Adaptive stochastic cellular automata: Applications
Qian, S.; Lee, Y. C.; Jones, R. D.; Barnes, C. W.; Flake, G. W.; O'Rourke, M. K.; Lee, K.; Chen, H. H.; Sun, G. Z.; Zhang, Y. Q.; Chen, D.; Giles, C. L.
1990-09-01
The stochastic learning cellular automata model has been applied to the problem of controlling unstable systems. Two example unstable systems studied are controlled by an adaptive stochastic cellular automata algorithm with an adaptive critic. The reinforcement learning algorithm and the architecture of the stochastic CA controller are presented. Learning to balance a single pole is discussed in detail. Balancing an inverted double pendulum highlights the power of the stochastic CA approach. The stochastic CA model is compared to conventional adaptive control and artificial neural network approaches.
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.
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
Stability of Stochastic Neutral Cellular Neural Networks
Chen, Ling; Zhao, Hongyong
In this paper, we study a class of stochastic neutral cellular neural networks. By constructing a suitable Lyapunov functional and employing the nonnegative semi-martingale convergence theorem we give some sufficient conditions ensuring the almost sure exponential stability of the networks. The results obtained are helpful to design stability of networks when stochastic noise is taken into consideration. Finally, two examples are provided to show the correctness of our analysis.
Stochastic Simulations on the Cellular Wave Computers
Ercsey-Ravasz, M.; Roska, T.; Néda, Z.
2006-01-01
The computational paradigm represented by Cellular Neural/nonlinear Networks (CNN) and the CNN Universal Machine (CNN-UM) as a Cellular Wave Computer, gives new perspectives for computational physics. Many numerical problems and simulations can be elegantly addressed on this fully parallelized and analogic architecture. Here we study the possibility of performing stochastic simulations on this chip. First a realistic random number generator is implemented on the CNN-UM, and then as an example...
Stochastic Simulations on the Cellular Wave Computers
Ercsey-Ravasz, M; Neda, Z
2006-01-01
The computational paradigm represented by Cellular Neural/nonlinear Networks (CNN) and the CNN Universal Machine (CNN-UM) as a Cellular Wave Computer, gives new perspectives for computational physics. Many numerical problems and simulations can be elegantly addressed on this fully parallelized and analogic architecture. Here we study the possibility of performing stochastic simulations on this chip. First a realistic random number generator is implemented on the CNN-UM, and then as an example the two-dimensional Ising model is studied by Monte Carlo type simulations. The results obtained on an experimental version of the CNN-UM with 128 * 128 cells are in good agreement with the results obtained on digital computers. Computational time measurements suggests that the developing trend of the CNN-UM chips - increasing the lattice size and the number of local logic memories - will assure an important advantage for the CNN-UM in the near future.
Directed Percolation arising in Stochastic Cellular Automata
Regnault, Damien
2008-01-01
Cellular automata are both seen as a model of computation and as tools to model real life systems. Historically they were studied under synchronous dynamics where all the cells of the system are updated at each time step. Meanwhile the question of probabilistic dynamics emerges: on the one hand, to develop cellular automata which are capable of reliable computation even when some random errors occur; on the other hand, because synchronous dynamics is not a reasonable assumption to simulate re...
Stochastic properties of disturbed Elementary Cellular Automata
International Nuclear Information System (INIS)
Cellular automata are class of simple mathematical systems that generate diverse, often complicated behaviour. Evolution of such a system is given by set of local and deterministic rules. However, in spite of simplicity of 'interactions' it's global behaviour can't be, in general, simply predicted or even can not be predicted in time shorter that time of it's strict evolution. We get as, a systems well known 1-dimensional, Wolfram class automata, and connect it into the reservoir consists of some random source (noise). In our experiment we are interested in: a) numeric verification of ergodicity for such a coupled system. b) finding it's probability distribution and evolution. c) finding some analogous for 'real' quantities and behaviour. d) using the dynamical systems and Markov chains theory to describe the system, and to make any predictions of it's behaviour. (author)
Traffic jam dynamics in stochastic cellular automata
Energy Technology Data Exchange (ETDEWEB)
Nagel, K. [Los Alamos National Lab., NM (United States)]|[Santa Fe Inst., NM (United States); Schreckenberg, M. [Univ. Duisburg (Germany)
1995-09-01
Simple models for particles hopping on a grid (cellular automata) are used to simulate (single lane) traffic flow. Despite their simplicity, these models are astonishingly realistic in reproducing start-stop-waves and realistic fundamental diagrams. One can use these models to investigate traffic phenomena near maximum flow. A so-called phase transition at average maximum flow is visible in the life-times of jams. The resulting dynamic picture is consistent with recent fluid-dynamical results by Kuehne/Kerner/Konhaeuser, and with Treiterer`s hysteresis description. This places CA models between car-following models and fluid-dynamical models for traffic flow. CA models are tested in projects in Los Alamos (USA) and in NRW (Germany) for large scale microsimulations of network traffic.
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...
Modeling and Analysis of Cellular Networks using Stochastic Geometry: A Tutorial
ElSawy, Hesham
2016-03-22
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 basic cellular network model. Then, it characterizes signal-tointerference- plus-noise-ratio (SINR) and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and 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 baseline 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. Finally, we point out future research directions.
Stochastic cellular fate decision making by multiple infecting lambda phage.
Directory of Open Access Journals (Sweden)
Matthew L Robb
Full Text Available Bacteriophage lambda is a classic system for the study of cellular decision making. Both experiments and mathematical models have demonstrated the importance of viral concentration in the lysis-lysogeny decision outcome in lambda phage. However, a recent experimental study using single cell and single phage resolution reported that cells with the same viral concentrations but different numbers of infecting phage (multiplicity of infection can have markedly different rates of lysogeny. Thus the decision depends on not only viral concentration, but also directly on the number of infecting phage. Here, we attempt to provide a mechanistic explanation of these results using a simple stochastic model of the lambda phage genetic network. Several potential factors including intrinsic gene expression noise, spatial dynamics and cell-cycle effects are investigated. We find that interplay between the level of intrinsic noise and viral protein decision threshold is a major factor that produces dependence on multiplicity of infection. However, simulations suggest spatial segregation of phage particles does not play a significant role. Cellular image processing is used to re-analyse the original time-lapse movies from the recent study and it is found that higher numbers of infecting phage reduce the cell elongation rate. This could also contribute to the observed phenomena as cellular growth rate can affect transcription rates. Our model further predicts that rate of lysogeny is dependent on bacterial growth rate, which can be experimentally tested. Our study provides new insight on the mechanisms of individual phage decision making. More generally, our results are relevant for the understanding of gene-dosage compensation in cellular systems.
Integrability of a deterministic cellular automaton driven by stochastic boundaries
Prosen, Tomaž; Mejía-Monasterio, Carlos
2016-05-01
We propose an interacting many-body space–time-discrete Markov chain model, which is composed of an integrable deterministic and reversible cellular automaton (rule 54 of Bobenko et al 1993 Commun. Math. Phys. 158 127) on a finite one-dimensional lattice {({{{Z}}}2)}× n, and local stochastic Markov chains at the two lattice boundaries which provide chemical baths for absorbing or emitting the solitons. Ergodicity and mixing of this many-body Markov chain is proven for generic values of bath parameters, implying the existence of a unique nonequilibrium steady state. The latter is constructed exactly and explicitly in terms of a particularly simple form of matrix product ansatz which is termed a patch ansatz. This gives rise to an explicit computation of observables and k-point correlations in the steady state as well as the construction of a nontrivial set of local conservation laws. The feasibility of an exact solution for the full spectrum and eigenvectors (decay modes) of the Markov matrix is suggested as well. We conjecture that our ideas can pave the road towards a theory of integrability of boundary driven classical deterministic lattice systems.
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.
International Nuclear Information System (INIS)
The paper considers the problems of existence of quadratic mean almost periodic and global exponential stability for stochastic cellular neural networks with delays. By employing the Holder's inequality and fixed points principle, we present some new criteria ensuring existence and uniqueness of a quadratic mean almost periodic and global exponential stability. These criteria are important in signal processing and the design of networks. Moreover, these criteria are also applied in others stochastic biological neural systems.
Transfer-matrix DMRG for stochastic models: The Domany-Kinzel cellular automaton
Kemper, A.; Schadschneider, A.; Zittartz, J.
2001-01-01
We apply the transfer-matrix DMRG (TMRG) to a stochastic model, the Domany-Kinzel cellular automaton, which exhibits a non-equilibrium phase transition in the directed percolation universality class. Estimates for the stochastic time evolution, phase boundaries and critical exponents can be obtained with high precision. This is possible using only modest numerical effort since the thermodynamic limit can be taken analytically in our approach. We also point out further advantages of the TMRG o...
Hanfeng Kuang; Jinbo Liu; Xi Chen; Jie Mao; Linjie He
2013-01-01
The asymptotic behavior of a class of switched stochastic cellular neural networks (CNNs) with mixed delays (discrete time-varying delays and distributed time-varying delays) is investigated in this paper. Employing the average dwell time approach (ADT), stochastic analysis technology, and linear matrix inequalities technique (LMI), some novel sufficient conditions on the issue of asymptotic behavior (the mean-square ultimate boundedness, the existence of an attractor, and the mean-square ...
Bit-Vectorized GPU Implementation of a Stochastic Cellular Automaton Model for Surface Growth
Kelling, Jeffrey; Gemming, Sibylle
2016-01-01
Stochastic surface growth models aid in studying properties of universality classes like the Kardar--Paris--Zhang class. High precision results obtained from large scale computational studies can be transferred to many physical systems. Many properties, such as roughening and some two-time functions can be studied using stochastic cellular automaton (SCA) variants of stochastic models. Here we present a highly efficient SCA implementation of a surface growth model capable of simulating billions of lattice sites on a single GPU. We also provide insight into cases requiring arbitrary random probabilities which are not accessible through bit-vectorization.
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.
Molecular and cellular fundamentals of stochastic radiation action
International Nuclear Information System (INIS)
Description of basic radiobiological processes in order to assess the risk of carcinogenesis due to radiotherapeutic procedures; demonstration of direct radiation-induced damage to DNA and indirect effects due to radiolysis of cellular water; description of repair mechanisms; radiation- induced chromosomal aberrations, genome mutations and disturbances of the cell cycle and their contributions to the carcinogenic effects of radiotherapy.(MG)
Stochastic Cellular Fate Decision Making by Multiple Infecting Lambda Phage
Robb, Matthew L.; Shahrezaei, Vahid
2014-01-01
Bacteriophage lambda is a classic system for the study of cellular decision making. Both experiments and mathematical models have demonstrated the importance of viral concentration in the lysis-lysogeny decision outcome in lambda phage. However, a recent experimental study using single cell and single phage resolution reported that cells with the same viral concentrations but different numbers of infecting phage (multiplicity of infection) can have markedly different rates of lysogeny. Thus t...
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.
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.
A Stochastic Cellular Automaton Model of Non-linear Diffusion and Diffusion with Reaction
Brieger, Leesa M.; Bonomi, Ernesto
1991-06-01
This article presents a stochastic cellular automaton model of diffusion and diffusion with reaction. The master equations for the model are examined, and we assess the difference between the implementation in which a single particle at a time moves (asynchronous dynamics) and one implementation in which all particles move simultaneously (synchronous dynamics). Biasing locally each particle's random walk, we alter the diffusion coefficients of the system. By appropriately choosing the biasing function, we can impose a desired non-linear diffusive behaviour in the model. We present an application of this model, adapted to include two diffusing species, two static species, and a chemical reaction in a prototypical simulation of carbonation in concrete.
Pseudo-stochastic signal characterization in wavelet-domain
International Nuclear Information System (INIS)
In this paper we present the method for fast and accurate characterization of pseudo-stochastic signals, which contain a large number of similar but randomly-located fragments. This method allows estimating the statistical characteristics of pseudo-stochastic signal, and it is based on digital signal processing in wavelet-domain. Continuous wavelet transform and the criterion for wavelet scale power density are utilized. We are experimentally implementing this method for the purpose of sand granulometry, and we are estimating the statistical parameters of test sand fractions
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...
Non-concave fundamental diagrams and phase transitions in a stochastic traffic cellular automaton
Maerivoet, S.; de Moor, B.
2004-11-01
Within the class of stochastic cellular automata models of traffic flows, we look at the velocity dependent randomization variant (VDR-TCA) whose parameters take on a specific set of extreme values. These initial conditions lead us to the discovery of the emergence of four distinct phases. Studying the transitions between these phases, allows us to establish a rigorous classification based on their tempo-spatial behavioral characteristics. As a result from the system’s complex dynamics, its flow-density relation exhibits a non-concave region in which forward propagating density waves are encountered. All four phases furthermore share the common property that moving vehicles can never increase their speed once the system has settled into an equilibrium.
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...
Stochastic Characterization of Cast Metal Microstructure
Energy Technology Data Exchange (ETDEWEB)
Steinzig, M.
1999-06-01
The major goal of this work is to provide a means to characterize the final structure of a metal that has solidified from a melt. The thermally controlled solidification of a binary alloy, nucleated at isolated sites, is described by the evolution of a probability distribution function (PDF). The relevant equation required for propagating the PDF is developed with variables for grain size and distance to nearest neighbor. The phenomena of nucleation, growth, and impingement of the grains are discussed, and used as the basis for developing rate equations that evolve the PDF. The complementary equations describing global heat and solute transfer are discussed, and coupled with the microstructure evolution equations for grain growth and PDF evolution. The full set of equations is solved numerically and results are compared with experimental data for the plutonium 1 weight percent gallium system. The three principal results of this work are: (1) The formulation of transient evolution equations for the PDF description of nucleation, growth, and impingement of a distribution of grain sizes and locations; (2) Solution of the equations to give a correlation for final average grain size as a function of material parameters, nucleation site density, and cooling rate; and (3) Solution of the equations for final distribution of grain size as a result of the initial random spatial distribution of nucleation sites.
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.
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.
Energy Technology Data Exchange (ETDEWEB)
Kemper, A. [Institut fuer Theoretische Physik, Universitaet zu Koeln, Cologne (Germany). E-mail: kemper@thp.uni-koeln.de; Schadschneider, A. [Institut fuer Theoretische Physik, Universitaet zu Koeln, Cologne (Germany). E-mail: as@thp.uni-koeln.de; Zittartz, J. [Institut fuer Theoretische Physik, Universitaet zu Koeln, Cologne (Germany)
2001-05-18
We apply the transfer-matrix density-matrix renormalization group (TMRG) to a stochastic model, the Domany-Kinzel cellular automaton, which exhibits a non-equilibrium phase transition in the directed percolation universality class. Estimates for the stochastic time evolution, phase boundaries and critical exponents can be obtained with high precision. This is possible using only modest numerical effort since the thermodynamic limit can be taken analytically in our approach. We also point out further advantages of the TMRG over other numerical approaches, such as classical DMRG or Monte Carlo simulations. (author). Letter-to-the-editor.
International Nuclear Information System (INIS)
We apply the transfer-matrix density-matrix renormalization group (TMRG) to a stochastic model, the Domany-Kinzel cellular automaton, which exhibits a non-equilibrium phase transition in the directed percolation universality class. Estimates for the stochastic time evolution, phase boundaries and critical exponents can be obtained with high precision. This is possible using only modest numerical effort since the thermodynamic limit can be taken analytically in our approach. We also point out further advantages of the TMRG over other numerical approaches, such as classical DMRG or Monte Carlo simulations. (author). Letter-to-the-editor
Roh, Min K.; Daigle, Bernie J.; Gillespie, Dan T.; Petzold, Linda R.
2011-12-01
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)], 10.1063/1.2987701. 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.
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.
Qian, Hong
2010-12-01
Based on a stochastic, nonlinear, open biochemical reaction system perspective, we present an analytical theory for cellular biochemical processes. The chemical master equation (CME) approach provides a unifying mathematical framework for cellular modeling. We apply this theory to both self-regulating gene networks and phosphorylation-dephosphorylation signaling modules with feedbacks. Two types of bistability are illustrated in mesoscopic biochemical systems: one that has a macroscopic, deterministic counterpart and another that does not. In certain cases, the latter stochastic bistability is shown to be a "ghost" of the extinction phenomenon. We argue the thermal fluctuations inherent in molecular processes do not disappear in mesoscopic cell-sized nonlinear systems; rather they manifest themselves as isogenetic variations on a different time scale. Isogenetic biochemical variations in terms of the stochastic attractors can have extremely long lifetime. Transitions among discrete stochastic attractors spend most of the time in "waiting", exhibit punctuated equilibria. It can be naturally passed to "daughter cells" via a simple growth and division process. The CME system follows a set of nonequilibrium thermodynamic laws that include non-increasing free energy F( t) with external energy drive Q hk ≥0, and total entropy production rate e p =- dF/ dt+ Q hk ≥0. In the thermodynamic limit, with a system's size being infinitely large, the nonlinear bistability in the CME exhibits many of the characteristics of macroscopic equilibrium phase transition.
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.
Challenges in Characterizing and Controlling Complex Cellular Systems
Wikswo, John
2011-03-01
Multicellular dynamic biological processes such as developmental differentiation, wound repair, disease, aging, and even homeostasis can be represented by trajectories through a phase space whose extent reflects the genetic, post-translational, and metabolic complexity of the process - easily extending to tens of thousands of dimensions. Intra- and inter-cellular sensing and regulatory systems and their nested, redundant, and non-linear feed-forward and feed-back controls create high-dimensioned attractors in this phase space. Metabolism provides free energy to drive non-equilibrium processes and dynamically reconfigure attractors. Studies of single molecules and cells provide only minimalist projections onto a small number of axes. It may be difficult to infer larger-scale emergent behavior from linearized experiments that perform only small amplitude perturbations on a limited number of the dimensions. Complete characterization may succeed for bounded component problems, such as an individual cell cycle or signaling cascade, but larger systems problems will require a coarse-grained approach. Hence a new experimental and analytical framework is needed. Possibly one could utilize high-amplitude, multi-variable driving of the system to infer coarse-grained, effective models, which in turn can be tested by their ability to control systems behavior. Navigation at will between attractors in a high-dimensioned dynamical system will provide not only detailed knowledge of the shape of attractor basins, but also measures of underlying stochastic events such as noise in gene expression or receptor binding and how both affect system stability and robustness. Needed for this are wide-bandwidth methods to sense and actuate large numbers of intracellular and extracellular variables and automatically and rapidly infer dynamic control models. The success of this approach may be determined by how broadly the sensors and actuators can span the full dimensionality of the phase space
International Nuclear Information System (INIS)
Full text: The Bauschinger effect refers to an observed asymmetry in the forward and reverse loading curves of a metal or an alloy. Typically, the absolute value of the yield stress in reverse loading is lower than the maximum stress imposed on the initial, forward loading. This difference arises from either the presence of a back stress or from the greater strength of obstacles opposing dislocation motion in the forward than in the reverse direction. Thus, the Bauschinger effect contributes to the phenomena referred to as kinematic hardening. In particular dispersion hardened systems, containing strong, non-shearable particles that offer obstacles to dislocation motion, will often exhibit a large kinematic hardening component. When a material is described as a group of parallel elements (a composite) having variable yield stresses and or Young's moduli, kinematic hardening of type KI, is observed when the first element to yield on forward loading is the first element to yield on reverse loading. Kinematic hardening types KII and KIII result when the order of relaxation of the elements is different from the order of their initial yielding. The reverse loading curves for types KII and KIII hardening generally exhibit inflection points at the initiation of yielding on reverse loading. In previous work, a micromechanics model, with a detailed description of the microstructure, was employed to model the effects of plastic inhomogeneity and duplicate the loading and unloading trends observed experimentally. Trends predicted by the model corresponded well to some of the expectations derived from observation, e.g. the effects related to the inclusions of different phases, however in some cases the correlation depended on the assignment of unrealistic properties to microstructural constituents. In the current work, the material is modeled as an array of coupled elements with varying stiffnesses and strengths. A stochastic cellular automaton is then used to simulate the
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 ((223)Ra) 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 ([Formula: see text]40%) can be attributed in part to the variation in LET with pathlength. We also found that [Formula: see text]18% of cell nuclei receive less than one sigma below the average dose per cell ([Formula: see text]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. PMID:26216391
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...
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
2016-01-01
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. PMID:27117858
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.
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.
2016-01-01
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. PMID:27117858
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
Weak Characterizations of Stochastic Integrability and Dudley's Theorem in Infinite Dimensions
Czech Academy of Sciences Publication Activity Database
Ondreját, Martin; Veraar, M.
2014-01-01
Roč. 27, č. 4 (2014), s. 1350-1374. ISSN 0894-9840 R&D Projects: GA ČR GAP201/10/0752 Institutional support: RVO:67985556 Keywords : stochastic integration in Banach spaces * almost sure limit theorems * Dudley representation theorem * universal representation theorem * weak characterization of stochastic integrability * Doob representation theorem Subject RIV: BA - General Mathematics Impact factor: 0.857, year: 2014 http://library.utia.cas.cz/separaty/2013/SI/ondrejat-0392394.pdf
Chattopadhyay, Arpan; Błaszczyszyn, Bartłomiej; Altman, Eitan
2016-01-01
We consider location-dependent opportunistic bandwidth sharing between static and mobile downlink users in a cellular network. Each cell has some fixed number of static users. Mobile users enter the cell, move inside the cell for some time and then leave the cell. In order to provide higher data rate to mobile users, we propose to provide higher bandwidth to the mobile users at favourable times and locations, and provide higher bandwidth to the static users in other times. We formulate the pr...
Stochastic Characterization of Flutter using Historical Wind Tunnel Data
Heeg, Jennifer
2007-01-01
Methods for predicting the onset of flutter during an experiment are traditionally applied treating the data as deterministic values. Uncertainty and variation in the data is often glossed over by using best-fit curves to represent the information. This paper applies stochastic treatments to wind tunnel data obtained for the Piezoelectric Aeroelastic Response Tailoring Investigation model. These methods include modal amplitude tracking, modal frequency tracking and several applications of the flutter margin method. The flutter margin method was developed by Zimmerman and Weissenburger, and extended by Poirel, Dunn and Porter to incorporate uncertainty. Much of the current work follows the future work recommendations of Poirel, Dunn and Porter.
Kemper, A.; Schadschneider, A.; Zittartz, J.
2001-05-01
We apply the transfer-matrix density-matrix renormalization group (TMRG) to a stochastic model, the Domany-Kinzel cellular automaton, which exhibits a non-equilibrium phase transition in the directed percolation universality class. Estimates for the stochastic time evolution, phase boundaries and critical exponents can be obtained with high precision. This is possible using only modest numerical effort since the thermodynamic limit can be taken analytically in our approach. We also point out further advantages of the TMRG over other numerical approaches, such as classical DMRG or Monte Carlo simulations.
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.
Murthy, Garimella Rama
2012-01-01
In this research paper, the relationship between finite / countable state space stochastic processes and point processes is explored. Utilizing the known relationship between Poisson processes and continuous time Markov chains, finite / countable state space random processes are related to continuous time Markov Chains. Based on the known results for binary random processes, characterization of auto-correlation function of finite state space random processes is explored. An important characte...
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.
International Nuclear Information System (INIS)
The 1996 performance assessment (PA) for the Waste Isolation Pilot Plant (WIPP) maintains a separation between stochastic (i.e. aleatory) and subjective (i.e. epistemic) uncertainty, with stochastic uncertainty arising from the possible disruptions that could occur at the WIPP over the 10,000-yr regulatory period specified by the US Environmental Protection Agency (40 CFR 191, 40 CFR 194) and subjective uncertainty arising from an inability to uniquely characterize many of the inputs required in the 1996 WIPP PA. The characterization of stochastic uncertainty is discussed, including drilling intrusion time, drilling location, penetration of excavated/nonexcavated areas of the repository, penetration of pressurized brine beneath the repository, borehole plugging patterns, activity level of waste, and occurrence of potash mining. Additional topics discussed include sampling procedures, generation of individual 10,000-yr futures for the WIPP, construction of complementary cumulative distribution functions (CCDFs), mechanistic calculations carried out to support CCDF construction, the Kaplan/Garrick ordered triple representation for risk, and determination of scenarios and scenario probabilities
Energy Technology Data Exchange (ETDEWEB)
HELTON,JON CRAIG; DAVIS,FREDDIE J.; JOHNSON,J.D.
2000-05-19
The 1996 performance assessment (PA) for the Waste Isolation Pilot Plant (WIPP) maintains a separation between stochastic (i.e., aleatory) and subjective (i.e., epistemic) uncertainty, with stochastic uncertainty arising from the possible disruptions that could occur at the WIPP over the 10,000 yr regulatory period specified by the US Environmental Protection Agency (40 CFR 191, 40 CFR 194) and subjective uncertainty arising from an inability to uniquely characterize many of the inputs required in the 1996 WIPP PA. The characterization of stochastic uncertainty is discussed including drilling intrusion time, drilling location penetration of excavated/nonexcavated areas of the repository, penetration of pressurized brine beneath the repository, borehole plugging patterns, activity level of waste, and occurrence of potash mining. Additional topics discussed include sampling procedures, generation of individual 10,000 yr futures for the WIPP, construction of complementary cumulative distribution functions (CCDFs), mechanistic calculations carried out to support CCDF construction the Kaplan/Garrick ordered triple representation for risk and determination of scenarios and scenario probabilities.
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
Progresses in the Analysis of Stochastic 2D Cellular Automata: a Study of Asynchronous 2D Minority
Regnault, Damien; Thierry, Éric
2007-01-01
Cellular automata are often used to model systems in physics, social sciences, biology that are inherently asynchronous. Over the past 20 years, studies have demonstrated that the behavior of cellular automata drastically changed under asynchronous updates. Still, the few mathematical analyses of asynchronism focus on one-dimensional probabilistic cellular automata, either on single examples or on specific classes. As for other classic dynamical systems in physics, extending known methods from one- to two-dimensional systems is a long lasting challenging problem. In this paper, we address the problem of analysing an apparently simple 2D asynchronous cellular automaton: 2D Minority where each cell, when fired, updates to the minority state of its neighborhood. Our experiments reveal that in spite of its simplicity, the minority rule exhibits a quite complex response to asynchronism. By focusing on the fully asynchronous regime, we are however able to describe completely the asymptotic behavior of this dynamics...
Sakr, Ahmed Hamdi; Hossain, Ekram
2014-01-01
While cognitive radio enables spectrum-efficient wireless communication, radio frequency (RF) energy harvesting from ambient interference is an enabler for energy-efficient wireless communication. In this paper, we model and analyze cognitive and energy harvesting-based D2D communication in cellular networks. The cognitive D2D transmitters harvest energy from ambient interference and use one of the channels allocated to cellular users (in uplink or downlink), which is referred to as the D2D c...
Cellular spectroscopy: applications to cancer stem cell characterization
Wiegand, G.; Xin, H.; Anderson, A.; Mullinax, J.; Jaiswal, K.; Wiegand, A.; Avital, Itzhak
2011-02-01
Spectroscopic and light scattering methods were used to gain insight into the existence and characterization of the cancer stem cell. Fundamental technical description of devices used have been reported elsewhere. We included alterations and implementation of these biophotonic instruments as applied to our objectives. We disassociated human tumor and submitted the cells to optical characterization to support our working hypothesis of stem cell origins to cancer and mechanisms. Single cell combined with population based analysis within the Pancreatic cancer system led us to information regarding the polarization state of cells possessing anchor proteins and drug influx pumps. Multispectral imaging combined with flow cytometry enabled us to target rare cells that appear to retain template DNA. rendering them resistant to anti-cancer drug therapy. In this study we describe an optical method that combines high-throughput population pattern and correlates each cell with an individual fluorescent and bright-field image.
Malignant and tuberculous pleural effusions: immunophenotypic cellular characterization
Lucia Maria Zanatta de Aguiar; Leila Antonangelo; Vargas, Francisco S.; Maria Cláudia Nogueira Zerbini; Maria Mirtes Sales; David E. Uip; Paulo Hilário Nascimento Saldiva
2008-01-01
INTRODUCTION AND OBJECTIVES: Tuberculosis and cancer are the main causes of pleural effusion. Pleural involvement is associated with migration of immune cells to the pleural cavity. We sought to characterize the immunophenotype of leukocytes in the pleural effusion and peripheral blood of patients with tuberculosis or malignancy. METHODS: Thirty patients with tuberculosis (14) or malignancy (16) were studied. A control group included 20 healthy blood donors. RESULTS: Malignant phycoerythrin p...
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.
Malignant and tuberculous pleural effusions: immunophenotypic cellular characterization
Directory of Open Access Journals (Sweden)
Lucia Maria Zanatta de Aguiar
2008-01-01
Full Text Available INTRODUCTION AND OBJECTIVES: Tuberculosis and cancer are the main causes of pleural effusion. Pleural involvement is associated with migration of immune cells to the pleural cavity. We sought to characterize the immunophenotype of leukocytes in the pleural effusion and peripheral blood of patients with tuberculosis or malignancy. METHODS: Thirty patients with tuberculosis (14 or malignancy (16 were studied. A control group included 20 healthy blood donors. RESULTS: Malignant phycoerythrin pleural effusions showed higher percentages of CD3, CD4, CD3CD45RO, and CD20CD25 lymphocytes and lower percentages of CD3CD25 and CD20HLA-DR when compared to PB lymphocytes. Compared to PB, tuberculous effusions had a higher percentage of lymphocytes that co-expressed CD3, CD4, CD3CD45RO, CD3TCRαβ, CD3CD28, and CD20 and a lower percentage of CD14, CD8 and CD3TCRγδ-positive lymphocytes. Malignant effusions presented higher expression of CD14 whereas tuberculous effusions had higher expression of CD3 and CD3CD95L. Peripheral blood cells from tuberculosis patients showed higher expression of CD14, CD20CD25 and CD3CD95L. Compared with the control cells, tuberculosis and cancer peripheral blood cells presented a lower percentage of CD3CD4 and CD3CD28-positive cells as well as a higher percentage of CD3CD8, CD3CD25 and CD3CD80-positive cells. CONCLUSIONS: Tuberculous and malignant peripheral blood is enriched with lymphocytes with a helper/inducer T cell phenotype, which are mainly of memory cells. CD14-positive cells were more frequently found in malignant effusions, while CD3-positive cells expressing Fas ligand were more frequently found in tuberculous effusions.
Malignant and Tuberculous Pleural Effusions: Immunophenotypic Cellular Characterization
de Aguiar, Lucia Maria Zanatta; Antonangelo, Leila; Vargas, Francisco S.; Zerbini, Maria Cláudia Nogueira; Sales, Maria Mirtes; Uip, David E.; Saldiva, Paulo Hilário Nascimento
2008-01-01
INTRODUCTION AND OBJECTIVES Tuberculosis and cancer are the main causes of pleural effusion. Pleural involvement is associated with migration of immune cells to the pleural cavity. We sought to characterize the immunophenotype of leukocytes in the pleural effusion and peripheral blood of patients with tuberculosis or malignancy. METHODS Thirty patients with tuberculosis (14) or malignancy (16) were studied. A control group included 20 healthy blood donors. RESULTS Malignant phycoerythrin pleural effusions showed higher percentages of CD3, CD4, CD3CD45RO, and CD20CD25 lymphocytes and lower percentages of CD3CD25 and CD20HLA-DR when compared to PB lymphocytes. Compared to PB, tuberculous effusions had a higher percentage of lymphocytes that co-expressed CD3, CD4, CD3CD45RO, CD3TCRαβ, CD3CD28, and CD20 and a lower percentage of CD14, CD8 and CD3TCRγδ-positive lymphocytes. Malignant effusions presented higher expression of CD14 whereas tuberculous effusions had higher expression of CD3 and CD3CD95L. Peripheral blood cells from tuberculosis patients showed higher expression of CD14, CD20CD25 and CD3CD95L. Compared with the control cells, tuberculosis and cancer peripheral blood cells presented a lower percentage of CD3CD4 and CD3CD28-positive cells as well as a higher percentage of CD3CD8, CD3CD25 and CD3CD80-positive cells. CONCLUSIONS Tuberculous and malignant peripheral blood is enriched with lymphocytes with a helper/inducer T cell phenotype, which are mainly of memory cells. CD14-positive cells were more frequently found in malignant effusions, while CD3-positive cells expressing Fas ligand were more frequently found in tuberculous effusions. PMID:18925324
Characterizations and simulations of a class of stochastic processes to model anomalous diffusion
International Nuclear Information System (INIS)
In this paper, we study a parametric class of stochastic processes to model both fast and slow anomalous diffusions. This class, called generalized grey Brownian motion (ggBm), is made up of self-similar with stationary increments processes (H-sssi) and depends on two real parameters α element of (0, 2) and β element of (0, 1]. It includes fractional Brownian motion when α element of (0, 2) and β = 1, and time-fractional diffusion stochastic processes when α = β element of (0, 1). The latter have a marginal probability density function governed by time-fractional diffusion equations of order β. The ggBm is defined through the explicit construction of the underlying probability space. However, in this paper we show that it is possible to define it in an unspecified probability space. For this purpose, we write down explicitly all the finite-dimensional probability density functions. Moreover, we provide different ggBm characterizations. The role of the M-Wright function, which is related to the fundamental solution of the time-fractional diffusion equation, emerges as a natural generalization of the Gaussian distribution. Furthermore, we show that the ggBm can be represented in terms of the product of a random variable, which is related to the M-Wright function, and an independent fractional Brownian motion. This representation highlights the H-sssi nature of the ggBm and provides a way to study and simulate the trajectories. For this purpose, we developed a random walk model based on a finite difference approximation of a partial integro-differential equation of a fractional type
Characterizing pervasive vehicular access to the cellular RAN infrastructure: an urban case study
Uppoor, Sandesh; Fiore, Marco
2015-01-01
Managing user mobility is historically one of the most critical issues in cellular radio access networks (RANs). That task will become an even greater challenge due to cellular users on-board vehicles and networked cars that autonomously access Internet-based services, whose number is expected to grow dramatically in the next few years. There is thus a need to characterize RAN access from/by vehicles in a similar way to what has been done for traditional pedestrian access. In this paper, we p...
Characterization of humoral and cellular immune responses in patients with human papilloma virus
International Nuclear Information System (INIS)
A descriptive and cross-sectional study was carried out in 30 females infected with the human papilloma virus, attended in the office of Immunology of the Specialty Polyclinic belonging to 'Saturnino Lora' Provincial Clinical Surgical Teaching Hospital in Santiago de Cuba, from June 2009 to June 2010, in order to characterize them according to immune response. To evaluate the humoral and cellular immune response rosetting assay and quantification of immunoglobulins were used respectively. Women between 25-36 years of age (40 %) infected with this virus, especially those coming from urban areas, prevailed in the series, and a significant decrease of the cellular response as compared to the humoral response was evidenced
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.
International Nuclear Information System (INIS)
Cellular electrets polymer is a new ferroelectret material exhibiting large piezoelectricity and has attracted considerable attentions in researches and industries. Property characterization is very important for this material and current investigations are mostly on macroscopic properties. In this work, we conduct nanoscale piezoelectric and ferroelectric characterizations of cellular polypropylene (PP) films using piezoresponse force microscopy (PFM). First, both the single-frequency PFM and dual-frequency resonance-tracking PFM testings were conducted on the cellular PP film. The localized piezoelectric constant d33 is estimated to be 7–11pC/N by correcting the resonance magnification with quality factor and it is about one order lower than the macroscopic value. Next, using the switching spectroscopy PFM (SS-PFM), we studied polarization switching behavior of the cellular PP films. Results show that it exhibits the typical ferroelectric-like phase hysteresis loops and butterfly-shaped amplitude loops, which is similar to that of a poly(vinylidene fluoride) (PVDF) ferroelectric polymer film. However, both the phase and amplitude loops of the PP film are intensively asymmetric, which is thought to be caused by the nonzero remnant polarization after poling. Then, the D-E hysteresis loops of both the cellular PP film and PVDF film were measured by using the same wave form as that used in the SS-PFM, and the results show significant differences. Finally, we suggest that the ferroelectric-like behavior of cellular electrets films should be distinguished from that of typical ferroelectrics, both macroscopically and microscopically
International Nuclear Information System (INIS)
This section contains summaries of research on the detection and characterization of damage in molecular, cellular, and physiological systems. Projects under investigation in this section include: chemical synthesis of nucleic acid derivatives; structural and conformational properties of biological molecules in solution; crystallographic and chemical studies of immunoglobulin structure; instrument design and development for x-ray and neutron scattering studies of biological molecules; and chromobiology and circadian regulation
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.
Kryvohuz, Maksym; Mukamel, Shaul
2015-06-01
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. PMID:26049450
International Nuclear Information System (INIS)
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
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. PMID:26350218
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.
Characterization of the cellular response triggered by gold nanoparticle-mediated laser manipulation
Kalies, Stefan; Keil, Sebastian; Sender, Sina; Hammer, Susanne C.; Antonopoulos, Georgios C.; Schomaker, Markus; Ripken, Tammo; Escobar, Hugo Murua; Meyer, Heiko; Heinemann, Dag
2015-11-01
Laser-based transfection techniques have proven high applicability in several cell biologic applications. The delivery of different molecules using these techniques has been extensively investigated. In particular, new high-throughput approaches such as gold nanoparticle-mediated laser transfection allow efficient delivery of antisense molecules or proteins into cells preserving high cell viabilities. However, the cellular response to the perforation procedure is not well understood. We herein analyzed the perforation kinetics of single cells during resonant gold nanoparticle-mediated laser manipulation with an 850-ps laser system at a wavelength of 532 nm. Inflow velocity of propidium iodide into manipulated cells reached a maximum within a few seconds. Experiments based on the inflow of FM4-64 indicated that the membrane remains permeable for a few minutes for small molecules. To further characterize the cellular response postmanipulation, we analyzed levels of oxidative heat or general stress. Although we observed an increased formation of reactive oxygen species by an increase of dichlorofluorescein fluorescence, heat shock protein 70 was not upregulated in laser-treated cells. Additionally, no evidence of stress granule formation was visible by immunofluorescence staining. The data provided in this study help to identify the cellular reactions to gold nanoparticle-mediated laser manipulation.
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
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...
Stochastic volatility and stochastic leverage
Veraart, Almut; Veraart, Luitgard A. M.
2009-01-01
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 correlationparameter between the asset return and the stochastic volatility process. We provide a systematictreatment 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 analyticallytractable and allo...
Oliveira, Roberto Imbuzeiro
2013-01-01
This paper introduces the concept of random context representations for the transition probabilities of a finite-alphabet stochastic process. Processes with these representations generalize context tree processes (a.k.a. variable length Markov chains), and are proven to coincide with processes whose transition probabilities are almost surely continuous functions of the (infinite) past. This is similar to a classical result by Kalikow about continuous transition probabilities. Existence and un...
Isolation and Characterization of Lactic Acid Bacteria (LAB) Produced Exo cellular Polysaccharide
International Nuclear Information System (INIS)
Isolation and characterization of exo cellular polysaccharide was studied in order to evaluate some parameters in the synthesis of exo polysaccharide (EPS) and improve their production through submerged fermentation processes. Isolation strains Lactobacillus delbrueckii ssp bulgaricus (IS1), Lactococcus lactis ssp cremoris (IS2) and Lactobacillus delbrueckii ssp bulgaricus (IS3) were studied in shake flasks using yeast extract, surfactants and different exposure doses of gamma irradiation.The optimum concentration of (EPS) formation (0.762 g/l) by Lactococcus lactis ssp cremoris (IS2), 3.0 (g/l) yeast extract, 1.72 (g/l) at 0.5 (%) surfactant Triton X-100. Also, EPS (1.842 g/l) was produced when Lactococcus lactis ssp cremoris (IS2) exposed to 0.2 kGy dose level.
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.
Berhanu, P; Kolterman, O G; Baron, A; Tsai, P; Olefsky, J M; Brandenburg, D.
1983-01-01
We photolabeled and characterized insulin receptors in isolated adipocytes from normal human subjects and then studied the cellular fate of the labeled insulin-receptor complexes at physiologic temperatures. The biologically active photosensitive insulin derivative, B2(2-nitro-4-azidophenylacetyl)des-PheB1-insulin (NAPA-DP-insulin) was used to photoaffinity label the insulin receptors, and the specifically labeled cellular proteins were identified by sodium dodecyl sulfate-polyacrylamide gel ...
Phenotypic characterization of the bone marrow stem cells used in regenerative cellular therapy
International Nuclear Information System (INIS)
Regenerative medicine is a novel therapeutic method with broad potential for the treatment of various illnesses, based on the use of bone marrow (BM) stem cells, whose phenotypic characterization is limited. The paper deals with the expression of different cell membrane markers in mononuclear BM cells from 14 patients who underwent autologous cell therapy, obtained by medullary puncture and mobilization to peripheral blood, with the purpose of characterizing the different types of cells present in that heterogeneous cellular population and identifying the adhesion molecules involved in their adhesion. A greater presence was observed of adherent stem cells from the marrow stroma in mononuclear cells obtained directly from the BM; a larger population of CD90+cells in mononuclear cells from CD34-/CD45-peripheral blood with a high expression of molecules CD44 and CD62L, which suggests a greater presence of mesenchymal stem cells (MSC) in mobilized cells from the marrow stroma. The higher levels of CD34+cells in peripheral blood stem cells with a low expression of molecules CD117-and DR-suggests the presence of hematopoietic stem cells, hemangioblasts and progenitor endothelial cells mobilized to peripheral circulation. It was found that mononuclear cells from both the BM and peripheral blood show a high presence of stem cells with expression of adhesion molecule CD44 (MMC marker), probably involved in their migration, settling and differentiation
Characterization of memory states of the Preisach operator with stochastic inputs
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The Preisach operator with inputs defined by a Markov process xt is considered. The question we address is: what is the distribution of the random memory state of the Preisach operator at a given time moment t0 in the limit r→∞ of infinitely long input history xt, t0-r≤t≤t0? In order to answer this question, we introduce a Markov chain (called the memory state Markov chain) where the states are pairs (mk,Mk) of elements from the monotone sequences of the local minimum input values mk and the local maximum input values Mk recorded in the memory state and the index k of the elements plays the role of time. We express the transition probabilities of this Markov chain in terms of the transition probabilities of the input stochastic process and show that the memory state Markov chain and the input process generate the same distribution of the memory states. These results are illustrated by several examples of stochastic inputs such as the Wiener and Bernoulli processes and their mixture (we first discuss a discrete version of these processes and then the continuous time and state setting). The memory state Markov chain is then used to find the distribution of the random number of elements in the memory state sequence. We show that this number has the Poisson distribution for the Wiener and Bernoulli processes inputs. In particular, in the discrete setting, the mean value of the number of elements in the memory state scales as lnN, where N is the number of the input states, while the mean time it takes the input to generate this memory state scales as N2 for the Wiener process and as N for the Bernoulli process. A similar relationship between the dimension of the memory state vector and the number of iterations in the numerical realization of the input is shown for the mixture of the Wiener and Bernoulli processes, thus confirming that the memory state Markov chain is an efficient tool for generating the distribution of the Preisach operator memory states
CSI 2264: Characterizing Young Stars in NGC 2264 with Stochastically Varying Light Curves
Stauffer, John; Cody, Ann Marie; Rebull, Luisa; Hillenbrand, Lynne A.; Turner, Neal J.; Carpenter, John; Carey, Sean; Terebey, Susan; Morales-Calderón, María; 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; Medeiros Guimarães, Marcelo; Bouy, Herve; Favata, Fabio
2016-03-01
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. Based on data from the Spitzer and CoRoT missions, as well as the Canada-France-Hawaii Telescope (CFHT) MegaCam CCD, and the European Southern Observatory Very Large Telescope, Paranal Chile, under program 088.C-0239. The CoRoT space mission was developed and is operated by the French space agency CNES, with particpiation of ESA’s RSSD and Science Programmes, Austria, Belgium, Brazil, Germany, and Spain
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.
International Nuclear Information System (INIS)
Highlights: → The present study focused on deformation behavior and failure mechanisms in lattice structure produced by selective laser melting (SLM). → It is demonstrated that heat treatments can be used to increase the energy absorption of an SLM-processed structure. → An in situ testing procedure was introduced, where local strains were calculated by digital image correlation → Shear failure could be predicted by localization using Tresca strains. → 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.
International Nuclear Information System (INIS)
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)
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.
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.
Stochastic volatility and stochastic leverage
DEFF Research Database (Denmark)
Veraart, Almut; Veraart, Luitgard A. M.
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......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...
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.
Principal eigenvalue characterization connected with stochastic particle motion in a finite interval
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Fethi Bin Muhammad Belgacem
2002-01-01
Full Text Available In this paper, we show that despite their distinction, both the Statonovich and Îto s calculi lead to the same reactive Fokker-Planck equation: ∂p∂t−∂∂x[D∂p∂x−bp]=λmp, (1 describing stochastic dynamics of a particle moving under the influence of an indefinite potential m(x,t, a drift b(x,t, and a constant diffusion D. We treat the periodic-parabolic eigenvalue problem (1 for finite domains having absorbing barriers. We show that under conditions required by the maximum principle, the positive principal eigenvalue λ* (and the negative principal λ* eigenvalue is connected to the probability eigendensity function p(x,t by a Raleigh-Ritz like formulation. In the process, we establish the manner of effect of the drift and any inducing potential on the size of the principal eigenvalue. We show that the degree of convexity of the potential plays a major role in this regard.
Smith, L J
1984-11-01
This study was designed to characterize the biochemical, cellular, and morphologic events produced in mice by butylated hydroxytoluene (BHT) and to relate these events to changes in extracellular angiotensin-converting enzyme (ACE) activity. On Day 1 after the administration of BHT, bronchoalveolar lavage (BAL) ACE activity increased 4-fold (p less than 0.001), its specific activity relative to BAL protein increased 3-fold (p less than 0.001), and both type 1 cell damage and endothelial cell damage were detected by electron microscopy. The early increase in BAL ACE activity preceded changes in plasma ACE levels, BAL cell number, protein, lactate, and lactate dehydrogenase (LDH) activity in both plasma and BAL, and the ACE content of alveolar macrophages. On Day 2, BAL ACE activity increased 9-fold, BAL protein increased 4-fold (p less than 0.001), BAL LDH activity increased 34% (p less than 0.05), and the BAL cell count doubled (p less than 0.01). Changes in each animal's appearance, body weight, wet and dry lung weights, and plasma ACE levels occurred between Days 3 and 5. The BAL differential cell count, which consisted of greater than 95% macrophages in uninjured mice, did not change until Day 5 when there was a small increase in polymorphonuclear leukocytes (PMN). On Day 7, the number of PMN peaked, and some of the other measures of lung injury began returning toward normal. These results indicate that BAL ACE activity is a sensitive, early marker of BHT-induced lung injury, which appears to reflect damage to the cells of the alveolar-capillary barrier. In addition, PMN do not appear to play a major role in this model of lung injury. Because of its effects on angiotensin, bradykinin, and prostaglandins, the early release of ACE from damaged cells may modulate the subsequent injury. PMID:6093659
Characterization of CdTe/CdSe quantum dots-transferrin fluorescent probes for cellular labeling
International Nuclear Information System (INIS)
Highlights: ► A convenient method was designed to assess cell efficiency of QDs probes for cellular labeling. ► The relationship between conjugation methods and effectiveness was evaluated clearly. ► QDs-Tf probe synthesized by EDC coupling had the highest labeling efficiency, followed by electrostatic interaction, and dTf coating. - Abstract: In this paper, we prepared three types of transferrin-quantum dots conjugates (QDs-Tf) using three different methods (electrostatic interaction, 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC) coupling, denatured transferrin (dTf) coating). Fluorescence emission spectra, surface characteristics, zeta potentials of quantum dots (QDs) and QDs-Tf fluorescent probes were characterized by spectrophotometer, capillary electrophoresis, and dynamic light scattering. Fluorescent imaging of HeLa cells was also performed by QDs and QDs-Tf fluorescent probes. It was found that the fluorescence imaging performances of QDs-Tf probes prepared by electrostatic interaction and EDC coupling were better compared with the one prepared by dTf coating. Then a real-time single cell detection system was established to quantitatively evaluate cell labeling effects of QDs-Tf fluorescent probes. It was found that for cell labeling efficiency, the proportion of cells labeled by quantum dot probes to a group of cells, QDs-Tf probe prepared by EDC coupling showed the highest labeling efficiency (85.55 ± 3.88%), followed by electrostatic interaction (78.86 ± 9.57%), and dTf coating showed the lowest (40.09 ± 10.2%). This efficiency order was confirmed by flow cytometry results. This study demonstrated the relationship between conjugation methods and the resultant QDs-Tf probes and provided a foundation for choosing appropriate QDs-Tf probes in cell labeling.
Characterization of CdTe/CdSe quantum dots-transferrin fluorescent probes for cellular labeling
Energy Technology Data Exchange (ETDEWEB)
Guan Liyun; Li Yongqiang; Lin Song; Zhang Mingzhen; Chen Jun; Ma Zhiya [Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Department of Biomedical Engineering, Wuhan, HuBei 430074 (China); Zhao Yuandi, E-mail: zydi@mail.hust.edu.cn [Britton Chance Center for Biomedical Photonics, Wuhan National Laboratory for Optoelectronics-Huazhong University of Science and Technology, Department of Biomedical Engineering, Wuhan, HuBei 430074 (China)
2012-09-05
Highlights: Black-Right-Pointing-Pointer A convenient method was designed to assess cell efficiency of QDs probes for cellular labeling. Black-Right-Pointing-Pointer The relationship between conjugation methods and effectiveness was evaluated clearly. Black-Right-Pointing-Pointer QDs-Tf probe synthesized by EDC coupling had the highest labeling efficiency, followed by electrostatic interaction, and dTf coating. - Abstract: In this paper, we prepared three types of transferrin-quantum dots conjugates (QDs-Tf) using three different methods (electrostatic interaction, 1-ethyl-3-(3-dimethylaminopropyl)carbodiimide hydrochloride (EDC) coupling, denatured transferrin (dTf) coating). Fluorescence emission spectra, surface characteristics, zeta potentials of quantum dots (QDs) and QDs-Tf fluorescent probes were characterized by spectrophotometer, capillary electrophoresis, and dynamic light scattering. Fluorescent imaging of HeLa cells was also performed by QDs and QDs-Tf fluorescent probes. It was found that the fluorescence imaging performances of QDs-Tf probes prepared by electrostatic interaction and EDC coupling were better compared with the one prepared by dTf coating. Then a real-time single cell detection system was established to quantitatively evaluate cell labeling effects of QDs-Tf fluorescent probes. It was found that for cell labeling efficiency, the proportion of cells labeled by quantum dot probes to a group of cells, QDs-Tf probe prepared by EDC coupling showed the highest labeling efficiency (85.55 {+-} 3.88%), followed by electrostatic interaction (78.86 {+-} 9.57%), and dTf coating showed the lowest (40.09 {+-} 10.2%). This efficiency order was confirmed by flow cytometry results. This study demonstrated the relationship between conjugation methods and the resultant QDs-Tf probes and provided a foundation for choosing appropriate QDs-Tf probes in cell labeling.
Flaw tolerance vs. performance: A tradeoff in metallic glass cellular structures
International Nuclear Information System (INIS)
Stochastic cellular structures are prevalent in nature and engineering materials alike. They are difficult to manipulate and study systematically and almost always contain imperfections. To design and characterize various degrees of imperfections in perfect periodic, stochastic and natural cellular structures, we fabricate a broad range of metallic glass cellular structures from perfectly periodic to highly stochastic by using a novel artificial microstructure approach based on thermoplastic replication of metallic glasses. For these cellular structures, precisely controlled imperfections are implemented and their effects on the mechanical response are evaluated. It is found that the mechanical performance of the periodic structures is generally superior to that of the stochastic structures. However, the stochastic structures experience a much higher tolerance to flaws than the periodic structure, especially in the plastic regime. The different flaw tolerance is explained by the stress distribution within the various structures, which leads to an overall 'strain-hardening' behavior of the stochastic structure compared to a 'strain-softening' behavior in the periodic structure. Our findings reveal how structure, 'strain-hardening' and flaw tolerance are microscopically related in structural materials
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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
Digital Repository Service at National Institute of Oceanography (India)
Chakraborty, B.; Haris, K.
characterize the patchiness of the seafloor (Table 1). The backscatter and bathymetry image blocks having 400 x 400 pixels, were classified according to the degree of seepage based on the backscatter strength as well as fractal dimension (determined using... box-dimension technique). Sample blocks F20 J19 F07 Q19 S23 N25 Seepage type Very high High Moderate Low Very low No Mean Backscatter (dB) -31.58 -34.40 -38.99 -38.96 -43.28 -42...
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
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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
Evaluation of soil characterization technologies using a stochastic, value-of-information approach
International Nuclear Information System (INIS)
The US Department of Energy has initiated an integrated demonstration program to develop and compare new technologies for the characterization of uranium-contaminated soils. As part of this effort, a performance-assessment task was funded in February, 1993 to evaluate the field tested technologies. Performance assessment can be cleaned as the analysis that evaluates a system's, or technology's, ability to meet the criteria specified for performance. Four new technologies were field tested at the Fernald Environmental Management Restoration Co. in Ohio. In the next section, the goals of this performance assessment task are discussed. The following section discusses issues that must be resolved if the goals are to be successfully met. The author concludes with a discussion of the potential benefits to performance assessment of the approach taken. This paper is intended to be the first of a series of documentation that describes the work. Also in this proceedings is a paper on the field demonstration at the Fernald site and a description of the technologies (Tidwell et al, 1993) and a paper on the application of advanced geostatistical techniques (Rautman, 1993). The overall approach is to simply demonstrate the applicability of concepts that are well described in the literature but are not routinely applied to problems in environmental remediation, restoration, and waste management. The basic geostatistical concepts are documented in Clark (1979) and in Issaks and Srivastava (1989). Advanced concepts and applications, along with software, are discussed in Deutsch and Journel (1992). Integration of geostatistical modeling with a decision-analytic framework is discussed in Freeze et al (1992). Information-theoretic and probabilistic concepts are borrowed from the work of Shannon (1948), Jaynes (1957), and Harr (1987). The author sees the task as one of introducing and applying robust methodologies with demonstrated applicability in other fields to the problem at hand
Ohira, Toru
2006-01-01
We present a simple dynamical model to address the question of introducing a stochastic nature in a time variable. This model includes noise in the time variable but not in the "space" variable, which is opposite to the normal description of stochastic dynamics. The notable feature is that these models can induce a "resonance" with varying noise strength in the time variable. Thus, they provide a different mechanism for stochastic resonance, which has been discussed within the normal context ...
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Jonathan M Behrendt
Full Text Available The efficient transport of micron-sized beads into cells, via a non-endocytosis mediated mechanism, has only recently been described. As such there is considerable scope for optimization and exploitation of this procedure to enable imaging and sensing applications to be realized. Herein, we report the design, synthesis and characterization of fluorescent microsphere-based cellular delivery agents that can also carry biological cargoes. These core-shell polymer microspheres possess two distinct chemical environments; the core is hydrophobic and can be labeled with fluorescent dye, to permit visual tracking of the microsphere during and after cellular delivery, whilst the outer shell renders the external surfaces of the microspheres hydrophilic, thus facilitating both bioconjugation and cellular compatibility. Cross-linked core particles were prepared in a dispersion polymerization reaction employing styrene, divinylbenzene and a thiol-functionalized co-monomer. These core particles were then shelled in a seeded emulsion polymerization reaction, employing styrene, divinylbenzene and methacrylic acid, to generate orthogonally functionalized core-shell microspheres which were internally labeled via the core thiol moieties through reaction with a thiol reactive dye (DY630-maleimide. Following internal labeling, bioconjugation of green fluorescent protein (GFP to their carboxyl-functionalized surfaces was successfully accomplished using standard coupling protocols. The resultant dual-labeled microspheres were visualized by both of the fully resolvable fluorescence emissions of their cores (DY630 and shells (GFP. In vitro cellular uptake of these microspheres by HeLa cells was demonstrated conventionally by fluorescence-based flow cytometry, whilst MTT assays demonstrated that 92% of HeLa cells remained viable after uptake. Due to their size and surface functionalities, these far-red-labeled microspheres are ideal candidates for in vitro, cellular
Characterizing SMS spam in a large cellular network via mining victim spam reports
Skudlark, Ann
2014-01-01
In this paper a study of SMS messages in a large US based cellular carrier utilizing both customer reported SMS spam and network Call Detail Records (CDRs) is conducted to develop a comprehensive understanding of SMS spam in order to develop strategies and approaches to detect and control SMS spam activity. The analysis provides insights into content classification of spam campaigns as well as spam characteristics based on sending patterns, tenure and geolocation.
Jin, Kelly
2012-01-01
Dinoflagellate bioluminescence represents a dramatic response to mechanical stress found in nature. The cellular mechanisms that govern this pathway, however, are not completely understood. The objective of this thesis is to build and expand from previous studies to explore the mechanosensitive properties of dinoflagellate bioluminescence. Chapter I tests the hypothesis that the signaling pathway involves a stretch-activated component. Chapter I uses two separate, measurable types of biolumin...
Characterization of the Interaction of Lassa Fever Virus with Its Cellular Receptor α-Dystroglycan
Kunz, Stefan; Rojek, Jillian M.; Perez, Mar; Spiropoulou, Christina F.; Oldstone, Michael B. A.
2005-01-01
The cellular receptor for the Old World arenaviruses Lassa fever virus (LFV) and lymphocytic choriomeningitis virus (LCMV) has recently been identified as α-dystroglycan (α-DG), a cell surface receptor that provides a molecular link between the extracellular matrix and the actin-based cytoskeleton. In the present study, we show that LFV binds to α-DG with high affinity in the low-nanomolar range. Recombinant vesicular stomatitis virus pseudotyped with LFV glycoprotein (GP) adopted the recepto...
Characterization of inhibitors of phosphodiesterase 1C on a human cellular system.
Dunkern, Torsten R; Hatzelmann, Armin
2007-09-01
Different inhibitors of the Ca(2+)/calmodulin-stimulated phosphodiesterase 1 family have been described and used for the examination of phosphodiesterase 1 in cellular, organ or animal models. However, the inhibitors described differ in potency and selectivity for the different phosphodiesterase family enzymes, and in part exhibit additional pharmacodynamic actions. In this study, we demonstrate that phosphodiesterase 1C is expressed in the human glioblastoma cell line A172 with regard to mRNA, protein and activity level, and that lower activities of phosphodiesterase 2, phosphodiesterase 3, phosphodiesterase 4 and phosphodiesterase 5 are also present. The identity of the phosphodiesterase 1C activity detected was verified by downregulation of the mRNA and protein through human phosphodiesterase 1C specific small interfering RNA. In addition, the measured K(m) values (cAMP, 1.7 microm; cGMP, 1.3 microm) are characteristic of phosphodiesterase 1C. We demonstrate that treatment with the Ca(2+) ionophore ionomycin increases intracellular Ca(2+) in a concentration-dependent way without affecting cell viability. Under conditions of enhanced intracellular Ca(2+) concentration, a rapid increase in cAMP levels caused by the adenylyl cyclase activator forskolin was abolished, indicating the involvement of Ca(2+)-activated phosphodiesterase 1C. The reduction of forskolin-stimulated cAMP levels was reversed by phosphodiesterase 1 inhibitors in a concentration-dependent way. Using this cellular system, we compared the cellular potency of published phosphodiesterase 1 inhibitors, including 8-methoxymethyl-3-isobutyl-1-methylxanthine, vinpocetine, SCH51866, and two established phosphodiesterase 1 inhibitors developed by Schering-Plough (named compounds 31 and 30). We demonstrate that up to 10 microm 8-methoxymethyl-3-isobutyl-1-methylxanthine and vinpocetine had no effect on the reduction of forskolin-stimulated cAMP levels by ionomycin, whereas the more selective and up to 10
Hanna, A. C.; Moysey, S. M.; Murdoch, L. C.
2014-12-01
Carbon injection projects introduce several operational, management and risk-assessment challenges, including leakage of carbon dioxide through fractures or derelict wells, reactivation of dormant faults, topographic subsidence/uplift, and contamination of existing groundwater resources. In this work we evaluate whether geomechanical measurements can be used within a stochastic estimation framework to characterize physical and geometric parameters of a system undergoing injection.A numerical forward model built in COMSOL Multiphysics is used to solve the equations governing linear poroelasticity to compute the geomechanical signals (e.g. pressure, strain, tilt and displacement) produced during injection given a set of model parameters (e.g. Young's modulus, Poisson's ratio, and permeability). A hybrid Markov Chain Monte Carlo/multiobjective genetic algorithm is then used to iteratively generate a sequence of parameter estimates; distributed high performance computing is used to efficiently evaluate the computationally expensive forward model for each set of parameters. The set of posterior parameter estimates is then used to find the mean and uncertainty of each parameter subject to measurement limitations (noise, model error, spatial/temporal constraints).We find that geomechanical measurements collected within the target formation can be used to accurately and efficiently estimate the physical parameters of the formation. We also observe that measurements taken in an overlying confining unit can be used to estimate the parameters of both the confining unit and target aquifer. This suggests that measurements made in the upper confining unit could mitigate drilling costs as well as reduce the risk of puncturing the confining unit. Using various combinations of synthetic measurements from the confining unit and target aquifer, we have also been able to resolve the geometry and physical parameters of heterogeneities analogous to fluvial gravel lenses and faults
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…
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
Decentralized stochastic control
Speyer, J. L.
1980-01-01
Decentralized stochastic control is characterized by being decentralized in that the information to one controller is not the same as information to another controller. The system including the information has a stochastic or uncertain component. This complicates the development of decision rules which one determines under the assumption that the system is deterministic. The system is dynamic which means the present decisions affect future system responses and the information in the system. This circumstance presents a complex problem where tools like dynamic programming are no longer applicable. These difficulties are discussed from an intuitive viewpoint. Particular assumptions are introduced which allow a limited theory which produces mechanizable affine decision rules.
Hu, B. L. (Bei-Lok)
1999-01-01
We give a summary of the status of current research in stochastic semiclassical gravity and suggest directions for further investigations. This theory generalizes the semiclassical Einstein equation to an Einstein-Langevin equation with a stochastic source term arising from the fluctuations of the energy-momentum tensor of quantum fields. We mention recent efforts in applying this theory to the study of black hole fluctuations and backreaction problems, linear response of hot flat space, and ...
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.
A High-Precision Micropipette Sensor for Cellular-Level Real-Time Thermal Characterization
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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.
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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.
Characterization of cellular traction forces at the single-molecule level
Dunn, Alexander
2013-03-01
The ability of cells to generate and respond to mechanical cues is an essential aspect of stem cell differentiation, embryonic development, and our senses of touch and hearing. However, our understanding of the roles of mechanical force in cell biology remains in its infancy, due largely to a lack of tools that measure the forces generated by living cells at the molecular scale. Here we describe a new technique termed Molecular Force Microscopy (MFM) that visualizes the forces exerted by single cellular adhesion molecules with nm, pN, and sub-second resolutions. MFM uses novel FRET-based molecular tension sensors that bind to a glass coverslip and present a binding site for integrins, a ubiquitous class of cell adhesion proteins. Cell-generated forces stretch the MFM sensor molecules, resulting in decreased FRET with increasing load that can be imaged at the single-molecule level. Human foreskin fibroblasts adhere to surfaces functionalized with the MFM probes and develop robust focal adhesions. FRET values measured using MFM indicate forces of between 1 and 4 pN per integrin, thus providing the first direct measurement of the tension per integrin molecule necessary to form stable adhesions. The relatively narrow force distribution suggests that mechanical tension is subject to exquisite feedback and control at the molecular level.
A high-precision micropipette sensor for cellular-level real-time thermal characterization.
Shrestha, Ramesh; Choi, Tae-Youl; Chang, Wonseok; Kim, Donsik
2011-01-01
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. PMID:22164108
Characterization of the Interaction of Lassa Fever Virus with Its Cellular Receptor α-Dystroglycan
Kunz, Stefan; Rojek, Jillian M.; Perez, Mar; Spiropoulou, Christina F.; Oldstone, Michael B. A.
2005-01-01
The cellular receptor for the Old World arenaviruses Lassa fever virus (LFV) and lymphocytic choriomeningitis virus (LCMV) has recently been identified as α-dystroglycan (α-DG), a cell surface receptor that provides a molecular link between the extracellular matrix and the actin-based cytoskeleton. In the present study, we show that LFV binds to α-DG with high affinity in the low-nanomolar range. Recombinant vesicular stomatitis virus pseudotyped with LFV glycoprotein (GP) adopted the receptor binding characteristics of LFV and depended on α-DG for infection of cells. Mapping of the binding site of LFV on α-DG revealed that LFV binding required the same domains of α-DG that are involved in the binding of LCMV. Further, LFV was found to efficiently compete with laminin α1 and α2 chains for α-DG binding. Together with our previous studies on receptor binding of the prototypic immunosuppressive LCMV isolate LCMV clone 13, these findings indicate a high degree of conservation in the receptor binding characteristics between the highly human-pathogenic LFV and murine-immunosuppressive LCMV isolates. PMID:15857984
Kunz, Stefan; Rojek, Jillian M; Perez, Mar; Spiropoulou, Christina F; Oldstone, Michael B A
2005-05-01
The cellular receptor for the Old World arenaviruses Lassa fever virus (LFV) and lymphocytic choriomeningitis virus (LCMV) has recently been identified as alpha-dystroglycan (alpha-DG), a cell surface receptor that provides a molecular link between the extracellular matrix and the actin-based cytoskeleton. In the present study, we show that LFV binds to alpha-DG with high affinity in the low-nanomolar range. Recombinant vesicular stomatitis virus pseudotyped with LFV glycoprotein (GP) adopted the receptor binding characteristics of LFV and depended on alpha-DG for infection of cells. Mapping of the binding site of LFV on alpha-DG revealed that LFV binding required the same domains of alpha-DG that are involved in the binding of LCMV. Further, LFV was found to efficiently compete with laminin alpha1 and alpha2 chains for alpha-DG binding. Together with our previous studies on receptor binding of the prototypic immunosuppressive LCMV isolate LCMV clone 13, these findings indicate a high degree of conservation in the receptor binding characteristics between the highly human-pathogenic LFV and murine-immunosuppressive LCMV isolates. PMID:15857984
International Nuclear Information System (INIS)
The objective of this research thesis is to characterize the expression of a mammal gene, called Kin-17, which codes for a protein which has a structural homology with the RecA protein of E. coli. This protein plays a crucial role in the cellular response to irradiations and in mutagenesis. In order to better understand the Kin 17 protein function, the author determined the Kin 17 gene expression profile in tissues and cells in culture. It appears that this expression is ubiquitous and weak. The Kin 17 protein quantity and localisation are also studied. The author suggests that this protein belongs to an intra-nuclear network of proteins required during cell growth, and might influence biological processes related to the cellular cycle. The co-localisation of the protein with the T-antigen is studied by immunofluorescence. The expression profile of different Kin-17 genes in cells after UV irradiation has been studied. The obtained results and observations suggest that the Kin 17 protein intervenes in a biological process which allows a cell to counterbalance toxic effects of UV radiations
Directory of Open Access Journals (Sweden)
Cynthia L Araujo-Palomares
Full Text Available Rho-type GTPases are key regulators that control eukaryotic cell polarity, but their role in fungal morphogenesis is only beginning to emerge. In this study, we investigate the role of the CDC-42 - RAC - CDC-24 module in Neurospora crassa. rac and cdc-42 deletion mutants are viable, but generate highly compact colonies with severe morphological defects. Double mutants carrying conditional and loss of function alleles of rac and cdc-42 are lethal, indicating that both GTPases share at least one common essential function. The defects of the GTPase mutants are phenocopied by deletion and conditional alleles of the guanine exchange factor (GEF cdc-24, and in vitro GDP-GTP exchange assays identify CDC-24 as specific GEF for both CDC-42 and RAC. In vivo confocal microscopy shows that this module is organized as membrane-associated cap that covers the hyphal apex. However, the specific localization patterns of the three proteins are distinct, indicating different functions of RAC and CDC-42 within the hyphal tip. CDC-42 localized as confined apical membrane-associated crescent, while RAC labeled a membrane-associated ring excluding the region labeled by CDC42. The GEF CDC-24 occupied a strategic position, localizing as broad apical membrane-associated crescent and in the apical cytosol excluding the Spitzenkörper. RAC and CDC-42 also display distinct localization patterns during branch initiation and germ tube formation, with CDC-42 accumulating at the plasma membrane before RAC. Together with the distinct cellular defects of rac and cdc-42 mutants, these localizations suggest that CDC-42 is more important for polarity establishment, while the primary function of RAC may be maintaining polarity. In summary, this study identifies CDC-24 as essential regulator for RAC and CDC-42 that have common and distinct functions during polarity establishment and maintenance of cell polarity in N. crassa.
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
Dai, Yongming; Yao, Qiuying; Wu, Guangyu; Wu, Dongmei; Wu, Lianming; Zhu, Li; Xue, Rong; Xu, Jianrong
2016-07-01
The aim of this study was to evaluate the role of diffusion kurtosis imaging (DKI) in the characterization of clear cell renal cell carcinoma (ccRCC) and to correlate DKI parameters with tumor cellularity. Fifty-nine patients with pathologically diagnosed ccRCCs were evaluated by DKI on a 3-T scanner. Regions of interest were drawn on the maps of the mean diffusion coefficient (MD) and mean diffusion kurtosis (MK). All ccRCCs were histologically graded according to the Fuhrman classification system. Tumor cellularity was measured by the nuclear-to-cytoplasm (N/C) ratio and the number of tumor cell nuclei (NTCN). ccRCCs were classified as grade 1 (n = 23), grade 2 (n = 24), grade 3 (n = 10) and grade 4 (n = 3). Both MD and MK could readily discriminate between normal renal parenchyma and ccRCCs (p 0.05) for both MD and MK. With regard to NTCN, no significant difference was found between any two grades (p > 0.05), and the N/C ratio changed significantly with grade (p correlations were found between MK and MD (r = -0.56, p r = -0.36, p correlated (r = 0.45, p = 0.003). DKI could quantitatively characterize ccRCC with different grades by probing non-Gaussian diffusion properties related to changes in the tumor microenvironment or tissue complexities in the tumor. Copyright © 2016 John Wiley & Sons, Ltd. PMID:27119793
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
International Nuclear Information System (INIS)
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.
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.
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...
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.
Biochemical characterization and cellular effects of CADASIL mutants of NOTCH3.
Directory of Open Access Journals (Sweden)
He Meng
Full Text Available 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 muscle gene regulation. We demonstrate that NOTCH3 forms heterodimers with NOTCH1, NOTCH3, and NOTCH4. R90C and C49Y mutant NOTCH3 form complexes which are more resistant to detergents than wild type NOTCH3 complexes. Using quantitative NOTCH3-luciferase clearance assays, we found significant inhibition of mutant NOTCH3 clearance. In coculture assays of NOTCH function, overexpressed wild type and mutant NOTCH3 significantly repressed NOTCH-regulated smooth muscle transcripts and potently impaired the activity of three independent smooth muscle promoters. Wildtype and R90C recombinant NOTCH3 proteins applied to cell cultures also blocked canonical Notch fuction. We conclude that CADASIL mutants of NOTCH3 complex with NOTCH1, 3, and 4, slow NOTCH3 clearance, and that overexpressed wild type and mutant NOTCH3 protein interfere with key NOTCH-mediated functions in smooth muscle cells.
Billing, Anja M; Ben Hamidane, Hisham; Dib, Shaima S; Cotton, Richard J; Bhagwat, Aditya M; Kumar, Pankaj; Hayat, Shahina; Yousri, Noha A; Goswami, Neha; Suhre, Karsten; Rafii, Arash; Graumann, Johannes
2016-01-01
Mesenchymal stem cells (MSC) are multipotent cells with great potential in therapy, reflected by more than 500 MSC-based clinical trials registered with the NIH. MSC are derived from multiple tissues but require invasive harvesting and imply donor-to-donor variability. Embryonic stem cell-derived MSC (ESC-MSC) may provide an alternative, but how similar they are to ex vivo MSC is unknown. Here we performed an in depth characterization of human ESC-MSC, comparing them to human bone marrow-derived MSC (BM-MSC) as well as human embryonic stem cells (hESC) by transcriptomics (RNA-seq) and quantitative proteomics (nanoLC-MS/MS using SILAC). Data integration highlighted and validated a central role of vesicle-mediated transport and exosomes in MSC biology and also demonstrated, through enrichment analysis, their versatility and broad application potential. Particular emphasis was placed on comparing profiles between ESC-MSC and BM-MSC and assessing their equivalency. Data presented here shows that differences between ESC-MSC and BM-MSC are similar in magnitude to those reported for MSC of different origin and the former may thus represent an alternative source for therapeutic applications. Finally, we report an unprecedented coverage of MSC CD markers, as well as membrane associated proteins which may benefit immunofluorescence-based applications and contribute to a refined molecular description of MSC. PMID:26857143
International Nuclear Information System (INIS)
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
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.
Synthesis and characterization of xanthan–hydroxyapatite nanocomposites for cellular uptake
International Nuclear Information System (INIS)
In this work xanthan–nanohydroxyapatite (XnHAp) and its equivalent strontium substituted (XnHApSr) were synthesized by the precipitation of nanohydroxyapatite in xanthan aqueous solution, characterized and compared to conventional hydroxyapatite particles (HAp). XnHAp and XnHApSr were less crystalline than HAp, as revealed by X-ray diffraction. Xanthan chains enriched the surface of XnHAp and XnHApSr particles, increasing the zeta potential values from −(7 ± 1) mV, determined for HAp, to −(17 ± 3) mV and −(25 ± 3) mV, respectively. This effect led to high colloidal stability of XnHAp and XnHApSr dispersions and acicular particles (140 ± 10) nm long and (8 ± 2) nm wide, as determined by scanning electron microscopy and atomic force microscopy. XnHAp and XnHApSr particles were added to xanthan hydrogels to produce compatible nanocomposites (XCA/XnHAp and XCA/XnHApSr). Dried nanocomposites presented surface energy, Young's modulus and stress at break values comparable to those determined for bare xanthan matrix. Moreover, adding XnHAp or XnHApSr nanoparticles to xanthan hydrogel did not influence its porous morphology, gel content and swelling ratio. XCA/XnHAp and XCA/XnHApSr composites proved to be suitable for osteoblast growth and particularly XCA/XnHapSr composites induced higher alkaline phosphatase activity. - Highlights: • Hydroxyapatites with or without strontium were prepared in xanthan solution. • Xanthan chains enriched the surface of hydroxyapatite nanoparticles (HAp). • Xanthan modified HAp and xanthan hydrogels formed compatible nanocomposites. • Nanocomposites are suitable for bone mineralization, particularly those with Sr
Synthesis and characterization of xanthan–hydroxyapatite nanocomposites for cellular uptake
Energy Technology Data Exchange (ETDEWEB)
Bueno, Vania Blasques; Bentini, Ricardo; Catalani, Luiz Henrique [Instituto de Química, Universidade de São Paulo, P.O. Box 26077, São Paulo, SP 05513-970 (Brazil); Barbosa, Leandro R.S. [Instituto de Física, DFGE, Universidade de São Paulo, São Paulo, 05508-090 SP (Brazil); Petri, Denise Freitas Siqueira, E-mail: dfsp@usp.br [Instituto de Química, Universidade de São Paulo, P.O. Box 26077, São Paulo, SP 05513-970 (Brazil)
2014-04-01
In this work xanthan–nanohydroxyapatite (XnHAp) and its equivalent strontium substituted (XnHApSr) were synthesized by the precipitation of nanohydroxyapatite in xanthan aqueous solution, characterized and compared to conventional hydroxyapatite particles (HAp). XnHAp and XnHApSr were less crystalline than HAp, as revealed by X-ray diffraction. Xanthan chains enriched the surface of XnHAp and XnHApSr particles, increasing the zeta potential values from −(7 ± 1) mV, determined for HAp, to −(17 ± 3) mV and −(25 ± 3) mV, respectively. This effect led to high colloidal stability of XnHAp and XnHApSr dispersions and acicular particles (140 ± 10) nm long and (8 ± 2) nm wide, as determined by scanning electron microscopy and atomic force microscopy. XnHAp and XnHApSr particles were added to xanthan hydrogels to produce compatible nanocomposites (XCA/XnHAp and XCA/XnHApSr). Dried nanocomposites presented surface energy, Young's modulus and stress at break values comparable to those determined for bare xanthan matrix. Moreover, adding XnHAp or XnHApSr nanoparticles to xanthan hydrogel did not influence its porous morphology, gel content and swelling ratio. XCA/XnHAp and XCA/XnHApSr composites proved to be suitable for osteoblast growth and particularly XCA/XnHapSr composites induced higher alkaline phosphatase activity. - Highlights: • Hydroxyapatites with or without strontium were prepared in xanthan solution. • Xanthan chains enriched the surface of hydroxyapatite nanoparticles (HAp). • Xanthan modified HAp and xanthan hydrogels formed compatible nanocomposites. • Nanocomposites are suitable for bone mineralization, particularly those with Sr.
Stochastic gene expression with bursting and positive feedback
Platini, Thierry; Pendar, Hodjat; Kulkarni, Rahul
2012-02-01
Stochasticity (or noise) in the process of gene expression can play a critical role in cellular circuits that control switching between probabilistic cell-fate decisions in diverse organisms. Such circuits often include positive feedback loops as critical elements. In some cases (e.g. HIV-1 viral infections), switching between different cell fates occurs even in the absence of bistability in the underlying deterministic model. To characterize the role of noise in such systems, we analyze a simple gene expression circuit that includes contributions from both transcriptional and translational bursting and positive feedback effects. Using a combination of analytical approaches and stochastic simulations, we explore how the underlying parameters control the corresponding mean and variance in protein distributions.
Stochasticity in the Josephson map
International Nuclear Information System (INIS)
The Josephson map describes nonlinear dynamics of systems characterized by standard map with the uniform external bias superposed. The intricate structures of the phase space portrait of the Josephson map are examined on the basis of the tangent map associated with the Josephson map. Numerical observation of the stochastic diffusion in the Josephson map is examined in comparison with the renormalized diffusion coefficient calculated by the method of characteristic function. The global stochasticity of the Josephson map occurs at the values of far smaller stochastic parameter than the case of the standard map. (author)
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.
International Nuclear Information System (INIS)
Stochastic cooling is the damping of betatron oscillations and momentum spread of a particle beam by a feedback system. In its simplest form, a pickup electrode detects the transverse positions or momenta of particles in a storage ring, and the signal produced is amplified and applied downstream to a kicker. The time delay of the cable and electronics is designed to match the transit time of particles along the arc of the storage ring between the pickup and kicker so that an individual particle receives the amplified version of the signal it produced at the pick-up. If there were only a single particle in the ring, it is obvious that betatron oscillations and momentum offset could be damped. However, in addition to its own signal, a particle receives signals from other beam particles. In the limit of an infinite number of particles, no damping could be achieved; we have Liouville's theorem with constant density of the phase space fluid. For a finite, albeit large number of particles, there remains a residue of the single particle damping which is of practical use in accumulating low phase space density beams of particles such as antiprotons. It was the realization of this fact that led to the invention of stochastic cooling by S. van der Meer in 1968. Since its conception, stochastic cooling has been the subject of much theoretical and experimental work. The earliest experiments were performed at the ISR in 1974, with the subsequent ICE studies firmly establishing the stochastic cooling technique. This work directly led to the design and construction of the Antiproton Accumulator at CERN and the beginnings of p anti p colliding beam physics at the SPS. Experiments in stochastic cooling have been performed at Fermilab in collaboration with LBL, and a design is currently under development for a anti p accumulator for the Tevatron
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 to the...... result is obtained and applied. Moreover, martingales indexed by the whole real line is studied and characterized and the thesis is concluded with a study of stationary solutions of the Langevin equation....
Foliated stochastic calculus: Harmonic measures
Catuogno, Pedro J.; Ledesma, Diego S.; 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.
Identifiability in stochastic models
1992-01-01
The problem of identifiability is basic to all statistical methods and data analysis, occurring in such diverse areas as Reliability Theory, Survival Analysis, and Econometrics, where stochastic modeling is widely used. Mathematics dealing with identifiability per se is closely related to the so-called branch of ""characterization problems"" in Probability Theory. This book brings together relevant material on identifiability as it occurs in these diverse fields.
Stochastic Weighted Fractal Networks
Carletti, Timoteo
2010-01-01
In this paper we introduce new models of complex weighted networks sharing several properties with fractal sets: the deterministic non-homogeneous weighted fractal networks and the stochastic weighted fractal networks. Networks of both classes can be completely analytically characterized in terms of the involved parameters. The proposed algorithms improve and extend the framework of weighted fractal networks recently proposed in (T. Carletti & S. Righi, in press Physica A, 2010)
Plata, J.
2016-01-01
We study the dynamics of a classical nonlinear oscillator subject to noise and driven by a sinusoidal force. In particular, we give an analytical identification of the mechanisms responsible for the supernarrow peaks observed recently in the spectrum of a mechanical realization of the system. Our approach, based on the application of averaging techniques, simulates standard detection schemes used in practice. The spectral peaks, detected in a range of parameters corresponding to the existence of two attractors in the deterministic system, are traced to characteristics already present in the linearized stochastic equations. It is found that, for specific variations of the parameters, the characteristic frequencies near the attractors converge on the driving frequency and, as a consequence, the widths of the peaks in the spectrum are significantly reduced. The implications of the study to the control of the observed coherent response of the system are discussed.
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
Directory of Open Access Journals (Sweden)
Sergey Shityakov
2015-06-01
Full Text Available The objective of the present investigation was to study the ability of sulfobutylether-β-cyclodextrin (SBEβCD to form an inclusion complex with sevoflurane (SEV, a volatile anesthetic with poor water solubility. The inclusion complex was prepared, characterized and its cellular toxicity and blood-brain barrier (BBB permeation potential of the formulated SEV have also been examined for the purpose of controlled drug delivery. The SEV-SBEβCD complex was nontoxic to the primary brain microvascular endothelial (pEND cells at a clinically relevant concentration of sevoflurane. The inclusion complex exhibited significantly higher BBB permeation profiles as compared with the reference substance (propranolol concerning calculated apparent permeability values (Papp. In addition, SEV binding affinity to SBEβCD was confirmed by a minimal Gibbs free energy of binding (ΔGbind value of −1.727 ± 0.042 kcal·mol−1 and an average binding constant (Kb of 53.66 ± 9.24 mM indicating rapid drug liberation from the cyclodextrin amphiphilic cavity.
Shityakov, Sergey; Puskás, István; Pápai, Katalin; Salvador, Ellaine; Roewer, Norbert; Förster, Carola; Broscheit, Jens-Albert
2015-01-01
The objective of the present investigation was to study the ability of sulfobutylether-β-cyclodextrin (SBEβCD) to form an inclusion complex with sevoflurane (SEV), a volatile anesthetic with poor water solubility. The inclusion complex was prepared, characterized and its cellular toxicity and blood-brain barrier (BBB) permeation potential of the formulated SEV have also been examined for the purpose of controlled drug delivery. The SEV-SBEβCD complex was nontoxic to the primary brain microvascular endothelial (pEND) cells at a clinically relevant concentration of sevoflurane. The inclusion complex exhibited significantly higher BBB permeation profiles as compared with the reference substance (propranolol) concerning calculated apparent permeability values (Papp). In addition, SEV binding affinity to SBEβCD was confirmed by a minimal Gibbs free energy of binding (ΔGbind) value of -1.727 ± 0.042 kcal·mol-1 and an average binding constant (Kb) of 53.66 ± 9.24 mM indicating rapid drug liberation from the cyclodextrin amphiphilic cavity. PMID:26046323
Reasor, Daniel; Clausen, Jonathan; Aidun, Cyrus
2010-11-01
In small vessels, the cellular nature of blood is of utmost importance. The investigation of the non-Newtonian effects of blood for a complete range of hematocrit values and shear rates requires the direct numerical simulation (DNS) of individual red blood cells (RBCs) immersed in Newtonian blood plasma with hemoglobin within. Consequently, a coarse-grained spectrin-link (SL) RBC membrane model is coupled with a highly scalable lattice-Boltzmann (LB) flow solver to capture RBC dynamics in isolation and in dense suspensions of O(1,000) RBCs at realistic hematocrit values. Validation results include experimental comparisons with results for isolated RBCs tumbling, tank-treading, deforming in the wheel configuration, and parachuting in a microvessel-sized rigid tube. The rheology of blood is analyzed via LB-SL simulations of RBC suspensions at physiological concentrations. The results characterize the effect of the RBC deformation on the viscosity, normal stress differences, and particle pressure. Also, a demonstration of the Fahraeus effect is included which correlates the cell-depleted wall layer thickness with tube diameter for a variety of rigid microvessel-sized tube sizes. Lastly, the Fahraeus--Lindqvist effect is demonstrated using the apparent viscosity obtained from these simulations.
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.
Shephard, Neil
2005-01-01
Stochastic volatility (SV) is the main concept used in the fields of financial economics and mathematical finance to deal with the endemic time-varying volatility and codependence found in financial markets. Such dependence has been known for a long time, early comments include Mandelbrot (1963) and Officer (1973). It was also clear to the founding fathers of modern continuous time finance that homogeneity was an unrealistic if convenient simplification, e.g. Black and Scholes (1972, p. 416) ...
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
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
International Nuclear Information System (INIS)
A stochastic representation of the lithologic units and associated hydrogeologic parameters of the potential high-level nuclear waste repository are developed for use in performance-assessment calculations, including the Total-System Performance Assessment for Yucca Mountain-SNL Second Iteration (TSPA-1993). A simplified lithologic model has been developed based on the physical characteristics of the welded and nonwelded units at Yucca Mountain. Ten hydrogeologic units are developed from site-specific data (lithologic and geophysical logs and core photographs) obtained from the unsaturated and saturated zones. The three-dimensional geostatistical model of the ten hydrogeologic units is based on indicator-coding techniques and improves on the two-dimensional model developed for TSPA91. The hydrogeologic properties (statistics and probability distribution functions) are developed from the results of laboratory tests and in-situ aquifer tests or are derived through fundamental relationships. Hydrogeologic properties for matrix properties, bulk conductivities, and fractures are developed from existing site specific data. Extensive data are available for matrix porosity, bulk density, and matrix saturated conductivity. For other hydrogeologic properties, the data are minimal or nonexistent. Parameters for the properties are developed as beta probability distribution functions. For the model units without enough data for analysis, parameters are developed as analogs to existing units. A relational, analytic approach coupled with bulk conductivity parameters is used to develop fracture parameters based on the smooth-wall-parallel-plate theory. An analytic method is introduced for scaling small-core matrix properties to the hydrogeologic unit scales
Irregular Cellular Learning Automata.
Esnaashari, Mehdi; Meybodi, Mohammad Reza
2015-08-01
Cellular learning automaton (CLA) is a recently introduced model that combines cellular automaton (CA) and learning automaton (LA). The basic idea of CLA is to use LA to adjust the state transition probability of stochastic CA. This model has been used to solve problems in areas such as channel assignment in cellular networks, call admission control, image processing, and very large scale integration placement. In this paper, an extension of CLA called irregular CLA (ICLA) is introduced. This extension is obtained by removing the structure regularity assumption in CLA. Irregularity in the structure of ICLA is needed in some applications, such as computer networks, web mining, and grid computing. The concept of expediency has been introduced for ICLA and then, conditions under which an ICLA becomes expedient are analytically found. PMID:25291810
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)
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.
Moore, R; King, N; Alroy, J
1988-06-01
Differences in colonic secretory glycoconjugates (ie, mucin) between normal and ulcerative colitis-prone patients have been noted. Similar differences may occur in a corresponding primate model, the cotton-top tamarin (CTT), Saguinus oedipus, a New World monkey which suffers from spontaneous chronic colitis and colon cancer. Lectin reagents were used to characterize and compare colonic cell surface, cytoplasmic, and secretory glycoconjugates of 9 clinically healthy cotton-top tamarins, 7 colitis-susceptible, cancer-resistant tamarins (Callithrix jacchus, Saguinus fuscicollis), and 8 colitis and cancer-resistant primates (Aotus trivirgatus, Saimiri sciureus, Macaca fascicularis, and Macaca mulatta). Paraffin-embedded colonic sections were labeled with ten different biotinylated lectins and visualized by the avidin-biotin peroxidase (ABC) method. Significant differences were demonstrated in the pattern of lectin staining between the colitis-resistant and colitis-prone groups of primates. The differences were noted with Griffonia simplicifolia-I (GS-I), Dolichos biflorus agglutinin (DBA), peanut agglutinin (PNA) before and after neuraminidase, Ricinus communis agglutinin-I (RCA-I), soybean agglutinin (SBA), Ulex europaeus agglutinin-I (UEA-I), wheat germ agglutinin (WGA), and succinylated WGA (S-WGA). Significant differences between the CTT and phylogenetically related colitis-prone but cancer-resistant tamarins were demonstrated with SBA, UEA-I, and PNA after desialylation with neuraminidase. These results suggest that differences in colonic cellular glycoconjugates between colitis- and cancer-susceptible species versus colitis-susceptible, cancer-resistant species may be associated with risk of cancer. PMID:3132857
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...
International Nuclear Information System (INIS)
Highlights: ► The study presents cloning and characterization of TCP1γ gene from L. donovani. ► TCP1γ is a subunit of T-complex protein-1 (TCP1), a chaperonin class of protein. ► LdTCPγ exhibited differential expression in different stages of promastigotes. ► LdTCPγ co-localized with actin, a cytoskeleton protein. ► The data suggests that this gene may have a role in differentiation/biogenesis. ► 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 (TCP1γ), 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 TCP1γ of Leishmania donovani (LdTCP1γ), the causative agent of Indian Kala-azar. Primary sequence analysis of LdTCP1γ revealed the presence of all the characteristic features of TCP1γ. However, leishmanial TCP1γ represents a distinct kinetoplastid group, clustered in a separate branch of the phylogenic tree. LdTCP1γ exhibited differential expression in different stages of promastigotes. The non-dividing stationary phase promastigotes exhibited 2.5-fold less expression of LdTCP1γ as compared to rapidly dividing log phase parasites. The sub-cellular distribution of LdTCP1γ 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 LdTCP1γ with actin suggests that, this gene may have a role in maintaining the structural dynamics of cytoskeleton of parasite.
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
Smirnova, Lena; Harris, Georgina; Leist, Marcel; Hartung, Thomas
2015-01-01
Cellular resilience describes the ability of a cell to cope with environmental changes such as toxicant exposure. If cellular metabolism does not collapse directly after the hit or end in programmed cell death, the ensuing stress responses promote a new homeostasis under stress. The processes of reverting "back to normal" and reversal of apoptosis ("anastasis") have been studied little at the cellular level. Cell types show astonishingly similar vulnerability to most toxicants, except for those that require a very specific target, metabolism or mechanism present only in specific cell types. The majority of chemicals triggers "general cytotoxicity" in any cell at similar concentrations. We hypothesize that cells differ less in their vulnerability to a given toxicant than in their resilience (coping with the "hit"). In many cases, cells do not return to the naive state after a toxic insult. The phenomena of "pre-conditioning", "tolerance" and "hormesis" describe this for low-dose exposures to toxicants that render the cell more resistant to subsequent hits. The defense and resilience programs include epigenetic changes that leave a "memory/scar" - an alteration as a consequence of the stress the cell has experienced. These memories might have long-term consequences, both positive (resistance) and negative, that contribute to chronic and delayed manifestations of hazard and, ultimately, disease. This article calls for more systematic analyses of how cells cope with toxic perturbations in the long-term after stressor withdrawal. A technical prerequisite for these are stable (organotypic) cultures and a characterization of stress response molecular networks. PMID:26536287
International Nuclear Information System (INIS)
Ti-6Al-4V open cellular foams were fabricated by additive manufacturing using electron beam melting (EBM). Foam models were developed from CT-scans of aluminum open cellular foams and embedded in CAD for EBM. These foams were fabricated with solid cell structures as well as hollow cell structures and exhibit tailorable stiffness and strength. The strength in proportion to the measured microindentation hardness is as much as 40% higher for hollow cell (wall) structures in contrast to solid, fully dense EBM fabricated components. Plots of relative stiffness versus relative density were in good agreement with the Gibson-Ashby model for open cellular foam materials. Stiffness or Young's modulus values measured using a resonant frequency-damping analysis technique were found to vary inversely with porosity especially for solid cell wall, open cellular structure foams. These foams exhibit the potential for novel biomedical, aeronautics, and automotive applications.
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...
International Nuclear Information System (INIS)
The majority of cancer patients experience dramatic weight loss, due to cachexia and consisting of skeletal muscle and fat tissue wasting. Cachexia is a negative prognostic factor, interferes with therapy and worsens the patients' quality of life by affecting muscle function. Mice bearing ectopically-implanted C26 colon carcinoma are widely used as an experimental model of cancer cachexia. As part of the search for novel clinical and basic research applications for this experimental model, we characterized novel cellular and molecular features of C26-bearing mice. A fragment of C26 tumor was subcutaneously grafted in isogenic BALB/c mice. The mass growth and proliferation rate of the tumor were analyzed. Histological and cytofluorometric analyses were used to assess cell death, ploidy and differentiation of the tumor cells. The main features of skeletal muscle atrophy, which were highlighted by immunohistochemical and electron microscopy analyses, correlated with biochemical alterations. Muscle force and resistance to fatigue were measured and analyzed as major functional deficits of the cachectic musculature. We found that the C26 tumor, ectopically implanted in mice, is an undifferentiated carcinoma, which should be referred to as such and not as adenocarcinoma, a common misconception. The C26 tumor displays aneuploidy and histological features typical of transformed cells, incorporates BrdU and induces severe weight loss in the host, which is largely caused by muscle wasting. The latter appears to be due to proteasome-mediated protein degradation, which disrupts the sarcomeric structure and muscle fiber-extracellular matrix interactions. A pivotal functional deficit of cachectic muscle consists in increased fatigability, while the reported loss of tetanic force is not statistically significant following normalization for decreased muscle fiber size. We conclude, on the basis of the definition of cachexia, that ectopically-implanted C26 carcinoma represents
Stochastic superparameterization in quasigeostrophic turbulence
International Nuclear Information System (INIS)
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
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.
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.
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...
Applications of queueing theory to stochastic models of gene expression
Kulkarni, Rahul
2012-02-01
The intrinsic stochasticity of cellular processes implies that analysis of fluctuations (`noise') is often essential for quantitative modeling of gene expression. Recent single-cell experiments have carried out such analysis to characterize moments and entire probability distributions for quantities of interest, e.g. mRNA and protein levels across a population of cells. Correspondingly, there is a need to develop general analytical tools for modeling and interpretation of data obtained from such single-cell experiments. One such approach involves the mapping between models of stochastic gene expression and systems analyzed in queueing theory. The talk will provide an overview of this approach and discuss how theorems from queueing theory (e.g. Little's Law) can be used to derive exact results for general stochastic models of gene expression. In the limit that gene expression occurs in bursts, analytical results can be obtained which provide insight into the effects of different regulatory mechanisms on the noise in protein steady-state distributions. In particular, the approach can be used to analyze the effect of post-transcriptional regulation by non-coding RNAs leading to new insights and experimentally testable predictions.
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.
Energy Technology Data Exchange (ETDEWEB)
Jiao, Yang, E-mail: yang.jiao.2@asu.edu; Chawla, Nikhilesh [Materials Science and Engineering, Arizona State University, Arizona 85287-6206 (United States)
2014-03-07
We present a framework to model and characterize the microstructure of heterogeneous materials with anisotropic inclusions of secondary phases based on the directional correlation functions of the inclusions. Specifically, we have devised an efficient method to incorporate both directional two-point correlation functions S{sub 2} and directional two-point cluster functions C{sub 2} that contain non-trivial topological connectedness information into the simulated annealing microstructure reconstruction procedure. Our framework is applied to model an anisotropic aluminum alloy and the accuracy of the reconstructed structural models is assessed by quantitative comparison with the actual microstructure obtained via x-ray tomography. We show that incorporation of directional clustering information via C{sub 2} significantly improves the accuracy of the reconstruction. In addition, a set of analytical “basis” correlation functions are introduced to approximate the actual S{sub 2} and C{sub 2} of the material. With the proper choice of basis functions, the anisotropic microstructure can be represented by a handful of parameters including the effective linear sizes of the iron-rich and silicon-rich inclusions along three orthogonal directions. This provides a general and efficient means for heterogeneous material modeling that enables one to significantly reduce the data set required to characterize the anisotropic microstructure.
International Nuclear Information System (INIS)
We present a framework to model and characterize the microstructure of heterogeneous materials with anisotropic inclusions of secondary phases based on the directional correlation functions of the inclusions. Specifically, we have devised an efficient method to incorporate both directional two-point correlation functions S2 and directional two-point cluster functions C2 that contain non-trivial topological connectedness information into the simulated annealing microstructure reconstruction procedure. Our framework is applied to model an anisotropic aluminum alloy and the accuracy of the reconstructed structural models is assessed by quantitative comparison with the actual microstructure obtained via x-ray tomography. We show that incorporation of directional clustering information via C2 significantly improves the accuracy of the reconstruction. In addition, a set of analytical “basis” correlation functions are introduced to approximate the actual S2 and C2 of the material. With the proper choice of basis functions, the anisotropic microstructure can be represented by a handful of parameters including the effective linear sizes of the iron-rich and silicon-rich inclusions along three orthogonal directions. This provides a general and efficient means for heterogeneous material modeling that enables one to significantly reduce the data set required to characterize the anisotropic microstructure
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
Eslami, Sohrab
This dissertation undertakes the theoretical and experimental developments microcantilevers utilized in Atomic Force Microscopy (AFM) with applications to cellular imaging and characterization. The capability of revealing the inhomogeneties or interior of ultra-small materials has been of most interest to many researchers. However, the fundamental concept of signal and image formation remains unexplored and not fully understood. For his, a semi-empirical nonlinear force model is proposed to show that virtual frequency generation, regarded as the simplest synthesized subsurface probe, occurs optimally when the force is tuned to the van der Waals form. This is the first-time observation of a novel theoretical dynamic multi-frequency force microscopy that has not been already reported. Owing to the broad applications of microcantilevers in the nanoscale imaging and microscopic techniques, there is an essential feeling to study and propose a comprehensive model of such systems. Therefore, in the theoretical part of this dissertation, a distributed-parameters representation modeling of the microcantilever along with a general interaction force comprising of two attractive and repulsive components with general amplitude and power terms is studied. This model is investigated in a general 2D Cartesian coordinate to consider the motions of the probe with a tip mass. There is an excitation at the microcantilever's base such that the end of the beam is subject to the proposed general force. These forces are very sensitive to the amplitude and power terms of these parts; on the other hand, atomic intermolecular force is a function of the distance such that this distance itself is also a function of the interaction force that will result in a nonlinear implicit equation. From a parametric study in the probe-sample excitation, it is shown that the predicted behavior of the generated difference-frequency oscillation amplitude agrees well with experimental measurements. Following
Work fluctuations and stochastic resonance
International Nuclear Information System (INIS)
We study Brownian particle motion in a double-well potential driven by an ac force. This system exhibits the phenomenon of stochastic resonance. Distribution of work done on the system over a drive period in the time asymptotic regime has been calculated. We show that fluctuations in the input energy or work done dominate the mean value. The mean value of work done over a period as a function of noise strength can also be used to characterize stochastic resonance in the system. We also discuss the validity of steady state fluctuation theorems in this particular system
Stochastic models of intracellular calcium signals
International Nuclear Information System (INIS)
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
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.
Vesper, B; Onul, A; Haines III, G; Tarjan, G; Xue, J; Elseth, K; Aydogan, B.; Altman, M.; Roeske, J; Paradise, W; De Vitto, H; Radosevich, J
2013-01-01
There is a lack of understanding of the casual mechanisms behind the observation that some breast adenocarcinomas have identical morphology and comparatively different cellular growth behavior. This is exemplified by a differential response to radiation, chemotherapy, and other biological intervention therapies. Elevated concentrations of the free radical nitric oxide (NO), coupled with the up-regulated enzyme nitric oxide synthase (NOS) which produces NO, are activities which impact tumor gr...
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.
Sakai, H; Yuasa, M; Onuma, H; Takeoka, S; Tsuchida, E
2000-01-01
A series of hemoglobin (Hb)-based O(2) carriers, acellular and cellular types, were synthesized and their physicochemical characteristics were compared. The acellular type includes intramolecularly cross-linked Hb (XLHb), polyoxyethylene (POE)-conjugated pyridoxalated Hb (POE-PLP-Hb), hydroxyethylstarch-conjugated Hb (HES-XLHb), and glutaraldehyde-polymerized XLHb (Poly-XLHb). The cellular type is Hb-vesicles (HbV) of which the surface is modified with POE (POE-HbV). Their particle diameters are 7 +/- 2, 22 +/- 2, 47 +/- 17, 68 +/- 24, and 224 +/- 76 nm, respectively, thus all the materials penetrate across membrane filters with 0.4 microm pore size, though only the POE-HbV cannot penetrate across the filter with 0.2 microm pore size. These characteristics of permeability are important to consider an optimal particle size in microcirculation in vivo. POE-PLP-Hb ([Hb] = 5 g/dL) showed viscosity of 6.1 cP at 332 s(-1) and colloid osmotic pressure (COP) of 70.2 Torr, which are beyond the physiological conditions (human blood, viscosity = 3-4 cP, COP = ca. 25 Torr). XLHb and Poly-XLHb showed viscosities of 1.0 and 1.5 cp, respectively, which are significantly lower than that of blood. COP of POE-HbV is regulated to 20 Torr in 5% human serum albumin (HSA). HES-XLHb and POE-HbV/HSA showed comparable viscosity with human blood. Microscopic observation of human red blood cells (RBC) after mixing blood with POE-PLP-Hb or HES-XLHb disclosed aggregates of RBC, a kind of sludge, indicating a strong interaction with RBC, which is anticipated to modify peripheral blood flow in vivo. On the other hand, XLHb and POE-HbV showed no rouleaux or aggregates of RBC. The acellular Hbs (P(50) = 14-32 Torr) have their specific O(2) affinities determined by their structures, while that of the cellular POE-HbV is regulated by coencapsulating an appropriate amount of an allosteric effector (e.g., P(50) = 18, 32 Torr). These differences in physicochemical characteristics between the acellular
Contreras, Arturo Javier
This dissertation describes a novel Amplitude-versus-Angle (AVA) inversion methodology to quantitatively integrate pre-stack seismic data, well logs, geologic data, and geostatistical information. Deterministic and stochastic inversion algorithms are used to characterize flow units of deepwater reservoirs located in the central Gulf of Mexico. A detailed fluid/lithology sensitivity analysis was conducted to assess the nature of AVA effects in the study area. Standard AVA analysis indicates that the shale/sand interface represented by the top of the hydrocarbon-bearing turbidite deposits generate typical Class III AVA responses. Layer-dependent Biot-Gassmann analysis shows significant sensitivity of the P-wave velocity and density to fluid substitution, indicating that presence of light saturating fluids clearly affects the elastic response of sands. Accordingly, AVA deterministic and stochastic inversions, which combine the advantages of AVA analysis with those of inversion, have provided quantitative information about the lateral continuity of the turbidite reservoirs based on the interpretation of inverted acoustic properties and fluid-sensitive modulus attributes (P-Impedance, S-Impedance, density, and LambdaRho, in the case of deterministic inversion; and P-velocity, S-velocity, density, and lithotype (sand-shale) distributions, in the case of stochastic inversion). The quantitative use of rock/fluid information through AVA seismic data, coupled with the implementation of co-simulation via lithotype-dependent multidimensional joint probability distributions of acoustic/petrophysical properties, provides accurate 3D models of petrophysical properties such as porosity, permeability, and water saturation. Pre-stack stochastic inversion provides more realistic and higher-resolution results than those obtained from analogous deterministic techniques. Furthermore, 3D petrophysical models can be more accurately co-simulated from AVA stochastic inversion results. By
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
Turbulent response in a stochastic regime
International Nuclear Information System (INIS)
The theory for the non-linear, turbulent response in a system with intrinsic stochasticity is considered. It is argued that perturbative Eulerian theories, such as the Direct Interaction Approximation (DIA), are inherently unsuited to describe such a system. The exponentiation property that characterizes stochasticity appears in the Lagrangian picture and cannot even be defined in the Eulerian representation. An approximation for stochastic systems - the Normal Stochastic Approximation - is developed and states that the perturbed orbit functions (Lagrangian fluctuations) behave as normally distributed random variables. This is independent of the Eulerian statistics and, in fact, we treat the Eulerian fluctuations as fixed. A simple model problem (appropriate for the electron response in the drift wave) is subjected to a series of computer experiments. To within numerical noise the results are in agreement with the Normal Stochastic Approximation. The predictions of the DIA for this mode show substantial qualitative and quantitative departures from the observations
Krampera, Mauro; Galipeau, Jacques; Shi, Yufang; Tarte, Karin; Sensebe, Luc
2013-09-01
Cultured mesenchymal stromal cells (MSCs) possess immune regulatory properties and are already used for clinical purposes, although preclinical data (both in vitro and in vivo in animal models) are not always homogeneous and unequivocal. However, the various MSC-based clinical approaches to treat immunological diseases would be significantly validated and strengthened by using standardized immune assays aimed at obtaining shared, reproducible and consistent data. Thus, the MSC Committee of the International Society for Cellular Therapy has decided to put forward for general discussion a working proposal for a standardized approach based on a critical view of literature data. PMID:23602578
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 approximation: invited paper
Lai, Tze Leung
2003-01-01
Stochastic approximation, introduced by Robbins and Monro in 1951, has become an important and vibrant subject in optimization, control and signal processing. This paper reviews Robbins' contributions to stochastic approximation and gives an overview of several related developments.
Stochastic tools in turbulence
Lumey, John L
2012-01-01
Stochastic Tools in Turbulence discusses the available mathematical tools to describe stochastic vector fields to solve problems related to these fields. The book deals with the needs of turbulence in relation to stochastic vector fields, particularly, on three-dimensional aspects, linear problems, and stochastic model building. The text describes probability distributions and densities, including Lebesgue integration, conditional probabilities, conditional expectations, statistical independence, lack of correlation. The book also explains the significance of the moments, the properties of the
Stochastic component mode synthesis
Bah, Mamadou T.; Nair, Prasanth B.; Bhaskar, Atul; Keane, Andy J.
2003-01-01
In this paper, a stochastic component mode synthesis method is developed for the dynamic analysis of large-scale structures with parameter uncertainties. The main idea is to represent each component displacement using a subspace spanned by a set of stochastic basis vectors in the same fashion as in stochastic reduced basis methods [1, 2]. These vectors represent however stochastic modes in contrast to the deterministic modes used in conventional substructuring methods [3]. The Craig-Bampton r...
Miller, D B; Hegele, R A; Wolfe, B M; Huff, M W
1995-03-01
Remnants of triglyceride-rich lipoproteins accumulate in plasma of subjects with type III hyperlipoproteinemia (HLP) due to defective clearance by hepatic receptors. Although most subjects with type III HLP are homozygous for apolipoprotein (apo) E2 (arg158-->cys, R158C), a variant that binds defectively to cell surface receptors, some individuals with type III HLP have rare mutations of apo E. We identified six subjects from three families with type III HLP who had either an apo E3/1 or E4/1 phenotype by isoelectric focusing. Using DNA restriction isotyping with HhaI, all six subjects were determined to have only one apo E allele encoding cys158 and the other encoding arg158. Subsequently, digestion of polymerase chain reaction-amplified portions of exon 4 of the apo E gene with endonucleases HaeIII, TaqI, and Sau3AI demonstrated a second DNA variant that encoded a single amino acid substitution (gly127-->asp, G127D) due to a guanosine-to-adenosine nucleotide change resulting in the apo E1 isoform (G127D, R158C), which had arisen from a parent apo E2 allele. This mutation was confirmed with direct DNA sequencing. Incubation of very low density lipoprotein (VLDL) isolated from hyperlipidemic apo E1 subjects with J774 macrophages resulted in a 7- to 12-fold increase in cellular cholesterol ester compared with VLDL from apo E2/2 subjects. Although heterozygosity for apo E1 alone did not impair the interaction of VLDL with cellular receptors in vitro, its presence in subjects with type III HLP suggests that apo E1, perhaps in combination with secondary factors, may be causative for the dyslipidemia. PMID:7883834
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
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
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. PMID:26735137
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...
Miyazawa, Kohtaro; Kanaya, Takashi; Tanaka, Sachi; Takakura, Ikuro; Watanabe, Kouichi; Ohwada, Shyuichi; Kitazawa, Haruki; Rose, Michael T; Sakaguchi, Suehiro; Katamine, Shigeru; Yamaguchi, Takahiro; Aso, Hisashi
2007-03-01
The gastrointestinal tract is thought to be the main site of entry for the pathological isoform of the prion protein (PrP(Sc)). Prion diseases are believed to result from a conformational change of the cellular prion protein (PrP(c)) to PrP(Sc). Therefore, PrP(c) expression is a prerequisite for the infection and spread of the disease to the central nervous system. However, the distribution of PrP(c) in the gut is still a matter of controversy. We therefore investigated the localization of PrP(c) in the bovine and murine small intestine. In cattle, most PrP(c) positive epithelial cells were detected in the duodenum, while a few positive cells were found in the jejunum. PrP(c) was expressed in serotonin producing cells. In bovine Peyer's patches, PrP(c) was distributed in extrafollicular areas, but not in the germinal centre of the jejunum and ileum. PrP(c) was expressed in myeloid lineage cells such as myeloid dendritic cells and macrophages. In mice, PrP(c) was expressed in some epithelial cells throughout the small intestine as well as in cells such as follicular dendritic cell in the germinal centre of Peyer's patches. In this study, we demonstrate that there are a number of differences in the localization of PrP(c) between the murine and bovine small intestines. PMID:17165097
International Nuclear Information System (INIS)
Full text: Photodynamic therapy (PDT) can result in apoptosis and/or necrosis. Several steps in the apoptotic program depend on ATP and the intracellular ATP level is one determinant in the decision between apoptosis and necrosis. Therefore, photochemical damage of cellular targets involved in energy supply might play a crucial role for the mode of cell death being executed. The present study aimed at the characterization of changes in cellular energy supply and the associated cell death modes in response to PDT. Using the human epidermoid carcinoma cell line A431 and aluminum (III) phthalocyanine tetrasulfonate (2.5 μM) as a photosensitizer, we studied the changes in mitochondrial function and intracellular ATP-level after irradiation with different light doses. Employing assays for caspase-3 activation and nuclear fragmentation, 50 % of the cells were found to undergo apoptosis after irradiation with light doses between 2.5 to 3.5 J.cm-2. At light doses above 6 J.cm-2 cells died exclusively by necrosis, indicated by rapid and complete loss of ATP and mitochondrial function and an absence of caspase activation and nuclear fragmentation. With apoptotic cell populations the ATP-level was maintained at near control levels for up to eight hours which was far beyond the onset of morphological changes. These data suggest that necrosis as well as apoptosis can be induced with AIPcS4 mediated PDT and that photo damage in energy supplying cellular targets may influence the mode of cell death. Further, it is speculated that cells undergoing apoptosis after PDT maintain high ATP levels long enough to complete the apoptotic program. (author)
Gal-Mor, Ohad; Suez, Jotham; Elhadad, Dana; Porwollik, Steffen; Leshem, Eyal; Valinsky, Lea; McClelland, Michael; Schwartz, Eliezer; Rahav, Galia
2012-01-01
Enteric fever is an invasive life-threatening systemic disease caused by the Salmonella enterica human-adapted serovars Typhi and Paratyphi. Increasing incidence of infections with Salmonella enterica serovar Paratyphi A and the spreading of its antibiotic-resistant derivates pose a significant health concern in some areas of the world. Herein, we describe a molecular and phenotypic characterization of an S. Paratyphi A strain accounted for a recent paratyphoid outbreak in Nepal that affected...
Saleh Heneidi; Simerman, Ariel A; Erica Keller; Prapti Singh; Xinmin Li; Daniel A Dumesic; 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...
Ramsey Stochastic Model via Multistage Stochastic Programming
Czech Academy of Sciences Publication Activity Database
Kaňková, Vlasta
Vol. Part II. České Budějovice: University of South Bohemia in České Budějovice, Faculty of Economy , 2010 - (Houda, M.; Friebelová, J.), s. 328-333 ISBN 978-80-7394-218-2. [28th International Conference on Mathematical Methods in Economics 2010. České Budějovice (CZ), 08.09.2010-10.09.2010] R&D Projects: GA ČR GAP402/10/0956; GA ČR(CZ) GA402/08/0107; GA ČR GAP402/10/1610 Institutional research plan: CEZ:AV0Z10750506 Keywords : Ramsey stochastic model * Multistage stochastic programming * Confidence intervals * Autoregressive sequences * Stability * Empirical estimates Subject RIV: AH - Economics http://library.utia.cas.cz/separaty/2010/E/kankova-ramsey stochastic model via multistage stochastic programming.pdf
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.
International Nuclear Information System (INIS)
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
Stochastic dynamical models for ecological regime shifts
DEFF Research Database (Denmark)
Møller, Jan Kloppenborg; Carstensen, Jacob; Madsen, Henrik; Andersen, Tom
Ecosystems are influenced by a variety of known and unknown drivers. Unknown drivers should be modeled as noise and it is therefore important to analyze how noise influences the deterministic skeleton of system equations. The deterministic skeleton of stochastic dynamical models contains the...... physical and biological knowledge of the system, and nonlinearities introduced here can generate regime shifts or enhance the probability of regime shifts in the case of stochastic models, typically characterized by a threshold value for the known driver. A simple model for light competition between...... phytoplankton and benthic vegetation with feedback mechanisms is formulated, and it is demonstrated that bistability can occur for specific parameter settings. When stochastic input and stochastic propagation of the states are applied on the system regime shifts occur more frequently, and the threshold...
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 considered as a testcase. The stochastic moments (mean, standard deviation, etc.) of the flutter point are computed by an uncertainty analysis. Sensitivity-based methods are used to determine the stoc...
Bagnoli, Franco
1998-01-01
An introduction to cellular automata (both deterministic and probabilistic) with examples. Definition of deterministic automata, dynamical properties, damage spreading and Lyapunov exponents; probabilistic automata and Markov processes, nonequilibrium phase transitions, directed percolation, diffusion; simulation techniques, mean field. Investigation themes: life, epidemics, forest fires, percolation, modeling of ecosystems and speciation. They represent my notes for the school "Dynamical Mod...
Stochastic quantization in general relativity
International Nuclear Information System (INIS)
The stochastic quantization method of Parisi and Wu is briefly reviewed stressing its formal resemblance to the Einstein-Smoluchowski theory of Brownian motion. In order to make it applicable in the context of General Relativity, we present a generalization of the method to the case of Lorentzian signature of the space-time metric. It is shown that this approach has non-trivial implications even for linear quantum fields in curved space-time, where it introduces preferred quantum states characterized by the analyticity of the Feynman propagator in the mass parameter. Finally we propose a stochastic quantization scheme for the full nonlinear Einstein theory of gravitation. It employs the concept of a metric in field configuration space and is based mathematically on Ito's calculus. Non-trivial implications for the gravitational path integral measure and for perturbation theory are pointed out. (Author)
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.
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.
Phase transitions in a cellular automaton model of a highway on-ramp
Belitsky, Vladimir; Maric, Nevena; Schütz, Gunter M.
2007-09-01
We introduce a lattice gas model for the merging of two single-lane automobile highways. The merging rules for traffic on the two lanes are deterministic, but the inflow on both lanes is stochastic. Analysing the stationary distribution of this stochastic cellular automaton, we find a discontinuous phase transition from a free-flow phase which depends on the initial state of the road to a jammed phase where all memory of the initial state is lost. Inside the jammed phase we identify dynamical phase transitions in the approach to stationarity. Each dynamical phase is characterized by a fixed number of relaxation cycles which is decreasing as one moves deeper into the jammed phase. In each cycle step, the number of 'desperate' drivers who force their way onto the main road when they reach the end of the on-ramp increases until stationarity.
Phase transitions in a cellular automaton model of a highway on-ramp
International Nuclear Information System (INIS)
We introduce a lattice gas model for the merging of two single-lane automobile highways. The merging rules for traffic on the two lanes are deterministic, but the inflow on both lanes is stochastic. Analysing the stationary distribution of this stochastic cellular automaton, we find a discontinuous phase transition from a free-flow phase which depends on the initial state of the road to a jammed phase where all memory of the initial state is lost. Inside the jammed phase we identify dynamical phase transitions in the approach to stationarity. Each dynamical phase is characterized by a fixed number of relaxation cycles which is decreasing as one moves deeper into the jammed phase. In each cycle step, the number of 'desperate' drivers who force their way onto the main road when they reach the end of the on-ramp increases until stationarity
Quantifying synergistic information using intermediate stochastic variables
Quax, Rick; Har-Shemesh, Omri; Sloot, Peter M. A.
2016-01-01
Quantifying synergy among stochastic variables is an important open problem in information theory. Information synergy occurs when multiple sources together predict an outcome variable better than the sum of single-source predictions. It is an essential phenomenon in biology such as in neuronal networks and cellular regulatory processes, where different information flows integrate to produce a single response, but also in social cooperation processes as well as in statistical inference tasks ...
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.
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.
Stochastic simulations of a synthetic bacteria-yeast ecosystem
Directory of Open Access Journals (Sweden)
Biliouris Konstantinos
2012-06-01
Full Text Available Abstract Background The field of synthetic biology has greatly evolved and numerous functions can now be implemented by artificially engineered cells carrying the appropriate genetic information. However, in order for the cells to robustly perform complex or multiple tasks, co-operation between them may be necessary. Therefore, various synthetic biological systems whose functionality requires cell-cell communication are being designed. These systems, microbial consortia, are composed of engineered cells and exhibit a wide range of behaviors. These include yeast cells whose growth is dependent on one another, or bacteria that kill or rescue each other, synchronize, behave as predator-prey ecosystems or invade cancer cells. Results In this paper, we study a synthetic ecosystem comprising of bacteria and yeast that communicate with and benefit from each other using small diffusible molecules. We explore the behavior of this heterogeneous microbial consortium, composed of Saccharomyces cerevisiae and Escherichia coli cells, using stochastic modeling. The stochastic model captures the relevant intra-cellular and inter-cellular interactions taking place in and between the eukaryotic and prokaryotic cells. Integration of well-characterized molecular regulatory elements into these two microbes allows for communication through quorum sensing. A gene controlling growth in yeast is induced by bacteria via chemical signals and vice versa. Interesting dynamics that are common in natural ecosystems, such as obligatory and facultative mutualism, extinction, commensalism and predator-prey like dynamics are observed. We investigate and report on the conditions under which the two species can successfully communicate and rescue each other. Conclusions This study explores the various behaviors exhibited by the cohabitation of engineered yeast and bacterial cells. The way that the model is built allows for studying the dynamics of any system consisting of two
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
Ole Peters; Alexander Adamou
2011-01-01
It is argued that the simple trading strategy of leveraging or deleveraging an investment in the market portfolio cannot outperform the market. Such stochastic market efficiency places strong constraints on the possible stochastic properties of the market. Historical data confirm the hypothesis.
Stochastic and non-stochastic radiation effects
International Nuclear Information System (INIS)
Both the carcinogenic and the mutagenic effects of ionizing radiation are thought to be induced by 'stochastic' mechanisms of action. It is generally accepted that the number of carcinogenic injury is proportional to the radiation dose applied, and that there is no direct relationship between radiation dose and severity of induced injury, so that no threshold dose can be defined. However, the severity of mutagenic effects, resulting for example from cell death or leading to functional disorders or malformations, has been observed to be a function of the radiation dose, so that in principle threshold doses can be defined. These latter effects are called non-stochastic radiation effects. (orig./DG)
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...
Stochastic quantization and gravity
International Nuclear Information System (INIS)
We give a preliminary account of the application of stochastic quantization to the gravitational field. We start in Section I from Nelson's formulation of quantum mechanics as Newtonian stochastic mechanics and only then introduce the Parisi-Wu stochastic quantization scheme on which all the later discussion will be based. In Section II we present a generalization of the scheme that is applicable to fields in physical (i.e. Lorentzian) space-time and treat the free linearized gravitational field in this manner. The most remarkable result of this is the noncausal propagation of conformal gravitons. Moreover the concept of stochastic gauge-fixing is introduced and a complete discussion of all the covariant gauges is given. A special symmetry relating two classes of covariant gauges is exhibited. Finally Section III contains some preliminary remarks on full nonlinear gravity. In particular we argue that in contrast to gauge fields the stochastic gravitational field cannot be transformed to a Gaussian process. (Author)
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...
Stochastic resonance during a polymer translocation process
Mondal, Debasish; Muthukumar, M.
2016-04-01
We have studied the occurrence of stochastic resonance when a flexible polymer chain undergoes a single-file translocation through a nano-pore separating two spherical cavities, under a time-periodic external driving force. The translocation of the chain is controlled by a free energy barrier determined by chain length, pore length, pore-polymer interaction, and confinement inside the donor and receiver cavities. The external driving force is characterized by a frequency and amplitude. By combining the Fokker-Planck formalism for polymer translocation and a two-state model for stochastic resonance, we have derived analytical formulas for criteria for emergence of stochastic resonance during polymer translocation. We show that no stochastic resonance is possible if the free energy barrier for polymer translocation is purely entropic in nature. The polymer chain exhibits stochastic resonance only in the presence of an energy threshold in terms of polymer-pore interactions. Once stochastic resonance is feasible, the chain entropy controls the optimal synchronization conditions significantly.
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. PMID:27083746
Turbulence, Spontaneous Stochasticity and Climate
Eyink, Gregory
Turbulence is well-recognized as important in the physics of climate. Turbulent mixing plays a crucial role in the global ocean circulation. Turbulence also provides a natural source of variability, which bedevils our ability to predict climate. I shall review here a recently discovered turbulence phenomenon, called ``spontaneous stochasticity'', which makes classical dynamical systems as intrinsically random as quantum mechanics. Turbulent dissipation and mixing of scalars (passive or active) is now understood to require Lagrangian spontaneous stochasticity, which can be expressed by an exact ``fluctuation-dissipation relation'' for scalar turbulence (joint work with Theo Drivas). Path-integral methods such as developed for quantum mechanics become necessary to the description. There can also be Eulerian spontaneous stochasticity of the flow fields themselves, which is intimately related to the work of Kraichnan and Leith on unpredictability of turbulent flows. This leads to problems similar to those encountered in quantum field theory. To quantify uncertainty in forecasts (or hindcasts), we can borrow from quantum field-theory the concept of ``effective actions'', which characterize climate averages by a variational principle and variances by functional derivatives. I discuss some work with Tom Haine (JHU) and Santha Akella (NASA-Goddard) to make this a practical predictive tool. More ambitious application of the effective action is possible using Rayleigh-Ritz schemes.
Threshold-Range Scaling of Excitable Cellular Automata
Fisch, R; Griffeath, D; Fisch, Robert; Gravner, Janko; Griffeath, David
1993-01-01
Each cell of a two-dimensional lattice is painted one of k colors, arranged in a "color wheel." The colors advance (0 to k-1 mod k) either automatically or by contact with at least a threshold number of successor colors in a prescribed local neighborhood. Discrete-time parallel systems of this sort in which color 0 updates by contact and the rest update automatically are called Greenberg-Hastings (GH) rules. A system in which all colors update by contact is called a cyclic cellular automaton (CCA). Started from appropriate initial conditions these models generate periodic traveling waves. Started from random configurations the same rules exhibit complex self-organization, typically characterized by nucleation of locally periodic "ram's horns" or spirals. Corresponding random processes give rise to a variety of "forest fire" equilibria that display large-scale stochastic wave fronts. This article describes a framework, theoretically based, but relying on extensive interactive computer graphics experimentation,...
Praet, Jelle; Santermans, Eva; Reekmans, Kristien; de Vocht, Nathalie; Le Blon, Debbie; Hoornaert, Chloé; Daans, Jasmijn; Goossens, Herman; Berneman, Zwi; Hens, Niel; Van der Linden, Annemie; Ponsaerts, Peter
2014-01-01
Preclinical animal studies involving intracerebral (stem) cell grafting are gaining popularity in many laboratories due to the reported beneficial effects of cell grafting on various diseases or traumata of the central nervous system (CNS). In this chapter, we describe a histological workflow to characterize and quantify cellular events following neural and fibroblast(-like) stem cell grafting in healthy and demyelinated CNS tissue. First, we provide standardized protocols to isolate and culture eGFP(+) neural and fibroblast(-like) stem cells from embryonic mouse tissue. Second, we describe flow cytometric procedures to determine cell viability, eGFP transgene expression, and the expression of different stem cell lineage markers. Third, we explain how to induce reproducible demyelination in the CNS of mice by means of cuprizone administration, a validated mouse model for human multiple sclerosis. Fourth, the technical procedures for cell grafting in the CNS are explained in detail. Finally, an optimized and validated workflow for the quantitative histological analysis of cell graft survival and endogenous astroglial and microglial responses is provided. PMID:25173390
Directory of Open Access Journals (Sweden)
Stefani N. Thomas
2013-08-01
Full Text Available Radiation and drug resistance are significant challenges in the treatment of locally advanced, recurrent and metastatic breast cancer that contribute to mortality. Clinically, radiotherapy requires oxygen to generate cytotoxic free radicals that cause DNA damage and allow that damage to become fixed in the genome rather than repaired. However, approximately 40% of all breast cancers have hypoxic tumor microenvironments that render cancer cells significantly more resistant to irradiation. Hypoxic stimuli trigger changes in the cell death/survival pathway that lead to increased cellular radiation resistance. As a result, the development of noninvasive strategies to assess tumor hypoxia in breast cancer has recently received considerable attention. Exosomes are secreted nanovesicles that have roles in paracrine signaling during breast tumor progression, including tumor-stromal interactions, activation of proliferative pathways and immunosuppression. The recent development of protocols to isolate and purify exosomes, as well as advances in mass spectrometry-based proteomics have facilitated the comprehensive analysis of exosome content and function. Using these tools, studies have demonstrated that the proteome profiles of tumor-derived exosomes are indicative of the oxygenation status of patient tumors. They have also demonstrated that exosome signaling pathways are potentially targetable drivers of hypoxia-dependent intercellular signaling during tumorigenesis. This article provides an overview of how proteomic tools can be effectively used to characterize exosomes and elucidate fundamental signaling pathways and survival mechanisms underlying hypoxia-mediated radiation resistance in breast cancer.
Charalambous, Charalambos D.; N. U. Ahmed
2013-01-01
We consider a team game reward, and we derive a stochastic Pontryagin's maximum principle for distributed stochastic differential systems with decentralized noisy information structures. Our methodology utilizes the semi martingale representation theorem, variational methods, and backward stochastic differential equations. Furthermore, we derive necessary and sufficient optimality conditions that characterize team and person-by-person optimality of decentralized strategies. Finally, we apply ...
Stochastic dynamics of macromolecular-assembly networks.
Saiz, Leonor; Vilar, Jose
2006-03-01
The formation and regulation of macromolecular complexes provides the backbone of most cellular processes, including gene regulation and signal transduction. The inherent complexity of assembling macromolecular structures makes current computational methods strongly limited for understanding how the physical interactions between cellular components give rise to systemic properties of cells. Here we present a stochastic approach to study the dynamics of networks formed by macromolecular complexes in terms of the molecular interactions of their components [1]. Exploiting key thermodynamic concepts, this approach makes it possible to both estimate reaction rates and incorporate the resulting assembly dynamics into the stochastic kinetics of cellular networks. As prototype systems, we consider the lac operon and phage λ induction switches, which rely on the formation of DNA loops by proteins [2] and on the integration of these protein-DNA complexes into intracellular networks. This cross-scale approach offers an effective starting point to move forward from network diagrams, such as those of protein-protein and DNA-protein interaction networks, to the actual dynamics of cellular processes. [1] L. Saiz and J.M.G. Vilar, submitted (2005). [2] J.M.G. Vilar and L. Saiz, Current Opinion in Genetics & Development, 15, 136-144 (2005).
Stochastic Processes in Electrochemistry.
Singh, Pradyumna S; Lemay, Serge G
2016-05-17
Stochastic behavior becomes an increasingly dominant characteristic of electrochemical systems as we probe them on the smallest scales. Advances in the tools and techniques of nanoelectrochemistry dictate that stochastic phenomena will become more widely manifest in the future. In this Perspective, we outline the conceptual tools that are required to analyze and understand this behavior. We draw on examples from several specific electrochemical systems where important information is encoded in, and can be derived from, apparently random signals. This Perspective attempts to serve as an accessible introduction to understanding stochastic phenomena in electrochemical systems and outlines why they cannot be understood with conventional macroscopic descriptions. PMID:27120701
Stochastic Schroedinger equations
International Nuclear Information System (INIS)
A derivation of Belavkin's stochastic Schroedinger equations is given using quantum filtering theory. We study an open system in contact with its environment, the electromagnetic field. Continuous observation of the field yields information on the system: it is possible to keep track in real time of the best estimate of the system's quantum state given the observations made. This estimate satisfies a stochastic Schroedinger equation, which can be derived from the quantum stochastic differential equation for the interaction picture evolution of system and field together. Throughout the paper we focus on the basic example of resonance fluorescence
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
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 $\
Stochastic Physicochemical Dynamics
Tsekov, Roumen
2001-01-01
The monograph considers thermodynamic relaxation in quantum systems, stochastic dynamics of gas molecules, fluctuation stability of thin liquid films, resonant diffusion in modulated solid structures and catalytic kinetics of chemical dissociation.
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.
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.
Dynamics of Double Stochastic Operators
Saburov, Mansoor
2016-03-01
A double stochastic operator is a generalization of a double stochastic matrix. In this paper, we study the dynamics of double stochastic operators. We give a criterion for a regularity of a double stochastic operator in terms of absences of its periodic points. We provide some examples to insure that, in general, a trajectory of a double stochastic operator may converge to any interior point of the simplex.
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 Resonance in Protein Folding Dynamics.
Davtyan, Aram; Platkov, Max; Gruebele, Martin; Papoian, Garegin A
2016-05-01
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. PMID:26992148
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.
Stochastic processes in muon ionization cooling
Errede, D.; Makino, K.; Berz, M.; Johnstone, C. J.; Van Ginneken, A.
2004-02-01
A muon ionization cooling channel consists of three major components: the magnet optics, an acceleration cavity, and an energy absorber. The absorber of liquid hydrogen contained by thin aluminum windows is the only component which introduces stochastic processes into the otherwise deterministic acceleration system. The scattering dynamics of the transverse coordinates is described by Gaussian distributions. The asymmetric energy loss function is represented by the Vavilov distribution characterized by the minimum number of collisions necessary for a particle undergoing loss of the energy distribution average resulting from the Bethe-Bloch formula. Examples of the interplay between stochastic processes and deterministic beam dynamics are given.
International Nuclear Information System (INIS)
After a brief review of the BRST formalism and of the Parisi-Wu stochastic quantization method we introduce the BRST stochastic quantization scheme. It allows the second quantization of constrained Hamiltonian systems in a manifestly gauge symmetry preserving way. The examples of the relativistic particle, the spinning particle and the bosonic string are worked out in detail. The paper is closed by a discussion on the interacting field theory associated to the relativistic point particle system. 58 refs. (Author)
What is Stochastic Independence?
Franz, Uwe
2002-01-01
The notion of a tensor product with projections or with inclusions is defined. It is shown that the definition of stochastic independence relies on such a structure and that independence can be defined in an arbitrary category with a tensor product with inclusions or projections. In this context, the classifications of quantum stochastic independence by Muraki, Ben Ghorbal, and Sch\\"urmann become classifications of the tensor products with inclusions for the categories of algebraic probabilit...
Stochastic Processes in Finance
Madan, Dilip B.
2010-01-01
Stochastic processes arising in the description of the risk-neutral evolution of equity prices are reviewed. Starting with Brownian motion, I review extensions to Lévy and Sato processes. These processes have independent increments; the former are homogeneous in time, whereas the latter are inhomogeneous. One-dimensional Markov processes such as local volatility and local Lévy are discussed next. Finally, I take up two forms of stochastic volatility that are due to either space scaling or tim...
Hu, Yan; Wang, Zesen; Wen, Jingya; Li, Yu
2016-10-01
Better decisions are made using risk assessment models when uncertainty and variability are explicitly acknowledged. Uncertainty caused by a lack of uniform and scientifically supported environmental quality guidelines and variability in the degree of exposure of environmental systems to contaminants are here incorporated in a stochastic fuzzy environmental risk characterization (SFERC) approach. The approach is based on quotient probability distribution and environmental risk level fuzzy membership function methods. The SFERC framework was used to characterize the environmental risks posed by 16 priority polycyclic aromatic hydrocarbons (PAHs) in soil at a typical petroleum-contaminated site in China. This relied on integrating data from the literature and field and laboratory experiments. The environmental risk levels posed by the PAHs under four risk scenarios were determined using the SFERC approach, using "residential land" and "industrial land" environmental quality guidelines under "loose" and "strict" strictness parameters. The results showed that environmental risks posed by PAHs in soil are primarily caused by oil exploitation, traffic emissions, and coal combustion. The SFERC approach is an effective tool for characterizing uncertainty and variability in environmental risk assessments and for managing contaminated sites. PMID:27232725
Directory of Open Access Journals (Sweden)
G. Srinivasa Rao
2015-06-01
Full Text Available As clustering techniques are gaining more important today, we propose a new clustering technique by means of ACFO and cellular automata. The cellular automata uniquely characterizes the condition of a cell at a specific moment by employing the data like the conditions of a reference cell together with its adjoining cell, total number of cells, restraint, transition function and neighbourhood calculation. With an eye on explaining the condition of the cell, morphological functions are executed on the image. In accordance with the four stages of the morphological process, the rural and the urban areas are grouped separately. In order to steer clear of the stochastic turbulences, the threshold is optimized by means of the ACFO. The test outcomes obtained vouchsafe superb performance of the innovative technique. The accomplishment of the new-fangled technique is assessed by using additional number of images and is contrasted with the traditional methods like CFO (Central Force Optimization and PSO (Particle Swarm Optimization.
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.
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.
Computational stochastic model of ions implantation
International Nuclear Information System (INIS)
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++ 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 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.
Stochastic modeling of the auroral electrojet index
Anh, V. V.; Yong, J. M.; Yu, Z. G.
2008-10-01
Substorms are often identified by bursts of activities in the magnetosphere-ionosphere system characterized by the auroral electrojet (AE) index. The highly complex nature of substorm-related bursts suggests that a stochastic approach would be needed. Stochastic models including fractional Brownian motion, linear fractional stable motion, Fokker-Planck equation and Itô-type stochastic differential equation have been suggested to model the AE index. This paper provides a stochastic model for the AE in the form of fractional stochastic differential equation. The long memory of the AE time series is represented by a fractional derivative, while its bursty behavior is modeled by a Lévy noise with inverse Gaussian marginal distribution. The equation has the form of the classical Stokes-Boussinesq-Basset equation of motion for a spherical particle in a fluid with retarded viscosity. Parameter estimation and approximation schemes are detailed for the simulation of the equation. The fractional order of the equation conforms with the previous finding that the fluctuations of the magnetosphere-ionosphere system as seen in the AE reflect the fluctuations in the solar wind: they both possess the same extent of long-range dependence. The introduction of a fractional derivative term into the equation to capture the extent of long-range dependence together with an inverse Gaussian noise input describe the right amount of intermittency inherent in the AE data.
International Nuclear Information System (INIS)
Classical transport of neutral particles in a binary, scattering, stochastic media is discussed. It is assumed that the cross-sections of the constituent materials and their volume fractions are known. The inner structure of the media is stochastic, but there exist a statistical knowledge about the lump sizes, shapes and arrangement. The transmission through the composite media depends on the specific heterogeneous realization of the media. The current research focuses on the averaged transmission through an ensemble of realizations, frm which an effective cross-section for the media can be derived. The problem of one dimensional transport in stochastic media has been studied extensively [1]. In the one dimensional description of the problem, particles are transported along a line populated with alternating material segments of random lengths. The current work discusses transport in two-dimensional stochastic media. The phenomenon that is unique to the multi-dimensional description of the problem is obstacle bypassing. Obstacle bypassing tends to reduce the opacity of the media, thereby reducing its effective cross-section. The importance of this phenomenon depends on the manner in which the obstacles are arranged in the media. Results of transport simulations in multi-dimensional stochastic media are presented. Effective cross-sections derived from the simulations are compared against those obtained for the one-dimensional problem, and against those obtained from effective multi-dimensional models, which are partially based on a Markovian assumption
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...
On synthesis of linear quantum stochastic systems by pure cascading
Nurdin, Hendra I
2010-01-01
Recently, it has been demonstrated that an arbitrary linear quantum stochastic system can be realized as a cascade connection of simple one degree of freedom quantum harmonic oscillators together with a direct interaction Hamiltonian which is bilinear in the canonical operators of the oscillators. However, from an experimental point of view, realizations by pure cascading, without a direct interaction Hamiltonian, would be much simpler to implement and this raises the natural question of what class of linear quantum stochastic systems are realizable by cascading alone. This paper gives a precise characterization of this class of linear quantum stochastic systems and then it is proved that, in the weaker sense of transfer function realizability, all passive linear quantum stochastic systems belong to this class. A constructive example is given to show the transfer function realization of a two degrees of freedom passive linear quantum stochastic system by pure cascading.
Stochastic modelling of turbulence
DEFF Research Database (Denmark)
Sørensen, Emil Hedevang Lohse
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......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 is...... still undergoing rapid development. Turbulence and wind energy are vast and complicated subjects. Turbulence has structures across a wide range of length and time scales, structures which cannot be captured by a Gaussian process that relies on only second order properties. Concerning wind energy, a wind...
DEFF Research Database (Denmark)
Abkarian, Manouk; Faivre, Magalie; Horton, Renita; Smistrup, Kristian; Best-Popescu, Catherine A; Stone, Howard A.
2008-01-01
Microfluidic tools are providing many new insights into the chemical, physical and physicochemical responses of cells. Both suspension-level and single-cell measurements have been studied. We review our studies of these kinds of problems for red blood cells with particular focus on the shapes of ...... mechanical effects on suspended cells can be studied systematically in small devices, and how these features can be exploited to develop methods for characterizing physicochemical responses and possibly for the diagnosis of cellular-scale changes to environmental factors....
Stochastic Time-Series Spectroscopy
Scoville, John
2015-01-01
Spectroscopically measuring low levels of non-equilibrium phenomena (e.g. emission in the presence of a large thermal background) can be problematic due to an unfavorable signal-to-noise ratio. An approach is presented to use time-series spectroscopy to separate non-equilibrium quantities from slowly varying equilibria. A stochastic process associated with the non-equilibrium part of the spectrum is characterized in terms of its central moments or cumulants, which may vary over time. This parameterization encodes information about the non-equilibrium behavior of the system. Stochastic time-series spectroscopy (STSS) can be implemented at very little expense in many settings since a series of scans are typically recorded in order to generate a low-noise averaged spectrum. Higher moments or cumulants may be readily calculated from this series, enabling the observation of quantities that would be difficult or impossible to determine from an average spectrum or from prinicipal components analysis (PCA). This meth...
Stochastic Geometric Wave Equations
Czech Academy of Sciences Publication Activity Database
Brzezniak, Z.; Ondreját, Martin
Cham: Springer, 2015, s. 157-188. (Progress in Probability. 68). ISBN 978-3-0348-0908-5. ISSN 1050-6977. [Stochastic analysis and applications at the Centre Interfacultaire Bernoulli, Ecole Polytechnique Fédérale de Lausanne. Lausanne (CH), 09.01.2012-29.6.2012] R&D Projects: GA ČR GAP201/10/0752 Institutional research plan: CEZ:AV0Z10750506 Institutional support: RVO:67985556 Keywords : Stochastic wave equation * Riemannian manifold * homogeneous space Subject RIV: BA - General Mathematics http://library.utia.cas.cz/separaty/2015/SI/ondrejat-0447803.pdf
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
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.
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 entrainment of a stochastic oscillator.
Wang, Guanyu; Peskin, Charles S
2015-11-01
In this work, we consider a stochastic oscillator described by a discrete-state continuous-time Markov chain, in which the states are arranged in a circle, and there is a constant probability per unit time of jumping from one state to the next in a specified direction around the circle. At each of a sequence of equally spaced times, the oscillator has a specified probability of being reset to a particular state. The focus of this work is the entrainment of the oscillator by this periodic but stochastic stimulus. We consider a distinguished limit, in which (i) the number of states of the oscillator approaches infinity, as does the probability per unit time of jumping from one state to the next, so that the natural mean period of the oscillator remains constant, (ii) the resetting probability approaches zero, and (iii) the period of the resetting signal approaches a multiple, by a ratio of small integers, of the natural mean period of the oscillator. In this distinguished limit, we use analytic and numerical methods to study the extent to which entrainment occurs. PMID:26651734
Stochastic Contraction in Riemannian Metrics
Pham, Quang-Cuong; Slotine, Jean-Jacques
2013-01-01
Stochastic contraction analysis is a recently developed tool for studying the global stability properties of nonlinear stochastic systems, based on a differential analysis of convergence in an appropriate metric. To date, stochastic contraction results and sharp associated performance bounds have been established only in the specialized context of state-independent metrics, which restricts their applicability. This paper extends stochastic contraction analysis to the case of general time- and...
Stochastic quantization: Stabilizing quantum models
International Nuclear Information System (INIS)
Osterwalder-Schrader positivity is shown to be fulfilled for stochastically quantized lattice gauge theories, spin models and P(phi) interactions bounded from below. Problems arising are discussed. A stochastic equation is derived to stabilize the quantum Einstein gravity. It is shown that the stochastic quantization of the Yang-Mills theory leads to a well-defined semiclassical expansion. (orig.)
Stochastic quantization of Proca field
International Nuclear Information System (INIS)
We discuss the complications that arise in the application of Nelson's stochastic quantization scheme to classical Proca field. One consistent way to obtain spin-one massive stochastic field is given. It is found that the result of Guerra et al on the connection between ground state stochastic field and the corresponding Euclidean-Markov field extends to the spin-one case. (author)
The stochastic quality calculus
DEFF Research Database (Denmark)
Zeng, Kebin; Nielson, Flemming; Nielson, Hanne Riis
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...
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 and...
Stochastic nonlinear beam equations
Czech Academy of Sciences Publication Activity Database
Brzezniak, Z.; Maslowski, Bohdan; Seidler, Jan
2005-01-01
Roč. 132, č. 1 (2005), s. 119-149. ISSN 0178-8051 R&D Projects: GA ČR(CZ) GA201/01/1197 Institutional research plan: CEZ:AV0Z10190503 Keywords : stochastic beam equation * stability Subject RIV: BA - General Mathematics Impact factor: 0.896, year: 2005
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...
International Nuclear Information System (INIS)
Major headings in this review include: proton sources; antiproton production; antiproton sources and Liouville, the role of the Debuncher; transverse stochastic cooling, time domain; the accumulator; frequency domain; pickups and kickers; Fokker-Planck equation; calculation of constants in the Fokker-Planck equation; and beam feedback
Jiang, Yuming
2009-01-01
Network calculus, a theory dealing with queuing systems found in computer networks, focuses on performance guarantees. This title presents a comprehensive treatment for the stochastic service-guarantee analysis research and provides basic introductory material on the subject, as well as discusses the various researches in the area.
Focus on stochastic thermodynamics
Van den Broeck, Christian; Sasa, Shin-ichi; Seifert, Udo
2016-02-01
We introduce the thirty papers collected in this ‘focus on’ issue. The contributions explore conceptual issues within and around stochastic thermodynamics, use this framework for the theoretical modeling and experimental investigation of specific systems, and provide further perspectives on and for this active field.
Stochastic resonance for exploration geophysics
Omerbashich, Mensur
2008-01-01
Stochastic resonance (SR) is a phenomenon in which signal to noise (SN) ratio gets improved by noise addition rather than removal as envisaged classically. SR was first claimed in climatology a few decades ago and then in other disciplines as well. The same as it is observed in natural systems, SR is used also for allowable SN enhancements at will. Here I report a proof of principle that SR can be useful in exploration geophysics. For this I perform high frequency GaussVanicek variance spectral analyses (GVSA) of model traces characterized by varying levels of complexity, completeness and pollution. This demonstration justifies all further research on SR in applied geophysics, as energy demands and depletion of reachable supplies potentially make SR vital in a near future.
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 Mappings and Random Distribution Fields. A Correlation Approach
Gaspar, Pastorel; Popa, Lorena
2014-01-01
This paper contains a study of multivariate second order stochastic mappings indexed by an abstract set $\\Lambda$ in close connection to their operator covariance functions. The characterizations of the normal Hilbert module or of Hilbert spaces associated to such a multivariate second order stochastic mapping in terms of reproducing kernel structures are given, aiming not only to gather into a unified way some concepts from the field, but also to indicate an instrument for extending the very...
Pricing Parisian Option under a Stochastic Volatility Model
Directory of Open Access Journals (Sweden)
Min-Ku Lee
2014-01-01
Full Text Available We study the pricing of a Parisian option under a stochastic volatility model. Based on the manipulation problem that barrier options might create near barriers, the Parisian option has been designed as an extended barrier option. A stochastic volatility correction to the Black-Scholes price of the Parisian option is obtained in a partial differential equation form and the solution is characterized numerically.
Tracking Level Set Representation Driven by a Stochastic Dynamics
Avenel, Christophe; Memin, Etienne; Pérez, Patrick
2010-01-01
International audience We introduce a non-linear stochastic filtering technique to track the state of a free curve from image data. The approach we propose is implemented through a particle filter, which includes color measurements characterizing the target and the background respectively. We design a continuous-time dynamics that allows us to infer inter-frame deformations. The curve is defined by an implicit level-set representation and the stochastic dynamics is expressed on the level-s...
The statistics of spikes trains: a stochastic calculus approach
Touboul, Jonathan; Faugeras, Olivier
2007-01-01
We discuss the statistics of spikes trains for different types of integrate-and-fire neurons and different types of synaptic noise models. In cotnrast with the usual approaches in neuroscience, mainly based on statistical physics methods such as the Fokker-Planck equation or the mean-field theory, we chose the point of the view of the stochastic calculus theory to characterize neurons in noisy environments. We present four stochastic calculus techniques that can be used to find the probabilit...
Noise in cellular signaling pathways: causes and effects
Ladbury, John E.; Arold, Stefan T.
2012-01-01
Noise caused by stochastic fluctuations in genetic circuits (transcription and translation) is now appreciated as a central aspect of cell function and phenotypic behavior. Noise has also been detected in signaling networks, but the origin of this noise and how it shapes cellular outcomes remain poorly understood. Here, we argue that noise in signaling networks results from the intrinsic promiscuity of protein-protein interactions, and that this noise has shaped cellular signal transduction. ...
Stochastic prediction of drought class transitions
Paulo, Ana A.; L. S. Pereira
2008-01-01
This paper aims at the stochastic characterization of droughts applying Markov chains modeling to drought class transitions derived from SPI time series. Several sites in Southern Portugal having updated data on precipitation available were considered. The drought class probabilities, the expected residence time in each class of severity, the expected time for the transition between drought classes and the drought severity class predictions 1, 2, or 3 months ahead have been obt...
Evaluating Portfolio Performance with Stochastic Discount Factors
1997-01-01
This paper provides evidence on the use of stochastic discount factors in the evaluation of portfolio performance. First, we discuss evaluation in this setting, and relate it to traditional mean-variance analysis. We then use Monte Carlo experiments to examine the small sample properties of generalized method of moment (GMM) estimators. Both size and power properties are characterized for various GMM approaches. Finally, we apply the methodology to Swedish-based mutual funds. We offer an eval...
Aging, cellular senescence, and cancer.
Campisi, Judith
2013-01-01
For most species, aging promotes a host of degenerative pathologies that are characterized by debilitating losses of tissue or cellular function. However, especially among vertebrates, aging also promotes hyperplastic pathologies, the most deadly of which is cancer. In contrast to the loss of function that characterizes degenerating cells and tissues, malignant (cancerous) cells must acquire new (albeit aberrant) functions that allow them to develop into a lethal tumor. This review discusses the idea that, despite seemingly opposite characteristics, the degenerative and hyperplastic pathologies of aging are at least partly linked by a common biological phenomenon: a cellular stress response known as cellular senescence. The senescence response is widely recognized as a potent tumor suppressive mechanism. However, recent evidence strengthens the idea that it also drives both degenerative and hyperplastic pathologies, most likely by promoting chronic inflammation. Thus, the senescence response may be the result of antagonistically pleiotropic gene action. PMID:23140366
Hondow, Nicole; Brown, M Rowan; Starborg, Tobias; Monteith, Alexander G; Brydson, Rik; Summers, Huw D; Rees, Paul; Brown, Andy
2016-02-01
Semiconductor quantum dot nanoparticles are in demand as optical biomarkers yet the cellular uptake process is not fully understood; quantification of numbers and the fate of internalized particles are still to be achieved. We have focussed on the characterization of cellular uptake of quantum dots using a combination of analytical electron microscopies because of the spatial resolution available to examine uptake at the nanoparticle level, using both imaging to locate particles and spectroscopy to confirm identity. In this study, commercially available quantum dots, CdSe/ZnS core/shell particles coated in peptides to target cellular uptake by endocytosis, have been investigated in terms of the agglomeration state in typical cell culture media, the traverse of particle agglomerates across U-2 OS cell membranes during endocytosis, the merging of endosomal vesicles during incubation of cells and in the correlation of imaging flow cytometry and transmission electron microscopy to measure the final nanoparticle dose internalized by the U-2 OS cells. We show that a combination of analytical transmission electron microscopy and serial block face scanning electron microscopy can provide a comprehensive description of the internalization of an initial exposure dose of nanoparticles by an endocytically active cell population and how the internalized, membrane bound nanoparticle load is processed by the cells. We present a stochastic model of an endosome merging process and show that this provides a data-driven modelling framework for the prediction of cellular uptake of engineered nanoparticles in general. PMID:25762522
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.
Molecular and Cellular Basis of Aging
DEFF Research Database (Denmark)
Rattan, Suresh
2016-01-01
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...
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
Towards a continuum theory of movement in interacting cellular systems
Newman, Timothy
2003-10-01
Interacting cellular systems form the basis of all higher organisms, and are fundamental to the understanding of embryogenesis, organ function, and neoplasms. I will describe a stochastic model of cell interactions which can be applied to these problems, and present some of our recent results on chemotactic response.
Almost sure exponential stability of delayed cellular neural networks
Directory of Open Access Journals (Sweden)
Chuangxia Huang
2007-03-01
Full Text Available The stability of stochastic delayed Cellular Neural Networks (DCNN is investigated in this paper. Using suitable Lyapunov functional and the semimartingale convergence theorem, we obtain some sufficient conditions for checking the almost sure exponential stability of the DCNN.
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
Samuelson, P A
1971-02-01
Because a commodity like wheat can be carried forward from one period to the next, speculative arbitrage serves to link its prices at different points of time. Since, however, the size of the harvest depends on complicated probability processes impossible to forecast with certainty, the minimal model for understanding market behavior must involve stochastic processes. The present study, on the basis of the axiom that it is the expected rather than the known-for-certain prices which enter into all arbitrage relations and carryover decisions, determines the behavior of price as the solution to a stochastic-dynamic-programming problem. The resulting stationary time series possesses an ergodic state and normative properties like those often observed for real-world bourses. PMID:16591903
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...
Stochastic flights of propellers
Pan, Margaret; Chiang, Eugene; Evans, Steven N
2012-01-01
Kilometer-sized moonlets in Saturn's A ring create S-shaped wakes called "propellers" in surrounding material. The Cassini spacecraft has tracked the motions of propellers for several years and finds that they deviate from Keplerian orbits having constant semimajor axes. The inferred orbital migration is known to switch sign. We show using a statistical test that the time series of orbital longitudes of the propeller Bl\\'eriot is consistent with that of a time-integrated Gaussian random walk. That is, Bl\\'eriot's observed migration pattern is consistent with being stochastic. We further show, using a combination of analytic estimates and collisional N-body simulations, that stochastic migration of the right magnitude to explain the Cassini observations can be driven by encounters with ring particles 10-20 m in radius. That the local ring mass is concentrated in decameter-sized particles is supported on independent grounds by occultation analyses.
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 ...
Stochastic Volatility Demand Systems
Apostolos Serletis; Maksim Isakin
2014-01-01
We address the estimation of stochastic volatility demand systems. In particular, we relax the homoscedasticity assumption and instead assume that the covariance matrix of the errors of demand systems is time-varying. Since most economic and fiÂ…nancial time series are nonlinear, we achieve superior modeling using parametric nonlinear demand systems in which the unconditional variance is constant but the conditional variance, like the conditional mean, is also a random variable depending on c...
Stochastic Overall Equipment Effectiveness
Zammori, Francesco Aldo; Braglia, Marcello; Frosolini, Marco
2011-01-01
Abstract This paper focuses on the Overall Equipment Effectiveness (OEE), a key performance indicator typically adopted to support Lean Manufacturing and Total Productive Maintenance. Unfortunately, being a deterministic metric, the OEE only provides a static representation of a process, but fails to capture the real variability of manufacturing performances. To take into account the stochastic nature of the OEE, an approximated procedure based on the application of the Central Lim...
Stochastic resonance and computation
Torres, José-Leonel; Trainor, Lynn
1997-09-01
Stochastic resonance (SR) occurs in bistable nonlinear systems subject to noise, as the entrainment of their output by a weak periodic modulation added to the input. Electronic computation involves switching of memory elements between two states that correspond to 1 and 0, respectively. The possibility of switching errors due to SR in memory elements is considered, showing that it represents a negligible danger to reliable computation.
Stochastic reconstruction of sandstones
Manwart, C.; Torquato, S.; Hilfer, R.
2000-01-01
A simulated annealing algorithm is employed to generate a stochastic model for a Berea and a Fontainebleau sandstone with 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 sandston...
Decentralized stochastic control
Mahajan, Aditya; Mannan, Mehnaz
2013-01-01
Decentralized stochastic control refers to the multi-stage optimization of a dynamical system by multiple controllers that have access to different information. Decentralization of information gives rise to new conceptual challenges that require new solution approaches. In this expository paper, we use the notion of an \\emph{information-state} to explain the two commonly used solution approaches to decentralized control: the person-by-person approach and the common-information approach.
International Nuclear Information System (INIS)
Evolution of waves subject to a randomly varying growth rate is considered and the statistical properties of the waves are calculated in terms of the mean, variance, and correlation time of the growth rate. This enables stochastic growth to be studied without needing full knowledge of the microphysics. However, where the microphysics is understood, this approach also allows it to be easily incorporated into studies of larger-scale phenomena involving stochastic growth. Stochastic differential equations and Fokker--Planck equations are obtained, which describe the wave evolution in the presence of a variety of linear and nonlinear processes and boundary conditions, and it is shown that these phenomena can be diagnosed observationally through their effects on the statistical distribution of the wave field strengths. The results are particularly useful for waves with small dispersion, where they explain the strong wave clumping often observed in nature and emphasize the role of marginal stability in setting the level about which fluctuations occur and in determining their magnitude. Application to type III solar radio bursts illustrates many of the main results and verifies and generalizes earlier conclusions reached using a less rigorous approach. In particular, a new condition for marginally stable propagation of type III solar electron beams is found. copyright 1995 American Institute of Physics
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.
Capturing the stochastic mechanical behavior of micro and nanopillars
International Nuclear Information System (INIS)
Experimental evidence has illustrated that micropillar deformation is highly stochastic, as the stress–strain curves are manifested by multiple strain bursts. Although initial theoretical works employing gradient plasticity can predict the stress–strain response of individual pillars, they cannot capture the stochastic effects observed for multiple same diameter specimens. This article presents simulations that are not only in precise qualitative and quantitative agreement with experimental stress–strain curves for varying diameter pillars, but can also account for the observed stochasticity in same diameter micropillars. This is accomplished by implementing gradient plasticity within a cellular automaton, while allowing the yield-stress to randomly vary within the micropillar. In concluding, it is shown that the aforementioned numerical code can also capture the stress drops and size dependent strengthening observed in metallic glass nanopillars
Stochastic and non-stochastic effects - a conceptual analysis
International Nuclear Information System (INIS)
The attempt to divide radiation effects into stochastic and non-stochastic effects is discussed. It is argued that radiation or toxicological effects are contingently related to radiation or chemical exposure. Biological effects in general can be described by general laws but these laws never represent a necessary connection. Actually stochastic effects express contingent, or empirical, connections while non-stochastic effects represent semantic and non-factual connections. These two expressions stem from two different levels of discourse. The consequence of this analysis for radiation biology and radiation protection is discussed. (author)
Cellular senescence in aging primates.
Herbig, Utz; Ferreira, Mark; Condel, Laura; Carey, Dee; Sedivy, John M
2006-03-01
The aging of organisms is characterized by a gradual functional decline of all organ systems. Mammalian somatic cells in culture display a limited proliferative life span, at the end of which they undergo an irreversible cell cycle arrest known as replicative senescence. Whether cellular senescence contributes to organismal aging has been controversial. We investigated telomere dysfunction, a recently discovered biomarker of cellular senescence, and found that the number of senescent fibroblasts increases exponentially in the skin of aging baboons, reaching >15% of all cells in very old individuals. In addition, the same cells contain activated ataxia-telangiectasia mutated kinase and heterochromatinized nuclei, confirming their senescent status. PMID:16456035
International Nuclear Information System (INIS)
The chemical phenotype of proneurotensin messenger RNA-expressing cells was determined in the acute haloperidol-treated rat striatum using a combination of [35S]-labelled and alkaline phosphatase-labelled oligonucleotides. Cellular sites of proneurotensin messenger RNA expression were visualized simultaneously on tissue sections processed to reveal cellular sites of preproenkephalin A messenger RNA or the dopamine and adenylate cyclase phosphoprotein-32, messenger RNA. The cellular co-expression of preproenkepahlin A and preprotachykinin messenger RNA was also examined within forebrain structures. Cellular sites of preproenkephalin A and dopamine and adenylate cyclase phosphoprotein-32 messenger RNAs were visualized using alkaline phosphatase-labelled oligonucleotides whilst sites of preprotachykinin and proneurotensin messenger RNA expression were detected using [35S]-labelled oligos. Cellular sites of enkephalin and dopamine and adenylate cyclase phosphoprotein-32 gene expression were identified microscopically by the concentration of purple alkaline phosphatase reaction product within the cell cytoplasm, whereas sites of substance P and proneurotensin gene expression were identified by the dense clustering of silver grains overlying cells.An intense hybridization signal was detected for all three neuropeptide messenger RNAs in the striatum, the nucleus accumbens and septum. Dopamine and adenylate cyclase phosphoprotein-32 messenger RNA was detected within the neostriatum but not within the septum. In all forebrain regions examined, with the exception of the islands of Cajella, the cellular expression of enkephalin messenger RNA and substance P messenger RNA was discordant; the two neuropeptide messenger RNAs were detected essentially in different cells, although in the striatum and nucleus accumbens occasional isolated cells were detected which contained both hybridization signals; dense clusters of silver grains overlay alkaline phosphatase-positive cells
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.
Robustness Analysis of Hybrid Stochastic Neural Networks with Neutral Terms and Time-Varying Delays
Chunmei Wu; Junhao Hu; Yan Li
2015-01-01
We analyze the robustness of global exponential stability of hybrid stochastic neural networks subject to neutral terms and time-varying delays simultaneously. Given globally exponentially stable hybrid stochastic neural networks, we characterize the upper bounds of contraction coefficients of neutral terms and time-varying delays by using the transcendental equation. Moreover, we prove theoretically that, for any globally exponentially stable hybrid stochastic neural networks, if additive ne...
Path-Dependent Optimal Stochastic Control and Viscosity Solution of Associated Bellman Equations
Tang, Shanjian; Zhang, Fu
2012-01-01
In this paper we study the optimal stochastic control problem for a path-dependent stochastic system under a recursive path-dependent cost functional, whose associated Bellman equation from dynamic programming principle is a path-dependent fully nonlinear partial differential equation of second order. A novel notion of viscosity solutions is introduced. Using Dupire's functional It\\^o calculus, we characterize the value functional of the optimal stochastic control problem as the unique viscos...
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
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.
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.
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...
The Effects of Reversibility and Noise on Stochastic Phosphorylation Cycles and Cascades
Miller, Clark A.; Beard, Daniel A.
2008-01-01
The phosphorylation-dephosphorylation cycle is a common motif in cellular signaling networks. Previous work has revealed that, when driven by a noisy input signal, these cycles may exhibit bistable behavior. Here, a recently introduced theorem on network bistability is applied to prove that the existence of bistability is dependent on the stochastic nature of the system. Furthermore, the thermodynamics of simple cycles and cascades is investigated in the stochastic setting. Because these cycl...
Stochastic Analysis with Financial Applications
Kohatsu-Higa, Arturo; Sheu, Shuenn-Jyi
2011-01-01
Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. This book also covers the areas of backward stochastic differential equations via the (non-li
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.
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.
Sugiyama, Mayu; Saitou, Takashi; Kurokawa, Hiroshi; Sakaue-Sawano, Asako; Imamura, Takeshi; Miyawaki, Atsushi; Iimura, Tadahiro
2014-12-01
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
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
Stochastic conditional intensity processes
DEFF Research Database (Denmark)
Bauwens, Luc; Hautsch, Nikolaus
2006-01-01
model allows for a wide range of (cross-)autocorrelation structures in multivariate point processes. The model is estimated by simulated maximum likelihood (SML) using the efficient importance sampling (EIS) technique. By modeling price intensities based on NYSE trading, we provide significant evidence......In this article, we introduce the so-called stochastic conditional intensity (SCI) model by extending Russell’s (1999) autoregressive conditional intensity (ACI) model by a latent common dynamic factor that jointly drives the individual intensity components. We show by simulations that the proposed...... for a joint latent factor and show that its inclusion allows for an improved and more parsimonious specification of the multivariate intensity process...
Structured Stochastic Linear Bandits
Johnson, Nicholas; Sivakumar, Vidyashankar; Banerjee, Arindam
2016-01-01
The stochastic linear bandit problem proceeds in rounds where at each round the algorithm selects a vector from a decision set after which it receives a noisy linear loss parameterized by an unknown vector. The goal in such a problem is to minimize the (pseudo) regret which is the difference between the total expected loss of the algorithm and the total expected loss of the best fixed vector in hindsight. In this paper, we consider settings where the unknown parameter has structure, e.g., spa...
Stochastic thermodynamics of resetting
Fuchs, Jaco; Goldt, Sebastian; Seifert, Udo
2016-03-01
Stochastic dynamics with random resetting leads to a non-equilibrium steady state. Here, we consider the thermodynamics of resetting by deriving the first and second law for resetting processes far from equilibrium. We identify the contributions to the entropy production of the system which arise due to resetting and show that they correspond to the rate with which information is either erased or created. Using Landauer's principle, we derive a bound on the amount of work that is required to maintain a resetting process. We discuss different regimes of resetting, including a Maxwell demon scenario where heat is extracted from a bath at constant temperature.
Stochastic cooling for beginners
International Nuclear Information System (INIS)
These two lectures have been prepared to give a simple introduction to the principles. In Part I we try to explain stochastic cooling using the time-domain picture which starts from the pulse response of the system. In Part II the discussion is repeated, looking more closely at the frequency-domain response. An attempt is made to familiarize the beginners with some of the elementary cooling equations, from the 'single particle case' up to equations which describe the evolution of the particle distribution. (orig.)
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.
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)
Kang MJ
2013-03-01
Full Text Available Myung Joo Kang, Sang Han Park, Mean Hyung Kang, Min Jung Park, Young Wook Choi College of Pharmacy, Chung-Ang University, Seoul, Korea Background: A novel dual ligand–modified liposome, folic acid-tethered Pep-1 peptide-conjugated liposomal nanocarrier (FP-Lipo, was designed to overcome the nonselectivity of conventional penetrating peptide-tagged nanoparticulates and to provide the advantage of selective targeting of the folic acid receptor, which is frequently overexpressed on epithelial cancer cells. Methods: FP-Lipo was prepared by a sequential process of formation of a maleimide-derivatized small unilamellar vesicle, postinsertion of distearoyl phosphatidyl ethanolamine-polyethylene glycol 2000–folate to the vesicle, and Pep-1 peptide conjugation via thiol-maleimide linkage. Conformational and physical characteristics of the FP-Lipo nanocarriers were investigated for the extent of Pep-1 peptide and folic acid on the surface, vesicle size, and zeta potential. In vitro cellular uptake behaviors of the novel carrier containing a fluorescein dextran isothiocyanate probe were examined by spectrophotometry or by confocal laser scanning microscopy. Results: A novel nanocarrier bearing approximately 750 folate ligands and 100 penetrating peptides per vesicle was successfully prepared. The physical properties were as follows: 140 nm in size; 5 mV in zeta potential; less than 0.3 in polydispersity index. An in vitro cellular uptake study revealed that the FP-Lipo nanocarrier system exhibited more than twofold enhanced translocation into the folic acid receptor–positive HeLa cells compared with the single Pep-1 peptide–modified liposome. Meanwhile, its cellular association and internalization into the folic acid receptor–negative normal HaCaT cells was comparable with that of Pep-1 peptide–modified liposome. Conclusion: An advanced dual ligand-modified liposome is potentially useful for the treatment of folic acid receptor
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...
Winkler, Dirk; Beconi, Maria; Toledo-Sherman, Leticia M; Prime, Michael; Ebneth, Andreas; Dominguez, Celia; Muñoz-Sanjuan, Ignacio
2013-09-01
Kynurenine monooxygenase (KMO) catalyzes the conversion of kynurenine to 3-hydroxykynurenine. Modulation of KMO activity has been implicated in several neurodegenerative diseases, including Huntington disease. Our goal is to develop potent and selective small-molecule KMO inhibitors with suitable pharmacokinetic characteristics for in vivo proof-of-concept studies and subsequent clinical development. We developed a comprehensive panel of biochemical and cell-based assays that use liquid chromatography/tandem mass spectrometry to quantify unlabeled kynurenine and 3-hydroxykynurenine. We describe assays to measure KMO inhibition in cell and tissue extracts, as well as cellular assays including heterologous cell lines and primary rat microglia and human peripheral blood mononuclear cells. PMID:23690293
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
Macromolecular lesions and cellular radiation chemistry
International Nuclear Information System (INIS)
Our studies of the interaction of densely ionizing particles with macromolecules in the living cell may be divided into four parts: characterization of lesions to cellular DNA in the unmodified Bragg ionization curve; characterization of lesions to cellular DNA in the spread Bragg curve as used in radiation therapy; elucidation of the cellular radiation chemistry characteristic of high vs. low LET radiation qualities; and the introduction of novel techniques designed to give a better understanding of the fundamental properties of induction of lesions and their repair potentials in high LET radiation
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.
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.
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...
Non Monotone Stochastic Evolution Equations
Kenneth L. Kuttler; Li, Ji
2013-01-01
An approach to stochastic evolution equations based on a simple generalization of known embedding theorems is presented. It allows for the inclusion of problems which have nonlinear non monotone operators. This is used to discuss the existence of strong solutions to a stochastic Navier Stokes problem in dimension less than four.
On stochastic finite difference schemes
Gyongy, Istvan
2013-01-01
Finite difference schemes in the spatial variable for degenerate stochastic parabolic PDEs are investigated. Sharp results on the rate of $L_p$ and almost sure convergence of the finite difference approximations are presented and results on Richardson extrapolation are established for stochastic parabolic schemes under smoothness assumptions.
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...
Alternative Asymmetric Stochastic Volatility Models
M. Asai (Manabu); M.J. McAleer (Michael)
2010-01-01
textabstractThe stochastic volatility model usually incorporates asymmetric effects by introducing the negative correlation between the innovations in returns and volatility. In this paper, we propose a new asymmetric stochastic volatility model, based on the leverage and size effects. The model is
Anticipated backward stochastic differential equations
Peng, Shige; Yang, Zhe
2009-01-01
In this paper we discuss new types of differential equations which we call anticipated backward stochastic differential equations (anticipated BSDEs). In these equations the generator includes not only the values of solutions of the present but also the future. We show that these anticipated BSDEs have unique solutions, a comparison theorem for their solutions, and a duality between them and stochastic differential delay equations.
Evolutionary computation in stochastic environments
Schmidt, Christian
2007-01-01
This book develops efficient methods for the application of Evolutionary Algorithms on stochastic problems. To achieve this, procedures for statistical selection are systematically analyzed with respect to different measures and significantly improved. It is shown how to adapt one of the best procedures for the needs of Evolutionary Algorithms and Evolutionary operators for efficient implementation in stochastic environments are identified.
Non-commutative stochastic distributions and applications to linear systems theory
Alpay, Daniel; Salomon, Guy
2012-01-01
In this paper, we introduce a non-commutative space of stochastic distributions, which contains the non-commutative white noise space, and forms, together with a natural multiplication, a topological algebra. A special inequality which holds in this space allows to characterize its invertible elements and to develop an appropriate framework of non-commutative stochastic linear systems.
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...
3-Dimensional Stochastic Seepage Analysis of a Yangtze River Embankment
Directory of Open Access Journals (Sweden)
Yajun Wang
2015-01-01
Full Text Available Three-dimensional stochastic simulation was performed to investigate the complexity of the seepage field of an embankment. Three-dimensional anisotropic heterogeneous steady state random seepage finite element model was developed. The material input data were derived from a statistical analysis of strata soil characteristics and geological columns. The Kolmogorov-Smirnov test was used to validate the hypothesis that the Gaussian probability distribution is applicable to the random permeability tensors. A stochastic boundary condition, the random variation of upstream and downstream water level, was taken into account in the three-dimensional finite element modelling. Furthermore, the functions of sheet-pile breakwater and catchwater were also incorporated as turbulent sources. This case, together with the variability of soil permeability, has been analyzed to investigate their influence on the hydraulic potential distributed and the random evolution of stochastic seepage field. Results from stochastic analyses have also been compared against those of deterministic analyses. The insights gained in this study suggest it is necessary, feasible, and practical to employ stochastic studies in seepage field problems. The method provides a more comprehensive stochastic algorithm than conventional ones to characterize and analyze three-dimensional random seepage field problems.
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...
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. PMID:25225046
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. PMID:26758854
Bunched beam stochastic cooling
Energy Technology Data Exchange (ETDEWEB)
Wei, Jie
1992-09-01
The scaling laws for bunched-beam stochastic cooling has been derived in terms of the optimum cooling rate and the mixing condition. In the case that particles occupy the entire sinusoidal rf bucket, the optimum cooling rate of the bunched beam is shown to be similar to that predicted from the coasting-beam theory using a beam of the same average density and mixing factor. However, in the case that particles occupy only the center of the bucket, the optimum rate decrease in proportion to the ratio of the bunch area to the bucket area. The cooling efficiency can be significantly improved if the synchrotron side-band spectrum is effectively broadened, e.g. by the transverse tune spread or by using a double rf system.
Bunched beam stochastic cooling
Energy Technology Data Exchange (ETDEWEB)
Wei, Jie.
1992-01-01
The scaling laws for bunched-beam stochastic cooling has been derived in terms of the optimum cooling rate and the mixing condition. In the case that particles occupy the entire sinusoidal rf bucket, the optimum cooling rate of the bunched beam is shown to be similar to that predicted from the coasting-beam theory using a beam of the same average density and mixing factor. However, in the case that particles occupy only the center of the bucket, the optimum rate decrease in proportion to the ratio of the bunch area to the bucket area. The cooling efficiency can be significantly improved if the synchrotron side-band spectrum is effectively broadened, e.g. by the transverse tune spread or by using a double rf system.
Stochastic Programming with Probability
Andrieu, Laetitia; Vázquez-Abad, Felisa
2007-01-01
In this work we study optimization problems subject to a failure constraint. This constraint is expressed in terms of a condition that causes failure, representing a physical or technical breakdown. We formulate the problem in terms of a probability constraint, where the level of "confidence" is a modelling parameter and has the interpretation that the probability of failure should not exceed that level. Application of the stochastic Arrow-Hurwicz algorithm poses two difficulties: one is structural and arises from the lack of convexity of the probability constraint, and the other is the estimation of the gradient of the probability constraint. We develop two gradient estimators with decreasing bias via a convolution method and a finite difference technique, respectively, and we provide a full analysis of convergence of the algorithms. Convergence results are used to tune the parameters of the numerical algorithms in order to achieve best convergence rates, and numerical results are included via an example of ...
Stochastic reconstruction of sandstones
International Nuclear Information System (INIS)
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. (c) 2000 The American Physical Society
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. PMID:11088546
Stochastic resonance in mammalian neuronal networks.
Gluckman, Bruce J.; So, Paul; Netoff, Theoden I.; Spano, Mark L.; Schiff, Steven J.
1998-09-01
We present stochastic resonance observed in the dynamics of neuronal networks from mammalian brain. Both sinusoidal signals and random noise were superimposed into an applied electric field. As the amplitude of the noise component was increased, an optimization (increase then decrease) in the signal-to-noise ratio of the network response to the sinusoidal signal was observed. The relationship between the measures used to characterize the dynamics is discussed. Finally, a computational model of these neuronal networks that includes the neuronal interactions with the electric field is presented to illustrate the physics behind the essential features of the experiment. (c) 1998 American Institute of Physics. PMID:12779762
Stochastic resonance in mammalian neuronal networks
International Nuclear Information System (INIS)
We present stochastic resonance observed in the dynamics of neuronal networks from mammalian brain. Both sinusoidal signals and random noise were superimposed into an applied electric field. As the amplitude of the noise component was increased, an optimization (increase then decrease) in the signal-to-noise ratio of the network response to the sinusoidal signal was observed. The relationship between the measures used to characterize the dynamics is discussed. Finally, a computational model of these neuronal networks that includes the neuronal interactions with the electric field is presented to illustrate the physics behind the essential features of the experiment. copyright 1998 American Institute of Physics
Backward stochastic differential equations and its application to stochastic control
Czech Academy of Sciences Publication Activity Database
Veverka, Petr
Praha : Nakladatelství ČVUT - výroba, 2010 - (Hobza, T.), s. 181-189 ISBN 978-80-01-04641-8. [Stochastic and Physical Monitoring Systems 2010. Děčín (CZ), 27.06.2010-03.07.2010] R&D Projects: GA ČR GD402/09/H045; GA ČR GAP402/10/1610 Institutional research plan: CEZ:AV0Z10750506 Keywords : BSDE * Stochastic control Subject RIV: BA - General Mathematics http://library.utia.cas.cz/separaty/2010/E/veverka-backward%20stochastic%20differential%20equations%20and%20its%20application%20to%20stochastic%20control.pdf
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
Linear stochastic neutron transport theory
International Nuclear Information System (INIS)
A new and direct derivation of the Bell-Pal fundamental equation for (low power) neutron stochastic behaviour in the Boltzmann continuum model is given. The development includes correlation of particle emission direction in induced and spontaneous fission. This leads to generalizations of the backward and forward equations for the mean and variance of neutron behaviour. The stochastic importance for neutron transport theory is introduced and related to the conventional deterministic importance. Defining equations and moment equations are derived and shown to be related to the backward fundamental equation with the detector distribution of the operational definition of stochastic importance playing the role of an adjoint source. (author)
Central limit theorems for multiple stochastic integrals and Malliavin calculus
Nualart, David; Ortiz, Salvador
2007-01-01
We give a new characterization for the convergence in distribution to a standard normal law of a sequence of multiple stochastic integrals of a fixed order with variance one, in terms of the Malliavin derivatives of the sequence. We extend our result to the multidimensional case and prove a weak convergence result for a sequence of square integrable random variables.
Stochastic dynamic equations on general time scales
Martin Bohner; Olexandr M. Stanzhytskyi; Anastasiia O. Bratochkina
2013-01-01
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.
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.
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.
Duclos, Guillaume; Erlenkaemper, Christoph; Garcia, Simon; Yevick, Hannah; Joanny, Jean-François; Silberzan, Pascal; Biology inspired physics at mesoscales Team; Physical approach of biological problems Team
We study the emergence of a nematic order in a two-dimensional tissue of apolar elongated fibroblast cells. Initially, these cells are very motile and the monolayer is characterized by giant density fluctuations, a signature of far-from-equilibrium systems. As the cell density increases because of proliferation, the cells align with each other forming large perfectly oriented domains while the cellular movements slow down and eventually freeze. Therefore topological defects characteristic of nematic phases remain trapped at long times, preventing the development of infinite domains. By analogy with classical non-active nematics, we have investigated the role of boundaries and we have shown that cells confined in stripes of width smaller than typically 500 µm are perfectly aligned in the stripe direction. Experiments performed in cross-shaped patterns show that both the number of cells and the degree of alignment impact the final orientation. Reference: Duclos G., Garcia S., Yevick H.G. and Silberzan P., ''Perfect nematic order in confined monolayers of spindle-shaped cells'', Soft Matter, 10, 14, 2014
Ricardo Josa-Fombellida; Juan Pablo Rincón-Zapatero
2008-01-01
This paper gives a new method to characterize Markov Perfect Nash Equilibrium in stochastic differential games by means of a set of Generalized Euler Equations. Necessary and sufficient conditions are given.
Nucleon structure from stochastic estimators
Bali, Gunnar S; Gläßle, Benjamin; Göckeler, Meinulf; Najjar, Johannes; Rödl, Rudolf; Schäfer, Andreas; Sternbeck, André; Söldner, Wolfgang
2013-01-01
Using stochastic estimators for connected meson and baryon three-point functions has successfully been tried in the past years. Compared to the standard sequential source method we trade the freedom to compute the current-to-sink propagator independently of the hadron sink for additional stochastic noise in our observables. In the case of the nucleon we can use this freedom to compute many different sink-momentum/polarization combinations, which grants access to more virtualities. We will present preliminary results on the scalar, electro-magnetic and axial form factors of the nucleon in $N_f=2+1$ lattice QCD and contrast the performance of the stochastic method to the sequential source method. We find the stochastic method to be competitive in terms of errors at fixed cost.
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 lag time in nucleated linear self-assembly
Tiwari, Nitin S.; van der Schoot, Paul
2016-06-01
Protein aggregation is of great importance in biology, e.g., in amyloid fibrillation. The aggregation processes that occur at the cellular scale must be highly stochastic in nature because of the statistical number fluctuations that arise on account of the small system size at the cellular scale. We study the nucleated reversible self-assembly of monomeric building blocks into polymer-like aggregates using the method of kinetic Monte Carlo. Kinetic Monte Carlo, being inherently stochastic, allows us to study the impact of fluctuations on the polymerization reactions. One of the most important characteristic features in this kind of problem is the existence of a lag phase before self-assembly takes off, which is what we focus attention on. We study the associated lag time as a function of system size and kinetic pathway. We find that the leading order stochastic contribution to the lag time before polymerization commences is inversely proportional to the system volume for large-enough system size for all nine reaction pathways tested. Finite-size corrections to this do depend on the kinetic pathway.
Optimization of stochastic database cracking
Bhardwaj, Meenesh
2013-01-01
Variant Stochastic cracking is a significantly more resilient approach to adaptive indexing. It showed [1]that Stochastic cracking uses each query as a hint on how to reorganize data, but not blindly so; it gains resilience and avoids performance bottlenecks by deliberately applying certain arbitrary choices in its decision making. Therefore bring, adaptive indexing forward to a mature formulation that confers the workload-robustness that previous approaches lacked. Original cracking relies o...
Pathwise construction of stochastic integrals
Nutz, Marcel
2012-01-01
We propose a method to construct the stochastic integral simultaneously under a non-dominated family of probability measures. Path-by-path, and without referring to a probability measure, we construct a sequence of Lebesgue-Stieltjes integrals whose medial limit coincides with the usual stochastic integral under essentially any probability measure such that the integrator is a semimartingale. This method applies to any predictable integrand.
On solving stochastic MADM problems
Văduva Ion; Resteanu Cornel
2009-01-01
The paper examines a MADM problem with stochastic attributes. The transformation of a stochastic MADM problem into a cardinal problem is done by the standardization of the probability distribution of each attribute X and calculating the information of each attribute as Shannon's entropy or Onicescu's informational energy. Some well known (performant) methods to solve a cardinal MADM problem are presented and a method for combining results of several methods to give a final MADM solution is di...
Abstractions of stochastic hybrid systems
Bujorianu, L.M.; Lygeros, J.; Bujorianu, M.C.
2005-01-01
Many control systems have large, infinite state space that can not be easily abstracted. One method to analyse and verify these systems is reachability analysis. It is frequently used for air traffic control and power plants. Because of lack of complete information about the environment or unpredicted changes, the stochastic approach is a viable alternative. In this paper, different ways of introducing rechability under uncertainty are presented. A new concept of stochastic bisimulation is in...
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.
Stochastic Geometric Partial Differential Equations
Czech Academy of Sciences Publication Activity Database
Brzezniak, Z.; Goldys, B.; Ondreját, Martin
1. Singapore : World Scientific Publishing Company, 2011 - (Zhao, H.; Truman, A.), s. 1-32 ISBN 978-981-4360-91-3. - (Interdisciplinary Mathematical Sciences. 12) R&D Projects: GA ČR GAP201/10/0752 Institutional support: RVO:67985556 Keywords : stochastic geometric * partial differential equations Subject RIV: BA - General Mathematics http://library.utia.cas.cz/separaty/2012/SI/ondrejat-stochastic geometric partial differential equations. pdf
Stochastic optimization: beyond mathematical programming
CERN. Geneva
2015-01-01
Stochastic optimization, among which bio-inspired algorithms, is gaining momentum in areas where more classical optimization algorithms fail to deliver satisfactory results, or simply cannot be directly applied. This presentation will introduce baseline stochastic optimization algorithms, and illustrate their efficiency in different domains, from continuous non-convex problems to combinatorial optimization problem, to problems for which a non-parametric formulation can help exploring unforeseen possible solution spaces.
Markovian Projection of Stochastic Processes
Bentata, Amel
2012-01-01
This PhD thesis studies various mathematical aspects of problems related to the Markovian projection of stochastic processes, and explores some ap- plications of the results obtained to mathematical finance, in the context of semimartingale models. Given a stochastic process ξ, modeled as a semimartingale, our aim is to build a Markov process X whose marginal laws are the same as ξ. This construction allows us to use analytical tools such as integro-differential equa- tions to explore or comp...
Stochastic quantization and gauge theories
International Nuclear Information System (INIS)
Stochastic quantization is presented taking the Flutuation-Dissipation Theorem as a guide. It is shown that the original approach of Parisi and Wu to gauge theories fails to give the right results to gauge invariant quantities when dimensional regularization is used. Although there is a simple solution in an abelian theory, in the non-abelian case it is probably necessary to start from a BRST invariant action instead of a gauge invariant one. Stochastic regularizations are also discussed. (author)
Stochastic comparisons of nonhomogeneous processes
Belzunce, Félix; Lillo, Rosa E.; Ruiz, José M.; Shaked, Moshe
2000-01-01
The purpose of this paper is to describe various conditions on the parameters of pairs of nonhomogeneous Poisson or birth processes under which the corresponding epoch or inter-epoch times are stochastically ordered in various senses. We derive results involving the usual stochastic order, the multivariate hazard rate order, the multivariate likelihood ratio order, and the multivariate mean residual life order. A sample of applications involving generalized Yule processes, load-sharing models...
Stochastic quantization and gauge invariance
International Nuclear Information System (INIS)
A survey of the fundamental ideas about Parisi-Wu's Stochastic Quantization Method, with applications to Scalar, Gauge and Fermionic theories, is done. In particular, the Analytic Stochastic Regularization Scheme is used to calculate the polarization tensor for Quantum Electrodynamics with Dirac bosons or Fermions. The regularization influence is studied for both theories and an extension of this method for some supersymmetrical models is suggested. (author)
An Automated Test Framework for Experimenting with Stochastic Behavior in Reconfigurable Logic
DEFF Research Database (Denmark)
Birklykke, Alex Aaen; Le Moullec, Yannick; Alminde, Lars; Prasad, Ramjee
In this paper, we present an automated test frame- work for the characterization of stochastic behavior in logic circuits. The framework is intended as a platform for experimenting with and providing statistics on digital architectures given behavioral uncertainties at the gate-level. As an...... block subject to voltage/frequency scaling and Vdd -noise. The framework provides easy interfacing with laboratory equipment, design of experiment capabilities and automatic test execution, thus providing a powerful tool for characterizing stochastic behavior in reconfigurable logic....
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...
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)....
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.
Nanomechanics of magnetically driven cellular endocytosis
Zablotskii, V.; Lunov, O.; Dejneka, A.; Jastrabík, L.; Polyakova, T.; Syrovets, T.; Simmet, Th.
2011-10-01
Being essential for many pharmacodynamic and pharmacokinetic processes and playing a crucial role in regulating substrate detachment that enables cellular locomotion, endocytotic mechanisms in many aspects still remain a mystery and therefore can hardly be controlled. Here, we report on experimental and modeling studies of the magnetically assisted endocytosis of functionalized superparamagnetic iron oxide nanoparticles by prostate cancer cells (PC-3) and characterize the time and force scales of the cellular uptake machinery. The results indicate how the cellular uptake rate could be controlled by applied magnetic field, membrane elasticity, and nanoparticle magnetic moment.
Cellular Automaton Model for Immunology of Tumor Growth
Voitikova, M
1998-01-01
The stochastic discrete space-time model of an immune response on tumor spreading in a two-dimensional square lattice has been developed. The immunity-tumor interactions are described at the cellular level and then transferred into the setting of cellular automata (CA). The multistate CA model for system, in which all statesoflattice sites, composing of both immune and tumor cells populations, are the functions of the states of the 12 nearest neighbors. The CA model incorporates the essential featuresof the immunity-tumor system. Three regimes of neoplastic evolution including metastatic tumor growth and screen effect by inactive immune cells surrounding a tumor have been predicted.
Mechanisms of Stochastic Diffusion of Energetic Ions in Spherical Tori
International Nuclear Information System (INIS)
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
Fully nonlinear dynamics of stochastic thin-film dewetting.
Nesic, S; Cuerno, R; Moro, E; Kondic, L
2015-12-01
The spontaneous formation of droplets via dewetting of a thin fluid film from a solid substrate allows materials nanostructuring. Often, it is crucial to be able to control the evolution, and to produce patterns characterized by regularly spaced droplets. While thermal fluctuations are expected to play a role in the dewetting process, their relevance has remained poorly understood, particularly during the nonlinear stages of evolution that involve droplet formation. Within a stochastic lubrication framework, we show that thermal noise substantially influences the process of droplets formation. Stochastic systems feature a smaller number of droplets with a larger variability in size and space distribution, when compared to their deterministic counterparts. Finally, we discuss the influence of stochasticity on droplet coarsening for asymptotically long times. PMID:26764623
Fully nonlinear dynamics of stochastic thin-film dewetting
Nesic, S.; Cuerno, R.; Moro, E.; Kondic, L.
2015-12-01
The spontaneous formation of droplets via dewetting of a thin fluid film from a solid substrate allows materials nanostructuring. Often, it is crucial to be able to control the evolution, and to produce patterns characterized by regularly spaced droplets. While thermal fluctuations are expected to play a role in the dewetting process, their relevance has remained poorly understood, particularly during the nonlinear stages of evolution that involve droplet formation. Within a stochastic lubrication framework, we show that thermal noise substantially influences the process of droplets formation. Stochastic systems feature a smaller number of droplets with a larger variability in size and space distribution, when compared to their deterministic counterparts. Finally, we discuss the influence of stochasticity on droplet coarsening for asymptotically long times.
The stochastic seasonal behavior of energy commodity convenience yields
International Nuclear Information System (INIS)
This paper contributes to the commodity pricing literature by consistently modeling the convenience yield with its empirically observed properties. Specifically, in this paper, we show how a four-factor model for the stochastic behavior of commodity prices, with two long- and short-term factors and two additional seasonal factors, may accommodate some of the most important empirically observed characteristics of commodity convenience yields, such as the mean reversion and stochastic seasonality. Based on this evidence, a theoretical model is presented and estimated to characterize the commodity convenience yield dynamics that are consistent with previous findings. We also show that commodity price seasonality is better estimated through convenience yields than through futures prices. - Highlights: • Energy commodity convenience yields exhibit mean reversion and stochastic seasonality. • We present a model for convenience yields accounting for their observed characteristics. • Commodity price seasonality is better estimated through convenience yields
Directory of Open Access Journals (Sweden)
S. Ghiamkazemi
2010-01-01
Full Text Available In this manuscript, we synthesized the potential non viral vector for gene delivery with proper transfection efficiency and low cytotoxicity. Polyethylenimine (PEI is a well-known cationic polymer which has high positive surface charge for condensing plasmid DNA. However; it is highly cytotoxic in many cell lines because of the high surface charge, non-biodegradability and non-biocompatibility. To enhance PEI biodegradability, the graft copolymer “PEG-g-PEI” was synthesized. To target cancer liver cells, two targeting ligands folic acid and galactose (lactobionic acid which are over expressed on human hepatocyte carcinoma were attached to graft copolymer and “FOL-PEG-g-PEI-GAL” copolymer was synthesized. Composition of this grafted copolymer was characterized using 1H-NMR and FTIR spectra. The molecular weight and zeta potential of this copolymer was compared to PEI. The particle size and zeta potential of FOL-PEG-g-PEI-GAL/DNA complexes at various N/P ratio were measured using dynamic light scattering (DLS. Cytotoxicity of the copolymer was also studied in cultured HepG2 human hepatoblastoma cell line. The FOL-PEG-g-PEI-GAL/DNA complexes at various N/P ratios exhibited no cytotoxicity in HepG2 cell line compared to PEI 25K as a control. The novel copolymer showed enhanced biodegradability in physiological conditions in compared with PEI and targeted cultured HepG2 cells. More importantly, significant transfection efficiency was exhibited in cancer liver cells. Together, our results showed that “FOL-PEG-g-PEI-GAL” nanoparticals could be considered as a useful non-viral vector for targeted gene delivery.
International Nuclear Information System (INIS)
In this manuscript, we synthesized the potential non viral vector for gene delivery with proper transfection efficiency and low cytotoxicity. Polyethylenimine (PEI) is a well-known cationic polymer which has high positive surface charge for condensing plasmid DNA. However; it is highly cytotoxic in many cell lines because of the high surface charge, non-biodegradability and non-biocompatibility. To enhance PEI biodegradability, the graft copolymer PEG-g-PEI was synthesized. To target cancer liver cells, two targeting ligands folic acid and galactose (lactobionic acid) which are over expressed on human hepatocyte carcinoma were attached to graft copolymer and FOL-PEG-g-PEI-GAL copolymer was synthesized. Composition of this grafted copolymer was characterized using 1H-NMR and FTIR spectra. The molecular weight and zeta potential of this copolymer was compared to PEI. The particle size and zeta potential of FOL-PEG-g-PEI-GAL/DNA complexes at various N/P ratio were measured using dynamic light scattering (DLS). Cytotoxicity of the copolymer was also studied in cultured HepG2 human hepatoblastoma cell line. The FOL-PEG-g-PEI-GAL/DNA complexes at various N/P ratios exhibited no cytotoxicity in HepG2 cell line compared to PEI 25K as a control. The novel copolymer showed enhanced biodegradability in physiological conditions in compared with PEI and targeted cultured HepG2 cells. More importantly, significant transfection efficiency was exhibited in cancer liver cells. Together, our results showed that FOL-PEG-g-PEI-GAL nanoparticles could be considered as a useful non-viral vector for targeted gene delivery.
Endy, Drew; Brent, Roger
2001-01-01
Representations of cellular processes that can be used to compute their future behaviour would be of general scientific and practical value. But past attempts to construct such representations have been disappointing. This is now changing. Increases in biological understanding combined with advances in computational methods and in computer power make it possible to foresee construction of useful and predictive simulations of cellular processes.
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.
Stacking with stochastic cooling
International Nuclear Information System (INIS)
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). 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 considerations to the 'azimuthal' schemes
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.
Deterministic versus stochastic trends: Detection and challenges
Fatichi, S.; Barbosa, S. M.; Caporali, E.; Silva, M. E.
2009-09-01
The detection of a trend in a time series and the evaluation of its magnitude and statistical significance is an important task in geophysical research. This importance is amplified in climate change contexts, since trends are often used to characterize long-term climate variability and to quantify the magnitude and the statistical significance of changes in climate time series, both at global and local scales. Recent studies have demonstrated that the stochastic behavior of a time series can change the statistical significance of a trend, especially if the time series exhibits long-range dependence. The present study examines the trends in time series of daily average temperature recorded in 26 stations in the Tuscany region (Italy). In this study a new framework for trend detection is proposed. First two parametric statistical tests, the Phillips-Perron test and the Kwiatkowski-Phillips-Schmidt-Shin test, are applied in order to test for trend stationary and difference stationary behavior in the temperature time series. Then long-range dependence is assessed using different approaches, including wavelet analysis, heuristic methods and by fitting fractionally integrated autoregressive moving average models. The trend detection results are further compared with the results obtained using nonparametric trend detection methods: Mann-Kendall, Cox-Stuart and Spearman's ρ tests. This study confirms an increase in uncertainty when pronounced stochastic behaviors are present in the data. Nevertheless, for approximately one third of the analyzed records, the stochastic behavior itself cannot explain the long-term features of the time series, and a deterministic positive trend is the most likely explanation.
The El Nino Stochastic Oscillator
Burgers, G
1997-01-01
Anomalies during an El Nino are dominated by a single, irregularly oscillating, mode. Equatorial dynamics has been linked to delayed-oscillator models of this mode. Usually, the El Nino mode is regarded as an unstable mode of the coupled atmosphere system and the irregularity is attributed to noise and possibly chaos. Here a variation on the delayed oscillator is explored. In this stochastic-oscillator view, El Nino is a stable mode excited by noise. It is shown that the autocorrelation function of the observed NINO3.4 index is that of a stochastic oscillator, within the measurement uncertainty. Decadal variations as would occur in a stochastic oscillator are shown to be comparable to those observed, only the increase in the long-term mean around 1980 is rather large. The observed dependence of the seasonal cycle on the variance and the correlation is so large that it can not be attributed to the natural variability of a stationary stochastic oscillator. So the El Niño stochastic-oscillator parameters must d...
Stochastic quantization and topological theories
International Nuclear Information System (INIS)
In the last two years topological quantum field theories (TQFT) have attached much attention. This paper reports that from the very beginning it was realized that due to a peculiar BRST-like symmetry these models admitted so-called Nicolai mapping: the Nicolai variables, in terms of which actions of the theories become gaussian, are nothing but (anti-) selfduality conditions or their generalizations. This fact became a starting point in the quest of possible stochastic interpretation to topological field theories. The reasons behind were quite simple and included, in particular, the well-known relations between stochastic processes and supersymmetry. The main goal would have been achieved, if it were possible to construct stochastic processes governed by Langevin or Fokker-Planck equations in a real Euclidean time leading to TQFT's path integrals (equivalently: to reformulate TQFTs as non-equilibrium phase dynamics of stochastic processes). Further on, if it would appear that these processes correspond to the stochastic quantization of theories of some definite kind, one could expect (d + 1)-dimensional TQFTs to share some common properties with d-dimensional ones
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.
Transcriptional stochasticity in gene expression.
Lipniacki, Tomasz; Paszek, Pawel; Marciniak-Czochra, Anna; Brasier, Allan R; Kimmel, Marek
2006-01-21
Due to the small number of copies of molecular species involved, such as DNA, mRNA and regulatory proteins, gene expression is a stochastic phenomenon. In eukaryotic cells, the stochastic effects primarily originate in regulation of gene activity. Transcription can be initiated by a single transcription factor binding to a specific regulatory site in the target gene. Stochasticity of transcription factor binding and dissociation is then amplified by transcription and translation, since target gene activation results in a burst of mRNA molecules, and each mRNA copy serves as a template for translating numerous protein molecules. In the present paper, we explore a mathematical approach to stochastic modeling. In this approach, the ordinary differential equations with a stochastic component for mRNA and protein levels in a single cells yield a system of first-order partial differential equations (PDEs) for two-dimensional probability density functions (pdf). We consider the following examples: Regulation of a single auto-repressing gene, and regulation of a system of two mutual repressors and of an activator-repressor system. The resulting PDEs are approximated by a system of many ordinary equations, which are then numerically solved. PMID:16039671
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 inp...... based on stochastic model checking and we compute closed form solutions for a number of interesting scenarios. The analyses are applied to the design of an intelligent smart electrical meter of the kind to be installed in European households by 2020....
Inversions of infinitely divisible distributions and conjugates of stochastic integral mappings
Sato, Ken-iti
2012-01-01
The dual of an infinitely divisible distribution on $\\mathbb{R}^d$ without Gaussian part defined in Sato, ALEA {\\bf 3} (2007), 67--110, is renamed to the inversion. Properties and characterization of the inversion are given. A stochastic integral mapping is a mapping $\\mu=\\Phi_{f}\\rho$ of $\\rho$ to $\\mu$ in the class of infinitely divisible distributions on $\\mathbb{R}^d$, where $\\mu$ is the distribution of an improper stochastic integral of a nonrandom function $f$ with respect to a L\\'{e}vy process on $\\mathbb{R}^d$ with distribution $\\rho$ at time 1. The concept of the conjugate is introduced for a class of stochastic integral mappings and its close connection with the inversion is shown. The domains and ranges of the conjugates of three two-parameter families of stochastic integral mappings are described. Applications to the study of the limits of the ranges of iterations of stochastic integral mappings are made.
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
Romanofsky, Robert R.
2010-01-01
The cellular reflectarray antenna is intended to replace conventional parabolic reflectors that must be physically aligned with a particular satellite in geostationary orbit. These arrays are designed for specified geographical locations, defined by latitude and longitude, each called a "cell." A particular cell occupies nominally 1,500 square miles (3,885 sq. km), but this varies according to latitude and longitude. The cellular reflectarray antenna designed for a particular cell is simply positioned to align with magnetic North, and the antenna surface is level (parallel to the ground). A given cellular reflectarray antenna will not operate in any other cell.
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
A stochastic approach to microphysics
International Nuclear Information System (INIS)
The presently widespread idea of ''vacuum population'', together with the quantum concept of vacuum fluctuations leads to assume a random level below that of matter. This stochastic approach starts by a reminder of the author's previous work, first on the relation of diffusion laws with the foundations of microphysics, and then on hadron spectrum. Following the latter, a random quark model is advanced; it gives to quark pairs properties similar to those of a harmonic oscillator or an elastic string, imagined as an explanation to their asymptotic freedom and their confinement. The stochastic study of such interactions as electron-nucleon, jets in e+e- collisions, or pp → π0 + X, gives form factors closely consistent with experiment. The conclusion is an epistemological comment (complementarity between stochastic and quantum domains, E.P.R. paradox, etc...)
Correlation functions in stochastic inflation
International Nuclear Information System (INIS)
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.)
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...
Stochastic approach to quantum mechanics
International Nuclear Information System (INIS)
A critical review of the Copenhagen interpretation of quantum mechanics, both in its early and later versions, shows that, as a model for the individual system, it suffers from severe conceptual difficulties, particularly with regard to the problem of measurement. Nor are the most common hidden variable interpretations free from complications in providing a physical explanation for the properties of the quantum system. A promising alternative interpretation is the stochastic approach, which presumes that every physical system is continually interacting with a hidden thermostat. This thermostat has a randomizing effect on the position variable and necessitates a probabilistic description of the path of the system. If the concepts of both backward and forward diffusion are utilized, it is possible to construct a straightforward stochastic rule for computing the mean value of any observable which has a classical operational definition. Estimates based upon this rule agree with standard quantum predictions up to second order in momentum but disagree in higher order terms. The rule also predicts the average measurement results for observables which cannot, in general, be estimated by the usual operator formalism. The Schroedinger equation is derivable by the stochastic approach if Newton's Second Law is assumed. Also, quantization of energy and the Heisenberg uncertainty principle are readily explained through the stochastic model, but spatial quantization is not predicted by this method. If the magnitude of the free velocity of the relativistic stochastic particle is assumed to be the speed of light, as in Dirac's relativistic theory of the electron, it is possible to provide a relativistic extension of the stochastic approach and to derive (from this extension) the Klein-Gordon equation
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.
Cellular Dynamics of RNA Modification
Yi, Chengqi; Pan, Tao
2011-01-01
Conspectus Decades of research have identified over 100 types of ribonucleosides that are post-transcriptionally modified. Many modified nucleosides are conserved in bacteria, archeae and eukaryotes, while some modified nucleosides are unique to each branch of life. However, the cellular and functional dynamics of RNA modifications remains largely unexplored, mostly due to the lack of functional hypotheses and experimental methods for quantification and large scale analysis. Just as many well characterized protein and DNA modifications, many RNA modifications are not essential for life. Instead, increasingly more evidence indicates that RNA modifications can play regulatory roles in cells, especially in response to stress conditions. In this Account, we review some known examples of RNA modifications that are dynamically controlled in cells and introduce some contemporary technologies and methods that enhance the studies of cellular dynamics of RNA modifications. Examples of RNA modifications discussed in this Account include (Figure 1): (1) 4-thio uridine (s4U) which can act as a cellular sensor of near UV-light; (2) queuosine (Q) which is a potential biomarker for malignancy; (3) N6-methyl adenine (m6A) which is the prevalent modification in eukaryotic mRNAs; and (4) pseudouridine (ψ) which are inducible by nutrient deprivation. Two recent technical advances that stimulated the studies of cellular dynamics of modified ribonucleosides are also described. First, a genome-wide method combines primer extension and microarray to study N1-methyl adenine (m1A) hypomodification in human tRNA. Second, a quantitative mass spectrometric method investigates dynamic changes of a wide range of tRNA modifications under stress conditions in yeast. In addition, we discuss potential mechanisms that control dynamic regulation of RNA modifications, and hypotheses for discovering potential RNA de-modification enzymes. We conclude the Account by highlighting the need to develop new
Cellular oncogenes in neoplasia.
Chan, V T; McGee, J O
1987-01-01
In recent years cellular homologues of many viral oncogenes have been identified. As these genes are partially homologous to viral oncogenes and are activated in some tumour cell lines they are termed "proto-oncogenes". In tumour cell lines proto-oncogenes are activated by either quantitative or qualitative changes in gene structure: activation of these genes was originally thought to be a necessary primary event in carcinogenesis, but activated cellular oncogenes, unlike viral oncogenes, do ...
Cellular Cardiomyoplasty: Clinical Application
Chachques, J. (J.); Acar, C; J. Herreros; Trainini, J. (Jorge); Prosper, F.; D’Attellis, N. (N.); Fabiani, J. N.; Carpentier, A
2004-01-01
Myocardial regeneration can be induced with the implantation of a variety of myogenic and angiogenic cell types. More than 150 patients have been treated with cellular cardiomyoplasty worldwide, 18 patients have been treated by our group. Cellular cardiomyoplasty seems to reduce the size and fibrosis of infarct scars, limit postischemic remodelling, and restore regional myocardial contractility. Techniques for skeletal myoblasts culture and ex vivo expansion using auto...
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.
Probability, Statistics, and Stochastic Processes
Olofsson, Peter
2011-01-01
A mathematical and intuitive approach to probability, statistics, and stochastic processes This textbook provides a unique, balanced approach to probability, statistics, and stochastic processes. Readers gain a solid foundation in all three fields that serves as a stepping stone to more advanced investigations into each area. This text combines a rigorous, calculus-based development of theory with a more intuitive approach that appeals to readers' sense of reason and logic, an approach developed through the author's many years of classroom experience. The text begins with three chapters that d
Stochastic vehicle routing with recourse
DEFF Research Database (Denmark)
Gørtz, Inge Li; Nagarajan, Viswanath; Saket, Rishi
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 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
Stochastic Optimization of Complex Systems
Energy Technology Data Exchange (ETDEWEB)
Birge, John R. [University of Chicago
2014-03-20
This project focused on methodologies for the solution of stochastic optimization problems based on relaxation and penalty methods, Monte Carlo simulation, parallel processing, and inverse optimization. The main results of the project were the development of a convergent method for the solution of models that include expectation constraints as in equilibrium models, improvement of Monte Carlo convergence through the use of a new method of sample batch optimization, the development of new parallel processing methods for stochastic unit commitment models, and the development of improved methods in combination with parallel processing for incorporating automatic differentiation methods into optimization.
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.
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 Modelling of Hydrologic Systems
DEFF Research Database (Denmark)
Jonsdottir, Harpa
2007-01-01
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...... are described, as at the time of publication these methods represent new contribution to hydrology. The second part also contains additional description of software used and a brief introduction to stiff systems. The system in one of the papers is stiff....
Stochastic modeling of Lagrangian accelerations
Reynolds, Andy
2002-11-01
It is shown how Sawford's second-order Lagrangian stochastic model (Phys. Fluids A 3, 1577-1586, 1991) for fluid-particle accelerations can be combined with a model for the evolution of the dissipation rate (Pope and Chen, Phys. Fluids A 2, 1437-1449, 1990) to produce a Lagrangian stochastic model that is consistent with both the measured distribution of Lagrangian accelerations (La Porta et al., Nature 409, 1017-1019, 2001) and Kolmogorov's similarity theory. The later condition is found not to be satisfied when a constant dissipation rate is employed and consistency with prescribed acceleration statistics is enforced through fulfilment of a well-mixed condition.
Stochastic cooling of bunched beams
International Nuclear Information System (INIS)
Numerical simulation studies are presented for transverse and longitudinal stochastic cooling of bunched particle beams. Radio frequency buckets of various shapes (e.g. rectangular, parabolic well, single sinusoidal waveform) are used to investigate the enhancement of phase space cooling by nonlinearities of synchrotron motion. The connection between the notions of Landau damping for instabilities and mixing for stochastic cooling are discussed. In particular, the need for synchrotron frequency spread for both Landau damping and good mixing is seen to be comparable for bunched beams
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.
Stochastic Simulation of Turing Patterns
Institute of Scientific and Technical Information of China (English)
FU Zheng-Ping; XU Xin-Hang; WANG Hong-Li; OUYANG Qi
2008-01-01
@@ We investigate the effects of intrinsic noise on Turing pattern formation near the onset of bifurcation from the homogeneous state to Turing pattern in the reaction-diffusion Brusselator. By performing stochastic simulations of the master equation and using Gillespie's algorithm, we check the spatiotemporal behaviour influenced by internal noises. We demonstrate that the patterns of occurrence frequency for the reaction and diffusion processes are also spatially ordered and temporally stable. Turing patterns are found to be robust against intrinsic fluctuations. Stochastic simulations also reveal that under the influence of intrinsic noises, the onset of Turing instability is advanced in comparison to that predicted deterministically.
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.
Stochastic model in microwave propagation
International Nuclear Information System (INIS)
Further experimental results of delay time in microwave propagation are reported in the presence of a lossy medium (wood). The measurements show that the presence of a lossy medium makes the propagation slightly superluminal. The results are interpreted on the basis of a stochastic (or path integral) model, showing how this model is able to describe each kind of physical system in which multi-path trajectories are present. -- Highlights: ► We present new experimental results on electromagnetic “anomalous” propagation. ► We apply a path integral theoretical model to wave propagation. ► Stochastic processes and multi-path trajectories in propagation are considered.
Stochastic heating of cooling flows
Pavlovski, Georgi
2009-01-01
It is generally accepted that the heating of gas in clusters of galaxies by active galactic nuclei (AGN) is a form of feedback. Feedback is required to ensure a long term, sustainable balance between heating and cooling. This work investigates the impact of proportional stochastic feedback on the energy balance in the intracluster medium. Using a generalised analytical model for a cluster atmosphere, it is shown that an energy equilibrium can be reached exponentially quickly. Applying the tools of stochastic calculus it is demonstrated that the result is robust with regard to the model parameters, even though they affect the amount of variability in the system.
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.
Elimination of stochasticity in stellarators
International Nuclear Information System (INIS)
A method for optimizing stellarator vacuum magnetic fields is introduced. Application of this method shows that the stochasticity of vacuum magnetic fields can be made negligible by proper choice of the coil configuration. This optimization is shown to increase the equilibrium β-limit by factors of two or more over that of the simple, straight coil winding law. This method is general and ought to be applicable to other systems in which stochasticity: (1) is a problem, yet (2) is affected by the design parameters
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....
Theory, technology, and technique of stochastic cooling
International Nuclear Information System (INIS)
The theory and technological implementation of stochastic cooling is described. Theoretical and technological limitations are discussed. Data from existing stochastic cooling systems are shown to illustrate some useful techniques
When greediness fails: Examples from stochastic scheduling
Uetz, Marc
2002-01-01
The purpose of this paper is to present examples which show that deterministic and stochastic scheduling problems often have a surprisingly different behavior. In particular, it demonstrates some seemingly counterintuitive properties of optimal scheduling policies for stochastic machine scheduling problems.
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)
State-feedback H2/H-infinity controller design with D-stability constraints for stochastic systems
Institute of Scientific and Technical Information of China (English)
Zhongwei LIN; Weihai ZHANG
2007-01-01
This paper addresses the state-feedback H2/H-infinity controller design that satisfies D-stability constraints for stochastic systems. Firstly, the concept of regional stability for stochastic systems is defined in linear matrix inequality(LMI) regions; Secondly, the characterization about stochastic D-stability is presented. This paper introduces a new technique to solve the regional stability problem for stochastic systems, which is different from the pole placement technique ever used in deterministic systems. Based on this, in the state-feedback case, mixed H2/H-infinity synthesis with D-stability constraints is discussed via LMI optimization.
Enhancing stochastic kriging metamodels with gradient estimators
Chen, X.; Ankenman, B. E.; Nelson, B. L.
2013-01-01
Stochastic kriging is a new metamodeling technique for effectively representing the mean response surface implied by a stochastic simulation; it takes into account both stochastic simulation noise and uncertainty about the underlying response surface of interest. We show theoretically, through some simplified models, that incorporating gradient estimators into stochastic kriging tends to significantly improve surface prediction. To address the issue of which type of gradient estimator to use,...
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
Quantum stochastic calculus with maximal operator domains
Lindsay, J Martin; Attal, Stéphane
2004-01-01
Quantum stochastic calculus is extended in a new formulation in which its stochastic integrals achieve their natural and maximal domains. Operator adaptedness, conditional expectations and stochastic integrals are all defined simply in terms of the orthogonal projections of the time filtration of Fock space, together with sections of the adapted gradient operator. Free from exponential vector domains, our stochastic integrals may be satisfactorily composed yielding quantum Itô formulas for op...
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.
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.
On Modeling Coverage and Rate of Random Cellular Networks under Generic Channel Fading
Al-Hourani, Akram; Kandeepan, Sithamparanathan
2016-01-01
In this paper we provide an analytic framework for computing the expected downlink coverage probability, and the associated data rate of cellular networks, where base stations are distributed in a random manner. The provided expressions are in computable integral forms that accommodate generic channel fading conditions. We develop these expressions by modelling the cellular interference using stochastic geometry analysis, then we employ them for comparing the coverage resulting from various c...
Stability of stochastic switched SIRS models
Meng, Xiaoying; Liu, Xinzhi; Deng, Feiqi
2011-11-01
Stochastic stability problems of a stochastic switched SIRS model with or without distributed time delay are considered. By utilizing the Lyapunov methods, sufficient stability conditions of the disease-free equilibrium are established. Stability conditions about the subsystem of the stochastic switched SIRS systems are also obtained.
Models and algorithms for stochastic online scheduling
Megow, N.; Uetz, M.J.; Vredeveld, T.
2006-01-01
We consider a model for scheduling under uncertainty. In this model, we combine the main characteristics of online and stochastic scheduling in a simple and natural way. Job processing times are assumed to be stochastic, but in contrast to traditional stochastic scheduling models, we assume that job
On physical diffusion and stochastic diffusion
Narasimhan, T.N.
2010-01-01
Although the same mathematical expression is used to describe physical diffusion and stochastic diffusion, there are intrinsic similarities and differences in their nature. A comparative study shows that characteristic terms of physical and stochastic diffusion cannot be placed exactly in one-to-one correspondence. Therefore, judgment needs to be exercised in transferring ideas between physical and stochastic diffusion.
Robustness Analysis of Hybrid Stochastic Neural Networks with Neutral Terms and Time-Varying Delays
Directory of Open Access Journals (Sweden)
Chunmei Wu
2015-01-01
Full Text Available We analyze the robustness of global exponential stability of hybrid stochastic neural networks subject to neutral terms and time-varying delays simultaneously. Given globally exponentially stable hybrid stochastic neural networks, we characterize the upper bounds of contraction coefficients of neutral terms and time-varying delays by using the transcendental equation. Moreover, we prove theoretically that, for any globally exponentially stable hybrid stochastic neural networks, if additive neutral terms and time-varying delays are smaller than the upper bounds arrived, then the perturbed neural networks are guaranteed to also be globally exponentially stable. Finally, a numerical simulation example is given to illustrate the presented criteria.
Short-term Probabilistic Forecasting of Wind Speed Using Stochastic Differential Equations
DEFF Research Database (Denmark)
Iversen, Jan Emil Banning; Morales González, Juan Miguel; Møller, Jan Kloppenborg;
2016-01-01
and uncertain nature. In this paper, we propose a modeling framework for wind speed that is based on stochastic differential equations. We show that stochastic differential equations allow us to naturally capture the time dependence structure of wind speed prediction errors (from 1 up to 24 hours...... ahead) and, most importantly, to derive point and quantile forecasts, predictive distributions, and time-path trajectories (also referred to as scenarios or ensemble forecasts), all by one single stochastic differential equation model characterized by a few parameters....
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...
Information theory in stochastic process
International Nuclear Information System (INIS)
Methods for calculating the Kolmogorov-Sinai disorder from Gaussian Probability density functions and by using information theory for chaotic dynamical systems are suggested. The autoregressive models may prove stochastic deterministic both for chaotic and non-chaotic dynamical systems. (author)
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 Subspace Modelling of Turbulence
DEFF Research Database (Denmark)
Sichani, Mahdi Teimouri; Pedersen, B. J.; Nielsen, Søren R.K.
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 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.
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 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 for...... river geometries are formulated and a coupling between hydraulic computational methods and numerical reliability methods is presented....
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.
A stochastic model of radiation-induced bone marrow damage
Energy Technology Data Exchange (ETDEWEB)
Cotlet, G.; Blue, T.E.
2000-03-01
A stochastic model, based on consensus principles from radiation biology, is used to estimate bone-marrow stem cell pool survival (CFU-S and stroma cells) after irradiation. The dose response model consists of three coupled first order linear differential equations which quantitatively describe time dependent cellular damage, repair, and killing of red bone marrow cells. This system of differential equations is solved analytically through the use of a matrix approach for continuous and fractionated irradiations. The analytic solutions are confirmed through the dynamical solution of the model equations using SIMULINK. Rate coefficients describing the cellular processes of radiation damage and repair, extrapolated to humans from animal data sets and adjusted for neutron-gamma mixed fields, are employed in a SIMULINK analysis of criticality accidents. The results show that, for the time structures which may occur in criticality accidents, cell survival is established mainly by the average dose and dose rate.
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...
Algorithmic advances in stochastic programming
Energy Technology Data Exchange (ETDEWEB)
Morton, D.P.
1993-07-01
Practical planning problems with deterministic forecasts of inherently uncertain parameters often yield unsatisfactory solutions. Stochastic programming formulations allow uncertain parameters to be modeled as random variables with known distributions, but the size of the resulting mathematical programs can be formidable. Decomposition-based algorithms take advantage of special structure and provide an attractive approach to such problems. We consider two classes of decomposition-based stochastic programming algorithms. The first type of algorithm addresses problems with a ``manageable`` number of scenarios. The second class incorporates Monte Carlo sampling within a decomposition algorithm. We develop and empirically study an enhanced Benders decomposition algorithm for solving multistage stochastic linear programs within a prespecified tolerance. The enhancements include warm start basis selection, preliminary cut generation, the multicut procedure, and decision tree traversing strategies. Computational results are presented for a collection of ``real-world`` multistage stochastic hydroelectric scheduling problems. Recently, there has been an increased focus on decomposition-based algorithms that use sampling within the optimization framework. These approaches hold much promise for solving stochastic programs with many scenarios. A critical component of such algorithms is a stopping criterion to ensure the quality of the solution. With this as motivation, we develop a stopping rule theory for algorithms in which bounds on the optimal objective function value are estimated by sampling. Rules are provided for selecting sample sizes and terminating the algorithm under which asymptotic validity of confidence interval statements for the quality of the proposed solution can be verified. Issues associated with the application of this theory to two sampling-based algorithms are considered, and preliminary empirical coverage results are presented.
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...
A note on stochastic dynamics in the state space of a commutative C*-algebra
International Nuclear Information System (INIS)
A functional characterization of stochastic evolutions within the state spaces of commutative C*-algebras with identity is derived. Consequences concerning the structure of those linear evolution equations (master equations) that give occassion to stochastic evolutions are discussed. In part, these results generalize facts which are well-known from the finite dimensional classical case. Examples are given and some important particularities of the W*-case are developed. (author)
Weiyin Fei
2014-01-01
This paper first describes a class of uncertain stochastic control systems with Markovian switching, and derives an It\\^o-Liu formula for Markov-modulated processes. And we characterize an optimal control law, which satisfies the generalized Hamilton-Jacobi-Bellman (HJB) equation with Markovian switching. Then, by using the generalized HJB equation, we deduce the optimal consumption and portfolio policies under uncertain stochastic financial markets with Markovian switching. Finally, for cons...
On L2-stability of solutions of linear stochastic delay differential equations
Gilsing, Hagen
2003-01-01
Stochastic Delay Differential Equations (SDDE) are Stochastic Functional Differential Equations with important applications. It is of interest to characterize the L2-stability (stability of second moments) of solutions of SDDE. For the class of linear, scalar SDDE we can show that second comoment function of the solution satisfies a partial differential equation (PDE) with time delay and derive a characteristic equation from it determining the asymptotic behaviour of the second moments. Addit...
Ergodic Optimal Quadratic Control for an Affine Equation with Stochastic and Stationary Coefficients
Guatteri, G; Masiero, F
2008-01-01
We study ergodic quadratic optimal stochastic control problems for an affine state equation with state and control dependent noise and with stochastic coefficients. We assume stationarity of the coefficients and a finite cost condition. We first treat the stationary case and we show that the optimal cost corresponding to this ergodic control problem coincides with the one corresponding to a suitable stationary control problem and we provide a full characterization of the ergodic optimal cost ...
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.
Cellular Homeostasis and Aging.
Hartl, F Ulrich
2016-06-01
Aging and longevity are controlled by a multiplicity of molecular and cellular signaling events that interface with environmental factors to maintain cellular homeostasis. Modulation of these pathways to extend life span, including insulin-like signaling and the response to dietary restriction, identified the cellular machineries and networks of protein homeostasis (proteostasis) and stress resistance pathways as critical players in the aging process. A decline of proteostasis capacity during aging leads to dysfunction of specific cell types and tissues, rendering the organism susceptible to a range of chronic diseases. This volume of the Annual Review of Biochemistry contains a set of two reviews addressing our current understanding of the molecular mechanisms underlying aging in model organisms and humans. PMID:27050288
Cellular structure of space near time singularity in the Einstein equations
International Nuclear Information System (INIS)
Taking one of the general cosmological solutions as an example it is shown, that under the metric evolution to singularity in stochastic oscillation regime areas with small-scale cellular structure of 3-geometry are formed near it. Statistics of indices and time dependence of lengths in such areas are investigated
Role of Noise in a Market Model with Stochastic Volatility
Bonanno, G.; Valenti, D.; Spagnolo, B
2005-01-01
We study a generalization of the Heston model, which consists of two coupled stochastic differential equations, one for the stock price and the other one for the volatility. We consider a cubic nonlinearity in the first equation and a correlation between the two Wiener processes, which model the two white noise sources. This model can be useful to describe the market dynamics characterized by different regimes corresponding to normal and extreme days. We analyze the effect of the noise on the...
Stochastic Modeling and Simulation of Reaction-Diffusion Biochemical Systems
LI Fei
2016-01-01
Reaction Diffusion Master Equation (RDME) framework, characterized by the discretization of the spatial domain, is one of the most widely used methods in the stochastic simulation of reaction-diffusion systems. Discretization sizes for RDME have to be appropriately chosen such that each discrete compartment is "well-stirred" and the computational cost is not too expensive. An efficient discretization size based on the reaction-diffusion dynamics of each species is derived in this disserta...
Deterministic and stochastic study of wind farm harmonic currents
Sainz Sapera, Luis; Mesas García, Juan José; Teodorescu, Remus; Rodríguez Cortés, Pedro
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 18MWwind 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 char...
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.
Nonlinear and stochastic dynamics in the heart
International Nuclear Information System (INIS)
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
Wireless Cellular Mobile Communications
Directory of Open Access Journals (Sweden)
V. Zalud
2002-12-01
Full Text Available In this article is briefly reviewed the history of wireless cellularmobile communications, examined the progress in current secondgeneration (2G cellular standards and discussed their migration to thethird generation (3G. The European 2G cellular standard GSM and itsevolution phases GPRS and EDGE are described somewhat in detail. Thethird generation standard UMTS taking up on GSM/GPRS core network andequipped with a new advanced access network on the basis of codedivision multiple access (CDMA is investigated too. A sketch of theperspective of mobile communication beyond 3G concludes this article.
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...
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...
Translating partitioned cellular automata into classical type cellular automata
Poupet, Victor
2008-01-01
Partitioned cellular automata are a variant of cellular automata that was defined in order to make it very simple to create complex automata having strong properties such as number conservation and reversibility (which are often difficult to obtain on cellular automata). In this article we show how a partitioned cellular automaton can be translated into a regular cellular automaton in such a way that these properties are conserved.
Stochastic resonance of vortices in a washboard pinning potential
International Nuclear Information System (INIS)
Highlights: • The dynamics of Abrikosov vortices in a cosine pinning potential is investigated. • The voltage responses are predicted to demonstrate stochastic resonance. • Experimental parameters for observing stochastic resonance are suggested. - Abstract: In a bistable potential at low temperatures, stochastic resonance can be characterized as a synchronization effect of the hopping mechanism induced by an external periodic stimulus, where synchronization attains a maximum by fine-tuning the forcing frequency close to the relevant switching rate. In this work, we theoretically investigate the nonlinear single-vortex dynamics in a tilted cosine (multistable) washboard pinning potential at nonzero temperature in the presence of dc and ac currents of arbitrary amplitudes and frequency. The conditions for stochastic resonance to appear are derived on the basis of the exact solution of the corresponding Langevin equation for non-interacting vortices in terms of a matrix continued fraction. The nonlinear ac voltage response is analyzed as a function of temperature, dc bias, ac amplitude and frequency, with particular focus on the amplification of the external harmonic signal and its conversion to the third harmonics of the input frequency
Stochastic optimization of multireservoir systems via reinforcement learning
Lee, Jin-Hee; Labadie, John W.
2007-11-01
Although several variants of stochastic dynamic programming have been applied to optimal operation of multireservoir systems, they have been plagued by a high-dimensional state space and the inability to accurately incorporate the stochastic environment as characterized by temporally and spatially correlated hydrologic inflows. Reinforcement learning has emerged as an effective approach to solving sequential decision problems by combining concepts from artificial intelligence, cognitive science, and operations research. A reinforcement learning system has a mathematical foundation similar to dynamic programming and Markov decision processes, with the goal of maximizing the long-term reward or returns as conditioned on the state of the system environment and the immediate reward obtained from operational decisions. Reinforcement learning can include Monte Carlo simulation where transition probabilities and rewards are not explicitly known a priori. The Q-Learning method in reinforcement learning is demonstrated on the two-reservoir Geum River system, South Korea, and is shown to outperform implicit stochastic dynamic programming and sampling stochastic dynamic programming methods.
Genetic Dominance & Cellular Processes
Seager, Robert D.
2014-01-01
In learning genetics, many students misunderstand and misinterpret what "dominance" means. Understanding is easier if students realize that dominance is not a mechanism, but rather a consequence of underlying cellular processes. For example, metabolic pathways are often little affected by changes in enzyme concentration. This means that…
Radioactivity of cellular concrete
International Nuclear Information System (INIS)
The natural radioactivity of cellular concrete is discussed. Some data on the concentrations of 40K, 226Ra and 232Th in building materials in Poland are given. The results of dose rates measurements in living quarters as well as outside are presented. (A.S.)
Claman, Henry N.
1973-01-01
Discusses the nature of the immune response and traces many of the discoveries that have led to the present state of knowledge in immunology. The new cellular immunology is directing its efforts toward improving health by proper manipulation of the immune mechanisms of the body. (JR)
Energy Technology Data Exchange (ETDEWEB)
Cirioni, L.; Patau, J.P.; Nepveu, F. [Universite Paul Sabatier, 31 - Toulouse (France)
1998-04-01
A Monte Carlo code is developed to study the action of particles in Boron Neutron Capture Therapy (BNCT). Our aim is to calculate the probability of dissipating a lethal dose in cell nuclei. Cytoplasmic and nuclear membranes are considered as non-concentric ellipsoids. All geometrical parameters may be adjusted to fit actual configurations. The reactions {sup 10}B(n,{gamma} {alpha}){sup 7}Li and {sup 14}N(n,p) {sup 14}C create heavy ions which slow clown losing their energy. Their trajectories can be simulated taking into account path length straggling. The contribution of each reaction to the deposited dose in different cellular compartments can be studied and analysed for any distribution of {sup 10}B. (authors)
Rapid Cellular Turnover in Adipose Tissue
Alessandra Rigamonti; Kristen Brennand; Frank Lau; Cowan, Chad A.
2011-01-01
It was recently shown that cellular turnover occurs within the human adipocyte population. Through three independent experimental approaches — dilution of an inducible histone 2B-green fluorescent protein (H2BGFP), labeling with the cell cycle marker Ki67 and incorporation of BrdU — we characterized the degree of cellular turnover in murine adipose tissue. We observed rapid turnover of the adipocyte population, finding that 4.8% of preadipocytes are replicating at any time and that between 1–...
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 stability of traffic maps
International Nuclear Information System (INIS)
We study the ergodic properties of a family of traffic maps acting in the space of bi-infinite sequences of real numbers. The corresponding dynamics mimics the motion of vehicles in a simple traffic flow, which explains the name. Using connections to topological Markov chains we obtain nontrivial invariant measures, prove their stochastic stability and calculate the topological entropy. Technically these results in the deterministic setting are related to the construction of measures of maximal entropy via measures uniformly distributed on periodic points of a given period, while in the random setting we construct (spatially) Markov invariant measures directly. In distinction to conventional results the limiting measures in the non-lattice case are non-ergodic. The average velocity of individual ‘vehicles’ as a function of their density and its stochastic stability is studied as well. (paper)
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...
Stochastic models of cell motility
DEFF Research Database (Denmark)
Gradinaru, Cristian
2012-01-01
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...... coefficient. By adding a persistence component to simple random motion I introduce the standard Ornstein-Uhlenbeck process. I build on this commonly used cell motility model to address the challenges of working with real-life data: positional (centroid coordinate measuring) error and time discretization (due...... generalizing the Orstein-Uhlenbeck process to study cell motility on anisotropic substrates. I apply the general model to analyze cell motility on a series of anisotropic substrates and discuss the implications of our observations. This work is potentially useful to cell biologists by addressing their need for...
Limits for Stochastic Reaction Networks
DEFF Research Database (Denmark)
Cappelletti, Daniele
Reaction systems have been introduced in the 70s to model biochemical systems. Nowadays their range of applications has increased and they are fruitfully used in dierent elds. The concept is simple: some chemical species react, the set of chemical reactions form a graph and a rate function is...... associated with each reaction. Such functions describe the speed of the dierent reactions, or their propensities. Two modelling regimes are then available: the evolution of the dierent species concentrations can be deterministically modelled through a system of ODE, while the counts of the dierent species 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...
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...
Concentration Bounds for Stochastic Approximations
Frikha, Noufel
2012-01-01
We obtain non asymptotic concentration bounds for two kinds of stochastic approximations. We first consider the deviations between the expectation of a given function of the Euler scheme of some diffusion process at a fixed deterministic time and its empirical mean obtained by the Monte-Carlo procedure. We then give some estimates concerning the deviation between the value at a given time-step of a stochastic approximation algorithm and its target. Under suitable assumptions both concentration bounds turn out to be Gaussian. The key tool consists in exploiting accurately the concentration properties of the increments of the schemes. For the first case, as opposed to the previous work of Lemaire and Menozzi (EJP, 2010), we do not have any systematic bias in our estimates. Also, no specific non-degeneracy conditions are assumed.
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 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 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...... variation by height is adopted. A particular problem for simulation studies with finite time steps is the construction of a reflection rule different from the rule of perfect reflection at the boundaries such that the rule complies with the imposed skewness of the velocity distribution for particle...... 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...
The analysis of stochastic stability of stochastic models that describe tumor-immune systems
Chis, O; Opris, D
2009-01-01
In this paper we investigate some stochastic models for tumor-immune systems. To describe these models, we used a Wiener process, as the noise has a stabilization effect. Their dynamics are studied in terms of stochastic stability in the equilibrium points, by constructing the Lyapunov exponent, depending on the parameters that describe the model. Stochastic stability was also proved by constructing a Lyapunov function. We have studied and and analyzed a Kuznetsov-Taylor like stochastic model and a Bell stochastic model for tumor-immune systems. These stochastic models are studied from stability point of view and they were represented using the second Euler scheme and Maple 12 software.