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.
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.
Unified Stochastic Geometry Model for MIMO Cellular Networks with Retransmissions
Afify, Laila H.
2016-10-11
This paper presents a unified mathematical paradigm, based on stochastic geometry, for downlink cellular networks with multiple-input-multiple-output (MIMO) base stations (BSs). The developed paradigm accounts for signal retransmission upon decoding errors, in which the temporal correlation among the signal-to-interference-plus-noise-ratio (SINR) of the original and retransmitted signals is captured. In addition to modeling the effect of retransmission on the network performance, the developed mathematical model presents twofold analysis unification for MIMO cellular networks literature. First, it integrates the tangible decoding error probability and the abstracted (i.e., modulation scheme and receiver type agnostic) outage probability analysis, which are largely disjoint in the literature. Second, it unifies the analysis for different MIMO configurations. The unified MIMO analysis is achieved by abstracting unnecessary information conveyed within the interfering signals by Gaussian signaling approximation along with an equivalent SISO representation for the per-data stream SINR in MIMO cellular networks. We show that the proposed unification simplifies the analysis without sacrificing the model accuracy. To this end, we discuss the diversity-multiplexing tradeoff imposed by different MIMO schemes and shed light on the diversity loss due to the temporal correlation among the SINRs of the original and retransmitted signals. Finally, several design insights are highlighted.
Stochastic Reservoir Characterization Constrained by Seismic Data
Energy Technology Data Exchange (ETDEWEB)
Eide, Alfhild Lien
1999-07-01
In order to predict future production of oil and gas from a petroleum reservoir, it is important to have a good description of the reservoir in terms of geometry and physical parameters. This description is used as input to large numerical models for the fluid flow in the reservoir. With increased quality of seismic data, it is becoming possible to extend their use from the study of large geologic structures such as seismic horizons to characterization of the properties of the reservoir between the horizons. Uncertainties because of the low resolution of seismic data can be successfully handled by means of stochastic modeling, and spatial statistics can provide tools for interpolation and simulation of reservoir properties not completely resolved by seismic data. This thesis deals with stochastic reservoir modeling conditioned to seismic data and well data. Part I presents a new model for stochastic reservoir characterization conditioned to seismic traces. Part II deals with stochastic simulation of high resolution impedance conditioned to measured impedance. Part III develops a new stochastic model for calcite cemented objects in a sandstone background; it is a superposition of a marked point model for the calcites and a continuous model for the background.
A stochastic parameterization for deep convection using cellular automata
Bengtsson, L.; Steinheimer, M.; Bechtold, P.; Geleyn, J.
2012-12-01
Cumulus parameterizations used in most operational weather and climate models today are based on the mass-flux concept which took form in the early 1970's. In such schemes it is assumed that a unique relationship exists between the ensemble-average of the sub-grid convection, and the instantaneous state of the atmosphere in a vertical grid box column. However, such a relationship is unlikely to be described by a simple deterministic function (Palmer, 2011). Thus, because of the statistical nature of the parameterization challenge, it has been recognized by the community that it is important to introduce stochastic elements to the parameterizations (for instance: Plant and Craig, 2008, Khouider et al. 2010, Frenkel et al. 2011, Bentsson et al. 2011, but the list is far from exhaustive). There are undoubtedly many ways in which stochastisity can enter new developments. In this study we use a two-way interacting cellular automata (CA), as its intrinsic nature possesses many qualities interesting for deep convection parameterization. In the one-dimensional entraining plume approach, there is no parameterization of horizontal transport of heat, moisture or momentum due to cumulus convection. In reality, mass transport due to gravity waves that propagate in the horizontal can trigger new convection, important for the organization of deep convection (Huang, 1988). The self-organizational characteristics of the CA allows for lateral communication between adjacent NWP model grid-boxes, and temporal memory. Thus the CA scheme used in this study contain three interesting components for representation of cumulus convection, which are not present in the traditional one-dimensional bulk entraining plume method: horizontal communication, memory and stochastisity. The scheme is implemented in the high resolution regional NWP model ALARO, and simulations show enhanced organization of convective activity along squall-lines. Probabilistic evaluation demonstrate an enhanced spread in
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.
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.
Bialecki, Mariusz
2010-01-01
Inspired by extremely simplified view of the earthquakes we propose the stochastic domino cellular automaton model exhibiting avalanches. From elementary combinatorial arguments we derive a set of nonlinear equations describing the automaton. Exact relations between the average parameters of the model are presented. Depending on imposed triggering, the model reproduces both exponential and inverse power statistics of clusters.
Spatial Stochastic Point Models for Reservoir Characterization
Energy Technology Data Exchange (ETDEWEB)
Syversveen, Anne Randi
1997-12-31
The main part of this thesis discusses stochastic modelling of geology in petroleum reservoirs. A marked point model is defined for objects against a background in a two-dimensional vertical cross section of the reservoir. The model handles conditioning on observations from more than one well for each object and contains interaction between objects, and the objects have the correct length distribution when penetrated by wells. The model is developed in a Bayesian setting. The model and the simulation algorithm are demonstrated by means of an example with simulated data. The thesis also deals with object recognition in image analysis, in a Bayesian framework, and with a special type of spatial Cox processes called log-Gaussian Cox processes. In these processes, the logarithm of the intensity function is a Gaussian process. The class of log-Gaussian Cox processes provides flexible models for clustering. The distribution of such a process is completely characterized by the intensity and the pair correlation function of the Cox process. 170 refs., 37 figs., 5 tabs.
Characterizing heterogeneous cellular responses to perturbations.
Slack, Michael D; Martinez, Elisabeth D; Wu, Lani F; Altschuler, Steven J
2008-12-01
Cellular populations have been widely observed to respond heterogeneously to perturbation. However, interpreting the observed heterogeneity is an extremely challenging problem because of the complexity of possible cellular phenotypes, the large dimension of potential perturbations, and the lack of methods for separating meaningful biological information from noise. Here, we develop an image-based approach to characterize cellular phenotypes based on patterns of signaling marker colocalization. Heterogeneous cellular populations are characterized as mixtures of phenotypically distinct subpopulations, and responses to perturbations are summarized succinctly as probabilistic redistributions of these mixtures. We apply our method to characterize the heterogeneous responses of cancer cells to a panel of drugs. We find that cells treated with drugs of (dis-)similar mechanism exhibit (dis-)similar patterns of heterogeneity. Despite the observed phenotypic diversity of cells observed within our data, low-complexity models of heterogeneity were sufficient to distinguish most classes of drug mechanism. Our approach offers a computational framework for assessing the complexity of cellular heterogeneity, investigating the degree to which perturbations induce redistributions of a limited, but nontrivial, repertoire of underlying states and revealing functional significance contained within distinct patterns of heterogeneous responses.
Modeling dynamics of HIV infected cells using stochastic cellular automaton
Precharattana, Monamorn; Triampo, Wannapong
2014-08-01
Ever since HIV was first diagnosed in human, a great number of scientific works have been undertaken to explore the biological mechanisms involved in the infection and progression of the disease. Several cellular automata (CA) models have been introduced to gain insights into the dynamics of the disease progression but none of them has taken into account effects of certain immune cells such as the dendritic cells (DCs) and the CD8+ T lymphocytes (CD8+ T cells). In this work, we present a CA model, which incorporates effects of the HIV specific immune response focusing on the cell-mediated immunities, and investigate the interaction between the host immune response and the HIV infected cells in the lymph nodes. The aim of our work is to propose a model more realistic than the one in Precharattana et al. (2010) [10], by incorporating roles of the DCs, the CD4+ T cells, and the CD8+ T cells into the model so that it would reproduce the HIV infection dynamics during the primary phase of HIV infection.
Stochastic Ordering based Carrier-to-Interference Ratio Analysis for the Shotgun Cellular Systems
Madhusudhanan, Prasanna; Youjian,; Liu,; Brown, Timothy X; Baker, Kenneth R
2011-01-01
A simple analytical tool based on stochastic ordering is developed to compare the distributions of carrier-to-interference ratio at the mobile station of two cellular systems where the base stations are distributed randomly according to certain non-homogeneous Poisson point processes. The comparison is conveniently done by studying only the base station densities without having to solve for the distributions of the carrier-to-interference ratio, that are often hard to obtain.
Unified tractable model for downlink MIMO cellular networks using stochastic geometry
Afify, Laila H.
2016-07-26
Several research efforts are invested to develop stochastic geometry models for cellular networks with multiple antenna transmission and reception (MIMO). On one hand, there are models that target abstract outage probability and ergodic rate for simplicity. On the other hand, there are models that sacrifice simplicity to target more tangible performance metrics such as the error probability. Both types of models are completely disjoint in terms of the analytic steps to obtain the performance measures, which makes it challenging to conduct studies that account for different performance metrics. This paper unifies both techniques and proposes a unified stochastic-geometry based mathematical paradigm to account for error probability, outage probability, and ergodic rates in MIMO cellular networks. The proposed model is also unified in terms of the antenna configurations and leads to simpler error probability analysis compared to existing state-of-the-art models. The core part of the analysis is based on abstracting unnecessary information conveyed within the interfering signals by assuming Gaussian signaling. To this end, the accuracy of the proposed framework is verified against state-of-the-art models as well as system level simulations. We provide via this unified study insights on network design by reflecting system parameters effect on different performance metrics. © 2016 IEEE.
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...
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.
Stochastic narrow escape in molecular and cellular biology analysis and applications
Holcman, David
2015-01-01
This book covers recent developments in the non-standard asymptotics of the mathematical narrow escape problem in stochastic theory, as well as applications of the narrow escape problem in cell biology. The first part of the book concentrates on mathematical methods, including advanced asymptotic methods in partial equations, and is aimed primarily at applied mathematicians and theoretical physicists who are interested in biological applications. The second part of the book is intended for computational biologists, theoretical chemists, biochemists, biophysicists, and physiologists. It includes a summary of output formulas from the mathematical portion of the book and concentrates on their applications in modeling specific problems in theoretical molecular and cellular biology. Critical biological processes, such as synaptic plasticity and transmission, activation of genes by transcription factors, or double-strained DNA break repair, are controlled by diffusion in structures that have both large and small sp...
Strong Attractors in Stochastic Adaptive Networks: Emergence and Characterization
Santos, Augusto Almeida; Krishnan, Ramayya; Moura, José M F
2016-01-01
We propose a family of models to study the evolution of ties in a network of interacting agents by reinforcement and penalization of their connections according to certain local laws of interaction. The family of stochastic dynamical systems, on the edges of a graph, exhibits \\emph{good} convergence properties, in particular, we prove a strong-stability result: a subset of binary matrices or graphs -- characterized by certain compatibility properties -- is a global almost sure attractor of the family of stochastic dynamical systems. To illustrate finer properties of the corresponding strong attractor, we present some simulation results that capture, e.g., the conspicuous phenomenon of emergence and downfall of leaders in social networks.
In-Band α-Duplex Scheme for Cellular Networks: A Stochastic Geometry Approach
Alammouri, Ahmad
2016-07-13
In-band full-duplex (FD) communications have been optimistically promoted to improve the spectrum utilization and efficiency. However, the penetration of FD communications to the cellular networks domain is challenging due to the imposed uplink/downlink interference. This paper presents a tractable framework, based on stochastic geometry, to study FD communications in cellular networks. Particularly, we assess the FD communications effect on the network performance and quantify the associated gains. The study proves the vulnerability of the uplink to the downlink interference and shows that FD rate gains harvested in the downlink (up to 97%) come at the expense of a significant degradation in the uplink rate (up to 94%). Therefore, we propose a novel fine-grained duplexing scheme, denoted as -duplex scheme, which allows a partial overlap between the uplink and the downlink frequency bands. We derive the required conditions to harvest rate gains from the -duplex scheme and show its superiority to both the FD and half-duplex (HD) schemes. In particular, we show that the -duplex scheme provides a simultaneous improvement of 28% for the downlink rate and 56% for the uplink rate. Finally, we show that the amount of the overlap can be optimized based on the network design objective.
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
Characterization of cellular titanium for biomedical applications
Hrabe, Nikolas Wilson
By controlling structural features (relative density, pore size, strut size) of cellular titanium (also known as porous titanium), the mechanical properties can be optimized to reduce the effects of stress shielding currently observed in load-bearing bone replacement implants. Thermal gravimetric analysis of a sacrificial scaffold system lead to important processing modifications in an attempt to meet chemistry requirements for surgical grade titanium not met in previous work. Despite these modifications chemistry did not meet requirements for carbon, nitrogen, or oxygen. Commercially pure titanium (CPTi) porous structures were made over a range of relative densities using laser engineered net shaping (LENS). From monotonic compression tests, yield strength and elastic modulus in the range of bone were achieved but did not scale with relative density as predicted by the Gibson-Ashby analytical model. Compression-compression fatigue resistance was high, as no failures were observed for test stresses up to 133% yield strength, which is thought to be influenced by the dense exterior shell of the samples. Structures were also fabricated over a range of relative densities using selective electron beam melting (SEBM or EBM), and structural, mechanical, and in-vitro properties were measured for three materials (as-built Ti-6A1-4V, Ti-6A1-4V after hot isostatic pressing (HIPing), and as-built CPTi). For structures of all three materials, yield strength and elastic modulus was within the range for bone. Numerical modeling results suggested cell shape and sintered particles on strut surfaces affect the scaling of elastic modulus with relative density and lead to the observed difference from the Gibson-Ashby model. Normalized fatigue strengths at 106 cycles ranged from 0.150.25 for as-built Ti-6A1-4V structures, which is lower than expected. Results for HIPed Ti-6A1-4V structures and CPTi structures suggest that stress concentrations from closed porosity within struts as well
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
Multiscale study for stochastic characterization of shale samples
Tahmasebi, Pejman; Javadpour, Farzam; Sahimi, Muhammad; Piri, Mohammad
2016-03-01
Characterization of shale reservoirs, which are typically of low permeability, is very difficult because of the presence of multiscale structures. While three-dimensional (3D) imaging can be an ultimate solution for revealing important complexities of such reservoirs, acquiring such images is costly and time consuming. On the other hand, high-quality 2D images, which are widely available, also reveal useful information about shales' pore connectivity and size. Most of the current modeling methods that are based on 2D images use limited and insufficient extracted information. One remedy to the shortcoming is direct use of qualitative images, a concept that we introduce in this paper. We demonstrate that higher-order statistics (as opposed to the traditional two-point statistics, such as variograms) are necessary for developing an accurate model of shales, and describe an efficient method for using 2D images that is capable of utilizing qualitative and physical information within an image and generating stochastic realizations of shales. We then further refine the model by describing and utilizing several techniques, including an iterative framework, for removing some possible artifacts and better pattern reproduction. Next, we introduce a new histogram-matching algorithm that accounts for concealed nanostructures in shale samples. We also present two new multiresolution and multiscale approaches for dealing with distinct pore structures that are common in shale reservoirs. In the multiresolution method, the original high-quality image is upscaled in a pyramid-like manner in order to achieve more accurate global and long-range structures. The multiscale approach integrates two images, each containing diverse pore networks - the nano- and microscale pores - using a high-resolution image representing small-scale pores and, at the same time, reconstructing large pores using a low-quality image. Eventually, the results are integrated to generate a 3D model. The methods
3D printed cellular solid outperforms traditional stochastic foam in long-term mechanical response
Maiti, A.; Small, W.; Lewicki, J. P.; Weisgraber, T. H.; Duoss, E. B.; Chinn, S. C.; Pearson, M. A.; Spadaccini, C. M.; Maxwell, R. S.; Wilson, T. S.
2016-04-01
3D printing of polymeric foams by direct-ink-write is a recent technological breakthrough that enables the creation of versatile compressible solids with programmable microstructure, customizable shapes, and tunable mechanical response including negative elastic modulus. However, in many applications the success of these 3D printed materials as a viable replacement for traditional stochastic foams critically depends on their mechanical performance and micro-architectural stability while deployed under long-term mechanical strain. To predict the long-term performance of the two types of foams we employed multi-year-long accelerated aging studies under compressive strain followed by a time-temperature-superposition analysis using a minimum-arc-length-based algorithm. The resulting master curves predict superior long-term performance of the 3D printed foam in terms of two different metrics, i.e., compression set and load retention. To gain deeper understanding, we imaged the microstructure of both foams using X-ray computed tomography, and performed finite-element analysis of the mechanical response within these microstructures. This indicates a wider stress variation in the stochastic foam with points of more extreme local stress as compared to the 3D printed material, which might explain the latter’s improved long-term stability and mechanical performance.
Maerivoet, S; Immers, B; De Moor, B; Maerivoet, Sven; Logghe, Steven; Immers, Ben; Moor, Bart De
2005-01-01
In this paper, we describe a relation between a microscopic traffic cellular automaton (TCA) model (i.e., the stochastic TCA model of Nagel and Schreckenberg) and the macroscopic first-order hydrodynamic model of Lighthill, Whitham, and Richards (LWR). The innovative aspect of our approach, is that we explicitly derive the LWR's fundamental diagram directly from the STCA's rule set, by assuming a stationarity condition that converts the STCA's rules into a set of linear inequalities. In turn, these constraints define the shape of the fundamental diagram, which is then specified to the LWR model. Application of our methodology to a simulation case study, allows us to compare the tempo-spatial behavior of both models. Our results indicate that, in the presence of noise, the capacity flows in the derived fundamental diagram are overestimations of those of the STCA model. Directly specifying the STCA's capacity flows to the LWR fundamental diagram, effectively remedies most of the mismatches between both approach...
Characterizing economic trends by Bayesian stochastic model specification search
DEFF Research Database (Denmark)
Grassi, Stefano; Proietti, Tommaso
We extend a recently proposed Bayesian model selection technique, known as stochastic model specification search, for characterising the nature of the trend in macroeconomic time series. In particular, we focus on autoregressive models with possibly time-varying intercept and slope and decide...... on whether their parameters are fixed or evolutive. Stochastic model specification is carried out to discriminate two alternative hypotheses concerning the generation of trends: the trend-stationary hypothesis, on the one hand, for which the trend is a deterministic function of time and the short run...... the traditional Nelson and Plosser dataset. The broad conclusion is that most series are better represented by autoregressive models with time-invariant intercept and slope and coefficients that are close to boundary of the stationarity region. The posterior distribution of the autoregressive parameters...
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...
Tucker, G. E.; Hobley, D. E. J.; Hutton, E.; Gasparini, N. M.; Istanbulluoglu, E.; Adams, J. M.; Nudurupati, S. S.
2015-11-01
CellLab-CTS 2015 is a Python-language software library for creating two-dimensional, continuous-time stochastic (CTS) cellular automaton models. The model domain consists of a set of grid nodes, with each node assigned an integer state-code that represents its condition or composition. Adjacent pairs of nodes may undergo transitions to different states, according to a user-defined average transition rate. A model is created by writing a Python code that defines the possible states, the transitions, and the rates of those transitions. The code instantiates, initializes, and runs one of four object classes that represent different types of CTS model. CellLab-CTS provides the option of using either square or hexagonal grid cells. The software provides the ability to treat particular grid-node states as moving particles, and to track their position over time. Grid nodes may also be assigned user-defined properties, which the user can update after each transition through the use of a callback function. As a component of the Landlab modeling framework, CellLab-CTS models take advantage of a suite of Landlab's tools and capabilities, such as support for standardized input and output.
Stochastic resonance in ion channels characterized by information theory.
Goychuk, I; Hänggi, P
2000-04-01
We identify a unifying measure for stochastic resonance (SR) in voltage dependent ion channels which comprises periodic (conventional), aperiodic, and nonstationary SR. Within a simplest setting, the gating dynamics is governed by two-state conductance fluctuations, which switch at random time points between two values. The corresponding continuous time point process is analyzed by virtue of information theory. In pursuing this goal we evaluate for our dynamics the tau information, the mutual information, and the rate of information gain. As a main result we find an analytical formula for the rate of information gain that solely involves the probability of the two channel states and their noise averaged rates. For small voltage signals it simplifies to a handy expression. Our findings are applied to study SR in a potassium channel. We find that SR occurs only when the closed state is predominantly dwelled upon. Upon increasing the probability for the open channel state the application of an extra dose of noise monotonically deteriorates the rate of information gain, i.e., no SR behavior occurs.
Characterization of ambient air pollution for stochastic health models
Energy Technology Data Exchange (ETDEWEB)
Batterman, S.A.
1981-08-01
This research is an analysis of various measures of ambient air pollution useful in cross-sectional epidemiological investigations and rick assessments. The Chestnut Ridge area health effects investigation, which includes a cross-sectional study of respiratory symptoms in young children, is used as a case study. Four large coal-fired electric generating power plants are the dominant pollution sources in this area of western Pennsylvania. The air pollution data base includes four years of sulfur dioxide and five years of total suspended particulate concentrations at seventeen monitors. Some 70 different characterizations of pollution are constructed and tested. These include pollutant concentrations at various percentiles and averaging times, exceedence measures which show the amount of time a specified threshold concentration is exceeded, and several dosage measures which transform non-linear dose-response relationships onto pollutant concentrations.
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.
Institute of Scientific and Technical Information of China (English)
M.Kalpana; P.Balasubramaniam
2013-01-01
We investigate the stochastic asymptotical synchronization of chaotic Markovian jumping fuzzy cellular neural networks (MJFCNNs) with discrete,unbounded distributed delays,and the Wiener process based on sampled-data control using the linear matrix inequality (LMI) approach.The Lyapunov-Krasovskii functional combined with the input delay approach as well as the free-weighting matrix approach is employed to derive several sufficient criteria in terms of LMIs to ensure that the delayed MJFCNNs with the Wiener process is stochastic asymptotical synchronous.Restrictions (e.g.,time derivative is smaller than one) are removed to obtain a proposed sampled-data controller.Finally,a numerical example is provided to demonstrate the reliability of the derived results.
Liang, Jie; Cao, Youfang; Gürsoy, Gamze; Naveed, Hammad; Terebus, Anna; Zhao, Jieling
2016-01-01
Genome sequences provide the overall genetic blueprint of cells, but cells possessing the same genome can exhibit diverse phenotypes. There is a multitude of mechanisms controlling cellular epigenetic states and that dictate the behavior of cells. Among these, networks of interacting molecules, often under stochastic control, depending on the specific wirings of molecular components and the physiological conditions, can have a different landscape of cellular states. In addition, chromosome folding in three-dimensional space provides another important control mechanism for selective activation and repression of gene expression. Fully differentiated cells with different properties grow, divide, and interact through mechanical forces and communicate through signal transduction, resulting in the formation of complex tissue patterns. Developing quantitative models to study these multi-scale phenomena and to identify opportunities for improving human health requires development of theoretical models, algorithms, and computational tools. Here we review recent progress made in these important directions. PMID:27480462
Hostetter, Megan
This thesis presents a new type of polypropylene (PP) cellular material fabricated through a simple melt-stretching process. Stochastic honeycombs have an open cell, random honeycomb structure, with webs oriented perpendicular to built-in skins. This process has the advantage that, for example, PP pellets can be turned into a sandwich panel in one step. It was demonstrated that despite the randomness in the web structure, the out-of-plane compressive strength of stochastic honeycombs was repeatable, and exceeded that of commercial PP foams and was comparable to commercial PP honeycombs. The key material properties required to produce an this architecture were shown to be a high melt strength and a high viscosity, branched polymer. The viscosity was shown to affect the total length of the webs in cross-section and the relative partitioning of material through the skin, transition region and webs. Web thickness was affected by the areal density of the polymer during fabrication. Mechanical testing methods were adapted from ASTM standards for honeycombs, and the fabrication method was advanced from a manual to a machine controlled process. Stochastic honeycombs were shown to buckle elastically, plastically, and fracture after the peak strength. Elastic and plastic buckling were dominant at lower densities, and plastic buckling and fracture at higher densities. A thin-plate buckling model for the strength of stochastic honeycombs was developed and verified experimentally. The crystallinity of the polymer affected the tensile strength and stiffness, having a linear effect on the buckling strength. The architecture was composed of webs bound on both sides and webs bound on one side and free on the other. A greater fraction of bound webs increased the strength of the structure in the buckling model. A fabrication study showed that melt-stretching the polymer at higher strain rates increased the connectivity and fraction of bound webs. Additionally, higher density led to a
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...
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.
Directory of Open Access Journals (Sweden)
Maria Luisa eGuerriero
2014-10-01
Full Text Available Rhythmic behavior is essential for plants; for example, daily (circadian rhythms control photosynthesis and seasonal rhythms regulate their life cycle. The core of the circadian clock is a genetic network that coordinates the expression of specific clock genes in a circadian rhythm reflecting the 24-hour day/night cycle.Circadian clocks exhibit stochastic noise due to the low copy numbers of clock genes and the consequent cell-to-cell variation: this intrinsic noise plays a major role in circadian clocks by inducing more robust oscillatory behavior. Another source of noise is the environment, which causes variation in temperature and light intensity: this extrinsic noise is part of the requirement for the structural complexity of clock networks.Advances in experimental techniques now permit single-cell measurements and the development of single-cell models. Here we present some modeling studies showing the importance of considering both types of noise in understanding how plants adapt to regular and irregular light variations. Stochastic models have proven useful for understanding the effect of regular variations. By contrast, the impact of irregular variations and the interaction of different noise sources are less studied.
Cellular and Phenotypic Characterization of Canine Osteosarcoma Cell Lines
Directory of Open Access Journals (Sweden)
Marie E. Legare, Jamie Bush, Amanda K. Ashley, Taka Kato, William H. Hanneman
2011-01-01
Full Text Available Canine and human osteosarcoma (OSA have many similarities, with the majority of reported cases occurring in the appendicular skeleton, gender predominance noted, high rate of metastasis at the time of presentation, and a lack of known etiology for this devastating disease. Due to poor understanding of the molecular mechanisms underlying OSA, we have characterized seven different OSA canine cell lines: Abrams, D17, Grey, Hughes, Ingles, Jarques, and Marisco and compared them to U2, a human OSA cell line, for the following parameters: morphology, growth, contact inhibition, migrational tendencies, alkaline phosphatase staining, heterologous tumor growth, double-strand DNA breaks, and oxidative damage. All results demonstrated the positive characteristics of the Abrams cell line for use in future studies of OSA. Of particular interest, the robust growth of a subcutaneous tumor and rapid pulmonary metastasis of the Abrams cell line in an immunocompromised mouse shows incredible potential for the future use of Abrams as a canine OSA model. Further investigations utilizing a canine cell model of OSA, such as Abrams, will be invaluable to understanding the molecular events underlying OSA, pharmaceutical inhibition of metastasis, and eventual prevention of this devastating disease.
A Characterization of Cellular Automata Generated by Idempotents on the Full Shift
Salo, Ville
2012-01-01
In this article, we discuss the family of cellular automata generated by so-called idempotent cellular automata (CA G such that G^2 = G) on the full shift. We prove a characterization of products of idempotent CA, and show examples of CA which are not easy to directly decompose into a product of idempotents, but which are trivially seen to satisfy the conditions of the characterization. Our proof uses ideas similar to those used in the well-known Embedding Theorem and Lower Entropy Factor Theorem in symbolic dynamics. We also consider some natural decidability questions for the class of products of idempotent CA.
On the behaviour characterization of metallic cellular materials under impact loading
Fang, Dai-Ning; Li, Yu-Long; Zhao, Han
2010-12-01
This paper reviews the common mechanical features of the metallic cellular material under impact loading as well as the characterization methods of such behaviours. The main focus is on the innovations of various testing methods at impact loading rates. Following aspects were discussed in details. (1) The use of soft nylon Hopkinson/Kolsky bar for an enhanced measuring accuracy in order to assess if there is a strength enhancement or not for this class of cellular materials under moderate impact loading; (2) The use of digital image correlations to determine the strain fields during the tests to confirm the existence of a pseudo-shock wave propagation inside the cellular material under high speed impact; (3) The use of new combined shear compression device to determine the loading envelop of cellular materials under impact multiaxial loadings.
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.
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
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.
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
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.
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
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
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
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...
Institute of Scientific and Technical Information of China (English)
Dal Hyung Kim; Sean E. Brigandi; Paul Kim; Doyoung Byun; Min Jun Kim
2011-01-01
Artificial magnetotactic Tetrahymena pyriformis GL (T. pyriformis) cells were created by the internalization of iron oxide nano particles and became controllable with a time-varying external magnetic field. Thus, T. pyriformis can be utilized as a cellular robot to conduct micro-scale tasks such as transportation and manipulation. To complete these tasks, loading inorganic or organic materials onto the cell body is essential, but functionalization of the cell membrane is obstructed by their motile organelles, cilia. Dibucaine HCl, a local anesthetic, removes the cilia from the cell body, and the functional group would be absorbed more efficiently during cilia regeneration. In this paper, we characterize the recovery of artificial magnetotactic T.pyriformis after the deciliation process to optimize a cellular robot fabrication process. After sufficient time to recover, the motility rate and the average velocity of the deciliated cells were six and ten percent lower than that of non-deciliated cells, respectively. We showed that the motile cells after recovery can still be controlled using magnetotaxis, making T. pyriformis a good candidate to be used as a cellular robot.
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.
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...
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...
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...
CSI 2264: CHARACTERIZING YOUNG STARS IN NGC 2264 WITH STOCHASTICALLY VARYING LIGHT CURVES
Energy Technology Data Exchange (ETDEWEB)
Stauffer, John; Rebull, Luisa; Carey, Sean [Spitzer Science Center, California Institute of Technology, Pasadena, CA 91125 (United States); Cody, Ann Marie [NASA Ames Research Center, Kepler Science Office, Mountain View, CA 94035 (United States); Hillenbrand, Lynne A.; Carpenter, John [Astronomy Department, California Institute of Technology, Pasadena, CA 91125 (United States); Turner, Neal J. [Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109 (United States); Terebey, Susan [Department of Physics and Astronomy, 5151 State University Drive, California State University at Los Angeles, Los Angeles, CA 90032 (United States); Morales-Calderón, Maria [Centro de Astrobiología, Dpto. de Astrofísica, INTA-CSIC, P.O. BOX 78, E-28691, ESAC Campus, Villanueva de la Cañada, Madrid (Spain); Alencar, Silvia H. P.; McGinnis, Pauline; Sousa, Alana [Departamento de Física—ICEx—UFMG, Av. Antônio Carlos, 6627, 30270-901, Belo Horizonte, MG (Brazil); Bouvier, Jerome; Venuti, Laura [Université de Grenoble, Institut de Planétologie et d’Astrophysique de Grenoble (IPAG), F-38000 Grenoble (France); Hartmann, Lee; Calvet, Nuria [Department of Astronomy, University of Michigan, 500 Church Street, Ann Arbor, MI:48105 (United States); Micela, Giusi; Flaccomio, Ettore [INAF—Osservatorio Astronomico di Palermo, Piazza del Parlamento 1, I-90134, Palermo (Italy); Song, Inseok [Department of Physics and Astronomy, The University of Georgia, Athens, GA 30602-2451 (United States); Gutermuth, Rob, E-mail: stauffer@ipac.caltech.edu [Department of Astronomy, University of Massachusetts, Amherst, MA 01003 (United States); and others
2016-03-15
We provide CoRoT and Spitzer light curves and other supporting data for 17 classical T Tauri stars in NGC 2264 whose CoRoT light curves exemplify the “stochastic” light curve class as defined in 2014 by Cody et al. The most probable physical mechanism to explain the optical variability within this light curve class is time-dependent mass accretion onto the stellar photosphere, producing transient hot spots. Where we have appropriate spectral data, we show that the veiling variability in these stars is consistent in both amplitude and timescale with the optical light curve morphology. The veiling variability is also well-correlated with the strength of the He i 6678 Å emission line, predicted by models to arise in accretion shocks on or near the stellar photosphere. Stars with accretion burst light curve morphology also have variable mass accretion. The stochastic and accretion burst light curves can both be explained by a simple model of randomly occurring flux bursts, with the stochastic light curve class having a higher frequency of lower amplitude events. Members of the stochastic light curve class have only moderate mass accretion rates. Their Hα profiles usually have blueshifted absorption features, probably originating in a disk wind. The lack of periodic signatures in the light curves suggests that little of the variability is due to long-lived hot spots rotating into or out of our line of sight; instead, the primary driver of the observed photometric variability is likely to be instabilities in the inner disk that lead to variable mass accretion.
Intrinsic Radiosensitivity and Cellular Characterization of 27 Canine Cancer Cell Lines.
Maeda, Junko; Froning, Coral E; Brents, Colleen A; Rose, Barbara J; Thamm, Douglas H; Kato, Takamitsu A
2016-01-01
Canine cancer cell lines have progressively been developed, but are still underused resources for radiation biology research. Measurement of the cellular intrinsic radiosensitivity is important because understanding the difference may provide a framework for further elucidating profiles for prediction of radiation therapy response. Our studies have focused on characterizing diverse canine cancer cell lines in vitro and understanding parameters that might contribute to intrinsic radiosensitivity. First, intrinsic radiosensitivity of 27 canine cancer cell lines derived from ten tumor types was determined using a clonogenic assay. The 27 cell lines had varying radiosensitivities regardless tumor type (survival fraction at 2 Gy, SF2 = 0.19-0.93). In order to understand parameters that might contribute to intrinsic radiosensitivity, we evaluated the relationships of cellular radiosensitivity with basic cellular characteristics of the cell lines. There was no significant correlation of SF2 with S-phase fraction, doubling time, chromosome number, ploidy, or number of metacentric chromosomes, while there was a statistically significant correlation between SF2 and plating efficiency. Next, we selected the five most radiosensitive cell lines as the radiosensitive group and the five most radioresistant cell lines as the radioresistant group. Then, we evaluated known parameters for cell killing by ionizing radiation, including radiation-induced DNA double strand break (DSB) repair and apoptosis, in the radiosensitive group as compared to the radioresistant group. High levels of residual γ-H2AX foci at the sites of DSBs were present in the four out of the five radiosensitive canine cancer cell lines. Our studies suggested that substantial differences in intrinsic radiosensitivity exist in canine cancer cell lines, and radiation-induced DSB repair was related to radiosensitivity, which is consistent with previous human studies. These data may assist further investigations
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.
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
Energy Technology Data Exchange (ETDEWEB)
Gorny, B.; Niendorf, T.; Lackmann, J. [Lehrstuhl fuer Werkstoffkunde (Materials Science), University of Paderborn, Pohlweg 47-49, 33098 Paderborn (Germany); Thoene, M.; Troester, T. [Lehrstuhl fuer Leichtbau im Automobil (Automotive Lightweight Construction), University of Paderborn, Pohlweg 47-49, 33098 Paderborn (Germany); Direct Manufacturing Research Center (DMRC), Mersinweg 3, 33098 Paderborn (Germany); Maier, H.J., E-mail: hmaier@mail.upb.de [Lehrstuhl fuer Werkstoffkunde (Materials Science), University of Paderborn, Pohlweg 47-49, 33098 Paderborn (Germany)
2011-10-15
Highlights: {yields} The present study focused on deformation behavior and failure mechanisms in lattice structure produced by selective laser melting (SLM). {yields} It is demonstrated that heat treatments can be used to increase the energy absorption of an SLM-processed structure. {yields} An in situ testing procedure was introduced, where local strains were calculated by digital image correlation {yields} Shear failure could be predicted by localization using Tresca strains. {yields} The approach employed provides a means to understand the microstructure-mechanical property-local deformation relationship. - Abstract: Cellular materials are promising candidates for load adapted light-weight structures. Direct manufacturing (DM) tools are effective methods to produce non-stochastic structures. Many DM studies currently focus on optimization of the geometric nature of the structures obtained. The literature available so far reports on the mechanical properties but local deformation mechanisms are not taken into account. In order to fill this gap, the current study addresses the deformation behavior of a lattice structure produced by selective laser melting (SLM) on the local scale by means of a comprehensive experimental in situ approach, including electron backscatter diffraction, scanning electron microscopy and digital image correlation. SLM-processed as well as heat treated lattice structures made from TiAl6V4 alloy were employed for mechanical testing. It is demonstrated that the current approach provides means to understand the microstructure-mechanical property-local deformation relationship to allow for optimization of load adapted lattice structures.
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
Stochastic volatility and stochastic leverage
DEFF Research Database (Denmark)
Veraart, Almut; Veraart, Luitgard A. M.
This paper proposes the new concept of stochastic leverage in stochastic volatility models. Stochastic leverage refers to a stochastic process which replaces the classical constant correlation parameter between the asset return and the stochastic volatility process. We provide a systematic...... treatment of stochastic leverage and propose to model the stochastic leverage effect explicitly, e.g. by means of a linear transformation of a Jacobi process. Such models are both analytically tractable and allow for a direct economic interpretation. In particular, we propose two new stochastic volatility...... models which allow for a stochastic leverage effect: the generalised Heston model and the generalised Barndorff-Nielsen & Shephard model. We investigate the impact of a stochastic leverage effect in the risk neutral world by focusing on implied volatilities generated by option prices derived from our new...
CSI 2264: Characterizing Young Stars in NGC 2264 with Stochastically Varying Light Curves
Stauffer, John; Rebull, Luisa; Hillenbrand, Lynne A; Turner, Neal J; Carpenter, John; Carey, Sean; Terebey, Susan; Morales-Calderon, Maria; Alencar, Silvia H P; McGinnis, Pauline; Sousa, Alana; Bouvier, Jerome; Venuti, Laura; Hartmann, Lee; Calvet, Nuria; Micela, Giusi; Flaccomio, Ettore; Song, Inseok; Gutermuth, Rob; Barrado, David; Vrba, Frederick J; Covey, Kevin; Herbst, William; Gillen, Edward; Guimaraes, Marcelo Medeiros; Bouy, Herve; Favata, Fabio
2016-01-01
We provide CoRoT and Spitzer light curves, as well as broad-band multi-wavelength photometry and high resolution, multi- and single-epoch spectroscopy for 17 classical T Tauris in NGC 2264 whose CoRoT light curves (LCs) exemplify the "stochastic" LC class as defined in Cody et al. (2014). The most probable physical mechanism to explain the optical variability in this LC class is time-dependent mass accretion onto the stellar photosphere, producing transient hot spots. As evidence in favor of this hypothesis, multi-epoch high resolution spectra for a subset of these stars shows that their veiling levels also vary in time and that this veiling variability is consistent in both amplitude and timescale with the optical LC morphology. Furthermore, the veiling variability is well-correlated with the strength of the HeI 6678A emission line, a feature predicted by models to arise in accretion shocks on or near the stellar photosphere. Stars with accretion burst LC morphology (Stauffer et al. 2014) are also attributed...
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.
Identification and characterization of cellular receptors for the growth regulator, oncostatin M
Energy Technology Data Exchange (ETDEWEB)
Linsley, P.S.; Bolton-Hanson, M.; Horn, D.; Malik, N.; Kallestad, J.C.; Ochs, V.; Zarling, J.M.; Shoyab, M.
1989-03-15
Oncostatin M is a polypeptide growth regulator produced by activated T cells and phorbol ester-treated U937 cells. To identify specific cellular receptors for this factor, we have characterized the binding of 125I-labeled oncostatin M to a variety of normal and malignant mammalian cells. Recombinant oncostatin M was labeled with 125I with full retention of growth inhibitory activity on A375 melanoma cells. 125I-Oncostatin M bound to sensitive cells in a time- and temperature-dependent fashion. Binding was specifically inhibited by unlabeled native or recombinant oncostatin M, but not by other polypeptide growth factors tested. Binding to human leukemic and normal blood cells was generally less than to nonhematopoietic cells. With four different cell lines, maximal growth inhibition by oncostatin M was achieved at less than maximal binding site occupancy. Scatchard graphs of direct binding data were curvilinear and indicated that 125I-oncostatin M bound with higher apparent affinity at lower 125I-oncostatin M concentrations. Using a two binding site model, affinity constants of Kd1 = 11 +/- 11 pM and Kd2 = 1000 +/- 380 pM were extrapolated from binding data with A375 cells, and values of Kd1 = 3 +/- 2 pM and Kd2 = 400 +/- 44 pM from A549 cells. The major 125I-oncostatin M binding species in a number of mammalian cell lines was identified by chemical cross-linking as a specific protein(s) of Mr = 150,000-160,000. 125I-Oncostatin M was internalized (t1/2 = 30 min) and degraded subsequent to binding to a responsive cell line.
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.
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.
Ander, M; Beltrao, P; Di Ventura, B; Ferkinghoff-Borg, J; Foglierini, M; Kaplan, A; Lemerle, C; Tomás-Oliveira, I; Serrano, L
2004-06-01
SmartCell has been developed to be a general framework for modelling and simulation of diffusion-reaction networks in a whole-cell context. It supports localisation and diffusion by using a mesoscopic stochastic reaction model. The SmartCell package can handle any cell geometry, considers different cell compartments, allows localisation of species, supports DNA transcription and translation, membrane diffusion and multistep reactions, as well as cell growth. Moreover, different temporal and spatial constraints can be applied to the model. A GUI interface that facilitates model making is also available. In this work we discuss limitations and advantages arising from the approach used in SmartCell and determine the impact of localisation on the behaviour of simple well-defined networks, previously analysed with differential equations. Our results show that this factor might play an important role in the response of networks and cannot be neglected in cell simulations.
Energy Technology Data Exchange (ETDEWEB)
Paliwal, Pranav; Parthasarathy, U. [Thermal Hydraulics Section, Nuclear and Safety Engineering Group, Indira Gandhi Centre for Atomic Research, Kalpakkam 603102 (India); Velusamy, K., E-mail: kvelu@igcar.gov.in [Thermal Hydraulics Section, Nuclear and Safety Engineering Group, Indira Gandhi Centre for Atomic Research, Kalpakkam 603102 (India); Sundararajan, T. [Department of Mechanical Engineering, IIT-Madras, Chennai 600036 (India); Chellapandi, P. [Thermal Hydraulics Section, Nuclear and Safety Engineering Group, Indira Gandhi Centre for Atomic Research, Kalpakkam 603102 (India)
2012-09-15
Highlights: Black-Right-Pointing-Pointer We present characterization of cellular convection by 3-D CFD analysis. Black-Right-Pointing-Pointer CFD model is validated against in-house experimental data. Black-Right-Pointing-Pointer We bring out effects of geometric and process parameters on cellular convection. Black-Right-Pointing-Pointer Correlations are developed to serve as guideline for design of FBR top shield. - Abstract: Cellular convection of argon gas that takes place in narrow annuli of component penetrations in FBR top shield has been investigated. The 3-D CFD simulations have been validated against in-house experimental data. The circumferential temperature difference in the shells, which is a result of cellular convection is given special attention. Cellular convection is seen to be highly sensitive to geometric and thermal conditions. For Rayleigh numbers (Ra) less than {approx}300, cellular convection effect is seen to be very weak. For Ra exceeding {approx}3 Multiplication-Sign 10{sup 8}, natural convection is vigorous with insignificant circumferential temperature variations. In the intermediate range of Rayleigh numbers, cellular convection assumes great significance. The maximum circumferential temperature difference in the component shell is seen to occur at Ra {approx} 3 Multiplication-Sign 10{sup 5}, which corresponds to a gap width of 50 mm. The number of convective cells increases with decrease in gap width as well as increase in forced cooling. The circumferential temperature difference is found to be directly proportional to annulus height, suggesting significant incentives in adopting shorter penetration heights. However, the circumferential temperature difference is found to be a weak function of annulus diameter. The number of cells is unfavorably less in an eccentric annulus compared to a concentric annulus. Appropriate correlations have been proposed to determine the circumferential temperature difference and number of convective cells
Directory of Open Access Journals (Sweden)
Lamichhane SP
2015-01-01
Full Text Available Surya P Lamichhane,1 Neha Arya,1,2 Nirdesh Ojha,3 Esther Kohler,1 V Prasad Shastri1,2,41Institute for Macromolecular Chemistry, University of Freiburg, Freiburg, 2Helmholtz Virtual Institute on “Multifunctional Biomaterials for Medicine”, 3Laboratory for Process Technology, Department of Microsystems Engineering, University of Freiburg, Freiburg, 4Centre for Biological Signaling Studies (BIOSS, University of Freiburg, Freiburg, GermanyAbstract: The efficient delivery of chemotherapeutics to the tumor via nanoparticle (NP-based delivery systems remains a significant challenge. This is compounded by the fact that the tumor is highly dynamic and complex environment composed of a plurality of cell types and extracellular matrix. Since glycosaminoglycan (GAG production is altered in many diseases (or pathologies, NPs bearing GAG moieties on the surface may confer some unique advantages in interrogating the tumor microenvironment. In order to explore this premise, in the study reported here poly-lactide-co-glycolide (PLGA NPs in the range of 100–150 nm bearing various proteoglycans were synthesized by a single-step nanoprecipitation and characterized. The surface functionalization of the NPs with GAG moieties was verified using zeta potential measurements and X-ray photoelectron spectroscopy. To establish these GAG-bearing NPs as carriers of therapeutics, cellular toxicity assays were undertaken in lung epithelial adenocarcinoma (A549 cells, human pulmonary microvascular endothelial cells (HPMEC, and renal proximal tubular epithelial cells. In general NPs were well tolerated over a wide concentration range (100–600 µg/mL by all cell types and were taken up to appreciable extents without any adverse cell response in A549 cells and HPMEC. Further, GAG-functionalized PLGA NPs were taken up to different extents in A459 cells and HPMEC. In both cell systems, the uptake of heparin-modified NPs was diminished by 50%–65% in comparison to that of
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
Characterization of the emergent properties of a synthetic quasi-cellular system
Directory of Open Access Journals (Sweden)
Lazzerini-Ospri Lorenzo
2012-03-01
Full Text Available Abstract Background The process of solutes entrapment during liposomes formation is interesting for the investigation of the relationship between the formation of compartments and the distribution of molecules inside them; a relevant issue in the studies of the origin of life. Theoretically, when no interactions are supposed among the chemical species to be entrapped, the entrapment is described by a standard Poisson process. But very recent experimental findings show that, for small liposomes (100 nm diameter, the distribution of entrapped molecules is best described by a power-law function. This is of a great importance, as the two random processes give rise to two completely different scenarios. Here we present an in silico stochastic simulation of the encapsulation of a cell-free molecular translation system (the PURE system, obtained following two different entrapment models: a pure Poisson process, and a power-law. The protein synthesis inside the liposomes has been studied in both cases, with the aim to highlight experimental observables that could be measured to assess which model gives a better representation of the real process. Results Firstly, a minimal model for in vitro protein synthesis, based on the PURE system molecular composition, has been formalized. Then, we have designed a reliable experimental simulation where stochastic factors affect the reaction course inside the compartment. To this end, 24 solutes, which represent the PURE system components, have been stochastically distributed among vesicles by following either a Poisson or a power-law distribution. The course of the protein synthesis within each vesicle has been consequently calculated, as a function of vesicle size. Our study can predict translation yield in a population of small liposomes down to the attoliter (10-18 L range. Our results show that the efficiency of protein synthesis peaks at approximately 3·10-16 L (840 nm diam. with a Poisson distribution of
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
DEFF Research Database (Denmark)
Fernandez-Guerra, Paula
Cell phenotyping of human dermal fibroblasts (HDFs) from patients with inherited metabolic diseases (IMDs) provide invaluable information for diagnosis, disease aetiology, predicting prognosis, and monitoring of treatments. HDFs possess the genetic composition of patients and many pathways...... and functions are expressed in HDFs’ culture environment. Studies of molecular disease mechanisms often point to the involvement of mitochondria. Mitochondria are involved in the regulation of cell cycle and programmed cell death as well as cellular stress responses because they are the main producers...... or E1b. Since BCKDH is a mitochondrial enzyme, we investigated iTRAQ labelled cellular fraction and mitochondrial enriched fraction of HDFs by mass spectrometry analysis. The MSUD protein profile was associated with changes in different biological processes: intracellular signalling, oxidative stress...
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
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
Cellular Response to Irradiation
Institute of Scientific and Technical Information of China (English)
LIU Bo; YAN Shi-Wei
2011-01-01
To explore the nonlinear activities of the cellular signaling system composed of one transcriptional arm and one protein-interaction arm, we use an irradiation-response module to study the dynamics of stochastic interactions.It is shown that the oscillatory behavior could be described in a unified way when the radiation-derived signal and noise are incorporated.
Jing, Xiaona; Kasimova, Marina R; Simonsen, Anders H; Jorgensen, Lene; Malmsten, Martin; Franzyk, Henrik; Foged, Camilla; Nielsen, Hanne M
2012-03-20
Enzymatically stable cell-penetrating α-peptide/β-peptoid peptidomimetics constitute promising drug delivery vehicles for the transport of therapeutic biomacromolecules across membrane barriers. The aim of the present study was to elucidate the mechanism of peptidomimetic-lipid bilayer interactions. A series of peptidomimetics consisting of alternating cationic and hydrophobic residues displaying variation in length and N-terminal end group were applied to fluid-phase, anionic lipid bilayers, and their interaction was investigated using isothermal titration calorimetry (ITC) and ellipsometry. Titration of lipid vesicles into solutions of peptidomimetics resulted in exothermic adsorption processes, and the interaction of all studied peptidomimetics with anionic lipid membranes was found to be enthalpy-driven. The enthalpy and Gibbs free energy (ΔG) proved more favorable with increasing chain length. However, not all charges contribute equally to the interaction, as evidenced by the charge-normalized ΔG being inversely correlated to the sequence length. Ellipsometry data suggested that the hydrophobic residues also played an important role in the interaction process. Furthermore, ΔG extracted from ellipsometry data showed good agreement with that obtained with ITC. To further elucidate their interaction with biological membranes, quantitative uptake and cellular distribution were studied in proliferating HeLa cells by flow cytometry and confocal microscopy. The cellular uptake of carboxyfluorescein-labeled peptidomimetics showed a similar ranking as that obtained from the adsorbed amount, and binding energy to model membranes demonstrated that the initial interaction with the membrane is of key importance for the cellular uptake.
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
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.
Directory of Open Access Journals (Sweden)
Santos Fabio M
2012-07-01
Full Text Available Abstract Background The neural mobilization technique is a noninvasive method that has proved clinically effective in reducing pain sensitivity and consequently in improving quality of life after neuropathic pain. The present study examined the effects of neural mobilization (NM on pain sensitivity induced by chronic constriction injury (CCI in rats. The CCI was performed on adult male rats, submitted thereafter to 10 sessions of NM, each other day, starting 14 days after the CCI injury. Over the treatment period, animals were evaluated for nociception using behavioral tests, such as tests for allodynia and thermal and mechanical hyperalgesia. At the end of the sessions, the dorsal root ganglion (DRG and spinal cord were analyzed using immunohistochemistry and Western blot assays for neural growth factor (NGF and glial fibrillary acidic protein (GFAP. Results The NM treatment induced an early reduction (from the second session of the hyperalgesia and allodynia in CCI-injured rats, which persisted until the end of the treatment. On the other hand, only after the 4th session we observed a blockade of thermal sensitivity. Regarding cellular changes, we observed a decrease of GFAP and NGF expression after NM in the ipsilateral DRG (68% and 111%, respectively and the decrease of only GFAP expression after NM in the lumbar spinal cord (L3-L6 (108%. Conclusions These data provide evidence that NM treatment reverses pain symptoms in CCI-injured rats and suggest the involvement of glial cells and NGF in such an effect.
Kim, Yong Bok; Kim, Geun Hyung
2015-02-01
Alginates have been used widely in biomedical applications because of good biocompatibility, low cost, and rapid gelation in the presence of calcium ions. However, poor mechanical properties and fabrication-ability for three-dimensional shapes have been obstacles in hard-tissue engineering applications. To overcome these shortcomings of alginates, we suggest a new composite system, consisting of a synthetic polymer, poly(ε-caprolactone), and various weight fractions (10-40 wt %) of alginate. The fabricated composite scaffolds displayed a multilayered 3D structure, consisting of microsized composite struts, and they provided a 100% offset for each layer. To show the feasibility of the scaffold for hard tissue regeneration, the composite scaffolds fabricated were assessed not only for physical properties, including surface roughness, tensile strength, and water absorption and wetting, but also in vitro osteoblastic cellular responses (cell-seeding efficiency, cell viability, fluorescence analyses, alkaline phosphatase (ALP) activity, and mineralization) by culturing with preosteoblasts (MC3T3-E1). Due to the alginate components in the composites, the scaffolds showed significantly enhanced wetting behavior, water-absorption (∼12-fold), and meaningful biological activities (∼2.1-fold for cell-seeding efficiency, ∼2.5-fold for cell-viability at 7 days, ∼3.4-fold for calcium deposition), compared with a pure PCL scaffold.
Characterization of 22 Vibrio species by gas chromatography analysis of their cellular fatty acids.
Urdaci, M C; Marchand, M; Grimont, P A
1990-05-01
The cellular fatty acid compositions of 51 Vibrio strains belonging to 22 species as well as five Aeromonas strains were determined by using capillary gas-liquid chromatography (GLC). The major fatty acids were most often hexadecenoic, hexadecanoic and octadecenoic acids. Heptadecenoic acid was present in significant amounts in V. alginolyticus, V. natriegens, V. parahaemolyticus and "Vibrio navarrensis". Twenty fatty acids including branched and hydroxy acids were detected in the genus Vibrio. Quantitative results were treated by principal component analysis to display groups of strains. The first three components (accounting for 69% of the variance) showed the type strains of V. fischeri, V. ordalii, V. damsela, V. mediterranei, V. tubiashii, V. campbellii, V. pelagius, V. gazogenes, and V. nereis to be unclustered. V. alginolyticus (4 strains) and V. parahaemolyticus (4 strains) showed some overlap and the type strain of V. natriegens was in their neighborhood. V. harveyi (4 strains) formed a cluster and V. vulnificus was in its vicinity. V. cholerae (5 strains) overlapped with V. diazotrophicus (3 strains) and was close to the type strain of V. mimicus and V. anguillarum. V. metschnikovii (3 strains) clustered with the type strain of V. cincinnatiensis. A decision tree was devised for the identification of Vibrio species based on qualitative characteristics of fatty acid patterns. However, the following three groups, V. alginolyticus-V. parahaemolyticus-V. natriegens, V. metschnikovii-V. cincinnatiensis and V. cholerae-V. mimicus could not be split into such a decision tree.
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
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
Directory of Open Access Journals (Sweden)
Wonseok Chang
2011-09-01
Full Text Available We report herein development of a novel glass micropipette thermal sensor fabricated in a cost-effective manner, which is capable of measuring steady thermal fluctuation at spatial resolution of ~2 µm with an accuracy of ±0.01 °C. We produced and tested various micrometer-sized sensors, ranging from 2 µm to 30 µm. The sensor comprises unleaded low-melting-point solder alloy (Sn-based as a core metal inside a pulled borosilicate glass pipette and a thin film of nickel coating outside, creating a thermocouple junction at the tip. The sensor was calibrated using a thermally insulated calibration chamber, the temperature of which can be controlled with an accuracy of ±0.01 °C, and the thermoelectric power (Seebeck coefficient of the sensor was recorded from 8.46 to 8.86 µV/°C. We have demonstrated the capability of measuring temperatures at a cellular level by inserting our temperature sensor into the membrane of a live retinal pigment epithelium cell subjected to a laser beam with a focal spot of 6 μm. We measured transient temperature profiles and the maximum temperatures were in the range of 38–55 ± 0.5 °C.
Variance decomposition in stochastic simulators
Le Maître, O. P.; Knio, O. M.; Moraes, A.
2015-06-01
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Variance decomposition in stochastic simulators
Le Maître, O. P.
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.
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)
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.
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
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.
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
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.
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.
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.
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; 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)
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.
Energy Technology Data Exchange (ETDEWEB)
Ari-Wahjoedi, Bambang, E-mail: bambang-ariwahjoedi@petronas.com.my [Department of Fundamental and Applied Sciences, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak Darul Ridzuan (Malaysia); Centre for Intelligent Signal and Imaging Research, Universiti Teknologi PETRONAS, Bandar Seri Iskandar (Malaysia); Ginta, Turnad Lenggo [Department of Mechanical Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak Darul Ridzuan (Malaysia); Centre for Intelligent Signal and Imaging Research, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tro (Malaysia); Parman, Setyamartana [Department of Mechanical Engineering, Universiti Teknologi PETRONAS, Bandar Seri Iskandar, 31750 Tronoh, Perak Darul Ridzuan (Malaysia); Abustaman, Mohd Zikri Ahmad [Kebabangan Petroleum Operating Company Sdn Bhd, Lvl. 52, Tower 2, PETRONAS Twin Towers, KLCC, 50088 Kuala Lumpur (Malaysia)
2014-10-24
Multicellular monolithic ceramic body is a ceramic material which has many gas or liquid passages partitioned by thin walls throughout the bulk material. There are many currently known advanced industrial applications of multicellular ceramics structures i.e. as supports for various catalysts, electrode support structure for solid oxide fuel cells, refractories, electric/electronic materials, aerospace vehicle re-entry heat shields and biomaterials for dental as well as orthopaedic implants by naming only a few. Multicellular ceramic bodies are usually made of ceramic phases such as mullite, cordierite, aluminum titanate or pure oxides such as silica, zirconia and alumina. What make alumina ceramics is excellent for the above functions are the intrinsic properties of alumina which are hard, wear resistant, excellent dielectric properties, resists strong acid and alkali attacks at elevated temperatures, good thermal conductivities, high strength and stiffness as well as biocompatible. In this work the processing technology leading to truly multicellular monolithic alumina ceramic bodies and their characterization are reported. Ceramic slip with 66 wt.% solid loading was found to be optimum as impregnant to the polyurethane foam template. Mullitic ceramic composite of alumina-sodium alumino disilicate-Leucite-like phases with bulk and true densities of 0.852 and 1.241 g cm{sup −3} respectively, pore linear density of ±35 cm{sup −1}, linear and bulk volume shrinkages of 7-16% and 32 vol.% were obtained. The compressive strength and elastic modulus of the bioceramics are ≈0.5-1.0 and ≈20 MPa respectively.
Cellular characterization of cells from the Fanconi anemia complementation group, FA-D1/BRCA2
Energy Technology Data Exchange (ETDEWEB)
Godthelp, Barbara C. [Department of Toxicogenetics, Leiden University Medical Center, Building 2, Postzone S-6-P, P.O. Box 9600, 2300 RC, Leiden (Netherlands); Buul, Paul P.W. van [Department of Toxicogenetics, Leiden University Medical Center, Building 2, Postzone S-6-P, P.O. Box 9600, 2300 RC, Leiden (Netherlands); Jaspers, Nicolaas G.J. [Department of Cell Biology and Genetics, Erasmus University, P.O. Box 1738, 3000 DR Rotterdam (Netherlands); Elghalbzouri-Maghrani, Elhaam [Department of Toxicogenetics, Leiden University Medical Center, Building 2, Postzone S-6-P, P.O. Box 9600, 2300 RC, Leiden (Netherlands); Duijn-Goedhart, Annemarie van [Department of Toxicogenetics, Leiden University Medical Center, Building 2, Postzone S-6-P, P.O. Box 9600, 2300 RC, Leiden (Netherlands); Arwert, Fre [Department of Clinical Genetics and Human Genetics, Free University Medical Center, Amsterdam (Netherlands); Joenje, Hans [Department of Clinical Genetics and Human Genetics, Free University Medical Center, Amsterdam (Netherlands); Zdzienicka, Malgorzata Z. [Department of Toxicogenetics, Leiden University Medical Center, Building 2, Postzone S-6-P, P.O. Box 9600, 2300 RC, Leiden (Netherlands) and Department of Molecular Cell Genetics, Collegium Medicum, N.Copernicus University, Bydgoszcz (Poland)]. E-mail: M.Z.Zdzienicka@LUMC.nl
2006-10-10
Fanconi anemia (FA) is an inherited cancer-susceptibility disorder, characterized by genomic instability and hypersensitivity to DNA cross-linking agents. The discovery of biallelic BRCA2 mutations in the FA-D1 complementation group allows for the first time to study the characteristics of primary BRCA2-deficient human cells. FANCD1/BRCA2-deficient fibroblasts appeared hypersensitive to mitomycin C (MMC), slightly sensitive to methyl methane sulfonate (MMS), and like cells derived from other FA complementation groups, not sensitive to X-ray irradiation. However, unlike other FA cells, FA-D1 cells were slightly sensitive to UV irradiation. Despite the observed lack of X-ray sensitivity in cell survival, significant radioresistant DNA synthesis (RDS) was observed in the BRCA2-deficient fibroblasts but also in the FANCA-deficient fibroblasts, suggesting an impaired S-phase checkpoint. FA-D1/BRCA2 cells displayed greatly enhanced levels of spontaneous as well as MMC-induced chromosomal aberrations (Canada), similar to cells deficient in homologous recombination (HR) and non-D1 FA cells. In contrast to Brca2-deficient rodent cells, FA-D1/BRCA2 cells showed normal sister chromatid exchange (SCE) levels, both spontaneous as well as after MMC treatment. Hence, these data indicate that human cells with biallelic BRCA2 mutations display typical features of both FA- and HR-deficient cells, which suggests that FANCD1/BRCA2 is part of the integrated FA/BRCA DNA damage response pathway but also controls other functions outside the FA pathway.
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
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
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) ...
Institute of Scientific and Technical Information of China (English)
Katsuaki Koike
2011-01-01
Sample data in the Earth and environmental sciences are limited in quantity and sampling location and therefore, sophisticated spatial modeling techniques are indispensable for accurate imaging of complicated structures and properties of geomaterials. This paper presents several effective methods that are grouped into two categories depending on the nature of regionalized data used. Type I data originate from plural populations and type II data satisfy the prerequisite of stationarity and have distinct spatial correlations. For the type I data, three methods are shown to be effective and demonstrated to produce plausible results: (1) a spline-based method, (2) a combination of a spline-based method with a stochastic simulation, and (3) a neural network method. Geostatistics proves to be a powerful tool for type II data. Three new approaches of geostatistics are presented with case studies: an application to directional data such as fracture, multi-scale modeling that incorporates a scaling law,and space-time joint analysis for multivariate data. Methods for improving the contribution of such spatial modeling to Earth and environmental sciences are also discussed and future important problems to be solved are summarized.
Energy Technology Data Exchange (ETDEWEB)
Foxall, W; Cunningham, C; Mellors, R; Templeton, D; Dyer, K; White, J
2012-02-27
ability to detect evidence for an underground facility using InSAR depends on the displacement sensitivity and spatial resolution of the interferogram, as well as on the size and depth of the facility and the time since its completion. The methodology development described in this report focuses on the exploitation of synthetic aperture radar data that are available commercially from a number of satellite missions. Development of the method involves three components: (1) Evaluation of the capability of InSAR to detect and characterize underground facilities ; (2) inversion of InSAR data to infer the location, depth, shape and volume of a subsurface facility; and (3) evaluation and selection of suitable geomechanical forward models to use in the inversion. We adapted LLNL's general-purpose Bayesian Markov Chain-Monte Carlo procedure, the 'Stochastic Engine' (SE), to carry out inversions to characterize subsurface void geometries. The SE performs forward simulations for a large number of trial source models to identify the set of models that are consistent with the observations and prior constraints. The inverse solution produced by this kind of stochastic method is a posterior probability density function (pdf) over alternative models, which forms an appropriate input to risk-based decision analyses to evaluate subsequent response strategies. One major advantage of a stochastic inversion approach is its ability to deal with complex, non-linear forward models employing empirical, analytical or numerical methods. However, while a geomechanical model must incorporate adequate physics to enable sufficiently accurate prediction of surface displacements, it must also be computationally fast enough to render the large number of forward realizations needed in stochastic inversion feasible. This latter requirement prompted us first to investigate computationally efficient empirical relations and closed-form analytical solutions. However, our evaluation revealed
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.
Dynamic stochastic optimization
Ermoliev, Yuri; Pflug, Georg
2004-01-01
Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu tions. Objective an...
Stochastic 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...
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
Directory of Open Access Journals (Sweden)
Staci L Solin
Full Text Available In this study we describe the molecular and cellular characterization of a zebrafish mutant that develops tumors in the optic pathway. Heterozygous Tg(flk1:RFPis18 transgenic adults develop tumors of the retina, optic nerve and optic tract. Molecular and genetic mapping demonstrate the tumor phenotype is linked to a high copy number transgene array integrated in the lincRNA gene lincRNAis18/Zv9_00007276 on chromosome 3. TALENs were used to isolate a 147 kb deletion allele that removes exons 2-5 of the lincRNAis18 gene. Deletion allele homozygotes are viable and do not develop tumors, indicating loss of function of the lincRNAis18 locus is not the trigger for tumor onset. Optic pathway tumors in the Tg(flk1:RFPis18 mutant occur with a penetrance of 80-100% by 1 year of age. The retinal tumors are highly vascularized and composed of rosettes of various sizes embedded in a fibrous matrix. Immunohistochemical analysis showed increased expression of the glial markers GFAP and BLBP throughout retinal tumors and in dysplastic optic nerve. We performed transcriptome analysis of pre-tumorous retina and retinal tumor tissue and found changes in gene expression signatures of radial glia and astrocytes (slc1a3, activated glia (atf3, blbp, apoeb, proliferating neural progenitors (foxd3, nestin, cdh2, her9/hes1, and glioma markers (S100β, vim. The transcriptome also revealed activation of cAMP, Stat3 and Wnt signal transduction pathways. qRT-PCR confirmed >10-fold overexpression of the Wnt pathway components hbegfa, ascl1a, and insm1a. Together the data indicate Müller glia and/or astrocyte-derived progenitors could contribute to the zebrafish Tg(flk1:RFPis18 optic pathway tumors.
Directory of Open Access Journals (Sweden)
Débora L Oliveira
Full Text Available BACKGROUND: Extracellular vesicles in yeast cells are involved in the molecular traffic across the cell wall. In yeast pathogens, these vesicles have been implicated in the transport of proteins, lipids, polysaccharide and pigments to the extracellular space. Cellular pathways required for the biogenesis of yeast extracellular vesicles are largely unknown. METHODOLOGY/PRINCIPAL FINDINGS: We characterized extracellular vesicle production in wild type (WT and mutant strains of the model yeast Saccharomyces cerevisiae using transmission electron microscopy in combination with light scattering analysis, lipid extraction and proteomics. WT cells and mutants with defective expression of Sec4p, a secretory vesicle-associated Rab GTPase essential for Golgi-derived exocytosis, or Snf7p, which is involved in multivesicular body (MVB formation, were analyzed in parallel. Bilayered vesicles with diameters at the 100-300 nm range were found in extracellular fractions from yeast cultures. Proteomic analysis of vesicular fractions from the cells aforementioned and additional mutants with defects in conventional secretion pathways (sec1-1, fusion of Golgi-derived exocytic vesicles with the plasma membrane; bos1-1, vesicle targeting to the Golgi complex or MVB functionality (vps23, late endosomal trafficking revealed a complex and interrelated protein collection. Semi-quantitative analysis of protein abundance revealed that mutations in both MVB- and Golgi-derived pathways affected the composition of yeast extracellular vesicles, but none abrogated vesicle production. Lipid analysis revealed that mutants with defects in Golgi-related components of the secretory pathway had slower vesicle release kinetics, as inferred from intracellular accumulation of sterols and reduced detection of these lipids in vesicle fractions in comparison with WT cells. CONCLUSIONS/SIGNIFICANCE: Our results suggest that both conventional and unconventional pathways of secretion are
Energy Technology Data Exchange (ETDEWEB)
Bhaskar,; Kumari, Neeti [Division of Biochemistry, CSIR-Central Drug Research Institute, Chattar Manzil Palace, PO Box 173, Lucknow (India); Goyal, Neena, E-mail: neenacdri@yahoo.com [Division of Biochemistry, CSIR-Central Drug Research Institute, Chattar Manzil Palace, PO Box 173, Lucknow (India)
2012-12-07
Highlights: Black-Right-Pointing-Pointer The study presents cloning and characterization of TCP1{gamma} gene from L. donovani. Black-Right-Pointing-Pointer TCP1{gamma} is a subunit of T-complex protein-1 (TCP1), a chaperonin class of protein. Black-Right-Pointing-Pointer LdTCP{gamma} exhibited differential expression in different stages of promastigotes. Black-Right-Pointing-Pointer LdTCP{gamma} co-localized with actin, a cytoskeleton protein. Black-Right-Pointing-Pointer The data suggests that this gene may have a role in differentiation/biogenesis. Black-Right-Pointing-Pointer First report on this chapronin in Leishmania. -- Abstract: T-complex protein-1 (TCP1) complex, a chaperonin class of protein, ubiquitous in all genera of life, is involved in intracellular assembly and folding of various proteins. The gamma subunit of TCP1 complex (TCP1{gamma}), plays a pivotal role in the folding and assembly of cytoskeleton protein(s) as an individual or complexed with other subunits. Here, we report for the first time cloning, characterization and expression of the TCP1{gamma} of Leishmania donovani (LdTCP1{gamma}), the causative agent of Indian Kala-azar. Primary sequence analysis of LdTCP1{gamma} revealed the presence of all the characteristic features of TCP1{gamma}. However, leishmanial TCP1{gamma} represents a distinct kinetoplastid group, clustered in a separate branch of the phylogenic tree. LdTCP1{gamma} exhibited differential expression in different stages of promastigotes. The non-dividing stationary phase promastigotes exhibited 2.5-fold less expression of LdTCP1{gamma} as compared to rapidly dividing log phase parasites. The sub-cellular distribution of LdTCP1{gamma} was studied in log phase promastigotes by employing indirect immunofluorescence microscopy. The protein was present not only in cytoplasm but it was also localized in nucleus, peri-nuclear region, flagella, flagellar pocket and apical region. Co-localization of LdTCP1{gamma} with actin suggests
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.
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)
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.
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...
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.
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.
Li, Xiuying; Chen, Dan; Le, Chaoyi; Zhu, Chunliu; Gan, Yong; Hovgaard, Lars; Yang, Mingshi
2011-01-01
Background The aim of this study was to investigate the intestinal mucus-penetrating properties and intestinal cellular uptake of two types of liposomes modified by Pluronic F127 (PF127). Methods The two types of liposomes, ie, PF127-inlaid liposomes and PF127-adsorbed liposomes, were prepared by a thin-film hydration method followed by extrusion, in which coumarin 6 was loaded as a fluorescence marker. A modified Franz diffusion cell mounted with the intestinal mucus of rats was used to study the diffusion characteristics of the two types of PF127 liposomes. Cell uptake studies were conducted in Caco-2 cells and analyzed using confocal laser scanning microcopy as well as flow cytometry. Results The diffusion efficiency of the two types of PF127-modified liposomes through intestinal rat mucus was 5–7-fold higher than that of unmodified liposomes. Compared with unmodified liposomes, PF127-inlaid liposomes showed significantly higher cellular uptake of courmarin 6. PF127-adsorbed liposomes showed a lower cellular uptake. Moreover, and interestingly, the two types of PF127-modified liposomes showed different cellular uptake mechanisms in Caco-2 cells. Conclusion PF127-inlaid liposomes with improved intestinal mucus-penetrating ability and enhanced cellular uptake might be a potential carrier candidate for oral drug delivery. PMID:22163166
Stochastic superparameterization in quasigeostrophic turbulence
Grooms, Ian
2013-01-01
In this article we expand and develop the authors' recent proposed methodology for efficient stochastic superparameterization (SP) algorithms for geophysical turbulence. Geophysical turbulence is characterized by significant intermittent cascades of energy from the unresolved to the resolved scales resulting in complex patterns of waves, jets, and vortices. Conventional SP simulates large scale dynamics on a coarse grid in a physical domain, and couples these dynamics to high-resolution simulations on periodic domains embedded in the coarse grid. Stochastic SP replaces the nonlinear, deterministic eddy equations on periodic embedded domains by quasilinear stochastic approximations on formally infinite embedded domains. The result is a seamless algorithm which never uses a small scale grid and is far cheaper than conventional SP, but with significant success in difficult test problems. Various design choices in the algorithm are investigated in detail here, including decoupling the timescale of evolution on th...
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.
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
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
A Temporal Approach to Stochastic Network Calculus
Xie, Jing; Xie, Min
2011-01-01
Stochastic network calculus is a newly developed theory for stochastic service guarantee analysis of computer networks. In the current stochastic network calculus literature, its fundamental models are based on the cumulative amount of traffic or cumulative amount of service. However, there are network scenarios where direct application of such models is difficult. This paper presents a temporal approach to stochastic network calculus. The key idea is to develop models and derive results from the time perspective. Particularly, we define traffic models and service models based on the cumulative packet inter-arrival time and the cumulative packet service time, respectively. Relations among these models as well as with the existing models in the literature are established. In addition, we prove the basic properties of the proposed models, such as delay bound and backlog bound, output characterization, concatenation property and superposition property. These results form a temporal stochastic network calculus an...
Directory of Open Access Journals (Sweden)
Judith Martín-de León
2016-07-01
Full Text Available This paper describes the processing conditions needed to produce low density nanocellular polymers based on polymethylmethacrylate (PMMA with relative densities between 0.45 and 0.25, cell sizes between 200 and 250 nm and cell densities higher than 1014 cells/cm3. To produce these nanocellular polymers, the foaming parameters of the gas dissolution foaming technique using CO2 as blowing agent have been optimized. Taking into account previous works, the amount of CO2 uptake was maintained constant (31% by weight for all the materials. Foaming parameters were modified between 40 °C and 110 °C for the foaming temperature and from 1 to 5 min for the foaming time. Foaming temperatures in the range of 80 to 100 °C and foaming times of 2 min allow for production of nanocellular polymers with relative densities as low as 0.25. Cellular structure has been studied in-depth to obtain the processing-cellular structure relationship. In addition, it has been proved that the glass transition temperature depends on the cellular structure. This effect is associated with a confinement of the polymer in the cell walls, and is one of the key reasons for the improved properties of nanocellular polymers.
Recursive Concurrent Stochastic Games
Etessami, Kousha
2008-01-01
We study Recursive Concurrent Stochastic Games (RCSGs), extending our recent analysis of recursive simple stochastic games [16,17] to a concurrent setting where the two players choose moves simultaneously and independently at each state. For multi-exit games, our earlier work already showed undecidability for basic questions like termination, thus we focus on the important case of single-exit RCSGs (1-RCSGs). We first characterize the value of a 1-RCSG termination game as the least fixed point solution of a system of nonlinear minimax functional equations, and use it to show PSPACE decidability for the quantitative termination problem. We then give a strategy improvement technique, which we use to show that player 1 (maximizer) has \\epsilon-optimal randomized Stackless & Memoryless (r-SM) strategies for all \\epsilon > 0, while player 2 (minimizer) has optimal r-SM strategies. Thus, such games are r-SM-determined. These results mirror and generalize in a strong sense the randomized memoryless determinacy r...
Stochastic 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...
Stochastic tools in turbulence
Lumey, John L
2012-01-01
Stochastic Tools in Turbulence discusses the available mathematical tools to describe stochastic vector fields to solve problems related to these fields. The book deals with the needs of turbulence in relation to stochastic vector fields, particularly, on three-dimensional aspects, linear problems, and stochastic model building. The text describes probability distributions and densities, including Lebesgue integration, conditional probabilities, conditional expectations, statistical independence, lack of correlation. The book also explains the significance of the moments, the properties of the
Modeling and analysis of stochastic systems
Kulkarni, Vidyadhar G
2011-01-01
Based on the author's more than 25 years of teaching experience, Modeling and Analysis of Stochastic Systems, Second Edition covers the most important classes of stochastic processes used in the modeling of diverse systems, from supply chains and inventory systems to genetics and biological systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. Along with reorganizing the material, this edition revises and adds new exercises and examples. New to the second edi
DEFF Research Database (Denmark)
Kjærup, Rikke Munkholm; Dalgaard, Tina Sørensen; Norup, Liselotte Rothmann;
2014-01-01
Chickens from two inbred lines selected for high (L10H) or low (L10L) mannose-binding lectin (MBL) serum concentrations were infected with infectious bronchitis virus (IBV), and innate as well as adaptive immunological parameters were measured throughout the experimental period. Chickens with high...... L10H chickens than in the infected and noninfected L10L chickens. Thus, these results indicate that MBL is produced locally and may be involved in the regulation of the cellular immune response after an IBV infection. However, MBL did not appear to influence the humoral immune response after IBV...
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
Oware, E. K.
2015-12-01
Modeling aquifer heterogeneities (AH) is a complex, multidimensional problem that mostly requires stochastic imaging strategies for tractability. While the traditional Bayesian Markov chain Monte Carlo (McMC) provides a powerful framework to model AH, the generic McMC is computationally prohibitive and, thus, unappealing for large-scale problems. An innovative variant of the McMC scheme that imposes priori spatial statistical constraints on model parameter updates, for improved characterization in a computationally efficient manner is proposed. The proposed algorithm (PA) is based on Markov random field (MRF) modeling, which is an image processing technique that infers the global behavior of a random field from its local properties, making the MRF approach well suited for imaging AH. MRF-based modeling leverages the equivalence of Gibbs (or Boltzmann) distribution (GD) and MRF to identify the local properties of an MRF in terms of the easily quantifiable Gibbs energy. The PA employs the two-step approach to model the lithological structure of the aquifer and the hydraulic properties within the identified lithologies simultaneously. It performs local Gibbs energy minimizations along a random path, which requires parameters of the GD (spatial statistics) to be specified. A PA that implicitly infers site-specific GD parameters within a Bayesian framework is also presented. The PA is illustrated with a synthetic binary facies aquifer with a lognormal heterogeneity simulated within each facies. GD parameters of 2.6, 1.2, -0.4, and -0.2 were estimated for the horizontal, vertical, NESW, and NWSE directions, respectively. Most of the high hydraulic conductivity zones (facies 2) were fairly resolved (see results below) with facies identification accuracy rate of 81%, 89%, and 90% for the inversions conditioned on concentration (R1), resistivity (R2), and joint (R3), respectively. The incorporation of the conditioning datasets improved on the root mean square error (RMSE
Cell-to-Cell stochastic fluctuations in apoptotic signaling can decide between life and death
Raychaudhuri, S; Nguyen, T; Khan, E M; Goldkorn, T
2007-01-01
Apoptosis, or genetically programmed cell death, is a crucial cellular process that maintains the balance between life and death in cells. The precise molecular mechanism of apoptosis signaling and how these two pathways are differentially activated under distinct apoptotic stimuli is poorly understood. We developed a Monte Carlo-based stochastic simulation model that can characterize distinct signaling behaviors in the two major pathways of apoptotic signaling using a novel probability distribution-based approach. Specifically, we show that for a weak death signal, such as low levels of death ligand Fas (CD95) binding or under stress conditions, the type 2 mitochondrial pathway dominates apoptotic signaling. Our results also show signaling in the type 2 pathway is stochastic, where the population average over many cells does not capture the cell-to-cell fluctuations in the time course (~1 - 10 hours) of downstream caspase-3 activation. On the contrary, the probability distribution of caspase-3 activation for...
Stochastic differential games with inside information
Draouil, Olfa; Øksendal, Bernt
2016-08-01
We study stochastic differential games of jump diffusions, where the players have access to inside information. Our approach is based on anticipative stochastic calculus, white noise, Hida-Malliavin calculus, forward integrals and the Donsker delta functional. We obtain a characterization of Nash equilibria of such games in terms of the corresponding Hamiltonians. This is used to study applications to insider games in finance, specifically optimal insider consumption and optimal insider portfolio under model uncertainty.
Reversible quantum cellular automata
Schumacher, B
2004-01-01
We define quantum cellular automata as infinite quantum lattice systems with discrete time dynamics, such that the time step commutes with lattice translations and has strictly finite propagation speed. In contrast to earlier definitions this allows us to give an explicit characterization of all local rules generating such automata. The same local rules also generate the global time step for automata with periodic boundary conditions. Our main structure theorem asserts that any quantum cellular automaton is structurally reversible, i.e., that it can be obtained by applying two blockwise unitary operations in a generalized Margolus partitioning scheme. This implies that, in contrast to the classical case, the inverse of a nearest neighbor quantum cellular automaton is again a nearest neighbor automaton. We present several construction methods for quantum cellular automata, based on unitaries commuting with their translates, on the quantization of (arbitrary) reversible classical cellular automata, on quantum c...
Spatial stochastic dynamics enable robust cell polarization.
Directory of Open Access Journals (Sweden)
Michael J Lawson
Full Text Available Although cell polarity is an essential feature of living cells, it is far from being well-understood. Using a combination of computational modeling and biological experiments we closely examine an important prototype of cell polarity: the pheromone-induced formation of the yeast polarisome. Focusing on the role of noise and spatial heterogeneity, we develop and investigate two mechanistic spatial models of polarisome formation, one deterministic and the other stochastic, and compare the contrasting predictions of these two models against experimental phenotypes of wild-type and mutant cells. We find that the stochastic model can more robustly reproduce two fundamental characteristics observed in wild-type cells: a highly polarized phenotype via a mechanism that we refer to as spatial stochastic amplification, and the ability of the polarisome to track a moving pheromone input. Moreover, we find that only the stochastic model can simultaneously reproduce these characteristics of the wild-type phenotype and the multi-polarisome phenotype of a deletion mutant of the scaffolding protein Spa2. Significantly, our analysis also demonstrates that higher levels of stochastic noise results in increased robustness of polarization to parameter variation. Furthermore, our work suggests a novel role for a polarisome protein in the stabilization of actin cables. These findings elucidate the intricate role of spatial stochastic effects in cell polarity, giving support to a cellular model where noise and spatial heterogeneity combine to achieve robust biological function.
Stochastic resonance in an intracellular genetic perceptron
Bates, Russell; Blyuss, Oleg; Zaikin, Alexey
2014-03-01
Intracellular genetic networks are more intelligent than was first assumed due to their ability to learn. One of the manifestations of this intelligence is the ability to learn associations of two stimuli within gene-regulating circuitry: Hebbian-type learning within the cellular life. However, gene expression is an intrinsically noisy process; hence, we investigate the effect of intrinsic and extrinsic noise on this kind of intracellular intelligence. We report a stochastic resonance in an intracellular associative genetic perceptron, a noise-induced phenomenon, which manifests itself in noise-induced increase of response in efficiency after the learning event under the conditions of optimal stochasticity.
Orillard, Emilie; Radicella, J. Pablo; Marsin, Stéphanie
2011-01-01
Helicobacter pylori is a bacterial pathogen colonizing half of the world's human population. It has been implicated in a number of gastric diseases, from asymptomatic gastritis to cancer. It is characterized by an amazing genetic variability that results from high mutation rates and efficient DNA homologous recombination and transformation systems. Here, we report the characterization of H. pylori RecA (HpRecA), a protein shown to be involved in DNA repair, transformation, and mouse colonizat...
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...
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.
Ito equations out of domino cellular automaton with efficiency parameters
Czechowski, Zbigniew
2011-01-01
Ito equations are derived for simple stochastic cellular automaton with parameters and compared with results obtained from the histogram method. Good agreement for various parameters supports wide applicability of the Ito equation as a macroscopic model.
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
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.
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
Park, Ok Hyun; Park, Joori; Yu, Mira; An, Hyoung-Tae; Ko, Jesang; Kim, Yoon Ki
2016-01-01
Glucocorticoid (GC) receptor (GR) has been shown recently to bind a subset of mRNAs and elicit rapid mRNA degradation. However, the molecular details of GR-mediated mRNA decay (GMD) remain unclear. Here, we demonstrate that GMD triggers rapid degradation of target mRNAs in a translation-independent and exon junction complex-independent manner, confirming that GMD is mechanistically distinct from nonsense-mediated mRNA decay (NMD). Efficient GMD requires PNRC2 (proline-rich nuclear receptor coregulatory protein 2) binding, helicase ability, and ATM-mediated phosphorylation of UPF1 (upstream frameshift 1). We also identify two GMD-specific factors: an RNA-binding protein, YBX1 (Y-box-binding protein 1), and an endoribonuclease, HRSP12 (heat-responsive protein 12). In particular, using HRSP12 variants, which are known to disrupt trimerization of HRSP12, we show that HRSP12 plays an essential role in the formation of a functionally active GMD complex. Moreover, we determine the hierarchical recruitment of GMD factors to target mRNAs. Finally, our genome-wide analysis shows that GMD targets a variety of transcripts, implicating roles in a wide range of cellular processes, including immune responses.
Ma, Rui; Tang, Songchao; Tan, Honglue; Qian, Jun; Lin, Wentao; Wang, Yugang; Liu, Changsheng; Wei, Jie; Tang, Tingting
2014-08-13
In this study, a nanocalcium silicate (n-CS)/polyetheretherketone (PEEK) bioactive composite was prepared using a process of compounding and injection-molding. The mechanical properties, hydrophilicity, and in vitro bioactivity of the composite, as well as the cellular responses of MC3T3-E1 cells (attachment, proliferation, spreading, and differentiation) to the composite, were investigated. The results showed that the mechanical properties and hydrophilicity of the composites were significantly improved by the addition of n-CS to PEEK. In addition, an apatite-layer formed on the composite surface after immersion in simulated body fluid (SBF) for 7 days. In cell culture tests, the results revealed that the n-CS/PEEK composite significantly promoted cell attachment, proliferation, and spreading compared with PEEK or ultrahigh molecular weight polyethylene (UHMWPE). Moreover, cells grown on the composite exhibited higher alkaline phosphatase (ALP) activity, more calcium nodule-formation, and higher expression levels of osteogenic differentiation-related genes than cells grown on PEEK or UHMWPE. These results indicated that the incorporation of n-CS to PEEK could greatly improve the bioactivity and biocompatibility of the composite. Thus, the n-CS/PEEK composite may be a promising bone repair material for use in orthopedic clinics.
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...
Fundamentals of Stochastic Networks
Ibe, Oliver C
2011-01-01
An interdisciplinary approach to understanding queueing and graphical networks In today's era of interdisciplinary studies and research activities, network models are becoming increasingly important in various areas where they have not regularly been used. Combining techniques from stochastic processes and graph theory to analyze the behavior of networks, Fundamentals of Stochastic Networks provides an interdisciplinary approach by including practical applications of these stochastic networks in various fields of study, from engineering and operations management to communications and the physi
Zhong, Yaogang; Zhang, Jing; Yu, Hanjie; Zhang, Jiaxu; Sun, Xiu-Xuan; Chen, Wentian; Bian, Huijie; Li, Zheng
2015-12-25
Although the expression levels of total GalNAc-binding proteins (GNBPs) were up-regulated significantly in human hepatic stellate cells (HSCs) activated with transforming growth factor-β1(TGF-β1), yet little is known about the precise types, distribution and sub-cellular localization of the GNBPs in HSCs. Here, 264 GNBPs from the activated HSCs and 257 GNBPs from the quiescent HSCs were identified and annotated. A total of 46 GNBPs were estimated to be significantly up-regulated and 40 GNBPs were estimated to be significantly down-regulated in the activated HSCs. For example, the GNBPs (i.e. BTF3, COX17, and ATP5A1) responsible for the regulation of protein binding were up-regulated, and those (i.e. FAM114A1, ENO3, and TKT) responsible for the regulation of protein binding were down-regulated in the activated HSCs. The motifs of the isolated GNBPs showed that Proline residue had the maximum preference in consensus sequences. The western blotting showed the expression levels of COX17, and PRMT1 were significantly up-regulated, while, the expression level of CLIC1(B5) was down-regulated in the activated HSCs and liver cirrhosis tissues. Moreover, the GNBPs were sub-localized in the Golgi apparatus of HSCs. In conclusion, the precision alteration of the GNBPs referred to pathological changes in liver fibrosis/cirrhosis may provide useful information to find new molecular mechanism of HSC activation and discover the biomarkers for diagnosis of liver fibrosis/cirrhosis as well as development of new anti-fibrotic strategies.
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.
Singular stochastic differential equations
Cherny, Alexander S
2005-01-01
The authors introduce, in this research monograph on stochastic differential equations, a class of points termed isolated singular points. Stochastic differential equations possessing such points (called singular stochastic differential equations here) arise often in theory and in applications. However, known conditions for the existence and uniqueness of a solution typically fail for such equations. The book concentrates on the study of the existence, the uniqueness, and, what is most important, on the qualitative behaviour of solutions of singular stochastic differential equations. This is done by providing a qualitative classification of isolated singular points, into 48 possible types.
Directory of Open Access Journals (Sweden)
Ding X
2012-02-01
Full Text Available Wei Fan1,2,*, Xin Wu1,*, Baoyue Ding3,*, Jing Gao4, Zhen Cai1, Wei Zhang1, Dongfeng Yin1, Xiang Wang1, Quangang Zhu1, Jiyong Liu1, Xueying Ding4, Shen Gao1 1Department of Pharmaceutics, Changhai Hospital, Second Military Medical University, Shanghai, 2Department of Pharmaceutics, The 425th Hospital of PLA, Sanya, 3Department of Pharmaceutics, Medical College of Jiaxing University, Jiaxing, 4Department of Pharmaceutics, School of Pharmacy, Second Military Medical University, Shanghai, People's Republic of China*These authors contributed equally to this workBackground: Cationic copolymers consisting of polycations linked to nonionic amphiphilic block polymers have been evaluated as nonviral gene delivery systems, and a large number of different polymers and copolymers of linear, branched, and dendrimeric architectures have been tested in terms of their suitability and efficacy for in vitro and in vivo transfection. However, the discovery of new potent materials still largely relies on empiric approaches rather than a rational design. The authors investigated the relationship between the polymers' structures and their biological performance, including DNA compaction, toxicity, transfection efficiency, and the effect of cellular uptake.Methods: This article reports the synthesis and characterization of a series of cationic copolymers obtained by grafting polyethyleneimine with nonionic amphiphilic surfactant polyether-Pluronic® consisting of hydrophilic ethylene oxide and hydrophobic propylene oxide blocks. Transgene expression, cytotoxicity, localization of plasmids, and cellular uptake of these copolymers were evaluated following in vitro transfection of HeLa cell lines with various individual components of the copolymers.Results: Pluronics can exhibit biological activity including effects on enhancing DNA cellular uptake, nuclear translocation, and gene expression. The Pluronics with a higher hydrophilic-lipophilic balance value lead to
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 ...
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 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)
Greenwood, Priscilla E
2016-01-01
This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise. This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may contribute neuroscience insight. An extensive bibliography is included. Dr. Priscilla E. Greenwood is a Professor Emerita in the Department of Mathematics at the University of British Columbia. Dr. Lawrence M. Ward is a Professor in the Department of Psychology and the Brain...
Directory of Open Access Journals (Sweden)
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.
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 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
Stochastic simulations of a synthetic bacteria-yeast ecosystem
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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
Institute of Scientific and Technical Information of China (English)
杨周
1996-01-01
Cellular phones, used in automobiles, airliners, and passenger trains, are basically low-power radiotelephones. Calls go through radio transmitters that are located within small geographical units called cells. Because each cell’s signals are too weak to interfere with those of other cells operating on the same fre-
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.
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 calculus with infinitesimals
Herzberg, Frederik
2013-01-01
Stochastic analysis is not only a thriving area of pure mathematics with intriguing connections to partial differential equations and differential geometry. It also has numerous applications in the natural and social sciences (for instance in financial mathematics or theoretical quantum mechanics) and therefore appears in physics and economics curricula as well. However, existing approaches to stochastic analysis either presuppose various concepts from measure theory and functional analysis or lack full mathematical rigour. This short book proposes to solve the dilemma: By adopting E. Nelson's "radically elementary" theory of continuous-time stochastic processes, it is based on a demonstrably consistent use of infinitesimals and thus permits a radically simplified, yet perfectly rigorous approach to stochastic calculus and its fascinating applications, some of which (notably the Black-Scholes theory of option pricing and the Feynman path integral) are also discussed in the book.
Frédéric, Pierret
2014-01-01
The equations of celestial mechanics that govern the variation of the orbital elements are completely derived for stochastic perturbation which generalized the classic perturbation equations which are used since Gauss, starting from Newton's equation and it's solution. The six most understandable orbital element, the semi-major axis, the eccentricity, the inclination, the longitude of the ascending node, the pericenter angle and the mean motion are express in term of the angular momentum vector $\\textbf{H}$ per unit of mass and the energy $E$ per unit of mass. We differentiate those expressions using It\\^o's theory of differential equations due to the stochastic nature of the perturbing force. The result is applied to the two-body problem perturbed by a stochastic dust cloud and also perturbed by a stochastic dynamical oblateness of the central body.
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 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.
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,...
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 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
Geometric Stochastic Resonance
Ghosh, Pulak Kumar; Savel'ev, Sergey E; Nori, Franco
2015-01-01
A Brownian particle moving across a porous membrane subject to an oscillating force exhibits stochastic resonance with properties which strongly depend on the geometry of the confining cavities on the two sides of the membrane. Such a manifestation of stochastic resonance requires neither energetic nor entropic barriers, and can thus be regarded as a purely geometric effect. The magnitude of this effect is sensitive to the geometry of both the cavities and the pores, thus leading to distinctive optimal synchronization conditions.
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...
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.
Scattering theory of stochastic electromagnetic light waves.
Wang, Tao; Zhao, Daomu
2010-07-15
We generalize scattering theory to stochastic electromagnetic light waves. It is shown that when a stochastic electromagnetic light wave is scattered from a medium, the properties of the scattered field can be characterized by a 3 x 3 cross-spectral density matrix. An example of scattering of a spatially coherent electromagnetic light wave from a deterministic medium is discussed. Some interesting phenomena emerge, including the changes of the spectral degree of coherence and of the spectral degree of polarization of the scattered field.
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.
Stochasticity in cell biology: Modeling across levels
Pedraza, Juan Manuel
2009-03-01
Effective modeling of biological processes requires focusing on a particular level of description, and this requires summarizing de details of lower levels into effective variables and properly accounting for the constrains that other levels impose. In the context of stochasticity in gene expression, I will show how the details of the stochastic process can be characterized by a few effective parameters, which facilitates modeling but complicates interpretation of current experiments. I will show how the resulting noise can provide advantageous or deleterious phenotypic fluctuation and how noise control in the copy number control system of plasmids can change the selective pressures. This system illustrates the direct connection between molecular dynamics and evolutionary dynamics.
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.
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
Contributions of stochastic events to biological evolution and cancer
Directory of Open Access Journals (Sweden)
Anderson KM
2015-10-01
Full Text Available Stochastic genetic and epigenetic events have been fundamental in contributing to the development of manifold life-forms, past and present. The development of malignant cell clones and the role of stochasticity as a driving force in cancer cell evolution complements, in a perverse way evidence for the role of chance in normal cellular development and evolution. Stochastic events at multiple levels of cellular control and implementation represent a primary driving force and an ultimate filter through which evolutionary innovation occurs. Stochasticity provides the opportunity for a random assortment of disparate genetic and epigenetic events, in some instances resulting in altered metabolic and developmental capabilities of sufficient stability and uniqueness to contribute to deterministic sequelae that promote the viability and procreation of cells under stress. Cellular evolution has so far resulted in a “survival of a (sic fittest”, often dependent mechanistically on and determined by stochastic events. The implications of this are mirrored in the evolution of malignant change, to some extent as a variant of “reverse engineering” of dedifferentiation. Efforts to reduce the incidence of malignant change will have to take in to account its random nature and further the understanding of this feature.
Computational stochastic model of ions implantation
Energy Technology Data Exchange (ETDEWEB)
Zmievskaya, Galina I., E-mail: zmi@gmail.ru; Bondareva, Anna L., E-mail: bal310775@yandex.ru [M.V. Keldysh Institute of Applied Mathematics RAS, 4,Miusskaya sq., 125047 Moscow (Russian Federation); Levchenko, Tatiana V., E-mail: tatlevchenko@mail.ru [VNII Geosystem Russian Federal Center, Varshavskoye roadway, 8, Moscow (Russian Federation); Maino, Giuseppe, E-mail: giuseppe.maino@enea.it [Scuola di Lettere e BeniCulturali, University di Bologna, sede di Ravenna, via Mariani 5, 48100 Ravenna (Italy)
2015-03-10
Implantation flux ions into crystal leads to phase transition /PT/ 1-st kind. Damaging lattice is associated with processes clustering vacancies and gaseous bubbles as well their brownian motion. System of stochastic differential equations /SDEs/ Ito for evolution stochastic dynamical variables corresponds to the superposition Wiener processes. The kinetic equations in partial derivatives /KE/, Kolmogorov-Feller and Einstein-Smolukhovskii, were formulated for nucleation into lattice of weakly soluble gases. According theory, coefficients of stochastic and kinetic equations uniquely related. Radiation stimulated phase transition are characterized by kinetic distribution functions /DFs/ of implanted clusters versus their sizes and depth of gas penetration into lattice. Macroscopic parameters of kinetics such as the porosity and stress calculated in thin layers metal/dielectric due to Xe{sup ++} irradiation are attracted as example. Predictions of porosity, important for validation accumulation stresses in surfaces, can be applied at restoring of objects the cultural heritage.
Stochastic 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.
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.
Wang, Maosheng; Sun, Runzhi
2014-03-01
The cooperative effects of inherent stochasticity and random long-range connections (RLRCs) on synchronization and coherence resonance in networks of calcium oscillators have been investigated. Two different types of collective behaviors, coherence resonance (CR) and synchronization, have been studied numerically in the context of chemical Langevin equations (CLEs). In the CLEs, the reaction steps are all stochastic, including the exchange of calcium ions between adjacent and non-adjacent cells through the gap junctions. The calcium oscillators’ synchronization was characterized by the standard deviation of the cytosolic calcium concentrations. Meanwhile, the temporal coherence of the calcium spike train was characterized by the reciprocal coefficient of variance (RCV). Synchronization induced by RLRCs was observed, namely, the exchange of calcium ions between non-adjacent cells can promote the synchronization of the cells. Moreover, it was found that the RCV shows a clear peak when both inherent stochasticity and RLRCs are optimal, indicating the existence of CR. Since inherent stochasticity and RLRCs are two essential ingredients of cellular processes, synchronization and CR are also important for cells’ functions. The results reported in this paper are expected to be useful for understanding the dynamics of intercellular calcium signaling processes in vivo.
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.
Dynamic range of hypercubic stochastic excitable media
de Assis, Vladimir R V
2007-01-01
We study the response properties of d-dimensional hypercubic excitable networks to a stochastic stimulus. Each site, modelled either by a three-state stochastic susceptible-infected-recovered-susceptible (SIRS) system or by the probabilistic Greenberg-Hastings cellular automaton (GHCA), is continuously and independently stimulated by an external Poisson rate h. The response function (mean density of active sites rho versus h) is obtained via simulations (for d=1, 2, 3, 4) and mean field approximations at the single-site and pair levels (for all d). In any dimension, the dynamic range of the response function is maximized precisely at the nonequilibrium phase transition to self-sustained activity, in agreement with a reasoning recently proposed. Moreover, the maximum dynamic range attained at a given dimension d is a decreasing function of d.
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...
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.
A NEW STOCHASTIC OPTIMAL CONTROL STRATEGY FOR HYSTERETIC MR DAMPERS
Institute of Scientific and Technical Information of China (English)
YingZuguang; NiYiqing; KoJanming
2004-01-01
A new stochastic optimal control strategy for randomly excited quasi-integrable Hamiltonian systems using magneto-theological (MR) dampers is proposed. The dynamic behavior of an MR damper is characterized by the Bouc-Wen hysteretic model. The control force produced by the MR damper is separated into a passive part incorporated in the uncontrolled system and a semi-active part to be determined. The system combining the Bouc-Wen hysteretic force is converted into an equivalent non-hysteretic nonlinear stochastic control system. Then Ito stochastic differential equations are derived from the equivalent system by using the stochastic averaging method. A dynamical programming equation for the controlled diffusion processes is established based on the stochastic dynamical programming principle. The non-clipping nonlinear optimal control law is obtained for a certain performance index by minimizing the dynamical programming equation. Finally, an example is given to illustrate the application and effectiveness of the proposed control strategy.
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
Pierret, Frédéric
2016-02-01
We derived the equations of Celestial Mechanics governing the variation of the orbital elements under a stochastic perturbation, thereby generalizing the classical Gauss equations. Explicit formulas are given for the semimajor axis, the eccentricity, the inclination, the longitude of the ascending node, the pericenter angle, and the mean anomaly, which are expressed in term of the angular momentum vector H per unit of mass and the energy E per unit of mass. Together, these formulas are called the stochastic Gauss equations, and they are illustrated numerically on an example from satellite dynamics.
Stochastic 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 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 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 entrainment of a stochastic oscillator.
Wang, Guanyu; Peskin, Charles S
2015-01-01
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.
Stochastic integrals: a combinatorial approach
Rota, Gian-Carlo; Wallstrom, Timothy C.
1997-01-01
A combinatorial definition of multiple stochastic integrals is given in the setting of random measures. It is shown that some properties of such stochastic integrals, formerly known to hold in special cases, are instances of combinatorial identities on the lattice of partitions of a set. The notion of stochastic sequences of binomial type is introduced as a generalization of special polynomial sequences occuring in stochastic integration, such as Hermite, Poisson–Charlier an...
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...
D.F. Schrager
2006-01-01
We propose a new model for stochastic mortality. The model is based on the literature on affine term structure models. It satisfies three important requirements for application in practice: analytical tractibility, clear interpretation of the factors and compatibility with financial option pricing m
Energy Technology Data Exchange (ETDEWEB)
Tollestrup, A.V.; Dugan, G
1983-12-01
Major headings in this review include: proton sources; antiproton production; antiproton sources and Liouville, the role of the Debuncher; transverse stochastic cooling, time domain; the accumulator; frequency domain; pickups and kickers; Fokker-Planck equation; calculation of constants in the Fokker-Planck equation; and beam feedback. (GHT)
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.
Heterogeneous ice nucleation: bridging stochastic and singular freezing behavior
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D. Niedermeier
2011-01-01
Full Text Available Heterogeneous ice nucleation, a primary pathway for ice formation in the atmosphere, has been described alternately as being stochastic, in direct analogy with homogeneous nucleation, or singular, with ice nuclei initiating freezing at deterministic temperatures. We present an idealized model that bridges these stochastic and singular descriptions of heterogeneous ice nucleation. This "soccer ball" model treats statistically similar particles as being covered with surface sites (patches of finite area characterized by different nucleation barriers, but with each surface site following the stochastic nature of ice embryo formation. The model provides a phenomenological explanation for seemingly contradictory experimental results obtained in our research groups. We suggest that ice nucleation is fundamentally a stochastic process but that for realistic atmospheric particle populations this process can be masked by the heterogeneity of surface properties. Full evaluation of the model will require experiments with well characterized ice nucleating particles and the ability to vary both temperature and waiting time for freezing.
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.
Pricing Parisian Option under a Stochastic Volatility Model
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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.
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...
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...
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...
Stochastic synchronization of genetic oscillator networks
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Chen Luonan
2007-01-01
Full Text Available Abstract Background The study of synchronization among genetic oscillators is essential for the understanding of the rhythmic phenomena of living organisms at both molecular and cellular levels. Genetic networks are intrinsically noisy due to natural random intra- and inter-cellular fluctuations. Therefore, it is important to study the effects of noise perturbation on the synchronous dynamics of genetic oscillators. From the synthetic biology viewpoint, it is also important to implement biological systems that minimizing the negative influence of the perturbations. Results In this paper, based on systems biology approach, we provide a general theoretical result on the synchronization of genetic oscillators with stochastic perturbations. By exploiting the specific properties of many genetic oscillator models, we provide an easy-verified sufficient condition for the stochastic synchronization of coupled genetic oscillators, based on the Lur'e system approach in control theory. A design principle for minimizing the influence of noise is also presented. To demonstrate the effectiveness of our theoretical results, a population of coupled repressillators is adopted as a numerical example. Conclusion In summary, we present an efficient theoretical method for analyzing the synchronization of genetic oscillator networks, which is helpful for understanding and testing the synchronization phenomena in biological organisms. Besides, the results are actually applicable to general oscillator networks.
Hoze, N; Holcman, D
2015-11-01
Recovering a stochastic process from noisy ensembles of single-particle trajectories is resolved here using the coarse-grained Langevin equation as a model. The massive redundancy contained in single-particle tracking data allows recovering local parameters of the underlying physical model. We use several parametric and nonparametric estimators to compute the first and second moments of the process, to recover the local drift, its derivative, and the diffusion tensor, and to deconvolve the instrumental from the physical noise. We use numerical simulations to also explore the range of validity for these estimators. The present analysis allows defining what can exactly be recovered from statistics of super-resolution microscopy trajectories used for characterizing molecular trafficking underlying cellular functions.
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.
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...
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
Stochastic ice stream dynamics
Mantelli, Elisa; Bertagni, Matteo Bernard; Ridolfi, Luca
2016-08-01
Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution.
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 modelling of turbulence
DEFF Research Database (Denmark)
Sørensen, Emil Hedevang Lohse
This thesis addresses stochastic modelling of turbulence with applications to wind energy in mind. The primary tool is ambit processes, a recently developed class of computationally tractable stochastic processes based on integration with respect to Lévy bases. The subject of ambit processes...... turbine operates in the turbulent atmospheric boundary layer. In this respect, three regimes are of particular interest: modelling the turbulent wind before it interacts with the wind turbine (e.g. to be used in load simulations), modelling of the interaction of the wind with the wind turbine (e.......g. to extract information about a wind turbine's production of power), and modelling the wake generated by the wind turbine so that its influence on other wind turbines further downstream in turn can be modelled (e.g. to be used in load simulations). The thesis makes the contributions listed below. A spatial...
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 porous media equations
Barbu, Viorel; Röckner, Michael
2016-01-01
Focusing on stochastic porous media equations, this book places an emphasis on existence theorems, asymptotic behavior and ergodic properties of the associated transition semigroup. Stochastic perturbations of the porous media equation have reviously been considered by physicists, but rigorous mathematical existence results have only recently been found. The porous media equation models a number of different physical phenomena, including the flow of an ideal gas and the diffusion of a compressible fluid through porous media, and also thermal propagation in plasma and plasma radiation. Another important application is to a model of the standard self-organized criticality process, called the "sand-pile model" or the "Bak-Tang-Wiesenfeld model". The book will be of interest to PhD students and researchers in mathematics, physics and biology.
Stochastic 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.
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...
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.
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.
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 of defense...
Capturing the stochastic mechanical behavior of micro and nanopillars
Energy Technology Data Exchange (ETDEWEB)
Konstantinidis, Avraam A. [Lab of Mechanics and Materials, Aristotle University of Thessaloniki, Thessaloniki 54124 (Greece); Aifantis, Katerina E., E-mail: aifantis@email.arizona.edu [Lab of Mechanics and Materials, Aristotle University of Thessaloniki, Thessaloniki 54124 (Greece); Civil Engineering, University of Arizona, Tucson, AZ 85721 (United States); De Hosson, Jeff Th.M. [Applied Physics, University of Groningen, Groningen 9747AG (Netherlands)
2014-03-01
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.
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.
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
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.
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.
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...
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...
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
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.
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.
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...
Environment Aware Cellular Networks
Ghazzai, Hakim
2015-02-01
The unprecedented rise of mobile user demand over the years have led to an enormous growth of the energy consumption of wireless networks as well as the greenhouse gas emissions which are estimated currently to be around 70 million tons per year. This significant growth of energy consumption impels network companies to pay huge bills which represent around half of their operating expenditures. Therefore, many service providers, including mobile operators, are looking for new and modern green solutions to help reduce their expenses as well as the level of their CO2 emissions. Base stations are the most power greedy element in cellular networks: they drain around 80% of the total network energy consumption even during low traffic periods. Thus, there is a growing need to develop more energy-efficient techniques to enhance the green performance of future 4G/5G cellular networks. Due to the problem of traffic load fluctuations in cellular networks during different periods of the day and between different areas (shopping or business districts and residential areas), the base station sleeping strategy has been one of the main popular research topics in green communications. In this presentation, we present several practical green techniques that provide significant gains for mobile operators. Indeed, combined with the base station sleeping strategy, these techniques achieve not only a minimization of the fossil fuel consumption but also an enhancement of mobile operator profits. We start with an optimized cell planning method that considers varying spatial and temporal user densities. We then use the optimal transport theory in order to define the cell boundaries such that the network total transmit power is reduced. Afterwards, we exploit the features of the modern electrical grid, the smart grid, as a new tool of power management for cellular networks and we optimize the energy procurement from multiple energy retailers characterized by different prices and pollutant
Stochastic 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 quadratic costs. We will start with the basic minimal variance problem and then move on to more complex and applicable strategies such as GMV, GPC and LQG control. These methods can be regarded as extension to the basic minimal variance strategy and have all a close relation to prediction. Consequently...... a section on that topic can be found in appendix....
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 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.
The stochastic quality calculus
DEFF Research Database (Denmark)
Zeng, Kebin; Nielson, Flemming; Nielson, Hanne Riis
2014-01-01
We introduce the Stochastic Quality Calculus in order to model and reason about distributed processes that rely on each other in order to achieve their overall behaviour. The calculus supports broadcast communication in a truly concurrent setting. Generally distributed delays are associated...... with the outputs and at the same time the inputs impose constraints on the waiting times. Consequently, the expected inputs may not be available when needed and therefore the calculus allows to express the absence of data.The communication delays are expressed by general distributions and the resulting semantics...
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...
Cellular: Toward personal communications
Heffernan, Stuart
1991-09-01
The cellular industry is one of the fastest growing segment of the telecommunications industry. With an estimated penetration rate of 20 percent in the near future, cellular is becoming an ubiquitous telecommunications service in the U.S. In this paper we will examine the major advancements in the cellular industry: customer equipment, cellular networks, engineering tools, customer support, and nationwide seamless service.
AA, stochastic precooling pickup
1980-01-01
The freshly injected antiprotons were subjected to fast stochastic "precooling". In this picture of a precooling pickup, the injection orbit is to the left, the stack orbit to the far right. After several seconds of precooling with the system's kickers (in momentum and in the vertical plane), the precooled antiprotons were transferred, by means of RF, to the stack tail, where they were subjected to further stochastic cooling in momentum and in both transverse planes, until they ended up, deeply cooled, in the stack core. During precooling, a shutter near the central orbit shielded the pickups from the signals emanating from the stack-core, whilst the stack-core was shielded from the violent action of the precooling kickers by a shutter on these. All shutters were opened briefly during transfer of the precooled antiprotons to the stack tail. Here, the shutter is not yet mounted. Precooling pickups and kickers had the same design, except that the kickers had cooling circuits and the pickups had none. Peering th...
Stochastic Blind Motion Deblurring
Xiao, Lei
2015-05-13
Blind motion deblurring from a single image is a highly under-constrained problem with many degenerate solutions. A good approximation of the intrinsic image can therefore only be obtained with the help of prior information in the form of (often non-convex) regularization terms for both the intrinsic image and the kernel. While the best choice of image priors is still a topic of ongoing investigation, this research is made more complicated by the fact that historically each new prior requires the development of a custom optimization method. In this paper, we develop a stochastic optimization method for blind deconvolution. Since this stochastic solver does not require the explicit computation of the gradient of the objective function and uses only efficient local evaluation of the objective, new priors can be implemented and tested very quickly. We demonstrate that this framework, in combination with different image priors produces results with PSNR values that match or exceed the results obtained by much more complex state-of-the-art blind motion deblurring algorithms.
Stochastic ferromagnetism analysis and numerics
Brzezniak, Zdzislaw; Neklyudov, Mikhail; Prohl, Andreas
2013-01-01
This monograph examines magnetization dynamics at elevated temperatures which can be described by the stochastic Landau-Lifshitz-Gilbert equation (SLLG). Comparative computational studies with the stochastic model are included. Constructive tools such as e.g. finite element methods are used to derive the theoretical results, which are then used for computational studies.
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.
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
Inferring single-cell gene expression mechanisms using stochastic simulation
Daigle, Bernie J.; Soltani, Mohammad; Petzold, Linda R.; Singh, Abhyudai
2015-01-01
Motivation: Stochastic promoter switching between transcriptionally active (ON) and inactive (OFF) states is a major source of noise in gene expression. It is often implicitly assumed that transitions between promoter states are memoryless, i.e. promoters spend an exponentially distributed time interval in each of the two states. However, increasing evidence suggests that promoter ON/OFF times can be non-exponential, hinting at more complex transcriptional regulatory architectures. Given the essential role of gene expression in all cellular functions, efficient computational techniques for characterizing promoter architectures are critically needed. Results: We have developed a novel model reduction for promoters with arbitrary numbers of ON and OFF states, allowing us to approximate complex promoter switching behavior with Weibull-distributed ON/OFF times. Using this model reduction, we created bursty Monte Carlo expectation-maximization with modified cross-entropy method (‘bursty MCEM2’), an efficient parameter estimation and model selection technique for inferring the number and configuration of promoter states from single-cell gene expression data. Application of bursty MCEM2 to data from the endogenous mouse glutaminase promoter reveals nearly deterministic promoter OFF times, consistent with a multi-step activation mechanism consisting of 10 or more inactive states. Our novel approach to modeling promoter fluctuations together with bursty MCEM2 provides powerful tools for characterizing transcriptional bursting across genes under different environmental conditions. Availability and implementation: R source code implementing bursty MCEM2 is available upon request. Contact: absingh@udel.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25573914
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.
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.
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
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
Densities and entropies in cellular automata
Guillon, Pierre
2012-01-01
Following work by Hochman and Meyerovitch on multidimensional SFT, we give computability-theoretic characterizations of the real numbers that can appear as the topological entropies of one-dimensional and two-dimensional cellular automata.
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
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...
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 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.
Dynamical critical behavior in a cellular model of superconducting vortex avalanches
Vadakkan, Tegy John
Bak, Tang, and Wiesenfeld showed that certain driven dissipative systems with many degrees of freedom organize into a critical state characterized by avalanche dynamics and power law distribution of avalanche sizes and durations. They called this phenomenon self-organized criticality and sandpile became the prototype of such dynamical systems. Universality in these systems is not yet well established. Forty years ago, de Gennes noted that the Bean state in a type-II superconductor is similar to a sandpile. Motivated by strong experimental evidences, Bassler and Paczuski (BP) proposed a 2D sandpile model to study self-organization in the dynamics of vortices in superconductors. In this dissertation, the effect of anisotropy in the vortex-vortex interaction, stochasticity in the vortex toppling rule, and the configuration of the pinning centers on the scaling properties of the avalanches in the BP model is studied. Also, universality in the cellular model of vortex dynamics is investigated.
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
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.
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.
On Local Homogeneity and Stochastically Ordered Mixed Rasch Models
Kreiner, Svend; Hansen, Mogens; Hansen, Carsten Rosenberg
2006-01-01
Mixed Rasch models add latent classes to conventional Rasch models, assuming that the Rasch model applies within each class and that relative difficulties of items are different in two or more latent classes. This article considers a family of stochastically ordered mixed Rasch models, with ordinal latent classes characterized by increasing total…
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 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.
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
Edman, R M; Linger, R J; Belikoff, E J; Li, F; Sze, S-H; Tarone, A M; Scott, M J
2015-02-01
The New World screwworm fly, Cochliomyia hominivorax, and the Australian sheep blow fly, Lucilia cuprina, are major pests of livestock. The sterile insect technique was used to eradicate C. hominivorax from North and Central America. This involved area-wide releases of male and female flies that had been sterilized by radiation. Genetic systems have been developed for making 'male-only' strains that would improve the efficiency of genetic control of insect pests. One system involves induction of female lethality in embryos through activation of a pro-apoptotic gene by the tetracycline-dependent transactivator. Sex-specific expression is achieved using an intron from the transformer gene, which we previously isolated from several calliphorids. In the present study, we report the isolation of the promoters from the C. hominivorax slam and Lucilia sericata bnk cellularization genes and show that these promoters can drive expression of a GFP reporter gene in early embryos of transgenic L. cuprina. Additionally, we report the isolation of the L. sericata pro-apoptotic hid and rpr genes, identify conserved motifs in the encoded proteins and determine the relative expression of these genes at different stages of development. We show that widespread expression of the L. sericata pro-apoptotic genes was lethal in Drosophila melanogaster. The isolated gene promoters and pro-apoptotic genes could potentially be used to build transgenic embryonic sexing strains of calliphorid livestock pests.
Lupo, Vincenzo; Pascual-Pascual, Samuel I; Sancho, Paula; Calpena, Eduardo; Gutiérrez-Molina, Manuel; Mateo-Martínez, Gonzalo; Espinós, Carmen; Arriola-Pereda, Gema
2015-10-01
Early-onset hereditary motor and sensory neuropathies are rare diseases representing a broad clinical and genetic spectrum. Without a notable familial history, the clinical diagnosis is complicated because acquired causes of peripheral neuropathy, such as inflammatory neuropathies, neuropathies with toxic causes, and nutritional deficiencies, must be considered. We examined the clinical, electrophysiological, and pathologic manifestations of a boy with an initial diagnosis of chronic inflammatory demyelinating polyneuropathy. The progression of the disease despite treatment led to a suspicion of hereditary motor and sensory neuropathy. Genetic testing revealed the presence of the MPZ p.D90E mutation in heterozygosis. To clarify the pathogenicity of this mutation and achieve a conclusive diagnosis, we investigated the MPZ p.D90E mutation through in silico and cellular approaches. This study broadens the clinical phenotype of hereditary motor and sensory neuropathy due to MPZ mutation and emphasises the difficulty of achieving an accurate genetic diagnosis in a sporadic patient to provide an appropriate pharmacologic treatment.
Stochastic 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...
CELLULAR INTERACTIONS MEDIATED BY GLYCONECTIDS
Popescu, O.; Sumanovski, L. T.; I. Checiu; Elisabeta Popescu; G. N. Misevic
1999-01-01
Cellular interactions involve many types of cell surface molecules and operate via homophilic and/or heterophilic protein-protein and protein-carbohydrate binding. Our investigations in different model-systems (marine invertebrates and mammals) have provided direct evidence that a novel class of primordial proteoglycans, named by us gliconectins, can mediate cell adhesion via a new alternative molecular mechanism of polyvalent carbohydrate-carbohydrate binding. Biochemical characterization of...
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.
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 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.
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 roots of growth phenomena
De Lauro, E.; De Martino, S.; De Siena, S.; Giorno, V.
2014-05-01
We show that the Gompertz equation describes the evolution in time of the median of a geometric stochastic process. Therefore, we induce that the process itself generates the growth. This result allows us further to exploit a stochastic variational principle to take account of self-regulation of growth through feedback of relative density variations. The conceptually well defined framework so introduced shows its usefulness by suggesting a form of control of growth by exploiting external actions.
Stochastic 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...
Steganalysis of stochastic modulation steganography
Institute of Scientific and Technical Information of China (English)
HE Junhui; HUANG Jiwu
2006-01-01
Stochastic modulation steganography embeds secret message within the cover image by adding stego-noise with a specific probabilistic distribution. No method is known to be applicable to the estimation of stochastic modulation steganography. By analyzing the distributions of the horizontal pixel difference of images before and after stochastic modulation embedding, we present a new steganalytic approach to accurately estimate the length of secret message in stochastic modulation steganography. The proposed method first establishes a model describing the statistical relationship among the differences of the cover image, stego-image and stego-noise. In the case of stego- image-only steganalysis, rough estimate of the distributional parameters of the cover image's pixel difference is obtained with the use of the provided stego-image. And grid search and Chi-square goodness of fit test are exploited to estimate the length of the secret message embedded with stochastic modulation steganography. The experimental results demonstrate that our new approach is effective for steganalyzing stochastic modulation steganography and accurately estimating the length of the secret message.
Multi-cellular logistics of collective cell migration.
Directory of Open Access Journals (Sweden)
Masataka Yamao
Full Text Available During development, the formation of biological networks (such as organs and neuronal networks is controlled by multicellular transportation phenomena based on cell migration. In multi-cellular systems, cellular locomotion is restricted by physical interactions with other cells in a crowded space, similar to passengers pushing others out of their way on a packed train. The motion of individual cells is intrinsically stochastic and may be viewed as a type of random walk. However, this walk takes place in a noisy environment because the cell interacts with its randomly moving neighbors. Despite this randomness and complexity, development is highly orchestrated and precisely regulated, following genetic (and even epigenetic blueprints. Although individual cell migration has long been studied, the manner in which stochasticity affects multi-cellular transportation within the precisely controlled process of development remains largely unknown. To explore the general principles underlying multicellular migration, we focus on the migration of neural crest cells, which migrate collectively and form streams. We introduce a mechanical model of multi-cellular migration. Simulations based on the model show that the migration mode depends on the relative strengths of the noise from migratory and non-migratory cells. Strong noise from migratory cells and weak noise from surrounding cells causes "collective migration," whereas strong noise from non-migratory cells causes "dispersive migration." Moreover, our theoretical analyses reveal that migratory cells attract each other over long distances, even without direct mechanical contacts. This effective interaction depends on the stochasticity of the migratory and non-migratory cells. On the basis of these findings, we propose that stochastic behavior at the single-cell level works effectively and precisely to achieve collective migration in multi-cellular systems.
Wang, J F; Olson, M E; Reno, C R; Wright, J B; Hart, D A
2001-08-01
A pig model of wound healing was developed by excision of 2-cm-diameter full thickness skin in young Yorkshire pigs. The results indicated that wound re-epithelialization in this animal model took an average of 20 days. Analysis of cellular change was assessed by use of DNA quantification and determination of apoptotic cells in tissue sections. The results indicate that RNA and DNA contents paralleled each other throughout the healing process, and observed changes in the pattern of RNA and DNA content of the scar tissues were consistent with cell loss due to apoptosis in this model. Expression of mRNA for relevant genes was assessed by use of semiquantitative reverse transcription-polymerase chain reaction (RT-PCR) analysis, using porcine specific primer sets and RNA isolated from normal skin and specimens obtained at various times after wounding. The mRNA values for tumor necrosis factor-alpha (TNF-alpha), connective tissue growth factor (CTGF), insulin-like growth factor II (IGF-II), and decorin were significantly high at specific times after wounding, but mRNA values for the transcription factors (c-fos and c-jun) were significantly decreased. Quantitative bacteriologic results indicated that the total bacterial count in this animal model reached 10(9) colony-forming units (CFU)/g, with the highest value at post-wounding day 7, and Pseudomonas aeruginosa and Staphylocococci aureus were the most common bacteria detected in this model. Further definition of this model should identify unique points in the healing process, and such information could lead to development of therapeutic interventions to improve skin wound healing.
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.
Hosaka, Tadaaki; Ohira, Toru; Lucian, Christian; Milton, John
2005-03-01
Time-delayed feedback control becomes problematic in situations in which the time constant of the system is fast compared to the feedback reaction time. In particular, when perturbations are unpredictable, traditional feedback or feed-forward control schemes can be insufficient. Nonethless a human can balance a stick at their fingertip in the presence of fluctuations that occur on time scales shorter than their neural reaction times. Here we study a simple model of a repulsive delayed random walk and demonstrate that the interplay between noise and delay can transiently stabilize an unstable fixed-point. This observation leads to the concept of ``delayed stochastic control,'' i.e. stabilization of tasks, such as stick balancing at the fingertip, by optimally tuning the noise level with respect to the feedback delay time. References:(1)J.L.Cabrera and J.G.Milton, PRL 89 158702 (2002);(2) T. Ohira and J.G.Milton, PRE 52 3277 (1995);(3)T.Hosaka, T.Ohira, C.Lucian, J.L.Cabrera, and J.G.Milton, Prog. Theor. Phys. (to appear).
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...
Turbulence and Stochastic Processes
Celani, Antonio; Mazzino, Andrea; Pumir, Alain
sec:08-1In 1931 the monograph Analytical Methods in Probability Theory appeared, in which A.N. Kolmogorov laid the foundations for the modern theory of Markov processes [1]. According to Gnedenko: "In the history of probability theory it is difficult to find other works that changed the established points of view and basic trends in research work in such a decisive way". Ten years later, his article on fully developed turbulence provided the framework within which most, if not all, of the subsequent theoretical investigations have been conducted [2] (see e.g. the review by Biferale et al. in this volume [3]. Remarkably, the greatest advances made in the last few years towards a thorough understanding of turbulence developed from the successful marriage between the theory of stochastic processes and the phenomenology of turbulent transport of scalar fields. In this article we will summarize these recent developments which expose the direct link between the intermittency of transported fields and the statistical properties of particle trajectories advected by the turbulent flow (see also [4], and, for a more thorough review, [5]. We also discuss the perspectives of the Lagrangian approach beyond passive scalars, especially for the modeling of hydrodynamic turbulence.
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...
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.
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
Mechanisms of Stochastic Diffusion of Energetic Ions in Spherical Tori
Energy Technology Data Exchange (ETDEWEB)
Ya.I. Kolesnichenko; R.B. White; Yu.V. Yakovenko
2001-01-18
Stochastic diffusion of the energetic ions in spherical tori is considered. The following issues are addressed: (I) Goldston-White-Boozer diffusion in a rippled field; (ii) cyclotron-resonance-induced diffusion caused by the ripple; (iii) effects of non-conservation of the magnetic moment in an axisymmetric field. It is found that the stochastic diffusion in spherical tori with a weak magnetic field has a number of peculiarities in comparison with conventional tokamaks; in particular, it is characterized by an increased role of mechanisms associated with non-conservation of the particle magnetic moment. It is concluded that in current experiments on National Spherical Torus eXperiment (NSTX) the stochastic diffusion does not have a considerable influence on the confinement of energetic ions.
On the combined gradient-stochastic plasticity model: Application to Mo-micropillar compression
Energy Technology Data Exchange (ETDEWEB)
Konstantinidis, A. A., E-mail: akonsta@civil.auth.gr [Aristotle University of Thessaloniki, Thessaloniki 54124 (Greece); Zhang, X., E-mail: zhangxu26@126.com [Southwest Jiaotong University, Chengdu 610031 (Greece); Aifantis, E. C., E-mail: mom@mom.gen.auth.gr [Aristotle University of Thessaloniki, Thessaloniki 54124 (Greece); Michigan Technological University, Houghton, MI 49931 (United States); ITMO University, St. Petersburg 197101 (Russian Federation)
2015-02-17
A formulation for addressing heterogeneous material deformation is proposed. It is based on the use of a stochasticity-enhanced gradient plasticity model implemented through a cellular automaton. The specific application is on Mo-micropillar compression, for which the irregularities of the strain bursts observed have been experimentally measured and theoretically interpreted through Tsallis' q-statistics.
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.
Automatic identification of model reductions for discrete stochastic simulation
Wu, Sheng; Fu, Jin; Li, Hong; Petzold, Linda
2012-07-01
Multiple time scales in cellular chemical reaction systems present a challenge for the efficiency of stochastic simulation. Numerous model reductions have been proposed to accelerate the simulation of chemically reacting systems by exploiting time scale separation. However, these are often identified and deployed manually, requiring expert knowledge. This is time-consuming, prone to error, and opportunities for model reduction may be missed, particularly for large models. We propose an automatic model analysis algorithm using an adaptively weighted Petri net to dynamically identify opportunities for model reductions for both the stochastic simulation algorithm and tau-leaping simulation, with no requirement of expert knowledge input. Results are presented to demonstrate the utility and effectiveness of this approach.
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.
Stochastic models: theory and simulation.
Energy Technology Data Exchange (ETDEWEB)
Field, Richard V., Jr.
2008-03-01
Many problems in applied science and engineering involve physical phenomena that behave randomly in time and/or space. Examples are diverse and include turbulent flow over an aircraft wing, Earth climatology, material microstructure, and the financial markets. Mathematical models for these random phenomena are referred to as stochastic processes and/or random fields, and Monte Carlo simulation is the only general-purpose tool for solving problems of this type. The use of Monte Carlo simulation requires methods and algorithms to generate samples of the appropriate stochastic model; these samples then become inputs and/or boundary conditions to established deterministic simulation codes. While numerous algorithms and tools currently exist to generate samples of simple random variables and vectors, no cohesive simulation tool yet exists for generating samples of stochastic processes and/or random fields. There are two objectives of this report. First, we provide some theoretical background on stochastic processes and random fields that can be used to model phenomena that are random in space and/or time. Second, we provide simple algorithms that can be used to generate independent samples of general stochastic models. The theory and simulation of random variables and vectors is also reviewed for completeness.
Stochastic 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
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...
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.
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.
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.
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 models of cell motility
DEFF Research Database (Denmark)
Gradinaru, Cristian
2012-01-01
Cell motility and migration are central to the development and maintenance of multicellular organisms, and errors during this process can lead to major diseases. Consequently, the mechanisms and phenomenology of cell motility are currently under intense study. In recent years, a new...... interdisciplinary field focusing on the study of biological processes at the nanoscale level, with a range of technological applications in medicine and biological research, has emerged. The work presented in this thesis is at the interface of cell biology, image processing, and stochastic modeling. The stochastic...... models introduced here are based on persistent random motion, which I apply to real-life studies of cell motility on flat and nanostructured surfaces. These models aim to predict the time-dependent position of cell centroids in a stochastic manner, and conversely determine directly from experimental...
Verification of Stochastic Process Calculi
DEFF Research Database (Denmark)
Skrypnyuk, Nataliya
process calculi. The description of a system in the syntax of a particular stochastic process calculus can be analysed in a compositional way, without expanding the state space by explicitly resolving all the interdependencies between the subsystems which may lead to the state space explosion problem....... In support of this claim we have developed analysis methods that belong to a particular type of Static Analysis { Data Flow / Pathway Analysis. These methods have previously been applied to a number of non-stochastic process calculi. In this thesis we are lifting them to the stochastic calculus...... description of a system. The presented methods have a clear application in the areas of embedded systems, (randomised) protocols run between a fixed number of parties etc....
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.
Gene regulation and noise reduction by coupling of stochastic processes
Ramos, Alexandre F.; Hornos, José Eduardo M.; Reinitz, John
2015-02-01
Here we characterize the low-noise regime of a stochastic model for a negative self-regulating binary gene. The model has two stochastic variables, the protein number and the state of the gene. Each state of the gene behaves as a protein source governed by a Poisson process. The coupling between the two gene states depends on protein number. This fact has a very important implication: There exist protein production regimes characterized by sub-Poissonian noise because of negative covariance between the two stochastic variables of the model. Hence the protein numbers obey a probability distribution that has a peak that is sharper than those of the two coupled Poisson processes that are combined to produce it. Biochemically, the noise reduction in protein number occurs when the switching of the genetic state is more rapid than protein synthesis or degradation. We consider the chemical reaction rates necessary for Poisson and sub-Poisson processes in prokaryotes and eucaryotes. Our results suggest that the coupling of multiple stochastic processes in a negative covariance regime might be a widespread mechanism for noise reduction.
Stochastic geometry for image analysis
Descombes, Xavier
2013-01-01
This book develops the stochastic geometry framework for image analysis purpose. Two main frameworks are described: marked point process and random closed sets models. We derive the main issues for defining an appropriate model. The algorithms for sampling and optimizing the models as well as for estimating parameters are reviewed. Numerous applications, covering remote sensing images, biological and medical imaging, are detailed. This book provides all the necessary tools for developing an image analysis application based on modern stochastic modeling.
Stochastic geometry and its applications
Chiu, Sung Nok; Kendall, Wilfrid S; Mecke, Joseph
2013-01-01
An extensive update to a classic text Stochastic geometry and spatial statistics play a fundamental role in many modern branches of physics, materials sciences, engineering, biology and environmental sciences. They offer successful models for the description of random two- and three-dimensional micro and macro structures and statistical methods for their analysis. The previous edition of this book has served as the key reference in its field for over 18 years and is regarded as the best treatment of the subject of stochastic geometry, both as a subject with vital a
Schwinger Mechanism with Stochastic Quantization
Fukushima, Kenji
2014-01-01
We prescribe a formulation of the particle production with real-time Stochastic Quantization. To construct the retarded and the time-ordered propagators we decompose the stochastic variables into positive- and negative-energy parts. In this way we demonstrate how to derive the Schwinger mechanism under a time-dependent electric field. We also discuss a physical interpretation with help of numerical simulations and develop an analogue to the one-dimensional scattering with the non-relativistic Schroedinger equation. We can then reformulate the Schwinger mechanism as the high-energy quantum reflection problem rather than tunneling.
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 methods in quantum mechanics
Gudder, Stanley P
2005-01-01
Practical developments in such fields as optical coherence, communication engineering, and laser technology have developed from the applications of stochastic methods. This introductory survey offers a broad view of some of the most useful stochastic methods and techniques in quantum physics, functional analysis, probability theory, communications, and electrical engineering. Starting with a history of quantum mechanics, it examines both the quantum logic approach and the operational approach, with explorations of random fields and quantum field theory.The text assumes a basic knowledge of fun
QB1 - Stochastic Gene Regulation
Energy Technology Data Exchange (ETDEWEB)
Munsky, Brian [Los Alamos National Laboratory
2012-07-23
Summaries of this presentation are: (1) Stochastic fluctuations or 'noise' is present in the cell - Random motion and competition between reactants, Low copy, quantization of reactants, Upstream processes; (2) Fluctuations may be very important - Cell-to-cell variability, Cell fate decisions (switches), Signal amplification or damping, stochastic resonances; and (3) Some tools are available to mode these - Kinetic Monte Carlo simulations (SSA and variants), Moment approximation methods, Finite State Projection. We will see how modeling these reactions can tell us more about the underlying processes of gene regulation.
Stochastic epidemic models: a survey
Britton, Tom
2009-01-01
This paper is a survey paper on stochastic epidemic models. A simple stochastic epidemic model is defined and exact and asymptotic model properties (relying on a large community) are presented. The purpose of modelling is illustrated by studying effects of vaccination and also in terms of inference procedures for important parameters, such as the basic reproduction number and the critical vaccination coverage. Several generalizations towards realism, e.g. multitype and household epidemic models, are also presented, as is a model for endemic diseases.
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
Stochastic and infinite dimensional analysis
Carpio-Bernido, Maria; Grothaus, Martin; Kuna, Tobias; Oliveira, Maria; Silva, José
2016-01-01
This volume presents a collection of papers covering applications from a wide range of systems with infinitely many degrees of freedom studied using techniques from stochastic and infinite dimensional analysis, e.g. Feynman path integrals, the statistical mechanics of polymer chains, complex networks, and quantum field theory. Systems of infinitely many degrees of freedom create their particular mathematical challenges which have been addressed by different mathematical theories, namely in the theories of stochastic processes, Malliavin calculus, and especially white noise analysis. These proceedings are inspired by a conference held on the occasion of Prof. Ludwig Streit’s 75th birthday and celebrate his pioneering and ongoing work in these fields.
Stochastic 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.
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
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.
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.
Stochastic Model Checking of the Stochastic Quality Calculus
DEFF Research Database (Denmark)
Nielson, Flemming; Nielson, Hanne Riis; Zeng, Kebin
2015-01-01
The Quality Calculus uses quality binders for input to express strategies for continuing the computation even when the desired input has not been received. The Stochastic Quality Calculus adds generally distributed delays for output actions and real-time constraints on the quality binders for input...
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.
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.
Exact Algorithms for Solving Stochastic Games
DEFF Research Database (Denmark)
Hansen, Kristoffer Arnsfelt; Koucky, Michal; Lauritzen, Niels;
2012-01-01
Shapley's discounted stochastic games, Everett's recursive games and Gillette's undiscounted stochastic games are classical models of game theory describing two-player zero-sum games of potentially infinite duration. We describe algorithms for exactly solving these games.......Shapley's discounted stochastic games, Everett's recursive games and Gillette's undiscounted stochastic games are classical models of game theory describing two-player zero-sum games of potentially infinite duration. We describe algorithms for exactly solving these games....
Stochastic modeling and analysis of telecoms networks
Decreusefond, Laurent
2012-01-01
This book addresses the stochastic modeling of telecommunication networks, introducing the main mathematical tools for that purpose, such as Markov processes, real and spatial point processes and stochastic recursions, and presenting a wide list of results on stability, performances and comparison of systems.The authors propose a comprehensive mathematical construction of the foundations of stochastic network theory: Markov chains, continuous time Markov chains are extensively studied using an original martingale-based approach. A complete presentation of stochastic recursions from an
Transport in a stochastic magnetic field
Energy Technology Data Exchange (ETDEWEB)
White, R.B.; Wu, Yanlin [Princeton Univ., NJ (United States). Plasma Physics Lab.; Rax, J.M. [Association Euratom-CEA, Centre d`Etudes Nucleaires de Cadarache, 13 -Saint-Paul-lez-Durance (France). Dept. de Recherches sur la Fusion Controlee
1992-09-01
Collisional heat transport in a stochastic magnetic field configuration is investigated. Well above stochastic threshold, a numerical solution of a Chirikov-Taylor model shows a short-time nonlocal regime, but at large time the Rechester-Rosenbluth effective diffusion is confirmed. Near stochastic threshold, subdiffusive behavior is observed for short mean free paths. The nature of this subdiffusive behavior is understood in terms of the spectrum of islands in the stochastic sea.
Transport in a stochastic magnetic field
Energy Technology Data Exchange (ETDEWEB)
White, R.B.; Wu, Yanlin (Princeton Univ., NJ (United States). Plasma Physics Lab.); Rax, J.M. (Association Euratom-CEA, Centre d' Etudes Nucleaires de Cadarache, 13 -Saint-Paul-lez-Durance (France). Dept. de Recherches sur la Fusion Controlee)
1992-01-01
Collisional heat transport in a stochastic magnetic field configuration is investigated. Well above stochastic threshold, a numerical solution of a Chirikov-Taylor model shows a short-time nonlocal regime, but at large time the Rechester-Rosenbluth effective diffusion is confirmed. Near stochastic threshold, subdiffusive behavior is observed for short mean free paths. The nature of this subdiffusive behavior is understood in terms of the spectrum of islands in the stochastic sea.
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...
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.
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.
Stochastic Programming with Simple Integer Recourse
Louveaux, François V.; van der Vlerk, Maarten H.
1993-01-01
Stochastic integer programs are notoriously difficult. Very few properties are known and solution algorithms are very scarce. In this paper, we introduce the class of stochastic programs with simple integer recourse, a natural extension of the simple recourse case extensively studied in stochastic c
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
Model checking mobile stochastic logic.
De Nicola, Rocco; Katoen, Joost-Pieter; Latella, Diego; Loreti, Michele; Massink, Mieke
2007-01-01
The Temporal Mobile Stochastic Logic (MOSL) has been introduced in previous work by the authors for formulating properties of systems specified in STOKLAIM, a Markovian extension of KLAIM. The main purpose of MOSL is to address key functional aspects of global computing such as distribution awarenes
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.
2009-01-01
Turbulence of the incoming wind field is of paramount importance to the dynamic response of civil engineering structures. Hence reliable stochastic models of the turbulence should be available from which time series can be generated for dynamic response and structural safety analysis. In the pape...
Stochastic Modelling of Hydrologic Systems
DEFF Research Database (Denmark)
Jonsdottir, Harpa
2007-01-01
In this PhD project several stochastic modelling methods are studied and applied on various subjects in hydrology. The research was prepared at Informatics and Mathematical Modelling at the Technical University of Denmark. The thesis is divided into two parts. The first part contains an introduct......In this PhD project several stochastic modelling methods are studied and applied on various subjects in hydrology. The research was prepared at Informatics and Mathematical Modelling at the Technical University of Denmark. The thesis is divided into two parts. The first part contains...... an introduction and an overview of the papers published. Then an introduction to basic concepts in hydrology along with a description of hydrological data is given. Finally an introduction to stochastic modelling is given. The second part contains the research papers. In the research papers the stochastic methods...... 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 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....
Stochastic-field cavitation model
Energy Technology Data Exchange (ETDEWEB)
Dumond, J., E-mail: julien.dumond@areva.com [AREVA Nuclear Professional School, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, D-76344 Eggenstein-Leopoldshafen (Germany); AREVA GmbH, Erlangen, Paul-Gossen-Strasse 100, D-91052 Erlangen (Germany); Magagnato, F. [Institute of Fluid Mechanics, Karlsruhe Institute of Technology, Kaiserstrasse 12, D-76131 Karlsruhe (Germany); Class, A. [AREVA Nuclear Professional School, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, D-76344 Eggenstein-Leopoldshafen (Germany); Institute for Nuclear and Energy Technologies, Karlsruhe Institute of Technology, Hermann-von-Helmholtz-Platz 1, D-76344 Eggenstein-Leopoldshafen (Germany)
2013-07-15
Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian “particles” or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations.
Stochastic-field cavitation model
Dumond, J.; Magagnato, F.; Class, A.
2013-07-01
Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian "particles" or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations.
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.
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...
Heterogeneous ice nucleation: exploring the transition from stochastic to singular freezing behavior
Directory of Open Access Journals (Sweden)
D. Niedermeier
2011-08-01
Full Text Available Heterogeneous ice nucleation, a primary pathway for ice formation in the atmosphere, has been described alternately as being stochastic, in direct analogy with homogeneous nucleation, or singular, with ice nuclei initiating freezing at deterministic temperatures. We present an idealized, conceptual model to explore the transition between stochastic and singular ice nucleation. This "soccer ball" model treats particles as being covered with surface sites (patches of finite area characterized by different nucleation barriers, but with each surface site following the stochastic nature of ice embryo formation. The model provides a phenomenological explanation for seemingly contradictory experimental results obtained in our research groups. Even with ice nucleation treated fundamentally as a stochastic process this process can be masked by the heterogeneity of surface properties, as might be typical for realistic atmospheric particle populations. Full evaluation of the model findings will require experiments with well characterized ice nucleating particles and the ability to vary both temperature and waiting time for freezing.
Stochastic resonance for nonlinear sensors with saturation
Rousseau, David; Rojas Varela, Julio; Chapeau-Blondeau, François
2003-02-01
We analyze the transmission of a noisy signal by sensor devices which are linear for small inputs and saturate at large inputs. Large information-carrying signals are thus distorted in their transmission. We demonstrate conditions where addition of noise to such large input signals can reduce the distortion that they undergo in the transmission. This is established for periodic, as well as aperiodic, and random information-carrying signals. Various measures characterizing the transmission, such as signal-to-noise ratio, input-output cross correlation, and mutual information, are shown improvable by addition of noise. These results constitute another instance of the nonlinear phenomenon of stochastic resonance where addition of noise enhances the signal.
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.
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
Stochastic averaging of quasi-Hamiltonian systems
Institute of Scientific and Technical Information of China (English)
朱位秋
1996-01-01
A stochastic averaging method is proposed for quasi-Hamiltonian systems (Hamiltonian systems with light dampings subject to weakly stochastic excitations). Various versions of the method, depending on whether the associated Hamiltonian systems are integrable or nonintegrable, resonant or nonresonant, are discussed. It is pointed out that the standard stochastic averaging method and the stochastic averaging method of energy envelope are special cases of the stochastic averaging method of quasi-Hamiltonian systems and that the results obtained by this method for several examples prove its effectiveness.
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.
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...
ATLAS: A geometric approach to learning high-dimensional stochastic systems near manifolds
Crosskey, Miles; Maggioni, Mauro
2014-01-01
When simulating multiscale stochastic differential equations (SDEs) in high-dimensions, separation of timescales, stochastic noise and high-dimensionality can make simulations prohibitively expensive. The computational cost is dictated by microscale properties and interactions of many variables, while the behavior of interest often occurs at the macroscale level and at large time scales, often characterized by few important, but unknown, degrees of freedom. For many problems bridging the gap ...
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)
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...
A stochastic differential equation framework for the turbulent velocity field
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole Eiler; Schmiegel, Jürgen
We discuss a stochastic differential equation, as a modelling framework for the turbulent velocity field, that is capable of capturing basic stylized facts of the statistics of velocity increments. In particular, we focus on the evolution of the probability density of velocity increments characte...... characterized by a normal inverse Gaussian shape with heavy tails for small scales and aggregational Gaussianity for large scales. In addition, we show that the proposed model is in accordance with Kolmogorov's refined similarity hypotheses....
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...
Stochastic Dynamics in Quenched-in Disorder and Hysteresis
Bertotti, Giorgio; Basso, Vittorio; Magni, Alessandro
1998-01-01
The conditions under which relaxation dynamics in the presence of quenched-in disorder lead to rate-independent hysteresis are discussed. The calculation of average hysteresis branches is reduced to the solution of the level-crossing problem for the stochastic field describing quenched-in disorder. Closed analytical solutions are derived for the case where the disorder is characterized by Wiener-Levy statistics. This case is shown to be equivalent to the Preisach model and the associated Prei...
Deterministic and Stochastic Study of Wind Farm Harmonic Currents
DEFF Research Database (Denmark)
Sainz, Luis; Mesas, Juan Jose; Teodorescu, Remus;
2010-01-01
Wind farm harmonic emissions are a well-known power quality problem, but little data based on actual wind farm measurements are available in literature. In this paper, harmonic emissions of an 18 MW wind farm are investigated using extensive measurements, and the deterministic and stochastic...... characterization of wind farm harmonic currents is analyzed. Specific issues addressed in the paper include the harmonic variation with the wind farm operating point and the random characteristics of their magnitude and phase angle....
Stochastic 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...
Nanostructured cellular networks.
Moriarty, P; Taylor, M D R; Brust, M
2002-12-01
Au nanocrystals spin-coated onto silicon from toluene form cellular networks. A quantitative statistical crystallography analysis shows that intercellular correlations drive the networks far from statistical equilibrium. Spin-coating from hexane does not produce cellular structure, yet a strong correlation is retained in the positions of nanocrystal aggregates. Mechanisms based on Marangoni convection alone cannot account for the variety of patterns observed, and we argue that spinodal decomposition plays an important role in foam formation.
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...
Ruin problems with stochastic premium stochastic return on investments
Institute of Scientific and Technical Information of China (English)
WANG Rongming; XU Lin; YAO Dingjun
2007-01-01
In this paper, ruin problems in the risk model with stochastic premium incomes and stochastic return on investments are studied. The logarithm of the asset price process is assumed to be a Lévy process. An exact expression for expected discounted penalty function is established. Lower bounds and two kinds of upper bounds for expected discounted penalty function are obtained by inductive method and martingale approach. Integro- differential equations for the expected discounted penalty function are ob- tained when the Lévy process is a Brownian motion with positive drift and a compound Poisson process, respectively. Some analytical examples and numerical examples are given to illustrate the upper bounds and the applications of the integro-differential equations in this paper.
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
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
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 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 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 coalescence in logarithmic time
Loh, Po-Shen
2011-01-01
The following distributed coalescence protocol was introduced by Dahlia Malkhi in 2006 motivated by applications in social networking. Initially there are n agents wishing to coalesce into one cluster via a decentralized stochastic process, where each round is as follows: Every cluster flips a fair coin to dictate whether it is to issue or accept requests in this round. Issuing a request amounts to contacting a cluster randomly chosen proportionally to its size. A cluster accepting requests is to select an incoming one uniformly (if there are such) and merge with that cluster. Empirical results by Fernandess and Malkhi suggested the protocol concludes in O(log n) rounds with high probability, whereas numerical estimates by Oded Schramm, based on an ingenious analytic approximation, suggested that the coalescence time should be super-logarithmic. Our contribution is a rigorous study of the stochastic coalescence process with two consequences. First, we confirm that the above process indeed requires super-logar...
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...
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...
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.
Stochastic Vehicle Routing with Recourse
Goertz, Inge Li; Saket, Rishi
2012-01-01
We study the classic Vehicle Routing Problem in the setting of stochastic optimization with recourse. StochVRP is a two-stage optimization problem, where demand is satisfied using two routes: fixed and recourse. The fixed route is computed using only a demand distribution. Then after observing the demand instantiations, a recourse route is computed -- but costs here become more expensive by a factor lambda. We present an O(log^2 n log(n lambda))-approximation algorithm for this stochastic routing problem, under arbitrary distributions. The main idea in this result is relating StochVRP to a special case of submodular orienteering, called knapsack rank-function orienteering. We also give a better approximation ratio for knapsack rank-function orienteering than what follows from prior work. Finally, we provide a Unique Games Conjecture based omega(1) hardness of approximation for StochVRP, even on star-like metrics on which our algorithm achieves a logarithmic approximation.
Optimal Advertising with Stochastic Demand
George E. Monahan
1983-01-01
A stochastic, sequential model is developed to determine optimal advertising expenditures as a function of product maturity and past advertising. Random demand for the product depends upon an aggregate measure of current and past advertising called "goodwill," and the position of the product in its life cycle measured by sales-to-date. Conditions on the parameters of the model are established that insure that it is optimal to advertise less as the product matures. Additional characteristics o...
Stochastic modelling of animal movement
Smouse, Peter E.; Focardi, Stefano; Moorcroft, Paul R.; Kie, John G.; Forester, James D.; Morales, Juan M.
2010-01-01
Modern animal movement modelling derives from two traditions. Lagrangian models, based on random walk behaviour, are useful for multi-step trajectories of single animals. Continuous Eulerian models describe expected behaviour, averaged over stochastic realizations, and are usefully applied to ensembles of individuals. We illustrate three modern research arenas. (i) Models of home-range formation describe the process of an animal ‘settling down’, accomplished by including one or more focal poi...
Stochastic Annealing for Variational Inference
Gultekin, San; Zhang, Aonan; Paisley, John
2015-01-01
We empirically evaluate a stochastic annealing strategy for Bayesian posterior optimization with variational inference. Variational inference is a deterministic approach to approximate posterior inference in Bayesian models in which a typically non-convex objective function is locally optimized over the parameters of the approximating distribution. We investigate an annealing method for optimizing this objective with the aim of finding a better local optimal solution and compare with determin...
Stochastic processes and filtering theory
Jazwinski, Andrew H
2007-01-01
This unified treatment of linear and nonlinear filtering theory presents material previously available only in journals, and in terms accessible to engineering students. Its sole prerequisites are advanced calculus, the theory of ordinary differential equations, and matrix analysis. Although theory is emphasized, the text discusses numerous practical applications as well.Taking the state-space approach to filtering, this text models dynamical systems by finite-dimensional Markov processes, outputs of stochastic difference, and differential equations. Starting with background material on probab
Stochastic Volatility and DSGE Models
DEFF Research Database (Denmark)
Andreasen, Martin Møller
This paper argues that a specification of stochastic volatility commonly used to analyze the Great Moderation in DSGE models may not be appropriate, because the level of a process with this specification does not have conditional or unconditional moments. This is unfortunate because agents may...... as a result expect productivity and hence consumption to be inifinite in all future periods. This observation is followed by three ways to overcome the problem....
Stochastic control of traffic patterns
DEFF Research Database (Denmark)
Gaididei, Yuri B.; Gorria, Carlos; Berkemer, Rainer;
2013-01-01
A stochastic modulation of the safety distance can reduce traffic jams. It is found that the effect of random modulation on congestive flow formation depends on the spatial correlation of the noise. Jam creation is suppressed for highly correlated noise. The results demonstrate the advantage...... of heterogeneous performance of the drivers in time as well as individually. This opens the possibility for the construction of technical tools to control traffic jam formation....
Stochastic Gravity: Theory and Applications
Directory of Open Access Journals (Sweden)
Hu Bei Lok
2008-05-01
Full Text Available Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein–Langevin equation, which has, in addition, sources due to the noise kernel. The noise kernel is the vacuum expectation value of the (operator-valued stress-energy bitensor, which describes the fluctuations of quantum-matter fields in curved spacetimes. A new improved criterion for the validity of semiclassical gravity may also be formulated from the viewpoint of this theory. In the first part of this review we describe the fundamentals of this new theory via two approaches: the axiomatic and the functional. The axiomatic approach is useful to see the structure of the theory from the framework of semiclassical gravity, showing the link from the mean value of the stress-energy tensor to the correlation functions. The functional approach uses the Feynman–Vernon influence functional and the Schwinger–Keldysh closed-time-path effective action methods. In the second part, we describe three applications of stochastic gravity. First, we consider metric perturbations in a Minkowski spacetime, compute the two-point correlation functions of these perturbations and prove that Minkowski spacetime is a stable solution of semiclassical gravity. Second, we discuss structure formation from the stochastic-gravity viewpoint, which can go beyond the standard treatment by incorporating the full quantum effect of the inflaton fluctuations. Third, using the Einstein–Langevin equation, we discuss the backreaction of Hawking radiation and the behavior of metric fluctuations for both the quasi-equilibrium condition of a black-hole in a box and the fully nonequilibrium condition of an evaporating black hole spacetime. Finally, we briefly discuss the theoretical structure of stochastic gravity in relation to quantum gravity and point out
Stochastic analysis of biochemical systems
Anderson, David F
2015-01-01
This book focuses on counting processes and continuous-time Markov chains motivated by examples and applications drawn from chemical networks in systems biology. The book should serve well as a supplement for courses in probability and stochastic processes. While the material is presented in a manner most suitable for students who have studied stochastic processes up to and including martingales in continuous time, much of the necessary background material is summarized in the Appendix. Students and Researchers with a solid understanding of calculus, differential equations, and elementary probability and who are well-motivated by the applications will find this book of interest. David F. Anderson is Associate Professor in the Department of Mathematics at the University of Wisconsin and Thomas G. Kurtz is Emeritus Professor in the Departments of Mathematics and Statistics at that university. Their research is focused on probability and stochastic processes with applications in biology and other ar...
Multiple fields in stochastic inflation
Assadullahi, Hooshyar; Firouzjahi, Hassan; Noorbala, Mahdiyar; Vennin, Vincent; Wands, David
2016-06-01
Stochastic effects in multi-field inflationary scenarios are investigated. A hierarchy of diffusion equations is derived, the solutions of which yield moments of the numbers of inflationary e-folds. Solving the resulting partial differential equations in multi-dimensional field space is more challenging than the single-field case. A few tractable examples are discussed, which show that the number of fields is, in general, a critical parameter. When more than two fields are present for instance, the probability to explore arbitrarily large-field regions of the potential, otherwise inaccessible to single-field dynamics, becomes non-zero. In some configurations, this gives rise to an infinite mean number of e-folds, regardless of the initial conditions. Another difference with respect to single-field scenarios is that multi-field stochastic effects can be large even at sub-Planckian energy. This opens interesting new possibilities for probing quantum effects in inflationary dynamics, since the moments of the numbers of e-folds can be used to calculate the distribution of primordial density perturbations in the stochastic-δ N formalism.
Stochastic gravity: beyond semiclassical gravity
Energy Technology Data Exchange (ETDEWEB)
Verdaguer, E [Departament de Fisica Fonamental and CER en Astrofisica, Fisica de Particules i Cosmologia, Universitat de Barcelona, Av. Diagonal 647, 08028 Barcelona (Spain)
2007-05-15
The back-reaction of a classical gravitational field interacting with quantum matter fields is described by the semiclassical Einstein equation, which has the expectation value of the quantum matter fields stress tensor as a source. The semiclassical theory may be obtained from the quantum field theory of gravity interacting with N matter fields in the large N limit. This theory breaks down when the fields quantum fluctuations are important. Stochastic gravity goes beyond the semiclassical limit and allows for a systematic and self-consistent description of the metric fluctuations induced by these quantum fluctuations. The correlation functions of the metric fluctuations obtained in stochastic gravity reproduce the correlation functions in the quantum theory to leading order in an 1/N expansion. Two main applications of stochastic gravity are discussed. The first, in cosmology, to obtain the spectrum of primordial metric perturbations induced by the inflaton fluctuations, even beyond the linear approximation. The second, in black hole physics, to study the fluctuations of the horizon of an evaporating black hole.
Mechanical Autonomous Stochastic Heat Engine
Serra-Garcia, Marc; Foehr, André; Molerón, Miguel; Lydon, Joseph; Chong, Christopher; Daraio, Chiara
2016-07-01
Stochastic heat engines are devices that generate work from random thermal motion using a small number of highly fluctuating degrees of freedom. Proposals for such devices have existed for more than a century and include the Maxwell demon and the Feynman ratchet. Only recently have they been demonstrated experimentally, using, e.g., thermal cycles implemented in optical traps. However, recent experimental demonstrations of classical stochastic heat engines are nonautonomous, since they require an external control system that prescribes a heating and cooling cycle and consume more energy than they produce. We present a heat engine consisting of three coupled mechanical resonators (two ribbons and a cantilever) subject to a stochastic drive. The engine uses geometric nonlinearities in the resonating ribbons to autonomously convert a random excitation into a low-entropy, nonpassive oscillation of the cantilever. The engine presents the anomalous heat transport property of negative thermal conductivity, consisting in the ability to passively transfer energy from a cold reservoir to a hot reservoir.
Optically-controlled platforms for transfection and single- and sub-cellular surgery
DEFF Research Database (Denmark)
Villangca, Mark Jayson; Casey, Duncan; Glückstad, Jesper
2015-01-01
Improving the resolution of biological research to the single- or sub-cellular level is of critical importance in a wide variety of processes and disease conditions. Most obvious are those linked to aging and cancer, many of which are dependent upon stochastic processes where individual, unpredic...
AESS: Accelerated Exact Stochastic Simulation
Jenkins, David D.; Peterson, Gregory D.
2011-12-01
The Stochastic Simulation Algorithm (SSA) developed by Gillespie provides a powerful mechanism for exploring the behavior of chemical systems with small species populations or with important noise contributions. Gene circuit simulations for systems biology commonly employ the SSA method, as do ecological applications. This algorithm tends to be computationally expensive, so researchers seek an efficient implementation of SSA. In this program package, the Accelerated Exact Stochastic Simulation Algorithm (AESS) contains optimized implementations of Gillespie's SSA that improve the performance of individual simulation runs or ensembles of simulations used for sweeping parameters or to provide statistically significant results. Program summaryProgram title: AESS Catalogue identifier: AEJW_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJW_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: University of Tennessee copyright agreement No. of lines in distributed program, including test data, etc.: 10 861 No. of bytes in distributed program, including test data, etc.: 394 631 Distribution format: tar.gz Programming language: C for processors, CUDA for NVIDIA GPUs Computer: Developed and tested on various x86 computers and NVIDIA C1060 Tesla and GTX 480 Fermi GPUs. The system targets x86 workstations, optionally with multicore processors or NVIDIA GPUs as accelerators. Operating system: Tested under Ubuntu Linux OS and CentOS 5.5 Linux OS Classification: 3, 16.12 Nature of problem: Simulation of chemical systems, particularly with low species populations, can be accurately performed using Gillespie's method of stochastic simulation. Numerous variations on the original stochastic simulation algorithm have been developed, including approaches that produce results with statistics that exactly match the chemical master equation (CME) as well as other approaches that approximate the CME. Solution
Epigenetics and Cellular Metabolism
Xu, Wenyi; Wang, Fengzhong; Yu, Zhongsheng; Xin, Fengjiao
2016-01-01
Living eukaryotic systems evolve delicate cellular mechanisms for responding to various environmental signals. Among them, epigenetic machinery (DNA methylation, histone modifications, microRNAs, etc.) is the hub in transducing external stimuli into transcriptional response. Emerging evidence reveals the concept that epigenetic signatures are essential for the proper maintenance of cellular metabolism. On the other hand, the metabolite, a main environmental input, can also influence the processing of epigenetic memory. Here, we summarize the recent research progress in the epigenetic regulation of cellular metabolism and discuss how the dysfunction of epigenetic machineries influences the development of metabolic disorders such as diabetes and obesity; then, we focus on discussing the notion that manipulating metabolites, the fuel of cell metabolism, can function as a strategy for interfering epigenetic machinery and its related disease progression as well. PMID:27695375
Architected Cellular Materials
Schaedler, Tobias A.; Carter, William B.
2016-07-01
Additive manufacturing enables fabrication of materials with intricate cellular architecture, whereby progress in 3D printing techniques is increasing the possible configurations of voids and solids ad infinitum. Examples are microlattices with graded porosity and truss structures optimized for specific loading conditions. The cellular architecture determines the mechanical properties and density of these materials and can influence a wide range of other properties, e.g., acoustic, thermal, and biological properties. By combining optimized cellular architectures with high-performance metals and ceramics, several lightweight materials that exhibit strength and stiffness previously unachievable at low densities were recently demonstrated. This review introduces the field of architected materials; summarizes the most common fabrication methods, with an emphasis on additive manufacturing; and discusses recent progress in the development of architected materials. The review also discusses important applications, including lightweight structures, energy absorption, metamaterials, thermal management, and bioscaffolds.
Epigenetics and Cellular Metabolism
Xu, Wenyi; Wang, Fengzhong; Yu, Zhongsheng; Xin, Fengjiao
2016-01-01
Living eukaryotic systems evolve delicate cellular mechanisms for responding to various environmental signals. Among them, epigenetic machinery (DNA methylation, histone modifications, microRNAs, etc.) is the hub in transducing external stimuli into transcriptional response. Emerging evidence reveals the concept that epigenetic signatures are essential for the proper maintenance of cellular metabolism. On the other hand, the metabolite, a main environmental input, can also influence the processing of epigenetic memory. Here, we summarize the recent research progress in the epigenetic regulation of cellular metabolism and discuss how the dysfunction of epigenetic machineries influences the development of metabolic disorders such as diabetes and obesity; then, we focus on discussing the notion that manipulating metabolites, the fuel of cell metabolism, can function as a strategy for interfering epigenetic machinery and its related disease progression as well.
Waiting time distribution for continuous stochastic systems.
Gernert, Robert; Emary, Clive; Klapp, Sabine H L
2014-12-01
The waiting time distribution (WTD) is a common tool for analyzing discrete stochastic processes in classical and quantum systems. However, there are many physical examples where the dynamics is continuous and only approximately discrete, or where it is favourable to discuss the dynamics on a discretized and a continuous level in parallel. An example is the hindered motion of particles through potential landscapes with barriers. In the present paper we propose a consistent generalization of the WTD from the discrete case to situations where the particles perform continuous barrier crossing characterized by a finite duration. To this end, we introduce a recipe to calculate the WTD from the Fokker-Planck (Smoluchowski) equation. In contrast to the closely related first passage time distribution (FPTD), which is frequently used to describe continuous processes, the WTD contains information about the direction of motion. As an application, we consider the paradigmatic example of an overdamped particle diffusing through a washboard potential. To verify the approach and to elucidate its numerical implications, we compare the WTD defined via the Smoluchowski equation with data from direct simulation of the underlying Langevin equation and find full consistency provided that the jumps in the Langevin approach are defined properly. Moreover, for sufficiently large energy barriers, the WTD defined via the Smoluchowski equation becomes consistent with that resulting from the analytical solution of a (two-state) master equation model for the short-time dynamics developed previously by us [Phys. Rev. E 86, 061135 (2012)]. Thus, our approach "interpolates" between these two types of stochastic motion. We illustrate our approach for both symmetric systems and systems under constant force. PMID:25615052
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)
Brownian motion, martingales, and stochastic calculus
Le Gall, Jean-François
2016-01-01
This book offers a rigorous and self-contained presentation of stochastic integration and stochastic calculus within the general framework of continuous semimartingales. The main tools of stochastic calculus, including Itô’s formula, the optional stopping theorem and Girsanov’s theorem, are treated in detail alongside many illustrative examples. The book also contains an introduction to Markov processes, with applications to solutions of stochastic differential equations and to connections between Brownian motion and partial differential equations. The theory of local times of semimartingales is discussed in the last chapter. Since its invention by Itô, stochastic calculus has proven to be one of the most important techniques of modern probability theory, and has been used in the most recent theoretical advances as well as in applications to other fields such as mathematical finance. Brownian Motion, Martingales, and Stochastic Calculus provides a strong theoretical background to the reader interested i...
Trajectory averaging for stochastic approximation MCMC algorithms
Liang, Faming
2010-01-01
The subject of stochastic approximation was founded by Robbins and Monro [Ann. Math. Statist. 22 (1951) 400--407]. After five decades of continual development, it has developed into an important area in systems control and optimization, and it has also served as a prototype for the development of adaptive algorithms for on-line estimation and control of stochastic systems. Recently, it has been used in statistics with Markov chain Monte Carlo for solving maximum likelihood estimation problems and for general simulation and optimizations. In this paper, we first show that the trajectory averaging estimator is asymptotically efficient for the stochastic approximation MCMC (SAMCMC) algorithm under mild conditions, and then apply this result to the stochastic approximation Monte Carlo algorithm [Liang, Liu and Carroll J. Amer. Statist. Assoc. 102 (2007) 305--320]. The application of the trajectory averaging estimator to other stochastic approximation MCMC algorithms, for example, a stochastic approximation MLE al...
Delay-induced stochastic bifurcations in a bistable system under white noise
International Nuclear Information System (INIS)
In this paper, the effects of noise and time delay on stochastic bifurcations are investigated theoretically and numerically in a time-delayed Duffing-Van der Pol oscillator subjected to white noise. Due to the time delay, the random response is not Markovian. Thereby, approximate methods have been adopted to obtain the Fokker-Planck-Kolmogorov equation and the stationary probability density function for amplitude of the response. Based on the knowledge that stochastic bifurcation is characterized by the qualitative properties of the steady-state probability distribution, it is found that time delay and feedback intensity as well as noise intensity will induce the appearance of stochastic P-bifurcation. Besides, results demonstrated that the effects of the strength of the delayed displacement feedback on stochastic bifurcation are accompanied by the sensitive dependence on time delay. Furthermore, the results from numerical simulations best confirm the effectiveness of the theoretical analyses
Improved dimensionally-reduced visual cortical network using stochastic noise modeling.
Tao, Louis; Praissman, Jeremy; Sornborger, Andrew T
2012-04-01
In this paper, we extend our framework for constructing low-dimensional dynamical system models of large-scale neuronal networks of mammalian primary visual cortex. Our dimensional reduction procedure consists of performing a suitable linear change of variables and then systematically truncating the new set of equations. The extended framework includes modeling the effect of neglected modes as a stochastic process. By parametrizing and including stochasticity in one of two ways we show that we can improve the systems-level characterization of our dimensionally reduced neuronal network model. We examined orientation selectivity maps calculated from the firing rate distribution of large-scale simulations and stochastic dimensionally reduced models and found that by using stochastic processes to model the neglected modes, we were able to better reproduce the mean and variance of firing rates in the original large-scale simulations while still accurately predicting the orientation preference distribution.
Delay-induced stochastic bifurcations in a bistable system under white noise.
Sun, Zhongkui; Fu, Jin; Xiao, Yuzhu; Xu, Wei
2015-08-01
In this paper, the effects of noise and time delay on stochastic bifurcations are investigated theoretically and numerically in a time-delayed Duffing-Van der Pol oscillator subjected to white noise. Due to the time delay, the random response is not Markovian. Thereby, approximate methods have been adopted to obtain the Fokker-Planck-Kolmogorov equation and the stationary probability density function for amplitude of the response. Based on the knowledge that stochastic bifurcation is characterized by the qualitative properties of the steady-state probability distribution, it is found that time delay and feedback intensity as well as noise intensity will induce the appearance of stochastic P-bifurcation. Besides, results demonstrated that the effects of the strength of the delayed displacement feedback on stochastic bifurcation are accompanied by the sensitive dependence on time delay. Furthermore, the results from numerical simulations best confirm the effectiveness of the theoretical analyses.
Delay-induced stochastic bifurcations in a bistable system under white noise
Energy Technology Data Exchange (ETDEWEB)
Sun, Zhongkui, E-mail: sunzk@nwpu.edu.cn; Fu, Jin; Xu, Wei [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Xiao, Yuzhu [Department of Mathematics and Information Science, Chang' an University, Xi' an 710086 (China)
2015-08-15
In this paper, the effects of noise and time delay on stochastic bifurcations are investigated theoretically and numerically in a time-delayed Duffing-Van der Pol oscillator subjected to white noise. Due to the time delay, the random response is not Markovian. Thereby, approximate methods have been adopted to obtain the Fokker-Planck-Kolmogorov equation and the stationary probability density function for amplitude of the response. Based on the knowledge that stochastic bifurcation is characterized by the qualitative properties of the steady-state probability distribution, it is found that time delay and feedback intensity as well as noise intensity will induce the appearance of stochastic P-bifurcation. Besides, results demonstrated that the effects of the strength of the delayed displacement feedback on stochastic bifurcation are accompanied by the sensitive dependence on time delay. Furthermore, the results from numerical simulations best confirm the effectiveness of the theoretical analyses.
Delay-induced stochastic bifurcations in a bistable system under white noise.
Sun, Zhongkui; Fu, Jin; Xiao, Yuzhu; Xu, Wei
2015-08-01
In this paper, the effects of noise and time delay on stochastic bifurcations are investigated theoretically and numerically in a time-delayed Duffing-Van der Pol oscillator subjected to white noise. Due to the time delay, the random response is not Markovian. Thereby, approximate methods have been adopted to obtain the Fokker-Planck-Kolmogorov equation and the stationary probability density function for amplitude of the response. Based on the knowledge that stochastic bifurcation is characterized by the qualitative properties of the steady-state probability distribution, it is found that time delay and feedback intensity as well as noise intensity will induce the appearance of stochastic P-bifurcation. Besides, results demonstrated that the effects of the strength of the delayed displacement feedback on stochastic bifurcation are accompanied by the sensitive dependence on time delay. Furthermore, the results from numerical simulations best confirm the effectiveness of the theoretical analyses. PMID:26328553
Stochastic Descent Analysis of Representation Learning Algorithms
Golden, Richard M.
2014-01-01
Although stochastic approximation learning methods have been widely used in the machine learning literature for over 50 years, formal theoretical analyses of specific machine learning algorithms are less common because stochastic approximation theorems typically possess assumptions which are difficult to communicate and verify. This paper presents a new stochastic approximation theorem for state-dependent noise with easily verifiable assumptions applicable to the analysis and design of import...
The Robustness of Stochastic Switching Networks
Loh, Po-Ling; Zhou, Hongchao; Bruck, Jehoshua
2009-01-01
Many natural systems, including chemical and biological systems, can be modeled using stochastic switching circuits. These circuits consist of stochastic switches, called pswitches, which operate with a fixed probability of being open or closed. We study the effect caused by introducing an error of size ∈ to each pswitch in a stochastic circuit. We analyze two constructions – simple series-parallel and general series-parallel circuits – and prove that simple series-parallel circuits are robus...
Stochastic vehicle routing: from theory to practice
Weyland, Dennis; Gambardella, Luca Maria; Montemanni, Roberto
2013-01-01
In this thesis we discuss practical and theoretical aspects of various stochastic vehicle routing problems. These are combinatorial optimization problems related to the field of transportation and logistics in which input data is (partially) represented in a stochastic way. More in detail, we focus on two-stage stochastic vehicle routing problems and in particular on so-called a priori optimization problems. The results are divided into a theoretical part and a practical part. In fact, the ...
Ambit processes and stochastic partial differential equations
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole; Benth, Fred Espen; Veraart, Almut
Ambit processes are general stochastic processes based on stochastic integrals with respect to Lévy bases. Due to their flexible structure, they have great potential for providing realistic models for various applications such as in turbulence and finance. This papers studies the connection betwe...... ambit processes and solutions to stochastic partial differential equations. We investigate this relationship from two angles: from the Walsh theory of martingale measures and from the viewpoint of the Lévy noise analysis....
Cooperative Games with Stochastic Payoffs: Determanistic Equivalents
Suijs, J.P.M.; Borm, P.E.M.
1996-01-01
This paper focuses on the subclass of cooperative games with stochastic payoffs in which the preferences of the agents are such that a stochastic payoff can be represented by a deterministic equivalent.To each game within this class one can associate a game with deterministic payoffs.It is shown that the core of such a cooperative game with stochastic payoffs is nonempty if and only if the core of the associated game is nonempty.
Stochastic Turing Patterns on a Network
Asslani, Malbor; Di Patti, Francesca; Fanelli, Duccio
2012-01-01
The process of stochastic Turing instability on a network is discussed for a specific case study, the stochastic Brusselator model. The system is shown to spontaneously differentiate into activator-rich and activator-poor nodes, outside the region of parameters classically deputed to the deterministic Turing instability. This phenomenon, as revealed by direct stochastic simulations, is explained analytically, and eventually traced back to the finite size corrections stemming from the inherent...
Stochastic Turing patterns on a network
Asslani, Malbor; Di Patti, Francesca; Fanelli, Duccio
2012-10-01
The process of stochastic Turing instability on a scale-free network is discussed for a specific case study: the stochastic Brusselator model. The system is shown to spontaneously differentiate into activator-rich and activator-poor nodes outside the region of parameters classically deputed to the deterministic Turing instability. This phenomenon, as revealed by direct stochastic simulations, is explained analytically and eventually traced back to the finite-size corrections stemming from the inherent graininess of the scrutinized medium.
Stochastic Fluid Dynamic Model and Dimensional Reduction
Resseguier, Valentin; Mémin, Etienne; Chapron, Bertrand
2015-01-01
International audience This paper uses a new decomposition of the fluid velocity in terms of a large-scale continuous component with respect to time and a small-scale non continuous random component. Within this general framework, a stochas-tic representation of the Reynolds transport theorem and Navier-Stokes equations can be derived, based on physical conservation laws. This physically relevant stochas-tic model is applied in the context of the POD-Galerkin method. In both the stochastic...
Credit Derivative Pricing with Stochastic Volatility Models
Carl Chiarella; Samuel Chege Maina; Christina Nikitopoulos-Sklibosios
2011-01-01
This paper proposes a framework for pricing credit derivatives within the defaultable Markovian HJM framework featuring unspanned stochastic volatility. Motivated by empirical evidence, hump-shaped level dependent stochastic volatility specifications are proposed, such that the model admits finite dimensional Markovian structures. The model also accommodates a correlation structure between the stochastic volatility, default-free interest rates and credit spreads. Default free and defaultable ...
Modelling Cow Behaviour Using Stochastic Automata
Jónsson, Ragnar Ingi
2010-01-01
This report covers an initial study on the modelling of cow behaviour using stochastic automata with the aim of detecting lameness. Lameness in cows is a serious problem that needs to be dealt with because it results in less profitable production units and in reduced quality of life for the affected livestock. By featuring training data consisting of measurements of cow activity, three different models are obtained, namely an autonomous stochastic automaton, a stochastic automaton with coinci...
Impulsive control of stochastic system under the sense of stochastic asymptotical stability
Institute of Scientific and Technical Information of China (English)
Niu Yu-Jun; Ma Ge
2010-01-01
This paper studies the stochastic asymptotical stability of stochastic impulsive differential equations,and establishes a comparison theory to ensure the trivial solution's stochastic asymptotical stability.From the comparison theory,it can find out whether the stochastic impulsive differential system is stable just by studying the stability of a deterimpulsive control method,and numerical simulations are employed to verify the feasibility of this method.
Debrabant, Kristian; Rößler, Andreas
2013-01-01
In the present paper, a class of stochastic Runge-Kutta methods containing the second order stochastic Runge-Kutta scheme due to E. Platen for the weak approximation of It\\^o stochastic differential equation systems with a multi-dimensional Wiener process is considered. Order one and order two conditions for the coefficients of explicit stochastic Runge-Kutta methods are solved and the solution space of the possible coefficients is analyzed. A full classification of the coefficients for such ...
Travelling fronts in stochastic Stokes’ drifts
Blanchet, Adrien
2008-10-01
By analytical methods we study the large time properties of the solution of a simple one-dimensional model of stochastic Stokes\\' drift. Semi-explicit formulae allow us to characterize the behaviour of the solutions and compute global quantities such as the asymptotic speed of the center of mass or the effective diffusion coefficient. Using an equivalent tilted ratchet model, we observe that the speed of the center of mass converges exponentially to its limiting value. A diffuse, oscillating front attached to the center of mass appears. The description of the front is given using an asymptotic expansion. The asymptotic solution attracts all solutions at an algebraic rate which is determined by the effective diffusion coefficient. The proof relies on an entropy estimate based on homogenized logarithmic Sobolev inequalities. In the travelling frame, the macroscopic profile obeys to an isotropic diffusion. Compared with the original diffusion, diffusion is enhanced or reduced, depending on the regime. At least in the limit cases, the rate of convergence to the effective profile is always decreased. All these considerations allow us to define a notion of efficiency for coherent transport, characterized by a dimensionless number, which is illustrated on two simple examples of travelling potentials with a sinusoidal shape in the first case, and a sawtooth shape in the second case. © 2008 Elsevier B.V. All rights reserved.
Efficient numerical integrators for stochastic models
De Fabritiis, G; Español, P; Coveney, P V
2006-01-01
The efficient simulation of models defined in terms of stochastic differential equations (SDEs) depends critically on an efficient integration scheme. In this article, we investigate under which conditions the integration schemes for general SDEs can be derived using the Trotter expansion. It follows that, in the stochastic case, some care is required in splitting the stochastic generator. We test the Trotter integrators on an energy-conserving Brownian model and derive a new numerical scheme for dissipative particle dynamics. We find that the stochastic Trotter scheme provides a mathematically correct and easy-to-use method which should find wide applicability.
Stochastic versus deterministic systems of differential equations
Ladde, G S
2003-01-01
This peerless reference/text unfurls a unified and systematic study of the two types of mathematical models of dynamic processes-stochastic and deterministic-as placed in the context of systems of stochastic differential equations. Using the tools of variational comparison, generalized variation of constants, and probability distribution as its methodological backbone, Stochastic Versus Deterministic Systems of Differential Equations addresses questions relating to the need for a stochastic mathematical model and the between-model contrast that arises in the absence of random disturbances/flu
ASYMPTOTIC STABILITIES OF STOCHASTIC FUNCTIONAL DIFFERENTIAL EQUATIONS
Institute of Scientific and Technical Information of China (English)
SHEN Yi; JIANG Ming-hui; LIAO Xiao-xin
2006-01-01
Asymptotic characteristic of solution of the stochastic functional differential equation was discussed and sufficient condition was established by multiple Lyapunov functions for locating the limit set of t he solution. Moreover, from them many effective criteria on stochastic asymptotic stability, which enable us to construct the Lyapunov functions much more easily in application, were obtained. The results show that the wellknown classical theorem on stochastic asymptotic stability is a special case of our more general results. In the end, application in stochastic Hopfield neural networks is given to verify our results.
Probabilistic Forecasts of Solar Irradiance by Stochastic Differential Equations
DEFF Research Database (Denmark)
Iversen, Jan Emil Banning; Morales González, Juan Miguel; Møller, Jan Kloppenborg;
2014-01-01
Probabilistic forecasts of renewable energy production provide users with valuable information about the uncertainty associated with the expected generation. Current state-of-the-art forecasts for solar irradiance have focused on producing reliable point forecasts. The additional information...... included in probabilistic forecasts may be paramount for decision makers to efficiently make use of this uncertain and variable generation. In this paper, a stochastic differential equation framework for modeling the uncertainty associated with the solar irradiance point forecast is proposed. This modeling...... approach allows for characterizing both the interdependence structure of prediction errors of short-term solar irradiance and their predictive distribution. Three different stochastic differential equation models are first fitted to a training data set and subsequently evaluated on a one-year test set...
Information Theoretic Limits on Learning Stochastic Differential Equations
Bento, José; Montanari, Andrea
2011-01-01
Consider the problem of learning the drift coefficient of a stochastic differential equation from a sample path. In this paper, we assume that the drift is parametrized by a high dimensional vector. We address the question of how long the system needs to be observed in order to learn this vector of parameters. We prove a general lower bound on this time complexity by using a characterization of mutual information as time integral of conditional variance, due to Kadota, Zakai, and Ziv. This general lower bound is applied to specific classes of linear and non-linear stochastic differential equations. In the linear case, the problem under consideration is the one of learning a matrix of interaction coefficients. We evaluate our lower bound for ensembles of sparse and dense random matrices. The resulting estimates match the qualitative behavior of upper bounds achieved by computationally efficient procedures.
Exploring stochasticity and imprecise knowledge based on linear inequality constraints.
Subbey, Sam; Planque, Benjamin; Lindstrøm, Ulf
2016-09-01
This paper explores the stochastic dynamics of a simple foodweb system using a network model that mimics interacting species in a biosystem. It is shown that the system can be described by a set of ordinary differential equations with real-valued uncertain parameters, which satisfy a set of linear inequality constraints. The constraints restrict the solution space to a bounded convex polytope. We present results from numerical experiments to show how the stochasticity and uncertainty characterizing the system can be captured by sampling the interior of the polytope with a prescribed probability rule, using the Hit-and-Run algorithm. The examples illustrate a parsimonious approach to modeling complex biosystems under vague knowledge. PMID:26746217
A stochastic approach to multi-gene expression dynamics
International Nuclear Information System (INIS)
In the last years, tens of thousands gene expression profiles for cells of several organisms have been monitored. Gene expression is a complex transcriptional process where mRNA molecules are translated into proteins, which control most of the cell functions. In this process, the correlation among genes is crucial to determine the specific functions of genes. Here, we propose a novel multi-dimensional stochastic approach to deal with the gene correlation phenomena. Interestingly, our stochastic framework suggests that the study of the gene correlation requires only one theoretical assumption-Markov property-and the experimental transition probability, which characterizes the gene correlation system. Finally, a gene expression experiment is proposed for future applications of the model
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)
Pricing long-dated insurance contracts with stochastic interest rates and stochastic volatility
A. van Haastrecht; R. Lord; A. Pelsser; D. Schrager
2009-01-01
We consider the pricing of long-dated insurance contracts under stochastic interest rates and stochastic volatility. In particular, we focus on the valuation of insurance options with long-term equity or foreign exchange exposures. Our modeling framework extends the stochastic volatility model of Sc
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–...
Stochastic modeling analysis and simulation
Nelson, Barry L
1995-01-01
A coherent introduction to the techniques for modeling dynamic stochastic systems, this volume also offers a guide to the mathematical, numerical, and simulation tools of systems analysis. Suitable for advanced undergraduates and graduate-level industrial engineers and management science majors, it proposes modeling systems in terms of their simulation, regardless of whether simulation is employed for analysis. Beginning with a view of the conditions that permit a mathematical-numerical analysis, the text explores Poisson and renewal processes, Markov chains in discrete and continuous time, se
Stochastic excitation of stellar oscillations
Samadi, R
2001-01-01
Excitation of solar oscillations is attribued to turbulent motions in the solar convective zone. It is also currently believed that oscillations of low massive stars (M <2 Mo) - which possess an upper convective zone - are stochastically excited by turbulent convection in their outer layers. A recent theoretical work (Samadi & Goupil, 2001 ; Samadi et al, 2001) supplements and reinforces this theory. This allows the use of any available model of turbulence and emphasizes some recent unsolved problems which are brought up by these new theoretical developments.
Mathematical statistics and stochastic processes
Bosq, Denis
2013-01-01
Generally, books on mathematical statistics are restricted to the case of independent identically distributed random variables. In this book however, both this case AND the case of dependent variables, i.e. statistics for discrete and continuous time processes, are studied. This second case is very important for today's practitioners.Mathematical Statistics and Stochastic Processes is based on decision theory and asymptotic statistics and contains up-to-date information on the relevant topics of theory of probability, estimation, confidence intervals, non-parametric statistics and rob
Constrained Stochastic Extended Redundancy Analysis.
DeSarbo, Wayne S; Hwang, Heungsun; Stadler Blank, Ashley; Kappe, Eelco
2015-06-01
We devise a new statistical methodology called constrained stochastic extended redundancy analysis (CSERA) to examine the comparative impact of various conceptual factors, or drivers, as well as the specific predictor variables that contribute to each driver on designated dependent variable(s). The technical details of the proposed methodology, the maximum likelihood estimation algorithm, and model selection heuristics are discussed. A sports marketing consumer psychology application is provided in a Major League Baseball (MLB) context where the effects of six conceptual drivers of game attendance and their defining predictor variables are estimated. Results compare favorably to those obtained using traditional extended redundancy analysis (ERA). PMID:24327066
Stochastic dynamics on slow manifolds
Constable, George W. A.; McKane, Alan J.; Rogers, Tim
2013-07-01
The theory of slow manifolds is an important tool in the study of deterministic dynamical systems, giving a practical method by which to reduce the number of relevant degrees of freedom in a model, thereby often resulting in a considerable simplification. In this paper we demonstrate how the same basic methodology may also be applied to stochastic dynamical systems, by examining the behaviour of trajectories conditioned on the event that they do not depart the slow manifold. We apply the method to two models: one from ecology and one from epidemiology, achieving a reduction in model dimension and illustrating the high quality of the analytical approximations.
Dual effect free stochastic controls
Barty, Kengy; Carpentier, P.; Chancelier, J.-P.; Cohen, G.; Lara, M; Guilbaud, T.
2003-01-01
In stochastic optimal control, a key issue is the fact that "solutions" are searched for in terms of "feedback" over available information and, as a consequence, a major potential difficulty is the fact that present control may affect future available information. This is known as the "dual effect" of control. Given a minimal framework (that is, an observation mapping from the product of a control set and of a random set towards an observation set), we define open-loop lack of dual effect as...
Probability, Statistics, and Stochastic Processes
Olofsson, Peter
2012-01-01
This book provides a unique and 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. The Second Edition features new coverage of analysis of variance (ANOVA), consistency and efficiency of estimators, asymptotic theory for maximum likelihood estimators, empirical distribution function and the Kolmogorov-Smirnov test, general linear models, multiple comparisons, Markov chain Monte Carlo (MCMC), Brownian motion, martingales, and
Stochastic Calculus of Wrapped Compartments
Coppo, Mario; Drocco, Maurizio; Grassi, Elena; Troina, Angelo; 10.4204/EPTCS.28.6
2010-01-01
The Calculus of Wrapped Compartments (CWC) is a variant of the Calculus of Looping Sequences (CLS). While keeping the same expressiveness, CWC strongly simplifies the development of automatic tools for the analysis of biological systems. The main simplification consists in the removal of the sequencing operator, thus lightening the formal treatment of the patterns to be matched in a term (whose complexity in CLS is strongly affected by the variables matching in the sequences). We define a stochastic semantics for this new calculus. As an application we model the interaction between macrophages and apoptotic neutrophils and a mechanism of gene regulation in E.Coli.
Coexistence in stochastic spatial models
Durrett, Rick
2009-01-01
In this paper I will review twenty years of work on the question: When is there coexistence in stochastic spatial models? The answer, announced in Durrett and Levin [Theor. Pop. Biol. 46 (1994) 363--394], and that we explain in this paper is that this can be determined by examining the mean-field ODE. There are a number of rigorous results in support of this picture, but we will state nine challenging and important open problems, most of which date from the 1990's.
Stochastic Gravity: Theory and Applications
Directory of Open Access Journals (Sweden)
Hu Bei Lok
2004-01-01
Full Text Available Whereas semiclassical gravity is based on the semiclassical Einstein equation with sources given by the expectation value of the stress-energy tensor of quantum fields, stochastic semiclassical gravity is based on the Einstein-Langevin equation, which has in addition sources due to the noise kernel. The noise kernel is the vacuum expectation value of the (operator-valued stress-energy bi-tensor which describes the fluctuations of quantum matter fields in curved spacetimes. In the first part, we describe the fundamentals of this new theory via two approaches: the axiomatic and the functional. The axiomatic approach is useful to see the structure of the theory from the framework of semiclassical gravity, showing the link from the mean value of the stress-energy tensor to their correlation functions. The functional approach uses the Feynman-Vernon influence functional and the Schwinger-Keldysh closed-time-path effective action methods which are convenient for computations. It also brings out the open systems concepts and the statistical and stochastic contents of the theory such as dissipation, fluctuations, noise, and decoherence. We then focus on the properties of the stress-energy bi-tensor. We obtain a general expression for the noise kernel of a quantum field defined at two distinct points in an arbitrary curved spacetime as products of covariant derivatives of the quantum field's Green function. In the second part, we describe three applications of stochastic gravity theory. First, we consider metric perturbations in a Minkowski spacetime. We offer an analytical solution of the Einstein-Langevin equation and compute the two-point correlation functions for the linearized Einstein tensor and for the metric perturbations. Second, we discuss structure formation from the stochastic gravity viewpoint, which can go beyond the standard treatment by incorporating the full quantum effect of the inflaton fluctuations. Third, we discuss the backreaction
Stochastic vehicle routing with recourse
DEFF Research Database (Denmark)
Gørtz, Inge Li; Nagarajan, Viswanath; Saket, Rishi
2012-01-01
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...... orienteering, called knapsack rank-function orienteering. We also give a better approximation ratio for knapsack rank-function orienteering than what follows from prior work. Finally, we provide a Unique Games Conjecture based ω(1) hardness of approximation for StochVRP, even on star-like metrics on which our...
From cellular to tissue scales by asymptotic limits of thermostatted kinetic models
Bianca, Carlo; Dogbe, Christian; Lemarchand, Annie
2016-02-01
Tumor growth strictly depends on the interactions occurring at the cellular scale. In order to obtain the linking between the dynamics described at tissue and cellular scales, asymptotic methods have been employed, consisting in deriving tissue equations by suitable limits of mesoscopic models. In this paper, the evolution at the cellular scale is described by thermostatted kinetic theory that include conservative, nonconservative (proliferation, destruction and mutations), stochastic terms, and the role of external agents. The dynamics at the tissue scale (cell-density evolution) is obtained by performing a low-field scaling and considering the related convergence of the rescaled framework when the scaling parameter goes to zero.
Molecular and Cellular Signaling
Beckerman, Martin
2005-01-01
A small number of signaling pathways, no more than a dozen or so, form a control layer that is responsible for all signaling in and between cells of the human body. The signaling proteins belonging to the control layer determine what kinds of cells are made during development and how they function during adult life. Malfunctions in the proteins belonging to the control layer are responsible for a host of human diseases ranging from neurological disorders to cancers. Most drugs target components in the control layer, and difficulties in drug design are intimately related to the architecture of the control layer. Molecular and Cellular Signaling provides an introduction to molecular and cellular signaling in biological systems with an emphasis on the underlying physical principles. The text is aimed at upper-level undergraduates, graduate students and individuals in medicine and pharmacology interested in broadening their understanding of how cells regulate and coordinate their core activities and how diseases ...
Multiple Fields in Stochastic Inflation
Assadullahi, Hooshyar; Noorbala, Mahdiyar; Vennin, Vincent; Wands, David
2016-01-01
Stochastic effects in multi-field inflationary scenarios are investigated. A hierarchy of diffusion equations is derived, the solutions of which yield moments of the numbers of inflationary $e$-folds. Solving the resulting partial differential equations in multi-dimensional field space is more challenging than the single-field case. A few tractable examples are discussed, which show that the number of fields is, in general, a critical parameter. When more than two fields are present for instance, the probability to explore arbitrarily large-field regions of the potential, otherwise inaccessible to single-field dynamics, becomes non-zero. In some configurations, this gives rise to an infinite mean number of $e$-folds, regardless of the initial conditions. Another difference with respect to single-field scenarios is that multi-field stochastic effects can be large even at sub-Planckian energy. This opens interesting new possibilities for probing quantum effects in inflationary dynamics, since the moments of the...
Stochastic background of gravitational waves
D'Araújo, J C N; Aguiar, O D
2000-01-01
A continuous stochastic background of gravitational waves (GWs) for burst sources is produced if the mean time interval between the occurrence of bursts is smaller than the average time duration of a single burst at the emission, i.e., the so called duty cycle must be greater than one. To evaluate the background of GWs produced by an ensemble of sources, during their formation, for example, one needs to know the average energy flux emitted during the formation of a single object and the formation rate of such objects as well. In many cases the energy flux emitted during an event of production of GWs is not known in detail, only characteristic values for the dimensionless amplitude and frequencies are known. Here we present a shortcut to calculate stochastic backgrounds of GWs produced from cosmological sources. For this approach it is not necessary to know in detail the energy flux emitted at each frequency. Knowing the characteristic values for the ``lumped'' dimensionless amplitude and frequency we show tha...
Single-molecule stochastic resonance
Hayashi, K; Manosas, M; Huguet, J M; Ritort, F; 10.1103/PhysRevX.2.031012
2012-01-01
Stochastic resonance (SR) is a well known phenomenon in dynamical systems. It consists of the amplification and optimization of the response of a system assisted by stochastic noise. Here we carry out the first experimental study of SR in single DNA hairpins which exhibit cooperatively folding/unfolding transitions under the action of an applied oscillating mechanical force with optical tweezers. By varying the frequency of the force oscillation, we investigated the folding/unfolding kinetics of DNA hairpins in a periodically driven bistable free-energy potential. We measured several SR quantifiers under varied conditions of the experimental setup such as trap stiffness and length of the molecular handles used for single-molecule manipulation. We find that the signal-to-noise ratio (SNR) of the spectral density of measured fluctuations in molecular extension of the DNA hairpins is a good quantifier of the SR. The frequency dependence of the SNR exhibits a peak at a frequency value given by the resonance match...
Overby, Darryl R.; Alenghat, Francis J.; Montoya-Zavala, Martín; Bei, HuCheng; Oh, Philmo; Karavitis, John; Ingber, Donald E.
2004-01-01
This paper focuses on the development of magnetic cellular switches to enable magnetic control of intracellular functions in living mammalian cells, including receptor signal transduction and gene transcription. Our approach takes advantage of the mechanosensitivity of adenosine 3′,5′-monophosphate (cAMP) induction and downstream transcription controlled by the cAMP regulatory element (CRE) to engineer gene constructs that optically report gene expression in living cells. We activate transcri...
Suprathreshold Stochastic Resonance in a Single Comparator
Institute of Scientific and Technical Information of China (English)
WANG Ren-Guo; LONG Zhang-Cai
2007-01-01
@@ Stochastic resonance usually appears when stimulus is too weak to overcome barriers in a nonlinear system.Unusually, we demonstrate that in a simple comparator as a prototype model, stochastic resonance can still occur when the stimulus is predominantly suprathreshold. This result provides new knowledge for understanding of mechanism underlying information process in biological systems and also finds applications in signal processing.
Optimizing Resource Acquisition Decisions by Stochastic Programming
Daniel Bienstock; Jeremy F. Shapiro
1988-01-01
This paper reports on the application of stochastic programming with recourse to strategic planning decisions regarding resource acquisition. A resource directed decomposition method, which simultaneously exploits stochastic programming and mixed integer programming model structures, is proposed. Computational experience with the method applied to fuel contract and plant construction decisions faced by an electric utility is presented.
Parallel transports associated to stochastic holonomies
Institute of Scientific and Technical Information of China (English)
CHEN; Shiping(陈世平); XIANG; Kainan(向开南)
2002-01-01
A stochastic holonomy along a loop obtained from the OU process on the path space over acompact Riemannian manifold is computed. The result shows that the stochastic holonomy just gives theparallel transport with respect to the Markov connection along the OU process on the path space.
Option valuation models with stochastic volatility
Šigut, Jiří
2012-01-01
This work describes stochastic volatility models and application of such models for option pricing. Models for underlying asset and then pricing models for options with stochastic volatility are derived. Black-Scholes and Heston-Nandi models are compared in empirical part of this work.
Some Recent Developments in Ambit Stochastics
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole E.; Hedevang, Emil; Schmiegel, Jürgen;
Some of the recent developments in the rapidly expanding field of Ambit Stochastics are here reviewed. After a brief recall of the framework of Ambit Stochastics three topics are considered: (i) Methods of modelling and inference for volatility/intermittency processes and fields (ii) Universal laws...
Stochastic Kinetics of Intracellular Calcium Oscillations
Institute of Scientific and Technical Information of China (English)
陈昌胜; 曾仁端
2003-01-01
A stochastic model of intracellular calcium oscillations is put forward by taking into account the random opening-closing of Ca2+ channels in endoplasmic reticulum (ER) membrane. The numerical results of the stochastic model show simple and complex calcium oscillations, which accord with the experiment results.
Cooperative Games with Stochastic Payoffs : Determanistic Equivalents
Suijs, J.P.M.; Borm, P.E.M.
1996-01-01
This paper focuses on the subclass of cooperative games with stochastic payoffs in which the preferences of the agents are such that a stochastic payoff can be represented by a deterministic equivalent.To each game within this class one can associate a game with deterministic payoffs.It is shown tha
Integration of stochastic generation in power systems
Papaefthymiou, G.
2007-01-01
Stochastic Generation is the electrical power production by the use of an uncontrollable prime energy mover, corresponding mainly to renewable energy sources. For the large-scale integration of stochastic generation in power systems, methods are necessary for the modeling of power generation uncerta
Stochastic Dynamics for the Matching Pennies Game
Ziv Gorodeisky
2006-01-01
We consider stochastic dynamics for the Matching Pennies game, that behave, in expectation, like best-response dynamics (the continuous fictitious play). We prove convergence to the unique equilibrium by extending the result of Benaim and Weibull [2003] on deterministic approximations for stochastic dynamics to the case of discontinuous dynamics - such as the best-reply dynamics.
Bisimulation for general stochastic hybrid systems
Bujorianu, Manuela L.; Lygeros, John; Bujorianu, Marius C.
2005-01-01
In this paper we define a bisimulation concept for some very general models for stochastic hybrid systems (general stochastic hybrid systems). The definition of bisimulation builds on the ideas of Edalat and of Larsen and Skou and of Joyal, Nielsen and Winskel. The main result is that this bisimulat
Stochastic online scheduling on parallel machines
Megow, N.; Uetz, M.J.; Vredeveld, T.; Persiano, G.; Solis-Oba, R.
2005-01-01
We consider a non-preemptive, stochastic parallel machine scheduling model with the goal to minimize the weighted completion times of jobs. In contrast to the classical stochastic model where jobs with their processing time distributions are known beforehand, we assume that jobs appear one by one, a
A stochastic indicator for sovereign debt sustainability
Lukkezen, J.H.J.; Rojas-Romagosa, Hugo
2016-01-01
We propose a stochastic indicator to assess government debt sustainability. This indicator combines the effect of economic uncertainty –represented by stochastic simulations of interest and growth rates– with the expected fiscal response that provides information on the long-term country specific at
Exact Algorithms for Solving Stochastic Games
Hansen, A K; Koucký, M.; Lauritzen, N.; Miltersen, P.B.; Tsigaridas, E.P.
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. When the number of positions of the game is constant, our algorithms run in polynomial time.
Stochastic Modelling and Analysis of Warehouse Operations
Y. Gong (Yeming)
2009-01-01
textabstractThis thesis has studied stochastic models and analysis of warehouse operations. After an overview of stochastic research in warehouse operations, we explore the following topics. Firstly, we search optimal batch sizes in a parallel-aisle warehouse with online order arrivals. We employ a
Causal random geometry from stochastic quantization
DEFF Research Database (Denmark)
Ambjørn, Jan; Loll, R.; Westra, W.;
2010-01-01
in this short note we review a recently found formulation of two-dimensional causal quantum gravity defined through Causal Dynamical Triangulations and stochastic quantization. This procedure enables one to extract the nonperturbative quantum Hamiltonian of the random surface model including the...... the sum over topologies. Interestingly, the generally fictitious stochastic time corresponds to proper time on the geometries...
Cellular therapy in Tuberculosis
Directory of Open Access Journals (Sweden)
Shreemanta K. Parida
2015-03-01
Full Text Available Cellular therapy now offer promise of potential adjunct therapeutic options for treatment of drug-resistant tuberculosis (TB. We review here the role of Mesenchymal stromal cells, (MSCs, as well as other immune effector cells in the therapy of infectious diseases with a focus on TB. MSCs represent a population of tissue-resident non-hematopoietic adult progenitor cells which home into injured tissues increase the proliferative potential of broncho-alveolar stem cells and restore lung epithelium. MSCs have been shown to be immune-modulatory and anti-inflammatory mediated via cell-cell contacts as well as soluble factors. We discuss the functional profile of MSCs and their potential use for adjunct cellular therapy of multi-drug resistant TB, with the aim of limiting tissue damage, and to convert unproductive inflammatory responses into effective anti-pathogen directed immune responses. Adjunct cellular therapy could potentially offer salvage therapy options for patients with drug-resistant TB, increase clinically relevant anti-M.tuberculosis directed immune responses and possibly shorten the duration of anti-TB therapy.
Modelling and application of stochastic processes
1986-01-01
The subject of modelling and application of stochastic processes is too vast to be exhausted in a single volume. In this book, attention is focused on a small subset of this vast subject. The primary emphasis is on realization and approximation of stochastic systems. Recently there has been considerable interest in the stochastic realization problem, and hence, an attempt has been made here to collect in one place some of the more recent approaches and algorithms for solving the stochastic realiza tion problem. Various different approaches for realizing linear minimum-phase systems, linear nonminimum-phase systems, and bilinear systems are presented. These approaches range from time-domain methods to spectral-domain methods. An overview of the chapter contents briefly describes these approaches. Also, in most of these chapters special attention is given to the problem of developing numerically ef ficient algorithms for obtaining reduced-order (approximate) stochastic realizations. On the application side,...
A cellular automata model of Ebola virus dynamics
Burkhead, Emily; Hawkins, Jane
2015-11-01
We construct a stochastic cellular automaton (SCA) model for the spread of the Ebola virus (EBOV). We make substantial modifications to an existing SCA model used for HIV, introduced by others and studied by the authors. We give a rigorous analysis of the similarities between models due to the spread of virus and the typical immune response to it, and the differences which reflect the drastically different timing of the course of EBOV. We demonstrate output from the model and compare it with clinical data.
Public Evacuation Process Modeling and Simulatiaon Based on Cellular Automata
Directory of Open Access Journals (Sweden)
Zhikun Wang
2013-11-01
Full Text Available Considering attraction of the nearest exit, repulsive force of the fire, barrier and its display style, effect of fire exit location on escape time in fire hazard, a mathematical model of evacuation process model was build based on cellular automatic theory. The program was developed by JavaScript. The influencing factors of evacuation were obtained through the simulation model by inputting crew size, creating initial positions of crew and fire seat stochastically. The experimental results show that the evacuation simulation model with authenticity and validity, which has guiding significance for people evacuation and public escape system design.
Development of stochastic indicator models of lithology, Yucca Mountain, Nevada
Energy Technology Data Exchange (ETDEWEB)
Rautman, C.A. [Sandia National Labs., Albuquerque, NM (United States); Robey, T.H. [Spectra Research Inst., Albuquerque, NM (United States)
1994-07-01
Indicator geostatistical techniques have been used to produce a number of fully three-dimensional stochastic simulations of large-scale lithologic categories at the Yucca Mountain site. Each realization reproduces the available drill hole data used to condition the simulation. Information is propagated away from each point of observation in accordance with a mathematical model of spatial continuity inferred through soft data taken from published geologic cross sections. Variations among the simulated models collectively represent uncertainty in the lithology at unsampled locations. These stochastic models succeed in capturing many major features of welded-nonwelded lithologic framework of Yucca Mountain. However, contacts between welded and nonwelded rock types for individual simulations appear more complex than suggested by field observation, and a number of probable numerical artifacts exist in these models. Many of the apparent discrepancies between the simulated models and the general geology of Yucca Mountain represent characterization uncertainty, and can be traced to the sparse site data used to condition the simulations. Several vertical stratigraphic columns have been extracted from the three-dimensional stochastic models for use in simplified total-system performance assessment exercises. Simple, manual adjustments are required to eliminate the more obvious simulation artifacts and to impose a secondary set of deterministic geologic features on the overall stratigraphic framework provided by the indictor models.
Stochastic ion heating by a lower hybrid wave. II
Energy Technology Data Exchange (ETDEWEB)
Karney, C.F.F.
1979-04-01
The motion of an ion in a coherent lower hybrid wave (characterized by vertical bar/sub parallel/vertical bar much less than vertical bar kappa/sub perpendicular to/vertical bar and ..omega.. much greater than ..cap omega../sub i/) in a tokamak plasma is studied. For ions satisfying ..nu../sub perpendicular to/ > ..omega../kappa/sub perpendicular to/, the Lorentz force law for the ions is reduced to a set of difference equations which give the Larmor radius and phase of an ion on one cyclotron orbit in terms of these quantities a cyclotron period earlier. From these difference equations an earlier result (Phys. Fluids 21, 1584(1978)) that above a certain wave amplitude the ion motion is stochastic, is readily obtained. The stochasticity threshold is given a simple physical interpretation. In addition, the difference equations are used to derive a diffusion equation governing the heating of the ions above the stochasticity threshold. By including the effects of collisions, the heating rate for the bulk ions is obtained.
Stochastic ion heating by a lower hybrid wave. II
International Nuclear Information System (INIS)
The motion of an ion in a coherent lower hybrid wave (characterized by vertical bar/sub parallel/vertical bar much less than vertical bar kappa/sub perpendicular to/vertical bar and ω much greater than Ω/sub i/) in a tokamak plasma is studied. For ions satisfying ν/sub perpendicular to/ > ω/kappa/sub perpendicular to/, the Lorentz force law for the ions is reduced to a set of difference equations which give the Larmor radius and phase of an ion on one cyclotron orbit in terms of these quantities a cyclotron period earlier. From these difference equations an earlier result [Phys. Fluids 21, 1584(1978)] that above a certain wave amplitude the ion motion is stochastic, is readily obtained. The stochasticity threshold is given a simple physical interpretation. In addition, the difference equations are used to derive a diffusion equation governing the heating of the ions above the stochasticity threshold. By including the effects of collisions, the heating rate for the bulk ions is obtained
Application of stochastic ground water models to geologic disposal of high-level nuclear waste
International Nuclear Information System (INIS)
The recognition that significant uncertainties are inherent in the characterization of hydrogeologic systems has led to increasing use of stochastic modeling techniques to predict performance of high-level nuclear waste (HLW) disposal systems. This is certainly true for the Basalt Waste Isolation Project (BWIP), which is investigating the feasibility of long-term storage of nuclear high level waste in the basalt sequence beneath the Hanford Site in Washington State. The Hanford Site is one of the three sites nominated for detailed characterization for the first national HLW repository. A summary of various stochastic methods considered for application to the Hanford Site are provided in this paper. The most commonly used method, that of Monte Carlo simulations, is described in detail. In this method, the uncertain parameters are treated as either lumped random variables with assigned univariate probability distribution functions (pdfs) or as spatially varying stochastic fields with multivariate probability distributions
Stochastic inflation and nonlinear gravity
Salopek, D. S.; Bond, J. R.
1991-02-01
We show how nonlinear effects of the metric and scalar fields may be included in stochastic inflation. Our formalism can be applied to non-Gaussian fluctuation models for galaxy formation. Fluctuations with wavelengths larger than the horizon length are governed by a network of Langevin equations for the physical fields. Stochastic noise terms arise from quantum fluctuations that are assumed to become classical at horizon crossing and that then contribute to the background. Using Hamilton-Jacobi methods, we solve the Arnowitt-Deser-Misner constraint equations which allows us to separate the growing modes from the decaying ones in the drift phase following each stochastic impulse. We argue that the most reasonable choice of time hypersurfaces for the Langevin system during inflation is T=ln(Ha), where H and a are the local values of the Hubble parameter and the scale factor, since T is the natural time for evolving the short-wavelength scalar field fluctuations in an inhomogeneous background. We derive a Fokker-Planck equation which describes how the probability distribution of scalar field values at a given spatial point evolves in T. Analytic Green's-function solutions obtained for a single scalar field self-interacting through an exponential potential are used to demonstrate (1) if the initial condition of the Hubble parameter is chosen to be consistent with microwave-background limits, H(φ0)/mρUniverse, the distribution is non-Gaussian, with a tail extending to large energy densities; although there are no observable manifestations, it does show eternal inflation. Lattice simulations of our Langevin network for the exponential potential demonstrate how spatial correlations are incorporated. An initially homogeneous and isotropic lattice develops fluctuations as more and more quantum fluctuation modes leave the horizon, yielding Gaussian contour maps for a region corresponding to our observable patch and non-Gaussian contour maps for the ultra
Multimodal Network Equilibrium with Stochastic Travel Times
Directory of Open Access Journals (Sweden)
M. Meng
2014-01-01
Full Text Available The private car, unlike public traffic modes (e.g., subway, trolley running along dedicated track-ways, is invariably subject to various uncertainties resulting in travel time variation. A multimodal network equilibrium model is formulated that explicitly considers stochastic link capacity variability in the road network. The travel time of combined-mode trips is accumulated based on the concept of the mean excess travel time (METT which is a summation of estimated buffer time and tardy time. The problem is characterized by an equivalent VI (variational inequality formulation where the mode choice is expressed in a hierarchical logit structure. Specifically, the supernetwork theory and expansion technique are used herein to represent the multimodal transportation network, which completely represents the combined-mode trips as constituting multiple modes within a trip. The method of successive weighted average is adopted for problem solutions. The model and solution method are further applied to study the trip distribution and METT variations caused by the different levels of the road conditions. Results of numerical examples show that travelers prefer to choose the combined travel mode as road capacity decreases. Travelers with different attitudes towards risk are shown to exhibit significant differences when making travel choice decisions.
Enhanced corticomuscular coherence by external stochastic noise.
Trenado, Carlos; Mendez-Balbuena, Ignacio; Manjarrez, Elias; Huethe, Frank; Schulte-Mönting, Jürgen; Feige, Bernd; Hepp-Reymond, Marie-Claude; Kristeva, Rumyana
2014-01-01
Noise can have beneficial effects as shown by the stochastic resonance (SR) phenomenon which is characterized by performance improvement when an optimal noise is added. Modern attempts to improve human performance utilize this phenomenon. The purpose of the present study was to investigate whether performance improvement by addition of optimum noise (ON) is related to increased cortical motor spectral power (SP) and increased corticomuscular coherence. Eight subjects performed a visuomotor task requiring to compensate with the right index finger a static force (SF) generated by a manipulandum on which Gaussian noise was applied. The finger position was displayed on-line on a monitor as a small white dot which the subjects had to maintain in the center of a green bigger circle. Electroencephalogram from the contralateral motor area, electromyogram from active muscles and finger position were recorded. The performance was measured by the mean absolute deviation (MAD) of the white dot from the zero position. ON compared to the zero noise condition induced an improvement in motor accuracy together with an enhancement of cortical motor SP and corticomuscular coherence in beta-range. These data suggest that the improved sensorimotor performance via SR is consistent with an increase in the cortical motor SP and in the corticomuscular coherence.
A stochastic model for early placental development.
Cotter, Simon L
2014-08-01
In the human, placental structure is closely related to placental function and consequent pregnancy outcome. Studies have noted abnormal placental shape in small-for-gestational-age infants which extends to increased lifetime risk of cardiovascular disease. The origins and determinants of placental shape are incompletely understood and are difficult to study in vivo. In this paper, we model the early development of the human placenta, based on the hypothesis that this is driven by a chemoattractant effect emanating from proximal spiral arteries in the decidua. We derive and explore a two-dimensional stochastic model, and investigate the effects of loss of spiral arteries in regions near to the cord insertion on the shape of the placenta. This model demonstrates that disruption of spiral arteries can exert profound effects on placental shape, particularly if this is close to the cord insertion. Thus, placental shape reflects the underlying maternal vascular bed. Abnormal placental shape may reflect an abnormal uterine environment, predisposing to pregnancy complications. Through statistical analysis of model placentas, we are able to characterize the probability that a given placenta grew in a disrupted environment, and even able to distinguish between different disruptions.
Stochastic transport in complex systems from molecules to vehicles
Schadschneider, Andreas; Nishinari, Katsuhiro
2011-01-01
What is common between a motor protein, an ant and a vehicle? Each can be modelled as a"self-propelled particle"whose forward movement can be hindered by another in front of it. Traffic flow of such interacting driven"particles"has become an active area of interdisciplinary research involving physics, civil engineering and computer science. We present a unified pedagogical introduction to the analytical and computational methods which are currently used for studying such complex systems far from equilibrium. We also review a number of applications ranging from intra-cellular molecular motor transport in living systems to ant trails and vehicular traffic. Researchers working on complex systems, in general, and on classical stochastic transport, in particular, will find the pedagogical style, scholarly critical overview and extensive list of references extremely useful.
Hierarchical Stochastic Simulation Algorithm for SBML Models of Genetic Circuits
Directory of Open Access Journals (Sweden)
Leandro eWatanabe
2014-11-01
Full Text Available This paper describes a hierarchical stochastic simulation algorithm which has been implemented within iBioSim, a tool used to model, analyze, and visualize genetic circuits. Many biological analysis tools flatten out hierarchy before simulation, but there are many disadvantages associated with this approach. First, the memory required to represent the model can quickly expand in the process. Second, the flattening process is computationally expensive. Finally, when modeling a dynamic cellular population within iBioSim, inlining the hierarchy of the model is inefficient since models must grow dynamically over time. This paper discusses a new approach to handle hierarchy on the fly to make the tool faster and more memory-efficient. This approach yields significant performance improvements as compared to the former flat analysis method.