Taking Control: Stealth Assessment of Deterministic Behaviors within a Game-Based System

ERIC Educational Resources Information Center

Snow, Erica L.; Likens, Aaron D.; Allen, Laura K.; McNamara, Danielle S.

2016-01-01

Game-based environments frequently afford students the opportunity to exert agency over their learning paths by making various choices within the environment. The combination of log data from these systems and dynamic methodologies may serve as a stealth means to assess how students behave (i.e., deterministic or random) within these learning…

Taking Control: Stealth Assessment of Deterministic Behaviors within a Game-Based System

ERIC Educational Resources Information Center

Snow, Erica L.; Likens, Aaron D.; Allen, Laura K.; McNamara, Danielle S.

2015-01-01

Game-based environments frequently afford students the opportunity to exert agency over their learning paths by making various choices within the environment. The combination of log data from these systems and dynamic methodologies may serve as a stealth means to assess how students behave (i.e., deterministic or random) within these learning…

Diversity in times of adversity: probabilistic strategies in microbial survival games.

PubMed

Wolf, Denise M; Vazirani, Vijay V; Arkin, Adam P

2005-05-21

Population diversification strategies are ubiquitous among microbes, encompassing random phase-variation (RPV) of pathogenic bacteria, viral latency as observed in some bacteriophage and HIV, and the non-genetic diversity of bacterial stress responses. Precise conditions under which these diversification strategies confer an advantage have not been well defined. We develop a model of population growth conditioned on dynamical environmental and cellular states. Transitions among cellular states, in turn, may be biased by possibly noisy readings of the environment from cellular sensors. For various types of environmental dynamics and cellular sensor capability, we apply game-theoretic analysis to derive the evolutionarily stable strategy (ESS) for an organism and determine when that strategy is diversification. We find that: (1) RPV, effecting a sort of Parrondo paradox wherein random alternations between losing strategies produce a winning strategy, is selected when transitions between different selective environments cannot be sensed, (2) optimal RPV cell switching rates are a function of environmental lifecycle asymmetries and environmental autocorrelation, (3) probabilistic diversification upon entering a new environment is selected when sensors can detect environmental transitions but have poor precision in identifying new environments, and (4) in the presence of excess additive noise, low-pass filtering is required for evolutionary stability. We show that even when RPV is not the ESS, it may minimize growth rate variance and the risk of extinction due to 'unlucky' environmental dynamics.

Dynamics of tripartite quantum entanglement and discord under a classical dephasing random telegraph noise

NASA Astrophysics Data System (ADS)

Kenfack, Lionel Tenemeza; Tchoffo, Martin; Fai, Lukong Cornelius

2017-02-01

We address the dynamics of quantum correlations, including entanglement and quantum discord of a three-qubit system interacting with a classical pure dephasing random telegraph noise (RTN) in three different physical environmental situations (independent, mixed and common environments). Two initial entangled states of the system are examined, namely the Greenberger-Horne-Zeilinger (GHZ)- and Werner (W)-type states. The classical noise is introduced as a stochastic process affecting the energy splitting of the qubits. With the help of suitable measures of tripartite entanglement (entanglement witnesses and lower bound of concurrence) and quantum discord (global quantum discord and quantum dissension), we show that the evolution of quantum correlations is not only affected by the type of the system-environment interaction but also by the input configuration of the qubits and the memory properties of the environmental noise. Indeed, depending on the memory properties of the environmental noise and the initial state considered, we find that independent, common and mixed environments can play opposite roles in preserving quantum correlations, and that the sudden death and revival phenomena or the survival of quantum correlations may occur. On the other hand, we also show that the W-type state has strong dynamics under this noise than the GHZ-type ones.

Single Particle Tracking reveals two distinct environments for CD4 receptors at the surface of living T lymphocytes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mascalchi, Patrice; Lamort, Anne Sophie; Salome, Laurence

2012-01-06

Highlights: Black-Right-Pointing-Pointer We studied the diffusion of single CD4 receptors on living lymphocytes. Black-Right-Pointing-Pointer This study reveals that CD4 receptors have either a random or confined diffusion. Black-Right-Pointing-Pointer The dynamics of unconfined CD4 receptors was accelerated by a temperature raise. Black-Right-Pointing-Pointer The dynamics of confined CD4 receptors was unchanged by a temperature raise. Black-Right-Pointing-Pointer Our results suggest the existence of two different environments for CD4 receptors. -- Abstract: We investigated the lateral diffusion of the HIV receptor CD4 at the surface of T lymphocytes at 20 Degree-Sign C and 37 Degree-Sign C by Single Particle Tracking using Quantum Dots. Wemore » found that the receptors presented two major distinct behaviors that were not equally affected by temperature changes. About half of the receptors showed a random diffusion with a diffusion coefficient increasing upon raising the temperature. The other half of the receptors was permanently or transiently confined with unchanged dynamics on raising the temperature. These observations suggest that two distinct subpopulations of CD4 receptors with different environments are present at the surface of living T lymphocytes.« less

SRG110 Stirling Generator Dynamic Simulator Vibration Test Results and Analysis Correlation

NASA Technical Reports Server (NTRS)

Suarez, Vicente J.; Lewandowski, Edward J.; Callahan, John

2006-01-01

The U.S. Department of Energy (DOE), Lockheed Martin (LM), and NASA Glenn Research Center (GRC) have been developing the Stirling Radioisotope Generator (SRG110) for use as a power system for space science missions. The launch environment enveloping potential missions results in a random input spectrum that is significantly higher than historical RPS launch levels and is a challenge for designers. Analysis presented in prior work predicted that tailoring the compliance at the generator-spacecraft interface reduced the dynamic response of the system thereby allowing higher launch load input levels and expanding the range of potential generator missions. To confirm analytical predictions, a dynamic simulator representing the generator structure, Stirling convertors and heat sources was designed and built for testing with and without a compliant interface. Finite element analysis was performed to guide the generator simulator and compliant interface design so that test modes and frequencies were representative of the SRG110 generator. This paper presents the dynamic simulator design, the test setup and methodology, test article modes and frequencies and dynamic responses, and post-test analysis results. With the compliant interface, component responses to an input environment exceeding the SRG110 qualification level spectrum were all within design allowables. Post-test analysis included finite element model tuning to match test frequencies and random response analysis using the test input spectrum. Analytical results were in good overall agreement with the test results and confirmed previous predictions that the SRG110 power system may be considered for a broad range of potential missions, including those with demanding launch environments.

SRG110 Stirling Generator Dynamic Simulator Vibration Test Results and Analysis Correlation

NASA Technical Reports Server (NTRS)

Lewandowski, Edward J.; Suarez, Vicente J.; Goodnight, Thomas W.; Callahan, John

2007-01-01

The U.S. Department of Energy (DOE), Lockheed Martin (LM), and NASA Glenn Research Center (GRC) have been developing the Stirling Radioisotope Generator (SRG110) for use as a power system for space science missions. The launch environment enveloping potential missions results in a random input spectrum that is significantly higher than historical radioisotope power system (RPS) launch levels and is a challenge for designers. Analysis presented in prior work predicted that tailoring the compliance at the generator-spacecraft interface reduced the dynamic response of the system thereby allowing higher launch load input levels and expanding the range of potential generator missions. To confirm analytical predictions, a dynamic simulator representing the generator structure, Stirling convertors and heat sources were designed and built for testing with and without a compliant interface. Finite element analysis was performed to guide the generator simulator and compliant interface design so that test modes and frequencies were representative of the SRG110 generator. This paper presents the dynamic simulator design, the test setup and methodology, test article modes and frequencies and dynamic responses, and post-test analysis results. With the compliant interface, component responses to an input environment exceeding the SRG110 qualification level spectrum were all within design allowables. Post-test analysis included finite element model tuning to match test frequencies and random response analysis using the test input spectrum. Analytical results were in good overall agreement with the test results and confirmed previous predictions that the SRG110 power system may be considered for a broad range of potential missions, including those with demanding launch environments.

Discrete stochastic charging of aggregate grains

NASA Astrophysics Data System (ADS)

Matthews, Lorin S.; Shotorban, Babak; Hyde, Truell W.

2018-05-01

Dust particles immersed in a plasma environment become charged through the collection of electrons and ions at random times, causing the dust charge to fluctuate about an equilibrium value. Small grains (with radii less than 1 μm) or grains in a tenuous plasma environment are sensitive to single additions of electrons or ions. Here we present a numerical model that allows examination of discrete stochastic charge fluctuations on the surface of aggregate grains and determines the effect of these fluctuations on the dynamics of grain aggregation. We show that the mean and standard deviation of charge on aggregate grains follow the same trends as those predicted for spheres having an equivalent radius, though aggregates exhibit larger variations from the predicted values. In some plasma environments, these charge fluctuations occur on timescales which are relevant for dynamics of aggregate growth. Coupled dynamics and charging models show that charge fluctuations tend to produce aggregates which are much more linear or filamentary than aggregates formed in an environment where the charge is stationary.

Structured crowding and its effects on enzyme catalysis.

PubMed

Ma, Buyong; Nussinov, Ruth

2013-01-01

Macromolecular crowding decreases the diffusion rate, shifts the equilibrium of protein-protein and protein-substrate interactions, and changes protein conformational dynamics. Collectively, these effects contribute to enzyme catalysis. Here we describe how crowding may bias the conformational change and dynamics of enzyme populations and in this way affect catalysis. Crowding effects have been studied using artificial crowding agents and in vivo-like environments. These studies revealed a correlation between protein dynamics and function in the crowded environment. We suggest that crowded environments be classified into uniform crowding and structured crowding. Uniform crowding represents random crowding conditions created by synthetic particles with a narrow size distribution. Structured crowding refers to the highly coordinated cellular environment, where proteins and other macromolecules are clustered and organized. In structured crowded environments the perturbation of protein thermal stability may be lower; however, it may still be able to modulate functions effectively and dynamically. Dynamic, allosteric enzymes could be more sensitive to cellular perturbations if their free energy landscape is flatter around the native state; on the other hand, if their free energy landscape is rougher, with high kinetic barriers separating deep minima, they could be more robust. Above all, cells are structured; and this holds both for the cytosol and for the membrane environment. The crowded environment is organized, which limits the search, and the crowders are not necessarily inert. More likely, they too transmit allosteric effects, and as such play important functional roles. Overall, structured cellular crowding may lead to higher enzyme efficiency and specificity.

Evolution of regulatory networks towards adaptability and stability in a changing environment

NASA Astrophysics Data System (ADS)

Lee, Deok-Sun

2014-11-01

Diverse biological networks exhibit universal features distinguished from those of random networks, calling much attention to their origins and implications. Here we propose a minimal evolution model of Boolean regulatory networks, which evolve by selectively rewiring links towards enhancing adaptability to a changing environment and stability against dynamical perturbations. We find that sparse and heterogeneous connectivity patterns emerge, which show qualitative agreement with real transcriptional regulatory networks and metabolic networks. The characteristic scaling behavior of stability reflects the balance between robustness and flexibility. The scaling of fluctuation in the perturbation spread shows a dynamic crossover, which is analyzed by investigating separately the stochasticity of internal dynamics and the network structure differences depending on the evolution pathways. Our study delineates how the ambivalent pressure of evolution shapes biological networks, which can be helpful for studying general complex systems interacting with environments.

A dynamic programming-based particle swarm optimization algorithm for an inventory management problem under uncertainty

NASA Astrophysics Data System (ADS)

Xu, Jiuping; Zeng, Ziqiang; Han, Bernard; Lei, Xiao

2013-07-01

This article presents a dynamic programming-based particle swarm optimization (DP-based PSO) algorithm for solving an inventory management problem for large-scale construction projects under a fuzzy random environment. By taking into account the purchasing behaviour and strategy under rules of international bidding, a multi-objective fuzzy random dynamic programming model is constructed. To deal with the uncertainties, a hybrid crisp approach is used to transform fuzzy random parameters into fuzzy variables that are subsequently defuzzified by using an expected value operator with optimistic-pessimistic index. The iterative nature of the authors' model motivates them to develop a DP-based PSO algorithm. More specifically, their approach treats the state variables as hidden parameters. This in turn eliminates many redundant feasibility checks during initialization and particle updates at each iteration. Results and sensitivity analysis are presented to highlight the performance of the authors' optimization method, which is very effective as compared to the standard PSO algorithm.

Comparison of different models of motion in a crowded environment: a Monte Carlo study.

PubMed

Polanowski, P; Sikorski, A

2017-02-22

In this paper we investigate the motion of molecules in crowded environments for two dramatically different types of molecular transport. The first type is realized by the dynamic lattice liquid model, which is based on a cooperative movement concept and thus, the motion of molecules is highly correlated. The second one corresponds to a so-called motion of a single agent where the motion of molecules is considered as a random walk without any correlation with other moving elements. The crowded environments are modeled as a two-dimensional triangular lattice with fixed impenetrable obstacles. Our simulation results indicate that the type of transport has an impact on the dynamics of the system, the percolation threshold, critical exponents, and on molecules' trajectories.

Scaling Limit of Symmetric Random Walk in High-Contrast Periodic Environment

NASA Astrophysics Data System (ADS)

Piatnitski, A.; Zhizhina, E.

2017-11-01

The paper deals with the asymptotic properties of a symmetric random walk in a high contrast periodic medium in Z^d, d≥1. From the existing homogenization results it follows that under diffusive scaling the limit behaviour of this random walk need not be Markovian. The goal of this work is to show that if in addition to the coordinate of the random walk in Z^d we introduce an extra variable that characterizes the position of the random walk inside the period then the limit dynamics of this two-component process is Markov. We describe the limit process and observe that the components of the limit process are coupled. We also prove the convergence in the path space for the said random walk.

Diffusion, subdiffusion, and localization of active colloids in random post lattices

NASA Astrophysics Data System (ADS)

Morin, Alexandre; Lopes Cardozo, David; Chikkadi, Vijayakumar; Bartolo, Denis

2017-10-01

Combining experiments and theory, we address the dynamics of self-propelled particles in crowded environments. We first demonstrate that motile colloids cruising at constant speed through random lattices undergo a smooth transition from diffusive to subdiffusive to localized dynamics upon increasing the obstacle density. We then elucidate the nature of these transitions by performing extensive simulations constructed from a detailed analysis of the colloid-obstacle interactions. We evidence that repulsion at a distance and hard-core interactions both contribute to slowing down the long-time diffusion of the colloids. In contrast, the localization transition stems solely from excluded-volume interactions and occurs at the void-percolation threshold. Within this critical scenario, equivalent to that of the random Lorentz gas, genuine asymptotic subdiffusion is found only at the critical density where the motile particles explore a fractal maze.

Probalistic Finite Elements (PFEM) structural dynamics and fracture mechanics

NASA Technical Reports Server (NTRS)

Liu, Wing-Kam; Belytschko, Ted; Mani, A.; Besterfield, G.

1989-01-01

The purpose of this work is to develop computationally efficient methodologies for assessing the effects of randomness in loads, material properties, and other aspects of a problem by a finite element analysis. The resulting group of methods is called probabilistic finite elements (PFEM). The overall objective of this work is to develop methodologies whereby the lifetime of a component can be predicted, accounting for the variability in the material and geometry of the component, the loads, and other aspects of the environment; and the range of response expected in a particular scenario can be presented to the analyst in addition to the response itself. Emphasis has been placed on methods which are not statistical in character; that is, they do not involve Monte Carlo simulations. The reason for this choice of direction is that Monte Carlo simulations of complex nonlinear response require a tremendous amount of computation. The focus of efforts so far has been on nonlinear structural dynamics. However, in the continuation of this project, emphasis will be shifted to probabilistic fracture mechanics so that the effect of randomness in crack geometry and material properties can be studied interactively with the effect of random load and environment.

Evolutionary stability concepts in a stochastic environment

NASA Astrophysics Data System (ADS)

Zheng, Xiu-Deng; Li, Cong; Lessard, Sabin; Tao, Yi

2017-09-01

Over the past 30 years, evolutionary game theory and the concept of an evolutionarily stable strategy have been not only extensively developed and successfully applied to explain the evolution of animal behaviors, but also widely used in economics and social sciences. Nonetheless, the stochastic dynamical properties of evolutionary games in randomly fluctuating environments are still unclear. In this study, we investigate conditions for stochastic local stability of fixation states and constant interior equilibria in a two-phenotype model with random payoffs following pairwise interactions. Based on this model, we develop the concepts of stochastic evolutionary stability (SES) and stochastic convergence stability (SCS). We show that the condition for a pure strategy to be SES and SCS is more stringent than in a constant environment, while the condition for a constant mixed strategy to be SES is less stringent than the condition to be SCS, which is less stringent than the condition in a constant environment.

Random Walk on a Perturbation of the Infinitely-Fast Mixing Interchange Process

NASA Astrophysics Data System (ADS)

Salvi, Michele; Simenhaus, François

2018-05-01

We consider a random walk in dimension d≥ 1 in a dynamic random environment evolving as an interchange process with rate γ >0. We prove that, if we choose γ large enough, almost surely the empirical velocity of the walker X_t/t eventually lies in an arbitrary small ball around the annealed drift. This statement is thus a perturbation of the case γ =+∞ where the environment is refreshed between each step of the walker. We extend three-way part of the results of Huveneers and Simenhaus (Electron J Probab 20(105):42, 2015), where the environment was given by the 1-dimensional exclusion process: (i) We deal with any dimension d≥1; (ii) We treat the much more general interchange process, where each particle carries a transition vector chosen according to an arbitrary law μ ; (iii) We show that X_t/t is not only in the same direction of the annealed drift, but that it is also close to it.

Long-range epidemic spreading in a random environment.

PubMed

Juhász, Róbert; Kovács, István A; Iglói, Ferenc

2015-03-01

Modeling long-range epidemic spreading in a random environment, we consider a quenched, disordered, d-dimensional contact process with infection rates decaying with distance as 1/rd+σ. We study the dynamical behavior of the model at and below the epidemic threshold by a variant of the strong-disorder renormalization-group method and by Monte Carlo simulations in one and two spatial dimensions. Starting from a single infected site, the average survival probability is found to decay as P(t)∼t-d/z up to multiplicative logarithmic corrections. Below the epidemic threshold, a Griffiths phase emerges, where the dynamical exponent z varies continuously with the control parameter and tends to zc=d+σ as the threshold is approached. At the threshold, the spatial extension of the infected cluster (in surviving trials) is found to grow as R(t)∼t1/zc with a multiplicative logarithmic correction and the average number of infected sites in surviving trials is found to increase as Ns(t)∼(lnt)χ with χ=2 in one dimension.

Model for disease dynamics of a waterborne pathogen on a random network.

PubMed

Li, Meili; Ma, Junling; van den Driessche, P

2015-10-01

A network epidemic SIWR model for cholera and other diseases that can be transmitted via the environment is developed and analyzed. The person-to-person contacts are modeled by a random contact network, and the contagious environment is modeled by an external node that connects to every individual. The model is adapted from the Miller network SIR model, and in the homogeneous mixing limit becomes the Tien and Earn deterministic cholera model without births and deaths. The dynamics of our model shows excellent agreement with stochastic simulations. The basic reproduction number [Formula: see text] is computed, and on a Poisson network shown to be the sum of the basic reproduction numbers of the person-to-person and person-to-water-to-person transmission pathways. However, on other networks, [Formula: see text] depends nonlinearly on the transmission along the two pathways. Type reproduction numbers are computed and quantify measures to control the disease. Equations giving the final epidemic size are obtained.

Taking chances and making mistakes: non-genetic phenotypic heterogeneity and its consequences for surviving in dynamic environments

PubMed Central

van Boxtel, Coco; van Heerden, Johan H.; Nordholt, Niclas; Schmidt, Phillipp

2017-01-01

Natural selection has shaped the strategies for survival and growth of microorganisms. The success of microorganisms depends not only on slow evolutionary tuning but also on the ability to adapt to unpredictable changes in their environment. In principle, adaptive strategies range from purely deterministic mechanisms to those that exploit the randomness intrinsic to many cellular and molecular processes. Depending on the environment and selective pressures, particular strategies can lie somewhere along this continuum. In recent years, non-genetic cell-to-cell differences have received a lot of attention, not least because of their potential impact on the ability of microbial populations to survive in dynamic environments. Using several examples, we describe the origins of spontaneous and induced mechanisms of phenotypic adaptation. We identify some of the commonalities of these examples and consider the potential role of chance and constraints in microbial phenotypic adaptation. PMID:28701503

Modeling Invasion Dynamics with Spatial Random-Fitness Due to Micro-Environment

PubMed Central

Manem, V. S. K.; Kaveh, K.; Kohandel, M.; Sivaloganathan, S.

2015-01-01

Numerous experimental studies have demonstrated that the microenvironment is a key regulator influencing the proliferative and migrative potentials of species. Spatial and temporal disturbances lead to adverse and hazardous microenvironments for cellular systems that is reflected in the phenotypic heterogeneity within the system. In this paper, we study the effect of microenvironment on the invasive capability of species, or mutants, on structured grids (in particular, square lattices) under the influence of site-dependent random proliferation in addition to a migration potential. We discuss both continuous and discrete fitness distributions. Our results suggest that the invasion probability is negatively correlated with the variance of fitness distribution of mutants (for both advantageous and neutral mutants) in the absence of migration of both types of cells. A similar behaviour is observed even in the presence of a random fitness distribution of host cells in the system with neutral fitness rate. In the case of a bimodal distribution, we observe zero invasion probability until the system reaches a (specific) proportion of advantageous phenotypes. Also, we find that the migrative potential amplifies the invasion probability as the variance of fitness of mutants increases in the system, which is the exact opposite in the absence of migration. Our computational framework captures the harsh microenvironmental conditions through quenched random fitness distributions and migration of cells, and our analysis shows that they play an important role in the invasion dynamics of several biological systems such as bacterial micro-habitats, epithelial dysplasia, and metastasis. We believe that our results may lead to more experimental studies, which can in turn provide further insights into the role and impact of heterogeneous environments on invasion dynamics. PMID:26509572

Modeling species-abundance relationships in multi-species collections

USGS Publications Warehouse

Peng, S.; Yin, Z.; Ren, H.; Guo, Q.

2003-01-01

Species-abundance relationship is one of the most fundamental aspects of community ecology. Since Motomura first developed the geometric series model to describe the feature of community structure, ecologists have developed many other models to fit the species-abundance data in communities. These models can be classified into empirical and theoretical ones, including (1) statistical models, i.e., negative binomial distribution (and its extension), log-series distribution (and its extension), geometric distribution, lognormal distribution, Poisson-lognormal distribution, (2) niche models, i.e., geometric series, broken stick, overlapping niche, particulate niche, random assortment, dominance pre-emption, dominance decay, random fraction, weighted random fraction, composite niche, Zipf or Zipf-Mandelbrot model, and (3) dynamic models describing community dynamics and restrictive function of environment on community. These models have different characteristics and fit species-abundance data in various communities or collections. Among them, log-series distribution, lognormal distribution, geometric series, and broken stick model have been most widely used.

Navigation of autonomous vehicles for oil spill cleaning in dynamic and uncertain environments

NASA Astrophysics Data System (ADS)

Jin, Xin; Ray, Asok

2014-04-01

In the context of oil spill cleaning by autonomous vehicles in dynamic and uncertain environments, this paper presents a multi-resolution algorithm that seamlessly integrates the concepts of local navigation and global navigation based on the sensory information; the objective here is to enable adaptive decision making and online replanning of vehicle paths. The proposed algorithm provides a complete coverage of the search area for clean-up of the oil spills and does not suffer from the problem of having local minima, which is commonly encountered in potential-field-based methods. The efficacy of the algorithm is tested on a high-fidelity player/stage simulator for oil spill cleaning in a harbour, where the underlying oil weathering process is modelled as 2D random-walk particle tracking. A preliminary version of this paper was presented by X. Jin and A. Ray as 'Coverage Control of Autonomous Vehicles for Oil Spill Cleaning in Dynamic and Uncertain Environments', Proceedings of the American Control Conference, Washington, DC, June 2013, pp. 2600-2605.

Heterogeneous Coordination Environments in Lithium-Neutralized Ionomers Identified Using 1H and 7Li MAS NMR

PubMed Central

Alam, Todd M.; Jenkins, Janelle E.; Bolintineanu, Dan S.; Stevens, Mark J.; Frischknecht, Amalie L.; Buitrago, C. Francisco; Winey, Karen I.; Opper, Kathleen L.; Wagener, Kenneth B.

2012-01-01

The carboxylic acid proton and the lithium coordination environments for precise and random Li-neutralized polyethylene acrylic acid P(E-AA) ionomers were explored using high speed solid-state 1H and 7Li MAS NMR. While the 7Li NMR revealed only a single Li coordination environment, the chemical shift temperature variation was dependent on the precise or random nature of the P(E-AA) ionomer. The 1H MAS NMR revealed two different carboxylic acid proton environments in these materials. By utilizing 1H-7Li rotational echo double resonance (REDOR) MAS NMR experiments, it was demonstrated that the proton environments correspond to different average 1H-7Li distances, with the majority of the protonated carboxylic acids having a close through space contact with the Li. Molecular dynamics simulations suggest that the shortest 1H-7Li distance corresponds to un-neutralized carboxylic acids directly involved in the coordination environment of Li clusters. These solid-state NMR results show that heterogeneous structural motifs need to be included when developing descriptions of these ionomer materials.

Optimal Control of a Surge-Mode WEC in Random Waves

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chertok, Allan; Ceberio, Olivier; Staby, Bill

2016-08-30

The objective of this project was to develop one or more real-time feedback and feed-forward (MPC) control algorithms for an Oscillating Surge Wave Converter (OSWC) developed by RME called SurgeWEC™ that leverages recent innovations in wave energy converter (WEC) control theory to maximize power production in random wave environments. The control algorithms synthesized innovations in dynamic programming and nonlinear wave dynamics using anticipatory wave sensors and localized sensor measurements; e.g. position and velocity of the WEC Power Take Off (PTO), with predictive wave forecasting data. The result was an advanced control system that uses feedback or feed-forward data from anmore » array of sensor channels comprised of both localized and deployed sensors fused into a single decision process that optimally compensates for uncertainties in the system dynamics, wave forecasts, and sensor measurement errors.« less

Random-order fractional bistable system and its stochastic resonance

NASA Astrophysics Data System (ADS)

Gao, Shilong; Zhang, Li; Liu, Hui; Kan, Bixia

2017-01-01

In this paper, the diffusion motion of Brownian particles in a viscous liquid suffering from stochastic fluctuations of the external environment is modeled as a random-order fractional bistable equation, and as a typical nonlinear dynamic behavior, the stochastic resonance phenomena in this system are investigated. At first, the derivation process of the random-order fractional bistable system is given. In particular, the random-power-law memory is deeply discussed to obtain the physical interpretation of the random-order fractional derivative. Secondly, the stochastic resonance evoked by random-order and external periodic force is mainly studied by numerical simulation. In particular, the frequency shifting phenomena of the periodical output are observed in SR induced by the excitation of the random order. Finally, the stochastic resonance of the system under the double stochastic excitations of the random order and the internal color noise is also investigated.

Event detection and localization for small mobile robots using reservoir computing.

PubMed

Antonelo, E A; Schrauwen, B; Stroobandt, D

2008-08-01

Reservoir Computing (RC) techniques use a fixed (usually randomly created) recurrent neural network, or more generally any dynamic system, which operates at the edge of stability, where only a linear static readout output layer is trained by standard linear regression methods. In this work, RC is used for detecting complex events in autonomous robot navigation. This can be extended to robot localization tasks which are solely based on a few low-range, high-noise sensory data. The robot thus builds an implicit map of the environment (after learning) that is used for efficient localization by simply processing the input stream of distance sensors. These techniques are demonstrated in both a simple simulation environment and in the physically realistic Webots simulation of the commercially available e-puck robot, using several complex and even dynamic environments.

Modelling nematode movement using time-fractional dynamics.

PubMed

Hapca, Simona; Crawford, John W; MacMillan, Keith; Wilson, Mike J; Young, Iain M

2007-09-07

We use a correlated random walk model in two dimensions to simulate the movement of the slug parasitic nematode Phasmarhabditis hermaphrodita in homogeneous environments. The model incorporates the observed statistical distributions of turning angle and speed derived from time-lapse studies of individual nematode trails. We identify strong temporal correlations between the turning angles and speed that preclude the case of a simple random walk in which successive steps are independent. These correlated random walks are appropriately modelled using an anomalous diffusion model, more precisely using a fractional sub-diffusion model for which the associated stochastic process is characterised by strong memory effects in the probability density function.

Nonequilibrium Statistical Mechanics in One Dimension

NASA Astrophysics Data System (ADS)

Privman, Vladimir

2005-08-01

Part I. Reaction-Diffusion Systems and Models of Catalysis; 1. Scaling theories of diffusion-controlled and ballistically-controlled bimolecular reactions S. Redner; 2. The coalescence process, A+A->A, and the method of interparticle distribution functions D. ben-Avraham; 3. Critical phenomena at absorbing states R. Dickman; Part II. Kinetic Ising Models; 4. Kinetic ising models with competing dynamics: mappings, correlations, steady states, and phase transitions Z. Racz; 5. Glauber dynamics of the ising model N. Ito; 6. 1D Kinetic ising models at low temperatures - critical dynamics, domain growth, and freezing S. Cornell; Part III. Ordering, Coagulation, Phase Separation; 7. Phase-ordering dynamics in one dimension A. J. Bray; 8. Phase separation, cluster growth, and reaction kinetics in models with synchronous dynamics V. Privman; 9. Stochastic models of aggregation with injection H. Takayasu and M. Takayasu; Part IV. Random Sequential Adsorption and Relaxation Processes; 10. Random and cooperative sequential adsorption: exactly solvable problems on 1D lattices, continuum limits, and 2D extensions J. W. Evans; 11. Lattice models of irreversible adsorption and diffusion P. Nielaba; 12. Deposition-evaporation dynamics: jamming, conservation laws and dynamical diversity M. Barma; Part V. Fluctuations In Particle and Surface Systems; 13. Microscopic models of macroscopic shocks S. A. Janowsky and J. L. Lebowitz; 14. The asymmetric exclusion model: exact results through a matrix approach B. Derrida and M. R. Evans; 15. Nonequilibrium surface dynamics with volume conservation J. Krug; 16. Directed walks models of polymers and wetting J. Yeomans; Part VI. Diffusion and Transport In One Dimension; 17. Some recent exact solutions of the Fokker-Planck equation H. L. Frisch; 18. Random walks, resonance, and ratchets C. R. Doering and T. C. Elston; 19. One-dimensional random walks in random environment K. Ziegler; Part VII. Experimental Results; 20. Diffusion-limited exciton kinetics in one-dimensional systems R. Kroon and R. Sprik; 21. Experimental investigations of molecular and excitonic elementary reaction kinetics in one-dimensional systems R. Kopelman and A. L. Lin; 22. Luminescence quenching as a probe of particle distribution S. H. Bossmann and L. S. Schulman; Index.

Empirical evaluation of sufficient similarity in dose-response for environmental risk assessment of a mixture of 11 pyrethroids.

EPA Science Inventory

Chemical mixtures in the environment are often the result of a dynamic process. When dose-response data are available on random samples throughout the process, equivalence testing can be used to determine whether the mixtures are sufficiently similar based on a pre-specified biol...

Random density matrices versus random evolution of open system

NASA Astrophysics Data System (ADS)

Pineda, Carlos; Seligman, Thomas H.

2015-10-01

We present and compare two families of ensembles of random density matrices. The first, static ensemble, is obtained foliating an unbiased ensemble of density matrices. As criterion we use fixed purity as the simplest example of a useful convex function. The second, dynamic ensemble, is inspired in random matrix models for decoherence where one evolves a separable pure state with a random Hamiltonian until a given value of purity in the central system is achieved. Several families of Hamiltonians, adequate for different physical situations, are studied. We focus on a two qubit central system, and obtain exact expressions for the static case. The ensemble displays a peak around Werner-like states, modulated by nodes on the degeneracies of the density matrices. For moderate and strong interactions good agreement between the static and the dynamic ensembles is found. Even in a model where one qubit does not interact with the environment excellent agreement is found, but only if there is maximal entanglement with the interacting one. The discussion is started recalling similar considerations for scattering theory. At the end, we comment on the reach of the results for other convex functions of the density matrix, and exemplify the situation with the von Neumann entropy.

Unfair and Anomalous Evolutionary Dynamics from Fluctuating Payoffs.

PubMed

Stollmeier, Frank; Nagler, Jan

2018-02-02

Evolution occurs in populations of reproducing individuals. Reproduction depends on the payoff a strategy receives. The payoff depends on the environment that may change over time, on intrinsic uncertainties, and on other sources of randomness. These temporal variations in the payoffs can affect which traits evolve. Understanding evolutionary game dynamics that are affected by varying payoffs remains difficult. Here we study the impact of arbitrary amplitudes and covariances of temporally varying payoffs on the dynamics. The evolutionary dynamics may be "unfair," meaning that, on average, two coexisting strategies may persistently receive different payoffs. This mechanism can induce an anomalous coexistence of cooperators and defectors in the prisoner's dilemma, and an unexpected selection reversal in the hawk-dove game.

Unfair and Anomalous Evolutionary Dynamics from Fluctuating Payoffs

NASA Astrophysics Data System (ADS)

Stollmeier, Frank; Nagler, Jan

2018-02-01

Evolution occurs in populations of reproducing individuals. Reproduction depends on the payoff a strategy receives. The payoff depends on the environment that may change over time, on intrinsic uncertainties, and on other sources of randomness. These temporal variations in the payoffs can affect which traits evolve. Understanding evolutionary game dynamics that are affected by varying payoffs remains difficult. Here we study the impact of arbitrary amplitudes and covariances of temporally varying payoffs on the dynamics. The evolutionary dynamics may be "unfair," meaning that, on average, two coexisting strategies may persistently receive different payoffs. This mechanism can induce an anomalous coexistence of cooperators and defectors in the prisoner's dilemma, and an unexpected selection reversal in the hawk-dove game.

Disruption of an Aligned Dendritic Network by Bubbles During Re-Melting in a Microgravity Environment

NASA Technical Reports Server (NTRS)

Grugel, Richard N.; Brush, Lucien N.; Anilkumar, Amrutur V.

2012-01-01

The quiescent Microgravity environment can be quite dynamic. Thermocapillary flow about "large" static bubbles on the order of 1mm in diameter was easily observed by following smaller tracer bubbles. The bubble induced flow was seen to disrupt a large dendritic array, effectively distributing free branches about the solid-liquid interface. "Small" dynamic bubbles were observed to travel at fast velocities through the mushy zone with the implication of bringing/detaching/redistributing dendrite arm fragments at the solid-liquid interface. Large and small bubbles effectively re-orient/re-distribute dendrite branches/arms/fragments at the solid liquid interface. Subsequent initiation of controlled directional solidification results in growth of dendrites having random orientations which significantly compromises the desired science.

Decoherence and tripartite entanglement dynamics in the presence of Gaussian and non-Gaussian classical noise

NASA Astrophysics Data System (ADS)

Kenfack, Lionel Tenemeza; Tchoffo, Martin; Fai, Lukong Cornelius; Fouokeng, Georges Collince

2017-04-01

We address the entanglement dynamics of a three-qubit system interacting with a classical fluctuating environment described either by a Gaussian or non-Gaussian noise in three different configurations namely: common, independent and mixed environments. Specifically, we focus on the Ornstein-Uhlenbeck (OU) noise and the random telegraph noise (RTN). The qubits are prepared in a state composed of a Greenberger-Horne-Zeilinger (GHZ) and a W state. With the help of the tripartite negativity, we show that the entanglement evolution is not only affected by the type of system-environment coupling but also by the kind and the memory properties of the considered noise. We also compared the dynamics induced by the two kinds of noise and we find that even if both noises have a Lorentzian spectrum, the effects of the OU noise cannot be in a simple way deduced from those of the RTN and vice-versa. In addition, we show that the entanglement can be indefinitely preserved when the qubits are coupled to the environmental noise in a common environment (CE). Finally, the presence or absence of peculiar phenomena such as entanglement revivals (ER) and entanglement sudden death (ESD) is observed.

Distinguishing signatures of determinism and stochasticity in spiking complex systems

PubMed Central

Aragoneses, Andrés; Rubido, Nicolás; Tiana-Alsina, Jordi; Torrent, M. C.; Masoller, Cristina

2013-01-01

We describe a method to infer signatures of determinism and stochasticity in the sequence of apparently random intensity dropouts emitted by a semiconductor laser with optical feedback. The method uses ordinal time-series analysis to classify experimental data of inter-dropout-intervals (IDIs) in two categories that display statistically significant different features. Despite the apparent randomness of the dropout events, one IDI category is consistent with waiting times in a resting state until noise triggers a dropout, and the other is consistent with dropouts occurring during the return to the resting state, which have a clear deterministic component. The method we describe can be a powerful tool for inferring signatures of determinism in the dynamics of complex systems in noisy environments, at an event-level description of their dynamics.

A Stochastic Simulation Framework for the Prediction of Strategic Noise Mapping and Occupational Noise Exposure Using the Random Walk Approach

PubMed Central

Haron, Zaiton; Bakar, Suhaimi Abu; Dimon, Mohamad Ngasri

2015-01-01

Strategic noise mapping provides important information for noise impact assessment and noise abatement. However, producing reliable strategic noise mapping in a dynamic, complex working environment is difficult. This study proposes the implementation of the random walk approach as a new stochastic technique to simulate noise mapping and to predict the noise exposure level in a workplace. A stochastic simulation framework and software, namely RW-eNMS, were developed to facilitate the random walk approach in noise mapping prediction. This framework considers the randomness and complexity of machinery operation and noise emission levels. Also, it assesses the impact of noise on the workers and the surrounding environment. For data validation, three case studies were conducted to check the accuracy of the prediction data and to determine the efficiency and effectiveness of this approach. The results showed high accuracy of prediction results together with a majority of absolute differences of less than 2 dBA; also, the predicted noise doses were mostly in the range of measurement. Therefore, the random walk approach was effective in dealing with environmental noises. It could predict strategic noise mapping to facilitate noise monitoring and noise control in the workplaces. PMID:25875019

Vibration Isolation for Launch of a Space Station Orbital Replacement Unit

NASA Technical Reports Server (NTRS)

Maly, Joseph R.; Sills, Joel W., Jr.; Pendleton, Scott C.; James, George H., III; Mimovich, Mark

2004-01-01

Delivery of Orbital Replacement Units (ORUs) to on-orbit destinations such a the International Space Station (ISS) and the Hubble Space Telescope is an important component of the space program. ORUs are integrated on orbit with space assets to maintain and upgrade functionality. For ORUs comprised of sensitive equipment, the dynamic launch environment drives design and testing requirements, and high frequency random vibrations are generally the cause for failure. Vibration isolation can mitigate the structure-borne vibration environment during launch, and hardware has been developed that can provide a reduced environment for current and future launch environments. Random vibration testing of one ORU to equivalent Space Shuttle launch levels revealed that its qualification and acceptance requirements were exceeded. An isolation system was designed to mitigate the structure-borne launch vibration environment. To protect this ORU, the random vibration levels at 50 Hz must be attenuated by a factor of two and those at higher frequencies even more. Design load factors for Shuttle launch are high, so a metallic load path is needed to maintain strength margins. Isolation system design was performed using a finite element model of the ORU on its carrier with representative disturbance inputs. Iterations on the modelled to an optimized design based on flight proven SoftRide MultiFlex isolators. Component testing has been performed on prototype isolators to validate analytical predictions.

Entanglement dynamics in random media

NASA Astrophysics Data System (ADS)

Menezes, G.; Svaiter, N. F.; Zarro, C. A. D.

2017-12-01

We study how the entanglement dynamics between two-level atoms is impacted by random fluctuations of the light cone. In our model the two-atom system is envisaged as an open system coupled with an electromagnetic field in the vacuum state. We employ the quantum master equation in the Born-Markov approximation in order to describe the completely positive time evolution of the atomic system. We restrict our investigations to the situation in which the atoms are coupled individually to two spatially separated cavities, one of which displays the emergence of light-cone fluctuations. In such a disordered cavity, we assume that the coefficients of the Klein-Gordon equation are random functions of the spatial coordinates. The disordered medium is modeled by a centered, stationary, and Gaussian process. We demonstrate that disorder has the effect of slowing down the entanglement decay. We conjecture that in a strong-disorder environment the mean life of entangled states can be enhanced in such a way as to almost completely suppress quantum nonlocal decoherence.

Network Randomization and Dynamic Defense for Critical Infrastructure Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chavez, Adrian R.; Martin, Mitchell Tyler; Hamlet, Jason

2015-04-01

Critical Infrastructure control systems continue to foster predictable communication paths, static configurations, and unpatched systems that allow easy access to our nation's most critical assets. This makes them attractive targets for cyber intrusion. We seek to address these attack vectors by automatically randomizing network settings, randomizing applications on the end devices themselves, and dynamically defending these systems against active attacks. Applying these protective measures will convert control systems into moving targets that proactively defend themselves against attack. Sandia National Laboratories has led this effort by gathering operational and technical requirements from Tennessee Valley Authority (TVA) and performing research and developmentmore » to create a proof-of-concept solution. Our proof-of-concept has been tested in a laboratory environment with over 300 nodes. The vision of this project is to enhance control system security by converting existing control systems into moving targets and building these security measures into future systems while meeting the unique constraints that control systems face.« less

Incorporating a Wheeled Vehicle Model in a New Monocular Visual Odometry Algorithm for Dynamic Outdoor Environments

PubMed Central

Jiang, Yanhua; Xiong, Guangming; Chen, Huiyan; Lee, Dah-Jye

2014-01-01

This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, which are the two most important parameters that describe the motion of a wheeled vehicle. Additionally, the pitch angle is also considered since the planar-motion hypothesis often fails due to the dynamic characteristics of wheel suspensions and tires in real-world environments. Linearization is used to calculate a closed-form solution of the motion parameters that works as a hypothesis generator in a RAndom SAmple Consensus (RANSAC) scheme to reduce the complexity in solving equations involving trigonometric. All inliers found are used to refine the winner solution through minimizing the reprojection error. Finally, the algorithm is applied to real-time on-board visual localization applications. Its performance is evaluated by comparing against the state-of-the-art monocular visual odometry methods using both synthetic data and publicly available datasets over several kilometers in dynamic outdoor environments. PMID:25256109

Active dynamics of colloidal particles in time-varying laser speckle patterns

PubMed Central

Bianchi, Silvio; Pruner, Riccardo; Vizsnyiczai, Gaszton; Maggi, Claudio; Di Leonardo, Roberto

2016-01-01

Colloidal particles immersed in a dynamic speckle pattern experience an optical force that fluctuates both in space and time. The resulting dynamics presents many interesting analogies with a broad class of non-equilibrium systems like: active colloids, self propelled microorganisms, transport in dynamical intracellular environments. Here we show that the use of a spatial light modulator allows to generate light fields that fluctuate with controllable space and time correlations and a prescribed average intensity profile. In particular we generate ring-shaped random patterns that can confine a colloidal particle over a quasi one-dimensional random energy landscape. We find a mean square displacement that is diffusive at both short and long times, while a superdiffusive or subdiffusive behavior is observed at intermediate times depending on the value of the speckles correlation time. We propose two alternative models for the mean square displacement in the two limiting cases of a short or long speckles correlation time. A simple interpolation formula is shown to account for the full phenomenology observed in the mean square displacement across the entire range from fast to slow fluctuating speckles. PMID:27279540

Polymer Dynamics from Synthetic to Biological Macromolecules

NASA Astrophysics Data System (ADS)

Richter, D.; Niedzwiedz, K.; Monkenbusch, M.; Wischnewski, A.; Biehl, R.; Hoffmann, B.; Merkel, R.

2008-02-01

High resolution neutron scattering together with a meticulous choice of the contrast conditions allows to access the large scale dynamics of soft materials including biological molecules in space and time. In this contribution we present two examples. One from the world of synthetic polymers, the other from biomolecules. First, we will address the peculiar dynamics of miscible polymer blends with very different component glass transition temperatures. Polymethylmetacrylate (PMMA), polyethyleneoxide (PEO) are perfectly miscible but exhibit a difference in the glass transition temperature by 200 K. We present quasielastic neutron scattering investigations on the dynamics of the fast component in the range from angströms to nanometers over a time frame of five orders of magnitude. All data may be consistently described in terms of a Rouse model with random friction, reflecting the random environment imposed by the nearly frozen PMMA matrix on the fast mobile PEO. In the second part we touch on some new developments relating to large scale internal dynamics of proteins by neutron spin echo. We will report results of some pioneering studies which show the feasibility of such experiments on large scale protein motion which will most likely initiate further studies in the future.

Multiagent Systems Based Modeling and Implementation of Dynamic Energy Management of Smart Microgrid Using MACSimJX.

PubMed

Raju, Leo; Milton, R S; Mahadevan, Senthilkumaran

The objective of this paper is implementation of multiagent system (MAS) for the advanced distributed energy management and demand side management of a solar microgrid. Initially, Java agent development environment (JADE) frame work is used to implement MAS based dynamic energy management of solar microgrid. Due to unstable nature of MATLAB, when dealing with multithreading environment, MAS operating in JADE is linked with the MATLAB using a middle ware called Multiagent Control Using Simulink with Jade Extension (MACSimJX). MACSimJX allows the solar microgrid components designed with MATLAB to be controlled by the corresponding agents of MAS. The microgrid environment variables are captured through sensors and given to agents through MATLAB/Simulink and after the agent operations in JADE, the results are given to the actuators through MATLAB for the implementation of dynamic operation in solar microgrid. MAS operating in JADE maximizes operational efficiency of solar microgrid by decentralized approach and increase in runtime efficiency due to JADE. Autonomous demand side management is implemented for optimizing the power exchange between main grid and microgrid with intermittent nature of solar power, randomness of load, and variation of noncritical load and grid price. These dynamics are considered for every time step and complex environment simulation is designed to emulate the distributed microgrid operations and evaluate the impact of agent operations.

Multiagent Systems Based Modeling and Implementation of Dynamic Energy Management of Smart Microgrid Using MACSimJX

PubMed Central

Raju, Leo; Milton, R. S.; Mahadevan, Senthilkumaran

2016-01-01

The objective of this paper is implementation of multiagent system (MAS) for the advanced distributed energy management and demand side management of a solar microgrid. Initially, Java agent development environment (JADE) frame work is used to implement MAS based dynamic energy management of solar microgrid. Due to unstable nature of MATLAB, when dealing with multithreading environment, MAS operating in JADE is linked with the MATLAB using a middle ware called Multiagent Control Using Simulink with Jade Extension (MACSimJX). MACSimJX allows the solar microgrid components designed with MATLAB to be controlled by the corresponding agents of MAS. The microgrid environment variables are captured through sensors and given to agents through MATLAB/Simulink and after the agent operations in JADE, the results are given to the actuators through MATLAB for the implementation of dynamic operation in solar microgrid. MAS operating in JADE maximizes operational efficiency of solar microgrid by decentralized approach and increase in runtime efficiency due to JADE. Autonomous demand side management is implemented for optimizing the power exchange between main grid and microgrid with intermittent nature of solar power, randomness of load, and variation of noncritical load and grid price. These dynamics are considered for every time step and complex environment simulation is designed to emulate the distributed microgrid operations and evaluate the impact of agent operations. PMID:27127802

Dynamics of tripartite quantum correlations and decoherence in flux qubit systems under local and non-local static noise

NASA Astrophysics Data System (ADS)

Arthur, Tsamouo Tsokeng; Martin, Tchoffo; Fai, Lukong Cornelius

2018-06-01

We investigate the dynamics of entanglement, decoherence and quantum discord in a system of three non-interacting superconducting flux qubits (fqubits) initially prepared in a Greenberger-Horne-Zeilinger (GHZ) state and subject to static noise in different, bipartite and common environments, since it is recognized that different noise configurations generally lead to completely different dynamical behavior of physical systems. The noise is modeled by randomizing the single fqubit transition amplitude. Decoherence and quantum correlations dynamics are strongly affected by the purity of the initial state, type of system-environment interaction and the system-environment coupling strength. Specifically, quantum correlations can persist when the fqubits are commonly coupled to a noise source, and reaches a saturation value respective to the purity of the initial state. As the number of decoherence channels increases (bipartite and different environments), decoherence becomes stronger against quantum correlations that decay faster, exhibiting sudden death and revival phenomena. The residual entanglement can be successfully detected by means of suitable entanglement witness, and we derive a necessary condition for entanglement detection related to the tunable and non-degenerated energy levels of fqubits. In accordance with the current literature, our results further suggest the efficiency of fqubits over ordinary ones, as far as the preservation of quantum correlations needed for quantum processing purposes is concerned.

Parasite transmission among relatives halts Red Queen dynamics.

PubMed

Greenspoon, Philip B; Mideo, Nicole

2017-03-01

The theory that coevolving hosts and parasites create a fluctuating selective environment for one another (i.e., produce Red Queen dynamics) has deep roots in evolutionary biology; yet empirical evidence for Red Queen dynamics remains scarce. Fluctuating coevolutionary dynamics underpin the Red Queen hypothesis for the evolution of sex, as well as hypotheses explaining the persistence of genetic variation under sexual selection, local parasite adaptation, the evolution of mutation rate, and the evolution of nonrandom mating. Coevolutionary models that exhibit Red Queen dynamics typically assume that hosts and parasites encounter one another randomly. However, if related individuals aggregate into family groups or are clustered spatially, related hosts will be more likely to encounter parasites transmitted by genetically similar individuals. Using a model that incorporates familial parasite transmission, we show that a slight degree of familial parasite transmission is sufficient to halt coevolutionary fluctuations. Our results predict that evidence for Red Queen dynamics, and its evolutionary consequences, are most likely to be found in biological systems in which hosts and parasites mix mainly at random, and are less likely to be found in systems with familial aggregation. This presents a challenge to the Red Queen hypothesis and other hypotheses that depend on coevolutionary cycling. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

Fractal Dynamics of Heartbeat Interval Fluctuations in Health and Disease

NASA Astrophysics Data System (ADS)

Meyer, M.; Marconi, C.; Rahmel, A.; Grassi, B.; Ferretti, G.; Skinner, J. E.; Cerretelli, P.

The dynamics of heartbeat interval time series were studied by a modified random walk analysis recently introduced as Detrended Fluctuation Analysis. In this analysis, the intrinsic fractal long-range power-law correlation properties of beat-to-beat fluctuations generated by the dynamical system (i.e. cardiac rhythm generator), after decomposition from extrinsic uncorrelated sources, can be quantified by the scaling exponent which, in healthy subjects, is about 1.0. The finding of a scaling coefficient of 1.0, indicating scale-invariant long-range power-law correlations (1/ƒnoise) of heartbeat fluctuations, would reflect a genuinely self-similar fractal process that typically generates fluctuations on a wide range of time scales. Lack of a characteristic time scale suggests that the neuroautonomic system underlying the control of heart rate dynamics helps prevent excessive mode-locking (error tolerance) that would restrict its functional responsiveness (plasticity) to environmental stimuli. The 1/ƒ dynamics of heartbeat interval fluctuations are unaffected by exposure to chronic hypoxia suggesting that the neuroautonomic cardiac control system is preadapted to hypoxia. Functional (hypothermia, cardiac disease) and/or structural (cardiac transplantation, early cardiac development) inactivation of neuroautonomic control is associated with the breakdown or absence of fractal complexity reflected by anticorrelated random walk-like dynamics, indicating that in these conditions the heart is unadapted to its environment.

Ontology of Earth's nonlinear dynamic complex systems

NASA Astrophysics Data System (ADS)

Babaie, Hassan; Davarpanah, Armita

2017-04-01

As a complex system, Earth and its major integrated and dynamically interacting subsystems (e.g., hydrosphere, atmosphere) display nonlinear behavior in response to internal and external influences. The Earth Nonlinear Dynamic Complex Systems (ENDCS) ontology formally represents the semantics of the knowledge about the nonlinear system element (agent) behavior, function, and structure, inter-agent and agent-environment feedback loops, and the emergent collective properties of the whole complex system as the result of interaction of the agents with other agents and their environment. It also models nonlinear concepts such as aperiodic, random chaotic behavior, sensitivity to initial conditions, bifurcation of dynamic processes, levels of organization, self-organization, aggregated and isolated functionality, and emergence of collective complex behavior at the system level. By incorporating several existing ontologies, the ENDCS ontology represents the dynamic system variables and the rules of transformation of their state, emergent state, and other features of complex systems such as the trajectories in state (phase) space (attractor and strange attractor), basins of attractions, basin divide (separatrix), fractal dimension, and system's interface to its environment. The ontology also defines different object properties that change the system behavior, function, and structure and trigger instability. ENDCS will help to integrate the data and knowledge related to the five complex subsystems of Earth by annotating common data types, unifying the semantics of shared terminology, and facilitating interoperability among different fields of Earth science.

An empirical evaluation of lightweight random walk based routing protocol in duty cycle aware wireless sensor networks.

PubMed

Mian, Adnan Noor; Fatima, Mehwish; Khan, Raees; Prakash, Ravi

2014-01-01

Energy efficiency is an important design paradigm in Wireless Sensor Networks (WSNs) and its consumption in dynamic environment is even more critical. Duty cycling of sensor nodes is used to address the energy consumption problem. However, along with advantages, duty cycle aware networks introduce some complexities like synchronization and latency. Due to their inherent characteristics, many traditional routing protocols show low performance in densely deployed WSNs with duty cycle awareness, when sensor nodes are supposed to have high mobility. In this paper we first present a three messages exchange Lightweight Random Walk Routing (LRWR) protocol and then evaluate its performance in WSNs for routing low data rate packets. Through NS-2 based simulations, we examine the LRWR protocol by comparing it with DYMO, a widely used WSN protocol, in both static and dynamic environments with varying duty cycles, assuming the standard IEEE 802.15.4 in lower layers. Results for the three metrics, that is, reliability, end-to-end delay, and energy consumption, show that LRWR protocol outperforms DYMO in scalability, mobility, and robustness, showing this protocol as a suitable choice in low duty cycle and dense WSNs.

Methods for Combining Payload Parameter Variations with Input Environment

NASA Technical Reports Server (NTRS)

Merchant, D. H.; Straayer, J. W.

1975-01-01

Methods are presented for calculating design limit loads compatible with probabilistic structural design criteria. The approach is based on the concept that the desired limit load, defined as the largest load occuring in a mission, is a random variable having a specific probability distribution which may be determined from extreme-value theory. The design limit load, defined as a particular value of this random limit load, is the value conventionally used in structural design. Methods are presented for determining the limit load probability distributions from both time-domain and frequency-domain dynamic load simulations. Numerical demonstrations of the methods are also presented.

Development and approach to low-frequency microgravity isolation systems

NASA Technical Reports Server (NTRS)

Grodsinsky, Carlos M.

1990-01-01

The low-gravity environment provided by space flight has afforded the science community a unique arena for the study of fundamental and technological sciences. However, the dynamic environment observed on space shuttle flights and predicted for Space Station Freedom has complicated the analysis of prior microgravity experiments and prompted concern for the viability of proposed space experiments requiring long-term, low-gravity environments. Thus, isolation systems capable of providing significant improvements to this random environment are being developed. The design constraints imposed by acceleration-sensitive, microgravity experiment payloads in the unique environment of space and a theoretical background for active isolation are discussed. A design is presented for a six-degree-of-freedom, active, inertial isolation system based on the baseline relative and inertial isolation techniques described.

An Approach for Dynamic Optimization of Prevention Program Implementation in Stochastic Environments

NASA Astrophysics Data System (ADS)

Kang, Yuncheol; Prabhu, Vittal

The science of preventing youth problems has significantly advanced in developing evidence-based prevention program (EBP) by using randomized clinical trials. Effective EBP can reduce delinquency, aggression, violence, bullying and substance abuse among youth. Unfortunately the outcomes of EBP implemented in natural settings usually tend to be lower than in clinical trials, which has motivated the need to study EBP implementations. In this paper we propose to model EBP implementations in natural settings as stochastic dynamic processes. Specifically, we propose Markov Decision Process (MDP) for modeling and dynamic optimization of such EBP implementations. We illustrate these concepts using simple numerical examples and discuss potential challenges in using such approaches in practice.

Mum, why do you keep on growing? Impacts of environmental variability on optimal growth and reproduction allocation strategies of annual plants.

PubMed

De Lara, Michel

2006-05-01

In their 1990 paper Optimal reproductive efforts and the timing of reproduction of annual plants in randomly varying environments, Amir and Cohen considered stochastic environments consisting of i.i.d. sequences in an optimal allocation discrete-time model. We suppose here that the sequence of environmental factors is more generally described by a Markov chain. Moreover, we discuss the connection between the time interval of the discrete-time dynamic model and the ability of the plant to rebuild completely its vegetative body (from reserves). We formulate a stochastic optimization problem covering the so-called linear and logarithmic fitness (corresponding to variation within and between years), which yields optimal strategies. For "linear maximizers'', we analyse how optimal strategies depend upon the environmental variability type: constant, random stationary, random i.i.d., random monotonous. We provide general patterns in terms of targets and thresholds, including both determinate and indeterminate growth. We also provide a partial result on the comparison between ;"linear maximizers'' and "log maximizers''. Numerical simulations are provided, allowing to give a hint at the effect of different mathematical assumptions.

Cooperation evolution in random multiplicative environments

NASA Astrophysics Data System (ADS)

Yaari, G.; Solomon, S.

2010-02-01

Most real life systems have a random component: the multitude of endogenous and exogenous factors influencing them result in stochastic fluctuations of the parameters determining their dynamics. These empirical systems are in many cases subject to noise of multiplicative nature. The special properties of multiplicative noise as opposed to additive noise have been noticed for a long while. Even though apparently and formally the difference between free additive vs. multiplicative random walks consists in just a move from normal to log-normal distributions, in practice the implications are much more far reaching. While in an additive context the emergence and survival of cooperation requires special conditions (especially some level of reward, punishment, reciprocity), we find that in the multiplicative random context the emergence of cooperation is much more natural and effective. We study the various implications of this observation and its applications in various contexts.

Effects of vibration and shock on the performance of gas-bearing space-power Brayton cycle turbomachinery. 2: Sinusoidal and random vibration

NASA Technical Reports Server (NTRS)

Tessarzik, J. M.; Chiang, T.; Badgley, R. H.

1973-01-01

The vibration response of a gas-bearing rotor-support system was analyzed experimentally documented for sinusoidal and random vibration environments. The NASA Brayton Rotating Unit (BRU), 36,000 rpm; 10 KWe turbogenerator; was subjected in the laboratory to sinusoidal and random vibrations to evaluate the capability of the BRU to (1) survive the vibration levels expected to be encountered during periods of nonoperation and (2) operate satisfactorily (that is, without detrimental bearing surface contacts) at the vibration levels expected during normal BRU operation. Response power spectral density was calculated for specified input random excitation, with particular emphasis upon the dynamic motions of the thrust bearing runner and stator. A three-mass model with nonlinear representation of the engine isolator mounts was used to calculate axial rotor-bearing shock response.

Stability and diversity in collective adaptation

NASA Astrophysics Data System (ADS)

Sato, Yuzuru; Akiyama, Eizo; Crutchfield, James P.

2005-10-01

We derive a class of macroscopic differential equations that describe collective adaptation, starting from a discrete-time stochastic microscopic model. The behavior of each agent is a dynamic balance between adaptation that locally achieves the best action and memory loss that leads to randomized behavior. We show that, although individual agents interact with their environment and other agents in a purely self-interested way, macroscopic behavior can be interpreted as game dynamics. Application to several familiar, explicit game interactions shows that the adaptation dynamics exhibits a diversity of collective behaviors. The simplicity of the assumptions underlying the macroscopic equations suggests that these behaviors should be expected broadly in collective adaptation. We also analyze the adaptation dynamics from an information-theoretic viewpoint and discuss self-organization induced by the dynamics of uncertainty, giving a novel view of collective adaptation.

Nature versus nurture: Predictability in low-temperature Ising dynamics

NASA Astrophysics Data System (ADS)

Ye, J.; Machta, J.; Newman, C. M.; Stein, D. L.

2013-10-01

Consider a dynamical many-body system with a random initial state subsequently evolving through stochastic dynamics. What is the relative importance of the initial state (“nature”) versus the realization of the stochastic dynamics (“nurture”) in predicting the final state? We examined this question for the two-dimensional Ising ferromagnet following an initial deep quench from T=∞ to T=0. We performed Monte Carlo studies on the overlap between “identical twins” raised in independent dynamical environments, up to size L=500. Our results suggest an overlap decaying with time as t-θh with θh=0.22±0.02; the same exponent holds for a quench to low but nonzero temperature. This “heritability exponent” may equal the persistence exponent for the two-dimensional Ising ferromagnet, but the two differ more generally.

Vibration testing of the JE-M-604-4-IUE rocket motor (Thiokol P/N E 28639-03)

NASA Technical Reports Server (NTRS)

Alt, R. E.; Tosh, J. T.

1976-01-01

The NASA International Ultraviolet Explorer (IUE) rocket motor (TE-M-604-4), a solid fuel, spherical rocket motor, was vibration tested in the Impact, Vibration, and Acceleration (IVA) Test Unit of the von Karman Gas Dynamics Facility (VKF). The objective of the test program was to subject the motor to qualification levels of sinusoidal and random vibration prior to the altitude firing of the motor in the Propulsion Development Test Cell (T-3), Engine Test Facility (ETF), AEDC. The vibration testing consisted of a low level sine survey from 5 to 2,000 Hz, followed by a qualification level sine sweep and qualification level random vibration. A second low level sine survey followed the qualification level testing. This sequence of testing was accomplished in each of three orthogonal axes. No motor problems were observed due to the imposition of these dynamic environments.

Soft X-ray spectromicroscopy using ptychography with randomly phased illumination

NASA Astrophysics Data System (ADS)

Maiden, A. M.; Morrison, G. R.; Kaulich, B.; Gianoncelli, A.; Rodenburg, J. M.

2013-04-01

Ptychography is a form of scanning diffractive imaging that can successfully retrieve the modulus and phase of both the sample transmission function and the illuminating probe. An experimental difficulty commonly encountered in diffractive imaging is the large dynamic range of the diffraction data. Here we report a novel ptychographic experiment using a randomly phased X-ray probe to considerably reduce the dynamic range of the recorded diffraction patterns. Images can be reconstructed reliably and robustly from this setup, even when scatter from the specimen is weak. A series of ptychographic reconstructions at X-ray energies around the L absorption edge of iron demonstrates the advantages of this method for soft X-ray spectromicroscopy, which can readily provide chemical sensitivity without the need for optical refocusing. In particular, the phase signal is in perfect registration with the modulus signal and provides complementary information that can be more sensitive to changes in the local chemical environment.

Chaos and the (un)predictability of evolution in a changing environment

PubMed Central

Rego-Costa, Artur; Débarre, Florence; Chevin, Luis-Miguel

2018-01-01

Among the factors that may reduce the predictability of evolution, chaos, characterized by a strong dependence on initial conditions, has received much less attention than randomness due to genetic drift or environmental stochasticity. It was recently shown that chaos in phenotypic evolution arises commonly under frequency-dependent selection caused by competitive interactions mediated by many traits. This result has been used to argue that chaos should often make evolutionary dynamics unpredictable. However, populations also evolve largely in response to external changing environments, and such environmental forcing is likely to influence the outcome of evolution in systems prone to chaos. We investigate how a changing environment causing oscillations of an optimal phenotype interacts with the internal dynamics of an eco-evolutionary system that would be chaotic in a constant environment. We show that strong environmental forcing can improve the predictability of evolution, by reducing the probability of chaos arising, and by dampening the magnitude of chaotic oscillations. In contrast, weak forcing can increase the probability of chaos, but it also causes evolutionary trajectories to track the environment more closely. Overall, our results indicate that, although chaos may occur in evolution, it does not necessarily undermine its predictability. PMID:29235104

Simulating Society Transitions: Standstill, Collapse and Growth in an Evolving Network Model

PubMed Central

Xu, Guanghua; Yang, Junjie; Li, Guoqing

2013-01-01

We developed a model society composed of various occupations that interact with each other and the environment, with the capability of simulating three widely recognized societal transition patterns: standstill, collapse and growth, which are important compositions of society evolving dynamics. Each occupation is equipped with a number of inhabitants that may randomly flow to other occupations, during which process new occupations may be created and then interact with existing ones. Total population of society is associated with productivity, which is determined by the structure and volume of the society. We ran the model under scenarios such as parasitism, environment fluctuation and invasion, which correspond to different driving forces of societal transition, and obtained reasonable simulation results. This work adds to our understanding of societal evolving dynamics as well as provides theoretical clues to sustainable development. PMID:24086530

Dynamical behavior of a stochastic SVIR epidemic model with vaccination

NASA Astrophysics Data System (ADS)

Zhang, Xinhong; Jiang, Daqing; Hayat, Tasawar; Ahmad, Bashir

2017-10-01

In this paper, we investigate the dynamical behavior of SVIR models in random environments. Firstly, we show that if R0s < 1, the disease of stochastic autonomous SVIR model will die out exponentially; if R˜0s > 1, the disease will be prevail. Moreover, this system admits a unique stationary distribution and it is ergodic when R˜0s > 1. Results show that environmental white noise is helpful for disease control. Secondly, we give sufficient conditions for the existence of nontrivial periodic solutions to stochastic SVIR model with periodic parameters. Finally, numerical simulations validate the analytical results.

The rise and fall of redundancy in decoherence and quantum Darwinism

NASA Astrophysics Data System (ADS)

Jess Riedel, C.; Zurek, Wojciech H.; Zwolak, Michael

2012-08-01

A state selected at random from the Hilbert space of a many-body system is overwhelmingly likely to exhibit highly non-classical correlations. For these typical states, half of the environment must be measured by an observer to determine the state of a given subsystem. The objectivity of classical reality—the fact that multiple observers can agree on the state of a subsystem after measuring just a small fraction of its environment—implies that the correlations found in nature between macroscopic systems and their environments are exceptional. Building on previous studies of quantum Darwinism showing that highly redundant branching states are produced ubiquitously during pure decoherence, we examine the conditions needed for the creation of branching states and study their demise through many-body interactions. We show that even constrained dynamics can suppress redundancy to the values typical of random states on relaxation timescales, and prove that these results hold exactly in the thermodynamic limit.

Active classifier selection for RGB-D object categorization using a Markov random field ensemble method

NASA Astrophysics Data System (ADS)

Durner, Maximilian; Márton, Zoltán.; Hillenbrand, Ulrich; Ali, Haider; Kleinsteuber, Martin

2017-03-01

In this work, a new ensemble method for the task of category recognition in different environments is presented. The focus is on service robotic perception in an open environment, where the robot's task is to recognize previously unseen objects of predefined categories, based on training on a public dataset. We propose an ensemble learning approach to be able to flexibly combine complementary sources of information (different state-of-the-art descriptors computed on color and depth images), based on a Markov Random Field (MRF). By exploiting its specific characteristics, the MRF ensemble method can also be executed as a Dynamic Classifier Selection (DCS) system. In the experiments, the committee- and topology-dependent performance boost of our ensemble is shown. Despite reduced computational costs and using less information, our strategy performs on the same level as common ensemble approaches. Finally, the impact of large differences between datasets is analyzed.

JT15D simulated flight data evaluation

NASA Technical Reports Server (NTRS)

Holm, R. G.

1984-01-01

The noise characteristics of the JT15D turbofan engine was analyzed with the objectives of: (1) assessing the state-of-art ability to simulate flight acoustic data using test results acquired in wind tunnel and outdoor (turbulence controlled) environments; and (2) predicting the farfield noise directivity of the blade passage frequency (BPF) tonal components using results from rotor blade mounted dynamic pressure instrumentation. Engine rotor tip speeds at subsonic, transonic, and supersonic conditions were evaluated. The ability to simulate flight results was generally within 2-3 dB for both outdoor and wind tunnel acoustic results. Some differences did occur in the broadband noise level and in the multiple-pure-tone harmonics at supersonic tip speeds. The prediction of blade passage frequency tone directivity from dynamic pressure measurements was accomplished for the three tip speed conditions. Predictions were made of the random and periodic components of the tone directivity. The technique for estimating the random tone component used hot wire data to establish a correlation between dynamic pressure and turbulence intensity. This prediction overestimated the tone level by typically 10 dB with the greatest overestimates occurring at supersonic conditions.

76 FR 73676 - Certain Dynamic Random Access Memory Devices, and Products Containing Same; Receipt of Complaint...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-29

... INTERNATIONAL TRADE COMMISSION [DN 2859] Certain Dynamic Random Access Memory Devices, and.... International Trade Commission has received a complaint entitled In Re Certain Dynamic Random Access Memory... certain dynamic random access memory devices, and products containing same. The complaint names Elpida...

75 FR 16507 - In the Matter of Certain Semiconductor Chips Having Synchronous Dynamic Random Access Memory...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-01

... Semiconductor Chips Having Synchronous Dynamic Random Access Memory Controllers and Products Containing Same... synchronous dynamic random access memory controllers and products containing same by reason of infringement of... semiconductor chips having synchronous dynamic random access memory controllers and products containing same...

Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements.

PubMed

Xiong, Chunbao; Lu, Huali; Zhu, Jinsong

2017-02-23

Real-time dynamic displacement and acceleration responses of the main span section of the Tianjin Fumin Bridge in China under ambient excitation were tested using a Global Navigation Satellite System (GNSS) dynamic deformation monitoring system and an acceleration sensor vibration test system. Considering the close relationship between the GNSS multipath errors and measurement environment in combination with the noise reduction characteristics of different filtering algorithms, the researchers proposed an AFEC mixed filtering algorithm, which is an combination of autocorrelation function-based empirical mode decomposition (EMD) and Chebyshev mixed filtering to extract the real vibration displacement of the bridge structure after system error correction and filtering de-noising of signals collected by the GNSS. The proposed AFEC mixed filtering algorithm had high accuracy (1 mm) of real displacement at the elevation direction. Next, the traditional random decrement technique (used mainly for stationary random processes) was expanded to non-stationary random processes. Combining the expanded random decrement technique (RDT) and autoregressive moving average model (ARMA), the modal frequency of the bridge structural system was extracted using an expanded ARMA_RDT modal identification method, which was compared with the power spectrum analysis results of the acceleration signal and finite element analysis results. Identification results demonstrated that the proposed algorithm is applicable to analyze the dynamic displacement monitoring data of real bridge structures under ambient excitation and could identify the first five orders of the inherent frequencies of the structural system accurately. The identification error of the inherent frequency was smaller than 6%, indicating the high identification accuracy of the proposed algorithm. Furthermore, the GNSS dynamic deformation monitoring method can be used to monitor dynamic displacement and identify the modal parameters of bridge structures. The GNSS can monitor the working state of bridges effectively and accurately. Research results can provide references to evaluate the bearing capacity, safety performance, and durability of bridge structures during operation.

Operational Modal Analysis of Bridge Structures with Data from GNSS/Accelerometer Measurements

PubMed Central

Xiong, Chunbao; Lu, Huali; Zhu, Jinsong

2017-01-01

Real-time dynamic displacement and acceleration responses of the main span section of the Tianjin Fumin Bridge in China under ambient excitation were tested using a Global Navigation Satellite System (GNSS) dynamic deformation monitoring system and an acceleration sensor vibration test system. Considering the close relationship between the GNSS multipath errors and measurement environment in combination with the noise reduction characteristics of different filtering algorithms, the researchers proposed an AFEC mixed filtering algorithm, which is an combination of autocorrelation function-based empirical mode decomposition (EMD) and Chebyshev mixed filtering to extract the real vibration displacement of the bridge structure after system error correction and filtering de-noising of signals collected by the GNSS. The proposed AFEC mixed filtering algorithm had high accuracy (1 mm) of real displacement at the elevation direction. Next, the traditional random decrement technique (used mainly for stationary random processes) was expanded to non-stationary random processes. Combining the expanded random decrement technique (RDT) and autoregressive moving average model (ARMA), the modal frequency of the bridge structural system was extracted using an expanded ARMA_RDT modal identification method, which was compared with the power spectrum analysis results of the acceleration signal and finite element analysis results. Identification results demonstrated that the proposed algorithm is applicable to analyze the dynamic displacement monitoring data of real bridge structures under ambient excitation and could identify the first five orders of the inherent frequencies of the structural system accurately. The identification error of the inherent frequency was smaller than 6%, indicating the high identification accuracy of the proposed algorithm. Furthermore, the GNSS dynamic deformation monitoring method can be used to monitor dynamic displacement and identify the modal parameters of bridge structures. The GNSS can monitor the working state of bridges effectively and accurately. Research results can provide references to evaluate the bearing capacity, safety performance, and durability of bridge structures during operation. PMID:28241472

Heterogeneous continuous-time random walks

NASA Astrophysics Data System (ADS)

Grebenkov, Denis S.; Tupikina, Liubov

2018-01-01

We introduce a heterogeneous continuous-time random walk (HCTRW) model as a versatile analytical formalism for studying and modeling diffusion processes in heterogeneous structures, such as porous or disordered media, multiscale or crowded environments, weighted graphs or networks. We derive the exact form of the propagator and investigate the effects of spatiotemporal heterogeneities onto the diffusive dynamics via the spectral properties of the generalized transition matrix. In particular, we show how the distribution of first-passage times changes due to local and global heterogeneities of the medium. The HCTRW formalism offers a unified mathematical language to address various diffusion-reaction problems, with numerous applications in material sciences, physics, chemistry, biology, and social sciences.

Dynamic species classification of microorganisms across time, abiotic and biotic environments—A sliding window approach

PubMed Central

Griffiths, Jason I.; Fronhofer, Emanuel A.; Garnier, Aurélie; Seymour, Mathew; Altermatt, Florian; Petchey, Owen L.

2017-01-01

The development of video-based monitoring methods allows for rapid, dynamic and accurate monitoring of individuals or communities, compared to slower traditional methods, with far reaching ecological and evolutionary applications. Large amounts of data are generated using video-based methods, which can be effectively processed using machine learning (ML) algorithms into meaningful ecological information. ML uses user defined classes (e.g. species), derived from a subset (i.e. training data) of video-observed quantitative features (e.g. phenotypic variation), to infer classes in subsequent observations. However, phenotypic variation often changes due to environmental conditions, which may lead to poor classification, if environmentally induced variation in phenotypes is not accounted for. Here we describe a framework for classifying species under changing environmental conditions based on the random forest classification. A sliding window approach was developed that restricts temporal and environmentally conditions to improve the classification. We tested our approach by applying the classification framework to experimental data. The experiment used a set of six ciliate species to monitor changes in community structure and behavior over hundreds of generations, in dozens of species combinations and across a temperature gradient. Differences in biotic and abiotic conditions caused simplistic classification approaches to be unsuccessful. In contrast, the sliding window approach allowed classification to be highly successful, as phenotypic differences driven by environmental change, could be captured by the classifier. Importantly, classification using the random forest algorithm showed comparable success when validated against traditional, slower, manual identification. Our framework allows for reliable classification in dynamic environments, and may help to improve strategies for long-term monitoring of species in changing environments. Our classification pipeline can be applied in fields assessing species community dynamics, such as eco-toxicology, ecology and evolutionary ecology. PMID:28472193

76 FR 80964 - Certain Dynamic Random Access Memory Devices, and Products Containing Same; Institution of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-12-27

... INTERNATIONAL TRADE COMMISSION [Investigation No. 337-TA-821] Certain Dynamic Random Access Memory... importation, and the sale within the United States after importation of certain dynamic random access memory... certain dynamic random access memory devices, and products containing same that infringe one or more of...

Optimal Strategy for Integrated Dynamic Inventory Control and Supplier Selection in Unknown Environment via Stochastic Dynamic Programming

NASA Astrophysics Data System (ADS)

Sutrisno; Widowati; Solikhin

2016-06-01

In this paper, we propose a mathematical model in stochastic dynamic optimization form to determine the optimal strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the optimal supplier and calculate the optimal product volume purchased from the optimal supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic dynamic programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the optimal supplier and the inventory level was tracked the reference point well.

Quantum Fisher information of the GHZ state due to classical phase noise lasers under non-Markovian environment

NASA Astrophysics Data System (ADS)

Chen, Yu; Zou, Jian; Yang, Zi-Yi; Li, Longwu; Li, Hai; Shao, Bin

2016-08-01

The dynamics of N-qubit GHZ state quantum Fisher information (QFI) under phase noise lasers (PNLs) driving is investigated in terms of non-Markovian master equation. We first investigate the non-Markovian dynamics of the QFI of N-qubit GHZ state and show that when the ratio of the PNL rate and the system-environment coupling strength is very small, the oscillations of the QFIs decay slower which corresponds to the non-Markovian region; yet when it becomes large, the QFIs monotonously decay which corresponds to the Markovian region. When the atom number N increases, QFIs in both regions decay faster. We further find that the QFI flow disappears suddenly followed by a sudden birth depending on the ratio of the PNL rate and the system-environment coupling strength and the atom number N, which unveil a fundamental connection between the non-Markovian behaviors and the parameters of system-environment couplings. We discuss two optimal positive operator-valued measures (POVMs) for two different strategies of our model and find the condition of the optimal measurement. At last, we consider the QFI of two atoms with qubit-qubit interaction under random telegraph noises (RTNs).

Rocket Engine Nozzle Side Load Transient Analysis Methodology: A Practical Approach

NASA Technical Reports Server (NTRS)

Shi, John J.

2005-01-01

At the sea level, a phenomenon common with all rocket engines, especially for a highly over-expanded nozzle, during ignition and shutdown is that of flow separation as the plume fills and empties the nozzle, Since the flow will be separated randomly. it will generate side loads, i.e. non-axial forces. Since rocket engines are designed to produce axial thrust to power the vehicles, it is not desirable to be excited by non-axial input forcing functions, In the past, several engine failures were attributed to side loads. During the development stage, in order to design/size the rocket engine components and to reduce the risks, the local dynamic environments as well as dynamic interface loads have to be defined. The methodology developed here is the way to determine the peak loads and shock environments for new engine components. In the past it is not feasible to predict the shock environments, e.g. shock response spectra, from one engine to the other, because it is not scaleable. Therefore, the problem has been resolved and the shock environments can be defined in the early stage of new engine development. Additional information is included in the original extended abstract.

A Re-entrant Phase Transition in the Survival of Secondary Infections on Networks

NASA Astrophysics Data System (ADS)

Moore, Sam; Mörters, Peter; Rogers, Tim

2018-06-01

We study the dynamics of secondary infections on networks, in which only the individuals currently carrying a certain primary infection are susceptible to the secondary infection. In the limit of large sparse networks, the model is mapped to a branching process spreading in a random time-sensitive environment, determined by the dynamics of the underlying primary infection. When both epidemics follow the Susceptible-Infective-Recovered model, we show that in order to survive, it is necessary for the secondary infection to evolve on a timescale that is closely matched to that of the primary infection on which it depends.

A Hybrid Search Algorithm for Swarm Robots Searching in an Unknown Environment

PubMed Central

Li, Shoutao; Li, Lina; Lee, Gordon; Zhang, Hao

2014-01-01

This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency. PMID:25386855

A hybrid search algorithm for swarm robots searching in an unknown environment.

PubMed

Li, Shoutao; Li, Lina; Lee, Gordon; Zhang, Hao

2014-01-01

This paper proposes a novel method to improve the efficiency of a swarm of robots searching in an unknown environment. The approach focuses on the process of feeding and individual coordination characteristics inspired by the foraging behavior in nature. A predatory strategy was used for searching; hence, this hybrid approach integrated a random search technique with a dynamic particle swarm optimization (DPSO) search algorithm. If a search robot could not find any target information, it used a random search algorithm for a global search. If the robot found any target information in a region, the DPSO search algorithm was used for a local search. This particle swarm optimization search algorithm is dynamic as all the parameters in the algorithm are refreshed synchronously through a communication mechanism until the robots find the target position, after which, the robots fall back to a random searching mode. Thus, in this searching strategy, the robots alternated between two searching algorithms until the whole area was covered. During the searching process, the robots used a local communication mechanism to share map information and DPSO parameters to reduce the communication burden and overcome hardware limitations. If the search area is very large, search efficiency may be greatly reduced if only one robot searches an entire region given the limited resources available and time constraints. In this research we divided the entire search area into several subregions, selected a target utility function to determine which subregion should be initially searched and thereby reduced the residence time of the target to improve search efficiency.

Stochastic and information-thermodynamic structures of population dynamics in a fluctuating environment

NASA Astrophysics Data System (ADS)

Kobayashi, Tetsuya J.; Sughiyama, Yuki

2017-07-01

Adaptation in a fluctuating environment is a process of fueling environmental information to gain fitness. Living systems have gradually developed strategies for adaptation from random and passive diversification of the phenotype to more proactive decision making, in which environmental information is sensed and exploited more actively and effectively. Understanding the fundamental relation between fitness and information is therefore crucial to clarify the limits and universal properties of adaptation. In this work, we elucidate the underlying stochastic and information-thermodynamic structure in this process, by deriving causal fluctuation relations (FRs) of fitness and information. Combined with a duality between phenotypic and environmental dynamics, the FRs reveal the limit of fitness gain, the relation of time reversibility with the achievability of the limit, and the possibility and condition for gaining excess fitness due to environmental fluctuation. The loss of fitness due to causal constraints and the limited capacity of real organisms is shown to be the difference between time-forward and time-backward path probabilities of phenotypic and environmental dynamics. Furthermore, the FRs generalize the concept of the evolutionary stable state (ESS) for fluctuating environment by giving the probability that the optimal strategy on average can be invaded by a suboptimal one owing to rare environmental fluctuation. These results clarify the information-thermodynamic structures in adaptation and evolution.

Non-Brownian dynamics and strategy of amoeboid cell locomotion.

PubMed

Nishimura, Shin I; Ueda, Masahiro; Sasai, Masaki

2012-04-01

Amoeboid cells such as Dictyostelium discoideum and Madin-Darby canine kidney cells show the non-Brownian dynamics of migration characterized by the superdiffusive increase of mean-squared displacement. In order to elucidate the physical mechanism of this non-Brownian dynamics, a computational model is developed which highlights a group of inhibitory molecules for actin polymerization. Based on this model, we propose a hypothesis that inhibitory molecules are sent backward in the moving cell to accumulate at the rear of cell. The accumulated inhibitory molecules at the rear further promote cell locomotion to form a slow positive feedback loop of the whole-cell scale. The persistent straightforward migration is stabilized with this feedback mechanism, but the fluctuation in the distribution of inhibitory molecules and the cell shape deformation concurrently interrupt the persistent motion to turn the cell into a new direction. A sequence of switching behaviors between persistent motions and random turns gives rise to the superdiffusive migration in the absence of the external guidance signal. In the complex environment with obstacles, this combined process of persistent motions and random turns drives the simulated amoebae to solve the maze problem in a highly efficient way, which suggests the biological advantage for cells to bear the non-Brownian dynamics.

Non-Markovian dynamics of single- and two-qubit systems interacting with Gaussian and non-Gaussian fluctuating transverse environments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rossi, Matteo A. C., E-mail: matteo.rossi@unimi.it; Paris, Matteo G. A., E-mail: matteo.paris@fisica.unimi.it; CNISM, Unità Milano Statale, I-20133 Milano

2016-01-14

We address the interaction of single- and two-qubit systems with an external transverse fluctuating field and analyze in detail the dynamical decoherence induced by Gaussian noise and random telegraph noise (RTN). Upon exploiting the exact RTN solution of the time-dependent von Neumann equation, we analyze in detail the behavior of quantum correlations and prove the non-Markovianity of the dynamical map in the full parameter range, i.e., for either fast or slow noise. The dynamics induced by Gaussian noise is studied numerically and compared to the RTN solution, showing the existence of (state dependent) regions of the parameter space where themore » two noises lead to very similar dynamics. We show that the effects of RTN noise and of Gaussian noise are different, i.e., the spectrum alone is not enough to summarize the noise effects, but the dynamics under the effect of one kind of noise may be simulated with high fidelity by the other one.« less

Chaos and the (un)predictability of evolution in a changing environment.

PubMed

Rego-Costa, Artur; Débarre, Florence; Chevin, Luis-Miguel

2018-02-01

Among the factors that may reduce the predictability of evolution, chaos, characterized by a strong dependence on initial conditions, has received much less attention than randomness due to genetic drift or environmental stochasticity. It was recently shown that chaos in phenotypic evolution arises commonly under frequency-dependent selection caused by competitive interactions mediated by many traits. This result has been used to argue that chaos should often make evolutionary dynamics unpredictable. However, populations also evolve largely in response to external changing environments, and such environmental forcing is likely to influence the outcome of evolution in systems prone to chaos. We investigate how a changing environment causing oscillations of an optimal phenotype interacts with the internal dynamics of an eco-evolutionary system that would be chaotic in a constant environment. We show that strong environmental forcing can improve the predictability of evolution by reducing the probability of chaos arising, and by dampening the magnitude of chaotic oscillations. In contrast, weak forcing can increase the probability of chaos, but it also causes evolutionary trajectories to track the environment more closely. Overall, our results indicate that, although chaos may occur in evolution, it does not necessarily undermine its predictability. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Acoustic and Vibration Environment for Crew Launch Vehicle Mobile Launcher

NASA Technical Reports Server (NTRS)

Vu, Bruce T.

2007-01-01

A launch-induced acoustic environment represents a dynamic load on the exposed facilities and ground support equipment (GSE) in the form of random pressures fluctuating around the ambient atmospheric pressure. In response to these fluctuating pressures, structural vibrations are generated and transmitted throughout the structure and to the equipment items supported by the structure. Certain equipment items are also excited by the direct acoustic input as well as by the vibration transmitted through the supporting structure. This paper presents the predicted acoustic and vibration environments induced by the launch of the Crew Launch Vehicle (CLV) from Launch Complex (LC) 39. The predicted acoustic environment depicted in this paper was calculated by scaling the statistically processed measured data available from Saturn V launches to the anticipated environment of the CLV launch. The scaling was accomplished by using the 5-segment Solid Rocket Booster (SRB) engine parameters. Derivation of vibration environment for various Mobile Launcher (ML) structures throughout the base and tower was accomplished by scaling the Saturn V vibration environment.

Confounding environmental colour and distribution shape leads to underestimation of population extinction risk.

PubMed

Fowler, Mike S; Ruokolainen, Lasse

2013-01-01

The colour of environmental variability influences the size of population fluctuations when filtered through density dependent dynamics, driving extinction risk through dynamical resonance. Slow fluctuations (low frequencies) dominate in red environments, rapid fluctuations (high frequencies) in blue environments and white environments are purely random (no frequencies dominate). Two methods are commonly employed to generate the coloured spatial and/or temporal stochastic (environmental) series used in combination with population (dynamical feedback) models: autoregressive [AR(1)] and sinusoidal (1/f) models. We show that changing environmental colour from white to red with 1/f models, and from white to red or blue with AR(1) models, generates coloured environmental series that are not normally distributed at finite time-scales, potentially confounding comparison with normally distributed white noise models. Increasing variability of sample Skewness and Kurtosis and decreasing mean Kurtosis of these series alter the frequency distribution shape of the realised values of the coloured stochastic processes. These changes in distribution shape alter patterns in the probability of single and series of extreme conditions. We show that the reduced extinction risk for undercompensating (slow growing) populations in red environments previously predicted with traditional 1/f methods is an artefact of changes in the distribution shapes of the environmental series. This is demonstrated by comparison with coloured series controlled to be normally distributed using spectral mimicry. Changes in the distribution shape that arise using traditional methods lead to underestimation of extinction risk in normally distributed, red 1/f environments. AR(1) methods also underestimate extinction risks in traditionally generated red environments. This work synthesises previous results and provides further insight into the processes driving extinction risk in model populations. We must let the characteristics of known natural environmental covariates (e.g., colour and distribution shape) guide us in our choice of how to best model the impact of coloured environmental variation on population dynamics.

Nonlinear complexity behaviors of agent-based 3D Potts financial dynamics with random environments

NASA Astrophysics Data System (ADS)

Xing, Yani; Wang, Jun

2018-02-01

A new microscopic 3D Potts interaction financial price model is established in this work, to investigate the nonlinear complexity behaviors of stock markets. 3D Potts model, which extends the 2D Potts model to three-dimensional, is a cubic lattice model to explain the interaction behavior among the agents. In order to explore the complexity of real financial markets and the 3D Potts financial model, a new random coarse-grained Lempel-Ziv complexity is proposed to certain series, such as the price returns, the price volatilities, and the random time d-returns. Then the composite multiscale entropy (CMSE) method is applied to the intrinsic mode functions (IMFs) and the corresponding shuffled data to study the complexity behaviors. The empirical results indicate that the 3D financial model is feasible.

Opinion dynamics in a group-based society

NASA Astrophysics Data System (ADS)

Gargiulo, F.; Huet, S.

2010-09-01

Many models have been proposed to analyze the evolution of opinion structure due to the interaction of individuals in their social environment. Such models analyze the spreading of ideas both in completely interacting backgrounds and on social networks, where each person has a finite set of interlocutors. In this paper we analyze the reciprocal feedback between the opinions of the individuals and the structure of the interpersonal relationships at the level of community structures. For this purpose we define a group-based random network and we study how this structure co-evolves with opinion dynamics processes. We observe that the adaptive network structure affects the opinion dynamics process helping the consensus formation. The results also show interesting behaviors in regards to the size distribution of the groups and their correlation with opinion structure.

Methods for combining payload parameter variations with input environment. [calculating design limit loads compatible with probabilistic structural design criteria

NASA Technical Reports Server (NTRS)

Merchant, D. H.

1976-01-01

Methods are presented for calculating design limit loads compatible with probabilistic structural design criteria. The approach is based on the concept that the desired limit load, defined as the largest load occurring in a mission, is a random variable having a specific probability distribution which may be determined from extreme-value theory. The design limit load, defined as a particular of this random limit load, is the value conventionally used in structural design. Methods are presented for determining the limit load probability distributions from both time-domain and frequency-domain dynamic load simulations. Numerical demonstrations of the method are also presented.

Adaptive mechanism-based congestion control for networked systems

NASA Astrophysics Data System (ADS)

Liu, Zhi; Zhang, Yun; Chen, C. L. Philip

2013-03-01

In order to assure the communication quality in network systems with heavy traffic and limited bandwidth, a new ATRED (adaptive thresholds random early detection) congestion control algorithm is proposed for the congestion avoidance and resource management of network systems. Different to the traditional AQM (active queue management) algorithms, the control parameters of ATRED are not configured statically, but dynamically adjusted by the adaptive mechanism. By integrating with the adaptive strategy, ATRED alleviates the tuning difficulty of RED (random early detection) and shows a better control on the queue management, and achieve a more robust performance than RED under varying network conditions. Furthermore, a dynamic transmission control protocol-AQM control system using ATRED controller is introduced for the systematic analysis. It is proved that the stability of the network system can be guaranteed when the adaptive mechanism is finely designed. Simulation studies show the proposed ATRED algorithm achieves a good performance in varying network environments, which is superior to the RED and Gentle-RED algorithm, and providing more reliable service under varying network conditions.

Experimental nonlinear dynamical studies in cesium magneto-optical trap using time-series analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anwar, M., E-mail: mamalik2000@gmail.com; Islam, R.; Faisal, M.

2015-03-30

A magneto-optical trap of neutral atoms is essentially a dissipative quantum system. The fast thermal atoms continuously dissipate their energy to the environment via spontaneous emissions during the cooling. The atoms are, therefore, strongly coupled with the vacuum reservoir and the laser field. The vacuum fluctuations as well as the field fluctuations are imparted to the atoms as random photon recoils. Consequently, the external and internal dynamics of atoms becomes stochastic. In this paper, we have investigated the stochastic dynamics of the atoms in a magneto-optical trap during the loading process. The time series analysis of the fluorescence signal showsmore » that the dynamics of the atoms evolves, like all dissipative systems, from deterministic to the chaotic regime. The subsequent disappearance and revival of chaos was attributed to chaos synchronization between spatially different atoms in the magneto-optical trap.« less

Mean first-passage times of non-Markovian random walkers in confinement.

PubMed

Guérin, T; Levernier, N; Bénichou, O; Voituriez, R

2016-06-16

The first-passage time, defined as the time a random walker takes to reach a target point in a confining domain, is a key quantity in the theory of stochastic processes. Its importance comes from its crucial role in quantifying the efficiency of processes as varied as diffusion-limited reactions, target search processes or the spread of diseases. Most methods of determining the properties of first-passage time in confined domains have been limited to Markovian (memoryless) processes. However, as soon as the random walker interacts with its environment, memory effects cannot be neglected: that is, the future motion of the random walker does not depend only on its current position, but also on its past trajectory. Examples of non-Markovian dynamics include single-file diffusion in narrow channels, or the motion of a tracer particle either attached to a polymeric chain or diffusing in simple or complex fluids such as nematics, dense soft colloids or viscoelastic solutions. Here we introduce an analytical approach to calculate, in the limit of a large confining volume, the mean first-passage time of a Gaussian non-Markovian random walker to a target. The non-Markovian features of the dynamics are encompassed by determining the statistical properties of the fictitious trajectory that the random walker would follow after the first-passage event takes place, which are shown to govern the first-passage time kinetics. This analysis is applicable to a broad range of stochastic processes, which may be correlated at long times. Our theoretical predictions are confirmed by numerical simulations for several examples of non-Markovian processes, including the case of fractional Brownian motion in one and higher dimensions. These results reveal, on the basis of Gaussian processes, the importance of memory effects in first-passage statistics of non-Markovian random walkers in confinement.

Mean first-passage times of non-Markovian random walkers in confinement

NASA Astrophysics Data System (ADS)

Guérin, T.; Levernier, N.; Bénichou, O.; Voituriez, R.

2016-06-01

The first-passage time, defined as the time a random walker takes to reach a target point in a confining domain, is a key quantity in the theory of stochastic processes. Its importance comes from its crucial role in quantifying the efficiency of processes as varied as diffusion-limited reactions, target search processes or the spread of diseases. Most methods of determining the properties of first-passage time in confined domains have been limited to Markovian (memoryless) processes. However, as soon as the random walker interacts with its environment, memory effects cannot be neglected: that is, the future motion of the random walker does not depend only on its current position, but also on its past trajectory. Examples of non-Markovian dynamics include single-file diffusion in narrow channels, or the motion of a tracer particle either attached to a polymeric chain or diffusing in simple or complex fluids such as nematics, dense soft colloids or viscoelastic solutions. Here we introduce an analytical approach to calculate, in the limit of a large confining volume, the mean first-passage time of a Gaussian non-Markovian random walker to a target. The non-Markovian features of the dynamics are encompassed by determining the statistical properties of the fictitious trajectory that the random walker would follow after the first-passage event takes place, which are shown to govern the first-passage time kinetics. This analysis is applicable to a broad range of stochastic processes, which may be correlated at long times. Our theoretical predictions are confirmed by numerical simulations for several examples of non-Markovian processes, including the case of fractional Brownian motion in one and higher dimensions. These results reveal, on the basis of Gaussian processes, the importance of memory effects in first-passage statistics of non-Markovian random walkers in confinement.

Effects of leadership style and group dynamics on enjoyment of physical activity.

PubMed

Fox, L D; Rejeski, W J; Gauvin, L

2000-01-01

The primary purpose of this study was to examine the independent and combined effects of leadership style and group dynamics on the enjoyment of physical activity. A completely randomized 2 x 2 factorial design was used in which the manipulation of "leadership style" (socially enriched vs. bland) was crossed with a manipulation of "group dynamics" (socially enriched vs. bland). The study was conducted in an aerobics studio on a university campus. The sample included 48 male and 42 female undergraduate students who were moderately active. Each participant was involved in a single session of step aerobics. A female graduate student provided either an enriched or bland series of interactions to manipulate leadership style, and a trained group of planted undergraduates was used to promote either an enriched or bland group environment. The outcome measures of interest were enjoyment and the probability of engaging in a similar activity in the future. Participants in the enriched leadership style plus enriched group dynamics condition reported higher enjoyment than did participants in the other three conditions. On average, the level of enjoyment was 22.07% higher in this condition than in the other three conditions (p < .001). The probability of future involvement was 13.93% higher for participants in the enriched group environment, irrespective of leadership style (p < .03). Enjoyment during physical activity is optimized when a positive and supportive leadership style is coupled with an enriched and supportive group environment. Future research is required to extend these findings to other activities and populations.

Model dynamics for quantum computing

NASA Astrophysics Data System (ADS)

Tabakin, Frank

2017-08-01

A model master equation suitable for quantum computing dynamics is presented. In an ideal quantum computer (QC), a system of qubits evolves in time unitarily and, by virtue of their entanglement, interfere quantum mechanically to solve otherwise intractable problems. In the real situation, a QC is subject to decoherence and attenuation effects due to interaction with an environment and with possible short-term random disturbances and gate deficiencies. The stability of a QC under such attacks is a key issue for the development of realistic devices. We assume that the influence of the environment can be incorporated by a master equation that includes unitary evolution with gates, supplemented by a Lindblad term. Lindblad operators of various types are explored; namely, steady, pulsed, gate friction, and measurement operators. In the master equation, we use the Lindblad term to describe short time intrusions by random Lindblad pulses. The phenomenological master equation is then extended to include a nonlinear Beretta term that describes the evolution of a closed system with increasing entropy. An external Bath environment is stipulated by a fixed temperature in two different ways. Here we explore the case of a simple one-qubit system in preparation for generalization to multi-qubit, qutrit and hybrid qubit-qutrit systems. This model master equation can be used to test the stability of memory and the efficacy of quantum gates. The properties of such hybrid master equations are explored, with emphasis on the role of thermal equilibrium and entropy constraints. Several significant properties of time-dependent qubit evolution are revealed by this simple study.

Random diffusivity from stochastic equations: comparison of two models for Brownian yet non-Gaussian diffusion

NASA Astrophysics Data System (ADS)

Sposini, Vittoria; Chechkin, Aleksei V.; Seno, Flavio; Pagnini, Gianni; Metzler, Ralf

2018-04-01

A considerable number of systems have recently been reported in which Brownian yet non-Gaussian dynamics was observed. These are processes characterised by a linear growth in time of the mean squared displacement, yet the probability density function of the particle displacement is distinctly non-Gaussian, and often of exponential (Laplace) shape. This apparently ubiquitous behaviour observed in very different physical systems has been interpreted as resulting from diffusion in inhomogeneous environments and mathematically represented through a variable, stochastic diffusion coefficient. Indeed different models describing a fluctuating diffusivity have been studied. Here we present a new view of the stochastic basis describing time-dependent random diffusivities within a broad spectrum of distributions. Concretely, our study is based on the very generic class of the generalised Gamma distribution. Two models for the particle spreading in such random diffusivity settings are studied. The first belongs to the class of generalised grey Brownian motion while the second follows from the idea of diffusing diffusivities. The two processes exhibit significant characteristics which reproduce experimental results from different biological and physical systems. We promote these two physical models for the description of stochastic particle motion in complex environments.

Lévy-like behaviour in deterministic models of intelligent agents exploring heterogeneous environments

NASA Astrophysics Data System (ADS)

Boyer, D.; Miramontes, O.; Larralde, H.

2009-10-01

Many studies on animal and human movement patterns report the existence of scaling laws and power-law distributions. Whereas a number of random walk models have been proposed to explain observations, in many situations individuals actually rely on mental maps to explore strongly heterogeneous environments. In this work, we study a model of a deterministic walker, visiting sites randomly distributed on the plane and with varying weight or attractiveness. At each step, the walker minimizes a function that depends on the distance to the next unvisited target (cost) and on the weight of that target (gain). If the target weight distribution is a power law, p(k) ~ k-β, in some range of the exponent β, the foraging medium induces movements that are similar to Lévy flights and are characterized by non-trivial exponents. We explore variations of the choice rule in order to test the robustness of the model and argue that the addition of noise has a limited impact on the dynamics in strongly disordered media.

76 FR 2336 - Dynamic Random Access Memory Semiconductors From the Republic of Korea: Final Results of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-01-13

... DEPARTMENT OF COMMERCE International Trade Administration [C-580-851] Dynamic Random Access Memory... administrative review of the countervailing duty order on dynamic random access memory semiconductors from the... following events have occurred since the publication of the preliminary results of this review. See Dynamic...

Analysis of stationary and dynamic factors affecting highway accident occurrence: A dynamic correlated grouped random parameters binary logit approach.

PubMed

Fountas, Grigorios; Sarwar, Md Tawfiq; Anastasopoulos, Panagiotis Ch; Blatt, Alan; Majka, Kevin

2018-04-01

Traditional accident analysis typically explores non-time-varying (stationary) factors that affect accident occurrence on roadway segments. However, the impact of time-varying (dynamic) factors is not thoroughly investigated. This paper seeks to simultaneously identify pre-crash stationary and dynamic factors of accident occurrence, while accounting for unobserved heterogeneity. Using highly disaggregate information for the potential dynamic factors, and aggregate data for the traditional stationary elements, a dynamic binary random parameters (mixed) logit framework is employed. With this approach, the dynamic nature of weather-related, and driving- and pavement-condition information is jointly investigated with traditional roadway geometric and traffic characteristics. To additionally account for the combined effect of the dynamic and stationary factors on the accident occurrence, the developed random parameters logit framework allows for possible correlations among the random parameters. The analysis is based on crash and non-crash observations between 2011 and 2013, drawn from urban and rural highway segments in the state of Washington. The findings show that the proposed methodological framework can account for both stationary and dynamic factors affecting accident occurrence probabilities, for panel effects, for unobserved heterogeneity through the use of random parameters, and for possible correlation among the latter. The comparative evaluation among the correlated grouped random parameters, the uncorrelated random parameters logit models, and their fixed parameters logit counterpart, demonstrate the potential of the random parameters modeling, in general, and the benefits of the correlated grouped random parameters approach, specifically, in terms of statistical fit and explanatory power. Published by Elsevier Ltd.

Stochastic resonance and noise delayed extinction in a model of two competing species

NASA Astrophysics Data System (ADS)

Valenti, D.; Fiasconaro, A.; Spagnolo, B.

2004-01-01

We study the role of the noise in the dynamics of two competing species. We consider generalized Lotka-Volterra equations in the presence of a multiplicative noise, which models the interaction between the species and the environment. The interaction parameter between the species is a random process which obeys a stochastic differential equation with a generalized bistable potential in the presence of a periodic driving term, which accounts for the environment temperature variation. We find noise-induced periodic oscillations of the species concentrations and stochastic resonance phenomenon. We find also a nonmonotonic behavior of the mean extinction time of one of the two competing species as a function of the additive noise intensity.

Comparing cluster-level dynamic treatment regimens using sequential, multiple assignment, randomized trials: Regression estimation and sample size considerations.

PubMed

NeCamp, Timothy; Kilbourne, Amy; Almirall, Daniel

2017-08-01

Cluster-level dynamic treatment regimens can be used to guide sequential treatment decision-making at the cluster level in order to improve outcomes at the individual or patient-level. In a cluster-level dynamic treatment regimen, the treatment is potentially adapted and re-adapted over time based on changes in the cluster that could be impacted by prior intervention, including aggregate measures of the individuals or patients that compose it. Cluster-randomized sequential multiple assignment randomized trials can be used to answer multiple open questions preventing scientists from developing high-quality cluster-level dynamic treatment regimens. In a cluster-randomized sequential multiple assignment randomized trial, sequential randomizations occur at the cluster level and outcomes are observed at the individual level. This manuscript makes two contributions to the design and analysis of cluster-randomized sequential multiple assignment randomized trials. First, a weighted least squares regression approach is proposed for comparing the mean of a patient-level outcome between the cluster-level dynamic treatment regimens embedded in a sequential multiple assignment randomized trial. The regression approach facilitates the use of baseline covariates which is often critical in the analysis of cluster-level trials. Second, sample size calculators are derived for two common cluster-randomized sequential multiple assignment randomized trial designs for use when the primary aim is a between-dynamic treatment regimen comparison of the mean of a continuous patient-level outcome. The methods are motivated by the Adaptive Implementation of Effective Programs Trial which is, to our knowledge, the first-ever cluster-randomized sequential multiple assignment randomized trial in psychiatry.

Tumor evolution in space: the effects of competition colonization tradeoffs on tumor invasion dynamics.

PubMed

Orlando, Paul A; Gatenby, Robert A; Brown, Joel S

2013-01-01

We apply competition colonization tradeoff models to tumor growth and invasion dynamics to explore the hypothesis that varying selection forces will result in predictable phenotypic differences in cells at the tumor invasive front compared to those in the core. Spatially, ecologically, and evolutionarily explicit partial differential equation models of tumor growth confirm that spatial invasion produces selection pressure for motile phenotypes. The effects of the invasive phenotype on normal adjacent tissue determine the patterns of growth and phenotype distribution. If tumor cells do not destroy their environment, colonizer and competitive phenotypes coexist with the former localized at the invasion front and the latter, to the tumor interior. If tumors cells do destroy their environment, then cell motility is strongly selected resulting in accelerated invasion speed with time. Our results suggest that the widely observed genetic heterogeneity within cancers may not be the stochastic effect of random mutations. Rather, it may be the consequence of predictable variations in environmental selection forces and corresponding phenotypic adaptations.

Tumor Evolution in Space: The Effects of Competition Colonization Tradeoffs on Tumor Invasion Dynamics

PubMed Central

Orlando, Paul A.; Gatenby, Robert A.; Brown, Joel S.

2013-01-01

We apply competition colonization tradeoff models to tumor growth and invasion dynamics to explore the hypothesis that varying selection forces will result in predictable phenotypic differences in cells at the tumor invasive front compared to those in the core. Spatially, ecologically, and evolutionarily explicit partial differential equation models of tumor growth confirm that spatial invasion produces selection pressure for motile phenotypes. The effects of the invasive phenotype on normal adjacent tissue determine the patterns of growth and phenotype distribution. If tumor cells do not destroy their environment, colonizer and competitive phenotypes coexist with the former localized at the invasion front and the latter, to the tumor interior. If tumors cells do destroy their environment, then cell motility is strongly selected resulting in accelerated invasion speed with time. Our results suggest that the widely observed genetic heterogeneity within cancers may not be the stochastic effect of random mutations. Rather, it may be the consequence of predictable variations in environmental selection forces and corresponding phenotypic adaptations. PMID:23508890

Testing the Efficacy of OurSpace, a Brief, Group Dynamics-Based Physical Activity Intervention: A Randomized Controlled Trial.

PubMed

Irwin, Brandon; Kurz, Daniel; Chalin, Patrice; Thompson, Nicholas

2016-05-06

Emerging technologies (ie, mobile phones, Internet) may be effective tools for promoting physical activity (PA). However, few interventions have provided effective means to enhance social support through these platforms. Face-to-face programs that use group dynamics-based principles of behavior change have been shown to be highly effective in enhancing social support through promoting group cohesion and PA, but to date, no studies have examined their effects in Web-based programs. The aim was to explore proof of concept and test the efficacy of a brief, online group dynamics-based intervention on PA in a controlled experiment. We expected that the impact of the intervention on PA would be moderated by perceptions of cohesion and the partner's degree of presence in the online media. Participants (n=135) were randomized into same-sex dyads and randomly assigned to one of four experimental conditions: standard social support (standard), group dynamics-based-high presence, group dynamics-based-low presence, or individual control. Participants performed two sets of planking exercises (pre-post). Between sets, participants in partnered conditions interacted with a virtual partner using either a standard social support app or a group dynamics-based app (group dynamics-based-low presence and group dynamics-based-high presence), the latter of which they participated in a series of online team-building exercises. Individual participants were given an equivalent rest period between sets. To increase presence during the second set, participants in the group dynamics-based-high presence group saw a live video stream of their partner exercising. Perceptions of cohesion were measured using a modified PA Group Environment Questionnaire. Physical activity was calculated as the time persisted during set 2 after controlling for persistence in set 1. Perceptions of cohesion were higher in the group dynamics-based-low presence (overall mean 5.81, SD 1.04) condition compared to the standard (overall mean 5.04, SD 0.81) conditions ( P=.006), but did not differ between group dynamics-based-low presence and group dynamics-based-high presence (overall mean 5.42, SD 1.07) conditions ( P=.25). Physical activity was higher in the high presence condition (mean 64.48, SD 20.19, P=.01) than all other conditions (mean 53.3, SD 17.35). A brief, online group dynamics-based intervention may be an effective method of improving group cohesion in virtual PA groups. However, it may be insufficient on its own to improve PA.

Methods and analysis of realizing randomized grouping.

PubMed

Hu, Liang-Ping; Bao, Xiao-Lei; Wang, Qi

2011-07-01

Randomization is one of the four basic principles of research design. The meaning of randomization includes two aspects: one is to randomly select samples from the population, which is known as random sampling; the other is to randomly group all the samples, which is called randomized grouping. Randomized grouping can be subdivided into three categories: completely, stratified and dynamically randomized grouping. This article mainly introduces the steps of complete randomization, the definition of dynamic randomization and the realization of random sampling and grouping by SAS software.

Corn rootworms (Coleoptera: Chrysomelidae) in space and time

NASA Astrophysics Data System (ADS)

Park, Yong-Lak

Spatial dispersion is a main characteristic of insect populations. Dispersion pattern provides useful information for developing effective sampling and scouting programs because it affects sampling accuracy, efficiency, and precision. Insect dispersion, however, is dynamic in space and time and largely dependent upon interactions among insect, plant and environmental factors. This study investigated the spatial and temporal dynamics of corn rootworm dispersion at different spatial scales by using the global positioning system, the geographic information system, and geostatistics. Egg dispersion pattern was random or uniform in 8-ha cornfields, but could be aggregated at a smaller scale. Larval dispersion pattern was aggregated regardless of spatial scales used in this study. Soil moisture positively affected corn rootworm egg and larval dispersions. Adult dispersion tended to be aggregated during peak population period and random or uniform early and late in the season and corn plant phenology was a major factor to determine dispersion patterns. The dispersion pattern of root injury by corn rootworm larval feeding was aggregated and the degree of aggregation increased as the root injury increased within the range of root injury observed in microscale study. Between-year relationships in dispersion among eggs, larvae, adult, and environment provided a strategy that could predict potential root damage the subsequent year. The best prediction map for the subsequent year's potential root damage was the dispersion maps of adults during population peaked in the cornfield. The prediction map was used to develop site-specific pest management that can reduce chemical input and increase control efficiency by controlling pests only where management is needed. This study demonstrated the spatio-temporal dynamics of insect population and spatial interactions among insects, plants, and environment.

Chaotic Traversal (CHAT): Very Large Graphs Traversal Using Chaotic Dynamics

NASA Astrophysics Data System (ADS)

Changaival, Boonyarit; Rosalie, Martin; Danoy, Grégoire; Lavangnananda, Kittichai; Bouvry, Pascal

2017-12-01

Graph Traversal algorithms can find their applications in various fields such as routing problems, natural language processing or even database querying. The exploration can be considered as a first stepping stone into knowledge extraction from the graph which is now a popular topic. Classical solutions such as Breadth First Search (BFS) and Depth First Search (DFS) require huge amounts of memory for exploring very large graphs. In this research, we present a novel memoryless graph traversal algorithm, Chaotic Traversal (CHAT) which integrates chaotic dynamics to traverse large unknown graphs via the Lozi map and the Rössler system. To compare various dynamics effects on our algorithm, we present an original way to perform the exploration of a parameter space using a bifurcation diagram with respect to the topological structure of attractors. The resulting algorithm is an efficient and nonresource demanding algorithm, and is therefore very suitable for partial traversal of very large and/or unknown environment graphs. CHAT performance using Lozi map is proven superior than the, commonly known, Random Walk, in terms of number of nodes visited (coverage percentage) and computation time where the environment is unknown and memory usage is restricted.

Real-Time Motion Planning and Safe Navigation in Dynamic Multi-Robot Environments

DTIC Science & Technology

2006-12-15

referee against a robot for pushing or hitting an opponent excessively, as well as for a non- goalie robot entering the team’s own defense area. The DSS... pulling ” a search graph by choosing random samples and then trying to connect a path to those points, some planners “push” samples by first choosing...implement the various roles (attacker, goalie , defender), which in turn build on sub-tactics known as skills [16]. One primitive skill used by almost all

Does the mask govern the mind?: effects of arbitrary gender representation on quantitative task performance in avatar-represented virtual groups.

PubMed

Lee, Jong-Eun Roselyn; Nass, Clifford I; Bailenson, Jeremy N

2014-04-01

Virtual environments employing avatars for self-representation-including the opportunity to represent or misrepresent social categories-raise interesting and intriguing questions as to how one's avatar-based social category shapes social identity dynamics, particularly when stereotypes prevalent in the offline world apply to the social categories visually represented by avatars. The present experiment investigated how social category representation via avatars (i.e., graphical representations of people in computer-mediated environments) affects stereotype-relevant task performance. In particular, building on and extending the Proteus effect model, we explored whether and how stereotype lift (i.e., a performance boost caused by the awareness of a domain-specific negative stereotype associated with outgroup members) occurred in virtual group settings in which avatar-based gender representation was arbitrary. Female and male participants (N=120) were randomly assigned either a female avatar or a male avatar through a process masked as a random drawing. They were then placed in a numerical minority status with respect to virtual gender-as the only virtual female (male) in a computer-mediated triad with two opposite-gendered avatars-and performed a mental arithmetic task either competitively or cooperatively. The data revealed that participants who were arbitrarily represented by a male avatar and competed against two ostensible female avatars showed strongest performance compared to others on the arithmetic task. This pattern occurred regardless of participants' actual gender, pointing to a virtual stereotype lift effect. Additional mediation tests showed that task motivation partially mediated the effect. Theoretical and practical implications for social identity dynamics in avatar-based virtual environments are discussed.

Nonparametric Online Learning Control for Soft Continuum Robot: An Enabling Technique for Effective Endoscopic Navigation

PubMed Central

Lee, Kit-Hang; Fu, Denny K.C.; Leong, Martin C.W.; Chow, Marco; Fu, Hing-Choi; Althoefer, Kaspar; Sze, Kam Yim; Yeung, Chung-Kwong

2017-01-01

Abstract Bioinspired robotic structures comprising soft actuation units have attracted increasing research interest. Taking advantage of its inherent compliance, soft robots can assure safe interaction with external environments, provided that precise and effective manipulation could be achieved. Endoscopy is a typical application. However, previous model-based control approaches often require simplified geometric assumptions on the soft manipulator, but which could be very inaccurate in the presence of unmodeled external interaction forces. In this study, we propose a generic control framework based on nonparametric and online, as well as local, training to learn the inverse model directly, without prior knowledge of the robot's structural parameters. Detailed experimental evaluation was conducted on a soft robot prototype with control redundancy, performing trajectory tracking in dynamically constrained environments. Advanced element formulation of finite element analysis is employed to initialize the control policy, hence eliminating the need for random exploration in the robot's workspace. The proposed control framework enabled a soft fluid-driven continuum robot to follow a 3D trajectory precisely, even under dynamic external disturbance. Such enhanced control accuracy and adaptability would facilitate effective endoscopic navigation in complex and changing environments. PMID:29251567

Nonparametric Online Learning Control for Soft Continuum Robot: An Enabling Technique for Effective Endoscopic Navigation.

PubMed

Lee, Kit-Hang; Fu, Denny K C; Leong, Martin C W; Chow, Marco; Fu, Hing-Choi; Althoefer, Kaspar; Sze, Kam Yim; Yeung, Chung-Kwong; Kwok, Ka-Wai

2017-12-01

Bioinspired robotic structures comprising soft actuation units have attracted increasing research interest. Taking advantage of its inherent compliance, soft robots can assure safe interaction with external environments, provided that precise and effective manipulation could be achieved. Endoscopy is a typical application. However, previous model-based control approaches often require simplified geometric assumptions on the soft manipulator, but which could be very inaccurate in the presence of unmodeled external interaction forces. In this study, we propose a generic control framework based on nonparametric and online, as well as local, training to learn the inverse model directly, without prior knowledge of the robot's structural parameters. Detailed experimental evaluation was conducted on a soft robot prototype with control redundancy, performing trajectory tracking in dynamically constrained environments. Advanced element formulation of finite element analysis is employed to initialize the control policy, hence eliminating the need for random exploration in the robot's workspace. The proposed control framework enabled a soft fluid-driven continuum robot to follow a 3D trajectory precisely, even under dynamic external disturbance. Such enhanced control accuracy and adaptability would facilitate effective endoscopic navigation in complex and changing environments.

Simulating star clusters with the AMUSE software framework. I. Dependence of cluster lifetimes on model assumptions and cluster dissolution modes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Whitehead, Alfred J.; McMillan, Stephen L. W.; Vesperini, Enrico

2013-12-01

We perform a series of simulations of evolving star clusters using the Astrophysical Multipurpose Software Environment (AMUSE), a new community-based multi-physics simulation package, and compare our results to existing work. These simulations model a star cluster beginning with a King model distribution and a selection of power-law initial mass functions and contain a tidal cutoff. They are evolved using collisional stellar dynamics and include mass loss due to stellar evolution. After studying and understanding that the differences between AMUSE results and results from previous studies are understood, we explored the variation in cluster lifetimes due to the random realization noisemore » introduced by transforming a King model to specific initial conditions. This random realization noise can affect the lifetime of a simulated star cluster by up to 30%. Two modes of star cluster dissolution were identified: a mass evolution curve that contains a runaway cluster dissolution with a sudden loss of mass, and a dissolution mode that does not contain this feature. We refer to these dissolution modes as 'dynamical' and 'relaxation' dominated, respectively. For Salpeter-like initial mass functions, we determined the boundary between these two modes in terms of the dynamical and relaxation timescales.« less

Evolutionary Perspective on Collective Decision Making

NASA Astrophysics Data System (ADS)

Farrell, Dene; Sayama, Hiroki; Dionne, Shelley D.; Yammarino, Francis J.; Wilson, David Sloan

Team decision making dynamics are investigated from a novel perspective by shifting agency from decision makers to representations of potential solutions. We provide a new way to navigate social dynamics of collective decision making by interpreting decision makers as constituents of an evolutionary environment of an ecology of evolving solutions. We demonstrate distinct patterns of evolution with respect to three forms of variation: (1) Results with random variations in utility functions of individuals indicate that groups demonstrating minimal internal variation produce higher true utility values of group solutions and display better convergence; (2) analysis of variations in behavioral patterns within a group shows that a proper balance between selective and creative evolutionary forces is crucial to producing adaptive solutions; and (3) biased variations of the utility functions diminish the range of variation for potential solution utility, leaving only the differential of convergence performance static. We generally find that group cohesion (low random variation within a group) and composition (appropriate variation of behavioral patterns within a group) are necessary for a successful navigation of the solution space, but performance in both cases is susceptible to group level biases.

Adaptive servo control for umbilical mating

NASA Technical Reports Server (NTRS)

Zia, Omar

1988-01-01

Robotic applications at Kennedy Space Center are unique and in many cases require the fime positioning of heavy loads in dynamic environments. Performing such operations is beyond the capabilities of an off-the-shelf industrial robot. Therefore Robotics Applications Development Laboratory at Kennedy Space Center has put together an integrated system that coordinates state of the art robotic system providing an excellent easy to use testbed for NASA sensor integration experiments. This paper reviews the ways of improving the dynamic response of the robot operating under force feedback with varying dynamic internal perturbations in order to provide continuous stable operations under variable load conditions. The goal is to improve the stability of the system with force feedback using the adaptive control feature of existing system over a wide range of random motions. The effect of load variations on the dynamics and the transfer function (order or values of the parameters) of the system has been investigated, more accurate models of the system have been determined and analyzed.

Dynamic spectrum management: an impact on EW systems

NASA Astrophysics Data System (ADS)

Gajewski, P.; Łopatka, J.; Suchanski, M.

2017-04-01

Rapid evolution of wireless systems caused an enormous growth of data streams transmitted through the networks and, as a consequence, an accompanying demand concerning spectrum resources (SR). An avoidance of advisable disturbances is one of the main demands in military communications. To solve the interference problems, dynamic spectrum management (DSM) techniques can be used. Two main techniques are possible: centralized Coordinated Dynamic Spectrum Access (CDSA) and distributed Opportunistic Spectrum Access (OSA). CDSA enables the wireless networks planning automation, and systems dynamic reaction to random changes of Radio Environment (RE). For OSA, cognitive radio (CR) is the most promising technology that enables avoidance of interference with the other spectrum users due to CR's transmission parameters adaptation to the current radio situation, according to predefined Radio Policies rules. If DSM techniques are used, the inherent changes in EW systems are also needed. On one hand, new techniques of jamming should be elaborated, on the other hand, the rules and protocols of cooperation between communication network and EW systems should be developed.

Quantifying uncertainty due to fission-fusion dynamics as a component of social complexity.

PubMed

Ramos-Fernandez, Gabriel; King, Andrew J; Beehner, Jacinta C; Bergman, Thore J; Crofoot, Margaret C; Di Fiore, Anthony; Lehmann, Julia; Schaffner, Colleen M; Snyder-Mackler, Noah; Zuberbühler, Klaus; Aureli, Filippo; Boyer, Denis

2018-05-30

Groups of animals (including humans) may show flexible grouping patterns, in which temporary aggregations or subgroups come together and split, changing composition over short temporal scales, (i.e. fission and fusion). A high degree of fission-fusion dynamics may constrain the regulation of social relationships, introducing uncertainty in interactions between group members. Here we use Shannon's entropy to quantify the predictability of subgroup composition for three species known to differ in the way their subgroups come together and split over time: spider monkeys ( Ateles geoffroyi ), chimpanzees ( Pan troglodytes ) and geladas ( Theropithecus gelada ). We formulate a random expectation of entropy that considers subgroup size variation and sample size, against which the observed entropy in subgroup composition can be compared. Using the theory of set partitioning, we also develop a method to estimate the number of subgroups that the group is likely to be divided into, based on the composition and size of single focal subgroups. Our results indicate that Shannon's entropy and the estimated number of subgroups present at a given time provide quantitative metrics of uncertainty in the social environment (within which social relationships must be regulated) for groups with different degrees of fission-fusion dynamics. These metrics also represent an indirect quantification of the cognitive challenges posed by socially dynamic environments. Overall, our novel methodological approach provides new insight for understanding the evolution of social complexity and the mechanisms to cope with the uncertainty that results from fission-fusion dynamics. © 2017 The Author(s).

Diffusion with stochastic resetting at power-law times.

PubMed

Nagar, Apoorva; Gupta, Shamik

2016-06-01

What happens when a continuously evolving stochastic process is interrupted with large changes at random intervals τ distributed as a power law ∼τ^{-(1+α)};α>0? Modeling the stochastic process by diffusion and the large changes as abrupt resets to the initial condition, we obtain exact closed-form expressions for both static and dynamic quantities, while accounting for strong correlations implied by a power law. Our results show that the resulting dynamics exhibits a spectrum of rich long-time behavior, from an ever-spreading spatial distribution for α<1, to one that is time independent for α>1. The dynamics has strong consequences on the time to reach a distant target for the first time; we specifically show that there exists an optimal α that minimizes the mean time to reach the target, thereby offering a step towards a viable strategy to locate targets in a crowded environment.

Randomized Dynamic Mode Decomposition

NASA Astrophysics Data System (ADS)

Erichson, N. Benjamin; Brunton, Steven L.; Kutz, J. Nathan

2017-11-01

The dynamic mode decomposition (DMD) is an equation-free, data-driven matrix decomposition that is capable of providing accurate reconstructions of spatio-temporal coherent structures arising in dynamical systems. We present randomized algorithms to compute the near-optimal low-rank dynamic mode decomposition for massive datasets. Randomized algorithms are simple, accurate and able to ease the computational challenges arising with `big data'. Moreover, randomized algorithms are amenable to modern parallel and distributed computing. The idea is to derive a smaller matrix from the high-dimensional input data matrix using randomness as a computational strategy. Then, the dynamic modes and eigenvalues are accurately learned from this smaller representation of the data, whereby the approximation quality can be controlled via oversampling and power iterations. Here, we present randomized DMD algorithms that are categorized by how many passes the algorithm takes through the data. Specifically, the single-pass randomized DMD does not require data to be stored for subsequent passes. Thus, it is possible to approximately decompose massive fluid flows (stored out of core memory, or not stored at all) using single-pass algorithms, which is infeasible with traditional DMD algorithms.

Data-driven modelling of vertical dynamic excitation of bridges induced by people running

NASA Astrophysics Data System (ADS)

Racic, Vitomir; Morin, Jean Benoit

2014-02-01

With increasingly popular marathon events in urban environments, structural designers face a great deal of uncertainty when assessing dynamic performance of bridges occupied and dynamically excited by people running. While the dynamic loads induced by pedestrians walking have been intensively studied since the infamous lateral sway of the London Millennium Bridge in 2000, reliable and practical descriptions of running excitation are still very rare and limited. This interdisciplinary study has addressed the issue by bringing together a database of individual running force signals recorded by two state-of-the-art instrumented treadmills and two attempts to mathematically describe the measurements. The first modelling strategy is adopted from the available design guidelines for human walking excitation of structures, featuring perfectly periodic and deterministic characterisation of pedestrian forces presentable via Fourier series. This modelling approach proved to be inadequate for running loads due to the inherent near-periodic nature of the measured signals, a great inter-personal randomness of the dominant Fourier amplitudes and the lack of strong correlation between the amplitudes and running footfall rate. Hence, utilising the database established and motivated by the existing models of wind and earthquake loading, speech recognition techniques and a method of replicating electrocardiogram signals, this paper finally presents a numerical generator of random near-periodic running force signals which can reliably simulate the measurements. Such a model is an essential prerequisite for future quality models of dynamic loading induced by individuals, groups and crowds running under a wide range of conditions, such as perceptibly vibrating bridges and different combinations of visual, auditory and tactile cues.

Dynamical evolution of galaxies in dense cluster environment.

NASA Astrophysics Data System (ADS)

Gnedin, O. Y.

1997-12-01

I present the results of study of the dynamics of galaxies in clusters of galaxies. The effects of the galaxy environment could be quite dramatic. The time-varying gravitational potential of the cluster subjects the galaxies to strong tidal effects. The tidal density cutoff effectively strips the dark matter halos and leads to highly concentrated structures in the galactic centers. The fast gravitational tidal shocks raise the random motion of stars in the galaxies, transforming the thin disks into the kinematically hot thick configurations. The tidal shocks also cause relaxation of stellar energies that enhances the rate of accretion onto the galactic centers. These effects of the time-varying cluster potential have not been consistently taken into account before. I present numerical N-body simulations of galaxies using the Self-Consistent Field code with 10(7) - 10(8) particles. The code is coupled with the PM code that provides a fully dynamic simulation of the cluster potential. The tidal field of the cluster along the galaxy trajectories is imposed as an external perturbation on the galaxies in the SCF scheme. Recent HST observations show that the high-redshift (z > 0.4) clusters contain numerous bright blue spirals, often with distorted profiles, whereas the nearby clusters are mostly populated by featureless ellipticals. The goal of my study is to understand whether dynamics is responsible for the observed strong evolution of galaxies in clusters.

Dynamic structure mediates halophilic adaptation of a DNA polymerase from the deep-sea brines of the Red Sea.

PubMed

Takahashi, Masateru; Takahashi, Etsuko; Joudeh, Luay I; Marini, Monica; Das, Gobind; Elshenawy, Mohamed M; Akal, Anastassja; Sakashita, Kosuke; Alam, Intikhab; Tehseen, Muhammad; Sobhy, Mohamed A; Stingl, Ulrich; Merzaban, Jasmeen S; Di Fabrizio, Enzo; Hamdan, Samir M

2018-01-24

The deep-sea brines of the Red Sea are remote and unexplored environments characterized by high temperatures, anoxic water, and elevated concentrations of salt and heavy metals. This environment provides a rare system to study the interplay between halophilic and thermophilic adaptation in biologic macromolecules. The present article reports the first DNA polymerase with halophilic and thermophilic features. Biochemical and structural analysis by Raman and circular dichroism spectroscopy showed that the charge distribution on the protein's surface mediates the structural balance between stability for thermal adaptation and flexibility for counteracting the salt-induced rigid and nonfunctional hydrophobic packing. Salt bridge interactions via increased negative and positive charges contribute to structural stability. Salt tolerance, conversely, is mediated by a dynamic structure that becomes more fixed and functional with increasing salt concentration. We propose that repulsive forces among excess negative charges, in addition to a high percentage of negatively charged random coils, mediate this structural dynamism. This knowledge enabled us to engineer a halophilic version of KOD DNA polymerase.-Takahashi, M., Takahashi, E., Joudeh, L. I., Marini, M., Das, G., Elshenawy, M. M., Akal, A., Sakashita, K., Alam, I., Tehseen, M., Sobhy, M. A., Stingl, U., Merzaban, J. S., Di Fabrizio, E., Hamdan, S. M. Dynamic structure mediates halophilic adaptation of a DNA polymerase from the deep-sea brines of the Red Sea.

Breather Rogue Waves in Random Seas

NASA Astrophysics Data System (ADS)

Wang, J.; Ma, Q. W.; Yan, S.; Chabchoub, A.

2018-01-01

Rogue or freak waves are extreme wave events that have heights exceeding 8 times the standard deviation of surrounding waves and emerge, for instance, in the ocean as well as in other physical dispersive wave guides, such as in optical fibers. One effective and convenient way to model such an extreme dynamics in laboratory environments within a controlled framework as well as for short process time and length scales is provided through the breather formalism. Breathers are pulsating localized structures known to model extreme waves in several nonlinear dispersive media in which the initial underlying process is assumed to be narrow banded. On the other hand, several recent studies suggest that breathers can also persist in more complex environments, such as in random seas, beyond the attributed physical limitations. In this work, we study the robustness of the Peregrine breather (PB) embedded in Joint North Sea Wave Project (JONSWAP) configurations using fully nonlinear hydrodynamic numerical simulations in order to validate its practicalness for ocean engineering applications. We provide a specific range for both the spectral bandwidth of the dynamical process as well as the background wave steepness and, thus, quantify the applicability of the PB in modeling rogue waves in realistic oceanic conditions. Our results may motivate analogous studies in fields of physics such as optics and plasma to quantify the limitations of exact weakly nonlinear models, such as solitons and breathers, within the framework of the fully nonlinear governing equations of the corresponding medium.

Sex differences in the inference and perception of causal relations within a video game

PubMed Central

Young, Michael E.

2014-01-01

The learning of immediate causation within a dynamic environment was examined. Participants encountered seven decision points in which they needed to choose, which of three possible candidates was the cause of explosions in the environment. Each candidate was firing a weapon at random every few seconds, but only one of them produced an immediate effect. Some participants showed little learning, but most demonstrated increases in accuracy across time. On average, men showed higher accuracy and shorter latencies that were not explained by differences in self-reported prior video game experience. This result suggests that prior reports of sex differences in causal choice in the game are not specific to situations involving delayed or probabilistic causal relations. PMID:25202293

Quasispecies theory for evolution of modularity.

PubMed

Park, Jeong-Man; Niestemski, Liang Ren; Deem, Michael W

2015-01-01

Biological systems are modular, and this modularity evolves over time and in different environments. A number of observations have been made of increased modularity in biological systems under increased environmental pressure. We here develop a quasispecies theory for the dynamics of modularity in populations of these systems. We show how the steady-state fitness in a randomly changing environment can be computed. We derive a fluctuation dissipation relation for the rate of change of modularity and use it to derive a relationship between rate of environmental changes and rate of growth of modularity. We also find a principle of least action for the evolved modularity at steady state. Finally, we compare our predictions to simulations of protein evolution and find them to be consistent.

Sex differences in the inference and perception of causal relations within a video game.

PubMed

Young, Michael E

2014-01-01

The learning of immediate causation within a dynamic environment was examined. Participants encountered seven decision points in which they needed to choose, which of three possible candidates was the cause of explosions in the environment. Each candidate was firing a weapon at random every few seconds, but only one of them produced an immediate effect. Some participants showed little learning, but most demonstrated increases in accuracy across time. On average, men showed higher accuracy and shorter latencies that were not explained by differences in self-reported prior video game experience. This result suggests that prior reports of sex differences in causal choice in the game are not specific to situations involving delayed or probabilistic causal relations.

Value of the future: Discounting in random environments

NASA Astrophysics Data System (ADS)

Farmer, J. Doyne; Geanakoplos, John; Masoliver, Jaume; Montero, Miquel; Perelló, Josep

2015-05-01

We analyze how to value future costs and benefits when they must be discounted relative to the present. We introduce the subject for the nonspecialist and take into account the randomness of the economic evolution by studying the discount function of three widely used processes for the dynamics of interest rates: Ornstein-Uhlenbeck, Feller, and log-normal. Besides obtaining exact expressions for the discount function and simple asymptotic approximations, we show that historical average interest rates overestimate long-run discount rates and that this effect can be large. In other words, long-run discount rates should be substantially less than the average rate observed in the past, otherwise any cost-benefit calculation would be biased in favor of the present and against interventions that may protect the future.

Value of the future: Discounting in random environments.

PubMed

Farmer, J Doyne; Geanakoplos, John; Masoliver, Jaume; Montero, Miquel; Perelló, Josep

2015-05-01

We analyze how to value future costs and benefits when they must be discounted relative to the present. We introduce the subject for the nonspecialist and take into account the randomness of the economic evolution by studying the discount function of three widely used processes for the dynamics of interest rates: Ornstein-Uhlenbeck, Feller, and log-normal. Besides obtaining exact expressions for the discount function and simple asymptotic approximations, we show that historical average interest rates overestimate long-run discount rates and that this effect can be large. In other words, long-run discount rates should be substantially less than the average rate observed in the past, otherwise any cost-benefit calculation would be biased in favor of the present and against interventions that may protect the future.

Random trinomial tree models and vanilla options

NASA Astrophysics Data System (ADS)

Ganikhodjaev, Nasir; Bayram, Kamola

2013-09-01

In this paper we introduce and study random trinomial model. The usual trinomial model is prescribed by triple of numbers (u, d, m). We call the triple (u, d, m) an environment of the trinomial model. A triple (Un, Dn, Mn), where {Un}, {Dn} and {Mn} are the sequences of independent, identically distributed random variables with 0 < Dn < 1 < Un and Mn = 1 for all n, is called a random environment and trinomial tree model with random environment is called random trinomial model. The random trinomial model is considered to produce more accurate results than the random binomial model or usual trinomial model.

Understanding of the Dynamics of the Stirling Convertor Advanced by Structural Testing

NASA Technical Reports Server (NTRS)

Hughes, William O.

2003-01-01

The NASA Glenn Research Center, the U.S. Department of Energy, and the Stirling Technology Company (STC) are developing a highly efficient, long-life, free-piston Stirling convertor for use as an advanced spacecraft power system for future NASA missions, including deep-space and Mars surface applications. As part of this development, four structural dynamic test programs were recently performed on Stirling Technology Demonstration Convertors (TDC's) that were designed and built by STC under contract to the Department of Energy. This testing was performed in Glenn's Structural Dynamics Laboratory and Microgravity Emissions Laboratory. The first test program, in November and December 1999, demonstrated that the Stirling TDC could withstand the harsh random vibration experienced during a typical spacecraft launch and survive with no structural damage or functional power performance degradation. This was a critical step in enabling the use of Stirling convertors for future spacecraft power systems. The most severe test was a 12.3grms random vibration test, with test durations of 3 min per axis. The random vibration test levels were chosen to simulate, with margin, the maximum anticipated launch vibration conditions. The Microgravity Emissions Laboratory is typically used to measure the dynamics produced by operating space experiments and the resulting impact to the International Space Station's microgravity environment. For the second Stirling dynamic test program, performed in January 2001, the Microgravity Emissions Laboratory was used to characterize the structure-borne disturbances produced by the normal operation of a pair of Stirling convertors. The forces and moments produced by the normal operation of a Stirling system must be recognized and controlled, if necessary, so that other nearby spacecraft components, such as cameras, are not adversely affected. The Stirling convertor pair emitted relatively benign tonal forces at its operational frequency and associated harmonics. Therefore, Stirling power systems will not disturb spacecraft science experiments if minimal appropriate mounting efforts are made. The third test program, performed in February and May 2001, resulted in a modal characterization of a Stirling convertor. Since the deflection of the TDC piston rod, under vibration excitation, was of particular interest, the outer pressure shell was removed to allow access to the rod. Through this testing, the Stirling TDC's natural frequencies and modes were identified. This knowledge advanced our understanding of the successful 1999 vibration test and may be utilized to optimize the output power of future Stirling designs. The fourth test program, in April 2001, was conducted to characterize the structural response of a pair of Stirling convertors, as a function of their mounting interface stiffness. The test results provide guidance for the Stirling power package interface design. Properly designed, the interface may lead to increased structural capability and power performance beyond what was demonstrated in the successful 1999 vibration test. Dynamic testing performed to date at Glenn has shown that the Stirling convertors can withstand liftoff random vibration environments and meet "good neighbor" vibratory emission requirements. Furthermore, the future utilization of the information obtained during the tests will allow the corporation selected to be the Stirling system integrator to optimize their convertor and system interfaces designs. Glenn's Thermo-Mechanical Systems Branch provides Stirling technology expertise under a Space Act Agreement with the Department of Energy. Additional vibration testing by Glenn's Structural Systems Dynamics Branch is planned to continue to demonstrate the Stirling power system's vibration capability as its technology and flight system designs progress.

Species survival and scaling laws in hostile and disordered environments

NASA Astrophysics Data System (ADS)

Rocha, Rodrigo P.; Figueiredo, Wagner; Suweis, Samir; Maritan, Amos

2016-10-01

In this work we study the likelihood of survival of single-species in the context of hostile and disordered environments. Population dynamics in this environment, as modeled by the Fisher equation, is characterized by negative average growth rate, except in some random spatially distributed patches that may support life. In particular, we are interested in the phase diagram of the survival probability and in the critical size problem, i.e., the minimum patch size required for surviving in the long-time dynamics. We propose a measure for the critical patch size as being proportional to the participation ratio of the eigenvector corresponding to the largest eigenvalue of the linearized Fisher dynamics. We obtain the (extinction-survival) phase diagram and the probability distribution function (PDF) of the critical patch sizes for two topologies, namely, the one-dimensional system and the fractal Peano basin. We show that both topologies share the same qualitative features, but the fractal topology requires higher spatial fluctuations to guarantee species survival. We perform a finite-size scaling and we obtain the associated scaling exponents. In addition, we show that the PDF of the critical patch sizes has an universal shape for the 1D case in terms of the model parameters (diffusion, growth rate, etc.). In contrast, the diffusion coefficient has a drastic effect on the PDF of the critical patch sizes of the fractal Peano basin, and it does not obey the same scaling law of the 1D case.

A flexible routing scheme for patients with topographical disorientation.

PubMed

Torres-Solis, Jorge; Chau, Tom

2007-11-28

Individuals with topographical disorientation have difficulty navigating through indoor environments. Recent literature has suggested that ambient intelligence technologies may provide patients with navigational assistance through auditory or graphical instructions delivered via embedded devices. We describe an automatic routing engine for such an ambient intelligence system. The method routes patients with topographical disorientation through indoor environments by repeatedly computing the route of minimal cost from the current location of the patient to a specified destination. The cost of a given path not only reflects the physical distance between end points, but also incorporates individual patient abilities, the presence of mobility-impeding physical barriers within a building and the dynamic nature of the indoor environment. We demonstrate the method by routing simulated patients with either topographical disorientation or physical disabilities. Additionally, we exemplify the ability to route a patient from source to destination while taking into account changes to the building interior. When compared to a random walk, the proposed routing scheme offers potential cost-savings even when the patient follows only a subset of instructions. The routing method presented reduces the navigational effort for patients with topographical disorientation in indoor environments, accounting for physical abilities of the patient, environmental barriers and dynamic building changes. The routing algorithm and database proposed could be integrated into wearable and mobile platforms within the context of an ambient intelligence solution.

Impact of Relative Residence Times in Highly Distinct Environments on the Distribution of Heavy Drinkers

PubMed Central

Mubayi, Anuj; Greenwood, Priscilla E.; Castillo-Chávez, Carlos; Gruenewald, Paul; Gorman, Dennis M.

2009-01-01

Alcohol consumption is a function of social dynamics, environmental contexts, individuals’ preferences and family history. Empirical surveys have focused primarily on identification of risk factors for high-level drinking but have done little to clarify the underlying mechanisms at work. Also, there have been few attempts to apply nonlinear dynamics to the study of these mechanisms and processes at the population level. A simple framework where drinking is modeled as a socially contagious process in low- and high-risk connected environments is introduced. Individuals are classified as light, moderate (assumed mobile), and heavy drinkers. Moderate drinkers provide the link between both environments, that is, they are assumed to be the only individuals drinking in both settings. The focus here is on the effect of moderate drinkers, measured by the proportion of their time spent in “low-” versus “high-” risk drinking environments, on the distribution of drinkers. A simple model within our contact framework predicts that if the relative residence times of moderate drinkers is distributed randomly between low- and high-risk environments then the proportion of heavy drinkers is likely to be higher than expected. However, the full story even in a highly simplified setting is not so simple because “strong” local social mixing tends to increase high-risk drinking on its own. High levels of social interaction between light and moderate drinkers in low-risk environments can diminish the importance of the distribution of relative drinking times on the prevalence of heavy drinking. PMID:20161388

Pricing for a basket of LCDS under fuzzy environments.

PubMed

Wu, Liang; Liu, Jie-Fang; Wang, Jun-Tao; Zhuang, Ya-Ming

2016-01-01

This paper looks at both the prepayment risks of housing mortgage loan credit default swaps (LCDS) as well as the fuzziness and hesitation of investors as regards prepayments by borrowers. It further discusses the first default pricing of a basket of LCDS in a fuzzy environment by using stochastic analysis and triangular intuition-based fuzzy set theory. Through the 'fuzzification' of the sensitivity coefficient in the prepayment intensity, this paper describes the dynamic features of mortgage housing values using the One-factor copula function and concludes with a formula for 'fuzzy' pricing the first default of a basket of LCDS. Using analog simulation to analyze the sensitivity of hesitation, we derive a model that considers what the LCDS fair premium is in a fuzzy environment, including a pure random environment. In addition, the model also shows that a suitable pricing range will give investors more flexible choices and make the predictions of the model closer to real market values.

Homeostatic Agent for General Environment

NASA Astrophysics Data System (ADS)

Yoshida, Naoto

2018-03-01

One of the essential aspect in biological agents is dynamic stability. This aspect, called homeostasis, is widely discussed in ethology, neuroscience and during the early stages of artificial intelligence. Ashby's homeostats are general-purpose learning machines for stabilizing essential variables of the agent in the face of general environments. However, despite their generality, the original homeostats couldn't be scaled because they searched their parameters randomly. In this paper, first we re-define the objective of homeostats as the maximization of a multi-step survival probability from the view point of sequential decision theory and probabilistic theory. Then we show that this optimization problem can be treated by using reinforcement learning algorithms with special agent architectures and theoretically-derived intrinsic reward functions. Finally we empirically demonstrate that agents with our architecture automatically learn to survive in a given environment, including environments with visual stimuli. Our survival agents can learn to eat food, avoid poison and stabilize essential variables through theoretically-derived single intrinsic reward formulations.

Individual Cell Based Traits Obtained by Scanning Flow-Cytometry Show Selection by Biotic and Abiotic Environmental Factors during a Phytoplankton Spring Bloom

PubMed Central

Pomati, Francesco; Kraft, Nathan J. B.; Posch, Thomas; Eugster, Bettina; Jokela, Jukka; Ibelings, Bas W.

2013-01-01

In ecology and evolution, the primary challenge in understanding the processes that shape biodiversity is to assess the relationship between the phenotypic traits of organisms and the environment. Here we tested for selection on physio-morphological traits measured by scanning flow-cytometry at the individual level in phytoplankton communities under a temporally changing biotic and abiotic environment. Our aim was to study how high-frequency temporal changes in the environment influence biodiversity dynamics in a natural community. We focused on a spring bloom in Lake Zurich (Switzerland), characterized by rapid changes in phytoplankton, water conditions, nutrients and grazing (mainly mediated by herbivore ciliates). We described bloom dynamics in terms of taxonomic and trait-based diversity and found that diversity dynamics of trait-based groups were more pronounced than those of identified phytoplankton taxa. We characterized the linkage between measured phytoplankton traits, abiotic environmental factors and abundance of the main grazers and observed weak but significant correlations between changing abiotic and biotic conditions and measured size-related and fluorescence-related traits. We tested for deviations in observed community-wide distributions of focal traits from random patterns and found evidence for both clustering and even spacing of traits, occurring sporadically over the time series. Patterns were consistent with environmental filtering and phenotypic divergence under herbivore pressure, respectively. Size-related traits showed significant even spacing during the peak of herbivore abundance, suggesting that morphology-related traits were under selection from grazing. Pigment distribution within cells and colonies appeared instead to be associated with acclimation to temperature and water chemistry. We found support for trade-offs among grazing resistance and environmental tolerance traits, as well as for substantial periods of dynamics in which our measured traits were not under selection. PMID:23951218

Individual cell based traits obtained by scanning flow-cytometry show selection by biotic and abiotic environmental factors during a phytoplankton spring bloom.

PubMed

Pomati, Francesco; Kraft, Nathan J B; Posch, Thomas; Eugster, Bettina; Jokela, Jukka; Ibelings, Bas W

2013-01-01

In ecology and evolution, the primary challenge in understanding the processes that shape biodiversity is to assess the relationship between the phenotypic traits of organisms and the environment. Here we tested for selection on physio-morphological traits measured by scanning flow-cytometry at the individual level in phytoplankton communities under a temporally changing biotic and abiotic environment. Our aim was to study how high-frequency temporal changes in the environment influence biodiversity dynamics in a natural community. We focused on a spring bloom in Lake Zurich (Switzerland), characterized by rapid changes in phytoplankton, water conditions, nutrients and grazing (mainly mediated by herbivore ciliates). We described bloom dynamics in terms of taxonomic and trait-based diversity and found that diversity dynamics of trait-based groups were more pronounced than those of identified phytoplankton taxa. We characterized the linkage between measured phytoplankton traits, abiotic environmental factors and abundance of the main grazers and observed weak but significant correlations between changing abiotic and biotic conditions and measured size-related and fluorescence-related traits. We tested for deviations in observed community-wide distributions of focal traits from random patterns and found evidence for both clustering and even spacing of traits, occurring sporadically over the time series. Patterns were consistent with environmental filtering and phenotypic divergence under herbivore pressure, respectively. Size-related traits showed significant even spacing during the peak of herbivore abundance, suggesting that morphology-related traits were under selection from grazing. Pigment distribution within cells and colonies appeared instead to be associated with acclimation to temperature and water chemistry. We found support for trade-offs among grazing resistance and environmental tolerance traits, as well as for substantial periods of dynamics in which our measured traits were not under selection.

MODIS Aerosol Optical Depth Bias Adjustment Using Machine Learning Algorithms

NASA Technical Reports Server (NTRS)

Albayrak, Arif; Wei, Jennifer; Petrenko, Maksym; Lary, David; Leptoukh, Gregory

2011-01-01

To monitor the earth atmosphere and its surface changes, satellite based instruments collect continuous data. While some of the data is directly used, some others such as aerosol properties are indirectly retrieved from the observation data. While retrieved variables (RV) form very powerful products, they don't come without obstacles. Different satellite viewing geometries, calibration issues, dynamically changing atmospheric and earth surface conditions, together with complex interactions between observed entities and their environment affect them greatly. This results in random and systematic errors in the final products.

Effects of physical randomness training on virtual and laboratory golf putting performance in novices.

PubMed

Pataky, T C; Lamb, P F

2018-06-01

External randomness exists in all sports but is perhaps most obvious in golf putting where robotic putters sink only 80% of 5 m putts due to unpredictable ball-green dynamics. The purpose of this study was to test whether physical randomness training can improve putting performance in novices. A virtual random-physics golf-putting game was developed based on controlled ball-roll data. Thirty-two subjects were assigned a unique randomness gain (RG) ranging from 0.1 to 2.0-times real-world randomness. Putter face kinematics were measured in 5 m laboratory putts before and after five days of virtual training. Performance was quantified using putt success rate and "miss-adjustment correlation" (MAC), the correlation between left-right miss magnitude and subsequent right-left kinematic adjustments. Results showed no RG-success correlation (r = -0.066, p = 0.719) but mildly stronger correlations with MAC for face angle (r = -0.168, p = 0.358) and clubhead path (r = -0.302, p = 0.093). The strongest RG-MAC correlation was observed during virtual training (r = -0.692, p < 0.001). These results suggest that subjects quickly adapt to physical randomness in virtual training, and also that this learning may weakly transfer to real golf putting kinematics. Adaptation to external physical randomness during virtual training may therefore help golfers adapt to external randomness in real-world environments.

Collective relaxation dynamics of small-world networks

NASA Astrophysics Data System (ADS)

Grabow, Carsten; Grosskinsky, Stefan; Kurths, Jürgen; Timme, Marc

2015-05-01

Complex networks exhibit a wide range of collective dynamic phenomena, including synchronization, diffusion, relaxation, and coordination processes. Their asymptotic dynamics is generically characterized by the local Jacobian, graph Laplacian, or a similar linear operator. The structure of networks with regular, small-world, and random connectivities are reasonably well understood, but their collective dynamical properties remain largely unknown. Here we present a two-stage mean-field theory to derive analytic expressions for network spectra. A single formula covers the spectrum from regular via small-world to strongly randomized topologies in Watts-Strogatz networks, explaining the simultaneous dependencies on network size N , average degree k , and topological randomness q . We present simplified analytic predictions for the second-largest and smallest eigenvalue, and numerical checks confirm our theoretical predictions for zero, small, and moderate topological randomness q , including the entire small-world regime. For large q of the order of one, we apply standard random matrix theory, thereby overarching the full range from regular to randomized network topologies. These results may contribute to our analytic and mechanistic understanding of collective relaxation phenomena of network dynamical systems.

Collective relaxation dynamics of small-world networks.

PubMed

Grabow, Carsten; Grosskinsky, Stefan; Kurths, Jürgen; Timme, Marc

2015-05-01

Complex networks exhibit a wide range of collective dynamic phenomena, including synchronization, diffusion, relaxation, and coordination processes. Their asymptotic dynamics is generically characterized by the local Jacobian, graph Laplacian, or a similar linear operator. The structure of networks with regular, small-world, and random connectivities are reasonably well understood, but their collective dynamical properties remain largely unknown. Here we present a two-stage mean-field theory to derive analytic expressions for network spectra. A single formula covers the spectrum from regular via small-world to strongly randomized topologies in Watts-Strogatz networks, explaining the simultaneous dependencies on network size N, average degree k, and topological randomness q. We present simplified analytic predictions for the second-largest and smallest eigenvalue, and numerical checks confirm our theoretical predictions for zero, small, and moderate topological randomness q, including the entire small-world regime. For large q of the order of one, we apply standard random matrix theory, thereby overarching the full range from regular to randomized network topologies. These results may contribute to our analytic and mechanistic understanding of collective relaxation phenomena of network dynamical systems.

NEDE: an open-source scripting suite for developing experiments in 3D virtual environments.

PubMed

Jangraw, David C; Johri, Ansh; Gribetz, Meron; Sajda, Paul

2014-09-30

As neuroscientists endeavor to understand the brain's response to ecologically valid scenarios, many are leaving behind hyper-controlled paradigms in favor of more realistic ones. This movement has made the use of 3D rendering software an increasingly compelling option. However, mastering such software and scripting rigorous experiments requires a daunting amount of time and effort. To reduce these startup costs and make virtual environment studies more accessible to researchers, we demonstrate a naturalistic experimental design environment (NEDE) that allows experimenters to present realistic virtual stimuli while still providing tight control over the subject's experience. NEDE is a suite of open-source scripts built on the widely used Unity3D game development software, giving experimenters access to powerful rendering tools while interfacing with eye tracking and EEG, randomizing stimuli, and providing custom task prompts. Researchers using NEDE can present a dynamic 3D virtual environment in which randomized stimulus objects can be placed, allowing subjects to explore in search of these objects. NEDE interfaces with a research-grade eye tracker in real-time to maintain precise timing records and sync with EEG or other recording modalities. Python offers an alternative for experienced programmers who feel comfortable mastering and integrating the various toolboxes available. NEDE combines many of these capabilities with an easy-to-use interface and, through Unity's extensive user base, a much more substantial body of assets and tutorials. Our flexible, open-source experimental design system lowers the barrier to entry for neuroscientists interested in developing experiments in realistic virtual environments. Copyright © 2014 Elsevier B.V. All rights reserved.

Early multisensory interactions affect the competition among multiple visual objects.

PubMed

Van der Burg, Erik; Talsma, Durk; Olivers, Christian N L; Hickey, Clayton; Theeuwes, Jan

2011-04-01

In dynamic cluttered environments, audition and vision may benefit from each other in determining what deserves further attention and what does not. We investigated the underlying neural mechanisms responsible for attentional guidance by audiovisual stimuli in such an environment. Event-related potentials (ERPs) were measured during visual search through dynamic displays consisting of line elements that randomly changed orientation. Search accuracy improved when a target orientation change was synchronized with an auditory signal as compared to when the auditory signal was absent or synchronized with a distractor orientation change. The ERP data show that behavioral benefits were related to an early multisensory interaction over left parieto-occipital cortex (50-60 ms post-stimulus onset), which was followed by an early positive modulation (80-100 ms) over occipital and temporal areas contralateral to the audiovisual event, an enhanced N2pc (210-250 ms), and a contralateral negative slow wave (CNSW). The early multisensory interaction was correlated with behavioral search benefits, indicating that participants with a strong multisensory interaction benefited the most from the synchronized auditory signal. We suggest that an auditory signal enhances the neural response to a synchronized visual event, which increases the chances of selection in a multiple object environment. Copyright © 2010 Elsevier Inc. All rights reserved.

Redundant Information and the Quantum-Classical Transition

NASA Astrophysics Data System (ADS)

Riedel, Charles Jess

A state selected at random from the Hilbert space of a many-body system is overwhelmingly likely to exhibit highly non-classical correlations. For these typical states, half of the environment must be measured by an observer to determine the state of a given subsystem. The objectivity of classical reality—the fact that multiple observers can each agree on the state of a subsystem after measuring just a small fraction of its environment—implies that the correlations found in nature between macroscopic systems and their environments are very exceptional. This is understood through the redundant recording of information about the preferred states of a decohering system by its environment, a phenomenon known as quantum Darwinism. To see this in action in the real world, we first consider the ubiquitous case of blackbody illumination. We show that it exhibits fast and extensive proliferation of information about an object into the environment, yielding redundancies orders of magnitude larger than the exactly soluble models considered previously. Turning to a universe of qubits, we examine the conditions needed for the creation of branching states and study their demise through many-body interactions. We show that even constrained dynamics can suppress redundancies to the values typical of random states on relaxation timescales, and prove that these results hold exactly in the thermodynamic limit. Finally, we connect these ideas to the consistent histories framework. Building on the criterion of partial-trace consistency, we introduce a sensible notion of mutual information between a fragment of the universe and a history itself.

Generalized essential energy space random walks to more effectively accelerate solute sampling in aqueous environment

NASA Astrophysics Data System (ADS)

Lv, Chao; Zheng, Lianqing; Yang, Wei

2012-01-01

Molecular dynamics sampling can be enhanced via the promoting of potential energy fluctuations, for instance, based on a Hamiltonian modified with the addition of a potential-energy-dependent biasing term. To overcome the diffusion sampling issue, which reveals the fact that enlargement of event-irrelevant energy fluctuations may abolish sampling efficiency, the essential energy space random walk (EESRW) approach was proposed earlier. To more effectively accelerate the sampling of solute conformations in aqueous environment, in the current work, we generalized the EESRW method to a two-dimension-EESRW (2D-EESRW) strategy. Specifically, the essential internal energy component of a focused region and the essential interaction energy component between the focused region and the environmental region are employed to define the two-dimensional essential energy space. This proposal is motivated by the general observation that in different conformational events, the two essential energy components have distinctive interplays. Model studies on the alanine dipeptide and the aspartate-arginine peptide demonstrate sampling improvement over the original one-dimension-EESRW strategy; with the same biasing level, the present generalization allows more effective acceleration of the sampling of conformational transitions in aqueous solution. The 2D-EESRW generalization is readily extended to higher dimension schemes and employed in more advanced enhanced-sampling schemes, such as the recent orthogonal space random walk method.

Markov stochasticity coordinates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eliazar, Iddo, E-mail: iddo.eliazar@intel.com

Markov dynamics constitute one of the most fundamental models of random motion between the states of a system of interest. Markov dynamics have diverse applications in many fields of science and engineering, and are particularly applicable in the context of random motion in networks. In this paper we present a two-dimensional gauging method of the randomness of Markov dynamics. The method–termed Markov Stochasticity Coordinates–is established, discussed, and exemplified. Also, the method is tweaked to quantify the stochasticity of the first-passage-times of Markov dynamics, and the socioeconomic equality and mobility in human societies.

Soil porosity correlation and its influence in percolation dynamics

NASA Astrophysics Data System (ADS)

Rodriguez, Alfredo; Capa-Morocho, Mirian; Ruis-Ramos, Margarita; Tarquis, Ana M.

2016-04-01

The prediction of percolation in natural soils is relevant for modeling root growth and optimizing infiltration of water and nutrients. Also, it would improve our understanding on how pollutants as pesticides, and virus and bacteria (Darnault et al., 2003) reach significant depths without being filtered out by the soil matrix (Beven and Germann, 2013). Random walk algorithms have been used successfully to date to characterize the dynamical characteristics of disordered media. This approach has been used here to describe how soil at different bulk densities and with different threshold values applied to the 3D gray images influences the structure of the pore network and their implications on particle flow and distribution (Ruiz-Ramos et al., 2009). In order to do so first we applied several threshold values to each image analyzed and characterized them through Hurst exponents, then we computed random walks algorithms to calculate distances reached by the particles and speed of those particles. At the same time, 3D structures with a Hurst exponent of ca 0.5 and with different porosities were constructed and the same random walks simulations were replicated over these generated structures. We have found a relationship between Hurst exponents and the speed distribution of the particles reaching percolation of the total soil depth. REFERENCES Darnault, C.J. G., P. Garnier, Y.J. Kim, K.L. Oveson, T.S. Steenhuis, J.Y. Parlange, M. Jenkins, W.C. Ghiorse, and P. Baveye (2003), Preferential transport of Cryptosporidium parvum oocysts in variably saturated subsurface environments, Water Environ. Res., 75, 113-120. Beven, Keith and Germann, Peter. 2013. Macropores and water flow in soils revisited. Water Resources Research, 49(6), 3071-3092. DOI: 10.1002/wrcr.20156. Ruiz-Ramos, M., D. del Valle, D. Grinev, and A.M. Tarquis. 2009. Soil hydraulic behaviour at different bulk densities. Geophysical Research Abstracts, 11, EGU2009-6234.

Dynamic analysis of a pumped-storage hydropower plant with random power load

NASA Astrophysics Data System (ADS)

Zhang, Hao; Chen, Diyi; Xu, Beibei; Patelli, Edoardo; Tolo, Silvia

2018-02-01

This paper analyzes the dynamic response of a pumped-storage hydropower plant in generating mode. Considering the elastic water column effects in the penstock, a linearized reduced order dynamic model of the pumped-storage hydropower plant is used in this paper. As the power load is always random, a set of random generator electric power output is introduced to research the dynamic behaviors of the pumped-storage hydropower plant. Then, the influences of the PI gains on the dynamic characteristics of the pumped-storage hydropower plant with the random power load are analyzed. In addition, the effects of initial power load and PI parameters on the stability of the pumped-storage hydropower plant are studied in depth. All of the above results will provide theoretical guidance for the study and analysis of the pumped-storage hydropower plant.

Electron spin resonance of nitrogen-vacancy centers in optically trapped nanodiamonds

PubMed Central

Horowitz, Viva R.; Alemán, Benjamín J.; Christle, David J.; Cleland, Andrew N.; Awschalom, David D.

2012-01-01

Using an optical tweezers apparatus, we demonstrate three-dimensional control of nanodiamonds in solution with simultaneous readout of ground-state electron-spin resonance (ESR) transitions in an ensemble of diamond nitrogen-vacancy color centers. Despite the motion and random orientation of nitrogen-vacancy centers suspended in the optical trap, we observe distinct peaks in the measured ESR spectra qualitatively similar to the same measurement in bulk. Accounting for the random dynamics, we model the ESR spectra observed in an externally applied magnetic field to enable dc magnetometry in solution. We estimate the dc magnetic field sensitivity based on variations in ESR line shapes to be approximately . This technique may provide a pathway for spin-based magnetic, electric, and thermal sensing in fluidic environments and biophysical systems inaccessible to existing scanning probe techniques. PMID:22869706

The random continued fraction transformation

NASA Astrophysics Data System (ADS)

Kalle, Charlene; Kempton, Tom; Verbitskiy, Evgeny

2017-03-01

We introduce a random dynamical system related to continued fraction expansions. It uses random combinations of the Gauss map and the Rényi (or backwards) continued fraction map. We explore the continued fraction expansions that this system produces, as well as the dynamical properties of the system.

A complete system for head tracking using motion-based particle filter and randomly perturbed active contour

NASA Astrophysics Data System (ADS)

Bouaynaya, N.; Schonfeld, Dan

2005-03-01

Many real world applications in computer and multimedia such as augmented reality and environmental imaging require an elastic accurate contour around a tracked object. In the first part of the paper we introduce a novel tracking algorithm that combines a motion estimation technique with the Bayesian Importance Sampling framework. We use Adaptive Block Matching (ABM) as the motion estimation technique. We construct the proposal density from the estimated motion vector. The resulting algorithm requires a small number of particles for efficient tracking. The tracking is adaptive to different categories of motion even with a poor a priori knowledge of the system dynamics. Particulary off-line learning is not needed. A parametric representation of the object is used for tracking purposes. In the second part of the paper, we refine the tracking output from a parametric sample to an elastic contour around the object. We use a 1D active contour model based on a dynamic programming scheme to refine the output of the tracker. To improve the convergence of the active contour, we perform the optimization over a set of randomly perturbed initial conditions. Our experiments are applied to head tracking. We report promising tracking results in complex environments.

Phase Transition Behavior in a Neutral Evolution Model

NASA Astrophysics Data System (ADS)

King, Dawn; Scott, Adam; Maric, Nevena; Bahar, Sonya

2014-03-01

The complexity of interactions among individuals and between individuals and the environment make agent based modeling ideal for studying emergent speciation. This is a dynamically complex problem that can be characterized via the critical behavior of a continuous phase transition. Concomitant with the main tenets of natural selection, we allow organisms to reproduce, mutate, and die within a neutral phenotype space. Previous work has shown phase transition behavior in an assortative mating model with variable fitness landscapes as the maximum mutation size (μ) was varied (Dees and Bahar, 2010). Similarly, this behavior was recently presented in the work of Scott et al. (2013), even on a completely neutral landscape, for bacterial-like fission as well as for assortative mating. Here we present another neutral model to investigate the `critical' phase transition behavior of three mating types - assortative, bacterial, and random - in a phenotype space as a function of the percentage of random death. Results show two types of phase transitions occurring for the parameters of the population size and the number of clusters (an analogue of species), indicating different evolutionary dynamics for system survival and clustering. This research was supported by funding from: University of Missouri Research Board and James S. McDonnell Foundation.

Diffusion in randomly perturbed dissipative dynamics

NASA Astrophysics Data System (ADS)

Rodrigues, Christian S.; Chechkin, Aleksei V.; de Moura, Alessandro P. S.; Grebogi, Celso; Klages, Rainer

2014-11-01

Dynamical systems having many coexisting attractors present interesting properties from both fundamental theoretical and modelling points of view. When such dynamics is under bounded random perturbations, the basins of attraction are no longer invariant and there is the possibility of transport among them. Here we introduce a basic theoretical setting which enables us to study this hopping process from the perspective of anomalous transport using the concept of a random dynamical system with holes. We apply it to a simple model by investigating the role of hyperbolicity for the transport among basins. We show numerically that our system exhibits non-Gaussian position distributions, power-law escape times, and subdiffusion. Our simulation results are reproduced consistently from stochastic continuous time random walk theory.

Dynamic defense and network randomization for computer systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chavez, Adrian R.; Stout, William M. S.; Hamlet, Jason R.

The various technologies presented herein relate to determining a network attack is taking place, and further to adjust one or more network parameters such that the network becomes dynamically configured. A plurality of machine learning algorithms are configured to recognize an active attack pattern. Notification of the attack can be generated, and knowledge gained from the detected attack pattern can be utilized to improve the knowledge of the algorithms to detect a subsequent attack vector(s). Further, network settings and application communications can be dynamically randomized, wherein artificial diversity converts control systems into moving targets that help mitigate the early reconnaissancemore » stages of an attack. An attack(s) based upon a known static address(es) of a critical infrastructure network device(s) can be mitigated by the dynamic randomization. Network parameters that can be randomized include IP addresses, application port numbers, paths data packets navigate through the network, application randomization, etc.« less

Random Matrix Theory in molecular dynamics analysis.

PubMed

Palese, Luigi Leonardo

2015-01-01

It is well known that, in some situations, principal component analysis (PCA) carried out on molecular dynamics data results in the appearance of cosine-shaped low index projections. Because this is reminiscent of the results obtained by performing PCA on a multidimensional Brownian dynamics, it has been suggested that short-time protein dynamics is essentially nothing more than a noisy signal. Here we use Random Matrix Theory to analyze a series of short-time molecular dynamics experiments which are specifically designed to be simulations with high cosine content. We use as a model system the protein apoCox17, a mitochondrial copper chaperone. Spectral analysis on correlation matrices allows to easily differentiate random correlations, simply deriving from the finite length of the process, from non-random signals reflecting the intrinsic system properties. Our results clearly show that protein dynamics is not really Brownian also in presence of the cosine-shaped low index projections on principal axes. Copyright © 2014 Elsevier B.V. All rights reserved.

Complementary fMRI and EEG evidence for more efficient neural processing of rhythmic vs. unpredictably timed sounds

PubMed Central

van Atteveldt, Nienke; Musacchia, Gabriella; Zion-Golumbic, Elana; Sehatpour, Pejman; Javitt, Daniel C.; Schroeder, Charles

2015-01-01

The brain’s fascinating ability to adapt its internal neural dynamics to the temporal structure of the sensory environment is becoming increasingly clear. It is thought to be metabolically beneficial to align ongoing oscillatory activity to the relevant inputs in a predictable stream, so that they will enter at optimal processing phases of the spontaneously occurring rhythmic excitability fluctuations. However, some contexts have a more predictable temporal structure than others. Here, we tested the hypothesis that the processing of rhythmic sounds is more efficient than the processing of irregularly timed sounds. To do this, we simultaneously measured functional magnetic resonance imaging (fMRI) and electro-encephalograms (EEG) while participants detected oddball target sounds in alternating blocks of rhythmic (e.g., with equal inter-stimulus intervals) or random (e.g., with randomly varied inter-stimulus intervals) tone sequences. Behaviorally, participants detected target sounds faster and more accurately when embedded in rhythmic streams. The fMRI response in the auditory cortex was stronger during random compared to random tone sequence processing. Simultaneously recorded N1 responses showed larger peak amplitudes and longer latencies for tones in the random (vs. the rhythmic) streams. These results reveal complementary evidence for more efficient neural and perceptual processing during temporally predictable sensory contexts. PMID:26579044

Dynamic Response of an Optomechanical System to a Stationary Random Excitation in the Time Domain

DOE PAGES

Palmer, Jeremy A.; Paez, Thomas L.

2011-01-01

Modern electro-optical instruments are typically designed with assemblies of optomechanical members that support optics such that alignment is maintained in service environments that include random vibration loads. This paper presents a nonlinear numerical analysis that calculates statistics for the peak lateral response of optics in an optomechanical sub-assembly subject to random excitation of the housing. The work is unique in that the prior art does not address peak response probability distribution for stationary random vibration in the time domain for a common lens-retainer-housing system with Coulomb damping. Analytical results are validated by using displacement response data from random vibration testingmore » of representative prototype sub-assemblies. A comparison of predictions to experimental results yields reasonable agreement. The Type I Asymptotic form provides the cumulative distribution function for peak response probabilities. Probabilities are calculated for actual lens centration tolerances. The probability that peak response will not exceed the centration tolerance is greater than 80% for prototype configurations where the tolerance is high (on the order of 30 micrometers). Conversely, the probability is low for those where the tolerance is less than 20 micrometers. The analysis suggests a design paradigm based on the influence of lateral stiffness on the magnitude of the response.« less

Dynamical behavior of the random field on the pulsating and snaking solitons in cubic-quintic complex Ginzburg-Landau equation

NASA Astrophysics Data System (ADS)

Bakhtiar, Nurizatul Syarfinas Ahmad; Abdullah, Farah Aini; Hasan, Yahya Abu

2017-08-01

In this paper, we consider the dynamical behaviour of the random field on the pulsating and snaking solitons in a dissipative systems described by the one-dimensional cubic-quintic complex Ginzburg-Landau equation (cqCGLE). The dynamical behaviour of the random filed was simulated by adding a random field to the initial pulse. Then, we solve it numerically by fixing the initial amplitude profile for the pulsating and snaking solitons without losing any generality. In order to create the random field, we choose 0 ≤ ɛ ≤ 1.0. As a result, multiple soliton trains are formed when the random field is applied to a pulse like initial profile for the parameters of the pulsating and snaking solitons. The results also show the effects of varying the random field of the transient energy peaks in pulsating and snaking solitons.

Analysis of dynamic system response to product random processes

NASA Technical Reports Server (NTRS)

Sidwell, K.

1978-01-01

The response of dynamic systems to the product of two independent Gaussian random processes is developed by use of the Fokker-Planck and associated moment equations. The development is applied to the amplitude modulated process which is used to model atmospheric turbulence in aeronautical applications. The exact solution for the system response is compared with the solution obtained by the quasi-steady approximation which omits the dynamic properties of the random amplitude modulation. The quasi-steady approximation is valid as a limiting case of the exact solution for the dynamic response of linear systems to amplitude modulated processes. In the nonlimiting case the quasi-steady approximation can be invalid for dynamic systems with low damping.

Entanglement dynamics in critical random quantum Ising chain with perturbations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Yichen, E-mail: ychuang@caltech.edu

We simulate the entanglement dynamics in a critical random quantum Ising chain with generic perturbations using the time-evolving block decimation algorithm. Starting from a product state, we observe super-logarithmic growth of entanglement entropy with time. The numerical result is consistent with the analytical prediction of Vosk and Altman using a real-space renormalization group technique. - Highlights: • We study the dynamical quantum phase transition between many-body localized phases. • We simulate the dynamics of a very long random spin chain with matrix product states. • We observe numerically super-logarithmic growth of entanglement entropy with time.

Lotka-Volterra systems in environments with randomly disordered temporal periodicity

NASA Astrophysics Data System (ADS)

Naess, Arvid; Dimentberg, Michael F.; Gaidai, Oleg

2008-08-01

A generalized Lotka-Volterra model for a pair of interacting populations of predators and prey is studied. The model accounts for the prey’s interspecies competition and therefore is asymptotically stable, whereas its oscillatory behavior is induced by temporal variations in environmental conditions simulated by those in the prey’s reproduction rate. Two models of the variations are considered, each of them combining randomness with “hidden” periodicity. The stationary joint probability density function (PDF) of the number of predators and prey is calculated numerically by the path integration (PI) method based on the use of characteristic functions and the fast Fourier transform. The numerical results match those for the asymptotic case of white-noise variations for which an analytical solution is available. Several examples are studied, with calculations of important characteristics of oscillations, for example the expected rate of up-crossings given the level of the predator number. The calculated PDFs may be of predominantly random (unimodal) or predominantly periodic nature (bimodal). Thus, the PI method has been demonstrated to be a powerful tool for studies of the dynamics of predator-prey pairs. The method captures the random oscillations as observed in nature, taking into account potential periodicity in the environmental conditions.

Lotka-Volterra systems in environments with randomly disordered temporal periodicity.

PubMed

Naess, Arvid; Dimentberg, Michael F; Gaidai, Oleg

2008-08-01

A generalized Lotka-Volterra model for a pair of interacting populations of predators and prey is studied. The model accounts for the prey's interspecies competition and therefore is asymptotically stable, whereas its oscillatory behavior is induced by temporal variations in environmental conditions simulated by those in the prey's reproduction rate. Two models of the variations are considered, each of them combining randomness with "hidden" periodicity. The stationary joint probability density function (PDF) of the number of predators and prey is calculated numerically by the path integration (PI) method based on the use of characteristic functions and the fast Fourier transform. The numerical results match those for the asymptotic case of white-noise variations for which an analytical solution is available. Several examples are studied, with calculations of important characteristics of oscillations, for example the expected rate of up-crossings given the level of the predator number. The calculated PDFs may be of predominantly random (unimodal) or predominantly periodic nature (bimodal). Thus, the PI method has been demonstrated to be a powerful tool for studies of the dynamics of predator-prey pairs. The method captures the random oscillations as observed in nature, taking into account potential periodicity in the environmental conditions.

Chance vs. necessity in living systems: a false antinomy.

PubMed

Buiatti, Marcello; Buiatti, Marco

2008-01-01

The concepts of order and randomness are crucial to understand 'living systems' structural and dynamical rules. In the history of biology, they lay behind the everlasting debate on the relative roles of chance and determinism in evolution. Jacques Monod [1970] built a theory where chance (randomness) and determinism (order) were considered as two complementary aspects of life. In the present paper, we will give an up to date version of the problem going beyond the dichotomy between chance and determinism. To this end, we will first see how the view on living systems has evolved from the mechanistic one of the 19th century to the one stemming from the most recent literature, where they emerge as complex systems continuously evolving through multiple interactions among their components and with the surrounding environment. We will then report on the ever increasing evidence of "friendly" co-existence in living beings between a number of "variability generators", fixed by evolution, and the "spontaneous order" derived from interactions between components. We will propose that the "disorder" generated is "benevolent" because it allows living systems to rapidly adapt to changes in the environment by continuously changing, while keeping their internal harmony.

On salesmen and tourists: Two-step optimization in deterministic foragers

NASA Astrophysics Data System (ADS)

Maya, Miguel; Miramontes, Octavio; Boyer, Denis

2017-02-01

We explore a two-step optimization problem in random environments, the so-called restaurant-coffee shop problem, where a walker aims at visiting the nearest and better restaurant in an area and then move to the nearest and better coffee-shop. This is an extension of the Tourist Problem, a one-step optimization dynamics that can be viewed as a deterministic walk in a random medium. A certain amount of heterogeneity in the values of the resources to be visited causes the emergence of power-laws distributions for the steps performed by the walker, similarly to a Lévy flight. The fluctuations of the step lengths tend to decrease as a consequence of multiple-step planning, thus reducing the foraging uncertainty. We find that the first and second steps of each planned movement play very different roles in heterogeneous environments. The two-step process improves only slightly the foraging efficiency compared to the one-step optimization, at a much higher computational cost. We discuss the implications of these findings for animal and human mobility, in particular in relation to the computational effort that informed agents should deploy to solve search problems.

Stochasticity and determinism in models of hematopoiesis.

PubMed

Kimmel, Marek

2014-01-01

This chapter represents a novel view of modeling in hematopoiesis, synthesizing both deterministic and stochastic approaches. Whereas the stochastic models work in situations where chance dominates, for example when the number of cells is small, or under random mutations, the deterministic models are more important for large-scale, normal hematopoiesis. New types of models are on the horizon. These models attempt to account for distributed environments such as hematopoietic niches and their impact on dynamics. Mixed effects of such structures and chance events are largely unknown and constitute both a challenge and promise for modeling. Our discussion is presented under the separate headings of deterministic and stochastic modeling; however, the connections between both are frequently mentioned. Four case studies are included to elucidate important examples. We also include a primer of deterministic and stochastic dynamics for the reader's use.

A Comparison of Three Random Number Generators for Aircraft Dynamic Modeling Applications

NASA Technical Reports Server (NTRS)

Grauer, Jared A.

2017-01-01

Three random number generators, which produce Gaussian white noise sequences, were compared to assess their suitability in aircraft dynamic modeling applications. The first generator considered was the MATLAB (registered) implementation of the Mersenne-Twister algorithm. The second generator was a website called Random.org, which processes atmospheric noise measured using radios to create the random numbers. The third generator was based on synthesis of the Fourier series, where the random number sequences are constructed from prescribed amplitude and phase spectra. A total of 200 sequences, each having 601 random numbers, for each generator were collected and analyzed in terms of the mean, variance, normality, autocorrelation, and power spectral density. These sequences were then applied to two problems in aircraft dynamic modeling, namely estimating stability and control derivatives from simulated onboard sensor data, and simulating flight in atmospheric turbulence. In general, each random number generator had good performance and is well-suited for aircraft dynamic modeling applications. Specific strengths and weaknesses of each generator are discussed. For Monte Carlo simulation, the Fourier synthesis method is recommended because it most accurately and consistently approximated Gaussian white noise and can be implemented with reasonable computational effort.

Toward a Dynamically Reconfigurable Computing and Communication System for Small Spacecraft

NASA Technical Reports Server (NTRS)

Kifle, Muli; Andro, Monty; Tran, Quang K.; Fujikawa, Gene; Chu, Pong P.

2003-01-01

Future science missions will require the use of multiple spacecraft with multiple sensor nodes autonomously responding and adapting to a dynamically changing space environment. The acquisition of random scientific events will require rapidly changing network topologies, distributed processing power, and a dynamic resource management strategy. Optimum utilization and configuration of spacecraft communications and navigation resources will be critical in meeting the demand of these stringent mission requirements. There are two important trends to follow with respect to NASA's (National Aeronautics and Space Administration) future scientific missions: the use of multiple satellite systems and the development of an integrated space communications network. Reconfigurable computing and communication systems may enable versatile adaptation of a spacecraft system's resources by dynamic allocation of the processor hardware to perform new operations or to maintain functionality due to malfunctions or hardware faults. Advancements in FPGA (Field Programmable Gate Array) technology make it possible to incorporate major communication and network functionalities in FPGA chips and provide the basis for a dynamically reconfigurable communication system. Advantages of higher computation speeds and accuracy are envisioned with tremendous hardware flexibility to ensure maximum survivability of future science mission spacecraft. This paper discusses the requirements, enabling technologies, and challenges associated with dynamically reconfigurable space communications systems.

Radiation Test Challenges for Scaled Commerical Memories

NASA Technical Reports Server (NTRS)

LaBel, Kenneth A.; Ladbury, Ray L.; Cohn, Lewis M.; Oldham, Timothy

2007-01-01

As sub-100nm CMOS technologies gather interest, the radiation effects performance of these technologies provide a significant challenge. In this talk, we shall discuss the radiation testing challenges as related to commercial memory devices. The focus will be on complex test and failure modes emerging in state-of-the-art Flash non-volatile memories (NVMs) and synchronous dynamic random access memories (SDRAMs), which are volatile. Due to their very high bit density, these device types are highly desirable for use in the natural space environment. In this presentation, we shall discuss these devices with emphasis on considerations for test and qualification methods required.

Computed narrow-band azimuthal time-reversing array retrofocusing in shallow water.

PubMed

Dungan, M R; Dowling, D R

2001-10-01

The process of acoustic time reversal sends sound waves back to their point of origin in reciprocal acoustic environments even when the acoustic environment is unknown. The properties of the time-reversed field commonly depend on the frequency of the original signal, the characteristics of the acoustic environment, and the configuration of the time-reversing transducer array (TRA). In particular, vertical TRAs are predicted to produce horizontally confined foci in environments containing random volume refraction. This article validates and extends this prediction to shallow water environments via monochromatic Monte Carlo propagation simulations (based on parabolic equation computations using RAM). The computational results determine the azimuthal extent of a TRA's retrofocus in shallow-water sound channels either having random bottom roughness or containing random internal-wave-induced sound speed fluctuations. In both cases, randomness in the environment may reduce the predicted azimuthal angular width of the vertical TRA retrofocus to as little as several degrees (compared to 360 degrees for uniform environments) for source-array ranges from 5 to 20 km at frequencies from 500 Hz to 2 kHz. For both types of randomness, power law scalings are found to collapse the calculated azimuthal retrofocus widths for shallow sources over a variety of acoustic frequencies, source-array ranges, water column depths, and random fluctuation amplitudes and correlation scales. Comparisons are made between retrofocusing on shallow and deep sources, and in strongly and mildly absorbing environments.

Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies.

PubMed

Häggström, Ida; Beattie, Bradley J; Schmidtlein, C Ross

2016-06-01

To develop and evaluate a fast and simple tool called dpetstep (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. The tool was developed in matlab using both new and previously reported modules of petstep (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuation are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). dpetstep was 8000 times faster than MC. Dynamic images from dpetstep had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dpetstep and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dpetstep images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p < 0.01). Compared to GAUSS, dpetstep images and noise properties agreed better with MC. The authors have developed a fast and easy one-stop solution for simulations of dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dpetstep to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for studies investigating these phenomena. dpetstep can be downloaded free of cost from https://github.com/CRossSchmidtlein/dPETSTEP.

RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis.

PubMed

Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

2012-01-01

RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. http://www.cemb.edu.pk/sw.html RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language.

Communication: Memory effects and active Brownian diffusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghosh, Pulak K.; Li, Yunyun, E-mail: yunyunli@tongji.edu.cn; Marchegiani, Giampiero

A self-propelled artificial microswimmer is often modeled as a ballistic Brownian particle moving with constant speed aligned along one of its axis, but changing direction due to random collisions with the environment. Similarly to thermal noise, its angular randomization is described as a memoryless stochastic process. Here, we speculate that finite-time correlations in the orientational dynamics can affect the swimmer’s diffusivity. To this purpose, we propose and solve two alternative models. In the first one, we simply assume that the environmental fluctuations governing the swimmer’s propulsion are exponentially correlated in time, whereas in the second one, we account for possiblemore » damped fluctuations of the propulsion velocity around the swimmer’s axis. The corresponding swimmer’s diffusion constants are predicted to get, respectively, enhanced or suppressed upon increasing the model memory time. Possible consequences of this effect on the interpretation of the experimental data are discussed.« less

Communication: Memory effects and active Brownian diffusion

NASA Astrophysics Data System (ADS)

Ghosh, Pulak K.; Li, Yunyun; Marchegiani, Giampiero; Marchesoni, Fabio

2015-12-01

A self-propelled artificial microswimmer is often modeled as a ballistic Brownian particle moving with constant speed aligned along one of its axis, but changing direction due to random collisions with the environment. Similarly to thermal noise, its angular randomization is described as a memoryless stochastic process. Here, we speculate that finite-time correlations in the orientational dynamics can affect the swimmer's diffusivity. To this purpose, we propose and solve two alternative models. In the first one, we simply assume that the environmental fluctuations governing the swimmer's propulsion are exponentially correlated in time, whereas in the second one, we account for possible damped fluctuations of the propulsion velocity around the swimmer's axis. The corresponding swimmer's diffusion constants are predicted to get, respectively, enhanced or suppressed upon increasing the model memory time. Possible consequences of this effect on the interpretation of the experimental data are discussed.

Effect of Stochastic Charge Fluctuations on Dust Dynamics

NASA Astrophysics Data System (ADS)

Matthews, Lorin; Shotorban, Babak; Hyde, Truell

2017-10-01

The charging of particles in a plasma environment occurs through the collection of electrons and ions on the particle surface. Depending on the particle size and the plasma density, the standard deviation of the number of collected elementary charges, which fluctuates due to the randomness in times of collisions with electrons or ions, may be a significant fraction of the equilibrium charge. We use a discrete stochastic charging model to simulate the variations in charge across the dust surface as well as in time. The resultant asymmetric particle potentials, even for spherical grains, has a significant impact on the particle coagulation rate as well as the structure of the resulting aggregates. We compare the effects on particle collisions and growth in typical laboratory and astrophysical plasma environments. This work was supported by the National Science Foundation under Grant PHY-1414523.

Dynamics of a Landau-Zener transitions in a two-level system driven by a dissipative environment

NASA Astrophysics Data System (ADS)

Ateuafack, M. E.; Diffo, J. T.; Fai, L. C.

2016-02-01

The paper investigates the effects of a two-level quantum system coupled to transversal and longitudinal dissipative environment. The time-dependent phase accumulation, LZ transition probability and entropy in the presence of fast-ohmic, sub-ohmic and super-ohmic quantum noise are derived. Analytical results are obtained in terms of temperature, dissipation strength, LZ parameter and bath cutoff frequency. The bath is observed to modify the standard occupation difference by a decaying random phase factor and also produces dephasing during the transfer of population. The dephasing characteristics or the initial non-zero decoherence rate are observed to increase in time with the bath temperature and depend on the system-bath coupling strength and cutoff frequency. These parameters are found to strongly affect the memory and thus tailor the coherence process of the system.

Cavity master equation for the continuous time dynamics of discrete-spin models.

PubMed

Aurell, E; Del Ferraro, G; Domínguez, E; Mulet, R

2017-05-01

We present an alternate method to close the master equation representing the continuous time dynamics of interacting Ising spins. The method makes use of the theory of random point processes to derive a master equation for local conditional probabilities. We analytically test our solution studying two known cases, the dynamics of the mean-field ferromagnet and the dynamics of the one-dimensional Ising system. We present numerical results comparing our predictions with Monte Carlo simulations in three different models on random graphs with finite connectivity: the Ising ferromagnet, the random field Ising model, and the Viana-Bray spin-glass model.

Cavity master equation for the continuous time dynamics of discrete-spin models

NASA Astrophysics Data System (ADS)

Aurell, E.; Del Ferraro, G.; Domínguez, E.; Mulet, R.

2017-05-01

We present an alternate method to close the master equation representing the continuous time dynamics of interacting Ising spins. The method makes use of the theory of random point processes to derive a master equation for local conditional probabilities. We analytically test our solution studying two known cases, the dynamics of the mean-field ferromagnet and the dynamics of the one-dimensional Ising system. We present numerical results comparing our predictions with Monte Carlo simulations in three different models on random graphs with finite connectivity: the Ising ferromagnet, the random field Ising model, and the Viana-Bray spin-glass model.

Statistical mechanics of a single particle in a multiscale random potential: Parisi landscapes in finite-dimensional Euclidean spaces

NASA Astrophysics Data System (ADS)

Fyodorov, Yan V.; Bouchaud, Jean-Philippe

2008-08-01

We construct an N-dimensional Gaussian landscape with multiscale, translation invariant, logarithmic correlations and investigate the statistical mechanics of a single particle in this environment. In the limit of high dimension N → ∞ the free energy of the system and overlap function are calculated exactly using the replica trick and Parisi's hierarchical ansatz. In the thermodynamic limit, we recover the most general version of the Derrida's generalized random energy model (GREM). The low-temperature behaviour depends essentially on the spectrum of length scales involved in the construction of the landscape. If the latter consists of K discrete values, the system is characterized by a K-step replica symmetry breaking solution. We argue that our construction is in fact valid in any finite spatial dimensions N >= 1. We discuss the implications of our results for the singularity spectrum describing multifractality of the associated Boltzmann-Gibbs measure. Finally we discuss several generalizations and open problems, such as the dynamics in such a landscape and the construction of a generalized multifractal random walk.

Hybrid time-variant reliability estimation for active control structures under aleatory and epistemic uncertainties

NASA Astrophysics Data System (ADS)

Wang, Lei; Xiong, Chuang; Wang, Xiaojun; Li, Yunlong; Xu, Menghui

2018-04-01

Considering that multi-source uncertainties from inherent nature as well as the external environment are unavoidable and severely affect the controller performance, the dynamic safety assessment with high confidence is of great significance for scientists and engineers. In view of this, the uncertainty quantification analysis and time-variant reliability estimation corresponding to the closed-loop control problems are conducted in this study under a mixture of random, interval, and convex uncertainties. By combining the state-space transformation and the natural set expansion, the boundary laws of controlled response histories are first confirmed with specific implementation of random items. For nonlinear cases, the collocation set methodology and fourth Rounge-Kutta algorithm are introduced as well. Enlightened by the first-passage model in random process theory as well as by the static probabilistic reliability ideas, a new definition of the hybrid time-variant reliability measurement is provided for the vibration control systems and the related solution details are further expounded. Two engineering examples are eventually presented to demonstrate the validity and applicability of the methodology developed.

The response of rotating machinery to external random vibration

NASA Technical Reports Server (NTRS)

Tessarzik, J. M.; Chiang, T.; Badgley, R. H.

1974-01-01

A high-speed turbogenerator employing gas-lubricated hydrodynamic journal and thrust bearings was subjected to external random vibrations for the purpose of assessing bearing performance in a dynamic environment. The pivoted-pad type journal bearings and the step-sector thrust bearing supported a turbine-driven rotor weighing approximately twenty-one pounds at a nominal operating speed of 36,000 rpm. The response amplitudes of both the rigid-supported and flexible-supported bearing pads, the gimballed thrust bearing, and the rotor relative to the machine casing were measured with capacitance type displacement probes. Random vibrations were applied by means of a large electrodynamic shaker at input levels ranging between 0.5 g (rms) and 1.5 g (rms). Vibrations were applied both along and perpendicular to the rotor axis. Response measurements were analyzed for amplitude distribution and power spectral density. Experimental results compare well with calculations of amplitude power spectral density made for the case where the vibrations were applied along the rotor axis. In this case, the rotor-bearing system was treated as a linear, three-mass model.

Fractal and Chaos Analysis for Dynamics of Radon Exhalation from Uranium Mill Tailings

NASA Astrophysics Data System (ADS)

Li, Yongmei; Tan, Wanyu; Tan, Kaixuan; Liu, Zehua; Xie, Yanshi

2016-08-01

Tailings from mining and milling of uranium ores potentially are large volumes of low-level radioactive materials. A typical environmental problem associated with uranium tailings is radon exhalation, which can significantly pose risks to environment and human health. In order to reduce these risks, it is essential to study the dynamical nature and underlying mechanism of radon exhalation from uranium mill tailings. This motivates the conduction of this study, which is based on the fractal and chaotic methods (e.g. calculating the Hurst exponent, Lyapunov exponent and correlation dimension) and laboratory experiments of the radon exhalation rates. The experimental results show that the radon exhalation rate from uranium mill tailings is highly oscillated. In addition, the nonlinear analyses of the time series of radon exhalation rate demonstrate the following points: (1) the value of Hurst exponent much larger than 0.5 indicates non-random behavior of the radon time series; (2) the positive Lyapunov exponent and non-integer correlation dimension of the time series imply that the radon exhalation from uranium tailings is a chaotic dynamical process; (3) the required minimum number of variables should be five to describe the time evolution of radon exhalation. Therefore, it can be concluded that the internal factors, including heterogeneous distribution of radium, and randomness of radium decay, as well as the fractal characteristics of the tailings, can result in the chaotic evolution of radon exhalation from the tailings.

Space-by-time manifold representation of dynamic facial expressions for emotion categorization

PubMed Central

Delis, Ioannis; Chen, Chaona; Jack, Rachael E.; Garrod, Oliver G. B.; Panzeri, Stefano; Schyns, Philippe G.

2016-01-01

Visual categorization is the brain computation that reduces high-dimensional information in the visual environment into a smaller set of meaningful categories. An important problem in visual neuroscience is to identify the visual information that the brain must represent and then use to categorize visual inputs. Here we introduce a new mathematical formalism—termed space-by-time manifold decomposition—that describes this information as a low-dimensional manifold separable in space and time. We use this decomposition to characterize the representations used by observers to categorize the six classic facial expressions of emotion (happy, surprise, fear, disgust, anger, and sad). By means of a Generative Face Grammar, we presented random dynamic facial movements on each experimental trial and used subjective human perception to identify the facial movements that correlate with each emotion category. When the random movements projected onto the categorization manifold region corresponding to one of the emotion categories, observers categorized the stimulus accordingly; otherwise they selected “other.” Using this information, we determined both the Action Unit and temporal components whose linear combinations lead to reliable categorization of each emotion. In a validation experiment, we confirmed the psychological validity of the resulting space-by-time manifold representation. Finally, we demonstrated the importance of temporal sequencing for accurate emotion categorization and identified the temporal dynamics of Action Unit components that cause typical confusions between specific emotions (e.g., fear and surprise) as well as those resolving these confusions. PMID:27305521

Benefits of Spacecraft Level Vibration Testing

NASA Technical Reports Server (NTRS)

Gordon, Scott; Kern, Dennis L.

2015-01-01

NASA-HDBK-7008 Spacecraft Level Dynamic Environments Testing discusses the approaches, benefits, dangers, and recommended practices for spacecraft level dynamic environments testing, including vibration testing. This paper discusses in additional detail the benefits and actual experiences of vibration testing spacecraft for NASA Goddard Space Flight Center (GSFC) and Jet Propulsion Laboratory (JPL) flight projects. JPL and GSFC have both similarities and differences in their spacecraft level vibration test approach: JPL uses a random vibration input and a frequency range usually starting at 5 Hz and extending to as high as 250 Hz. GSFC uses a sine sweep vibration input and a frequency range usually starting at 5 Hz and extending only to the limits of the coupled loads analysis (typically 50 to 60 Hz). However, both JPL and GSFC use force limiting to realistically notch spacecraft resonances and response (acceleration) limiting as necessary to protect spacecraft structure and hardware from exceeding design strength capabilities. Despite GSFC and JPL differences in spacecraft level vibration test approaches, both have uncovered a significant number of spacecraft design and workmanship anomalies in vibration tests. This paper will give an overview of JPL and GSFC spacecraft vibration testing approaches and provide a detailed description of spacecraft anomalies revealed.

ESTIMATION OF THE SPACE SHUTTLE ROLLOUT FORCING FUNCTION

NASA Technical Reports Server (NTRS)

James, George H., III; Carne, Thomas; Elliott, Kenny; Wilson, Bruce

2005-01-01

The Space Shuttle Vehicle is assembled in the Vertical Assembly Building (VAB) at Kennedy Space Flight Center in Florida. The Vehicle is stacked on a Mobile Launch Platform (MLP) that weighs eight million pounds. A Crawler Transporter (CT) then carries the MLP and the stacked vehicle (12 million pounds total weight) to the launch complex located 5 miles away. This operation is performed at 0.9 mph resulting in a 4.5-hour transport. A recent test was performed to monitor the dynamic environment that was produced during rollout. It was found that the rollout is a harmonic-rich dynamic environment that was previously not understood. This paper will describe work that has been performed to estimate the forcing function that is produced in the transportation process. The rollout analysis team has determined that there are two families of harmonics of the drive train, which excite the system as a function of CT speed. There are also excitation sources, which are random or narrow-band in frequency and are not a function of CT speed. This presentation will discuss the application of the Sum of Weighted Accelerations Technique (SWAT) to further refine this understanding by estimating the forces and moments at the center-of-mass.

75 FR 44283 - In the Matter of Certain Dynamic Random Access Memory Semiconductors and Products Containing Same...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-28

... Random Access Memory Semiconductors and Products Containing Same, Including Memory Modules; Notice of a... importation of certain dynamic random access memory semiconductors and products containing same, including memory modules, by reason of infringement of certain claims of U.S. Patent Nos. 5,480,051; 5,422,309; 5...

Tracer diffusion in a sea of polymers with binding zones: mobile vs. frozen traps.

PubMed

Samanta, Nairhita; Chakrabarti, Rajarshi

2016-10-19

We use molecular dynamics simulations to investigate the tracer diffusion in a sea of polymers with specific binding zones for the tracer. These binding zones act as traps. Our simulations show that the tracer can undergo normal yet non-Gaussian diffusion under certain circumstances, e.g., when the polymers with traps are frozen in space and the volume fraction and the binding strength of the traps are moderate. In this case, as the tracer moves, it experiences a heterogeneous environment and exhibits confined continuous time random walk (CTRW) like motion resulting in a non-Gaussian behavior. Also the long time dynamics becomes subdiffusive as the number or the binding strength of the traps increases. However, if the polymers are mobile then the tracer dynamics is Gaussian but could be normal or subdiffusive depending on the number and the binding strength of the traps. In addition, with increasing binding strength and number of polymer traps, the probability of the tracer being trapped increases. On the other hand, removing the binding zones does not result in trapping, even at comparatively high crowding. Our simulations also show that the trapping probability increases with the increasing size of the tracer and for a bigger tracer with the frozen polymer background the dynamics is only weakly non-Gaussian but highly subdiffusive. Our observations are in the same spirit as found in many recent experiments on tracer diffusion in polymeric materials and question the validity of using Gaussian theory to describe diffusion in a crowded environment in general.

Continuous-time quantum random walks require discrete space

NASA Astrophysics Data System (ADS)

Manouchehri, K.; Wang, J. B.

2007-11-01

Quantum random walks are shown to have non-intuitive dynamics which makes them an attractive area of study for devising quantum algorithms for long-standing open problems as well as those arising in the field of quantum computing. In the case of continuous-time quantum random walks, such peculiar dynamics can arise from simple evolution operators closely resembling the quantum free-wave propagator. We investigate the divergence of quantum walk dynamics from the free-wave evolution and show that, in order for continuous-time quantum walks to display their characteristic propagation, the state space must be discrete. This behavior rules out many continuous quantum systems as possible candidates for implementing continuous-time quantum random walks.

Random Vibrations

NASA Technical Reports Server (NTRS)

Messaro. Semma; Harrison, Phillip

2010-01-01

Ares I Zonal Random vibration environments due to acoustic impingement and combustion processes are develop for liftoff, ascent and reentry. Random Vibration test criteria for Ares I Upper Stage pyrotechnic components are developed by enveloping the applicable zonal environments where each component is located. Random vibration tests will be conducted to assure that these components will survive and function appropriately after exposure to the expected vibration environments. Methodology: Random Vibration test criteria for Ares I Upper Stage pyrotechnic components were desired that would envelope all the applicable environments where each component was located. Applicable Ares I Vehicle drawings and design information needed to be assessed to determine the location(s) for each component on the Ares I Upper Stage. Design and test criteria needed to be developed by plotting and enveloping the applicable environments using Microsoft Excel Spreadsheet Software and documenting them in a report Using Microsoft Word Processing Software. Conclusion: Random vibration liftoff, ascent, and green run design & test criteria for the Upper Stage Pyrotechnic Components were developed by using Microsoft Excel to envelope zonal environments applicable to each component. Results were transferred from Excel into a report using Microsoft Word. After the report is reviewed and edited by my mentor it will be submitted for publication as an attachment to a memorandum. Pyrotechnic component designers will extract criteria from my report for incorporation into the design and test specifications for components. Eventually the hardware will be tested to the environments I developed to assure that the components will survive and function appropriately after exposure to the expected vibration environments.

Dynamic fair node spectrum allocation for ad hoc networks using random matrices

NASA Astrophysics Data System (ADS)

Rahmes, Mark; Lemieux, George; Chester, Dave; Sonnenberg, Jerry

2015-05-01

Dynamic Spectrum Access (DSA) is widely seen as a solution to the problem of limited spectrum, because of its ability to adapt the operating frequency of a radio. Mobile Ad Hoc Networks (MANETs) can extend high-capacity mobile communications over large areas where fixed and tethered-mobile systems are not available. In one use case with high potential impact, cognitive radio employs spectrum sensing to facilitate the identification of allocated frequencies not currently accessed by their primary users. Primary users own the rights to radiate at a specific frequency and geographic location, while secondary users opportunistically attempt to radiate at a specific frequency when the primary user is not using it. We populate a spatial radio environment map (REM) database with known information that can be leveraged in an ad hoc network to facilitate fair path use of the DSA-discovered links. Utilization of high-resolution geospatial data layers in RF propagation analysis is directly applicable. Random matrix theory (RMT) is useful in simulating network layer usage in nodes by a Wishart adjacency matrix. We use the Dijkstra algorithm for discovering ad hoc network node connection patterns. We present a method for analysts to dynamically allocate node-node path and link resources using fair division. User allocation of limited resources as a function of time must be dynamic and based on system fairness policies. The context of fair means that first available request for an asset is not envied as long as it is not yet allocated or tasked in order to prevent cycling of the system. This solution may also save money by offering a Pareto efficient repeatable process. We use a water fill queue algorithm to include Shapley value marginal contributions for allocation.

Parabolic Anderson Model in a Dynamic Random Environment: Random Conductances

NASA Astrophysics Data System (ADS)

Erhard, D.; den Hollander, F.; Maillard, G.

2016-06-01

The parabolic Anderson model is defined as the partial differential equation ∂ u( x, t)/ ∂ t = κ Δ u( x, t) + ξ( x, t) u( x, t), x ∈ ℤ d , t ≥ 0, where κ ∈ [0, ∞) is the diffusion constant, Δ is the discrete Laplacian, and ξ is a dynamic random environment that drives the equation. The initial condition u( x, 0) = u 0( x), x ∈ ℤ d , is typically taken to be non-negative and bounded. The solution of the parabolic Anderson equation describes the evolution of a field of particles performing independent simple random walks with binary branching: particles jump at rate 2 d κ, split into two at rate ξ ∨ 0, and die at rate (- ξ) ∨ 0. In earlier work we looked at the Lyapunov exponents λ p(κ ) = limlimits _{tto ∞} 1/t log {E} ([u(0,t)]p)^{1/p}, quad p in {N} , qquad λ 0(κ ) = limlimits _{tto ∞} 1/2 log u(0,t). For the former we derived quantitative results on the κ-dependence for four choices of ξ : space-time white noise, independent simple random walks, the exclusion process and the voter model. For the latter we obtained qualitative results under certain space-time mixing conditions on ξ. In the present paper we investigate what happens when κΔ is replaced by Δ𝓚, where 𝓚 = {𝓚( x, y) : x, y ∈ ℤ d , x ˜ y} is a collection of random conductances between neighbouring sites replacing the constant conductances κ in the homogeneous model. We show that the associated annealed Lyapunov exponents λ p (𝓚), p ∈ ℕ, are given by the formula λ p({K} ) = {sup} {λ p(κ ) : κ in {Supp} ({K} )}, where, for a fixed realisation of 𝓚, Supp(𝓚) is the set of values taken by the 𝓚-field. We also show that for the associated quenched Lyapunov exponent λ 0(𝓚) this formula only provides a lower bound, and we conjecture that an upper bound holds when Supp(𝓚) is replaced by its convex hull. Our proof is valid for three classes of reversible ξ, and for all 𝓚 satisfying a certain clustering property, namely, there are arbitrarily large balls where 𝓚 is almost constant and close to any value in Supp(𝓚). What our result says is that the annealed Lyapunov exponents are controlled by those pockets of 𝓚 where the conductances are close to the value that maximises the growth in the homogeneous setting. In contrast our conjecture says that the quenched Lyapunov exponent is controlled by a mixture of pockets of 𝓚 where the conductances are nearly constant. Our proof is based on variational representations and confinement arguments.

Recovering full coherence in a qubit by measuring half of its environment

NASA Astrophysics Data System (ADS)

Miatto, Filippo M.; Piché, Kevin; Brougham, Thomas; Boyd, Robert W.

2015-12-01

When a quantum system interacts with its environment it may incur in decoherence. Quantum erasure makes it possible to restore coherence in a system by gaining information about its environment, but measuring the whole of it may be prohibitive: Realistically, one might be forced to address only an accessible subspace and neglect the rest. In such a case, under what conditions will quantum erasure still be effective? In this work we compute analytically the largest recoverable coherence of a random qubit plus environment state and we show that it approaches 100% with overwhelmingly high probability as long as the dimension of the accessible subspace of the environment is larger than √{D }, where D is the dimension of the whole environment. Additionally, we find a sharp transition between a linear behavior and a power-law behavior as soon as the dimension of the inaccessible environment exceeds the dimension of the accessible one. Our results imply that the typical states of a qubit plus environment system admit a measurement spanning only about √{D } degrees of freedom, any outcome of which projects the qubit on a maximally coherent state. This suggests, for instance, that in the dynamics of open quantum systems, if the interactions are known, it would in principle be possible to gain sufficient information and restore coherence in a qubit by dealing with a fraction of the physical resources.

Feynman-Kac formula for stochastic hybrid systems.

PubMed

Bressloff, Paul C

2017-01-01

We derive a Feynman-Kac formula for functionals of a stochastic hybrid system evolving according to a piecewise deterministic Markov process. We first derive a stochastic Liouville equation for the moment generator of the stochastic functional, given a particular realization of the underlying discrete Markov process; the latter generates transitions between different dynamical equations for the continuous process. We then analyze the stochastic Liouville equation using methods recently developed for diffusion processes in randomly switching environments. In particular, we obtain dynamical equations for the moment generating function, averaged with respect to realizations of the discrete Markov process. The resulting Feynman-Kac formula takes the form of a differential Chapman-Kolmogorov equation. We illustrate the theory by calculating the occupation time for a one-dimensional velocity jump process on the infinite or semi-infinite real line. Finally, we present an alternative derivation of the Feynman-Kac formula based on a recent path-integral formulation of stochastic hybrid systems.

Dynamic heterogeneity and non-Gaussian statistics for acetylcholine receptors on live cell membrane

NASA Astrophysics Data System (ADS)

He, W.; Song, H.; Su, Y.; Geng, L.; Ackerson, B. J.; Peng, H. B.; Tong, P.

2016-05-01

The Brownian motion of molecules at thermal equilibrium usually has a finite correlation time and will eventually be randomized after a long delay time, so that their displacement follows the Gaussian statistics. This is true even when the molecules have experienced a complex environment with a finite correlation time. Here, we report that the lateral motion of the acetylcholine receptors on live muscle cell membranes does not follow the Gaussian statistics for normal Brownian diffusion. From a careful analysis of a large volume of the protein trajectories obtained over a wide range of sampling rates and long durations, we find that the normalized histogram of the protein displacements shows an exponential tail, which is robust and universal for cells under different conditions. The experiment indicates that the observed non-Gaussian statistics and dynamic heterogeneity are inherently linked to the slow-active remodelling of the underlying cortical actin network.

Climate variability, rice production and groundwater depletion in India

NASA Astrophysics Data System (ADS)

Bhargava, Alok

2018-03-01

This paper modeled the proximate determinants of rice outputs and groundwater depths in 27 Indian states during 1980-2010. Dynamic random effects models were estimated by maximum likelihood at state and well levels. The main findings from models for rice outputs were that temperatures and rainfall levels were significant predictors, and the relationships were quadratic with respect to rainfall. Moreover, nonlinearities with respect to population changes indicated greater rice production with population increases. Second, groundwater depths were positively associated with temperatures and negatively with rainfall levels and there were nonlinear effects of population changes. Third, dynamic models for in situ groundwater depths in 11 795 wells in mainly unconfined aquifers, accounting for latitudes, longitudes and altitudes, showed steady depletion. Overall, the results indicated that population pressures on food production and environment need to be tackled via long-term healthcare, agricultural, and groundwater recharge policies in India.

A Strategic Interaction Model of Punishment Favoring Contagion of Honest Behavior

PubMed Central

Cremene, Marcel; Dumitrescu, D.; Cremene, Ligia

2014-01-01

The punishment effect on social behavior is analyzed within the strategic interaction framework of Cellular Automata and computational Evolutionary Game Theory. A new game, called Social Honesty (SH), is proposed. The SH game is analyzed in spatial configurations. Probabilistic punishment is used as a dishonesty deterrence mechanism. In order to capture the intrinsic uncertainty of social environments, payoffs are described as random variables. New dynamics, with a new relation between punishment probability and punishment severity, are revealed. Punishment probability proves to be more important than punishment severity in guiding convergence towards honesty as predominant behavior. This result is confirmed by empirical evidence and reported experiments. Critical values and transition intervals for punishment probability and severity are identified and analyzed. Clusters of honest or dishonest players emerge spontaneously from the very first rounds of interaction and are determinant for the future dynamics and outcomes. PMID:24489917

Real-time monitoring of Lévy flights in a single quantum system

NASA Astrophysics Data System (ADS)

Issler, M.; Höller, J.; Imamoǧlu, A.

2016-02-01

Lévy flights are random walks where the dynamics is dominated by rare events. Even though they have been studied in vastly different physical systems, their observation in a single quantum system has remained elusive. Here we analyze a periodically driven open central spin system and demonstrate theoretically that the dynamics of the spin environment exhibits Lévy flights. For the particular realization in a single-electron charged quantum dot driven by periodic resonant laser pulses, we use Monte Carlo simulations to confirm that the long waiting times between successive nuclear spin-flip events are governed by a power-law distribution; the corresponding exponent η =-3 /2 can be directly measured in real time by observing the waiting time distribution of successive photon emission events. Remarkably, the dominant intrinsic limitation of the scheme arising from nuclear quadrupole coupling can be minimized by adjusting the magnetic field or by implementing spin echo.

Early Exposure to Dynamic Environments Alters Patterns of Motor Exploration throughout the Lifespan

PubMed Central

Hong, S. Lee; Estrada-Sánchez, Ana María; Barton, Scott J.; Rebec, George V.

2016-01-01

We assessed early rearing conditions on aging-related changes in mouse behavior. Two isolated-housing groups, Running Wheel (IHRW) and Empty Cage (IHEC), were compared against two enriched environments, Static (EEST) and Dynamic (EEDY), both of which included toys and other mice. For EEDY, the location of toys and sources of food and water changed daily, but remained constant for EEST. All mice, randomly assigned to one of the four groups at ~4 weeks of age, remained in their respective environments for 25 weeks followed by single housing in empty cages. Beginning at ~40 weeks of age, all mice were tested at monthly intervals in a plus-shaped maze in which we measured the number of arm entries and the probability of entering a perpendicular arm. Despite making significantly more arm entries than any other group, IHEC mice also were less likely to turn into the left or right arm, a sign of motor inflexibility. Both EEDY and EEST mice showed enhanced turning relative to IHRW and IHEC groups, but only EEDY mice maintained their turning performance for up to ~100 weeks of age. EEDY and EEST mice also were unique in showing an increase in expression of the major glutamate transporter (GLT1) in striatum, but a decrease in motor cortex, suggesting a need for further assessment of environmental manipulations on long-term changes in forebrain glutamate transmission. Our behavioral results indicate that early exposure to continually changing environments, rather than socialization or exercise alone, results in life-long changes in patterns of motor exploration. PMID:26778790

Dimensional study of the dynamical arrest in a random Lorentz gas.

PubMed

Jin, Yuliang; Charbonneau, Patrick

2015-04-01

The random Lorentz gas (RLG) is a minimal model for transport in heterogeneous media. Upon increasing the obstacle density, it exhibits a growing subdiffusive transport regime and then a dynamical arrest. Here, we study the dimensional dependence of the dynamical arrest, which can be mapped onto the void percolation transition for Poisson-distributed point obstacles. We numerically determine the arrest in dimensions d=2-6. Comparison of the results with standard mode-coupling theory reveals that the dynamical theory prediction grows increasingly worse with d. In an effort to clarify the origin of this discrepancy, we relate the dynamical arrest in the RLG to the dynamic glass transition of the infinite-range Mari-Kurchan-model glass former. Through a mixed static and dynamical analysis, we then extract an improved dimensional scaling form as well as a geometrical upper bound for the arrest. The results suggest that understanding the asymptotic behavior of the random Lorentz gas may be key to surmounting fundamental difficulties with the mode-coupling theory of glasses.

Markov switching of the electricity supply curve and power prices dynamics

NASA Astrophysics Data System (ADS)

Mari, Carlo; Cananà, Lucianna

2012-02-01

Regime-switching models seem to well capture the main features of power prices behavior in deregulated markets. In a recent paper, we have proposed an equilibrium methodology to derive electricity prices dynamics from the interplay between supply and demand in a stochastic environment. In particular, assuming that the supply function is described by a power law where the exponent is a two-state strictly positive Markov process, we derived a regime switching dynamics of power prices in which regime switches are induced by transitions between Markov states. In this paper, we provide a dynamical model to describe the random behavior of power prices where the only non-Brownian component of the motion is endogenously introduced by Markov transitions in the exponent of the electricity supply curve. In this context, the stochastic process driving the switching mechanism becomes observable, and we will show that the non-Brownian component of the dynamics induced by transitions from Markov states is responsible for jumps and spikes of very high magnitude. The empirical analysis performed on three Australian markets confirms that the proposed approach seems quite flexible and capable of incorporating the main features of power prices time-series, thus reproducing the first four moments of log-returns empirical distributions in a satisfactory way.

Dynamics of comb-of-comb-network polymers in random layered flows

NASA Astrophysics Data System (ADS)

Katyal, Divya; Kant, Rama

2016-12-01

We analyze the dynamics of comb-of-comb-network polymers in the presence of external random flows. The dynamics of such structures is evaluated through relevant physical quantities, viz., average square displacement (ASD) and the velocity autocorrelation function (VACF). We focus on comparing the dynamics of the comb-of-comb network with the linear polymer. The present work displays an anomalous diffusive behavior of this flexible network in the random layered flows. The effect of the polymer topology on the dynamics is analyzed by varying the number of generations and branch lengths in these networks. In addition, we investigate the influence of external flow on the dynamics by varying flow parameters, like the flow exponent α and flow strength Wα. Our analysis highlights two anomalous power-law regimes, viz., subdiffusive (intermediate-time polymer stretching and flow-induced diffusion) and superdiffusive (long-time flow-induced diffusion). The anomalous long-time dynamics is governed by the temporal exponent ν of ASD, viz., ν =2 -α /2 . Compared to a linear polymer, the comb-of-comb network shows a shorter crossover time (from the subdiffusive to superdiffusive regime) but a reduced magnitude of ASD. Our theory displays an anomalous VACF in the random layered flows that scales as t-α /2. We show that the network with greater total mass moves faster.

Random complex dynamics and devil's coliseums

NASA Astrophysics Data System (ADS)

Sumi, Hiroki

2015-04-01

We investigate the random dynamics of polynomial maps on the Riemann sphere \\hat{\\Bbb{C}} and the dynamics of semigroups of polynomial maps on \\hat{\\Bbb{C}} . In particular, the dynamics of a semigroup G of polynomials whose planar postcritical set is bounded and the associated random dynamics are studied. In general, the Julia set of such a G may be disconnected. We show that if G is such a semigroup, then regarding the associated random dynamics, the chaos of the averaged system disappears in the C0 sense, and the function T∞ of probability of tending to ∞ \\in \\hat{\\Bbb{C}} is Hölder continuous on \\hat{\\Bbb{C}} and varies only on the Julia set of G. Moreover, the function T∞ has a kind of monotonicity. It turns out that T∞ is a complex analogue of the devil's staircase, and we call T∞ a ‘devil’s coliseum'. We investigate the details of T∞ when G is generated by two polynomials. In this case, T∞ varies precisely on the Julia set of G, which is a thin fractal set. Moreover, under this condition, we investigate the pointwise Hölder exponents of T∞.

Uncertain dynamic analysis for rigid-flexible mechanisms with random geometry and material properties

NASA Astrophysics Data System (ADS)

Wu, Jinglai; Luo, Zhen; Zhang, Nong; Zhang, Yunqing; Walker, Paul D.

2017-02-01

This paper proposes an uncertain modelling and computational method to analyze dynamic responses of rigid-flexible multibody systems (or mechanisms) with random geometry and material properties. Firstly, the deterministic model for the rigid-flexible multibody system is built with the absolute node coordinate formula (ANCF), in which the flexible parts are modeled by using ANCF elements, while the rigid parts are described by ANCF reference nodes (ANCF-RNs). Secondly, uncertainty for the geometry of rigid parts is expressed as uniform random variables, while the uncertainty for the material properties of flexible parts is modeled as a continuous random field, which is further discretized to Gaussian random variables using a series expansion method. Finally, a non-intrusive numerical method is developed to solve the dynamic equations of systems involving both types of random variables, which systematically integrates the deterministic generalized-α solver with Latin Hypercube sampling (LHS) and Polynomial Chaos (PC) expansion. The benchmark slider-crank mechanism is used as a numerical example to demonstrate the characteristics of the proposed method.

Synchronization in Random Pulse Oscillator Networks

NASA Astrophysics Data System (ADS)

Brown, Kevin; Hermundstad, Ann

Motivated by synchronization phenomena in neural systems, we study synchronization of random networks of coupled pulse oscillators. We begin by considering binomial random networks whose nodes have intrinsic linear dynamics. We quantify order in the network spiking dynamics using a new measure: the normalized Lev-Zimpel complexity (LZC) of the nodes' spike trains. Starting from a globally-synchronized state, we see two broad classes of behaviors. In one (''temporally random''), the LZC is high and nodes spike independently with no coherent pattern. In another (''temporally regular''), the network does not globally synchronize but instead forms coherent, repeating population firing patterns with low LZC. No topological feature of the network reliably predicts whether an individual network will show temporally random or regular behavior; however, we find evidence that degree heterogeneity in binomial networks has a strong effect on the resulting state. To confirm these findings, we generate random networks with independently-adjustable degree mean and variance. We find that the likelihood of temporally-random behavior increases as degree variance increases. Our results indicate the subtle and complex relationship between network structure and dynamics.

Tunable aqueous virtual micropore.

PubMed

Park, Jae Hyun; Guan, Weihua; Reed, Mark A; Krstić, Predrag S

2012-03-26

A charged microparticle can be trapped in an aqueous environment by forming a narrow virtual pore--a cylindrical space region in which the particle motion in the radial direction is limited by forces emerging from dynamical interactions of the particle charge and dipole moment with an external radiofrequency quadrupole electric field. If the particle satisfies the trap stability criteria, its mean motion is reduced exponentially with time due to the viscosity of the aqueous environment; thereafter the long-time motion of particle is subject only to random, Brownian fluctuations, whose magnitude, influenced by the electrophoretic and dielectrophoretic effects and added to the particle size, determines the radius of the virtual pore, which is demonstrated by comparison of computer simulations and experiment. The measured size of the virtual nanopore could be utilized to estimate the charge of a trapped micro-object. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

From plant traits to plant communities: a statistical mechanistic approach to biodiversity.

PubMed

Shipley, Bill; Vile, Denis; Garnier, Eric

2006-11-03

We developed a quantitative method, analogous to those used in statistical mechanics, to predict how biodiversity will vary across environments, which plant species from a species pool will be found in which relative abundances in a given environment, and which plant traits determine community assembly. This provides a scaling from plant traits to ecological communities while bypassing the complications of population dynamics. Our method treats community development as a sorting process involving species that are ecologically equivalent except with respect to particular functional traits, which leads to a constrained random assembly of species; the relative abundance of each species adheres to a general exponential distribution as a function of its traits. Using data for eight functional traits of 30 herbaceous species and community-aggregated values of these traits in 12 sites along a 42-year chronosequence of secondary succession, we predicted 94% of the variance in the relative abundances.

Physical Principle for Generation of Randomness

NASA Technical Reports Server (NTRS)

Zak, Michail

2009-01-01

A physical principle (more precisely, a principle that incorporates mathematical models used in physics) has been conceived as the basis of a method of generating randomness in Monte Carlo simulations. The principle eliminates the need for conventional random-number generators. The Monte Carlo simulation method is among the most powerful computational methods for solving high-dimensional problems in physics, chemistry, economics, and information processing. The Monte Carlo simulation method is especially effective for solving problems in which computational complexity increases exponentially with dimensionality. The main advantage of the Monte Carlo simulation method over other methods is that the demand on computational resources becomes independent of dimensionality. As augmented by the present principle, the Monte Carlo simulation method becomes an even more powerful computational method that is especially useful for solving problems associated with dynamics of fluids, planning, scheduling, and combinatorial optimization. The present principle is based on coupling of dynamical equations with the corresponding Liouville equation. The randomness is generated by non-Lipschitz instability of dynamics triggered and controlled by feedback from the Liouville equation. (In non-Lipschitz dynamics, the derivatives of solutions of the dynamical equations are not required to be bounded.)

Diffusion limit of Lévy-Lorentz gas is Brownian motion

NASA Astrophysics Data System (ADS)

Magdziarz, Marcin; Szczotka, Wladyslaw

2018-07-01

In this paper we analyze asymptotic behaviour of a stochastic process called Lévy-Lorentz gas. This process is aspecial kind of continuous-time random walk in which walker moves in the fixed environment composed of scattering points. Upon each collision the walker performs a flight to the nearest scattering point. This type of dynamics is observed in Lévy glasses or long quenched polymers. We show that the diffusion limit of Lévy-Lorentz gas with finite mean distance between scattering centers is the standard Brownian motion. Thus, for long times the behaviour of the Lévy-Lorentz gas is close to the diffusive regime.

On the apparent insignificance of the randomness of flexible joints on large space truss dynamics

NASA Technical Reports Server (NTRS)

Koch, R. M.; Klosner, J. M.

1993-01-01

Deployable periodic large space structures have been shown to exhibit high dynamic sensitivity to period-breaking imperfections and uncertainties. These can be brought on by manufacturing or assembly errors, structural imperfections, as well as nonlinear and/or nonconservative joint behavior. In addition, the necessity of precise pointing and position capability can require the consideration of these usually negligible and unknown parametric uncertainties and their effect on the overall dynamic response of large space structures. This work describes the use of a new design approach for the global dynamic solution of beam-like periodic space structures possessing parametric uncertainties. Specifically, the effect of random flexible joints on the free vibrations of simply-supported periodic large space trusses is considered. The formulation is a hybrid approach in terms of an extended Timoshenko beam continuum model, Monte Carlo simulation scheme, and first-order perturbation methods. The mean and mean-square response statistics for a variety of free random vibration problems are derived for various input random joint stiffness probability distributions. The results of this effort show that, although joint flexibility has a substantial effect on the modal dynamic response of periodic large space trusses, the effect of any reasonable uncertainty or randomness associated with these joint flexibilities is insignificant.

Stability and dynamical properties of material flow systems on random networks

NASA Astrophysics Data System (ADS)

Anand, K.; Galla, T.

2009-04-01

The theory of complex networks and of disordered systems is used to study the stability and dynamical properties of a simple model of material flow networks defined on random graphs. In particular we address instabilities that are characteristic of flow networks in economic, ecological and biological systems. Based on results from random matrix theory, we work out the phase diagram of such systems defined on extensively connected random graphs, and study in detail how the choice of control policies and the network structure affects stability. We also present results for more complex topologies of the underlying graph, focussing on finitely connected Erdös-Réyni graphs, Small-World Networks and Barabási-Albert scale-free networks. Results indicate that variability of input-output matrix elements, and random structures of the underlying graph tend to make the system less stable, while fast price dynamics or strong responsiveness to stock accumulation promote stability.

Clearing out a maze: A model of chemotactic motion in porous media

NASA Astrophysics Data System (ADS)

Schilling, Tanja; Voigtmann, Thomas

2017-12-01

We study the anomalous dynamics of a biased "hungry" (or "greedy") random walk on a percolating cluster. The model mimics chemotaxis in a porous medium: In close resemblance to the 1980s arcade game PAC-MA N ®, the hungry random walker consumes food, which is initially distributed in the maze, and biases its movement towards food-filled sites. We observe that the mean-squared displacement of the process follows a power law with an exponent that is different from previously known exponents describing passive or active microswimmer dynamics. The change in dynamics is well described by a dynamical exponent that depends continuously on the propensity to move towards food. It results in slower differential growth when compared to the unbiased random walk.

A stochastic approach to noise modeling for barometric altimeters.

PubMed

Sabatini, Angelo Maria; Genovese, Vincenzo

2013-11-18

The question whether barometric altimeters can be applied to accurately track human motions is still debated, since their measurement performance are rather poor due to either coarse resolution or drifting behavior problems. As a step toward accurate short-time tracking of changes in height (up to few minutes), we develop a stochastic model that attempts to capture some statistical properties of the barometric altimeter noise. The barometric altimeter noise is decomposed in three components with different physical origin and properties: a deterministic time-varying mean, mainly correlated with global environment changes, and a first-order Gauss-Markov (GM) random process, mainly accounting for short-term, local environment changes, the effects of which are prominent, respectively, for long-time and short-time motion tracking; an uncorrelated random process, mainly due to wideband electronic noise, including quantization noise. Autoregressive-moving average (ARMA) system identification techniques are used to capture the correlation structure of the piecewise stationary GM component, and to estimate its standard deviation, together with the standard deviation of the uncorrelated component. M-point moving average filters used alone or in combination with whitening filters learnt from ARMA model parameters are further tested in few dynamic motion experiments and discussed for their capability of short-time tracking small-amplitude, low-frequency motions.

Athletic equipment microbiota are shaped by interactions with human skin

DOE PAGES

Wood, Mariah; Gibbons, Sean M.; Lax, Simon; ...

2015-06-19

Background: Americans spend the vast majority of their lives in built environments. Even traditionally outdoor pursuits, such as exercising, are often now performed indoors. Bacteria that colonize these indoor ecosystems are primarily derived from the human microbiome. The modes of human interaction with indoor surfaces and the physical conditions associated with each surface type determine the steady-state ecology of the microbial community. Results: Bacterial assemblages associated with different surfaces in three athletic facilities, including floors, mats, benches, free weights, and elliptical handles, were sampled every other hour (8 am to 6 pm) for 2 days. Surface and equipment type hadmore » a stronger influence on bacterial community composition than the facility in which they were housed. Surfaces that were primarily in contact with human skin exhibited highly dynamic bacterial community composition and non-random co-occurrence patterns, suggesting that different host microbiomes—shaped by selective forces—were being deposited on these surfaces through time. Bacterial assemblages found on the floors and mats changed less over time, and species co-occurrence patterns appeared random, suggesting more neutral community assembly. Conclusions: These longitudinal patterns highlight the dramatic turnover of microbial communities on surfaces in regular contact with human skin. By uncovering these longitudinal patterns, this study promotes a better understanding of microbe-human interactions within the built environment.« less

Weak Ergodicity Breaking of Receptor Motion in Living Cells Stemming from Random Diffusivity

NASA Astrophysics Data System (ADS)

Manzo, Carlo; Torreno-Pina, Juan A.; Massignan, Pietro; Lapeyre, Gerald J.; Lewenstein, Maciej; Garcia Parajo, Maria F.

2015-01-01

Molecular transport in living systems regulates numerous processes underlying biological function. Although many cellular components exhibit anomalous diffusion, only recently has the subdiffusive motion been associated with nonergodic behavior. These findings have stimulated new questions for their implications in statistical mechanics and cell biology. Is nonergodicity a common strategy shared by living systems? Which physical mechanisms generate it? What are its implications for biological function? Here, we use single-particle tracking to demonstrate that the motion of dendritic cell-specific intercellular adhesion molecule 3-grabbing nonintegrin (DC-SIGN), a receptor with unique pathogen-recognition capabilities, reveals nonergodic subdiffusion on living-cell membranes In contrast to previous studies, this behavior is incompatible with transient immobilization, and, therefore, it cannot be interpreted according to continuous-time random-walk theory. We show that the receptor undergoes changes of diffusivity, consistent with the current view of the cell membrane as a highly dynamic and diverse environment. Simulations based on a model of an ordinary random walk in complex media quantitatively reproduce all our observations, pointing toward diffusion heterogeneity as the cause of DC-SIGN behavior. By studying different receptor mutants, we further correlate receptor motion to its molecular structure, thus establishing a strong link between nonergodicity and biological function. These results underscore the role of disorder in cell membranes and its connection with function regulation. Because of its generality, our approach offers a framework to interpret anomalous transport in other complex media where dynamic heterogeneity might play a major role, such as those found, e.g., in soft condensed matter, geology, and ecology.

Heritability estimations for inner muscular fat in Hereford cattle using random regressions

USDA-ARS?s Scientific Manuscript database

Random regressions make possible to make genetic predictions and parameters estimation across a gradient of environments, allowing a more accurate and beneficial use of animals as breeders in specific environments. The objective of this study was to use random regression models to estimate heritabil...

Random walks of colloidal probes in viscoelastic materials

NASA Astrophysics Data System (ADS)

Khan, Manas; Mason, Thomas G.

2014-04-01

To overcome limitations of using a single fixed time step in random walk simulations, such as those that rely on the classic Wiener approach, we have developed an algorithm for exploring random walks based on random temporal steps that are uniformly distributed in logarithmic time. This improvement enables us to generate random-walk trajectories of probe particles that span a highly extended dynamic range in time, thereby facilitating the exploration of probe motion in soft viscoelastic materials. By combining this faster approach with a Maxwell-Voigt model (MVM) of linear viscoelasticity, based on a slowly diffusing harmonically bound Brownian particle, we rapidly create trajectories of spherical probes in soft viscoelastic materials over more than 12 orders of magnitude in time. Appropriate windowing of these trajectories over different time intervals demonstrates that random walk for the MVM is neither self-similar nor self-affine, even if the viscoelastic material is isotropic. We extend this approach to spatially anisotropic viscoelastic materials, using binning to calculate the anisotropic mean square displacements and creep compliances along different orthogonal directions. The elimination of a fixed time step in simulations of random processes, including random walks, opens up interesting possibilities for modeling dynamics and response over a highly extended temporal dynamic range.

High Pressure Oxidizer Turbopump (HPOTP) inducer dynamic design environment

NASA Technical Reports Server (NTRS)

Herda, D. A.; Gross, R. S.

1995-01-01

The dynamic environment must be known to evaluate high pressure oxidizer turbopump inducer fatigue life. This report sets the dynamic design loads for the alternate turbopump inducer as determined by water-flow rig testing. Also, guidelines are given for estimating the dynamic environment for other inducer and impeller applications.

Magnetic susceptibility, nanorheology, and magnetoviscosity of magnetic nanoparticles in viscoelastic environments

NASA Astrophysics Data System (ADS)

Ilg, Patrick; Evangelopoulos, Apostolos E. A. S.

2018-03-01

While magnetic nanoparticles suspended in Newtonian solvents (ferrofluids) have been intensively studied in recent years, the effects of viscoelasticity of the surrounding medium on the nanoparticle dynamics are much less understood. Here we investigate a mesoscopic model for the orientational dynamics of isolated magnetic nanoparticles subject to external fields, viscous and viscoelastic friction, as well as the corresponding random torques. We solve the model analytically in the overdamped limit for weak viscoelasticity. By comparison to Brownian dynamics simulations we establish the limits of validity of the analytical solution. We find that viscoelasticity not only slows down the magnetization relaxation, shifts the peak of the imaginary magnetic susceptibility χ″ to lower frequencies, and increases the magnetoviscosity but also leads to nonexponential relaxation and a broadening of χ″. The model we study also allows us to test a recent proposal for using magnetic susceptibility measurements as a nanorheological tool using a variant of the Germant-DiMarzio-Bishop relation. We find for the present model and certain parameter ranges that the relation of the magnetic susceptibility to the shear modulus is satisfied to a good approximation.

Comparison of RF spectrum prediction methods for dynamic spectrum access

NASA Astrophysics Data System (ADS)

Kovarskiy, Jacob A.; Martone, Anthony F.; Gallagher, Kyle A.; Sherbondy, Kelly D.; Narayanan, Ram M.

2017-05-01

Dynamic spectrum access (DSA) refers to the adaptive utilization of today's busy electromagnetic spectrum. Cognitive radio/radar technologies require DSA to intelligently transmit and receive information in changing environments. Predicting radio frequency (RF) activity reduces sensing time and energy consumption for identifying usable spectrum. Typical spectrum prediction methods involve modeling spectral statistics with Hidden Markov Models (HMM) or various neural network structures. HMMs describe the time-varying state probabilities of Markov processes as a dynamic Bayesian network. Neural Networks model biological brain neuron connections to perform a wide range of complex and often non-linear computations. This work compares HMM, Multilayer Perceptron (MLP), and Recurrent Neural Network (RNN) algorithms and their ability to perform RF channel state prediction. Monte Carlo simulations on both measured and simulated spectrum data evaluate the performance of these algorithms. Generalizing spectrum occupancy as an alternating renewal process allows Poisson random variables to generate simulated data while energy detection determines the occupancy state of measured RF spectrum data for testing. The results suggest that neural networks achieve better prediction accuracy and prove more adaptable to changing spectral statistics than HMMs given sufficient training data.

Towards Cluster-Assembled Materials of True Monodispersity in Size and Chemical Environment: Synthesis, Dynamics and Activity

DTIC Science & Technology

2016-10-27

AFRL-AFOSR-UK-TR-2016-0037 Towards cluster-assembled materials of true monodispersity in size and chemical environment: Synthesis, Dynamics and...Towards cluster-assembled materials of true monodispersity in size and chemical environment: synthesis, dynamics and activity 5a.  CONTRACT NUMBER 5b...report Towards cluster-assembled materials of true monodispersity in size and chemical environment: Synthesis, Dynamics and Activity Ulrich Heiz

Quantitative assessments of the distinct contributions of polypeptide backbone amides versus sidechain groups to chain expansion via chemical denaturation

PubMed Central

Holehouse, Alex S.; Garai, Kanchan; Lyle, Nicholas; Vitalis, Andreas; Pappu, Rohit V.

2015-01-01

In aqueous solutions with high concentrations of chemical denaturants such as urea and guanidinium chloride (GdmCl) proteins expand to populate heterogeneous conformational ensembles. These denaturing environments are thought to be good solvents for generic protein sequences because properties of conformational distributions align with those of canonical random coils. Previous studies showed that water is a poor solvent for polypeptide backbones and therefore backbones form collapsed globular structures in aqueous solvents. Here, we ask if polypeptide backbones can intrinsically undergo the requisite chain expansion in aqueous solutions with high concentrations of urea and GdmCl. We answer this question using a combination of molecular dynamics simulations and fluorescence correlation spectroscopy. We find that the degree of backbone expansion is minimal in aqueous solutions with high concentrations denaturants. Instead, polypeptide backbones sample conformations that are denaturant-specific mixtures of coils and globules, with a persistent preference for globules. Therefore, typical denaturing environments cannot be classified as good solvents for polypeptide backbones. How then do generic protein sequences expand in denaturing environments? To answer this question, we investigated the effects of sidechains using simulations of two archetypal sequences with amino acid compositions that are mixtures of charged, hydrophobic, and polar groups. We find that sidechains lower the effective concentration of backbone amides in water leading to an intrinsic expansion of polypeptide backbones in the absence of denaturants. Additional dilution of the effective concentration of backbone amides is achieved through preferential interactions with denaturants. These effects lead to conformational statistics in denaturing environments that are congruent with those of canonical random coils. Our results highlight the role of sidechain-mediated interactions as determinants of the conformational properties of unfolded states in water and in influencing chain expansion upon denaturation. PMID:25664638

Coupled continuous time-random walks in quenched random environment

NASA Astrophysics Data System (ADS)

Magdziarz, M.; Szczotka, W.

2018-02-01

We introduce a coupled continuous-time random walk with coupling which is characteristic for Lévy walks. Additionally we assume that the walker moves in a quenched random environment, i.e. the site disorder at each lattice point is fixed in time. We analyze the scaling limit of such a random walk. We show that for large times the behaviour of the analyzed process is exactly the same as in the case of uncoupled quenched trap model for Lévy flights.

Effective dynamics of a random walker on a heterogeneous ring: Exact results

NASA Astrophysics Data System (ADS)

Masharian, S. R.

2018-07-01

In this paper, by considering a biased random walker hopping on a one-dimensional lattice with a ring geometry, we investigate the fluctuations of the speed of the random walker. We assume that the lattice is heterogeneous i.e. the hopping rate of the random walker between the first and the last lattice sites is different from the hopping rate of the random walker between the other links of the lattice. Assuming that the average speed of the random walker in the steady-state is v∗, we have been able to find the unconditional effective dynamics of the random walker where the absolute value of the average speed of the random walker is -v∗. Using a perturbative method in the large system-size limit, we have also been able to show that the effective hopping rates of the random walker near the defective link are highly site-dependent.

Oscillations and chaos in neural networks: an exactly solvable model.

PubMed Central

Wang, L P; Pichler, E E; Ross, J

1990-01-01

We consider a randomly diluted higher-order network with noise, consisting of McCulloch-Pitts neurons that interact by Hebbian-type connections. For this model, exact dynamical equations are derived and solved for both parallel and random sequential updating algorithms. For parallel dynamics, we find a rich spectrum of different behaviors including static retrieving and oscillatory and chaotic phenomena in different parts of the parameter space. The bifurcation parameters include first- and second-order neuronal interaction coefficients and a rescaled noise level, which represents the combined effects of the random synaptic dilution, interference between stored patterns, and additional background noise. We show that a marked difference in terms of the occurrence of oscillations or chaos exists between neural networks with parallel and random sequential dynamics. Images PMID:2251287

Fatigue Damage Spectrum calculation in a Mission Synthesis procedure for Sine-on-Random excitations

NASA Astrophysics Data System (ADS)

Angeli, Andrea; Cornelis, Bram; Troncossi, Marco

2016-09-01

In many real-life environments, certain mechanical and electronic components may be subjected to Sine-on-Random vibrations, i.e. excitations composed of random vibrations superimposed on deterministic (sinusoidal) contributions, in particular sine tones due to some rotating parts of the system (e.g. helicopters, engine-mounted components,...). These components must be designed to withstand the fatigue damage induced by the “composed” vibration environment, and qualification tests are advisable for the most critical ones. In the case of an accelerated qualification test, a proper test tailoring which starts from the real environment (measured vibration signals) and which preserves not only the accumulated fatigue damage but also the “nature” of the excitation (i.e. sinusoidal components plus random process) is important to obtain reliable results. In this paper, the classic time domain approach is taken as a reference for the comparison of different methods for the Fatigue Damage Spectrum (FDS) calculation in case of Sine-on-Random vibration environments. Then, a methodology to compute a Sine-on-Random specification based on a mission FDS is proposed.

A modified hybrid uncertain analysis method for dynamic response field of the LSOAAC with random and interval parameters

NASA Astrophysics Data System (ADS)

Zi, Bin; Zhou, Bin

2016-07-01

For the prediction of dynamic response field of the luffing system of an automobile crane (LSOAAC) with random and interval parameters, a hybrid uncertain model is introduced. In the hybrid uncertain model, the parameters with certain probability distribution are modeled as random variables, whereas, the parameters with lower and upper bounds are modeled as interval variables instead of given precise values. Based on the hybrid uncertain model, the hybrid uncertain dynamic response equilibrium equation, in which different random and interval parameters are simultaneously included in input and output terms, is constructed. Then a modified hybrid uncertain analysis method (MHUAM) is proposed. In the MHUAM, based on random interval perturbation method, the first-order Taylor series expansion and the first-order Neumann series, the dynamic response expression of the LSOAAC is developed. Moreover, the mathematical characteristics of extrema of bounds of dynamic response are determined by random interval moment method and monotonic analysis technique. Compared with the hybrid Monte Carlo method (HMCM) and interval perturbation method (IPM), numerical results show the feasibility and efficiency of the MHUAM for solving the hybrid LSOAAC problems. The effects of different uncertain models and parameters on the LSOAAC response field are also investigated deeply, and numerical results indicate that the impact made by the randomness in the thrust of the luffing cylinder F is larger than that made by the gravity of the weight in suspension Q . In addition, the impact made by the uncertainty in the displacement between the lower end of the lifting arm and the luffing cylinder a is larger than that made by the length of the lifting arm L .

Dynamic load environment of bridge-mounted sign support structures : research implementation plan.

DOT National Transportation Integrated Search

2005-09-01

Welded aluminum highway sign support trusses must withstand in-service dynamic loads, which largely : constitute the fatigue environment. Sources of these dynamic loads include the natural wind and seismic : environment, the artificial wind environme...

Relaxation dynamics of maximally clustered networks

NASA Astrophysics Data System (ADS)

Klaise, Janis; Johnson, Samuel

2018-01-01

We study the relaxation dynamics of fully clustered networks (maximal number of triangles) to an unclustered state under two different edge dynamics—the double-edge swap, corresponding to degree-preserving randomization of the configuration model, and single edge replacement, corresponding to full randomization of the Erdős-Rényi random graph. We derive expressions for the time evolution of the degree distribution, edge multiplicity distribution and clustering coefficient. We show that under both dynamics networks undergo a continuous phase transition in which a giant connected component is formed. We calculate the position of the phase transition analytically using the Erdős-Rényi phenomenology.

Population and prehistory III: food-dependent demography in variable environments.

PubMed

Lee, Charlotte T; Puleston, Cedric O; Tuljapurkar, Shripad

2009-11-01

The population dynamics of preindustrial societies depend intimately on their surroundings, and food is a primary means through which environment influences population size and individual well-being. Food production requires labor; thus, dependence of survival and fertility on food involves dependence of a population's future on its current state. We use a perturbation approach to analyze the effects of random environmental variation on this nonlinear, age-structured system. We show that in expanding populations, direct environmental effects dominate induced population fluctuations, so environmental variability has little effect on mean hunger levels, although it does decrease population growth. The growth rate determines the time until population is limited by space. This limitation introduces a tradeoff between population density and well-being, so population effects become more important than the direct effects of the environment: environmental fluctuation increases mortality, releasing density dependence and raising average well-being for survivors. We discuss the social implications of these findings for the long-term fate of populations as they transition from expansion into limitation, given that conditions leading to high well-being during growth depress well-being during limitation.

Characteristics of trajectory in the migration of Amoeba proteus.

PubMed

Miyoshi, Hiromi; Masaki, Noritaka; Tsuchiya, Yoshimi

2003-01-01

We investigated the behavior of migration of Amoeba proteus in an isotropic environment. We found that the trajectory in the migration of A. proteus is smooth in the observation time of 500-1000 s, but its migration every second (the cell velocity) on the trajectory randomly changes. Stochastic analysis of the cell velocity and the turn angle of the trajectory has shown that the histograms of the both variables well fit to Gaussian curves. Supposing a simple model equation for the cell motion, we have estimated the motive force of the migrating cell, which is of the order of piconewton. Furthermore, we have found that the cell velocity and the turn angle have a negative cross-correlation coefficient, which suggests that the amoeba explores better environment by changing frequently its migrating direction at a low speed and it moves rectilinearly to the best environment at a high speed. On the other hand, the model equation has simulated the negative correlation between the cell velocity and the turn angle. This indicates that the apparently rational behavior comes from intrinsic characteristics in the dynamical system where the motive force is not torquelike.

Random Dynamics

NASA Astrophysics Data System (ADS)

Bennett, D. L.; Brene, N.; Nielsen, H. B.

1987-01-01

The goal of random dynamics is the derivation of the laws of Nature as we know them (standard model) from inessential assumptions. The inessential assumptions made here are expressed as sets of general models at extremely high energies: gauge glass and spacetime foam. Both sets of models lead tentatively to the standard model.

Biodiversity in models of cyclic dominance is preserved by heterogeneity in site-specific invasion rates.

PubMed

Szolnoki, Attila; Perc, Matjaž

2016-12-05

Global, population-wide oscillations in models of cyclic dominance may result in the collapse of biodiversity due to the accidental extinction of one species in the loop. Previous research has shown that such oscillations can emerge if the interaction network has small-world properties, and more generally, because of long-range interactions among individuals or because of mobility. But although these features are all common in nature, global oscillations are rarely observed in actual biological systems. This begets the question what is the missing ingredient that would prevent local oscillations to synchronize across the population to form global oscillations. Here we show that, although heterogeneous species-specific invasion rates fail to have a noticeable impact on species coexistence, randomness in site-specific invasion rates successfully hinders the emergence of global oscillations and thus preserves biodiversity. Our model takes into account that the environment is often not uniform but rather spatially heterogeneous, which may influence the success of microscopic dynamics locally. This prevents the synchronization of locally emerging oscillations, and ultimately results in a phenomenon where one type of randomness is used to mitigate the adverse effects of other types of randomness in the system.

Biodiversity in models of cyclic dominance is preserved by heterogeneity in site-specific invasion rates

NASA Astrophysics Data System (ADS)

Szolnoki, Attila; Perc, Matjaž

2016-12-01

Global, population-wide oscillations in models of cyclic dominance may result in the collapse of biodiversity due to the accidental extinction of one species in the loop. Previous research has shown that such oscillations can emerge if the interaction network has small-world properties, and more generally, because of long-range interactions among individuals or because of mobility. But although these features are all common in nature, global oscillations are rarely observed in actual biological systems. This begets the question what is the missing ingredient that would prevent local oscillations to synchronize across the population to form global oscillations. Here we show that, although heterogeneous species-specific invasion rates fail to have a noticeable impact on species coexistence, randomness in site-specific invasion rates successfully hinders the emergence of global oscillations and thus preserves biodiversity. Our model takes into account that the environment is often not uniform but rather spatially heterogeneous, which may influence the success of microscopic dynamics locally. This prevents the synchronization of locally emerging oscillations, and ultimately results in a phenomenon where one type of randomness is used to mitigate the adverse effects of other types of randomness in the system.

How Random Is Social Behaviour? Disentangling Social Complexity through the Study of a Wild House Mouse Population

PubMed Central

Perony, Nicolas; Tessone, Claudio J.; König, Barbara; Schweitzer, Frank

2012-01-01

Out of all the complex phenomena displayed in the behaviour of animal groups, many are thought to be emergent properties of rather simple decisions at the individual level. Some of these phenomena may also be explained by random processes only. Here we investigate to what extent the interaction dynamics of a population of wild house mice (Mus domesticus) in their natural environment can be explained by a simple stochastic model. We first introduce the notion of perceptual landscape, a novel tool used here to describe the utilisation of space by the mouse colony based on the sampling of individuals in discrete locations. We then implement the behavioural assumptions of the perceptual landscape in a multi-agent simulation to verify their accuracy in the reproduction of observed social patterns. We find that many high-level features – with the exception of territoriality – of our behavioural dataset can be accounted for at the population level through the use of this simplified representation. Our findings underline the potential importance of random factors in the apparent complexity of the mice's social structure. These results resonate in the general context of adaptive behaviour versus elementary environmental interactions. PMID:23209394

Poissonian steady states: from stationary densities to stationary intensities.

PubMed

Eliazar, Iddo

2012-10-01

Markov dynamics are the most elemental and omnipresent form of stochastic dynamics in the sciences, with applications ranging from physics to chemistry, from biology to evolution, and from economics to finance. Markov dynamics can be either stationary or nonstationary. Stationary Markov dynamics represent statistical steady states and are quantified by stationary densities. In this paper, we generalize the notion of steady state to the case of general Markov dynamics. Considering an ensemble of independent motions governed by common Markov dynamics, we establish that the entire ensemble attains Poissonian steady states which are quantified by stationary Poissonian intensities and which hold valid also in the case of nonstationary Markov dynamics. The methodology is applied to a host of Markov dynamics, including Brownian motion, birth-death processes, random walks, geometric random walks, renewal processes, growth-collapse dynamics, decay-surge dynamics, Ito diffusions, and Langevin dynamics.

Poissonian steady states: From stationary densities to stationary intensities

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2012-10-01

Markov dynamics are the most elemental and omnipresent form of stochastic dynamics in the sciences, with applications ranging from physics to chemistry, from biology to evolution, and from economics to finance. Markov dynamics can be either stationary or nonstationary. Stationary Markov dynamics represent statistical steady states and are quantified by stationary densities. In this paper, we generalize the notion of steady state to the case of general Markov dynamics. Considering an ensemble of independent motions governed by common Markov dynamics, we establish that the entire ensemble attains Poissonian steady states which are quantified by stationary Poissonian intensities and which hold valid also in the case of nonstationary Markov dynamics. The methodology is applied to a host of Markov dynamics, including Brownian motion, birth-death processes, random walks, geometric random walks, renewal processes, growth-collapse dynamics, decay-surge dynamics, Ito diffusions, and Langevin dynamics.

Clinical Applications of Stochastic Dynamic Models of the Brain, Part I: A Primer.

PubMed

Roberts, James A; Friston, Karl J; Breakspear, Michael

2017-04-01

Biological phenomena arise through interactions between an organism's intrinsic dynamics and stochastic forces-random fluctuations due to external inputs, thermal energy, or other exogenous influences. Dynamic processes in the brain derive from neurophysiology and anatomical connectivity; stochastic effects arise through sensory fluctuations, brainstem discharges, and random microscopic states such as thermal noise. The dynamic evolution of systems composed of both dynamic and random effects can be studied with stochastic dynamic models (SDMs). This article, Part I of a two-part series, offers a primer of SDMs and their application to large-scale neural systems in health and disease. The companion article, Part II, reviews the application of SDMs to brain disorders. SDMs generate a distribution of dynamic states, which (we argue) represent ideal candidates for modeling how the brain represents states of the world. When augmented with variational methods for model inversion, SDMs represent a powerful means of inferring neuronal dynamics from functional neuroimaging data in health and disease. Together with deeper theoretical considerations, this work suggests that SDMs will play a unique and influential role in computational psychiatry, unifying empirical observations with models of perception and behavior. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Dynamically analyzing cell interactions in biological environments using multiagent social learning framework.

PubMed

Zhang, Chengwei; Li, Xiaohong; Li, Shuxin; Feng, Zhiyong

2017-09-20

Biological environment is uncertain and its dynamic is similar to the multiagent environment, thus the research results of the multiagent system area can provide valuable insights to the understanding of biology and are of great significance for the study of biology. Learning in a multiagent environment is highly dynamic since the environment is not stationary anymore and each agent's behavior changes adaptively in response to other coexisting learners, and vice versa. The dynamics becomes more unpredictable when we move from fixed-agent interaction environments to multiagent social learning framework. Analytical understanding of the underlying dynamics is important and challenging. In this work, we present a social learning framework with homogeneous learners (e.g., Policy Hill Climbing (PHC) learners), and model the behavior of players in the social learning framework as a hybrid dynamical system. By analyzing the dynamical system, we obtain some conditions about convergence or non-convergence. We experimentally verify the predictive power of our model using a number of representative games. Experimental results confirm the theoretical analysis. Under multiagent social learning framework, we modeled the behavior of agent in biologic environment, and theoretically analyzed the dynamics of the model. We present some sufficient conditions about convergence or non-convergence and prove them theoretically. It can be used to predict the convergence of the system.

Improving Classroom Learning Environments by Cultivating Awareness and Resilience in Education (CARE): Results of a Randomized Controlled Trial

ERIC Educational Resources Information Center

Jennings, Patricia A.; Frank, Jennifer L.; Snowberg, Karin E.; Coccia, Michael A.; Greenberg, Mark T.

2013-01-01

Cultivating Awareness and Resilience in Education (CARE for Teachers) is a mindfulness-based professional development program designed to reduce stress and improve teachers' performance and classroom learning environments. A randomized controlled trial examined program efficacy and acceptability among a sample of 50 teachers randomly assigned to…

A stochastic model for transmission, extinction and outbreak of Escherichia coli O157:H7 in cattle as affected by ambient temperature and cleaning practices.

PubMed

Wang, Xueying; Gautam, Raju; Pinedo, Pablo J; Allen, Linda J S; Ivanek, Renata

2014-08-01

Many infectious agents transmitting through a contaminated environment are able to persist in the environment depending on the temperature and sanitation determined rates of their replication and clearance, respectively. There is a need to elucidate the effect of these factors on the infection transmission dynamics in terms of infection outbreaks and extinction while accounting for the random nature of the process. Also, it is important to distinguish between the true and apparent extinction, where the former means pathogen extinction in both the host and the environment while the latter means extinction only in the host population. This study proposes a stochastic-differential equation model as an approximation to a Markov jump process model, using Escherichia coli O157:H7 in cattle as a model system. In the model, the host population infection dynamics are described using the standard susceptible-infected-susceptible framework, and the E. coli O157:H7 population in the environment is represented by an additional variable. The backward Kolmogorov equations that determine the probability distribution and the expectation of the first passage time are provided in a general setting. The outbreak and apparent extinction of infection are investigated by numerically solving the Kolmogorov equations for the probability density function of the associated process and the expectation of the associated stopping time. The results provide insight into E. coli O157:H7 transmission and apparent extinction, and suggest ways for controlling the spread of infection in a cattle herd. Specifically, this study highlights the importance of ambient temperature and sanitation, especially during summer.

RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis

PubMed Central

Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

2012-01-01

RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. Availability http://www.cemb.edu.pk/sw.html Abbreviations RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language. PMID:23055611

Navigator-3, a modulator of cell migration, may act as a suppressor of breast cancer progression

PubMed Central

Cohen-Dvashi, Hadas; Ben-Chetrit, Nir; Russell, Roslin; Carvalho, Silvia; Lauriola, Mattia; Nisani, Sophia; Mancini, Maicol; Nataraj, Nishanth; Kedmi, Merav; Roth, Lee; Köstler, Wolfgang; Zeisel, Amit; Yitzhaky, Assif; Zylberg, Jacques; Tarcic, Gabi; Eilam, Raya; Wigelman, Yoav; Will, Rainer; Lavi, Sara; Porat, Ziv; Wiemann, Stefan; Ricardo, Sara; Schmitt, Fernando; Caldas, Carlos; Yarden, Yosef

2015-01-01

Dissemination of primary tumor cells depends on migratory and invasive attributes. Here, we identify Navigator-3 (NAV3), a gene frequently mutated or deleted in human tumors, as a regulator of epithelial migration and invasion. Following induction by growth factors, NAV3 localizes to the plus ends of microtubules and enhances their polarized growth. Accordingly, NAV3 depletion trimmed microtubule growth, prolonged growth factor signaling, prevented apoptosis and enhanced random cell migration. Mathematical modeling suggested that NAV3-depleted cells acquire an advantage in terms of the way they explore their environment. In animal models, silencing NAV3 increased metastasis, whereas ectopic expression of the wild-type form, unlike expression of two, relatively unstable oncogenic mutants from human tumors, inhibited metastasis. Congruently, analyses of > 2,500 breast and lung cancer patients associated low NAV3 with shorter survival. We propose that NAV3 inhibits breast cancer progression by regulating microtubule dynamics, biasing directionally persistent rather than random migration, and inhibiting locomotion of initiated cells. PMID:25678558

Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Häggström, Ida, E-mail: haeggsti@mskcc.org; Beattie, Bradley J.; Schmidtlein, C. Ross

2016-06-15

Purpose: To develop and evaluate a fast and simple tool called dPETSTEP (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. Methods: The tool was developed in MATLAB using both new and previously reported modules of PETSTEP (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuationmore » are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). Results: dPETSTEP was 8000 times faster than MC. Dynamic images from dPETSTEP had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dPETSTEP and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dPETSTEP images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p < 0.01). Compared to GAUSS, dPETSTEP images and noise properties agreed better with MC. Conclusions: The authors have developed a fast and easy one-stop solution for simulations of dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dPETSTEP to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for studies investigating these phenomena. dPETSTEP can be downloaded free of cost from https://github.com/CRossSchmidtlein/dPETSTEP.« less

Randomized Control Trials on the Dynamic Geometry Approach

ERIC Educational Resources Information Center

Jiang, Zhonghong; White, Alexander; Rosenwasser, Alana

2011-01-01

The project reported here is conducting repeated randomized control trials of an approach to high school geometry that utilizes Dynamic Geometry (DG) software to supplement ordinary instructional practices. It compares effects of that intervention with standard instruction that does not make use of computer drawing/exploration tools. The basic…

75 FR 14467 - In the Matter of: Certain Dynamic Random Access Memory Semiconductors and Products Containing...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-03-25

... Access Memory Semiconductors and Products Containing Same, Including Memory Modules; Notice of... the sale within the United States after importation of certain dynamic random access memory semiconductors and products containing same, including memory modules, by reason of infringement of certain...

The home environment and disability-related outcomes in aging individuals: what is the empirical evidence?

PubMed

Wahl, Hans-Werner; Fänge, Agneta; Oswald, Frank; Gitlin, Laura N; Iwarsson, Susanne

2009-06-01

Building on the disablement process model and the concept of person-environment fit (p-e fit), this review article examines 2 critical questions concerning the role of home environments: (a) What is the recent evidence supporting a relationship between home environments and disability-related outcomes? and (b) What is the recent evidence regarding the effects of home modifications on disability-related outcomes? Using computerized and manual search, we identified relevant peer-reviewed original publications and review articles published between January 1, 1997, and August 31, 2006. For Research Question 1, 25 original investigations and for Research Question 2, 29 original investigations and 10 review articles were identified. For Research Question 1, evidence for a relationship between home environments and disability-related outcomes for older adults exists but is limited by cross-sectional designs and poor research quality. For Research Question 2, evidence based on randomized controlled trials shows that improving home environments enhances functional ability outcomes but not so much falls-related outcomes. Some evidence also exists that studies using a p-e fit perspective result in more supportive findings than studies that do not use this framework. Considerable evidence exists that supports the role of home environments in the disablement process, but there are also inconsistencies in findings across studies. Future research should optimize psychometric properties of home environment assessment tools and explore the role of both objective characteristics and perceived attributions of home environments to understand person-environment dynamics and their impact on disability-related outcomes in old age.

The Home Environment and Disability-Related Outcomes in Aging Individuals: What Is the Empirical Evidence?

PubMed Central

Wahl, Hans-Werner; Fänge, Agneta; Oswald, Frank; Gitlin, Laura N.; Iwarsson, Susanne

2009-01-01

Purpose: Building on the disablement process model and the concept of person–environment fit (p-e fit), this review article examines 2 critical questions concerning the role of home environments: (a) What is the recent evidence supporting a relationship between home environments and disability-related outcomes? and (b) What is the recent evidence regarding the effects of home modifications on disability-related outcomes?Design and Methods: Using computerized and manual search, we identified relevant peer-reviewed original publications and review articles published between January 1, 1997, and August 31, 2006. For Research Question 1, 25 original investigations and for Research Question 2, 29 original investigations and 10 review articles were identified.Results: For Research Question 1, evidence for a relationship between home environments and disability-related outcomes for older adults exists but is limited by cross-sectional designs and poor research quality. For Research Question 2, evidence based on randomized controlled trials shows that improving home environments enhances functional ability outcomes but not so much falls-related outcomes. Some evidence also exists that studies using a p-e fit perspective result in more supportive findings than studies that do not use this framework.Implications: Considerable evidence exists that supports the role of home environments in the disablement process, but there are also inconsistencies in findings across studies. Future research should optimize psychometric properties of home environment assessment tools and explore the role of both objective characteristics and perceived attributions of home environments to understand person–environment dynamics and their impact on disability-related outcomes in old age. PMID:19420315

The influence of mesoscopic confinement on the dynamics of imidazolium-based room temperature ionic liquids in polyether sulfone membranes.

PubMed

Thomaz, Joseph E; Bailey, Heather E; Fayer, Michael D

2017-11-21

The structural dynamics of a series of 1-alkyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (C n mimNTf 2 , n = 2, 4, 6, 10: ethyl-Emim; butyl-Bmim; hexyl-Hmim; decyl-Dmim) room temperature ionic liquids confined in the pores of polyether sulfone (PES 200) membranes with an average pore size of ∼350 nm and in the bulk liquids were studied. Time correlated single photon counting measurements of the fluorescence of the fluorophore coumarin 153 (C153) were used to observe the time-dependent Stokes shift (solvation dynamics). The solvation dynamics of C153 in the ionic liquids are multiexponential decays. The multiexponential functional form of the decays was confirmed as the slowest decay component of each bulk liquid matches the slowest component of the liquid dynamics measured by optical heterodyne-detected optical Kerr effect (OHD-OKE) experiments, which is single exponential. The fact that the slowest component of the Stokes shift matches the OHD-OKE data in all four liquids identifies this component of the solvation dynamics as arising from the complete structural randomization of the liquids. Although the pores in the PES membranes are large, confinement on the mesoscopic length scale results in substantial slowing of the dynamics, a factor of ∼4, for EmimNTf 2 , with the effect decreasing as the chain length increases. By DmimNTf 2 , the dynamics are virtually indistinguishable from those in the bulk liquid. The rotation relaxation of C153 in the four bulk liquids was also measured and showed strong coupling between the C153 probe and its environment.

The influence of mesoscopic confinement on the dynamics of imidazolium-based room temperature ionic liquids in polyether sulfone membranes

NASA Astrophysics Data System (ADS)

Thomaz, Joseph E.; Bailey, Heather E.; Fayer, Michael D.

2017-11-01

The structural dynamics of a series of 1-alkyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (CnmimNTf2, n = 2, 4, 6, 10: ethyl—Emim; butyl—Bmim; hexyl—Hmim; decyl—Dmim) room temperature ionic liquids confined in the pores of polyether sulfone (PES 200) membranes with an average pore size of ˜350 nm and in the bulk liquids were studied. Time correlated single photon counting measurements of the fluorescence of the fluorophore coumarin 153 (C153) were used to observe the time-dependent Stokes shift (solvation dynamics). The solvation dynamics of C153 in the ionic liquids are multiexponential decays. The multiexponential functional form of the decays was confirmed as the slowest decay component of each bulk liquid matches the slowest component of the liquid dynamics measured by optical heterodyne-detected optical Kerr effect (OHD-OKE) experiments, which is single exponential. The fact that the slowest component of the Stokes shift matches the OHD-OKE data in all four liquids identifies this component of the solvation dynamics as arising from the complete structural randomization of the liquids. Although the pores in the PES membranes are large, confinement on the mesoscopic length scale results in substantial slowing of the dynamics, a factor of ˜4, for EmimNTf2, with the effect decreasing as the chain length increases. By DmimNTf2, the dynamics are virtually indistinguishable from those in the bulk liquid. The rotation relaxation of C153 in the four bulk liquids was also measured and showed strong coupling between the C153 probe and its environment.

Relativistic diffusive motion in random electromagnetic fields

NASA Astrophysics Data System (ADS)

Haba, Z.

2011-08-01

We show that the relativistic dynamics in a Gaussian random electromagnetic field can be approximated by the relativistic diffusion of Schay and Dudley. Lorentz invariant dynamics in the proper time leads to the diffusion in the proper time. The dynamics in the laboratory time gives the diffusive transport equation corresponding to the Jüttner equilibrium at the inverse temperature β-1 = mc2. The diffusion constant is expressed by the field strength correlation function (Kubo's formula).

A Neural Network Model to Learn Multiple Tasks under Dynamic Environments

NASA Astrophysics Data System (ADS)

Tsumori, Kenji; Ozawa, Seiichi

When environments are dynamically changed for agents, the knowledge acquired in an environment might be useless in future. In such dynamic environments, agents should be able to not only acquire new knowledge but also modify old knowledge in learning. However, modifying all knowledge acquired before is not efficient because the knowledge once acquired may be useful again when similar environment reappears and some knowledge can be shared among different environments. To learn efficiently in such environments, we propose a neural network model that consists of the following modules: resource allocating network, long-term & short-term memory, and environment change detector. We evaluate the model under a class of dynamic environments where multiple function approximation tasks are sequentially given. The experimental results demonstrate that the proposed model possesses stable incremental learning, accurate environmental change detection, proper association and recall of old knowledge, and efficient knowledge transfer.

Topics in quantum chaos

NASA Astrophysics Data System (ADS)

Jordan, Andrew Noble

2002-09-01

In this dissertation, we study the quantum mechanics of classically chaotic dynamical systems. We begin by considering the decoherence effects a quantum chaotic system has on a simple quantum few state system. Typical time evolution of a quantum system whose classical limit is chaotic generates structures in phase space whose size is much smaller than Planck's constant. A naive application of Heisenberg's uncertainty principle indicates that these structures are not physically relevant. However, if we take the quantum chaotic system in question to be an environment which interacts with a simple two state quantum system (qubit), we show that these small phase-space structures cause the qubit to generically lose quantum coherence if and only if the environment has many degrees of freedom, such as a dilute gas. This implies that many-body environments may be crucial for the phenomenon of quantum decoherence. Next, we turn to an analysis of statistical properties of time correlation functions and matrix elements of quantum chaotic systems. A semiclassical evaluation of matrix elements of an operator indicates that the dominant contribution will be related to a classical time correlation function over the energy surface. For a highly chaotic class of dynamics, these correlation functions may be decomposed into sums of Ruelle resonances, which control exponential decay to the ergodic distribution. The theory is illustrated both numerically and theoretically on the Baker map. For this system, we are able to isolate individual Ruelle modes. We further consider dynamical systems whose approach to ergodicity is given by a power law rather than an exponential in time. We propose a billiard with diffusive boundary conditions, whose classical solution may be calculated analytically. We go on to compare the exact solution with an approximation scheme, as well calculate asympotic corrections. Quantum spectral statistics are calculated assuming the validity of the Again, Altshuler and Andreev ansatz. We find singular behavior of the two point spectral correlator in the limit of small spacing. Finally, we analyse the effect that slow decay to ergodicity has on the structure of the quantum propagator, as well as wavefunction localization. We introduce a statistical quantum description of systems that are composed of both an orderly region and a random region. By averaging over the random region only, we find that measures of localization in momentum space semiclassically diverge with the dimension of the Hilbert space. We illustrate this numerically with quantum maps and suggest various other systems where this behavior should be important.

A model of gene expression based on random dynamical systems reveals modularity properties of gene regulatory networks.

PubMed

Antoneli, Fernando; Ferreira, Renata C; Briones, Marcelo R S

2016-06-01

Here we propose a new approach to modeling gene expression based on the theory of random dynamical systems (RDS) that provides a general coupling prescription between the nodes of any given regulatory network given the dynamics of each node is modeled by a RDS. The main virtues of this approach are the following: (i) it provides a natural way to obtain arbitrarily large networks by coupling together simple basic pieces, thus revealing the modularity of regulatory networks; (ii) the assumptions about the stochastic processes used in the modeling are fairly general, in the sense that the only requirement is stationarity; (iii) there is a well developed mathematical theory, which is a blend of smooth dynamical systems theory, ergodic theory and stochastic analysis that allows one to extract relevant dynamical and statistical information without solving the system; (iv) one may obtain the classical rate equations form the corresponding stochastic version by averaging the dynamic random variables (small noise limit). It is important to emphasize that unlike the deterministic case, where coupling two equations is a trivial matter, coupling two RDS is non-trivial, specially in our case, where the coupling is performed between a state variable of one gene and the switching stochastic process of another gene and, hence, it is not a priori true that the resulting coupled system will satisfy the definition of a random dynamical system. We shall provide the necessary arguments that ensure that our coupling prescription does indeed furnish a coupled regulatory network of random dynamical systems. Finally, the fact that classical rate equations are the small noise limit of our stochastic model ensures that any validation or prediction made on the basis of the classical theory is also a validation or prediction of our model. We illustrate our framework with some simple examples of single-gene system and network motifs. Copyright © 2016 Elsevier Inc. All rights reserved.

Water-mediated influence of a crowded environment on internal vibrations of a protein molecule.

PubMed

Kuffel, Anna; Zielkiewicz, Jan

2016-02-14

The influence of crowding on the protein inner dynamics is examined by putting a single protein molecule close to one or two neighboring protein molecules. The presence of additional molecules influences the amplitudes of protein fluctuations. Also, a weak dynamical coupling of collective velocities of surface atoms of proteins separated by a layer of water is detected. The possible mechanisms of these phenomena are described. The cross-correlation function of the collective velocities of surface atoms of two proteins was decomposed into the Fourier series. The amplitude spectrum displays a peak at low frequencies. Also, the results of principal component analysis suggest that the close presence of an additional protein molecule influences the high-amplitude, low-frequency modes in the most prominent way. This part of the spectrum covers biologically important protein motions. The neighbor-induced changes in the inner dynamics of the protein may be connected with the changes in the velocity power spectrum of interfacial water. The additional protein molecule changes the properties of solvation water and in this way it can influence the dynamics of the second protein. It is suggested that this phenomenon may be described, at first approximation, by a damped oscillator driven by an external random force. This model was successfully applied to conformationally rigid Choristoneura fumiferana antifreeze protein molecules.

Autonomous Byte Stream Randomizer

NASA Technical Reports Server (NTRS)

Paloulian, George K.; Woo, Simon S.; Chow, Edward T.

2013-01-01

Net-centric networking environments are often faced with limited resources and must utilize bandwidth as efficiently as possible. In networking environments that span wide areas, the data transmission has to be efficient without any redundant or exuberant metadata. The Autonomous Byte Stream Randomizer software provides an extra level of security on top of existing data encryption methods. Randomizing the data s byte stream adds an extra layer to existing data protection methods, thus making it harder for an attacker to decrypt protected data. Based on a generated crypto-graphically secure random seed, a random sequence of numbers is used to intelligently and efficiently swap the organization of bytes in data using the unbiased and memory-efficient in-place Fisher-Yates shuffle method. Swapping bytes and reorganizing the crucial structure of the byte data renders the data file unreadable and leaves the data in a deconstructed state. This deconstruction adds an extra level of security requiring the byte stream to be reconstructed with the random seed in order to be readable. Once the data byte stream has been randomized, the software enables the data to be distributed to N nodes in an environment. Each piece of the data in randomized and distributed form is a separate entity unreadable on its own right, but when combined with all N pieces, is able to be reconstructed back to one. Reconstruction requires possession of the key used for randomizing the bytes, leading to the generation of the same cryptographically secure random sequence of numbers used to randomize the data. This software is a cornerstone capability possessing the ability to generate the same cryptographically secure sequence on different machines and time intervals, thus allowing this software to be used more heavily in net-centric environments where data transfer bandwidth is limited.

Stochastic analysis of a novel nonautonomous periodic SIRI epidemic system with random disturbances

NASA Astrophysics Data System (ADS)

Zhang, Weiwei; Meng, Xinzhu

2018-02-01

In this paper, a new stochastic nonautonomous SIRI epidemic model is formulated. Given that the incidence rates of diseases may change with the environment, we propose a novel type of transmission function. The main aim of this paper is to obtain the thresholds of the stochastic SIRI epidemic model. To this end, we investigate the dynamics of the stochastic system and establish the conditions for extinction and persistence in mean of the disease by constructing some suitable Lyapunov functions and using stochastic analysis technique. Furthermore, we show that the stochastic system has at least one nontrivial positive periodic solution. Finally, numerical simulations are introduced to illustrate our results.

Pinning time statistics for vortex lines in disordered environments.

PubMed

Dobramysl, Ulrich; Pleimling, Michel; Täuber, Uwe C

2014-12-01

We study the pinning dynamics of magnetic flux (vortex) lines in a disordered type-II superconductor. Using numerical simulations of a directed elastic line model, we extract the pinning time distributions of vortex line segments. We compare different model implementations for the disorder in the surrounding medium: discrete, localized pinning potential wells that are either attractive and repulsive or purely attractive, and whose strengths are drawn from a Gaussian distribution; as well as continuous Gaussian random potential landscapes. We find that both schemes yield power-law distributions in the pinned phase as predicted by extreme-event statistics, yet they differ significantly in their effective scaling exponents and their short-time behavior.

Nonperturbative Treatment of non-Markovian Dynamics of Open Quantum Systems

NASA Astrophysics Data System (ADS)

Tamascelli, D.; Smirne, A.; Huelga, S. F.; Plenio, M. B.

2018-01-01

We identify the conditions that guarantee equivalence of the reduced dynamics of an open quantum system (OQS) for two different types of environments—one a continuous bosonic environment leading to a unitary system-environment evolution and the other a discrete-mode bosonic environment resulting in a system-mode (nonunitary) Lindbladian evolution. Assuming initial Gaussian states for the environments, we prove that the two OQS dynamics are equivalent if both the expectation values and two-time correlation functions of the environmental interaction operators are the same at all times for the two configurations. Since the numerical and analytical description of a discrete-mode environment undergoing a Lindbladian evolution is significantly more efficient than that of a continuous bosonic environment in a unitary evolution, our result represents a powerful, nonperturbative tool to describe complex and possibly highly non-Markovian dynamics. As a special application, we recover and generalize the well-known pseudomodes approach to open-system dynamics.

Characterizing channel change along a multithread gravel-bed river using random forest image classification

NASA Astrophysics Data System (ADS)

Overstreet, B. T.; Legleiter, C. J.

2012-12-01

The Snake River in Grand Teton National Park is a dam-regulated but highly dynamic gravel-bed river that alternates between a single thread and a multithread planform. Identifying key drivers of channel change on this river could improve our understanding of 1) how flow regulation at Jackson Lake Dam has altered the character of the river over time; 2) how changes in the distribution of various types of vegetation impacts river dynamics; and 3) how the Snake River will respond to future human and climate driven disturbances. Despite the importance of monitoring planform changes over time, automated channel extraction and understanding the physical drivers contributing to channel change continue to be challenging yet critical steps in the remote sensing of riverine environments. In this study we use the random forest statistical technique to first classify land cover within the Snake River corridor and then extract channel features from a sequence of high-resolution multispectral images of the Snake River spanning the period from 2006 to 2012, which encompasses both exceptionally dry years and near-record runoff in 2011. We show that the random forest technique can be used to classify images with as few as four spectral bands with far greater accuracy than traditional single-tree classification approaches. Secondly, we couple random forest derived land cover maps with LiDAR derived topography, bathymetry, and canopy height to explore physical drivers contributing to observed channel changes on the Snake River. In conclusion we show that the random forest technique is a powerful tool for classifying multispectral images of rivers. Moreover, we hypothesize that with sufficient data for calculating spatially distributed metrics of channel form and more frequent channel monitoring, this tool can also be used to identify areas with high probabilities of channel change. Land cover maps of a portion of the Snake River produced from digital aerial photography from 2010 and a 2011 WorldView2 satellite image. This pair of maps thus captures changes that occurred during the 2011 runoff

Finite Birth-and-Death Models in Randomly Changing Environments.

DTIC Science & Technology

1982-02-01

7 AD-AL14 188 NAVAL POSTGRADUATE SCHOOL MONTEREY CA F/ 12/2 FINITE BIRTH-AND-DEATH MODELS IN RANDOMLY CHANGING ENVROENTS-(TC(U) FEB 82 D P 6AVER...Monterey, California DTIC $ELECTEMAY6 1982 B FINITE BIRTH-AND-DEATH MODELS IN RANDOMLY CHANGING ENVIRONMENTS by D. P. Gayer P. A. Jacobs G. Latouche February...CATALOG NUMUEi4NPS55-82-007 [iI. (. 4. TITLE (d Subtitle) S. TYPE OF REPORT A PERIOO COVERED FINITE BIRTH-AND-DEATH MODELS IN RANDOMLY Technical

Interrogating the topological robustness of gene regulatory circuits by randomization

PubMed Central

Levine, Herbert; Onuchic, Jose N.

2017-01-01

One of the most important roles of cells is performing their cellular tasks properly for survival. Cells usually achieve robust functionality, for example, cell-fate decision-making and signal transduction, through multiple layers of regulation involving many genes. Despite the combinatorial complexity of gene regulation, its quantitative behavior has been typically studied on the basis of experimentally verified core gene regulatory circuitry, composed of a small set of important elements. It is still unclear how such a core circuit operates in the presence of many other regulatory molecules and in a crowded and noisy cellular environment. Here we report a new computational method, named random circuit perturbation (RACIPE), for interrogating the robust dynamical behavior of a gene regulatory circuit even without accurate measurements of circuit kinetic parameters. RACIPE generates an ensemble of random kinetic models corresponding to a fixed circuit topology, and utilizes statistical tools to identify generic properties of the circuit. By applying RACIPE to simple toggle-switch-like motifs, we observed that the stable states of all models converge to experimentally observed gene state clusters even when the parameters are strongly perturbed. RACIPE was further applied to a proposed 22-gene network of the Epithelial-to-Mesenchymal Transition (EMT), from which we identified four experimentally observed gene states, including the states that are associated with two different types of hybrid Epithelial/Mesenchymal phenotypes. Our results suggest that dynamics of a gene circuit is mainly determined by its topology, not by detailed circuit parameters. Our work provides a theoretical foundation for circuit-based systems biology modeling. We anticipate RACIPE to be a powerful tool to predict and decode circuit design principles in an unbiased manner, and to quantitatively evaluate the robustness and heterogeneity of gene expression. PMID:28362798

75 FR 20564 - Dynamic Random Access Memory Semiconductors from the Republic of Korea: Extension of Time Limit...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-04-20

... DEPARTMENT OF COMMERCE International Trade Administration [C-580-851] Dynamic Random Access Memory Semiconductors from the Republic of Korea: Extension of Time Limit for Preliminary Results of Countervailing Duty... access memory semiconductors from the Republic of Korea, covering the period January 1, 2008 through...

Construction of a stochastic model of track geometry irregularities and validation through experimental measurements of dynamic loading

NASA Astrophysics Data System (ADS)

Panunzio, Alfonso M.; Puel, G.; Cottereau, R.; Simon, S.; Quost, X.

2017-03-01

This paper describes the construction of a stochastic model of urban railway track geometry irregularities, based on experimental data. The considered irregularities are track gauge, superelevation, horizontal and vertical curvatures. They are modelled as random fields whose statistical properties are extracted from a large set of on-track measurements of the geometry of an urban railway network. About 300-1000 terms are used in the Karhunen-Loève/Polynomial Chaos expansions to represent the random fields with appropriate accuracy. The construction of the random fields is then validated by comparing on-track measurements of the contact forces and numerical dynamics simulations for different operational conditions (train velocity and car load) and horizontal layouts (alignment, curve). The dynamics simulations are performed both with and without randomly generated geometrical irregularities for the track. The power spectrum densities obtained from the dynamics simulations with the model of geometrical irregularities compare extremely well with those obtained from the experimental contact forces. Without irregularities, the spectrum is 10-50 dB too low.

Student Errors in Dynamic Mathematical Environments

ERIC Educational Resources Information Center

Brown, Molly; Bossé, Michael J.; Chandler, Kayla

2016-01-01

This study investigates the nature of student errors in the context of problem solving and Dynamic Math Environments. This led to the development of the Problem Solving Action Identification Framework; this framework captures and defines all activities and errors associated with problem solving in a dynamic math environment. Found are three…

Transient Oscilliations in Mechanical Systems of Automatic Control with Random Parameters

NASA Astrophysics Data System (ADS)

Royev, B.; Vinokur, A.; Kulikov, G.

2018-04-01

Transient oscillations in mechanical systems of automatic control with random parameters is a relevant but insufficiently studied issue. In this paper, a modified spectral method was applied to investigate the problem. The nature of dynamic processes and the phase portraits are analyzed depending on the amplitude and frequency of external influence. It is evident from the obtained results, that the dynamic phenomena occurring in the systems with random parameters under external influence are complex, and their study requires further investigation.

Spin dynamics of random Ising chain in coexisting transverse and longitudinal magnetic fields

NASA Astrophysics Data System (ADS)

Liu, Zhong-Qiang; Jiang, Su-Rong; Kong, Xiang-Mu; Xu, Yu-Liang

2017-05-01

The dynamics of the random Ising spin chain in coexisting transverse and longitudinal magnetic fields is studied by the recursion method. Both the spin autocorrelation function and its spectral density are investigated by numerical calculations. It is found that system's dynamical behaviors depend on the deviation σJ of the random exchange coupling between nearest-neighbor spins and the ratio rlt of the longitudinal and the transverse fields: (i) For rlt = 0, the system undergoes two crossovers from N independent spins precessing about the transverse magnetic field to a collective-mode behavior, and then to a central-peak behavior as σJ increases. (ii) For rlt ≠ 0, the system may exhibit a coexistence behavior of a collective-mode one and a central-peak one. When σJ is small (or large enough), system undergoes a crossover from a coexistence behavior (or a disordered behavior) to a central-peak behavior as rlt increases. (iii) Increasing σJ depresses effects of both the transverse and the longitudinal magnetic fields. (iv) Quantum random Ising chain in coexisting magnetic fields may exhibit under-damping and critical-damping characteristics simultaneously. These results indicate that changing the external magnetic fields may control and manipulate the dynamics of the random Ising chain.

Hindered bacterial mobility in porous media flow enhances dispersion

NASA Astrophysics Data System (ADS)

Dehkharghani, Amin; Waisbord, Nicolas; Dunkel, Jörn; Guasto, Jeffrey

2017-11-01

Swimming bacteria live in porous environments characterized by dynamic fluid flows, where they play a crucial role in processes ranging from the bioremediation to the spread of infections. We study bacterial transport in a quasi-two-dimensional porous microfluidic device, which is complemented by Langevin simulations. The cell trajectories reveal filamentous patterns of high cell concentration, which result from the accumulation of bacteria in the high-shear regions of the flow and their subsequent advection. Moreover, the effective diffusion coefficient of the motile bacteria is severely hindered in the transverse direction to the flow due to decorrelation of the cells' persistent random walk by shear-induced rotation. The hindered lateral diffusion has the surprising consequence of strongly enhancing the longitudinal bacterial transport through a dispersion effect. These results demonstrate the significant role of the flow and geometry in bacterial transport through porous media with potential implications for understanding ecosystem dynamics and engineering bioreactors. NSF CBET-1511340, NSF CAREER-1554095.

Automated sequence-specific protein NMR assignment using the memetic algorithm MATCH.

PubMed

Volk, Jochen; Herrmann, Torsten; Wüthrich, Kurt

2008-07-01

MATCH (Memetic Algorithm and Combinatorial Optimization Heuristics) is a new memetic algorithm for automated sequence-specific polypeptide backbone NMR assignment of proteins. MATCH employs local optimization for tracing partial sequence-specific assignments within a global, population-based search environment, where the simultaneous application of local and global optimization heuristics guarantees high efficiency and robustness. MATCH thus makes combined use of the two predominant concepts in use for automated NMR assignment of proteins. Dynamic transition and inherent mutation are new techniques that enable automatic adaptation to variable quality of the experimental input data. The concept of dynamic transition is incorporated in all major building blocks of the algorithm, where it enables switching between local and global optimization heuristics at any time during the assignment process. Inherent mutation restricts the intrinsically required randomness of the evolutionary algorithm to those regions of the conformation space that are compatible with the experimental input data. Using intact and artificially deteriorated APSY-NMR input data of proteins, MATCH performed sequence-specific resonance assignment with high efficiency and robustness.

Impact cratering and regolith dynamics. [on moon

NASA Technical Reports Server (NTRS)

Hoerz, F.

1977-01-01

The most recent models concerning mechanical aspects of lunar regolith dynamics related to impact cratering use probabilistic approaches to account for the randomness of the meteorite environment in both space and time. Accordingly the absolute regolith thickness is strictly a function of total bombardment intensity and absolute regolith growth rate in nonlinear through geologic time. Regoliths of increasing median thickness will have larger and larger proportions of more and more deep seated materials. An especially active zone of reworking on the lunar surface of about 1 mm depth has been established. With increasing depth, the probability of excavation and regolith turnover decreases very rapidly. Thus small scale stratigraphy - observable in lunar core materials - is perfectly compatible with regolith gardening, though it is also demonstrated that any such stratigraphy does not necessarily present a complete record of the regolith's depositional history. At present, the lifetimes of exposed lunar rocks against comminution by impact processes can be modeled; it appears that catastrophic rupture dominates over single particle abrasion.

Framework for Infectious Disease Analysis: A comprehensive and integrative multi-modeling approach to disease prediction and management.

PubMed

Erraguntla, Madhav; Zapletal, Josef; Lawley, Mark

2017-12-01

The impact of infectious disease on human populations is a function of many factors including environmental conditions, vector dynamics, transmission mechanics, social and cultural behaviors, and public policy. A comprehensive framework for disease management must fully connect the complete disease lifecycle, including emergence from reservoir populations, zoonotic vector transmission, and impact on human societies. The Framework for Infectious Disease Analysis is a software environment and conceptual architecture for data integration, situational awareness, visualization, prediction, and intervention assessment. Framework for Infectious Disease Analysis automatically collects biosurveillance data using natural language processing, integrates structured and unstructured data from multiple sources, applies advanced machine learning, and uses multi-modeling for analyzing disease dynamics and testing interventions in complex, heterogeneous populations. In the illustrative case studies, natural language processing from social media, news feeds, and websites was used for information extraction, biosurveillance, and situation awareness. Classification machine learning algorithms (support vector machines, random forests, and boosting) were used for disease predictions.

Dynamics of planetary rings

NASA Technical Reports Server (NTRS)

Araki, Suguru

1991-01-01

The modeling of the dynamics of particle collisions within planetary rings is discussed. Particles in the rings collide with one another because they have small random motions in addition to their orbital velocity. The orbital speed is roughly 10 km/s, while the random motions have an average speed of about a tenth of a millimeter per second. As a result, the particle collisions are very gentle. Numerical analysis and simulation of the ring dynamics, performed with the aid of a supercomputer, is outlined.

Resonant spatiotemporal learning in large random recurrent networks.

PubMed

Daucé, Emmanuel; Quoy, Mathias; Doyon, Bernard

2002-09-01

Taking a global analogy with the structure of perceptual biological systems, we present a system composed of two layers of real-valued sigmoidal neurons. The primary layer receives stimulating spatiotemporal signals, and the secondary layer is a fully connected random recurrent network. This secondary layer spontaneously displays complex chaotic dynamics. All connections have a constant time delay. We use for our experiments a Hebbian (covariance) learning rule. This rule slowly modifies the weights under the influence of a periodic stimulus. The effect of learning is twofold: (i) it simplifies the secondary-layer dynamics, which eventually stabilizes to a periodic orbit; and (ii) it connects the secondary layer to the primary layer, and realizes a feedback from the secondary to the primary layer. This feedback signal is added to the incoming signal, and matches it (i.e., the secondary layer performs a one-step prediction of the forthcoming stimulus). After learning, a resonant behavior can be observed: the system resonates with familiar stimuli, which activates a feedback signal. In particular, this resonance allows the recognition and retrieval of partial signals, and dynamic maintenance of the memory of past stimuli. This resonance is highly sensitive to the temporal relationships and to the periodicity of the presented stimuli. When we present stimuli which do not match in time or space, the feedback remains silent. The number of different stimuli for which resonant behavior can be learned is analyzed. As with Hopfield networks, the capacity is proportional to the size of the second, recurrent layer. Moreover, the high capacity displayed allows the implementation of our model on real-time systems interacting with their environment. Such an implementation is reported in the case of a simple behavior-based recognition task on a mobile robot. Finally, we present some functional analogies with biological systems in terms of autonomy and dynamic binding, and present some hypotheses on the computational role of feedback connections.

Dynamical Response of Networks Under External Perturbations: Exact Results

NASA Astrophysics Data System (ADS)

Chinellato, David D.; Epstein, Irving R.; Braha, Dan; Bar-Yam, Yaneer; de Aguiar, Marcus A. M.

2015-04-01

We give exact statistical distributions for the dynamic response of influence networks subjected to external perturbations. We consider networks whose nodes have two internal states labeled 0 and 1. We let nodes be frozen in state 0, in state 1, and the remaining nodes change by adopting the state of a connected node with a fixed probability per time step. The frozen nodes can be interpreted as external perturbations to the subnetwork of free nodes. Analytically extending and to be smaller than 1 enables modeling the case of weak coupling. We solve the dynamical equations exactly for fully connected networks, obtaining the equilibrium distribution, transition probabilities between any two states and the characteristic time to equilibration. Our exact results are excellent approximations for other topologies, including random, regular lattice, scale-free and small world networks, when the numbers of fixed nodes are adjusted to take account of the effect of topology on coupling to the environment. This model can describe a variety of complex systems, from magnetic spins to social networks to population genetics, and was recently applied as a framework for early warning signals for real-world self-organized economic market crises.

Dynamics of a modified Hindmarsh-Rose neural model with random perturbations: Moment analysis and firing activities

NASA Astrophysics Data System (ADS)

Mondal, Argha; Upadhyay, Ranjit Kumar

2017-11-01

In this paper, an attempt has been made to understand the activity of mean membrane voltage and subsidiary system variables with moment equations (i.e., mean, variance and covariance's) under noisy environment. We consider a biophysically plausible modified Hindmarsh-Rose (H-R) neural system injected by an applied current exhibiting spiking-bursting phenomenon. The effects of predominant parameters on the dynamical behavior of a modified H-R system are investigated. Numerically, it exhibits period-doubling, period halving bifurcation and chaos phenomena. Further, a nonlinear system has been analyzed for the first and second order moments with additive stochastic perturbations. It has been solved using fourth order Runge-Kutta method and noisy systems by Euler's scheme. It has been demonstrated that the firing properties of neurons to evoke an action potential in a certain parameter space of the large exact systems can be estimated using an approximated model. Strong stimulation can cause a change in increase or decrease of the firing patterns. Corresponding to a fixed set of parameter values, the firing behavior and dynamical differences of the collective variables of a large, exact and approximated systems are investigated.

Mapping entropy: Analysis of population-environment dynamics using integrated remote sensing and transition theory based on a general systems perspective

NASA Astrophysics Data System (ADS)

de La Sierra, Ruben Ulises

The present study introduces entropy mapping as a comprehensive method to analyze and describe complex interactive systems; and to assess the effect that entropy has in paradigm changes as described by transition theory. Dynamics of interactions among environmental, economic and demographic conditions affect a number of fast growing locations throughout the world. One of the regions especially affected by accelerated growth in terms of demographic and economic development is the border region between Mexico and the US. As the contrast between these countries provides a significant economic and cultural differential, the dynamics of capital, goods, services and people and the rates at which they interact are rather unique. To illustrate the most fundamental economic and political changes affecting the region, a background addressing the causes for these changes leading to the North America Free Trade Agreement (NAFTA) is presented. Although the concept of thermodynamic entropy was first observed in physical sciences, a relevant homology exists in biological, social and economic sciences as the universal tendency towards disorder, dissipation and equilibrium is present in these disciplines when energy or resources become deficient. Furthermore, information theory is expressed as uncertainty and randomness in terms of efficiency in transmission of information. Although entropy in closed systems is unavoidable, its increase in open systems, can be arrested by a flux of energy, resources and/or information. A critical component of all systems is the boundary. If a boundary is impermeable, it will prevent energy flow from the environment into the system; likewise, if the boundary is too porous, it will not be able to prevent the dissipation of energy and resources into the environment, and will not prevent entropy from entering. Therefore, two expressions of entropy--thermodynamic and information--are identified and related to systems in transition and to spatial distribution. These expressions are used to identify causes and trends leading to growth or disorder.

PREFACE: Complex dynamics of fluids in disordered and crowded environments Complex dynamics of fluids in disordered and crowded environments

NASA Astrophysics Data System (ADS)

Coslovich, Daniele; Kahl, Gerhard; Krakoviack, Vincent

2011-06-01

Over the past two decades, the dynamics of fluids under nanoscale confinement has attracted much attention. Motivation for this rapidly increasing interest is based on both practical and fundamental reasons. On the practical and rather applied side, problems in a wide range of scientific topics, such as polymer and colloidal sciences, rheology, geology, or biophysics, benefit from a profound understanding of the dynamical behaviour of confined fluids. Further, effects similar to those observed in confinement are expected in fluids whose constituents have strong size or mass asymmetry, and in biological systems where crowding and obstruction phenomena in the cytosol are responsible for clear separations of time scales for macromolecular transport in the cell. In fundamental research, on the other hand, the interest focuses on the complex interplay between confinement and structural relaxation, which is responsible for the emergence of new phenomena in the dynamics of the system: in confinement, geometric constraints associated with the pore shape are imposed to the adsorbed fluids and an additional characteristic length scale, i.e. the pore size, comes into play. For many years, the topic has been mostly experimentally driven. Indeed, a broad spectrum of systems has been investigated by sophisticated experimental techniques, while theoretical and simulation studies were rather scarce due to conceptual and computational issues. In the past few years, however, theory and simulations could largely catch up with experiments. On one side, new theories have been put forward that duly take into account the porosity, the connectivity, and the randomness of the confinement. On the other side, the ever increasing available computational power now allows investigations that were far out of reach a few years ago. Nowadays, instead of isolated state points, systematic investigations on the dynamics of confined fluids, covering a wide range of system parameters, can be realized. In fact, theory and simulations were recently able to predict new and surprising dynamical features, such as the occurrence of sub-diffusive laws, which result from the trapping due to the geometric and topological constraints and/or quenched disorder, the presence of both continuous and discontinuous glass transitions, and diffusion-localization transitions. Together, theory and simulations are thus able to contribute to a deeper insight into the complex dynamical behaviour of fluids in disordered confinement. Still, many yet unsolved problems remain. The fact that theoretical and simulation approaches have caught up with experimental investigations, has motivated us to organize a workshop on the dynamics of fluids confined in disordered environments, so as to bring together the different communities working in this field: theory and simulations, with their recent developments based on the mode-coupling theory of the glass transition, and experiments, with particular emphasis on colloidal systems and novel techniques. In an effort to give credit to recent developments in related problems of biophysical relevance, an entire session of the programme was dedicated to anomalous diffusion in crowded environments. The workshop was thus aimed at providing a deeper understanding of the complex dynamics of fluids in confinement as well as up-to-date perspectives on the interdisciplinary applications of this field of research. We are proud to say that all 32 contacted speakers accepted our invitation. Additional participants were attracted by our scientific programme, contributing poster presentations to the workshop. In total, close to 50 participants were registered, arriving from 11 different countries (including the US, Japan, and Mexico). Thus we conclude that the workshop indeed addressed a highly topical scientific field. From the scientific point of view a broad range of problems was covered, ranging from biophysics over soft matter to fermion systems. From the vivid discussions it became evident that the close scientific contact between theory, simulation and experiment brought along a fruitful and mutually inspiring atmosphere. On the theoretical side, these discussions have allowed clarification of several connections between the dynamics of models of fluids in porous media (quenched-annealed, pinned particles models), those of well-known limiting cases (Lorentz gas), of realistic models of liquids with strong dynamic asymmetry (asymmetric size and mass mixtures, sodium silicates, polymers blends) and even of bulk glass-formers. On the experimental side, it appeared that soft matter systems may provide an excellent test-bed to verify the theoretical predictions. From the concluding discussion it was also clear that addressing related issues relevant to biology still remains an open challenge for the future. In view of all this, it was concluded that within a short time period a workshop with analogous scope should be organized to address the progress made on both fundamental and interdisciplinary aspects. The realization of this workshop was made possible by generous financial support from CECAM, Centre Blaise Pascal-ENS de Lyon, and the ESF network 'Molecular Simulations in Biosystems and Material Science' (SimBioMa). Complex dynamics of fluids in disordered and crowded environments contents Phonon dispersions of cluster crystals Tim Neuhaus and Christos N Likos Challenges in determining anomalous diffusion in crowded fluids Marcel Hellmann, Joseph Klafter, Dieter W Heermann and Matthias Weiss Diffusion of active tracers in fluctuating fields David S Dean and Vincent Démery Self-diffusion of non-interacting hard spheres in particle gels Jean-Christophe Gimel and Taco Nicolai Probing glassy states in binary mixtures of soft interpenetrable colloids E Stiakakis, B M Erwin, D Vlassopoulos, M Cloitre, A Munam, M Gauthier, H Iatrou and N Hadjichristidis Fluids with quenched disorder: scaling of the free energy barrier near critical points T Fischer and R L C Vink Lennard-Jones binary mixture in disordered matrices: exploring the mode coupling scenario at increasing confinement P Gallo and M Rovere Static and dynamic contributions to anomalous chain dynamics in polymer blends Marco Bernabei, Angel J Moreno and J Colmenero Anomalous transport of a tracer on percolating clusters Markus Spanner, Felix Höfling, Gerd E Schröder-Turk, Klaus Mecke and Thomas Franosch Long-wavelength anomalies in the asymptotic behavior of mode-coupling theory S K Schnyder, F Höfling, T Franosch and Th Voigtmann Dynamic arrest of colloids in porous environments: disentangling crowding and confinement Jan Kurzidim, Daniele Coslovich and Gerhard Kahl Slow dynamics, dynamic heterogeneities, and fragility of supercooled liquids confined in random media Kang Kim, Kunimasa Miyazaki and Shinji Saito

76 FR 55417 - In the Matter of Certain Dynamic Random Access Memory and Nand Flash Memory Devices and Products...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-07

... Access Memory and Nand Flash Memory Devices and Products Containing Same; Notice of Institution of... importation, and the sale within the United States after importation of certain dynamic random access memory and NAND flash memory devices and products containing same by reason of infringement of certain claims...

Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials.

PubMed

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A; Burgueño, Juan; Bandeira E Sousa, Massaine; Crossa, José

2018-03-28

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines ([Formula: see text]) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. Copyright © 2018 Cuevas et al.

Genomic-Enabled Prediction Kernel Models with Random Intercepts for Multi-environment Trials

PubMed Central

Cuevas, Jaime; Granato, Italo; Fritsche-Neto, Roberto; Montesinos-Lopez, Osval A.; Burgueño, Juan; Bandeira e Sousa, Massaine; Crossa, José

2018-01-01

In this study, we compared the prediction accuracy of the main genotypic effect model (MM) without G×E interactions, the multi-environment single variance G×E deviation model (MDs), and the multi-environment environment-specific variance G×E deviation model (MDe) where the random genetic effects of the lines are modeled with the markers (or pedigree). With the objective of further modeling the genetic residual of the lines, we incorporated the random intercepts of the lines (l) and generated another three models. Each of these 6 models were fitted with a linear kernel method (Genomic Best Linear Unbiased Predictor, GB) and a Gaussian Kernel (GK) method. We compared these 12 model-method combinations with another two multi-environment G×E interactions models with unstructured variance-covariances (MUC) using GB and GK kernels (4 model-method). Thus, we compared the genomic-enabled prediction accuracy of a total of 16 model-method combinations on two maize data sets with positive phenotypic correlations among environments, and on two wheat data sets with complex G×E that includes some negative and close to zero phenotypic correlations among environments. The two models (MDs and MDE with the random intercept of the lines and the GK method) were computationally efficient and gave high prediction accuracy in the two maize data sets. Regarding the more complex G×E wheat data sets, the prediction accuracy of the model-method combination with G×E, MDs and MDe, including the random intercepts of the lines with GK method had important savings in computing time as compared with the G×E interaction multi-environment models with unstructured variance-covariances but with lower genomic prediction accuracy. PMID:29476023

Effects of random initial conditions on the dynamical scaling behaviors of a fixed-energy Manna sandpile model in one dimension

NASA Astrophysics Data System (ADS)

Kwon, Sungchul; Kim, Jin Min

2015-01-01

For a fixed-energy (FE) Manna sandpile model in one dimension, we investigate the effects of random initial conditions on the dynamical scaling behavior of an order parameter. In the FE Manna model, the density ρ of total particles is conserved, and an absorbing phase transition occurs at ρc as ρ varies. In this work, we show that, for a given ρ , random initial distributions of particles lead to the domain structure in which domains with particle densities higher and lower than ρc alternate with each other. In the domain structure, the dominant length scale is the average domain length, which increases via the coalescence of adjacent domains. At ρc, the domain structure slows down the decay of an order parameter and also causes anomalous finite-size effects, i.e., power-law decay followed by an exponential one before the quasisteady state. As a result, the interplay of particle conservation and random initial conditions causes the domain structure, which is the origin of the anomalous dynamical scaling behaviors for random initial conditions.

Dual Dynamically Orthogonal approximation of incompressible Navier Stokes equations with random boundary conditions

NASA Astrophysics Data System (ADS)

Musharbash, Eleonora; Nobile, Fabio

2018-02-01

In this paper we propose a method for the strong imposition of random Dirichlet boundary conditions in the Dynamical Low Rank (DLR) approximation of parabolic PDEs and, in particular, incompressible Navier Stokes equations. We show that the DLR variational principle can be set in the constrained manifold of all S rank random fields with a prescribed value on the boundary, expressed in low rank format, with rank smaller then S. We characterize the tangent space to the constrained manifold by means of a Dual Dynamically Orthogonal (Dual DO) formulation, in which the stochastic modes are kept orthonormal and the deterministic modes satisfy suitable boundary conditions, consistent with the original problem. The Dual DO formulation is also convenient to include the incompressibility constraint, when dealing with incompressible Navier Stokes equations. We show the performance of the proposed Dual DO approximation on two numerical test cases: the classical benchmark of a laminar flow around a cylinder with random inflow velocity, and a biomedical application for simulating blood flow in realistic carotid artery reconstructed from MRI data with random inflow conditions coming from Doppler measurements.

Sub-diffusion and trapped dynamics of neutral and charged probes in DNA-protein coacervates

NASA Astrophysics Data System (ADS)

Arfin, Najmul; Yadav, Avinash Chand; Bohidar, H. B.

2013-11-01

The physical mechanism leading to the formation of large intermolecular DNA-protein complexes has been studied. Our study aims to explain the occurrence of fast coacervation dynamics at the charge neutralization point, followed by the appearance of smaller complexes and slower coacervation dynamics as the complex experiences overcharging. Furthermore, the electrostatic potential and probe mobility was investigated to mimic the transport of DNA / DNA-protein complex in a DNA-protein complex coacervate medium [N. Arfin and H. B. Bohidar, J. Phys. Chem. B 116, 13192 (2012)] by assigning neutral, negative, or positive charge to the probe particle. The mobility of the neutral probe was maximal at low matrix concentrations and showed random walk behavior, while its mobility ceased at the jamming concentration of c = 0.6, showing sub-diffusion and trapped dynamics. The positively charged probe showed sub-diffusive random walk followed by trapped dynamics, while the negatively charged probe showed trapping with occasional hopping dynamics at much lower concentrations. Sub-diffusion of the probe was observed in all cases under consideration, where the electrostatic interaction was used exclusively as the dominant force involved in the dynamics. For neutral and positive probes, the mean square displacement ⟨R2⟩ exhibits a scaling with time as ⟨R2⟩ ˜ tα, distinguishing random walk and trapped dynamics at α = 0.64 ± 0.04 at c = 0.12 and c = 0.6, respectively. In addition, the same scaling factors with the exponent β = 0.64 ± 0.04 can be used to distinguish random walk and trapped dynamics for the neutral and positive probes using the relation between the number of distinct sites visited by the probe, S(t), which follows the scaling, S(t) ˜ tβ/ln (t). Our results established the occurrence of a hierarchy of diffusion dynamics experienced by a probe in a dense medium that is either charged or neutral.

Enhanced functional connectivity properties of human brains during in-situ nature experience

PubMed Central

2016-01-01

In this study, we investigated the impacts of in-situ nature and urban exposure on human brain activities and their dynamics. We randomly assigned 32 healthy right-handed college students (mean age = 20.6 years, SD = 1.6; 16 males) to a 20 min in-situ sitting exposure in either a nature (n = 16) or urban environment (n = 16) and measured their Electroencephalography (EEG) signals. Analyses revealed that a brief in-situ restorative nature experience may induce more efficient and stronger brain connectivity with enhanced small-world properties compared with a stressful urban experience. The enhanced small-world properties were found to be correlated with “coherent” experience measured by Perceived Restorativeness Scale (PRS). Exposure to nature also induces stronger long-term correlated activity across different brain regions with a right lateralization. These findings may advance our understanding of the functional activities during in-situ environmental exposures and imply that a nature or nature-like environment may potentially benefit cognitive processes and mental well-being. PMID:27547533

Epidemic spreading in localized environments with recurrent mobility patterns

NASA Astrophysics Data System (ADS)

Granell, Clara; Mucha, Peter J.

2018-05-01

The spreading of epidemics is very much determined by the structure of the contact network, which may be impacted by the mobility dynamics of the individuals themselves. In confined scenarios where a small, closed population spends most of its time in localized environments and has easily identifiable mobility patterns—such as workplaces, university campuses, or schools—it is of critical importance to identify the factors controlling the rate of disease spread. Here, we present a discrete-time, metapopulation-based model to describe the transmission of susceptible-infected-susceptible-like diseases that take place in confined scenarios where the mobilities of the individuals are not random but, rather, follow clear recurrent travel patterns. This model allows analytical determination of the onset of epidemics, as well as the ability to discern which contact structures are most suited to prevent the infection to spread. It thereby determines whether common prevention mechanisms, as isolation, are worth implementing in such a scenario and their expected impact.

Translating models of antisocial behavioral development into efficacious intervention policy to prevent adolescent violence.

PubMed

Dodge, Kenneth A; McCourt, Sandra N

2010-04-01

Adolescent chronic antisocial behavior is costly but concentrated in a relatively small number of individuals. The search for effective preventive interventions draws from empirical findings of three kinds of gene-by-environment interactions: (1) parenting behaviors mute the impact of genes; (2) genes alter the impact of traumatic environmental experiences such as physical abuse and peer social rejection; and (3) individuals and environments influence each other in a dynamic developmental cascade. Thus, environmental interventions that focus on high-risk youth may prove effective. The Fast Track intervention and randomized controlled trial are described. The intervention is a 10-year series of efforts to produce proximal change in parenting, peer relations, social cognition, and academic performance in order to lead to distal prevention of adolescent conduct disorder. Findings indicate that conduct disorder cases can be prevented, but only in the highest risk group of children. Implications for policy are discussed. (c) 2010 Wiley Periodicals, Inc.

Coarse-Grained Simulations of Membrane Insertion and Folding of Small Helical Proteins Using the CABS Model.

PubMed

Pulawski, Wojciech; Jamroz, Michal; Kolinski, Michal; Kolinski, Andrzej; Kmiecik, Sebastian

2016-11-28

The CABS coarse-grained model is a well-established tool for modeling globular proteins (predicting their structure, dynamics, and interactions). Here we introduce an extension of the CABS representation and force field (CABS-membrane) to the modeling of the effect of the biological membrane environment on the structure of membrane proteins. We validate the CABS-membrane model in folding simulations of 10 short helical membrane proteins not using any knowledge about their structure. The simulations start from random protein conformations placed outside the membrane environment and allow for full flexibility of the modeled proteins during their spontaneous insertion into the membrane. In the resulting trajectories, we have found models close to the experimental membrane structures. We also attempted to select the correctly folded models using simple filtering followed by structural clustering combined with reconstruction to the all-atom representation and all-atom scoring. The CABS-membrane model is a promising approach for further development toward modeling of large protein-membrane systems.

Blob-Spring Model for the Dynamics of Ring Polymer in Obstacle Environment

NASA Astrophysics Data System (ADS)

Lele, Ashish K.; Iyer, Balaji V. S.; Juvekar, Vinay A.

2008-07-01

The dynamical behavior of cyclic macromolecules in a fixed obstacle (FO) environment is very different than the behavior of linear chains in the same topological environment; while the latter relax by a snake-like reptational motion from their chain ends the former can relax only by contour length fluctuations since they are endless. Duke, Obukhov and Rubinstein proposed a scaling model (the DOR model) to interpret the dynamical scaling exponents shown by Monte Carlo simulations of rings in a FO environment. We present a model (blob-spring model) to describe the dynamics of flexible and non-concatenated ring polymer in FO environment based on a theoretical formulation developed for the dynamics of an unentangled fractal polymer. We argue that the perpetual evolution of ring perimeter by the motion of contour segments results in an extra frictional load. Our model predicts self-similar dynamics with scaling exponents for the molecular weight dependence of diffusion coefficient and relaxation times that are in agreement with the scaling model proposed by Obukhov et al.

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models

PubMed Central

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A.; Burgueño, Juan; Pérez-Rodríguez, Paulino; de los Campos, Gustavo

2016-01-01

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects (u) that can be assessed by the Kronecker product of variance–covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model (u) plus an extra component, f, that captures random effects between environments that were not captured by the random effects u. We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with u and f over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect u. PMID:27793970

Bayesian Genomic Prediction with Genotype × Environment Interaction Kernel Models.

PubMed

Cuevas, Jaime; Crossa, José; Montesinos-López, Osval A; Burgueño, Juan; Pérez-Rodríguez, Paulino; de Los Campos, Gustavo

2017-01-05

The phenomenon of genotype × environment (G × E) interaction in plant breeding decreases selection accuracy, thereby negatively affecting genetic gains. Several genomic prediction models incorporating G × E have been recently developed and used in genomic selection of plant breeding programs. Genomic prediction models for assessing multi-environment G × E interaction are extensions of a single-environment model, and have advantages and limitations. In this study, we propose two multi-environment Bayesian genomic models: the first model considers genetic effects [Formula: see text] that can be assessed by the Kronecker product of variance-covariance matrices of genetic correlations between environments and genomic kernels through markers under two linear kernel methods, linear (genomic best linear unbiased predictors, GBLUP) and Gaussian (Gaussian kernel, GK). The other model has the same genetic component as the first model [Formula: see text] plus an extra component, F: , that captures random effects between environments that were not captured by the random effects [Formula: see text] We used five CIMMYT data sets (one maize and four wheat) that were previously used in different studies. Results show that models with G × E always have superior prediction ability than single-environment models, and the higher prediction ability of multi-environment models with [Formula: see text] over the multi-environment model with only u occurred 85% of the time with GBLUP and 45% of the time with GK across the five data sets. The latter result indicated that including the random effect f is still beneficial for increasing prediction ability after adjusting by the random effect [Formula: see text]. Copyright © 2017 Cuevas et al.

Signs of universality in the structure of culture

NASA Astrophysics Data System (ADS)

Băbeanu, Alexandru-Ionuţ; Talman, Leandros; Garlaschelli, Diego

2017-11-01

Understanding the dynamics of opinions, preferences and of culture as whole requires more use of empirical data than has been done so far. It is clear that an important role in driving this dynamics is played by social influence, which is the essential ingredient of many quantitative models. Such models require that all traits are fixed when specifying the "initial cultural state". Typically, this initial state is randomly generated, from a uniform distribution over the set of possible combinations of traits. However, recent work has shown that the outcome of social influence dynamics strongly depends on the nature of the initial state. If the latter is sampled from empirical data instead of being generated in a uniformly random way, a higher level of cultural diversity is found after long-term dynamics, for the same level of propensity towards collective behavior in the short-term. Moreover, if the initial state is randomized by shuffling the empirical traits among people, the level of long-term cultural diversity is in-between those obtained for the empirical and uniformly random counterparts. The current study repeats the analysis for multiple empirical data sets, showing that the results are remarkably similar, although the matrix of correlations between cultural variables clearly differs across data sets. This points towards robust structural properties inherent in empirical cultural states, possibly due to universal laws governing the dynamics of culture in the real world. The results also suggest that this dynamics might be characterized by criticality and involve mechanisms beyond social influence.

Meaningful interpretation of subdiffusive measurements in living cells (crowded environment) by fluorescence fluctuation microscopy.

PubMed

Baumann, Gerd; Place, Robert F; Földes-Papp, Zeno

2010-08-01

In living cell or its nucleus, the motions of molecules are complicated due to the large crowding and expected heterogeneity of the intracellular environment. Randomness in cellular systems can be either spatial (anomalous) or temporal (heterogeneous). In order to separate both processes, we introduce anomalous random walks on fractals that represented crowded environments. We report the use of numerical simulation and experimental data of single-molecule detection by fluorescence fluctuation microscopy for detecting resolution limits of different mobile fractions in crowded environment of living cells. We simulate the time scale behavior of diffusion times tau(D)(tau) for one component, e.g. the fast mobile fraction, and a second component, e.g. the slow mobile fraction. The less the anomalous exponent alpha the higher the geometric crowding of the underlying structure of motion that is quantified by the ratio of the Hausdorff dimension and the walk exponent d(f)/d(w) and specific for the type of crowding generator used. The simulated diffusion time decreases for smaller values of alpha # 1 but increases for a larger time scale tau at a given value of alpha # 1. The effect of translational anomalous motion is substantially greater if alpha differs much from 1. An alpha value close to 1 contributes little to the time dependence of subdiffusive motions. Thus, quantitative determination of molecular weights from measured diffusion times and apparent diffusion coefficients, respectively, in temporal auto- and crosscorrelation analyses and from time-dependent fluorescence imaging data are difficult to interpret and biased in crowded environments of living cells and their cellular compartments; anomalous dynamics on different time scales tau must be coupled with the quantitative analysis of how experimental parameters change with predictions from simulated subdiffusive dynamics of molecular motions and mechanistic models. We first demonstrate that the crowding exponent alpha also determines the resolution of differences in diffusion times between two components in addition to photophysical parameters well-known for normal motion in dilute solution. The resolution limit between two different kinds of single molecule species is also analyzed under translational anomalous motion with broken ergodicity. We apply our theoretical predictions of diffusion times and lower limits for the time resolution of two components to fluorescence images in human prostate cancer cells transfected with GFP-Ago2 and GFP-Ago1. In order to mimic heterogeneous behavior in crowded environments of living cells, we need to introduce so-called continuous time random walks (CTRW). CTRWs were originally performed on regular lattice. This purely stochastic molecule behavior leads to subdiffusive motion with broken ergodicity in our simulations. For the first time, we are able to quantitatively differentiate between anomalous motion without broken ergodicity and anomalous motion with broken ergodicity in time-dependent fluorescence microscopy data sets of living cells. Since the experimental conditions to measure a selfsame molecule over an extended period of time, at which biology is taken place, in living cells or even in dilute solution are very restrictive, we need to perform the time average over a subpopulation of different single molecules of the same kind. For time averages over subpopulations of single molecules, the temporal auto- and crosscorrelation functions are first found. Knowing the crowding parameter alpha for the cell type and cellular compartment type, respectively, the heterogeneous parameter gamma can be obtained from the measurements in the presence of the interacting reaction partner, e.g. ligand, with the same alpha value. The product alpha x gamma = gamma is not a simple fitting parameter in the temporal auto- and two-color crosscorrelation functions because it is related to the proper physical models of anomalous (spatial) and heterogeneous (temporal) randomness in cellular systems.We have already derived an analytical solution gamma for in the special case of gamma = 3/2. In the case of two-color crosscorrelation or/and two-color fluorescence imaging (co-localization experiments), the second component is also a two-color species gr, for example a different molecular complex with an additional ligand. Here, we first show that plausible biological mechanisms from FCS/ FCCS and fluorescence imaging in living cells are highly questionable without proper quantitative physical models of subdiffusive motion and temporal randomness. At best, such quantitative FCS/ FCCS and fluorescence imaging data are difficult to interpret under crowding and heterogeneous conditions. It is challenging to translate proper physical models of anomalous (spatial) and heterogeneous (temporal) randomness in living cells and their cellular compartments like the nucleus into biological models of the cell biological process under study testable by single-molecule approaches. Otherwise, quantitative FCS/FCCS and fluorescence imaging measurements in living cells are not well described and cannot be interpreted in a meaningful way.

Manifestations of Dynamical Localization in the Disordered XXZ Spin Chain

NASA Astrophysics Data System (ADS)

Elgart, Alexander; Klein, Abel; Stolz, Günter

2018-04-01

We study disordered XXZ spin chains in the Ising phase exhibiting droplet localization, a single cluster localization property we previously proved for random XXZ spin chains. It holds in an energy interval I near the bottom of the spectrum, known as the droplet spectrum. We establish dynamical manifestations of localization in the energy window I, including non-spreading of information, zero-velocity Lieb-Robinson bounds, and general dynamical clustering. Our results do not rely on knowledge of the dynamical characteristics of the model outside the droplet spectrum. A byproduct of our analysis is that for random XXZ spin chains this droplet localization can happen only inside the droplet spectrum.

Statistical properties of fluctuating enzymes with dynamic cooperativity using a first passage time distribution formalism.

PubMed

Singh, Divya; Chaudhury, Srabanti

2017-04-14

We study the temporal fluctuations in catalytic rates for single enzyme reactions undergoing slow transitions between two active states. We use a first passage time distribution formalism to obtain the closed-form analytical expressions of the mean reaction time and the randomness parameter for reaction schemes where conformational fluctuations are present between two free enzyme conformers. Our studies confirm that the sole presence of free enzyme fluctuations yields a non Michaelis-Menten equation and can lead to dynamic cooperativity. The randomness parameter, which is a measure of the dynamic disorder in the system, converges to unity at a high substrate concentration. If slow fluctuations are present between the enzyme-substrate conformers (off-pathway mechanism), dynamic disorder is present at a high substrate concentration. Our results confirm that the dynamic disorder at a high substrate concentration is determined only by the slow fluctuations between the enzyme-substrate conformers and the randomness parameter is greater than unity. Slow conformational fluctuations between free enzymes are responsible for the emergence of dynamic cooperativity in single enzymes. Our theoretical findings are well supported by comparison with experimental data on the single enzyme beta-galactosidase.

Effects of random tooth profile errors on the dynamic behaviors of planetary gears

NASA Astrophysics Data System (ADS)

Xun, Chao; Long, Xinhua; Hua, Hongxing

2018-02-01

In this paper, a nonlinear random model is built to describe the dynamics of planetary gear trains (PGTs), in which the time-varying mesh stiffness, tooth profile modification (TPM), tooth contact loss, and random tooth profile error are considered. A stochastic method based on the method of multiple scales (MMS) is extended to analyze the statistical property of the dynamic performance of PGTs. By the proposed multiple-scales based stochastic method, the distributions of the dynamic transmission errors (DTEs) are investigated, and the lower and upper bounds are determined based on the 3σ principle. Monte Carlo method is employed to verify the proposed method. Results indicate that the proposed method can be used to determine the distribution of the DTE of PGTs high efficiently and allow a link between the manufacturing precision and the dynamical response. In addition, the effects of tooth profile modification on the distributions of vibration amplitudes and the probability of tooth contact loss with different manufacturing tooth profile errors are studied. The results show that the manufacturing precision affects the distribution of dynamic transmission errors dramatically and appropriate TPMs are helpful to decrease the nominal value and the deviation of the vibration amplitudes.

Efficient Quantum Pseudorandomness.

PubMed

Brandão, Fernando G S L; Harrow, Aram W; Horodecki, Michał

2016-04-29

Randomness is both a useful way to model natural systems and a useful tool for engineered systems, e.g., in computation, communication, and control. Fully random transformations require exponential time for either classical or quantum systems, but in many cases pseudorandom operations can emulate certain properties of truly random ones. Indeed, in the classical realm there is by now a well-developed theory regarding such pseudorandom operations. However, the construction of such objects turns out to be much harder in the quantum case. Here, we show that random quantum unitary time evolutions ("circuits") are a powerful source of quantum pseudorandomness. This gives for the first time a polynomial-time construction of quantum unitary designs, which can replace fully random operations in most applications, and shows that generic quantum dynamics cannot be distinguished from truly random processes. We discuss applications of our result to quantum information science, cryptography, and understanding the self-equilibration of closed quantum dynamics.

Noise, chaos, and (ɛ, τ)-entropy per unit time

NASA Astrophysics Data System (ADS)

Gaspard, Pierre; Wang, Xiao-Jing

1993-12-01

The degree of dynamical randomness of different time processes is characterized in terms of the (ε, τ)-entropy per unit time. The (ε, τ)-entropy is the amount of information generated per unit time, at different scales τ of time and ε of the observables. This quantity generalizes the Kolmogorov-Sinai entropy per unit time from deterministic chaotic processes, to stochastic processes such as fluctuations in mesoscopic physico-chemical phenomena or strong turbulence in macroscopic spacetime dynamics. The random processes that are characterized include chaotic systems, Bernoulli and Markov chains, Poisson and birth-and-death processes, Ornstein-Uhlenbeck and Yaglom noises, fractional Brownian motions, different regimes of hydrodynamical turbulence, and the Lorentz-Boltzmann process of nonequilibrium statistical mechanics. We also extend the (ε, τ)-entropy to spacetime processes like cellular automata, Conway's game of life, lattice gas automata, coupled maps, spacetime chaos in partial differential equations, as well as the ideal, the Lorentz, and the hard sphere gases. Through these examples it is demonstrated that the (ε, τ)-entropy provides a unified quantitative measure of dynamical randomness to both chaos and noises, and a method to detect transitions between dynamical states of different degrees of randomness as a parameter of the system is varied.

Dynamical influence processes on networks: general theory and applications to social contagion.

PubMed

Harris, Kameron Decker; Danforth, Christopher M; Dodds, Peter Sheridan

2013-08-01

We study binary state dynamics on a network where each node acts in response to the average state of its neighborhood. By allowing varying amounts of stochasticity in both the network and node responses, we find different outcomes in random and deterministic versions of the model. In the limit of a large, dense network, however, we show that these dynamics coincide. We construct a general mean-field theory for random networks and show this predicts that the dynamics on the network is a smoothed version of the average response function dynamics. Thus, the behavior of the system can range from steady state to chaotic depending on the response functions, network connectivity, and update synchronicity. As a specific example, we model the competing tendencies of imitation and nonconformity by incorporating an off-threshold into standard threshold models of social contagion. In this way, we attempt to capture important aspects of fashions and societal trends. We compare our theory to extensive simulations of this "limited imitation contagion" model on Poisson random graphs, finding agreement between the mean-field theory and stochastic simulations.

Projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random networks.

PubMed

Feng, Cun-Fang; Xu, Xin-Jian; Wang, Sheng-Jun; Wang, Ying-Hai

2008-06-01

We study projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random networks. We relax some limitations of previous work, where projective-anticipating and projective-lag synchronization can be achieved only on two coupled chaotic systems. In this paper, we realize projective-anticipating and projective-lag synchronization on complex dynamical networks composed of a large number of interconnected components. At the same time, although previous work studied projective synchronization on complex dynamical networks, the dynamics of the nodes are coupled partially linear chaotic systems. In this paper, the dynamics of the nodes of the complex networks are time-delayed chaotic systems without the limitation of the partial linearity. Based on the Lyapunov stability theory, we suggest a generic method to achieve the projective-anticipating, projective, and projective-lag synchronization of time-delayed chaotic systems on random dynamical networks, and we find both its existence and sufficient stability conditions. The validity of the proposed method is demonstrated and verified by examining specific examples using Ikeda and Mackey-Glass systems on Erdos-Renyi networks.

Dynamical Localization for Unitary Anderson Models

NASA Astrophysics Data System (ADS)

Hamza, Eman; Joye, Alain; Stolz, Günter

2009-11-01

This paper establishes dynamical localization properties of certain families of unitary random operators on the d-dimensional lattice in various regimes. These operators are generalizations of one-dimensional physical models of quantum transport and draw their name from the analogy with the discrete Anderson model of solid state physics. They consist in a product of a deterministic unitary operator and a random unitary operator. The deterministic operator has a band structure, is absolutely continuous and plays the role of the discrete Laplacian. The random operator is diagonal with elements given by i.i.d. random phases distributed according to some absolutely continuous measure and plays the role of the random potential. In dimension one, these operators belong to the family of CMV-matrices in the theory of orthogonal polynomials on the unit circle. We implement the method of Aizenman-Molchanov to prove exponential decay of the fractional moments of the Green function for the unitary Anderson model in the following three regimes: In any dimension, throughout the spectrum at large disorder and near the band edges at arbitrary disorder and, in dimension one, throughout the spectrum at arbitrary disorder. We also prove that exponential decay of fractional moments of the Green function implies dynamical localization, which in turn implies spectral localization. These results complete the analogy with the self-adjoint case where dynamical localization is known to be true in the same three regimes.

Auditory Magnetoencephalographic Frequency-Tagged Responses Mirror the Ongoing Segmentation Processes Underlying Statistical Learning.

PubMed

Farthouat, Juliane; Franco, Ana; Mary, Alison; Delpouve, Julie; Wens, Vincent; Op de Beeck, Marc; De Tiège, Xavier; Peigneux, Philippe

2017-03-01

Humans are highly sensitive to statistical regularities in their environment. This phenomenon, usually referred as statistical learning, is most often assessed using post-learning behavioural measures that are limited by a lack of sensibility and do not monitor the temporal dynamics of learning. In the present study, we used magnetoencephalographic frequency-tagged responses to investigate the neural sources and temporal development of the ongoing brain activity that supports the detection of regularities embedded in auditory streams. Participants passively listened to statistical streams in which tones were grouped as triplets, and to random streams in which tones were randomly presented. Results show that during exposure to statistical (vs. random) streams, tritone frequency-related responses reflecting the learning of regularities embedded in the stream increased in the left supplementary motor area and left posterior superior temporal sulcus (pSTS), whereas tone frequency-related responses decreased in the right angular gyrus and right pSTS. Tritone frequency-related responses rapidly developed to reach significance after 3 min of exposure. These results suggest that the incidental extraction of novel regularities is subtended by a gradual shift from rhythmic activity reflecting individual tone succession toward rhythmic activity synchronised with triplet presentation, and that these rhythmic processes are subtended by distinct neural sources.

Risk factors for proper oral language development in children: a systematic literature review.

PubMed

Gurgel, Léia Gonçalves; Vidor, Deisi Cristina Gollo Marques; Joly, Maria Cristina Rodrigues Azevedo; Reppold, Caroline Tozzi

2014-01-01

To conduct a systematic review of literature production related to risk factors for proper oral language development in children. We used the terms "child language," "risk factors," and "randomized controlled trial" in MEDLINE (accessed via PubMed), Lilacs, SciELO, and The Cochrane Library from January 1980 to February 2014. Randomized controlled trials involving the study of some risk factors related to child language were included. Works with individuals who were not from the age group 0-12 years and presented no reliable definition of risk factors were excluded. The research findings were classified according to their theme and categorized methodological aspects. We observed the lack of a standardized list of risk factors for language available for health professionals. The main risk factor mentioned was family dynamics, followed by interaction with parents, immediate social environment, and encouragement given to the child in the first years of life. It was also observed that organic hazards such as brain injury, persistent otitis media, and cardiac surgery, besides the type of food and parental counseling, may be related to language disorders. More randomized controlled trials involving the evaluation of risk factors for child language and the creation of further studies involving children above 6 years of age and males are needed.

Mean-field theory of a plastic network of integrate-and-fire neurons.

PubMed

Chen, Chun-Chung; Jasnow, David

2010-01-01

We consider a noise-driven network of integrate-and-fire neurons. The network evolves as result of the activities of the neurons following spike-timing-dependent plasticity rules. We apply a self-consistent mean-field theory to the system to obtain the mean activity level for the system as a function of the mean synaptic weight, which predicts a first-order transition and hysteresis between a noise-dominated regime and a regime of persistent neural activity. Assuming Poisson firing statistics for the neurons, the plasticity dynamics of a synapse under the influence of the mean-field environment can be mapped to the dynamics of an asymmetric random walk in synaptic-weight space. Using a master equation for small steps, we predict a narrow distribution of synaptic weights that scales with the square root of the plasticity rate for the stationary state of the system given plausible physiological parameter values describing neural transmission and plasticity. The dependence of the distribution on the synaptic weight of the mean-field environment allows us to determine the mean synaptic weight self-consistently. The effect of fluctuations in the total synaptic conductance and plasticity step sizes are also considered. Such fluctuations result in a smoothing of the first-order transition for low number of afferent synapses per neuron and a broadening of the synaptic-weight distribution, respectively.

Separating intrinsic from extrinsic fluctuations in dynamic biological systems

PubMed Central

Paulsson, Johan

2011-01-01

From molecules in cells to organisms in ecosystems, biological populations fluctuate due to the intrinsic randomness of individual events and the extrinsic influence of changing environments. The combined effect is often too complex for effective analysis, and many studies therefore make simplifying assumptions, for example ignoring either intrinsic or extrinsic effects to reduce the number of model assumptions. Here we mathematically demonstrate how two identical and independent reporters embedded in a shared fluctuating environment can be used to identify intrinsic and extrinsic noise terms, but also how these contributions are qualitatively and quantitatively different from what has been previously reported. Furthermore, we show for which classes of biological systems the noise contributions identified by dual-reporter methods correspond to the noise contributions predicted by correct stochastic models of either intrinsic or extrinsic mechanisms. We find that for broad classes of systems, the extrinsic noise from the dual-reporter method can be rigorously analyzed using models that ignore intrinsic stochasticity. In contrast, the intrinsic noise can be rigorously analyzed using models that ignore extrinsic stochasticity only under very special conditions that rarely hold in biology. Testing whether the conditions are met is rarely possible and the dual-reporter method may thus produce flawed conclusions about the properties of the system, particularly about the intrinsic noise. Our results contribute toward establishing a rigorous framework to analyze dynamically fluctuating biological systems. PMID:21730172

Separating intrinsic from extrinsic fluctuations in dynamic biological systems.

PubMed

Hilfinger, Andreas; Paulsson, Johan

2011-07-19

From molecules in cells to organisms in ecosystems, biological populations fluctuate due to the intrinsic randomness of individual events and the extrinsic influence of changing environments. The combined effect is often too complex for effective analysis, and many studies therefore make simplifying assumptions, for example ignoring either intrinsic or extrinsic effects to reduce the number of model assumptions. Here we mathematically demonstrate how two identical and independent reporters embedded in a shared fluctuating environment can be used to identify intrinsic and extrinsic noise terms, but also how these contributions are qualitatively and quantitatively different from what has been previously reported. Furthermore, we show for which classes of biological systems the noise contributions identified by dual-reporter methods correspond to the noise contributions predicted by correct stochastic models of either intrinsic or extrinsic mechanisms. We find that for broad classes of systems, the extrinsic noise from the dual-reporter method can be rigorously analyzed using models that ignore intrinsic stochasticity. In contrast, the intrinsic noise can be rigorously analyzed using models that ignore extrinsic stochasticity only under very special conditions that rarely hold in biology. Testing whether the conditions are met is rarely possible and the dual-reporter method may thus produce flawed conclusions about the properties of the system, particularly about the intrinsic noise. Our results contribute toward establishing a rigorous framework to analyze dynamically fluctuating biological systems.

Simulating Open Quantum Systems with Hamiltonian Ensembles and the Nonclassicality of the Dynamics

NASA Astrophysics Data System (ADS)

Chen, Hong-Bin; Gneiting, Clemens; Lo, Ping-Yuan; Chen, Yueh-Nan; Nori, Franco

2018-01-01

The incoherent dynamical properties of open quantum systems are generically attributed to an ongoing correlation between the system and its environment. Here, we propose a novel way to assess the nature of these system-environment correlations by examining the system dynamics alone. Our approach is based on the possibility or impossibility to simulate open-system dynamics with Hamiltonian ensembles. As we show, such (im)possibility to simulate is closely linked to the system-environment correlations. We thus define the nonclassicality of open-system dynamics in terms of the nonexistence of a Hamiltonian-ensemble simulation. This classifies any nonunital open-system dynamics as nonclassical. We give examples for open-system dynamics that are unital and classical, as well as unital and nonclassical.

Rumor Processes in Random Environment on and on Galton-Watson Trees

NASA Astrophysics Data System (ADS)

Bertacchi, Daniela; Zucca, Fabio

2013-11-01

The aim of this paper is to study rumor processes in random environment. In a rumor process a signal starts from the stations of a fixed vertex (the root) and travels on a graph from vertex to vertex. We consider two rumor processes. In the firework process each station, when reached by the signal, transmits it up to a random distance. In the reverse firework process, on the other hand, stations do not send any signal but they “listen” for it up to a random distance. The first random environment that we consider is the deterministic 1-dimensional tree with a random number of stations on each vertex; in this case the root is the origin of . We give conditions for the survival/extinction on almost every realization of the sequence of stations. Later on, we study the processes on Galton-Watson trees with random number of stations on each vertex. We show that if the probability of survival is positive, then there is survival on almost every realization of the infinite tree such that there is at least one station at the root. We characterize the survival of the process in some cases and we give sufficient conditions for survival/extinction.

Gamma ray observatory dynamics simulator in Ada (GRODY)

NASA Technical Reports Server (NTRS)

1990-01-01

This experiment involved the parallel development of dynamics simulators for the Gamma Ray Observatory in both FORTRAN and Ada for the purpose of evaluating the applicability of Ada to the NASA/Goddard Space Flight Center's flight dynamics environment. The experiment successfully demonstrated that Ada is a viable, valuable technology for use in this environment. In addition to building a simulator, the Ada team evaluated training approaches, developed an Ada methodology appropriate to the flight dynamics environment, and established a baseline for evaluating future Ada projects.

Experimental evolution of protein–protein interaction networks

PubMed Central

Kaçar, Betül; Gaucher, Eric A.

2013-01-01

The modern synthesis of evolutionary theory and genetics has enabled us to discover underlying molecular mechanisms of organismal evolution. We know that in order to maximize an organism's fitness in a particular environment, individual interactions among components of protein and nucleic acid networks need to be optimized by natural selection, or sometimes through random processes, as the organism responds to changes and/or challenges in the environment. Despite the significant role of molecular networks in determining an organism's adaptation to its environment, we still do not know how such inter- and intra-molecular interactions within networks change over time and contribute to an organism's evolvability while maintaining overall network functions. One way to address this challenge is to identify connections between molecular networks and their host organisms, to manipulate these connections, and then attempt to understand how such perturbations influence molecular dynamics of the network and thus influence evolutionary paths and organismal fitness. In the present review, we discuss how integrating evolutionary history with experimental systems that combine tools drawn from molecular evolution, synthetic biology and biochemistry allow us to identify the underlying mechanisms of organismal evolution, particularly from the perspective of protein interaction networks. PMID:23849056

High-temperature acoustic test facilities and methods

NASA Astrophysics Data System (ADS)

Pearson, Jerome

1994-09-01

The Wright Laboratory is the Air Force center for air vehicles, responsible for developing advanced technology and incorporating it into new flight vehicles and for continuous technological improvement of operational air vehicles. Part of that responsibility is the problem of acoustic fatigue. With the advent of jet aircraft in the 1950's, acoustic fatigue of aircraft structure became a significant problem. In the 1960's the Wright Laboratory constructed the first large acoustic fatigue test facilities in the United States, and the laboratory has been a dominant factor in high-intensity acoustic testing since that time. This paper discusses some of the intense environments encountered by new and planned Air Force flight vehicles, and describes three new acoustic test facilities of the Wright Laboratory designed for testing structures in these dynamic environments. These new test facilities represent the state of the art in high-temperature, high-intensity acoustic testing and random fatigue testing. They will allow the laboratory scientists and engineers to test the new structures and materials required to withstand the severe environments of captive-carry missiles, augmented lift wings and flaps, exhaust structures of stealth aircraft, and hypersonic vehicle structures well into the twenty-first century.

Emergent Neutrality in Adaptive Asexual Evolution

PubMed Central

Schiffels, Stephan; Szöllősi, Gergely J.; Mustonen, Ville; Lässig, Michael

2011-01-01

In nonrecombining genomes, genetic linkage can be an important evolutionary force. Linkage generates interference interactions, by which simultaneously occurring mutations affect each other’s chance of fixation. Here, we develop a comprehensive model of adaptive evolution in linked genomes, which integrates interference interactions between multiple beneficial and deleterious mutations into a unified framework. By an approximate analytical solution, we predict the fixation rates of these mutations, as well as the probabilities of beneficial and deleterious alleles at fixed genomic sites. We find that interference interactions generate a regime of emergent neutrality: all genomic sites with selection coefficients smaller in magnitude than a characteristic threshold have nearly random fixed alleles, and both beneficial and deleterious mutations at these sites have nearly neutral fixation rates. We show that this dynamic limits not only the speed of adaptation, but also a population’s degree of adaptation in its current environment. We apply the model to different scenarios: stationary adaptation in a time-dependent environment and approach to equilibrium in a fixed environment. In both cases, the analytical predictions are in good agreement with numerical simulations. Our results suggest that interference can severely compromise biological functions in an adapting population, which sets viability limits on adaptive evolution under linkage. PMID:21926305

Blackmail propagation on small-world networks

NASA Astrophysics Data System (ADS)

Shao, Zhi-Gang; Jian-Ping Sang; Zou, Xian-Wu; Tan, Zhi-Jie; Jin, Zhun-Zhi

2005-06-01

The dynamics of the blackmail propagation model based on small-world networks is investigated. It is found that for a given transmitting probability λ the dynamical behavior of blackmail propagation transits from linear growth type to logistical growth one with the network randomness p increases. The transition takes place at the critical network randomness pc=1/N, where N is the total number of nodes in the network. For a given network randomness p the dynamical behavior of blackmail propagation transits from exponential decrease type to logistical growth one with the transmitting probability λ increases. The transition occurs at the critical transmitting probability λc=1/, where is the average number of the nearest neighbors. The present work will be useful for understanding computer virus epidemics and other spreading phenomena on communication and social networks.

Similarities between principal components of protein dynamics and random diffusion

NASA Astrophysics Data System (ADS)

Hess, Berk

2000-12-01

Principal component analysis, also called essential dynamics, is a powerful tool for finding global, correlated motions in atomic simulations of macromolecules. It has become an established technique for analyzing molecular dynamics simulations of proteins. The first few principal components of simulations of large proteins often resemble cosines. We derive the principal components for high-dimensional random diffusion, which are almost perfect cosines. This resemblance between protein simulations and noise implies that for many proteins the time scales of current simulations are too short to obtain convergence of collective motions.

Non-equilibrium many-body dynamics following a quantum quench

NASA Astrophysics Data System (ADS)

Vyas, Manan

2017-12-01

We study analytically and numerically the non-equilibrium dynamics of an isolated interacting many-body quantum system following a random quench. We model the system Hamiltonian by Embedded Gaussian Orthogonal Ensemble (EGOE) of random matrices with one plus few-body interactions for fermions. EGOE are paradigmatic models to study the crossover from integrability to chaos in interacting many-body quantum systems. We obtain a generic formulation, based on spectral variances, for describing relaxation dynamics of survival probabilities as a function of rank of interactions. Our analytical results are in good agreement with numerics.

The persistence of the attentional bias to regularities in a changing environment.

PubMed

Yu, Ru Qi; Zhao, Jiaying

2015-10-01

The environment often is stable, but some aspects may change over time. The challenge for the visual system is to discover and flexibly adapt to the changes. We examined how attention is shifted in the presence of changes in the underlying structure of the environment. In six experiments, observers viewed four simultaneous streams of objects while performing a visual search task. In the first half of each experiment, the stream in the structured location contained regularities, the shapes in the random location were randomized, and gray squares appeared in two neutral locations. In the second half, the stream in the structured or the random location may change. In the first half of all experiments, visual search was facilitated in the structured location, suggesting that attention was consistently biased toward regularities. In the second half, this bias persisted in the structured location when no change occurred (Experiment 1), when the regularities were removed (Experiment 2), or when new regularities embedded in the original or novel stimuli emerged in the previously random location (Experiments 3 and 6). However, visual search was numerically but no longer reliably faster in the structured location when the initial regularities were removed and new regularities were introduced in the previously random location (Experiment 4), or when novel random stimuli appeared in the random location (Experiment 5). This suggests that the attentional bias was weakened. Overall, the results demonstrate that the attentional bias to regularities was persistent but also sensitive to changes in the environment.

Predicting Adaptive Behavior in the Environment from Central Nervous System Dynamics

PubMed Central

Proekt, Alex; Wong, Jane; Zhurov, Yuriy; Kozlova, Nataliya; Weiss, Klaudiusz R.; Brezina, Vladimir

2008-01-01

To generate adaptive behavior, the nervous system is coupled to the environment. The coupling constrains the dynamical properties that the nervous system and the environment must have relative to each other if adaptive behavior is to be produced. In previous computational studies, such constraints have been used to evolve controllers or artificial agents to perform a behavioral task in a given environment. Often, however, we already know the controller, the real nervous system, and its dynamics. Here we propose that the constraints can also be used to solve the inverse problem—to predict from the dynamics of the nervous system the environment to which they are adapted, and so reconstruct the production of the adaptive behavior by the entire coupled system. We illustrate how this can be done in the feeding system of the sea slug Aplysia. At the core of this system is a central pattern generator (CPG) that, with dynamics on both fast and slow time scales, integrates incoming sensory stimuli to produce ingestive and egestive motor programs. We run models embodying these CPG dynamics—in effect, autonomous Aplysia agents—in various feeding environments and analyze the performance of the entire system in a realistic feeding task. We find that the dynamics of the system are tuned for optimal performance in a narrow range of environments that correspond well to those that Aplysia encounter in the wild. In these environments, the slow CPG dynamics implement efficient ingestion of edible seaweed strips with minimal sensory information about them. The fast dynamics then implement a switch to a different behavioral mode in which the system ignores the sensory information completely and follows an internal “goal,” emergent from the dynamics, to egest again a strip that proves to be inedible. Key predictions of this reconstruction are confirmed in real feeding animals. PMID:18989362

Dynamics and asymptotics of correlations in a many-body localized system

NASA Astrophysics Data System (ADS)

Campbell, Steve; Power, Matthew J. M.; De Chiara, Gabriele

2017-08-01

We examine the dynamics of nearest-neighbor bipartite concurrence and total correlations in the spin-1/2 XXZ model with random fields. We show, starting from factorized random initial states, that the concurrence can suffer entanglement sudden death in the long time limit and therefore may not be a useful indicator of the properties of the system. In contrast, we show that the total correlations capture the dynamics more succinctly, and further reveal a fundamental difference in the dynamics governed by the ergodic versus many-body localized phases, with the latter exhibiting dynamical oscillations. Finally, we consider an initial state composed of several singlet pairs and show that by fixing the correlation properties, while the dynamics do not reveal noticeable differences between the phases, the long-time values of the correlation measures appear to indicate the critical region.

Reducing the risk of falls through proprioceptive dynamic posture training in osteoporotic women with kyphotic posturing: a randomized pilot study.

PubMed

Sinaki, Mehrsheed; Lynn, Susan G

2002-04-01

To assess the effect of a proprioceptive dynamic posture training program on balance in osteoporotic women with kyphotic posture. Subjects were randomly assigned to either a proprioceptive dynamic posture training program or exercise only group. Anthropometric measurements, muscle strength, level of physical activity, computerized dynamic posturography, and spine radiography were performed at baseline and 1 mo. At the 1-mo follow-up, three groups were formed on the basis of the baseline computerized dynamic posturography results. In general, groups 1 and 2 had no significant change at 1 mo, whereas group 3 improved balance significantly at 1 mo. The subjects who had abnormal balance and used the proprioceptive dynamic posture training program had the most significant improvement in balance. Improved balance could reduce the risk of falls.

From stage to age in variable environments: life expectancy and survivorship.

PubMed

Tuljapurkar, Shripad; Horvitz, Carol C

2006-06-01

Stage-based demographic data are now available on many species of plants and some animals, and they often display temporal and spatial variability. We provide exact formulas to compute age-specific life expectancy and survivorship from stage-based data for three models of temporal variability: cycles, serially independent random variation, and a Markov chain. These models provide a comprehensive description of patterns of temporal variation. Our formulas describe the effects of cohort (birth) environmental condition on mortality at all ages, and of the effects on survivorship of environmental variability experienced over the course of life. This paper complements existing methods for time-invariant stage-based data, and adds to the information on population growth and dynamics available from stochastic demography.

Dynamics of a prey-predator system under Poisson white noise excitation

NASA Astrophysics Data System (ADS)

Pan, Shan-Shan; Zhu, Wei-Qiu

2014-10-01

The classical Lotka-Volterra (LV) model is a well-known mathematical model for prey-predator ecosystems. In the present paper, the pulse-type version of stochastic LV model, in which the effect of a random natural environment has been modeled as Poisson white noise, is investigated by using the stochastic averaging method. The averaged generalized Itô stochastic differential equation and Fokker-Planck-Kolmogorov (FPK) equation are derived for prey-predator ecosystem driven by Poisson white noise. Approximate stationary solution for the averaged generalized FPK equation is obtained by using the perturbation method. The effect of prey self-competition parameter ɛ2 s on ecosystem behavior is evaluated. The analytical result is confirmed by corresponding Monte Carlo (MC) simulation.

Do Working Conditions at Older Ages Shape the Health Gradient?

PubMed Central

Schmitz, Lauren L.

2016-01-01

This study examines whether working conditions at the end of workers’ careers impact health and contribute to health disparities across occupations. A dynamic panel correlated random effects model is used in conjunction with a rich data set that combines information from the Health and Retirement Study (HRS), expert ratings of job demands from the Occupational Information Network (O*NET), and mid-career earnings records from the Social Security Administration’s (SSA) Master Earnings File (MEF). Results reveal a strong relationship between positive aspects of the psychosocial work environment and improved self-reported health status, blood pressure, and cognitive function. However, there is little evidence to suggest that working conditions shape observed health disparities between occupations in the years leading up to retirement. PMID:27814483

Qualitative models of seat discomfort including static and dynamic factors.

PubMed

Ebe, K; Griffin, M J

2000-06-01

Judgements of overall seating comfort in dynamic conditions sometimes correlate better with the static characteristics of a seat than with measures of the dynamic environment. This study developed qualitative models of overall seat discomfort to include both static and dynamic seat characteristics. A dynamic factor that reflected how vibration discomfort increased as vibration magnitude increased was combined with a static seat factor which reflected seating comfort without vibration. The ability of the model to predict the relative and overall importance of dynamic and static seat characteristics on comfort was tested in two experiments. A paired comparison experiment, using four polyurethane foam cushions (50, 70, 100, 120 mm thick), provided different static and dynamic comfort when 12 subjects were exposed to one-third octave band random vertical vibration with centre frequencies of 2.5 and 5.5 Hz, at magnitudes of 0.00, 0.25 and 0.50 m x s(-2) rms measured beneath the foam samples. Subject judgements of the relative discomfort of the different conditions depended on both static and dynamic characteristics in a manner consistent with the model. The effect of static and dynamic seat factors on overall seat discomfort was investigated by magnitude estimation using three foam cushions (of different hardness) and a rigid wooden seat at six vibration magnitudes with 20 subjects. Static seat factors (i.e. cushion stiffness) affected the manner in which vibration influenced the overall discomfort: cushions with lower stiffness were more comfortable and more sensitive to changes in vibration magnitude than those with higher stiffness. The experiments confirm that judgements of overall seat discomfort can be affected by both the static and dynamic characteristics of a seat, with the effect depending on vibration magnitude: when vibration magnitude was low, discomfort was dominated by static seat factors; as the vibration magnitude increased, discomfort became dominated by dynamic factors.

Modeling and complexity of stochastic interacting Lévy type financial price dynamics

NASA Astrophysics Data System (ADS)

Wang, Yiduan; Zheng, Shenzhou; Zhang, Wei; Wang, Jun; Wang, Guochao

2018-06-01

In attempt to reproduce and investigate nonlinear dynamics of security markets, a novel nonlinear random interacting price dynamics, which is considered as a Lévy type process, is developed and investigated by the combination of lattice oriented percolation and Potts dynamics, which concerns with the instinctive random fluctuation and the fluctuation caused by the spread of the investors' trading attitudes, respectively. To better understand the fluctuation complexity properties of the proposed model, the complexity analyses of random logarithmic price return and corresponding volatility series are preformed, including power-law distribution, Lempel-Ziv complexity and fractional sample entropy. In order to verify the rationality of the proposed model, the corresponding studies of actual security market datasets are also implemented for comparison. The empirical results reveal that this financial price model can reproduce some important complexity features of actual security markets to some extent. The complexity of returns decreases with the increase of parameters γ1 and β respectively, furthermore, the volatility series exhibit lower complexity than the return series

Macroscopic damping model for structural dynamics with random polycrystalline configurations

NASA Astrophysics Data System (ADS)

Yang, Yantao; Cui, Junzhi; Yu, Yifan; Xiang, Meizhen

2018-06-01

In this paper the macroscopic damping model for dynamical behavior of the structures with random polycrystalline configurations at micro-nano scales is established. First, the global motion equation of a crystal is decomposed into a set of motion equations with independent single degree of freedom (SDOF) along normal discrete modes, and then damping behavior is introduced into each SDOF motion. Through the interpolation of discrete modes, the continuous representation of damping effects for the crystal is obtained. Second, from energy conservation law the expression of the damping coefficient is derived, and the approximate formula of damping coefficient is given. Next, the continuous damping coefficient for polycrystalline cluster is expressed, the continuous dynamical equation with damping term is obtained, and then the concrete damping coefficients for a polycrystalline Cu sample are shown. Finally, by using statistical two-scale homogenization method, the macroscopic homogenized dynamical equation containing damping term for the structures with random polycrystalline configurations at micro-nano scales is set up.

Amoeba-Inspired Heuristic Search Dynamics for Exploring Chemical Reaction Paths.

PubMed

Aono, Masashi; Wakabayashi, Masamitsu

2015-09-01

We propose a nature-inspired model for simulating chemical reactions in a computationally resource-saving manner. The model was developed by extending our previously proposed heuristic search algorithm, called "AmoebaSAT [Aono et al. 2013]," which was inspired by the spatiotemporal dynamics of a single-celled amoeboid organism that exhibits sophisticated computing capabilities in adapting to its environment efficiently [Zhu et al. 2013]. AmoebaSAT is used for solving an NP-complete combinatorial optimization problem [Garey and Johnson 1979], "the satisfiability problem," and finds a constraint-satisfying solution at a speed that is dramatically faster than one of the conventionally known fastest stochastic local search methods [Iwama and Tamaki 2004] for a class of randomly generated problem instances [ http://www.cs.ubc.ca/~hoos/5/benchm.html ]. In cases where the problem has more than one solution, AmoebaSAT exhibits dynamic transition behavior among a variety of the solutions. Inheriting these features of AmoebaSAT, we formulate "AmoebaChem," which explores a variety of metastable molecules in which several constraints determined by input atoms are satisfied and generates dynamic transition processes among the metastable molecules. AmoebaChem and its developed forms will be applied to the study of the origins of life, to discover reaction paths for which expected or unexpected organic compounds may be formed via unknown unstable intermediates and to estimate the likelihood of each of the discovered paths.

Photoinduced nanobubble-driven superfast diffusion of nanoparticles imaged by 4D electron microscopy

PubMed Central

Fu, Xuewen; Chen, Bin; Tang, Jau; Zewail, Ahmed H.

2017-01-01

Dynamics of active or propulsive Brownian particles in nonequilibrium status have recently attracted great interest in many fields including artificial micro/nanoscopic motors and biological entities. Understanding of their dynamics can provide insight into the statistical properties of physical and biological systems far from equilibrium. We report the translational dynamics of photon-activated gold nanoparticles (NPs) in water imaged by liquid-cell four-dimensional electron microscopy (4D-EM) with high spatiotemporal resolution. Under excitation of femtosecond laser pulses, we observed that those NPs exhibit superfast diffusive translation with a diffusion constant four to five orders of magnitude greater than that in the absence of laser excitation. The measured diffusion constant follows a power-law dependence on the laser fluence and a linear increase with the laser repetition rate, respectively. This superfast diffusion of the NPs is induced by a strong random driving force arising from the photoinduced steam nanobubbles (NBs) near the NP surface. In contrast, the NPs exhibit a superfast ballistic translation at a short time scale down to nanoseconds. Combining with a physical model simulation, this study reveals a photoinduced NB propulsion mechanism for propulsive motion, providing physical insights into better design of light-activated artificial micro/nanomotors. The liquid-cell 4D-EM also provides the potential of studying other numerical dynamical behaviors in their native environments. PMID:28875170

Effects of learning climate and registered nurse staffing on medication errors.

PubMed

Chang, Yunkyung; Mark, Barbara

2011-01-01

Despite increasing recognition of the significance of learning from errors, little is known about how learning climate contributes to error reduction. The purpose of this study was to investigate whether learning climate moderates the relationship between error-producing conditions and medication errors. A cross-sectional descriptive study was done using data from 279 nursing units in 146 randomly selected hospitals in the United States. Error-producing conditions included work environment factors (work dynamics and nurse mix), team factors (communication with physicians and nurses' expertise), personal factors (nurses' education and experience), patient factors (age, health status, and previous hospitalization), and medication-related support services. Poisson models with random effects were used with the nursing unit as the unit of analysis. A significant negative relationship was found between learning climate and medication errors. It also moderated the relationship between nurse mix and medication errors: When learning climate was negative, having more registered nurses was associated with fewer medication errors. However, no relationship was found between nurse mix and medication errors at either positive or average levels of learning climate. Learning climate did not moderate the relationship between work dynamics and medication errors. The way nurse mix affects medication errors depends on the level of learning climate. Nursing units with fewer registered nurses and frequent medication errors should examine their learning climate. Future research should be focused on the role of learning climate as related to the relationships between nurse mix and medication errors.

Moving Target Techniques: Cyber Resilience throught Randomization, Diversity, and Dynamism

DTIC Science & Technology

2017-03-03

Moving Target Techniques: Cyber Resilience through Randomization, Diversity, and Dynamism Hamed Okhravi and Howard Shrobe Overview: The static...nature of computer systems makes them vulnerable to cyber attacks. Consider a situation where an attacker wants to compromise a remote system running... cyber resilience that attempts to rebalance the cyber landscape is known as cyber moving target (MT) (or just moving target) techniques. Moving target

Vibration Testing of an Operating Stirling Convertor

NASA Technical Reports Server (NTRS)

Hughes, William O.; McNelis, Mark E.; Goodnight, Thomas W.

2000-01-01

The NASA John H. Glenn Research Center and the U.S. Department of Energy are currently developing a Stirling convertor for use as an advanced spacecraft power system for future NASA deep-space missions. As part of this development, a Stirling Technology Demonstrator Convertor (TDC) was recently tested to verify its survivability and capability of withstanding its expected launch random vibration environment. The TDC was fully operational (producing power) during the random vibration testing. The output power of the convertor was measured during the testing, and these results are discussed in this paper. Numerous accelerometers and force gauges were also present which provided information on the dynamic characteristics of the TDC and an indication of any possible damage due to vibration. These measurements will also be discussed in this paper. The vibration testing of the Stirling TDC was extremely successful. The TDC survived all its vibration testing with no structural damage or functional performance degradation. As a result of this testing, the Stirling convertor's capability to withstand vibration has been demonstrated, enabling its usage in future spacecraft power systems.

Eternal non-Markovianity: from random unitary to Markov chain realisations.

PubMed

Megier, Nina; Chruściński, Dariusz; Piilo, Jyrki; Strunz, Walter T

2017-07-25

The theoretical description of quantum dynamics in an intriguing way does not necessarily imply the underlying dynamics is indeed intriguing. Here we show how a known very interesting master equation with an always negative decay rate [eternal non-Markovianity (ENM)] arises from simple stochastic Schrödinger dynamics (random unitary dynamics). Equivalently, it may be seen as arising from a mixture of Markov (semi-group) open system dynamics. Both these approaches lead to a more general family of CPT maps, characterized by a point within a parameter triangle. Our results show how ENM quantum dynamics can be realised easily in the laboratory. Moreover, we find a quantum time-continuously measured (quantum trajectory) realisation of the dynamics of the ENM master equation based on unitary transformations and projective measurements in an extended Hilbert space, guided by a classical Markov process. Furthermore, a Gorini-Kossakowski-Sudarshan-Lindblad (GKSL) representation of the dynamics in an extended Hilbert space can be found, with a remarkable property: there is no dynamics in the ancilla state. Finally, analogous constructions for two qubits extend these results from non-CP-divisible to non-P-divisible dynamics.

Solution to the SLAM problem in low dynamic environments using a pose graph and an RGB-D sensor.

PubMed

Lee, Donghwa; Myung, Hyun

2014-07-11

In this study, we propose a solution to the simultaneous localization and mapping (SLAM) problem in low dynamic environments by using a pose graph and an RGB-D (red-green-blue depth) sensor. The low dynamic environments refer to situations in which the positions of objects change over long intervals. Therefore, in the low dynamic environments, robots have difficulty recognizing the repositioning of objects unlike in highly dynamic environments in which relatively fast-moving objects can be detected using a variety of moving object detection algorithms. The changes in the environments then cause groups of false loop closing when the same moved objects are observed for a while, which means that conventional SLAM algorithms produce incorrect results. To address this problem, we propose a novel SLAM method that handles low dynamic environments. The proposed method uses a pose graph structure and an RGB-D sensor. First, to prune the falsely grouped constraints efficiently, nodes of the graph, that represent robot poses, are grouped according to the grouping rules with noise covariances. Next, false constraints of the pose graph are pruned according to an error metric based on the grouped nodes. The pose graph structure is reoptimized after eliminating the false information, and the corrected localization and mapping results are obtained. The performance of the method was validated in real experiments using a mobile robot system.

Dynamical continuous time random Lévy flights

NASA Astrophysics Data System (ADS)

Liu, Jian; Chen, Xiaosong

2016-03-01

The Lévy flights' diffusive behavior is studied within the framework of the dynamical continuous time random walk (DCTRW) method, while the nonlinear friction is introduced in each step. Through the DCTRW method, Lévy random walker in each step flies by obeying the Newton's Second Law while the nonlinear friction f(v) = - γ0v - γ2v3 being considered instead of Stokes friction. It is shown that after introducing the nonlinear friction, the superdiffusive Lévy flights converges, behaves localization phenomenon with long time limit, but for the Lévy index μ = 2 case, it is still Brownian motion.

Small-World Network Spectra in Mean-Field Theory

NASA Astrophysics Data System (ADS)

Grabow, Carsten; Grosskinsky, Stefan; Timme, Marc

2012-05-01

Collective dynamics on small-world networks emerge in a broad range of systems with their spectra characterizing fundamental asymptotic features. Here we derive analytic mean-field predictions for the spectra of small-world models that systematically interpolate between regular and random topologies by varying their randomness. These theoretical predictions agree well with the actual spectra (obtained by numerical diagonalization) for undirected and directed networks and from fully regular to strongly random topologies. These results may provide analytical insights to empirically found features of dynamics on small-world networks from various research fields, including biology, physics, engineering, and social science.

Scaling Techniques for Combustion Device Random Vibration Predictions

NASA Technical Reports Server (NTRS)

Kenny, R. J.; Ferebee, R. C.; Duvall, L. D.

2016-01-01

This work presents compares scaling techniques that can be used for prediction of combustion device component random vibration levels with excitation due to the internal combustion dynamics. Acceleration and unsteady dynamic pressure data from multiple component test programs are compared and normalized per the two scaling approaches reviewed. Two scaling technique are reviewed and compared against the collected component test data. The first technique is an existing approach developed by Barrett, and the second technique is an updated approach new to this work. Results from utilizing both techniques are presented and recommendations about future component random vibration prediction approaches are given.

Study on Nonlinear Vibration Analysis of Gear System with Random Parameters

NASA Astrophysics Data System (ADS)

Tong, Cao; Liu, Xiaoyuan; Fan, Li

2018-03-01

In order to study the dynamic characteristics of gear nonlinear vibration system and the influence of random parameters, firstly, a nonlinear stochastic vibration analysis model of gear 3-DOF is established based on Newton’s Law. And the random response of gear vibration is simulated by stepwise integration method. Secondly, the influence of stochastic parameters such as meshing damping, tooth side gap and excitation frequency on the dynamic response of gear nonlinear system is analyzed by using the stability analysis method such as bifurcation diagram and Lyapunov exponent method. The analysis shows that the stochastic process can not be neglected, which can cause the random bifurcation and chaos of the system response. This study will provide important reference value for vibration engineering designers.

Eye Movement Training and Suggested Gaze Strategies in Tunnel Vision - A Randomized and Controlled Pilot Study.

PubMed

Ivanov, Iliya V; Mackeben, Manfred; Vollmer, Annika; Martus, Peter; Nguyen, Nhung X; Trauzettel-Klosinski, Susanne

2016-01-01

Degenerative retinal diseases, especially retinitis pigmentosa (RP), lead to severe peripheral visual field loss (tunnel vision), which impairs mobility. The lack of peripheral information leads to fewer horizontal eye movements and, thus, diminished scanning in RP patients in a natural environment walking task. This randomized controlled study aimed to improve mobility and the dynamic visual field by applying a compensatory Exploratory Saccadic Training (EST). Oculomotor responses during walking and avoiding obstacles in a controlled environment were studied before and after saccade or reading training in 25 RP patients. Eye movements were recorded using a mobile infrared eye tracker (Tobii glasses) that measured a range of spatial and temporal variables. Patients were randomly assigned to two training conditions: Saccade (experimental) and reading (control) training. All subjects who first performed reading training underwent experimental training later (waiting list control group). To assess the effect of training on subjects, we measured performance in the training task and the following outcome variables related to daily life: Response Time (RT) during exploratory saccade training, Percent Preferred Walking Speed (PPWS), the number of collisions with obstacles, eye position variability, fixation duration, and the total number of fixations including the ones in the subjects' blind area of the visual field. In the saccade training group, RTs on average decreased, while the PPWS significantly increased. The improvement persisted, as tested 6 weeks after the end of the training. On average, the eye movement range of RP patients before and after training was similar to that of healthy observers. In both, the experimental and reading training groups, we found many fixations outside the subjects' seeing visual field before and after training. The average fixation duration was significantly shorter after the training, but only in the experimental training condition. We conclude that the exploratory saccade training was beneficial for RP patients and resulted in shorter fixation durations after the training. We also found a significant improvement in relative walking speed during navigation in a real-world like controlled environment.

Eye Movement Training and Suggested Gaze Strategies in Tunnel Vision - A Randomized and Controlled Pilot Study

PubMed Central

Ivanov, Iliya V.; Mackeben, Manfred; Vollmer, Annika; Martus, Peter; Nguyen, Nhung X.; Trauzettel-Klosinski, Susanne

2016-01-01

Purpose Degenerative retinal diseases, especially retinitis pigmentosa (RP), lead to severe peripheral visual field loss (tunnel vision), which impairs mobility. The lack of peripheral information leads to fewer horizontal eye movements and, thus, diminished scanning in RP patients in a natural environment walking task. This randomized controlled study aimed to improve mobility and the dynamic visual field by applying a compensatory Exploratory Saccadic Training (EST). Methods Oculomotor responses during walking and avoiding obstacles in a controlled environment were studied before and after saccade or reading training in 25 RP patients. Eye movements were recorded using a mobile infrared eye tracker (Tobii glasses) that measured a range of spatial and temporal variables. Patients were randomly assigned to two training conditions: Saccade (experimental) and reading (control) training. All subjects who first performed reading training underwent experimental training later (waiting list control group). To assess the effect of training on subjects, we measured performance in the training task and the following outcome variables related to daily life: Response Time (RT) during exploratory saccade training, Percent Preferred Walking Speed (PPWS), the number of collisions with obstacles, eye position variability, fixation duration, and the total number of fixations including the ones in the subjects' blind area of the visual field. Results In the saccade training group, RTs on average decreased, while the PPWS significantly increased. The improvement persisted, as tested 6 weeks after the end of the training. On average, the eye movement range of RP patients before and after training was similar to that of healthy observers. In both, the experimental and reading training groups, we found many fixations outside the subjects' seeing visual field before and after training. The average fixation duration was significantly shorter after the training, but only in the experimental training condition. Conclusions We conclude that the exploratory saccade training was beneficial for RP patients and resulted in shorter fixation durations after the training. We also found a significant improvement in relative walking speed during navigation in a real-world like controlled environment. PMID:27351629

Self-organization of complex networks as a dynamical system

NASA Astrophysics Data System (ADS)

Aoki, Takaaki; Yawata, Koichiro; Aoyagi, Toshio

2015-01-01

To understand the dynamics of real-world networks, we investigate a mathematical model of the interplay between the dynamics of random walkers on a weighted network and the link weights driven by a resource carried by the walkers. Our numerical studies reveal that, under suitable conditions, the co-evolving dynamics lead to the emergence of stationary power-law distributions of the resource and link weights, while the resource quantity at each node ceaselessly changes with time. We analyze the network organization as a deterministic dynamical system and find that the system exhibits multistability, with numerous fixed points, limit cycles, and chaotic states. The chaotic behavior of the system leads to the continual changes in the microscopic network dynamics in the absence of any external random noises. We conclude that the intrinsic interplay between the states of the nodes and network reformation constitutes a major factor in the vicissitudes of real-world networks.

Self-organization of complex networks as a dynamical system.

PubMed

Aoki, Takaaki; Yawata, Koichiro; Aoyagi, Toshio

2015-01-01

To understand the dynamics of real-world networks, we investigate a mathematical model of the interplay between the dynamics of random walkers on a weighted network and the link weights driven by a resource carried by the walkers. Our numerical studies reveal that, under suitable conditions, the co-evolving dynamics lead to the emergence of stationary power-law distributions of the resource and link weights, while the resource quantity at each node ceaselessly changes with time. We analyze the network organization as a deterministic dynamical system and find that the system exhibits multistability, with numerous fixed points, limit cycles, and chaotic states. The chaotic behavior of the system leads to the continual changes in the microscopic network dynamics in the absence of any external random noises. We conclude that the intrinsic interplay between the states of the nodes and network reformation constitutes a major factor in the vicissitudes of real-world networks.

Parallel capillary-tube-based extension of thermoacoustic theory for random porous media.

PubMed

Roh, Heui-Seol; Raspet, Richard; Bass, Henry E

2007-03-01

Thermoacoustic theory is extended to stacks made of random bulk media. Characteristics of the porous stack such as the tortuosity and dynamic shape factors are introduced into the thermoacoustic wave equation in the low reduced frequency approximation. Basic thermoacoustic equations for a bulk porous medium are formulated analogously to the equations for a single pore. Use of different dynamic shape factors for the viscous and thermal effects is adopted and scaling using the dynamic shape factors and tortuosity is demonstrated. Comparisons of the calculated and experimentally derived thermoacoustic properties of reticulated vitreous carbon and aluminum foam show good agreement. A consistent mathematical model of sound propagation in a random porous medium with an imposed temperature is developed. This treatment leads to an expression for the coefficient of the temperature gradient in terms of scaled cylindrical thermoviscous functions.

Quantum critical probing and simulation of colored quantum noise

NASA Astrophysics Data System (ADS)

Mascarenhas, Eduardo; de Vega, Inés

2017-12-01

We propose a protocol to simulate the evolution of a non-Markovian open quantum system by considering a collisional process with a many-body system, which plays the role of an environment. As a result of our protocol, the environment spatial correlations are mapped into the time correlations of a noise that drives the dynamics of the open system. Considering the weak coupling limit, the open system can also be considered as a probe of the environment properties. In this regard, when preparing the environment in its ground state, a measurement of the dynamics of the open system allows to determine the length of the environment spatial correlations and therefore its critical properties. To illustrate our proposal we simulate the full system dynamics with matrix-product-states and compare this to the reduced dynamics obtained with an approximated variational master equation.

Dynamical evolution of entanglement of a three-qubit system driven by a classical environmental colored noise

NASA Astrophysics Data System (ADS)

Kenfack, Lionel Tenemeza; Tchoffo, Martin; Fouokeng, Georges Collince; Fai, Lukong Cornelius

2018-04-01

The effects of 1/f^{α } (α =1,2) noise stemming from one or a collection of random bistable fluctuators (RBFs), on the evolution of entanglement, of three non-interacting qubits are investigated. Three different initial configurations of the qubits are analyzed in detail: the Greenberger-Horne-Zeilinger (GHZ)-type states, W-type states and mixed states composed of a GHZ state and a W state (GHZ-W). For each initial configuration, the evolution of entanglement is investigated for three different qubit-environment (Q-E) coupling setups, namely independent environments, mixed environments and common environment coupling. With the help of tripartite negativity and suitable entanglement witnesses, we show that the evolution of entanglement is extremely influenced not only by the initial configuration of the qubits, the spectrum of the environment and the Q-E coupling setup considered, but also by the number of RBF modeling the environment. Indeed, we find that the decay of entanglement is accelerated when the number of fluctuators modeling the environment is increased. Furthermore, we find that entanglement can survive indefinitely to the detrimental effects of noise even for increasingly larger numbers of RBFs. On the other hand, we find that the proficiency of the tripartite entanglement witnesses to detect entanglement is weaker than that of the tripartite negativity and that the symmetry of the initial states is broken when the qubits are coupled to the noise in mixed environments. Finally, we find that the 1 / f noise is more harmful to the survival of entanglement than the 1/f2 noise and that the mixed GHZ-W states followed by the GHZ-type states preserve better entanglement than the W-type ones.

Trans-algorithmic nature of learning in biological systems.

PubMed

Shimansky, Yury P

2018-05-02

Learning ability is a vitally important, distinctive property of biological systems, which provides dynamic stability in non-stationary environments. Although several different types of learning have been successfully modeled using a universal computer, in general, learning cannot be described by an algorithm. In other words, algorithmic approach to describing the functioning of biological systems is not sufficient for adequate grasping of what is life. Since biosystems are parts of the physical world, one might hope that adding some physical mechanisms and principles to the concept of algorithm could provide extra possibilities for describing learning in its full generality. However, a straightforward approach to that through the so-called physical hypercomputation so far has not been successful. Here an alternative approach is proposed. Biosystems are described as achieving enumeration of possible physical compositions though random incremental modifications inflicted on them by active operating resources (AORs) in the environment. Biosystems learn through algorithmic regulation of the intensity of the above modifications according to a specific optimality criterion. From the perspective of external observers, biosystems move in the space of different algorithms driven by random modifications imposed by the environmental AORs. A particular algorithm is only a snapshot of that motion, while the motion itself is essentially trans-algorithmic. In this conceptual framework, death of unfit members of a population, for example, is viewed as a trans-algorithmic modification made in the population as a biosystem by environmental AORs. Numerous examples of AOR utilization in biosystems of different complexity, from viruses to multicellular organisms, are provided.

Orientation Preferences and Motion Sickness Induced in a Virtual Reality Environment.

PubMed

Chen, Wei; Chao, Jian-Gang; Zhang, Yan; Wang, Jin-Kun; Chen, Xue-Wen; Tan, Cheng

2017-10-01

Astronauts' orientation preferences tend to correlate with their susceptibility to space motion sickness (SMS). Orientation preferences appear universally, since variable sensory cue priorities are used between individuals. However, SMS susceptibility changes after proper training, while orientation preferences seem to be intrinsic proclivities. The present study was conducted to investigate whether orientation preferences change if susceptibility is reduced after repeated exposure to a virtual reality (VR) stimulus environment that induces SMS. A horizontal supine posture was chosen to create a sensory context similar to weightlessness, and two VR devices were used to produce a highly immersive virtual scene. Subjects were randomly allocated to an experimental group (trained through exposure to a provocative rotating virtual scene) and a control group (untrained). All subjects' orientation preferences were measured twice with the same interval, but the experimental group was trained three times during the interval, while the control group was not. Trained subjects were less susceptible to SMS, with symptom scores reduced by 40%. Compared with untrained subjects, trained subjects' orientation preferences were significantly different between pre- and posttraining assessments. Trained subjects depended less on visual cues, whereas few subjects demonstrated the opposite tendency. Results suggest that visual information may be inefficient and unreliable for body orientation and stabilization in a rotating visual scene, while reprioritizing preferences for different sensory cues was dynamic and asymmetric between individuals. The present findings should facilitate customization of efficient and proper training for astronauts with different sensory prioritization preferences and dynamic characteristics.Chen W, Chao J-G, Zhang Y, Wang J-K, Chen X-W, Tan C. Orientation preferences and motion sickness induced in a virtual reality environment. Aerosp Med Hum Perform. 2017; 88(10):903-910.

Hidden acoustic information revealed by intentional nonlinearity

NASA Astrophysics Data System (ADS)

Dowling, David R.

2017-11-01

Acoustic waves are omnipresent in modern life and are well described by the linearized equations of fluid dynamics. Once generated, acoustic waves carry and collect information about their source and the environment through which they propagate, respectively, and this information may be retrieved by analyzing recordings of these waves. Because of this, acoustics is the primary means for observation, surveillance, reconnaissance, and remote sensing in otherwise opaque environments, such as the Earth's oceans and crust, and the interior of the human body. For such information-retrieval tasks, acoustic fields are nearly always interrogated within their recorded frequency range or bandwidth. However, this frequency-range restriction is not general; acoustic fields may also carry (hidden) information at frequencies outside their bandwidth. Although such a claim may seem counter intuitive, hidden acoustic-field information can be revealed by re-introducing a marquee trait of fluid dynamics: nonlinearity. In particular, an intentional quadratic nonlinearity - a form of intra-signal heterodyning - can be used to obtain acoustic field information at frequencies outside a recorded acoustic field's bandwidth. This quadratic nonlinearity enables a variety of acoustic remote sensing applications that were long thought to be impossible. In particular, it allows the detrimental effects of sparse recordings and random scattering to be suppressed when the original acoustic field has sufficient bandwidth. In this presentation, the topic is developed heuristically, with a just brief exposition of the relevant mathematics. Hidden acoustic field information is then revealed from simulated and measured acoustic fields in simple and complicated acoustic environments involving frequencies from a few Hertz to more than 100 kHz, and propagation distances from tens of centimeters to hundreds of kilometers. Sponsored by ONR, NAVSEA, and NSF.

The influence of an uncertain force environment on reshaping trial-to-trial motor variability.

PubMed

Izawa, Jun; Yoshioka, Toshinori; Osu, Rieko

2014-09-10

Motor memory is updated to generate ideal movements in a novel environment. When the environment changes every trial randomly, how does the brain incorporate this uncertainty into motor memory? To investigate how the brain adapts to an uncertain environment, we considered a reach adaptation protocol where individuals practiced moving in a force field where a noise was injected. After they had adapted, we measured the trial-to-trial variability in the temporal profiles of the produced hand force. We found that the motor variability was significantly magnified by the adaptation to the random force field. Temporal profiles of the motor variance were significantly dissociable between two different types of random force fields experienced. A model-based analysis suggests that the variability is generated by noise in the gains of the internal model. It further suggests that the trial-to-trial motor variability magnified by the adaptation in a random force field is generated by the uncertainty of the internal model formed in the brain as a result of the adaptation.

Investigations Into Internal and External Aspects of Dynamic Agent-Environment Couplings

NASA Astrophysics Data System (ADS)

Dautenhahn, Kerstin

This paper originates from my work on `social agents'. An issue which I consider important to this kind of research is the dynamic coupling of an agent with its social and non-social environment. I hypothesize `internal dynamics' inside an agent as a basic step towards understanding. The paper therefore focuses on the internal and external dynamics which couple an agent to its environment. The issue of embodiment in animals and artifacts and its relation to `social dynamics' is discussed first. I argue that embodiment is linked to a concept of a body and is not necessarily given when running a control program on robot hardware. I stress the individual characteristics of an embodied cognitive system, as well as its social embeddedness. I outline the framework of a physical-psychological state space which changes dynamically in a self-modifying way as a holistic approach towards embodied human and artificial cognition. This framework is meant to discuss internal and external dynamics of an embodied, natural or artificial agent. In order to stress the importance of a dynamic memory I introduce the concept of an `autobiographical agent'. The second part of the paper gives an example of the implementation of a physical agent, a robot, which is dynamically coupled to its environment by balancing on a seesaw. For the control of the robot a behavior-oriented approach using the dynamical systems metaphor is used. The problem is studied through building a complete and co-adapted robot-environment system. A seesaw which varies its orientation with one or two degrees of freedom is used as the artificial `habitat'. The problem of stabilizing the body axis by active motion on a seesaw is solved by using two inclination sensors and a parallel, behavior-oriented control architecture. Some experiments are described which demonstrate the exploitation of the dynamics of the robot-environment system.

Most Undirected Random Graphs Are Amplifiers of Selection for Birth-Death Dynamics, but Suppressors of Selection for Death-Birth Dynamics.

PubMed

Hindersin, Laura; Traulsen, Arne

2015-11-01

We analyze evolutionary dynamics on graphs, where the nodes represent individuals of a population. The links of a node describe which other individuals can be displaced by the offspring of the individual on that node. Amplifiers of selection are graphs for which the fixation probability is increased for advantageous mutants and decreased for disadvantageous mutants. A few examples of such amplifiers have been developed, but so far it is unclear how many such structures exist and how to construct them. Here, we show that almost any undirected random graph is an amplifier of selection for Birth-death updating, where an individual is selected to reproduce with probability proportional to its fitness and one of its neighbors is replaced by that offspring at random. If we instead focus on death-Birth updating, in which a random individual is removed and its neighbors compete for the empty spot, then the same ensemble of graphs consists of almost only suppressors of selection for which the fixation probability is decreased for advantageous mutants and increased for disadvantageous mutants. Thus, the impact of population structure on evolutionary dynamics is a subtle issue that will depend on seemingly minor details of the underlying evolutionary process.

Fractal attractors in economic growth models with random pollution externalities

NASA Astrophysics Data System (ADS)

La Torre, Davide; Marsiglio, Simone; Privileggi, Fabio

2018-05-01

We analyze a discrete time two-sector economic growth model where the production technologies in the final and human capital sectors are affected by random shocks both directly (via productivity and factor shares) and indirectly (via a pollution externality). We determine the optimal dynamics in the decentralized economy and show how these dynamics can be described in terms of a two-dimensional affine iterated function system with probability. This allows us to identify a suitable parameter configuration capable of generating exactly the classical Barnsley's fern as the attractor of the log-linearized optimal dynamical system.

Deterministic chaotic dynamics of Raba River flow (Polish Carpathian Mountains)

NASA Astrophysics Data System (ADS)

Kędra, Mariola

2014-02-01

Is the underlying dynamics of river flow random or deterministic? If it is deterministic, is it deterministic chaotic? This issue is still controversial. The application of several independent methods, techniques and tools for studying daily river flow data gives consistent, reliable and clear-cut results to the question. The outcomes point out that the investigated discharge dynamics is not random but deterministic. Moreover, the results completely confirm the nonlinear deterministic chaotic nature of the studied process. The research was conducted on daily discharge from two selected gauging stations of the mountain river in southern Poland, the Raba River.

Population and Environment

PubMed Central

de Sherbinin, Alex; Carr, David; Cassels, Susan; Jiang, Leiwen

2009-01-01

The interactions between human population dynamics and the environment have often been viewed mechanistically. This review elucidates the complexities and contextual specificities of population-environment relationships in a number of domains. It explores the ways in which demographers and other social scientists have sought to understand the relationships among a full range of population dynamics (e.g., population size, growth, density, age and sex composition, migration, urbanization, vital rates) and environmental changes. The chapter briefly reviews a number of the theories for understanding population and the environment and then proceeds to provide a state-of-the-art review of studies that have examined population dynamics and their relationship to five environmental issue areas. The review concludes by relating population-environment research to emerging work on human-environment systems. PMID:20011237

A scaling law for random walks on networks

PubMed Central

Perkins, Theodore J.; Foxall, Eric; Glass, Leon; Edwards, Roderick

2014-01-01

The dynamics of many natural and artificial systems are well described as random walks on a network: the stochastic behaviour of molecules, traffic patterns on the internet, fluctuations in stock prices and so on. The vast literature on random walks provides many tools for computing properties such as steady-state probabilities or expected hitting times. Previously, however, there has been no general theory describing the distribution of possible paths followed by a random walk. Here, we show that for any random walk on a finite network, there are precisely three mutually exclusive possibilities for the form of the path distribution: finite, stretched exponential and power law. The form of the distribution depends only on the structure of the network, while the stepping probabilities control the parameters of the distribution. We use our theory to explain path distributions in domains such as sports, music, nonlinear dynamics and stochastic chemical kinetics. PMID:25311870

Conserved linear dynamics of single-molecule Brownian motion.

PubMed

Serag, Maged F; Habuchi, Satoshi

2017-06-06

Macromolecular diffusion in homogeneous fluid at length scales greater than the size of the molecule is regarded as a random process. The mean-squared displacement (MSD) of molecules in this regime increases linearly with time. Here we show that non-random motion of DNA molecules in this regime that is undetectable by the MSD analysis can be quantified by characterizing the molecular motion relative to a latticed frame of reference. Our lattice occupancy analysis reveals unexpected sub-modes of motion of DNA that deviate from expected random motion in the linear, diffusive regime. We demonstrate that a subtle interplay between these sub-modes causes the overall diffusive motion of DNA to appear to conform to the linear regime. Our results show that apparently random motion of macromolecules could be governed by non-random dynamics that are detectable only by their relative motion. Our analytical approach should advance broad understanding of diffusion processes of fundamental relevance.

Conserved linear dynamics of single-molecule Brownian motion

PubMed Central

Serag, Maged F.; Habuchi, Satoshi

2017-01-01

Macromolecular diffusion in homogeneous fluid at length scales greater than the size of the molecule is regarded as a random process. The mean-squared displacement (MSD) of molecules in this regime increases linearly with time. Here we show that non-random motion of DNA molecules in this regime that is undetectable by the MSD analysis can be quantified by characterizing the molecular motion relative to a latticed frame of reference. Our lattice occupancy analysis reveals unexpected sub-modes of motion of DNA that deviate from expected random motion in the linear, diffusive regime. We demonstrate that a subtle interplay between these sub-modes causes the overall diffusive motion of DNA to appear to conform to the linear regime. Our results show that apparently random motion of macromolecules could be governed by non-random dynamics that are detectable only by their relative motion. Our analytical approach should advance broad understanding of diffusion processes of fundamental relevance. PMID:28585925

Conserved linear dynamics of single-molecule Brownian motion

NASA Astrophysics Data System (ADS)

Serag, Maged F.; Habuchi, Satoshi

2017-06-01

Macromolecular diffusion in homogeneous fluid at length scales greater than the size of the molecule is regarded as a random process. The mean-squared displacement (MSD) of molecules in this regime increases linearly with time. Here we show that non-random motion of DNA molecules in this regime that is undetectable by the MSD analysis can be quantified by characterizing the molecular motion relative to a latticed frame of reference. Our lattice occupancy analysis reveals unexpected sub-modes of motion of DNA that deviate from expected random motion in the linear, diffusive regime. We demonstrate that a subtle interplay between these sub-modes causes the overall diffusive motion of DNA to appear to conform to the linear regime. Our results show that apparently random motion of macromolecules could be governed by non-random dynamics that are detectable only by their relative motion. Our analytical approach should advance broad understanding of diffusion processes of fundamental relevance.

A scaling law for random walks on networks

NASA Astrophysics Data System (ADS)

Perkins, Theodore J.; Foxall, Eric; Glass, Leon; Edwards, Roderick

2014-10-01

The dynamics of many natural and artificial systems are well described as random walks on a network: the stochastic behaviour of molecules, traffic patterns on the internet, fluctuations in stock prices and so on. The vast literature on random walks provides many tools for computing properties such as steady-state probabilities or expected hitting times. Previously, however, there has been no general theory describing the distribution of possible paths followed by a random walk. Here, we show that for any random walk on a finite network, there are precisely three mutually exclusive possibilities for the form of the path distribution: finite, stretched exponential and power law. The form of the distribution depends only on the structure of the network, while the stepping probabilities control the parameters of the distribution. We use our theory to explain path distributions in domains such as sports, music, nonlinear dynamics and stochastic chemical kinetics.

A scaling law for random walks on networks.

PubMed

Perkins, Theodore J; Foxall, Eric; Glass, Leon; Edwards, Roderick

2014-10-14

The dynamics of many natural and artificial systems are well described as random walks on a network: the stochastic behaviour of molecules, traffic patterns on the internet, fluctuations in stock prices and so on. The vast literature on random walks provides many tools for computing properties such as steady-state probabilities or expected hitting times. Previously, however, there has been no general theory describing the distribution of possible paths followed by a random walk. Here, we show that for any random walk on a finite network, there are precisely three mutually exclusive possibilities for the form of the path distribution: finite, stretched exponential and power law. The form of the distribution depends only on the structure of the network, while the stepping probabilities control the parameters of the distribution. We use our theory to explain path distributions in domains such as sports, music, nonlinear dynamics and stochastic chemical kinetics.

Inflation with a graceful exit in a random landscape

NASA Astrophysics Data System (ADS)

Pedro, F. G.; Westphal, A.

2017-03-01

We develop a stochastic description of small-field inflationary histories with a graceful exit in a random potential whose Hessian is a Gaussian random matrix as a model of the unstructured part of the string landscape. The dynamical evolution in such a random potential from a small-field inflation region towards a viable late-time de Sitter (dS) minimum maps to the dynamics of Dyson Brownian motion describing the relaxation of non-equilibrium eigenvalue spectra in random matrix theory. We analytically compute the relaxation probability in a saddle point approximation of the partition function of the eigenvalue distribution of the Wigner ensemble describing the mass matrices of the critical points. When applied to small-field inflation in the landscape, this leads to an exponentially strong bias against small-field ranges and an upper bound N ≪ 10 on the number of light fields N participating during inflation from the non-observation of negative spatial curvature.

Supportive-Expressive Dynamic Psychotherapy in the Community Mental Health System: A Pilot Effectiveness Trial for the Treatment of Depression

PubMed Central

Connolly Gibbons, Mary Beth; Thompson, Sarah M.; Scott, Kelli; Schauble, Lindsay A.; Mooney, Tessa; Thompson, Donald; Green, Patricia; MacArthur, Mary Jo; Crits-Christoph, Paul

2013-01-01

The goal of the current article is to present the results of a randomized pilot investigation of a brief dynamic psychotherapy compared with treatment-as-usual (TAU) in the treatment of moderate-to-severe depression in the community mental health system. Forty patients seeking services for moderate-to-severe depression in the community mental health system were randomized to 12 weeks of psychotherapy, with either a community therapist trained in brief dynamic psychotherapy or a TAU therapist. Results indicated that blind judges could discriminate the dynamic sessions from the TAU sessions on adherence to dynamic interventions. The results indicate moderate-to-large effect sizes in favor of the dynamic psychotherapy over the TAU therapy in the treatment of depression. The Behavior and Symptom Identification Scale-24 showed that 50% of patients treated with dynamic therapy moved into a normative range compared with only 29% of patients treated with TAU. PMID:22962971

Dynamic SLA Negotiation in Autonomic Federated Environments

NASA Astrophysics Data System (ADS)

Rubach, Pawel; Sobolewski, Michael

Federated computing environments offer requestors the ability to dynamically invoke services offered by collaborating providers in the virtual service network. Without an efficient resource management that includes Dynamic SLA Negotiation, however, the assignment of providers to customer's requests cannot be optimized and cannot offer high reliability without relevant SLA guarantees. We propose a new SLA-based SERViceable Metacomputing Environment (SERVME) capable of matching providers based on QoS requirements and performing autonomic provisioning and deprovisioning of services according to dynamic requestor needs. This paper presents the SLA negotiation process that includes on-demand provisioning and uses an object-oriented SLA model for large-scale service-oriented systems supported by SERVME. An initial reference implementation in the SORCER environment is also described.

Model-Based Analysis of Cell Cycle Responses to Dynamically Changing Environments

PubMed Central

Seaton, Daniel D; Krishnan, J

2016-01-01

Cell cycle progression is carefully coordinated with a cell’s intra- and extracellular environment. While some pathways have been identified that communicate information from the environment to the cell cycle, a systematic understanding of how this information is dynamically processed is lacking. We address this by performing dynamic sensitivity analysis of three mathematical models of the cell cycle in Saccharomyces cerevisiae. We demonstrate that these models make broadly consistent qualitative predictions about cell cycle progression under dynamically changing conditions. For example, it is shown that the models predict anticorrelated changes in cell size and cell cycle duration under different environments independently of the growth rate. This prediction is validated by comparison to available literature data. Other consistent patterns emerge, such as widespread nonmonotonic changes in cell size down generations in response to parameter changes. We extend our analysis by investigating glucose signalling to the cell cycle, showing that known regulation of Cln3 translation and Cln1,2 transcription by glucose is sufficient to explain the experimentally observed changes in cell cycle dynamics at different glucose concentrations. Together, these results provide a framework for understanding the complex responses the cell cycle is capable of producing in response to dynamic environments. PMID:26741131

Activated aging dynamics and effective trap model description in the random energy model

NASA Astrophysics Data System (ADS)

Baity-Jesi, M.; Biroli, G.; Cammarota, C.

2018-01-01

We study the out-of-equilibrium aging dynamics of the random energy model (REM) ruled by a single spin-flip Metropolis dynamics. We focus on the dynamical evolution taking place on time-scales diverging with the system size. Our aim is to show to what extent the activated dynamics displayed by the REM can be described in terms of an effective trap model. We identify two time regimes: the first one corresponds to the process of escaping from a basin in the energy landscape and to the subsequent exploration of high energy configurations, whereas the second one corresponds to the evolution from a deep basin to the other. By combining numerical simulations with analytical arguments we show why the trap model description does not hold in the former but becomes exact in the second.

Implementation of Dynamic Extensible Adaptive Locally Exchangeable Measures (IDEALEM) v 0.1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sim, Alex; Lee, Dongeun; Wu, K. John

2016-03-04

Handling large streaming data is essential for various applications such as network traffic analysis, social networks, energy cost trends, and environment modeling. However, it is in general intractable to store, compute, search, and retrieve large streaming data. This software addresses a fundamental issue, which is to reduce the size of large streaming data and still obtain accurate statistical analysis. As an example, when a high-speed network such as 100 Gbps network is monitored, the collected measurement data rapidly grows so that polynomial time algorithms (e.g., Gaussian processes) become intractable. One possible solution to reduce the storage of vast amounts ofmore » measured data is to store a random sample, such as one out of 1000 network packets. However, such static sampling methods (linear sampling) have drawbacks: (1) it is not scalable for high-rate streaming data, and (2) there is no guarantee of reflecting the underlying distribution. In this software, we implemented a dynamic sampling algorithm, based on the recent technology from the relational dynamic bayesian online locally exchangeable measures, that reduces the storage of data records in a large scale, and still provides accurate analysis of large streaming data. The software can be used for both online and offline data records.« less

Mode Reduction and Upscaling of Reactive Transport Under Incomplete Mixing

NASA Astrophysics Data System (ADS)

Lester, D. R.; Bandopadhyay, A.; Dentz, M.; Le Borgne, T.

2016-12-01

Upscaling of chemical reactions in partially-mixed fluid environments is a challenging problem due to the detailed interactions between inherently nonlinear reaction kinetics and complex spatio-temporal concentration distributions under incomplete mixing. We address this challenge via the development of an order reduction method for the advection-diffusion-reaction equation (ADRE) via projection of the reaction kinetics onto a small number N of leading eigenmodes of the advection-diffusion operator (the so-called "strange eigenmodes" of the flow) as an N-by-N nonlinear system, whilst mixing dynamics only are projected onto the remaining modes. For simple kinetics and moderate Péclet and Damkhöler numbers, this approach yields analytic solutions for the concentration mean, evolving spatio-temporal distribution and PDF in terms of the well-mixed reaction kinetics and mixing dynamics. For more complex kinetics or large Péclet or Damkhöler numbers only a small number of modes are required to accurately quantify the mixing and reaction dynamics in terms of the concentration field and PDF, facilitating greatly simplified approximation and analysis of reactive transport. Approximate solutions of this low-order nonlinear system provide quantiative predictions of the evolving concentration PDF. We demonstrate application of this method to a simple random flow and various mass-action reaction kinetics.

Numerical approach on dynamic self-assembly of colloidal particles

NASA Astrophysics Data System (ADS)

Ibrahimi, Muhamet; Ilday, Serim; Makey, Ghaith; Pavlov, Ihor; Yavuz, Özgàn; Gulseren, Oguz; Ilday, Fatih Omer

Far from equilibrium systems of artificial ensembles are crucial for understanding many intelligent features in self-organized natural systems. However, the lack of established theory underlies a need for numerical implementations. Inspired by a novel work, we simulate a solution-suspended colloidal system that dynamically self assembles due to convective forces generated in the solvent when heated by a laser. In order to incorporate with random fluctuations of particles and continuously changing flow, we exploit a random-walk based Brownian motion model and a fluid dynamics solver prepared for games, respectively. Simulation results manage to fit to experiments and show many quantitative features of a non equilibrium dynamic self assembly, including phase space compression and an ensemble-energy input feedback loop.

Nonlinear Dynamic Characteristics of Oil-in-Water Emulsions

NASA Astrophysics Data System (ADS)

Yin, Zhaoqi; Han, Yunfeng; Ren, Yingyu; Yang, Qiuyi; Jin, Ningde

2016-08-01

In this article, the nonlinear dynamic characteristics of oil-in-water emulsions under the addition of surfactant were experimentally investigated. Firstly, based on the vertical upward oil-water two-phase flow experiment in 20 mm inner diameter (ID) testing pipe, dynamic response signals of oil-in-water emulsions were recorded using vertical multiple electrode array (VMEA) sensor. Afterwards, the recurrence plot (RP) algorithm and multi-scale weighted complexity entropy causality plane (MS-WCECP) were employed to analyse the nonlinear characteristics of the signals. The results show that the certainty is decreasing and the randomness is increasing with the increment of surfactant concentration. This article provides a novel method for revealing the nonlinear dynamic characteristics, complexity, and randomness of oil-in-water emulsions with experimental measurement signals.

Metabolic gene regulation in a dynamically changing environment.

PubMed

Bennett, Matthew R; Pang, Wyming Lee; Ostroff, Natalie A; Baumgartner, Bridget L; Nayak, Sujata; Tsimring, Lev S; Hasty, Jeff

2008-08-28

Natural selection dictates that cells constantly adapt to dynamically changing environments in a context-dependent manner. Gene-regulatory networks often mediate the cellular response to perturbation, and an understanding of cellular adaptation will require experimental approaches aimed at subjecting cells to a dynamic environment that mimics their natural habitat. Here we monitor the response of Saccharomyces cerevisiae metabolic gene regulation to periodic changes in the external carbon source by using a microfluidic platform that allows precise, dynamic control over environmental conditions. We show that the metabolic system acts as a low-pass filter that reliably responds to a slowly changing environment, while effectively ignoring fast fluctuations. The sensitive low-frequency response was significantly faster than in predictions arising from our computational modelling, and this discrepancy was resolved by the discovery that two key galactose transcripts possess half-lives that depend on the carbon source. Finally, to explore how induction characteristics affect frequency response, we compare two S. cerevisiae strains and show that they have the same frequency response despite having markedly different induction properties. This suggests that although certain characteristics of the complex networks may differ when probed in a static environment, the system has been optimized for a robust response to a dynamically changing environment.

Anomalous diffusion of water molecules at grain boundaries in ice Ih.

PubMed

Moreira, Pedro Augusto Franco Pinheiro; Veiga, Roberto Gomes de Aguiar; Ribeiro, Ingrid de Almeida; Freitas, Rodrigo; Helfferich, Julian; de Koning, Maurice

2018-05-23

Using ab initio and classical molecular dynamics simulations, we study pre-melting phenomena in pristine coincident-site-lattice grain boundaries (GBs) in proton-disordered hexagonal ice Ih at temperatures just below the melting point Tm. Concerning pre-melt-layer thicknesses, the results are consistent with the available experimental estimates for low-disorder impurity-free GBs. With regard to molecular mobility, the simulations provide a key new insight: the translational motion of the water molecules is found to be subdiffusive for time scales from ∼10 ns up to at least 0.1 μs. Moreover, the fact that the anomalous diffusion occurs even at temperatures just below Tm where the bulk supercooled liquid still diffuses normally suggests that it is related to the confinement of the GB pre-melt layers by the surrounding crystalline environment. Furthermore, we show that this behavior can be characterized by continuous-time random walk models in which the waiting-time distributions decay according to power-laws that are very similar to those describing dynamics in glass-forming systems.

Quenched Large Deviations for Simple Random Walks on Percolation Clusters Including Long-Range Correlations

NASA Astrophysics Data System (ADS)

Berger, Noam; Mukherjee, Chiranjib; Okamura, Kazuki

2018-03-01

We prove a quenched large deviation principle (LDP) for a simple random walk on a supercritical percolation cluster (SRWPC) on {Z^d} ({d ≥ 2}). The models under interest include classical Bernoulli bond and site percolation as well as models that exhibit long range correlations, like the random cluster model, the random interlacement and the vacant set of random interlacements (for {d ≥ 3}) and the level sets of the Gaussian free field ({d≥ 3}). Inspired by the methods developed by Kosygina et al. (Commun Pure Appl Math 59:1489-1521, 2006) for proving quenched LDP for elliptic diffusions with a random drift, and by Yilmaz (Commun Pure Appl Math 62(8):1033-1075, 2009) and Rosenbluth (Quenched large deviations for multidimensional random walks in a random environment: a variational formula. Ph.D. thesis, NYU, arXiv:0804.1444v1) for similar results regarding elliptic random walks in random environment, we take the point of view of the moving particle and prove a large deviation principle for the quenched distribution of the pair empirical measures of the environment Markov chain in the non-elliptic case of SRWPC. Via a contraction principle, this reduces easily to a quenched LDP for the distribution of the mean velocity of the random walk and both rate functions admit explicit variational formulas. The main difficulty in our set up lies in the inherent non-ellipticity as well as the lack of translation-invariance stemming from conditioning on the fact that the origin belongs to the infinite cluster. We develop a unifying approach for proving quenched large deviations for SRWPC based on exploiting coercivity properties of the relative entropies in the context of convex variational analysis, combined with input from ergodic theory and invoking geometric properties of the supercritical percolation cluster.

Quenched Large Deviations for Simple Random Walks on Percolation Clusters Including Long-Range Correlations

NASA Astrophysics Data System (ADS)

Berger, Noam; Mukherjee, Chiranjib; Okamura, Kazuki

2017-12-01

We prove a quenched large deviation principle (LDP) for a simple random walk on a supercritical percolation cluster (SRWPC) on {Z^d} ({d ≥ 2} ). The models under interest include classical Bernoulli bond and site percolation as well as models that exhibit long range correlations, like the random cluster model, the random interlacement and the vacant set of random interlacements (for {d ≥ 3} ) and the level sets of the Gaussian free field ({d≥ 3} ). Inspired by the methods developed by Kosygina et al. (Commun Pure Appl Math 59:1489-1521, 2006) for proving quenched LDP for elliptic diffusions with a random drift, and by Yilmaz (Commun Pure Appl Math 62(8):1033-1075, 2009) and Rosenbluth (Quenched large deviations for multidimensional random walks in a random environment: a variational formula. Ph.D. thesis, NYU, arXiv:0804.1444v1) for similar results regarding elliptic random walks in random environment, we take the point of view of the moving particle and prove a large deviation principle for the quenched distribution of the pair empirical measures of the environment Markov chain in the non-elliptic case of SRWPC. Via a contraction principle, this reduces easily to a quenched LDP for the distribution of the mean velocity of the random walk and both rate functions admit explicit variational formulas. The main difficulty in our set up lies in the inherent non-ellipticity as well as the lack of translation-invariance stemming from conditioning on the fact that the origin belongs to the infinite cluster. We develop a unifying approach for proving quenched large deviations for SRWPC based on exploiting coercivity properties of the relative entropies in the context of convex variational analysis, combined with input from ergodic theory and invoking geometric properties of the supercritical percolation cluster.

Short-Time Dynamics of the Random n-Vector Model

NASA Astrophysics Data System (ADS)

Chen, Yuan; Li, Zhi-Bing; Fang, Hai; He, Shun-Shan; Situ, Shu-Ping

2001-11-01

Short-time critical behavior of the random n-vector model is studied by the theoretic renormalization-group approach. Asymptotic scaling laws are studied in a frame of the expansion in ɛ=4-d for n≠1 and {√ɛ} for n=1 respectively. In d<4, the initial slip exponents θ‧ for the order parameter and θ for the response function are calculated up to the second order in ɛ=4-d for n≠1 and {√ɛ} for n=1 at the random fixed point respectively. Our results show that the random impurities exert a strong influence on the short-time dynamics for d<4 and n

Bayesian dynamic modeling of time series of dengue disease case counts.

PubMed

Martínez-Bello, Daniel Adyro; López-Quílez, Antonio; Torres-Prieto, Alexander

2017-07-01

The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model's short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful models for decision-making in public health.

Theory of activated glassy dynamics in randomly pinned fluids.

PubMed

Phan, Anh D; Schweizer, Kenneth S

2018-02-07

We generalize the force-level, microscopic, Nonlinear Langevin Equation (NLE) theory and its elastically collective generalization [elastically collective nonlinear Langevin equation (ECNLE) theory] of activated dynamics in bulk spherical particle liquids to address the influence of random particle pinning on structural relaxation. The simplest neutral confinement model is analyzed for hard spheres where there is no change of the equilibrium pair structure upon particle pinning. As the pinned fraction grows, cage scale dynamical constraints are intensified in a manner that increases with density. This results in the mobile particles becoming more transiently localized, with increases of the jump distance, cage scale barrier, and NLE theory mean hopping time; subtle changes of the dynamic shear modulus are predicted. The results are contrasted with recent simulations. Similarities in relaxation behavior are identified in the dynamic precursor regime, including a roughly exponential, or weakly supra-exponential, growth of the alpha time with pinning fraction and a reduction of dynamic fragility. However, the increase of the alpha time with pinning predicted by the local NLE theory is too small and severely so at very high volume fractions. The strong deviations are argued to be due to the longer range collective elasticity aspect of the problem which is expected to be modified by random pinning in a complex manner. A qualitative physical scenario is offered for how the three distinct aspects that quantify the elastic barrier may change with pinning. ECNLE theory calculations of the alpha time are then presented based on the simplest effective-medium-like treatment for how random pinning modifies the elastic barrier. The results appear to be consistent with most, but not all, trends seen in recent simulations. Key open problems are discussed with regard to both theory and simulation.

Theory of activated glassy dynamics in randomly pinned fluids

NASA Astrophysics Data System (ADS)

Phan, Anh D.; Schweizer, Kenneth S.

2018-02-01

We generalize the force-level, microscopic, Nonlinear Langevin Equation (NLE) theory and its elastically collective generalization [elastically collective nonlinear Langevin equation (ECNLE) theory] of activated dynamics in bulk spherical particle liquids to address the influence of random particle pinning on structural relaxation. The simplest neutral confinement model is analyzed for hard spheres where there is no change of the equilibrium pair structure upon particle pinning. As the pinned fraction grows, cage scale dynamical constraints are intensified in a manner that increases with density. This results in the mobile particles becoming more transiently localized, with increases of the jump distance, cage scale barrier, and NLE theory mean hopping time; subtle changes of the dynamic shear modulus are predicted. The results are contrasted with recent simulations. Similarities in relaxation behavior are identified in the dynamic precursor regime, including a roughly exponential, or weakly supra-exponential, growth of the alpha time with pinning fraction and a reduction of dynamic fragility. However, the increase of the alpha time with pinning predicted by the local NLE theory is too small and severely so at very high volume fractions. The strong deviations are argued to be due to the longer range collective elasticity aspect of the problem which is expected to be modified by random pinning in a complex manner. A qualitative physical scenario is offered for how the three distinct aspects that quantify the elastic barrier may change with pinning. ECNLE theory calculations of the alpha time are then presented based on the simplest effective-medium-like treatment for how random pinning modifies the elastic barrier. The results appear to be consistent with most, but not all, trends seen in recent simulations. Key open problems are discussed with regard to both theory and simulation.

Response of moderately thick laminated cross-ply composite shells subjected to random excitation

NASA Technical Reports Server (NTRS)

Elishakoff, Isaak; Cederbaum, Gabriel; Librescu, Liviu

1989-01-01

This study deals with the dynamic response of transverse shear deformable laminated shells subjected to random excitation. The analysis encompasses the following problems: (1) the dynamic response of circular cylindrical shells of finite length excited by an axisymmetric uniform ring loading, stationary in time, and (2) the response of spherical and cylindrical panels subjected to stationary random loadings with uniform spatial distribution. The associated equations governing the structural theory of shells are derived upon discarding the classical Love-Kirchhoff (L-K) assumptions. In this sense, the theory is formulated in the framework of the first-order transverse shear deformation theory (FSDT).

Narrow linewidth short cavity Brillouin random laser based on Bragg grating array fiber and dynamical population inversion gratings

NASA Astrophysics Data System (ADS)

Popov, S. M.; Butov, O. V.; Chamorovski, Y. K.; Isaev, V. A.; Mégret, P.; Korobko, D. A.; Zolotovskii, I. O.; Fotiadi, A. A.

2018-06-01

We report on random lasing observed with 100-m-long fiber comprising an array of weak FBGs inscribed in the fiber core and uniformly distributed over the fiber length. Extended fluctuation-free oscilloscope traces highlight power dynamics typical for lasing. An additional piece of Er-doped fiber included into the laser cavity enables a stable laser generation with a linewidth narrower than 10 kHz.

Parallel Processing and Scientific Applications

DTIC Science & Technology

1992-11-30

Lattice QCD Calculations on the Connection Machine), SIAM News 24, 1 (May 1991) 5. C. F. Baillie and D. A. Johnston, Crumpling Dynamically Triangulated...hypercubic lattice ; in the second, the surface is randomly triangulated once at the beginning of the simulation; and in the third the random...Sharpe, QCD with Dynamical Wilson Fermions 1I, Phys. Rev. D44, 3272 (1991), 8. R. Gupta and C. F. Baillie, Critical Behavior of the 2D XY Model, Phys

Pushing the glass transition towards random close packing using self-propelled hard spheres

NASA Astrophysics Data System (ADS)

Ni, Ran; Stuart, Martien A. Cohen; Dijkstra, Marjolein

2013-10-01

Although the concept of random close packing with an almost universal packing fraction of approximately 0.64 for hard spheres was introduced more than half a century ago, there are still ongoing debates. The main difficulty in searching the densest packing is that states with packing fractions beyond the glass transition at approximately 0.58 are inherently non-equilibrium systems, where the dynamics slows down with a structural relaxation time diverging with density; hence, the random close packing is inaccessible. Here we perform simulations of self-propelled hard spheres, and we find that with increasing activity the relaxation dynamics can be sped up by orders of magnitude. The glass transition shifts to higher packing fractions upon increasing the activity, allowing the study of sphere packings with fluid-like dynamics at packing fractions close to RCP. Our study opens new possibilities of investigating dense packings and the glass transition in systems of hard particles.

Stochastic Resonance and Safe Basin of Single-Walled Carbon Nanotubes with Strongly Nonlinear Stiffness under Random Magnetic Field.

PubMed

Xu, Jia; Li, Chao; Li, Yiran; Lim, Chee Wah; Zhu, Zhiwen

2018-05-04

In this paper, a kind of single-walled carbon nanotube nonlinear model is developed and the strongly nonlinear dynamic characteristics of such carbon nanotubes subjected to random magnetic field are studied. The nonlocal effect of the microstructure is considered based on Eringen’s differential constitutive model. The natural frequency of the strongly nonlinear dynamic system is obtained by the energy function method, the drift coefficient and the diffusion coefficient are verified. The stationary probability density function of the system dynamic response is given and the fractal boundary of the safe basin is provided. Theoretical analysis and numerical simulation show that stochastic resonance occurs when varying the random magnetic field intensity. The boundary of safe basin has fractal characteristics and the area of safe basin decreases when the intensity of the magnetic field permeability increases.

Study on the Vehicle Dynamic Load Considering the Vehicle-Pavement Coupled Effect

NASA Astrophysics Data System (ADS)

Xu, H. L.; He, L.; An, D.

2017-11-01

The vibration of vehicle-pavement interaction system is sophisticated random vibration process and the vehicle-pavement coupled effect was not considered in the previous study. A new linear elastic model of the vehicle-pavement coupled system was established in the paper. The new model was verified with field measurement which could reflect the real vibration between vehicle and pavement. Using the new model, the study on the vehicle dynamic load considering the vehicle-pavement coupled effect showed that random forces (centralization) between vehicle and pavement were influenced largely by vehicle-pavement coupled effect. Numerical calculation indicated that the maximum of random forces in coupled model was 2.4 times than that in uncoupled model. Inquiring the reason, it was found that the main vibration frequency of the vehicle non-suspension system was similar with that of the vehicle suspension system in the coupled model and the resonance vibration lead to vehicle dynamic load increase significantly.

Effects of a resistance training program on balance and fatigue perception in patients with Parkinson's disease: A randomized controlled trial.

PubMed

Ortiz-Rubio, Araceli; Cabrera-Martos, Irene; Torres-Sánchez, Irene; Casilda-López, Jesús; López-López, Laura; Valenza, Marie Carmen

2017-11-22

Fatigue and balance impairment leads to a loss of independence and are important to adequately manage. The objective of this study was to examine the effects of a resistance training program on dynamic balance and fatigue in patients with Parkinson's disease (PD). Randomized controlled trial. Forty-six patients with PD were randomly allocated to an intervention group receiving a 8-week resistance training program focused on lower limbs or to a control group. Balance was assessed using the Mini-BESTest and fatigue was assessed by the Piper Fatigue Scale. Patients in the intervention group improved significantly (p<0.05) on dynamic balance (reactive postural control and total values) and perceived fatigue. An 8-week resistance training program was found to be effective at improving dynamic balance and fatigue in patients with PD. Copyright © 2017 Elsevier España, S.L.U. All rights reserved.

Dynamic Geometry as a Context for Exploring Conjectures

ERIC Educational Resources Information Center

Wares, Arsalan

2018-01-01

The purpose of this paper is to provide examples of "non-traditional" proof-related activities that can explored in a dynamic geometry environment by university and high school students of mathematics. These propositions were encountered in the dynamic geometry environment. The author believes that teachers can ask their students to…

Optimization Of Mean-Semivariance-Skewness Portfolio Selection Model In Fuzzy Random Environment

NASA Astrophysics Data System (ADS)

Chatterjee, Amitava; Bhattacharyya, Rupak; Mukherjee, Supratim; Kar, Samarjit

2010-10-01

The purpose of the paper is to construct a mean-semivariance-skewness portfolio selection model in fuzzy random environment. The objective is to maximize the skewness with predefined maximum risk tolerance and minimum expected return. Here the security returns in the objectives and constraints are assumed to be fuzzy random variables in nature and then the vagueness of the fuzzy random variables in the objectives and constraints are transformed into fuzzy variables which are similar to trapezoidal numbers. The newly formed fuzzy model is then converted into a deterministic optimization model. The feasibility and effectiveness of the proposed method is verified by numerical example extracted from Bombay Stock Exchange (BSE). The exact parameters of fuzzy membership function and probability density function are obtained through fuzzy random simulating the past dates.

Bayesian Estimation of Random Coefficient Dynamic Factor Models

ERIC Educational Resources Information Center

Song, Hairong; Ferrer, Emilio

2012-01-01

Dynamic factor models (DFMs) have typically been applied to multivariate time series data collected from a single unit of study, such as a single individual or dyad. The goal of DFMs application is to capture dynamics of multivariate systems. When multiple units are available, however, DFMs are not suited to capture variations in dynamics across…

Programmable random interval generator

NASA Technical Reports Server (NTRS)

Lindsey, R. S., Jr.

1973-01-01

Random pulse generator can supply constant-amplitude randomly distributed pulses with average rate ranging from a few counts per second to more than one million counts per second. Generator requires no high-voltage power supply or any special thermal cooling apparatus. Device is uniquely versatile and provides wide dynamic range of operation.

Elastin: a representative ideal protein elastomer.

PubMed Central

Urry, D W; Hugel, T; Seitz, M; Gaub, H E; Sheiba, L; Dea, J; Xu, J; Parker, T

2002-01-01

During the last half century, identification of an ideal (predominantly entropic) protein elastomer was generally thought to require that the ideal protein elastomer be a random chain network. Here, we report two new sets of data and review previous data. The first set of new data utilizes atomic force microscopy to report single-chain force-extension curves for (GVGVP)(251) and (GVGIP)(260), and provides evidence for single-chain ideal elasticity. The second class of new data provides a direct contrast between low-frequency sound absorption (0.1-10 kHz) exhibited by random-chain network elastomers and by elastin protein-based polymers. Earlier composition, dielectric relaxation (1-1000 MHz), thermoelasticity, molecular mechanics and dynamics calculations and thermodynamic and statistical mechanical analyses are presented, that combine with the new data to contrast with random-chain network rubbers and to detail the presence of regular non-random structural elements of the elastin-based systems that lose entropic elastomeric force upon thermal denaturation. The data and analyses affirm an earlier contrary argument that components of elastin, the elastic protein of the mammalian elastic fibre, and purified elastin fibre itself contain dynamic, non-random, regularly repeating structures that exhibit dominantly entropic elasticity by means of a damping of internal chain dynamics on extension. PMID:11911774

Failure and recovery in dynamical networks.

PubMed

Böttcher, L; Luković, M; Nagler, J; Havlin, S; Herrmann, H J

2017-02-03

Failure, damage spread and recovery crucially underlie many spatially embedded networked systems ranging from transportation structures to the human body. Here we study the interplay between spontaneous damage, induced failure and recovery in both embedded and non-embedded networks. In our model the network's components follow three realistic processes that capture these features: (i) spontaneous failure of a component independent of the neighborhood (internal failure), (ii) failure induced by failed neighboring nodes (external failure) and (iii) spontaneous recovery of a component. We identify a metastable domain in the global network phase diagram spanned by the model's control parameters where dramatic hysteresis effects and random switching between two coexisting states are observed. This dynamics depends on the characteristic link length of the embedded system. For the Euclidean lattice in particular, hysteresis and switching only occur in an extremely narrow region of the parameter space compared to random networks. We develop a unifying theory which links the dynamics of our model to contact processes. Our unifying framework may help to better understand controllability in spatially embedded and random networks where spontaneous recovery of components can mitigate spontaneous failure and damage spread in dynamical networks.

Self-Similar Random Process and Chaotic Behavior In Serrated Flow of High Entropy Alloys

PubMed Central

Chen, Shuying; Yu, Liping; Ren, Jingli; Xie, Xie; Li, Xueping; Xu, Ying; Zhao, Guangfeng; Li, Peizhen; Yang, Fuqian; Ren, Yang; Liaw, Peter K.

2016-01-01

The statistical and dynamic analyses of the serrated-flow behavior in the nanoindentation of a high-entropy alloy, Al0.5CoCrCuFeNi, at various holding times and temperatures, are performed to reveal the hidden order associated with the seemingly-irregular intermittent flow. Two distinct types of dynamics are identified in the high-entropy alloy, which are based on the chaotic time-series, approximate entropy, fractal dimension, and Hurst exponent. The dynamic plastic behavior at both room temperature and 200 °C exhibits a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. The fractal dimension of the indentation depth increases with the increase of temperature, and there is an inflection at the holding time of 10 s at the same temperature. A large fractal dimension suggests the concurrent nucleation of a large number of slip bands. In particular, for the indentation with the holding time of 10 s at room temperature, the slip process evolves as a self-similar random process with a weak negative correlation similar to a random walk. PMID:27435922

Self-similar random process and chaotic behavior in serrated flow of high entropy alloys

DOE PAGES

Chen, Shuying; Yu, Liping; Ren, Jingli; ...

2016-07-20

Here, the statistical and dynamic analyses of the serrated-flow behavior in the nanoindentation of a high-entropy alloy, Al 0.5CoCrCuFeNi, at various holding times and temperatures, are performed to reveal the hidden order associated with the seemingly-irregular intermittent flow. Two distinct types of dynamics are identified in the high-entropy alloy, which are based on the chaotic time-series, approximate entropy, fractal dimension, and Hurst exponent. The dynamic plastic behavior at both room temperature and 200 °C exhibits a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. The fractal dimension of the indentation depth increases with the increase of temperature, andmore » there is an inflection at the holding time of 10 s at the same temperature. A large fractal dimension suggests the concurrent nucleation of a large number of slip bands. In particular, for the indentation with the holding time of 10 s at room temperature, the slip process evolves as a self-similar random process with a weak negative correlation similar to a random walk.« less

Self-Similar Random Process and Chaotic Behavior In Serrated Flow of High Entropy Alloys.

PubMed

Chen, Shuying; Yu, Liping; Ren, Jingli; Xie, Xie; Li, Xueping; Xu, Ying; Zhao, Guangfeng; Li, Peizhen; Yang, Fuqian; Ren, Yang; Liaw, Peter K

2016-07-20

The statistical and dynamic analyses of the serrated-flow behavior in the nanoindentation of a high-entropy alloy, Al0.5CoCrCuFeNi, at various holding times and temperatures, are performed to reveal the hidden order associated with the seemingly-irregular intermittent flow. Two distinct types of dynamics are identified in the high-entropy alloy, which are based on the chaotic time-series, approximate entropy, fractal dimension, and Hurst exponent. The dynamic plastic behavior at both room temperature and 200 °C exhibits a positive Lyapunov exponent, suggesting that the underlying dynamics is chaotic. The fractal dimension of the indentation depth increases with the increase of temperature, and there is an inflection at the holding time of 10 s at the same temperature. A large fractal dimension suggests the concurrent nucleation of a large number of slip bands. In particular, for the indentation with the holding time of 10 s at room temperature, the slip process evolves as a self-similar random process with a weak negative correlation similar to a random walk.

Controlling quantum memory-assisted entropic uncertainty in non-Markovian environments

NASA Astrophysics Data System (ADS)

Zhang, Yanliang; Fang, Maofa; Kang, Guodong; Zhou, Qingping

2018-03-01

Quantum memory-assisted entropic uncertainty relation (QMA EUR) addresses that the lower bound of Maassen and Uffink's entropic uncertainty relation (without quantum memory) can be broken. In this paper, we investigated the dynamical features of QMA EUR in the Markovian and non-Markovian dissipative environments. It is found that dynamical process of QMA EUR is oscillation in non-Markovian environment, and the strong interaction is favorable for suppressing the amount of entropic uncertainty. Furthermore, we presented two schemes by means of prior weak measurement and posterior weak measurement reversal to control the amount of entropic uncertainty of Pauli observables in dissipative environments. The numerical results show that the prior weak measurement can effectively reduce the wave peak values of the QMA-EUA dynamic process in non-Markovian environment for long periods of time, but it is ineffectual on the wave minima of dynamic process. However, the posterior weak measurement reversal has an opposite effects on the dynamic process. Moreover, the success probability entirely depends on the quantum measurement strength. We hope that our proposal could be verified experimentally and might possibly have future applications in quantum information processing.

The resonant system: Linking brain-body-environment in sport performance☆.

PubMed

Teques, Pedro; Araújo, Duarte; Seifert, Ludovic; Del Campo, Vicente L; Davids, Keith

2017-01-01

The ecological dynamics approach offers new insights to understand how athlete nervous systems are embedded within the body-environment system in sport. Cognitive neuroscience focuses on the neural bases of athlete behaviors in terms of perceptual, cognitive, and motor functions defined within specific brain structures. Here, we discuss some limitations of this traditional perspective, addressing how athletes functionally adapt perception and action to the dynamics of complex performance environments by continuously perceiving information to regulate goal-directed actions. We examine how recent neurophysiological evidence of functioning in diverse cortical and subcortical regions appears more compatible with an ecological dynamics perspective, than traditional views in cognitive neuroscience. We propose how athlete behaviors in sports may be related to the tuning of resonant mechanisms indicating that perception is a dynamic process involving the whole body of the athlete. We emphasize the important role of metastable dynamics in the brain-body-environment system facilitating continuous interactions with a landscape of affordances (opportunities for action) in a performance environment. We discuss implications of these ideas for performance preparation and practice design in sport. © 2017 Elsevier B.V. All rights reserved.

A Disk Origin for S-Stars in the Galactic Center?

NASA Astrophysics Data System (ADS)

Haislip, G.; Youdin, A. N.

2005-12-01

Young massive stars in the central 0.5" of our Galaxy probe dynamics around supermassive black holes, and challenge our understanding of star formation in extreme environments. Recent observations (Ghez et al. 2005, Eisenhauer et al. 2005) show large eccentricities and a seemingly random distribution of inclinations, which seems to contradict formation in a disk. We investigate scenarios in which the massive S-stars are born with circular, coplanar orbits and perturbed to their current relaxed state. John Chambers' MERCURY code is modified to include post-Newtonian corrections to the gravitational central force of a Schwarzchild hole and Lense-Thirring precession about a Kerr black hole. The role of resonant relaxation (Rauch & Tremaine, 1996) of angular momentum between S-stars and a background stellar halo is studied in this context.

CM-2 Environmental / Modal Testing of Spacehab Racks

NASA Technical Reports Server (NTRS)

McNelis, Mark E.; Goodnight, Thomas W.; Farkas, Michael A.

2001-01-01

Combined environmental/modal vibration testing has been implemented at the NASA Glenn Research Center's Structural Dynamics Laboratory. The benefits of combined vibration testing are that it facilitates test article modal characterization and vibration qualification testing. The Combustion Module-2 (CM-2) is a space experiment that launches on Shuttle mission STS 107 in the SPACEHAB Research Double Module. The CM-2 flight hardware is integrated into a SPACEHAB single and double rack. CM-2 rack level combined vibration testing was recently completed on a shaker table to characterize the structure's modal response and verify the random vibration response. Control accelerometers and limit force gauges, located between the fixture and rack interface, were used to verify the input excitation. Results of the testing were used to verify the loads and environments for flight on the Shuttle.

Random dust charge fluctuations in the near-Enceladus plasma

NASA Astrophysics Data System (ADS)

Yaroshenko, V. V.; Lühr, H.

2014-08-01

Stochastic dust charge fluctuations have been studied in the light of Cassini data on the near-Enceladus plasma environment. Estimates of fluctuation time scales showed that this process can be of importance for the grains emanating from the icy moon. The analytical modeling predicts that in the dust-loaded Enceladus plasma a majority of the grains acquires fluctuating negative charges, but there might appear a minority of positively charged particles. The probability of this effect mostly depends on the ratio of the dust/plasma number densities. Our findings appear to be supported by the available Cassini Plasma Spectrometer measurements of the charged grain distributions during E3 and E5 plume flybys. The theoretical results can also provide new insights into the intricate process of particle dynamics in the inner magnetosphere.

Natural selection of memory-one strategies for the iterated prisoner's dilemma.

PubMed

Kraines, D P; Kraines, V Y

2000-04-21

In the iterated Prisoner's Dilemma, mutually cooperative behavior can become established through Darwinian natural selection. In simulated interactions of stochastic memory-one strategies for the Iterated Prisoner's Dilemma, Nowak and Sigmund discovered that cooperative agents using a Pavlov (Win-Stay Lose-Switch) type strategy eventually dominate a random population. This emergence follows more directly from a deterministic dynamical system based on differential reproductive success or natural selection. When restricted to an environment of memory-one agents interacting in iterated Prisoner's Dilemma games with a 1% noise level, the Pavlov agent is the only cooperative strategy and one of very few others that cannot be invaded by a similar strategy. Pavlov agents are trusting but no suckers. They will exploit weakness but repent if punished for cheating. Copyright 2000 Academic Press.

Persistent Factors Facilitating Excellence in Research Environments

ERIC Educational Resources Information Center

Kalpazidou Schmidt, Evanthia; Graversen, Ebbe Krogh

2018-01-01

The study presented here identifies robust and time-invariant features that characterise dynamic and innovative research environments. It takes as its point of departure the results of an empirical study conducted in 2002 which identified the common characteristics of 15 dynamic and innovative public research environments, and focusses on their…

Chaotic itinerancy within the coupled dynamics between a physical body and neural oscillator networks

PubMed Central

Mori, Hiroki; Okuyama, Yuji; Asada, Minoru

2017-01-01

Chaotic itinerancy is a phenomenon in which the state of a nonlinear dynamical system spontaneously explores and attracts certain states in a state space. From this perspective, the diverse behavior of animals and its spontaneous transitions lead to a complex coupled dynamical system, including a physical body and a brain. Herein, a series of simulations using different types of non-linear oscillator networks (i.e., regular, small-world, scale-free, random) with a musculoskeletal model (i.e., a snake-like robot) as a physical body are conducted to understand how the chaotic itinerancy of bodily behavior emerges from the coupled dynamics between the body and the brain. A behavior analysis (behavior clustering) and network analysis for the classified behavior are then applied. The former consists of feature vector extraction from the motions and classification of the movement patterns that emerged from the coupled dynamics. The network structures behind the classified movement patterns are revealed by estimating the “information networks” different from the given non-linear oscillator networks based on the transfer entropy which finds the information flow among neurons. The experimental results show that: (1) the number of movement patterns and their duration depend on the sensor ratio to control the balance of strength between the body and the brain dynamics and on the type of the given non-linear oscillator networks; and (2) two kinds of information networks are found behind two kinds movement patterns with different durations by utilizing the complex network measures, clustering coefficient and the shortest path length with a negative and a positive relationship with the duration periods of movement patterns. The current results seem promising for a future extension of the method to a more complicated body and environment. Several requirements are also discussed. PMID:28796797

Chaotic itinerancy within the coupled dynamics between a physical body and neural oscillator networks.

PubMed

Park, Jihoon; Mori, Hiroki; Okuyama, Yuji; Asada, Minoru

2017-01-01

Chaotic itinerancy is a phenomenon in which the state of a nonlinear dynamical system spontaneously explores and attracts certain states in a state space. From this perspective, the diverse behavior of animals and its spontaneous transitions lead to a complex coupled dynamical system, including a physical body and a brain. Herein, a series of simulations using different types of non-linear oscillator networks (i.e., regular, small-world, scale-free, random) with a musculoskeletal model (i.e., a snake-like robot) as a physical body are conducted to understand how the chaotic itinerancy of bodily behavior emerges from the coupled dynamics between the body and the brain. A behavior analysis (behavior clustering) and network analysis for the classified behavior are then applied. The former consists of feature vector extraction from the motions and classification of the movement patterns that emerged from the coupled dynamics. The network structures behind the classified movement patterns are revealed by estimating the "information networks" different from the given non-linear oscillator networks based on the transfer entropy which finds the information flow among neurons. The experimental results show that: (1) the number of movement patterns and their duration depend on the sensor ratio to control the balance of strength between the body and the brain dynamics and on the type of the given non-linear oscillator networks; and (2) two kinds of information networks are found behind two kinds movement patterns with different durations by utilizing the complex network measures, clustering coefficient and the shortest path length with a negative and a positive relationship with the duration periods of movement patterns. The current results seem promising for a future extension of the method to a more complicated body and environment. Several requirements are also discussed.

Critical Dynamics in Genetic Regulatory Networks: Examples from Four Kingdoms

PubMed Central

Balleza, Enrique; Alvarez-Buylla, Elena R.; Chaos, Alvaro; Kauffman, Stuart; Shmulevich, Ilya; Aldana, Maximino

2008-01-01

The coordinated expression of the different genes in an organism is essential to sustain functionality under the random external perturbations to which the organism might be subjected. To cope with such external variability, the global dynamics of the genetic network must possess two central properties. (a) It must be robust enough as to guarantee stability under a broad range of external conditions, and (b) it must be flexible enough to recognize and integrate specific external signals that may help the organism to change and adapt to different environments. This compromise between robustness and adaptability has been observed in dynamical systems operating at the brink of a phase transition between order and chaos. Such systems are termed critical. Thus, criticality, a precise, measurable, and well characterized property of dynamical systems, makes it possible for robustness and adaptability to coexist in living organisms. In this work we investigate the dynamical properties of the gene transcription networks reported for S. cerevisiae, E. coli, and B. subtilis, as well as the network of segment polarity genes of D. melanogaster, and the network of flower development of A. thaliana. We use hundreds of microarray experiments to infer the nature of the regulatory interactions among genes, and implement these data into the Boolean models of the genetic networks. Our results show that, to the best of the current experimental data available, the five networks under study indeed operate close to criticality. The generality of this result suggests that criticality at the genetic level might constitute a fundamental evolutionary mechanism that generates the great diversity of dynamically robust living forms that we observe around us. PMID:18560561

Spatially explicit feedbacks between seagrass meadow structure, sediment and light: Habitat suitability for seagrass growth

USGS Publications Warehouse

Carr, Joel; D'Odorico, Paul; McGlathery, Karen; Wiberg, Patricia L.

2016-01-01

In shallow coastal bays where nutrient loading and riverine inputs are low, turbidity, and the consequent light environment are controlled by resuspension of bed sediments due to wind-waves and tidal currents. High sediment resuspension and low light environments can limit benthic primary productivity; however, both currents and waves are affected by the presence of benthic plants such as seagrass. This feedback between the presence of benthic primary producers such as seagrass and the consequent light environment has been predicted to induce bistable dynamics locally. However, these vegetated areas influence a larger area than they footprint, including a barren adjacent downstream area which exhibits reduced shear stresses. Here we explore through modeling how the patchy structure of seagrass meadows on a landscape may affect sediment resuspension and the consequent light environment due to the presence of this sheltered region. Heterogeneous vegetation covers comprising a mosaic of randomly distributed patches were generated to investigate the effect of patch modified hydrodynamics. Actual cover of vegetation on the landscape was used to facilitate comparisons across landscape realizations. Hourly wave and current shear stresses on the landscape along with suspended sediment concentration and light attenuation characteristics were then calculated and spatially averaged to examine how actual cover and mean water depth affect the bulk sediment and light environment. The results indicate that an effective cover, which incorporates the sheltering area, has important controls on the distributions of shear stress, suspended sediment, light environment, and consequent seagrass habitat suitability. Interestingly, an optimal habitat occurs within a depth range where, if actual cover is reduced past some threshold, the bulk light environment would no longer favor seagrass growth.

Land change variability and human-environment dynamics in the United States Great Plains

USGS Publications Warehouse

Drummond, M.A.; Auch, Roger F.; Karstensen, K.A.; Sayler, K. L.; Taylor, Janis L.; Loveland, Thomas R.

2012-01-01

Land use and land cover changes have complex linkages to climate variability and change, biophysical resources, and socioeconomic driving forces. To assess these land change dynamics and their causes in the Great Plains, we compare and contrast contemporary changes across 16 ecoregions using Landsat satellite data and statistical analysis. Large-area change analysis of agricultural regions is often hampered by change detection error and the tendency for land conversions to occur at the local-scale. To facilitate a regional-scale analysis, a statistical sampling design of randomly selected 10 km × 10 km blocks is used to efficiently identify the types and rates of land conversions for four time intervals between 1973 and 2000, stratified by relatively homogenous ecoregions. Nearly 8% of the overall Great Plains region underwent land-use and land-cover change during the study period, with a substantial amount of ecoregion variability that ranged from less than 2% to greater than 13%. Agricultural land cover declined by more than 2% overall, with variability contingent on the differential characteristics of regional human–environment systems. A large part of the Great Plains is in relatively stable land cover. However, other land systems with significant biophysical and climate limitations for agriculture have high rates of land change when pushed by economic, policy, technology, or climate forcing factors. The results indicate the regionally based potential for land cover to persist or fluctuate as land uses are adapted to spatially and temporally variable forcing factors.

Temporal variations in a phytoplankton community in a subtropical reservoir: An interplay of extrinsic and intrinsic community effects.

PubMed

Yang, Wen; Zheng, Zhongming; Zheng, Cheng; Lu, Kaihong; Ding, Dewen; Zhu, Jinyong

2018-01-15

The phytoplankton community structure is potentially influenced by both extrinsic effects originating from the surrounding environment and intrinsic effects relying on interspecific interactions between two species. However, few studies have simultaneously considered both types of effects and assessed the relative importance of these factors. In this study, we used data collected over nine months (August 2012-May 2013) from a typical subtropical reservoir in southeast China to analyze the temporal variation of its phytoplankton community structure and develop a quantitative understanding of the extrinsic and intrinsic effects on phytoplankton community dynamics. Significant temporal variations were observed in environmental variables as well as the phytoplankton and zooplankton communities, whereas their variational trajectories and directions were entirely different. Variance partitioning analysis showed that extrinsic factors significantly explained only 31% of the variation in the phytoplankton community, thus suggesting that these factors were incomplete predictors of the community structure. Random forest-based models showed that 48% of qualified responsible phytoplankton species were more accurately predicted by phytoplankton-only models, which revealed clear effects of interspecific species-to-species interactions. Furthermore, we used association networks to model the interactions among phytoplankton, zooplankton and the environment. Network comparisons indicated that interspecific interactions were widely present in the phytoplankton community and dominated the network rather than those between phytoplankton and extrinsic factors. These findings expand the current understanding of the underlying mechanisms that govern phytoplankton community dynamics. Copyright © 2017 Elsevier B.V. All rights reserved.

Influence of the membrane lipophilic environment on the structure and on the substrate access/egress routes of the human aromatase enzyme. A computational study.

PubMed

Sgrignani, Jacopo; Magistrato, Alessandra

2012-06-25

Human aromatase (HA), an enzyme located on the membrane of the endoplasmatic reticulum, is of crucial biological importance in the biosynthesis of estrogens. High levels of estrogens are related with important pathologies, conferring to HA a key role as a pharmacological target. In this study we provide, for the first time, an atomistic model of HA embedded on a membrane model to understand the influence of the membrane lipophilic environment on the structural and dynamical properties of HA and on the access/egress pathways of the substrate (androstenedione, ASD) and of the oxygen molecule (involved in the enzymatic process) into/from the HA active site. To this end we used several computational techniques such as force field-based molecular dynamics (MD) simulations, Random Expulsion MD, Steered MD, and Implicit Ligand Sampling. Our results show that the membrane anchoring does not markedly affect the structural properties and the flexibility of the protein, but they clearly point out that the membrane has a marked effect on the access/egress routes of the reactants, stabilizing the formation of different channels for both ASD and O(2) with respect to those observed in pure water solution. Due to the importance of HA in medicine and since access/egress channels may influence its substrate selectivity, a detailed understanding of the role of the membrane in shaping these channels may be of valuable help in drug design.

Atmospheric Electrical Modeling in Support of the NASA F-106 Storm Hazards Project

NASA Technical Reports Server (NTRS)

Helsdon, John H., Jr.

1988-01-01

A recently developed storm electrification model (SEM) is used to investigate the operating environment of the F-106 airplane during the NASA Storm Hazards Project. The model is 2-D, time dependent and uses a bulkwater microphysical parameterization scheme. Electric charges and fields are included, and the model is fully coupled dynamically, microphysically and electrically. One flight showed that a high electric field was developed at the aircraft's operating altitude (28 kft) and that a strong electric field would also be found below 20 kft; however, this low-altitude, high-field region was associated with the presence of small hail, posing a hazard to the aircraft. An operational procedure to increase the frequency of low-altitude lightning strikes was suggested. To further the understanding of lightning within the cloud environment, a parameterization of the lightning process was included in the SEM. It accounted for the initiation, propagation, termination, and charge redistribution associated with an intracloud discharge. Finally, a randomized lightning propagation scheme was developed, and the effects of cloud particles on the initiation of lightning investigated.

Load Balancing in Cloud Computing Environment Using Improved Weighted Round Robin Algorithm for Nonpreemptive Dependent Tasks.

PubMed

Devi, D Chitra; Uthariaraj, V Rhymend

2016-01-01

Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM's multiple cores. Also, the jobs arrive during the run time of the server in varying random intervals under various load conditions. The participating heterogeneous resources are managed by allocating the tasks to appropriate resources by static or dynamic scheduling to make the cloud computing more efficient and thus it improves the user satisfaction. Objective of this work is to introduce and evaluate the proposed scheduling and load balancing algorithm by considering the capabilities of each virtual machine (VM), the task length of each requested job, and the interdependency of multiple tasks. Performance of the proposed algorithm is studied by comparing with the existing methods.

Load Balancing in Cloud Computing Environment Using Improved Weighted Round Robin Algorithm for Nonpreemptive Dependent Tasks

PubMed Central

Devi, D. Chitra; Uthariaraj, V. Rhymend

2016-01-01

Cloud computing uses the concepts of scheduling and load balancing to migrate tasks to underutilized VMs for effectively sharing the resources. The scheduling of the nonpreemptive tasks in the cloud computing environment is an irrecoverable restraint and hence it has to be assigned to the most appropriate VMs at the initial placement itself. Practically, the arrived jobs consist of multiple interdependent tasks and they may execute the independent tasks in multiple VMs or in the same VM's multiple cores. Also, the jobs arrive during the run time of the server in varying random intervals under various load conditions. The participating heterogeneous resources are managed by allocating the tasks to appropriate resources by static or dynamic scheduling to make the cloud computing more efficient and thus it improves the user satisfaction. Objective of this work is to introduce and evaluate the proposed scheduling and load balancing algorithm by considering the capabilities of each virtual machine (VM), the task length of each requested job, and the interdependency of multiple tasks. Performance of the proposed algorithm is studied by comparing with the existing methods. PMID:26955656

Characterization of Pump-Induced Acoustics in Space Launch System Main Propulsion System Liquid Hydrogen Feedline Using Airflow Test Data

NASA Technical Reports Server (NTRS)

Eberhart, C. J.; Snellgrove, L. M.; Zoladz, T. F.

2015-01-01

High intensity acoustic edgetones located upstream of the RS-25 Low Pressure Fuel Turbo Pump (LPFTP) were previously observed during Space Launch System (STS) airflow testing of a model Main Propulsion System (MPS) liquid hydrogen (LH2) feedline mated to a modified LPFTP. MPS hardware has been adapted to mitigate the problematic edgetones as part of the Space Launch System (SLS) program. A follow-on airflow test campaign has subjected the adapted hardware to tests mimicking STS-era airflow conditions, and this manuscript describes acoustic environment identification and characterization born from the latest test results. Fluid dynamics responsible for driving discrete excitations were well reproduced using legacy hardware. The modified design was found insensitive to high intensity edgetone-like discretes over the bandwidth of interest to SLS MPS unsteady environments. Rather, the natural acoustics of the test article were observed to respond in a narrowband-random/mixed discrete manner to broadband noise thought generated by the flow field. The intensity of these responses were several orders of magnitude reduced from those driven by edgetones.

Standards for Radiation Effects Testing: Ensuring Scientific Rigor in the Face of Budget Realities and Modern Device Challenges

NASA Technical Reports Server (NTRS)

Lauenstein, J M.

2015-01-01

An overview is presented of the space radiation environment and its effects on electrical, electronic, and electromechanical parts. Relevant test standards and guidelines are listed. Test standards and guidelines are necessary to ensure best practices, minimize and bound systematic and random errors, and to ensure comparable results from different testers and vendors. Test standards are by their nature static but exist in a dynamic environment of advancing technology and radiation effects research. New technologies, failure mechanisms, and advancement in our understanding of known failure mechanisms drive the revision or development of test standards. Changes to standards must be weighed against their impact on cost and existing part qualifications. There must be consensus on new best practices. The complexity of some new technologies exceeds the scope of existing test standards and may require development of a guideline specific to the technology. Examples are given to illuminate the value and limitations of key radiation test standards as well as the challenges in keeping these standards up to date.

Grain-resolving simulations of settling cohesive sediment

NASA Astrophysics Data System (ADS)

Vowinckel, Bernhard; Whithers, Jade; Meiburg, Eckart; Luzzatto-Fegiz, Paolo

2017-11-01

Cohesive sediment is ubiquitous in natural environments such as rivers, lakes and coastal ecosystems. For this type of sediment, we can no longer ignore the short-range attractive forces that result in flocculation of aggregates much larger than the individual grain size. Hence, understanding the complex dynamics of the interplay between flocculated sediment and the ambient fluid is of prime interest for managing aquatic environments, although a comprehensive understanding of these phenomena is still lacking. In the present study, we address this issue by carrying out grain-resolved simulations of cohesive particles settling under gravity using the Immersed Boundary Method. We present a computational model formulation to accurately resolve the process of flocculation. The cohesive model is then applied to a complex test case. A randomly distributed ensemble of 1261 polydisperse particles is released in a tank of quiescent fluid. Subsequently, particles start to settle, thereby replacing fluid at the bottom of the tank, which induces a counter flow opposing the settling direction. This mechanism will be compared to experimental studies from the literature, as well as to the non-cohesive counterpart to assessthe impact of flocculation on sedimentation.

Integrating association data and disease dynamics: an illustration using African Buffalo in Kruger National Park

USGS Publications Warehouse

Cross, Paul C.; James O, Lloyd-Smith; Bowers, Justin A.; Hay, Craig T.; Hofmeyr, Markus; Getz, Wayne M.

2004-01-01

Recognition is a prerequisite for non-random association amongst individuals. We explore how non-random association patterns (i.e. who spends time with whom) affect disease dynamics. We estimated the amount of time individuals spent together per month using radio-tracking data from African buffalo and incorporated these data into a dynamic social network model. The dynamic nature of the network has a strong influence on simulated disease dynamics particularly for diseases with shorter infectious periods. Cluster analyses of the association data demonstrated that buffalo herds were not as well defined as previously thought. Associations were more tightly clustered in 2002 than 2003, perhaps due to drier conditions in 2003. As a result, diseases may spread faster during drought conditions due to increased population mixing. Association data are often collected but this is the first use of empirical data in a network disease model in a wildlife population.

Proceedings: Shrubland ecosystem dynamics in a changing environment

Treesearch

Jerry R. Barrow; E. Durant McArthur; Ronald E. Sosebee; Robin J. Tausch

1996-01-01

This proceedings contains 50 papers including an overview of shrubland ecosystem dynamics in a changing environment and several papers each on vegetation dynamics, management concerns and options, and plant ecophysiology as well as an account of a Jornada Basin field trip. Contributions emphasize the impact of changing environmental conditions on vegetative composition...

Dragging in a Dynamic Geometry Environment through the Lens of Variation

ERIC Educational Resources Information Center

Leung, Allen

2008-01-01

What makes Dynamic Geometry Environment (DGE) a powerful mathematical knowledge acquisition microworld is its ability to visually make explicit the implicit dynamism of thinking about mathematical geometrical concepts. One of DGE's powers is to equip us with the ability to retain the background of a geometrical configuration while we can…

Young Children Reasoning about Symmetry in a Dynamic Geometry Environment

ERIC Educational Resources Information Center

Ng, Oi-Lam; Sinclair, Nathalie

2015-01-01

In this paper, we investigate children's learning of reflectional symmetry in a dynamic geometry environment. Through a classroom-based intervention involving two 1-h lessons, we analyse the changes in the children's thinking about reflectional symmetry: first, they developed dynamic and embodied ways of thinking about symmetry after working with…

Dynamic geometry as a context for exploring conjectures

NASA Astrophysics Data System (ADS)

Wares, Arsalan

2018-01-01

The purpose of this paper is to provide examples of 'non-traditional' proof-related activities that can explored in a dynamic geometry environment by university and high school students of mathematics. These propositions were encountered in the dynamic geometry environment. The author believes that teachers can ask their students to construct proofs for these propositions.

Self-Organizing Distributed Architecture Supporting Dynamic Space Expanding and Reducing in Indoor LBS Environment

PubMed Central

Jeong, Seol Young; Jo, Hyeong Gon; Kang, Soon Ju

2015-01-01

Indoor location-based services (iLBS) are extremely dynamic and changeable, and include numerous resources and mobile devices. In particular, the network infrastructure requires support for high scalability in the indoor environment, and various resource lookups are requested concurrently and frequently from several locations based on the dynamic network environment. A traditional map-based centralized approach for iLBSs has several disadvantages: it requires global knowledge to maintain a complete geographic indoor map; the central server is a single point of failure; it can also cause low scalability and traffic congestion; and it is hard to adapt to a change of service area in real time. This paper proposes a self-organizing and fully distributed platform for iLBSs. The proposed self-organizing distributed platform provides a dynamic reconfiguration of locality accuracy and service coverage by expanding and contracting dynamically. In order to verify the suggested platform, scalability performance according to the number of inserted or deleted nodes composing the dynamic infrastructure was evaluated through a simulation similar to the real environment. PMID:26016908

Outcome Evaluation of "Family Eats": An Eight-Session Web-Based Program Promoting Healthy Home Food Environments and Dietary Behaviors for African American Families

ERIC Educational Resources Information Center

Cullen, Karen Weber; Thompson, Debbe; Chen, Tzu-An

2017-01-01

This article presents the results of a randomized clinical trial evaluating the eight-session "Family Eats" web-based intervention promoting healthy home food environments for African American families. African American families (n = 126) with 8- to 12-year-old children completed online baseline questionnaires and were randomized into…

[Situational awareness: you won't see it unless you understand it].

PubMed

Graafland, Maurits; Schijven, Marlies P

2015-01-01

In dynamic, high-risk environments such as the modern operating theatre, healthcare providers are required to identify a multitude of signals correctly and in time. Errors resulting from failure to identify or interpret signals correctly lead to calamities. Medical training curricula focus largely on teaching technical skills and knowledge, not on the cognitive skills needed to interact appropriately with fast-changing, complex environments in practice. The term 'situational awareness' describes the dynamic process of receiving, interpreting and processing information in such dynamic environments. Improving situational awareness in high-risk environments should be part of medical curricula. In addition, the flood of information in high-risk environments should be presented more clearly and effectively. It is important that physicians become more involved in this regard.

Neurofeedback Tunes Scale-Free Dynamics in Spontaneous Brain Activity.

PubMed

Ros, T; Frewen, P; Théberge, J; Michela, A; Kluetsch, R; Mueller, A; Candrian, G; Jetly, R; Vuilleumier, P; Lanius, R A

2017-10-01

Brain oscillations exhibit long-range temporal correlations (LRTCs), which reflect the regularity of their fluctuations: low values representing more random (decorrelated) while high values more persistent (correlated) dynamics. LRTCs constitute supporting evidence that the brain operates near criticality, a state where neuronal activities are balanced between order and randomness. Here, healthy adults used closed-loop brain training (neurofeedback, NFB) to reduce the amplitude of alpha oscillations, producing a significant increase in spontaneous LRTCs post-training. This effect was reproduced in patients with post-traumatic stress disorder, where abnormally random dynamics were reversed by NFB, correlating with significant improvements in hyperarousal. Notably, regions manifesting abnormally low LRTCs (i.e., excessive randomness) normalized toward healthy population levels, consistent with theoretical predictions about self-organized criticality. Hence, when exposed to appropriate training, spontaneous cortical activity reveals a residual capacity for "self-tuning" its own temporal complexity, despite manifesting the abnormal dynamics seen in individuals with psychiatric disorder. Lastly, we observed an inverse-U relationship between strength of LRTC and oscillation amplitude, suggesting a breakdown of long-range dependence at high/low synchronization extremes, in line with recent computational models. Together, our findings offer a broader mechanistic framework for motivating research and clinical applications of NFB, encompassing disorders with perturbed LRTCs. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A Perspective on Research on Dishonesty: Limited External Validity Due to the Lack of Possibility of Self-Selection in Experimental Designs.

PubMed

Houdek, Petr

2017-01-01

The aim of this perspective article is to show that current experimental evidence on factors influencing dishonesty has limited external validity. Most of experimental studies is built on random assignments, in which control/experimental groups of subjects face varied sizes of the expected reward for behaving dishonestly, opportunities for cheating, means of rationalizing dishonest behavior etc., and mean groups' reactions are observed. The studies have internal validity in assessing the causal influence of these and other factors, but they lack external validity in organizational, market and other environments. If people can opt into or out of diverse real-world environments, an experiment aimed at studying factors influencing real-life degree of dishonesty should permit for such an option. The behavior of such self-selected groups of marginal subjects would probably contain a larger level of (non)deception than the behavior of average people. The article warns that there are not many studies that would enable self-selection or sorting of participants into varying environments, and that limits current knowledge of the extent and dynamics of dishonest and fraudulent behavior. The article focuses on suggestions how to improve dishonesty research, especially how to avoid the experimenter demand bias.

Repeatable group differences in the collective behaviour of stickleback shoals across ecological contexts

PubMed Central

2018-01-01

Establishing how collective behaviour emerges is central to our understanding of animal societies. Previous research has highlighted how universal interaction rules shape collective behaviour, and that individual differences can drive group functioning. Groups themselves may also differ considerably in their collective behaviour, but little is known about the consistency of such group variation, especially across different ecological contexts that may alter individuals' behavioural responses. Here, we test if randomly composed groups of sticklebacks differ consistently from one another in both their structure and movement dynamics across an open environment, an environment with food, and an environment with food and shelter. Based on high-resolution tracking data of the free-swimming shoals, we found large context-associated changes in the average behaviour of the groups. But despite these changes and limited social familiarity among group members, substantial and predictable behavioural differences between the groups persisted both within and across the different contexts (group-level repeatability): some groups moved consistently faster, more cohesively, showed stronger alignment and/or clearer leadership than other groups. These results suggest that among-group heterogeneity could be a widespread feature in animal societies. Future work that considers group-level variation in collective behaviour may help understand the selective pressures that shape how animal collectives form and function. PMID:29436496

A Perspective on Research on Dishonesty: Limited External Validity Due to the Lack of Possibility of Self-Selection in Experimental Designs

PubMed Central

Houdek, Petr

2017-01-01

The aim of this perspective article is to show that current experimental evidence on factors influencing dishonesty has limited external validity. Most of experimental studies is built on random assignments, in which control/experimental groups of subjects face varied sizes of the expected reward for behaving dishonestly, opportunities for cheating, means of rationalizing dishonest behavior etc., and mean groups’ reactions are observed. The studies have internal validity in assessing the causal influence of these and other factors, but they lack external validity in organizational, market and other environments. If people can opt into or out of diverse real-world environments, an experiment aimed at studying factors influencing real-life degree of dishonesty should permit for such an option. The behavior of such self-selected groups of marginal subjects would probably contain a larger level of (non)deception than the behavior of average people. The article warns that there are not many studies that would enable self-selection or sorting of participants into varying environments, and that limits current knowledge of the extent and dynamics of dishonest and fraudulent behavior. The article focuses on suggestions how to improve dishonesty research, especially how to avoid the experimenter demand bias. PMID:28955279

Soil Characterization and Site Response of Marine and Continental Environments

NASA Astrophysics Data System (ADS)

Contreras-Porras, R. S.; Huerta-Lopez, C. I.; Martinez-Cruzado, J. A.; Gaherty, J. B.; Collins, J. A.

2009-05-01

An in situ soil properties study was conducted to characterize both site and shallow layer sediments under marine and continental environments. Data from the SCoOBA (Sea of Cortez Ocean Bottom Array) seismic experiment and in land ambient vibration measurements on the urban areas of Tijuana, B. C., and Ensenada, B. C., Mexico were used in the analysis. The goal of this investigation is to identify and to analyze the effect of the physical/geotechnical properties of the ground on the site response upon seismic excitations in both marine and continental environments. The time series were earthquakes and background noise recorded within interval of 10/2005 to 10/2006 in the Gulf of California (GoC) with very-broadband Ocean Bottom Seismographs (OBS), and ambient vibration measurements collected during different time periods on Tijuana and Ensenada urban areas. The data processing and analysis was conducted by means of the H/V Spectral Ratios (HVSPR) of multi component data, the Random Decrement Method (RDM), and Blind Deconvolution (BD). This study presents ongoing results of a long term project to characterize the local site response of soil layers upon dynamic excitations using digital signal processing algorithms on time series, as well as the comparison between the results these methodologies are providing.

Hydrological drivers of wetland vegetational biodiversity patterns within Everglades National Park, Florida

NASA Astrophysics Data System (ADS)

Todd, J.; Pumo, D.; Azaele, S.; Muneepeerakul, R.; Miralles-Wilhelm, F. R.; Rinaldo, A.; Rodriguez-Iturbe, I.

2009-12-01

The influence of hydrological dynamics on vegetational biodiversity and structuring of wetland environments is of growing interest as wetlands are modified by human alteration and the increasing threat from climate change. Hydrology has long been considered a driving force in shaping wetland communities as the frequency of inundation along with the duration and depth of flooding are key determinants of wetland structure. We attempt to link hydrological dynamics with vegetational distribution and species richness across Everglades National Park (ENP) using two publicly available datasets. The first, the Everglades Depth Estimation Network (EDEN),is a water-surface model which determines the median daily measure of water level across a 400mX400m grid over seven years of measurement. The second is a vegetation map and classification system at the 1:15,000 scale which categorizes vegetation within the Everglades into 79 community types. From these data, we have studied the probabilistic structure of the frequency, duration, and depth of hydroperiods. Preliminary results indicate that the percentage of time a location is inundated is a principal structuring variable with individual communities responding differently. For example, sawgrass appears to be more of a generalist community as it is found across a wide range of time inundated percentages while spike rush has a more restricted distribution and favors wetter environments disproportionately more than predicted at random. Further, the diversity of vegetation communities (e.g. a measure of biodiversity) found across a hydrologic variable does not necessarily match the distribution function for that variable on the landscape. For instance, the number of communities does not differ across the percentage of time inundated. Different measures of vegetation biodiversity such as the local number of community types are also studied at different spatial scales with some characteristics, like the slope of the semi-logarithmic relation between rank and occupancy, found to be robust to scale changes. The ENP offers an expansive natural environment in which to study how vegetational dynamics and community composition are affected by hydrologic variables from the small scale (at the individual community level) to the large (biodiversity measures at differing spatial scales).

Epidemic transmission on random mobile network with diverse infection periods

NASA Astrophysics Data System (ADS)

Li, Kezan; Yu, Hong; Zeng, Zhaorong; Ding, Yong; Ma, Zhongjun

2015-05-01

The heterogeneity of individual susceptibility and infectivity and time-varying topological structure are two realistic factors when we study epidemics on complex networks. Current research results have shown that the heterogeneity of individual susceptibility and infectivity can increase the epidemic threshold in a random mobile dynamical network with the same infection period. In this paper, we will focus on random mobile dynamical networks with diverse infection periods due to people's different constitutions and external circumstances. Theoretical results indicate that the epidemic threshold of the random mobile network with diverse infection periods is larger than the counterpart with the same infection period. Moreover, the heterogeneity of individual susceptibility and infectivity can play a significant impact on disease transmission. In particular, the homogeneity of individuals will avail to the spreading of epidemics. Numerical examples verify further our theoretical results very well.

Standard model group: Survival of the fittest

NASA Astrophysics Data System (ADS)

Nielsen, H. B.; Brene, N.

1983-09-01

The essential content of this paper is related to random dynamics. We speculate that the world seen through a sub-Planck-scale microscope has a lattice structure and that the dynamics on this lattice is almost completely random, except for the requirement that the random (plaquette) action is invariant under some "world (gauge) group". We see that the randomness may lead to spontaneous symmetry breakdown in the vacuum (spontaneous collapse) without explicit appeal to any scalar field associated with the usual Higgs mechanism. We further argue that the subgroup which survives as the end product of a possible chain of collapses is likely to have certain properties; the most important is that it has a topologically connected center. The standard group, i.e. the group of the gauge theory which combines the Salam-Weinberg model with QCD, has this property.

Stochastic Models of Emerging Infectious Disease Transmission on Adaptive Random Networks

PubMed Central

Pipatsart, Navavat; Triampo, Wannapong

2017-01-01

We presented adaptive random network models to describe human behavioral change during epidemics and performed stochastic simulations of SIR (susceptible-infectious-recovered) epidemic models on adaptive random networks. The interplay between infectious disease dynamics and network adaptation dynamics was investigated in regard to the disease transmission and the cumulative number of infection cases. We found that the cumulative case was reduced and associated with an increasing network adaptation probability but was increased with an increasing disease transmission probability. It was found that the topological changes of the adaptive random networks were able to reduce the cumulative number of infections and also to delay the epidemic peak. Our results also suggest the existence of a critical value for the ratio of disease transmission and adaptation probabilities below which the epidemic cannot occur. PMID:29075314

Random Telegraph Signal-Like Fluctuation Created by Fowler-Nordheim Stress in Gate Induced Drain Leakage Current of the Saddle Type Dynamic Random Access Memory Cell Transistor

NASA Astrophysics Data System (ADS)

Kim, Heesang; Oh, Byoungchan; Kim, Kyungdo; Cha, Seon-Yong; Jeong, Jae-Goan; Hong, Sung-Joo; Lee, Jong-Ho; Park, Byung-Gook; Shin, Hyungcheol

2010-09-01

We generated traps inside gate oxide in gate-drain overlap region of recess channel type dynamic random access memory (DRAM) cell transistor through Fowler-Nordheim (FN) stress, and observed gate induced drain leakage (GIDL) current both in time domain and in frequency domain. It was found that the trap inside gate oxide could generate random telegraph signal (RTS)-like fluctuation in GIDL current. The characteristics of that fluctuation were similar to those of RTS-like fluctuation in GIDL current observed in the non-stressed device. This result shows the possibility that the trap causing variable retention time (VRT) in DRAM data retention time can be located inside gate oxide like channel RTS of metal-oxide-semiconductor field-effect transistors (MOSFETs).

Visualization of early events in acetic acid denaturation of HIV-1 protease: a molecular dynamics study.

PubMed

Borkar, Aditi Narendra; Rout, Manoj Kumar; Hosur, Ramakrishna V

2011-01-01

Protein denaturation plays a crucial role in cellular processes. In this study, denaturation of HIV-1 Protease (PR) was investigated by all-atom MD simulations in explicit solvent. The PR dimer and monomer were simulated separately in 9 M acetic acid (9 M AcOH) solution and water to study the denaturation process of PR in acetic acid environment. Direct visualization of the denaturation dynamics that is readily available from such simulations has been presented. Our simulations in 9 M AcOH reveal that the PR denaturation begins by separation of dimer into intact monomers and it is only after this separation that the monomer units start denaturing. The denaturation of the monomers is flagged off by the loss of crucial interactions between the α-helix at C-terminal and surrounding β-strands. This causes the structure to transit from the equilibrium dynamics to random non-equilibrating dynamics. Residence time calculations indicate that denaturation occurs via direct interaction of the acetic acid molecules with certain regions of the protein in 9 M AcOH. All these observations have helped to decipher a picture of the early events in acetic acid denaturation of PR and have illustrated that the α-helix and the β-sheet at the C-terminus of a native and functional PR dimer should maintain both the stability and the function of the enzyme and thus present newer targets for blocking PR function.

Vision-based navigation in a dynamic environment for virtual human

NASA Astrophysics Data System (ADS)

Liu, Yan; Sun, Ji-Zhou; Zhang, Jia-Wan; Li, Ming-Chu

2004-06-01

Intelligent virtual human is widely required in computer games, ergonomics software, virtual environment and so on. We present a vision-based behavior modeling method to realize smart navigation in a dynamic environment. This behavior model can be divided into three modules: vision, global planning and local planning. Vision is the only channel for smart virtual actor to get information from the outside world. Then, the global and local planning module use A* and D* algorithm to find a way for virtual human in a dynamic environment. Finally, the experiments on our test platform (Smart Human System) verify the feasibility of this behavior model.

Charging power optimization for nonlinear vibration energy harvesting systems subjected to arbitrary, persistent base excitations

NASA Astrophysics Data System (ADS)

Dai, Quanqi; Harne, Ryan L.

2018-01-01

The vibrations of mechanical systems and structures are often a combination of periodic and random motions. Emerging interest to exploit nonlinearities in vibration energy harvesting systems for charging microelectronics may be challenged by such reality due to the potential to transition between favorable and unfavorable dynamic regimes for DC power delivery. Therefore, a need exists to devise an optimization method whereby charging power from nonlinear energy harvesters remains maximized when excitation conditions are neither purely harmonic nor purely random, which have been the attention of past research. This study meets the need by building from an analytical approach that characterizes the dynamic response of nonlinear energy harvesting platforms subjected to combined harmonic and stochastic base accelerations. Here, analytical expressions are formulated and validated to optimize charging power while the influences of the relative proportions of excitation types are concurrently assessed. It is found that about a 2 times deviation in optimal resistive loads can reduce the charging power by 20% when the system is more prominently driven by harmonic base accelerations, whereas a greater proportion of stochastic excitation results in a 11% reduction in power for the same resistance deviation. In addition, the results reveal that when the frequency of a predominantly harmonic excitation deviates by 50% from optimal conditions the charging power reduces by 70%, whereas the same frequency deviation for a more stochastically dominated excitation reduce total DC power by only 20%. These results underscore the need for maximizing direct current power delivery for nonlinear energy harvesting systems in practical operating environments.

Modelling Mathematics Teachers' Intention to Use the Dynamic Geometry Environments in Macau: An SEM Approach

ERIC Educational Resources Information Center

Zhou, Mingming; Chan, Kan Kan; Teo, Timothy

2016-01-01

Dynamic geometry environments (DGEs) provide computer-based environments to construct and manipulate geometric figures with great ease. Research has shown that DGEs has positive impact on student motivation, engagement, and achievement in mathematics learning. However, the adoption of DGEs by mathematics teachers varies substantially worldwide.…

Accommodating the Instrumental Genesis Framework within Dynamic Technology Environments

ERIC Educational Resources Information Center

Hegedus, Stephen J.; Moreno-Armella, Luis

2010-01-01

In certain digital environments, "hot-spots" are key infrastructural pieces that allow the dynamic construction and re-construction of mathematical figures. We shall discuss their existence with respect to what we call user-environment co-actions, describing how they are sustainable bi-directional processes that have the potential to ground and…

Dynamic and Interactive Mathematics Learning Environments: The Case of Teaching the Limit Concept

ERIC Educational Resources Information Center

Martinovic, Dragana; Karadag, Zekeriya

2012-01-01

This theoretical study is an attempt to explore the potential of the dynamic and interactive mathematics learning environments (DIMLE) in relation to the technological pedagogical content knowledge (TPACK) framework. DIMLE are developed with intent to support learning mathematics through free exploration in a less constrained environment. A…

Random attractor of non-autonomous stochastic Boussinesq lattice system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhao, Min, E-mail: zhaomin1223@126.com; Zhou, Shengfan, E-mail: zhoushengfan@yahoo.com

2015-09-15

In this paper, we first consider the existence of tempered random attractor for second-order non-autonomous stochastic lattice dynamical system of nonlinear Boussinesq equations effected by time-dependent coupled coefficients and deterministic forces and multiplicative white noise. Then, we establish the upper semicontinuity of random attractors as the intensity of noise approaches zero.

Dynamic probability of reinforcement for cooperation: Random game termination in the centipede game.

PubMed

Krockow, Eva M; Colman, Andrew M; Pulford, Briony D

2018-03-01

Experimental games have previously been used to study principles of human interaction. Many such games are characterized by iterated or repeated designs that model dynamic relationships, including reciprocal cooperation. To enable the study of infinite game repetitions and to avoid endgame effects of lower cooperation toward the final game round, investigators have introduced random termination rules. This study extends previous research that has focused narrowly on repeated Prisoner's Dilemma games by conducting a controlled experiment of two-player, random termination Centipede games involving probabilistic reinforcement and characterized by the longest decision sequences reported in the empirical literature to date (24 decision nodes). Specifically, we assessed mean exit points and cooperation rates, and compared the effects of four different termination rules: no random game termination, random game termination with constant termination probability, random game termination with increasing termination probability, and random game termination with decreasing termination probability. We found that although mean exit points were lower for games with shorter expected game lengths, the subjects' cooperativeness was significantly reduced only in the most extreme condition with decreasing computer termination probability and an expected game length of two decision nodes. © 2018 Society for the Experimental Analysis of Behavior.

A Dynamic Bayesian Network Model for the Production and Inventory Control

NASA Astrophysics Data System (ADS)

Shin, Ji-Sun; Takazaki, Noriyuki; Lee, Tae-Hong; Kim, Jin-Il; Lee, Hee-Hyol

In general, the production quantities and delivered goods are changed randomly and then the total stock is also changed randomly. This paper deals with the production and inventory control using the Dynamic Bayesian Network. Bayesian Network is a probabilistic model which represents the qualitative dependence between two or more random variables by the graph structure, and indicates the quantitative relations between individual variables by the conditional probability. The probabilistic distribution of the total stock is calculated through the propagation of the probability on the network. Moreover, an adjusting rule of the production quantities to maintain the probability of a lower limit and a ceiling of the total stock to certain values is shown.

Dynamical Localization for Discrete and Continuous Random Schrödinger Operators

NASA Astrophysics Data System (ADS)

Germinet, F.; De Bièvre, S.

We show for a large class of random Schrödinger operators Ho on and on that dynamical localization holds, i.e. that, with probability one, for a suitable energy interval I and for q a positive real, Here ψ is a function of sufficiently rapid decrease, and PI(Ho) is the spectral projector of Ho corresponding to the interval I. The result is obtained through the control of the decay of the eigenfunctions of Ho and covers, in the discrete case, the Anderson tight-binding model with Bernoulli potential (dimension ν = 1) or singular potential (ν > 1), and in the continuous case Anderson as well as random Landau Hamiltonians.

Continuous quantum measurement in spin environments

NASA Astrophysics Data System (ADS)

Xie, Dong; Wang, An Min

2015-08-01

We derive a stochastic master equation (SME) which describes the decoherence dynamics of a system in spin environments conditioned on the measurement record. Markovian and non-Markovian nature of environment can be revealed by a spectroscopy method based on weak continuous quantum measurement. On account of that correlated environments can lead to a non-local open system which exhibits strong non-Markovian effects although the local dynamics are Markovian, the spectroscopy method can be used to demonstrate that there is correlation between two environments.

Central limit theorem for recurrent random walks on a strip with bounded potential

NASA Astrophysics Data System (ADS)

Dolgopyat, D.; Goldsheid, I.

2018-07-01

We prove that the recurrent random walk (RW) in random environment (RE) on a strip in bounded potential satisfies the central limit theorem (CLT). The key ingredients of the proof are the analysis of the invariant measure equation and construction of a linearly growing martingale for walks in bounded potential. Our main result implies a complete classification of recurrent i.i.d. RWRE on the strip. Namely the walk either exhibits the Sinai behaviour in the sense that converges, as , to a (random) limit (the Sinai law) or, it satisfies the CLT. Another application of our main result is the CLT for the quasiperiodic environments with Diophantine frequencies in the recurrent case. We complement this result by proving that in the transient case the CLT holds for all uniquely ergodic environments. We also investigate the algebraic structure of the environments satisfying the CLT. In particular, we show that there exists a collection of proper algebraic subvarieties in the space of transition probabilities, such that: • If RE is stationary and ergodic and the transition probabilities are con-centrated on one of subvarieties from our collection then the CLT holds. • If the environment is i.i.d then the above condition is also necessary forthe CLT. All these results are valid for one-dimensional RWRE with bounded jumps as a particular case of the strip model.

Structure, Dynamics and Environment of Galaxies

NASA Astrophysics Data System (ADS)

Combes, Francoise; Terlevich, Roberto

This contribution presents a summary of the discussion on structure, dynamics and environment of Galaxies, held on Friday May 26 evening, after the Sherry/Coffee interval and the oral presentation of two dozen posters papers.

Shuttle payload bay dynamic environments: Summary and conclusion report for STS flights 1-5 and 9

NASA Technical Reports Server (NTRS)

Oconnell, M.; Garba, J.; Kern, D.

1984-01-01

The vibration, acoustic and low frequency loads data from the first 5 shuttle flights are presented. The engineering analysis of that data is also presented. Vibroacoustic data from STS-9 are also presented because they represent the only data taken on a large payload. Payload dynamic environment predictions developed by the participation of various NASA and industrial centers are presented along with a comparison of analytical loads methodology predictions with flight data, including a brief description of the methodologies employed in developing those predictions for payloads. The review of prediction methodologies illustrates how different centers have approached the problems of developing shuttle dynamic environmental predictions and criteria. Ongoing research activities related to the shuttle dynamic environments are also described. Analytical software recently developed for the prediction of payload acoustic and vibration environments are also described.

Dynamic evolution of Rayleigh-Taylor bubbles from sinusoidal, W-shaped, and random perturbations

NASA Astrophysics Data System (ADS)

Zhou, Zhi-Rui; Zhang, You-Sheng; Tian, Bao-Lin

2018-03-01

Implicit large eddy simulations of two-dimensional Rayleigh-Taylor instability at different density ratios (i.e., Atwood number A =0.05 , 0.5, and 0.9) are conducted to investigate the late-time dynamics of bubbles. To produce a flow field full of bounded, semibounded, and chaotic bubbles, three problems with distinct perturbations are simulated: (I) periodic sinusoidal perturbation, (II) isolated W-shaped perturbation, and (III) random short-wave perturbations. The evolution of height h , velocity v , and diameter D of the (dominant) bubble with time t are formulated and analyzed. In problem I, during the quasisteady stage, the simulations confirm Goncharov's prediction of the terminal speed v∞=Fr√{A g λ /(1 +A ) } , where Fr=1 /√{3 π } . Moreover, the diameter D at this stage is found to be proportional to the initial perturbation wavelength λ as D ≈λ . This differed from Daly's simulation result of D =λ (1 +A )/2 . In problem II, a W-shaped perturbation is designed to produce a bubble environment similar to that of chaotic bubbles in problem III. We obtain a similar terminal speed relationship as above, but Fr is replaced by Frw≈0.63 . In problem III, the simulations show that h grows quadratically with the bubble acceleration constant α ≡h /(A g t2)≈0.05 , and D expands self-similarly with a steady aspect ratio β ≡D /h ≈(1 +A )/2 , which differs from existing theories. Therefore, following the mechanism of self-similar growth, we derive a relationship of β =4 α (1 +A ) /Frw2 to relate the evolution of chaotic bubbles in problem III to that of semibounded bubbles in problem II. The validity of this relationship highlights the fact that the dynamics of chaotic bubbles in problem III are similar to the semibounded isolated bubbles in problem II, but not to that of bounded periodic bubbles in problem I.

From homeostasis to behavior: Balanced activity in an exploration of embodied dynamic environmental-neural interaction.

PubMed

Hellyer, Peter John; Clopath, Claudia; Kehagia, Angie A; Turkheimer, Federico E; Leech, Robert

2017-08-01

In recent years, there have been many computational simulations of spontaneous neural dynamics. Here, we describe a simple model of spontaneous neural dynamics that controls an agent moving in a simple virtual environment. These dynamics generate interesting brain-environment feedback interactions that rapidly destabilize neural and behavioral dynamics demonstrating the need for homeostatic mechanisms. We investigate roles for homeostatic plasticity both locally (local inhibition adjusting to balance excitatory input) as well as more globally (regional "task negative" activity that compensates for "task positive", sensory input in another region) balancing neural activity and leading to more stable behavior (trajectories through the environment). Our results suggest complementary functional roles for both local and macroscale mechanisms in maintaining neural and behavioral dynamics and a novel functional role for macroscopic "task-negative" patterns of activity (e.g., the default mode network).

Dynamic access control model for privacy preserving personalized healthcare in cloud environment.

PubMed

Son, Jiseong; Kim, Jeong-Dong; Na, Hong-Seok; Baik, Doo-Kwon

2015-01-01

When sharing and storing healthcare data in a cloud environment, access control is a central issue for preserving data privacy as a patient's personal health data may be accessed without permission from many stakeholders. Specifically, dynamic authorization for the access of data is required because personal health data is stored in cloud storage via wearable devices. Therefore, we propose a dynamic access control model for preserving the privacy of personal healthcare data in a cloud environment. The proposed model considers context information for dynamic access. According to the proposed model, access control can be dynamically determined by changing the context information; this means that even for a subject with the same role in the cloud, access permission is defined differently depending on the context information and access condition. Furthermore, we experiment the ability of the proposed model to provide correct responses by representing a dynamic access decision with real-life personalized healthcare system scenarios.

High-resolution digital mapping of soil organic carbon in permafrost terrain using machine learning: a case study in a sub-Arctic peatland environment

NASA Astrophysics Data System (ADS)

Siewert, Matthias B.

2018-03-01

Soil organic carbon (SOC) stored in northern peatlands and permafrost-affected soils are key components in the global carbon cycle. This article quantifies SOC stocks in a sub-Arctic mountainous peatland environment in the discontinuous permafrost zone in Abisko, northern Sweden. Four machine-learning techniques are evaluated for SOC quantification: multiple linear regression, artificial neural networks, support vector machine and random forest. The random forest model performed best and was used to predict SOC for several depth increments at a spatial resolution of 1 m (1×1 m). A high-resolution (1 m) land cover classification generated for this study is the most relevant predictive variable. The landscape mean SOC storage (0-150 cm) is estimated to be 8.3 ± 8.0 kg C m-2 and the SOC stored in the top meter (0-100 cm) to be 7.7 ± 6.2 kg C m-2. The predictive modeling highlights the relative importance of wetland areas and in particular peat plateaus for the landscape's SOC storage. The total SOC was also predicted at reduced spatial resolutions of 2, 10, 30, 100, 250 and 1000 m and shows a significant drop in land cover class detail and a tendency to underestimate the SOC at resolutions > 30 m. This is associated with the occurrence of many small-scale wetlands forming local hot-spots of SOC storage that are omitted at coarse resolutions. Sharp transitions in SOC storage associated with land cover and permafrost distribution are the most challenging methodological aspect. However, in this study, at local, regional and circum-Arctic scales, the main factor limiting robust SOC mapping efforts is the scarcity of soil pedon data from across the entire environmental space. For the Abisko region, past SOC and permafrost dynamics indicate that most of the SOC is barely 2000 years old and very dynamic. Future research needs to investigate the geomorphic response of permafrost degradation and the fate of SOC across all landscape compartments in post-permafrost landscapes.

Stochastic dynamics of time correlation in complex systems with discrete time

NASA Astrophysics Data System (ADS)

Yulmetyev, Renat; Hänggi, Peter; Gafarov, Fail

2000-11-01

In this paper we present the concept of description of random processes in complex systems with discrete time. It involves the description of kinetics of discrete processes by means of the chain of finite-difference non-Markov equations for time correlation functions (TCFs). We have introduced the dynamic (time dependent) information Shannon entropy Si(t) where i=0,1,2,3,..., as an information measure of stochastic dynamics of time correlation (i=0) and time memory (i=1,2,3,...). The set of functions Si(t) constitute the quantitative measure of time correlation disorder (i=0) and time memory disorder (i=1,2,3,...) in complex system. The theory developed started from the careful analysis of time correlation involving dynamics of vectors set of various chaotic states. We examine two stochastic processes involving the creation and annihilation of time correlation (or time memory) in details. We carry out the analysis of vectors' dynamics employing finite-difference equations for random variables and the evolution operator describing their natural motion. The existence of TCF results in the construction of the set of projection operators by the usage of scalar product operation. Harnessing the infinite set of orthogonal dynamic random variables on a basis of Gram-Shmidt orthogonalization procedure tends to creation of infinite chain of finite-difference non-Markov kinetic equations for discrete TCFs and memory functions (MFs). The solution of the equations above thereof brings to the recurrence relations between the TCF and MF of senior and junior orders. This offers new opportunities for detecting the frequency spectra of power of entropy function Si(t) for time correlation (i=0) and time memory (i=1,2,3,...). The results obtained offer considerable scope for attack on stochastic dynamics of discrete random processes in a complex systems. Application of this technique on the analysis of stochastic dynamics of RR intervals from human ECG's shows convincing evidence for a non-Markovian phenomemena associated with a peculiarities in short- and long-range scaling. This method may be of use in distinguishing healthy from pathologic data sets based in differences in these non-Markovian properties.

Perceptions of the Effectiveness of System Dynamics-Based Interactive Learning Environments: An Empirical Study

ERIC Educational Resources Information Center

Qudrat-Ullah, Hassan

2010-01-01

The use of simulations in general and of system dynamics simulation based interactive learning environments (SDILEs) in particular is well recognized as an effective way of improving users' decision making and learning in complex, dynamic tasks. However, the effectiveness of SDILEs in classrooms has rarely been evaluated. This article describes…

Investigating the Problem Solving Competency of Pre Service Teachers in Dynamic Geometry Environment

ERIC Educational Resources Information Center

Haja, Shajahan

2005-01-01

This study investigated the problem-solving competency of four secondary pre service teachers (PSTs) of University of London as they explored geometry problems in dynamic geometry environment (DGE) in 2004. A constructivist experiment was designed in which dynamic software Cabri-Geometre II (hereafter Cabri) was used as an interactive medium.…

Condensation of helium in aerogel and athermal dynamics of the random-field Ising model.

PubMed

Aubry, Geoffroy J; Bonnet, Fabien; Melich, Mathieu; Guyon, Laurent; Spathis, Panayotis; Despetis, Florence; Wolf, Pierre-Etienne

2014-08-22

High resolution measurements reveal that condensation isotherms of (4)He in high porosity silica aerogel become discontinuous below a critical temperature. We show that this behavior does not correspond to an equilibrium phase transition modified by the disorder induced by the aerogel structure, but to the disorder-driven critical point predicted for the athermal out-of-equilibrium dynamics of the random-field Ising model. Our results evidence the key role of nonequilibrium effects in the phase transitions of disordered systems.

Modeling of synchronization behavior of bursting neurons at nonlinearly coupled dynamical networks.

PubMed

Çakir, Yüksel

2016-01-01

Synchronization behaviors of bursting neurons coupled through electrical and dynamic chemical synapses are investigated. The Izhikevich model is used with random and small world network of bursting neurons. Various currents which consist of diffusive electrical and time-delayed dynamic chemical synapses are used in the simulations to investigate the influences of synaptic currents and couplings on synchronization behavior of bursting neurons. The effects of parameters, such as time delay, inhibitory synaptic strengths, and decay time on synchronization behavior are investigated. It is observed that in random networks with no delay, bursting synchrony is established with the electrical synapse alone, single spiking synchrony is observed with hybrid coupling. In small world network with no delay, periodic bursting behavior with multiple spikes is observed when only chemical and only electrical synapse exist. Single-spike and multiple-spike bursting are established with hybrid couplings. A decrease in the synchronization measure is observed with zero time delay, as the decay time is increased in random network. For synaptic delays which are above active phase period, synchronization measure increases with an increase in synaptic strength and time delay in small world network. However, in random network, it increases with only an increase in synaptic strength.

Dynamic Resource Allocation and Access Class Barring Scheme for Delay-Sensitive Devices in Machine to Machine (M2M) Communications.

PubMed

Li, Ning; Cao, Chao; Wang, Cong

2017-06-15

Supporting simultaneous access of machine-type devices is a critical challenge in machine-to-machine (M2M) communications. In this paper, we propose an optimal scheme to dynamically adjust the Access Class Barring (ACB) factor and the number of random access channel (RACH) resources for clustered machine-to-machine (M2M) communications, in which Delay-Sensitive (DS) devices coexist with Delay-Tolerant (DT) ones. In M2M communications, since delay-sensitive devices share random access resources with delay-tolerant devices, reducing the resources consumed by delay-sensitive devices means that there will be more resources available to delay-tolerant ones. Our goal is to optimize the random access scheme, which can not only satisfy the requirements of delay-sensitive devices, but also take the communication quality of delay-tolerant ones into consideration. We discuss this problem from the perspective of delay-sensitive services by adjusting the resource allocation and ACB scheme for these devices dynamically. Simulation results show that our proposed scheme realizes good performance in satisfying the delay-sensitive services as well as increasing the utilization rate of the random access resources allocated to them.

Essential energy space random walk via energy space metadynamics method to accelerate molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Li, Hongzhi; Min, Donghong; Liu, Yusong; Yang, Wei

2007-09-01

To overcome the possible pseudoergodicity problem, molecular dynamic simulation can be accelerated via the realization of an energy space random walk. To achieve this, a biased free energy function (BFEF) needs to be priori obtained. Although the quality of BFEF is essential for sampling efficiency, its generation is usually tedious and nontrivial. In this work, we present an energy space metadynamics algorithm to efficiently and robustly obtain BFEFs. Moreover, in order to deal with the associated diffusion sampling problem caused by the random walk in the total energy space, the idea in the original umbrella sampling method is generalized to be the random walk in the essential energy space, which only includes the energy terms determining the conformation of a region of interest. This essential energy space generalization allows the realization of efficient localized enhanced sampling and also offers the possibility of further sampling efficiency improvement when high frequency energy terms irrelevant to the target events are free of activation. The energy space metadynamics method and its generalization in the essential energy space for the molecular dynamics acceleration are demonstrated in the simulation of a pentanelike system, the blocked alanine dipeptide model, and the leucine model.

G-Consistent Subsets and Reduced Dynamical Quantum Maps

NASA Astrophysics Data System (ADS)

Ceballos, Russell R.

A quantum system which evolves in time while interacting with an external environ- ment is said to be an open quantum system (OQS), and the influence of the environment on the unperturbed unitary evolution of the system generally leads to non-unitary dynamics. This kind of open system dynamical evolution has been typically modeled by a Standard Prescription (SP) which assumes that the state of the OQS is initially uncorrelated with the environment state. It is here shown that when a minimal set of physically motivated assumptions are adopted, not only does there exist constraints on the reduced dynamics of an OQS such that this SP does not always accurately describe the possible initial cor- relations existing between the OQS and environment, but such initial correlations, and even entanglement, can be witnessed when observing a particular class of reduced state transformations termed purity extractions are observed. Furthermore, as part of a more fundamental investigation to better understand the minimal set of assumptions required to formulate well defined reduced dynamical quantum maps, it is demonstrated that there exists a one-to-one correspondence between the set of initial reduced states and the set of admissible initial system-environment composite states when G-consistency is enforced. Given the discussions surrounding the requirement of complete positivity and the reliance on the SP, the results presented here may well be found valuable for determining the ba- sic properties of reduced dynamical maps, and when restrictions on the OQS dynamics naturally emerge.

Peer Influence, Genetic Propensity, and Binge Drinking: A Natural Experiment and a Replication.

PubMed

Guo, Guang; Li, Yi; Wang, Hongyu; Cai, Tianji; Duncan, Greg J

2015-11-01

The authors draw data from the College Roommate Study (ROOM) and the National Longitudinal Study of Adolescent Health to investigate gene-environment interaction effects on youth binge drinking. In ROOM, the environmental influence was measured by the precollege drinking behavior of randomly assigned roommates. Random assignment safeguards against friend selection and removes the threat of gene-environment correlation that makes gene-environment interaction effects difficult to interpret. On average, being randomly assigned a drinking peer as opposed to a nondrinking peer increased college binge drinking by 0.5-1.0 episodes per month, or 20%-40% the average amount of binge drinking. However, this peer influence was found only among youths with a medium level of genetic propensity for alcohol use; those with either a low or high genetic propensity were not influenced by peer drinking. A replication of the findings is provided in data drawn from Add Health. The study shows that gene-environment interaction analysis can uncover social-contextual effects likely to be missed by traditional sociological approaches.

Channeling of Branched Flow in Weakly Scattering Anisotropic Media.

PubMed

Degueldre, Henri; Metzger, Jakob J; Schultheis, Erik; Fleischmann, Ragnar

2017-01-13

When waves propagate through weakly scattering but correlated, disordered environments they are randomly focused into pronounced branchlike structures, a phenomenon referred to as branched flow, which has been studied in a wide range of isotropic random media. In many natural environments, however, the fluctuations of the random medium typically show pronounced anisotropies. A prominent example is the focusing of tsunami waves by the anisotropic structure of the ocean floor topography. We study the influence of anisotropy on such natural focusing events and find a strong and nonintuitive dependence on the propagation angle which we explain by semiclassical theory.

Organizational Strategy and Business Environment Effects Based on a Computation Method

NASA Astrophysics Data System (ADS)

Reklitis, Panagiotis; Konstantopoulos, Nikolaos; Trivellas, Panagiotis

2007-12-01

According to many researchers of organizational theory, a great number of problems encountered by the manufacturing firms are due to their ineffectiveness to respond to significant changes of their external environment and align their competitive strategy accordingly. From this point of view, the pursuit of the appropriate generic strategy is vital for firms facing a dynamic and highly competitive environment. In the present paper, we adopt Porter's typology to operationalise organizational strategy (cost leadership, innovative and marketing differentiation, and focus) considering changes in the external business environment (dynamism, complexity and munificence). Although simulation of social events is a quite difficult task, since there are so many considerations (not all well understood) involved, in the present study we developed a dynamic system based on the conceptual framework of strategy-environment associations.

Recovery time after localized perturbations in complex dynamical networks

NASA Astrophysics Data System (ADS)

Mitra, Chiranjit; Kittel, Tim; Choudhary, Anshul; Kurths, Jürgen; Donner, Reik V.

2017-10-01

Maintaining the synchronous motion of dynamical systems interacting on complex networks is often critical to their functionality. However, real-world networked dynamical systems operating synchronously are prone to random perturbations driving the system to arbitrary states within the corresponding basin of attraction, thereby leading to epochs of desynchronized dynamics with a priori unknown durations. Thus, it is highly relevant to have an estimate of the duration of such transient phases before the system returns to synchrony, following a random perturbation to the dynamical state of any particular node of the network. We address this issue here by proposing the framework of single-node recovery time (SNRT) which provides an estimate of the relative time scales underlying the transient dynamics of the nodes of a network during its restoration to synchrony. We utilize this in differentiating the particularly slow nodes of the network from the relatively fast nodes, thus identifying the critical nodes which when perturbed lead to significantly enlarged recovery time of the system before resuming synchronized operation. Further, we reveal explicit relationships between the SNRT values of a network, and its global relaxation time when starting all the nodes from random initial conditions. Earlier work on relaxation time generally focused on investigating its dependence on macroscopic topological properties of the respective network. However, we employ the proposed concept for deducing microscopic relationships between topological features of nodes and their respective SNRT values. The framework of SNRT is further extended to a measure of resilience of the different nodes of a networked dynamical system. We demonstrate the potential of SNRT in networks of Rössler oscillators on paradigmatic topologies and a model of the power grid of the United Kingdom with second-order Kuramoto-type nodal dynamics illustrating the conceivable practical applicability of the proposed concept.

Students' Views about the Problem Based Collaborative Learning Environment Supported by Dynamic Web Technologies

ERIC Educational Resources Information Center

Ünal, Erhan; Çakir, Hasan

2017-01-01

The purpose of this study was to design a problem based collaborative learning environment supported by dynamic web technologies and to examine students' views about this learning environment. The study was designed as a qualitative research. Some 36 students who took an Object Oriented Programming I-II course at the department of computer…

Dynamic but Prosaic: A Methodology for Studying E-Learning Environments

ERIC Educational Resources Information Center

Whitworth, Andrew

2006-01-01

This paper develops a critical methodology which could be applied to the study and use of e-learning environments. The foundations are, first, an ontological appreciation of environments as multiple, dynamic and interactive: this is based on the environmental theories of Vladimir Vernadsky. The next step is then into epistemology, and here use is…

Fractal Landscape Algorithms for Environmental Simulations

NASA Astrophysics Data System (ADS)

Mao, H.; Moran, S.

2014-12-01

Natural science and geographical research are now able to take advantage of environmental simulations that more accurately test experimental hypotheses, resulting in deeper understanding. Experiments affected by the natural environment can benefit from 3D landscape simulations capable of simulating a variety of terrains and environmental phenomena. Such simulations can employ random terrain generation algorithms that dynamically simulate environments to test specific models against a variety of factors. Through the use of noise functions such as Perlin noise, Simplex noise, and diamond square algorithms, computers can generate simulations that model a variety of landscapes and ecosystems. This study shows how these algorithms work together to create realistic landscapes. By seeding values into the diamond square algorithm, one can control the shape of landscape. Perlin noise and Simplex noise are also used to simulate moisture and temperature. The smooth gradient created by coherent noise allows more realistic landscapes to be simulated. Terrain generation algorithms can be used in environmental studies and physics simulations. Potential studies that would benefit from simulations include the geophysical impact of flash floods or drought on a particular region and regional impacts on low lying area due to global warming and rising sea levels. Furthermore, terrain generation algorithms also serve as aesthetic tools to display landscapes (Google Earth), and simulate planetary landscapes. Hence, it can be used as a tool to assist science education. Algorithms used to generate these natural phenomena provide scientists a different approach in analyzing our world. The random algorithms used in terrain generation not only contribute to the generating the terrains themselves, but are also capable of simulating weather patterns.

Non-equilibrium quantum phase transition via entanglement decoherence dynamics.

PubMed

Lin, Yu-Chen; Yang, Pei-Yun; Zhang, Wei-Min

2016-10-07

We investigate the decoherence dynamics of continuous variable entanglement as the system-environment coupling strength varies from the weak-coupling to the strong-coupling regimes. Due to the existence of localized modes in the strong-coupling regime, the system cannot approach equilibrium with its environment, which induces a nonequilibrium quantum phase transition. We analytically solve the entanglement decoherence dynamics for an arbitrary spectral density. The nonequilibrium quantum phase transition is demonstrated as the system-environment coupling strength varies for all the Ohmic-type spectral densities. The 3-D entanglement quantum phase diagram is obtained.

The Living Arrangement Dynamics of Sick, Elderly Individuals

ERIC Educational Resources Information Center

Dostie, Benoit; Leger, Pierre Thomas

2005-01-01

We model the dynamics associated with living-arrangement decisions of sick elderly individuals. Using the Panel Study of Income Dynamics? Parental Health Supplement, we construct the complete living-arrangement histories of elderly individuals in need of care. We use a simultaneous random-effects competing-risks model to analyze the impact of…

Two-dimensional confocal laser scanning microscopy image correlation for nanoparticle flow velocimetry

NASA Astrophysics Data System (ADS)

Jun, Brian; Giarra, Matthew; Golz, Brian; Main, Russell; Vlachos, Pavlos

2016-11-01

We present a methodology to mitigate the major sources of error associated with two-dimensional confocal laser scanning microscopy (CLSM) images of nanoparticles flowing through a microfluidic channel. The correlation-based velocity measurements from CLSM images are subject to random error due to the Brownian motion of nanometer-sized tracer particles, and a bias error due to the formation of images by raster scanning. Here, we develop a novel ensemble phase correlation with dynamic optimal filter that maximizes the correlation strength, which diminishes the random error. In addition, we introduce an analytical model of CLSM measurement bias error correction due to two-dimensional image scanning of tracer particles. We tested our technique using both synthetic and experimental images of nanoparticles flowing through a microfluidic channel. We observed that our technique reduced the error by up to a factor of ten compared to ensemble standard cross correlation (SCC) for the images tested in the present work. Subsequently, we will assess our framework further, by interrogating nanoscale flow in the cell culture environment (transport within the lacunar-canalicular system) to demonstrate our ability to accurately resolve flow measurements in a biological system.

Ensembles of Spiking Neurons with Noise Support Optimal Probabilistic Inference in a Dynamically Changing Environment

PubMed Central

Legenstein, Robert; Maass, Wolfgang

2014-01-01

It has recently been shown that networks of spiking neurons with noise can emulate simple forms of probabilistic inference through “neural sampling”, i.e., by treating spikes as samples from a probability distribution of network states that is encoded in the network. Deficiencies of the existing model are its reliance on single neurons for sampling from each random variable, and the resulting limitation in representing quickly varying probabilistic information. We show that both deficiencies can be overcome by moving to a biologically more realistic encoding of each salient random variable through the stochastic firing activity of an ensemble of neurons. The resulting model demonstrates that networks of spiking neurons with noise can easily track and carry out basic computational operations on rapidly varying probability distributions, such as the odds of getting rewarded for a specific behavior. We demonstrate the viability of this new approach towards neural coding and computation, which makes use of the inherent parallelism of generic neural circuits, by showing that this model can explain experimentally observed firing activity of cortical neurons for a variety of tasks that require rapid temporal integration of sensory information. PMID:25340749

Using trading strategies to detect phase transitions in financial markets.

PubMed

Forró, Z; Woodard, R; Sornette, D

2015-04-01

We show that the log-periodic power law singularity model (LPPLS), a mathematical embodiment of positive feedbacks between agents and of their hierarchical dynamical organization, has a significant predictive power in financial markets. We find that LPPLS-based strategies significantly outperform the randomized ones and that they are robust with respect to a large selection of assets and time periods. The dynamics of prices thus markedly deviate from randomness in certain pockets of predictability that can be associated with bubble market regimes. Our hybrid approach, marrying finance with the trading strategies, and critical phenomena with LPPLS, demonstrates that targeting information related to phase transitions enables the forecast of financial bubbles and crashes punctuating the dynamics of prices.

Using trading strategies to detect phase transitions in financial markets

NASA Astrophysics Data System (ADS)

Forró, Z.; Woodard, R.; Sornette, D.

2015-04-01

We show that the log-periodic power law singularity model (LPPLS), a mathematical embodiment of positive feedbacks between agents and of their hierarchical dynamical organization, has a significant predictive power in financial markets. We find that LPPLS-based strategies significantly outperform the randomized ones and that they are robust with respect to a large selection of assets and time periods. The dynamics of prices thus markedly deviate from randomness in certain pockets of predictability that can be associated with bubble market regimes. Our hybrid approach, marrying finance with the trading strategies, and critical phenomena with LPPLS, demonstrates that targeting information related to phase transitions enables the forecast of financial bubbles and crashes punctuating the dynamics of prices.

Capillary-tube-based extension of thermoacoustic theory for a random medium

NASA Astrophysics Data System (ADS)

Roh, Heui-Seol; Raspet, Richard; Bass, Henry E.

2005-09-01

Thermoacoustic theory for a single capillary tube is extended to random bulk medium on the basis of capillary tubes. The characteristics of the porous stack inside the resonator such as the tortuosity, dynamic shape factor, and porosity are introduced for the extension of wave equation by following Attenborough's approach. Separation of the dynamic shape factor for the viscous and thermal effect is adopted and scaling using the dynamic shape factor and tortuosity factor is demonstrated. The theoretical and experimental comparison of thermoviscous functions in reticulated vitreous carbon (RVC) and aluminum foam shows reasonable agreement. The extension is useful for investigations of the properties of a stack with arbitrary shapes of non-parallel pores.

Evolutionary dynamics of adult stem cells: comparison of random and immortal-strand segregation mechanisms.

PubMed

Tannenbaum, Emmanuel; Sherley, James L; Shakhnovich, Eugene I

2005-04-01

This paper develops a point-mutation model describing the evolutionary dynamics of a population of adult stem cells. Such a model may prove useful for quantitative studies of tissue aging and the emergence of cancer. We consider two modes of chromosome segregation: (1) random segregation, where the daughter chromosomes of a given parent chromosome segregate randomly into the stem cell and its differentiating sister cell and (2) "immortal DNA strand" co-segregation, for which the stem cell retains the daughter chromosomes with the oldest parent strands. Immortal strand co-segregation is a mechanism, originally proposed by [Cairns Nature (London) 255, 197 (1975)], by which stem cells preserve the integrity of their genomes. For random segregation, we develop an ordered strand pair formulation of the dynamics, analogous to the ordered strand pair formalism developed for quasispecies dynamics involving semiconservative replication with imperfect lesion repair (in this context, lesion repair is taken to mean repair of postreplication base-pair mismatches). Interestingly, a similar formulation is possible with immortal strand co-segregation, despite the fact that this segregation mechanism is age dependent. From our model we are able to mathematically show that, when lesion repair is imperfect, then immortal strand co-segregation leads to better preservation of the stem cell lineage than random chromosome segregation. Furthermore, our model allows us to estimate the optimal lesion repair efficiency for preserving an adult stem cell population for a given period of time. For human stem cells, we obtain that mispaired bases still present after replication and cell division should be left untouched, to avoid potentially fixing a mutation in both DNA strands.

Evolutionary dynamics of adult stem cells: Comparison of random and immortal-strand segregation mechanisms

NASA Astrophysics Data System (ADS)

Tannenbaum, Emmanuel; Sherley, James L.; Shakhnovich, Eugene I.

2005-04-01

This paper develops a point-mutation model describing the evolutionary dynamics of a population of adult stem cells. Such a model may prove useful for quantitative studies of tissue aging and the emergence of cancer. We consider two modes of chromosome segregation: (1) random segregation, where the daughter chromosomes of a given parent chromosome segregate randomly into the stem cell and its differentiating sister cell and (2) “immortal DNA strand” co-segregation, for which the stem cell retains the daughter chromosomes with the oldest parent strands. Immortal strand co-segregation is a mechanism, originally proposed by [Cairns Nature (London) 255, 197 (1975)], by which stem cells preserve the integrity of their genomes. For random segregation, we develop an ordered strand pair formulation of the dynamics, analogous to the ordered strand pair formalism developed for quasispecies dynamics involving semiconservative replication with imperfect lesion repair (in this context, lesion repair is taken to mean repair of postreplication base-pair mismatches). Interestingly, a similar formulation is possible with immortal strand co-segregation, despite the fact that this segregation mechanism is age dependent. From our model we are able to mathematically show that, when lesion repair is imperfect, then immortal strand co-segregation leads to better preservation of the stem cell lineage than random chromosome segregation. Furthermore, our model allows us to estimate the optimal lesion repair efficiency for preserving an adult stem cell population for a given period of time. For human stem cells, we obtain that mispaired bases still present after replication and cell division should be left untouched, to avoid potentially fixing a mutation in both DNA strands.

Steady States, Fluctuation-Dissipation Theorems and Homogenization for Reversible Diffusions in a Random Environment

NASA Astrophysics Data System (ADS)

Mathieu, P.; Piatnitski, A.

2018-04-01

Prolongating our previous paper on the Einstein relation, we study the motion of a particle diffusing in a random reversible environment when subject to a small external forcing. In order to describe the long time behavior of the particle, we introduce the notions of steady state and weak steady state. We establish the continuity of weak steady states for an ergodic and uniformly elliptic environment. When the environment has finite range of dependence, we prove the existence of the steady state and weak steady state and compute its derivative at a vanishing force. Thus we obtain a complete `fluctuation-dissipation Theorem' in this context as well as the continuity of the effective variance.

Lattice Boltzmann simulations for wall-flow dynamics in porous ceramic diesel particulate filters

NASA Astrophysics Data System (ADS)

Lee, Da Young; Lee, Gi Wook; Yoon, Kyu; Chun, Byoungjin; Jung, Hyun Wook

2018-01-01

Flows through porous filter walls of wall-flow diesel particulate filter are investigated using the lattice Boltzmann method (LBM). The microscopic model of the realistic filter wall is represented by randomly overlapped arrays of solid spheres. The LB simulation results are first validated by comparison to those from previous hydrodynamic theories and constitutive models for flows in porous media with simple regular and random solid-wall configurations. We demonstrate that the newly designed randomly overlapped array structures of porous walls allow reliable and accurate simulations for the porous wall-flow dynamics in a wide range of solid volume fractions from 0.01 to about 0.8, which is beyond the maximum random packing limit of 0.625. The permeable performance of porous media is scrutinized by changing the solid volume fraction and particle Reynolds number using Darcy's law and Forchheimer's extension in the laminar flow region.

Dynamic speckle - Interferometry of micro-displacements

NASA Astrophysics Data System (ADS)

Vladimirov, A. P.

2012-06-01

The problem of the dynamics of speckles in the image plane of the object, caused by random movements of scattering centers is solved. We consider three cases: 1) during the observation the points move at random, but constant speeds, and 2) the relative displacement of any pair of points is a continuous random process, and 3) the motion of the centers is the sum of a deterministic movement and random displacement. For the cases 1) and 2) the characteristics of temporal and spectral autocorrelation function of the radiation intensity can be used for determining of individually and the average relative displacement of the centers, their dispersion and the relaxation time. For the case 3) is showed that under certain conditions, the optical signal contains a periodic component, the number of periods is proportional to the derivations of the deterministic displacements. The results of experiments conducted to test and application of theory are given.

Dynamic stability of spinning pretwisted beams subjected to axial random forces

NASA Astrophysics Data System (ADS)

Young, T. H.; Gau, C. Y.

2003-11-01

This paper studies the dynamic stability of a pretwisted cantilever beam spinning along its longitudinal axis and subjected to an axial random force at the free end. The axial force is assumed as the sum of a constant force and a random process with a zero mean. Due to this axial force, the beam may experience parametric random instability. In this work, the finite element method is first applied to yield discretized system equations. The stochastic averaging method is then adopted to obtain Ito's equations for the response amplitudes of the system. Finally the mean-square stability criterion is utilized to determine the stability condition of the system. Numerical results show that the stability boundary of the system converges as the first three modes are taken into calculation. Before the convergence is reached, the stability condition predicted is not conservative enough.

Correlated Fluctuations in Strongly Coupled Binary Networks Beyond Equilibrium

NASA Astrophysics Data System (ADS)

Dahmen, David; Bos, Hannah; Helias, Moritz

2016-07-01

Randomly coupled Ising spins constitute the classical model of collective phenomena in disordered systems, with applications covering glassy magnetism and frustration, combinatorial optimization, protein folding, stock market dynamics, and social dynamics. The phase diagram of these systems is obtained in the thermodynamic limit by averaging over the quenched randomness of the couplings. However, many applications require the statistics of activity for a single realization of the possibly asymmetric couplings in finite-sized networks. Examples include reconstruction of couplings from the observed dynamics, representation of probability distributions for sampling-based inference, and learning in the central nervous system based on the dynamic and correlation-dependent modification of synaptic connections. The systematic cumulant expansion for kinetic binary (Ising) threshold units with strong, random, and asymmetric couplings presented here goes beyond mean-field theory and is applicable outside thermodynamic equilibrium; a system of approximate nonlinear equations predicts average activities and pairwise covariances in quantitative agreement with full simulations down to hundreds of units. The linearized theory yields an expansion of the correlation and response functions in collective eigenmodes, leads to an efficient algorithm solving the inverse problem, and shows that correlations are invariant under scaling of the interaction strengths.

Quantum dynamics of nuclear spins and spin relaxation in organic semiconductors

NASA Astrophysics Data System (ADS)

Mkhitaryan, V. V.; Dobrovitski, V. V.

2017-06-01

We investigate the role of the nuclear-spin quantum dynamics in hyperfine-induced spin relaxation of hopping carriers in organic semiconductors. The fast-hopping regime, when the carrier spin does not rotate much between subsequent hops, is typical for organic semiconductors possessing long spin coherence times. We consider this regime and focus on a carrier random-walk diffusion in one dimension, where the effect of the nuclear-spin dynamics is expected to be the strongest. Exact numerical simulations of spin systems with up to 25 nuclear spins are performed using the Suzuki-Trotter decomposition of the evolution operator. Larger nuclear-spin systems are modeled utilizing the spin-coherent state P -representation approach developed earlier. We find that the nuclear-spin dynamics strongly influences the carrier spin relaxation at long times. If the random walk is restricted to a small area, it leads to the quenching of carrier spin polarization at a nonzero value at long times. If the random walk is unrestricted, the carrier spin polarization acquires a long-time tail, decaying as 1 /√{t } . Based on the numerical results, we devise a simple formula describing the effect quantitatively.

Visual Environments for CFD Research

NASA Technical Reports Server (NTRS)

Watson, Val; George, Michael W. (Technical Monitor)

1994-01-01

This viewgraph presentation gives an overview of the visual environments for computational fluid dynamics (CFD) research. It includes details on critical needs from the future computer environment, features needed to attain this environment, prospects for changes in and the impact of the visualization revolution on the human-computer interface, human processing capabilities, limits of personal environment and the extension of that environment with computers. Information is given on the need for more 'visual' thinking (including instances of visual thinking), an evaluation of the alternate approaches for and levels of interactive computer graphics, a visual analysis of computational fluid dynamics, and an analysis of visualization software.

Esterified sago waste for engine oil removal in aqueous environment.

PubMed

Ngaini, Zainab; Noh, Farid; Wahi, Rafeah

2014-01-01

Agro-waste from the bark of Metroxylon sagu (sago) was studied as a low cost and effective oil sorbent in dry and aqueous environments. Sorption study was conducted using untreated sago bark (SB) and esterified sago bark (ESB) in used engine oil. Characterization study showed that esterification has successfully improved the hydrophobicity, buoyancy, surface roughness and oil sorption capacity of ESB. Sorption study revealed that water uptake of SB is higher (30 min static: 2.46 g/g, dynamic: 2.67 g/g) compared with ESB (30 min static: 0.18 g/g, dynamic: 0.14 g/g). ESB, however, showed higher oil sorption capacity in aqueous environment (30 min static: 2.30 g/g, dynamic: 2.14) compared with SB (30 min static: 0 g/g, dynamic: 0 g/g). ESB has shown great poTENTial as effective oil sorbent in aqueous environment due to its high oil sorption capacity, low water uptake and high buoyancy.

Rotational diffusion of a molecular cat

NASA Astrophysics Data System (ADS)

Katz-Saporta, Ori; Efrati, Efi

We show that a simple isolated system can perform rotational random walk on account of internal excitations alone. We consider the classical dynamics of a ''molecular cat'': a triatomic molecule connected by three harmonic springs with non-zero rest lengths, suspended in free space. In this system, much like for falling cats, the angular momentum constraint is non-holonomic allowing for rotations with zero overall angular momentum. The geometric nonlinearities arising from the non-zero rest lengths of the springs suffice to break integrability and lead to chaotic dynamics. The coupling of the non-integrability of the system and its non-holonomic nature results in an angular random walk of the molecule. We study the properties and dynamics of this angular motion analytically and numerically. For low energy excitations the system displays normal-mode-like motion, while for high enough excitation energy we observe regular random-walk. In between, at intermediate energies we observe an angular Lévy-walk type motion associated with a fractional diffusion coefficient interpolating between the two regimes.

How Fast Can Networks Synchronize? A Random Matrix Theory Approach

NASA Astrophysics Data System (ADS)

Timme, Marc; Wolf, Fred; Geisel, Theo

2004-03-01

Pulse-coupled oscillators constitute a paradigmatic class of dynamical systems interacting on networks because they model a variety of biological systems including flashing fireflies and chirping crickets as well as pacemaker cells of the heart and neural networks. Synchronization is one of the most simple and most prevailing kinds of collective dynamics on such networks. Here we study collective synchronization [1] of pulse-coupled oscillators interacting on asymmetric random networks. Using random matrix theory we analytically determine the speed of synchronization in such networks in dependence on the dynamical and network parameters [2]. The speed of synchronization increases with increasing coupling strengths. Surprisingly, however, it stays finite even for infinitely strong interactions. The results indicate that the speed of synchronization is limited by the connectivity of the network. We discuss the relevance of our findings to general equilibration processes on complex networks. [5mm] [1] M. Timme, F. Wolf, T. Geisel, Phys. Rev. Lett. 89:258701 (2002). [2] M. Timme, F. Wolf, T. Geisel, cond-mat/0306512 (2003).

Dynamical traps in Wang-Landau sampling of continuous systems: Mechanism and solution

NASA Astrophysics Data System (ADS)

Koh, Yang Wei; Sim, Adelene Y. L.; Lee, Hwee Kuan

2015-08-01

We study the mechanism behind dynamical trappings experienced during Wang-Landau sampling of continuous systems reported by several authors. Trapping is caused by the random walker coming close to a local energy extremum, although the mechanism is different from that of the critical slowing-down encountered in conventional molecular dynamics or Monte Carlo simulations. When trapped, the random walker misses the entire or even several stages of Wang-Landau modification factor reduction, leading to inadequate sampling of the configuration space and a rough density of states, even though the modification factor has been reduced to very small values. Trapping is dependent on specific systems, the choice of energy bins, and the Monte Carlo step size, making it highly unpredictable. A general, simple, and effective solution is proposed where the configurations of multiple parallel Wang-Landau trajectories are interswapped to prevent trapping. We also explain why swapping frees the random walker from such traps. The efficacy of the proposed algorithm is demonstrated.

Generic dynamical features of quenched interacting quantum systems: Survival probability, density imbalance, and out-of-time-ordered correlator

NASA Astrophysics Data System (ADS)

Torres-Herrera, E. J.; García-García, Antonio M.; Santos, Lea F.

2018-02-01

We study numerically and analytically the quench dynamics of isolated many-body quantum systems. Using full random matrices from the Gaussian orthogonal ensemble, we obtain analytical expressions for the evolution of the survival probability, density imbalance, and out-of-time-ordered correlator. They are compared with numerical results for a one-dimensional-disordered model with two-body interactions and shown to bound the decay rate of this realistic system. Power-law decays are seen at intermediate times, and dips below the infinite time averages (correlation holes) occur at long times for all three quantities when the system exhibits level repulsion. The fact that these features are shared by both the random matrix and the realistic disordered model indicates that they are generic to nonintegrable interacting quantum systems out of equilibrium. Assisted by the random matrix analytical results, we propose expressions that describe extremely well the dynamics of the realistic chaotic system at different time scales.

Dynamic assessment of urban economy-environment-energy system using system dynamics model: A case study in Beijing.

PubMed

Wu, Desheng; Ning, Shuang

2018-07-01

Economic development, accompanying with environmental damage and energy depletion, becomes essential nowadays. There is a complicated and comprehensive interaction between economics, environment and energy. Understanding the operating mechanism of Energy-Environment-Economy model (3E) and its key factors is the inherent part in dealing with the issue. In this paper, we combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. Beijing is selected as a case study to verify our SD-GIS model. Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Policy-making insights are given based on our results and analysis. Copyright © 2018 Elsevier Inc. All rights reserved.

Experimental Evaluation Methodology for Spacecraft Proximity Maneuvers in a Dynamic Environment

DTIC Science & Technology

2017-06-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA DISSERTATION EXPERIMENTAL EVALUATION METHODOLOGY FOR SPACECRAFT PROXIMITY MANEUVERS IN A DYNAMIC...29, 2014 – June 16, 2017 4. TITLE AND SUBTITLE EXPERIMENTAL EVALUATION METHODOLOGY FOR SPACECRAFT PROXIMITY MANEUVERS IN A DYNAMIC ENVIRONMENT 5...LEFT BLANK ii Approved for public release. Distribution is unlimited. EXPERIMENTAL EVALUATION METHODOLOGY FOR SPACECRAFT PROXIMITY MANEUVERS IN A