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.
Intrinsic Simulations between Stochastic Cellular Automata
Directory of Open Access Journals (Sweden)
Pablo Arrighi
2012-08-01
Full Text Available The paper proposes a simple formalism for dealing with deterministic, non-deterministic and stochastic cellular automata in a unifying and composable manner. Armed with this formalism, we extend the notion of intrinsic simulation between deterministic cellular automata, to the non-deterministic and stochastic settings. We then provide explicit tools to prove or disprove the existence of such a simulation between two stochastic cellular automata, even though the intrinsic simulation relation is shown to be undecidable in dimension two and higher. The key result behind this is the caracterization of equality of stochastic global maps by the existence of a coupling between the random sources. We then prove that there is a universal non-deterministic cellular automaton, but no universal stochastic cellular automaton. Yet we provide stochastic cellular automata achieving optimal partial universality.
Energy Technology Data Exchange (ETDEWEB)
Scott, Bobby, R., Ph.D.
2003-06-27
OAK - B135 This project final report summarizes modeling research conducted in the U.S. Department of Energy (DOE), Low Dose Radiation Research Program at the Lovelace Respiratory Research Institute from October 1998 through June 2003. The modeling research described involves critically evaluating the validity of the linear nonthreshold (LNT) risk model as it relates to stochastic effects induced in cells by low doses of ionizing radiation and genotoxic chemicals. The LNT model plays a central role in low-dose risk assessment for humans. With the LNT model, any radiation (or genotoxic chemical) exposure is assumed to increase one¡¯s risk of cancer. Based on the LNT model, others have predicted tens of thousands of cancer deaths related to environmental exposure to radioactive material from nuclear accidents (e.g., Chernobyl) and fallout from nuclear weapons testing. Our research has focused on developing biologically based models that explain the shape of dose-response curves for low-dose radiation and genotoxic chemical-induced stochastic effects in cells. Understanding the shape of the dose-response curve for radiation and genotoxic chemical-induced stochastic effects in cells helps to better understand the shape of the dose-response curve for cancer induction in humans. We have used a modeling approach that facilitated model revisions over time, allowing for timely incorporation of new knowledge gained related to the biological basis for low-dose-induced stochastic effects in cells. Both deleterious (e.g., genomic instability, mutations, and neoplastic transformation) and protective (e.g., DNA repair and apoptosis) effects have been included in our modeling. Our most advanced model, NEOTRANS2, involves differing levels of genomic instability. Persistent genomic instability is presumed to be associated with nonspecific, nonlethal mutations and to increase both the risk for neoplastic transformation and for cancer occurrence. Our research results, based on
Energy Technology Data Exchange (ETDEWEB)
Scott, Bobby, R., Ph.D.
2003-06-27
OAK - B135 This project final report summarizes modeling research conducted in the U.S. Department of Energy (DOE), Low Dose Radiation Research Program at the Lovelace Respiratory Research Institute from October 1998 through June 2003. The modeling research described involves critically evaluating the validity of the linear nonthreshold (LNT) risk model as it relates to stochastic effects induced in cells by low doses of ionizing radiation and genotoxic chemicals. The LNT model plays a central role in low-dose risk assessment for humans. With the LNT model, any radiation (or genotoxic chemical) exposure is assumed to increase one¡¯s risk of cancer. Based on the LNT model, others have predicted tens of thousands of cancer deaths related to environmental exposure to radioactive material from nuclear accidents (e.g., Chernobyl) and fallout from nuclear weapons testing. Our research has focused on developing biologically based models that explain the shape of dose-response curves for low-dose radiation and genotoxic chemical-induced stochastic effects in cells. Understanding the shape of the dose-response curve for radiation and genotoxic chemical-induced stochastic effects in cells helps to better understand the shape of the dose-response curve for cancer induction in humans. We have used a modeling approach that facilitated model revisions over time, allowing for timely incorporation of new knowledge gained related to the biological basis for low-dose-induced stochastic effects in cells. Both deleterious (e.g., genomic instability, mutations, and neoplastic transformation) and protective (e.g., DNA repair and apoptosis) effects have been included in our modeling. Our most advanced model, NEOTRANS2, involves differing levels of genomic instability. Persistent genomic instability is presumed to be associated with nonspecific, nonlethal mutations and to increase both the risk for neoplastic transformation and for cancer occurrence. Our research results, based on
Stochastic cellular automata model for stock market dynamics
Bartolozzi, M.; Thomas, A. W.
2004-04-01
In the present work we introduce a stochastic cellular automata model in order to simulate the dynamics of the stock market. A direct percolation method is used to create a hierarchy of clusters of active traders on a two-dimensional grid. Active traders are characterized by the decision to buy, σi (t)=+1 , or sell, σi (t)=-1 , a stock at a certain discrete time step. The remaining cells are inactive, σi (t)=0 . The trading dynamics is then determined by the stochastic interaction between traders belonging to the same cluster. Extreme, intermittent events, such as crashes or bubbles, are triggered by a phase transition in the state of the bigger clusters present on the grid, where almost all the active traders come to share the same spin orientation. Most of the stylized aspects of the financial market time series, including multifractal proprieties, are reproduced by the model. A direct comparison is made with the daily closures of the S&P500 index.
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...
Handover management in dense cellular networks: A stochastic geometry approach
Arshad, Rabe
2016-07-26
Cellular operators are continuously densifying their networks to cope with the ever-increasing capacity demand. Furthermore, an extreme densification phase for cellular networks is foreseen to fulfill the ambitious fifth generation (5G) performance requirements. Network densification improves spectrum utilization and network capacity by shrinking base stations\\' (BSs) footprints and reusing the same spectrum more frequently over the spatial domain. However, network densification also increases the handover (HO) rate, which may diminish the capacity gains for mobile users due to HO delays. In highly dense 5G cellular networks, HO delays may neutralize or even negate the gains offered by network densification. In this paper, we present an analytical paradigm, based on stochastic geometry, to quantify the effect of HO delay on the average user rate in cellular networks. To this end, we propose a flexible handover scheme to reduce HO delay in case of highly dense cellular networks. This scheme allows skipping the HO procedure with some BSs along users\\' trajectories. The performance evaluation and testing of this scheme for only single HO skipping shows considerable gains in many practical scenarios. © 2016 IEEE.
Error performance analysis in K-tier uplink cellular networks using a stochastic geometric approach
Afify, Laila H.
2015-09-14
In this work, we develop an analytical paradigm to analyze the average symbol error probability (ASEP) performance of uplink traffic in a multi-tier cellular network. The analysis is based on the recently developed Equivalent-in-Distribution approach that utilizes stochastic geometric tools to account for the network geometry in the performance characterization. Different from the other stochastic geometry models adopted in the literature, the developed analysis accounts for important communication system parameters and goes beyond signal-to-interference-plus-noise ratio characterization. That is, the presented model accounts for the modulation scheme, constellation type, and signal recovery techniques to model the ASEP. To this end, we derive single integral expressions for the ASEP for different modulation schemes due to aggregate network interference. Finally, all theoretical findings of the paper are verified via Monte Carlo simulations.
Unified Stochastic Geometry Model for MIMO Cellular Networks with Retransmissions
Afify, Laila H.
2016-10-11
This paper presents a unified mathematical paradigm, based on stochastic geometry, for downlink cellular networks with multiple-input-multiple-output (MIMO) base stations (BSs). The developed paradigm accounts for signal retransmission upon decoding errors, in which the temporal correlation among the signal-to-interference-plus-noise-ratio (SINR) of the original and retransmitted signals is captured. In addition to modeling the effect of retransmission on the network performance, the developed mathematical model presents twofold analysis unification for MIMO cellular networks literature. First, it integrates the tangible decoding error probability and the abstracted (i.e., modulation scheme and receiver type agnostic) outage probability analysis, which are largely disjoint in the literature. Second, it unifies the analysis for different MIMO configurations. The unified MIMO analysis is achieved by abstracting unnecessary information conveyed within the interfering signals by Gaussian signaling approximation along with an equivalent SISO representation for the per-data stream SINR in MIMO cellular networks. We show that the proposed unification simplifies the analysis without sacrificing the model accuracy. To this end, we discuss the diversity-multiplexing tradeoff imposed by different MIMO schemes and shed light on the diversity loss due to the temporal correlation among the SINRs of the original and retransmitted signals. Finally, several design insights are highlighted.
Stochastic Reservoir Characterization Constrained by Seismic Data
Energy Technology Data Exchange (ETDEWEB)
Eide, Alfhild Lien
1999-07-01
In order to predict future production of oil and gas from a petroleum reservoir, it is important to have a good description of the reservoir in terms of geometry and physical parameters. This description is used as input to large numerical models for the fluid flow in the reservoir. With increased quality of seismic data, it is becoming possible to extend their use from the study of large geologic structures such as seismic horizons to characterization of the properties of the reservoir between the horizons. Uncertainties because of the low resolution of seismic data can be successfully handled by means of stochastic modeling, and spatial statistics can provide tools for interpolation and simulation of reservoir properties not completely resolved by seismic data. This thesis deals with stochastic reservoir modeling conditioned to seismic data and well data. Part I presents a new model for stochastic reservoir characterization conditioned to seismic traces. Part II deals with stochastic simulation of high resolution impedance conditioned to measured impedance. Part III develops a new stochastic model for calcite cemented objects in a sandstone background; it is a superposition of a marked point model for the calcites and a continuous model for the background.
A stochastic parameterization for deep convection using cellular automata
Bengtsson, L.; Steinheimer, M.; Bechtold, P.; Geleyn, J.
2012-12-01
Cumulus parameterizations used in most operational weather and climate models today are based on the mass-flux concept which took form in the early 1970's. In such schemes it is assumed that a unique relationship exists between the ensemble-average of the sub-grid convection, and the instantaneous state of the atmosphere in a vertical grid box column. However, such a relationship is unlikely to be described by a simple deterministic function (Palmer, 2011). Thus, because of the statistical nature of the parameterization challenge, it has been recognized by the community that it is important to introduce stochastic elements to the parameterizations (for instance: Plant and Craig, 2008, Khouider et al. 2010, Frenkel et al. 2011, Bentsson et al. 2011, but the list is far from exhaustive). There are undoubtedly many ways in which stochastisity can enter new developments. In this study we use a two-way interacting cellular automata (CA), as its intrinsic nature possesses many qualities interesting for deep convection parameterization. In the one-dimensional entraining plume approach, there is no parameterization of horizontal transport of heat, moisture or momentum due to cumulus convection. In reality, mass transport due to gravity waves that propagate in the horizontal can trigger new convection, important for the organization of deep convection (Huang, 1988). The self-organizational characteristics of the CA allows for lateral communication between adjacent NWP model grid-boxes, and temporal memory. Thus the CA scheme used in this study contain three interesting components for representation of cumulus convection, which are not present in the traditional one-dimensional bulk entraining plume method: horizontal communication, memory and stochastisity. The scheme is implemented in the high resolution regional NWP model ALARO, and simulations show enhanced organization of convective activity along squall-lines. Probabilistic evaluation demonstrate an enhanced spread in
Modeling and Analysis of Cellular Networks using Stochastic Geometry: A Tutorial
Elsawy, Hesham
2016-11-03
This paper presents a tutorial on stochastic geometry (SG) based analysis for cellular networks. This tutorial is distinguished by its depth with respect to wireless communication details and its focus on cellular networks. The paper starts by modeling and analyzing the baseband interference in a baseline single-tier downlink cellular network with single antenna base stations and universal frequency reuse. Then, it characterizes signal-to-interference-plus-noise-ratio (SINR) and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and transmission rate analysis is presented. Although the main focus of the paper is on cellular networks, the presented unified approach applies for other types of wireless networks that impose interference protection around receivers. The paper then extends the unified approach to capture cellular network characteristics (e.g., frequency reuse, multiple antenna, power control, etc.). It also presents numerical examples associated with demonstrations and discussions. To this end, the paper highlights the state-of-the- art research and points out future research directions.
Stochastic Model of Maturation and Vesicular Exchange in Cellular Organelles
Vagne, Quentin
2016-01-01
The dynamical organization of membrane-bound organelles along intracellular transport pathways relies on vesicular exchange between organelles and on biochemical maturation of the organelle content by specific enzymes. The relative importance of each mechanism in controlling organelle dynamics remains controversial, in particular for transport through the Golgi apparatus. Using a stochastic model, we show that full maturation of membrane-bound compartments can be seen as the stochastic escape from a steady-state in which export is dominated by vesicular exchange. We show that full maturation can contribute a significant fraction of the total out-flux for small organelles such as endosomes and Golgi cisternae.
Stochastic fluctuations and distributed control of gene expression impact cellular memory.
Directory of Open Access Journals (Sweden)
Guillaume Corre
Full Text Available Despite the stochastic noise that characterizes all cellular processes the cells are able to maintain and transmit to their daughter cells the stable level of gene expression. In order to better understand this phenomenon, we investigated the temporal dynamics of gene expression variation using a double reporter gene model. We compared cell clones with transgenes coding for highly stable mRNA and fluorescent proteins with clones expressing destabilized mRNA-s and proteins. Both types of clones displayed strong heterogeneity of reporter gene expression levels. However, cells expressing stable gene products produced daughter cells with similar level of reporter proteins, while in cell clones with short mRNA and protein half-lives the epigenetic memory of the gene expression level was completely suppressed. Computer simulations also confirmed the role of mRNA and protein stability in the conservation of constant gene expression levels over several cell generations. These data indicate that the conservation of a stable phenotype in a cellular lineage may largely depend on the slow turnover of mRNA-s and proteins.
Computation of steady-state probability distributions in stochastic models of cellular networks.
Directory of Open Access Journals (Sweden)
Mark Hallen
2011-10-01
Full Text Available Cellular processes are "noisy". In each cell, concentrations of molecules are subject to random fluctuations due to the small numbers of these molecules and to environmental perturbations. While noise varies with time, it is often measured at steady state, for example by flow cytometry. When interrogating aspects of a cellular network by such steady-state measurements of network components, a key need is to develop efficient methods to simulate and compute these distributions. We describe innovations in stochastic modeling coupled with approaches to this computational challenge: first, an approach to modeling intrinsic noise via solution of the chemical master equation, and second, a convolution technique to account for contributions of extrinsic noise. We show how these techniques can be combined in a streamlined procedure for evaluation of different sources of variability in a biochemical network. Evaluation and illustrations are given in analysis of two well-characterized synthetic gene circuits, as well as a signaling network underlying the mammalian cell cycle entry.
Bialecki, Mariusz
2010-01-01
Inspired by extremely simplified view of the earthquakes we propose the stochastic domino cellular automaton model exhibiting avalanches. From elementary combinatorial arguments we derive a set of nonlinear equations describing the automaton. Exact relations between the average parameters of the model are presented. Depending on imposed triggering, the model reproduces both exponential and inverse power statistics of clusters.
Spatial Stochastic Point Models for Reservoir Characterization
Energy Technology Data Exchange (ETDEWEB)
Syversveen, Anne Randi
1997-12-31
The main part of this thesis discusses stochastic modelling of geology in petroleum reservoirs. A marked point model is defined for objects against a background in a two-dimensional vertical cross section of the reservoir. The model handles conditioning on observations from more than one well for each object and contains interaction between objects, and the objects have the correct length distribution when penetrated by wells. The model is developed in a Bayesian setting. The model and the simulation algorithm are demonstrated by means of an example with simulated data. The thesis also deals with object recognition in image analysis, in a Bayesian framework, and with a special type of spatial Cox processes called log-Gaussian Cox processes. In these processes, the logarithm of the intensity function is a Gaussian process. The class of log-Gaussian Cox processes provides flexible models for clustering. The distribution of such a process is completely characterized by the intensity and the pair correlation function of the Cox process. 170 refs., 37 figs., 5 tabs.
Enhancement of cellular memory by reducing stochastic transitions
Acar, Murat; Becskei, Attila; van Oudenaarden, Alexander
2005-05-01
On induction of cell differentiation, distinct cell phenotypes are encoded by complex genetic networks. These networks can prevent the reversion of established phenotypes even in the presence of significant fluctuations. Here we explore the key parameters that determine the stability of cellular memory by using the yeast galactose-signalling network as a model system. This network contains multiple nested feedback loops. Of the two positive feedback loops, only the loop mediated by the cytoplasmic signal transducer Gal3p is able to generate two stable expression states with a persistent memory of previous galactose consumption states. The parallel loop mediated by the galactose transporter Gal2p only increases the expression difference between the two states. A negative feedback through the inhibitor Gal80p reduces the strength of the core positive feedback. Despite this, a constitutive increase in the Gal80p concentration tunes the system from having destabilized memory to having persistent memory. A model reveals that fluctuations are trapped more efficiently at higher Gal80p concentrations. Indeed, the rate at which single cells randomly switch back and forth between expression states was reduced. These observations provide a quantitative understanding of the stability and reversibility of cellular differentiation states.
Characterizing heterogeneous cellular responses to perturbations.
Slack, Michael D; Martinez, Elisabeth D; Wu, Lani F; Altschuler, Steven J
2008-12-01
Cellular populations have been widely observed to respond heterogeneously to perturbation. However, interpreting the observed heterogeneity is an extremely challenging problem because of the complexity of possible cellular phenotypes, the large dimension of potential perturbations, and the lack of methods for separating meaningful biological information from noise. Here, we develop an image-based approach to characterize cellular phenotypes based on patterns of signaling marker colocalization. Heterogeneous cellular populations are characterized as mixtures of phenotypically distinct subpopulations, and responses to perturbations are summarized succinctly as probabilistic redistributions of these mixtures. We apply our method to characterize the heterogeneous responses of cancer cells to a panel of drugs. We find that cells treated with drugs of (dis-)similar mechanism exhibit (dis-)similar patterns of heterogeneity. Despite the observed phenotypic diversity of cells observed within our data, low-complexity models of heterogeneity were sufficient to distinguish most classes of drug mechanism. Our approach offers a computational framework for assessing the complexity of cellular heterogeneity, investigating the degree to which perturbations induce redistributions of a limited, but nontrivial, repertoire of underlying states and revealing functional significance contained within distinct patterns of heterogeneous responses.
Modeling dynamics of HIV infected cells using stochastic cellular automaton
Precharattana, Monamorn; Triampo, Wannapong
2014-08-01
Ever since HIV was first diagnosed in human, a great number of scientific works have been undertaken to explore the biological mechanisms involved in the infection and progression of the disease. Several cellular automata (CA) models have been introduced to gain insights into the dynamics of the disease progression but none of them has taken into account effects of certain immune cells such as the dendritic cells (DCs) and the CD8+ T lymphocytes (CD8+ T cells). In this work, we present a CA model, which incorporates effects of the HIV specific immune response focusing on the cell-mediated immunities, and investigate the interaction between the host immune response and the HIV infected cells in the lymph nodes. The aim of our work is to propose a model more realistic than the one in Precharattana et al. (2010) [10], by incorporating roles of the DCs, the CD4+ T cells, and the CD8+ T cells into the model so that it would reproduce the HIV infection dynamics during the primary phase of HIV infection.
Stochastic Ordering based Carrier-to-Interference Ratio Analysis for the Shotgun Cellular Systems
Madhusudhanan, Prasanna; Youjian,; Liu,; Brown, Timothy X; Baker, Kenneth R
2011-01-01
A simple analytical tool based on stochastic ordering is developed to compare the distributions of carrier-to-interference ratio at the mobile station of two cellular systems where the base stations are distributed randomly according to certain non-homogeneous Poisson point processes. The comparison is conveniently done by studying only the base station densities without having to solve for the distributions of the carrier-to-interference ratio, that are often hard to obtain.
Unified tractable model for downlink MIMO cellular networks using stochastic geometry
Afify, Laila H.
2016-07-26
Several research efforts are invested to develop stochastic geometry models for cellular networks with multiple antenna transmission and reception (MIMO). On one hand, there are models that target abstract outage probability and ergodic rate for simplicity. On the other hand, there are models that sacrifice simplicity to target more tangible performance metrics such as the error probability. Both types of models are completely disjoint in terms of the analytic steps to obtain the performance measures, which makes it challenging to conduct studies that account for different performance metrics. This paper unifies both techniques and proposes a unified stochastic-geometry based mathematical paradigm to account for error probability, outage probability, and ergodic rates in MIMO cellular networks. The proposed model is also unified in terms of the antenna configurations and leads to simpler error probability analysis compared to existing state-of-the-art models. The core part of the analysis is based on abstracting unnecessary information conveyed within the interfering signals by assuming Gaussian signaling. To this end, the accuracy of the proposed framework is verified against state-of-the-art models as well as system level simulations. We provide via this unified study insights on network design by reflecting system parameters effect on different performance metrics. © 2016 IEEE.
Barik, Debashis; Ball, David A; Peccoud, Jean; Tyson, John J
2016-12-01
The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization) of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally.
de la Cruz, Roberto; Spill, Fabian; Alarcón, Tomás
2016-01-01
We propose a modelling framework to analyse the stochastic behaviour of heterogeneous, multi-scale cellular populations. We illustrate our methodology with a particular example in which we study a population with an oxygen-regulated proliferation rate. Our formulation is based on an age-dependent stochastic process. Cells within the population are characterised by their age. The age-dependent (oxygen-regulated) birth rate is given by a stochastic model of oxygen-dependent cell cycle progression. We then formulate an age-dependent birth-and-death process, which dictates the time evolution of the cell population. The population is under a feedback loop which controls its steady state size: cells consume oxygen which in turns fuels cell proliferation. We show that our stochastic model of cell cycle progression allows for heterogeneity within the cell population induced by stochastic effects. Such heterogeneous behaviour is reflected in variations in the proliferation rate. Within this set-up, we have established...
González-Díaz, Humberto; Uriarte, Eugenio
2005-04-05
Stochastic moments may be applied as molecular descriptors in quantitative structure-activity relationship (QSAR) studies for small molecules (H. González-Dìaz et al., Journal of Molecular Modeling, 2002, Vol. 8, pp. 237-245; 2003, Vol. 9, pp. 395-407). However, applications in the field of biopolymers are less known. Recently, the MARCH-INSIDE approach has been generalized to encode structural features of proteins and other biopolymers (H. González-Dáaz et al., Bioinformatics, 2003, Vol. 19, pp. 2079-2087; Bioorganic & Medicinal Chemistry Letters, 2004, Vol. 14, pp. 4691-4695; Polymers, 2004, Vol. 45, pp. 3845-3853; Bioorganic & Medicinal Chemistry, 2005, Vol. 13, pp. 323-331). The present article attempts to extend this research by introducing for the first time stochastic moments for a surface road map of viral proteins. These moments are afterward used to seek a model that predicts the cellular receptor for human rhinoviruses. The model correctly classified 100% of 10 viruses binding to low-density lipoprotein receptor (LDLR) and 88.9% of 9 viruses binding to the intracellular adhesion molecule (ICAM) receptors in training. The same results have been obtained in four cross-validation experiments using a resubstitution technique. The present model favorably compares, in terms of complexity, with other previously reported based on entropy considerations, and offers a quantitative basis for the visual rule previously reported by Vlasak et al.
Stochastic narrow escape in molecular and cellular biology analysis and applications
Holcman, David
2015-01-01
This book covers recent developments in the non-standard asymptotics of the mathematical narrow escape problem in stochastic theory, as well as applications of the narrow escape problem in cell biology. The first part of the book concentrates on mathematical methods, including advanced asymptotic methods in partial equations, and is aimed primarily at applied mathematicians and theoretical physicists who are interested in biological applications. The second part of the book is intended for computational biologists, theoretical chemists, biochemists, biophysicists, and physiologists. It includes a summary of output formulas from the mathematical portion of the book and concentrates on their applications in modeling specific problems in theoretical molecular and cellular biology. Critical biological processes, such as synaptic plasticity and transmission, activation of genes by transcription factors, or double-strained DNA break repair, are controlled by diffusion in structures that have both large and small sp...
Strong Attractors in Stochastic Adaptive Networks: Emergence and Characterization
Santos, Augusto Almeida; Krishnan, Ramayya; Moura, José M F
2016-01-01
We propose a family of models to study the evolution of ties in a network of interacting agents by reinforcement and penalization of their connections according to certain local laws of interaction. The family of stochastic dynamical systems, on the edges of a graph, exhibits \\emph{good} convergence properties, in particular, we prove a strong-stability result: a subset of binary matrices or graphs -- characterized by certain compatibility properties -- is a global almost sure attractor of the family of stochastic dynamical systems. To illustrate finer properties of the corresponding strong attractor, we present some simulation results that capture, e.g., the conspicuous phenomenon of emergence and downfall of leaders in social networks.
In-Band α-Duplex Scheme for Cellular Networks: A Stochastic Geometry Approach
Alammouri, Ahmad
2016-07-13
In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization and efficiency. However, the penetration of FD communications to the cellular networks domain is challenging due to the imposed uplink/downlink interference. This paper presents a tractable framework, based on stochastic geometry, to study FD communications in cellular networks. Particularly, we assess the FD communications effect on the network performance and quantify the associated gains. The study proves the vulnerability of the uplink to the downlink interference and shows that FD rate gains harvested in the downlink (up to 97%) come at the expense of a significant degradation in the uplink rate (up to 94%). Therefore, we propose a novel fine-grained duplexing scheme, denoted as -duplex scheme, which allows a partial overlap between the uplink and the downlink frequency bands. We derive the required conditions to harvest rate gains from the -duplex scheme and show its superiority to both the FD and half-duplex (HD) schemes. In particular, we show that the -duplex scheme provides a simultaneous improvement of 28% for the downlink rate and 56% for the uplink rate. Finally, we show that the amount of the overlap can be optimized based on the network design objective.
Modeling Cellular Networks with Full Duplex D2D Communication: A Stochastic Geometry Approach
Ali, Konpal S.
2016-08-24
Full-duplex (FD) communication is optimistically promoted to double the spectral efficiency if sufficient self-interference cancellation (SIC) is achieved. However, this is not true when deploying FD-communication in a large-scale setup due to the induced mutual interference. Therefore, a large-scale study is necessary to draw legitimate conclusions about gains associated with FD-communication. This paper studies the FD operation for underlay device-to-device (D2D) communication sharing the uplink resources in cellular networks. We propose a disjoint fine-tuned selection criterion for the D2D and FD modes of operation. Then, we develop a tractable analytical paradigm, based on stochastic geometry, to calculate the outage probability and rate for cellular and D2D users. The results reveal that even in the case of perfect SIC, due to the increased interference injected to the network by FD-D2D communication, having all proximity UEs transmit in FD-D2D is not beneficial for the network. However, if the system parameters are carefully tuned, non-trivial network spectral-efficiency gains (64% shown) can be harvested. We also investigate the effects of imperfect SIC and D2D-link distance distribution on the harvested FD gains.
2017-01-01
Mathematical models of cardiac electrical excitation are increasingly complex, with multiscale models seeking to represent and bridge physiological behaviours across temporal and spatial scales. The increasing complexity of these models makes it computationally expensive to both evaluate long term (more than 60 s) behaviour and determine sensitivity of model outputs to inputs. This is particularly relevant in models of atrial fibrillation (AF), where individual episodes last from seconds to days, and interepisode waiting times can be minutes to months. Potential mechanisms of transition between sinus rhythm and AF have been identified but are not well understood, and it is difficult to simulate AF for long periods of time using state-of-the-art models. In this study, we implemented a Moe-type cellular automaton on a novel, topologically equivalent surface geometry of the left atrium. We used the model to simulate stochastic initiation and spontaneous termination of AF, arising from bursts of spontaneous activation near pulmonary veins. The simplified representation of atrial electrical activity reduced computational cost, and so permitted us to investigate AF mechanisms in a probabilistic setting. We computed large numbers (approx. 105) of sample paths of the model, to infer stochastic initiation and termination rates of AF episodes using different model parameters. By generating statistical distributions of model outputs, we demonstrated how to propagate uncertainties of inputs within our microscopic level model up to a macroscopic level. Lastly, we investigated spontaneous termination in the model and found a complex dependence on its past AF trajectory, the mechanism of which merits future investigation. PMID:28356539
Roh, Min K; Daigle, Bernie J; Gillespie, Dan T; Petzold, Linda R
2011-12-21
In recent years there has been substantial growth in the development of algorithms for characterizing rare events in stochastic biochemical systems. Two such algorithms, the state-dependent weighted stochastic simulation algorithm (swSSA) and the doubly weighted SSA (dwSSA) are extensions of the weighted SSA (wSSA) by H. Kuwahara and I. Mura [J. Chem. Phys. 129, 165101 (2008)]. The swSSA substantially reduces estimator variance by implementing system state-dependent importance sampling (IS) parameters, but lacks an automatic parameter identification strategy. In contrast, the dwSSA provides for the automatic determination of state-independent IS parameters, thus it is inefficient for systems whose states vary widely in time. We present a novel modification of the dwSSA--the state-dependent doubly weighted SSA (sdwSSA)--that combines the strengths of the swSSA and the dwSSA without inheriting their weaknesses. The sdwSSA automatically computes state-dependent IS parameters via the multilevel cross-entropy method. We apply the method to three examples: a reversible isomerization process, a yeast polarization model, and a lac operon model. Our results demonstrate that the sdwSSA offers substantial improvements over previous methods in terms of both accuracy and efficiency.
A Study on Stochastic Thermal Characterization of Electronic Packages
Directory of Open Access Journals (Sweden)
Zakaria El Haddad
2016-08-01
Full Text Available Insofar as the electronics can be found now in several applications of multiple domains, we have tried to highlight in this study that, those systems must be based on unquestionable reliability and meet the needs of the external environment. Starting from the unit "°c / w" concerning the thermal resistance from the gap between junction temperature and a reference temperature, we have tried to compare the thermal performance of electronic packages taking into consideration the thermal management. Our approach is based on the Monte Carlo simulation and the stochastic characterization of the QFN. From the norm of normalization, we have obtained standardized data sheets allowing accurate comparisons of the thermal performance of electronic packages as produced by different manufacturers. Our numerical model through simulation, prototyping concerning the design involves the JEDEC recommendations, which we consider a very interesting alternative. Through the deterministic analysis, we conducted an analysis from the Matlab program parameters, which control the Ansys software, the results were processed by statistical techniques to evaluate the times of the thermal resistance of the QFN. That is why we must consider the electronic package (encapsulating the integrated circuit, through the printed circuit board (PCB to ensure the junction temperature maintenance and avoid the dissipation of the heat. Also our process was based on the union of the finite element method to the Monte Carlo simulation and stochastic characterization of the QFN
CellLab-CTS 2015: continuous-time stochastic cellular automaton modeling using Landlab
Tucker, Gregory E.; Hobley, Daniel E. J.; Hutton, Eric; Gasparini, Nicole M.; Istanbulluoglu, Erkan; Adams, Jordan M.; Siddartha Nudurupati, Sai
2016-02-01
CellLab-CTS 2015 is a Python-language software library for creating two-dimensional, continuous-time stochastic (CTS) cellular automaton models. The model domain consists of a set of grid nodes, with each node assigned an integer state code that represents its condition or composition. Adjacent pairs of nodes may undergo transitions to different states, according to a user-defined average transition rate. A model is created by writing a Python code that defines the possible states, the transitions, and the rates of those transitions. The code instantiates, initializes, and runs one of four object classes that represent different types of CTS models. CellLab-CTS provides the option of using either square or hexagonal grid cells. The software provides the ability to treat particular grid-node states as moving particles, and to track their position over time. Grid nodes may also be assigned user-defined properties, which the user can update after each transition through the use of a callback function. As a component of the Landlab modeling framework, CellLab-CTS models take advantage of a suite of Landlab's tools and capabilities, such as support for standardized input and output.
Elsawy, Hesham
2014-08-01
Using stochastic geometry, we develop a tractable uplink modeling paradigm for outage probability and spectral efficiency in both single and multi-tier cellular wireless networks. The analysis accounts for per user equipment (UE) power control as well as the maximum power limitations for UEs. More specifically, for interference mitigation and robust uplink communication, each UE is required to control its transmit power such that the average received signal power at its serving base station (BS) is equal to a certain threshold ρo. Due to the limited transmit power, the UEs employ a truncated channel inversion power control policy with a cutoff threshold of ρo. We show that there exists a transfer point in the uplink system performance that depends on the following tuple: BS intensity λ, maximum transmit power of UEs Pu, and ρo. That is, when Pu is a tight operational constraint with respect to (w.r.t.) λ and ρo, the uplink outage probability and spectral efficiency highly depend on the values of λ and ρo. In this case, there exists an optimal cutoff threshold ρ*o, which depends on the system parameters, that minimizes the outage probability. On the other hand, when Pu is not a binding operational constraint w.r.t. λ and ρo, the uplink outage probability and spectral efficiency become independent of λ and ρo. We obtain approximate yet accurate simple expressions for outage probability and spectral efficiency, which reduce to closed forms in some special cases. © 2002-2012 IEEE.
Characterization of cellular titanium for biomedical applications
Hrabe, Nikolas Wilson
By controlling structural features (relative density, pore size, strut size) of cellular titanium (also known as porous titanium), the mechanical properties can be optimized to reduce the effects of stress shielding currently observed in load-bearing bone replacement implants. Thermal gravimetric analysis of a sacrificial scaffold system lead to important processing modifications in an attempt to meet chemistry requirements for surgical grade titanium not met in previous work. Despite these modifications chemistry did not meet requirements for carbon, nitrogen, or oxygen. Commercially pure titanium (CPTi) porous structures were made over a range of relative densities using laser engineered net shaping (LENS). From monotonic compression tests, yield strength and elastic modulus in the range of bone were achieved but did not scale with relative density as predicted by the Gibson-Ashby analytical model. Compression-compression fatigue resistance was high, as no failures were observed for test stresses up to 133% yield strength, which is thought to be influenced by the dense exterior shell of the samples. Structures were also fabricated over a range of relative densities using selective electron beam melting (SEBM or EBM), and structural, mechanical, and in-vitro properties were measured for three materials (as-built Ti-6A1-4V, Ti-6A1-4V after hot isostatic pressing (HIPing), and as-built CPTi). For structures of all three materials, yield strength and elastic modulus was within the range for bone. Numerical modeling results suggested cell shape and sintered particles on strut surfaces affect the scaling of elastic modulus with relative density and lead to the observed difference from the Gibson-Ashby model. Normalized fatigue strengths at 106 cycles ranged from 0.150.25 for as-built Ti-6A1-4V structures, which is lower than expected. Results for HIPed Ti-6A1-4V structures and CPTi structures suggest that stress concentrations from closed porosity within struts as well
Stability analysis of stochastic delayed cellular neural networks by LMI approach
Energy Technology Data Exchange (ETDEWEB)
Zhu Wenli [Department of Economic Mathematics, South Western University of Finance and Economics, Chengdu 610074 (China)]. E-mail: zhuwenli67@hotmail.com; Hu Jin [School of Applied Mathematics, University of Electronic Science and Technology of China, Chengdu 610054 (China)
2006-07-15
Some sufficient mean square exponential stability conditions for a class of stochastic DCNN model are obtained via the LMI approach. These conditions improve and generalize some existing global asymptotic stability conditions for DCNN model.
Cruz, Roberto de la; Guerrero, Pilar; Spill, Fabian; Alarcón, Tomás
2016-10-21
We propose a modelling framework to analyse the stochastic behaviour of heterogeneous, multi-scale cellular populations. We illustrate our methodology with a particular example in which we study a population with an oxygen-regulated proliferation rate. Our formulation is based on an age-dependent stochastic process. Cells within the population are characterised by their age (i.e. time elapsed since they were born). The age-dependent (oxygen-regulated) birth rate is given by a stochastic model of oxygen-dependent cell cycle progression. Once the birth rate is determined, we formulate an age-dependent birth-and-death process, which dictates the time evolution of the cell population. The population is under a feedback loop which controls its steady state size (carrying capacity): cells consume oxygen which in turn fuels cell proliferation. We show that our stochastic model of cell cycle progression allows for heterogeneity within the cell population induced by stochastic effects. Such heterogeneous behaviour is reflected in variations in the proliferation rate. Within this set-up, we have established three main results. First, we have shown that the age to the G1/S transition, which essentially determines the birth rate, exhibits a remarkably simple scaling behaviour. Besides the fact that this simple behaviour emerges from a rather complex model, this allows for a huge simplification of our numerical methodology. A further result is the observation that heterogeneous populations undergo an internal process of quasi-neutral competition. Finally, we investigated the effects of cell-cycle-phase dependent therapies (such as radiation therapy) on heterogeneous populations. In particular, we have studied the case in which the population contains a quiescent sub-population. Our mean-field analysis and numerical simulations confirm that, if the survival fraction of the therapy is too high, rescue of the quiescent population occurs. This gives rise to emergence of resistance
Stochastic similarities between hydroclimatic processes for variability characterization
Dimitriadis, Panayiotis; Markonis, Yannis; Iliopoulou, Theano; Gournari, Naya; Deligiannis, Ilias; Kastis, Paris; Nasika, Xristina; Lerias, Eleutherios; Moustakis, Yannis; Petsiou, Amalia; Sotiriadou, Alexia; Stefanidis, Eleutherios; Tyrogiannis, Vassilis; Feloni, Elisavet; Koutsoyiannis, Demetris
2016-04-01
The most important hydroclimatic processes such as temperature, dew point, wind, precipitation and river discharges are investigated for their stochastic behaviour on annual scale through several historical records. We investigate the stochastic similarities between them in terms of long-term persistence and we comment on their statistical variability giving emphasis on the last period. Acknowledgement: This research is conducted within the frame of the undergraduate course "Stochastic Methods in Water Resources" of the National Technical University of Athens (NTUA). The School of Civil Engineering of NTUA provided moral support for the participation of the students in the Assembly.
Stochastic simulation of radium-223 dichloride therapy at the sub-cellular level
Gholami, Y.; Zhu, X.; Fulton, R.; Meikle, S.; El-Fakhri, G.; Kuncic, Z.
2015-08-01
Radium-223 dichloride (223Ra) is an alpha particle emitter and a natural bone-seeking radionuclide that is currently used for treating osteoblastic bone metastases associated with prostate cancer. The stochastic nature of alpha emission, hits and energy deposition poses some challenges for estimating radiation damage. In this paper we investigate the distribution of hits to cells by multiple alpha particles corresponding to a typical clinically delivered dose using a Monte Carlo model to simulate the stochastic effects. The number of hits and dose deposition were recorded in the cytoplasm and nucleus of each cell. Alpha particle tracks were also visualized. We found that the stochastic variation in dose deposited in cell nuclei (≃ 40%) can be attributed in part to the variation in LET with pathlength. We also found that ≃ 18% of cell nuclei receive less than one sigma below the average dose per cell (≃ 15.4 Gy). One possible implication of this is that the efficacy of cell kill in alpha particle therapy need not rely solely on ionization clustering on DNA but possibly also on indirect DNA damage through the production of free radicals and ensuing intracellular signaling.
Characterizing economic trends by Bayesian stochastic model specification search
DEFF Research Database (Denmark)
Grassi, Stefano; Proietti, Tommaso
We extend a recently proposed Bayesian model selection technique, known as stochastic model specification search, for characterising the nature of the trend in macroeconomic time series. In particular, we focus on autoregressive models with possibly time-varying intercept and slope and decide...... on whether their parameters are fixed or evolutive. Stochastic model specification is carried out to discriminate two alternative hypotheses concerning the generation of trends: the trend-stationary hypothesis, on the one hand, for which the trend is a deterministic function of time and the short run......, estimated by a suitable Gibbs sampling scheme, provides useful insight on quasi-integrated nature of the specifications selected....
Multiscale study for stochastic characterization of shale samples
Tahmasebi, Pejman; Javadpour, Farzam; Sahimi, Muhammad; Piri, Mohammad
2016-03-01
Characterization of shale reservoirs, which are typically of low permeability, is very difficult because of the presence of multiscale structures. While three-dimensional (3D) imaging can be an ultimate solution for revealing important complexities of such reservoirs, acquiring such images is costly and time consuming. On the other hand, high-quality 2D images, which are widely available, also reveal useful information about shales' pore connectivity and size. Most of the current modeling methods that are based on 2D images use limited and insufficient extracted information. One remedy to the shortcoming is direct use of qualitative images, a concept that we introduce in this paper. We demonstrate that higher-order statistics (as opposed to the traditional two-point statistics, such as variograms) are necessary for developing an accurate model of shales, and describe an efficient method for using 2D images that is capable of utilizing qualitative and physical information within an image and generating stochastic realizations of shales. We then further refine the model by describing and utilizing several techniques, including an iterative framework, for removing some possible artifacts and better pattern reproduction. Next, we introduce a new histogram-matching algorithm that accounts for concealed nanostructures in shale samples. We also present two new multiresolution and multiscale approaches for dealing with distinct pore structures that are common in shale reservoirs. In the multiresolution method, the original high-quality image is upscaled in a pyramid-like manner in order to achieve more accurate global and long-range structures. The multiscale approach integrates two images, each containing diverse pore networks - the nano- and microscale pores - using a high-resolution image representing small-scale pores and, at the same time, reconstructing large pores using a low-quality image. Eventually, the results are integrated to generate a 3D model. The methods
3D printed cellular solid outperforms traditional stochastic foam in long-term mechanical response
Maiti, A.; Small, W.; Lewicki, J. P.; Weisgraber, T. H.; Duoss, E. B.; Chinn, S. C.; Pearson, M. A.; Spadaccini, C. M.; Maxwell, R. S.; Wilson, T. S.
2016-04-01
3D printing of polymeric foams by direct-ink-write is a recent technological breakthrough that enables the creation of versatile compressible solids with programmable microstructure, customizable shapes, and tunable mechanical response including negative elastic modulus. However, in many applications the success of these 3D printed materials as a viable replacement for traditional stochastic foams critically depends on their mechanical performance and micro-architectural stability while deployed under long-term mechanical strain. To predict the long-term performance of the two types of foams we employed multi-year-long accelerated aging studies under compressive strain followed by a time-temperature-superposition analysis using a minimum-arc-length-based algorithm. The resulting master curves predict superior long-term performance of the 3D printed foam in terms of two different metrics, i.e., compression set and load retention. To gain deeper understanding, we imaged the microstructure of both foams using X-ray computed tomography, and performed finite-element analysis of the mechanical response within these microstructures. This indicates a wider stress variation in the stochastic foam with points of more extreme local stress as compared to the 3D printed material, which might explain the latter’s improved long-term stability and mechanical performance.
Maerivoet, S; Immers, B; De Moor, B; Maerivoet, Sven; Logghe, Steven; Immers, Ben; Moor, Bart De
2005-01-01
In this paper, we describe a relation between a microscopic traffic cellular automaton (TCA) model (i.e., the stochastic TCA model of Nagel and Schreckenberg) and the macroscopic first-order hydrodynamic model of Lighthill, Whitham, and Richards (LWR). The innovative aspect of our approach, is that we explicitly derive the LWR's fundamental diagram directly from the STCA's rule set, by assuming a stationarity condition that converts the STCA's rules into a set of linear inequalities. In turn, these constraints define the shape of the fundamental diagram, which is then specified to the LWR model. Application of our methodology to a simulation case study, allows us to compare the tempo-spatial behavior of both models. Our results indicate that, in the presence of noise, the capacity flows in the derived fundamental diagram are overestimations of those of the STCA model. Directly specifying the STCA's capacity flows to the LWR fundamental diagram, effectively remedies most of the mismatches between both approach...
Directory of Open Access Journals (Sweden)
Vahid Reza Ghezavati
2011-01-01
Full Text Available This research defines a new application of mathematical modeling to design a cellular manufacturing system integrated with group scheduling and layout aspects in an uncertain decision space under a supply chain characteristics. The aim is to present a mixed integer programming (MIP which optimizes cell formation, scheduling and layout decisions, concurrently where the suppliers are required to operate exceptional products. For this purpose, the time in which parts need to be operated on machines and also products' demand are uncertain and explained by set of scenarios. This model tries to optimize expected holding cost and the costs regarded to the suppliers network in a supply chain in order to outsource exceptional operations. Scheduling decisions in a cellular manufacturing framework is treated as group scheduling problem, which assumes that all parts in a part group are operated in the same cell and no inter-cellular transfer is required. An efficient hybrid method made of genetic algorithm (GA and simulated annealing (SA will be proposed to solve such a complex problem under an optimization rule as a sub-ordinate section. This integrative combination algorithm is compared with global solutions and also, a benchmark heuristic algorithm introduced in the literature. Finally, performance of the algorithm will be verified through some test problems.
Tucker, G. E.; Hobley, D. E. J.; Hutton, E.; Gasparini, N. M.; Istanbulluoglu, E.; Adams, J. M.; Nudurupati, S. S.
2015-11-01
CellLab-CTS 2015 is a Python-language software library for creating two-dimensional, continuous-time stochastic (CTS) cellular automaton models. The model domain consists of a set of grid nodes, with each node assigned an integer state-code that represents its condition or composition. Adjacent pairs of nodes may undergo transitions to different states, according to a user-defined average transition rate. A model is created by writing a Python code that defines the possible states, the transitions, and the rates of those transitions. The code instantiates, initializes, and runs one of four object classes that represent different types of CTS model. CellLab-CTS provides the option of using either square or hexagonal grid cells. The software provides the ability to treat particular grid-node states as moving particles, and to track their position over time. Grid nodes may also be assigned user-defined properties, which the user can update after each transition through the use of a callback function. As a component of the Landlab modeling framework, CellLab-CTS models take advantage of a suite of Landlab's tools and capabilities, such as support for standardized input and output.
Stochastic resonance in ion channels characterized by information theory.
Goychuk, I; Hänggi, P
2000-04-01
We identify a unifying measure for stochastic resonance (SR) in voltage dependent ion channels which comprises periodic (conventional), aperiodic, and nonstationary SR. Within a simplest setting, the gating dynamics is governed by two-state conductance fluctuations, which switch at random time points between two values. The corresponding continuous time point process is analyzed by virtue of information theory. In pursuing this goal we evaluate for our dynamics the tau information, the mutual information, and the rate of information gain. As a main result we find an analytical formula for the rate of information gain that solely involves the probability of the two channel states and their noise averaged rates. For small voltage signals it simplifies to a handy expression. Our findings are applied to study SR in a potassium channel. We find that SR occurs only when the closed state is predominantly dwelled upon. Upon increasing the probability for the open channel state the application of an extra dose of noise monotonically deteriorates the rate of information gain, i.e., no SR behavior occurs.
Characterization of ambient air pollution for stochastic health models
Energy Technology Data Exchange (ETDEWEB)
Batterman, S.A.
1981-08-01
This research is an analysis of various measures of ambient air pollution useful in cross-sectional epidemiological investigations and rick assessments. The Chestnut Ridge area health effects investigation, which includes a cross-sectional study of respiratory symptoms in young children, is used as a case study. Four large coal-fired electric generating power plants are the dominant pollution sources in this area of western Pennsylvania. The air pollution data base includes four years of sulfur dioxide and five years of total suspended particulate concentrations at seventeen monitors. Some 70 different characterizations of pollution are constructed and tested. These include pollutant concentrations at various percentiles and averaging times, exceedence measures which show the amount of time a specified threshold concentration is exceeded, and several dosage measures which transform non-linear dose-response relationships onto pollutant concentrations.
Institute of Scientific and Technical Information of China (English)
M.Kalpana; P.Balasubramaniam
2013-01-01
We investigate the stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks (MJFCNNs) with discrete,unbounded distributed delays,and the Wiener process based on sampled-data control using the linear matrix inequality (LMI) approach.The Lyapunov-Krasovskii functional combined with the input delay approach as well as the free-weighting matrix approach is employed to derive several sufficient criteria in terms of LMIs to ensure that the delayed MJFCNNs with the Wiener process is stochastic asymptotical synchronous.Restrictions (e.g.,time derivative is smaller than one) are removed to obtain a proposed sampled-data controller.Finally,a numerical example is provided to demonstrate the reliability of the derived results.
Liang, Jie; Cao, Youfang; Gürsoy, Gamze; Naveed, Hammad; Terebus, Anna; Zhao, Jieling
2016-01-01
Genome sequences provide the overall genetic blueprint of cells, but cells possessing the same genome can exhibit diverse phenotypes. There is a multitude of mechanisms controlling cellular epigenetic states and that dictate the behavior of cells. Among these, networks of interacting molecules, often under stochastic control, depending on the specific wirings of molecular components and the physiological conditions, can have a different landscape of cellular states. In addition, chromosome folding in three-dimensional space provides another important control mechanism for selective activation and repression of gene expression. Fully differentiated cells with different properties grow, divide, and interact through mechanical forces and communicate through signal transduction, resulting in the formation of complex tissue patterns. Developing quantitative models to study these multi-scale phenomena and to identify opportunities for improving human health requires development of theoretical models, algorithms, and computational tools. Here we review recent progress made in these important directions. PMID:27480462
Hostetter, Megan
This thesis presents a new type of polypropylene (PP) cellular material fabricated through a simple melt-stretching process. Stochastic honeycombs have an open cell, random honeycomb structure, with webs oriented perpendicular to built-in skins. This process has the advantage that, for example, PP pellets can be turned into a sandwich panel in one step. It was demonstrated that despite the randomness in the web structure, the out-of-plane compressive strength of stochastic honeycombs was repeatable, and exceeded that of commercial PP foams and was comparable to commercial PP honeycombs. The key material properties required to produce an this architecture were shown to be a high melt strength and a high viscosity, branched polymer. The viscosity was shown to affect the total length of the webs in cross-section and the relative partitioning of material through the skin, transition region and webs. Web thickness was affected by the areal density of the polymer during fabrication. Mechanical testing methods were adapted from ASTM standards for honeycombs, and the fabrication method was advanced from a manual to a machine controlled process. Stochastic honeycombs were shown to buckle elastically, plastically, and fracture after the peak strength. Elastic and plastic buckling were dominant at lower densities, and plastic buckling and fracture at higher densities. A thin-plate buckling model for the strength of stochastic honeycombs was developed and verified experimentally. The crystallinity of the polymer affected the tensile strength and stiffness, having a linear effect on the buckling strength. The architecture was composed of webs bound on both sides and webs bound on one side and free on the other. A greater fraction of bound webs increased the strength of the structure in the buckling model. A fabrication study showed that melt-stretching the polymer at higher strain rates increased the connectivity and fraction of bound webs. Additionally, higher density led to a
Ezzedine, S. M.
2009-12-01
Fractures and fracture networks are the principal pathways for transport of water and contaminants in groundwater systems, enhanced geothermal system fluids, migration of oil and gas, carbon dioxide leakage from carbon sequestration sites, and of radioactive and toxic industrial wastes from underground storage repositories. A major issue to overcome when characterizing a fractured reservoir is that of data limitation due to accessibility and affordability. Moreover, the ability to map discontinuities in the rock with available geological and geophysical tools tends to decrease particularly as the scale of the discontinuity goes down. Geological characterization data include measurements of fracture density, orientation, extent, and aperture, and are based on analysis of outcrops, borehole optical and acoustic televiewer logs, aerial photographs, and core samples, among other techniques. All of these measurements are taken at the field scale through a very sparse limited number of deep boreholes. These types of data are often reduced to probability distribution functions for predictive modeling and simulation in a stochastic framework such as a stochastic discrete fracture network. Stochastic discrete fracture network models enable, through Monte Carlo realizations and simulations, probabilistic assessment of flow and transport phenomena that are not adequately captured using continuum models. Despite the fundamental uncertainties inherited within the probabilistic reduction of the sparse data collected, very little work has been conducted on quantifying uncertainty on the reduced probabilistic distribution functions. In the current study, using nested Monte Carlo simulations, we present the impact of parameter uncertainties of the distribution functions of fracture density, orientation, aperture and size on the flow and transport using topological measures such as fracture connectivity, physical characteristics such as effective hydraulic conductivity tensors, and
Energy Technology Data Exchange (ETDEWEB)
Doubrawa, Paula [Sibley School of Mechanical and Aerospace Engineering, Cornell University, Upson Hall Ithaca 14850 New York USA; Barthelmie, Rebecca J. [Sibley School of Mechanical and Aerospace Engineering, Cornell University, Upson Hall Ithaca 14850 New York USA; Wang, Hui [Sibley School of Mechanical and Aerospace Engineering, Cornell University, Upson Hall Ithaca 14850 New York USA; Churchfield, Matthew J. [National Renewable Energy Laboratory, Golden 80401 Colorado USA
2016-08-04
Understanding the detailed dynamics of wind turbine wakes is critical to predicting the performance and maximizing the efficiency of wind farms. This knowledge requires atmospheric data at a high spatial and temporal resolution, which are not easily obtained from direct measurements. Therefore, research is often based on numerical models, which vary in fidelity and computational cost. The simplest models produce axisymmetric wakes and are only valid beyond the near wake. Higher-fidelity results can be obtained by solving the filtered Navier-Stokes equations at a resolution that is sufficient to resolve the relevant turbulence scales. This work addresses the gap between these two extremes by proposing a stochastic model that produces an unsteady asymmetric wake. The model is developed based on a large-eddy simulation (LES) of an offshore wind farm. Because there are several ways of characterizing wakes, the first part of this work explores different approaches to defining global wake characteristics. From these, a model is developed that captures essential features of a LES-generated wake at a small fraction of the cost. The synthetic wake successfully reproduces the mean characteristics of the original LES wake, including its area and stretching patterns, and statistics of the mean azimuthal radius. The mean and standard deviation of the wake width and height are also reproduced. This preliminary study focuses on reproducing the wake shape, while future work will incorporate velocity deficit and meandering, as well as different stability scenarios.
Directory of Open Access Journals (Sweden)
Maria Luisa eGuerriero
2014-10-01
Full Text Available Rhythmic behavior is essential for plants; for example, daily (circadian rhythms control photosynthesis and seasonal rhythms regulate their life cycle. The core of the circadian clock is a genetic network that coordinates the expression of specific clock genes in a circadian rhythm reflecting the 24-hour day/night cycle.Circadian clocks exhibit stochastic noise due to the low copy numbers of clock genes and the consequent cell-to-cell variation: this intrinsic noise plays a major role in circadian clocks by inducing more robust oscillatory behavior. Another source of noise is the environment, which causes variation in temperature and light intensity: this extrinsic noise is part of the requirement for the structural complexity of clock networks.Advances in experimental techniques now permit single-cell measurements and the development of single-cell models. Here we present some modeling studies showing the importance of considering both types of noise in understanding how plants adapt to regular and irregular light variations. Stochastic models have proven useful for understanding the effect of regular variations. By contrast, the impact of irregular variations and the interaction of different noise sources are less studied.
Cellular and Phenotypic Characterization of Canine Osteosarcoma Cell Lines
Directory of Open Access Journals (Sweden)
Marie E. Legare, Jamie Bush, Amanda K. Ashley, Taka Kato, William H. Hanneman
2011-01-01
Full Text Available Canine and human osteosarcoma (OSA have many similarities, with the majority of reported cases occurring in the appendicular skeleton, gender predominance noted, high rate of metastasis at the time of presentation, and a lack of known etiology for this devastating disease. Due to poor understanding of the molecular mechanisms underlying OSA, we have characterized seven different OSA canine cell lines: Abrams, D17, Grey, Hughes, Ingles, Jarques, and Marisco and compared them to U2, a human OSA cell line, for the following parameters: morphology, growth, contact inhibition, migrational tendencies, alkaline phosphatase staining, heterologous tumor growth, double-strand DNA breaks, and oxidative damage. All results demonstrated the positive characteristics of the Abrams cell line for use in future studies of OSA. Of particular interest, the robust growth of a subcutaneous tumor and rapid pulmonary metastasis of the Abrams cell line in an immunocompromised mouse shows incredible potential for the future use of Abrams as a canine OSA model. Further investigations utilizing a canine cell model of OSA, such as Abrams, will be invaluable to understanding the molecular events underlying OSA, pharmaceutical inhibition of metastasis, and eventual prevention of this devastating disease.
A Characterization of Cellular Automata Generated by Idempotents on the Full Shift
Salo, Ville
2012-01-01
In this article, we discuss the family of cellular automata generated by so-called idempotent cellular automata (CA G such that G^2 = G) on the full shift. We prove a characterization of products of idempotent CA, and show examples of CA which are not easy to directly decompose into a product of idempotents, but which are trivially seen to satisfy the conditions of the characterization. Our proof uses ideas similar to those used in the well-known Embedding Theorem and Lower Entropy Factor Theorem in symbolic dynamics. We also consider some natural decidability questions for the class of products of idempotent CA.
On the behaviour characterization of metallic cellular materials under impact loading
Fang, Dai-Ning; Li, Yu-Long; Zhao, Han
2010-12-01
This paper reviews the common mechanical features of the metallic cellular material under impact loading as well as the characterization methods of such behaviours. The main focus is on the innovations of various testing methods at impact loading rates. Following aspects were discussed in details. (1) The use of soft nylon Hopkinson/Kolsky bar for an enhanced measuring accuracy in order to assess if there is a strength enhancement or not for this class of cellular materials under moderate impact loading; (2) The use of digital image correlations to determine the strain fields during the tests to confirm the existence of a pseudo-shock wave propagation inside the cellular material under high speed impact; (3) The use of new combined shear compression device to determine the loading envelop of cellular materials under impact multiaxial loadings.
VANROON, WMC; COPRAY, JCVM; HOGENESCH, RI; KEMA, [No Value; MEYER, EM; MOLENAAR, G; LUGARD, C; STAAL, MJ; GO, KG
1995-01-01
The objective of this study was to develop an optimal dissection procedure for fetal porcine ventral mesencephalon (VM) grafts and to characterize the cellular composition of such an explant, in particular with respect to the dopaminergic and GABAergic components. We have used a monolayer cell cultu
Characterization of positive solution to stochastic competitor-competitor-cooperative model
Directory of Open Access Journals (Sweden)
Partha Sarathi Mandal
2013-04-01
Full Text Available In this article we study a randomized three-dimensional Lotka-Volterra model with competitor-competitor-mutualist interaction. We show the existence, uniqueness, moment boundedness, stochastic boundedness and global asymptotic stability of positive global solutions for this stochastic model. Analytical results are validated by numerical examples.
Xu, Hongyi; Zhu, Min; Marcicki, James; Yang, Xiao Guang
2017-03-01
A microstructure-based modeling method is developed to predict the mechanical behaviors of lithium-ion battery separators. Existing battery separator modeling methods cannot capture the structural features on the microscale. To overcome this issue, we propose an image-based microstructure Representative Volume Element (RVE) modeling method, which facilitates the understanding of the separators' complex macro mechanical behaviors from the perspective of microstructural features. A generic image processing workflow is developed to identify different phases in the microscopic image. The processed RVE image supplies microstructural information to the Finite Element Analysis (FEA). Both mechanical behavior and microstructure evolution are obtained from the simulation. The evolution of microstructure features is quantified using the stochastic microstructure characterization methods. The proposed method successfully captures the anisotropic behavior of the separator under tensile test, and provides insights into the microstructure deformation, such as the growth of voids. We apply the proposed method to a commercially available separator as the demonstration. The analysis results are validated using experimental testing results that are reported in literature.
Energy Technology Data Exchange (ETDEWEB)
Kryvohuz, Maksym, E-mail: mkryvohu@uci.edu; Mukamel, Shaul [Chemistry Department, University of California, Irvine, California 92697-2025 (United States)
2015-06-07
Generalized nonlinear response theory is presented for stochastic dynamical systems. Experiments in which multiple measurements of dynamical quantities are used along with multiple perturbations of parameters of dynamical systems are described by generalized response functions (GRFs). These constitute a new type of multidimensional measures of stochastic dynamics either in the time or the frequency domains. Closed expressions for GRFs in stochastic dynamical systems are derived and compared with numerical non-equilibrium simulations. Several types of perturbations are considered: impulsive and periodic perturbations of temperature and impulsive perturbations of coordinates. The present approach can be used to study various types of stochastic processes ranging from single-molecule conformational dynamics to chemical kinetics of finite-size reactors such as biocells.
Thermo-mechanical characterization of polypyrrole compliance using stochastic system identification.
Pillai, Priam V; Hunter, Ian W
2009-01-01
Conducting polymers such as polypyrrole are studied as novel biologically inspired actuators. Their capacity to generate stresses of up to 5 MPa, strains of up to 10% at low voltages (2 V) make them ideal candidates to be used as artificial muscle materials. It has been shown that the modulus of polypyrrole can change when the material is electrochemically excited. In this paper we develop a technique that uses a stochastic stress input that can be used to measure the compliance frequency response (between 10(-2) Hz and 100 Hz) of polypyrrole in-situ. We validate the compliance calculated from the stochastic stress input by comparing it with the compliance calculated from a single sinusoidal stress input. We also measure the compliance as a function of temperature using both techniques and show that the stochastic compliance follows the same trends as the compliance calculated from single sinusoidal stress input.
Directory of Open Access Journals (Sweden)
Aldine R. Amiel
2015-12-01
Full Text Available Cnidarians, the extant sister group to bilateria, are well known for their impressive regenerative capacity. The sea anemone Nematostella vectensis is a well-established system for the study of development and evolution that is receiving increased attention for its regenerative capacity. Nematostella is able to regrow missing body parts within five to six days after its bisection, yet studies describing the morphological, cellular, and molecular events underlying this process are sparse and very heterogeneous in their experimental approaches. In this study, we lay down the basic framework to study oral regeneration in Nematostella vectensis. Using various imaging and staining techniques we characterize in detail the morphological, cellular, and global molecular events that define specific landmarks of this process. Furthermore, we describe in vivo assays to evaluate wound healing success and the initiation of pharynx reformation. Using our described landmarks for regeneration and in vivo assays, we analyze the effects of perturbing either transcription or cellular proliferation on the regenerative process. Interestingly, neither one of these experimental perturbations has major effects on wound closure, although they slightly delay or partially block it. We further show that while the inhibition of transcription blocks regeneration in a very early step, inhibiting cellular proliferation only affects later events such as pharynx reformation and tentacle elongation.
Endo, Noritaka
2016-12-01
A simple stochastic cellular automaton model is proposed for simulating bedload transport, especially for cases with a low transport rate and where available sediments are very sparse on substrates in a subaqueous system. Numerical simulations show that the bed type changes from sheet flow through sand patches to ripples as the amount of sand increases; this is consistent with observations in flume experiments and in the field. Without changes in external conditions, the sand flux calculated for a given amount of sand decreases over time as bedforms develop from a flat bed. This appears to be inconsistent with the general understanding that sand flux remains unchanged under the constant-fluid condition, but it is consistent with the previous experimental data. For areas of low sand abundance, the sand flux versus sand amount (flux-density relation) in the simulation shows a single peak with an abrupt decrease, followed by a long tail; this is very similar to the flux-density relation seen in automobile traffic flow. This pattern (the relation between segments of the curve and the corresponding bed states) suggests that sand sheets, sand patches, and sand ripples correspond respectively to the free-flow phase, congested phase, and jam phase of traffic flows. This implies that sand topographic features on starved beds are determined by the degree of interference between sand particles. Although the present study deals with simple cases only, this can provide a simplified but effective modeling of the more complicated sediment transport processes controlled by interference due to contact between grains, such as the pulsatory migration of grain-size bimodal mixtures with repetition of clustering and scattering.
Simultaneous characterization of cellular RNA structure and function with in-cell SHAPE-Seq.
Watters, Kyle E; Abbott, Timothy R; Lucks, Julius B
2016-01-29
Many non-coding RNAs form structures that interact with cellular machinery to control gene expression. A central goal of molecular and synthetic biology is to uncover design principles linking RNA structure to function to understand and engineer this relationship. Here we report a simple, high-throughput method called in-cell SHAPE-Seq that combines in-cell probing of RNA structure with a measurement of gene expression to simultaneously characterize RNA structure and function in bacterial cells. We use in-cell SHAPE-Seq to study the structure-function relationship of two RNA mechanisms that regulate translation in Escherichia coli. We find that nucleotides that participate in RNA-RNA interactions are highly accessible when their binding partner is absent and that changes in RNA structure due to RNA-RNA interactions can be quantitatively correlated to changes in gene expression. We also characterize the cellular structures of three endogenously expressed non-coding RNAs: 5S rRNA, RNase P and the btuB riboswitch. Finally, a comparison between in-cell and in vitro folded RNA structures revealed remarkable similarities for synthetic RNAs, but significant differences for RNAs that participate in complex cellular interactions. Thus, in-cell SHAPE-Seq represents an easily approachable tool for biologists and engineers to uncover relationships between sequence, structure and function of RNAs in the cell.
Directory of Open Access Journals (Sweden)
Jean-Marc Tulliani
2013-01-01
Full Text Available A modified gel-casting process was developed to produce both dense and highly porous (40% volume yttria tetragonal zirconia polycrystal (Y-TZP using agar, a natural polysaccharide, as gelling agent. A fugitive phase, made of commercial polyethylene spheres, was added to the ceramic suspension before gelling to produce cellular ceramic structures. The characterization of the microstructural features of both dense and cellular ceramics was carried out by FEG SEM analysis of cross-sections produced by focused ion beam. The mechanical properties of the components were characterized at room temperature by nanoindentation tests in continuous stiffness measurement mode, by investigating the direct effect of the presence of residual microporosity. The presence of a diffuse residual microporosity from incomplete gel deaeration resulted in a decay of the bending strength and of the elastic modulus. The mechanical behavior of both dense and cellular zirconia (in terms of elastic modulus, flexural strength, and deformation at rupture was investigated by performing four-point bending tests at the temperature of 1500°C.
Ray-based stochastic inversion of prestack seismic data for improved reservoir characterization
Van der Burg, D.; Verdel, A.; Wapenaar, C.P.A.
2009-01-01
Trace inversion for reservoir parameters is affected by angle averaging of seismic data and wavelet distortion on the migration image. In an alternative approach to stochastic trace inversion, the data are inverted prestack before migration using 3D dynamic ray tracing. This choice makes it possible
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...
Eichhorn, Ralf; Aurell, Erik
2014-04-01
theory for small deviations from equilibrium, in which a general framework is constructed from the analysis of non-equilibrium states close to equilibrium. In a next step, Prigogine and others developed linear irreversible thermodynamics, which establishes relations between transport coefficients and entropy production on a phenomenological level in terms of thermodynamic forces and fluxes. However, beyond the realm of linear response no general theoretical results were available for quite a long time. This situation has changed drastically over the last 20 years with the development of stochastic thermodynamics, revealing that the range of validity of thermodynamic statements can indeed be extended deep into the non-equilibrium regime. Early developments in that direction trace back to the observations of symmetry relations between the probabilities for entropy production and entropy annihilation in non-equilibrium steady states [5-8] (nowadays categorized in the class of so-called detailed fluctuation theorems), and the derivations of the Bochkov-Kuzovlev [9, 10] and Jarzynski relations [11] (which are now classified as so-called integral fluctuation theorems). Apart from its fundamental theoretical interest, the developments in stochastic thermodynamics have experienced an additional boost from the recent experimental progress in fabricating, manipulating, controlling and observing systems on the micro- and nano-scale. These advances are not only of formidable use for probing and monitoring biological processes on the cellular, sub-cellular and molecular level, but even include the realization of a microscopic thermodynamic heat engine [12] or the experimental verification of Landauer's principle in a colloidal system [13]. The scientific program Stochastic Thermodynamics held between 4 and 15 March 2013, and hosted by The Nordic Institute for Theoretical Physics (Nordita), was attended by more than 50 scientists from the Nordic countries and elsewhere, amongst them
Institute of Scientific and Technical Information of China (English)
Dal Hyung Kim; Sean E. Brigandi; Paul Kim; Doyoung Byun; Min Jun Kim
2011-01-01
Artificial magnetotactic Tetrahymena pyriformis GL (T. pyriformis) cells were created by the internalization of iron oxide nano particles and became controllable with a time-varying external magnetic field. Thus, T. pyriformis can be utilized as a cellular robot to conduct micro-scale tasks such as transportation and manipulation. To complete these tasks, loading inorganic or organic materials onto the cell body is essential, but functionalization of the cell membrane is obstructed by their motile organelles, cilia. Dibucaine HCl, a local anesthetic, removes the cilia from the cell body, and the functional group would be absorbed more efficiently during cilia regeneration. In this paper, we characterize the recovery of artificial magnetotactic T.pyriformis after the deciliation process to optimize a cellular robot fabrication process. After sufficient time to recover, the motility rate and the average velocity of the deciliated cells were six and ten percent lower than that of non-deciliated cells, respectively. We showed that the motile cells after recovery can still be controlled using magnetotaxis, making T. pyriformis a good candidate to be used as a cellular robot.
Vladimirov, Igor G
2012-01-01
The paper is concerned with open quantum systems whose Heisenberg dynamics are described by quantum stochastic differential equations driven by external boson fields. The system-field coupling operators are assumed to be quadratic polynomials of the system observables, with the latter satisfying canonical commutation relations. In combination with a cubic system Hamiltonian, this leads to a class of quasilinear quantum stochastic systems which retain algebraic closedness in the evolution of mixed moments of the observables. Although such a system is nonlinear and its quantum state is no longer Gaussian, the dynamics of the moments of any order are amenable to exact analysis, including the computation of their steady-state values. In particular, a generalized criterion is developed for quadratic stability of the quasilinear systems. The results of the paper are applicable to the generation of non-Gaussian quantum states with manageable moments and an optimal design of linear quantum controllers for quasilinear...
Maerker, Michael; Bolus, Michael
2014-05-01
We present a unique spatial dataset of Neanderthal sites in Europe that was used to train a set of stochastic models to reveal the correlations between the site locations and environmental indices. In order to assess the relations between the Neanderthal sites and environmental variables as described above we applied a boosted regression tree approach (TREENET) a statistical mechanics approach (MAXENT) and support vector machines. The stochastic models employ a learning algorithm to identify a model that best fits the relationship between the attribute set (predictor variables (environmental variables) and the classified response variable which is in this case the types of Neanderthal sites. A quantitative evaluation of model performance was done by determining the suitability of the model for the geo-archaeological applications and by helping to identify those aspects of the methodology that need improvements. The models' predictive performances were assessed by constructing the Receiver Operating Characteristics (ROC) curves for each Neanderthal class, both for training and test data. In a ROC curve the Sensitivity is plotted over the False Positive Rate (1-Specificity) for all possible cut-off points. The quality of a ROC curve is quantified by the measure of the parameter area under the ROC curve. The dependent variable or target variable in this study are the locations of Neanderthal sites described by latitude and longitude. The information on the site location was collected from literature and own research. All sites were checked for site accuracy using high resolution maps and google earth. The study illustrates that the models show a distinct ranking in model performance with TREENET outperforming the other approaches. Moreover Pre-Neanderthals, Early Neanderthals and Classic Neanderthals show a specific spatial distribution. However, all models show a wide correspondence in the selection of the most important predictor variables generally showing less
CSI 2264: CHARACTERIZING YOUNG STARS IN NGC 2264 WITH STOCHASTICALLY VARYING LIGHT CURVES
Energy Technology Data Exchange (ETDEWEB)
Stauffer, John; Rebull, Luisa; Carey, Sean [Spitzer Science Center, California Institute of Technology, Pasadena, CA 91125 (United States); Cody, Ann Marie [NASA Ames Research Center, Kepler Science Office, Mountain View, CA 94035 (United States); Hillenbrand, Lynne A.; Carpenter, John [Astronomy Department, California Institute of Technology, Pasadena, CA 91125 (United States); Turner, Neal J. [Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109 (United States); Terebey, Susan [Department of Physics and Astronomy, 5151 State University Drive, California State University at Los Angeles, Los Angeles, CA 90032 (United States); Morales-Calderón, Maria [Centro de Astrobiología, Dpto. de Astrofísica, INTA-CSIC, P.O. BOX 78, E-28691, ESAC Campus, Villanueva de la Cañada, Madrid (Spain); Alencar, Silvia H. P.; McGinnis, Pauline; Sousa, Alana [Departamento de Física—ICEx—UFMG, Av. Antônio Carlos, 6627, 30270-901, Belo Horizonte, MG (Brazil); Bouvier, Jerome; Venuti, Laura [Université de Grenoble, Institut de Planétologie et d’Astrophysique de Grenoble (IPAG), F-38000 Grenoble (France); Hartmann, Lee; Calvet, Nuria [Department of Astronomy, University of Michigan, 500 Church Street, Ann Arbor, MI:48105 (United States); Micela, Giusi; Flaccomio, Ettore [INAF—Osservatorio Astronomico di Palermo, Piazza del Parlamento 1, I-90134, Palermo (Italy); Song, Inseok [Department of Physics and Astronomy, The University of Georgia, Athens, GA 30602-2451 (United States); Gutermuth, Rob, E-mail: stauffer@ipac.caltech.edu [Department of Astronomy, University of Massachusetts, Amherst, MA 01003 (United States); and others
2016-03-15
We provide CoRoT and Spitzer light curves and other supporting data for 17 classical T Tauri stars in NGC 2264 whose CoRoT light curves exemplify the “stochastic” light curve class as defined in 2014 by Cody et al. The most probable physical mechanism to explain the optical variability within this light curve class is time-dependent mass accretion onto the stellar photosphere, producing transient hot spots. Where we have appropriate spectral data, we show that the veiling variability in these stars is consistent in both amplitude and timescale with the optical light curve morphology. The veiling variability is also well-correlated with the strength of the He i 6678 Å emission line, predicted by models to arise in accretion shocks on or near the stellar photosphere. Stars with accretion burst light curve morphology also have variable mass accretion. The stochastic and accretion burst light curves can both be explained by a simple model of randomly occurring flux bursts, with the stochastic light curve class having a higher frequency of lower amplitude events. Members of the stochastic light curve class have only moderate mass accretion rates. Their Hα profiles usually have blueshifted absorption features, probably originating in a disk wind. The lack of periodic signatures in the light curves suggests that little of the variability is due to long-lived hot spots rotating into or out of our line of sight; instead, the primary driver of the observed photometric variability is likely to be instabilities in the inner disk that lead to variable mass accretion.
Intrinsic Radiosensitivity and Cellular Characterization of 27 Canine Cancer Cell Lines.
Directory of Open Access Journals (Sweden)
Junko Maeda
Full Text Available Canine cancer cell lines have progressively been developed, but are still underused resources for radiation biology research. Measurement of the cellular intrinsic radiosensitivity is important because understanding the difference may provide a framework for further elucidating profiles for prediction of radiation therapy response. Our studies have focused on characterizing diverse canine cancer cell lines in vitro and understanding parameters that might contribute to intrinsic radiosensitivity. First, intrinsic radiosensitivity of 27 canine cancer cell lines derived from ten tumor types was determined using a clonogenic assay. The 27 cell lines had varying radiosensitivities regardless tumor type (survival fraction at 2 Gy, SF2 = 0.19-0.93. In order to understand parameters that might contribute to intrinsic radiosensitivity, we evaluated the relationships of cellular radiosensitivity with basic cellular characteristics of the cell lines. There was no significant correlation of SF2 with S-phase fraction, doubling time, chromosome number, ploidy, or number of metacentric chromosomes, while there was a statistically significant correlation between SF2 and plating efficiency. Next, we selected the five most radiosensitive cell lines as the radiosensitive group and the five most radioresistant cell lines as the radioresistant group. Then, we evaluated known parameters for cell killing by ionizing radiation, including radiation-induced DNA double strand break (DSB repair and apoptosis, in the radiosensitive group as compared to the radioresistant group. High levels of residual γ-H2AX foci at the sites of DSBs were present in the four out of the five radiosensitive canine cancer cell lines. Our studies suggested that substantial differences in intrinsic radiosensitivity exist in canine cancer cell lines, and radiation-induced DSB repair was related to radiosensitivity, which is consistent with previous human studies. These data may assist further
Directory of Open Access Journals (Sweden)
Weiqiang eChen
2013-04-01
Full Text Available Rapid, accurate, and quantitative characterization of immune status of patients is of utmost importance for disease diagnosis and prognosis, evaluating efficacy of immunotherapeutics and tailoring drug treatments. Immune status of patients is often dynamic and patient-specific, and such complex heterogeneity has made accurate, real-time measurements of patient immune status challenging in the clinical setting. Recent advances in microfluidics have demonstrated promising applications of microfluidics for immune monitoring with minimum sample requirement and rapid functional immunophenotyping capability. This review will highlight recent developments of microfluidic platforms that can perform rapid and accurate cellular functional assays on patient immune cells. We will also discuss the future potential of integrated microfluidics to perform rapid, accurate, and sensitive cellular functional assays at a single-cell resolution on different types or subpopulations of immune cells, to provide an unprecedented level of information depth on the distribution of immune cell functionalities. We envision that such microfluidic immunophenotyping tools will allow comprehensive and systems-level immunomonitoring, unlocking the potential to transform experimental clinical immunology into an information-rich science.
Energy Technology Data Exchange (ETDEWEB)
Cardona-Felix, Cesar S.; Lara-Gonzalez, Samuel; Brieba, Luis G. (LNLS)
2012-02-08
Proliferating cellular nuclear antigen (PCNA) is a toroidal-shaped protein that is involved in cell-cycle control, DNA replication and DNA repair. Parasitic protozoa are early-diverged eukaryotes that are responsible for neglected diseases. In this work, a PCNA from a parasitic protozoon was identified, cloned and biochemically characterized and its crystal structure was determined. Structural and biochemical studies demonstrate that PCNA from Entamoeba histolytica assembles as a homotrimer that is able to interact with and stimulate the activity of a PCNA-interacting peptide-motif protein from E. histolytica, EhDNAligI. The data indicate a conservation of the biochemical mechanisms of PCNA-mediated interactions between metazoa, yeast and parasitic protozoa.
Vorobiev, O.; Ezzedine, S. M.; Antoun, T.; Glenn, L.
2014-12-01
This work describes a methodology used for large scale modeling of wave propagation fromunderground explosions conducted at the Nevada Test Site (NTS) in two different geological settings:fractured granitic rock mass and in alluvium deposition. We show that the discrete nature of rockmasses as well as the spatial variability of the fabric of alluvium is very important to understand groundmotions induced by underground explosions. In order to build a credible conceptual model of thesubsurface we integrated the geological, geomechanical and geophysical characterizations conductedduring recent test at the NTS as well as historical data from the characterization during the undergroundnuclear test conducted at the NTS. Because detailed site characterization is limited, expensive and, insome instances, impossible we have numerically investigated the effects of the characterization gaps onthe overall response of the system. We performed several computational studies to identify the keyimportant geologic features specific to fractured media mainly the joints; and those specific foralluvium porous media mainly the spatial variability of geological alluvium facies characterized bytheir variances and their integral scales. We have also explored common key features to both geologicalenvironments such as saturation and topography and assess which characteristics affect the most theground motion in the near-field and in the far-field. Stochastic representation of these features based onthe field characterizations have been implemented in Geodyn and GeodynL hydrocodes. Both codeswere used to guide site characterization efforts in order to provide the essential data to the modelingcommunity. We validate our computational results by comparing the measured and computed groundmotion at various ranges. This work performed under the auspices of the U.S. Department of Energy by Lawrence LivermoreNational Laboratory under Contract DE-AC52-07NA27344.
In vivo characterization of skin using a Weiner nonlinear stochastic system identification method.
Chen, Yi; Hunter, Ian W
2009-01-01
This paper describes an indentometer device used to identify the linear dynamic and nonlinear properties of skin and underlying tissue using an in vivo test. The device uses a Lorentz force actuator to apply a dynamic force to the skin and measures the resulting displacement. It was found that the skin could be modeled as a Wiener system (i.e. a linear dynamic system followed by a static nonlinearity). Using a stochastic nonlinear system identification technique, the method presented in this paper was able to identify the dynamic linear and static nonlinear mechanical parameters of the indentometer-skin system within 2 to 4 seconds. The shape of the nonlinearity was found to vary depending on the area of the skin that was tested. We show that the device can repeatably distinguish between different areas of human tissue for multiple test subjects.
Parker, Matthew D; Jones, Lynette A; Hunter, Ian W; Taberner, A J; Nash, M P; Nielsen, P M F
2017-01-01
A triaxial force-sensitive microrobot was developed to dynamically perturb skin in multiple deformation modes, in vivo. Wiener static nonlinear identification was used to extract the linear dynamics and static nonlinearity of the force-displacement behavior of skin. Stochastic input forces were applied to the volar forearm and thenar eminence of the hand, producing probe tip perturbations in indentation and tangential extension. Wiener static nonlinear approaches reproduced the resulting displacements with variances accounted for (VAF) ranging 94-97%, indicating a good fit to the data. These approaches provided VAF improvements of 0.1-3.4% over linear models. Thenar eminence stiffness measures were approximately twice those measured on the forearm. Damping was shown to be significantly higher on the palm, whereas the perturbed mass typically was lower. Coefficients of variation (CVs) for nonlinear parameters were assessed within and across individuals. Individual CVs ranged from 2% to 11% for indentation and from 2% to 19% for extension. Stochastic perturbations with incrementally increasing mean amplitudes were applied to the same test areas. Differences between full-scale and incremental reduced-scale perturbations were investigated. Different incremental preloading schemes were investigated. However, no significant difference in parameters was found between different incremental preloading schemes. Incremental schemes provided depth-dependent estimates of stiffness and damping, ranging from 300 N/m and 2 Ns/m, respectively, at the surface to 5 kN/m and 50 Ns/m at greater depths. The device and techniques used in this research have potential applications in areas, such as evaluating skincare products, assessing skin hydration, or analyzing wound healing.
Energy Technology Data Exchange (ETDEWEB)
Gorny, B.; Niendorf, T.; Lackmann, J. [Lehrstuhl fuer Werkstoffkunde (Materials Science), University of Paderborn, Pohlweg 47-49, 33098 Paderborn (Germany); Thoene, M.; Troester, T. [Lehrstuhl fuer Leichtbau im Automobil (Automotive Lightweight Construction), University of Paderborn, Pohlweg 47-49, 33098 Paderborn (Germany); Direct Manufacturing Research Center (DMRC), Mersinweg 3, 33098 Paderborn (Germany); Maier, H.J., E-mail: hmaier@mail.upb.de [Lehrstuhl fuer Werkstoffkunde (Materials Science), University of Paderborn, Pohlweg 47-49, 33098 Paderborn (Germany)
2011-10-15
Highlights: {yields} The present study focused on deformation behavior and failure mechanisms in lattice structure produced by selective laser melting (SLM). {yields} It is demonstrated that heat treatments can be used to increase the energy absorption of an SLM-processed structure. {yields} An in situ testing procedure was introduced, where local strains were calculated by digital image correlation {yields} Shear failure could be predicted by localization using Tresca strains. {yields} The approach employed provides a means to understand the microstructure-mechanical property-local deformation relationship. - Abstract: Cellular materials are promising candidates for load adapted light-weight structures. Direct manufacturing (DM) tools are effective methods to produce non-stochastic structures. Many DM studies currently focus on optimization of the geometric nature of the structures obtained. The literature available so far reports on the mechanical properties but local deformation mechanisms are not taken into account. In order to fill this gap, the current study addresses the deformation behavior of a lattice structure produced by selective laser melting (SLM) on the local scale by means of a comprehensive experimental in situ approach, including electron backscatter diffraction, scanning electron microscopy and digital image correlation. SLM-processed as well as heat treated lattice structures made from TiAl6V4 alloy were employed for mechanical testing. It is demonstrated that the current approach provides means to understand the microstructure-mechanical property-local deformation relationship to allow for optimization of load adapted lattice structures.
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...
CSI 2264: Characterizing Young Stars in NGC 2264 with Stochastically Varying Light Curves
Stauffer, John; Rebull, Luisa; Hillenbrand, Lynne A; Turner, Neal J; Carpenter, John; Carey, Sean; Terebey, Susan; Morales-Calderon, Maria; Alencar, Silvia H P; McGinnis, Pauline; Sousa, Alana; Bouvier, Jerome; Venuti, Laura; Hartmann, Lee; Calvet, Nuria; Micela, Giusi; Flaccomio, Ettore; Song, Inseok; Gutermuth, Rob; Barrado, David; Vrba, Frederick J; Covey, Kevin; Herbst, William; Gillen, Edward; Guimaraes, Marcelo Medeiros; Bouy, Herve; Favata, Fabio
2016-01-01
We provide CoRoT and Spitzer light curves, as well as broad-band multi-wavelength photometry and high resolution, multi- and single-epoch spectroscopy for 17 classical T Tauris in NGC 2264 whose CoRoT light curves (LCs) exemplify the "stochastic" LC class as defined in Cody et al. (2014). The most probable physical mechanism to explain the optical variability in this LC class is time-dependent mass accretion onto the stellar photosphere, producing transient hot spots. As evidence in favor of this hypothesis, multi-epoch high resolution spectra for a subset of these stars shows that their veiling levels also vary in time and that this veiling variability is consistent in both amplitude and timescale with the optical LC morphology. Furthermore, the veiling variability is well-correlated with the strength of the HeI 6678A emission line, a feature predicted by models to arise in accretion shocks on or near the stellar photosphere. Stars with accretion burst LC morphology (Stauffer et al. 2014) are also attributed...
Directory of Open Access Journals (Sweden)
Hao Lei
2015-12-01
Full Text Available Trip travel time reliability is an important measure of transportation system performance and a key factor affecting travelers’ choices. This paper explores a method for estimating travel time distributions for corridors that contain multiple bottlenecks. A set of analytical equations are used to calculate the number of queued vehicles ahead of a probe vehicle and further capture many important factors affecting travel times: the prevailing congestion level, queue discharge rates at the bottlenecks, and flow rates associated with merges and diverges. Based on multiple random scenarios and a vector of arrival times, the lane-by-lane delay at each bottleneck along the corridor is recursively estimated to produce a route-level travel time distribution. The model incorporates stochastic variations of bottleneck capacity and demand and explains the travel time correlations between sequential links. Its data needs are the entering and exiting flow rates and a sense of the lane-by-lane distribution of traffic at each bottleneck. A detailed vehicle trajectory data-set from the Next Generation SIMulation (NGSIM project has been used to verify that the estimated distributions are valid, and the sources of estimation error are examined.
Directory of Open Access Journals (Sweden)
Zaccolo Manuela
2008-06-01
Full Text Available Abstract Background A novel fluorescent cAMP analog (8-[Pharos-575]- adenosine-3', 5'-cyclic monophosphate was characterized with respect to its spectral properties, its ability to bind to and activate three main isoenzymes of the cAMP-dependent protein kinase (PKA-Iα, PKA-IIα, PKA-IIβ in vitro, its stability towards phosphodiesterase and its ability to permeate into cultured eukaryotic cells using resonance energy transfer based indicators, and conventional fluorescence imaging. Results The Pharos fluorophore is characterized by a Stokes shift of 42 nm with an absorption maximum at 575 nm and the emission peaking at 617 nm. The quantum yield is 30%. Incubation of the compound to RIIα and RIIβ subunits increases the amplitude of excitation and absorption maxima significantly; no major change was observed with RIα. In vitro binding of the compound to RIα subunit and activation of the PKA-Iα holoenzyme was essentially equivalent to cAMP; RII subunits bound the fluorescent analog up to ten times less efficiently, resulting in about two times reduced apparent activation constants of the holoenzymes compared to cAMP. The cellular uptake of the fluorescent analog was investigated by cAMP indicators. It was estimated that about 7 μM of the fluorescent cAMP analog is available to the indicator after one hour of incubation and that about 600 μM of the compound had to be added to intact cells to half-maximally dissociate a PKA type IIα sensor. Conclusion The novel analog combines good membrane permeability- comparable to 8-Br-cAMP – with superior spectral properties of a modern, red-shifted fluorophore. GFP-tagged regulatory subunits of PKA and the analog co-localized. Furthermore, it is a potent, PDE-resistant activator of PKA-I and -II, suitable for in vitro applications and spatial distribution evaluations in living cells.
Parab, Harshala J; Huang, Jing-Hong; Lai, Tsung-Ching; Jan, Yi-Hua; Liu, Ru-Shi; Wang, Jui-Ling; Hsiao, Michael; Chen, Chung-Hsuan; Hwu, Yeu-Kuang; Tsai, Din Ping; Chuang, Shih-Yi; Pang, Jong-Hwei S
2011-09-30
The feasibility of using gold nanoparticles (AuNPs) for biomedical applications has led to considerable interest in the development of novel synthetic protocols and surface modification strategies for AuNPs to produce biocompatible molecular probes. This investigation is, to our knowledge, the first to elucidate the synthesis and characterization of sodium hexametaphosphate (HMP)-stabilized gold nanoparticles (Au-HMP) in an aqueous medium. The role of HMP, a food additive, as a polymeric stabilizing and protecting agent for AuNPs is elucidated. The surface modification of Au-HMP nanoparticles was carried out using polyethylene glycol and transferrin to produce molecular probes for possible clinical applications. In vitro cell viability studies performed using as-synthesized Au-HMP nanoparticles and their surface-modified counterparts reveal the biocompatibility of the nanoparticles. The transferrin-conjugated nanoparticles have significantly higher cellular uptake in J5 cells (liver cancer cells) than control cells (oral mucosa fibroblast cells), as determined by inductively coupled plasma mass spectrometry. This study demonstrates the possibility of using an inexpensive and non-toxic food additive, HMP, as a stabilizer in the large-scale generation of biocompatible and monodispersed AuNPs, which may have future diagnostic and therapeutic applications.
Energy Technology Data Exchange (ETDEWEB)
Parab, Harshala J; Huang, Jing-Hong; Liu, Ru-Shi [Department of Chemistry, National Taiwan University, Taipei 106, Taiwan (China); Lai, Tsung-Ching; Jan, Yi-Hua; Wang, Jui-Ling; Hsiao, Michael; Chen, Chung-Hsuan [Genomics Research Center, Academia Sinica, Taipei 115, Taiwan (China); Hwu, Yeu-Kuang [Institute of Physics, Academia Sinica, Taipei 115, Taiwan (China); Tsai, Din Ping [Department of Physics, National Taiwan University, Taipei 106, Taiwan (China); Chuang, Shih-Yi; Pang, Jong-Hwei S, E-mail: rsliu@ntu.edu.tw, E-mail: mhsiao@gate.sinica.edu.tw [Graduate Institute of Clinical Medical Sciences, Chang Gung University, Tao-Yuan, Taiwan (China)
2011-09-30
The feasibility of using gold nanoparticles (AuNPs) for biomedical applications has led to considerable interest in the development of novel synthetic protocols and surface modification strategies for AuNPs to produce biocompatible molecular probes. This investigation is, to our knowledge, the first to elucidate the synthesis and characterization of sodium hexametaphosphate (HMP)-stabilized gold nanoparticles (Au-HMP) in an aqueous medium. The role of HMP, a food additive, as a polymeric stabilizing and protecting agent for AuNPs is elucidated. The surface modification of Au-HMP nanoparticles was carried out using polyethylene glycol and transferrin to produce molecular probes for possible clinical applications. In vitro cell viability studies performed using as-synthesized Au-HMP nanoparticles and their surface-modified counterparts reveal the biocompatibility of the nanoparticles. The transferrin-conjugated nanoparticles have significantly higher cellular uptake in J5 cells (liver cancer cells) than control cells (oral mucosa fibroblast cells), as determined by inductively coupled plasma mass spectrometry. This study demonstrates the possibility of using an inexpensive and non-toxic food additive, HMP, as a stabilizer in the large-scale generation of biocompatible and monodispersed AuNPs, which may have future diagnostic and therapeutic applications.
Physical characterization and cellular uptake of propylene glycol liposomes in vitro.
Zhang, Lu; Lu, Cui-Tao; Li, Wen-Feng; Cheng, Jin-Guo; Tian, Xin-Qiao; Zhao, Ying-Zheng; Li, Xing; Lv, Hai-Feng; Li, Xiao-Kun
2012-03-01
In order to facilitate the intracellular delivery of therapeutic agents, a new type of liposomes-propylene glycol liposomes (PGL) were prepared, and their cell translocation capability in vitro was examined. PGL was composed of hydrogenated egg yolk lecithin, cholesterol, Tween 80 and propylene glycol. With curcumin as a model drug, characterization of loaded PGL were measured including surface morphology, particle size, elasticity, encapsulation efficiency of curcumin and physical stability. Using curcumin-loaded conventional liposomes as the control, the cell uptake capacity of loaded PGL was evaluated by detection the concentration of curcumin in cytoplasm. Compared with conventional liposomes, PGL exhibited such advantages as high encapsulation efficiency (92.74% ± 3.44%), small particle size (182.4 ± 89.2 nm), high deformability (Elasticity index = 48.6) and high stability both at normal temperature (about 25°C) and low temperature at 4°C. From cell experiment in vitro, PGL exhibited the highest uptake of curcumin compared with that of conventional liposomes and free curcumin solution. Little toxic effect on cellular viability was observed by methyl tetrazolium assay. In conclusion, PGL might be developed as a promising intracellular delivery carrier for therapeutic agents.
The first characterization of free radicals formed from cellular COX-catalyzed peroxidation.
Gu, Yan; Xu, Yi; Law, Benedict; Qian, Steven Y
2013-04-01
Through free radical-mediated peroxidation, cyclooxygenase (COX) can metabolize dihomo-γ-linolenic acid (DGLA) and arachidonic acid (AA) to form well-known bioactive metabolites, namely, the 1-series of prostaglandins (PGs1) and the 2-series of prostaglandins (PGs2), respectively. Unlike PGs2, which are generally viewed as proinflammatory and procarcinogenic PGs, PGs1 may possess anti-inflammatory and anti-cancer activity. Previous studies using ovine COX along with spin trapping and the LC/ESR/MS technique have shown that certain exclusive free radicals are generated from different free radical reactions in DGLA and AA peroxidation. However, it has been unclear whether the differences were associated with the contrasting bioactivity of DGLA vs AA. The aim of this study was to refine the LC/MS and spin trapping technique to make it possible for the association between free radicals and cancer cell growth to be directly tested. Using a colon cancer cell line, HCA-7 colony 29, and LC/MS along with a solid-phase extraction, we were able to characterize the reduced forms of radical adducts (hydroxylamines) as the free radicals generated from cellular COX-catalyzed peroxidation. For the first time, free radicals formed in the COX-catalyzed peroxidation of AA vs DGLA and their association with cancer cell growth were assessed (cell proliferation via MTS and cell cycle distribution via propidium iodide staining) in the same experimental setting. The exclusive free radicals formed from the COX-catalyzed peroxidation of AA and DGLA were shown to be correlated with the cell growth response. Our results indicate that free radicals generated from the distinct radical reactions in COX-catalyzed peroxidation may represent the novel metabolites of AA and DGLA that correspond to their contrasting bioactivity.
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.
Ander, M; Beltrao, P; Di Ventura, B; Ferkinghoff-Borg, J; Foglierini, M; Kaplan, A; Lemerle, C; Tomás-Oliveira, I; Serrano, L
2004-06-01
SmartCell has been developed to be a general framework for modelling and simulation of diffusion-reaction networks in a whole-cell context. It supports localisation and diffusion by using a mesoscopic stochastic reaction model. The SmartCell package can handle any cell geometry, considers different cell compartments, allows localisation of species, supports DNA transcription and translation, membrane diffusion and multistep reactions, as well as cell growth. Moreover, different temporal and spatial constraints can be applied to the model. A GUI interface that facilitates model making is also available. In this work we discuss limitations and advantages arising from the approach used in SmartCell and determine the impact of localisation on the behaviour of simple well-defined networks, previously analysed with differential equations. Our results show that this factor might play an important role in the response of networks and cannot be neglected in cell simulations.
Stochastic characterization of small-scale algorithms for human sensory processing.
Neri, Peter
2010-12-01
Human sensory processing can be viewed as a functional H mapping a stimulus vector s into a decisional variable r. We currently have no direct access to r; rather, the human makes a decision based on r in order to drive subsequent behavior. It is this (typically binary) decision that we can measure. For example, there may be two external stimuli s([0]) and s([1]), mapped onto r([0]) and r([1]) by the sensory apparatus H; the human chooses the stimulus associated with largest r. This kind of decisional transduction poses a major challenge for an accurate characterization of H. In this article, we explore a specific approach based on a behavioral variant of reverse correlation techniques, where the input s contains a target signal corrupted by a controlled noisy perturbation. The presence of the target signal poses an additional challenge because it distorts the otherwise unbiased nature of the noise source. We consider issues arising from both the decisional transducer and the target signal, their impact on system identification, and ways to handle them effectively for system characterizations that extend to second-order functional approximations with associated small-scale cascade models.
Directory of Open Access Journals (Sweden)
Lamichhane SP
2015-01-01
Full Text Available Surya P Lamichhane,1 Neha Arya,1,2 Nirdesh Ojha,3 Esther Kohler,1 V Prasad Shastri1,2,41Institute for Macromolecular Chemistry, University of Freiburg, Freiburg, 2Helmholtz Virtual Institute on “Multifunctional Biomaterials for Medicine”, 3Laboratory for Process Technology, Department of Microsystems Engineering, University of Freiburg, Freiburg, 4Centre for Biological Signaling Studies (BIOSS, University of Freiburg, Freiburg, GermanyAbstract: The efficient delivery of chemotherapeutics to the tumor via nanoparticle (NP-based delivery systems remains a significant challenge. This is compounded by the fact that the tumor is highly dynamic and complex environment composed of a plurality of cell types and extracellular matrix. Since glycosaminoglycan (GAG production is altered in many diseases (or pathologies, NPs bearing GAG moieties on the surface may confer some unique advantages in interrogating the tumor microenvironment. In order to explore this premise, in the study reported here poly-lactide-co-glycolide (PLGA NPs in the range of 100–150 nm bearing various proteoglycans were synthesized by a single-step nanoprecipitation and characterized. The surface functionalization of the NPs with GAG moieties was verified using zeta potential measurements and X-ray photoelectron spectroscopy. To establish these GAG-bearing NPs as carriers of therapeutics, cellular toxicity assays were undertaken in lung epithelial adenocarcinoma (A549 cells, human pulmonary microvascular endothelial cells (HPMEC, and renal proximal tubular epithelial cells. In general NPs were well tolerated over a wide concentration range (100–600 µg/mL by all cell types and were taken up to appreciable extents without any adverse cell response in A549 cells and HPMEC. Further, GAG-functionalized PLGA NPs were taken up to different extents in A459 cells and HPMEC. In both cell systems, the uptake of heparin-modified NPs was diminished by 50%–65% in comparison to that of
Institute of Scientific and Technical Information of China (English)
周凤燕
2012-01-01
研究了一类反应扩散广义时滞细胞神经网络在噪声干扰下的指数稳定性.利用Ito公式,Holder不等式,M矩阵性质和微分不等式技巧,给出了系统均值指数稳定的充分条件,并且判断方法简单易操作.最后给出了主要定理的两个应用实例,表明结论的有效性.%The exponential stability of a class of reaction-diffusion general cellular neural network with time delay and noise perturbation is studied. Using the Ito formula, Holder inequality, M-matric properties and a skill of differential inequality, some sufficient conditions are given to guarantee the mean value exponential stability of the equilibrium for the stochastic reaction-diffusion general cellular neural network with time delay and the sufficient conditions are easier to operate. In the end, two examples are given to illustrate the main theoretical results.
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 ...
Characterization of the emergent properties of a synthetic quasi-cellular system
Directory of Open Access Journals (Sweden)
Lazzerini-Ospri Lorenzo
2012-03-01
Full Text Available Abstract Background The process of solutes entrapment during liposomes formation is interesting for the investigation of the relationship between the formation of compartments and the distribution of molecules inside them; a relevant issue in the studies of the origin of life. Theoretically, when no interactions are supposed among the chemical species to be entrapped, the entrapment is described by a standard Poisson process. But very recent experimental findings show that, for small liposomes (100 nm diameter, the distribution of entrapped molecules is best described by a power-law function. This is of a great importance, as the two random processes give rise to two completely different scenarios. Here we present an in silico stochastic simulation of the encapsulation of a cell-free molecular translation system (the PURE system, obtained following two different entrapment models: a pure Poisson process, and a power-law. The protein synthesis inside the liposomes has been studied in both cases, with the aim to highlight experimental observables that could be measured to assess which model gives a better representation of the real process. Results Firstly, a minimal model for in vitro protein synthesis, based on the PURE system molecular composition, has been formalized. Then, we have designed a reliable experimental simulation where stochastic factors affect the reaction course inside the compartment. To this end, 24 solutes, which represent the PURE system components, have been stochastically distributed among vesicles by following either a Poisson or a power-law distribution. The course of the protein synthesis within each vesicle has been consequently calculated, as a function of vesicle size. Our study can predict translation yield in a population of small liposomes down to the attoliter (10-18 L range. Our results show that the efficiency of protein synthesis peaks at approximately 3·10-16 L (840 nm diam. with a Poisson distribution of
Vliet, T. van; Castro-Prada, E.M.; Luyten, H.; Lichtendonk, W.; Hamer, R.J.
2007-01-01
A detailed study was performed to simultaneously measure the mechanical and acoustic properties of crispy cellular solid foods. Different critical aspects are discussed in order to assess optimal test conditions. These are primarily data sampling rate, microphone positioning, frequency spectrum of i
Directory of Open Access Journals (Sweden)
Pabitra Pal Choudhury
2011-01-01
Full Text Available Dynamics of a nonlinear cellular automaton (CA is, in general asymmetric, irregular, and unpredictable as opposed to that of a linear CA, which is highly systematic and tractable, primarily due to the presence of a matrix handle. In this paper, we present a novel technique of studying the properties of the State Transition Diagram of a nonlinear uniform one-dimensional cellular automaton in terms of its deviation from a suggested linear model. We have considered mainly elementary cellular automata with neighborhood of size three, and, in order to facilitate our analysis, we have classified the Boolean functions of three variables on the basis of number and position(s of bit mismatch with linear rules. The concept of deviant and nondeviant states is introduced, and hence an algorithm is proposed for deducing the State Transition Diagram of a nonlinear CA rule from that of its nearest linear rule. A parameter called the proportion of deviant states is introduced, and its dependence on the length of the CA is studied for a particular class of nonlinear rules.
Cellular Response to Irradiation
Institute of Scientific and Technical Information of China (English)
LIU Bo; YAN Shi-Wei
2011-01-01
To explore the nonlinear activities of the cellular signaling system composed of one transcriptional arm and one protein-interaction arm, we use an irradiation-response module to study the dynamics of stochastic interactions.It is shown that the oscillatory behavior could be described in a unified way when the radiation-derived signal and noise are incorporated.
Energy Technology Data Exchange (ETDEWEB)
Ramirez, A; Mcnab, W; Hao, Y; White, D; Johnson, J
2011-04-14
During the last months of this project, our project activities have concentrated on four areas: (1) performing a stochastic inversion of pattern 16 seismic data to deduce reservoir bulk/shear moduli and density; the need for this inversion was not anticipated in the original scope of work, (2) performing a stochastic inversion of pattern 16 seismic data to deduce reservoir porosity and permeability, (3) complete the software needed to perform geochemical inversions and (4) use the software to perform stochastic inversion of aqueous chemistry data to deduce mineral volume fractions. This report builds on work described in progress reports previously submitted (Ramirez et al., 2009, 2010, 2011 - reports fulfilled the requirements of deliverables D1-D4) and fulfills deliverable D5: Field-based single-pattern simulations work product. The main challenge with our stochastic inversion approach is its large computational expense, even for single reservoir patterns. We dedicated a significant level of effort to improve computational efficiency but inversions involving multiple patterns were still intractable by project's end. As a result, we were unable to fulfill Deliverable D6: Field-based multi-pattern simulations work product.
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
From Complex to Simple: Interdisciplinary Stochastic Models
Mazilu, D. A.; Zamora, G.; Mazilu, I.
2012-01-01
We present two simple, one-dimensional, stochastic models that lead to a qualitative understanding of very complex systems from biology, nanoscience and social sciences. The first model explains the complicated dynamics of microtubules, stochastic cellular highways. Using the theory of random walks in one dimension, we find analytical expressions…
Eroh, Guy D.; Clayton, Fred C.; Florell, Scott R.; Cassidy, Pamela B.; Chirife, Andrea; Marón, Carina F.; Valenzuela, Luciano O.; Campbell, Michael S.; Seger, Jon; Rowntree, Victoria J.; Leachman, Sancy A.
2017-01-01
Southern right whales (SRWs, Eubalena australis) are polymorphic for an X-linked pigmentation pattern known as grey morphism. Most SRWs have completely black skin with white patches on their bellies and occasionally on their backs; these patches remain white as the whale ages. Grey morphs (previously referred to as partial albinos) appear mostly white at birth, with a splattering of rounded black marks; but as the whales age, the white skin gradually changes to a brownish grey color. The cellular and developmental bases of grey morphism are not understood. Here we describe cellular and ultrastructural features of grey-morph skin in relation to that of normal, wild-type skin. Melanocytes were identified histologically and counted, and melanosomes were measured using transmission electron microscopy. Grey-morph skin had fewer melanocytes when compared to wild-type skin, suggesting reduced melanocyte survival, migration, or proliferation in these whales. Grey-morph melanocytes had smaller melanosomes relative to wild-type skin, normal transport of melanosomes to surrounding keratinocytes, and normal localization of melanin granules above the keratinocyte nuclei. These findings indicate that SRW grey-morph pigmentation patterns are caused by reduced numbers of melanocytes in the skin, as well as by reduced amounts of melanin production and/or reduced sizes of mature melanosomes. Grey morphism is distinct from piebaldism and albinism found in other species, which are genetic pigmentation conditions resulting from the local absence of melanocytes, or the inability to synthesize melanin, respectively. PMID:28170433
Directory of Open Access Journals (Sweden)
Richard J Giannone
Full Text Available Nanoarchaeum equitans, the only cultured representative of the Nanoarchaeota, is dependent on direct physical contact with its host, the hyperthermophile Ignicoccus hospitalis. The molecular mechanisms that enable this relationship are unknown. Using whole-cell proteomics, differences in the relative abundance of >75% of predicted protein-coding genes from both Archaea were measured to identify the specific response of I. hospitalis to the presence of N. equitans on its surface. A purified N. equitans sample was also analyzed for evidence of interspecies protein transfer. The depth of cellular proteome coverage achieved here is amongst the highest reported for any organism. Based on changes in the proteome under the specific conditions of this study, I. hospitalis reacts to N. equitans by curtailing genetic information processing (replication, transcription in lieu of intensifying its energetic, protein processing and cellular membrane functions. We found no evidence of significant Ignicoccus biosynthetic enzymes being transported to N. equitans. These results suggest that, under laboratory conditions, N. equitans diverts some of its host's metabolism and cell cycle control to compensate for its own metabolic shortcomings, thus appearing to be entirely dependent on small, transferable metabolites and energetic precursors from I. hospitalis.
Giannone, Richard J; Huber, Harald; Karpinets, Tatiana; Heimerl, Thomas; Küper, Ulf; Rachel, Reinhard; Keller, Martin; Hettich, Robert L; Podar, Mircea
2011-01-01
Nanoarchaeum equitans, the only cultured representative of the Nanoarchaeota, is dependent on direct physical contact with its host, the hyperthermophile Ignicoccus hospitalis. The molecular mechanisms that enable this relationship are unknown. Using whole-cell proteomics, differences in the relative abundance of >75% of predicted protein-coding genes from both Archaea were measured to identify the specific response of I. hospitalis to the presence of N. equitans on its surface. A purified N. equitans sample was also analyzed for evidence of interspecies protein transfer. The depth of cellular proteome coverage achieved here is amongst the highest reported for any organism. Based on changes in the proteome under the specific conditions of this study, I. hospitalis reacts to N. equitans by curtailing genetic information processing (replication, transcription) in lieu of intensifying its energetic, protein processing and cellular membrane functions. We found no evidence of significant Ignicoccus biosynthetic enzymes being transported to N. equitans. These results suggest that, under laboratory conditions, N. equitans diverts some of its host's metabolism and cell cycle control to compensate for its own metabolic shortcomings, thus appearing to be entirely dependent on small, transferable metabolites and energetic precursors from I. hospitalis.
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
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.
DEFF Research Database (Denmark)
Fernandez-Guerra, Paula
an image cytometry protocol for HDFs that combines cellular and mitochondrial parameters: cell number and viability, thiol redox state (TRS), mitochondrial membrane potential (MMP), and mitochondrial superoxide. HDFs were analysed after treatment with various concentrations of hydrogen peroxide...... at different time points. Cell number and viability, TRS and MMP decreased in a time- and concentration-dependent manner, while mitochondrial superoxide levels were increased. Another emerging technology is targeted quantitative proteomics that can measure low abundant proteins. Selected Reaction Monitoring......Cell phenotyping of human dermal fibroblasts (HDFs) from patients with inherited metabolic diseases (IMDs) provide invaluable information for diagnosis, disease aetiology, predicting prognosis, and monitoring of treatments. HDFs possess the genetic composition of patients and many pathways...
The mandibular condylar growth center: separation and characterization of the cellular elements.
Landesberg, R; Proctor, R L; Rosier, R N; Puzas, J E
1995-01-01
The developing mandibular condylar growth center consists of a number of histologically distinct cell types. There is an increase in cell volume that takes place from the condylar surface layer through the center of ossification, resulting in a disorganized, irregular cellular pattern. Consequently, the isolation and separation of the different cells from this tissue is difficult using standard methodologies. Countercurrent centrifugal elutriation, whereby cells are separated on the basis of size, was applied to bovine mandibular condylar growth center cells. The cell volume, alkaline phosphatase content, proteoglycan synthesis, and type X collagen synthesis all showed a positive correlation with increasing cell size. The largest cells had characteristics that are consistent with hypertrophic chondrocytes; the smallest cells, on the other hand, had many fibroblastic characteristics.
Characterization of 316L Steel Cellular Dodecahedron Structures Produced by Selective Laser Melting
Directory of Open Access Journals (Sweden)
Konda Gokuldoss Prashanth
2016-10-01
Full Text Available The compression behavior of different 316L steel cellular dodecahedron structures with different density values were studied. The 316L steel structures produced using the selective laser melting process has four different geometries: single unit cells with and without the addition of base plates beneath and on top, and sandwich structures with multiple unit cells with different unit cell sizes. The relation between the relative compressive strength and the relative density was compared using different Gibson-Ashby models and with other published reports. The different aspects of the deformation and the mechanical properties were evaluated and the deformation at distinct loading levels was recorded. Finite element method (FEM simulations were carried out with the defined structures and the mechanical testing results were compared. The calculated theory, simulation estimation, and the observed experimental results are in good agreement.
Davis, Mindy I; Gross, Stefan; Shen, Min; Straley, Kimberly S; Pragani, Rajan; Lea, Wendy A; Popovici-Muller, Janeta; DeLaBarre, Byron; Artin, Erin; Thorne, Natasha; Auld, Douglas S; Li, Zhuyin; Dang, Lenny; Boxer, Matthew B; Simeonov, Anton
2014-05-16
Two mutant forms (R132H and R132C) of isocitrate dehydrogenase 1 (IDH1) have been associated with a number of cancers including glioblastoma and acute myeloid leukemia. These mutations confer a neomorphic activity of 2-hydroxyglutarate (2-HG) production, and 2-HG has previously been implicated as an oncometabolite. Inhibitors of mutant IDH1 can potentially be used to treat these diseases. In this study, we investigated the mechanism of action of a newly discovered inhibitor, ML309, using biochemical, cellular, and biophysical approaches. Substrate binding and product inhibition studies helped to further elucidate the IDH1 R132H catalytic cycle. This rapidly equilibrating inhibitor is active in both biochemical and cellular assays. The (+) isomer is active (IC50 = 68 nm), whereas the (-) isomer is over 400-fold less active (IC50 = 29 μm) for IDH1 R132H inhibition. IDH1 R132C was similarly inhibited by (+)-ML309. WT IDH1 was largely unaffected by (+)-ML309 (IC50 >36 μm). Kinetic analyses combined with microscale thermophoresis and surface plasmon resonance indicate that this reversible inhibitor binds to IDH1 R132H competitively with respect to α-ketoglutarate and uncompetitively with respect to NADPH. A reaction scheme for IDH1 R132H inhibition by ML309 is proposed in which ML309 binds to IDH1 R132H after formation of the IDH1 R132H NADPH complex. ML309 was also able to inhibit 2-HG production in a glioblastoma cell line (IC50 = 250 nm) and had minimal cytotoxicity. In the presence of racemic ML309, 2-HG levels drop rapidly. This drop was sustained until 48 h, at which point the compound was washed out and 2-HG levels recovered.
Florian, Ehmele; Michael, Kunz
2016-04-01
Several major flood events occurred in Germany in the past 15-20 years especially in the eastern parts along the rivers Elbe and Danube. Examples include the major floods of 2002 and 2013 with an estimated loss of about 2 billion Euros each. The last major flood events in the State of Baden-Württemberg in southwest Germany occurred in the years 1978 and 1993/1994 along the rivers Rhine and Neckar with an estimated total loss of about 150 million Euros (converted) each. Flood hazard originates from a combination of different meteorological, hydrological and hydraulic processes. Currently there is no defined methodology available for evaluating and quantifying the flood hazard and related risk for larger areas or whole river catchments instead of single gauges. In order to estimate the probable maximum loss for higher return periods (e.g. 200 years, PML200), a stochastic model approach is designed since observational data are limited in time and space. In our approach, precipitation is linearly composed of three elements: background precipitation, orographically-induces precipitation, and a convectively-driven part. We use linear theory of orographic precipitation formation for the stochastic precipitation model (SPM), which is based on fundamental statistics of relevant atmospheric variables. For an adequate number of historic flood events, the corresponding atmospheric conditions and parameters are determined in order to calculate a probability density function (pdf) for each variable. This method involves all theoretically possible scenarios which may not have happened, yet. This work is part of the FLORIS-SV (FLOod RISk Sparkassen Versicherung) project and establishes the first step of a complete modelling chain of the flood risk. On the basis of the generated stochastic precipitation event set, hydrological and hydraulic simulations will be performed to estimate discharge and water level. The resulting stochastic flood event set will be used to quantify the
Characterization of 22 Vibrio species by gas chromatography analysis of their cellular fatty acids.
Urdaci, M C; Marchand, M; Grimont, P A
1990-05-01
The cellular fatty acid compositions of 51 Vibrio strains belonging to 22 species as well as five Aeromonas strains were determined by using capillary gas-liquid chromatography (GLC). The major fatty acids were most often hexadecenoic, hexadecanoic and octadecenoic acids. Heptadecenoic acid was present in significant amounts in V. alginolyticus, V. natriegens, V. parahaemolyticus and "Vibrio navarrensis". Twenty fatty acids including branched and hydroxy acids were detected in the genus Vibrio. Quantitative results were treated by principal component analysis to display groups of strains. The first three components (accounting for 69% of the variance) showed the type strains of V. fischeri, V. ordalii, V. damsela, V. mediterranei, V. tubiashii, V. campbellii, V. pelagius, V. gazogenes, and V. nereis to be unclustered. V. alginolyticus (4 strains) and V. parahaemolyticus (4 strains) showed some overlap and the type strain of V. natriegens was in their neighborhood. V. harveyi (4 strains) formed a cluster and V. vulnificus was in its vicinity. V. cholerae (5 strains) overlapped with V. diazotrophicus (3 strains) and was close to the type strain of V. mimicus and V. anguillarum. V. metschnikovii (3 strains) clustered with the type strain of V. cincinnatiensis. A decision tree was devised for the identification of Vibrio species based on qualitative characteristics of fatty acid patterns. However, the following three groups, V. alginolyticus-V. parahaemolyticus-V. natriegens, V. metschnikovii-V. cincinnatiensis and V. cholerae-V. mimicus could not be split into such a decision tree.
Kim, Yong Bok; Kim, Geun Hyung
2015-02-09
Alginates have been used widely in biomedical applications because of good biocompatibility, low cost, and rapid gelation in the presence of calcium ions. However, poor mechanical properties and fabrication-ability for three-dimensional shapes have been obstacles in hard-tissue engineering applications. To overcome these shortcomings of alginates, we suggest a new composite system, consisting of a synthetic polymer, poly(ε-caprolactone), and various weight fractions (10-40 wt %) of alginate. The fabricated composite scaffolds displayed a multilayered 3D structure, consisting of microsized composite struts, and they provided a 100% offset for each layer. To show the feasibility of the scaffold for hard tissue regeneration, the composite scaffolds fabricated were assessed not only for physical properties, including surface roughness, tensile strength, and water absorption and wetting, but also in vitro osteoblastic cellular responses (cell-seeding efficiency, cell viability, fluorescence analyses, alkaline phosphatase (ALP) activity, and mineralization) by culturing with preosteoblasts (MC3T3-E1). Due to the alginate components in the composites, the scaffolds showed significantly enhanced wetting behavior, water-absorption (∼12-fold), and meaningful biological activities (∼2.1-fold for cell-seeding efficiency, ∼2.5-fold for cell-viability at 7 days, ∼3.4-fold for calcium deposition), compared with a pure PCL scaffold.
Directory of Open Access Journals (Sweden)
Santos Fabio M
2012-07-01
Full Text Available Abstract Background The neural mobilization technique is a noninvasive method that has proved clinically effective in reducing pain sensitivity and consequently in improving quality of life after neuropathic pain. The present study examined the effects of neural mobilization (NM on pain sensitivity induced by chronic constriction injury (CCI in rats. The CCI was performed on adult male rats, submitted thereafter to 10 sessions of NM, each other day, starting 14 days after the CCI injury. Over the treatment period, animals were evaluated for nociception using behavioral tests, such as tests for allodynia and thermal and mechanical hyperalgesia. At the end of the sessions, the dorsal root ganglion (DRG and spinal cord were analyzed using immunohistochemistry and Western blot assays for neural growth factor (NGF and glial fibrillary acidic protein (GFAP. Results The NM treatment induced an early reduction (from the second session of the hyperalgesia and allodynia in CCI-injured rats, which persisted until the end of the treatment. On the other hand, only after the 4th session we observed a blockade of thermal sensitivity. Regarding cellular changes, we observed a decrease of GFAP and NGF expression after NM in the ipsilateral DRG (68% and 111%, respectively and the decrease of only GFAP expression after NM in the lumbar spinal cord (L3-L6 (108%. Conclusions These data provide evidence that NM treatment reverses pain symptoms in CCI-injured rats and suggest the involvement of glial cells and NGF in such an effect.
A High-Precision Micropipette Sensor for Cellular-Level Real-Time Thermal Characterization
Directory of Open Access Journals (Sweden)
Wonseok Chang
2011-09-01
Full Text Available We report herein development of a novel glass micropipette thermal sensor fabricated in a cost-effective manner, which is capable of measuring steady thermal fluctuation at spatial resolution of ~2 µm with an accuracy of ±0.01 °C. We produced and tested various micrometer-sized sensors, ranging from 2 µm to 30 µm. The sensor comprises unleaded low-melting-point solder alloy (Sn-based as a core metal inside a pulled borosilicate glass pipette and a thin film of nickel coating outside, creating a thermocouple junction at the tip. The sensor was calibrated using a thermally insulated calibration chamber, the temperature of which can be controlled with an accuracy of ±0.01 °C, and the thermoelectric power (Seebeck coefficient of the sensor was recorded from 8.46 to 8.86 µV/°C. We have demonstrated the capability of measuring temperatures at a cellular level by inserting our temperature sensor into the membrane of a live retinal pigment epithelium cell subjected to a laser beam with a focal spot of 6 μm. We measured transient temperature profiles and the maximum temperatures were in the range of 38–55 ± 0.5 °C.
Biochemical Characterization and Cellular Effects of CADASIL Mutants of NOTCH3
He Meng; Xiaojie Zhang; Genggeng Yu; Soo Jung Lee; Y Eugene Chen; Igor Prudovsky; Wang, Michael M.
2012-01-01
Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) is the best understood cause of dominantly inherited stroke and results from NOTCH3 mutations that lead to NOTCH3 protein accumulation and selective arterial smooth muscle degeneration. Previous studies show that NOTCH3 protein forms multimers. Here, we investigate protein interactions between NOTCH3 and other vascular Notch isoforms and characterize the effects of elevated NOTCH3 on smooth mu...
Stochastic transition model for pedestrian dynamics
Schultz, Michael
2012-01-01
The proposed stochastic model for pedestrian dynamics is based on existing approaches using cellular automata, combined with substantial extensions, to compensate the deficiencies resulting of the discrete grid structure. This agent motion model is extended by both a grid-based path planning and mid-range agent interaction component. The stochastic model proves its capabilities for a quantitative reproduction of the characteristic shape of the common fundamental diagram of pedestrian dynamics. Moreover, effects of self-organizing behavior are successfully reproduced. The stochastic cellular automata approach is found to be adequate with respect to uncertainties in human motion patterns, a feature previously held by artificial noise terms alone.
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.
Fu, YuHong; Rusznák, Zoltán; Herculano-Houzel, Suzana; Watson, Charles; Paxinos, George
2013-09-01
The process of development, maturation, and regression in the central nervous system (CNS) are genetically programmed and influenced by environment. Hitherto, most research efforts have focused on either the early development of the CNS or the late changes associated with aging, whereas an important period corresponding to adolescence has been overlooked. In this study, we searched for age-dependent changes in the number of cells that compose the CNS (divided into isocortex, hippocampus, olfactory bulb, cerebellum, 'rest of the brain', and spinal cord) and the pituitary gland in 4-40-week-old C57BL6 mice, using the isotropic fractionator method in combination with neuronal nuclear protein as a marker for neuronal cells. We found that all CNS structures, except for the isocortex, increased in mass in the period of 4-15 weeks. Over the same period, the absolute number of neurons significantly increased in the olfactory bulb and cerebellum while non-neuronal cell numbers increased in the 'rest of the brain' and isocortex. Along with the gain in body length and weight, the pituitary gland also increased in mass and cell number, the latter correlating well with changes of the brain and spinal cord mass. The majority of the age-dependent alterations (e.g., somatic parameters, relative brain mass, number of pituitary cells, and cellular composition of the cerebellum, isocortex, rest of the brain, and spinal cord) occur rapidly between the 4th and 11th postnatal weeks. This period includes murine adolescence, underscoring the significance of this stage in the postnatal development of the mouse CNS.
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
Directory of Open Access Journals (Sweden)
Chang WK
2011-10-01
the liposomes at 3.3 hours. A Caco-2 cell model was used for evaluating the cytotoxicity and cell uptake efficiency of the PEG-modified lipoparticles. At a lipid content below 0.25 mM, neither the liposomes nor the lipoparticles caused significant cellular cytotoxicity (P < 0.01 and FITC-BSA was significantly taken up into cells within 60 minutes (P < 0.01. Keywords: liposomes, lipoparticles, formulation, protein, stability
Palihawadana Arachchige, Maheshika
with dextran functionalized FITC conjugated Fe3O4 nanoparticles, and our results demonstrate that there is a time-dependent distribution of these nanoparticles into different cellular compartments. Moreover, a novel conjugation of anti-cancer drug, Doxorubicin (Dox) with a labeling dye (FITC) onto dextran coated Fe3O4 nanoparticles was developed using existing EDC/NHS technique for specific drug targeting. The experiments on this unique drug-dye dual conjugation with human pancreatic cancer cell line (MIA PaCa-2) show that association of Dox onto the surface of nanoparticles enhances its penetration into the cancer cells as compared to the unconjugated drug while releasing Dox into the nucleus of the malignant cells.
Energy Technology Data Exchange (ETDEWEB)
Esfandyari-Manesh, Mehdi [Nanotechnology Research Center,Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Department of Chemistry, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Darvishi, Behrad [Nanotechnology Research Center,Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Ishkuh, Fatemeh Azizi [Department of Chemistry, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Shahmoradi, Elnaz [Department of Chemical Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Mohammadi, Ali [Nanotechnology Research Center,Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Department of Drug and Food Control, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Javanbakht, Mehran [Department of Chemistry, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Dinarvand, Rassoul [Nanotechnology Research Center,Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Atyabi, Fatemeh, E-mail: atyabifa@tums.ac.ir [Nanotechnology Research Center,Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of)
2016-05-01
showed high drug loading and encapsulation efficiency, 15.57 ± 0.84 and 100%, respectively. • Nanoparticles demonstrated a superior cellular uptake over non-targeted nanoparticles. • IC{sub 50} of nanoparticles and IC{sub 50} of free paclitaxel were 4.86 ± 0.91 and 32.80 ± 3.80 nM, respectively. • The imprinted nanoparticles showed high affinity to paclitaxel in biological samples.
Knapinska, Anna M; Tokmina-Roszyk, Dorota; Amar, Sabrina; Tokmina-Roszyk, Michal; Mochalin, Vadym N; Gogotsi, Yury; Cosme, Patrick; Terentis, Andrew C; Fields, Gregg B
2015-05-01
Nanodiamonds (NDs) have received considerable attention as potential drug delivery vehicles. NDs are small (∼5 nm diameter), can be surface modified in a controllable fashion with a variety of functional groups, and have little observed toxicity in vitro and in vivo. However, most biomedical applications of NDs utilize surface adsorption of biomolecules, as opposed to covalent attachment. Covalent modification provides reliable and reproducible ND-biomolecule ratios, and alleviates concerns over biomolecule desorption prior to delivery. The present study has outlined methods for the efficient solid-phase conjugation of ND to peptides and characterization of ND-peptide conjugates. Utilizing collagen-derived peptides, the ND was found to support or even enhance the cell adhesion and viability activities of the conjugated sequence. Thus, NDs can be incorporated into peptides and proteins in a selective manner, where the presence of the ND could potentially enhance the in vivo activities of the biomolecule it is attached to.
Lagapa, J T; Oku, Y; Kamiya, M
2008-07-01
Rats infected with the larvae of Taenia taeniaeformis harbour the intermediate stage of the parasite Strobilocercus fasciolaris within the liver. Affected animals also develop gastric and intestinal hyperplasia. The pathogenesis of the gastric hyperplasia has been extensively investigated, but few studies have addressed the nature of the intestinal changes. This study characterizes the proliferation of small intestinal epithelial cells by immunohistochemical labelling for proliferating cell nuclear antigen (PCNA) and bromodeoxyuridine (BrdU) uptake. At 6 weeks post-infection (wpi) there was an increase in villous length but crypt depth was normal. At 9 wpi there was evidence of epithelial hyperplasia, increased villous length and crypt depth, and expansion of zones of epithelial proliferation. Immunohistochemical labelling indicated that an increase in the number of proliferating cells produced a greater number of progeny cells. Intestinal hyperplasia during experimental infection with T. taeniaeformis larvae is likely to be related to the associated gastropathy, although the mechanisms underlying both changes remain undefined.
Eslami, Sohrab; Zareian, Ramin; Jalili, Nader
2012-10-01
Surface microscopy of individual biological cells is essential for determining the patterns of cell migration to study the tumor formation or metastasis. This paper presents a correlated and effective theoretical and experimental technique to automatically address the biophysical and mechanical properties and acquire live images of biological cells which are of interest in studying cancer. In the theoretical part, a distributed-parameters model as the comprehensive representation of the microcantilever is presented along with a model of the contact force as a function of the indentation depth and mechanical properties of the biological sample. Analysis of the transfer function of the whole system in the frequency domain is carried out to characterize the stiffness and damping coefficients of the sample. In the experimental section, unlike the conventional atomic force microscope techniques basically using the laser for determining the deflection of microcantilever's tip, a piezoresistive microcantilever serving as a force sensor is implemented to produce the appropriate voltage and measure the deflection of the microcantilever. A micromanipulator robotic system is integrated with the MATLAB® and programmed in such a way to automatically control the microcantilever mounted on the tip of the micromanipulator to achieve the topography of biological samples including the human corneal cells. For this purpose, the human primary corneal fibroblasts are extracted and adhered on a sterilized culture dish and prepared to attain their topographical image. The proposed methodology herein allows an approach to obtain 2D quality images of cells being comparatively cost effective and extendable to obtain 3D images of individual cells. The characterized mechanical properties of the human corneal cell are furthermore established by comparing and validating the phase shift of the theoretical and experimental results of the frequency response.
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...
Detecting Stochastic Information of Electrocardiograms
Gutíerrez, R M; Guti'errez, Rafael M.; Sandoval, Luis A.
2003-01-01
In this work we present a method to detect, identify and characterize stochastic information contained in an electrocardiogram (ECG). We assume, as it is well known, that the ECG has information corresponding to many different processes related to the cardiac activity. We analyze scaling and Markov processes properties of the detected stochastic information using the power spectrum of the ECG and the Fokker-Planck equation respectively. The detected stochastic information is then characterized by three measures. First, the slope of the power spectrum in a particular range of frequencies as a scaling parameter. Second, an empirical estimation of the drift and diffusion coefficients of the Fokker-Planck equation through the Kramers-Moyal coefficients which define the evolution of the probability distribution of the detected stochastic information.
Directory of Open Access Journals (Sweden)
Azza A. Al-Mahrouki
2014-03-01
Full Text Available Tumor radiation resistance poses a major obstacle in achieving an optimal outcome in radiation therapy. In the current study, we characterize a novel therapeutic approach that combines ultrasound-driven microbubbles with radiation to increase treatment responses in a prostate cancer xenograft model in mice. Tumor response to ultrasound-driven microbubbles and radiation was assessed 24 hours after treatment, which consisted of radiation treatments alone (2 Gy or 8 Gy or ultrasound-stimulated microbubbles only, or a combination of radiation and ultrasound-stimulated microbubbles. Immunohistochemical analysis using in situ end labeling (ISEL and terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL revealed increased cell death within tumors exposed to combined treatments compared with untreated tumors or tumors exposed to radiation alone. Several biomarkers were investigated to evaluate cell proliferation (Ki67, blood leakage (factor VIII, angiogenesis (cluster of differentiation molecule CD31, ceramide-formation, angiogenesis signaling [vascular endothelial growth factor (VEGF], oxygen limitation (prolyl hydroxylase PHD2 and DNA damage/repair (γH2AX. Results demonstrated reduced vascularity due to vascular disruption by ultrasound-stimulated microbubbles, increased ceramide production and increased DNA damage of tumor cells, despite decreased tumor oxygenation with significantly less proliferating cells in the combined treatments. This combined approach could be a feasible option as a novel enhancing approach in radiation therapy.
Ari-Wahjoedi, Bambang; Ginta, Turnad Lenggo; Parman, Setyamartana; Abustaman, Mohd Zikri Ahmad
2014-10-01
Multicellular monolithic ceramic body is a ceramic material which has many gas or liquid passages partitioned by thin walls throughout the bulk material. There are many currently known advanced industrial applications of multicellular ceramics structures i.e. as supports for various catalysts, electrode support structure for solid oxide fuel cells, refractories, electric/electronic materials, aerospace vehicle re-entry heat shields and biomaterials for dental as well as orthopaedic implants by naming only a few. Multicellular ceramic bodies are usually made of ceramic phases such as mullite, cordierite, aluminum titanate or pure oxides such as silica, zirconia and alumina. What make alumina ceramics is excellent for the above functions are the intrinsic properties of alumina which are hard, wear resistant, excellent dielectric properties, resists strong acid and alkali attacks at elevated temperatures, good thermal conductivities, high strength and stiffness as well as biocompatible. In this work the processing technology leading to truly multicellular monolithic alumina ceramic bodies and their characterization are reported. Ceramic slip with 66 wt.% solid loading was found to be optimum as impregnant to the polyurethane foam template. Mullitic ceramic composite of alumina-sodium alumino disilicate-Leucite-like phases with bulk and true densities of 0.852 and 1.241 g cm-3 respectively, pore linear density of ±35 cm-1, linear and bulk volume shrinkages of 7-16% and 32 vol.% were obtained. The compressive strength and elastic modulus of the bioceramics are ≈0.5-1.0 and ≈20 MPa respectively.
Foliated stochastic calculus: Harmonic measures
Catuogno, Pedro J; Ruffino, Paulo R
2010-01-01
In this article we present an intrinsec construction of foliated Brownian motion via stochastic calculus adapted to foliation. The stochastic approach together with a proposed foliated vector calculus provide a natural method to work on harmonic measures. Other results include a decomposition of the Laplacian in terms of the foliated and basic Laplacians, a characterization of totally invariant measures and a differential equation for the density of harmonic measures.
Energy Technology Data Exchange (ETDEWEB)
Ari-Wahjoedi, Bambang, E-mail: bambang-ariwahjoedi@petronas.com.my [Department of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak Darul Ridzuan (Malaysia); Centre for Intelligent Signal and Imaging Research, Universiti Teknologi PETRONAS, Bandar Seri Iskandar (Malaysia); Ginta, Turnad Lenggo [Department of Mechanical Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak Darul Ridzuan (Malaysia); Centre for Intelligent Signal and Imaging Research, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tro (Malaysia); Parman, Setyamartana [Department of Mechanical Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak Darul Ridzuan (Malaysia); Abustaman, Mohd Zikri Ahmad [Kebabangan Petroleum Operating Company Sdn Bhd, Lvl. 52, Tower 2, PETRONAS Twin Towers, KLCC, 50088 Kuala Lumpur (Malaysia)
2014-10-24
Multicellular monolithic ceramic body is a ceramic material which has many gas or liquid passages partitioned by thin walls throughout the bulk material. There are many currently known advanced industrial applications of multicellular ceramics structures i.e. as supports for various catalysts, electrode support structure for solid oxide fuel cells, refractories, electric/electronic materials, aerospace vehicle re-entry heat shields and biomaterials for dental as well as orthopaedic implants by naming only a few. Multicellular ceramic bodies are usually made of ceramic phases such as mullite, cordierite, aluminum titanate or pure oxides such as silica, zirconia and alumina. What make alumina ceramics is excellent for the above functions are the intrinsic properties of alumina which are hard, wear resistant, excellent dielectric properties, resists strong acid and alkali attacks at elevated temperatures, good thermal conductivities, high strength and stiffness as well as biocompatible. In this work the processing technology leading to truly multicellular monolithic alumina ceramic bodies and their characterization are reported. Ceramic slip with 66 wt.% solid loading was found to be optimum as impregnant to the polyurethane foam template. Mullitic ceramic composite of alumina-sodium alumino disilicate-Leucite-like phases with bulk and true densities of 0.852 and 1.241 g cm{sup −3} respectively, pore linear density of ±35 cm{sup −1}, linear and bulk volume shrinkages of 7-16% and 32 vol.% were obtained. The compressive strength and elastic modulus of the bioceramics are ≈0.5-1.0 and ≈20 MPa respectively.
Cellular characterization of cells from the Fanconi anemia complementation group, FA-D1/BRCA2
Energy Technology Data Exchange (ETDEWEB)
Godthelp, Barbara C. [Department of Toxicogenetics, Leiden University Medical Center, Building 2, Postzone S-6-P, P.O. Box 9600, 2300 RC, Leiden (Netherlands); Buul, Paul P.W. van [Department of Toxicogenetics, Leiden University Medical Center, Building 2, Postzone S-6-P, P.O. Box 9600, 2300 RC, Leiden (Netherlands); Jaspers, Nicolaas G.J. [Department of Cell Biology and Genetics, Erasmus University, P.O. Box 1738, 3000 DR Rotterdam (Netherlands); Elghalbzouri-Maghrani, Elhaam [Department of Toxicogenetics, Leiden University Medical Center, Building 2, Postzone S-6-P, P.O. Box 9600, 2300 RC, Leiden (Netherlands); Duijn-Goedhart, Annemarie van [Department of Toxicogenetics, Leiden University Medical Center, Building 2, Postzone S-6-P, P.O. Box 9600, 2300 RC, Leiden (Netherlands); Arwert, Fre [Department of Clinical Genetics and Human Genetics, Free University Medical Center, Amsterdam (Netherlands); Joenje, Hans [Department of Clinical Genetics and Human Genetics, Free University Medical Center, Amsterdam (Netherlands); Zdzienicka, Malgorzata Z. [Department of Toxicogenetics, Leiden University Medical Center, Building 2, Postzone S-6-P, P.O. Box 9600, 2300 RC, Leiden (Netherlands) and Department of Molecular Cell Genetics, Collegium Medicum, N.Copernicus University, Bydgoszcz (Poland)]. E-mail: M.Z.Zdzienicka@LUMC.nl
2006-10-10
Fanconi anemia (FA) is an inherited cancer-susceptibility disorder, characterized by genomic instability and hypersensitivity to DNA cross-linking agents. The discovery of biallelic BRCA2 mutations in the FA-D1 complementation group allows for the first time to study the characteristics of primary BRCA2-deficient human cells. FANCD1/BRCA2-deficient fibroblasts appeared hypersensitive to mitomycin C (MMC), slightly sensitive to methyl methane sulfonate (MMS), and like cells derived from other FA complementation groups, not sensitive to X-ray irradiation. However, unlike other FA cells, FA-D1 cells were slightly sensitive to UV irradiation. Despite the observed lack of X-ray sensitivity in cell survival, significant radioresistant DNA synthesis (RDS) was observed in the BRCA2-deficient fibroblasts but also in the FANCA-deficient fibroblasts, suggesting an impaired S-phase checkpoint. FA-D1/BRCA2 cells displayed greatly enhanced levels of spontaneous as well as MMC-induced chromosomal aberrations (Canada), similar to cells deficient in homologous recombination (HR) and non-D1 FA cells. In contrast to Brca2-deficient rodent cells, FA-D1/BRCA2 cells showed normal sister chromatid exchange (SCE) levels, both spontaneous as well as after MMC treatment. Hence, these data indicate that human cells with biallelic BRCA2 mutations display typical features of both FA- and HR-deficient cells, which suggests that FANCD1/BRCA2 is part of the integrated FA/BRCA DNA damage response pathway but also controls other functions outside the FA pathway.
Stochastic Kinetics of Nascent RNA
Xu, Heng; Skinner, Samuel O.; Sokac, Anna Marie; Golding, Ido
2016-09-01
The stochastic kinetics of transcription is typically inferred from the distribution of RNA numbers in individual cells. However, cellular RNA reflects additional processes downstream of transcription, hampering this analysis. In contrast, nascent (actively transcribed) RNA closely reflects the kinetics of transcription. We present a theoretical model for the stochastic kinetics of nascent RNA, which we solve to obtain the probability distribution of nascent RNA per gene. The model allows us to evaluate the kinetic parameters of transcription from single-cell measurements of nascent RNA. The model also predicts surprising discontinuities in the distribution of nascent RNA, a feature which we verify experimentally.
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.
Balakrishnan, Suhrid; Roy, Amit; Ierapetritou, Marianthi G.; Flach, Gregory P.; Georgopoulos, Panos G.
2003-12-01
In this work, a computationally efficient Bayesian framework for the reduction and characterization of parametric uncertainty in computationally demanding environmental 3-D numerical models has been developed. The framework is based on the combined application of the Stochastic Response Surface Method (SRSM, which generates accurate and computationally efficient statistically equivalent reduced models) and the Markov chain Monte Carlo method. The application selected to demonstrate this framework involves steady state groundwater flow at the U.S. Department of Energy Savannah River Site General Separations Area, modeled using the Subsurface Flow And Contaminant Transport (FACT) code. Input parameter uncertainty, based initially on expert opinion, was found to decrease in all variables of the posterior distribution. The joint posterior distribution obtained was then further used for the final uncertainty analysis of the stream base flows and well location hydraulic head values.
Energy Technology Data Exchange (ETDEWEB)
Foxall, W; Cunningham, C; Mellors, R; Templeton, D; Dyer, K; White, J
2012-02-27
ability to detect evidence for an underground facility using InSAR depends on the displacement sensitivity and spatial resolution of the interferogram, as well as on the size and depth of the facility and the time since its completion. The methodology development described in this report focuses on the exploitation of synthetic aperture radar data that are available commercially from a number of satellite missions. Development of the method involves three components: (1) Evaluation of the capability of InSAR to detect and characterize underground facilities ; (2) inversion of InSAR data to infer the location, depth, shape and volume of a subsurface facility; and (3) evaluation and selection of suitable geomechanical forward models to use in the inversion. We adapted LLNL's general-purpose Bayesian Markov Chain-Monte Carlo procedure, the 'Stochastic Engine' (SE), to carry out inversions to characterize subsurface void geometries. The SE performs forward simulations for a large number of trial source models to identify the set of models that are consistent with the observations and prior constraints. The inverse solution produced by this kind of stochastic method is a posterior probability density function (pdf) over alternative models, which forms an appropriate input to risk-based decision analyses to evaluate subsequent response strategies. One major advantage of a stochastic inversion approach is its ability to deal with complex, non-linear forward models employing empirical, analytical or numerical methods. However, while a geomechanical model must incorporate adequate physics to enable sufficiently accurate prediction of surface displacements, it must also be computationally fast enough to render the large number of forward realizations needed in stochastic inversion feasible. This latter requirement prompted us first to investigate computationally efficient empirical relations and closed-form analytical solutions. However, our evaluation revealed
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
Institute of Scientific and Technical Information of China (English)
Katsuaki Koike
2011-01-01
Sample data in the Earth and environmental sciences are limited in quantity and sampling location and therefore, sophisticated spatial modeling techniques are indispensable for accurate imaging of complicated structures and properties of geomaterials. This paper presents several effective methods that are grouped into two categories depending on the nature of regionalized data used. Type I data originate from plural populations and type II data satisfy the prerequisite of stationarity and have distinct spatial correlations. For the type I data, three methods are shown to be effective and demonstrated to produce plausible results: (1) a spline-based method, (2) a combination of a spline-based method with a stochastic simulation, and (3) a neural network method. Geostatistics proves to be a powerful tool for type II data. Three new approaches of geostatistics are presented with case studies: an application to directional data such as fracture, multi-scale modeling that incorporates a scaling law,and space-time joint analysis for multivariate data. Methods for improving the contribution of such spatial modeling to Earth and environmental sciences are also discussed and future important problems to be solved are summarized.
Energy Technology Data Exchange (ETDEWEB)
Foxall, W; Cunningham, C; Mellors, R; Templeton, D; Dyer, K; White, J
2012-02-27
ability to detect evidence for an underground facility using InSAR depends on the displacement sensitivity and spatial resolution of the interferogram, as well as on the size and depth of the facility and the time since its completion. The methodology development described in this report focuses on the exploitation of synthetic aperture radar data that are available commercially from a number of satellite missions. Development of the method involves three components: (1) Evaluation of the capability of InSAR to detect and characterize underground facilities ; (2) inversion of InSAR data to infer the location, depth, shape and volume of a subsurface facility; and (3) evaluation and selection of suitable geomechanical forward models to use in the inversion. We adapted LLNL's general-purpose Bayesian Markov Chain-Monte Carlo procedure, the 'Stochastic Engine' (SE), to carry out inversions to characterize subsurface void geometries. The SE performs forward simulations for a large number of trial source models to identify the set of models that are consistent with the observations and prior constraints. The inverse solution produced by this kind of stochastic method is a posterior probability density function (pdf) over alternative models, which forms an appropriate input to risk-based decision analyses to evaluate subsequent response strategies. One major advantage of a stochastic inversion approach is its ability to deal with complex, non-linear forward models employing empirical, analytical or numerical methods. However, while a geomechanical model must incorporate adequate physics to enable sufficiently accurate prediction of surface displacements, it must also be computationally fast enough to render the large number of forward realizations needed in stochastic inversion feasible. This latter requirement prompted us first to investigate computationally efficient empirical relations and closed-form analytical solutions. However, our evaluation revealed
Woodell-May, Jennifer E; Tan, Matthew L; King, William J; Swift, Matthew J; Welch, Zachary R; Murphy, Michael P; McKale, James M
2015-01-01
Critical limb ischemia (CLI) is a terminal disease with high morbidity and healthcare costs due to limb loss. There are no effective medical therapies for patients with CLI to prevent amputation. Cell-based therapies are currently being investigated to address this unmet clinical need and have shown promising preliminary results. The purpose of this study was to characterize the output of a point-of-care cell separator (MarrowStim P.A.D. Kit), currently under investigation for the treatment of CLI, and compare its output with Ficoll-based separation. The outputs of the MarrowStim P.A.D. Kit and Ficoll separation were characterized using an automated hematology analyzer, colony-forming unit (CFU) assays, and tubulogenesis assays. Hematology analysis indicated that the MarrowStim P.A.D. Kit concentrated the total nucleated cells, mononuclear cells, and granulocytes compared with baseline bone marrow aspirate. Cells collected were positive for VEGFR-2, CD3, CD14, CD34, CD45, CD56, CD105, CD117, CD133, and Stro-1 antigen. CFU assays demonstrated that the MarrowStim P.A.D. Kit output a significantly greater number of mesenchymal stem cells and hematopoietic stem cells compared with cells output by Ficoll separation. There was no significant difference in the number of endothelial progenitor cells output by the two separation techniques. Isolated cells from both techniques formed interconnected nodes and microtubules in a three-dimensional cell culture assay. This information, along with data currently being collected in large-scale clinical trials, will help instruct how different cellular fractions may affect the outcomes for CLI patients.
Directory of Open Access Journals (Sweden)
Rajesh Prasad
Full Text Available Papain-like cysteine proteases of malaria parasites degrade haemoglobin in an acidic food vacuole to provide amino acids for intraerythrocytic parasites. These proteases are potential drug targets because their inhibitors block parasite development, and efforts are underway to develop chemotherapeutic inhibitors of these proteases as the treatments for malaria. Plasmodium knowlesi has recently been shown to be an important human pathogen in parts of Asia. We report expression and characterization of three P. knowlesi papain-like proteases, termed knowpains (KP2-4. Recombinant knowpains were produced using a bacterial expression system, and tested for various biochemical properties. Antibodies against recombinant knowpains were generated and used to determine their cellular localization in parasites. Inhibitory effects of the cysteine protease inhibitor E64 were assessed on P. knowlesi culture to validate drug target potential of knowpains. All three knowpains were present in the food vacuole, active in acidic pH, and capable of degrading haemoglobin at the food vacuolar pH (≈5.5, suggesting roles in haemoglobin degradation. The proteases showed absolute (KP2 and KP3 to moderate (KP4 preference for peptide substrates containing leucine at the P2 position; KP4 preferred arginine at the P2 position. While the three knowpains appear to have redundant roles in haemoglobin degradation, KP4 may also have a role in degradation of erythrocyte cytoskeleton during merozoite egress, as it displayed broad substrate specificity and was primarily localized at the parasite periphery. Importantly, E64 blocked erythrocytic development of P. knowlesi, with enlargement of food vacuoles, indicating inhibition of haemoglobin hydrolysis and supporting the potential for inhibition of knowpains as a strategy for the treatment of malaria. Functional expression and characterization of knowpains should enable simultaneous screening of available cysteine protease
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...
Directory of Open Access Journals (Sweden)
Saleh Heneidi
Full Text Available Advances in stem cell therapy face major clinical limitations, particularly challenged by low rates of post-transplant cell survival. Hostile host factors of the engraftment microenvironment such as hypoxia, nutrition deprivation, pro-inflammatory cytokines, and reactive oxygen species can each contribute to unwanted differentiation or apoptosis. In this report, we describe the isolation and characterization of a new population of adipose tissue (AT derived pluripotent stem cells, termed Multilineage Differentiating Stress-Enduring (Muse Cells, which are isolated using severe cellular stress conditions, including long-term exposure to the proteolytic enzyme collagenase, serum deprivation, low temperatures and hypoxia. Under these conditions, a highly purified population of Muse-AT cells is isolated without the utilization of cell sorting methods. Muse-AT cells grow in suspension as cell spheres reminiscent of embryonic stem cell clusters. Muse-AT cells are positive for the pluripotency markers SSEA3, TR-1-60, Oct3/4, Nanog and Sox2, and can spontaneously differentiate into mesenchymal, endodermal and ectodermal cell lineages with an efficiency of 23%, 20% and 22%, respectively. When using specific differentiation media, differentiation efficiency is greatly enhanced in Muse-AT cells (82% for mesenchymal, 75% for endodermal and 78% for ectodermal. When compared to adipose stem cells (ASCs, microarray data indicate a substantial up-regulation of Sox2, Oct3/4, and Rex1. Muse-ATs also exhibit gene expression patterns associated with the down-regulation of genes involved in cell death and survival, embryonic development, DNA replication and repair, cell cycle and potential factors related to oncogenecity. Gene expression analysis indicates that Muse-ATs and ASCs are mesenchymal in origin; however, Muse-ATs also express numerous lymphocytic and hematopoietic genes, such as CCR1 and CXCL2, encoding chemokine receptors and ligands involved in stem cell
Heneidi, Saleh; Simerman, Ariel A; Keller, Erica; Singh, Prapti; Li, Xinmin; Dumesic, Daniel A; Chazenbalk, Gregorio
2013-01-01
Advances in stem cell therapy face major clinical limitations, particularly challenged by low rates of post-transplant cell survival. Hostile host factors of the engraftment microenvironment such as hypoxia, nutrition deprivation, pro-inflammatory cytokines, and reactive oxygen species can each contribute to unwanted differentiation or apoptosis. In this report, we describe the isolation and characterization of a new population of adipose tissue (AT) derived pluripotent stem cells, termed Multilineage Differentiating Stress-Enduring (Muse) Cells, which are isolated using severe cellular stress conditions, including long-term exposure to the proteolytic enzyme collagenase, serum deprivation, low temperatures and hypoxia. Under these conditions, a highly purified population of Muse-AT cells is isolated without the utilization of cell sorting methods. Muse-AT cells grow in suspension as cell spheres reminiscent of embryonic stem cell clusters. Muse-AT cells are positive for the pluripotency markers SSEA3, TR-1-60, Oct3/4, Nanog and Sox2, and can spontaneously differentiate into mesenchymal, endodermal and ectodermal cell lineages with an efficiency of 23%, 20% and 22%, respectively. When using specific differentiation media, differentiation efficiency is greatly enhanced in Muse-AT cells (82% for mesenchymal, 75% for endodermal and 78% for ectodermal). When compared to adipose stem cells (ASCs), microarray data indicate a substantial up-regulation of Sox2, Oct3/4, and Rex1. Muse-ATs also exhibit gene expression patterns associated with the down-regulation of genes involved in cell death and survival, embryonic development, DNA replication and repair, cell cycle and potential factors related to oncogenecity. Gene expression analysis indicates that Muse-ATs and ASCs are mesenchymal in origin; however, Muse-ATs also express numerous lymphocytic and hematopoietic genes, such as CCR1 and CXCL2, encoding chemokine receptors and ligands involved in stem cell homing. Being
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.
Directory of Open Access Journals (Sweden)
Staci L Solin
Full Text Available In this study we describe the molecular and cellular characterization of a zebrafish mutant that develops tumors in the optic pathway. Heterozygous Tg(flk1:RFPis18 transgenic adults develop tumors of the retina, optic nerve and optic tract. Molecular and genetic mapping demonstrate the tumor phenotype is linked to a high copy number transgene array integrated in the lincRNA gene lincRNAis18/Zv9_00007276 on chromosome 3. TALENs were used to isolate a 147 kb deletion allele that removes exons 2-5 of the lincRNAis18 gene. Deletion allele homozygotes are viable and do not develop tumors, indicating loss of function of the lincRNAis18 locus is not the trigger for tumor onset. Optic pathway tumors in the Tg(flk1:RFPis18 mutant occur with a penetrance of 80-100% by 1 year of age. The retinal tumors are highly vascularized and composed of rosettes of various sizes embedded in a fibrous matrix. Immunohistochemical analysis showed increased expression of the glial markers GFAP and BLBP throughout retinal tumors and in dysplastic optic nerve. We performed transcriptome analysis of pre-tumorous retina and retinal tumor tissue and found changes in gene expression signatures of radial glia and astrocytes (slc1a3, activated glia (atf3, blbp, apoeb, proliferating neural progenitors (foxd3, nestin, cdh2, her9/hes1, and glioma markers (S100β, vim. The transcriptome also revealed activation of cAMP, Stat3 and Wnt signal transduction pathways. qRT-PCR confirmed >10-fold overexpression of the Wnt pathway components hbegfa, ascl1a, and insm1a. Together the data indicate Müller glia and/or astrocyte-derived progenitors could contribute to the zebrafish Tg(flk1:RFPis18 optic pathway tumors.
Directory of Open Access Journals (Sweden)
Débora L Oliveira
Full Text Available BACKGROUND: Extracellular vesicles in yeast cells are involved in the molecular traffic across the cell wall. In yeast pathogens, these vesicles have been implicated in the transport of proteins, lipids, polysaccharide and pigments to the extracellular space. Cellular pathways required for the biogenesis of yeast extracellular vesicles are largely unknown. METHODOLOGY/PRINCIPAL FINDINGS: We characterized extracellular vesicle production in wild type (WT and mutant strains of the model yeast Saccharomyces cerevisiae using transmission electron microscopy in combination with light scattering analysis, lipid extraction and proteomics. WT cells and mutants with defective expression of Sec4p, a secretory vesicle-associated Rab GTPase essential for Golgi-derived exocytosis, or Snf7p, which is involved in multivesicular body (MVB formation, were analyzed in parallel. Bilayered vesicles with diameters at the 100-300 nm range were found in extracellular fractions from yeast cultures. Proteomic analysis of vesicular fractions from the cells aforementioned and additional mutants with defects in conventional secretion pathways (sec1-1, fusion of Golgi-derived exocytic vesicles with the plasma membrane; bos1-1, vesicle targeting to the Golgi complex or MVB functionality (vps23, late endosomal trafficking revealed a complex and interrelated protein collection. Semi-quantitative analysis of protein abundance revealed that mutations in both MVB- and Golgi-derived pathways affected the composition of yeast extracellular vesicles, but none abrogated vesicle production. Lipid analysis revealed that mutants with defects in Golgi-related components of the secretory pathway had slower vesicle release kinetics, as inferred from intracellular accumulation of sterols and reduced detection of these lipids in vesicle fractions in comparison with WT cells. CONCLUSIONS/SIGNIFICANCE: Our results suggest that both conventional and unconventional pathways of secretion are
Energy Technology Data Exchange (ETDEWEB)
Bhaskar,; Kumari, Neeti [Division of Biochemistry, CSIR-Central Drug Research Institute, Chattar Manzil Palace, PO Box 173, Lucknow (India); Goyal, Neena, E-mail: neenacdri@yahoo.com [Division of Biochemistry, CSIR-Central Drug Research Institute, Chattar Manzil Palace, PO Box 173, Lucknow (India)
2012-12-07
Highlights: Black-Right-Pointing-Pointer The study presents cloning and characterization of TCP1{gamma} gene from L. donovani. Black-Right-Pointing-Pointer TCP1{gamma} is a subunit of T-complex protein-1 (TCP1), a chaperonin class of protein. Black-Right-Pointing-Pointer LdTCP{gamma} exhibited differential expression in different stages of promastigotes. Black-Right-Pointing-Pointer LdTCP{gamma} co-localized with actin, a cytoskeleton protein. Black-Right-Pointing-Pointer The data suggests that this gene may have a role in differentiation/biogenesis. Black-Right-Pointing-Pointer First report on this chapronin in Leishmania. -- Abstract: T-complex protein-1 (TCP1) complex, a chaperonin class of protein, ubiquitous in all genera of life, is involved in intracellular assembly and folding of various proteins. The gamma subunit of TCP1 complex (TCP1{gamma}), plays a pivotal role in the folding and assembly of cytoskeleton protein(s) as an individual or complexed with other subunits. Here, we report for the first time cloning, characterization and expression of the TCP1{gamma} of Leishmania donovani (LdTCP1{gamma}), the causative agent of Indian Kala-azar. Primary sequence analysis of LdTCP1{gamma} revealed the presence of all the characteristic features of TCP1{gamma}. However, leishmanial TCP1{gamma} represents a distinct kinetoplastid group, clustered in a separate branch of the phylogenic tree. LdTCP1{gamma} exhibited differential expression in different stages of promastigotes. The non-dividing stationary phase promastigotes exhibited 2.5-fold less expression of LdTCP1{gamma} as compared to rapidly dividing log phase parasites. The sub-cellular distribution of LdTCP1{gamma} was studied in log phase promastigotes by employing indirect immunofluorescence microscopy. The protein was present not only in cytoplasm but it was also localized in nucleus, peri-nuclear region, flagella, flagellar pocket and apical region. Co-localization of LdTCP1{gamma} with actin suggests
Stochastic superparameterization in quasigeostrophic turbulence
Energy Technology Data Exchange (ETDEWEB)
Grooms, Ian, E-mail: grooms@cims.nyu.edu [Center for Atmosphere Ocean Science, Courant Institute of Mathematical Sciences, New York University, 251 Mercer St., New York, NY 10012 (United States); Majda, Andrew J., E-mail: jonjon@cims.nyu.edu [Center for Atmosphere Ocean Science, Courant Institute of Mathematical Sciences, New York University, 251 Mercer St., New York, NY 10012 (United States); Center for Prototype Climate Modelling, NYU-Abu Dhabi (United Arab Emirates)
2014-08-15
In this article we expand and develop the authors' recent proposed methodology for efficient stochastic superparameterization algorithms for geophysical turbulence. Geophysical turbulence is characterized by significant intermittent cascades of energy from the unresolved to the resolved scales resulting in complex patterns of waves, jets, and vortices. Conventional superparameterization simulates large scale dynamics on a coarse grid in a physical domain, and couples these dynamics to high-resolution simulations on periodic domains embedded in the coarse grid. Stochastic superparameterization replaces the nonlinear, deterministic eddy equations on periodic embedded domains by quasilinear stochastic approximations on formally infinite embedded domains. The result is a seamless algorithm which never uses a small scale grid and is far cheaper than conventional SP, but with significant success in difficult test problems. Various design choices in the algorithm are investigated in detail here, including decoupling the timescale of evolution on the embedded domains from the length of the time step used on the coarse grid, and sensitivity to certain assumed properties of the eddies (e.g. the shape of the assumed eddy energy spectrum). We present four closures based on stochastic superparameterization which elucidate the properties of the underlying framework: a ‘null hypothesis’ stochastic closure that uncouples the eddies from the mean, a stochastic closure with nonlinearly coupled eddies and mean, a nonlinear deterministic closure, and a stochastic closure based on energy conservation. The different algorithms are compared and contrasted on a stringent test suite for quasigeostrophic turbulence involving two-layer dynamics on a β-plane forced by an imposed background shear. The success of the algorithms developed here suggests that they may be fruitfully applied to more realistic situations. They are expected to be particularly useful in providing accurate and
Robustness of a Cellular Automata Model for the HIV Infection
Figueirêdo, P H; Santos, R M Zorzenon dos
2008-01-01
An investigation was conducted to study the robustness of the results obtained from the cellular automata model which describes the spread of the HIV infection within lymphoid tissues [R. M. Zorzenon dos Santos and S. Coutinho, Phys. Rev. Lett. 87, 168102 (2001)]. The analysis focussed on the dynamic behavior of the model when defined in lattices with different symmetries and dimensionalities. The results illustrated that the three-phase dynamics of the planar models suffered minor changes in relation to lattice symmetry variations and, while differences were observed regarding dimensionality changes, qualitative behavior was preserved. A further investigation was conducted into primary infection and sensitiveness of the latency period to variations of the model's stochastic parameters over wide ranging values. The variables characterizing primary infection and the latency period exhibited power-law behavior when the stochastic parameters varied over a few orders of magnitude. The power-law exponents were app...
Indian Academy of Sciences (India)
S K Das
2011-08-01
An earlier developed stochastic model has been applied to describe the relative rate of material loss from the steel surface subjected to simultaneous action of high temperature oxidation involving multiple oxides and mechanical erosion. Different oxide scale growths, namely, nickel, iron and chromium have been treated deterministically and erosion is described using a literature based probabilistic framework. Oxidation is described with a power law (parabolic) approach to quantify the rate of growth of all the three oxide scales. In consonance with the published model, erosion is treated using a probabilistic methodology as spatially random phenomena on the oxide surface. The concept of ‘erosion footprint’ has been incorporated in the present model to characterize the erosion-induced damage on the steel surface. The model has been applied to predict the relative material loss as a function of time resulted from erosion–oxidation interaction pertaining to nickel, iron and chromium oxides in dimensionless form. This investigation is expected to provide a quantitative understanding of relative material loss due to solid particle erosion for oxide scales, (composed of multiple oxides) formed on the steel components of coal-ﬁred boilers.
Zanderigo, Francesca; Bertoldo, Alessandra; Pillonetto, Gianluigi; Cobelli Ast, Claudio
2009-05-01
An accurate characterization of tissue residue function R(t) in bolus-tracking magnetic resonance imaging is of crucial importance to quantify cerebral hemodynamics. R(t) estimation requires to solve a deconvolution problem. The most popular deconvolution method is singular value decomposition (SVD). However, SVD is known to bear some limitations, e.g., R(t) profiles exhibit nonphysiological oscillations and take on negative values. In addition, SVD estimates are biased in presence of bolus delay and dispersion. Recently, other deconvolution methods have been proposed, in particular block-circulant SVD (cSVD) and Tikhonov regularization (TIKH). Here we propose a new method based on nonlinear stochastic regularization (NSR). NSR is tested on simulated data and compared with SVD, cSVD, and TIKH in presence and absence of bolus dispersion. A clinical case in one patient has also been considered. NSR is shown to perform better than SVD, cSVD, and TIKH in reconstructing both the peak and the residue function, in particular when bolus dispersion is considered. In addition, differently from SVD, cSVD, and TIKH, NSR always provides positive and smooth R(t).
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.
PRODUCTIVE GOVERNMENT EXPENDITURE IN A STOCHASTICALLY GROWING OPEN ECONOMY
Institute of Scientific and Technical Information of China (English)
Haijun WANG; Shigeng HU
2007-01-01
This paper employs a stochastic endogenous growth model with productive government expenditure in a small open economy to analyze the optimal fiscal policy.First,a stochastic model of a small open economy is constructed.Second.the equilibrium solutions of the representative agent's stochastic optimization problem are derived.Third,we obtain the equilibrium solutions of the central planner's stochastic optimization problem and the optimal government expenditure policy.Finally,the optimal tax policy is characterized.
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...
Li, Xiuying; Chen, Dan; Le, Chaoyi; Zhu, Chunliu; Gan, Yong; Hovgaard, Lars; Yang, Mingshi
2011-01-01
Background The aim of this study was to investigate the intestinal mucus-penetrating properties and intestinal cellular uptake of two types of liposomes modified by Pluronic F127 (PF127). Methods The two types of liposomes, ie, PF127-inlaid liposomes and PF127-adsorbed liposomes, were prepared by a thin-film hydration method followed by extrusion, in which coumarin 6 was loaded as a fluorescence marker. A modified Franz diffusion cell mounted with the intestinal mucus of rats was used to study the diffusion characteristics of the two types of PF127 liposomes. Cell uptake studies were conducted in Caco-2 cells and analyzed using confocal laser scanning microcopy as well as flow cytometry. Results The diffusion efficiency of the two types of PF127-modified liposomes through intestinal rat mucus was 5–7-fold higher than that of unmodified liposomes. Compared with unmodified liposomes, PF127-inlaid liposomes showed significantly higher cellular uptake of courmarin 6. PF127-adsorbed liposomes showed a lower cellular uptake. Moreover, and interestingly, the two types of PF127-modified liposomes showed different cellular uptake mechanisms in Caco-2 cells. Conclusion PF127-inlaid liposomes with improved intestinal mucus-penetrating ability and enhanced cellular uptake might be a potential carrier candidate for oral drug delivery. PMID:22163166
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.
Stochastic superparameterization in quasigeostrophic turbulence
Grooms, Ian
2013-01-01
In this article we expand and develop the authors' recent proposed methodology for efficient stochastic superparameterization (SP) algorithms for geophysical turbulence. Geophysical turbulence is characterized by significant intermittent cascades of energy from the unresolved to the resolved scales resulting in complex patterns of waves, jets, and vortices. Conventional SP simulates large scale dynamics on a coarse grid in a physical domain, and couples these dynamics to high-resolution simulations on periodic domains embedded in the coarse grid. Stochastic SP replaces the nonlinear, deterministic eddy equations on periodic embedded domains by quasilinear stochastic approximations on formally infinite embedded domains. The result is a seamless algorithm which never uses a small scale grid and is far cheaper than conventional SP, but with significant success in difficult test problems. Various design choices in the algorithm are investigated in detail here, including decoupling the timescale of evolution on th...
Directory of Open Access Journals (Sweden)
Li X
2011-12-01
Full Text Available Xiuying Li1, Dan Chen1, Chaoyi Le2, Chunliu Zhu1, Yong Gan1, Lars Hovgaard3, Mingshi Yang41Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, China; 2University of Toronto Mississauga Campus, Ontario, Canada; 3Oral Formulation Development, Novo Nordisk A/S, Maalov; 4Department of Pharmaceutics and Analytical Chemistry, University of Copenhagen, Copenhagen, DenmarkBackground: The aim of this study was to investigate the intestinal mucus-penetrating properties and intestinal cellular uptake of two types of liposomes modified by Pluronic F127 (PF127.Methods: The two types of liposomes, ie, PF127-inlaid liposomes and PF127-adsorbed liposomes, were prepared by a thin-film hydration method followed by extrusion, in which coumarin 6 was loaded as a fluorescence marker. A modified Franz diffusion cell mounted with the intestinal mucus of rats was used to study the diffusion characteristics of the two types of PF127 liposomes. Cell uptake studies were conducted in Caco-2 cells and analyzed using confocal laser scanning microcopy as well as flow cytometry.Results: The diffusion efficiency of the two types of PF127-modified liposomes through intestinal rat mucus was 5–7-fold higher than that of unmodified liposomes. Compared with unmodified liposomes, PF127-inlaid liposomes showed significantly higher cellular uptake of courmarin 6. PF127-adsorbed liposomes showed a lower cellular uptake. Moreover, and interestingly, the two types of PF127-modified liposomes showed different cellular uptake mechanisms in Caco-2 cells.Conclusion: PF127-inlaid liposomes with improved intestinal mucus-penetrating ability and enhanced cellular uptake might be a potential carrier candidate for oral drug delivery.Keywords: Pluronic F127, mucus-penetrating, particles, liposomes, oral drug delivery
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.
A Temporal Approach to Stochastic Network Calculus
Xie, Jing; Xie, Min
2011-01-01
Stochastic network calculus is a newly developed theory for stochastic service guarantee analysis of computer networks. In the current stochastic network calculus literature, its fundamental models are based on the cumulative amount of traffic or cumulative amount of service. However, there are network scenarios where direct application of such models is difficult. This paper presents a temporal approach to stochastic network calculus. The key idea is to develop models and derive results from the time perspective. Particularly, we define traffic models and service models based on the cumulative packet inter-arrival time and the cumulative packet service time, respectively. Relations among these models as well as with the existing models in the literature are established. In addition, we prove the basic properties of the proposed models, such as delay bound and backlog bound, output characterization, concatenation property and superposition property. These results form a temporal stochastic network calculus an...
Directory of Open Access Journals (Sweden)
Judith Martín-de León
2016-07-01
Full Text Available This paper describes the processing conditions needed to produce low density nanocellular polymers based on polymethylmethacrylate (PMMA with relative densities between 0.45 and 0.25, cell sizes between 200 and 250 nm and cell densities higher than 1014 cells/cm3. To produce these nanocellular polymers, the foaming parameters of the gas dissolution foaming technique using CO2 as blowing agent have been optimized. Taking into account previous works, the amount of CO2 uptake was maintained constant (31% by weight for all the materials. Foaming parameters were modified between 40 °C and 110 °C for the foaming temperature and from 1 to 5 min for the foaming time. Foaming temperatures in the range of 80 to 100 °C and foaming times of 2 min allow for production of nanocellular polymers with relative densities as low as 0.25. Cellular structure has been studied in-depth to obtain the processing-cellular structure relationship. In addition, it has been proved that the glass transition temperature depends on the cellular structure. This effect is associated with a confinement of the polymer in the cell walls, and is one of the key reasons for the improved properties of nanocellular polymers.
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...
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.
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 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
Modeling and analysis of stochastic systems
Kulkarni, Vidyadhar G
2011-01-01
Based on the author's more than 25 years of teaching experience, Modeling and Analysis of Stochastic Systems, Second Edition covers the most important classes of stochastic processes used in the modeling of diverse systems, from supply chains and inventory systems to genetics and biological systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. Along with reorganizing the material, this edition revises and adds new exercises and examples. New to the second edi
Esatbeyoglu, Tuba; Ewald, Philipp; Yasui, Yoshiaki; Yokokawa, Haruka; Wagner, Anika E; Matsugo, Seiichi; Winterhalter, Peter; Rimbach, Gerald
2016-01-01
Dietary stilbenoids are receiving increasing attention due to their potential health benefits. However, most studies concerning the bioactivity of stilbenoids were conducted with pure compounds, for example, resveratrol. The aim of this study was to characterize a complex root extract of Vitis vinifera in terms of its free radical scavenging and cellular antioxidant and anti-inflammatory properties. HPLC-ESI-MS/MS analyses of the root extract of Vitis vinifera identified seven stilbenoids including two monomeric (resveratrol and piceatannol), two dimeric (trans-ɛ-viniferin and ampelopsin A), one trimeric (miyabenol C), and two tetrameric (r-2-viniferin = vitisin A and r-viniferin = vitisin B) compounds which may mediate its biological activity. Electron spin resonance and spin trapping experiments indicate that the root extract scavenged 2,2-diphenyl-1-picrylhydrazyl, hydroxyl, galvinoxyl, and superoxide free radicals. On a cellular level it was observed that the root extract of Vitis vinifera protects against hydrogen peroxide-induced DNA damage and induces Nrf2 and its target genes heme oxygenase-1 and γ-glutamylcysteine synthetase. Furthermore, the root extract could induce the antiatherogenic hepatic enzyme paraoxonase 1 and downregulate proinflammatory gene expression (interleukin 1β, inducible nitric oxide synthase) in macrophages. Collectively our data suggest that the root extract of Vitis vinifera exhibits free radical scavenging as well as cellular antioxidant and anti-inflammatory properties.
Prata, Thiago Theodoro Martins; Bonin, Camila Mareti; Ferreira, Alda Maria Teixeira; Padovani, Cacilda Tezelli Junqueira; Fernandes, Carlos Eurico dos Santos; Machado, Ana Paula; Tozetti, Inês Aparecida
2015-09-01
A specific immune response to human papillomavirus (HPV) in the cervical microenvironment plays a key role in eradicating infection and eliminating mutated cells. However, high-risk HPVs modulate immune cells to create an immunosuppressive microenvironment, and induce these immune cells to produce interleukin 10 (IL-10). This production of IL-10, in conjunction with HPV infection, contributes to the appearance of cervical neoplastic lesions. We sought to characterize the IL-10-producing cellular phenotype, and investigate the influence of host and HPV factors upon the induction of an immunosuppressive microenvironment. Immunohistochemical analysis demonstrated an increase in IL-10 production by keratinocytes, macrophages and Langerhans cells in high-grade cervical lesions and cervical cancer. This increase was more pronounced in patients older than 30 years, and was also correlated with high viral load, and infection with a single HPV type, particularly high-risk HPVs. Our results indicate the existence of a highly immunosuppressive microenvironment composed of different IL-10-producing cellular phenotypes in cervical cancer samples, and samples classified as high-grade cervical lesions (cervical intraepithelial neoplasia stages II and III). The immunosuppressive microenvironment that developed for these different cellular phenotypes favours viral persistence and neoplastic progression.
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...
Stochastic differential games with inside information
Draouil, Olfa; Øksendal, Bernt
2016-08-01
We study stochastic differential games of jump diffusions, where the players have access to inside information. Our approach is based on anticipative stochastic calculus, white noise, Hida-Malliavin calculus, forward integrals and the Donsker delta functional. We obtain a characterization of Nash equilibria of such games in terms of the corresponding Hamiltonians. This is used to study applications to insider games in finance, specifically optimal insider consumption and optimal insider portfolio under model uncertainty.
Oware, E. K.
2015-12-01
Modeling aquifer heterogeneities (AH) is a complex, multidimensional problem that mostly requires stochastic imaging strategies for tractability. While the traditional Bayesian Markov chain Monte Carlo (McMC) provides a powerful framework to model AH, the generic McMC is computationally prohibitive and, thus, unappealing for large-scale problems. An innovative variant of the McMC scheme that imposes priori spatial statistical constraints on model parameter updates, for improved characterization in a computationally efficient manner is proposed. The proposed algorithm (PA) is based on Markov random field (MRF) modeling, which is an image processing technique that infers the global behavior of a random field from its local properties, making the MRF approach well suited for imaging AH. MRF-based modeling leverages the equivalence of Gibbs (or Boltzmann) distribution (GD) and MRF to identify the local properties of an MRF in terms of the easily quantifiable Gibbs energy. The PA employs the two-step approach to model the lithological structure of the aquifer and the hydraulic properties within the identified lithologies simultaneously. It performs local Gibbs energy minimizations along a random path, which requires parameters of the GD (spatial statistics) to be specified. A PA that implicitly infers site-specific GD parameters within a Bayesian framework is also presented. The PA is illustrated with a synthetic binary facies aquifer with a lognormal heterogeneity simulated within each facies. GD parameters of 2.6, 1.2, -0.4, and -0.2 were estimated for the horizontal, vertical, NESW, and NWSE directions, respectively. Most of the high hydraulic conductivity zones (facies 2) were fairly resolved (see results below) with facies identification accuracy rate of 81%, 89%, and 90% for the inversions conditioned on concentration (R1), resistivity (R2), and joint (R3), respectively. The incorporation of the conditioning datasets improved on the root mean square error (RMSE
Spatial stochastic dynamics enable robust cell polarization.
Directory of Open Access Journals (Sweden)
Michael J Lawson
Full Text Available Although cell polarity is an essential feature of living cells, it is far from being well-understood. Using a combination of computational modeling and biological experiments we closely examine an important prototype of cell polarity: the pheromone-induced formation of the yeast polarisome. Focusing on the role of noise and spatial heterogeneity, we develop and investigate two mechanistic spatial models of polarisome formation, one deterministic and the other stochastic, and compare the contrasting predictions of these two models against experimental phenotypes of wild-type and mutant cells. We find that the stochastic model can more robustly reproduce two fundamental characteristics observed in wild-type cells: a highly polarized phenotype via a mechanism that we refer to as spatial stochastic amplification, and the ability of the polarisome to track a moving pheromone input. Moreover, we find that only the stochastic model can simultaneously reproduce these characteristics of the wild-type phenotype and the multi-polarisome phenotype of a deletion mutant of the scaffolding protein Spa2. Significantly, our analysis also demonstrates that higher levels of stochastic noise results in increased robustness of polarization to parameter variation. Furthermore, our work suggests a novel role for a polarisome protein in the stabilization of actin cables. These findings elucidate the intricate role of spatial stochastic effects in cell polarity, giving support to a cellular model where noise and spatial heterogeneity combine to achieve robust biological function.
Codd, E F
1968-01-01
Cellular Automata presents the fundamental principles of homogeneous cellular systems. This book discusses the possibility of biochemical computers with self-reproducing capability.Organized into eight chapters, this book begins with an overview of some theorems dealing with conditions under which universal computation and construction can be exhibited in cellular spaces. This text then presents a design for a machine embedded in a cellular space or a machine that can compute all computable functions and construct a replica of itself in any accessible and sufficiently large region of t
Reversible quantum cellular automata
Schumacher, B
2004-01-01
We define quantum cellular automata as infinite quantum lattice systems with discrete time dynamics, such that the time step commutes with lattice translations and has strictly finite propagation speed. In contrast to earlier definitions this allows us to give an explicit characterization of all local rules generating such automata. The same local rules also generate the global time step for automata with periodic boundary conditions. Our main structure theorem asserts that any quantum cellular automaton is structurally reversible, i.e., that it can be obtained by applying two blockwise unitary operations in a generalized Margolus partitioning scheme. This implies that, in contrast to the classical case, the inverse of a nearest neighbor quantum cellular automaton is again a nearest neighbor automaton. We present several construction methods for quantum cellular automata, based on unitaries commuting with their translates, on the quantization of (arbitrary) reversible classical cellular automata, on quantum c...
Stochastic resonance in an intracellular genetic perceptron
Bates, Russell; Blyuss, Oleg; Zaikin, Alexey
2014-03-01
Intracellular genetic networks are more intelligent than was first assumed due to their ability to learn. One of the manifestations of this intelligence is the ability to learn associations of two stimuli within gene-regulating circuitry: Hebbian-type learning within the cellular life. However, gene expression is an intrinsically noisy process; hence, we investigate the effect of intrinsic and extrinsic noise on this kind of intracellular intelligence. We report a stochastic resonance in an intracellular associative genetic perceptron, a noise-induced phenomenon, which manifests itself in noise-induced increase of response in efficiency after the learning event under the conditions of optimal stochasticity.
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...
Ito equations out of domino cellular automaton with efficiency parameters
Czechowski, Zbigniew
2011-01-01
Ito equations are derived for simple stochastic cellular automaton with parameters and compared with results obtained from the histogram method. Good agreement for various parameters supports wide applicability of the Ito equation as a macroscopic model.
Energy Technology Data Exchange (ETDEWEB)
Buchanan, M V.; Larimer, Frank; Wiley, H S.; Kennel, S J.; Squier, Thomas C.; Ramsey, John M.; Rodland, Karin D.; Hurst, G B.; Smith, Richard D.; Xu, Ying; Dixon, David A.; Doktycz, M J.; Colson, Steve D.; Gesteland, R; Giometti, Carol S.; Young, Mark E.; Giddings, Ralph M.
2002-02-01
Goal 1 of Department of Energy's Genomes to Life (GTL) program seeks to identify and characterize the complete set of protein complexes within a cell. Goal 1 forms the foundation necessary to accomplish the other objectives of the GTL program, which focus on gene regulatory networks and molecular level characterization of interactions in microbial communities. Together this information would allow cells and their components to be understood in sufficient detail to predict, test, and understand the responses of a biological system to its environment. The Center for Molecular and Cellular Systems has been established to identify and characterize protein complexes using high through-put analytical technologies. A dynamic research program is being developed that supports the goals of the Center by focusing on the development of new capabilities for sample preparation and complex separations, molecular level identification of the protein complexes by mass spectrometry, characterization of the complexes in living cells by imaging techniques, and bioinformatics and computational tools for the collection and interpretation of data and formation of databases and tools to allow the data to be shared by the biological community.
Directory of Open Access Journals (Sweden)
Ma Wujun
2010-09-01
Full Text Available Abstract Background Isoprenylcysteine methylesterases (ICME demethylate prenylated protein in eukaryotic cell. Until now, knowledge about their molecular information, localization and expression pattern is largely unavailable in plant species. One ICME in Arabidopsis, encoded by At5g15860, has been identified recently. Over-expression of At5g15860 caused an ABA hypersensitive phenotype in transgenic Arabidopsis plants, indicating that it functions as a positive regulator of ABA signaling. Moreover, ABA induced the expression of this gene in Arabidopsis seedlings. The current study extends these findings by examining the sub-cellular localization, expression profiling, and physiological functions of ICME and two other ICME-like proteins, ICME-LIKE1 and ICME-LIKE2, which were encoded by two related genes At1g26120 and At3g02410, respectively. Results Bioinformatics investigations showed that the ICME and other two ICME-like homologs comprise a small subfamily of carboxylesterase (EC 3.1.1.1 in Arabidopsis. Sub-cellular localization of GFP tagged ICME and its homologs showed that the ICME and ICME-like proteins are intramembrane proteins predominantly localizing in the endoplasmic reticulum (ER and Golgi apparatus. Semi-quantitative and real-time quantitative PCR revealed that the ICME and ICME-like genes are expressed in all examined tissues, including roots, rosette leaves, cauline leaves, stems, flowers, and siliques, with differential expression levels. Within the gene family, the base transcript abundance of ICME-LIKE2 gene is very low with higher expression in reproductive organs (flowers and siliques. Time-course analysis uncovered that both ICME and ICME-like genes are up-regulated by mannitol, NaCl and ABA treatment, with ICME showing the highest level of up-regulation by these treatments. Heat stress resulted in up-regulation of the ICME gene significantly but down-regulation of the ICME-LIKE1 and ICME-LIKE2 genes. Cold and dehydration
Directory of Open Access Journals (Sweden)
Youichi Suzuki
2016-01-01
Full Text Available Dengue virus (DENV is one of the most important arthropod-borne pathogens that cause life-threatening diseases in humans. However, no vaccine or specific antiviral is available for dengue. As seen in other RNA viruses, the innate immune system plays a key role in controlling DENV infection and disease outcome. Although the interferon (IFN response, which is central to host protective immunity, has been reported to limit DENV replication, the molecular details of how DENV infection is modulated by IFN treatment are elusive. In this study, by employing a gain-of-function screen using a type I IFN-treated cell-derived cDNA library, we identified a previously uncharacterized gene, C19orf66, as an IFN-stimulated gene (ISG that inhibits DENV replication, which we named Repressor of yield of DENV (RyDEN. Overexpression and gene knockdown experiments revealed that expression of RyDEN confers resistance to all serotypes of DENV in human cells. RyDEN expression also limited the replication of hepatitis C virus, Kunjin virus, Chikungunya virus, herpes simplex virus type 1, and human adenovirus. Importantly, RyDEN was considered to be a crucial effector molecule in the IFN-mediated anti-DENV response. When affinity purification-mass spectrometry analysis was performed, RyDEN was revealed to form a complex with cellular mRNA-binding proteins, poly(A-binding protein cytoplasmic 1 (PABPC1, and La motif-related protein 1 (LARP1. Interestingly, PABPC1 and LARP1 were found to be positive modulators of DENV replication. Since RyDEN influenced intracellular events on DENV replication and, suppression of protein synthesis from DENV-based reporter construct RNA was also observed in RyDEN-expressing cells, our data suggest that RyDEN is likely to interfere with the translation of DENV via interaction with viral RNA and cellular mRNA-binding proteins, resulting in the inhibition of virus replication in infected cells.
Suzuki, Youichi; Chin, Wei-Xin; Han, Qi'En; Ichiyama, Koji; Lee, Ching Hua; Eyo, Zhi Wen; Ebina, Hirotaka; Takahashi, Hirotaka; Takahashi, Chikako; Tan, Beng Hui; Hishiki, Takayuki; Ohba, Kenji; Matsuyama, Toshifumi; Koyanagi, Yoshio; Tan, Yee-Joo; Sawasaki, Tatsuya; Chu, Justin Jang Hann; Vasudevan, Subhash G; Sano, Kouichi; Yamamoto, Naoki
2016-01-01
Dengue virus (DENV) is one of the most important arthropod-borne pathogens that cause life-threatening diseases in humans. However, no vaccine or specific antiviral is available for dengue. As seen in other RNA viruses, the innate immune system plays a key role in controlling DENV infection and disease outcome. Although the interferon (IFN) response, which is central to host protective immunity, has been reported to limit DENV replication, the molecular details of how DENV infection is modulated by IFN treatment are elusive. In this study, by employing a gain-of-function screen using a type I IFN-treated cell-derived cDNA library, we identified a previously uncharacterized gene, C19orf66, as an IFN-stimulated gene (ISG) that inhibits DENV replication, which we named Repressor of yield of DENV (RyDEN). Overexpression and gene knockdown experiments revealed that expression of RyDEN confers resistance to all serotypes of DENV in human cells. RyDEN expression also limited the replication of hepatitis C virus, Kunjin virus, Chikungunya virus, herpes simplex virus type 1, and human adenovirus. Importantly, RyDEN was considered to be a crucial effector molecule in the IFN-mediated anti-DENV response. When affinity purification-mass spectrometry analysis was performed, RyDEN was revealed to form a complex with cellular mRNA-binding proteins, poly(A)-binding protein cytoplasmic 1 (PABPC1), and La motif-related protein 1 (LARP1). Interestingly, PABPC1 and LARP1 were found to be positive modulators of DENV replication. Since RyDEN influenced intracellular events on DENV replication and, suppression of protein synthesis from DENV-based reporter construct RNA was also observed in RyDEN-expressing cells, our data suggest that RyDEN is likely to interfere with the translation of DENV via interaction with viral RNA and cellular mRNA-binding proteins, resulting in the inhibition of virus replication in infected cells.
Park, Ok Hyun; Park, Joori; Yu, Mira; An, Hyoung-Tae; Ko, Jesang; Kim, Yoon Ki
2016-01-01
Glucocorticoid (GC) receptor (GR) has been shown recently to bind a subset of mRNAs and elicit rapid mRNA degradation. However, the molecular details of GR-mediated mRNA decay (GMD) remain unclear. Here, we demonstrate that GMD triggers rapid degradation of target mRNAs in a translation-independent and exon junction complex-independent manner, confirming that GMD is mechanistically distinct from nonsense-mediated mRNA decay (NMD). Efficient GMD requires PNRC2 (proline-rich nuclear receptor coregulatory protein 2) binding, helicase ability, and ATM-mediated phosphorylation of UPF1 (upstream frameshift 1). We also identify two GMD-specific factors: an RNA-binding protein, YBX1 (Y-box-binding protein 1), and an endoribonuclease, HRSP12 (heat-responsive protein 12). In particular, using HRSP12 variants, which are known to disrupt trimerization of HRSP12, we show that HRSP12 plays an essential role in the formation of a functionally active GMD complex. Moreover, we determine the hierarchical recruitment of GMD factors to target mRNAs. Finally, our genome-wide analysis shows that GMD targets a variety of transcripts, implicating roles in a wide range of cellular processes, including immune responses.
Włodarczyk-Biegun, Małgorzata K; Werten, Marc W T; de Wolf, Frits A; van den Beucken, Jeroen J J P; Leeuwenburgh, Sander C G; Kamperman, Marleen; Cohen Stuart, Martien A
2014-08-01
Genetically engineered protein polymers (GEPP) are a class of multifunctional materials with precisely controlled molecular structure and property profile. Representing a promising alternative for currently used materials in biomedical applications, GEPP offer multiple benefits over natural and chemically synthesized polymers. However, producing them in sufficient quantities for preclinical research remains challenging. Here, we present results from an in vitro cellular response study of a recombinant protein polymer that is soluble at low pH but self-organizes into supramolecular fibers and physical hydrogels at neutral pH. It has a triblock structure denoted as C2S(H)48C2, which consists of hydrophilic collagen-inspired and histidine-rich silk-inspired blocks. The protein was successfully produced by the yeast Pichia pastoris in laboratory-scale bioreactors, and it was purified by selective precipitation. This efficient and inexpensive production method provided material of sufficient quantities, purity and sterility for cell culture study. Rheology and erosion studies showed that it forms hydrogels exhibiting long-term stability, self-healing behavior and tunable mechanical properties. Primary rat bone marrow cells cultured in direct contact with these hydrogels remained fully viable; however, proliferation and mineralization were relatively low compared to collagen hydrogel controls, probably because of the absence of cell-adhesive motifs. As biofunctional factors can be readily incorporated to improve material performance, our approach provides a promising route towards biomedical applications.
Wang, Fang; Eric Knabe, W; Li, Liwei; Jo, Inha; Mani, Timmy; Roehm, Hartmut; Oh, Kyungsoo; Li, Jing; Khanna, May; Meroueh, Samy O
2012-08-01
The urokinase receptor (uPAR) serves as a docking site to the serine protease urokinase-type plasminogen activator (uPA) to promote extracellular matrix (ECM) degradation and tumor invasion and metastasis. Previously, we had reported a small molecule inhibitor of the uPAR·uPA interaction that emerged from structure-based virtual screening. Here, we measure the affinity of a large number of derivatives from commercial sources. Synthesis of additional compounds was carried out to probe the role of various groups on the parent compound. Extensive structure-based computational studies suggested a binding mode for these compounds that led to a structure-activity relationship study. Cellular studies in non-small cell lung cancer (NSCLC) cell lines that include A549, H460 and H1299 showed that compounds blocked invasion, migration and adhesion. The effects on invasion of active compounds were consistent with their inhibition of uPA and MMP proteolytic activity. These compounds showed weak cytotoxicity consistent with the confined role of uPAR to metastasis.
Ma, Rui; Tang, Songchao; Tan, Honglue; Qian, Jun; Lin, Wentao; Wang, Yugang; Liu, Changsheng; Wei, Jie; Tang, Tingting
2014-08-13
In this study, a nanocalcium silicate (n-CS)/polyetheretherketone (PEEK) bioactive composite was prepared using a process of compounding and injection-molding. The mechanical properties, hydrophilicity, and in vitro bioactivity of the composite, as well as the cellular responses of MC3T3-E1 cells (attachment, proliferation, spreading, and differentiation) to the composite, were investigated. The results showed that the mechanical properties and hydrophilicity of the composites were significantly improved by the addition of n-CS to PEEK. In addition, an apatite-layer formed on the composite surface after immersion in simulated body fluid (SBF) for 7 days. In cell culture tests, the results revealed that the n-CS/PEEK composite significantly promoted cell attachment, proliferation, and spreading compared with PEEK or ultrahigh molecular weight polyethylene (UHMWPE). Moreover, cells grown on the composite exhibited higher alkaline phosphatase (ALP) activity, more calcium nodule-formation, and higher expression levels of osteogenic differentiation-related genes than cells grown on PEEK or UHMWPE. These results indicated that the incorporation of n-CS to PEEK could greatly improve the bioactivity and biocompatibility of the composite. Thus, the n-CS/PEEK composite may be a promising bone repair material for use in orthopedic clinics.
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
Saleh Heneidi; Simerman, Ariel A; Erica Keller; Prapti Singh; Xinmin Li; Dumesic, Daniel A; Gregorio Chazenbalk
2013-01-01
Advances in stem cell therapy face major clinical limitations, particularly challenged by low rates of post-transplant cell survival. Hostile host factors of the engraftment microenvironment such as hypoxia, nutrition deprivation, pro-inflammatory cytokines, and reactive oxygen species can each contribute to unwanted differentiation or apoptosis. In this report, we describe the isolation and characterization of a new population of adipose tissue (AT) derived pluripotent stem cells, termed Mul...
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.
Zhong, Yaogang; Zhang, Jing; Yu, Hanjie; Zhang, Jiaxu; Sun, Xiu-Xuan; Chen, Wentian; Bian, Huijie; Li, Zheng
2015-12-25
Although the expression levels of total GalNAc-binding proteins (GNBPs) were up-regulated significantly in human hepatic stellate cells (HSCs) activated with transforming growth factor-β1(TGF-β1), yet little is known about the precise types, distribution and sub-cellular localization of the GNBPs in HSCs. Here, 264 GNBPs from the activated HSCs and 257 GNBPs from the quiescent HSCs were identified and annotated. A total of 46 GNBPs were estimated to be significantly up-regulated and 40 GNBPs were estimated to be significantly down-regulated in the activated HSCs. For example, the GNBPs (i.e. BTF3, COX17, and ATP5A1) responsible for the regulation of protein binding were up-regulated, and those (i.e. FAM114A1, ENO3, and TKT) responsible for the regulation of protein binding were down-regulated in the activated HSCs. The motifs of the isolated GNBPs showed that Proline residue had the maximum preference in consensus sequences. The western blotting showed the expression levels of COX17, and PRMT1 were significantly up-regulated, while, the expression level of CLIC1(B5) was down-regulated in the activated HSCs and liver cirrhosis tissues. Moreover, the GNBPs were sub-localized in the Golgi apparatus of HSCs. In conclusion, the precision alteration of the GNBPs referred to pathological changes in liver fibrosis/cirrhosis may provide useful information to find new molecular mechanism of HSC activation and discover the biomarkers for diagnosis of liver fibrosis/cirrhosis as well as development of new anti-fibrotic strategies.
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
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.
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.
Directory of Open Access Journals (Sweden)
Ding X
2012-02-01
Full Text Available Wei Fan1,2,*, Xin Wu1,*, Baoyue Ding3,*, Jing Gao4, Zhen Cai1, Wei Zhang1, Dongfeng Yin1, Xiang Wang1, Quangang Zhu1, Jiyong Liu1, Xueying Ding4, Shen Gao1 1Department of Pharmaceutics, Changhai Hospital, Second Military Medical University, Shanghai, 2Department of Pharmaceutics, The 425th Hospital of PLA, Sanya, 3Department of Pharmaceutics, Medical College of Jiaxing University, Jiaxing, 4Department of Pharmaceutics, School of Pharmacy, Second Military Medical University, Shanghai, People's Republic of China*These authors contributed equally to this workBackground: Cationic copolymers consisting of polycations linked to nonionic amphiphilic block polymers have been evaluated as nonviral gene delivery systems, and a large number of different polymers and copolymers of linear, branched, and dendrimeric architectures have been tested in terms of their suitability and efficacy for in vitro and in vivo transfection. However, the discovery of new potent materials still largely relies on empiric approaches rather than a rational design. The authors investigated the relationship between the polymers' structures and their biological performance, including DNA compaction, toxicity, transfection efficiency, and the effect of cellular uptake.Methods: This article reports the synthesis and characterization of a series of cationic copolymers obtained by grafting polyethyleneimine with nonionic amphiphilic surfactant polyether-Pluronic® consisting of hydrophilic ethylene oxide and hydrophobic propylene oxide blocks. Transgene expression, cytotoxicity, localization of plasmids, and cellular uptake of these copolymers were evaluated following in vitro transfection of HeLa cell lines with various individual components of the copolymers.Results: Pluronics can exhibit biological activity including effects on enhancing DNA cellular uptake, nuclear translocation, and gene expression. The Pluronics with a higher hydrophilic-lipophilic balance value lead to
100 years after Smoluchowski: stochastic processes in cell biology
Holcman, D.; Schuss, Z.
2017-03-01
100 years after Smoluchowski introduced his approach to stochastic processes, they are now at the basis of mathematical and physical modeling in cellular biology: they are used for example to analyse and to extract features from a large number (tens of thousands) of single molecular trajectories or to study the diffusive motion of molecules, proteins or receptors. Stochastic modeling is a new step in large data analysis that serves extracting cell biology concepts. We review here Smoluchowski’s approach to stochastic processes and provide several applications for coarse-graining diffusion, studying polymer models for understanding nuclear organization and finally, we discuss the stochastic jump dynamics of telomeres across cell division and stochastic gene regulation.
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.
StochPy: a comprehensive, user-friendly tool for simulating stochastic biological processes.
Directory of Open Access Journals (Sweden)
Timo R Maarleveld
Full Text Available Single-cell and single-molecule measurements indicate the importance of stochastic phenomena in cell biology. Stochasticity creates spontaneous differences in the copy numbers of key macromolecules and the timing of reaction events between genetically-identical cells. Mathematical models are indispensable for the study of phenotypic stochasticity in cellular decision-making and cell survival. There is a demand for versatile, stochastic modeling environments with extensive, preprogrammed statistics functions and plotting capabilities that hide the mathematics from the novice users and offers low-level programming access to the experienced user. Here we present StochPy (Stochastic modeling in Python, which is a flexible software tool for stochastic simulation in cell biology. It provides various stochastic simulation algorithms, SBML support, analyses of the probability distributions of molecule copy numbers and event waiting times, analyses of stochastic time series, and a range of additional statistical functions and plotting facilities for stochastic simulations. We illustrate the functionality of StochPy with stochastic models of gene expression, cell division, and single-molecule enzyme kinetics. StochPy has been successfully tested against the SBML stochastic test suite, passing all tests. StochPy is a comprehensive software package for stochastic simulation of the molecular control networks of living cells. It allows novice and experienced users to study stochastic phenomena in cell biology. The integration with other Python software makes StochPy both a user-friendly and easily extendible simulation tool.
Directory of Open Access Journals (Sweden)
Giuseppe Crescenzo
2010-01-01
Full Text Available Gilthead sea bream (Sparus aurata L. is one of the most intensively farmed fish spe- cies in the Mediterranean, greatly studied for the relevant economic value, although its sensitivity to Aflatoxin B1 (AFB1 has to be investigated, yet. The aim of this study was to perform an in vitro evalua- tion of cytotoxic potential of AFB1 on S. aurata hepatocytes in order to grade the range of AFB1 toxicity, and the boundary between acute and long-term toxicity. Primary monolayer cultures of hepatocytes from S. aurata juveniles were treated with a wide range of concentrations from 5x103 ng/ml to 2x10 2x10-5 ng/ml of AFB1 for a different period of exposure (24, 48, 72 hours. The cytotoxic activity was characterized by MTT reduction assay. After each exposition hepatocytes were examined for morphologic alterations and apoptosis induction. AFB1 exposure significantly reduced cell viability in a dose- and time-depend- ent manner. Dose-response curves obtained after 24, 48 and 72 hrs revealed that prolonged exposure times lead to a significant increase of the toxicpotencyofAFB toxic potency of AFB AFB1. Ourresultsdemonstratethat Our results demonstrate that S. aurata hepatocytes are highly sensitive to AFB1 exposure. Such scientific findings could provide new insights to investigate the real impact of aflatoxin on marine farmed fish.
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
Harish, Gangadharappa; Mahadevan, Anita; Pruthi, Nupur; Sreenivasamurthy, Sreelakshmi K; Puttamallesh, Vinuth N; Keshava Prasad, Thottethodi Subrahmanya; Shankar, Susarla Krishna; Srinivas Bharath, Muchukunte Mukunda
2015-07-01
Traumatic brain injury (TBI) contributes to fatalities and neurological disabilities worldwide. While primary injury causes immediate damage, secondary events contribute to long-term neurological defects. Contusions (Ct) are primary injuries correlated with poor clinical prognosis, and can expand leading to delayed neurological deterioration. Pericontusion (PC) (penumbra), the region surrounding Ct, can also expand with edema, increased intracranial pressure, ischemia, and poor clinical outcome. Analysis of Ct and PC can therefore assist in understanding the pathobiology of TBI and its management. This study on human TBI brains noted extensive neuronal, astroglial and inflammatory changes, alterations in mitochondrial, synaptic and oxidative markers, and associated proteomic profile, with distinct differences in Ct and PC. While Ct displayed petechial hemorrhages, thrombosis, inflammation, neuronal pyknosis, and astrogliosis, PC revealed edema, vacuolation of neuropil, axonal loss, and dystrophic changes. Proteomic analysis demonstrated altered immune response, synaptic, and mitochondrial dysfunction, among others, in Ct, while PC displayed altered regulation of neurogenesis and cytoskeletal architecture, among others. TBI brains displayed oxidative damage, glutathione depletion, mitochondrial dysfunction, and loss of synaptic proteins, with these changes being more profound in Ct. We suggest that analysis of markers specific to Ct and PC may be valuable in the evaluation of TBI pathobiology and therapeutics. We have characterized the primary injury in human traumatic brain injury (TBI). Contusions (Ct) - the injury core displayed hemorrhages, inflammation, and astrogliosis, while the surrounding pericontusion (PC) revealed edema, vacuolation, microglial activation, axonal loss, and dystrophy. Proteomic analysis demonstrated altered immune response, synaptic and mitochondrial dysfunction in Ct, and altered regulation of neurogenesis and cytoskeletal architecture in
Stochastic learning via optimizing the variational inequalities.
Tao, Qing; Gao, Qian-Kun; Chu, De-Jun; Wu, Gao-Wei
2014-10-01
A wide variety of learning problems can be posed in the framework of convex optimization. Many efficient algorithms have been developed based on solving the induced optimization problems. However, there exists a gap between the theoretically unbeatable convergence rate and the practically efficient learning speed. In this paper, we use the variational inequality (VI) convergence to describe the learning speed. To this end, we avoid the hard concept of regret in online learning and directly discuss the stochastic learning algorithms. We first cast the regularized learning problem as a VI. Then, we present a stochastic version of alternating direction method of multipliers (ADMMs) to solve the induced VI. We define a new VI-criterion to measure the convergence of stochastic algorithms. While the rate of convergence for any iterative algorithms to solve nonsmooth convex optimization problems cannot be better than O(1/√t), the proposed stochastic ADMM (SADMM) is proved to have an O(1/t) VI-convergence rate for the l1-regularized hinge loss problems without strong convexity and smoothness. The derived VI-convergence results also support the viewpoint that the standard online analysis is too loose to analyze the stochastic setting properly. The experiments demonstrate that SADMM has almost the same performance as the state-of-the-art stochastic learning algorithms but its O(1/t) VI-convergence rate is capable of tightly characterizing the real learning speed.
Stochastic resonance during a polymer translocation process.
Mondal, Debasish; Muthukumar, M
2016-04-14
We have studied the occurrence of stochastic resonance when a flexible polymer chain undergoes a single-file translocation through a nano-pore separating two spherical cavities, under a time-periodic external driving force. The translocation of the chain is controlled by a free energy barrier determined by chain length, pore length, pore-polymer interaction, and confinement inside the donor and receiver cavities. The external driving force is characterized by a frequency and amplitude. By combining the Fokker-Planck formalism for polymer translocation and a two-state model for stochastic resonance, we have derived analytical formulas for criteria for emergence of stochastic resonance during polymer translocation. We show that no stochastic resonance is possible if the free energy barrier for polymer translocation is purely entropic in nature. The polymer chain exhibits stochastic resonance only in the presence of an energy threshold in terms of polymer-pore interactions. Once stochastic resonance is feasible, the chain entropy controls the optimal synchronization conditions significantly.
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...
Directory of Open Access Journals (Sweden)
Mark Sokolowski
Full Text Available Long INterspersed Element-1 (LINE-1, L1 is an active retrotransposon that mobilizes using a ribonucleoprotein particle (RNP intermediate composed of the full-length bicistronic L1 mRNA and the two proteins (ORF1p and ORF2p encoded by that mRNA. ORF1p and ORF2p demonstrate cis-preference for their encoding mRNA. Previous studies of ORF1p, purified from bacterial and insect cells demonstrated that this protein forms trimers in vitro. While valuable for understanding ORF1p function, these in vitro approaches do not provide any information on ORF1p self-interaction in the context of mammalian cells. We used a mammalian two-hybrid (M2H system in order to study L1 ORF1p self-interaction in human and mouse cells. We demonstrate that the M2H system successfully detects human and mouse ORF1p self-interactions in transiently transfected mammalian cells. We also generated mouse and human ORF1p-specific antibodies to characterize the expression of ORF1p fusion proteins used in the M2H system. Using these antibodies, we demonstrate that ORF1p interaction in trans leads to the formation of heterodimers that are expected to produce a positive signal in the M2H system. Although the role for L1 ORF1p cis-preference in L1 mobilization is established, the impact of ability of ORF1pto interact in trans on the L1 replication cycle is not known. Furthermore, western blot analysis of ORF1p generated by a full-length L1, wild type ORF1, or a codon-optimized ORF1 expression vector is detected in the nucleus. In contrast, the addition of a tag to the N-terminus of the mouse and human ORF1 proteins can significantly alter the subcellular localization in a tag-specific manner. These data support that nuclear localization of ORF1p may contribute to L1 (and potentially the SINE Alu RNP nuclear access in the host cell.
Energy Technology Data Exchange (ETDEWEB)
Ramirez, A; Mcnab, W; Carle, S; Hao, Y; White, D; Johnson, J
2010-12-17
Over the last project six months, our project activities have concentrated on three areas: (1) performing a stochastic inversion of pattern 16 seismic data to deduce reservoir permeability, (2) development of the geochemical inversion strategy and implementation of associated software, and (3) completing the software implementation of TProGS and the geostatistical analysis that provides the information needed when using the software to produce realizations of the Midale reservoir. The report partially the following deliverables: D2: Model development: MCMC tool (synthetic fluid chemistry data); deliverable completed. D4: Model development/verification: MCMC tool (TProGS, field seismic/chemistry data) work product; deliverable requirements partially fulfilled. D5: Field-based single-pattern simulations work product; deliverable requirements partially fulfilled. When completed, our completed stochastic inversion tool will explicitly integrate reactive transport modeling, facies-based geostatistical methods, and a novel stochastic inversion technique to optimize agreement between observed and predicted storage performance. Such optimization will be accomplished through stepwise refinement of: (1) the reservoir model - principally its permeability magnitude and heterogeneity - and (2) geochemical parameters - primarily key mineral volume fractions and kinetic data. We anticipate that these refinements will facilitate significantly improved history matching and forward modeling of CO{sub 2} storage. Our tool uses the Markov Chain Monte Carlo (MCMC) methodology. Deliverable D1, previously submitted as a report titled ''Development of a Stochastic Inversion Tool To Optimize Agreement Between The Observed And Predicted Seismic Response To CO{sub 2} Injection/Migration in the Weyburn-Midale Project'' (Ramirez et al., 2009), described the stochastic inversion approach that will identify reservoir models that optimize agreement between the observed and
Institute of Scientific and Technical Information of China (English)
杨周
1996-01-01
Cellular phones, used in automobiles, airliners, and passenger trains, are basically low-power radiotelephones. Calls go through radio transmitters that are located within small geographical units called cells. Because each cell’s signals are too weak to interfere with those of other cells operating on the same fre-
Lin, Qian
2011-01-01
In this paper, we study Nash equilibrium payoffs for nonzero-sum stochastic differential games via the theory of backward stochastic differential equations. We obtain an existence theorem and a characterization theorem of Nash equilibrium payoffs for nonzero-sum stochastic differential games with nonlinear cost functionals defined with the help of a doubly controlled backward stochastic differential equation. Our results extend former ones by Buckdahn, Cardaliaguet and Rainer (2004) and are b...
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
Applying causality principles to the axiomatization of probabilistic cellular automata
Arrighi, Pablo; Nesme, Vincent; Thierry, Eric
2011-01-01
Cellular automata (CA) consist of an array of identical cells, each of which may take one of a finite number of possible states. The entire array evolves in discrete time steps by iterating a global evolution G. Further, this global evolution G is required to be shift-invariant (it acts the same everywhere) and causal (information cannot be transmitted faster than some fixed number of cells per time step). At least in the classical, reversible and quantum cases, these two top-down axiomatic conditions are sufficient to entail more bottom-up, operational descriptions of G. We investigate whether the same is true in the probabilistic case. Keywords: Characterization, noise, Markov process, stochastic Einstein locality, screening-off, common cause principle, non-signalling, Multi-party non-local box.
Parametric resonance and particle stochastic interactions with a periodic medium
Pinheiro, Mario J
2015-01-01
A non-markovian stochastic model shows the emergence of structures in the medium, a self-organization characterized by a relationship between particle's energy, driven frequency $\\omega$ and a frequency of interaction with the medium $\
Aminova, G G; Sapinj, M R; Yerofeyeva, L M
2015-01-01
The cellular composition of the lamina propria of the mucous membrane of the jejunum was examined in the villi (LPV) and between the crypts (LPC). Two groups of male C57/BL6 mice aged 4-5 months were studied. Experimental group of animals (n=8) for 30 days was living under the terrestrial conditions in "BIOS-SLA" blocks and received a paste-like food made with standard feed containing water and casein. The control group of animals (n=6) were kept in standard vivarium conditions and received standard dry pellets. Studies have shown no significant changes in the content of lymphocytes in LPV and LPC in a terrestrial experiment. LPV was characterized by a sharp reduction in the number of plasma cells. In both LPV and LPC the number of eosinophils was increased, while the content of low differentiated forms of cells (blasts and large lymphocytes) was decreased. It is suggested that the changes in the contents of different cell types in ground-based experiment were due not only to the limited mobility of the animals but also to different composition of the feed.
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
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.
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.
On orthogonality preserving quadratic stochastic operators
Energy Technology Data Exchange (ETDEWEB)
Mukhamedov, Farrukh; Taha, Muhammad Hafizuddin Mohd [Department of Computational and Theoretical Sciences, Faculty of Science International Islamic University Malaysia, P.O. Box 141, 25710 Kuantan, Pahang Malaysia (Malaysia)
2015-05-15
A quadratic stochastic operator (in short QSO) is usually used to present the time evolution of differing species in biology. Some quadratic stochastic operators have been studied by Lotka and Volterra. In the present paper, we first give a simple characterization of Volterra QSO in terms of absolutely continuity of discrete measures. Further, we introduce a notion of orthogonal preserving QSO, and describe such kind of operators defined on two dimensional simplex. It turns out that orthogonal preserving QSOs are permutations of Volterra QSO. The associativity of genetic algebras generated by orthogonal preserving QSO is studied too.
Scattering theory of stochastic electromagnetic light waves.
Wang, Tao; Zhao, Daomu
2010-07-15
We generalize scattering theory to stochastic electromagnetic light waves. It is shown that when a stochastic electromagnetic light wave is scattered from a medium, the properties of the scattered field can be characterized by a 3 x 3 cross-spectral density matrix. An example of scattering of a spatially coherent electromagnetic light wave from a deterministic medium is discussed. Some interesting phenomena emerge, including the changes of the spectral degree of coherence and of the spectral degree of polarization of the scattered field.
A theory of stochastic choice under uncertainty
Karni, Edi; Safra, Zvi
2016-01-01
In this paper we propose a characterization of stochastic choice\\ud under risk and under uncertainty. We presume that decision makers'\\ud actual choices are governed by randomly selected states of mind, and\\ud study the representation of decision makers' perceptions of the stochastic process underlying the selection of their state of mind. The\\ud connections of this work to the literatures on random choice, choice\\ud behavior when preference are incomplete; choice of menus; and grades of inde...
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.
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.
Contributions of stochastic events to biological evolution and cancer
Directory of Open Access Journals (Sweden)
Anderson KM
2015-10-01
Full Text Available Stochastic genetic and epigenetic events have been fundamental in contributing to the development of manifold life-forms, past and present. The development of malignant cell clones and the role of stochasticity as a driving force in cancer cell evolution complements, in a perverse way evidence for the role of chance in normal cellular development and evolution. Stochastic events at multiple levels of cellular control and implementation represent a primary driving force and an ultimate filter through which evolutionary innovation occurs. Stochasticity provides the opportunity for a random assortment of disparate genetic and epigenetic events, in some instances resulting in altered metabolic and developmental capabilities of sufficient stability and uniqueness to contribute to deterministic sequelae that promote the viability and procreation of cells under stress. Cellular evolution has so far resulted in a “survival of a (sic fittest”, often dependent mechanistically on and determined by stochastic events. The implications of this are mirrored in the evolution of malignant change, to some extent as a variant of “reverse engineering” of dedifferentiation. Efforts to reduce the incidence of malignant change will have to take in to account its random nature and further the understanding of this feature.
A Real-Space Cellular Automaton Laboratory for the modeling of complex dunefields
Rozier, Olivier; Narteau, Clement
2013-04-01
Using applications in the physics of sand dunes, we explore the capabilities of a Real Space Cellular Automaton Laboratory (ReSCAL), a generator of 3D stochastic cellular automaton stochastic cellular automaton models with continuous time. The objective of this software is to develop interdisciplinary research collaboration to investigate the dynamics of complex systems. In the vast majority of numerical models, any point in space is entirely characterized by a local set of physical variables (e. g. temperature, pressure, velocity) that are recalculated over time according to some predetermined set of fundamental laws. However, there is not always a satisfactory theoretical framework from which we can try to quantify the overall dynamics of the system. For this reason, we prefer concentrate on features of organization and ReSCAL is entirely constructed from a finite number of discrete states that represent the different phases of matter involved in the system under consideration. Then, an elementary cell is a real-space representation of the physical environment. Pairs of nearest neighbor cells are called doublets and each individual physical process is associated with a set of doublet transitions and a characteristic transition rate. Using a modular approach, we show how it is possible to model and combine a wide range of physical, chemical and/or anthropological processes. As an example, we discuss different dune morphologies with respect to rotating wind conditions.
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
Cai, Huawei; Singh, Ajay N; Sun, Xiankai; Peng, Fangyu
2015-01-01
To synthesize a fluorescent Her2-NLP peptide conjugate consisting of Her2/neu targeting peptide and nuclear localization sequence peptide (NLP) and assess its cellular uptake and intracellular localization for radionuclide cancer therapy targeting Her2/neu-positive circulating breast cancer cells (CBCC). Fluorescent Cy5.5 Her2-NLP peptide conjugate was synthesized by coupling a bivalent peptide sequence, which consisted of a Her2-binding peptide (NH2-GSGKCCYSL) and an NLP peptide (CGYGPKKKRKVGG) linked by a polyethylene glycol (PEG) chain with 6 repeating units, with an activated Cy5.5 ester. The conjugate was separated and purified by HPLC and then characterized by Maldi-MS. The intracellular localization of fluorescent Cy5.5 Her2-NLP peptide conjugate was assessed by fluorescent microscopic imaging using a confocal microscope after incubation of Cy5.5-Her2-NLP with Her2/neu positive breast cancer cells and Her2/neu negative control breast cancer cells, respectively. Fluorescent signals were detected in cytoplasm of Her2/neu positive breast cancer cells (SKBR-3 and BT474 cell lines), but not or little in cytoplasm of Her2/neu negative breast cancer cells (MDA-MB-231), after incubation of the breast cancer cells with Cy5.5-Her2-NLP conjugates in vitro. No fluorescent signals were detected within the nuclei of Her2/neu positive SKBR-3 and BT474 breast cancer cells, neither Her2/neu negative MDA-MB-231 cells, incubated with the Cy5.5-Her2-NLP peptide conjugates, suggesting poor nuclear localization of the Cy5.5-Her2-NLP conjugates localized within the cytoplasm after their cellular uptake and internalization by the Her2/neu positive breast cancer cells. Her2-binding peptide (KCCYSL) is a promising agent for radionuclide therapy of Her2/neu positive breast cancer using a β(-) or α emitting radionuclide, but poor nuclear localization of the Her2-NLP peptide conjugates may limit its use for eradication of Her2/neu-positive CBCC using I-125 or other Auger electron
Computational stochastic model of ions implantation
Energy Technology Data Exchange (ETDEWEB)
Zmievskaya, Galina I., E-mail: zmi@gmail.ru; Bondareva, Anna L., E-mail: bal310775@yandex.ru [M.V. Keldysh Institute of Applied Mathematics RAS, 4,Miusskaya sq., 125047 Moscow (Russian Federation); Levchenko, Tatiana V., E-mail: tatlevchenko@mail.ru [VNII Geosystem Russian Federal Center, Varshavskoye roadway, 8, Moscow (Russian Federation); Maino, Giuseppe, E-mail: giuseppe.maino@enea.it [Scuola di Lettere e BeniCulturali, University di Bologna, sede di Ravenna, via Mariani 5, 48100 Ravenna (Italy)
2015-03-10
Implantation flux ions into crystal leads to phase transition /PT/ 1-st kind. Damaging lattice is associated with processes clustering vacancies and gaseous bubbles as well their brownian motion. System of stochastic differential equations /SDEs/ Ito for evolution stochastic dynamical variables corresponds to the superposition Wiener processes. The kinetic equations in partial derivatives /KE/, Kolmogorov-Feller and Einstein-Smolukhovskii, were formulated for nucleation into lattice of weakly soluble gases. According theory, coefficients of stochastic and kinetic equations uniquely related. Radiation stimulated phase transition are characterized by kinetic distribution functions /DFs/ of implanted clusters versus their sizes and depth of gas penetration into lattice. Macroscopic parameters of kinetics such as the porosity and stress calculated in thin layers metal/dielectric due to Xe{sup ++} irradiation are attracted as example. Predictions of porosity, important for validation accumulation stresses in surfaces, can be applied at restoring of objects the cultural heritage.
Stochastic description for open quantum systems
Calzetta, E A; Verdaguer, E; Calzetta, Esteban; Roura, Albert; Verdaguer, Enric
2000-01-01
A linear open quantum system consisting of a harmonic oscillator coupled linearly to an infinite set of independent harmonic oscillators is considered; these oscillators have a general spectral density function and are initially in thermal equilibrium. Using the influence functional formalism a formal Langevin equation can be introduced to describe the system's fully quantum properties even beyond the semiclassical regime. It is shown that the reduced Wigner function for the system is exactly the formal distribution function resulting from averaging both over the initial conditions and the stochastic source of the formal Langevin equation. The master equation for the reduced density matrix is then obtained in the same way a Fokker-Planck equation can always be derived from a Langevin equation characterizing a stochastic process. We also show that the quantum correlation functions for the system can be deduced within the stochastic description provided by the Langevin equation. It is emphasized that when the s...
Wang, Maosheng; Sun, Runzhi
2014-03-01
The cooperative effects of inherent stochasticity and random long-range connections (RLRCs) on synchronization and coherence resonance in networks of calcium oscillators have been investigated. Two different types of collective behaviors, coherence resonance (CR) and synchronization, have been studied numerically in the context of chemical Langevin equations (CLEs). In the CLEs, the reaction steps are all stochastic, including the exchange of calcium ions between adjacent and non-adjacent cells through the gap junctions. The calcium oscillators’ synchronization was characterized by the standard deviation of the cytosolic calcium concentrations. Meanwhile, the temporal coherence of the calcium spike train was characterized by the reciprocal coefficient of variance (RCV). Synchronization induced by RLRCs was observed, namely, the exchange of calcium ions between non-adjacent cells can promote the synchronization of the cells. Moreover, it was found that the RCV shows a clear peak when both inherent stochasticity and RLRCs are optimal, indicating the existence of CR. Since inherent stochasticity and RLRCs are two essential ingredients of cellular processes, synchronization and CR are also important for cells’ functions. The results reported in this paper are expected to be useful for understanding the dynamics of intercellular calcium signaling processes in vivo.
Directory of Open Access Journals (Sweden)
Zhi Chen
2015-01-01
Full Text Available This paper presents an online method for the assessment of the dynamic performance of the chassis frame in a heavy-duty dump truck based on a novel stochastic subspace identification (SSI method. It introduces the use of an average correlation signal as the input data to conventional SSI methods in order to reduce the noisy and nonstationary contents in the vibration signals from the frame, allowing accurate modal properties to be attained for realistically assessing the dynamic behaviour of the frame when the vehicle travels on both bumped and unpaved roads under different operating conditions. The modal results show that the modal properties obtained online are significantly different from the offline ones in that the identifiable modes are less because of the integration of different vehicle systems onto the frame. Moreover, the modal shapes between 7 Hz and 40 Hz clearly indicate the weak section of the structure where earlier fatigues and unsafe operations may occur due to the high relative changes in the modal shapes. In addition, the loaded operations show more modes which cause high deformation on the weak section. These results have verified the performance of the proposed SSI method and provide reliable references for optimizing the construction of the frame.
Dynamic range of hypercubic stochastic excitable media
de Assis, Vladimir R V
2007-01-01
We study the response properties of d-dimensional hypercubic excitable networks to a stochastic stimulus. Each site, modelled either by a three-state stochastic susceptible-infected-recovered-susceptible (SIRS) system or by the probabilistic Greenberg-Hastings cellular automaton (GHCA), is continuously and independently stimulated by an external Poisson rate h. The response function (mean density of active sites rho versus h) is obtained via simulations (for d=1, 2, 3, 4) and mean field approximations at the single-site and pair levels (for all d). In any dimension, the dynamic range of the response function is maximized precisely at the nonequilibrium phase transition to self-sustained activity, in agreement with a reasoning recently proposed. Moreover, the maximum dynamic range attained at a given dimension d is a decreasing function of d.
Stochastic discrete model of karstic networks
Jaquet, O.; Siegel, P.; Klubertanz, G.; Benabderrhamane, H.
Karst aquifers are characterised by an extreme spatial heterogeneity that strongly influences their hydraulic behaviour and the transport of pollutants. These aquifers are particularly vulnerable to contamination because of their highly permeable networks of conduits. A stochastic model is proposed for the simulation of the geometry of karstic networks at a regional scale. The model integrates the relevant physical processes governing the formation of karstic networks. The discrete simulation of karstic networks is performed with a modified lattice-gas cellular automaton for a representative description of the karstic aquifer geometry. Consequently, more reliable modelling results can be obtained for the management and the protection of karst aquifers. The stochastic model was applied jointly with groundwater modelling techniques to a regional karst aquifer in France for the purpose of resolving surface pollution issues.
Organization of cellular receptors into a nanoscale junction during HIV-1 adhesion.
Directory of Open Access Journals (Sweden)
Terrence M Dobrowsky
Full Text Available The fusion of the human immunodeficiency virus type 1 (HIV-1 with its host cell is the target for new antiretroviral therapies. Viral particles interact with the flexible plasma membrane via viral surface protein gp120 which binds its primary cellular receptor CD4 and subsequently the coreceptor CCR5. However, whether and how these receptors become organized at the adhesive junction between cell and virion are unknown. Here, stochastic modeling predicts that, regarding binding to gp120, cellular receptors CD4 and CCR5 form an organized, ring-like, nanoscale structure beneath the virion, which locally deforms the plasma membrane. This organized adhesive junction between cell and virion, which we name the viral junction, is reminiscent of the well-characterized immunological synapse, albeit at much smaller length scales. The formation of an organized viral junction under multiple physiopathologically relevant conditions may represent a novel intermediate step in productive infection.
Organization of cellular receptors into a nanoscale junction during HIV-1 adhesion.
Dobrowsky, Terrence M; Daniels, Brian R; Siliciano, Robert F; Sun, Sean X; Wirtz, Denis
2010-07-15
The fusion of the human immunodeficiency virus type 1 (HIV-1) with its host cell is the target for new antiretroviral therapies. Viral particles interact with the flexible plasma membrane via viral surface protein gp120 which binds its primary cellular receptor CD4 and subsequently the coreceptor CCR5. However, whether and how these receptors become organized at the adhesive junction between cell and virion are unknown. Here, stochastic modeling predicts that, regarding binding to gp120, cellular receptors CD4 and CCR5 form an organized, ring-like, nanoscale structure beneath the virion, which locally deforms the plasma membrane. This organized adhesive junction between cell and virion, which we name the viral junction, is reminiscent of the well-characterized immunological synapse, albeit at much smaller length scales. The formation of an organized viral junction under multiple physiopathologically relevant conditions may represent a novel intermediate step in productive infection.
Genomic analysis of QTLs and genes altering natural variation in stochastic noise.
Jimenez-Gomez, Jose M; Corwin, Jason A; Joseph, Bindu; Maloof, Julin N; Kliebenstein, Daniel J
2011-09-01
genetic variation controlling stochasticity is equally distributed across the genomes of other multi-cellular eukaryotes.
A NEW STOCHASTIC OPTIMAL CONTROL STRATEGY FOR HYSTERETIC MR DAMPERS
Institute of Scientific and Technical Information of China (English)
YingZuguang; NiYiqing; KoJanming
2004-01-01
A new stochastic optimal control strategy for randomly excited quasi-integrable Hamiltonian systems using magneto-theological (MR) dampers is proposed. The dynamic behavior of an MR damper is characterized by the Bouc-Wen hysteretic model. The control force produced by the MR damper is separated into a passive part incorporated in the uncontrolled system and a semi-active part to be determined. The system combining the Bouc-Wen hysteretic force is converted into an equivalent non-hysteretic nonlinear stochastic control system. Then Ito stochastic differential equations are derived from the equivalent system by using the stochastic averaging method. A dynamical programming equation for the controlled diffusion processes is established based on the stochastic dynamical programming principle. The non-clipping nonlinear optimal control law is obtained for a certain performance index by minimizing the dynamical programming equation. Finally, an example is given to illustrate the application and effectiveness of the proposed control strategy.
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...
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.
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.
Asymptotic problems for stochastic partial differential equations
Salins, Michael
Stochastic partial differential equations (SPDEs) can be used to model systems in a wide variety of fields including physics, chemistry, and engineering. The main SPDEs of interest in this dissertation are the semilinear stochastic wave equations which model the movement of a material with constant mass density that is exposed to both determinstic and random forcing. Cerrai and Freidlin have shown that on fixed time intervals, as the mass density of the material approaches zero, the solutions of the stochastic wave equation converge uniformly to the solutions of a stochastic heat equation, in probability. This is called the Smoluchowski-Kramers approximation. In Chapter 2, we investigate some of the multi-scale behaviors that these wave equations exhibit. In particular, we show that the Freidlin-Wentzell exit place and exit time asymptotics for the stochastic wave equation in the small noise regime can be approximated by the exit place and exit time asymptotics for the stochastic heat equation. We prove that the exit time and exit place asymptotics are characterized by quantities called quasipotentials and we prove that the quasipotentials converge. We then investigate the special case where the equation has a gradient structure and show that we can explicitly solve for the quasipotentials, and that the quasipotentials for the heat equation and wave equation are equal. In Chapter 3, we study the Smoluchowski-Kramers approximation in the case where the material is electrically charged and exposed to a magnetic field. Interestingly, if the system is frictionless, then the Smoluchowski-Kramers approximation does not hold. We prove that the Smoluchowski-Kramers approximation is valid for systems exposed to both a magnetic field and friction. Notably, we prove that the solutions to the second-order equations converge to the solutions of the first-order equation in an Lp sense. This strengthens previous results where convergence was proved in probability.
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 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 waves in a Brusselator model with nonlocal interaction.
Biancalani, Tommaso; Galla, Tobias; McKane, Alan J
2011-08-01
We show that intrinsic noise can induce spatiotemporal phenomena such as Turing patterns and traveling waves in a Brusselator model with nonlocal interaction terms. In order to predict and to characterize these stochastic waves we analyze the nonlocal model using a system-size expansion. The resulting theory is used to calculate the power spectra of the stochastic waves analytically and the outcome is tested successfully against simulations. We discuss the possibility that nonlocal models in other areas, such as epidemic spread or social dynamics, may contain similar stochastically induced patterns.
Heterogeneous ice nucleation: bridging stochastic and singular freezing behavior
Directory of Open Access Journals (Sweden)
D. Niedermeier
2011-01-01
Full Text Available Heterogeneous ice nucleation, a primary pathway for ice formation in the atmosphere, has been described alternately as being stochastic, in direct analogy with homogeneous nucleation, or singular, with ice nuclei initiating freezing at deterministic temperatures. We present an idealized model that bridges these stochastic and singular descriptions of heterogeneous ice nucleation. This "soccer ball" model treats statistically similar particles as being covered with surface sites (patches of finite area characterized by different nucleation barriers, but with each surface site following the stochastic nature of ice embryo formation. The model provides a phenomenological explanation for seemingly contradictory experimental results obtained in our research groups. We suggest that ice nucleation is fundamentally a stochastic process but that for realistic atmospheric particle populations this process can be masked by the heterogeneity of surface properties. Full evaluation of the model will require experiments with well characterized ice nucleating particles and the ability to vary both temperature and waiting time for freezing.
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
Stochastically Induced Critical Depensation and Risk of Stock Collapse
Diwakar Poudel; Sandal, Leif K.; Kvamsdal, Sturla F.
2015-01-01
This article investigates the risk of stock collapse due to stochastically induced critical depensation in managed fisheries. We use a continuous-time surplus production model and an economic model with downward-sloping demand and stock-dependent costs. First, we derive an optimal exploitation policy as a feedback control rule by applying the Hamilton-Jacobi-Bellman approach and analyze the effects of stochasticity on the optimal policy. Then, we characterize the long-term sustainable optimal...
Stochastic observability, reconstructibility, controllability, and reachability
Liu, Andrew R.
2011-01-01
This thesis formulates versions of observability, reconstructibility, controllability, and reachability for stochastic linear and nonlinear systems. The concepts of observability and reconstructibility concern whether the measurements of a system suffice to construct a complete characterization of the system behavior while the concepts of controllability and reachability concern whether the actuation of the system suffices to cause the system to behave according to various user specifications...
Inácio, Celso dos Santos Laurinda
2011-01-01
The Multi-Point Stochastic Inversion (MPSI) is a method based on both deterministic inversion and stochastic inversion. The deterministic inversion is used prior to the stochastic inversion and it is more general and works well for thick layers while the stochastic inversion works well for thin layers. Because of its combination, the MPSI method is one of suitable methods for reservoir characterization. Apart from being used for post-stack seismic acoustic impedance (AI) inversion, the MPSI m...
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...
Hoze, N; Holcman, D
2015-11-01
Recovering a stochastic process from noisy ensembles of single-particle trajectories is resolved here using the coarse-grained Langevin equation as a model. The massive redundancy contained in single-particle tracking data allows recovering local parameters of the underlying physical model. We use several parametric and nonparametric estimators to compute the first and second moments of the process, to recover the local drift, its derivative, and the diffusion tensor, and to deconvolve the instrumental from the physical noise. We use numerical simulations to also explore the range of validity for these estimators. The present analysis allows defining what can exactly be recovered from statistics of super-resolution microscopy trajectories used for characterizing molecular trafficking underlying cellular functions.
Stochastic population growth in spatially heterogeneous environments.
Evans, Steven N; Ralph, Peter L; Schreiber, Sebastian J; Sen, Arnab
2013-02-01
Classical ecological theory predicts that environmental stochasticity increases extinction risk by reducing the average per-capita growth rate of populations. For sedentary populations in a spatially homogeneous yet temporally variable environment, a simple model of population growth is a stochastic differential equation dZ(t) = μZ(t)dt + σZ(t)dW(t), t ≥ 0, where the conditional law of Z(t+Δt)-Z(t) given Z(t) = z has mean and variance approximately z μΔt and z²σ²Δt when the time increment Δt is small. The long-term stochastic growth rate lim(t→∞) t⁻¹ log Z(t) for such a population equals μ − σ²/2 . Most populations, however, experience spatial as well as temporal variability. To understand the interactive effects of environmental stochasticity, spatial heterogeneity, and dispersal on population growth, we study an analogous model X(t) = (X¹(t) , . . . , X(n)(t)), t ≥ 0, for the population abundances in n patches: the conditional law of X(t+Δt) given X(t) = x is such that the conditional mean of X(i)(t+Δt) − X(i)(t) is approximately [x(i)μ(i) + Σ(j) (x(j) D(ji) − x(i) D(i j) )]Δt where μ(i) is the per capita growth rate in the ith patch and D(ij) is the dispersal rate from the ith patch to the jth patch, and the conditional covariance of X(i)(t+Δt)− X(i)(t) and X(j)(t+Δt) − X(j)(t) is approximately x(i)x(j)σ(ij)Δt for some covariance matrix Σ = (σ(ij)). We show for such a spatially extended population that if S(t) = X¹(t)+· · ·+ X(n)(t) denotes the total population abundance, then Y(t) = X(t)/S(t), the vector of patch proportions, converges in law to a random vector Y(∞) as t → ∞, and the stochastic growth rate lim(t→∞) t⁻¹ log S(t) equals the space-time average per-capita growth rate Σ(i)μ(i)E[Y(i)(∞)] experienced by the population minus half of the space-time average temporal variation E[Σ(i,j) σ(i j)Y(i)(∞) Y(j)(∞)] experienced by the population. Using this characterization of the
Directory of Open Access Journals (Sweden)
Li Xing'an
2010-08-01
Full Text Available Abstract Background Cooperation of constituents of the ubiquitin proteasome system (UPS with chaperone proteins in degrading proteins mediate a wide range of cellular processes, such as synaptic function and neurotransmission, gene transcription, protein trafficking, mitochondrial function and metabolism, antioxidant defence mechanisms, and apoptotic signal transduction. It is supposed that constituents of the UPS and chaperone proteins are recruited into aggresomes where aberrant and potentially cytotoxic proteins may be sequestered in an inactive form. Results To determinate the proteomic pattern of synthetic proteasome inhibitor (PSI-induced inclusions in PC12 cells after proteasome inhibition by PSI, we analyzed a fraction of PSI-induced inclusions. A proteomic feature of the isolated fraction was characterized by identification of fifty six proteins including twenty previously reported protein components of Lewy bodies, twenty eight newly identified proteins and eight unknown proteins. These proteins, most of which were recognized as a profile of proteins within cellular processes mediated by the UPS, a profile of constituents of the UPS and a profile of chaperone proteins, are classed into at least nine accepted categories. In addition, prolyl-4-hydroxylase beta polypeptide, an endoplasmic reticulum member of the protein disulfide isomerase family, was validated in the developmental process of PSI-induced inclusions in the cells. Conclusions It is speculated that proteomic characterization of an isolated fraction of PSI-induced inclusions in PC12 cells might offer clues to appearance of aggresomes serving as a cellular defensive response against proteasome inhibition.
Stochastic porous media equations
Barbu, Viorel; Röckner, Michael
2016-01-01
Focusing on stochastic porous media equations, this book places an emphasis on existence theorems, asymptotic behavior and ergodic properties of the associated transition semigroup. Stochastic perturbations of the porous media equation have reviously been considered by physicists, but rigorous mathematical existence results have only recently been found. The porous media equation models a number of different physical phenomena, including the flow of an ideal gas and the diffusion of a compressible fluid through porous media, and also thermal propagation in plasma and plasma radiation. Another important application is to a model of the standard self-organized criticality process, called the "sand-pile model" or the "Bak-Tang-Wiesenfeld model". The book will be of interest to PhD students and researchers in mathematics, physics and biology.
Stochastic 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...
Directory of Open Access Journals (Sweden)
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
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 ...
Cellular non-deterministic automata and partial differential equations
Kohler, D.; Müller, J.; Wever, U.
2015-09-01
We define cellular non-deterministic automata (CNDA) in the spirit of non-deterministic automata theory. They are different from the well-known stochastic automata. We propose the concept of deterministic superautomata to analyze the dynamical behavior of a CNDA and show especially that a CNDA can be embedded in a deterministic cellular automaton. As an application we discuss a connection between certain partial differential equations and CNDA.
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.
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.
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.
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
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...
An agent-based model of cellular dynamics and circadian variability in human endotoxemia.
Directory of Open Access Journals (Sweden)
Tung T Nguyen
Full Text Available As cellular variability and circadian rhythmicity play critical roles in immune and inflammatory responses, we present in this study an agent-based model of human endotoxemia to examine the interplay between circadian controls, cellular variability and stochastic dynamics of inflammatory cytokines. The model is qualitatively validated by its ability to reproduce circadian dynamics of inflammatory mediators and critical inflammatory responses after endotoxin administration in vivo. Novel computational concepts are proposed to characterize the cellular variability and synchronization of inflammatory cytokines in a population of heterogeneous leukocytes. Our results suggest that there is a decrease in cell-to-cell variability of inflammatory cytokines while their synchronization is increased after endotoxin challenge. Model parameters that are responsible for IκB production stimulated by NFκB activation and for the production of anti-inflammatory cytokines have large impacts on system behaviors. Additionally, examining time-dependent systemic responses revealed that the system is least vulnerable to endotoxin in the early morning and most vulnerable around midnight. Although much remains to be explored, proposed computational concepts and the model we have pioneered will provide important insights for future investigations and extensions, especially for single-cell studies to discover how cellular variability contributes to clinical implications.
Fundamental Limits to Cellular Sensing
ten Wolde, Pieter Rein; Becker, Nils B.; Ouldridge, Thomas E.; Mugler, Andrew
2016-03-01
In recent years experiments have demonstrated that living cells can measure low chemical concentrations with high precision, and much progress has been made in understanding what sets the fundamental limit to the precision of chemical sensing. Chemical concentration measurements start with the binding of ligand molecules to receptor proteins, which is an inherently noisy process, especially at low concentrations. The signaling networks that transmit the information on the ligand concentration from the receptors into the cell have to filter this receptor input noise as much as possible. These networks, however, are also intrinsically stochastic in nature, which means that they will also add noise to the transmitted signal. In this review, we will first discuss how the diffusive transport and binding of ligand to the receptor sets the receptor correlation time, which is the timescale over which fluctuations in the state of the receptor, arising from the stochastic receptor-ligand binding, decay. We then describe how downstream signaling pathways integrate these receptor-state fluctuations, and how the number of receptors, the receptor correlation time, and the effective integration time set by the downstream network, together impose a fundamental limit on the precision of sensing. We then discuss how cells can remove the receptor input noise while simultaneously suppressing the intrinsic noise in the signaling network. We describe why this mechanism of time integration requires three classes (groups) of resources—receptors and their integration time, readout molecules, energy—and how each resource class sets a fundamental sensing limit. We also briefly discuss the scheme of maximum-likelihood estimation, the role of receptor cooperativity, and how cellular copy protocols differ from canonical copy protocols typically considered in the computational literature, explaining why cellular sensing systems can never reach the Landauer limit on the optimal trade
Liang, Jie; Qian, Hong
2010-01-01
Modern molecular biology has always been a great source of inspiration for computational science. Half a century ago, the challenge from understanding macromolecular dynamics has led the way for computations to be part of the tool set to study molecular biology. Twenty-five years ago, the demand from genome science has inspired an entire generation of computer scientists with an interest in discrete mathematics to join the field that is now called bioinformatics. In this paper, we shall lay out a new mathematical theory for dynamics of biochemical reaction systems in a small volume (i.e., mesoscopic) in terms of a stochastic, discrete-state continuous-time formulation, called the chemical master equation (CME). Similar to the wavefunction in quantum mechanics, the dynamically changing probability landscape associated with the state space provides a fundamental characterization of the biochemical reaction system. The stochastic trajectories of the dynamics are best known through the simulations using the Gillespie algorithm. In contrast to the Metropolis algorithm, this Monte Carlo sampling technique does not follow a process with detailed balance. We shall show several examples how CMEs are used to model cellular biochemical systems. We shall also illustrate the computational challenges involved: multiscale phenomena, the interplay between stochasticity and nonlinearity, and how macroscopic determinism arises from mesoscopic dynamics. We point out recent advances in computing solutions to the CME, including exact solution of the steady state landscape and stochastic differential equations that offer alternatives to the Gilespie algorithm. We argue that the CME is an ideal system from which one can learn to understand "complex behavior" and complexity theory, and from which important biological insight can be gained.
Heuristic for Stochastic Online Flowshop Problem with Preemption Penalties
Directory of Open Access Journals (Sweden)
Mohammad Bayat
2013-01-01
Full Text Available The deterministic flowshop model is one of the most widely studied problems; whereas its stochastic equivalent has remained a challenge. Furthermore, the preemptive online stochastic flowshop problem has received much less attention, and most of the previous researches have considered a nonpreemptive version. Moreover, little attention has been devoted to the problems where a certain time penalty is incurred when preemption is allowed. This paper examines the preemptive stochastic online flowshop with the objective of minimizing the expected makespan. All the jobs arrive overtime, which means that the existence and the parameters of each job are unknown until its release date. The processing time of the jobs is stochastic and actual processing time is unknown until completion of the job. A heuristic procedure for this problem is presented, which is applicable whenever the job processing times are characterized by their means and standard deviation. The performance of the proposed heuristic method is explored using some numerical examples.
Characterization of renal cellular carcinoma with contrast-enhanced ultrasound%肾细胞癌的超声造影研究
Institute of Scientific and Technical Information of China (English)
徐作峰; 万广生; 谢晓燕; 吕明德; 徐辉雄; 刘广健; 黄蓓
2008-01-01
Objective To conclude the characterization of renal cellular carcinoma(RCC)with contrast enhanced ultrasound.Methods Seventy patients(seventy-two nodules)with RCC,which were confirmed by operation and biopsy underwent conventional ultrasound and contrast-enhanced ultrasound(CEUS).Microbubble agents SonoVue and contrast pulse sequence(CPS)were used.The conventional uItrasonographic characterization and the enhancement patterns of lesions were analyzed.Results On baseline sonography,the numbers of lesions that showed hypoechogenicity,isoechogenicity,and hyperechogenicity were 44.4%(32/72),25.0%(18/72)and 30.6%(22/72),respectively.Only 28 lesions(38.9%)showed flow signals on color Doppler sonography,the mean maximum velocity of which WSS(43.7±16.8)cm/s(range,24.8-95 cm/s),and the mean resistance index was 0.635±0.11(range.0.52-0.83).Sixty-three(87.5%)lesions were hyper-vascular in cortical phase.Among them forty-eight(76.2%)lesions were hypo-enhanced,and fifteen(23.8%)lesions were still hyper-vascular in late phase.The remaining nine hypervascular nodules in cortical phase were still hyper-enhancing in late phase.Fifty-four(75.0%)lesions were inhomogeneous enhancement.and pseudocapsule was observed in sixty-three(87.5%)RCC lesions.Conclusions The enhancement patterns of RCC are characteristic,and CEUS may be helpful in differential diagnosis of focal renal lesions.%目的 总结和探讨肾细胞癌的超声造影特征.方法 70例肾细胞癌共72个病灶接受了常规超声和超声造影检查,分析病灶的常规超声及超声造影表现特征.超声造影使用造影剂声诺维和对比脉冲序列成像技术.结果 常规超声显示低、等、高回声的病灶分别为44.4%(32/72)、25.0%(18/72)和30.6%(22/72).病灶彩色血流信号显示率为38.9%(28/72),动脉峰值流速(43.7±16.8)cm/s(24.8～95 cm/s),阻力指数0.63±0.11(0.53～0.80).超声造影显示皮质期63个(87.5%)病灶表现为等或高增强,9个(12.5%)为低增强.63
Constructing stochastic models from deterministic process equations by propensity adjustment
Directory of Open Access Journals (Sweden)
Wu Jialiang
2011-11-01
Full Text Available Abstract Background Gillespie's stochastic simulation algorithm (SSA for chemical reactions admits three kinds of elementary processes, namely, mass action reactions of 0th, 1st or 2nd order. All other types of reaction processes, for instance those containing non-integer kinetic orders or following other types of kinetic laws, are assumed to be convertible to one of the three elementary kinds, so that SSA can validly be applied. However, the conversion to elementary reactions is often difficult, if not impossible. Within deterministic contexts, a strategy of model reduction is often used. Such a reduction simplifies the actual system of reactions by merging or approximating intermediate steps and omitting reactants such as transient complexes. It would be valuable to adopt a similar reduction strategy to stochastic modelling. Indeed, efforts have been devoted to manipulating the chemical master equation (CME in order to achieve a proper propensity function for a reduced stochastic system. However, manipulations of CME are almost always complicated, and successes have been limited to relative simple cases. Results We propose a rather general strategy for converting a deterministic process model into a corresponding stochastic model and characterize the mathematical connections between the two. The deterministic framework is assumed to be a generalized mass action system and the stochastic analogue is in the format of the chemical master equation. The analysis identifies situations: where a direct conversion is valid; where internal noise affecting the system needs to be taken into account; and where the propensity function must be mathematically adjusted. The conversion from deterministic to stochastic models is illustrated with several representative examples, including reversible reactions with feedback controls, Michaelis-Menten enzyme kinetics, a genetic regulatory motif, and stochastic focusing. Conclusions The construction of a stochastic
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.
Fuzzy Stochastic Optimization Theory, Models and Applications
Wang, Shuming
2012-01-01
Covering in detail both theoretical and practical perspectives, this book is a self-contained and systematic depiction of current fuzzy stochastic optimization that deploys the fuzzy random variable as a core mathematical tool to model the integrated fuzzy random uncertainty. It proceeds in an orderly fashion from the requisite theoretical aspects of the fuzzy random variable to fuzzy stochastic optimization models and their real-life case studies. The volume reflects the fact that randomness and fuzziness (or vagueness) are two major sources of uncertainty in the real world, with significant implications in a number of settings. In industrial engineering, management and economics, the chances are high that decision makers will be confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and optimization in the form of a decision must be made in an environment that is doubly uncertain, characterized by a co-occurrence of randomness and fuzziness. This book begins...
Stochastic Combinatorial Optimization under Probabilistic Constraints
Agrawal, Shipra; Ye, Yinyu
2008-01-01
In this paper, we present approximation algorithms for combinatorial optimization problems under probabilistic constraints. Specifically, we focus on stochastic variants of two important combinatorial optimization problems: the k-center problem and the set cover problem, with uncertainty characterized by a probability distribution over set of points or elements to be covered. We consider these problems under adaptive and non-adaptive settings, and present efficient approximation algorithms for the case when underlying distribution is a product distribution. In contrast to the expected cost model prevalent in stochastic optimization literature, our problem definitions support restrictions on the probability distributions of the total costs, via incorporating constraints that bound the probability with which the incurred costs may exceed a given threshold.
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.
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.
Environment Aware Cellular Networks
Ghazzai, Hakim
2015-02-01
The unprecedented rise of mobile user demand over the years have led to an enormous growth of the energy consumption of wireless networks as well as the greenhouse gas emissions which are estimated currently to be around 70 million tons per year. This significant growth of energy consumption impels network companies to pay huge bills which represent around half of their operating expenditures. Therefore, many service providers, including mobile operators, are looking for new and modern green solutions to help reduce their expenses as well as the level of their CO2 emissions. Base stations are the most power greedy element in cellular networks: they drain around 80% of the total network energy consumption even during low traffic periods. Thus, there is a growing need to develop more energy-efficient techniques to enhance the green performance of future 4G/5G cellular networks. Due to the problem of traffic load fluctuations in cellular networks during different periods of the day and between different areas (shopping or business districts and residential areas), the base station sleeping strategy has been one of the main popular research topics in green communications. In this presentation, we present several practical green techniques that provide significant gains for mobile operators. Indeed, combined with the base station sleeping strategy, these techniques achieve not only a minimization of the fossil fuel consumption but also an enhancement of mobile operator profits. We start with an optimized cell planning method that considers varying spatial and temporal user densities. We then use the optimal transport theory in order to define the cell boundaries such that the network total transmit power is reduced. Afterwards, we exploit the features of the modern electrical grid, the smart grid, as a new tool of power management for cellular networks and we optimize the energy procurement from multiple energy retailers characterized by different prices and pollutant
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
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…
Directory of Open Access Journals (Sweden)
Mayu Sugiyama
2014-12-01
Full Text Available In multicellular organism development, a stochastic cellular response is observed, even when a population of cells is exposed to the same environmental conditions. Retrieving the spatiotemporal regulatory mode hidden in the heterogeneous cellular behavior is a challenging task. The G1/S transition observed in cell cycle progression is a highly stochastic process. By taking advantage of a fluorescence cell cycle indicator, Fucci technology, we aimed to unveil a hidden regulatory mode of cell cycle progression in developing zebrafish. Fluorescence live imaging of Cecyil, a zebrafish line genetically expressing Fucci, demonstrated that newly formed notochordal cells from the posterior tip of the embryonic mesoderm exhibited the red (G1 fluorescence signal in the developing notochord. Prior to their initial vacuolation, these cells showed a fluorescence color switch from red to green, indicating G1/S transitions. This G1/S transition did not occur in a synchronous manner, but rather exhibited a stochastic process, since a mixed population of red and green cells was always inserted between newly formed red (G1 notochordal cells and vacuolating green cells. We termed this mixed population of notochordal cells, the G1/S transition window. We first performed quantitative analyses of live imaging data and a numerical estimation of the probability of the G1/S transition, which demonstrated the existence of a posteriorly traveling regulatory wave of the G1/S transition window. To obtain a better understanding of this regulatory mode, we constructed a mathematical model and performed a model selection by comparing the results obtained from the models with those from the experimental data. Our analyses demonstrated that the stochastic G1/S transition window in the notochord travels posteriorly in a periodic fashion, with doubled the periodicity of the neighboring paraxial mesoderm segmentation. This approach may have implications for the characterization of
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.
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...
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...
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.
Error performance analysis in downlink cellular networks with interference management
Afify, Laila H.
2015-05-01
Modeling aggregate network interference in cellular networks has recently gained immense attention both in academia and industry. While stochastic geometry based models have succeeded to account for the cellular network geometry, they mostly abstract many important wireless communication system aspects (e.g., modulation techniques, signal recovery techniques). Recently, a novel stochastic geometry model, based on the Equivalent-in-Distribution (EiD) approach, succeeded to capture the aforementioned communication system aspects and extend the analysis to averaged error performance, however, on the expense of increasing the modeling complexity. Inspired by the EiD approach, the analysis developed in [1] takes into consideration the key system parameters, while providing a simple tractable analysis. In this paper, we extend this framework to study the effect of different interference management techniques in downlink cellular network. The accuracy of the proposed analysis is verified via Monte Carlo simulations.
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...
Inferring single-cell gene expression mechanisms using stochastic simulation
Daigle, Bernie J.; Soltani, Mohammad; Petzold, Linda R.; Singh, Abhyudai
2015-01-01
Motivation: Stochastic promoter switching between transcriptionally active (ON) and inactive (OFF) states is a major source of noise in gene expression. It is often implicitly assumed that transitions between promoter states are memoryless, i.e. promoters spend an exponentially distributed time interval in each of the two states. However, increasing evidence suggests that promoter ON/OFF times can be non-exponential, hinting at more complex transcriptional regulatory architectures. Given the essential role of gene expression in all cellular functions, efficient computational techniques for characterizing promoter architectures are critically needed. Results: We have developed a novel model reduction for promoters with arbitrary numbers of ON and OFF states, allowing us to approximate complex promoter switching behavior with Weibull-distributed ON/OFF times. Using this model reduction, we created bursty Monte Carlo expectation-maximization with modified cross-entropy method (‘bursty MCEM2’), an efficient parameter estimation and model selection technique for inferring the number and configuration of promoter states from single-cell gene expression data. Application of bursty MCEM2 to data from the endogenous mouse glutaminase promoter reveals nearly deterministic promoter OFF times, consistent with a multi-step activation mechanism consisting of 10 or more inactive states. Our novel approach to modeling promoter fluctuations together with bursty MCEM2 provides powerful tools for characterizing transcriptional bursting across genes under different environmental conditions. Availability and implementation: R source code implementing bursty MCEM2 is available upon request. Contact: absingh@udel.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25573914
Directory of Open Access Journals (Sweden)
Zhang Deshui
2012-11-01
Full Text Available Abstract Background Transferrin (TF plays a critical physiological role in cellular iron delivery via the transferrin receptor (TFR-mediated endocytosis pathway in nearly all eukaryotic organisms. Human serum TF (hTF is extensively used as an iron-delivery vehicle in various mammalian cell cultures for production of therapeutic proteins, and is also being explored for use as a drug carrier to treat a number of diseases by employing its unique TFR-mediated endocytosis pathway. With the increasing concerns over the risk of transmission of infectious pathogenic agents of human plasma-derived TF, recombinant hTF is preferred to use for these applications. Here, we carry out comparative studies of the TFR binding, TFR-mediated endocytosis and cellular iron delivery of recombinant hTF from rice (rhTF, and evaluate its suitability for biopharmaceutical applications. Result Through a TFR competition binding affinity assay with HeLa human cervic carcinoma cells (CCL-2 and Caco-2 human colon carcinoma cells (HTB-37, we show that rhTF competes similarly as hTF to bind TFR, and both the TFR binding capacity and dissociation constant of rhTF are comparable to that of hTF. The endocytosis assay confirms that rhTF behaves similarly as hTF in the slow accumulation in enterocyte-like Caco-2 cells and the rapid recycling pathway in HeLa cells. The pulse-chase assay of rhTF in Caco-2 and HeLa cells further illustrates that rice-derived rhTF possesses the similar endocytosis and intracellular processing compared to hTF. The cell culture assays show that rhTF is functionally similar to hTF in the delivery of iron to two diverse mammalian cell lines, HL-60 human promyelocytic leukemia cells (CCL-240 and murine hybridoma cells derived from a Sp2/0-Ag14 myeloma fusion partner (HB-72, for supporting their proliferation, differentiation, and physiological function of antibody production. Conclusion The functional similarity between rice derived rhTF and native hTF in
Directory of Open Access Journals (Sweden)
Sun Z
2013-03-01
Full Text Available Zhizhi Sun,1 Vinith Yathindranath,2 Matthew Worden,3 James A Thliveris,4 Stephanie Chu,1 Fiona E Parkinson,1 Torsten Hegmann,1–3 Donald W Miller1 1Department of Pharmacology and Therapeutics, 2Department of Chemistry, University of Manitoba, Winnipeg, Manitoba, Canada; 3Chemical Physics Interdisciplinary Program, Liquid Crystal Institute, Kent State University, Kent, OH, USA; 4Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, Manitoba, Canada Background: Aminosilane-coated iron oxide nanoparticles (AmS-IONPs have been widely used in constructing complex and multifunctional drug delivery systems. However, the biocompatibility and uptake characteristics of AmS-IONPs in central nervous system (CNS-relevant cells are unknown. The purpose of this study was to determine the effect of surface charge and magnetic field on toxicity and uptake of AmS-IONPs in CNS-relevant cell types. Methods: The toxicity and uptake profile of positively charged AmS-IONPs and negatively charged COOH-AmS-IONPs of similar size were examined using a mouse brain microvessel endothelial cell line (bEnd.3 and primary cultured mouse astrocytes and neurons. Cell accumulation of IONPs was examined using the ferrozine assay, and cytotoxicity was assessed by the 3-(4,5-dimethylthiazol-2-yl-2,5-diphenyltetrazolium bromide (MTT assay. Results: No toxicity was observed in bEnd.3 cells at concentrations up to 200 µg/mL for either AmS-IONPs or COOH-AmS-IONPs. AmS-IONPs at concentrations above 200 µg/mL reduced neuron viability by 50% in the presence or absence of a magnetic field, while only 20% reductions in viability were observed with COOH-AmS-IONPs. Similar concentrations of AmS-IONPs in astrocyte cultures reduced viability to 75% but only in the presence of a magnetic field, while exposure to COOH-AmS-IONPs reduced viability to 65% and 35% in the absence and presence of a magnetic field, respectively. Cellular accumulation of AmS-IONPs was greater
Directory of Open Access Journals (Sweden)
Qingxiang Guan
2016-12-01
Full Text Available Poorly soluble drugs have low bioavailability after oral administration, thereby hindering effective drug delivery. A novel drug-delivery system of docetaxel (DTX-based stearic acid (SA-modified Bletilla striata polysaccharides (BSPs copolymers was successfully developed. Particle size, zeta potential, encapsulation efficiency (EE, and loading capacity (LC were determined. The DTX release percentage in vitro was determined using high performance liquid chromatography (HPLC. The hemolysis and in vitro anticancer activity were studied. Cellular uptake and apoptotic rate were measured using flow cytometry assay. Particle size, zeta potential, EE and LC were 125.30 ± 1.89 nm, −26.92 ± 0.18 mV, 86.6% ± 0.17%, and 14.8% ± 0.13%, respectively. The anticancer activities of DTX-SA-BSPs copolymer micelles against HepG2, HeLa, SW480, and MCF-7 (83.7% ± 1.0%, 54.5% ± 4.2%, 48.5% ± 4.2%, and 59.8% ± 1.4%, respectively were superior to that of docetaxel injection (39.2% ± 1.1%, 44.5% ± 5.3%, 38.5% ± 5.4%, and 49.8% ± 2.9%, respectively at 0.5 μg/mL drug concentration. The DTX release percentage of DTX-SA-BSPs copolymer micelles and docetaxel injection were 66.93% ± 1.79% and 97.06% ± 1.56% in two days, respectively. Cellular uptake of DTX-FITC-SA-BSPs copolymer micelles in cells had a time-dependent relation. Apoptotic rate of DTX-SA-BSPs copolymer micelles and docetaxel injection were 73.48% and 69.64%, respectively. The SA-BSPs copolymer showed good hemocompatibility. Therefore, SA-BSPs copolymer can be used as a carrier for delivering hydrophobic drugs.
Guan, Qingxiang; Sun, Dandan; Zhang, Guangyuan; Sun, Cheng; Wang, Miao; Ji, Danyang; Yang, Wei
2016-12-02
Poorly soluble drugs have low bioavailability after oral administration, thereby hindering effective drug delivery. A novel drug-delivery system of docetaxel (DTX)-based stearic acid (SA)-modified Bletilla striata polysaccharides (BSPs) copolymers was successfully developed. Particle size, zeta potential, encapsulation efficiency (EE), and loading capacity (LC) were determined. The DTX release percentage in vitro was determined using high performance liquid chromatography (HPLC). The hemolysis and in vitro anticancer activity were studied. Cellular uptake and apoptotic rate were measured using flow cytometry assay. Particle size, zeta potential, EE and LC were 125.30 ± 1.89 nm, -26.92 ± 0.18 mV, 86.6% ± 0.17%, and 14.8% ± 0.13%, respectively. The anticancer activities of DTX-SA-BSPs copolymer micelles against HepG2, HeLa, SW480, and MCF-7 (83.7% ± 1.0%, 54.5% ± 4.2%, 48.5% ± 4.2%, and 59.8% ± 1.4%, respectively) were superior to that of docetaxel injection (39.2% ± 1.1%, 44.5% ± 5.3%, 38.5% ± 5.4%, and 49.8% ± 2.9%, respectively) at 0.5 μg/mL drug concentration. The DTX release percentage of DTX-SA-BSPs copolymer micelles and docetaxel injection were 66.93% ± 1.79% and 97.06% ± 1.56% in two days, respectively. Cellular uptake of DTX-FITC-SA-BSPs copolymer micelles in cells had a time-dependent relation. Apoptotic rate of DTX-SA-BSPs copolymer micelles and docetaxel injection were 73.48% and 69.64%, respectively. The SA-BSPs copolymer showed good hemocompatibility. Therefore, SA-BSPs copolymer can be used as a carrier for delivering hydrophobic drugs.
Cellular Automaton Modeling of Pattern Formation
Boerlijst, M.C.
2006-01-01
Book review Andreas Deutsch and Sabine Dormann, Cellular Automaton Modeling of Biological Pattern Formation, Characterization, Applications, and Analysis, Birkhäuser (2005) ISBN 0-8176-4281-1 331pp..
Densities and entropies in cellular automata
Guillon, Pierre
2012-01-01
Following work by Hochman and Meyerovitch on multidimensional SFT, we give computability-theoretic characterizations of the real numbers that can appear as the topological entropies of one-dimensional and two-dimensional cellular automata.
Dynamical critical behavior in a cellular model of superconducting vortex avalanches
Vadakkan, Tegy John
Bak, Tang, and Wiesenfeld showed that certain driven dissipative systems with many degrees of freedom organize into a critical state characterized by avalanche dynamics and power law distribution of avalanche sizes and durations. They called this phenomenon self-organized criticality and sandpile became the prototype of such dynamical systems. Universality in these systems is not yet well established. Forty years ago, de Gennes noted that the Bean state in a type-II superconductor is similar to a sandpile. Motivated by strong experimental evidences, Bassler and Paczuski (BP) proposed a 2D sandpile model to study self-organization in the dynamics of vortices in superconductors. In this dissertation, the effect of anisotropy in the vortex-vortex interaction, stochasticity in the vortex toppling rule, and the configuration of the pinning centers on the scaling properties of the avalanches in the BP model is studied. Also, universality in the cellular model of vortex dynamics is investigated.
Chemical kinetics, stochastic processes, and irreversible thermodynamics
Santillán, Moisés
2014-01-01
This book brings theories in nonlinear dynamics, stochastic processes, irreversible thermodynamics, physical chemistry, and biochemistry together in an introductory but formal and comprehensive manner. Coupled with examples, the theories are developed stepwise, starting with the simplest concepts and building upon them into a more general framework. Furthermore, each new mathematical derivation is immediately applied to one or more biological systems. The last chapters focus on applying mathematical and physical techniques to study systems such as: gene regulatory networks and ion channels. The target audience of this book are mainly final year undergraduate and graduate students with a solid mathematical background (physicists, mathematicians, and engineers), as well as with basic notions of biochemistry and cellular biology. This book can also be useful to students with a biological background who are interested in mathematical modeling, and have a working knowledge of calculus, differential equatio...
Multiscale mathematical modeling and simulation of cellular dynamical process.
Nakaoka, Shinji
2014-01-01
Epidermal homeostasis is maintained by dynamic interactions among molecules and cells at different spatiotemporal scales. Mathematical modeling and simulation is expected to provide clear understanding and precise description of multiscaleness in tissue homeostasis under systems perspective. We introduce a stochastic process-based description of multiscale dynamics. Agent-based modeling as a framework of multiscale modeling to achieve consistent integration of definitive subsystems is proposed. A newly developed algorithm that particularly aims to perform stochastic simulations of cellular dynamical process is introduced. Finally we review applications of multiscale modeling and quantitative study to important aspects of epidermal and epithelial homeostasis.
Scattering matrix theory for stochastic scalar fields.
Korotkova, Olga; Wolf, Emil
2007-05-01
We consider scattering of stochastic scalar fields on deterministic as well as on random media, occupying a finite domain. The scattering is characterized by a generalized scattering matrix which transforms the angular correlation function of the incident field into the angular correlation function of the scattered field. Within the accuracy of the first Born approximation this matrix can be expressed in a simple manner in terms of the scattering potential of the scatterer. Apart from determining the angular distribution of the spectral intensity of the scattered field, the scattering matrix makes it possible also to determine the changes in the state of coherence of the field produced on scattering.
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 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.
Complexity, dynamic cellular network, and tumorigenesis.
Waliszewski, P
1997-01-01
A holistic approach to tumorigenesis is proposed. The main element of the model is the existence of dynamic cellular network. This network comprises a molecular and an energetistic structure of a cell connected through the multidirectional flow of information. The interactions within dynamic cellular network are complex, stochastic, nonlinear, and also involve quantum effects. From this non-reductionist perspective, neither tumorigenesis can be limited to the genetic aspect, nor the initial event must be of molecular nature, nor mutations and epigenetic factors are mutually exclusive, nor a link between cause and effect can be established. Due to complexity, an unstable stationary state of dynamic cellular network rather than a group of unrelated genes determines the phenotype of normal and transformed cells. This implies relativity of tumor suppressor genes and oncogenes. A bifurcation point is defined as an unstable state of dynamic cellular network leading to the other phenotype-stationary state. In particular, the bifurcation point may be determined by a change of expression of a single gene. Then, the gene is called bifurcation point gene. The unstable stationary state facilitates the chaotic dynamics. This may result in a fractal dimension of both normal and tumor tissues. The co-existence of chaotic dynamics and complexity is the essence of cellular processes and shapes differentiation, morphogenesis, and tumorigenesis. In consequence, tumorigenesis is a complex, unpredictable process driven by the interplay between self-organisation and selection.
A toolkit for analyzing nonlinear dynamic stochastic models easily
Uhlig, H.F.H.V.S.
1995-01-01
Often, researchers wish to analyze nonlinear dynamic discrete-time stochastic models. This paper provides a toolkit for solving such models easily, building on log-linearizing the necessary equations characterizing the equilibrium and solving for the recursive equilibrium law of motion with the meth
On Local Homogeneity and Stochastically Ordered Mixed Rasch Models
Kreiner, Svend; Hansen, Mogens; Hansen, Carsten Rosenberg
2006-01-01
Mixed Rasch models add latent classes to conventional Rasch models, assuming that the Rasch model applies within each class and that relative difficulties of items are different in two or more latent classes. This article considers a family of stochastically ordered mixed Rasch models, with ordinal latent classes characterized by increasing total…
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.
Liu, Na; Yu, Peiqiang
2010-07-14
Barley varieties have similar chemical composition but exhibit different rumen degradation kinetics and nutrient availability. These biological differences may be related to molecular, structural, and chemical makeup among the seed endosperm tissue. No detailed study was carried out. The objectives of this study were: (1) to use a molecular spectroscopy technique, synchrotron-based Fourier transform infrared microspectroscopy (SFTIRM), to determine the microchemical-structural features in seed endosperm tissue of six developed barley varieties; (2) to study the relationship among molecular-structural characteristics, degradation kinetics, and nutrient availability in six genotypes of barley. The results showed that inherent microchemical-structural differences in the endosperm among the six barley varieties were detected by the synchrotron-based analytical technique, SFTIRM, with the univariate molecular spectral analysis. The SFTIRM spectral profiles differed (P degradation). Weak correlations may indicate that limited variations of these six barley varieties might not be sufficient to interpret the relationship between spectroscopic information and the nutrient value of barley grain, although significant differences in biodegradation kinetics were observed. In conclusion, the studies demonstrated the potential of ultraspatially resolved synchrotron based technology (SFTIRM) to reveal the structural and chemical makeup within cellular and subcellular dimensions without destruction of the inherent structure of cereal grain tissue.
Edman, R M; Linger, R J; Belikoff, E J; Li, F; Sze, S-H; Tarone, A M; Scott, M J
2015-02-01
The New World screwworm fly, Cochliomyia hominivorax, and the Australian sheep blow fly, Lucilia cuprina, are major pests of livestock. The sterile insect technique was used to eradicate C. hominivorax from North and Central America. This involved area-wide releases of male and female flies that had been sterilized by radiation. Genetic systems have been developed for making 'male-only' strains that would improve the efficiency of genetic control of insect pests. One system involves induction of female lethality in embryos through activation of a pro-apoptotic gene by the tetracycline-dependent transactivator. Sex-specific expression is achieved using an intron from the transformer gene, which we previously isolated from several calliphorids. In the present study, we report the isolation of the promoters from the C. hominivorax slam and Lucilia sericata bnk cellularization genes and show that these promoters can drive expression of a GFP reporter gene in early embryos of transgenic L. cuprina. Additionally, we report the isolation of the L. sericata pro-apoptotic hid and rpr genes, identify conserved motifs in the encoded proteins and determine the relative expression of these genes at different stages of development. We show that widespread expression of the L. sericata pro-apoptotic genes was lethal in Drosophila melanogaster. The isolated gene promoters and pro-apoptotic genes could potentially be used to build transgenic embryonic sexing strains of calliphorid livestock pests.
Lupo, Vincenzo; Pascual-Pascual, Samuel I; Sancho, Paula; Calpena, Eduardo; Gutiérrez-Molina, Manuel; Mateo-Martínez, Gonzalo; Espinós, Carmen; Arriola-Pereda, Gema
2015-10-01
Early-onset hereditary motor and sensory neuropathies are rare diseases representing a broad clinical and genetic spectrum. Without a notable familial history, the clinical diagnosis is complicated because acquired causes of peripheral neuropathy, such as inflammatory neuropathies, neuropathies with toxic causes, and nutritional deficiencies, must be considered. We examined the clinical, electrophysiological, and pathologic manifestations of a boy with an initial diagnosis of chronic inflammatory demyelinating polyneuropathy. The progression of the disease despite treatment led to a suspicion of hereditary motor and sensory neuropathy. Genetic testing revealed the presence of the MPZ p.D90E mutation in heterozygosis. To clarify the pathogenicity of this mutation and achieve a conclusive diagnosis, we investigated the MPZ p.D90E mutation through in silico and cellular approaches. This study broadens the clinical phenotype of hereditary motor and sensory neuropathy due to MPZ mutation and emphasises the difficulty of achieving an accurate genetic diagnosis in a sporadic patient to provide an appropriate pharmacologic treatment.
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.
Wang, Shuai; Li, Feng; Quan, Enxi; Dong, Dong; Wu, Baojian
2016-04-01
Resveratrol undergoes extensive metabolism to form biologically active glucuronides in humans. However, the transport mechanisms for resveratrol glucuronides are not fully established. Here, we aimed to characterize the efflux transport of resveratrol glucuronides using UGT1A1-overexpressing HeLa cells (HeLa1A1 cells), and to determine the contribution of multidrug resistance-associated protein (MRP) 4 to cellular excretion of the glucuronides. Two glucuronide isomers [i.e., resveratrol 3-O-glucuronide (R3G) and resveratrol 4'-O-glucuronide (R4'G)] were excreted into the extracellular compartment after incubation of resveratrol (1-100 μM) with HeLa1A1 cells. The excretion rate was linearly related to the level of intracellular glucuronide, indicating that glucuronide efflux was a nonsaturable process. MK-571 (a dual inhibitor of UGT1A1 and MRPs) significantly decreased the excretion rates of R3G and R4'G while increasing their intracellular levels. Likewise, short-hairpin RNA (shRNA)-mediated silencing of MRP4 caused a significant reduction in glucuronide excretion but an elevation in glucuronide accumulation. Furthermore, β-glucuronidase expressed in the cells catalyzed the hydrolysis of the glucuronides back to the parent compound. A cellular pharmacokinetic model integrating resveratrol transport/metabolism with glucuronide hydrolysis/excretion was well fitted to the experimental data, allowing derivation of the efflux rate constant values in the absence or presence of shRNA targeting MRP4. It was found that a large percentage of glucuronide excretion (43%-46%) was attributed to MRP4. In conclusion, MRP4 participated in cellular excretion of R3G and R4'G. Integration of mechanistic pharmacokinetic modeling with transporter knockdown was a useful method to derive the contribution percentage of an exporter to overall glucuronide excretion.
Bosch, H.G.P.; Samuel, L.G.; Mullender, S.J.; Polakos, P.; Rittenhouse, G.
2007-01-01
Traditionally, cellular systems have been built in a hierarchical manner: many specialized cellular access network elements that collectively form a hierarchical cellular system. When 2G and later 3G systems were designed there was a good reason to make system hierarchical: from a cost-perspective i
A Note on Almost Stochastic Dominance
Guo, Xu; Zhu, Xuehu; Wong, Wing-Keung; Zhu, Lixing
2013-01-01
To satisfy the property of expected-utility maximization, Tzeng et al. (2012) modify the almost second-degree stochastic dominance proposed by Leshno and Levy (2002) and define almost higher-degree stochastic dominance. In this note, we further investigate the relevant properties. We define an almost third-degree stochastic dominance in the same way that Leshno and Levy (2002) define second-degree stochastic dominance and show that Leshno and Levy's (2002) almost stochastic dominance has t...
Computer Auxiliary Analysis for Stochasticity of Chaos
Institute of Scientific and Technical Information of China (English)
ZHAOGeng; FANGJin-qing
2003-01-01
In this work, we propose a mathematics-physical statistic analytical method for stochastic process of chaos, based on stochastic test via combination measurement of Monobit and Runs. Computer auxiliary analysis shows that it is of stochasticity for stochastic number produced from the chaotic circuit. Our software is written by VB and C++, the later can be tested by the former, and at the same time it is verified by stochastic number produced by the computer. So the data treatment results are reliable.
Cellular fiber–reinforced concrete
Isachenko S.; Kodzoev M.
2016-01-01
Methods disperse reinforcement of concrete matrix using polypropylene, glass, basalt and metal fibers allows to make the construction of complex configuration, solve the problem of frost products. Dispersed reinforcement reduces the overall weight of the structures. The fiber replaces the secondary reinforcement, reducing the volume of use of structural steel reinforcement. Cellular Fiber concretes are characterized by high-performance properties, especially increased bending strength and...
CELLULAR INTERACTIONS MEDIATED BY GLYCONECTIDS
Popescu, O.; Sumanovski, L. T.; I. Checiu; Elisabeta Popescu; G. N. Misevic
1999-01-01
Cellular interactions involve many types of cell surface molecules and operate via homophilic and/or heterophilic protein-protein and protein-carbohydrate binding. Our investigations in different model-systems (marine invertebrates and mammals) have provided direct evidence that a novel class of primordial proteoglycans, named by us gliconectins, can mediate cell adhesion via a new alternative molecular mechanism of polyvalent carbohydrate-carbohydrate binding. Biochemical characterization of...
Multi-cellular logistics of collective cell migration.
Directory of Open Access Journals (Sweden)
Masataka Yamao
Full Text Available During development, the formation of biological networks (such as organs and neuronal networks is controlled by multicellular transportation phenomena based on cell migration. In multi-cellular systems, cellular locomotion is restricted by physical interactions with other cells in a crowded space, similar to passengers pushing others out of their way on a packed train. The motion of individual cells is intrinsically stochastic and may be viewed as a type of random walk. However, this walk takes place in a noisy environment because the cell interacts with its randomly moving neighbors. Despite this randomness and complexity, development is highly orchestrated and precisely regulated, following genetic (and even epigenetic blueprints. Although individual cell migration has long been studied, the manner in which stochasticity affects multi-cellular transportation within the precisely controlled process of development remains largely unknown. To explore the general principles underlying multicellular migration, we focus on the migration of neural crest cells, which migrate collectively and form streams. We introduce a mechanical model of multi-cellular migration. Simulations based on the model show that the migration mode depends on the relative strengths of the noise from migratory and non-migratory cells. Strong noise from migratory cells and weak noise from surrounding cells causes "collective migration," whereas strong noise from non-migratory cells causes "dispersive migration." Moreover, our theoretical analyses reveal that migratory cells attract each other over long distances, even without direct mechanical contacts. This effective interaction depends on the stochasticity of the migratory and non-migratory cells. On the basis of these findings, we propose that stochastic behavior at the single-cell level works effectively and precisely to achieve collective migration in multi-cellular systems.
Wang, J F; Olson, M E; Reno, C R; Wright, J B; Hart, D A
2001-08-01
A pig model of wound healing was developed by excision of 2-cm-diameter full thickness skin in young Yorkshire pigs. The results indicated that wound re-epithelialization in this animal model took an average of 20 days. Analysis of cellular change was assessed by use of DNA quantification and determination of apoptotic cells in tissue sections. The results indicate that RNA and DNA contents paralleled each other throughout the healing process, and observed changes in the pattern of RNA and DNA content of the scar tissues were consistent with cell loss due to apoptosis in this model. Expression of mRNA for relevant genes was assessed by use of semiquantitative reverse transcription-polymerase chain reaction (RT-PCR) analysis, using porcine specific primer sets and RNA isolated from normal skin and specimens obtained at various times after wounding. The mRNA values for tumor necrosis factor-alpha (TNF-alpha), connective tissue growth factor (CTGF), insulin-like growth factor II (IGF-II), and decorin were significantly high at specific times after wounding, but mRNA values for the transcription factors (c-fos and c-jun) were significantly decreased. Quantitative bacteriologic results indicated that the total bacterial count in this animal model reached 10(9) colony-forming units (CFU)/g, with the highest value at post-wounding day 7, and Pseudomonas aeruginosa and Staphylocococci aureus were the most common bacteria detected in this model. Further definition of this model should identify unique points in the healing process, and such information could lead to development of therapeutic interventions to improve skin wound healing.
Bayram-Weston, Zubeyde; Torres, Eduardo M; Jones, Lesley; Dunnett, Stephen B; Brooks, Simon P
2012-06-01
Huntington's disease is an autosomal dominant, progressive neurodegenerative disease in which a single mutation in the gene responsible for the protein huntingtin leads to a primarily striatal and cortical neuronal loss, resulting progressive motor, cognitive and psychiatric disability and ultimately death. The mutation induces an abnormal protein accumulation within cells, although the precise role of this accumulation in the disease process is unknown. Several animal models have been created to model the disease. In the present study, the pathology of the Hdh(CAG(150)) mouse model was analyzed longitudinally over 24 months. At 5 months of age, the mutant N-terminal antibody S830 found dense nuclear staining and nuclear inclusions in the olfactory tubercle and striatum of the Hdh(Q150/Q150) mice. Nuclear inclusions increased in number and size with age and disease progression, and spread in ventral to dorsal, and anterior to posterior pattern. Electron microscopy observations at 14 months of age revealed that the neurons showed a normal nucleus having a circular shape and regular membranes in a densely packed cytoplasm, whereas by 21 months the cytoplasm was vacuolated and contained swollen mitochondria with many degenerated cytoplasmic organelles. Immunogold labelling of the S830 antibody was found to be specifically localised to the inner area of the neuronal intra-nuclear inclusions. Our data demonstrate a marked and progressive cellular phenotype that begins at 5 months of age and progresses with time. The pathology the Hdh(Q150/Q150) line was focused on the striatum and cortex until the late stage of the disease, consistent with the human condition.
Cabrillana, María E; Monclus, María A; Sáez Lancellotti, Tania E; Boarelli, Paola V; Clementi, Marisa A; Vincenti, Amanda E; Yunes, Roberto F M; Fornés, Miguel W
2011-09-01
Mammalian sperm proteins undergo thiol group (SH) oxidation to form disulfides bonds (SS) as they travel through the epididymis during cell maturation. Disulfide bonds are involved in chromatin condensation and tail organelle stabilization. In this work, we used a fluorescent thiol-selective labeling agent, monobromobimane (mBBr), to study the protein thiol status of rat sperm during maturation. Fluorescence signal decrease along the epididymal trip, more evidently in the head, but also in the tail, indicates that both sub cellular regions participate in the thiol changes. The sources of the fluorescence signal are sulfhydryls sperm proteins labeled by mBBr (mBBr-spp). Initial attempts to identify the mBBr-spp labeled were detected in the initial-caput, but not in the distal cauda-segment of the epididymis in sodium dodecyl sulfate (SDS)-PAGE analysis. This phenomenon could be due to protein resistance to solubilization. For this reason, disulfide bond reduction was accomplished by sodium dodecyl sulfate plus dithiothreitol treatment to recover the mBBr signal in SDS-PAGE. Under this protocol, a major 27 kDa protein band displays a strong signal. Protein identification by mass spectrometry and sequence database searching correlated this protein with the outer dense fiber 1 (ODF1). The mBBr specifically bound to N-terminal domain cysteine of ODF1. The mBBr reduces rat sperm motility, quantitatively and qualitatively, and the effects are dose dependent, without significantly increasing the percentage of dead sperm. Thus, we found that ODF1 is highly responsible for mBBr fluorescence detection in the sperm tail, and the motility inhibition by the fluorescence marker indicates that ODF1 N-terminal domain are related to sperm motility. © 2011 Wiley-Liss, Inc.
Li, Pan; Zhou, Junhui; Huang, Pingsheng; Zhang, Chuangnian; Wang, Weiwei; Li, Chen; Kong, Deling
2017-01-01
Antigen uptake by dendritic cells (DCs) is a key step for initiating antigen-specific T cell immunity. In the present study, novel synthetic polymeric nanoparticles were prepared as antigen delivery vehicles to improve the antigen uptake by DCs. Well-defined cationic and acid-responsive copolymers, monomethoxy poly(ethylene glycol)-block-poly(2-(diisopropyl amino) ethyl methacrylate)-block-poly(2-(guanidyl) ethyl methacrylate) (mPEG-b-PDPA-b-PGEM, PEDG) were synthesized by reversible addition-fragmentation chain transfer polymerization of 2-(diisopropylamino)ethyl methacrylate) and N-(tert-butoxycarbonyl) amino ethyl methacrylate monomers, followed by deprotection of tert-butyl protective groups and guanidinylation of obtained primary amines. 1H NMR, 13C NMR and GPC results indicated the successful synthesis of well-defined PEDG copolymers. PEDG copolymers could self-assemble into nanoparticles in aqueous solution, which were of cationic surface charges and showed acid-triggered disassembly contributed by PGEM and PDPA moieties, respectively. Significantly, PEDG nanoparticles could effectively condense with negatively charged model antigen ovalbumin (OVA) to form OVA/PEDG nanoparticle formulations with no influence on its secondary and tertiary structures demonstrating by far-UV circular dichroism and UV–vis spectra. In vitro antigen cellular uptake by bone marrow DCs (BMDCs) indicated using PEDG nanoparticles as antigen delivery vehicles could significantly improve the antigen uptake efficiency of OVA compared with free OVA or the commercialized Alum adjuvant. Moreover, as the surface cationic charges of OVA/PEDG nanoparticle formulations reduced, the uptake efficiency decreased correspondingly. Collectively, our work suggests that guanidinylated, cationic and acid-responsive PEDG nanoparticles represent a new kind of promising antigen delivery vehicle to DCs and hold great potential to serve as immunoadjuvants in the development of vaccines. PMID:28149525
Stochastic Climate Theory and Modelling
Franzke, Christian L E; Berner, Judith; Williams, Paul D; Lucarini, Valerio
2014-01-01
Stochastic methods are a crucial area in contemporary climate research and are increasingly being used in comprehensive weather and climate prediction models as well as reduced order climate models. Stochastic methods are used as subgrid-scale parameterizations as well as for model error representation, uncertainty quantification, data assimilation and ensemble prediction. The need to use stochastic approaches in weather and climate models arises because we still cannot resolve all necessary processes and scales in comprehensive numerical weather and climate prediction models. In many practical applications one is mainly interested in the largest and potentially predictable scales and not necessarily in the small and fast scales. For instance, reduced order models can simulate and predict large scale modes. Statistical mechanics and dynamical systems theory suggest that in reduced order models the impact of unresolved degrees of freedom can be represented by suitable combinations of deterministic and stochast...
Stochastic Modelling of Hydrologic Systems
DEFF Research Database (Denmark)
Jonsdottir, Harpa
2007-01-01
In this PhD project several stochastic modelling methods are studied and applied on various subjects in hydrology. The research was prepared at Informatics and Mathematical Modelling at the Technical University of Denmark. The thesis is divided into two parts. The first part contains an introduct......In this PhD project several stochastic modelling methods are studied and applied on various subjects in hydrology. The research was prepared at Informatics and Mathematical Modelling at the Technical University of Denmark. The thesis is divided into two parts. The first part contains...... an introduction and an overview of the papers published. Then an introduction to basic concepts in hydrology along with a description of hydrological data is given. Finally an introduction to stochastic modelling is given. The second part contains the research papers. In the research papers the stochastic methods...
Stochastic Still Water Response Model
DEFF Research Database (Denmark)
Friis-Hansen, Peter; Ditlevsen, Ove Dalager
2002-01-01
In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model...... is to establish the stochastic load field conditional on a given draft and trim of the vessel. The model contributes to a realistic modelling of the stochastic load processes to be used in a reliability evaluation of the ship hull. Emphasis is given to container vessels. The formulation of the model for obtaining...... the stochastic cargo container load field is based on a queuing and loading policy that assumes containers are handled by a first-come-first-serve policy. The load field is assumed to be Gaussian. The ballast system is imposed to counteract the angle of heel and to regulate both the draft and the trim caused...
Stochastic roots of growth phenomena
De Lauro, E.; De Martino, S.; De Siena, S.; Giorno, V.
2014-05-01
We show that the Gompertz equation describes the evolution in time of the median of a geometric stochastic process. Therefore, we induce that the process itself generates the growth. This result allows us further to exploit a stochastic variational principle to take account of self-regulation of growth through feedback of relative density variations. The conceptually well defined framework so introduced shows its usefulness by suggesting a form of control of growth by exploiting external actions.
Stochastic Analysis and Related Topics
Ustunel, Ali
1988-01-01
The Silvri Workshop was divided into a short summer school and a working conference, producing lectures and research papers on recent developments in stochastic analysis on Wiener space. The topics treated in the lectures relate to the Malliavin calculus, the Skorohod integral and nonlinear functionals of white noise. Most of the research papers are applications of these subjects. This volume addresses researchers and graduate students in stochastic processes and theoretical physics.
Steganalysis of stochastic modulation steganography
Institute of Scientific and Technical Information of China (English)
HE Junhui; HUANG Jiwu
2006-01-01
Stochastic modulation steganography embeds secret message within the cover image by adding stego-noise with a specific probabilistic distribution. No method is known to be applicable to the estimation of stochastic modulation steganography. By analyzing the distributions of the horizontal pixel difference of images before and after stochastic modulation embedding, we present a new steganalytic approach to accurately estimate the length of secret message in stochastic modulation steganography. The proposed method first establishes a model describing the statistical relationship among the differences of the cover image, stego-image and stego-noise. In the case of stego- image-only steganalysis, rough estimate of the distributional parameters of the cover image's pixel difference is obtained with the use of the provided stego-image. And grid search and Chi-square goodness of fit test are exploited to estimate the length of the secret message embedded with stochastic modulation steganography. The experimental results demonstrate that our new approach is effective for steganalyzing stochastic modulation steganography and accurately estimating the length of the secret message.
Directory of Open Access Journals (Sweden)
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.
Energy Technology Data Exchange (ETDEWEB)
Schmitz, O.
2006-07-15
For a detailed study of the plasma structure and the transport characteristics of a stochastized plasma edge at the tokamak TEXTOR the dynamic ergodic divertor (DED) was constructed, by which differently shaped external disturbing fields are statically and dynamically generated. Aim of this thgesis is to study experimentally the radial and poloidal structure of the plasma edge stochastized by the DED disturbing field and to analyze its transport characteristics. For this spatially highly resolved radial profiles of the electron density and temperature were measured by means of radiation-emission spectroscopy on thermal helium at the high- and low-field side of TEXTOR. These experimental results yield a good stating base for the validation and further development of three-dimensional transport codes.
Mechanisms of Stochastic Diffusion of Energetic Ions in Spherical Tori
Energy Technology Data Exchange (ETDEWEB)
Ya.I. Kolesnichenko; R.B. White; Yu.V. Yakovenko
2001-01-18
Stochastic diffusion of the energetic ions in spherical tori is considered. The following issues are addressed: (I) Goldston-White-Boozer diffusion in a rippled field; (ii) cyclotron-resonance-induced diffusion caused by the ripple; (iii) effects of non-conservation of the magnetic moment in an axisymmetric field. It is found that the stochastic diffusion in spherical tori with a weak magnetic field has a number of peculiarities in comparison with conventional tokamaks; in particular, it is characterized by an increased role of mechanisms associated with non-conservation of the particle magnetic moment. It is concluded that in current experiments on National Spherical Torus eXperiment (NSTX) the stochastic diffusion does not have a considerable influence on the confinement of energetic ions.
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...
AA, stochastic precooling kicker
1980-01-01
The freshly injected antiprotons were subjected to fast stochastic "precooling", while a shutter shielded the deeply cooled antiproton stack from the violent action of the precooling kicker. In this picture, the injection orbit is to the left, the stack orbit to the far right, the separating shutter is in open position. After several seconds of precooling (in momentum and in the vertical plane), the shutter was opened briefly, so that by means of RF the precooled antiprotons could be transferred to the stack tail, where they were subjected to further cooling in momentum and both transverse planes, until they ended up, deeply cooled, in the stack core. The fast shutter, which had to open and close in a fraction of a second was an essential item of the cooling scheme and a mechanical masterpiece. Here the shutter is in the open position. The precooling pickups were of the same design, with the difference that the kickers had cooling circuits and the pickups not. 8401150 shows a precooling pickup with the shutte...
Energy Technology Data Exchange (ETDEWEB)
Brennan J. M.; Blaskiewicz, M.; Mernick, K.
2012-05-20
The full 6-dimensional [x,x'; y,y'; z,z'] stochastic cooling system for RHIC was completed and operational for the FY12 Uranium-Uranium collider run. Cooling enhances the integrated luminosity of the Uranium collisions by a factor of 5, primarily by reducing the transverse emittances but also by cooling in the longitudinal plane to preserve the bunch length. The components have been deployed incrementally over the past several runs, beginning with longitudinal cooling, then cooling in the vertical planes but multiplexed between the Yellow and Blue rings, next cooling both rings simultaneously in vertical (the horizontal plane was cooled by betatron coupling), and now simultaneous horizontal cooling has been commissioned. The system operated between 5 and 9 GHz and with 3 x 10{sup 8} Uranium ions per bunch and produces a cooling half-time of approximately 20 minutes. The ultimate emittance is determined by the balance between cooling and emittance growth from Intra-Beam Scattering. Specific details of the apparatus and mathematical techniques for calculating its performance have been published elsewhere. Here we report on: the method of operation, results with beam, and comparison of results to simulations.
Adaptation in stochastic environments
Clark, Colib
1993-01-01
The classical theory of natural selection, as developed by Fisher, Haldane, and 'Wright, and their followers, is in a sense a statistical theory. By and large the classical theory assumes that the underlying environment in which evolution transpires is both constant and stable - the theory is in this sense deterministic. In reality, on the other hand, nature is almost always changing and unstable. We do not yet possess a complete theory of natural selection in stochastic environ ments. Perhaps it has been thought that such a theory is unimportant, or that it would be too difficult. Our own view is that the time is now ripe for the development of a probabilistic theory of natural selection. The present volume is an attempt to provide an elementary introduction to this probabilistic theory. Each author was asked to con tribute a simple, basic introduction to his or her specialty, including lively discussions and speculation. We hope that the book contributes further to the understanding of the roles of "Cha...
Stacking with Stochastic Cooling
Caspers, Friedhelm
2004-01-01
Accumulation of large stacks of antiprotons or ions with the aid of stochastic cooling is more delicate than cooling a constant intensity beam. Basically the difficulty stems from the fact that the optimized gain and the cooling rate are inversely proportional to the number of particles seen by the cooling system. Therefore, to maintain fast stacking, the newly injected batch has to be strongly protected from the Schottky noise of the stack. Vice versa the stack has to be efficiently shielded against the high gain cooling system for the injected beam. In the antiproton accumulators with stacking ratios up to 105, the problem is solved by radial separation of the injection and the stack orbits in a region of large dispersion. An array of several tapered cooling systems with a matched gain profile provides a continuous particle flux towards the high-density stack core. Shielding of the different systems from each other is obtained both through the spatial separation and via the revolution frequencies (filters)....
Turbulence and Stochastic Processes
Celani, Antonio; Mazzino, Andrea; Pumir, Alain
sec:08-1In 1931 the monograph Analytical Methods in Probability Theory appeared, in which A.N. Kolmogorov laid the foundations for the modern theory of Markov processes [1]. According to Gnedenko: "In the history of probability theory it is difficult to find other works that changed the established points of view and basic trends in research work in such a decisive way". Ten years later, his article on fully developed turbulence provided the framework within which most, if not all, of the subsequent theoretical investigations have been conducted [2] (see e.g. the review by Biferale et al. in this volume [3]. Remarkably, the greatest advances made in the last few years towards a thorough understanding of turbulence developed from the successful marriage between the theory of stochastic processes and the phenomenology of turbulent transport of scalar fields. In this article we will summarize these recent developments which expose the direct link between the intermittency of transported fields and the statistical properties of particle trajectories advected by the turbulent flow (see also [4], and, for a more thorough review, [5]. We also discuss the perspectives of the Lagrangian approach beyond passive scalars, especially for the modeling of hydrodynamic turbulence.
Tensor methods for parameter estimation and bifurcation analysis of stochastic reaction networks.
Liao, Shuohao; Vejchodský, Tomáš; Erban, Radek
2015-07-06
Stochastic modelling of gene regulatory networks provides an indispensable tool for understanding how random events at the molecular level influence cellular functions. A common challenge of stochastic models is to calibrate a large number of model parameters against the experimental data. Another difficulty is to study how the behaviour of a stochastic model depends on its parameters, i.e. whether a change in model parameters can lead to a significant qualitative change in model behaviour (bifurcation). In this paper, tensor-structured parametric analysis (TPA) is developed to address these computational challenges. It is based on recently proposed low-parametric tensor-structured representations of classical matrices and vectors. This approach enables simultaneous computation of the model properties for all parameter values within a parameter space. The TPA is illustrated by studying the parameter estimation, robustness, sensitivity and bifurcation structure in stochastic models of biochemical networks. A Matlab implementation of the TPA is available at http://www.stobifan.org.
Stochastic reduced order models for inverse problems under uncertainty.
Warner, James E; Aquino, Wilkins; Grigoriu, Mircea D
2015-03-01
This work presents a novel methodology for solving inverse problems under uncertainty using stochastic reduced order models (SROMs). Given statistical information about an observed state variable in a system, unknown parameters are estimated probabilistically through the solution of a model-constrained, stochastic optimization problem. The point of departure and crux of the proposed framework is the representation of a random quantity using a SROM - a low dimensional, discrete approximation to a continuous random element that permits e cient and non-intrusive stochastic computations. Characterizing the uncertainties with SROMs transforms the stochastic optimization problem into a deterministic one. The non-intrusive nature of SROMs facilitates e cient gradient computations for random vector unknowns and relies entirely on calls to existing deterministic solvers. Furthermore, the method is naturally extended to handle multiple sources of uncertainty in cases where state variable data, system parameters, and boundary conditions are all considered random. The new and widely-applicable SROM framework is formulated for a general stochastic optimization problem in terms of an abstract objective function and constraining model. For demonstration purposes, however, we study its performance in the specific case of inverse identification of random material parameters in elastodynamics. We demonstrate the ability to efficiently recover random shear moduli given material displacement statistics as input data. We also show that the approach remains effective for the case where the loading in the problem is random as well.
Segmentation of stochastic images with a stochastic random walker method.
Pätz, Torben; Preusser, Tobias
2012-05-01
We present an extension of the random walker segmentation to images with uncertain gray values. Such gray-value uncertainty may result from noise or other imaging artifacts or more general from measurement errors in the image acquisition process. The purpose is to quantify the influence of the gray-value uncertainty onto the result when using random walker segmentation. In random walker segmentation, a weighted graph is built from the image, where the edge weights depend on the image gradient between the pixels. For given seed regions, the probability is evaluated for a random walk on this graph starting at a pixel to end in one of the seed regions. Here, we extend this method to images with uncertain gray values. To this end, we consider the pixel values to be random variables (RVs), thus introducing the notion of stochastic images. We end up with stochastic weights for the graph in random walker segmentation and a stochastic partial differential equation (PDE) that has to be solved. We discretize the RVs and the stochastic PDE by the method of generalized polynomial chaos, combining the recent developments in numerical methods for the discretization of stochastic PDEs and an interactive segmentation algorithm. The resulting algorithm allows for the detection of regions where the segmentation result is highly influenced by the uncertain pixel values. Thus, it gives a reliability estimate for the resulting segmentation, and it furthermore allows determining the probability density function of the segmented object volume.
Automatic identification of model reductions for discrete stochastic simulation
Wu, Sheng; Fu, Jin; Li, Hong; Petzold, Linda
2012-07-01
Multiple time scales in cellular chemical reaction systems present a challenge for the efficiency of stochastic simulation. Numerous model reductions have been proposed to accelerate the simulation of chemically reacting systems by exploiting time scale separation. However, these are often identified and deployed manually, requiring expert knowledge. This is time-consuming, prone to error, and opportunities for model reduction may be missed, particularly for large models. We propose an automatic model analysis algorithm using an adaptively weighted Petri net to dynamically identify opportunities for model reductions for both the stochastic simulation algorithm and tau-leaping simulation, with no requirement of expert knowledge input. Results are presented to demonstrate the utility and effectiveness of this approach.
Modelling the SOS Response by Semi-Stochastic Simulation
Institute of Scientific and Technical Information of China (English)
NI Ming; WANG Si-Yuan; OUYANG Qi
2008-01-01
The SOS (save our soul) response induced by DNA damage in bacteria E coli has raised a great interests in biophysics and has been extensively studied. Previously we have developed a stochastic simulation model to explain the oscillatory-like modulation of SOS gene expression observed in experiment. Here we present an improved semi-stochastic model which has higher simulation efficiency, taking into account the updated knowledge about SOS response. The improved model suggests that frequency of the modulation is controlled by the negative feedback in the system. DNA polymerase V, the key enzyme for error-prone translesion synthesis during SOS response, plays a major role in closing up the negative feedback. It is also indicated that the correlation between the modulation and cellular growth observed in experiment is due to DNA damage induced slowing down of transcription and translation.
Cellular neurothekeoma with melanocytosis.
Wu, Ren-Chin; Hsieh, Yi-Yueh; Chang, Yi-Chin; Kuo, Tseng-Tong
2008-02-01
Cellular neurothekeoma (CNT) is a benign dermal tumor mainly affecting the head and neck and the upper extremities. It is characterized histologically by interconnecting fascicles of plump spindle or epithelioid cells with ample cytoplasm infiltrating in the reticular dermis. The histogenesis of CNT has been controversial, although it is generally regarded as an immature counterpart of classic/myxoid neurothekeoma, a tumor with nerve sheath differentiation. Two rare cases of CNT containing melanin-laden cells were described. Immunohistochemical study with NKI/C3, vimentin, epithelial membrane antigen, smooth muscle antigen, CD34, factor XIIIa, collagen type IV, S100 protein and HMB-45 was performed. Both cases showed typical growth pattern of CNT with interconnecting fascicles of epithelioid cells infiltrating in collagenous stroma. One of the nodules contained areas exhibiting atypical cytological features. Melanin-laden epithelioid or dendritic cells were diffusely scattered throughout one nodule, and focally present in the peripheral portion of the other nodule. Both nodules were strongly immunoreactive to NKI/C3 and vimentin, but negative to all the other markers employed. CNT harboring melanin-laden cells may pose diagnostic problems because of their close resemblance to nevomelanocytic lesions and other dermal mesenchymal tumors. These peculiar cases may also provide further clues to the histogenesis of CNT.
Crociara, Paola; Parolisi, Roberta; Conte, Daniele; Fumagalli, Marta; Bonfanti, Luca
2013-01-01
Although extremely interesting in adult neuro-glio-genesis and promising as an endogenous source for repair, parenchymal progenitors remain largely obscure in their identity and physiology, due to a scarce availability of stage-specific markers. What appears difficult is the distinction between real cell populations and various differentiation stages of the same population. Here we focused on a subset of multipolar, polydendrocyte-like cells (mMap5 cells) expressing the microtubule associated protein 5 (Map5), which is known to be present in most neurons. We characterized the morphology, phenotype, regional distribution, proliferative dynamics, and stage-specific marker expression of these cells in the rabbit and mouse CNS, also assessing their existence in other mammalian species. mMap5 cells were never found to co-express the Ng2 antigen. They appear to be a population of glial cells sharing features but also differences with Ng2+progenitor cells. We show that mMap5 cells are newly generated, postmitotic parenchymal elements of the oligodendroglial lineage, thus being a stage-specific population of polydendrocytes. Finally, we report that the number of mMap5 cells, although reduced within the brain of adult/old animals, can increase in neurodegenerative and traumatic conditions.
A Stochastic Collocation Algorithm for Uncertainty Analysis
Mathelin, Lionel; Hussaini, M. Yousuff; Zang, Thomas A. (Technical Monitor)
2003-01-01
This report describes a stochastic collocation method to adequately handle a physically intrinsic uncertainty in the variables of a numerical simulation. For instance, while the standard Galerkin approach to Polynomial Chaos requires multi-dimensional summations over the stochastic basis functions, the stochastic collocation method enables to collapse those summations to a one-dimensional summation only. This report furnishes the essential algorithmic details of the new stochastic collocation method and provides as a numerical example the solution of the Riemann problem with the stochastic collocation method used for the discretization of the stochastic parameters.
Stability Analysis for Stochastic Optimization Problems
Institute of Scientific and Technical Information of China (English)
无
2007-01-01
Stochastic optimization offers a means of considering the objectives and constrains with stochastic parameters. However, it is generally difficult to solve the stochastic optimization problem by employing conventional methods for nonlinear programming when the number of random variables involved is very large. Neural network models and algorithms were applied to solve the stochastic optimization problem on the basis of the stability theory. Stability for stochastic programs was discussed. If random vector sequence converges to the random vector in the original problem in distribution, the optimal value of the corresponding approximation problems converges to the optimal value of the original stochastic optimization problem.
General N-th Degree Stochastic Dominance
Institute of Scientific and Technical Information of China (English)
张顺明
2001-01-01
This paper examines N-th degree stochastic dominance which isused to compare the risk factor of risky assets after summarizing the definitions of first degree stochastic dominance and second degree stochastic dominance. The paper defines general N-th degree stochastic dominance, presents a sufficient and necessary condition which is the equivalent theorem of general N-th degree stochastic dominance. The feasible utility form is constructed to explain the economic meaning of N-th degree stochastic dominance in the field of financial economics. The equivalent condition is described by the probability distribution functions of risky assets, which are not related to utility functions (preference relations).
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 ...
Stochastic multiscale modeling of polycrystalline materials
Wen, Bin
Mechanical properties of engineering materials are sensitive to the underlying random microstructure. Quantification of mechanical property variability induced by microstructure variation is essential for the prediction of extreme properties and microstructure-sensitive design of materials. Recent advances in high throughput characterization of polycrystalline microstructures have resulted in huge data sets of microstructural descriptors and image snapshots. To utilize these large scale experimental data for computing the resulting variability of macroscopic properties, appropriate mathematical representation of microstructures is needed. By exploring the space containing all admissible microstructures that are statistically similar to the available data, one can estimate the distribution/envelope of possible properties by employing efficient stochastic simulation methodologies along with robust physics-based deterministic simulators. The focus of this thesis is on the construction of low-dimensional representations of random microstructures and the development of efficient physics-based simulators for polycrystalline materials. By adopting appropriate stochastic methods, such as Monte Carlo and Adaptive Sparse Grid Collocation methods, the variability of microstructure-sensitive properties of polycrystalline materials is investigated. The primary outcomes of this thesis include: (1) Development of data-driven reduced-order representations of microstructure variations to construct the admissible space of random polycrystalline microstructures. (2) Development of accurate and efficient physics-based simulators for the estimation of material properties based on mesoscale microstructures. (3) Investigating property variability of polycrystalline materials using efficient stochastic simulation methods in combination with the above two developments. The uncertainty quantification framework developed in this work integrates information science and materials science, and
MIMO Cellular Networks with Simultaneous Wireless Information and Power Transfer
2016-01-01
International audience; In this paper, we introduce a mathematical approach for system-level analysis and optimization of densely deployed multiple-antenna cellular networks, where low-energy devices are capable of decoding information data and harvesting power simultaneously. The base stations are assumed to be deployed according to a Poisson point process and tools from stochastic geometry are exploited to quantify the trade-off in terms of information rate and harvested power. It is shown ...
Stochastic models: theory and simulation.
Energy Technology Data Exchange (ETDEWEB)
Field, Richard V., Jr.
2008-03-01
Many problems in applied science and engineering involve physical phenomena that behave randomly in time and/or space. Examples are diverse and include turbulent flow over an aircraft wing, Earth climatology, material microstructure, and the financial markets. Mathematical models for these random phenomena are referred to as stochastic processes and/or random fields, and Monte Carlo simulation is the only general-purpose tool for solving problems of this type. The use of Monte Carlo simulation requires methods and algorithms to generate samples of the appropriate stochastic model; these samples then become inputs and/or boundary conditions to established deterministic simulation codes. While numerous algorithms and tools currently exist to generate samples of simple random variables and vectors, no cohesive simulation tool yet exists for generating samples of stochastic processes and/or random fields. There are two objectives of this report. First, we provide some theoretical background on stochastic processes and random fields that can be used to model phenomena that are random in space and/or time. Second, we provide simple algorithms that can be used to generate independent samples of general stochastic models. The theory and simulation of random variables and vectors is also reviewed for completeness.
Stochastic simulation in systems biology.
Székely, Tamás; Burrage, Kevin
2014-11-01
Natural systems are, almost by definition, heterogeneous: this can be either a boon or an obstacle to be overcome, depending on the situation. Traditionally, when constructing mathematical models of these systems, heterogeneity has typically been ignored, despite its critical role. However, in recent years, stochastic computational methods have become commonplace in science. They are able to appropriately account for heterogeneity; indeed, they are based around the premise that systems inherently contain at least one source of heterogeneity (namely, intrinsic heterogeneity). In this mini-review, we give a brief introduction to theoretical modelling and simulation in systems biology and discuss the three different sources of heterogeneity in natural systems. Our main topic is an overview of stochastic simulation methods in systems biology. There are many different types of stochastic methods. We focus on one group that has become especially popular in systems biology, biochemistry, chemistry and physics. These discrete-state stochastic methods do not follow individuals over time; rather they track only total populations. They also assume that the volume of interest is spatially homogeneous. We give an overview of these methods, with a discussion of the advantages and disadvantages of each, and suggest when each is more appropriate to use. We also include references to software implementations of them, so that beginners can quickly start using stochastic methods for practical problems of interest.
Etiology and treatment of hematological neoplasms: stochastic mathematical models.
Radivoyevitch, Tomas; Li, Huamin; Sachs, Rainer K
2014-01-01
Leukemias are driven by stemlike cancer cells (SLCC), whose initiation, growth, response to treatment, and posttreatment behavior are often "stochastic", i.e., differ substantially even among very similar patients for reasons not observable with present techniques. We review the probabilistic mathematical methods used to analyze stochastics and give two specific examples. The first example concerns a treatment protocol, e.g., for acute myeloid leukemia (AML), where intermittent cytotoxic drug dosing (e.g., once each weekday) is used with intent to cure. We argue mathematically that, if independent SLCC are growing stochastically during prolonged treatment, then, other things being equal, front-loading doses are more effective for tumor eradication than back loading. We also argue that the interacting SLCC dynamics during treatment is often best modeled by considering SLCC in microenvironmental niches, with SLCC-SLCC interactions occurring only among SLCC within the same niche, and we present a stochastic dynamics formalism, involving "Poissonization," applicable in such situations. Interactions at a distance due to partial control of total cell numbers are also considered. The second half of this chapter concerns chromosomal aberrations, lesions known to cause some leukemias. A specific example is the induction of a Philadelphia chromosome by ionizing radiation, subsequent development of chronic myeloid leukemia (CML), CML treatment, and treatment outcome. This time evolution involves a coordinated sequence of > 10 steps, each stochastic in its own way, at the subatomic, molecular, macromolecular, cellular, tissue, and population scales, with corresponding time scales ranging from picoseconds to decades. We discuss models of these steps and progress in integrating models across scales.
Cellular automaton rules conserving the number of active sites
Boccara, N; Boccara, Nino; Fuks, Henryk
1997-01-01
This paper shows how to determine all the unidimensional two-state cellular automaton rules of a given number of inputs which conserve the number of active sites. These rules have to satisfy a necessary and sufficient condition. If the active sites are viewed as cells occupied by identical particles, these cellular automaton rules represent evolution operators of systems of identical interacting particles whose total number is conserved. Some of these rules, which allow motion in both directions, mimic ensembles of one-dimensional pseudo-random walkers. The corresponding stochastic processes are, however, not Gaussian.
Gene regulation and noise reduction by coupling of stochastic processes
Ramos, Alexandre F.; Hornos, José Eduardo M.; Reinitz, John
2015-02-01
Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.
Stochastic models of cell motility
DEFF Research Database (Denmark)
Gradinaru, Cristian
2012-01-01
Cell motility and migration are central to the development and maintenance of multicellular organisms, and errors during this process can lead to major diseases. Consequently, the mechanisms and phenomenology of cell motility are currently under intense study. In recent years, a new...... interdisciplinary field focusing on the study of biological processes at the nanoscale level, with a range of technological applications in medicine and biological research, has emerged. The work presented in this thesis is at the interface of cell biology, image processing, and stochastic modeling. The stochastic...... models introduced here are based on persistent random motion, which I apply to real-life studies of cell motility on flat and nanostructured surfaces. These models aim to predict the time-dependent position of cell centroids in a stochastic manner, and conversely determine directly from experimental...
Mechanical autonomous stochastic heat engines
Serra-Garcia, Marc; Foehr, Andre; Moleron, Miguel; Lydon, Joseph; Chong, Christopher; Daraio, Chiara; . Team
Stochastic heat engines extract work from the Brownian motion of a set of particles out of equilibrium. So far, experimental demonstrations of stochastic heat engines have required extreme operating conditions or nonautonomous external control systems. In this talk, we will present a simple, purely classical, autonomous stochastic heat engine that uses the well-known tension induced nonlinearity in a string. Our engine operates between two heat baths out of equilibrium, and transfers energy from the hot bath to a work reservoir. This energy transfer occurs even if the work reservoir is at a higher temperature than the hot reservoir. The talk will cover a theoretical investigation and experimental results on a macroscopic setup subject to external noise excitations. This system presents an opportunity for the study of non equilibrium thermodynamics and is an interesting candidate for innovative energy conversion devices.
Principal axes for stochastic dynamics.
Vasconcelos, V V; Raischel, F; Haase, M; Peinke, J; Wächter, M; Lind, P G; Kleinhans, D
2011-09-01
We introduce a general procedure for directly ascertaining how many independent stochastic sources exist in a complex system modeled through a set of coupled Langevin equations of arbitrary dimension. The procedure is based on the computation of the eigenvalues and the corresponding eigenvectors of local diffusion matrices. We demonstrate our algorithm by applying it to two examples of systems showing Hopf bifurcation. We argue that computing the eigenvectors associated to the eigenvalues of the diffusion matrix at local mesh points in the phase space enables one to define vector fields of stochastic eigendirections. In particular, the eigenvector associated to the lowest eigenvalue defines the path of minimum stochastic forcing in phase space, and a transform to a new coordinate system aligned with the eigenvectors can increase the predictability of the system.
Principal axes for stochastic dynamics
Vasconcelos, V V; Haase, M; Peinke, J; Wächter, M; Lind, P G; Kleinhans, D
2011-01-01
We introduce a general procedure for directly ascertaining how many independent stochastic sources exist in a complex system modeled through a set of coupled Langevin equations of arbitrary dimension. The procedure is based on the computation of the eigenvalues and the corresponding eigenvectors of local diffusion matrices. We demonstrate our algorithm by applying it to two examples of systems showing Hopf-bifurcation. We argue that computing the eigenvectors associated to the eigenvalues of the diffusion matrix at local mesh points in the phase space enables one to define vector fields of stochastic eigendirections. In particular, the eigenvector associated to the lowest eigenvalue defines the path of minimum stochastic forcing in phase space, and a transform to a new coordinate system aligned with the eigenvectors can increase the predictability of the system.
Correlation functions in stochastic inflation
Energy Technology Data Exchange (ETDEWEB)
Vennin, Vincent [University of Portsmouth, Institute of Cosmology and Gravitation, Portsmouth (United Kingdom); Starobinsky, Alexei A. [L.D. Landau Institute for Theoretical Physics RAS, Moscow (Russian Federation); Utrecht University, Department of Physics and Astronomy, Institute for Theoretical Physics, Utrecht (Netherlands)
2015-09-15
Combining the stochastic and δ N formalisms, we derive non-perturbative analytical expressions for all correlation functions of scalar perturbations in single-field, slow-roll inflation. The standard, classical formulas are recovered as saddle-point limits of the full results. This yields a classicality criterion that shows that stochastic effects are small only if the potential is sub-Planckian and not too flat. The saddle-point approximation also provides an expansion scheme for calculating stochastic corrections to observable quantities perturbatively in this regime. In the opposite regime, we show that a strong suppression in the power spectrum is generically obtained, and we comment on the physical implications of this effect. (orig.)
Stochastic models for atmospheric dispersion
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
2003-01-01
Simple stochastic differential equation models have been applied by several researchers to describe the dispersion of tracer particles in the planetary atmospheric boundary layer and to form the basis for computer simulations of particle paths. To obtain the drift coefficient, empirical vertical...... positions close to the boundaries. Different rules have been suggested in the literature with justifications based on simulation studies. Herein the relevant stochastic differential equation model is formulated in a particular way. The formulation is based on the marginal transformation of the position...... dependent particle velocity into a position independent Gaussian velocity. Boundary conditions are obtained from Itos rule of stochastic differentiation. The model directly point at a canonical rule of reflection for the approximating random walk with finite time step. This reflection rule is different from...
Applied probability and stochastic processes
Sumita, Ushio
1999-01-01
Applied Probability and Stochastic Processes is an edited work written in honor of Julien Keilson. This volume has attracted a host of scholars in applied probability, who have made major contributions to the field, and have written survey and state-of-the-art papers on a variety of applied probability topics, including, but not limited to: perturbation method, time reversible Markov chains, Poisson processes, Brownian techniques, Bayesian probability, optimal quality control, Markov decision processes, random matrices, queueing theory and a variety of applications of stochastic processes. The book has a mixture of theoretical, algorithmic, and application chapters providing examples of the cutting-edge work that Professor Keilson has done or influenced over the course of his highly-productive and energetic career in applied probability and stochastic processes. The book will be of interest to academic researchers, students, and industrial practitioners who seek to use the mathematics of applied probability i...
Intrinsic optimization using stochastic nanomagnets
Sutton, Brian; Camsari, Kerem Yunus; Behin-Aein, Behtash; Datta, Supriyo
2017-01-01
This paper draws attention to a hardware system which can be engineered so that its intrinsic physics is described by the generalized Ising model and can encode the solution to many important NP-hard problems as its ground state. The basic constituents are stochastic nanomagnets which switch randomly between the ±1 Ising states and can be monitored continuously with standard electronics. Their mutual interactions can be short or long range, and their strengths can be reconfigured as needed to solve specific problems and to anneal the system at room temperature. The natural laws of statistical mechanics guide the network of stochastic nanomagnets at GHz speeds through the collective states with an emphasis on the low energy states that represent optimal solutions. As proof-of-concept, we present simulation results for standard NP-complete examples including a 16-city traveling salesman problem using experimentally benchmarked models for spin-transfer torque driven stochastic nanomagnets. PMID:28295053
Lacksonen, Thomas A.
1994-01-01
Small space flight project design at NASA Langley Research Center goes through a multi-phase process from preliminary analysis to flight operations. The process insures that each system achieves its technical objectives with demonstrated quality and within planned budgets and schedules. A key technical component of early phases is decision analysis, which is a structure procedure for determining the best of a number of feasible concepts based upon project objectives. Feasible system concepts are generated by the designers and analyzed for schedule, cost, risk, and technical measures. Each performance measure value is normalized between the best and worst values and a weighted average score of all measures is calculated for each concept. The concept(s) with the highest scores are retained, while others are eliminated from further analysis. This project automated and enhanced the decision analysis process. Automation of the decision analysis process was done by creating a user-friendly, menu-driven, spreadsheet macro based decision analysis software program. The program contains data entry dialog boxes, automated data and output report generation, and automated output chart generation. The enhancements to the decision analysis process permit stochastic data entry and analysis. Rather than enter single measure values, the designers enter the range and most likely value for each measure and concept. The data can be entered at the system or subsystem level. System level data can be calculated as either sum, maximum, or product functions of the subsystem data. For each concept, the probability distributions are approximated for each measure and the total score for each concept as either constant, triangular, normal, or log-normal distributions. Based on these distributions, formulas are derived for the probability that the concept meets any given constraint, the probability that the concept meets all constraints, and the probability that the concept is within a given
Stacking with stochastic cooling
Energy Technology Data Exchange (ETDEWEB)
Caspers, Fritz E-mail: Fritz.Caspers@cern.ch; Moehl, Dieter
2004-10-11
Accumulation of large stacks of antiprotons or ions with the aid of stochastic cooling is more delicate than cooling a constant intensity beam. Basically the difficulty stems from the fact that the optimized gain and the cooling rate are inversely proportional to the number of particles 'seen' by the cooling system. Therefore, to maintain fast stacking, the newly injected batch has to be strongly 'protected' from the Schottky noise of the stack. Vice versa the stack has to be efficiently 'shielded' against the high gain cooling system for the injected beam. In the antiproton accumulators with stacking ratios up to 10{sup 5} the problem is solved by radial separation of the injection and the stack orbits in a region of large dispersion. An array of several tapered cooling systems with a matched gain profile provides a continuous particle flux towards the high-density stack core. Shielding of the different systems from each other is obtained both through the spatial separation and via the revolution frequencies (filters). In the 'old AA', where the antiproton collection and stacking was done in one single ring, the injected beam was further shielded during cooling by means of a movable shutter. The complexity of these systems is very high. For more modest stacking ratios, one might use azimuthal rather than radial separation of stack and injected beam. Schematically half of the circumference would be used to accept and cool new beam and the remainder to house the stack. Fast gating is then required between the high gain cooling of the injected beam and the low gain stack cooling. RF-gymnastics are used to merge the pre-cooled batch with the stack, to re-create free space for the next injection, and to capture the new batch. This scheme is less demanding for the storage ring lattice, but at the expense of some reduction in stacking rate. The talk reviews the 'radial' separation schemes and also gives some
When greediness fails: examples from stochastic scheduling
Uetz, Marc
2003-01-01
The purpose of this paper is to present examples for the sometimes surprisingly different behavior of deterministic and stochastic scheduling problems. In particular, it demonstrates some seemingly counterintuitive properties of optimal scheduling policies for stochastic machine scheduling problems.
Transport properties of stochastic Lorentz models
Beijeren, H. van
1982-01-01
Diffusion processes are considered for one-dimensional stochastic Lorentz models, consisting of randomly distributed fixed scatterers and one moving light particle. In waiting time Lorentz models the light particle makes instantaneous jumps between scatterers after a stochastically distributed waiti
A stochastic description of Dictyostelium chemotaxis.
Directory of Open Access Journals (Sweden)
Gabriel Amselem
Full Text Available Chemotaxis, the directed motion of a cell toward a chemical source, plays a key role in many essential biological processes. Here, we derive a statistical model that quantitatively describes the chemotactic motion of eukaryotic cells in a chemical gradient. Our model is based on observations of the chemotactic motion of the social ameba Dictyostelium discoideum, a model organism for eukaryotic chemotaxis. A large number of cell trajectories in stationary, linear chemoattractant gradients is measured, using microfluidic tools in combination with automated cell tracking. We describe the directional motion as the interplay between deterministic and stochastic contributions based on a Langevin equation. The functional form of this equation is directly extracted from experimental data by angle-resolved conditional averages. It contains quadratic deterministic damping and multiplicative noise. In the presence of an external gradient, the deterministic part shows a clear angular dependence that takes the form of a force pointing in gradient direction. With increasing gradient steepness, this force passes through a maximum that coincides with maxima in both speed and directionality of the cells. The stochastic part, on the other hand, does not depend on the orientation of the directional cue and remains independent of the gradient magnitude. Numerical simulations of our probabilistic model yield quantitative agreement with the experimental distribution functions. Thus our model captures well the dynamics of chemotactic cells and can serve to quantify differences and similarities of different chemotactic eukaryotes. Finally, on the basis of our model, we can characterize the heterogeneity within a population of chemotactic cells.
Stochastic model for tumor growth with immunization
Bose, Thomas; Trimper, Steffen
2009-05-01
We analyze a stochastic model for tumor cell growth with both multiplicative and additive colored noises as well as nonzero cross correlations in between. Whereas the death rate within the logistic model is altered by a deterministic term characterizing immunization, the birth rate is assumed to be stochastically changed due to biological motivated growth processes leading to a multiplicative internal noise. Moreover, the system is subjected to an external additive noise which mimics the influence of the environment of the tumor. The stationary probability distribution Ps is derived depending on the finite correlation time, the immunization rate, and the strength of the cross correlation. Ps offers a maximum which becomes more pronounced for increasing immunization rate. The mean-first-passage time is also calculated in order to find out under which conditions the tumor can suffer extinction. Its characteristics are again controlled by the degree of immunization and the strength of the cross correlation. The behavior observed can be interpreted in terms of a biological model of tumor evolution.
Stochastic geometry and its applications
Chiu, Sung Nok; Kendall, Wilfrid S; Mecke, Joseph
2013-01-01
An extensive update to a classic text Stochastic geometry and spatial statistics play a fundamental role in many modern branches of physics, materials sciences, engineering, biology and environmental sciences. They offer successful models for the description of random two- and three-dimensional micro and macro structures and statistical methods for their analysis. The previous edition of this book has served as the key reference in its field for over 18 years and is regarded as the best treatment of the subject of stochastic geometry, both as a subject with vital a
Schwinger Mechanism with Stochastic Quantization
Fukushima, Kenji
2014-01-01
We prescribe a formulation of the particle production with real-time Stochastic Quantization. To construct the retarded and the time-ordered propagators we decompose the stochastic variables into positive- and negative-energy parts. In this way we demonstrate how to derive the Schwinger mechanism under a time-dependent electric field. We also discuss a physical interpretation with help of numerical simulations and develop an analogue to the one-dimensional scattering with the non-relativistic Schroedinger equation. We can then reformulate the Schwinger mechanism as the high-energy quantum reflection problem rather than tunneling.
Algebraic and stochastic coding theory
Kythe, Dave K
2012-01-01
Using a simple yet rigorous approach, Algebraic and Stochastic Coding Theory makes the subject of coding theory easy to understand for readers with a thorough knowledge of digital arithmetic, Boolean and modern algebra, and probability theory. It explains the underlying principles of coding theory and offers a clear, detailed description of each code. More advanced readers will appreciate its coverage of recent developments in coding theory and stochastic processes. After a brief review of coding history and Boolean algebra, the book introduces linear codes, including Hamming and Golay codes.
Stochastic and infinite dimensional analysis
Carpio-Bernido, Maria; Grothaus, Martin; Kuna, Tobias; Oliveira, Maria; Silva, José
2016-01-01
This volume presents a collection of papers covering applications from a wide range of systems with infinitely many degrees of freedom studied using techniques from stochastic and infinite dimensional analysis, e.g. Feynman path integrals, the statistical mechanics of polymer chains, complex networks, and quantum field theory. Systems of infinitely many degrees of freedom create their particular mathematical challenges which have been addressed by different mathematical theories, namely in the theories of stochastic processes, Malliavin calculus, and especially white noise analysis. These proceedings are inspired by a conference held on the occasion of Prof. Ludwig Streit’s 75th birthday and celebrate his pioneering and ongoing work in these fields.
Stochastic geometry for image analysis
Descombes, Xavier
2013-01-01
This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Numerous applications, covering remote sensing images, biological and medical imaging, are detailed. This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.
Stochastic vehicle routing with recourse
DEFF Research Database (Denmark)
Gørtz, Inge Li; Nagarajan, Viswanath; Saket, Rishi
2012-01-01
We study the classic Vehicle Routing Problem in the setting of stochastic optimization with recourse. StochVRP is a two-stage problem, where demand is satisfied using two routes: fixed and recourse. The fixed route is computed using only a demand distribution. Then after observing the demand...... instantiations, a recourse route is computed - but costs here become more expensive by a factor λ. We present an O(log2n ·log(nλ))-approximation algorithm for this stochastic routing problem, under arbitrary distributions. The main idea in this result is relating StochVRP to a special case of submodular...
Stochastic methods in quantum mechanics
Gudder, Stanley P
2005-01-01
Practical developments in such fields as optical coherence, communication engineering, and laser technology have developed from the applications of stochastic methods. This introductory survey offers a broad view of some of the most useful stochastic methods and techniques in quantum physics, functional analysis, probability theory, communications, and electrical engineering. Starting with a history of quantum mechanics, it examines both the quantum logic approach and the operational approach, with explorations of random fields and quantum field theory.The text assumes a basic knowledge of fun
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.
Stochastic epidemic models: a survey
Britton, Tom
2009-01-01
This paper is a survey paper on stochastic epidemic models. A simple stochastic epidemic model is defined and exact and asymptotic model properties (relying on a large community) are presented. The purpose of modelling is illustrated by studying effects of vaccination and also in terms of inference procedures for important parameters, such as the basic reproduction number and the critical vaccination coverage. Several generalizations towards realism, e.g. multitype and household epidemic models, are also presented, as is a model for endemic diseases.
Three-dimensional stochastic seepage field for embankment engineering
Institute of Scientific and Technical Information of China (English)
Ya-jun WANG; Wo-hua ZHANG; Chang-yu WU; Da-chun REN
2009-01-01
Owing to the complexity of get-engineering seepage problems influenced by different random factors, three-dimensional simulation and analysis of the stochastic seepage field plays an important role in engineering applications. A three-dimensional anisotropic heterogeneous steady random seepage model was developed on the basis of the finite element method. A statistical analysis of the distribution characteristics of soil parameters sampled from the main embankment of the Yangtze River in the Southern Jingzhou zone of China was conducted. The Kolomogorov-Smimov test verified the statistical hypothesis that the permeability coefficient tensor has a Gaussian distribution. With the help of numerical analysis of the stochastic seepage field using the developed model, various statistical and random characteristics of the stochastic seepage field of the main embankment of the Yangtze River in the Southern Jingzhou zone of China were investigated. The model was also examined with statistical testing. Through the introduction of random variation of the upstream and downstream water levels into the model, the effects of the boundary randomness due to variation of the downstream and upstream water levels on the variation of simulated results presented with a vector series of the random seepage field were analyzed. Furthermore, the combined influence of the variation of the soil permeability coefficient and such seepage resistance measures as the cut-off wall and relief ditch on the hydraulic head distribution was analyzed and compared with the results obtained by determinate analysis. Meanwhile, sensitivities of the hydraulic gradient and downstream exit height to the variation of boundary water level were studied. The validity of the simulated results was verified by stochastic testing and measured data. The developed model provides more detail and a full stochastic algorithm to characterize and analyze three-dimensional stochastic seepage field problems.
Transport in a stochastic magnetic field
Energy Technology Data Exchange (ETDEWEB)
White, R.B.; Wu, Yanlin [Princeton Univ., NJ (United States). Plasma Physics Lab.; Rax, J.M. [Association Euratom-CEA, Centre d`Etudes Nucleaires de Cadarache, 13 -Saint-Paul-lez-Durance (France). Dept. de Recherches sur la Fusion Controlee
1992-09-01
Collisional heat transport in a stochastic magnetic field configuration is investigated. Well above stochastic threshold, a numerical solution of a Chirikov-Taylor model shows a short-time nonlocal regime, but at large time the Rechester-Rosenbluth effective diffusion is confirmed. Near stochastic threshold, subdiffusive behavior is observed for short mean free paths. The nature of this subdiffusive behavior is understood in terms of the spectrum of islands in the stochastic sea.
Transport in a stochastic magnetic field
Energy Technology Data Exchange (ETDEWEB)
White, R.B.; Wu, Yanlin (Princeton Univ., NJ (United States). Plasma Physics Lab.); Rax, J.M. (Association Euratom-CEA, Centre d' Etudes Nucleaires de Cadarache, 13 -Saint-Paul-lez-Durance (France). Dept. de Recherches sur la Fusion Controlee)
1992-01-01
Collisional heat transport in a stochastic magnetic field configuration is investigated. Well above stochastic threshold, a numerical solution of a Chirikov-Taylor model shows a short-time nonlocal regime, but at large time the Rechester-Rosenbluth effective diffusion is confirmed. Near stochastic threshold, subdiffusive behavior is observed for short mean free paths. The nature of this subdiffusive behavior is understood in terms of the spectrum of islands in the stochastic sea.
Exact Algorithms for Solving Stochastic Games
DEFF Research Database (Denmark)
Hansen, Kristoffer Arnsfelt; Koucky, Michal; Lauritzen, Niels;
2012-01-01
Shapley's discounted stochastic games, Everett's recursive games and Gillette's undiscounted stochastic games are classical models of game theory describing two-player zero-sum games of potentially infinite duration. We describe algorithms for exactly solving these games.......Shapley's discounted stochastic games, Everett's recursive games and Gillette's undiscounted stochastic games are classical models of game theory describing two-player zero-sum games of potentially infinite duration. We describe algorithms for exactly solving these games....
Stochastic modeling and analysis of telecoms networks
Decreusefond, Laurent
2012-01-01
This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an
Observability Estimate for Stochastic Schroedinger Equations
2012-01-01
In this paper, we establish a boundary observability estimate for stochastic Schr\\"{o}dinger equations by means of the global Carleman estimate. Our Carleman estimate is based on a new fundamental identity for a stochastic Schr\\"{o}dinger-like operator. Applications to the state observation problem for semilinear stochastic Schr\\"{o}dinger equations and the unique continuation problem for stochastic Schr\\"{o}dinger equations are also addressed.
Stochastic Model Checking of the Stochastic Quality Calculus
DEFF Research Database (Denmark)
Nielson, Flemming; Nielson, Hanne Riis; Zeng, Kebin
2015-01-01
The Quality Calculus uses quality binders for input to express strategies for continuing the computation even when the desired input has not been received. The Stochastic Quality Calculus adds generally distributed delays for output actions and real-time constraints on the quality binders for input...
Stochastic modeling of p53-regulated apoptosis upon radiation damage
Bhatt, Divesh; Bahar, Ivet
2011-01-01
We develop and study the evolution of a model of radiation induced apoptosis in cells using stochastic simulations, and identified key protein targets for effective mitigation of radiation damage. We identified several key proteins associated with cellular apoptosis using an extensive literature survey. In particular, we focus on the p53 transcription dependent and p53 transcription independent pathways for mitochondrial apoptosis. Our model reproduces known p53 oscillations following radiation damage. The key, experimentally testable hypotheses that we generate are - inhibition of PUMA is an effective strategy for mitigation of radiation damage if the treatment is administered immediately, at later stages following radiation damage, inhibition of tBid is more effective.
Michta, Mariusz
2017-02-01
In the paper we study properties of solutions to stochastic differential inclusions and set-valued stochastic differential equations with respect to semimartingale integrators. We present new connections between their solutions. In particular, we show that attainable sets of solutions to stochastic inclusions are subsets of values of multivalued solutions of certain set-valued stochastic equations. We also show that every solution to stochastic inclusion is a continuous selection of a multivalued solution of an associated set-valued stochastic equation. The results obtained in the paper generalize results dealing with this topic known both in deterministic and stochastic cases.
Symmetry reduction for stochastic hybrid systems
Bujorianu, L.M.; Katoen, J.P.
2009-01-01
This paper is focused on adapting symmetry reduction, a technique that is highly successful in traditional model checking, to stochastic hybrid systems. We first show that performability analysis of stochastic hybrid systems can be reduced to a stochastic reachability analysis (SRA). Then, we genera
Symmetry Reduction For Stochastic Hybrid Systems
Bujorianu, L.M.; Katoen, J.P.
2008-01-01
This paper is focused on adapting symmetry reduction, a technique that is highly successful in traditional model checking, to stochastic hybrid systems. To that end, we first show that performability analysis of stochastic hybrid systems can be reduced to a stochastic reachability analysis (SRA). Th
Stochastic Programming with Simple Integer Recourse
Louveaux, François V.; van der Vlerk, Maarten H.
1993-01-01
Stochastic integer programs are notoriously difficult. Very few properties are known and solution algorithms are very scarce. In this paper, we introduce the class of stochastic programs with simple integer recourse, a natural extension of the simple recourse case extensively studied in stochastic c
Symmetrized solutions for nonlinear stochastic differential equations
Directory of Open Access Journals (Sweden)
G. Adomian
1981-01-01
Full Text Available Solutions of nonlinear stochastic differential equations in series form can be put into convenient symmetrized forms which are easily calculable. This paper investigates such forms for polynomial nonlinearities, i.e., equations of the form Ly+ym=x where x is a stochastic process and L is a linear stochastic operator.
Variational principles for stochastic soliton dynamics.
Holm, Darryl D; Tyranowski, Tomasz M
2016-03-01
We develop a variational method of deriving stochastic partial differential equations whose solutions follow the flow of a stochastic vector field. As an example in one spatial dimension, we numerically simulate singular solutions (peakons) of the stochastically perturbed Camassa-Holm (CH) equation derived using this method. These numerical simulations show that peakon soliton solutions of the stochastically perturbed CH equation persist and provide an interesting laboratory for investigating the sensitivity and accuracy of adding stochasticity to finite dimensional solutions of stochastic partial differential equations. In particular, some choices of stochastic perturbations of the peakon dynamics by Wiener noise (canonical Hamiltonian stochastic deformations, CH-SD) allow peakons to interpenetrate and exchange order on the real line in overtaking collisions, although this behaviour does not occur for other choices of stochastic perturbations which preserve the Euler-Poincaré structure of the CH equation (parametric stochastic deformations, P-SD), and it also does not occur for peakon solutions of the unperturbed deterministic CH equation. The discussion raises issues about the science of stochastic deformations of finite-dimensional approximations of evolutionary partial differential equation and the sensitivity of the resulting solutions to the choices made in stochastic modelling.
Directory of Open Access Journals (Sweden)
Yan Che
2012-01-01
Full Text Available The estimation problem is investigated for a class of stochastic nonlinear systems with distributed time-varying delays and missing measurements. The considered distributed time-varying delays, stochastic nonlinearities, and missing measurements are modeled in random ways governed by Bernoulli stochastic variables. The discussed nonlinearities are expressed by the statistical means. By using the linear matrix inequality method, a sufficient condition is established to guarantee the mean-square stability of the estimation error, and then the estimator parameters are characterized by the solution to a set of LMIs. Finally, a simulation example is exploited to show the effectiveness of the proposed design procedures.
Heterogeneous ice nucleation: exploring the transition from stochastic to singular freezing behavior
Directory of Open Access Journals (Sweden)
D. Niedermeier
2011-08-01
Full Text Available Heterogeneous ice nucleation, a primary pathway for ice formation in the atmosphere, has been described alternately as being stochastic, in direct analogy with homogeneous nucleation, or singular, with ice nuclei initiating freezing at deterministic temperatures. We present an idealized, conceptual model to explore the transition between stochastic and singular ice nucleation. This "soccer ball" model treats particles as being covered with surface sites (patches of finite area characterized by different nucleation barriers, but with each surface site following the stochastic nature of ice embryo formation. The model provides a phenomenological explanation for seemingly contradictory experimental results obtained in our research groups. Even with ice nucleation treated fundamentally as a stochastic process this process can be masked by the heterogeneity of surface properties, as might be typical for realistic atmospheric particle populations. Full evaluation of the model findings will require experiments with well characterized ice nucleating particles and the ability to vary both temperature and waiting time for freezing.
A Real Space Cellular Automaton Laboratory (ReSCAL) to analyze complex geophysical systems
Rozier, O.; Narteau, C.
2012-04-01
The Real Space Cellular Automaton Laboratory (ReSCAL) is a generator of 3D multiphysics, markovian and stochastic cellular automata with continuous time. The objective of this new software released under a GNU licence is to develop interdisciplinary research collaboration to investigate the dynamics of complex geophysical systems. In a vast majority of cases, a numerical model is a set of physical variables (temperature, pressure, velocity, etc...) that are recalculated over time according to some predetermined rules or equations. Then, any point in space is entirely characterized by a local set of parameters. This is not the case in ReSCAL where the only local variable is a state-parameter that represent the different phases involved in the problem. An elementary cell represent a given volume of real-space. Pairs of nearest neighbour cells are called doublet. For each individual physical process that we take into account, there is a set of doublet transitions. Using this approach we can model a wide range of physical-chemical or anthropological processes. Here, we present different ingredients of ReSCAL using published applications in geosciences (Narteau et al. 2001 and 2009). We also show how ReSCAL can be developped and used across many displines in geophysics and physical geography. Supplementary informations: Sources files of ReSCAL can be download on http://www.ipgp.fr/~rozier/ReSCAL/rescal-en.html
Network Analysis with Stochastic Grammars
2015-09-17
hypotheses. In practice, association rarely identifies the specific offending element, but focuses the investigation by reducing the suspect pool [73...J. Young , “The estimation of stochastic context-free grammars using the Inside-Outside algorithm,” Comput. Speech Lang., vol. 4, no. 1, pp. 35– 56
Stochastic Processes in Epidemic Theory
Lefèvre, Claude; Picard, Philippe
1990-01-01
This collection of papers gives a representative cross-selectional view of recent developments in the field. After a survey paper by C. Lefèvre, 17 other research papers look at stochastic modeling of epidemics, both from a theoretical and a statistical point of view. Some look more specifically at a particular disease such as AIDS, malaria, schistosomiasis and diabetes.
Model checking mobile stochastic logic.
De Nicola, Rocco; Katoen, Joost-Pieter; Latella, Diego; Loreti, Michele; Massink, Mieke
2007-01-01
The Temporal Mobile Stochastic Logic (MOSL) has been introduced in previous work by the authors for formulating properties of systems specified in STOKLAIM, a Markovian extension of KLAIM. The main purpose of MOSL is to address key functional aspects of global computing such as distribution awarenes
Stochastic Subspace Modelling of Turbulence
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Pedersen, B. J.; Nielsen, Søren R.K.
2009-01-01
Turbulence of the incoming wind field is of paramount importance to the dynamic response of civil engineering structures. Hence reliable stochastic models of the turbulence should be available from which time series can be generated for dynamic response and structural safety analysis. In the paper...
Stochastic-field cavitation model
Energy Technology Data Exchange (ETDEWEB)
Dumond, J., E-mail: julien.dumond@areva.com [AREVA Nuclear Professional School, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, D-76344 Eggenstein-Leopoldshafen (Germany); AREVA GmbH, Erlangen, Paul-Gossen-Strasse 100, D-91052 Erlangen (Germany); Magagnato, F. [Institute of Fluid Mechanics, Karlsruhe Institute of Technology, Kaiserstrasse 12, D-76131 Karlsruhe (Germany); Class, A. [AREVA Nuclear Professional School, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, D-76344 Eggenstein-Leopoldshafen (Germany); Institute for Nuclear and Energy Technologies, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, D-76344 Eggenstein-Leopoldshafen (Germany)
2013-07-15
Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian “particles” or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations.
Stochastic-field cavitation model
Dumond, J.; Magagnato, F.; Class, A.
2013-07-01
Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian "particles" or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations.
Stochastic Modelling of Energy Systems
DEFF Research Database (Denmark)
Andersen, Klaus Kaae
2001-01-01
equations are expressed in terms of stochastic differential equations. From a theoretical viewpoint the techniques for experimental design, parameter estimation and model validation are considered. From the practical viewpoint emphasis is put on how this methods can be used to construct models adequate...
Stochastic Modelling of River Geometry
DEFF Research Database (Denmark)
Sørensen, John Dalsgaard; Schaarup-Jensen, K.
1996-01-01
Numerical hydrodynamic river models are used in a large number of applications to estimate critical events for rivers. These estimates are subject to a number of uncertainties. In this paper, the problem to evaluate these estimates using probabilistic methods is considered. Stochastic models...
The bicriterion stochastic knapsack problem
DEFF Research Database (Denmark)
Andersen, Kim Allan
We discuss the bicriterion stochastic knapsack problem. It is described as follows. We have a known capacity of some resource, and a finite set of projects. Each project requires some units of the resource which is not known in advance, but given by a discrete probability distribution with a finite...
Stochastic Volatility and DSGE Models
DEFF Research Database (Denmark)
Andreasen, Martin Møller
This paper argues that a specification of stochastic volatility commonly used to analyze the Great Moderation in DSGE models may not be appropriate, because the level of a process with this specification does not have conditional or unconditional moments. This is unfortunate because agents may...
Stochastic resin transfer molding process
Park, M
2016-01-01
We consider one-dimensional and two-dimensional models of stochastic resin transfer molding process, which are formulated as random moving boundary problems. We study their properties, analytically in the one-dimensional case and numerically in the two-dimensional case. We show how variability of time to fill depends on correlation lengths and smoothness of a random permeability field.
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
A Real Space Cellular Automaton Laboratory
Rozier, O.; Narteau, C.
2013-12-01
Investigations in geomorphology may benefit from computer modelling approaches that rely entirely on self-organization principles. In the vast majority of numerical models, instead, points in space are characterised by a variety of physical variables (e.g. sediment transport rate, velocity, temperature) recalculated over time according to some predetermined set of laws. However, there is not always a satisfactory theoretical framework from which we can quantify the overall dynamics of the system. For these reasons, we prefer to concentrate on interaction patterns using a basic cellular automaton modelling framework, the Real Space Cellular Automaton Laboratory (ReSCAL), a powerful and versatile generator of 3D stochastic models. The objective of this software suite released under a GNU license is to develop interdisciplinary research collaboration to investigate the dynamics of complex systems. The models in ReSCAL are essentially constructed from a small number of discrete states distributed on a cellular grid. An elementary cell is a real-space representation of the physical environment and pairs of nearest neighbour cells are called doublets. Each individual physical process is associated with a set of doublet transitions and characteristic transition rates. Using a modular approach, we can simulate and combine a wide range of physical, chemical and/or anthropological processes. Here, we present different ingredients of ReSCAL leading to applications in geomorphology: dune morphodynamics and landscape evolution. We also discuss how ReSCAL can be applied and developed across many disciplines in natural and human sciences.
Accelerated stochastic and hybrid methods for spatial simulations of reaction-diffusion systems
Rossinelli, D; Bayati, B; Koumoutsakos, P.
2008-01-01
Spatial distributions characterize the evolution of reaction-diffusion models of several physical, chemical, and biological systems. We present two novel algorithms for the efficient simulation of these models: Spatial т-Leaping (Sт -Leaping), employing a unified acceleration of the stochastic simulation of reaction and diffusion, and Hybrid т-Leaping (Hт-Leaping), combining a deterministic diffusion approximation with a т-Leaping acceleration of the stochastic reactions. The algorithms are v...
MATHEMATICAL FRAMEWORK FOR THE ANALYSIS OF DYNAMC STOCHASTIC SYSTEMS WITH THE RAVEN CODE
Energy Technology Data Exchange (ETDEWEB)
C. Rabiti; D. Mandelli; J. Cogliati; R. Kinoshita
2013-05-01
RAVEN (Reactor Analysis and Virtual control Environment) is a software code under development at Idaho National Laboratory aimed at performing probabilistic risk assessment and uncertainty quantification using RELAP-7, for which it acts also as a simulation controller. In this paper we will present the equations characterizing a dynamic stochastic system and we will then discuss the behavior of each stochastic term and how it is accounted for in the RAVEN software design. Moreover we will present preliminary results of the implementation.
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...
Stochastic stability properties of jump linear systems
Feng, Xiangbo; Loparo, Kenneth A.; Ji, Yuandong; Chizeck, Howard J.
1992-01-01
Jump linear systems are defined as a family of linear systems with randomly jumping parameters (usually governed by a Markov jump process) and are used to model systems subject to failures or changes in structure. The authors study stochastic stability properties in jump linear systems and the relationship among various moment and sample path stability properties. It is shown that all second moment stability properties are equivalent and are sufficient for almost sure sample path stability, and a testable necessary and sufficient condition for second moment stability is derived. The Lyapunov exponent method for the study of almost sure sample stability is discussed, and a theorem which characterizes the Lyapunov exponents of jump linear systems is presented.
Stochastic evolution in populations of ideas
Nicole, Robin; Sollich, Peter; Galla, Tobias
2017-01-01
It is known that learning of players who interact in a repeated game can be interpreted as an evolutionary process in a population of ideas. These analogies have so far mostly been established in deterministic models, and memory loss in learning has been seen to act similarly to mutation in evolution. We here propose a representation of reinforcement learning as a stochastic process in finite ‘populations of ideas’. The resulting birth-death dynamics has absorbing states and allows for the extinction or fixation of ideas, marking a key difference to mutation-selection processes in finite populations. We characterize the outcome of evolution in populations of ideas for several classes of symmetric and asymmetric games.
Hardware implementation of stochastic spiking neural networks.
Rosselló, Josep L; Canals, Vincent; Morro, Antoni; Oliver, Antoni
2012-08-01
Spiking Neural Networks, the last generation of Artificial Neural Networks, are characterized by its bio-inspired nature and by a higher computational capacity with respect to other neural models. In real biological neurons, stochastic processes represent an important mechanism of neural behavior and are responsible of its special arithmetic capabilities. In this work we present a simple hardware implementation of spiking neurons that considers this probabilistic nature. The advantage of the proposed implementation is that it is fully digital and therefore can be massively implemented in Field Programmable Gate Arrays. The high computational capabilities of the proposed model are demonstrated by the study of both feed-forward and recurrent networks that are able to implement high-speed signal filtering and to solve complex systems of linear equations.
Heterogeneous cellular networks
Hu, Rose Qingyang
2013-01-01
A timely publication providing coverage of radio resource management, mobility management and standardization in heterogeneous cellular networks The topic of heterogeneous cellular networks has gained momentum in industry and the research community, attracting the attention of standardization bodies such as 3GPP LTE and IEEE 802.16j, whose objectives are looking into increasing the capacity and coverage of the cellular networks. This book focuses on recent progresses, covering the related topics including scenarios of heterogeneous network deployment, interference management i
Energy Technology Data Exchange (ETDEWEB)
Regulus, P
2006-10-15
Deoxyribonucleic acid (DNA) contains the genetic information and chemical injury to this macromolecule may have severe biological consequences. We report here the detection of 4 new radiation-induced DNA lesions by using a high-performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS/MS) approach. For that purpose, the characteristic fragmentation of most 2'-deoxy-ribo nucleosides, the loss of 116 Da corresponding to the loss of the 2-deoxyribose moiety, was used in the so-called neutral loss mode of the HPLC-MS/MS. One of the newly detected lesions, named dCyd341 because it is a 2'-deoxycytidine modification exhibiting a molecular weight of 341 Da, was also detected in cellular DNA. Characterization of this modified nucleoside was performed using NMR and exact mass determination of the product obtained by chemical synthesis. A mechanism of formation was then proposed, in which the first event is the H-abstraction at the C4 position of a 2-deoxyribose moiety. Then, the sugar modification produced exhibits a reactive aldehyde that, through reaction with a vicinal cytosine base, gives rise to dCyd341. dCyd341 could be considered as a complex damage since its formation involves a DNA strand break and a cross-link between a damaged sugar residue and a vicinal cytosine base located most probably on the complementary DNA strand. In addition to its characterization, preliminary biological studies revealed that cells are able to remove the lesion from DNA. Repair studies have revealed the ability of cells to excise the lesion. Identification of the repair systems involved could represent an interesting challenge. (author)
Deepika, Nancherla; Kumar, Yata Praveen; Shobha Devi, Chittimalli; Reddy, Putta Venkat; Srishailam, Avudoddi; Satyanarayana, Sirasani
2013-10-01
Four new ruthenium(II) polypyridyl complexes-[Ru(phen)2(7-F-dppz)](2+) (7-F-dppz is 7-fluorodipyrido[3,2-a:2',3'-c]phenazine, phen is 1,10-phenanthroline), [Ru(bpy)2(7-F-dppz)](2+)(2) (bpy is 2,2'-bipyridine), [Ru(dmb)2(7-F-dppz)](2+) (dmb is 4,4'-dimethyl-2,2'-bipyridine), and [Ru(hdpa)2(7-F-dppz)](2+) (hdpa is 2,2'-dipyridylamine)-have been synthesized and characterized. Their DNA binding behavior has been explored by various spectroscopic titrations and viscosity measurements, which indicated that all the complexes bind to calf thymus DNA by means of intercalation with different binding strengths. The light switching properties of these complexes have been evaluated, and their antimicrobial activities have been investigated. Photoinduced DNA cleavage studies have been performed. All the complexes exhibited efficient photocleavage of pBR322 DNA on irradiation. The cytotoxicity of these complexes has been evaluated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay with various tumor cell lines. Cellular uptake was studied by flow cytometry and confocal microscopy. Flow cytometry experiments showed that these complexes induced apoptosis of HeLa cell lines.
Research on nonlinear stochastic dynamical price model
Energy Technology Data Exchange (ETDEWEB)
Li Jiaorui [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); School of Statistics, Xi' an University of Finance and Economics, Xi' an 710061 (China)], E-mail: jiaoruili@mail.nwpu.edu.cn; Xu Wei; Xie Wenxian; Ren Zhengzheng [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)
2008-09-15
In consideration of many uncertain factors existing in economic system, nonlinear stochastic dynamical price model which is subjected to Gaussian white noise excitation is proposed based on deterministic model. One-dimensional averaged Ito stochastic differential equation for the model is derived by using the stochastic averaging method, and applied to investigate the stability of the trivial solution and the first-passage failure of the stochastic price model. The stochastic price model and the methods presented in this paper are verified by numerical studies.
Stochastic averaging of quasi-Hamiltonian systems
Institute of Scientific and Technical Information of China (English)
朱位秋
1996-01-01
A stochastic averaging method is proposed for quasi-Hamiltonian systems (Hamiltonian systems with light dampings subject to weakly stochastic excitations). Various versions of the method, depending on whether the associated Hamiltonian systems are integrable or nonintegrable, resonant or nonresonant, are discussed. It is pointed out that the standard stochastic averaging method and the stochastic averaging method of energy envelope are special cases of the stochastic averaging method of quasi-Hamiltonian systems and that the results obtained by this method for several examples prove its effectiveness.
Correlative stochastic optical reconstruction microscopy and electron microscopy.
Directory of Open Access Journals (Sweden)
Doory Kim
Full Text Available Correlative fluorescence light microscopy and electron microscopy allows the imaging of spatial distributions of specific biomolecules in the context of cellular ultrastructure. Recent development of super-resolution fluorescence microscopy allows the location of molecules to be determined with nanometer-scale spatial resolution. However, correlative super-resolution fluorescence microscopy and electron microscopy (EM still remains challenging because the optimal specimen preparation and imaging conditions for super-resolution fluorescence microscopy and EM are often not compatible. Here, we have developed several experiment protocols for correlative stochastic optical reconstruction microscopy (STORM and EM methods, both for un-embedded samples by applying EM-specific sample preparations after STORM imaging and for embedded and sectioned samples by optimizing the fluorescence under EM fixation, staining and embedding conditions. We demonstrated these methods using a variety of cellular targets.
Deterministic and Stochastic Study of Wind Farm Harmonic Currents
DEFF Research Database (Denmark)
Sainz, Luis; Mesas, Juan Jose; Teodorescu, Remus;
2010-01-01
Wind farm harmonic emissions are a well-known power quality problem, but little data based on actual wind farm measurements are available in literature. In this paper, harmonic emissions of an 18 MW wind farm are investigated using extensive measurements, and the deterministic and stochastic...... characterization of wind farm harmonic currents is analyzed. Specific issues addressed in the paper include the harmonic variation with the wind farm operating point and the random characteristics of their magnitude and phase angle....
Stochastic Reachability Analysis of Hybrid Systems
Bujorianu, Luminita Manuela
2012-01-01
Stochastic reachability analysis (SRA) is a method of analyzing the behavior of control systems which mix discrete and continuous dynamics. For probabilistic discrete systems it has been shown to be a practical verification method but for stochastic hybrid systems it can be rather more. As a verification technique SRA can assess the safety and performance of, for example, autonomous systems, robot and aircraft path planning and multi-agent coordination but it can also be used for the adaptive control of such systems. Stochastic Reachability Analysis of Hybrid Systems is a self-contained and accessible introduction to this novel topic in the analysis and development of stochastic hybrid systems. Beginning with the relevant aspects of Markov models and introducing stochastic hybrid systems, the book then moves on to coverage of reachability analysis for stochastic hybrid systems. Following this build up, the core of the text first formally defines the concept of reachability in the stochastic framework and then...
Stochastic Analysis : A Series of Lectures
Dozzi, Marco; Flandoli, Franco; Russo, Francesco
2015-01-01
This book presents in thirteen refereed survey articles an overview of modern activity in stochastic analysis, written by leading international experts. The topics addressed include stochastic fluid dynamics and regularization by noise of deterministic dynamical systems; stochastic partial differential equations driven by Gaussian or Lévy noise, including the relationship between parabolic equations and particle systems, and wave equations in a geometric framework; Malliavin calculus and applications to stochastic numerics; stochastic integration in Banach spaces; porous media-type equations; stochastic deformations of classical mechanics and Feynman integrals and stochastic differential equations with reflection. The articles are based on short courses given at the Centre Interfacultaire Bernoulli of the Ecole Polytechnique Fédérale de Lausanne, Switzerland, from January to June 2012. They offer a valuable resource not only for specialists, but also for other researchers and Ph.D. students in the fields o...
Identification and estimation algorithm for stochastic neural system.
Nakao, M; Hara, K; Kimura, M; Sato, R
1984-01-01
An algorithm for the estimation of stochastic processes in a neural system is presented. This process is defined here as the continuous stochastic process reflecting the dynamics of the neural system which has some inputs and generates output spike trains. The algorithm proposed here is to identify the system parameters and then estimate the stochastic process called neural system process here. These procedures carried out on the basis of the output spike trains which are supposed to be the data observed in the randomly missing way by the threshold time function in the neural system. The algorithm is constructed with the well-known Kalman filters and realizes the estimation of the neural system process by cooperating with the algorithm for the parameter estimation of the threshold time function presented previously (Nakao et al., 1983). The performance of the algorithm is examined by applying it to the various spike trains simulated by some artificial models and also to the neural spike trains recorded in cat's optic tract fibers. The results in these applications are thought to prove the effectiveness of the algorithm proposed here to some extent. Such attempts, we think, will serve to improve the characterizing and modelling techniques of the stochastic neural systems.
Stochastic analysis of Chemical Reaction Networks using Linear Noise Approximation.
Cardelli, Luca; Kwiatkowska, Marta; Laurenti, Luca
2016-11-01
Stochastic evolution of Chemical Reactions Networks (CRNs) over time is usually analyzed through solving the Chemical Master Equation (CME) or performing extensive simulations. Analysing stochasticity is often needed, particularly when some molecules occur in low numbers. Unfortunately, both approaches become infeasible if the system is complex and/or it cannot be ensured that initial populations are small. We develop a probabilistic logic for CRNs that enables stochastic analysis of the evolution of populations of molecular species. We present an approximate model checking algorithm based on the Linear Noise Approximation (LNA) of the CME, whose computational complexity is independent of the population size of each species and polynomial in the number of different species. The algorithm requires the solution of first order polynomial differential equations. We prove that our approach is valid for any CRN close enough to the thermodynamical limit. However, we show on four case studies that it can still provide good approximation even for low molecule counts. Our approach enables rigorous analysis of CRNs that are not analyzable by solving the CME, but are far from the deterministic limit. Moreover, it can be used for a fast approximate stochastic characterization of a CRN.
Nanostructured cellular networks.
Moriarty, P; Taylor, M D R; Brust, M
2002-12-01
Au nanocrystals spin-coated onto silicon from toluene form cellular networks. A quantitative statistical crystallography analysis shows that intercellular correlations drive the networks far from statistical equilibrium. Spin-coating from hexane does not produce cellular structure, yet a strong correlation is retained in the positions of nanocrystal aggregates. Mechanisms based on Marangoni convection alone cannot account for the variety of patterns observed, and we argue that spinodal decomposition plays an important role in foam formation.
The effect of extrinsic noise on cellular decision making
Roberts, Elijah; Assaf, Michael; Luthey-Schulten, Zaida; Goldenfeld, Nigel
2013-03-01
Many cellular processes are not deterministic, i.e., genetically identical cells can display different phenotypic behavior even in identical environments. Such processes involve cellular decision making, in which individual cells randomly make choices determining their fate. One view is that the stochastic nature of cellular decision making is due to noise present in the biomolecular interaction networks. Most previous work has focused on the role of intrinsic noise of these networks. Yet, especially in the high copy-number regime, extrinsic noise may be much more significant, likely governing the overall dynamics. Here we develop a theoretical framework describing the combined effect of intrinsic and extrinsic noise on the stochastic dynamics of genetic switches responsible for cellular decision making. We do so by devising a semi-classical theory accounting for extrinsic noise as an effective species. Our theory, corroborated by extensive Monte-Carlo simulations, is tested on a simple bistable self-regulating gene model, and is then generalized to gain insight on the behavior of the lac genetic switch under extrinsic noise. We show that extrinsic noise not only significantly lowers the escape time from a phenotypic state, but can fundamentally change the actual escape process.
Ruin problems with stochastic premium stochastic return on investments
Institute of Scientific and Technical Information of China (English)
WANG Rongming; XU Lin; YAO Dingjun
2007-01-01
In this paper, ruin problems in the risk model with stochastic premium incomes and stochastic return on investments are studied. The logarithm of the asset price process is assumed to be a Lévy process. An exact expression for expected discounted penalty function is established. Lower bounds and two kinds of upper bounds for expected discounted penalty function are obtained by inductive method and martingale approach. Integro- differential equations for the expected discounted penalty function are ob- tained when the Lévy process is a Brownian motion with positive drift and a compound Poisson process, respectively. Some analytical examples and numerical examples are given to illustrate the upper bounds and the applications of the integro-differential equations in this paper.
Stochastic Movement of Multiple Motor Transported Cargo
Ando, David; Gopinathan, Ajay; Xu, Jing
2015-03-01
Experimental observations of cargo position during transport by multiple motors are determined by several coupled stochastic processes. During collective transport, each motor can transition between multiple kinetic states, with the state of each motor influencing the states of the others via mechanical coupling through a common cargo. We measured the motion of a micron sized bead as it is transported by two kinesin motors along a single microtubule track, focusing on cargo displacements which are both axial and transverse to the microtubule. We model the effects of inter-motor interference and the state of each motor throughout time, and back out motor properties using a systematic comparison of experimental observations with simulated model traces over a wide parameter space. Our model captures a surface-associated mode of kinesin, which is only accessible via inter-motor interference in groups, in which kinesin diffuses along the microtubule surface and rapidly ``hops'' between protofilaments without dissociating from the microtubule. This enhances local exploration of the microtubule surface, possibly enabling cellular cargos to overcome macromolecular crowding and to navigate obstacles along micro- tubule tracks without sacrificing overall travel distance.
City traffic jam relief by stochastic resonance
Castillo, F.; Toledo, B. A.; Muñoz, V.; Rogan, J.; Zarama, R.; Kiwi, M.; Valdivia, J. A.
2014-06-01
We simulate traffic in a city by means of the evolution of a row of interacting cars, using a cellular automaton model, in a sequence of traffic lights synchronized by a "green wave". When our initial condition is a small density jammed state, its evolution shows the expected scaling laws close to the synchronization resonance, with a uniform car density along the street. However, for an initial large density jammed state, we observe density variations along the streets, which results in the breakdown of the scaling laws. This spatial disorder corresponds to a different attractor of the system. As we include velocity perturbations in the dynamics of the cars, all these attractors converge to a statistically equivalent system for all initial jammed densities. However, this emergent state shows a stochastic resonance-like behavior in which the average traffic velocity increases with respect to that of the system without noise, for several initial jammed densities. This result may help in the understanding of dynamics of traffic jams in cities.
Nonlinear and stochastic dynamics in the heart
Energy Technology Data Exchange (ETDEWEB)
Qu, Zhilin, E-mail: zqu@mednet.ucla.edu [Department of Medicine (Cardiology), David Geffen School of Medicine, University of California, Los Angeles, CA 90095 (United States); Hu, Gang [Department of Physics, Beijing Normal University, Beijing 100875 (China); Garfinkel, Alan [Department of Medicine (Cardiology), David Geffen School of Medicine, University of California, Los Angeles, CA 90095 (United States); Department of Integrative Biology and Physiology, University of California, Los Angeles, CA 90095 (United States); Weiss, James N. [Department of Medicine (Cardiology), David Geffen School of Medicine, University of California, Los Angeles, CA 90095 (United States); Department of Physiology, David Geffen School of Medicine, University of California, Los Angeles, CA 90095 (United States)
2014-10-10
In a normal human life span, the heart beats about 2–3 billion times. Under diseased conditions, a heart may lose its normal rhythm and degenerate suddenly into much faster and irregular rhythms, called arrhythmias, which may lead to sudden death. The transition from a normal rhythm to an arrhythmia is a transition from regular electrical wave conduction to irregular or turbulent wave conduction in the heart, and thus this medical problem is also a problem of physics and mathematics. In the last century, clinical, experimental, and theoretical studies have shown that dynamical theories play fundamental roles in understanding the mechanisms of the genesis of the normal heart rhythm as well as lethal arrhythmias. In this article, we summarize in detail the nonlinear and stochastic dynamics occurring in the heart and their links to normal cardiac functions and arrhythmias, providing a holistic view through integrating dynamics from the molecular (microscopic) scale, to the organelle (mesoscopic) scale, to the cellular, tissue, and organ (macroscopic) scales. We discuss what existing problems and challenges are waiting to be solved and how multi-scale mathematical modeling and nonlinear dynamics may be helpful for solving these problems.
Bhatia, Prateek A; Moaddel, Ruin; Wainer, Irving W
2010-06-15
CMAC (cellular membrane affinity chromatography columns) have been developed for the study of the human multidrug transporters MRP1, MRP2 and the breast cancer resistance protein (BCRP). The columns were constructed using the immobilized artificial membrane (IAM) stationary phase and cellular membrane fragments obtained from Spodoptera frugiperda (Sf9) cells that had been stably transfected with human Mrp1, Mrp2 or Bcrp cDNA, using a baculovirus expression system. The resulting CMAC(Sf9(MRP1)), CMAC(Sf9(MRP2)) and CMAC(Sf9(BCRP)) columns and a control column produced using membrane fragments from non-transfected Sf9 cells, CMAC(Sf9), were characterized using frontal affinity chromatography using [(3)H]-etoposide as the marker ligand and etoposide, benzbromarone and MK571 as the displacers on the CMAC(Sf9(MRP1)) column, etoposide and furosemide on the CMAC(Sf9(MRP2)) column and etoposide and fumitremorgin C on the CMAC(Sf9(BCPR)) column. The binding affinities (K(i) values) obtained from the chromatographic studies were consistent with the data obtained using non-chromatographic techniques and the results indicate that the immobilized MRP1, MRP2 and BCRP transporters retained their ability to selectively bind known ligands. (S)-verapamil displaced [(3)H]-etoposide on the CMAC(Sf9(MRP1)) column to a greater extent than (R)-verapamil and the relative IC(50) values of the enantiomers were calculated using the changes in the retention times of the marker. The observed enantioselectivity and calculated IC(50) values were consistent with previously reported data. The results indicated that the CMAC(Sf9(MRP1)), CMAC(Sf9(MRP2)) and CMAC(Sf9(BCRP)) columns can be used for the study of binding to the MRP1, MRP2 and BCRP transporters and that membranes from the Sf9 cell line can be used to prepare CMAC columns. This is the first example of the use of membranes from a non-mammalian cell line in an affinity chromatographic system.
Molecular and Cellular Basis of Aging
DEFF Research Database (Denmark)
Rattan, Suresh
2016-01-01
KEY FACTS • Signs of biological aging appear progressively and exponentially during the period of survival beyond the ELS of a species. • There are no gerontogenes evolved with a specific function of causing aging and eventual death. • The role of genes in aging and longevity is mainly at the level...... of longevity-assurance in evolutionary terms. • The phenotype of aging is highly differential and heterogeneous at all levels of biological organization. • Aging is characterized by a stochastic occurrence, accumulation, and heterogeneity of damage in macromolecules. • Mild stress-induced activation of defense...
The Urge to Merge: When Cellular Service Providers Pool Capacity
Hua, Sha; Panwar, Shivendra
2011-01-01
As cellular networks are turning into a platform for ubiquitous data access, cellular operators are facing a severe data capacity crisis due to the exponential growth of traffic generated by mobile users. In this work, we investigate the benefits of sharing infrastructure and spectrum among two cellular operators. Specifically, we provide a multi-cell analytical model using stochastic geometry to identify the performance gain under different sharing strategies, which gives tractable and accurate results. To validate the performance using a realistic setting, we conduct extensive simulations for a multi-cell OFDMA system using real base station locations. Both analytical and simulation results show that even a simple cooperation strategy between two similar operators, where they share spectrum and base stations, roughly quadruples capacity as compared to the capacity of a single operator. This is equivalent to doubling the capacity per customer, providing a strong incentive for operators to cooperate, if not a...
Fourier analysis and stochastic processes
Brémaud, Pierre
2014-01-01
This work is unique as it provides a uniform treatment of the Fourier theories of functions (Fourier transforms and series, z-transforms), finite measures (characteristic functions, convergence in distribution), and stochastic processes (including arma series and point processes). It emphasises the links between these three themes. The chapter on the Fourier theory of point processes and signals structured by point processes is a novel addition to the literature on Fourier analysis of stochastic processes. It also connects the theory with recent lines of research such as biological spike signals and ultrawide-band communications. Although the treatment is mathematically rigorous, the convivial style makes the book accessible to a large audience. In particular, it will be interesting to anyone working in electrical engineering and communications, biology (point process signals) and econometrics (arma models). A careful review of the prerequisites (integration and probability theory in the appendix, Hilbert spa...
Stochastic Vehicle Routing with Recourse
Goertz, Inge Li; Saket, Rishi
2012-01-01
We study the classic Vehicle Routing Problem in the setting of stochastic optimization with recourse. StochVRP is a two-stage optimization problem, where demand is satisfied using two routes: fixed and recourse. The fixed route is computed using only a demand distribution. Then after observing the demand instantiations, a recourse route is computed -- but costs here become more expensive by a factor lambda. We present an O(log^2 n log(n lambda))-approximation algorithm for this stochastic routing problem, under arbitrary distributions. The main idea in this result is relating StochVRP to a special case of submodular orienteering, called knapsack rank-function orienteering. We also give a better approximation ratio for knapsack rank-function orienteering than what follows from prior work. Finally, we provide a Unique Games Conjecture based omega(1) hardness of approximation for StochVRP, even on star-like metrics on which our algorithm achieves a logarithmic approximation.
Optical stochastic cooling in Tevatron
Lebedev, V
2012-01-01
Intrabeam scattering is the major mechanism resulting in a growth of beam emittances and fast luminosity degradation in the Tevatron. As a result in the case of optimal collider operation only about 40% of antiprotons are used to the store end and the rest are discarded. Beam cooling is the only effective remedy to increase the particle burn rate and, consequently, the luminosity. Unfortunately neither electron nor stochastic cooling can be effective at the Tevatron energy and bunch density. Thus the optical stochastic cooling (OSC) is the only promising technology capable to cool the Tevatron beam. Possible ways of such cooling implementation in the Tevatron and advances in the OSC cooling theory are discussed in this paper. The technique looks promising and potentially can double the average Tevatron luminosity without increasing its peak value and the antiproton production.
Stochastic Modeling of Soil Salinity
Suweis, S; Van der Zee, S E A T M; Daly, E; Maritan, A; Porporato, A; 10.1029/2010GL042495
2012-01-01
A minimalist stochastic model of primary soil salinity is proposed, in which the rate of soil salinization is determined by the balance between dry and wet salt deposition and the intermittent leaching events caused by rainfall events. The long term probability density functions of salt mass and concentration are found by reducing the coupled soil moisture and salt mass balance equation to a single stochastic differential equation driven by multiplicative Poisson noise. The novel analytical solutions provide insight on the interplay of the main soil, plant and climate parameters responsible for long-term soil salinization. In particular, they show the existence of two distinct regimes, one where the mean salt mass remains nearly constant (or decreases) with increasing rainfall frequency, and another where mean salt content increases markedly with increasing rainfall frequency. As a result, relatively small reductions of rainfall in drier climates may entail dramatic shifts in long-term soil salinization trend...
Stochastic integration and differential equations
Protter, Philip E
2003-01-01
It has been 15 years since the first edition of Stochastic Integration and Differential Equations, A New Approach appeared, and in those years many other texts on the same subject have been published, often with connections to applications, especially mathematical finance. Yet in spite of the apparent simplicity of approach, none of these books has used the functional analytic method of presenting semimartingales and stochastic integration. Thus a 2nd edition seems worthwhile and timely, though it is no longer appropriate to call it "a new approach". The new edition has several significant changes, most prominently the addition of exercises for solution. These are intended to supplement the text, but lemmas needed in a proof are never relegated to the exercises. Many of the exercises have been tested by graduate students at Purdue and Cornell Universities. Chapter 3 has been completely redone, with a new, more intuitive and simultaneously elementary proof of the fundamental Doob-Meyer decomposition theorem, t...
Stochastic problems in population genetics
Maruyama, Takeo
1977-01-01
These are" notes based on courses in Theoretical Population Genetics given at the University of Texas at Houston during the winter quarter, 1974, and at the University of Wisconsin during the fall semester, 1976. These notes explore problems of population genetics and evolution involving stochastic processes. Biological models and various mathematical techniques are discussed. Special emphasis is given to the diffusion method and an attempt is made to emphasize the underlying unity of various problems based on the Kolmogorov backward equation. A particular effort was made to make the subject accessible to biology students who are not familiar with stochastic processes. The references are not exhaustive but were chosen to provide a starting point for the reader interested in pursuing the subject further. Acknowledgement I would like to use this opportunity to express my thanks to Drs. J. F. Crow, M. Nei and W. J. Schull for their hospitality during my stays at their universities. I am indebted to Dr. M. Kimura...
Self-Organising Stochastic Encoders
Luttrell, Stephen
2010-01-01
The processing of mega-dimensional data, such as images, scales linearly with image size only if fixed size processing windows are used. It would be very useful to be able to automate the process of sizing and interconnecting the processing windows. A stochastic encoder that is an extension of the standard Linde-Buzo-Gray vector quantiser, called a stochastic vector quantiser (SVQ), includes this required behaviour amongst its emergent properties, because it automatically splits the input space into statistically independent subspaces, which it then separately encodes. Various optimal SVQs have been obtained, both analytically and numerically. Analytic solutions which demonstrate how the input space is split into independent subspaces may be obtained when an SVQ is used to encode data that lives on a 2-torus (e.g. the superposition of a pair of uncorrelated sinusoids). Many numerical solutions have also been obtained, using both SVQs and chains of linked SVQs: (1) images of multiple independent targets (encod...
Stochastic control of traffic patterns
DEFF Research Database (Denmark)
Gaididei, Yuri B.; Gorria, Carlos; Berkemer, Rainer
2013-01-01
A stochastic modulation of the safety distance can reduce traffic jams. It is found that the effect of random modulation on congestive flow formation depends on the spatial correlation of the noise. Jam creation is suppressed for highly correlated noise. The results demonstrate the advantage...... of heterogeneous performance of the drivers in time as well as individually. This opens the possibility for the construction of technical tools to control traffic jam formation....
Foundations of infinitesimal stochastic analysis
Stroyan, KD
2011-01-01
This book gives a complete and elementary account of fundamental results on hyperfinite measures and their application to stochastic processes, including the *-finite Stieltjes sum approximation of martingale integrals. Many detailed examples, not found in the literature, are included. It begins with a brief chapter on tools from logic and infinitesimal (or non-standard) analysis so that the material is accessible to beginning graduate students.
Stochastic processes and filtering theory
Jazwinski, Andrew H
2007-01-01
This unified treatment of linear and nonlinear filtering theory presents material previously available only in journals, and in terms accessible to engineering students. Its sole prerequisites are advanced calculus, the theory of ordinary differential equations, and matrix analysis. Although theory is emphasized, the text discusses numerous practical applications as well.Taking the state-space approach to filtering, this text models dynamical systems by finite-dimensional Markov processes, outputs of stochastic difference, and differential equations. Starting with background material on probab
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
Stochastic cooling technology at Fermilab
Energy Technology Data Exchange (ETDEWEB)
Pasquinelli, R.J. E-mail: pasquin@fnal.gov
2004-10-11
The first antiproton cooling systems were installed and commissioned at Fermilab in 1984-1985. In the interim period, there have been several major upgrades, system improvements, and complete reincarnation of cooling systems. This paper will present some of the technology that was pioneered at Fermilab to implement stochastic cooling systems in both the Antiproton Source and Recycler accelerators. Current performance data will also be presented.
Information Anatomy of Stochastic Equilibria
Directory of Open Access Journals (Sweden)
Sarah Marzen
2014-08-01
Full Text Available A stochastic nonlinear dynamical system generates information, as measured by its entropy rate. Some—the ephemeral information—is dissipated and some—the bound information—is actively stored and so affects future behavior. We derive analytic expressions for the ephemeral and bound information in the limit of infinitesimal time discretization for two classical systems that exhibit dynamical equilibria: first-order Langevin equations (i where the drift is the gradient of an analytic potential function and the diffusion matrix is invertible and (ii with a linear drift term (Ornstein–Uhlenbeck, but a noninvertible diffusion matrix. In both cases, the bound information is sensitive to the drift and diffusion, while the ephemeral information is sensitive only to the diffusion matrix and not to the drift. Notably, this information anatomy changes discontinuously as any of the diffusion coefficients vanishes, indicating that it is very sensitive to the noise structure. We then calculate the information anatomy of the stochastic cusp catastrophe and of particles diffusing in a heat bath in the overdamped limit, both examples of stochastic gradient descent on a potential landscape. Finally, we use our methods to calculate and compare approximations for the time-local predictive information for adaptive agents.
Nonlinear and Stochastic Morphological Segregation
Blanton, M R
1999-01-01
I perform a joint counts-in-cells analysis of galaxies of different spectral types using the Las Campanas Redshift Survey (LCRS). Using a maximum-likelihood technique to fit for the relationship between the density fields of early- and late-type galaxies, I find a relative linear bias of $b=0.76\\pm 0.02$. This technique can probe the nonlinearity and stochasticity of the relationship as well. However, the degree to which nonlinear and stochastic fits improve upon the linear fit turns out to depend on the redshift range in question. In particular, there seems to be a systematic difference between the high- and low-redshift halves of the data (respectively, further than and closer than $cz\\approx 36,000$ km/s); all of the signal of stochasticity and nonlinearity comes from the low-redshift portion. Analysis of mock catalogs shows that the peculiar geometry and variable flux limits of the LCRS do not cause this effect. I speculate that the central surface brightness selection criteria of the LCRS may be responsi...
Stochastic analysis of biochemical systems
Anderson, David F
2015-01-01
This book focuses on counting processes and continuous-time Markov chains motivated by examples and applications drawn from chemical networks in systems biology. The book should serve well as a supplement for courses in probability and stochastic processes. While the material is presented in a manner most suitable for students who have studied stochastic processes up to and including martingales in continuous time, much of the necessary background material is summarized in the Appendix. Students and Researchers with a solid understanding of calculus, differential equations, and elementary probability and who are well-motivated by the applications will find this book of interest. David F. Anderson is Associate Professor in the Department of Mathematics at the University of Wisconsin and Thomas G. Kurtz is Emeritus Professor in the Departments of Mathematics and Statistics at that university. Their research is focused on probability and stochastic processes with applications in biology and other ar...
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.
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.
Realistic boundary conditions for stochastic simulations of reaction-diffusion processes
Erban, R; Erban, Radek
2006-01-01
Many cellular and subcellular biological processes can be described in terms of diffusing and chemically reacting species (e.g. enzymes). Such reaction-diffusion processes can be mathematically modelled using either deterministic partial-differential equations or stochastic simulation algorithms. The latter provide a more detailed and precise picture, and several stochastic simulation algorithms have been proposed in recent years. Such models typically give the same description of the reaction-diffusion processes far from the boundary of the simulated domain, but the behaviour close to a reactive boundary (e.g. a membrane with receptors) is unfortunately model-dependent. In this paper, we study four different approaches to stochastic modelling of reaction-diffusion problems and show the correct choice of the boundary condition for each model. The reactive boundary is treated as partially reflective, which means that some molecules hitting the boundary are adsorbed (e.g. bound to the receptor) and some molecul...
Epigenetics and Cellular Metabolism
Xu, Wenyi; Wang, Fengzhong; Yu, Zhongsheng; Xin, Fengjiao
2016-01-01
Living eukaryotic systems evolve delicate cellular mechanisms for responding to various environmental signals. Among them, epigenetic machinery (DNA methylation, histone modifications, microRNAs, etc.) is the hub in transducing external stimuli into transcriptional response. Emerging evidence reveals the concept that epigenetic signatures are essential for the proper maintenance of cellular metabolism. On the other hand, the metabolite, a main environmental input, can also influence the processing of epigenetic memory. Here, we summarize the recent research progress in the epigenetic regulation of cellular metabolism and discuss how the dysfunction of epigenetic machineries influences the development of metabolic disorders such as diabetes and obesity; then, we focus on discussing the notion that manipulating metabolites, the fuel of cell metabolism, can function as a strategy for interfering epigenetic machinery and its related disease progression as well. PMID:27695375
Architected Cellular Materials
Schaedler, Tobias A.; Carter, William B.
2016-07-01
Additive manufacturing enables fabrication of materials with intricate cellular architecture, whereby progress in 3D printing techniques is increasing the possible configurations of voids and solids ad infinitum. Examples are microlattices with graded porosity and truss structures optimized for specific loading conditions. The cellular architecture determines the mechanical properties and density of these materials and can influence a wide range of other properties, e.g., acoustic, thermal, and biological properties. By combining optimized cellular architectures with high-performance metals and ceramics, several lightweight materials that exhibit strength and stiffness previously unachievable at low densities were recently demonstrated. This review introduces the field of architected materials; summarizes the most common fabrication methods, with an emphasis on additive manufacturing; and discusses recent progress in the development of architected materials. The review also discusses important applications, including lightweight structures, energy absorption, metamaterials, thermal management, and bioscaffolds.
Waiting time distribution for continuous stochastic systems.
Gernert, Robert; Emary, Clive; Klapp, Sabine H L
2014-12-01
The waiting time distribution (WTD) is a common tool for analyzing discrete stochastic processes in classical and quantum systems. However, there are many physical examples where the dynamics is continuous and only approximately discrete, or where it is favourable to discuss the dynamics on a discretized and a continuous level in parallel. An example is the hindered motion of particles through potential landscapes with barriers. In the present paper we propose a consistent generalization of the WTD from the discrete case to situations where the particles perform continuous barrier crossing characterized by a finite duration. To this end, we introduce a recipe to calculate the WTD from the Fokker-Planck (Smoluchowski) equation. In contrast to the closely related first passage time distribution (FPTD), which is frequently used to describe continuous processes, the WTD contains information about the direction of motion. As an application, we consider the paradigmatic example of an overdamped particle diffusing through a washboard potential. To verify the approach and to elucidate its numerical implications, we compare the WTD defined via the Smoluchowski equation with data from direct simulation of the underlying Langevin equation and find full consistency provided that the jumps in the Langevin approach are defined properly. Moreover, for sufficiently large energy barriers, the WTD defined via the Smoluchowski equation becomes consistent with that resulting from the analytical solution of a (two-state) master equation model for the short-time dynamics developed previously by us [Phys. Rev. E 86, 061135 (2012)]. Thus, our approach "interpolates" between these two types of stochastic motion. We illustrate our approach for both symmetric systems and systems under constant force.
Delay-induced stochastic bifurcations in a bistable system under white noise.
Sun, Zhongkui; Fu, Jin; Xiao, Yuzhu; Xu, Wei
2015-08-01
In this paper, the effects of noise and time delay on stochastic bifurcations are investigated theoretically and numerically in a time-delayed Duffing-Van der Pol oscillator subjected to white noise. Due to the time delay, the random response is not Markovian. Thereby, approximate methods have been adopted to obtain the Fokker-Planck-Kolmogorov equation and the stationary probability density function for amplitude of the response. Based on the knowledge that stochastic bifurcation is characterized by the qualitative properties of the steady-state probability distribution, it is found that time delay and feedback intensity as well as noise intensity will induce the appearance of stochastic P-bifurcation. Besides, results demonstrated that the effects of the strength of the delayed displacement feedback on stochastic bifurcation are accompanied by the sensitive dependence on time delay. Furthermore, the results from numerical simulations best confirm the effectiveness of the theoretical analyses.
Delay-induced stochastic bifurcations in a bistable system under white noise
Energy Technology Data Exchange (ETDEWEB)
Sun, Zhongkui, E-mail: sunzk@nwpu.edu.cn; Fu, Jin; Xu, Wei [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Xiao, Yuzhu [Department of Mathematics and Information Science, Chang' an University, Xi' an 710086 (China)
2015-08-15
In this paper, the effects of noise and time delay on stochastic bifurcations are investigated theoretically and numerically in a time-delayed Duffing-Van der Pol oscillator subjected to white noise. Due to the time delay, the random response is not Markovian. Thereby, approximate methods have been adopted to obtain the Fokker-Planck-Kolmogorov equation and the stationary probability density function for amplitude of the response. Based on the knowledge that stochastic bifurcation is characterized by the qualitative properties of the steady-state probability distribution, it is found that time delay and feedback intensity as well as noise intensity will induce the appearance of stochastic P-bifurcation. Besides, results demonstrated that the effects of the strength of the delayed displacement feedback on stochastic bifurcation are accompanied by the sensitive dependence on time delay. Furthermore, the results from numerical simulations best confirm the effectiveness of the theoretical analyses.
ARIMA-Based Time Series Model of Stochastic Wind Power Generation
DEFF Research Database (Denmark)
Chen, Peiyuan; Pedersen, Troels; Bak-Jensen, Birgitte
2010-01-01
This paper proposes a stochastic wind power model based on an autoregressive integrated moving average (ARIMA) process. The model takes into account the nonstationarity and physical limits of stochastic wind power generation. The model is constructed based on wind power measurement of one year from...... the Nysted offshore wind farm in Denmark. The proposed limited-ARIMA (LARIMA) model introduces a limiter and characterizes the stochastic wind power generation by mean level, temporal correlation and driving noise. The model is validated against the measurement in terms of temporal correlation...... and probability distribution. The LARIMA model outperforms a first-order transition matrix based discrete Markov model in terms of temporal correlation, probability distribution and model parameter number. The proposed LARIMA model is further extended to include the monthly variation of the stochastic wind power...