Cell-to-Cell stochastic fluctuations in apoptotic signaling can decide between life and death
Raychaudhuri, S; Nguyen, T; Khan, E M; Goldkorn, T
2007-01-01
Apoptosis, or genetically programmed cell death, is a crucial cellular process that maintains the balance between life and death in cells. The precise molecular mechanism of apoptosis signaling and how these two pathways are differentially activated under distinct apoptotic stimuli is poorly understood. We developed a Monte Carlo-based stochastic simulation model that can characterize distinct signaling behaviors in the two major pathways of apoptotic signaling using a novel probability distribution-based approach. Specifically, we show that for a weak death signal, such as low levels of death ligand Fas (CD95) binding or under stress conditions, the type 2 mitochondrial pathway dominates apoptotic signaling. Our results also show signaling in the type 2 pathway is stochastic, where the population average over many cells does not capture the cell-to-cell fluctuations in the time course (~1 - 10 hours) of downstream caspase-3 activation. On the contrary, the probability distribution of caspase-3 activation for...
Fluctuations as stochastic deformation
Kazinski, P. O.
2008-04-01
A notion of stochastic deformation is introduced and the corresponding algebraic deformation procedure is developed. This procedure is analogous to the deformation of an algebra of observables like deformation quantization, but for an imaginary deformation parameter (the Planck constant). This method is demonstrated on diverse relativistic and nonrelativistic models with finite and infinite degrees of freedom. It is shown that under stochastic deformation the model of a nonrelativistic particle interacting with the electromagnetic field on a curved background passes into the stochastic model described by the Fokker-Planck equation with the diffusion tensor being the inverse metric tensor. The first stochastic correction to the Newton equations for this system is found. The Klein-Kramers equation is also derived as the stochastic deformation of a certain classical model. Relativistic generalizations of the Fokker-Planck and Klein-Kramers equations are obtained by applying the procedure of stochastic deformation to appropriate relativistic classical models. The analog of the Fokker-Planck equation associated with the stochastic Lorentz-Dirac equation is derived too. The stochastic deformation of the models of a free scalar field and an electromagnetic field is investigated. It turns out that in the latter case the obtained stochastic model describes a fluctuating electromagnetic field in a transparent medium.
Mesoscopic Fluctuations in Stochastic Spacetime
Shiokawa, K
2000-01-01
Mesoscopic effects associated with wave propagation in spacetime with metric stochasticity are studied. We show that the scalar and spinor waves in a stochastic spacetime behave similarly to the electrons in a disordered system. Viewing this as the quantum transport problem, mesoscopic fluctuations in such a spacetime are discussed. The conductance and its fluctuations are expressed in terms of a nonlinear sigma model in the closed time path formalism. We show that the conductance fluctuations are universal, independent of the volume of the stochastic region and the amount of stochasticity.
From single-cell to cell-pool transcriptomes: stochasticity in gene expression and RNA splicing.
Marinov, Georgi K; Williams, Brian A; McCue, Ken; Schroth, Gary P; Gertz, Jason; Myers, Richard M; Wold, Barbara J
2014-03-01
Single-cell RNA-seq mammalian transcriptome studies are at an early stage in uncovering cell-to-cell variation in gene expression, transcript processing and editing, and regulatory module activity. Despite great progress recently, substantial challenges remain, including discriminating biological variation from technical noise. Here we apply the SMART-seq single-cell RNA-seq protocol to study the reference lymphoblastoid cell line GM12878. By using spike-in quantification standards, we estimate the absolute number of RNA molecules per cell for each gene and find significant variation in total mRNA content: between 50,000 and 300,000 transcripts per cell. We directly measure technical stochasticity by a pool/split design and find that there are significant differences in expression between individual cells, over and above technical variation. Specific gene coexpression modules were preferentially expressed in subsets of individual cells, including one enriched for mRNA processing and splicing factors. We assess cell-to-cell variation in alternative splicing and allelic bias and report evidence of significant differences in splice site usage that exceed splice variation in the pool/split comparison. Finally, we show that transcriptomes from small pools of 30-100 cells approach the information content and reproducibility of contemporary RNA-seq from large amounts of input material. Together, our results define an experimental and computational path forward for analyzing gene expression in rare cell types and cell states.
Stochastic Einstein equations with fluctuating volume
Dzhunushaliev, Vladimir
2016-01-01
We develop a simple model to study classical fields on the background of a fluctuating spacetime volume. It is applied to formulate the stochastic Einstein equations with a perfect-fluid source. We investigate the particular case of a stochastic Friedmann-Lema\\^itre-Robertson-Walker cosmology, and show that the resulting field equations can lead to solutions which avoid the initial big bang singularity. By interpreting the fluctuations as the result of the presence of a quantum spacetime, we conclude that classical singularities can be avoided even within a stochastic model that include quantum effects in a very simple manner.
Mapping current fluctuations of stochastic pumps to nonequilibrium steady states
Rotskoff, Grant M.
2017-03-01
We show that current fluctuations in a stochastic pump can be robustly mapped to fluctuations in a corresponding time-independent nonequilibrium steady state. We thus refine a recently proposed mapping so that it ensures equivalence of not only the averages, but also optimal representation of fluctuations in currents and density. Our mapping leads to a natural decomposition of the entropy production in stochastic pumps similar to the "housekeeping" heat. As a consequence of the decomposition of entropy production, the current fluctuations in weakly perturbed stochastic pumps are shown to satisfy a universal bound determined by the steady state entropy production.
Stochastic isocurvature baryon fluctuations, baryon diffusion, and primordial nucleosynthesis
Kurki-Suonio, H; Mathews, G J; Kurki-Suonio, Hannu; Jedamzik, Karsten; Mathews, Grant J
1996-01-01
We examine effects on primordial nucleosynthesis from a truly random spatial distribution in the baryon-to-photon ratio (\\eta). We generate stochastic fluctuation spectra characterized by different spectral indices and root-mean-square fluctuation amplitudes. For the first time we explicitly calculate the effects of baryon diffusion on the nucleosynthesis yields of such stochastic fluctuations. We also consider the collapse instability of large-mass-scale inhomogeneities. Our results are generally applicable to any primordial mechanism producing fluctuations in \\eta which can be characterized by a spectral index. In particular, these results apply to primordial isocurvature baryon fluctuation (PIB) models. The amplitudes of scale-invariant baryon fluctuations are found to be severely constrained by primordial nucleosynthesis. However, when the \\eta distribution is characterized by decreasing fluctuation amplitudes with increasing length scale, surprisingly large fluctuation amplitudes on the baryon diffusion ...
Current fluctuations in stochastic systems with long-range memory
Energy Technology Data Exchange (ETDEWEB)
Harris, R J; Touchette, H [School of Mathematical Sciences, Queen Mary University of London, Mile End Road, London, E1 4NS (United Kingdom)], E-mail: rosemary.harris@qmul.ac.uk, E-mail: h.touchette@qmul.ac.uk
2009-08-28
We propose a method to calculate the large deviations of current fluctuations in a class of stochastic particle systems with history-dependent rates. Long-range temporal correlations are seen to alter the speed of the large deviation function in analogy with long-range spatial correlations in equilibrium systems. We give some illuminating examples and discuss the applicability of the Gallavotti-Cohen fluctuation theorem. (fast track communication)
Gravitational brainwaves, quantum fluctuations and stochastic quantization
Bar, D
2007-01-01
It is known that the biological activity of the brain involves radiation of electric waves. These waves result from ionic currents and charges traveling among the brain's neurons. But it is obvious that these ions and charges are carried by their relevant masses which should give rise, according to the gravitational theory, to extremely weak gravitational waves. We use in the following the stochastic quantization (SQ) theory to calculate the probability to find a large ensemble of brains radiating similar gravitational waves. We also use this SQ theory to derive the equilibrium state related to the known Lamb shift.
Posterior Probability and Fluctuation Theorem in Stochastic Processes
Ohkubo, Jun
2009-12-01
A generalization of fluctuation theorems in stochastic processes is proposed. The new theorem is written in terms of posterior probabilities, which are introduced via Bayes’ theorem. In conventional fluctuation theorems, a forward path and its time reversal play an important role, so that a microscopically reversible condition is essential. In contrast, the microscopically reversible condition is not necessary in the new theorem. It is shown that the new theorem recovers various theorems and relations previously known, such as the Gallavotti-Cohen-type fluctuation theorem, the Jarzynski equality, and the Hatano-Sasa relation, when suitable assumptions are employed.
Stochastic Heisenberg limit: optimal estimation of a fluctuating phase.
Berry, Dominic W; Hall, Michael J W; Wiseman, Howard M
2013-09-13
The ultimate limits to estimating a fluctuating phase imposed on an optical beam can be found using the recently derived continuous quantum Cramér-Rao bound. For Gaussian stationary statistics, and a phase spectrum scaling asymptotically as ω(-p) with p>1, the minimum mean-square error in any (single-time) phase estimate scales as N(-2(p-1)/(p+1)), where N is the photon flux. This gives the usual Heisenberg limit for a constant phase (as the limit p→∞) and provides a stochastic Heisenberg limit for fluctuating phases. For p=2 (Brownian motion), this limit can be attained by phase tracking.
Effective cosmological constant induced by stochastic fluctuations of Newton's constant
de Cesare, Marco; Sakellariadou, Mairi
2016-01-01
We consider implications of the microscopic dynamics of spacetime for the evolution of cosmological models. We argue that quantum geometry effects may lead to stochastic fluctuations of the gravitational constant, which is thus considered as a macroscopic effective dynamical quantity. Consistency with Riemannian geometry entails the presence of a time-dependent dark energy term in the modified field equations, which can be expressed in terms of the dynamical gravitational constant. We suggest that the late-time accelerated expansion of the Universe may be ascribed to quantum fluctuations in the geometry of spacetime rather than the vacuum energy from the matter sector.
Effective cosmological constant induced by stochastic fluctuations of Newton's constant
de Cesare, Marco; Lizzi, Fedele; Sakellariadou, Mairi
2016-09-01
We consider implications of the microscopic dynamics of spacetime for the evolution of cosmological models. We argue that quantum geometry effects may lead to stochastic fluctuations of the gravitational constant, which is thus considered as a macroscopic effective dynamical quantity. Consistency with Riemannian geometry entails the presence of a time-dependent dark energy term in the modified field equations, which can be expressed in terms of the dynamical gravitational constant. We suggest that the late-time accelerated expansion of the Universe may be ascribed to quantum fluctuations in the geometry of spacetime rather than the vacuum energy from the matter sector.
Stochastic Dynamics of Infrared Fluctuations in Accelerating Universe
Cho, Gihyuk; Kitamoto, Hiroyuki
2015-01-01
We extend investigations of infrared dynamics in accelerating universes. In the presence of massless and minimally coupled scalar fields, physical quantities may acquire growing time dependences through quantum fluctuations at super-horizon scales. From a semiclassical viewpoint, it was proposed that such infrared effects are described by a Langevin equation. In de Sitter space, the stochastic approach has been proved to be equivalent to resummation of the growing time dependences at the leading power. In this paper, we make the resummation derivation of the Langevin equation in a general accelerating universe. We first consider an accelerating universe whose slow-roll parameter is constant, and then extend the background as the slow-roll parameter becomes time dependent. The resulting Langevin equation contains a white noise term and the coefficient of each term is modified by the slow-roll parameter. Furthermore we find that the semiclassical description of the scalar fields leads to the same stochastic equ...
Stochasticity and Spatial Resonance in Interdecadal Climate Fluctuations.
Saravanan, R.; McWilliams, James C.
1997-09-01
Ocean-atmosphere interaction plays a key role in climate fluctuations on interdecadal timescales. In this study, different aspects of this interaction are investigated using an idealized ocean-atmosphere model, and a hierarchy of uncoupled and stochastic models derived from it. The atmospheric component is an eddy-resolving two-level global primitive equation model with simplified physical parameterizations. The oceanic component is a zonally averaged sector model of the thermohaline circulation. The coupled model exhibits spontaneous oscillations of the thermohaline circulation on interdecadal timescales. The interdecadal oscillation has qualitatively realistic features, such as dipolar sea surface temperature anomalies in the extratropics. Atmospheric forcing of the ocean plays a dominant role in exciting this oscillation. Although the coupled model is in itself deterministic, it is convenient to conceptualize the atmospheric forcing arising from weather excitation as having stochastic time dependence. Spatial correlations inherent in the atmospheric low-frequency variability play a crucial role in determining the oceanic interdecadal variability, through a form of spatial resonance. Local feedback from the ocean affects the amplitude of the interdecadal variability. The spatial patterns of correlations between the atmospheric flow and the oceanic variability fall into two categories: (i) upstream forcing patterns, and (ii) downstream response patterns. Both categories of patterns are expressible as linear combinations of the dominant modes of variability associated with the uncoupled atmosphere.
Stochastic amplification of fluctuations in cortical up-states.
Directory of Open Access Journals (Sweden)
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 Amplification of Fluctuations in Cortical Up-States
Hidalgo, Jorge; Seoane, Luís F.; Cortés, Jesús M.; Muñoz, Miguel A.
2012-01-01
Cortical neurons are bistable; as a consequence their local field potentials can fluctuate between quiescent and active states, generating slow 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 Hz appears in their associated power-spectra, what produces an enhancement of the activity power for higher frequencies (in the 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. PMID:22879879
Stochastic fluctuations and the detectability limit of network communities
Lucio, Floretta; Alessandro, Flammini; Paolo, De Los Rios
2013-01-01
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 conclusions that the native, putative partition of the network is completely lost even before the in-degree/out-degree ratio becomes equal to the one of a structure-less Erd\\"os-R\\'enyi 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 (semi-quantitatively) 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...
Study of TEC fluctuation via stochastic models and Bayesian inversion
Bires, A.; Roininen, L.; Damtie, B.; Nigussie, M.; Vanhamäki, H.
2016-11-01
We propose stochastic processes to be used to model the total electron content (TEC) observation. Based on this, we model the rate of change of TEC (ROT) variation during ionospheric quiet conditions with stationary processes. During ionospheric disturbed conditions, for example, when irregularity in ionospheric electron density distribution occurs, stationarity assumption over long time periods is no longer valid. In these cases, we make the parameter estimation for short time scales, during which we can assume stationarity. We show the relationship between the new method and commonly used TEC characterization parameters ROT and the ROT Index (ROTI). We construct our parametric model within the framework of Bayesian statistical inverse problems and hence give the solution as an a posteriori probability distribution. Bayesian framework allows us to model measurement errors systematically. Similarly, we mitigate variation of TEC due to factors which are not of ionospheric origin, like due to the motion of satellites relative to the receiver, by incorporating a priori knowledge in the Bayesian model. In practical computations, we draw the so-called maximum a posteriori estimates, which are our ROT and ROTI estimates, from the posterior distribution. Because the algorithm allows to estimate ROTI at each observation time, the estimator does not depend on the period of time for ROTI computation. We verify the method by analyzing TEC data recorded by GPS receiver located in Ethiopia (11.6°N, 37.4°E). The results indicate that the TEC fluctuations caused by the ionospheric irregularity can be effectively detected and quantified from the estimated ROT and ROTI values.
Institute of Scientific and Technical Information of China (English)
MA Song-Hua; LI Jing-Hui; JIANG Yong-Qing; FANG Jian-Ping
2008-01-01
A single (independent of each other) protein motor system with fluctuating potential barrier and subject to sine electric field is investigated. We first derive the approximate Langevin equation of this system with fluctuating potential barrier. Then from this approximate Langevin equation, we calculate the signal-to-noise ratio (SNR) in the adiabatic limit. The phenomenon of stochastic resonance is found for this protein motor system with fluctuating potential barrier.
Stochastic bifurcation, slow fluctuations, and bistability as an origin of biochemical complexity.
Qian, Hong; Shi, Pei-Zhe; Xing, Jianhua
2009-06-28
We present a simple, unifying theory for stochastic biochemical systems with multiple time-scale dynamics that exhibit noise-induced bistability in an open-chemical environment, while the corresponding macroscopic reaction is unistable. Nonlinear stochastic biochemical systems like these are fundamentally different from classical systems in equilibrium or near-equilibrium steady state whose fluctuations are unimodal following Einstein-Onsager-Lax-Keizer theory. We show that noise-induced bistability in general arises from slow fluctuations, and a pitchfork bifurcation occurs as the rate of fluctuations decreases. Since an equilibrium distribution, due to detailed balance, has to be independent of changes in time-scale, the bifurcation is necessarily a driven phenomenon. As examples, we analyze three biochemical networks of currently interest: self-regulating gene, stochastic binary decision, and phosphorylation-dephosphorylation cycle with fluctuating kinase. The implications of bistability to biochemical complexity are discussed.
Non Equilibrium Current Fluctuations in Stochastic Lattice Gases
Bertini, L.; Sole, A. De; Gabrielli, D.; Jona-Lasinio, G.; Landim, C.
2006-04-01
We study current fluctuations in lattice gases in the macroscopic limit extending the dynamic approach for density fluctuations developed in previous articles. More precisely, we establish a large deviation principle for a space-time fluctuation j of the empirical current with a rate functional I( j). We then estimate the probability of a fluctuation of the average current over a large time interval; this probability can be obtained by solving a variational problem for the functional I. We discuss several possible scenarios, interpreted as dynamical phase transitions, for this variational problem. They actually occur in specific models. We finally discuss the time reversal properties of I and derive a fluctuation relationship akin to the Gallavotti-Cohen theorem for the entropy production.
FAST TRACK COMMUNICATION: Current fluctuations in stochastic systems with long-range memory
Harris, R. J.; Touchette, H.
2009-08-01
We propose a method to calculate the large deviations of current fluctuations in a class of stochastic particle systems with history-dependent rates. Long-range temporal correlations are seen to alter the speed of the large deviation function in analogy with long-range spatial correlations in equilibrium systems. We give some illuminating examples and discuss the applicability of the Gallavotti-Cohen fluctuation theorem.
Enhanced stochastic fluctuations to measure steep adhesive energy landscapes.
Haider, Ahmad; Potter, Daniel; Sulchek, Todd A
2016-12-13
Free-energy landscapes govern the behavior of all interactions in the presence of thermal fluctuations in the fields of physical chemistry, materials sciences, and the biological sciences. From the energy landscape, critical information about an interaction, such as the reaction kinetic rates, bond lifetimes, and the presence of intermediate states, can be determined. Despite the importance of energy landscapes to understanding reaction mechanisms, most experiments do not directly measure energy landscapes, particularly for interactions with steep force gradients that lead to premature jump to contact of the probe and insufficient sampling of transition regions. Here we present an atomic force microscopy (AFM) approach for measuring energy landscapes that increases sampling of strongly adhesive interactions by using white-noise excitation to enhance the cantilever's thermal fluctuations. The enhanced fluctuations enable the recording of subtle deviations from a harmonic potential to accurately reconstruct interfacial energy landscapes with steep gradients. Comparing the measured energy landscape with adhesive force measurements reveals the existence of an optimal excitation voltage that enables the cantilever fluctuations to fully sample the shape and depth of the energy surface.
Shearer, Joseph; Boone, Deborah; Weisz, Harris; Jennings, Kristofer; Uchida, Tatsuo; Parsley, Margaret; DeWitt, Douglas; Prough, Donald; Hellmich, Helen
2016-04-01
Traumatic brain injury (TBI) is a risk factor for age-related dementia and development of neurodegenerative disorders such as Alzheimer's disease that are associated with cognitive decline. The exact mechanism for this risk is unknown but we hypothesized that TBI is exacerbating age-related changes in gene expression. Here, we present evidence in an animal model that experimental TBI increases age-related stochastic gene expression. We compared the variability in expression of several genes associated with cell survival or death, among three groups of laser capture microdissected hippocampal neurons from aging rat brains. TBI increased stochastic fluctuations in gene expression in both dying and surviving neurons compared to the naïve neurons. Increases in random, stochastic fluctuations in prosurvival or prodeath gene expression could potentially alter cell survival or cell death pathways in aging neurons after TBI which may lead to age-related cognitive decline.
A model for the optimal design of a supply chain network driven by stochastic fluctuations
Petridis, Kostas; Dey, Prasanta K
2015-01-01
Supply chain optimization schemes have more often than not underplayed the role of inherent stochastic fluctuations in the associated variables. The present article focuses on the associated reengagement and correlated renormalization of supply chain predictions now with the inclusion of stochasticity induced fluctuations in the structure. With a processing production plant in mind that involves stochastically varying production and transportation costs both from the site to the plant as well as from the plant to the customer base, this article proves that the producer may benefit through better outlay in the form of higher sale prices with lowered optimized production costs only through a suitable selective choice of producers whose production cost probability density function abides a Pareto distribution. Lower the Pareto exponent, better is the supply chain prediction for cost optimization. On the other hand, other symmetric (normal) and asymmetric (lognormal) distributions lead to upscaled costs both in t...
Emergence of dynamic cooperativity in the stochastic kinetics of fluctuating enzymes.
Kumar, Ashutosh; Chatterjee, Sambarta; Nandi, Mintu; Dua, Arti
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.
Five-dimensional scenario with a fluctuating three-brane an stochastic approach to gravity
Quirós, I
2001-01-01
A five-dimensional scenario with a non compact extra dimension of infinite extent is studied, in which a single three-brane is affected by small Gaussian fluctuations in the extra dimension. The average magnitude of the fluctuations is of order of the electro-weak length scale ($\\sigma\\sim m_{EW}^{-1}$). The model provides an stochastic approach to gravity that accounts for an alternative resolution of the mass hierarchy problem. The cosmological constant problem can be suitably treated as well. Surprisingly the Mach's principle finds a place in the model. It is argued that the Mach's principle, the mass hierarchy and the cosmological constant problem, are different aspects of a same property of gravity in this model: its stochastic character. Thin-brane scenarios are recovered in the "no-fluctuations" limit ($\\sigma\\to 0$).
Emergence of Dynamic Cooperativity in the Stochastic Kinetics of Fluctuating Enzymes
Kumar, Ashutosh; Nandi, Mintu; Dua, Arti
2016-01-01
Dynamic cooperativity 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 cooperativity in terms of a slowing down of the Michaelis-Menten (MM) kinetics resulting in negative cooperativity. For fewer enzymes, dynamic cooperativity emerges due to the combined effects of enzymatic conformational fluctuations and molecular discreteness. The increase in the number of enzymes, how...
Zhang, Yue; Zheng, Yan; Liu, Xi; Zhang, Qingling; Li, Aihua
2016-11-01
This study considers a class of differential algebraic stage-structured bio-economic models with stochastic fluctuations. The stochastic bio-economic model is simplified to an Itô equation using the stochastic averaging method. The stochastic stability, Hopf bifurcation, and P-bifurcation are discussed based on the singular boundary theory of the diffusion process for the system and the invariant measure theory of dynamic systems. Numerical simulations are presented to illustrate our main results.
Nonequilibrium Steady State Thermodynamics and Fluctuations for Stochastic Systems
Taniguchi, Tooru; Cohen, E. G. D.
2008-02-01
We use the work done on and the heat removed from a system to maintain it in a nonequilibrium steady state for a thermodynamic-like description of such a system as well as of its fluctuations. Based on an extended Onsager-Machlup theory for nonequilibrium steady states we indicate two ambiguities, not present in an equilibrium state, in defining such work and heat: one due to a non-uniqueness of time-reversal procedures and another due to multiple possibilities to separate heat into work and an energy difference in nonequilibrium steady states. As a consequence, for such systems, the work and heat satisfy multiple versions of the first and second laws of thermodynamics as well as of their fluctuation theorems. Unique laws and relations appear only to be obtainable for concretely defined systems, using physical arguments to choose the relevant physical quantities. This is illustrated on a number of systems, including a Brownian particle in an electric field, a driven torsion pendulum, electric circuits and an energy transfer driven by a temperature difference.
Rocha, Paulo; Raischel, Frank; Boto, João P.; Lind, Pedro G.
2016-05-01
We present a framework for describing the evolution of stochastic observables having a nonstationary distribution of values. The framework is applied to empirical volume-prices from assets traded at the New York Stock Exchange, about which several remarks are pointed out from our analysis. Using Kullback-Leibler divergence we evaluate the best model out of four biparametric models commonly used in the context of financial data analysis. In our present data sets we conclude that the inverse Γ distribution is a good model, particularly for the distribution tail of the largest volume-price fluctuations. Extracting the time series of the corresponding parameter values we show that they evolve in time as stochastic variables themselves. For the particular case of the parameter controlling the volume-price distribution tail we are able to extract an Ornstein-Uhlenbeck equation which describes the fluctuations of the highest volume-prices observed in the data. Finally, we discuss how to bridge the gap from the stochastic evolution of the distribution parameters to the stochastic evolution of the (nonstationary) observable and put our conclusions into perspective for other applications in geophysics and biology.
A stochastic approach to thermal fluctuations during a first order electroweak phase transition
Illuminati, F
1995-01-01
We investigate the role played by subcritical bubbles at the onset of the electroweak phase transition. Treating the configuration modelling the thermal fluctuations around the homogeneous zero configuration of the Higgs field as a stochastic variable, we describe its dynamics by a phenomenological Langevin equation. This approach allows to properly take into account both the effects of the thermal bath on the system: a systematic dyssipative force, which tends to erase out any initial subcritical configuration, and a random stochastic force responsible for the fluctuations. We show that the contribution to the variance \\lgh\\phi^2(t)\\rg_V in a given volume V from any initial subcritical configuration is quickly damped away and that, in the limit of long times, \\lgh\\phi^2(t)\\rg_V approaches its equilibrium value provided by the stochastic force and independent from the viscosity coefficient, as predicted by the fluctuation-dissipation theorem. In agreement with some recent claims, we conclude that thermal fluc...
Directory of Open Access Journals (Sweden)
Daniel Stockholm
Full Text Available BACKGROUND: In culture, isogenic mammalian cells typically display enduring phenotypic heterogeneity that arises from fluctuations of gene expression and other intracellular processes. This diversity is not just simple noise but has biological relevance by generating plasticity. Noise driven plasticity was suggested to be a stem cell-specific feature. RESULTS: Here we show that the phenotypes of proliferating tissue progenitor cells such as primary mononuclear muscle cells can also spontaneously fluctuate between different states characterized by the either high or low expression of the muscle-specific cell surface molecule CD56 and by the corresponding high or low capacity to form myotubes. Although this capacity is a cell-intrinsic property, the cells switch their phenotype under the constraints imposed by the highly heterogeneous microenvironment created by their own collective movement. The resulting heterogeneous cell population is characterized by a dynamic equilibrium between "high CD56" and "low CD56" phenotype cells with distinct spatial distribution. Computer simulations reveal that this complex dynamic is consistent with a context-dependent noise driven bistable model where local microenvironment acts on the cellular state by encouraging the cell to fluctuate between the phenotypes until the low noise state is found. CONCLUSIONS: These observations suggest that phenotypic fluctuations may be a general feature of any non-terminally differentiated cell. The cellular microenvironment created by the cells themselves contributes actively and continuously to the generation of fluctuations depending on their phenotype. As a result, the cell phenotype is determined by the joint action of the cell-intrinsic fluctuations and by collective cell-to-cell interactions.
Fluctuations of large-scale jets in the stochastic 2D Euler equation
Nardini, Cesare
2016-01-01
Two-dimensional turbulence in a rectangular domain self-organises into large-scale unidirectional jets. While several results are present to characterize the mean jets velocity profile, much less is known about the fluctuations. We study jets dynamics in the stochastically forced two-dimensional Euler equations. In the limit where the average jets velocity profile evolves slowly with respect to turbulent fluctuations, we employ a multi-scale (kinetic theory) approach, which relates jet dynamics to the statistics of Reynolds stresses. We study analytically the Gaussian fluctuations of Reynolds stresses and predict the spatial structure of the jets velocity covariance. Our results agree qualitatively well with direct numerical simulations, clearly showing that the jets velocity profile are enhanced away from the stationary points of the average velocity profile. A numerical test of our predictions at quantitative level seems out of reach at the present day.
Stochastic Faraday rotation induced by the electric current fluctuations in nanosystems
Smirnov, D. S.; Glazov, M. M.
2017-01-01
We demonstrate theoretically that in gyrotropic semiconductors and semiconductor nanosystems the Brownian motion of electrons results in temporal fluctuations of the polarization plane of light passing through or reflected from the structure, i.e., in stochastic Faraday or Kerr rotation effects. The theory of the effects is developed for a number of prominent gyrotropic systems such as bulk tellurium, ensembles of chiral carbon nanotubes, and GaAs-based quantum wells of different crystallographic orientations. We show that the power spectrum of these fluctuations in thermal equilibrium is proportional to the a c conductivity of the system. We evaluate contributions resulting from the fluctuations of the electric current, as well as of spin, valley polarization, and the spin current to the noise of the Faraday/Kerr rotation. Hence all-optical measurements of the Faraday and Kerr rotation noise provide an access to the transport properties of the semiconductor systems.
Zhou, Shenggao; Sun, Hui; Cheng, Li-Tien; Dzubiella, Joachim; Li, Bo; McCammon, J Andrew
2016-08-01
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 inclusion of
Experimental study of the stochastic heating of a single Brownian particle by charge fluctuations
Schmidt, Christian; Piel, Alexander
2016-08-01
The Brownian motion of a micro-particle, which is suspended in the sheath of a radio-frequency discharge, is studied by high-speed video microscopy. In this environment, stochastic heating by charge fluctuations is expected, which should lead to an anisotropic kinetic temperature of the particle with a preferential heating in the direction of the mean electric field in the sheath. The stochastic heating should become more effective at low gas pressures where cooling by the neutral gas becomes ineffective. Our refined experiments confirm the anisotropic heating and the temperature rise for diminishing pressure. Particle-in-cell simulations have guided us in modifying the gap width of the discharge and to specify the dependence of the plasma density on gas pressure as n i ∝ p 1 / 2 . Since the stochastic heating rate also depends on the life-time of charge fluctuations, a temperature scaling T kin ∝ p 3 / 2 results, which is in agreement with the experimental data. The experimental procedure to eliminate other spurious heating mechanisms is described in detail.
Energy Technology Data Exchange (ETDEWEB)
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.
Energy Technology Data Exchange (ETDEWEB)
Mekkaoui, A. [Institute for Energy and Climate Research-Plasma Physics, Research Center Juelich GmbH, Association FZJ-Euratom, D-52425 Juelich (Germany)
2013-01-15
A stochastic differential equation for intermittent plasma density dynamics in magnetic fusion edge plasma is derived, which is consistent with the experimentally measured gamma distribution and the theoretically expected quadratic nonlinearity. 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. The sensitivity of intermittency to the nonlinear dynamics is investigated by analyzing the nonlinear Langevin representation of the beta process, which leads to a root-square nonlinearity.
QB1 - Stochastic Gene Regulation
Energy Technology Data Exchange (ETDEWEB)
Munsky, Brian [Los Alamos National Laboratory
2012-07-23
Summaries of this presentation are: (1) Stochastic fluctuations or 'noise' is present in the cell - Random motion and competition between reactants, Low copy, quantization of reactants, Upstream processes; (2) Fluctuations may be very important - Cell-to-cell variability, Cell fate decisions (switches), Signal amplification or damping, stochastic resonances; and (3) Some tools are available to mode these - Kinetic Monte Carlo simulations (SSA and variants), Moment approximation methods, Finite State Projection. We will see how modeling these reactions can tell us more about the underlying processes of gene regulation.
Russell, Matthew J.; Jensen, Oliver E.; Galla, Tobias
2016-10-01
Motivated by uncertainty quantification in natural transport systems, we investigate an individual-based transport process involving particles undergoing a random walk along a line of point sinks whose strengths are themselves independent random variables. We assume particles are removed from the system via first-order kinetics. We analyze the system using a hierarchy of approaches when the sinks are sparsely distributed, including a stochastic homogenization approximation that yields explicit predictions for the extrinsic disorder in the stationary state due to sink strength fluctuations. The extrinsic noise induces long-range spatial correlations in the particle concentration, unlike fluctuations due to the intrinsic noise alone. Additionally, the mean concentration profile, averaged over both intrinsic and extrinsic noise, is elevated compared with the corresponding profile from a uniform sink distribution, showing that the classical homogenization approximation can be a biased estimator of the true mean.
Benedetti-Cecchi, Lisandro; Canepa, Antonio; Fuentes, Veronica; Tamburello, Laura; Purcell, Jennifer E; Piraino, Stefano; Roberts, Jason; Boero, Ferdinando; Halpin, Patrick
2015-01-01
Jellyfish outbreaks are increasingly viewed as a deterministic response to escalating levels of environmental degradation and climate extremes. However, a comprehensive understanding of the influence of deterministic drivers and stochastic environmental variations favouring population renewal processes has remained elusive. This study quantifies the deterministic and stochastic components of environmental change that lead to outbreaks of the jellyfish Pelagia noctiluca in the Mediterranen Sea. Using data of jellyfish abundance collected at 241 sites along the Catalan coast from 2007 to 2010 we: (1) tested hypotheses about the influence of time-varying and spatial predictors of jellyfish outbreaks; (2) evaluated the relative importance of stochastic vs. deterministic forcing of outbreaks through the environmental bootstrap method; and (3) quantified return times of extreme events. Outbreaks were common in May and June and less likely in other summer months, which resulted in a negative relationship between outbreaks and SST. Cross- and along-shore advection by geostrophic flow were important concentrating forces of jellyfish, but most outbreaks occurred in the proximity of two canyons in the northern part of the study area. This result supported the recent hypothesis that canyons can funnel P. noctiluca blooms towards shore during upwelling. This can be a general, yet unappreciated mechanism leading to outbreaks of holoplanktonic jellyfish species. The environmental bootstrap indicated that stochastic environmental fluctuations have negligible effects on return times of outbreaks. Our analysis emphasized the importance of deterministic processes leading to jellyfish outbreaks compared to the stochastic component of environmental variation. A better understanding of how environmental drivers affect demographic and population processes in jellyfish species will increase the ability to anticipate jellyfish outbreaks in the future.
Charmet, Jérôme; Michaels, Thomas C. T.; Daly, Ronan; Prasad, Abhinav; Thiruvenkathanathan, Pradyumna; Langley, Robin S.; Knowles, Tuomas P. J.; Seshia, Ashwin A.
2016-06-01
Recent advances in micro- and nanotechnology have enabled the development of ultrasensitive sensors capable of detecting small numbers of species. In general, however, the response induced by the random adsorption of a small number of objects onto the surface of such sensors results in significant fluctuations due to the heterogeneous sensitivity inherent to many such sensors coupled to statistical fluctuations in the particle number. At present, this issue is addressed by considering either the limit of very large numbers of analytes, where fluctuations vanish, or the converse limit, where the sensor response is governed by individual analytes. Many cases of practical interest, however, fall between these two limits and remain challenging to analyze. Here, we address this limitation by deriving a general theoretical framework for quantifying measurement variations on mechanical resonators resulting from statistical-number fluctuations of analyte species. Our results provide insights into the stochastic processes in the sensing environment and offer opportunities to improve the performance of mechanical-resonator-based sensors. This metric can be used, among others, to aid in the design of robust sensor platforms to reach ultrahigh-resolution measurements using an array of sensors. These concepts, illustrated here in the context of biosensing, are general and can therefore be adapted and extended to other sensors with heterogeneous sensitivity.
Stochastic Equations in Black Hole Backgrounds and Non-equilibrium Fluctuation Theorems
Iso, Satoshi
2011-01-01
We apply the non-equilibrium fluctuation theorems developed in the statistical physics to the thermodynamics of black hole horizons. In particular, we consider a scalar field in a black hole background. The system of the scalar field behaves stochastically due to the absorption of energy into the black hole and emission of the Hawking radiation from the black hole horizon. We derive the stochastic equations, i.e. Langevin and Fokker-Planck equations for a scalar field in a black hole background in the $\\hbar \\rightarrow 0$ limit with the Hawking temperature $\\hbar \\kappa/2 \\pi$ fixed. We consider two cases, one confined in a box with a black hole at the center and the other in contact with a heat bath with temperature different from the Hawking temperature. In the first case, the system eventually becomes equilibrium with the Hawking temperature while in the second case there is an energy flow between the black hole and the heat bath. Applying the fluctuation theorems to these cases, we derive the generalized...
Stochastic switching in slow-fast systems: a large-fluctuation approach.
Heckman, Christoffer R; Schwartz, Ira B
2014-02-01
In this paper we develop a perturbation method to predict the rate of occurrence of rare events for singularly perturbed stochastic systems using a probability density function approach. In contrast to a stochastic normal form approach, we model rare event occurrences due to large fluctuations probabilistically and employ a WKB ansatz to approximate their rate of occurrence. This results in the generation of a two-point boundary value problem that models the interaction of the state variables and the most likely noise force required to induce a rare event. The resulting equations of motion of describing the phenomenon are shown to be singularly perturbed. Vastly different time scales among the variables are leveraged to reduce the dimension and predict the dynamics on the slow manifold in a deterministic setting. The resulting constrained equations of motion may be used to directly compute an exponent that determines the probability of rare events. To verify the theory, a stochastic damped Duffing oscillator with three equilibrium points (two sinks separated by a saddle) is analyzed. The predicted switching time between states is computed using the optimal path that resides in an expanded phase space. We show that the exponential scaling of the switching rate as a function of system parameters agrees well with numerical simulations. Moreover, the dynamics of the original system and the reduced system via center manifolds are shown to agree in an exponentially scaling sense.
Guo, Xinmeng; Wang, Jiang; Liu, Jing; Yu, Haitao; Galán, Roberto F.; Cao, Yibin; Deng, Bin
2017-02-01
Channel noise, which is generated by the random transitions of ion channels between open and closed states, is distinguished from external sources of physiological variability such as spontaneous synaptic release and stimulus fluctuations. This inherent stochasticity in ion-channel current can lead to variability of the timing of spikes occurring both spontaneously and in response to stimuli. In this paper, we investigate how intrinsic channel noise affects the response of stochastic Hodgkin-Huxley (HH) neuron to external fluctuating inputs with different amplitudes and correlation time. It is found that there is an optimal correlation time of input fluctuations for the maximal spiking coherence, where the input current has a fluctuating rate approximately matching the inherent oscillation of stochastic HH model and plays a dominating role in the timing of spike firing. We also show that the reliability of spike timing in the model is very sensitive to the properties of the current input. An optimal time scale of input fluctuations exists to induce the most reliable firing. The channel-noise-induced unreliability can be mostly overridden by injecting a fluctuating current with an appropriate correlation time. The spiking coherence and reliability can also be regulated by the size of channel stochasticity. As the membrane area (or total channel number) of the neuron increases, the spiking coherence decreases but the spiking reliability increases.
Davey, H M; Davey, C L; Woodward, A M; Edmonds, A N; Lee, A W; Kell, D B
1996-01-01
We describe a continuous culture system related to the turbidostat, but using a feedback system based on biomass estimation from the dielectric permittivity of the cell suspension rather than its optical density. It is shown that this system provides an excellent method of maintaining a constant biomass level within a fermentor. The computer-controlled system was able to effect the essentially continuous registration of growth rate by monitoring the rate of medium addition via the time-dependent activity of the pump. At some biomass setpoints for aerobically grown cultures of baker's yeast substantial time-dependent fluctuations in the growth rate of the culture were thereby observed. At some biomass setpoints, however, or under anaerobic conditions, or when using a non-Crabtree yeast, the growth rate was constant, indicating that the fluctuations were inherent to the biological system and not simply a property of the fermentor and control system. A variety of time series analyses (Fourier transformations, Hurst and Lyapunov exponents, the determination of embedding dimension, and non-linear time series predictions based on the methodology of Sugihara and May) were used to demonstrate, for the first time, that as well as stochastic and periodic components these fluctuations exhibited deterministic chaos. 'Trivial predictors' were unable to give accurate predictions of the growth rate in these cultures. The growth rate fluctuations were studied further by means of offline measurements of changes in percentage viability, bud count, and in the external ethanol and glucose concentrations; these data and other evidence suggested that the growth rate fluctuations were closely linked to the primary respiro-fermentative metabolism of this organism. The identification of chaotic growth rates in cell cultures suggests that there may be novel methods for controlling the growth of such cultures.
Bressloff, Paul C
2015-01-01
We consider applications of path-integral methods to the analysis of a stochastic hybrid model representing a network of synaptically coupled spiking neuronal populations. The state of each local population is described in terms of two stochastic variables, a continuous synaptic variable and a discrete activity variable. The synaptic variables evolve according to piecewise-deterministic dynamics describing, at the population level, synapses driven by spiking activity. The dynamical equations for the synaptic currents are only valid between jumps in spiking activity, and the latter are described by a jump Markov process whose transition rates depend on the synaptic variables. We assume a separation of time scales between fast spiking dynamics with time constant [Formula: see text] and slower synaptic dynamics with time constant τ. This naturally introduces a small positive parameter [Formula: see text], which can be used to develop various asymptotic expansions of the corresponding path-integral representation of the stochastic dynamics. First, we derive a variational principle for maximum-likelihood paths of escape from a metastable state (large deviations in the small noise limit [Formula: see text]). We then show how the path integral provides an efficient method for obtaining a diffusion approximation of the hybrid system for small ϵ. The resulting Langevin equation can be used to analyze the effects of fluctuations within the basin of attraction of a metastable state, that is, ignoring the effects of large deviations. We illustrate this by using the Langevin approximation to analyze the effects of intrinsic noise on pattern formation in a spatially structured hybrid network. In particular, we show how noise enlarges the parameter regime over which patterns occur, in an analogous fashion to PDEs. Finally, we carry out a [Formula: see text]-loop expansion of the path integral, and use this to derive corrections to voltage-based mean-field equations, analogous
A simple stochastic model for dipole moment fluctuations in numerical dynamo simulations
Directory of Open Access Journals (Sweden)
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.
A simple stochastic model for dipole moment fluctuations in numerical dynamo simulations
Meduri, Domenico G.; Wicht, Johannes
2016-04-01
Earth's axial dipole field changes in a complex fashion on many different time scales ranging from less than a year to tens of million years. Documenting, analysing, and replicating this intricate signal is a challenge for data acquisition, theoretical interpretation, and dynamo modelling alike. Here we explore whether axial dipole variations can be described by the superposition of a slow deterministic drift and 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 which allows useful predictions, including the average rates of dipole reversals and excursions. We analyse several numerical dynamo simulations, most of which have been integrated particularly long in time, and also the palaeomagnetic model PADM2M which covers the past 2 Myr. The results show that the Langevin description provides a viable statistical model of the axial dipole variations on time scales longer than about 1 kyr. For example, the axial dipole probability distribution and the average reversal rate are successfully predicted. The exception is PADM2M where the stochastic model reversal rate seems too low. The dependence of the drift on the axial dipole moment reveals the nonlinear interactions that establish the dynamo balance. A separate analysis of inductive and diffusive magnetic effects in three dynamo simulations suggests that the classical quadratic quenching of induction predicted by mean-field theory seems at work.
EFT beyond the horizon: stochastic inflation and how primordial quantum fluctuations go classical
Energy Technology Data Exchange (ETDEWEB)
Burgess, C.P. [Physics & Astronomy, McMaster University,Hamilton, ON, L8S 4M1 (Canada); Perimeter Institute for Theoretical Physics,Waterloo, ON, N2L 2Y5 (Canada); Division PH -TH, CERN,Genève 23, CH-1211 (Switzerland); Holman, R. [Physics Department, Carnegie Mellon University,Pittsburgh, PA, 15213 (United States); Tasinato, G. [ICG, University of Portsmouth,Portsmouth, PO1 3FX United Kingdom (United Kingdom); Department of Physics, Swansea University,Vivian Tower, Swansea, SA2 8PP United Kingdom (United Kingdom); Williams, M. [Physics & Astronomy, McMaster University,Hamilton, ON, L8S 4M1 (Canada); Perimeter Institute for Theoretical Physics,Waterloo, ON, N2L 2Y5 (Canada)
2015-03-18
We identify the effective field theory describing the physics of super-Hubble scales and show it to be a special case of a class of effective field theories appropriate to open systems. Open systems are those that allow information to be exchanged between the degrees of freedom of interest and those that are integrated out, such as would be appropriate 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 time-evolution of the density matrix of the slow degrees of freedom. We derive the equation relevant to super-Hubble modes of quantum fields in de Sitter (and near-de Sitter) spacetimes and derive two of its implications. We show that the evolution of the diagonal density-matrix elements quickly approach the Fokker-Planck equation of Starobinsky’s stochastic inflationary picture. This allows us both to identify the leading corrections and provide an alternative first-principles derivation of this picture’s stochastic noise and drift. (As applications we show that the noise for massless fields is independent of the details of the window function used, and also compute how the noise changes for systems with a sub-luminal speed of sound, c{sub s}<1.) We then argue that the presence of interactions drive the off-diagonal density-matrix elements to zero in the field basis. This shows why the field basis is generally the ‘pointer basis’ for the process that decoheres primordial quantum fluctuations while they are outside the horizon, thus allowing them to re-enter later as classical field fluctuations, as assumed when analyzing CMB data. The decoherence process is very efficient, occurring after several Hubble times even for interactions as weak as gravitational-strength. Crucially, the details of the interactions largely control only the decoherence time and not the nature of the final late-time stochastic
On the range of validity of the fluctuation theorem for stochastic Markovian dynamics
Rákos, A.; Harris, R. J.
2008-05-01
We consider the fluctuations of generalized currents in stochastic Markovian dynamics. The large deviations of current fluctuations are shown to obey a Gallavotti-Cohen (GC) type symmetry in systems with a finite state space. However, this symmetry is not guaranteed to hold in systems with an infinite state space. A simple example of such a case is the zero-range process (ZRP). Here we discuss in more detail the already reported (Harris et al 2006 Europhys. Lett. 75 227) breakdown of the GC symmetry in the context of the ZRP with open boundaries and we give a physical interpretation of the phases that appear. Furthermore, the earlier analytical results for the single-site case are extended to cover multiple-site systems. We also use our exact results to test an efficient numerical algorithm of Giardinà et al (2006 Phys. Rev. Lett. 96 120603), which was developed to measure the current large deviation function directly. We find that this method breaks down in some phases which we associate with the gapless spectrum of an effective Hamiltonian.
Zhao, Yu; Yuan, Sanling; Zhang, Tonghua
2017-03-01
Phytoplankton allelopathy is an ecological phenomenon that concerns the interaction among toxic-producing phytoplankton. Recently, researchers pay great attention to whether the cyclic outbreaks of the harmful algal blooms are related with the allelopathy in a random fluctuating environment. In this paper, we are particularly interested in a non-autonomous toxic-producing phytoplankton allelopathy model with environmental fluctuation. For the model, we first consider the existence of the global positive solution and the boundary periodic solution. Then, by using Khasminskii's method and Lyapunov function, we derive the sufficient conditions for the existence of the nontrivial positive stochastically periodic solution. Our results show that the allelopathic effect plays an important role in the existence of the stochastic periodic solution, for example it can lead to the decrease of the peaks of the cyclic outbreaks of the harmful algal blooms. Numerical simulations are carried out to support our theoretical results.
Hong, Dawei; Man, Shushuang; Martin, Joseph V
2016-01-21
There are two functionally important factors in signal propagation in a brain structural network: the very first synaptic delay-a time delay about 1ms-from the moment when signals originate to the moment when observation on the signal propagation can begin; and rapid random fluctuations in membrane potentials of every individual neuron in the network at a timescale of microseconds. We provide a stochastic analysis of signal propagation in a general setting. The analysis shows that the two factors together result in a stochastic mechanism for the signal propagation as described below. A brain structural network is not a rigid circuit rather a very flexible framework that guides signals to propagate but does not guarantee success of the signal propagation. In such a framework, with the very first synaptic delay, rapid random fluctuations in every individual neuron in the network cause an "alter-and-concentrate effect" that almost surely forces signals to successfully propagate. By the stochastic mechanism we provide analytic evidence for the existence of a force behind signal propagation in a brain structural network caused by rapid random fluctuations in every individual neuron in the network at a timescale of microseconds with a time delay of 1ms.
Rocha, Paulo; Boto, João P; Lind, Pedro G
2015-01-01
We present a framework for describing the evolution of stochastic observables having a non-stationary distribution of values. The framework is applied to empirical volume-prices from assets traded at the New York stock exchange. Using Kullback-Leibler divergence we evaluate the best model out from four biparametric models standardly used in the context of financial data analysis. In our present data sets we conclude that the inverse $\\Gamma$-distribution is a good model, particularly for the distribution tail of the largest volume-price fluctuations. Extracting the time-series of the corresponding parameter values we show that they evolve in time as stochastic variables themselves. For the particular case of the parameter controlling the volume-price distribution tail we are able to extract an Ornstein-Uhlenbeck equation which describes the fluctuations of the largest volume-prices observed in the data. Finally, we discuss how to bridge from the stochastic evolution of the distribution parameters to the stoch...
Kim, Won Kyu; 10.1063/1.4746118
2012-01-01
Within the cell, biopolymers are often situated in constrained, fluid environments, e.g., cytoskeletal networks, stretched DNAs in chromatin. It is of paramount importance to understand quantitatively how they, utilizing their flexibility, optimally respond to a minute signal, which is, in general, temporally fluctuating far away from equilibrium. To this end, we analytically study viscoelastic response and associated stochastic resonance in a stretched single semi-flexible chain to an oscillatory force or electric field. Including hydrodynamic interactions between chain segments, we evaluate dynamics of the polymer extension in coherent response to the force or field. We find power amplification factor of the response at a noise-strength (temperature) can attain the maximum that grows as the chain length increases, indicative of an entropic stochastic resonance (ESR). In particular for a charged chain under an electric field, we find that the maximum also occurs at an optimal chain length, a new feature of E...
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.
d'Onofrio, Alberto; Gandolfi, Alberto; Gattoni, Sara
2012-12-01
By studying a simple but realistic biophysical model of tumor growth in the presence of a constant continuous chemotherapy, we show that if an extended Norton-Simon hypothesis holds, the system may have multiple equilibria. Thus, the stochastic bounded fluctuations that affect both the tumor carrying capacity and/or the drug pharmacodynamics (and/or the drug pharmacokinetics) may cause the transition from a small equilibrium to a far larger one, not compatible with the life of the host. In particular, we mainly investigated the effects of fluctuations that involve parameters nonlinearly affecting the deterministic model. We propose to frame the above phenomena as a new and non-genetic kind of resistance to chemotherapy.
Hill's Equation with Small Fluctuations: Cycle to Cycle Variations and Stochastic Processes
Adams, Fred C
2013-01-01
Hill's equations arise in a wide variety of physical problems, and are specified by a natural frequency, a periodic forcing function, and a forcing strength parameter. This classic problem is generalized here in two ways: [A] to Random Hill's equations which allow the forcing strength q_k, the oscillation frequency \\lambda_k, and the period \\tau_k of the forcing function to vary from cycle to cycle, and [B] to Stochastic Hill's equations which contain (at least) one additional term that is a stochastic process \\xi. This paper considers both random and stochastic Hill's equations with small parameter variations, so that p_k=q_k-, \\ell_k=\\lambda_k-, and \\xi are all O(\\epsilon), where \\epsilon<<1. We show that random Hill's equations and stochastic Hill's equations have the same growth rates when the parameter variations p_k and \\ell_k obey certain constraints given in terms of the moments of \\xi. For random Hill's equations, the growth rates for the solutions are given by the growth rates of a matrix tran...
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 ...
A Bayesian Approach Accounting for Stochastic Fluctuations in Stellar Cluster Properties
Fouesneau, M
2009-01-01
The integrated spectro-photometric properties of star clusters are subject to large cluster-to-cluster variations. They are distributed in non trivial ways around the average properties predicted by standard population synthesis models. This results from the stochastic mass distribution of the finite (small) number of luminous stars in each cluster, stars which may be either particularly blue or particularly red. The color distributions are broad and usually far from Gaussian, especially for young and intermediate age clusters, as found in interacting galaxies. When photometric measurements of clusters are used to estimate ages and masses in conjunction with standard models, biases are to be expected. We present a Bayesian approach that explicitly accounts for stochasticity when estimating ages and masses of star clusters that cannot be resolved into stars. Based on Monte-Carlo simulations, we are starting to explore the probability distributions of star cluster properties obtained given a set of multi-wavele...
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.
Stochastic Dynamics of Electrical Membrane with Voltage-Dependent Ion Channel Fluctuations
Qian, Hong; Qian, Min
2014-01-01
Brownian ratchet like stochastic theory for the electrochemical membrane system of Hodgkin-Huxley (HH) is developed. The system is characterized by a continuous variable $Q_m(t)$, representing mobile membrane charge density, and a discrete variable $K_t$ representing ion channel conformational dynamics. A Nernst-Planck-Nyquist-Johnson type equilibrium is obtained when multiple conducting ions have a common reversal potential. Detailed balance yields a previously unknown relation between the channel switching rates and membrane capacitance, bypassing Eyring-type explicit treatment of gating charge kinetics. From a molecular structural standpoint, membrane charge $Q_m$ is a more natural dynamic variable than potential $V_m$; our formalism treats $Q_m$-dependent conformational transition rates $\\lambda_{ij}$ as intrinsic parameters. Therefore in principle, $\\lambda_{ij}$ vs. $V_m$ is experimental protocol dependent,e.g., different from voltage or charge clamping measurements. For constant membrane capacitance pe...
Modeling water table fluctuations by means of a stochastic differential equation
Bierkens, Marc F. P.
1998-10-01
The combined system of soil-water and shallow groundwater is modeled with simple mass balance equations assuming equilibrium soil moisture conditions. This results in an ordinary but nonlinear differential equation of water table depth at a single location. If errors in model inputs, errors due to model assumptions and parameter uncertainty are lumped and modeled as a wide band noise process, a stochastic differential equation (SDE) results. A solution for the stationary probability density function is given through use of the Fokker-Planck equation. For the nonstationary case, where the model inputs are given as daily time series, sample functions of water table depth, soil saturation, and drainage discharge can be simulated by numerically solving the SDE. These sample functions can be used for designing drainage systems and to perform risk analyses. The parameters and noise statistics of the SDE are calibrated on time series of water table depths by embedding the SDE in a Kaiman filter algorithm and using the filter innovations in a filter-type maximum likelihood criterion. The stochastic model is calibrated and validated at two locations: a peat soil with a very shallow water table and a loamy sand soil with a moderately shallow water table. It is shown in both cases that sample functions simulated with the SDE are able to reproduce a wide range of statistics of water table depth. Despite its unrealistic assumption of constant inputs, the stationary solution derived from the Fokker-Planck equation gives good results for the peat soil, most likely because the characteristic response time of the water table is very small.
Proton and heavy ion acceleration by stochastic fluctuations in the Earth's magnetotail
Energy Technology Data Exchange (ETDEWEB)
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 +}.
Stochastic fluctuations and distributed control of gene expression impact cellular memory.
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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.
Conformally-related Einstein-Langevin equations for metric fluctuations in stochastic gravity
Satin, Seema; Hu, Bei Lok
2016-01-01
For a conformally-coupled scalar field we obtain the conformally-related Einstein-Langevin equations, using appropriate transformations for all the quantities in the equations between two conformally-related spacetimes. In particular, we analyze the transformations of the influence action, the stress energy tensor, the noise kernel and the dissipation kernel. In due course the fluctuation-dissipation relation is also discussed. The analysis in this paper thereby facilitates a general solution to the Einstein-Langevin equation once the solution of the equation in a simpler, conformally-related spacetime is known. For example, from the Minkowski solution of Martin and Verdaguer, those of the Einstein-Langevin equations in conformally-flat spacetimes, especially for spatially-flat Friedmann-Robertson-Walker models, can be readily obtained.
Conformally related Einstein-Langevin equations for metric fluctuations in stochastic gravity
Satin, Seema; Cho, H. T.; Hu, Bei Lok
2016-09-01
For a conformally coupled scalar field we obtain the conformally related Einstein-Langevin equations, using appropriate transformations for all the quantities in the equations between two conformally related spacetimes. In particular, we analyze the transformations of the influence action, the stress energy tensor, the noise kernel and the dissipation kernel. In due course the fluctuation-dissipation relation is also discussed. The analysis in this paper thereby facilitates a general solution to the Einstein-Langevin equation once the solution of the equation in a simpler, conformally related spacetime is known. For example, from the Minkowski solution of Martín and Verdaguer, those of the Einstein-Langevin equations in conformally flat spacetimes, especially for spatially flat Friedmann-Robertson-Walker models, can be readily obtained.
Fluctuation complexity of agent-based financial time series model by stochastic Potts system
Hong, Weijia; Wang, Jun
2015-03-01
Financial market is a complex evolved dynamic system with high volatilities and noises, and the modeling and analyzing of financial time series are regarded as the rather challenging tasks in financial research. In this work, by applying the Potts dynamic system, a random agent-based financial time series model is developed in an attempt to uncover the empirical laws in finance, where the Potts model is introduced to imitate the trading interactions among the investing agents. Based on the computer simulation in conjunction with the statistical analysis and the nonlinear analysis, we present numerical research to investigate the fluctuation behaviors of the proposed time series model. Furthermore, in order to get a robust conclusion, we consider the daily returns of Shanghai Composite Index and Shenzhen Component Index, and the comparison analysis of return behaviors between the simulation data and the actual data is exhibited.
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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
Directory of Open Access Journals (Sweden)
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
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Suzanne Gaudet
Full Text Available Stochastic fluctuations in gene expression give rise to cell-to-cell variability in protein levels which can potentially cause variability in cellular phenotype. For TRAIL (TNF-related apoptosis-inducing ligand variability manifests itself as dramatic differences in the time between ligand exposure and the sudden activation of the effector caspases that kill cells. However, the contribution of individual proteins to phenotypic variability has not been explored in detail. In this paper we use feature-based sensitivity analysis as a means to estimate the impact of variation in key apoptosis regulators on variability in the dynamics of cell death. We use Monte Carlo sampling from measured protein concentration distributions in combination with a previously validated ordinary differential equation model of apoptosis to simulate the dynamics of receptor-mediated apoptosis. We find that variation in the concentrations of some proteins matters much more than variation in others and that precisely which proteins matter depends both on the concentrations of other proteins and on whether correlations in protein levels are taken into account. A prediction from simulation that we confirm experimentally is that variability in fate is sensitive to even small increases in the levels of Bcl-2. We also show that sensitivity to Bcl-2 levels is itself sensitive to the levels of interacting proteins. The contextual dependency is implicit in the mathematical formulation of sensitivity, but our data show that it is also important for biologically relevant parameter values. Our work provides a conceptual and practical means to study and understand the impact of cell-to-cell variability in protein expression levels on cell fate using deterministic models and sampling from parameter distributions.
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Seth H. Weinberg
2012-01-01
Full Text Available 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.
Asymptotic behaviors of a cell-to-cell HIV-1 infection model perturbed by white noise
Liu, Qun
2017-02-01
In this paper, we analyze a mathematical model of cell-to-cell HIV-1 infection to CD4+ T cells perturbed by stochastic perturbations. First of all, we investigate that there exists a unique global positive solution of the system for any positive initial value. Then by using Lyapunov analysis methods, we study the asymptotic property of this solution. Moreover, we discuss whether there is a stationary distribution for this system and if it owns the ergodic property. Numerical simulations are presented to illustrate the theoretical results.
Peng, Di; Chen, Yujia; Wang, Shaofei; Liu, Yingzheng; Wang, Weizhe
2016-11-01
Previous studies have shown that it is possible to reconstruct the full flow field based on time-resolved measurements at discrete locations using linear stochastic estimation (LSE). The objective of this study is to develop and apply this technique to wall pressure fluctuation measurements in low speed flows. Time-resolved wall pressure fluctuations on a flat plate in the wake of a step cylinder at low speed (V PSP). The microphone arrays are arranged properly to capture the dominant features in the flow field at 10 kHz. The PSP is excited using a continuous UV-LED, and the luminescent signal is recorded by a high-speed camera at 2 kHz. The microphone data at discrete locations are used to reconstruct the full-field wall pressure fluctuations based on LSE. The PSP results serve as basis for improvement of the LSE scheme and also for validation of the reconstructed pressure field. Other data processing techniques including proper orthogonal decomposition (POD) and dynamic mode decomposition (DMD) are also used for analyzing the unsteady flow features. This LSE technique has great potential in real-time flow diagnostics and control.
Determinants of cell-to-cell variability in protein kinase signaling.
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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
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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.
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Yijin Zhang
2013-01-01
Full Text Available This work is concerned with the random dynamics of two-dimensional stochastic Boussinesq system with dynamical boundary condition. The white noises affect the system through a dynamical boundary condition. Using a method based on the theory of omega-limit compactness of a random dynamical system, we prove that the L2-random attractor for the generated random dynamical system is exactly the H1-random attractor. This improves a recent conclusion derived by Brune et al. on the existence of the L2-random attractor for the same system.
DEFF Research Database (Denmark)
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 fe...... for differentmolecular weight, the transient and steady-state behavior of the extinction angle, and the stress relaxation in cessation of steady shear flow....
Matsakos, T; Stehlé, C; González, M; Ibgui, L; de Sá, L; Lanz, T; Orlando, S; Bonito, R; Argiroffi, C; Reale, F; Peres, G
2013-01-01
Context. Theoretical arguments and numerical simulations of radiative shocks produced by the impact of the accreting gas onto young stars predict quasi-periodic oscillations in the emitted radiation. However, observational data do not show evidence of such periodicity. Aims. We investigate whether physically plausible perturbations in the accretion column or in the chromosphere could disrupt the shock structure influencing the observability of the oscillatory behavior. Methods. We performed local 2D magneto-hydrodynamical simulations of an accretion shock impacting a chromosphere, taking optically thin radiation losses and thermal conduction into account. We investigated the effects of several perturbation types, such as clumps in the accretion stream or chromospheric fluctuations, and also explored a wide range of plasma-\\beta values. Results. In the case of a weak magnetic field, the post-shock region shows chaotic motion and mixing, smoothing out the perturbations and retaining a global periodic signature....
Effect of promoter architecture on the cell-to-cell variability in gene expression.
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Alvaro Sanchez
2011-03-01
Full Text Available According to recent experimental evidence, promoter architecture, defined by the number, strength and regulatory role of the operators that control transcription, plays a major role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effort that addresses the question of how changes in promoter architecture affect variability in gene expression in a systematic rather than case-by-case fashion. In this article we make such a systematic investigation, based on a microscopic model of gene regulation that incorporates stochastic effects. In particular, we show how operator strength and operator multiplicity affect this variability. We examine different modes of transcription factor binding to complex promoters (cooperative, independent, simultaneous and how each of these affects the level of variability in transcriptional output from cell-to-cell. We propose that direct comparison between in vivo single-cell experiments and theoretical predictions for the moments of the probability distribution of mRNA number per cell can be used to test kinetic models of gene regulation. The emphasis of the discussion is on prokaryotic gene regulation, but our analysis can be extended to eukaryotic cells as well.
Regulation of cell-to-cell variability in divergent gene expression
Yan, Chao; Wu, Shuyang; Pocetti, Christopher; Bai, Lu
2016-03-01
Cell-to-cell variability (noise) is an important feature of gene expression that impacts cell fitness and development. The regulatory mechanism of this variability is not fully understood. Here we investigate the effect on gene expression noise in divergent gene pairs (DGPs). We generated reporters driven by divergent promoters, rearranged their gene order, and probed their expressions using time-lapse fluorescence microscopy and single-molecule fluorescence in situ hybridization (smFISH). We show that two genes in a co-regulated DGP have higher expression covariance compared with the separate, tandem and convergent configurations, and this higher covariance is caused by more synchronized firing of the divergent transcriptions. For differentially regulated DGPs, the regulatory signal of one gene can stochastically `leak' to the other, causing increased gene expression noise. We propose that the DGPs' function in limiting or promoting gene expression noise may enhance or compromise cell fitness, providing an explanation for the conservation pattern of DGPs.
Tetherin restricts productive HIV-1 cell-to-cell transmission.
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Nicoletta Casartelli
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.
Molecular Mechanisms of HTLV-1 Cell-to-Cell Transmission
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Christine Gross
2016-03-01
Full Text Available The tumorvirus human T-cell lymphotropic virus type 1 (HTLV-1, a member of the delta-retrovirus family, is transmitted via cell-containing body fluids such as blood products, semen, and breast milk. In vivo, HTLV-1 preferentially infects CD4+ T-cells, and to a lesser extent, CD8+ T-cells, dendritic cells, and monocytes. Efficient infection of CD4+ T-cells requires cell-cell contacts while cell-free virus transmission is inefficient. Two types of cell-cell contacts have been described to be critical for HTLV-1 transmission, tight junctions and cellular conduits. Further, two non-exclusive mechanisms of virus transmission at cell-cell contacts have been proposed: (1 polarized budding of HTLV-1 into synaptic clefts; and (2 cell surface transfer of viral biofilms at virological synapses. In contrast to CD4+ T-cells, dendritic cells can be infected cell-free and, to a greater extent, via viral biofilms in vitro. Cell-to-cell transmission of HTLV-1 requires a coordinated action of steps in the virus infectious cycle with events in the cell-cell adhesion process; therefore, virus propagation from cell-to-cell depends on specific interactions between cellular and viral proteins. Here, we review the molecular mechanisms of HTLV-1 transmission with a focus on the HTLV-1-encoded proteins Tax and p8, their impact on host cell factors mediating cell-cell contacts, cytoskeletal remodeling, and thus, virus propagation.
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
Cell to substratum and cell to cell interactions of microalgae.
Ozkan, Altan; Berberoglu, Halil
2013-12-01
This paper reports the cell to substratum and cell to cell interactions of a diverse group of microalgae based on the Extended Derjaguin, Landau, Verwey, Overbeek (XDLVO) approach using the previously reported physico-chemical surface properties. The microalgae included 10 different species of green algae and diatoms from both freshwater and saltwater environments while the substrata included glass, indium-tin oxide (ITO), stainless steel, polycarbonate, polyethylene, and polystryrene. The results indicated that acid-base interactions were the dominating mechanism of interaction for microalgae. For green algae, if at least one of the interacting surfaces was hydrophobic, adhesion at primary minimum was predicted without any energy barrier. However, most diatom systems featured energy barriers for adhesion due to repulsive van der Waals interactions. The results reported in this study are expected to provide useful data and insight into the interaction mechanisms of microalgae cells with each other and with substrata for a number of practical applications including prevention of biofouling of photobioreactors and other man-made surfaces, promotion of biofilm formation in algal biofilm photobioreactors, and developing bioflocculation strategies for energy efficient harvesting of algal biomass. Particularly, Botryococcus braunii and Cerithiopsis fusiformis were identified as promising species for biofloccuation and biofilm formation in freshwater and saltwater aquatic systems, respectively. Finally, based on the observed trends in this study, use of hydrophilic algae and hydrophilic coatings over surfaces are recommended for minimizing biofouling in aquatic systems.
Effects of cell-cycle-dependent expression on random fluctuations in protein levels.
Soltani, Mohammad; Singh, Abhyudai
2016-12-01
Expression of many genes varies as a cell transitions through different cell-cycle stages. How coupling between stochastic expression and cell cycle impacts cell-to-cell variability (noise) in the level of protein is not well understood. We analyse a model where a stable protein is synthesized in random bursts, and the frequency with which bursts occur varies within the cell cycle. Formulae quantifying the extent of fluctuations in the protein copy number are derived and decomposed into components arising from the cell cycle and stochastic processes. The latter stochastic component represents contributions from bursty expression and errors incurred during partitioning of molecules between daughter cells. These formulae reveal an interesting trade-off: cell-cycle dependencies that amplify the noise contribution from bursty expression also attenuate the contribution from partitioning errors. We investigate the existence of optimum strategies for coupling expression to the cell cycle that minimize the stochastic component. Intriguingly, results show that a zero production rate throughout the cell cycle, with expression only occurring just before cell division, minimizes noise from bursty expression for a fixed mean protein level. By contrast, the optimal strategy in the case of partitioning errors is to make the protein just after cell division. We provide examples of regulatory proteins that are expressed only towards the end of the cell cycle, and argue that such strategies enhance robustness of cell-cycle decisions to the intrinsic stochasticity of gene expression.
Effect of Interaction between Chromatin Loops on Cell-to-Cell Variability in Gene Expression.
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Tuoqi Liu
2016-05-01
Full Text Available According to recent experimental evidence, the interaction between chromatin loops, which can be characterized by three factors-connection pattern, distance between regulatory elements, and communication form, play an important role in determining the level of cell-to-cell variability in gene expression. These quantitative experiments call for a corresponding modeling effect that addresses the question of how changes in these factors affect variability at the expression level in a systematic rather than case-by-case fashion. Here we make such an effort, based on a mechanic model that maps three fundamental patterns for two interacting DNA loops into a 4-state model of stochastic transcription. We first show that in contrast to side-by-side loops, nested loops enhance mRNA expression and reduce expression noise whereas alternating loops have just opposite effects. Then, we compare effects of facilitated tracking and direct looping on gene expression. We find that the former performs better than the latter in controlling mean expression and in tuning expression noise, but this control or tuning is distance-dependent, remarkable for moderate loop lengths, and there is a limit loop length such that the difference in effect between two communication forms almost disappears. Our analysis and results justify the facilitated chromatin-looping hypothesis.
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
Listening to the noise: random fluctuations reveal gene network parameters
Energy Technology Data Exchange (ETDEWEB)
Munsky, Brian [Los Alamos National Laboratory; Khammash, Mustafa [UCSB
2009-01-01
The cellular environment is abuzz with noise. The origin of this noise is attributed to the inherent random motion of reacting molecules that take part in gene expression and post expression interactions. In this noisy environment, clonal populations of cells exhibit cell-to-cell variability that frequently manifests as significant phenotypic differences within the cellular population. The stochastic fluctuations in cellular constituents induced by noise can be measured and their statistics quantified. 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. This establishes a potentially powerful approach for the identification of gene networks and offers a new window into the workings of these networks.
Hu, B L; Roura, Albert
2006-01-01
We give a progress report of our research on spacetime fluctuations induced by quantum fields in an evaporating black hole and a black hole in quasi-equilibrium with its Hawking radiation. We note the main issues involved in these two classes of problems and outline the key steps for a systematic quantitative investigation. This report contains unpublished new ideas for further studies.
Kazeroonian, Atefeh; Fröhlich, Fabian; Raue, Andreas; Theis, Fabian J; Hasenauer, Jan
2016-01-01
Gene expression, signal transduction and many other cellular processes are subject to stochastic fluctuations. The analysis of these stochastic chemical kinetics is important for understanding cell-to-cell variability and its functional implications, but it is also challenging. A multitude of exact and approximate descriptions of stochastic chemical kinetics have been developed, however, tools to automatically generate the descriptions and compare their accuracy and computational efficiency are missing. In this manuscript we introduced CERENA, a toolbox for the analysis of stochastic chemical kinetics using Approximations of the Chemical Master Equation solution statistics. CERENA implements stochastic simulation algorithms and the finite state projection for microscopic descriptions of processes, the system size expansion and moment equations for meso- and macroscopic descriptions, as well as the novel conditional moment equations for a hybrid description. This unique collection of descriptions in a single toolbox facilitates the selection of appropriate modeling approaches. Unlike other software packages, the implementation of CERENA is completely general and allows, e.g., for time-dependent propensities and non-mass action kinetics. By providing SBML import, symbolic model generation and simulation using MEX-files, CERENA is user-friendly and computationally efficient. The availability of forward and adjoint sensitivity analyses allows for further studies such as parameter estimation and uncertainty analysis. The MATLAB code implementing CERENA is freely available from http://cerenadevelopers.github.io/CERENA/.
A recurrent stochastic binary network
Institute of Scientific and Technical Information of China (English)
赵杰煜
2001-01-01
Stochastic neural networks are usually built by introducing random fluctuations into the network. A natural method is to use stochastic connections rather than stochastic activation functions. We propose a new model in which each neuron has very simple functionality but all the connections are stochastic. It is shown that the stationary distribution of the network uniquely exists and it is approximately a Boltzmann-Gibbs distribution. The relationship between the model and the Markov random field is discussed. New techniques to implement simulated annealing and Boltzmann learning are proposed. Simulation results on the graph bisection problem and image recognition show that the network is powerful enough to solve real world problems.
Stochastic volatility and stochastic leverage
DEFF Research Database (Denmark)
Veraart, Almut; Veraart, Luitgard A. M.
This paper proposes the new concept of stochastic leverage in stochastic volatility models. Stochastic leverage refers to a stochastic process which replaces the classical constant correlation parameter between the asset return and the stochastic volatility process. We provide a systematic...... treatment of stochastic leverage and propose to model the stochastic leverage effect explicitly, e.g. by means of a linear transformation of a Jacobi process. Such models are both analytically tractable and allow for a direct economic interpretation. In particular, we propose two new stochastic volatility...... models which allow for a stochastic leverage effect: the generalised Heston model and the generalised Barndorff-Nielsen & Shephard model. We investigate the impact of a stochastic leverage effect in the risk neutral world by focusing on implied volatilities generated by option prices derived from our new...
Oseltamivir expands quasispecies of influenza virus through cell-to-cell transmission.
Mori, Kotaro; Murano, Kensaku; Ohniwa, Ryosuke L; Kawaguchi, Atsushi; Nagata, Kyosuke
2015-03-16
The population of influenza virus consists of a huge variety of variants, called quasispecies, due to error-prone replication. Previously, we reported that progeny virions of influenza virus become infected to adjacent cells via cell-to-cell transmission pathway in the presence of oseltamivir. During cell-to-cell transmission, viruses become infected to adjacent cells at high multiplicity since progeny virions are enriched on plasma membrane between infected cells and their adjacent cells. Co-infection with viral variants may rescue recessive mutations with each other. Thus, it is assumed that the cell-to-cell transmission causes expansion of virus quasispecies. Here, we have demonstrated that temperature-sensitive mutations remain in progeny viruses even at non-permissive temperature by co-infection in the presence of oseltamivir. This is possibly due to a multiplex infection through the cell-to-cell transmission by the addition of oseltamivir. Further, by the addition of oseltamivir, the number of missense mutation introduced by error-prone replication in segment 8 encoding NS1 was increased in a passage-dependent manner. The number of missense mutation in segment 5 encoding NP was not changed significantly, whereas silent mutation was increased. Taken together, we propose that oseltamivir expands influenza virus quasispecies via cell-to-cell transmission, and may facilitate the viral evolution and adaptation.
Consistency of detrended fluctuation analysis
Løvsletten, Ola
2016-01-01
The scaling function $F(s)$ in detrended fluctuation analysis (DFA) scales as $F(s)\\sim s^{H}$ for stochastic processes with Hurst exponents $H$. We prove this scaling law for both stationary stochastic processes with $01$. As a final application of the new theory, we present an estimator $\\hat F(s)$ that can handle missing data in regularly sampled time series without the need for interpolation schemes. Under mild regularity conditions, $\\hat F(s)$ is equal in expectation to the fluctuation function $F(s)$ in the gap-free case.
The evolution of cell-to-cell communication in a sporulating bacterium.
van Gestel, Jordi; Nowak, Martin A; Tarnita, Corina E
2012-01-01
Traditionally microorganisms were considered to be autonomous organisms that could be studied in isolation. However, over the last decades cell-to-cell communication has been found to be ubiquitous. By secreting molecular signals in the extracellular environment microorganisms can indirectly assess the cell density and respond in accordance. In one of the best-studied microorganisms, Bacillus subtilis, the differentiation processes into a number of distinct cell types have been shown to depend on cell-to-cell communication. One of these cell types is the spore. Spores are metabolically inactive cells that are highly resistant against environmental stress. The onset of sporulation is dependent on cell-to-cell communication, as well as on a number of other environmental cues. By using individual-based simulations we examine when cell-to-cell communication that is involved in the onset of sporulation can evolve. We show that it evolves when three basic premises are satisfied. First, the population of cells has to affect the nutrient conditions. Second, there should be a time-lag between the moment that a cell decides to sporulate and the moment that it turns into a mature spore. Third, there has to be environmental variation. Cell-to-cell communication is a strategy to cope with environmental variation, by allowing cells to predict future environmental conditions. As a consequence, cells can anticipate environmental stress by initiating sporulation. Furthermore, signal production could be considered a cooperative trait and therefore evolves when it is not too costly to produce signal and when there are recurrent colony bottlenecks, which facilitate assortment. Finally, we also show that cell-to-cell communication can drive ecological diversification. Different ecotypes can evolve and be maintained due to frequency-dependent selection.
The evolution of cell-to-cell communication in a sporulating bacterium.
Directory of Open Access Journals (Sweden)
Jordi van Gestel
Full Text Available Traditionally microorganisms were considered to be autonomous organisms that could be studied in isolation. However, over the last decades cell-to-cell communication has been found to be ubiquitous. By secreting molecular signals in the extracellular environment microorganisms can indirectly assess the cell density and respond in accordance. In one of the best-studied microorganisms, Bacillus subtilis, the differentiation processes into a number of distinct cell types have been shown to depend on cell-to-cell communication. One of these cell types is the spore. Spores are metabolically inactive cells that are highly resistant against environmental stress. The onset of sporulation is dependent on cell-to-cell communication, as well as on a number of other environmental cues. By using individual-based simulations we examine when cell-to-cell communication that is involved in the onset of sporulation can evolve. We show that it evolves when three basic premises are satisfied. First, the population of cells has to affect the nutrient conditions. Second, there should be a time-lag between the moment that a cell decides to sporulate and the moment that it turns into a mature spore. Third, there has to be environmental variation. Cell-to-cell communication is a strategy to cope with environmental variation, by allowing cells to predict future environmental conditions. As a consequence, cells can anticipate environmental stress by initiating sporulation. Furthermore, signal production could be considered a cooperative trait and therefore evolves when it is not too costly to produce signal and when there are recurrent colony bottlenecks, which facilitate assortment. Finally, we also show that cell-to-cell communication can drive ecological diversification. Different ecotypes can evolve and be maintained due to frequency-dependent selection.
Holmes-Cerfon, Miranda
2016-11-01
We study a model of rolling particles subject to stochastic fluctuations, which may be relevant in systems of nano- or microscale particles where rolling is an approximation for strong static friction. We consider the simplest possible nontrivial system: a linear polymer of three disks constrained to remain in contact and immersed in an equilibrium heat bath so the internal angle of the polymer changes due to stochastic fluctuations. We compare two cases: one where the disks can slide relative to each other and the other where they are constrained to roll, like gears. Starting from the Langevin equations with arbitrary linear velocity constraints, we use formal homogenization theory to derive the overdamped equations that describe the process in configuration space only. The resulting dynamics have the formal structure of a Brownian motion on a Riemannian or sub-Riemannian manifold, depending on if the velocity constraints are holonomic or nonholonomic. We use this to compute the trimer's equilibrium distribution with and without the rolling constraints. Surprisingly, the two distributions are different. We suggest two possible interpretations of this result: either (i) dry friction (or other dissipative, nonequilibrium forces) changes basic thermodynamic quantities like the free energy of a system, a statement that could be tested experimentally, or (ii) as a lesson in modeling rolling or friction more generally as a velocity constraint when stochastic fluctuations are present. In the latter case, we speculate there could be a "roughness" entropy whose inclusion as an effective force could compensate the constraint and preserve classical Boltzmann statistics. Regardless of the interpretation, our calculation shows the word "rolling" must be used with care when stochastic fluctuations are present.
The Evolution of Cell-to-Cell Communication in a Sporulating Bacterium
van Gestel, Jordi; Nowak, Martin A.; Tarnita, Corina E.
2012-01-01
Traditionally microorganisms were considered to be autonomous organisms that could be studied in isolation. However, over the last decades cell-to-cell communication has been found to be ubiquitous. By secreting molecular signals in the extracellular environment microorganisms can indirectly assess
The Arabidopsis synaptotagmin SYTA regulates the cell-to-cell movement of diverse plant viruses
Directory of Open Access Journals (Sweden)
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.
Stochastic Shadowing and Stochastic Stability
Todorov, Dmitry
2014-01-01
The notion of stochastic shadowing property is introduced. Relations to stochastic stability and standard shadowing are studied. Using tent map as an example it is proved that, in contrast to what happens for standard shadowing, there are significantly non-uniformly hyperbolic systems that satisfy stochastic shadowing property.
Stochastic gravity: beyond semiclassical gravity
Energy Technology Data Exchange (ETDEWEB)
Verdaguer, E [Departament de Fisica Fonamental and CER en Astrofisica, Fisica de Particules i Cosmologia, Universitat de Barcelona, Av. Diagonal 647, 08028 Barcelona (Spain)
2007-05-15
The back-reaction of a classical gravitational field interacting with quantum matter fields is described by the semiclassical Einstein equation, which has the expectation value of the quantum matter fields stress tensor as a source. The semiclassical theory may be obtained from the quantum field theory of gravity interacting with N matter fields in the large N limit. This theory breaks down when the fields quantum fluctuations are important. Stochastic gravity goes beyond the semiclassical limit and allows for a systematic and self-consistent description of the metric fluctuations induced by these quantum fluctuations. The correlation functions of the metric fluctuations obtained in stochastic gravity reproduce the correlation functions in the quantum theory to leading order in an 1/N expansion. Two main applications of stochastic gravity are discussed. The first, in cosmology, to obtain the spectrum of primordial metric perturbations induced by the inflaton fluctuations, even beyond the linear approximation. The second, in black hole physics, to study the fluctuations of the horizon of an evaporating black hole.
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.
Directory of Open Access Journals (Sweden)
Casadevall Arturo
2007-08-01
Full Text Available Abstract Background The interaction between macrophages and Cryptococcus neoformans (Cn is critical for containing dissemination of this pathogenic yeast. However, Cn can either lyse macrophages or escape from within them through a process known as phagosomal extrusion. Both events result in live extracellular yeasts capable of reproducing and disseminating in the extracellular milieu. Another method of exiting the intracellular confines of cells is through host cell-to-cell transfer of the pathogen, and this commonly occurs with the human immuno-deficiency virus (HIV and CD4+ T cells and macrophages. In this report we have used time-lapse imaging to determine if this occurs with Cn. Results Live imaging of Cryptococcus neoformans interactions with murine macrophages revealed cell-to-cell spread of yeast cells from infected donor cells to uninfected cells. Although this phenomenon was relatively rare its occurrence documents a new capacity for this pathogen to infect adjacent cells without exiting the intracellular space. Cell-to-cell spread appeared to be an actin-dependent process. In addition, we noted that cryptococcal phagosomal extrusion was followed by the formation of massive vacuoles suggesting that intracellular residence is accompanied by long lasting damage to host cells. Conclusion C. neoformans can escape the intracellular confines of macrophages in an actin dependent manner by cell-to-cell transfer of the yeast leading to infection of adjacent cells. In addition, complete extrusion of internalized Cn cells can lead to the formation of a massive vacuole which may be a sign of damage to the host macrophage. These observations document new outcomes for the interaction of C. neoformans with host cells that provide precedents for cell biological effects that may contribute to the pathogenesis of cryptococcal infections.
Casadevall Arturo; Alvarez Mauricio
2007-01-01
Abstract Background The interaction between macrophages and Cryptococcus neoformans (Cn) is critical for containing dissemination of this pathogenic yeast. However, Cn can either lyse macrophages or escape from within them through a process known as phagosomal extrusion. Both events result in live extracellular yeasts capable of reproducing and disseminating in the extracellular milieu. Another method of exiting the intracellular confines of cells is through host cell-to-cell transfer of the ...
Bible, Amber N.; Khalsa-Moyers, Gurusahai K.; Mukherjee, Tanmoy; Green, Calvin S.; Mishra, Priyanka; Purcell, Alicia; Aksenova, Anastasia; Hurst, Gregory B.
2015-01-01
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. PMID:26407887
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.
Human Cytomegalovirus US28 Facilitates Cell-to-Cell Viral Dissemination
Directory of Open Access Journals (Sweden)
Vanessa M. Noriega
2014-03-01
Full Text Available Human cytomegalovirus (HCMV encodes a number of viral proteins with homology to cellular G protein-coupled receptors (GPCRs. These viral GPCRs, including US27, US28, UL33, and UL78, have been ascribed numerous functions during infection, including activating diverse cellular pathways, binding to immunomodulatory chemokines, and impacting virus dissemination. To investigate the role of US28 during virus infection, two variants of the clinical isolate TB40/E were generated: TB40/E-US28YFP expressing a C-terminal yellow fluorescent protein tag, and TB40/E-FLAGYFP in which a FLAG-YFP cassette replaces the US28 coding region. The TB40/E-US28YFP protein localized as large perinuclear fluorescent structures at late times post-infection in fibroblasts, endothelial, and epithelial cells. Interestingly, US28YFP is a non-glycosylated membrane protein throughout the course of infection. US28 appears to impact cell-to-cell spread of virus, as the DUS28 virus (TB40/E-FLAGYFP generated a log-greater yield of extracellular progeny whose spread could be significantly neutralized in fibroblasts. Most strikingly, in epithelial cells, where dissemination of virus occurs exclusively by the cell-to-cell route, TB40/E-FLAGYFP (DUS28 displayed a significant growth defect. The data demonstrates that HCMV US28 may contribute at a late stage of the viral life cycle to cell-to-cell dissemination of virus.
Stochastic nonlinear differential equations. I
Heilmann, O.J.; Kampen, N.G. van
1974-01-01
A solution method is developed for nonlinear differential equations having the following two properties. Their coefficients are stochastic through their dependence on a Markov process. The magnitude of the fluctuations, multiplied with their auto-correlation time, is a small quantity. Under these co
Stochastic Physicochemical Dynamics
Tsekov, R.
2001-02-01
Thermodynamic Relaxation in Quantum Systems: A new approach to quantum Markov processes is developed and the corresponding Fokker-Planck equation is derived. The latter is examined to reproduce known results from classical and quantum physics. It was also applied to the phase-space description of a mechanical system thus leading to a new treatment of this problem different from the Wigner presentation. The equilibrium probability density obtained in the mixed coordinate-momentum space is a reasonable extension of the Gibbs canonical distribution. The validity of the Einstein fluctuation-dissipation relation is discussed in respect to the type of relaxation in an isothermal system. The first model, presuming isothermic fluctuations, leads to the Einstein formula. The second model supposes adiabatic fluctuations and yields another relation between the diffusion coefficient and mobility of a Brownian particle. A new approach to relaxations in quantum systems is also proposed that demonstrates applicability only of the adiabatic model for description of the quantum Brownian dynamics. Stochastic Dynamics of Gas Molecules: A stochastic Langevin equation is derived, describing the thermal motion of a molecule immersed in a rested fluid of identical molecules. The fluctuation-dissipation theorem is proved and a number of correlation characteristics of the molecular Brownian motion are obtained. A short review of the classical theory of Brownian motion is presented. A new method is proposed for derivation of the Fokker-Planck equations, describing the probability density evolution, from stochastic differential equations. It is also proven via the central limit theorem that the white noise is only Gaussian. The applicability of stochastic differential equations to thermodynamics is considered and a new form, different from the classical Ito and Stratonovich forms, is introduced. It is shown that the new presentation is more appropriate for the description of thermodynamic
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 ...
Global Dynamics of a Virus Dynamical Model with Cell-to-Cell Transmission and Cure Rate
Directory of Open Access Journals (Sweden)
Tongqian Zhang
2015-01-01
Full Text Available The cure effect of a virus model with both cell-to-cell transmission and cell-to-virus transmission is studied. By the method of next generation matrix, the basic reproduction number is obtained. The locally asymptotic stability of the virus-free equilibrium and the endemic equilibrium is considered by investigating the characteristic equation of the model. The globally asymptotic stability of the virus-free equilibrium is proved by constructing suitable Lyapunov function, and the sufficient condition for the globally asymptotic stability of the endemic equilibrium is obtained by constructing suitable Lyapunov function and using LaSalle invariance principal.
Mihailović, Dragutin T.; Kostić, Vladimir R.; Balaž, Igor; Kapor, Darko
2016-10-01
We examine the threshold of the influence of the tunneling nanotubes (TNTs) on the cell-to-cell communication integrity. A deterministic model is introduced with the Michaelis-Menten dynamics and the intercellular exchange of substance. The influence of TNTs are considered as a functional perturbation of the main communication and treated as the matrix nearness problems. We analyze communication integrity in terms of the \\emph{pseudospectra} of the exchange, to find the \\emph{distance to instability}. The threshold of TNTs influence is computed for Newman-Gastner and Erd\\H{o}s-R\\'enyi gap junction (GJ) networks.
Parzen, Emanuel
2015-01-01
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
Cytorhabdovirus P3 genes encode 30K-like cell-to-cell movement proteins.
Mann, Krin S; Bejerman, Nicolas; Johnson, Karyn N; Dietzgen, Ralf G
2016-02-01
Plant viruses encode movement proteins (MP) to facilitate cell-to-cell transport through plasmodesmata. In this study, using trans-complementation of a movement-defective turnip vein-clearing tobamovirus (TVCV) replicon, we show for the first time for cytorhabdoviruses (lettuce necrotic yellows virus (LNYV) and alfalfa dwarf virus (ADV)) that their P3 proteins function as MP similar to the TVCV P30 protein. All three MP localized to plasmodesmata when ectopically expressed. In addition, we show that these MP belong to the 30K superfamily since movement was inhibited by mutation of an aspartic acid residue in the critical 30K-specific LxD/N50-70G motif. We also report that Nicotiana benthamiana microtubule-associated VOZ1-like transcriptional activator interacts with LNYV P3 and TVCV P30 but not with ADV P3 or any of the MP point mutants. This host protein, which is known to interact with P3 of sonchus yellow net nucleorhabdovirus, may be involved in aiding the cell-to-cell movement of LNYV and TVCV.
Directory of Open Access Journals (Sweden)
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.
Natural sequence variants of yeast environmental sensors confer cell-to-cell expression variability.
Fehrmann, Steffen; Bottin-Duplus, Hélène; Leonidou, Andri; Mollereau, Esther; Barthelaix, Audrey; Wei, Wu; Steinmetz, Lars M; Yvert, Gaël
2013-10-08
Living systems may have evolved probabilistic bet hedging strategies that generate cell-to-cell phenotypic diversity in anticipation of environmental catastrophes, as opposed to adaptation via a deterministic response to environmental changes. Evolution of bet hedging assumes that genotypes segregating in natural populations modulate the level of intraclonal diversity, which so far has largely remained hypothetical. Using a fluorescent P(met17)-GFP reporter, we mapped four genetic loci conferring to a wild yeast strain an elevated cell-to-cell variability in the expression of MET17, a gene regulated by the methionine pathway. A frameshift mutation in the Erc1p transmembrane transporter, probably resulting from a release of laboratory strains from negative selection, reduced P(met17)-GFP expression variability. At a second locus, cis-regulatory polymorphisms increased mean expression of the Mup1p methionine permease, causing increased expression variability in trans. These results demonstrate that an expression quantitative trait locus (eQTL) can simultaneously have a deterministic effect in cis and a probabilistic effect in trans. Our observations indicate that the evolution of transmembrane transporter genes can tune intraclonal variation and may therefore be implicated in both reactive and anticipatory strategies of adaptation.
Schneider, Johannes J
2007-01-01
This book addresses stochastic optimization procedures in a broad manner. The first part offers an overview of relevant optimization philosophies; the second deals with benchmark problems in depth, by applying a selection of optimization procedures. Written primarily with scientists and students from the physical and engineering sciences in mind, this book addresses a larger community of all who wish to learn about stochastic optimization techniques and how to use them.
Quantum Fluctuations Of The Stress Tensor
Wu, C
2002-01-01
Quantum fluctuations of the stress tensor are important in many branches of physics, including the study of the validity of semiclassical gravity and the backreaction problem in stochastic semiclassical gravity. The geometry fluctuations induced by stress tensor fluctuations are important to understand quantum gravity and the problem of lightcone fluctuations. Stress tensor fluctuations also hold the key to understand fundamental physical effects like quantum fluctuations of radiation pressure, and that is crucial to the sensitivity of interferometers and the limitations on the detection of gravitational waves. Even the wave-particle duality of light can be better understood by the study of quantum fluctuations of thermal radiation. It is well known in quantum field theory that the expectation value of the energy density, which contains quadratic field operators (e.g. E2 and B2 in the electromagnatic field case), is divergent and can be renormalized simply by normal ordering, which is subtracting out the vac...
Smith, S Abigail; Derdeyn, Cynthia A
2017-03-01
HIV-1 infection from cell to cell may provide an efficient mode of viral spread in vivo and could therefore present a significant challenge for preventative or therapeutic strategies based on broadly neutralizing antibodies. Indeed, Li et al show that the potency and magnitude of multiple HIV-1 broadly neutralizing antibody classes are decreased during cell to cell infection in a context dependent manner. A functional motif in gp41 appears to contribute to this differential susceptibility by modulating exposure of neutralization epitopes.
Directory of Open Access Journals (Sweden)
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.
Damodaran, Shima P; Eberhard, Stephan; Boitard, Laurent; Rodriguez, Jairo Garnica; Wang, Yuxing; Bremond, Nicolas; Baudry, Jean; Bibette, Jérôme; Wollman, Francis-André
2015-01-01
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.
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.
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.
Small RNA Control of Cell-to-Cell Communication in Vibrio Harveyi and Vibrio Cholerae
Svenningsen, Sine Lo
Quorum sensing is a process of cell-to-cell communication, by which bacteria coordinate gene expression and behavior on a population-wide scale. Quorum sensing is accomplished through production, secretion, and subsequent detection of chemical signaling molecules termed autoinducers. The human pathogen Vibrio cholerae and the marine bioluminescent bacterium Vibrio harveyi incorporate information from multiple autoinducers, and also environmental signals and metabolic cues into their quorum-sensing pathways. At the core of these pathways lie several homologous small regulatory RNA molecules, the Quorum Regulatory RNAs. Small noncoding RNAs have emerged throughout the bacterial and eukaryotic kingdoms as key regulators of behavioral and developmental processes. Here, I review our present understanding of the role of the Qrr small RNAs in integrating quorum-sensing signals and in regulating the individual cells response to this information.
Alpha-synuclein cell-to-cell transfer and seeding in grafted dopaminergic neurons in vivo.
Directory of Open Access Journals (Sweden)
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.
Directory of Open Access Journals (Sweden)
Hidetada eHirakawa
2013-05-01
Full Text Available Bacteria use a cell-to-cell communication activity termed Quorum sensing to coordinate group behaviors in a cell-density dependent manner. Quorum sensing influences the expression profile of diverse genes, including antibiotic tolerance and virulence determinants, via specific chemical compounds called Auto-inducers. During quorum sensing, Gram-negative bacteria typically use an acylated homoserine lactone (AHL called auto-inducer 1 (AI-1. Since the first discovery of quorum sensing in a marine bacterium, it has been recognized that more than 100 species possess this mechanism of cell-to-cell communication. In addition to being of interest from a biological standpoint, quorum sensing is a potential target for antimicrobial chemotherapy. This unique concept of antimicrobial control relies on reducing the burden of virulence rather than killing the bacteria. It is believed that this approach will not only suppress the development of antibiotic resistance, but will also improve the treatment of refractory infections triggered by multi-drug resistant (MDR pathogens. In this paper, we review and track recent progress in studies on AHL inhibitors/modulators from a biological standpoint. It has been discovered that both natural and synthetic compounds can disrupt quorum sensing by a variety of means, such as jamming signal transduction, inhibition of signal production and break-down and trapping of signal compounds. We also focus on the regulatory elements that attenuate quorum sensing activities and discuss their unique properties. Understanding the biological roles of regulatory elements might be useful in developing inhibitor applications and understanding how quorum sensing is controlled.
Institute of Scientific and Technical Information of China (English)
侯威; 钱忠华; 杨萍; 封国林
2012-01-01
By combining detrended fluctuation analysis （DFA） method with surrogate data method, and using the heuristic segmentation algorithm as well as ChiSquare statistics, the stochastically resorting detrended fluctuation analysis（ S- DFA） method was developed to define the threshold of extreme events. By using S - DFA method, we obtained the thresholds of extreme precipitation events from 1961 to 2006 in China and analyzed its spatial - temporal distribution characteristics. We also validated the effectiveness of S - DFA method through extreme events detection by using precipitation series. The composite index of extreme precipitation events was given in this paper, which integrated the information about frequency and strength of extreme precipitation events, considering the characteristic of regional climate system. Based on the composite index, we divided into three zones according to different precipitation rank of extreme precipitation events from 1961 to 2006 in China. The composite index of extreme precipitation maintained smooth fluctuation with no obvious increasing or decreasing trend on the whole during 1961 -2006 in Chine.%将去趋势波动分析法（Detrended Fluctuation Analysis,DFA）和替代数据法相结合,同时引入启发式分割算法和卡方检验,提出了一种确定极端气候事件阈值的新方法,称为随机重排去趋势波动分析（Stochastic resort detrended Fluctuation Analysis,S-DFA）方法。同百分位阈值方法相比,S-DFA方法明确指出了极端事件和非极端事件之间的临界值。利用随机重排去趋势波动分析（S-DFA）方法计算并分析了中国极端降水事件阈值的空间分布特征,并对S-DFA方法在实际资料中的应用进行了检验。基于极端降水事件综合指标将中国1961～2006年间极端降水事件分为3个不同等级的地区,进一步发现我国1961～2006年间极端降水的综合指标整体没有表现出明显的上升或下降趋势,保持平稳的波动变化。
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...
Stochastic partial differential equations
Chow, Pao-Liu
2014-01-01
Preliminaries Introduction Some Examples Brownian Motions and Martingales Stochastic Integrals Stochastic Differential Equations of Itô Type Lévy Processes and Stochastic IntegralsStochastic Differential Equations of Lévy Type Comments Scalar Equations of First Order Introduction Generalized Itô's Formula Linear Stochastic Equations Quasilinear Equations General Remarks Stochastic Parabolic Equations Introduction Preliminaries Solution of Stochastic Heat EquationLinear Equations with Additive Noise Some Regularity Properties Stochastic Reaction-Diffusion Equations Parabolic Equations with Grad
On the stochastic dynamics of molecular conformation
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
An important functioning mechanism of biological macromolecules is the transition between different conformed states due to thermal fluctuation. In the present paper, a biological macromolecule is modeled as two strands with side chains facing each other, and its stochastic dynamics including the statistics of stationary motion and the statistics of conformational transition is studied by using the stochastic averaging method for quasi Hamiltonian systems. The theoretical results are confirmed with the results from Monte Carlo simulation.
Crossing Statistics of Anisotropic Stochastic Surface
Nezhadhaghighi, M Ghasemi; Yasseri, T; Allaei, S M Vaez
2015-01-01
We use crossing statistics and its generalization to determine the anisotropic direction imposed on a stochastic fields in $(2+1)$Dimension. This approach enables us to examine not only the rotational invariance of morphology but also we can determine the Gaussianity of underlying stochastic field in various dimensions. Theoretical prediction of up-crossing statistics (crossing with positive slope at a given threshold $\\alpha$ of height fluctuation), $\
Stochastic Constraint Programming
Walsh, Toby
2009-01-01
To model combinatorial decision problems involving uncertainty and probability, we introduce stochastic constraint programming. Stochastic constraint programs contain both decision variables (which we can set) and stochastic variables (which follow a probability distribution). They combine together the best features of traditional constraint satisfaction, stochastic integer programming, and stochastic satisfiability. We give a semantics for stochastic constraint programs, and propose a number...
Exploration of the spontaneous fluctuating activity of single enzyme molecules
Schwabe, A.; Maarleveld, T.R.; Bruggeman, F.J.
2013-01-01
Single enzyme molecules display inevitable, stochastic fluctuations in their catalytic activity. In metabolism, for instance, the stochastic activity of individual enzymes is averaged out due to their high copy numbers per single cell. However, many processes inside cells rely on single enzyme activ
Simulated microgravity allows to demonstrate cell-to-cell communication in bacteria
Mastroleo, Felice; van Houdt, Rob; Mergeay, Max; Hendrickx, Larissa; Wattiez, Ruddy; Leys, Natalie
Through the MELiSSA project, the European Space Agency aims to develop a closed life support system for oxygen, water and food production to support human life in space in forth-coming long term space exploration missions. This production is based on the recycling of the missions organic waste, including CO2 and minerals. The photosynthetic bacterium Rhodospir-illum rubrum S1H is used in MELiSSA to degrade organics with light energy and is the first MELiSSA organism that has been studied in space related environmental conditions (Mastroleo et al., 2009). It was tested in actual space flight to the International Space Station (ISS) as well as in ground simulations of ISS-like ionizing radiation and microgravity. In the present study, R. rubrum S1H was cultured in liquid medium in 2 devices simulating microgravity conditions, i.e. the Rotating Wall Vessel (RWV) and the Random Positioning Machine (RPM). The re-sponse of the bacterium was evaluated at both the transcriptomic and proteomic levels using respectively a dedicated whole-genome microarray and high-throughput gel-free quantitative proteomics. Both at transcriptomic and proteomic level, the bacterium showed a significant response to cultivation in simulated microgravity. The response to low fluid shear modeled microgravity in RWV was different than to randomized microgravity in RPM. Nevertheless, both tests pointed out a change in and a likely interrelation between cell-to-cell communica-tion (i.e. quorum sensing) and cell pigmentation (i.e. photosynthesis) for R. rubrum S1H in microgravity conditions. A new type of cell-to-cell communication molecule in R. rubrum S1H was discovered and characterized. It is hypothised that the lack of convection currents and the fluid quiescence in (simulated) microgravity limits communications molecules to be spread throughout the medium. Cultivation in this new artificial environment of simulated micro-gravity has showed new properties of this well know bacterium
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
Stochastic deformation of a thermodynamic symplectic structure
Kazinski, P. O.
2009-01-01
A stochastic deformation of a thermodynamic symplectic structure is studied. The stochastic deformation is analogous to the deformation of an algebra of observables such as 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 transformations and gauge fields is given. An application of the formalism to a description of systems with distributed parameters in a local thermodynamic equilibrium is considered.
A Nonlinear Dynamic Characterization of The Universal Scrape-off Layer Plasma Fluctuations
Mekkaoui, A
2012-01-01
A stochastic differential equation of plasma density dynamic is derived, consistent with the experimentally measured pdf and the theoretical quadratic nonlinearity. The plasma density evolves on the turbulence correlation time scale and is driven by a stochastic white noise proportional to the turbulence fluctuations amplitude, while the linear growth is quadratically damped by the fluctuation level $n_e(t)/\\bar{n}_e$.
Asymptotic behavior of stochastic multi-group epidemic models with distributed delays
Liu, Qun; Jiang, Daqing; Shi, Ningzhong; Hayat, Tasawar; Alsaedi, Ahmed
2017-02-01
In this paper, we introduce stochasticity into multi-group epidemic models with distributed delays and general kernel functions. The stochasticity in the model is a standard technique in stochastic population modeling. When the perturbations are small, by using the method of stochastic Lyapunov functions, we carry out a detailed analysis on the asymptotic behavior of the stochastic model regarding of the basic reproduction number R0. If R0 ≤ 1, the solution of the stochastic system oscillates around the disease-free equilibrium E0, while if R0 > 1, the solution of the stochastic model fluctuates around the endemic equilibrium E∗. Moreover, we also establish sufficient conditions of these results.
Rate dependence of cell-to-cell variations of lithium-ion cells
An, Fuqiang; Chen, Lufan; Huang, Jun; Zhang, Jianbo; Li, Ping
2016-10-01
Lithium-ion cells are commonly used in a multicell configuration in power devices and electric vehicles, making the cell-to-cell variation (CtCV) a key factor to consider in system design and management. Previous studies on CtCV have two major limitations: the number of cells is usually less than one hundred, and the cells are usually commercial cells already subjected to cell-screenings. In this article, we first make a statistical analysis on the CtCV of 5473 fresh cells from an automotive battery manufacturer before the cell-screening process. Secondly, 198 cells are randomly selected from these 5473 cells and the rate dependence of the CtCV is examined, focusing on the correlations of capacity versus weight and capacity versus resistance, corresponding to thermodynamic and kinetic factors, respectively. The rate dependence of these two correlations is explained from a phenomenological model. Finally, eight cells from the 198 cells are further characterized with electrochemical impedance spectroscopy method to elucidate the kinetic origins of the CtCV.
Directory of Open Access Journals (Sweden)
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.
Institute of Scientific and Technical Information of China (English)
Ingrid Rupp; Gabriele Pradel; Ludmilla Sologub; Kim C Williamson; Matthias Scheuermayer; Luc Reininger; Christian Doerig; Saliha Eksi; Davy U Kombilaa; Matthias Frank
2011-01-01
Physical contact is important for the interaction between animal cells, but it can represent a major challenge for protists like malaria parasites. Recently, novel filamentous cell-cell contacts have been identified in different types of eukaryotic cells and termed nanotubes due to their morphological appearance. Nanotubes represent small dynamic membranous extensions that consist of F-actin and are considered an ancient feature evolved by eukaryotic cells to establish contact for communication. We here describe similar tubular structures in the malaria pathogen Plasmodium falciparum, which emerge from the surfaces of the forming gametes upon gametocyte activation in the mosquito midgut. The filaments can exhibit a length of>100 μm and contain the F-actin isoform actin 2. They actively form within a few minutes after gametocyte activation and persist until the zygote transforms into the ookinete. The filaments originate from the parasite plasma membrane, are close ended and express adhesion proteins on their surfaces that are typically found in gametes, like Pfs230, Pfs48/45 or Pfs25, but not the zygote surface protein Pfs28. We show that these tubular structures represent long-distance cell-to-cell connections between sexual stage parasites and demonstrate that they meet the characteristics of nanotubes. We propose that malaria parasites utilize these adhesive "nanotubes" in order to facilitate intercellular contact between gametes during reproduction in the mosquito midgut.
Plasmodesmal-mediated cell-to-cell transport in wheat roots is modulated by anaerobic stress
Cleland, R. E.; Fujiwara, T.; Lucas, W. J.
1994-01-01
Cell-to-cell transport of small molecules and ions occurs in plants through plasmodesmata. Plant roots are frequently subjected to localized anaerobic stress, with a resultant decrease in ATP. In order to determine the effect of this stress on plasmodesmal transport, fluorescent dyes of increasing molecular weight (0.46 to 1OkDa) were injected into epidermal and cortical cells of 3-day-old wheat roots, and their movement into neighboring cells was determined by fluorescence microscopy. Anaerobiosis was generated by N2 gas or simulated by the presence of sodium azide, both of which reduced the ATP levels in the tissue by over 80%. In the absence of such stress, the upper limit for movement, or size exclusion limit (SEL), of cortical plasmodesmata was roots, indicating that plasmodesmata may be conduits for nucleotide (ATP and ADP) exchange between cells. Upon imposition of stress, the SEL rose to between 5 and 10 kDa. This response of plasmodesmata to a decrease in the level of ATP suggests that they are constricted by an ATP-dependent process so as to maintain a restricted SEL. When roots are subjected to anaerobic stress, an increase in SEL may permit enhanced delivery of sugars to the affected cells of the root where anaerobic respiration could regenerate the needed ATP.
From cusps to cores: a stochastic model
El-Zant, Amr; Combes, Francoise
2016-01-01
The cold dark matter model of structure formation faces apparent problems on galactic scales. Several threads point to excessive halo concentration, including central densities that rise too steeply with decreasing radius. Yet, random fluctuations in the gaseous component can 'heat' the centres of haloes, decreasing their densities. We present a theoretical model deriving this effect from first principles: stochastic variations in the gas density are converted into potential fluctuations that act on the dark matter; the associated force correlation function is calculated and the corresponding stochastic equation solved. Assuming a power law spectrum of fluctuations with maximal and minimal cutoff scales, we derive the velocity dispersion imparted to the halo particles and the relevant relaxation time. We further perform numerical simulations, with fluctuations realised as a Gaussian random field, which confirm the formation of a core within a timescale comparable to that derived analytically. Non-radial colle...
2013-01-01
Single-cell variations in gene and protein expression are important during development and disease. Cell-to-cell heterogeneities can be directly inspected one cell at a time, but global methods are usually not sensitive enough to work with such a small amount of starting material. Here, we provide a detailed protocol for stochastic profiling, a method that infers single-cell regulatory heterogeneities by repeatedly sampling small collections of cells at random. Repeated stochastic sampling is...
Li, Yi; Bao, Yi M; Wei, Chun H; Kang, Zhen S; Zhong, Yong W; Mao, Peng; Wu, Gang; Chen, Zhang L; Schiemann, Joachim; Nelson, Richard S
2004-05-01
Rice dwarf virus (RDV) is a member of the genus Phytoreovirus, which is composed of viruses with segmented double-stranded RNA genomes. Proteins that support the intercellular movement of these viruses in the host have not been identified. Microprojectile bombardment was used to determine which open reading frames (ORFs) support intercellular movement of a heterologous virus. A plasmid containing an infectious clone of Potato virus X (PVX) defective in cell-to-cell movement and expressing either beta-glucuronidase or green fluorescent protein (GFP) was used for cobombardment with plasmids containing ORFs from RDV gene segments S1 through S12 onto leaves of Nicotiana benthamiana. Cell-to-cell movement of the movement-defective PVX was restored by cobombardment with a plasmid containing S6. In the absence of S6, no other gene segment supported movement. Identical results were obtained with Nicotiana tabacum, a host that allows fewer viruses to infect and spread within its tissue. S6 supported the cell-to-cell movement of the movement-defective PVX in sink and source leaves of N. benthamiana. A mutant S6 lacking the translation start codon did not complement the cell-to-cell movement of the movement-defective PVX. An S6 protein product (Pns6)-enhanced GFP fusion was observed near or within cell walls of epidermal cells from N. tabacum. By immunocytochemistry, unfused Pns6 was localized to plasmodesmata in rice leaves infected with RDV. S6 thus encodes a protein with characteristics identical to those of other viral proteins required for the cell-to-cell movement of their genome and therefore is likely required for the cell-to-cell movement of RDV.
Laboratory Evidence for Stochastic Plasma-Wave Growth
Austin, D. R.; Hole, M. J.; Robinson, P. A.; Cairns, Iver H.; Dallaqua, R.
2007-11-01
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.
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 relia
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
Stochastic Gravity: Theory and Applications
Directory of Open Access Journals (Sweden)
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
Modelling the Impact of Cell-To-Cell Transmission in Hepatitis B Virus
2016-01-01
Cell-free virus is a well-recognized and efficient mechanism for the spread of hepatitis B virus (HBV) infection in the liver. Cell-to-cell transmission (CCT) can be a more efficient means of virus propagation. Despite experimental evidence implying CCT occurs in HBV, its relative impact is uncertain. We develop a 3-D agent-based model where each hepatocyte changes its viral state according to a dynamical process driven by cell-free virus infection, CCT and intracellular replication. We determine the relative importance of CCT in the development and resolution of acute HBV infection in the presence of cytolytic (CTL) and non-CTL mechanisms. T cell clearance number is defined as the minimum number of infected cells needed to be killed by each T cell at peak infection that results in infection clearance within 12 weeks with hepatocyte turnover (HT, number of equivalent livers) ≤3. We find that CCT has very little impact on the establishment of infection as the mean cccDNA copies/cell remains between 15 to 20 at the peak of the infection regardless of CCT strength. In contrast, CCT inhibit immune-mediated clearance of acute HBV infection as higher CCT strength requires higher T cell clearance number and increases the probability of T cell exhaustion. An effective non-CTL inhibition can counter these negative effects of higher strengths of CCT by supporting rapid, efficient viral clearance and with little liver destruction. This is evident as the T cell clearance number drops by approximately 50% when non-CTL inhibition is increased from 10% to 80%. Higher CCT strength also increases the probability of the incidence of fulminant hepatitis with this phenomenon being unlikely to arise for no CCT. In conclusion, we report the possibility of CCT impacting HBV clearance and its contribution to fulminant hepatitis. PMID:27560827
Stochastic Gravity: Theory and Applications
Directory of Open Access Journals (Sweden)
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
Enhanced droplet spreading due to thermal fluctuations
Energy Technology Data Exchange (ETDEWEB)
Willis, A M; Freund, J B, E-mail: jbfreund@illinois.ed [Department of Mechanical Science and Engineering, College of Engineering, University of Illinois at Urbana-Champaign, 1206 West Green Street, Urbana, IL 61801 (United States)
2009-11-18
The lubrication equation that governs the dynamics of thin liquid films can be augmented to account for stochastic stresses associated with the thermal fluctuations of the fluid. It has been suggested that under certain conditions the spreading rate of a liquid drop on a surface will be increased by these stochastic stresses. Here, an atomistic simulation of a spreading drop is designed to examine such a regime and provide a quantitative assessment of the stochastic lubrication equation for spreading. It is found that the atomistic drop does indeed spread faster than the standard lubrication equations would suggest and that the stochastic lubrication equation of Gruen et al (2006 J. Stat. Phys. 122 1261-91) predicts the spread rate.
Stochastic Resonance in Protein Folding Dynamics.
Davtyan, Aram; Platkov, Max; Gruebele, Martin; Papoian, Garegin A
2016-05-04
Although protein folding reactions are usually studied under static external conditions, it is likely that proteins fold in a locally fluctuating cellular environment in vivo. To mimic such behavior in in vitro experiments, the local temperature of the solvent can be modulated either harmonically or using correlated noise. In this study, coarse-grained molecular simulations are used to investigate these possibilities, and it is found that both periodic and correlated random fluctuations of the environment can indeed accelerate folding kinetics if the characteristic frequencies of the applied fluctuations are commensurate with the internal timescale of the folding reaction; this is consistent with the phenomenon of stochastic resonance observed in many other condensed-matter processes. To test this theoretical prediction, the folding dynamics of phosphoglycerate kinase under harmonic temperature fluctuations are experimentally probed using Förster resonance energy transfer fluorescence measurements. To analyze these experiments, a combination of theoretical approaches is developed, including stochastic simulations of folding kinetics and an analytical mean-field kinetic theory. The experimental observations are consistent with the theoretical predictions of stochastic resonance in phosphoglycerate kinase folding. When combined with an alternative experiment on the protein VlsE using a power spectrum analysis, elaborated in Dave et al., ChemPhysChem 2016, 10.1002/cphc.201501041, the overall data overwhelmingly point to the experimental confirmation of stochastic resonance in protein folding dynamics.
Institute of Scientific and Technical Information of China (English)
张文柯; 张劲军; 宇波
2011-01-01
An efficient numerical algorithm, which employed the finite volume , finite difference , Monte Carlo and proper orthogonal decomposition ( POD) method, was proposed to simulate the stochastic fluctuation of oil temperatures. The effects of outlet oil temperature, flow rate, pressure, buried depth, soil temperature. soil thermal conductivity, oil viscosity and oil density on the stochastic fluctuation of oil temperatures were investigated through Sobol global sensitivity induces. The results show that the deviations of the mean oil temperatures between numerical simulations and field measurements were lower than 0. 1 ℃ , and the standard deviations vary from 0. 006 ℃ to 0.023 ℃ . When considered the following 4 factors: outlet oil temperature, throughput, soil temperature and oil viscosity, case studies on the China West crude pipeline show that the sum of first order global sensitivity achieved as 77. 44％ on Sipu station and 80. 86％ on Hexi station. Therefore, it is acceptable to consider these 4 factors when simulating the fluctuation of inlet oil temperatures.%综合采用有限容积法、有限差分法、Monte Carlo算法和POD算法建立埋地热油管道沿线油温的随机数值模拟算法,使用Sobol全局敏感性指标进行敏感性分析,综合评价出站油温、流量、压力、埋深、埋深处自然地温、土壤导热系数、油品黏度和密度的随机波动对管道沿线油温波动的影响.计算结果表明:进站油温模拟结果与现场油温均值偏差在0.1℃以内,标准差的偏差为0.006～0.023℃;出站油温、流量、埋深处地温和油品黏度4个参数的不确定性对四堡进站油温波动的敏感性指标之和为77.44%,河西站的该指标为80.86%,进站温度的随机数值模拟中主要考虑这4个参数的不确定性即可.
Wave Propagation in Stochastic Spacetimes Localization, Amplification and Particle Creation
Hu, B L
1998-01-01
Here we study novel effects associated with electromagnetic wave propagation in a Robertson-Walker universe and the Schwarzschild spacetime with a small amount of metric stochasticity. We find that localization of electromagnetic waves occurs in a Robertson-Walker universe with time-independent metric stochasticity, while time-dependent metric stochasticity induces exponential instability in the particle production rate. For the Schwarzschild metric, time-independent randomness can decrease the total luminosity of Hawking radiation due to multiple scattering of waves outside the black hole and gives rise to event horizon fluctuations and thus fluctuations in the Hawking temperature.
Algorithm refinement for stochastic partial differential equations.
Energy Technology Data Exchange (ETDEWEB)
Alexander, F. J. (Francis J.); Garcia, Alejandro L.,; Tartakovsky, D. M. (Daniel M.)
2001-01-01
A hybrid particle/continuum algorithm is formulated for Fickian diffusion in the fluctuating hydrodynamic limit. The particles are taken as independent random walkers; the fluctuating diffusion equation is solved by finite differences with deterministic and white-noise fluxes. At the interface between the particle and continuum computations the coupling is by flux matching, giving exact mass conservation. This methodology is an extension of Adaptive Mesh and Algorithm Refinement to stochastic partial differential equations. A variety of numerical experiments were performed for both steady and time-dependent scenarios. In all cases the mean and variance of density are captured correctly by the stochastic hybrid algorithm. For a non-stochastic version (i.e., using only deterministic continuum fluxes) the mean density is correct, but the variance is reduced except within the particle region, far from the interface. Extensions of the methodology to fluid mechanics applications are discussed.
Directory of Open Access Journals (Sweden)
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.
Algorithm refinement for fluctuating hydrodynamics
Energy Technology Data Exchange (ETDEWEB)
Williams, Sarah A.; Bell, John B.; Garcia, Alejandro L.
2007-07-03
This paper introduces an adaptive mesh and algorithmrefinement method for fluctuating hydrodynamics. This particle-continuumhybrid simulates the dynamics of a compressible fluid with thermalfluctuations. The particle algorithm is direct simulation Monte Carlo(DSMC), a molecular-level scheme based on the Boltzmann equation. Thecontinuum algorithm is based on the Landau-Lifshitz Navier-Stokes (LLNS)equations, which incorporate thermal fluctuations into macroscopichydrodynamics by using stochastic fluxes. It uses a recently-developedsolver for LLNS, based on third-order Runge-Kutta. We present numericaltests of systems in and out of equilibrium, including time-dependentsystems, and demonstrate dynamic adaptive refinement by the computationof a moving shock wave. Mean system behavior and second moment statisticsof our simulations match theoretical values and benchmarks well. We findthat particular attention should be paid to the spectrum of the flux atthe interface between the particle and continuum methods, specificallyfor the non-hydrodynamic (kinetic) time scales.
Assessing the quality of stochastic oscillations
Indian Academy of Sciences (India)
Guillermo Abramson; Sebastián Risau-Gusman
2008-06-01
We analyze the relationship between the macroscopic and microscopic descriptions of two-state systems, in particular the regime in which the microscopic one shows sustained `stochastic oscillations' while the macroscopic tends to a fixed point. We propose a quantification of the oscillatory appearance of the fluctuating populations, and show that good stochastic oscillations are present if a parameter of the macroscopic model is small, and that no microscopic model will show oscillations if that parameter is large. The transition between these two regimes is smooth. In other words, given a macroscopic deterministic model, one can know whether any microscopic stochastic model that has it as a limit, will display good sustained stochastic oscillations.
The influence of stochastic dispersion on optical soliton system and its suppression
Institute of Scientific and Technical Information of China (English)
杨祥林; 温扬敬; 张明德
1995-01-01
The influence of stochastic dispersion on an optical soliton communication system is investigated, and the method of reducing this influence is also given. The analysis shows that the existence-of stochastic dispersion results in the arrival time jitter, which is in proportion to the mean square fluctuation of the imaginary component of stochastic dispersion and is related to soliton amplitude and velocity. The influence of stochastic dispersion can be reduced by using filtering method in frequency domain.
Energy Technology Data Exchange (ETDEWEB)
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.
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.
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 ...
Energy Technology Data Exchange (ETDEWEB)
Blaskiewicz, M.
2011-01-01
Stochastic Cooling was invented by Simon van der Meer and was demonstrated at the CERN ISR and ICE (Initial Cooling Experiment). Operational systems were developed at Fermilab and CERN. A complete theory of cooling of unbunched beams was developed, and was applied at CERN and Fermilab. Several new and existing rings employ coasting beam cooling. Bunched beam cooling was demonstrated in ICE and has been observed in several rings designed for coasting beam cooling. High energy bunched beams have proven more difficult. Signal suppression was achieved in the Tevatron, though operational cooling was not pursued at Fermilab. Longitudinal cooling was achieved in the RHIC collider. More recently a vertical cooling system in RHIC cooled both transverse dimensions via betatron coupling.
Sasaki, Nobumitsu; Ogata, Takuya; Deguchi, Masakazu; Nagai, Shoko; Tamai, Atsushi; Meshi, Tetsuo; Kawakami, Shigeki; Watanabe, Yuichiro; Matsushita, Yasuhiko; Nyunoya, Hiroshi
2009-03-01
Tomato mosaic virus (ToMV) encodes a movement protein (MP) that is necessary for virus cell-to-cell movement. We have demonstrated previously that KELP, a putative transcriptional coactivator of Arabidopsis thaliana, and its orthologue from Brassica campestris can bind to ToMV MP in vitro. In this study, we examined the effects of the transient over-expression of KELP on ToMV infection and the intracellular localization of MP in Nicotiana benthamiana, an experimental host of the virus. In co-bombardment experiments, the over-expression of KELP inhibited virus cell-to-cell movement. The N-terminal half of KELP (KELPdC), which had been shown to bind to MP, was sufficient for inhibition. Furthermore, the over-expression of KELP and KELPdC, both of which were co-localized with ToMV MP, led to a reduction in the plasmodesmal association of MP. In the absence of MP expression, KELP was localized in the nucleus and the cytoplasm by the localization signal in its N-terminal half. It was also shown that ToMV amplified normally in protoplasts prepared from leaf tissue that expressed KELP transiently. These results indicate that over-expressed KELP interacts with MP in vivo and exerts an inhibitory effect on MP function for virus cell-to-cell movement, but not on virus amplification in individual cells.
Institute of Scientific and Technical Information of China (English)
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...
Abramov, Rafail V.
2017-03-01
The classical fluctuation-dissipation theorem predicts the average response of a dynamical system to an external deterministic perturbation via time-lagged statistical correlation functions of the corresponding unperturbed system. In this work we develop a fluctuation-response theory and test a computational framework for the leading order response of statistical averages of a deterministic or stochastic dynamical system to an external stochastic perturbation. In the case of a stochastic unperturbed dynamical system, we compute the leading order fluctuation-response formulas for two different cases: when the existing stochastic term is perturbed, and when a new, statistically independent, stochastic perturbation is introduced. We numerically investigate the effectiveness of the new response formulas for an appropriately rescaled Lorenz 96 system, in both the deterministic and stochastic unperturbed dynamical regimes.
Stochastic effects in a seasonally forced epidemic model
Rozhnova, G.; Nunes, A.
2010-10-01
The interplay of seasonality, the system’s nonlinearities and intrinsic stochasticity, is studied for a seasonally forced susceptible-exposed-infective-recovered stochastic model. The model is explored in the parameter region that corresponds to childhood infectious diseases such as measles. The power spectrum of the stochastic fluctuations around the attractors of the deterministic system that describes the model in the thermodynamic limit is computed analytically and validated by stochastic simulations for large system sizes. Size effects are studied through additional simulations. Other effects such as switching between coexisting attractors induced by stochasticity often mentioned in the literature as playing an important role in the dynamics of childhood infectious diseases are also investigated. The main conclusion is that stochastic amplification, rather than these effects, is the key ingredient to understand the observed incidence patterns.
Stochastic effects in a seasonally forced epidemic model
Rozhnova, Ganna
2010-01-01
The interplay of seasonality, the system's nonlinearities and intrinsic stochasticity is studied for a seasonally forced susceptible-exposed-infective-recovered stochastic model. The model is explored in the parameter region that corresponds to childhood infectious diseases such as measles. The power spectrum of the stochastic fluctuations around the attractors of the deterministic system that describes the model in the thermodynamic limit is computed analytically and validated by stochastic simulations for large system sizes. Size effects are studied through additional simulations. Other effects such as switching between coexisting attractors induced by stochasticity often mentioned in the literature as playing an important role in the dynamics of childhood infectious diseases are also investigated. The main conclusion is that stochastic amplification, rather than these effects, is the key ingredient to understand the observed incidence patterns.
Biologically variable respiration as a stochastic process in ventilation - a stochastic model study.
Min, Kyongyob; Hosoi, Keita; Degami, Masayuki; Kinoshita, Yoshinori
2010-01-01
Based on the fractal bronchial tree, we introduced a function of "asynchronous phasic contractions of lobular bronchiole", which would generate fluctuations in tidal volumes. Stochastic control theory was able to describe a genesis of biological variability in spontaneous respirations using a Schroedinger wave function.
Stochastic homothetically revealed preference for tight stochastic demand functions
Jan Heufer
2009-01-01
This paper strengthens the framework of stochastic revealed preferences introduced by Bandyopadhyay et al. (1999, 2004) for stochastic homothetically revealed preferences for tight stochastic demand functions.
da Silva, Robert L; Krumholz, Mark R
2014-01-01
The integrated light of a stellar population, measured through photometric filters that are sensitive to the presence of young stars, is often used to infer the star formation rate (SFR) for that population. However, these techniques rely on an assumption that star formation is a continuous process, whereas in reality stars form in discrete spatially- and temporally-correlated structures. This discreteness causes the light output to undergo significant time-dependent fluctuations, which, if not accounted for, introduce errors and biases in the inferred SFRs. We use SLUG (a code that Stochastically Lights Up Galaxies) to simulate galaxies undergoing stochastic star formation. We then use these simulations to present a quantitative analysis of these effects and provide tools for calculating probability distribution functions of SFRs given a set of observations. We show that, depending on the SFR tracer used, stochastic fluctuations can produce non-trivial errors at SFRs as high as 1 Msun/yr, and we suggest meth...
Giant natural fluctuation models and anthropogenic warming
Lovejoy, S.; Rio Amador, L.; Hébert, R.; Lima, I.
2016-08-01
Explanations for the industrial epoch warming are polarized around the hypotheses of anthropogenic warming (AW) and giant natural fluctuations (GNFs). While climate sceptics have systematically attacked AW, up until now they have only invoked GNFs. This has now changed with the publication by D. Keenan of a sample of 1000 series from stochastic processes purporting to emulate the global annual temperature since 1880. While Keenan's objective was to criticize the International Panel on Climate Change's trend uncertainty analysis (their assumption that residuals are only weakly correlated), for the first time it is possible to compare a stochastic GNF model with real data. Using Haar fluctuations, probability distributions, and other techniques of time series analysis, we show that his model has unrealistically strong low-frequency variability so that even mild extrapolations imply ice ages every ≈1000 years. Helped by statistics, the GNF model can easily be scientifically rejected.
Stochasticity in cell biology: Modeling across levels
Pedraza, Juan Manuel
2009-03-01
Effective modeling of biological processes requires focusing on a particular level of description, and this requires summarizing de details of lower levels into effective variables and properly accounting for the constrains that other levels impose. In the context of stochasticity in gene expression, I will show how the details of the stochastic process can be characterized by a few effective parameters, which facilitates modeling but complicates interpretation of current experiments. I will show how the resulting noise can provide advantageous or deleterious phenotypic fluctuation and how noise control in the copy number control system of plasmids can change the selective pressures. This system illustrates the direct connection between molecular dynamics and evolutionary dynamics.
Statistical mechanics of stochastic growth phenomena
Alekseev, Oleg
2016-01-01
We develop statistical mechanics for stochastic growth processes as applied to Laplacian growth by using its remarkable connection with a random matrix theory. The Laplacian growth equation is obtained from the variation principle and describes adiabatic (quasi-static) thermodynamic processes in the two-dimensional Dyson gas. By using Einstein's theory of thermodynamic fluctuations we consider transitional probabilities between thermodynamic states, which are in a one-to-one correspondence with planar domains. Transitions between these domains are described by the stochastic Laplacian growth equation, while the transitional probabilities coincide with the free-particle propagator on the infinite dimensional complex manifold with the K\\"ahler metric.
Constraints on Fluctuations in Sparsely Characterized Biological Systems
Hilfinger, Andreas; Norman, Thomas M.; Vinnicombe, Glenn; Paulsson, Johan
2016-02-01
Biochemical processes are inherently stochastic, creating molecular fluctuations in otherwise identical cells. Such "noise" is widespread but has proven difficult to analyze because most systems are sparsely characterized at the single cell level and because nonlinear stochastic models are analytically intractable. Here, we exactly relate average abundances, lifetimes, step sizes, and covariances for any pair of components in complex stochastic reaction systems even when the dynamics of other components are left unspecified. Using basic mathematical inequalities, we then establish bounds for whole classes of systems. These bounds highlight fundamental trade-offs that show how efficient assembly processes must invariably exhibit large fluctuations in subunit levels and how eliminating fluctuations in one cellular component requires creating heterogeneity in another.
Constraints on Fluctuations in Sparsely Characterized Biological Systems
Hilfinger, Andreas; Norman, Thomas M.; Vinnicombe, Glenn
2016-01-01
Biochemical processes are inherently stochastic, creating molecular fluctuations in otherwise identical cells. Such “noise” is widespread but has proven difficult to analyze because most systems are sparsely characterized at the single cell level and because nonlinear stochastic models are analytically intractable. Here, we exactly relate average abundances, lifetimes, step sizes, and covariances for any pair of components in complex stochastic reaction systems even when the dynamics of other components are left unspecified. Using basic mathematical inequalities, we then establish bounds for whole classes of systems. These bounds highlight fundamental trade-offs that show how efficient assembly processes must invariably exhibit large fluctuations in subunit levels and how eliminating fluctuations in one cellular component requires creating heterogeneity in another. PMID:26894735
Cosmological fluctuations of a random field and radiation fluid
Energy Technology Data Exchange (ETDEWEB)
Bastero-Gil, Mar [Departamento de Física Teórica y del Cosmos, Campus de Fuentenueva, Universidad de Granada, Granada, 18071 (Spain); Berera, Arjun [SUPA, School of Physics and Astronomy, University of Edinburgh, Edinburgh, EH9 3JZ (United Kingdom); Moss, Ian G. [School of Mathematics and Statistics, Newcastlle University, Newcastle upon Tyne, NE1 7RU (United Kingdom); Ramos, Rudnei O., E-mail: mbg@ugr.es, E-mail: ab@ph.ed.ac.uk, E-mail: ian.moss@ncl.ac.uk, E-mail: rudnei@uerj.br [Departamento de Física Teórica, Universidade do Estado do Rio de Janeiro, Rio de Janeiro, RJ, 20550-013 Brazil (Brazil)
2014-05-01
A generalization of the random fluid hydrodynamic fluctuation theory due to Landau and Lifshitz is applied to describe cosmological fluctuations in systems with radiation and scalar fields. The viscous pressures, parametrized in terms of the bulk and shear viscosity coefficients, and the respective random fluctuations in the radiation fluid are combined with the stochastic and dissipative scalar evolution equation. This results in a complete set of equations describing the perturbations in both scalar and radiation fluids. These derived equations are then studied, as an example, in the context of warm inflation. Similar treatments can be done for other cosmological early universe scenarios involving thermal or statistical fluctuations.
Almquist, Joachim; Bendrioua, Loubna; Adiels, Caroline Beck; Goksör, Mattias; Hohmann, Stefan; Jirstrand, Mats
2015-01-01
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 response of Mig1 tend
Directory of Open Access Journals (Sweden)
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
Stochastic flux freezing and magnetic dynamo.
Eyink, Gregory L
2011-05-01
Magnetic flux conservation in turbulent plasmas at high magnetic Reynolds numbers is argued neither to hold in the conventional sense nor to be entirely broken, but instead to be valid in a statistical sense associated to the "spontaneous stochasticity" of Lagrangian particle trajectories. The latter phenomenon is due to the explosive separation of particles undergoing turbulent Richardson diffusion, which leads to a breakdown of Laplacian determinism for classical dynamics. Empirical evidence is presented for spontaneous stochasticity, including numerical results. A Lagrangian path-integral approach is then exploited to establish stochastic flux freezing for resistive hydromagnetic equations and to argue, based on the properties of Richardson diffusion, that flux conservation must remain stochastic at infinite magnetic Reynolds number. An important application of these results is the kinematic, fluctuation dynamo in nonhelical, incompressible turbulence at magnetic Prandtl number (Pr(m)) equal to unity. Numerical results on the Lagrangian dynamo mechanisms by a stochastic particle method demonstrate a strong similarity between the Pr(m)=1 and 0 dynamos. Stochasticity of field-line motion is an essential ingredient of both. Finally, some consequences for nonlinear magnetohydrodynamic turbulence, dynamo, and reconnection are briefly considered.
Mechanical Autonomous Stochastic Heat Engine
Serra-Garcia, Marc; Foehr, André; Molerón, Miguel; Lydon, Joseph; Chong, Christopher; Daraio, Chiara
2016-07-01
Stochastic heat engines are devices that generate work from random thermal motion using a small number of highly fluctuating degrees of freedom. Proposals for such devices have existed for more than a century and include the Maxwell demon and the Feynman ratchet. Only recently have they been demonstrated experimentally, using, e.g., thermal cycles implemented in optical traps. However, recent experimental demonstrations of classical stochastic heat engines are nonautonomous, since they require an external control system that prescribes a heating and cooling cycle and consume more energy than they produce. We present a heat engine consisting of three coupled mechanical resonators (two ribbons and a cantilever) subject to a stochastic drive. The engine uses geometric nonlinearities in the resonating ribbons to autonomously convert a random excitation into a low-entropy, nonpassive oscillation of the cantilever. The engine presents the anomalous heat transport property of negative thermal conductivity, consisting in the ability to passively transfer energy from a cold reservoir to a hot reservoir.
General Analysis of Type I Planetary Migration with Stochastic Perturbations
Adams, Fred C
2009-01-01
This paper presents a generalized treatment of Type I planetary migration in the presence of stochastic perturbations. In many planet-forming disks, the Type I migration mechanism, driven by asymmetric torques, acts on a short time scale and compromises planet formation. If the disk also supports MHD instabilities, however, the corresponding turbulent fluctuations produce additional stochastic torques that modify the steady inward migration scenario. This work studies the migration of planetary cores in the presence of stochastic fluctuations using complementary methods, including a Fokker-Planck approach and iterative maps. Stochastic torques have two main effects: [1] Through outward diffusion, a small fraction of the planetary cores can survive in the face of Type I inward migration. [2] For a given starting condition, the result of any particular realization of migration is uncertain, so that results must be described in terms of the distributions of outcomes. In addition to exploring different regimes of...
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...
Asymmetric stochastic switching driven by intrinsic molecular noise.
Directory of Open Access Journals (Sweden)
David Frigola
Full Text Available Low-copy-number molecules are involved in many functions in cells. The intrinsic fluctuations of these numbers can enable stochastic switching between multiple steady states, inducing phenotypic variability. Herein we present a theoretical and computational study based on Master Equations and Fokker-Planck and Langevin descriptions of stochastic switching for a genetic circuit of autoactivation. We show that in this circuit the intrinsic fluctuations arising from low-copy numbers, which are inherently state-dependent, drive asymmetric switching. These theoretical results are consistent with experimental data that have been reported for the bistable system of the gallactose signaling network in yeast. Our study unravels that intrinsic fluctuations, while not required to describe bistability, are fundamental to understand stochastic switching and the dynamical relative stability of multiple states.
The stochastic integrable AKNS hierarchy
Arnaudon, Alexis
2015-01-01
We derive a stochastic AKNS hierarchy using geometrical methods. The integrability is shown via a stochastic zero curvature relation associated with a stochastic isospectral problem. We expose some of the stochastic integrable partial differential equations which extend the stochastic KdV equation discovered by M. Wadati in 1983 for all the AKNS flows. We also show how to find stochastic solitons from the stochastic evolution of the scattering data of the stochastic IST. We finally expose som...
Modified diffusion with memory for cyclone track fluctuations
Energy Technology Data Exchange (ETDEWEB)
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.
Dando, Robin; Roper, Stephen D
2009-12-15
Isolated taste cells, taste buds and strips of lingual tissue from taste papillae secrete ATP upon taste stimulation. Taste bud receptor (Type II) cells have been identified as the source of ATP secretion. Based on studies on isolated taste buds and single taste cells, we have postulated that ATP secreted from receptor cells via pannexin 1 hemichannels acts within the taste bud to excite neighbouring presynaptic (Type III) cells. This hypothesis, however, remains to be tested in intact tissues. In this report we used confocal Ca(2+) imaging and lingual slices containing intact taste buds to test the hypothesis of purinergic signalling between taste cells in a more integral preparation. Incubating lingual slices with apyrase reversibly blocked cell-to-cell communication between receptor cells and presynaptic cells, consistent with ATP being the transmitter. Inhibiting pannexin 1 gap junction hemichannels with CO(2)-saturated buffer or probenecid significantly reduced cell-cell signalling between receptor cells and presynaptic cells. In contrast, anandamide, a blocker of connexin gap junction channels, had no effect of cell-to-cell communication in taste buds. These findings are consistent with the model for peripheral signal processing via ATP and pannexin 1 hemichannels in mammalian taste buds.
Stochasticity or the fatal `imperfection' of cloning
Indian Academy of Sciences (India)
Reiner A Veitia
2005-02-01
The concept of clone is analysed with the aim of exploring the limits to which a phenotype can be said to be determined geneticaly. First of all, mutations that result from the replication, topological manipulation or lesion of DNA introduce a source of heritable variation in an otherwise identical genetic background. But more important, stochastic effects in many biological processes may superimpose a phenotypic variation which is not encoded in the genome. The source of stochasticity ranges from the random selection of alleles or whole chromosomes to be expressed in small cell populations, to fluctuations in processes such as gene expression, due to limiting amounts of the players involved. The picture emerging is that the term clone is a statistical over-simplification representing a series of individuals having essentially the same genome but capable of exhibiting wide phenotypic variation. Finally, to what extent fluctuations in biological processes, usually thought of as noise, are in fact signal is also discussed.
Moawia Alghalith
2012-01-01
We present new stochastic differential equations, that are more general and simpler than the existing Ito-based stochastic differential equations. As an example, we apply our approach to the investment (portfolio) model.
Stochastic processes - quantum physics
Energy Technology Data Exchange (ETDEWEB)
Streit, L. (Bielefeld Univ. (Germany, F.R.))
1984-01-01
The author presents an elementary introduction to stochastic processes. He starts from simple quantum mechanics and considers problems in probability, finally presenting quantum dynamics in terms of stochastic processes.
Modeling stochasticity in biochemical reaction networks
Constantino, P. H.; Vlysidis, M.; Smadbeck, P.; Kaznessis, Y. N.
2016-03-01
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.
Stochastic Power Grid Analysis Considering Process Variations
Ghanta, Praveen; Panda, Rajendran; Wang, Janet
2011-01-01
In this paper, we investigate the impact of interconnect and device process variations on voltage fluctuations in power grids. We consider random variations in the power grid's electrical parameters as spatial stochastic processes and propose a new and efficient method to compute the stochastic voltage response of the power grid. Our approach provides an explicit analytical representation of the stochastic voltage response using orthogonal polynomials in a Hilbert space. The approach has been implemented in a prototype software called OPERA (Orthogonal Polynomial Expansions for Response Analysis). Use of OPERA on industrial power grids demonstrated speed-ups of up to two orders of magnitude. The results also show a significant variation of about $\\pm$ 35% in the nominal voltage drops at various nodes of the power grids and demonstrate the need for variation-aware power grid analysis.
Stochastic phenomena in a fiber Raman amplifier
Kalashnikov, Vladimir; Ania-Castanón, Juan Diego; Jacobsen, Gunnar; Popov, Sergei
2016-01-01
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 outpu...
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
Analysis of a novel stochastic SIRS epidemic model with two different saturated incidence rates
Chang, Zhengbo; Meng, Xinzhu; Lu, Xiao
2017-04-01
This paper presents a stochastic SIRS epidemic model with two different nonlinear incidence rates and double epidemic asymmetrical hypothesis, and we devote to develop a mathematical method to obtain the threshold of the stochastic epidemic model. We firstly investigate the boundness and extinction of the stochastic system. Furthermore, we use Ito's formula, the comparison theorem and some new inequalities techniques of stochastic differential systems to discuss persistence in mean of two diseases on three cases. The results indicate that stochastic fluctuations can suppress the disease outbreak. Finally, numerical simulations about different noise disturbance coefficients are carried out to illustrate the obtained theoretical results.
Semiclassical Aspects of Quantum Mechanics by Classical Fluctuations
De Martino, S; Illuminati, F; Martino, Salvatore De; Siena, Silvio De
1998-01-01
Building on a model recently proposed by F. Calogero, we postulate the existence of a coherent, long--range universal tremor affecting any stable and confined classical dynamical system. Deriving the characteristic fluctuative unit of action for each classical interaction, we obtain in all cases its numerical coincidence with the Planck action constant. We therefore suggest that quantum corrections to classical dynamics can be simulated by suitable classical stochastic fluctuations.
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...
Going with the flow: enhancing stochastic switching rates in multi-gyre systems
Heckman, Christoffer R; Schwartz, Ira B
2014-01-01
A control strategy is employed that modifies the stochastic escape times from one basin of attraction to another in a model of a double-gyre flow. The system studied captures the behavior of a large class of fluid flows that circulate and have multiple almost invariant sets. In the presence of noise, a particle in one gyre may randomly switch to an adjacent gyre due to a rare large fluctuation. We show that large fluctuation theory may be applied for controlling autonomous agents in a stochastic environment, in fact leveraging the stochastic- ity to the advantage of switching between regions of interest and concluding that patterns may be broken or held over time as the result of noise. We demonstrate that a controller can effectively manipulate the probability of a large fluctuation, thereby modifying escape times exponentially; this demonstrates the potential of optimal control strategies that work in combination with the endemic stochastic environment. To demonstrate this, stochastic simulations and numeri...
Fluctuation-Enhanced Sensing of Bacterium Odors
Chang, Hung-Chih; King, Maria D; Kwan, Chiman
2009-01-01
The goal of this paper is to explore the possibility to detect and identify bacteria by sensing their odor via fluctuation-enhanced sensing with commercial Taguchi sensors. The fluctuations of the electrical resistance during exposure to different bacterial odors, Escherichia coli and anthrax-surrogate Bacillus subtilis, have been measured and analyzed. In the present study, the simplest method, the measurement and analysis of power density spectra was used. The sensors were run in the normal heated and the sampling-and-hold working modes, respectively. The results indicate that Taguchi sensors used in these fluctuation-enhanced modes are effective tools of bacterium detection and identification even when they are utilizing only the power density spectrum of the stochastic sensor signal.
Stochastic single-molecule dynamics of synaptic membrane protein domains
Kahraman, Osman; Haselwandter, Christoph A
2016-01-01
Motivated by single-molecule experiments on synaptic membrane protein domains, we use a stochastic lattice model to study protein reaction and diffusion processes in crowded membranes. We find that the stochastic reaction-diffusion dynamics of synaptic proteins provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the single-molecule trajectories observed for synaptic proteins, and spatially inhomogeneous protein lifetimes at the cell membrane. Our results suggest that central aspects of the single-molecule and collective dynamics observed for membrane protein domains can be understood in terms of stochastic reaction-diffusion processes at the cell membrane.
Random-order fractional bistable system and its stochastic resonance
Gao, Shilong; Zhang, Li; Liu, Hui; Kan, Bixia
2017-01-01
In this paper, the diffusion motion of Brownian particles in a viscous liquid suffering from stochastic fluctuations of the external environment is modeled as a random-order fractional bistable equation, and as a typical nonlinear dynamic behavior, the stochastic resonance phenomena in this system are investigated. At first, the derivation process of the random-order fractional bistable system is given. In particular, the random-power-law memory is deeply discussed to obtain the physical interpretation of the random-order fractional derivative. Secondly, the stochastic resonance evoked by random-order and external periodic force is mainly studied by numerical simulation. In particular, the frequency shifting phenomena of the periodical output are observed in SR induced by the excitation of the random order. Finally, the stochastic resonance of the system under the double stochastic excitations of the random order and the internal color noise is also investigated.
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.
A NOTE ON THE STOCHASTIC ROOTS OF STOCHASTIC MATRICES
Institute of Scientific and Technical Information of China (English)
Qi-Ming HE; Eldon GUNN
2003-01-01
In this paper, we study the stochastic root matrices of stochastic matrices. All stochastic roots of 2×2 stochastic matrices are found explicitly. A method based on characteristic polynomial of matrix is developed to find all real root matrices that are functions of the original 3×3 matrix, including all possible (function) stochastic root matrices. In addition, we comment on some numerical methods for computing stochastic root matrices of stochastic matrices.
Stochastic Lie group integrators
Malham, Simon J A
2007-01-01
We present Lie group integrators for nonlinear stochastic differential equations with non-commutative vector fields whose solution evolves on a smooth finite dimensional manifold. Given a Lie group action that generates transport along the manifold, we pull back the stochastic flow on the manifold to the Lie group via the action, and subsequently pull back the flow to the corresponding Lie algebra via the exponential map. We construct an approximation to the stochastic flow in the Lie algebra via closed operations and then push back to the Lie group and then to the manifold, thus ensuring our approximation lies in the manifold. We call such schemes stochastic Munthe-Kaas methods after their deterministic counterparts. We also present stochastic Lie group integration schemes based on Castell--Gaines methods. These involve using an underlying ordinary differential integrator to approximate the flow generated by a truncated stochastic exponential Lie series. They become stochastic Lie group integrator schemes if...
Directory of Open Access Journals (Sweden)
Chia Yin Lee
2011-12-01
Full Text Available Chikungunya virus (CHIKV is an alphavirus responsible for numerous epidemics throughout Africa and Asia, causing infectious arthritis and reportedly linked with fatal infections in newborns and elderly. Previous studies in animal models indicate that humoral immunity can protect against CHIKV infection, but despite the potential efficacy of B-cell-driven intervention strategies, there are no virus-specific vaccines or therapies currently available. In addition, CHIKV has been reported to elicit long-lasting virus-specific IgM in humans, and to establish long-term persistence in non-human primates, suggesting that the virus might evade immune defenses to establish chronic infections in man. However, the mechanisms of immune evasion potentially employed by CHIKV remain uncharacterized. We previously described two human monoclonal antibodies that potently neutralize CHIKV infection. In the current report, we have characterized CHIKV mutants that escape antibody-dependent neutralization to identify the CHIKV E2 domain B and fusion loop "groove" as the primary determinants of CHIKV interaction with these antibodies. Furthermore, for the first time, we have also demonstrated direct CHIKV cell-to-cell transmission, as a mechanism that involves the E2 domain A and that is associated with viral resistance to antibody-dependent neutralization. Identification of CHIKV sub-domains that are associated with human protective immunity, will pave the way for the development of CHIKV-specific sub-domain vaccination strategies. Moreover, the clear demonstration of CHIKV cell-to-cell transmission and its possible role in the establishment of CHIKV persistence, will also inform the development of future anti-viral interventions. These data shed new light on CHIKV-host interactions that will help to combat human CHIKV infection and inform future studies of CHIKV pathogenesis.
Eph/ephrin-B-mediated cell-to-cell interactions govern MTS20(+) thymic epithelial cell development.
Montero-Herradón, Sara; García-Ceca, Javier; Sánchez Del Collado, Beatriz; Alfaro, David; Zapata, Agustín G
2016-08-01
Thymus development is a complex process in which cell-to-cell interactions between thymocytes and thymic epithelial cells (TECs) are essential to allow a proper maturation of both thymic cell components. Although signals that control thymocyte development are well known, mechanisms governing TEC maturation are poorly understood, especially those that regulate the maturation of immature TEC populations during early fetal thymus development. In this study, we show that EphB2-deficient, EphB2LacZ and EphB3-deficient fetal thymuses present a lower number of cells and delayed maturation of DN cell subsets compared to WT values. Moreover, deficits in the production of chemokines, known to be involved in the lymphoid seeding into the thymus, contribute in decreased proportions of intrathymic T cell progenitors (PIRA/B(+)) in the mutant thymuses from early stages of development. These features correlate with increased proportions of MTS20(+) cells but fewer MTS20(-) cells from E13.5 onward in the deficient thymuses, suggesting a delayed development of the first epithelial cells. In addition, in vitro the lack of thymocytes or the blockade of Eph/ephrin-B-mediated cell-to-cell interactions between either thymocytes-TECs or TECs-TECs in E13.5 fetal thymic lobes coursed with increased proportions of MTS20(+) TECs. This confirms, for the first time, that the presence of CD45(+) cells, corresponding at these stages to DN1 and DN2 cells, and Eph/ephrin-B-mediated heterotypic or homotypic cell interactions between thymocytes and TECs, or between TECs and themselves, contribute to the early maturation of MTS20(+) TECs.
Optimal control of stochastic magnetization dynamics by spin current
Wang, Yong; Zhang, Fu-Chun
2013-05-01
Fluctuation-induced stochastic magnetization dynamics plays an important role in spintronics devices. Here we propose that it can be optimally controlled by spin currents to minimize or maximize the Freidlin-Wentzell action functional of the system hence to increase or decrease the probability of the large fluctuations. We apply this method to study the thermally activated magnetization switching problem and to demonstrate the merits of the optimal control strategy.
Directory of Open Access Journals (Sweden)
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.
Growth and decay of large fluctuations far from equilibrium
Indian Academy of Sciences (India)
Shrabani Sen; Syed Shahed Riaz; Deb Shankar Ray
2009-09-01
We have explored the weak noise limit of stochastic processes in nonlinear dissipative systems which admit of stable dynamical attractors in absence of noise. An interesting `detailed balance’ like condition in the steady state which is manifested in the time reversal symmetry between growth and decay of fluctuation far from equilibrium, similar to what is observed in thermally equilibrated systems, is demonstrated.
Mean, fluctuations and predictability in biological dispersal
Giometto, A.; Altermatt, F.; Carrara, F.; Rinaldo, A.
2013-12-01
Dispersal is a key ecological phenomenon, fundamental to the understanding of the dynamics of invasive species, spread of epidemics and range shifts due to climate or environmental change. Additionally, organisms' spread drives species distribution and affects their coexistence. Despite its relevance, replicated experimentation on biological dispersal is inconclusive to date and current assessments point at inherent limitations to predictability owing to large fluctuations even in the simplest ecological settings. In contrast, we show by replicated experimentation on the spread of the ciliate Tetrahymena sp. in linear landscapes, that information on local unconstrained movement and reproduction of individuals allows to predict reliably the existence and speed of traveling waves of invasion at the macroscopic scale. Furthermore, a theoretical approach introducing demographic stochasticity in the Fisher-Kolmogorov framework of reaction-diffusion processes is shown to capture both the mean and the observed fluctuations in range expansions between replicated invasions. Thus, the predictability of the phenomenon overcomes the inherent stochasticity. Notably, predictions on the spread of organisms are based on local, short-time and independent observations of the two processes affecting dispersal, namely individuals' movement and reproduction. Our results establish a causal link from the short-term individual level to the long-term, broad-scale population patterns and may be generalized to sort whether the variability observed in nature or in experimental ensembles might be accounted for by systematic differences between landscapes or by stochasticity affecting basic vital rates of the organisms involved.
Jordan-Brans-Dicke stochastic inflation
García-Bellido, J
1994-01-01
We study stochastic inflation in the presence of a dynamical gravitational constant. We describe the Arnowitt--Deser--Misner formalism for Jordan--Brans--Dicke theory of gravity with an inflaton field. The inflaton and dilaton scalar fields can be separated into coarse-grained background fields and quantum fluctuations. We compute the amplitude of the perturbations generated by those quantum fluctuations in JBD theory with an arbitrary potential for the inflaton field. The effect of the quantum fluctuations on the background fields is equivalent to a Brownian motion of the scalar fields, which can be described with the use of a Fokker--Planck diffusion equation. The probability to find a given value of the fields in the comoving frame can be written as a Gaussian distribution centered on their classical trajectory, with decreasing dispersion along both field directions. We also calculate the condition for the Universe to enter a self-regenerating inflationary phase. The probability distribution in the physica...
Fluctuating hydrodynamics of multi-species reactive mixtures
Energy Technology Data Exchange (ETDEWEB)
Bhattacharjee, Amit Kumar; Donev, Aleksandar [Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, New York 10012 (United States); Balakrishnan, Kaushik [Jet Propulsion Laboratory, 4800 Oak Grove Drive, Pasadena, California 91109 (United States); Garcia, Alejandro L. [Department of Physics and Astronomy, San Jose State University, 1 Washington Square, San Jose, California 95192 (United States); Bell, John B. [Computational Research Division, Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, California 94720 (United States)
2015-06-14
We formulate and study computationally the fluctuating compressible Navier-Stokes equations for reactive multi-species fluid mixtures. We contrast two different expressions for the covariance of the stochastic chemical production rate in the Langevin formulation of stochastic chemistry, and compare both of them to predictions of the chemical master equation for homogeneous well-mixed systems close to and far from thermodynamic equilibrium. We develop a numerical scheme for inhomogeneous reactive flows, based on our previous methods for non-reactive mixtures [Balakrishnan , Phys. Rev. E 89, 013017 (2014)]. We study the suppression of non-equilibrium long-ranged correlations of concentration fluctuations by chemical reactions, as well as the enhancement of pattern formation by spontaneous fluctuations. Good agreement with available theory demonstrates that the formulation is robust and a useful tool in the study of fluctuations in reactive multi-species fluids. At the same time, several problems with Langevin formulations of stochastic chemistry are identified, suggesting that future work should examine combining Langevin and master equation descriptions of hydrodynamic and chemical fluctuations.
Fundamentals of Stochastic Networks
Ibe, Oliver C
2011-01-01
An interdisciplinary approach to understanding queueing and graphical networks In today's era of interdisciplinary studies and research activities, network models are becoming increasingly important in various areas where they have not regularly been used. Combining techniques from stochastic processes and graph theory to analyze the behavior of networks, Fundamentals of Stochastic Networks provides an interdisciplinary approach by including practical applications of these stochastic networks in various fields of study, from engineering and operations management to communications and the physi
A Lagrangian fluctuation-dissipation relation for scalar turbulence
Drivas, Theodore D
2016-01-01
An exact relation is derived between the dissipation of scalar fluctuations and the variance of the scalar inputs (due to initial scalar values, scalar sources, and boundary fluxes) as those are sampled by stochastic Lagrangian trajectories. Previous work on the Kraichnan (1968) model of turbulent scalar advection has shown that anomalous scalar dissipation, non-vanishing in the limit of vanishing viscosity and diffusivity, is in that model due to Lagrangian spontaneous stochasticity, or non-determinism of the Lagrangian particle trajectories in the limit. We here extend this result to scalars advected by any incompressible velocity field. For fluid flows in domains without walls (e.g. periodic boxes) and for insulating/impermeable walls with zero scalar fluxes, we prove that anomalous scalar dissipation and spontaneous stochasticity are completely equivalent. For flows with imposed scalar values or non-vanishing scalar fluxes at the walls, spontaneous stochasticity still implies anomalous scalar dissipation ...
Single-molecule stochastic resonance
Hayashi, K; Manosas, M; Huguet, J M; Ritort, F; 10.1103/PhysRevX.2.031012
2012-01-01
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 noise. Here we carry out the first experimental study of SR in single DNA hairpins which exhibit cooperatively folding/unfolding transitions under the action of an applied oscillating mechanical force with optical tweezers. By varying the frequency of the force oscillation, we investigated the folding/unfolding kinetics of DNA hairpins in a periodically driven bistable free-energy potential. We measured 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 the signal-to-noise ratio (SNR) of the spectral density of measured fluctuations in molecular extension of the DNA hairpins is a good quantifier of the SR. The frequency dependence of the SNR exhibits a peak at a frequency value given by the resonance match...
Fluctuations and correlations in modulation instability
Solli, D. R.; Herink, G.; Jalali, B.; Ropers, C.
2012-07-01
Stochastically driven nonlinear processes are responsible for spontaneous pattern formation and instabilities in numerous natural and artificial systems, including well-known examples such as sand ripples, cloud formations, water waves, animal pigmentation and heart rhythms. Technologically, a type of such self-amplification drives free-electron lasers and optical supercontinuum sources whose radiation qualities, however, suffer from the stochastic origins. Through time-resolved observations, we identify intrinsic properties of these fluctuations that are hidden in ensemble measurements. We acquire single-shot spectra of modulation instability produced by laser pulses in glass fibre at megahertz real-time capture rates. The temporally confined nature of the gain physically limits the number of amplified modes, which form an antibunched arrangement as identified from a statistical analysis of the data. These dynamics provide an example of pattern competition and interaction in confined nonlinear systems.
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.
Low Mach Number Fluctuating Hydrodynamics of Diffusively Mixing Fluids
Donev, A; Sun, Y; Fai, T; Garcia, A L; Bell, J B
2012-01-01
We formulate low Mach number fluctuating hydrodynamic equations appropriate for modeling diffusive mixing in isothermal mixtures of fluids with different density and transport coefficients. These equations eliminate the fast isentropic fluctuations in pressure associated with the propagation of sound waves by replacing the equation of state with a local thermodynamic constraint. We demonstrate that the low Mach number model preserves the spatio-temporal spectrum of the slower diffusive fluctuations. We develop a strictly conservative finite-volume spatial discretization of the low Mach number fluctuating equations in both two and three dimensions. We construct several explicit Runge-Kutta temporal integrators that strictly maintain the equation of state constraint. The resulting spatio-temporal discretization is second-order accurate deterministically and maintains fluctuation-dissipation balance in the linearized stochastic equations. We apply our algorithms to model the development of giant concentration fl...
Time Evolution of the Dynamical Variables of a Stochastic System.
de la Pena, L.
1980-01-01
By using the method of moments, it is shown that several important and apparently unrelated theorems describing average properties of stochastic systems are in fact particular cases of a general law; this method is applied to generalize the virial theorem and the fluctuation-dissipation theorem to the time-dependent case. (Author/SK)
A stochastic boundary forcing for dissipative particle dynamics
Altenhoff, Adrian M.; Walther, Jens H.; Koumoutsakos, Petros
2007-07-01
The method of dissipative particle dynamics (DPD) is an effective, coarse grained model of the hydrodynamics of complex fluids. DPD simulations of wall-bounded flows are however often associated with spurious fluctuations of the fluid properties near the wall. We present a novel stochastic boundary forcing for DPD simulations of wall-bounded flows, based on the identification of fluctuations in simulations of the corresponding homogeneous system at equilibrium. The present method is shown to enforce accurately the no-slip boundary condition, while minimizing spurious fluctuations of material properties, in a number of benchmark problems.
Agbo, Solomon N.; Merdzhanova, Tsvetelina; Yu, Shicheng; Tempel, Hermann; Kungl, Hans; Eichel, Rüdiger-A.; Rau, Uwe; Astakhov, Oleksandr
2016-09-01
This work focuses on the potentials of monolithic integrated thin-film silicon solar cell and lithium ion cell in a simple cell-to-cell integration without any control electronics as a compact power solution for portable electronic devices. To demonstrate this we used triple-junction thin-film silicon solar cell connected directly to a lithium ion battery cell to charge the battery and in turn discharge the battery through the solar cell. Our results show that with appropriate voltage matching the solar cell provides efficient charging for lab-scale lithium ion storage cell. Despite the absence of any control electronics the discharge rate of the Li-ion cell through the non-illuminated solar cell can be much lower than the charging rate when the current voltage (IV) characteristics of the solar cell is matched properly to the charge-discharge characteristics of the battery. This indicates good sustainability of the ultimately simple integrated device. At the maximum power point, solar energy-to-battery charging efficiency of 8.5% which is nearly the conversion efficiency of the solar cell was obtained indicating potential for loss-free operation of the photovoltaic (PV)-battery integration. For the rest of the charging points, an average of 8.0% charging efficiency was obtained.
Puolakkainen, Mirja; Campbell, Lee Ann; Lin, Tsun-Mei; Richards, Theresa; Patton, Dorothy L; Kuo, Cho-Chou
2003-02-01
Chlamydia pneumoniae can infect arterial cells. It has been shown that coculture of human monocytes (U937) and endothelial cells promotes infection of C. pneumoniae in endothelial cells and that the enhancement was mediated by a soluble factor (insulin-like growth factor 2) secreted by monocytes. In this study, it is shown that coculture of monocytes with C. pneumoniae enhances infection of C. pneumoniae in arterial smooth-muscle cells 5.3-fold at a monocyte-to-smooth-muscle cell ratio of 5. However, unlike endothelial cells, no enhancement was observed if monocytes were placed in cell culture inserts or if conditioned medium from monocyte cultures was used, which suggests that cell-to-cell contact is critical. The addition of mannose 6-phosphate or octyl glucoside, a nonionic detergent containing a sugar group, to cocultures inhibited the enhancement. These findings suggest that the monocyte-smooth-muscle cell interaction may be mediated by mannose 6-phosphate receptors present on monocytes.
Directory of Open Access Journals (Sweden)
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.
Cell-to-Cell Transmission of Dipeptide Repeat Proteins Linked to C9orf72-ALS/FTD
Directory of Open Access Journals (Sweden)
Thomas Westergard
2016-10-01
Full Text Available Aberrant hexanucleotide repeat expansions in C9orf72 are the most common genetic change underlying amyotrophic lateral sclerosis (ALS and frontotemporal dementia (FTD. RNA transcripts containing these expansions undergo repeat-associated non-ATG translation (RAN-T to form five dipeptide repeat proteins (DPRs. DPRs are found as aggregates throughout the CNS of C9orf72-ALS/FTD patients, and some cause degeneration when expressed in vitro in neuronal cultures and in vivo in animal models. The spread of characteristic disease-related proteins drives the progression of pathology in many neurodegenerative diseases. While DPR toxic mechanisms continue to be investigated, the potential for DPRs to spread has yet to be determined. Using different experimental cell culture platforms, including spinal motor neurons derived from induced pluripotent stem cells from C9orf72-ALS patients, we found evidence for cell-to-cell spreading of DPRs via exosome-dependent and exosome-independent pathways, which may be relevant to disease.
Directory of Open Access Journals (Sweden)
Yi eXu
2012-12-01
Full Text Available Our previous work has demonstrated that the NSvc4 protein of Rice stripe virus (RSV functions as a cell-to-cell movement protein. However, the mechanisms whereby RSV traffics through plasmodesmata (PD are unknown. Here we provide evidence that the NSvc4 moves on the actin filament and endoplasmic reticulum (ER network, but not microtubules, to reach cell wall PD. Disruption of cytoskeleton using different inhibitors altered NSvc4 localization to PD, thus impeding RSV infection of Nicotiana benthamiana. Sequence analyses and deletion mutagenesis experiment revealed that the N-terminal 125 amino acids (AAs of the NSvc4 determine PD targeting and that a transmembrane domain spanning AAs 106 to 125 is critical for PD localization. We also found that the NSvc4 protein can localize to chloroplasts in infected cells. Analyses using deletion mutants revealed that the N-terminal 73 AAs are essential for chloroplast localization. Furthermore, expression of NSvc4 from a Potato virus X (PVX vector resulted in more severe disease symptoms than PVX alone in systemically infected N. benthamiana leaves. Expression of NSvc4 in Spodoptera frugiperda 9 (Sf-9 cells did not elicit tubule formation, but instead resulted in punctate foci at the plasma membrane. These findings shed new light on our understanding of the movement mechanisms whereby RSV infects host plants.
Directory of Open Access Journals (Sweden)
Jianzhong Hu
Full Text Available In the first few hours following Newcastle disease viral infection of human monocyte-derived dendritic cells, the induction of IFNB1 is extremely low and the secreted type I interferon response is below the limits of ELISA assay. However, many interferon-induced genes are activated at this time, for example DDX58 (RIGI, which in response to viral RNA induces IFNB1. We investigated whether the early induction of IFNBI in only a small percentage of infected cells leads to low level IFN secretion that then induces IFN-responsive genes in all cells. We developed an agent-based mathematical model to explore the IFNBI and DDX58 temporal dynamics. Simulations showed that a small number of early responder cells provide a mechanism for efficient and controlled activation of the DDX58-IFNBI positive feedback loop. The model predicted distributions of single cell responses that were confirmed by single cell mRNA measurements. The results suggest that large cell-to-cell variation plays an important role in the early innate immune response, and that the variability is essential for the efficient activation of the IFNB1 based feedback loop.
Spinner, Neil S.; Field, Christopher R.; Hammond, Mark H.; Williams, Bradley A.; Myers, Kristina M.; Lubrano, Adam L.; Rose-Pehrsson, Susan L.; Tuttle, Steven G.
2015-04-01
A 5-cubic meter decompression chamber was re-purposed as a fire test chamber to conduct failure and abuse experiments on lithium-ion batteries. Various modifications were performed to enable remote control and monitoring of chamber functions, along with collection of data from instrumentation during tests including high speed and infrared cameras, a Fourier transform infrared spectrometer, real-time gas analyzers, and compact reconfigurable input and output devices. Single- and multi-cell packages of LiCoO2 chemistry 18650 lithium-ion batteries were constructed and data was obtained and analyzed for abuse and failure tests. Surrogate 18650 cells were designed and fabricated for multi-cell packages that mimicked the thermal behavior of real cells without using any active components, enabling internal temperature monitoring of cells adjacent to the active cell undergoing failure. Heat propagation and video recordings before, during, and after energetic failure events revealed a high degree of heterogeneity; some batteries exhibited short burst of sparks while others experienced a longer, sustained flame during failure. Carbon monoxide, carbon dioxide, methane, dimethyl carbonate, and ethylene carbonate were detected via gas analysis, and the presence of these species was consistent throughout all failure events. These results highlight the inherent danger in large format lithium-ion battery packs with regards to cell-to-cell failure, and illustrate the need for effective safety features.
Stochastic longshore current dynamics
Restrepo, Juan M.; Venkataramani, Shankar
2016-12-01
We develop a stochastic parametrization, based on a 'simple' deterministic model for the dynamics of steady longshore currents, that produces ensembles that are statistically consistent with field observations of these currents. Unlike deterministic models, stochastic parameterization incorporates randomness and hence can only match the observations in a statistical sense. Unlike statistical emulators, in which the model is tuned to the statistical structure of the observation, stochastic parametrization are not directly tuned to match the statistics of the observations. Rather, stochastic parameterization combines deterministic, i.e physics based models with stochastic models for the "missing physics" to create hybrid models, that are stochastic, but yet can be used for making predictions, especially in the context of data assimilation. We introduce a novel measure of the utility of stochastic models of complex processes, that we call consistency of sensitivity. A model with poor consistency of sensitivity requires a great deal of tuning of parameters and has a very narrow range of realistic parameters leading to outcomes consistent with a reasonable spectrum of physical outcomes. We apply this metric to our stochastic parametrization and show that, the loss of certainty inherent in model due to its stochastic nature is offset by the model's resulting consistency of sensitivity. In particular, the stochastic model still retains the forward sensitivity of the deterministic model and hence respects important structural/physical constraints, yet has a broader range of parameters capable of producing outcomes consistent with the field data used in evaluating the model. This leads to an expanded range of model applicability. We show, in the context of data assimilation, the stochastic parametrization of longshore currents achieves good results in capturing the statistics of observation that were not used in tuning the model.
Macroscopic fluctuations theory of aerogel dynamics
Lefevere, Raphael; Zambotti, Lorenzo
2010-01-01
We consider extensive deterministic dynamics made of $N$ particles modeling aerogels under a macroscopic fluctuation theory description. By using a stochastic model describing those dynamics after a diffusive rescaling, we show that the functional giving the exponential decay in $N$ of the probability of observing a given energy and current profile is not strictly convex as a function of the current. This behaviour is caused by the fact that the energy current is carried by particles which may have arbitrary low speed with sufficiently large probability.
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.
A Stochastic Employment Problem
Wu, Teng
2013-01-01
The Stochastic Employment Problem(SEP) is a variation of the Stochastic Assignment Problem which analyzes the scenario that one assigns balls into boxes. Balls arrive sequentially with each one having a binary vector X = (X[subscript 1], X[subscript 2],...,X[subscript n]) attached, with the interpretation being that if X[subscript i] = 1 the ball…
Stochastic Convection Parameterizations
Teixeira, Joao; Reynolds, Carolyn; Suselj, Kay; Matheou, Georgios
2012-01-01
computational fluid dynamics, radiation, clouds, turbulence, convection, gravity waves, surface interaction, radiation interaction, cloud and aerosol microphysics, complexity (vegetation, biogeochemistry, radiation versus turbulence/convection stochastic approach, non-linearities, Monte Carlo, high resolutions, large-Eddy Simulations, cloud structure, plumes, saturation in tropics, forecasting, parameterizations, stochastic, radiation-clod interaction, hurricane forecasts
Verhoosel, C.V.; Gutiérrez, M.A.; Hulshoff, S.J.
2006-01-01
The field of fluid-structure interaction is combined with the field of stochastics to perform a stochastic flutter analysis. Various methods to directly incorporate the effects of uncertainties in the flutter analysis are investigated. The panel problem with a supersonic fluid flowing over it is con
Control of stochastic resonance in bistable systems by using periodic signals
Institute of Scientific and Technical Information of China (English)
Lin Min; Fang Li-Min; Zheng Yong-Jun
2009-01-01
According to the characteristic structure of double wells in bistable systems, this paper analyses stochastic fluctu-ations 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.
Stochastic volatility selected readings
Shephard, Neil
2005-01-01
Neil Shephard has brought together a set of classic and central papers that have contributed to our understanding of financial volatility. They cover stocks, bonds and currencies and range from 1973 up to 2001. Shephard, a leading researcher in the field, provides a substantial introduction in which he discusses all major issues involved. General Introduction N. Shephard. Part I: Model Building. 1. A Subordinated Stochastic Process Model with Finite Variance for Speculative Prices, (P. K. Clark). 2. Financial Returns Modelled by the Product of Two Stochastic Processes: A Study of Daily Sugar Prices, 1961-7, S. J. Taylor. 3. The Behavior of Random Variables with Nonstationary Variance and the Distribution of Security Prices, B. Rosenberg. 4. The Pricing of Options on Assets with Stochastic Volatilities, J. Hull and A. White. 5. The Dynamics of Exchange Rate Volatility: A Multivariate Latent Factor ARCH Model, F. X. Diebold and M. Nerlove. 6. Multivariate Stochastic Variance Models. 7. Stochastic Autoregressive...
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...
Hydrodynamics of charge fluctuations and balance functions
Ling, B; Stephanov, M
2013-01-01
We apply stochastic hydrodynamics to the study of charge density fluctuations in QCD matter undergoing Bjorken expansion. We find that the charge density correlations are given by a time integral over the history of the system, with the dominant contribution coming from the QCD crossover region where the change of susceptibility per entropy, chi T/s, is most significant. We study the rapidity and azimuthal angle dependence of the resulting charge balance function using a simple analytic model of heavy-ion collision evolution. Our results are in agreement with experimental measurements, indicating that hydrodynamic fluctuations contribute significantly to the measured charge correlations in high energy heavy-ion collisions. The sensitivity of the balance function to the value of the charge diffusion coefficient D allows us to estimate the typical value of this coefficient in the crossover region to be rather small, of the order of 1/(2pi T), characteristic of a strongly coupled plasma.
Fractality feature in oil price fluctuations
Momeni, M; Talebi, K
2008-01-01
The scaling properties of oil price fluctuations are described as a non-stationary stochastic process realized by a time series of finite length. An original model is used to extract the scaling exponent of the fluctuation functions within a non-stationary process formulation. It is shown that, when returns are measured over intervals less than 10 days, the Probability Density Functions (PDFs) exhibit self-similarity and monoscaling, in contrast to the multifractal behavior of the PDFs at macro-scales (typically larger than one month). We find that the time evolution of the distributions are well fitted by a Levy distribution law at micro-scales. The relevance of a Levy distribution is made plausible by a simple model of nonlinear transfer
Stochastic energy balancing in substation energy management
Directory of Open Access Journals (Sweden)
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.
Stochastic models of intracellular calcium signals
Energy Technology Data Exchange (ETDEWEB)
Rüdiger, Sten, E-mail: sten.ruediger@physik.hu-berlin.de
2014-01-10
Cellular signaling operates in a noisy environment shaped by low molecular concentrations and cellular heterogeneity. For calcium release through intracellular channels–one of the most important cellular signaling mechanisms–feedback by liberated calcium endows fluctuations with critical functions in signal generation and formation. In this review it is first described, under which general conditions the environment makes stochasticity relevant, and which conditions allow approximating or deterministic equations. This analysis provides a framework, in which one can deduce an efficient hybrid description combining stochastic and deterministic evolution laws. Within the hybrid approach, Markov chains model gating of channels, while the concentrations of calcium and calcium binding molecules (buffers) are described by reaction–diffusion equations. The article further focuses on the spatial representation of subcellular calcium domains related to intracellular calcium channels. It presents analysis for single channels and clusters of channels and reviews the effects of buffers on the calcium release. For clustered channels, we discuss the application and validity of coarse-graining as well as approaches based on continuous gating variables (Fokker–Planck and chemical Langevin equations). Comparison with recent experiments substantiates the stochastic and spatial approach, identifies minimal requirements for a realistic modeling, and facilitates an understanding of collective channel behavior. At the end of the review, implications of stochastic and local modeling for the generation and properties of cell-wide release and the integration of calcium dynamics into cellular signaling models are discussed.
Applications of Little's Law to stochastic models of gene expression
Elgart, Vlad; Kulkarni, Rahul V
2010-01-01
The intrinsic stochasticity of gene expression can lead to large variations in protein levels across a population of cells. To explain this variability, different sources of mRNA fluctuations ('Poisson' and 'Telegraph' processes) have been proposed in stochastic models of gene expression. Both Poisson and Telegraph scenario models explain experimental observations of noise in protein levels in terms of 'bursts' of protein expression. Correspondingly, there is considerable interest in establishing relations between burst and steady-state protein distributions for general stochastic models of gene expression. In this work, we address this issue by considering a mapping between stochastic models of gene expression and problems of interest in queueing theory. By applying a general theorem from queueing theory, Little's Law, we derive exact relations which connect burst and steady-state distribution means for models with arbitrary waiting-time distributions for arrival and degradation of mRNAs and proteins. The de...
Amplitude death of coupled hair bundles with stochastic channel noise
Kim, Kyung-Joong
2014-01-01
Hair cells conduct auditory transduction in vertebrates. In lower vertebrates such as frogs and turtles, due to the active mechanism in hair cells, hair bundles(stereocilia) can be spontaneously oscillating or quiescent. Recently, the amplitude death phenomenon has been proposed [K.-H. Ahn, J. R. Soc. Interface, {\\bf 10}, 20130525 (2013)] as a mechanism for auditory transduction in frog hair-cell bundles, where sudden cessation of the oscillations arises due to the coupling between non-identical hair bundles. The gating of the ion channel is intrinsically stochastic due to the stochastic nature of the configuration change of the channel. The strength of the noise due to the channel gating can be comparable to the thermal Brownian noise of hair bundles. Thus, we perform stochastic simulations of the elastically coupled hair bundles. In spite of stray noisy fluctuations due to its stochastic dynamics, our simulation shows the transition from collective oscillation to amplitude death as inter-bundle coupling str...
From cusps to cores: a stochastic model
El-Zant, Amr A.; Freundlich, Jonathan; Combes, Françoise
2016-09-01
The cold dark matter model of structure formation faces apparent problems on galactic scales. Several threads point to excessive halo concentration, including central densities that rise too steeply with decreasing radius. Yet, random fluctuations in the gaseous component can `heat' the centres of haloes, decreasing their densities. We present a theoretical model deriving this effect from first principles: stochastic variations in the gas density are converted into potential fluctuations that act on the dark matter; the associated force correlation function is calculated and the corresponding stochastic equation solved. Assuming a power-law spectrum of fluctuations with maximal and minimal cutoff scales, we derive the velocity dispersion imparted to the halo particles and the relevant relaxation time. We further perform numerical simulations, with fluctuations realized as a Gaussian random field, which confirm the formation of a core within a time-scale comparable to that derived analytically. Non-radial collective modes enhance the energy transport process that erases the cusp, though the parametrizations of the analytical model persist. In our model, the dominant contribution to the dynamical coupling driving the cusp-core transformation comes from the largest scale fluctuations. Yet, the efficiency of the transformation is independent of the value of the largest scale and depends weakly (linearly) on the power-law exponent; it effectively depends on two parameters: the gas mass fraction and the normalization of the power spectrum. This suggests that cusp-core transformations observed in hydrodynamic simulations of galaxy formation may be understood and parametrized in simple terms, the physical and numerical complexities of the various implementations notwithstanding.
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.
Aerodynamic Noise Prediction Using stochastic Turbulence Modeling
Directory of Open Access Journals (Sweden)
Arash Ahmadzadegan
2008-01-01
Full Text Available Amongst many approaches to determine the sound propagated from turbulent flows, hybrid methods, in which the turbulent noise source field is computed or modeled separately from the far field calculation, are frequently used. For basic estimation of sound propagation, less computationally intensive methods can be developed using stochastic models of the turbulent fluctuations (turbulent noise source field. A simple and easy to use stochastic model for generating turbulent velocity fluctuations called continuous filter white noise (CFWN model was used. This method based on the use of classical Langevian-equation to model the details of fluctuating field superimposed on averaged computed quantities. The resulting sound field due to the generated unsteady flow field was evaluated using Lighthill's acoustic analogy. Volume integral method used for evaluating the acoustic analogy. This formulation presents an advantage, as it confers the possibility to determine separately the contribution of the different integral terms and also integration regions to the radiated acoustic pressure. Our results validated by comparing the directivity and the overall sound pressure level (OSPL magnitudes with the available experimental results. Numerical results showed reasonable agreement with the experiments, both in maximum directivity and magnitude of the OSPL. This method presents a very suitable tool for the noise calculation of different engineering problems in early stages of the design process where rough estimates using cheaper methods are needed for different geometries.
The stochastic resonance mechanism in the Aerosol Index dynamics
De Martino, S; Mona, L
2002-01-01
We consider Aerosol Index (AI) time-series extracted from TOMS archive for an area covering Italy $(7-18^o E ; 36-47^o N)$. The missing of convergence in estimating the embedding dimension of the system and the inability of the Independent Component Analysis (ICA) in separating the fluctuations from deterministic component of the signals are evidences of an intrinsic link between the periodic behavior of AI and its fluctuations. We prove that these time series are well described by a stochastic dynamical model. Moreover, the principal peak in the power spectrum of these signals can be explained whereby a stochastic resonance, linking variable external factors, such as Sun-Earth radiation budget and local insolation, and fluctuations on smaller spatial and temporal scale due to internal weather and antrophic components.
Fluctuation relations for spintronics.
López, Rosa; Lim, Jong Soo; Sánchez, David
2012-06-15
Fluctuation relations are derived in systems where the spin degree of freedom and magnetic interactions play a crucial role. The form of the nonequilibrium fluctuation theorems relies on the assumption of a local balance condition. We demonstrate that in some cases the presence of magnetic interactions violates this condition. Nevertheless, fluctuation relations can be obtained from the microreversibility principle sustained only at equilibrium as a symmetry of the cumulant generating function for spin currents. We illustrate the spintronic fluctuation relations for a quantum dot coupled to partially polarized helical edge states.
Studies of Fluctuation Processes in Nuclear Collisions
Energy Technology Data Exchange (ETDEWEB)
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.
Generalized Stochastic Fokker-Planck Equations
Directory of Open Access Journals (Sweden)
Pierre-Henri Chavanis
2015-05-01
Full Text Available We consider a system of Brownian particles with long-range interactions. We go beyond the mean field approximation and take fluctuations into account. We introduce a new class of stochastic Fokker-Planck equations associated with a generalized thermodynamical formalism. Generalized thermodynamics arises in the case of complex systems experiencing small-scale constraints. In the limit of short-range interactions, we obtain a generalized class of stochastic Cahn-Hilliard equations. Our formalism has application for several systems of physical interest including self-gravitating Brownian particles, colloid particles at a fluid interface, superconductors of type II, nucleation, the chemotaxis of bacterial populations, and two-dimensional turbulence. We also introduce a new type of generalized entropy taking into account anomalous diffusion and exclusion or inclusion constraints.
Lee, Soo Young; Gertler, Frank B; Goldberg, Marcia B
2015-11-01
Shigella spp. are intracellular bacterial pathogens that cause diarrhoeal disease in humans. Shigella utilize the host actin cytoskeleton to enter cells, move through the cytoplasm of cells and pass into adjacent cells. Ena/VASP family proteins are highly conserved proteins that participate in actin-dependent dynamic cellular processes. We tested whether Ena/VASP family members VASP (vasodilator-stimulated phosphoprotein), Mena (mammalian-enabled) or EVL (Ena-VASP-like) contribute to Shigella flexneri spread through cell monolayers. VASP and EVL restricted cell-to-cell spread without significantly altering actin-based motility, whereas Mena had no effect on these processes. Phosphorylation of VASP on Ser153, Ser235 and Thr274 regulated its subcellular distribution and function. VASP derivatives that lack the Ena/VASP homology 1 (EVH1) domain or contain a phosphoablative mutation of Ser153 were defective in restricting S. flexneri spread, indicating that the EVH1 domain and phosphorylation on Ser153 are required for this process. The EVH1 domain and Ser153 of VASP were required for VASP localization to focal adhesions, and localization of VASP to focal adhesions and/or the leading edge was required for restriction of spread. The contribution of the EVH1 domain was from both the donor and the recipient cell, whereas the contribution of Ser153 phosphorylation was only from the donor cell. Thus, unlike host proteins characterized in Shigella pathogenesis that promote bacterial spread, VASP and EVL function to limit it. The ability of VASP and EVL to limit spread highlights the critical role of focal adhesion complexes and/or the leading edge in bacterial passage between cells.
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.
Energy Technology Data Exchange (ETDEWEB)
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.
Stochastic behavior of nanoscale dielectric wall buckling
Friedman, Lawrence H.; Levin, Igor; Cook, Robert F.
2016-01-01
The random buckling patterns of nanoscale dielectric walls are analyzed using a nonlinear multi-scale stochastic method that combines experimental measurements with simulations. The dielectric walls, approximately 200 nm tall and 20 nm wide, consist of compliant, low dielectric constant (low-k) fins capped with stiff, compressively stressed TiN lines that provide the driving force for buckling. The deflections of the buckled lines exhibit sinusoidal pseudoperiodicity with amplitude fluctuation and phase decorrelation arising from stochastic variations in wall geometry, properties, and stress state at length scales shorter than the characteristic deflection wavelength of about 1000 nm. The buckling patterns are analyzed and modeled at two length scales: a longer scale (up to 5000 nm) that treats randomness as a longer-scale measurable quantity, and a shorter-scale (down to 20 nm) that treats buckling as a deterministic phenomenon. Statistical simulation is used to join the two length scales. Through this approach, the buckling model is validated and material properties and stress states are inferred. In particular, the stress state of TiN lines in three different systems is determined, along with the elastic moduli of low-k fins and the amplitudes of the small-scale random fluctuations in wall properties—all in the as-processed state. The important case of stochastic effects giving rise to buckling in a deterministically sub-critical buckling state is demonstrated. The nonlinear multiscale stochastic analysis provides guidance for design of low-k structures with acceptable buckling behavior and serves as a template for how randomness that is common to nanoscale phenomena might be measured and analyzed in other contexts. PMID:27330220
Low Mach number fluctuating hydrodynamics for electrolytes
Péraud, Jean-Philippe; Nonaka, Andy; Chaudhri, Anuj; Bell, John B.; Donev, Aleksandar; Garcia, Alejandro L.
2016-11-01
We formulate and study computationally the low Mach number fluctuating hydrodynamic equations for electrolyte solutions. We are interested in studying transport in mixtures of charged species at the mesoscale, down to scales below the Debye length, where thermal fluctuations have a significant impact on the dynamics. Continuing our previous work on fluctuating hydrodynamics of multicomponent mixtures of incompressible isothermal miscible liquids [A. Donev et al., Phys. Fluids 27, 037103 (2015), 10.1063/1.4913571], we now include the effect of charged species using a quasielectrostatic approximation. Localized charges create an electric field, which in turn provides additional forcing in the mass and momentum equations. Our low Mach number formulation eliminates sound waves from the fully compressible formulation and leads to a more computationally efficient quasi-incompressible formulation. We demonstrate our ability to model saltwater (NaCl) solutions in both equilibrium and nonequilibrium settings. We show that our algorithm is second order in the deterministic setting and for length scales much greater than the Debye length gives results consistent with an electroneutral approximation. In the stochastic setting, our model captures the predicted dynamics of equilibrium and nonequilibrium fluctuations. We also identify and model an instability that appears when diffusive mixing occurs in the presence of an applied electric field.
Directory of Open Access Journals (Sweden)
Nicolas Richerioux
Full Text Available Marek's Disease Virus (MDV is an avian alpha-herpesvirus that only spreads from cell-to-cell in cell culture. While its cell-to-cell spread has been shown to be dependent on actin filament dynamics, the mechanisms regulating this spread remain largely unknown. Using a recombinant BAC20 virus expressing an EGFPVP22 tegument protein, we found that the actin cytoskeleton arrangements and cell-cell contacts differ in the center and periphery of MDV infection plaques, with cells in the latter areas showing stress fibers and rare cellular projections. Using specific inhibitors and activators, we determined that Rho-ROCK pathway, known to regulate stress fiber formation, and Rac-PAK, known to promote lamellipodia formation and destabilize stress fibers, had strong contrasting effects on MDV cell-to-cell spread in primary chicken embryo skin cells (CESCs. Inhibition of Rho and its ROCKs effectors led to reduced plaque sizes whereas inhibition of Rac or its group I-PAKs effectors had the adverse effect. Importantly, we observed that the shape of MDV plaques is related to the semi-ordered arrangement of the elongated cells, at the monolayer level in the vicinity of the plaques. Inhibition of Rho-ROCK signaling also resulted in a perturbation of the cell arrangement and a rounding of plaques. These opposing effects of Rho and Rac pathways in MDV cell-to-cell spread were validated for two parental MDV recombinant viruses with different ex vivo spread efficiencies. Finally, we demonstrated that Rho/Rac pathways have opposing effects on the accumulation of N-cadherin at cell-cell contact regions between CESCs, and defined these contacts as adherens junctions. Considering the importance of adherens junctions in HSV-1 cell-to-cell spread in some cell types, this result makes of adherens junctions maintenance one potential and attractive hypothesis to explain the Rho/Rac effects on MDV cell-to-cell spread. Our study provides the first evidence that MDV cell-to-cell
Kraenkel, R. A.; da Silva, D. J. Pamplona
2010-01-01
We consider the dynamics of a biological population described by the Fisher-Kolmogorov-Petrovskii-Piskunov (FKPP) equation in the case where the spatial domain consists of alternating favorable and adverse patches whose sizes are distributed randomly. For the one-dimensional case we define a stochastic analogue of the classical critical patch size. We address the issue of persistence of a population and we show that the minimum fraction of the length of favorable segments to the total length is always smaller in the stochastic case than in a periodic arrangement. In this sense, spatial stochasticity favors viability of a population.
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
Stochastic dynamic model of SARS spreading
Institute of Scientific and Technical Information of China (English)
SHI Yaolin
2003-01-01
Based upon the simulation of the stochastic process of infection, onset and spreading of each SARS patient, a system dynamic model of SRAS spreading is constructed. Data from Vietnam is taken as an example for Monte Carlo test. The preliminary results indicate that the time-dependent infection rate is the most important control factor for SARS spreading. The model can be applied to prediction of the course with fluctuations of the epidemics, if the previous history of the epidemics and the future infection rate under control measures are known.
Variable diffusion in stock market fluctuations
Hua, Jia-Chen; Chen, Lijian; Falcon, Liberty; McCauley, Joseph L.; Gunaratne, Gemunu H.
2015-02-01
We analyze intraday fluctuations in several stock indices to investigate the underlying stochastic processes using techniques appropriate for processes with nonstationary increments. The five most actively traded stocks each contains two time intervals during the day where the variance of increments can be fit by power law scaling in time. The fluctuations in return within these intervals follow asymptotic bi-exponential distributions. The autocorrelation function for increments vanishes rapidly, but decays slowly for absolute and squared increments. Based on these results, we propose an intraday stochastic model with linear variable diffusion coefficient as a lowest order approximation to the real dynamics of financial markets, and to test the effects of time averaging techniques typically used for financial time series analysis. We find that our model replicates major stylized facts associated with empirical financial time series. We also find that ensemble averaging techniques can be used to identify the underlying dynamics correctly, whereas time averages fail in this task. Our work indicates that ensemble average approaches will yield new insight into the study of financial markets' dynamics. Our proposed model also provides new insight into the modeling of financial markets dynamics in microscopic time scales.
Stochastic modeling and performance monitoring of wind farm power production
Milan, Patrick; Peinke, Joachim
2015-01-01
We present a new stochastic approach to describe and remodel the conversion process of a wind farm at a sampling frequency of 1Hz. When conditioning on various wind direction sectors, the dynamics of the conversion process appear as a fluctuating trajectory around an average IEC-like power curve, see section II. Our approach is to consider the wind farm as a dynamical system that can be described as a stochastic drift/diffusion model, where a drift coefficient describes the attraction towards the power curve and a diffusion coefficient quantifies additional turbulent fluctuations. These stochastic coefficients are inserted into a Langevin equation that, once properly adapted to our particular system, models a synthetic signal of power output for any given wind speed/direction signals, see section III. When combined with a pre-model for turbulent wind fluctuations, the stochastic approach models the power output of the wind farm at a sampling frequency of 1Hz using only ten-minute average values of wind speed ...
Stochastic differential equations and applications
Friedman, Avner
2006-01-01
This text develops the theory of systems of stochastic differential equations, and it presents applications in probability, partial differential equations, and stochastic control problems. Originally published in two volumes, it combines a book of basic theory and selected topics with a book of applications.The first part explores Markov processes and Brownian motion; the stochastic integral and stochastic differential equations; elliptic and parabolic partial differential equations and their relations to stochastic differential equations; the Cameron-Martin-Girsanov theorem; and asymptotic es
Fluctuations in the relativistic plasma and primordial magnetic fields
Energy Technology Data Exchange (ETDEWEB)
Lemoine, D. (Institut d' Astrophysique de Paris, CNRS, 98bis Bd Arago, F-75014 Paris (France) DAEC, Observatoire de Paris, Universite Paris VII, CNRS (UA173), F-92195 Meudon Cedex (France))
1995-03-15
The stochastic fluctuations of the electromagnetic field in a relativistic electron-positron plasma are studied. The correlation functions of the fluctuating four-current, electric and magnetic fields are computed to leading order using the Schwinger-Keldysh closed time path formulation of thermal field theory. As an application, we consider the scenario proposed by Tajima [ital et] [ital al]. for generating a primordial magnetic field from thermal fluctuations in the prerecombination plasma. We compute the level of magnetic fluctuations sustained by the pair plasma at or before the epoch of big bang nucleosynthesis and conclude that the early Universe was pervaded by a strong low-frequency, albeit small-scale, random magnetic field. The astrophysical implications are briefly discussed.
Motion of Euglena gracilis: Active fluctuations and velocity distribution
Romanczuk, P.; Romensky, M.; Scholz, D.; Lobaskin, V.; Schimansky-Geier, L.
2015-07-01
We study the velocity distribution of unicellular swimming algae Euglena gracilis using optical microscopy and active Brownian particle theory. To characterize a peculiar feature of the experimentally observed distribution at small velocities we use the concept of active fluctuations, which was recently proposed for the description of stochastically self-propelled particles [Romanczuk, P. and Schimansky-Geier, L., Phys. Rev. Lett. 106, 230601 (2011)]. In this concept, the fluctuating forces arise due to internal random performance of the propulsive motor. The fluctuating forces are directed in parallel to the heading direction, in which the propulsion acts. In the theory, we introduce the active motion via the depot model [Schweitzer, et al., Phys. Rev. Lett. 80(23), 5044 (1998)]. We demonstrate that the theoretical predictions based on the depot model with active fluctuations are consistent with the experimentally observed velocity distributions. In addition to the model with additive active noise, we obtain theoretical results for a constant propulsion with multiplicative noise.
Motion of Euglena Gracilis: Active Fluctuations and Velocity Distribution
Romanczuk, Pawel; Scholz, Dimitri; Lobaskin, Vladimir; Schimansky-Geier, Lutz
2015-01-01
We study the velocity distribution of unicellular swimming algae Euglena gracilis using optical microscopy and theory. To characterize a peculiar feature of the experimentally observed distribution at small velocities we use the concept of active fluctuations, which was recently proposed for the description of stochastically self-propelled particles [Romanczuk, P. and Schimansky-Geier, L., Phys. Rev. Lett. 106, 230601 (2011)]. In this concept, the fluctuating forces arise due to internal random performance of the propulsive motor. The fluctuating forces are directed in parallel to the heading direction, in which the propulsion acts. In the theory, we introduce the active motion via the depot model [Schweitzer et al., Phys. Rev. Lett. 80, 23, 5044 (1998)]. We demonstrate that the theoretical predictions based on the depot model with active fluctuations are consistent with the experimentally observed velocity distributions. In addition to the model with additive active noise, we obtain theoretical results for a...
Enhancement of Ambipolar Diffusion Rates through Field Fluctuations
Fatuzzo, M; Fatuzzo, Marco; Adams, Fred C.
2002-01-01
Previous treatments of ambipolar diffusion in star-forming molecular clouds do not consider the effects of fluctuations in the fluid fields about their mean values. This paper generalizes the ambipolar diffusion problem in molecular cloud layers to include such fluctuations. Because magnetic diffusion is a nonlinear process, fluctuations can lead to an enhancement of the ambipolar diffusion rate. In addition, the stochastic nature of the process makes the ambipolar diffusion time take on a distribution of different values. In this paper, we focus on the case of long wavelength fluctuations and find that the rate of ambipolar diffusion increases by a significant factor $\\Lambda \\sim 1 - 10$. The corresponding decrease in the magnetic diffusion time helps make ambipolar diffusion more consistent with observations.
Concentration fluctuations in gas releases by industrial accidents
DEFF Research Database (Denmark)
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...... is fluctuating with a log-normal distribution. The position of the instantaneous plume centreline 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 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...
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.
Stochastic modelling of turbulence
DEFF Research Database (Denmark)
Sørensen, Emil Hedevang Lohse
This thesis addresses stochastic modelling of turbulence with applications to wind energy in mind. The primary tool is ambit processes, a recently developed class of computationally tractable stochastic processes based on integration with respect to Lévy bases. The subject of ambit processes...... stochastic turbulence model based on ambit processes is proposed. It is shown how a prescribed isotropic covariance structure can be reproduced. Non-Gaussian turbulence models are obtained through non-Gaussian Lévy bases or through volatility modulation of Lévy bases. As opposed to spectral models operating...... is dissipated into heat due to the internal friction caused by viscosity. An existing stochastic model, also expressed in terms of ambit processes, is extended and shown to give a universal and parsimonious description of the turbulent energy dissipation. The volatility modulation, referred to above, has...
Stochastic calculus with infinitesimals
Herzberg, Frederik
2013-01-01
Stochastic analysis is not only a thriving area of pure mathematics with intriguing connections to partial differential equations and differential geometry. It also has numerous applications in the natural and social sciences (for instance in financial mathematics or theoretical quantum mechanics) and therefore appears in physics and economics curricula as well. However, existing approaches to stochastic analysis either presuppose various concepts from measure theory and functional analysis or lack full mathematical rigour. This short book proposes to solve the dilemma: By adopting E. Nelson's "radically elementary" theory of continuous-time stochastic processes, it is based on a demonstrably consistent use of infinitesimals and thus permits a radically simplified, yet perfectly rigorous approach to stochastic calculus and its fascinating applications, some of which (notably the Black-Scholes theory of option pricing and the Feynman path integral) are also discussed in the book.
Frédéric, Pierret
2014-01-01
The equations of celestial mechanics that govern the variation of the orbital elements are completely derived for stochastic perturbation which generalized the classic perturbation equations which are used since Gauss, starting from Newton's equation and it's solution. The six most understandable orbital element, the semi-major axis, the eccentricity, the inclination, the longitude of the ascending node, the pericenter angle and the mean motion are express in term of the angular momentum vector $\\textbf{H}$ per unit of mass and the energy $E$ per unit of mass. We differentiate those expressions using It\\^o's theory of differential equations due to the stochastic nature of the perturbing force. The result is applied to the two-body problem perturbed by a stochastic dust cloud and also perturbed by a stochastic dynamical oblateness of the central body.
Notes on the Stochastic Exponential and Logarithm
Larsson, Martin; Ruf, Johannes
2017-01-01
Stochastic exponentials are defined for semimartingales on stochastic intervals, and stochastic logarithms are defined for nonnegative semimartingales, up to the first time the semimartingale hits zero continuously. In the case of (nonnegative) local supermartingales, these two stochastic transformations are inverse to each other. The reciprocal of a stochastic exponential is again a stochastic exponential on a stochastic interval.
Geometric Stochastic Resonance
Ghosh, Pulak Kumar; Savel'ev, Sergey E; Nori, Franco
2015-01-01
A Brownian particle moving across a porous membrane subject to an oscillating force exhibits stochastic resonance with properties which strongly depend on the geometry of the confining cavities on the two sides of the membrane. Such a manifestation of stochastic resonance requires neither energetic nor entropic barriers, and can thus be regarded as a purely geometric effect. The magnitude of this effect is sensitive to the geometry of both the cavities and the pores, thus leading to distinctive optimal synchronization conditions.
Continuous information flow fluctuations
Rosinberg, Martin Luc; Horowitz, Jordan M.
2016-10-01
Information plays a pivotal role in the thermodynamics of nonequilibrium processes with feedback. However, much remains to be learned about the nature of information fluctuations in small-scale devices and their relation with fluctuations in other thermodynamics quantities, like heat and work. Here we derive a series of fluctuation theorems for information flow and partial entropy production in a Brownian particle model of feedback cooling and extend them to arbitrary driven diffusion processes. We then analyze the long-time behavior of the feedback-cooling model in detail. Our results provide insights into the structure and origin of large deviations of information and thermodynamic quantities in autonomous Maxwell's demons.
Hadronic Correlations and Fluctuations
Energy Technology Data Exchange (ETDEWEB)
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.
Pérez-Espigares, Carlos; Redig, Frank; Giardinà, Cristian
2015-08-01
For non-equilibrium systems of interacting particles and for interacting diffusions in d-dimensions, a novel fluctuation relation is derived. The theorem establishes a quantitative relation between the probabilities of observing two current values in different spatial directions. The result is a consequence of spatial symmetries of the microscopic dynamics, generalizing in this way the Gallavotti-Cohen fluctuation theorem related to the time-reversal symmetry. This new perspective opens up the possibility of direct experimental measurements of fluctuation relations of vectorial observables.
Adaptive mesh refinement for stochastic reaction-diffusion processes
Bayati, Basil; Chatelain, Philippe; Koumoutsakos, Petros
2011-01-01
We present an algorithm for adaptive mesh refinement applied to mesoscopic stochastic simulations of spatially evolving reaction-diffusion processes. The transition rates for the diffusion process are derived on adaptive, locally refined structured meshes. Convergence of the diffusion process is presented and the fluctuations of the stochastic process are verified. Furthermore, a refinement criterion is proposed for the evolution of the adaptive mesh. The method is validated in simulations of reaction-diffusion processes as described by the Fisher-Kolmogorov and Gray-Scott equations.
Stochastic hard-sphere dynamics for hydrodynamics of nonideal fluids.
Donev, Aleksandar; Alder, Berni J; Garcia, Alejandro L
2008-08-15
A novel stochastic fluid model is proposed with a nonideal structure factor consistent with compressibility, and adjustable transport coefficients. This stochastic hard-sphere dynamics (SHSD) algorithm is a modification of the direct simulation Monte Carlo algorithm and has several computational advantages over event-driven hard-sphere molecular dynamics. Surprisingly, SHSD results in an equation of state and a pair correlation function identical to that of a deterministic Hamiltonian system of penetrable spheres interacting with linear core pair potentials. The fluctuating hydrodynamic behavior of the SHSD fluid is verified for the Brownian motion of a nanoparticle suspended in a compressible solvent.
Charge fluctuations for particles on a surface exposed to plasma
Sheridan, T E
2011-01-01
We develop a stochastic model for the charge fluctuations on a microscopic dust particle resting on a surface exposed to plasma. We find in steady state that the fluctuations are normally distributed with a standard deviation that is proportional to $CT_{e})^{1/2}$, where $C$ is the particle-surface capacitance and $T_{e}$ is the plasma electron temperature. The time for an initially uncharged ensemble of particles to reach the steady state distribution is directly proportional to $CT_{e}$.
Shocks, Rarefaction Waves, and Current Fluctuations for Anharmonic Chains
Mendl, Christian B.; Spohn, Herbert
2016-10-01
The nonequilibrium dynamics of anharmonic chains is studied by imposing an initial domain-wall state, in which the two half lattices are prepared in equilibrium with distinct parameters. We analyse the Riemann problem for the corresponding Euler equations and, in specific cases, compare with molecular dynamics. Additionally, the fluctuations of time-integrated currents are investigated. In analogy with the KPZ equation, their typical fluctuations should be of size t^{1/3} and have a Tracy-Widom GUE distributed amplitude. The proper extension to anharmonic chains is explained and tested through molecular dynamics. Our results are calibrated against the stochastic LeRoux lattice gas.
Messenger RNA Fluctuations and Regulatory RNAs Shape the Dynamics of Negative Feedback Loop
Martínez, María Rodríguez; Tlusty, Tsvi; Pilpel, Yitzhak; Furman, Itay; 10.1103/PhysRevE.81.031924
2010-01-01
Single cell experiments of simple regulatory networks can markedly differ from cell population experiments. Such differences arise from stochastic events in individual cells that are averaged out in cell populations. For instance, while individual cells may show sustained oscillations in the concentrations of some proteins, such oscillations may appear damped in the population average. In this paper we investigate the role of RNA stochastic fluctuations as a leading force to produce a sustained excitatory behavior at the single cell level. Opposed to some previous models, we build a fully stochastic model of a negative feedback loop that explicitly takes into account the RNA stochastic dynamics. We find that messenger RNA random fluctuations can be amplified during translation and produce sustained pulses of protein expression. Motivated by the recent appreciation of the importance of non--coding regulatory RNAs in post--transcription regulation, we also consider the possibility that a regulatory RNA transcri...
Accuracy versus speed in fluctuation-enhanced sensing
Makra, P; Granqvist, C G; Kish, L B; Kwan, C
2011-01-01
Fluctuation-enhanced sensing comprises the analysis of the stochastic component of the sensor signal and the utilization of the microscopic dynamics of the interaction between the agent and the sensor. We study the relationship between the measurement time window and the statistical error of the measurement data in the simplest case, when the output is the mean-square value of the stochastic signal. This situation is relevant at any practical case when the time window is finite, for example, when a sampling of the output of a fluctuation-enhanced array takes place; or a single sensor's activation (temperature, etc) is stepped up; or a single sensor's output is monitored by sampling subsequently in different frequency windows. Our study provides a lower limit of the relative error versus data window size with different types of power density spectra: white noise, 1/f (flicker, pink) noise, and 1/f^2 (red) noise spectra.
Fluctuations of fragment observables
Gulminelli, F
2006-01-01
This contribution presents a review of our present theoretical as well as experimental knowledge of different fluctuation observables relevant to nuclear multifragmentation. The possible connection between the presence of a fluctuation peak and the occurrence of a phase transition or a critical phenomenon is critically analyzed. Many different phenomena can lead both to the creation and to the suppression of a fluctuation peak. In particular, the role of constraints due to conservation laws and to data sorting is shown to be essential. From the experimental point of view, a comparison of the available fragmentation data reveals that there is a good agreement between different data sets of basic fluctuation observables, if the fragmenting source is of comparable size. This compatibility suggests that the fragmentation process is largely independent of the reaction mechanism (central versus peripheral collisions, symmetric versus asymmetric systems, light ions versus heavy ion induced reactions). Configurationa...
Stochastic population growth in spatially heterogeneous environments.
Evans, Steven N; Ralph, Peter L; Schreiber, Sebastian J; Sen, Arnab
2013-02-01
stochastic growth rate, we derive an explicit expression for the stochastic growth rate for populations living in two patches, determine which choices of the dispersal matrix D produce the maximal stochastic growth rate for a freely dispersing population, derive an analytic approximation of the stochastic growth rate for dispersal limited populations, and use group theoretic techniques to approximate the stochastic growth rate for populations living in multi-scale landscapes (e.g. insects on plants in meadows on islands). Our results provide fundamental insights into "ideal free" movement in the face of uncertainty, the persistence of coupled sink populations, the evolution of dispersal rates, and the single large or several small (SLOSS) debate in conservation biology. For example, our analysis implies that even in the absence of density-dependent feedbacks, ideal-free dispersers occupy multiple patches in spatially heterogeneous environments provided environmental fluctuations are sufficiently strong and sufficiently weakly correlated across space. In contrast, for diffusively dispersing populations living in similar environments, intermediate dispersal rates maximize their stochastic growth rate.
Dynamical Analysis of a Parasite-Host Model within Fluctuating Environment
Directory of Open Access Journals (Sweden)
Kun Xu
2016-01-01
Full Text Available A parasite-host model within fluctuating environment is proposed. Firstly, the positivity and boundedness of solutions of the model within deterministic environment are discussed, and, then, the asymptotical stability and global stability of equilibria of deterministic model are investigated. Secondly, we show that the stochastic model has a unique global positive solution; furthermore, we show that the stochastic model has a stationary distribution under certain conditions. Finally, we give some numerical simulations to illustrate our analytical results.
Gaussian fluctuations of singleeigenvalues intime-dependent GUE
Schön, Victor
2013-01-01
This thesis investigates the fluctuations of the eigenvalues of the Gaussian Unitary Ensemble on the basis of numerical simulations performed in the programming environment MATLAB. As is well known: if a Wiener process is defined on the space of Hermitian matrices then the eigenvalues describe a stochastic process known as Dyson Brownian motion. Thus, given a realisation of Dyson Brownian motion, the aim of this thesis is to investigate the distribution of a certain random vector pertaining t...
Diffusion in fluctuating media: first passage time problem
Energy Technology Data Exchange (ETDEWEB)
Revelli, Jorge A.; Budde, Carlos E.; Wio, Horacio S
2002-12-30
We study the actual and important problem of Mean First Passage Time (MFPT) for diffusion in fluctuating media. We exploit van Kampen's technique of composite stochastic processes, obtaining analytical expressions for the MFPT for a general system, and focus on the two state case where the transitions between the states are modelled introducing both Markovian and non-Markovian processes. The comparison between the analytical and simulations results show an excellent agreement.
Institute of Scientific and Technical Information of China (English)
SUN Zhaogang; ZHANG Manfu
2005-01-01
The secreted alphaherpesvirus glycoprotein G (gG) works differently from other proteins. Analysis of the role of ILTV gG in virus attachment, penetration, direct cell-to-cell spread (CTCS) and the growth curve showed that gG or its antibody had no effect on ILTV attachment and penetration and that the gG antibody reduced the virus plaque size and the one-step growth curve on chicken embryo liver (CEL) cells, but gG did not affect the virus plaque size or the one-step growth curve on CEL cells. Laser scanning confocal microscopy (LSCM) detection showed that ILTV gG is located in the perinuclear region and the membrane of the CEL cells. These results suggested that ILTV gG might contribute to direct cell-to-cell transmission.
Directory of Open Access Journals (Sweden)
Arnaud Devie
2016-09-01
Full Text Available Vehicle-to-grid (V2G and grid-to-vehicle (G2V strategies are considered to help stabilize the electric grid but their true impact on battery degradation is still unknown. The intention of this study is to test the impact of such strategies on the degradation of commercial Li-ion batteries. This first part looks into the preliminary testing performed prior to the start of degradation studies to ensure that the selected cells are compatible. Both the thermodynamic and kinetic cell-to-cell variation within the selected batch and the diagnostic-ability of the cells were investigated. The cells were found to have low cell-to-cell variations and are thus consistent. Moreover, the emulation of the full cell from the half-cell data prepared from harvested electrodes was successful and the degradation forecast showed that the main degradation modes can be differentiated.
Fluctuations around mean walking behaviors in diluted pedestrian flows
Corbetta, Alessandro; Lee, Chung-min; Benzi, Roberto; Muntean, Adrian; Toschi, Federico
2017-03-01
Understanding and modeling the dynamics of pedestrian crowds can help with designing and increasing the safety of civil facilities. A key feature of a crowd is its intrinsic stochasticity, appearing even under very diluted conditions, due to the variability in individual behaviors. Individual stochasticity becomes even more important under densely crowded conditions, since it can be nonlinearly magnified and may lead to potentially dangerous collective behaviors. To understand quantitatively crowd stochasticity, we study the real-life dynamics of a large ensemble of pedestrians walking undisturbed, and we perform a statistical analysis of the fully resolved pedestrian trajectories obtained by a yearlong high-resolution measurement campaign. Our measurements have been carried out in a corridor of the Eindhoven University of Technology via a combination of Microsoft Kinect 3D range sensor and automatic head-tracking algorithms. The temporal homogeneity of our large database of trajectories allows us to robustly define and separate average walking behaviors from fluctuations parallel and orthogonal with respect to the average walking path. Fluctuations include rare events when individuals suddenly change their minds and invert their walking directions. Such tendency to invert direction has been poorly studied so far, even if it may have important implications on the functioning and safety of facilities. We propose a model for the dynamics of undisturbed pedestrians, based on stochastic differential equations, that provides a good agreement with our field observations, including the occurrence of rare events.
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
Energy Technology Data Exchange (ETDEWEB)
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
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 Gravity A Primer with Applications
Hu, B L
2003-01-01
Stochastic semiclassical gravity of the 90's is a theory naturally evolved from semiclassical gravity of the 70's and 80's. 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 spacetimes 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 centerpiece is the (stochastic) 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. The functional approach uses the Feynman-Vernon influence functional and the Schwinger-Keldysh close-time-path effective action methods which are convenient for computations. It also brings out the open systems concepts and the statistical ...
Critical Number of Fields in Stochastic Inflation
Vennin, Vincent; Assadullahi, Hooshyar; Firouzjahi, Hassan; Noorbala, Mahdiyar; Wands, David
2017-01-01
Stochastic effects in generic scenarios of inflation with multiple fields are investigated. First passage time techniques are employed to calculate the statistical moments of the number of inflationary e -folds, which give rise to all correlation functions of primordial curvature perturbations through the stochastic δ N formalism. The number of fields is a critical parameter. The probability of exploring arbitrarily large-field regions of the potential becomes nonvanishing when more than two fields are driving inflation. The mean number of e -folds can be infinite, depending on the number of fields; for plateau potentials, this occurs even with one field. In such cases, correlation functions of curvature perturbations are infinite. They can, however, be regularized if a reflecting (or absorbing) wall is added at large energy or field value. The results are found to be independent of the exact location of the wall and this procedure is, therefore, well defined for a wide range of cutoffs, above or below the Planck scale. Finally, we show that, contrary to single-field setups, multifield models can yield large stochastic corrections even at sub-Planckian energy, opening interesting prospects for probing quantum effects on cosmological fluctuations.
Fluctuations in tension during contraction of single muscle fibers.
Borejdo, J; Morales, M F
1977-12-01
We have searched for fluctuations in the steady-state tension developed by stimulated single muscle fibers. Such tension "noise" is expected to be present as a result of the statistical fluctuations in the number and/or state of myosin cross-bridges interacting with thin filament sites at any time. A sensitive electro-optical tension transducer capable of resolving the expected fluctuations in magnitude and frequency was constructed to search for the fluctuations. The noise was analyzed by computing the power spectra and amplitude of stochastic fluctuations in the photomultiplier counting rate, which was made proportional to muscle force. The optical system and electronic instrumentation together with the minicomputer software are described. Tensions were measured in single skinned glycerinated rabbit psoas muscle fibers in rigor and during contraction and relaxation. The results indicate the presence of fluctuations in contracting muscles and a complete absence of tension noise in eith rigor or relaxation. Also, a numerical method was developed to simulate the power spectra and amplitude of fluctuations, given the rate constants for association and dissociation of the cross-bridges and actin. The simulated power spectra and the frequency distributions observed experimentally are similar.
Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns.
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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.
Fermionic influence (action) on inflationary fluctuations
Boyanovsky, Daniel
2016-01-01
Motivated by apparent persistent large scale anomalies in the CMB we study the influence of fermionic degrees of freedom on the dynamics of inflaton fluctuations as a possible source of violations of (nearly) scale invariance on cosmological scales. We obtain the non-equilibrium effective action of an inflaton-like scalar field with Yukawa interactions ($Y_{D,M}$) to light \\emph{fermionic} degrees of freedom both for Dirac and Majorana fields in de Sitter space-time. The effective action leads to Langevin equations of motion for the fluctuations of the inflaton-like field, with self-energy corrections and a stochastic gaussian noise. We solve the Langevin equation in the super-Hubble limit implementing a dynamical renormalization group resummation. For a nearly massless inflaton its power spectrum of super Hubble fluctuations is \\emph{enhanced}, $\\mathcal{P}(k;\\eta) = (\\frac{H}{2\\pi})^2\\,e^{\\gamma_t[-k\\eta] }$ with $\\gamma_t[-k\\eta] = \\frac{1}{6\\pi^2} \\Big[\\sum_{i=1}^{N_D}{Y^2_{i,D}}+2\\sum_{j=1}^{N_M}{Y^2_{j,...
Quantum Spontaneous Stochasticity
Eyink, Gregory L
2015-01-01
The quantum wave-function of a massive particle with small initial uncertainties (consistent with the uncertainty relation) is believed to spread very slowly, so that the dynamics is deterministic. This assumes that the classical motions for given initial data are unique. In fluid turbulence non-uniqueness due to "roughness" of the advecting velocity field is known to lead to stochastic motion of classical particles. Vanishingly small random perturbations are magnified by Richardson diffusion in a "nearly rough" velocity field so that motion remains stochastic as the noise disappears, or classical spontaneous stochasticity, . Analogies between stochastic particle motion in turbulence and quantum evolution suggest that there should be quantum spontaneous stochasticity (QSS). We show this for 1D models of a particle in a repulsive potential that is "nearly rough" with $V(x) \\sim C|x|^{1+\\alpha}$ at distances $|x|\\gg \\ell$ , for some UV cut-off $\\ell$, and for initial Gaussian wave-packet centered at 0. We consi...
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Kiss Levente
2010-04-01
Full Text Available Abstract Background Bone marrow derived mesenchymal stem cells (MSCs are promising candidates for cell based therapies in myocardial infarction. However, the exact underlying cellular mechanisms are still not fully understood. Our aim was to explore the possible role of direct cell-to-cell interaction between ischemic H9c2 cardiomyoblasts and normal MSCs. Using an in vitro ischemia model of 150 minutes of oxygen glucose deprivation we investigated cell viability and cell interactions with confocal microscopy and flow cytometry. Results Our model revealed that adding normal MSCs to the ischemic cell population significantly decreased the ratio of dead H9c2 cells (H9c2 only: 0.85 ± 0.086 vs. H9c2+MSCs: 0.16 ± 0.035. This effect was dependent on direct cell-to-cell contact since co-cultivation with MSCs cultured in cell inserts did not exert the same beneficial effect (ratio of dead H9c2 cells: 0.90 ± 0.055. Confocal microscopy revealed that cardiomyoblasts and MSCs frequently formed 200-500 nm wide intercellular connections and cell fusion rarely occurred between these cells. Conclusion Based on these results we hypothesize that mesenchymal stem cells may reduce the number of dead cardiomyoblasts after ischemic damage via direct cell-to-cell interactions and intercellular tubular connections may play an important role in these processes.
Martínez, Carolina; Coll-Bonfill, Nuria; Aramburu, Jose; Pallás, Vicente; Aparicio, Frederic; Galipienso, Luis
2014-05-12
The movement protein (MP) of parietaria mottle virus (PMoV) is required for virus cell-to-cell movement. Bioinformatics analysis identified two hydrophilic non-contiguous regions (R1 and R2) rich in the basic amino acids lysine and arginine and with the predicted secondary structure of an α-helix. Different approaches were used to determine the implication of the R1 and R2 regions in RNA binding, plasmodesmata (PD) targeting and cell-to-cell movement. EMSA (Electrophoretic Mobility Shift Assay) showed that both regions have RNA-binding activity whereas that mutational analysis reported that either deletion of any of these regions, or loss of the basic amino acids, interfered with the viral intercellular movement. Subcellular localization studies showed that PMoV MP locates at PD. Mutants designed to impeded cell-to-cell movement failed to accumulate at PD indicating that basic residues in both R1 and R2 are critical for binding the MP at PD.
Kumari, Sindhu S; Gandhi, Jason; Mustehsan, Mohammed H; Eren, Semih; Varadaraj, Kulandaiappan
2013-11-01
Aquaporin 0 (AQP0) performs dual functions in the lens fiber cells, as a water pore and as a cell-to-cell adhesion molecule. Mutations in AQP0 cause severe lens cataract in both humans and mice. An arginine to cysteine missense mutation at amino acid 33 (R33C) produced congenital autosomal dominant cataract in a Chinese family for five generations. We re-created this mutation in wild type human AQP0 (WT-AQP0) cDNA by site-directed mutagenesis, and cloned and expressed the mutant AQP0 (AQP0-R33C) in heterologous expression systems. Mutant AQP0-R33C showed proper trafficking and membrane localization like WT-AQP0. Functional studies conducted in Xenopus oocytes showed no significant difference (P > 0.05) in water permeability between AQP0-R33C and WT-AQP0. However, the cell-to-cell adhesion property of AQP0-R33C was significantly reduced (P cataract suggest that the conserved positive charge of Extracellular Loop A may play an important role in bringing fiber cells closer. The proposed schematic models illustrate that cell-to-cell adhesion elicited by AQP0 is vital for lens transparency and homeostasis.
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Ghadah A Karasneh
Full Text Available Herpes simplex virus type-1 (HSV-1 is a common human pathogen that relies heavily on cell-to-cell spread for establishing a lifelong latent infection. Molecular aspects of HSV-1 entry into host cells have been well studied; however, the molecular details of the spread of the virus from cell-to-cell remain poorly understood. In the past, the role of heparan sulfate proteoglycans (HSPG during HSV-1 infection has focused solely on the role of HS chains as an attachment receptor for the virus, while the core protein has been assumed to perform a passive role of only carrying the HS chains. Likewise, very little is known about the involvement of any specific HSPGs in HSV-1 lifecycle. Here we demonstrate that a HSPG, syndecan-1, plays an important role in HSV-1 induced membrane fusion and cell-to-cell spread. Interestingly, the functions of syndecan-1 in fusion and spread are independent of the presence of HS on the core protein. Using a mutant CHO-K1 cell line that lacks all glycosaminoglycans (GAGs on its surface (CHO-745 we demonstrate that the core protein of syndecan-1 possesses the ability to modulate membrane fusion and viral spread. Altogether, we identify a new role for syndecan-1 in HSV-1 pathogenesis and demonstrate HS-independent functions of its core protein in viral spread.
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.
Electron density fluctuations accelerate the branching of streamer discharges in air
Luque, A
2011-01-01
Branching is an essential element of streamer discharge dynamics but today it is understood only qualitatively. The variability and irregularity observed in branched streamer trees suggest that stochastic terms are relevant for the description of streamer branching. We here consider electron density fluctuations due to the discrete particle number as a source of stochasticity in positive streamers in air at standard temperature and pressure. We derive a quantitative estimate for the branching distance that agrees within a factor of 2 with experimental values. As branching without noise would occur later, if at all, we conclude that stochastic particle noise is relevant for streamer branching in air at atmospheric pressure.
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.
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 ...
Algorithm Refinement for Stochastic Partial Differential Equations. I. Linear Diffusion
Alexander, Francis J.; Garcia, Alejandro L.; Tartakovsky, Daniel M.
2002-10-01
A hybrid particle/continuum algorithm is formulated for Fickian diffusion in the fluctuating hydrodynamic limit. The particles are taken as independent random walkers; the fluctuating diffusion equation is solved by finite differences with deterministic and white-noise fluxes. At the interface between the particle and continuum computations the coupling is by flux matching, giving exact mass conservation. This methodology is an extension of Adaptive Mesh and Algorithm Refinement to stochastic partial differential equations. Results from a variety of numerical experiments are presented for both steady and time-dependent scenarios. In all cases the mean and variance of density are captured correctly by the stochastic hybrid algorithm. For a nonstochastic version (i.e., using only deterministic continuum fluxes) the mean density is correct, but the variance is reduced except in particle regions away from the interface. Extensions of the methodology to fluid mechanics applications are discussed.
Algorithm refinement for stochastic partial differential equations I. linear diffusion
Alexander, F J; Tartakovsky, D M
2002-01-01
A hybrid particle/continuum algorithm is formulated for Fickian diffusion in the fluctuating hydrodynamic limit. The particles are taken as independent random walkers; the fluctuating diffusion equation is solved by finite differences with deterministic and white-noise fluxes. At the interface between the particle and continuum computations the coupling is by flux matching, giving exact mass conservation. This methodology is an extension of Adaptive Mesh and Algorithm Refinement to stochastic partial differential equations. Results from a variety of numerical experiments are presented for both steady and time-dependent scenarios. In all cases the mean and variance of density are captured correctly by the stochastic hybrid algorithm. For a nonstochastic version (i.e., using only deterministic continuum fluxes) the mean density is correct, but the variance is reduced except in particle regions away from the interface. Extensions of the methodology to fluid mechanics applications are discussed.
Fluorescence Correlation Spectroscopy and Nonlinear Stochastic Reaction-Diffusion
Del Razo, Mauricio J; Qian, Hong; Lin, Guang
2014-01-01
The currently existing theory of fluorescence correlation spectroscopy(FCS) is based on the linear fluctuation theory originally developed by Einstein, Onsager, Lax, and others as a phenomenological approach to equilibrium fluctuations in bulk solutions. For mesoscopic reaction-diffusion systems with nonlinear chemical reactions among a small number of molecules, a situation often encountered in single-cell biochemistry, it is expected that FCS time correlation functions of a reaction-diffusion system can deviate from the classic results of Elson and Magde. We first discuss this nonlinear effect for reaction systems without diffusion. For nonlinear stochastic reaction-diffusion systems here are no closed solutions; therefore, stochastic Monte-Carlo simulations are carried out. We show that the deviation is small for a simple bimolecular reaction; the most significant deviations occur when the number of molecules is small and of the same order. Our results show that current linear FCS theory could be adequate ...
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.
STOCHASTIC COOLING FOR BUNCHED BEAMS.
Energy Technology Data Exchange (ETDEWEB)
BLASKIEWICZ, M.
2005-05-16
Problems associated with bunched beam stochastic cooling are reviewed. A longitudinal stochastic cooling system for RHIC is under construction and has been partially commissioned. The state of the system and future plans are discussed.
Stochastic Electrochemical Kinetics
Beruski, O
2016-01-01
A model enabling the extension of the Stochastic Simulation Algorithm to electrochemical systems is proposed. The physical justifications and constraints for the derivation of a chemical master equation are provided and discussed. The electrochemical driving forces are included in the mathematical framework, and equations are provided for the associated electric responses. The implementation for potentiostatic and galvanostatic systems is presented, with results pointing out the stochastic nature of the algorithm. The electric responses presented are in line with the expected results from the theory, providing a new tool for the modeling of electrochemical kinetics.
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
Pierret, Frédéric
2016-02-01
We derived the equations of Celestial Mechanics governing the variation of the orbital elements under a stochastic perturbation, thereby generalizing the classical Gauss equations. Explicit formulas are given for the semimajor axis, the eccentricity, the inclination, the longitude of the ascending node, the pericenter angle, and the mean anomaly, which are expressed in term of the angular momentum vector H per unit of mass and the energy E per unit of mass. Together, these formulas are called the stochastic Gauss equations, and they are illustrated numerically on an example from satellite dynamics.
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
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.
Regular and stochastic behavior of Parkinsonian pathological tremor signals
Yulmetyev, R M; Panischev, O Y; Hänggi, P; Timashev, S F; Vstovsky, G V; Yulmetyev, Renat M.; Demin, Sergey A.; Panischev, Oleg Yu.; H\\"anggi, Peter; Timashev, Serge F.; Vstovsky, Grigoriy V.
2006-01-01
Regular and stochastic behavior in the time series of Parkinsonian pathological tremor velocity is studied on the basis of the statistical theory of discrete non-Markov stochastic processes and flicker-noise spectroscopy. We have developed a new method of analyzing and diagnosing Parkinson's disease (PD) by taking into consideration discreteness, fluctuations, long- and short-range correlations, regular and stochastic behavior, Markov and non-Markov effects and dynamic alternation of relaxation modes in the initial time signals. The spectrum of the statistical non-Markovity parameter reflects Markovity and non-Markovity in the initial time series of tremor. The relaxation and kinetic parameters used in the method allow us to estimate the relaxation scales of diverse scenarios of the time signals produced by the patient in various dynamic states. The local time behavior of the initial time correlation function and the first point of the non-Markovity parameter give detailed information about the variation of p...
Stochastically forced dislocation density distribution in plastic deformation
Chattopadhyay, Amit K
2016-01-01
The dynamical evolution of dislocations in plastically deformed metals is controlled by both deterministic factors arising out of applied loads and stochastic effects appearing due to fluctuations of internal stress. Such type of stochastic dislocation processes and the associated spatially inhomogeneous modes lead to randomness in the observed deformation structure. Previous studies have analyzed the role of randomness in such textural evolution but none of these models have considered the impact of a finite decay time (all previous models assumed instantaneous relaxation which is "unphysical") of the stochastic perturbations in the overall dynamics of the system. The present article bridges this knowledge gap by introducing a colored noise in the form of an Ornstein-Uhlenbeck noise in the analysis of a class of linear and nonlinear Wiener and Ornstein-Uhlenbeck processes that these structural dislocation dynamics could be mapped on to. Based on an analysis of the relevant Fokker-Planck model, our results sh...
Turning the resistive MHD into a stochastic field theory
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M. Materassi
2008-08-01
Full Text Available Classical systems stirred by random forces of given statistics may be described via a path integral formulation in which their degrees of freedom are stochastic variables themselves, undergoing a multiple-history probabilistic evolution. This framework seems to be easily applicable to resistive Magneto-Hydro-Dynamics (MHD. Indeed, MHD equations form a dynamic system of classical variables in which the terms representing the density, the pressure and the conductivity of the plasma are irregular functions of space and time when turbulence occurs. By treating those irregular terms as random stirring forces, it is possible to introduce a Stochastic Field Theory which should represent correctly the impulsive phenomena caused by the spece- and time-irregularity of plasma turbulence. This work is motivated by the recent observational evidences of the crucial role played by stochastic fluctuations in space plasmas.
Turning the resistive MHD into a stochastic field theory
Materassi, M.; Consolini, G.
2008-08-01
Classical systems stirred by random forces of given statistics may be described via a path integral formulation in which their degrees of freedom are stochastic variables themselves, undergoing a multiple-history probabilistic evolution. This framework seems to be easily applicable to resistive Magneto-Hydro-Dynamics (MHD). Indeed, MHD equations form a dynamic system of classical variables in which the terms representing the density, the pressure and the conductivity of the plasma are irregular functions of space and time when turbulence occurs. By treating those irregular terms as random stirring forces, it is possible to introduce a Stochastic Field Theory which should represent correctly the impulsive phenomena caused by the spece- and time-irregularity of plasma turbulence. This work is motivated by the recent observational evidences of the crucial role played by stochastic fluctuations in space plasmas.
Stochastic heart-rate model can reveal pathologic cardiac dynamics
Kuusela, Tom
2004-03-01
A simple one-dimensional Langevin-type stochastic difference equation can simulate the heart-rate fluctuations in a time scale from minutes to hours. The model consists of a deterministic nonlinear part and a stochastic part typical of Gaussian noise, and both parts can be directly determined from measured heart-rate data. Data from healthy subjects typically exhibit the deterministic part with two or more stable fixed points. Studies of 15 congestive heart-failure subjects reveal that the deterministic part of pathologic heart dynamics has no clear stable fixed points. Direct simulations of the stochastic model for normal and pathologic cases can produce statistical parameters similar to those of real subjects. Results directly indicate that pathologic situations simplify the heart-rate control system.
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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.
Stochastic integrals: a combinatorial approach
Rota, Gian-Carlo; Wallstrom, Timothy C.
1997-01-01
A combinatorial definition of multiple stochastic integrals is given in the setting of random measures. It is shown that some properties of such stochastic integrals, formerly known to hold in special cases, are instances of combinatorial identities on the lattice of partitions of a set. The notion of stochastic sequences of binomial type is introduced as a generalization of special polynomial sequences occuring in stochastic integration, such as Hermite, Poisson–Charlier an...
Hamiltonian mechanics of stochastic acceleration.
Burby, J W; Zhmoginov, A I; Qin, H
2013-11-08
We show how to find the physical Langevin equation describing the trajectories of particles undergoing collisionless stochastic acceleration. These stochastic differential equations retain not only one-, but two-particle statistics, and inherit the Hamiltonian nature of the underlying microscopic equations. This opens the door to using stochastic variational integrators to perform simulations of stochastic interactions such as Fermi acceleration. We illustrate the theory by applying it to two example problems.
Stochastic effects on biodiversity in cyclic coevolutionary dynamics
Reichenbach, Tobias; Frey, Erwin
2008-01-01
Finite-size fluctuations arising in the dynamics of competing populations may have dramatic influence on their fate. As an example, in this article, we investigate a model of three species which dominate each other in a cyclic manner. Although the deterministic approach predicts (neutrally) stable coexistence of all species, for any finite population size, the intrinsic stochasticity unavoidably causes the eventual extinction of two of them.
On generalized Gaussian free fields and stochastic homogenization
Gu, Yu; Mourrat, Jean-Christophe
2016-01-01
We study a generalization of the notion of Gaussian free field (GFF). Although the extension seems minor, we first show that a generalized GFF does not satisfy the spatial Markov property, unless it is a classical GFF. In stochastic homogenization, the scaling limit of the corrector is a possibly generalized GFF described in terms of an "effective fluctuation tensor" that we denote by $\\mathsf{Q}$. We prove an expansion of $\\mathsf{Q}$ in the regime of small ellipticity ratio. This expansion ...
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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
Stochastic integral equations without probability
Mikosch, T; Norvaisa, R
2000-01-01
A pathwise approach to stochastic integral equations is advocated. Linear extended Riemann-Stieltjes integral equations driven by certain stochastic processes are solved. Boundedness of the p-variation for some 0
stochastic process. Typical examples of such
Analysis of bilinear stochastic systems
Willsky, A. S.; Martin, D. N.; Marcus, S. I.
1975-01-01
Analysis of stochastic dynamical systems that involve multiplicative (bilinear) noise processes. After defining the systems of interest, consideration is given to the evolution of the moments of such systems, the question of stochastic stability, and estimation for bilinear stochastic systems. Both exact and approximate methods of analysis are introduced, and, in particular, the uses of Lie-theoretic concepts and harmonic analysis are discussed.
Stochastic Circumplanetary Dynamics of Rotating Non-Spherical Dust Particles
Makuch, Martin; Brilliantov, N. V.; Sremcevic, M.; Spahn, F.; Krivov, A. V.
2006-12-01
Influence of stochastically fluctuating radiation pressure on the dynamics of dust grains on circumplanetary orbits was studied. Stochasticity stems from the permanent change of the particle cross-section due to rotation of nonspherical grains, exposed to the solar radiation. We found that stochasticity depends on the characteristic angular velocity of particles which, according to our estimates, spins very fast on the time scale of the orbital motion. According to this we modelled the stochastic part of the radiation pressure by a Gaussian white noise. Gauss perturbation equations with the radiation pressure being a sum of the deterministic and stochastic component have been used. We observed monotonous increasing standard deviation of the orbital elements, that is, the diffusive-like behaviour of the ensemble, which results in a spatial spreading of initially confined set of particles. By linear approximation we obtained expression for the effective diffusion coefficients and estimate their dependence on the geometrical characteristics of particles and their spin. Teoretical results were compared with numerical simulations performed for the putative dust tori of Mars. Our theory agrees fairly well with simulations for the initial period of the system evolution. The agreement however deteriorates with increasing time where impact of the non-linear terms of the perturbation equations becomes important. Analysis shows that the theoretical results may estimate the low boundary of the time-dependent standard deviation of the orbital elements. In the case of dust ejected from Martian moon Deimos we observed a change of orbital elements up to 10% of their initial values during the first 1000 years of orbital evolution. Our results indicate that the stochastic modulation of the radiation pressure can play an important role in the circumplanetary dynamics of dust and may, together with further noise sources (shadow, planetary bowshock, charge fluctuations, etc
Where are the Dust Tori of Mars? - A Possible Role of Stochastic Effects
Makuch, M.; Brilliantov, N. V.; Spahn, F.; Krivov, A. V.
2005-08-01
Dust tori around Mars were predicted theoretically several decades ago, but still escape direct detection. On the base of our recent analytical and numerical studies we re-assess expected properties of the dust belts. In addition to deterministic models developed before we investigate the influence of stochastic effects on the dynamics, lifetimes of particles, and configuration of the dust tori. There exist various sources of stochasticity. For instance, we consider the influence of solar radiation on an ensemble of differently-shaped dust particles. Following the ergodic hypothesis, the dynamics of a single dust grain exposed to fluctuating radiation mimics the stochastic evolution of the whole ensemble. Further, we study the action of the planetary shadow on the dynamics of dust particles, a perturbation which turns out to be stochastic. Additional stochastic perturbations of deterministic dust trajectories are expected to be caused by different material properties of the dust grains, fluctuations of the solar wind, and the related magnetic field. As a result the fluctuating forces cause a diffusion of the dust configuration whose related fluxes can be estimated from our numerical experiments. This effect leads to a decrease of the expected optical depth of the tori, which is mainly determined by the strength of the stochastic force. We will provide estimates for the latter resulting in a diffusion coefficient. This will give new information about change of the configuration and lifetimes of the Martian dust-tori.
Pluralistic and stochastic gene regulation: examples, models and consistent theory.
Salas, Elisa N; Shu, Jiang; Cserhati, Matyas F; Weeks, Donald P; Ladunga, Istvan
2016-06-01
We present a theory of pluralistic and stochastic gene regulation. To bridge the gap between empirical studies and mathematical models, we integrate pre-existing observations with our meta-analyses of the ENCODE ChIP-Seq experiments. Earlier evidence includes fluctuations in levels, location, activity, and binding of transcription factors, variable DNA motifs, and bursts in gene expression. Stochastic regulation is also indicated by frequently subdued effects of knockout mutants of regulators, their evolutionary losses/gains and massive rewiring of regulatory sites. We report wide-spread pluralistic regulation in ≈800 000 tightly co-expressed pairs of diverse human genes. Typically, half of ≈50 observed regulators bind to both genes reproducibly, twice more than in independently expressed gene pairs. We also examine the largest set of co-expressed genes, which code for cytoplasmic ribosomal proteins. Numerous regulatory complexes are highly significant enriched in ribosomal genes compared to highly expressed non-ribosomal genes. We could not find any DNA-associated, strict sense master regulator. Despite major fluctuations in transcription factor binding, our machine learning model accurately predicted transcript levels using binding sites of 20+ regulators. Our pluralistic and stochastic theory is consistent with partially random binding patterns, redundancy, stochastic regulator binding, burst-like expression, degeneracy of binding motifs and massive regulatory rewiring during evolution.
Stochastic population oscillations in spatial predator-prey models
Energy Technology Data Exchange (ETDEWEB)
Taeuber, Uwe C, E-mail: tauber@vt.edu [Department of Physics, Virginia Tech, Blacksburg, VA 24061-0435 (United States)
2011-09-15
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.
2003-01-01
In this review, we systematically examine the principles and the practices of fluctuations such as the momentum and the charge fluctuations as applied to the heavy ion collisions. Main emphases are: (i) Fluctuations as signals of phase transition (ii) Relationship between correlation functions and fluctuations (iii) Qualitative difference between fluctuations in small systems and large systems. Whenever available, theoretical results are compared with data from RHIC and SPS.
Multistage quadratic stochastic programming
Lau, Karen K.; Womersley, Robert S.
2001-04-01
Quadratic stochastic programming (QSP) in which each subproblem is a convex piecewise quadratic program with stochastic data, is a natural extension of stochastic linear programming. This allows the use of quadratic or piecewise quadratic objective functions which are essential for controlling risk in financial and project planning. Two-stage QSP is a special case of extended linear-quadratic programming (ELQP). The recourse functions in QSP are piecewise quadratic convex and Lipschitz continuous. Moreover, they have Lipschitz gradients if each QP subproblem is strictly convex and differentiable. Using these properties, a generalized Newton algorithm exhibiting global and superlinear convergence has been proposed recently for the two stage case. We extend the generalized Newton algorithm to multistage QSP and show that it is globally and finitely convergent under suitable conditions. We present numerical results on randomly generated data and modified publicly available stochastic linear programming test sets. Efficiency schemes on different scenario tree structures are discussed. The large-scale deterministic equivalent of the multistage QSP is also generated and their accuracy compared.
Understanding Stochastic Subspace Identification
DEFF Research Database (Denmark)
Brincker, Rune; Andersen, Palle
2006-01-01
The data driven Stochastic Subspace Identification techniques is considered to be the most powerful class of the known identification techniques for natural input modal analysis in the time domain. However, the techniques involves several steps of "mysterious mathematics" that is difficult...
Stochastic Control - External Models
DEFF Research Database (Denmark)
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...
D.F. Schrager
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 m
Energy Technology Data Exchange (ETDEWEB)
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)
Indian Academy of Sciences (India)
C. S. Leung; J. Y. Wei; T. Harko; Z. Kovacs
2011-03-01
In this paper, we introduce a simplified model for explaining the observations of optical intra-day variability (IDV) of the BL Lac Objects. We assume that the source of the IDV are the stochastic oscillations of an accretion disk around a supermassive black hole. The stochastic fluctuations on the vertical direction of the accretion disk are described by using a Langevin type equation with a damping term and a random, white noise type force. Furthermore, preliminary numerical simulation results are presented, which are based on the numerical analysis of the Langevin stochastic differential equation.
Energy fluctuations in a biharmonically driven nonlinear system
Indian Academy of Sciences (India)
Navinder Singh; Sourabh Lahiri; A M Jayannavar
2010-03-01
We study the fluctuations of work done and dissipated heat of a Brownian particle in a symmetric double well system. The system is driven by two periodic input signals that rock the potential simultaneously. Confinement in one preferred well can be achieved by modulating the relative phase between the drives. We show that in the presence of pumping the stochastic resonance signal is enhanced when analysed in terms of the average work done on the system per cycle. This is in contrast with the case when pumping is achieved by applying an external static bias, which degrades resonance. We analyse the nature of work and heat fluctuations and show that the steady state fluctuation theorem holds in this system.
Tsunami Energy, Ocean-Bottom Pressure, and Hydrodynamic Force from Stochastic Bottom Displacement
Ramadan, Khaled T.; Omar, M. A.; Allam, Allam A.
2017-03-01
Tsunami generation and propagation due to a randomly fluctuating of submarine earthquake modeled by vertical time-dependent of a stochastic bottom displacement are investigated. The increase in oscillations and amplitude in the free surface elevation are controlled by the noise intensity parameter of the stochastic bottom displacement. Evolution of kinetic and potential energy of the resulting waves by the stochastic bottom displacement is examined. Exchange between potential and kinetic energy was achieved in the propagation process. The dynamic ocean-bottom pressure during tsunami generation is investigated. As the vertical displacement of the stochastic bottom increases, the peak amplitude of the ocean-bottom pressure increases through the dynamic effect. Time series of the maximum tsunami wave amplitude, kinetic and potential energy, wave and ocean-bottom pressure gauges and the hydrodynamic force caused by the stochastic source model under the effect of the water depth of the ocean are investigated.
Stochastic model for aerodynamic force dynamics on wind turbine blades in unsteady wind inflow
Luhur, Muhammad Ramzan; Kühn, Martin; Wächter, Matthias
2015-01-01
The paper presents a stochastic approach to estimate the aerodynamic forces with local dynamics on wind turbine blades in unsteady wind inflow. This is done by integrating a stochastic model of lift and drag dynamics for an airfoil into the aerodynamic simulation software AeroDyn. The model is added as an alternative to the static table lookup approach in blade element momentum (BEM) wake model used by AeroDyn. The stochastic forces are obtained for a rotor blade element using full field turbulence simulated wind data input and compared with the classical BEM and dynamic stall models for identical conditions. The comparison shows that the stochastic model generates additional extended dynamic response in terms of local force fluctuations. Further, the comparison of statistics between the classical BEM, dynamic stall and stochastic models' results in terms of their increment probability density functions gives consistent results.
Binary Fingerprints at Fluctuation-Enhanced Sensing
Chang, Hung-Chih; King, Maria D; Kwan, Chiman
2009-01-01
We developed a simple way to generate binary patterns based on spectral slopes in different frequency ranges at fluctuation-enhanced sensing. Such patterns can be considered as binary "fingerprints" of odors. The method has experimentally been demonstrated with a commercial semiconducting metal oxide (Taguchi) sensor exposed to bacterial odors (Escherichia coli and Anthrax-surrogate Bacillus subtilis) and processing their stochastic signals. With a single Taguchi sensor, the situations of empty chamber, tryptic soy agar (TSA) medium, or TSA with bacteria could be distinguished with 100% reproducibility. The bacterium numbers were in the range of 25 thousands to 1 million. To illustrate the relevance for ultra-low power consumption, we show that this new type of signal processing and pattern recognition task can be implemented by a simple analog circuitry and a few logic gates with total power consumption in the microWatts range.
Fluctuation and dissipation in de Sitter space
Fischler, Willy; Pedraza, Juan F; Tangarife, Walter
2014-01-01
In this paper we study some thermal properties of quantum field theories in de Sitter space by means of holographic techniques. We focus on the static patch of de Sitter and assume that the quantum fields are in the standard Bunch-Davies vacuum. More specifically, we follow the stochastic motion of a massive charged particle due to its interaction with Hawking radiation. The process is described in terms of the theory of Brownian motion in inhomogeneous media and its associated Langevin dynamics. At late times, we find that the particle undergoes a regime of slow diffusion and never reaches the horizon, in stark contrast to the usual random walk behavior at finite temperature. Nevertheless, the fluctuation-dissipation theorem is found to hold at all times.
Multiplane 3D superresolution optical fluctuation imaging
Geissbuehler, Stefan; Godinat, Aurélien; Bocchio, Noelia L; Dubikovskaya, Elena A; Lasser, Theo; Leutenegger, Marcel
2013-01-01
By switching fluorophores on and off in either a deterministic or a stochastic manner, superresolution microscopy has enabled the imaging of biological structures at resolutions well beyond the diffraction limit. Superresolution optical fluctuation imaging (SOFI) provides an elegant way of overcoming the diffraction limit in all three spatial dimensions by computing higher-order cumulants of image sequences of blinking fluorophores acquired with a conventional widefield microscope. So far, three-dimensional (3D) SOFI has only been demonstrated by sequential imaging of multiple depth positions. Here we introduce a versatile imaging scheme which allows for the simultaneous acquisition of multiple focal planes. Using 3D cross-cumulants, we show that the depth sampling can be increased. Consequently, the simultaneous acquisition of multiple focal planes reduces the acquisition time and hence the photo-bleaching of fluorescent markers. We demonstrate multiplane 3D SOFI by imaging the mitochondria network in fixed ...
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.
Fluctuations in type IV pilus retraction
Linden, M; Jonsson, A B; Wallin, M; Linden, Martin; Johansson, Emil; Jonsson, Ann-Beth; Wallin, Mats
2005-01-01
The type IV pilus retraction motor is found in many important bacterial pathogens. It is the strongest known linear motor protein and is required for bacterial infectivity. We characterize the dynamics of type IV pilus retraction in terms of a stochastic chemical reaction model. We find that a two state model can describe the experimental force velocity relation and qualitative dependence of ATP concentration. The results indicate that the dynamics is limited by an ATP-dependent step at low load and a force-dependent step at high load, and that at least one step is effectively irreversible in the measured range of forces. The irreversible nature of the sub-step(s) lead to interesting predictions for future experiments: We find different parameterizations with mathematically identical force velocity relations but different fluctuations (diffusion constant). We also find a longer elementary step compared to an earlier analysis, which agrees better with known facts about the structure of the pilus filament and e...
Diagnostics for fluctuation measurements
Donne, A. J. H.
2000-01-01
Transport of particles and heat in magnetic confinement devices is largely attributed to the presence of microscopic instabilities. To better understand the physical mechanisms underlying plasma transport processes it is necessary to diagnose the fluctuations in the various quantities along with the
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…
Nonequilibrium mesoscopic conductance fluctuations
Ludwig, T.; Blanter, Ya. M.; Mirlin, A. D.
2004-12-01
We investigate the amplitude of mesoscopic fluctuations of the differential conductance of a metallic wire at arbitrary bias voltage V . For noninteracting electrons, the variance ⟨δg2⟩ increases with V . The asymptotic large- V behavior is ⟨δg2⟩˜V/Vc (where eVc=D/L2 is the Thouless energy), in agreement with the earlier prediction by Larkin and Khmelnitskii. We find, however, that this asymptotics has a very small numerical prefactor and sets in at very large V/Vc only, which strongly complicates its experimental observation. This high-voltage behavior is preceded by a crossover regime, V/Vc≲30 , where the conductance variance increases by a factor ˜3 as compared to its value in the regime of universal conductance fluctuations (i.e., at V→0 ). We further analyze the effect of dephasing due to the electron-electron scattering on ⟨δg2⟩ at high voltages. With the Coulomb interaction taken into account, the amplitude of conductance fluctuations becomes a nonmonotonic function of V . Specifically, ⟨δg2⟩ drops as 1/V for voltages V≫gVc , where g is the dimensionless conductance. In this regime, the conductance fluctuations are dominated by quantum-coherent regions of the wire adjacent to the reservoirs.
Wei, Katy; Moinat, Maxim; Maarleveld, Timo R; Bruggeman, Frank J
2014-07-29
Signal transduction by prokaryotes almost exclusively relies on two-component systems for sensing and responding to (extracellular) signals. Here, we use stochastic models of two-component systems to better understand the impact of stochasticity on the fidelity and robustness of signal transmission, the outcome of autoregulatory gene expression and the influence of cell growth and division. We report that two-component systems are remarkably robust against copy number fluctuations of the signalling proteins they are composed of, which enhances signal transmission fidelity. Furthermore, we find that due to stochasticity these systems can get locked in an active state for extended time periods when (initially high) signal levels drop to zero. This behaviour can contribute to a bet-hedging adaptation strategy, aiding survival in fluctuating environments. Additionally, autoregulatory gene expression can cause two-component systems to become bistable at realistic parameter values. As a result, two sub-populations of cells can co-exist-active and inactive cells, which contributes to fitness in unpredictable environments. Bistability proved robust with respect to cell growth and division, and is tunable by the growth rate. In conclusion, our results indicate how single cells can cope with the inevitable stochasticity occurring in the activity of their two-component systems. They are robust to disadvantageous fluctuations that scramble signal transduction and they exploit beneficial stochasticity that generates fitness-enhancing heterogeneity across an isogenic population of cells.
Testing the Propagating Fluctuations Model with a Long, Global Accretion Disk Simulation
Hogg, J Drew
2015-01-01
The broad-band variability of many accreting systems displays characteristic structure; log-normal flux distributions, RMS-flux relations, and long inter-band lags. These characteristics are usually interpreted as inward propagating fluctuations in an accretion disk driven by stochasticity of the angular momentum transport mechanism. We present the first analysis of propagating fluctuations in a long-duration, high-resolution, global three-dimensional magnetohydrodynamic (MHD) simulation of a geometrically-thin ($h/r\\approx0.1$) accretion disk around a black hole. While the dynamical-timescale turbulent fluctuations in the Maxwell stresses are too rapid to drive radially-coherent fluctuations in the accretion rate, we find that the low-frequency quasi-periodic dynamo action introduces low-frequency fluctuations in the Maxwell stresses which then drive the propagating fluctuations. Examining both the mass accretion rate and emission proxies, we recover log-normality, linear RMS-flux relations, and radial coher...
Terrestrial Gravity Fluctuations
Directory of Open Access Journals (Sweden)
Jan Harms
2015-12-01
Full Text Available Different forms of fluctuations of the terrestrial gravity field are observed by gravity experiments. For example, atmospheric pressure fluctuations generate a gravity-noise foreground in measurements with super-conducting gravimeters. Gravity changes caused by high-magnitude earthquakes have been detected with the satellite gravity experiment GRACE, and we expect high-frequency terrestrial gravity fluctuations produced by ambient seismic fields to limit the sensitivity of ground-based gravitational-wave (GW detectors. Accordingly, terrestrial gravity fluctuations are considered noise and signal depending on the experiment. Here, we will focus on ground-based gravimetry. This field is rapidly progressing through the development of GW detectors. The technology is pushed to its current limits in the advanced generation of the LIGO and Virgo detectors, targeting gravity strain sensitivities better than 10^–23 Hz^–1/2 above a few tens of a Hz. Alternative designs for GW detectors evolving from traditional gravity gradiometers such as torsion bars, atom interferometers, and superconducting gradiometers are currently being developed to extend the detection band to frequencies below 1 Hz. The goal of this article is to provide the analytical framework to describe terrestrial gravity perturbations in these experiments. Models of terrestrial gravity perturbations related to seismic fields, atmospheric disturbances, and vibrating, rotating or moving objects, are derived and analyzed. The models are then used to evaluate passive and active gravity noise mitigation strategies in GW detectors, or alternatively, to describe their potential use in geophysics. The article reviews the current state of the field, and also presents new analyses especially with respect to the impact of seismic scattering on gravity perturbations, active gravity noise cancellation, and time-domain models of gravity perturbations from atmospheric and seismic point sources. Our
Terrestrial Gravity Fluctuations.
Harms, Jan
2015-01-01
Different forms of fluctuations of the terrestrial gravity field are observed by gravity experiments. For example, atmospheric pressure fluctuations generate a gravity-noise foreground in measurements with super-conducting gravimeters. Gravity changes caused by high-magnitude earthquakes have been detected with the satellite gravity experiment GRACE, and we expect high-frequency terrestrial gravity fluctuations produced by ambient seismic fields to limit the sensitivity of ground-based gravitational-wave (GW) detectors. Accordingly, terrestrial gravity fluctuations are considered noise and signal depending on the experiment. Here, we will focus on ground-based gravimetry. This field is rapidly progressing through the development of GW detectors. The technology is pushed to its current limits in the advanced generation of the LIGO and Virgo detectors, targeting gravity strain sensitivities better than 10(-23) Hz(-1/2) above a few tens of a Hz. Alternative designs for GW detectors evolving from traditional gravity gradiometers such as torsion bars, atom interferometers, and superconducting gradiometers are currently being developed to extend the detection band to frequencies below 1 Hz. The goal of this article is to provide the analytical framework to describe terrestrial gravity perturbations in these experiments. Models of terrestrial gravity perturbations related to seismic fields, atmospheric disturbances, and vibrating, rotating or moving objects, are derived and analyzed. The models are then used to evaluate passive and active gravity noise mitigation strategies in GW detectors, or alternatively, to describe their potential use in geophysics. The article reviews the current state of the field, and also presents new analyses especially with respect to the impact of seismic scattering on gravity perturbations, active gravity noise cancellation, and time-domain models of gravity perturbations from atmospheric and seismic point sources. Our understanding of
Superfluid phase transition with activated velocity fluctuations: Renormalization group approach.
Dančo, Michal; Hnatič, Michal; Komarova, Marina V; Lučivjanský, Tomáš; Nalimov, Mikhail Yu
2016-01-01
A quantum field model that incorporates Bose-condensed systems near their phase transition into a superfluid phase and velocity fluctuations is proposed. The stochastic Navier-Stokes equation is used for a generation of the velocity fluctuations. As such this model generalizes model F of critical dynamics. The field-theoretic action is derived using the Martin-Siggia-Rose formalism and path integral approach. The regime of equilibrium fluctuations is analyzed within the perturbative renormalization group method. The double (ε,δ)-expansion scheme is employed, where ε is a deviation from space dimension 4 and δ describes scaling of velocity fluctuations. The renormalization procedure is performed to the leading order. The main corollary gained from the analysis of the thermal equilibrium regime suggests that one-loop calculations of the presented models are not sufficient to make a definite conclusion about the stability of fixed points. We also show that critical exponents are drastically changed as a result of the turbulent background and critical fluctuations are in fact destroyed by the developed turbulence fluctuations. The scaling exponent of effective viscosity is calculated and agrees with expected value 4/3.
Concentration fluctuations in gas releases by industrial accidents. Final report
Energy Technology Data Exchange (ETDEWEB)
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 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...
Limits for Stochastic Reaction Networks
DEFF Research Database (Denmark)
Cappelletti, Daniele
at a certain time are stochastically modelled by means of a continuous-time Markov chain. Our work concerns primarily stochastic reaction systems, and their asymptotic properties. In Paper I, we consider a reaction system with intermediate species, i.e. species that are produced and fast degraded along a path...... of the stochastic reaction systems. Specically, we build a theory for stochastic reaction systems that is parallel to the deciency zero theory for deterministic systems, which dates back to the 70s. A deciency theory for stochastic reaction systems was missing, and few results connecting deciency and stochastic....... Such species, in the deterministic modelling regime, assume always the same value at any positive steady state. In the stochastic setting, we prove that, if the initial condition is a point in the basin of attraction of a positive steady state of the corresponding deterministic model and tends to innity...
Numerical methods for the stochastic Landau-Lifshitz Navier-Stokes equations.
Bell, John B; Garcia, Alejandro L; Williams, Sarah A
2007-07-01
The Landau-Lifshitz Navier-Stokes (LLNS) equations incorporate thermal fluctuations into macroscopic hydrodynamics by using stochastic fluxes. This paper examines explicit Eulerian discretizations of the full LLNS equations. Several computational fluid dynamics approaches are considered (including MacCormack's two-step Lax-Wendroff scheme and the piecewise parabolic method) and are found to give good results for the variance of momentum fluctuations. However, neither of these schemes accurately reproduces the fluctuations in energy or density. We introduce a conservative centered scheme with a third-order Runge-Kutta temporal integrator that does accurately produce fluctuations in density, energy, and momentum. A variety of numerical tests, including the random walk of a standing shock wave, are considered and results from the stochastic LLNS solver are compared with theory, when available, and with molecular simulations using a direct simulation Monte Carlo algorithm.
Dynamics of an electric dipole moment in a stochastic electric field.
Band, Y B
2013-08-01
The mean-field dynamics of an electric dipole moment in a deterministic and a fluctuating electric field is solved to obtain the average over fluctuations of the dipole moment and the angular momentum as a function of time for a Gaussian white-noise stochastic electric field. 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 stochastic magnetic field with Gaussian white noise in all three components. The components of the average electric dipole moment and the average angular momentum perpendicular to the deterministic electric-field direction oscillate with time but decay to zero, and their variance grows with time.
Fluctuating hyperfine interactions: an updated computational implementation
Zacate, M. O.; Evenson, W. E.
2015-04-01
The stochastic hyperfine interactions modeling library (SHIML) is a set of routines written in the C programming language designed to assist in the analysis of stochastic models of hyperfine interactions. The routines read a text-file description of the model, set up the Blume matrix, upon which the evolution operator of the quantum mechanical system depends, and calculate the eigenvalues and eigenvectors of the Blume matrix, from which theoretical spectra of experimental techniques can be calculated. The original version of SHIML constructs Blume matrices applicable for methods that measure hyperfine interactions with only a single nuclear spin state. In this paper, we report an extension of the library to provide support for methods such as Mössbauer spectroscopy and nuclear resonant scattering of synchrotron radiation, which are sensitive to interactions with two nuclear spin states. Examples will be presented that illustrate the use of this extension of SHIML to generate Mössbauer spectra for polycrystalline samples under a number of fluctuating hyperfine field models.
Fluctuating hyperfine interactions: an updated computational implementation
Energy Technology Data Exchange (ETDEWEB)
Zacate, M. O., E-mail: zacatem1@nku.edu [Northern Kentucky University, Department of Physics and Geology (United States); Evenson, W. E. [Utah Valley University, Department of Physics (United States)
2015-04-15
The stochastic hyperfine interactions modeling library (SHIML) is a set of routines written in the C programming language designed to assist in the analysis of stochastic models of hyperfine interactions. The routines read a text-file description of the model, set up the Blume matrix, upon which the evolution operator of the quantum mechanical system depends, and calculate the eigenvalues and eigenvectors of the Blume matrix, from which theoretical spectra of experimental techniques can be calculated. The original version of SHIML constructs Blume matrices applicable for methods that measure hyperfine interactions with only a single nuclear spin state. In this paper, we report an extension of the library to provide support for methods such as Mössbauer spectroscopy and nuclear resonant scattering of synchrotron radiation, which are sensitive to interactions with two nuclear spin states. Examples will be presented that illustrate the use of this extension of SHIML to generate Mössbauer spectra for polycrystalline samples under a number of fluctuating hyperfine field models.
Balint, Richard; Richardson, Stephen M; Cartmell, Sarah H
2015-10-01
Numerous scientific studies and clinical trials are carried out each year exploring the use of mesenchymal stromal cells in regenerative medicine and tissue engineering. However, the effective and reliable expansion of this very important cell type remains a challenge. In this study the importance of cell-to-cell contact during expansion has been explored on the proliferation and differentiation potential of the produced cells. Cells were cultured up to passage 5 under conditions where cell-to-cell contact was either probable (40-70% confluence; see supporting information, Protocol A) or where it was unlikely (10-50% confluence; see supporting information, Protocol B). The effect of the two different conditions on expansion efficiency; proliferation rate and tri-lineage differentiation potential was assessed. Differences in immunophenotype, cell size and senescence were also investigated. Protocol B cultures expanded twice as fast as those cultured with Protocol A. In passage 5 experiments low confluence expanded cells displayed a 10% higher overall proliferation rate, and produced 23% more cells in growth, 12% more in osteogenic, 77% more in adipogenic, but 27% less in chondrogenic medium. Differentiation potential wasn't decisively affected at the mRNA level. However, Protocol B favoured bone and cartilage differentiation at the secretional level. Protocol A populations showed reduced purity, expressing CD105 in only 76% compared to the 96.7% in Protocol B cultures. Protocol A populations also contained significantly more (+4.2%) senescent cells, however, no difference was found in cell size between the two protocols. The findings of this study suggest that cell-to-cell contact, and therefore high confluence levels, is detrimental to MSC quality.
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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.
Estepa, A M; Rocha, A I; Mas, V; Pérez, L; Encinar, J A; Nuñez, E; Fernandez, A; Gonzalez Ros, J M; Gavilanes, F; Coll, J M
2001-12-07
The fusion-related properties of segments p9, p3, p4, and p9 + p2 surrounding the p2 phospholipid-binding domain of the protein G (pG) of the salmonid rhabdovirus of viral hemorrhagic septicemia (VHS) (Nuñez, E., Fernandez, A. M., Estepa, A., Gonzalez-Ros, J. M., Gavilanes, F., and Coll, J. M. (1998) Virology 243, 322-330; Estepa, A., and Coll, J. M. (1996) Virology 216, 60-70), have been studied at neutral and fusion (low) pH values by using its derived peptides. Cell-to-cell fusion, translocation of phosphatidylserine, and inhibition of fusion of pG-transfected cells defined the p9 + p2 (fragment 11, sequence 56-110) as a fragment with higher specific activity for anionic phospholipid aggregation than the previously reported p2. While fragment 11, p2, and p3 showed interactions with anionic phospholipids, p9 and p4 showed no interactions with any phospholipids. When added to a cell monolayer model at low pH, fragment 11 induced pH-dependent cell-to-cell fusion and translocated phosphatidylserine from the inner to the outer leaflet of the membrane. At low pH and in the presence of anionic phospholipids, fragment 11 showed more than 80% beta-sheet conformation (IR and CD spectroscopies). Finally, anti-fragment 11 antibodies inhibited low pH-dependent pG-transfected cell-to-cell fusion. All of the data support the conclusion that fragment 11 is a primary determinant of some of the viral cell fusion events in VHSV.
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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.
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Robert C Cannon
Full Text Available Neuronal activity is mediated through changes in the probability of stochastic transitions between open and closed states of ion channels. While differences in morphology define neuronal cell types and may underlie neurological disorders, very little is known about influences of stochastic ion channel gating in neurons with complex morphology. We introduce and validate new computational tools that enable efficient generation and simulation of models containing stochastic ion channels distributed across dendritic and axonal membranes. Comparison of five morphologically distinct neuronal cell types reveals that when all simulated neurons contain identical densities of stochastic ion channels, the amplitude of stochastic membrane potential fluctuations differs between cell types and depends on sub-cellular location. For typical neurons, the amplitude of membrane potential fluctuations depends on channel kinetics as well as open probability. Using a detailed model of a hippocampal CA1 pyramidal neuron, we show that when intrinsic ion channels gate stochastically, the probability of initiation of dendritic or somatic spikes by dendritic synaptic input varies continuously between zero and one, whereas when ion channels gate deterministically, the probability is either zero or one. At physiological firing rates, stochastic gating of dendritic ion channels almost completely accounts for probabilistic somatic and dendritic spikes generated by the fully stochastic model. These results suggest that the consequences of stochastic ion channel gating differ globally between neuronal cell-types and locally between neuronal compartments. Whereas dendritic neurons are often assumed to behave deterministically, our simulations suggest that a direct consequence of stochastic gating of intrinsic ion channels is that spike output may instead be a probabilistic function of patterns of synaptic input to dendrites.
Demography of Verreaux's sifaka in a stochastic rainfall environment.
Lawler, Richard R; Caswell, Hal; Richard, Alison F; Ratsirarson, Joelisoa; Dewar, Robert E; Schwartz, Marion
2009-09-01
In this study, we use deterministic and stochastic models to analyze the demography of Verreaux's sifaka (Propithecus verreauxi verreauxi) in a fluctuating rainfall environment. The model is based on 16 years of data from Beza Mahafaly Special Reserve, southwest Madagascar. The parameters in the stage-classified life cycle were estimated using mark-recapture methods. Statistical models were evaluated using information-theoretic techniques and multi-model inference. The highest ranking model is time-invariant, but the averaged model includes rainfall-dependence of survival and breeding. We used a time-series model of rainfall to construct a stochastic demographic model. The time-invariant model and the stochastic model give a population growth rate of about 0.98. Bootstrap confidence intervals on the growth rates, both deterministic and stochastic, include 1. Growth rates are most elastic to changes in adult survival. Many demographic statistics show a nonlinear response to annual rainfall but are depressed when annual rainfall is low, or the variance in annual rainfall is high. Perturbation analyses from both the time-invariant and stochastic models indicate that recruitment and survival of older females are key determinants of population growth rate.
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.
Fluctuations in quantum devices
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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.
Terrestrial Gravity Fluctuations
Harms, Jan
2015-01-01
The article reviews the current state of the field, and also presents new analyses especially with respect to the impact of seismic scattering on gravity perturbations, active gravity noise cancellation, and time-domain models of gravity perturbations from atmospheric and seismic point sources. Our understanding of terrestrial gravity fluctuations will have great impact on the future development of GW detectors and high-precision gravimetry in general, and many open questions need to be answered still as emphasized in this article.
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.
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 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...
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...
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William Margulies
2004-11-01
Full Text Available In this paper, we study a specific stochastic differential equation depending on a parameter and obtain a representation of its probability density function in terms of Jacobi Functions. The equation arose in a control problem with a quadratic performance criteria. The quadratic performance is used to eliminate the control in the standard Hamilton-Jacobi variational technique. The resulting stochastic differential equation has a noise amplitude which complicates the solution. We then solve Kolmogorov's partial differential equation for the probability density function by using Jacobi Functions. A particular value of the parameter makes the solution a Martingale and in this case we prove that the solution goes to zero almost surely as time tends to infinity.
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
Petukhov, B. V.
2016-04-01
The dynamics of kink solitons is very sensitive to random irregularities of the potential relief. The evolution of kinks after their generation is essentially modified by strong fluctuations of the potential. The stochastic nature of such modification is taken into account by the theory of extreme deviations on a random walk.
Stochastic power system operation
Power, Michael
2010-01-01
This paper outlines how to economically and reliably operate a power system with high levels of renewable generation which are stochastic in nature. It outlines the challenges for system operators, and suggests tools and methods for meeting this challenge, which is one of the most fundamental since large scale power networks were instituted. The Ireland power system, due to its nature and level of renewable generation, is considered as an example in this paper.
Stochastic Games. I. Foundations,
1982-04-01
stimulate discussion and critical coment. Requests for single copies of a Paper will be filled by the Cowles Foundation within the limits of the supply...underpinning for the theory of stochastic games. Section 2 is a reworking of the Bevley- Kohlberg result integrated with Shapley’s; the "black magic" of... Kohlberg : The values of the r-discount game, and the stationary optimal strategies, have Puiseaux expansions. L.. 11" 6 3. More generally, consider an
Stochastic Thermodynamics of Learning
Goldt, Sebastian; Seifert, Udo
2017-01-01
Virtually every organism gathers information about its noisy environment and builds models from those data, mostly using neural networks. Here, we use stochastic thermodynamics to analyze the learning of a classification rule by a neural network. We show that the information acquired by the network is bounded by the thermodynamic cost of learning and introduce a learning efficiency η ≤1 . We discuss the conditions for optimal learning and analyze Hebbian learning in the thermodynamic limit.
Stochastic gravitoelectromagnetic inflation
Madriz Aguilar, José Edgar; Bellini, Mauricio
2006-11-01
Gravitoelectromagnetic inflation was recently introduced to describe, in an unified manner, electromagnetic, gravitatory and inflaton fields in the early (accelerated) inflationary universe from a 5D vacuum state. In this Letter, we study a stochastic treatment for the gravitoelectromagnetic components A=(A,φ), on cosmological scales. We focus our study on the seed magnetic fields on super-Hubble scales, which could play an important role in large scale structure formation of the universe.
Stochastic gravitoelectromagnetic inflation
Aguilar, J E M; Bellini, Mauricio
2006-01-01
Gravitoelectromagnetic inflation was recently introduced to describe, in an unified manner, electromagnetic, gravitatory and inflaton fields in the early (accelerated) inflationary universe from a 5D vacuum state. In this paper, we study a stochastic treatment for the gravitoelectromagnetic components $A_B=(A_{\\mu},\\phi)$, on cosmological scales. We focus our study on the seed magnetic fields on super Hubble scales, which could play an important role in large scale structure formation of the universe.
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 Thermodynamics of Learning
Goldt, Sebastian
2016-01-01
Virtually every organism gathers information about its noisy environment and builds models from that data, mostly using neural networks. Here, we use stochastic thermodynamics to analyse the learning of a classification rule by a neural network. We show that the information acquired by the network is bounded by the thermodynamic cost of learning and introduce a learning efficiency $\\eta\\le1$. We discuss the conditions for optimal learning and analyse Hebbian learning in the thermodynamic limit.
Stochastic Nonlinear Aeroelasticity
2009-01-01
STOCHASTIC NONLINEAR AEROELASTICITY 5a. CONTRACT NUMBER In- house 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 0601102 6. AUTHOR(S) Philip S...ABSTRACT This report documents the culmination of in- house work in the area of uncertainty quantification and probabilistic techniques for... coff U∞ cs ea lw cw Figure 6: Wing and store geometry (left), wing box structural model (middle), flutter distribution (right
Kemsawasd, Varongsiri; Branco, Patrícia; Almeida, Maria Gabriela; Caldeira, Jorge; Albergaria, Helena; Arneborg, Nils
2015-07-01
The roles of cell-to-cell contact and antimicrobial peptides in the early death of Lachanchea thermotolerans CBS2803 during anaerobic, mixed-culture fermentations with Saccharomyces cerevisiae S101 were investigated using a commercially available, double-compartment fermentation system separated by cellulose membranes with different pore sizes, i.e. 1000 kDa for mixed- and single-culture fermentations, and 1000 and 3.5-5 kDa for compartmentalized-culture fermentations. SDS-PAGE and gel filtration chromatography were used to determine an antimicrobial peptidic fraction in the fermentations. Our results showed comparable amounts of the antimicrobial peptidic fraction in the inner compartments of the mixed-culture and 1000 kDa compartmentalized-culture fermentations containing L. thermotolerans after 4 days of fermentation, but a lower death rate of L. thermotolerans in the 1000 kDa compartmentalized-culture fermentation than in the mixed-culture fermentation. Furthermore, L. thermotolerans died off even more slowly in the 3.5-5 kDa than in the 1000 kDa compartmentalized-culture fermentation, which coincided with the presence of less of the antimicrobial peptidic fraction in the inner compartment of that fermentation than of the 1000 kDa compartmentalized-culture fermentation. Taken together, these results indicate that the death of L. thermotolerans in mixed cultures with S. cerevisiae is caused by a combination of cell-to-cell contact and antimicrobial peptides.
Energy Technology Data Exchange (ETDEWEB)
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.
Lim, Hyoun-Sub; Vaira, Anna Maria; Bae, Hanhong; Bragg, Jennifer N; Ruzin, Steven E; Bauchan, Gary R; Dienelt, Margaret M; Owens, Robert A; Hammond, John
2010-08-01
Cell-to-cell movement of potexviruses requires coordinated action of the coat protein and triple gene block (TGB) proteins. The structural properties of Alternanthera mosaic virus (AltMV) TGB3 were examined by methods differentiating between signal peptides and transmembrane domains, and its subcellular localization was studied by Agrobacterium-mediated transient expression and confocal microscopy. Unlike potato virus X (PVX) TGB3, AltMV TGB3 was not associated with the endoplasmic reticulum, and accumulated preferentially in mesophyll cells. Deletion and site-specific mutagenesis revealed an internal signal VL(17,18) of TGB3 essential for chloroplast localization, and either deletion of the TGB3 start codon or alteration of the chloroplast-localization signal limited cell-to-cell movement to the epidermis, yielding a virus that was unable to move into the mesophyll layer. Overexpression of AltMV TGB3 from either AltMV or PVX infectious clones resulted in veinal necrosis and vesiculation at the chloroplast membrane, a cytopathology not observed in wild-type infections. The distinctive mesophyll and chloroplast localization of AltMV TGB3 highlights the critical role played by mesophyll targeting in virus long-distance movement within plants.
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.
Pulmanausahakul, Rojjanaporn; Li, Jianwei; Schnell, Matthias J; Dietzschold, Bernhard
2008-03-01
While the glycoprotein (G) of rabies virus (RV) is known to play a predominant role in the pathogenesis of rabies, the function of the RV matrix protein (M) in RV pathogenicity is not completely clear. To further investigate the roles of these proteins in viral pathogenicity, we constructed chimeric recombinant viruses by exchanging the G and M genes of the attenuated SN strain with those of the highly pathogenic SB strain. Infection of mice with these chimeric viruses revealed a significant increase in the pathogenicity of the SN strain bearing the RV G from the pathogenic SB strain. Moreover, the pathogenicity was further increased when both G and M from SB were introduced into SN. Interestingly, the replacement of the G or M gene or both in SN by the corresponding genes of SB was associated with a significant decrease in the rate of viral replication and viral RNA synthesis. In addition, a chimeric SN virus bearing both the M and G genes from SB exhibited more efficient cell-to-cell spread than a chimeric SN virus in which only the G gene was replaced. Together, these data indicate that both G and M play an important role in RV pathogenesis by regulating virus replication and facilitating cell-to-cell spread.
Lyapunov exponents of stochastic systems—from micro to macro
Laffargue, Tanguy; Tailleur, Julien; van Wijland, Frédéric
2016-03-01
Lyapunov exponents of dynamical systems are defined from the rates of divergence of nearby trajectories. For stochastic systems, one typically assumes that these trajectories are generated under the ‘same noise realization’. The purpose of this work is to critically examine what this expression means. For Brownian particles, we consider two natural interpretations of the noise: intrinsic to the particles or stemming from the fluctuations of the environment. We show how they lead to different distributions of the largest Lyapunov exponent as well as different fluctuating hydrodynamics for the collective density field. We discuss, both at microscopic and macroscopic levels, the limits in which these noise prescriptions become equivalent. We close this paper by providing an estimate of the largest Lyapunov exponent and of its fluctuations for interacting particles evolving with Dean-Kawasaki dynamics.
Institute of Scientific and Technical Information of China (English)
郑忠华; 张瑜
2015-01-01
This paper establishes a dynamic stochastic general equilibrium model of multi -departmentcontains a heterogeneous family,enterprise,retailers,commercial bank,etc.The borrowing behaviors of enterprises and borrowing households make the economic impacts on enterprise production and even the entire supply field by corporate borrowing behavior. Through the influences on consumption savings by household borrowing, important subject of transmission of economic fluctuation is composed of real estate market and banking system. Accordingly,the model portrays a variety of shocks (including the preference of real estate ) on dynamic impacts of macroeconomic variables. The results of the model show that the increase in real estate demand to some extent will bring economic recession,The impact of monetary policy through the banking system to economic fluctuations,different expression form the main body of the real estate market,the bank to business, personalfinance,in China,the bank system China's economic fluctuation is the subject of transmission can not be ignored.%本文建立了一个包含异质性家庭、企业、零售商、商业银行、中央银行等多部门的动态随机一般均衡模型。模型中企业以房地产抵押向银行借贷，普通家庭通过银行借款提前消费房地产，将房地产市场与银行体系引入模型，两者构成模型中经济波动传导的主体。我们模拟了各种冲击（包括房地产偏好、存款准备金率、通胀等）对宏观经济变量的动态影响，模拟的一些结果和现实中国经济反应非常一致。模拟结果表明：房地产需求的增加会在一定程度上引发经济衰退，影响经济最重要的变量是央行的存款准备金率和通胀冲击，银行体系将外生冲击分散传导，导致经济主体在冲击下形成其不同经济表现，在我国，银行体系是我国经济波动不可忽视的传导途径。
SOL width and intermittent fluctuations in KSTAR
Garcia, O E; Theodorsen, A; Bak, J -G; Hong, S -H; Kim, H -S; Pitts, R A
2016-01-01
Radial profiles of the ion saturation current and its fluctuation statistics are presented from probe measurements in L-mode, neutral beam heated plasmas at the outboard mid-plane region of KSTAR. The familiar two-layer structure, seen elsewhere in tokamak L-mode discharges, with a steep near-SOL profile and a broad far-SOL profile, is observed. The profile scale length in the far-SOL increases drastically with line-averaged density, thereby enhancing plasma interactions with the main chamber walls. Time series from the far-SOL region are characterised by large-amplitude bursts attributed to the radial motion of blob-like plasma filaments. Analysis of a data time series of several seconds duration under stationary plasma conditions reveals the statistical properties of these fluctuations, including the rate of level crossings and the average duration of periods spent above a given threshold level. This is shown to be in excellent agreement with predictions of a stochastic model, giving novel predictions of pl...
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.
Simulation of Stochastic Partial Differential Equations and Stochastic Active Contours
Lang, Annika
2007-01-01
This thesis discusses several aspects of the simulation of stochastic partial differential equations. First, two fast algorithms for the approximation of infinite dimensional Gaussian random fields with given covariance are introduced. Later Hilbert space-valued Wiener processes are constructed out of these random fields. A short introduction to infinite-dimensional stochastic analysis and stochastic differential equations is given. Furthermore different definitions of numerical stability for...
Wandering bumps in stochastic neural fields
Kilpatrick, Zachary P
2012-01-01
We study the effects of noise on stationary pulse solutions (bumps) in spatially extended neural fields. The dynamics of a neural field is described by an integrodifferential equation whose integral term characterizes synaptic interactions between neurons in different spatial locations of the network. Translationally symmetric neural fields support a continuum of stationary bump solutions, which may be centered at any spatial location. Random fluctuations are introduced by modeling the system as a spatially extended Langevin equation whose noise term we take to be multiplicative or additive. For nonzero noise, these bumps are shown to wander about the domain in a purely diffusive way. We can approximate the effective diffusion coefficient using a small noise expansion. Upon breaking the (continuous) translation symmetry of the system using a spatially heterogeneous inputs or synapses, bumps in the stochastic neural field can become temporarily pinned to a finite number of locations in the network. In the case...
Overdamped stochastic thermodynamics with multiple reservoirs
Murashita, Yûto; Esposito, Massimiliano
2016-12-01
After establishing stochastic thermodynamics for underdamped Langevin systems in contact with multiple reservoirs, we derive its overdamped limit using timescale separation techniques. The overdamped theory is different from the naive theory that one obtains when starting from overdamped Langevin or Fokker-Planck dynamics and only coincides with it in the presence of a single reservoir. The reason is that the coarse-grained fast momentum dynamics reaches a nonequilibrium state, which conducts heat in the presence of multiple reservoirs. The underdamped and overdamped theory are both shown to satisfy fundamental fluctuation theorems. Their predictions for the heat statistics are derived analytically for a Brownian particle on a ring in contact with two reservoirs and subjected to a nonconservative force and are shown to coincide in the long-time limit.
Mixing properties of stochastic quantum Hamiltonians
Onorati, E; Kliesch, M; Brown, W; Werner, A H; Eisert, J
2016-01-01
Random quantum processes play a central role both in the study of fundamental mixing processes in quantum mechanics related to equilibration, thermalisation and fast scrambling by black holes, as well as in quantum process design and quantum information theory. In this work, we present a framework describing the mixing properties of continuous-time unitary evolutions originating from local Hamiltonians having time-fluctuating terms, reflecting a Brownian motion on the unitary group. The induced stochastic time evolution is shown to converge to a unitary design. As a first main result, we present bounds to the mixing time. By developing tools in representation theory, we analytically derive an expression for a local k-th moment operator that is entirely independent of k, giving rise to approximate unitary k-designs and quantum tensor product expanders. As a second main result, we introduce tools for proving bounds on the rate of decoupling from an environment with random quantum processes. By tying the mathema...
A Model for Lightcone Fluctuations due to Stress Tensor Fluctuations
Bessa, C H G; Ford, L H; Ribeiro, C C H
2016-01-01
We study a model for quantum lightcone fluctuations in which vacuum fluctuations of the electric field and of the squared electric field in a nonlinear dielectric material produce variations in the flight times of probe pulses. When this material has a non-zero third order polarizability, the flight time variations arise from squared electric field fluctuations, and are analogous to effects expected when the stress tensor of a quantized field drives passive spacetime geometry fluctuations. We also discuss the dependence of the squared electric field fluctuations upon the geometry of the material, which in turn determines a sampling function for averaging the squared electric field along the path of the pulse. This allows us to estimate the probability of especially large fluctuations, which is a measure of the probability distribution for quantum stress tensor fluctuations.
Some stochastic aspects of quantization
Indian Academy of Sciences (India)
Ichiro Ohba
2002-08-01
From the advent of quantum mechanics, various types of stochastic-dynamical approach to quantum mechanics have been tried. We discuss how to utilize Nelson’s stochastic quantum mechanics to analyze the tunneling phenomena, how to derive relativistic ﬁeld equations via the Poisson process and how to describe a quantum dynamics of open systems by the use of quantum state diffusion, or the stochastic Schrödinger equation.
Verification of Stochastic Process Calculi
DEFF Research Database (Denmark)
Skrypnyuk, Nataliya
Stochastic process calculi represent widely accepted formalisms within Computer Science for modelling nondeterministic stochastic systems in a compositional way. Similar to process calculi in general, they are suited for modelling systems in a hierarchical manner, by explicitly specifying...... subsystems as well as their interdependences and communication channels. Stochastic process calculi incorporate both the quantified uncertainty on probabilities or durations of events and nondeterministic choices between several possible continuations of the system behaviour. Modelling of a system is often...
Stochastic Analysis of Cylindrical Shell
Directory of Open Access Journals (Sweden)
Grzywiński Maksym
2014-06-01
Full Text Available The paper deals with some chosen aspects of stochastic structural analysis and its application in the engineering practice. The main aim of the study is to apply the generalized stochastic perturbation techniques based on classical Taylor expansion with a single random variable for solution of stochastic problems in structural mechanics. The study is illustrated by numerical results concerning an industrial thin shell structure modeled as a 3-D structure.
Stochastic Nature in Cellular Processes
Institute of Scientific and Technical Information of China (English)
刘波; 刘圣君; 王祺; 晏世伟; 耿轶钊; SAKATA Fumihiko; GAO Xing-Fa
2011-01-01
The importance of stochasticity in cellular processes is increasingly recognized in both theoretical and experimental studies. General features of stochasticity in gene regulation and expression are briefly reviewed in this article, which include the main experimental phenomena, classification, quantization and regulation of noises. The correlation and transmission of noise in cascade networks are analyzed further and the stochastic simulation methods that can capture effects of intrinsic and extrinsic noise are described.
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...
Stochastic basins of attraction for metastable states.
Serdukova, Larissa; Zheng, Yayun; Duan, Jinqiao; Kurths, Jürgen
2016-07-01
Basin of attraction of a stable equilibrium point is an effective concept for stability analysis in deterministic systems; however, it does not contain information on the external perturbations that may affect it. Here we introduce the concept of stochastic basin of attraction (SBA) by incorporating a suitable probabilistic notion of basin. We define criteria for the size of the SBA based on the escape probability, which is one of the deterministic quantities that carry dynamical information and can be used to quantify dynamical behavior of the corresponding stochastic basin of attraction. SBA is an efficient tool to describe the metastable phenomena complementing the known exit time, escape probability, or relaxation time. Moreover, the geometric structure of SBA gives additional insight into the system's dynamical behavior, which is important for theoretical and practical reasons. This concept can be used not only in models with small noise intensity but also with noise whose amplitude is proportional or in general is a function of an order parameter. As an application of our main results, we analyze a three potential well system perturbed by two types of noise: Brownian motion and non-Gaussian α-stable Lévy motion. Our main conclusions are that the thermal fluctuations stabilize the metastable system with an asymmetric three-well potential but have the opposite effect for a symmetric one. For Lévy noise with larger jumps and lower jump frequencies ( α=0.5) metastability is enhanced for both symmetric and asymmetric potentials.
Alexandrov, Dmitri V.; Bashkirtseva, Irina A.; Ryashko, Lev B.
2015-11-01
Motivated by important paleoclimate applications we study a three dimensional model of the Quaternary climatic variations in the presence of stochastic forcing. It is shown that the deterministic system exhibits a limit cycle and two stable system equilibria. We demonstrate that the closer paleoclimate system to its bifurcation points (lying either in its monostable or bistable zone) the smaller noise generates small or large amplitude stochastic oscillations, respectively. In the bistable zone with two stable equilibria, noise induces a complex multimodal stochastic regime with intermittency of small and large amplitude stochastic fluctuations. In the monostable zone, the small amplitude stochastic oscillations localized in the vicinity of unstable equilibrium appear along with the large amplitude oscillations near the stable limit cycle. For the analysis of these noise-induced effects, we develop the stochastic sensitivity technique and use the Mahalanobis metric in the three-dimensional case. To approximate the distribution of random trajectories in Poincare sections, we use a method of confidence ellipses. A spatial configuration of these ellipses is defined by the stochastic sensitivity and noise intensity. The glaciation/deglaciation transitions going between two polar Earth's states with the warm and cold climate become easier and quicker with increasing the noise intensity. Our stochastic analysis demonstrates a near 100 ky saw-tooth type climate self fluctuations known from paleoclimate records. In addition, the enhancement of noise intensity blurs the sharp climate cycles and reduces the glaciation-deglaciation periods of the Earth's paleoclimate.
Dynamic density functional theory with hydrodynamic interactions and fluctuations
Energy Technology Data Exchange (ETDEWEB)
Donev, Aleksandar, E-mail: donev@courant.nyu.edu; Vanden-Eijnden, Eric, E-mail: eve2@courant.nyu.edu [Courant Institute of Mathematical Sciences, New York University, New York, New York 10012 (United States)
2014-06-21
We derive a closed equation for the empirical concentration of colloidal particles in the presence of both hydrodynamic and direct interactions. The ensemble average of our functional Langevin equation reproduces known deterministic Dynamic Density Functional Theory (DDFT) [M. Rex and H. Löwen, “Dynamical density functional theory with hydrodynamic interactions and colloids in unstable traps,” Phys. Rev. Lett. 101(14), 148302 (2008)], and, at the same time, it also describes the microscopic fluctuations around the mean behavior. We suggest separating the ideal (non-interacting) contribution from additional corrections due to pairwise interactions. We find that, for an incompressible fluid and in the absence of direct interactions, the mean concentration follows Fick's law just as for uncorrelated walkers. At the same time, the nature of the stochastic terms in fluctuating DDFT is shown to be distinctly different for hydrodynamically-correlated and uncorrelated walkers. This leads to striking differences in the behavior of the fluctuations around Fick's law, even in the absence of pairwise interactions. We connect our own prior work [A. Donev, T. G. Fai, and E. Vanden-Eijnden, “A reversible mesoscopic model of diffusion in liquids: from giant fluctuations to Fick's law,” J. Stat. Mech.: Theory Exp. (2014) P04004] on fluctuating hydrodynamics of diffusion in liquids to the DDFT literature, and demonstrate that the fluid cannot easily be eliminated from consideration if one wants to describe the collective diffusion in colloidal suspensions.
Langevin equation with stochastic damping - Possible application to critical binary fluid
Jasnow, D.; Gerjuoy, E.
1975-01-01
We solve the familiar Langevin equation with stochastic damping to represent the motion of a Brownian particle in a fluctuating medium. A connection between the damping and the random driving forces is proposed which preserves quite generally the Einstein relation between the diffusion and mobility coefficients. We present an application to the case of a Brownian particle in a critical binary mixture.
Nomura, Fumimasa; Kaneko, Tomoyuki; Hamada, Tomoyo; Hattori, Akihiro; Yasuda, Kenji
2013-06-01
To predict the risk of fatal arrhythmia induced by cardiotoxicity in the highly complex human heart system, we have developed a novel quasi-in vivo electrophysiological measurement assay, which combines a ring-shaped human cardiomyocyte network and a set of two electrodes that form a large single ring-shaped electrode for the direct measurement of irregular cell-to-cell conductance occurrence in a cardiomyocyte network, and a small rectangular microelectrode for forced pacing of cardiomyocyte beating and for acquiring the field potential waveforms of cardiomyocytes. The advantages of this assay are as follows. The electrophysiological signals of cardiomyocytes in the ring-shaped network are superimposed directly on a single loop-shaped electrode, in which the information of asynchronous behavior of cell-to-cell conductance are included, without requiring a set of huge numbers of microelectrode arrays, a set of fast data conversion circuits, or a complex analysis in a computer. Another advantage is that the small rectangular electrode can control the position and timing of forced beating in a ring-shaped human induced pluripotent stem cell (hiPS)-derived cardiomyocyte network and can also acquire the field potentials of cardiomyocytes. First, we constructed the human iPS-derived cardiomyocyte ring-shaped network on the set of two electrodes, and acquired the field potential signals of particular cardiomyocytes in the ring-shaped cardiomyocyte network during simultaneous acquisition of the superimposed signals of whole-cardiomyocyte networks representing cell-to-cell conduction. Using the small rectangular electrode, we have also evaluated the response of the cell network to electrical stimulation. The mean and SD of the minimum stimulation voltage required for pacing (VMin) at the small rectangular electrode was 166+/-74 mV, which is the same as the magnitude of amplitude for the pacing using the ring-shaped electrode (179+/-33 mV). The results showed that the
[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. ‡.
Multifractal detrended fluctuation analysis of analog random multiplicative processes
Energy Technology Data Exchange (ETDEWEB)
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.
Effects of stochastic channel gating and distribution on the cardiac action potential.
Lemay, Mathieu; de Lange, Enno; Kucera, Jan P
2011-07-21
Ion channels exhibit stochastic conformational changes determining their gating behavior. In addition, the process of protein turnover leads to a natural variability of the number of membrane and gap junctional channels. Nevertheless, in computational models, these two aspects are scarcely considered and their impacts are largely unknown. We investigated the effects of stochastic current fluctuations and channel distributions on action potential duration (APD), intercellular conduction delays (ICDs) and conduction blocks using a modified ventricular cell model (Rudy et al.) with Markovian formulations of the principal ion currents (to simulate their stochastic open-close gating behavior) and with channel counts drawn from Poisson distributions (to simulate their natural variability). In single cells, APD variability (coefficient of variation: 1.6% at BCL=1000ms) was essentially caused by stochastic channel gating of I(Ks), persistent I(Na) and I(Ca,L). In cell strands, ICD variability induced by stochastic channel gating and Poissonian channel distributions was low under normal conditions. Nonetheless, at low intercellular coupling levels, Poissonian gap junctional channel distribution resulted in a large ICD variability (coefficient of variation >20%), highly heterogeneous conduction patterns and conduction blocks. Therefore, the stochastic behavior of current fluctuations and channel distributions can contribute to the heterogeneity of conduction patterns and to conduction block, as observed previously in experiments in cardiac tissue with altered intercellular coupling.
Stochastic extinction and persistence of a parasite-host epidemiological model
Liu, Yuting; Shan, Meijing; Lian, Xinze; Wang, Weiming
2016-11-01
In this paper, we investigate the stochastic extinction and persistence of a parasite-host epidemiological model. We show that the global dynamics of the stochastic model can be governed by the basic reproduction number R0S: if R0S 1, under mild extra conditions, the disease persists and endemic dynamics occurs almost surely, the solutions of the stochastic model fluctuate around the steady state of the deterministic model, and a unique stationary distribution can be found. Based on realistic parameters of Daphnia-microparasite system, numerical simulations have been performed to verify/extend our analytical results. Epidemiologically, we find that: (1) Large environment fluctuations can suppress the outbreak of disease; (2) The distributions are governed by R0S; (3) The noise perturbations can be beneficial to control the spread of disease on average.
Modelling Meso-Scale Diffusion Processes in Stochastic Fluid Bio-Membranes
Rafii-Tabar, H
1999-01-01
The space-time dynamics of rigid inhomogeneities (inclusions) free to move in a randomly fluctuating fluid bio-membrane is derived and numerically simulated as a function of the membrane shape changes. Both vertically placed (embedded) inclusions and horizontally placed (surface) inclusions are considered. The energetics of the membrane, as a two-dimensional (2D) meso-scale continuum sheet, is described by the Canham-Helfrich Hamiltonian, with the membrane height function treated as a stochastic process. The diffusion parameter of this process acts as the link coupling the membrane shape fluctuations to the kinematics of the inclusions. The latter is described via Ito stochastic differential equation. In addition to stochastic forces, the inclusions also experience membrane-induced deterministic forces. Our aim is to simulate the diffusion-driven aggregation of inclusions and show how the external inclusions arrive at the sites of the embedded inclusions. The model has potential use in such emerging fields as...
Localized Spectral Analysis of Fluctuating Power Generation from Solar Energy Systems
Directory of Open Access Journals (Sweden)
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.
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…
A Mechanistic Stochastic Ricker Model: Analytical and Numerical Investigations
Gadrich, Tamar; Katriel, Guy
The Ricker model is one of the simplest and most widely-used ecological models displaying complex nonlinear dynamics. We study a discrete-time population model, which is derived from simple assumptions concerning individual organisms’ behavior, using the “site-based” approach, developed by Brännström, Broomhead, Johansson and Sumpter. In the large-population limit the model converges to the Ricker model, and can thus be considered a mechanistic version of the Ricker model, derived from basic ecological principles, and taking into account the demographic stochasticity inherent to finite populations. We employ several analytical and precise numerical methods to study the model, showing how each approach contributes to understanding the model’s dynamics. Expressing the model as a Markov chain, we employ the concept of quasi-stationary distributions, which are computed numerically, and used to examine the interaction between complex deterministic dynamics and demographic stochasticity, as well as to calculate mean times to extinction. A Gaussian Markov chain approximation is used to obtain quantitative asymptotic approximations for the size of fluctuations of the stochastic model’s time series around the deterministic trajectory, and for the correlations between successive fluctuations. Results of these approximations are compared to results obtained from quasi-stationary distributions and from direct simulations, and are shown to be in good agreement.
Fluorescence Correlation Spectroscopy and Nonlinear Stochastic Reaction-Diffusion
Energy Technology Data Exchange (ETDEWEB)
Del Razo, Mauricio; Pan, Wenxiao; Qian, Hong; Lin, Guang
2014-05-30
The currently existing theory of fluorescence correlation spectroscopy (FCS) is based on the linear fluctuation theory originally developed by Einstein, Onsager, Lax, and others as a phenomenological approach to equilibrium fluctuations in bulk solutions. For mesoscopic reaction-diffusion systems with nonlinear chemical reactions among a small number of molecules, a situation often encountered in single-cell biochemistry, it is expected that FCS time correlation functions of a reaction-diffusion system can deviate from the classic results of Elson and Magde [Biopolymers (1974) 13:1-27]. We first discuss this nonlinear effect for reaction systems without diffusion. For nonlinear stochastic reaction-diffusion systems there are no closed solutions; therefore, stochastic Monte-Carlo simulations are carried out. We show that the deviation is small for a simple bimolecular reaction; the most significant deviations occur when the number of molecules is small and of the same order. Extending Delbrück-Gillespie’s theory for stochastic nonlinear reactions with rapidly stirring to reaction-diffusion systems provides a mesoscopic model for chemical and biochemical reactions at nanometric and mesoscopic level such as a single biological cell.
The stochastic quality calculus
DEFF Research Database (Denmark)
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...
Deduction as Stochastic Simulation
2013-07-01
Eab Oa b Eab Ob a Iab Aab Iab Aba Iab Eab Iab EbaIab Iab Iab Iba Iab Oa b Iab Ob a Oa bAa b Oa bAb a Oa bEa b Oa bEb a Oa bIa b Oa bIb a Oa bO ab Oa bO...Oa bIa b Oa bIb a Oa bO ab Oa bO ba % C or re ct A. B. stochastic system’s parameters could be tweaked for individual reasoners. For example, the λ
Stochastic conditional intensity processes
DEFF Research Database (Denmark)
Bauwens, Luc; Hautsch, Nikolaus
2006-01-01
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...... 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...
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.
Carpentier, Pierre; Cohen, Guy; De Lara, Michel
2015-01-01
The focus of the present volume is stochastic optimization of dynamical systems in discrete time where - by concentrating on the role of information regarding optimization problems - it discusses the related discretization issues. There is a growing need to tackle uncertainty in applications of optimization. For example the massive introduction of renewable energies in power systems challenges traditional ways to manage them. This book lays out basic and advanced tools to handle and numerically solve such problems and thereby is building a bridge between Stochastic Programming and Stochastic Control. It is intended for graduates readers and scholars in optimization or stochastic control, as well as engineers with a background in applied mathematics.
Galloway, Nicole L K; Doitsh, Gilad; Monroe, Kathryn M; Yang, Zhiyuan; Muñoz-Arias, Isa; Levy, David N; Greene, Warner C
2015-09-01
The progressive depletion of CD4 T cells underlies clinical progression to AIDS in untreated HIV-infected subjects. Most dying CD4 T cells correspond to resting nonpermissive cells residing in lymphoid tissues. Death is due to an innate immune response against the incomplete cytosolic viral DNA intermediates accumulating in these cells. The viral DNA is detected by the IFI16 sensor, leading to inflammasome assembly, caspase-1 activation, and the induction of pyroptosis, a highly inflammatory form of programmed cell death. We now show that cell-to-cell transmission of HIV is obligatorily required for activation of this death pathway. Cell-free HIV-1 virions, even when added in large quantities, fail to activate pyroptosis. These findings underscore the infected CD4 T cells as the major killing units promoting progression to AIDS and highlight a previously unappreciated role for the virological synapse in HIV pathogenesis.
Kuhn, Dagmar A.; Hartmann, Raimo; Fytianos, Kleanthis; Petri-Fink, Alke; Rothen-Rutishauser, Barbara; Parak, Wolfgang J.
2015-06-01
Polyelectrolyte multilayer microcapsules around 3.4 micrometers in diameter were added to epithelial cells, monocyte-derived macrophages, and dendritic cells in vitro and their uptake kinetics were quantified. All three cell types were combined in a triple co-culture model, mimicking the human epithelial alveolar barrier. Hereby, macrophages were separated in a three-dimensional model from dendritic cells by a monolayer of epithelial cells. While passing of small nanoparticles has been demonstrated from macrophages to dendritic cells across the epithelial barrier in previous studies, for the micrometer-sized capsules, this process could not be observed in a significant amount. Thus, this barrier is a limiting factor for cell-to-cell transfer of micrometer-sized particles.
DEFF Research Database (Denmark)
Shang, Yunlong; Zhang, Chenghui; Cui, Naxin
2015-01-01
voltage gap for large balancing current and ZVG between cells. Instead of a dedicated equalizer for each cell, only one balancing converter is employed and shared by all cells, reducing the size and implementation cost. Moreover, the equalization current can be regulated as needed by controlling the duty...... cycle of the BDDC, which not only prevents efficiently over-equalization but also abridges the balancing time. Simulation and experimental results show the proposed scheme exhibits outstanding balancing performance, and the energy conversion efficiency is higher than 98%. The validity of the proposed...... 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...
Stochastic Runge-Kutta Software Package for Stochastic Differential Equations
Gevorkyan, M N; Korolkova, A V; Kulyabov, D S; Sevastyanov, L A
2016-01-01
As a result of the application of a technique of multistep processes stochastic models construction the range of models, implemented as a self-consistent differential equations, was obtained. These are partial differential equations (master equation, the Fokker--Planck equation) and stochastic differential equations (Langevin equation). However, analytical methods do not always allow to research these equations adequately. It is proposed to use the combined analytical and numerical approach studying these equations. For this purpose the numerical part is realized within the framework of symbolic computation. It is recommended to apply stochastic Runge--Kutta methods for numerical study of stochastic differential equations in the form of the Langevin. Under this approach, a program complex on the basis of analytical calculations metasystem Sage is developed. For model verification logarithmic walks and Black--Scholes two-dimensional model are used. To illustrate the stochastic "predator--prey" type model is us...
Directory of Open Access Journals (Sweden)
María Isabel Clemente
Full Text Available BACKGROUND: The course of human immunodeficiency virus type-1 (HIV-1 infection is influenced by a complex interplay between viral and host factors. HIV infection stimulates several proinflammatory genes, such as cyclooxigense-2 (COX-2, which leads to an increase in prostaglandin (PG levels in the plasma of HIV-1-infected patients. These genes play an indeterminate role in HIV replication and pathogenesis. The effect of prostaglandin E2 (PGE2 on HIV infection is quite controversial and even contradictory, so we sought to determine the role of PGE2 and the signal transduction pathways involved in HIV infection to elucidate possible new targets for antiretrovirals. RESULTS: Our results suggest that PGE2 post-infection treatment acts in the late stages of the viral cycle to reduce HIV replication. Interestingly, viral protein synthesis was not affected, but a loss of progeny virus production was observed. No modulation of CD4 CXCR4 and CCR5 receptor expression, cell proliferation, or activation after PGE2 treatment was detected. Moreover, PGE2 induced an increase in intracellular cAMP (cyclic AMP levels through the EP2/EP4 receptors. PGE2 effects were mimicked by dbcAMP and by a specific Epac (exchange protein directly activated by cyclic AMP agonist, 8-Cpt-cAMP. Treatment with PGE2 increased Rap1 activity, decreased RhoA activity and subsequently reduced the polymerization of actin by approximately 30% compared with untreated cells. In connection with this finding, polarized viral assembly platforms enriched in Gag were disrupted, altering HIV cell-to-cell transfer and the infectivity of new virions. CONCLUSIONS: Our results demonstrate that PGE2, through Epac and Rap activation, alters the transport of newly synthesized HIV-1 components to the assembly site, reducing the release and infectivity of new cell-free virions and cell-to-cell HIV-1 transfer.
Directory of Open Access Journals (Sweden)
Mary Jane Beilby
2016-07-01
Full Text Available 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.
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.
Lemaire, Morgane; Masquelier, Cécile; Beraud, Cyprien; Rybicki, Arkadiusz; Servais, Jean-Yves; Iserentant, Gilles; Schmit, Jean-Claude; Seguin-Devaux, Carole; Perez Bercoff, Danielle
2016-01-01
The cytoplasmic tail (gp41CT) of the HIV-1 envelope (Env) mediates Env incorporation into virions and regulates Env intracellular trafficking. Little is known about the functional impact of variability in this domain. To address this issue, we compared the replication of recombinant virus pairs carrying the full Env (Env viruses) or the Env ectodomain fused to the gp41CT of NL4.3 (EnvEC viruses) (12 subtype C and 10 subtype B pairs) in primary CD4+ T-cells and monocyte-derived-macrophages (MDMs). In CD4+ T-cells, replication was as follows: B-EnvEC = B-Env>C-EnvEC>C-Env, indicating that the gp41CT of subtype C contributes to the low replicative capacity of this subtype. In MDMs, in contrast, replication capacity was comparable for all viruses regardless of subtype and of gp41CT. In CD4+ T-cells, viral entry, viral release and viral gene expression were similar. However, infectivity of free virions and cell-to-cell transmission of C-Env viruses released by CD4+ T-cells was lower, suggestive of lower Env incorporation into virions. Subtype C matrix only minimally rescued viral replication and failed to restore infectivity of free viruses and cell-to-cell transmission. Taken together, these results show that polymorphisms in the gp41CT contribute to viral replication capacity and suggest that the number of Env spikes per virion may vary across subtypes. These findings should be taken into consideration in the design of vaccines. PMID:27598717
Energy Technology Data Exchange (ETDEWEB)
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
Stokes efficiency and its stochastic properties
Sahoo, Mamata; Jayannavar, A. M.
2017-01-01
We study the Stokes efficiency and its fluctuating properties in the case of a spatial asymmetric ratchet potential with a temporal asymmetric driving force from adiabatic to nonadiabatic regime. Our numerical investigations show that the average Stokes efficiency and the average current decrease with increase in the frequency of driving. For low frequency of driving, i.e., in the case of an adiabatic regime, we reproduced the analytical results supporting our numerical simulations. By evaluating the probability distribution p(ηs) for Stokes efficiency ηs, we focus on the stochastic properties of Stokes efficiency. We find that in most of the parameter space, fluctuations in ηs are comparable to or larger than the mean values. In such a situation, one has to study the nature of the full probability distribution of ηs. We observe that with increase in frequency of driving, the distribution becomes multipeaked. At the same time, the average Stokes efficiency monotonically decreases with increase in frequency of the drive. For high frequency of driving, the distribution develops a peak at zero. With further increase in frequency of the drive this peak gets sharper. And finally at sufficiently high frequency, we get a strong peak at zero indicating that there is no effective transport in this regime.
Mixed effects in stochastic differential equation models
DEFF Research Database (Denmark)
Ditlevsen, Susanne; De Gaetano, Andrea
2005-01-01
maximum likelihood; pharmacokinetics; population estimates; random effects; repeated measurements; stochastic processes......maximum likelihood; pharmacokinetics; population estimates; random effects; repeated measurements; stochastic processes...
Discretization error of Stochastic Integrals
Fukasawa, Masaaki
2010-01-01
Asymptotic error distribution for approximation of a stochastic integral with respect to continuous semimartingale by Riemann sum with general stochastic partition is studied. Effective discretization schemes of which asymptotic conditional mean-squared error attains a lower bound are constructed. Two applications are given; efficient delta hedging strategies with transaction costs and effective discretization schemes for the Euler-Maruyama approximation are constructed.
The dynamics of stochastic processes
DEFF Research Database (Denmark)
Basse-O'Connor, Andreas
In the present thesis the dynamics of stochastic processes is studied with a special attention to the semimartingale property. This is mainly motivated by the fact that semimartingales provide the class of the processes for which it is possible to define a reasonable stochastic calculus due...
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.
Stochastic Pi-calculus Revisited
DEFF Research Database (Denmark)
Cardelli, Luca; Mardare, Radu Iulian
2013-01-01
We develop a version of stochastic Pi-calculus with a semantics based on measure theory. We dene the behaviour of a process in a rate environment using measures over the measurable space of processes induced by structural congruence. We extend the stochastic bisimulation to include the concept of...
Recursive Concurrent Stochastic Games
Etessami, Kousha
2008-01-01
We study Recursive Concurrent Stochastic Games (RCSGs), extending our recent analysis of recursive simple stochastic games [16,17] to a concurrent setting where the two players choose moves simultaneously and independently at each state. For multi-exit games, our earlier work already showed undecidability for basic questions like termination, thus we focus on the important case of single-exit RCSGs (1-RCSGs). We first characterize the value of a 1-RCSG termination game as the least fixed point solution of a system of nonlinear minimax functional equations, and use it to show PSPACE decidability for the quantitative termination problem. We then give a strategy improvement technique, which we use to show that player 1 (maximizer) has \\epsilon-optimal randomized Stackless & Memoryless (r-SM) strategies for all \\epsilon > 0, while player 2 (minimizer) has optimal r-SM strategies. Thus, such games are r-SM-determined. These results mirror and generalize in a strong sense the randomized memoryless determinacy r...
Stochastic power flow modeling
Energy Technology Data Exchange (ETDEWEB)
1980-06-01
The stochastic nature of customer demand and equipment failure on large interconnected electric power networks has produced a keen interest in the accurate modeling and analysis of the effects of probabilistic behavior on steady state power system operation. The principle avenue of approach has been to obtain a solution to the steady state network flow equations which adhere both to Kirchhoff's Laws and probabilistic laws, using either combinatorial or functional approximation techniques. Clearly the need of the present is to develop sound techniques for producing meaningful data to serve as input. This research has addressed this end and serves to bridge the gap between electric demand modeling, equipment failure analysis, etc., and the area of algorithm development. Therefore, the scope of this work lies squarely on developing an efficient means of producing sensible input information in the form of probability distributions for the many types of solution algorithms that have been developed. Two major areas of development are described in detail: a decomposition of stochastic processes which gives hope of stationarity, ergodicity, and perhaps even normality; and a powerful surrogate probability approach using proportions of time which allows the calculation of joint events from one dimensional probability spaces.
AA, stochastic precooling pickup
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...
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.
Quantifying economic fluctuations
Stanley, H. Eugene; Nunes Amaral, Luis A.; Gabaix, Xavier; Gopikrishnan, Parameswaran; Plerou, Vasiliki
2001-12-01
This manuscript is a brief summary of a talk designed to address the question of whether two of the pillars of the field of phase transitions and critical phenomena-scale invariance and universality-can be useful in guiding research on interpreting empirical data on economic fluctuations. Using this conceptual framework as a guide, we empirically quantify the relation between trading activity-measured by the number of transactions N-and the price change G( t) for a given stock, over a time interval [ t, t+Δ t]. We relate the time-dependent standard deviation of price changes-volatility-to two microscopic quantities: the number of transactions N( t) in Δ t and the variance W2( t) of the price changes for all transactions in Δ t. We find that the long-ranged volatility correlations are largely due to those of N. We then argue that the tail-exponent of the distribution of N is insufficient to account for the tail-exponent of P{ G> x}. Since N and W display only weak inter-dependency, our results show that the fat tails of the distribution P{ G> x} arises from W. Finally, we review recent work on quantifying collective behavior among stocks by applying the conceptual framework of random matrix theory (RMT). RMT makes predictions for “universal” properties that do not depend on the interactions between the elements comprising the system, and deviations from RMT provide clues regarding system-specific properties. We compare the statistics of the cross-correlation matrix C-whose elements Cij are the correlation coefficients of price fluctuations of stock i and j-against a random matrix having the same symmetry properties. It is found that RMT methods can distinguish random and non-random parts of C. The non-random part of C which deviates from RMT results, provides information regarding genuine collective behavior among stocks. We also discuss results that are reminiscent of phase transitions in spin systems, where the divergent behavior of the response function at
Variance decomposition in stochastic simulators
Le Maître, O. P.
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.
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.
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...
System Entropy Measurement of Stochastic Partial Differential Systems
Directory of Open Access Journals (Sweden)
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.
Stochastic analysis of response functions in environmental modeling
Energy Technology Data Exchange (ETDEWEB)
Tumeo, M.A.
1988-01-01
Development of a new mathematical technique to include stochasticity in environmental models used of resource management and public health risk analysis is reported. The technique is based on the expansion of basic governing equations to include stochastic terms. The stochastic terms are then separated from the non-fluctuating terms, and the resulting set of equations solved simultaneously. The solutions of this set of equations are used to calculate the moments of the output variables. In addition, the moments are used in conjunction with the Fokker-Planck Equation to produce an analytical solution for the probability density functions of the dependent variables. The technique is applied in two examples. The first example is an application to the Streeter-Phelps BOD-OD Equations. Results of the analysis are compared to field data as well as to results of a Monte Carlo model and to moments derived using a Stochastic Differential Equations approach. The second application involves analysis of health risks associated with waterborne diseases. Results are compared to the results of a Monte Carlo simulation of a similar system of equations.
Persistence for stochastic difference equations: A mini-review
Schreiber, Sebastian J
2011-01-01
Understanding under what conditions populations, whether they be plants, animals, or viral particles, persist is an issue of theoretical and practical importance in population biology. Both biotic interactions and environmental fluctuations are key factors that can facilitate or disrupt persistence. One approach to examining the interplay between these deterministic and stochastic forces is the construction and analysis of stochastic difference equations $X_{t+1}=F(X_t,\\xi_{t+1})$ where $X_t \\in \\R^k$ represents the state of the populations and $\\xi_1,\\xi_2,...$ is a sequence of random variables representing environmental stochasticity. In the analysis of these stochastic models, many theoretical population biologists are interested in whether the models are bounded and persistent. Here, boundedness asserts that asymptotically $X_t$ tends to remain in compact sets. In contrast, persistence requires that $X_t$ tends to be "repelled" by some "extinction set" $S_0\\subset \\R^k$. Here, results on both of these pro...
Energy Technology Data Exchange (ETDEWEB)
Li, Xiao, E-mail: lixiao1228@163.com; Ji, Guanghua, E-mail: ghji@bnu.edu.cn; Zhang, Hui, E-mail: hzhang@bnu.edu.cn
2015-02-15
We use the stochastic Cahn–Hilliard equation to simulate the phase transitions of the macromolecular microsphere composite (MMC) hydrogels under a random disturbance. Based on the Flory–Huggins lattice model and the Boltzmann entropy theorem, we develop a reticular free energy suit for the network structure of MMC hydrogels. Taking the random factor into account, with the time-dependent Ginzburg-Landau (TDGL) mesoscopic simulation method, we set up a stochastic Cahn–Hilliard equation, designated herein as the MMC-TDGL equation. The stochastic term in the equation is constructed appropriately to satisfy the fluctuation-dissipation theorem and is discretized on a spatial grid for the simulation. A semi-implicit difference scheme is adopted to numerically solve the MMC-TDGL equation. Some numerical experiments are performed with different parameters. The results are consistent with the physical phenomenon, which verifies the good simulation of the stochastic term.
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.
Primordial Fluctuations within Teleparallelism
Wu, Yi-Peng
2011-01-01
To study the primordial fluctuations for gravity within teleparallelism, we perform a 3+1 decomposition of the vierbein field which makes the metric tensor identical to the ADM formulation. The torsion scalar is differ by a total divergence from the Ricci scalar under this representation as a consistent result. Using the unitary gauge of the scalar field, we obtain the same quadratic actions for both scalar and tensor perturbations as the standard ones in the minimal torsion scalar coupling. When the same scenario is applied to the higher-order action, $f(T)$ gravity, we find that the scalar-tensor coupling in the Einstein frame becomes a total divergence. Consequently, the cosmological perturbations are the same for $f(T)$ and $f(R)$ gravity theories in the earlier universe although the behaviors of the late time cosmic acceleration are apparently different.
Stochastic variability of large-scale oceanic flows above topography anomalies
Venaille, Antoine; Molines, J -M; Barnier, B
2011-01-01
Large-scale oceanic currents show large fluctuations at decadal, centennial and even millennial time scales. Here, we describe a new stochastic variability mechanism which is genuinely internal to the ocean, i.e. not due to fluctuations in atmospheric forcing. The key ingredient is the existence of closed contours of bottom topography surrounded by a stirring region of enhanced eddy activity. This configuration leads to the formation of a robust but highly variable vortex above the topography anomaly. The vortex dynamics integrates the white noise forcing of oceanic eddies into a red noise signal for the large scale volume transport of the vortex. The fluctuations of the transport of the Zapiola anticyclone (100 Sv) in the Argentine basin are argued to be an example of such eddy-driven stochastic variability, on the basis of a 310 years long simulation of a comprehensive ocean model run driven by a repeated-year forcing.
Extreme reaction times determine fluctuation scaling in human color vision
Medina, José M.; Díaz, José A.
2016-11-01
In modern mental chronometry, human reaction time defines the time elapsed from stimulus presentation until a response occurs and represents a reference paradigm for investigating stochastic latency mechanisms in color vision. Here we examine the statistical properties of extreme reaction times and whether they support fluctuation scaling in the skewness-kurtosis plane. Reaction times were measured for visual stimuli across the cardinal directions of the color space. For all subjects, the results show that very large reaction times deviate from the right tail of reaction time distributions suggesting the existence of dragon-kings events. The results also indicate that extreme reaction times are correlated and shape fluctuation scaling over a wide range of stimulus conditions. The scaling exponent was higher for achromatic than isoluminant stimuli, suggesting distinct generative mechanisms. Our findings open a new perspective for studying failure modes in sensory-motor communications and in complex networks.
The Measure-theoretic Identity Underlying Transient Fluctuation Theorems
Shargel, Benjamin Hertz
2010-01-01
We prove a measure-theoretic identity that underlies all transient fluctuation theorems (TFTs) for entropy production and dissipated work in inhomogeneous deterministic and stochastic processes, including those of Evans and Searles, Crooks, and Seifert. The identity is used to deduce a tautological physical interpretation of TFTs in terms of the arrow of time, and its generality reveals that the self-inverse nature of the various trajectory and process transformations historically relied upon to prove TFTs, while necessary for these theorems from a physical standpoint, is not necessary from a mathematical one. The moment generating functions of thermodynamic variables appearing in the identity are shown to converge in general only in a vertical strip in the complex plane, with the consequence that a TFT that holds over arbitrary timescales may fail to give rise to an asymptotic fluctuation theorem for any possible speed of the corresponding large deviation principle. The case of strongly biased birth-death ch...
Absorbing State Phase Transition with Competing Quantum and Classical Fluctuations
Marcuzzi, Matteo; Buchhold, Michael; Diehl, Sebastian; Lesanovsky, Igor
2016-06-01
Stochastic processes with absorbing states feature examples of nonequilibrium universal phenomena. While the classical regime has been thoroughly investigated in the past, relatively little is known about the behavior of these nonequilibrium systems in the presence of quantum fluctuations. Here, we theoretically address such a scenario in an open quantum spin model which, in its classical limit, undergoes a directed percolation phase transition. By mapping the problem to a nonequilibrium field theory, we show that the introduction of quantum fluctuations stemming from coherent, rather than statistical, spin flips alters the nature of the transition such that it becomes first order. In the intermediate regime, where classical and quantum dynamics compete on equal terms, we highlight the presence of a bicritical point with universal features different from the directed percolation class in a low dimension. We finally propose how this physics could be explored within gases of interacting atoms excited to Rydberg states.
Fluctuation theorem for a deterministic one-particle system
Schmick, Malte; Markus, Mario
2004-12-01
A Duffing oscillator is driven by a sum of N chaotic time series. These time series are solutions of the undriven Duffing equation. It is shown that N=1 is sufficient to render the fluctuation theorem [Gallavotti and Cohen, Phys. Rev. Lett. 74, 2694 (1995); Gallavotti, J. Math. Phys. 41, 4061 (2000); Evans and Searles, Adv. Phys. 51, 1529 (2002)] for the power Jτ averaged within intervals of length τ . In particular, the probabilities p(Jτ) follow a nearly Gaussian distribution. Also, ln[p(Jτ)/p(-Jτ)] versus Jτ can be fitted by strikingly linear functions, the slopes being proportional to τ for large τ . These results indicate that validity of the fluctuation theorem requires neither a many-particle system nor a stochastic process, which are requirements used in previous works.
Transport generated by dichotomous fluctuations
Kula, J.; Czernik, T.; łuczka, J.
1996-02-01
Overdamped motion of Brownian particles in spatially periodic potentials and subjected to fluctuations modeled by asymmetric exponentially correlated two-state noise of zero mean value is considered. The probability current is presented in a closed form and analyzed in asymptotic regimes of very long and very short correlation times of the fluctuations. Explicit results are obtained for a piecewise linear potential. The role of correlations and temporal asymmetry of fluctuations is elucidated.
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.
Stochastic Models of Vesicular Sorting in Cellular Organelles
Vagne, Quentin
2016-01-01
The proper sorting of membrane components by regulated exchange between cellular organelles is crucial to intra-cellular 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 leads to fast sorting, but results in a broad size distribution of sorted compartments dominated by small entities. High ratio values result in two well defined sorted compartments but is exponentially slow. Our results suggests 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 organizati...
Environmental versus demographic variability in stochastic predator-prey models
Dobramysl, U.; Täuber, U. C.
2013-10-01
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.
Stochastic dynamics of active swimmers in linear flows
Sandoval, Mario; Subramanian, Ganesh; Lauga, Eric
2014-01-01
Most classical work on the hydrodynamics of low-Reynolds-number swimming addresses deterministic locomotion in quiescent environments. Thermal fluctuations in fluids are known to lead to a Brownian loss of the swimming direction. As most cells or synthetic swimmers are immersed in external flows, we consider theoretically in this paper the stochastic dynamics of a model active particle (a self-propelled sphere) in a steady general linear flow. The stochasticity arises both from translational diffusion in physical space, and from a combination of rotary diffusion and run-and-tumble dynamics in orientation space. We begin by deriving a general formulation for all components of the long-time mean square displacement tensor for a swimmer with a time-dependent swimming velocity and whose orientation decorrelates due to rotary diffusion alone. This general framework is applied to obtain the convectively enhanced mean-squared displacements of a steadily-swimming particle in three canonical linear flows (extension, s...
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...
Pham, T. M.; Virchenko, Yu. P.
2016-08-01
We completely investigate the stationary distribution density in the space of relative concentrations for the three-parameter stochastic Horsthemke-Lefever model of a binary self-catalyzed cyclic chemical reaction with perturbations produced by thermal fluctuations of reagents taken into account. This model is a stationary diffusion random process generated by a stochastic equation with the Stratonovich differential, whose marginal distribution density admits a bifurcation restructuring from the unimodal to the bimodal phase with increasing noise intensity, which is interpreted physically as a dynamical phase transition induced by fluctuations in the system.
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...
Stochastic Engine Convergence Diagnostics
Energy Technology Data Exchange (ETDEWEB)
Glaser, R
2001-12-11
The stochastic engine uses a Markov Chain Monte Carlo (MCMC) sampling device to allow an analyst to construct a reasonable estimate of the state of nature that is consistent with observed data and modeling assumptions. The key engine output is a sample from the posterior distribution, which is the conditional probability distribution of the state of nature, given the data. In applications the state of nature may refer to a complicated, multi-attributed feature like the lithology map of a volume of earth, or to a particular related parameter of interest, say the centroid of the largest contiguous sub-region of specified lithology type. The posterior distribution, which we will call f, can be thought of as the best stochastic description of the state of nature that incorporates all pertinent physical and theoretical models as well as observed data. Characterization of the posterior distribution is the primary goal in the Bayesian statistical paradigm. In applications of the stochastic engine, however, analytical calculation of the posterior distribution is precluded, and only a sample drawn from the distribution is feasible. The engine's MCMC technique, which employs the Metropolis-Hastings algorithm, provides a sample in the form of a sequence (chain) of possible states of nature, x{sup (1)}, x{sup (2)}, ..., x{sup (T)}, .... The sequencing is motivated by consideration of comparative likelihoods of the data. Asymptotic results ensure that the sample ultimately spans the entire posterior distribution and reveals the actual state frequencies that characterize the posterior. In mathematical jargon, the sample is an ergodic Markov chain with stationary distribution f. What this means is that once the chain has gone a sufficient number of steps, T{sub 0}, the (unconditional) distribution of the state, x{sup (T)}, at any step T {ge} T{sub 0} is the same (i.e., is ''stationary''), and is the posterior distribution, f. We call T{sub 0} the &apos
Stochastic reconstruction of sandstones
Manwart; Torquato; Hilfer
2000-07-01
A simulated annealing algorithm is employed to generate a stochastic model for a Berea sandstone and a Fontainebleau sandstone, with each a prescribed two-point probability function, lineal-path function, and "pore size" distribution function, respectively. We find that the temperature decrease of the annealing has to be rather quick to yield isotropic and percolating configurations. A comparison of simple morphological quantities indicates good agreement between the reconstructions and the original sandstones. Also, the mean survival time of a random walker in the pore space is reproduced with good accuracy. However, a more detailed investigation by means of local porosity theory shows that there may be significant differences of the geometrical connectivity between the reconstructed and the experimental samples.
Crystallization by stochastic flips
Bodini, Olivier; Fernique, Thomas; Regnault, Damien
2010-04-01
Tilings are often used as a toy model for quasicrystals, with the ground states corresponding to the tilings satisfying some local properties (matching rules). In this context, a challenging problem is to provide a theory for quasicrystals growth. One of the proposed theories is the relaxation process. One assumes that the entropy of a tiling increases with the number of tilings which can be formed with the same tiles, while its energy is proportional to the ratio of satisfied matching rules. Then, by starting from an entropically stabilized tiling at high temperature and by decreasing the temperature, the phason flips which decrease (resp. increase) the energy would become more and more favoured (resp. inhibited). Ideally, the tiling eventually satisfies all the matching rules, and thus shows a quasicrystalline structure. This paper describes a stochastic process inspired by this and discusses its convergence rate.
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.
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.
Real gas effects on receptivity to kinetic fluctuations
Tumin, Anatoli; Edwards, Luke
2016-11-01
Receptivity of high-speed boundary layers is considered within the framework of fluctuating hydrodynamics where stochastic forcing is introduced through fluctuating shear stress and heat flux stemming from kinetic fluctuations (thermal noise). The forcing generates unstable modes whose amplification downstream and may lead to transition. An example of high-enthalpy (16 . 53 MJ / kg) boundary layer at relatively low wall temperatures (Tw = 1000 K - 3000 K), free stream temperature (Te = 834 K), and low pressure (0 . 0433 atm) is considered. Dissociation at the chosen flow parameters is still insignificant. The stability and receptivity analyses are carried out using a solver for calorically perfect gas with effective Prandtl number and specific heats ratio. The receptivity phenomenon is unchanged by the inclusion of real gas effects in the mean flow profiles. This is attributed to the fact that the mechanism for receptivity to kinetic fluctuations is localized near the upper edge of the boundary layer. Amplitudes of the generated wave packets are larger downstream in the case including real gas effects. It was found that spectra in both cases include supersonic second Mack unstable modes despite the temperature ratio Tw /Te > 1 . Supported by AFOSR.
Cude, W Nathan; Prevatte, Carson W; Hadden, Mary K; May, Amanda L; Smith, Russell T; Swain, Caleb L; Campagna, Shawn R; Buchan, Alison
2015-02-01
The marine roseobacter Phaeobacter sp. strain Y4I synthesizes the blue antimicrobial secondary metabolite indigoidine when grown in a biofilm or on agar plates. Prior studies suggested that indigoidine production may be, in part, regulated by cell-to-cell communication systems. Phaeobacter sp. strain Y4I possesses two luxR and luxI homologous N-acyl-L-homoserine lactone (AHL)-mediated cell-to-cell communication systems, designated pgaRI and phaRI. We show here that Y4I produces two dominantAHLs, the novel monounsaturated N-(3-hydroxydodecenoyl)-L-homoserine lactone (3OHC(12:1)-HSL) and the relatively common N-octanoyl-L-homoserine lactone (C8-HSL), and provide evidence that they are synthesized by PhaI and PgaI, respectively.A Tn5 insertional mutation in either genetic locus results in the abolishment (pgaR::Tn5) or reduction (phaR::Tn5) of pigment production. Motility defects and denser biofilms were also observed in these mutant backgrounds, suggesting an overlap in the functional roles of these systems. Production of the AHLs occurs at distinct points during growth on an agar surface and was determined by isotope dilution high-performance liquid chromatography–tandem mass spectrometry (ID-HPLC-MS/MS) analysis.Within 2 h of surface inoculation, only 3OHC(12:1)-HSL was detected in agar extracts. As surface-attached cells became established (at approximately 10 h), the concentration of 3OHC(12:1)-HSL decreased, and the concentration of C8-HSL increased rapidly over 14 h.After longer (>24-h) establishment periods, the concentrations of the two AHLs increased to and stabilized at approximately 15 nM and approximately 600 nM for 3OHC12:1-HSL and C8-HSL, respectively. In contrast, the total amount of indigoidine increased steadily from undetectable to 642 Mby 48 h. Gene expression profiles of the AHL and indigoidine synthases (pgaI, phaI, and igiD) were consistent with their metabolite profiles. These data provide evidence that pgaRI and phaRI play overlapping roles
Stochastic dynamic equations on general time scales
Directory of Open Access Journals (Sweden)
Martin Bohner
2013-02-01
Full Text Available In this article, we construct stochastic integral and stochastic differential equations on general time scales. We call these equations stochastic dynamic equations. We provide the existence and uniqueness theorem for solutions of stochastic dynamic equations. The crucial tool of our construction is a result about a connection between the time scales Lebesgue integral and the Lebesgue integral in the common sense.
Overview of Stochastic Vehicle Routing Problems
Institute of Scientific and Technical Information of China (English)
郭耀煌; 谢秉磊; 郭强
2002-01-01
Stochastic vehicle routing problems (VRPs) play important roles in logistics, though they have not been studied systematically yet. The paper summaries the definition, properties and classification of stochastic VRPs, makes further discussion about two strategies in stochastic VRPs, and at last overviews dynamic and stochastic VRPs.
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.
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
Frequency Resonance in Stochastic Systems
Institute of Scientific and Technical Information of China (English)
钱敏; 张雪娟
2003-01-01
The phenomenon of frequency resonance, which is usually related to deterministic systems, is investigated in stochastic systems. We show that for those autonomous systems driven only by white noise, if the output power spectrum exhibits a nonzero peak frequency, then applying a periodic signel just on this noise-induced central frequency can also induce a resonance phenomenon, which we call the frequency stochastic resonance. The effect of such a resonance in a coupled stochastic system is shown to be much better than that in a single-oscillator system.
Uniqueness of stochastic entropy solutions for stochastic balance laws with Lipschitz fluxes
Wei, Jinlong; Liu, Bin
2014-01-01
In this paper, we consider a stochastic balance law with a Lipschitz flux and gain the uniqueness for stochastic entropy solutions. The argument is supported by the stochastic kinetic formulation, the It\\^{o} formula and the regularization techniques. Furthermore, as an application, we derive the uniqueness of stochastic entropy solutions for stochastic porous media type equations.
The importance of stochastic transitions for the origin of life.
Higgs, Paul G; Wu, Meng
2012-10-01
We discuss the origin of life in terms of an RNA World scenario in which the creation of autocatalytic sequences is the key step. Our computational models illustrate that life arises by a rare stochastic event that occurs due to spatially localized concentration fluctuations. This allows the chemical system to jump from a non-living state with very low ribozyme concentration to a living state that is controlled by ribozymes. Once the living state is established locally, it can spread deterministically through the rest of the system. These are generic features also possessed by more complex models with a greater degree of chemical realism.
Large amplitude motion with a stochastic mean-field approach
Directory of Open Access Journals (Sweden)
Yilmaz Bulent
2012-12-01
Full Text Available In the stochastic mean-field approach, an ensemble of initial conditions is considered to incorporate correlations beyond the mean-field. Then each starting point is propagated separately using the Time-Dependent Hartree-Fock equation of motion. This approach provides a rather simple tool to better describe fluctuations compared to the standard TDHF. Several illustrations are presented showing that this theory can be rather effective to treat the dynamics close to a quantum phase transition. Applications to fusion and transfer reactions demonstrate the great improvement in the description of mass dispersion.
Stochastic pumping of heat: approaching the Carnot efficiency.
Segal, Dvira
2008-12-31
Random noise can generate a unidirectional heat current across asymmetric nano-objects in the absence (or against) a temperature gradient. We present a minimal model for a molecular-level stochastic heat pump that may operate arbitrarily close to the Carnot efficiency. The model consists a fluctuating molecular unit coupled to two solids characterized by distinct phonon spectral properties. Heat pumping persists for a broad range of system and bath parameters. Furthermore, by filtering the reservoirs' phonons the pump efficiency can approach the Carnot limit.
Diffusive dynamics and stochastic models of turbulent axisymmetric wakes
Rigas, G; Brackston, R D; Morrison, J F
2015-01-01
A modelling methodology to reproduce the experimental measurements of a turbulent flow under the presence of symmetry is presented. The flow is a three-dimensional wake generated by an axisymmetric body. We show that the dynamics of the turbulent wake- flow can be assimilated by a nonlinear two-dimensional Langevin equation, the deterministic part of which accounts for the broken symmetries which occur at the laminar and transitional regimes at low Reynolds numbers and the stochastic part of which accounts for the turbulent fluctuations. Comparison between theoretical and experimental results allows the extraction of the model parameters.
Stochastic differential equation approach for waves in a random medium.
Dimitropoulos, Dimitris; Jalali, Bahram
2009-03-01
We present a mathematical approach that simplifies the theoretical treatment of electromagnetic localization in random media and leads to closed-form analytical solutions. Starting with the assumption that the dielectric permittivity of the medium has delta-correlated spatial fluctuations, and using Ito's lemma, we derive a linear stochastic differential equation for a one-dimensional random medium. The equation leads to localized wave solutions. The localized wave solutions have a localization length that scales as L approximately omega(-2) for low frequencies whereas in the high-frequency regime this length behaves as L approximately omega(-2/3) .
Fluctuating Selection in the Moran
Dean, Antony M.; Lehman, Clarence; Yi, Xiao
2017-01-01
Contrary to classical population genetics theory, experiments demonstrate that fluctuating selection can protect a haploid polymorphism in the absence of frequency dependent effects on fitness. Using forward simulations with the Moran model, we confirm our analytical results showing that a fluctuating selection regime, with a mean selection coefficient of zero, promotes polymorphism. We find that increases in heterozygosity over neutral expectations are especially pronounced when fluctuations are rapid, mutation is weak, the population size is large, and the variance in selection is big. Lowering the frequency of fluctuations makes selection more directional, and so heterozygosity declines. We also show that fluctuating selection raises dn/ds ratios for polymorphism, not only by sweeping selected alleles into the population, but also by purging the neutral variants of selected alleles as they undergo repeated bottlenecks. Our analysis shows that randomly fluctuating selection increases the rate of evolution by increasing the probability of fixation. The impact is especially noticeable when the selection is strong and mutation is weak. Simulations show the increase in the rate of evolution declines as the rate of new mutations entering the population increases, an effect attributable to clonal interference. Intriguingly, fluctuating selection increases the dn/ds ratios for divergence more than for polymorphism, a pattern commonly seen in comparative genomics. Our model, which extends the classical neutral model of molecular evolution by incorporating random fluctuations in selection, accommodates a wide variety of observations, both neutral and selected, with economy. PMID:28108586
Fluctuation Relations for Molecular Motors
Lacoste, David; Mallick, Kirone
This review is focused on the application of specific fluctuation relations, such as the Gallavotti-Cohen relation, to ratchet models of a molecular motor. A special emphasis is placed on two-state models such as the flashing ratchet model. We derive the Gallavotti-Cohen fluctuation relation for these models and we discuss some of its implications.
Fluctuation of the Download Network
Institute of Scientific and Technical Information of China (English)
HAN Ding-Ding; LIV Jin-Gao; MA Yu-Gang
2008-01-01
The scaling behaviour of fluctuation for a download network we investigated a few years ago based upon Zhang's Econophysics web page is presented.A power law scaling,namely σ～α exists between the dispersion σ and average flux of the download rates.The fluctuation exponent α is neither 1/2 nor 1,which were claimed as two universal fluctuation classes in previous publication,while it varies from 1/2 to 1 with the time window in which the download data are accumulated.The crossover behaviour of fluctuation exponents can be qualitatively understood by the external driving fluctuation model for a small-size system or a network traffic model which suggests congestion as the origin.
Stochastic analysis of laminated composite plate considering stochastic homogenization problem
Institute of Scientific and Technical Information of China (English)
S. SAKATA; K. OKUDA; K. IKEDA
2015-01-01
This paper discusses a multiscale stochastic analysis of a laminated composite plate consisting of unidirectional fiber reinforced composite laminae. In particular, influence of a microscopic random variation of the elastic properties of component materials on mechanical properties of the laminated plate is investigated. Laminated composites are widely used in civil engineering, and therefore multiscale stochastic analysis of laminated composites should be performed for reliability evaluation of a composite civil structure. This study deals with the stochastic response of a laminated composite plate against the microscopic random variation in addition to a random variation of fiber orientation in each lamina, and stochastic properties of the mechanical responses of the laminated plate is investigated. Halpin-Tsai formula and the homogenization theory-based finite element analysis are employed for estimation of effective elastic properties of lamina, and the classical laminate theory is employed for analysis of a laminated plate. The Monte-Carlo simulation and the first-order second moment method with sensitivity analysis are employed for the stochastic analysis. From the numerical results, importance of the multiscale stochastic analysis for reliability evaluation of a laminated composite structure and applicability of the sensitivity-based approach are discussed.
Armstrong, Cameron R; David, John A; Thompson, John R
2015-07-13
We present a simple numerical model that is used in conjunction with a systematic algorithm for parameter optimization to understand the three-dimensional stochastic intensity dynamics of stimulated Brillouin scattering in a two-mode optical fiber. The primary factors driving the complex dynamics appear to be thermal density fluctuations, transverse pump fluctuations, and asymmetric transverse mode fractions over the beam cross-section.