also be introduced with the use of fractional derivatives and fractional noise. Construction of renormalized stochastic field theory with fractional derivatives and fractional noise in the underlying stochastic differential equations and master equations and the interplay between fluctuation-induced and built-in anomalous scaling behaviour is reviewed and discussed.
Dynamics of stochastic systems
Klyatskin, Valery I
2005-01-01
Fluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. The well known example of Brownian particle suspended in fluid and subjected to random molecular bombardment laid the foundation for modern stochastic calculus and statistical physics. Other important examples include turbulent transport and diffusion of particle-tracers (pollutants), or continuous densities (''''oil slicks''''), wave propagation and scattering in randomly inhomogeneous media, for instance light or sound propagating in the turbulent atmosphere.Such models naturally render to statistical description, where the input parameters and solutions are expressed by random processes and fields.The fundamental problem of stochastic dynamics is to identify the essential characteristics of system (its state and evolution), and relate those to the input parameters of ...
Ryan Chong
Full Text Available Intracellular bacterial pathogens, such as Listeria monocytogenes and Rickettsia conorii display actin-based motility in the cytosol of infected cells and spread from cell to cell through the formation of membrane protrusions at the cell cortex. Whereas the mechanisms supporting cytosolic actin-based motility are fairly well understood, it is unclear whether specific host factors may be required for supporting the formation and resolution of membrane protrusions. To address this gap in knowledge, we have developed high-throughput fluorescence microscopy and computer-assisted image analysis procedures to quantify pathogen spread in human epithelial cells. We used the approach to screen a siRNA library covering the human kinome and identified 7 candidate kinases whose depletion led to severe spreading defects in cells infected with L. monocytogenes. We conducted systematic validation procedures with redundant silencing reagents and confirmed the involvement of the serine/threonine kinases, CSNK1A1 and CSNK2B. We conducted secondary assays showing that, in contrast with the situation observed in CSNK2B-depleted cells, L. monocytogenes formed wild-type cytosolic tails and displayed wild-type actin-based motility in the cytosol of CSNK1A1-depleted cells. Furthermore, we developed a protrusion formation assay and showed that the spreading defect observed in CSNK1A1-depleted cells correlated with the formation of protrusion that did not resolve into double-membrane vacuoles. Moreover, we developed sending and receiving cell-specific RNAi procedures and showed that CSNK1A was required in the sending cells, but was dispensable in the receiving cells, for protrusion resolution. Finally, we showed that the observed defects were specific to Listeria monocytogenes, as Rickettsia conorii displayed wild-type cell-to-cell spread in CSNK1A1- and CSNK2B-depleted cells. We conclude that, in addition to the specific host factors supporting cytosolic actin
Shima P Damodaran
Full Text Available To address possible cell-to-cell heterogeneity in growth dynamics of isogenic cell populations of Chlamydomonas reinhardtii, we developed a millifluidic drop-based device that not only allows the analysis of populations grown from single cells over periods of a week, but is also able to sort and collect drops of interest, containing viable and healthy cells, which can be used for further experimentation. In this study, we used isogenic algal cells that were first synchronized in mixotrophic growth conditions. We show that these synchronized cells, when placed in droplets and kept in mixotrophic growth conditions, exhibit mostly homogeneous growth statistics, but with two distinct subpopulations: a major population with a short doubling-time (fast-growers and a significant subpopulation of slowly dividing cells (slow-growers. These observations suggest that algal cells from an isogenic population may be present in either of two states, a state of restricted division and a state of active division. When isogenic cells were allowed to propagate for about 1000 generations on solid agar plates, they displayed an increased heterogeneity in their growth dynamics. Although we could still identify the original populations of slow- and fast-growers, drops inoculated with a single progenitor cell now displayed a wider diversity of doubling-times. Moreover, populations dividing with the same growth-rate often reached different cell numbers in stationary phase, suggesting that the progenitor cells differed in the number of cell divisions they could undertake. We discuss possible explanations for these cell-to-cell heterogeneities in growth dynamics, such as mutations, differential aging or stochastic variations in metabolites and macromolecules yielding molecular switches, in the light of single-cell heterogeneities that have been reported among isogenic populations of other eu- and prokaryotes.
Lai, Julian; Koh, Chuan Hock; Tjota, Monika; Pieuchot, Laurent; Raman, Vignesh; Chandrababu, Karthik Balakrishna; Yang, Daiwen; Wong, Limsoon; Jedd, Gregory
2012-09-25
Like animals and plants, multicellular fungi possess cell-to-cell channels (septal pores) that allow intercellular communication and transport. Here, using a combination of MS of Woronin body-associated proteins and a bioinformatics approach that identifies related proteins based on composition and character, we identify 17 septal pore-associated (SPA) proteins that localize to the septal pore in rings and pore-centered foci. SPA proteins are not homologous at the primary sequence level but share overall physical properties with intrinsically disordered proteins. Some SPA proteins form aggregates at the septal pore, and in vitro assembly assays suggest aggregation through a nonamyloidal mechanism involving mainly α-helical and disordered structures. SPA loss-of-function phenotypes include excessive septation, septal pore degeneration, and uncontrolled Woronin body activation. Together, our data identify the septal pore as a complex subcellular compartment and focal point for the assembly of unstructured proteins controlling diverse aspects of intercellular connectivity.
Cell-to-cell communication in plants, animals, and fungi: a comparative review.
Bloemendal, Sandra; Kück, Ulrich
2013-01-01
Cell-to-cell communication is a prerequisite for differentiation and development in multicellular organisms. This communication has to be tightly regulated to ensure that cellular components such as organelles, macromolecules, hormones, or viruses leave the cell in a precisely organized way. During evolution, plants, animals, and fungi have developed similar ways of responding to this biological challenge. For example, in higher plants, plasmodesmata connect adjacent cells and allow communication to regulate differentiation and development. In animals, two main general structures that enable short- and long-range intercellular communication are known, namely gap junctions and tunneling nanotubes, respectively. Finally, filamentous fungi have also developed specialized structures called septal pores that allow intercellular communication via cytoplasmic flow. This review summarizes the underlying mechanisms for intercellular communication in these three eukaryotic groups and discusses its consequences for the regulation of differentiation and developmental processes.
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
Alpha-synuclein cell-to-cell transfer and seeding in grafted dopaminergic neurons in vivo.
Elodie Angot
Full Text Available Several people with Parkinson's disease have been treated with intrastriatal grafts of fetal dopaminergic neurons. Following autopsy, 10-22 years after surgery, some of the grafted neurons contained Lewy bodies similar to those observed in the host brain. Numerous studies have attempted to explain these findings in cell and animal models. In cell culture, α-synuclein has been found to transfer from one cell to another, via mechanisms that include exosomal transport and endocytosis, and in certain cases seed aggregation in the recipient cell. In animal models, transfer of α-synuclein from host brain cells to grafted neurons has been shown, but the reported frequency of the event has been relatively low and little is known about the underlying mechanisms as well as the fate of the transferred α-synuclein. We now demonstrate frequent transfer of α-synuclein from a rat brain engineered to overexpress human α-synuclein to grafted dopaminergic neurons. Further, we show that this model can be used to explore mechanisms underlying cell-to-cell transfer of α-synuclein. Thus, we present evidence both for the involvement of endocytosis in α-synuclein uptake in vivo, and for seeding of aggregation of endogenous α-synuclein in the recipient neuron by the transferred α-synuclein. Finally, we show that, at least in a subset of the studied cells, the transmitted α-synuclein is sensitive to proteinase K. Our new model system could be used to test compounds that inhibit cell-to-cell transfer of α-synuclein and therefore might retard progression of Parkinson neuropathology.
Cell-to-cell communication and cellular environment alter the somatostatin status of delta cells
Kelly, Catriona, E-mail: catriona.kelly@qub.ac.uk [SAAD Centre for Pharmacy and Diabetes, School of Biomedical Sciences, University of Ulster, Coleraine (United Kingdom); Flatt, Peter R.; McClenaghan, Neville H. [SAAD Centre for Pharmacy and Diabetes, School of Biomedical Sciences, University of Ulster, Coleraine (United Kingdom)
2010-08-20
Research highlights: {yields} TGP52 cells display enhanced functionality in pseudoislet form. {yields} Somatostatin content was reduced, but secretion increased in high glucose conditions. {yields} Cellular interactions and environment alter the somatostatin status of TGP52 cells. -- Abstract: Introduction: Somatostatin, released from pancreatic delta cells, is a potent paracrine inhibitor of insulin and glucagon secretion. Islet cellular interactions and glucose homeostasis are essential to maintain normal patterns of insulin secretion. However, the importance of cell-to-cell communication and cellular environment in the regulation of somatostatin release remains unclear. Methods: This study employed the somatostatin-secreting TGP52 cell line maintained in DMEM:F12 (17.5 mM glucose) or DMEM (25 mM glucose) culture media. The effect of pseudoislet formation and culture medium on somatostatin content and release in response to a variety of stimuli was measured by somatostatin EIA. In addition, the effect of pseudoislet formation on cellular viability (MTT and LDH assays) and proliferation (BrdU ELISA) was determined. Results: TGP52 cells readily formed pseudoislets and showed enhanced functionality in three-dimensional form with increased E-cadherin expression irrespective of the culture environment used. However, culture in DMEM decreased cellular somatostatin content (P < 0.01) and increased somatostatin secretion in response to a variety of stimuli including arginine, calcium and PMA (P < 0.001) when compared with cells grown in DMEM:F12. Configuration of TGP52 cells as pseudoislets reduced the proliferative rate and increased cellular cytotoxicity irrespective of culture medium used. Conclusions: Somatostatin secretion is greatly facilitated by cell-to-cell interactions and E-cadherin expression. Cellular environment and extracellular glucose also significantly influence the function of delta cells.
Cell-to-cell communication and cellular environment alter the somatostatin status of delta cells
Kelly, Catriona; Flatt, Peter R.; McClenaghan, Neville H.
2010-01-01
Research highlights: → TGP52 cells display enhanced functionality in pseudoislet form. → Somatostatin content was reduced, but secretion increased in high glucose conditions. → Cellular interactions and environment alter the somatostatin status of TGP52 cells. -- Abstract: Introduction: Somatostatin, released from pancreatic delta cells, is a potent paracrine inhibitor of insulin and glucagon secretion. Islet cellular interactions and glucose homeostasis are essential to maintain normal patterns of insulin secretion. However, the importance of cell-to-cell communication and cellular environment in the regulation of somatostatin release remains unclear. Methods: This study employed the somatostatin-secreting TGP52 cell line maintained in DMEM:F12 (17.5 mM glucose) or DMEM (25 mM glucose) culture media. The effect of pseudoislet formation and culture medium on somatostatin content and release in response to a variety of stimuli was measured by somatostatin EIA. In addition, the effect of pseudoislet formation on cellular viability (MTT and LDH assays) and proliferation (BrdU ELISA) was determined. Results: TGP52 cells readily formed pseudoislets and showed enhanced functionality in three-dimensional form with increased E-cadherin expression irrespective of the culture environment used. However, culture in DMEM decreased cellular somatostatin content (P < 0.01) and increased somatostatin secretion in response to a variety of stimuli including arginine, calcium and PMA (P < 0.001) when compared with cells grown in DMEM:F12. Configuration of TGP52 cells as pseudoislets reduced the proliferative rate and increased cellular cytotoxicity irrespective of culture medium used. Conclusions: Somatostatin secretion is greatly facilitated by cell-to-cell interactions and E-cadherin expression. Cellular environment and extracellular glucose also significantly influence the function of delta cells.
Klauder, J.R.
1983-01-01
The author provides an introductory survey to stochastic quantization in which he outlines this new approach for scalar fields, gauge fields, fermion fields, and condensed matter problems such as electrons in solids and the statistical mechanics of quantum spins. (Auth.)
Stochastic inflation and nonlinear gravity
Salopek, D.S.; Bond, J.R.
1991-01-01
We show how nonlinear effects of the metric and scalar fields may be included in stochastic inflation. Our formalism can be applied to non-Gaussian fluctuation models for galaxy formation. Fluctuations with wavelengths larger than the horizon length are governed by a network of Langevin equations for the physical fields. Stochastic noise terms arise from quantum fluctuations that are assumed to become classical at horizon crossing and that then contribute to the background. Using Hamilton-Jacobi methods, we solve the Arnowitt-Deser-Misner constraint equations which allows us to separate the growing modes from the decaying ones in the drift phase following each stochastic impulse. We argue that the most reasonable choice of time hypersurfaces for the Langevin system during inflation is T=ln(Ha), where H and a are the local values of the Hubble parameter and the scale factor, since T is the natural time for evolving the short-wavelength scalar field fluctuations in an inhomogeneous background
Stochastic Effects in Microstructure
Glicksman M.E.
2002-01-01
Full Text Available We are currently studying microstructural responses to diffusion-limited coarsening in two-phase materials. A mathematical solution to late-stage multiparticle diffusion in finite systems is formulated with account taken of particle-particle interactions and their microstructural correlations, or "locales". The transition from finite system behavior to that for an infinite microstructure is established analytically. Large-scale simulations of late-stage phase coarsening dynamics show increased fluctuations with increasing volume fraction, Vv, of the mean flux entering or leaving particles of a given size class. Fluctuations about the mean flux were found to depend on the scaled particle size, R/, where R is the radius of a particle and is the radius of the dispersoid averaged over the population within the microstructure. Specifically, small (shrinking particles tend to display weak fluctuations about their mean flux, whereas particles of average, or above average size, exhibit strong fluctuations. Remarkably, even in cases of microstructures with a relatively small volume fraction (Vv ~ 10-4, the particle size distribution is broader than that for the well-known Lifshitz-Slyozov limit predicted at zero volume fraction. The simulation results reported here provide some additional surprising insights into the effect of diffusion interactions and stochastic effects during evolution of a microstructure, as it approaches its thermodynamic end-state.
STOCHASTIC ASSESSMENT OF NIGERIAN STOCHASTIC ...
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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.
Reynaud, S.; Giacobino, S.; Zinn-Justin, J.
1997-01-01
This course is dedicated to present in a pedagogical manner the recent developments in peculiar fields concerned by quantum fluctuations: quantum noise in optics, light propagation through dielectric media, sub-Poissonian light generated by lasers and masers, quantum non-demolition measurements, quantum electrodynamics applied to cavities and electrical circuits involving superconducting tunnel junctions. (A.C.)
Can Cell to Cell Thermal Runaway Propagation be Prevented in a Li-ion Battery Module?
Jeevarajan, Judith; Lopez, Carlos; Orieukwu, Josephat
2014-01-01
Increasing cell spacing decreased adjacent cell damage center dotElectrically connected adjacent cells drained more than physically adjacent cells center dotRadiant barrier prevents propagation when fully installed between BP cells center dotBP cells vent rapidly and expel contents at 100% SOC -Slower vent with flame/smoke at 50% -Thermal runaway event typically occurs at 160 degC center dotLG cells vent but do not expel contents -Thermal runaway event typically occurs at 200 degC center dotSKC LFP modules did not propagate; fuses on negative terminal of cell may provide a benefit in reducing cell to cell damage propagation. New requirement in NASA-Battery Safety Requirements document: JSC 20793 Rev C 5.1.5.1 Requirements - Thermal Runaway Propagation a. For battery designs greater than a 80-Wh energy employing high specific energy cells (greater than 80 watt-hours/kg, for example, lithium-ion chemistries) with catastrophic failure modes, the battery shall be evaluated to ascertain the severity of a worst-case single-cell thermal runaway event and the propensity of the design to demonstrate cell-to-cell propagation in the intended application and environment. NASA has traditionally addressed the threat of thermal runaway incidents in its battery deployments through comprehensive prevention protocols. This prevention-centered approach has included extensive screening for manufacturing defects, as well as robust battery management controls that prevent abuse-induced runaway even in the face of multiple system failures. This focused strategy has made the likelihood of occurrence of such an event highly improbable. b. The evaluation shall include all necessary analysis and test to quantify the severity (consequence) of the event in the intended application and environment as well as to identify design modifications to the battery or the system that could appreciably reduce that severity. In addition to prevention protocols, programs developing battery designs with
Fluctuation Relations for Currents
Sinitsyn, Nikolai; Akimov, Alexei; Chernyak, Vladimir; Chertkov, Michael
2011-03-01
We consider a non-equilibrium statistical system on a graph or a network. Identical particles are injected, interact with each other, traverse, and leave the graph in a stochastic manner described in terms of Poisson rates, possibly strongly dependent on time and instantaneous occupation numbers at the nodes of the graph. We show that the system demonstrates a profound statistical symmetry, leading to new Fluctuation Relations that originate from the supersymmetry and the principle of the geometric universality of currents rather than from the relations between probabilities of forward and reverse trajectories. NSF/ECCS-0925618, NSF/CHE-0808910 and DOE at LANL under Contract No. DE-AC52-06NA25396.
Non-equilibrium fluctuation-induced interactions
Dean, David S
2012-01-01
We discuss non-equilibrium aspects of fluctuation-induced interactions. While the equilibrium behavior of such interactions has been extensively studied and is relatively well understood, the study of these interactions out of equilibrium is relatively new. We discuss recent results on the non-equilibrium behavior of systems whose dynamics is of the dissipative stochastic type and identify a number of outstanding problems concerning non-equilibrium fluctuation-induced interactions.
Stochastic quantization of instantons
Grandati, Y.; Berard, A.; Grange, P.
1996-01-01
The method of Parisi and Wu to quantize classical fields is applied to instanton solutions var-phi I of euclidian non-linear theory in one dimension. The solution var-phi var-epsilon of the corresponding Langevin equation is built through a singular perturbative expansion in var-epsilon=h 1/2 in the frame of the center of the mass of the instanton, where the difference var-phi var-epsilon -var-phi I carries only fluctuations of the instanton form. The relevance of the method is shown for the stochastic K dV equation with uniform noise in space: the exact solution usually obtained by the inverse scattering method is retrieved easily by the singular expansion. A general diagrammatic representation of the solution is then established which makes a thorough use of regrouping properties of stochastic diagrams derived in scalar field theory. Averaging over the noise and in the limit of infinite stochastic time, the authors obtain explicit expressions for the first two orders in var-epsilon of the pertrubed instanton of its Green function. Specializing to the Sine-Gordon and var-phi 4 models, the first anaharmonic correction is obtained analytically. The calculation is carried to second order for the var-phi 4 model, showing good convergence. 21 refs., 5 fig
G. Natale
2013-03-01
Full Text Available Formation, aggregation and transmission of abnormal proteins are common features in neurodegenerative disorders including Parkinson’s disease, Alzheimer’s disease, amyotrophic lateral sclerosis, and Huntington’s disease. The mechanisms underlying protein alterations in neurodegenerative diseases remain controversial. Novel findings highlighted altered protein clearing systems as common biochemical pathways which generate protein misfolding, which in turn causes protein aggregation and protein spreading. In fact, proteinaceous aggregates are prone to cell-to-cell propagation. This is reminiscent of what happens in prion disorders, where the prion protein misfolds thus forming aggregates which spread to neighbouring cells. For this reason, the term prionoids is currently used to emphasize how several misfolded proteins are transmitted in neurodegenerative diseases following this prion-like pattern. Histochemical techniques including the use of specific antibodies covering both light and electron microscopy offer a powerful tool to describe these phenomena and investigate specific molecular steps. These include: prion like protein alterations; glycation of prion-like altered proteins to form advanced glycation end-products (AGEs; mechanisms of extracellular secretion; interaction of AGEs with specific receptors placed on neighbouring cells (RAGEs. The present manuscript comments on these phenomena aimed to provide a consistent scenario of the available histochemical approaches to dissect each specific step.
Wiley, Christopher D; Flynn, James M; Morrissey, Christapher; Lebofsky, Ronald; Shuga, Joe; Dong, Xiao; Unger, Marc A; Vijg, Jan; Melov, Simon; Campisi, Judith
2017-10-01
Senescent cells play important roles in both physiological and pathological processes, including cancer and aging. In all cases, however, senescent cells comprise only a small fraction of tissues. Senescent phenotypes have been studied largely in relatively homogeneous populations of cultured cells. In vivo, senescent cells are generally identified by a small number of markers, but whether and how these markers vary among individual cells is unknown. We therefore utilized a combination of single-cell isolation and a nanofluidic PCR platform to determine the contributions of individual cells to the overall gene expression profile of senescent human fibroblast populations. Individual senescent cells were surprisingly heterogeneous in their gene expression signatures. This cell-to-cell variability resulted in a loss of correlation among the expression of several senescence-associated genes. Many genes encoding senescence-associated secretory phenotype (SASP) factors, a major contributor to the effects of senescent cells in vivo, showed marked variability with a subset of highly induced genes accounting for the increases observed at the population level. Inflammatory genes in clustered genomic loci showed a greater correlation with senescence compared to nonclustered loci, suggesting that these genes are coregulated by genomic location. Together, these data offer new insights into how genes are regulated in senescent cells and suggest that single markers are inadequate to identify senescent cells in vivo. © 2017 The Authors. Aging Cell published by the Anatomical Society and John Wiley & Sons Ltd.
Spreading of a prion domain from cell-to-cell by vesicular transport in Caenorhabditis elegans.
Carmen I Nussbaum-Krammer
2013-03-01
Full Text Available Prion proteins can adopt self-propagating alternative conformations that account for the infectious nature of transmissible spongiform encephalopathies (TSEs and the epigenetic inheritance of certain traits in yeast. Recent evidence suggests a similar propagation of misfolded proteins in the spreading of pathology of neurodegenerative diseases including Alzheimer's or Parkinson's disease. Currently there is only a limited number of animal model systems available to study the mechanisms that underlie the cell-to-cell transmission of aggregation-prone proteins. Here, we have established a new metazoan model in Caenorhabditis elegans expressing the prion domain NM of the cytosolic yeast prion protein Sup35, in which aggregation and toxicity are dependent upon the length of oligopeptide repeats in the glutamine/asparagine (Q/N-rich N-terminus. NM forms multiple classes of highly toxic aggregate species and co-localizes to autophagy-related vesicles that transport the prion domain from the site of expression to adjacent tissues. This is associated with a profound cell autonomous and cell non-autonomous disruption of mitochondrial integrity, embryonic and larval arrest, developmental delay, widespread tissue defects, and loss of organismal proteostasis. Our results reveal that the Sup35 prion domain exhibits prion-like properties when expressed in the multicellular organism C. elegans and adapts to different requirements for propagation that involve the autophagy-lysosome pathway to transmit cytosolic aggregation-prone proteins between tissues.
Harnessing cell-to-cell variations to probe bacterial structure and biophysics
Cass, Julie A.
Advances in microscopy and biotechnology have given us novel insights into cellular biology and physics. While bacteria were long considered to be relatively unstructured, the development of fluorescence microscopy techniques, and spatially and temporally resolved high-throughput quantitative studies, have uncovered that the bacterial cell is highly organized, and its structure rigorously maintained. In this thesis I will describe our gateTool software, designed to harness cell-to-cell variations to probe bacterial structure, and discuss two exciting aspects of structure that we have employed gateTool to investigate: (i) chromosome organization and the cellular mechanisms for controlling DNA dynamics, and (ii) the study of cell wall synthesis, and how the genes in the synthesis pathway impact cellular shape. In the first project, we develop a spatial and temporal mapping of cell-cycle-dependent chromosomal organization, and use this quantitative map to discover that chromosomal loci segregate from midcell with universal dynamics. In the second project, I describe preliminary time- lapse and snapshot imaging analysis suggesting phentoypical coherence across peptidoglycan synthesis pathways.
6K2-induced vesicles can move cell to cell during turnip mosaic virus infection
Romain eGrangeon
2013-12-01
Full Text Available To successfully infect plants, viruses replicate in an initially infected cell and then move to neighboring cells through plasmodesmata (PDs. However, the nature of the viral entity that crosses over the cell barrier into non-infected ones is not clear. The membrane-associated 6K2 protein of turnip mosaic virus (TuMV induces the formation of vesicles involved in the replication and intracellular movement of viral RNA. This study shows that 6K2-induced vesicles trafficked towards the plasma membrane and were associated with plasmodesmata (PD. We demonstrated also that 6K2 moved cell-to-cell into adjoining cells when plants were infected with TuMV. 6K2 was then fused to photo-activable GFP (6K2:PAGFP to visualize how 6K2 move intercellularly during TuMV infection. After activation, 6K2:PAGFP-tagged vesicles moved to the cell periphery and across the cell wall into adjacent cells. These vesicles were shown to contain the viral RNA-dependent RNA polymerase and viral RNA. Symplasmic movement of TuMV may thus be achieved in the form of a membrane-associated viral RNA complex induced by 6K2.
Stochastic gene expression in Arabidopsis thaliana.
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.
Perturbation theory for continuous stochastic equations
Chechetkin, V.R.; Lutovinov, V.S.
1987-01-01
The various general perturbational schemes for continuous stochastic equations are considered. These schemes have many analogous features with the iterational solution of Schwinger equation for S-matrix. The following problems are discussed: continuous stochastic evolution equations for probability distribution functionals, evolution equations for equal time correlators, perturbation theory for Gaussian and Poissonian additive noise, perturbation theory for birth and death processes, stochastic properties of systems with multiplicative noise. The general results are illustrated by diffusion-controlled reactions, fluctuations in closed systems with chemical processes, propagation of waves in random media in parabolic equation approximation, and non-equilibrium phase transitions in systems with Poissonian breeding centers. The rate of irreversible reaction X + X → A (Smoluchowski process) is calculated with the use of general theory based on continuous stochastic equations for birth and death processes. The threshold criterion and range of fluctuational region for synergetic phase transition in system with Poissonian breeding centers are also considered. (author)
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...
Estrada, Javier; Andrew, Natalie; Gibson, Daniel; Chang, Frederick; Gnad, Florian; Gunawardena, Jeremy
2016-07-01
The molecular complexity within a cell may be seen as an evolutionary response to the external complexity of the cell's environment. This suggests that the external environment may be harnessed to interrogate the cell's internal molecular architecture. Cells, however, are not only nonlinear and non-stationary, but also exhibit heterogeneous responses within a clonal, isogenic population. In effect, each cell undertakes its own experiment. Here, we develop a method of cellular interrogation using programmable microfluidic devices which exploits the additional information present in cell-to-cell variation, without requiring model parameters to be fitted to data. We focussed on Ca2+ signalling in response to hormone stimulation, which exhibits oscillatory spiking in many cell types and chose eight models of Ca2+ signalling networks which exhibit similar behaviour in simulation. We developed a nonlinear frequency analysis for non-stationary responses, which could classify models into groups under parameter variation, but found that this question alone was unable to distinguish critical feedback loops. We further developed a nonlinear amplitude analysis and found that the combination of both questions ruled out six of the models as inconsistent with the experimentally-observed dynamics and heterogeneity. The two models that survived the double interrogation were mathematically different but schematically identical and yielded the same unexpected predictions that we confirmed experimentally. Further analysis showed that subtle mathematical details can markedly influence non-stationary responses under parameter variation, emphasising the difficulty of finding a "correct" model. By developing questions for the pathway being studied, and designing more versatile microfluidics, cellular interrogation holds promise as a systematic strategy that can complement direct intervention by genetics or pharmacology.
Mastoparan-Induced Intracellular Ca2+ Fluxes May Regulate Cell-to-Cell Communication in Plants.
Tucker, E. B.; Boss, W. F.
1996-06-01
The relationship of Ca2+ and plasmodesmatal closure was examined in staminal hairs of Setcreasea purpurea by microinjecting cells with active mastoparan (Mas-7), inactive mastoparan (Mas-17), active inositol-1,4,5-trisphosphate (IP3), or inactive IP3. Calcium green dextran 10,000 was used to study cellular free Ca2+, and carboxyfluorescein was used to monitor plasmodesmatal closure. When Mas-7 was microinjected into the cytoplasm of cell 1 (the tip cell of a chain of cells), a rapid increase in calcium green dextran-10,000 fluorescence was observed in the cytoplasmic areas on both sides of the plasmodesmata connecting cells 1 and 2 during the same time that the diffusion of carboxyfluorescein through them was blocked. The inhibition of cell-to-cell diffusion was transient, and the closed plasmodesmata reopened within 30 s. The elevated Ca2+ level near plasmodesmata was also transient and returned to base level in about 1.5 min. The transient increase in Ca2+, once initiated in cell 1, repeated with an oscillatory period of 3 min. Elevated Ca2+ and oscillations of Ca2+ were also observed near interconnecting cell walls throughout the chain of cells, indicating that the signal had been transmitted. Previously, we reported that IP3 closed plasmodesmata; now we report that it stimulated Ca2+ and oscillations similar to Mas-7. The effect was specific for similar concentrations of Mas-7 over Mas-17 and active IP3 over inactive IP3. It is important that the Ca2+ channel blocker La3+ eliminated the responses from Mas-7 and IP3, indicating that an influx of Ca2+ was required. These results support the contention that plasmodesmata functioning is regulated via Ca2+ and that IP3 may be an intermediary between the stimulus and Ca2+ elevations.
Mikaël Boullé
2016-11-01
Full Text Available Cell-to-cell spread of HIV, a directed mode of viral transmission, has been observed to be more rapid than cell-free infection. However, a mechanism for earlier onset of viral gene expression in cell-to-cell spread was previously uncharacterized. Here we used time-lapse microscopy combined with automated image analysis to quantify the timing of the onset of HIV gene expression in a fluorescent reporter cell line, as well as single cell staining for infection over time in primary cells. We compared cell-to-cell spread of HIV to cell-free infection, and limited both types of transmission to a two-hour window to minimize differences due to virus transit time to the cell. The mean time to detectable onset of viral gene expression in cell-to-cell spread was accelerated by 19% in the reporter cell line and by 35% in peripheral blood mononuclear cells relative to cell-free HIV infection. Neither factors secreted by infected cells, nor contact with infected cells in the absence of transmission, detectably changed onset. We recapitulated the earlier onset by infecting with multiple cell-free viruses per cell. Surprisingly, the acceleration in onset of viral gene expression was not explained by cooperativity between infecting virions. Instead, more rapid onset was consistent with a model where the fastest expressing virus out of the infecting virus pool sets the time for infection independently of the other co-infecting viruses.
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
Cell-to-Cell Communication Circuits: Quantitative Analysis of Synthetic Logic Gates
Hoffman-Sommer, Marta; Supady, Adriana; Klipp, Edda
2012-01-01
One of the goals in the field of synthetic biology is the construction of cellular computation devices that could function in a manner similar to electronic circuits. To this end, attempts are made to create biological systems that function as logic gates. In this work we present a theoretical quantitative analysis of a synthetic cellular logic-gates system, which has been implemented in cells of the yeast Saccharomyces cerevisiae (Regot et al., 2011). It exploits endogenous MAP kinase signaling pathways. The novelty of the system lies in the compartmentalization of the circuit where all basic logic gates are implemented in independent single cells that can then be cultured together to perform complex logic functions. We have constructed kinetic models of the multicellular IDENTITY, NOT, OR, and IMPLIES logic gates, using both deterministic and stochastic frameworks. All necessary model parameters are taken from literature or estimated based on published kinetic data, in such a way that the resulting models correctly capture important dynamic features of the included mitogen-activated protein kinase pathways. We analyze the models in terms of parameter sensitivity and we discuss possible ways of optimizing the system, e.g., by tuning the culture density. We apply a stochastic modeling approach, which simulates the behavior of whole populations of cells and allows us to investigate the noise generated in the system; we find that the gene expression units are the major sources of noise. Finally, the model is used for the design of system modifications: we show how the current system could be transformed to operate on three discrete values. PMID:22934039
Bierkens, M.F.P.; Bron, W.A.; Knotters, M.
2002-01-01
A description is given of the program VIDENTE. VIDENTE contains a decision support system to choose between different models for stochastic modelling of water-table depths and a graphical user interface to facilitate operating and running four implemented models: KALMAX, KALTFN, SSD and EMERALD. In
Sensory optimization by stochastic tuning.
Jurica, Peter; Gepshtein, Sergei; Tyukin, Ivan; van Leeuwen, Cees
2013-10-01
Individually, visual neurons are each selective for several aspects of stimulation, such as stimulus location, frequency content, and speed. Collectively, the neurons implement the visual system's preferential sensitivity to some stimuli over others, manifested in behavioral sensitivity functions. We ask how the individual neurons are coordinated to optimize visual sensitivity. We model synaptic plasticity in a generic neural circuit and find that stochastic changes in strengths of synaptic connections entail fluctuations in parameters of neural receptive fields. The fluctuations correlate with uncertainty of sensory measurement in individual neurons: The higher the uncertainty the larger the amplitude of fluctuation. We show that this simple relationship is sufficient for the stochastic fluctuations to steer sensitivities of neurons toward a characteristic distribution, from which follows a sensitivity function observed in human psychophysics and which is predicted by a theory of optimal allocation of receptive fields. The optimal allocation arises in our simulations without supervision or feedback about system performance and independently of coupling between neurons, making the system highly adaptive and sensitive to prevailing stimulation. PsycINFO Database Record (c) 2013 APA, all rights reserved.
Fluctuating hyperfine interactions: computational implementation
Zacate, M. O.; Evenson, W. E.
2010-01-01
A library of computational routines has been created to assist in the analysis of stochastic models of hyperfine interactions. We call this library the stochastic hyperfine interactions modeling library (SHIML). It provides routines written in the C programming language that (1) read a text description of a model for fluctuating hyperfine fields, (2) set up the Blume matrix, upon which the evolution operator of the system depends, and (3) find the eigenvalues and eigenvectors of the Blume matrix so that theoretical spectra of experimental hyperfine interaction measurements can be calculated. Example model calculations are included in the SHIML package to illustrate its use and to generate perturbed angular correlation spectra for the special case of polycrystalline samples when anisotropy terms of higher order than A 22 can be neglected.
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
Reliability-based Dynamic Network Design with Stochastic Networks
Li, H.
2009-01-01
Transportation systems are stochastic and dynamic systems. The road capacities and the travel demand are fluctuating from time to time within a day and at the same time from day to day. For road users, the travel time and travel costs experienced over time and space are stochastic, thus desire
Laboratory Evidence for Stochastic Plasma-Wave Growth
Austin, D. R.; Hole, M. J.; Robinson, P. A.; Cairns, Iver H.; Dallaqua, R.
2007-01-01
The first laboratory confirmation of stochastic growth theory is reported. Floating potential fluctuations are measured in a vacuum arc centrifuge using a Langmuir probe. Statistical analysis of the energy density reveals a lognormal distribution over roughly 2 orders of magnitude, with a high-field nonlinear cutoff whose spatial dependence is consistent with the predicted eigenmode profile. These results are consistent with stochastic growth and nonlinear saturation of a spatially extended eigenmode, the first evidence for stochastic growth of an extended structure
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.
Stochastic Gravity: Theory and Applications
Hu Bei Lok
2004-01-01
Full Text Available Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein-Langevin equation, which has in addition sources due to the noise kernel. The noise kernel is the vacuum expectation value of the (operator-valued stress-energy bi-tensor which describes the fluctuations of quantum matter fields in curved spacetimes. In the first part, we describe the fundamentals of this new theory via two approaches: the axiomatic and the functional. The axiomatic approach is useful to see the structure of the theory from the framework of semiclassical gravity, showing the link from the mean value of the stress-energy tensor to their correlation functions. The functional approach uses the Feynman-Vernon influence functional and the Schwinger-Keldysh closed-time-path effective action methods which are convenient for computations. It also brings out the open systems concepts and the statistical and stochastic contents of the theory such as dissipation, fluctuations, noise, and decoherence. We then focus on the properties of the stress-energy bi-tensor. We obtain a general expression for the noise kernel of a quantum field defined at two distinct points in an arbitrary curved spacetime as products of covariant derivatives of the quantum field's Green function. In the second part, we describe three applications of stochastic gravity theory. First, we consider metric perturbations in a Minkowski spacetime. We offer an analytical solution of the Einstein-Langevin equation and compute the two-point correlation functions for the linearized Einstein tensor and for the metric perturbations. Second, we discuss structure formation from the stochastic gravity viewpoint, which can go beyond the standard treatment by incorporating the full quantum effect of the inflaton fluctuations. Third, we discuss the backreaction
Changes in atomic populations due to edge plasma fluctuations
Hammami, R., E-mail: ramzi.hammami@univ-provence.fr [PIIM, Aix-Marseille Université and CNRS, centre Saint Jérôme, Marseille 13397 (France); Capes, H. [PIIM, Aix-Marseille Université and CNRS, centre Saint Jérôme, Marseille 13397 (France); Catoire, F. [CELIA, Université de Bordeaux 1 and CNRS, Domaine du Haut Carré, Talence 33405 (France); Godbert-Mouret, L.; Koubiti, M.; Marandet, Y.; Mekkaoui, A.; Rosato, J.; Stamm, R. [PIIM, Aix-Marseille Université and CNRS, centre Saint Jérôme, Marseille 13397 (France)
2013-07-15
The population balance of atoms or ions in an edge plasma is calculated in the presence of fluctuating density or temperature. We have used a stochastic model taking advantage of the knowledge of the plasma parameter statistical properties, and assuming a stepwise constant stochastic process for the fluctuating variable. The model is applied to simplified atomic systems such as three level hydrogen atoms or the ionization balance of carbon affected by electronic temperature or density fluctuations obeying a gamma PDF, and an exponential waiting time distribution.
Influence of thermal fluctuations on ligament break-up: a fluctuating lattice Boltzmann study
Xue, Xiao; Biferale, Luca; Sbragaglia, Mauro; Toschi, Federico
2017-11-01
Thermal fluctuations are essential ingredients in a nanoscale system, driving Brownian motion of particles and capillary waves at non-ideal interfaces. Here we study the influence of thermal fluctuations on the breakup of liquid ligaments at the nanoscale. We offer quantitative characterization of the effects of thermal fluctuations on the Plateau-Rayleigh mechanism that drives the breakup process of ligaments. Due to thermal fluctuations, the droplet sizes after break-up need to be analyzed in terms of their distribution over an ensemble made of repeated experiments. To this aim, we make use of numerical simulations based on the fluctuating lattice Boltzmann method (FLBM) for multicomponent mixtures. The method allows an accurate and efficient simulation of the fluctuating hydrodynamics equations of a binary mixture, where both stochastic viscous stresses and diffusion fluxes are introduced. This project has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No 642069.
Stochastic Gravity: Theory and Applications
Hu Bei Lok
2008-05-01
Full Text Available Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein–Langevin equation, which has, in addition, sources due to the noise kernel. The noise kernel is the vacuum expectation value of the (operator-valued stress-energy bitensor, which describes the fluctuations of quantum-matter fields in curved spacetimes. A new improved criterion for the validity of semiclassical gravity may also be formulated from the viewpoint of this theory. In the first part of this review we describe the fundamentals of this new theory via two approaches: the axiomatic and the functional. The axiomatic approach is useful to see the structure of the theory from the framework of semiclassical gravity, showing the link from the mean value of the stress-energy tensor to the correlation functions. The functional approach uses the Feynman–Vernon influence functional and the Schwinger–Keldysh closed-time-path effective action methods. In the second part, we describe three applications of stochastic gravity. First, we consider metric perturbations in a Minkowski spacetime, compute the two-point correlation functions of these perturbations and prove that Minkowski spacetime is a stable solution of semiclassical gravity. Second, we discuss structure formation from the stochastic-gravity viewpoint, which can go beyond the standard treatment by incorporating the full quantum effect of the inflaton fluctuations. Third, using the Einstein–Langevin equation, we discuss the backreaction of Hawking radiation and the behavior of metric fluctuations for both the quasi-equilibrium condition of a black-hole in a box and the fully nonequilibrium condition of an evaporating black hole spacetime. Finally, we briefly discuss the theoretical structure of stochastic gravity in relation to quantum gravity and point out
Hydrodynamical fluctuations in smooth shear flows
Chagelishvili, G.D.; Khujadze, G.R.; Lominadze, J.G.
1999-11-01
Background of hydrodynamical fluctuations in a intrinsically/stochastically forced, laminar, uniform shear flow is studied. The employment of so-called nonmodal mathematical analysis makes it possible to represent the background of fluctuations in a new light and to get more insight into the physics of its formation. The basic physical processes responsible for the formation of vortex and acoustic wave fluctuation backgrounds are analyzed. Interplay of the processes at low and moderate shear rates is described. Three-dimensional vortex fluctuations around a given macroscopic state are numerically calculated. The correlation functions of the fluctuations of physical quantities are analyzed. It is shown that there exists subspace D k in the wave-number space (k-space) that is limited externally by spherical surface with radius k ν ≡ A/ν (where A is the velocity shear parameter, ν - the kinematic viscosity) in the nonequilibrium open system under study. The spatial Fourier harmonics of vortex as well as acoustic wave fluctuations are strongly subjected by flow shear (by the open character of the system) at wave-numbers satisfying the condition k ν . Specifically it is shown that in D k : The fluctuations are non-Markovian; the spatial spectral density of energy of the vortex fluctuations by far exceeds the white-noise; the term of a new type associated to the hydrodynamical fluctuation of velocity appears in the correlation function of pressure; the fluctuation background of the acoustic waves is completely different at low and moderate shear rates (at low shear rates it is reduced in D k in comparison to the uniform (non-shear) flow; at moderate shear rates it it comparable to the background of the vortex fluctuations). The fluctuation background of both the vortex and the acoustic wave modes is anisotropic. The possible significance of the fluctuation background of vortices for the subcritical transition to turbulence and Brownian motion of small macroscopic
Radiation-induced perturbation of cell-to-cell signalling and communication
Mariotti, L.; Facoetti, A.; Bertolotti, A.; Ranza, E.; Alloni, D.; Ottolenghi, A.
2011-01-01
The investigation of the bystander phenomena (i.e. the induction of damage in cells not directly traversed by radiation) is strictly related to the study of the mechanisms of intercellular communication and of the perturbative effects of radiation. A new possible way to try to solve the bystander puzzle is through a 'systems radiation biology' approach with the total integration of experimental and theoretical activities. In particular, this contribution will focus on: (1) 'ad hoc' experiments designed to quantify key parameters involved in intercellular signalling (focusing, as a pilot study, on release, decay and internalization of interleukin-6 molecules, their modulation by radiation, and possible differences between in vivo/in vitro behaviour); (2) the implementation and the development of two different modelling approaches: a stochastic model (based on a Monte Carlo code) that takes account of the local mechanisms of release and internalization of signalling molecules (e.g. cytokines) and an analytical model where signal molecules are treated as a population and their temporal behaviour is described by differential equations. This approach provided instruments to investigate the complex phenomena of signal transmission and the role of cell communication to guarantee (maintain) the robustness of the in vitro experimental systems against the effects of perturbations. (authors)
Parallel arrangements of positive feedback loops limit cell-to-cell variability in differentiation.
Anupam Dey
Full Text Available Cellular differentiations are often regulated by bistable switches resulting from specific arrangements of multiple positive feedback loops (PFL fused to one another. Although bistability generates digital responses at the cellular level, stochasticity in chemical reactions causes population heterogeneity in terms of its differentiated states. We hypothesized that the specific arrangements of PFLs may have evolved to minimize the cellular heterogeneity in differentiation. In order to test this we investigated variability in cellular differentiation controlled either by parallel or serial arrangements of multiple PFLs having similar average properties under extrinsic and intrinsic noises. We find that motifs with PFLs fused in parallel to one another around a central regulator are less susceptible to noise as compared to the motifs with PFLs arranged serially. Our calculations suggest that the increased resistance to noise in parallel motifs originate from the less sensitivity of bifurcation points to the extrinsic noise. Whereas estimation of mean residence times indicate that stable branches of bifurcations are robust to intrinsic noise in parallel motifs as compared to serial motifs. Model conclusions are consistent both in AND- and OR-gate input signal configurations and also with two different modeling strategies. Our investigations provide some insight into recent findings that differentiation of preadipocyte to mature adipocyte is controlled by network of parallel PFLs.
Parallel arrangements of positive feedback loops limit cell-to-cell variability in differentiation.
Dey, Anupam; Barik, Debashis
2017-01-01
Cellular differentiations are often regulated by bistable switches resulting from specific arrangements of multiple positive feedback loops (PFL) fused to one another. Although bistability generates digital responses at the cellular level, stochasticity in chemical reactions causes population heterogeneity in terms of its differentiated states. We hypothesized that the specific arrangements of PFLs may have evolved to minimize the cellular heterogeneity in differentiation. In order to test this we investigated variability in cellular differentiation controlled either by parallel or serial arrangements of multiple PFLs having similar average properties under extrinsic and intrinsic noises. We find that motifs with PFLs fused in parallel to one another around a central regulator are less susceptible to noise as compared to the motifs with PFLs arranged serially. Our calculations suggest that the increased resistance to noise in parallel motifs originate from the less sensitivity of bifurcation points to the extrinsic noise. Whereas estimation of mean residence times indicate that stable branches of bifurcations are robust to intrinsic noise in parallel motifs as compared to serial motifs. Model conclusions are consistent both in AND- and OR-gate input signal configurations and also with two different modeling strategies. Our investigations provide some insight into recent findings that differentiation of preadipocyte to mature adipocyte is controlled by network of parallel PFLs.
Safranyos, Richard G. A.; Caveney, Stanley; Miller, James G.; Petersen, Nils O.
1987-04-01
Intercellular (tissue) diffusion of molecules requires cytoplasmic diffusion and diffusion through gap junctional (or cell-to-cell) channels. The rates of tissue and cytoplasmic diffusion of fluorescent tracers, expressed as an effective diffusion coefficient, De, and a cytoplasmic diffusion coefficient, Dcyt, have been measured among the developing epidermal cells of a larval beetle, Tenebrio molitor L., to determine the contribution of the junctional channels to intercellular diffusion. Tracer diffusion was measured by injecting fluorescent tracers into cells and quantitating the rate of subsequent spread into adjacent cells. Cytoplasmic diffusion was determined by fluorescence photobleaching. These experiments show that gap junctional channels constitute approximately 70-80% of the total cell-to-cell resistance to the diffusion of organic tracers at high concentrations in this tissue. At low concentrations, however, the binding of tracer to cytoplasm slows down the cytoplasmic diffusion, which may limit intercellular diffusion.
Tiwari, Vaibhav [Department of Ophthalmology, University of Illinois at Chicago, Chicago, IL 60612 (United States); Department of Microbiology and Immunology, University of Illinois at Chicago, Chicago, IL 60612 (United States); Department of Basic Medical Sciences, College of Osteopathic Medicine of the Pacific and College of Optometry, Western University of Health Sciences, Pomona, CA 91766 (United States); Darmani, Nissar A.; Thrush, Gerald R. [Department of Basic Medical Sciences, College of Osteopathic Medicine of the Pacific and College of Optometry, Western University of Health Sciences, Pomona, CA 91766 (United States); Shukla, Deepak, E-mail: dshukla@uic.edu [Department of Ophthalmology, University of Illinois at Chicago, Chicago, IL 60612 (United States); Department of Microbiology and Immunology, University of Illinois at Chicago, Chicago, IL 60612 (United States)
2009-12-18
Human herpesvirus-8 (HHV-8) is known to interact with cell surface heparan sulfate (HS) for entry into a target cell. Here we investigated the role of HS during HHV-8 glycoproteins-induced cell fusion. Interestingly, the observed fusion demonstrated an unusual dependence on HS as evident from following lines of evidence: (1) a significant reduction in cell-to-cell fusion occurred when target cells were treated with heparinase; (2) in a competition assay, when the effector cells expressing HHV-8 glycoproteins were challenged with soluble HS, cell-to-cell fusion was reduced; and, (3) co-expression of HHV-8 glycoproteins gH-gL on target cells resulted in inhibition of cell surface HS expression. Taken together, our results indicate that cell surface HS can play an additional role during HHV-8 pathogenesis.
Martínez-Gil, Luis; Sánchez-Navarro, Jesús A; Cruz, Antonio; Pallás, Vicente; Pérez-Gil, Jesús; Mingarro, Ismael
2009-06-01
The cell-to-cell transport of plant viruses depends on one or more virus-encoded movement proteins (MPs). Some MPs are integral membrane proteins that interact with the membrane of the endoplasmic reticulum, but a detailed understanding of the interaction between MPs and biological membranes has been lacking. The cell-to-cell movement of the Prunus necrotic ringspot virus (PNRSV) is facilitated by a single MP of the 30K superfamily. Here, using a myriad of biochemical and biophysical approaches, we show that the PNRSV MP contains only one hydrophobic region (HR) that interacts with the membrane interface, as opposed to being a transmembrane protein. We also show that a proline residue located in the middle of the HR constrains the structural conformation of this region at the membrane interface, and its replacement precludes virus movement.
Martínez-Gil, Luis; Sánchez-Navarro, Jesús A.; Cruz, Antonio; Pallás, Vicente; Pérez-Gil, Jesús; Mingarro, Ismael
2009-01-01
The cell-to-cell transport of plant viruses depends on one or more virus-encoded movement proteins (MPs). Some MPs are integral membrane proteins that interact with the membrane of the endoplasmic reticulum, but a detailed understanding of the interaction between MPs and biological membranes has been lacking. The cell-to-cell movement of the Prunus necrotic ringspot virus (PNRSV) is facilitated by a single MP of the 30K superfamily. Here, using a myriad of biochemical and biophysical approaches, we show that the PNRSV MP contains only one hydrophobic region (HR) that interacts with the membrane interface, as opposed to being a transmembrane protein. We also show that a proline residue located in the middle of the HR constrains the structural conformation of this region at the membrane interface, and its replacement precludes virus movement. PMID:19321624
Tiwari, Vaibhav; Darmani, Nissar A.; Thrush, Gerald R.; Shukla, Deepak
2009-01-01
Human herpes virus 8 (HHV-8) is known to interact with cell surface heparan sulfate (HS) for entry into a target cell. Here we investigated the role of HS during HHV-8 glycoproteins induced cell fusion. Interestingly, the observed fusion demonstrated an unusual dependence on HS as evident from following lines of evidence: 1) a significant reduction in cell-to-cell fusion occurred when target cells were treated with heparinase; 2) in a competition assay, when the effector cells expressing HHV-8 glycoproteins were challenged with soluble HS, cell-to-cell fusion was reduced; and, 3) coexpression of HHV-8 glycoproteins gH-gL on target cells resulted in inhibition of cell surface HS expression. Taken together, our results indicate that cell surface HS can play an additional role during HHV-8 pathogenesis. PMID:19747451
Tiwari, Vaibhav; Darmani, Nissar A.; Thrush, Gerald R.; Shukla, Deepak
2009-01-01
Human herpesvirus-8 (HHV-8) is known to interact with cell surface heparan sulfate (HS) for entry into a target cell. Here we investigated the role of HS during HHV-8 glycoproteins-induced cell fusion. Interestingly, the observed fusion demonstrated an unusual dependence on HS as evident from following lines of evidence: (1) a significant reduction in cell-to-cell fusion occurred when target cells were treated with heparinase; (2) in a competition assay, when the effector cells expressing HHV-8 glycoproteins were challenged with soluble HS, cell-to-cell fusion was reduced; and, (3) co-expression of HHV-8 glycoproteins gH-gL on target cells resulted in inhibition of cell surface HS expression. Taken together, our results indicate that cell surface HS can play an additional role during HHV-8 pathogenesis.
The HSV-1 mechanisms of cell-to-cell spread and fusion are critically dependent on host PTP1B.
Jillian C Carmichael
2018-05-01
Full Text Available All herpesviruses have mechanisms for passing through cell junctions, which exclude neutralizing antibodies and offer a clear path to neighboring, uninfected cells. In the case of herpes simplex virus type 1 (HSV-1, direct cell-to-cell transmission takes place between epithelial cells and sensory neurons, where latency is established. The spreading mechanism is poorly understood, but mutations in four different HSV-1 genes can dysregulate it, causing neighboring cells to fuse to produce syncytia. Because the host proteins involved are largely unknown (other than the virus entry receptor, we were intrigued by an earlier discovery that cells infected with wild-type HSV-1 will form syncytia when treated with salubrinal. A biotinylated derivative of this drug was used to pull down cellular complexes, which were analyzed by mass spectrometry. One candidate was a protein tyrosine phosphatase (PTP1B, and although it ultimately proved not to be the target of salubrinal, it was found to be critical for the mechanism of cell-to-cell spread. In particular, a highly specific inhibitor of PTP1B (CAS 765317-72-4 blocked salubrinal-induced fusion, and by itself resulted in a dramatic reduction in the ability of HSV-1 to spread in the presence of neutralizing antibodies. The importance of this phosphatase was confirmed in the absence of drugs by using PTP1B-/- cells. Importantly, replication assays showed that virus titers were unaffected when PTP1B was inhibited or absent. Only cell-to-cell spread was altered. We also examined the effects of salubrinal and the PTP1B inhibitor on the four Syn mutants of HSV-1, and strikingly different responses were found. That is, both drugs individually enhanced fusion for some mutants and reduced fusion for others. PTP1B is the first host factor identified to be specifically required for cell-to-cell spread, and it may be a therapeutic target for preventing HSV-1 reactivation disease.
The HSV-1 mechanisms of cell-to-cell spread and fusion are critically dependent on host PTP1B.
Carmichael, Jillian C; Yokota, Hiroki; Craven, Rebecca C; Schmitt, Anthony; Wills, John W
2018-05-01
All herpesviruses have mechanisms for passing through cell junctions, which exclude neutralizing antibodies and offer a clear path to neighboring, uninfected cells. In the case of herpes simplex virus type 1 (HSV-1), direct cell-to-cell transmission takes place between epithelial cells and sensory neurons, where latency is established. The spreading mechanism is poorly understood, but mutations in four different HSV-1 genes can dysregulate it, causing neighboring cells to fuse to produce syncytia. Because the host proteins involved are largely unknown (other than the virus entry receptor), we were intrigued by an earlier discovery that cells infected with wild-type HSV-1 will form syncytia when treated with salubrinal. A biotinylated derivative of this drug was used to pull down cellular complexes, which were analyzed by mass spectrometry. One candidate was a protein tyrosine phosphatase (PTP1B), and although it ultimately proved not to be the target of salubrinal, it was found to be critical for the mechanism of cell-to-cell spread. In particular, a highly specific inhibitor of PTP1B (CAS 765317-72-4) blocked salubrinal-induced fusion, and by itself resulted in a dramatic reduction in the ability of HSV-1 to spread in the presence of neutralizing antibodies. The importance of this phosphatase was confirmed in the absence of drugs by using PTP1B-/- cells. Importantly, replication assays showed that virus titers were unaffected when PTP1B was inhibited or absent. Only cell-to-cell spread was altered. We also examined the effects of salubrinal and the PTP1B inhibitor on the four Syn mutants of HSV-1, and strikingly different responses were found. That is, both drugs individually enhanced fusion for some mutants and reduced fusion for others. PTP1B is the first host factor identified to be specifically required for cell-to-cell spread, and it may be a therapeutic target for preventing HSV-1 reactivation disease.
Clarke, J.
1980-01-01
This paper briefly reviews sources of noise in Josephson junctions, and the limits they impose on the sensitivity of dc and rf SQUIDS. The results are strictly valid only for a resistively shunted junction (RSJ) with zero capacitance, but should be applicable to point contact junctions and microbridges in so far as these devices can be approximated by the RSJ model. Fluctuations arising from Nyquist noise in the resistive shunt of a single junction are discussed in the limit eI/sub o/R/k/sub B/T << 1 in which a classical treatment is appropriate, and then extend the treatment to the limit eI/sub o/R/k/sub B/T greater than or equal to 1 in which quantum effects become important. The Nyquist limit theory is used to calculate the noise in a dc SQUID, and the results are compared with a number of practical devices. The quantum limit is briefly considered. Results for the predicted sensitivity of rf SQUIDS are presented, and also compared with a number of practical devices. Finally, the importance of l/f noise (f is the frequency) in limiting the low frequency performance of SQUIDS is discussed
Tominaga-Wada, Rumi; Wada, Takuji
2018-03-01
An R3-type MYB transcription factor, CAPRICE (CPC), is known to promote root hair cell differentiation in Arabidopsis root epidermis. The CPC protein moves from non-hair cells to the neighboring cells, and acts as an inducer of root hair formation. In contrast, we previously showed that the CPC homolog, ENHANCER OF TRY AND CPC1 (ETC1), does not move between the root epidermal cells. To clarify the critical difference in the cell-to-cell movement ability of CPC and ETC1 proteins, we generated five different chimeras of CPC and ETC1. As expected, four of the five chimeric proteins with substitution of CPC amino acids with those of ETC1 induced many root hair and no-trichome phenotype, like CPC. These chimeric proteins essentially maintained the cell-to-cell movement ability of CPC. However, one chimeric protein in which ETC1 was sandwiched between the CPC-specific movement motifs of S1 and S2 did not induce ectopic root hair formation. This chimeric protein did not move between the cells. These results indicate that the maintenance of not only the S1 and S2 motifs but also the precise structure of CPC protein might be necessary for the cell-to-cell movement of CPC. Our results should help in further unraveling of the roles of these MYB transcription factors in root hair formation. Copyright © 2018 Elsevier Inc. All rights reserved.
Colombino, A.; Mosiello, R.; Norelli, F.; Jorio, V.M.; Pacilio, N.
1975-01-01
A nuclear system kinetics is formulated according to a stochastic approach. The detailed probability balance equations are written for the probability of finding the mixed population of neutrons and detected neutrons, i.e. detectrons, at a given level for a given instant of time. Equations are integrated in search of a probability profile: a series of cases is analyzed through a progressive criterium. It tends to take into account an increasing number of physical processes within the chosen model. The most important contribution is that solutions interpret analytically experimental conditions of equilibrium (moise analysis) and non equilibrium (pulsed neutron measurements, source drop technique, start up procedures)
Romanu Ekaterini
2006-01-01
Full Text Available This article shows the similarities between Claude Debussy’s and Iannis Xenakis’ philosophy of music and work, in particular the formers Jeux and the latter’s Metastasis and the stochastic works succeeding it, which seem to proceed parallel (with no personal contact to what is perceived as the evolution of 20th century Western music. Those two composers observed the dominant (German tradition as outsiders, and negated some of its elements considered as constant or natural by "traditional" innovators (i.e. serialists: the linearity of musical texture, its form and rhythm.
Universality in stochastic exponential growth.
Iyer-Biswas, Srividya; Crooks, Gavin E; Scherer, Norbert F; Dinner, Aaron R
2014-07-11
Recent imaging data for single bacterial cells reveal that their mean sizes grow exponentially in time and that their size distributions collapse to a single curve when rescaled by their means. An analogous result holds for the division-time distributions. A model is needed to delineate the minimal requirements for these scaling behaviors. We formulate a microscopic theory of stochastic exponential growth as a Master Equation that accounts for these observations, in contrast to existing quantitative models of stochastic exponential growth (e.g., the Black-Scholes equation or geometric Brownian motion). Our model, the stochastic Hinshelwood cycle (SHC), is an autocatalytic reaction cycle in which each molecular species catalyzes the production of the next. By finding exact analytical solutions to the SHC and the corresponding first passage time problem, we uncover universal signatures of fluctuations in exponential growth and division. The model makes minimal assumptions, and we describe how more complex reaction networks can reduce to such a cycle. We thus expect similar scalings to be discovered in stochastic processes resulting in exponential growth that appear in diverse contexts such as cosmology, finance, technology, and population growth.
COSMIC DUST AGGREGATION WITH STOCHASTIC CHARGING
Matthews, Lorin S.; Hyde, Truell W.; Shotorban, Babak
2013-01-01
The coagulation of cosmic dust grains is a fundamental process which takes place in astrophysical environments, such as presolar nebulae and circumstellar and protoplanetary disks. Cosmic dust grains can become charged through interaction with their plasma environment or other processes, and the resultant electrostatic force between dust grains can strongly affect their coagulation rate. Since ions and electrons are collected on the surface of the dust grain at random time intervals, the electrical charge of a dust grain experiences stochastic fluctuations. In this study, a set of stochastic differential equations is developed to model these fluctuations over the surface of an irregularly shaped aggregate. Then, employing the data produced, the influence of the charge fluctuations on the coagulation process and the physical characteristics of the aggregates formed is examined. It is shown that dust with small charges (due to the small size of the dust grains or a tenuous plasma environment) is affected most strongly
Evolutionary stability concepts in a stochastic environment
Zheng, Xiu-Deng; Li, Cong; Lessard, Sabin; Tao, Yi
2017-09-01
Over the past 30 years, evolutionary game theory and the concept of an evolutionarily stable strategy have been not only extensively developed and successfully applied to explain the evolution of animal behaviors, but also widely used in economics and social sciences. Nonetheless, the stochastic dynamical properties of evolutionary games in randomly fluctuating environments are still unclear. In this study, we investigate conditions for stochastic local stability of fixation states and constant interior equilibria in a two-phenotype model with random payoffs following pairwise interactions. Based on this model, we develop the concepts of stochastic evolutionary stability (SES) and stochastic convergence stability (SCS). We show that the condition for a pure strategy to be SES and SCS is more stringent than in a constant environment, while the condition for a constant mixed strategy to be SES is less stringent than the condition to be SCS, which is less stringent than the condition in a constant environment.
Stochastic Effects; Application in Nuclear Physics
Mazonka, O.
2000-04-01
Stochastic effects in nuclear physics refer to the study of the dynamics of nuclear systems evolving under stochastic equations of motion. In this dissertation we restrict our attention to classical scattering models. We begin with introduction of the model of nuclear dynamics and deterministic equations of evolution. We apply a Langevin approach - an additional property of the model, which reflect the statistical nature of low energy nuclear behaviour. We than concentrate our attention on the problem of calculating tails of distribution functions, which actually is the problem of calculating probabilities of rare outcomes. Two general strategies are proposed. Result and discussion follow. Finally in the appendix we consider stochastic effects in nonequilibrium systems. A few exactly solvable models are presented. For one model we show explicitly that stochastic behaviour in a microscopic description can lead to ordered collective effects on the macroscopic scale. Two others are solved to confirm the predictions of the fluctuation theorem. (author)
Novikov Engine with Fluctuating Heat Bath Temperature
Schwalbe, Karsten; Hoffmann, Karl Heinz
2018-04-01
The Novikov engine is a model for heat engines that takes the irreversible character of heat fluxes into account. Using this model, the maximum power output as well as the corresponding efficiency of the heat engine can be deduced, leading to the well-known Curzon-Ahlborn efficiency. The classical model assumes constant heat bath temperatures, which is not a reasonable assumption in the case of fluctuating heat sources. Therefore, in this article the influence of stochastic fluctuations of the hot heat bath's temperature on the optimal performance measures is investigated. For this purpose, a Novikov engine with fluctuating heat bath temperature is considered. Doing so, a generalization of the Curzon-Ahlborn efficiency is found. The results can help to quantify how the distribution of fluctuating quantities affects the performance measures of power plants.
Fluctuations, dynamical instabilities and clusterization processes
Burgio, G.F.; Chomaz, Ph.; Randrup, J.
1992-01-01
Recent progress with regard to the numerical simulation of fluctuations in nuclear dynamics is reported. Cluster formation in unstable nuclear matter is studied within the framework of a Boltzmann-Langevin equation developed to describe large amplitude fluctuations. Through the Fourier analysis of the fluctuating nuclear density in coordinate space, the onset of the clusterization is related to the dispersion relation of harmonic density oscillations. This detailed study on the simple two-dimensional case demonstrates the validity of the general approach. It is also shown, how the inclusion of fluctuations implies a description in terms of ensemble of trajectories and it is discussed why the presence of a stochastic term may cure the intrinsic unpredictability of deterministic theories (such as mean-field approximation) in presence of instabilities and/or chaos. (author) 8 refs., 3 figs
Lanchier, Nicolas
2017-01-01
Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes. The first part of the text begins with a brief review of measure theory and revisits the main concepts of probability theory, from random variables to the standard limit theorems. The second part covers traditional material on stochastic processes, including martingales, discrete-time Markov chains, Poisson processes, and continuous-time Markov chains. The theory developed is illustrated by a variety of examples surrounding applications such as the ...
Balachandran, Suchandra; Xiang, Yu; Schobert, Christian; Thompson, Gary A.; Lucas, William J.
1997-01-01
In angiosperms, the functional enucleate sieve tube system of the phloem appears to be maintained by the surrounding companion cells. In this study, we tested the hypothesis that polypeptides present within the phloem sap traffic cell to cell from the companion cells, where they are synthesized, into the sieve tube via plasmodesmata. Coinjection of fluorescently labeled dextrans along with size-fractionated Cucurbita maxima phloem proteins, ranging in size from 10 to 200 kDa, as well as injection of individual fluorescently labeled phloem proteins, provided unambiguous evidence that these proteins have the capacity to interact with mesophyll plasmodesmata in cucurbit cotyledons to induce an increase in size exclusion limit and traffic cell to cell. Plasmodesmal size exclusion limit increased to greater than 20 kDa, but less than 40 kDa, irrespective of the size of the injected protein, indicating that partial protein unfolding may be a requirement for transport. A threshold concentration in the 20–100 nM range was required for cell-to-cell transport indicating that phloem proteins have a high affinity for the mesophyll plasmodesmal binding site(s). Parallel experiments with glutaredoxin and cystatin, phloem sap proteins from Ricinus communis, established that these proteins can also traffic through cucurbit mesophyll plasmodesmata. These results are discussed in terms of the requirements for regulated protein trafficking between companion cells and the sieve tube system. As the threshold value for plasmodesmal transport of phloem sap proteins falls within the same range as many plant hormones, the possibility is discussed that some of these proteins may act as long-distance signaling molecules. PMID:9391168
Balachandran, S; Xiang, Y; Schobert, C; Thompson, G A; Lucas, W J
1997-12-09
In angiosperms, the functional enucleate sieve tube system of the phloem appears to be maintained by the surrounding companion cells. In this study, we tested the hypothesis that polypeptides present within the phloem sap traffic cell to cell from the companion cells, where they are synthesized, into the sieve tube via plasmodesmata. Coinjection of fluorescently labeled dextrans along with size-fractionated Cucurbita maxima phloem proteins, ranging in size from 10 to 200 kDa, as well as injection of individual fluorescently labeled phloem proteins, provided unambiguous evidence that these proteins have the capacity to interact with mesophyll plasmodesmata in cucurbit cotyledons to induce an increase in size exclusion limit and traffic cell to cell. Plasmodesmal size exclusion limit increased to greater than 20 kDa, but less than 40 kDa, irrespective of the size of the injected protein, indicating that partial protein unfolding may be a requirement for transport. A threshold concentration in the 20-100 nM range was required for cell-to-cell transport indicating that phloem proteins have a high affinity for the mesophyll plasmodesmal binding site(s). Parallel experiments with glutaredoxin and cystatin, phloem sap proteins from Ricinus communis, established that these proteins can also traffic through cucurbit mesophyll plasmodesmata. These results are discussed in terms of the requirements for regulated protein trafficking between companion cells and the sieve tube system. As the threshold value for plasmodesmal transport of phloem sap proteins falls within the same range as many plant hormones, the possibility is discussed that some of these proteins may act as long-distance signaling molecules.
Dmitriy Mazurov
2010-02-01
Full Text Available We have developed an efficient method to quantify cell-to-cell infection with single-cycle, replication dependent reporter vectors. This system was used to examine the mechanisms of infection with HTLV-1 and HIV-1 vectors in lymphocyte cell lines. Effector cells transfected with reporter vector, packaging vector, and Env expression plasmid produced virus-like particles that transduced reporter gene activity into cocultured target cells with zero background. Reporter gene expression was detected exclusively in target cells and required an Env-expression plasmid and a viral packaging vector, which provided essential structural and enzymatic proteins for virus replication. Cell-cell fusion did not contribute to infection, as reporter protein was rarely detected in syncytia. Coculture of transfected Jurkat T cells and target Raji/CD4 B cells enhanced HIV-1 infection two fold and HTLV-1 infection ten thousand fold in comparison with cell-free infection of Raji/CD4 cells. Agents that interfere with actin and tubulin polymerization strongly inhibited HTLV-1 and modestly decreased HIV-1 cell-to-cell infection, an indication that cytoskeletal remodeling was more important for HTLV-1 transmission. Time course studies showed that HTLV-1 transmission occurred very rapidly after cell mixing, whereas slower kinetics of HIV-1 coculture infection implies a different mechanism of infectious transmission. HTLV-1 Tax was demonstrated to play an important role in altering cell-cell interactions that enhance virus infection and replication. Interestingly, superantigen-induced synapses between Jurkat cells and Raji/CD4 cells did not enhance infection for either HTLV-1 or HIV-1. In general, the dependence on cell-to-cell infection was determined by the virus, the effector and target cell types, and by the nature of the cell-cell interaction.
Joachim Almquist
Full Text Available The last decade has seen a rapid development of experimental techniques that allow data collection from individual cells. These techniques have enabled the discovery and characterization of variability within a population of genetically identical cells. Nonlinear mixed effects (NLME modeling is an established framework for studying variability between individuals in a population, frequently used in pharmacokinetics and pharmacodynamics, but its potential for studies of cell-to-cell variability in molecular cell biology is yet to be exploited. Here we take advantage of this novel application of NLME modeling to study cell-to-cell variability in the dynamic behavior of the yeast transcription repressor Mig1. In particular, we investigate a recently discovered phenomenon where Mig1 during a short and transient period exits the nucleus when cells experience a shift from high to intermediate levels of extracellular glucose. A phenomenological model based on ordinary differential equations describing the transient dynamics of nuclear Mig1 is introduced, and according to the NLME methodology the parameters of this model are in turn modeled by a multivariate probability distribution. Using time-lapse microscopy data from nearly 200 cells, we estimate this parameter distribution according to the approach of maximizing the population likelihood. Based on the estimated distribution, parameter values for individual cells are furthermore characterized and the resulting Mig1 dynamics are compared to the single cell times-series data. The proposed NLME framework is also compared to the intuitive but limited standard two-stage (STS approach. We demonstrate that the latter may overestimate variabilities by up to almost five fold. Finally, Monte Carlo simulations of the inferred population model are used to predict the distribution of key characteristics of the Mig1 transient response. We find that with decreasing levels of post-shift glucose, the transient
Particle transport due to magnetic fluctuations
Stoneking, M.R.; Hokin, S.A.; Prager, S.C.; Fiksel, G.; Ji, H.; Den Hartog, D.J.
1994-01-01
Electron current fluctuations are measured with an electrostatic energy analyzer at the edge of the MST reversed-field pinch plasma. The radial flux of fast electrons (E>T e ) due to parallel streaming along a fluctuating magnetic field is determined locally by measuring the correlated product e B r >. Particle transport is small just inside the last closed flux surface (Γ e,mag e,total ), but can account for all observed particle losses inside r/a=0.8. Electron diffusion is found to increase with parallel velocity, as expected for diffusion in a region of field stochasticity
Casati, G.; Chirikov, B.V.
1996-01-01
Various fluctuations in quantum systems with discrete spectrum are discussed, including recent unpublished results. Open questions and unexplained peculiarities of quantum fluctuations are formulated [ru
Lombardía, Esteban; Rovetto, Adrián J.; Arabolaza, Ana L.; Grau, Roberto R.
2006-01-01
Cell-to-cell communication in bacteria is mediated by quorum-sensing systems (QSS) that produce chemical signal molecules called autoinducers (AI). In particular, LuxS/AI-2-dependent QSS has been proposed to act as a universal lexicon that mediates intra- and interspecific bacterial behavior. Here we report that the model organism Bacillus subtilis operates a luxS-dependent QSS that regulates its morphogenesis and social behavior. We demonstrated that B. subtilis luxS is a growth-phase-regula...
无
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.
Stochastic Averaging and Stochastic Extremum Seeking
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...
Stochastic growth of localized plasma waves
Robinson, P.A.; Cairns, Iver H.
2001-01-01
Localized bursty plasma waves are detected by spacecraft in many space plasmas. The large spatiotemporal scales involved imply that beam and other instabilities relax to marginal stability and that mean wave energies are low. Stochastic wave growth occurs when ambient fluctuations perturb the system, causing fluctuations about marginal stability. This yields regions where growth is enhanced and others where damping is increased; bursts are associated with enhanced growth and can occur even when the mean growth rate is negative. In stochastic growth, energy loss from the source is suppressed relative to secular growth, preserving it far longer than otherwise possible. Linear stochastic growth can operate at wave levels below thresholds of nonlinear wave-clumping mechanisms such as strong-turbulence modulational instability and is not subject to their coherence and wavelength limits. These mechanisms can be distinguished by statistics of the fields, whose strengths are lognormally distributed if stochastically growing and power-law distributed in strong turbulence. Recent applications of stochastic growth theory (SGT) are described, involving bursty plasma waves and unstable particle distributions in type III solar radio sources, the Earth's foreshock, magnetosheath, and polar cap regions. It is shown that when combined with wave-wave processes, SGT also accounts for associated radio emissions
Fluctuation-Induced Pattern Formation in a Surface Reaction
Starke, Jens; Reichert, Christian; Eiswirth, Markus
2006-01-01
Spontaneous nucleation, pulse formation, and propagation failure have been observed experimentally in CO oxidation on Pt(110) at intermediate pressures ($\\approx 10^{-2}$mbar). This phenomenon can be reproduced with a stochastic model which includes temperature effects. Nucleation occurs randomly...... due to fluctuations in the reaction processes, whereas the subsequent damping out essentially follows the deterministic path. Conditions for the occurence of stochastic effects in the pattern formation during CO oxidation on Pt are discussed....
Tucker, E B
1988-06-01
pH-buffered carboxyfluorescein (Buffered-CF) alone (control), or Buffered-CF solutions containing one of the following: (1)D-myo-inositol (I); (2)D-myo-inositol 2-monophosphate (IP1); (3)D-myo-inositol 1,4-bisphosphate (IP2); (4)D-myo-inositol 1,4,5-trisphosphate (IP3); (5)D-fructose 2,6-diphosphate (F-2,6P2) were microinjected into the terminal cells of staminal hairs ofSetcreasea purpurea Boom. Passage of the CF from this terminal cell along the chain of cells towards the filament was monitored for 5 min using fluorescence microscopy and quantified using computer-assisted fluorescence-intensity video analysis. Cell-to-cell transport of CF in hairs microinjected with Buffered-CF containing either I, IP1 or F-2,6P2 was similar to that in hairs microinjected with Buffered-CF only. On the other hand, cell-to-cell transport of CF in hairs microinjected with Buffered-CF containing either IP2 or IP3 was inhibited. These results indicate that polyphosphoinositols may be involved in the regulation of intercellular transport of low-molecular-weight, hydrophilic molecules in plants.
Active Brownian particles with velocity-alignment and active fluctuations
Großmann, R; Schimansky-Geier, L; Romanczuk, P
2012-01-01
We consider a model of active Brownian particles (ABPs) with velocity alignment in two spatial dimensions with passive and active fluctuations. Here, active fluctuations refers to purely non-equilibrium stochastic forces correlated with the heading of an individual active particle. In the simplest case studied here, they are assumed to be independent stochastic forces parallel (speed noise) and perpendicular (angular noise) to the velocity of the particle. On the other hand, passive fluctuations are defined by a noise vector independent of the direction of motion of a particle, and may account, for example, for thermal fluctuations. We derive a macroscopic description of the ABP gas with velocity-alignment interaction. Here, we start from the individual-based description in terms of stochastic differential equations (Langevin equations) and derive equations of motion for the coarse-grained kinetic variables (density, velocity and temperature) via a moment expansion of the corresponding probability density function. We focus here on the different impact of active and passive fluctuations on onset of collective motion and show how active fluctuations in the active Brownian dynamics can change the phase-transition behaviour of the system. In particular, we show that active angular fluctuations lead to an earlier breakdown of collective motion and to the emergence of a new bistable regime in the mean-field case. (paper)
Stochastic persistence and stationary distribution in an SIS epidemic model with media coverage
Guo, Wenjuan; Cai, Yongli; Zhang, Qimin; Wang, Weiming
2018-02-01
This paper aims to study an SIS epidemic model with media coverage from a general deterministic model to a stochastic differential equation with environment fluctuation. Mathematically, we use the Markov semigroup theory to prove that the basic reproduction number R0s can be used to control the dynamics of stochastic system. Epidemiologically, we show that environment fluctuation can inhibit the occurrence of the disease, namely, in the case of disease persistence for the deterministic model, the disease still dies out with probability one for the stochastic model. So to a great extent the stochastic perturbation under media coverage affects the outbreak of the disease.
Wellens, Thomas; Shatokhin, Vyacheslav; Buchleitner, Andreas
2004-01-01
We are taught by conventional wisdom that the transmission and detection of signals is hindered by noise. However, during the last two decades, the paradigm of stochastic resonance (SR) proved this assertion wrong: indeed, addition of the appropriate amount of noise can boost a signal and hence facilitate its detection in a noisy environment. Due to its simplicity and robustness, SR has been implemented by mother nature on almost every scale, thus attracting interdisciplinary interest from physicists, geologists, engineers, biologists and medical doctors, who nowadays use it as an instrument for their specific purposes. At the present time, there exist a lot of diversified models of SR. Taking into account the progress achieved in both theoretical understanding and practical application of this phenomenon, we put the focus of the present review not on discussing in depth technical details of different models and approaches but rather on presenting a general and clear physical picture of SR on a pedagogical level. Particular emphasis will be given to the implementation of SR in generic quantum systems-an issue that has received limited attention in earlier review papers on the topic. The major part of our presentation relies on the two-state model of SR (or on simple variants thereof), which is general enough to exhibit the main features of SR and, in fact, covers many (if not most) of the examples of SR published so far. In order to highlight the diversity of the two-state model, we shall discuss several examples from such different fields as condensed matter, nonlinear and quantum optics and biophysics. Finally, we also discuss some situations that go beyond the generic SR scenario but are still characterized by a constructive role of noise
Herranz, M. Carmen; Sánchez Navarro, Jesús A.; Saurí Peris, Ana; Mingarro Muñoz, Ismael; Pallás Benet, Vicente
2005-01-01
The movement protein (MP) of Prunus necrotic ringspot virus (PNRSV) is required for cell-to-cell movement. MP subcellular localization studies using a GFP fusion protein revealed highly punctate structures between neighboring cells, believed to represent plasmodesmata. Deletion of the RNA-binding domain (RBD) of PNRSV MP abolishes the cell-to-cell movement. A mutational analysis on this RBD was performed in order to identify in vivo the features that govern viral transport. Loss of positive c...
Modified diffusion with memory for cyclone track fluctuations
Bernido, Christopher C., E-mail: cbernido@mozcom.com [Research Center for Theoretical Physics, Central Visayan Institute Foundation, Jagna, Bohol 6308 (Philippines); Carpio-Bernido, M. Victoria [Research Center for Theoretical Physics, Central Visayan Institute Foundation, Jagna, Bohol 6308 (Philippines); Escobido, Matthew G.O. [W. Sycip Graduate School of Business, Asian Institute of Management, 123 Paseo de Roxas Ave., Makati City 1260 (Philippines)
2014-06-13
Fluctuations in a time series for tropical cyclone tracks are investigated based on an exponentially modified Brownian motion. The mean square displacement (MSD) is evaluated and compared to a recent work on cyclone tracks based on fractional Brownian motion (fBm). Unlike the work based on fBm, the present approach is found to capture the behavior of MSD versus time graphs for cyclones even for large values of time. - Highlights: • Cyclone track fluctuations are modeled as stochastic processes with memory. • Stochastic memory functions beyond fractional Brownian motion are introduced. • The model captures the behavior of cyclone track fluctuations for longer periods of time. • The approach can model time series for other fluctuating phenomena.
Mao, Sifeng; Zhang, Jie; Li, Haifang; Lin, Jin-Ming
2013-01-15
Cell-to-cell communication is a very important physiological behavior in life entity, and most of human behaviors are related to it. Although cell-to-cell communications are attracting much attention and financial support, rare methods have been successfully developed for in vitro cell-to-cell communication study. In this work, we developed a novel method for cell-to-cell communication study on an integrated microdevice, and signaling molecule and metabolites were online-detected by an electrospray ionization-quadrupole-time-of-flight-mass spectrometer (ESI-Q-TOF-MS) after on-chip solid-phase extraction. Moreover, we presented a "Surface Tension Plug" on a microchip to control cell-to-cell communication. The microdevice consists of three functional sections: cell coculture channel, targets pretreatment, and targets detection sections. To verify the feasibility of cell-to-cell communications on the integrated microdevice, we studied the communication between the 293 and the L-02 cells. Epinephrine and glucose were successfully detected using an ESI-Q-TOF-MS with short analysis time (communication study.
Kallianpur, Gopinath; Hida, Takeyuki
1987-01-01
The use of probabilistic methods in the biological sciences has been so well established by now that mathematical biology is regarded by many as a distinct dis cipline with its own repertoire of techniques. The purpose of the Workshop on sto chastic methods in biology held at Nagoya University during the week of July 8-12, 1985, was to enable biologists and probabilists from Japan and the U. S. to discuss the latest developments in their respective fields and to exchange ideas on the ap plicability of the more recent developments in stochastic process theory to problems in biology. Eighteen papers were presented at the Workshop and have been grouped under the following headings: I. Population genetics (five papers) II. Measure valued diffusion processes related to population genetics (three papers) III. Neurophysiology (two papers) IV. Fluctuation in living cells (two papers) V. Mathematical methods related to other problems in biology, epidemiology, population dynamics, etc. (six papers) An important f...
Frank B. Dazzo
2012-05-01
Full Text Available This paper describes how the quantitative analytical tools of CMEIAS image analysis software can be used to investigate in situ microbial interactions involving cell-to-cell communication within biofilms. Various spatial pattern analyses applied to the data extracted from the 2-dimensional coordinate positioning of individual bacterial cells at single-cell resolution indicate that microbial colonization within natural biofilms is not a spatially random process, but rather involves strong positive interactions between communicating cells that influence their neighbors’ aggregated colonization behavior. Geostatistical analysis of the data provide statistically defendable estimates of the micrometer scale and interpolation maps of the spatial heterogeneity and local intensity at which these microbial interactions autocorrelate with their spatial patterns of distribution. Including in situ image analysis in cell communication studies fills an important gap in understanding the spatially dependent microbial ecophysiology that governs the intensity of biofilm colonization and its unique architecture.
Pitzalis, Nicolas; Heinlein, Manfred
2017-12-18
The infection of plants by viruses depends on cellular mechanisms that support the replication of the viral genomes, and the cell-to-cell and systemic movement of the virus via plasmodesmata (PD) and the connected phloem. While the propagation of some viruses requires the conventional endoplasmic reticulum (ER)-Golgi pathway, others replicate and spread between cells in association with the ER and are independent of this pathway. Using selected viruses as examples, this review re-examines the involvement of membranes and the cytoskeleton during virus infection and proposes potential roles of class VIII myosins and membrane-tethering proteins in controlling viral functions at specific ER subdomains, such as cortical microtubule-associated ER sites, ER-plasma membrane contact sites, and PD. © The Author(s) 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Sato, Yuma; Watanabe, Shumpei; Fukuda, Yoshinari; Hashiguchi, Takao; Yanagi, Yusuke; Ohno, Shinji
2018-03-15
Measles virus (MV) usually causes acute infection but in rare cases persists in the brain, resulting in subacute sclerosing panencephalitis (SSPE). Since human neurons, an important target affected in the disease, do not express the known MV receptors (signaling lymphocyte activation molecule [SLAM] and nectin 4), how MV infects neurons and spreads between them is unknown. Recent studies have shown that many virus strains isolated from SSPE patients possess substitutions in the extracellular domain of the fusion (F) protein which confer enhanced fusion activity. Hyperfusogenic viruses with such mutations, unlike the wild-type MV, can induce cell-cell fusion even in SLAM- and nectin 4-negative cells and spread efficiently in human primary neurons and the brains of animal models. We show here that a hyperfusogenic mutant MV, IC323-F(T461I)-EGFP (IC323 with a fusion-enhancing T461I substitution in the F protein and expressing enhanced green fluorescent protein), but not the wild-type MV, spreads in differentiated NT2 cells, a widely used human neuron model. Confocal time-lapse imaging revealed the cell-to-cell spread of IC323-F(T461I)-EGFP between NT2 neurons without syncytium formation. The production of virus particles was strongly suppressed in NT2 neurons, also supporting cell-to-cell viral transmission. The spread of IC323-F(T461I)-EGFP was inhibited by a fusion inhibitor peptide as well as by some but not all of the anti-hemagglutinin antibodies which neutralize SLAM- or nectin-4-dependent MV infection, suggesting the presence of a distinct neuronal receptor. Our results indicate that MV spreads in a cell-to-cell manner between human neurons without causing syncytium formation and that the spread is dependent on the hyperfusogenic F protein, the hemagglutinin, and the putative neuronal receptor for MV. IMPORTANCE Measles virus (MV), in rare cases, persists in the human central nervous system (CNS) and causes subacute sclerosing panencephalitis (SSPE) several
Transient fluctuation relations for time-dependent particle transport
Altland, Alexander; de Martino, Alessandro; Egger, Reinhold; Narozhny, Boris
2010-09-01
We consider particle transport under the influence of time-varying driving forces, where fluctuation relations connect the statistics of pairs of time-reversed evolutions of physical observables. In many “mesoscopic” transport processes, the effective many-particle dynamics is dominantly classical while the microscopic rates governing particle motion are of quantum-mechanical origin. We here employ the stochastic path-integral approach as an optimal tool to probe the fluctuation statistics in such applications. Describing the classical limit of the Keldysh quantum nonequilibrium field theory, the stochastic path integral encapsulates the quantum origin of microscopic particle exchange rates. Dynamically, it is equivalent to a transport master equation which is a formalism general enough to describe many applications of practical interest. We apply the stochastic path integral to derive general functional fluctuation relations for current flow induced by time-varying forces. We show that the successive measurement processes implied by this setup do not put the derivation of quantum fluctuation relations in jeopardy. While in many cases the fluctuation relation for a full time-dependent current profile may contain excessive information, we formulate a number of reduced relations, and demonstrate their application to mesoscopic transport. Examples include the distribution of transmitted charge, where we show that the derivation of a fluctuation relation requires the combined monitoring of the statistics of charge and work.
Modeling stochasticity in biochemical reaction networks
Constantino, P H; Vlysidis, M; Smadbeck, P; Kaznessis, Y N
2016-01-01
Small biomolecular systems are inherently stochastic. Indeed, fluctuations of molecular species are substantial in living organisms and may result in significant variation in cellular phenotypes. The chemical master equation (CME) is the most detailed mathematical model that can describe stochastic behaviors. However, because of its complexity the CME has been solved for only few, very small reaction networks. As a result, the contribution of CME-based approaches to biology has been very limited. In this review we discuss the approach of solving CME by a set of differential equations of probability moments, called moment equations. We present different approaches to produce and to solve these equations, emphasizing the use of factorial moments and the zero information entropy closure scheme. We also provide information on the stability analysis of stochastic systems. Finally, we speculate on the utility of CME-based modeling formalisms, especially in the context of synthetic biology efforts. (topical review)
Stochastic tools in turbulence
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
Stochastic transport processes in discrete biological systems
Frehland, Eckart
1982-01-01
These notes are in part based on a course for advanced students in the applications of stochastic processes held in 1978 at the University of Konstanz. These notes contain the results of re cent studies on the stochastic description of ion transport through biological membranes. In particular, they serve as an introduction to an unified theory of fluctuations in complex biological transport systems. We emphasize that the subject of this volume is not to introduce the mathematics of stochastic processes but to present a field of theoretical biophysics in which stochastic methods are important. In the last years the study of membrane noise has become an important method in biophysics. Valuable information on the ion transport mechanisms in membranes can be obtained from noise analysis. A number of different processes such as the opening and closing of ion channels have been shown to be sources of the measured current or voltage fluctuations. Bio logical 'transport systems can be complex. For example, the tr...
Stochastic growth of localized plasma waves
Robinson, P.A.; Cairns, I.H.
2000-01-01
Full text: Localized bursty plasma waves occur in many natural systems, where they are detected by spacecraft. The large spatiotemporal scales involved imply that beam and other instabilities relax to marginal stability and that mean wave energies are low. Stochastic wave growth occurs when ambient fluctuations perturb the wave-driver interaction, causing fluctuations about marginal stability. This yields regions where growth is enhanced and others where damping is increased; observed bursts are associated with enhanced growth and can occur even when the mean growth rate is negative. In stochastic growth, energy loss from the source is suppressed relative to secular growth, preserving it for much longer times and distances than otherwise possible. Linear stochastic growth can operate at wave levels below thresholds of nonlinear wave-clumping mechanisms such as strong-turbulence modulational instability and is not subject to their coherence and wavelength limits. Growth mechanisms can be distinguished by statistics of the fields, whose strengths are lognormally distributed if stochastically growing, power-law distributed in strong turbulence, and uniformly distributed in log under secular growth. After delineating stochastic growth and strong-turbulence regimes, recent applications of stochastic growth theory (SGT) are described, involving bursty plasma waves and unstable particle distributions in type II and III solar radio sources, foreshock regions upstream of the bow shocks of Earth and planets, and Earth's magnetosheath, auroras, and polar-caps. It is shown that when combined with wave-wave processes, SGT accounts for type II and III solar radio emissions. SGT thus removes longstanding problems in understanding persistent unstable distributions, bursty fields, and radio emissions observed in space
Mellin Transform Method for European Option Pricing with Hull-White Stochastic Interest Rate
Ji-Hun Yoon
2014-01-01
Full Text Available Even though interest rates fluctuate randomly in the marketplace, many option-pricing models do not fully consider their stochastic nature owing to their generally limited impact on option prices. However, stochastic dynamics in stochastic interest rates may have a significant impact on option prices as we take account of issues of maturity, hedging, or stochastic volatility. In this paper, we derive a closed form solution for European options in Black-Scholes model with stochastic interest rate using Mellin transform techniques.
Some remarks on stochastic collective oscillations in ECRIS plasmas
Golovanivsky, K.S.
1993-08-01
It is proposed that the thermal fluctuations in plasmas in general and in ECRIS plasmas in particular create rather strong stochastic electrical fields affecting both confinement and heating of an ECRIS plasma. The amplitude, range and characteristic frequency of the stochastic fields as well as the perpendicular diffusion coefficient and the upper density limit for the mirror confinement are determined on the level of the approximate evaluations. Some aspects of the ECRIS plasma's peculiarities due to the stochastic electrical fields are discussed. (author) 7 refs., 5 figs
Stochastic samples versus vacuum expectation values in cosmology
Tsamis, N.C.; Tzetzias, Aggelos; Woodard, R.P.
2010-01-01
Particle theorists typically use expectation values to study the quantum back-reaction on inflation, whereas many cosmologists stress the stochastic nature of the process. While expectation values certainly give misleading results for some things, such as the stress tensor, we argue that operators exist for which there is no essential problem. We quantify this by examining the stochastic properties of a noninteracting, massless, minimally coupled scalar on a locally de Sitter background. The square of the stochastic realization of this field seems to provide an example of great relevance for which expectation values are not misleading. We also examine the frequently expressed concern that significant back-reaction from expectation values necessarily implies large stochastic fluctuations between nearby spatial points. Rather than viewing the stochastic formalism in opposition to expectation values, we argue that it provides a marvelously simple way of capturing the leading infrared logarithm corrections to the latter, as advocated by Starobinsky
Stochastic goal-oriented error estimation with memory
Ackmann, Jan; Marotzke, Jochem; Korn, Peter
2017-11-01
We propose a stochastic dual-weighted error estimator for the viscous shallow-water equation with boundaries. For this purpose, previous work on memory-less stochastic dual-weighted error estimation is extended by incorporating memory effects. The memory is introduced by describing the local truncation error as a sum of time-correlated random variables. The random variables itself represent the temporal fluctuations in local truncation errors and are estimated from high-resolution information at near-initial times. The resulting error estimator is evaluated experimentally in two classical ocean-type experiments, the Munk gyre and the flow around an island. In these experiments, the stochastic process is adapted locally to the respective dynamical flow regime. Our stochastic dual-weighted error estimator is shown to provide meaningful error bounds for a range of physically relevant goals. We prove, as well as show numerically, that our approach can be interpreted as a linearized stochastic-physics ensemble.
Stochastic hyperfine interactions modeling library
Zacate, Matthew O.; Evenson, William E.
2011-04-01
The stochastic hyperfine interactions modeling library (SHIML) provides a set of routines to assist in the development and application of stochastic models of hyperfine interactions. The library provides routines written in the C programming language that (1) read a text description of a model for fluctuating hyperfine fields, (2) set up the Blume matrix, upon which the evolution operator of the system depends, and (3) find the eigenvalues and eigenvectors of the Blume matrix so that theoretical spectra of experimental techniques that measure hyperfine interactions can be calculated. The optimized vector and matrix operations of the BLAS and LAPACK libraries are utilized; however, there was a need to develop supplementary code to find an orthonormal set of (left and right) eigenvectors of complex, non-Hermitian matrices. In addition, example code is provided to illustrate the use of SHIML to generate perturbed angular correlation spectra for the special case of polycrystalline samples when anisotropy terms of higher order than A can be neglected. Program summaryProgram title: SHIML Catalogue identifier: AEIF_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIF_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU GPL 3 No. of lines in distributed program, including test data, etc.: 8224 No. of bytes in distributed program, including test data, etc.: 312 348 Distribution format: tar.gz Programming language: C Computer: Any Operating system: LINUX, OS X RAM: Varies Classification: 7.4 External routines: TAPP [1], BLAS [2], a C-interface to BLAS [3], and LAPACK [4] Nature of problem: In condensed matter systems, hyperfine methods such as nuclear magnetic resonance (NMR), Mössbauer effect (ME), muon spin rotation (μSR), and perturbed angular correlation spectroscopy (PAC) measure electronic and magnetic structure within Angstroms of nuclear probes through the hyperfine interaction. When
Michelle Hawkins
2013-11-01
Full Text Available Eukaryotic genome replication is stochastic, and each cell uses a different cohort of replication origins. We demonstrate that interpreting high-resolution Saccharomyces cerevisiae genome replication data with a mathematical model allows quantification of the stochastic nature of genome replication, including the efficiency of each origin and the distribution of termination events. Single-cell measurements support the inferred values for stochastic origin activation time. A strain, in which three origins were inactivated, confirmed that the distribution of termination events is primarily dictated by the stochastic activation time of origins. Cell-to-cell variability in origin activity ensures that termination events are widely distributed across virtually the whole genome. We propose that the heterogeneity in origin usage contributes to genome stability by limiting potentially deleterious events from accumulating at particular loci.
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 ...
Gupta, Sourendu
2007-01-01
In this talk I discuss measures of fluctuations, especially those leading to the proof that the quark gluon plasma indeed contains quarks. I discuss the quark mass dependence of the critical end point of QCD. Then I discuss probes of the QCD critical point. Non-gaussian behaviour of event-to-event fluctuations of conserved quantum numbers is one such probe. Another is due to the coupling of fluctuations in baryon number and electrical charge, giving rise to long range random fluctuations of local charge density which relax slowly. These fluctuations can scatter photons, giving rise to critical opalescence
Gupta, Sourendu
2007-02-01
In this talk I discuss measures of fluctuations, especially those leading to the proof that the quark gluon plasma indeed contains quarks. I discuss the quark mass dependence of the critical end point of QCD. Then I discuss probes of the QCD critical point. Non-gaussian behaviour of event-to-event fluctuations of conserved quantum numbers is one such probe. Another is due to the coupling of fluctuations in baryon number and electrical charge, giving rise to long range random fluctuations of local charge density which relax slowly. These fluctuations can scatter photons, giving rise to critical opalescence.
Gupta, Sourendu [Department of Theoretical Physics, Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400005 (India)
2007-02-15
In this talk I discuss measures of fluctuations, especially those leading to the proof that the quark gluon plasma indeed contains quarks. I discuss the quark mass dependence of the critical end point of QCD. Then I discuss probes of the QCD critical point. Non-gaussian behaviour of event-to-event fluctuations of conserved quantum numbers is one such probe. Another is due to the coupling of fluctuations in baryon number and electrical charge, giving rise to long range random fluctuations of local charge density which relax slowly. These fluctuations can scatter photons, giving rise to critical opalescence.
Stochastic Modelling, Analysis, and Simulations of the Solar Cycle Dynamic Process
Turner, Douglas C.; Ladde, Gangaram S.
2018-03-01
Analytical solutions, discretization schemes and simulation results are presented for the time delay deterministic differential equation model of the solar dynamo presented by Wilmot-Smith et al. In addition, this model is extended under stochastic Gaussian white noise parametric fluctuations. The introduction of stochastic fluctuations incorporates variables affecting the dynamo process in the solar interior, estimation error of parameters, and uncertainty of the α-effect mechanism. Simulation results are presented and analyzed to exhibit the effects of stochastic parametric volatility-dependent perturbations. The results generalize and extend the work of Hazra et al. In fact, some of these results exhibit the oscillatory dynamic behavior generated by the stochastic parametric additative perturbations in the absence of time delay. In addition, the simulation results of the modified stochastic models influence the change in behavior of the very recently developed stochastic model of Hazra et al.
Polarization of the vacuum by a stochastic external field
Krive, I.V.; Pastur, L.A.; Rozhavskii, A.S.
1988-01-01
The effect of disorder, realized in the form of a fluctuating extra mass term, on the bosonic vacuum and fermionic vacuum of models of quantum field theory is studied. A method is developed for calculating the mean effective potential in the stochastic external field. For a model of interacting scalar and fermion fields in (3+1)-dimensional space-time it is shown that random fluctuations of the mass lead to an increase of the equilibrium mean scalar field in the system
Magnetic fluctuation measurements in the Tokapole II tokamak
LaPointe, M.A.
1990-09-01
Magnetic fluctuation measurements have been made in the Tokapole II tokamak in the frequency range 10 kHz ≤ f ≤ 5 MHz. The fluctuations above 500 kHz varied greatly as the effective edge safety factor, q a , was varied over the range 0.8 ≤ q a ≤ 3.8. As q a was varied from 3.8 to 0.8 the high frequency magnetic fluctuation amplitude increased by over three orders of magnitude. The fluctuation amplitude for 0.5 to 2.0 MHz was a factor of 10 lower than the fluctuation amplitude in the range 100 to 400 kHz for q a of 0.8. When q a was increased to 3.8 the difference between the differing frequency ranges increased to a factor of 10 3 . Comparison of the measured broadband fluctuation amplitudes with those predicted from thermally driven Alfven and magnetosonic waves shows that the amplitudes are at least 1000 times larger than the theoretical predictions. This indicates that there is some other mechanism driving the higher frequency magnetic fluctuations. Estimates show that the contribution by the magnetic fluctuations above 500 kHz to the estimated electron energy loss from stochastic fields is negligible. The profiles of the various components of the magnetic fluctuations indicate the possibility that the shear in the magnetic field may stabilize whatever instabilities drive the magnetic fluctuations
Stochastic and Deterministic Fluctuations in Stimulated Brillouin Scattering
1990-10-01
Partial Fulfillment of the Requirements for the Degree DOCTOR OF PHILOSOPHY Supervised by Professor Robert W. Boyd Accessionl For isGRA&I DTIC TAB The...earned a Master of Science degree in Optics in February of 1985. His thesis work has been conducted under the supervision of Professor Robert W. Boyd...by R. W. Boyd, M. G. Raymer , and L. M. Narducci 8. H. Haken, "Analogy between higher instabilities in fluids and lasers," Phys. Lett. 53A, 77 (1975
Stochastic scalar mixing models accounting for turbulent frequency multiscale fluctuations
Soulard, Olivier; Sabel'nikov, Vladimir; Gorokhovski, Michael
2004-01-01
Two new scalar micromixing models accounting for a turbulent frequency scale distribution are investigated. These models were derived by Sabel'nikov and Gorokhovski [Second International Symposium on Turbulence and Shear FLow Phenomena, Royal Institute of technology (KTH), Stockholm, Sweden, June 27-29, 2001] using a multiscale extension of the classical interaction by exchange with the mean (IEM) and Langevin models. They are, respectively, called Extended IEM (EIEM) and Extended Langevin (ELM) models. The EIEM and ELM models are tested against DNS results in the case of the decay of a homogeneous scalar field in homogeneous turbulence. This comparison leads to a reformulation of the law governing the mixing frequency distribution. Finally, the asymptotic behaviour of the modeled PDF is discussed
A cell-to-cell Markovian model for the reliability of a digital control system of a steam generator
Gomes, Ian B.; Melo, Paulo F.F. Frutuoso e; Saldanha, Pedro L.C.
2013-01-01
With the shift of technology from analog to digital systems, due to the obsolescence of the older analog systems and the functional advantages of the digital ones, existing nuclear power plants have begun to replace their systems, while newer plants use digital systems from the beginning of their construction. However, the process of risk-informed analysis for digital systems has not been satisfactorily developed yet. Traditional methods, such as fault trees, have limitations, while dynamic methods are still in the tests stage and may be difficult to be applied to a real size probabilistic safety assessment (PSA) model. The objective of this paper is to study and obtain a better comprehension of the Markov/CCMT method, a method that combines the traditional Markovian methodology with the cell-to-cell mapping technique for representing the possible failure events that can be originated in the dynamic interactions between the instrumentation and control system and the controlled process, and among the various components of the digital system. The study consists of the simulation of a digital water level control system of the steam generator of a PWR plant. From this simulation, a Failure Modes and Effects Analysis (FMEA) was made and the information obtained was used to calculate the system reliability, using the Markov/CCMT methodology. The results show that the method is capable of identifying the most probable causes for a possible failure of the digital system. (author)
Automated image-based assay for evaluation of HIV neutralization and cell-to-cell fusion inhibition.
Sheik-Khalil, Enas; Bray, Mark-Anthony; Özkaya Şahin, Gülsen; Scarlatti, Gabriella; Jansson, Marianne; Carpenter, Anne E; Fenyö, Eva Maria
2014-08-30
Standardized techniques to detect HIV-neutralizing antibody responses are of great importance in the search for an HIV vaccine. Here, we present a high-throughput, high-content automated plaque reduction (APR) assay based on automated microscopy and image analysis that allows evaluation of neutralization and inhibition of cell-cell fusion within the same assay. Neutralization of virus particles is measured as a reduction in the number of fluorescent plaques, and inhibition of cell-cell fusion as a reduction in plaque area. We found neutralization strength to be a significant factor in the ability of virus to form syncytia. Further, we introduce the inhibitory concentration of plaque area reduction (ICpar) as an additional measure of antiviral activity, i.e. fusion inhibition. We present an automated image based high-throughput, high-content HIV plaque reduction assay. This allows, for the first time, simultaneous evaluation of neutralization and inhibition of cell-cell fusion within the same assay, by quantifying the reduction in number of plaques and mean plaque area, respectively. Inhibition of cell-to-cell fusion requires higher quantities of inhibitory reagent than inhibition of virus neutralization.
McLeod, Claire M; Mauck, Robert L
2016-12-12
Extracellular matrix dynamics are key to tissue morphogenesis, homeostasis, injury, and repair. The spatiotemporal organization of this matrix has profound biological implications, but is challenging to monitor using standard techniques. Here, we address these challenges by using noncanonical amino acid tagging to fluorescently label extracellular matrix synthesized in the presence of bio-orthogonal methionine analogs. This strategy labels matrix proteins with high resolution, without compromising their distribution or mechanical function. We demonstrate that the organization and temporal dynamics of the proteinaceous matrix depend on the biophysical features of the microenvironment, including the biomaterial scaffold and the niche constructed by cells themselves. Pulse labeling experiments reveal that, in immature constructs, nascent matrix is highly fibrous and interdigitates with pre-existing matrix, while in more developed constructs, nascent matrix lacks fibrous organization and is retained in the immediate pericellular space. Inhibition of collagen crosslinking increases matrix synthesis, but compromises matrix organization. Finally, these data demonstrate marked cell-to-cell heterogeneity amongst both chondrocytes and mesenchymal stem cells undergoing chondrogenesis. Collectively, these results introduce fluorescent noncanonical amino acid tagging as a strategy to investigate spatiotemporal matrix organization, and demonstrate its ability to identify differences in phenotype, microenvironment, and matrix assembly at the single cell level.
Gabriella Schiera
2015-01-01
Full Text Available Extracellular vesicles are involved in a great variety of physiological events occurring in the nervous system, such as cross talk among neurons and glial cells in synapse development and function, integrated neuronal plasticity, neuronal-glial metabolic exchanges, and synthesis and dynamic renewal of myelin. Many of these EV-mediated processes depend on the exchange of proteins, mRNAs, and noncoding RNAs, including miRNAs, which occurs among glial and neuronal cells. In addition, production and exchange of EVs can be modified under pathological conditions, such as brain cancer and neurodegeneration. Like other cancer cells, brain tumours can use EVs to secrete factors, which allow escaping from immune surveillance, and to transfer molecules into the surrounding cells, thus transforming their phenotype. Moreover, EVs can function as a way to discard material dangerous to cancer cells, such as differentiation-inducing proteins, and even drugs. Intriguingly, EVs seem to be also involved in spreading through the brain of aggregated proteins, such as prions and aggregated tau protein. Finally, EVs can carry useful biomarkers for the early diagnosis of diseases. Herein we summarize possible roles of EVs in brain physiological functions and discuss their involvement in the horizontal spreading, from cell to cell, of both cancer and neurodegenerative pathologies.
Moral hazard in the credit market when the collateral value is stochastic
Niinimäki, Juha-Pekka
2010-01-01
This theoretical paper explores the effects of costly and non-costly collateral on moral hazard, when collateral value may fluctuate. Given that all collateral is costly, stochastic collateral will entail the same positive incentive effects as nonstochastic collateral, provided the variation in collateral value is modest. If it is large, the incentive effects are smaller under stochastic collateral. With non-costly collateral, stochastic collateral entails positive incentive effects or no eff...
Cosmophysical Factors in the Fluctuation Amplitude Spectrum of Brownian Motion
Kaminsky A. V.
2010-04-01
Full Text Available Phenomenon of the regular variability of the fine structure of the fluctuation in the amplitude distributions (shapes of related histograms for the case of Brownian motion was investigated. We took an advantage of the dynamic light scattering method (DLS to get a stochastically fluctuated signal determined by Brownian motion. Shape of the histograms is most likely to vary, synchronous, in two proximally located independent cells containing Brownian particles. The synchronism persists in the cells distant at 2m from each other, and positioned meridionally. With a parallel-wise positioning of the cells, high probability of the synchronous variation in the shape of the histograms by local time has been observed. This result meets the previous conclusion about the dependency of histogram shapes ("fluctuation amplitudes" of the spectra of stochastic processes upon rotation of the Earth.
Cosmophysical Factors in the Fluctuation Amplitude Spectrum of Brownian Motion
Kaminsky A. V.
2010-07-01
Full Text Available Phenomenon of the regular variability of the fine structure of the fluctuation in the am- plitude distributions (shapes of related histograms for the case of Brownian motion was investigated. We took an advantage of the dynamic light scattering method (DLS to get a stochastically fluctuated signal determined by Brownian motion. Shape of the histograms is most likely to vary, synchronous, in two proximally located independent cells containing Brownian particles. The synchronism persists in the cells distant at 2 m from each other, and positioned meridionally. With a parallel-wise positioning of the cells, high probability of the synchronous variation in the shape of the histograms by local time has been observed. This result meets the previous conclusion about the dependency of histogram shapes (“fluctuation amplitudes” of the spectra of stochastic processes upon rotation of the Earth.
Engen, Steinar; Saether, Bernt-Erik
2014-03-01
We analyze the stochastic components of the Robertson-Price equation for the evolution of quantitative characters that enables decomposition of the selection differential into components due to demographic and environmental stochasticity. We show how these two types of stochasticity affect the evolution of multivariate quantitative characters by defining demographic and environmental variances as components of individual fitness. The exact covariance formula for selection is decomposed into three components, the deterministic mean value, as well as stochastic demographic and environmental components. We show that demographic and environmental stochasticity generate random genetic drift and fluctuating selection, respectively. This provides a common theoretical framework for linking ecological and evolutionary processes. Demographic stochasticity can cause random variation in selection differentials independent of fluctuating selection caused by environmental variation. We use this model of selection to illustrate that the effect on the expected selection differential of random variation in individual fitness is dependent on population size, and that the strength of fluctuating selection is affected by how environmental variation affects the covariance in Malthusian fitness between individuals with different phenotypes. Thus, our approach enables us to partition out the effects of fluctuating selection from the effects of selection due to random variation in individual fitness caused by demographic stochasticity. © 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.
Stochastic effects in hybrid inflation
Martin, Jérôme; Vennin, Vincent
2012-02-01
Hybrid inflation is a two-field model where inflation ends due to an instability. In the neighborhood of the instability point, the potential is very flat and the quantum fluctuations dominate over the classical motion of the inflaton and waterfall fields. In this article, we study this regime in the framework of stochastic inflation. We numerically solve the two coupled Langevin equations controlling the evolution of the fields and compute the probability distributions of the total number of e-folds and of the inflation exit point. Then, we discuss the physical consequences of our results, in particular, the question of how the quantum diffusion can affect the observable predictions of hybrid inflation.
Elitism and Stochastic Dominance
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...
Single-Molecule Stochastic Resonance
K. Hayashi
2012-08-01
Full Text Available Stochastic resonance (SR is a well-known phenomenon in dynamical systems. It consists of the amplification and optimization of the response of a system assisted by stochastic (random or probabilistic noise. Here we carry out the first experimental study of SR in single DNA hairpins which exhibit cooperatively transitions from folded to unfolded configurations under the action of an oscillating mechanical force applied with optical tweezers. By varying the frequency of the force oscillation, we investigate the folding and unfolding kinetics of DNA hairpins in a periodically driven bistable free-energy potential. We measure several SR quantifiers under varied conditions of the experimental setup such as trap stiffness and length of the molecular handles used for single-molecule manipulation. We find that a good quantifier of the SR is the signal-to-noise ratio (SNR of the spectral density of measured fluctuations in molecular extension of the DNA hairpins. The frequency dependence of the SNR exhibits a peak at a frequency value given by the resonance-matching condition. Finally, we carry out experiments on short hairpins that show how SR might be useful for enhancing the detection of conformational molecular transitions of low SNR.
Effects of dissipation and fluctuation in preheating
Vartuli, Rodrigo; Ramos, Rudnei de O.
2006-01-01
In this paper, we study the effects of dissipation and fluctuation in preheating after inflation. The effective equation of motion for a scalar field χ interacting with lighter fields is derived using the field theoretical method of closed time path due to Schwinger, winch is suitable to study nonequilibrium and time dependent process. In this derivation the emergent equation is intrinsically dissipative and stochastic in nature. The resulting dynamics is then studied both analytically and numerically. The results obtained are then discussed for then relevance for the reheating epoch right after an inflationary phase(preheating) for the case of the evolution of the scalar field χ and its decay into fermion. (author)
Intermittent dislocation density fluctuations in crystal plasticity from a phase-field crystal model
Tarp, Jens M.; Angheluta, Luiza; Mathiesen, Joachim
2014-01-01
Plastic deformation mediated by collective dislocation dynamics is investigated in the two-dimensional phase-field crystal model of sheared single crystals. We find that intermittent fluctuations in the dislocation population number accompany bursts in the plastic strain-rate fluctuations...... propose a simple stochastic model of dislocation reaction kinetics that is able to capture these statistical properties of the dislocation density fluctuations as a function of shear rate....
Singular stochastic differential equations
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.
Takegahara, Yuki; Yamanouchi, Keitaro; Nakamura, Katsuyuki; Nakano, Shin-ichi; Nishihara, Masugi
2014-01-01
Intramuscular adipose tissue (IMAT) formation is observed in some pathological conditions such as Duchenne muscular dystrophy (DMD) and sarcopenia. Several studies have suggested that IMAT formation is not only negatively correlated with skeletal muscle mass but also causes decreased muscle contraction in sarcopenia. In the present study, we examined w hether adipocytes affect myogenesis. For this purpose, skeletal muscle progenitor cells were transfected with siRNA of PPARγ (siPPARγ) in an attempt to inhibit adipogenesis. Myosin heavy chain (MHC)-positive myotube formation was promoted in cells transfected with siPPARγ compared to that of cells transfected with control siRNA. To determine whether direct cell-to-cell contact between adipocytes and myoblasts is a prerequisite for adipocytes to affect myogenesis, skeletal muscle progenitor cells were cocultured with pre- or mature adipocytes in a Transwell coculture system. MHC-positive myotube formation was inhibited when skeletal muscle progenitor cells were cocultured with mature adipocytes, but was promoted when they were cocultured with preadipocytes. Similar effects were observed when pre- or mature adipocyte-conditioned medium was used. These results indicate that preadipocytes play an important role in maintaining skeletal muscle mass by promoting myogenesis; once differentiated, the resulting mature adipocytes negatively affect myogenesis, leading to the muscle deterioration observed in skeletal muscle pathologies. - Highlights: • We examined the effects of pre- and mature adipocytes on myogenesis in vitro. • Preadipocytes and mature adipocytes affect myoblast fusion. • Preadipocytes play an important role in maintaining skeletal muscle mass. • Mature adipocytes lead to muscle deterioration observed in skeletal muscle pathologies
The neuropeptides CCK and NPY and the changing view of cell-to-cell communication in the taste bud.
Herness, Scott; Zhao, Fang-Li
2009-07-14
The evolving view of the taste bud increasingly suggests that it operates as a complex signal processing unit. A number of neurotransmitters and neuropeptides and their corresponding receptors are now known to be expressed in subsets of taste receptor cells in the mammalian bud. These expression patterns set up hard-wired cell-to-cell communication pathways whose exact physiological roles still remain obscure. As occurs in other cellular systems, it is likely that neuropeptides are co-expressed with neurotransmitters and function as neuromodulators. Several neuropeptides have been identified in taste receptor cells including cholecystokinin (CCK), neuropeptide Y (NPY), vasoactive intestinal peptide (VIP), and glucagon-like peptide 1 (GLP-1). Of these, CCK and NPY are the best studied. These two peptides are co-expressed in the same presynaptic cells; however, their postsynaptic actions are both divergent and antagonistic. CCK and its receptor, the CCK-1 subtype, are expressed in the same subset of taste receptor cells and the autocrine activation of these cells produces a number of excitatory physiological actions. Further, most of these cells are responsive to bitter stimuli. On the other hand, NPY and its receptor, the NPY-1 subtype, are expressed in different cells. NPY, acting in a paracrine fashion on NPY-1 receptors, results in inhibitory actions on the cell. Preliminary evidence suggests the NPY-1 receptor expressing cell co-expresses T1R3, a member of the T1R family of G-protein coupled receptors thought to be important in detection of sweet and umami stimuli. Thus the neuropeptide expressing cells co-express CCK, NPY, and CCK-1 receptor. Neuropeptides released from these cells during bitter stimulation may work in concert to both modulate the excitation of bitter-sensitive taste receptor cells while concurrently inhibiting sweet-sensitive cells. This modulatory process is similar to the phenomenon of lateral inhibition that occurs in other sensory systems.
Bible, Amber; Russell, Matthew H; Alexandre, Gladys
2012-07-01
The Che1 chemotaxis-like pathway of Azospirillum brasilense contributes to chemotaxis and aerotaxis, and it has also been found to contribute to regulating changes in cell surface adhesive properties that affect the propensity of cells to clump and to flocculate. The exact contribution of Che1 to the control of chemotaxis and flocculation in A. brasilense remains poorly understood. Here, we show that Che1 affects reversible cell-to-cell clumping, a cellular behavior in which motile cells transiently interact by adhering to one another at their nonflagellated poles before swimming apart. Clumping precedes and is required for flocculation, and both processes appear to be independently regulated. The phenotypes of a ΔaerC receptor mutant and of mutant strains lacking cheA1, cheY1, cheB1, or cheR1 (alone or in combination) or with che1 deleted show that Che1 directly mediates changes in the flagellar swimming velocity and that this behavior directly modulates the transient nature of clumping. Our results also suggest that an additional receptor(s) and signaling pathway(s) are implicated in mediating other Che1-independent changes in clumping identified in the present study. Transient clumping precedes the transition to stable clump formation, which involves the production of specific extracellular polysaccharides (EPS); however, production of these clumping-specific EPS is not directly controlled by Che1 activity. Che1-dependent clumping may antagonize motility and prevent chemotaxis, thereby maintaining cells in a metabolically favorable niche.
Takegahara, Yuki; Yamanouchi, Keitaro, E-mail: akeita@mail.ecc.u-tokyo.ac.jp; Nakamura, Katsuyuki; Nakano, Shin-ichi; Nishihara, Masugi
2014-05-15
Intramuscular adipose tissue (IMAT) formation is observed in some pathological conditions such as Duchenne muscular dystrophy (DMD) and sarcopenia. Several studies have suggested that IMAT formation is not only negatively correlated with skeletal muscle mass but also causes decreased muscle contraction in sarcopenia. In the present study, we examined w hether adipocytes affect myogenesis. For this purpose, skeletal muscle progenitor cells were transfected with siRNA of PPARγ (siPPARγ) in an attempt to inhibit adipogenesis. Myosin heavy chain (MHC)-positive myotube formation was promoted in cells transfected with siPPARγ compared to that of cells transfected with control siRNA. To determine whether direct cell-to-cell contact between adipocytes and myoblasts is a prerequisite for adipocytes to affect myogenesis, skeletal muscle progenitor cells were cocultured with pre- or mature adipocytes in a Transwell coculture system. MHC-positive myotube formation was inhibited when skeletal muscle progenitor cells were cocultured with mature adipocytes, but was promoted when they were cocultured with preadipocytes. Similar effects were observed when pre- or mature adipocyte-conditioned medium was used. These results indicate that preadipocytes play an important role in maintaining skeletal muscle mass by promoting myogenesis; once differentiated, the resulting mature adipocytes negatively affect myogenesis, leading to the muscle deterioration observed in skeletal muscle pathologies. - Highlights: • We examined the effects of pre- and mature adipocytes on myogenesis in vitro. • Preadipocytes and mature adipocytes affect myoblast fusion. • Preadipocytes play an important role in maintaining skeletal muscle mass. • Mature adipocytes lead to muscle deterioration observed in skeletal muscle pathologies.
Hidehiko Takigawa
2017-05-01
Full Text Available We previously reported that in an orthotopic nude mouse model of human colon cancer, bone marrow–derived mesenchymal stem cells (MSCs migrated to the tumor stroma and promoted tumor growth and metastasis. Here, we evaluated the proliferation and migration ability of cancer cells cocultured with MSCs to elucidate the mechanism of interaction between cancer cells and MSCs. Proliferation and migration of cancer cells increased following direct coculture with MSCs but not following indirect coculture. Thus, we hypothesized that direct contact between cancer cells and MSCs was important. We performed a microarray analysis of gene expression in KM12SM colon cancer cells directly cocultured with MSCs. Expression of epithelial-mesenchymal transition (EMT–related genes such as fibronectin (FN, SPARC, and galectin 1 was increased by direct coculture with MSCs. We also confirmed the upregulation of these genes with real-time polymerase chain reaction. Gene expression was not elevated in cancer cells indirectly cocultured with MSCs. Among the EMT-related genes upregulated by direct coculture with MSCs, we examined the immune localization of FN, a well-known EMT marker. In coculture assay in chamber slides, expression of FN was seen only at the edges of cancer clusters where cancer cells directly contacted MSCs. FN expression in cancer cells increased at the tumor periphery and invasive edge in orthotopic nude mouse tumors and human colon cancer tissues. These results suggest that MSCs induce EMT in colon cancer cells via direct cell-to-cell contact and may play an important role in colon cancer metastasis.
A contribution to the systematics of stochastic volatility models
Slanina, František
2010-01-01
Roč. 389, č. 16 (2010), s. 3230-3239 ISSN 0378-4371 R&D Projects: GA MŠk OC09078 Institutional research plan: CEZ:AV0Z10100520 Keywords : fluctuations * econophysics * stochastic differential equations Subject RIV: BM - Solid Matter Physics ; Magnetism Impact factor: 1.521, year: 2010
Carmen Herranz, Ma; Sanchez-Navarro, Jesús-Angel; Saurí, Ana; Mingarro, Ismael; Pallás, Vicente
2005-08-15
The movement protein (MP) of Prunus necrotic ringspot virus (PNRSV) is required for cell-to-cell movement. MP subcellular localization studies using a GFP fusion protein revealed highly punctate structures between neighboring cells, believed to represent plasmodesmata. Deletion of the RNA-binding domain (RBD) of PNRSV MP abolishes the cell-to-cell movement. A mutational analysis on this RBD was performed in order to identify in vivo the features that govern viral transport. Loss of positive charges prevented the cell-to-cell movement even though all mutants showed a similar accumulation level in protoplasts to those observed with the wild-type (wt) MP. Synthetic peptides representing the mutants and wild-type RBDs were used to study RNA-binding affinities by EMSA assays being approximately 20-fold lower in the mutants. Circular dichroism analyses revealed that the secondary structure of the peptides was not significantly affected by mutations. The involvement of the affinity changes between the viral RNA and the MP in the viral cell-to-cell movement is discussed.
Carmen Herranz, Ma; Sanchez-Navarro, Jesus-Angel; Sauri, Ana; Mingarro, Ismael; Pallas, Vicente
2005-01-01
The movement protein (MP) of Prunus necrotic ringspot virus (PNRSV) is required for cell-to-cell movement. MP subcellular localization studies using a GFP fusion protein revealed highly punctate structures between neighboring cells, believed to represent plasmodesmata. Deletion of the RNA-binding domain (RBD) of PNRSV MP abolishes the cell-to-cell movement. A mutational analysis on this RBD was performed in order to identify in vivo the features that govern viral transport. Loss of positive charges prevented the cell-to-cell movement even though all mutants showed a similar accumulation level in protoplasts to those observed with the wild-type (wt) MP. Synthetic peptides representing the mutants and wild-type RBDs were used to study RNA-binding affinities by EMSA assays being approximately 20-fold lower in the mutants. Circular dichroism analyses revealed that the secondary structure of the peptides was not significantly affected by mutations. The involvement of the affinity changes between the viral RNA and the MP in the viral cell-to-cell movement is discussed
As, van H.
2007-01-01
Water content and hydraulic conductivity, including transport within cells, over membranes, cell-to-cell, and long-distance xylem and phloem transport, are strongly affected by plant water stress. By being able to measure these transport processes non-invasely in the intact plant situation in
Shang, Yunlong; Zhang, Chenghui; Cui, Naxin
2015-01-01
these difficulties, an innovative direct cell-to-cell battery equalizer based on quasi-resonant LC converter (QRLCC) and boost DC-DC converter (BDDC) is proposed. The QRLCC is employed to gain zero-current switching (ZCS), leading to a reduction of power losses. The BDDC is employed to enhance the equalization...
Cytoskeleton dynamics: Fluctuations within the network
Bursac, Predrag; Fabry, Ben; Trepat, Xavier; Lenormand, Guillaume; Butler, James P.; Wang, Ning; Fredberg, Jeffrey J.; An, Steven S.
2007-01-01
Out-of-equilibrium systems, such as the dynamics of a living cytoskeleton (CSK), are inherently noisy with fluctuations arising from the stochastic nature of the underlying biochemical and molecular events. Recently, such fluctuations within the cell were characterized by observing spontaneous nano-scale motions of an RGD-coated microbead bound to the cell surface [Bursac et al., Nat. Mater. 4 (2005) 557-561]. While these reported anomalous bead motions represent a molecular level reorganization (remodeling) of microstructures in contact with the bead, a precise nature of these cytoskeletal constituents and forces that drive their remodeling dynamics are largely unclear. Here, we focused upon spontaneous motions of an RGD-coated bead and, in particular, assessed to what extent these motions are attributable to (i) bulk cell movement (cell crawling), (ii) dynamics of focal adhesions, (iii) dynamics of lipid membrane, and/or (iv) dynamics of the underlying actin CSK driven by myosin motors
Extremal-point densities of interface fluctuations
Toroczkai, Z.; Korniss, G.; Das Sarma, S.; Zia, R. K. P.
2000-01-01
We introduce and investigate the stochastic dynamics of the density of local extrema (minima and maxima) of nonequilibrium surface fluctuations. We give a number of analytic results for interface fluctuations described by linear Langevin equations, and for on-lattice, solid-on-solid surface-growth models. We show that, in spite of the nonuniversal character of the quantities studied, their behavior against the variation of the microscopic length scales can present generic features, characteristic of the macroscopic observables of the system. The quantities investigated here provide us with tools that give an unorthodox approach to the dynamics of surface morphologies: a statistical analysis from the short-wavelength end of the Fourier decomposition spectrum. In addition to surface-growth applications, our results can be used to solve the asymptotic scalability problem of massively parallel algorithms for discrete-event simulations, which are extensively used in Monte Carlo simulations on parallel architectures. (c) 2000 The American Physical Society
Studies of Fluctuation Processes in Nuclear Collisions
Ayik, Sakir [Tennessee Technological Univ., Cookeville, TN (United States). Dept. of Physics
2016-04-14
fluctuation mechanism do not play an important role at low energies and the mean-field fluctuations provide the dominant mechanism. The PI developed a stochastic mean-field (SMF) approach for nuclear dynamics by incorporating zero-point and thermal fluctuations of the initial state. This improvement provides an approximate description of quantal fluctuations of the collective motion, which was missing in the standard mean-field approach. We carried out a number of applications of the SMF approach for dynamics of spinodal instabilities in nuclear matter and the nucleon exchange mechanism in the quasi fission reactions. Further applications of the approach are currently in progress.
Stochastic modeling of mass transport in porous media
Lim, Seung Cheol; Lee, Kun Jai
1990-01-01
The stochastic moments analysis technique is developed to investigate radionuclide migration in geologic porous media. The mechanisms for radionuclide transport are assumed to be advection in the micropore, radioactive decay of the species, and sorption on the pore wall. Two covariance functions of groundwater velocity, retardation factor, and concentration are derived to incorporate the geologic parameter uncertainty in porous media of small medium dispersivity. The parametric studies show that the correlation length of groundwater velocity has significant influence on the migration behavior of radionuclide. Macro dispersivity is dominantly affected by the fluctuation of groundwater velocity, while the fluctuation of retardation factor has a considerable effect on the retarded stochastic velocity. The upper estimated concentration evaluated from this stochastic moments analysis can be used as a practical conservative value for the performance assessment of nuclear waste repository
Superconductivity and spin fluctuations
Scalapino, D.J.
1999-01-01
The organizers of the Memorial Session for Herman Rietschel asked that the author review some of the history of the interplay of superconductivity and spin fluctuations. Initially, Berk and Schrieffer showed how paramagnon spin fluctuations could suppress superconductivity in nearly-ferromagnetic materials. Following this, Rietschel and various co-workers wrote a number of papers in which they investigated the role of spin fluctuations in reducing the Tc of various electron-phonon superconductors. Paramagnon spin fluctuations are also believed to provide the p-wave pairing mechanism responsible for the superfluid phases of 3 He. More recently, antiferromagnetic spin fluctuations have been proposed as the mechanism for d-wave pairing in the heavy-fermion superconductors and in some organic materials as well as possibly the high-Tc cuprates. Here the author will review some of this early history and discuss some of the things he has learned more recently from numerical simulations
Stochastic analytic regularization
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)
Instantaneous stochastic perturbation theory
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.
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
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.
The interpolation method of stochastic functions and the stochastic variational principle
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
Joint probability distributions and fluctuation theorems
García-García, Reinaldo; Kolton, Alejandro B; Domínguez, Daniel; Lecomte, Vivien
2012-01-01
We derive various exact results for Markovian systems that spontaneously relax to a non-equilibrium steady state by using joint probability distribution symmetries of different entropy production decompositions. The analytical approach is applied to diverse problems such as the description of the fluctuations induced by experimental errors, for unveiling symmetries of correlation functions appearing in fluctuation–dissipation relations recently generalized to non-equilibrium steady states, and also for mapping averages between different trajectory-based dynamical ensembles. Many known fluctuation theorems arise as special instances of our approach for particular twofold decompositions of the total entropy production. As a complement, we also briefly review and synthesize the variety of fluctuation theorems applying to stochastic dynamics of both continuous systems described by a Langevin dynamics and discrete systems obeying a Markov dynamics, emphasizing how these results emerge from distinct symmetries of the dynamical entropy of the trajectory followed by the system. For Langevin dynamics, we embed the 'dual dynamics' with a physical meaning, and for Markov systems we show how the fluctuation theorems translate into symmetries of modified evolution operators
Stochastic quantization and gravity
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)
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...
Single-particle stochastic heat engine
Rana, Shubhashis; Pal, P. S.; Saha, Arnab; Jayannavar, A. M.
2014-10-01
We have performed an extensive analysis of a single-particle stochastic heat engine constructed by manipulating a Brownian particle in a time-dependent harmonic potential. The cycle consists of two isothermal steps at different temperatures and two adiabatic steps similar to that of a Carnot engine. The engine shows qualitative differences in inertial and overdamped regimes. All the thermodynamic quantities, including efficiency, exhibit strong fluctuations in a time periodic steady state. The fluctuations of stochastic efficiency dominate over the mean values even in the quasistatic regime. Interestingly, our system acts as an engine provided the temperature difference between the two reservoirs is greater than a finite critical value which in turn depends on the cycle time and other system parameters. This is supported by our analytical results carried out in the quasistatic regime. Our system works more reliably as an engine for large cycle times. By studying various model systems, we observe that the operational characteristics are model dependent. Our results clearly rule out any universal relation between efficiency at maximum power and temperature of the baths. We have also verified fluctuation relations for heat engines in time periodic steady state.
Discrete stochastic charging of aggregate grains
Matthews, Lorin S.; Shotorban, Babak; Hyde, Truell W.
2018-05-01
Dust particles immersed in a plasma environment become charged through the collection of electrons and ions at random times, causing the dust charge to fluctuate about an equilibrium value. Small grains (with radii less than 1 μm) or grains in a tenuous plasma environment are sensitive to single additions of electrons or ions. Here we present a numerical model that allows examination of discrete stochastic charge fluctuations on the surface of aggregate grains and determines the effect of these fluctuations on the dynamics of grain aggregation. We show that the mean and standard deviation of charge on aggregate grains follow the same trends as those predicted for spheres having an equivalent radius, though aggregates exhibit larger variations from the predicted values. In some plasma environments, these charge fluctuations occur on timescales which are relevant for dynamics of aggregate growth. Coupled dynamics and charging models show that charge fluctuations tend to produce aggregates which are much more linear or filamentary than aggregates formed in an environment where the charge is stationary.
Stochastic energy balancing in substation energy management
Hassan Shirzeh
2015-12-01
Full Text Available In the current research, a smart grid is considered as a network of distributed interacting nodes represented by renewable energy sources, storage and loads. The source nodes become active or inactive in a stochastic manner due to the intermittent nature of natural resources such as wind and solar irradiance. Prediction and stochastic modelling of electrical energy flow is a critical task in such a network in order to achieve load levelling and/or peak shaving in order to minimise the fluctuation between off-peak and peak energy demand. An effective approach is proposed to model and administer the behaviour of source nodes in this grid through a scheduling strategy control algorithm using the historical data collected from the system. The stochastic model predicts future power consumption/injection to determine the power required for storage components. The stochastic models developed based on the Box-Jenkins method predict the most efficient state of the electrical energy flow between a distribution network and nodes and minimises the peak demand and off-peak consumption of acquiring electrical energy from the main grid. The performance of the models is validated against the autoregressive moving average (ARIMA and the Markov chain models used in previous work. The results demonstrate that the proposed method outperforms both the ARIMA and the Markov chain model in terms of forecast accuracy. Results are presented, the strengths and limitations of the approach are discussed, and possible future work is described.
Entropy Production and Fluctuation Theorems for Active Matter
Mandal, Dibyendu; Klymko, Katherine; DeWeese, Michael R.
2017-12-01
Active biological systems reside far from equilibrium, dissipating heat even in their steady state, thus requiring an extension of conventional equilibrium thermodynamics and statistical mechanics. In this Letter, we have extended the emerging framework of stochastic thermodynamics to active matter. In particular, for the active Ornstein-Uhlenbeck model, we have provided consistent definitions of thermodynamic quantities such as work, energy, heat, entropy, and entropy production at the level of single, stochastic trajectories and derived related fluctuation relations. We have developed a generalization of the Clausius inequality, which is valid even in the presence of the non-Hamiltonian dynamics underlying active matter systems. We have illustrated our results with explicit numerical studies.
Control of stochastic resonance in bistable systems by using periodic signals
Min, Lin; Li-Min, Fang; Yong-Jun, Zheng
2009-01-01
According to the characteristic structure of double wells in bistable systems, this paper analyses stochastic fluctuations in the single potential well and probability transitions between the two potential wells and proposes a method of controlling stochastic resonance by using a periodic signal. Results of theoretical analysis and numerical simulation show that the phenomenon of stochastic resonance happens when the time scales of the periodic signal and the noise-induced probability transitions between the two potential wells achieve stochastic synchronization. By adding a bistable system with a controllable periodic signal, fluctuations in the single potential well can be effectively controlled, thus affecting the probability transitions between the two potential wells. In this way, an effective control can be achieved which allows one to either enhance or realize stochastic resonance
Cotter, C J; Gottwald, G A; Holm, D D
2017-09-01
In Holm (Holm 2015 Proc. R. Soc. A 471 , 20140963. (doi:10.1098/rspa.2014.0963)), stochastic fluid equations were derived by employing a variational principle with an assumed stochastic Lagrangian particle dynamics. Here we show that the same stochastic Lagrangian dynamics naturally arises in a multi-scale decomposition of the deterministic Lagrangian flow map into a slow large-scale mean and a rapidly fluctuating small-scale map. We employ homogenization theory to derive effective slow stochastic particle dynamics for the resolved mean part, thereby obtaining stochastic fluid partial equations in the Eulerian formulation. To justify the application of rigorous homogenization theory, we assume mildly chaotic fast small-scale dynamics, as well as a centring condition. The latter requires that the mean of the fluctuating deviations is small, when pulled back to the mean flow.
Hadronic Correlations and Fluctuations
Koch, Volker
2008-10-09
We will provide a review of some of the physics which can be addressed by studying fluctuations and correlations in heavy ion collisions. We will discuss Lattice QCD results on fluctuations and correlations and will put them into context with observables which have been measured in heavy-ion collisions. Special attention will be given to the QCD critical point and the first order co-existence region, and we will discuss how the measurement of fluctuations and correlations can help in an experimental search for non-trivial structures in the QCD phase diagram.
Quantum fluctuations and inflation
Bardeen, J.M.; Bublik, G.J.
1986-05-01
We study the effect of quantum fluctuations on the roll-down rate of the inflation field in a semiclassical approximation; this is done by treating the inflation field as a classical random field. The quantum fluctuations are simulated by a noise term in the equation of motion. We consider two different inflationary scenarios (new and chaotic inflation) and find that the roll-down rate of the median value of the inflation field is increased by the quantum fluctuations. Non-linear effects may become important in the later stages of the inflationary regime. 8 refs., 2 figs
Quantum fluctuations and inflation
Bardeen, J.M.; Bublik, G.J.
1987-01-01
The authors study the effect of quantum fluctuations on the roll-down rate of the inflation field in a semiclassical approximation; this is done by treating the inflation field as a classical random field. The quantum fluctuations are simulated by a noise term in the equation of motion. Two different inflationary scenarios (new and chaotic inflation) are considered and it is found that the roll-down rate of the median value of the inflation field is increased by the quantum fluctuations. Non-linear effects may become important in the later stages of the inflationary regime. (author)
Studies of fluctuation processes in nuclear collisions
Ayik, S.
1991-02-01
This report summarizes the progress on grant No. DE-FG05-89ER40530 during the period April 15, 1990 to February 15, 1991. Our studies of heavy-ion collisions in the framework of ''a stochastic one-body transport model'' has progress in several directions. We developed a method for obtaining approximate numerical solutions of the transport-equation in semi-classical limit, i.e., Boltzmann-Langevin equation, and tested the method in realistic cases of heavy-ion collisions at energies below 100 MeV per nucleon. Some results of the numerical simulations for a head-on collision of 12 C + 12 C system is included in this report. Work has also continued on studying the stochastic one-body transport model in a quantal representation, which provides a microscopic basis for a consistent description of dissipation and fluctuation properties of large amplitude collective nuclear motion. The previous derivation of the stochastic one-body transport model was presented within the density matrix formalisam. We generalized this treatment and proposed an alternative derivation of the model by employing the Green's function approach within the real-time path formalism of Keldish. One manuscript has been submitted to Nucl. Phys. A for publication. Two other manuscripts are in preparation for publication. Several seminars and contributed talks were presented at various meeting
Enhancement of large fluctuations to extinction in adaptive networks
Hindes, Jason; Schwartz, Ira B.; Shaw, Leah B.
2018-01-01
During an epidemic, individual nodes in a network may adapt their connections to reduce the chance of infection. A common form of adaption is avoidance rewiring, where a noninfected node breaks a connection to an infected neighbor and forms a new connection to another noninfected node. Here we explore the effects of such adaptivity on stochastic fluctuations in the susceptible-infected-susceptible model, focusing on the largest fluctuations that result in extinction of infection. Using techniques from large-deviation theory, combined with a measurement of heterogeneity in the susceptible degree distribution at the endemic state, we are able to predict and analyze large fluctuations and extinction in adaptive networks. We find that in the limit of small rewiring there is a sharp exponential reduction in mean extinction times compared to the case of zero adaption. Furthermore, we find an exponential enhancement in the probability of large fluctuations with increased rewiring rate, even when holding the average number of infected nodes constant.
Concentration fluctuations in gas releases by industrial accidents
Nielsen, M.; Chatwin, P.C.; Ejsing Jørgensen, Hans
2002-01-01
The COFIN project studied existing remote-sensing Lidar data on concentration fluctuations in atmospheric dispersion from continuous sources at ground level. Fluctuations are described by stochastic models developed by a combination of statisticalanalyses and surface-layer scaling. The statistical...... and the probability distribution for the plume centreline. The distance-neighbour function generalizedfor higher-order statistics has a universal exponential shape. Simulation tools for concentration fluctuations have been developed for either multiple correlated time series or multi-dimensional fields. These tools...... moments and probability density distribution of the fluctuations are most accurately determined in a frame of reference following the instantaneous plume centreline. The spatial distribution of thesemoments is universal with a gaussian core and exponential tails. The instantaneous plume width...
Fluorescence fluctuation spectroscopy (FFS)
Tetin, Sergey
2012-01-01
This new volume of Methods in Enzymology continues the legacy of this premier serial with quality chapters authored by leaders in the field. This volume covers fluorescence fluctuation spectroscopy and includes chapters on such topics as Förster resonance energy transfer (fret) with fluctuation algorithms, protein corona on nanoparticles by FCS, and FFS approaches to the study of receptors in live cells. Continues the legacy of this premier serial with quality chapters authored by leaders in the field Covers fluorescence fluctuation spectroscopy Contains chapters on such topics as Förster resonance energy transfer (fret) with fluctuation algorithms, protein corona on nanoparticles by FCS, and FFS approaches to the study of receptors in live cells.
Fully Quantum Fluctuation Theorems
Åberg, Johan
2018-02-01
Systems that are driven out of thermal equilibrium typically dissipate random quantities of energy on microscopic scales. Crooks fluctuation theorem relates the distribution of these random work costs to the corresponding distribution for the reverse process. By an analysis that explicitly incorporates the energy reservoir that donates the energy and the control system that implements the dynamic, we obtain a quantum generalization of Crooks theorem that not only includes the energy changes in the reservoir but also the full description of its evolution, including coherences. Moreover, this approach opens up the possibility for generalizations of the concept of fluctuation relations. Here, we introduce "conditional" fluctuation relations that are applicable to nonequilibrium systems, as well as approximate fluctuation relations that allow for the analysis of autonomous evolution generated by global time-independent Hamiltonians. We furthermore extend these notions to Markovian master equations, implicitly modeling the influence of the heat bath.
Sequential stochastic optimization
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
Remarks on stochastic acceleration
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.)
Lectures on Dynamics of Stochastic Systems
Klyatskin, Valery I
2010-01-01
Fluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. Models naturally render to statistical description, where random processes and fields express the input parameters and solutions. The fundamental problem of stochastic dynamics is to identify the essential characteristics of system (its state and evolution), and relate those to the input parameters of the system and initial data. This book is a revised a
On the stochastic quantization of gauge theories
Jona-Lasinio, G.; Parrinello, C.
1988-11-03
The non-gradient stochastic quantization scheme for gauge theories proposed by Zwanziger is analyzed in the semiclassical limit. Using ideas from the theory of small random perturbations of dynamical systems we derive a lower bound for the equilibrium distribution in a neighbourhood of a stable critical point of the drift. In this approach the calculation of the equilibrium distribution is reduced to the problem of finding a minimum for the large fluctuation functional associated to the Langevin equation. Our estimate follows from a simple upper bound for this minimum; in addition to the Yang-Mills action a gauge-fixing term which tends to suppress Gribov copies appears.
Aparicio, Frederic; Pallás, Vicente; Sánchez-Navarro, Jesús
2010-07-01
The movement protein (MP) of Prunus necrotic ringspot virus (PNRSV) is required for viral transport. Previous analysis with MPs of other members of the family Bromoviridae has shown that the C-terminal part of these MPs plays a critical role in the interaction with the cognate coat protein (CP) and in cell-to-cell transport. Bimolecular fluorescence complementation and overlay analysis confirm an interaction between the C-terminal 38 aa of PNRSV MP and its cognate CP. Mutational analysis of the C-terminal region of the PNRSV MP revealed that its C-terminal 38 aa are dispensable for virus transport, however, the 4 aa preceding the dispensable C terminus are necessary to target the MP to the plasmodesmata and for the functionality of the protein. The capacity of the PNRSV MP to use either a CP-dependent or a CP-independent cell-to-cell transport is discussed.
Scale-invariant curvature fluctuations from an extended semiclassical gravity
Pinamonti, Nicola, E-mail: pinamont@dima.unige.it, E-mail: siemssen@dima.unige.it [Dipartimento di Matematica, Università di Genova, Via Dodecaneso 35, 16146 Genova (Italy); INFN Sezione di Genova, Via Dodecaneso 33, 16146 Genova (Italy); Siemssen, Daniel, E-mail: pinamont@dima.unige.it, E-mail: siemssen@dima.unige.it [Dipartimento di Matematica, Università di Genova, Via Dodecaneso 35, 16146 Genova (Italy)
2015-02-15
We present an extension of the semiclassical Einstein equations which couple n-point correlation functions of a stochastic Einstein tensor to the n-point functions of the quantum stress-energy tensor. We apply this extension to calculate the quantum fluctuations during an inflationary period, where we take as a model a massive conformally coupled scalar field on a perturbed de Sitter space and describe how a renormalization independent, almost-scale-invariant power spectrum of the scalar metric perturbation is produced. Furthermore, we discuss how this model yields a natural basis for the calculation of non-Gaussianities of the considered metric fluctuations.
A generalized integral fluctuation theorem for general jump processes
Liu Fei; Ouyang Zhongcan; Luo Yupin; Huang Mingchang
2009-01-01
Using the Feynman-Kac and Cameron-Martin-Girsanov formulae, we obtain a generalized integral fluctuation theorem (GIFT) for discrete jump processes by constructing a time-invariable inner product. The existing discrete IFTs can be derived as its specific cases. A connection between our approach and the conventional time-reversal method is also established. Unlike the latter approach that has been extensively employed in the existing literature, our approach can naturally bring out the definition of a time reversal of a Markovian stochastic system. Additionally, we find that the robust GIFT usually does not result in a detailed fluctuation theorem. (fast track communication)
Dissipation and fluctuation of quantum fields in expanding universes
Morikawa, M.
1990-01-01
A stochastic dynamics of a long-wavelength part of a scalar field in an expanding universe is derived by using the influence functional method. Dissipation as well as fluctuation are derived for general parameters: a mass, a coupling to the scalar curvature, and a cutoff scale parameter. A dissipation-fluctuation relation is found with a temperature which is proportional to the Hawking temperature, but system dependent. The method is further applied to an expanding universe with a power law and yields the dispersion which agrees with that obtained by the regularization method. The back reaction to the background de Sitter space itself is also obtained
The stochastic resonance for the incidence function model of metapopulation
Li, Jiang-Cheng; Dong, Zhi-Wei; Zhou, Ruo-Wei; Li, Yun-Xian; Qian, Zhen-Wei
2017-06-01
A stochastic model with endogenous and exogenous periodicities is proposed in this paper on the basis of metapopulation dynamics to model the crop yield losses due to pests and diseases. The rationale is that crop yield losses occur because the physiology of the growing crop is negatively affected by pests and diseases in a dynamic way over time as crop both grows and develops. Metapopulation dynamics can thus be used to model the resultant crop yield losses. The stochastic metapopulation process is described by using the Simplified Incidence Function model (IFM). Compared to the original IFMs, endogenous and exogenous periodicities are considered in the proposed model to handle the cyclical patterns observed in pest infestations, diseases epidemics, and exogenous affecting factors such as temperature and rainfalls. Agricultural loss data in China are used to fit the proposed model. Experimental results demonstrate that: (1) Model with endogenous and exogenous periodicities is a better fit; (2) When the internal system fluctuations and external environmental fluctuations are negatively correlated, EIL or the cost of loss is monotonically increasing; when the internal system fluctuations and external environmental fluctuations are positively correlated, an outbreak of pests and diseases might occur; (3) If the internal system fluctuations and external environmental fluctuations are positively correlated, an optimal patch size can be identified which will greatly weaken the effects of external environmental influence and hence inhibit pest infestations and disease epidemics.
On stochastic differential equations with random delay
Krapivsky, P L; Luck, J M; Mallick, K
2011-01-01
We consider stochastic dynamical systems defined by differential equations with a uniform random time delay. The latter equations are shown to be equivalent to deterministic higher-order differential equations: for an nth-order equation with random delay, the corresponding deterministic equation has order n + 1. We analyze various examples of dynamical systems of this kind, and find a number of unusual behaviors. For instance, for the harmonic oscillator with random delay, the energy grows as exp((3/2) t 2/3 ) in reduced units. We then investigate the effect of introducing a discrete time step ε. At variance with the continuous situation, the discrete random recursion relations thus obtained have intrinsic fluctuations. The crossover between the fluctuating discrete problem and the deterministic continuous one as ε goes to zero is studied in detail on the example of a first-order linear differential equation
Critical fluctuations in cortical models near instability
Matthew J. Aburn
2012-08-01
Full Text Available Computational studies often proceed from the premise that cortical dynamics operate in a linearly stable domain, where fluctuations dissipate quickly and show only short memory. Studies of human EEG, however, have shown significant autocorrelation at time lags on the scale of minutes, indicating the need to consider regimes where nonlinearities influence the dynamics. Statistical properties such as increased autocorrelation length, increased variance, power-law scaling and bistable switching have been suggested as generic indicators of the approach to bifurcation in nonlinear dynamical systems. We study temporal fluctuations in a widely-employed computational model (the Jansen-Rit model of cortical activity, examining the statistical signatures that accompany bifurcations. Approaching supercritical Hopf bifurcations through tuning of the background excitatory input, we find a dramatic increase in the autocorrelation length that depends sensitively on the direction in phase space of the input fluctuations and hence on which neuronal subpopulation is stochastically perturbed. Similar dependence on the input direction is found in the distribution of fluctuation size and duration, which show power law scaling that extends over four orders of magnitude at the Hopf bifurcation. We conjecture that the alignment in phase space between the input noise vector and the center manifold of the Hopf bifurcation is directly linked to these changes. These results are consistent with the possibility of statistical indicators of linear instability being detectable in real EEG time series. However, even in a simple cortical model, we find that these indicators may not necessarily be visible even when bifurcations are present because their expression can depend sensitively on the neuronal pathway of incoming fluctuations.
Stochastic processes inference theory
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.
Introduction to stochastic calculus
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...
Doberkat, Ernst-Erich
2009-01-01
Combining coalgebraic reasoning, stochastic systems and logic, this volume presents the principles of coalgebraic logic from a categorical perspective. Modal logics are also discussed, including probabilistic interpretations and an analysis of Kripke models.
Approximating Preemptive Stochastic Scheduling
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...
The stochastic goodwill problem
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...
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)
Extension of Nelson's stochastic quantization to finite temperature using thermo field dynamics
Kobayashi, K.; Yamanaka, Y.
2011-01-01
We present an extension of Nelson's stochastic quantum mechanics to finite temperature. Utilizing the formulation of Thermo Field Dynamics (TFD), we can show that Ito's stochastic equations for tilde and non-tilde particle positions reproduce the TFD-type Schroedinger equation which is equivalent to the Liouville-von Neumann equation. In our formalism, the drift terms in the Ito's stochastic equation have the temperature dependence and the thermal fluctuation is induced through the correlation of the non-tilde and tilde particles. We show that our formalism satisfies the position-momentum uncertainty relation at finite temperature. -- Highlights: → Utilizing TFD, we extend Nelson's stochastic method to finite temperature. → We introduce stochastic equations for tilde and non-tilde particles. → Our stochastic equations can reproduce the TFD-type Schroedinger equation. → Our formalism satisfies the uncertainly relation at finite temperature.
Pérez-Pascual, David; Gaudu, Philippe; Fleuchot, Betty; Besset, Colette; Rosinski-Chupin, Isabelle; Guillot, Alain; Monnet, Véronique; Gardan, Rozenn
2015-01-20
Bacteria can communicate with each other to coordinate their biological functions at the population level. In a previous study, we described a cell-to-cell communication system in streptococci that involves a transcriptional regulator belonging to the Rgg family and short hydrophobic peptides (SHPs) that act as signaling molecules. Streptococcus agalactiae, an opportunistic pathogenic bacterium responsible for fatal infections in neonates and immunocompromised adults, has one copy of the shp/rgg locus. The SHP-associated Rgg is called RovS in S. agalactiae. In this study, we found that the SHP/RovS cell-to-cell communication system is active in the strain NEM316 of S. agalactiae, and we identified different partners that are involved in this system, such as the Eep peptidase, the PptAB, and the OppA1-F oligopeptide transporters. We also identified a new target gene controlled by this system and reexamined the regulation of a previously proposed target gene, fbsA, in the context of the SHP-associated RovS system. Furthermore, our results are the first to indicate the SHP/RovS system specificity to host liver and spleen using a murine model, which demonstrates its implication in streptococci virulence. Finally, we observed that SHP/RovS regulation influences S. agalactiae's ability to adhere to and invade HepG2 hepatic cells. Hence, the SHP/RovS cell-to-cell communication system appears to be an essential mechanism that regulates pathogenicity in S. agalactiae and represents an attractive target for the development of new therapeutic strategies. Rgg regulators and their cognate pheromones, called small hydrophobic peptides (SHPs), are present in nearly all streptococcal species. The general pathways of the cell-to-cell communication system in which Rgg and SHP take part are well understood. However, many other players remain unidentified, and the direct targets of the system, as well as its link to virulence, remain unclear. Here, we identified the different players
Interplay between endogenous and exogenous fluctuations in financial markets
Gontis, Vygintas
2016-01-01
We address microscopic, agent based, and macroscopic, stochastic, modeling of the financial markets combining it with the exogenous noise. The interplay between the endogenous dynamics of agents and the exogenous noise is the primary mechanism responsible for the observed long-range dependence and statistical properties of high volatility return intervals. By exogenous noise we mean information flow or/and order flow fluctuations. Numerical results based on the proposed model reveal that the ...
Stochastic resonance based on modulation instability in spatiotemporal chaos.
Han, Jing; Liu, Hongjun; Huang, Nan; Wang, Zhaolu
2017-04-03
A novel dynamic of stochastic resonance in spatiotemporal chaos is presented, which is based on modulation instability of perturbed partially coherent wave. The noise immunity of chaos can be reinforced through this effect and used to restore the coherent signal information buried in chaotic perturbation. A theoretical model with fluctuations term is derived from the complex Ginzburg-Landau equation via Wigner transform. It shows that through weakening the nonlinear threshold and triggering energy redistribution, the coherent component dominates the instability damped by incoherent component. The spatiotemporal output showing the properties of stochastic resonance may provide a potential application of signal encryption and restoration.
Stochastic responses of tumor–immune system with periodic treatment
Li Dong-Xi; Li Ying
2017-01-01
We investigate the stochastic responses of a tumor–immune system competition model with environmental noise and periodic treatment. Firstly, a mathematical model describing the interaction between tumor cells and immune system under external fluctuations and periodic treatment is established based on the stochastic differential equation. Then, sufficient conditions for extinction and persistence of the tumor cells are derived by constructing Lyapunov functions and Ito’s formula. Finally, numerical simulations are introduced to illustrate and verify the results. The results of this work provide the theoretical basis for designing more effective and precise therapeutic strategies to eliminate cancer cells, especially for combining the immunotherapy and the traditional tools. (paper)
INFERENCE AND SENSITIVITY IN STOCHASTIC WIND POWER FORECAST MODELS.
Elkantassi, Soumaya
2017-10-03
Reliable forecasting of wind power generation is crucial to optimal control of costs in generation of electricity with respect to the electricity demand. Here, we propose and analyze stochastic wind power forecast models described by parametrized stochastic differential equations, which introduce appropriate fluctuations in numerical forecast outputs. We use an approximate maximum likelihood method to infer the model parameters taking into account the time correlated sets of data. Furthermore, we study the validity and sensitivity of the parameters for each model. We applied our models to Uruguayan wind power production as determined by historical data and corresponding numerical forecasts for the period of March 1 to May 31, 2016.
INFERENCE AND SENSITIVITY IN STOCHASTIC WIND POWER FORECAST MODELS.
Elkantassi, Soumaya; Kalligiannaki, Evangelia; Tempone, Raul
2017-01-01
Reliable forecasting of wind power generation is crucial to optimal control of costs in generation of electricity with respect to the electricity demand. Here, we propose and analyze stochastic wind power forecast models described by parametrized stochastic differential equations, which introduce appropriate fluctuations in numerical forecast outputs. We use an approximate maximum likelihood method to infer the model parameters taking into account the time correlated sets of data. Furthermore, we study the validity and sensitivity of the parameters for each model. We applied our models to Uruguayan wind power production as determined by historical data and corresponding numerical forecasts for the period of March 1 to May 31, 2016.
Large fluctuations and fixation in evolutionary games
Assaf, Michael; Mobilia, Mauro
2010-01-01
We study large fluctuations in evolutionary games belonging to the coordination and anti-coordination classes. The dynamics of these games, modeling cooperation dilemmas, is characterized by a coexistence fixed point separating two absorbing states. We are particularly interested in the problem of fixation that refers to the possibility that a few mutants take over the entire population. Here, the fixation phenomenon is induced by large fluctuations and is investigated by a semiclassical WKB (Wentzel–Kramers–Brillouin) theory generalized to treat stochastic systems possessing multiple absorbing states. Importantly, this method allows us to analyze the combined influence of selection and random fluctuations on the evolutionary dynamics beyond the weak selection limit often considered in previous works. We accurately compute, including pre-exponential factors, the probability distribution function in the long-lived coexistence state and the mean fixation time necessary for a few mutants to take over the entire population in anti-coordination games, and also the fixation probability in the coordination class. Our analytical results compare excellently with extensive numerical simulations. Furthermore, we demonstrate that our treatment is superior to the Fokker–Planck approximation when the selection intensity is finite
Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns.
Andrea Maesani
2015-11-01
Full Text Available The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs-locomotor bouts-matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior.
Separating intrinsic from extrinsic fluctuations in dynamic biological systems.
Hilfinger, Andreas; Paulsson, Johan
2011-07-19
From molecules in cells to organisms in ecosystems, biological populations fluctuate due to the intrinsic randomness of individual events and the extrinsic influence of changing environments. The combined effect is often too complex for effective analysis, and many studies therefore make simplifying assumptions, for example ignoring either intrinsic or extrinsic effects to reduce the number of model assumptions. Here we mathematically demonstrate how two identical and independent reporters embedded in a shared fluctuating environment can be used to identify intrinsic and extrinsic noise terms, but also how these contributions are qualitatively and quantitatively different from what has been previously reported. Furthermore, we show for which classes of biological systems the noise contributions identified by dual-reporter methods correspond to the noise contributions predicted by correct stochastic models of either intrinsic or extrinsic mechanisms. We find that for broad classes of systems, the extrinsic noise from the dual-reporter method can be rigorously analyzed using models that ignore intrinsic stochasticity. In contrast, the intrinsic noise can be rigorously analyzed using models that ignore extrinsic stochasticity only under very special conditions that rarely hold in biology. Testing whether the conditions are met is rarely possible and the dual-reporter method may thus produce flawed conclusions about the properties of the system, particularly about the intrinsic noise. Our results contribute toward establishing a rigorous framework to analyze dynamically fluctuating biological systems.
Universal mesoscopic conductance fluctuations
Evangelou, S.N.
1992-01-01
The theory of conductance fluctuations in disordered metallic systems with size large compared to the mean free path of the electron but small compared to localization length is considered. It is demonstrates that fluctuations have an universal character and are due to repulsion between levels and spectral rigidity. The basic fluctuation measures for the energy spectrum in the mesoscopic regime of disordered systems are consistent with the Gaussian random matrix ensemble predictions. Although our disordered electron random matrix ensemble does not belong to the Gaussian ensemble the two ensembles turn out to be essentially similar. The level repulsion and the spectral rigidity found in nuclear spectra should also be observed in the metallic regime of Anderson localization. 7 refs. (orig.)
V.M. Loktev
2008-09-01
Full Text Available We analyze the spectral properties of a phenomenological model for a weakly doped two-dimensional antiferromagnet, in which the carriers move within one of the two sublattices where they were introduced. Such a constraint results in the free carrier spectra with the maxima at k=(± π/2 , ± π/2 observed in some cuprates. We consider the spectral properties of the model by taking into account fluctuations of the spins in the antiferromagnetic background. We show that such fluctuations lead to a non-pole-like structure of the single-hole Green's function and these fluctuations can be responsible for some anomalous "strange metal" properties of underdoped cuprates in the nonsuperconducting regime.
Cao, Xiaobin
2011-01-15
The quasi-one-dimensional systems exhibit some unusual phenomenon, such as the Peierls instability, the pseudogap phenomena and the absence of a Fermi-Dirac distribution function line shape in the photoemission spectroscopy. Ever since the discovery of materials with highly anisotropic properties, it has been recognized that fluctuations play an important role above the three-dimensional phase transition. This regime where the precursor fluctuations are presented can be described by the so called fluctuating gap model (FGM) which was derived from the Froehlich Hamiltonian to study the low energy physics of the one-dimensional electron-phonon system. Not only is the FGM of great interest in the context of quasi-one-dimensional materials, liquid metal and spin waves above T{sub c} in ferromagnets, but also in the semiclassical approximation of superconductivity, it is possible to replace the original three-dimensional problem by a directional average over effectively one-dimensional problem which in the weak coupling limit is described by the FGM. In this work, we investigate the FGM in a wide temperature range with different statistics of the order parameter fluctuations. We derive a formally exact solution to this problem and calculate the density of states, the spectral function and the optical conductivity. In our calculation, we show that a Dyson singularity appears in the low energy density of states for Gaussian fluctuations in the commensurate case. In the incommensurate case, there is no such kind of singularity, and the zero frequency density of states varies differently as a function of the correlation lengths for different statistics of the order parameter fluctuations. Using the density of states we calculated with non-Gaussian order parameter fluctuations, we are able to calculate the static spin susceptibility which agrees with the experimental data very well. In the calculation of the spectral functions, we show that as the correlation increases, the
Cao, Xiaobin
2011-01-01
The quasi-one-dimensional systems exhibit some unusual phenomenon, such as the Peierls instability, the pseudogap phenomena and the absence of a Fermi-Dirac distribution function line shape in the photoemission spectroscopy. Ever since the discovery of materials with highly anisotropic properties, it has been recognized that fluctuations play an important role above the three-dimensional phase transition. This regime where the precursor fluctuations are presented can be described by the so called fluctuating gap model (FGM) which was derived from the Froehlich Hamiltonian to study the low energy physics of the one-dimensional electron-phonon system. Not only is the FGM of great interest in the context of quasi-one-dimensional materials, liquid metal and spin waves above T c in ferromagnets, but also in the semiclassical approximation of superconductivity, it is possible to replace the original three-dimensional problem by a directional average over effectively one-dimensional problem which in the weak coupling limit is described by the FGM. In this work, we investigate the FGM in a wide temperature range with different statistics of the order parameter fluctuations. We derive a formally exact solution to this problem and calculate the density of states, the spectral function and the optical conductivity. In our calculation, we show that a Dyson singularity appears in the low energy density of states for Gaussian fluctuations in the commensurate case. In the incommensurate case, there is no such kind of singularity, and the zero frequency density of states varies differently as a function of the correlation lengths for different statistics of the order parameter fluctuations. Using the density of states we calculated with non-Gaussian order parameter fluctuations, we are able to calculate the static spin susceptibility which agrees with the experimental data very well. In the calculation of the spectral functions, we show that as the correlation increases, the quasi
Stochastic inflation in phase space: is slow roll a stochastic attractor?
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.
Information Dynamics of a Nonlinear Stochastic Nanopore System
Claire Gilpin
2018-03-01
Full Text Available Nanopores have become a subject of interest in the scientific community due to their potential uses in nanometer-scale laboratory and research applications, including infectious disease diagnostics and DNA sequencing. Additionally, they display behavioral similarity to molecular and cellular scale physiological processes. Recent advances in information theory have made it possible to probe the information dynamics of nonlinear stochastic dynamical systems, such as autonomously fluctuating nanopore systems, which has enhanced our understanding of the physical systems they model. We present the results of local (LER and specific entropy rate (SER computations from a simulation study of an autonomously fluctuating nanopore system. We learn that both metrics show increases that correspond to fluctuations in the nanopore current, indicating fundamental changes in information generation surrounding these fluctuations.
Stochastic nature of series of waiting times
Anvari, Mehrnaz; Aghamohammadi, Cina; Dashti-Naserabadi, H.; Salehi, E.; Behjat, E.; Qorbani, M.; Khazaei Nezhad, M.; Zirak, M.; Hadjihosseini, Ali; Peinke, Joachim; Tabar, M. Reza Rahimi
2013-06-01
Although fluctuations in the waiting time series have been studied for a long time, some important issues such as its long-range memory and its stochastic features in the presence of nonstationarity have so far remained unstudied. Here we find that the “waiting times” series for a given increment level have long-range correlations with Hurst exponents belonging to the interval 1/2
Front Propagation in Stochastic Neural Fields
Bressloff, Paul C.
2012-01-01
We analyze the effects of extrinsic multiplicative noise on front propagation in a scalar neural field with excitatory connections. Using a separation of time scales, we represent the fluctuating front in terms of a diffusive-like displacement (wandering) of the front from its uniformly translating position at long time scales, and fluctuations in the front profile around its instantaneous position at short time scales. One major result of our analysis is a comparison between freely propagating fronts and fronts locked to an externally moving stimulus. We show that the latter are much more robust to noise, since the stochastic wandering of the mean front profile is described by an Ornstein-Uhlenbeck process rather than a Wiener process, so that the variance in front position saturates in the long time limit rather than increasing linearly with time. Finally, we consider a stochastic neural field that supports a pulled front in the deterministic limit, and show that the wandering of such a front is now subdiffusive. © 2012 Society for Industrial and Applied Mathematics.
Stochastic gravity: a primer with applications
Hu, B L; Verdaguer, E
2003-01-01
Stochastic semiclassical gravity of the 1990s is a theory naturally evolved from semiclassical gravity of the 1970s and 1980s. It improves on the semiclassical Einstein equation with source given by the expectation value of the stress-energy tensor of quantum matter fields in curved spacetime by incorporating an additional source due to their fluctuations. In stochastic semiclassical gravity the main object of interest is the noise kernel, the vacuum expectation value of the (operator-valued) stress-energy bi-tensor, and the centrepiece is the (semiclassical) Einstein-Langevin equation. We describe this new theory via two approaches: the axiomatic and the functional. The axiomatic approach is useful to see the structure of the theory from the framework of semiclassical gravity, showing the link from the mean value of the energy-momentum tensor to their correlation functions. The functional approach uses the Feynman-Vernon influence functional and the Schwinger-Keldysh closed-time-path effective action methods which are convenient for computations. It also brings out the open system concepts and the statistical and stochastic contents of the theory such as dissipation, fluctuations, noise and decoherence. We then describe the applications of stochastic gravity to the backreaction problems in cosmology and black-hole physics. In the first problem, we study the backreaction of conformally coupled quantum fields in a weakly inhomogeneous cosmology. In the second problem, we study the backreaction of a thermal field in the gravitational background of a quasi-static black hole (enclosed in a box) and its fluctuations. These examples serve to illustrate closely the ideas and techniques presented in the first part. This topical review is intended as a first introduction providing readers with some basic ideas and working knowledge. Thus, we place more emphasis here on pedagogy than completeness. (Further discussions of ideas, issues and ongoing research topics can be found
Stochastic gravity: a primer with applications
Hu, B L [Department of Physics, University of Maryland, College Park, MD 20742-4111 (United States); Verdaguer, E [Departament de Fisica Fonamental and CER en Astrofisica Fisica de Particules i Cosmologia, Universitat de Barcelona, Av. Diagonal 647, 08028 Barcelona (Spain)
2003-03-21
Stochastic semiclassical gravity of the 1990s is a theory naturally evolved from semiclassical gravity of the 1970s and 1980s. It improves on the semiclassical Einstein equation with source given by the expectation value of the stress-energy tensor of quantum matter fields in curved spacetime by incorporating an additional source due to their fluctuations. In stochastic semiclassical gravity the main object of interest is the noise kernel, the vacuum expectation value of the (operator-valued) stress-energy bi-tensor, and the centrepiece is the (semiclassical) Einstein-Langevin equation. We describe this new theory via two approaches: the axiomatic and the functional. The axiomatic approach is useful to see the structure of the theory from the framework of semiclassical gravity, showing the link from the mean value of the energy-momentum tensor to their correlation functions. The functional approach uses the Feynman-Vernon influence functional and the Schwinger-Keldysh closed-time-path effective action methods which are convenient for computations. It also brings out the open system concepts and the statistical and stochastic contents of the theory such as dissipation, fluctuations, noise and decoherence. We then describe the applications of stochastic gravity to the backreaction problems in cosmology and black-hole physics. In the first problem, we study the backreaction of conformally coupled quantum fields in a weakly inhomogeneous cosmology. In the second problem, we study the backreaction of a thermal field in the gravitational background of a quasi-static black hole (enclosed in a box) and its fluctuations. These examples serve to illustrate closely the ideas and techniques presented in the first part. This topical review is intended as a first introduction providing readers with some basic ideas and working knowledge. Thus, we place more emphasis here on pedagogy than completeness. (Further discussions of ideas, issues and ongoing research topics can be found
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
A stochastic model for quantum measurement
Budiyono, Agung
2013-01-01
We develop a statistical model of microscopic stochastic deviation from classical mechanics based on a stochastic process with a transition probability that is assumed to be given by an exponential distribution of infinitesimal stationary action. We apply the statistical model to stochastically modify a classical mechanical model for the measurement of physical quantities reproducing the prediction of quantum mechanics. The system+apparatus always has a definite configuration at all times, as in classical mechanics, fluctuating randomly following a continuous trajectory. On the other hand, the wavefunction and quantum mechanical Hermitian operator corresponding to the physical quantity arise formally as artificial mathematical constructs. During a single measurement, the wavefunction of the whole system+apparatus evolves according to a Schrödinger equation and the configuration of the apparatus acts as the pointer of the measurement so that there is no wavefunction collapse. We will also show that while the outcome of each single measurement event does not reveal the actual value of the physical quantity prior to measurement, its average in an ensemble of identical measurements is equal to the average of the actual value of the physical quantity prior to measurement over the distribution of the configuration of the system. (paper)
Models of the stochastic activity of neurones
Holden, Arun Vivian
1976-01-01
These notes have grown from a series of seminars given at Leeds between 1972 and 1975. They represent an attempt to gather together the different kinds of model which have been proposed to account for the stochastic activity of neurones, and to provide an introduction to this area of mathematical biology. A striking feature of the electrical activity of the nervous system is that it appears stochastic: this is apparent at all levels of recording, ranging from intracellular recordings to the electroencephalogram. The chapters start with fluctuations in membrane potential, proceed through single unit and synaptic activity and end with the behaviour of large aggregates of neurones: L have chgaen this seque~~e\\/~~';uggest that the interesting behaviourr~f :the nervous system - its individuality, variability and dynamic forms - may in part result from the stochastic behaviour of its components. I would like to thank Dr. Julio Rubio for reading and commenting on the drafts, Mrs. Doris Beighton for producing the fin...
Stochastic phenomena in a fiber Raman amplifier
Kalashnikov, Vladimir [Aston Institute of Photonic Technologies, Aston University, Birmingham (United Kingdom); Institute of Photonics, Vienna University of Technology (Austria); Sergeyev, Sergey V. [Aston Institute of Photonic Technologies, Aston University, Birmingham (United Kingdom); Ania-Castanon, Juan Diego [Instituto de Optica CSIC, Madrid (Spain); Jacobsen, Gunnar [Acreo, Kista (Sweden); Popov, Sergei [Royal Institute of Technology (KTH), Stockholm (Sweden)
2017-01-15
The interplay of such cornerstones of modern nonlinear fiber optics as a nonlinearity, stochasticity and polarization leads to variety of the noise induced instabilities including polarization attraction and escape phenomena harnessing of which is a key to unlocking the fiber optic systems specifications required in high resolution spectroscopy, metrology, biomedicine and telecommunications. Here, by using direct stochastic modeling, the mapping of interplay of the Raman scattering-based nonlinearity, the random birefringence of a fiber, and the pump-to-signal intensity noise transfer has been done in terms of the fiber Raman amplifier parameters, namely polarization mode dispersion, the relative intensity noise of the pump laser, fiber length, and the signal power. The obtained results reveal conditions for emergence of the random birefringence-induced resonance-like enhancement of the gain fluctuations (stochastic anti-resonance) accompanied by pulse broadening and rare events in the form of low power output signals having probability heavily deviated from the Gaussian distribution. (copyright 2016 by WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)
Stochastic inflation: Quantum phase-space approach
Habib, S.
1992-01-01
In this paper a quantum-mechanical phase-space picture is constructed for coarse-grained free quantum fields in an inflationary universe. The appropriate stochastic quantum Liouville equation is derived. Explicit solutions for the phase-space quantum distribution function are found for the cases of power-law and exponential expansions. The expectation values of dynamical variables with respect to these solutions are compared to the corresponding cutoff regularized field-theoretic results (we do not restrict ourselves only to left-angle Φ 2 right-angle). Fair agreement is found provided the coarse-graining scale is kept within certain limits. By focusing on the full phase-space distribution function rather than a reduced distribution it is shown that the thermodynamic interpretation of the stochastic formalism faces several difficulties (e.g., there is no fluctuation-dissipation theorem). The coarse graining does not guarantee an automatic classical limit as quantum correlations turn out to be crucial in order to get results consistent with standard quantum field theory. Therefore, the method does not by itself constitute an explanation of the quantum to classical transition in the early Universe. In particular, we argue that the stochastic equations do not lead to decoherence
Fluctuating Asymmetry and Intelligence
Bates, Timothy C.
2007-01-01
The general factor of mental ability ("g") may reflect general biological fitness. If so, "g"-loaded measures such as Raven's progressive matrices should be related to morphological measures of fitness such as fluctuating asymmetry (FA: left-right asymmetry of a set of typically left-right symmetrical body traits such as finger…
Stochastic models of intracellular transport
Bressloff, Paul C.
2013-01-09
The interior of a living cell is a crowded, heterogenuous, fluctuating environment. Hence, a major challenge in modeling intracellular transport is to analyze stochastic processes within complex environments. Broadly speaking, there are two basic mechanisms for intracellular transport: passive diffusion and motor-driven active transport. Diffusive transport can be formulated in terms of the motion of an overdamped Brownian particle. On the other hand, active transport requires chemical energy, usually in the form of adenosine triphosphate hydrolysis, and can be direction specific, allowing biomolecules to be transported long distances; this is particularly important in neurons due to their complex geometry. In this review a wide range of analytical methods and models of intracellular transport is presented. In the case of diffusive transport, narrow escape problems, diffusion to a small target, confined and single-file diffusion, homogenization theory, and fractional diffusion are considered. In the case of active transport, Brownian ratchets, random walk models, exclusion processes, random intermittent search processes, quasi-steady-state reduction methods, and mean-field approximations are considered. Applications include receptor trafficking, axonal transport, membrane diffusion, nuclear transport, protein-DNA interactions, virus trafficking, and the self-organization of subcellular structures. © 2013 American Physical Society.
Petit, Chad M.; Melancon, Jeffrey M.; Chouljenko, Vladimir N.; Colgrove, Robin; Farzan, Michael; Knipe, David M.; Kousoulas, K.G.
2005-01-01
The SARS-coronavirus (SARS-CoV) is the etiological agent of severe acute respiratory syndrome (SARS). The SARS-CoV spike (S) glycoprotein mediates membrane fusion events during virus entry and virus-induced cell-to-cell fusion. To delineate functional domains of the SARS-CoV S glycoprotein, single point mutations, cluster-to-lysine and cluster-to-alanine mutations, as well as carboxyl-terminal truncations were investigated in transient expression experiments. Mutagenesis of either the coiled-coil domain of the S glycoprotein amino terminal heptad repeat, the predicted fusion peptide, or an adjacent but distinct region, severely compromised S-mediated cell-to-cell fusion, while intracellular transport and cell-surface expression were not adversely affected. Surprisingly, a carboxyl-terminal truncation of 17 amino acids substantially increased S glycoprotein-mediated cell-to-cell fusion suggesting that the terminal 17 amino acids regulated the S fusogenic properties. In contrast, truncation of 26 or 39 amino acids eliminating either one or both of the two endodomain cysteine-rich motifs, respectively, inhibited cell fusion in comparison to the wild-type S. The 17 and 26 amino-acid deletions did not adversely affect S cell-surface expression, while the 39 amino-acid truncation inhibited S cell-surface expression suggesting that the membrane proximal cysteine-rich motif plays an essential role in S cell-surface expression. Mutagenesis of the acidic amino-acid cluster in the carboxyl terminus of the S glycoprotein as well as modification of a predicted phosphorylation site within the acidic cluster revealed that this amino-acid motif may play a functional role in the retention of S at cell surfaces. This genetic analysis reveals that the SARS-CoV S glycoprotein contains extracellular domains that regulate cell fusion as well as distinct endodomains that function in intracellular transport, cell-surface expression, and cell fusion
Niu, Shengniao; Gil-Salas, Francisco M.; Tewary, Sunil Kumar; Samales, Ashwin Kuppusamy; Johnson, John; Swaminathan, Kunchithapadam; Wong, Sek-Man
2014-01-01
Hibiscus chlorotic ringspot virus (HCRSV) is a member of the genus Carmovirus in the family Tombusviridae. In order to study its coat protein (CP) functions on virus replication and movement in kenaf (Hibiscus cannabinus L.), two HCRSV mutants, designated as p2590 (A to G) in which the first start codon ATG was replaced with GTG and p2776 (C to G) in which proline 63 was replaced with alanine, were constructed. In vitro transcripts of p2590 (A to G) were able to replicate to a similar level as wild type without CP expression in kenaf protoplasts. However, its cell-to-cell movement was not detected in the inoculated kenaf cotyledons. Structurally the proline 63 in subunit C acts as a kink for β-annulus formation during virion assembly. Progeny of transcripts derived from p2776 (C to G) was able to move from cell-to-cell in inoculated cotyledons but its long-distance movement was not detected. Virions were not observed in partially purified mutant virus samples isolated from 2776 (C to G) inoculated cotyledons. Removal of the N-terminal 77 amino acids of HCRSV CP by trypsin digestion of purified wild type HCRSV virions resulted in only T = 1 empty virus-like particles. Taken together, HCRSV CP is dispensable for viral RNA replication but essential for cell-to-cell movement, and virion is required for the virus systemic movement. The proline 63 is crucial for HCRSV virion assembly in kenaf plants and the N-terminal 77 amino acids including the β-annulus domain is required in T = 3 assembly in vitro. PMID:25402344
Shengniao Niu
Full Text Available Hibiscus chlorotic ringspot virus (HCRSV is a member of the genus Carmovirus in the family Tombusviridae. In order to study its coat protein (CP functions on virus replication and movement in kenaf (Hibiscus cannabinus L., two HCRSV mutants, designated as p2590 (A to G in which the first start codon ATG was replaced with GTG and p2776 (C to G in which proline 63 was replaced with alanine, were constructed. In vitro transcripts of p2590 (A to G were able to replicate to a similar level as wild type without CP expression in kenaf protoplasts. However, its cell-to-cell movement was not detected in the inoculated kenaf cotyledons. Structurally the proline 63 in subunit C acts as a kink for β-annulus formation during virion assembly. Progeny of transcripts derived from p2776 (C to G was able to move from cell-to-cell in inoculated cotyledons but its long-distance movement was not detected. Virions were not observed in partially purified mutant virus samples isolated from 2776 (C to G inoculated cotyledons. Removal of the N-terminal 77 amino acids of HCRSV CP by trypsin digestion of purified wild type HCRSV virions resulted in only T = 1 empty virus-like particles. Taken together, HCRSV CP is dispensable for viral RNA replication but essential for cell-to-cell movement, and virion is required for the virus systemic movement. The proline 63 is crucial for HCRSV virion assembly in kenaf plants and the N-terminal 77 amino acids including the β-annulus domain is required in T = 3 assembly in vitro.
Rika Etchuuya
Full Text Available Escherichia coli is not assumed to be naturally transformable. However, several recent reports have shown that E. coli can express modest genetic competence in certain conditions that may arise in its environment. We have shown previously that spontaneous lateral transfer of non-conjugative plasmids occurs in a colony biofilm of mixed E. coli strains (a set of a donor strain harbouring a plasmid and a plasmid-free recipient strain. In this study, with high-frequency combinations of strains and a plasmid, we constructed the same lateral plasmid transfer system in liquid culture. Using this system, we demonstrated that this lateral plasmid transfer was DNase-sensitive, indicating that it is a kind of transformation in which DNase-accessible extracellular naked DNA is essential. However, this transformation did not occur with purified plasmid DNA and required a direct supply of plasmid from co-existing donor cells. Based on this feature, we have termed this transformation type as 'cell-to-cell transformation'. Analyses using medium conditioned with the high-frequency strain revealed that this strain released a certain factor(s that promoted cell-to-cell transformation and arrested growth of the other strains. This factor is heat-labile and protease-sensitive, and its roughly estimated molecular mass was between ∼9 kDa and ∼30 kDa, indicating that it is a polypeptide factor. Interestingly, this factor was effective even when the conditioned medium was diluted 10(-5-10(-6, suggesting that it acts like a pheromone with high bioactivity. Based on these results, we propose that cell-to-cell transformation is a novel natural transformation mechanism in E. coli that requires cell-derived DNA and is promoted by a peptide pheromone. This is the first evidence that suggests the existence of a peptide pheromone-regulated transformation mechanism in E. coli and in Gram-negative bacteria.
Stochastic dynamics and irreversibility
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 ...
Stochastic optimization methods
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.
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)
Separable quadratic stochastic operators
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)
Stochastic cooling at Fermilab
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
From stochastic phase space evolution to Brownian motion in collective space
Benhassine, B.; Farine, M.; Hernandez, E.S.; Idier, D.; Remaud, B.; Sebille, F.
1993-01-01
Within the framework of stochastic transport equations in phase space, the dynamics of fluctuations on collective variables in homogeneous fermion systems is studied. The transport coefficients are formally deduced in the relaxation time approximation and a general method to compute dynamically the dispersions of collective observables is proposed as a set of coupled equations. Independently, the general covariance matrix of phase space fluctuations and the dispersion on collective variables at equilibrium are derived. Detailed numerical applications show that dynamics of fluctuations can be extracted from noisy numerical simulations and that the leading parameter for collective fluctuations is the excitation energy whatever is its degree of thermalization. (authors). 16 refs., 12 figs
Delpeut, Sebastien; Noyce, Ryan S; Richardson, Christopher D
2014-04-01
The entry of canine distemper virus (CDV) is a multistep process that involves the attachment of CDV hemagglutinin (H) to its cellular receptor, followed by fusion between virus and cell membranes. Our laboratory recently identified PVRL4 (nectin-4) to be the epithelial receptor for measles and canine distemper viruses. In this study, we demonstrate that the V domain of PVRL4 is critical for CDV entry and virus cell-to-cell spread. Furthermore, four key amino acid residues within the V domain of dog PVRL4 and two within the CDV hemagglutinin were shown to be essential for receptor-mediated virus entry. Copyright © 2014 Elsevier Inc. All rights reserved.
Effects of demographic stochasticity on biological community assembly on evolutionary time scales
Murase, Yohsuke
2010-04-13
We study the effects of demographic stochasticity on the long-term dynamics of biological coevolution models of community assembly. The noise is induced in order to check the validity of deterministic population dynamics. While mutualistic communities show little dependence on the stochastic population fluctuations, predator-prey models show strong dependence on the stochasticity, indicating the relevance of the finiteness of the populations. For a predator-prey model, the noise causes drastic decreases in diversity and total population size. The communities that emerge under influence of the noise consist of species strongly coupled with each other and have stronger linear stability around the fixed-point populations than the corresponding noiseless model. The dynamics on evolutionary time scales for the predator-prey model are also altered by the noise. Approximate 1/f fluctuations are observed with noise, while 1/ f2 fluctuations are found for the model without demographic noise. © 2010 The American Physical Society.
Effects of demographic stochasticity on biological community assembly on evolutionary time scales
Murase, Yohsuke; Shimada, Takashi; Ito, Nobuyasu; Rikvold, Per Arne
2010-01-01
We study the effects of demographic stochasticity on the long-term dynamics of biological coevolution models of community assembly. The noise is induced in order to check the validity of deterministic population dynamics. While mutualistic communities show little dependence on the stochastic population fluctuations, predator-prey models show strong dependence on the stochasticity, indicating the relevance of the finiteness of the populations. For a predator-prey model, the noise causes drastic decreases in diversity and total population size. The communities that emerge under influence of the noise consist of species strongly coupled with each other and have stronger linear stability around the fixed-point populations than the corresponding noiseless model. The dynamics on evolutionary time scales for the predator-prey model are also altered by the noise. Approximate 1/f fluctuations are observed with noise, while 1/ f2 fluctuations are found for the model without demographic noise. © 2010 The American Physical Society.
Stochastic resonance in a generalized Von Foerster population growth model
Lumi, N.; Mankin, R. [Institute of Mathematics and Natural Sciences, Tallinn University, 25 Narva Road, 10120 Tallinn (Estonia)
2014-11-12
The stochastic dynamics of a population growth model, similar to the Von Foerster model for human population, is studied. The influence of fluctuating environment on the carrying capacity is modeled as a multiplicative dichotomous noise. It is established that an interplay between nonlinearity and environmental fluctuations can cause single unidirectional discontinuous transitions of the mean population size versus the noise amplitude, i.e., an increase of noise amplitude can induce a jump from a state with a moderate number of individuals to that with a very large number, while by decreasing the noise amplitude an opposite transition cannot be effected. An analytical expression of the mean escape time for such transitions is found. Particularly, it is shown that the mean transition time exhibits a strong minimum at intermediate values of noise correlation time, i.e., the phenomenon of stochastic resonance occurs. Applications of the results in ecology are also discussed.
Stochastic inflation as a time-dependent random walk
Kandrup, H.E.
1989-01-01
This paper exploits the ''stochastic inflation'' paradigm introduced by Starobinskii to study the evolution of long-wavelength modes for a free scalar field Phi in an inflationary Universe. By relaxing the assumption of a ''slow roll,'' it becomes obvious that the well-known late-time infrared divergence of the vacuum for a massless field in de Sitter space may be viewed as a consequence of the fluctuation-dissipation theorem. This stochastic model is also extended to allow for nonvacuum states and power-law inflation, situations where the fluctuation-dissipation theorem no longer holds. One recovers the correct late-time form for the expectation value 2 > in these cases as well, corroborating thereby the intuitive picture that, quite generally, the long-wavelength modes of the field evolve in a thermal ''bath'' provided by the shorter-wavelength modes
Stochastic Feedforward Control Technique
Halyo, Nesim
1990-01-01
Class of commanded trajectories modeled as stochastic process. Advanced Transport Operating Systems (ATOPS) research and development program conducted by NASA Langley Research Center aimed at developing capabilities for increases in capacities of airports, safe and accurate flight in adverse weather conditions including shear, winds, avoidance of wake vortexes, and reduced consumption of fuel. Advances in techniques for design of modern controls and increased capabilities of digital flight computers coupled with accurate guidance information from Microwave Landing System (MLS). Stochastic feedforward control technique developed within context of ATOPS program.
Markov stochasticity coordinates
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.
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...
Stochastic dynamics and control
Sun, Jian-Qiao; Zaslavsky, George
2006-01-01
This book is a result of many years of author's research and teaching on random vibration and control. It was used as lecture notes for a graduate course. It provides a systematic review of theory of probability, stochastic processes, and stochastic calculus. The feedback control is also reviewed in the book. Random vibration analyses of SDOF, MDOF and continuous structural systems are presented in a pedagogical order. The application of the random vibration theory to reliability and fatigue analysis is also discussed. Recent research results on fatigue analysis of non-Gaussian stress proc
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...
Foundations of stochastic analysis
Rao, M M; Lukacs, E
1981-01-01
Foundations of Stochastic Analysis deals with the foundations of the theory of Kolmogorov and Bochner and its impact on the growth of stochastic analysis. Topics covered range from conditional expectations and probabilities to projective and direct limits, as well as martingales and likelihood ratios. Abstract martingales and their applications are also discussed. Comprised of five chapters, this volume begins with an overview of the basic Kolmogorov-Bochner theorem, followed by a discussion on conditional expectations and probabilities containing several characterizations of operators and mea
Markov stochasticity coordinates
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.
Queues and Lévy fluctuation theory
Dębicki, Krzysztof
2015-01-01
The book provides an extensive introduction to queueing models driven by Lévy-processes as well as a systematic account of the literature on Lévy-driven queues. The objective is to make the reader familiar with the wide set of probabilistic techniques that have been developed over the past decades, including transform-based techniques, martingales, rate-conservation arguments, change-of-measure, importance sampling, and large deviations. On the application side, it demonstrates how Lévy traffic models arise when modelling current queueing-type systems (as communication networks) and includes applications to finance. Queues and Lévy Fluctuation Theory will appeal to graduate/postgraduate students and researchers in mathematics, computer science, and electrical engineering. Basic prerequisites are probability theory and stochastic processes.
Stochastic models, estimation, and control
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.
Do investment-specific technological changes matter for business fluctuations? Evidence from Japan
Hirose, Yasuo; Kurozumi, Takushi
2011-01-01
The observed decline in the relative price of investment goods to consumption goods in Japan suggests the existence of investment-specific technological (IST) changes. We examine whether IST changes are a major source of business fluctuations in Japan, by estimating a dynamic stochastic general equilibrium model with Bayesian methods. We show that IST changes are less important than neutral technological changes in explaining output fluctuations. We also demonstrate that investment fluctuatio...
Quantifying fluctuations in reversible enzymatic cycles and clocks
Wierenga, Harmen; ten Wolde, Pieter Rein; Becker, Nils B.
2018-04-01
Biochemical reactions are fundamentally noisy at a molecular scale. This limits the precision of reaction networks, but it also allows fluctuation measurements that may reveal the structure and dynamics of the underlying biochemical network. Here, we study nonequilibrium reaction cycles, such as the mechanochemical cycle of molecular motors, the phosphorylation cycle of circadian clock proteins, or the transition state cycle of enzymes. Fluctuations in such cycles may be measured using either of two classical definitions of the randomness parameter, which we show to be equivalent in general microscopically reversible cycles. We define a stochastic period for reversible cycles and present analytical solutions for its moments. Furthermore, we associate the two forms of the randomness parameter with the thermodynamic uncertainty relation, which sets limits on the timing precision of the cycle in terms of thermodynamic quantities. Our results should prove useful also for the study of temporal fluctuations in more general networks.
Studies to the stochastic theory of coupled reactorkinetic-thermohydraulic systems Pt. 2
Mesko, L.
1983-06-01
The description is given of the noise phenomena taking place in a multivariable coupled system by a comprehensive model based on the theory of stochastic fluctuations. A comparison is made with models using transfer function formalism for systems characterized by deterministic open and closed loop signal transmission properties. The advantages of the stochastic model are illustrated by simple reactor dynamical examples having diagnostical importance. (author)
Linear response in stochastic mean-field theories and the onset of instabilities
Colonna, M.; Chomaz, Ph.
1993-01-01
The small amplitude response of stochastic one-body theories, such as the Boltzmann-Langevin approach is studied. Whereas the two-time correlation function only describes the propagation of fluctuations initially present, the equal-time correlation function is related to the source of stochasticity. For stable systems it yields the Einstein relation, while for unstable systems it determines the growth of the instabilities. These features are illustrated for unstable nuclear matter in two dimensions. (author) 14 refs.; 5 figs
Single-molecule stochastic times in a reversible bimolecular reaction
Keller, Peter; Valleriani, Angelo
2012-08-01
In this work, we consider the reversible reaction between reactants of species A and B to form the product C. We consider this reaction as a prototype of many pseudobiomolecular reactions in biology, such as for instance molecular motors. We derive the exact probability density for the stochastic waiting time that a molecule of species A needs until the reaction with a molecule of species B takes place. We perform this computation taking fully into account the stochastic fluctuations in the number of molecules of species B. We show that at low numbers of participating molecules, the exact probability density differs from the exponential density derived by assuming the law of mass action. Finally, we discuss the condition of detailed balance in the exact stochastic and in the approximate treatment.
Stochastic quantisation: theme and variation
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.)
Nonperturbative stochastic dynamics driven by strongly correlated colored noise
Jing, Jun; Li, Rui; You, J. Q.; Yu, Ting
2015-02-01
We propose a quantum model consisting of two remote qubits interacting with two correlated colored noises and establish an exact stochastic Schrödinger equation for this open quantum system. It is shown that the quantum dynamics of the qubit system is profoundly modulated by the mutual correlation between baths and the bath memory capability through dissipation and fluctuation. We report a physical effect on generating inner correlation and entanglement of two distant qubits arising from the strong bath-bath correlation.
Concentration fluctuations in gas releases by industrial accidents. Final report
Nielsen, M.; Chatwin, P.C.; Joergensen, H.E.; Mole, N.; Munro, R.J.; Ott, S.
2002-05-01
The COFIN project studied existing remote-sensing Lidar data on concentration fluctuations in atmospheric dispersion from continuous sources at ground level. Fluctuations are described by stochastic models developed by a combination of statistical analyses and surface-layer scaling. The statistical moments and probability density distribution of the fluctuations are most accurately determined in a frame of reference following the instantaneous plume centreline. The spatial distribution of these moments is universal with a gaussian core and exponential tails. The instantaneous plume width is fluctuating with a log-normal distribution. The position of the instantaneous plume centre-line is modelled by a normal distribution and a Langevin equation, by which the meander effect on the time-averaged plume width is predicted. Fixed-frame statistics are modelled by convolution of moving-frame statistics and the probability distribution for the plume centreline. The distance-neighbour function generalized for higher-order statistics has a universal exponential shape. Simulation tools for concentration fluctuations have been developed for either multiple correlated time series or multi-dimensional fields. These tools are based on Karhunen-Loeve expansion and Fourier transformations using iterative or correlation-distortion techniques. The input to the simulation is the probability distribution of the individual processes, assumed stationary, and the cross-correlations of all signal combinations. The use in practical risk assessment is illustrated by implementation of a typical heavy-gas dispersion model, enhanced for prediction and simulation of concentration fluctuations. (au)
Stochastic quantization of Proca field
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)
Stochastic Estimation via Polynomial Chaos
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
General framework for fluctuating dynamic density functional theory
Durán-Olivencia, Miguel A.; Yatsyshin, Peter; Goddard, Benjamin D.; Kalliadasis, Serafim
2017-12-01
We introduce a versatile bottom-up derivation of a formal theoretical framework to describe (passive) soft-matter systems out of equilibrium subject to fluctuations. We provide a unique connection between the constituent-particle dynamics of real systems and the time evolution equation of their measurable (coarse-grained) quantities, such as local density and velocity. The starting point is the full Hamiltonian description of a system of colloidal particles immersed in a fluid of identical bath particles. Then, we average out the bath via Zwanzig’s projection-operator techniques and obtain the stochastic Langevin equations governing the colloidal-particle dynamics. Introducing the appropriate definition of the local number and momentum density fields yields a generalisation of the Dean-Kawasaki (DK) model, which resembles the stochastic Navier-Stokes description of a fluid. Nevertheless, the DK equation still contains all the microscopic information and, for that reason, does not represent the dynamical law of observable quantities. We address this controversial feature of the DK description by carrying out a nonequilibrium ensemble average. Adopting a natural decomposition into local-equilibrium and nonequilibrium contribution, where the former is related to a generalised version of the canonical distribution, we finally obtain the fluctuating-hydrodynamic equation governing the time-evolution of the mesoscopic density and momentum fields. Along the way, we outline the connection between the ad hoc energy functional introduced in previous DK derivations and the free-energy functional from classical density-functional theory. The resultant equation has the structure of a dynamical density-functional theory (DDFT) with an additional fluctuating force coming from the random interactions with the bath. We show that our fluctuating DDFT formalism corresponds to a particular version of the fluctuating Navier-Stokes equations, originally derived by Landau and Lifshitz
Kulasiri, Don
2011-01-01
We discuss the quantification of molecular fluctuations in the biochemical reaction systems within the context of intracellular processes associated with gene expression. We take the molecular reactions pertaining to circadian rhythms to develop models of molecular fluctuations in this chapter. There are a significant number of studies on stochastic fluctuations in intracellular genetic regulatory networks based on single cell-level experiments. In order to understand the fluctuations associated with the gene expression in circadian rhythm networks, it is important to model the interactions of transcriptional factors with the E-boxes in the promoter regions of some of the genes. The pertinent aspects of a near-equilibrium theory that would integrate the thermodynamical and particle dynamic characteristics of intracellular molecular fluctuations would be discussed, and the theory is extended by using the theory of stochastic differential equations. We then model the fluctuations associated with the promoter regions using general mathematical settings. We implemented ubiquitous Gillespie's algorithms, which are used to simulate stochasticity in biochemical networks, for each of the motifs. Both the theory and the Gillespie's algorithms gave the same results in terms of the time evolution of means and variances of molecular numbers. As biochemical reactions occur far away from equilibrium-hence the use of the Gillespie algorithm-these results suggest that the near-equilibrium theory should be a good approximation for some of the biochemical reactions. © 2011 Elsevier Inc. All rights reserved.
Stochastic population oscillations in spatial predator-prey models
Taeuber, Uwe C
2011-01-01
It is well-established that including spatial structure and stochastic noise in models for predator-prey interactions invalidates the classical deterministic Lotka-Volterra picture of neutral population cycles. In contrast, stochastic models yield long-lived, but ultimately decaying erratic population oscillations, which can be understood through a resonant amplification mechanism for density fluctuations. In Monte Carlo simulations of spatial stochastic predator-prey systems, one observes striking complex spatio-temporal structures. These spreading activity fronts induce persistent correlations between predators and prey. In the presence of local particle density restrictions (finite prey carrying capacity), there exists an extinction threshold for the predator population. The accompanying continuous non-equilibrium phase transition is governed by the directed-percolation universality class. We employ field-theoretic methods based on the Doi-Peliti representation of the master equation for stochastic particle interaction models to (i) map the ensuing action in the vicinity of the absorbing state phase transition to Reggeon field theory, and (ii) to quantitatively address fluctuation-induced renormalizations of the population oscillation frequency, damping, and diffusion coefficients in the species coexistence phase.
Delpeut, Sebastien; Noyce, Ryan S.; Richardson, Christopher D.
2014-01-01
The entry of canine distemper virus (CDV) is a multistep process that involves the attachment of CDV hemagglutinin (H) to its cellular receptor, followed by fusion between virus and cell membranes. Our laboratory recently identified PVRL4 (nectin-4) to be the epithelial receptor for measles and canine distemper viruses. In this study, we demonstrate that the V domain of PVRL4 is critical for CDV entry and virus cell-to-cell spread. Furthermore, four key amino acid residues within the V domain of dog PVRL4 and two within the CDV hemagglutinin were shown to be essential for receptor-mediated virus entry. - Highlights: • PVRL4 (nectin-4) is the epithelial cell receptor for measles and canine distemper viruses. • V domain of PVRL4 is critical for CDV entry, cell-to-cell spread, and syncytia formation. • Chimeric PVRL1 backbone substituted with the V domain of PVRL4 can function as a receptor. • Amino acids (F132/P133/A134/G135) within the V domain are essential for PVRL4 receptor activity. • Amino acids (P493/Y539) within CDV H protein are essential for PVRL4 receptor interaction
Delpeut, Sebastien; Noyce, Ryan S. [The Department of Microbiology and Immunology, Dalhousie University, Halifax, Nova Scotia, Canada B3H 1X5 (Canada); IWK Health Centre, Canadian Center for Vaccinology, Goldbloom Pavilion, Halifax, Nova Scotia, Canada B3H 1X5 (Canada); Richardson, Christopher D., E-mail: chris.richardson@dal.ca [The Department of Microbiology and Immunology, Dalhousie University, Halifax, Nova Scotia, Canada B3H 1X5 (Canada); IWK Health Centre, Canadian Center for Vaccinology, Goldbloom Pavilion, Halifax, Nova Scotia, Canada B3H 1X5 (Canada); The Department of Pediatrics, Dalhousie University, Halifax, Nova Scotia (Canada)
2014-04-15
The entry of canine distemper virus (CDV) is a multistep process that involves the attachment of CDV hemagglutinin (H) to its cellular receptor, followed by fusion between virus and cell membranes. Our laboratory recently identified PVRL4 (nectin-4) to be the epithelial receptor for measles and canine distemper viruses. In this study, we demonstrate that the V domain of PVRL4 is critical for CDV entry and virus cell-to-cell spread. Furthermore, four key amino acid residues within the V domain of dog PVRL4 and two within the CDV hemagglutinin were shown to be essential for receptor-mediated virus entry. - Highlights: • PVRL4 (nectin-4) is the epithelial cell receptor for measles and canine distemper viruses. • V domain of PVRL4 is critical for CDV entry, cell-to-cell spread, and syncytia formation. • Chimeric PVRL1 backbone substituted with the V domain of PVRL4 can function as a receptor. • Amino acids (F132/P133/A134/G135) within the V domain are essential for PVRL4 receptor activity. • Amino acids (P493/Y539) within CDV H protein are essential for PVRL4 receptor interaction.
Mitra, Ruchira; Krishnamurthy, Konduru; Blancaflor, Elison; Payton, Mark; Nelson, Richard S.; Verchot-Lubicz, Jeanmarie
2003-01-01
Potato virus X (PVX) TGBp1, TGBp2, TGBp3, and coat protein are required for virus cell-to-cell movement. Plasmids expressing GFP fused to TGBp2 were bombarded to leaf epidermal cells and GFP:TGBp2 moved cell to cell in Nicotiana benthamiana leaves but not in Nicotiana tabacum leaves. GFP:TGBp2 movement was observed in TGBp1-transgenic N. tabacum, indicating that TGBp2 requires TGBp1 to promote its movement in N. tabacum. In this study, GFP:TGBp2 was detected in a polygonal pattern that resembles the endoplasmic reticulum (ER) network. Amino acid sequence analysis revealed TGBp2 has two putative transmembrane domains. Two mutations separately introduced into the coding sequences encompassing the putative transmembrane domains within the GFP:TGBp2 plasmids and PVX genome, disrupted membrane binding of GFP:TGBp2, inhibited GFP:TGBp2 movement in N. benthamiana and TGBp1-expressing N. tabacum, and inhibited PVX movement. A third mutation, lying outside the transmembrane domains, had no effect on GFP:TGBp2 ER association or movement in N. benthamiana but inhibited GFP:TGBp2 movement in TGBp1-expressing N. tabacum and PVX movement in either Nicotiana species. Thus, ER association of TGBp2 may be required but not be sufficient for virus movement. TGBp2 likely provides an activity for PVX movement beyond ER association
Lee, Byung-Chul; Kim, Hyung-Sik; Shin, Tae-Hoon; Kang, Insung; Lee, Jin Young; Kim, Jae-Jun; Kang, Hyun Kyoung; Seo, Yoojin; Lee, Seunghee; Yu, Kyung-Rok; Choi, Soon Won; Kang, Kyung-Sun
2016-05-27
Mesenchymal stem cells (MSCs) possess unique immunomodulatory abilities. Many studies have elucidated the clinical efficacy and underlying mechanisms of MSCs in immune disorders. Although immunoregulatory factors, such as Prostaglandin E2 (PGE2), and their mechanisms of action on immune cells have been revealed, their effects on MSCs and regulation of their production by the culture environment are less clear. Therefore, we investigated the autocrine effect of PGE2 on human adult stem cells from cord blood or adipose tissue, and the regulation of its production by cell-to-cell contact, followed by the determination of its immunomodulatory properties. MSCs were treated with specific inhibitors to suppress PGE2 secretion, and proliferation was assessed. PGE2 exerted an autocrine regulatory function in MSCs by triggering E-Prostanoid (EP) 2 receptor. Inhibiting PGE2 production led to growth arrest, whereas addition of MSC-derived PGE2 restored proliferation. The level of PGE2 production from an equivalent number of MSCs was down-regulated via gap junctional intercellular communication. This cell contact-mediated decrease in PGE2 secretion down-regulated the suppressive effect of MSCs on immune cells. In conclusion, PGE2 produced by MSCs contributes to maintenance of self-renewal capacity through EP2 in an autocrine manner, and PGE2 secretion is down-regulated by cell-to-cell contact, attenuating its immunomodulatory potency.
Tollestrup, A.V.; Dugan, G
1983-12-01
Major headings in this review include: proton sources; antiproton production; antiproton sources and Liouville, the role of the Debuncher; transverse stochastic cooling, time domain; the accumulator; frequency domain; pickups and kickers; Fokker-Planck equation; calculation of constants in the Fokker-Planck equation; and beam feedback. (GHT)
Schrager, D.F.
2006-01-01
We propose a new model for stochastic mortality. The model is based on the literature on affine term structure models. It satisfies three important requirements for application in practice: analytical tractibility, clear interpretation of the factors and compatibility with financial option pricing
Composite stochastic processes
Kampen, N.G. van
Certain problems in physics and chemistry lead to the definition of a class of stochastic processes. Although they are not Markovian they can be treated explicitly to some extent. In particular, the probability distribution for large times can be found. It is shown to obey a master equation. This
Entropy Production in Stochastics
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.
Stochastic modelling of turbulence
Sørensen, Emil Hedevang Lohse
previously been shown to be closely connected to the energy dissipation. The incorporation of the small scale dynamics into the spatial model opens the door to a fully fledged stochastic model of turbulence. Concerning the interaction of wind and wind turbine, a new method is proposed to extract wind turbine...
Research in Stochastic Processes.
1982-10-31
Office of Scientific Research Grant AFOSR F49620 82 C 0009 Period: 1 Noveber 1981 through 31 October 1982 Title: Research in Stochastic Processes Co...STA4ATIS CAMBANIS The work briefly described here was developed in connection with problems arising from and related to the statistical comunication
Stochastic Control - External Models
Poulsen, Niels Kjølstad
2005-01-01
This note is devoted to control of stochastic systems described in discrete time. We are concerned with external descriptions or transfer function model, where we have a dynamic model for the input output relation only (i.e.. no direct internal information). The methods are based on LTI systems...
Stochastic nonlinear beam equations
Brzezniak, Z.; Maslowski, Bohdan; Seidler, Jan
2005-01-01
Roč. 132, č. 1 (2005), s. 119-149 ISSN 0178-8051 R&D Projects: GA ČR(CZ) GA201/01/1197 Institutional research plan: CEZ:AV0Z10190503 Keywords : stochastic beam equation * stability Subject RIV: BA - General Mathematics Impact factor: 0.896, year: 2005
Fluctuations in quantum devices
H.Haken
2004-01-01
Full Text Available Logical gates can be formalized by Boolean algebra whose elementary operations can be realized by devices that employ the interactions of macroscopic numbers of elementary excitations such as electrons, holes, photons etc. With increasing miniaturization to the nano scale and below, quantum fluctuations become important and can no longer be ignored. Based on Heisenberg equations of motion for the creation and annihilation operators of elementary excitations, I determine the noise sources of composite quantum systems.
Detrended fluctuation analysis made flexible to detect range of cross-correlated fluctuations
Kwapień, Jarosław; Oświecimka, Paweł; DroŻdŻ, Stanisław
2015-11-01
The detrended cross-correlation coefficient ρDCCA has recently been proposed to quantify the strength of cross-correlations on different temporal scales in bivariate, nonstationary time series. It is based on the detrended cross-correlation and detrended fluctuation analyses (DCCA and DFA, respectively) and can be viewed as an analog of the Pearson coefficient in the case of the fluctuation analysis. The coefficient ρDCCA works well in many practical situations but by construction its applicability is limited to detection of whether two signals are generally cross-correlated, without the possibility to obtain information on the amplitude of fluctuations that are responsible for those cross-correlations. In order to introduce some related flexibility, here we propose an extension of ρDCCA that exploits the multifractal versions of DFA and DCCA: multifractal detrended fluctuation analysis and multifractal detrended cross-correlation analysis, respectively. The resulting new coefficient ρq not only is able to quantify the strength of correlations but also allows one to identify the range of detrended fluctuation amplitudes that are correlated in two signals under study. We show how the coefficient ρq works in practical situations by applying it to stochastic time series representing processes with long memory: autoregressive and multiplicative ones. Such processes are often used to model signals recorded from complex systems and complex physical phenomena like turbulence, so we are convinced that this new measure can successfully be applied in time-series analysis. In particular, we present an example of such application to highly complex empirical data from financial markets. The present formulation can straightforwardly be extended to multivariate data in terms of the q -dependent counterpart of the correlation matrices and then to the network representation.
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.
Environmental Noise Could Promote Stochastic Local Stability of Behavioral Diversity Evolution
Zheng, Xiu-Deng; Li, Cong; Lessard, Sabin; Tao, Yi
2018-05-01
In this Letter, we investigate stochastic stability in a two-phenotype evolutionary game model for an infinite, well-mixed population undergoing discrete, nonoverlapping generations. We assume that the fitness of a phenotype is an exponential function of its expected payoff following random pairwise interactions whose outcomes randomly fluctuate with time. We show that the stochastic local stability of a constant interior equilibrium can be promoted by the random environmental noise even if the system may display a complicated nonlinear dynamics. This result provides a new perspective for a better understanding of how environmental fluctuations may contribute to the evolution of behavioral diversity.
Fluctuations and Instability in Sedimentation
Guazzelli, É lisabeth; Hinch, John
2011-01-01
This review concentrates on the fluctuations of the velocities of sedimenting spheres, and on the structural instability of a suspension of settling fibers. For many years, theoretical estimates and numerical simulations predicted the fluctuations
Silva, Milena Wollmann da; Vilhena, Marco Tullio M.B.; Bodmann, Bardo Ernst J.; Vasques, Richard, E-mail: milena.wollmann@ufrgs.br, E-mail: vilhena@mat.ufrgs.br, E-mail: bardobodmann@ufrgs.br, E-mail: richard.vasques@fulbrightmail.org [Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS (Brazil). Programa de Pos-Graduacao em Engenharia Mecanica
2015-07-01
The neutron point kinetics equation, which models the time-dependent behavior of nuclear reactors, is often used to understand the dynamics of nuclear reactor operations. It consists of a system of coupled differential equations that models the interaction between (i) the neutron population; and (II) the concentration of the delayed neutron precursors, which are radioactive isotopes formed in the fission process that decay through neutron emission. These equations are deterministic in nature, and therefore can provide only average values of the modeled populations. However, the actual dynamical process is stochastic: the neutron density and the delayed neutron precursor concentrations vary randomly with time. To address this stochastic behavior, Hayes and Allen have generalized the standard deterministic point kinetics equation. They derived a system of stochastic differential equations that can accurately model the random behavior of the neutron density and the precursor concentrations in a point reactor. Due to the stiffness of these equations, this system was numerically implemented using a stochastic piecewise constant approximation method (Stochastic PCA). Here, we present a study of the influence of stochastic fluctuations on the results of the neutron point kinetics equation. We reproduce the stochastic formulation introduced by Hayes and Allen and compute Monte Carlo numerical results for examples with constant and time-dependent reactivity, comparing these results with stochastic and deterministic methods found in the literature. Moreover, we introduce a modified version of the stochastic method to obtain a non-stiff solution, analogue to a previously derived deterministic approach. (author)
Silva, Milena Wollmann da; Vilhena, Marco Tullio M.B.; Bodmann, Bardo Ernst J.; Vasques, Richard
2015-01-01
The neutron point kinetics equation, which models the time-dependent behavior of nuclear reactors, is often used to understand the dynamics of nuclear reactor operations. It consists of a system of coupled differential equations that models the interaction between (i) the neutron population; and (II) the concentration of the delayed neutron precursors, which are radioactive isotopes formed in the fission process that decay through neutron emission. These equations are deterministic in nature, and therefore can provide only average values of the modeled populations. However, the actual dynamical process is stochastic: the neutron density and the delayed neutron precursor concentrations vary randomly with time. To address this stochastic behavior, Hayes and Allen have generalized the standard deterministic point kinetics equation. They derived a system of stochastic differential equations that can accurately model the random behavior of the neutron density and the precursor concentrations in a point reactor. Due to the stiffness of these equations, this system was numerically implemented using a stochastic piecewise constant approximation method (Stochastic PCA). Here, we present a study of the influence of stochastic fluctuations on the results of the neutron point kinetics equation. We reproduce the stochastic formulation introduced by Hayes and Allen and compute Monte Carlo numerical results for examples with constant and time-dependent reactivity, comparing these results with stochastic and deterministic methods found in the literature. Moreover, we introduce a modified version of the stochastic method to obtain a non-stiff solution, analogue to a previously derived deterministic approach. (author)
Pazsit, I.; Glockler, O.
1984-01-01
In an earlier publication, using the theory of neutron fluctuations induced by a vibrating control rod, a complete formal solution of rod vibration diagnostics based on neutron noise measurements was given in terms of Fourier-transformed neutron detector time signals. The suggested procedure was checked in numerical simulation tests where only periodic vibrations could be considered. The procedure and its numerical testing are elaborated for stochastic two-dimensional vibrations. A simple stochastic theory of two-dimensional flow-induced vibrations is given; then the diagnostic method is formulated in the stochastic case, that is, in terms of neutron detector auto- and crosspower spectra. A previously suggested approximate rod localization technique is also formulated in the stochastic case. Applicability of the methods is then investigated in numerical simulation tests, using the proposed model of stochastic two-dimensional vibrations when generating neutron detector spectra that simulate measured data
Fluctuations in Schottky barrier heights
Mahan, G.D.
1984-01-01
A double Schottky barrier is often formed at the grain boundary in polycrystalline semiconductors. The barrier height is shown to fluctuate in value due to the random nature of the impurity positions. The magnitude of the fluctuations is 0.1 eV, and the fluctuations cause the barrier height measured by capacitance to differ from the one measured by electrical conductivity
Stochastic processes in cell biology
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...
Exploiting intrinsic fluctuations to identify model parameters.
Zimmer, Christoph; Sahle, Sven; Pahle, Jürgen
2015-04-01
Parameterisation of kinetic models plays a central role in computational systems biology. Besides the lack of experimental data of high enough quality, some of the biggest challenges here are identification issues. Model parameters can be structurally non-identifiable because of functional relationships. Noise in measured data is usually considered to be a nuisance for parameter estimation. However, it turns out that intrinsic fluctuations in particle numbers can make parameters identifiable that were previously non-identifiable. The authors present a method to identify model parameters that are structurally non-identifiable in a deterministic framework. The method takes time course recordings of biochemical systems in steady state or transient state as input. Often a functional relationship between parameters presents itself by a one-dimensional manifold in parameter space containing parameter sets of optimal goodness. Although the system's behaviour cannot be distinguished on this manifold in a deterministic framework it might be distinguishable in a stochastic modelling framework. Their method exploits this by using an objective function that includes a measure for fluctuations in particle numbers. They show on three example models, immigration-death, gene expression and Epo-EpoReceptor interaction, that this resolves the non-identifiability even in the case of measurement noise with known amplitude. The method is applied to partially observed recordings of biochemical systems with measurement noise. It is simple to implement and it is usually very fast to compute. This optimisation can be realised in a classical or Bayesian fashion.
Simulation of the fluctuations of energy and charge deposited during e-beam exposure
Borisov, S. S.; Zaitsev, S. I.; Grachev, E. A.
2007-01-01
The stochastic nature of an energy and charge deposition process is examined using a model based on discrete loss approximation (DLA). Deposited energy deviations computed using the continuous slowing down approximation (CSDA) and DLA are compared. It is shown that CSDA underestimates fluctuations in deposited energy
A test particle motion in the Kerr field with fluctuating perturbations
Zhuk, I.T.; Piragas, K.A.
1982-01-01
Motion of a stochastic test particle in the Kerr black hole field in the approximation of Brown interaction is considered. Probability distribution of orbit position by the latitude angle is revealed, bifurcation values of their parameters are determined. Fluctuating instability of orbits characteristic of critical modes of motion is investigated, properties of some statistical characteristics of the system are identified
Fluctuations of one-body observables. Comparison between exact predictions and numerical simulation
Burgio, G.F.; Benhassine, B.; Remaud, B.; Sebille, F.
1994-01-01
Within the framework of a stochastic transport equation, we discuss a theoretical approach in order to derive the general covariance matrix of phase-space fluctuations and the dispersion of one-body variables at equilibrium. We compare with the independently obtained numerical results of Chomaz, Burgio and Randrup. The analysis proves the validity of the general approach. (orig.)
Fluctuations of one-body observables. Comparison between exact predictions and numerical simulation
Burgio, G.F. (Lab. de Physique Nucleaire/CNRS and Univ. de Nantes, 44 Nantes (France)); Benhassine, B. (Lab. de Physique Nucleaire/CNRS and Univ. de Nantes, 44 Nantes (France)); Remaud, B. (Lab. de Physique Nucleaire/CNRS and Univ. de Nantes, 44 Nantes (France)); Sebille, F. (Lab. de Physique Nucleaire/CNRS and Univ. de Nantes, 44 Nantes (France))
1994-01-24
Within the framework of a stochastic transport equation, we discuss a theoretical approach in order to derive the general covariance matrix of phase-space fluctuations and the dispersion of one-body variables at equilibrium. We compare with the independently obtained numerical results of Chomaz, Burgio and Randrup. The analysis proves the validity of the general approach. (orig.)
Tucker, E B
1990-08-01
The effect of microinjected calcium-loaded 1,2-bis(2-aminophenoxy) ethane-N,N,N',N'-tetraacetic acid (CaBAPTA) on cell-to-cell diffusion of carboxyfluorescein (CF) was examined in staminal hairs of S. purpurea Boom. The CaBAPTA was microinjected into the cytoplasm of the staminal hairs either with CF or prior to a subsequent microinjection of CF. The cell-to-cell diffusion of CF along the hair was monitored using enhanced-fluorescence video microscopy. Cytoplasmic streaming stopped in cells treated with CaBAPTA, indicating that intracellular Ca(2+) had increased. Cell-to-cell diffusion of CF was blocked in cells treated with Ca-BAPTA. An inhibition of cytoplasmic streaming and cell-to-cell diffusion was observed in the cells adjoining the CaBAPTA-microinjected cell, indicating that the Ca-BAPTA appeared to pass through plasmodesmata. While cytoplasmic streaming resumed 5-10 min after CaBAPTA treatment, cell-to-cell diffusion did not resume until 30-120 min later. These data support an involvement of calcium in the regulation of cell-to-cell communication in plants.
Simulation of power fluctuation of wind farms based on frequency domain
Lin, Jin; Sun, Yuanzhang; Li, Guojie
2011-01-01
, however, is incapable of completely explaining the physical mechanism of randomness of power fluctuation. To remedy such a situation, fluctuation modeling based on the frequency domain is proposed. The frequency domain characteristics of stochastic fluctuation on large wind farms are studied using...... the power spectral density of wind speed, the frequency domain model of a wind power generator and the information on weather and geography of the wind farms. The correctness and effectiveness of the model are verified by comparing the measurement data with simulation results of a certain wind farm. © 2011...
Strain fluctuations and elastic constants
Parrinello, M.; Rahman, A.
1982-03-01
It is shown that the elastic strain fluctuations are a direct measure of elastic compliances in a general anisotropic medium; depending on the ensemble in which the fluctuation is measured either the isothermal or the adiabatic compliances are obtained. These fluctuations can now be calculated in a constant enthalpy and pressure, and hence, constant entropy, ensemble due to recent develpments in the molecular dynamics techniques. A calculation for a Ni single crystal under uniform uniaxial 100 tensile or compressive load is presented as an illustration of the relationships derived between various strain fluctuations and the elastic modulii. The Born stability criteria and the behavior of strain fluctuations are shown to be related.
Fluctuations in the hadronization
Bozek, P.; Ploszajaczak, M.
1992-01-01
The multiscaling in the fluctuations of the multiparticle distributions at small scales is studied. Similarly to the multiscaling effect, recently found in multifractal models, the dependence of the intermittency patterns on the low density cut-off in the cascade is analyzed. The effect changes the scaling behaviour and leads to stronger dependence of the scaled factorial moments on the resolution than the power law. This could be an explanation of the behaviour observed recently in the experimental 3-dimensional data. The multiscaling analysis allows to restore the universality in the processes with different cut-offs and could be used in the analysis of the experimental data. (author) 17 refs., 5 figs
Periodic and stochastic thermal modulation of protein folding kinetics.
Platkov, Max; Gruebele, Martin
2014-07-21
Chemical reactions are usually observed either by relaxation of a bulk sample after applying a sudden external perturbation, or by intrinsic fluctuations of a few molecules. Here we show that the two ideas can be combined to measure protein folding kinetics, either by periodic thermal modulation, or by creating artificial thermal noise that greatly exceeds natural thermal fluctuations. We study the folding reaction of the enzyme phosphoglycerate kinase driven by periodic temperature waveforms. As the temperature waveform unfolds and refolds the protein, its fluorescence color changes due to FRET (Förster resonant Energy Transfer) of two donor/acceptor fluorophores labeling the protein. We adapt a simple model of periodically driven kinetics that nicely fits the data at all temperatures and driving frequencies: The phase shifts of the periodic donor and acceptor fluorescence signals as a function of driving frequency reveal reaction rates. We also drive the reaction with stochastic temperature waveforms that produce thermal fluctuations much greater than natural fluctuations in the bulk. Such artificial thermal noise allows the recovery of weak underlying signals due to protein folding kinetics. This opens up the possibility for future detection of a stochastic resonance for protein folding subject to noise with controllable amplitude.
Stochastic calculus and applications
Cohen, Samuel N
2015-01-01
Completely revised and greatly expanded, the new edition of this text takes readers who have been exposed to only basic courses in analysis through the modern general theory of random processes and stochastic integrals as used by systems theorists, electronic engineers and, more recently, those working in quantitative and mathematical finance. Building upon the original release of this title, this text will be of great interest to research mathematicians and graduate students working in those fields, as well as quants in the finance industry. New features of this edition include: End of chapter exercises; New chapters on basic measure theory and Backward SDEs; Reworked proofs, examples and explanatory material; Increased focus on motivating the mathematics; Extensive topical index. "Such a self-contained and complete exposition of stochastic calculus and applications fills an existing gap in the literature. The book can be recommended for first-year graduate studies. It will be useful for all who intend to wo...
Some illustrations of stochasticity
Laslett, L.J.
1977-01-01
A complex, and apparently stochastic, character frequently can be seen to occur in the solutions to simple Hamiltonian problems. Such behavior is of interest, and potentially of importance, to designers of particle accelerators--as well as to workers in other fields of physics and related disciplines. Even a slow development of disorder in the motion of particles in a circular accelerator or storage ring could be troublesome, because a practical design requires the beam particles to remain confined in an orderly manner within a narrow beam tube for literally tens of billions of revolutions. The material presented is primarily the result of computer calculations made to investigate the occurrence of ''stochasticity,'' and is organized in a manner similar to that adopted for presentation at a 1974 accelerator conference
Essentials of stochastic processes
Durrett, Richard
2016-01-01
Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martingales, and option pricing. One can only learn a subject by seeing it in action, so there are a large number of examples and more than 300 carefully chosen exercises to deepen the reader’s understanding. Drawing from teaching experience and student feedback, there are many new examples and problems with solutions that use TI-83 to eliminate the tedious details of solving linear equations by hand, and the collection of exercises is much improved, with many more biological examples. Originally included in previous editions, material too advanced for this first course in stochastic processes has been eliminated while treatm...
Dynamic stochastic optimization
Ermoliev, Yuri; Pflug, Georg
2004-01-01
Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu tions. Objective an...
Stochastic porous media equations
Barbu, Viorel; Röckner, Michael
2016-01-01
Focusing on stochastic porous media equations, this book places an emphasis on existence theorems, asymptotic behavior and ergodic properties of the associated transition semigroup. Stochastic perturbations of the porous media equation have reviously been considered by physicists, but rigorous mathematical existence results have only recently been found. The porous media equation models a number of different physical phenomena, including the flow of an ideal gas and the diffusion of a compressible fluid through porous media, and also thermal propagation in plasma and plasma radiation. Another important application is to a model of the standard self-organized criticality process, called the "sand-pile model" or the "Bak-Tang-Wiesenfeld model". The book will be of interest to PhD students and researchers in mathematics, physics and biology.
Stochastic stacking without filters
Johnson, R.P.; Marriner, J.
1982-12-01
The rate of accumulation of antiprotons is a critical factor in the design of p anti p colliders. A design of a system to accumulate higher anti p fluxes is presented here which is an alternative to the schemes used at the CERN AA and in the Fermilab Tevatron I design. Contrary to these stacking schemes, which use a system of notch filters to protect the dense core of antiprotons from the high power of the stack tail stochastic cooling, an eddy current shutter is used to protect the core in the region of the stack tail cooling kicker. Without filters one can have larger cooling bandwidths, better mixing for stochastic cooling, and easier operational criteria for the power amplifiers. In the case considered here a flux of 1.4 x 10 8 per sec is achieved with a 4 to 8 GHz bandwidth
Multistage stochastic optimization
Pflug, Georg Ch
2014-01-01
Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today’s state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book
Identifiability in stochastic models
1992-01-01
The problem of identifiability is basic to all statistical methods and data analysis, occurring in such diverse areas as Reliability Theory, Survival Analysis, and Econometrics, where stochastic modeling is widely used. Mathematics dealing with identifiability per se is closely related to the so-called branch of ""characterization problems"" in Probability Theory. This book brings together relevant material on identifiability as it occurs in these diverse fields.
Stochastic split determinant algorithms
Horvatha, Ivan
2000-01-01
I propose a large class of stochastic Markov processes associated with probability distributions analogous to that of lattice gauge theory with dynamical fermions. The construction incorporates the idea of approximate spectral split of the determinant through local loop action, and the idea of treating the infrared part of the split through explicit diagonalizations. I suggest that exact algorithms of practical relevance might be based on Markov processes so constructed
Stochasticity Modeling in Memristors
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.
Stochasticity Modeling in Memristors
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.
Beilby, Mary J.
2016-01-01
The morphology of characean algae could be mistaken for a higher plant: stem-like axes with leaf-like branchlets anchored in the soil by root-like rhizoids. However, all of these structures are made up of giant multinucleate cells separated by multicellular nodal complexes. The excised internodal cells survive long enough for the nodes to give rise to new thallus. The size of the internodes and their thick cytoplasmic layer minimize impalement injury and allow specific micro-electrode placement. The cell structure can be manipulated by centrifugation, perfusion of cell contents or creation of cytoplasmic droplets, allowing access to both vacuolar and cytoplasmic compartments and both sides of the cell membranes. Thousands of electrical measurements on intact or altered cells and cytoplasmic droplets laid down basis to modern plant electrophysiology. Furthermore, the giant internodal cells and whole thalli facilitate research into many other plant properties. As nutrients have to be transported from rhizoids to growing parts of the thallus and hormonal signals need to pass from cell to cell, Characeae possess very fast cytoplasmic streaming. The mechanism was resolved in the characean model. Plasmodesmata between the internodal cells and nodal complexes facilitate transport of ions, nutrients and photosynthates across the nodes. The internal structure was found to be similar to those of higher plants. Recent experiments suggest a strong circadian influence on metabolic pathways producing indole-3-acetic acid (IAA) and serotonin/melatonin. The review will discuss the impact of the characean models arising from fragments of cells, single cells, cell-to-cell transport or whole thalli on understanding of plant evolution and physiology. PMID:27504112
Takizawa, Naoki; Okubo, Naoto; Kamo, Masaharu; Chosa, Naoyuki; Mikami, Toshinari; Suzuki, Keita; Yokota, Seiji; Ibi, Miho; Ohtsuka, Masato; Taira, Masayuki; Yaegashi, Takashi; Ishisaki, Akira; Kyakumoto, Seiko
2017-09-15
Immunosuppressive/anti-inflammatory macrophage (Mφ), M2-Mφ that expressed the typical M2-Mφs marker, CD206, and anti-inflammatory cytokine, interleukin (IL)-10, is beneficial and expected tool for the cytotherapy against inflammatory diseases. Here, we demonstrated that bone marrow-derived lineage-positive (Lin+) blood cells proliferated and differentiated into M2-Mφs by cooperation with the bone marrow-derived mesenchymal stem cells (MSCs) under hypoxic condition: MSCs not only promoted proliferation of undifferentiated M2-Mφs, pre-M2-Mφs, in the Lin+ fraction via a proliferative effect of the MSCs-secreted macrophage colony-stimulating factor, but also promoted M2-Mφ polarization of the pre-M2-Mφs through cell-to-cell contact with the pre-M2-Mφs. Intriguingly, an inhibitor for intercellular adhesion molecule (ICAM)-1 receptor/lymphocyte function-associated antigen (LFA)-1, Rwj50271, partially suppressed expression of CD206 in the Lin+ blood cells but an inhibitor for VCAM-1 receptor/VLA-4, BIO5192, did not, suggesting that the cell-to-cell adhesion through LFA-1 on pre-M2-Mφs and ICAM-1 on MSCs was supposed to promoted the M2-Mφ polarization. Thus, the co-culture system consisting of bone marrow-derived Lin+ blood cells and MSCs under hypoxic condition was a beneficial supplier of a number of M2-Mφs, which could be clinically applicable to inflammatory diseases. Copyright © 2017 Elsevier Inc. All rights reserved.
Fuchigami, Takao; Kibe, Toshiro; Koyama, Hirofumi; Kishida, Shosei; Iijima, Mikio; Nishizawa, Yoshiaki; Hijioka, Hiroshi; Fujii, Tomomi; Ueda, Masahiro; Nakamura, Norifumi; Kiyono, Tohru; Kishida, Michiko
2014-01-01
Highlights: • We studied the interaction between tumor cells and fibroblasts in ameloblastoma. • AM-3 ameloblastoma cells secreted significantly high IL-1α levels. • IL-1α derived from AM-3 cells promoted IL-6 and IL-8 secretion of fibroblasts. • IL-6 and IL-8 activated the cellular motility and proliferation of AM-3 cells. - Abstract: Ameloblastoma is an odontogenic benign tumor that occurs in the jawbone, which invades bone and reoccurs locally. This tumor is treated by wide surgical excision and causes various problems, including changes in facial countenance and mastication disorders. Ameloblastomas have abundant tumor stroma, including fibroblasts and immune cells. Although cell-to-cell interactions are considered to be involved in the pathogenesis of many diseases, intercellular communications in ameloblastoma have not been fully investigated. In this study, we examined interactions between tumor cells and stromal fibroblasts via soluble factors in ameloblastoma. We used a human ameloblastoma cell line (AM-3 ameloblastoma cells), human fibroblasts (HFF-2 fibroblasts), and primary-cultured fibroblasts from human ameloblastoma tissues, and analyzed the effect of ameloblastoma-associated cell-to-cell communications on gene expression, cytokine secretion, cellular motility and proliferation. AM-3 ameloblastoma cells secreted higher levels of interleukin (IL)-1α than HFF-2 fibroblasts. Treatment with conditioned medium from AM-3 ameloblastoma cells upregulated gene expression and secretion of IL-6 and IL-8 of HFF-2 fibroblasts and primary-cultured fibroblast cells from ameloblastoma tissues. The AM3-stimulated production of IL-6 and IL-8 in fibroblasts was neutralized by pretreatment of AM-3 cells with anti-IL-1α antibody and IL-1 receptor antagonist. Reciprocally, cellular motility of AM-3 ameloblastoma cells was stimulated by HFF-2 fibroblasts in IL-6 and IL-8 dependent manner. In conclusion, ameloblastoma cells and stromal fibroblasts behave
Fuchigami, Takao [Department of Biochemistry and Genetics, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544 (Japan); Department of Oral and Maxillofacial Surgery, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544 (Japan); Kibe, Toshiro [Department of Oral and Maxillofacial Surgery, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544 (Japan); Koyama, Hirofumi; Kishida, Shosei; Iijima, Mikio [Department of Biochemistry and Genetics, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544 (Japan); Nishizawa, Yoshiaki [Kagoshima University Faculty of Medicine, 8-35-1 Sakuragaoka, Kagoshima 890-8544 (Japan); Hijioka, Hiroshi; Fujii, Tomomi [Department of Oral and Maxillofacial Surgery, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544 (Japan); Ueda, Masahiro [Natural Science Centre for Research and Education, Kagoshima University, 1-21-24 Koorimoto, Kagoshima 890-8580 (Japan); Nakamura, Norifumi [Department of Oral and Maxillofacial Surgery, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544 (Japan); Kiyono, Tohru [Department of Virology, National Cancer Center Research Institute, 5-1-1 Tsukiji, Chuouku, Tokyo 104-0045 (Japan); Kishida, Michiko, E-mail: kmichiko@m2.kufm.kagoshima-u.ac.jp [Department of Biochemistry and Genetics, Kagoshima University Graduate School of Medical and Dental Sciences, 8-35-1 Sakuragaoka, Kagoshima 890-8544 (Japan)
2014-09-05
Highlights: • We studied the interaction between tumor cells and fibroblasts in ameloblastoma. • AM-3 ameloblastoma cells secreted significantly high IL-1α levels. • IL-1α derived from AM-3 cells promoted IL-6 and IL-8 secretion of fibroblasts. • IL-6 and IL-8 activated the cellular motility and proliferation of AM-3 cells. - Abstract: Ameloblastoma is an odontogenic benign tumor that occurs in the jawbone, which invades bone and reoccurs locally. This tumor is treated by wide surgical excision and causes various problems, including changes in facial countenance and mastication disorders. Ameloblastomas have abundant tumor stroma, including fibroblasts and immune cells. Although cell-to-cell interactions are considered to be involved in the pathogenesis of many diseases, intercellular communications in ameloblastoma have not been fully investigated. In this study, we examined interactions between tumor cells and stromal fibroblasts via soluble factors in ameloblastoma. We used a human ameloblastoma cell line (AM-3 ameloblastoma cells), human fibroblasts (HFF-2 fibroblasts), and primary-cultured fibroblasts from human ameloblastoma tissues, and analyzed the effect of ameloblastoma-associated cell-to-cell communications on gene expression, cytokine secretion, cellular motility and proliferation. AM-3 ameloblastoma cells secreted higher levels of interleukin (IL)-1α than HFF-2 fibroblasts. Treatment with conditioned medium from AM-3 ameloblastoma cells upregulated gene expression and secretion of IL-6 and IL-8 of HFF-2 fibroblasts and primary-cultured fibroblast cells from ameloblastoma tissues. The AM3-stimulated production of IL-6 and IL-8 in fibroblasts was neutralized by pretreatment of AM-3 cells with anti-IL-1α antibody and IL-1 receptor antagonist. Reciprocally, cellular motility of AM-3 ameloblastoma cells was stimulated by HFF-2 fibroblasts in IL-6 and IL-8 dependent manner. In conclusion, ameloblastoma cells and stromal fibroblasts behave
Experimental scaling of fluctuations and confinement with Lundquist number in the RFP
Stoneking, M.R.; Chapman, J.T.; Prager, S.C.; Sarff, J.S.
1997-09-01
The scaling of the magnetic and velocity fluctuations with Lundquist number (S) is examined experimentally over a range of values from 7 x 10 4 to 10 6 in a reversed field pinch (RFP) plasma. Magnetic fluctuations do not scale uniquely with the Lundquist number. At high (relative) density, fluctuations scale as b∝S -0.18 , and fluctuations are almost independent of S at low relative density, b∝S -0.07 ; however both exponents fall in the range of theoretical and numerical predictions. At high relative density, the scaling of the energy confinement time follows expectations for transport in a stochastic magnetic field. A confinement scaling law (nτ E ∝β 4/5 T -7/10 A -3/5 I φ 2 ) is derived assuming the persistent dominance of stochastic magnetic diffusion in the RFP and on the measured scaling of magnetic fluctuations. The peak velocity fluctuations during a sawtooth cycle scale marginally stronger than magnetic fluctuations but weaker than a simple Ohm's law prediction. The sawtooth period is determined by a resistive-Alfvenic hybrid time (T saw ∝√(τ R τ Alf )) rather than a purely resistive time
Stochastic Electrodynamics and the Compton effect
Franca, H.M.; Barranco, A.V.
1987-12-01
Some of the main qualitative features of the Compton effect are tried to be described within the realm of Classical Stochastic Electrodynamics (SED). It is found indications that the combined action of the incident wave (frequency ω), the radiation reaction force and the zero point fluctuating electromagnetic fields of SED, are able to given a high average recoil velocity v/c=α/(1+α) to the charged particle. The estimate of the parameter α gives α ∼ ℎω/mc 2 where 2Πℎ is the constant and mc 2 is the rest energy of the particle. It is verified that this recoil is just that necessary to explain the frequency shift, observed in the scattered radiation as due to a classical double Doppler shift. The differential cross section for the radiation scattered by the recoiling charge using classical electromagnetism also calculated. The same expression as obtained by Compton in his fundamental work of 1923 is found. (author) [pt
Stochastic and non-stochastic effects - a conceptual analysis
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)
Multifractal detrended fluctuation analysis of analog random multiplicative processes
Silva, L.B.M.; Vermelho, M.V.D. [Instituto de Fisica, Universidade Federal de Alagoas, Maceio - AL, 57072-970 (Brazil); Lyra, M.L. [Instituto de Fisica, Universidade Federal de Alagoas, Maceio - AL, 57072-970 (Brazil)], E-mail: marcelo@if.ufal.br; Viswanathan, G.M. [Instituto de Fisica, Universidade Federal de Alagoas, Maceio - AL, 57072-970 (Brazil)
2009-09-15
We investigate non-Gaussian statistical properties of stationary stochastic signals generated by an analog circuit that simulates a random multiplicative process with weak additive noise. The random noises are originated by thermal shot noise and avalanche processes, while the multiplicative process is generated by a fully analog circuit. The resulting signal describes stochastic time series of current interest in several areas such as turbulence, finance, biology and environment, which exhibit power-law distributions. Specifically, we study the correlation properties of the signal by employing a detrended fluctuation analysis and explore its multifractal nature. The singularity spectrum is obtained and analyzed as a function of the control circuit parameter that tunes the asymptotic power-law form of the probability distribution function.
[Symmetry is beauty - or is it? The rise and fall of fluctuating asymmetry].
Debat, Vincent
Fluctuating asymmetry is the stochastic, minor deviation from perfect symmetry in bilaterally symmetrical organisms. It reflects the limit of developmental precision. Such a precision can be influenced by various factors, both internal (genetic mutations, stochastic variation at every levels of development) and external (environmental influences). Fluctuating asymmetry has receive an extreme attention for the past few decades, that culminated in the 90s: it has been used as an estimator of heterozygosity, fitness, environmental stress, and widely applied to human biology, sociobiology and psychology before being more or less discredited in the early 2000s. The reasons for such an extreme popularity and then disgrace are discussed here. Far from suggesting to abandon the study of fluctuating asymmetry, we indicate some of the most promising research avenues. ‡. © 2016 médecine/sciences – Inserm.
Localized Spectral Analysis of Fluctuating Power Generation from Solar Energy Systems
Johan Nijs
2007-01-01
Full Text Available Fluctuations in solar irradiance are a serious obstacle for the future large-scale application of photovoltaics. Occurring regularly with the passage of clouds, they can cause unexpected power variations and introduce voltage dips to the power distribution system. This paper proposes the treatment of such fluctuating time series as realizations of a stochastic, locally stationary, wavelet process. Its local spectral density can be estimated from empirical data by means of wavelet periodograms. The wavelet approach allows the analysis of the amplitude of fluctuations per characteristic scale, hence, persistence of the fluctuation. Furthermore, conclusions can be drawn on the frequency of occurrence of fluctuations of different scale. This localized spectral analysis was applied to empirical data of two successive years. The approach is especially useful for network planning and load management of power distribution systems containing a high density of photovoltaic generation units.
A retrodictive stochastic simulation algorithm
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.
Stochastic processes and quantum theory
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.)
Beer bottle whistling: a stochastic Hopf bifurcation
Boujo, Edouard; Bourquard, Claire; Xiong, Yuan; Noiray, Nicolas
2017-11-01
Blowing in a bottle to produce sound is a popular and yet intriguing entertainment. We reproduce experimentally the common observation that the bottle ``whistles'', i.e. produces a distinct tone, for large enough blowing velocity and over a finite interval of blowing angle. For a given set of parameters, the whistling frequency stays constant over time while the acoustic pressure amplitude fluctuates. Transverse oscillations of the shear layer in the bottle's neck are clearly identified with time-resolved particle image velocimetry (PIV) and proper orthogonal decomposition (POD). To account for these observations, we develop an analytical model of linear acoustic oscillator (the air in the bottle) subject to nonlinear stochastic forcing (the turbulent jet impacting the bottle's neck). We derive a stochastic differential equation and, from the associated Fokker-Planck equation and the measured acoustic pressure signals, we identify the model's parameters with an adjoint optimization technique. Results are further validated experimentally, and allow us to explain (i) the occurrence of whistling in terms of linear instability, and (ii) the amplitude of the limit cycle as a competition between linear growth rate, noise intensity, and nonlinear saturation. E. B. and N. N. acknowledge support by Repower and the ETH Zurich Foundation.
Stochastic modeling of thermal fatigue crack growth
Radu, Vasile
2015-01-01
The book describes a systematic stochastic modeling approach for assessing thermal-fatigue crack-growth in mixing tees, based on the power spectral density of temperature fluctuation at the inner pipe surface. It shows the development of a frequency-temperature response function in the framework of single-input, single-output (SISO) methodology from random noise/signal theory under sinusoidal input. The frequency response of stress intensity factor (SIF) is obtained by a polynomial fitting procedure of thermal stress profiles at various instants of time. The method, which takes into account the variability of material properties, and has been implemented in a real-world application, estimates the probabilities of failure by considering a limit state function and Monte Carlo analysis, which are based on the proposed stochastic model. Written in a comprehensive and accessible style, this book presents a new and effective method for assessing thermal fatigue crack, and it is intended as a concise and practice-or...
Diffusive processes in a stochastic magnetic field
Wang, H.; Vlad, M.; Vanden Eijnden, E.; Spineanu, F.; Misguich, J.H.; Balescu, R.
1995-01-01
The statistical representation of a fluctuating (stochastic) magnetic field configuration is studied in detail. The Eulerian correlation functions of the magnetic field are determined, taking into account all geometrical constraints: these objects form a nondiagonal matrix. The Lagrangian correlations, within the reasonable Corrsin approximation, are reduced to a single scalar function, determined by an integral equation. The mean square perpendicular deviation of a geometrical point moving along a perturbed field line is determined by a nonlinear second-order differential equation. The separation of neighboring field lines in a stochastic magnetic field is studied. We find exponentiation lengths of both signs describing, in particular, a decay (on the average) of any initial anisotropy. The vanishing sum of these exponentiation lengths ensures the existence of an invariant which was overlooked in previous works. Next, the separation of a particle's trajectory from the magnetic field line to which it was initially attached is studied by a similar method. Here too an initial phase of exponential separation appears. Assuming the existence of a final diffusive phase, anomalous diffusion coefficients are found for both weakly and strongly collisional limits. The latter is identical to the well known Rechester-Rosenbluth coefficient, which is obtained here by a more quantitative (though not entirely deductive) treatment than in earlier works
Hybrid stochastic simplifications for multiscale gene networks
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.
Approaching complexity by stochastic methods: From biological systems to turbulence
Friedrich, Rudolf [Institute for Theoretical Physics, University of Muenster, D-48149 Muenster (Germany); Peinke, Joachim [Institute of Physics, Carl von Ossietzky University, D-26111 Oldenburg (Germany); Sahimi, Muhammad [Mork Family Department of Chemical Engineering and Materials Science, University of Southern California, Los Angeles, CA 90089-1211 (United States); Reza Rahimi Tabar, M., E-mail: mohammed.r.rahimi.tabar@uni-oldenburg.de [Department of Physics, Sharif University of Technology, Tehran 11155-9161 (Iran, Islamic Republic of); Institute of Physics, Carl von Ossietzky University, D-26111 Oldenburg (Germany); Fachbereich Physik, Universitaet Osnabrueck, Barbarastrasse 7, 49076 Osnabrueck (Germany)
2011-09-15
This review addresses a central question in the field of complex systems: given a fluctuating (in time or space), sequentially measured set of experimental data, how should one analyze the data, assess their underlying trends, and discover the characteristics of the fluctuations that generate the experimental traces? In recent years, significant progress has been made in addressing this question for a class of stochastic processes that can be modeled by Langevin equations, including additive as well as multiplicative fluctuations or noise. Important results have emerged from the analysis of temporal data for such diverse fields as neuroscience, cardiology, finance, economy, surface science, turbulence, seismic time series and epileptic brain dynamics, to name but a few. Furthermore, it has been recognized that a similar approach can be applied to the data that depend on a length scale, such as velocity increments in fully developed turbulent flow, or height increments that characterize rough surfaces. A basic ingredient of the approach to the analysis of fluctuating data is the presence of a Markovian property, which can be detected in real systems above a certain time or length scale. This scale is referred to as the Markov-Einstein (ME) scale, and has turned out to be a useful characteristic of complex systems. We provide a review of the operational methods that have been developed for analyzing stochastic data in time and scale. We address in detail the following issues: (i) reconstruction of stochastic evolution equations from data in terms of the Langevin equations or the corresponding Fokker-Planck equations and (ii) intermittency, cascades, and multiscale correlation functions.
Approaching complexity by stochastic methods: From biological systems to turbulence
Friedrich, Rudolf; Peinke, Joachim; Sahimi, Muhammad; Reza Rahimi Tabar, M.
2011-01-01
This review addresses a central question in the field of complex systems: given a fluctuating (in time or space), sequentially measured set of experimental data, how should one analyze the data, assess their underlying trends, and discover the characteristics of the fluctuations that generate the experimental traces? In recent years, significant progress has been made in addressing this question for a class of stochastic processes that can be modeled by Langevin equations, including additive as well as multiplicative fluctuations or noise. Important results have emerged from the analysis of temporal data for such diverse fields as neuroscience, cardiology, finance, economy, surface science, turbulence, seismic time series and epileptic brain dynamics, to name but a few. Furthermore, it has been recognized that a similar approach can be applied to the data that depend on a length scale, such as velocity increments in fully developed turbulent flow, or height increments that characterize rough surfaces. A basic ingredient of the approach to the analysis of fluctuating data is the presence of a Markovian property, which can be detected in real systems above a certain time or length scale. This scale is referred to as the Markov-Einstein (ME) scale, and has turned out to be a useful characteristic of complex systems. We provide a review of the operational methods that have been developed for analyzing stochastic data in time and scale. We address in detail the following issues: (i) reconstruction of stochastic evolution equations from data in terms of the Langevin equations or the corresponding Fokker-Planck equations and (ii) intermittency, cascades, and multiscale correlation functions.
Matsubara, Yoshitsugu; Musashi, Yasuo
2017-12-01
The purpose of this study is to explain fluctuations in email size. We have previously investigated the long-term correlations between email send requests and data flow in the system log of the primary staff email server at a university campus, finding that email size frequency follows a power-law distribution with two inflection points, and that the power-law property weakens the correlation of the data flow. However, the mechanism underlying this fluctuation is not completely understood. We collected new log data from both staff and students over six academic years and analyzed the frequency distribution thereof, focusing on the type of content contained in the emails. Furthermore, we obtained permission to collect "Content-Type" log data from the email headers. We therefore collected the staff log data from May 1, 2015 to July 31, 2015, creating two subdistributions. In this paper, we propose a model to explain these subdistributions, which follow log-normal-like distributions. In the log-normal-like model, email senders -consciously or unconsciously- regulate the size of new email sentences according to a normal distribution. The fitting of the model is acceptable for these subdistributions, and the model demonstrates power-law properties for large email sizes. An analysis of the length of new email sentences would be required for further discussion of our model; however, to protect user privacy at the participating organization, we left this analysis for future work. This study provides new knowledge on the properties of email sizes, and our model is expected to contribute to the decision on whether to establish upper size limits in the design of email services.
Stochastic Analysis with Financial Applications
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
Fluctuating Thermodynamics for Biological Processes
Ham, Sihyun
Because biomolecular processes are largely under thermodynamic control, dynamic extension of thermodynamics is necessary to uncover the mechanisms and driving factors of fluctuating processes. The fluctuating thermodynamics technology presented in this talk offers a practical means for the thermodynamic characterization of conformational dynamics in biomolecules. The use of fluctuating thermodynamics has the potential to provide a comprehensive picture of fluctuating phenomena in diverse biological processes. Through the application of fluctuating thermodynamics, we provide a thermodynamic perspective on the misfolding and aggregation of the various proteins associated with human diseases. In this talk, I will present the detailed concepts and applications of the fluctuating thermodynamics technology for elucidating biological processes. This work was supported by Samsung Science and Technology Foundation under Project Number SSTF-BA1401-13.
Big Bang or vacuum fluctuation
Zel'dovich, Ya.B.
1980-01-01
Some general properties of vacuum fluctuations in quantum field theory are described. The connection between the ''energy dominance'' of the energy density of vacuum fluctuations in curved space-time and the presence of singularity is discussed. It is pointed out that a de-Sitter space-time (with the energy density of the vacuum fluctuations in the Einstein equations) that matches the expanding Friedman solution may describe the history of the Universe before the Big Bang. (P.L.)
Fluctuations from dissipation in a hot non-Abelian plasma
Litim, Daniel F; Litim, Daniel F.; Manuel, Cristina
2000-01-01
We consider a transport equation of the Boltzmann-Langevin type for non-Abelian plasmas close to equilibrium to derive the spectral functions of the underlying microscopic fluctuations from the entropy. The correlator of the stochastic source is obtained from the dissipative processes in the plasma. This approach, based on classical transport theory, exploits the well-known link between a linearized collision integral, the entropy and the spectral functions. Applied to the ultra-soft modes of a hot non-Abelian (classical or quantum) plasma, the resulting spectral functions agree with earlier findings obtained from the microscopic theory. As a by-product, it follows that theorem.
Hardwick, Robert J.; Vennin, Vincent; Wands, David [Institute of Cosmology and Gravitation, University of Portsmouth, Dennis Sciama Building, Burnaby Road, Portsmouth, PO1 3FX (United Kingdom); Byrnes, Christian T.; Torrado, Jesús, E-mail: robert.hardwick@port.ac.uk, E-mail: vincent.vennin@port.ac.uk, E-mail: c.byrnes@sussex.ac.uk, E-mail: jesus.torrado@sussex.ac.uk, E-mail: david.wands@port.ac.uk [Department of Physics and Astronomy, University of Sussex, Brighton BN1 9QH (United Kingdom)
2017-10-01
We study the stochastic distribution of spectator fields predicted in different slow-roll inflation backgrounds. Spectator fields have a negligible energy density during inflation but may play an important dynamical role later, even giving rise to primordial density perturbations within our observational horizon today. During de-Sitter expansion there is an equilibrium solution for the spectator field which is often used to estimate the stochastic distribution during slow-roll inflation. However slow roll only requires that the Hubble rate varies slowly compared to the Hubble time, while the time taken for the stochastic distribution to evolve to the de-Sitter equilibrium solution can be much longer than a Hubble time. We study both chaotic (monomial) and plateau inflaton potentials, with quadratic, quartic and axionic spectator fields. We give an adiabaticity condition for the spectator field distribution to relax to the de-Sitter equilibrium, and find that the de-Sitter approximation is never a reliable estimate for the typical distribution at the end of inflation for a quadratic spectator during monomial inflation. The existence of an adiabatic regime at early times can erase the dependence on initial conditions of the final distribution of field values. In these cases, spectator fields acquire sub-Planckian expectation values. Otherwise spectator fields may acquire much larger field displacements than suggested by the de-Sitter equilibrium solution. We quantify the information about initial conditions that can be obtained from the final field distribution. Our results may have important consequences for the viability of spectator models for the origin of structure, such as the simplest curvaton models.
Hardwick, Robert J.; Vennin, Vincent; Wands, David; Byrnes, Christian T.; Torrado, Jesús
2017-01-01
We study the stochastic distribution of spectator fields predicted in different slow-roll inflation backgrounds. Spectator fields have a negligible energy density during inflation but may play an important dynamical role later, even giving rise to primordial density perturbations within our observational horizon today. During de-Sitter expansion there is an equilibrium solution for the spectator field which is often used to estimate the stochastic distribution during slow-roll inflation. However slow roll only requires that the Hubble rate varies slowly compared to the Hubble time, while the time taken for the stochastic distribution to evolve to the de-Sitter equilibrium solution can be much longer than a Hubble time. We study both chaotic (monomial) and plateau inflaton potentials, with quadratic, quartic and axionic spectator fields. We give an adiabaticity condition for the spectator field distribution to relax to the de-Sitter equilibrium, and find that the de-Sitter approximation is never a reliable estimate for the typical distribution at the end of inflation for a quadratic spectator during monomial inflation. The existence of an adiabatic regime at early times can erase the dependence on initial conditions of the final distribution of field values. In these cases, spectator fields acquire sub-Planckian expectation values. Otherwise spectator fields may acquire much larger field displacements than suggested by the de-Sitter equilibrium solution. We quantify the information about initial conditions that can be obtained from the final field distribution. Our results may have important consequences for the viability of spectator models for the origin of structure, such as the simplest curvaton models.
Thermodynamic theory of equilibrium fluctuations
Mishin, Y.
2015-01-01
The postulational basis of classical thermodynamics has been expanded to incorporate equilibrium fluctuations. The main additional elements of the proposed thermodynamic theory are the concept of quasi-equilibrium states, a definition of non-equilibrium entropy, a fundamental equation of state in the entropy representation, and a fluctuation postulate describing the probability distribution of macroscopic parameters of an isolated system. Although these elements introduce a statistical component that does not exist in classical thermodynamics, the logical structure of the theory is different from that of statistical mechanics and represents an expanded version of thermodynamics. Based on this theory, we present a regular procedure for calculations of equilibrium fluctuations of extensive parameters, intensive parameters and densities in systems with any number of fluctuating parameters. The proposed fluctuation formalism is demonstrated by four applications: (1) derivation of the complete set of fluctuation relations for a simple fluid in three different ensembles; (2) fluctuations in finite-reservoir systems interpolating between the canonical and micro-canonical ensembles; (3) derivation of fluctuation relations for excess properties of grain boundaries in binary solid solutions, and (4) derivation of the grain boundary width distribution for pre-melted grain boundaries in alloys. The last two applications offer an efficient fluctuation-based approach to calculations of interface excess properties and extraction of the disjoining potential in pre-melted grain boundaries. Possible future extensions of the theory are outlined.
Portfolio Optimization with Stochastic Dividends and Stochastic Volatility
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…
Stochastic ontogenetic growth model
West, B. J.; West, D.
2012-02-01
An ontogenetic growth model (OGM) for a thermodynamically closed system is generalized to satisfy both the first and second law of thermodynamics. The hypothesized stochastic ontogenetic growth model (SOGM) is shown to entail the interspecies allometry relation by explicitly averaging the basal metabolic rate and the total body mass over the steady-state probability density for the total body mass (TBM). This is the first derivation of the interspecies metabolic allometric relation from a dynamical model and the asymptotic steady-state distribution of the TBM is fit to data and shown to be inverse power law.
Stochastic calculus in physics
Fox, R.F.
1987-01-01
The relationship of Ito-Stratonovich stochastic calculus to studies of weakly colored noise is explained. A functional calculus approach is used to obtain an effective Fokker-Planck equation for the weakly colored noise regime. In a smooth limit, this representation produces the Stratonovich version of the Ito-Stratonovich calculus for white noise. It also provides an approach to steady state behavior for strongly colored noise. Numerical simulation algorithms are explored, and a novel suggestion is made for efficient and accurate simulation of white noise equations
The stochastic quality calculus
Zeng, Kebin; Nielson, Flemming; Nielson, Hanne Riis
2014-01-01
We introduce the Stochastic Quality Calculus in order to model and reason about distributed processes that rely on each other in order to achieve their overall behaviour. The calculus supports broadcast communication in a truly concurrent setting. Generally distributed delays are associated...... with the outputs and at the same time the inputs impose constraints on the waiting times. Consequently, the expected inputs may not be available when needed and therefore the calculus allows to express the absence of data.The communication delays are expressed by general distributions and the resulting semantics...
Stochastic conditional intensity processes
Bauwens, Luc; Hautsch, Nikolaus
2006-01-01
model allows for a wide range of (cross-)autocorrelation structures in multivariate point processes. The model is estimated by simulated maximum likelihood (SML) using the efficient importance sampling (EIS) technique. By modeling price intensities based on NYSE trading, we provide significant evidence......In this article, we introduce the so-called stochastic conditional intensity (SCI) model by extending Russell’s (1999) autoregressive conditional intensity (ACI) model by a latent common dynamic factor that jointly drives the individual intensity components. We show by simulations that the proposed...... for a joint latent factor and show that its inclusion allows for an improved and more parsimonious specification of the multivariate intensity process...
Stochastic cooling for beginners
Moehl, D.
1984-01-01
These two lectures have been prepared to give a simple introduction to the principles. In Part I we try to explain stochastic cooling using the time-domain picture which starts from the pulse response of the system. In Part II the discussion is repeated, looking more closely at the frequency-domain response. An attempt is made to familiarize the beginners with some of the elementary cooling equations, from the 'single particle case' up to equations which describe the evolution of the particle distribution. (orig.)
A stochastic SIRS epidemic model with infectious force under intervention strategies
Cai, Yongli; Kang, Yun; Banerjee, Malay; Wang, Weiming
2015-12-01
In this paper, we extend a classical SIRS epidemic model with the infectious forces under intervention strategies from a deterministic framework to a stochastic differential equation (SDE) one through introducing random fluctuations. The value of our study lies in two aspects. Mathematically, by using the Markov semigroups theory, we prove that the reproduction number R0S can be used to govern the stochastic dynamics of SDE model. If R0S 1, under mild extra conditions, it has an endemic stationary distribution which leads to the stochastical persistence of the disease. Epidemiologically, we find that random fluctuations can suppress disease outbreak, which can provide us some useful control strategies to regulate disease dynamics.
Stochastic modelling of conjugate heat transfer in near-wall turbulence
Pozorski, Jacek; Minier, Jean-Pierre
2006-01-01
The paper addresses the conjugate heat transfer in turbulent flows with temperature assumed to be a passive scalar. The Lagrangian approach is applied and the heat transfer is modelled with the use of stochastic particles. The intensity of thermal fluctuations in near-wall turbulence is determined from the scalar probability density function (PDF) with externally provided dynamical statistics. A stochastic model for the temperature field in the wall material is proposed and boundary conditions for stochastic particles at the solid-fluid interface are formulated. The heated channel flow with finite-thickness walls is considered as a validation case. Computation results for the mean temperature profiles and the variance of thermal fluctuations are presented and compared with available DNS data
Stochastic modelling of conjugate heat transfer in near-wall turbulence
Pozorski, Jacek [Institute of Fluid-Flow Machinery, Polish Academy of Sciences, Fiszera 14, 80952 Gdansk (Poland)]. E-mail: jp@imp.gda.pl; Minier, Jean-Pierre [Research and Development Division, Electricite de France, 6 quai Watier, 78400 Chatou (France)
2006-10-15
The paper addresses the conjugate heat transfer in turbulent flows with temperature assumed to be a passive scalar. The Lagrangian approach is applied and the heat transfer is modelled with the use of stochastic particles. The intensity of thermal fluctuations in near-wall turbulence is determined from the scalar probability density function (PDF) with externally provided dynamical statistics. A stochastic model for the temperature field in the wall material is proposed and boundary conditions for stochastic particles at the solid-fluid interface are formulated. The heated channel flow with finite-thickness walls is considered as a validation case. Computation results for the mean temperature profiles and the variance of thermal fluctuations are presented and compared with available DNS data.
Stochastic lag time in nucleated linear self-assembly
Tiwari, Nitin S. [Group Theory of Polymers and Soft Matter, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands); Schoot, Paul van der [Group Theory of Polymers and Soft Matter, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands); Institute for Theoretical Physics, Utrecht University, Leuvenlaan 4, 3584 CE Utrecht (Netherlands)
2016-06-21
Protein aggregation is of great importance in biology, e.g., in amyloid fibrillation. The aggregation processes that occur at the cellular scale must be highly stochastic in nature because of the statistical number fluctuations that arise on account of the small system size at the cellular scale. We study the nucleated reversible self-assembly of monomeric building blocks into polymer-like aggregates using the method of kinetic Monte Carlo. Kinetic Monte Carlo, being inherently stochastic, allows us to study the impact of fluctuations on the polymerization reactions. One of the most important characteristic features in this kind of problem is the existence of a lag phase before self-assembly takes off, which is what we focus attention on. We study the associated lag time as a function of system size and kinetic pathway. We find that the leading order stochastic contribution to the lag time before polymerization commences is inversely proportional to the system volume for large-enough system size for all nine reaction pathways tested. Finite-size corrections to this do depend on the kinetic pathway.
Trajectory averaging for stochastic approximation MCMC algorithms
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
Double diffusivity model under stochastic forcing
Chattopadhyay, Amit K.; Aifantis, Elias C.
2017-05-01
account all boundary layer fluctuations. Our stochastic-ILG diffusion calculation confirms rapprochement between theory and experiment, thereby benchmarking a new generation of gradient-based continuum models that conform closer to real-life fluctuating environments.
Magnetic fluctuations associated with density fluctuations in the tokamak edge
Kim, Y.J.; Gentle, K.W.; Ritz, C.P.; Rhodes, T.L.; Bengtson, R.D.
1989-01-01
Electrostatic density and potential fluctuations occurring with high amplitude near the edge of a tokamak are correlated with components of the fluctuating magnetic field measured outside the limiter radius. It has been established that this turbulence is associated with fluctuations in current as well as density and potential. The correlation extends for substantial toroidal distances, but only if the probes are displaced approximately along field lines, consistent with the short coherence lengths poloidally but long coherence lengths parallel to the field which are characteristic for this turbulence. Furthermore, the correlation can be found only with density fluctuations measured inside the limiter radius; density fluctuations behind the limiter have no detectable magnetic concomitant for the toroidally spaced probes used here. (author). Letter-to-the-editor. 12 refs, 3 figs
Ras activation by SOS: Allosteric regulation by altered fluctuation dynamics
Iversen, Lars; Tu, Hsiung-Lin; Lin, Wan-Chen; Christensen, Sune M.; Abel, Steven M.; Iwig, Jeff; Wu, Hung-Jen; Gureasko, Jodi; Rhodes, Christopher; Petit, Rebecca S.; Hansen, Scott D.; Thill, Peter; Yu, Cheng-Han; Stamou, Dimitrios; Chakraborty, Arup K.; Kuriyan, John; Groves, Jay T.
2014-01-01
Activation of the small guanosine triphosphatase H-Ras by the exchange factor Son of Sevenless (SOS) is an important hub for signal transduction. Multiple layers of regulation, through protein and membrane interactions, govern activity of SOS. We characterized the specific activity of individual SOS molecules catalyzing nucleotide exchange in H-Ras. Single-molecule kinetic traces revealed that SOS samples a broad distribution of turnover rates through stochastic fluctuations between distinct, long-lived (more than 100 seconds), functional states. The expected allosteric activation of SOS by Ras–guanosine triphosphate (GTP) was conspicuously absent in the mean rate. However, fluctuations into highly active states were modulated by Ras-GTP. This reveals a mechanism in which functional output may be determined by the dynamical spectrum of rates sampled by a small number of enzymes, rather than the ensemble average. PMID:24994643
Resonant behavior of a fractional oscillator with fluctuating frequency
Soika, Erkki; Mankin, Romi; Ainsaar, Ain
2010-01-01
The long-time behavior of the first moment for the output signal of a fractional oscillator with fluctuating frequency subjected to an external periodic force is considered. Colored fluctuations of the oscillator eigenfrequency are modeled as a dichotomous noise. The viscoelastic type friction kernel with memory is assumed as a power-law function of time. Using the Shapiro-Loginov formula, exact expressions for the response to an external periodic field and for the complex susceptibility are presented. On the basis of the exact formulas it is demonstrated that interplay of colored noise and memory can generate a variety of cooperation effects, such as multiresonances versus the driving frequency and the friction coefficient as well as stochastic resonance versus noise parameters. The necessary and sufficient conditions for the cooperation effects are also discussed. Particularly, two different critical memory exponents have been found, which mark dynamical transitions in the behavior of the system.
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.
Stochastic dynamic modeling of regular and slow earthquakes
Aso, N.; Ando, R.; Ide, S.
2017-12-01
Both regular and slow earthquakes are slip phenomena on plate boundaries and are simulated by a (quasi-)dynamic modeling [Liu and Rice, 2005]. In these numerical simulations, spatial heterogeneity is usually considered not only for explaining real physical properties but also for evaluating the stability of the calculations or the sensitivity of the results on the condition. However, even though we discretize the model space with small grids, heterogeneity at smaller scales than the grid size is not considered in the models with deterministic governing equations. To evaluate the effect of heterogeneity at the smaller scales we need to consider stochastic interactions between slip and stress in a dynamic modeling. Tidal stress is known to trigger or affect both regular and slow earthquakes [Yabe et al., 2015; Ide et al., 2016], and such an external force with fluctuation can also be considered as a stochastic external force. A healing process of faults may also be stochastic, so we introduce stochastic friction law. In the present study, we propose a stochastic dynamic model to explain both regular and slow earthquakes. We solve mode III problem, which corresponds to the rupture propagation along the strike direction. We use BIEM (boundary integral equation method) scheme to simulate slip evolution, but we add stochastic perturbations in the governing equations, which is usually written in a deterministic manner. As the simplest type of perturbations, we adopt Gaussian deviations in the formulation of the slip-stress kernel, external force, and friction. By increasing the amplitude of perturbations of the slip-stress kernel, we reproduce complicated rupture process of regular earthquakes including unilateral and bilateral ruptures. By perturbing external force, we reproduce slow rupture propagation at a scale of km/day. The slow propagation generated by a combination of fast interaction at S-wave velocity is analogous to the kinetic theory of gasses: thermal
Stochastic lattice model of synaptic membrane protein domains.
Li, Yiwei; Kahraman, Osman; Haselwandter, Christoph A
2017-05-01
Neurotransmitter receptor molecules, concentrated in synaptic membrane domains along with scaffolds and other kinds of proteins, are crucial for signal transmission across chemical synapses. In common with other membrane protein domains, synaptic domains are characterized by low protein copy numbers and protein crowding, with rapid stochastic turnover of individual molecules. We study here in detail a stochastic lattice model of the receptor-scaffold reaction-diffusion dynamics at synaptic domains that was found previously to capture, at the mean-field level, the self-assembly, stability, and characteristic size of synaptic domains observed in experiments. We show that our stochastic lattice model yields quantitative agreement with mean-field models of nonlinear diffusion in crowded membranes. Through a combination of analytic and numerical solutions of the master equation governing the reaction dynamics at synaptic domains, together with kinetic Monte Carlo simulations, we find substantial discrepancies between mean-field and stochastic models for the reaction dynamics at synaptic domains. Based on the reaction and diffusion properties of synaptic receptors and scaffolds suggested by previous experiments and mean-field calculations, we show that the stochastic reaction-diffusion dynamics of synaptic receptors and scaffolds provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the observed single-molecule trajectories, and spatial heterogeneity in the effective rates at which receptors and scaffolds are recycled at the cell membrane. Our work sheds light on the physical mechanisms and principles linking the collective properties of membrane protein domains to the stochastic dynamics that rule their molecular components.
Stochastic Blind Motion Deblurring
Xiao, Lei
2015-05-13
Blind motion deblurring from a single image is a highly under-constrained problem with many degenerate solutions. A good approximation of the intrinsic image can therefore only be obtained with the help of prior information in the form of (often non-convex) regularization terms for both the intrinsic image and the kernel. While the best choice of image priors is still a topic of ongoing investigation, this research is made more complicated by the fact that historically each new prior requires the development of a custom optimization method. In this paper, we develop a stochastic optimization method for blind deconvolution. Since this stochastic solver does not require the explicit computation of the gradient of the objective function and uses only efficient local evaluation of the objective, new priors can be implemented and tested very quickly. We demonstrate that this framework, in combination with different image priors produces results with PSNR values that match or exceed the results obtained by much more complex state-of-the-art blind motion deblurring algorithms.
Schilstra, Maria J; Martin, Stephen R
2009-01-01
Stochastic simulations may be used to describe changes with time of a reaction system in a way that explicitly accounts for the fact that molecules show a significant degree of randomness in their dynamic behavior. The stochastic approach is almost invariably used when small numbers of molecules or molecular assemblies are involved because this randomness leads to significant deviations from the predictions of the conventional deterministic (or continuous) approach to the simulation of biochemical kinetics. Advances in computational methods over the three decades that have elapsed since the publication of Daniel Gillespie's seminal paper in 1977 (J. Phys. Chem. 81, 2340-2361) have allowed researchers to produce highly sophisticated models of complex biological systems. However, these models are frequently highly specific for the particular application and their description often involves mathematical treatments inaccessible to the nonspecialist. For anyone completely new to the field to apply such techniques in their own work might seem at first sight to be a rather intimidating prospect. However, the fundamental principles underlying the approach are in essence rather simple, and the aim of this article is to provide an entry point to the field for a newcomer. It focuses mainly on these general principles, both kinetic and computational, which tend to be not particularly well covered in specialist literature, and shows that interesting information may even be obtained using very simple operations in a conventional spreadsheet.
AA, stochastic precooling pickup
CERN PhotoLab
1980-01-01
The freshly injected antiprotons were subjected to fast stochastic "precooling". In this picture of a precooling pickup, the injection orbit is to the left, the stack orbit to the far right. After several seconds of precooling with the system's kickers (in momentum and in the vertical plane), the precooled antiprotons were transferred, by means of RF, to the stack tail, where they were subjected to further stochastic cooling in momentum and in both transverse planes, until they ended up, deeply cooled, in the stack core. During precooling, a shutter near the central orbit shielded the pickups from the signals emanating from the stack-core, whilst the stack-core was shielded from the violent action of the precooling kickers by a shutter on these. All shutters were opened briefly during transfer of the precooled antiprotons to the stack tail. Here, the shutter is not yet mounted. Precooling pickups and kickers had the same design, except that the kickers had cooling circuits and the pickups had none. Peering th...
Behavioral Stochastic Resonance
Freund, Jan A.; Schimansky-Geier, Lutz; Beisner, Beatrix; Neiman, Alexander; Russell, David F.; Yakusheva, Tatyana; Moss, Frank
2001-03-01
Zooplankton emit weak electric fields into the surrounding water that originate from their own muscular activities associated with swimming and feeding. Juvenile paddlefish prey upon single zooplankton by detecting and tracking these weak electric signatures. The passive electric sense in the fish is provided by an elaborate array of electroreceptors, Ampullae Lorenzini, spread over the surface of an elongated rostrum. We have previously shown that the fish use stochastic resonance to enhance prey capture near the detection threshold of their sensory system. But stochastic resonance requires an external source of electrical noise in order to function. The required noise can be provided by a swarm of plankton, for example Daphnia. Thus juvenile paddlefish can detect and attack single Daphnia as outliers in the vicinity of the swarm by making use of noise from the swarm itself. From the power spectral density of the noise plus the weak signal from a single Daphnia we calculate the signal-to-noise ratio and the Fisher information at the surface of the paddlefish's rostrum. The results predict a specific attack pattern for the paddlefish that appears to be experimentally testable.
Stochastic programming with integer recourse
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
Thermal mixtures in stochastic mechanics
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.
Stochastic Pi-calculus Revisited
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...
Alternative Asymmetric Stochastic Volatility Models
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
Stochastic ferromagnetism analysis and numerics
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.
Charge Fluctuations in Nanoscale Capacitors
Limmer, D.T.; Merlet, C.; Salanne, M.; Chandler, D.; Madden, P.A.; van Roij, R.H.H.G.; Rotenberg, B.
2013-01-01
The fluctuations of the charge on an electrode contain information on the microscopic correlations within the adjacent fluid and their effect on the electronic properties of the interface. We investigate these fluctuations using molecular dynamics simulations in a constant-potential ensemble with
Fluctuating attention in Parkinson's disease
Starrfelt, Randi; Aarsland, Dag; Janvin, Carmen
2001-01-01
Lewy body dementia (DLB), which share many clinical and pathological features with Parkinson’s disease (PD), is charac- terised by marked fluctuations in cognition and consciousness. Fluctuating cognition has not been formally studied in PD, although some studies indicate that PD patients show...
Variance decomposition in stochastic simulators.
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.
Variance decomposition in stochastic simulators
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.
Brownian motion and stochastic calculus
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...
Variance decomposition in stochastic simulators
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.
Variance decomposition in stochastic simulators
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.
Nonequilibrium fluctuations in a resistor.
Garnier, N; Ciliberto, S
2005-06-01
In small systems where relevant energies are comparable to thermal agitation, fluctuations are of the order of average values. In systems in thermodynamical equilibrium, the variance of these fluctuations can be related to the dissipation constant in the system, exploiting the fluctuation-dissipation theorem. In nonequilibrium steady systems, fluctuations theorems (FT) additionally describe symmetry properties of the probability density functions (PDFs) of the fluctuations of injected and dissipated energies. We experimentally probe a model system: an electrical dipole driven out of equilibrium by a small constant current I, and show that FT are experimentally accessible and valid. Furthermore, we stress that FT can be used to measure the dissipated power P = R I2 in the system by just studying the PDFs' symmetries.
System Entropy Measurement of Stochastic Partial Differential Systems
Bor-Sen Chen
2016-03-01
Full Text Available System entropy describes the dispersal of a system’s energy and is an indication of the disorder of a physical system. Several system entropy measurement methods have been developed for dynamic systems. However, most real physical systems are always modeled using stochastic partial differential dynamic equations in the spatio-temporal domain. No efficient method currently exists that can calculate the system entropy of stochastic partial differential systems (SPDSs in consideration of the effects of intrinsic random fluctuation and compartment diffusion. In this study, a novel indirect measurement method is proposed for calculating of system entropy of SPDSs using a Hamilton–Jacobi integral inequality (HJII-constrained optimization method. In other words, we solve a nonlinear HJII-constrained optimization problem for measuring the system entropy of nonlinear stochastic partial differential systems (NSPDSs. To simplify the system entropy measurement of NSPDSs, the global linearization technique and finite difference scheme were employed to approximate the nonlinear stochastic spatial state space system. This allows the nonlinear HJII-constrained optimization problem for the system entropy measurement to be transformed to an equivalent linear matrix inequalities (LMIs-constrained optimization problem, which can be easily solved using the MATLAB LMI-toolbox (MATLAB R2014a, version 8.3. Finally, several examples are presented to illustrate the system entropy measurement of SPDSs.
The stochastic dance of circling sperm cells: sperm chemotaxis in the plane
Friedrich, B M; Juelicher, F [Max Planck Institute for the Physics of Complex Systems, Noethnitzer Strasse 38, 01187 Dresden (Germany)], E-mail: ben@pks.mpg.de, E-mail: julicher@pks.mpg.de
2008-12-15
Biological systems such as single cells must function in the presence of fluctuations. It has been shown in a two-dimensional experimental setup that sea urchin sperm cells move toward a source of chemoattractant along planar trochoidal swimming paths, i.e. drifting circles. In these experiments, a pronounced variability of the swimming paths is observed. We present a theoretical description of sperm chemotaxis in two dimensions which takes fluctuations into account. We derive a coarse-grained theory of stochastic sperm swimming paths in a concentration field of chemoattractant. Fluctuations enter as multiplicative noise in the equations for the sperm swimming path. We discuss the stochastic properties of sperm swimming and predict a concentration-dependence of the effective diffusion constant of sperm swimming which could be tested in experiments.
The stochastic dance of circling sperm cells: sperm chemotaxis in the plane
Friedrich, B M; Juelicher, F
2008-01-01
Biological systems such as single cells must function in the presence of fluctuations. It has been shown in a two-dimensional experimental setup that sea urchin sperm cells move toward a source of chemoattractant along planar trochoidal swimming paths, i.e. drifting circles. In these experiments, a pronounced variability of the swimming paths is observed. We present a theoretical description of sperm chemotaxis in two dimensions which takes fluctuations into account. We derive a coarse-grained theory of stochastic sperm swimming paths in a concentration field of chemoattractant. Fluctuations enter as multiplicative noise in the equations for the sperm swimming path. We discuss the stochastic properties of sperm swimming and predict a concentration-dependence of the effective diffusion constant of sperm swimming which could be tested in experiments.
Chang, Yu-Jen; Jeng, U-Ser; Chiang, Ya-Ling; Hwang, Ing-Shouh; Chen, Yun-Ru
2016-03-04
Hexanucleotide expansions, GGGGCC, in the non-coding regions of the C9orf72 gene were found in major frontotemporal lobar dementia and amyotrophic lateral sclerosis patients (C9FTD/ALS). In addition to possible RNA toxicity, several dipeptide repeats (DPRs) are translated through repeat-associated non-ATG-initiated translation. The DPRs, including poly(GA), poly(GR), poly(GP), poly(PR), and poly(PA), were found in the brains and spinal cords of C9FTD/ALS patients. Among the DPRs, poly(GA) is highly susceptible to form cytoplasmic inclusions, which is a characteristic of C9FTD/ALS. To elucidate DPR aggregation, we used synthetic (GA)15 DPR as a model system to examine the aggregation and structural properties in vitro. We found that (GA)15 with 15 repeats fibrillates rapidly and ultimately forms flat, ribbon-type fibrils evidenced by transmission electron microscopy and atomic force microscopy. The fibrils are capable of amyloid dye binding and contain a characteristic cross-β sheet structure, as revealed by x-ray scattering. Furthermore, using neuroblastoma cells, we demonstrated the neurotoxicity and cell-to-cell transmission property of (GA)15 DPR. Overall, our results show the structural and toxicity properties of GA DPR to facilitate future DPR-related therapeutic development. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.
Ishii, Keiichiro; Watanabe, Masami.
1994-01-01
To clarify the radio-adaptive response of normal cells to low-dose radiation, we irradiated human embryonic cells and HeLa cells with low-dose X-ray and examined the changes in sensitivity to subsequent high-dose X-irradiation. The results obtained were as follows; (1) When HE cells were irradiated by a high-dose of 200 cGy, the growth ratio of the living cells five days after the irradiation decreased to 37% of that of the cells which received no X-irradiation. When the cells received a preliminary irradiation of 10 to 20 cGy four hours before the irradiation of 200 cGy, the relative growth ratios increased significantly to 45-53%. (2) This preliminary irradiation effect was not observed in HeLa cells, being cancer cells. (3) When the HE cells suspended in a Ca 2+ iron-free medium or TPA added medium while receiving the preliminary irradiation of 13 cGy, the effect of the preliminary irradiation in increasing the relative growth ratio of living cells was not observed. (4) This indicates that normal cells shows an adaptive response to low-dose radiation and become more radioresistant. This phenomenon is considered to involve cell-to-cell communication maintained in normal cells and intracellular signal transduction in which Ca 2+ ion plays a role. (author)
Yunlong Shang
2017-02-01
Full Text Available Due to the low cost, small size, and ease of control, the switched-capacitor (SC battery equalizers are promising among active balancing methods. However, it is difficult to achieve the full cell equalization for the SC equalizers due to the inevitable voltage drops across Metal-Oxide-Semiconductor Field Effect Transistor (MOSFET switches. Moreover, when the voltage gap among cells is larger, the balancing efficiency is lower, while the balancing speed becomes slower as the voltage gap gets smaller. In order to soften these downsides, this paper proposes a cell-to-cell battery equalization topology with zero-current switching (ZCS and zero-voltage gap (ZVG among cells based on three-resonant-state SC converters. Based on the conventional inductor-capacitor (LC converter, an additional resonant path is built to release the charge of the capacitor into the inductor in each switching cycle, which lays the foundations for obtaining ZVG among cells, improves the balancing efficiency at a large voltage gap, and increases the balancing speed at a small voltage gap. A four-lithium-ion-cell prototype is applied to validate the theoretical analysis. Experiment results demonstrate that the proposed topology has good equalization performances with fast equalization, ZCS, and ZVG among cells.
Clare Jolly
2011-09-01
Full Text Available Direct cell-cell spread of Human Immunodeficiency Virus type-1 (HIV-1 at the virological synapse (VS is an efficient mode of dissemination between CD4(+ T cells but the mechanisms by which HIV-1 proteins are directed towards intercellular contacts is unclear. We have used confocal microscopy and electron tomography coupled with functional virology and cell biology of primary CD4(+ T cells from normal individuals and patients with Chediak-Higashi Syndrome and report that the HIV-1 VS displays a regulated secretion phenotype that shares features with polarized secretion at the T cell immunological synapse (IS. Cell-cell contact at the VS re-orientates the microtubule organizing center (MTOC and organelles within the HIV-1-infected T cell towards the engaged target T cell, concomitant with polarization of viral proteins. Directed secretion of proteins at the T cell IS requires specialized organelles termed secretory lysosomes (SL and we show that the HIV-1 envelope glycoprotein (Env localizes with CTLA-4 and FasL in SL-related compartments and at the VS. Finally, CD4(+ T cells that are disabled for regulated secretion are less able to support productive cell-to-cell HIV-1 spread. We propose that HIV-1 hijacks the regulated secretory pathway of CD4(+ T cells to enhance its dissemination.
Molecules with an induced dipole moment in a stochastic electric field.
Band, Y B; Ben-Shimol, Y
2013-10-01
The mean-field dynamics of a molecule with an induced dipole moment (e.g., a homonuclear diatomic molecule) in a deterministic and a stochastic (fluctuating) electric field is solved to obtain the decoherence properties of the system. The average (over fluctuations) electric dipole moment and average angular momentum as a function of time for a Gaussian white noise electric field are determined via perturbative and nonperturbative solutions in the fluctuating field. In the perturbative solution, the components of the average electric dipole moment and the average angular momentum along the deterministic electric field direction do not decay to zero, despite fluctuations in all three components of the electric field. This is in contrast to the decay of the average over fluctuations of a magnetic moment in a Gaussian white noise magnetic field. In the nonperturbative solution, the component of the average electric dipole moment and the average angular momentum in the deterministic electric field direction also decay to zero.
Can Intrinsic Fluctuations Increase Efficiency in Neural Information Processing?
Liljenström, Hans
2003-05-01
All natural processes are accompanied by fluctuations, characterized as noise or chaos. Biological systems, which have evolved during billions of years, are likely to have adapted, not only to cope with such fluctuations, but also to make use of them. We investigate how the complex dynamics of the brain, including oscillations, chaos and noise, can affect the efficiency of neural information processing. In particular, we consider the amplification and functional role of internal fluctuations. Using computer simulations of a neural network model of the olfactory cortex and hippocampus, we demonstrate how microscopic fluctuations can result in global effects at the network level. We show that the rate of information processing in associative memory tasks can be maximized for optimal noise levels, analogous to stochastic resonance phenomena. Noise can also induce transitions between different dynamical states, which could be of significance for learning and memory. A chaotic-like behavior, induced by noise or by an increase in neuronal excitability, can enhance system performance if it is transient and converges to a limit cycle memory state. We speculate whether this dynamical behavior perhaps could be related to (creative) thinking.
Nonergodicity, fluctuations, and criticality in heterogeneous diffusion processes.
Cherstvy, A G; Metzler, R
2014-07-01
We study the stochastic behavior of heterogeneous diffusion processes with the power-law dependence D(x) ∼ |x|(α) of the generalized diffusion coefficient encompassing sub- and superdiffusive anomalous diffusion. Based on statistical measures such as the amplitude scatter of the time-averaged mean-squared displacement of individual realizations, the ergodicity breaking and non-Gaussianity parameters, as well as the probability density function P(x,t), we analyze the weakly nonergodic character of the heterogeneous diffusion process and, particularly, the degree of irreproducibility of individual realizations. As we show, the fluctuations between individual realizations increase with growing modulus |α| of the scaling exponent. The fluctuations appear to diverge when the critical value α = 2 is approached, while for even larger α the fluctuations decrease, again. At criticality, the power-law behavior of the mean-squared displacement changes to an exponentially fast growth, and the fluctuations of the time-averaged mean-squared displacement do not converge for increasing number of realizations. From a systematic comparison we observe some striking similarities of the heterogeneous diffusion process with the familiar subdiffusive continuous time random walk process with power-law waiting time distribution and diverging characteristic waiting time.
Klyatskin, Valery I
2015-01-01
This monograph set presents a consistent and self-contained framework of stochastic dynamic systems with maximal possible completeness. Volume 1 presents the basic concepts, exact results, and asymptotic approximations of the theory of stochastic equations on the basis of the developed functional approach. This approach offers a possibility of both obtaining exact solutions to stochastic problems for a number of models of fluctuating parameters and constructing various asymptotic buildings. Ideas of statistical topography are used to discuss general issues of generating coherent structures from chaos with probability one, i.e., almost in every individual realization of random parameters. The general theory is illustrated with certain problems and applications of stochastic mathematical physics in various fields such as mechanics, hydrodynamics, magnetohydrodynamics, acoustics, optics, and radiophysics.
Energy loss of ions by electric-field fluctuations in a magnetized plasma.
Nersisyan, Hrachya B; Deutsch, Claude
2011-06-01
The results of a theoretical investigation of the energy loss of charged particles in a magnetized classical plasma due to the electric-field fluctuations are reported. The energy loss for a test particle is calculated through the linear-response theory. At vanishing magnetic field, the electric-field fluctuations lead to an energy gain of the charged particle for all velocities. It has been shown that in the presence of strong magnetic field, this effect occurs only at low velocities. In the case of high velocities, the test particle systematically loses its energy due to the interaction with a stochastic electric field. The net effect of the fluctuations is the systematic reduction of the total energy loss (i.e., the sum of the polarization and stochastic energy losses) at vanishing magnetic field and reduction or enhancement at strong field, depending on the velocity of the particle. It is found that the energy loss of the slow heavy ion contains an anomalous term that depends logarithmically on the projectile mass. The physical origin of this anomalous term is the coupling between the cyclotron motion of the plasma electrons and the long-wavelength, low-frequency fluctuations produced by the projectile ion. This effect may strongly enhance the stochastic energy gain of the particle.
Quantum fluctuations from thermal fluctuations in Jacobson formalism
Faizal, Mir [University of British Columbia-Okanagan, Irving K. Barber School of Arts and Sciences, Kelowna, BC (Canada); University of Lethbridge, Department of Physics and Astronomy, Lethbridge, AB (Canada); Ashour, Amani; Alcheikh, Mohammad [Damascus University, Mathematics Department, Faculty of Science, Damascus (Syrian Arab Republic); Alasfar, Lina [Universite Clermont Auvergne, Laboratoire de Physique Corpusculaire de Clermont-Ferrand, Aubiere (France); Alsaleh, Salwa; Mahroussah, Ahmed [King Saud University, Department of Physics and Astronomy, Riyadh (Saudi Arabia)
2017-09-15
In the Jacobson formalism general relativity is obtained from thermodynamics. This is done by using the Bekenstein-Hawking entropy-area relation. However, as a black hole gets smaller, its temperature will increase. This will cause the thermal fluctuations to also increase, and these will in turn correct the Bekenstein-Hawking entropy-area relation. Furthermore, with the reduction in the size of the black hole, quantum effects will also start to dominate. Just as the general relativity can be obtained from thermodynamics in the Jacobson formalism, we propose that the quantum fluctuations to the geometry can be obtained from thermal fluctuations. (orig.)
Environmental versus demographic variability in stochastic predator–prey models
Dobramysl, U; Täuber, U C
2013-01-01
In contrast to the neutral population cycles of the deterministic mean-field Lotka–Volterra rate equations, including spatial structure and stochastic noise in models for predator–prey interactions yields complex spatio-temporal structures associated with long-lived erratic population oscillations. Environmental variability in the form of quenched spatial randomness in the predation rates results in more localized activity patches. Our previous study showed that population fluctuations in rare favorable regions in turn cause a remarkable increase in the asymptotic densities of both predators and prey. Very intriguing features are found when variable interaction rates are affixed to individual particles rather than lattice sites. Stochastic dynamics with demographic variability in conjunction with inheritable predation efficiencies generate non-trivial time evolution for the predation rate distributions, yet with overall essentially neutral optimization. (paper)
Information theory and stochastics for multiscale nonlinear systems
Majda, Andrew J; Grote, Marcus J
2005-01-01
This book introduces mathematicians to the fascinating emerging mathematical interplay between ideas from stochastics and information theory and important practical issues in studying complex multiscale nonlinear systems. It emphasizes the serendipity between modern applied mathematics and applications where rigorous analysis, the development of qualitative and/or asymptotic models, and numerical modeling all interact to explain complex phenomena. After a brief introduction to the emerging issues in multiscale modeling, the book has three main chapters. The first chapter is an introduction to information theory with novel applications to statistical mechanics, predictability, and Jupiter's Red Spot for geophysical flows. The second chapter discusses new mathematical issues regarding fluctuation-dissipation theorems for complex nonlinear systems including information flow, various approximations, and illustrates applications to various mathematical models. The third chapter discusses stochastic modeling of com...
Stochasticity in processes fundamentals and applications to chemistry and biology
Schuster, Peter
2016-01-01
This book has developed over the past fifteen years from a modern course on stochastic chemical kinetics for graduate students in physics, chemistry and biology. The first part presents a systematic collection of the mathematical background material needed to understand probability, statistics, and stochastic processes as a prerequisite for the increasingly challenging practical applications in chemistry and the life sciences examined in the second part. Recent advances in the development of new techniques and in the resolution of conventional experiments at nano-scales have been tremendous: today molecular spectroscopy can provide insights into processes down to scales at which current theories at the interface of physics, chemistry and the life sciences cannot be successful without a firm grasp of randomness and its sources. Routinely measured data is now sufficiently accurate to allow the direct recording of fluctuations. As a result, the sampling of data and the modeling of relevant processes are doomed t...
Stochastic Model of Vesicular Sorting in Cellular Organelles
Vagne, Quentin; Sens, Pierre
2018-02-01
The proper sorting of membrane components by regulated exchange between cellular organelles is crucial to intracellular organization. This process relies on the budding and fusion of transport vesicles, and should be strongly influenced by stochastic fluctuations, considering the relatively small size of many organelles. We identify the perfect sorting of two membrane components initially mixed in a single compartment as a first passage process, and we show that the mean sorting time exhibits two distinct regimes as a function of the ratio of vesicle fusion to budding rates. Low ratio values lead to fast sorting but result in a broad size distribution of sorted compartments dominated by small entities. High ratio values result in two well-defined sorted compartments but sorting is exponentially slow. Our results suggest an optimal balance between vesicle budding and fusion for the rapid and efficient sorting of membrane components and highlight the importance of stochastic effects for the steady-state organization of intracellular compartments.
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.
Anisotropic KPZ growth in 2+1 dimensions: fluctuations and covariance structure
Borodin, Alexei; Ferrari, Patrik L
2009-01-01
In Borodin and Ferrari (2008 arXiv:0804.3035) we studied an interacting particle system which can be also interpreted as a stochastic growth model. This model belongs to the anisotropic KPZ class in 2+1 dimensions. In this paper we present the results that are relevant from the perspective of stochastic growth models, in particular: (a) the surface fluctuations are asymptotically Gaussian on a √ln t scale and (b) the correlation structure of the surface is asymptotically given by the massless field
Effects of Demographic Noise on the Synchronization of a Metapopulation in a Fluctuating Environment
Lai, Yi Ming
2011-09-08
We use the theory of noise-induced phase synchronization to analyze the effects of demographic noise on the synchronization of a metapopulation of predator-prey systems within a fluctuating environment (Moran effect). Treating each local predator-prey population as a stochastic urn model, we derive a Langevin equation for the stochastic dynamics of the metapopulation. Assuming each local population acts as a limit cycle oscillator in the deterministic limit, we use phase reduction and averaging methods to derive the steady-state probability density for pairwise phase differences between oscillators, which is then used to determine the degree of synchronization of the metapopulation. © 2011 American Physical Society.
Morgan, Byron JT; Tanner, Martin Abba; Carlin, Bradley P
2008-01-01
Introduction and Examples Introduction Examples of data sets Basic Model Fitting Introduction Maximum-likelihood estimation for a geometric model Maximum-likelihood for the beta-geometric model Modelling polyspermy Which model? What is a model for? Mechanistic models Function Optimisation Introduction MATLAB: graphs and finite differences Deterministic search methods Stochastic search methods Accuracy and a hybrid approach Basic Likelihood ToolsIntroduction Estimating standard errors and correlations Looking at surfaces: profile log-likelihoods Confidence regions from profiles Hypothesis testing in model selectionScore and Wald tests Classical goodness of fit Model selection biasGeneral Principles Introduction Parameterisation Parameter redundancy Boundary estimates Regression and influence The EM algorithm Alternative methods of model fitting Non-regular problemsSimulation Techniques Introduction Simulating random variables Integral estimation Verification Monte Carlo inference Estimating sampling distributi...
Stochastic population theories
Ludwig, Donald
1974-01-01
These notes serve as an introduction to stochastic theories which are useful in population biology; they are based on a course given at the Courant Institute, New York, in the Spring of 1974. In order to make the material. accessible to a wide audience, it is assumed that the reader has only a slight acquaintance with probability theory and differential equations. The more sophisticated topics, such as the qualitative behavior of nonlinear models, are approached through a succession of simpler problems. Emphasis is placed upon intuitive interpretations, rather than upon formal proofs. In most cases, the reader is referred elsewhere for a rigorous development. On the other hand, an attempt has been made to treat simple, useful models in some detail. Thus these notes complement the existing mathematical literature, and there appears to be little duplication of existing works. The authors are indebted to Miss Jeanette Figueroa for her beautiful and speedy typing of this work. The research was supported by the Na...
Propagator of stochastic electrodynamics
Cavalleri, G.
1981-01-01
The ''elementary propagator'' for the position of a free charged particle subject to the zero-point electromagnetic field with Lorentz-invariant spectral density proportionalω 3 is obtained. The nonstationary process for the position is solved by the stationary process for the acceleration. The dispersion of the position elementary propagator is compared with that of quantum electrodynamics. Finally, the evolution of the probability density is obtained starting from an initial distribution confined in a small volume and with a Gaussian distribution in the velocities. The resulting probability density for the position turns out to be equal, to within radiative corrections, to psipsi* where psi is the Kennard wave packet. If the radiative corrections are retained, the present result is new since the corresponding expression in quantum electrodynamics has not yet been found. Besides preceding quantum electrodynamics for this problem, no renormalization is required in stochastic electrodynamics
RES: Regularized Stochastic BFGS Algorithm
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.
Current density fluctuations and ambipolarity of transport
Shen, W.; Dexter, R.N.; Prager, S.C.
1991-10-01
The fluctuation in the plasma current density is measured in the MIST reversed field pinch experiment. Such fluctuations, and the measured radial profile of the k spectrum of magnetic fluctuations, supports the view and that low frequency fluctuations (f r >) demonstrates that radial particle transport from particle motion parallel to a fluctuating magnetic field is ambipolar over the full frequency range
Quantum fluctuation theorems and power measurements
Prasanna Venkatesh, B; Watanabe, Gentaro; Talkner, Peter
2015-01-01
Work in the paradigm of the quantum fluctuation theorems of Crooks and Jarzynski is determined by projective measurements of energy at the beginning and end of the force protocol. In analogy to classical systems, we consider an alternative definition of work given by the integral of the supplied power determined by integrating up the results of repeated measurements of the instantaneous power during the force protocol. We observe that such a definition of work, in spite of taking account of the process dependence, has different possible values and statistics from the work determined by the conventional two energy measurement approach (TEMA). In the limit of many projective measurements of power, the system’s dynamics is frozen in the power measurement basis due to the quantum Zeno effect leading to statistics only trivially dependent on the force protocol. In general the Jarzynski relation is not satisfied except for the case when the instantaneous power operator commutes with the total Hamiltonian at all times. We also consider properties of the joint statistics of power-based definition of work and TEMA work in protocols where both values are determined. This allows us to quantify their correlations. Relaxing the projective measurement condition, weak continuous measurements of power are considered within the stochastic master equation formalism. Even in this scenario the power-based work statistics is in general not able to reproduce qualitative features of the TEMA work statistics. (paper)
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.
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.
Stochastic estimation of electricity consumption
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)
Linear stochastic neutron transport theory
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)
Stochasticity in the Josephson map
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)
Introduction to stochastic dynamic programming
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
ARMA modelling of neutron stochastic processes with large measurement noise
Zavaljevski, N.; Kostic, Lj.; Pesic, M.
1994-01-01
An autoregressive moving average (ARMA) model of the neutron fluctuations with large measurement noise is derived from langevin stochastic equations and validated using time series data obtained during prompt neutron decay constant measurements at the zero power reactor RB in Vinca. Model parameters are estimated using the maximum likelihood (ML) off-line algorithm and an adaptive pole estimation algorithm based on the recursive prediction error method (RPE). The results show that subcriticality can be determined from real data with high measurement noise using much shorter statistical sample than in standard methods. (author)
Study of the stochastic point reactor kinetic equation
Gotoh, Yorio
1980-01-01
Diagrammatic technique is used to solve the stochastic point reactor kinetic equation. The method gives exact results which are derived from Fokker-Plank theory. A Green's function dressed with the clouds of noise is defined, which is a transfer function of point reactor with fluctuating reactivity. An integral equation for the correlation function of neutron power is derived using the following assumptions: 1) Green's funntion should be dressed with noise, 2) The ladder type diagrams only contributes to the correlation function. For a white noise and the one delayed neutron group approximation, the norm of the integral equation and the variance to mean-squared ratio are analytically obtained. (author)
Unifying three perspectives on information processing in stochastic thermodynamics.
Barato, A C; Seifert, U
2014-03-07
So far, feedback-driven systems have been discussed using (i) measurement and control, (ii) a tape interacting with a system, or (iii) by identifying an implicit Maxwell demon in steady-state transport. We derive the corresponding second laws from one master fluctuation theorem and discuss their relationship. In particular, we show that both the entropy production involving mutual information between system and controller and the one involving a Shannon entropy difference of an information reservoir like a tape carry an extra term different from the usual current times affinity. We, thus, generalize stochastic thermodynamics to the presence of an information reservoir.
Functional Abstraction of Stochastic Hybrid Systems
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
An introduction to probability and stochastic processes
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.
Abhinav Parihar
2018-04-01
Full Text Available Artificial neural networks can harness stochasticity in multiple ways to enable a vast class of computationally powerful models. Boltzmann machines and other stochastic neural networks have been shown to outperform their deterministic counterparts by allowing dynamical systems to escape local energy minima. Electronic implementation of such stochastic networks is currently limited to addition of algorithmic noise to digital machines which is inherently inefficient; albeit recent efforts to harness physical noise in devices for stochasticity have shown promise. To succeed in fabricating electronic neuromorphic networks we need experimental evidence of devices with measurable and controllable stochasticity which is complemented with the development of reliable statistical models of such observed stochasticity. Current research literature has sparse evidence of the former and a complete lack of the latter. This motivates the current article where we demonstrate a stochastic neuron using an insulator-metal-transition (IMT device, based on electrically induced phase-transition, in series with a tunable resistance. We show that an IMT neuron has dynamics similar to a piecewise linear FitzHugh-Nagumo (FHN neuron and incorporates all characteristics of a spiking neuron in the device phenomena. We experimentally demonstrate spontaneous stochastic spiking along with electrically controllable firing probabilities using Vanadium Dioxide (VO2 based IMT neurons which show a sigmoid-like transfer function. The stochastic spiking is explained by two noise sources - thermal noise and threshold fluctuations, which act as precursors of bifurcation. As such, the IMT neuron is modeled as an Ornstein-Uhlenbeck (OU process with a fluctuating boundary resulting in transfer curves that closely match experiments. The moments of interspike intervals are calculated analytically by extending the first-passage-time (FPT models for Ornstein-Uhlenbeck (OU process to include a