Robust control and linear parameter varying approaches application to vehicle dynamics

CERN Document Server

Gaspar, Peter; Bokor, József

2013-01-01

Vehicles are complex systems (non-linear, multi-variable) where the abundance of embedded controllers should ensure better security. This book aims at emphasizing the interest and potential of Linear Parameter Varying methods within the framework of vehicle dynamics, e.g.   ·          proposed control-oriented model, complex enough to handle some system non linearities but still simple for control or observer design,   ·          take into account the adaptability of the vehicle's response to driving situations, to the driver request and/or to the road sollicitations,   ·          manage interactions between various actuators to optimize the dynamic behavior of vehicles.   This book results from the 32th International Summer School in Automatic that held in Grenoble, France, in September 2011, where recent methods (based on robust control and LPV technics), then applied to the control of vehicle dynamics, have been presented. After some theoretical background and a view on so...

Distributed leader-follower flocking control for multi-agent dynamical systems with time-varying velocities

NARCIS (Netherlands)

Yu, Wenwu; Chen, Guanrong; Cao, Ming

Using tools from algebraic graph theory and nonsmooth analysis in combination with ideas of collective potential functions, velocity consensus and navigation feedback, a distributed leader-follower flocking algorithm for multi-agent dynamical systems with time-varying velocities is developed where

Time-Varying Dynamic Properties of Offshore Wind Turbines Evaluated by Modal Testing

DEFF Research Database (Denmark)

Damgaard, Mads; Andersen, J. K. F.; Ibsen, Lars Bo

2014-01-01

resonance of the wind turbine structure. In this paper, free vibration tests and a numerical Winkler type approach are used to evaluate the dynamic properties of a total of 30 offshore wind turbines located in the North Sea. Analyses indicate time-varying eigenfrequencies and damping ratios of the lowest...... structural eigenmode. Isolating the oscillation oil damper performance, moveable seabed conditions may lead to the observed time dependency....

On the scaling limits of Galton Watson processes in varying environment

NARCIS (Netherlands)

Bansaye, V.; Simatos, F.

2011-01-01

Renormalized sequences of Galton Watson processes converge to Continuous State Branching Processes (CSBP), characterized by a L\\'evy triplet of two numbers and a measure. This paper investigates the case of Galton Watson processes in varying environment and provides an explicit sufficient condition

Closeness-Centrality-Based Synchronization Criteria for Complex Dynamical Networks With Interval Time-Varying Coupling Delays.

Science.gov (United States)

Park, Myeongjin; Lee, Seung-Hoon; Kwon, Oh-Min; Seuret, Alexandre

2017-09-06

This paper investigates synchronization in complex dynamical networks (CDNs) with interval time-varying delays. The CDNs are representative of systems composed of a large number of interconnected dynamical units, and for the purpose of the mathematical analysis, the leading work is to model them as graphs whose nodes represent the dynamical units. At this time, we take note of the importance of each node in networks. One way, in this paper, is that the closeness-centrality mentioned in the field of social science is grafted onto the CDNs. By constructing a suitable Lyapunov-Krasovskii functional, and utilizing some mathematical techniques, the sufficient and closeness-centrality-based conditions for synchronization stability of the networks are established in terms of linear matrix inequalities. Ultimately, the use of the closeness-centrality can be weighted with regard to not only the interconnection relation among the nodes, which was utilized in the existing works but also more information about nodes. Here, the centrality will be added as the concerned information. Moreover, to avoid the computational burden causing the nonconvex term including the square of the time-varying delay, how to deal with it is applied by estimating it to the convex term including time-varying delay. Finally, two illustrative examples are given to show the advantage of the closeness-centrality in point of the robustness on time-delay.

Analyzing the term structure of interest rates using the dynamic Nelson-Siegel model with time-varying parameters

NARCIS (Netherlands)

Koopman, S.J.; Mallee, M.I.P.; van der Wel, M.

2010-01-01

In this article we introduce time-varying parameters in the dynamic Nelson-Siegel yield curve model for the simultaneous analysis and forecasting of interest rates of different maturities. The Nelson-Siegel model has been recently reformulated as a dynamic factor model with vector autoregressive

A Tentative Application Of Morphological Filters To Time-Varying Images

Science.gov (United States)

Billard, D.; Poquillon, B.

1989-03-01

In this paper, morphological filters, which are commonly used to process either 2D or multidimensional static images, are generalized to the analysis of time-varying image sequence. The introduction of the time dimension induces then interesting prop-erties when designing such spatio-temporal morphological filters. In particular, the specification of spatio-temporal structuring ele-ments (equivalent to time-varying spatial structuring elements) can be adjusted according to the temporal variations of the image sequences to be processed : this allows to derive specific morphological transforms to perform noise filtering or moving objects discrimination on dynamic images viewed by a non-stationary sensor. First, a brief introduction to the basic principles underlying morphological filters will be given. Then, a straightforward gener-alization of these principles to time-varying images will be pro-posed. This will lead us to define spatio-temporal opening and closing and to introduce some of their possible applications to process dynamic images. At last, preliminary results obtained us-ing a natural forward looking infrared (FUR) image sequence are presented.

Positive Analysis of Invasive Species Control as a Dynamic Spatial Process

OpenAIRE

Buyuktahtakin, Esra; Feng, Zhuo; Olsson, Aaryn; Frisvold, George B.; Szidarovszky, Ferenc

2010-01-01

This paper models control of invasive buffelgrass (Pennisetum ciliare), a fire-prone African bunchgrass spreading rapidly across the southern Arizona desert as a spatial dynamic process. Buffelgrass spreads over a gridded landscape. Weed carrying capacity, treatment costs, and damages vary over grid cells. Damage from buffelgrass depends on its spatial distribution in relation to valued resources. We conduct positive analysis of recommended heuristic strategies for buffelgrass control, evalua...

Dynamic Optimization of UV Flash Processes

DEFF Research Database (Denmark)

Ritschel, Tobias Kasper Skovborg; Capolei, Andrea; Jørgensen, John Bagterp

2017-01-01

UV ash processes, also referred to as isoenergetic-isochoric ash processes, occur for dynamic simulation and optimization of vapor-liquid equilibrium processes. Dynamic optimization and nonlinear model predictive control of distillation columns, certain two-phase ow problems, as well as oil reser...... that the optimization solver, the compiler, and high-performance linear algebra software are all important for e_cient dynamic optimization of UV ash processes....

Identification of time-varying structural dynamic systems - An artificial intelligence approach

Science.gov (United States)

Glass, B. J.; Hanagud, S.

1992-01-01

An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.

Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.

Science.gov (United States)

Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis

2018-01-01

Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.

Sex differences in in-group cooperation vary dynamically with competitive conditions and outcomes.

Science.gov (United States)

Bailey, Drew H; Winegard, Benjamin; Oxford, Jon; Geary, David C

2012-03-18

Men's but not women's investment in a public goods game varied dynamically with the presence or absence of a perceived out-group. Three hundred fifty-four (167 male) young adults participated in multiple iterations of a public goods game under intergroup and individual competition conditions. Participants received feedback about whether their investments in the group were sufficient to earn a bonus to be shared among all in-group members. Results for the first trial confirm previous research in which men's but not women's investments were higher when there was a competing out-group. We extended these findings by showing that men's investment in the in-group varied dynamically by condition depending on the outcome of the previous trial: In the group condition, men, but not women, decreased spending following a win (i.e., earning an in-group bonus). In the individual condition, men, but not women, increased spending following a win. We hypothesize that these patterns reflect a male bias to calibrate their level of in-group investment such that they sacrifice only what is necessary for their group to successfully compete against a rival group.

Sex Differences in In-Group Cooperation Vary Dynamically with Competitive Conditions and Outcomes

Directory of Open Access Journals (Sweden)

Drew H. Bailey

2012-01-01

Full Text Available Men's but not women's investment in a public goods game varied dynamically with the presence or absence of a perceived out-group. Three hundred fifty-four (167 male young adults participated in multiple iterations of a public goods game under intergroup and individual competition conditions. Participants received feedback about whether their investments in the group were sufficient to earn a bonus to be shared among all in-group members. Results for the first trial confirm previous research in which men's but not women's investments were higher when there was a competing out-group. We extended these findings by showing that men's investment in the in-group varied dynamically by condition depending on the outcome of the previous trial: In the group condition, men, but not women, decreased spending following a win (i.e., earning an in-group bonus. In the individual condition, men, but not women, increased spending following a win. We hypothesize that these patterns reflect a male bias to calibrate their level of in-group investment such that they sacrifice only what is necessary for their group to successfully compete against a rival group.

Microbial phylogeny determines transcriptional response of resistome to dynamic composting processes.

Science.gov (United States)

Wang, Cheng; Dong, Da; Strong, P J; Zhu, Weijing; Ma, Zhuang; Qin, Yong; Wu, Weixiang

2017-08-16

Animal manure is a reservoir of antibiotic resistance genes (ARGs) that pose a potential health risk globally, especially for resistance to the antibiotics commonly used in livestock production (such as tetracycline, sulfonamide, and fluoroquinolone). Currently, the effects of biological treatment (composting) on the transcriptional response of manure ARGs and their microbial hosts are not well characterized. Composting is a dynamic process that consists of four distinct phases that are distinguished by the temperature resulting from microbial activity, namely the mesophilic, thermophilic, cooling, and maturing phases. In this study, changes of resistome expression were determined and related to active microbiome profiles during the dynamic composting process. This was achieved by integrating metagenomic and time series metatranscriptomic data for the evolving microbial community during composting. Composting noticeably reduced the aggregated expression level of the manure resistome, which primarily consisted of genes encoding for tetracycline, vancomycin, fluoroquinolone, beta-lactam, and aminoglycoside resistance, as well as efflux pumps. Furthermore, a varied transcriptional response of resistome to composting at the ARG levels was highlighted. The expression of tetracycline resistance genes (tetM-tetW-tetO-tetS) decreased during composting, where distinctive shifts in the four phases of composting were related to variations in antibiotic concentration. Composting had no effect on the expression of sulfonamide and fluoroquinolone resistance genes, which increased slightly during the thermophilic phase and then decreased to initial levels. As indigenous populations switched greatly throughout the dynamic composting, the core resistome persisted and their reservoir hosts' composition was significantly correlated with dynamic active microbial phylogenetic structure. Hosts for sulfonamide and fuoroquinolone resistance genes changed notably in phylognetic structure

From point process observations to collective neural dynamics: Nonlinear Hawkes process GLMs, low-dimensional dynamics and coarse graining.

Science.gov (United States)

Truccolo, Wilson

2016-11-01

This review presents a perspective on capturing collective dynamics in recorded neuronal ensembles based on multivariate point process models, inference of low-dimensional dynamics and coarse graining of spatiotemporal measurements. A general probabilistic framework for continuous time point processes reviewed, with an emphasis on multivariate nonlinear Hawkes processes with exogenous inputs. A point process generalized linear model (PP-GLM) framework for the estimation of discrete time multivariate nonlinear Hawkes processes is described. The approach is illustrated with the modeling of collective dynamics in neocortical neuronal ensembles recorded in human and non-human primates, and prediction of single-neuron spiking. A complementary approach to capture collective dynamics based on low-dimensional dynamics ("order parameters") inferred via latent state-space models with point process observations is presented. The approach is illustrated by inferring and decoding low-dimensional dynamics in primate motor cortex during naturalistic reach and grasp movements. Finally, we briefly review hypothesis tests based on conditional inference and spatiotemporal coarse graining for assessing collective dynamics in recorded neuronal ensembles. Published by Elsevier Ltd.

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

International Nuclear Information System (INIS)

Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze

2017-01-01

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

Energy Technology Data Exchange (ETDEWEB)

Lu, Fengbin, E-mail: fblu@amss.ac.cn [Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); Qiao, Han, E-mail: qiaohan@ucas.ac.cn [School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 (China); Wang, Shouyang, E-mail: sywang@amss.ac.cn [School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 (China); Lai, Kin Keung, E-mail: mskklai@cityu.edu.hk [Department of Management Sciences, City University of Hong Kong (Hong Kong); Li, Yuze, E-mail: richardyz.li@mail.utoronto.ca [Department of Industrial Engineering, University of Toronto (Canada)

2017-01-15

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.

Adaptive fuzzy dynamic surface control of nonlinear systems with input saturation and time-varying output constraints

Science.gov (United States)

Edalati, L.; Khaki Sedigh, A.; Aliyari Shooredeli, M.; Moarefianpour, A.

2018-02-01

This paper deals with the design of adaptive fuzzy dynamic surface control for uncertain strict-feedback nonlinear systems with asymmetric time-varying output constraints in the presence of input saturation. To approximate the unknown nonlinear functions and overcome the problem of explosion of complexity, a Fuzzy logic system is combined with the dynamic surface control in the backstepping design technique. To ensure the output constraints satisfaction, an asymmetric time-varying Barrier Lyapunov Function (BLF) is used. Moreover, by applying the minimal learning parameter technique, the number of the online parameters update for each subsystem is reduced to 2. Hence, the semi-globally uniformly ultimately boundedness (SGUUB) of all the closed-loop signals with appropriate tracking error convergence is guaranteed. The effectiveness of the proposed control is demonstrated by two simulation examples.

Dynamical processes and epidemic threshold on nonlinear coupled multiplex networks

Science.gov (United States)

Gao, Chao; Tang, Shaoting; Li, Weihua; Yang, Yaqian; Zheng, Zhiming

2018-04-01

Recently, the interplay between epidemic spreading and awareness diffusion has aroused the interest of many researchers, who have studied models mainly based on linear coupling relations between information and epidemic layers. However, in real-world networks the relation between two layers may be closely correlated with the property of individual nodes and exhibits nonlinear dynamical features. Here we propose a nonlinear coupled information-epidemic model (I-E model) and present a comprehensive analysis in a more generalized scenario where the upload rate differs from node to node, deletion rate varies between susceptible and infected states, and infection rate changes between unaware and aware states. In particular, we develop a theoretical framework of the intra- and inter-layer dynamical processes with a microscopic Markov chain approach (MMCA), and derive an analytic epidemic threshold. Our results suggest that the change of upload and deletion rate has little effect on the diffusion dynamics in the epidemic layer.

Formal analysis of design process dynamics

NARCIS (Netherlands)

Bosse, T.; Jonker, C.M.; Treur, J.

2010-01-01

This paper presents a formal analysis of design process dynamics. Such a formal analysis is a prerequisite to come to a formal theory of design and for the development of automated support for the dynamics of design processes. The analysis was geared toward the identification of dynamic design

Formal Analysis of Design Process Dynamics

NARCIS (Netherlands)

Bosse, T.; Jonker, C.M.; Treur, J.

2010-01-01

This paper presents a formal analysis of design process dynamics. Such a formal analysis is a prerequisite to come to a formal theory of design and for the development of automated support for the dynamics of design processes. The analysis was geared toward the identification of dynamic design

Visualizing time: how linguistic metaphors are incorporated into displaying instruments in the process of interpreting time-varying signals

Science.gov (United States)

Garcia-Belmonte, Germà

2017-06-01

Spatial visualization is a well-established topic of education research that has allowed improving science and engineering students' skills on spatial relations. Connections have been established between visualization as a comprehension tool and instruction in several scientific fields. Learning about dynamic processes mainly relies upon static spatial representations or images. Visualization of time is inherently problematic because time can be conceptualized in terms of two opposite conceptual metaphors based on spatial relations as inferred from conventional linguistic patterns. The situation is particularly demanding when time-varying signals are recorded using displaying electronic instruments, and the image should be properly interpreted. This work deals with the interplay between linguistic metaphors, visual thinking and scientific instrument mediation in the process of interpreting time-varying signals displayed by electronic instruments. The analysis draws on a simplified version of a communication system as example of practical signal recording and image visualization in a physics and engineering laboratory experience. Instrumentation delivers meaningful signal representations because it is designed to incorporate a specific and culturally favored time view. It is suggested that difficulties in interpreting time-varying signals are linked with the existing dual perception of conflicting time metaphors. The activation of specific space-time conceptual mapping might allow for a proper signal interpretation. Instruments play then a central role as visualization mediators by yielding an image that matches specific perception abilities and practical purposes. Here I have identified two ways of understanding time as used in different trajectories through which students are located. Interestingly specific displaying instruments belonging to different cultural traditions incorporate contrasting time views. One of them sees time in terms of a dynamic metaphor

Parallel processing for fluid dynamics applications

International Nuclear Information System (INIS)

Johnson, G.M.

1989-01-01

The impact of parallel processing on computational science and, in particular, on computational fluid dynamics is growing rapidly. In this paper, particular emphasis is given to developments which have occurred within the past two years. Parallel processing is defined and the reasons for its importance in high-performance computing are reviewed. Parallel computer architectures are classified according to the number and power of their processing units, their memory, and the nature of their connection scheme. Architectures which show promise for fluid dynamics applications are emphasized. Fluid dynamics problems are examined for parallelism inherent at the physical level. CFD algorithms and their mappings onto parallel architectures are discussed. Several example are presented to document the performance of fluid dynamics applications on present-generation parallel processing devices

Feedback topology and XOR-dynamics in Boolean networks with varying input structure.

Science.gov (United States)

Ciandrini, L; Maffi, C; Motta, A; Bassetti, B; Cosentino Lagomarsino, M

2009-08-01

We analyze a model of fixed in-degree random Boolean networks in which the fraction of input-receiving nodes is controlled by the parameter gamma. We investigate analytically and numerically the dynamics of graphs under a parallel XOR updating scheme. This scheme is interesting because it is accessible analytically and its phenomenology is at the same time under control and as rich as the one of general Boolean networks. We give analytical formulas for the dynamics on general graphs, showing that with a XOR-type evolution rule, dynamic features are direct consequences of the topological feedback structure, in analogy with the role of relevant components in Kauffman networks. Considering graphs with fixed in-degree, we characterize analytically and numerically the feedback regions using graph decimation algorithms (Leaf Removal). With varying gamma , this graph ensemble shows a phase transition that separates a treelike graph region from one in which feedback components emerge. Networks near the transition point have feedback components made of disjoint loops, in which each node has exactly one incoming and one outgoing link. Using this fact, we provide analytical estimates of the maximum period starting from topological considerations.

Feedback topology and XOR-dynamics in Boolean networks with varying input structure

Science.gov (United States)

Ciandrini, L.; Maffi, C.; Motta, A.; Bassetti, B.; Cosentino Lagomarsino, M.

2009-08-01

We analyze a model of fixed in-degree random Boolean networks in which the fraction of input-receiving nodes is controlled by the parameter γ . We investigate analytically and numerically the dynamics of graphs under a parallel XOR updating scheme. This scheme is interesting because it is accessible analytically and its phenomenology is at the same time under control and as rich as the one of general Boolean networks. We give analytical formulas for the dynamics on general graphs, showing that with a XOR-type evolution rule, dynamic features are direct consequences of the topological feedback structure, in analogy with the role of relevant components in Kauffman networks. Considering graphs with fixed in-degree, we characterize analytically and numerically the feedback regions using graph decimation algorithms (Leaf Removal). With varying γ , this graph ensemble shows a phase transition that separates a treelike graph region from one in which feedback components emerge. Networks near the transition point have feedback components made of disjoint loops, in which each node has exactly one incoming and one outgoing link. Using this fact, we provide analytical estimates of the maximum period starting from topological considerations.

Normalized value coding explains dynamic adaptation in the human valuation process.

Science.gov (United States)

Khaw, Mel W; Glimcher, Paul W; Louie, Kenway

2017-11-28

The notion of subjective value is central to choice theories in ecology, economics, and psychology, serving as an integrated decision variable by which options are compared. Subjective value is often assumed to be an absolute quantity, determined in a static manner by the properties of an individual option. Recent neurobiological studies, however, have shown that neural value coding dynamically adapts to the statistics of the recent reward environment, introducing an intrinsic temporal context dependence into the neural representation of value. Whether valuation exhibits this kind of dynamic adaptation at the behavioral level is unknown. Here, we show that the valuation process in human subjects adapts to the history of previous values, with current valuations varying inversely with the average value of recently observed items. The dynamics of this adaptive valuation are captured by divisive normalization, linking these temporal context effects to spatial context effects in decision making as well as spatial and temporal context effects in perception. These findings suggest that adaptation is a universal feature of neural information processing and offer a unifying explanation for contextual phenomena in fields ranging from visual psychophysics to economic choice.

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets.

Science.gov (United States)

Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze

2017-01-01

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor's 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model. Copyright © 2016 Elsevier Ltd. All rights reserved.

A behavioral asset pricing model with a time-varying second moment

International Nuclear Information System (INIS)

Chiarella, Carl; He Xuezhong; Wang, Duo

2006-01-01

We develop a simple behavioral asset pricing model with fundamentalists and chartists in order to study price behavior in financial markets when chartists estimate both conditional mean and variance by using a weighted averaging process. Through a stability, bifurcation, and normal form analysis, the market impact of the weighting process and time-varying second moment are examined. It is found that the fundamental price becomes stable (unstable) when the activities from both types of traders are balanced (unbalanced). When the fundamental price becomes unstable, the weighting process leads to different price dynamics, depending on whether the chartists act as either trend followers or contrarians. It is also found that a time-varying second moment of the chartists does not change the stability of the fundamental price, but it does influence the stability of the bifurcations. The bifurcation becomes stable (unstable) when the chartists are more (less) concerned about the market risk characterized by the time-varying second moment. Different routes to complicated price dynamics are also observed. The analysis provides an analytical foundation for the statistical analysis of the corresponding stochastic version of this type of behavioral model

Reduced dielectric response in spatially varying electric fields

DEFF Research Database (Denmark)

Hansen, Jesper Schmidt

2015-01-01

relations between the flux and the gradient of the polarization. Comparison between the theory and molecular dynamics simulations confirms this effect. The effect is significant for small length scale electric field variations and the inclusion of the flux is thus important in nanoscale modeling......In this paper, the dynamical equation for polarization is derived. From this the dielectric response to a spatially varying electric field is analyzed showing a reduced response due to flux of polarization in the material. This flux is modeled as a diffusive process through linear constitutive...

Selection of Activities in Dynamic Business Process Simulation

Directory of Open Access Journals (Sweden)

Toma Rusinaitė

2016-06-01

Full Text Available Maintaining dynamicity of business processes is one of the core issues of today's business as it enables businesses to adapt to constantly changing environment. Upon changing the processes, it is vital to assess possible impact, which is achieved by using simulation of dynamic processes. In order to implement dynamicity in business processes, it is necessary to have an ability to change components of the process (a set of activities, a content of activity, a set of activity sequences, a set of rules, performers and resources or dynamically select them during execution. This problem attracted attention of researches over the past few years; however, there is no proposed solution, which ensures the business process (BP dynamicity. This paper proposes and specifies dynamic business process (DBP simulation model, which satisfies all of the formulated DBP requirements.

From dynamical systems with time-varying delay to circle maps and Koopman operators

Science.gov (United States)

Müller, David; Otto, Andreas; Radons, Günter

2017-06-01

In this paper, we investigate the influence of the retarded access by a time-varying delay on the dynamics of delay systems. We show that there are two universality classes of delays, which lead to fundamental differences in dynamical quantities such as the Lyapunov spectrum. Therefore, we introduce an operator theoretic framework, where the solution operator of the delay system is decomposed into the Koopman operator describing the delay access and an operator similar to the solution operator known from systems with constant delay. The Koopman operator corresponds to an iterated map, called access map, which is defined by the iteration of the delayed argument of the delay equation. The dynamics of this one-dimensional iterated map determines the universality classes of the infinite-dimensional state dynamics governed by the delay differential equation. In this way, we connect the theory of time-delay systems with the theory of circle maps and the framework of the Koopman operator. In this paper, we extend our previous work [A. Otto, D. Müller, and G. Radons, Phys. Rev. Lett. 118, 044104 (2017), 10.1103/PhysRevLett.118.044104] by elaborating the mathematical details and presenting further results also on the Lyapunov vectors.

Hydration structure and dynamics of a hydroxide ion in water clusters of varying size and temperature: Quantum chemical and ab initio molecular dynamics studies

International Nuclear Information System (INIS)

Bankura, Arindam; Chandra, Amalendu

2012-01-01

Highlights: ► A theoretical study of hydroxide ion-water clusters is carried for varying cluster size and temperature. ► The structures of OH − (H 2 O) n are found out through quantum chemical calculations for n = 4, 8, 16 and 20. ► The finite temperature behavior of the clusters is studied through ab initio dynamical simulations. ► The spectral features of OH modes (deuterated) and their dependence on hydrogen bonding states of water are discussed. ► The mechanism and kinetics of proton transfer processes in these anionic clusters are also investigated. - Abstract: We have investigated the hydration structure and dynamics of OH − (H 2 O) n clusters (n = 4, 8, 16 and 20) by means of quantum chemical and ab initio molecular dynamics calculations. Quantum chemical calculations reveal that the solvation structure of the hydroxide ion transforms from three and four-coordinated surface states to five-coordinated interior state with increase in cluster size. Several other isomeric structures with energies not very different from the most stable isomer are also found. Ab initio simulations show that the most probable configurations at higher temperatures need not be the lowest energy isomeric structure. The rates of proton transfer in these clusters are found to be slower than that in bulk water. The vibrational spectral calculations reveal distinct features for free OH (deuterated) stretch modes of water in different hydrogen bonding states. Effects of temperature on the structural and dynamical properties are also investigated for the largest cluster considered here.

Time-varying Crash Risk

DEFF Research Database (Denmark)

Christoffersen, Peter; Feunoua, Bruno; Jeon, Yoontae

We estimate a continuous-time model with stochastic volatility and dynamic crash probability for the S&P 500 index and find that market illiquidity dominates other factors in explaining the stock market crash risk. While the crash probability is time-varying, its dynamic depends only weakly on re...

Identification of process dynamics. Stability monitoring in BWR type reactors

International Nuclear Information System (INIS)

Abrahamsson, P.; Hallgren, P.

1991-06-01

Identification of process dynamics is used for stability monitoring in nuclear reactors (Boiling Water Reactor). This report treats the problem of estimating a damping factor and a resonance frequency from the neutron flux as measured in the reactor. A new parametric online method for identification is derived and presented, and is shown to meet the requirements of stability monitoring. The technique for estimating the process parameters is based on a recursive lattice filter algorithm. The problem of time varying parameters and offset, as well as offline experiments and signal processing are treated. All parts are implemented in a realtime program, using the language C. In comparison with earlier identifications, the new way of estimating the damping factor is shown to work well. Estimates of both the damping factor and the resonance frequency show a stable and reliable behavior. Future development and improvements are also indicated. (au)

Parent-child coregulation of parasympathetic processes varies by social context and risk for psychopathology.

Science.gov (United States)

Lunkenheimer, Erika; Tiberio, Stacey S; Skoranski, Amanda M; Buss, Kristin A; Cole, Pamela M

2018-02-01

The parasympathetic nervous system supports social interaction and varies in relation to psychopathology. However, we know little about parasympathetic processes from a dyadic framework, nor in early childhood when parent-child social interactions become more complex and child psychopathology first emerges. We hypothesized that higher risk for psychopathology (maternal psychopathology symptoms and child problem behavior) would be related to weaker concordance of respiratory sinus arrhythmia (RSA) between mothers and children (M = 3½ years old; N = 47) and that these relations could vary by social contextual demands, comparing unstructured free play, semistructured cleanup, and structured teaching tasks. Multilevel coupled autoregressive models of RSA during parent-child interactions showed overall dynamic, positive concordance in mother-child RSA over time, but this concordance was weaker during the more structured teaching task. In contrast, higher maternal psychological aggression and child externalizing and internalizing problems were associated with weaker dyadic RSA concordance, which was weakest during unstructured free play. Higher maternal depressive symptoms were related to disrupted individual mother and child RSA but not to RSA concordance. Thus, risk for psychopathology was generally related to weaker dyadic mother-child RSA concordance in contexts with less complex structure or demands (free play, cleanup), as compared to the structured teaching task that showed weaker RSA concordance for all dyads. Implications for the meaning and utility of the construct of parent-child physiological coregulation are discussed. © 2017 Society for Psychophysiological Research.

Fuzzy control of pressurizer dynamic process

International Nuclear Information System (INIS)

Ming Zhedong; Zhao Fuyu

2006-01-01

Considering the characteristics of pressurizer dynamic process, the fuzzy control system that takes the advantages of both fuzzy controller and PID controller is designed for the dynamic process in pressurizer. The simulation results illustrate this type of composite control system is with better qualities than those of single fuzzy controller and single PID controller. (authors)

State space modeling of time-varying contemporaneous and lagged relations in connectivity maps.

Science.gov (United States)

Molenaar, Peter C M; Beltz, Adriene M; Gates, Kathleen M; Wilson, Stephen J

2016-01-15

Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. Published by Elsevier Inc.

ESTIMATION OF CONSTANT AND TIME-VARYING DYNAMIC PARAMETERS OF HIV INFECTION IN A NONLINEAR DIFFERENTIAL EQUATION MODEL.

Science.gov (United States)

Liang, Hua; Miao, Hongyu; Wu, Hulin

2010-03-01

Modeling viral dynamics in HIV/AIDS studies has resulted in deep understanding of pathogenesis of HIV infection from which novel antiviral treatment guidance and strategies have been derived. Viral dynamics models based on nonlinear differential equations have been proposed and well developed over the past few decades. However, it is quite challenging to use experimental or clinical data to estimate the unknown parameters (both constant and time-varying parameters) in complex nonlinear differential equation models. Therefore, investigators usually fix some parameter values, from the literature or by experience, to obtain only parameter estimates of interest from clinical or experimental data. However, when such prior information is not available, it is desirable to determine all the parameter estimates from data. In this paper, we intend to combine the newly developed approaches, a multi-stage smoothing-based (MSSB) method and the spline-enhanced nonlinear least squares (SNLS) approach, to estimate all HIV viral dynamic parameters in a nonlinear differential equation model. In particular, to the best of our knowledge, this is the first attempt to propose a comparatively thorough procedure, accounting for both efficiency and accuracy, to rigorously estimate all key kinetic parameters in a nonlinear differential equation model of HIV dynamics from clinical data. These parameters include the proliferation rate and death rate of uninfected HIV-targeted cells, the average number of virions produced by an infected cell, and the infection rate which is related to the antiviral treatment effect and is time-varying. To validate the estimation methods, we verified the identifiability of the HIV viral dynamic model and performed simulation studies. We applied the proposed techniques to estimate the key HIV viral dynamic parameters for two individual AIDS patients treated with antiretroviral therapies. We demonstrate that HIV viral dynamics can be well characterized and

Surface-Assisted Dynamic Search Processes.

Science.gov (United States)

Shin, Jaeoh; Kolomeisky, Anatoly B

2018-03-01

Many chemical and biological systems exhibit intermittent search phenomena when participating particles alternate between dynamic regimes with different dimensionalities. Here we investigate theoretically a dynamic search process of finding a small target on a two-dimensional surface starting from a bulk solution, which is an example of such an intermittent search process. Both continuum and discrete-state stochastic descriptions are developed. It is found that depending on the scanning length λ, which describes the area visited by the reacting molecule during one search cycle, the system can exhibit three different search regimes: (i) For small λ values, the reactant finds the target mostly via three-dimensional bulk diffusion; (ii) for large λ values, the reactant molecule associates to the target mostly via surface diffusion; and (iii) for intermediate λ values, the reactant reaches the target via a combination of three-dimensional and two-dimensional search cycles. Our analysis also shows that the mean search times have different scalings as a function of the size of the surface segment depending on the nature of the dynamic search regime. Search dynamics are also sensitive to the position of the target for large scanning lengths. In addition, it is argued that the continuum description underestimates mean search times and does not always correctly describe the most optimal conditions for the surface-assisted dynamic processes. The importance of our findings for real natural systems is discussed.

Simulation of dynamic processes when machining transition surfaces of stepped shafts

Science.gov (United States)

Maksarov, V. V.; Krasnyy, V. A.; Viushin, R. V.

2018-03-01

The paper addresses the characteristics of stepped surfaces of parts categorized as "solids of revolution". It is noted that in the conditions of transition modes during the switch to end surface machining, there is cutting with varied load intensity in the section of the cut layer, which leads to change in cutting force, onset of vibrations, an increase in surface layer roughness, a decrease of size precision, and increased wear of a tool's cutting edge. This work proposes a method that consists in developing a CNC program output code that allows one to process complex forms of stepped shafts with only one machine setup. The authors developed and justified a mathematical model of a technological system for mechanical processing with consideration for the resolution of tool movement at the stages of transition processes to assess the dynamical stability of a system in the process of manufacturing stepped surfaces of parts of “solid of revolution” type.

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)

Advancing the Assessment of Dynamic Psychological Processes.

Science.gov (United States)

Wright, Aidan G C; Hopwood, Christopher J

2016-08-01

Most commonly used clinical assessment tools cannot fully capture the dynamic psychological processes often hypothesized as core mechanisms of psychopathology and psychotherapy. There is therefore a gap between our theories of problems and interventions for those problems and the tools we use to understand clients. The purpose of this special issue is to connect theory about clinical dynamics to practice by focusing on methods for collecting dynamic data, statistical models for analyzing dynamic data, and conceptual schemes for implementing dynamic data in applied settings. In this introductory article, we argue for the importance of assessing dynamic processes, highlight recent advances in assessment science that enable their measurement, review challenges in using these advances in applied practice, and adumbrate the articles in this issue.

Dynamic similarity in erosional processes

Science.gov (United States)

Scheidegger, A.E.

1963-01-01

A study is made of the dynamic similarity conditions obtaining in a variety of erosional processes. The pertinent equations for each type of process are written in dimensionless form; the similarity conditions can then easily be deduced. The processes treated are: raindrop action, slope evolution and river erosion. ?? 1963 Istituto Geofisico Italiano.

Approximate P-wave ray tracing and dynamic ray tracing in weakly orthorhombic media of varying symmetry orientation

KAUST Repository

Masmoudi, Nabil; Pšenčí k, Ivan

2014-01-01

We present an approximate, but efficient and sufficiently accurate P-wave ray tracing and dynamic ray tracing procedure for 3D inhomogeneous, weakly orthorhombic media with varying orientation of symmetry planes. In contrast to commonly used approaches, the orthorhombic symmetry is preserved at any point of the model. The model is described by six weak-anisotropy parameters and three Euler angles, which may vary arbitrarily, but smoothly, throughout the model. We use the procedure for the calculation of rays and corresponding two-point traveltimes in a VSP experiment in a part of the BP benchmark model generalized to orthorhombic symmetry.

Cortical processing of dynamic sound envelope transitions.

Science.gov (United States)

Zhou, Yi; Wang, Xiaoqin

2010-12-08

Slow envelope fluctuations in the range of 2-20 Hz provide important segmental cues for processing communication sounds. For a successful segmentation, a neural processor must capture envelope features associated with the rise and fall of signal energy, a process that is often challenged by the interference of background noise. This study investigated the neural representations of slowly varying envelopes in quiet and in background noise in the primary auditory cortex (A1) of awake marmoset monkeys. We characterized envelope features based on the local average and rate of change of sound level in envelope waveforms and identified envelope features to which neurons were selective by reverse correlation. Our results showed that envelope feature selectivity of A1 neurons was correlated with the degree of nonmonotonicity in their static rate-level functions. Nonmonotonic neurons exhibited greater feature selectivity than monotonic neurons in quiet and in background noise. The diverse envelope feature selectivity decreased spike-timing correlation among A1 neurons in response to the same envelope waveforms. As a result, the variability, but not the average, of the ensemble responses of A1 neurons represented more faithfully the dynamic transitions in low-frequency sound envelopes both in quiet and in background noise.

Information Processing Capacity of Dynamical Systems

Science.gov (United States)

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-07-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory.

Information Processing Capacity of Dynamical Systems

Science.gov (United States)

Dambre, Joni; Verstraeten, David; Schrauwen, Benjamin; Massar, Serge

2012-01-01

Many dynamical systems, both natural and artificial, are stimulated by time dependent external signals, somehow processing the information contained therein. We demonstrate how to quantify the different modes in which information can be processed by such systems and combine them to define the computational capacity of a dynamical system. This is bounded by the number of linearly independent state variables of the dynamical system, equaling it if the system obeys the fading memory condition. It can be interpreted as the total number of linearly independent functions of its stimuli the system can compute. Our theory combines concepts from machine learning (reservoir computing), system modeling, stochastic processes, and functional analysis. We illustrate our theory by numerical simulations for the logistic map, a recurrent neural network, and a two-dimensional reaction diffusion system, uncovering universal trade-offs between the non-linearity of the computation and the system's short-term memory. PMID:22816038

IMPACT OF SUPERNOVA DYNAMICS ON THE νp-PROCESS

International Nuclear Information System (INIS)

Arcones, A.; Fröhlich, C.; Martínez-Pinedo, G.

2012-01-01

We study the impact of the late-time dynamical evolution of ejecta from core-collapse supernovae on νp-process nucleosynthesis. Our results are based on hydrodynamical simulations of neutrino-driven wind ejecta. Motivated by recent two-dimensional wind simulations, we vary the dynamical evolution during the νp-process and show that final abundances strongly depend on the temperature evolution. When the expansion is very fast, there is not enough time for antineutrino absorption on protons to produce enough neutrons to overcome the β + -decay waiting points and no heavy elements beyond A = 64 are produced. The wind termination shock or reverse shock dramatically reduces the expansion speed of the ejecta. This extends the period during which matter remains at relatively high temperatures and is exposed to high neutrino fluxes, thus allowing for further (p, γ) and (n, p) reactions to occur and to synthesize elements beyond iron. We find that the νp-process starts to efficiently produce heavy elements only when the temperature drops below ∼3 GK. At higher temperatures, due to the low alpha separation energy of 60 Zn (S α = 2.7 MeV) the reaction 59 Cu(p, α) 56 Ni is faster than the reaction 59 Cu(p, γ) 60 Zn. This results in the closed NiCu cycle that we identify and discuss here for the first time. We also investigate the late phase of the νp-process when the temperatures become too low to maintain proton captures. Depending on the late neutron density, the evolution to stability is dominated by β + decays or by (n, γ) reactions. In the latter case, the matter flow can even reach the neutron-rich side of stability and the isotopic composition of a given element is then dominated by neutron-rich isotopes.

Event-Based $H_\\infty $ State Estimation for Time-Varying Stochastic Dynamical Networks With State- and Disturbance-Dependent Noises.

Science.gov (United States)

Sheng, Li; Wang, Zidong; Zou, Lei; Alsaadi, Fuad E

2017-10-01

In this paper, the event-based finite-horizon H ∞ state estimation problem is investigated for a class of discrete time-varying stochastic dynamical networks with state- and disturbance-dependent noises [also called (x,v) -dependent noises]. An event-triggered scheme is proposed to decrease the frequency of the data transmission between the sensors and the estimator, where the signal is transmitted only when certain conditions are satisfied. The purpose of the problem addressed is to design a time-varying state estimator in order to estimate the network states through available output measurements. By employing the completing-the-square technique and the stochastic analysis approach, sufficient conditions are established to ensure that the error dynamics of the state estimation satisfies a prescribed H ∞ performance constraint over a finite horizon. The desired estimator parameters can be designed via solving coupled backward recursive Riccati difference equations. Finally, a numerical example is exploited to demonstrate the effectiveness of the developed state estimation scheme.

A dynamic balanced scorecard for identification internal process factor

Directory of Open Access Journals (Sweden)

Javad sofiyabadi

2012-08-01

Full Text Available We present a dynamic balanced score card (BSC to investigate the strategic internal process management factors. The proposed dynamic BSC emphasizes on internal processes aspect, and using VIKOR and Shannon Entropy, determinants the internal processes, process management and improvement and all important factors are ranked. The current study first introduces dynamic BSC and examines effective factors on the process. The proposed model focuses on internal processes perspective of BSC and determines importance degree of each factor is used using VIKOR decision-making techniques.

Computer Modelling of Dynamic Processes

Directory of Open Access Journals (Sweden)

B. Rybakin

2000-10-01

Full Text Available Results of numerical modeling of dynamic problems are summed in the article up. These problems are characteristic for various areas of human activity, in particular for problem solving in ecology. The following problems are considered in the present work: computer modeling of dynamic effects on elastic-plastic bodies, calculation and determination of performances of gas streams in gas cleaning equipment, modeling of biogas formation processes.

Temporal Gillespie Algorithm: Fast Simulation of Contagion Processes on Time-Varying Networks.

Science.gov (United States)

Vestergaard, Christian L; Génois, Mathieu

2015-10-01

Stochastic simulations are one of the cornerstones of the analysis of dynamical processes on complex networks, and are often the only accessible way to explore their behavior. The development of fast algorithms is paramount to allow large-scale simulations. The Gillespie algorithm can be used for fast simulation of stochastic processes, and variants of it have been applied to simulate dynamical processes on static networks. However, its adaptation to temporal networks remains non-trivial. We here present a temporal Gillespie algorithm that solves this problem. Our method is applicable to general Poisson (constant-rate) processes on temporal networks, stochastically exact, and up to multiple orders of magnitude faster than traditional simulation schemes based on rejection sampling. We also show how it can be extended to simulate non-Markovian processes. The algorithm is easily applicable in practice, and as an illustration we detail how to simulate both Poissonian and non-Markovian models of epidemic spreading. Namely, we provide pseudocode and its implementation in C++ for simulating the paradigmatic Susceptible-Infected-Susceptible and Susceptible-Infected-Recovered models and a Susceptible-Infected-Recovered model with non-constant recovery rates. For empirical networks, the temporal Gillespie algorithm is here typically from 10 to 100 times faster than rejection sampling.

Dynamic process management for engineering environments

NARCIS (Netherlands)

Mentink, R.J.; van Houten, Frederikus J.A.M.; Kals, H.J.J.

2003-01-01

The research presented in this paper proposes a concept for dynamic process management as part of an integrated approach to engineering process support. The theory of information management is the starting point for the development of a process management system based on evolution of information

Dynamic IQC-Based Control of Uncertain LFT Systems With Time-Varying State Delay.

Science.gov (United States)

Yuan, Chengzhi; Wu, Fen

2016-12-01

This paper presents a new exact-memory delay control scheme for a class of uncertain systems with time-varying state delay under the integral quadratic constraint (IQC) framework. The uncertain system is described as a linear fractional transformation model including a state-delayed linear time-invariant (LTI) system and time-varying structured uncertainties. The proposed exact-memory delay controller consists of a linear state-feedback control law and an additional term that captures the delay behavior of the plant. We first explore the delay stability and the L 2 -gain performance using dynamic IQCs incorporated with quadratic Lyapunov functions. Then, the design of exact-memory controllers that guarantee desired L 2 -gain performance is examined. The resulting delay control synthesis conditions are formulated in terms of linear matrix inequalities, which are convex on all design variables including the scaling matrices associated with the IQC multipliers. The IQC-based exact-memory control scheme provides a novel approach for delay control designs via convex optimization, and advances existing control methods in two important ways: 1) better controlled performance and 2) simplified design procedure with less computational cost. The effectiveness and advantages of the proposed approach have been demonstrated through numerical studies.

Dynamic RSA: Examining parasympathetic regulatory dynamics via vector-autoregressive modeling of time-varying RSA and heart period.

Science.gov (United States)

Fisher, Aaron J; Reeves, Jonathan W; Chi, Cyrus

2016-07-01

Expanding on recently published methods, the current study presents an approach to estimating the dynamic, regulatory effect of the parasympathetic nervous system on heart period on a moment-to-moment basis. We estimated second-to-second variation in respiratory sinus arrhythmia (RSA) in order to estimate the contemporaneous and time-lagged relationships among RSA, interbeat interval (IBI), and respiration rate via vector autoregression. Moreover, we modeled these relationships at lags of 1 s to 10 s, in order to evaluate the optimal latency for estimating dynamic RSA effects. The IBI (t) on RSA (t-n) regression parameter was extracted from individual models as an operationalization of the regulatory effect of RSA on IBI-referred to as dynamic RSA (dRSA). Dynamic RSA positively correlated with standard averages of heart rate and negatively correlated with standard averages of RSA. We propose that dRSA reflects the active downregulation of heart period by the parasympathetic nervous system and thus represents a novel metric that provides incremental validity in the measurement of autonomic cardiac control-specifically, a method by which parasympathetic regulatory effects can be measured in process. © 2016 Society for Psychophysiological Research.

Spatiotemporal neural network dynamics for the processing of dynamic facial expressions

Science.gov (United States)

Sato, Wataru; Kochiyama, Takanori; Uono, Shota

2015-01-01

The dynamic facial expressions of emotion automatically elicit multifaceted psychological activities; however, the temporal profiles and dynamic interaction patterns of brain activities remain unknown. We investigated these issues using magnetoencephalography. Participants passively observed dynamic facial expressions of fear and happiness, or dynamic mosaics. Source-reconstruction analyses utilizing functional magnetic-resonance imaging data revealed higher activation in broad regions of the bilateral occipital and temporal cortices in response to dynamic facial expressions than in response to dynamic mosaics at 150–200 ms and some later time points. The right inferior frontal gyrus exhibited higher activity for dynamic faces versus mosaics at 300–350 ms. Dynamic causal-modeling analyses revealed that dynamic faces activated the dual visual routes and visual–motor route. Superior influences of feedforward and feedback connections were identified before and after 200 ms, respectively. These results indicate that hierarchical, bidirectional neural network dynamics within a few hundred milliseconds implement the processing of dynamic facial expressions. PMID:26206708

Spatiotemporal neural network dynamics for the processing of dynamic facial expressions.

Science.gov (United States)

Sato, Wataru; Kochiyama, Takanori; Uono, Shota

2015-07-24

The dynamic facial expressions of emotion automatically elicit multifaceted psychological activities; however, the temporal profiles and dynamic interaction patterns of brain activities remain unknown. We investigated these issues using magnetoencephalography. Participants passively observed dynamic facial expressions of fear and happiness, or dynamic mosaics. Source-reconstruction analyses utilizing functional magnetic-resonance imaging data revealed higher activation in broad regions of the bilateral occipital and temporal cortices in response to dynamic facial expressions than in response to dynamic mosaics at 150-200 ms and some later time points. The right inferior frontal gyrus exhibited higher activity for dynamic faces versus mosaics at 300-350 ms. Dynamic causal-modeling analyses revealed that dynamic faces activated the dual visual routes and visual-motor route. Superior influences of feedforward and feedback connections were identified before and after 200 ms, respectively. These results indicate that hierarchical, bidirectional neural network dynamics within a few hundred milliseconds implement the processing of dynamic facial expressions.

Computer processing of dynamic scintigraphic studies

International Nuclear Information System (INIS)

Ullmann, V.

1985-01-01

The methods are discussed of the computer processing of dynamic scintigraphic studies which were developed, studied or implemented by the authors within research task no. 30-02-03 in nuclear medicine within the five year plan 1981 to 85. This was mainly the method of computer processing radionuclide angiography, phase radioventriculography, regional lung ventilation, dynamic sequential scintigraphy of kidneys and radionuclide uroflowmetry. The problems are discussed of the automatic definition of fields of interest, the methodology of absolute volumes of the heart chamber in radionuclide cardiology, the design and uses are described of the multipurpose dynamic phantom of heart activity for radionuclide angiocardiography and ventriculography developed within the said research task. All methods are documented with many figures showing typical clinical (normal and pathological) and phantom measurements. (V.U.)

Toward understanding dynamic annealing processes in irradiated ceramics

Energy Technology Data Exchange (ETDEWEB)

Myers, Michael Thomas [Texas A & M Univ., College Station, TX (United States)

2013-05-01

High energy particle irradiation inevitably generates defects in solids. The ballistic formation and thermalization of the defect creation process occur rapidly, and are believed to be reasonably well understood. However, knowledge of the evolution of defects after damage cascade thermalization, referred to as dynamic annealing, is quite limited. Unraveling the mechanisms associated with dynamic annealing is crucial since such processes play an important role in the formation of stable postirradiation disorder in ion-beam-processing of semiconductors, and determines the “radiation tolerance” of many nuclear materials. The purpose of this dissertation is to further our understanding of the processes involved in dynamic annealing. In order to achieve this, two main tasks are undertaken.

The Intrinsic Dynamics of Psychological Process

NARCIS (Netherlands)

Vallacher, Robin R.; van Geert, Paul; Nowak, Andrzej

2015-01-01

Psychological processes unfold on various timescales in accord with internally generated patterns. The intrinsic dynamism of psychological process is difficult to investigate using traditional methods emphasizing cause–effect relations, however, and therefore is rarely incorporated into social

Generated dynamics of Markov and quantum processes

CERN Document Server

Janßen, Martin

2016-01-01

This book presents Markov and quantum processes as two sides of a coin called generated stochastic processes. It deals with quantum processes as reversible stochastic processes generated by one-step unitary operators, while Markov processes are irreversible stochastic processes generated by one-step stochastic operators. The characteristic feature of quantum processes are oscillations, interference, lots of stationary states in bounded systems and possible asymptotic stationary scattering states in open systems, while the characteristic feature of Markov processes are relaxations to a single stationary state. Quantum processes apply to systems where all variables, that control reversibility, are taken as relevant variables, while Markov processes emerge when some of those variables cannot be followed and are thus irrelevant for the dynamic description. Their absence renders the dynamic irreversible. A further aim is to demonstrate that almost any subdiscipline of theoretical physics can conceptually be put in...

Design of 2D time-varying vector fields.

Science.gov (United States)

Chen, Guoning; Kwatra, Vivek; Wei, Li-Yi; Hansen, Charles D; Zhang, Eugene

2012-10-01

Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects.

Information governance in dynamic networked business process management

NARCIS (Netherlands)

Rasouli, M.; Eshuis, H.; Grefen, P.W.P.J.; Trienekens, J.J.M.; Kusters, R.J.

2016-01-01

Competition in today’s globalized markets forces organizations to collaborate within dynamic business networks to provide mass-customized integrated solutions for customers. The collaboration within dynamic business networks necessitates forming dynamic networked business processes (DNBPs).

Molecular Mechanisms That Underlie the Dynamic Adaptation of Innate Monocyte Memory to Varying Stimulant Strength of TLR Ligands.

Science.gov (United States)

Yuan, Ruoxi; Geng, Shuo; Li, Liwu

2016-01-01

In adaptation to rising stimulant strength, innate monocytes can be dynamically programed to preferentially express either pro- or anti-inflammatory mediators. Such dynamic innate adaptation or programing may bear profound relevance in host health and disease. However, molecular mechanisms that govern innate adaptation to varying strength of stimulants are not well understood. Using lipopolysaccharide (LPS), the model stimulant of toll-like-receptor 4 (TLR4), we reported that the expressions of pro-inflammatory mediators are preferentially sustained in monocytes adapted by lower doses of LPS, and suppressed/tolerized in monocytes adapted by higher doses of LPS. Mechanistically, monocytes adapted by super-low dose LPS exhibited higher levels of transcription factor, interferon regulatory factor 5 (IRF5), and reduced levels of transcriptional modulator B lymphocyte-induced maturation protein-1 (Blimp-1). Intriguingly, the inflammatory monocyte adaptation by super-low dose LPS is dependent upon TRAM/TRIF but not MyD88. Similar to LPS, we also observed biphasic inflammatory adaptation and tolerance in monocytes challenged with varying dosages of TLR7 agonist. In sharp contrast, rising doses of TLR3 agonist preferentially caused inflammatory adaptation without inducing tolerance. At the molecular level, the differential regulation of IRF5 and Blimp-1 coincides with unique monocyte adaptation dynamics by TLR4/7 and TLR3 agonists. Our study provides novel clue toward the understanding of monocyte adaptation and memory toward distinct TLR ligands.

Molecular mechanisms that underlie the dynamic adaptation of innate monocyte memory to varying stimulant strength of TLR ligands

Directory of Open Access Journals (Sweden)

Ruoxi Yuan

2016-11-01

Full Text Available In adaptation to rising stimulant strength, innate monocytes can be dynamically programmed to preferentially express either pro- or anti-inflammatory mediators. Such dynamic innate adaptation or programming may bear profound relevance in host health and disease. However, molecular mechanisms that govern innate adaptation to varying strength of stimulants are not well understood. Using lipopolysaccharide (LPS, the model stimulant of Toll-Like-Receptor 4 (TLR4, we reported that the expressions of pro-inflammatory mediators are preferentially sustained in monocytes adapted by lower doses of LPS, and suppressed/tolerized in monocytes adapted by higher doses of LPS. Mechanistically, monocytes adapted by super-low dose LPS exhibited higher levels of transcription factor IRF5 and reduced levels of transcriptional modulator BLIMP-1. Intriguingly, the inflammatory monocyte adaptation by super-low dose LPS is dependent upon TRAM/TRIF but not MyD88. Similar to LPS, we also observed biphasic inflammatory adaptation and tolerance in monocytes challenged with varying dosages of TLR7 agonist. In sharp contrast, rising doses of TLR3 agonist preferentially caused inflammatory adaptation without inducing tolerance. At the molecular level, the differential regulation of IRF5 and Blimp-1 coincides with unique monocyte adaptation dynamics by TLR4/7 and TLR3 agonists. Our study provides novel clue toward the understanding of monocyte adaptation and memory toward distinct TLR ligands.

Dynamic analysis of a guided projectile during engraving process

Directory of Open Access Journals (Sweden)

Tao Xue

2014-06-01

Full Text Available The reliability of the electronic components inside a guided projectile is highly affected by the launch dynamics of guided projectile. The engraving process plays a crucial role on determining the ballistic performance and projectile stability. This paper analyzes the dynamic response of a guided projectile during the engraving process. By considering the projectile center of gravity moving during the engraving process, a dynamics model is established with the coupling of interior ballistic equations. The results detail the stress situation of a guided projectile band during its engraving process. Meanwhile, the axial dynamic response of projectile in the several milliseconds following the engraving process is also researched. To further explore how the different performance of the engraving band can affect the dynamics of guided projectile, this paper focuses on these two aspects: (a the effects caused by the different band geometry; and (b the effects caused by different band materials. The time domain and frequency domain responses show that the dynamics of the projectile are quite sensitive to the engraving band width. A material with a small modulus of elasticity is more stable than one with a high modulus of elasticity.

Dynamic modeling and experimental validation for direct contact membrane distillation (DCMD) process

KAUST Repository

Eleiwi, Fadi

2016-02-01

This work proposes a mathematical dynamic model for the direct contact membrane distillation (DCMD) process. The model is based on a 2D Advection–Diffusion Equation (ADE), which describes the heat and mass transfer mechanisms that take place inside the DCMD module. The model studies the behavior of the process in the time varying and the steady state phases, contributing to understanding the process performance, especially when it is driven by intermittent energy supply, such as the solar energy. The model is experimentally validated in the steady state phase, where the permeate flux is measured for different feed inlet temperatures and the maximum absolute error recorded is 2.78 °C. Moreover, experimental validation includes the time variation phase, where the feed inlet temperature ranges from 30 °C to 75 °C with 0.1 °C increment every 2min. The validation marks relative error to be less than 5%, which leads to a strong correlation between the model predictions and the experiments.

Dynamic modeling and experimental validation for direct contact membrane distillation (DCMD) process

KAUST Repository

Eleiwi, Fadi; Ghaffour, NorEddine; Alsaadi, Ahmad Salem; Francis, Lijo; Laleg-Kirati, Taous-Meriem

2016-01-01

This work proposes a mathematical dynamic model for the direct contact membrane distillation (DCMD) process. The model is based on a 2D Advection–Diffusion Equation (ADE), which describes the heat and mass transfer mechanisms that take place inside the DCMD module. The model studies the behavior of the process in the time varying and the steady state phases, contributing to understanding the process performance, especially when it is driven by intermittent energy supply, such as the solar energy. The model is experimentally validated in the steady state phase, where the permeate flux is measured for different feed inlet temperatures and the maximum absolute error recorded is 2.78 °C. Moreover, experimental validation includes the time variation phase, where the feed inlet temperature ranges from 30 °C to 75 °C with 0.1 °C increment every 2min. The validation marks relative error to be less than 5%, which leads to a strong correlation between the model predictions and the experiments.

Varying parameter models to accommodate dynamic promotion effects

NARCIS (Netherlands)

Foekens, E.W.; Leeflang, P.S.H.; Wittink, D.R.

1999-01-01

The purpose of this paper is to examine the dynamic effects of sales promotions. We create dynamic brand sales models (for weekly store-level scanner data) by relating store intercepts and a brand's own price elasticity to a measure of the cumulated previous price discounts - amount and time - for

Development of the Log-in Process and the Operation Process for the VHTR-SI Process Dynamic Simulation Code

International Nuclear Information System (INIS)

Chang, Jiwoon; Shin, Youngjoon; Kim, Jihwan; Lee, Kiyoung; Lee, Wonjae; Chang, Jonghwa; Youn, Cheung

2009-01-01

The VHTR-SI process is a hydrogen production technique by using Sulfur and Iodine. The SI process for a hydrogen production uses a high temperature (about 950 .deg. C) of the He gas which is a cooling material for an energy sources. The Korea Atomic Energy Research Institute Dynamic Simulation Code (KAERI DySCo) is an integration application software that simulates the dynamic behavior of the VHTR-SI process. A dynamic modeling is used to express and model the behavior of the software system over time. The dynamic modeling deals with the control flow of system, the interaction of objects and the order of actions in view of a time and transition by using a sequence diagram and a state transition diagram. In this paper, we present an user log-in process and an operation process for the KAERI DySCo by using a sequence diagram and a state transition diagram

Cooperative Multiagent System for Parking Availability Prediction Based on Time Varying Dynamic Markov Chains

Directory of Open Access Journals (Sweden)

Surafel Luleseged Tilahun

2017-01-01

Full Text Available Traffic congestion is one of the main issues in the study of transportation planning and management. It creates different problems including environmental pollution and health problem and incurs a cost which is increasing through years. One-third of this congestion is created by cars searching for parking places. Drivers may be aware that parking places are fully occupied but will drive around hoping that a parking place may become vacant. Opportunistic services, involving learning, predicting, and exploiting Internet of Things scenarios, are able to adapt to dynamic unforeseen situations and have the potential to ease parking search issues. Hence, in this paper, a cooperative dynamic prediction mechanism between multiple agents for parking space availability in the neighborhood, integrating foreseen and unforeseen events and adapting for long-term changes, is proposed. An agent in each parking place will use a dynamic and time varying Markov chain to predict the parking availability and these agents will communicate to produce the parking availability prediction in the whole neighborhood. Furthermore, a learning approach is proposed where the system can adapt to different changes in the parking demand including long-term changes. Simulation results, using synthesized data based on an actual parking lot data from a shopping mall in Geneva, show that the proposed model is promising based on the learning accuracy with service adaptation and performance in different cases.

Importance of neutral processes varies in time and space: Evidence from dryland stream ecosystems.

Directory of Open Access Journals (Sweden)

Xiaoli Dong

Full Text Available Many ecosystems experience strong temporal variability in environmental conditions; yet, a clear picture of how niche and neutral processes operate to determine community assembly in temporally variable systems remains elusive. In this study, we constructed neutral metacommunity models to assess the relative importance of neutral processes in a spatially and temporally variable ecosystem. We analyzed macroinvertebrate community data spanning multiple seasons and years from 20 sites in a Sonoran Desert river network in Arizona. The model goodness-of-fit was used to infer the importance of neutral processes. Averaging over eight stream flow conditions across three years, we found that neutral processes were more important in perennial streams than in non-perennial streams (intermittent and ephemeral streams. Averaging across perennial and non-perennial streams, we found that neutral processes were more important during very high flow and in low flow periods; whereas, at very low flows, the relative importance of neutral processes varied greatly. These findings were robust to the choice of model parameter values. Our study suggested that the net effect of disturbance on the relative importance of niche and neutral processes in community assembly varies non-monotonically with the severity of disturbance. In contrast to the prevailing view that disturbance promotes niche processes, we found that neutral processes could become more important when the severity of disturbance is beyond a certain threshold such that all organisms are adversely affected regardless of their biological traits and strategies.

MECHANICS OF DYNAMIC POWDER COMPACTION PROCESS

OpenAIRE

Nurettin YAVUZ

1996-01-01

In recent years, interest in dynamic compaction methods of metal powders has increased due to the need to improve compaction properties and to increase production rates of compacts. In this paper, review of dynamic and explosive compaction of metal powders are given. An attempt is made to get a better understanding of the compaction process with the mechanicis of powder compaction.

Analysis of Uncertainty in Dynamic Processes Development of Banks Functioning

Directory of Open Access Journals (Sweden)

Aleksei V. Korovyakovskii

2013-01-01

Full Text Available The paper offers the approach to measure of uncertainty estimation in dynamic processes of banks functioning, using statistic data of different banking operations indicators. To calculate measure of uncertainty in dynamic processes of banks functioning the phase images of relevant sets of statistic data are considered. Besides, it is shown that the form of phase image of the studied sets of statistic data can act as a basis of measure of uncertainty estimation in dynamic processes of banks functioning. The set of analytical characteristics are offered to formalize the form of phase image definition of the studied sets of statistic data. It is shown that the offered analytical characteristics consider inequality of changes in values of the studied sets of statistic data, which is one of the ways of uncertainty display in dynamic processes development. The invariant estimates of measure of uncertainty in dynamic processes of banks functioning, considering significant changes in absolute values of the same indicators for different banks were obtained. The examples of calculation of measure of uncertainty in dynamic processes of concrete banks functioning were cited.

Design of 2D Time-Varying Vector Fields

KAUST Repository

Chen, Guoning

2012-10-01

Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects. © 1995-2012 IEEE.

Design of 2D Time-Varying Vector Fields

KAUST Repository

Chen, Guoning; Kwatra, Vivek; Wei, Li-Yi; Hansen, Charles D.; Zhang, Eugene

2012-01-01

Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects. © 1995-2012 IEEE.

Multi-scale Dynamical Processes in Space and Astrophysical Plasmas

CERN Document Server

Vörös, Zoltán; IAFA 2011 - International Astrophysics Forum 2011 : Frontiers in Space Environment Research

2012-01-01

Magnetized plasmas in the universe exhibit complex dynamical behavior over a huge range of scales. The fundamental mechanisms of energy transport, redistribution and conversion occur at multiple scales. The driving mechanisms often include energy accumulation, free-energy-excited relaxation processes, dissipation and self-organization. The plasma processes associated with energy conversion, transport and self-organization, such as magnetic reconnection, instabilities, linear and nonlinear waves, wave-particle interactions, dynamo processes, turbulence, heating, diffusion and convection represent fundamental physical effects. They demonstrate similar dynamical behavior in near-Earth space, on the Sun, in the heliosphere and in astrophysical environments. 'Multi-scale Dynamical Processes in Space and Astrophysical Plasmas' presents the proceedings of the International Astrophysics Forum Alpbach 2011. The contributions discuss the latest advances in the exploration of dynamical behavior in space plasmas environm...

Interestingness-Driven Diffusion Process Summarization in Dynamic Networks

DEFF Research Database (Denmark)

Qu, Qiang; Liu, Siyuan; Jensen, Christian S.

2014-01-01

The widespread use of social networks enables the rapid diffusion of information, e.g., news, among users in very large communities. It is a substantial challenge to be able to observe and understand such diffusion processes, which may be modeled as networks that are both large and dynamic. A key...... tool in this regard is data summarization. However, few existing studies aim to summarize graphs/networks for dynamics. Dynamic networks raise new challenges not found in static settings, including time sensitivity and the needs for online interestingness evaluation and summary traceability, which...... render existing techniques inapplicable. We study the topic of dynamic network summarization: how to summarize dynamic networks with millions of nodes by only capturing the few most interesting nodes or edges over time, and we address the problem by finding interestingness-driven diffusion processes...

Reduction of water consumption in the dynamic acid leaching process of uranium

International Nuclear Information System (INIS)

Chocron, M.; Arias, M.J.; Avato, A.M.; Díaz, V.A.

2013-01-01

In 2006 the Argentine state announced a plan to reactivate the nuclear sector. As a result of this decision, the National Atomic Energy Commission (CNEA) resumed its research in uranium mining for Argentine deposits. The first step was the study of the leaching process, mainly the dynamic leaching. In this work the influence of the reduction of the water content in the dynamic leaching process in acid medium, at laboratory scale and under batch operating conditions, on the main operating parameters (concentration of the leaching reagent, the oxidizing reagent and The reaction temperature). The percentages of pulp solids studied in the dynamic leaching were 53% and 66% w / w. For the tests uranium-molybdenum ores of the sandstone type were used. Two different working schemes were used to study the different operating parameters. In the tests carried out with 53% of solid in pulp, the parameters were studied individually (varying one parameter at a time), while working with a pulp of 66% solids, the study of the parameters was performed by a Factorial design of two levels of three variables, which in addition to studying the dependence of the different parameters allowed to analyze how they influence each other. During the leaching tests with 66% solids content in pulp, changes in the geometric and dynamic conditions of the system were necessary because of the poor mixing observed when using the same agitation conditions used in the leaching tests with 53% solids in pulp. When comparing the tests for both solids content conditions (53% and 66% w / w), similar extraction yields were observed for both uranium and molybdenum (more than 90% for uranium and more than 80% for The molybdenum). As a final result, the process water consumption (380 liters of water per ton of ore) is reduced by more than 50% by working with pulps of 66% w / w of solids, obtaining acceptable extraction yields and, as an additional, reducing The consumption of the leaching reagent. (author)

Testing for time-varying loadings in dynamic factor models

DEFF Research Database (Denmark)

Mikkelsen, Jakob Guldbæk

Abstract: In this paper we develop a test for time-varying factor loadings in factor models. The test is simple to compute and is constructed from estimated factors and residuals using the principal components estimator. The hypothesis is tested by regressing the squared residuals on the squared...... there is evidence of time-varying loadings on the risk factors underlying portfolio returns for around 80% of the portfolios....

Optimum Control for Nonlinear Dynamic Radial Deformation of Turbine Casing with Time-Varying LSSVM

Directory of Open Access Journals (Sweden)

Cheng-Wei Fei

2015-01-01

Full Text Available With the development of the high performance and high reliability of aeroengine, the blade-tip radial running clearance (BTRRC of high pressure turbine seriously influences the reliability and performance of aeroengine, wherein the radial deformation control of turbine casing has to be concerned in BTRRC design. To improve BTRRC design, the optimum control-based probabilistic optimization of turbine casing radial deformation was implemented using time-varying least square support vector machine (T-LSSVM by considering nonlinear material properties and dynamic thermal load. First the T-LSSVM method was proposed and its mathematical model was established. And then the nonlinear dynamic optimal control model of casing radial deformation was constructed with T-LSSVM. Thirdly, through the numerical experiments, the T-LSSVM method is demonstrated to be a promising approach in reducing additional design samples and improving computational efficiency with acceptable computational precision. Through the optimum control-based probabilistic optimization for nonlinear dynamic radial turbine casing deformation, the optimum radial deformation is 7.865 × 10−4 m with acceptable reliability degree 0.995 6, which is reduced by 7.86 × 10−5 m relative to that before optimization. These results validate the effectiveness and feasibility of the proposed T-LSSVM method, which provides a useful insight into casing radial deformation, BTRRC control, and the development of gas turbine with high performance and high reliability.

Biomolecular Modeling in a Process Dynamics and Control Course

Science.gov (United States)

Gray, Jeffrey J.

2006-01-01

I present modifications to the traditional course entitled, "Process dynamics and control," which I renamed "Modeling, dynamics, and control of chemical and biological processes." Additions include the central dogma of biology, pharmacokinetic systems, population balances, control of gene transcription, and large­-scale…

Method and apparatus of prefetching streams of varying prefetch depth

Science.gov (United States)

Gara, Alan [Mount Kisco, NY; Ohmacht, Martin [Yorktown Heights, NY; Salapura, Valentina [Chappaqua, NY; Sugavanam, Krishnan [Mahopac, NY; Hoenicke, Dirk [Seebruck-Seeon, DE

2012-01-24

Method and apparatus of prefetching streams of varying prefetch depth dynamically changes the depth of prefetching so that the number of multiple streams as well as the hit rate of a single stream are optimized. The method and apparatus in one aspect monitor a plurality of load requests from a processing unit for data in a prefetch buffer, determine an access pattern associated with the plurality of load requests and adjust a prefetch depth according to the access pattern.

Organizational agility key factors for dynamic business process management

OpenAIRE

Triaa , Wafa; Gzara , Lilia; Verjus , Hervé

2016-01-01

International audience; For several years, Business Process Management (BPM) is recognized as a holistic management approach that promotes business effectiveness and efficiency. Increasingly, corporates find themselves, operating in business environments filled with unpredictable, complex and continuous change. Driven by these dynamic competitive conditions, they look for a dynamic management of their business processes to maintain their processes performance. To be competitive, companies hav...

The neural basis of emotions varies over time: different regions go with onset- and offset-bound processes underlying emotion intensity.

Science.gov (United States)

Résibois, Maxime; Verduyn, Philippe; Delaveau, Pauline; Rotgé, Jean-Yves; Kuppens, Peter; Van Mechelen, Iven; Fossati, Philippe

2017-08-01

According to theories of emotion dynamics, emotions unfold across two phases in which different types of processes come to the fore: emotion onset and emotion offset. Differences in onset-bound processes are reflected by the degree of explosiveness or steepness of the response at onset, and differences in offset-bound processes by the degree of accumulation or intensification of the subsequent response. Whether onset- and offset-bound processes have distinctive neural correlates and, hence, whether the neural basis of emotions varies over time, still remains unknown. In the present fMRI study, we address this question using a recently developed paradigm that allows to disentangle explosiveness and accumulation. Thirty-one participants were exposed to neutral and negative social feedback, and asked to reflect on its contents. Emotional intensity while reading and thinking about the feedback was measured with an intensity profile tracking approach. Using non-negative matrix factorization, the resulting profile data were decomposed in explosiveness and accumulation components, which were subsequently entered as continuous regressors of the BOLD response. It was found that the neural basis of emotion intensity shifts as emotions unfold over time with emotion explosiveness and accumulation having distinctive neural correlates. © The Author (2017). Published by Oxford University Press.

Bayesian dynamic mediation analysis.

Science.gov (United States)

Huang, Jing; Yuan, Ying

2017-12-01

Most existing methods for mediation analysis assume that mediation is a stationary, time-invariant process, which overlooks the inherently dynamic nature of many human psychological processes and behavioral activities. In this article, we consider mediation as a dynamic process that continuously changes over time. We propose Bayesian multilevel time-varying coefficient models to describe and estimate such dynamic mediation effects. By taking the nonparametric penalized spline approach, the proposed method is flexible and able to accommodate any shape of the relationship between time and mediation effects. Simulation studies show that the proposed method works well and faithfully reflects the true nature of the mediation process. By modeling mediation effect nonparametrically as a continuous function of time, our method provides a valuable tool to help researchers obtain a more complete understanding of the dynamic nature of the mediation process underlying psychological and behavioral phenomena. We also briefly discuss an alternative approach of using dynamic autoregressive mediation model to estimate the dynamic mediation effect. The computer code is provided to implement the proposed Bayesian dynamic mediation analysis. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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...

Hybrid Percolation Transition in Cluster Merging Processes: Continuously Varying Exponents

Science.gov (United States)

Cho, Y. S.; Lee, J. S.; Herrmann, H. J.; Kahng, B.

2016-01-01

Consider growing a network, in which every new connection is made between two disconnected nodes. At least one node is chosen randomly from a subset consisting of g fraction of the entire population in the smallest clusters. Here we show that this simple strategy for improving connection exhibits a more unusual phase transition, namely a hybrid percolation transition exhibiting the properties of both first-order and second-order phase transitions. The cluster size distribution of finite clusters at a transition point exhibits power-law behavior with a continuously varying exponent τ in the range 2 power-law behavior of the avalanche size distribution arising in models with link-deleting processes in interdependent networks.

Nonlinear dynamic range transformation in visual communication channels.

Science.gov (United States)

Alter-Gartenberg, R

1996-01-01

The article evaluates nonlinear dynamic range transformation in the context of the end-to-end continuous-input/discrete processing/continuous-display imaging process. Dynamic range transformation is required when we have the following: (i) the wide dynamic range encountered in nature is compressed into the relatively narrow dynamic range of the display, particularly for spatially varying irradiance (e.g., shadow); (ii) coarse quantization is expanded to the wider dynamic range of the display; and (iii) nonlinear tone scale transformation compensates for the correction in the camera amplifier.

The socially-dynamic entrepreneurial process

DEFF Research Database (Denmark)

Bjerregaard, Toke; Lauring, Jakob

2012-01-01

Large shares of the entrepreneurship research are informed by two central lines of thought. One focuses on the role of formal and informal social networks for mobilising resources and obtaining information about new markets and opportunities. The other conceives of individual personality traits o....... The article thus proposes an approach integrating the social and subjective levels of analysis as part of the same socially-dynamic entrepreneurial process....... or cognitive schemes as the independent variable behind entrepreneurial activity. Elaborating on the socially-dynamic perspectives of anthropological theories, this article presents a coherent theoretical framework for entrepreneurship research embracing the social dimensions as well as individual factors...

Safety, Liveness and Run-time Refinement for Modular Process-Aware Information Systems with Dynamic Sub Processes

DEFF Research Database (Denmark)

Debois, Søren; Hildebrandt, Thomas; Slaats, Tijs

2015-01-01

and verification of flexible, run-time adaptable process-aware information systems, moved into practice via the Dynamic Condition Response (DCR) Graphs notation co-developed with our industrial partner. Our key contributions are: (1) A formal theory of dynamic sub-process instantiation for declarative, event......We study modularity, run-time adaptation and refinement under safety and liveness constraints in event-based process models with dynamic sub-process instantiation. The study is part of a larger programme to provide semantically well-founded technologies for modelling, implementation......-based processes under safety and liveness constraints, given as the DCR* process language, equipped with a compositional operational semantics and conservatively extending the DCR Graphs notation; (2) an expressiveness analysis revealing that the DCR* process language is Turing-complete, while the fragment cor...

[Dynamics of change of ureaplasma laboratory strain titers and quantity of their DNA in transport medium at varying temperature].

Science.gov (United States)

Gamova, N A; Ivanova, T A

2013-01-01

Study of preservation dynamics of ureaplasma laboratory strain live cultures and their DNA in transport medium at varying temperature. The study was carried out in laboratory strains Ureaplasma urealyticum serotype 8 and Ureaplasma parvum serotype 1. The quantity of live ureaplasmas was determined by method of tenfold dilutions in liquid medium. The growth of ureaplasmas was registered by changes in the color of the cultivation medium due to its alkalization by metabolism products and expressed in CCU/ml. DNA quantity in samples was determined by real time PCR performed by using Florocenosis-micoplasmas-FL test system produced by ILS. Live ureaplasmas wer shown to be preserved in transport medium at 4 degrees C for 12 - 29 days, at 18 - 22 degrees C--for 9 - 20 days and at 37 degrees C--for only 2 days. In samples incubated at 37 degrees C the quantity of live ureaplasmas increased and then sharply decreased to 0, at lower temperature titers of the cells decreased smoothly. The quantity of ureaplasma DNA in the process of their incubation did not change significantly. Fundamental differences in the duration of survival of U. urealyticum strain and U. parvum strain in transport medium at varying temperature were not detected. Based on the studies performed a practical conclusion can be drawn that in cases of emergency when clinical material transportation is necessary its storage in transport medium for several days is acceptable.

Continuous time modelling with individually varying time intervals for oscillating and non-oscillating processes.

Science.gov (United States)

Voelkle, Manuel C; Oud, Johan H L

2013-02-01

When designing longitudinal studies, researchers often aim at equal intervals. In practice, however, this goal is hardly ever met, with different time intervals between assessment waves and different time intervals between individuals being more the rule than the exception. One of the reasons for the introduction of continuous time models by means of structural equation modelling has been to deal with irregularly spaced assessment waves (e.g., Oud & Delsing, 2010). In the present paper we extend the approach to individually varying time intervals for oscillating and non-oscillating processes. In addition, we show not only that equal intervals are unnecessary but also that it can be advantageous to use unequal sampling intervals, in particular when the sampling rate is low. Two examples are provided to support our arguments. In the first example we compare a continuous time model of a bivariate coupled process with varying time intervals to a standard discrete time model to illustrate the importance of accounting for the exact time intervals. In the second example the effect of different sampling intervals on estimating a damped linear oscillator is investigated by means of a Monte Carlo simulation. We conclude that it is important to account for individually varying time intervals, and encourage researchers to conceive of longitudinal studies with different time intervals within and between individuals as an opportunity rather than a problem. © 2012 The British Psychological Society.

Musashi dynamic image processing system

International Nuclear Information System (INIS)

Murata, Yutaka; Mochiki, Koh-ichi; Taguchi, Akira

1992-01-01

In order to produce transmitted neutron dynamic images using neutron radiography, a real time system called Musashi dynamic image processing system (MDIPS) was developed to collect, process, display and record image data. The block diagram of the MDIPS is shown. The system consists of a highly sensitive, high resolution TV camera driven by a custom-made scanner, a TV camera deflection controller for optimal scanning, which adjusts to the luminous intensity and the moving speed of an object, a real-time corrector to perform the real time correction of dark current, shading distortion and field intensity fluctuation, a real time filter for increasing the image signal to noise ratio, a video recording unit and a pseudocolor monitor to realize recording in commercially available products and monitoring by means of the CRTs in standard TV scanning, respectively. The TV camera and the TV camera deflection controller utilized for producing still images can be applied to this case. The block diagram of the real-time corrector is shown. Its performance is explained. Linear filters and ranked order filters were developed. (K.I.)

Linking Polymer Dynamics to Melt Processing

Indian Academy of Sciences (India)

Ashish Lele

Linking Polymer Dynamics to Melt Processing. Ashish Lele. NaUonal Chemical Laboratory, Pune ak.lele@ncl.res.in www.cfpegroup.net. Mid-‐Year MeeUng July 2-‐3, 2010. Indian Academy of Sciences, Bangalore ...

Dynamic strain analysis of structures employing digital signal processing, storage and display

Energy Technology Data Exchange (ETDEWEB)

Patwardhan, P K; Misra, V M; Kumar, Surendra

1975-01-01

A multi-channel digital technique has been adopted for analysing wave patterns of stresses and strains in structures, particularly under dynamic conditions. This technique provides adequate signal to noise discrimination and high sensitivity for very small (few milli-volts) and slow varying signals (few Hz to 100 Hz.), and A-D conversion accompined by live display during the course of data gathering and computer compatible output. This system also provides fast response because of inherent 50 MHz digitising speed and a large dynamic range of 1024 discrete signal steps. The signals can be suitably fed to the A-D converter (50 MHz) or can be analysed employing frequency modulation techniques and time mode operation of the analyser. The data can be gathered in the field on cassette tapes and replayed in the laboratory for detailed analysis. This technique would provide a versatile system for dynamic analysis of structures under varying conditions. e.g. structures in nuclear power systems, such as testing of end fittings, calandria, vibration testing and measurements exploying pressure transducers.

Dynamic strain analysis of structures employing digital signal processing, storage and display

International Nuclear Information System (INIS)

Patwardhan, P.K.; Misra, V.M.; Kumar, Surendra

1975-01-01

A multi-channel digital technique has been adopted for analysing wave patterns of stresses and strains in structures, particularly under dynamic conditions. This technique provides adequate signal to noise discrimination and high sensitivity for very small (few milli-volts) and slow varying signals (few Hz to 100 Hz.), A-D conversion accompined by live display during the course of data gathering and computer compatible output. This system also provides fast response because of inherent 50 MHz digitising speed and a large dynamic range of 1024 discrete signal steps. The signals can be suitably fed to the A-D converter (50 MHz) or can be analysed employing frequency modulation techniques and time mode operation of the analyser. The data can be gathered in the field on cassette tapes and replayed in the laboratory for detailed analysis. This technique would provide a versatile system for dynamic analysis of structures under varying conditions. e.g. structures in nuclear power systems, such as testing of end fittings, calandria, vibration testing and measurements exploying pressure transducers. (author)

Dynamic Disturbance Processes Create Dynamic Lek Site Selection in a Prairie Grouse.

Directory of Open Access Journals (Sweden)

Torre J Hovick

Full Text Available It is well understood that landscape processes can affect habitat selection patterns, movements, and species persistence. These selection patterns may be altered or even eliminated as a result of changes in disturbance regimes and a concomitant management focus on uniform, moderate disturbance across landscapes. To assess how restored landscape heterogeneity influences habitat selection patterns, we examined 21 years (1991, 1993-2012 of Greater Prairie-Chicken (Tympanuchus cupido lek location data in tallgrass prairie with restored fire and grazing processes. Our study took place at The Nature Conservancy's Tallgrass Prairie Preserve located at the southern extent of Flint Hills in northeastern Oklahoma. We specifically addressed stability of lek locations in the context of the fire-grazing interaction, and the environmental factors influencing lek locations. We found that lek locations were dynamic in a landscape with interacting fire and grazing. While previous conservation efforts have treated leks as stable with high site fidelity in static landscapes, a majority of lek locations in our study (i.e., 65% moved by nearly one kilometer on an annual basis in this dynamic setting. Lek sites were in elevated areas with low tree cover and low road density. Additionally, lek site selection was influenced by an interaction of fire and patch edge, indicating that in recently burned patches, leks were located near patch edges. These results suggest that dynamic and interactive processes such as fire and grazing that restore heterogeneity to grasslands do influence habitat selection patterns in prairie grouse, a phenomenon that is likely to apply throughout the Greater Prairie-Chicken's distribution when dynamic processes are restored. As conservation moves toward restoring dynamic historic disturbance patterns, it will be important that siting and planning of anthropogenic structures (e.g., wind energy, oil and gas and management plans not view lek

Evolving chemometric models for predicting dynamic process parameters in viscose production

Energy Technology Data Exchange (ETDEWEB)

Cernuda, Carlos [Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz (Austria); Lughofer, Edwin, E-mail: edwin.lughofer@jku.at [Department of Knowledge-Based Mathematical Systems, Johannes Kepler University Linz (Austria); Suppan, Lisbeth [Kompetenzzentrum Holz GmbH, St. Peter-Str. 25, 4021 Linz (Austria); Roeder, Thomas; Schmuck, Roman [Lenzing AG, 4860 Lenzing (Austria); Hintenaus, Peter [Software Research Center, Paris Lodron University Salzburg (Austria); Maerzinger, Wolfgang [i-RED Infrarot Systeme GmbH, Linz (Austria); Kasberger, Juergen [Recendt GmbH, Linz (Austria)

2012-05-06

Highlights: Black-Right-Pointing-Pointer Quality assurance of process parameters in viscose production. Black-Right-Pointing-Pointer Automatic prediction of spin-bath concentrations based on FTNIR spectra. Black-Right-Pointing-Pointer Evolving chemometric models for efficiently handling changing system dynamics over time (no time-intensive re-calibration needed). Black-Right-Pointing-Pointer Significant reduction of huge errors produced by statistical state-of-the-art calibration methods. Black-Right-Pointing-Pointer Sufficient flexibility achieved by gradual forgetting mechanisms. - Abstract: In viscose production, it is important to monitor three process parameters in order to assure a high quality of the final product: the concentrations of H{sub 2}SO{sub 4}, Na{sub 2}SO{sub 4} and Z{sub n}SO{sub 4}. During on-line production these process parameters usually show a quite high dynamics depending on the fiber type that is produced. Thus, conventional chemometric models, which are trained based on collected calibration spectra from Fourier transform near infrared (FT-NIR) measurements and kept fixed during the whole life-time of the on-line process, show a quite imprecise and unreliable behavior when predicting the concentrations of new on-line data. In this paper, we are demonstrating evolving chemometric models which are able to adapt automatically to varying process dynamics by updating their inner structures and parameters in a single-pass incremental manner. These models exploit the Takagi-Sugeno fuzzy model architecture, being able to model flexibly different degrees of non-linearities implicitly contained in the mapping between near infrared spectra (NIR) and reference values. Updating the inner structures is achieved by moving the position of already existing local regions and by evolving (increasing non-linearity) or merging (decreasing non-linearity) new local linear predictors on demand, which are guided by distance-based and similarity criteria. Gradual

DYNSIR; A dynamic simulator for the chemical process

International Nuclear Information System (INIS)

Park, Hyun Soo; Yoo, Jae Hyung; Byeon, Kee Hoh; Park, Jeong Hwa; Park, Seong Won

1990-03-01

A program code for dynamic simulation of arbitrary chemical process, called DYNSIR, is developed. The code can simulate rather arbitrary arrangements of individual chemical processing units whose models are described by ordinary differential equations. The code structure to handle input/output, memory and data management, numerical interactive or predetermined changes in parameter values during the simulation. Individual model is easy to maintain since the modular approach is used. The integration routine is highly effective because of the development of algorithm for modular integration method using the cubic spline. DYNSIR's data structures are not the index but the pointer structure. This pointer structure allows the dynamic memory allocation for the memory management. The dynamic memory allocation methods is to minimize the amount of memories and to overcome the limitation of the number of variables to be used. Finally, it includes various functions, such as the input preprocessor, the effective error processing, and plotting and reporting routines. (author)

Scaling properties in time-varying networks with memory

Science.gov (United States)

Kim, Hyewon; Ha, Meesoon; Jeong, Hawoong

2015-12-01

The formation of network structure is mainly influenced by an individual node's activity and its memory, where activity can usually be interpreted as the individual inherent property and memory can be represented by the interaction strength between nodes. In our study, we define the activity through the appearance pattern in the time-aggregated network representation, and quantify the memory through the contact pattern of empirical temporal networks. To address the role of activity and memory in epidemics on time-varying networks, we propose temporal-pattern coarsening of activity-driven growing networks with memory. In particular, we focus on the relation between time-scale coarsening and spreading dynamics in the context of dynamic scaling and finite-size scaling. Finally, we discuss the universality issue of spreading dynamics on time-varying networks for various memory-causality tests.

Stochastic dynamics of penetrable rods in one dimension: Entangled dynamics and transport properties

Energy Technology Data Exchange (ETDEWEB)

Craven, Galen T.; Popov, Alexander V.; Hernandez, Rigoberto, E-mail: hernandez@chemistry.gatech.edu [Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332-0400 (United States)

2015-04-21

The dynamical properties of a system of soft rods governed by stochastic hard collisions (SHCs) have been determined over a varying range of softness using molecular dynamics simulations in one dimension and analytic theory. The SHC model allows for interpenetration of the system’s constituent particles in the simulations, generating overlapping clustering behavior analogous to the spatial structures observed in systems governed by deterministic bounded potentials. Through variation of an assigned softness parameter δ, the limiting ranges of intermolecular softness are bridged, connecting the limiting ensemble behavior from hard to ideal (completely soft). Various dynamical and structural observables are measured from simulation and compared to developed theoretical values. The spatial properties are found to be well predicted by theories developed for the deterministic penetrable-sphere model with a transformation from energetic to probabilistic arguments. While the overlapping spatial structures are complex, the dynamical properties can be adequately approximated through a theory built on impulsive interactions with Enskog corrections. Our theory suggests that as the softness of interaction is varied toward the ideal limit, correlated collision processes are less important to the energy transfer mechanism, and Markovian processes dominate the evolution of the configuration space ensemble. For interaction softness close to hard limit, collision processes are highly correlated and overlapping spatial configurations give rise to entanglement of single-particle trajectories.

Flat Milling Process Simulation Taking into Consideration a Dependence of Dynamic Characteristics of the Machine

Directory of Open Access Journals (Sweden)

D. A. Zavarzin

2016-01-01

Full Text Available The milling process inherently is on/off, and therefore inevitably there is vibration excitation in the Machine/Fixture/Tool/Part (MFTP system, which results in a different quality of the treated surface, depending on the machining conditions. The objective is to identify effective operation conditions to cut a part on the 3-way easy class machines when there is no unwanted regenerative self-oscillation, leading to a significant deterioration in the quality of the surface machined. The paper describes vibrations arising during a milling process and their effect on the surface shape and the working tool. To solve this problem we apply a numerical simulation method of cutting dynamics, which consist of 4 modules. The main module is an algorithm of the geometric simulation. The second module is a phenomenological model of the cutting forces. Two remaining modules are responsible for dynamics simulation of the part machined and the cutting tool under time-varying cutting forces. The calculated values are transferred back to the geometric modelling algorithm at each step in time. Thus, the model is closed and allows us to take into account an effect of delay in a dynamic system. A finite element machine model to perform calculation in 3DCUT software has been a selected and compiled. The paper presents geometrical mapping of the machining process and natural frequencies and shapes found for the finite element model. Conducting multivariate calculations allowed us to analyse the dependences of a dynamic behaviour of the system on changing spindle speed. The multivariate modelling results are presented as the Poincare maps for a moving free end of the tool. These Poincare maps allow us to select the operation conditions domains coming both with forced vibration and with self-excited oscillations. On the Poincaré map for two operation conditions of different domains there are graphics of the cutting forces, a thickness of the cutting layer, tool

Assessing the viability of successful reconstruction of the dynamics of dark energy using varying fundamental couplings

Energy Technology Data Exchange (ETDEWEB)

Avelino, P.P., E-mail: ppavelin@fc.up.pt [Centro de Astrofisica da Universidade do Porto, Rua das Estrelas, 4150-762 Porto (Portugal); Departamento de Fisica e Astronomia, Faculdade de Ciencias, Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto (Portugal); Losano, L., E-mail: losano@fisica.ufpb.br [Departamento de Fisica, Universidade Federal da Paraiba, 58051-970 Joao Pessoa, Paraiba (Brazil); Centro de Fisica do Porto, Rua do Campo Alegre 687, 4169-007 Porto (Portugal); Departamento de Fisica e Astronomia, Faculdade de Ciencias, Universidade do Porto, Rua do Campo Alegre 687, 4169-007 Porto (Portugal); Menezes, R., E-mail: rmenezes@dce.ufpb.br [Departamento de Ciencias Exatas, Universidade Federal da Paraiba, 58297-000 Rio Tinto, PB (Brazil); Departamento de Fisica, Universidade Federal de Campina Grande, 58109-970 Campina Grande, Paraiba (Brazil); Oliveira, J.C.R.E., E-mail: jespain@fe.up.pt [Centro de Fisica do Porto, Rua do Campo Alegre 687, 4169-007 Porto (Portugal); Departamento de Engenharia Fisica da Faculdade de Engenharia da Universidade do Porto, Rua Dr. Roberto Frias, s/n, 4200-465 Porto (Portugal)

2012-10-31

We assess the viability of successful reconstruction of the evolution of the dark energy equation of state using varying fundamental couplings, such as the fine structure constant or the proton-to-electron mass ratio. We show that the same evolution of the dark energy equation of state parameter with cosmic time may be associated with arbitrary variations of the fundamental couplings. Various examples of models with the same (different) background evolution and different (the same) time variation of fundamental couplings are studied in the Letter. Although we demonstrate that, for a broad family of models, it is possible to redefine the scalar field in such a way that its dynamics is that of a standard quintessence scalar field, in general such redefinition leads to the breakdown of the linear relation between the scalar field and the variation of fundamental couplings. This implies that the assumption of a linear coupling is not sufficient to guarantee a successful reconstruction of the dark energy dynamics and consequently additional model dependent assumptions about the scalar field responsible for the dark energy need to be made.

Process dynamics, advantage and difficulties of investigations

International Nuclear Information System (INIS)

Oude-Hengel, H.H.; Geigle, F.W.; Drucks, G.

1974-01-01

Process models, amongst other things, are designed to inform about stressability of power plants. This paper introduces some of the most important models and assesses them. Mathematical results concerning a turbine trip incident are made clear. Finally some of the problems are dealt with which occur while investigating process dynamics. (orig./RW) [de

Psychosis and the dynamics of the psychotherapy process

DEFF Research Database (Denmark)

Rosenbaum, Bent; Harder, Susanne

2007-01-01

The role of psychotherapy in the treatment of psychoses remains controversial but there is improving acceptance that an understanding of the dynamics of the psychological processes involved in treatment and in the disorder itself may be important. Psychosis is understood as a detachment of the 's......The role of psychotherapy in the treatment of psychoses remains controversial but there is improving acceptance that an understanding of the dynamics of the psychological processes involved in treatment and in the disorder itself may be important. Psychosis is understood as a detachment...

Detection of microparticles in dynamic processes

International Nuclear Information System (INIS)

Ten, K A; Pruuel, E R; Kashkarov, A O; Rubtsov, I A; Shechtman, L I; Zhulanov, V V; Tolochko, B P; Rykovanov, G N; Muzyrya, A K; Smirnov, E B; Stolbikov, M Yu; Prosvirnin, K M

2016-01-01

When a metal plate is subjected to a strong shock impact, its free surface emits a flow of particles of different sizes (shock-wave “dusting”). Traditionally, the process of dusting is investigated by the methods of pulsed x-ray or piezoelectric sensor or via an optical technique. The particle size ranges from a few microns to hundreds of microns. The flow is assumed to include also finer particles, which cannot be detected with the existing methods yet. On the accelerator complex VEPP-3-VEPP-4 at the BINP there are two experiment stations for research on fast processes, including explosion ones. The stations enable measurement of both passed radiation (absorption) and small-angle x-ray scattering on synchrotron radiation (SR). Radiation is detected with a precision high-speed detector DIMEX. The detector has an internal memory of 32 frames, which enables recording of the dynamics of the process (shooting of movies) with intervals of 250 ns to 2 μ s. Flows of nano- and microparticles from free surfaces of various materials (copper and tin) have been examined. Microparticle flows were emitted from grooves of 50-200 μ s in size and joints (gaps) between metal parts. With the soft x-ray spectrum of SR one can explore the dynamics of a single microjet of micron size. The dynamics of density distribution along micro jets were determined. Under a shock wave (∼ 60 GPa) acting on tin disks, flows of microparticles from a smooth surface were recorded. (paper)

A dynamic capacity degradation model and its applications considering varying load for a large format Li-ion battery

International Nuclear Information System (INIS)

Ouyang, Minggao; Feng, Xuning; Han, Xuebing; Lu, Languang; Li, Zhe; He, Xiangming

2016-01-01

Highlights: • A dynamic capacity degradation model for large format Li-ion battery is proposed. • The change of the model parameters directly link with the degradation mechanisms. • The model can simulate the fading behavior of Li-ion battery under varying loads. • The model can help evaluate the longevity of a battery system under specific load. • The model can help predict the evolution of cell variations within a battery pack. - Abstract: The capacity degradation of the lithium ion battery should be well predicted during battery system design. Therefore, high-fidelity capacity degradation models that are suitable for the task of capacity prediction are required. This paper proposes a novel capacity degradation model that can simulate the degradation dynamics under varying working conditions for large-format lithium ion batteries. The degradation model is built based on a mechanistic and prognostic model (MPM) whose parameters are closely linked with the degradation mechanisms of lithium ion batteries. Chemical kinetics was set to drive the parameters of the MPM to change as capacity degradation continues. With the dynamic parameters of the MPM, the capacity predicted by the degradation model decreases as the cycle continues. Accelerated aging tests were conducted on three types of commercial lithium ion batteries to calibrate the capacity degradation model. The good fit with the experimental data indicates that the model can capture the degradation mechanisms well for different types of commercial lithium ion batteries. Furthermore, the calibrated model can be used to (1) evaluate the longevity of a battery system under a specific working load and (2) predict the evolution of cell variations within a battery pack when different cell works at different conditions. Correlated applications are discussed using the calibrated degradation model.

High-speed AFM for Studying Dynamic Biomolecular Processes

Science.gov (United States)

Ando, Toshio

2008-03-01

Biological molecules show their vital activities only in aqueous solutions. It had been one of dreams in biological sciences to directly observe biological macromolecules (protein, DNA) at work under a physiological condition because such observation is straightforward to understanding their dynamic behaviors and functional mechanisms. Optical microscopy has no sufficient spatial resolution and electron microscopy is not applicable to in-liquid samples. Atomic force microscopy (AFM) can visualize molecules in liquids at high resolution but its imaging rate was too low to capture dynamic biological processes. This slow imaging rate is because AFM employs mechanical probes (cantilevers) and mechanical scanners to detect the sample height at each pixel. It is quite difficult to quickly move a mechanical device of macroscopic size with sub-nanometer accuracy without producing unwanted vibrations. It is also difficult to maintain the delicate contact between a probe tip and fragile samples. Two key techniques are required to realize high-speed AFM for biological research; fast feedback control to maintain a weak tip-sample interaction force and a technique to suppress mechanical vibrations of the scanner. Various efforts have been carried out in the past decade to materialize high-speed AFM. The current high-speed AFM can capture images on video at 30-60 frames/s for a scan range of 250nm and 100 scan lines, without significantly disturbing week biomolecular interaction. Our recent studies demonstrated that this new microscope can reveal biomolecular processes such as myosin V walking along actin tracks and association/dissociation dynamics of chaperonin GroEL-GroES that occurs in a negatively cooperative manner. The capacity of nanometer-scale visualization of dynamic processes in liquids will innovate on biological research. In addition, it will open a new way to study dynamic chemical/physical processes of various phenomena that occur at the liquid-solid interfaces.

Alternating event processes during lifetimes: population dynamics and statistical inference.

Science.gov (United States)

Shinohara, Russell T; Sun, Yifei; Wang, Mei-Cheng

2018-01-01

In the literature studying recurrent event data, a large amount of work has been focused on univariate recurrent event processes where the occurrence of each event is treated as a single point in time. There are many applications, however, in which univariate recurrent events are insufficient to characterize the feature of the process because patients experience nontrivial durations associated with each event. This results in an alternating event process where the disease status of a patient alternates between exacerbations and remissions. In this paper, we consider the dynamics of a chronic disease and its associated exacerbation-remission process over two time scales: calendar time and time-since-onset. In particular, over calendar time, we explore population dynamics and the relationship between incidence, prevalence and duration for such alternating event processes. We provide nonparametric estimation techniques for characteristic quantities of the process. In some settings, exacerbation processes are observed from an onset time until death; to account for the relationship between the survival and alternating event processes, nonparametric approaches are developed for estimating exacerbation process over lifetime. By understanding the population dynamics and within-process structure, the paper provide a new and general way to study alternating event processes.

Hydrodynamic mean-field solutions of 1D exclusion processes with spatially varying hopping rates

Energy Technology Data Exchange (ETDEWEB)

Lakatos, Greg; O' Brien, John; Chou, Tom [Department of Biomathematics and Institute for Pure and Applied Mathematics, UCLA, Los Angeles, CA 90095 (United States)

2006-03-10

We analyse the open boundary partially asymmetric exclusion process with smoothly varying internal hopping rates in the infinite-size, mean-field limit. The mean-field equations for particle densities are written in terms of Ricatti equations with the steady-state current J as a parameter. These equations are solved both analytically and numerically. Upon imposing the boundary conditions set by the injection and extraction rates, the currents J are found self-consistently. We find a number of cases where analytic solutions can be found exactly or approximated. Results for J from asymptotic analyses for slowly varying hopping rates agree extremely well with those from extensive Monte Carlo simulations, suggesting that mean-field currents asymptotically approach the exact currents in the hydrodynamic limit, as the hopping rates vary slowly over the lattice. If the forward hopping rate is greater than or less than the backward hopping rate throughout the entire chain, the three standard steady-state phases are preserved. Our analysis reveals the sensitivity of the current to the relative phase between the forward and backward hopping rate functions.

Hydrodynamic mean-field solutions of 1D exclusion processes with spatially varying hopping rates

International Nuclear Information System (INIS)

Lakatos, Greg; O'Brien, John; Chou, Tom

2006-01-01

We analyse the open boundary partially asymmetric exclusion process with smoothly varying internal hopping rates in the infinite-size, mean-field limit. The mean-field equations for particle densities are written in terms of Ricatti equations with the steady-state current J as a parameter. These equations are solved both analytically and numerically. Upon imposing the boundary conditions set by the injection and extraction rates, the currents J are found self-consistently. We find a number of cases where analytic solutions can be found exactly or approximated. Results for J from asymptotic analyses for slowly varying hopping rates agree extremely well with those from extensive Monte Carlo simulations, suggesting that mean-field currents asymptotically approach the exact currents in the hydrodynamic limit, as the hopping rates vary slowly over the lattice. If the forward hopping rate is greater than or less than the backward hopping rate throughout the entire chain, the three standard steady-state phases are preserved. Our analysis reveals the sensitivity of the current to the relative phase between the forward and backward hopping rate functions

Flight Dynamic Simulation of Fighter In the Asymmetric External Store Release Process

Science.gov (United States)

Safi’i, Imam; Arifianto, Ony; Nurohman, Chandra

2018-04-01

In the fighter design, it is important to evaluate and analyze the flight dynamic of the aircraft earlier in the development process. One of the case is the dynamics of external store release process. A simulation tool can be used to analyze the fighter/external store system’s dynamics in the preliminary design stage. This paper reports the flight dynamics of Jet Fighter Experiment (JF-1 E) in asymmetric Advance Medium Range Air to Air Missile (AMRAAM) release process through simulations. The JF-1 E and AIM 120 AMRAAAM models are built by using Advanced Aircraft Analysis (AAA) and Missile Datcom software. By using these softwares, the aerodynamic stability and control derivatives can be obtained and used to model the dynamic characteristic of the fighter and the external store. The dynamic system is modeled by using MATLAB/Simulink software. By using this software, both the fighter/external store integration and the external store release process is simulated, and the dynamic of the system can be analyzed.

Psychosis and the dynamics of the psychotherapy process

DEFF Research Database (Denmark)

Rosenbaum, Bent; Harder, Susanne

2007-01-01

The role of psychotherapy in the treatment of psychoses remains controversial but there is improving acceptance that an understanding of the dynamics of the psychological processes involved in treatment and in the disorder itself may be important. Psychosis is understood as a detachment of the 's......The role of psychotherapy in the treatment of psychoses remains controversial but there is improving acceptance that an understanding of the dynamics of the psychological processes involved in treatment and in the disorder itself may be important. Psychosis is understood as a detachment......-subjective process, a therapeutic relationship is disrupted and a therapeutic alliance is not assured. Therapists have to pay particular attention to the empathic aspects of the interaction as they attempt to integrate affects to restore meaning to the inner life of the patient. The psychodynamics of this process...

Information processing and dynamics in minimally cognitive agents.

Science.gov (United States)

Beer, Randall D; Williams, Paul L

2015-01-01

There has been considerable debate in the literature about the relative merits of information processing versus dynamical approaches to understanding cognitive processes. In this article, we explore the relationship between these two styles of explanation using a model agent evolved to solve a relational categorization task. Specifically, we separately analyze the operation of this agent using the mathematical tools of information theory and dynamical systems theory. Information-theoretic analysis reveals how task-relevant information flows through the system to be combined into a categorization decision. Dynamical analysis reveals the key geometrical and temporal interrelationships underlying the categorization decision. Finally, we propose a framework for directly relating these two different styles of explanation and discuss the possible implications of our analysis for some of the ongoing debates in cognitive science. Copyright © 2014 Cognitive Science Society, Inc.

Time-varying linear control for tiltrotor aircraft

Directory of Open Access Journals (Sweden)

Jing ZHANG

2018-04-01

Full Text Available Tiltrotor aircraft have three flight modes: helicopter mode, airplane mode, and transition mode. A tiltrotor has characteristics of highly nonlinear, time-varying flight dynamics and inertial/control couplings in its transition mode. It can transit from the helicopter mode to the airplane mode by tilting its nacelles, and an effective controller is crucial to accomplish tilting transition missions. Longitudinal dynamic characteristics of the tiltrotor are described by a nonlinear Lagrange-form model, which takes into account inertial/control couplings and aerodynamic interferences. Reference commands for airspeed velocity and attitude in the transition mode are calculated dynamically by visiting a command library which is founded in advance by analyzing the flight envelope of the tiltrotor. A Time-Varying Linear (TVL model is obtained using a Taylor-expansion based online linearization technique from the nonlinear model. Subsequently, based on an optimal control concept, an online optimization based control method with input constraints considered is proposed. To validate the proposed control method, three typical tilting transition missions are simulated using the nonlinear model of XV-15 tiltrotor aircraft. Simulation results show that the controller can be used to control the tiltrotor throughout its operating envelop which includes a transition flight, and can also deal with vertical gust disturbances. Keywords: Constrained optimal control, Inertia/control couplings, Tiltrotor aircraft, Time-varying control, Transition mode

Becoming a Learning Organization Through Dynamic Business Process Management

Directory of Open Access Journals (Sweden)

Marek Szelągowski

2014-01-01

Full Text Available As customers demand easier access to individualized products and services, companies now face an ongoing problem of how to deliver flexible and innovative solutions while maintaining efficiency and competitiveness. In this environment, the only sustainable form of competitive advantage rests in the ability to learn faster than the competition (de Geus, 1988. The article returns to the somewhat forgotten concept of the learning organization and explores how its principles can be applied with the use of dynamic business process management (dynamic BPM. Enabling in this concept individual or team-based limited experimentation and providing conditions for learning though experience in the course of performing business processes allows for the constant creation of practical knowledge. This article provides examples of how dynamic BPM facilitates the constant creation and verification of practical knowledge, with the aim of improving and adapting processes to maintain the competitive advantage of the organization.

Process model for ammonia volatilization from anaerobic swine lagoons incorporating varying wind speeds and biogas bubbling

Science.gov (United States)

Ammonia volatilization from treatment lagoons varies widely with the total ammonia concentration, pH, temperature, suspended solids, atmospheric ammonia concentration above the water surface, and wind speed. Ammonia emissions were estimated with a process-based mechanistic model integrating ammonia ...

A Unified Point Process Probabilistic Framework to Assess Heartbeat Dynamics and Autonomic Cardiovascular Control

Directory of Open Access Journals (Sweden)

Zhe eChen

2012-02-01

Full Text Available In recent years, time-varying inhomogeneous point process models have been introduced for assessment of instantaneous heartbeat dynamics as well as specific cardiovascular control mechanisms and hemodynamics. Assessment of the model's statistics is established through the Wiener-Volterra theory and a multivariate autoregressive (AR structure. A variety of instantaneous cardiovascular metrics, such as heart rate (HR, heart rate variability (HRV, respiratory sinus arrhythmia (RSA, and baroreceptor-cardiac reflex (baroreflex sensitivity (BRS, are derived within a parametric framework and instantaneously updated with adaptive and local maximum likelihood estimation algorithms. Inclusion of second order nonlinearities, with subsequent bispectral quantification in the frequency domain, further allows for definition of instantaneous metrics of nonlinearity. We here organize a comprehensive review of the devised methods as applied to experimental recordings from healthy subjects during propofol anesthesia. Collective results reveal interesting dynamic trends across the different pharmacological interventions operated within each anesthesia session, confirming the ability of the algorithm to track important changes in cardiorespiratory elicited interactions, and pointing at our mathematical approach as a promising monitoring tool for an accurate, noninvasive assessment in clinical practice.

Workshop on Dynamic Process Management (DPM 2006) : Preface

NARCIS (Netherlands)

Reichert, Manfred; Verma, Kunal; Wombacher, Andreas; Eder, Johann; Dustdar, Schahram

The agility of an enterprise increasingly depends on its ability to dynamically set up new business processes or to modify existing ones, and to quickly adapt its information systems to these process changes. Companies are therefore developing a growing interest in concepts, technologies and systems

Two-boundary first exit time of Gauss-Markov processes for stochastic modeling of acto-myosin dynamics.

Science.gov (United States)

D'Onofrio, Giuseppe; Pirozzi, Enrica

2017-05-01

We consider a stochastic differential equation in a strip, with coefficients suitably chosen to describe the acto-myosin interaction subject to time-varying forces. By simulating trajectories of the stochastic dynamics via an Euler discretization-based algorithm, we fit experimental data and determine the values of involved parameters. The steps of the myosin are represented by the exit events from the strip. Motivated by these results, we propose a specific stochastic model based on the corresponding time-inhomogeneous Gauss-Markov and diffusion process evolving between two absorbing boundaries. We specify the mean and covariance functions of the stochastic modeling process taking into account time-dependent forces including the effect of an external load. We accurately determine the probability density function (pdf) of the first exit time (FET) from the strip by solving a system of two non singular second-type Volterra integral equations via a numerical quadrature. We provide numerical estimations of the mean of FET as approximations of the dwell-time of the proteins dynamics. The percentage of backward steps is given in agreement to experimental data. Numerical and simulation results are compared and discussed.

Propagation of 3D internal gravity wave beams in a slowly varying stratification

Science.gov (United States)

Fan, Boyu; Akylas, T. R.

2017-11-01

The time-mean flows induced by internal gravity wave beams (IGWB) with 3D variations have been shown to have dramatic implications for long-term IGWB dynamics. While uniform stratifications are convenient both theoretically and in the laboratory, stratifications in the ocean can vary by more than an order of magnitude over the ocean depth. Here, in view of this fact, we study the propagation of a 3D IGWB in a slowly varying stratification. We assume that the stratification varies slowly relative to the local variations in the wave profile. In the 2D case, the IGWB bends in response to the changing stratification, but nonlinear effects are minor even in the finite amplitude regime. For a 3D IGWB, in addition to bending, we find that nonlinearity results in the transfer of energy from waves to a large-scale time-mean flow associated with the mean potential vorticity, similar to IGWB behavior in a uniform stratification. In a weakly nonlinear setting, we derive coupled evolution equations that govern this process. We also use these equations to determine the stability properties of 2D IGWB to 3D perturbations. These findings indicate that 3D effects may be relevant and possibly fundamental to IGWB dynamics in nature. Supported by NSF Grant DMS-1512925.

Disease processes as hybrid dynamical systems

Directory of Open Access Journals (Sweden)

Pietro Liò

2012-08-01

Full Text Available We investigate the use of hybrid techniques in complex processes of infectious diseases. Since predictive disease models in biomedicine require a multiscale approach for understanding the molecule-cell-tissue-organ-body interactions, heterogeneous methodologies are often employed for describing the different biological scales. Hybrid models provide effective means for complex disease modelling where the action and dosage of a drug or a therapy could be meaningfully investigated: the infection dynamics can be classically described in a continuous fashion, while the scheduling of multiple treatment discretely. We define an algebraic language for specifying general disease processes and multiple treatments, from which a semantics in terms of hybrid dynamical system can be derived. Then, the application of control-theoretic tools is proposed in order to compute the optimal scheduling of multiple therapies. The potentialities of our approach are shown in the case study of the SIR epidemic model and we discuss its applicability on osteomyelitis, a bacterial infection affecting the bone remodelling system in a specific and multiscale manner. We report that formal languages are helpful in giving a general homogeneous formulation for the different scales involved in a multiscale disease process; and that the combination of hybrid modelling and control theory provides solid grounds for computational medicine.

Remaining useful life estimation for deteriorating systems with time-varying operational conditions and condition-specific failure zones

Directory of Open Access Journals (Sweden)

Li Qi

2016-06-01

Full Text Available Dynamic time-varying operational conditions pose great challenge to the estimation of system remaining useful life (RUL for the deteriorating systems. This paper presents a method based on probabilistic and stochastic approaches to estimate system RUL for periodically monitored degradation processes with dynamic time-varying operational conditions and condition-specific failure zones. The method assumes that the degradation rate is influenced by specific operational condition and moreover, the transition between different operational conditions plays the most important role in affecting the degradation process. These operational conditions are assumed to evolve as a discrete-time Markov chain (DTMC. The failure thresholds are also determined by specific operational conditions and described as different failure zones. The 2008 PHM Conference Challenge Data is utilized to illustrate our method, which contains mass sensory signals related to the degradation process of a commercial turbofan engine. The RUL estimation method using the sensor measurements of a single sensor was first developed, and then multiple vital sensors were selected through a particular optimization procedure in order to increase the prediction accuracy. The effectiveness and advantages of the proposed method are presented in a comparison with existing methods for the same dataset.

Population and evolutionary dynamics in spatially structured seasonally varying environments.

Science.gov (United States)

Reid, Jane M; Travis, Justin M J; Daunt, Francis; Burthe, Sarah J; Wanless, Sarah; Dytham, Calvin

2018-03-25

Increasingly imperative objectives in ecology are to understand and forecast population dynamic and evolutionary responses to seasonal environmental variation and change. Such population and evolutionary dynamics result from immediate and lagged responses of all key life-history traits, and resulting demographic rates that affect population growth rate, to seasonal environmental conditions and population density. However, existing population dynamic and eco-evolutionary theory and models have not yet fully encompassed within-individual and among-individual variation, covariation, structure and heterogeneity, and ongoing evolution, in a critical life-history trait that allows individuals to respond to seasonal environmental conditions: seasonal migration. Meanwhile, empirical studies aided by new animal-tracking technologies are increasingly demonstrating substantial within-population variation in the occurrence and form of migration versus year-round residence, generating diverse forms of 'partial migration' spanning diverse species, habitats and spatial scales. Such partially migratory systems form a continuum between the extreme scenarios of full migration and full year-round residence, and are commonplace in nature. Here, we first review basic scenarios of partial migration and associated models designed to identify conditions that facilitate the maintenance of migratory polymorphism. We highlight that such models have been fundamental to the development of partial migration theory, but are spatially and demographically simplistic compared to the rich bodies of population dynamic theory and models that consider spatially structured populations with dispersal but no migration, or consider populations experiencing strong seasonality and full obligate migration. Second, to provide an overarching conceptual framework for spatio-temporal population dynamics, we define a 'partially migratory meta-population' system as a spatially structured set of locations that can

Estimating varying coefficients for partial differential equation models.

Science.gov (United States)

Zhang, Xinyu; Cao, Jiguo; Carroll, Raymond J

2017-09-01

Partial differential equations (PDEs) are used to model complex dynamical systems in multiple dimensions, and their parameters often have important scientific interpretations. In some applications, PDE parameters are not constant but can change depending on the values of covariates, a feature that we call varying coefficients. We propose a parameter cascading method to estimate varying coefficients in PDE models from noisy data. Our estimates of the varying coefficients are shown to be consistent and asymptotically normally distributed. The performance of our method is evaluated by a simulation study and by an empirical study estimating three varying coefficients in a PDE model arising from LIDAR data. © 2017, The International Biometric Society.

A Three-Level Process Framework for Contract-Based Dynamic Service Outsourcing

NARCIS (Netherlands)

Grefen, P.W.P.J.; Angelov, S.A.

Service outsourcing is the business paradigm, in which an organization has part of its business process performed by a service provider. In dynamic markets, service providers are selected on the fly during process enactment. The cooperation between the parties is specified in a dynamically made

Renormalization group theory for percolation in time-varying networks.

Science.gov (United States)

Karschau, Jens; Zimmerling, Marco; Friedrich, Benjamin M

2018-05-22

Motivated by multi-hop communication in unreliable wireless networks, we present a percolation theory for time-varying networks. We develop a renormalization group theory for a prototypical network on a regular grid, where individual links switch stochastically between active and inactive states. The question whether a given source node can communicate with a destination node along paths of active links is equivalent to a percolation problem. Our theory maps the temporal existence of multi-hop paths on an effective two-state Markov process. We show analytically how this Markov process converges towards a memoryless Bernoulli process as the hop distance between source and destination node increases. Our work extends classical percolation theory to the dynamic case and elucidates temporal correlations of message losses. Quantification of temporal correlations has implications for the design of wireless communication and control protocols, e.g. in cyber-physical systems such as self-organized swarms of drones or smart traffic networks.

Information Processing and Dynamics in Minimally Cognitive Agents

Science.gov (United States)

Beer, Randall D.; Williams, Paul L.

2015-01-01

There has been considerable debate in the literature about the relative merits of information processing versus dynamical approaches to understanding cognitive processes. In this article, we explore the relationship between these two styles of explanation using a model agent evolved to solve a relational categorization task. Specifically, we…

Identifying and tracking dynamic processes in social networks

Science.gov (United States)

Chung, Wayne; Savell, Robert; Schütt, Jan-Peter; Cybenko, George

2006-05-01

The detection and tracking of embedded malicious subnets in an active social network can be computationally daunting due to the quantity of transactional data generated in the natural interaction of large numbers of actors comprising a network. In addition, detection of illicit behavior may be further complicated by evasive strategies designed to camouflage the activities of the covert subnet. In this work, we move beyond traditional static methods of social network analysis to develop a set of dynamic process models which encode various modes of behavior in active social networks. These models will serve as the basis for a new application of the Process Query System (PQS) to the identification and tracking of covert dynamic processes in social networks. We present a preliminary result from application of our technique in a real-world data stream-- the Enron email corpus.

Processing and characterization of oval piezoelectric actuators

Science.gov (United States)

Jadidian, B.; Allahverdi, M.; Mohammadi, F.; Safari, A.

2002-03-01

The processing and characterization of piezoelectric actuators with oval geometry are presented. The monolithic actuators were fabricated using the fused deposition of ceramic process. The minor diameter of the ovals varied between 2 and 14 mm and their major diameter, wall thickness, and width were 20, 0.85, and 7 mm, respectively. When driven under electric field, the actuators expanded along their minor diameter. The static and dynamic displacements of ˜7 and ˜5.6 μm were observed at 850 V(dc) and 100 V(ac). The static displacement of the ovals varied almost linearly with voltage and did not change under the application of external load in the range of 1-15 N. However, both dynamic displacement and resonant frequency of the ovals varied, with a maximum of 42 μm and 38 Hz, respectively, under 13 N load.

A 2-D process-based model for suspended sediment dynamics: a first step towards ecological modeling

Science.gov (United States)

Achete, F. M.; van der Wegen, M.; Roelvink, D.; Jaffe, B.

2015-06-01

In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions. This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011. Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.

A 2-D process-based model for suspended sediment dynamics: A first step towards ecological modeling

Science.gov (United States)

Achete, F. M.; van der Wegen, M.; Roelvink, D.; Jaffe, B.

2015-01-01

In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space and over time. A robust sediment transport model is a first step in developing a chain of models enabling simulations of contaminants, phytoplankton and habitat conditions. This works aims to determine turbidity levels in the complex-geometry delta of the San Francisco estuary using a process-based approach (Delft3D Flexible Mesh software). Our approach includes a detailed calibration against measured SSC levels, a sensitivity analysis on model parameters and the determination of a yearly sediment budget as well as an assessment of model results in terms of turbidity levels for a single year, water year (WY) 2011. Model results show that our process-based approach is a valuable tool in assessing sediment dynamics and their related ecological parameters over a range of spatial and temporal scales. The model may act as the base model for a chain of ecological models assessing the impact of climate change and management scenarios. Here we present a modeling approach that, with limited data, produces reliable predictions and can be useful for estuaries without a large amount of processes data.

Dynamical bifurcation in a system of coupled oscillators with slowly varying parameters

Directory of Open Access Journals (Sweden)

Igor Parasyuk

2016-08-01

Full Text Available This paper deals with a fast-slow system representing n nonlinearly coupled oscillators with slowly varying parameters. We find conditions which guarantee that all omega-limit sets near the slow surface of the system are equilibria and invariant tori of all dimensions not exceeding n, the tori of dimensions less then n being hyperbolic. We show that a typical trajectory demonstrates the following transient process: while its slow component is far from the stationary points of the slow vector field, the fast component exhibits damping oscillations; afterwards, the former component enters and stays in a small neighborhood of some stationary point, and the oscillation amplitude of the latter begins to increase; eventually the trajectory is attracted by an n-dimesional invariant torus and a multi-frequency oscillatory regime is established.

Burst analysis tool for developing neuronal networks exhibiting highly varying action potential dynamics

Directory of Open Access Journals (Sweden)

Fikret Emre eKapucu

2012-06-01

Full Text Available In this paper we propose a firing statistics based neuronal network burst detection algorithm for neuronal networks exhibiting highly variable action potential dynamics. Electrical activity of neuronal networks is generally analyzed by the occurrences of spikes and bursts both in time and space. Commonly accepted analysis tools employ burst detection algorithms based on predefined criteria. However, maturing neuronal networks, such as those originating from human embryonic stem cells (hESC, exhibit highly variable network structure and time-varying dynamics. To explore the developing burst/spike activities of such networks, we propose a burst detection algorithm which utilizes the firing statistics based on interspike interval (ISI histograms. Moreover, the algorithm calculates interspike interval thresholds for burst spikes as well as for pre-burst spikes and burst tails by evaluating the cumulative moving average and skewness of the ISI histogram. Because of the adaptive nature of the proposed algorithm, its analysis power is not limited by the type of neuronal cell network at hand. We demonstrate the functionality of our algorithm with two different types of microelectrode array (MEA data recorded from spontaneously active hESC-derived neuronal cell networks. The same data was also analyzed by two commonly employed burst detection algorithms and the differences in burst detection results are illustrated. The results demonstrate that our method is both adaptive to the firing statistics of the network and yields successful burst detection from the data. In conclusion, the proposed method is a potential tool for analyzing of hESC-derived neuronal cell networks and thus can be utilized in studies aiming to understand the development and functioning of human neuronal networks and as an analysis tool for in vitro drug screening and neurotoxicity assays.

Efficient kinetic Monte Carlo method for reaction-diffusion problems with spatially varying annihilation rates

Science.gov (United States)

Schwarz, Karsten; Rieger, Heiko

2013-03-01

We present an efficient Monte Carlo method to simulate reaction-diffusion processes with spatially varying particle annihilation or transformation rates as it occurs for instance in the context of motor-driven intracellular transport. Like Green's function reaction dynamics and first-passage time methods, our algorithm avoids small diffusive hops by propagating sufficiently distant particles in large hops to the boundaries of protective domains. Since for spatially varying annihilation or transformation rates the single particle diffusion propagator is not known analytically, we present an algorithm that generates efficiently either particle displacements or annihilations with the correct statistics, as we prove rigorously. The numerical efficiency of the algorithm is demonstrated with an illustrative example.

Dynamic Modeling of Process Technologies for Closed-Loop Water Recovery Systems

Science.gov (United States)

Allada, Rama Kumar; Lange, Kevin E.; Anderson, Molly S.

2012-01-01

Detailed chemical process simulations are a useful tool in designing and optimizing complex systems and architectures for human life support. Dynamic and steady-state models of these systems help contrast the interactions of various operating parameters and hardware designs, which become extremely useful in trade-study analyses. NASA s Exploration Life Support technology development project recently made use of such models to compliment a series of tests on different waste water distillation systems. This paper presents dynamic simulations of chemical process for primary processor technologies including: the Cascade Distillation System (CDS), the Vapor Compression Distillation (VCD) system, the Wiped-Film Rotating Disk (WFRD), and post-distillation water polishing processes such as the Volatiles Removal Assembly (VRA). These dynamic models were developed using the Aspen Custom Modeler (Registered TradeMark) and Aspen Plus(Registered TradeMark) process simulation tools. The results expand upon previous work for water recovery technology models and emphasize dynamic process modeling and results. The paper discusses system design, modeling details, and model results for each technology and presents some comparisons between the model results and available test data. Following these initial comparisons, some general conclusions and forward work are discussed.

A Dynamic Simulation Program for a Hydriodic Acid Concentration and Decomposition Process in the VHTR-SI Process

International Nuclear Information System (INIS)

Chang, Ji Woon; Shin, Young Joon; Lee, Tae Hoon; Lee, Ki Young; Kim, Yong Wan; Chang, Jong Hwa; Youn, Cheung

2011-01-01

The Sulfur-Iodine (SI) cycle which can produce hydrogen by using nuclear heat consists of a Bunsen reaction (Section 1), a sulfur acid concentration and decomposition (Section 2), and a hydriodic acid concentration and decomposition (Section 3). The heat required in the SI process can be supplied through an intermediate heat exchanger (IHX) by a Very High Temperature Gas Cooled Reactor (VHTR). The Korea Atomic Energy Research Institute-Dynamic Simulation Code (KAERI-DySCo) based on the Visual C++ is an integration application software that simulates the dynamic behavior of the SI process. KAERI-DySCo was prepared to solve dynamic problem of the seven chemical reactors which consist of Sections 2 and 3. Section 3 is the key part of the SI process, because the strong non-ideality and the partial immiscibility of the binary HI.H 2 O and the ternary HI.I 2 .H 2 O (HIX solution) mixture make it difficult to model and simulate the dynamic behavior of the system. Therefore, it is necessary to compose separately a dynamic simulation program for Section 3 in KAERI-DySCo optimization. In this paper, a simulation program to analyze the dynamic behavior of Section 3 is introduced using the prepared KAERI-DySCo, and results of dynamic simulation are represented by running the program

Memory-related functional connectivity in visual processing regions varies by prior emotional context.

Science.gov (United States)

Bowen, Holly J; Kensinger, Elizabeth A

2017-09-06

Memory retrieval involves the reactivation of processes that were engaged at encoding. Using a Generalized Linear Model to test for effects of valence, our prior study suggests that memory for information previously encoded in a negative context reengages sensory processing regions at retrieval to a greater extent than positive. Here, we used partial least squares analyses of the same dataset to determine whether this valence-specific processing was one of the dominant patterns in the retrieval data. Trials previously paired with a face revealed a strong pattern of emotion that did not vary by valence, but for trials previously paired with a scene, an extensive network of regions was active during recollection of trials paired with negative content. These same regions were negatively correlated with recollection of trials paired with positive content. These results confirm that, despite no emotional content present during the time of retrieval, strong patterns of emotional study context are present in the data. Moreover, at least for trials paired with scenes at encoding, valence-specific networks are linked to episodic memory recollection, providing further support for recapitulation of sensory processing during recollection of negative emotional information.

Developmental Dynamics of Emotion and Cognition Processes in Preschoolers

Science.gov (United States)

Blankson, A. Nayena; O'Brien, Marion; Leerkes, Esther M.; Marcovitch, Stuart; Calkins, Susan D.; Weaver, Jennifer Miner

2013-01-01

Dynamic relations during the preschool years across processes of control and understanding in the domains of emotion and cognition were examined. Participants were 263 children (42% non-White) and their mothers who were seen first when the children were 3 years old and again when they were 4. Results indicated dynamic dependence among the…

Adaptive Dynamic Process Scheduling on Distributed Memory Parallel Computers

Directory of Open Access Journals (Sweden)

Wei Shu

1994-01-01

Full Text Available One of the challenges in programming distributed memory parallel machines is deciding how to allocate work to processors. This problem is particularly important for computations with unpredictable dynamic behaviors or irregular structures. We present a scheme for dynamic scheduling of medium-grained processes that is useful in this context. The adaptive contracting within neighborhood (ACWN is a dynamic, distributed, load-dependent, and scalable scheme. It deals with dynamic and unpredictable creation of processes and adapts to different systems. The scheme is described and contrasted with two other schemes that have been proposed in this context, namely the randomized allocation and the gradient model. The performance of the three schemes on an Intel iPSC/2 hypercube is presented and analyzed. The experimental results show that even though the ACWN algorithm incurs somewhat larger overhead than the randomized allocation, it achieves better performance in most cases due to its adaptiveness. Its feature of quickly spreading the work helps it outperform the gradient model in performance and scalability.

Predicting seizures in untreated temporal lobe epilepsy using point-process nonlinear models of heartbeat dynamics.

Science.gov (United States)

Valenza, G; Romigi, A; Citi, L; Placidi, F; Izzi, F; Albanese, M; Scilingo, E P; Marciani, M G; Duggento, A; Guerrisi, M; Toschi, N; Barbieri, R

2016-08-01

Symptoms of temporal lobe epilepsy (TLE) are frequently associated with autonomic dysregulation, whose underlying biological processes are thought to strongly contribute to sudden unexpected death in epilepsy (SUDEP). While abnormal cardiovascular patterns commonly occur during ictal events, putative patterns of autonomic cardiac effects during pre-ictal (PRE) periods (i.e. periods preceding seizures) are still unknown. In this study, we investigated TLE-related heart rate variability (HRV) through instantaneous, nonlinear estimates of cardiovascular oscillations during inter-ictal (INT) and PRE periods. ECG recordings from 12 patients with TLE were processed to extract standard HRV indices, as well as indices of instantaneous HRV complexity (dominant Lyapunov exponent and entropy) and higher-order statistics (bispectra) obtained through definition of inhomogeneous point-process nonlinear models, employing Volterra-Laguerre expansions of linear, quadratic, and cubic kernels. Experimental results demonstrate that the best INT vs. PRE classification performance (balanced accuracy: 73.91%) was achieved only when retaining the time-varying, nonlinear, and non-stationary structure of heartbeat dynamical features. The proposed approach opens novel important avenues in predicting ictal events using information gathered from cardiovascular signals exclusively.

Understanding the Entrepreneurial Process: a Dynamic Approach

Directory of Open Access Journals (Sweden)

Vânia Maria Jorge Nassif

2010-04-01

Full Text Available There is considerable predominance in the adoption of perspectives based on characteristics in research into entrepreneurship. However, most studies describe the entrepreneur from a static or snapshot approach; very few adopt a dynamic perspective. The aim of this study is to contribute to the enhancement of knowledge concerning entrepreneurial process dynamics through an understanding of the values, characteristics and actions of the entrepreneur over time. By focusing on personal attributes, we have developed a framework that shows the importance of affective and cognitive aspects of entrepreneurs and the way that they evolve during the development of their business.

Darlington tritium removal facility and station upgrading plant dynamic process simulation

International Nuclear Information System (INIS)

Busigin, A.; Williams, G. I. D.; Wong, T. C. W.; Kulczynski, D.; Reid, A.

2008-01-01

Ontario Power Generation Nuclear (OPGN) has a 4 x 880 MWe CANDU nuclear station at its Darlington Nuclear Div. located in Bowmanville. The station has been operating a Tritium Removal Facility (TRF) and a D 2 O station Upgrading Plant (SUP) since 1989. Both facilities were designed with a Distributed Control System (DCS) and programmable logic controllers (PLC) for process control. This control system was replaced with a DCS only, in 1998. A dynamic plant simulator was developed for the Darlington TRF (DTRF) and the SUP, as part of the computer control system replacement. The simulator was used to test the new software, required to eliminate the PLCs. The simulator is now used for operator training and testing of process control software changes prior to field installation. Dynamic simulation will be essential for the ITER isotope separation system, where the process is more dynamic than the relatively steady-state DTRF process. This paper describes the development and application of the DTRF and SUP dynamic simulator, its benefits, architecture, and the operational experience with the simulator. (authors)

Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks.

Science.gov (United States)

Nicosia, Vincenzo; Skardal, Per Sebastian; Arenas, Alex; Latora, Vito

2017-03-31

We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

Collective Phenomena Emerging from the Interactions between Dynamical Processes in Multiplex Networks

Science.gov (United States)

Nicosia, Vincenzo; Skardal, Per Sebastian; Arenas, Alex; Latora, Vito

2017-03-01

We introduce a framework to intertwine dynamical processes of different nature, each with its own distinct network topology, using a multilayer network approach. As an example of collective phenomena emerging from the interactions of multiple dynamical processes, we study a model where neural dynamics and nutrient transport are bidirectionally coupled in such a way that the allocation of the transport process at one layer depends on the degree of synchronization at the other layer, and vice versa. We show numerically, and we prove analytically, that the multilayer coupling induces a spontaneous explosive synchronization and a heterogeneous distribution of allocations, otherwise not present in the two systems considered separately. Our framework can find application to other cases where two or more dynamical processes such as synchronization, opinion formation, information diffusion, or disease spreading, are interacting with each other.

A System Structure for a VHTR-SI Process Dynamic Simulation Code

International Nuclear Information System (INIS)

Chang, Jiwoon; Shin, Youngjoon; Kim, Jihwan; Lee, Kiyoung; Lee, Wonjae; Chang, Jonghwa; Youn, Cheung

2008-01-01

The VHTR-SI process dynamic simulation code embedded in a mathematical solution engine is an application software system that simulates the dynamic behavior of the VHTR-SI process. Also, the software system supports a user friendly graphical user interface (GUI) for user input/out. Structured analysis techniques were developed in the late 1970s by Yourdon, DeMarco, Gane and Sarson for applying a systematic approach to a systems analysis. It included the use of data flow diagrams and data modeling and fostered the use of an implementation-independent graphical notation for a documentation. In this paper, we present a system structure for a VHRT-SI process dynamic simulation code by using the methodologies of structured analysis

PRODIAG -- Dynamic qualitative analysis for process fault diagnosis

International Nuclear Information System (INIS)

Reifman, J.; Wei, T.Y.C.

1995-01-01

The authors present a method for handling the dynamic effects of process component malfunctions through time-independent rule-based diagnostic systems. The method's theory is discussed and a simplified version is implemented in the process diagnostic expert system PRODIAG. Simulation results from a full-scope operator training simulator of a nuclear power plant are used to illustrate the method

Dynamic modelling of an adsorption storage tank using a hybrid approach combining computational fluid dynamics and process simulation

Science.gov (United States)

Mota, J.P.B.; Esteves, I.A.A.C.; Rostam-Abadi, M.

2004-01-01

A computational fluid dynamics (CFD) software package has been coupled with the dynamic process simulator of an adsorption storage tank for methane fuelled vehicles. The two solvers run as independent processes and handle non-overlapping portions of the computational domain. The codes exchange data on the boundary interface of the two domains to ensure continuity of the solution and of its gradient. A software interface was developed to dynamically suspend and activate each process as necessary, and be responsible for data exchange and process synchronization. This hybrid computational tool has been successfully employed to accurately simulate the discharge of a new tank design and evaluate its performance. The case study presented here shows that CFD and process simulation are highly complementary computational tools, and that there are clear benefits to be gained from a close integration of the two. ?? 2004 Elsevier Ltd. All rights reserved.

Modelling the Dynamics of Intracellular Processes as an Organisation of Multiple Agents

NARCIS (Netherlands)

Bosse, T.; Jonker, C.M.; Treur, J.; Armano, G.; Merelli, E.; Denzinger, J.; Martin, A.; Miles, S.; Tianfield, H.; Unland, R.

2005-01-01

This paper explores how the dynamics of complex biological processes can be modeled as an organisation of multiple agents. This modelling perspective identifies organisational structure occurring in complex decentralised processes and handles complexity of the analysis of the dynamics by structuring

Implications of tidally-varying bed stress and intermittent estuarine stratification on fine-sediment dynamics through the Mekong's tidal river to estuarine reach

Science.gov (United States)

McLachlan, R. L.; Ogston, A. S.; Allison, M. A.

2017-09-01

River gauging stations are often located upriver of tidal propagation where sediment transport processes and storage are impacted by widely varying ratios of marine to freshwater influence. These impacts are not yet thoroughly understood. Therefore, sediment fluxes measured at these stations may not be suitable for predicting changes to coastal morphology. To characterize sediment transport dynamics in this understudied zone, flow velocity, salinity, and suspended-sediment properties (concentration, size, and settling velocity) were measured within the tidal Sông Hậu distributary of the lower Mekong River, Vietnam. Fine-sediment aggregation, settling, and trapping rates were promoted by seasonal and tidal fluctuations in near-bed shear stress as well as the intermittent presence of a salt wedge and estuary turbidity maximum. Beginning in the tidal river, fine-grained particles were aggregated in freshwater. Then, in the interface zone between the tidal river and estuary, impeded near-bed shear stress and particle flux convergence promoted settling and trapping. Finally, in the estuary, sediment retention was further encouraged by stratification and estuarine circulation which protected the bed against particle resuspension and enhanced particle aggregation. These patterns promote mud export ( 1.7 t s-1) from the entire study area in the high-discharge season when fluvial processes dominate and mud import ( 0.25 t s-1) into the estuary and interface zone in the low-discharge season when estuarine processes dominate. Within the lower region of the distributaries, morphological change in the form of channel abandonment was found to be promoted within minor distributaries by feedbacks between channel depth, vertical mixing, and aggregate trapping. In effect, this field study sheds light on the sediment trapping capabilities of the tidal river - estuary interface zone, a relatively understudied region upstream of where traditional concepts place sites of deposition

Brown Dwarf Variability: What's Varying and Why?

Science.gov (United States)

Marley, Mark Scott

2014-01-01

Surveys by ground based telescopes, HST, and Spitzer have revealed that brown dwarfs of most spectral classes exhibit variability. The spectral and temporal signatures of the variability are complex and apparently defy simplistic classification which complicates efforts to model the changes. Important questions include understanding if clearings are forming in an otherwise uniform cloud deck or if thermal perturbations, perhaps associated with breaking gravity waves, are responsible. If clouds are responsible how long does it take for the atmospheric thermal profile to relax from a hot cloudy to a cooler cloudless state? If thermal perturbations are responsible then what atmospheric layers are varying? How do the observed variability timescales compare to atmospheric radiative, chemical, and dynamical timescales? I will address such questions by presenting modeling results for time-varying partly cloudy atmospheres and explore the importance of various atmospheric processes over the relevant timescales for brown dwarfs of a range of effective temperatures. Regardless of the origin of the observed variability, the complexity seen in the atmospheres of the field dwarfs hints at the variability that we may encounter in the next few years in directly imaged young Jupiters. Thus understanding the nature of variability in the field dwarfs, including sensitivity to gravity and metallicity, is of particular importance for exoplanet characterization.

A functional-dynamic reflection on participatory processes in modeling projects.

Science.gov (United States)

Seidl, Roman

2015-12-01

The participation of nonscientists in modeling projects/studies is increasingly employed to fulfill different functions. However, it is not well investigated if and how explicitly these functions and the dynamics of a participatory process are reflected by modeling projects in particular. In this review study, I explore participatory modeling projects from a functional-dynamic process perspective. The main differences among projects relate to the functions of participation-most often, more than one per project can be identified, along with the degree of explicit reflection (i.e., awareness and anticipation) on the dynamic process perspective. Moreover, two main approaches are revealed: participatory modeling covering diverse approaches and companion modeling. It becomes apparent that the degree of reflection on the participatory process itself is not always explicit and perfectly visible in the descriptions of the modeling projects. Thus, the use of common protocols or templates is discussed to facilitate project planning, as well as the publication of project results. A generic template may help, not in providing details of a project or model development, but in explicitly reflecting on the participatory process. It can serve to systematize the particular project's approach to stakeholder collaboration, and thus quality management.

Dynamics of carbon 14 in soils: a review

International Nuclear Information System (INIS)

Tamponnet, C.

2004-01-01

In terrestrial ecosystems, soil is the main interface between atmosphere, hydrosphere, lithosphere and biosphere. Its interactions with carbon cycle are primordial. Information about carbon 14 dynamics in soils is quite dispersed and an up-to-date status is therefore presented in this paper. Carbon 14 dynamics in soils are governed by physical processes (soil structure, soil aggregation, soil erosion) chemical processes (sequestration by soil components either mineral or organic), and soil biological processes (soil microbes, soil fauna, soil biochemistry). The relative importance of such processes varied remarkably among the various biomes (tropical forest, temperate forest, boreal forest, tropical savannah, temperate pastures, deserts, tundra, marshlands, agro ecosystems) encountered in the terrestrial eco-sphere. Moreover, application for a simplified modelling of carbon 14 dynamics in soils is proposed. (author)

Adaptive control of chaotic systems with stochastic time varying unknown parameters

Energy Technology Data Exchange (ETDEWEB)

Salarieh, Hassan [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: salarieh@mech.sharif.edu; Alasty, Aria [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: aalasti@sharif.edu

2008-10-15

In this paper based on the Lyapunov stability theorem, an adaptive control scheme is proposed for stabilizing the unstable periodic orbits (UPO) of chaotic systems. It is assumed that the chaotic system has some linearly dependent unknown parameters which are stochastically time varying. The stochastic parameters are modeled through the Weiner process derivative. To demonstrate the effectiveness of the proposed technique it has been applied to the Lorenz, Chen and Rossler dynamical systems, as some case studies. Simulation results indicate that the proposed adaptive controller has a high performance in stabilizing the UPO of chaotic systems in noisy environment.

The shifting appearance/disappearance of holographic images and the dynamic ontology of perceptual and cognitive processes

Science.gov (United States)

Boissonnet, Philippe

2013-02-01

The French philosopher M Merleau-Ponty captured the dynamic of perception with his idea of the intertwining of perceiver and perceived. Light is what links them. In the case of holographic images, not only is spatial and colour perception the pure product of light, but this light information is always in the process of self-construction with our eyes, according to our movements and the point of view adopted. According to the aesthetic reception of a work of art, Holographic images vary greatly from those of cinema, photography and even every kind of digital 3D animation. This particular image's status truly makes perceptually apparent the "co-emergence" of light and our gaze. But holography never misleads us with respect to the precarious nature of our perceptions. We have no illusion as to the limits of our empirical understanding of the perceived reality. Holography, like our knowledge of the visible, thus brings to light the phenomenon of reality's "co-constitution" and contributes to a dynamic ontology of perceptual and cognitive processes. The cognitivist Francico Varela defines this as the paradigm of enaction,i which I will adapt and apply to the appearance/disappearance context of holographic images to bring out their affinities on a metaphorical level.

Molecular dynamics modeling of bonding two materials by atomic scale friction stir welding at different process parameters

Science.gov (United States)

Konovalenko S., Iv.; Psakhie, S. G.

2017-12-01

Using the molecular dynamics method, we simulated the atomic scale butt friction stir welding on two crystallites and varied the onset FSW tool plunge depth. The effects of the plunge depth value on the thermomechanical evolution of nanosized crystallites and mass transfer in the course of FSW have been studied. The increase of plunge depth values resulted in more intense heating and reducing the plasticized metal resistance to the tool movement. The mass transfer intensity was hardly dependent on the plunge depth value. The plunge depth was recommended to be used as a FSW process control parameter in addition to the commonly used ones.

Protein Dynamics in Organic Media at Varying Water Activity Studied by Molecular Dynamics Simulation

DEFF Research Database (Denmark)

Wedberg, Nils Hejle Rasmus Ingemar; Abildskov, Jens; Peters, Günther H.J.

2012-01-01

In nonaqueous enzymology, control of enzyme hydration is commonly approached by fixing the thermodynamic water activity of the medium. In this work, we present a strategy for evaluating the water activity in molecular dynamics simulations of proteins in water/organic solvent mixtures. The method...... relies on determining the water content of the bulk phase and uses a combination of Kirkwood−Buff theory and free energy calculations to determine corresponding activity coefficients. We apply the method in a molecular dynamics study of Candida antarctica lipase B in pure water and the organic solvents...

Benchmarking novel approaches for modelling species range dynamics.

Science.gov (United States)

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

2016-08-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches

Exogenic geomorphic processes dynamics at the Black Sea coast, Russia

Science.gov (United States)

Kuznetsova, Yulia; Tsvetkova, Daria

2017-04-01

Nowadays there is an obvious grow of anthropogenic load going on in many areas worldwide. Under such conditions, intensive activation of a number of exogenic geomorphic processes may be observed. Moreover, if natural environment is aggressive itself their dynamics and rates may reach enormous values. Our work is conducted at the Black Sea coast, known for its mountainous topography, wet subtropical climate and intensive anthropogenic development (especially during the last decade due to the recent Olympic games). We chose two key basins near Sochi, Russia to study a number of presented exogenic processes, including rill, gully and channel erosion, weathering, suffusion and piping, soil creep. A set of field study methods is used to monitor the processes dynamics since 2005 (and late 1970s for soil creep). In addition, soil erosion rates and landslide susceptibility were modelled to get information of the watersheds dynamics. This is ongoing work, but the results of the passed period of observations will be resented. Special attention is paid to the processes connectivity and their input into sediment redistribution over the river basins.

Dynamic process model of a plutonium oxalate precipitator. Final report

Energy Technology Data Exchange (ETDEWEB)

Miller, C.L.; Hammelman, J.E.; Borgonovi, G.M.

1977-11-01

In support of LLL material safeguards program, a dynamic process model was developed which simulates the performance of a plutonium (IV) oxalate precipitator. The plutonium oxalate precipitator is a component in the plutonium oxalate process for making plutonium oxide powder from plutonium nitrate. The model is based on state-of-the-art crystallization descriptive equations, the parameters of which are quantified through the use of batch experimental data. The dynamic model predicts performance very similar to general Hanford oxalate process experience. The utilization of such a process model in an actual plant operation could promote both process control and material safeguards control by serving as a baseline predictor which could give early warning of process upsets or material diversion. The model has been incorporated into a FORTRAN computer program and is also compatible with the DYNSYS 2 computer code which is being used at LLL for process modeling efforts.

Dynamic process model of a plutonium oxalate precipitator. Final report

International Nuclear Information System (INIS)

Miller, C.L.; Hammelman, J.E.; Borgonovi, G.M.

1977-11-01

In support of LLL material safeguards program, a dynamic process model was developed which simulates the performance of a plutonium (IV) oxalate precipitator. The plutonium oxalate precipitator is a component in the plutonium oxalate process for making plutonium oxide powder from plutonium nitrate. The model is based on state-of-the-art crystallization descriptive equations, the parameters of which are quantified through the use of batch experimental data. The dynamic model predicts performance very similar to general Hanford oxalate process experience. The utilization of such a process model in an actual plant operation could promote both process control and material safeguards control by serving as a baseline predictor which could give early warning of process upsets or material diversion. The model has been incorporated into a FORTRAN computer program and is also compatible with the DYNSYS 2 computer code which is being used at LLL for process modeling efforts

Emergency material allocation with time-varying supply-demand based on dynamic optimization method for river chemical spills.

Science.gov (United States)

Liu, Jie; Guo, Liang; Jiang, Jiping; Jiang, Dexun; Wang, Peng

2018-04-13

Aiming to minimize the damage caused by river chemical spills, efficient emergency material allocation is critical for an actual emergency rescue decision-making in a quick response. In this study, an emergency material allocation framework based on time-varying supply-demand constraint is developed to allocate emergency material, minimize the emergency response time, and satisfy the dynamic emergency material requirements in post-accident phases dealing with river chemical spills. In this study, the theoretically critical emergency response time is firstly obtained for the emergency material allocation system to select a series of appropriate emergency material warehouses as potential supportive centers. Then, an enumeration method is applied to identify the practically critical emergency response time, the optimum emergency material allocation and replenishment scheme. Finally, the developed framework is applied to a computational experiment based on south-to-north water transfer project in China. The results illustrate that the proposed methodology is a simple and flexible tool for appropriately allocating emergency material to satisfy time-dynamic demands during emergency decision-making. Therefore, the decision-makers can identify an appropriate emergency material allocation scheme in a balance between time-effective and cost-effective objectives under the different emergency pollution conditions.

Time varying voltage combustion control and diagnostics sensor

Science.gov (United States)

Chorpening, Benjamin T [Morgantown, WV; Thornton, Jimmy D [Morgantown, WV; Huckaby, E David [Morgantown, WV; Fincham, William [Fairmont, WV

2011-04-19

A time-varying voltage is applied to an electrode, or a pair of electrodes, of a sensor installed in a fuel nozzle disposed adjacent the combustion zone of a continuous combustion system, such as of the gas turbine engine type. The time-varying voltage induces a time-varying current in the flame which is measured and used to determine flame capacitance using AC electrical circuit analysis. Flame capacitance is used to accurately determine the position of the flame from the sensor and the fuel/air ratio. The fuel and/or air flow rate (s) is/are then adjusted to provide reduced flame instability problems such as flashback, combustion dynamics and lean blowout, as well as reduced emissions. The time-varying voltage may be an alternating voltage and the time-varying current may be an alternating current.

A Thermodynamic Library for Simulation and Optimization of Dynamic Processes

DEFF Research Database (Denmark)

Ritschel, Tobias Kasper Skovborg; Gaspar, Jozsef; Jørgensen, John Bagterp

2017-01-01

Process system tools, such as simulation and optimization of dynamic systems, are widely used in the process industries for development of operational strategies and control for process systems. These tools rely on thermodynamic models and many thermodynamic models have been developed for different...... compounds and mixtures. However, rigorous thermodynamic models are generally computationally intensive and not available as open-source libraries for process simulation and optimization. In this paper, we describe the application of a novel open-source rigorous thermodynamic library, ThermoLib, which...... is designed for dynamic simulation and optimization of vapor-liquid processes. ThermoLib is implemented in Matlab and C and uses cubic equations of state to compute vapor and liquid phase thermodynamic properties. The novelty of ThermoLib is that it provides analytical first and second order derivatives...

Dynamic Study of Feed-Effluent Heat Exchanger Addition on Double Bed Configuration Ammonia Reactor System within Varied Quenching Ratio

Directory of Open Access Journals (Sweden)

Adhi Tri Partono

2018-01-01

Full Text Available Ammonia is one of the most important industrial commodity due to its wide function. Ammonia synthesis reaction is an exotermic reaction. Therefore, Feed-Effluent Heat Exchanger (FEHE is added to increase thermal efficiency. However, FEHE could lead the process to experience hysteresis phenomenon due to interaction between equipments as one steady state T feed could result several T outlet. Hysteresis phenomenon may result asset losses like explosion, leakage, and loosing material integrity. Double bed reactor configuration allows us to use several operating parameters as variation to overcome hysteresis. In this review, quenching ratio was chosen to be that varied parameter. This study aims to determine how quenching ratio affects hysteresis zone by utilizing Aspen Hysys® V8.8 as simulation tool. Simulation showed that quenching ratio would narrow hysteresis zone yet increased extinction temperature that lower the conversion. Conversion profile showed that 0.2 quenching ratio got the highest conversion for system with bed volume ratio 2:1 while total volume was 30 m3. However, the feed temperature was fallen at hysteresis zone. Dynamic simulation showed that highest conversion feed temperature (10%ΔTf above extinct temperature was still able to preserve stability with descending temperature approach. Hysteresis itself started to occur at 1.7%ΔTf above extinct temperature

Quantifying chaotic dynamics from integrate-and-fire processes

Energy Technology Data Exchange (ETDEWEB)

Pavlov, A. N. [Department of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov (Russian Federation); Saratov State Technical University, Politehnicheskaya Str. 77, 410054 Saratov (Russian Federation); Pavlova, O. N. [Department of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov (Russian Federation); Mohammad, Y. K. [Department of Physics, Saratov State University, Astrakhanskaya Str. 83, 410012 Saratov (Russian Federation); Tikrit University Salahudin, Tikrit Qadisiyah, University Str. P.O. Box 42, Tikrit (Iraq); Kurths, J. [Potsdam Institute for Climate Impact Research, Telegraphenberg A 31, 14473 Potsdam (Germany); Institute of Physics, Humboldt University Berlin, 12489 Berlin (Germany)

2015-01-15

Characterizing chaotic dynamics from integrate-and-fire (IF) interspike intervals (ISIs) is relatively easy performed at high firing rates. When the firing rate is low, a correct estimation of Lyapunov exponents (LEs) describing dynamical features of complex oscillations reflected in the IF ISI sequences becomes more complicated. In this work we discuss peculiarities and limitations of quantifying chaotic dynamics from IF point processes. We consider main factors leading to underestimated LEs and demonstrate a way of improving numerical determining of LEs from IF ISI sequences. We show that estimations of the two largest LEs can be performed using around 400 mean periods of chaotic oscillations in the regime of phase-coherent chaos. Application to real data is discussed.

Dynamics Explorer science data processing system

International Nuclear Information System (INIS)

Smith, P.H.; Freeman, C.H.; Hoffman, R.A.

1981-01-01

The Dynamics Explorer project has acquired the ground data processing system from the Atmosphere Explorer project to provide a central computer facility for the data processing, data management and data analysis activities of the investigators. Access to this system is via remote terminals at the investigators' facilities, which provide ready access to the data sets derived from groups of instruments on both spacecraft. The original system has been upgraded with both new hardware and enhanced software systems. These new systems include color and grey scale graphics terminals, an augmentation computer, micrographies facility, a versatile data base with a directory and data management system, and graphics display software packages. (orig.)

Time-varying acceleration coefficients IPSO for solving dynamic economic dispatch with non-smooth cost function

International Nuclear Information System (INIS)

Mohammadi-ivatloo, Behnam; Rabiee, Abbas; Ehsan, Mehdi

2012-01-01

Highlights: ► New approach to solve power systems dynamic economic dispatch. ► Considering Valve-point effect, prohibited operation zones. ► Proposing TVAC-IPSO algorithm. - Abstract: The objective of the dynamic economic dispatch (DED) problem is to schedule power generation for the online units for a given time horizon economically, satisfying various operational constraints. Due to the effect of valve-point effects and prohibited operating zones (POZs) in the generating units cost functions, DED problem is a highly non-linear and non-convex optimization problem. The DED problem even may be more complicated if transmission losses and ramp-rate constraints are taken into account. This paper presents a novel and heuristic algorithm to solve DED problem of generating units, by employing time varying acceleration coefficients iteration particle swarm optimization (TVAC-IPSO) method. The effectiveness of the proposed method is examined and validated by carrying out extensive tests on different test systems, i.e. 5-unit and 10-unit test systems. Valve-point effects, POZs and ramp-rate constraints along with transmission losses are considered. To examine the efficiency of the proposed TVAC-IPSO algorithm, comprehensive studies are carried out, which compare convergence properties of the proposed TVAC-IPSO approach with conventional PSO algorithm, in addition to the other recently reported approaches. Numerical results show that the TVAC-IPSO method has good convergence properties and the generation costs resulted from the proposed method are lower than other algorithms reported in recent literature.

Dynamics of nonlinear oscillators with time-varying conjugate coupling

Indian Academy of Sciences (India)

oscillators. We analyze the behavior of coupled systems with respect to the coupling switching frequency using ..... are of potential utility in appropriate design strategies and/or understanding of complex systems with dynamic interaction ...

Modeling Dynamic Systems with Efficient Ensembles of Process-Based Models.

Directory of Open Access Journals (Sweden)

Nikola Simidjievski

Full Text Available Ensembles are a well established machine learning paradigm, leading to accurate and robust models, predominantly applied to predictive modeling tasks. Ensemble models comprise a finite set of diverse predictive models whose combined output is expected to yield an improved predictive performance as compared to an individual model. In this paper, we propose a new method for learning ensembles of process-based models of dynamic systems. The process-based modeling paradigm employs domain-specific knowledge to automatically learn models of dynamic systems from time-series observational data. Previous work has shown that ensembles based on sampling observational data (i.e., bagging and boosting, significantly improve predictive performance of process-based models. However, this improvement comes at the cost of a substantial increase of the computational time needed for learning. To address this problem, the paper proposes a method that aims at efficiently learning ensembles of process-based models, while maintaining their accurate long-term predictive performance. This is achieved by constructing ensembles with sampling domain-specific knowledge instead of sampling data. We apply the proposed method to and evaluate its performance on a set of problems of automated predictive modeling in three lake ecosystems using a library of process-based knowledge for modeling population dynamics. The experimental results identify the optimal design decisions regarding the learning algorithm. The results also show that the proposed ensembles yield significantly more accurate predictions of population dynamics as compared to individual process-based models. Finally, while their predictive performance is comparable to the one of ensembles obtained with the state-of-the-art methods of bagging and boosting, they are substantially more efficient.

Fast engineering optimization: A novel highly effective control parameterization approach for industrial dynamic processes.

Science.gov (United States)

Liu, Ping; Li, Guodong; Liu, Xinggao

2015-09-01

Control vector parameterization (CVP) is an important approach of the engineering optimization for the industrial dynamic processes. However, its major defect, the low optimization efficiency caused by calculating the relevant differential equations in the generated nonlinear programming (NLP) problem repeatedly, limits its wide application in the engineering optimization for the industrial dynamic processes. A novel highly effective control parameterization approach, fast-CVP, is first proposed to improve the optimization efficiency for industrial dynamic processes, where the costate gradient formulae is employed and a fast approximate scheme is presented to solve the differential equations in dynamic process simulation. Three well-known engineering optimization benchmark problems of the industrial dynamic processes are demonstrated as illustration. The research results show that the proposed fast approach achieves a fine performance that at least 90% of the computation time can be saved in contrast to the traditional CVP method, which reveals the effectiveness of the proposed fast engineering optimization approach for the industrial dynamic processes. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Nonlinear Dynamics Modeling and Analysis of Torsional Spring-Loaded Antibacklash Gear with Time-Varying Meshing Stiffness and Friction

Directory of Open Access Journals (Sweden)

Zheng Yang

2013-01-01

Full Text Available Torsional spring-loaded antibacklash gear which can improve the transmission precision is widely used in many precision transmission fields. It is very important to investigate the dynamic characteristics of antibacklash gear. In the paper, applied force analysis is completed in detail. Then, defining the starting point of double-gear meshing as initial position, according to the meshing characteristic of antibacklash gear, single- or double-tooth meshing states of two gear pairs and the transformation relationship at any moment are determined. Based on this, a nonlinear model of antibacklash gear with time-varying friction and meshing stiffness is proposed. The influences of friction and variations of torsional spring stiffness, damping ratio and preload on dynamic transmission error (DTE are analyzed by numerical calculation and simulation, and the results show that antibacklash gear can increase the composite meshing stiffness; when the torsional spring stiffness is large enough, the oscillating components of the DTE (ODTE and the RMS of the DTE (RDTE trend to be a constant value; the variations of ODTE and RDTE are not significant, unless preload exceeds a certain value.

Dynamic networks: Presentation held at the Workshop "Beyond Workflow Management: Supporting Dynamic Organizational Processes", CSCW 2000. 2. Dezember 2000, Philadelphia

OpenAIRE

Fuchs-Kittowski, F.

2000-01-01

Complex, dynamic organizational processes, especially problem-solving processes, require that the design and control of the cooperative work process is left to the cooperating persons. In reality of social organizations, a permanent change between extraneous- and self-organization is taking place. By integrating communication tools with application sharing synchronous CSCW systems can support dynamic workflows without restraining the self-organizing social processes of the people involved. .

Efficient rare-event simulation for multiple jump events in regularly varying random walks and compound Poisson processes

NARCIS (Netherlands)

B. Chen (Bohan); J. Blanchet; C.H. Rhee (Chang-Han); A.P. Zwart (Bert)

2017-01-01

textabstractWe propose a class of strongly efficient rare event simulation estimators for random walks and compound Poisson processes with a regularly varying increment/jump-size distribution in a general large deviations regime. Our estimator is based on an importance sampling strategy that hinges

Nonlinear control of linear parameter varying systems with applications to hypersonic vehicles

Science.gov (United States)

Wilcox, Zachary Donald

The focus of this dissertation is to design a controller for linear parameter varying (LPV) systems, apply it specifically to air-breathing hypersonic vehicles, and examine the interplay between control performance and the structural dynamics design. Specifically a Lyapunov-based continuous robust controller is developed that yields exponential tracking of a reference model, despite the presence of bounded, nonvanishing disturbances. The hypersonic vehicle has time varying parameters, specifically temperature profiles, and its dynamics can be reduced to an LPV system with additive disturbances. Since the HSV can be modeled as an LPV system the proposed control design is directly applicable. The control performance is directly examined through simulations. A wide variety of applications exist that can be effectively modeled as LPV systems. In particular, flight systems have historically been modeled as LPV systems and associated control tools have been applied such as gain-scheduling, linear matrix inequalities (LMIs), linear fractional transformations (LFT), and mu-types. However, as the type of flight environments and trajectories become more demanding, the traditional LPV controllers may no longer be sufficient. In particular, hypersonic flight vehicles (HSVs) present an inherently difficult problem because of the nonlinear aerothermoelastic coupling effects in the dynamics. HSV flight conditions produce temperature variations that can alter both the structural dynamics and flight dynamics. Starting with the full nonlinear dynamics, the aerothermoelastic effects are modeled by a temperature dependent, parameter varying state-space representation with added disturbances. The model includes an uncertain parameter varying state matrix, an uncertain parameter varying non-square (column deficient) input matrix, and an additive bounded disturbance. In this dissertation, a robust dynamic controller is formulated for a uncertain and disturbed LPV system. The developed

Dynamic modeling of ultrafiltration membranes for whey separation processes

NARCIS (Netherlands)

Saltik, M.B.; Ozkan, L.; Jacobs, M.; van der Padt, A.

2017-01-01

In this paper, we present a control relevant rigorous dynamic model for an ultrafiltration membrane unit in a whey separation process. The model consists of a set of differential algebraic equations and is developed for online model based applications such as model based control and process

Bit-level plane image encryption based on coupled map lattice with time-varying delay

Science.gov (United States)

Lv, Xiupin; Liao, Xiaofeng; Yang, Bo

2018-04-01

Most of the existing image encryption algorithms had two basic properties: confusion and diffusion in a pixel-level plane based on various chaotic systems. Actually, permutation in a pixel-level plane could not change the statistical characteristics of an image, and many of the existing color image encryption schemes utilized the same method to encrypt R, G and B components, which means that the three color components of a color image are processed three times independently. Additionally, dynamical performance of a single chaotic system degrades greatly with finite precisions in computer simulations. In this paper, a novel coupled map lattice with time-varying delay therefore is applied in color images bit-level plane encryption to solve the above issues. Spatiotemporal chaotic system with both much longer period in digitalization and much excellent performances in cryptography is recommended. Time-varying delay embedded in coupled map lattice enhances dynamical behaviors of the system. Bit-level plane image encryption algorithm has greatly reduced the statistical characteristics of an image through the scrambling processing. The R, G and B components cross and mix with one another, which reduces the correlation among the three components. Finally, simulations are carried out and all the experimental results illustrate that the proposed image encryption algorithm is highly secure, and at the same time, also demonstrates superior performance.

Fluctuating interaction network and time-varying stability of a natural fish community

Science.gov (United States)

Ushio, Masayuki; Hsieh, Chih-Hao; Masuda, Reiji; Deyle, Ethan R.; Ye, Hao; Chang, Chun-Wei; Sugihara, George; Kondoh, Michio

2018-02-01

Ecological theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current ecological theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of ecological communities in nature.

Analytical Modeling of Transient Process In Terms of One-Dimensional Problem of Dynamics With Kinematic Action

Directory of Open Access Journals (Sweden)

Kravets Victor V.

2016-05-01

Full Text Available One-dimensional dynamic design of a component characterized by inertia coefficient, elastic coefficient, and coefficient of energy dispersion. The component is affected by external action in the form of time-independent initial kinematic disturbances and varying ones. Mathematical model of component dynamics as well as a new form of analytical representation of transient in terms of one-dimensional problem of kinematic effect is provided. Dynamic design of a component is being carried out according to a theory of modal control.

Control-focused, nonlinear and time-varying modelling of dielectric elastomer actuators with frequency response analysis

International Nuclear Information System (INIS)

Jacobs, William R; Dodd, Tony J; Anderson, Sean R; Wilson, Emma D; Porrill, John; Assaf, Tareq; Rossiter, Jonathan

2015-01-01

Current models of dielectric elastomer actuators (DEAs) are mostly constrained to first principal descriptions that are not well suited to the application of control design due to their computational complexity. In this work we describe an integrated framework for the identification of control focused, data driven and time-varying DEA models that allow advanced analysis of nonlinear system dynamics in the frequency-domain. Experimentally generated input–output data (voltage-displacement) was used to identify control-focused, nonlinear and time-varying dynamic models of a set of film-type DEAs. The model description used was the nonlinear autoregressive with exogenous input structure. Frequency response analysis of the DEA dynamics was performed using generalized frequency response functions, providing insight and a comparison into the time-varying dynamics across a set of DEA actuators. The results demonstrated that models identified within the presented framework provide a compact and accurate description of the system dynamics. The frequency response analysis revealed variation in the time-varying dynamic behaviour of DEAs fabricated to the same specifications. These results suggest that the modelling and analysis framework presented here is a potentially useful tool for future work in guiding DEA actuator design and fabrication for application domains such as soft robotics. (paper)

Time-Varying Combinations of Bayesian Dynamic Models and Equity Momentum Strategies

NARCIS (Netherlands)

N. Basturk (Nalan); S. Grassi (Stefano); L.F. Hoogerheide (Lennart); H.K. van Dijk (Herman)

2016-01-01

markdownabstractA novel dynamic asset-allocation approach is proposed where portfolios as well as portfolio strategies are updated at every decision period based on their past performance. For modeling, a general class of models is specified that combines a dynamic factor and a vector autoregressive

A Diagnostic System for Speed-Varying Motor Rotary Faults

Directory of Open Access Journals (Sweden)

Chwan-Lu Tseng

2014-01-01

Full Text Available This study proposed an intelligent rotary fault diagnostic system for motors. A sensorless rotational speed detection method and an improved dynamic structural neural network are used. Moreover, to increase the convergence speed of training, a terminal attractor method and a hybrid discriminant analysis are also adopted. The proposed method can be employed to detect the rotary frequencies of motors with varying speeds and can enhance the discrimination of motor faults. To conduct the experiments, this study used wireless sensor nodes to transmit vibration data and employed MATLAB to write codes for functional modules, including the signal processing, sensorless rotational speed estimation, neural network, and stochastic process control chart. Additionally, Visual Basic software was used to create an integrated human-machine interface. The experimental results regarding the test of equipment faults indicated that the proposed novel diagnostic system can effectively estimate rotational speeds and provide superior ability of motor fault discrimination with fast training convergence.

Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

Science.gov (United States)

Popovici, Alexandru; Zaal, Peter M. T.; Pool, Daan M.

2017-01-01

A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.

Implementing Firm Dynamic Capabilities Through the Concept Design Process

DEFF Research Database (Denmark)

Nedergaard, Nicky; Jones, Richard

2011-01-01

It is well understood that firms operating in highly dynamic and fluid markets need to possess strong dynamic capabilities of sensing (market trajectories), seizing (to capitalise on these trajectories), and transformation (in order to implement sustainable strategies). Less understood is how firms...... actually implement these capabilities. A conceptual model showing how managing concept design processes can help firms systematically develop dynamic capabilities and help bridge the gap between the market-oriented and resource-focused strategic perspectives is presented. By placing this model in a design......-driven innovation perspective three theoretical propositions is derived explicating both the paper’s implementation approach to dynamic capabilities as well as new ways of understanding these capabilities. Concluding remarks are made discussing both the paper’s contribution to the strategic marketing literature...

The Adjoint Method for Gradient-based Dynamic Optimization of UV Flash Processes

DEFF Research Database (Denmark)

Ritschel, Tobias Kasper Skovborg; Capolei, Andrea; Jørgensen, John Bagterp

2017-01-01

This paper presents a novel single-shooting algorithm for gradient-based solution of optimal control problems with vapor-liquid equilibrium constraints. Dynamic optimization of UV flash processes is relevant in nonlinear model predictive control of distillation columns, certain two-phase flow pro......-component flash process which demonstrate the importance of the optimization solver, the compiler, and the linear algebra software for the efficiency of dynamic optimization of UV flash processes....

Molecular dynamics study of dynamic and structural properties of supercooled liquid and glassy iron in the rapid-cooling processes

Energy Technology Data Exchange (ETDEWEB)

Cao, Qi-Long; Huang, Duo-Hui; Yang, Jun-Sheng; Wan, Min-Jie; Wang, Fan-Hou, E-mail: eatonch@gmail.com

2014-10-01

Molecular dynamics simulations were applied to study the dynamic and structural properties of supercooled liquid and glassy iron in the rapid-cooling processes. The mean-square displacement and the non-Gaussian parameter were used to describe the dynamic properties. The evolution of structural properties was investigated using the pair distribution functions and bond-angle distribution functions. Results for dynamic and structural relaxations indicate that the dynamic features are consistently correlated with the structure evolution, and there are three temperature regions as the temperature decreases: (1) at higher temperatures (1500 K, 1300 K, and 1100 K), the system remains in the liquid characteristics during the overall relaxation process. (2) At medial temperatures (1050 K, 900 K, and 700 K), a fast β-relaxation is followed by a much slower α-relaxation. There is a little change in the structural properties in the β-relaxation region, while major configuration rearrangements occurred in the α-relaxation range and the crystallization process was completed at the end of α-relaxation region. (3) At lower temperature (500 K), the system shows glassy characteristics during the overall relaxation process. In addition, the melting temperature, glass transition temperature and diffusion coefficients of supercooled liquid iron are also computed.

Effect of Food Regulation on the Spanish Food Processing Industry: A Dynamic Productivity Analysis.

Science.gov (United States)

Kapelko, Magdalena; Oude Lansink, Alfons; Stefanou, Spiro E

2015-01-01

This article develops the decomposition of the dynamic Luenberger productivity growth indicator into dynamic technical change, dynamic technical inefficiency change and dynamic scale inefficiency change in the dynamic directional distance function context using Data Envelopment Analysis. These results are used to investigate for the Spanish food processing industry the extent to which dynamic productivity growth and its components are affected by the introduction of the General Food Law in 2002 (Regulation (EC) No 178/2002). The empirical application uses panel data of Spanish meat, dairy, and oils and fats industries over the period 1996-2011. The results suggest that in the oils and fats industry the impact of food regulation on dynamic productivity growth is negative initially and then positive over the long run. In contrast, the opposite pattern is observed for the meat and dairy processing industries. The results further imply that firms in the meat processing and oils and fats industries face similar impacts of food safety regulation on dynamic technical change, dynamic inefficiency change and dynamic scale inefficiency change.

Effect of Food Regulation on the Spanish Food Processing Industry: A Dynamic Productivity Analysis

Science.gov (United States)

Kapelko, Magdalena; Lansink, Alfons Oude; Stefanou, Spiro E.

2015-01-01

This article develops the decomposition of the dynamic Luenberger productivity growth indicator into dynamic technical change, dynamic technical inefficiency change and dynamic scale inefficiency change in the dynamic directional distance function context using Data Envelopment Analysis. These results are used to investigate for the Spanish food processing industry the extent to which dynamic productivity growth and its components are affected by the introduction of the General Food Law in 2002 (Regulation (EC) No 178/2002). The empirical application uses panel data of Spanish meat, dairy, and oils and fats industries over the period 1996-2011. The results suggest that in the oils and fats industry the impact of food regulation on dynamic productivity growth is negative initially and then positive over the long run. In contrast, the opposite pattern is observed for the meat and dairy processing industries. The results further imply that firms in the meat processing and oils and fats industries face similar impacts of food safety regulation on dynamic technical change, dynamic inefficiency change and dynamic scale inefficiency change. PMID:26057878

Dynamical processes in atomic and molecular physics

CERN Document Server

Ogurtsov, Gennadi

2012-01-01

Atomic and molecular physics underlie a basis for our knowledge of fundamental processes in nature and technology and in such applications as solid state physics, chemistry and biology. In recent years, atomic and molecular physics has undergone a revolutionary change due to great achievements in computing and experimental techniques. As a result, it has become possible to obtain information both on atomic and molecular characteristics and on dynamics of atomic and molecular processes. This e-book highlights the present state of investigations in the field of atomic and molecular physics. Rece

Entropy Rate of Time-Varying Wireless Networks

DEFF Research Database (Denmark)

Cika, Arta; Badiu, Mihai Alin; Coon, Justin P.

2018-01-01

In this paper, we present a detailed framework to analyze the evolution of the random topology of a time-varying wireless network via the information theoretic notion of entropy rate. We consider a propagation channel varying over time with random node positions in a closed space and Rayleigh...... fading affecting the connections between nodes. The existence of an edge between two nodes at given locations is modeled by a Markov chain, enabling memory effects in network dynamics. We then derive a lower and an upper bound on the entropy rate of the spatiotemporal network. The entropy rate measures...

Network Dynamics of Innovation Processes

Science.gov (United States)

Iacopini, Iacopo; Milojević, Staša; Latora, Vito

2018-01-01

We introduce a model for the emergence of innovations, in which cognitive processes are described as random walks on the network of links among ideas or concepts, and an innovation corresponds to the first visit of a node. The transition matrix of the random walk depends on the network weights, while in turn the weight of an edge is reinforced by the passage of a walker. The presence of the network naturally accounts for the mechanism of the "adjacent possible," and the model reproduces both the rate at which novelties emerge and the correlations among them observed empirically. We show this by using synthetic networks and by studying real data sets on the growth of knowledge in different scientific disciplines. Edge-reinforced random walks on complex topologies offer a new modeling framework for the dynamics of correlated novelties and are another example of coevolution of processes and networks.

Interactive exploration of large-scale time-varying data using dynamic tracking graphs

KAUST Repository

Widanagamaachchi, W.

2012-10-01

Exploring and analyzing the temporal evolution of features in large-scale time-varying datasets is a common problem in many areas of science and engineering. One natural representation of such data is tracking graphs, i.e., constrained graph layouts that use one spatial dimension to indicate time and show the "tracks" of each feature as it evolves, merges or disappears. However, for practical data sets creating the corresponding optimal graph layouts that minimize the number of intersections can take hours to compute with existing techniques. Furthermore, the resulting graphs are often unmanageably large and complex even with an ideal layout. Finally, due to the cost of the layout, changing the feature definition, e.g. by changing an iso-value, or analyzing properly adjusted sub-graphs is infeasible. To address these challenges, this paper presents a new framework that couples hierarchical feature definitions with progressive graph layout algorithms to provide an interactive exploration of dynamically constructed tracking graphs. Our system enables users to change feature definitions on-the-fly and filter features using arbitrary attributes while providing an interactive view of the resulting tracking graphs. Furthermore, the graph display is integrated into a linked view system that provides a traditional 3D view of the current set of features and allows a cross-linked selection to enable a fully flexible spatio-temporal exploration of data. We demonstrate the utility of our approach with several large-scale scientific simulations from combustion science. © 2012 IEEE.

Welding quality evaluation of resistance spot welding using the time-varying inductive reactance signal

Science.gov (United States)

Zhang, Hongjie; Hou, Yanyan; Yang, Tao; Zhang, Qian; Zhao, Jian

2018-05-01

In the spot welding process, a high alternating current is applied, resulting in a time-varying electromagnetic field surrounding the welder. When measuring the welding voltage signal, the impedance of the measuring circuit consists of two parts: dynamic resistance relating to weld nugget nucleation event and inductive reactance caused by mutual inductance. The aim of this study is to develop a method to acquire the dynamic reactance signal and to discuss the possibility of using this signal to evaluate the weld quality. For this purpose, a series of experiments were carried out. The reactance signals under different welding conditions were compared and the results showed that the morphological feature of the reactance signal was closely related to the welding current and it was also significantly influenced by some abnormal welding conditions. Some features were extracted from the reactance signal and combined to construct weld nugget strength and diameter prediction models based on the radial basis function (RBF) neural network. In addition, several features were also used to monitor the expulsion in the welding process by using Fisher linear discriminant analysis. The results indicated that using the dynamic reactance signal to evaluate weld quality is possible and feasible.

Application of processing maps in the optimization of the parameters of a hot working process. Part 2. Processing maps of a microalloyed medium carbon steel

International Nuclear Information System (INIS)

Al Omar, A.; Cabrera, J.M.; Prado, J.M.

1997-01-01

Part 1 of this work presents a revision of the general characteristics of the so called dynamic materials model on which processing maps are developed. In this part following the methodology described in part 1, processing maps of a microalloyed medium carbon steel are developed over a temperature range varying from 900 to 1.150 degree centigree at different true strain rates ranging from 10''-4 to 10s''-1. The analysis of these maps revealed a domain of dynamic recrystallization centred at about 1.1.50 degree centigree and strain rate 10 s''-1 and a domain of dynamic recovery centred at 900 degree centigree and 0,1 s''-1. (Author) 20 refs

Time-varying economic dominance in financial markets: A bistable dynamics approach

Science.gov (United States)

He, Xue-Zhong; Li, Kai; Wang, Chuncheng

2018-05-01

By developing a continuous-time heterogeneous agent financial market model of multi-assets traded by fundamental and momentum investors, we provide a potential mechanism for generating time-varying dominance between fundamental and non-fundamental in financial markets. We show that investment constraints lead to the coexistence of a locally stable fundamental steady state and a locally stable limit cycle around the fundamental, characterized by a Bautin bifurcation. This provides a mechanism for market prices to switch stochastically between the two persistent but very different market states, leading to the coexistence and time-varying dominance of seemingly controversial efficient market and price momentum over different time periods. The model also generates other financial market stylized facts, such as spillover effects in both momentum and volatility, market booms, crashes, and correlation reduction due to cross-sectional momentum trading. Empirical evidence based on the U.S. market supports the main findings. The mechanism developed in this paper can be used to characterize time-varying economic dominance in economics and finance in general.

Lane-changing model with dynamic consideration of driver's propensity

Science.gov (United States)

Wang, Xiaoyuan; Wang, Jianqiang; Zhang, Jinglei; Ban, Xuegang Jeff

2015-07-01

Lane-changing is the driver's selection result of the satisfaction degree in different lane driving conditions. There are many different factors influencing lane-changing behavior, such as diversity, randomicity and difficulty of measurement. So it is hard to accurately reflect the uncertainty of drivers' lane-changing behavior. As a result, the research of lane-changing models is behind that of car-following models. Driver's propensity is her/his emotion state or the corresponding preference of a decision or action toward the real objective traffic situations under the influence of various dynamic factors. It represents the psychological characteristics of the driver in the process of vehicle operation and movement. It is an important factor to influence lane-changing. In this paper, dynamic recognition of driver's propensity is considered during simulation based on its time-varying discipline and the analysis of the driver's psycho-physic characteristics. The Analytic Hierarchy Process (AHP) method is used to quantify the hierarchy of driver's dynamic lane-changing decision-making process, especially the influence of the propensity. The model is validated using real data. Test results show that the developed lane-changing model with the dynamic consideration of a driver's time-varying propensity and the AHP method are feasible and with improved accuracy.

Flexible Demand Management under Time-Varying Prices

Science.gov (United States)

Liang, Yong

optimization problem when the objective is to minimize the expected total cost and discomfort, then since the decision maker is likely to be risk-averse, and she wants to protect herself from price spikes, we study the robust optimization problem to address the risk-aversion of the decision maker. We conduct numerical studies to evaluate the price of robustness. Next, we present a detailed model that manages multiple types of flexible demand in the absence of knowledge regarding the distributions of related stochastic processes. Specifically, we consider the case in which time-varying prices with general structures are offered to users, and an energy management system for each household makes optimal energy usage, storage, and trading decisions according to the preferences of users. Because of the uncertainties associated with electricity prices, local generation, and the arrival processes of demand, we formulate a stochastic dynamic programming model, and outline a novel and tractable ADP approach to overcome the curses of dimensionality. Then, we perform numerical studies, whose results demonstrate the effectiveness of the ADP approach. At last, we propose another approximation approach based on Q-learning. In addition, we also develop another decentralization-based heuristic. Both the Q-learning approach and the heuristic make necessary assumptions on the knowledge of information, and each of them has unique advantages. We conduct numerical studies on a testing problem. The simulation results show that both the Q-learning and the decentralization based heuristic approaches work well. Lastly, we conclude the paper with some discussions on future extension directions.

Varying acoustic-phonemic ambiguity reveals that talker normalization is obligatory in speech processing.

Science.gov (United States)

Choi, Ja Young; Hu, Elly R; Perrachione, Tyler K

2018-04-01

The nondeterministic relationship between speech acoustics and abstract phonemic representations imposes a challenge for listeners to maintain perceptual constancy despite the highly variable acoustic realization of speech. Talker normalization facilitates speech processing by reducing the degrees of freedom for mapping between encountered speech and phonemic representations. While this process has been proposed to facilitate the perception of ambiguous speech sounds, it is currently unknown whether talker normalization is affected by the degree of potential ambiguity in acoustic-phonemic mapping. We explored the effects of talker normalization on speech processing in a series of speeded classification paradigms, parametrically manipulating the potential for inconsistent acoustic-phonemic relationships across talkers for both consonants and vowels. Listeners identified words with varying potential acoustic-phonemic ambiguity across talkers (e.g., beet/boat vs. boot/boat) spoken by single or mixed talkers. Auditory categorization of words was always slower when listening to mixed talkers compared to a single talker, even when there was no potential acoustic ambiguity between target sounds. Moreover, the processing cost imposed by mixed talkers was greatest when words had the most potential acoustic-phonemic overlap across talkers. Models of acoustic dissimilarity between target speech sounds did not account for the pattern of results. These results suggest (a) that talker normalization incurs the greatest processing cost when disambiguating highly confusable sounds and (b) that talker normalization appears to be an obligatory component of speech perception, taking place even when the acoustic-phonemic relationships across sounds are unambiguous.

Time-varying correlation and common structures in volatility

NARCIS (Netherlands)

Liu, Yang

2016-01-01

This thesis studies time series properties of the covariance structure of multivariate asset returns. First, the time-varying feature of correlation is investigated at the intraday level with a new correlation model incorporating the intraday correlation dynamics. Second, the thesis develops a

Web Services Support for Dynamic Business Process Outsourcing

NARCIS (Netherlands)

Grefen, P.W.P.J.; Ludwig, Heiko; Dan, Asit; Angelov, S.A.

2003-01-01

Outsourcing of business processes is crucial for organizations to be effective, efficient and flexible. To meet fast-changing market conditions, dynamic outsourcing is required, in which business relationships are established and enacted on-the-fly in an adaptive, fine-grained way unrestricted by

Experimental design for dynamics identification of cellular processes.

Science.gov (United States)

Dinh, Vu; Rundell, Ann E; Buzzard, Gregery T

2014-03-01

We address the problem of using nonlinear models to design experiments to characterize the dynamics of cellular processes by using the approach of the Maximally Informative Next Experiment (MINE), which was introduced in W. Dong et al. (PLoS ONE 3(8):e3105, 2008) and independently in M.M. Donahue et al. (IET Syst. Biol. 4:249-262, 2010). In this approach, existing data is used to define a probability distribution on the parameters; the next measurement point is the one that yields the largest model output variance with this distribution. Building upon this approach, we introduce the Expected Dynamics Estimator (EDE), which is the expected value using this distribution of the output as a function of time. We prove the consistency of this estimator (uniform convergence to true dynamics) even when the chosen experiments cluster in a finite set of points. We extend this proof of consistency to various practical assumptions on noisy data and moderate levels of model mismatch. Through the derivation and proof, we develop a relaxed version of MINE that is more computationally tractable and robust than the original formulation. The results are illustrated with numerical examples on two nonlinear ordinary differential equation models of biomolecular and cellular processes.

The representational dynamics of task and object processing in humans

Science.gov (United States)

Bankson, Brett B; Harel, Assaf

2018-01-01

Despite the importance of an observer’s goals in determining how a visual object is categorized, surprisingly little is known about how humans process the task context in which objects occur and how it may interact with the processing of objects. Using magnetoencephalography (MEG), functional magnetic resonance imaging (fMRI) and multivariate techniques, we studied the spatial and temporal dynamics of task and object processing. Our results reveal a sequence of separate but overlapping task-related processes spread across frontoparietal and occipitotemporal cortex. Task exhibited late effects on object processing by selectively enhancing task-relevant object features, with limited impact on the overall pattern of object representations. Combining MEG and fMRI data, we reveal a parallel rise in task-related signals throughout the cerebral cortex, with an increasing dominance of task over object representations from early to higher visual areas. Collectively, our results reveal the complex dynamics underlying task and object representations throughout human cortex. PMID:29384473

Numerical studies of neon gas-puff Z-pinch dynamic processes

International Nuclear Information System (INIS)

Ning Cheng; Yang Zhenhua; Ding Ning

2003-01-01

Dynamic processes of neon gas-puff Z-pinch are studied numerically in this paper. A high temperature plasma with a high density can be generated in the process. Based on some physical analysis and assumption, a set of equations of one-dimensional Lagrangian radiation magneto-hydrodynamic (MHD) and its code are developed to solve the problem. Spatio-temporal distributions of plasma parameters in the processes are obtained, and their dynamic variations show that the major results are self-consistent. The duration for the plasma pinched to centre, as well as the width and the total energy of the x-ray pulse caused by the Z-pinch are in reasonable agreement with experimental results of GAMBLE-II. A zipping effect is also clearly shown in the simulation

Molecular dynamics simulation of self-diffusion processes in titanium in bulk material, on grain junctions and on surface.

Science.gov (United States)

Sushko, Gennady B; Verkhovtsev, Alexey V; Yakubovich, Alexander V; Schramm, Stefan; Solov'yov, Andrey V

2014-08-21

The process of self-diffusion of titanium atoms in a bulk material, on grain junctions and on surface is explored numerically in a broad temperature range by means of classical molecular dynamics simulation. The analysis is carried out for a nanoscale cylindrical sample consisting of three adjacent sectors and various junctions between nanocrystals. The calculated diffusion coefficient varies by several orders of magnitude for different regions of the sample. The calculated values of the bulk diffusion coefficient correspond reasonably well to the experimental data obtained for solid and molten states of titanium. Investigation of diffusion in the nanocrystalline titanium is of a significant importance because of its numerous technological applications. This paper aims to reduce the lack of data on diffusion in titanium and describe the processes occurring in bulk, at different interfaces and on surface of the crystalline titanium.

Direction of Amygdala-Neocortex Interaction During Dynamic Facial Expression Processing.

Science.gov (United States)

Sato, Wataru; Kochiyama, Takanori; Uono, Shota; Yoshikawa, Sakiko; Toichi, Motomi

2017-03-01

Dynamic facial expressions of emotion strongly elicit multifaceted emotional, perceptual, cognitive, and motor responses. Neuroimaging studies revealed that some subcortical (e.g., amygdala) and neocortical (e.g., superior temporal sulcus and inferior frontal gyrus) brain regions and their functional interaction were involved in processing dynamic facial expressions. However, the direction of the functional interaction between the amygdala and the neocortex remains unknown. To investigate this issue, we re-analyzed functional magnetic resonance imaging (fMRI) data from 2 studies and magnetoencephalography (MEG) data from 1 study. First, a psychophysiological interaction analysis of the fMRI data confirmed the functional interaction between the amygdala and neocortical regions. Then, dynamic causal modeling analysis was used to compare models with forward, backward, or bidirectional effective connectivity between the amygdala and neocortical networks in the fMRI and MEG data. The results consistently supported the model of effective connectivity from the amygdala to the neocortex. Further increasing time-window analysis of the MEG demonstrated that this model was valid after 200 ms from the stimulus onset. These data suggest that emotional processing in the amygdala rapidly modulates some neocortical processing, such as perception, recognition, and motor mimicry, when observing dynamic facial expressions of emotion. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Dynamic Modeling of Process Technologies for Closed-Loop Water Recovery Systems

Science.gov (United States)

Allada, Rama Kumar; Lange, Kevin; Anderson, Molly

2011-01-01

Detailed chemical process simulations are a useful tool in designing and optimizing complex systems and architectures for human life support. Dynamic and steady-state models of these systems help contrast the interactions of various operating parameters and hardware designs, which become extremely useful in trade-study analyses. NASA s Exploration Life Support technology development project recently made use of such models to compliment a series of tests on different waste water distillation systems. This paper presents dynamic simulations of chemical process for primary processor technologies including: the Cascade Distillation System (CDS), the Vapor Compression Distillation (VCD) system, the Wiped-Film Rotating Disk (WFRD), and post-distillation water polishing processes such as the Volatiles Removal Assembly (VRA) that were developed using the Aspen Custom Modeler and Aspen Plus process simulation tools. The results expand upon previous work for water recovery technology models and emphasize dynamic process modeling and results. The paper discusses system design, modeling details, and model results for each technology and presents some comparisons between the model results and available test data. Following these initial comparisons, some general conclusions and forward work are discussed.

Effects of Bubble-Mediated Processes on Nitrous Oxide Dynamics in Denitrifying Bioreactors

Science.gov (United States)

McGuire, P. M.; Falk, L. M.; Reid, M. C.

2017-12-01

To mitigate groundwater and surface water impacts of reactive nitrogen (N), agricultural and stormwater management practices can employ denitrifying bioreactors (DNBs) as low-cost solutions for enhancing N removal. Due to the variable nature of hydrologic events, DNBs experience dynamic flows which can impact physical and biological processes within the reactors and affect performance. A particular concern is incomplete denitrification, which can release the potent greenhouse gas nitrous oxide (N2O) to the atmosphere. This study aims to provide insight into the effects of varying hydrologic conditions upon the operation of DNBs by disentangling abiotic and biotic controls on denitrification and N2O dynamics within a laboratory-scale bioreactor. We hypothesize that under transient hydrologic flows, rising water levels lead to air entrapment and bubble formation within the DNB porous media. Mass transfer of oxygen (O2) between trapped gas and liquid phases creates aerobic microenvironments that can inhibit N2O reductase (NosZ) enzymes and lead to N2O accumulation. These bubbles also retard N2O transport and make N2O unavailable for biological reduction, further enhancing atmospheric fluxes when water levels fall. The laboratory-scale DNB permits measurements of longitudinal and vertical profiles of dissolved constituents as well as trace gas concentrations in the reactor headspace. We describe a set of experiments quantifying denitrification pathway biokinetics under steady-state and transient hydrologic conditions and evaluate the role of bubble-mediated processes in enhancing N2O accumulation and fluxes. We use sulfur hexafluoride and helium as dissolved gas tracers to examine the impact of bubble entrapment upon retarded gas transport and enhanced trace gas fluxes. A planar optode sensor within the bioreactor provides near-continuous 2-D profiles of dissolved O2 within the bioreactor and allows for identification of aerobic microenvironments. We use qPCR to

Time-varying Concurrent Risk of Extreme Droughts and Heatwaves in California

Science.gov (United States)

Sarhadi, A.; Diffenbaugh, N. S.; Ausin, M. C.

2016-12-01

Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena such as droughts and heatwaves. The concurrent of these nature-changing climatic extremes may result in intensifying undesirable consequences in terms of human health and destructive effects in water resources. The present study assesses the risk of concurrent extreme droughts and heatwaves under dynamic nonstationary conditions arising from climate change in California. For doing so, a generalized fully Bayesian time-varying multivariate risk framework is proposed evolving through time under dynamic human-induced environment. In this methodology, an extreme, Bayesian, dynamic copula (Gumbel) is developed to model the time-varying dependence structure between the two different climate extremes. The time-varying extreme marginals are previously modeled using a Generalized Extreme Value (GEV) distribution. Bayesian Markov Chain Monte Carlo (MCMC) inference is integrated to estimate parameters of the nonstationary marginals and copula using a Gibbs sampling method. Modelled marginals and copula are then used to develop a fully Bayesian, time-varying joint return period concept for the estimation of concurrent risk. Here we argue that climate change has increased the chance of concurrent droughts and heatwaves over decades in California. It is also demonstrated that a time-varying multivariate perspective should be incorporated to assess realistic concurrent risk of the extremes for water resources planning and management in a changing climate in this area. The proposed generalized methodology can be applied for other stochastic nature-changing compound climate extremes that are under the influence of climate change.

Dynamic information processing states revealed through neurocognitive models of object semantics

Science.gov (United States)

Clarke, Alex

2015-01-01

Recognising objects relies on highly dynamic, interactive brain networks to process multiple aspects of object information. To fully understand how different forms of information about objects are represented and processed in the brain requires a neurocognitive account of visual object recognition that combines a detailed cognitive model of semantic knowledge with a neurobiological model of visual object processing. Here we ask how specific cognitive factors are instantiated in our mental processes and how they dynamically evolve over time. We suggest that coarse semantic information, based on generic shared semantic knowledge, is rapidly extracted from visual inputs and is sufficient to drive rapid category decisions. Subsequent recurrent neural activity between the anterior temporal lobe and posterior fusiform supports the formation of object-specific semantic representations – a conjunctive process primarily driven by the perirhinal cortex. These object-specific representations require the integration of shared and distinguishing object properties and support the unique recognition of objects. We conclude that a valuable way of understanding the cognitive activity of the brain is though testing the relationship between specific cognitive measures and dynamic neural activity. This kind of approach allows us to move towards uncovering the information processing states of the brain and how they evolve over time. PMID:25745632

Diagnosis of dynamic process over rainband of landfall typhoon

International Nuclear Information System (INIS)

Ling-Kun, Ran; Wen-Xia, Yang; Yan-Li, Chu

2010-01-01

This paper introduces a new physical parameter — thermodynamic shear advection parameter combining the perturbation vertical component of convective vorticity vector with the coupling of horizontal divergence perturbation and vertical gradient of general potential temperature perturbation. For a heavy-rainfall event resulting from the landfall typhoon 'Wipha', the parameter is calculated by using National Centres for Enviromental Prediction/National Centre for Atmospheric Research global final analysis data. The results showed that the parameter corresponds to the observed 6 h accumulative rainband since it is capable of catching hold of the dynamic and thermodynamic disturbance in the lower troposphere over the observed rainband. Before the typhoon landed, the advection of the parameter by basic-state flow and the coupling of general potential temperature perturbation with curl of Coriolis force perturbation are the primary dynamic processes which are responsible for the local change of the parameter. After the typhoon landed, the disturbance is mainly driven by the combination of five primary dynamic processes. The advection of the parameter by basic-state flow was weakened after the typhoon landed. (geophysics, astronomy and astrophysics)

Diagnosis of dynamic process over rainband of landfall typhoon

Science.gov (United States)

Ran, Ling-Kun; Yang, Wen-Xia; Chu, Yan-Li

2010-07-01

This paper introduces a new physical parameter — thermodynamic shear advection parameter combining the perturbation vertical component of convective vorticity vector with the coupling of horizontal divergence perturbation and vertical gradient of general potential temperature perturbation. For a heavy-rainfall event resulting from the landfall typhoon 'Wipha', the parameter is calculated by using National Centres for Enviromental Prediction/National Centre for Atmospheric Research global final analysis data. The results showed that the parameter corresponds to the observed 6 h accumulative rainband since it is capable of catching hold of the dynamic and thermodynamic disturbance in the lower troposphere over the observed rainband. Before the typhoon landed, the advection of the parameter by basic-state flow and the coupling of general potential temperature perturbation with curl of Coriolis force perturbation are the primary dynamic processes which are responsible for the local change of the parameter. After the typhoon landed, the disturbance is mainly driven by the combination of five primary dynamic processes. The advection of the parameter by basic-state flow was weakened after the typhoon landed.

Software for the nuclear reactor dynamics study using time series processing

International Nuclear Information System (INIS)

Valero, Esbel T.; Montesino, Maria E.

1997-01-01

The parametric monitoring in Nuclear Power Plant (NPP) permits the operational surveillance of nuclear reactor. The methods employed in order to process this information such as FFT, autoregressive models and other, have some limitations when those regimens in which appear strongly non-linear behaviors are analyzed. In last years the chaos theory has offered new ways in order to explain complex dynamic behaviors. This paper describes a software (ECASET) that allow, by time series processing from NPP's acquisition system, to characterize the nuclear reactor dynamic as a complex dynamical system. Here we show using ECASET's results the possibility of classifying the different regimens appearing in nuclear reactors. The results of several temporal series processing from real systems are introduced. This type of analysis complements the results obtained with traditional methods and can constitute a new tool for monitoring nuclear reactors. (author). 13 refs., 3 figs

Nonlinear dynamics near resonances of a rotor-active magnetic bearings system with 16-pole legs and time varying stiffness

Science.gov (United States)

Wu, R. Q.; Zhang, W.; Yao, M. H.

2018-02-01

In this paper, we analyze the complicated nonlinear dynamics of rotor-active magnetic bearings (rotor-AMB) with 16-pole legs and the time varying stiffness. The magnetic force with 16-pole legs is obtained by applying the electromagnetic theory. The governing equation of motion for rotor-active magnetic bearings is derived by using the Newton's second law. The resulting dimensionless equation of motion for the rotor-AMB system is expressed as a two-degree-of-freedom nonlinear system including the parametric excitation, quadratic and cubic nonlinearities. The averaged equation of the rotor-AMB system is obtained by using the method of multiple scales when the primary parametric resonance and 1/2 subharmonic resonance are taken into account. From the frequency-response curves, it is found that there exist the phenomena of the soft-spring type nonlinearity and the hardening-spring type nonlinearity in the rotor-AMB system. The effects of different parameters on the nonlinear dynamic behaviors of the rotor-AMB system are investigated. The numerical results indicate that the periodic, quasi-periodic and chaotic motions occur alternately in the rotor-AMB system.

Inversion factor in the comparative analysis of dynamical processes in radioecology

Energy Technology Data Exchange (ETDEWEB)

Zarubin, O.; Zarubina, N. [Institute for Nuclear Researh of National Academy of Science of Ukraine (Ukraine)

2014-07-01

We have studied levels of specific activity of radionuclides in fish and fungi of the Kiev region of Ukraine since 1986 till 2013, including 30-km alienation zone of Chernobyl Nuclear Power Plant (ChNPP) after the accident. The radionuclides specific activity dynamics analysis for 10 species of freshwater fishes of different trophic levels and at 7 species of higher fungi was carried out for this period. Multiple research of specific activity of radionuclides in fish was carried out on the Kanevskoe reservoir and cooling-pond of ChNPP, in fungi - on 6 testing areas, which are situated within the range of 2 to 150 km from ChNPP. The basic attention was given to accumulation of {sup 137}Cs. We have established that dynamics of specific activity of {sup 137}Cs within different species of fish in the same reservoir is not identical. Dynamics of specific activity of {sup 137}Cs within various species of fungi of the same testing area is also not identical. Dynamics of specific activity of {sup 137}Cs with the investigated objects of various testing dry-land and water areas also varies. Authors suggest an inversion factor to be used for comparison of dynamics of specific activity of {sup 137}Cs, which in case of biota is a nonlinear process: K{sub inv} = A{sub 0} / A{sub t}, where A{sub 0} stands for the value of specific activity of the radionuclide at time 0; A{sub t} - specific activity of radionuclide at time t. Therefore, K{sub inv} reflects ratio (inversion) of specific activity of radionuclides to its starting value as a function of time, where K{sub inv} > 1 corresponds to increase in radionuclides' specific activity and K{sub inv} < 1 corresponds to its decrease. For example, K{sub inv} of {sup 137}Cs in fish Rutilus rutilus in the Kanevskoe reservoir was equal to 0.57, and 13.33 in the cooling-pond of ChNPP, at Blicca bjoerkna 0.95 and 29.61 accordingly in 1987 - 1996. In 1987 - 2011 K{sub inv} of {sup 137}Cs at R. rutilus in the Kanevskoe reservoir

Multidimensional biochemical information processing of dynamical patterns.

Science.gov (United States)

Hasegawa, Yoshihiko

2018-02-01

Cells receive signaling molecules by receptors and relay information via sensory networks so that they can respond properly depending on the type of signal. Recent studies have shown that cells can extract multidimensional information from dynamical concentration patterns of signaling molecules. We herein study how biochemical systems can process multidimensional information embedded in dynamical patterns. We model the decoding networks by linear response functions, and optimize the functions with the calculus of variations to maximize the mutual information between patterns and output. We find that, when the noise intensity is lower, decoders with different linear response functions, i.e., distinct decoders, can extract much information. However, when the noise intensity is higher, distinct decoders do not provide the maximum amount of information. This indicates that, when transmitting information by dynamical patterns, embedding information in multiple patterns is not optimal when the noise intensity is very large. Furthermore, we explore the biochemical implementations of these decoders using control theory and demonstrate that these decoders can be implemented biochemically through the modification of cascade-type networks, which are prevalent in actual signaling pathways.

A concise review of dynamical processes in polymorphic ...

Indian Academy of Sciences (India)

TECS

This article describes our ongoing efforts to understand dynamical processes such as rota- tional diffusion and photoisomerization in polymorphic environments of a block copolymer. ... tional surfactants, these triblock copolymers do not possess a polar head group and nonpolar tail, but at- tain amphiphilic character as a ...

Dynamic Complexity Study of Nuclear Reactor and Process Heat Application Integration

International Nuclear Information System (INIS)

Taylor, J'Tia Patrice; Shropshire, David E.

2009-01-01

This paper describes the key obstacles and challenges facing the integration of nuclear reactors with process heat applications as they relate to dynamic issues. The paper also presents capabilities of current modeling and analysis tools available to investigate these issues. A pragmatic approach to an analysis is developed with the ultimate objective of improving the viability of nuclear energy as a heat source for process industries. The extension of nuclear energy to process heat industries would improve energy security and aid in reduction of carbon emissions by reducing demands for foreign derived fossil fuels. The paper begins with an overview of nuclear reactors and process application for potential use in an integrated system. Reactors are evaluated against specific characteristics that determine their compatibility with process applications such as heat outlet temperature. The reactor system categories include light water, heavy water, small to medium, near term high-temperature, and far term high temperature reactors. Low temperature process systems include desalination, district heating, and tar sands and shale oil recovery. High temperature processes that support hydrogen production include steam reforming, steam cracking, hydrogen production by electrolysis, and far-term applications such as the sulfur iodine chemical process and high-temperature electrolysis. A simple static matching between complementary systems is performed; however, to gain a true appreciation for system integration complexity, time dependent dynamic analysis is required. The paper identifies critical issues arising from dynamic complexity associated with integration of systems. Operational issues include scheduling conflicts and resource allocation for heat and electricity. Additionally, economic and safety considerations that could impact the successful integration of these systems are considered. Economic issues include the cost differential arising due to an integrated system

On-line statistical processing of radiation detector pulse trains with time-varying count rates

International Nuclear Information System (INIS)

Apostolopoulos, G.

2008-01-01

Statistical analysis is of primary importance for the correct interpretation of nuclear measurements, due to the inherent random nature of radioactive decay processes. This paper discusses the application of statistical signal processing techniques to the random pulse trains generated by radiation detectors. The aims of the presented algorithms are: (i) continuous, on-line estimation of the underlying time-varying count rate θ(t) and its first-order derivative dθ/dt; (ii) detection of abrupt changes in both of these quantities and estimation of their new value after the change point. Maximum-likelihood techniques, based on the Poisson probability distribution, are employed for the on-line estimation of θ and dθ/dt. Detection of abrupt changes is achieved on the basis of the generalized likelihood ratio statistical test. The properties of the proposed algorithms are evaluated by extensive simulations and possible applications for on-line radiation monitoring are discussed

Dynamic modeling and control of industrial crude terephthalic acid hydropurification process

Energy Technology Data Exchange (ETDEWEB)

Li, Zhi; Zhong, Weimin; Liu, Yang; Luo, Na; Qian, Feng [East China University of Science and Technology, Shanghai (China)

2015-04-15

Purified terephthalic acid (PTA) is critical to the development of the polyester industry. PTA production consists of p-xylene oxidation reaction and crude terephthalic acid (CTA) hydropurification. The hydropurification process is necessary to eliminate 4-carboxybenzaldehyde (4-CBA), which is a harmful byproduct of the oxidation reaction process. Based on the dynamic model of the hydropurification process, two control systems are studied using Aspen Dynamics. The first system is the ratio control system, in which the mass flows of CTA and deionized water are controlled. The second system is the multivariable predictive control-proportional-integral-derivative cascade control strategy, in which the concentrations of 4-CBA and carbon monoxide are chosen as control variables and the reaction temperature and hydrogen flow are selected as manipulated variables. A detailed dynamic behavior is investigated through simulation. Results show that the developed control strategies exhibit good control performances, thereby providing theoretical guidance for advanced control of industry-scale PTA production.

A Partially Observed Markov Decision Process for Dynamic Pricing

OpenAIRE

Yossi Aviv; Amit Pazgal

2005-01-01

In this paper, we develop a stylized partially observed Markov decision process (POMDP) framework to study a dynamic pricing problem faced by sellers of fashion-like goods. We consider a retailer that plans to sell a given stock of items during a finite sales season. The objective of the retailer is to dynamically price the product in a way that maximizes expected revenues. Our model brings together various types of uncertainties about the demand, some of which are resolvable through sales ob...

DYNSYL: a general-purpose dynamic simulator for chemical processes

International Nuclear Information System (INIS)

Patterson, G.K.; Rozsa, R.B.

1978-01-01

Lawrence Livermore Laboratory is conducting a safeguards program for the Nuclear Regulatory Commission. The goal of the Material Control Project of this program is to evaluate material control and accounting (MCA) methods in plants that handle special nuclear material (SNM). To this end we designed and implemented the dynamic chemical plant simulation program DYNSYL. This program can be used to generate process data or to provide estimates of process performance; it simulates both steady-state and dynamic behavior. The MCA methods that may have to be evaluated range from sophisticated on-line material trackers such as Kalman filter estimators, to relatively simple material balance procedures. This report describes the overall structure of DYNSYL and includes some example problems. The code is still in the experimental stage and revision is continuing

In-process, non-destructive multimodal dynamic testing of high-speed composite rotors

Science.gov (United States)

Kuschmierz, Robert; Filippatos, Angelos; Langkamp, Albert; Hufenbach, Werner; Czarske, Jürgern W.; Fischer, Andreas

2014-03-01

Fibre reinforced plastic (FRP) rotors are lightweight and offer great perspectives in high-speed applications such as turbo machinery. Currently, novel rotor structures and materials are investigated for the purpose of increasing machine efficiency, lifetime and loading limits. Due to complex rotor structures, high anisotropy and non-linear behavior of FRP under dynamic loads, an in-process measurement system is necessary to monitor and to investigate the evolution of damages under real operation conditions. A non-invasive, optical laser Doppler distance sensor measurement system is applied to determine the biaxial deformation of a bladed FRP rotor with micron uncertainty as well as the tangential blade vibrations at surface speeds above 300 m/s. The laser Doppler distance sensor is applicable under vacuum conditions. Measurements at varying loading conditions are used to determine elastic and plastic deformations. Furthermore they allow to determine hysteresis, fatigue, Eigenfrequency shifts and loading limits. The deformation measurements show a highly anisotropic and nonlinear behavior and offer a deeper understanding of the damage evolution in FRP rotors. The experimental results are used to validate and to calibrate a simulation model of the deformation. The simulation combines finite element analysis and a damage mechanics model. The combination of simulation and measurement system enables the monitoring and prediction of damage evolutions of FRP rotors in process.

Forecasting financial asset processes: stochastic dynamics via learning neural networks.

Science.gov (United States)

Giebel, S; Rainer, M

2010-01-01

Models for financial asset dynamics usually take into account their inherent unpredictable nature by including a suitable stochastic component into their process. Unknown (forward) values of financial assets (at a given time in the future) are usually estimated as expectations of the stochastic asset under a suitable risk-neutral measure. This estimation requires the stochastic model to be calibrated to some history of sufficient length in the past. Apart from inherent limitations, due to the stochastic nature of the process, the predictive power is also limited by the simplifying assumptions of the common calibration methods, such as maximum likelihood estimation and regression methods, performed often without weights on the historic time series, or with static weights only. Here we propose a novel method of "intelligent" calibration, using learning neural networks in order to dynamically adapt the parameters of the stochastic model. Hence we have a stochastic process with time dependent parameters, the dynamics of the parameters being themselves learned continuously by a neural network. The back propagation in training the previous weights is limited to a certain memory length (in the examples we consider 10 previous business days), which is similar to the maximal time lag of autoregressive processes. We demonstrate the learning efficiency of the new algorithm by tracking the next-day forecasts for the EURTRY and EUR-HUF exchange rates each.

Experiential Learning as a Constraint-Led Process: An Ecological Dynamics Perspective

Science.gov (United States)

Brymer, Eric; Davids, Keith

2014-01-01

In this paper we present key ideas for an ecological dynamics approach to learning that reveal the importance of learner-environment interactions to frame outdoor experiential learning. We propose that ecological dynamics provides a useful framework for understanding the interacting constraints of the learning process and for designing learning…

Emergence of epidemics in rapidly varying networks

International Nuclear Information System (INIS)

Kohar, Vivek; Sinha, Sudeshna

2013-01-01

We describe a simple model mimicking disease spreading on a network with dynamically varying connections, and investigate the dynamical consequences of switching links in the network. Our central observation is that the disease cycles get more synchronized, indicating the onset of epidemics, as the underlying network changes more rapidly. This behavior is found for periodically switched links, as well as links that switch randomly in time. We find that the influence of changing links is more pronounced in networks where the nodes have lower degree, and the disease cycle has a longer infective stage. Further, when the switching of links is periodic we observe finer dynamical features, such as beating patterns in the emergent oscillations and resonant enhancement of synchronization, arising from the interplay between the time-scales of the connectivity changes and that of the epidemic outbreaks

Improving the effectiveness of detailed processing by dynamic control of processing with high sports range

Directory of Open Access Journals (Sweden)

Yu.V. Shapoval

2017-12-01

Full Text Available In this article the possibility of increasing the efficiency of the processing of parts with a diameter of up to 20 mm is analyzed, namely: vibration resistance of the cutting process at pinching due to cutting speed control in the processing, forecasting and selection of rotational frequencies, which ensure the stability of the processing system, controlling the dynamics of the process of displacement of the additional mass. The method of investigation of vibration processes during the sharpening is developed. As a result of the processing of experimental data, it was found that when an oscillatory motion is applied to the spindle rotation, the overall level of oscillation decreases, which is reflected on the quality of the treated surface. The choice of a previously known spindle rotation frequency range at which the lowest value of the oscillation amplitude of the instrument is observed in the radial direction to the detail part, allows you to increase the processing efficiency while maintaining the drawing requirements for roughness by increasing the spindle rotational speed. The combination of the node of the own forms of oscillation and the cutting zone, by dynamically controlling the fluctuations of the lathe armature due to the increase of the inertia characteristics of the machine and the reduction of the oscillation amplitude of the tool, can improve the accuracy of machining and roughness of the processed surface of the component at higher spindle speeds.

Riverine habitat dynamics

Science.gov (United States)

Jacobson, R.B.

2013-01-01

The physical habitat template is a fundamental influence on riverine ecosystem structure and function. Habitat dynamics refers to the variation in habitat through space and time as the result of varying discharge and varying geomorphology. Habitat dynamics can be assessed at spatial scales ranging from the grain (the smallest resolution at which an organism relates to its environment) to the extent (the broadest resolution inclusive of all space occupied during its life cycle). In addition to a potentially broad range of spatial scales, assessments of habitat dynamics may include dynamics of both occupied and nonoccupied habitat patches because of process interactions among patches. Temporal aspects of riverine habitat dynamics can be categorized into hydrodynamics and morphodynamics. Hydrodynamics refers to habitat variation that results from changes in discharge in the absence of significant change of channel morphology and at generally low sediment-transport rates. Hydrodynamic assessments are useful in cases of relatively high flow exceedance (percent of time a flow is equaled or exceeded) or high critical shear stress, conditions that are applicable in many studies of instream flows. Morphodynamics refers to habitat variation resulting from changes to substrate conditions or channel/floodplain morphology. Morphodynamic assessments are necessary when channel and floodplain boundary conditions have been significantly changed, generally by relatively rare flood events or in rivers with low critical shear stress. Morphodynamic habitat variation can be particularly important as disturbance mechanisms that mediate population growth or for providing conditions needed for reproduction, such as channel-migration events that erode cutbanks and provide new pointbar surfaces for germination of riparian trees. Understanding of habitat dynamics is increasing in importance as societal goals shift toward restoration of riverine ecosystems. Effective investment in restoration

A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

Science.gov (United States)

Ingram, James N; Howard, Ian S; Flanagan, J Randall; Wolpert, Daniel M

2011-09-01

Motor learning has been extensively studied using dynamic (force-field) perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar object dynamics

A single-rate context-dependent learning process underlies rapid adaptation to familiar object dynamics.

Directory of Open Access Journals (Sweden)

James N Ingram

2011-09-01

Full Text Available Motor learning has been extensively studied using dynamic (force-field perturbations. These induce movement errors that result in adaptive changes to the motor commands. Several state-space models have been developed to explain how trial-by-trial errors drive the progressive adaptation observed in such studies. These models have been applied to adaptation involving novel dynamics, which typically occurs over tens to hundreds of trials, and which appears to be mediated by a dual-rate adaptation process. In contrast, when manipulating objects with familiar dynamics, subjects adapt rapidly within a few trials. Here, we apply state-space models to familiar dynamics, asking whether adaptation is mediated by a single-rate or dual-rate process. Previously, we reported a task in which subjects rotate an object with known dynamics. By presenting the object at different visual orientations, adaptation was shown to be context-specific, with limited generalization to novel orientations. Here we show that a multiple-context state-space model, with a generalization function tuned to visual object orientation, can reproduce the time-course of adaptation and de-adaptation as well as the observed context-dependent behavior. In contrast to the dual-rate process associated with novel dynamics, we show that a single-rate process mediates adaptation to familiar object dynamics. The model predicts that during exposure to the object across multiple orientations, there will be a degree of independence for adaptation and de-adaptation within each context, and that the states associated with all contexts will slowly de-adapt during exposure in one particular context. We confirm these predictions in two new experiments. Results of the current study thus highlight similarities and differences in the processes engaged during exposure to novel versus familiar dynamics. In both cases, adaptation is mediated by multiple context-specific representations. In the case of familiar

Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone.

Science.gov (United States)

Zhang, Luyan; Liang, Yi; Li, Fali; Sun, Hongbin; Peng, Wenjing; Du, Peishan; Si, Yajing; Song, Limeng; Yu, Liang; Xu, Peng

2017-01-01

The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI) recorded during the ictal discharging or the resting-state, and few studies have probed into the dynamic patterns during the inter-ictal discharging that are much easier to record in clinical applications. Here, we propose a time-varying network analysis based on adaptive directed transfer function to uncover the dynamic brain network patterns during the inter-ictal discharging. In addition, an algorithm based on the time-varying outflow of information derived from the network analysis is developed to detect the epileptogenic zone. The analysis performed revealed the time-varying network patterns during different stages of inter-ictal discharging; the epileptogenic zone was activated prior to the discharge onset then worked as the source to propagate the activity to other brain regions. Consistence between the epileptogenic zones detected by our proposed approach and the actual epileptogenic zones proved that time-varying network analysis could not only reveal the underlying neural mechanism of epilepsy, but also function as a useful tool in detecting the epileptogenic zone based on the EEGs in the inter-ictal discharging.

Targeted quantification of functional enzyme dynamics in environmental samples for microbially mediated biogeochemical processes: Targeted quantification of functional enzyme dynamics

Energy Technology Data Exchange (ETDEWEB)

Li, Minjing [School of Environmental Studies, China University of Geosciences, Wuhan 430074 People' s Republic of China; Gao, Yuqian [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Qian, Wei-Jun [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Shi, Liang [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Liu, Yuanyuan [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Nelson, William C. [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Nicora, Carrie D. [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Resch, Charles T. [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Thompson, Christopher [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Yan, Sen [School of Environmental Studies, China University of Geosciences, Wuhan 430074 People' s Republic of China; Fredrickson, James K. [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Zachara, John M. [Pacific Northwest National Laboratory, Richland, WA 99354 USA; Liu, Chongxuan [Pacific Northwest National Laboratory, Richland, WA 99354 USA; School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055 People' s Republic of China

2017-07-13

Microbially mediated biogeochemical processes are catalyzed by enzymes that control the transformation of carbon, nitrogen, and other elements in environment. The dynamic linkage between enzymes and biogeochemical species transformation has, however, rarely been investigated because of the lack of analytical approaches to efficiently and reliably quantify enzymes and their dynamics in soils and sediments. Herein, we developed a signature peptide-based technique for sensitively quantifying dissimilatory and assimilatory enzymes using nitrate-reducing enzymes in a hyporheic zone sediment as an example. Moreover, the measured changes in enzyme concentration were found to correlate with the nitrate reduction rate in a way different from that inferred from biogeochemical models based on biomass or functional genes as surrogates for functional enzymes. This phenomenon has important implications for understanding and modeling the dynamics of microbial community functions and biogeochemical processes in environments. Our results also demonstrate the importance of enzyme quantification for the identification and interrogation of those biogeochemical processes with low metabolite concentrations as a result of faster enzyme-catalyzed consumption of metabolites than their production. The dynamic enzyme behaviors provide a basis for the development of enzyme-based models to describe the relationship between the microbial community and biogeochemical processes.

Classical molecular dynamics simulation of electronically non-adiabatic processes.

Science.gov (United States)

Miller, William H; Cotton, Stephen J

2016-12-22

Both classical and quantum mechanics (as well as hybrids thereof, i.e., semiclassical approaches) find widespread use in simulating dynamical processes in molecular systems. For large chemical systems, however, which involve potential energy surfaces (PES) of general/arbitrary form, it is usually the case that only classical molecular dynamics (MD) approaches are feasible, and their use is thus ubiquitous nowadays, at least for chemical processes involving dynamics on a single PES (i.e., within a single Born-Oppenheimer electronic state). This paper reviews recent developments in an approach which extends standard classical MD methods to the treatment of electronically non-adiabatic processes, i.e., those that involve transitions between different electronic states. The approach treats nuclear and electronic degrees of freedom (DOF) equivalently (i.e., by classical mechanics, thereby retaining the simplicity of standard MD), and provides "quantization" of the electronic states through a symmetrical quasi-classical (SQC) windowing model. The approach is seen to be capable of treating extreme regimes of strong and weak coupling between the electronic states, as well as accurately describing coherence effects in the electronic DOF (including the de-coherence of such effects caused by coupling to the nuclear DOF). A survey of recent applications is presented to illustrate the performance of the approach. Also described is a newly developed variation on the original SQC model (found universally superior to the original) and a general extension of the SQC model to obtain the full electronic density matrix (at no additional cost/complexity).

Tracking single dynamic MEG dipole sources using the projected Extended Kalman Filter.

Science.gov (United States)

Yao, Yuchen; Swindlehurst, A Lee

2011-01-01

This paper presents two new algorithms based on the Extended Kalman Filter (EKF) for tracking the parameters of single dynamic magnetoencephalography (MEG) dipole sources. We assume a dynamic MEG dipole source with possibly both time-varying location and dipole orientation. The standard EKF-based tracking algorithm performs well under the assumption that the dipole source components vary in time as a Gauss-Markov process, provided that the background noise is temporally stationary. We propose a Projected-EKF algorithm that is adapted to a more forgiving condition where the background noise is temporally nonstationary, as well as a Projected-GLS-EKF algorithm that works even more universally, when the dipole components vary arbitrarily from one sample to the next.

Recurrent-Neural-Network-Based Multivariable Adaptive Control for a Class of Nonlinear Dynamic Systems With Time-Varying Delay.

Science.gov (United States)

Hwang, Chih-Lyang; Jan, Chau

2016-02-01

At the beginning, an approximate nonlinear autoregressive moving average (NARMA) model is employed to represent a class of multivariable nonlinear dynamic systems with time-varying delay. It is known that the disadvantages of robust control for the NARMA model are as follows: 1) suitable control parameters for larger time delay are more sensitive to achieving desirable performance; 2) it only deals with bounded uncertainty; and 3) the nominal NARMA model must be learned in advance. Due to the dynamic feature of the NARMA model, a recurrent neural network (RNN) is online applied to learn it. However, the system performance becomes deteriorated due to the poor learning of the larger variation of system vector functions. In this situation, a simple network is employed to compensate the upper bound of the residue caused by the linear parameterization of the approximation error of RNN. An e -modification learning law with a projection for weight matrix is applied to guarantee its boundedness without persistent excitation. Under suitable conditions, the semiglobally ultimately bounded tracking with the boundedness of estimated weight matrix is obtained by the proposed RNN-based multivariable adaptive control. Finally, simulations are presented to verify the effectiveness and robustness of the proposed control.

Sensitivity of CO2 storage performance to varying rates and dynamic injectivity in the Bunter Sandstone, UK

Science.gov (United States)

Kolster, C.; Mac Dowell, N.; Krevor, S. C.; Agada, S.

2016-12-01

Carbon capture and storage (CCS) is needed for meeting legally binding greenhouse gas emissions targets in the UK (ECCC 2016). Energy systems models have been key to identifying the importance of CCS but they tend to impose few constraints on the availability and use of geologic CO2 storage reservoirs. Our aim is to develop simple models that use dynamic representations of limits on CO2 storage resources. This will allow for a first order representation of the storage reservoir for use in systems models with CCS. We use the ECLIPSE reservoir simulator and a model of the Southern North Sea Bunter Sandstone saline aquifer. We analyse reservoir performance sensitivities to scenarios of varying CO2 injection demand for a future UK low carbon energy market. With 12 injection sites, we compare the impact of injecting at a constant 2MtCO2/year per site and varying this rate by a factor of 1.8 and 0.2 cyclically every 5 and 2.5 years over 50 years of injection. The results show a maximum difference in average reservoir pressure of 3% amongst each case and a similar variation in plume migration extent. This suggests that simplified models can maintain accuracy by using average rates of injection over similar time periods. Meanwhile, by initiating injection at rates limited by pressurization at the wellhead we find that injectivity steadily increases. As a result, dynamic capacity increases. We find that instead of injecting into sites on a need basis, we can strategically inject the CO2 into 6 of the deepest sites increasing injectivity for the first 15 years by 13%. Our results show injectivity as highly dependent on reservoir heterogeneity near the injection site. Injecting 1MTCO2/year into a shallow, low permeability and porosity site instead of into a deep injection site with high permeability and porosity reduces injectivity in the first 5 years by 52%. ECCC. 2016. Future of Carbon Capture and Storage in the UK. UK Parliament House of Commons, Energy and Climate Change

A 2-D process-based model for suspended sediment dynamics : A first step towards ecological modeling

NARCIS (Netherlands)

Minikowski Achete, F.; van der Wegen, M.; Roelvink, D.; Jaffe, Bruce E.

2015-01-01

In estuaries suspended sediment concentration (SSC) is one of the most important contributors to turbidity, which influences habitat conditions and ecological functions of the system. Sediment dynamics differs depending on sediment supply and hydrodynamic forcing conditions that vary over space

Rate processes with non-Markovian dynamical disorder

International Nuclear Information System (INIS)

Goychuk, Igor

2005-01-01

Rate processes with dynamical disorder are investigated within a simple framework provided by unidirectional electron transfer (ET) with fluctuating transfer rate. The rate fluctuations are assumed to be described by a non-Markovian stochastic jump process which reflects conformational dynamics of an electron transferring donor-acceptor molecular complex. A tractable analytical expression is obtained for the relaxation of the donor population (in the Laplace-transformed time domain) averaged over the stationary conformational fluctuations. The corresponding mean transfer time is also obtained in an analytical form. The case of two-state fluctuations is studied in detail for a model incorporating substate diffusion within one of the conformations. It is shown that an increase of the conformational diffusion time results in a gradual transition from the regime of fast modulation characterized by the averaged ET rate to the regime of quasistatic disorder. This transition occurs at the conformational mean residence time intervals fixed much less than the inverse of the corresponding ET rates. An explanation of this paradoxical effect is provided. Moreover, its presence is also manifested for the simplest, exactly solvable non-Markovian model with a biexponential distribution of the residence times in one of the conformations. The nontrivial conditions for this phenomenon to occur are found

Tracking the sleep onset process: an empirical model of behavioral and physiological dynamics.

Directory of Open Access Journals (Sweden)

Michael J Prerau

2014-10-01

Full Text Available The sleep onset process (SOP is a dynamic process correlated with a multitude of behavioral and physiological markers. A principled analysis of the SOP can serve as a foundation for answering questions of fundamental importance in basic neuroscience and sleep medicine. Unfortunately, current methods for analyzing the SOP fail to account for the overwhelming evidence that the wake/sleep transition is governed by continuous, dynamic physiological processes. Instead, current practices coarsely discretize sleep both in terms of state, where it is viewed as a binary (wake or sleep process, and in time, where it is viewed as a single time point derived from subjectively scored stages in 30-second epochs, effectively eliminating SOP dynamics from the analysis. These methods also fail to integrate information from both behavioral and physiological data. It is thus imperative to resolve the mismatch between the physiological evidence and analysis methodologies. In this paper, we develop a statistically and physiologically principled dynamic framework and empirical SOP model, combining simultaneously-recorded physiological measurements with behavioral data from a novel breathing task requiring no arousing external sensory stimuli. We fit the model using data from healthy subjects, and estimate the instantaneous probability that a subject is awake during the SOP. The model successfully tracked physiological and behavioral dynamics for individual nights, and significantly outperformed the instantaneous transition models implicit in clinical definitions of sleep onset. Our framework also provides a principled means for cross-subject data alignment as a function of wake probability, allowing us to characterize and compare SOP dynamics across different populations. This analysis enabled us to quantitatively compare the EEG of subjects showing reduced alpha power with the remaining subjects at identical response probabilities. Thus, by incorporating both

Quantization of systems with temporally varying discretization. I. Evolving Hilbert spaces

International Nuclear Information System (INIS)

Höhn, Philipp A.

2014-01-01

A temporally varying discretization often features in discrete gravitational systems and appears in lattice field theory models subject to a coarse graining or refining dynamics. To better understand such discretization changing dynamics in the quantum theory, an according formalism for constrained variational discrete systems is constructed. While this paper focuses on global evolution moves and, for simplicity, restricts to flat configuration spaces R N , a Paper II [P. A. Höhn, “Quantization of systems with temporally varying discretization. II. Local evolution moves,” J. Math. Phys., e-print http://arxiv.org/abs/arXiv:1401.7731 [gr-qc].] discusses local evolution moves. In order to link the covariant and canonical picture, the dynamics of the quantum states is generated by propagators which satisfy the canonical constraints and are constructed using the action and group averaging projectors. This projector formalism offers a systematic method for tracing and regularizing divergences in the resulting state sums. Non-trivial coarse graining evolution moves lead to non-unitary, and thus irreversible, projections of physical Hilbert spaces and Dirac observables such that these concepts become evolution move dependent on temporally varying discretizations. The formalism is illustrated in a toy model mimicking a “creation from nothing.” Subtleties arising when applying such a formalism to quantum gravity models are discussed

Time varying moments, regime switch, and crisis warning: The birth-death process with changing transition probability

Science.gov (United States)

Tang, Yinan; Chen, Ping

2014-06-01

The sub-prime crisis in the U.S. reveals the limitation of diversification strategy based on mean-variance analysis. A regime switch and a turning point can be observed using a high moment representation and time-dependent transition probability. Up-down price movements are induced by interactions among agents, which can be described by the birth-death (BD) process. Financial instability is visible by dramatically increasing 3rd to 5th moments one-quarter before and during the crisis. The sudden rising high moments provide effective warning signals of a regime-switch or a coming crisis. The critical condition of a market breakdown can be identified from nonlinear stochastic dynamics. The master equation approach of population dynamics provides a unified theory of a calm and turbulent market.

Nonlinear identification of process dynamics using neural networks

International Nuclear Information System (INIS)

Parlos, A.G.; Atiya, A.F.; Chong, K.T.

1992-01-01

In this paper the nonlinear identification of process dynamics encountered in nuclear power plant components is addressed, in an input-output sense, using artificial neural systems. A hybrid feedforward/feedback neural network, namely, a recurrent multilayer perceptron, is used as the model structure to be identified. The feedforward portion of the network architecture provides its well-known interpolation property, while through recurrency and cross-talk, the local information feedback enables representation of temporal variations in the system nonlinearities. The standard backpropagation learning algorithm is modified, and it is used for the supervised training of the proposed hybrid network. The performance of recurrent multilayer perceptron networks in identifying process dynamics is investigated via the case study of a U-tube steam generator. The response of representative steam generator is predicted using a neural network, and it is compared to the response obtained from a sophisticated computer model based on first principles. The transient responses compare well, although further research is warranted to determine the predictive capabilities of these networks during more severe operational transients and accident scenarios

Dynamic Complexity Study of Nuclear Reactor and Process Heat Application Integration

Energy Technology Data Exchange (ETDEWEB)

J' Tia Patrice Taylor; David E. Shropshire

2009-09-01

Abstract This paper describes the key obstacles and challenges facing the integration of nuclear reactors with process heat applications as they relate to dynamic issues. The paper also presents capabilities of current modeling and analysis tools available to investigate these issues. A pragmatic approach to an analysis is developed with the ultimate objective of improving the viability of nuclear energy as a heat source for process industries. The extension of nuclear energy to process heat industries would improve energy security and aid in reduction of carbon emissions by reducing demands for foreign derived fossil fuels. The paper begins with an overview of nuclear reactors and process application for potential use in an integrated system. Reactors are evaluated against specific characteristics that determine their compatibility with process applications such as heat outlet temperature. The reactor system categories include light water, heavy water, small to medium, near term high-temperature, and far term high temperature reactors. Low temperature process systems include desalination, district heating, and tar sands and shale oil recovery. High temperature processes that support hydrogen production include steam reforming, steam cracking, hydrogen production by electrolysis, and far-term applications such as the sulfur iodine chemical process and high-temperature electrolysis. A simple static matching between complementary systems is performed; however, to gain a true appreciation for system integration complexity, time dependent dynamic analysis is required. The paper identifies critical issues arising from dynamic complexity associated with integration of systems. Operational issues include scheduling conflicts and resource allocation for heat and electricity. Additionally, economic and safety considerations that could impact the successful integration of these systems are considered. Economic issues include the cost differential arising due to an integrated

Process-based distributed modeling approach for analysis of sediment dynamics in a river basin

Directory of Open Access Journals (Sweden)

M. A. Kabir

2011-04-01

Full Text Available Modeling of sediment dynamics for developing best management practices of reducing soil erosion and of sediment control has become essential for sustainable management of watersheds. Precise estimation of sediment dynamics is very important since soils are a major component of enormous environmental processes and sediment transport controls lake and river pollution extensively. Different hydrological processes govern sediment dynamics in a river basin, which are highly variable in spatial and temporal scales. This paper presents a process-based distributed modeling approach for analysis of sediment dynamics at river basin scale by integrating sediment processes (soil erosion, sediment transport and deposition with an existing process-based distributed hydrological model. In this modeling approach, the watershed is divided into an array of homogeneous grids to capture the catchment spatial heterogeneity. Hillslope and river sediment dynamic processes have been modeled separately and linked to each other consistently. Water flow and sediment transport at different land grids and river nodes are modeled using one dimensional kinematic wave approximation of Saint-Venant equations. The mechanics of sediment dynamics are integrated into the model using representative physical equations after a comprehensive review. The model has been tested on river basins in two different hydro climatic areas, the Abukuma River Basin, Japan and Latrobe River Basin, Australia. Sediment transport and deposition are modeled using Govers transport capacity equation. All spatial datasets, such as, Digital Elevation Model (DEM, land use and soil classification data, etc., have been prepared using raster "Geographic Information System (GIS" tools. The results of relevant statistical checks (Nash-Sutcliffe efficiency and R–squared value indicate that the model simulates basin hydrology and its associated sediment dynamics reasonably well. This paper presents the

DYNAMIC ITELLECTUAL SYSTEM OF PROCESS MANAGEMENT IN INFORMATION AND EDUCATION ENVIRONMENT OF HIGHER EDUCATIONAL INSTITUTIONS

Directory of Open Access Journals (Sweden)

Yuriy F. Telnov

2013-01-01

Full Text Available The paper represents the technology of application of dynamic intelligent process management system for integrated information-educational environment of university and providing the access for community in order to develop flexible education programs and teaching manuals based on multi-agent and service-oriented architecture. The article depicts the prototype of dynamic intelligent process management system using for forming of educational-methodic body. Efficiency of creation and usage of dynamic intelligent process management system is evaluated. 

Molecular dynamics simulation study of the influence of the lattice atom potential function upon atom ejection processes

International Nuclear Information System (INIS)

Harrison, D.E. Jr.; Webb, R.P.

1982-01-01

A molecular dynamics simulation has been used to investigate the sensitivity of atom ejection processes from a single-crystal target to changes in the atom-atom potential function. Four functions, three constructed from the Gibson potentials with Anderman's attractive well, and a fouth specifically developed for this investigation, were investigated in the Cu/Ar/sup +/ system over a range of ion energies from 1.0 to 10.0 kev with the KSE-B ion-atom potential. Well depths and widths also were varied. The calculations were done at normal incidence on the fcc (111) crystal orientation. Computed values were compared with experimental data where they exist. Sputtering yields, multimer yield ratios, layer yield ratios, and the ejected atom energy distribution vary systematically with the parameters of the atom-atom potential function. Calculations also were done with the modified Moliere function. Yields and other properties fall exactly into the positions predicted from the Born-Mayer function analysis. Simultaneous analysis of the ejected atom energy distribution and the ion energy dependence of the sputtering yield curve provides information about the parameters of both the wall and well portions of the atom-atom potential function

Risk-based determination of design pressure of LNG fuel storage tanks based on dynamic process simulation combined with Monte Carlo method

International Nuclear Information System (INIS)

Noh, Yeelyong; Chang, Kwangpil; Seo, Yutaek; Chang, Daejun

2014-01-01

This study proposes a new methodology that combines dynamic process simulation (DPS) and Monte Carlo simulation (MCS) to determine the design pressure of fuel storage tanks on LNG-fueled ships. Because the pressure of such tanks varies with time, DPS is employed to predict the pressure profile. Though equipment failure and subsequent repair affect transient pressure development, it is difficult to implement these features directly in the process simulation due to the randomness of the failure. To predict the pressure behavior realistically, MCS is combined with DPS. In MCS, discrete events are generated to create a lifetime scenario for a system. The combination of MCS with long-term DPS reveals the frequency of the exceedance pressure. The exceedance curve of the pressure provides risk-based information for determining the design pressure based on risk acceptance criteria, which may vary with different points of view. - Highlights: • The realistic operation scenario of the LNG FGS system is estimated by MCS. • In repeated MCS trials, the availability of the FGS system is evaluated. • The realistic pressure profile is obtained by the proposed methodology. • The exceedance curve provides risk-based information for determining design pressure

Dynamic Processes in Nanostructured Crystals Under Ion Irradiation

Science.gov (United States)

Uglov, V. V.; Kvasov, N. T.; Shimanski, V. I.; Safronov, I. V.; Komarov, N. D.

2018-02-01

The paper presents detailed investigations of dynamic processes occurring in nanostructured Si(Fe) material under the radiation exposure, namely: heating, thermoelastic stress generation, elastic disturbances of the surrounding medium similar to weak shock waves, and dislocation generation. The performance calculations are proposed for elastic properties of the nanostructured material with a glance to size effects in nanoparticles.

The Behavior of Procurement Process as Described by Using System Dynamics Methodology

OpenAIRE

Mohd Yusoff, Mohd Izhan

2018-01-01

System dynamics methodology has been used in many fields of study which include supply chain, project management and performance, and procurement process. The said methodology enables the researchers to identify and study the impact of the variables or factors on the outcome of the model they developed. In this paper, we showed the use of system dynamics methodology in studying the behavior of procurement process that is totally different from those mentioned in previous studies. By using a t...

Cautious NMPC with Gaussian Process Dynamics for Miniature Race Cars

OpenAIRE

Hewing, Lukas; Liniger, Alexander; Zeilinger, Melanie N.

2017-01-01

This paper presents an adaptive high performance control method for autonomous miniature race cars. Racing dynamics are notoriously hard to model from first principles, which is addressed by means of a cautious nonlinear model predictive control (NMPC) approach that learns to improve its dynamics model from data and safely increases racing performance. The approach makes use of a Gaussian Process (GP) and takes residual model uncertainty into account through a chance constrained formulation. ...

Stochastic disturbances and dynamics of thermal processes. With application to municipal solid waste combustion

Energy Technology Data Exchange (ETDEWEB)

Van Kessel, L.B.M.

2003-06-11

The main topic of this thesis is the research into the disturbances and dynamics of the Municipal and Solid Waste Combustion (MSWC) process. As already said, the MSWC process suffers from large disturbances in the calorific value. At the start of this research it was obvious that for a good process analysis of the dynamics more information about the disturbances would be necessary. Therefore, a new on-line calorific value sensor was developed, which is described in chapter 2. The new on-line calorific value sensor makes it possible to monitor on-line important process variables like the calorific value and the water content of the fuel. The sensor is used to collect data from four different MSWC plants. Results from these MSWC plants will be presented. A comparison with traditional off-line methods and possible applications will be discussed as well. After revealing the main disturbances of the process the study of the process dynamics can be performed. A mathematical dynamic model of the process is very useful for studying the dynamics of a process. Therefore, in chapter 3 a general model for the dynamics of thermal processes is derived. This general model is applied to MSWC, which yields a completely new model description of the MSWC process. However, a model has to be validated with practical data. Unfortunately, MSWC plants suffer from large disturbances, which makes a good validation complicated. As no good information for the validation of processes like MSWC was available in literature, new validation techniques have been applied to MSWC plants. The validation results will be presented. The results from the validation experiments will show that the combustion process in practice can become completely different when different primary air temperatures are used. Two situations with different primary air temperatures will be discussed in detail including the application of the derived dynamic model to explain the differences. When the disturbances are measured

Model of the Dynamic Construction Process of Texts and Scaling Laws of Words Organization in Language Systems.

Science.gov (United States)

Li, Shan; Lin, Ruokuang; Bian, Chunhua; Ma, Qianli D Y; Ivanov, Plamen Ch

2016-01-01

Scaling laws characterize diverse complex systems in a broad range of fields, including physics, biology, finance, and social science. The human language is another example of a complex system of words organization. Studies on written texts have shown that scaling laws characterize the occurrence frequency of words, words rank, and the growth of distinct words with increasing text length. However, these studies have mainly concentrated on the western linguistic systems, and the laws that govern the lexical organization, structure and dynamics of the Chinese language remain not well understood. Here we study a database of Chinese and English language books. We report that three distinct scaling laws characterize words organization in the Chinese language. We find that these scaling laws have different exponents and crossover behaviors compared to English texts, indicating different words organization and dynamics of words in the process of text growth. We propose a stochastic feedback model of words organization and text growth, which successfully accounts for the empirically observed scaling laws with their corresponding scaling exponents and characteristic crossover regimes. Further, by varying key model parameters, we reproduce differences in the organization and scaling laws of words between the Chinese and English language. We also identify functional relationships between model parameters and the empirically observed scaling exponents, thus providing new insights into the words organization and growth dynamics in the Chinese and English language.

Model of the Dynamic Construction Process of Texts and Scaling Laws of Words Organization in Language Systems.

Directory of Open Access Journals (Sweden)

Shan Li

Full Text Available Scaling laws characterize diverse complex systems in a broad range of fields, including physics, biology, finance, and social science. The human language is another example of a complex system of words organization. Studies on written texts have shown that scaling laws characterize the occurrence frequency of words, words rank, and the growth of distinct words with increasing text length. However, these studies have mainly concentrated on the western linguistic systems, and the laws that govern the lexical organization, structure and dynamics of the Chinese language remain not well understood. Here we study a database of Chinese and English language books. We report that three distinct scaling laws characterize words organization in the Chinese language. We find that these scaling laws have different exponents and crossover behaviors compared to English texts, indicating different words organization and dynamics of words in the process of text growth. We propose a stochastic feedback model of words organization and text growth, which successfully accounts for the empirically observed scaling laws with their corresponding scaling exponents and characteristic crossover regimes. Further, by varying key model parameters, we reproduce differences in the organization and scaling laws of words between the Chinese and English language. We also identify functional relationships between model parameters and the empirically observed scaling exponents, thus providing new insights into the words organization and growth dynamics in the Chinese and English language.

Computer Processing and Display of Positron Scintigrams and Dynamic Function Curves

Energy Technology Data Exchange (ETDEWEB)

Wilensky, S.; Ashare, A. B.; Pizer, S. M.; Hoop, B. Jr.; Brownell, G. L. [Massachusetts General Hospital, Boston, MA (United States)

1969-01-15

A computer processing and display system for handling radioisotope data is described. The system has been used to upgrade and display brain scans and to process dynamic function curves. The hardware and software are described, and results are presented. (author)

Application of computer picture processing to dynamic strain measurement under electromagnetic field

International Nuclear Information System (INIS)

Yagawa, G.; Soneda, N.

1987-01-01

For the structural design of fusion reactors, it is very important to ensure the structural integrity of components under various dynamic loading conditions due to a solid-electromagnetic field interaction, an earthquake, MHD effects and so on. As one of the experimental approaches to assess the dynamic fracture, we consider the strain measurement near a crack tip under a transient electromagnetic field, which in general involves several experimental difficulties. The authors have developed a strain measurement method using a picture processing technique. In this method, locations of marks printed on a surface of specimen are determined by the picture processing. The displacement field is interpolated using the mark displacements and finite elements. Finally the strain distribution is calculated by differentiating the displacement field. In the present study, the method is improved and automated apply to the measurement of dynamic strain distribution under an electromagnetic field. Then the effects of dynamic loading on the strain distribution are investigated by comparing the dynamic results with the static ones. (orig./GL)

Molecular dynamics simulations of cluster fission and fusion processes

DEFF Research Database (Denmark)

Lyalin, Andrey G.; Obolensky, Oleg I.; Solov'yov, Ilia

2004-01-01

Results of molecular dynamics simulations of fission reactions Na_10^2+ --> Na_7^+ +Na_3^+ and Na_18^2+ --> 2Na_9^+ are presented. The dependence of the fission barriers on the isomer structure of the parent cluster is analyzed. It is demonstrated that the energy necessary for removing homothetic...... separation of the daughter fragments begins and/or forming a "neck" between the separating fragments. A novel algorithm for modeling the cluster growth process is described. This approach is based on dynamic search for the most stable cluster isomers and allows one to find the optimized cluster geometries...... groups of atoms from the parent cluster is largely independent of the isomer form of the parent cluster. The importance of rearrangement of the cluster structure during the fission process is elucidated. This rearrangement may include transition to another isomer state of the parent cluster before actual...

STREAM PROCESSING ALGORITHMS FOR DYNAMIC 3D SCENE ANALYSIS

Science.gov (United States)

2018-02-15

PROCESSING ALGORITHMS FOR DYNAMIC 3D SCENE ANALYSIS 5a. CONTRACT NUMBER FA8750-14-2-0072 5b. GRANT NUMBER N/A 5c. PROGRAM ELEMENT NUMBER 62788F 6...of Figures 1 The 3D processing pipeline flowchart showing key modules. . . . . . . . . . . . . . . . . 12 2 Overall view (data flow) of the proposed...pipeline flowchart showing key modules. from motion and bundle adjustment algorithm. By fusion of depth masks of the scene obtained from 3D

Observer-based linear parameter varying H∞ tracking control for hypersonic vehicles

Directory of Open Access Journals (Sweden)

Yiqing Huang

2016-11-01

Full Text Available This article aims to develop observer-based linear parameter varying output feedback H∞ tracking controller for hypersonic vehicles. Due to the complexity of an original nonlinear model of the hypersonic vehicle dynamics, a slow–fast loop linear parameter varying polytopic model is introduced for system stability analysis and controller design. Then, a state observer is developed by linear parameter varying technique in order to estimate the unmeasured attitude angular for slow loop system. Also, based on the designed linear parameter varying state observer, a kind of attitude tracking controller is presented to reduce tracking errors for all bounded reference attitude angular inputs. The closed-loop linear parameter varying system is proved to be quadratically stable by Lypapunov function technique. Finally, simulation results show that the developed linear parameter varying H∞ controller has good tracking capability for reference commands.

Light-Activated Gigahertz Ferroelectric Domain Dynamics

Science.gov (United States)

Akamatsu, Hirofumi; Yuan, Yakun; Stoica, Vladimir A.; Stone, Greg; Yang, Tiannan; Hong, Zijian; Lei, Shiming; Zhu, Yi; Haislmaier, Ryan C.; Freeland, John W.; Chen, Long-Qing; Wen, Haidan; Gopalan, Venkatraman

2018-03-01

Using time- and spatially resolved hard x-ray diffraction microscopy, the striking structural and electrical dynamics upon optical excitation of a single crystal of BaTiO3 are simultaneously captured on subnanoseconds and nanoscale within individual ferroelectric domains and across walls. A large emergent photoinduced electric field of up to 20 ×106 V /m is discovered in a surface layer of the crystal, which then drives polarization and lattice dynamics that are dramatically distinct in a surface layer versus bulk regions. A dynamical phase-field modeling method is developed that reveals the microscopic origin of these dynamics, leading to gigahertz polarization and elastic waves traveling in the crystal with sonic speeds and spatially varying frequencies. The advances in spatiotemporal imaging and dynamical modeling tools open up opportunities for disentangling ultrafast processes in complex mesoscale structures such as ferroelectric domains.

Family dynamics during the grieving process: a systematic literature review.

Science.gov (United States)

Delalibera, Mayra; Presa, Joana; Coelho, Alexandra; Barbosa, António; Franco, Maria Helena Pereira

2015-04-01

The loss of a loved one can affect family dynamics by changing the family system and creating the need for family members to reorganize. Good family functioning, which is characterized by open communication, expression of feelings and thoughts and cohesion among family members, facilitates adaptive adjustment to the loss. This study conducted a systematic review of the literature on family dynamics during the grieving process. A search was conducted in the EBSCO, Web of Knowledge and Bireme databases for scientific articles published from January 1980 to June 2013. Of the 389 articles found, only 15 met all the inclusion criteria. The selected studies provided evidence that dysfunctional families exhibit more psychopathological symptoms, more psychosocial morbidity, poorer social functioning, greater difficulty accessing community resources, lower functional capacity at work, and a more complicated grieving process. Family conflicts were also emphasized as contributing to the development of a complicated grieving process, while cohesion, expression of affection and good communication in families are believed to mitigate grief symptoms.

Dynamic tensile response of alumina-Al composites

International Nuclear Information System (INIS)

Atisivan, R.; Bandyopadhyay, A.; Gupta, Y. M.

2002-01-01

Plate impact experiments were carried out to examine the high strain-rate tensile response of alumina-aluminum (Al) composites with tailored microstructures. A novel processing technique was used to fabricate interpenetrating phase alumina-aluminum composites with controlled microstructures. Fused deposition modeling (FDM), a commercially available rapid prototyping technique, was used to produce the controlled porosity mullite ceramic preforms. Alumina-Al composites were then processed via reactive metal infiltration of porous mullite ceramics. With this approach, both the micro as well as the macro structures can be designed via computer aided design (CAD) to tailor the properties of the composites. Two sets of dynamic tensile experiments were performed. In the first, the metal content was varied between 23 and 39 wt. percent. In the second, the microstructure was varied while holding the metal content nearly constant. Samples with higher metal content, as expected, displayed better spall resistance. For a given metal content, samples with finer metal diameter showed better spall resistance. Relationship of the microstructural parameters on the dynamic tensile response of the structured composites is discussed here

A Low Cost Microcomputer System for Process Dynamics and Control Simulations.

Science.gov (United States)

Crowl, D. A.; Durisin, M. J.

1983-01-01

Discusses a video simulator microcomputer system used to provide real-time demonstrations to strengthen students' understanding of process dynamics and control. Also discusses hardware/software and simulations developed using the system. The four simulations model various configurations of a process liquid level tank system. (JN)

Dynamic Stimuli And Active Processing In Human Visual Perception

Science.gov (United States)

Haber, Ralph N.

1990-03-01

Theories of visual perception traditionally have considered a static retinal image to be the starting point for processing; and has considered processing both to be passive and a literal translation of that frozen, two dimensional, pictorial image. This paper considers five problem areas in the analysis of human visually guided locomotion, in which the traditional approach is contrasted to newer ones that utilize dynamic definitions of stimulation, and an active perceiver: (1) differentiation between object motion and self motion, and among the various kinds of self motion (e.g., eyes only, head only, whole body, and their combinations); (2) the sources and contents of visual information that guide movement; (3) the acquisition and performance of perceptual motor skills; (4) the nature of spatial representations, percepts, and the perceived layout of space; and (5) and why the retinal image is a poor starting point for perceptual processing. These newer approaches argue that stimuli must be considered as dynamic: humans process the systematic changes in patterned light when objects move and when they themselves move. Furthermore, the processing of visual stimuli must be active and interactive, so that perceivers can construct panoramic and stable percepts from an interaction of stimulus information and expectancies of what is contained in the visual environment. These developments all suggest a very different approach to the computational analyses of object location and identification, and of the visual guidance of locomotion.

A dynamic dual process model of risky decision making.

Science.gov (United States)

Diederich, Adele; Trueblood, Jennifer S

2018-03-01

Many phenomena in judgment and decision making are often attributed to the interaction of 2 systems of reasoning. Although these so-called dual process theories can explain many types of behavior, they are rarely formalized as mathematical or computational models. Rather, dual process models are typically verbal theories, which are difficult to conclusively evaluate or test. In the cases in which formal (i.e., mathematical) dual process models have been proposed, they have not been quantitatively fit to experimental data and are often silent when it comes to the timing of the 2 systems. In the current article, we present a dynamic dual process model framework of risky decision making that provides an account of the timing and interaction of the 2 systems and can explain both choice and response-time data. We outline several predictions of the model, including how changes in the timing of the 2 systems as well as time pressure can influence behavior. The framework also allows us to explore different assumptions about how preferences are constructed by the 2 systems as well as the dynamic interaction of the 2 systems. In particular, we examine 3 different possible functional forms of the 2 systems and 2 possible ways the systems can interact (simultaneously or serially). We compare these dual process models with 2 single process models using risky decision making data from Guo, Trueblood, and Diederich (2017). Using this data, we find that 1 of the dual process models significantly outperforms the other models in accounting for both choices and response times. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Microscopic dynamics and relaxation processes in liquid hydrogen fluoride

International Nuclear Information System (INIS)

Angelini, R.; Giura, P.; Monaco, G.; Sette, F.; Fioretto, D.; Ruocco, G.

2004-01-01

Inelastic x-ray scattering and Brillouin light scattering measurements of the dynamic structure factor of liquid hydrogen fluoride have been performed in the temperature range T=214-283 K. The data, analyzed using a viscoelastic model with a two time-scale memory function, show a positive dispersion of the sound velocity c(Q) between the low frequency value c 0 (Q) and the high frequency value c ∞α (Q). This finding confirms the existence of a structural (α) relaxation directly related to the dynamical organization of the hydrogen bonds network of the system. The activation energy E a of the process has been extracted by the analysis of the temperature behavior of the relaxation time τ α (T) that follows an Arrhenius law. The obtained value for E a , when compared with that observed in another hydrogen bond liquid as water, suggests that the main parameter governing the α-relaxation process is the number of hydrogen bonds per molecule

Capturing dynamic processes of change in GROW mutual help groups for mental health.

Science.gov (United States)

Finn, Lizzie D; Bishop, Brian J; Sparrow, Neville

2009-12-01

The need for a model that can portray dynamic processes of change in mutual help groups for mental health (MHGMHs) is emphasized. A dynamic process model has the potential to capture a more comprehensive understanding of how MHGMHs may assist their members. An investigation into GROW, a mutual help organization for mental health, employed ethnographic, phenomenological and collaborative research methods. The study examined how GROW impacts on psychological well being. Study outcomes aligned with the social ecological paradigm (Maton in Understanding the self-help organization: frameworks and findings. Sage, Thousand Oaks 1994) indicating multifactorial processes of change at and across three levels of analysis: group level, GROW program/community level and individual level. Outcome themes related to life skills acquisition and a change in self-perception in terms of belonging within community and an increased sense of personal value. The GROW findings are used to assist development of a dynamic multi-dimensional process model to explain how MHGMHs may promote positive change.

Image processing analysis of vortex dynamics of lobed jets from three-dimensional diffusers

International Nuclear Information System (INIS)

Nastase, Ilinca; Meslem, Amina; El Hassan, Mouhammad

2011-01-01

The passive control of jet flows with the aim to enhance mixing and entrainment is of wide practical interest. Our purpose here is to develop new air diffusers for heating ventilating air conditioning systems by using lobed geometry nozzles, in order to ameliorate the users' thermal comfort. Two turbulent six-lobed air jets, issued from a lobed tubular nozzle and an innovative hemispherical lobed nozzle, were studied experimentally. It was shown that the proposed innovative concept of a lobed jet, which can be easily integrated in air diffusion devices, is very efficient regarding induction capability. A vortical dynamics analysis for the two jets is performed using a new method of image processing, namely dynamic mode decomposition. A validation of this method is also proposed suggesting that the dynamical mode decomposition (DMD) image processing method succeeds in capturing the most dominant frequencies of the flow dynamics, which in our case are related to the quite special dynamics of the Kelvin–Helmholtz vortices.

Dynamic Optimization of Feedforward Automatic Gauge Control Based on Extended Kalman Filter

Institute of Scientific and Technical Information of China (English)

YANG Bin-hu; YANG Wei-dong; CHEN Lian-gui; QU Lei

2008-01-01

Automatic gauge control is an essentially nonlinear process varying with time delay, and stochastically varying input and process noise always influence the target gauge control accuracy. To improve the control capability of feedforward automatic gauge control, Kalman filter was employed to filter the noise signal transferred from one stand to another. The linearized matrix that the Kalman filter algorithm needed was concluded; thus, the feedforward automatic gauge control architecture was dynamically optimized. The theoretical analyses and simulation show that the proposed algorithm is reasonable and effective.

r-process nucleosynthesis in dynamic helium-burning environments

International Nuclear Information System (INIS)

Cowan, J.J.; Cameron, A.G.W.; Truran, J.W.

1985-01-01

The results of an extended examination of r-process nucleosynthesis in helium-burning environments are presented. Using newly calculated nuclear rates, dynamical r-process calculations have been made of thermal runaways in helium cores typical of low-mass stars and in the helium zones of stars undergoing supernova explosions. These calculations show that, for a sufficient flux of neutrons produced by the 13 C neutron source, r-process nuclei in solar proportions can be produced. The conditions required for r-process production are found to be: 10 20 --10 21 neutrons cm -3 for times of 0.01--0.1 s and neutron number densities in excess of 10 19 cm -3 for times of approx.1 s. The amount of 13 C required is found to be exceedingly high: larger than is found to occur in any current stellar evolutionary model. It is thus unlikely that these helium-burning environments are responsible for producing the bulk of the r-process elements seen in the solar system

Continuous process tracing and the Iowa Gambling Task: Extending response dynamics to multialternative choice

Directory of Open Access Journals (Sweden)

Gregory J. Koop

2011-12-01

Full Text Available The history of judgment and decision making is defined by a trend toward increasingly nuanced explanations of the decision making process. Recently, process models have become incredibly sophisticated, yet the tools available to directly test these models have not kept pace. These increasingly complex process models require increasingly complex process data by which they can be adequately tested. We propose a new class of data collection that will facilitate evaluation of sophisticated process models. Tracking mouse paths during a continuous response provides an implicit measure of the growth of preference that produces a choice---rather than the current practice of recording just the button press that indicates that choice itself. Recent research in cognitive science (Spivey and Dale, 2006 has shown that cognitive processing can be revealed in these dynamic motor responses. Unlike current process methodologies, these response dynamics studies can demonstrate continuous competition between choice options and even online preference reversals. Here, in order to demonstrate the mechanics and utility of the methodology, we present an example response dynamics experiment utilizing a common multi-alternative decision task.

Automatic differentiation tools in the dynamic simulation of chemical engineering processes

Directory of Open Access Journals (Sweden)

Castro M.C.

2000-01-01

Full Text Available Automatic Differentiation is a relatively recent technique developed for the differentiation of functions applicable directly to the source code to compute the function written in standard programming languages. That technique permits the automatization of the differentiation step, crucial for dynamic simulation and optimization of processes. The values for the derivatives obtained with AD are exact (to roundoff. The theoretical exactness of the AD comes from the fact that it uses the same rules of differentiation as in differential calculus, but these rules are applied to an algorithmic specification of the function rather than to a formula. The main purpose of this contribution is to discuss the impact of Automatic Differentiation in the field of dynamic simulation of chemical engineering processes. The influence of the differentiation technique on the behavior of the integration code, the performance of the generated code and the incorporation of AD tools in consistent initialization tools are discussed from the viewpoint of dynamic simulation of typical models in chemical engineering.

Modelling dynamic processes in a nuclear reactor by state change modal method

Science.gov (United States)

Avvakumov, A. V.; Strizhov, V. F.; Vabishchevich, P. N.; Vasilev, A. O.

2017-12-01

Modelling of dynamic processes in nuclear reactors is carried out, mainly, using the multigroup neutron diffusion approximation. The basic model includes a multidimensional set of coupled parabolic equations and ordinary differential equations. Dynamic processes are modelled by a successive change of the reactor states. It is considered that the transition from one state to another occurs promptly. In the modal method the approximate solution is represented as eigenfunction expansion. The numerical-analytical method is based on the use of dominant time-eigenvalues of a group diffusion model taking into account delayed neutrons.

Estimation of time-varying reactivity by the H∞ optimal linear filter

International Nuclear Information System (INIS)

Suzuki, Katsuo; Shimazaki, Junya; Watanabe, Koiti

1995-01-01

The problem of estimating the time-varying net reactivity from flux measurements is solved for a point reactor kinetics model using a linear filtering technique in an H ∞ settings. In order to sue this technique, an appropriate dynamical model of the reactivity is constructed that can be embedded into the reactor model as one of its variables. A filter, which minimizes the H ∞ norm of the estimation error power spectrum, operates on neutron density measurements corrupted by noise and provides an estimate of the dynamic net reactivity. Computer simulations are performed to reveal the basic characteristics of the H ∞ optimal filter. The results of the simulation indicate that the filter can be used to determine the time-varying reactivity from neutron density measurements that have been corrupted by noise

Time-varying properties of renal autoregulatory mechanisms

DEFF Research Database (Denmark)

Zou, Rui; Cupples, Will A; Yip, K P

2002-01-01

In order to assess the possible time-varying properties of renal autoregulation, time-frequency and time-scaling methods were applied to renal blood flow under broad-band forced arterial blood pressure fluctuations and single-nephron renal blood flow with spontaneous oscillations obtained from...... normotensive (Sprague-Dawley, Wistar, and Long-Evans) rats, and spontaneously hypertensive rats. Time-frequency analyses of normotensive and hypertensive blood flow data obtained from either the whole kidney or the single-nephron show that indeed both the myogenic and tubuloglomerular feedback (TGF) mechanisms...... have time-varying characteristics. Furthermore, we utilized the Renyi entropy to measure the complexity of blood-flow dynamics in the time-frequency plane in an effort to discern differences between normotensive and hypertensive recordings. We found a clear difference in Renyi entropy between...

Exploring process dynamics by near infrared spectroscopy in lactic fermentations

DEFF Research Database (Denmark)

Svendsen, Carina; Cieplak, Tomasz; van der Berg, Franciscus Winfried J

2016-01-01

In the industrial production of yoghurt, measurement of pH is normally the only in-line technique applied as a real-time monitoring signalfor following the dynamics during the fermentation process. However, every dairy company would benefit from an in-line technique giving information about...... the chemical composition, physical/textural properties and/or microbial contamination. In this study lactic fermentation batches with the starter bacteria Streptococcus thermophilus and Lactobacillus delbrueckii subsp. bulgaricus are explored by in-line near infrared (NIR) spectroscopy. The dynamics obtained...

Systematic and heuristic processing of majority and minority-endorsed messages: the effects of varying outcome relevance and levels of orientation on attitude and message processing.

Science.gov (United States)

Martin, Robin; Hewstone, Miles; Martin, Pearl Y

2007-01-01

Two experiments investigated the conditions under which majority and minority sources instigate systematic processing of their messages. Both experiments crossed source status (majority vs. minority) with message quality (strong vs. weak arguments). In each experiment, message elaboration was manipulated by varying either motivational (outcome relevance, Experiment 1) or cognitive (orientating tasks, Experiment 2) factors. The results showed that when either motivational or cognitive factors encouraged low message elaboration, there was heuristic acceptance of the majority position without detailed message processing. When the level of message elaboration was intermediate, there was message processing only for the minority source. Finally, when message elaboration was high, there was message processing for both source conditions. These results show that majority and minority influence is sensitive to motivational and cognitive factors that constrain or enhance message elaboration and that both sources can lead to systematic processing under specific circumstances.

A linear dynamic model for rotor-spun composite yarn spinning process

International Nuclear Information System (INIS)

Yang, R H; Wang, S Y

2008-01-01

A linear dynamic model is established for the stable rotor-spun composite yarn spinning process. Approximate oscillating frequencies in the vertical and horizontal directions are obtained. By suitable choice of certain processing parameters, the mixture construction after the convergent point can be optimally matched. The presented study is expected to provide a general pathway to understand the motion of the rotor-spun composite yarn spinning process

A dynamic processes study of PM retention by trees under different wind conditions.

Science.gov (United States)

Xie, Changkun; Kan, Liyan; Guo, Jiankang; Jin, Sijia; Li, Zhigang; Chen, Dan; Li, Xin; Che, Shengquan

2018-02-01

Particulate matter (PM) is one of the most serious environmental problems, exacerbating respiratory and vascular illnesses. Plants have the ability to reduce non-point source PM pollution through retention on leaves and branches. Studies of the dynamic processes of PM retention by plants and the mechanisms influencing this process will help to improve the efficiency of urban greening for PM reduction. We examined dynamic processes of PM retention and the major factors influencing PM retention by six trees with different branch structure characteristics in wind tunnel experiments at three different wind speeds. The results showed that the changes of PM numbers retained by plant leaves over time were complex dynamic processes for which maximum values could exceed minimum values by over 10 times. The average value of PM measured in multiple periods and situations can be considered a reliable indicator of the ability of the plant to retain PM. The dynamic processes were similar for PM 10 and PM 2.5 . They could be clustered into three groups simulated by continually-rising, inverse U-shaped, and U-shaped polynomial functions, respectively. The processes were the synthetic effect of characteristics such as species, wind speed, period of exposure and their interactions. Continually-rising functions always explained PM retention in species with extremely complex branch structure. Inverse U-shaped processes explained PM retention in species with relatively simple branch structure and gentle wind. The U-shaped processes mainly explained PM retention at high wind speeds and in species with a relatively simple crown. These results indicate that using plants with complex crowns in urban greening and decreasing wind speed in plant communities increases the chance of continually-rising or inverse U-shaped relationships, which have a positive effect in reducing PM pollution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Modeling Dynamic Processes in Smallholder Dairy Value Chains in Nicaragua: A System Dynamics Approach

Directory of Open Access Journals (Sweden)

Helene Lie

2016-08-01

Full Text Available In Nicaragua, the production of dairy and beef is the most important source of household income for many smallholder producers. However, erratic volumes and quality of milk limit the participation of small- and medium-scale cattle farmers into higher-value dairy value chains. This research uses a system dynamics (SD approach to analyze the Matiguás dairy value chain in Nicaragua. The paper presents the conceptual framework of the model and highlights the dynamic processes in the value chain, with a focus on improving feeding systems to achieve higher milk productivity and increased income for producers. The model was developed using a participatory group model building (GMB technique to jointly conceptualize and validate the model with stakeholders.

Adaptive Process Management in Highly Dynamic and Pervasive Scenarios

Directory of Open Access Journals (Sweden)

Massimiliano de Leoni

2009-06-01

Full Text Available Process Management Systems (PMSs are currently more and more used as a supporting tool for cooperative processes in pervasive and highly dynamic situations, such as emergency situations, pervasive healthcare or domotics/home automation. But in all such situations, designed processes can be easily invalidated since the execution environment may change continuously due to frequent unforeseeable events. This paper aims at illustrating the theoretical framework and the concrete implementation of SmartPM, a PMS that features a set of sound and complete techniques to automatically cope with unplanned exceptions. PMS SmartPM is based on a general framework which adopts the Situation Calculus and Indigolog.

Contagion processes on the static and activity driven coupling networks

OpenAIRE

Lei, Yanjun; Jiang, Xin; Guo, Quantong; Ma, Yifang; Li, Meng; Zheng, Zhiming

2015-01-01

The evolution of network structure and the spreading of epidemic are common coexistent dynamical processes. In most cases, network structure is treated either static or time-varying, supposing the whole network is observed in a same time window. In this paper, we consider the epidemic spreading on a network consisting of both static and time-varying structures. At meanwhile, the time-varying part and the epidemic spreading are supposed to be of the same time scale. We introduce a static and a...

Family dynamics during the grieving process: a systematic literature review

Directory of Open Access Journals (Sweden)

Mayra Delalibera

2015-04-01

Full Text Available The loss of a loved one can affect family dynamics by changing the family system and creating the need for family members to reorganize. Good family functioning, which is characterized by open communication, expression of feelings and thoughts and cohesion among family members, facilitates adaptive adjustment to the loss. This study conducted a systematic review of the literature on family dynamics during the grieving process. A search was conducted in the EBSCO, Web of Knowledge and Bireme databases for scientific articles published from January 1980 to June 2013. Of the 389 articles found, only 15 met all the inclusion criteria. The selected studies provided evidence that dysfunctional families exhibit more psychopathological symptoms, more psychosocial morbidity, poorer social functioning, greater difficulty accessing community resources, lower functional capacity at work, and a more complicated grieving process. Family conflicts were also emphasized as contributing to the development of a complicated grieving process, while cohesion, expression of affection and good communication in families are believed to mitigate grief symptoms.

DYNAMIC MODELLING AND ADVANCED PREDICTIVE CONTROL OF A CONTINUOUS PROCESS OF ENZYME PURIFICATION

Directory of Open Access Journals (Sweden)

Dechechi E.C.

1997-01-01

Full Text Available A dynamic mathematical model, simulation and computer control of a Continuous Affinity Recycle Extraction (CARE process, a protein purification technique based on protein adsorption on solid-phase adsorbents is described in this work. This process, consisting of three reactors, is a multivariable process with considerable time delay in the on-line analyses of the controlled variable. An advanced predictive control configuration, specifically the Dynamic Matrix Control (DMC, was applied. The DMC algorithm was applied in process schemes where the aim was to maintain constant the enzyme concentration in the outlet of the third reactor. The performance of the DMC controller was analyzed in the feed-flow disturbances and the results are presented.

Detection of random alterations to time-varying musical instrument spectra.

Science.gov (United States)

Horner, Andrew; Beauchamp, James; So, Richard

2004-09-01

The time-varying spectra of eight musical instrument sounds were randomly altered by a time-invariant process to determine how detection of spectral alteration varies with degree of alteration, instrument, musical experience, and spectral variation. Sounds were resynthesized with centroids equalized to the original sounds, with frequencies harmonically flattened, and with average spectral error levels of 8%, 16%, 24%, 32%, and 48%. Listeners were asked to discriminate the randomly altered sounds from reference sounds resynthesized from the original data. For all eight instruments, discrimination was very good for the 32% and 48% error levels, moderate for the 16% and 24% error levels, and poor for the 8% error levels. When the error levels were 16%, 24%, and 32%, the scores of musically experienced listeners were found to be significantly better than the scores of listeners with no musical experience. Also, in this same error level range, discrimination was significantly affected by the instrument tested. For error levels of 16% and 24%, discrimination scores were significantly, but negatively correlated with measures of spectral incoherence and normalized centroid deviation on unaltered instrument spectra, suggesting that the presence of dynamic spectral variations tends to increase the difficulty of detecting spectral alterations. Correlation between discrimination and a measure of spectral irregularity was comparatively low.

Stochastic evolution of the Universe: A possible dynamical process ...

Indian Academy of Sciences (India)

C Sivakumar

2017-12-11

Dec 11, 2017 ... https://doi.org/10.1007/s12043-017-1491-z. Stochastic evolution of the Universe: A possible dynamical process leading to fractal structures. C SIVAKUMAR. Department of Physics, Maharaja's College, Ernakulam 682 011, India. E-mail: thrisivc@yahoo.com. MS received 6 July 2016; revised 26 June 2017; ...

Variations in calcite growth kinetics with surface topography: molecular dynamics simulations and process-based growth kinetics modelling

NARCIS (Netherlands)

Wolthers, M.; Di Tommaso, D.; Du, Zhimei; de Leeuw, Nora H.

2013-01-01

It is generally accepted that cation dehydration is the rate-limiting step to crystal growth from aqueous solution. Here we employ classical molecular dynamics simulations to show that the water exchange frequency at structurally distinct calcium sites in the calcite surface varies by about two

Dynamics of the anaerobic process: Effects of volatile fatty acids

DEFF Research Database (Denmark)

Pind, Peter Frode; Angelidaki, Irini; Ahring, Birgitte Kiær

2003-01-01

A complex and fast dynamic response of the anaerobic biogas system was observed when the system was subjected to pulses of volatile fatty acids (VFAs). It was shown that a pulse of specific VFAs into a well-functioning continuous stirred tank reactor (CSTR) system operating on cow manure affected...... and the history of the reactor process. It should be pointed out that the observed dynamics of VFA responses were based on hourly measurements, meaning that the response duration was much lower than the hydraulic retention time, which exceeds several days in anaerobic CSTR systems....

The computation of dynamic fractional difference parameter for S&P500 index

Science.gov (United States)

Pei, Tan Pei; Cheong, Chin Wen; Galagedera, Don U. A.

2015-10-01

This study evaluates the time-varying long memory behaviors of the S&P500 volatility index using dynamic fractional difference parameters. Time-varying fractional difference parameter shows the dynamic of long memory in volatility series for the pre and post subprime mortgage crisis triggered by U.S. The results find an increasing trend in the S&P500 long memory volatility for the pre-crisis period. However, the onset of Lehman Brothers event reduces the predictability of volatility series following by a slight fluctuation of the factional differencing parameters. After that, the U.S. financial market becomes more informationally efficient and follows a non-stationary random process.

Loading Processes Dynamics Modelling Taking into Account the Bucket-Soil Interaction

Directory of Open Access Journals (Sweden)

Carmen Debeleac

2007-10-01

Full Text Available The author propose three dynamic models specialized for the vibrations and resistive forces analysis that appear at the loading process with different construction equipment like frontal loaders and excavators.The models used putting into evidence the components of digging: penetration, cutting, and loading.The conclusions of this study consist by evidentiate the dynamic overloads that appear on the working state and that induced the self-oscillations into the equipment structure.

High speed, wide dynamic range analog signal processing for avalanche photodiode

CERN Document Server

Walder, J P; Pangaud, P

2000-01-01

A wide dynamic range multi-gain analog transimpedance amplifier integrated circuit has been developed for avalanche photodiode signal processing. The 96 dB input dynamic range is divided into four ranges of 12-bits each in order to provide 40 MHz analog sampled data to a 12-bits ADC. This concept which has been integrated in both BiCMOS and full complementary bipolar technology along with fitted design techniques will be presented.

High speed, wide dynamic range analog signal processing for avalanche photodiode

International Nuclear Information System (INIS)

Walder, J.P.; El Mamouni, Houmani; Pangaud, Patrick

2000-01-01

A wide dynamic range multi-gain analog transimpedance amplifier integrated circuit has been developed for avalanche photodiode signal processing. The 96 dB input dynamic range is divided into four ranges of 12-bits each in order to provide 40 MHz analog sampled data to a 12-bits ADC. This concept which has been integrated in both BiCMOS and full complementary bipolar technology along with fitted design techniques will be presented

High speed, wide dynamic range analog signal processing for avalanche photodiode

Energy Technology Data Exchange (ETDEWEB)

Walder, J.P. E-mail: walder@in2p3.fr; El Mamouni, Houmani; Pangaud, Patrick

2000-03-11

A wide dynamic range multi-gain analog transimpedance amplifier integrated circuit has been developed for avalanche photodiode signal processing. The 96 dB input dynamic range is divided into four ranges of 12-bits each in order to provide 40 MHz analog sampled data to a 12-bits ADC. This concept which has been integrated in both BiCMOS and full complementary bipolar technology along with fitted design techniques will be presented.

Dynamical analysis of yeast protein interaction network during the sake brewing process.

Science.gov (United States)

Mirzarezaee, Mitra; Sadeghi, Mehdi; Araabi, Babak N

2011-12-01

Proteins interact with each other for performing essential functions of an organism. They change partners to get involved in various processes at different times or locations. Studying variations of protein interactions within a specific process would help better understand the dynamic features of the protein interactions and their functions. We studied the protein interaction network of Saccharomyces cerevisiae (yeast) during the brewing of Japanese sake. In this process, yeast cells are exposed to several stresses. Analysis of protein interaction networks of yeast during this process helps to understand how protein interactions of yeast change during the sake brewing process. We used gene expression profiles of yeast cells for this purpose. Results of our experiments revealed some characteristics and behaviors of yeast hubs and non-hubs and their dynamical changes during the brewing process. We found that just a small portion of the proteins (12.8 to 21.6%) is responsible for the functional changes of the proteins in the sake brewing process. The changes in the number of edges and hubs of the yeast protein interaction networks increase in the first stages of the process and it then decreases at the final stages.

Epidemic spread in coupled populations with seasonally varying migration rates

Science.gov (United States)

Muzyczyn, Adam; Shaw, Leah B.

2009-03-01

The H5N1 strain of avian influenza has spread worldwide, and this spread may be due to seasonal migration of birds and mixing of birds from different regions in the wintering grounds. We studied a multipatch model for avian influenza with seasonally varying migration rates. The bird population was divided into two spatially distinct patches, or subpopulations. Within each patch, the disease followed the SIR (susceptible-infected-recovered) model for epidemic spread. Migration rates were varied periodically, with a net flux toward the breeding grounds during the spring and towards the wintering grounds during the fall. The case of two symmetric patches reduced to single-patch SIR dynamics. However, asymmetry in the birth and contact rates in the breeding grounds and wintering grounds led to bifurcations to longer period orbits and chaotic dynamics. We studied the bifurcation structure of the model and the phase relationships between outbreaks in the two patches.

Characterizing Dynamic Walking Patterns and Detecting Falls with Wearable Sensors Using Gaussian Process Methods

Directory of Open Access Journals (Sweden)

Taehwan Kim

2017-05-01

Full Text Available By incorporating a growing number of sensors and adopting machine learning technologies, wearable devices have recently become a prominent health care application domain. Among the related research topics in this field, one of the most important issues is detecting falls while walking. Since such falls may lead to serious injuries, automatically and promptly detecting them during daily use of smartphones and/or smart watches is a particular need. In this paper, we investigate the use of Gaussian process (GP methods for characterizing dynamic walking patterns and detecting falls while walking with built-in wearable sensors in smartphones and/or smartwatches. For the task of characterizing dynamic walking patterns in a low-dimensional latent feature space, we propose a novel approach called auto-encoded Gaussian process dynamical model, in which we combine a GP-based state space modeling method with a nonlinear dimensionality reduction method in a unique manner. The Gaussian process methods are fit for this task because one of the most import strengths of the Gaussian process methods is its capability of handling uncertainty in the model parameters. Also for detecting falls while walking, we propose to recycle the latent samples generated in training the auto-encoded Gaussian process dynamical model for GP-based novelty detection, which can lead to an efficient and seamless solution to the detection task. Experimental results show that the combined use of these GP-based methods can yield promising results for characterizing dynamic walking patterns and detecting falls while walking with the wearable sensors.

r-process nucleosynthesis in dynamic helium-burning environments

Science.gov (United States)

Cowan, J. J.; Cameron, A. G. W.; Truran, J. W.

1985-01-01

The results of an extended examination of r-process nucleosynthesis in helium-burning enviroments are presented. Using newly calculated nuclear rates, dynamical r-process calculations have been made of thermal runaways in helium cores typical of low-mass stars and in the helium zones of stars undergoing supernova explosions. These calculations show that, for a sufficient flux of neutrons produced by the C-13 neutron source, r-process nuclei in solar proportions can be produced. The conditions required for r-process production are found to be 10 to the 20th-10 to the 21st neutrons per cubic centimeter for times of 0.01-0.1 s and neutron number densities in excess of 10 to the 19th per cubic centimeter for times of about 1 s. The amount of C-13 required is found to be exceedingly high - larger than is found to occur in any current stellar evolutionary model. It is thus unlikely that these helium-burning environments are responsible for producing the bulk of the r-process elements seen in the solar system.

Reinforcement learning for partially observable dynamic processes: adaptive dynamic programming using measured output data.

Science.gov (United States)

Lewis, F L; Vamvoudakis, Kyriakos G

2011-02-01

Approximate dynamic programming (ADP) is a class of reinforcement learning methods that have shown their importance in a variety of applications, including feedback control of dynamical systems. ADP generally requires full information about the system internal states, which is usually not available in practical situations. In this paper, we show how to implement ADP methods using only measured input/output data from the system. Linear dynamical systems with deterministic behavior are considered herein, which are systems of great interest in the control system community. In control system theory, these types of methods are referred to as output feedback (OPFB). The stochastic equivalent of the systems dealt with in this paper is a class of partially observable Markov decision processes. We develop both policy iteration and value iteration algorithms that converge to an optimal controller that requires only OPFB. It is shown that, similar to Q -learning, the new methods have the important advantage that knowledge of the system dynamics is not needed for the implementation of these learning algorithms or for the OPFB control. Only the order of the system, as well as an upper bound on its "observability index," must be known. The learned OPFB controller is in the form of a polynomial autoregressive moving-average controller that has equivalent performance with the optimal state variable feedback gain.

Accelerating Molecular Dynamic Simulation on Graphics Processing Units

Science.gov (United States)

Friedrichs, Mark S.; Eastman, Peter; Vaidyanathan, Vishal; Houston, Mike; Legrand, Scott; Beberg, Adam L.; Ensign, Daniel L.; Bruns, Christopher M.; Pande, Vijay S.

2009-01-01

We describe a complete implementation of all-atom protein molecular dynamics running entirely on a graphics processing unit (GPU), including all standard force field terms, integration, constraints, and implicit solvent. We discuss the design of our algorithms and important optimizations needed to fully take advantage of a GPU. We evaluate its performance, and show that it can be more than 700 times faster than a conventional implementation running on a single CPU core. PMID:19191337

Hawkes process as a model of social interactions: a view on video dynamics

International Nuclear Information System (INIS)

Mitchell, Lawrence; Cates, Michael E

2010-01-01

We study by computer simulation the 'Hawkes process' that was proposed in a recent paper by Crane and Sornette (2008 Proc. Natl Acad. Sci. USA 105 15649) as a plausible model for the dynamics of YouTube video viewing numbers. We test the claims made there that robust identification is possible for classes of dynamic response following activity bursts. Our simulated time series for the Hawkes process indeed fall into the different categories predicted by Crane and Sornette. However, the Hawkes process gives a much narrower spread of decay exponents than the YouTube data, suggesting limits to the universality of the Hawkes-based analysis.

Hawkes process as a model of social interactions: a view on video dynamics

Energy Technology Data Exchange (ETDEWEB)

Mitchell, Lawrence; Cates, Michael E, E-mail: lawrence.mitchell@ed.ac.u [SUPA, School of Physics and Astronomy, University of Edinburgh, JCMB Kings Buildings, Mayfield Road, Edinburgh EH9 3JZ (United Kingdom)

2010-01-29

We study by computer simulation the 'Hawkes process' that was proposed in a recent paper by Crane and Sornette (2008 Proc. Natl Acad. Sci. USA 105 15649) as a plausible model for the dynamics of YouTube video viewing numbers. We test the claims made there that robust identification is possible for classes of dynamic response following activity bursts. Our simulated time series for the Hawkes process indeed fall into the different categories predicted by Crane and Sornette. However, the Hawkes process gives a much narrower spread of decay exponents than the YouTube data, suggesting limits to the universality of the Hawkes-based analysis.

Hawkes process as a model of social interactions: a view on video dynamics

Energy Technology Data Exchange (ETDEWEB)

Mitchell, Lawrence; Cates, Michael E, E-mail: lawrence.mitchell@ed.ac.u [SUPA, School of Physics and Astronomy, University of Edinburgh, JCMB Kings Buildings, Mayfield Road, Edinburgh EH9 3JZ (United Kingdom)

2010-01-29

We study by computer simulation the 'Hawkes process' that was proposed in a recent paper by Crane and Sornette (2008 Proc. Natl Acad. Sci. USA 105 15649) as a plausible model for the dynamics of YouTube video viewing numbers. We test the claims made there that robust identification is possible for classes of dynamic response following activity bursts. Our simulated time series for the Hawkes process indeed fall into the different categories predicted by Crane and Sornette. However, the Hawkes process gives a much narrower spread of decay exponents than the YouTube data, suggesting limits to the universality of the Hawkes-based analysis.

Evolutionary Game Dynamics in a Fitness-Dependent Wright-Fisher Process with Noise

International Nuclear Information System (INIS)

Quan Ji; Wang Xianjia

2011-01-01

Evolutionary game dynamics in finite size populations can be described by a fitness-dependent Wright-Fisher process. We consider symmetric 2x2 games in a well-mixed population. In our model, two parameters to describe the level of player's rationality and noise intensity in environment are introduced. In contrast with the fixation probability method that used in a noiseless case, the introducing of the noise intensity parameter makes the process an ergodic Markov process and based on the limit distribution of the process, we can analysis the evolutionary stable strategy (ESS) of the games. We illustrate the effects of the two parameters on the ESS of games using the Prisoner's dilemma games (PDG) and the snowdrift games (SG). We also compare the ESS of our model with that of the replicator dynamics in infinite size populations. The results are determined by simulation experiments. (general)

Dynamic Training Elements in a Circuit Theory Course to Implement a Self-Directed Learning Process

Science.gov (United States)

Krouk, B. I.; Zhuravleva, O. B.

2009-01-01

This paper reports on the implementation of a self-directed learning process in a circuit theory course, incorporating dynamic training elements which were designed on the basis of a cybernetic model of cognitive process management. These elements are centrally linked in a dynamic learning frame, created on the monitor screen, which displays the…

Quantum Processes and Dynamic Networks in Physical and Biological Systems.

Science.gov (United States)

Dudziak, Martin Joseph

Quantum theory since its earliest formulations in the Copenhagen Interpretation has been difficult to integrate with general relativity and with classical Newtonian physics. There has been traditionally a regard for quantum phenomena as being a limiting case for a natural order that is fundamentally classical except for microscopic extrema where quantum mechanics must be applied, more as a mathematical reconciliation rather than as a description and explanation. Macroscopic sciences including the study of biological neural networks, cellular energy transports and the broad field of non-linear and chaotic systems point to a quantum dimension extending across all scales of measurement and encompassing all of Nature as a fundamentally quantum universe. Theory and observation lead to a number of hypotheses all of which point to dynamic, evolving networks of fundamental or elementary processes as the underlying logico-physical structure (manifestation) in Nature and a strongly quantized dimension to macroscalar processes such as are found in biological, ecological and social systems. The fundamental thesis advanced and presented herein is that quantum phenomena may be the direct consequence of a universe built not from objects and substance but from interacting, interdependent processes collectively operating as sets and networks, giving rise to systems that on microcosmic or macroscopic scales function wholistically and organically, exhibiting non-locality and other non -classical phenomena. The argument is made that such effects as non-locality are not aberrations or departures from the norm but ordinary consequences of the process-network dynamics of Nature. Quantum processes are taken to be the fundamental action-events within Nature; rather than being the exception quantum theory is the rule. The argument is also presented that the study of quantum physics could benefit from the study of selective higher-scale complex systems, such as neural processes in the brain

Dynamic contrast-enhanced MRI of the prostate. Comparison of two different post-processing algorithms

International Nuclear Information System (INIS)

Beyersdorff, Dirk; Franiel, T.; Luedemann, L.; Dietz, E.; Galler, D.; Marchot, P.

2011-01-01

Purpose: To evaluate the usefulness of a commercially available post-processing software tool for detecting prostate cancer on dynamic contrast-enhanced magnetic resonance imaging (MRI) and to compare the results to those obtained with a custom-made post-processing algorithm already tested under clinical conditions. Materials and Methods: Forty-eight patients with proven prostate cancer were examined by standard MRI supplemented by dynamic contrast-enhanced dual susceptibility contrast (DCE-DSC) MRI prior to prostatectomy. A custom-made post-processing algorithm was used to analyze the MRI data sets and the results were compared to those obtained using a post-processing algorithm from Invivo Corporation (Dyna CAD for Prostate) applied to dynamic T 1-weighted images. Histology was used as the gold standard. Results: The sensitivity for prostate cancer detection was 78 % for the custom-made algorithm and 60 % for the commercial algorithm and the specificity was 79 % and 82 %, respectively. The accuracy was 79 % for our algorithm and 77.5 % for the commercial software tool. The chi-square test (McNemar-Bowker test) yielded no significant differences between the two tools (p = 0.06). Conclusion: The two investigated post-processing algorithms did not differ in terms of prostate cancer detection. The commercially available software tool allows reliable and fast analysis of dynamic contrast-enhanced MRI for the detection of prostate cancer. (orig.)

Recrystallization kinetics of nanostructured copper processed by dynamic plastic deformation

DEFF Research Database (Denmark)

Lin, Fengxiang; Zhang, Yubin; Pantleon, Wolfgang

2012-01-01

The recrystallization kinetics of nanostructured copper samples processed by dynamic plastic deformation was investigated by electron backscatter diffraction. It was found that the evolution of the recrystallized volume fraction as a function of annealing time has a very low slope (n=0.37) when...

Dynamic modeling of the isoamyl acetate reactive distillation process

Directory of Open Access Journals (Sweden)

Ali Syed Sadiq

2017-03-01

Full Text Available The cost-effectiveness of reactive distillation (RD processes makes them highly attractive for industrial applications. However, their preliminary design and subsequent scale-up and operation are challenging. Specifically, the response of RD system during fluctuations in process parameters is of paramount importance to ensure the stability of the whole process. As a result of carrying out simulations using Aspen Plus, it is shown that the RD process for isoamyl acetate production was much more economical than conventional reactor distillation configuration under optimized process conditions due to lower utilities consumption, higher conversion and smaller sizes of condenser and reboiler. Rigorous dynamic modeling of RD system was performed to evaluate its sensitivity to disturbances in critical process parameters; the product flow was quite sensitive to disturbances. Even more sensitive was product composition when the disturbance in heat duties of condenser or reboiler led to a temperature decrease. However, positive disturbance in alcohol feed is of particular concern, which clearly made the system unstable.

Dynamics of a Bioreactor with a Bacteria Piecewise-Linear Growth Model in a Methane-Producing Process

Directory of Open Access Journals (Sweden)

Luz A. Melo Varela

2013-01-01

Full Text Available This paper shows a study, both analytical and numerical, of a continuous-time dynamical system associated with a simple model of a wastewater biorreactor. Nonsmooth phenomena and border-collision local bifurcations appear when the main parameters (dilution and biomass concentration at the inflow are varied. We apply the Filippov methods following Kuznetsov’s work.

Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

Directory of Open Access Journals (Sweden)

Mauricio Herrera

Full Text Available There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions.

Integrable Floquet dynamics, generalized exclusion processes and "fused" matrix ansatz

Science.gov (United States)

Vanicat, Matthieu

2018-04-01

We present a general method for constructing integrable stochastic processes, with two-step discrete time Floquet dynamics, from the transfer matrix formalism. The models can be interpreted as a discrete time parallel update. The method can be applied for both periodic and open boundary conditions. We also show how the stationary distribution can be built as a matrix product state. As an illustration we construct parallel discrete time dynamics associated with the R-matrix of the SSEP and of the ASEP, and provide the associated stationary distributions in a matrix product form. We use this general framework to introduce new integrable generalized exclusion processes, where a fixed number of particles is allowed on each lattice site in opposition to the (single particle) exclusion process models. They are constructed using the fusion procedure of R-matrices (and K-matrices for open boundary conditions) for the SSEP and ASEP. We develop a new method, that we named "fused" matrix ansatz, to build explicitly the stationary distribution in a matrix product form. We use this algebraic structure to compute physical observables such as the correlation functions and the mean particle current.

Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

Science.gov (United States)

Herrera, Mauricio; Armelini, Guillermo; Salvaj, Erica

2015-01-01

There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions.

Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks

Science.gov (United States)

2015-01-01

There are many studies in the marketing and diffusion literature of the conditions in which social contagion affects adoption processes. Yet most of these studies assume that social interactions do not change over time, even though actors in social networks exhibit different likelihoods of being influenced across the diffusion period. Rooted in physics and epidemiology theories, this study proposes a Susceptible Infectious Susceptible (SIS) model to assess the role of social contagion in adoption processes, which takes changes in social dynamics over time into account. To study the adoption over a span of ten years, the authors used detailed data sets from a community of consumers and determined the importance of social contagion, as well as how the interplay of social and non-social influences from outside the community drives adoption processes. Although social contagion matters for diffusion, it is less relevant in shaping adoption when the study also includes social dynamics among members of the community. This finding is relevant for managers and entrepreneurs who trust in word-of-mouth marketing campaigns whose effect may be overestimated if marketers fail to acknowledge variations in social interactions. PMID:26505473

R-process nucleosynthesis: a dynamical model

Energy Technology Data Exchange (ETDEWEB)

Hillebrandt, W; Takahashi, K [Technische Hochschule Darmstadt (Germany, F.R.). Inst. fuer Kernphysik; Kodama, T [Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro

1976-10-01

The synthesis of heavy and neutron-rich elements (with the mass number A > approximately 70) is reconsidered in the framework of a dynamical supernova model. The synthesis equation for the rapid neutron-capture (or, the r-) process and the hydrodynamical equations for the supernova explosion are solved simultaneously. Improved systematics of nuclear parameters are used, and the energy release due to ..beta..-decays as well as the energy loss due to neutrinos is taken into account. It is shown that the observed solar-system abundance curve can be reproduced fairly well by assuming only one supernova event on a time-scale of the order of 1 s. However there are still some discrepancies which may be explained by uncertainties in the nuclear data used.

Achieving Synchronization in Arrays of Coupled Differential Systems with Time-Varying Couplings

Directory of Open Access Journals (Sweden)

Xinlei Yi

2013-01-01

Full Text Available We study complete synchronization of the complex dynamical networks described by linearly coupled ordinary differential equation systems (LCODEs. Here, the coupling is timevarying in both network structure and reaction dynamics. Inspired by our previous paper (Lu et al. (2007-2008, the extended Hajnal diameter is introduced and used to measure the synchronization in a general differential system. Then we find that the Hajnal diameter of the linear system induced by the time-varying coupling matrix and the largest Lyapunov exponent of the synchronized system play the key roles in synchronization analysis of LCODEs with identity inner coupling matrix. As an application, we obtain a general sufficient condition guaranteeing directed time-varying graph to reach consensus. Example with numerical simulation is provided to show the effectiveness of the theoretical results.

Adaptive Fault Detection for Complex Dynamic Processes Based on JIT Updated Data Set

Directory of Open Access Journals (Sweden)

Jinna Li

2012-01-01

Full Text Available A novel fault detection technique is proposed to explicitly account for the nonlinear, dynamic, and multimodal problems existed in the practical and complex dynamic processes. Just-in-time (JIT detection method and k-nearest neighbor (KNN rule-based statistical process control (SPC approach are integrated to construct a flexible and adaptive detection scheme for the control process with nonlinear, dynamic, and multimodal cases. Mahalanobis distance, representing the correlation among samples, is used to simplify and update the raw data set, which is the first merit in this paper. Based on it, the control limit is computed in terms of both KNN rule and SPC method, such that we can identify whether the current data is normal or not by online approach. Noted that the control limit obtained changes with updating database such that an adaptive fault detection technique that can effectively eliminate the impact of data drift and shift on the performance of detection process is obtained, which is the second merit in this paper. The efficiency of the developed method is demonstrated by the numerical examples and an industrial case.

Discrete Control Processes, Dynamic Games and Multicriterion Control Problems

Directory of Open Access Journals (Sweden)

Dumitru Lozovanu

2002-07-01

Full Text Available The discrete control processes with state evaluation in time of dynamical system is considered. A general model of control problems with integral-time cost criterion by a trajectory is studied and a general scheme for solving such classes of problems is proposed. In addition the game-theoretical and multicriterion models for control problems are formulated and studied.

Nonlinear modeling and dynamic analysis of hydro-turbine governing system in the process of load rejection transient

International Nuclear Information System (INIS)

Zhang, Hao; Chen, Diyi; Xu, Beibei; Wang, Feifei

2015-01-01

Graphical abstract: Nonlinear dynamic transfer coefficients are introduced to the hydro-turbine governing system. In the process of load reject ion transient, the nonlinear dynamical behaviors of the system are studied in detail. - Highlights: • A novel mathematical model of a hydro-turbine governing system is established. • The process of load rejection transient is considered. • Nonlinear dynamic transfer coefficients are introduced to the system. • The bifurcation diagram with the variable t has better engineering significance. • The nonlinear dynamical behaviors of the system are studied in detail. - Abstract: This article pays attention to the mathematical modeling of a hydro-turbine governing system in the process of load rejection transient. As a pioneer work, the nonlinear dynamic transfer coefficients are introduced in a penstock system. Considering a generator system, a turbine system and a governor system, we present a novel nonlinear dynamical model of a hydro-turbine governing system. Fortunately, for the unchanged of PID parameters, we acquire the stable regions of the governing system in the process of load rejection transient by numerical simulations. Moreover, the nonlinear dynamic behaviors of the governing system are illustrated by bifurcation diagrams, Poincare maps, time waveforms and phase orbits. More importantly, these methods and analytic results will present theoretical groundwork for allowing a hydropower station in the process of load rejection transient

Dynamic biogas upgrading based on the Sabatier process

DEFF Research Database (Denmark)

Jurgensen, Lars; Ehimen, Ehiazesebhor Augustine; Born, Jens

2015-01-01

index, CO2 content and calorific value were found to be controllable by the H2/CO2 ratio fed the methanation reactor. An optimal H2/CO2 ratio of 3.45–3.7 was seen to result in a product gas with high calorific value and Wobbe index. The dynamic reactor simulation verified that the process start......This study aimed to investigate the feasibility of substitute natural gas (SNG) generation using biogas from anaerobic digestion and hydrogen from renewable energy systems. Using thermodynamic equilibrium analysis, kinetic reactor modeling and transient simulation, an integrated approach...... for the operation of a biogas-based Sabatier process was put forward, which was then verified using a lab scale heterogenous methanation reactor. The process simulation using a kinetic reactor model demonstrated the feasibility of the production of SNG at gas grid standards using a single reactor setup. The Wobbe...

Three-Level Process Specification for Dynamic Service Outsourcing : From Petri Nets to ebXML and WFPDL

NARCIS (Netherlands)

Grefen, P.W.P.J.; Angelov, S.A.; Ehrig, Hartmut; Reisig, Wolfgang; Rozenberg, Grzegorz; Weber, Herbert

2003-01-01

Service outsourcing is the business paradigm, in which an organization has part of its business process performed by a service provider. In dynamic markets, service providers are selected on the fly during process enactment. The cooperation between the parties is specified in a dynamically made

Three-Level Process Specification for Dynamic Service Outsourcing: From Petri Nets to ebXML and WFPDL

NARCIS (Netherlands)

Grefen, P.W.P.J.; Angelov, S.A.

2003-01-01

Service outsourcing is the business paradigm, in which an organization has part of its business process performed by a service provider. In dynamic markets, service providers are selected on the fly during process enactment. The cooperation between the parties is specified in a dynamically made

Optimal critic learning for robot control in time-varying environments.

Science.gov (United States)

Wang, Chen; Li, Yanan; Ge, Shuzhi Sam; Lee, Tong Heng

2015-10-01

In this paper, optimal critic learning is developed for robot control in a time-varying environment. The unknown environment is described as a linear system with time-varying parameters, and impedance control is employed for the interaction control. Desired impedance parameters are obtained in the sense of an optimal realization of the composite of trajectory tracking and force regulation. Q -function-based critic learning is developed to determine the optimal impedance parameters without the knowledge of the system dynamics. The simulation results are presented and compared with existing methods, and the efficacy of the proposed method is verified.

On non-stationarity of dynamic systems

DEFF Research Database (Denmark)

Høskuldsson, Agnar

2004-01-01

. Covariance structure of dynamic systems tends to vary over time. Here some procedures to find stable solutions to linear dynamic systems with low rank are presented. Subsets of variables and samples to be included in a model are considered. The procedures are based on the H-principle of mathematical...... that are based on exact solutions. With in few seconds the algorithms can provide with solutions of models having hundreds or thousands of variables. The procedure is described mathematically and demonstrated for a dynamic industrial case. It is shown how the algorithms can provide solutions involving NIR data...... for process control. The method is simple to apply and the motivation of the procedure is obvious for industrial applications. It can be used, e.g., when modelling on-line systems....

Inferring time-varying network topologies from gene expression data.

Science.gov (United States)

Rao, Arvind; Hero, Alfred O; States, David J; Engel, James Douglas

2007-01-01

Most current methods for gene regulatory network identification lead to the inference of steady-state networks, that is, networks prevalent over all times, a hypothesis which has been challenged. There has been a need to infer and represent networks in a dynamic, that is, time-varying fashion, in order to account for different cellular states affecting the interactions amongst genes. In this work, we present an approach, regime-SSM, to understand gene regulatory networks within such a dynamic setting. The approach uses a clustering method based on these underlying dynamics, followed by system identification using a state-space model for each learnt cluster--to infer a network adjacency matrix. We finally indicate our results on the mouse embryonic kidney dataset as well as the T-cell activation-based expression dataset and demonstrate conformity with reported experimental evidence.

Dynamics and structure of ignition process in plasma. Ignition dynamics and structure of laboratory plasmas

International Nuclear Information System (INIS)

Nagasaki, Kazunobu; Takamura, Shuichi; Razzak, Md. Abdur; Uesugi, Yoshihiko; Yoshimura, Yasuo; Cappa, Alvaro

2008-01-01

The dynamics and structure of plasma production are stated by the results of two experiments such as the radio frequency thermal plasmas produced by inductively coupled plasma technique at atmospheric pressure and the second harmonic ECH. The first experiment results explained transition from the electrostatic discharge mode of forming streamer to the induced discharge mode after forming the discharge channel that the streamer connected to in the azimuth direction. The other experiment explained the dynamics which the initial plasma produced at the ECH resonance point spread in the direction of radius. The divergence and transition related to the nonlinear process were observed independently existing the magnetic field or incident power. The experiment devices, conditions, results, and modeling are reported. (S.Y.)

Dynamics of soil CO2 efflux under varying atmospheric CO2 concentrations reveal dominance of slow processes.

Science.gov (United States)

Kim, Dohyoung; Oren, Ram; Clark, James S; Palmroth, Sari; Oishi, A Christopher; McCarthy, Heather R; Maier, Chris A; Johnsen, Kurt

2017-09-01

We evaluated the effect on soil CO 2 efflux (F CO 2 ) of sudden changes in photosynthetic rates by altering CO 2 concentration in plots subjected to +200 ppmv for 15 years. Five-day intervals of exposure to elevated CO 2 (eCO 2 ) ranging 1.0-1.8 times ambient did not affect F CO 2 . F CO 2 did not decrease until 4 months after termination of the long-term eCO 2 treatment, longer than the 10 days observed for decrease of F CO 2 after experimental blocking of C flow to belowground, but shorter than the ~13 months it took for increase of F CO 2 following the initiation of eCO 2 . The reduction of F CO 2 upon termination of enrichment (~35%) cannot be explained by the reduction of leaf area (~15%) and associated carbohydrate production and allocation, suggesting a disproportionate contraction of the belowground ecosystem components; this was consistent with the reductions in base respiration and F CO 2 -temperature sensitivity. These asymmetric responses pose a tractable challenge to process-based models attempting to isolate the effect of individual processes on F CO2 . © 2017 John Wiley & Sons Ltd.

Merging constitutional and motional covalent dynamics in reversible imine formation and exchange processes.

Science.gov (United States)

Kovaříček, Petr; Lehn, Jean-Marie

2012-06-06

The formation and exchange processes of imines of salicylaldehyde, pyridine-2-carboxaldehyde, and benzaldehyde have been studied, showing that the former has features of particular interest for dynamic covalent chemistry, displaying high efficiency and fast rates. The monoimines formed with aliphatic α,ω-diamines display an internal exchange process of self-transimination type, inducing a local motion of either "stepping-in-place" or "single-step" type by bond interchange, whose rate decreases rapidly with the distance of the terminal amino groups. Control of the speed of the process over a wide range may be achieved by substituents, solvent composition, and temperature. These monoimines also undergo intermolecular exchange, thus merging motional and constitutional covalent behavior within the same molecule. With polyamines, the monoimines formed execute internal motions that have been characterized by extensive one-dimensional, two-dimensional, and EXSY proton NMR studies. In particular, with linear polyamines, nondirectional displacement occurs by shifting of the aldehyde residue along the polyamine chain serving as molecular track. Imines thus behave as simple prototypes of systems displaying relative motions of molecular moieties, a subject of high current interest in the investigation of synthetic and biological molecular motors. The motional processes described are of dynamic covalent nature and take place without change in molecular constitution. They thus represent a category of dynamic covalent motions, resulting from reversible covalent bond formation and dissociation. They extend dynamic covalent chemistry into the area of molecular motions. A major further step will be to achieve control of directionality. The results reported here for imines open wide perspectives, together with other chemical groups, for the implementation of such features in multifunctional molecules toward the design of molecular devices presenting a complex combination of

Optimal protocol for maximum work extraction in a feedback process with a time-varying potential

Science.gov (United States)

Kwon, Chulan

2017-12-01

The nonequilibrium nature of information thermodynamics is characterized by the inequality or non-negativity of the total entropy change of the system, memory, and reservoir. Mutual information change plays a crucial role in the inequality, in particular if work is extracted and the paradox of Maxwell's demon is raised. We consider the Brownian information engine where the protocol set of the harmonic potential is initially chosen by the measurement and varies in time. We confirm the inequality of the total entropy change by calculating, in detail, the entropic terms including the mutual information change. We rigorously find the optimal values of the time-dependent protocol for maximum extraction of work both for the finite-time and the quasi-static process.

Automated processing of data generated by molecular dynamics

International Nuclear Information System (INIS)

Lobato Hoyos, Ivan; Rojas Tapia, Justo; Instituto Peruano de Energia Nuclear, Lima

2008-01-01

A new integrated tool for automated processing of data generated by molecular dynamics packages and programs have been developed. The program allows to calculate important quantities such as pair correlation function, the analysis of common neighbors, counting nanoparticles and their size distribution, conversion of output files between different formats. The work explains in detail the modules of the tool, the interface between them. The uses of program are illustrated in application examples in the calculation of various properties of silver nanoparticles. (author)

Dynamic process model of a plutonium oxalate precipitator

International Nuclear Information System (INIS)

Borgonovi, G.M.; Hammelman, J.E.; Miller, C.L.

1980-01-01

A dynamic model of a plutonium oxalate precipitator is developed to provide a means of predicting plutonium inventory on a continuous basis. The model is based on state-of-the-art crystallization equations, which describe nucleation and growth phenomena. The model parameters were obtained through the use of batch experimental data. The model has been used to study the approach to steady state, to investigate the response to input transients, and to simulate the control of the precipitation process. 12 refs

Dynamic wavefront creation for processing units using a hybrid compactor

Energy Technology Data Exchange (ETDEWEB)

Puthoor, Sooraj; Beckmann, Bradford M.; Yudanov, Dmitri

2018-02-20

A method, a non-transitory computer readable medium, and a processor for repacking dynamic wavefronts during program code execution on a processing unit, each dynamic wavefront including multiple threads are presented. If a branch instruction is detected, a determination is made whether all wavefronts following a same control path in the program code have reached a compaction point, which is the branch instruction. If no branch instruction is detected in executing the program code, a determination is made whether all wavefronts following the same control path have reached a reconvergence point, which is a beginning of a program code segment to be executed by both a taken branch and a not taken branch from a previous branch instruction. The dynamic wavefronts are repacked with all threads that follow the same control path, if all wavefronts following the same control path have reached the branch instruction or the reconvergence point.

Effects of the amount and schedule of varied practice after constant practice on the adaptive process of motor learning

Directory of Open Access Journals (Sweden)

Umberto Cesar Corrêa

2014-12-01

Full Text Available This study investigated the effects of different amounts and schedules of varied practice, after constant practice, on the adaptive process of motor learning. Participants were one hundred and seven children with a mean age of 11.1 ± 0.9 years. Three experiments were carried out using a complex anticipatory timing task manipulating the following components in the varied practice: visual stimulus speed (experiment 1; sequential response pattern (experiment 2; and visual stimulus speed plus sequential response pattern (experiment 3. In all experiments the design involved three amounts (18, 36, and 63 trials, and two schedules (random and blocked of varied practice. The experiments also involved two learning phases: stabilization and adaptation. The dependent variables were the absolute, variable, and constant errors related to the task goal, and the relative timing of the sequential response. Results showed that all groups worsened the performances in the adaptation phase, and no difference was observed between them. Altogether, the results of the three experiments allow the conclusion that the amounts of trials manipulated in the random and blocked practices did not promote the diversification of the skill since no adaptation was observed.

Identification of different processes in magnetization dynamics of API steels using magnetic Barkhausen noise

International Nuclear Information System (INIS)

Pérez-Benítez, J A; Espina-Hernández, J H; Le Man, Tu; Caleyo, F; Hallen, J M

2015-01-01

This work presents a method to identify processes in magnetization dynamics using the angular dependence of the magnetic Barkhausen noise. The analysis reveals that three different processes of the magnetization dynamics could be identified using the angular dependence of the magnetic Barkhausen noise energy. The first process is the reversed domain nucleation which is related to the magneto-crystalline energy of the material, and the second and third ones are associated with 180° and 90° domain walls motions, respectively. Additionally, two transition regions were identified and they are located between the regions associated with the aforementioned processes. The causes involving these processes are analyzed and a method for establishing their location in the Barkhausen noise signal with respect to the applied magnetic field intensity is proposed. (paper)

Mapping the concentration changes during the dynamic processes of crevice corrosion by digital

Directory of Open Access Journals (Sweden)

HENGLEI JIA

2009-02-01

Full Text Available The dynamic process of crevice corrosion during anodic dissolution of a crevice electrode in a 5.0 mmol dm-3 NaCl solution has been studied by digital holographic reconstruction. Digital holographic reconstruction has been proved to be an effective and in situ technique to detect the changes in the solution concentration because useful and direct information can be obtained from the three-dimensional images. It provides a valuable method for a better understanding of the mechanism of crevice corrosion by studying the dynamic processes of changes in the solution concentration at the interface of crevice corrosion.

Dynamical processes in space: Cluster results

Directory of Open Access Journals (Sweden)

C. P. Escoubet

2013-06-01

Full Text Available After 12 years of operations, the Cluster mission continues to successfully fulfil its scientific objectives. The main goal of the Cluster mission, comprised of four identical spacecraft, is to study in three dimensions small-scale plasma structures in key plasma regions of the Earth's environment: solar wind and bow shock, magnetopause, polar cusps, magnetotail, plasmasphere and auroral zone. During the course of the mission, the relative distance between the four spacecraft has been varied from 20 km to 36 000 km to study the scientific regions of interest at different scales. Since summer 2005, new multi-scale constellations have been implemented, wherein three spacecraft (C1, C2, C3 are separated by 10 000 km, while the fourth one (C4 is at a variable distance ranging between 20 km and 10 000 km from C3. Recent observations were conducted in the auroral acceleration region with the spacecraft separated by 1000s km. We present highlights of the results obtained during the last 12 years on collisionless shocks, magnetopause waves, magnetotail dynamics, plasmaspheric structures, and the auroral acceleration region. In addition, we highlight Cluster results on understanding the impact of Coronal Mass Ejections (CME on the Earth environment. We will also present Cluster data accessibility through the Cluster Science Data System (CSDS, and the Cluster Active Archive (CAA, which was implemented to provide a permanent and public archive of high resolution Cluster data from all instruments.

Detecting causality in policy diffusion processes

Science.gov (United States)

Grabow, Carsten; Macinko, James; Silver, Diana; Porfiri, Maurizio

2016-08-01

A universal question in network science entails learning about the topology of interaction from collective dynamics. Here, we address this question by examining diffusion of laws across US states. We propose two complementary techniques to unravel determinants of this diffusion process: information-theoretic union transfer entropy and event synchronization. In order to systematically investigate their performance on law activity data, we establish a new stochastic model to generate synthetic law activity data based on plausible networks of interactions. Through extensive parametric studies, we demonstrate the ability of these methods to reconstruct networks, varying in size, link density, and degree heterogeneity. Our results suggest that union transfer entropy should be preferred for slowly varying processes, which may be associated with policies attending to specific local problems that occur only rarely or with policies facing high levels of opposition. In contrast, event synchronization is effective for faster enactment rates, which may be related to policies involving Federal mandates or incentives. This study puts forward a data-driven toolbox to explain the determinants of legal activity applicable to political science, across dynamical systems, information theory, and complex networks.

Multivariate Option Pricing with Time Varying Volatility and Correlations

DEFF Research Database (Denmark)

Rombouts, Jeroen V.K.; Stentoft, Lars Peter

In recent years multivariate models for asset returns have received much attention, in particular this is the case for models with time varying volatility. In this paper we consider models of this class and examine their potential when it comes to option pricing. Specifically, we derive the risk...... neutral dynamics for a general class of multivariate heteroskedastic models, and we provide a feasible way to price options in this framework. Our framework can be used irrespective of the assumed underlying distribution and dynamics, and it nests several important special cases. We provide an application...... to options on the minimum of two indices. Our results show that not only is correlation important for these options but so is allowing this correlation to be dynamic. Moreover, we show that for the general model exposure to correlation risk carries an important premium, and when this is neglected option...

Study of a low-dose capsule filling process by dynamic and static tests for advanced process understanding.

Science.gov (United States)

Stranzinger, S; Faulhammer, E; Scheibelhofer, O; Calzolari, V; Biserni, S; Paudel, A; Khinast, J G

2018-04-05

Precise filling of capsules with doses in the mg-range requires a good understanding of the filling process. Therefore, we investigated the various process steps of the filling process by dynamic and static mode tests. Dynamic tests refer to filling of capsules in a regular laboratory dosator filling machine. Static tests were conducted using a novel filling system developed by us. Three grades of lactose excipients were filled into size 3 capsules with different dosing chamber lengths, nozzle diameters and powder bed heights, and, in the dynamic mode, with two filling speeds (500, 3000 caps/h). The influence of the gap at the bottom of the powder container on the fill weight and variability was assessed. Different gaps resulted in a change in fill weight in all materials, although in different ways. In all cases, the fill weight of highly cohesive Lactohale 220 increased when decreasing the gap. Furthermore, experiments with the stand-alone static test tool indicated that this very challenging powder could successfully be filled without any pre-compression in the range of 5 mg-20 mg with acceptable RSDs. This finding is of great importance since for very fine lactose powders high compression ratios (dosing-chamber-length-to-powder-bed height compression ratios) may result in jamming of the piston. Moreover, it shows that the static mode setup is suitable for studying fill weight and variability. Since cohesive powders, such as Lactohale 220, are hard to fill, we investigated the impact of vibration on the process. Interestingly, we found no correlation between the reported fill weight changes in dynamic mode at 3000 cph and static mode using similar vibration. However, we could show that vibrations during sampling in the static mode dramatically reduced fill weight variability. Overall, our results indicate that by fine-tuning instrumental settings even very challenging powders can be filled with a low-dose dosator capsule filling machine. This study is a

Extending topological surgery to natural processes and dynamical systems.

Directory of Open Access Journals (Sweden)

Stathis Antoniou

Full Text Available Topological surgery is a mathematical technique used for creating new manifolds out of known ones. We observe that it occurs in natural phenomena where a sphere of dimension 0 or 1 is selected, forces are applied and the manifold in which they occur changes type. For example, 1-dimensional surgery happens during chromosomal crossover, DNA recombination and when cosmic magnetic lines reconnect, while 2-dimensional surgery happens in the formation of tornadoes, in the phenomenon of Falaco solitons, in drop coalescence and in the cell mitosis. Inspired by such phenomena, we introduce new theoretical concepts which enhance topological surgery with the observed forces and dynamics. To do this, we first extend the formal definition to a continuous process caused by local forces. Next, for modeling phenomena which do not happen on arcs or surfaces but are 2-dimensional or 3-dimensional, we fill in the interior space by defining the notion of solid topological surgery. We further introduce the notion of embedded surgery in S3 for modeling phenomena which involve more intrinsically the ambient space, such as the appearance of knotting in DNA and phenomena where the causes and effect of the process lies beyond the initial manifold, such as the formation of black holes. Finally, we connect these new theoretical concepts with a dynamical system and we present it as a model for both 2-dimensional 0-surgery and natural phenomena exhibiting a 'hole drilling' behavior. We hope that through this study, topology and dynamics of many natural phenomena, as well as topological surgery itself, will be better understood.

New Dynamic Analysis and System Identification of Biodiesel Production Process from Palm Oil

Directory of Open Access Journals (Sweden)

Hikmat S. Al-Salim

2009-12-01

Full Text Available In this study we present advanced mathematical model was used to capture the batch reactor characteristics of reacting compounds new parameters and new a prerequisite average slope analysis (PASA method for the system dynamic behaviour under different operational conditions is a prerequisite to the good selection for these parameters. The model was applied to batch reactor for the production of bio-diesel from palm and kapok oils. Results of the model were compared with experimental data in terms of conversion of transesterification reaction for the production of bio-diesel under unsteady state. A good agreement was obtained between our model predictions and the experimental data. Both experimental and modeling results showed that the conversion of triglycerides to methyl ester was affected by the process conditions and by using PASA that could be achieved by making some deterministic tests either in real data plant or in the physical model that properly and adequately fits the actual process. The input-output relationships are studied using the open-loop dynamic response of the process, which can be determined from the process model by stepping different inputs and recording output responses. Starting from steady state conditions, each input is perturbed with certain magnitude that is enough to show the effect on the system dynamics. The transesterficition process with temperature of about 70 oC, and methanol ratio to the triglyceride of about 5 times its stoichiometry and the NAOH catalyst of wt 0.4%, appear to be acceptable process conditions. PASA shows methanol ratio to the triglyceride has big effect on the system. PASA method can be applied for different processes. © 2009 BCREC UNDIP. All rights reserved[Received: 12 November 2009, Revised: 20 December 2009, Accepted: 27 December 2009][How to Cite: A. S. Ibrehem, H.S. Al-Salim. (2009. New Dynamic Analysis and System Identification of Biodiesel Production Process from Palm Oil. Bulletin

New Dynamic Analysis and System Identification of Biodiesel Production Process from Palm Oil

Directory of Open Access Journals (Sweden)

Ahmmed S. Ibrehem

2009-12-01

Full Text Available In this study we present advanced mathematical model was used to capture the batch reactor characteristics of reacting compounds new parameters and new a prerequisite average slope analysis (PASA method for the system dynamic behaviour under different operational conditions is a prerequisite to the good selection for these parameters. The model was applied to batch reactor for the production of bio-diesel from palm and kapok oils. Results of the model were compared with experimental data in terms of conversion of transesterification reaction for the production of bio-diesel under unsteady state. A good agreement was obtained between our model predictions and the experimental data. Both experimental and modeling results showed that the conversion of triglycerides to methyl ester was affected by the process conditions and by using PASA that could be achieved by making some deterministic tests either in real data plant or in the physical model that properly and adequately fits the actual process. The input-output relationships are studied using the open-loop dynamic response of the process, which can be determined from the process model by stepping different inputs and recording output responses. Starting from steady state conditions, each input is perturbed with certain magnitude that is enough to show the effect on the system dynamics. The transesterficition process with temperature of about 70 oC, and methanol ratio to the triglyceride of about 5 times its stoichiometry and the NAOH catalyst of wt 0.4%, appear to be acceptable process conditions. PASA shows methanol ratio to the triglyceride has big effect on the system. PASA method can be applied for different processes. © 2009 BCREC UNDIP. All rights reserved[Received: 12 November 2009, Revised: 20 December 2009, Accepted: 27 December 2009][How to Cite: A. S. Ibrehem, H.S. Al-Salim. (2009. New Dynamic Analysis and System Identification of Biodiesel Production Process from Palm Oil. Bulletin

The Horse Raced Past: Gardenpath Processing in Dynamical Systems

OpenAIRE

Graben, Peter beim

2012-01-01

I pinpoint an interesting similarity between a recent account to rational parsing and the treatment of sequential decisions problems in a dynamical systems approach. I argue that expectation-driven search heuristics aiming at fast computation resembles a high-risk decision strategy in favor of large transition velocities. Hale's rational parser, combining generalized left-corner parsing with informed $\\mathrm{A}^*$ search to resolve processing conflicts, explains gardenpath effects in natural...

Equilibrium and Dynamic Osmotic Behaviour of Aqueous Solutions with Varied Concentration at Constant and Variable Volume

Science.gov (United States)

Minkov, Ivan L.; Manev, Emil D.; Sazdanova, Svetla V.; Kolikov, Kiril H.

2013-01-01

Osmosis is essential for the living organisms. In biological systems the process usually occurs in confined volumes and may express specific features. The osmotic pressure in aqueous solutions was studied here experimentally as a function of solute concentration (0.05–0.5 M) in two different regimes: of constant and variable solution volume. Sucrose, a biologically active substance, was chosen as a reference solute for the complex tests. A custom made osmotic cell was used. A novel operative experimental approach, employing limited variation of the solution volume, was developed and applied for the purpose. The established equilibrium values of the osmotic pressure are in agreement with the theoretical expectations and do not exhibit any evident differences for both regimes. In contrast, the obtained kinetic dependences reveal striking divergence in the rates of the process at constant and varied solution volume for the respective solute concentrations. The rise of pressure is much faster at constant solution volume, while the solvent influx is many times greater in the regime of variable volume. The results obtained suggest a feasible mechanism for the way in which the living cells rapidly achieve osmotic equilibrium upon changes in the environment. PMID:24459448

LCM and MCM: Specification of a control system using dynamic logic and process algebra

NARCIS (Netherlands)

Wieringa, Roelf J.; Lewerentz, Claus; Lindner, Thomas

1994-01-01

LCM 3.0 is a specification language based on dynamic logic and process algebra, and can be used to specify systems of dynamic objects that communicate synchronously. LCM 3.0 was developed for the specification of object-oriented information systems, but contains sufficient facilities for the

Correlated receptor transport processes buffer single-cell heterogeneity.

Directory of Open Access Journals (Sweden)

Stefan M Kallenberger

2017-09-01

Full Text Available Cells typically vary in their response to extracellular ligands. Receptor transport processes modulate ligand-receptor induced signal transduction and impact the variability in cellular responses. Here, we quantitatively characterized cellular variability in erythropoietin receptor (EpoR trafficking at the single-cell level based on live-cell imaging and mathematical modeling. Using ensembles of single-cell mathematical models reduced parameter uncertainties and showed that rapid EpoR turnover, transport of internalized EpoR back to the plasma membrane, and degradation of Epo-EpoR complexes were essential for receptor trafficking. EpoR trafficking dynamics in adherent H838 lung cancer cells closely resembled the dynamics previously characterized by mathematical modeling in suspension cells, indicating that dynamic properties of the EpoR system are widely conserved. Receptor transport processes differed by one order of magnitude between individual cells. However, the concentration of activated Epo-EpoR complexes was less variable due to the correlated kinetics of opposing transport processes acting as a buffering system.

International Symposium on Dynamics of Ordering Processes in Condensed Matter

CERN Document Server

Furukawa, H

1988-01-01

The International Symposium on Dynamics of Ordering Processes in Condensed Matter was held at the Kansai Seminar House, Kyoto, for four days, from 27 to 30 August 1987, under the auspices of the Physical Soci­ ety of Japan. The symposium was financially supported by the four orga­ nizations and 45 companies listed on other pages in this volume. We are very grateful to all of them and particularly to the greatest sponsor, the Commemorative Association for the Japan World Exposition 1970. A total Df 22 invited lectures and 48 poster presentations were given and 110 participants attended from seven nations. An objective of the Symposium was to review and extend our present understanding of the dynamics of ordering processes in condensed matters, (for example, alloys, polymers and fluids), that are brought to an un­ stable state by sudden change of such external parameters as temperature and pressure. A second objective, no less important, was to identify new fields of science that might be investigated by sim...

Nonlinear dynamics analysis of the spur gear system for railway locomotive

Science.gov (United States)

Wang, Junguo; He, Guangyue; Zhang, Jie; Zhao, Yongxiang; Yao, Yuan

2017-02-01

Considering the factors such as the nonlinearity backlash, static transmission error and time-varying meshing stiffness, a three-degree-of-freedom torsional vibration model of spur gear transmission system for a typical locomotive is developed, in which the wheel/rail adhesion torque is considered as uncertain but bounded parameter. Meantime, the Ishikawa method is used for analysis and calculation of the time-varying mesh stiffness of the gear pair in meshing process. With the help of bifurcation diagrams, phase plane diagrams, Poincaré maps, time domain response diagrams and amplitude-frequency spectrums, the effects of the pinion speed and stiffness on the dynamic behavior of gear transmission system for locomotive are investigated in detail by using the numerical integration method. Numerical examples reveal various types of nonlinear phenomena and dynamic evolution mechanism involving one-period responses, multi-periodic responses, bifurcation and chaotic responses. Some research results present useful information to dynamic design and vibration control of the gear transmission system for railway locomotive.

Parallel processing for nonlinear dynamics simulations of structures including rotating bladed-disk assemblies

Science.gov (United States)

Hsieh, Shang-Hsien

1993-01-01

The principal objective of this research is to develop, test, and implement coarse-grained, parallel-processing strategies for nonlinear dynamic simulations of practical structural problems. There are contributions to four main areas: finite element modeling and analysis of rotational dynamics, numerical algorithms for parallel nonlinear solutions, automatic partitioning techniques to effect load-balancing among processors, and an integrated parallel analysis system.

An analysis of web services support for dynamic business process outsourcing

NARCIS (Netherlands)

Grefen, P.W.P.J.; Ludwig, H.; Dan, A.; Angelov, S.

2006-01-01

Outsourcing of business processes is crucial for organizations to be effective, efficient and flexible. In fast changing markets, dynamic outsourcing is required, in which business relationships are established and enacted on-the-fly in an adaptive, fine-grained way. This requires automated means

Quality-by-Design (QbD): An integrated process analytical technology (PAT) approach for a dynamic pharmaceutical co-precipitation process characterization and process design space development.

Science.gov (United States)

Wu, Huiquan; White, Maury; Khan, Mansoor A

2011-02-28

The aim of this work was to develop an integrated process analytical technology (PAT) approach for a dynamic pharmaceutical co-precipitation process characterization and design space development. A dynamic co-precipitation process by gradually introducing water to the ternary system of naproxen-Eudragit L100-alcohol was monitored at real-time in situ via Lasentec FBRM and PVM. 3D map of count-time-chord length revealed three distinguishable process stages: incubation, transition, and steady-state. The effects of high risk process variables (slurry temperature, stirring rate, and water addition rate) on both derived co-precipitation process rates and final chord-length-distribution were evaluated systematically using a 3(3) full factorial design. Critical process variables were identified via ANOVA for both transition and steady state. General linear models (GLM) were then used for parameter estimation for each critical variable. Clear trends about effects of each critical variable during transition and steady state were found by GLM and were interpreted using fundamental process principles and Nyvlt's transfer model. Neural network models were able to link process variables with response variables at transition and steady state with R(2) of 0.88-0.98. PVM images evidenced nucleation and crystal growth. Contour plots illustrated design space via critical process variables' ranges. It demonstrated the utility of integrated PAT approach for QbD development. Published by Elsevier B.V.

Dynamic interracial/intercultural processes: the role of lay theories of race.

Science.gov (United States)

Hong, Ying-yi; Chao, Melody Manchi; No, Sun

2009-10-01

This paper explores how the lay theory approach provides a framework beyond previous stereotype/prejudice research to understand dynamic personality processes in interracial/ethnic contexts. The authors conceptualize theory of race within the Cognitive-Affective Personality System (CAPS), in which lay people's beliefs regarding the essential nature of race sets up a mind-set through which individuals construe and interpret their social experiences. The research findings illustrate that endorsement of the essentialist theory (i.e., that race reflects deep-seated, inalterable essence and is indicative of traits and ability) versus the social constructionist theory (i.e., that race is socially constructed, malleable, and arbitrary) are associated with different encoding and representation of social information, which in turn affect feelings, motivation, and competence in navigating between racial and cultural boundaries. These findings shed light on dynamic interracial/intercultural processes. Relations of this approach to CAPS are discussed.

MOBILE TECHNOLOGY AIDED FIELD SALES PROCESS MANAGEMENT WIYH DYNAMICS ANYWHERE FOR MICROSOFT DYNAMIC NAV

Directory of Open Access Journals (Sweden)

Simon Sándor

2013-03-01

Full Text Available The evolution of information society, globalisation, made great changes concerning the human-computer relationship. Mobile technology gives new perspectives for the administration of enterprises and decision making. Microsoft Dynamics NAV is not only a software capable to model the various activities of a firm through the desktop platform, but with a properly developed user interface which is optimised for a mobile device, the possibilities of the use of this ERP software can be broadened with workflows characterised with great distances. In this study I show how a field sales workflow can be modelled and managed by me with the software environment “NAV Anywhere Framework”. The survey gives a closer look at both a suggestible administrative process for an imagined workflow and its technical management on a mobile device. For my development creates specialised and dynamic web pages for a mobile device, it can be accessible from a lot of types of smart phones and tablet computers.

Initial post dynamic buckling of a quadratic-cubic column ...

African Journals Online (AJOL)

In this investigation, we determine the dynamic buckling load of an imperfect finite column resting on a mixed quadratic-cubic nonlinear elastic foundation trapped by an explicitly time dependent sinusoidally slowly varying dynamic load .The resultant coefficients are dynamically slowly varying and the formulation contains ...

Complexities, Catastrophes and Cities: Emergency Dynamics in Varying Scenarios and Urban Topologies

Science.gov (United States)

Narzisi, Giuseppe; Mysore, Venkatesh; Byeon, Jeewoong; Mishra, Bud

Complex Systems are often characterized by agents capable of interacting with each other dynamically, often in non-linear and non-intuitive ways. Trying to characterize their dynamics often results in partial differential equations that are difficult, if not impossible, to solve. A large city or a city-state is an example of such an evolving and self-organizing complex environment that efficiently adapts to different and numerous incremental changes to its social, cultural and technological infrastructure [1]. One powerful technique for analyzing such complex systems is Agent-Based Modeling (ABM) [9], which has seen an increasing number of applications in social science, economics and also biology. The agent-based paradigm facilitates easier transfer of domain specific knowledge into a model. ABM provides a natural way to describe systems in which the overall dynamics can be described as the result of the behavior of populations of autonomous components: agents, with a fixed set of rules based on local information and possible central control. As part of the NYU Center for Catastrophe Preparedness and Response (CCPR1), we have been exploring how ABM can serve as a powerful simulation technique for analyzing large-scale urban disasters. The central problem in Disaster Management is that it is not immediately apparent whether the current emergency plans are robust against such sudden, rare and punctuated catastrophic events.

Surface Dynamic Process Simulation with the Use of Cellular Automata

International Nuclear Information System (INIS)

Adamska-Szatko, M.; Bala, J.

2010-01-01

Cellular automata are known for many applications, especially for physical and biological simulations. Universal cellular automata can be used for modelling complex natural phenomena. The paper presents simulation of surface dynamic process. Simulation uses 2-dimensional cellular automata algorithm. Modelling and visualisation were created by in-house developed software with standard OpenGL graphic library. (authors)

Brain-heart linear and nonlinear dynamics during visual emotional elicitation in healthy subjects.

Science.gov (United States)

Valenza, G; Greco, A; Gentili, C; Lanata, A; Toschi, N; Barbieri, R; Sebastiani, L; Menicucci, D; Gemignani, A; Scilingo, E P

2016-08-01

This study investigates brain-heart dynamics during visual emotional elicitation in healthy subjects through linear and nonlinear coupling measures of EEG spectrogram and instantaneous heart rate estimates. To this extent, affective pictures including different combinations of arousal and valence levels, gathered from the International Affective Picture System, were administered to twenty-two healthy subjects. Time-varying maps of cortical activation were obtained through EEG spectral analysis, whereas the associated instantaneous heartbeat dynamics was estimated using inhomogeneous point-process linear models. Brain-Heart linear and nonlinear coupling was estimated through the Maximal Information Coefficient (MIC), considering EEG time-varying spectra and point-process estimates defined in the time and frequency domains. As a proof of concept, we here show preliminary results considering EEG oscillations in the θ band (4-8 Hz). This band, indeed, is known in the literature to be involved in emotional processes. MIC highlighted significant arousal-dependent changes, mediated by the prefrontal cortex interplay especially occurring at intermediate arousing levels. Furthermore, lower and higher arousing elicitations were associated to not significant brain-heart coupling changes in response to pleasant/unpleasant elicitations.

Application of the non lineal dynamics to the design of processes in the administration of quality

International Nuclear Information System (INIS)

Domech More, Jesus

1999-01-01

The present work thinks about the possibility to apply the techniques from the non lineal dynamics to the one design of processes like a complex but realler tool that the statistical techniques. As study object the process of production of lead containers is used (means of shielding) that are used to carry radioisotopos in the system of vat health. It intends a model of non lineal dynamics of the process that allows to evaluate what so predictable it is the chosen system (entrance control to the matter prevails) and which the one will be behavior average of the same one based in the complex interactions that arise in the relationships client-supplier, operative-machine, supplier-supplier, operative-environment and operative-method. Each one of these interactions constitutes a source of uncertainty in the one I process and he/she has a weight on the temporary dynamics of the characteristic of real quality (homogeneity of the blindaje) in the process

Nonlinear dynamics of regenerative cutting processes-Comparison of two models

International Nuclear Information System (INIS)

Wang, X.S.; Hu, J.; Gao, J.B.

2006-01-01

Understanding the nonlinear dynamics of cutting processes is essential for the improvement of machining technology. We study machine cutting processes by two different models, one has been recently introduced by Litak [Litak G. Chaotic vibrations in a regenerative cutting process. Chaos, Solitons and Fractals 2002;13:1531-5] and the other is the classic delay differential equation model. Although chaotic solutions have been found in both models, well known routes to chaos, such as period-doubling or quasi-periodic motion to chaos are not observed in either model. Careful analysis shows that the chaotic motion from the Litak's model has sharper spectral peaks, a smaller correlation dimension and a smaller value for the largest positive Lyapunov exponent. Implications to the control of chaos in cutting processes are discussed

Research progress of laser welding process dynamic monitoring technology based on plasma characteristics signal

Directory of Open Access Journals (Sweden)

Teng WANG

2017-02-01

Full Text Available During the high-power laser welding process, plasmas are induced by the evaporation of metal under laser radiation, which can affect the coupling of laser energy and the workpiece, and ultimately impact on the reliability of laser welding quality and process directly. The research of laser-induced plasma is a focus in high-power deep penetration welding field, which provides a promising research area for realizing the automation of welding process quality inspection. In recent years, the research of laser welding process dynamic monitoring technology based on plasma characteristics is mainly in two aspects, namely the research of plasma signal detection and the research of laser welding process modeling. The laser-induced plasma in the laser welding is introduced, and the related research of laser welding process dynamic monitoring technology based on plasma characteristics at home and abroad is analyzed. The current problems in the field are summarized, and the future development trend is put forward.

Dynamic simulation of the in-tank precipitation process

International Nuclear Information System (INIS)

Hang, T.; Shanahan, K.L.; Gregory, M.V.; Walker, D.D.

1993-01-01

As part of the High-Level Waste Tank Farm at the Savannah River Site (SRS), the In-Tank Precipitation (ITP) facility was designed to decontaminate the radioactive waste supernate by removing cesium as precipitated cesium tetraphenylborate. A dynamic computer model of the ITP process was developed using SPEEDUP TM software to provide guidance in the areas of operation and production forecast, production scheduling, safety, air emission, and process improvements. The model performs material balance calculations in all phase (solid, liquid, and gas) for 50 key chemical constituents to account for inventory accumulation, depletion, and dilution. Calculations include precipitation, benzene radiolytic reactions, evaporation, dissolution, adsorption, filtration, and stripping. To control the ITP batch operation a customized FORTRAN program was generated and linked to SPEEDUP TM simulation This paper summarizes the model development and initial results of the simulation study

Thermal dynamic simulation of wall for building energy efficiency under varied climate environment

Science.gov (United States)

Wang, Xuejin; Zhang, Yujin; Hong, Jing

2017-08-01

Aiming at different kind of walls in five cities of different zoning for thermal design, using thermal instantaneous response factors method, the author develops software to calculation air conditioning cooling load temperature, thermal response factors, and periodic response factors. On the basis of the data, the author gives the net work analysis about the influence of dynamic thermal of wall on air-conditioning load and thermal environment in building of different zoning for thermal design regional, and put forward the strategy how to design thermal insulation and heat preservation wall base on dynamic thermal characteristic of wall under different zoning for thermal design regional. And then provide the theory basis and the technical references for the further study on the heat preservation with the insulation are in the service of energy saving wall design. All-year thermal dynamic load simulating and energy consumption analysis for new energy-saving building is very important in building environment. This software will provide the referable scientific foundation for all-year new thermal dynamic load simulation, energy consumption analysis, building environment systems control, carrying through farther research on thermal particularity and general particularity evaluation for new energy -saving walls building. Based on which, we will not only expediently design system of building energy, but also analyze building energy consumption and carry through scientific energy management. The study will provide the referable scientific foundation for carrying through farther research on thermal particularity and general particularity evaluation for new energy saving walls building.

Dynamics of an exclusion process with creation and annihilation

International Nuclear Information System (INIS)

Juhasz, Robert; Santen, Ludger

2004-01-01

We examine the dynamical properties of an exclusion process with creation and annihilation of particles in the framework of a phenomenological domain-wall theory, by scaling arguments and by numerical simulation. We find that the length and the time scales are finite in the maximum current phase for finite creation and annihilation rates as opposed to the algebraically decaying correlations of the totally asymmetric simple exclusion process (TASEP). Critical exponents of the transition to the TASEP are determined. The case where bulk creation and annihilation rates vanish faster than the inverse of the system size N is also analysed. We point out that shock localization is possible even for rates proportional to N -a , 1 < a < 2

A comparative analysis between FinFET Semi-Dynamic Flip-Flop topologies under process variations

KAUST Repository

Rabie, Mohamed A.; Bahgat, Ahmed B G; Ramadan, Khaled S.; Shobak, Hosam; Nasr, Tarek Adel Hosny; Abdelhafez, Mohamed R.; Moustafa, Eslam M.; Anis, Mohab H.

2011-01-01

Semi-Dynamic Flip-Flops are widely used in state-of-art microprocessors. Moreover, scaling down traditional CMOS technology faces major challenges which rises the need for new devices for replacement. FinFET technology is a potential replacement due to similarity in both fabrication process and theory of operation to current CMOS technology. Hence, this paper presents the study of Semi Dynamic Flip Flops using both Independent gate and Tied gate FinFET devices in 32nm technology node. Furthermore, it studies the performance of these new circuits under process variations. © 2011 IEEE.

A comparative analysis between FinFET Semi-Dynamic Flip-Flop topologies under process variations

KAUST Repository

Rabie, Mohamed A.

2011-11-01

Semi-Dynamic Flip-Flops are widely used in state-of-art microprocessors. Moreover, scaling down traditional CMOS technology faces major challenges which rises the need for new devices for replacement. FinFET technology is a potential replacement due to similarity in both fabrication process and theory of operation to current CMOS technology. Hence, this paper presents the study of Semi Dynamic Flip Flops using both Independent gate and Tied gate FinFET devices in 32nm technology node. Furthermore, it studies the performance of these new circuits under process variations. © 2011 IEEE.

Multiscale response of ionic systems to a spatially varying electric field

Directory of Open Access Journals (Sweden)

Jesper Schmidt Hansen

2017-05-01

Full Text Available In this paper the response of ionic systems subjected to a spatially varying electric field is studied. Following the Nernst-Planck equation, two forces driving the mass flux are present, namely, the concentration gradient and the electric potential gradient. The mass flux due to the concentration gradient is modelled through Fick's law, and a new constitutive relation for the mass flux due to the potential gradient is proposed. In the regime of low screening the response function due to the potential gradient is closely related to the ionic conductivity. In the large screening regime, on the other hand, the response function is governed by the charge-charge structure. Molecular dynamics simulations are conducted and the two wave vector dependent response functions are evaluated for models of a molten salt and an ionic liquid. In the low screening regime the response functions show same wave vector dependency, indicating that it is the same underlying physical processes that govern the response. In the screening regime the wave vector dependency is very different and, thus, the overall response is determined by different processes. This is in agreement with the observed failure of the Nernst-Einstein relation.

Review of computational fluid dynamics applications in biotechnology processes.

Science.gov (United States)

Sharma, C; Malhotra, D; Rathore, A S

2011-01-01

Computational fluid dynamics (CFD) is well established as a tool of choice for solving problems that involve one or more of the following phenomena: flow of fluids, heat transfer,mass transfer, and chemical reaction. Unit operations that are commonly utilized in biotechnology processes are often complex and as such would greatly benefit from application of CFD. The thirst for deeper process and product understanding that has arisen out of initiatives such as quality by design provides further impetus toward usefulness of CFD for problems that may otherwise require extensive experimentation. Not surprisingly, there has been increasing interest in applying CFD toward a variety of applications in biotechnology processing in the last decade. In this article, we will review applications in the major unit operations involved with processing of biotechnology products. These include fermentation,centrifugation, chromatography, ultrafiltration, microfiltration, and freeze drying. We feel that the future applications of CFD in biotechnology processing will focus on establishing CFD as a tool of choice for providing process understanding that can be then used to guide more efficient and effective experimentation. This article puts special emphasis on the work done in the last 10 years. © 2011 American Institute of Chemical Engineers

The DCRS: Dynamic compaction resistance sintering. A flash sintering process with a dynamic loading ability

Directory of Open Access Journals (Sweden)

Allain-Bonnasso N.

2012-08-01

Full Text Available A homemade powder processing device combining Joule heating and dynamic compaction is presented. This device has been tested at temperatures as high as 1850 ∘C with heating rates up to 1000 ∘C/min. A detailed description of this device is given here followed by mechanical response and thermal validation tests. This highlights the reproducibility of the results on both the thermal and mechanical point of view.

Line shapes and time dynamics of the Förster resonances between two Rydberg atoms in a time-varying electric field

KAUST Repository

Yakshina, E. A.

2016-10-21

The observation of the Stark-tuned Förster resonances between Rydberg atoms excited by narrowband cw laser radiation requires usage of a Stark-switching technique in order to excite the atoms first in a fixed electric field and then to induce the interactions in a varied electric field, which is scanned across the Förster resonance. In our experiments with a few cold Rb Rydberg atoms, we have found that the transients at the edges of the electric pulses strongly affect the line shapes of the Förster resonances, since the population transfer at the resonances occurs on a time scale of ∼100 ns, which is comparable with the duration of the transients. For example, a short-term ringing at a certain frequency causes additional radio-frequency-assisted Förster resonances, while nonsharp edges lead to asymmetry. The intentional application of the radio-frequency field induces transitions between collective states, whose line shape depends on the interaction strengths and time. Spatial averaging over the atom positions in a single interaction volume yields a cusped line shape of the Förster resonance. We present a detailed experimental and theoretical analysis of the line shape and time dynamics of the Stark-tuned Förster resonances Rb(nP3/2)+Rb(nP3/2)→Rb(nS1/2)+Rb([n+1]S1/2) for two Rb Rydberg atoms interacting in a time-varying electric field.

Line shapes and time dynamics of the Förster resonances between two Rydberg atoms in a time-varying electric field

KAUST Repository

Yakshina, E. A.; Tretyakov, D. B.; Beterov, I. I.; Entin, V. M.; Andreeva, C.; Cinins, A.; Markovski, A.; Iftikhar, Z.; Ekers, Aigars; Ryabtsev, I. I.

2016-01-01

The observation of the Stark-tuned Förster resonances between Rydberg atoms excited by narrowband cw laser radiation requires usage of a Stark-switching technique in order to excite the atoms first in a fixed electric field and then to induce the interactions in a varied electric field, which is scanned across the Förster resonance. In our experiments with a few cold Rb Rydberg atoms, we have found that the transients at the edges of the electric pulses strongly affect the line shapes of the Förster resonances, since the population transfer at the resonances occurs on a time scale of ∼100 ns, which is comparable with the duration of the transients. For example, a short-term ringing at a certain frequency causes additional radio-frequency-assisted Förster resonances, while nonsharp edges lead to asymmetry. The intentional application of the radio-frequency field induces transitions between collective states, whose line shape depends on the interaction strengths and time. Spatial averaging over the atom positions in a single interaction volume yields a cusped line shape of the Förster resonance. We present a detailed experimental and theoretical analysis of the line shape and time dynamics of the Stark-tuned Förster resonances Rb(nP3/2)+Rb(nP3/2)→Rb(nS1/2)+Rb([n+1]S1/2) for two Rb Rydberg atoms interacting in a time-varying electric field.

A Process for Comparing Dynamics of Distributed Space Systems Simulations

Science.gov (United States)

Cures, Edwin Z.; Jackson, Albert A.; Morris, Jeffery C.

2009-01-01

The paper describes a process that was developed for comparing the primary orbital dynamics behavior between space systems distributed simulations. This process is used to characterize and understand the fundamental fidelities and compatibilities of the modeling of orbital dynamics between spacecraft simulations. This is required for high-latency distributed simulations such as NASA s Integrated Mission Simulation and must be understood when reporting results from simulation executions. This paper presents 10 principal comparison tests along with their rationale and examples of the results. The Integrated Mission Simulation (IMSim) (formerly know as the Distributed Space Exploration Simulation (DSES)) is a NASA research and development project focusing on the technologies and processes that are related to the collaborative simulation of complex space systems involved in the exploration of our solar system. Currently, the NASA centers that are actively participating in the IMSim project are the Ames Research Center, the Jet Propulsion Laboratory (JPL), the Johnson Space Center (JSC), the Kennedy Space Center, the Langley Research Center and the Marshall Space Flight Center. In concept, each center participating in IMSim has its own set of simulation models and environment(s). These simulation tools are used to build the various simulation products that are used for scientific investigation, engineering analysis, system design, training, planning, operations and more. Working individually, these production simulations provide important data to various NASA projects.

Dynamical interaction of He atoms with metal surfaces: Charge transfer processes

International Nuclear Information System (INIS)

Flores, F.; Garcia Vidal, F.J.; Monreal, R.

1993-01-01

A self-consistent Kohn-Sham LCAO method is presented to calculate the charge transfer processes between a He * -atom and metal surfaces. Intra-atomic correlation effects are taken into account by considering independently each single He-orbital and by combining the different charge transfer processes into a set of dynamical rate equations for the different ion charge fractions. Our discussion reproduces qualitatively the experimental evidence and gives strong support to the method presented here. (author). 24 refs, 4 figs

Modeling Dynamic Food Choice Processes to Understand Dietary Intervention Effects.

Science.gov (United States)

Marcum, Christopher Steven; Goldring, Megan R; McBride, Colleen M; Persky, Susan

2018-02-17

Meal construction is largely governed by nonconscious and habit-based processes that can be represented as a collection of in dividual, micro-level food choices that eventually give rise to a final plate. Despite this, dietary behavior intervention research rarely captures these micro-level food choice processes, instead measuring outcomes at aggregated levels. This is due in part to a dearth of analytic techniques to model these dynamic time-series events. The current article addresses this limitation by applying a generalization of the relational event framework to model micro-level food choice behavior following an educational intervention. Relational event modeling was used to model the food choices that 221 mothers made for their child following receipt of an information-based intervention. Participants were randomized to receive either (a) control information; (b) childhood obesity risk information; (c) childhood obesity risk information plus a personalized family history-based risk estimate for their child. Participants then made food choices for their child in a virtual reality-based food buffet simulation. Micro-level aspects of the built environment, such as the ordering of each food in the buffet, were influential. Other dynamic processes such as choice inertia also influenced food selection. Among participants receiving the strongest intervention condition, choice inertia decreased and the overall rate of food selection increased. Modeling food selection processes can elucidate the points at which interventions exert their influence. Researchers can leverage these findings to gain insight into nonconscious and uncontrollable aspects of food selection that influence dietary outcomes, which can ultimately improve the design of dietary interventions.

The Temporal Dynamics of Visual Search: Evidence for Parallel Processing in Feature and Conjunction Searches

Science.gov (United States)

McElree, Brian; Carrasco, Marisa

2012-01-01

Feature and conjunction searches have been argued to delineate parallel and serial operations in visual processing. The authors evaluated this claim by examining the temporal dynamics of the detection of features and conjunctions. The 1st experiment used a reaction time (RT) task to replicate standard mean RT patterns and to examine the shapes of the RT distributions. The 2nd experiment used the response-signal speed–accuracy trade-off (SAT) procedure to measure discrimination (asymptotic detection accuracy) and detection speed (processing dynamics). Set size affected discrimination in both feature and conjunction searches but affected detection speed only in the latter. Fits of models to the SAT data that included a serial component overpredicted the magnitude of the observed dynamics differences. The authors concluded that both features and conjunctions are detected in parallel. Implications for the role of attention in visual processing are discussed. PMID:10641310

The development and application of dynamic operational risk assessment in oil/gas and chemical process industry

International Nuclear Information System (INIS)

Yang Xiaole; Mannan, M. Sam

2010-01-01

A methodology of dynamic operational risk assessment (DORA) is proposed for operational risk analysis in oil/gas and chemical industries. The methodology is introduced comprehensively starting from the conceptual framework design to mathematical modeling and to decision making based on cost-benefit analysis. The probabilistic modeling part of DORA integrates stochastic modeling and process dynamics modeling to evaluate operational risk. The stochastic system-state trajectory is modeled according to the abnormal behavior or failure of each component. For each of the possible system-state trajectories, a process dynamics evaluation is carried out to check whether process variables, e.g., level, flow rate, temperature, pressure, or chemical concentration, remain in their desirable regions. Component testing/inspection intervals and repair times are critical parameters to define the system-state configuration, and play an important role for evaluating the probability of operational failure. This methodology not only provides a framework to evaluate the dynamic operational risk in oil/gas and chemical industries, but also guides the process design and further optimization. To illustrate the probabilistic study, we present a case-study of a level control in an oil/gas separator at an offshore plant.

Study of selected phenotype switching strategies in time varying environment

Energy Technology Data Exchange (ETDEWEB)

Horvath, Denis, E-mail: horvath.denis@gmail.com [Centre of Interdisciplinary Biosciences, Institute of Physics, Faculty of Science, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia); Brutovsky, Branislav, E-mail: branislav.brutovsky@upjs.sk [Department of Biophysics, Institute of Physics, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia)

2016-03-22

Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

Study of selected phenotype switching strategies in time varying environment

International Nuclear Information System (INIS)

Horvath, Denis; Brutovsky, Branislav

2016-01-01

Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

On process model representation and AlF{sub 3} dynamics of aluminium electrolysis cells

Energy Technology Data Exchange (ETDEWEB)

Drengstig, Tormod

1997-12-31

This thesis develops a formal graphical based process representation scheme for modelling complex, non-standard unit processes. The scheme is based on topological and phenomenological decompositions. The topological decomposition is the modularization of processes into modules representing volumes and boundaries, whereas the phenomenological decomposition focuses on physical phenomena and characteristics inside these topological modules. This defines legal and illegal connections between components at all levels and facilitates a full implementation of the methodology into a computer aided modelling tool that can interpret graphical symbols and guide modelers towards a consistent mathematical model of the process. The thesis also presents new results on the excess AlF{sub 3} and bath temperature dynamics of an aluminium electrolysis cell. A dynamic model of such a cell is developed and validated against known behaviour and real process data. There are dynamics that the model does not capture and this is further discussed. It is hypothesized that long-term prediction of bath temperature and excess AlF{sub 3} is impossible with a current efficiency model considering only bath composition and temperature. A control strategy for excess AlF{sub 3} and bath temperature is proposed based on an almost constant AlF{sub 3} input close to average consumption and energy manipulations to compensate for the disturbances. 96 refs., 135 figs., 22 tabs.

Statistical mechanical approach to secondary processes and structural relaxation in glasses and glass formers: a leading model to describe the onset of Johari-Goldstein processes and their relationship with fully cooperative processes.

Science.gov (United States)

Crisanti, A; Leuzzi, L; Paoluzzi, M

2011-09-01

The interrelation of dynamic processes active on separated time-scales in glasses and viscous liquids is investigated using a model displaying two time-scale bifurcations both between fast and secondary relaxation and between secondary and structural relaxation. The study of the dynamics allows for predictions on the system relaxation above the temperature of dynamic arrest in the mean-field approximation, that are compared with the outcomes of the equations of motion directly derived within the Mode Coupling Theory (MCT) for under-cooled viscous liquids. By varying the external thermodynamic parameters, a wide range of phenomenology can be represented, from a very clear separation of structural and secondary peak in the susceptibility loss to excess wing structures.

Dynamic Characteristics of Buildings from Signal Processing of Ambient Vibration

Science.gov (United States)

Dobre, Daniela; Sorin Dragomir, Claudiu

2017-10-01

The experimental technique used to determine the dynamic characteristics of buildings is based on records of low intensity oscillations of the building produced by various natural factors, such as permanent agitation type microseismic motions, city traffic, wind etc. The possibility of recording these oscillations is provided by the latest seismic stations (Geosig and Kinemetrics digital accelerographs). The permanent microseismic agitation of the soil is a complex form of stationary random oscillations. The building filters the soil excitation, selects and increases the components of disruptive vibrations corresponding to its natural vibration periods. For some selected buildings, with different instrumentation schemes for the location of sensors (in free-field, at basement, ground floor, roof level), a correlation between the dynamic characteristics resulted from signal processing of ambient vibration and from a theoretical analysis will be presented. The interpretation of recording results could highlight the behavior of the whole structure. On the other hand, these results are compared with those from strong motions, or obtained from a complex dynamic analysis, and they are quite different, but they are explicable.

Hematopoietic differentiation: a coordinated dynamical process towards attractor stable states

Directory of Open Access Journals (Sweden)

Rossi Simona

2010-06-01

Full Text Available Abstract Background The differentiation process, proceeding from stem cells towards the different committed cell types, can be considered as a trajectory towards an attractor of a dynamical process. This view, taking into consideration the transcriptome and miRNome dynamics considered as a whole, instead of looking at few 'master genes' driving the system, offers a novel perspective on this phenomenon. We investigated the 'differentiation trajectories' of the hematopoietic system considering a genome-wide scenario. Results We developed serum-free liquid suspension unilineage cultures of cord blood (CB CD34+ hematopoietic progenitor cells through erythroid (E, megakaryocytic (MK, granulocytic (G and monocytic (Mo pathways. These cultures recapitulate physiological hematopoiesis, allowing the analysis of almost pure unilineage precursors starting from initial differentiation of HPCs until terminal maturation. By analyzing the expression profile of protein coding genes and microRNAs in unilineage CB E, MK, G and Mo cultures, at sequential stages of differentiation and maturation, we observed a coordinated, fully interconnected and scalable character of cell population behaviour in both transcriptome and miRNome spaces reminiscent of an attractor-like dynamics. MiRNome and transcriptome space differed for a still not terminally committed behaviour of microRNAs. Conclusions Consistent with their roles, the transcriptome system can be considered as the state space of a cell population, while the continuously evolving miRNA space corresponds to the tuning system necessary to reach the attractor. The behaviour of miRNA machinery could be of great relevance not only for the promise of reversing the differentiated state but even for tumor biology.

Seasonal sediment dynamics shape temperate bedrock reef communities

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Figurski, Jared D.; Freiwald, Jan; Lonhart, Steve I.; Storlazzi, Curt

2016-01-01

Mobilized seafloor sediment can impact benthic reef communities through burial, scour, and turbidity. These processes are ubiquitous in coastal oceans and, through their influence on the survival, fitness, and interactions of species, can alter the structure and function of benthic communities. In northern Monterey Bay, California, USA, as much as 30% of the seafloor is buried or exposed seasonally, making this an ideal location to test how subtidal temperate rocky reef communities vary in the presence and absence of chronic sediment-based disturbances. Designated dynamic plots were naturally inundated by sediment in summer (50 to 100% cover) and swept clean in winter, whereas designated stable plots remained free of sediment during our study. Multivariate analyses indicated significant differences in the structure of sessile and mobile communities between dynamic and stable reef habitats. For sessile species, community structure in disturbed plots was less variable in space and time than in stable plots due to the maintenance of an early successional state. In contrast, community structure of mobile species varied more in disturbed plots than in stable plots, reflecting how mobile species distribute in response to sediment dynamics. Some species were found only in these disturbed areas, suggesting that the spatial mosaic of disturbance could increase regional diversity. We discuss how the relative ability of species to tolerate disturbance at different life history stages and their ability to colonize habitat translate into community-level differences among habitats, and how this response varies between mobile and sessile communities.

Emotion unfolded by motion: a role for parietal lobe in decoding dynamic facial expressions.

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Sarkheil, Pegah; Goebel, Rainer; Schneider, Frank; Mathiak, Klaus

2013-12-01

Facial expressions convey important emotional and social information and are frequently applied in investigations of human affective processing. Dynamic faces may provide higher ecological validity to examine perceptual and cognitive processing of facial expressions. Higher order processing of emotional faces was addressed by varying the task and virtual face models systematically. Blood oxygenation level-dependent activation was assessed using functional magnetic resonance imaging in 20 healthy volunteers while viewing and evaluating either emotion or gender intensity of dynamic face stimuli. A general linear model analysis revealed that high valence activated a network of motion-responsive areas, indicating that visual motion areas support perceptual coding for the motion-based intensity of facial expressions. The comparison of emotion with gender discrimination task revealed increased activation of inferior parietal lobule, which highlights the involvement of parietal areas in processing of high level features of faces. Dynamic emotional stimuli may help to emphasize functions of the hypothesized 'extended' over the 'core' system for face processing.

Modeling information diffusion in time-varying community networks

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Cui, Xuelian; Zhao, Narisa

2017-12-01

Social networks are rarely static, and they typically have time-varying network topologies. A great number of studies have modeled temporal networks and explored social contagion processes within these models; however, few of these studies have considered community structure variations. In this paper, we present a study of how the time-varying property of a modular structure influences the information dissemination. First, we propose a continuous-time Markov model of information diffusion where two parameters, mobility rate and community attractiveness, are introduced to address the time-varying nature of the community structure. The basic reproduction number is derived, and the accuracy of this model is evaluated by comparing the simulation and theoretical results. Furthermore, numerical results illustrate that generally both the mobility rate and community attractiveness significantly promote the information diffusion process, especially in the initial outbreak stage. Moreover, the strength of this promotion effect is much stronger when the modularity is higher. Counterintuitively, it is found that when all communities have the same attractiveness, social mobility no longer accelerates the diffusion process. In addition, we show that the local spreading in the advantage group has been greatly enhanced due to the agglomeration effect caused by the social mobility and community attractiveness difference, which thus increases the global spreading.

Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.

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Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod

2017-07-15

There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal

Importance of interactions between food quality, quantity, and gut transit time on consumer feeding, growth, and trophic dynamics.

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Mitra, Aditee; Flynn, Kevin J

2007-05-01

Ingestion kinetics of animals are controlled by both external food availability and feedback from the quantity of material already within the gut. The latter varies with gut transit time (GTT) and digestion of the food. Ingestion, assimilation efficiency, and thus, growth dynamics are not related in a simple fashion. For the first time, the important linkage between these processes and GTT is demonstrated; this is achieved using a biomass-based, mechanistic multinutrient model fitted to experimental data for zooplankton growth dynamics when presented with food items of varying quality (stoichiometric composition) or quantity. The results show that trophic transfer dynamics will vary greatly between the extremes of feeding on low-quantity/high-quality versus high-quantity/low-quality food; these conditions are likely to occur in nature. Descriptions of consumer behavior that assume a constant relationship between the kinetics of grazing and growth irrespective of food quality and/or quantity, with little or no recognition of the combined importance of these factors on consumer behavior, may seriously misrepresent consumer activity in dynamic situations.

The role of gap phase processes in the biomass dynamics of tropical forests

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Feeley, Kenneth J; Davies, Stuart J; Ashton, Peter S; Bunyavejchewin, Sarayudh; Nur Supardi, M.N; Kassim, Abd Rahman; Tan, Sylvester; Chave, Jérôme

2007-01-01

The responses of tropical forests to global anthropogenic disturbances remain poorly understood. Above-ground woody biomass in some tropical forest plots has increased over the past several decades, potentially reflecting a widespread response to increased resource availability, for example, due to elevated atmospheric CO2 and/or nutrient deposition. However, previous studies of biomass dynamics have not accounted for natural patterns of disturbance and gap phase regeneration, making it difficult to quantify the importance of environmental changes. Using spatially explicit census data from large (50 ha) inventory plots, we investigated the influence of gap phase processes on the biomass dynamics of four ‘old-growth’ tropical forests (Barro Colorado Island (BCI), Panama; Pasoh and Lambir, Malaysia; and Huai Kha Khaeng (HKK), Thailand). We show that biomass increases were gradual and concentrated in earlier-phase forest patches, while biomass losses were generally of greater magnitude but concentrated in rarer later-phase patches. We then estimate the rate of biomass change at each site independent of gap phase dynamics using reduced major axis regressions and ANCOVA tests. Above-ground woody biomass increased significantly at Pasoh (+0.72% yr−1) and decreased at HKK (−0.56% yr−1) independent of changes in gap phase but remained stable at both BCI and Lambir. We conclude that gap phase processes play an important role in the biomass dynamics of tropical forests, and that quantifying the role of gap phase processes will help improve our understanding of the factors driving changes in forest biomass as well as their place in the global carbon budget. PMID:17785266

The Dose-Dependent Effects of Vascular Risk Factors on Dynamic Compensatory Neural Processes in Mild Cognitive Impairment

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Haifeng Chen

2018-05-01

Full Text Available Background/Objectives: Mild cognitive impairment (MCI has been associated with risk for Alzheimer's Disease (AD. Previous investigations have suggested that vascular risk factors (VRFs were associated with cognitive decline and AD pathogenesis, and the intervention of VRFs may be a possible way to prevent dementia. However, in MCI, little is known about the potential impacts of VRFs on neural networks and their neural substrates, which may be a neuroimaging biomarker of the disease progression.Methods: 128 elderly Han Chinese participants (67 MCI subjects and 61 matched normal elderly with or without VRFs (hypertension, diabetes mellitus, hypercholesterolemia, smoking and alcohol drinking underwent the resting-state functional magnetic resonance imaging (fMRI and neuropsychological tests. We obtained the default mode network (DMN to identify alterations in MCI with the varying number of the VRF and analyzed the significant correlation with behavioral performance.Results: The effects of VRF on the DMN were primarily in bilateral dorsolateral prefrontal cortex (DLPFC (i.e., middle frontal gyrus. Normal elderly showed the gradually increased functional activity of DLPFC, while a fluctuant activation of DLPFC was displayed in MCI with the growing number of the VRF. Interestingly, the left DLPFC further displayed significantly dynamic correlation with executive function as the variation of VRF loading. Initial level of compensation was observed in normal aging and none-vascular risk factor (NVRF MCI, while these compensatory neural processes were suppressed in One-VRF MCI and were subsequently re-aroused in Over-One-VRF MCI.Conclusions: These findings suggested that the dose-dependent effects of VRF on DLPFC were highlighted in MCI, and the dynamic compensatory neural processes that fluctuated along with variations of VRF loading could be key role in the progression of MCI.

Ultrafast dynamics in semiconductor optical amplifiers and all-optical processing: Bulk versus quantum dot devices

DEFF Research Database (Denmark)

Mørk, Jesper; Berg, Tommy Winther; Magnúsdóttir, Ingibjörg

2003-01-01

We discuss the dynamical properties of semiconductor optical amplifiers and the importance for all-optical signal processing. In particular, the dynamics of quantum dot amplifiers is considered and it is suggested that these may be operated at very high bit-rates without significant patterning...

Dynamical modeling of microRNA action on the protein translation process.

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Zinovyev, Andrei; Morozova, Nadya; Nonne, Nora; Barillot, Emmanuel; Harel-Bellan, Annick; Gorban, Alexander N

2010-02-24

Protein translation is a multistep process which can be represented as a cascade of biochemical reactions (initiation, ribosome assembly, elongation, etc.), the rate of which can be regulated by small non-coding microRNAs through multiple mechanisms. It remains unclear what mechanisms of microRNA action are the most dominant: moreover, many experimental reports deliver controversial messages on what is the concrete mechanism actually observed in the experiment. Nissan and Parker have recently demonstrated that it might be impossible to distinguish alternative biological hypotheses using the steady state data on the rate of protein synthesis. For their analysis they used two simple kinetic models of protein translation. In contrary to the study by Nissan and Parker, we show that dynamical data allow discriminating some of the mechanisms of microRNA action. We demonstrate this using the same models as developed by Nissan and Parker for the sake of comparison but the methods developed (asymptotology of biochemical networks) can be used for other models. We formulate a hypothesis that the effect of microRNA action is measurable and observable only if it affects the dominant system (generalization of the limiting step notion for complex networks) of the protein translation machinery. The dominant system can vary in different experimental conditions that can partially explain the existing controversy of some of the experimental data. Our analysis of the transient protein translation dynamics shows that it gives enough information to verify or reject a hypothesis about a particular molecular mechanism of microRNA action on protein translation. For multiscale systems only that action of microRNA is distinguishable which affects the parameters of dominant system (critical parameters), or changes the dominant system itself. Dominant systems generalize and further develop the old and very popular idea of limiting step. Algorithms for identifying dominant systems in multiscale

Dynamical modeling of microRNA action on the protein translation process

Directory of Open Access Journals (Sweden)

Barillot Emmanuel

2010-02-01

Full Text Available Abstract Background Protein translation is a multistep process which can be represented as a cascade of biochemical reactions (initiation, ribosome assembly, elongation, etc., the rate of which can be regulated by small non-coding microRNAs through multiple mechanisms. It remains unclear what mechanisms of microRNA action are the most dominant: moreover, many experimental reports deliver controversial messages on what is the concrete mechanism actually observed in the experiment. Nissan and Parker have recently demonstrated that it might be impossible to distinguish alternative biological hypotheses using the steady state data on the rate of protein synthesis. For their analysis they used two simple kinetic models of protein translation. Results In contrary to the study by Nissan and Parker, we show that dynamical data allow discriminating some of the mechanisms of microRNA action. We demonstrate this using the same models as developed by Nissan and Parker for the sake of comparison but the methods developed (asymptotology of biochemical networks can be used for other models. We formulate a hypothesis that the effect of microRNA action is measurable and observable only if it affects the dominant system (generalization of the limiting step notion for complex networks of the protein translation machinery. The dominant system can vary in different experimental conditions that can partially explain the existing controversy of some of the experimental data. Conclusions Our analysis of the transient protein translation dynamics shows that it gives enough information to verify or reject a hypothesis about a particular molecular mechanism of microRNA action on protein translation. For multiscale systems only that action of microRNA is distinguishable which affects the parameters of dominant system (critical parameters, or changes the dominant system itself. Dominant systems generalize and further develop the old and very popular idea of limiting step

Leading-process actomyosin coordinates organelle positioning and adhesion receptor dynamics in radially migrating cerebellar granule neurons.

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Trivedi, Niraj; Ramahi, Joseph S; Karakaya, Mahmut; Howell, Danielle; Kerekes, Ryan A; Solecki, David J

2014-12-02

During brain development, neurons migrate from germinal zones to their final positions to assemble neural circuits. A unique saltatory cadence involving cyclical organelle movement (e.g., centrosome motility) and leading-process actomyosin enrichment prior to nucleokinesis organizes neuronal migration. While functional evidence suggests that leading-process actomyosin is essential for centrosome motility, the role of the actin-enriched leading process in globally organizing organelle transport or traction forces remains unexplored. We show that myosin ii motors and F-actin dynamics are required for Golgi apparatus positioning before nucleokinesis in cerebellar granule neurons (CGNs) migrating along glial fibers. Moreover, we show that primary cilia are motile organelles, localized to the leading-process F-actin-rich domain and immobilized by pharmacological inhibition of myosin ii and F-actin dynamics. Finally, leading process adhesion dynamics are dependent on myosin ii and F-actin. We propose that actomyosin coordinates the overall polarity of migrating CGNs by controlling asymmetric organelle positioning and cell-cell contacts as these cells move along their glial guides.

Neural pathways in processing of sexual arousal: a dynamic causal modeling study.

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Seok, J-W; Park, M-S; Sohn, J-H

2016-09-01

Three decades of research have investigated brain processing of visual sexual stimuli with neuroimaging methods. These researchers have found that sexual arousal stimuli elicit activity in a broad neural network of cortical and subcortical brain areas that are known to be associated with cognitive, emotional, motivational and physiological components. However, it is not completely understood how these neural systems integrate and modulated incoming information. Therefore, we identify cerebral areas whose activations were correlated with sexual arousal using event-related functional magnetic resonance imaging and used the dynamic causal modeling method for searching the effective connectivity about the sexual arousal processing network. Thirteen heterosexual males were scanned while they passively viewed alternating short trials of erotic and neutral pictures on a monitor. We created a subset of seven models based on our results and previous studies and selected a dominant connectivity model. Consequently, we suggest a dynamic causal model of the brain processes mediating the cognitive, emotional, motivational and physiological factors of human male sexual arousal. These findings are significant implications for the neuropsychology of male sexuality.

Dynamic flowgraph modeling of process and control systems of a nuclear-based hydrogen production plant

Energy Technology Data Exchange (ETDEWEB)

Al-Dabbagh, Ahmad W. [Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario (Canada); Lu, Lixuan [Faculty of Energy Systems and Nuclear Science, Faculty of Engineering and Applied Science, University of Ontario Institute of Technology, 2000 Simcoe Street North, Oshawa, Ontario (Canada)

2010-09-15

Modeling and analysis of system reliability facilitate the identification of areas of potential improvement. The Dynamic Flowgraph Methodology (DFM) is an emerging discrete modeling framework that allows for capturing time dependent behaviour, switching logic and multi-state representation of system components. The objective of this research is to demonstrate the process of dynamic flowgraph modeling of a nuclear-based hydrogen production plant with the copper-chlorine (Cu-Cl) cycle. Modeling of the thermochemical process of the Cu-Cl cycle in conjunction with a networked control system proposed for monitoring and control of the process is provided. This forms the basis for future component selection. (author)

Stochastic population dynamics of a montane ground-dwelling squirrel.

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Hostetler, Jeffrey A; Kneip, Eva; Van Vuren, Dirk H; Oli, Madan K

2012-01-01

Understanding the causes and consequences of population fluctuations is a central goal of ecology. We used demographic data from a long-term (1990-2008) study and matrix population models to investigate factors and processes influencing the dynamics and persistence of a golden-mantled ground squirrel (Callospermophilus lateralis) population, inhabiting a dynamic subalpine habitat in Colorado, USA. The overall deterministic population growth rate λ was 0.94±SE 0.05 but it varied widely over time, ranging from 0.45±0.09 in 2006 to 1.50±0.12 in 2003, and was below replacement (λbounce back from low densities and prevented extinction. These results suggest that dynamics and persistence of our study population are determined synergistically by density-dependence, stochastic forces, and immigration.

Seasonal dynamics of phytoplankton in two tropical rivers of varying size and human impact in Southeast Nigeria

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Okechukwu Idumah Okogwu

2013-12-01

Full Text Available Phytoplankton occurrence and dynamics in rivers are mainly shaped by hydrophysical conditions and nutrient availability. Phytoplankton main structuring factors have been poorly studied in West African rivers, and this study was undertaken to identify these conditions in two tropical rivers that vary in size and human impact. For this, environmental variables and phytoplankton monthly samples were collected from the middle reaches of Asu and Cross rivers during an 18 months survey from March 2005-July 2006. Phytoplankton biomass (F=11.87, p=0.003, Shannon-Weiner diversity and species richness (F=5.93, p=0.003 showed significant seasonality in Asu but not in Cross River. Data was analyzed with Canonical correspondence analysis (CCA and showed environmental differences between the two rivers, nitrate in Asu River (5.1-15.5mg/L was significantly higher than Cross River (0.03-1.7mg/L, while PO4 (0.2-0.9mg/L was significantly lower in Asu River compared to Cross River (0.03-2.6mg/L (p<0.05. Eutrophic factors (NO3 determined primarily phytoplankton dynamics in Asu River, especially during the dry season, whereas hydrophysical factors (depth, transparency and temperature shaped phytoplankton in Cross River. Taxa indicative of an eutrophic condition, such as Euglena, Chlorella, Chlorococcus, Ceratium, Peridinium, Anabaena, Aphanizomenon, Closterium, Scenedesmus and Pediastrum spp., were frequently encountered in the shallow impounded Asu River, while riverine species, such as Frustulia rhomboids, Gyrosigma sp., Opephora martyr and Surirella splendida dominated Cross River. A succession pattern was observed in the functional groups identified: Na/MP→TB→P (rainy→dry season was observed in Asu River, whereas MP/D predominated in Cross River for both seasons. We concluded that, if nutrients predominate hydrophysical factors in shaping phytoplankton during dry season (half of the year then, they are as important as hydrophysical factors structuring

Innovation diffusion on time-varying activity driven networks

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Rizzo, Alessandro; Porfiri, Maurizio

2016-01-01

Since its introduction in the 1960s, the theory of innovation diffusion has contributed to the advancement of several research fields, such as marketing management and consumer behavior. The 1969 seminal paper by Bass [F.M. Bass, Manag. Sci. 15, 215 (1969)] introduced a model of product growth for consumer durables, which has been extensively used to predict innovation diffusion across a range of applications. Here, we propose a novel approach to study innovation diffusion, where interactions among individuals are mediated by the dynamics of a time-varying network. Our approach is based on the Bass' model, and overcomes key limitations of previous studies, which assumed timescale separation between the individual dynamics and the evolution of the connectivity patterns. Thus, we do not hypothesize homogeneous mixing among individuals or the existence of a fixed interaction network. We formulate our approach in the framework of activity driven networks to enable the analysis of the concurrent evolution of the interaction and individual dynamics. Numerical simulations offer a systematic analysis of the model behavior and highlight the role of individual activity on market penetration when targeted advertisement campaigns are designed, or a competition between two different products takes place.

Contamination control in HVAC systems for aseptic processing area. Part I: Case study of the airflow velocity in a unidirectional airflow workstation with computational fluid dynamics.

Science.gov (United States)

Ogawa, M

2000-01-01

A unidirectional airflow workstation for processing a sterile pharmaceutical product is required to be "Grade A," according to EU-GMP and WHO-GMP. These regulations have employed the wording of "laminar airflow" for unidirectional airflow, with an unclear definition given. This seems to have allowed many reports to describe discussion of airflow velocity only. The guidance values as to the velocity are expressed in various words of 90 ft/min, 0.45 m/sec, 0.3 m/sec, +/- 20%, or "homogeneous air speed." It has been also little clarified how variation in airflow velocity gives influences on contamination control of a workstation working with varying key characteristics, such as ceiling height, internal heat load, internal particle generation, etc. The present author has revealed following points from a case study using Computational Fluid Dynamics: the airflow characteristic in Grade A area shows no significant changes with varying the velocity of supplied airflow, and the particles generated from the operator will be exhausted outside Grade A area without contamination.

Finite element simulation of dynamic wetting flows as an interface formation process

KAUST Repository

Sprittles, J.E.; Shikhmurzaev, Y.D.

2013-01-01

A mathematically challenging model of dynamic wetting as a process of interface formation has been, for the first time, fully incorporated into a numerical code based on the finite element method and applied, as a test case, to the problem

Application of Wavelet-Based Tools to Study the Dynamics of Biological Processes

DEFF Research Database (Denmark)

Pavlov, A. N.; Makarov, V. A.; Mosekilde, Erik

2006-01-01

The article makes use of three different examples (sensory information processing in the rat trigeminal complex, intracellular interaction in snail neurons and multimodal dynamics in nephron autoregulation) to demonstrate how modern approaches to time-series analysis based on the wavelet-transfor...

Path coefficient analysis of zinc dynamics in varying soil environment

International Nuclear Information System (INIS)

Rattan, R.K.; Phung, C.V.; Singhal, S.K.; Deb, D.L.; Singh, A.K.

1994-01-01

Influence of soil properties on labile zinc, as measured by diethylene-triamine pentaacetic acid (DTPA) and zinc-65, and self-diffusion coefficients of zinc was assessed on 22 surface soil samples varying widely in their characteristics following linear regression and path coefficient analysis techniques. DTPA extractable zinc could be predicted from organic carbon status and pH of the soil with a highly significant coefficient of determination (R 2 =0.84 ** ). Ninety seven per cent variation in isotopically exchangeable zinc was explained by pH, clay content and cation exchange capacity (CEC) of soil. The self-diffusion coefficients (DaZn and DpZn) and buffer power of zinc exhibited exponential relationship with soil properties, pH being the most dominant one. Soil properties like organic matter, clay content etc. exhibited indirect effects on zinc diffusion rates via pH only. (author). 13 refs., 6 tabs

Dynamic Musical Communication of Core Affect

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Nicole eFlaig

2014-03-01

Full Text Available Is there something special about the way music communicates feelings? Theorists since Meyer (1956 have attempted to explain how music could stimulate varied and subtle affective experiences by violating learned expectancies, or by mimicking other forms of social interaction. Our proposal is that music speaks to the brain in its own language; it need not imitate any other form of communication. We review recent theoretical and empirical literature, which suggests that all conscious processes consist of dynamic neural events, produced by spatially dispersed processes in the physical brain. Intentional thought and affective experience arise as dynamical aspects of neural events taking place in multiple brain areas simultaneously. At any given moment, this content comprises a unified scene that is integrated into a dynamic core through synchrony of neuronal oscillations. We propose that 1 neurodynamic synchrony with musical stimuli gives rise to musical qualia including tonal and temporal expectancies, and that 2 music-synchronous responses couple into core neurodynamics, enabling music to directly modulate core affect. Expressive music performance, for example, may recruit rhythm-synchronous neural responses to support affective communication. We suggest that the dynamic relationship between musical expression and the experience of affect presents a unique opportunity for the study of emotional experience. This may help elucidate the neural mechanisms underlying arousal and valence, and offer a new approach to exploring the complex dynamics of the how and why of emotional experience.

Evaluation and improvement of dynamic optimality in electrochemical reactors

International Nuclear Information System (INIS)

Vijayasekaran, B.; Basha, C. Ahmed

2005-01-01

A systematic approach for the dynamic optimization problem statement to improve the dynamic optimality in electrochemical reactors is presented in this paper. The formulation takes an account of the diffusion phenomenon in the electrode/electrolyte interface. To demonstrate the present methodology, the optimal time-varying electrode potential for a coupled chemical-electrochemical reaction scheme, that maximizes the production of the desired product in a batch electrochemical reactor with/without recirculation are determined. The dynamic optimization problem statement, based upon this approach, is a nonlinear differential algebraic system, and its solution provides information about the optimal policy. Optimal control policy at different conditions is evaluated using the best-known Pontryagin's maximum principle. The two-point boundary value problem resulting from the application of the maximum principle is then solved using the control vector iteration technique. These optimal time-varying profiles of electrode potential are then compared to the best uniform operation through the relative improvements of the performance index. The application of the proposed approach to two electrochemical systems, described by ordinary differential equations, shows that the existing electrochemical process control strategy could be improved considerably when the proposed method is incorporated

Genetic algorithm–based varying parameter linear quadratic regulator control for four-wheel independent steering vehicle

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Linlin Gao

2015-11-01

Full Text Available From the perspective of vehicle dynamics, the four-wheel independent steering vehicle dynamics stability control method is studied, and a four-wheel independent steering varying parameter linear quadratic regulator control system is proposed with the help of expert control method. In the article, a four-wheel independent steering linear quadratic regulator controller for model following purpose is designed first. Then, by analyzing the four-wheel independent steering vehicle dynamic characteristics and the influence of linear quadratic regulator control parameters on control performance, a linear quadratic regulator control parameter adjustment strategy based on vehicle steering state is proposed to achieve the adaptive adjustment of linear quadratic regulator control parameters. In addition, to further improve the control performance, the proposed varying parameter linear quadratic regulator control system is optimized by genetic algorithm. Finally, simulation studies have been conducted by applying the proposed control system to the 8-degree-of-freedom four-wheel independent steering vehicle dynamics model. The simulation results indicate that the proposed control system has better performance and robustness and can effectively improve the stability and steering safety of the four-wheel independent steering vehicle.

Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.

Science.gov (United States)

Shi, Junxing; Wen, Haiguang; Zhang, Yizhen; Han, Kuan; Liu, Zhongming

2018-05-01

The human visual cortex extracts both spatial and temporal visual features to support perception and guide behavior. Deep convolutional neural networks (CNNs) provide a computational framework to model cortical representation and organization for spatial visual processing, but unable to explain how the brain processes temporal information. To overcome this limitation, we extended a CNN by adding recurrent connections to different layers of the CNN to allow spatial representations to be remembered and accumulated over time. The extended model, or the recurrent neural network (RNN), embodied a hierarchical and distributed model of process memory as an integral part of visual processing. Unlike the CNN, the RNN learned spatiotemporal features from videos to enable action recognition. The RNN better predicted cortical responses to natural movie stimuli than the CNN, at all visual areas, especially those along the dorsal stream. As a fully observable model of visual processing, the RNN also revealed a cortical hierarchy of temporal receptive window, dynamics of process memory, and spatiotemporal representations. These results support the hypothesis of process memory, and demonstrate the potential of using the RNN for in-depth computational understanding of dynamic natural vision. © 2018 Wiley Periodicals, Inc.

Estimation of Dynamic Friction Process of the Akatani Landslide Based on the Waveform Inversion and Numerical Simulation

Science.gov (United States)

Yamada, M.; Mangeney, A.; Moretti, L.; Matsushi, Y.

2014-12-01

Understanding physical parameters, such as frictional coefficients, velocity change, and dynamic history, is important issue for assessing and managing the risks posed by deep-seated catastrophic landslides. Previously, landslide motion has been inferred qualitatively from topographic changes caused by the event, and occasionally from eyewitness reports. However, these conventional approaches are unable to evaluate source processes and dynamic parameters. In this study, we use broadband seismic recordings to trace the dynamic process of the deep-seated Akatani landslide that occurred on the Kii Peninsula, Japan, which is one of the best recorded large slope failures. Based on the previous results of waveform inversions and precise topographic surveys done before and after the event, we applied numerical simulations using the SHALTOP numerical model (Mangeney et al., 2007). This model describes homogeneous continuous granular flows on a 3D topography based on a depth averaged thin layer approximation. We assume a Coulomb's friction law with a constant friction coefficient, i. e. the friction is independent of the sliding velocity. We varied the friction coefficients in the simulation so that the resulting force acting on the surface agrees with the single force estimated from the seismic waveform inversion. Figure shows the force history of the east-west components after the band-pass filtering between 10-100 seconds. The force history of the simulation with frictional coefficient 0.27 (thin red line) the best agrees with the result of seismic waveform inversion (thick gray line). Although the amplitude is slightly different, phases are coherent for the main three pulses. This is an evidence that the point-source approximation works reasonably well for this particular event. The friction coefficient during the sliding was estimated to be 0.38 based on the seismic waveform inversion performed by the previous study and on the sliding block model (Yamada et al., 2013

Dynamics of nanomaterials released from polymer composites in the pelletizing process

International Nuclear Information System (INIS)

Kato, Nobuyuki; Yoneda, Minoru; Matsui, Yasuto

2017-01-01

Measures against exposure to carbon nanotubes (CNT) are necessary, especially in workplaces that handle nanomaterials, because adverse health effects are a concern. This study focuses on the dynamics of CNT released from CNT/polymer composites during the pelletizing process at a pilot factory. It is difficult to identify CNT and the base resin. By characterizing the possibility of separating CNT from the composite with a kinetic weighting coefficient, estimation can be carried out using a Computational Fluid Dynamics (CFD) simulation. The mass concentration of black carbon and the particle number concentration by diameter were measured using two different measurement apparatuses. The simulation results were then compared to the measured data. The model was verified by the correlation between the simulation and measured results. The model provided a strong correlation, indicating that the dynamics of CNT and the base resin released from the polymer composite can be simulated. It is expected that the model using the CFD simulation can be applied to the occupational health field. (paper)

Does dynamic information about the speaker's face contribute to semantic speech processing? ERP evidence.

Science.gov (United States)

Hernández-Gutiérrez, David; Abdel Rahman, Rasha; Martín-Loeches, Manuel; Muñoz, Francisco; Schacht, Annekathrin; Sommer, Werner

2018-07-01

Face-to-face interactions characterize communication in social contexts. These situations are typically multimodal, requiring the integration of linguistic auditory input with facial information from the speaker. In particular, eye gaze and visual speech provide the listener with social and linguistic information, respectively. Despite the importance of this context for an ecological study of language, research on audiovisual integration has mainly focused on the phonological level, leaving aside effects on semantic comprehension. Here we used event-related potentials (ERPs) to investigate the influence of facial dynamic information on semantic processing of connected speech. Participants were presented with either a video or a still picture of the speaker, concomitant to auditory sentences. Along three experiments, we manipulated the presence or absence of the speaker's dynamic facial features (mouth and eyes) and compared the amplitudes of the semantic N400 elicited by unexpected words. Contrary to our predictions, the N400 was not modulated by dynamic facial information; therefore, semantic processing seems to be unaffected by the speaker's gaze and visual speech. Even though, during the processing of expected words, dynamic faces elicited a long-lasting late posterior positivity compared to the static condition. This effect was significantly reduced when the mouth of the speaker was covered. Our findings may indicate an increase of attentional processing to richer communicative contexts. The present findings also demonstrate that in natural communicative face-to-face encounters, perceiving the face of a speaker in motion provides supplementary information that is taken into account by the listener, especially when auditory comprehension is non-demanding. Copyright © 2018 Elsevier Ltd. All rights reserved.

Extremal dynamics: A unifying physical explanation of fractals, 1/f noise, and activated processes

International Nuclear Information System (INIS)

Miller, S.L.; Miller, W.M.; McWhorter, P.J.

1993-01-01

The properties of physical systems whose observable properties depend upon random exceedances of critical parameters are quantitatively examined. Using extreme value theory, the dynamical behavior of this broad class of systems is derived. This class of systems can exhibit two characteristic signatures: generalized activation when far from equilibrium and noise with a characteristic power spectrum (including 1/f ) when in quasiequilibrium. Fractal structures can also arise from these systems. It is thus demonstrated that generalized activation, noise, and fractals, in some cases, are simply different manifestations of a single common dynamical principle, which is termed ''extremal dynamics.'' Examples of physical processes governed by extremal dynamics are discussed, including data loss of nonvolatile memories and dielectric breakdown

Information Factor in the Dynamics of Contemporary Geopolitical Processes

Directory of Open Access Journals (Sweden)

A. V. Vilovatykh

2014-01-01

Full Text Available Th e role of information in shaping geopolitical situation needs a greater academic attention, because the infl uence of external actors in favour of theor political preferences forms the vectors of state development. Modern world’s turbulence is based on technologies of managing social reality. It requires a principally new methodology in evaluating and forecasting geopolitical processes. Nowadays it makes sense to speak of information factor of geopolitical dynamics, which shapes a new quality of geopolitical space.

How Do Parenting Concepts Vary within and between the Families?

Science.gov (United States)

Roskam, Isabelle; Meunier, Jean Christophe

2009-01-01

How do parenting concepts vary within and between the families? The present study regards parenting as a complex family process by considering three concepts of parenting: styles, differential treatment and coparenting consistency. A main question was addressed: whether and how these parenting concepts vary within the families towards siblings or…

Tracking control of time-varying knee exoskeleton disturbed by interaction torque.

Science.gov (United States)

Li, Zhan; Ma, Wenhao; Yin, Ziguang; Guo, Hongliang

2017-11-01

Knee exoskeletons have been increasingly applied as assistive devices to help lower-extremity impaired people to make their knee joints move through providing external movement compensation. Tracking control of knee exoskeletons guided by human intentions often encounters time-varying (time-dependent) issues and the disturbance interaction torque, which may dramatically put an influence up on their dynamic behaviors. Inertial and viscous parameters of knee exoskeletons can be estimated to be time-varying due to unexpected mechanical vibrations and contact interactions. Moreover, the interaction torque produced from knee joint of wearers has an evident disturbance effect on regular motions of knee exoskeleton. All of these points can increase difficultly of accurate control of knee exoskeletons to follow desired joint angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-varying inertial and viscous coefficients disturbed by interaction torque. Such designed controller is able to make the tracking error of joint angle of knee exoskeletons exponentially converge to zero. Meanwhile, the proposed approach is robust to guarantee the tracking error bounded when the interaction torque exists. Illustrative simulation and experiment results are presented to show efficiency of the proposed controller. Additionally, comparisons with gradient dynamic (GD) approach and other methods are also presented to demonstrate efficiency and superiority of the proposed control strategy for tracking joint angle of knee exoskeleton. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Complexity Variability Assessment of Nonlinear Time-Varying Cardiovascular Control

Science.gov (United States)

Valenza, Gaetano; Citi, Luca; Garcia, Ronald G.; Taylor, Jessica Noggle; Toschi, Nicola; Barbieri, Riccardo

2017-02-01

The application of complex systems theory to physiology and medicine has provided meaningful information about the nonlinear aspects underlying the dynamics of a wide range of biological processes and their disease-related aberrations. However, no studies have investigated whether meaningful information can be extracted by quantifying second-order moments of time-varying cardiovascular complexity. To this extent, we introduce a novel mathematical framework termed complexity variability, in which the variance of instantaneous Lyapunov spectra estimated over time serves as a reference quantifier. We apply the proposed methodology to four exemplary studies involving disorders which stem from cardiology, neurology and psychiatry: Congestive Heart Failure (CHF), Major Depression Disorder (MDD), Parkinson’s Disease (PD), and Post-Traumatic Stress Disorder (PTSD) patients with insomnia under a yoga training regime. We show that complexity assessments derived from simple time-averaging are not able to discern pathology-related changes in autonomic control, and we demonstrate that between-group differences in measures of complexity variability are consistent across pathologies. Pathological states such as CHF, MDD, and PD are associated with an increased complexity variability when compared to healthy controls, whereas wellbeing derived from yoga in PTSD is associated with lower time-variance of complexity.

Dynamically slow processes in supercooled water confined between hydrophobic plates

Energy Technology Data Exchange (ETDEWEB)

Franzese, Giancarlo [Departamento de Fisica Fundamental, Universidad de Barcelona, Diagonal 647, Barcelona 08028 (Spain); Santos, Francisco de los, E-mail: gfranzese@ub.ed, E-mail: fdlsant@ugr.e [Departamento de Electromagnetismo y Fisica de la Materia, Universidad de Granada, Fuentenueva s/n, 18071 Granada (Spain)

2009-12-16

We study the dynamics of water confined between hydrophobic flat surfaces at low temperature. At different pressures, we observe different behaviors that we understand in terms of the hydrogen bond dynamics. At high pressure, the formation of the open structure of the hydrogen bond network is inhibited and the surfaces can be rapidly dried (dewetted) by formation of a large cavity with decreasing temperature. At lower pressure we observe strong non-exponential behavior of the correlation function, but with no strong increase of the correlation time. This behavior can be associated, on the one hand, to the rapid ordering of the hydrogen bonds that generates heterogeneities and, on the other hand, to the lack of a single timescale as a consequence of the cooperativity in the vicinity of the liquid-liquid critical point that characterizes the phase diagram at low temperature of the water model considered here. At very low pressures, the gradual formation of the hydrogen bond network is responsible for the large increase of the correlation time and, eventually, the dynamical arrest of the system, with a strikingly different dewetting process, characterized by the formation of many small cavities.

Dynamically slow processes in supercooled water confined between hydrophobic plates

International Nuclear Information System (INIS)

Franzese, Giancarlo; Santos, Francisco de los

2009-01-01

We study the dynamics of water confined between hydrophobic flat surfaces at low temperature. At different pressures, we observe different behaviors that we understand in terms of the hydrogen bond dynamics. At high pressure, the formation of the open structure of the hydrogen bond network is inhibited and the surfaces can be rapidly dried (dewetted) by formation of a large cavity with decreasing temperature. At lower pressure we observe strong non-exponential behavior of the correlation function, but with no strong increase of the correlation time. This behavior can be associated, on the one hand, to the rapid ordering of the hydrogen bonds that generates heterogeneities and, on the other hand, to the lack of a single timescale as a consequence of the cooperativity in the vicinity of the liquid-liquid critical point that characterizes the phase diagram at low temperature of the water model considered here. At very low pressures, the gradual formation of the hydrogen bond network is responsible for the large increase of the correlation time and, eventually, the dynamical arrest of the system, with a strikingly different dewetting process, characterized by the formation of many small cavities.

A Quasi-Dynamic Optimal Control Strategy for Non-Linear Multivariable Processes Based upon Non-Quadratic Objective Functions

Directory of Open Access Journals (Sweden)

Jens G. Balchen

1984-10-01

Full Text Available The problem of systematic derivation of a quasi-dynamic optimal control strategy for a non-linear dynamic process based upon a non-quadratic objective function is investigated. The wellknown LQG-control algorithm does not lead to an optimal solution when the process disturbances have non-zero mean. The relationships between the proposed control algorithm and LQG-control are presented. The problem of how to constrain process variables by means of 'penalty' - terms in the objective function is dealt with separately.

Effects of mobile vacancies on the dynamics of ordering and phase separation in nonconserved multicomponent systems

DEFF Research Database (Denmark)

Gilhøj, Henriette; Jeppesen, Claus; Mouritsen, Ole G.

1995-01-01

The effects of mobile vacancies on the dynamics of ordering processes and phase separation in multicomponent systems are studied via Monte Carlo simulations of a two-dimensional seven-state ferromagnetic Potts model with varying degrees of site dilution. The model displays phase equilibria...