Energy Technology Data Exchange (ETDEWEB)
Scott, Bobby, R., Ph.D.
2003-06-27
OAK - B135 This project final report summarizes modeling research conducted in the U.S. Department of Energy (DOE), Low Dose Radiation Research Program at the Lovelace Respiratory Research Institute from October 1998 through June 2003. The modeling research described involves critically evaluating the validity of the linear nonthreshold (LNT) risk model as it relates to stochastic effects induced in cells by low doses of ionizing radiation and genotoxic chemicals. The LNT model plays a central role in low-dose risk assessment for humans. With the LNT model, any radiation (or genotoxic chemical) exposure is assumed to increase one¡¯s risk of cancer. Based on the LNT model, others have predicted tens of thousands of cancer deaths related to environmental exposure to radioactive material from nuclear accidents (e.g., Chernobyl) and fallout from nuclear weapons testing. Our research has focused on developing biologically based models that explain the shape of dose-response curves for low-dose radiation and genotoxic chemical-induced stochastic effects in cells. Understanding the shape of the dose-response curve for radiation and genotoxic chemical-induced stochastic effects in cells helps to better understand the shape of the dose-response curve for cancer induction in humans. We have used a modeling approach that facilitated model revisions over time, allowing for timely incorporation of new knowledge gained related to the biological basis for low-dose-induced stochastic effects in cells. Both deleterious (e.g., genomic instability, mutations, and neoplastic transformation) and protective (e.g., DNA repair and apoptosis) effects have been included in our modeling. Our most advanced model, NEOTRANS2, involves differing levels of genomic instability. Persistent genomic instability is presumed to be associated with nonspecific, nonlethal mutations and to increase both the risk for neoplastic transformation and for cancer occurrence. Our research results, based on
Stochastic properties of disturbed Elementary Cellular Automata
International Nuclear Information System (INIS)
Posiewnik, M.
2005-01-01
Cellular automata are class of simple mathematical systems that generate diverse, often complicated behaviour. Evolution of such a system is given by set of local and deterministic rules. However, in spite of simplicity of 'interactions' it's global behaviour can't be, in general, simply predicted or even can not be predicted in time shorter that time of it's strict evolution. We get as, a systems well known 1-dimensional, Wolfram class automata, and connect it into the reservoir consists of some random source (noise). In our experiment we are interested in: a) numeric verification of ergodicity for such a coupled system. b) finding it's probability distribution and evolution. c) finding some analogous for 'real' quantities and behaviour. d) using the dynamical systems and Markov chains theory to describe the system, and to make any predictions of it's behaviour. (author)
Stochastic Model of Vesicular Sorting in Cellular Organelles
Vagne, Quentin; Sens, Pierre
2018-02-01
The proper sorting of membrane components by regulated exchange between cellular organelles is crucial to intracellular organization. This process relies on the budding and fusion of transport vesicles, and should be strongly influenced by stochastic fluctuations, considering the relatively small size of many organelles. We identify the perfect sorting of two membrane components initially mixed in a single compartment as a first passage process, and we show that the mean sorting time exhibits two distinct regimes as a function of the ratio of vesicle fusion to budding rates. Low ratio values lead to fast sorting but result in a broad size distribution of sorted compartments dominated by small entities. High ratio values result in two well-defined sorted compartments but sorting is exponentially slow. Our results suggest an optimal balance between vesicle budding and fusion for the rapid and efficient sorting of membrane components and highlight the importance of stochastic effects for the steady-state organization of intracellular compartments.
Handover management in dense cellular networks: A stochastic geometry approach
Arshad, Rabe; Elsawy, Hesham; Sorour, Sameh; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2016-01-01
Cellular operators are continuously densifying their networks to cope with the ever-increasing capacity demand. Furthermore, an extreme densification phase for cellular networks is foreseen to fulfill the ambitious fifth generation (5G) performance requirements. Network densification improves spectrum utilization and network capacity by shrinking base stations' (BSs) footprints and reusing the same spectrum more frequently over the spatial domain. However, network densification also increases the handover (HO) rate, which may diminish the capacity gains for mobile users due to HO delays. In highly dense 5G cellular networks, HO delays may neutralize or even negate the gains offered by network densification. In this paper, we present an analytical paradigm, based on stochastic geometry, to quantify the effect of HO delay on the average user rate in cellular networks. To this end, we propose a flexible handover scheme to reduce HO delay in case of highly dense cellular networks. This scheme allows skipping the HO procedure with some BSs along users' trajectories. The performance evaluation and testing of this scheme for only single HO skipping shows considerable gains in many practical scenarios. © 2016 IEEE.
Handover management in dense cellular networks: A stochastic geometry approach
Arshad, Rabe
2016-07-26
Cellular operators are continuously densifying their networks to cope with the ever-increasing capacity demand. Furthermore, an extreme densification phase for cellular networks is foreseen to fulfill the ambitious fifth generation (5G) performance requirements. Network densification improves spectrum utilization and network capacity by shrinking base stations\\' (BSs) footprints and reusing the same spectrum more frequently over the spatial domain. However, network densification also increases the handover (HO) rate, which may diminish the capacity gains for mobile users due to HO delays. In highly dense 5G cellular networks, HO delays may neutralize or even negate the gains offered by network densification. In this paper, we present an analytical paradigm, based on stochastic geometry, to quantify the effect of HO delay on the average user rate in cellular networks. To this end, we propose a flexible handover scheme to reduce HO delay in case of highly dense cellular networks. This scheme allows skipping the HO procedure with some BSs along users\\' trajectories. The performance evaluation and testing of this scheme for only single HO skipping shows considerable gains in many practical scenarios. © 2016 IEEE.
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.
Unified Stochastic Geometry Model for MIMO Cellular Networks with Retransmissions
Afify, Laila H.; Elsawy, Hesham; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2016-01-01
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.
Error performance analysis in K-tier uplink cellular networks using a stochastic geometric approach
Afify, Laila H.
2015-09-14
In this work, we develop an analytical paradigm to analyze the average symbol error probability (ASEP) performance of uplink traffic in a multi-tier cellular network. The analysis is based on the recently developed Equivalent-in-Distribution approach that utilizes stochastic geometric tools to account for the network geometry in the performance characterization. Different from the other stochastic geometry models adopted in the literature, the developed analysis accounts for important communication system parameters and goes beyond signal-to-interference-plus-noise ratio characterization. That is, the presented model accounts for the modulation scheme, constellation type, and signal recovery techniques to model the ASEP. To this end, we derive single integral expressions for the ASEP for different modulation schemes due to aggregate network interference. Finally, all theoretical findings of the paper are verified via Monte Carlo simulations.
Gharbieh, Mohammad; Elsawy, Hesham; Bader, Ahmed; Alouini, Mohamed-Slim
2017-01-01
The Internet of Things (IoT) is large-scale by nature, which is manifested by the massive number of connected devices as well as their vast spatial existence. Cellular networks, which provide ubiquitous, reliable, and efficient wireless access, will play fundamental rule in delivering the first-mile access for the data tsunami to be generated by the IoT. However, cellular networks may have scalability problems to provide uplink connectivity to massive numbers of connected things. To characterize the scalability of cellular uplink in the context of IoT networks, this paper develops a traffic-aware spatiotemporal mathematical model for IoT devices supported by cellular uplink connectivity. The developed model is based on stochastic geometry and queueing theory to account for the traffic requirement per IoT device, the different transmission strategies, and the mutual interference between the IoT devices. To this end, the developed model is utilized to characterize the extent to which cellular networks can accommodate IoT traffic as well as to assess and compare three different transmission strategies that incorporate a combination of transmission persistency, backoff, and power-ramping. The analysis and the results clearly illustrate the scalability problem imposed by IoT on cellular network and offer insights into effective scenarios for each transmission strategy.
Gharbieh, Mohammad
2017-05-02
The Internet of Things (IoT) is large-scale by nature, which is manifested by the massive number of connected devices as well as their vast spatial existence. Cellular networks, which provide ubiquitous, reliable, and efficient wireless access, will play fundamental rule in delivering the first-mile access for the data tsunami to be generated by the IoT. However, cellular networks may have scalability problems to provide uplink connectivity to massive numbers of connected things. To characterize the scalability of cellular uplink in the context of IoT networks, this paper develops a traffic-aware spatiotemporal mathematical model for IoT devices supported by cellular uplink connectivity. The developed model is based on stochastic geometry and queueing theory to account for the traffic requirement per IoT device, the different transmission strategies, and the mutual interference between the IoT devices. To this end, the developed model is utilized to characterize the extent to which cellular networks can accommodate IoT traffic as well as to assess and compare three different transmission strategies that incorporate a combination of transmission persistency, backoff, and power-ramping. The analysis and the results clearly illustrate the scalability problem imposed by IoT on cellular network and offer insights into effective scenarios for each transmission strategy.
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
Error performance analysis in K-tier uplink cellular networks using a stochastic geometric approach
Afify, Laila H.; Elsawy, Hesham; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2015-01-01
-in-Distribution approach that utilizes stochastic geometric tools to account for the network geometry in the performance characterization. Different from the other stochastic geometry models adopted in the literature, the developed analysis accounts for important
Stochastic, weighted hit size theory of cellular radiobiological action
International Nuclear Information System (INIS)
Bond, V.P.; Varma, M.N.
1982-01-01
A stochastic theory that appears to account well for the observed responses of cell populations exposed in radiation fields of different qualities and for different durations of exposure is described. The theory appears to explain well most cellular radiobiological phenomena observed in at least autonomous cell systems, argues for the use of fluence rate (phi) instead of absorbed dose for quantification of the amount of radiation involved in low level radiation exposure. With or without invoking the cell sensitivity function, the conceptual improvement would be substantial. The approach suggested also shows that the absorbed dose-cell response functions currently employed do not reflect the spectrum of cell sensitivities to increasing cell doses of a single agent, nor can RBE represent the potency ratio for different agents that can produce similar quantal responses. Thus, for accurate comparison of cell sensitivities among different cells in the same individual, or between the cells in different kinds of individuals, it is necessary to quantify cell sensitivity in terms of the hit size weighting or cell sensitivity function introduced here. Similarly, this function should be employed to evaluate the relative potency of radiation and other radiomimetic chemical or physical agents
Modeling and Analysis of Cellular Networks using Stochastic Geometry: A Tutorial
Elsawy, Hesham; Salem, Ahmed Sultan; Alouini, Mohamed-Slim; Win, Moe Z.
2016-01-01
This paper presents a tutorial on stochastic geometry (SG) based analysis for cellular networks. This tutorial is distinguished by its depth with respect to wireless communication details and its focus on cellular networks. The paper starts by modeling and analyzing the baseband interference in a baseline single-tier downlink cellular network with single antenna base stations and universal frequency reuse. Then, it characterizes signal-to-interference-plus-noise-ratio (SINR) and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and transmission rate analysis is presented. Although the main focus of the paper is on cellular networks, the presented unified approach applies for other types of wireless networks that impose interference protection around receivers. The paper then extends the unified approach to capture cellular network characteristics (e.g., frequency reuse, multiple antenna, power control, etc.). It also presents numerical examples associated with demonstrations and discussions. To this end, the paper highlights the state-of-the- art research and points out future research directions.
Modeling and Analysis of Cellular Networks using Stochastic Geometry: A Tutorial
Elsawy, Hesham
2016-11-03
This paper presents a tutorial on stochastic geometry (SG) based analysis for cellular networks. This tutorial is distinguished by its depth with respect to wireless communication details and its focus on cellular networks. The paper starts by modeling and analyzing the baseband interference in a baseline single-tier downlink cellular network with single antenna base stations and universal frequency reuse. Then, it characterizes signal-to-interference-plus-noise-ratio (SINR) and its related performance metrics. In particular, a unified approach to conduct error probability, outage probability, and transmission rate analysis is presented. Although the main focus of the paper is on cellular networks, the presented unified approach applies for other types of wireless networks that impose interference protection around receivers. The paper then extends the unified approach to capture cellular network characteristics (e.g., frequency reuse, multiple antenna, power control, etc.). It also presents numerical examples associated with demonstrations and discussions. To this end, the paper highlights the state-of-the- art research and points out future research directions.
Elsawy, Hesham; Hossain, Ekram
2014-01-01
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
Using stochastic cell division and death to probe minimal units of cellular replication
Chib, Savita; Das, Suman; Venkatesan, Soumya; Sai Narain Seshasayee, Aswin; Thattai, Mukund
2018-03-01
The invariant cell initiation mass measured in bacterial growth experiments has been interpreted as a minimal unit of cellular replication. Here we argue that the existence of such minimal units induces a coupling between the rates of stochastic cell division and death. To probe this coupling we tracked live and dead cells in Escherichia coli populations treated with a ribosome-targeting antibiotic. We find that the growth exponent from macroscopic cell growth or decay measurements can be represented as the difference of microscopic first-order cell division and death rates. The boundary between cell growth and decay, at which the number of live cells remains constant over time, occurs at the minimal inhibitory concentration (MIC) of the antibiotic. This state appears macroscopically static but is microscopically dynamic: division and death rates exactly cancel at MIC but each is remarkably high, reaching 60% of the antibiotic-free division rate. A stochastic model of cells as collections of minimal replicating units we term ‘widgets’ reproduces both steady-state and transient features of our experiments. Sub-cellular fluctuations of widget numbers stochastically drive each new daughter cell to one of two alternate fates, division or death. First-order division or death rates emerge as eigenvalues of a stationary Markov process, and can be expressed in terms of the widget’s molecular properties. High division and death rates at MIC arise due to low mean and high relative fluctuations of widget number. Isolating cells at the threshold of irreversible death might allow molecular characterization of this minimal replication unit.
International Nuclear Information System (INIS)
Huang Zaitang; Yang Qigui
2009-01-01
The paper considers the problems of existence of quadratic mean almost periodic and global exponential stability for stochastic cellular neural networks with delays. By employing the Holder's inequality and fixed points principle, we present some new criteria ensuring existence and uniqueness of a quadratic mean almost periodic and global exponential stability. These criteria are important in signal processing and the design of networks. Moreover, these criteria are also applied in others stochastic biological neural systems.
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.
Stochastic processes, multiscale modeling, and numerical methods for computational cellular biology
2017-01-01
This book focuses on the modeling and mathematical analysis of stochastic dynamical systems along with their simulations. The collected chapters will review fundamental and current topics and approaches to dynamical systems in cellular biology. This text aims to develop improved mathematical and computational methods with which to study biological processes. At the scale of a single cell, stochasticity becomes important due to low copy numbers of biological molecules, such as mRNA and proteins that take part in biochemical reactions driving cellular processes. When trying to describe such biological processes, the traditional deterministic models are often inadequate, precisely because of these low copy numbers. This book presents stochastic models, which are necessary to account for small particle numbers and extrinsic noise sources. The complexity of these models depend upon whether the biochemical reactions are diffusion-limited or reaction-limited. In the former case, one needs to adopt the framework of s...
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.
Almost sure exponential stability of stochastic fuzzy cellular neural networks with delays
International Nuclear Information System (INIS)
Zhao Hongyong; Ding Nan; Chen Ling
2009-01-01
This paper is concerned with the problem of exponential stability analysis for fuzzy cellular neural network with delays. By constructing suitable Lyapunov functional and using stochastic analysis we present some sufficient conditions ensuring almost sure exponential stability for the network. Moreover, an example is given to demonstrate the advantages of our method.
Characterizing heterogeneous cellular responses to perturbations.
Slack, Michael D; Martinez, Elisabeth D; Wu, Lani F; Altschuler, Steven J
2008-12-09
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.
A new stochastic cellular automaton model on traffic flow and its jamming phase transition
International Nuclear Information System (INIS)
Sakai, Satoshi; Nishinari, Katsuhiro; Iida, Shinji
2006-01-01
A general stochastic traffic cellular automaton (CA) model, which includes the slow-to-start effect and driver's perspective, is proposed in this paper. It is shown that this model includes well-known traffic CA models such as the Nagel-Schreckenberg model, the quick-start model and the slow-to-start model as specific cases. Fundamental diagrams of this new model clearly show metastable states around the critical density even when the stochastic effect is present. We also obtain analytic expressions of the phase transition curve in phase diagrams by using approximate flow-density relations at boundaries. These phase transition curves are in excellent agreement with numerical results
On the distribution and mean of received power in stochastic cellular network
Cao, Fengming; Ganesh, Ayalvadi; Armour, Simon; Sooriyabandara, Mahesh
2016-01-01
This paper exploits the distribution and mean of received power for cellular network with stochastic network modeling to study the difference between the two cell association criteria, i.e. the strongest received power based cell association and the closest distance based cell association. Consequently we derive the analytical expression of the distribution and the mean of the nth strongest received power and the received power from the nth nearest base station and the derivations have been c...
Bridging time scales in cellular decision making with a stochastic bistable switch
Directory of Open Access Journals (Sweden)
Waldherr Steffen
2010-08-01
Full Text Available Abstract Background Cellular transformations which involve a significant phenotypical change of the cell's state use bistable biochemical switches as underlying decision systems. Some of these transformations act over a very long time scale on the cell population level, up to the entire lifespan of the organism. Results In this work, we aim at linking cellular decisions taking place on a time scale of years to decades with the biochemical dynamics in signal transduction and gene regulation, occuring on a time scale of minutes to hours. We show that a stochastic bistable switch forms a viable biochemical mechanism to implement decision processes on long time scales. As a case study, the mechanism is applied to model the initiation of follicle growth in mammalian ovaries, where the physiological time scale of follicle pool depletion is on the order of the organism's lifespan. We construct a simple mathematical model for this process based on experimental evidence for the involved genetic mechanisms. Conclusions Despite the underlying stochasticity, the proposed mechanism turns out to yield reliable behavior in large populations of cells subject to the considered decision process. Our model explains how the physiological time constant may emerge from the intrinsic stochasticity of the underlying gene regulatory network. Apart from ovarian follicles, the proposed mechanism may also be of relevance for other physiological systems where cells take binary decisions over a long time scale.
Pseudo-stochastic signal characterization in wavelet-domain
International Nuclear Information System (INIS)
Zaytsev, Kirill I; Zhirnov, Andrei A; Alekhnovich, Valentin I; Yurchenko, Stanislav O
2015-01-01
In this paper we present the method for fast and accurate characterization of pseudo-stochastic signals, which contain a large number of similar but randomly-located fragments. This method allows estimating the statistical characteristics of pseudo-stochastic signal, and it is based on digital signal processing in wavelet-domain. Continuous wavelet transform and the criterion for wavelet scale power density are utilized. We are experimentally implementing this method for the purpose of sand granulometry, and we are estimating the statistical parameters of test sand fractions
Stochastic microstructure characterization and reconstruction via supervised learning
International Nuclear Information System (INIS)
Bostanabad, Ramin; Bui, Anh Tuan; Xie, Wei; Apley, Daniel W.; Chen, Wei
2016-01-01
Microstructure characterization and reconstruction have become indispensable parts of computational materials science. The main contribution of this paper is to introduce a general methodology for practical and efficient characterization and reconstruction of stochastic microstructures based on supervised learning. The methodology is general in that it can be applied to a broad range of microstructures (clustered, porous, and anisotropic). By treating the digitized microstructure image as a set of training data, we generically learn the stochastic nature of the microstructure via fitting a supervised learning model to it (we focus on classification trees). The fitted supervised learning model provides an implicit characterization of the joint distribution of the collection of pixel phases in the image. Based on this characterization, we propose two different approaches to efficiently reconstruct any number of statistically equivalent microstructure samples. We test the approach on five examples and show that the spatial dependencies within the microstructures are well preserved, as evaluated via correlation and lineal-path functions. The main advantages of our approach stem from having a compact empirically-learned model that characterizes the stochastic nature of the microstructure, which not only makes reconstruction more computationally efficient than existing methods, but also provides insight into morphological complexity.
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.
Directory of Open Access Journals (Sweden)
Khairul Salleh Basaruddin
Full Text Available Randomness in the microstructure due to variations in microscopic properties and geometrical information is used to predict the stochastically homogenised properties of cellular media. Two stochastic problems at the micro-scale level that commonly occur due to fabrication inaccuracies, degradation mechanisms or natural heterogeneity were analysed using a stochastic homogenisation method based on a first-order perturbation. First, the influence of Young's modulus variation in an adhesive on the macroscopic properties of an aluminium-adhesive honeycomb structure was investigated. The fluctuations in the microscopic properties were then combined by varying the microstructure periodicity in a corrugated-core sandwich plate to obtain the variation of the homogenised property. The numerical results show that the uncertainties in the microstructure affect the dispersion of the homogenised property. These results indicate the importance of the presented stochastic multi-scale analysis for the design and fabrication of cellular solids when considering microscopic random variation.
Barik, Debashis; Ball, David A; Peccoud, Jean; Tyson, John J
2016-12-01
The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs) and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization) of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally.
Directory of Open Access Journals (Sweden)
Debashis Barik
2016-12-01
Full Text Available The cell division cycle of eukaryotes is governed by a complex network of cyclin-dependent protein kinases (CDKs and auxiliary proteins that govern CDK activities. The control system must function reliably in the context of molecular noise that is inevitable in tiny yeast cells, because mistakes in sequencing cell cycle events are detrimental or fatal to the cell or its progeny. To assess the effects of noise on cell cycle progression requires not only extensive, quantitative, experimental measurements of cellular heterogeneity but also comprehensive, accurate, mathematical models of stochastic fluctuations in the CDK control system. In this paper we provide a stochastic model of the budding yeast cell cycle that accurately accounts for the variable phenotypes of wild-type cells and more than 20 mutant yeast strains simulated in different growth conditions. We specifically tested the role of feedback regulations mediated by G1- and SG2M-phase cyclins to minimize the noise in cell cycle progression. Details of the model are informed and tested by quantitative measurements (by fluorescence in situ hybridization of the joint distributions of mRNA populations in yeast cells. We use the model to predict the phenotypes of ~30 mutant yeast strains that have not yet been characterized experimentally.
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...
Garijo, N; Manzano, R; Osta, R; Perez, M A
2012-12-07
Cell migration and proliferation has been modelled in the literature as a process similar to diffusion. However, using diffusion models to simulate the proliferation and migration of cells tends to create a homogeneous distribution in the cell density that does not correlate to empirical observations. In fact, the mechanism of cell dispersal is not diffusion. Cells disperse by crawling or proliferation, or are transported in a moving ﬂuid. The use of cellular automata, particle models or cell-based models can overcome this limitation. This paper presents a stochastic cellular automata model to simulate the proliferation, migration and differentiation of cells. These processes are considered as completely stochastic as well as discrete. The model developed was applied to predict the behaviour of in vitro cell cultures performed with adult muscle satellite cells. Moreover, non homogeneous distribution of cells has been observed inside the culture well and, using the above mentioned stochastic cellular automata model, we have been able to predict this heterogeneous cell distribution and compute accurate quantitative results. Differentiation was also incorporated into the computational simulation. The results predicted the myotube formation that typically occurs with adult muscle satellite cells. In conclusion, we have shown how a stochastic cellular automata model can be implemented and is capable of reproducing the in vitro behaviour of adult muscle satellite cells. Copyright © 2012 Elsevier Ltd. All rights reserved.
Modeling Cellular Networks with Full Duplex D2D Communication: A Stochastic Geometry Approach
Ali, Konpal S.
2016-08-24
Full-duplex (FD) communication is optimistically promoted to double the spectral efficiency if sufficient self-interference cancellation (SIC) is achieved. However, this is not true when deploying FD-communication in a large-scale setup due to the induced mutual interference. Therefore, a large-scale study is necessary to draw legitimate conclusions about gains associated with FD-communication. This paper studies the FD operation for underlay device-to-device (D2D) communication sharing the uplink resources in cellular networks. We propose a disjoint fine-tuned selection criterion for the D2D and FD modes of operation. Then, we develop a tractable analytical paradigm, based on stochastic geometry, to calculate the outage probability and rate for cellular and D2D users. The results reveal that even in the case of perfect SIC, due to the increased interference injected to the network by FD-D2D communication, having all proximity UEs transmit in FD-D2D is not beneficial for the network. However, if the system parameters are carefully tuned, non-trivial network spectral-efficiency gains (64% shown) can be harvested. We also investigate the effects of imperfect SIC and D2D-link distance distribution on the harvested FD gains.
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.
Chen, Po-Wei; Chen, Bor-Sen
2011-08-01
Naturally, a cellular network consisted of a large amount of interacting cells is complex. These cells have to be synchronized in order to emerge their phenomena for some biological purposes. However, the inherently stochastic intra and intercellular interactions are noisy and delayed from biochemical processes. In this study, a robust synchronization scheme is proposed for a nonlinear stochastic time-delay coupled cellular network (TdCCN) in spite of the time-varying process delay and intracellular parameter perturbations. Furthermore, a nonlinear stochastic noise filtering ability is also investigated for this synchronized TdCCN against stochastic intercellular and environmental disturbances. Since it is very difficult to solve a robust synchronization problem with the Hamilton-Jacobi inequality (HJI) matrix, a linear matrix inequality (LMI) is employed to solve this problem via the help of a global linearization method. Through this robust synchronization analysis, we can gain a more systemic insight into not only the robust synchronizability but also the noise filtering ability of TdCCN under time-varying process delays, intracellular perturbations and intercellular disturbances. The measures of robustness and noise filtering ability of a synchronized TdCCN have potential application to the designs of neuron transmitters, on-time mass production of biochemical molecules, and synthetic biology. Finally, a benchmark of robust synchronization design in Escherichia coli repressilators is given to confirm the effectiveness of the proposed methods. Copyright © 2011 Elsevier Inc. All rights reserved.
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.
Learning-based stochastic object models for characterizing anatomical variations
Dolly, Steven R.; Lou, Yang; Anastasio, Mark A.; Li, Hua
2018-03-01
It is widely known that the optimization of imaging systems based on objective, task-based measures of image quality via computer-simulation requires the use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in human anatomy within a specified ensemble of patients remains a challenging task. Previously reported numerical anatomic models lack the ability to accurately model inter-patient and inter-organ variations in human anatomy among a broad patient population, mainly because they are established on image data corresponding to a few of patients and individual anatomic organs. This may introduce phantom-specific bias into computer-simulation studies, where the study result is heavily dependent on which phantom is used. In certain applications, however, databases of high-quality volumetric images and organ contours are available that can facilitate this SOM development. In this work, a novel and tractable methodology for learning a SOM and generating numerical phantoms from a set of volumetric training images is developed. The proposed methodology learns geometric attribute distributions (GAD) of human anatomic organs from a broad patient population, which characterize both centroid relationships between neighboring organs and anatomic shape similarity of individual organs among patients. By randomly sampling the learned centroid and shape GADs with the constraints of the respective principal attribute variations learned from the training data, an ensemble of stochastic objects can be created. The randomness in organ shape and position reflects the learned variability of human anatomy. To demonstrate the methodology, a SOM of an adult male pelvis is computed and examples of corresponding numerical phantoms are created.
Characterizing economic trends by Bayesian stochastic model specifi cation search
Grassi, Stefano; Proietti, Tommaso
2010-01-01
We apply a recently proposed Bayesian model selection technique, known as stochastic model specification search, for characterising the nature of the trend in macroeconomic time series. We illustrate that the methodology can be quite successfully applied to discriminate between stochastic and deterministic trends. In particular, we formulate autoregressive models with stochastic trends components and decide on whether a specific feature of the series, i.e. the underlying level and/or the rate...
Stability analysis of stochastic delayed cellular neural networks by LMI approach
International Nuclear Information System (INIS)
Zhu Wenli; Hu Jin
2006-01-01
Some sufficient mean square exponential stability conditions for a class of stochastic DCNN model are obtained via the LMI approach. These conditions improve and generalize some existing global asymptotic stability conditions for DCNN model
Stochastic Geometric Coverage Analysis in mmWave Cellular Networks with a Realistic Channel Model
DEFF Research Database (Denmark)
Rebato, Mattia; Park, Jihong; Popovski, Petar
2017-01-01
Millimeter-wave (mmWave) bands have been attracting growing attention as a possible candidate for next-generation cellular networks, since the available spectrum is orders of magnitude larger than in current cellular allocations. To precisely design mmWave systems, it is important to examine mmWa...
In-Band α-Duplex Scheme for Cellular Networks: A Stochastic Geometry Approach
Alammouri, Ahmad; Elsawy, Hesham; Amin, Osama; Alouini, Mohamed-Slim
2016-01-01
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
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 ...
Stochastic modeling for dynamics of HIV-1 infection using cellular automata: A review.
Precharattana, Monamorn
2016-02-01
Recently, the description of immune response by discrete models has emerged to play an important role to study the problems in the area of human immunodeficiency virus type 1 (HIV-1) infection, leading to AIDS. As infection of target immune cells by HIV-1 mainly takes place in the lymphoid tissue, cellular automata (CA) models thus represent a significant step in understanding when the infected population is dispersed. Motivated by these, the studies of the dynamics of HIV-1 infection using CA in memory have been presented to recognize how CA have been developed for HIV-1 dynamics, which issues have been studied already and which issues still are objectives in future studies.
Cellular automata rule characterization and classification using texture descriptors
Machicao, Jeaneth; Ribas, Lucas C.; Scabini, Leonardo F. S.; Bruno, Odermir M.
2018-05-01
The cellular automata (CA) spatio-temporal patterns have attracted the attention from many researchers since it can provide emergent behavior resulting from the dynamics of each individual cell. In this manuscript, we propose an approach of texture image analysis to characterize and classify CA rules. The proposed method converts the CA spatio-temporal patterns into a gray-scale image. The gray-scale is obtained by creating a binary number based on the 8-connected neighborhood of each dot of the CA spatio-temporal pattern. We demonstrate that this technique enhances the CA rule characterization and allow to use different texture image analysis algorithms. Thus, various texture descriptors were evaluated in a supervised training approach aiming to characterize the CA's global evolution. Our results show the efficiency of the proposed method for the classification of the elementary CA (ECAs), reaching a maximum of 99.57% of accuracy rate according to the Li-Packard scheme (6 classes) and 94.36% for the classification of the 88 rules scheme. Moreover, within the image analysis context, we found a better performance of the method by means of a transformation of the binary states to a gray-scale.
Mechanical characterization of disordered and anisotropic cellular monolayers
Nestor-Bergmann, Alexander; Johns, Emma; Woolner, Sarah; Jensen, Oliver E.
2018-05-01
We consider a cellular monolayer, described using a vertex-based model, for which cells form a spatially disordered array of convex polygons that tile the plane. Equilibrium cell configurations are assumed to minimize a global energy defined in terms of cell areas and perimeters; energy is dissipated via dynamic area and length changes, as well as cell neighbor exchanges. The model captures our observations of an epithelium from a Xenopus embryo showing that uniaxial stretching induces spatial ordering, with cells under net tension (compression) tending to align with (against) the direction of stretch, but with the stress remaining heterogeneous at the single-cell level. We use the vertex model to derive the linearized relation between tissue-level stress, strain, and strain rate about a deformed base state, which can be used to characterize the tissue's anisotropic mechanical properties; expressions for viscoelastic tissue moduli are given as direct sums over cells. When the base state is isotropic, the model predicts that tissue properties can be tuned to a regime with high elastic shear resistance but low resistance to area changes, or vice versa.
Sensitivity-based research prioritization through stochastic characterization modeling
DEFF Research Database (Denmark)
Wender, Ben A.; Prado-Lopez, Valentina; Fantke, Peter
2018-01-01
to guide research efforts in data refinement and design of experiments for existing and emerging chemicals alike. This study presents a sensitivity-based approach for estimating toxicity characterization factors given high input data uncertainty and using the results to prioritize data collection according...
Characterization of ambient air pollution for stochastic health models
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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.
Characterization and reconstruction of 3D stochastic microstructures via supervised learning.
Bostanabad, R; Chen, W; Apley, D W
2016-12-01
The need for computational characterization and reconstruction of volumetric maps of stochastic microstructures for understanding the role of material structure in the processing-structure-property chain has been highlighted in the literature. Recently, a promising characterization and reconstruction approach has been developed where the essential idea is to convert the digitized microstructure image into an appropriate training dataset to learn the stochastic nature of the morphology by fitting a supervised learning model to the dataset. This compact model can subsequently be used to efficiently reconstruct as many statistically equivalent microstructure samples as desired. The goal of this paper is to build upon the developed approach in three major directions by: (1) extending the approach to characterize 3D stochastic microstructures and efficiently reconstruct 3D samples, (2) improving the performance of the approach by incorporating user-defined predictors into the supervised learning model, and (3) addressing potential computational issues by introducing a reduced model which can perform as effectively as the full model. We test the extended approach on three examples and show that the spatial dependencies, as evaluated via various measures, are well preserved in the reconstructed samples. © 2016 The Authors Journal of Microscopy © 2016 Royal Microscopical Society.
International Nuclear Information System (INIS)
Helton, Jon Craig; Davis, Freddie J.; Johnson, J.D.
2000-01-01
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
Characterizing cellular mechanical phenotypes with mechano-node-pore sensing
Kim, Junghyun; Han, Sewoon; Lei, Andy; Miyano, Masaru; Bloom, Jessica; Srivastava, Vasudha; Stampfer, Martha M.; Gartner, Zev J.; LaBarge, Mark A.; Sohn, Lydia L.
2018-01-01
The mechanical properties of cells change with their differentiation, chronological age, and malignant progression. Consequently, these properties may be useful label-free biomarkers of various functional or clinically relevant cell states. Here, we demonstrate mechano-node-pore sensing (mechano-NPS), a multi-parametric single-cell-analysis method that utilizes a four-terminal measurement of the current across a microfluidic channel to quantify simultaneously cell diameter, resistance to compressive deformation, transverse deformation under constant strain, and recovery time after deformation. We define a new parameter, the whole-cell deformability index (wCDI), which provides a quantitative mechanical metric of the resistance to compressive deformation that can be used to discriminate among different cell types. The wCDI and the transverse deformation under constant strain show malignant MCF-7 and A549 cell lines are mechanically distinct from non-malignant, MCF-10A and BEAS-2B cell lines, and distinguishes between cells treated or untreated with cytoskeleton-perturbing small molecules. We categorize cell recovery time, ΔTr, as instantaneous (ΔTr ~ 0 ms), transient (ΔTr ≤ 40ms), or prolonged (ΔTr > 40ms), and show that the composition of recovery types, which is a consequence of changes in cytoskeletal organization, correlates with cellular transformation. Through the wCDI and cell-recovery time, mechano-NPS discriminates between sub-lineages of normal primary human mammary epithelial cells with accuracy comparable to flow cytometry, but without antibody labeling. Mechano-NPS identifies mechanical phenotypes that distinguishes lineage, chronological age, and stage of malignant progression in human epithelial cells. PMID:29780657
International Nuclear Information System (INIS)
Tung Wenwen; Qi Yan; Gao, J.B.; Cao Yinhe; Billings, Lora
2005-01-01
In recent years it has been increasingly recognized that noise and determinism may have comparable but different influences on population dynamics. However, no simple analysis methods have been introduced into ecology which can readily characterize those impacts. In this paper, we study a population model with strong periodicity and both with and without noise. The noise-free model generates both quasi-periodic and chaotic dynamics for certain parameter values. Due to the strong periodicity, however, the generated chaotic dynamics have not been satisfactorily described. The dynamics becomes even more complicated when there is noise. Characterizing the chaotic and stochastic dynamics in this model thus represents a challenging problem. Here we show how the chaotic dynamics can be readily characterized by the direct dynamical test for deterministic chaos developed by [Gao JB, Zheng ZM. Europhys. Lett. 1994;25:485] and how the influence of noise on quasi-periodic motions can be characterized as asymmetric diffusions wandering along the quasi-periodic orbit. It is hoped that the introduced methods will be useful in studying other population models as well as population time series obtained both in field and laboratory experiments
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.
International Nuclear Information System (INIS)
Ding Chaoliang; Lue Baida; Pan Liuzhan
2009-01-01
The unified theory of coherence and polarization proposed by Wolf is extended from stochastic stationary electromagnetic beams to stochastic spatially and spectrally partially coherent electromagnetic pulsed beams. Taking the stochastic electromagnetic Gaussian Schell-model pulsed (GSMP) beam as a typical example of stochastic spatially and spectrally partially coherent electromagnetic pulsed beams, the expressions for the spectral density, spectral degree of polarization and spectral degree of coherence of stochastic electromagnetic GSMP beams propagating in free space are derived. Some special cases are analyzed. The illustrative examples are given and the results are interpreted physically.
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.
A Stochastic Imaging Technique for Spatio-Spectral Characterization of Special Nuclear Material
Hamel, Michael C.
Radiation imaging is advantageous for detecting, locating and characterizing special nuclear material (SNM) in complex environments. A dual-particle imager (DPI) has been designed that is capable of detecting gamma-ray and neutron signatures from shielded SNM. The system combines liquid organic and NaI(Tl) scintillators to form a combined Compton and neutron scatter camera. Effective image reconstruction of detected particles is a crucial component for maximizing the performance of the system; however, a key deficiency exists in the widely used list-mode maximum-likelihood estimation-maximization (MLEM) image reconstruction technique. The steady-state solution produced by this iterative method will have poor quality compared to solutions produced with fewer iterations. A stopping condition is required to achieve a better solution but these conditions fail to achieve maximum image quality. Stochastic origin ensembles (SOE) imaging is a good candidate to address this problem as it uses Markov chain Monte Carlo to reach a stochastic steady-state solution that has image quality comparable to the best MLEM solution. The application of SOE to the DPI is presented in this work. SOE was originally applied in medical imaging applications with no mechanism to isolate spectral information based on location. This capability is critical for non-proliferation applications as complex radiation environments with multiple sources are often encountered. This dissertation extends the SOE algorithm to produce spatially dependent spectra and presents experimental result showing that the technique was effective for isolating a 4.1-kg mass of weapons grade plutonium (WGPu) when other neutron and gamma-ray sources were present. This work also demonstrates the DPI as an effective tool for localizing and characterizing highly enriched uranium (HEU). A series of experiments were performed with the DPI using a deuterium-deuterium (DD) and deuterium-tritium (DT) neutron generator, as well as
VANROON, WMC; COPRAY, JCVM; HOGENESCH, RI; KEMA, [No Value; MEYER, EM; MOLENAAR, G; LUGARD, C; STAAL, MJ; GO, KG
The objective of this study was to develop an optimal dissection procedure for fetal porcine ventral mesencephalon (VM) grafts and to characterize the cellular composition of such an explant, in particular with respect to the dopaminergic and GABAergic components. We have used a monolayer cell
Effect of crumb cellular structure characterized by image analysis on cake softness.
Dewaest, Marine; Villemejane, Cindy; Berland, Sophie; Neron, Stéphane; Clement, Jérôme; Verel, Aliette; Michon, Camille
2017-10-04
Sponge cake is a cereal product characterized by an aerated crumb and appreciated for its softness. When formulating such product, it is interesting to be able to characterize the crumb structure using image analysis and to bring knowledge about the effects of the crumb cellular structure on its mechanical properties which contribute to softness. An image analysis method based on mathematical morphology was adapted from the one developed for bread crumb. In order to evaluate its ability to discriminate cellular structures, series of cakes were prepared using two rather similar emulsifiers but also using flours with different aging times before use. The mechanical properties of the crumbs of these different cakes were also characterized. It allowed a cell structure classification taking into account cell size and homogeneity, but also cell wall thickness and the number of holes in the walls. Interestingly, the cellular structure differences had a larger impact on the aerated crumb Young modulus than the wall firmness. Increasing the aging time of flour before use leads to the production of firmer crumbs due to coarser and inhomogeneous cellular structures. Changing the composition of the emulsifier may change the cellular structure and, depending on the type of the structural changes, have an impact on the firmness of the crumb. Cellular structure rather than cell wall firmness was found to impact cake crumb firmness. The new fast and automated tool for cake crumb structure analysis allows detecting quickly any change in cell size or homogeneity but also cell wall thickness and number of holes in the walls (openness degree). To obtain a softer crumb, it seems that options are to decrease the cell size and the cell wall thickness and/or to increase the openness degree. It is then possible to easily evaluate the effects of ingredients (flour composition, emulsifier …) or change in the process on the crumb structure and thus its softness. Moreover, this image
Characterization of humoral and cellular immune responses in patients with human papilloma virus
International Nuclear Information System (INIS)
Clares Pochet, Maria del Carmen; Ferrer Cosme, Belkis Maria; Dominguez Cardosa, Magda
2012-01-01
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
Sipahi, Rifat; Zupanc, Günther K H
2018-05-14
Neural stem and progenitor cells isolated from the central nervous system form, under specific culture conditions, clonal cell clusters known as neurospheres. The neurosphere assay has proven to be a powerful in vitro system to study the behavior of such cells and the development of their progeny. However, the theory of neurosphere growth has remained poorly understood. To overcome this limitation, we have, in the present paper, developed a cellular automata model, with which we examined the effects of proliferative potential, contact inhibition, cell death, and clearance of dead cells on growth rate, final size, and composition of neurospheres. Simulations based on this model indicated that the proliferative potential of the founder cell and its progenitors has a major influence on neurosphere size. On the other hand, contact inhibition of proliferation limits the final size, and reduces the growth rate, of neurospheres. The effect of this inhibition is particularly dramatic when a stem cell becomes encapsulated by differentiated or other non-proliferating cells, thereby suppressing any further mitotic division - despite the existing proliferative potential of the stem cell. Conversely, clearance of dead cells through phagocytosis is predicted to accelerate growth by reducing contact inhibition. A surprising prediction derived from our model is that cell death, while resulting in a decrease in growth rate and final size of neurospheres, increases the degree of differentiation of neurosphere cells. It is likely that the cellular automata model developed as part of the present investigation is applicable to the study of tissue growth in a wide range of systems. Copyright © 2018 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Miao, Hongchen; Sun, Yao; Zhou, Xilong; Li, Yingwei [LTCS and Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing 100871 (China); Li, Faxin, E-mail: lifaxin@pku.edu.cn [LTCS and Department of Mechanics and Engineering Science, College of Engineering, Peking University, Beijing 100871 (China); HEDPS and Center for Applied Physics and Technology, Peking University, Beijing (China)
2014-08-14
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 d{sub 33} 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)
Danyluk, S.S.
1979-01-01
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
Precharattana, Monamorn; Nokkeaw, Arthorn; Triampo, Wannapong; Triampo, Darapond; Lenbury, Yongwimon
2011-07-01
Acquired Immunodeficiency Syndrome (AIDS) is responsible for millions of deaths worldwide. To date, many drug treatment regimens have been applied to AIDS patients but none has resulted in a successful cure. This is mainly due to the fact that free HIV particles are frequently in mutation, and infected CD4(+) T cells normally reside in the lymphoid tissue where they cannot (so far) be eradicated. We present a stochastic cellular automaton (CA) model to computationally study what could be an alternative treatment, namely Leukapheresis (LCAP), to remove HIV infected leukocytes in the lymphoid tissue. We base our investigations on Monte Carlo computer simulations. Our major objective is to investigate how the number of infected CD4(+) T cells changes in response to LCAP during the short-time (weeks) and long-time (years) scales of HIV/AIDS progression in an infected individual. To achieve our goal, we analyze the time evolution of the CD4(+) T cell population in the lymphoid tissue (i.e., the lymph node) for HIV dynamics in treatment situations with various starting times and frequencies and under a no treatment condition. Our findings suggest that the effectiveness of the treatment depends mainly on the treatment starting time and the frequency of the LCAP. Other factors (e.g., the removal proportion, the treatment duration, and the state of removed cells) that likely influence disease progression are subjects for further investigation. Copyright © 2011 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Aldine R. Amiel
2015-12-01
Full Text Available Cnidarians, the extant sister group to bilateria, are well known for their impressive regenerative capacity. The sea anemone Nematostella vectensis is a well-established system for the study of development and evolution that is receiving increased attention for its regenerative capacity. Nematostella is able to regrow missing body parts within five to six days after its bisection, yet studies describing the morphological, cellular, and molecular events underlying this process are sparse and very heterogeneous in their experimental approaches. In this study, we lay down the basic framework to study oral regeneration in Nematostella vectensis. Using various imaging and staining techniques we characterize in detail the morphological, cellular, and global molecular events that define specific landmarks of this process. Furthermore, we describe in vivo assays to evaluate wound healing success and the initiation of pharynx reformation. Using our described landmarks for regeneration and in vivo assays, we analyze the effects of perturbing either transcription or cellular proliferation on the regenerative process. Interestingly, neither one of these experimental perturbations has major effects on wound closure, although they slightly delay or partially block it. We further show that while the inhibition of transcription blocks regeneration in a very early step, inhibiting cellular proliferation only affects later events such as pharynx reformation and tentacle elongation.
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. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Giona, Massimiliano; Brasiello, Antonio; Crescitelli, Silvestro
2017-07-01
We analyze the thermodynamic properties of stochastic differential equations driven by smooth Poisson-Kac fluctuations, and their convergence, in the Kac limit, towards Wiener-driven Langevin equations. Using a Markovian embedding of the stochastic work variable, it is proved that the Kac-limit convergence implies a Stratonovich formulation of the limit Langevin equations, in accordance with the Wong-Zakai theorem. Exact moment analysis applied to the case of a purely frictional system shows the occurrence of different regimes and crossover phenomena in the parameter space.
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
Kalies, Stefan; Keil, Sebastian; Sender, Sina; Hammer, Susanne C; Antonopoulos, Georgios C; Schomaker, Markus; Ripken, Tammo; Murua Escobar, Hugo; 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.
Park, Jong Seok; Aziz, Moez Karim; Li, Sensen; Chi, Taiyun; Grijalva, Sandra Ivonne; Sung, Jung Hoon; Cho, Hee Cheol; Wang, Hua
2018-02-01
This paper presents a fully integrated CMOS multimodality joint sensor/stimulator array with 1024 pixels for real-time holistic cellular characterization and drug screening. The proposed system consists of four pixel groups and four parallel signal-conditioning blocks. Every pixel group contains 16 × 16 pixels, and each pixel includes one gold-plated electrode, four photodiodes, and in-pixel circuits, within a pixel footprint. Each pixel supports real-time extracellular potential recording, optical detection, charge-balanced biphasic current stimulation, and cellular impedance measurement for the same cellular sample. The proposed system is fabricated in a standard 130-nm CMOS process. Rat cardiomyocytes are successfully cultured on-chip. Measured high-resolution optical opacity images, extracellular potential recordings, biphasic current stimulations, and cellular impedance images demonstrate the unique advantages of the system for holistic cell characterization and drug screening. Furthermore, this paper demonstrates the use of optical detection on the on-chip cultured cardiomyocytes to real-time track their cyclic beating pattern and beating rate.
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...
Litichevskiy, Lev; Peckner, Ryan; Abelin, Jennifer G; Asiedu, Jacob K; Creech, Amanda L; Davis, John F; Davison, Desiree; Dunning, Caitlin M; Egertson, Jarrett D; Egri, Shawn; Gould, Joshua; Ko, Tak; Johnson, Sarah A; Lahr, David L; Lam, Daniel; Liu, Zihan; Lyons, Nicholas J; Lu, Xiaodong; MacLean, Brendan X; Mungenast, Alison E; Officer, Adam; Natoli, Ted E; Papanastasiou, Malvina; Patel, Jinal; Sharma, Vagisha; Toder, Courtney; Tubelli, Andrew A; Young, Jennie Z; Carr, Steven A; Golub, Todd R; Subramanian, Aravind; MacCoss, Michael J; Tsai, Li-Huei; Jaffe, Jacob D
2018-04-25
Although the value of proteomics has been demonstrated, cost and scale are typically prohibitive, and gene expression profiling remains dominant for characterizing cellular responses to perturbations. However, high-throughput sentinel assays provide an opportunity for proteomics to contribute at a meaningful scale. We present a systematic library resource (90 drugs × 6 cell lines) of proteomic signatures that measure changes in the reduced-representation phosphoproteome (P100) and changes in epigenetic marks on histones (GCP). A majority of these drugs elicited reproducible signatures, but notable cell line- and assay-specific differences were observed. Using the "connectivity" framework, we compared signatures across cell types and integrated data across assays, including a transcriptional assay (L1000). Consistent connectivity among cell types revealed cellular responses that transcended lineage, and consistent connectivity among assays revealed unexpected associations between drugs. We further leveraged the resource against public data to formulate hypotheses for treatment of multiple myeloma and acute lymphocytic leukemia. This resource is publicly available at https://clue.io/proteomics. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.
Characterizing Protein Interactions Employing a Genome-Wide siRNA Cellular Phenotyping Screen
Suratanee, Apichat; Schaefer, Martin H.; Betts, Matthew J.; Soons, Zita; Mannsperger, Heiko; Harder, Nathalie; Oswald, Marcus; Gipp, Markus; Ramminger, Ellen; Marcus, Guillermo; Männer, Reinhard; Rohr, Karl; Wanker, Erich; Russell, Robert B.; Andrade-Navarro, Miguel A.; Eils, Roland; König, Rainer
2014-01-01
Characterizing the activating and inhibiting effect of protein-protein interactions (PPI) is fundamental to gain insight into the complex signaling system of a human cell. A plethora of methods has been suggested to infer PPI from data on a large scale, but none of them is able to characterize the effect of this interaction. Here, we present a novel computational development that employs mitotic phenotypes of a genome-wide RNAi knockdown screen and enables identifying the activating and inhibiting effects of PPIs. Exemplarily, we applied our technique to a knockdown screen of HeLa cells cultivated at standard conditions. Using a machine learning approach, we obtained high accuracy (82% AUC of the receiver operating characteristics) by cross-validation using 6,870 known activating and inhibiting PPIs as gold standard. We predicted de novo unknown activating and inhibiting effects for 1,954 PPIs in HeLa cells covering the ten major signaling pathways of the Kyoto Encyclopedia of Genes and Genomes, and made these predictions publicly available in a database. We finally demonstrate that the predicted effects can be used to cluster knockdown genes of similar biological processes in coherent subgroups. The characterization of the activating or inhibiting effect of individual PPIs opens up new perspectives for the interpretation of large datasets of PPIs and thus considerably increases the value of PPIs as an integrated resource for studying the detailed function of signaling pathways of the cellular system of interest. PMID:25255318
Isolation and Characterization of Lactic Acid Bacteria (LAB) Produced Exo cellular Polysaccharide
International Nuclear Information System (INIS)
Meleigy, S.A.; Hendawy, W.S.
2009-01-01
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 (IS 1 ), Lactococcus lactis ssp cremoris (IS 2 ) and Lactobacillus delbrueckii ssp bulgaricus (IS 3 ) 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 (IS 2 ), 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 (IS 2 ) 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
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.
Phenotypic characterization of the bone marrow stem cells used in regenerative cellular therapy
International Nuclear Information System (INIS)
Macias Abraham, Consuelo; Valle Perez, Lazaro O del; Baganet Cobas, Aymara
2011-01-01
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 +c ells in mononuclear cells from CD34 -/ CD45 -p eripheral 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 +c ells in peripheral blood stem cells with a low expression of molecules CD117 -a nd DR -s uggests the presence of hematopoietic stem cells, hemangioblasts and progenitor endothelial cells mobilized to peripheral circulation. It was found that mononuclear cells from both the BM and peripheral blood show a high presence of stem cells with expression of adhesion molecule CD44 (MMC marker), probably involved in their migration, settling and differentiation
Characterization of memory states of the Preisach operator with stochastic inputs
International Nuclear Information System (INIS)
Amann, A.; Brokate, M.; McCarthy, S.; Rachinskii, D.; Temnov, G.
2012-01-01
The Preisach operator with inputs defined by a Markov process x t is considered. The question we address is: what is the distribution of the random memory state of the Preisach operator at a given time moment t 0 in the limit r→∞ of infinitely long input history x t , t 0 -r≤t≤t 0 ? In order to answer this question, we introduce a Markov chain (called the memory state Markov chain) where the states are pairs (m k ,M k ) of elements from the monotone sequences of the local minimum input values m k and the local maximum input values M k recorded in the memory state and the index k of the elements plays the role of time. We express the transition probabilities of this Markov chain in terms of the transition probabilities of the input stochastic process and show that the memory state Markov chain and the input process generate the same distribution of the memory states. These results are illustrated by several examples of stochastic inputs such as the Wiener and Bernoulli processes and their mixture (we first discuss a discrete version of these processes and then the continuous time and state setting). The memory state Markov chain is then used to find the distribution of the random number of elements in the memory state sequence. We show that this number has the Poisson distribution for the Wiener and Bernoulli processes inputs. In particular, in the discrete setting, the mean value of the number of elements in the memory state scales as lnN, where N is the number of the input states, while the mean time it takes the input to generate this memory state scales as N 2 for the Wiener process and as N for the Bernoulli process. A similar relationship between the dimension of the memory state vector and the number of iterations in the numerical realization of the input is shown for the mixture of the Wiener and Bernoulli processes, thus confirming that the memory state Markov chain is an efficient tool for generating the distribution of the Preisach operator memory
Characterization of memory states of the Preisach operator with stochastic inputs
Energy Technology Data Exchange (ETDEWEB)
Amann, A. [Department of Applied Mathematics, University College Cork (Ireland); Brokate, M. [Zentrum Mathematik, Technische Universitaet Muenchen (Germany); McCarthy, S. [Department of Applied Mathematics, University College Cork (Ireland); Rachinskii, D., E-mail: d.rachinskii@ucc.ie [Department of Applied Mathematics, University College Cork (Ireland); Temnov, G. [Department of Mathematics, University College Cork (Ireland)
2012-05-01
The Preisach operator with inputs defined by a Markov process x{sup t} is considered. The question we address is: what is the distribution of the random memory state of the Preisach operator at a given time moment t{sub 0} in the limit r{yields}{infinity} of infinitely long input history x{sup t}, t{sub 0}-r{<=}t{<=}t{sub 0}? In order to answer this question, we introduce a Markov chain (called the memory state Markov chain) where the states are pairs (m{sub k},M{sub k}) of elements from the monotone sequences of the local minimum input values m{sub k} and the local maximum input values M{sub k} recorded in the memory state and the index k of the elements plays the role of time. We express the transition probabilities of this Markov chain in terms of the transition probabilities of the input stochastic process and show that the memory state Markov chain and the input process generate the same distribution of the memory states. These results are illustrated by several examples of stochastic inputs such as the Wiener and Bernoulli processes and their mixture (we first discuss a discrete version of these processes and then the continuous time and state setting). The memory state Markov chain is then used to find the distribution of the random number of elements in the memory state sequence. We show that this number has the Poisson distribution for the Wiener and Bernoulli processes inputs. In particular, in the discrete setting, the mean value of the number of elements in the memory state scales as lnN, where N is the number of the input states, while the mean time it takes the input to generate this memory state scales as N{sup 2} for the Wiener process and as N for the Bernoulli process. A similar relationship between the dimension of the memory state vector and the number of iterations in the numerical realization of the input is shown for the mixture of the Wiener and Bernoulli processes, thus confirming that the memory state Markov chain is an efficient tool for
Vorobiev, O.; Ezzedine, S. M.; Antoun, T.; Glenn, L.
2014-12-01
This work describes a methodology used for large scale modeling of wave propagation fromunderground explosions conducted at the Nevada Test Site (NTS) in two different geological settings:fractured granitic rock mass and in alluvium deposition. We show that the discrete nature of rockmasses as well as the spatial variability of the fabric of alluvium is very important to understand groundmotions induced by underground explosions. In order to build a credible conceptual model of thesubsurface we integrated the geological, geomechanical and geophysical characterizations conductedduring recent test at the NTS as well as historical data from the characterization during the undergroundnuclear test conducted at the NTS. Because detailed site characterization is limited, expensive and, insome instances, impossible we have numerically investigated the effects of the characterization gaps onthe overall response of the system. We performed several computational studies to identify the keyimportant geologic features specific to fractured media mainly the joints; and those specific foralluvium porous media mainly the spatial variability of geological alluvium facies characterized bytheir variances and their integral scales. We have also explored common key features to both geologicalenvironments such as saturation and topography and assess which characteristics affect the most theground motion in the near-field and in the far-field. Stochastic representation of these features based onthe field characterizations have been implemented in Geodyn and GeodynL hydrocodes. Both codeswere used to guide site characterization efforts in order to provide the essential data to the modelingcommunity. We validate our computational results by comparing the measured and computed groundmotion at various ranges. This work performed under the auspices of the U.S. Department of Energy by Lawrence LivermoreNational Laboratory under Contract DE-AC52-07NA27344.
Marin, E; Fusi, S; Pressacco, M; Paussa, L; Fedrizzi, L
2010-07-01
EBM (Electron Beam Melting) technology can be used successfully to obtain cellular solids in metallic biomaterials that can greatly increase osseointegration in arthroprothesis and at the same time maintain good mechanical properties. The investigated structures, called Trabecular Titanium, usually cannot be obtained by traditional machining. Two samples: (A) with a smaller single cell area and, (B) with a bigger single cell area, were produced and studied in this project. They have been completely characterized and compared with the results in similar literature pertinent to Ti6Al4V EBM structures. Relative density was evaluated using different methods, the mean diameter of the open porosities was calculated by Scanning Electron Microscope images; the composition was evaluated using Energy-Dispersive X-Ray Spectroscopy; the microstructure (alpha-beta) was investigated using chemical etching and, the mechanical proprieties were investigated using UMTS. The mean porosity values resulted comparable with spongy bone (63% for A and 72% for B). The mean diameter of the single porosity (650 mum for A and 1400 mum for B) resulted compatible with the osseointegration data from the literature, in particular for sample A. The Vickers micro-hardness tests and the chemical etching demonstrated that the structure is fine, uniform and well distributed. The mechanical test proved that sample (A) was more resistant than sample (B), but sample (B) showed an elastic modulus almost equal to the value of spongy bone. The results of this study suggest that the two Ti6Al4V cellular solids can be used in biomedical applications to promote osseointegration demonstrating that they maybe successfully used in prosthetic implants. Additional implant results will be published in the near future. Copyright 2010 Elsevier Ltd. All rights reserved.
A generalized cellular automata approach to modeling first order ...
Indian Academy of Sciences (India)
system, consisting of space, time and state, structured with simple local rules without ... Sensitivity analysis of a stochastic cellular automata model. 413 ..... Baetens J M and De Baets B 2011 Design and parameterization of a stochastic cellular.
A metric for characterizing the bistability of molecular quantum-dot cellular automata
International Nuclear Information System (INIS)
Lu Yuhui; Lent, Craig S
2008-01-01
Much of molecular electronics involves trying to use molecules as (a) wires, (b) diodes or (c) field-effect transistors. In each case the criterion for determining good performance is well known: for wires it is conductance, for diodes it is conductance asymmetry, while for transistors it is high transconductance. Candidate molecules can be screened in terms of these criteria by calculating molecular conductivity in forward and reverse directions, and in the presence of a gating field. Hence so much theoretical work has focused on understanding molecular conductance. In contrast a molecule used as a quantum-dot cellular automata (QCA) cell conducts no current at all. The keys to QCA functionality are (a) charge localization, (b) bistable charge switching within the cell and (c) electric field coupling between one molecular cell and its neighbor. The combination of these effects can be examined using the cell-cell response function which relates the polarization of one cell to the induced polarization of a neighboring cell. The response function can be obtained by calculating the molecular electronic structure with ab initio quantum chemistry techniques. We present an analysis of molecular QCA performance that can be applied to any candidate molecule. From the full quantum chemistry, all-electron ab initio calculations we extract parameters for a reduced-state model which reproduces the cell-cell response function very well. Techniques from electron transfer theory are used to derive analytical models of the response function and can be employed on molecules too large for full ab initio treatment. A metric is derived which characterizes molecular QCA performance the way transconductance characterizes transistor performance. This metric can be assessed from absorption measurements of the electron transfer band or quantum chemistry calculations of appropriate sophistication
International Nuclear Information System (INIS)
Regulus, P.
2006-10-01
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)
Cellular characterization of the peritumoral edema zone in malignant brain tumors
International Nuclear Information System (INIS)
Engelhorn, T.; Schwarz, M.A.; Savaskan, N.E.
2009-01-01
Brain edema is a hallmark of human malignant brain tumors and contributes to the clinical course and outcome of brain tumor patients. The so-called perifocal edema or brain swelling imposes in T2-weighted MR scans as high intensity areas surrounding the bulk tumor mass. The mechanisms of this increased fluid attraction and the cellular composition of the microenvironment are only partially understood. In this study, we focus on imaging perifocal edema in orthotopically implanted gliomas in rodents and correlate perifocal edema with immunohistochemical markers. We identified that areas of perifocal edema not only include the tumor invasion zone, but also are associated with increased glial fibrillary acidic protein (GFAP) and aquaporin-4 expression surrounding the bulk tumor mass. Moreover, a high number of activated microglial cells expressing CD11b and macrophage migration inhibitory factor (MIF) accumulate at the tumor border. Thus, the area of perifocal edema is mainly dominated by reactive changes of vital brain tissue. These data corroborate that perifocal edema identified in T2-weighted MR scans are characterized with alterations in glial cell distribution and marker expression forming an inflammatory tumor microenvironment. (author)
International Nuclear Information System (INIS)
Parab, Harshala J; Huang, Jing-Hong; Liu, Ru-Shi; Lai, Tsung-Ching; Jan, Yi-Hua; Wang, Jui-Ling; Hsiao, Michael; Chen, Chung-Hsuan; Hwu, Yeu-Kuang; Tsai, Din Ping; Chuang, Shih-Yi; Pang, Jong-Hwei S
2011-01-01
The feasibility of using gold nanoparticles (AuNPs) for biomedical applications has led to considerable interest in the development of novel synthetic protocols and surface modification strategies for AuNPs to produce biocompatible molecular probes. This investigation is, to our knowledge, the first to elucidate the synthesis and characterization of sodium hexametaphosphate (HMP)-stabilized gold nanoparticles (Au-HMP) in an aqueous medium. The role of HMP, a food additive, as a polymeric stabilizing and protecting agent for AuNPs is elucidated. The surface modification of Au-HMP nanoparticles was carried out using polyethylene glycol and transferrin to produce molecular probes for possible clinical applications. In vitro cell viability studies performed using as-synthesized Au-HMP nanoparticles and their surface-modified counterparts reveal the biocompatibility of the nanoparticles. The transferrin-conjugated nanoparticles have significantly higher cellular uptake in J5 cells (liver cancer cells) than control cells (oral mucosa fibroblast cells), as determined by inductively coupled plasma mass spectrometry. This study demonstrates the possibility of using an inexpensive and non-toxic food additive, HMP, as a stabilizer in the large-scale generation of biocompatible and monodispersed AuNPs, which may have future diagnostic and therapeutic applications.
Energy Technology Data Exchange (ETDEWEB)
Parab, Harshala J; Huang, Jing-Hong; Liu, Ru-Shi [Department of Chemistry, National Taiwan University, Taipei 106, Taiwan (China); Lai, Tsung-Ching; Jan, Yi-Hua; Wang, Jui-Ling; Hsiao, Michael; Chen, Chung-Hsuan [Genomics Research Center, Academia Sinica, Taipei 115, Taiwan (China); Hwu, Yeu-Kuang [Institute of Physics, Academia Sinica, Taipei 115, Taiwan (China); Tsai, Din Ping [Department of Physics, National Taiwan University, Taipei 106, Taiwan (China); Chuang, Shih-Yi; Pang, Jong-Hwei S, E-mail: rsliu@ntu.edu.tw, E-mail: mhsiao@gate.sinica.edu.tw [Graduate Institute of Clinical Medical Sciences, Chang Gung University, Tao-Yuan, Taiwan (China)
2011-09-30
The feasibility of using gold nanoparticles (AuNPs) for biomedical applications has led to considerable interest in the development of novel synthetic protocols and surface modification strategies for AuNPs to produce biocompatible molecular probes. This investigation is, to our knowledge, the first to elucidate the synthesis and characterization of sodium hexametaphosphate (HMP)-stabilized gold nanoparticles (Au-HMP) in an aqueous medium. The role of HMP, a food additive, as a polymeric stabilizing and protecting agent for AuNPs is elucidated. The surface modification of Au-HMP nanoparticles was carried out using polyethylene glycol and transferrin to produce molecular probes for possible clinical applications. In vitro cell viability studies performed using as-synthesized Au-HMP nanoparticles and their surface-modified counterparts reveal the biocompatibility of the nanoparticles. The transferrin-conjugated nanoparticles have significantly higher cellular uptake in J5 cells (liver cancer cells) than control cells (oral mucosa fibroblast cells), as determined by inductively coupled plasma mass spectrometry. This study demonstrates the possibility of using an inexpensive and non-toxic food additive, HMP, as a stabilizer in the large-scale generation of biocompatible and monodispersed AuNPs, which may have future diagnostic and therapeutic applications.
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...
Cellular automaton modeling of biological pattern formation characterization, examples, and analysis
Deutsch, Andreas
2017-01-01
This text explores the use of cellular automata in modeling pattern formation in biological systems. It describes several mathematical modeling approaches utilizing cellular automata that can be used to study the dynamics of interacting cell systems both in simulation and in practice. New in this edition are chapters covering cell migration, tissue development, and cancer dynamics, as well as updated references and new research topic suggestions that reflect the rapid development of the field. The book begins with an introduction to pattern-forming principles in biology and the various mathematical modeling techniques that can be used to analyze them. Cellular automaton models are then discussed in detail for different types of cellular processes and interactions, including random movement, cell migration, adhesive cell interaction, alignment and cellular swarming, growth processes, pigment cell pattern formation, tissue development, tumor growth and invasion, and Turing-type patterns and excitable media. In ...
Energy Technology Data Exchange (ETDEWEB)
Ameme, Dan Selorm Kwami [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Guttromson, Ross [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2017-10-01
This report characterizes communications network latency under various network topologies and qualities of service (QoS). The characterizations are probabilistic in nature, allowing deeper analysis of stability for Internet Protocol (IP) based feedback control systems used in grid applications. The work involves the use of Raspberry Pi computers as a proxy for a controlled resource, and an ns-3 network simulator on a Linux server to create an experimental platform (testbed) that can be used to model wide-area grid control network communications in smart grid. Modbus protocol is used for information transport, and Routing Information Protocol is used for dynamic route selection within the simulated network.
Phadungsil, Wansika; Smooker, Peter M; Vichasri-Grams, Suksiri; Grams, Rudi
2016-01-01
Even at the present age of whole-organism analysis, e.g., genomics, transcriptomics, and proteomics, the biological roles of many proteins remain unresolved. Classified among the proteins of unknown function is a family of proteins harboring repeats of the DM9 domain, a 60-75 amino acids motif first described in a small number of Drosophila melanogaster proteins. Proteins may carry two or more DM9 domains either in combination with other domains or as their sole constituent. Here we have characterized a 16.8 kDa Fasciola gigantica protein comprising two tandem repeated DM9 domains (FgDM9-1). The protein was located in the parenchyma of the immature and mature parasite and consequently it was not detected in the ES product of the parasite but only in the whole worm extract. Interestingly, extraction with SDS yielded a substantially higher amount of the protein suggesting association with insoluble cell components. In Sf9 insect cells a heterologously expressed EGFP-FgDM9-1 chimera showed cell-wide distribution but relocated to vesicle-like structures in the cytoplasm after stimulating cellular stress by bacteria, heat shock or chloroquine. These structures did not colocalize with the markers of endocytosis/phagocytosis ubiquitin, RAB7, GABARAP. The same behavior was noted for Aedes aegypti PRS1, a homologous mosquito DM9 protein as a positive control while EGFP did not exhibit such relocation in the insect cells. Cross-linking experiments on soluble recombinant FgDM9-1 indicated that the protein can undergo specific oligomerization. It is speculated that proteins carrying the DM9 domain have a role in vesicular transport in flatworms and insects. Copyright © 2016 Elsevier B.V. All rights reserved.
Directory of Open Access Journals (Sweden)
Frances S. Ligler
2008-06-01
Full Text Available We present a simplified, highly reproducible process to fabricate arrays of tapered silicon micro-funnels and micro-channels using a single lithographic step with a silicon oxide (SiO2 hard mask on at a wafer scale. Two approaches were used for the fabrication. The first one involves a single wet anisotropic etch step in concentrated potassium hydroxide (KOH and the second one is a combined approach comprising Deep Reactive Ion Etch (DRIE followed by wet anisotropic etching. The etching is performed through a 500 mm thick silicon wafer, and the resulting structures are characterized by sharp tapered ends with a sub-micron cross-sectional area at the tip. We discuss the influence of various parameters involved in the fabrication such as the size and thickness variability of the substrate, dry and wet anisotropic etching conditions, the etchant composition, temperature, diffusion and micro-masking effects, the quality of the hard mask in the uniformity and reproducibility of the structures, and the importance of a complete removal of debris and precipitates. The presence of apertures at the tip of the structures is corroborated through current voltage measurements and by the translocation of DNA through the apertures. The relevance of the results obtained in this report is discussed in terms of the potential use of these structures for stochastic sensing.
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
Flaw tolerance vs. performance: A tradeoff in metallic glass cellular structures
International Nuclear Information System (INIS)
Chen, Wen; Liu, Ze; Robinson, Hannah Mae; Schroers, Jan
2014-01-01
Stochastic cellular structures are prevalent in nature and engineering materials alike. They are difficult to manipulate and study systematically and almost always contain imperfections. To design and characterize various degrees of imperfections in perfect periodic, stochastic and natural cellular structures, we fabricate a broad range of metallic glass cellular structures from perfectly periodic to highly stochastic by using a novel artificial microstructure approach based on thermoplastic replication of metallic glasses. For these cellular structures, precisely controlled imperfections are implemented and their effects on the mechanical response are evaluated. It is found that the mechanical performance of the periodic structures is generally superior to that of the stochastic structures. However, the stochastic structures experience a much higher tolerance to flaws than the periodic structure, especially in the plastic regime. The different flaw tolerance is explained by the stress distribution within the various structures, which leads to an overall 'strain-hardening' behavior of the stochastic structure compared to a 'strain-softening' behavior in the periodic structure. Our findings reveal how structure, 'strain-hardening' and flaw tolerance are microscopically related in structural materials
International Nuclear Information System (INIS)
Ahmadi, Abdollah; Charwand, Mansour; Siano, Pierluigi; Nezhad, Ali Esmaeel; Sarno, Debora; Gitizadeh, Mohsen; Raeisi, Fatima
2016-01-01
In order to supply the demands of the end users in a competitive market, a distribution company purchases energy from the wholesale market while other options would be in access in the case of possessing distributed generation units and interruptible loads. In this regard, this study presents a two-stage stochastic programming model for a distribution company energy acquisition market model to manage the involvement of different electric energy resources characterized by uncertainties with the minimum cost. In particular, the distribution company operations planning over a day-ahead horizon is modeled as a stochastic mathematical optimization, with the objective of minimizing costs. By this, distribution company decisions on grid purchase, owned distributed generation units and interruptible load scheduling are determined. Then, these decisions are considered as boundary constraints to a second step, which deals with distribution company's operations in the hour-ahead market with the objective of minimizing the short-term cost. The uncertainties in spot market prices and wind speed are modeled by means of probability distribution functions of their forecast errors and the roulette wheel mechanism and lattice Monte Carlo simulation are used to generate scenarios. Numerical results show the capability of the proposed method. - Highlights: • Proposing a new a stochastic-based two-stage operations framework in retail competitive markets. • Proposing a Mixed Integer Non-Linear stochastic programming. • Employing roulette wheel mechanism and Lattice Monte Carlo Simulation.
Directory of Open Access Journals (Sweden)
Mario Muñoz-Organero
2017-01-01
Full Text Available The automatic detection of road related information using data from sensors while driving has many potential applications such as traffic congestion detection or automatic routable map generation. This paper focuses on the automatic detection of road elements based on GPS data from on-vehicle systems. A new algorithm is developed that uses the total variation distance instead of the statistical moments to improve the classification accuracy. The algorithm is validated for detecting traffic lights, roundabouts, and street-crossings in a real scenario and the obtained accuracy (0.75 improves the best results using previous approaches based on statistical moments based features (0.71. Each road element to be detected is characterized as a vector of speeds measured when a driver goes through it. We first eliminate the speed samples in congested traffic conditions which are not comparable with clear traffic conditions and would contaminate the dataset. Then, we calculate the probability mass function for the speed (in 1 m/s intervals at each point. The total variation distance is then used to find the similarity among different points of interest (which can contain a similar road element or a different one. Finally, a k-NN approach is used for assigning a class to each unlabelled element.
Evaluation of soil characterization technologies using a stochastic, value-of-information approach
International Nuclear Information System (INIS)
Kaplan, P.G.
1993-01-01
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
DEFF Research Database (Denmark)
Fernandez-Guerra, Paula
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...
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
Stochastic dynamics and irreversibility
Tomé, Tânia
2015-01-01
This textbook presents an exposition of stochastic dynamics and irreversibility. It comprises the principles of probability theory and the stochastic dynamics in continuous spaces, described by Langevin and Fokker-Planck equations, and in discrete spaces, described by Markov chains and master equations. Special concern is given to the study of irreversibility, both in systems that evolve to equilibrium and in nonequilibrium stationary states. Attention is also given to the study of models displaying phase transitions and critical phenomema both in thermodynamic equilibrium and out of equilibrium. These models include the linear Glauber model, the Glauber-Ising model, lattice models with absorbing states such as the contact process and those used in population dynamic and spreading of epidemic, probabilistic cellular automata, reaction-diffusion processes, random sequential adsorption and dynamic percolation. A stochastic approach to chemical reaction is also presented.The textbook is intended for students of ...
Nanomechanical and electrical characterization of a new cellular electret sensor-actuator
International Nuclear Information System (INIS)
Windmill, J F C; Zorab, A; Bedwell, D J; Robert, D
2008-01-01
Electrically charged cellular polymers are known to display pseudo-piezoelectric effects that endow them with interesting mechano-electrical characteristics. When a film of such a polymer is compressed, charge is generated across its thickness, and conversely, applying an oscillatory or static potential elicits mechanical motions. This dual sensor-actuator behaviour can be embedded in one material and presents distinct advantages of functional integration. A novel electroactive foam is presented here that embeds such a sensor-actuator function. The foam has a sensitivity constant (d 33 ) of 330 pC N -1 . Interestingly, the resonant behaviour of the cellular film can be altered by variation in the DC offset across the material. Such adaptive capacity could be of great advantage for tuning polymer-based mechanical devices to be either efficient sound radiators and mechanical actuators, or sensitive and coherent sensors. Possible applications in microfluidics are also discussed
Robba, Tiziana; Chianca, Vito; Albano, Domenico; Clementi, Valeria; Piana, Raimondo; Linari, Alessandra; Comandone, Alessandro; Regis, Guido; Stratta, Maurizio; Faletti, Carlo; Borrè, Alda
2017-11-01
To evaluate whether apparent diffusion coefficient (ADC) of diffusion-weighted imaging (DWI) is able to investigate the histological features of soft tissue tumours. We reviewed MRIs of soft tissue tumours performed from 2012 to 2015 to calculate the average ADCs. We included 46 patients (27 male; mean age: 57 years, range 12-85 years) with histologically proven soft tissue tumours (10 benign, 2 intermediate 34 malignant) grouped into eight tumour type classes. An experienced pathologist assigned a semi-quantitative cellularity score (very high, high, medium and low) and tumour grading. The t test, ANOVA and linear regression were used to correlate ADC with clinicopathological data. Approximate receiver operating characteristic curves were created to predict possible uses of ADC to differentiate benign from malignant tumours. There was a significant difference (p < 0.01) in ADCs between these three groups excluding myxoid sarcomas. A significant difference was also evident between the tumour type classes (p < 0.001), grade II and III myxoid lesions (p < 0.05), tumour grading classes (p < 0.001) and cellularity scores classes (p < 0.001), with the lowest ADCs in the very high cellularity. While the linear regression analysis showed a significant relationship between ADC and tumour cellularity (r = 0.590, p ≤ 0.05) and grading (r = 0.437, p ≤ 0.05), no significant relationship was found with age, gender, tumour size and histological subtype. An optimal cut-off ADC value of 1.45 × 10 -3 mm 2 /s with 76.8% accuracy was found to differentiate benign from malignant tumours. DWI may offer adjunctive information about soft tissue tumours, but its clinical role is still to be defined.
Fokkens, W. J.; Holm, A. F.; Rijntjes, E.; Mulder, P. G.; Vroom, T. M.
1990-01-01
Little is known about cellular infiltrates in nasal mucosa and the differences between these infiltrates in allergic and non-allergic patients. A reproducible and objective method making use of monoclonal antibodies for the quantification and characterization of cellular infiltrates in biopsy
Cellular characterization of compression induced-damage in live biological samples
Bo, Chiara; Balzer, Jens; Hahnel, Mark; Rankin, Sara M.; Brown, Katherine A.; Proud, William G.
2011-06-01
Understanding the dysfunctions that high-intensity compression waves induce in human tissues is critical to impact on acute-phase treatments and requires the development of experimental models of traumatic damage in biological samples. In this study we have developed an experimental system to directly assess the impact of dynamic loading conditions on cellular function at the molecular level. Here we present a confinement chamber designed to subject live cell cultures in liquid environment to compression waves in the range of tens of MPa using a split Hopkinson pressure bars system. Recording the loading history and collecting the samples post-impact without external contamination allow the definition of parameters such as pressure and duration of the stimulus that can be related to the cellular damage. The compression experiments are conducted on Mesenchymal Stem Cells from BALB/c mice and the damage analysis are compared to two control groups. Changes in Stem cell viability, phenotype and function are assessed flow cytometry and with in vitro bioassays at two different time points. Identifying the cellular and molecular mechanisms underlying the damage caused by dynamic loading in live biological samples could enable the development of new treatments for traumatic injuries.
Matthäus, Franziska; Pahle, Jürgen
2017-01-01
This contributed volume comprises research articles and reviews on topics connected to the mathematical modeling of cellular systems. These contributions cover signaling pathways, stochastic effects, cell motility and mechanics, pattern formation processes, as well as multi-scale approaches. All authors attended the workshop on "Modeling Cellular Systems" which took place in Heidelberg in October 2014. The target audience primarily comprises researchers and experts in the field, but the book may also be beneficial for graduate students.
Gallego-Villar, Lorena; Pérez-Cerdá, Celia; Pérez, Belén; Abia, David; Ugarte, Magdalena; Richard, Eva; Desviat, Lourdes R
2013-09-01
Propionic acidemia (PA), caused by a deficiency of the mitochondrial biotin dependent enzyme propionyl-CoA carboxylase (PCC) is one of the most frequent organic acidurias in humans. PA is caused by mutations in either the PCCA or PCCB genes encoding the α- and β-subunits of the PCC enzyme which are assembled as an α6β6 dodecamer. In this study we have investigated the molecular basis of the defect in ten fibroblast samples from PA patients. Using homology modeling with the recently solved crystal structure of the PCC holoenzyme and a eukaryotic expression system we have analyzed the structural and functional effect of novel point mutations, also revealing a novel splice defect by minigene analysis. In addition, we have investigated the contribution of oxidative stress to cellular damage measuring reactive oxygen species (ROS) levels and apoptosis parameters in patient fibroblasts, as recent studies point to a secondary mitochondrial dysfunction as pathophysiological mechanism in this disorder. The results show an increase in intracellular ROS content compared to controls, correlating with the activation of the JNK and p38 signaling pathways. Highest ROS levels were present in cells harboring functionally null mutations, including one severe missense mutation. This work provides molecular insight into the pathogenicity of PA variants and indicates that oxidative stress may be a major contributing factor to the cellular damage, supporting the proposal of antioxidant strategies as novel supplementary therapy in this rare disease.
Directory of Open Access Journals (Sweden)
Richard J Giannone
Full Text Available Nanoarchaeum equitans, the only cultured representative of the Nanoarchaeota, is dependent on direct physical contact with its host, the hyperthermophile Ignicoccus hospitalis. The molecular mechanisms that enable this relationship are unknown. Using whole-cell proteomics, differences in the relative abundance of >75% of predicted protein-coding genes from both Archaea were measured to identify the specific response of I. hospitalis to the presence of N. equitans on its surface. A purified N. equitans sample was also analyzed for evidence of interspecies protein transfer. The depth of cellular proteome coverage achieved here is amongst the highest reported for any organism. Based on changes in the proteome under the specific conditions of this study, I. hospitalis reacts to N. equitans by curtailing genetic information processing (replication, transcription in lieu of intensifying its energetic, protein processing and cellular membrane functions. We found no evidence of significant Ignicoccus biosynthetic enzymes being transported to N. equitans. These results suggest that, under laboratory conditions, N. equitans diverts some of its host's metabolism and cell cycle control to compensate for its own metabolic shortcomings, thus appearing to be entirely dependent on small, transferable metabolites and energetic precursors from I. hospitalis.
Eroh, Guy D; Clayton, Fred C; Florell, Scott R; Cassidy, Pamela B; Chirife, Andrea; Marón, Carina F; Valenzuela, Luciano O; Campbell, Michael S; Seger, Jon; Rowntree, Victoria J; Leachman, Sancy A
2017-01-01
Southern right whales (SRWs, Eubalena australis) are polymorphic for an X-linked pigmentation pattern known as grey morphism. Most SRWs have completely black skin with white patches on their bellies and occasionally on their backs; these patches remain white as the whale ages. Grey morphs (previously referred to as partial albinos) appear mostly white at birth, with a splattering of rounded black marks; but as the whales age, the white skin gradually changes to a brownish grey color. The cellular and developmental bases of grey morphism are not understood. Here we describe cellular and ultrastructural features of grey-morph skin in relation to that of normal, wild-type skin. Melanocytes were identified histologically and counted, and melanosomes were measured using transmission electron microscopy. Grey-morph skin had fewer melanocytes when compared to wild-type skin, suggesting reduced melanocyte survival, migration, or proliferation in these whales. Grey-morph melanocytes had smaller melanosomes relative to wild-type skin, normal transport of melanosomes to surrounding keratinocytes, and normal localization of melanin granules above the keratinocyte nuclei. These findings indicate that SRW grey-morph pigmentation patterns are caused by reduced numbers of melanocytes in the skin, as well as by reduced amounts of melanin production and/or reduced sizes of mature melanosomes. Grey morphism is distinct from piebaldism and albinism found in other species, which are genetic pigmentation conditions resulting from the local absence of melanocytes, or the inability to synthesize melanin, respectively.
Arnst, M.; Abello Álvarez, B.; Ponthot, J.-P.; Boman, R.
2017-11-01
This paper is concerned with the characterization and the propagation of errors associated with data limitations in polynomial-chaos-based stochastic methods for uncertainty quantification. Such an issue can arise in uncertainty quantification when only a limited amount of data is available. When the available information does not suffice to accurately determine the probability distributions that must be assigned to the uncertain variables, the Bayesian method for assigning these probability distributions becomes attractive because it allows the stochastic model to account explicitly for insufficiency of the available information. In previous work, such applications of the Bayesian method had already been implemented by using the Metropolis-Hastings and Gibbs Markov Chain Monte Carlo (MCMC) methods. In this paper, we present an alternative implementation, which uses an alternative MCMC method built around an Itô stochastic differential equation (SDE) that is ergodic for the Bayesian posterior. We draw together from the mathematics literature a number of formal properties of this Itô SDE that lend support to its use in the implementation of the Bayesian method, and we describe its discretization, including the choice of the free parameters, by using the implicit Euler method. We demonstrate the proposed methodology on a problem of uncertainty quantification in a complex nonlinear engineering application relevant to metal forming.
Energy Technology Data Exchange (ETDEWEB)
Ramirez, A; Mcnab, W; Hao, Y; White, D; Johnson, J
2011-04-14
During the last months of this project, our project activities have concentrated on four areas: (1) performing a stochastic inversion of pattern 16 seismic data to deduce reservoir bulk/shear moduli and density; the need for this inversion was not anticipated in the original scope of work, (2) performing a stochastic inversion of pattern 16 seismic data to deduce reservoir porosity and permeability, (3) complete the software needed to perform geochemical inversions and (4) use the software to perform stochastic inversion of aqueous chemistry data to deduce mineral volume fractions. This report builds on work described in progress reports previously submitted (Ramirez et al., 2009, 2010, 2011 - reports fulfilled the requirements of deliverables D1-D4) and fulfills deliverable D5: Field-based single-pattern simulations work product. The main challenge with our stochastic inversion approach is its large computational expense, even for single reservoir patterns. We dedicated a significant level of effort to improve computational efficiency but inversions involving multiple patterns were still intractable by project's end. As a result, we were unable to fulfill Deliverable D6: Field-based multi-pattern simulations work product.
Energy Technology Data Exchange (ETDEWEB)
Ou, Xiaoxia [School of Chemical Engineering and Analytical Science, The University of Manchester, M13 9PL (United Kingdom); Zhang, Xun; Lowe, Tristan [Henry Moseley X-ray Imaging Facility, Materials Science Centre, School of Materials, The University of Manchester, M13 9PL (United Kingdom); Blanc, Remi [FEI, 3 Impasse Rudolf Diesel, BP 50227, 33708 Mérignac (France); Rad, Mansoureh Norouzi [School of Chemical Engineering and Analytical Science, The University of Manchester, M13 9PL (United Kingdom); Wang, Ying [Henry Moseley X-ray Imaging Facility, Materials Science Centre, School of Materials, The University of Manchester, M13 9PL (United Kingdom); Batail, Nelly; Pham, Charlotte [SICAT SARL, 20 Place des Halles, 67000 Strasbourg (France); Shokri, Nima; Garforth, Arthur A. [School of Chemical Engineering and Analytical Science, The University of Manchester, M13 9PL (United Kingdom); Withers, Philip J. [Henry Moseley X-ray Imaging Facility, Materials Science Centre, School of Materials, The University of Manchester, M13 9PL (United Kingdom); Fan, Xiaolei, E-mail: xiaolei.fan@manchester.ac.uk [School of Chemical Engineering and Analytical Science, The University of Manchester, M13 9PL (United Kingdom)
2017-01-15
Open-cell SiC foams clearly are promising materials for continuous-flow chemical applications such as heterogeneous catalysis and distillation. X-ray micro computed tomography characterization of cellular β-SiC foams at a spatial voxel size of 13.6{sup 3} μm{sup 3} and the interpretation of morphological properties of SiC open-cell foams with implications to their transport properties are presented. Static liquid hold-up in SiC foams was investigated through in-situ draining experiments for the first time using the μ-CT technique providing thorough 3D information about the amount and distribution of liquid hold-up inside the foam. This will enable better modeling and design of structured reactors based on SiC foams in the future. In order to see more practical uses, μ-CT data of cellular foams must be exploited to optimize the design of the morphology of foams for a specific application. - Highlights: •Characterization of SiC foams using novel X-ray micro computed tomography. •Interpretation of structural properties of SiC foams regarding to their transport properties. •Static liquid hold-up analysis of SiC foams through in-situ draining experiments.
Directory of Open Access Journals (Sweden)
Ming-Hui Yang
2014-01-01
Full Text Available The purpose of this study was to develop the pathway of silk fibroin (SF biopolymer surface induced cell membrane protein activation. Fibroblasts were used as an experimental model to evaluate the responses of cellular proteins induced by biopolymer material using a mass spectrometry-based profiling system. The surface was covered by multiwalled carbon nanotubes (CNTs and SF to increase the surface area, enhance the adhesion of biopolymer, and promote the rate of cell proliferation. The amount of adhered fibroblasts on CNTs/SF electrodes of quartz crystal microbalance (QCM greatly exceeded those on other surfaces. Moreover, analyzing differential protein expressions of adhered fibroblasts on the biopolymer surface by proteomic approaches indicated that CD44 may be a key protein. Through this study, utilization of mass spectrometry-based proteomics in evaluation of cell adhesion on biopolymer was proposed.
Chavali, Arvind K; Gianchandani, Erwin P; Tung, Kenneth S; Lawrence, Michael B; Peirce, Shayn M; Papin, Jason A
2008-12-01
The immune system is comprised of numerous components that interact with one another to give rise to phenotypic behaviors that are sometimes unexpected. Agent-based modeling (ABM) and cellular automata (CA) belong to a class of discrete mathematical approaches in which autonomous entities detect local information and act over time according to logical rules. The power of this approach lies in the emergence of behavior that arises from interactions between agents, which would otherwise be impossible to know a priori. Recent work exploring the immune system with ABM and CA has revealed novel insights into immunological processes. Here, we summarize these applications to immunology and, particularly, how ABM can help formulate hypotheses that might drive further experimental investigations of disease mechanisms.
Characterization of 316L Steel Cellular Dodecahedron Structures Produced by Selective Laser Melting
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Konda Gokuldoss Prashanth
2016-10-01
Full Text Available The compression behavior of different 316L steel cellular dodecahedron structures with different density values were studied. The 316L steel structures produced using the selective laser melting process has four different geometries: single unit cells with and without the addition of base plates beneath and on top, and sandwich structures with multiple unit cells with different unit cell sizes. The relation between the relative compressive strength and the relative density was compared using different Gibson-Ashby models and with other published reports. The different aspects of the deformation and the mechanical properties were evaluated and the deformation at distinct loading levels was recorded. Finite element method (FEM simulations were carried out with the defined structures and the mechanical testing results were compared. The calculated theory, simulation estimation, and the observed experimental results are in good agreement.
Kihara, Takanori; Kashitani, Kosuke; Miyake, Jun
2017-07-14
Cell proliferation is a key characteristic of eukaryotic cells. During cell proliferation, cells interact with each other. In this study, we developed a cellular automata model to estimate cell-cell interactions using experimentally obtained images of cultured cells. We used four types of cells; HeLa cells, human osteosarcoma (HOS) cells, rat mesenchymal stem cells (MSCs), and rat smooth muscle A7r5 cells. These cells were cultured and stained daily. The obtained cell images were binarized and clipped into squares containing about 10 4 cells. These cells showed characteristic cell proliferation patterns. The growth curves of these cells were generated from the cell proliferation images and we determined the doubling time of these cells from the growth curves. We developed a simple cellular automata system with an easily accessible graphical user interface. This system has five variable parameters, namely, initial cell number, doubling time, motility, cell-cell adhesion, and cell-cell contact inhibition (of proliferation). Within these parameters, we obtained initial cell numbers and doubling times experimentally. We set the motility at a constant value because the effect of the parameter for our simulation was restricted. Therefore, we simulated cell proliferation behavior with cell-cell adhesion and cell-cell contact inhibition as variables. By comparing growth curves and proliferation cell images, we succeeded in determining the cell-cell interaction properties of each cell. Simulated HeLa and HOS cells exhibited low cell-cell adhesion and weak cell-cell contact inhibition. Simulated MSCs exhibited high cell-cell adhesion and positive cell-cell contact inhibition. Simulated A7r5 cells exhibited low cell-cell adhesion and strong cell-cell contact inhibition. These simulated results correlated with the experimental growth curves and proliferation images. Our simulation approach is an easy method for evaluating the cell-cell interaction properties of cells.
Parzen, Emanuel
1962-01-01
Well-written and accessible, this classic introduction to stochastic processes and related mathematics is appropriate for advanced undergraduate students of mathematics with a knowledge of calculus and continuous probability theory. The treatment offers examples of the wide variety of empirical phenomena for which stochastic processes provide mathematical models, and it develops the methods of probability model-building.Chapter 1 presents precise definitions of the notions of a random variable and a stochastic process and introduces the Wiener and Poisson processes. Subsequent chapters examine
Characterization of non-dimer DNA lesions and cellular damages caused by ultraviolet light
International Nuclear Information System (INIS)
Nakao, Kumi
1989-01-01
To understand the mechanisms of carcinogenicity and cytotoxicity induced by ultraviolet (UV) light, non-dimer DNA damages produced by near UV light (wave-length: 290∼320 nm) were examined by alkaline elution using Chinese hamster V-79 cells. UV exposure produced a dose-dependent induction of DNA single strand breaks and DNA-protein crosslinks. However, neither of these DNA lesions were repaired within a 24 hr incubation of the cells following UV exposure. Rather the number of these lesions increased. Also, UV exposure inhibited DNA and RNA synthesis. In addition, UV induced both cytotoxicity and chromosomal aberration. Electron spin resornance (ESR) studies showed that the exposure of cells to UV light resulted in the appearance of an ESR signal at -120degC. The roles of glutathione, vitamin E and vitamin B 2 , which were celluar antioxidant, on the induction of cytotoxicity by UV exposure were also examined. Pretreatment with vitamin E reduced the cytotoxicty caused by UV, whereas neither preteatment with vitamin B 2 nor the alteration of cellular gluthaione content affected the cytotoxicity. These results suggest that non-dimer DNA damages, such as DNA single strand breaks and DNA-protein crosslinks play an important role in inducing UV-carcinogenicity and UV-cytotoxicity, and that the mechanisms of these damages may be associated with the generation of free radicals. (author)
Karstensen, John Gásdal; Klausen, Pia Helene; Saftoiu, Adrian; Vilmann, Peter
2014-06-28
While flexible endoscopy is essential for macroscopic evaluation, confocal laser endomicroscopy (CLE) has recently emerged as an endoscopic method enabling visualization at a cellular level. Two systems are currently available, one based on miniprobes that can be inserted via a conventional endoscope or via a needle guided by endoscopic ultrasound. The second system has a confocal microscope integrated into the distal part of an endoscope. By adding molecular probes like fluorescein conjugated antibodies or fluorescent peptides to this procedure (either topically or systemically administered during on-going endoscopy), a novel world of molecular evaluation opens up. The method of molecular CLE could potentially be used for estimating the expression of important receptors in carcinomas, subsequently resulting in immediate individualization of treatment regimens, but also for improving the diagnostic accuracy of endoscopic procedures by identifying otherwise invisible mucosal lesions. Furthermore, studies have shown that fluorescein labelled drugs can be used to estimate the affinity of the drug to a target organ, which probably can be correlated to the efficacy of the drug. However, several of the studies in this research field have been conducted in animal facilities or in vitro, while only a limited number of trials have actually been carried out in vivo. Therefore, safety issues still needs further evaluations. This review will present an overview of the implications and pitfalls, as well as future challenges of molecular CLE in gastrointestinal diseases.
International Nuclear Information System (INIS)
Klauder, J.R.
1983-01-01
The author provides an introductory survey to stochastic quantization in which he outlines this new approach for scalar fields, gauge fields, fermion fields, and condensed matter problems such as electrons in solids and the statistical mechanics of quantum spins. (Auth.)
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
Foundations of stochastic analysis
Rao, M M; Lukacs, E
1981-01-01
Foundations of Stochastic Analysis deals with the foundations of the theory of Kolmogorov and Bochner and its impact on the growth of stochastic analysis. Topics covered range from conditional expectations and probabilities to projective and direct limits, as well as martingales and likelihood ratios. Abstract martingales and their applications are also discussed. Comprised of five chapters, this volume begins with an overview of the basic Kolmogorov-Bochner theorem, followed by a discussion on conditional expectations and probabilities containing several characterizations of operators and mea
International Nuclear Information System (INIS)
Kannouche, Patricia-Laila
1998-01-01
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 [fr
International Nuclear Information System (INIS)
Wellens, Thomas; Shatokhin, Vyacheslav; Buchleitner, Andreas
2004-01-01
We are taught by conventional wisdom that the transmission and detection of signals is hindered by noise. However, during the last two decades, the paradigm of stochastic resonance (SR) proved this assertion wrong: indeed, addition of the appropriate amount of noise can boost a signal and hence facilitate its detection in a noisy environment. Due to its simplicity and robustness, SR has been implemented by mother nature on almost every scale, thus attracting interdisciplinary interest from physicists, geologists, engineers, biologists and medical doctors, who nowadays use it as an instrument for their specific purposes. At the present time, there exist a lot of diversified models of SR. Taking into account the progress achieved in both theoretical understanding and practical application of this phenomenon, we put the focus of the present review not on discussing in depth technical details of different models and approaches but rather on presenting a general and clear physical picture of SR on a pedagogical level. Particular emphasis will be given to the implementation of SR in generic quantum systems-an issue that has received limited attention in earlier review papers on the topic. The major part of our presentation relies on the two-state model of SR (or on simple variants thereof), which is general enough to exhibit the main features of SR and, in fact, covers many (if not most) of the examples of SR published so far. In order to highlight the diversity of the two-state model, we shall discuss several examples from such different fields as condensed matter, nonlinear and quantum optics and biophysics. Finally, we also discuss some situations that go beyond the generic SR scenario but are still characterized by a constructive role of noise
STOCHASTIC ASSESSMENT OF NIGERIAN STOCHASTIC ...
African Journals Online (AJOL)
eobe
STOCHASTIC ASSESSMENT OF NIGERIAN WOOD FOR BRIDGE DECKS ... abandoned bridges with defects only in their decks in both rural and urban locations can be effectively .... which can be seen as the detection of rare physical.
International Nuclear Information System (INIS)
Esfandyari-Manesh, Mehdi; Darvishi, Behrad; Ishkuh, Fatemeh Azizi; Shahmoradi, Elnaz; Mohammadi, Ali; Javanbakht, Mehran; Dinarvand, Rassoul; Atyabi, Fatemeh
2016-01-01
showed high drug loading and encapsulation efficiency, 15.57 ± 0.84 and 100%, respectively. • Nanoparticles demonstrated a superior cellular uptake over non-targeted nanoparticles. • IC_5_0 of nanoparticles and IC_5_0 of free paclitaxel were 4.86 ± 0.91 and 32.80 ± 3.80 nM, respectively. • The imprinted nanoparticles showed high affinity to paclitaxel in biological samples.
Energy Technology Data Exchange (ETDEWEB)
Esfandyari-Manesh, Mehdi [Nanotechnology Research Center,Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Department of Chemistry, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Darvishi, Behrad [Nanotechnology Research Center,Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Ishkuh, Fatemeh Azizi [Department of Chemistry, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Shahmoradi, Elnaz [Department of Chemical Engineering, Sharif University of Technology, Tehran (Iran, Islamic Republic of); Mohammadi, Ali [Nanotechnology Research Center,Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Department of Drug and Food Control, Faculty of Pharmacy, Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Javanbakht, Mehran [Department of Chemistry, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of); Dinarvand, Rassoul [Nanotechnology Research Center,Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of); Atyabi, Fatemeh, E-mail: atyabifa@tums.ac.ir [Nanotechnology Research Center,Tehran University of Medical Sciences, Tehran (Iran, Islamic Republic of)
2016-05-01
showed high drug loading and encapsulation efficiency, 15.57 ± 0.84 and 100%, respectively. • Nanoparticles demonstrated a superior cellular uptake over non-targeted nanoparticles. • IC{sub 50} of nanoparticles and IC{sub 50} of free paclitaxel were 4.86 ± 0.91 and 32.80 ± 3.80 nM, respectively. • The imprinted nanoparticles showed high affinity to paclitaxel in biological samples.
DEFF Research Database (Denmark)
Madsen, Steffen S; Olesen, Jesper H; Bedal, Konstanze
2011-01-01
Intestinal water absorption is greatly enhanced in salmonids upon acclimation from freshwater (FW) to seawater (SW); however, the molecular mechanism for water transport is unknown. We conducted a pharmacological characterization of water absorption in the rainbow trout intestine along......%), 0.1 ouabain (72%), and 0.1 bumetanide (82%) suggesting that active transport, Na(+), K(+)-ATPase and Na(+), K(+), 2Cl(-)-co-transport are involved in establishing the driving gradient for water transport. J(v) was also inhibited by 1 mmol L(-1) HgCl(2), serosally (23% in M and 44% in P), mucosally...... (27% in M), or both (61% in M and 58% in P), suggesting involvement of both apical and basolateral aquaporins in water transport. The inhibition was antagonized by 5 mmol L(-1) mercaptoethanol. By comparison, 10 mmol L(-1) mucosal tetraethylammonium, an inhibitor of certain aquaporins, inhibited J...
Eslami, Sohrab; Zareian, Ramin; Jalili, Nader
2012-10-01
Surface microscopy of individual biological cells is essential for determining the patterns of cell migration to study the tumor formation or metastasis. This paper presents a correlated and effective theoretical and experimental technique to automatically address the biophysical and mechanical properties and acquire live images of biological cells which are of interest in studying cancer. In the theoretical part, a distributed-parameters model as the comprehensive representation of the microcantilever is presented along with a model of the contact force as a function of the indentation depth and mechanical properties of the biological sample. Analysis of the transfer function of the whole system in the frequency domain is carried out to characterize the stiffness and damping coefficients of the sample. In the experimental section, unlike the conventional atomic force microscope techniques basically using the laser for determining the deflection of microcantilever's tip, a piezoresistive microcantilever serving as a force sensor is implemented to produce the appropriate voltage and measure the deflection of the microcantilever. A micromanipulator robotic system is integrated with the MATLAB® and programmed in such a way to automatically control the microcantilever mounted on the tip of the micromanipulator to achieve the topography of biological samples including the human corneal cells. For this purpose, the human primary corneal fibroblasts are extracted and adhered on a sterilized culture dish and prepared to attain their topographical image. The proposed methodology herein allows an approach to obtain 2D quality images of cells being comparatively cost effective and extendable to obtain 3D images of individual cells. The characterized mechanical properties of the human corneal cell are furthermore established by comparing and validating the phase shift of the theoretical and experimental results of the frequency response.
Brewster, J.; Oware, E. K.
2017-12-01
Groundwater hosted in fractured rocks constitutes almost 65% of the principal aquifers in the US. The exploitation and contaminant management of fractured aquifers require fracture flow and transport modeling, which in turn requires a detailed understanding of the structure of the aquifer. The widely used equivalent porous medium approach to modeling fractured aquifer systems is inadequate to accurately predict fracture transport processes due to the averaging of the sharp lithological contrast between the matrix and the fractures. The potential of geophysical imaging (GI) to estimate spatially continuous subsurface profiles in a minimally invasive fashion is well proven. Conventional deterministic GI strategies, however, produce geologically unrealistic, smoothed-out results due to commonly enforced smoothing constraints. Stochastic GI of fractured aquifers is becoming increasing appealing due to its ability to recover realistic fracture features while providing multiple likely realizations that enable uncertainty assessment. Generating prior spatial features consistent with the expected target structures is crucial in stochastic imaging. We propose to utilize eigenvalue ratios to resolve the elongated fracture features expected in a fractured aquifer system. Eigenvalues capture the major and minor directions of variability in a region, which can be employed to evaluate shape descriptors, such as eccentricity (elongation) and orientation of features in the region. Eccentricity ranges from zero to one, representing a circularly sharped to a line feature, respectively. Here, we apply eigenvalue ratios to define a joint objective parameter consisting of eccentricity (shape) and direction terms to guide the generation of prior fracture-like features in some predefined principal directions for stochastic GI. Preliminary unconditional, synthetic experiments reveal the potential of the algorithm to simulate prior fracture-like features. We illustrate the strategy with a
Variance decomposition in stochastic simulators.
Le Maître, O P; Knio, O M; Moraes, A
2015-06-28
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Variance decomposition in stochastic simulators
Le Maître, O. P.; Knio, O. M.; Moraes, A.
2015-06-01
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Variance decomposition in stochastic simulators
Energy Technology Data Exchange (ETDEWEB)
Le Maître, O. P., E-mail: olm@limsi.fr [LIMSI-CNRS, UPR 3251, Orsay (France); Knio, O. M., E-mail: knio@duke.edu [Department of Mechanical Engineering and Materials Science, Duke University, Durham, North Carolina 27708 (United States); Moraes, A., E-mail: alvaro.moraesgutierrez@kaust.edu.sa [King Abdullah University of Science and Technology, Thuwal (Saudi Arabia)
2015-06-28
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Variance decomposition in stochastic simulators
Le Maî tre, O. P.; Knio, O. M.; Moraes, Alvaro
2015-01-01
This work aims at the development of a mathematical and computational approach that enables quantification of the inherent sources of stochasticity and of the corresponding sensitivities in stochastic simulations of chemical reaction networks. The approach is based on reformulating the system dynamics as being generated by independent standardized Poisson processes. This reformulation affords a straightforward identification of individual realizations for the stochastic dynamics of each reaction channel, and consequently a quantitative characterization of the inherent sources of stochasticity in the system. By relying on the Sobol-Hoeffding decomposition, the reformulation enables us to perform an orthogonal decomposition of the solution variance. Thus, by judiciously exploiting the inherent stochasticity of the system, one is able to quantify the variance-based sensitivities associated with individual reaction channels, as well as the importance of channel interactions. Implementation of the algorithms is illustrated in light of simulations of simplified systems, including the birth-death, Schlögl, and Michaelis-Menten models.
Ari-Wahjoedi, Bambang; Ginta, Turnad Lenggo; Parman, Setyamartana; Abustaman, Mohd Zikri Ahmad
2014-10-01
Multicellular monolithic ceramic body is a ceramic material which has many gas or liquid passages partitioned by thin walls throughout the bulk material. There are many currently known advanced industrial applications of multicellular ceramics structures i.e. as supports for various catalysts, electrode support structure for solid oxide fuel cells, refractories, electric/electronic materials, aerospace vehicle re-entry heat shields and biomaterials for dental as well as orthopaedic implants by naming only a few. Multicellular ceramic bodies are usually made of ceramic phases such as mullite, cordierite, aluminum titanate or pure oxides such as silica, zirconia and alumina. What make alumina ceramics is excellent for the above functions are the intrinsic properties of alumina which are hard, wear resistant, excellent dielectric properties, resists strong acid and alkali attacks at elevated temperatures, good thermal conductivities, high strength and stiffness as well as biocompatible. In this work the processing technology leading to truly multicellular monolithic alumina ceramic bodies and their characterization are reported. Ceramic slip with 66 wt.% solid loading was found to be optimum as impregnant to the polyurethane foam template. Mullitic ceramic composite of alumina-sodium alumino disilicate-Leucite-like phases with bulk and true densities of 0.852 and 1.241 g cm-3 respectively, pore linear density of ±35 cm-1, linear and bulk volume shrinkages of 7-16% and 32 vol.% were obtained. The compressive strength and elastic modulus of the bioceramics are ≈0.5-1.0 and ≈20 MPa respectively.
Biochemical characterization and cellular effects of CADASIL mutants of NOTCH3.
Directory of Open Access Journals (Sweden)
He Meng
Full Text Available Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL is the best understood cause of dominantly inherited stroke and results from NOTCH3 mutations that lead to NOTCH3 protein accumulation and selective arterial smooth muscle degeneration. Previous studies show that NOTCH3 protein forms multimers. Here, we investigate protein interactions between NOTCH3 and other vascular Notch isoforms and characterize the effects of elevated NOTCH3 on smooth muscle gene regulation. We demonstrate that NOTCH3 forms heterodimers with NOTCH1, NOTCH3, and NOTCH4. R90C and C49Y mutant NOTCH3 form complexes which are more resistant to detergents than wild type NOTCH3 complexes. Using quantitative NOTCH3-luciferase clearance assays, we found significant inhibition of mutant NOTCH3 clearance. In coculture assays of NOTCH function, overexpressed wild type and mutant NOTCH3 significantly repressed NOTCH-regulated smooth muscle transcripts and potently impaired the activity of three independent smooth muscle promoters. Wildtype and R90C recombinant NOTCH3 proteins applied to cell cultures also blocked canonical Notch fuction. We conclude that CADASIL mutants of NOTCH3 complex with NOTCH1, 3, and 4, slow NOTCH3 clearance, and that overexpressed wild type and mutant NOTCH3 protein interfere with key NOTCH-mediated functions in smooth muscle cells.
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...
International Nuclear Information System (INIS)
Ari-Wahjoedi, Bambang; Ginta, Turnad Lenggo; Parman, Setyamartana; Abustaman, Mohd Zikri Ahmad
2014-01-01
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
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.
Cellular characterization of cells from the Fanconi anemia complementation group, FA-D1/BRCA2
International Nuclear Information System (INIS)
Godthelp, Barbara C.; Buul, Paul P.W. van; Jaspers, Nicolaas G.J.; Elghalbzouri-Maghrani, Elhaam; Duijn-Goedhart, Annemarie van; Arwert, Fre; Joenje, Hans; Zdzienicka, Malgorzata Z.
2006-01-01
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
Cicione, Claudia; Díaz-Prado, Silvia; Muiños-López, Emma; Hermida-Gómez, Tamara; Blanco, Francisco J
2010-01-01
The use of autologous or allogenic stem cells has recently been suggested as an alternative therapeutic approach for treatment of cartilage defects. Bone marrow mesenchymal stem cells (BM-MSCs) are well-characterized multipotent cells that can differentiate into different cell types. Understanding the potential of these cells and the molecular mechanisms underlying their differentiation should lead to innovative protocols for clinical applications. The aim of this study was to evaluate the usefulness of surface antigen selection of BM-MSCs and to understand the mechanisms underlying their differentiation. MSCs were isolated from BM stroma and expanded. CD105+ subpopulation was isolated using a magnetic separator. We compared culture-expanded selected cells with non-selected cells. We analyzed the phenotypic profiles, the expression of the stem cell marker genes Nanog, Oct3/4, and Sox2 and the multi-lineage differentiation potential (adipogenic, osteogenic, and chondrogenic). The multi-lineage differentiation was confirmed using histochemistry, immunohistochemistry and/or real-time polymerase chain reaction (qPCR) techniques. The selected and non-selected cells displayed similar phenotypes and multi-lineage differentiation potentials. Analyzing each cell source individually, we could divide the six donors into two groups: one with a high percentage of CD29 (β1-integrin) expression (HL); one with a low percentage of CD29 (LL). These two groups had different chondrogenic capacities and different expression levels of the stem cell marker genes. This study showed that phenotypic profiles of donors were related to the chondrogenic potential of human BM-MSCs. The chondrogenic potential of donors was related to CD29 expression levels. The high expression of CD29 antigen seemed necessary for chondrogenic differentiation. Further investigation into the mechanisms responsible for these differences in BM-MSCs chondrogenesis is therefore warranted. Understanding the mechanisms
Stochasticity in the Josephson map
International Nuclear Information System (INIS)
Nomura, Y.; Ichikawa, Y.H.; Filippov, A.T.
1996-04-01
The Josephson map describes nonlinear dynamics of systems characterized by standard map with the uniform external bias superposed. The intricate structures of the phase space portrait of the Josephson map are examined on the basis of the tangent map associated with the Josephson map. Numerical observation of the stochastic diffusion in the Josephson map is examined in comparison with the renormalized diffusion coefficient calculated by the method of characteristic function. The global stochasticity of the Josephson map occurs at the values of far smaller stochastic parameter than the case of the standard map. (author)
Stochastic Stability of Endogenous Growth: Theory and Applications
Boucekkine, Raouf; Pintus, Patrick; Zou, Benteng
2015-01-01
We examine the issue of stability of stochastic endogenous growth. First, stochastic stability concepts are introduced and applied to stochastic linear homogenous differen- tial equations to which several stochastic endogenous growth models reduce. Second, we apply the mathematical theory to two models, starting with the stochastic AK model. It’s shown that in this case exponential balanced paths, which characterize optimal trajectories in the absence of uncertainty, are not robust to uncerta...
International Nuclear Information System (INIS)
Bisognano, J.; Leemann, C.
1982-03-01
Stochastic cooling is the damping of betatron oscillations and momentum spread of a particle beam by a feedback system. In its simplest form, a pickup electrode detects the transverse positions or momenta of particles in a storage ring, and the signal produced is amplified and applied downstream to a kicker. The time delay of the cable and electronics is designed to match the transit time of particles along the arc of the storage ring between the pickup and kicker so that an individual particle receives the amplified version of the signal it produced at the pick-up. If there were only a single particle in the ring, it is obvious that betatron oscillations and momentum offset could be damped. However, in addition to its own signal, a particle receives signals from other beam particles. In the limit of an infinite number of particles, no damping could be achieved; we have Liouville's theorem with constant density of the phase space fluid. For a finite, albeit large number of particles, there remains a residue of the single particle damping which is of practical use in accumulating low phase space density beams of particles such as antiprotons. It was the realization of this fact that led to the invention of stochastic cooling by S. van der Meer in 1968. Since its conception, stochastic cooling has been the subject of much theoretical and experimental work. The earliest experiments were performed at the ISR in 1974, with the subsequent ICE studies firmly establishing the stochastic cooling technique. This work directly led to the design and construction of the Antiproton Accumulator at CERN and the beginnings of p anti p colliding beam physics at the SPS. Experiments in stochastic cooling have been performed at Fermilab in collaboration with LBL, and a design is currently under development for a anti p accumulator for the Tevatron
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.
Error performance analysis in downlink cellular networks with interference management
Afify, Laila H.; Elsawy, Hesham; Al-Naffouri, Tareq Y.; Alouini, Mohamed-Slim
2015-01-01
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
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
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
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
Borodin, Andrei N
2017-01-01
This book provides a rigorous yet accessible introduction to the theory of stochastic processes. A significant part of the book is devoted to the classic theory of stochastic processes. In turn, it also presents proofs of well-known results, sometimes together with new approaches. Moreover, the book explores topics not previously covered elsewhere, such as distributions of functionals of diffusions stopped at different random times, the Brownian local time, diffusions with jumps, and an invariance principle for random walks and local times. Supported by carefully selected material, the book showcases a wealth of examples that demonstrate how to solve concrete problems by applying theoretical results. It addresses a broad range of applications, focusing on concrete computational techniques rather than on abstract theory. The content presented here is largely self-contained, making it suitable for researchers and graduate students alike.
Liu, Xiangdong; Li, Qingze; Pan, Jianxin
2018-06-01
Modern medical studies show that chemotherapy can help most cancer patients, especially for those diagnosed early, to stabilize their disease conditions from months to years, which means the population of tumor cells remained nearly unchanged in quite a long time after fighting against immune system and drugs. In order to better understand the dynamics of tumor-immune responses under chemotherapy, deterministic and stochastic differential equation models are constructed to characterize the dynamical change of tumor cells and immune cells in this paper. The basic dynamical properties, such as boundedness, existence and stability of equilibrium points, are investigated in the deterministic model. Extended stochastic models include stochastic differential equations (SDEs) model and continuous-time Markov chain (CTMC) model, which accounts for the variability in cellular reproduction, growth and death, interspecific competitions, and immune response to chemotherapy. The CTMC model is harnessed to estimate the extinction probability of tumor cells. Numerical simulations are performed, which confirms the obtained theoretical results.
International Nuclear Information System (INIS)
Schenker, A.R.; Guerin, D.C.; Robey, T.H.; Rautman, C.A.; Barnard, R.W.
1995-09-01
A stochastic representation of the lithologic units and associated hydrogeologic parameters of the potential high-level nuclear waste repository are developed for use in performance-assessment calculations, including the Total-System Performance Assessment for Yucca Mountain-SNL Second Iteration (TSPA-1993). A simplified lithologic model has been developed based on the physical characteristics of the welded and nonwelded units at Yucca Mountain. Ten hydrogeologic units are developed from site-specific data (lithologic and geophysical logs and core photographs) obtained from the unsaturated and saturated zones. The three-dimensional geostatistical model of the ten hydrogeologic units is based on indicator-coding techniques and improves on the two-dimensional model developed for TSPA91. The hydrogeologic properties (statistics and probability distribution functions) are developed from the results of laboratory tests and in-situ aquifer tests or are derived through fundamental relationships. Hydrogeologic properties for matrix properties, bulk conductivities, and fractures are developed from existing site specific data. Extensive data are available for matrix porosity, bulk density, and matrix saturated conductivity. For other hydrogeologic properties, the data are minimal or nonexistent. Parameters for the properties are developed as beta probability distribution functions. For the model units without enough data for analysis, parameters are developed as analogs to existing units. A relational, analytic approach coupled with bulk conductivity parameters is used to develop fracture parameters based on the smooth-wall-parallel-plate theory. An analytic method is introduced for scaling small-core matrix properties to the hydrogeologic unit scales
Vaiyapuri, Periasamy S; Ali, Alshatwi A; Mohammad, Akbarsha A; Kandhavelu, Jeyalakshmi; Kandhavelu, Meenakshisundaram
2015-01-01
The effect of Calotropis gigantea latex (CGLX) on human mammary carcinoma cells is not well established. We present the results of this drug activity at total population and single cell level. CGLX inhibited the growth of MCF7 cancer cells at lower IC50 concentration (17 µL/mL). Microscopy of IC50 drug treated cells at 24 hr confirming the appearance of morphological characteristics of apoptotic and necrotic cells, associated with 70% of DNA damage. FACS analysis confirmed that, 10 and 20% of the disruption of cellular mitochondrial nature by at 24 and 48 h, respectively. Microscopic image analysis of total population level proved that MMP changes were statistically significant with P values. The cell to cell variation was confirmed by functional heterogeneity analysis which proves that CGLX was able to induce the apoptosis without the contribution of mitochondria. We conclude that CGLX inhibits cell proliferation, survival, and heterogeneity of pathways in human mammary carcinoma cells. © 2014 Wiley Periodicals, Inc.
Directory of Open Access Journals (Sweden)
Débora L Oliveira
2010-06-01
Full Text Available 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.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.Our results suggest that both conventional and unconventional pathways of secretion are required for biogenesis of extracellular vesicles, which demonstrate the
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
International Nuclear Information System (INIS)
Bhaskar,; Kumari, Neeti; Goyal, Neena
2012-01-01
Highlights: ► The study presents cloning and characterization of TCP1γ gene from L. donovani. ► TCP1γ is a subunit of T-complex protein-1 (TCP1), a chaperonin class of protein. ► LdTCPγ exhibited differential expression in different stages of promastigotes. ► LdTCPγ co-localized with actin, a cytoskeleton protein. ► The data suggests that this gene may have a role in differentiation/biogenesis. ► First report on this chapronin in Leishmania. -- Abstract: T-complex protein-1 (TCP1) complex, a chaperonin class of protein, ubiquitous in all genera of life, is involved in intracellular assembly and folding of various proteins. The gamma subunit of TCP1 complex (TCP1γ), plays a pivotal role in the folding and assembly of cytoskeleton protein(s) as an individual or complexed with other subunits. Here, we report for the first time cloning, characterization and expression of the TCP1γ of Leishmania donovani (LdTCP1γ), the causative agent of Indian Kala-azar. Primary sequence analysis of LdTCP1γ revealed the presence of all the characteristic features of TCP1γ. However, leishmanial TCP1γ represents a distinct kinetoplastid group, clustered in a separate branch of the phylogenic tree. LdTCP1γ exhibited differential expression in different stages of promastigotes. The non-dividing stationary phase promastigotes exhibited 2.5-fold less expression of LdTCP1γ as compared to rapidly dividing log phase parasites. The sub-cellular distribution of LdTCP1γ was studied in log phase promastigotes by employing indirect immunofluorescence microscopy. The protein was present not only in cytoplasm but it was also localized in nucleus, peri-nuclear region, flagella, flagellar pocket and apical region. Co-localization of LdTCP1γ with actin suggests that, this gene may have a role in maintaining the structural dynamics of cytoskeleton of parasite.
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...
International Nuclear Information System (INIS)
Colombino, A.; Mosiello, R.; Norelli, F.; Jorio, V.M.; Pacilio, N.
1975-01-01
A nuclear system kinetics is formulated according to a stochastic approach. The detailed probability balance equations are written for the probability of finding the mixed population of neutrons and detected neutrons, i.e. detectrons, at a given level for a given instant of time. Equations are integrated in search of a probability profile: a series of cases is analyzed through a progressive criterium. It tends to take into account an increasing number of physical processes within the chosen model. The most important contribution is that solutions interpret analytically experimental conditions of equilibrium (moise analysis) and non equilibrium (pulsed neutron measurements, source drop technique, start up procedures)
Directory of Open Access Journals (Sweden)
Romanu Ekaterini
2006-01-01
Full Text Available This article shows the similarities between Claude Debussy’s and Iannis Xenakis’ philosophy of music and work, in particular the formers Jeux and the latter’s Metastasis and the stochastic works succeeding it, which seem to proceed parallel (with no personal contact to what is perceived as the evolution of 20th century Western music. Those two composers observed the dominant (German tradition as outsiders, and negated some of its elements considered as constant or natural by "traditional" innovators (i.e. serialists: the linearity of musical texture, its form and rhythm.
International Nuclear Information System (INIS)
Murr, L.E.; Gaytan, S.M.; Medina, F.; Martinez, E.; Martinez, J.L.; Hernandez, D.H.; Machado, B.I.; Ramirez, D.A.; Wicker, R.B.
2010-01-01
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.
Multivariate Discrete First Order Stochastic Dominance
DEFF Research Database (Denmark)
Tarp, Finn; Østerdal, Lars Peter
This paper characterizes the principle of first order stochastic dominance in a multivariate discrete setting. We show that a distribution f first order stochastic dominates distribution g if and only if f can be obtained from g by iteratively shifting density from one outcome to another...
Praet, J.; SANTERMANS, Eva; Reekmans, K.; de Vocht, N.; Le Blon, D.; Hoornaert, C.; Daans, J.; Goossens, H.; Berneman, Z.; HENS, Niel; Van der Linden, A.; Ponsaerts, P.
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 cult...
Energy Technology Data Exchange (ETDEWEB)
Seck Tuoh Mora, J. C. [Instituto Politecnico Nacional, Mexico, D. F. (Mexico)
2001-06-01
We present a review of reversible one dimensional cellular automata and their representation by block permutations. We analyze in detail the behavior of such block permutations to get their characterization. [Spanish] En el siguiente escrito se da una revision a la representacion y comportamiento de automatas celulares unidimensionales reversibles por medio de permutaciones en bloque. Hacemos un analisis detallado del comportamiento de dichas permutaciones para obtener su caracterizacion.
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Valérie Rodrigues
2018-01-01
Full Text Available The tropical bont tick, Amblyomma variegatum, is a tick species of veterinary importance and is considered as one of major pest of ruminants in Africa and in the Caribbean. It causes direct skin lesions, transmits heartwater, and reactivates bovine dermatophilosis. Tick saliva is reported to affect overall host responses through immunomodulatory and anti-inflammatory molecules, among other bioactive molecules. The general objective of this study was to better understand the role of saliva in interaction between the Amblyomma tick and the host using cellular biology approaches and proteomics, and to discuss its impact on disease transmission and/or activation. We first focused on the immuno-modulating effects of semi-fed A. variegatum female saliva on bovine peripheral blood mononuclear cells (PBMC and monocyte-derived macrophages in vitro. We analyzed its immuno-suppressive properties by measuring the effect of saliva on PBMC proliferation, and observed a significant decrease in ConA-stimulated PBMC lymphoproliferation. We then studied the effect of saliva on bovine macrophages using flow cytometry to analyze the expression of MHC-II and co-stimulation molecules (CD40, CD80, and CD86 and by measuring the production of nitric oxide (NO and pro- or anti-inflammatory cytokines. We observed a significant decrease in the expression of MHC-II, CD40, and CD80 molecules, associated with decreased levels of IL-12-p40 and TNF-α and increased level of IL-10, which could explain the saliva-induced modulation of NO. To elucidate these immunomodulatory effects, crude saliva proteins were analyzed using proteomics with an Orbitrap Elite mass spectrometer. Among the 336 proteins identified in A. variegatum saliva, we evidenced bioactive molecules exhibiting anti-inflammatory, immuno-modulatory, and anti-oxidant properties (e.g., serpins, phospholipases A2, heme lipoprotein. We also characterized an intriguing ubiquitination complex that could be involved in
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Baldi Alfonso
2010-07-01
Full Text Available Abstract Background The majority of cancer patients experience dramatic weight loss, due to cachexia and consisting of skeletal muscle and fat tissue wasting. Cachexia is a negative prognostic factor, interferes with therapy and worsens the patients' quality of life by affecting muscle function. Mice bearing ectopically-implanted C26 colon carcinoma are widely used as an experimental model of cancer cachexia. As part of the search for novel clinical and basic research applications for this experimental model, we characterized novel cellular and molecular features of C26-bearing mice. Methods A fragment of C26 tumor was subcutaneously grafted in isogenic BALB/c mice. The mass growth and proliferation rate of the tumor were analyzed. Histological and cytofluorometric analyses were used to assess cell death, ploidy and differentiation of the tumor cells. The main features of skeletal muscle atrophy, which were highlighted by immunohistochemical and electron microscopy analyses, correlated with biochemical alterations. Muscle force and resistance to fatigue were measured and analyzed as major functional deficits of the cachectic musculature. Results We found that the C26 tumor, ectopically implanted in mice, is an undifferentiated carcinoma, which should be referred to as such and not as adenocarcinoma, a common misconception. The C26 tumor displays aneuploidy and histological features typical of transformed cells, incorporates BrdU and induces severe weight loss in the host, which is largely caused by muscle wasting. The latter appears to be due to proteasome-mediated protein degradation, which disrupts the sarcomeric structure and muscle fiber-extracellular matrix interactions. A pivotal functional deficit of cachectic muscle consists in increased fatigability, while the reported loss of tetanic force is not statistically significant following normalization for decreased muscle fiber size. Conclusions We conclude, on the basis of the definition of
Energy Technology Data Exchange (ETDEWEB)
Aulino, Paola [Department of Histology and Medical Embryology, Sapienza University of Rome, Via Scarpa 16, 00161 Rome, Italy and Interuniversity Institute of Myology (Italy); Faiola, Fabio [DVM Veterinarian chief, Health Status and Animal Welfare, Sapienza University of Rome, Via Scarpa 16, 00161 Rome (Italy); Adamo, Sergio; Coletti, Dario; Berardi, Emanuele; Cardillo, Veronica M; Rizzuto, Emanuele; Perniconi, Barbara; Ramina, Carla; Padula, Fabrizio [Department of Histology and Medical Embryology, Sapienza University of Rome, Via Scarpa 16, 00161 Rome, Italy and Interuniversity Institute of Myology (Italy); Spugnini, Enrico P [SAFU Department, Regina Elena Cancer Institute, Via delle Messi d' Oro 156, 00158 Rome (Italy); Baldi, Alfonso [Department Biochemistry, Section of Pathology, Second University of Naples, Via L. Armanni 5, 80138 Naples (Italy)
2010-07-08
The majority of cancer patients experience dramatic weight loss, due to cachexia and consisting of skeletal muscle and fat tissue wasting. Cachexia is a negative prognostic factor, interferes with therapy and worsens the patients' quality of life by affecting muscle function. Mice bearing ectopically-implanted C26 colon carcinoma are widely used as an experimental model of cancer cachexia. As part of the search for novel clinical and basic research applications for this experimental model, we characterized novel cellular and molecular features of C26-bearing mice. A fragment of C26 tumor was subcutaneously grafted in isogenic BALB/c mice. The mass growth and proliferation rate of the tumor were analyzed. Histological and cytofluorometric analyses were used to assess cell death, ploidy and differentiation of the tumor cells. The main features of skeletal muscle atrophy, which were highlighted by immunohistochemical and electron microscopy analyses, correlated with biochemical alterations. Muscle force and resistance to fatigue were measured and analyzed as major functional deficits of the cachectic musculature. We found that the C26 tumor, ectopically implanted in mice, is an undifferentiated carcinoma, which should be referred to as such and not as adenocarcinoma, a common misconception. The C26 tumor displays aneuploidy and histological features typical of transformed cells, incorporates BrdU and induces severe weight loss in the host, which is largely caused by muscle wasting. The latter appears to be due to proteasome-mediated protein degradation, which disrupts the sarcomeric structure and muscle fiber-extracellular matrix interactions. A pivotal functional deficit of cachectic muscle consists in increased fatigability, while the reported loss of tetanic force is not statistically significant following normalization for decreased muscle fiber size. We conclude, on the basis of the definition of cachexia, that ectopically-implanted C26 carcinoma represents a
International Nuclear Information System (INIS)
Aulino, Paola; Faiola, Fabio; Adamo, Sergio; Coletti, Dario; Berardi, Emanuele; Cardillo, Veronica M; Rizzuto, Emanuele; Perniconi, Barbara; Ramina, Carla; Padula, Fabrizio; Spugnini, Enrico P; Baldi, Alfonso
2010-01-01
The majority of cancer patients experience dramatic weight loss, due to cachexia and consisting of skeletal muscle and fat tissue wasting. Cachexia is a negative prognostic factor, interferes with therapy and worsens the patients' quality of life by affecting muscle function. Mice bearing ectopically-implanted C26 colon carcinoma are widely used as an experimental model of cancer cachexia. As part of the search for novel clinical and basic research applications for this experimental model, we characterized novel cellular and molecular features of C26-bearing mice. A fragment of C26 tumor was subcutaneously grafted in isogenic BALB/c mice. The mass growth and proliferation rate of the tumor were analyzed. Histological and cytofluorometric analyses were used to assess cell death, ploidy and differentiation of the tumor cells. The main features of skeletal muscle atrophy, which were highlighted by immunohistochemical and electron microscopy analyses, correlated with biochemical alterations. Muscle force and resistance to fatigue were measured and analyzed as major functional deficits of the cachectic musculature. We found that the C26 tumor, ectopically implanted in mice, is an undifferentiated carcinoma, which should be referred to as such and not as adenocarcinoma, a common misconception. The C26 tumor displays aneuploidy and histological features typical of transformed cells, incorporates BrdU and induces severe weight loss in the host, which is largely caused by muscle wasting. The latter appears to be due to proteasome-mediated protein degradation, which disrupts the sarcomeric structure and muscle fiber-extracellular matrix interactions. A pivotal functional deficit of cachectic muscle consists in increased fatigability, while the reported loss of tetanic force is not statistically significant following normalization for decreased muscle fiber size. We conclude, on the basis of the definition of cachexia, that ectopically-implanted C26 carcinoma represents
Rodrigues, Valérie; Fernandez, Bernard; Vercoutere, Arthur; Chamayou, Léo; Andersen, Alexandre; Vigy, Oana; Demettre, Edith; Seveno, Martial; Aprelon, Rosalie; Giraud-Girard, Ken; Stachurski, Frédéric; Loire, Etienne; Vachiéry, Nathalie; Holzmuller, Philippe
2018-01-01
The tropical bont tick, Amblyomma variegatum, is a tick species of veterinary importance and is considered as one of major pest of ruminants in Africa and in the Caribbean. It causes direct skin lesions, transmits heartwater, and reactivates bovine dermatophilosis. Tick saliva is reported to affect overall host responses through immunomodulatory and anti-inflammatory molecules, among other bioactive molecules. The general objective of this study was to better understand the role of saliva in interaction between the Amblyomma tick and the host using cellular biology approaches and proteomics, and to discuss its impact on disease transmission and/or activation. We first focused on the immuno-modulating effects of semi-fed A. variegatum female saliva on bovine peripheral blood mononuclear cells (PBMC) and monocyte-derived macrophages in vitro. We analyzed its immuno-suppressive properties by measuring the effect of saliva on PBMC proliferation, and observed a significant decrease in ConA-stimulated PBMC lymphoproliferation. We then studied the effect of saliva on bovine macrophages using flow cytometry to analyze the expression of MHC-II and co-stimulation molecules (CD40, CD80, and CD86) and by measuring the production of nitric oxide (NO) and pro- or anti-inflammatory cytokines. We observed a significant decrease in the expression of MHC-II, CD40, and CD80 molecules, associated with decreased levels of IL-12-p40 and TNF-α and increased level of IL-10, which could explain the saliva-induced modulation of NO. To elucidate these immunomodulatory effects, crude saliva proteins were analyzed using proteomics with an Orbitrap Elite mass spectrometer. Among the 336 proteins identified in A. variegatum saliva, we evidenced bioactive molecules exhibiting anti-inflammatory, immuno-modulatory, and anti-oxidant properties (e.g., serpins, phospholipases A2, heme lipoprotein). We also characterized an intriguing ubiquitination complex that could be involved in saliva
Evaluation of Structural Cellular Glass
Adams, M. A.; Zwissler, J. G.
1984-01-01
Preliminary design information presented. First report discusses state of structural-cellular-glass programs as of June 1979. Second report gives further details of program to develop improved cellular glasses and to characterize properties of glasses and commercially available materials.
Lanchier, Nicolas
2017-01-01
Three coherent parts form the material covered in this text, portions of which have not been widely covered in traditional textbooks. In this coverage the reader is quickly introduced to several different topics enriched with 175 exercises which focus on real-world problems. Exercises range from the classics of probability theory to more exotic research-oriented problems based on numerical simulations. Intended for graduate students in mathematics and applied sciences, the text provides the tools and training needed to write and use programs for research purposes. The first part of the text begins with a brief review of measure theory and revisits the main concepts of probability theory, from random variables to the standard limit theorems. The second part covers traditional material on stochastic processes, including martingales, discrete-time Markov chains, Poisson processes, and continuous-time Markov chains. The theory developed is illustrated by a variety of examples surrounding applications such as the ...
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...
Eslami, Sohrab
This dissertation undertakes the theoretical and experimental developments microcantilevers utilized in Atomic Force Microscopy (AFM) with applications to cellular imaging and characterization. The capability of revealing the inhomogeneties or interior of ultra-small materials has been of most interest to many researchers. However, the fundamental concept of signal and image formation remains unexplored and not fully understood. For his, a semi-empirical nonlinear force model is proposed to show that virtual frequency generation, regarded as the simplest synthesized subsurface probe, occurs optimally when the force is tuned to the van der Waals form. This is the first-time observation of a novel theoretical dynamic multi-frequency force microscopy that has not been already reported. Owing to the broad applications of microcantilevers in the nanoscale imaging and microscopic techniques, there is an essential feeling to study and propose a comprehensive model of such systems. Therefore, in the theoretical part of this dissertation, a distributed-parameters representation modeling of the microcantilever along with a general interaction force comprising of two attractive and repulsive components with general amplitude and power terms is studied. This model is investigated in a general 2D Cartesian coordinate to consider the motions of the probe with a tip mass. There is an excitation at the microcantilever's base such that the end of the beam is subject to the proposed general force. These forces are very sensitive to the amplitude and power terms of these parts; on the other hand, atomic intermolecular force is a function of the distance such that this distance itself is also a function of the interaction force that will result in a nonlinear implicit equation. From a parametric study in the probe-sample excitation, it is shown that the predicted behavior of the generated difference-frequency oscillation amplitude agrees well with experimental measurements. Following
Travelling fronts in stochastic Stokes’ drifts
Blanchet, Adrien; Dolbeault, Jean; Kowalczyk, Michał
2008-01-01
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
Thermal expansion behavior in fabricated cellular structures
International Nuclear Information System (INIS)
Oruganti, R.K.; Ghosh, A.K.; Mazumder, J.
2004-01-01
Thermal expansion behavior of cellular structures is of interest in applications where undesirable deformation and failure are caused by thermal expansion mismatch. This report describes the role of processing-induced effects and metallurgical aspects of melt-processed cellular structures, such as a bi-material structure designed to contract on heating, as well as uni-material structures of regular and stochastic topology. This bi-material structure utilized the principle of internal geometric constraints to alter the expansion behavior of the internal ligaments to create overall contraction of the structure. Homogenization design method was used to design the structure, and fabrication was by direct metal deposition by laser melting of powder in another part of a joint effort. The degree of porosity and grain size in the fabricated structure are characterized and related to the laser deposition parameters. The structure was found to contract upon heating over a short range of temperature subsequent to which normal expansion ensued. Also examined in this report are uni-material cellular structures, in which internal constraints arise from residual stress variations caused by the fabrication process, and thereby alter their expansion characteristics. A simple analysis of thermal strain of this material supports the observed thermal expansion behavior
Maina, J. N.; Cowley, H. M.
1998-01-01
Free (surface) avian respiratory macrophages (FARMs) were harvested by lavage of the lung/air-sac system of the rock dove, Columba livia. The presence of FARMs in the atria and infundibula was confirmed by scanning electron microscopy. The respiratory system has developed several cellular defence lines that include surface macrophages, epithelial, subepithelial and interstitial phagocytes, and pulmonary intravascular macrophages (PIMs). Hence, C. livia appears to have a multiple pulmonary cellular protective armoury. Ultrastructurally, the FARMs and the PIMs were similar to the corresponding cells of mammals. The purported high susceptibility of birds to respiratory diseases, a state that has largely been deduced from morbidities and mortalities of commercial birds, and which has chiefly been attributed to paucity of the FARMs, is not supported by the present observations.
Schmidt, Carl R; Shires, Peter; Mootoo, Mary
2012-02-01
Irreversible electroporation (IRE) is a largely non-thermal method for the ablation of solid tumours. The ability of ultrasound (US) to measure the size of the IRE ablation zone was studied in a porcine liver model. Three normal pig livers were treated in vivo with a total of 22 ablations using IRE. Ultrasound was used within minutes after ablation and just prior to liver harvest at either 6 h or 24 h after the procedure. The area of cellular necrosis was measured after staining with nitroblue tetrazolium and the percentage of cell death determined by histomorphometry. Visible changes in the hepatic parenchyma were apparent by US after all 22 ablations using IRE. The mean maximum diameter of the ablation zone measured by US during the procedure was 20.1 ± 2.7 mm. This compared with a mean cellular necrosis zone maximum diameter of 20.3 ± 2.9 mm as measured histologically. The mean percentage of dead cells within the ablation zone was 77% at 6 h and 98% at 24 h after ablation. Ultrasound is a useful modality for measuring the ablation zone within minutes of applying IRE to normal liver tissue. The area of parenchymal change measured by US correlates with the area of cellular necrosis. © 2011 International Hepato-Pancreato-Biliary Association.
Alam, Shahabuddin; Amemiya, Kei; Bernhards, Robert C; Ulrich, Robert G; Waag, David M; Saikh, Kamal U
2015-01-01
Burkholderia pseudomallei infection causes melioidosis and is often characterized by severe sepsis. Although rare in humans, Burkholderia mallei has caused infections in laboratory workers, and the early innate cellular response to B. mallei in human and nonhuman primates has not been characterized. In this study, we examined the primary cellular immune response to B. mallei in PBMC cultures of non-human primates (NHPs), Chlorocebus aethiops (African Green Monkeys), Macaca fascicularis (Cynomolgus macaque), and Macaca mulatta (Rhesus macaque) and humans. Our results demonstrated that B. mallei elicited strong primary pro-inflammatory cytokines (IFN-γ, TNF-α, IL-1β, and IL-6) equivalent to the levels of B. pseudomallei in primary PBMC cultures of NHPs and humans. When we examined IL-1β and other cytokine responses by comparison to Escherichia coli LPS, African Green Monkeys appears to be most responsive to B. mallei than Cynomolgus or Rhesus. Characterization of the immune signaling mechanism for cellular response was conducted by using a ligand induced cell-based reporter assay, and our results demonstrated that MyD88 mediated signaling contributed to the B. mallei and B. pseudomallei induced pro-inflammatory responses. Notably, the induced reporter activity with B. mallei, B. pseudomallei, or purified LPS from these pathogens was inhibited and cytokine production was attenuated by a MyD88 inhibitor. Together, these results show that in the scenario of severe hyper-inflammatory responses to B. mallei infection, MyD88 targeted therapeutic intervention may be a successful strategy for therapy. Published by Elsevier Ltd.
International Nuclear Information System (INIS)
Hu, Yan; Wang, Zesen; Wen, Jingya; Li, Yu
2016-01-01
Highlights: • Deal with environmental quality guidelines absence in risk characterization. • Quantitative represention of uncertainty from environmental quality guidelines. • Quantitative represention of variability from contaminant exposure concentrations. • Establishment of stochastic-fuzzy environmental risk characterization approach framework. - Abstract: 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.
Energy Technology Data Exchange (ETDEWEB)
Hu, Yan [MOE Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China); State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environment Sciences, Beijing 100012 (China); Wang, Zesen [MOE Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China); Wen, Jingya [MOE Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China); Institute of Hydropower and Environment Research, Beijing 100012 (China); Li, Yu, E-mail: liyuxx8@hotmail.com [MOE Key Laboratory of Regional Energy Systems Optimization, Resources and Environmental Research Academy, North China Electric Power University, Beijing 102206 (China)
2016-10-05
Highlights: • Deal with environmental quality guidelines absence in risk characterization. • Quantitative represention of uncertainty from environmental quality guidelines. • Quantitative represention of variability from contaminant exposure concentrations. • Establishment of stochastic-fuzzy environmental risk characterization approach framework. - Abstract: 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.
Turbulent response in a stochastic regime
International Nuclear Information System (INIS)
Molvig, K.; Freidberg, J.P.; Potok, R.; Hirshman, S.P.; Whitson, J.C.; Tajima, T.
1981-06-01
The theory for the non-linear, turbulent response in a system with intrinsic stochasticity is considered. It is argued that perturbative Eulerian theories, such as the Direct Interaction Approximation (DIA), are inherently unsuited to describe such a system. The exponentiation property that characterizes stochasticity appears in the Lagrangian picture and cannot even be defined in the Eulerian representation. An approximation for stochastic systems - the Normal Stochastic Approximation - is developed and states that the perturbed orbit functions (Lagrangian fluctuations) behave as normally distributed random variables. This is independent of the Eulerian statistics and, in fact, we treat the Eulerian fluctuations as fixed. A simple model problem (appropriate for the electron response in the drift wave) is subjected to a series of computer experiments. To within numerical noise the results are in agreement with the Normal Stochastic Approximation. The predictions of the DIA for this mode show substantial qualitative and quantitative departures from the observations
Gomez-Lopez, Nardhy; Romero, Roberto; Plazyo, Olesya; Schwenkel, George; Garcia-Flores, Valeria; Unkel, Ronald; Xu, Yi; Leng, Yaozhu; Hassan, Sonia S; Panaitescu, Bogdan; Cha, Jeeyeon; Dey, Sudhansu K
2017-11-01
Decidual senescence has been considered a mechanism of disease for spontaneous preterm labor in the absence of severe acute inflammation. Yet, signs of cellular senescence have also been observed in the chorioamniotic membranes from women who underwent the physiological process of labor at term. We aimed to investigate whether, in the absence of acute histologic chorioamnionitis, the chorioamniotic membranes from women who underwent spontaneous preterm labor or labor at term exhibit signs of cellular senescence. Chorioamniotic membrane samples were collected from women who underwent spontaneous preterm labor or labor at term. Gestational age-matched nonlabor controls were also included. Senescence-associated genes/proteins were determined using reverse transcription quantitative polymerase chain reaction analysis (n = 7-9 each for array; n = 26-28 each for validation), enzyme-linked immunosorbent assays (n = 7-9 each), immunoblotting (n = 6-7 each), and immunohistochemistry (n = 7-8 each). Senescence-associated β-galactosidase activity (n = 7-11 each) and telomere length (n = 15-22 each) were also evaluated. In the chorioamniotic membranes without acute histologic chorioamnionitis: (1) the expression profile of senescence-associated genes was different between the labor groups (term in labor and preterm in labor) and the nonlabor groups (term no labor and preterm no labor), yet there were differences between the term in labor and preterm in labor groups; (2) most of the differentially expressed genes among the groups were closely related to the tumor suppressor protein (TP53) pathway; (3) the expression of TP53 was down-regulated in the term in labor and preterm in labor groups compared to their nonlabor counterparts; (4) the expression of CDKN1A (gene coding for p21) was up-regulated in the term in labor and preterm in labor groups compared to their nonlabor counterparts; (5) the expression of the cyclin kinase CDK2 and cyclins CCNA2, CCNB1, and
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
F.C. Gruau; J.T. Tromp (John)
1999-01-01
textabstractWe consider the problem of establishing gravity in cellular automata. In particular, when cellular automata states can be partitioned into empty, particle, and wall types, with the latter enclosing rectangular areas, we desire rules that will make the particles fall down and pile up on
Modeling and analysis of stochastic systems
Kulkarni, Vidyadhar G
2011-01-01
Based on the author's more than 25 years of teaching experience, Modeling and Analysis of Stochastic Systems, Second Edition covers the most important classes of stochastic processes used in the modeling of diverse systems, from supply chains and inventory systems to genetics and biological systems. For each class of stochastic process, the text includes its definition, characterization, applications, transient and limiting behavior, first passage times, and cost/reward models. Along with reorganizing the material, this edition revises and adds new exercises and examples. New to the second edi
Directory of Open Access Journals (Sweden)
Youichi Suzuki
2016-01-01
Full Text Available Dengue virus (DENV is one of the most important arthropod-borne pathogens that cause life-threatening diseases in humans. However, no vaccine or specific antiviral is available for dengue. As seen in other RNA viruses, the innate immune system plays a key role in controlling DENV infection and disease outcome. Although the interferon (IFN response, which is central to host protective immunity, has been reported to limit DENV replication, the molecular details of how DENV infection is modulated by IFN treatment are elusive. In this study, by employing a gain-of-function screen using a type I IFN-treated cell-derived cDNA library, we identified a previously uncharacterized gene, C19orf66, as an IFN-stimulated gene (ISG that inhibits DENV replication, which we named Repressor of yield of DENV (RyDEN. Overexpression and gene knockdown experiments revealed that expression of RyDEN confers resistance to all serotypes of DENV in human cells. RyDEN expression also limited the replication of hepatitis C virus, Kunjin virus, Chikungunya virus, herpes simplex virus type 1, and human adenovirus. Importantly, RyDEN was considered to be a crucial effector molecule in the IFN-mediated anti-DENV response. When affinity purification-mass spectrometry analysis was performed, RyDEN was revealed to form a complex with cellular mRNA-binding proteins, poly(A-binding protein cytoplasmic 1 (PABPC1, and La motif-related protein 1 (LARP1. Interestingly, PABPC1 and LARP1 were found to be positive modulators of DENV replication. Since RyDEN influenced intracellular events on DENV replication and, suppression of protein synthesis from DENV-based reporter construct RNA was also observed in RyDEN-expressing cells, our data suggest that RyDEN is likely to interfere with the translation of DENV via interaction with viral RNA and cellular mRNA-binding proteins, resulting in the inhibition of virus replication in infected cells.
Full-Duplex Communications in Large-Scale Cellular Networks
Alammouri, Ahmad
2016-01-01
/downlink interference. This thesis presents a tractable framework, based on stochastic geometry, to study FD communications in multi-tier cellular networks. Particularly, we assess the FD communications effect on the network performance and quantify the associated gains
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 Bichteler-Dellacherie Theorem. The semimartingale property of Gaussian processes is characterized in terms of their covariance function, spectral measure and spectral representation. In addition, representation and expansion of filtration results are provided as well. Special attention is given to moving...... average processes, and when the driving process is a Lévy or a chaos process the semimartingale property is characterized in the filtration spanned by the driving process and in the natural filtration when the latter is a Brownian motion. To obtain some of the above results an integrability of seminorm...
Covy, Jason P; Waxman, Elisa A; Giasson, Benoit I
2012-12-01
Mutations in ATP13A2, which encodes a lysosomal P-type ATPase of unknown function, cause an autosomal recessive parkinsonian syndrome. With mammalian cells, we show that ATP13A2 expression protects against manganese and nickel toxicity, in addition to proteasomal, mitochondrial, and oxidative stress. Consistent with a recessive mode of inheritance of gene defects, disease-causing mutations F182L and G504R are prone to misfolding and do not protect against manganese and nickel toxicity because they are unstable as a result of degradation via the endoplasmic reticulum-associated degradation (ERAD)-proteasome system. The protective effects of ATP13A2 expression are not due to inhibition of apoptotic pathways or a reduction in typical stress pathways, insofar as these pathways are still activated in challenged ATP13A2-expressing cells; however, these cells display a dramatic reduction in the accumulation of oxidized and damaged proteins. These data indicate that, contrary to a previous suggestion, ATP13A2 is unlikely to convey cellular resilience simply by acting as a lysosomal manganese transporter. Consistent with the recent identification of an ATP13A2 recessive mutation in Tibetan terriers that develop neurodegeneration with neuronal ceroid lipofucinoses, our data suggest that ATP13A2 may function to import a cofactor required for the function of a lysosome enzyme(s). Copyright © 2012 Wiley Periodicals, Inc.
Ogawa, Shigeyoshi
2017-01-01
This book presents an elementary introduction to the theory of noncausal stochastic calculus that arises as a natural alternative to the standard theory of stochastic calculus founded in 1944 by Professor Kiyoshi Itô. As is generally known, Itô Calculus is essentially based on the "hypothesis of causality", asking random functions to be adapted to a natural filtration generated by Brownian motion or more generally by square integrable martingale. The intention in this book is to establish a stochastic calculus that is free from this "hypothesis of causality". To be more precise, a noncausal theory of stochastic calculus is developed in this book, based on the noncausal integral introduced by the author in 1979. After studying basic properties of the noncausal stochastic integral, various concrete problems of noncausal nature are considered, mostly concerning stochastic functional equations such as SDE, SIE, SPDE, and others, to show not only the necessity of such theory of noncausal stochastic calculus but ...
International Nuclear Information System (INIS)
Kiesslich, T.; Plaetzer, K.; Oberdanner, C.; Krammer, B.
2003-01-01
Full text: Photodynamic therapy (PDT) can result in apoptosis and/or necrosis. Several steps in the apoptotic program depend on ATP and the intracellular ATP level is one determinant in the decision between apoptosis and necrosis. Therefore, photochemical damage of cellular targets involved in energy supply might play a crucial role for the mode of cell death being executed. The present study aimed at the characterization of changes in cellular energy supply and the associated cell death modes in response to PDT. Using the human epidermoid carcinoma cell line A431 and aluminum (III) phthalocyanine tetrasulfonate (2.5 μM) as a photosensitizer, we studied the changes in mitochondrial function and intracellular ATP-level after irradiation with different light doses. Employing assays for caspase-3 activation and nuclear fragmentation, 50 % of the cells were found to undergo apoptosis after irradiation with light doses between 2.5 to 3.5 J.cm -2 . At light doses above 6 J.cm -2 cells died exclusively by necrosis, indicated by rapid and complete loss of ATP and mitochondrial function and an absence of caspase activation and nuclear fragmentation. With apoptotic cell populations the ATP-level was maintained at near control levels for up to eight hours which was far beyond the onset of morphological changes. These data suggest that necrosis as well as apoptosis can be induced with AIPcS4 mediated PDT and that photo damage in energy supplying cellular targets may influence the mode of cell death. Further, it is speculated that cells undergoing apoptosis after PDT maintain high ATP levels long enough to complete the apoptotic program. (author)
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
Drift-Implicit Multi-Level Monte Carlo Tau-Leap Methods for Stochastic Reaction Networks
Ben Hammouda, Chiheb
2015-01-01
-space and deterministic ones. These stochastic models constitute the theory of stochastic reaction networks (SRNs). Furthermore, in some cases, the dynamics of fast and slow time scales can be well separated and this is characterized by what is called sti
Gal-Mor, Ohad; Suez, Jotham; Elhadad, Dana; Porwollik, Steffen; Leshem, Eyal; Valinsky, Lea; McClelland, Michael; Schwartz, Eliezer; Rahav, Galia
2012-02-01
Enteric fever is an invasive life-threatening systemic disease caused by the Salmonella enterica human-adapted serovars Typhi and Paratyphi. Increasing incidence of infections with Salmonella enterica serovar Paratyphi A and the spreading of its antibiotic-resistant derivates pose a significant health concern in some areas of the world. Herein, we describe a molecular and phenotypic characterization of an S. Paratyphi A strain accounted for a recent paratyphoid outbreak in Nepal that affected at least 37 travelers. Pulsed-field gel electrophoresis analysis of the outbreak isolates revealed one genetic clone (pulsotype), confirming a single infecting source. Genetic profiling of the outbreak strain demonstrated the contribution of specific bacteriophages as a prime source of genetic diversity among clinical isolates of S. Paratyphi A. Phenotypic characterization in comparison with the S. Paratyphi A ATCC 9150 reference sequenced strain showed differences in flagellar morphology and increased abilities of the outbreak strain with respect to its motility, invasion into nonphagocytic cells, intracellular multiplication, survival within macrophages, and higher induction of interleukin-8 (IL-8) secreted by host cells. Collectively, these differences suggest an enhanced virulence potential of this strain and demonstrate an interesting phenotypic variation among S. Paratyphi A isolates. In vivo profiling of 16 inflammatory cytokines in patients infected with the outbreak strain revealed a common profile of a remarkable gamma interferon (IFN-γ) induction together with elevated concentrations of tumor necrosis factor alpha (TNF-α), IL-6, IL-8, IL-10, and IL-15, but not IL-12, which was previously demonstrated as elevated in nontyphoidal Salmonella infections. This apparent profile implies a distinct immune response to paratyphoid infections.
Modeling stochasticity in biochemical reaction networks
International Nuclear Information System (INIS)
Constantino, P H; Vlysidis, M; Smadbeck, P; Kaznessis, Y N
2016-01-01
Small biomolecular systems are inherently stochastic. Indeed, fluctuations of molecular species are substantial in living organisms and may result in significant variation in cellular phenotypes. The chemical master equation (CME) is the most detailed mathematical model that can describe stochastic behaviors. However, because of its complexity the CME has been solved for only few, very small reaction networks. As a result, the contribution of CME-based approaches to biology has been very limited. In this review we discuss the approach of solving CME by a set of differential equations of probability moments, called moment equations. We present different approaches to produce and to solve these equations, emphasizing the use of factorial moments and the zero information entropy closure scheme. We also provide information on the stability analysis of stochastic systems. Finally, we speculate on the utility of CME-based modeling formalisms, especially in the context of synthetic biology efforts. (topical review)
From complex to simple: interdisciplinary stochastic models
International Nuclear Information System (INIS)
Mazilu, D A; Zamora, G; Mazilu, I
2012-01-01
We present two simple, one-dimensional, stochastic models that lead to a qualitative understanding of very complex systems from biology, nanoscience and social sciences. The first model explains the complicated dynamics of microtubules, stochastic cellular highways. Using the theory of random walks in one dimension, we find analytical expressions for certain physical quantities, such as the time dependence of the length of the microtubules, and diffusion coefficients. The second one is a stochastic adsorption model with applications in surface deposition, epidemics and voter systems. We introduce the ‘empty interval method’ and show sample calculations for the time-dependent particle density. These models can serve as an introduction to the field of non-equilibrium statistical physics, and can also be used as a pedagogical tool to exemplify standard statistical physics concepts, such as random walks or the kinetic approach of the master equation. (paper)
Stochastic Thermodynamics: A Dynamical Systems Approach
Directory of Open Access Journals (Sweden)
Tanmay Rajpurohit
2017-12-01
Full Text Available In this paper, we develop an energy-based, large-scale dynamical system model driven by Markov diffusion processes to present a unified framework for statistical thermodynamics predicated on a stochastic dynamical systems formalism. Specifically, using a stochastic state space formulation, we develop a nonlinear stochastic compartmental dynamical system model characterized by energy conservation laws that is consistent with statistical thermodynamic principles. In particular, we show that the difference between the average supplied system energy and the average stored system energy for our stochastic thermodynamic model is a martingale with respect to the system filtration. In addition, we show that the average stored system energy is equal to the mean energy that can be extracted from the system and the mean energy that can be delivered to the system in order to transfer it from a zero energy level to an arbitrary nonempty subset in the state space over a finite stopping time.
Xu, Min; Wu, Tao T; Qu, Jianan Y
2008-01-01
A unified Mie and fractal model for light scattering by biological cells is presented. This model is shown to provide an excellent global agreement with the angular dependent elastic light scattering spectroscopy of cells over the whole visible range (400 to 700 nm) and at all scattering angles (1.1 to 165 deg) investigated. Mie scattering from the bare cell and the nucleus is found to dominate light scattering in the forward directions, whereas the random fluctuation of the background refractive index within the cell, behaving as a fractal random continuous medium, is found to dominate light scattering at other angles. Angularly dependent elastic light scattering spectroscopy aided by the unified Mie and fractal model is demonstrated to be an effective noninvasive approach to characterize biological cells and their internal structures. The acetowhitening effect induced by applying acetic acid on epithelial cells is investigated as an example. The changes in morphology and refractive index of epithelial cells, nuclei, and subcellular structures after the application of acetic acid are successfully probed and quantified using the proposed approach. The unified Mie and fractal model may serve as the foundation for optical detection of precancerous and cancerous changes in biological cells and tissues based on light scattering techniques.
Harrington, Charles R; Storey, John M D; Clunas, Scott; Harrington, Kathleen A; Horsley, David; Ishaq, Ahtsham; Kemp, Steven J; Larch, Christopher P; Marshall, Colin; Nicoll, Sarah L; Rickard, Janet E; Simpson, Michael; Sinclair, James P; Storey, Lynda J; Wischik, Claude M
2015-04-24
Alzheimer disease (AD) is a degenerative tauopathy characterized by aggregation of Tau protein through the repeat domain to form intraneuronal paired helical filaments (PHFs). We report two cell models in which we control the inherent toxicity of the core Tau fragment. These models demonstrate the properties of prion-like recruitment of full-length Tau into an aggregation pathway in which template-directed, endogenous truncation propagates aggregation through the core Tau binding domain. We use these in combination with dissolution of native PHFs to quantify the activity of Tau aggregation inhibitors (TAIs). We report the synthesis of novel stable crystalline leucomethylthioninium salts (LMTX®), which overcome the pharmacokinetic limitations of methylthioninium chloride. LMTX®, as either a dihydromesylate or a dihydrobromide salt, retains TAI activity in vitro and disrupts PHFs isolated from AD brain tissues at 0.16 μM. The Ki value for intracellular TAI activity, which we have been able to determine for the first time, is 0.12 μM. These values are close to the steady state trough brain concentration of methylthioninium ion (0.18 μM) that is required to arrest progression of AD on clinical and imaging end points and the minimum brain concentration (0.13 μM) required to reverse behavioral deficits and pathology in Tau transgenic mice. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.
Elitism and Stochastic Dominance
Bazen, Stephen; Moyes, Patrick
2011-01-01
Stochastic dominance has typically been used with a special emphasis on risk and inequality reduction something captured by the concavity of the utility function in the expected utility model. We claim that the applicability of the stochastic dominance approach goes far beyond risk and inequality measurement provided suitable adpations be made. We apply in the paper the stochastic dominance approach to the measurment of elitism which may be considered the opposite of egalitarianism. While the...
Overview of cellular automaton models for corrosion
International Nuclear Information System (INIS)
Perez-Brokate, Cristian Felipe; De Lamare, Jacques; Dung di Caprio; Feron, Damien; Chausse, Annie
2014-01-01
A review of corrosion process modeling using cellular automata methods is presented. This relatively new and growing approach takes into account the stochastic nature of the phenomena and uses physico-chemical rules to make predictions at a mesoscopic scale. Milestone models are analyzed and perspectives are established. (authors)
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.
100 years after Smoluchowski: stochastic processes in cell biology
International Nuclear Information System (INIS)
Holcman, D; Schuss, Z
2017-01-01
100 years after Smoluchowski introduced his approach to stochastic processes, they are now at the basis of mathematical and physical modeling in cellular biology: they are used for example to analyse and to extract features from a large number (tens of thousands) of single molecular trajectories or to study the diffusive motion of molecules, proteins or receptors. Stochastic modeling is a new step in large data analysis that serves extracting cell biology concepts. We review here Smoluchowski’s approach to stochastic processes and provide several applications for coarse-graining diffusion, studying polymer models for understanding nuclear organization and finally, we discuss the stochastic jump dynamics of telomeres across cell division and stochastic gene regulation. (topical review)
Stochastic analytic regularization
International Nuclear Information System (INIS)
Alfaro, J.
1984-07-01
Stochastic regularization is reexamined, pointing out a restriction on its use due to a new type of divergence which is not present in the unregulated theory. Furthermore, we introduce a new form of stochastic regularization which permits the use of a minimal subtraction scheme to define the renormalized Green functions. (author)
Instantaneous stochastic perturbation theory
International Nuclear Information System (INIS)
Lüscher, Martin
2015-01-01
A form of stochastic perturbation theory is described, where the representative stochastic fields are generated instantaneously rather than through a Markov process. The correctness of the procedure is established to all orders of the expansion and for a wide class of field theories that includes all common formulations of lattice QCD.
Gottwald, G.A.; Crommelin, D.T.; Franzke, C.L.E.; Franzke, C.L.E.; O'Kane, T.J.
2017-01-01
In this chapter we review stochastic modelling methods in climate science. First we provide a conceptual framework for stochastic modelling of deterministic dynamical systems based on the Mori-Zwanzig formalism. The Mori-Zwanzig equations contain a Markov term, a memory term and a term suggestive of
Meyer, Joerg M.
2018-01-01
The contrary of stochastic independence splits up into two cases: pairs of events being favourable or being unfavourable. Examples show that both notions have quite unexpected properties, some of them being opposite to intuition. For example, transitivity does not hold. Stochastic dependence is also useful to explain cases of Simpson's paradox.
Probabilistic Sophistication, Second Order Stochastic Dominance, and Uncertainty Aversion
Simone Cerreia-Vioglio; Fabio Maccheroni; Massimo Marinacci; Luigi Montrucchio
2010-01-01
We study the interplay of probabilistic sophistication, second order stochastic dominance, and uncertainty aversion, three fundamental notions in choice under uncertainty. In particular, our main result, Theorem 2, characterizes uncertainty averse preferences that satisfy second order stochastic dominance, as well as uncertainty averse preferences that are probabilistically sophisticated.
Basic Ideas to Approach Metastability in Probabilistic Cellular Automata
Cirillo, Emilio N. M.; Nardi, Francesca R.; Spitoni, Cristian
2016-01-01
Cellular Automata are discrete--time dynamical systems on a spatially extended discrete space which provide paradigmatic examples of nonlinear phenomena. Their stochastic generalizations, i.e., Probabilistic Cellular Automata, are discrete time Markov chains on lattice with finite single--cell
Stochastic quantization and gravity
International Nuclear Information System (INIS)
Rumpf, H.
1984-01-01
We give a preliminary account of the application of stochastic quantization to the gravitational field. We start in Section I from Nelson's formulation of quantum mechanics as Newtonian stochastic mechanics and only then introduce the Parisi-Wu stochastic quantization scheme on which all the later discussion will be based. In Section II we present a generalization of the scheme that is applicable to fields in physical (i.e. Lorentzian) space-time and treat the free linearized gravitational field in this manner. The most remarkable result of this is the noncausal propagation of conformal gravitons. Moreover the concept of stochastic gauge-fixing is introduced and a complete discussion of all the covariant gauges is given. A special symmetry relating two classes of covariant gauges is exhibited. Finally Section III contains some preliminary remarks on full nonlinear gravity. In particular we argue that in contrast to gauge fields the stochastic gravitational field cannot be transformed to a Gaussian process. (Author)
Greenwood, Priscilla E
2016-01-01
This book describes a large number of open problems in the theory of stochastic neural systems, with the aim of enticing probabilists to work on them. This includes problems arising from stochastic models of individual neurons as well as those arising from stochastic models of the activities of small and large networks of interconnected neurons. The necessary neuroscience background to these problems is outlined within the text, so readers can grasp the context in which they arise. This book will be useful for graduate students and instructors providing material and references for applying probability to stochastic neuron modeling. Methods and results are presented, but the emphasis is on questions where additional stochastic analysis may contribute neuroscience insight. An extensive bibliography is included. Dr. Priscilla E. Greenwood is a Professor Emerita in the Department of Mathematics at the University of British Columbia. Dr. Lawrence M. Ward is a Professor in the Department of Psychology and the Brain...
Stochastic resonance during a polymer translocation process
International Nuclear Information System (INIS)
Mondal, Debasish; Muthukumar, M.
2016-01-01
We have studied the occurrence of stochastic resonance when a flexible polymer chain undergoes a single-file translocation through a nano-pore separating two spherical cavities, under a time-periodic external driving force. The translocation of the chain is controlled by a free energy barrier determined by chain length, pore length, pore-polymer interaction, and confinement inside the donor and receiver cavities. The external driving force is characterized by a frequency and amplitude. By combining the Fokker-Planck formalism for polymer translocation and a two-state model for stochastic resonance, we have derived analytical formulas for criteria for emergence of stochastic resonance during polymer translocation. We show that no stochastic resonance is possible if the free energy barrier for polymer translocation is purely entropic in nature. The polymer chain exhibits stochastic resonance only in the presence of an energy threshold in terms of polymer-pore interactions. Once stochastic resonance is feasible, the chain entropy controls the optimal synchronization conditions significantly.
A stochastic model of hormesis
International Nuclear Information System (INIS)
Yakovlev, A.Yu.; Tsodikov, A.D.; Bass, L.
1993-01-01
In order to describe the life-prolonging effect of some agents that are harmful at higher doses, ionizing radiations in particular, a stochastic model is developed in terms of accumulation and progression of intracellular lesions caused by the environment and by the agent itself. The processes of lesion repair, operating at the molecular and cellular level, are assumed to be responsible for this hormesis effect within the framework of the proposed model. Properties of lifetime distributions, derived for analysis of animal experiments with prolonged and acute irradiation, are given special attention. The model provides efficient means of interpreting experimental findings, as evidenced by its application to analysis of some published data on the hormetic effects of prolonged irradiation and of procaine on animal longevity. 51 refs., 2 figs., 1 tabs
International Nuclear Information System (INIS)
Hildebrand, C.E.; Walters, R.A.
1977-01-01
Progress is reported on the following research projects: chromatin structure; the use of circular synthetic polydeoxynucleotides as substrates for the study of DNA repair enzymes; human cellular kinetic response following exposure to DNA-interactive compounds; histone phosphorylation and chromatin structure in cell proliferation; photoaddition products induced in chromatin by uv light; pollutants and genetic information transfer; altered RNA metabolism as a function of cadmium accumulation and intracellular distribution in cultured cells; and thymidylate chromophore destruction by water free radicals
Ramos, Raddy L; Toia, Alyssa R; Pasternack, Daniel M; Dotzler, Timothy P; Cuoco, Joshua A; Esposito, Anthony W; Le, Megan M; Parker, Alexander K; Goodman, Jeffrey H; Sarkisian, Matthew R
2016-11-19
Subcortical band heterotopia (SBH) are malformations of the human cerebral cortex typically associated with epilepsy and cognitive delay/disability. Rodent models of SBH have demonstrated strong face validity as they are accompanied by both cognitive deficits and spontaneous seizures or reduced seizure threshold. BXD29-Tlr4 lps-2J /J recombinant inbred mice display striking bilateral SBH, partial callosal agenesis, morphological changes in subcortical structures of the auditory pathway, and display sensory deficits in behavioral tests (Rosen et al., 2013; Truong et al., 2013, 2015). Surprisingly, these mice show no cognitive deficits and have a higher seizure threshold to chemi-convulsive treatment (Gabel et al., 2013) making them different than other rodent SBH models described previously. In the present report, we perform a detailed characterization of the cellular and axonal constituents of SBH in BXD29-Tlr4 lps-2J /J mice and demonstrate that various types of interneurons and glia as well as cortical and subcortical projections are found in SBH. In addition, the length of neuronal cilia was reduced in SBH compared to neurons in the overlying and adjacent normotopic cortex. Finally, we describe additional and novel malformations of the hippocampus and neocortex present in BXD29-Tlr4 lps-2J /J mice. Together, our findings in BXD29-Tlr4 lps-2J /J mice are discussed in the context of the known neuroanatomy and phenotype of other SBH rodent models. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.
Liu, Betty R; Winiarz, Jeffrey G; Moon, Jong-Sik; Lo, Shih-Yen; Huang, Yue-Wern; Aronstam, Robert S; Lee, Han-Jung
2013-11-01
Semiconductor nanoparticles, also known as quantum dots (QDs), are widely used in biomedical imaging studies and pharmaceutical research. Cell-penetrating peptides (CPPs) are a group of small peptides that are able to traverse cell membrane and deliver a variety of cargoes into living cells. CPPs deliver QDs into cells with minimal nonspecific absorption and toxic effect. In this study, water-soluble, monodisperse, carboxyl-functionalized indium phosphide (InP)/zinc sulfide (ZnS) QDs coated with polyethylene glycol lipids (designated QInP) were synthesized for the first time. The physicochemical properties (optical absorption, fluorescence and charging state) and cellular internalization of QInP and CPP/QInP complexes were characterized. CPPs noncovalently interact with QInP in vitro to form stable CPP/QInP complexes, which can then efficiently deliver QInP into human A549 cells. The introduction of 500nM of CPP/QInP complexes and QInP at concentrations of less than 1μM did not reduce cell viability. These results indicate that carboxylated and polyethylene-glycolylated (PEGylated) bifunctionalized QInP are biocompatible nanoparticles with potential for use in biomedical imaging studies and drug delivery applications. Copyright © 2013 Elsevier B.V. All rights reserved.
Sequential stochastic optimization
Cairoli, Renzo
1996-01-01
Sequential Stochastic Optimization provides mathematicians and applied researchers with a well-developed framework in which stochastic optimization problems can be formulated and solved. Offering much material that is either new or has never before appeared in book form, it lucidly presents a unified theory of optimal stopping and optimal sequential control of stochastic processes. This book has been carefully organized so that little prior knowledge of the subject is assumed; its only prerequisites are a standard graduate course in probability theory and some familiarity with discrete-paramet
Remarks on stochastic acceleration
International Nuclear Information System (INIS)
Graeff, P.
1982-12-01
Stochastic acceleration and turbulent diffusion are strong turbulence problems since no expansion parameter exists. Hence the problem of finding rigorous results is of major interest both for checking approximations and for reference models. Since we have found a way of constructing such models in the turbulent diffusion case the question of the extension to stochastic acceleration now arises. The paper offers some possibilities illustrated by the case of 'stochastic free fall' which may be particularly interesting in the context of linear response theory. (orig.)
Stochastic processes inference theory
Rao, Malempati M
2014-01-01
This is the revised and enlarged 2nd edition of the authors’ original text, which was intended to be a modest complement to Grenander's fundamental memoir on stochastic processes and related inference theory. The present volume gives a substantial account of regression analysis, both for stochastic processes and measures, and includes recent material on Ridge regression with some unexpected applications, for example in econometrics. The first three chapters can be used for a quarter or semester graduate course on inference on stochastic processes. The remaining chapters provide more advanced material on stochastic analysis suitable for graduate seminars and discussions, leading to dissertation or research work. In general, the book will be of interest to researchers in probability theory, mathematical statistics and electrical and information theory.
Introduction to stochastic calculus
Karandikar, Rajeeva L
2018-01-01
This book sheds new light on stochastic calculus, the branch of mathematics that is most widely applied in financial engineering and mathematical finance. The first book to introduce pathwise formulae for the stochastic integral, it provides a simple but rigorous treatment of the subject, including a range of advanced topics. The book discusses in-depth topics such as quadratic variation, Ito formula, and Emery topology. The authors briefly address continuous semi-martingales to obtain growth estimates and study solution of a stochastic differential equation (SDE) by using the technique of random time change. Later, by using Metivier–Pellumail inequality, the solutions to SDEs driven by general semi-martingales are discussed. The connection of the theory with mathematical finance is briefly discussed and the book has extensive treatment on the representation of martingales as stochastic integrals and a second fundamental theorem of asset pricing. Intended for undergraduate- and beginning graduate-level stud...
Doberkat, Ernst-Erich
2009-01-01
Combining coalgebraic reasoning, stochastic systems and logic, this volume presents the principles of coalgebraic logic from a categorical perspective. Modal logics are also discussed, including probabilistic interpretations and an analysis of Kripke models.
Approximating Preemptive Stochastic Scheduling
Megow Nicole; Vredeveld Tjark
2009-01-01
We present constant approximative policies for preemptive stochastic scheduling. We derive policies with a guaranteed performance ratio of 2 for scheduling jobs with release dates on identical parallel machines subject to minimizing the sum of weighted completion times. Our policies as well as their analysis apply also to the recently introduced more general model of stochastic online scheduling. The performance guarantee we give matches the best result known for the corresponding determinist...
The stochastic goodwill problem
Marinelli, Carlo
2003-01-01
Stochastic control problems related to optimal advertising under uncertainty are considered. In particular, we determine the optimal strategies for the problem of maximizing the utility of goodwill at launch time and minimizing the disutility of a stream of advertising costs that extends until the launch time for some classes of stochastic perturbations of the classical Nerlove-Arrow dynamics. We also consider some generalizations such as problems with constrained budget and with discretionar...
International Nuclear Information System (INIS)
Hueffel, H.
1990-01-01
After a brief review of the BRST formalism and of the Parisi-Wu stochastic quantization method we introduce the BRST stochastic quantization scheme. It allows the second quantization of constrained Hamiltonian systems in a manifestly gauge symmetry preserving way. The examples of the relativistic particle, the spinning particle and the bosonic string are worked out in detail. The paper is closed by a discussion on the interacting field theory associated to the relativistic point particle system. 58 refs. (Author)
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.
On orthogonality preserving quadratic stochastic operators
International Nuclear Information System (INIS)
Mukhamedov, Farrukh; Taha, Muhammad Hafizuddin Mohd
2015-01-01
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
Organization of cellular receptors into a nanoscale junction during HIV-1 adhesion.
Directory of Open Access Journals (Sweden)
Terrence M Dobrowsky
2010-07-01
Full Text Available The fusion of the human immunodeficiency virus type 1 (HIV-1 with its host cell is the target for new antiretroviral therapies. Viral particles interact with the flexible plasma membrane via viral surface protein gp120 which binds its primary cellular receptor CD4 and subsequently the coreceptor CCR5. However, whether and how these receptors become organized at the adhesive junction between cell and virion are unknown. Here, stochastic modeling predicts that, regarding binding to gp120, cellular receptors CD4 and CCR5 form an organized, ring-like, nanoscale structure beneath the virion, which locally deforms the plasma membrane. This organized adhesive junction between cell and virion, which we name the viral junction, is reminiscent of the well-characterized immunological synapse, albeit at much smaller length scales. The formation of an organized viral junction under multiple physiopathologically relevant conditions may represent a novel intermediate step in productive infection.
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.
Sharp asymptotics for stochastic dynamics with parallel updating rule
Nardi, F.R.; Spitoni, C.
2012-01-01
In this paper we study the metastability problem for a stochastic dynamics with a parallel updating rule; in particular we consider a ¿nite volume Probabilistic Cellular Automaton (PCA) in a small external ¿eld at low temperature regime. We are interested in the nucleation of the system, i.e., the
Sharp asymptotics for stochastic dynamics with parallel updating rule
Nardi, F.R.; Spitoni, C.
2012-01-01
In this paper we study the metastability problem for a stochastic dynamics with a parallel updating rule; in particular we consider a finite volume Probabilistic Cellular Automaton (PCA) in a small external field at low temperature regime. We are interested in the nucleation of the system, i.e., the
Sharp Asymptotics for Stochastic Dynamics with Parallel Updating Rule
Nardi, F.R.; Spitoni, C.
2012-01-01
In this paper we study the metastability problem for a stochastic dynamics with a parallel updating rule; in particular we consider a finite volume Probabilistic Cellular Automaton (PCA) in a small external field at low temperature regime. We are interested in the nucleation of the system, i.e.,
Isabey, Daniel; Pelle, Gabriel; André Dias, Sofia; Bottier, Mathieu; Nguyen, Ngoc-Minh; Filoche, Marcel; Louis, Bruno
2016-08-01
Cellular adhesion forces depend on local biological conditions meaning that adhesion characterization must be performed while preserving cellular integrity. We presently postulate that magnetic bead twisting provides an appropriate stress, i.e., basically a clamp, for assessment in living cells of both cellular adhesion and mechanical properties of the cytoskeleton. A global dissociation rate obeying a Bell-type model was used to determine the natural dissociation rate ([Formula: see text]) and a reference stress ([Formula: see text]). These adhesion parameters were determined in parallel to the mechanical properties for a variety of biological conditions in which either adhesion or cytoskeleton was selectively weakened or strengthened by changing successively ligand concentration, actin polymerization level (by treating with cytochalasin D), level of exerted stress (by increasing magnetic torque), and cell environment (by using rigid and soft 3D matrices). On the whole, this multiscale evaluation of the cellular and molecular responses to a controlled stress reveals an evolution which is consistent with stochastic multiple bond theories and with literature results obtained with other molecular techniques. Present results confirm the validity of the proposed bead-twisting approach for its capability to probe cellular and molecular responses in a variety of biological conditions.
Cellular automata analysis and applications
Hadeler, Karl-Peter
2017-01-01
This book focuses on a coherent representation of the main approaches to analyze the dynamics of cellular automata. Cellular automata are an inevitable tool in mathematical modeling. In contrast to classical modeling approaches as partial differential equations, cellular automata are straightforward to simulate but hard to analyze. In this book we present a review of approaches and theories that allow the reader to understand the behavior of cellular automata beyond simulations. The first part consists of an introduction of cellular automata on Cayley graphs, and their characterization via the fundamental Cutis-Hedlund-Lyndon theorems in the context of different topological concepts (Cantor, Besicovitch and Weyl topology). The second part focuses on classification results: What classification follows from topological concepts (Hurley classification), Lyapunov stability (Gilman classification), and the theory of formal languages and grammars (Kůrka classification). These classifications suggest to cluster cel...
International Nuclear Information System (INIS)
Haran, O.; Shvarts, D.; Thieberger, R.
1998-01-01
Classical transport of neutral particles in a binary, scattering, stochastic media is discussed. It is assumed that the cross-sections of the constituent materials and their volume fractions are known. The inner structure of the media is stochastic, but there exist a statistical knowledge about the lump sizes, shapes and arrangement. The transmission through the composite media depends on the specific heterogeneous realization of the media. The current research focuses on the averaged transmission through an ensemble of realizations, frm which an effective cross-section for the media can be derived. The problem of one dimensional transport in stochastic media has been studied extensively [1]. In the one dimensional description of the problem, particles are transported along a line populated with alternating material segments of random lengths. The current work discusses transport in two-dimensional stochastic media. The phenomenon that is unique to the multi-dimensional description of the problem is obstacle bypassing. Obstacle bypassing tends to reduce the opacity of the media, thereby reducing its effective cross-section. The importance of this phenomenon depends on the manner in which the obstacles are arranged in the media. Results of transport simulations in multi-dimensional stochastic media are presented. Effective cross-sections derived from the simulations are compared against those obtained for the one-dimensional problem, and against those obtained from effective multi-dimensional models, which are partially based on a Markovian assumption
Stochastic approach to microphysics
Energy Technology Data Exchange (ETDEWEB)
Aron, J.C.
1987-01-01
The presently widespread idea of ''vacuum population'', together with the quantum concept of vacuum fluctuations leads to assume a random level below that of matter. This stochastic approach starts by a reminder of the author's previous work, first on the relation of diffusion laws with the foundations of microphysics, and then on hadron spectrum. Following the latter, a random quark model is advanced; it gives to quark pairs properties similar to those of a harmonic oscillator or an elastic string, imagined as an explanation to their asymptotic freedom and their confinement. The stochastic study of such interactions as electron-nucleon, jets in e/sup +/e/sup -/ collisions, or pp -> ..pi../sup 0/ + X, gives form factors closely consistent with experiment. The conclusion is an epistemological comment (complementarity between stochastic and quantum domains, E.P.R. paradox, etc...).
Stochastic optimization methods
Marti, Kurt
2005-01-01
Optimization problems arising in practice involve random parameters. For the computation of robust optimal solutions, i.e., optimal solutions being insensitive with respect to random parameter variations, deterministic substitute problems are needed. Based on the distribution of the random data, and using decision theoretical concepts, optimization problems under stochastic uncertainty are converted into deterministic substitute problems. Due to the occurring probabilities and expectations, approximative solution techniques must be applied. Deterministic and stochastic approximation methods and their analytical properties are provided: Taylor expansion, regression and response surface methods, probability inequalities, First Order Reliability Methods, convex approximation/deterministic descent directions/efficient points, stochastic approximation methods, differentiation of probability and mean value functions. Convergence results of the resulting iterative solution procedures are given.
International Nuclear Information System (INIS)
Rumpf, H.
1987-01-01
We begin with a naive application of the Parisi-Wu scheme to linearized gravity. This will lead into trouble as one peculiarity of the full theory, the indefiniteness of the Euclidean action, shows up already at this level. After discussing some proposals to overcome this problem, Minkowski space stochastic quantization will be introduced. This will still not result in an acceptable quantum theory of linearized gravity, as the Feynman propagator turns out to be non-causal. This defect will be remedied only after a careful analysis of general covariance in stochastic quantization has been performed. The analysis requires the notion of a metric on the manifold of metrics, and a natural candidate for this is singled out. With this a consistent stochastic quantization of Einstein gravity becomes possible. It is even possible, at least perturbatively, to return to the Euclidean regime. 25 refs. (Author)
Separable quadratic stochastic operators
International Nuclear Information System (INIS)
Rozikov, U.A.; Nazir, S.
2009-04-01
We consider quadratic stochastic operators, which are separable as a product of two linear operators. Depending on properties of these linear operators we classify the set of the separable quadratic stochastic operators: first class of constant operators, second class of linear and third class of nonlinear (separable) quadratic stochastic operators. Since the properties of operators from the first and second classes are well known, we mainly study the properties of the operators of the third class. We describe some Lyapunov functions of the operators and apply them to study ω-limit sets of the trajectories generated by the operators. We also compare our results with known results of the theory of quadratic operators and give some open problems. (author)
Stochastic cooling at Fermilab
International Nuclear Information System (INIS)
Marriner, J.
1986-08-01
The topics discussed are the stochastic cooling systems in use at Fermilab and some of the techniques that have been employed to meet the particular requirements of the anti-proton source. Stochastic cooling at Fermilab became of paramount importance about 5 years ago when the anti-proton source group at Fermilab abandoned the electron cooling ring in favor of a high flux anti-proton source which relied solely on stochastic cooling to achieve the phase space densities necessary for colliding proton and anti-proton beams. The Fermilab systems have constituted a substantial advance in the techniques of cooling including: large pickup arrays operating at microwave frequencies, extensive use of cryogenic techniques to reduce thermal noise, super-conducting notch filters, and the development of tools for controlling and for accurately phasing the system
International Nuclear Information System (INIS)
Humm, J.L.; Chin, L.M.
1989-01-01
Radiation dose is a useful predictive parameter for describing radiation toxicity in conventional radiotherapy. Traditionally, in vitro radiation biology dose-effect relations are expressed in the form of cell survival curves, a semilog plot of cell survival versus dose. However, the characteristic linear or linear quadratic survival curve shape, for high- and low-LET radiations respectively, is only strictly valid when the radiation dose is uniform across the entire target population. With an external beam of 60 Co gamma rays or x-rays, a uniform field may be readily achievable. When radionuclides are incorporated into a cell milieu, several new problems emerge which can result in a departure from uniformity in energy deposition throughout a cell population. This nonuniformity can have very important consequences for the shape of the survival curve. Cases in which perturbations of source uniformity may arise include: 1. Elemental sources may equilibrate in the cell medium with partition coefficients between the extracellular, cytosol, and nuclear compartments. The effect of preferential cell internalization or binding to cell membrane of some radionuclides can increase or decrease the slope of the survival curve. 2. Radionuclides bound to antibodies, hormones, metabolite precursors, etc., may result in a source localization pattern characteristic of the carrier agent, i.e., the sources may bind to cell surface receptors or antigens, be internalized, bind to secreted antigen concentrated around a fraction of the cell population, or become directly incorporated into the cell DNA. We propose to relate the distribution of energy deposition in cell nuclei to biological correlates of cellular inactivation. The probability of each cell's survival is weighted by its individual radiation burden, and the summation of these probabilities for the cell population can be used to predict the number or fraction of cell survivors
Stochastic Feedforward Control Technique
Halyo, Nesim
1990-01-01
Class of commanded trajectories modeled as stochastic process. Advanced Transport Operating Systems (ATOPS) research and development program conducted by NASA Langley Research Center aimed at developing capabilities for increases in capacities of airports, safe and accurate flight in adverse weather conditions including shear, winds, avoidance of wake vortexes, and reduced consumption of fuel. Advances in techniques for design of modern controls and increased capabilities of digital flight computers coupled with accurate guidance information from Microwave Landing System (MLS). Stochastic feedforward control technique developed within context of ATOPS program.
Markov stochasticity coordinates
International Nuclear Information System (INIS)
Eliazar, Iddo
2017-01-01
Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.
DEFF Research Database (Denmark)
Simonsen, Maria
This thesis treats stochastic systems with switching dynamics. Models with these characteristics are studied from several perspectives. Initially in a simple framework given in the form of stochastic differential equations and, later, in an extended form which fits into the framework of sliding...... mode control. It is investigated how to understand and interpret solutions to models of switched systems, which are exposed to discontinuous dynamics and uncertainties (primarily) in the form of white noise. The goal is to gain knowledge about the performance of the system by interpreting the solution...
Stochastic dynamics and control
Sun, Jian-Qiao; Zaslavsky, George
2006-01-01
This book is a result of many years of author's research and teaching on random vibration and control. It was used as lecture notes for a graduate course. It provides a systematic review of theory of probability, stochastic processes, and stochastic calculus. The feedback control is also reviewed in the book. Random vibration analyses of SDOF, MDOF and continuous structural systems are presented in a pedagogical order. The application of the random vibration theory to reliability and fatigue analysis is also discussed. Recent research results on fatigue analysis of non-Gaussian stress proc
CSIR Research Space (South Africa)
Roux, FS
2013-09-01
Full Text Available Roux Presented at the International Conference on Correlation Optics 2013 Chernivtsi, Ukraine 18-20 September 2013 CSIR National Laser Centre, Pretoria, South Africa – p. 1/24 Contents ⊲ Defining Stochastic Singular Optics (SSO) ⊲ Tools of Stochastic... of vortices: topological charge ±1 (higher order are unstable). Positive and negative vortex densities np(x, y, z) and nn(x, y, z) ⊲ Vortex density: V = np + nn ⊲ Topological charge density: T = np − nn – p. 4/24 Subfields of SSO ⊲ Homogeneous, normally...
Markov stochasticity coordinates
Energy Technology Data Exchange (ETDEWEB)
Eliazar, Iddo, E-mail: iddo.eliazar@intel.com
2017-01-15
Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.
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.
On the Meta Distribution of Coverage Probability in Uplink Cellular Networks
Elsawy, Hesham; Alouini, Mohamed-Slim
2017-01-01
This letter studies the meta distribution of coverage probability (CP), within a stochastic geometry framework, for cellular uplink transmission with fractional path-loss inversion power control. Using the widely accepted Poisson point process (PPP
Load-aware modeling for uplink cellular networks in a multi-channel environment
Alammouri, Ahmad; Elsawy, Hesham; Alouini, Mohamed-Slim
2014-01-01
We exploit tools from stochastic geometry to develop a tractable analytical approach for modeling uplink cellular networks. The developed model is load aware and accounts for per-user power control as well as the limited transmit power constraint
Stochastic quantisation: theme and variation
International Nuclear Information System (INIS)
Klauder, J.R.; Kyoto Univ.
1987-01-01
The paper on stochastic quantisation is a contribution to the book commemorating the sixtieth birthday of E.S. Fradkin. Stochastic quantisation reformulates Euclidean quantum field theory in the language of Langevin equations. The generalised free field is discussed from the viewpoint of stochastic quantisation. An artificial family of highly singular model theories wherein the space-time derivatives are dropped altogether is also examined. Finally a modified form of stochastic quantisation is considered. (U.K.)
Asymptotic problems for stochastic partial differential equations
Salins, Michael
Stochastic partial differential equations (SPDEs) can be used to model systems in a wide variety of fields including physics, chemistry, and engineering. The main SPDEs of interest in this dissertation are the semilinear stochastic wave equations which model the movement of a material with constant mass density that is exposed to both determinstic and random forcing. Cerrai and Freidlin have shown that on fixed time intervals, as the mass density of the material approaches zero, the solutions of the stochastic wave equation converge uniformly to the solutions of a stochastic heat equation, in probability. This is called the Smoluchowski-Kramers approximation. In Chapter 2, we investigate some of the multi-scale behaviors that these wave equations exhibit. In particular, we show that the Freidlin-Wentzell exit place and exit time asymptotics for the stochastic wave equation in the small noise regime can be approximated by the exit place and exit time asymptotics for the stochastic heat equation. We prove that the exit time and exit place asymptotics are characterized by quantities called quasipotentials and we prove that the quasipotentials converge. We then investigate the special case where the equation has a gradient structure and show that we can explicitly solve for the quasipotentials, and that the quasipotentials for the heat equation and wave equation are equal. In Chapter 3, we study the Smoluchowski-Kramers approximation in the case where the material is electrically charged and exposed to a magnetic field. Interestingly, if the system is frictionless, then the Smoluchowski-Kramers approximation does not hold. We prove that the Smoluchowski-Kramers approximation is valid for systems exposed to both a magnetic field and friction. Notably, we prove that the solutions to the second-order equations converge to the solutions of the first-order equation in an Lp sense. This strengthens previous results where convergence was proved in probability.
Stochastic quantization of Proca field
International Nuclear Information System (INIS)
Lim, S.C.
1981-03-01
We discuss the complications that arise in the application of Nelson's stochastic quantization scheme to classical Proca field. One consistent way to obtain spin-one massive stochastic field is given. It is found that the result of Guerra et al on the connection between ground state stochastic field and the corresponding Euclidean-Markov field extends to the spin-one case. (author)
Stochastic Estimation via Polynomial Chaos
2015-10-01
AFRL-RW-EG-TR-2015-108 Stochastic Estimation via Polynomial Chaos Douglas V. Nance Air Force Research...COVERED (From - To) 20-04-2015 – 07-08-2015 4. TITLE AND SUBTITLE 5a. CONTRACT NUMBER Stochastic Estimation via Polynomial Chaos ...This expository report discusses fundamental aspects of the polynomial chaos method for representing the properties of second order stochastic
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)
Schrager, D.F.
2006-01-01
We propose a new model for stochastic mortality. The model is based on the literature on affine term structure models. It satisfies three important requirements for application in practice: analytical tractibility, clear interpretation of the factors and compatibility with financial option pricing
Composite stochastic processes
Kampen, N.G. van
Certain problems in physics and chemistry lead to the definition of a class of stochastic processes. Although they are not Markovian they can be treated explicitly to some extent. In particular, the probability distribution for large times can be found. It is shown to obey a master equation. This
Entropy Production in Stochastics
Directory of Open Access Journals (Sweden)
Demetris Koutsoyiannis
2017-10-01
Full Text Available While the modern definition of entropy is genuinely probabilistic, in entropy production the classical thermodynamic definition, as in heat transfer, is typically used. Here we explore the concept of entropy production within stochastics and, particularly, two forms of entropy production in logarithmic time, unconditionally (EPLT or conditionally on the past and present having been observed (CEPLT. We study the theoretical properties of both forms, in general and in application to a broad set of stochastic processes. A main question investigated, related to model identification and fitting from data, is how to estimate the entropy production from a time series. It turns out that there is a link of the EPLT with the climacogram, and of the CEPLT with two additional tools introduced here, namely the differenced climacogram and the climacospectrum. In particular, EPLT and CEPLT are related to slopes of log-log plots of these tools, with the asymptotic slopes at the tails being most important as they justify the emergence of scaling laws of second-order characteristics of stochastic processes. As a real-world application, we use an extraordinary long time series of turbulent velocity and show how a parsimonious stochastic model can be identified and fitted using the tools developed.
Stochastic modelling of turbulence
DEFF Research Database (Denmark)
Sørensen, Emil Hedevang Lohse
previously been shown to be closely connected to the energy dissipation. The incorporation of the small scale dynamics into the spatial model opens the door to a fully fledged stochastic model of turbulence. Concerning the interaction of wind and wind turbine, a new method is proposed to extract wind turbine...
Research in Stochastic Processes.
1982-10-31
Office of Scientific Research Grant AFOSR F49620 82 C 0009 Period: 1 Noveber 1981 through 31 October 1982 Title: Research in Stochastic Processes Co...STA4ATIS CAMBANIS The work briefly described here was developed in connection with problems arising from and related to the statistical comunication
Stochastic Control - External Models
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...
Stochastic nonlinear beam equations
Czech Academy of Sciences Publication Activity Database
Brzezniak, Z.; Maslowski, Bohdan; Seidler, Jan
2005-01-01
Roč. 132, č. 1 (2005), s. 119-149 ISSN 0178-8051 R&D Projects: GA ČR(CZ) GA201/01/1197 Institutional research plan: CEZ:AV0Z10190503 Keywords : stochastic beam equation * stability Subject RIV: BA - General Mathematics Impact factor: 0.896, year: 2005
Stochastic models for tumoral growth
Escudero, Carlos
2006-02-01
Strong experimental evidence has indicated that tumor growth belongs to the molecular beam epitaxy universality class. This type of growth is characterized by the constraint of cell proliferation to the tumor border and the surface diffusion of cells at the growing edge. Tumor growth is thus conceived as a competition for space between the tumor and the host, and cell diffusion at the tumor border is an optimal strategy adopted for minimizing the pressure and helping tumor development. Two stochastic partial differential equations are reported in this paper in order to correctly model the physical properties of tumoral growth in (1+1) and (2+1) dimensions. The advantage of these models is that they reproduce the correct geometry of the tumor and are defined in terms of polar variables. An analysis of these models allows us to quantitatively estimate the response of the tumor to an unfavorable perturbation during growth.
Directory of Open Access Journals (Sweden)
Li Xing'an
2010-08-01
Full Text Available Abstract Background Cooperation of constituents of the ubiquitin proteasome system (UPS with chaperone proteins in degrading proteins mediate a wide range of cellular processes, such as synaptic function and neurotransmission, gene transcription, protein trafficking, mitochondrial function and metabolism, antioxidant defence mechanisms, and apoptotic signal transduction. It is supposed that constituents of the UPS and chaperone proteins are recruited into aggresomes where aberrant and potentially cytotoxic proteins may be sequestered in an inactive form. Results To determinate the proteomic pattern of synthetic proteasome inhibitor (PSI-induced inclusions in PC12 cells after proteasome inhibition by PSI, we analyzed a fraction of PSI-induced inclusions. A proteomic feature of the isolated fraction was characterized by identification of fifty six proteins including twenty previously reported protein components of Lewy bodies, twenty eight newly identified proteins and eight unknown proteins. These proteins, most of which were recognized as a profile of proteins within cellular processes mediated by the UPS, a profile of constituents of the UPS and a profile of chaperone proteins, are classed into at least nine accepted categories. In addition, prolyl-4-hydroxylase beta polypeptide, an endoplasmic reticulum member of the protein disulfide isomerase family, was validated in the developmental process of PSI-induced inclusions in the cells. Conclusions It is speculated that proteomic characterization of an isolated fraction of PSI-induced inclusions in PC12 cells might offer clues to appearance of aggresomes serving as a cellular defensive response against proteasome inhibition.
Stochastic dynamical models for ecological regime shifts
DEFF Research Database (Denmark)
Møller, Jan Kloppenborg; Carstensen, Jacob; Madsen, Henrik
the physical and biological knowledge of the system, and nonlinearities introduced here can generate regime shifts or enhance the probability of regime shifts in the case of stochastic models, typically characterized by a threshold value for the known driver. A simple model for light competition between...... definition and stability of regimes become less subtle. Ecological regime shifts and their modeling must be viewed in a probabilistic manner, particularly if such model results are to be used in ecosystem management....
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.
Stochastic calculus and applications
Cohen, Samuel N
2015-01-01
Completely revised and greatly expanded, the new edition of this text takes readers who have been exposed to only basic courses in analysis through the modern general theory of random processes and stochastic integrals as used by systems theorists, electronic engineers and, more recently, those working in quantitative and mathematical finance. Building upon the original release of this title, this text will be of great interest to research mathematicians and graduate students working in those fields, as well as quants in the finance industry. New features of this edition include: End of chapter exercises; New chapters on basic measure theory and Backward SDEs; Reworked proofs, examples and explanatory material; Increased focus on motivating the mathematics; Extensive topical index. "Such a self-contained and complete exposition of stochastic calculus and applications fills an existing gap in the literature. The book can be recommended for first-year graduate studies. It will be useful for all who intend to wo...
Some illustrations of stochasticity
International Nuclear Information System (INIS)
Laslett, L.J.
1977-01-01
A complex, and apparently stochastic, character frequently can be seen to occur in the solutions to simple Hamiltonian problems. Such behavior is of interest, and potentially of importance, to designers of particle accelerators--as well as to workers in other fields of physics and related disciplines. Even a slow development of disorder in the motion of particles in a circular accelerator or storage ring could be troublesome, because a practical design requires the beam particles to remain confined in an orderly manner within a narrow beam tube for literally tens of billions of revolutions. The material presented is primarily the result of computer calculations made to investigate the occurrence of ''stochasticity,'' and is organized in a manner similar to that adopted for presentation at a 1974 accelerator conference
Stochastic ice stream dynamics.
Mantelli, Elisa; Bertagni, Matteo Bernard; Ridolfi, Luca
2016-08-09
Ice streams are narrow corridors of fast-flowing ice that constitute the arterial drainage network of ice sheets. Therefore, changes in ice stream flow are key to understanding paleoclimate, sea level changes, and rapid disintegration of ice sheets during deglaciation. The dynamics of ice flow are tightly coupled to the climate system through atmospheric temperature and snow recharge, which are known exhibit stochastic variability. Here we focus on the interplay between stochastic climate forcing and ice stream temporal dynamics. Our work demonstrates that realistic climate fluctuations are able to (i) induce the coexistence of dynamic behaviors that would be incompatible in a purely deterministic system and (ii) drive ice stream flow away from the regime expected in a steady climate. We conclude that environmental noise appears to be crucial to interpreting the past behavior of ice sheets, as well as to predicting their future evolution.
Fractional Stochastic Field Theory
Honkonen, Juha
2018-02-01
Models describing evolution of physical, chemical, biological, social and financial processes are often formulated as differential equations with the understanding that they are large-scale equations for averages of quantities describing intrinsically random processes. Explicit account of randomness may lead to significant changes in the asymptotic behaviour (anomalous scaling) in such models especially in low spatial dimensions, which in many cases may be captured with the use of the renormalization group. Anomalous scaling and memory effects may also be introduced with the use of fractional derivatives and fractional noise. Construction of renormalized stochastic field theory with fractional derivatives and fractional noise in the underlying stochastic differential equations and master equations and the interplay between fluctuation-induced and built-in anomalous scaling behaviour is reviewed and discussed.
Essentials of stochastic processes
Durrett, Richard
2016-01-01
Building upon the previous editions, this textbook is a first course in stochastic processes taken by undergraduate and graduate students (MS and PhD students from math, statistics, economics, computer science, engineering, and finance departments) who have had a course in probability theory. It covers Markov chains in discrete and continuous time, Poisson processes, renewal processes, martingales, and option pricing. One can only learn a subject by seeing it in action, so there are a large number of examples and more than 300 carefully chosen exercises to deepen the reader’s understanding. Drawing from teaching experience and student feedback, there are many new examples and problems with solutions that use TI-83 to eliminate the tedious details of solving linear equations by hand, and the collection of exercises is much improved, with many more biological examples. Originally included in previous editions, material too advanced for this first course in stochastic processes has been eliminated while treatm...
Stochastic porous media equations
Barbu, Viorel; Röckner, Michael
2016-01-01
Focusing on stochastic porous media equations, this book places an emphasis on existence theorems, asymptotic behavior and ergodic properties of the associated transition semigroup. Stochastic perturbations of the porous media equation have reviously been considered by physicists, but rigorous mathematical existence results have only recently been found. The porous media equation models a number of different physical phenomena, including the flow of an ideal gas and the diffusion of a compressible fluid through porous media, and also thermal propagation in plasma and plasma radiation. Another important application is to a model of the standard self-organized criticality process, called the "sand-pile model" or the "Bak-Tang-Wiesenfeld model". The book will be of interest to PhD students and researchers in mathematics, physics and biology.
Stochastic stacking without filters
International Nuclear Information System (INIS)
Johnson, R.P.; Marriner, J.
1982-12-01
The rate of accumulation of antiprotons is a critical factor in the design of p anti p colliders. A design of a system to accumulate higher anti p fluxes is presented here which is an alternative to the schemes used at the CERN AA and in the Fermilab Tevatron I design. Contrary to these stacking schemes, which use a system of notch filters to protect the dense core of antiprotons from the high power of the stack tail stochastic cooling, an eddy current shutter is used to protect the core in the region of the stack tail cooling kicker. Without filters one can have larger cooling bandwidths, better mixing for stochastic cooling, and easier operational criteria for the power amplifiers. In the case considered here a flux of 1.4 x 10 8 per sec is achieved with a 4 to 8 GHz bandwidth
Multistage stochastic optimization
Pflug, Georg Ch
2014-01-01
Multistage stochastic optimization problems appear in many ways in finance, insurance, energy production and trading, logistics and transportation, among other areas. They describe decision situations under uncertainty and with a longer planning horizon. This book contains a comprehensive treatment of today’s state of the art in multistage stochastic optimization. It covers the mathematical backgrounds of approximation theory as well as numerous practical algorithms and examples for the generation and handling of scenario trees. A special emphasis is put on estimation and bounding of the modeling error using novel distance concepts, on time consistency and the role of model ambiguity in the decision process. An extensive treatment of examples from electricity production, asset liability management and inventory control concludes the book
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 split determinant algorithms
International Nuclear Information System (INIS)
Horvatha, Ivan
2000-01-01
I propose a large class of stochastic Markov processes associated with probability distributions analogous to that of lattice gauge theory with dynamical fermions. The construction incorporates the idea of approximate spectral split of the determinant through local loop action, and the idea of treating the infrared part of the split through explicit diagonalizations. I suggest that exact algorithms of practical relevance might be based on Markov processes so constructed
Stochasticity Modeling in Memristors
Naous, Rawan; Al-Shedivat, Maruan; Salama, Khaled N.
2015-01-01
Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital feature for the integration of this nonlinear device into the stochastic electronics realm of study. In this paper, experimentally observed innate stochasticity is modeled in a circuit compatible format. The model proposed is generic and could be incorporated into variants of threshold-based memristor models in which apparent variations in the output hysteresis convey the switching threshold shift. Further application as a noise injection alternative paves the way for novel approaches in the fields of neuromorphic engineering circuits design. On the other hand, extra caution needs to be paid to variability intolerant digital designs based on non-deterministic memristor logic.
Stochasticity Modeling in Memristors
Naous, Rawan
2015-10-26
Diverse models have been proposed over the past years to explain the exhibiting behavior of memristors, the fourth fundamental circuit element. The models varied in complexity ranging from a description of physical mechanisms to a more generalized mathematical modeling. Nonetheless, stochasticity, a widespread observed phenomenon, has been immensely overlooked from the modeling perspective. This inherent variability within the operation of the memristor is a vital feature for the integration of this nonlinear device into the stochastic electronics realm of study. In this paper, experimentally observed innate stochasticity is modeled in a circuit compatible format. The model proposed is generic and could be incorporated into variants of threshold-based memristor models in which apparent variations in the output hysteresis convey the switching threshold shift. Further application as a noise injection alternative paves the way for novel approaches in the fields of neuromorphic engineering circuits design. On the other hand, extra caution needs to be paid to variability intolerant digital designs based on non-deterministic memristor logic.
Stochastic quantization of instantons
International Nuclear Information System (INIS)
Grandati, Y.; Berard, A.; Grange, P.
1996-01-01
The method of Parisi and Wu to quantize classical fields is applied to instanton solutions var-phi I of euclidian non-linear theory in one dimension. The solution var-phi var-epsilon of the corresponding Langevin equation is built through a singular perturbative expansion in var-epsilon=h 1/2 in the frame of the center of the mass of the instanton, where the difference var-phi var-epsilon -var-phi I carries only fluctuations of the instanton form. The relevance of the method is shown for the stochastic K dV equation with uniform noise in space: the exact solution usually obtained by the inverse scattering method is retrieved easily by the singular expansion. A general diagrammatic representation of the solution is then established which makes a thorough use of regrouping properties of stochastic diagrams derived in scalar field theory. Averaging over the noise and in the limit of infinite stochastic time, the authors obtain explicit expressions for the first two orders in var-epsilon of the pertrubed instanton of its Green function. Specializing to the Sine-Gordon and var-phi 4 models, the first anaharmonic correction is obtained analytically. The calculation is carried to second order for the var-phi 4 model, showing good convergence. 21 refs., 5 fig
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
Liang, Jie; Qian, Hong
2010-01-01
Modern molecular biology has always been a great source of inspiration for computational science. Half a century ago, the challenge from understanding macromolecular dynamics has led the way for computations to be part of the tool set to study molecular biology. Twenty-five years ago, the demand from genome science has inspired an entire generation of computer scientists with an interest in discrete mathematics to join the field that is now called bioinformatics. In this paper, we shall lay out a new mathematical theory for dynamics of biochemical reaction systems in a small volume (i.e., mesoscopic) in terms of a stochastic, discrete-state continuous-time formulation, called the chemical master equation (CME). Similar to the wavefunction in quantum mechanics, the dynamically changing probability landscape associated with the state space provides a fundamental characterization of the biochemical reaction system. The stochastic trajectories of the dynamics are best known through the simulations using the Gillespie algorithm. In contrast to the Metropolis algorithm, this Monte Carlo sampling technique does not follow a process with detailed balance. We shall show several examples how CMEs are used to model cellular biochemical systems. We shall also illustrate the computational challenges involved: multiscale phenomena, the interplay between stochasticity and nonlinearity, and how macroscopic determinism arises from mesoscopic dynamics. We point out recent advances in computing solutions to the CME, including exact solution of the steady state landscape and stochastic differential equations that offer alternatives to the Gilespie algorithm. We argue that the CME is an ideal system from which one can learn to understand "complex behavior" and complexity theory, and from which important biological insight can be gained.
Probabilistic cellular automata: Some statistical mechanical considerations
International Nuclear Information System (INIS)
Lebowitz, J.L.; Maes, C.; Speer, E.R.
1990-01-01
Spin systems evolving in continuous or discrete time under the action of stochastic dynamics are used to model phenomena as diverse as the structure of alloys and the functioning of neural networks. While in some cases the dynamics are secondary, designed to produce a specific stationary measure whose properties one is interested in studying, there are other cases in which the only available information is the dynamical rule. Prime examples of the former are computer simulations, via Glauber dynamics, of equilibrium Gibbs measures with a specified interaction potential. Examples of the latter include various types of majority rule dynamics used as models for pattern recognition and for error-tolerant computations. The present note discusses ways in which techniques found useful in equilibrium statistical mechanics can be applied to a particular class of models of the latter types. These are cellular automata with noise: systems in which the spins are updated stochastically at integer times, simultaneously at all sites of some regular lattice. These models were first investigated in detail in the Soviet literature of the late sixties and early seventies. They are now generally referred to as Stochastic or Probabilistic Cellular Automata (PCA), and may be considered to include deterministic automata (CA) as special limits. 16 refs., 3 figs
International Nuclear Information System (INIS)
Emson, P.C.; Westmore, K.; Augood, S.J.
1996-01-01
The chemical phenotype of proneurotensin messenger RNA-expressing cells was determined in the acute haloperidol-treated rat striatum using a combination of [ 35 S]-labelled and alkaline phosphatase-labelled oligonucleotides. Cellular sites of proneurotensin messenger RNA expression were visualized simultaneously on tissue sections processed to reveal cellular sites of preproenkephalin A messenger RNA or the dopamine and adenylate cyclase phosphoprotein-32, messenger RNA. The cellular co-expression of preproenkepahlin A and preprotachykinin messenger RNA was also examined within forebrain structures. Cellular sites of preproenkephalin A and dopamine and adenylate cyclase phosphoprotein-32 messenger RNAs were visualized using alkaline phosphatase-labelled oligonucleotides whilst sites of preprotachykinin and proneurotensin messenger RNA expression were detected using [ 35 S]-labelled oligos. Cellular sites of enkephalin and dopamine and adenylate cyclase phosphoprotein-32 gene expression were identified microscopically by the concentration of purple alkaline phosphatase reaction product within the cell cytoplasm, whereas sites of substance P and proneurotensin gene expression were identified by the dense clustering of silver grains overlying cells.An intense hybridization signal was detected for all three neuropeptide messenger RNAs in the striatum, the nucleus accumbens and septum. Dopamine and adenylate cyclase phosphoprotein-32 messenger RNA was detected within the neostriatum but not within the septum. In all forebrain regions examined, with the exception of the islands of Cajella, the cellular expression of enkephalin messenger RNA and substance P messenger RNA was discordant; the two neuropeptide messenger RNAs were detected essentially in different cells, although in the striatum and nucleus accumbens occasional isolated cells were detected which contained both hybridization signals; dense clusters of silver grains overlay alkaline phosphatase-positive cells
Energy Technology Data Exchange (ETDEWEB)
Emson, P C; Westmore, K; Augood, S J [MRC Molecular Neuroscience Group, The Department of Neurobiology, The Babraham Institute, Babraham, Cambridge (United Kingdom)
1996-12-11
The chemical phenotype of proneurotensin messenger RNA-expressing cells was determined in the acute haloperidol-treated rat striatum using a combination of [{sup 35}S]-labelled and alkaline phosphatase-labelled oligonucleotides. Cellular sites of proneurotensin messenger RNA expression were visualized simultaneously on tissue sections processed to reveal cellular sites of preproenkephalin A messenger RNA or the dopamine and adenylate cyclase phosphoprotein-32, messenger RNA. The cellular co-expression of preproenkepahlin A and preprotachykinin messenger RNA was also examined within forebrain structures. Cellular sites of preproenkephalin A and dopamine and adenylate cyclase phosphoprotein-32 messenger RNAs were visualized using alkaline phosphatase-labelled oligonucleotides whilst sites of preprotachykinin and proneurotensin messenger RNA expression were detected using [{sup 35}S]-labelled oligos. Cellular sites of enkephalin and dopamine and adenylate cyclase phosphoprotein-32 gene expression were identified microscopically by the concentration of purple alkaline phosphatase reaction product within the cell cytoplasm, whereas sites of substance P and proneurotensin gene expression were identified by the dense clustering of silver grains overlying cells.An intense hybridization signal was detected for all three neuropeptide messenger RNAs in the striatum, the nucleus accumbens and septum. Dopamine and adenylate cyclase phosphoprotein-32 messenger RNA was detected within the neostriatum but not within the septum. In all forebrain regions examined, with the exception of the islands of Cajella, the cellular expression of enkephalin messenger RNA and substance P messenger RNA was discordant; the two neuropeptide messenger RNAs were detected essentially in different cells, although in the striatum and nucleus accumbens occasional isolated cells were detected which contained both hybridization signals; dense clusters of silver grains overlay alkaline phosphatase
Stochastic and non-stochastic effects - a conceptual analysis
International Nuclear Information System (INIS)
Karhausen, L.R.
1980-01-01
The attempt to divide radiation effects into stochastic and non-stochastic effects is discussed. It is argued that radiation or toxicological effects are contingently related to radiation or chemical exposure. Biological effects in general can be described by general laws but these laws never represent a necessary connection. Actually stochastic effects express contingent, or empirical, connections while non-stochastic effects represent semantic and non-factual connections. These two expressions stem from two different levels of discourse. The consequence of this analysis for radiation biology and radiation protection is discussed. (author)
Winkler, Dirk; Beconi, Maria; Toledo-Sherman, Leticia M; Prime, Michael; Ebneth, Andreas; Dominguez, Celia; Muñoz-Sanjuan, Ignacio
2013-09-01
Kynurenine monooxygenase (KMO) catalyzes the conversion of kynurenine to 3-hydroxykynurenine. Modulation of KMO activity has been implicated in several neurodegenerative diseases, including Huntington disease. Our goal is to develop potent and selective small-molecule KMO inhibitors with suitable pharmacokinetic characteristics for in vivo proof-of-concept studies and subsequent clinical development. We developed a comprehensive panel of biochemical and cell-based assays that use liquid chromatography/tandem mass spectrometry to quantify unlabeled kynurenine and 3-hydroxykynurenine. We describe assays to measure KMO inhibition in cell and tissue extracts, as well as cellular assays including heterologous cell lines and primary rat microglia and human peripheral blood mononuclear cells.
Fast stochastic algorithm for simulating evolutionary population dynamics
Tsimring, Lev; Hasty, Jeff; Mather, William
2012-02-01
Evolution and co-evolution of ecological communities are stochastic processes often characterized by vastly different rates of reproduction and mutation and a coexistence of very large and very small sub-populations of co-evolving species. This creates serious difficulties for accurate statistical modeling of evolutionary dynamics. In this talk, we introduce a new exact algorithm for fast fully stochastic simulations of birth/death/mutation processes. It produces a significant speedup compared to the direct stochastic simulation algorithm in a typical case when the total population size is large and the mutation rates are much smaller than birth/death rates. We illustrate the performance of the algorithm on several representative examples: evolution on a smooth fitness landscape, NK model, and stochastic predator-prey system.
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.
A retrodictive stochastic simulation algorithm
International Nuclear Information System (INIS)
Vaughan, T.G.; Drummond, P.D.; Drummond, A.J.
2010-01-01
In this paper we describe a simple method for inferring the initial states of systems evolving stochastically according to master equations, given knowledge of the final states. This is achieved through the use of a retrodictive stochastic simulation algorithm which complements the usual predictive stochastic simulation approach. We demonstrate the utility of this new algorithm by applying it to example problems, including the derivation of likely ancestral states of a gene sequence given a Markovian model of genetic mutation.
Stochastic processes and quantum theory
International Nuclear Information System (INIS)
Klauder, J.R.
1975-01-01
The author analyses a variety of stochastic processes, namely real time diffusion phenomena, which are analogues of imaginary time quantum theory and convariant imaginary time quantum field theory. He elaborates some standard properties involving probability measures and stochastic variables and considers a simple class of examples. Finally he develops the fact that certain stochastic theories actually exhibit divergences that simulate those of covariant quantum field theory and presents examples of both renormaizable and unrenormalizable behavior. (V.J.C.)
Stochastic theory of nonequilibrium steady states and its applications. Part I
International Nuclear Information System (INIS)
Zhang Xuejuan; Qian Hong; Qian Min
2012-01-01
The concepts of equilibrium and nonequilibrium steady states are introduced in the present review as mathematical concepts associated with stationary Markov processes. For both discrete stochastic systems with master equations and continuous diffusion processes with Fokker–Planck equations, the nonequilibrium steady state (NESS) is characterized in terms of several key notions which are originated from nonequilibrium physics: time irreversibility, breakdown of detailed balance, free energy dissipation, and positive entropy production rate. After presenting this NESS theory in pedagogically accessible mathematical terms that require only a minimal amount of prerequisites in nonlinear differential equations and the theory of probability, it is applied, in Part I, to two widely studied problems: the stochastic resonance (also known as coherent resonance) and molecular motors (also known as Brownian ratchet). Although both areas have advanced rapidly on their own with a vast amount of literature, the theory of NESS provides them with a unifying mathematical foundation. Part II of this review contains applications of the NESS theory to processes from cellular biochemistry, ranging from enzyme catalyzed reactions, kinetic proofreading, to zeroth-order ultrasensitivity.
Fuzzy Stochastic Optimization Theory, Models and Applications
Wang, Shuming
2012-01-01
Covering in detail both theoretical and practical perspectives, this book is a self-contained and systematic depiction of current fuzzy stochastic optimization that deploys the fuzzy random variable as a core mathematical tool to model the integrated fuzzy random uncertainty. It proceeds in an orderly fashion from the requisite theoretical aspects of the fuzzy random variable to fuzzy stochastic optimization models and their real-life case studies. The volume reflects the fact that randomness and fuzziness (or vagueness) are two major sources of uncertainty in the real world, with significant implications in a number of settings. In industrial engineering, management and economics, the chances are high that decision makers will be confronted with information that is simultaneously probabilistically uncertain and fuzzily imprecise, and optimization in the form of a decision must be made in an environment that is doubly uncertain, characterized by a co-occurrence of randomness and fuzziness. This book begins...
Stochastic control theory dynamic programming principle
Nisio, Makiko
2015-01-01
This book offers a systematic introduction to the optimal stochastic control theory via the dynamic programming principle, which is a powerful tool to analyze control problems. First we consider completely observable control problems with finite horizons. Using a time discretization we construct a nonlinear semigroup related to the dynamic programming principle (DPP), whose generator provides the Hamilton–Jacobi–Bellman (HJB) equation, and we characterize the value function via the nonlinear semigroup, besides the viscosity solution theory. When we control not only the dynamics of a system but also the terminal time of its evolution, control-stopping problems arise. This problem is treated in the same frameworks, via the nonlinear semigroup. Its results are applicable to the American option price problem. Zero-sum two-player time-homogeneous stochastic differential games and viscosity solutions of the Isaacs equations arising from such games are studied via a nonlinear semigroup related to DPP (the min-ma...
Stochastic Analysis with Financial Applications
Kohatsu-Higa, Arturo; Sheu, Shuenn-Jyi
2011-01-01
Stochastic analysis has a variety of applications to biological systems as well as physical and engineering problems, and its applications to finance and insurance have bloomed exponentially in recent times. The goal of this book is to present a broad overview of the range of applications of stochastic analysis and some of its recent theoretical developments. This includes numerical simulation, error analysis, parameter estimation, as well as control and robustness properties for stochastic equations. This book also covers the areas of backward stochastic differential equations via the (non-li
Global properties of cellular automata
International Nuclear Information System (INIS)
Jen, E.
1986-01-01
Cellular automata are discrete mathematical systems that generate diverse, often complicated, behavior using simple deterministic rules. Analysis of the local structure of these rules makes possible a description of the global properties of the associated automata. A class of cellular automata that generate infinitely many aperoidic temporal sequences is defined,a s is the set of rules for which inverses exist. Necessary and sufficient conditions are derived characterizing the classes of ''nearest-neighbor'' rules for which arbitrary finite initial conditions (i) evolve to a homogeneous state; (ii) generate at least one constant temporal sequence
Directory of Open Access Journals (Sweden)
Mayu Sugiyama
2014-12-01
Full Text Available In multicellular organism development, a stochastic cellular response is observed, even when a population of cells is exposed to the same environmental conditions. Retrieving the spatiotemporal regulatory mode hidden in the heterogeneous cellular behavior is a challenging task. The G1/S transition observed in cell cycle progression is a highly stochastic process. By taking advantage of a fluorescence cell cycle indicator, Fucci technology, we aimed to unveil a hidden regulatory mode of cell cycle progression in developing zebrafish. Fluorescence live imaging of Cecyil, a zebrafish line genetically expressing Fucci, demonstrated that newly formed notochordal cells from the posterior tip of the embryonic mesoderm exhibited the red (G1 fluorescence signal in the developing notochord. Prior to their initial vacuolation, these cells showed a fluorescence color switch from red to green, indicating G1/S transitions. This G1/S transition did not occur in a synchronous manner, but rather exhibited a stochastic process, since a mixed population of red and green cells was always inserted between newly formed red (G1 notochordal cells and vacuolating green cells. We termed this mixed population of notochordal cells, the G1/S transition window. We first performed quantitative analyses of live imaging data and a numerical estimation of the probability of the G1/S transition, which demonstrated the existence of a posteriorly traveling regulatory wave of the G1/S transition window. To obtain a better understanding of this regulatory mode, we constructed a mathematical model and performed a model selection by comparing the results obtained from the models with those from the experimental data. Our analyses demonstrated that the stochastic G1/S transition window in the notochord travels posteriorly in a periodic fashion, with doubled the periodicity of the neighboring paraxial mesoderm segmentation. This approach may have implications for the characterization of
Energy Technology Data Exchange (ETDEWEB)
Hardwick, Robert J.; Vennin, Vincent; Wands, David [Institute of Cosmology and Gravitation, University of Portsmouth, Dennis Sciama Building, Burnaby Road, Portsmouth, PO1 3FX (United Kingdom); Byrnes, Christian T.; Torrado, Jesús, E-mail: robert.hardwick@port.ac.uk, E-mail: vincent.vennin@port.ac.uk, E-mail: c.byrnes@sussex.ac.uk, E-mail: jesus.torrado@sussex.ac.uk, E-mail: david.wands@port.ac.uk [Department of Physics and Astronomy, University of Sussex, Brighton BN1 9QH (United Kingdom)
2017-10-01
We study the stochastic distribution of spectator fields predicted in different slow-roll inflation backgrounds. Spectator fields have a negligible energy density during inflation but may play an important dynamical role later, even giving rise to primordial density perturbations within our observational horizon today. During de-Sitter expansion there is an equilibrium solution for the spectator field which is often used to estimate the stochastic distribution during slow-roll inflation. However slow roll only requires that the Hubble rate varies slowly compared to the Hubble time, while the time taken for the stochastic distribution to evolve to the de-Sitter equilibrium solution can be much longer than a Hubble time. We study both chaotic (monomial) and plateau inflaton potentials, with quadratic, quartic and axionic spectator fields. We give an adiabaticity condition for the spectator field distribution to relax to the de-Sitter equilibrium, and find that the de-Sitter approximation is never a reliable estimate for the typical distribution at the end of inflation for a quadratic spectator during monomial inflation. The existence of an adiabatic regime at early times can erase the dependence on initial conditions of the final distribution of field values. In these cases, spectator fields acquire sub-Planckian expectation values. Otherwise spectator fields may acquire much larger field displacements than suggested by the de-Sitter equilibrium solution. We quantify the information about initial conditions that can be obtained from the final field distribution. Our results may have important consequences for the viability of spectator models for the origin of structure, such as the simplest curvaton models.
International Nuclear Information System (INIS)
Hardwick, Robert J.; Vennin, Vincent; Wands, David; Byrnes, Christian T.; Torrado, Jesús
2017-01-01
We study the stochastic distribution of spectator fields predicted in different slow-roll inflation backgrounds. Spectator fields have a negligible energy density during inflation but may play an important dynamical role later, even giving rise to primordial density perturbations within our observational horizon today. During de-Sitter expansion there is an equilibrium solution for the spectator field which is often used to estimate the stochastic distribution during slow-roll inflation. However slow roll only requires that the Hubble rate varies slowly compared to the Hubble time, while the time taken for the stochastic distribution to evolve to the de-Sitter equilibrium solution can be much longer than a Hubble time. We study both chaotic (monomial) and plateau inflaton potentials, with quadratic, quartic and axionic spectator fields. We give an adiabaticity condition for the spectator field distribution to relax to the de-Sitter equilibrium, and find that the de-Sitter approximation is never a reliable estimate for the typical distribution at the end of inflation for a quadratic spectator during monomial inflation. The existence of an adiabatic regime at early times can erase the dependence on initial conditions of the final distribution of field values. In these cases, spectator fields acquire sub-Planckian expectation values. Otherwise spectator fields may acquire much larger field displacements than suggested by the de-Sitter equilibrium solution. We quantify the information about initial conditions that can be obtained from the final field distribution. Our results may have important consequences for the viability of spectator models for the origin of structure, such as the simplest curvaton models.
Portfolio Optimization with Stochastic Dividends and Stochastic Volatility
Varga, Katherine Yvonne
2015-01-01
We consider an optimal investment-consumption portfolio optimization model in which an investor receives stochastic dividends. As a first problem, we allow the drift of stock price to be a bounded function. Next, we consider a stochastic volatility model. In each problem, we use the dynamic programming method to derive the Hamilton-Jacobi-Bellman…
Stochastic ontogenetic growth model
West, B. J.; West, D.
2012-02-01
An ontogenetic growth model (OGM) for a thermodynamically closed system is generalized to satisfy both the first and second law of thermodynamics. The hypothesized stochastic ontogenetic growth model (SOGM) is shown to entail the interspecies allometry relation by explicitly averaging the basal metabolic rate and the total body mass over the steady-state probability density for the total body mass (TBM). This is the first derivation of the interspecies metabolic allometric relation from a dynamical model and the asymptotic steady-state distribution of the TBM is fit to data and shown to be inverse power law.
Stochastic calculus in physics
International Nuclear Information System (INIS)
Fox, R.F.
1987-01-01
The relationship of Ito-Stratonovich stochastic calculus to studies of weakly colored noise is explained. A functional calculus approach is used to obtain an effective Fokker-Planck equation for the weakly colored noise regime. In a smooth limit, this representation produces the Stratonovich version of the Ito-Stratonovich calculus for white noise. It also provides an approach to steady state behavior for strongly colored noise. Numerical simulation algorithms are explored, and a novel suggestion is made for efficient and accurate simulation of white noise equations
The stochastic quality calculus
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...
Stochastic conditional intensity processes
DEFF Research Database (Denmark)
Bauwens, Luc; Hautsch, Nikolaus
2006-01-01
model allows for a wide range of (cross-)autocorrelation structures in multivariate point processes. The model is estimated by simulated maximum likelihood (SML) using the efficient importance sampling (EIS) technique. By modeling price intensities based on NYSE trading, we provide significant evidence......In this article, we introduce the so-called stochastic conditional intensity (SCI) model by extending Russell’s (1999) autoregressive conditional intensity (ACI) model by a latent common dynamic factor that jointly drives the individual intensity components. We show by simulations that the proposed...... for a joint latent factor and show that its inclusion allows for an improved and more parsimonious specification of the multivariate intensity process...
Stochastic cooling for beginners
International Nuclear Information System (INIS)
Moehl, D.
1984-01-01
These two lectures have been prepared to give a simple introduction to the principles. In Part I we try to explain stochastic cooling using the time-domain picture which starts from the pulse response of the system. In Part II the discussion is repeated, looking more closely at the frequency-domain response. An attempt is made to familiarize the beginners with some of the elementary cooling equations, from the 'single particle case' up to equations which describe the evolution of the particle distribution. (orig.)
Trajectory averaging for stochastic approximation MCMC algorithms
Liang, Faming
2010-01-01
to the stochastic approximation Monte Carlo algorithm [Liang, Liu and Carroll J. Amer. Statist. Assoc. 102 (2007) 305-320]. The application of the trajectory averaging estimator to other stochastic approximationMCMC algorithms, for example, a stochastic
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.
Stochastic Blind Motion Deblurring
Xiao, Lei
2015-05-13
Blind motion deblurring from a single image is a highly under-constrained problem with many degenerate solutions. A good approximation of the intrinsic image can therefore only be obtained with the help of prior information in the form of (often non-convex) regularization terms for both the intrinsic image and the kernel. While the best choice of image priors is still a topic of ongoing investigation, this research is made more complicated by the fact that historically each new prior requires the development of a custom optimization method. In this paper, we develop a stochastic optimization method for blind deconvolution. Since this stochastic solver does not require the explicit computation of the gradient of the objective function and uses only efficient local evaluation of the objective, new priors can be implemented and tested very quickly. We demonstrate that this framework, in combination with different image priors produces results with PSNR values that match or exceed the results obtained by much more complex state-of-the-art blind motion deblurring algorithms.
Schilstra, Maria J; Martin, Stephen R
2009-01-01
Stochastic simulations may be used to describe changes with time of a reaction system in a way that explicitly accounts for the fact that molecules show a significant degree of randomness in their dynamic behavior. The stochastic approach is almost invariably used when small numbers of molecules or molecular assemblies are involved because this randomness leads to significant deviations from the predictions of the conventional deterministic (or continuous) approach to the simulation of biochemical kinetics. Advances in computational methods over the three decades that have elapsed since the publication of Daniel Gillespie's seminal paper in 1977 (J. Phys. Chem. 81, 2340-2361) have allowed researchers to produce highly sophisticated models of complex biological systems. However, these models are frequently highly specific for the particular application and their description often involves mathematical treatments inaccessible to the nonspecialist. For anyone completely new to the field to apply such techniques in their own work might seem at first sight to be a rather intimidating prospect. However, the fundamental principles underlying the approach are in essence rather simple, and the aim of this article is to provide an entry point to the field for a newcomer. It focuses mainly on these general principles, both kinetic and computational, which tend to be not particularly well covered in specialist literature, and shows that interesting information may even be obtained using very simple operations in a conventional spreadsheet.
AA, stochastic precooling pickup
CERN PhotoLab
1980-01-01
The freshly injected antiprotons were subjected to fast stochastic "precooling". In this picture of a precooling pickup, the injection orbit is to the left, the stack orbit to the far right. After several seconds of precooling with the system's kickers (in momentum and in the vertical plane), the precooled antiprotons were transferred, by means of RF, to the stack tail, where they were subjected to further stochastic cooling in momentum and in both transverse planes, until they ended up, deeply cooled, in the stack core. During precooling, a shutter near the central orbit shielded the pickups from the signals emanating from the stack-core, whilst the stack-core was shielded from the violent action of the precooling kickers by a shutter on these. All shutters were opened briefly during transfer of the precooled antiprotons to the stack tail. Here, the shutter is not yet mounted. Precooling pickups and kickers had the same design, except that the kickers had cooling circuits and the pickups had none. Peering th...
Behavioral Stochastic Resonance
Freund, Jan A.; Schimansky-Geier, Lutz; Beisner, Beatrix; Neiman, Alexander; Russell, David F.; Yakusheva, Tatyana; Moss, Frank
2001-03-01
Zooplankton emit weak electric fields into the surrounding water that originate from their own muscular activities associated with swimming and feeding. Juvenile paddlefish prey upon single zooplankton by detecting and tracking these weak electric signatures. The passive electric sense in the fish is provided by an elaborate array of electroreceptors, Ampullae Lorenzini, spread over the surface of an elongated rostrum. We have previously shown that the fish use stochastic resonance to enhance prey capture near the detection threshold of their sensory system. But stochastic resonance requires an external source of electrical noise in order to function. The required noise can be provided by a swarm of plankton, for example Daphnia. Thus juvenile paddlefish can detect and attack single Daphnia as outliers in the vicinity of the swarm by making use of noise from the swarm itself. From the power spectral density of the noise plus the weak signal from a single Daphnia we calculate the signal-to-noise ratio and the Fisher information at the surface of the paddlefish's rostrum. The results predict a specific attack pattern for the paddlefish that appears to be experimentally testable.
Stochastic programming with integer recourse
van der Vlerk, Maarten Hendrikus
1995-01-01
In this thesis we consider two-stage stochastic linear programming models with integer recourse. Such models are at the intersection of two different branches of mathematical programming. On the one hand some of the model parameters are random, which places the problem in the field of stochastic
Thermal mixtures in stochastic mechanics
Energy Technology Data Exchange (ETDEWEB)
Guerra, F [Rome Univ. (Italy). Ist. di Matematica; Loffredo, M I [Salerno Univ. (Italy). Ist. di Fisica
1981-01-17
Stochastic mechanics is extended to systems in thermal equilibrium. The resulting stochastic processes are mixtures of Nelson processes. Their Markov property is investigated in some simple cases. It is found that in order to inforce Markov property the algebra of observable associated to the present must be suitably enlarged.
Stochastic Pi-calculus Revisited
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
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.
Brownian motion and stochastic calculus
Karatzas, Ioannis
1998-01-01
This book is designed as a text for graduate courses in stochastic processes. It is written for readers familiar with measure-theoretic probability and discrete-time processes who wish to explore stochastic processes in continuous time. The vehicle chosen for this exposition is Brownian motion, which is presented as the canonical example of both a martingale and a Markov process with continuous paths. In this context, the theory of stochastic integration and stochastic calculus is developed. The power of this calculus is illustrated by results concerning representations of martingales and change of measure on Wiener space, and these in turn permit a presentation of recent advances in financial economics (option pricing and consumption/investment optimization). This book contains a detailed discussion of weak and strong solutions of stochastic differential equations and a study of local time for semimartingales, with special emphasis on the theory of Brownian local time. The text is complemented by a large num...
Zhang, Wenji; Li, Xuedong; Ye, Tiantian; Chen, Fen; Sun, Xiao; Kong, Jun; Yang, Xinggang; Pan, Weisan; Li, Sanming
2013-09-15
This study was to design an innovative nanostructured lipid carrier (NLC) for drug delivery of genistein applied after cataract surgery for the prevention of posterior capsular opacification. NLC loaded with genistein (GEN-NLC) was produced with Compritol 888 ATO, Gelucire 44/14 and Miglyol 812N, stabilized by Solutol(®) HS15 by melt emulsification method. A 2(4) central composite design of 4 independent variables was performed for optimization. Effects of drug concentration, Gelucire 44/14 concentration in total solid lipid, liquid lipid concentration, and surfactant concentration on the mean particle size, polydispersity index, zeta potential and encapsulation efficiency were investigated. Analysis of variance (ANOVA) statistical test was used to assess the optimization. The optimized GEN-NLC showed a homogeneous particle size of 90.16 nm (with PI=0.33) of negatively charged surface (-25.08 mv) and high encapsulation efficiency (91.14%). Particle morphology assessed by TEM revealed a spherical shape. DSC analyses confirmed that GEN was mostly entrapped in amorphous state. In vitro release experiments indicated a prolonged and controlled genistein release for 72 h. In vitro growth inhibition assay showed an effective growth inhibition of GEN-NLCs on human lens epithelial cells (HLECs). Preliminary cellular uptake test proved a enhanced penetration of genistein into HLECs when delivered in NLC. Copyright © 2013 Elsevier B.V. All rights reserved.
Expressing stochastic unravellings using random evolution operators
International Nuclear Information System (INIS)
Salgado, D; Sanchez-Gomez, J L
2002-01-01
We prove how the form of the most general invariant stochastic unravelling for Markovian (recently given in the literature by Wiseman and Diosi) and non-Markovian but Lindblad-type open quantum systems can be attained by imposing a single mathematical condition upon the random evolution operator of the system, namely a.s. trace preservation (a.s. stands for almost surely). The use of random operators ensures the complete positivity of the density operator evolution and characterizes the linear/non-linear character of the evolution in a straightforward way. It is also shown how three quantum stochastic evolution models - continuous spontaneous localization, quantum state diffusion and quantum mechanics with universal position localization - appear as concrete choices for the noise term of the evolution random operators are assumed. We finally conjecture how these operators may in the future be used in two different directions: both to connect quantum stochastic evolution models with random properties of space-time and to handle noisy quantum logical gates
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...
Stochasticity and stereotypy in the Ciona notochord.
Carlson, Maia; Reeves, Wendy; Veeman, Michael
2015-01-15
Fate mapping with single cell resolution has typically been confined to embryos with completely stereotyped development. The lineages giving rise to the 40 cells of the Ciona notochord are invariant, but the intercalation of those cells into a single-file column is not. Here we use genetic labeling methods to fate map the Ciona notochord with both high resolution and large sample sizes. We find that the ordering of notochord cells into a single column is not random, but instead shows a distinctive signature characteristic of mediolaterally-biased intercalation. We find that patterns of cell intercalation in the notochord are somewhat stochastic but far more stereotyped than previously believed. Cell behaviors vary by lineage, with the secondary notochord lineage being much more constrained than the primary lineage. Within the primary lineage, patterns of intercalation reflect the geometry of the intercalating tissue. We identify the latest point at which notochord morphogenesis is largely stereotyped, which is shortly before the onset of mediolateral intercalation and immediately after the final cell divisions in the primary lineage. These divisions are consistently oriented along the AP axis. Our results indicate that the interplay between stereotyped and stochastic cell behaviors in morphogenesis can only be assessed by fate mapping experiments that have both cellular resolution and large sample sizes. Copyright © 2014 Elsevier Inc. All rights reserved.
Morgan, Byron JT; Tanner, Martin Abba; Carlin, Bradley P
2008-01-01
Introduction and Examples Introduction Examples of data sets Basic Model Fitting Introduction Maximum-likelihood estimation for a geometric model Maximum-likelihood for the beta-geometric model Modelling polyspermy Which model? What is a model for? Mechanistic models Function Optimisation Introduction MATLAB: graphs and finite differences Deterministic search methods Stochastic search methods Accuracy and a hybrid approach Basic Likelihood ToolsIntroduction Estimating standard errors and correlations Looking at surfaces: profile log-likelihoods Confidence regions from profiles Hypothesis testing in model selectionScore and Wald tests Classical goodness of fit Model selection biasGeneral Principles Introduction Parameterisation Parameter redundancy Boundary estimates Regression and influence The EM algorithm Alternative methods of model fitting Non-regular problemsSimulation Techniques Introduction Simulating random variables Integral estimation Verification Monte Carlo inference Estimating sampling distributi...
Stochastic population theories
Ludwig, Donald
1974-01-01
These notes serve as an introduction to stochastic theories which are useful in population biology; they are based on a course given at the Courant Institute, New York, in the Spring of 1974. In order to make the material. accessible to a wide audience, it is assumed that the reader has only a slight acquaintance with probability theory and differential equations. The more sophisticated topics, such as the qualitative behavior of nonlinear models, are approached through a succession of simpler problems. Emphasis is placed upon intuitive interpretations, rather than upon formal proofs. In most cases, the reader is referred elsewhere for a rigorous development. On the other hand, an attempt has been made to treat simple, useful models in some detail. Thus these notes complement the existing mathematical literature, and there appears to be little duplication of existing works. The authors are indebted to Miss Jeanette Figueroa for her beautiful and speedy typing of this work. The research was supported by the Na...
Propagator of stochastic electrodynamics
International Nuclear Information System (INIS)
Cavalleri, G.
1981-01-01
The ''elementary propagator'' for the position of a free charged particle subject to the zero-point electromagnetic field with Lorentz-invariant spectral density proportionalω 3 is obtained. The nonstationary process for the position is solved by the stationary process for the acceleration. The dispersion of the position elementary propagator is compared with that of quantum electrodynamics. Finally, the evolution of the probability density is obtained starting from an initial distribution confined in a small volume and with a Gaussian distribution in the velocities. The resulting probability density for the position turns out to be equal, to within radiative corrections, to psipsi* where psi is the Kennard wave packet. If the radiative corrections are retained, the present result is new since the corresponding expression in quantum electrodynamics has not yet been found. Besides preceding quantum electrodynamics for this problem, no renormalization is required in stochastic electrodynamics
RES: Regularized Stochastic BFGS Algorithm
Mokhtari, Aryan; Ribeiro, Alejandro
2014-12-01
RES, a regularized stochastic version of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) quasi-Newton method is proposed to solve convex optimization problems with stochastic objectives. The use of stochastic gradient descent algorithms is widespread, but the number of iterations required to approximate optimal arguments can be prohibitive in high dimensional problems. Application of second order methods, on the other hand, is impracticable because computation of objective function Hessian inverses incurs excessive computational cost. BFGS modifies gradient descent by introducing a Hessian approximation matrix computed from finite gradient differences. RES utilizes stochastic gradients in lieu of deterministic gradients for both, the determination of descent directions and the approximation of the objective function's curvature. Since stochastic gradients can be computed at manageable computational cost RES is realizable and retains the convergence rate advantages of its deterministic counterparts. Convergence results show that lower and upper bounds on the Hessian egeinvalues of the sample functions are sufficient to guarantee convergence to optimal arguments. Numerical experiments showcase reductions in convergence time relative to stochastic gradient descent algorithms and non-regularized stochastic versions of BFGS. An application of RES to the implementation of support vector machines is developed.
Stochastic estimation of electricity consumption
International Nuclear Information System (INIS)
Kapetanovic, I.; Konjic, T.; Zahirovic, Z.
1999-01-01
Electricity consumption forecasting represents a part of the stable functioning of the power system. It is very important because of rationality and increase of control process efficiency and development planning of all aspects of society. On a scientific basis, forecasting is a possible way to solve problems. Among different models that have been used in the area of forecasting, the stochastic aspect of forecasting as a part of quantitative models takes a very important place in applications. ARIMA models and Kalman filter as stochastic estimators have been treated together for electricity consumption forecasting. Therefore, the main aim of this paper is to present the stochastic forecasting aspect using short time series. (author)
Linear stochastic neutron transport theory
International Nuclear Information System (INIS)
Lewins, J.
1978-01-01
A new and direct derivation of the Bell-Pal fundamental equation for (low power) neutron stochastic behaviour in the Boltzmann continuum model is given. The development includes correlation of particle emission direction in induced and spontaneous fission. This leads to generalizations of the backward and forward equations for the mean and variance of neutron behaviour. The stochastic importance for neutron transport theory is introduced and related to the conventional deterministic importance. Defining equations and moment equations are derived and shown to be related to the backward fundamental equation with the detector distribution of the operational definition of stochastic importance playing the role of an adjoint source. (author)
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
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.
Functional Abstraction of Stochastic Hybrid Systems
Bujorianu, L.M.; Blom, Henk A.P.; Hermanns, H.
2006-01-01
The verification problem for stochastic hybrid systems is quite difficult. One method to verify these systems is stochastic reachability analysis. Concepts of abstractions for stochastic hybrid systems are needed to ease the stochastic reachability analysis. In this paper, we set up different ways
An introduction to probability and stochastic processes
Melsa, James L
2013-01-01
Geared toward college seniors and first-year graduate students, this text is designed for a one-semester course in probability and stochastic processes. Topics covered in detail include probability theory, random variables and their functions, stochastic processes, linear system response to stochastic processes, Gaussian and Markov processes, and stochastic differential equations. 1973 edition.
A Stochastic Geometry Model for Multi-hop Highway Vehicular Communication
Farooq, Muhammad Junaid; Elsawy, Hesham; Alouini, Mohamed-Slim
2015-01-01
dissemination. This paper exploits stochastic geometry to develop a tractable and accurate modeling framework to characterize the multi-hop transmissions for vehicular networks in a multi-lane highway setup. In particular, we study the tradeoffs between per
Stochastic backgrounds of gravitational waves
International Nuclear Information System (INIS)
Maggiore, M.
2001-01-01
We review the motivations for the search for stochastic backgrounds of gravitational waves and we compare the experimental sensitivities that can be reached in the near future with the existing bounds and with the theoretical predictions. (author)
Stochastic theories of quantum mechanics
International Nuclear Information System (INIS)
De la Pena, L.; Cetto, A.M.
1991-01-01
The material of this article is organized into five sections. In Sect. I the basic characteristics of quantum systems are briefly discussed, with emphasis on their stochastic properties. In Sect. II a version of stochastic quantum mechanics is presented, to conclude that the quantum formalism admits an interpretation in terms of stochastic processes. In Sect. III the elements of stochastic electrodynamics are described, and its possibilities and limitations as a fundamental theory of quantum systems are discussed. Section IV contains a recent reformulation that overcomes the limitations of the theory discussed in the foregoing section. Finally, in Sect. V the theorems of EPR, Von Neumann and Bell are discussed briefly. The material is pedagogically presented and includes an ample list of references, but the details of the derivations are generally omitted. (Author)
International Nuclear Information System (INIS)
Faris, W.G.
1981-01-01
Dankel has shown how to incorporate spin into stochastic mechanics. The resulting non-local hidden variable theory gives an appealing picture of spin correlation experiments in which Bell's inequality is violated. (orig.)
Statistical inference for stochastic processes
National Research Council Canada - National Science Library
Basawa, Ishwar V; Prakasa Rao, B. L. S
1980-01-01
The aim of this monograph is to attempt to reduce the gap between theory and applications in the area of stochastic modelling, by directing the interest of future researchers to the inference aspects...
Stochastic singular optics (Conference paper)
CSIR Research Space (South Africa)
Roux, FS
2014-09-01
Full Text Available The study of optical vortices in stochastic optical fields involves various quantities, including the vortex density and topological charge density, that are defined in terms of local expectation values of distributions of optical vortices...
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.
Stochastic massless fields I: Integer spin
International Nuclear Information System (INIS)
Lim, S.C.
1981-04-01
Nelson's stochastic quantization scheme is applied to classical massless tensor potential in ''Coulomb'' gauge. The relationship between stochastic potential field in various gauges is discussed using the case of vector potential as an illustration. It is possible to identify the Euclidean tensor potential with the corresponding stochastic field in physical Minkowski space-time. Stochastic quantization of massless fields can also be carried out in terms of field strength tensors. An example of linearized stochastic gravitational field in vacuum is given. (author)
Stochastic lag time in nucleated linear self-assembly
Energy Technology Data Exchange (ETDEWEB)
Tiwari, Nitin S. [Group Theory of Polymers and Soft Matter, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands); Schoot, Paul van der [Group Theory of Polymers and Soft Matter, Eindhoven University of Technology, P.O. Box 513, 5600 MB Eindhoven (Netherlands); Institute for Theoretical Physics, Utrecht University, Leuvenlaan 4, 3584 CE Utrecht (Netherlands)
2016-06-21
Protein aggregation is of great importance in biology, e.g., in amyloid fibrillation. The aggregation processes that occur at the cellular scale must be highly stochastic in nature because of the statistical number fluctuations that arise on account of the small system size at the cellular scale. We study the nucleated reversible self-assembly of monomeric building blocks into polymer-like aggregates using the method of kinetic Monte Carlo. Kinetic Monte Carlo, being inherently stochastic, allows us to study the impact of fluctuations on the polymerization reactions. One of the most important characteristic features in this kind of problem is the existence of a lag phase before self-assembly takes off, which is what we focus attention on. We study the associated lag time as a function of system size and kinetic pathway. We find that the leading order stochastic contribution to the lag time before polymerization commences is inversely proportional to the system volume for large-enough system size for all nine reaction pathways tested. Finite-size corrections to this do depend on the kinetic pathway.
Stochastic theory of fatigue corrosion
Hu, Haiyun
1999-10-01
A stochastic theory of corrosion has been constructed. The stochastic equations are described giving the transportation corrosion rate and fluctuation corrosion coefficient. In addition the pit diameter distribution function, the average pit diameter and the most probable pit diameter including other related empirical formula have been derived. In order to clarify the effect of stress range on the initiation and growth behaviour of pitting corrosion, round smooth specimen were tested under cyclic loading in 3.5% NaCl solution.
Stochastic quantization and gauge theories
International Nuclear Information System (INIS)
Kolck, U. van.
1987-01-01
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) [pt
Stochasticity induced by coherent wavepackets
International Nuclear Information System (INIS)
Fuchs, V.; Krapchev, V.; Ram, A.; Bers, A.
1983-02-01
We consider the momentum transfer and diffusion of electrons periodically interacting with a coherent longitudinal wavepacket. Such a problem arises, for example, in lower-hybrid current drive. We establish the stochastic threshold, the stochastic region δv/sub stoch/ in velocity space, the associated momentum transfer j, and the diffusion coefficient D. We concentrate principally on the weak-field regime, tau/sub autocorrelation/ < tau/sub bounce/
Stochastic runaway of dynamical systems
International Nuclear Information System (INIS)
Pfirsch, D.; Graeff, P.
1984-10-01
One-dimensional, stochastic, dynamical systems are well studied with respect to their stability properties. Less is known for the higher dimensional case. This paper derives sufficient and necessary criteria for the asymptotic divergence of the entropy (runaway) and sufficient ones for the moments of n-dimensional, stochastic, dynamical systems. The crucial implication is the incompressibility of their flow defined by the equations of motion in configuration space. Two possible extensions to compressible flow systems are outlined. (orig.)
Stochastic Models of Polymer Systems
2016-01-01
Distribution Unlimited Final Report: Stochastic Models of Polymer Systems The views, opinions and/or findings contained in this report are those of the...ADDRESS. Princeton University PO Box 0036 87 Prospect Avenue - 2nd floor Princeton, NJ 08544 -2020 14-Mar-2014 ABSTRACT Number of Papers published in...peer-reviewed journals: Number of Papers published in non peer-reviewed journals: Final Report: Stochastic Models of Polymer Systems Report Title
Stochastic efficiency: five case studies
International Nuclear Information System (INIS)
Proesmans, Karel; Broeck, Christian Van den
2015-01-01
Stochastic efficiency is evaluated in five case studies: driven Brownian motion, effusion with a thermo-chemical and thermo-velocity gradient, a quantum dot and a model for information to work conversion. The salient features of stochastic efficiency, including the maximum of the large deviation function at the reversible efficiency, are reproduced. The approach to and extrapolation into the asymptotic time regime are documented. (paper)
Optimal Liquidation under Stochastic Liquidity
Becherer, Dirk; Bilarev, Todor; Frentrup, Peter
2016-01-01
We solve explicitly a two-dimensional singular control problem of finite fuel type for infinite time horizon. The problem stems from the optimal liquidation of an asset position in a financial market with multiplicative and transient price impact. Liquidity is stochastic in that the volume effect process, which determines the inter-temporal resilience of the market in spirit of Predoiu, Shaikhet and Shreve (2011), is taken to be stochastic, being driven by own random noise. The optimal contro...
Memory effects on stochastic resonance
Neiman, Alexander; Sung, Wokyung
1996-02-01
We study the phenomenon of stochastic resonance (SR) in a bistable system with internal colored noise. In this situation the system possesses time-dependent memory friction connected with noise via the fluctuation-dissipation theorem, so that in the absence of periodic driving the system approaches the thermodynamic equilibrium state. For this non-Markovian case we find that memory usually suppresses stochastic resonance. However, for a large memory time SR can be enhanced by the memory.
Stochastic 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.
Stochastic quantization and gauge invariance
International Nuclear Information System (INIS)
Viana, R.L.
1987-01-01
A survey of the fundamental ideas about Parisi-Wu's Stochastic Quantization Method, with applications to Scalar, Gauge and Fermionic theories, is done. In particular, the Analytic Stochastic Regularization Scheme is used to calculate the polarization tensor for Quantum Electrodynamics with Dirac bosons or Fermions. The regularization influence is studied for both theories and an extension of this method for some supersymmetrical models is suggested. (author)
Stochastic Analysis and Related Topics
Ustunel, Ali
1988-01-01
The Silvri Workshop was divided into a short summer school and a working conference, producing lectures and research papers on recent developments in stochastic analysis on Wiener space. The topics treated in the lectures relate to the Malliavin calculus, the Skorohod integral and nonlinear functionals of white noise. Most of the research papers are applications of these subjects. This volume addresses researchers and graduate students in stochastic processes and theoretical physics.
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
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...... 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...
Phenomenology of stochastic exponential growth
Pirjol, Dan; Jafarpour, Farshid; Iyer-Biswas, Srividya
2017-06-01
Stochastic exponential growth is observed in a variety of contexts, including molecular autocatalysis, nuclear fission, population growth, inflation of the universe, viral social media posts, and financial markets. Yet literature on modeling the phenomenology of these stochastic dynamics has predominantly focused on one model, geometric Brownian motion (GBM), which can be described as the solution of a Langevin equation with linear drift and linear multiplicative noise. Using recent experimental results on stochastic exponential growth of individual bacterial cell sizes, we motivate the need for a more general class of phenomenological models of stochastic exponential growth, which are consistent with the observation that the mean-rescaled distributions are approximately stationary at long times. We show that this behavior is not consistent with GBM, instead it is consistent with power-law multiplicative noise with positive fractional powers. Therefore, we consider this general class of phenomenological models for stochastic exponential growth, provide analytical solutions, and identify the important dimensionless combination of model parameters, which determines the shape of the mean-rescaled distribution. We also provide a prescription for robustly inferring model parameters from experimentally observed stochastic growth trajectories.
Stochastic Effects in Microstructure
Directory of Open Access Journals (Sweden)
Glicksman M.E.
2002-01-01
Full Text Available We are currently studying microstructural responses to diffusion-limited coarsening in two-phase materials. A mathematical solution to late-stage multiparticle diffusion in finite systems is formulated with account taken of particle-particle interactions and their microstructural correlations, or "locales". The transition from finite system behavior to that for an infinite microstructure is established analytically. Large-scale simulations of late-stage phase coarsening dynamics show increased fluctuations with increasing volume fraction, Vv, of the mean flux entering or leaving particles of a given size class. Fluctuations about the mean flux were found to depend on the scaled particle size, R/, where R is the radius of a particle and is the radius of the dispersoid averaged over the population within the microstructure. Specifically, small (shrinking particles tend to display weak fluctuations about their mean flux, whereas particles of average, or above average size, exhibit strong fluctuations. Remarkably, even in cases of microstructures with a relatively small volume fraction (Vv ~ 10-4, the particle size distribution is broader than that for the well-known Lifshitz-Slyozov limit predicted at zero volume fraction. The simulation results reported here provide some additional surprising insights into the effect of diffusion interactions and stochastic effects during evolution of a microstructure, as it approaches its thermodynamic end-state.
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...
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...
Stochastic partial differential equations
Lototsky, Sergey V
2017-01-01
Taking readers with a basic knowledge of probability and real analysis to the frontiers of a very active research discipline, this textbook provides all the necessary background from functional analysis and the theory of PDEs. It covers the main types of equations (elliptic, hyperbolic and parabolic) and discusses different types of random forcing. The objective is to give the reader the necessary tools to understand the proofs of existing theorems about SPDEs (from other sources) and perhaps even to formulate and prove a few new ones. Most of the material could be covered in about 40 hours of lectures, as long as not too much time is spent on the general discussion of stochastic analysis in infinite dimensions. As the subject of SPDEs is currently making the transition from the research level to that of a graduate or even undergraduate course, the book attempts to present enough exercise material to fill potential exams and homework assignments. Exercises appear throughout and are usually directly connected ...
AA, stochastic precooling kicker
CERN PhotoLab
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...
International Nuclear Information System (INIS)
Ghiamkazemi, S.; Amanzadeh, A.; Dinarvand, R.; Rafiee-Tehrani, M.; Amini, M.; Ghiamkazemi, S.; Dinarvand, R.; Rafiee-Tehrani, M.; Ghiamkazemi, S.; Rafiee-Tehrani, M.; Amanzadeh, A.; Rafiee-Tehrani, M.
2010-01-01
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.
Wireless Cellular Mobile Communications
Zalud, V.
2002-01-01
In this article is briefly reviewed the history of wireless cellular mobile communications, examined the progress in current second generation (2G) cellular standards and discussed their migration to the third generation (3G). The European 2G cellular standard GSM and its evolution phases GPRS and EDGE are described somewhat in detail. The third generation standard UMTS taking up on GSM/GPRS core network and equipped with a new advanced access network on the basis of code division multiple ac...
The stochastic seasonal behavior of energy commodity convenience yields
International Nuclear Information System (INIS)
Mirantes, Andrés García; Población, Javier; Serna, Gregorio
2013-01-01
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.
Biomechanics of cellular solids.
Gibson, Lorna J
2005-03-01
Materials with a cellular structure are widespread in nature and include wood, cork, plant parenchyma and trabecular bone. Natural cellular materials are often mechanically efficient: the honeycomb-like microstructure of wood, for instance, gives it an exceptionally high performance index for resisting bending and buckling. Here we review the mechanics of a wide range of natural cellular materials and examine their role in lightweight natural sandwich structures (e.g. iris leaves) and natural tubular structures (e.g. plant stems or animal quills). We also describe two examples of engineered biomaterials with a cellular structure, designed to replace or regenerate tissue in the body.
Sharp asymptotics for stochastic dynamics with parallel updating rule with self-interaction
Bovier, A.; Nardi, F.R.; Spitoni, C.
2011-01-01
In this paper we study metastability for a stochastic dynamics with a parallel updating rule in particular for a probabilistic cellular automata. The problem is addressed in the Freidlin Wentzel regime, i.e., finite volume, small magnetic field, and in the limit when temperature tends to zero. We
Directory of Open Access Journals (Sweden)
María del Carmen Clares Pochet
2012-09-01
Full Text Available Se realizó un estudio descriptivo y transversal de 30 féminas con infección por el virus del papiloma humano, atendidas en la consulta de Inmunología del Policlínico de Especialidades perteneciente al Hospital Provincial Docente Clinicoquirúrgico "Saturnino Lora Torres" de Santiago de Cuba, desde junio del 2009 hasta igual mes del 2010, a fin de caracterizarlas según la respuesta inmunitaria. Para evaluar la respuesta inmune celular y humoral se empleó el test de rosetas y la cuantificación de inmunoglobulinas, respectivamente. En la serie prevaleció la infección por el virus antes mencionado en las mujeres de 25-35 años (40,0 %, en especial las procedentes de la zona urbana y se evidenció una disminución de la respuesta celular significativa con relación a la humoral.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 immunoglobulines 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.
Mobility-Aware User Association in Uplink Cellular Networks
Arshad, Rabe
2017-07-20
This letter studies the mobility aware user-to-BS association policies, within a stochastic geometry framework, in two tier uplink cellular networks with fractional channel inversion power control. Particularly, we model the base stations’ locations using the widely accepted poisson point process and obtain the coverage probability and handover cost expressions for the coupled and decoupled uplink and downlink associations. To this end, we compute the average throughput for the mobile users and study the merits and demerits of each association strategy.
Mobility-Aware User Association in Uplink Cellular Networks
Arshad, Rabe; Elsawy, Hesham; Sorour, Sameh; Alouini, Mohamed-Slim; Al-Naffouri, Tareq Y.
2017-01-01
This letter studies the mobility aware user-to-BS association policies, within a stochastic geometry framework, in two tier uplink cellular networks with fractional channel inversion power control. Particularly, we model the base stations’ locations using the widely accepted poisson point process and obtain the coverage probability and handover cost expressions for the coupled and decoupled uplink and downlink associations. To this end, we compute the average throughput for the mobile users and study the merits and demerits of each association strategy.
On Number of Almost Blank Subframes in Heterogeneous Cellular Networks
Cierny, Michal; Wang, Haining; Wichman, Risto; Ding, Zhi; Wijting, Carl
2013-01-01
In heterogeneous cellular scenarios with macrocells, femtocells or picocells users may suffer from significant co-channel cross-tier interference. To manage this interference 3GPP introduced almost blank subframe (ABSF), a subframe in which the interferer tier is not allowed to transmit data. Vulnerable users thus get a chance to be scheduled in ABSFs with reduced cross-tier interference. We analyze downlink scenarios using stochastic geometry and formulate a condition for the required number...
Symmetry pattern transition in cellular automata with complex behavior
International Nuclear Information System (INIS)
Sanchez, Juan R.; Lopez-Ruiz, Ricardo
2008-01-01
A transition from asymmetric to symmetric patterns in time-dependent extended systems is described. It is shown that one dimensional cellular automata, started from fully random initial conditions, can be forced to evolve into complex symmetrical patterns by stochastically coupling a proportion p of pairs of sites located at equal distance from the center of the lattice. A nontrivial critical value of p must be surpassed in order to obtain symmetrical patterns during the evolution. This strategy is able to classify the cellular automata rules - with complex behavior - between those that support time-dependent symmetric patterns and those which do not support such kind of patterns
Linearizable cellular automata
International Nuclear Information System (INIS)
Nobe, Atsushi; Yura, Fumitaka
2007-01-01
The initial value problem for a class of reversible elementary cellular automata with periodic boundaries is reduced to an initial-boundary value problem for a class of linear systems on a finite commutative ring Z 2 . Moreover, a family of such linearizable cellular automata is given
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 Still Water Response Model
DEFF Research Database (Denmark)
Friis-Hansen, Peter; Ditlevsen, Ove Dalager
2002-01-01
In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model is...... out that an important parameter of the stochastic cargo field model is the mean number of containers delivered by each customer.......In this study a stochastic field model for the still water loading is formulated where the statistics (mean value, standard deviation, and correlation) of the sectional forces are obtained by integration of the load field over the relevant part of the ship structure. The objective of the model...... is to establish the stochastic load field conditional on a given draft and trim of the vessel. The model contributes to a realistic modelling of the stochastic load processes to be used in a reliability evaluation of the ship hull. Emphasis is given to container vessels. The formulation of the model for obtaining...
Stochastic quantization and topological theories
International Nuclear Information System (INIS)
Fainberg, V.Y.; Subbotin, A.V.; Kuznetsov, A.N.
1992-01-01
In the last two years topological quantum field theories (TQFT) have attached much attention. This paper reports that from the very beginning it was realized that due to a peculiar BRST-like symmetry these models admitted so-called Nicolai mapping: the Nicolai variables, in terms of which actions of the theories become gaussian, are nothing but (anti-) selfduality conditions or their generalizations. This fact became a starting point in the quest of possible stochastic interpretation to topological field theories. The reasons behind were quite simple and included, in particular, the well-known relations between stochastic processes and supersymmetry. The main goal would have been achieved, if it were possible to construct stochastic processes governed by Langevin or Fokker-Planck equations in a real Euclidean time leading to TQFT's path integrals (equivalently: to reformulate TQFTs as non-equilibrium phase dynamics of stochastic processes). Further on, if it would appear that these processes correspond to the stochastic quantization of theories of some definite kind, one could expect (d + 1)-dimensional TQFTs to share some common properties with d-dimensional ones
Stochastic quantization of Einstein gravity
International Nuclear Information System (INIS)
Rumpf, H.
1986-01-01
We determine a one-parameter family of covariant Langevin equations for the metric tensor of general relativity corresponding to DeWitt's one-parameter family of supermetrics. The stochastic source term in these equations can be expressed in terms of a Gaussian white noise upon the introduction of a stochastic tetrad field. The only physically acceptable resolution of a mathematical ambiguity in the ansatz for the source term is the adoption of Ito's calculus. By taking the formal equilibrium limit of the stochastic metric a one-parameter family of covariant path-integral measures for general relativity is obtained. There is a unique parameter value, distinguished by any one of the following three properties: (i) the metric is harmonic with respect to the supermetric, (ii) the path-integral measure is that of DeWitt, (iii) the supermetric governs the linearized Einstein dynamics. Moreover the Feynman propagator corresponding to this parameter is causal. Finally we show that a consistent stochastic perturbation theory gives rise to a new type of diagram containing ''stochastic vertices.''
Joseph, Bindu; Corwin, Jason A.; Kliebenstein, Daniel J.
2015-01-01
Recent studies are starting to show that genetic control over stochastic variation is a key evolutionary solution of single celled organisms in the face of unpredictable environments. This has been expanded to show that genetic variation can alter stochastic variation in transcriptional processes within multi-cellular eukaryotes. However, little is known about how genetic diversity can control stochastic variation within more non-cell autonomous phenotypes. Using an Arabidopsis reciprocal RIL population, we showed that there is significant genetic diversity influencing stochastic variation in the plant metabolome, defense chemistry, and growth. This genetic diversity included loci specific for the stochastic variation of each phenotypic class that did not affect the other phenotypic classes or the average phenotype. This suggests that the organism's networks are established so that noise can exist in one phenotypic level like metabolism and not permeate up or down to different phenotypic levels. Further, the genomic variation within the plastid and mitochondria also had significant effects on the stochastic variation of all phenotypic classes. The genetic influence over stochastic variation within the metabolome was highly metabolite specific, with neighboring metabolites in the same metabolic pathway frequently showing different levels of noise. As expected from bet-hedging theory, there was more genetic diversity and a wider range of stochastic variation for defense chemistry than found for primary metabolism. Thus, it is possible to begin dissecting the stochastic variation of whole organismal phenotypes in multi-cellular organisms. Further, there are loci that modulate stochastic variation at different phenotypic levels. Finding the identity of these genes will be key to developing complete models linking genotype to phenotype. PMID:25569687
Campo, M. A.; Lopez, J. J.; Rebole, J. P.
2012-04-01
This work was carried out in north of Spain. San Sebastian A meteorological station, where there are available precipitation records every ten minutes was selected. Precipitation data covers from October of 1927 to September of 1997. Pulse models describe the temporal process of rainfall as a succession of rainy cells, main storm, whose origins are distributed in time according to a Poisson process and a secondary process that generates a random number of cells of rain within each storm. Among different pulse models, the Bartlett-Lewis was used. On the other hand, alternative renewal processes and Markov chains describe the way in which the process will evolve in the future depending only on the current state. Therefore they are nor dependant on past events. Two basic processes are considered when describing the occurrence of rain: the alternation of wet and dry periods and temporal distribution of rainfall in each rain event, which determines the rainwater collected in each of the intervals that make up the rain. This allows the introduction of alternative renewal processes and Markov chains of three states, where interstorm time is given by either of the two dry states, short or long. Thus, the stochastic model of Markov chains tries to reproduce the basis of pulse models: the succession of storms, each one composed for a series of rain, separated by a short interval of time without theoretical complexity of these. In a first step, we analyzed all variables involved in the sequential process of the rain: rain event duration, event duration of non-rain, average rainfall intensity in rain events, and finally, temporal distribution of rainfall within the rain event. Additionally, for pulse Bartlett-Lewis model calibration, main descriptive statistics were calculated for each month, considering the process of seasonal rainfall in each month. In a second step, both models were calibrated. Finally, synthetic series were simulated with calibration parameters; series
Stacking with stochastic cooling
Energy Technology Data Exchange (ETDEWEB)
Caspers, Fritz E-mail: Fritz.Caspers@cern.ch; Moehl, Dieter
2004-10-11
Accumulation of large stacks of antiprotons or ions with the aid of stochastic cooling is more delicate than cooling a constant intensity beam. Basically the difficulty stems from the fact that the optimized gain and the cooling rate are inversely proportional to the number of particles 'seen' by the cooling system. Therefore, to maintain fast stacking, the newly injected batch has to be strongly 'protected' from the Schottky noise of the stack. Vice versa the stack has to be efficiently 'shielded' against the high gain cooling system for the injected beam. In the antiproton accumulators with stacking ratios up to 10{sup 5} the problem is solved by radial separation of the injection and the stack orbits in a region of large dispersion. An array of several tapered cooling systems with a matched gain profile provides a continuous particle flux towards the high-density stack core. Shielding of the different systems from each other is obtained both through the spatial separation and via the revolution frequencies (filters). In the 'old AA', where the antiproton collection and stacking was done in one single ring, the injected beam was further shielded during cooling by means of a movable shutter. The complexity of these systems is very high. For more modest stacking ratios, one might use azimuthal rather than radial separation of stack and injected beam. Schematically half of the circumference would be used to accept and cool new beam and the remainder to house the stack. Fast gating is then required between the high gain cooling of the injected beam and the low gain stack cooling. RF-gymnastics are used to merge the pre-cooled batch with the stack, to re-create free space for the next injection, and to capture the new batch. This scheme is less demanding for the storage ring lattice, but at the expense of some reduction in stacking rate. The talk reviews the 'radial' separation schemes and also gives some
Uncertainty Reduction for Stochastic Processes on Complex Networks
Radicchi, Filippo; Castellano, Claudio
2018-05-01
Many real-world systems are characterized by stochastic dynamical rules where a complex network of interactions among individual elements probabilistically determines their state. Even with full knowledge of the network structure and of the stochastic rules, the ability to predict system configurations is generally characterized by a large uncertainty. Selecting a fraction of the nodes and observing their state may help to reduce the uncertainty about the unobserved nodes. However, choosing these points of observation in an optimal way is a highly nontrivial task, depending on the nature of the stochastic process and on the structure of the underlying interaction pattern. In this paper, we introduce a computationally efficient algorithm to determine quasioptimal solutions to the problem. The method leverages network sparsity to reduce computational complexity from exponential to almost quadratic, thus allowing the straightforward application of the method to mid-to-large-size systems. Although the method is exact only for equilibrium stochastic processes defined on trees, it turns out to be effective also for out-of-equilibrium processes on sparse loopy networks.
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.
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.
Fundamentals of stochastic nature sciences
Klyatskin, Valery I
2017-01-01
This book addresses the processes of stochastic structure formation in two-dimensional geophysical fluid dynamics based on statistical analysis of Gaussian random fields, as well as stochastic structure formation in dynamic systems with parametric excitation of positive random fields f(r,t) described by partial differential equations. Further, the book considers two examples of stochastic structure formation in dynamic systems with parametric excitation in the presence of Gaussian pumping. In dynamic systems with parametric excitation in space and time, this type of structure formation either happens – or doesn’t! However, if it occurs in space, then this almost always happens (exponentially quickly) in individual realizations with a unit probability. In the case considered, clustering of the field f(r,t) of any nature is a general feature of dynamic fields, and one may claim that structure formation is the Law of Nature for arbitrary random fields of such type. The study clarifies the conditions under wh...
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...
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 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 quantization of general relativity
International Nuclear Information System (INIS)
Rumpf, H.
1986-01-01
Following an elementary exposition of the basic mathematical concepts used in the theory of stochastic relaxation processes the stochastic quantization method of Parisi and Wu is briefly reviewed. The method is applied to Einstein's theory of gravitation using a formalism that is manifestly covariant with respect to field redefinitions. This requires the adoption of Ito's calculus and the introduction of a metric in field configuration space, for which there is a unique candidate. Due to the indefiniteness of the Euclidean Einstein-Hilbert action stochastic quantization is generalized to the pseudo-Riemannian case. It is formally shown to imply the DeWitt path integral measure. Finally a new type of perturbation theory is developed. (Author)
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...
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)
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 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
STOCHASTIC METHODS IN RISK ANALYSIS
Directory of Open Access Journals (Sweden)
Vladimíra OSADSKÁ
2017-06-01
Full Text Available In this paper, we review basic stochastic methods which can be used to extend state-of-the-art deterministic analytical methods for risk analysis. We can conclude that the standard deterministic analytical methods highly depend on the practical experience and knowledge of the evaluator and therefore, the stochastic methods should be introduced. The new risk analysis methods should consider the uncertainties in input values. We present how large is the impact on the results of the analysis solving practical example of FMECA with uncertainties modelled using Monte Carlo sampling.
Stochastic dynamics of new inflation
International Nuclear Information System (INIS)
Nakao, Ken-ichi; Nambu, Yasusada; Sasaki, Misao.
1988-07-01
We investigate thoroughly the dynamics of an inflation-driving scalar field in terms of an extended version of the stochastic approach proposed by Starobinsky and discuss the spacetime structure of the inflationary universe. To avoid any complications which might arise due to quantum gravity, we concentrate our discussions on the new inflationary universe scenario in which all the energy scales involved are well below the planck mass. The investigation is done both analytically and numerically. In particular, we present a full numerical analysis of the stochastic scalar field dynamics on the phase space. Then implications of the results are discussed. (author)
Stochastic mechanics and quantum theory
International Nuclear Information System (INIS)
Goldstein, S.
1987-01-01
Stochastic mechanics may be regarded as both generalizing classical mechanics to processes with intrinsic randomness, as well as providing the sort of detailed description of microscopic events declared impossible under the traditional interpretation of quantum mechanics. It avoids the many conceptual difficulties which arise from the assumption that quantum mechanics, i.e., the wave function, provides a complete description of (microscopic) physical reality. Stochastic mechanics presents a unified treatment of the microscopic and macroscopic domains, in which the process of measurement plays no special physical role and which reduces to Newtonian mechanics in the macroscopic limit
Probability, Statistics, and Stochastic Processes
Olofsson, Peter
2011-01-01
A mathematical and intuitive approach to probability, statistics, and stochastic processes This textbook provides a unique, balanced approach to probability, statistics, and stochastic processes. Readers gain a solid foundation in all three fields that serves as a stepping stone to more advanced investigations into each area. This text combines a rigorous, calculus-based development of theory with a more intuitive approach that appeals to readers' sense of reason and logic, an approach developed through the author's many years of classroom experience. The text begins with three chapters that d
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 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
Algebraic and stochastic coding theory
Kythe, Dave K
2012-01-01
Using a simple yet rigorous approach, Algebraic and Stochastic Coding Theory makes the subject of coding theory easy to understand for readers with a thorough knowledge of digital arithmetic, Boolean and modern algebra, and probability theory. It explains the underlying principles of coding theory and offers a clear, detailed description of each code. More advanced readers will appreciate its coverage of recent developments in coding theory and stochastic processes. After a brief review of coding history and Boolean algebra, the book introduces linear codes, including Hamming and Golay codes.
Stochastic and infinite dimensional analysis
Carpio-Bernido, Maria; Grothaus, Martin; Kuna, Tobias; Oliveira, Maria; Silva, José
2016-01-01
This volume presents a collection of papers covering applications from a wide range of systems with infinitely many degrees of freedom studied using techniques from stochastic and infinite dimensional analysis, e.g. Feynman path integrals, the statistical mechanics of polymer chains, complex networks, and quantum field theory. Systems of infinitely many degrees of freedom create their particular mathematical challenges which have been addressed by different mathematical theories, namely in the theories of stochastic processes, Malliavin calculus, and especially white noise analysis. These proceedings are inspired by a conference held on the occasion of Prof. Ludwig Streit’s 75th birthday and celebrate his pioneering and ongoing work in these fields.
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
Cellular decomposition in vikalloys
International Nuclear Information System (INIS)
Belyatskaya, I.S.; Vintajkin, E.Z.; Georgieva, I.Ya.; Golikov, V.A.; Udovenko, V.A.
1981-01-01
Austenite decomposition in Fe-Co-V and Fe-Co-V-Ni alloys at 475-600 deg C is investigated. The cellular decomposition in ternary alloys results in the formation of bcc (ordered) and fcc structures, and in quaternary alloys - bcc (ordered) and 12R structures. The cellular 12R structure results from the emergence of stacking faults in the fcc lattice with irregular spacing in four layers. The cellular decomposition results in a high-dispersion structure and magnetic properties approaching the level of well-known vikalloys [ru
Romanofsky, Robert R.
2010-01-01
The cellular reflectarray antenna is intended to replace conventional parabolic reflectors that must be physically aligned with a particular satellite in geostationary orbit. These arrays are designed for specified geographical locations, defined by latitude and longitude, each called a "cell." A particular cell occupies nominally 1,500 square miles (3,885 sq. km), but this varies according to latitude and longitude. The cellular reflectarray antenna designed for a particular cell is simply positioned to align with magnetic North, and the antenna surface is level (parallel to the ground). A given cellular reflectarray antenna will not operate in any other cell.
A Fractionally Integrated Wishart Stochastic Volatility Model
M. Asai (Manabu); M.J. McAleer (Michael)
2013-01-01
textabstractThere has recently been growing interest in modeling and estimating alternative continuous time multivariate stochastic volatility models. We propose a continuous time fractionally integrated Wishart stochastic volatility (FIWSV) process. We derive the conditional Laplace transform of
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....
Transport properties of stochastic Lorentz models
Beijeren, H. van
Diffusion processes are considered for one-dimensional stochastic Lorentz models, consisting of randomly distributed fixed scatterers and one moving light particle. In waiting time Lorentz models the light particle makes instantaneous jumps between scatterers after a stochastically distributed
Theory, technology, and technique of stochastic cooling
International Nuclear Information System (INIS)
Marriner, J.
1993-10-01
The theory and technological implementation of stochastic cooling is described. Theoretical and technological limitations are discussed. Data from existing stochastic cooling systems are shown to illustrate some useful techniques
King, E.; Brodie, E.; Anantharaman, K.; Karaoz, U.; Bouskill, N.; Banfield, J. F.; Steefel, C. I.; Molins, S.
2016-12-01
Characterizing and predicting the microbial and chemical compositions of subsurface aquatic systems necessitates an understanding of the metabolism and physiology of organisms that are often uncultured or studied under conditions not relevant for one's environment of interest. Cultivation-independent approaches are therefore important and have greatly enhanced our ability to characterize functional microbial diversity. The capability to reconstruct genomes representing thousands of populations from microbial communities using metagenomic techniques provides a foundation for development of predictive models for community structure and function. Here, we discuss a genome-informed stochastic trait-based model incorporated into a reactive transport framework to represent the activities of coupled guilds of hypothetical microorganisms. Metabolic pathways for each microbe within a functional guild are parameterized from metagenomic data with a unique combination of traits governing organism fitness under dynamic environmental conditions. We simulate the thermodynamics of coupled electron donor and acceptor reactions to predict the energy available for cellular maintenance, respiration, biomass development, and enzyme production. While `omics analyses can now characterize the metabolic potential of microbial communities, it is functionally redundant as well as computationally prohibitive to explicitly include the thousands of recovered organisms into biogeochemical models. However, one can derive potential metabolic pathways from genomes along with trait-linkages to build probability distributions of traits. These distributions are used to assemble groups of microbes that couple one or more of these pathways. From the initial ensemble of microbes, only a subset will persist based on the interaction of their physiological and metabolic traits with environmental conditions, competing organisms, etc. Here, we analyze the predicted niches of these hypothetical microbes and
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
Dynamical and hamiltonian dilations of stochastic processes
International Nuclear Information System (INIS)
Baumgartner, B.; Gruemm, H.-R.
1982-01-01
This is a study of the problem, which stochastic processes could arise from dynamical systems by loss of information. The notions of ''dilation'' and ''approximate dilation'' of a stochastic process are introduced to give exact definitions of this particular relationship. It is shown that every generalized stochastic process is approximately dilatable by a sequence of dynamical systems, but for stochastic processes in full generality one needs nets. (Author)
Stochastic lattice model of synaptic membrane protein domains.
Li, Yiwei; Kahraman, Osman; Haselwandter, Christoph A
2017-05-01
Neurotransmitter receptor molecules, concentrated in synaptic membrane domains along with scaffolds and other kinds of proteins, are crucial for signal transmission across chemical synapses. In common with other membrane protein domains, synaptic domains are characterized by low protein copy numbers and protein crowding, with rapid stochastic turnover of individual molecules. We study here in detail a stochastic lattice model of the receptor-scaffold reaction-diffusion dynamics at synaptic domains that was found previously to capture, at the mean-field level, the self-assembly, stability, and characteristic size of synaptic domains observed in experiments. We show that our stochastic lattice model yields quantitative agreement with mean-field models of nonlinear diffusion in crowded membranes. Through a combination of analytic and numerical solutions of the master equation governing the reaction dynamics at synaptic domains, together with kinetic Monte Carlo simulations, we find substantial discrepancies between mean-field and stochastic models for the reaction dynamics at synaptic domains. Based on the reaction and diffusion properties of synaptic receptors and scaffolds suggested by previous experiments and mean-field calculations, we show that the stochastic reaction-diffusion dynamics of synaptic receptors and scaffolds provide a simple physical mechanism for collective fluctuations in synaptic domains, the molecular turnover observed at synaptic domains, key features of the observed single-molecule trajectories, and spatial heterogeneity in the effective rates at which receptors and scaffolds are recycled at the cell membrane. Our work sheds light on the physical mechanisms and principles linking the collective properties of membrane protein domains to the stochastic dynamics that rule their molecular components.
Environmental vs Demographic Stochasticity in Population Growth
Braumann, C. A.
2010-01-01
Compares the effect on population growth of envinonmental stochasticity (random environmental variations described by stochastic differential equations) with demographic stochasticity (random variations in births and deaths described by branching processes and birth-and-death processes), in the density-independent and the density-dependent cases.
Stochastic diffusion models for substitutable technological innovations
Wang, L.; Hu, B.; Yu, X.
2004-01-01
Based on the analysis of firms' stochastic adoption behaviour, this paper first points out the necessity to build more practical stochastic models. And then, stochastic evolutionary models are built for substitutable innovation diffusion system. Finally, through the computer simulation of the
Magnetohydrodynamics cellular automata
International Nuclear Information System (INIS)
Hatori, Tadatsugu.
1990-02-01
There has been a renewal of interest in cellular automata, partly because they give an architecture for a special purpose computer with parallel processing optimized to solve a particular problem. The lattice gas cellular automata are briefly surveyed, which are recently developed to solve partial differential equations such as hydrodynamics or magnetohydrodynamics. A new model is given in the present paper to implement the magnetic Lorentz force in a more deterministic and local procedure than the previous one. (author)
Epigenetics and Cellular Metabolism
Wenyi Xu; Fengzhong Wang; Zhongsheng Yu; Fengjiao Xin
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 proce...
Magnetohydrodynamic cellular automata
Energy Technology Data Exchange (ETDEWEB)
Hatori, Tadatsugu [National Inst. for Fusion Science, Nagoya (Japan)
1990-03-01
There has been a renewal of interest in cellular automata, partly because they give an architecture for a special purpose computer with parallel processing optimized to solve a particular problem. The lattice gas cellular automata are briefly surveyed, which are recently developed to solve partial differential equations such as hydrodynamics or magnetohydrodynamics. A new model is given in the present paper to implement the magnetic Lorentz force in a more deterministic and local procedure than the previous one. (author).
Magnetohydrodynamic cellular automata
International Nuclear Information System (INIS)
Hatori, Tadatsugu
1990-01-01
There has been a renewal of interest in cellular automata, partly because they give an architecture for a special purpose computer with parallel processing optimized to solve a particular problem. The lattice gas cellular automata are briefly surveyed, which are recently developed to solve partial differential equations such as hydrodynamics or magnetohydrodynamics. A new model is given in the present paper to implement the magnetic Lorentz force in a more deterministic and local procedure than the previous one. (author)
Directory of Open Access Journals (Sweden)
Michel Modo
2005-07-01
Full Text Available Cellular MR imaging is a young field that aims to visualize targeted cells in living organisms. In order to provide a different signal intensity of the targeted cell, they are either labeled with MR contrast agents in vivo or prelabeled in vitro. Either (ultrasmall superparamagnetic iron oxide [(USPIO] particles or (polymeric paramagnetic chelates can be used for this purpose. For in vivo cellular labeling, Gd3+- and Mn2+- chelates have mainly been used for targeted hepatobiliary imaging, and (USPIO-based cellular imaging has been focused on imaging of macrophage activity. Several of these magneto-pharmaceuticals have been FDA-approved or are in late-phase clinical trials. As for prelabeling of cells in vitro, a challenge has been to induce a sufficient uptake of contrast agents into nonphagocytic cells, without affecting normal cellular function. It appears that this issue has now largely been resolved, leading to an active research on monitoring the cellular biodistribution in vivo following transplantation or transfusion of these cells, including cell migration and trafficking. New applications of cellular MR imaging will be directed, for instance, towards our understanding of hematopoietic (immune cell trafficking and of novel guided (stem cell-based therapies aimed to be translated to the clinic in the future.
Perturbation theory from stochastic quantization
International Nuclear Information System (INIS)
Hueffel, H.
1984-01-01
By using a diagrammatical method it is shown that in scalar theories the stochastic quantization method of Parisi and Wu gives the usual perturbation series in Feynman diagrams. It is further explained how to apply the diagrammatical method to gauge theories, discussing the origin of ghost effects. (Author)
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 ...... for river geometries are formulated and a coupling between hydraulic computational methods and numerical reliability methods is presented....
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 theory of grain growth
International Nuclear Information System (INIS)
Hu Haiyun; Xing Xiusan.
1990-11-01
The purpose of this note is to set up a stochastic theory of grain growth and to derive the statistical distribution function and the average value of the grain radius so as to match them with the experiment further. 8 refs, 1 fig
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...
Universality in stochastic exponential growth.
Iyer-Biswas, Srividya; Crooks, Gavin E; Scherer, Norbert F; Dinner, Aaron R
2014-07-11
Recent imaging data for single bacterial cells reveal that their mean sizes grow exponentially in time and that their size distributions collapse to a single curve when rescaled by their means. An analogous result holds for the division-time distributions. A model is needed to delineate the minimal requirements for these scaling behaviors. We formulate a microscopic theory of stochastic exponential growth as a Master Equation that accounts for these observations, in contrast to existing quantitative models of stochastic exponential growth (e.g., the Black-Scholes equation or geometric Brownian motion). Our model, the stochastic Hinshelwood cycle (SHC), is an autocatalytic reaction cycle in which each molecular species catalyzes the production of the next. By finding exact analytical solutions to the SHC and the corresponding first passage time problem, we uncover universal signatures of fluctuations in exponential growth and division. The model makes minimal assumptions, and we describe how more complex reaction networks can reduce to such a cycle. We thus expect similar scalings to be discovered in stochastic processes resulting in exponential growth that appear in diverse contexts such as cosmology, finance, technology, and population growth.
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 h...
The fermion stochastic calculus I
International Nuclear Information System (INIS)
Streater, R.F.
1984-01-01
The author describes the stochastic calculus of quantum processes with fermions. After a description of the Clifford algebra as the csup(*)-algebra generated by spinor fields the damped harmonic oscillator with quantum noise is considered as example. Then the Clifford process is described. Finally the Ito-Clifford integral and the Ito-Clifford isometry are presented. (HSI)
Stochastic and Chaotic Relaxation Oscillations
Grasman, J.; Roerdink, J.B.T.M.
1988-01-01
For relaxation oscillators stochastic and chaotic dynamics are investigated. The effect of random perturbations upon the period is computed. For an extended system with additional state variables chaotic behavior can be expected. As an example, the Van der Pol oscillator is changed into a
Stochastic processes in mechanical engineering
Brouwers, J.J.H.
2006-01-01
Stochastic or random vibrations occur in a variety of applications of mechanicalengineering. Examples are: the dynamics of a vehicle on an irregular roadsurface; the variation in time of thermodynamic variables in municipal wasteincinerators due to fluctuations in heating value of the waste; the
Testing for Stochastic Dominance Efficiency
G.T. Post (Thierry); O. Linton; Y-J. Whang
2005-01-01
textabstractWe propose a new test of the stochastic dominance efficiency of a given portfolio over a class of portfolios. We establish its null and alternative asymptotic properties, and define a method for consistently estimating critical values. We present some numerical evidence that our
Network Analysis with Stochastic Grammars
2015-09-17
rules N = 0 //non-terminal index clusters = cluster(W) //number of clusters drive the number S productions //cluster function described in text...Essa, “Recognizing multitasked activities from video using stochastic context-free grammar,” AAAI/IAAI, pp. 770–776, 2002. [18] R. Nevatia, T. Zhao
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...
American options under stochastic volatility
Chockalingam, A.; Muthuraman, K.
2011-01-01
The problem of pricing an American option written on an underlying asset with constant price volatility has been studied extensively in literature. Real-world data, however, demonstrate that volatility is not constant, and stochastic volatility models are used to account for dynamic volatility
Stochastic cooling system in COSY
International Nuclear Information System (INIS)
Brittner, P.; Hacker, H.U.; Prasuhn, D.; Schug, G.; Singer, H.; Spiess, W.; Stassen, R.
1994-01-01
The stochastic cooler system in COSY is designed for proton kinetic energies between 0.8 and 2.5 GeV. Fabrication of the mechanical parts of the system is going on. Test results of the prototype measurements as well as data of the active RF-compontens are presented. (orig.)
Stochastic cooling system in COSY
Energy Technology Data Exchange (ETDEWEB)
Brittner, P [Forschungszentrum Juelich GmbH (Germany); Hacker, H U [Forschungszentrum Juelich GmbH (Germany); Prasuhn, D [Forschungszentrum Juelich GmbH (Germany); Schug, G [Forschungszentrum Juelich GmbH (Germany); Singer, H [Forschungszentrum Juelich GmbH (Germany); Spiess, W [Forschungszentrum Juelich GmbH (Germany); Stassen, R [Forschungszentrum Juelich GmbH (Germany)
1994-09-01
The stochastic cooler system in COSY is designed for proton kinetic energies between 0.8 and 2.5 GeV. Fabrication of the mechanical parts of the system is going on. Test results of the prototype measurements as well as data of the active RF-compontens are presented. (orig.)
Stochastic-field cavitation model
International Nuclear Information System (INIS)
Dumond, J.; Magagnato, F.; Class, A.
2013-01-01
Nonlinear phenomena can often be well described using probability density functions (pdf) and pdf transport models. Traditionally, the simulation of pdf transport requires Monte-Carlo codes based on Lagrangian “particles” or prescribed pdf assumptions including binning techniques. Recently, in the field of combustion, a novel formulation called the stochastic-field method solving pdf transport based on Eulerian fields has been proposed which eliminates the necessity to mix Eulerian and Lagrangian techniques or prescribed pdf assumptions. In the present work, for the first time the stochastic-field method is applied to multi-phase flow and, in particular, to cavitating flow. To validate the proposed stochastic-field cavitation model, two applications are considered. First, sheet cavitation is simulated in a Venturi-type nozzle. The second application is an innovative fluidic diode which exhibits coolant flashing. Agreement with experimental results is obtained for both applications with a fixed set of model constants. The stochastic-field cavitation model captures the wide range of pdf shapes present at different locations
Stochastic-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.
Distance covariance for stochastic processes
DEFF Research Database (Denmark)
Matsui, Muneya; Mikosch, Thomas Valentin; Samorodnitsky, Gennady
2017-01-01
The distance covariance of two random vectors is a measure of their dependence. The empirical distance covariance and correlation can be used as statistical tools for testing whether two random vectors are independent. We propose an analog of the distance covariance for two stochastic processes...
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.
Correlative Stochastic Optical Reconstruction Microscopy and Electron Microscopy
Kim, Doory; Deerinck, Thomas J.; Sigal, Yaron M.; Babcock, Hazen P.; Ellisman, Mark H.; Zhuang, Xiaowei
2015-01-01
Correlative fluorescence light microscopy and electron microscopy allows the imaging of spatial distributions of specific biomolecules in the context of cellular ultrastructure. Recent development of super-resolution fluorescence microscopy allows the location of molecules to be determined with nanometer-scale spatial resolution. However, correlative super-resolution fluorescence microscopy and electron microscopy (EM) still remains challenging because the optimal specimen preparation and imaging conditions for super-resolution fluorescence microscopy and EM are often not compatible. Here, we have developed several experiment protocols for correlative stochastic optical reconstruction microscopy (STORM) and EM methods, both for un-embedded samples by applying EM-specific sample preparations after STORM imaging and for embedded and sectioned samples by optimizing the fluorescence under EM fixation, staining and embedding conditions. We demonstrated these methods using a variety of cellular targets. PMID:25874453
Using cellular automata to simulate forest fire propagation in Portugal
Freire, Joana; daCamara, Carlos
2017-04-01
Wildfires in the Mediterranean region have severe damaging effects mainly due to large fire events [1, 2]. When restricting to Portugal, wildfires have burned over 1:4 million ha in the last decade. Considering the increasing tendency in the extent and severity of wildfires [1, 2], the availability of modeling tools of fire episodes is of crucial importance. Two main types of mathematical models are generally available, namely deterministic and stochastic models. Deterministic models attempt a description of fires, fuel and atmosphere as multiphase continua prescribing mass, momentum and energy conservation, which typically leads to systems of coupled PDEs to be solved numerically on a grid. Simpler descriptions, such as FARSITE, neglect the interaction with atmosphere and propagate the fire front using wave techniques. One of the most important stochastic models are Cellular Automata (CA), in which space is discretized into cells, and physical quantities take on a finite set of values at each cell. The cells evolve in discrete time according to a set of transition rules, and the states of the neighboring cells. In the present work, we implement and then improve a simple and fast CA model designed to operationally simulate wildfires in Portugal. The reference CA model chosen [3] has the advantage of having been applied successfully in other Mediterranean ecosystems, namely to historical fires in Greece. The model is defined on a square grid with propagation to 8 nearest and next-nearest neighbors, where each cell is characterized by 4 possible discrete states, corresponding to burning, not-yet burned, fuel-free and completely burned cells, with 4 possible rules of evolution which take into account fuel properties, meteorological conditions, and topography. As a CA model, it offers the possibility to run a very high number of simulations in order to verify and apply the model, and is easily modified by implementing additional variables and different rules for the
Stochastic dark energy from inflationary quantum fluctuations
Glavan, Dražen; Prokopec, Tomislav; Starobinsky, Alexei A.
2018-05-01
We study the quantum backreaction from inflationary fluctuations of a very light, non-minimally coupled spectator scalar and show that it is a viable candidate for dark energy. The problem is solved by suitably adapting the formalism of stochastic inflation. This allows us to self-consistently account for the backreaction on the background expansion rate of the Universe where its effects are large. This framework is equivalent to that of semiclassical gravity in which matter vacuum fluctuations are included at the one loop level, but purely quantum gravitational fluctuations are neglected. Our results show that dark energy in our model can be characterized by a distinct effective equation of state parameter (as a function of redshift) which allows for testing of the model at the level of the background.
Hardware implementation of stochastic spiking neural networks.
Rosselló, Josep L; Canals, Vincent; Morro, Antoni; Oliver, Antoni
2012-08-01
Spiking Neural Networks, the last generation of Artificial Neural Networks, are characterized by its bio-inspired nature and by a higher computational capacity with respect to other neural models. In real biological neurons, stochastic processes represent an important mechanism of neural behavior and are responsible of its special arithmetic capabilities. In this work we present a simple hardware implementation of spiking neurons that considers this probabilistic nature. The advantage of the proposed implementation is that it is fully digital and therefore can be massively implemented in Field Programmable Gate Arrays. The high computational capabilities of the proposed model are demonstrated by the study of both feed-forward and recurrent networks that are able to implement high-speed signal filtering and to solve complex systems of linear equations.
Stochastic Relational Presheaves and Dynamic Logic for Contextuality
Directory of Open Access Journals (Sweden)
Kohei Kishida
2014-12-01
Full Text Available Presheaf models provide a formulation of labelled transition systems that is useful for, among other things, modelling concurrent computation. This paper aims to extend such models further to represent stochastic dynamics such as shown in quantum systems. After reviewing what presheaf models represent and what certain operations on them mean in terms of notions such as internal and external choices, composition of systems, and so on, I will show how to extend those models and ideas by combining them with ideas from other category-theoretic approaches to relational models and to stochastic processes. It turns out that my extension yields a transitional formulation of sheaf-theoretic structures that Abramsky and Brandenburger proposed to characterize non-locality and contextuality. An alternative characterization of contextuality will then be given in terms of a dynamic modal logic of the models I put forward.
Parallel Stochastic discrete event simulation of calcium dynamics in neuron.
Ishlam Patoary, Mohammad Nazrul; Tropper, Carl; McDougal, Robert A; Zhongwei, Lin; Lytton, William W
2017-09-26
The intra-cellular calcium signaling pathways of a neuron depends on both biochemical reactions and diffusions. Some quasi-isolated compartments (e.g. spines) are so small and calcium concentrations are so low that one extra molecule diffusing in by chance can make a nontrivial difference in its concentration (percentage-wise). These rare events can affect dynamics discretely in such way that they cannot be evaluated by a deterministic simulation. Stochastic models of such a system provide a more detailed understanding of these systems than existing deterministic models because they capture their behavior at a molecular level. Our research focuses on the development of a high performance parallel discrete event simulation environment, Neuron Time Warp (NTW), which is intended for use in the parallel simulation of stochastic reaction-diffusion systems such as intra-calcium signaling. NTW is integrated with NEURON, a simulator which is widely used within the neuroscience community. We simulate two models, a calcium buffer and a calcium wave model. The calcium buffer model is employed in order to verify the correctness and performance of NTW by comparing it to a serial deterministic simulation in NEURON. We also derived a discrete event calcium wave model from a deterministic model using the stochastic IP3R structure.
Robust synthetic biology design: stochastic game theory approach.
Chen, Bor-Sen; Chang, Chia-Hung; Lee, Hsiao-Ching
2009-07-15
Synthetic biology is to engineer artificial biological systems to investigate natural biological phenomena and for a variety of applications. However, the development of synthetic gene networks is still difficult and most newly created gene networks are non-functioning due to uncertain initial conditions and disturbances of extra-cellular environments on the host cell. At present, how to design a robust synthetic gene network to work properly under these uncertain factors is the most important topic of synthetic biology. A robust regulation design is proposed for a stochastic synthetic gene network to achieve the prescribed steady states under these uncertain factors from the minimax regulation perspective. This minimax regulation design problem can be transformed to an equivalent stochastic game problem. Since it is not easy to solve the robust regulation design problem of synthetic gene networks by non-linear stochastic game method directly, the Takagi-Sugeno (T-S) fuzzy model is proposed to approximate the non-linear synthetic gene network via the linear matrix inequality (LMI) technique through the Robust Control Toolbox in Matlab. Finally, an in silico example is given to illustrate the design procedure and to confirm the efficiency and efficacy of the proposed robust gene design method. http://www.ee.nthu.edu.tw/bschen/SyntheticBioDesign_supplement.pdf.
Stochastic calculus of protein filament formation under spatial confinement
Michaels, Thomas C. T.; Dear, Alexander J.; Knowles, Tuomas P. J.
2018-05-01
The growth of filamentous aggregates from precursor proteins is a process of central importance to both normal and aberrant biology, for instance as the driver of devastating human disorders such as Alzheimer's and Parkinson's diseases. The conventional theoretical framework for describing this class of phenomena in bulk is based upon the mean-field limit of the law of mass action, which implicitly assumes deterministic dynamics. However, protein filament formation processes under spatial confinement, such as in microdroplets or in the cellular environment, show intrinsic variability due to the molecular noise associated with small-volume effects. To account for this effect, in this paper we introduce a stochastic differential equation approach for investigating protein filament formation processes under spatial confinement. Using this framework, we study the statistical properties of stochastic aggregation curves, as well as the distribution of reaction lag-times. Moreover, we establish the gradual breakdown of the correlation between lag-time and normalized growth rate under spatial confinement. Our results establish the key role of spatial confinement in determining the onset of stochasticity in protein filament formation and offer a formalism for studying protein aggregation kinetics in small volumes in terms of the kinetic parameters describing the aggregation dynamics in bulk.
Studies to the stochastic theory of coupled reactorkinetic-thermohydraulic systems Pt. 2
International Nuclear Information System (INIS)
Mesko, L.
1983-06-01
The description is given of the noise phenomena taking place in a multivariable coupled system by a comprehensive model based on the theory of stochastic fluctuations. A comparison is made with models using transfer function formalism for systems characterized by deterministic open and closed loop signal transmission properties. The advantages of the stochastic model are illustrated by simple reactor dynamical examples having diagnostical importance. (author)
Research on nonlinear stochastic dynamical price model
International Nuclear Information System (INIS)
Li Jiaorui; Xu Wei; Xie Wenxian; Ren Zhengzheng
2008-01-01
In consideration of many uncertain factors existing in economic system, nonlinear stochastic dynamical price model which is subjected to Gaussian white noise excitation is proposed based on deterministic model. One-dimensional averaged Ito stochastic differential equation for the model is derived by using the stochastic averaging method, and applied to investigate the stability of the trivial solution and the first-passage failure of the stochastic price model. The stochastic price model and the methods presented in this paper are verified by numerical studies
Stochastic volatility of volatility in continuous time
DEFF Research Database (Denmark)
Barndorff-Nielsen, Ole; Veraart, Almut
This paper introduces the concept of stochastic volatility of volatility in continuous time and, hence, extends standard stochastic volatility (SV) models to allow for an additional source of randomness associated with greater variability in the data. We discuss how stochastic volatility...... of volatility can be defined both non-parametrically, where we link it to the quadratic variation of the stochastic variance process, and parametrically, where we propose two new SV models which allow for stochastic volatility of volatility. In addition, we show that volatility of volatility can be estimated...
Stochastic model of Rayleigh-Taylor turbulent mixing
International Nuclear Information System (INIS)
Abarzhi, S.I.; Cadjan, M.; Fedotov, S.
2007-01-01
We propose a stochastic model to describe the random character of the dissipation process in Rayleigh-Taylor turbulent mixing. The parameter alpha, used conventionally to characterize the mixing growth-rate, is not a universal constant and is very sensitive to the statistical properties of the dissipation. The ratio between the rates of momentum loss and momentum gain is the statistic invariant and a robust parameter to diagnose with or without turbulent diffusion accounted for
A unified approach to stochastic integration on the real line
DEFF Research Database (Denmark)
Basse-O'Connor, Andreas; Graversen, Svend-Erik; Pedersen, Jan
Stochastic integration on the predictable σ-field with respect to σ-finite L0-valued measures, also known as formal semimartingales, is studied. In particular, the triplet of such measures is introduced and used to characterize the set of integrable processes. Special attention is given to Lévy...... processes indexed by the real line. Surprisingly, many of the basic properties break down in this situation compared to the usual R+ case....
Nonlinear and Stochastic Dynamics in the Heart
Qu, Zhilin; Hu, Gang; Garfinkel, Alan; Weiss, James N.
2014-01-01
In a normal human life span, the heart beats about 2 to 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. PMID:25267872
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)
Qu, Zhilin; Hu, Gang; Garfinkel, Alan; Weiss, James N.
2014-01-01
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
Ramírez-López, A.; Romero-Romo, M. A.; Muñoz-Negron, D.; López-Ramírez, S.; Escarela-Pérez, R.; Duran-Valencia, C.
2012-10-01
Computational models are developed to create grain structures using mathematical algorithms based on the chaos theory such as cellular automaton, geometrical models, fractals, and stochastic methods. Because of the chaotic nature of grain structures, some of the most popular routines are based on the Monte Carlo method, statistical distributions, and random walk methods, which can be easily programmed and included in nested loops. Nevertheless, grain structures are not well defined as the results of computational errors and numerical inconsistencies on mathematical methods. Due to the finite definition of numbers or the numerical restrictions during the simulation of solidification, damaged images appear on the screen. These images must be repaired to obtain a good measurement of grain geometrical properties. Some mathematical algorithms were developed to repair, measure, and characterize grain structures obtained from cellular automata in the present work. An appropriate measurement of grain size and the corrected identification of interfaces and length are very important topics in materials science because they are the representation and validation of mathematical models with real samples. As a result, the developed algorithms are tested and proved to be appropriate and efficient to eliminate the errors and characterize the grain structures.
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...
Momentum Maps and Stochastic Clebsch Action Principles
Cruzeiro, Ana Bela; Holm, Darryl D.; Ratiu, Tudor S.
2018-01-01
We derive stochastic differential equations whose solutions follow the flow of a stochastic nonlinear Lie algebra operation on a configuration manifold. For this purpose, we develop a stochastic Clebsch action principle, in which the noise couples to the phase space variables through a momentum map. This special coupling simplifies the structure of the resulting stochastic Hamilton equations for the momentum map. In particular, these stochastic Hamilton equations collectivize for Hamiltonians that depend only on the momentum map variable. The Stratonovich equations are derived from the Clebsch variational principle and then converted into Itô form. In comparing the Stratonovich and Itô forms of the stochastic dynamical equations governing the components of the momentum map, we find that the Itô contraction term turns out to be a double Poisson bracket. Finally, we present the stochastic Hamiltonian formulation of the collectivized momentum map dynamics and derive the corresponding Kolmogorov forward and backward equations.
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...
Molecular and Cellular Basis of Aging
DEFF Research Database (Denmark)
Rattan, Suresh
2016-01-01
KEY FACTS • Signs of biological aging appear progressively and exponentially during the period of survival beyond the ELS of a species. • There are no gerontogenes evolved with a specific function of causing aging and eventual death. • The role of genes in aging and longevity is mainly at the level...... of longevity-assurance in evolutionary terms. • The phenotype of aging is highly differential and heterogeneous at all levels of biological organization. • Aging is characterized by a stochastic occurrence, accumulation, and heterogeneity of damage in macromolecules. • Mild stress-induced activation of defense...
Anomalous scaling of stochastic processes and the Moses effect.
Chen, Lijian; Bassler, Kevin E; McCauley, Joseph L; Gunaratne, Gemunu H
2017-04-01
The state of a stochastic process evolving over a time t is typically assumed to lie on a normal distribution whose width scales like t^{1/2}. However, processes in which the probability distribution is not normal and the scaling exponent differs from 1/2 are known. The search for possible origins of such "anomalous" scaling and approaches to quantify them are the motivations for the work reported here. In processes with stationary increments, where the stochastic process is time-independent, autocorrelations between increments and infinite variance of increments can cause anomalous scaling. These sources have been referred to as the Joseph effect and the Noah effect, respectively. If the increments are nonstationary, then scaling of increments with t can also lead to anomalous scaling, a mechanism we refer to as the Moses effect. Scaling exponents quantifying the three effects are defined and related to the Hurst exponent that characterizes the overall scaling of the stochastic process. Methods of time series analysis that enable accurate independent measurement of each exponent are presented. Simple stochastic processes are used to illustrate each effect. Intraday financial time series data are analyzed, revealing that their anomalous scaling is due only to the Moses effect. In the context of financial market data, we reiterate that the Joseph exponent, not the Hurst exponent, is the appropriate measure to test the efficient market hypothesis.
Anomalous scaling of stochastic processes and the Moses effect
Chen, Lijian; Bassler, Kevin E.; McCauley, Joseph L.; Gunaratne, Gemunu H.
2017-04-01
The state of a stochastic process evolving over a time t is typically assumed to lie on a normal distribution whose width scales like t1/2. However, processes in which the probability distribution is not normal and the scaling exponent differs from 1/2 are known. The search for possible origins of such "anomalous" scaling and approaches to quantify them are the motivations for the work reported here. In processes with stationary increments, where the stochastic process is time-independent, autocorrelations between increments and infinite variance of increments can cause anomalous scaling. These sources have been referred to as the Joseph effect and the Noah effect, respectively. If the increments are nonstationary, then scaling of increments with t can also lead to anomalous scaling, a mechanism we refer to as the Moses effect. Scaling exponents quantifying the three effects are defined and related to the Hurst exponent that characterizes the overall scaling of the stochastic process. Methods of time series analysis that enable accurate independent measurement of each exponent are presented. Simple stochastic processes are used to illustrate each effect. Intraday financial time series data are analyzed, revealing that their anomalous scaling is due only to the Moses effect. In the context of financial market data, we reiterate that the Joseph exponent, not the Hurst exponent, is the appropriate measure to test the efficient market hypothesis.
Evolving Stochastic Learning Algorithm based on Tsallis entropic index
Anastasiadis, A. D.; Magoulas, G. D.
2006-03-01
In this paper, inspired from our previous algorithm, which was based on the theory of Tsallis statistical mechanics, we develop a new evolving stochastic learning algorithm for neural networks. The new algorithm combines deterministic and stochastic search steps by employing a different adaptive stepsize for each network weight, and applies a form of noise that is characterized by the nonextensive entropic index q, regulated by a weight decay term. The behavior of the learning algorithm can be made more stochastic or deterministic depending on the trade off between the temperature T and the q values. This is achieved by introducing a formula that defines a time-dependent relationship between these two important learning parameters. Our experimental study verifies that there are indeed improvements in the convergence speed of this new evolving stochastic learning algorithm, which makes learning faster than using the original Hybrid Learning Scheme (HLS). In addition, experiments are conducted to explore the influence of the entropic index q and temperature T on the convergence speed and stability of the proposed method.
Flexible Design for α-Duplex Communications in Multi-Tier Cellular Networks
Alammouri, Ahmad; Elsawy, Hesham; Alouini, Mohamed-Slim
2016-01-01
the foreseen FD gains. This paper presents flexible and tractable modeling framework for multi-tier cellular networks with FD BSs and FD/HD UEs. The presented model is based on stochastic geometry and accounts for the intrinsic vulnerability of uplink
Cellularized Cellular Solids via Freeze-Casting.
Christoph, Sarah; Kwiatoszynski, Julien; Coradin, Thibaud; Fernandes, Francisco M
2016-02-01
The elaboration of metabolically active cell-containing materials is a decisive step toward the successful application of cell based technologies. The present work unveils a new process allowing to simultaneously encapsulate living cells and shaping cell-containing materials into solid-state macroporous foams with precisely controlled morphology. Our strategy is based on freeze casting, an ice templating materials processing technique that has recently emerged for the structuration of colloids into macroporous materials. Our results indicate that it is possible to combine the precise structuration of the materials with cellular metabolic activity for the model organism Saccharomyces cerevisiae. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Epigenetics and Cellular Metabolism
Directory of Open Access Journals (Sweden)
Wenyi Xu
2016-01-01
Full Text Available 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.
Wireless Cellular Mobile Communications
Directory of Open Access Journals (Sweden)
V. Zalud
2002-12-01
Full Text Available In this article is briefly reviewed the history of wireless cellularmobile communications, examined the progress in current secondgeneration (2G cellular standards and discussed their migration to thethird generation (3G. The European 2G cellular standard GSM and itsevolution phases GPRS and EDGE are described somewhat in detail. Thethird generation standard UMTS taking up on GSM/GPRS core network andequipped with a new advanced access network on the basis of codedivision multiple access (CDMA is investigated too. A sketch of theperspective of mobile communication beyond 3G concludes this article.
Stochastic geometry model for multi-channel fog radio access networks
Emara, Mostafa
2017-06-29
Cache-enabled base station (BS) densification, denoted as a fog radio access network (F-RAN), is foreseen as a key component of 5G cellular networks. F-RAN enables storing popular files at the network edge (i.e., BS caches), which empowers local communication and alleviates traffic congestions at the core/backhaul network. The hitting probability, which is the probability of successfully transmitting popular files request from the network edge, is a fundamental key performance indicator (KPI) for F-RAN. This paper develops a scheduling aware mathematical framework, based on stochastic geometry, to characterize the hitting probability of F-RAN in a multi-channel environment. To this end, we assess and compare the performance of two caching distribution schemes, namely, uniform caching and Zipf caching. The numerical results show that the commonly used single channel environment leads to pessimistic assessment for the hitting probability of F-RAN. Furthermore, the numerical results manifest the superiority of the Zipf caching scheme and quantify the hitting probability gains in terms of the number of channels and cache size.
Energy Technology Data Exchange (ETDEWEB)
Guerrier, C. [Applied Mathematics and Computational Biology, IBENS, Ecole Normale Supérieure, 46 rue d' Ulm, 75005 Paris (France); Holcman, D., E-mail: david.holcman@ens.fr [Applied Mathematics and Computational Biology, IBENS, Ecole Normale Supérieure, 46 rue d' Ulm, 75005 Paris (France); Mathematical Institute, Oxford OX2 6GG, Newton Institute (United Kingdom)
2017-07-01
The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationally greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.
International Nuclear Information System (INIS)
Guerrier, C.; Holcman, D.
2017-01-01
The main difficulty in simulating diffusion processes at a molecular level in cell microdomains is due to the multiple scales involving nano- to micrometers. Few to many particles have to be simulated and simultaneously tracked while there are exploring a large portion of the space for binding small targets, such as buffers or active sites. Bridging the small and large spatial scales is achieved by rare events representing Brownian particles finding small targets and characterized by long-time distribution. These rare events are the bottleneck of numerical simulations. A naive stochastic simulation requires running many Brownian particles together, which is computationally greedy and inefficient. Solving the associated partial differential equations is also difficult due to the time dependent boundary conditions, narrow passages and mixed boundary conditions at small windows. We present here two reduced modeling approaches for a fast computation of diffusing fluxes in microdomains. The first approach is based on a Markov mass-action law equations coupled to a Markov chain. The second is a Gillespie's method based on the narrow escape theory for coarse-graining the geometry of the domain into Poissonian rates. The main application concerns diffusion in cellular biology, where we compute as an example the distribution of arrival times of calcium ions to small hidden targets to trigger vesicular release.
Base Station Ordering for Emergency Call Localization in Ultra-dense Cellular Networks
Elsawy, Hesham
2017-10-04
This paper proposes the base station ordering localization technique (BoLT) for emergency call localization in cellular networks. Exploiting the foreseen ultra-densification of the next-generation (5G and beyond) cellular networks, we utilize higher-order Voronoi tessellations to provide ubiquitous localization services that are in compliance to the public safety standards in cellular networks. The proposed localization algorithm runs at the base stations (BSs) and requires minimal operation from agents (i.e., mobile users). Particularly, BoLT requires each agent to feedback a neighbor cell list (NCL) that contains the order of neighboring BSs based on the received signal power in the pilots sent from these BSs. Moreover, this paper utilizes stochastic geometry to develop a tractable mathematical model to assess the performance of BoLT in a general network setting. The goal of this paper is to answer the following two fundamental questions: i) how many BSs should be ordered and reported by the agent to achieve a desirable localization accuracy? and ii) what is the localization error probability given that the pilot signals are subject to shadowing? Assuming that the BSs are deployed according to a Poisson point process (PPP), we answer these two questions via characterizing the tradeoff between the area of location region (ALR) and the localization error probability in terms of the number of BSs ordered by the agent. The results show that reporting the order of six neighboring BSs is sufficient to localize the agent within 10% of the cell area. Increasing the number of reported BSs to ten confines the location region to 1% of the cell area. This would translate to the range of a few meters to decimeters in the foreseen ultra-dense 5G networks.
Base Station Ordering for Emergency Call Localization in Ultra-dense Cellular Networks
Elsawy, Hesham; Dai, Wenhan; Alouini, Mohamed-Slim; Win, Moe Z.
2017-01-01
This paper proposes the base station ordering localization technique (BoLT) for emergency call localization in cellular networks. Exploiting the foreseen ultra-densification of the next-generation (5G and beyond) cellular networks, we utilize higher-order Voronoi tessellations to provide ubiquitous localization services that are in compliance to the public safety standards in cellular networks. The proposed localization algorithm runs at the base stations (BSs) and requires minimal operation from agents (i.e., mobile users). Particularly, BoLT requires each agent to feedback a neighbor cell list (NCL) that contains the order of neighboring BSs based on the received signal power in the pilots sent from these BSs. Moreover, this paper utilizes stochastic geometry to develop a tractable mathematical model to assess the performance of BoLT in a general network setting. The goal of this paper is to answer the following two fundamental questions: i) how many BSs should be ordered and reported by the agent to achieve a desirable localization accuracy? and ii) what is the localization error probability given that the pilot signals are subject to shadowing? Assuming that the BSs are deployed according to a Poisson point process (PPP), we answer these two questions via characterizing the tradeoff between the area of location region (ALR) and the localization error probability in terms of the number of BSs ordered by the agent. The results show that reporting the order of six neighboring BSs is sufficient to localize the agent within 10% of the cell area. Increasing the number of reported BSs to ten confines the location region to 1% of the cell area. This would translate to the range of a few meters to decimeters in the foreseen ultra-dense 5G networks.
Verification of Stochastic Process Calculi
DEFF Research Database (Denmark)
Skrypnyuk, Nataliya
algorithms for constructing bisimulation relations, computing (overapproximations of) sets of reachable states and computing the expected time reachability, the last for a linear fragment of IMC. In all the cases we have the complexities of algorithms which are low polynomial in the size of the syntactic....... 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...... of Interactive Markov Chains (IMC). We have devised the Pathway Analysis of IMC that is not only correct in the sense of overapproximating all possible behaviour scenarios, as is usual for Static Analysis methods, but is also precise. This gives us the possibility to explicitly decide on the trade-o between...
Fourier analysis and stochastic processes
Brémaud, Pierre
2014-01-01
This work is unique as it provides a uniform treatment of the Fourier theories of functions (Fourier transforms and series, z-transforms), finite measures (characteristic functions, convergence in distribution), and stochastic processes (including arma series and point processes). It emphasises the links between these three themes. The chapter on the Fourier theory of point processes and signals structured by point processes is a novel addition to the literature on Fourier analysis of stochastic processes. It also connects the theory with recent lines of research such as biological spike signals and ultrawide-band communications. Although the treatment is mathematically rigorous, the convivial style makes the book accessible to a large audience. In particular, it will be interesting to anyone working in electrical engineering and communications, biology (point process signals) and econometrics (arma models). A careful review of the prerequisites (integration and probability theory in the appendix, Hilbert spa...
Stochastic integration and differential equations
Protter, Philip E
2003-01-01
It has been 15 years since the first edition of Stochastic Integration and Differential Equations, A New Approach appeared, and in those years many other texts on the same subject have been published, often with connections to applications, especially mathematical finance. Yet in spite of the apparent simplicity of approach, none of these books has used the functional analytic method of presenting semimartingales and stochastic integration. Thus a 2nd edition seems worthwhile and timely, though it is no longer appropriate to call it "a new approach". The new edition has several significant changes, most prominently the addition of exercises for solution. These are intended to supplement the text, but lemmas needed in a proof are never relegated to the exercises. Many of the exercises have been tested by graduate students at Purdue and Cornell Universities. Chapter 3 has been completely redone, with a new, more intuitive and simultaneously elementary proof of the fundamental Doob-Meyer decomposition theorem, t...
Modular invariance and stochastic quantization
International Nuclear Information System (INIS)
Ordonez, C.R.; Rubin, M.A.; Zwanziger, D.
1989-01-01
In Polyakov path integrals and covariant closed-string field theory, integration over Teichmueller parameters must be restricted by hand to a single modular region. This problem has an analog in Yang-Mills gauge theory---namely, the Gribov problem, which can be resolved by the method of stochastic gauge fixing. This method is here employed to quantize a simple modular-invariant system: the Polyakov point particle. In the limit of a large gauge-fixing force, it is shown that suitable choices for the functional form of the gauge-fixing force can lead to a restriction of Teichmueller integration to a single modular region. Modifications which arise when applying stochastic quantization to a system in which the volume of the orbits of the gauge group depends on a dynamical variable, such as a Teichmueller parameter, are pointed out, and the extension to Polyakov strings and covariant closed-string field theory is discussed
Stochastic models for atmospheric dispersion
DEFF Research Database (Denmark)
Ditlevsen, Ove Dalager
2003-01-01
Simple stochastic differential equation models have been applied by several researchers to describe the dispersion of tracer particles in the planetary atmospheric boundary layer and to form the basis for computer simulations of particle paths. To obtain the drift coefficient, empirical vertical...... positions close to the boundaries. Different rules have been suggested in the literature with justifications based on simulation studies. Herein the relevant stochastic differential equation model is formulated in a particular way. The formulation is based on the marginal transformation of the position...... velocity distributions that depend on height above the ground both with respect to standard deviation and skewness are substituted into the stationary Fokker/Planck equation. The particle position distribution is taken to be uniform *the well/mixed condition( and also a given dispersion coefficient...
Stochastic Generalized Method of Moments
Yin, Guosheng; Ma, Yanyuan; Liang, Faming; Yuan, Ying
2011-01-01
The generalized method of moments (GMM) is a very popular estimation and inference procedure based on moment conditions. When likelihood-based methods are difficult to implement, one can often derive various moment conditions and construct the GMM objective function. However, minimization of the objective function in the GMM may be challenging, especially over a large parameter space. Due to the special structure of the GMM, we propose a new sampling-based algorithm, the stochastic GMM sampler, which replaces the multivariate minimization problem by a series of conditional sampling procedures. We develop the theoretical properties of the proposed iterative Monte Carlo method, and demonstrate its superior performance over other GMM estimation procedures in simulation studies. As an illustration, we apply the stochastic GMM sampler to a Medfly life longevity study. Supplemental materials for the article are available online. © 2011 American Statistical Association.
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 Generalized Method of Moments
Yin, Guosheng
2011-08-16
The generalized method of moments (GMM) is a very popular estimation and inference procedure based on moment conditions. When likelihood-based methods are difficult to implement, one can often derive various moment conditions and construct the GMM objective function. However, minimization of the objective function in the GMM may be challenging, especially over a large parameter space. Due to the special structure of the GMM, we propose a new sampling-based algorithm, the stochastic GMM sampler, which replaces the multivariate minimization problem by a series of conditional sampling procedures. We develop the theoretical properties of the proposed iterative Monte Carlo method, and demonstrate its superior performance over other GMM estimation procedures in simulation studies. As an illustration, we apply the stochastic GMM sampler to a Medfly life longevity study. Supplemental materials for the article are available online. © 2011 American Statistical Association.
Limits for Stochastic Reaction Networks
DEFF Research Database (Denmark)
Cappelletti, Daniele
Reaction systems have been introduced in the 70s to model biochemical systems. Nowadays their range of applications has increased and they are fruitfully used in dierent elds. The concept is simple: some chemical species react, the set of chemical reactions form a graph and a rate function...... is associated with each reaction. Such functions describe the speed of the dierent reactions, or their propensities. Two modelling regimes are then available: the evolution of the dierent species concentrations can be deterministically modelled through a system of ODE, while the counts of the dierent species...... at a certain time are stochastically modelled by means of a continuous-time Markov chain. Our work concerns primarily stochastic reaction systems, and their asymptotic properties. In Paper I, we consider a reaction system with intermediate species, i.e. species that are produced and fast degraded along a path...
Some Topics in Stochastic Control
2010-10-14
assimilation problems. (a) Papers published in peer-reviewed journals (N/A for none) 1. R. Atar and A. Budhiraja. A stochastic differential game for...the inhomogeneous infinity-Laplace equation. Ann. Prob., 38 (2010), no. 2, 498--531. 2. R. Atar and A. Budhiraja. On near optimal trajectories for a...G. Aronsson. A mathematical model in sand mechanics: presentation and analysis. SIAM J. Appl. Math., 22 (1972), 437-458 [3] R. Atar and A. Budhiraja
Stochastic background of atmospheric cascades
International Nuclear Information System (INIS)
Wilk, G.; Wlodarczyk, Z.
1993-01-01
Fluctuations in the atmospheric cascades developing during the propagation of very high energy cosmic rays through the atmosphere are investigated using stochastic branching model of pure birth process with immigration. In particular, we show that the multiplicity distributions of secondaries emerging from gamma families are much narrower than those resulting from hadronic families. We argue that the strong intermittent like behaviour found recently in atmospheric families results from the fluctuations in the cascades themselves and are insensitive to the details of elementary interactions
Foundations of infinitesimal stochastic analysis
Stroyan, KD
2011-01-01
This book gives a complete and elementary account of fundamental results on hyperfinite measures and their application to stochastic processes, including the *-finite Stieltjes sum approximation of martingale integrals. Many detailed examples, not found in the literature, are included. It begins with a brief chapter on tools from logic and infinitesimal (or non-standard) analysis so that the material is accessible to beginning graduate students.
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 cooling technology at Fermilab
Energy Technology Data Exchange (ETDEWEB)
Pasquinelli, R.J. E-mail: pasquin@fnal.gov
2004-10-11
The first antiproton cooling systems were installed and commissioned at Fermilab in 1984-1985. In the interim period, there have been several major upgrades, system improvements, and complete reincarnation of cooling systems. This paper will present some of the technology that was pioneered at Fermilab to implement stochastic cooling systems in both the Antiproton Source and Recycler accelerators. Current performance data will also be presented.
Stochastic cooling technology at Fermilab
Pasquinelli, Ralph J.
2004-10-01
The first antiproton cooling systems were installed and commissioned at Fermilab in 1984-1985. In the interim period, there have been several major upgrades, system improvements, and complete reincarnation of cooling systems. This paper will present some of the technology that was pioneered at Fermilab to implement stochastic cooling systems in both the Antiproton Source and Recycler accelerators. Current performance data will also be presented.
Stochastic cooling technology at Fermilab
International Nuclear Information System (INIS)
Pasquinelli, R.J.
2004-01-01
The first antiproton cooling systems were installed and commissioned at Fermilab in 1984-1985. In the interim period, there have been several major upgrades, system improvements, and complete reincarnation of cooling systems. This paper will present some of the technology that was pioneered at Fermilab to implement stochastic cooling systems in both the Antiproton Source and Recycler accelerators. Current performance data will also be presented
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 processes and filtering theory
Jazwinski, Andrew H
1970-01-01
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
Multiple fields in stochastic inflation
Energy Technology Data Exchange (ETDEWEB)
Assadullahi, Hooshyar [Institute of Cosmology & Gravitation, University of Portsmouth,Dennis Sciama Building, Burnaby Road, Portsmouth, PO1 3FX (United Kingdom); Firouzjahi, Hassan [School of Astronomy, Institute for Research in Fundamental Sciences (IPM),P.O. Box 19395-5531, Tehran (Iran, Islamic Republic of); Noorbala, Mahdiyar [Department of Physics, University of Tehran,P.O. Box 14395-547, Tehran (Iran, Islamic Republic of); School of Astronomy, Institute for Research in Fundamental Sciences (IPM),P.O. Box 19395-5531, Tehran (Iran, Islamic Republic of); Vennin, Vincent; Wands, David [Institute of Cosmology & Gravitation, University of Portsmouth,Dennis Sciama Building, Burnaby Road, Portsmouth, PO1 3FX (United Kingdom)
2016-06-24
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-δN formalism.
Stochastic processes, slaves and supersymmetry
International Nuclear Information System (INIS)
Drummond, I T; Horgan, R R
2012-01-01
We extend the work of Tănase-Nicola and Kurchan on the structure of diffusion processes and the associated supersymmetry algebra by examining the responses of a simple statistical system to external disturbances of various kinds. We consider both the stochastic differential equations (SDEs) for the process and the associated diffusion equation. The influence of the disturbances can be understood by augmenting the original SDE with an equation for slave variables. The evolution of the slave variables describes the behaviour of line elements carried along in the stochastic flow. These line elements, together with the associated surface and volume elements constructed from them, provide the basis of the supersymmetry properties of the theory. For ease of visualization, and in order to emphasize a helpful electromagnetic analogy, we work in three dimensions. The results are all generalizable to higher dimensions and can be specialized to one and two dimensions. The electromagnetic analogy is a useful starting point for calculating asymptotic results at low temperature that can be compared with direct numerical evaluations. We also examine the problems that arise in a direct numerical simulation of the stochastic equation together with the slave equations. We pay special attention to the dependence of the slave variable statistics on temperature. We identify in specific models the critical temperature below which the slave variable distribution ceases to have a variance and consider the effect on estimates of susceptibilities. (paper)
Stochastic cooling in muon colliders
International Nuclear Information System (INIS)
Barletta, W.A.; Sessler, A.M.
1993-09-01
Analysis of muon production techniques for high energy colliders indicates the need for rapid and effective beam cooling in order that one achieve luminosities > 10 30 cm -2 s -1 as required for high energy physics experiments. This paper considers stochastic cooling to increase the phase space density of the muons in the collider. Even at muon energies greater than 100 GeV, the number of muons per bunch must be limited to ∼10 3 for the cooling rate to be less than the muon lifetime. With such a small number of muons per bunch, the final beam emittance implied by the luminosity requirement is well below the thermodynamic limit for beam electronics at practical temperatures. Rapid bunch stacking after the cooling process can raise the number of muons per bunch to a level consistent with both the luminosity goals and with practical temperatures for the stochastic cooling electronics. A major advantage of our stochastic cooling/stacking scheme over scenarios that employ only ionization cooling is that the power on the production target can be reduced below 1 MW
Stochastic analysis of biochemical systems
Anderson, David F
2015-01-01
This book focuses on counting processes and continuous-time Markov chains motivated by examples and applications drawn from chemical networks in systems biology. The book should serve well as a supplement for courses in probability and stochastic processes. While the material is presented in a manner most suitable for students who have studied stochastic processes up to and including martingales in continuous time, much of the necessary background material is summarized in the Appendix. Students and Researchers with a solid understanding of calculus, differential equations, and elementary probability and who are well-motivated by the applications will find this book of interest. David F. Anderson is Associate Professor in the Department of Mathematics at the University of Wisconsin and Thomas G. Kurtz is Emeritus Professor in the Departments of Mathematics and Statistics at that university. Their research is focused on probability and stochastic processes with applications in biology and other ar...
Stochastic inflation and nonlinear gravity
International Nuclear Information System (INIS)
Salopek, D.S.; Bond, J.R.
1991-01-01
We show how nonlinear effects of the metric and scalar fields may be included in stochastic inflation. Our formalism can be applied to non-Gaussian fluctuation models for galaxy formation. Fluctuations with wavelengths larger than the horizon length are governed by a network of Langevin equations for the physical fields. Stochastic noise terms arise from quantum fluctuations that are assumed to become classical at horizon crossing and that then contribute to the background. Using Hamilton-Jacobi methods, we solve the Arnowitt-Deser-Misner constraint equations which allows us to separate the growing modes from the decaying ones in the drift phase following each stochastic impulse. We argue that the most reasonable choice of time hypersurfaces for the Langevin system during inflation is T=ln(Ha), where H and a are the local values of the Hubble parameter and the scale factor, since T is the natural time for evolving the short-wavelength scalar field fluctuations in an inhomogeneous background
Radiolabelled cellular blood elements
International Nuclear Information System (INIS)
Sinzinger, H.
1990-01-01
This book reports on radiolabelled cellular blood elements, covering new advances made during the past several years, in particular the use of Tc-99 as a tracer for blood elements. Coverage extends to several radiolabelled monoclonal antibodies that are specific for blood components and may label blood elements in vivo
Building synthetic cellular organization
Polka, Jessica K.; Silver, Pamela A.
2013-01-01
The elaborate spatial organization of cells enhances, restricts, and regulates protein–protein interactions. However, the biological significance of this organization has been difficult to study without ways of directly perturbing it. We highlight synthetic biology tools for engineering novel cellular organization, describing how they have been, and can be, used to advance cell biology.
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)
Electromagnetic cellular interactions.
Cifra, Michal; Fields, Jeremy Z; Farhadi, Ashkan
2011-05-01
Chemical and electrical interaction within and between cells is well established. Just the opposite is true about cellular interactions via other physical fields. The most probable candidate for an other form of cellular interaction is the electromagnetic field. We review theories and experiments on how cells can generate and detect electromagnetic fields generally, and if the cell-generated electromagnetic field can mediate cellular interactions. We do not limit here ourselves to specialized electro-excitable cells. Rather we describe physical processes that are of a more general nature and probably present in almost every type of living cell. The spectral range included is broad; from kHz to the visible part of the electromagnetic spectrum. We show that there is a rather large number of theories on how cells can generate and detect electromagnetic fields and discuss experimental evidence on electromagnetic cellular interactions in the modern scientific literature. Although small, it is continuously accumulating. Copyright © 2010 Elsevier Ltd. All rights reserved.
Genetic Dominance & Cellular Processes
Seager, Robert D.
2014-01-01
In learning genetics, many students misunderstand and misinterpret what "dominance" means. Understanding is easier if students realize that dominance is not a mechanism, but rather a consequence of underlying cellular processes. For example, metabolic pathways are often little affected by changes in enzyme concentration. This means that…
Spatiotemporal Stochastic Resonance:Theory and Experiment
Peter, Jung
1996-03-01
The amplification of weak periodic signals in bistable or excitable systems via stochastic resonance has been studied intensively over the last years. We are going one step further and ask: Can noise enhance spatiotemporal patterns in excitable media and can this effect be observed in nature? To this end, we are looking at large, two dimensional arrays of coupled excitable elements. Due to the coupling, excitation can propagate through the array in form of nonlinear waves. We observe target waves, rotating spiral waves and other wave forms. If the coupling between the elements is below a critical threshold, any excitational pattern will die out in the absence of noise. Below this threshold, large scale rotating spiral waves - as they are observed above threshold - can be maintained by a proper level of the noise[1]. Furthermore, their geometric features, such as the curvature can be controlled by the homogeneous noise level[2]. If the noise level is too large, break up of spiral waves and collisions with spontaneously nucleated waves yields spiral turbulence. Driving our array with a spatiotemporal pattern, e.g. a rotating spiral wave, we show that for weak coupling the excitational response of the array shows stochastic resonance - an effect we have termed spatiotemporal stochastic resonance. In the last part of the talk I'll make contact with calcium waves, observed in astrocyte cultures and hippocampus slices[3]. A. Cornell-Bell and collaborators[3] have pointed out the role of calcium waves for long-range glial signaling. We demonstrate the similarity of calcium waves with nonlinear waves in noisy excitable media. The noise level in the tissue is characterized by spontaneous activity and can be controlled by applying neuro-transmitter substances[3]. Noise effects in our model are compared with the effect of neuro-transmitters on calcium waves. [1]P. Jung and G. Mayer-Kress, CHAOS 5, 458 (1995). [2]P. Jung and G. Mayer-Kress, Phys. Rev. Lett.62, 2682 (1995). [3
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
Sensing Phosphatidylserine in Cellular Membranes
Directory of Open Access Journals (Sweden)
Jason G. Kay
2011-01-01
Full Text Available Phosphatidylserine, a phospholipid with a negatively charged head-group, is an important constituent of eukaryotic cellular membranes. On the plasma membrane, rather than being evenly distributed, phosphatidylserine is found preferentially in the inner leaflet. Disruption of this asymmetry, leading to the appearance of phosphatidylserine on the surface of the cell, is known to play a central role in both apoptosis and blood clotting. Despite its importance, comparatively little is known about phosphatidylserine in cells: its precise subcellular localization, transmembrane topology and intracellular dynamics are poorly characterized. The recent development of new, genetically-encoded probes able to detect phosphatidylserine within live cells, however, is leading to a more in-depth understanding of the biology of this phospholipid. This review aims to give an overview of the current methods for phosphatidylserine detection within cells, and some of the recent realizations derived from their use.
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...
Stochastic synaptic plasticity with memristor crossbar arrays
Naous, Rawan
2016-11-01
Memristive devices have been shown to exhibit slow and stochastic resistive switching behavior under low-voltage, low-current operating conditions. Here we explore such mechanisms to emulate stochastic plasticity in memristor crossbar synapse arrays. Interfaced with integrate-and-fire spiking neurons, the memristive synapse arrays are capable of implementing stochastic forms of spike-timing dependent plasticity which parallel mean-rate models of stochastic learning with binary synapses. We present theory and experiments with spike-based stochastic learning in memristor crossbar arrays, including simplified modeling as well as detailed physical simulation of memristor stochastic resistive switching characteristics due to voltage and current induced filament formation and collapse. © 2016 IEEE.