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

PubMed

Truccolo, Wilson

2016-11-01

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

Stochastic thermodynamics across scales: Emergent inter-attractoral discrete Markov jump process and its underlying continuous diffusion

NASA Astrophysics Data System (ADS)

Santillán, Moisés; Qian, Hong

2013-01-01

We investigate the internal consistency of a recently developed mathematical thermodynamic structure across scales, between a continuous stochastic nonlinear dynamical system, i.e., a diffusion process with Langevin and Fokker-Planck equations, and its emergent discrete, inter-attractoral Markov jump process. We analyze how the system’s thermodynamic state functions, e.g. free energy F, entropy S, entropy production ep, free energy dissipation Ḟ, etc., are related when the continuous system is described with coarse-grained discrete variables. It is shown that the thermodynamics derived from the underlying, detailed continuous dynamics gives rise to exactly the free-energy representation of Gibbs and Helmholtz. That is, the system’s thermodynamic structure is the same as if one only takes a middle road and starts with the natural discrete description, with the corresponding transition rates empirically determined. By natural we mean in the thermodynamic limit of a large system, with an inherent separation of time scales between inter- and intra-attractoral dynamics. This result generalizes a fundamental idea from chemistry, and the theory of Kramers, by incorporating thermodynamics: while a mechanical description of a molecule is in terms of continuous bond lengths and angles, chemical reactions are phenomenologically described by a discrete representation, in terms of exponential rate laws and a stochastic thermodynamics.

Risk-Sensitive Control of Pure Jump Process on Countable Space with Near Monotone Cost

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

Suresh Kumar, K., E-mail: suresh@math.iitb.ac.in; Pal, Chandan, E-mail: cpal@math.iitb.ac.in

2013-12-15

In this article, we study risk-sensitive control problem with controlled continuous time pure jump process on a countable space as state dynamics. We prove multiplicative dynamic programming principle, elliptic and parabolic Harnack’s inequalities. Using the multiplicative dynamic programing principle and the Harnack’s inequalities, we prove the existence and a characterization of optimal risk-sensitive control under the near monotone condition.

Evaluation of interaction dynamics of concurrent processes

NASA Astrophysics Data System (ADS)

Sobecki, Piotr; Białasiewicz, Jan T.; Gross, Nicholas

2017-03-01

The purpose of this paper is to present the wavelet tools that enable the detection of temporal interactions of concurrent processes. In particular, the determination of interaction coherence of time-varying signals is achieved using a complex continuous wavelet transform. This paper has used electrocardiogram (ECG) and seismocardiogram (SCG) data set to show multiple continuous wavelet analysis techniques based on Morlet wavelet transform. MATLAB Graphical User Interface (GUI), developed in the reported research to assist in quick and simple data analysis, is presented. These software tools can discover the interaction dynamics of time-varying signals, hence they can reveal their correlation in phase and amplitude, as well as their non-linear interconnections. The user-friendly MATLAB GUI enables effective use of the developed software what enables to load two processes under investigation, make choice of the required processing parameters, and then perform the analysis. The software developed is a useful tool for researchers who have a need for investigation of interaction dynamics of concurrent processes.

A Dynamical System Approach Explaining the Process of Development by Introducing Different Time-scales.

PubMed

Hashemi Kamangar, Somayeh Sadat; Moradimanesh, Zahra; Mokhtari, Setareh; Bakouie, Fatemeh

2018-06-11

A developmental process can be described as changes through time within a complex dynamic system. The self-organized changes and emergent behaviour during development can be described and modeled as a dynamical system. We propose a dynamical system approach to answer the main question in human cognitive development i.e. the changes during development happens continuously or in discontinuous stages. Within this approach there is a concept; the size of time scales, which can be used to address the aforementioned question. We introduce a framework, by considering the concept of time-scale, in which "fast" and "slow" is defined by the size of time-scales. According to our suggested model, the overall pattern of development can be seen as one continuous function, with different time-scales in different time intervals.

Fixation, transient landscape, and diffusion dilemma in stochastic evolutionary game dynamics

NASA Astrophysics Data System (ADS)

Zhou, Da; Qian, Hong

2011-09-01

Agent-based stochastic models for finite populations have recently received much attention in the game theory of evolutionary dynamics. Both the ultimate fixation and the pre-fixation transient behavior are important to a full understanding of the dynamics. In this paper, we study the transient dynamics of the well-mixed Moran process through constructing a landscape function. It is shown that the landscape playing a central theoretical “device” that integrates several lines of inquiries: the stable behavior of the replicator dynamics, the long-time fixation, and continuous diffusion approximation associated with asymptotically large population. Several issues relating to the transient dynamics are discussed: (i) multiple time scales phenomenon associated with intra- and inter-attractoral dynamics; (ii) discontinuous transition in stochastically stationary process akin to Maxwell construction in equilibrium statistical physics; and (iii) the dilemma diffusion approximation facing as a continuous approximation of the discrete evolutionary dynamics. It is found that rare events with exponentially small probabilities, corresponding to the uphill movements and barrier crossing in the landscape with multiple wells that are made possible by strong nonlinear dynamics, plays an important role in understanding the origin of the complexity in evolutionary, nonlinear biological systems.

A Dynamic Interactive Theory of Person Construal

ERIC Educational Resources Information Center

Freeman, Jonathan B.; Ambady, Nalini

2011-01-01

A dynamic interactive theory of person construal is proposed. It assumes that the perception of other people is accomplished by a dynamical system involving continuous interaction between social categories, stereotypes, high-level cognitive states, and the low-level processing of facial, vocal, and bodily cues. This system permits lower-level…

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

USGS Publications Warehouse

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

2004-01-01

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

Dynamic Programming for Structured Continuous Markov Decision Problems

NASA Technical Reports Server (NTRS)

Dearden, Richard; Meuleau, Nicholas; Washington, Richard; Feng, Zhengzhu

2004-01-01

We describe an approach for exploiting structure in Markov Decision Processes with continuous state variables. At each step of the dynamic programming, the state space is dynamically partitioned into regions where the value function is the same throughout the region. We first describe the algorithm for piecewise constant representations. We then extend it to piecewise linear representations, using techniques from POMDPs to represent and reason about linear surfaces efficiently. We show that for complex, structured problems, our approach exploits the natural structure so that optimal solutions can be computed efficiently.

Continuous functional magnetic resonance imaging reveals dynamic nonlinearities of "dose-response" curves for finger opposition.

PubMed

Berns, G S; Song, A W; Mao, H

1999-07-15

Linear experimental designs have dominated the field of functional neuroimaging, but although successful at mapping regions of relative brain activation, the technique assumes that both cognition and brain activation are linear processes. To test these assumptions, we performed a continuous functional magnetic resonance imaging (MRI) experiment of finger opposition. Subjects performed a visually paced bimanual finger-tapping task. The frequency of finger tapping was continuously varied between 1 and 5 Hz, without any rest blocks. After continuous acquisition of fMRI images, the task-related brain regions were identified with independent components analysis (ICA). When the time courses of the task-related components were plotted against tapping frequency, nonlinear "dose- response" curves were obtained for most subjects. Nonlinearities appeared in both the static and dynamic sense, with hysteresis being prominent in several subjects. The ICA decomposition also demonstrated the spatial dynamics with different components active at different times. These results suggest that the brain response to tapping frequency does not scale linearly, and that it is history-dependent even after accounting for the hemodynamic response function. This implies that finger tapping, as measured with fMRI, is a nonstationary process. When analyzed with a conventional general linear model, a strong correlation to tapping frequency was identified, but the spatiotemporal dynamics were not apparent.

Nonequilibrium thermodynamic potentials for continuous-time Markov chains.

PubMed

Verley, Gatien

2016-01-01

We connect the rare fluctuations of an equilibrium (EQ) process and the typical fluctuations of a nonequilibrium (NE) stationary process. In the framework of large deviation theory, this observation allows us to introduce NE thermodynamic potentials. For continuous-time Markov chains, we identify the relevant pairs of conjugated variables and propose two NE ensembles: one with fixed dynamics and fluctuating time-averaged variables, and another with fixed time-averaged variables, but a fluctuating dynamics. Accordingly, we show that NE processes are equivalent to conditioned EQ processes ensuring that NE potentials are Legendre dual. We find a variational principle satisfied by the NE potentials that reach their maximum in the NE stationary state and whose first derivatives produce the NE equations of state and second derivatives produce the NE Maxwell relations generalizing the Onsager reciprocity relations.

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.

Studies on Manfred Eigen's model for the self-organization of information processing.

PubMed

Ebeling, W; Feistel, R

2018-05-01

In 1971, Manfred Eigen extended the principles of Darwinian evolution to chemical processes, from catalytic networks to the emergence of information processing at the molecular level, leading to the emergence of life. In this paper, we investigate some very general characteristics of this scenario, such as the valuation process of phenotypic traits in a high-dimensional fitness landscape, the effect of spatial compartmentation on the valuation, and the self-organized transition from structural to symbolic genetic information of replicating chain molecules. In the first part, we perform an analysis of typical dynamical properties of continuous dynamical models of evolutionary processes. In particular, we study the mapping of genotype to continuous phenotype spaces following the ideas of Wright and Conrad. We investigate typical features of a Schrödinger-like dynamics, the consequences of the high dimensionality, the leading role of saddle points, and Conrad's extra-dimensional bypass. In the last part, we discuss in brief the valuation of compartment models and the self-organized emergence of molecular symbols at the beginning of life.

A Buoy for Continuous Monitoring of Suspended Sediment Dynamics

PubMed Central

Mueller, Philip; Thoss, Heiko; Kaempf, Lucas; Güntner, Andreas

2013-01-01

Knowledge of Suspended Sediments Dynamics (SSD) across spatial scales is relevant for several fields of hydrology, such as eco-hydrological processes, the operation of hydrotechnical facilities and research on varved lake sediments as geoarchives. Understanding the connectivity of sediment flux between source areas in a catchment and sink areas in lakes or reservoirs is of primary importance to these fields. Lacustrine sediments may serve as a valuable expansion of instrumental hydrological records for flood frequencies and magnitudes, but depositional processes and detrital layer formation in lakes are not yet fully understood. This study presents a novel buoy system designed to continuously measure suspended sediment concentration and relevant boundary conditions at a high spatial and temporal resolution in surface water bodies. The buoy sensors continuously record turbidity as an indirect measure of suspended sediment concentrations, water temperature and electrical conductivity at up to nine different water depths. Acoustic Doppler current meters and profilers measure current velocities along a vertical profile from the water surface to the lake bottom. Meteorological sensors capture the atmospheric boundary conditions as main drivers of lake dynamics. It is the high spatial resolution of multi-point turbidity measurements, the dual-sensor velocity measurements and the temporally synchronous recording of all sensors along the water column that sets the system apart from existing buoy systems. Buoy data collected during a 4-month field campaign in Lake Mondsee demonstrate the potential and effectiveness of the system in monitoring suspended sediment dynamics. Observations were related to stratification and mixing processes in the lake and increased turbidity close to a catchment outlet during flood events. The rugged buoy design assures continuous operation in terms of stability, energy management and sensor logging throughout the study period. We conclude that the buoy is a suitable tool for continuous monitoring of suspended sediment concentrations and general dynamics in fresh water bodies. PMID:24129017

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

Zitney, S.E.

This presentation will examine process systems engineering R&D needs for application to advanced fossil energy (FE) systems and highlight ongoing research activities at the National Energy Technology Laboratory (NETL) under the auspices of a recently launched Collaboratory for Process & Dynamic Systems Research. The three current technology focus areas include: 1) High-fidelity systems with NETL's award-winning Advanced Process Engineering Co-Simulator (APECS) technology for integrating process simulation with computational fluid dynamics (CFD) and virtual engineering concepts, 2) Dynamic systems with R&D on plant-wide IGCC dynamic simulation, control, and real-time training applications, and 3) Systems optimization including large-scale process optimization, stochastic simulationmore » for risk/uncertainty analysis, and cost estimation. Continued R&D aimed at these and other key process systems engineering models, methods, and tools will accelerate the development of advanced gasification-based FE systems and produce increasingly valuable outcomes for DOE and the Nation.« less

Dynamics of Quantum Causal Structures

NASA Astrophysics Data System (ADS)

Castro-Ruiz, Esteban; Giacomini, Flaminia; Brukner, Časlav

2018-01-01

It was recently suggested that causal structures are both dynamical, because of general relativity, and indefinite, because of quantum theory. The process matrix formalism furnishes a framework for quantum mechanics on indefinite causal structures, where the order between operations of local laboratories is not definite (e.g., one cannot say whether operation in laboratory A occurs before or after operation in laboratory B ). Here, we develop a framework for "dynamics of causal structures," i.e., for transformations of process matrices into process matrices. We show that, under continuous and reversible transformations, the causal order between operations is always preserved. However, the causal order between a subset of operations can be changed under continuous yet nonreversible transformations. An explicit example is that of the quantum switch, where a party in the past affects the causal order of operations of future parties, leading to a transition from a channel from A to B , via superposition of causal orders, to a channel from B to A . We generalize our framework to construct a hierarchy of quantum maps based on transformations of process matrices and transformations thereof.

The optimization of essential oils supercritical CO2 extraction from Lavandula hybrida through static-dynamic steps procedure and semi-continuous technique using response surface method

PubMed Central

Kamali, Hossein; Aminimoghadamfarouj, Noushin; Golmakani, Ebrahim; Nematollahi, Alireza

2015-01-01

Aim: The aim of this study was to examine and evaluate crucial variables in essential oils extraction process from Lavandula hybrida through static-dynamic and semi-continuous techniques using response surface method. Materials and Methods: Essential oil components were extracted from Lavandula hybrida (Lavandin) flowers using supercritical carbon dioxide via static-dynamic steps (SDS) procedure, and semi-continuous (SC) technique. Results: Using response surface method the optimum extraction yield (4.768%) was obtained via SDS at 108.7 bar, 48.5°C, 120 min (static: 8×15), 24 min (dynamic: 8×3 min) in contrast to the 4.620% extraction yield for the SC at 111.6 bar, 49.2°C, 14 min (static), 121.1 min (dynamic). Conclusion: The results indicated that a substantial reduction (81.56%) solvent usage (kg CO2/g oil) is observed in the SDS method versus the conventional SC method. PMID:25598636

Mitochondrial Dynamics in Mitochondrial Diseases

PubMed Central

Suárez-Rivero, Juan M.; Villanueva-Paz, Marina; de la Cruz-Ojeda, Patricia; de la Mata, Mario; Cotán, David; Oropesa-Ávila, Manuel; de Lavera, Isabel; Álvarez-Córdoba, Mónica; Luzón-Hidalgo, Raquel; Sánchez-Alcázar, José A.

2016-01-01

Mitochondria are very versatile organelles in continuous fusion and fission processes in response to various cellular signals. Mitochondrial dynamics, including mitochondrial fission/fusion, movements and turnover, are essential for the mitochondrial network quality control. Alterations in mitochondrial dynamics can cause neuropathies such as Charcot-Marie-Tooth disease in which mitochondrial fusion and transport are impaired, or dominant optic atrophy which is caused by a reduced mitochondrial fusion. On the other hand, mitochondrial dysfunction in primary mitochondrial diseases promotes reactive oxygen species production that impairs its own function and dynamics, causing a continuous vicious cycle that aggravates the pathological phenotype. Mitochondrial dynamics provides a new way to understand the pathophysiology of mitochondrial disorders and other diseases related to mitochondria dysfunction such as diabetes, heart failure, or Hungtinton’s disease. The knowledge about mitochondrial dynamics also offers new therapeutics targets in mitochondrial diseases. PMID:28933354

How interactions between animal movement and landscape processes modify range dynamics and extinction risk

EPA Science Inventory

Range dynamics models now incorporate many of the mechanisms and interactions that drive species distributions. However, connectivity continues to be studied using overly simple distance-based dispersal models with little consideration of how the individual behavior of dispersin...

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

Chen, Hang, E-mail: hangchen@mit.edu; Thill, Peter; Cao, Jianshu

In biochemical systems, intrinsic noise may drive the system switch from one stable state to another. We investigate how kinetic switching between stable states in a bistable network is influenced by dynamic disorder, i.e., fluctuations in the rate coefficients. Using the geometric minimum action method, we first investigate the optimal transition paths and the corresponding minimum actions based on a genetic toggle switch model in which reaction coefficients draw from a discrete probability distribution. For the continuous probability distribution of the rate coefficient, we then consider two models of dynamic disorder in which reaction coefficients undergo different stochastic processes withmore » the same stationary distribution. In one, the kinetic parameters follow a discrete Markov process and in the other they follow continuous Langevin dynamics. We find that regulation of the parameters modulating the dynamic disorder, as has been demonstrated to occur through allosteric control in bistable networks in the immune system, can be crucial in shaping the statistics of optimal transition paths, transition probabilities, and the stationary probability distribution of the network.« less

A hybrid-system model of the coagulation cascade: simulation, sensitivity, and validation.

PubMed

Makin, Joseph G; Narayanan, Srini

2013-10-01

The process of human blood clotting involves a complex interaction of continuous-time/continuous-state processes and discrete-event/discrete-state phenomena, where the former comprise the various chemical rate equations and the latter comprise both threshold-limited behaviors and binary states (presence/absence of a chemical). Whereas previous blood-clotting models used only continuous dynamics and perforce addressed only portions of the coagulation cascade, we capture both continuous and discrete aspects by modeling it as a hybrid dynamical system. The model was implemented as a hybrid Petri net, a graphical modeling language that extends ordinary Petri nets to cover continuous quantities and continuous-time flows. The primary focus is simulation: (1) fidelity to the clinical data in terms of clotting-factor concentrations and elapsed time; (2) reproduction of known clotting pathologies; and (3) fine-grained predictions which may be used to refine clinical understanding of blood clotting. Next we examine sensitivity to rate-constant perturbation. Finally, we propose a method for titrating between reliance on the model and on prior clinical knowledge. For simplicity, we confine these last two analyses to a critical purely-continuous subsystem of the model.

Ergodicity convergence test suggests telomere motion obeys fractional dynamics

NASA Astrophysics Data System (ADS)

Kepten, E.; Bronshtein, I.; Garini, Y.

2011-04-01

Anomalous diffusion, observed in many biological processes, is a generalized description of a wide variety of processes, all obeying the same law of mean-square displacement. Identifying the basic mechanisms of these observations is important for deducing the nature of the biophysical systems measured. We implement a previously suggested method for distinguishing between fractional Langevin dynamics, fractional Brownian motion, and continuous time random walk based on the ergodic nature of the data. We apply the method together with the recently suggested P-variation test and the displacement correlation to the lately measured dynamics of telomeres in the nucleus of mammalian cells and find strong evidence that the telomeres motion obeys fractional dynamics. The ergodic dynamics are observed experimentally to fit fractional Brownian or Langevin dynamics.

Context-Aware Design for Process Flexibility and Adaptation

ERIC Educational Resources Information Center

Yao, Wen

2012-01-01

Today's organizations face continuous and unprecedented changes in their business environment. Traditional process design tools tend to be inflexible and can only support rigidly defined processes (e.g., order processing in the supply chain). This considerably restricts their real-world applications value, especially in the dynamic and…

Continuous monitoring bed-level dynamics on an intertidal flat: introducing novel stand-alone high-resolution SED-sensors

NASA Astrophysics Data System (ADS)

Hu, Zhan; Lenting, Walther; van der Wal, Daphne; Bouma, Tjeerd

2015-04-01

Tidal flat morphology is continuously shaped by hydrodynamic force, resulting in highly dynamic bed elevations. The knowledge of short-term bed-level changes is important both for understanding sediment transport processes as well as for assessing critical ecological processes such as e.g. vegetation recruitment chances on tidal flats. Due to the labour involved, manual discontinuous measurements lack the ability to continuously monitor bed-elevation changes. Existing methods for automated continuous monitoring of bed-level changes lack vertical accuracy (e.g., Photo-Electronic Erosion Pin sensor and resistive rod) or limited in spatial application by using expensive technology (e.g., acoustic bed level sensors). A method provides sufficient accuracy with a reasonable cost is needed. In light of this, a high-accuracy sensor (2 mm) for continuously measuring short-term Surface-Elevation Dynamics (SED-sensor) was developed. This SED-sensor makes use of photovoltaic cells and operates stand-alone using internal power supply and data logging system. The unit cost and the labour in deployments is therefore reduced, which facilitates monitoring with a number of units. In this study, the performance of a group of SED-sensors is tested against data obtained with precise manual measurements using traditional Sediment Erosion Bars (SEB). An excellent agreement between the two methods was obtained, indicating the accuracy and precision of the SED-sensors. Furthermore, to demonstrate how the SED-sensors can be used for measuring short-term bed-level dynamics, two SED-sensors were deployed for 1 month at two sites with contrasting wave exposure conditions. Daily bed-level changes were obtained including a severe storm erosion event. The difference in observed bed-level dynamics at both sites was statistically explained by their different hydrodynamic conditions. Thus, the stand-alone SED-sensor can be applied to monitor sediment surface dynamics with high vertical and temporal resolutions, which provides opportunities to pinpoint morphological responses to various forces in a number of environments (e.g. tidal flats, beaches, rivers and dunes).

Stochastic optimal control of ultradiffusion processes with application to dynamic portfolio management

NASA Astrophysics Data System (ADS)

Marcozzi, Michael D.

2008-12-01

We consider theoretical and approximation aspects of the stochastic optimal control of ultradiffusion processes in the context of a prototype model for the selling price of a European call option. Within a continuous-time framework, the dynamic management of a portfolio of assets is effected through continuous or point control, activation costs, and phase delay. The performance index is derived from the unique weak variational solution to the ultraparabolic Hamilton-Jacobi equation; the value function is the optimal realization of the performance index relative to all feasible portfolios. An approximation procedure based upon a temporal box scheme/finite element method is analyzed; numerical examples are presented in order to demonstrate the viability of the approach.

Design and Performance Analysis of a new Rotary Hydraulic Joint

NASA Astrophysics Data System (ADS)

Feng, Yong; Yang, Junhong; Shang, Jianzhong; Wang, Zhuo; Fang, Delei

2017-07-01

To improve the driving torque of the robots joint, a wobble plate hydraulic joint is proposed, and the structure and working principle are described. Then mathematical models of kinematics and dynamics was established. On the basis of this, dynamic simulation and characteristic analysis are carried out. Results show that the motion curve of the joint is continuous and the impact is small. Moreover the output torque of the joint characterized by simple structure and easy processing is large and can be rotated continuously.

Structured population dynamics: continuous size and discontinuous stage structures.

PubMed

Buffoni, Giuseppe; Pasquali, Sara

2007-04-01

A nonlinear stochastic model for the dynamics of a population with either a continuous size structure or a discontinuous stage structure is formulated in the Eulerian formalism. It takes into account dispersion effects due to stochastic variability of the development process of the individuals. The discrete equations of the numerical approximation are derived, and an analysis of the existence and stability of the equilibrium states is performed. An application to a copepod population is illustrated; numerical results of Eulerian and Lagrangian models are compared.

Molecular dynamics simulations investigating consecutive nucleation, solidification and grain growth in a twelve-million-atom Fe-system

NASA Astrophysics Data System (ADS)

Okita, Shin; Verestek, Wolfgang; Sakane, Shinji; Takaki, Tomohiro; Ohno, Munekazu; Shibuta, Yasushi

2017-09-01

Continuous processes of homogeneous nucleation, solidification and grain growth are spontaneously achieved from an undercooled iron melt without any phenomenological parameter in the molecular dynamics (MD) simulation with 12 million atoms. The nucleation rate at the critical temperature is directly estimated from the atomistic configuration by cluster analysis to be of the order of 1034 m-3 s-1. Moreover, time evolution of grain size distribution during grain growth is obtained by the combination of Voronoi and cluster analyses. The grain growth exponent is estimated to be around 0.3 from the geometric average of the grain size distribution. Comprehensive understanding of kinetic properties during continuous processes is achieved in the large-scale MD simulation by utilizing the high parallel efficiency of a graphics processing unit (GPU), which is shedding light on the fundamental aspects of production processes of materials from the atomistic viewpoint.

A Neural Dynamic Model Generates Descriptions of Object-Oriented Actions.

PubMed

Richter, Mathis; Lins, Jonas; Schöner, Gregor

2017-01-01

Describing actions entails that relations between objects are discovered. A pervasively neural account of this process requires that fundamental problems are solved: the neural pointer problem, the binding problem, and the problem of generating discrete processing steps from time-continuous neural processes. We present a prototypical solution to these problems in a neural dynamic model that comprises dynamic neural fields holding representations close to sensorimotor surfaces as well as dynamic neural nodes holding discrete, language-like representations. Making the connection between these two types of representations enables the model to describe actions as well as to perceptually ground movement phrases-all based on real visual input. We demonstrate how the dynamic neural processes autonomously generate the processing steps required to describe or ground object-oriented actions. By solving the fundamental problems of neural pointing, binding, and emergent discrete processing, the model may be a first but critical step toward a systematic neural processing account of higher cognition. Copyright © 2017 The Authors. Topics in Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.

Temporal Dynamics of Hypothesis Generation: The Influences of Data Serial Order, Data Consistency, and Elicitation Timing

PubMed Central

Lange, Nicholas D.; Thomas, Rick P.; Davelaar, Eddy J.

2012-01-01

The pre-decisional process of hypothesis generation is a ubiquitous cognitive faculty that we continually employ in an effort to understand our environment and thereby support appropriate judgments and decisions. Although we are beginning to understand the fundamental processes underlying hypothesis generation, little is known about how various temporal dynamics, inherent in real world generation tasks, influence the retrieval of hypotheses from long-term memory. This paper presents two experiments investigating three data acquisition dynamics in a simulated medical diagnosis task. The results indicate that the mere serial order of data, data consistency (with previously generated hypotheses), and mode of responding influence the hypothesis generation process. An extension of the HyGene computational model endowed with dynamic data acquisition processes is forwarded and explored to provide an account of the present data. PMID:22754547

Natural Length Scales Shape Liquid Phase Continuity in Unsaturated Flows

NASA Astrophysics Data System (ADS)

Assouline, S.; Lehmann, P. G.; Or, D.

2015-12-01

Unsaturated flows supporting soil evaporation and internal drainage play an important role in various hydrologic and climatic processes manifested at a wide range of scales. We study inherent natural length scales that govern these flow processes and constrain the spatial range of their representation by continuum models. These inherent length scales reflect interactions between intrinsic porous medium properties that affect liquid phase continuity, and the interplay among forces that drive and resist unsaturated flow. We have defined an intrinsic length scale for hydraulic continuity based on pore size distribution that controls soil evaporation dynamics (i.e., stage 1 to stage 2 transition). This simple metric may be used to delineate upper bounds for regional evaporative losses or the depth of soil-atmosphere interactions (in the absence of plants). A similar length scale governs the dynamics of internal redistribution towards attainment of field capacity, again through its effect on hydraulic continuity in the draining porous medium. The study provides a framework for guiding numerical and mathematical models for capillary flows across different scales considering the necessary conditions for coexistence of stationarity (REV), hydraulic continuity and intrinsic capillary gradients.

The Response Dynamics of Recognition Memory: Sensitivity and Bias

ERIC Educational Resources Information Center

Koop, Gregory J.; Criss, Amy H.

2016-01-01

Advances in theories of memory are hampered by insufficient metrics for measuring memory. The goal of this paper is to further the development of model-independent, sensitive empirical measures of the recognition decision process. We evaluate whether metrics from continuous mouse tracking, or response dynamics, uniquely identify response bias and…

Optical studies of dynamical processes in disordered materials

NASA Astrophysics Data System (ADS)

Yen, William M.

1990-12-01

The research continues to focus on the study of the structure and the dynamic behavior of insulating solids which can be activated optically. The physical processes which produce relaxation and energy transfer in the optical excited states were of particular interest. The studies were based principally on optical laser spectroscopic techniques which reveal a more detailed view of the materials of interest and which will ultimately lead to the development of more efficient optoelectronic materials.

Continued reduction and analysis of data from the Dynamics Explorer Plasma Wave Instrument

NASA Technical Reports Server (NTRS)

Gurnett, Donald A.; Weimer, Daniel R.

1994-01-01

The plasma wave instrument on the Dynamics Explorer 1 spacecraft provided measurements of the electric and magnetic components of plasma waves in the Earth's magnetosphere. Four receiver systems processed signals from five antennas. Sixty-seven theses, scientific papers and reports were prepared from the data generated. Data processing activities and techniques used to analyze the data are described and highlights of discoveries made and research undertaken are tabulated.

Modeling and Simulation of Metallurgical Process Based on Hybrid Petri Net

NASA Astrophysics Data System (ADS)

Ren, Yujuan; Bao, Hong

2016-11-01

In order to achieve the goals of energy saving and emission reduction of iron and steel enterprises, an increasing number of modeling and simulation technologies are used to research and analyse metallurgical production process. In this paper, the basic principle of Hybrid Petri net is used to model and analyse the Metallurgical Process. Firstly, the definition of Hybrid Petri Net System of Metallurgical Process (MPHPNS) and its modeling theory are proposed. Secondly, the model of MPHPNS based on material flow is constructed. The dynamic flow of materials and the real-time change of each technological state in metallurgical process are simulated vividly by using this model. The simulation process can implement interaction between the continuous event dynamic system and the discrete event dynamic system at the same level, and play a positive role in the production decision.

Spatial dynamics of thermokarst and thermo-erosion at lakes and ponds in North Siberia and Northwest Alaska using high-resolution remote sensing

NASA Astrophysics Data System (ADS)

Grosse, G.; Tillapaugh, M.; Romanovsky, V. E.; Walter, K. M.; Plug, L. J.

2008-12-01

Formation, growth, and drainage of thermokarst lakes in ice-rich permafrost deposits are important factors of landscape dynamics in extent Arctic lowlands. Monitoring of spatial and temporal dynamics of such lakes will allow an assessment of permafrost stability and enhance the capabilities for modelling and quantifying biogeochemical processes related to permafrost degradation in a warming Arctic. In this study we use high-resolution remote sensing and GIS to analyze the development of thermokarst lakes and ponds in two study regions in North Siberia and Northwest Alaska. The sites are 1) the Cherskii region in the Kolyma lowland (Siberia) and 2) the Kitluk River area on the northern Seward Peninsula (Alaska). Both regions are characterized by continuous permafrost, a highly dissected and dynamic thermokarst landscape, uplands of Late Pleistocene permafrost deposits with high excess ice contents, and a large total volume of permafrost-stored carbon. These ice-rich Yedoma or Yedoma-like deposits are highly vulnerable to permafrost degradation forced by climate warming or other surface disturbance. Time series of high- resolution imagery (aerial, Corona, Ikonos, Alos Prism) covering more than 50 years of lake dynamics allow detailed assessments of processes and spatial patterns of thermokarst lake expansion and drainage in continuous permafrost. Time series of high-resolution imagery (aerial, Corona, Ikonos, Alos Prism) covering more than 50 years of lake dynamics allow detailed assessments of processes and spatial patterns of thermokarst lake expansion and drainage in continuous permafrost. Processes identified include thaw slumping, wave undercutting of frozen sediments or peat blocks and subsequent mass wasting, thaw collapse of near-shore zones, sinkhole formation and ice-wedge tunnelling, and gully formation by thermo-erosion. We use GIS-based tools to relate the remote sensing results to field data (ground ice content, topography, lithology, and relative age of landscape units). Results exhibit a very dynamic lake environment at both sites strongly related to landscape history and past cryolithological development. Lake shore erosion rates reach values of more than 1 m per year over the 50 year observation period at some sites. Permafrost degradation processes are identified as a key driver of both lake expansion and drainage.

Adaptive hybrid simulations for multiscale stochastic reaction networks

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

Hepp, Benjamin; Gupta, Ankit; Khammash, Mustafa

2015-01-21

The probability distribution describing the state of a Stochastic Reaction Network (SRN) evolves according to the Chemical Master Equation (CME). It is common to estimate its solution using Monte Carlo methods such as the Stochastic Simulation Algorithm (SSA). In many cases, these simulations can take an impractical amount of computational time. Therefore, many methods have been developed that approximate sample paths of the underlying stochastic process and estimate the solution of the CME. A prominent class of these methods include hybrid methods that partition the set of species and the set of reactions into discrete and continuous subsets. Such amore » partition separates the dynamics into a discrete and a continuous part. Simulating such a stochastic process can be computationally much easier than simulating the exact discrete stochastic process with SSA. Moreover, the quasi-stationary assumption to approximate the dynamics of fast subnetworks can be applied for certain classes of networks. However, as the dynamics of a SRN evolves, these partitions may have to be adapted during the simulation. We develop a hybrid method that approximates the solution of a CME by automatically partitioning the reactions and species sets into discrete and continuous components and applying the quasi-stationary assumption on identifiable fast subnetworks. Our method does not require any user intervention and it adapts to exploit the changing timescale separation between reactions and/or changing magnitudes of copy-numbers of constituent species. We demonstrate the efficiency of the proposed method by considering examples from systems biology and showing that very good approximations to the exact probability distributions can be achieved in significantly less computational time. This is especially the case for systems with oscillatory dynamics, where the system dynamics change considerably throughout the time-period of interest.« less

Adaptive hybrid simulations for multiscale stochastic reaction networks.

PubMed

Hepp, Benjamin; Gupta, Ankit; Khammash, Mustafa

2015-01-21

The probability distribution describing the state of a Stochastic Reaction Network (SRN) evolves according to the Chemical Master Equation (CME). It is common to estimate its solution using Monte Carlo methods such as the Stochastic Simulation Algorithm (SSA). In many cases, these simulations can take an impractical amount of computational time. Therefore, many methods have been developed that approximate sample paths of the underlying stochastic process and estimate the solution of the CME. A prominent class of these methods include hybrid methods that partition the set of species and the set of reactions into discrete and continuous subsets. Such a partition separates the dynamics into a discrete and a continuous part. Simulating such a stochastic process can be computationally much easier than simulating the exact discrete stochastic process with SSA. Moreover, the quasi-stationary assumption to approximate the dynamics of fast subnetworks can be applied for certain classes of networks. However, as the dynamics of a SRN evolves, these partitions may have to be adapted during the simulation. We develop a hybrid method that approximates the solution of a CME by automatically partitioning the reactions and species sets into discrete and continuous components and applying the quasi-stationary assumption on identifiable fast subnetworks. Our method does not require any user intervention and it adapts to exploit the changing timescale separation between reactions and/or changing magnitudes of copy-numbers of constituent species. We demonstrate the efficiency of the proposed method by considering examples from systems biology and showing that very good approximations to the exact probability distributions can be achieved in significantly less computational time. This is especially the case for systems with oscillatory dynamics, where the system dynamics change considerably throughout the time-period of interest.

Dynamical mechanism of atrial fibrillation: A topological approach

NASA Astrophysics Data System (ADS)

Marcotte, Christopher D.; Grigoriev, Roman O.

2017-09-01

While spiral wave breakup has been implicated in the emergence of atrial fibrillation, its role in maintaining this complex type of cardiac arrhythmia is less clear. We used the Karma model of cardiac excitation to investigate the dynamical mechanisms that sustain atrial fibrillation once it has been established. The results of our numerical study show that spatiotemporally chaotic dynamics in this regime can be described as a dynamical equilibrium between topologically distinct types of transitions that increase or decrease the number of wavelets, in general agreement with the multiple wavelets' hypothesis. Surprisingly, we found that the process of continuous excitation waves breaking up into discontinuous pieces plays no role whatsoever in maintaining spatiotemporal complexity. Instead, this complexity is maintained as a dynamical balance between wave coalescence—a unique, previously unidentified, topological process that increases the number of wavelets—and wave collapse—a different topological process that decreases their number.

Modelling and simulation techniques for membrane biology.

PubMed

Burrage, Kevin; Hancock, John; Leier, André; Nicolau, Dan V

2007-07-01

One of the most important aspects of Computational Cell Biology is the understanding of the complicated dynamical processes that take place on plasma membranes. These processes are often so complicated that purely temporal models cannot always adequately capture the dynamics. On the other hand, spatial models can have large computational overheads. In this article, we review some of these issues with respect to chemistry, membrane microdomains and anomalous diffusion and discuss how to select appropriate modelling and simulation paradigms based on some or all the following aspects: discrete, continuous, stochastic, delayed and complex spatial processes.

Numerical continuation and bifurcation analysis in aircraft design: an industrial perspective.

PubMed

Sharma, Sanjiv; Coetzee, Etienne B; Lowenberg, Mark H; Neild, Simon A; Krauskopf, Bernd

2015-09-28

Bifurcation analysis is a powerful method for studying the steady-state nonlinear dynamics of systems. Software tools exist for the numerical continuation of steady-state solutions as parameters of the system are varied. These tools make it possible to generate 'maps of solutions' in an efficient way that provide valuable insight into the overall dynamic behaviour of a system and potentially to influence the design process. While this approach has been employed in the military aircraft control community to understand the effectiveness of controllers, the use of bifurcation analysis in the wider aircraft industry is yet limited. This paper reports progress on how bifurcation analysis can play a role as part of the design process for passenger aircraft. © 2015 The Author(s).

Dynamic pupillary exchange engages brain regions encoding social salience

PubMed Central

Harrison, Neil A.; Gray, Marcus A.; Critchley, Hugo D.

2008-01-01

Covert exchange of autonomic responses may shape social affective behavior, as observed in mirroring of pupillary responses during sadness processing. We examined how, independent of facial emotional expression, dynamic coherence between one's own and another's pupil size modulates regional brain activity. Fourteen subjects viewed pairs of eye stimuli while undergoing fMRI. Using continuous pupillometry biofeedback, the size of the observed pupils was varied, correlating positively or negatively with changes in participants’ own pupils. Viewing both static and dynamic stimuli activated right fusiform gyrus. Observing dynamically changing pupils activated STS and amygdala, regions engaged by non-static and salient facial features. Discordance between observed and observer's pupillary changes enhanced activity within bilateral anterior insula, left amygdala and anterior cingulate. In contrast, processing positively correlated pupils enhanced activity within left frontal operculum. Our findings suggest pupillary signals are monitored continuously during social interactions and that incongruent changes activate brain regions involved in tracking motivational salience and attentionally meaningful information. Naturalistically, dynamic coherence in pupillary change follows fluctuations in ambient light. Correspondingly, in social contexts discordant pupil response is likely to reflect divergence of dispositional state. Our data provide empirical evidence for an autonomically mediated extension of forward models of motor control into social interaction. PMID:19048432

A Decision Tool that Combines Discrete Event Software Process Models with System Dynamics Pieces for Software Development Cost Estimation and Analysis

NASA Technical Reports Server (NTRS)

Mizell, Carolyn Barrett; Malone, Linda

2007-01-01

The development process for a large software development project is very complex and dependent on many variables that are dynamic and interrelated. Factors such as size, productivity and defect injection rates will have substantial impact on the project in terms of cost and schedule. These factors can be affected by the intricacies of the process itself as well as human behavior because the process is very labor intensive. The complex nature of the development process can be investigated with software development process models that utilize discrete event simulation to analyze the effects of process changes. The organizational environment and its effects on the workforce can be analyzed with system dynamics that utilizes continuous simulation. Each has unique strengths and the benefits of both types can be exploited by combining a system dynamics model and a discrete event process model. This paper will demonstrate how the two types of models can be combined to investigate the impacts of human resource interactions on productivity and ultimately on cost and schedule.

Speed of feedforward and recurrent processing in multilayer networks of integrate-and-fire neurons.

PubMed

Panzeri, S; Rolls, E T; Battaglia, F; Lavis, R

2001-11-01

The speed of processing in the visual cortical areas can be fast, with for example the latency of neuronal responses increasing by only approximately 10 ms per area in the ventral visual system sequence V1 to V2 to V4 to inferior temporal visual cortex. This has led to the suggestion that rapid visual processing can only be based on the feedforward connections between cortical areas. To test this idea, we investigated the dynamics of information retrieval in multiple layer networks using a four-stage feedforward network modelled with continuous dynamics with integrate-and-fire neurons, and associative synaptic connections between stages with a synaptic time constant of 10 ms. Through the implementation of continuous dynamics, we found latency differences in information retrieval of only 5 ms per layer when local excitation was absent and processing was purely feedforward. However, information latency differences increased significantly when non-associative local excitation was included. We also found that local recurrent excitation through associatively modified synapses can contribute significantly to processing in as little as 15 ms per layer, including the feedforward and local feedback processing. Moreover, and in contrast to purely feed-forward processing, the contribution of local recurrent feedback was useful and approximately this rapid even when retrieval was made difficult by noise. These findings suggest that cortical information processing can benefit from recurrent circuits when the allowed processing time per cortical area is at least 15 ms long.

The co-development of looking dynamics and discrimination performance

PubMed Central

Perone, Sammy; Spencer, John P.

2015-01-01

The study of looking dynamics and discrimination form the backbone of developmental science and are central processes in theories of infant cognition. Looking dynamics and discrimination change dramatically across the first year of life. Surprisingly, developmental changes in looking and discrimination have not been studied together. Recent simulations of a dynamic neural field (DNF) model of infant looking and memory suggest that looking and discrimination do change together over development and arise from a single neurodevelopmental mechanism. We probe this claim by measuring looking dynamics and discrimination along continuous, metrically organized dimensions in 5-, 7, and 10-month-old infants (N = 119). The results showed that looking dynamics and discrimination changed together over development and are linked within individuals. Quantitative simulations of a DNF model provide insights into the processes that underlie developmental change in looking dynamics and discrimination. Simulation results support the view that these changes might arise from a single neurodevelopmental mechanism. PMID:23957821

Enhancing Student Learning of Enterprise Integration and Business Process Orientation through an ERP Business Simulation Game

ERIC Educational Resources Information Center

Seethamraju, Ravi

2011-01-01

The sophistication of the integrated world of work and increased recognition of business processes as critical corporate assets require graduates to develop "process orientation" and an "integrated view" of business. Responding to these dynamic changes in business organizations, business schools are also continuing to modify…

Evaluating competing forces constraining glacial grounding-line stability (Invited)

NASA Astrophysics Data System (ADS)

Powell, R. D.

2013-12-01

Stability of grounding lines of marine-terminating glaciers and ice sheets is of concern due to their importance in governing rates of ice mass loss and consequent sea level rise during global warming. Although processes are similar at tidewater and floating grounding zones their relative magnitudes in terms of their influence on grounding-line stability vary between these two end members. Processes considered Important for this discussion are ice dynamics, ice surface melting and crevassing, ocean dynamics, subglacial sediment and water dynamics, and subglacial bed geometries. Models have continued to improve in their representation of these complex interactions but reliable field measurements and data continue to be hard earned and too few to properly constrain the range of boundary conditions in this complicated system. Some data will be presented covering a range of regimes from Alaska, Svalbard and Antarctica. Certainly more data are required on subglacial sediment/water dynamics and fluxes to fully represent the spectrum of glacial regimes and to assess the significance of grounding-zone sediment systems in counteracting the other processes to force grounding-line stability. Especially important here is constraining the duration of the stability that could be maintained by sediment flux - present data appear to show that it is likely to be a limited period.

Age structure and cooperation in coevolutionary games on dynamic network

NASA Astrophysics Data System (ADS)

Qin, Zilong; Hu, Zhenhua; Zhou, Xiaoping; Yi, Jingzhang

2015-04-01

Our proposed model imitates the growth of a population and describes the age structure and the level of cooperation in games on dynamic network with continuous changes of structure and topology. The removal of nodes and links caused by age-dependent attack, together with the nodes addition standing for the newborns of population, badly ruins Matthew effect in this coevolutionary process. Though the network is generated by growth and preferential attachment, it degenerates into random network and it is no longer heterogeneous. When the removal of nodes and links is equal to the addition of nodes and links, the size of dynamic network is maintained in steady-state, so is the low level of cooperation. Severe structure variation, homogeneous topology and continuous invasion of new defection jointly make dynamic network unsuitable for the survival of cooperator even when the probability with which the newborn players initially adopt the strategy cooperation is high, while things change slightly when the connections of newborn players are restricted. Fortunately, moderate interactions in a generation trigger an optimal recovering process to encourage cooperation. The model developed in this paper outlines an explanation of the cohesion changes in the development process of an organization. Some suggestions for cooperative behavior improvement are given in the end.

A discrete in continuous mathematical model of cardiac progenitor cells formation and growth as spheroid clusters (Cardiospheres).

PubMed

Di Costanzo, Ezio; Giacomello, Alessandro; Messina, Elisa; Natalini, Roberto; Pontrelli, Giuseppe; Rossi, Fabrizio; Smits, Robert; Twarogowska, Monika

2018-03-14

We propose a discrete in continuous mathematical model describing the in vitro growth process of biophsy-derived mammalian cardiac progenitor cells growing as clusters in the form of spheres (Cardiospheres). The approach is hybrid: discrete at cellular scale and continuous at molecular level. In the present model, cells are subject to the self-organizing collective dynamics mechanism and, additionally, they can proliferate and differentiate, also depending on stochastic processes. The two latter processes are triggered and regulated by chemical signals present in the environment. Numerical simulations show the structure and the development of the clustered progenitors and are in a good agreement with the results obtained from in vitro experiments.

Non-Equlibrium Driven Dynamics of Continuous Attractors in Place Cell Networks

NASA Astrophysics Data System (ADS)

Zhong, Weishun; Kim, Hyun Jin; Schwab, David; Murugan, Arvind

Attractors have found much use in neuroscience as a means of information processing and decision making. Examples include associative memory with point and continuous attractors, spatial navigation and planning using place cell networks, dynamic pattern recognition among others. The functional use of such attractors requires the action of spatially and temporally varying external driving signals and yet, most theoretical work on attractors has been in the limit of small or no drive. We take steps towards understanding the non-equilibrium driven dynamics of continuous attractors in place cell networks. We establish an `equivalence principle' that relates fluctuations under a time-dependent external force to equilibrium fluctuations in a `co-moving' frame with only static forces, much like in Newtonian physics. Consequently, we analytically derive a network's capacity to encode multiple attractors as a function of the driving signal size and rate of change.

Modeling and Properties of Nonlinear Stochastic Dynamical System of Continuous Culture

NASA Astrophysics Data System (ADS)

Wang, Lei; Feng, Enmin; Ye, Jianxiong; Xiu, Zhilong

The stochastic counterpart to the deterministic description of continuous fermentation with ordinary differential equation is investigated in the process of glycerol bio-dissimilation to 1,3-propanediol by Klebsiella pneumoniae. We briefly discuss the continuous fermentation process driven by three-dimensional Brownian motion and Lipschitz coefficients, which is suitable for the factual fermentation. Subsequently, we study the existence and uniqueness of solutions for the stochastic system as well as the boundedness of the Two-order Moment and the Markov property of the solution. Finally stochastic simulation is carried out under the Stochastic Euler-Maruyama method.

Hybrid Cubature Kalman filtering for identifying nonlinear models from sampled recording: Estimation of neuronal dynamics.

PubMed

Madi, Mahmoud K; Karameh, Fadi N

2017-01-01

Kalman filtering methods have long been regarded as efficient adaptive Bayesian techniques for estimating hidden states in models of linear dynamical systems under Gaussian uncertainty. Recent advents of the Cubature Kalman filter (CKF) have extended this efficient estimation property to nonlinear systems, and also to hybrid nonlinear problems where by the processes are continuous and the observations are discrete (continuous-discrete CD-CKF). Employing CKF techniques, therefore, carries high promise for modeling many biological phenomena where the underlying processes exhibit inherently nonlinear, continuous, and noisy dynamics and the associated measurements are uncertain and time-sampled. This paper investigates the performance of cubature filtering (CKF and CD-CKF) in two flagship problems arising in the field of neuroscience upon relating brain functionality to aggregate neurophysiological recordings: (i) estimation of the firing dynamics and the neural circuit model parameters from electric potentials (EP) observations, and (ii) estimation of the hemodynamic model parameters and the underlying neural drive from BOLD (fMRI) signals. First, in simulated neural circuit models, estimation accuracy was investigated under varying levels of observation noise (SNR), process noise structures, and observation sampling intervals (dt). When compared to the CKF, the CD-CKF consistently exhibited better accuracy for a given SNR, sharp accuracy increase with higher SNR, and persistent error reduction with smaller dt. Remarkably, CD-CKF accuracy shows only a mild deterioration for non-Gaussian process noise, specifically with Poisson noise, a commonly assumed form of background fluctuations in neuronal systems. Second, in simulated hemodynamic models, parametric estimates were consistently improved under CD-CKF. Critically, time-localization of the underlying neural drive, a determinant factor in fMRI-based functional connectivity studies, was significantly more accurate under CD-CKF. In conclusion, and with the CKF recently benchmarked against other advanced Bayesian techniques, the CD-CKF framework could provide significant gains in robustness and accuracy when estimating a variety of biological phenomena models where the underlying process dynamics unfold at time scales faster than those seen in collected measurements.

Hybrid Cubature Kalman filtering for identifying nonlinear models from sampled recording: Estimation of neuronal dynamics

PubMed Central

2017-01-01

Kalman filtering methods have long been regarded as efficient adaptive Bayesian techniques for estimating hidden states in models of linear dynamical systems under Gaussian uncertainty. Recent advents of the Cubature Kalman filter (CKF) have extended this efficient estimation property to nonlinear systems, and also to hybrid nonlinear problems where by the processes are continuous and the observations are discrete (continuous-discrete CD-CKF). Employing CKF techniques, therefore, carries high promise for modeling many biological phenomena where the underlying processes exhibit inherently nonlinear, continuous, and noisy dynamics and the associated measurements are uncertain and time-sampled. This paper investigates the performance of cubature filtering (CKF and CD-CKF) in two flagship problems arising in the field of neuroscience upon relating brain functionality to aggregate neurophysiological recordings: (i) estimation of the firing dynamics and the neural circuit model parameters from electric potentials (EP) observations, and (ii) estimation of the hemodynamic model parameters and the underlying neural drive from BOLD (fMRI) signals. First, in simulated neural circuit models, estimation accuracy was investigated under varying levels of observation noise (SNR), process noise structures, and observation sampling intervals (dt). When compared to the CKF, the CD-CKF consistently exhibited better accuracy for a given SNR, sharp accuracy increase with higher SNR, and persistent error reduction with smaller dt. Remarkably, CD-CKF accuracy shows only a mild deterioration for non-Gaussian process noise, specifically with Poisson noise, a commonly assumed form of background fluctuations in neuronal systems. Second, in simulated hemodynamic models, parametric estimates were consistently improved under CD-CKF. Critically, time-localization of the underlying neural drive, a determinant factor in fMRI-based functional connectivity studies, was significantly more accurate under CD-CKF. In conclusion, and with the CKF recently benchmarked against other advanced Bayesian techniques, the CD-CKF framework could provide significant gains in robustness and accuracy when estimating a variety of biological phenomena models where the underlying process dynamics unfold at time scales faster than those seen in collected measurements. PMID:28727850

Nonlinear Dynamics in Viscoelastic Jets

NASA Astrophysics Data System (ADS)

Majmudar, Trushant; Varagnat, Matthieu; McKinley, Gareth

2008-11-01

Instabilities in free surface continuous jets of non-Newtonian fluids, although relevant for many industrial processes, remain poorly understood in terms of fundamental fluid dynamics. Inviscid, and viscous Newtonian jets have been studied in considerable detail, both theoretically and experimentally. Instability in viscous jets leads to regular periodic coiling of the jet, which exhibits a non-trivial frequency dependence with the height of the fall. Here we present a systematic study of the effect of viscoelasticity on the dynamics of continuous jets of worm-like micellar surfactant solutions of varying viscosities and elasticities. We observe complex nonlinear spatio-temporal dynamics of the jet, and uncover a transition from periodic to quasi-periodic to a multi-frequency, broad-spectrum dynamics. Beyond this regime, the jet dynamics smoothly crosses over to exhibit the ``leaping shampoo'' or the Kaye effect. We examine different dynamical regimes in terms of scaling variables, which depend on the geometry (dimensionless height), kinematics (dimensionless flow rate), and the fluid properties (elasto-gravity number) and present a regime map of the dynamics of the jet in terms of these dimensionless variables.

Nonlinear Dynamics in Viscoelastic Jets

NASA Astrophysics Data System (ADS)

Majmudar, Trushant; Varagnat, Matthieu; McKinley, Gareth

2009-03-01

Instabilities in free surface continuous jets of non-Newtonian fluids, although relevant for many industrial processes, remain poorly understood in terms of fundamental fluid dynamics. Inviscid, and viscous Newtonian jets have been studied in considerable detail, both theoretically and experimentally. Instability in viscous jets leads to regular periodic coiling of the jet, which exhibits a non-trivial frequency dependence with the height of the fall. Here we present a systematic study of the effect of viscoelasticity on the dynamics of continuous jets of worm-like micellar surfactant solutions of varying viscosities and elasticities. We observe complex nonlinear spatio-temporal dynamics of the jet, and uncover a transition from periodic to quasi-periodic to a multi-frequency, broad-spectrum dynamics. Beyond this regime, the jet dynamics smoothly crosses over to exhibit the ``leaping shampoo'' or the Kaye effect. We examine different dynamical regimes in terms of scaling variables, which depend on the geometry (dimensionless height), kinematics (dimensionless flow rate), and the fluid properties (elasto-gravity number) and present a regime map of the dynamics of the jet in terms of these dimensionless variables.

Dynamic deformation measurement and analysis of active stressed lap using optical method

NASA Astrophysics Data System (ADS)

Zhang, Qican; Su, Xianyu; Liu, Yuankun; Xiang, Liqun

2007-12-01

The active stressed lap is the heart of polishing process. A novel non-contact optical method of dynamic deformation measurement and analysis of an active stressed lap is put forward. This method, based on structured illumination, is able to record full-field information of the bending and rotating stressed lap dynamically and continuously, while its profile is changed under computer control, and restore the whole process of lap deformation varied with time at different position and rotating angle. It has been verified by experiments that this proposed method will be helpful to the opticians to ensure the stressed lap as expected.

Model-Based Prognostics of Hybrid Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil; Bregon, Anibal

2015-01-01

Model-based prognostics has become a popular approach to solving the prognostics problem. However, almost all work has focused on prognostics of systems with continuous dynamics. In this paper, we extend the model-based prognostics framework to hybrid systems models that combine both continuous and discrete dynamics. In general, most systems are hybrid in nature, including those that combine physical processes with software. We generalize the model-based prognostics formulation to hybrid systems, and describe the challenges involved. We present a general approach for modeling hybrid systems, and overview methods for solving estimation and prediction in hybrid systems. As a case study, we consider the problem of conflict (i.e., loss of separation) prediction in the National Airspace System, in which the aircraft models are hybrid dynamical systems.

Continuous monitoring the vehicle dynamics and driver behavior using navigation systems

NASA Astrophysics Data System (ADS)

Ene, George

2017-10-01

In all fields cost is very important and the increasing amount of data that are needed for active safety systems, like ADAS, lead to implementation of some complex and powerful unit for processing raw data. In this manner is necessary a cost-effective method to estimate the maximum available tire road friction during acceleration and braking by continuous monitoring the vehicle dynamics and driver behavior. The method is based on the hypothesis that short acceleration and braking periods can indicate vehicle dynamics, and thus the available tire road friction coefficient, and also human behavior and his limits. Support for this hypothesis is found in the literature and is supported by the result of experiments conducted under different conditions and seasons.

Dynamic Modeling of Yield and Particle Size Distribution in Continuous Bayer Precipitation

NASA Astrophysics Data System (ADS)

Stephenson, Jerry L.; Kapraun, Chris

Process engineers at Alcoa's Point Comfort refinery are using a dynamic model of the Bayer precipitation area to evaluate options in operating strategies. The dynamic model, a joint development effort between Point Comfort and the Alcoa Technical Center, predicts process yields, particle size distributions and occluded soda levels for various flowsheet configurations of the precipitation and classification circuit. In addition to rigorous heat, material and particle population balances, the model includes mechanistic kinetic expressions for particle growth and agglomeration and semi-empirical kinetics for nucleation and attrition. The kinetic parameters have been tuned to Point Comfort's operating data, with excellent matches between the model results and plant data. The model is written for the ACSL dynamic simulation program with specifically developed input/output graphical user interfaces to provide a user-friendly tool. Features such as a seed charge controller enhance the model's usefulness for evaluating operating conditions and process control approaches.

Derivation and computation of discrete-delay and continuous-delay SDEs in mathematical biology.

PubMed

Allen, Edward J

2014-06-01

Stochastic versions of several discrete-delay and continuous-delay differential equations, useful in mathematical biology, are derived from basic principles carefully taking into account the demographic, environmental, or physiological randomness in the dynamic processes. In particular, stochastic delay differential equation (SDDE) models are derived and studied for Nicholson's blowflies equation, Hutchinson's equation, an SIS epidemic model with delay, bacteria/phage dynamics, and glucose/insulin levels. Computational methods for approximating the SDDE models are described. Comparisons between computational solutions of the SDDEs and independently formulated Monte Carlo calculations support the accuracy of the derivations and of the computational methods.

Synthetic clock states generated in a Bose-Einstein condensate via continuous dynamical decoupling

NASA Astrophysics Data System (ADS)

Lundblad, Nathan; Trypogeorgos, Dimitrios; Valdes-Curiel, Ana; Marshall, Erin; Spielman, Ian

2017-04-01

Radiofrequency- or microwave-dressed states have been used in NV center and ion-trap experiments to extend coherence times, shielding qubits from magnetic field noise through a process known as continuous dynamical decoupling. Such field-insensitive dressed states, as applied in the context of ultracold neutral atoms, have applications related to the creation of novel phases of spin-orbit-coupled quantum matter. We present observations of such a protected dressed-state system in a Bose-Einstein condensate, including measurements of the dependence of the protection on rf coupling strength, and estimates of residual field sensitivities.

Worst error performance of continuous Kalman filters. [for deep space navigation and maneuvers

NASA Technical Reports Server (NTRS)

Nishimura, T.

1975-01-01

The worst error performance of estimation filters is investigated for continuous systems in this paper. The pathological performance study, without assuming any dynamical model such as Markov processes for perturbations, except for its bounded amplitude, will give practical and dependable criteria in establishing the navigation and maneuver strategy in deep space missions.

Exploring Population Admixture Dynamics via Empirical and Simulated Genome-wide Distribution of Ancestral Chromosomal Segments

PubMed Central

Jin, Wenfei; Wang, Sijia; Wang, Haifeng; Jin, Li; Xu, Shuhua

2012-01-01

The processes of genetic admixture determine the haplotype structure and linkage disequilibrium patterns of the admixed population, which is important for medical and evolutionary studies. However, most previous studies do not consider the inherent complexity of admixture processes. Here we proposed two approaches to explore population admixture dynamics, and we demonstrated, by analyzing genome-wide empirical and simulated data, that the approach based on the distribution of chromosomal segments of distinct ancestry (CSDAs) was more powerful than that based on the distribution of individual ancestry proportions. Analysis of 1,890 African Americans showed that a continuous gene flow model, in which the African American population continuously received gene flow from European populations over about 14 generations, best explained the admixture dynamics of African Americans among several putative models. Interestingly, we observed that some African Americans had much more European ancestry than the simulated samples, indicating substructures of local ancestries in African Americans that could have been caused by individuals from some particular lineages having repeatedly admixed with people of European ancestry. In contrast, the admixture dynamics of Mexicans could be explained by a gradual admixture model in which the Mexican population continuously received gene flow from both European and Amerindian populations over about 24 generations. Our results also indicated that recent gene flows from Sub-Saharan Africans have contributed to the gene pool of Middle Eastern populations such as Mozabite, Bedouin, and Palestinian. In summary, this study not only provides approaches to explore population admixture dynamics, but also advances our understanding on population history of African Americans, Mexicans, and Middle Eastern populations. PMID:23103229

Orodispersible films: Product transfer from lab-scale to continuous manufacturing.

PubMed

Thabet, Yasmin; Breitkreutz, Joerg

2018-01-15

Orodispersible films have been described as new beneficial dosage forms for special patient populations. Due to various production settings, different requirements on film formulations are required for non- continuous and continuous manufacturing. In this study, a continuous coating machine was qualified in regards of the process conditions for film compositions and their effects on the formed films. To investigate differences between both manufacturing processes, various film formulations of hydrochlorothiazide and hydroxypropylcellulose (HPC) or hydroxypropylmethycellulose (HPMC) as film formers were produced and the resulting films were characterized. The qualification of the continuously operating coating machine reveals no uniform heat distribution during drying. Coating solutions for continuous manufacturing should provide at least a dynamic viscosity of 1 Pa*s (wet film thickness of 500 μm, velocity of 15.9 cm/min). HPC films contain higher residuals of ethanol or acetone in bench-scale than in continuous production mode. Continuous production lead to lower drug content of the films. All continuously produced films disintegrate within less than 30 s. There are observed significant effects of the production process on the film characteristics. When transferring film manufacturing from lab-scale to continuous mode, film compositions, processing conditions and suitable characterization methods have to be carefully selected and adopted. Copyright © 2017 Elsevier B.V. All rights reserved.

Nonlinear stochastic exclusion financial dynamics modeling and time-dependent intrinsic detrended cross-correlation

NASA Astrophysics Data System (ADS)

Zhang, Wei; Wang, Jun

2017-09-01

In attempt to reproduce price dynamics of financial markets, a stochastic agent-based financial price model is proposed and investigated by stochastic exclusion process. The exclusion process, one of interacting particle systems, is usually thought of as modeling particle motion (with the conserved number of particles) in a continuous time Markov process. In this work, the process is utilized to imitate the trading interactions among the investing agents, in order to explain some stylized facts found in financial time series dynamics. To better understand the correlation behaviors of the proposed model, a new time-dependent intrinsic detrended cross-correlation (TDI-DCC) is introduced and performed, also, the autocorrelation analyses are applied in the empirical research. Furthermore, to verify the rationality of the financial price model, the actual return series are also considered to be comparatively studied with the simulation ones. The comparison results of return behaviors reveal that this financial price dynamics model can reproduce some correlation features of actual stock markets.

Glucans monomer-exchange dynamics as an open chemical network

NASA Astrophysics Data System (ADS)

Rao, Riccardo; Lacoste, David; Esposito, Massimiliano

2015-12-01

We describe the oligosaccharides-exchange dynamics performed by the so-called D-enzymes on polysaccharides. To mimic physiological conditions, we treat this process as an open chemical network by assuming some of the polymer concentrations fixed (chemostatting). We show that three different long-time behaviors may ensue: equilibrium states, nonequilibrium steady states, and continuous growth states. We dynamically and thermodynamically characterize these states and emphasize the crucial role of conservation laws in identifying the chemostatting conditions inducing them.

Glucans monomer-exchange dynamics as an open chemical network

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

Rao, Riccardo, E-mail: riccardo.rao@uni.lu; Esposito, Massimiliano, E-mail: massimiliano.esposito@uni.lu; Lacoste, David

2015-12-28

We describe the oligosaccharides-exchange dynamics performed by the so-called D-enzymes on polysaccharides. To mimic physiological conditions, we treat this process as an open chemical network by assuming some of the polymer concentrations fixed (chemostatting). We show that three different long-time behaviors may ensue: equilibrium states, nonequilibrium steady states, and continuous growth states. We dynamically and thermodynamically characterize these states and emphasize the crucial role of conservation laws in identifying the chemostatting conditions inducing them.

Analyzing Hedges in Verbal Communication: An Adaptation-Based Approach

ERIC Educational Resources Information Center

Wang, Yuling

2010-01-01

Based on Adaptation Theory, the article analyzes the production process of hedges. The procedure consists of the continuous making of choices in linguistic forms and communicative strategies. These choices are made just for adaptation to the contextual correlates. Besides, the adaptation process is dynamic, intentional and bidirectional.

Catalytic biofilms on structured packing for the production of glycolic acid.

PubMed

Li, Xuan Zhong; Hauer, Bernhard; Rosche, Bettina

2013-02-01

While structured packing modules are known to be efficient for surface wetting and gas-liquid exchange in abiotic surface catalysis, this model study explores structured packing as a growth surface for catalytic biofilms. Microbial biofilms have been proposed as self-immobilized and self-regenerating catalysts for the production of chemicals. A concern is that the complex and dynamic nature of biofilms may cause fluctuations in their catalytic performance over time or may affect process reproducibility. An aerated continuous trickle-bed biofilm reactor system was designed with a 3 L structured packing, liquid recycling and pH control. Pseudomonas diminuta established a biofilm on the stainless steel structured packing with a specific surface area of 500 m2 m-3 and catalyzed the oxidation of ethylene glycol to glycolic acid for over two months of continuous operation. A steady-state productivity of up to 1.6 gl-1h-1 was achieved at a dilution rate of 0.33 h-1. Process reproducibility between three independent runs was excellent, despite process interruptions and activity variations in cultures grown from biofilm effluent cells. The results demonstrate the robustness of a catalytic biofilm on structured packing, despite its dynamic nature. Implementation is recommended for whole-cell processes that require efficient gas-liquid exchange, catalyst retention for continuous operation, or improved catalyst stability.

Combination of CT scanning and fluoroscopy imaging on a flat-panel CT scanner

NASA Astrophysics Data System (ADS)

Grasruck, M.; Gupta, R.; Reichardt, B.; Suess, Ch.; Schmidt, B.; Stierstorfer, K.; Popescu, S.; Brady, T.; Flohr, T.

2006-03-01

We developed and evaluated a prototype flat-panel detector based Volume CT (fpVCT) scanner. The fpVCT scanner consists of a Varian 4030CB a-Si flat-panel detector mounted in a multi slice CT-gantry (Siemens Medical Solutions). It provides a 25 cm field of view with 18 cm z-coverage at the isocenter. In addition to the standard tomographic scanning, fpVCT allows two new scan modes: (1) fluoroscopic imaging from any arbitrary rotation angle, and (2) continuous, time-resolved tomographic scanning of a dynamically changing viewing volume. Fluoroscopic imaging is feasible by modifying the standard CT gantry so that the imaging chain can be oriented along any user-selected rotation angle. Scanning with a stationary gantry, after it has been oriented, is equivalent to a conventional fluoroscopic examination. This scan mode enables combined use of high-resolution tomography and real-time fluoroscopy with a clinically usable field of view in the z direction. The second scan mode allows continuous observation of a timeevolving process such as perfusion. The gantry can be continuously rotated for up to 80 sec, with the rotation time ranging from 3 to 20 sec, to gather projection images of a dynamic process. The projection data, that provides a temporal log of the viewing volume, is then converted into multiple image stacks that capture the temporal evolution of a dynamic process. Studies using phantoms, ex vivo specimens, and live animals have confirmed that these new scanning modes are clinically usable and offer a unique view of the anatomy and physiology that heretofore has not been feasible using static CT scanning. At the current level of image quality and temporal resolution, several clinical applications such a dynamic angiography, tumor enhancement pattern and vascularity studies, organ perfusion, and interventional applications are in reach.

Continuous catchment-scale monitoring of geomorphic processes with a 2-D seismological array

NASA Astrophysics Data System (ADS)

Burtin, A.; Hovius, N.; Milodowski, D.; Chen, Y.-G.; Wu, Y.-M.; Lin, C.-W.; Chen, H.

2012-04-01

The monitoring of geomorphic processes during extreme climatic events is of a primary interest to estimate their impact on the landscape dynamics. However, available techniques to survey the surface activity do not provide a relevant time and/or space resolution. Furthermore, these methods hardly investigate the dynamics of the events since their detection are made a posteriori. To increase our knowledge of the landscape evolution and the influence of extreme climatic events on a catchment dynamics, we need to develop new tools and procedures. In many past works, it has been shown that seismic signals are relevant to detect and locate surface processes (landslides, debris flows). During the 2010 typhoon season, we deployed a network of 12 seismometers dedicated to monitor the surface processes of the Chenyoulan catchment in Taiwan. We test the ability of a two dimensional array and small inter-stations distances (~ 11 km) to map in continuous and at a catchment-scale the geomorphic activity. The spectral analysis of continuous records shows a high-frequency (> 1 Hz) seismic energy that is coherent with the occurrence of hillslope and river processes. Using a basic detection algorithm and a location approach running on the analysis of seismic amplitudes, we manage to locate the catchment activity. We mainly observe short-time events (> 300 occurrences) associated with debris falls and bank collapses during daily convective storms, where 69% of occurrences are coherent with the time distribution of precipitations. We also identify a couple of debris flows during a large tropical storm. In contrast, the FORMOSAT imagery does not detect any activity, which somehow reflects the lack of extreme climatic conditions during the experiment. However, high resolution pictures confirm the existence of links between most of geomorphic events and existing structures (landslide scars, gullies...). We thus conclude to an activity that is dominated by reactivation processes. It highlights the major interest of a seismic monitoring since it allows a detailed spatial and temporal survey of events that classic approaches are not able to observe. In the future, dense two dimensional seismological arrays will assess in real-time the landscape dynamics of an entire catchment, tracking sediments from slopes to rivers.

Tracking Second Thoughts: Continuous and Discrete Revision Processes during Visual Lexical Decision

PubMed Central

Barca, Laura; Pezzulo, Giovanni

2015-01-01

We studied the dynamics of lexical decisions by asking participants to categorize lexical and nonlexical stimuli and recording their mouse movements toward response buttons during the choice. In a previous report we revealed greater trajectory curvature and attraction to competitors for Low Frequency words and Pseudowords. This analysis did not clarify whether the trajectory curvature in the two conditions was due to a continuous dynamic competition between the response alternatives or if a discrete revision process (a "change of mind") took place during the choice from an initially selected response to the opposite one. To disentangle these two possibilities, here we analyse the velocity and acceleration profiles of mouse movements during the choice. Pseudowords' peak movement velocity occurred with 100ms delay with respect to words and Letters Strings. Acceleration profile for High and Low Frequency words and Letters Strings exhibited a butterfly plot with one acceleration peak at 400ms and one deceleration peak at 650ms. Differently, Pseudowords' acceleration profile had double positive peaks (at 400 and 600ms) followed by movement deceleration, in correspondence with changes in the decision from lexical to nonlexical response buttons. These results speak to different online processes during the categorization of Low Frequency words and Pseudowords, with a continuous competition process for the former and a discrete revision process for the latter. PMID:25699992

Development of Continuum-Atomistic Approach for Modeling Metal Irradiation by Heavy Ions

NASA Astrophysics Data System (ADS)

Batgerel, Balt; Dimova, Stefka; Puzynin, Igor; Puzynina, Taisia; Hristov, Ivan; Hristova, Radoslava; Tukhliev, Zafar; Sharipov, Zarif

2018-02-01

Over the last several decades active research in the field of materials irradiation by high-energy heavy ions has been worked out. The experiments in this area are labor-consuming and expensive. Therefore the improvement of the existing mathematical models and the development of new ones based on the experimental data of interaction of high-energy heavy ions with materials are of interest. Presently, two approaches are used for studying these processes: a thermal spike model and molecular dynamics methods. The combination of these two approaches - the continuous-atomistic model - will give the opportunity to investigate more thoroughly the processes of irradiation of materials by high-energy heavy ions. To solve the equations of the continuous-atomistic model, a software package was developed and the block of molecular dynamics software was tested on the heterogeneous cluster HybriLIT.

Simulation of economic agents interaction in a trade chain

NASA Astrophysics Data System (ADS)

Gimanova, I. A.; Dulesov, A. S.; Litvin, N. V.

2017-01-01

The mathematical model of economic agents interaction is offered in the work. It allowsconsidering the change of price and sales volumesin dynamics according to the process of purchase and sale in the single-product market of the trade and intermediary network. The description of data-flow processes is based on the use of the continuous dynamic market model. The application of ordinary differential equations during the simulation allows one to define areas of coefficients - characteristics of agents - and to investigate their interaction in a chain on stability.

Higher Order Chemistry Models in the CFD Simulation of Laser-Ablated Carbon Plumes

NASA Technical Reports Server (NTRS)

Greendyke, R. B.; Creel, J. R.; Payne, B. T.; Scott, C. D.

2005-01-01

Production of single-walled carbon nanotubes (SWNT) has taken place for a number of years and by a variety of methods such as laser ablation, chemical vapor deposition, and arc-jet ablation. Yet, little is actually understood about the exact chemical kinetics and processes that occur in SWNT formation. In recent time, NASA Johnson Space Center has devoted a considerable effort to the experimental evaluation of the laser ablation production process for SWNT originally developed at Rice University. To fully understand the nature of the laser ablation process it is necessary to understand the development of the carbon plume dynamics within the laser ablation oven. The present work is a continuation of previous studies into the efforts to model plume dynamics using computational fluid dynamics (CFD). The ultimate goal of the work is to improve understanding of the laser ablation process, and through that improved understanding, refine the laser ablation production of SWNT.

A Complexity Theory Approach to Sustainability: A Longitudinal Study in Two London NHS Hospitals

ERIC Educational Resources Information Center

Mitleton-Kelly, Eve

2011-01-01

Purpose: The purpose of this paper is to demonstrate that organisational sustainability is not a continuation of the status quo but, seen from a complexity theory perspective, is a continuous dynamic process of co-evolution with a changing environment. It is underpinned by learning, and it creates new structures and ways of working to adjust and…

A variational method for analyzing limit cycle oscillations in stochastic hybrid systems

NASA Astrophysics Data System (ADS)

Bressloff, Paul C.; MacLaurin, James

2018-06-01

Many systems in biology can be modeled through ordinary differential equations, which are piece-wise continuous, and switch between different states according to a Markov jump process known as a stochastic hybrid system or piecewise deterministic Markov process (PDMP). In the fast switching limit, the dynamics converges to a deterministic ODE. In this paper, we develop a phase reduction method for stochastic hybrid systems that support a stable limit cycle in the deterministic limit. A classic example is the Morris-Lecar model of a neuron, where the switching Markov process is the number of open ion channels and the continuous process is the membrane voltage. We outline a variational principle for the phase reduction, yielding an exact analytic expression for the resulting phase dynamics. We demonstrate that this decomposition is accurate over timescales that are exponential in the switching rate ɛ-1 . That is, we show that for a constant C, the probability that the expected time to leave an O(a) neighborhood of the limit cycle is less than T scales as T exp (-C a /ɛ ) .

Implications of the spatial dynamics of fire spread for the bistability of savanna and forest.

PubMed

Schertzer, E; Staver, A C; Levin, S A

2015-01-01

The role of fire in expanding the global distribution of savanna is well recognized. Empirical observations and modeling suggest that fire spread has a threshold response to fuel-layer continuity, which sets up a positive feedback that maintains savanna-forest bistability. However, modeling has so far failed to examine fire spread as a spatial process that interacts with vegetation. Here, we use simple, well-supported assumptions about fire spread as an infection process and its effects on trees to ask whether spatial dynamics qualitatively change the potential for savanna-forest bistability. We show that the spatial effects of fire spread are the fundamental reason that bistability is possible: because fire spread is an infection process, it exhibits a threshold response to fuel continuity followed by a rapid increase in fire size. Other ecological processes affecting fire spread may also contribute including temporal variability in demography or fire spread. Finally, including the potential for spatial aggregation increases the potential both for savanna-forest bistability and for savanna and forest to coexist in a landscape mosaic.

[Intracranial pressure monitoring and CSF dynamics in patients with neurological disorders: indications and practical considerations].

PubMed

Poca, M; Sahuquillo, J

2001-01-01

The study of cerebrospinal fluid (CSF) dynamics is central to the diagnosis of adult chronic hydrocephalus (ACH). At present, many neurology and neurosurgery departments use one or more tests to guide diagnosis of this syndrome and to predict patient response to shunting. In specialised centres, the study of CSF dynamics is combined with continuous intracranial pressure (ICP) monitoring. Determination of several variables of CSF dynamics and definitions of qualitative and quantitative characteristics of ICP can be used to establish whether the hydrocephalus is active, compensated or arrested. CSF dynamics and ICP monitoring can also be used to check the correct functioning of the shunt and can be of use in the clinical management of patients with pseudotumor cerebri. Moreover, ICP monitoring is used to guide the treatment of several acute neurological processes. The aim of this review is to describe the fundamentals of CSF dynamics studies and the bases of continuous ICP monitoring. The advantages and disadvantages of several hydrodynamic tests that can be performed by lumbar puncture, as well as the normal and abnormal characteristics of an ICP recording, are discussed.

A new dynamic method for the rapid determination of the biodegradable dissolved organic carbon in drinking water.

PubMed

Ribas, F; Frias, J; Lucena, F

1991-10-01

A new method for the determination of biodegradable dissolved organic carbon (BDOC), which may be useful to the water industry, is proposed. It is a dynamic method that measures the BDOC of circulating water continuously pumped across a biofilm attached to a special support that fills a system of two glass columns. The BDOC value corresponds to the difference in DOC between inlet and outlet water samples. The sampling may be intermittent or continuous, but the process is continuous. The biofilms give good performances over periods of at least 1 year. The analytical results are not significantly different from those of other bioassays based on the use of indigenous bacteria and the total duration of analysis is between 2 and 3 h.

Interacting opinion and disease dynamics in multiplex networks: Discontinuous phase transition and nonmonotonic consensus times

NASA Astrophysics Data System (ADS)

Velásquez-Rojas, Fátima; Vazquez, Federico

2017-05-01

Opinion formation and disease spreading are among the most studied dynamical processes on complex networks. In real societies, it is expected that these two processes depend on and affect each other. However, little is known about the effects of opinion dynamics over disease dynamics and vice versa, since most studies treat them separately. In this work we study the dynamics of the voter model for opinion formation intertwined with that of the contact process for disease spreading, in a population of agents that interact via two types of connections, social and contact. These two interacting dynamics take place on two layers of networks, coupled through a fraction q of links present in both networks. The probability that an agent updates its state depends on both the opinion and disease states of the interacting partner. We find that the opinion dynamics has striking consequences on the statistical properties of disease spreading. The most important is that the smooth (continuous) transition from a healthy to an endemic phase observed in the contact process, as the infection probability increases beyond a threshold, becomes abrupt (discontinuous) in the two-layer system. Therefore, disregarding the effects of social dynamics on epidemics propagation may lead to a misestimation of the real magnitude of the spreading. Also, an endemic-healthy discontinuous transition is found when the coupling q overcomes a threshold value. Furthermore, we show that the disease dynamics delays the opinion consensus, leading to a consensus time that varies nonmonotonically with q in a large range of the model's parameters. A mean-field approach reveals that the coupled dynamics of opinions and disease can be approximately described by the dynamics of the voter model decoupled from that of the contact process, with effective probabilities of opinion and disease transmission.

From Particles and Point Clouds to Voxel Models: High Resolution Modeling of Dynamic Landscapes in Open Source GIS

NASA Astrophysics Data System (ADS)

Mitasova, H.; Hardin, E. J.; Kratochvilova, A.; Landa, M.

2012-12-01

Multitemporal data acquired by modern mapping technologies provide unique insights into processes driving land surface dynamics. These high resolution data also offer an opportunity to improve the theoretical foundations and accuracy of process-based simulations of evolving landforms. We discuss development of new generation of visualization and analytics tools for GRASS GIS designed for 3D multitemporal data from repeated lidar surveys and from landscape process simulations. We focus on data and simulation methods that are based on point sampling of continuous fields and lead to representation of evolving surfaces as series of raster map layers or voxel models. For multitemporal lidar data we present workflows that combine open source point cloud processing tools with GRASS GIS and custom python scripts to model and analyze dynamics of coastal topography (Figure 1) and we outline development of coastal analysis toolbox. The simulations focus on particle sampling method for solving continuity equations and its application for geospatial modeling of landscape processes. In addition to water and sediment transport models, already implemented in GIS, the new capabilities under development combine OpenFOAM for wind shear stress simulation with a new module for aeolian sand transport and dune evolution simulations. Comparison of observed dynamics with the results of simulations is supported by a new, integrated 2D and 3D visualization interface that provides highly interactive and intuitive access to the redesigned and enhanced visualization tools. Several case studies will be used to illustrate the presented methods and tools and demonstrate the power of workflows built with FOSS and highlight their interoperability.Figure 1. Isosurfaces representing evolution of shoreline and a z=4.5m contour between the years 1997-2011at Cape Hatteras, NC extracted from a voxel model derived from series of lidar-based DEMs.

Dynamic Transitions and Baroclinic Instability for 3D Continuously Stratified Boussinesq Flows

NASA Astrophysics Data System (ADS)

Şengül, Taylan; Wang, Shouhong

2018-02-01

The main objective of this article is to study the nonlinear stability and dynamic transitions of the basic (zonal) shear flows for the three-dimensional continuously stratified rotating Boussinesq model. The model equations are fundamental equations in geophysical fluid dynamics, and dynamics associated with their basic zonal shear flows play a crucial role in understanding many important geophysical fluid dynamical processes, such as the meridional overturning oceanic circulation and the geophysical baroclinic instability. In this paper, first we derive a threshold for the energy stability of the basic shear flow, and obtain a criterion for local nonlinear stability in terms of the critical horizontal wavenumbers and the system parameters such as the Froude number, the Rossby number, the Prandtl number and the strength of the shear flow. Next, we demonstrate that the system always undergoes a dynamic transition from the basic shear flow to either a spatiotemporal oscillatory pattern or circle of steady states, as the shear strength of the basic flow crosses a critical threshold. Also, we show that the dynamic transition can be either continuous or catastrophic, and is dictated by the sign of a transition number, fully characterizing the nonlinear interactions of different modes. Both the critical shear strength and the transition number are functions of the system parameters. A systematic numerical method is carried out to explore transition in different flow parameter regimes. In particular, our numerical investigations show the existence of a hypersurface which separates the parameter space into regions where the basic shear flow is stable and unstable. Numerical investigations also yield that the selection of horizontal wave indices is determined only by the aspect ratio of the box. We find that the system admits only critical eigenmodes with roll patterns aligned with the x-axis. Furthermore, numerically we encountered continuous transitions to multiple steady states, as well as continuous and catastrophic transitions to spatiotemporal oscillations.

DYNSYL: a general-purpose dynamic simulator for chemical processes

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

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

1978-09-05

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

Optimal post-experiment estimation of poorly modeled dynamic systems

NASA Technical Reports Server (NTRS)

Mook, D. Joseph

1988-01-01

Recently, a novel strategy for post-experiment state estimation of discretely-measured dynamic systems has been developed. The method accounts for errors in the system dynamic model equations in a more general and rigorous manner than do filter-smoother algorithms. The dynamic model error terms do not require the usual process noise assumptions of zero-mean, symmetrically distributed random disturbances. Instead, the model error terms require no prior assumptions other than piecewise continuity. The resulting state estimates are more accurate than filters for applications in which the dynamic model error clearly violates the typical process noise assumptions, and the available measurements are sparse and/or noisy. Estimates of the dynamic model error, in addition to the states, are obtained as part of the solution of a two-point boundary value problem, and may be exploited for numerous reasons. In this paper, the basic technique is explained, and several example applications are given. Included among the examples are both state estimation and exploitation of the model error estimates.

Modelling on optimal portfolio with exchange rate based on discontinuous stochastic process

NASA Astrophysics Data System (ADS)

Yan, Wei; Chang, Yuwen

2016-12-01

Considering the stochastic exchange rate, this paper is concerned with the dynamic portfolio selection in financial market. The optimal investment problem is formulated as a continuous-time mathematical model under mean-variance criterion. These processes follow jump-diffusion processes (Weiner process and Poisson process). Then the corresponding Hamilton-Jacobi-Bellman(HJB) equation of the problem is presented and its efferent frontier is obtained. Moreover, the optimal strategy is also derived under safety-first criterion.

Regenerable Incinerator Exhaust Purification and Trace Contaminant Control System

NASA Technical Reports Server (NTRS)

Finn, John E.; Cho, Shelia Y.; LeVan, M. Douglas

2003-01-01

In this novel approach to air purification, contaminants removed from a process air stream by a high-capacity adsorbent are displaced periodically by a warm, high-humidity, reverse-flow air stream. Displaced contaminants flow into a closed regeneration loop, in which organic compounds are oxidized catalytically and acid gases are removed by a gas- water contactor (which also serves as the source of the water vapor). These features are expected to result in a design that has few expendables and lower energy consumption than alternative regenerable techniques. The joint project between NASA Ames Research Center and Vanderbilt University has completed its third year. Breadboard development continues at NASA Ames, while Vanderbilt has completed most of its adsorption equilibria development. Vanderbilt has completed its fixed-bed apparatus for investigation of dynamic adsorption and desorption processes for trace organic compounds and water vapor, and is continuing its development of the mathematical model describing the column dynamics.

Waiting time distribution for continuous stochastic systems

NASA Astrophysics Data System (ADS)

Gernert, Robert; Emary, Clive; Klapp, Sabine H. L.

2014-12-01

The waiting time distribution (WTD) is a common tool for analyzing discrete stochastic processes in classical and quantum systems. However, there are many physical examples where the dynamics is continuous and only approximately discrete, or where it is favourable to discuss the dynamics on a discretized and a continuous level in parallel. An example is the hindered motion of particles through potential landscapes with barriers. In the present paper we propose a consistent generalization of the WTD from the discrete case to situations where the particles perform continuous barrier crossing characterized by a finite duration. To this end, we introduce a recipe to calculate the WTD from the Fokker-Planck (Smoluchowski) equation. In contrast to the closely related first passage time distribution (FPTD), which is frequently used to describe continuous processes, the WTD contains information about the direction of motion. As an application, we consider the paradigmatic example of an overdamped particle diffusing through a washboard potential. To verify the approach and to elucidate its numerical implications, we compare the WTD defined via the Smoluchowski equation with data from direct simulation of the underlying Langevin equation and find full consistency provided that the jumps in the Langevin approach are defined properly. Moreover, for sufficiently large energy barriers, the WTD defined via the Smoluchowski equation becomes consistent with that resulting from the analytical solution of a (two-state) master equation model for the short-time dynamics developed previously by us [Phys. Rev. E 86, 061135 (2012), 10.1103/PhysRevE.86.061135]. Thus, our approach "interpolates" between these two types of stochastic motion. We illustrate our approach for both symmetric systems and systems under constant force.

Influence of the heat transfer on the thermoelastic response of metals on heating by the laser pulse

NASA Astrophysics Data System (ADS)

Sudenkov, Y. V.; Zimin, B. A.; Sventitskaya, V. E.

2018-05-01

The paper presents an analysis of the effect of the heat transfer process in metals on the parameters of thermal stresses under pulsed laser action. The dynamic problem of thermoelasticity is considered as a two-stage process. The first stage is determined by the time of action of the radiation pulse. The second stage is caused by the dynamics of the heat transfer process after the end of the laser pulse. For showing the continuity of thermoelastic and thermoelectric processes, the analysis of the electronic mechanism for the propagation of heat in metals and the results of experimental studies of these processes are presented. The results of the experiments demonstrate the high sensitivity of the parameters of thermoelastic and thermoelectric pulses to the microstructure of metals.

Advances in the continuous monitoring of erosion and deposition dynamics: Developments and applications of the new PEEP-3T system

NASA Astrophysics Data System (ADS)

Lawler, D. M.

2008-01-01

In most episodic erosion and deposition systems, knowledge of the timing of geomorphological change, in relation to fluctuations in the driving forces, is crucial to strong erosion process inference, and model building, validation and development. A challenge for geomorphology, however, is that few studies have focused on geomorphological event structure (timing, magnitude, frequency and duration of individual erosion and deposition events), in relation to applied stresses, because of the absence of key monitoring methodologies. This paper therefore (a) presents full details of a new erosion and deposition measurement system — PEEP-3T — developed from the Photo-Electronic Erosion Pin sensor in five key areas, including the addition of nocturnal monitoring through the integration of the Thermal Consonance Timing (TCT) concept, to produce a continuous sensing system; (b) presents novel high-resolution datasets from the redesigned PEEP-3T system for river bank system of the Rivers Nidd and Wharfe, northern England, UK; and (c) comments on their potential for wider application throughout geomorphology to address these key measurement challenges. Relative to manual methods of erosion and deposition quantification, continuous PEEP-3T methodologies increase the temporal resolution of erosion/deposition event detection by more than three orders of magnitude (better than 1-second resolution if required), and this facility can significantly enhance process inference. Results show that river banks are highly dynamic thermally and respond quickly to radiation inputs. Data on bank retreat timing, fixed with PEEP-3T TCT evidence, confirmed that they were significantly delayed up to 55 h after flood peaks. One event occurred 13 h after emergence from the flow. This suggests that mass failure processes rather than fluid entrainment dominated the system. It is also shown how, by integrating turbidity instrumentation with TCT ideas, linkages between sediment supply and sediment flux can be forged at event timescales, and a lack of sediment exhaustion was evident here. Five challenges for wider geomorphological process investigation are discussed. This event-based dynamics approach, based on continuous monitoring methodologies, appears to have considerable wider potential for stronger process inference and model testing and validation in many areas of geomorphology.

Generalized master equations for non-Poisson dynamics on networks.

PubMed

Hoffmann, Till; Porter, Mason A; Lambiotte, Renaud

2012-10-01

The traditional way of studying temporal networks is to aggregate the dynamics of the edges to create a static weighted network. This implicitly assumes that the edges are governed by Poisson processes, which is not typically the case in empirical temporal networks. Accordingly, we examine the effects of non-Poisson inter-event statistics on the dynamics of edges, and we apply the concept of a generalized master equation to the study of continuous-time random walks on networks. We show that this equation reduces to the standard rate equations when the underlying process is Poissonian and that its stationary solution is determined by an effective transition matrix whose leading eigenvector is easy to calculate. We conduct numerical simulations and also derive analytical results for the stationary solution under the assumption that all edges have the same waiting-time distribution. We discuss the implications of our work for dynamical processes on temporal networks and for the construction of network diagnostics that take into account their nontrivial stochastic nature.

Generalized master equations for non-Poisson dynamics on networks

NASA Astrophysics Data System (ADS)

Hoffmann, Till; Porter, Mason A.; Lambiotte, Renaud

2012-10-01

The traditional way of studying temporal networks is to aggregate the dynamics of the edges to create a static weighted network. This implicitly assumes that the edges are governed by Poisson processes, which is not typically the case in empirical temporal networks. Accordingly, we examine the effects of non-Poisson inter-event statistics on the dynamics of edges, and we apply the concept of a generalized master equation to the study of continuous-time random walks on networks. We show that this equation reduces to the standard rate equations when the underlying process is Poissonian and that its stationary solution is determined by an effective transition matrix whose leading eigenvector is easy to calculate. We conduct numerical simulations and also derive analytical results for the stationary solution under the assumption that all edges have the same waiting-time distribution. We discuss the implications of our work for dynamical processes on temporal networks and for the construction of network diagnostics that take into account their nontrivial stochastic nature.

Active Polar Gels: a Paradigm for Cytoskeletal Dynamics

NASA Astrophysics Data System (ADS)

Julicher, Frank

2006-03-01

The cytoskeleton of eucaryotic cells is an intrinsically dynamic network of rod-like filaments. Active processes on the molecular scale such as the action of motor proteins and the polymerization and depolymerization of filaments drive active dynamic behaviors while consuming chemical energy in the form of a fuel. Such emergent dynamics is regulated by the cell and is important for many cellular processes such as cell locomotion and cell division. From a general point of view the cytoskeleton represents an active gel-like material with interesting material properties. We present a general theory of active viscoelastic materials made of polar filaments which is motivated by the the cytoskeleton. The continuous consumption of a fuel generates a non- equilibrium state characterized by the generation of flows and stresses. Our theory can be applied to experiments in which cytoskeletal patterns are set in motion by active processes such as those which are at work in cells. It can also capture generic aspects of the flows and stress profiles which occur during cell locomotion.

Coarsening dynamics in condensing zero-range processes and size-biased birth death chains

NASA Astrophysics Data System (ADS)

Jatuviriyapornchai, Watthanan; Grosskinsky, Stefan

2016-05-01

Zero-range processes with decreasing jump rates are well known to exhibit a condensation transition under certain conditions on the jump rates, and the dynamics of this transition continues to be a subject of current research interest. Starting from homogeneous initial conditions, the time evolution of the condensed phase exhibits an interesting coarsening phenomenon of mass transport between cluster sites characterized by a power law. We revisit the approach in Godrèche (2003 J. Phys. A: Math. Gen. 36 6313) to derive effective single site dynamics which form a nonlinear birth death chain describing the coarsening behavior. We extend these results to a larger class of parameter values, and introduce a size-biased version of the single site process, which provides an effective tool to analyze the dynamics of the condensed phase without finite size effects and is the main novelty of this paper. Our results are based on a few heuristic assumptions and exact computations, and are corroborated by detailed simulation data.

Frontiers in Applied and Computational Mathematics 05’

DTIC Science & Technology

2005-03-01

dynamics, forcing subsets to have the same oscillation numbers and interleaving spiking times . Our analysis follows the theory of coupled systems of...continuum is described by a continuous- time stochastic process, as are their internal dynamics. Soluble factors, such as cytokines, are represent- ed...scale of a partide pas- sage time through the reaction zone. Both are realistic for many systems of physical interest. A higher order theory includes

Dynamic Decision Making in Complex Task Environments: Principles and Neural Mechanisms

DTIC Science & Technology

2013-03-01

Dynamical models of cognition . Mathematical models of mental processes. Human performance optimization. U U U U Dr. Jay Myung 703-696-8487 Reset 1...we have continued to develop a neurodynamic theory of decision making, using a combination of computational and experimental approaches, to address...a long history in the field of human cognitive psychology. The theoretical foundations of this research can be traced back to signal detection

Using continuous in-situ measurements to adaptively trigger urban storm water samples

NASA Astrophysics Data System (ADS)

Wong, B. P.; Kerkez, B.

2015-12-01

Until cost-effective in-situ sensors are available for biological parameters, nutrients and metals, automated samplers will continue to be the primary source of reliable water quality measurements. Given limited samples bottles, however, autosamplers often obscure insights on nutrient sources and biogeochemical processes which would otherwise be captured using a continuous sampling approach. To that end, we evaluate the efficacy a novel method to measure first-flush nutrient dynamics in flashy, urban watersheds. Our approach reduces the number of samples required to capture water quality dynamics by leveraging an internet-connected sensor node, which is equipped with a suite of continuous in-situ sensors and an automated sampler. To capture both the initial baseflow as well as storm concentrations, a cloud-hosted adaptive algorithm analyzes the high-resolution sensor data along with local weather forecasts to optimize a sampling schedule. The method was tested in a highly developed urban catchment in Ann Arbor, Michigan and collected samples of nitrate, phosphorus, and suspended solids throughout several storm events. Results indicate that the watershed does not exhibit first flush dynamics, a behavior that would have been obscured when using a non-adaptive sampling approach.

Analysis of discrete and continuous distributions of ventilatory time constants from dynamic computed tomography

NASA Astrophysics Data System (ADS)

Doebrich, Marcus; Markstaller, Klaus; Karmrodt, Jens; Kauczor, Hans-Ulrich; Eberle, Balthasar; Weiler, Norbert; Thelen, Manfred; Schreiber, Wolfgang G.

2005-04-01

In this study, an algorithm was developed to measure the distribution of pulmonary time constants (TCs) from dynamic computed tomography (CT) data sets during a sudden airway pressure step up. Simulations with synthetic data were performed to test the methodology as well as the influence of experimental noise. Furthermore the algorithm was applied to in vivo data. In five pigs sudden changes in airway pressure were imposed during dynamic CT acquisition in healthy lungs and in a saline lavage ARDS model. The fractional gas content in the imaged slice (FGC) was calculated by density measurements for each CT image. Temporal variations of the FGC were analysed assuming a model with a continuous distribution of exponentially decaying time constants. The simulations proved the feasibility of the method. The influence of experimental noise could be well evaluated. Analysis of the in vivo data showed that in healthy lungs ventilation processes can be more likely characterized by discrete TCs whereas in ARDS lungs continuous distributions of TCs are observed. The temporal behaviour of lung inflation and deflation can be characterized objectively using the described new methodology. This study indicates that continuous distributions of TCs reflect lung ventilation mechanics more accurately compared to discrete TCs.

Impact of coastal processes on resource development with an example from Icy Bay, Alaska

USGS Publications Warehouse

Molnia, Bruce F.

1978-01-01

The coastline of Alaska is dynamic and continually readjusting to changes in the many processes that operate in the coastal zone. Because of this dynamic nature, special consideration must be made in planning for development, and. caution must be exercised in site selection for facilities to be emplaced in the coastal zone. All types of coastal processes from continuously active normal processes to the low frequency-high intensity rare event must be considered. Site-specific evaluation-s considering the broad range of possible processes must precede initiation of development. An example of the relation between coastal processes and a proposed resource treatment facility is presented for Icy Bay, Alaska. Icy Bay is the only sheltered bay near many of the offshore tracts leased for petroleum exploration in the 1976 northern Gulf of Alaska OCS (Outer Continental Shelf) lease sale. Consequently, it has been selected as a primary onshore staging site for the support of offshore exploration and development. The environment of Icy Bay has many potentially hazardous features, including a submarine moraine at the bay mouth and actively calving glaciers at the bay's head which produce many icebergs. But most significant from the point of view of locating onshore facilities and pipeline corridors are the high rates of shoreline erosion and sediment deposition. If pipelines or any onshore staging facilities are to be placed in the coastal areas of Icy Bay, then the dynamic changes in shoreline position must be considered so that man-made structures will not be eroded away or be silted in before the completion of development.

African Peoples and Western Education

ERIC Educational Resources Information Center

Onwauchi, P. Chike

1972-01-01

Argues that if the educational process is to be functionally relevant for the African peoples, it must be structured so as to maintain a dynamic pattern of continuity with the family and the cultural life patterns of the people. (Author/JM)

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.

Visual cortex responses reflect temporal structure of continuous quasi-rhythmic sensory stimulation.

PubMed

Keitel, Christian; Thut, Gregor; Gross, Joachim

2017-02-01

Neural processing of dynamic continuous visual input, and cognitive influences thereon, are frequently studied in paradigms employing strictly rhythmic stimulation. However, the temporal structure of natural stimuli is hardly ever fully rhythmic but possesses certain spectral bandwidths (e.g. lip movements in speech, gestures). Examining periodic brain responses elicited by strictly rhythmic stimulation might thus represent ideal, yet isolated cases. Here, we tested how the visual system reflects quasi-rhythmic stimulation with frequencies continuously varying within ranges of classical theta (4-7Hz), alpha (8-13Hz) and beta bands (14-20Hz) using EEG. Our findings substantiate a systematic and sustained neural phase-locking to stimulation in all three frequency ranges. Further, we found that allocation of spatial attention enhances EEG-stimulus locking to theta- and alpha-band stimulation. Our results bridge recent findings regarding phase locking ("entrainment") to quasi-rhythmic visual input and "frequency-tagging" experiments employing strictly rhythmic stimulation. We propose that sustained EEG-stimulus locking can be considered as a continuous neural signature of processing dynamic sensory input in early visual cortices. Accordingly, EEG-stimulus locking serves to trace the temporal evolution of rhythmic as well as quasi-rhythmic visual input and is subject to attentional bias. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Data-based mechanistic modeling of dissolved organic carbon load through storms using continuous 15-minute resolution observations within UK upland watersheds

NASA Astrophysics Data System (ADS)

Jones, T.; Chappell, N. A.

2013-12-01

Few watershed modeling studies have addressed DOC dynamics through storm hydrographs (notable exceptions include Boyer et al., 1997 Hydrol Process; Jutras et al., 2011 Ecol Model; Xu et al., 2012 Water Resour Res). In part this has been a consequence of an incomplete understanding of the biogeochemical processes leading to DOC export to streams (Neff & Asner, 2001, Ecosystems) & an insufficient frequency of DOC monitoring to capture sometimes complex time-varying relationships between DOC & storm hydrographs (Kirchner et al., 2004, Hydrol Process). We present the results of a new & ongoing UK study that integrates two components - 1/ New observations of DOC concentrations (& derived load) continuously monitored at 15 minute intervals through multiple seasons for replicated watersheds; & 2/ A dynamic modeling technique that is able to quantify storage-decay effects, plus hysteretic, nonlinear, lagged & non-stationary relationships between DOC & controlling variables (including rainfall, streamflow, temperature & specific biogeochemical variables e.g., pH, nitrate). DOC concentration is being monitored continuously using the latest generation of UV spectrophotometers (i.e. S::CAN spectro::lysers) with in situ calibrations to laboratory analyzed DOC. The controlling variables are recorded simultaneously at the same stream stations. The watersheds selected for study are among the most intensively studied basins in the UK uplands, namely the Plynlimon & Llyn Brianne experimental basins. All contain areas of organic soils, with three having improved grasslands & three conifer afforested. The dynamic response characteristics (DRCs) that describe detailed DOC behaviour through sequences of storms are simulated using the latest identification routines for continuous time transfer function (CT-TF) models within the Matlab-based CAPTAIN toolbox (some incorporating nonlinear components). To our knowledge this is the first application of CT-TFs to modelling DOC processes. Furthermore this allows a data-based mechanistic (DBM) modelling philosophy to be followed where no assumptions about processes are defined a priori (given that dominant processes are often not known before analysis) & where the information contained in the time-series is used to identify multiple structures of models that are statistically robust. Within the final stage of DBM, biogeochemical & hydrological processes are interpreted from those models that are observable from the available stream time-series. We show that this approach can simulate the key features of DOC dynamics within & between storms & that some of the resultant response characteristics change with varying DOC processes in different seasons. Through the use of MISO (multiple-input single-output) models we demonstrate the relative importance of different variables (e.g., rainfall, temperature) in controlling DOC responses. The contrasting behaviour of the six experimental catchments is also reflected in differing response characteristics. These characteristics are shown to contribute to understanding of basin-integrated DOC export processes & to the ecosystem service impacts of DOC & color on commercial water treatment within the surrounding water supply basins.

Stochastic dynamics and stable equilibrium of evolutionary optional public goods game in finite populations

NASA Astrophysics Data System (ADS)

Quan, Ji; Liu, Wei; Chu, Yuqing; Wang, Xianjia

2018-07-01

Continuous noise caused by mutation is widely present in evolutionary systems. Considering the noise effects and under the optional participation mechanism, a stochastic model for evolutionary public goods game in a finite size population is established. The evolutionary process of strategies in the population is described as a multidimensional ergodic and continuous time Markov process. The stochastic stable state of the system is analyzed by the limit distribution of the stochastic process. By numerical experiments, the influences of the fixed income coefficient for non-participants and the investment income coefficient of the public goods on the stochastic stable equilibrium of the system are analyzed. Through the numerical calculation results, we found that the optional participation mechanism can change the evolutionary dynamics and the equilibrium of the public goods game, and there is a range of parameters which can effectively promote the evolution of cooperation. Further, we obtain the accurate quantitative relationship between the parameters and the probabilities for the system to choose different stable equilibriums, which can be used to realize the control of cooperation.

Exploiting Fast-Variables to Understand Population Dynamics and Evolution

NASA Astrophysics Data System (ADS)

Constable, George W. A.; McKane, Alan J.

2018-07-01

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.

Exploiting Fast-Variables to Understand Population Dynamics and Evolution

NASA Astrophysics Data System (ADS)

Constable, George W. A.; McKane, Alan J.

2017-11-01

We describe a continuous-time modelling framework for biological population dynamics that accounts for demographic noise. In the spirit of the methodology used by statistical physicists, transitions between the states of the system are caused by individual events while the dynamics are described in terms of the time-evolution of a probability density function. In general, the application of the diffusion approximation still leaves a description that is quite complex. However, in many biological applications one or more of the processes happen slowly relative to the system's other processes, and the dynamics can be approximated as occurring within a slow low-dimensional subspace. We review these time-scale separation arguments and analyse the more simple stochastic dynamics that result in a number of cases. We stress that it is important to retain the demographic noise derived in this way, and emphasise this point by showing that it can alter the direction of selection compared to the prediction made from an analysis of the corresponding deterministic model.

Process and continuous apparatus for chemical conversion of materials

DOEpatents

Rugg, Barry; Stanton, Robert

1983-01-01

A process and apparatus for the acid hydrolysis of waste cellulose to glucose of the type wherein waste cellulose is continuously fed into an inlet port of a twin screw extruder, water is continuously fed into reaction zone in the extruder, downstream of the inlet port, the cellulose is continuously reacted with water in the presence of an acid catalyst at elevated temperature and pressure in the reaction zone while being continuously conveyed to an outlet port of the extruder having a given diameter and the reacted cellulose is discharged from the extruder while the elevated temperature and pressure in the reaction zone is maintained. The elevated pressure is maintained by forming a dynamic seal zone at the upstream end of the reaction and continuously discharging the reacted material downstream of the outlet port at a predetermined volume rate of flow to maintain the pressure by passing the discharge through an orifice pipe having a smaller diameter than the given diameter of the outlet port.

Calculational investigation of impact cratering dynamics - Material motions during the crater growth period

NASA Technical Reports Server (NTRS)

Austin, M. G.; Thomsen, J. M.; Ruhl, S. F.; Orphal, D. L.; Schultz, P. H.

1980-01-01

The considered investigation was conducted in connection with studies which are to provide a better understanding of the detailed dynamics of impact cratering processes. Such an understanding is vital for a comprehension of planetary surfaces. The investigation is the continuation of a study of impact dynamics in a uniform, nongeologic material at impact velocities achievable in laboratory-scale experiments conducted by Thomsen et al. (1979). A calculation of a 6 km/sec impact of a 0.3 g spherical 2024 aluminum projectile into low strength (50 kPa) homogeneous plasticene clay has been continued from 18 microseconds to past 600 microseconds. The cratering flow field, defined as the material flow field in the target beyond the transient cavity but well behind the outgoing shock wave, has been analyzed in detail to see how applicable the Maxwell Z-Model, developed from analysis of near-surface explosion cratering calculations, is to impact cratering

Satellite-tracking and Earth dynamics research programs

NASA Technical Reports Server (NTRS)

1982-01-01

The activities carried out by the Smithsonian Astrophysical Observatory (SAO) are described. The SAO network continued to track LAGEOS at highest priority for polar motion and Earth rotation studies, and for other geophysical investigations, including crustal dynamics, Earth and ocean tides, and the general development of precision orbit determination. The network performed regular tracking of several other retroreflector satellites including GEOS-1, GEOS-3, BE-C, and Starlette for refined determinations of station coordinates and the Earth's gravity field and for studies of solid Earth dynamics. A major program in laser upgrading continued to improve ranging accuracy and data yield. This program includes an increase in pulse repetition rate from 8 ppm to 30 ppm, a reduction in laser pulse width from 6 nsec to 2 to 3 nsec, improvements in the photoreceiver and the electronics to improve daylight ranging, and an analog pulse detection system to improve range noise and accuracy. Data processing hardware and software are discussed.

Prediction of flow dynamics using point processes

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; Stemler, Thomas; Eroglu, Deniz; Marwan, Norbert

2018-01-01

Describing a time series parsimoniously is the first step to study the underlying dynamics. For a time-discrete system, a generating partition provides a compact description such that a time series and a symbolic sequence are one-to-one. But, for a time-continuous system, such a compact description does not have a solid basis. Here, we propose to describe a time-continuous time series using a local cross section and the times when the orbit crosses the local cross section. We show that if such a series of crossing times and some past observations are given, we can predict the system's dynamics with fine accuracy. This reconstructability neither depends strongly on the size nor the placement of the local cross section if we have a sufficiently long database. We demonstrate the proposed method using the Lorenz model as well as the actual measurement of wind speed.

Dynamics of sustained use and abandonment of clean cooking systems: lessons from rural India

NASA Astrophysics Data System (ADS)

Chalise, Nishesh; Kumar, Praveen; Priyadarshini, Pratiti; Yadama, Gautam N.

2018-03-01

Clean cooking technologies—ranging from efficient cookstoves to clean fuels—are widely deployed to reduce household air pollution and alleviate adverse health and climate consequences. Although much progress has been made on the technical aspects, sustained and proper use of clean cooking technologies by populations with the most need has been problematic. Only by understanding how clean cooking as an intervention is embedded within complex community processes can we ensure its sustained implementation. Using a community-based system dynamics approach, we engaged two rural communities in co-creating a dynamic model to explain the processes influencing the uptake and transition to sustained use of biogas (an anaerobic methane digester), a clean fuel and cooking technology. The two communities provided contrasting cases: one abandoned biogas while the other continues to use it. We present a system dynamics simulation model, associated analyses, and experiments to understand what factors drive transition and sustained use. A central insight of the model is community processes influencing the capacity to solve technical issues. Model analysis shows that families begin to abandon the technology when it takes longer to solve problems. The momentum in the community then shifts from a determination to address issues with the cooking technology toward caution in further adhering to it. We also conducted experiments using the simulation model to understand the impact of interventions aimed at renewing the use of biogas. A combination of theoretical interventions, including repair of non-functioning biogas units and provision of embedded technical support in communities, resulted in a scenario where the community can continue using the technology even after support is retracted. Our study also demonstrates the utility of a systems approach for engaging local stakeholders in delineating complex community processes to derive significant insights into the dynamic feedback mechanisms involved in the sustained use of biogas by the poor.

Neural networks for self-learning control systems

NASA Technical Reports Server (NTRS)

Nguyen, Derrick H.; Widrow, Bernard

1990-01-01

It is shown how a neural network can learn of its own accord to control a nonlinear dynamic system. An emulator, a multilayered neural network, learns to identify the system's dynamic characteristics. The controller, another multilayered neural network, next learns to control the emulator. The self-trained controller is then used to control the actual dynamic system. The learning process continues as the emulator and controller improve and track the physical process. An example is given to illustrate these ideas. The 'truck backer-upper,' a neural network controller that steers a trailer truck while the truck is backing up to a loading dock, is demonstrated. The controller is able to guide the truck to the dock from almost any initial position. The technique explored should be applicable to a wide variety of nonlinear control problems.

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.

Molecular dynamics study of dual-phase microstructure of Titanium and Zirconium metals during the quenching process

NASA Astrophysics Data System (ADS)

Miyazaki, Narumasa; Sato, Kazunori; Shibutani, Yoji

Dual-phase (DP) transformation, which is composed of felite- and/or martensite- multicomponent microstructural phases, is one of the most effective tools to product functional alloys. To obtain this DP structure such as DP steels and other materials, we usually apply thermal processes such as quenching, tempering and annealing. As the transformation dynamics of DP microstructure depends on conditions of temperature, annealing time, and quenching rate, physical properties of materials are able to be tuned by controlling microstructure type, size, their interfaces and so on. In this study, to understand the behavior of DP transformation and to control physical properties of materials by tuning DP microstructures, we analyze the atomistic dynamics of DP transformation during the quenching process and the detail of DP microstructures by using the molecular dynamics simulations. As target metals of DP transformation, we focus on group 4 transition metals, such as Ti and Zr described by EAM interatomic potentials. For Ti and Zr models we perform molecular dynamics simulations by assuming melt-quenching process from 3000 K to 0 K under the isothermal-isobaric ensemble. During the process for each material, we observe liquid to HCP like transition around the melting temperature, and continuously HCP-BCC like transition around martensitic transformation temperature. Furthermore, we clearly distinguish DP microstructure for each quenched model.

Concentration dependent carriers dynamics in CsPbBr3 perovskite nanocrystals film with transient grating

NASA Astrophysics Data System (ADS)

Wang, Yinghui; Wang, Yanting; Dev Verma, Sachin; Tan, Mingrui; Liu, Qinghui; Yuan, Qilin; Sui, Ning; Kang, Zhihui; Zhou, Qiang; Zhang, Han-Zhuang

2017-05-01

The concentration dependence of the carrier dynamics is a key parameter to describe the photo-physical properties of semiconductor films. Here, we investigate the carrier dynamics in the CsPbBr3 perovskite nanocrystal film by employing the transient grating (TG) technique with continuous bias light. The concentration of initial carriers is determined by the average number of photons per nanocrystals induced by pump light (⟨N⟩). The multi-body interaction would appear and accelerate the TG dynamics with ⟨N⟩. When ⟨N⟩ is more than 3.0, the TG dynamics slightly changes, which implies that the Auger recombination would be the highest order multi-body interaction in carrier recombination dynamics. The concentration of non-equilibrium carriers in the film is controlled by the average number of photons per nanocrystals excited by continuous bias light (⟨nne⟩). Increasing ⟨nne⟩ would improve the trapping-detrapping process by filling the trapping state, which would accelerate the carrier diffusion and add the complexity of the mono-molecular recombination mechanism. The results should be useful to further understand the mechanism of carrier dynamics in the CsPbBr3 perovskite nanocrystal film and of great importance for the operation of the corresponding optoelectronic devices.

Dynamic frailty models based on compound birth-death processes.

PubMed

Putter, Hein; van Houwelingen, Hans C

2015-07-01

Frailty models are used in survival analysis to model unobserved heterogeneity. They accommodate such heterogeneity by the inclusion of a random term, the frailty, which is assumed to multiply the hazard of a subject (individual frailty) or the hazards of all subjects in a cluster (shared frailty). Typically, the frailty term is assumed to be constant over time. This is a restrictive assumption and extensions to allow for time-varying or dynamic frailties are of interest. In this paper, we extend the auto-correlated frailty models of Henderson and Shimakura and of Fiocco, Putter and van Houwelingen, developed for longitudinal count data and discrete survival data, to continuous survival data. We present a rigorous construction of the frailty processes in continuous time based on compound birth-death processes. When the frailty processes are used as mixtures in models for survival data, we derive the marginal hazards and survival functions and the marginal bivariate survival functions and cross-ratio function. We derive distributional properties of the processes, conditional on observed data, and show how to obtain the maximum likelihood estimators of the parameters of the model using a (stochastic) expectation-maximization algorithm. The methods are applied to a publicly available data set. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Regulation of Dynamic Behavior of Retinal Microglia by CX3CR1 Signaling

PubMed Central

Liang, Katharine J.; Lee, Jung Eun; Wang, Yunqing D.; Ma, Wenxin; Fontainhas, Aurora M.; Fariss, Robert N.; Wong, Wai T.

2009-01-01

PURPOSE Microglia in the central nervous system display a marked structural dynamism in their processes in the resting state. This dynamic behavior, which may play a constitutive surveying role in the uninjured neural parenchyma, is also highly responsive to tissue injury. The role of CX3CR1, a chemokine receptor expressed in microglia, in regulating microglia morphology and dynamic behavior in the resting state and after laser-induced focal injury was examined. METHODS Time-lapse confocal imaging of retinal explants was used to evaluate the dynamic behavior of retinal microglia labeled with green fluorescent protein (GFP). Transgenic mice in which CX3CR1 signaling was ablated (CX3CR1GFP/GFP/CX3CR1−/−) and preserved (CX3CR1+/GFP/CX3CR1+/−) were used. RESULTS Retinal microglial density, distribution, cellular morphology, and overall retinal tissue anatomy were not altered in young CX3CR1−/− animals. In the absence of CX3CR1, retinal microglia continued to exhibit dynamic motility in their processes. However, rates of process movement were significantly decreased, both under resting conditions and in response to tissue injury. In addition, microglia migration occurring in response to focal laser injury was also significantly slowed in microglia lacking CX3CR1. CONCLUSIONS CX3CR1 signaling in retinal microglia, though not absolutely required for the presence of microglial dynamism, plays a role in potentiating the rate of retinal microglial process dynamism and cellular migration. CX3CL1 signaling from retinal neurons and endothelial cells likely modulates dynamic microglia behavior so as to influence the level of microglial surveillance under basal conditions and the rate of dynamic behavior in response to tissue injury. PMID:19443728

'Scaling' analysis of the ice accretion process on aircraft surfaces

NASA Technical Reports Server (NTRS)

Keshock, E. G.; Tabrizi, A. H.; Missimer, J. R.

1982-01-01

A comprehensive set of scaling parameters is developed for the ice accretion process by analyzing the energy equations of the dynamic freezing zone and the already frozen ice layer, the continuity equation associated with supercooled liquid droplets entering into and impacting within the dynamic freezing zone, and energy equation of the ice layer. No initial arbitrary judgments are made regarding the relative magnitudes of each of the terms. The method of intrinsic reference variables in employed in order to develop the appropriate scaling parameters and their relative significance in rime icing conditions in an orderly process, rather than utilizing empiricism. The significance of these parameters is examined and the parameters are combined with scaling criteria related to droplet trajectory similitude.

Shear rate analysis of water dynamic in the continuous stirred tank

NASA Astrophysics Data System (ADS)

Tulus; Mardiningsih; Sawaluddin; Sitompul, O. S.; Ihsan, A. K. A. M.

2018-02-01

Analysis of mixture in a continuous stirred tank reactor (CSTR) is an important part in some process of biogas production. This paper is a preliminary study of fluid dynamic phenomenon in a continuous stirred tank numerically. The tank is designed in the form of cylindrical tank equipped with a stirrer. In this study, it is considered that the tank is filled with water. Stirring is done with a stirring speed of 10rpm, 15rpm, 20rpm, and 25rpm. Mathematical modeling of stirred tank is derived. The model is calculated by using the finite element method that are calculated using CFD software. The result shows that the shear rate is high on the front end portion of the stirrer. The maximum shear rate tend to a stable behaviour after the stirring time of 2 second. The relation between the speed and the maximum shear rate is in the form of linear equation.

Modelling hydrological processes in mountainous permafrost basin in North-East of Russia

NASA Astrophysics Data System (ADS)

Makarieva, Olga; Lebedeva, Lyudmila; Nesterova, Natalia

2017-04-01

The studies of hydrological processes in continuous permafrost and the projections of their changes in future have been receiving a lot of attention in the recent years. They are limited by the availability of long-term joint observational data on permafrost dynamic and river runoff which would allow revealing the mechanisms of interaction, tracking the dynamic in historical period and projecting changes in future. The Kolyma Water-Balance Station (KWBS), the Kontaktovy Creek watershed with an area of 22 km2, is situated in the zone of continuous permafrost in the upper reaches of the Kolyma River (Magadan district of Russia). The topography at KWBS is mountainous with the elevations up to 1700 m. Permafrost thickness ranges from 100 to 400 m with temperature -4...-6 °C. Detailed observations of river runoff, active layer dynamics and water balance were carried out at the KWBS from 1948 to 1997. After that permafrost studies were ceased but runoff gauges have been in use and have continuous time series of observations up to 68 years. The hydrological processes at KWBS are representative for the vast NE region of Russia where standard observational network is very scarce. We aim to study and model the mechanisms of interactions between permafrost and runoff, including water flow paths in different landscapes of mountainous permafrost based on detailed historical data of KWBS and the analysis of stable isotopes composition from water samples collected at KWBS in 2016. Mathematical modelling of soil temperature, active layer properties and dynamics, flow formation and interactions between ground and surface water is performed by the means of Hydrograph model (Vinogradov et al. 2011, Semenova et al. 2013). The model algorithms combine process-based and conceptual approaches, which allows for maintaining a balance between the complexity of model design and the use of limited input information. The method for modeling heat dynamics in soil was integrated into Hydrograph model (Semenova et al., 2015; Lebedeva et al., 2015). Small watersheds of KWBS with areas less than 0.5 km2 presenting rocky talus, mountainous tundra and moist larch-forest landscapes were modelled with satisfactory results. The dependence of surface and subsurface flow formation on thawing depth and landscape characteristics is parametrically described. Process analysis and modelling in permafrost regions, including ungauged basins, is suggested, with observable properties of landscapes being used as model parameters, combined with an appropriate level of physically-based conceptualization. The study is partially supported by Russian foundation of basic research, projects 16-35-50151 and 17-05-01138.

SOCIAL PSYCHOLOGICAL DYNAMICS OF ENHANCED HIV RISK REDUCTION AMONG PEER INTERVENTIONISTS

PubMed Central

Dickson-Gomez, Julia; Weeks, Margaret R.; Convey, Mark; Li, Jianghong

2014-01-01

The authors present a model of interactive social psychological and relational feedback processes leading to human immunodeficiency virus (HIV) risk reduction behavior change among active drug users trained as Peer Health Advocates (PHAs). The model is supported by data from qualitative interviews with PHAs and members of their drug-using networks in the Risk Avoidance Partnership (RAP) project. Results suggest three mutually reinforcing social psychological processes that motivate PHAs to provide HIV prevention intervention to their peers and to reduce their own risk behaviors: development of a prosocial identity, positive social reinforcement from drug users and community members, and cognitive dissonance associated with continued risk behavior while engaging in health advocacy. These processes directly influence peer interventionists’ motivation and efficacy to continue giving intervention to their peers, and to reduce their HIV risk behaviors. The authors discuss implications of the model for continued research on effective HIV prevention in high-risk groups. PMID:25414528

The SEL Adapts to Meet Changing Times

NASA Technical Reports Server (NTRS)

Pajerski, Rose S.; Basili, Victor R.

1997-01-01

Since 1976, the Software Engineering Laboratory (SEL) has been dedicated to understanding and improving the way in which one NASA organization, the Flight Dynamics Division (FDD) at Goddard Space Flight Center, develops, maintains, and manages complex flight dynamics systems. It has done this by developing and refining a continual process improvement approach that allows an organization such as the FDD to fine-tune its process for its particular domain. Experimental software engineering and measurement play a significant role in this approach. The SEL is a partnership of NASA Goddard, its major software contractor, Computer Sciences Corporation (CSC), and the University of Maryland's (LTM) Department of Computer Science. The FDD primarily builds software systems that provide ground-based flight dynamics support for scientific satellites. They fall into two sets: ground systems and simulators. Ground systems are midsize systems that average around 250 thousand source lines of code (KSLOC). Ground system development projects typically last 1 - 2 years. Recent systems have been rehosted to workstations from IBM mainframes, and also contain significant new subsystems written in C and C++. The simulators are smaller systems averaging around 60 KSLOC that provide the test data for the ground systems. Simulator development lasts up to 1 year. Most of the simulators have been built in Ada on workstations. The SEL is responsible for the management and continual improvement of the software engineering processes used on these FDD projects.

Past observable dynamics of a continuously monitored qubit

NASA Astrophysics Data System (ADS)

García-Pintos, Luis Pedro; Dressel, Justin

2017-12-01

Monitoring a quantum observable continuously in time produces a stochastic measurement record that noisily tracks the observable. For a classical process, such noise may be reduced to recover an average signal by minimizing the mean squared error between the noisy record and a smooth dynamical estimate. We show that for a monitored qubit, this usual procedure returns unusual results. While the record seems centered on the expectation value of the observable during causal generation, examining the collected past record reveals that it better approximates a moving-mean Gaussian stochastic process centered at a distinct (smoothed) observable estimate. We show that this shifted mean converges to the real part of a generalized weak value in the time-continuous limit without additional postselection. We verify that this smoothed estimate minimizes the mean squared error even for individual measurement realizations. We go on to show that if a second observable is weakly monitored concurrently, then that second record is consistent with the smoothed estimate of the second observable based solely on the information contained in the first observable record. Moreover, we show that such a smoothed estimate made from incomplete information can still outperform estimates made using full knowledge of the causal quantum state.

Stability of Dynamical Systems with Discontinuous Motions:

NASA Astrophysics Data System (ADS)

Michel, Anthony N.; Hou, Ling

In this paper we present a stability theory for discontinuous dynamical systems (DDS): continuous-time systems whose motions are not necessarily continuous with respect to time. We show that this theory is not only applicable in the analysis of DDS, but also in the analysis of continuous dynamical systems (continuous-time systems whose motions are continuous with respect to time), discrete-time dynamical systems (systems whose motions are defined at discrete points in time) and hybrid dynamical systems (HDS) (systems whose descriptions involve simultaneously continuous-time and discrete-time). We show that the stability results for DDS are in general less conservative than the corresponding well-known classical Lyapunov results for continuous dynamical systems and discrete-time dynamical systems. Although the DDS stability results are applicable to general dynamical systems defined on metric spaces (divorced from any kind of description by differential equations, or any other kinds of equations), we confine ourselves to finite-dimensional dynamical systems defined by ordinary differential equations and difference equations, to make this paper as widely accessible as possible. We present only sample results, namely, results for uniform asymptotic stability in the large.

Forging property, processing map, and mesoscale microstructural evolution modeling of a Ti-17 alloy with a lamellar (α+β) starting microstructure

NASA Astrophysics Data System (ADS)

Matsumoto, Hiroaki; Naito, Daiki; Miyoshi, Kento; Yamanaka, Kenta; Chiba, Akihiko; Yamabe-Mitarai, Yoko

2017-12-01

This work identifies microstructural conversion mechanisms during hot deformation (at temperatures ranging from 750 °C to 1050 °C and strain rates ranging from 10-3 s-1 to 1 s-1) of a Ti-5Al-2Sn-2Zr-4Mo-4Cr (Ti-17) alloy with a lamellar starting microstructure and establishes constitutive formulae for predicting the microstructural evolution using finite-element analysis. In the α phase, lamellae kinking is the dominant mode in the higher strain rate region and dynamic globularization frequently occurs at higher temperatures. In the β phase, continuous dynamic recrystallization is the dominant mode below the transition temperature, Tβ (880 890 °C). Dynamic recovery tends to be more active at conditions of lower strain rates and higher temperatures. At temperatures above Tβ, continuous dynamic recrystallization of the β phase frequently occurs, especially in the lower strain rate region. A set of constitutive equations modeling the microstructural evolution and processing map characteristic are established by optimizing the experimental data and were later implemented in the DEFORM-3D software package. There is a satisfactory agreement between the experimental and simulated results, indicating that the established series of constitutive models can be used to reliably predict the properties of a Ti-17 alloy after forging in the (α+β) region.

Forging property, processing map, and mesoscale microstructural evolution modeling of a Ti-17 alloy with a lamellar (α+β) starting microstructure

PubMed Central

Matsumoto, Hiroaki; Naito, Daiki; Miyoshi, Kento; Yamanaka, Kenta; Chiba, Akihiko; Yamabe-Mitarai, Yoko

2017-01-01

Abstract This work identifies microstructural conversion mechanisms during hot deformation (at temperatures ranging from 750 °C to 1050 °C and strain rates ranging from 10−3 s−1 to 1 s−1) of a Ti-5Al-2Sn-2Zr-4Mo-4Cr (Ti-17) alloy with a lamellar starting microstructure and establishes constitutive formulae for predicting the microstructural evolution using finite-element analysis. In the α phase, lamellae kinking is the dominant mode in the higher strain rate region and dynamic globularization frequently occurs at higher temperatures. In the β phase, continuous dynamic recrystallization is the dominant mode below the transition temperature, T β (880~890 °C). Dynamic recovery tends to be more active at conditions of lower strain rates and higher temperatures. At temperatures above T β, continuous dynamic recrystallization of the β phase frequently occurs, especially in the lower strain rate region. A set of constitutive equations modeling the microstructural evolution and processing map characteristic are established by optimizing the experimental data and were later implemented in the DEFORM-3D software package. There is a satisfactory agreement between the experimental and simulated results, indicating that the established series of constitutive models can be used to reliably predict the properties of a Ti-17 alloy after forging in the (α+β) region. PMID:29152021

Forging property, processing map, and mesoscale microstructural evolution modeling of a Ti-17 alloy with a lamellar (α+β) starting microstructure.

PubMed

Matsumoto, Hiroaki; Naito, Daiki; Miyoshi, Kento; Yamanaka, Kenta; Chiba, Akihiko; Yamabe-Mitarai, Yoko

2017-01-01

This work identifies microstructural conversion mechanisms during hot deformation (at temperatures ranging from 750 °C to 1050 °C and strain rates ranging from 10 -3  s -1 to 1 s -1 ) of a Ti-5Al-2Sn-2Zr-4Mo-4Cr (Ti-17) alloy with a lamellar starting microstructure and establishes constitutive formulae for predicting the microstructural evolution using finite-element analysis. In the α phase, lamellae kinking is the dominant mode in the higher strain rate region and dynamic globularization frequently occurs at higher temperatures. In the β phase, continuous dynamic recrystallization is the dominant mode below the transition temperature, T β (880~890 °C). Dynamic recovery tends to be more active at conditions of lower strain rates and higher temperatures. At temperatures above T β , continuous dynamic recrystallization of the β phase frequently occurs, especially in the lower strain rate region. A set of constitutive equations modeling the microstructural evolution and processing map characteristic are established by optimizing the experimental data and were later implemented in the DEFORM-3D software package. There is a satisfactory agreement between the experimental and simulated results, indicating that the established series of constitutive models can be used to reliably predict the properties of a Ti-17 alloy after forging in the (α+ β ) region.

Ethyl acetate as an acyl donor in the continuous flow kinetic resolution of (±)-1-phenylethylamine catalyzed by lipases.

PubMed

de Miranda, Amanda S; Miranda, Leandro S M; de Souza, Rodrigo O M A

2013-05-28

The synthesis of chiral amines is still a challenge for organic synthesis since optically pure amines are of great importance for the pharmaceutical and agrochemical industries. Among all the methodologies developed until now, chemoenzymatic dynamic kinetic resolution has proven to be useful for the preparation of enantioenriched primary chiral amines. In our continuous efforts toward the development of a continuous flow process, herein we report our results on the continuous flow kinetic resolution of (±)-1-phenylethylamine leading to the desired products with high enantiomeric ratios (>200) and short residence times (40 minutes) using ethyl acetate as the acyl donor.

Rich or poor: Who should pay higher tax rates?

NASA Astrophysics Data System (ADS)

Murilo Castro de Oliveira, Paulo

2017-08-01

A dynamic agent model is introduced with an annual random wealth multiplicative process followed by taxes paid according to a linear wealth-dependent tax rate. If poor agents pay higher tax rates than rich agents, eventually all wealth becomes concentrated in the hands of a single agent. By contrast, if poor agents are subject to lower tax rates, the economic collective process continues forever.

Entry and Exit.

DTIC Science & Technology

1987-03-01

1. Introduction R Analyses of industrial competition have attained a new vigor with the application of game -theoretic methods. The process of... competition is represented in models that reflect genuine struggles for entry, market power, and continuing survival. Dynamics and informational effects are...presents a few of the models developed recently to study competitive processes that affect a firm’s entry into a market , and the decision to exit. The

Stochastic Adaptive Estimation and Control.

DTIC Science & Technology

1994-10-26

Marcus, "Language Stability and Stabilizability of Discrete Event Dynamical Systems ," SIAM Journal on Control and Optimization, 31, September 1993...in the hierarchical control of flexible manufacturing systems ; in this problem, the model involves a hybrid process in continuous time whose state is...of the average cost control problem for discrete- time Markov processes. Our exposition covers from finite to Borel state and action spaces and

The stochastic dynamics of intermittent porescale particle motion

NASA Astrophysics Data System (ADS)

Dentz, Marco; Morales, Veronica; Puyguiraud, Alexandre; Gouze, Philippe; Willmann, Matthias; Holzner, Markus

2017-04-01

Numerical and experimental data for porescale particle dynamics show intermittent patterns in Lagrangian velocities and accelerations, which manifest in long time intervals of low and short durations of high velocities [1, 2]. This phenomenon is due to the spatial persistence of particle velocities on characteristic heterogeneity length scales. In order to systematically quantify these behaviors and extract the stochastic dynamics of particle motion, we focus on the analysis of Lagrangian velocities sampled equidistantly along trajectories [3]. This method removes the intermittency observed under isochrone sampling. The space-Lagrangian velocity series can be quantified by a Markov process that is continuous in distance along streamline. It is fully parameterized in terms of the flux-weighted Eulerian velocity PDF and the characteristic pore-length. The resulting stochastic particle motion describes a continuous time random walk (CTRW). This approach allows for the process based interpretation of experimental and numerical porescale velocity, acceleration and displacement data. It provides a framework for the characterization and upscaling of particle transport and dispersion from the pore to the Darcy-scale based on the medium geometry and Eulerian flow attributes. [1] P. De Anna, T. Le Borgne, M. Dentz, A.M. Tartakovsky, D. Bolster, and P. Davy, "Flow intermittency, dispersion, and correlated continuous time random walks in porous media," Phys. Rev. Lett. 110, 184502 (2013). [2] M. Holzner, V. L. Morales, M. Willmann, and M. Dentz, "Intermittent Lagrangian velocities and accelerations in three- dimensional porous medium flow," Phys. Rev. E 92, 013015 (2015). [3] M. Dentz, P. K. Kang, A. Comolli, T. Le Borgne, and D. R. Lester, "Continuous time random walks for the evolution of Lagrangian velocities," Phys. Rev. Fluids (2016).

Spatial distribution visualization of PWM continuous variable-rate spray

USDA-ARS?s Scientific Manuscript database

Chemical application is a dynamic spatial distribution process, during which spray liquid covers the targets with certain thickness and uniformity. Therefore, it is important to study the 2-D and 3-D (dimensional) spray distribution to evaluate spraying quality. The curve-surface generation methods ...

Constitutional Dynamics of Metal-Organic Motifs on a Au(111) Surface.

PubMed

Kong, Huihui; Zhang, Chi; Xie, Lei; Wang, Likun; Xu, Wei

2016-06-13

Constitutional dynamic chemistry (CDC), including both dynamic covalent chemistry and dynamic noncovalent chemistry, relies on reversible formation and breakage of bonds to achieve continuous changes in constitution by reorganization of components. In this regard, CDC is considered to be an efficient and appealing strategy for selective fabrication of surface nanostructures by virtue of dynamic diversity. Although constitutional dynamics of monolayered structures has been recently demonstrated at liquid/solid interfaces, most of molecular reorganization/reaction processes were thought to be irreversible under ultrahigh vacuum (UHV) conditions where CDC is therefore a challenge to be achieved. Here, we have successfully constructed a system that presents constitutional dynamics on a solid surface based on dynamic coordination chemistry, in which selective formation of metal-organic motifs is achieved under UHV conditions. The key to making this reversible switching successful is the molecule-substrate interaction as revealed by DFT calculations. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Labor progress indices and dynamics of the individual uterine contraction during the active stage of labor.

PubMed

Ophir, Ella; Bornstein, Jacob; Odeh, Marwan; Kaminsky, Svetlana; Shnaider, Oleg; Megel, Yuri; Barnea, Ofer

2014-03-01

To obtain and study new data on the dynamics of the labor process and to develop a contraction-based index of labor progress. This study was carried out at the Delivery Room, Department of Obstetrics and Gynecology, Western Galilee Hospital, Nahariya, Israel, using a new device (Birth Track). We continuously monitored cervical dilatation (CD) and head descent (HD) in 30 nulliparaous women during active labor with (augmented group) and without (study group) oxytocin augmentation. This led to the development and validation of progress indices based on features extracted from continuous monitoring. There were no significant differences between the average of each parameter in the study and augmented groups, except for HD velocity. Average HD velocity was faster in the study group. Linear regression analyses demonstrated that head station (HS) amplitude and Toco amplitude were the best parameters for predicting HD velocity in both groups. In the study group, average HD velocity was also significantly related to Toco rate and contraction efficiency. In the augmented group, only a weak correlation with Toco rate was seen, and no correlation with contraction efficiency. With the assistance of the Birth Track device, we can obtain continuous data on the labor process and indices to estimate the labor progress process without the use of vaginal (manual) examination. © 2013 The Authors. Journal of Obstetrics and Gynaecology Research © 2013 Japan Society of Obstetrics and Gynecology.

Voltage Imaging of Waking Mouse Cortex Reveals Emergence of Critical Neuronal Dynamics

PubMed Central

Scott, Gregory; Fagerholm, Erik D.; Mutoh, Hiroki; Leech, Robert; Sharp, David J.; Shew, Woodrow L.

2014-01-01

Complex cognitive processes require neuronal activity to be coordinated across multiple scales, ranging from local microcircuits to cortex-wide networks. However, multiscale cortical dynamics are not well understood because few experimental approaches have provided sufficient support for hypotheses involving multiscale interactions. To address these limitations, we used, in experiments involving mice, genetically encoded voltage indicator imaging, which measures cortex-wide electrical activity at high spatiotemporal resolution. Here we show that, as mice recovered from anesthesia, scale-invariant spatiotemporal patterns of neuronal activity gradually emerge. We show for the first time that this scale-invariant activity spans four orders of magnitude in awake mice. In contrast, we found that the cortical dynamics of anesthetized mice were not scale invariant. Our results bridge empirical evidence from disparate scales and support theoretical predictions that the awake cortex operates in a dynamical regime known as criticality. The criticality hypothesis predicts that small-scale cortical dynamics are governed by the same principles as those governing larger-scale dynamics. Importantly, these scale-invariant principles also optimize certain aspects of information processing. Our results suggest that during the emergence from anesthesia, criticality arises as information processing demands increase. We expect that, as measurement tools advance toward larger scales and greater resolution, the multiscale framework offered by criticality will continue to provide quantitative predictions and insight on how neurons, microcircuits, and large-scale networks are dynamically coordinated in the brain. PMID:25505314

Continuous enzymatic hydrolysis of lignocellulosic biomass in a membrane-reactor system: Continuous enzymatic hydrolysis of lignocellulosic biomass in a membrane-reactor system

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

Stickel, Jonathan J.; Adhikari, Birendra; Sievers, David A.

Converting abundant lignocellulosic biomass to sugars as fungible precursors to fuels and chemicals has the potential to diversify the supply chain for those products, but further process improvements are needed to achieve economic viability. In the current work, process intensification of the key enzymatic hydrolysis unit operation is demonstrated by means of a membrane reactor system that was operated continuously. Lignocellulosic biomass (pretreated corn stover) and buffered enzyme solution were fed to a continuously stirred-tank reactor, and clarified sugar solution was withdrawn via a commercial tubular ultrafiltration membrane. The membrane permeance decline and membrane cleaning efficacy were studied and didmore » not vary significantly when increasing fraction insoluble solids (FIS) from 2.5% to 5%. Continuous enzymatic hydrolysis was successfully operated for more than 80 h. A model for the reactor system was able to predict dynamic behavior that was in reasonable agreement with experimental results. The modeled technical performance of anticipated commercial batch and continuous enzymatic hydrolysis processes were compared and showed that continuous operation would provide at least twice the volumetric productivity for the conditions studied. Further improvements are anticipated by better membrane selection and by increasing FIS.« less

Continuous enzymatic hydrolysis of lignocellulosic biomass in a membrane-reactor system: Continuous enzymatic hydrolysis of lignocellulosic biomass in a membrane-reactor system

DOE PAGES

Stickel, Jonathan J.; Adhikari, Birendra; Sievers, David A.; ...

2018-02-21

Converting abundant lignocellulosic biomass to sugars as fungible precursors to fuels and chemicals has the potential to diversify the supply chain for those products, but further process improvements are needed to achieve economic viability. In the current work, process intensification of the key enzymatic hydrolysis unit operation is demonstrated by means of a membrane reactor system that was operated continuously. Lignocellulosic biomass (pretreated corn stover) and buffered enzyme solution were fed to a continuously stirred-tank reactor, and clarified sugar solution was withdrawn via a commercial tubular ultrafiltration membrane. The membrane permeance decline and membrane cleaning efficacy were studied and didmore » not vary significantly when increasing fraction insoluble solids (FIS) from 2.5% to 5%. Continuous enzymatic hydrolysis was successfully operated for more than 80 h. A model for the reactor system was able to predict dynamic behavior that was in reasonable agreement with experimental results. The modeled technical performance of anticipated commercial batch and continuous enzymatic hydrolysis processes were compared and showed that continuous operation would provide at least twice the volumetric productivity for the conditions studied. Further improvements are anticipated by better membrane selection and by increasing FIS.« less

Cellular dynamical mechanisms for encoding the time and place of events along spatiotemporal trajectories in episodic memory.

PubMed

Hasselmo, Michael E; Giocomo, Lisa M; Brandon, Mark P; Yoshida, Motoharu

2010-12-31

Understanding the mechanisms of episodic memory requires linking behavioral data and lesion effects to data on the dynamics of cellular membrane potentials and population interactions within brain regions. Linking behavior to specific membrane channels and neurochemicals has implications for therapeutic applications. Lesions of the hippocampus, entorhinal cortex and subcortical nuclei impair episodic memory function in humans and animals, and unit recording data from these regions in behaving animals indicate episodic memory processes. Intracellular recording in these regions demonstrates specific cellular properties including resonance, membrane potential oscillations and bistable persistent spiking that could underlie the encoding and retrieval of episodic trajectories. A model presented here shows how intrinsic dynamical properties of neurons could mediate the encoding of episodic memories as complex spatiotemporal trajectories. The dynamics of neurons allow encoding and retrieval of unique episodic trajectories in multiple continuous dimensions including temporal intervals, personal location, the spatial coordinates and sensory features of perceived objects and generated actions, and associations between these elements. The model also addresses how cellular dynamics could underlie unit firing data suggesting mechanisms for coding continuous dimensions of space, time, sensation and action. Copyright © 2010 Elsevier B.V. All rights reserved.

Cellular dynamical mechanisms for encoding the time and place of events along spatiotemporal trajectories in episodic memory

PubMed Central

Hasselmo, Michael E.; Giocomo, Lisa M.; Yoshida, Motoharu

2010-01-01

Understanding the mechanisms of episodic memory requires linking behavioural data and lesion effects to data on the dynamics of cellular membrane potentials and population interactions within these brain regions. Linking behavior to specific membrane channels and neurochemicals has implications for therapeutic applications. Lesions of the hippocampus, entorhinal cortex and subcortical nuclei impair episodic memory function in humans and animals, and unit recording data from these regions in behaving animals indicate episodic memory processes. Intracellular recording in these regions demonstrates specific cellular properties including resonance, membrane potential oscillations and bistable persistent spiking that could underlie the encoding and retrieval of episodic trajectories. A model presented here shows how intrinsic dynamical properties of neurons could mediate the encoding of episodic memories as complex spatiotemporal trajectories. The dynamics of neurons allow encoding and retrieval of unique episodic trajectories in multiple continuous dimensions including temporal intervals, personal location, the spatial coordinates and sensory features of perceived objects and generated actions, and associations between these elements. The model also addresses how cellular dynamics could underlie unit firing data suggesting mechanisms for coding continuous dimensions of space, time, sensation and action. PMID:20018213

Nonlinear dynamics of coiling, and mounding in viscoelastic jets

NASA Astrophysics Data System (ADS)

Majmudar, Trushant; Ober, Thomas; McKinley, Gareth

2009-11-01

Free surface continuous jets of non-Newtonian fluids, although relevant for many industrial processes like bottle filling, remain poorly understood in terms of fundamental fluid dynamics. Here we present a systematic study of the effect of viscoelasticity on the dynamics of continuous jets of worm-like micellar surfactant solutions of varying viscosities and elasticities, and model yield-stress fluids. We systematically vary the height of the drop and the flow rate in order to study the effects of varying geometric and kinematic parameters. We observe that for fluids with higher elastic relaxation times, folding is the preferred mode. In contrast, for low elasticity fluids we observe complex nonlinear dynamics consisting of coiling, folding, and irregular meandering as the height of the fall increases. Beyond this regime, the jet dynamics smoothly crosses over to exhibit the ``leaping shampoo" or the Kaye effect. Upon increasing the flow rate to very high values, the ``leaping shampoo" state disappears and is replaced by a pronounced mounding or ``heaping". A subsequent increase in the flow rate results in finger-like protrusions to emerge out of the mound and climb up towards the nozzle. This novel transition is currently under investigation and remains a theoretical challenge.

Soil Moisture Dynamics under Corn, Soybean, and Perennial Kura Clover

NASA Astrophysics Data System (ADS)

Ochsner, T.; Venterea, R. T.

2009-12-01

Rising global food and energy consumption call for increased agricultural production, whereas rising concerns for environmental quality call for farming systems with more favorable environmental impacts. Improved understanding and management of plant-soil water interactions are central to meeting these twin challenges. The objective of this research was to compare the temporal dynamics of soil moisture under contrasting cropping systems suited for the Midwestern region of the United States. Precipitation, infiltration, drainage, evapotranspiration, soil water storage, and freeze/thaw processes were measured hourly for three years in field plots of continuous corn (Zea mays L.), corn/soybean [Glycine max (L.) Merr.] rotation, and perennial kura clover (Trifolium ambiguum M. Bieb.) in southeastern Minnesota. The evapotranspiration from the perennial clover most closely followed the temporal dynamics of precipitation, resulting in deep drainage which was reduced up to 50% relative to the annual crops. Soil moisture utilization also continued later into the fall under the clover than under the annual crops. In the annual cropping systems, crop sequence influenced the soil moisture dynamics. Soybean following corn and continuous corn exhibited evapotranspiration which was 80 mm less than and deep drainage which was 80 mm greater than that of corn following soybean. These differences occurred primarily during the spring and were associated with differences in early season plant growth between the systems. In the summer, soil moisture depletion was up to 30 mm greater under corn than soybean. Crop residue also played an important role in the soil moisture dynamics. Higher amounts of residue were associated with reduced soil freezing. This presentation will highlight key aspects of the soil moisture dynamics for these contrasting cropping systems across temporal scales ranging from hours to years. The links between soil moisture dynamics, crop yields, and nutrient leaching will also be examined.

The stream of experience when watching artistic movies. Dynamic aesthetic effects revealed by the Continuous Evaluation Procedure (CEP).

PubMed

Muth, Claudia; Raab, Marius H; Carbon, Claus-Christian

2015-01-01

Research in perception and appreciation is often focused on snapshots, stills of experience. Static approaches allow for multidimensional assessment, but are unable to catch the crucial dynamics of affective and perceptual processes; for instance, aesthetic phenomena such as the "Aesthetic-Aha" (the increase in liking after the sudden detection of Gestalt), effects of expectation, or Berlyne's idea that "disorientation" with a "promise of success" elicits interest. We conducted empirical studies on indeterminate artistic movies depicting the evolution and metamorphosis of Gestalt and investigated (i) the effects of sudden perceptual insights on liking; that is, "Aesthetic Aha"-effects, (ii) the dynamics of interest before moments of insight, and (iii) the dynamics of complexity before and after moments of insight. Via the so-called Continuous Evaluation Procedure (CEP) enabling analogous evaluation in a continuous way, participants assessed the material on two aesthetic dimensions blockwise either in a gallery or a laboratory. The material's inherent dynamics were described via assessments of liking, interest, determinacy, and surprise along with a computational analysis on the variable complexity. We identified moments of insight as peaks in determinacy and surprise. Statistically significant changes in liking and interest demonstrated that: (i) insights increase liking, (ii) interest already increases 1500 ms before such moments of insight, supporting the idea that it is evoked by an expectation of understanding, and (iii) insights occur during increasing complexity. We propose a preliminary model of dynamics in liking and interest with regard to complexity and perceptual insight and discuss descriptions of participants' experiences of insight. Our results point to the importance of systematic analyses of dynamics in art perception and appreciation.

Formalizing Knowledge in Multi-Scale Agent-Based Simulations

PubMed Central

Somogyi, Endre; Sluka, James P.; Glazier, James A.

2017-01-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused. PMID:29338063

Formalizing Knowledge in Multi-Scale Agent-Based Simulations.

PubMed

Somogyi, Endre; Sluka, James P; Glazier, James A

2016-10-01

Multi-scale, agent-based simulations of cellular and tissue biology are increasingly common. These simulations combine and integrate a range of components from different domains. Simulations continuously create, destroy and reorganize constituent elements causing their interactions to dynamically change. For example, the multi-cellular tissue development process coordinates molecular, cellular and tissue scale objects with biochemical, biomechanical, spatial and behavioral processes to form a dynamic network. Different domain specific languages can describe these components in isolation, but cannot describe their interactions. No current programming language is designed to represent in human readable and reusable form the domain specific knowledge contained in these components and interactions. We present a new hybrid programming language paradigm that naturally expresses the complex multi-scale objects and dynamic interactions in a unified way and allows domain knowledge to be captured, searched, formalized, extracted and reused.

Dynamic predictive model for the growth of Salmonella spp. in liquid whole egg.

PubMed

Singh, Aikansh; Korasapati, Nageswara R; Juneja, Vijay K; Subbiah, Jeyamkondan; Froning, Glenn; Thippareddi, Harshavardhan

2011-04-01

A dynamic model for the growth of Salmonella spp. in liquid whole egg (LWE) (approximately pH 7.8) under continuously varying temperature was developed. The model was validated using 2 (5 to 15 °C; 600 h and 10 to 40 °C; 52 h) sinusoidal, continuously varying temperature profiles. LWE adjusted to pH 7.8 was inoculated with approximately 2.5-3.0 log CFU/mL of Salmonella spp., and the growth data at several isothermal conditions (5, 7, 10, 15, 20, 25, 30, 35, 37, 39, 41, 43, 45, and 47 °C) was collected. A primary model (Baranyi model) was fitted for each temperature growth data and corresponding maximum growth rates were estimated. Pseudo-R2 values were greater than 0.97 for primary models. Modified Ratkowsky model was used to fit the secondary model. The pseudo-R2 and root mean square error were 0.99 and 0.06 log CFU/mL, respectively, for the secondary model. A dynamic model for the prediction of Salmonella spp. growth under varying temperature conditions was developed using 4th-order Runge-Kutta method. The developed dynamic model was validated for 2 sinusoidal temperature profiles, 5 to 15 °C (for 600 h) and 10 to 40 °C (for 52 h) with corresponding root mean squared error values of 0.28 and 0.23 log CFU/mL, respectively, between predicted and observed Salmonella spp. populations. The developed dynamic model can be used to predict the growth of Salmonella spp. in LWE under varying temperature conditions.   Liquid egg and egg products are widely used in food processing and in restaurant operations. These products can be contaminated with Salmonella spp. during breaking and other unit operations during processing. The raw, liquid egg products are stored under refrigeration prior to pasteurization. However, process deviations can occur such as refrigeration failure, leading to temperature fluctuations above the required temperatures as specified in the critical limits within hazard analysis and critical control point plans for the operations. The processors are required to evaluate the potential growth of Salmonella spp. in such products before the product can be used, or further processed. Dynamic predictive models are excellent tools for regulators as well as the processing plant personnel to evaluate the microbiological safety of the product under such conditions.

Systems approach to managing educational quality in the engineering classroom

NASA Astrophysics Data System (ADS)

Grygoryev, Kostyantyn

Today's competitive environment in post-secondary education requires universities to demonstrate the quality of their programs in order to attract financing, and student and academic talent. Despite significant efforts devoted to improving the quality of higher education, systematic, continuous performance measurement and management still have not reached the level where educational outputs and outcomes are actually produced---the classroom. An engineering classroom is a complex environment in which educational inputs are transformed by educational processes into educational outputs and outcomes. By treating a classroom as a system, one can apply tools such as Structural Equation Modeling, Statistical Process Control, and System Dynamics in order to discover cause-and-effect relationships among the classroom variables, control the classroom processes, and evaluate the effect of changes to the course organization, content, and delivery, on educational processes and outcomes. Quality improvement is best achieved through the continuous, systematic application of efforts and resources. Improving classroom processes and outcomes is an iterative process that starts with identifying opportunities for improvement, designing the action plan, implementing the changes, and evaluating their effects. Once the desired objectives are achieved, the quality improvement cycle may start again. The goal of this research was to improve the educational processes and outcomes in an undergraduate engineering management course taught at the University of Alberta. The author was involved with the course, first, as a teaching assistant, and, then, as a primary instructor. The data collected from the course over four years were used to create, first, a static and, then, a dynamic model of a classroom system. By using model output and qualitative feedback from students, changes to the course organization and content were introduced. These changes led to a lower perceived course workload and increased the students' satisfaction with the instructor, but the students' overall satisfaction with the course did not change significantly, and their attitude toward the course subject actually became more negative. This research brought performance measurement to the level of a classroom, created a dynamic model of the classroom system based on the cause-and-effect relationships discovered by using statistical analysis, and used a systematic, continuous improvement approach to modify the course in order to improve selected educational processes and outcomes.

Network dynamics and systems biology

NASA Astrophysics Data System (ADS)

Norrell, Johannes A.

The physics of complex systems has grown considerably as a field in recent decades, largely due to improved computational technology and increased availability of systems level data. One area in which physics is of growing relevance is molecular biology. A new field, systems biology, investigates features of biological systems as a whole, a strategy of particular importance for understanding emergent properties that result from a complex network of interactions. Due to the complicated nature of the systems under study, the physics of complex systems has a significant role to play in elucidating the collective behavior. In this dissertation, we explore three problems in the physics of complex systems, motivated in part by systems biology. The first of these concerns the applicability of Boolean models as an approximation of continuous systems. Studies of gene regulatory networks have employed both continuous and Boolean models to analyze the system dynamics, and the two have been found produce similar results in the cases analyzed. We ask whether or not Boolean models can generically reproduce the qualitative attractor dynamics of networks of continuously valued elements. Using a combination of analytical techniques and numerical simulations, we find that continuous networks exhibit two effects---an asymmetry between on and off states, and a decaying memory of events in each element's inputs---that are absent from synchronously updated Boolean models. We show that in simple loops these effects produce exactly the attractors that one would predict with an analysis of the stability of Boolean attractors, but in slightly more complicated topologies, they can destabilize solutions that are stable in the Boolean approximation, and can stabilize new attractors. Second, we investigate ensembles of large, random networks. Of particular interest is the transition between ordered and disordered dynamics, which is well characterized in Boolean systems. Networks at the transition point, called critical, exhibit many of the features of regulatory networks, and recent studies suggest that some specific regulatory networks are indeed near-critical. We ask whether certain statistical measures of the ensemble behavior of large continuous networks are reproduced by Boolean models. We find that, in spite of the lack of correspondence between attractors observed in smaller systems, the statistical characterization given by the continuous and Boolean models show close agreement, and the transition between order and disorder known in Boolean systems can occur in continuous systems as well. One effect that is not present in Boolean systems, the failure of information to propagate down chains of elements of arbitrary length, is present in a class of continuous networks. In these systems, a modified Boolean theory that takes into account the collective effect of propagation failure on chains throughout the network gives a good description of the observed behavior. We find that propagation failure pushes the system toward greater order, resulting in a partial or complete suppression of the disordered phase. Finally, we explore a dynamical process of direct biological relevance: asymmetric cell division in A. thaliana. The long term goal is to develop a model for the process that accurately accounts for both wild type and mutant behavior. To contribute to this endeavor, we use confocal microscopy to image roots in a SHORT-ROOT inducible mutant. We compute correlation functions between the locations of asymmetrically divided cells, and we construct stochastic models based on a few simple assumptions that accurately predict the non-zero correlations. Our result shows that intracellular processes alone cannot be responsible for the observed divisions, and that an intercell signaling mechanism could account for the measured correlations.

Definition and dynamic control of a continuous chromatography process independent of cell culture titer and impurities.

PubMed

Chmielowski, Rebecca A; Mathiasson, Linda; Blom, Hans; Go, Daniel; Ehring, Hanno; Khan, Heera; Li, Hong; Cutler, Collette; Lacki, Karol; Tugcu, Nihal; Roush, David

2017-12-01

Advances in cell culture technology have enabled the production of antibody titers upwards of 30g/L. These highly productive cell culture systems can potentially lead to productivity bottlenecks in downstream purification due to lower column loadings, especially in the primary capture chromatography step. Alternative chromatography solutions to help remedy this bottleneck include the utilization of continuous processing systems such as periodic counter-current chromatography (PCC). Recent studies have provided methods to optimize and improve the design of PCC for cell culture titers up to about 3g/L. This paper defines a continuous loading strategy for PCC that is independent of cell culture background and encompasses cell culture titers up to about 31g/L. Initial experimentation showed a challenge with determining a difference in change in UV280nm signal (ie. ΔUV) between cell culture feed and monoclonal antibody (mAb) concentration. Further investigation revealed UV280nm absorbance of the cell culture feedstock without antibody was outside of the linear range of detection for a given cell pathlength. Additional experimentation showed the difference in ΔUV for various cell culture feeds can be either theoretically predicted by Beer's Law given a known absorbance of the media background and impurities or experimentally determined using various UV280nm cell pathlengths. Based on these results, a 0.35mm pathlength at UV280nm was chosen for dynamic control to overcome the background signal. The pore diffusion model showed good agreement with the experimental frontal analysis data, which resulted in definition of a ΔUV setpoint range between 20 and 70% for 3C-PCC experiments. Product quality of the elution pools was acceptable between various cell culture feeds and titers up to about 41g/L. Results indicated the following ΔUV setpoints to achieve robust dynamic control and maintain 3C-PCC yield: ∼20-45% for titers greater than 10g/L depending on UV absorbance of the HCCF and ∼45-70% for titers of up to 10g/L independent of UV absorbance of the HCCF. The strategy and results presented in this paper show column loading in a continuous chromatography step can be dynamically controlled independent of the cell culture feedstock and titer, and allow for enhanced process control built into the downstream continuous operations. Copyright © 2017 Elsevier B.V. All rights reserved.

Assessment of Gestational Age and Neuromaturation

ERIC Educational Resources Information Center

Allen, Marilee C.

2005-01-01

Neuromaturation is the functional development of the central nervous system (CNS). It is by its very nature a dynamic process, a continuous interaction between the genome and first the intrauterine environment, then the extrauterine environment. Understanding neuromaturation and being able to measure it is fundamental to infant neurodevelopmental…

Motivations and Concerns: Voices from Pre-Service Language Teachers

ERIC Educational Resources Information Center

Kavanoz, Suzan; Yüksel, Hatice G.

2017-01-01

Contemporary interactionist theories conceive identity formation as a dynamic process that is continuously co-constructed within a social context. For pre-service language teachers, teacher education programs constitute the context in which their professional identities are formed. This cross-sectional qualitative study aims at exploring…

Nonlinear dynamics of global atmospheric and Earth-system processes

NASA Technical Reports Server (NTRS)

Saltzman, Barry; Ebisuzaki, Wesley; Maasch, Kirk A.; Oglesby, Robert; Pandolfo, Lionel

1990-01-01

Researchers are continuing their studies of the nonlinear dynamics of global weather systems. Sensitivity analyses of large-scale dynamical models of the atmosphere (i.e., general circulation models i.e., GCM's) were performed to establish the role of satellite-signatures of soil moisture, sea surface temperature, snow cover, and sea ice as crucial boundary conditions determining global weather variability. To complete their study of the bimodality of the planetary wave states, they are using the dynamical systems approach to construct a low-order theoretical explanation of this phenomenon. This work should have important implications for extended range forecasting of low-frequency oscillations, elucidating the mechanisms for the transitions between the two wave modes. Researchers are using the methods of jump analysis and attractor dimension analysis to examine the long-term satellite records of significant variables (e.g., long wave radiation, and cloud amount), to explore the nature of mode transitions in the atmosphere, and to determine the minimum number of equations needed to describe the main weather variations with a low-order dynamical system. Where feasible they will continue to explore the applicability of the methods of complex dynamical systems analysis to the study of the global earth-system from an integrative viewpoint involving the roles of geochemical cycling and the interactive behavior of the atmosphere, hydrosphere, and biosphere.

The within-host population dynamics of Mycobacterium tuberculosis vary with treatment efficacy.

PubMed

Trauner, Andrej; Liu, Qingyun; Via, Laura E; Liu, Xin; Ruan, Xianglin; Liang, Lili; Shi, Huimin; Chen, Ying; Wang, Ziling; Liang, Ruixia; Zhang, Wei; Wei, Wang; Gao, Jingcai; Sun, Gang; Brites, Daniela; England, Kathleen; Zhang, Guolong; Gagneux, Sebastien; Barry, Clifton E; Gao, Qian

2017-04-19

Combination therapy is one of the most effective tools for limiting the emergence of drug resistance in pathogens. Despite the widespread adoption of combination therapy across diseases, drug resistance rates continue to rise, leading to failing treatment regimens. The mechanisms underlying treatment failure are well studied, but the processes governing successful combination therapy are poorly understood. We address this question by studying the population dynamics of Mycobacterium tuberculosis within tuberculosis patients undergoing treatment with different combinations of antibiotics. By combining very deep whole genome sequencing (~1000-fold genome-wide coverage) with sequential sputum sampling, we were able to detect transient genetic diversity driven by the apparently continuous turnover of minor alleles, which could serve as the source of drug-resistant bacteria. However, we report that treatment efficacy has a clear impact on the population dynamics: sufficient drug pressure bears a clear signature of purifying selection leading to apparent genetic stability. In contrast, M. tuberculosis populations subject to less drug pressure show markedly different dynamics, including cases of acquisition of additional drug resistance. Our findings show that for a pathogen like M. tuberculosis, which is well adapted to the human host, purifying selection constrains the evolutionary trajectory to resistance in effectively treated individuals. Nonetheless, we also report a continuous turnover of minor variants, which could give rise to the emergence of drug resistance in cases of drug pressure weakening. Monitoring bacterial population dynamics could therefore provide an informative metric for assessing the efficacy of novel drug combinations.

Sustaining a Mature Risk Management Process: Ensuring the International Space Station for a Vibrant Future

NASA Technical Reports Server (NTRS)

Raftery, Michael; Carter-Journet, Katrina

2013-01-01

The International Space Station (ISS) risk management methodology is an example of a mature and sustainable process. Risk management is a systematic approach used to proactively identify, analyze, plan, track, control, communicate, and document risks to help management make risk-informed decisions that increase the likelihood of achieving program objectives. The ISS has been operating in space for over 14 years and permanently crewed for over 12 years. It is the longest surviving habitable vehicle in low Earth orbit history. Without a mature and proven risk management plan, it would be increasingly difficult to achieve mission success throughout the life of the ISS Program. A successful risk management process must be able to adapt to a dynamic program. As ISS program-level decision processes have evolved, so too has the ISS risk management process continued to innovate, improve, and adapt. Constant adaptation of risk management tools and an ever-improving process is essential to the continued success of the ISS Program. Above all, sustained support from program management is vital to risk management continued effectiveness. Risk management is valued and stressed as an important process by the ISS Program.

How input fluctuations reshape the dynamics of a biological switching system

NASA Astrophysics Data System (ADS)

Hu, Bo; Kessler, David A.; Rappel, Wouter-Jan; Levine, Herbert

2012-12-01

An important task in quantitative biology is to understand the role of stochasticity in biochemical regulation. Here, as an extension of our recent work [Phys. Rev. Lett.PRLTAO0031-900710.1103/PhysRevLett.107.148101 107, 148101 (2011)], we study how input fluctuations affect the stochastic dynamics of a simple biological switch. In our model, the on transition rate of the switch is directly regulated by a noisy input signal, which is described as a non-negative mean-reverting diffusion process. This continuous process can be a good approximation of the discrete birth-death process and is much more analytically tractable. Within this setup, we apply the Feynman-Kac theorem to investigate the statistical features of the output switching dynamics. Consistent with our previous findings, the input noise is found to effectively suppress the input-dependent transitions. We show analytically that this effect becomes significant when the input signal fluctuates greatly in amplitude and reverts slowly to its mean.

Numerical study of impact erosion of multiple solid particle

NASA Astrophysics Data System (ADS)

Zheng, Chao; Liu, Yonghong; Chen, Cheng; Qin, Jie; Ji, Renjie; Cai, Baoping

2017-11-01

Material erosion caused by continuous particle impingement during hydraulic fracturing results in significant economic loss and increased production risks. The erosion process is complex and has not been clearly explained through physical experiments. To address this problem, a multiple particle model in a 3D configuration was proposed to investigate the dynamic erosion process. This approach can significantly reduce experiment costs. The numerical model considered material damping and elastic-plastic material behavior of target material. The effects of impact parameters on erosion characteristics, such as plastic deformation, contact time, and energy loss rate, were investigated. Based on comprehensive studies, the dynamic erosion mechanism and geometry evolution of eroded crater was obtained. These findings can provide a detailed erosion process of target material and insights into the material erosion caused by multiple particle impingement.

35-GHz radar sensor for automotive collision avoidance

NASA Astrophysics Data System (ADS)

Zhang, Jun

1999-07-01

This paper describes the development of a radar sensor system used for automotive collision avoidance. Because the heavy truck may have great larger radar cross section than a motorcyclist has, the radar receiver may have a large dynamic range. And multi-targets at different speed may confuse the echo spectrum causing the ambiguity between range and speed of target. To get more information about target and background and to adapt to the large dynamic range and multi-targets, a frequency modulated and pseudo- random binary sequences phase modulated continuous wave radar system is described. The analysis of this double- modulation system is given. A high-speed signal processing and data processing component are used to process and combine the data and information from echo at different direction and at every moment.

Selective host molecules obtained by dynamic adaptive chemistry.

PubMed

Matache, Mihaela; Bogdan, Elena; Hădade, Niculina D

2014-02-17

Up till 20 years ago, in order to endow molecules with function there were two mainstream lines of thought. One was to rationally design the positioning of chemical functionalities within candidate molecules, followed by an iterative synthesis-optimization process. The second was the use of a "brutal force" approach of combinatorial chemistry coupled with advanced screening for function. Although both methods provided important results, "rational design" often resulted in time-consuming efforts of modeling and synthesis only to find that the candidate molecule was not performing the designed job. "Combinatorial chemistry" suffered from a fundamental limitation related to the focusing of the libraries employed, often using lead compounds that limit its scope. Dynamic constitutional chemistry has developed as a combination of the two approaches above. Through the rational use of reversible chemical bonds together with a large plethora of precursor libraries, one is now able to build functional structures, ranging from quite simple molecules up to large polymeric structures. Thus, by introduction of the dynamic component within the molecular recognition processes, a new perspective of deciphering the world of the molecular events has aroused together with a new field of chemistry. Since its birth dynamic constitutional chemistry has continuously gained attention, in particular due to its ability to easily create from scratch outstanding molecular structures as well as the addition of adaptive features. The fundamental concepts defining the dynamic constitutional chemistry have been continuously extended to currently place it at the intersection between the supramolecular chemistry and newly defined adaptive chemistry, a pivotal feature towards evolutive chemistry. Copyright © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Dental caries: a dynamic disease process.

PubMed

Featherstone, J D B

2008-09-01

Abstract Dental caries is a transmissible bacterial disease process caused by acids from bacterial metabolism diffusing into enamel and dentine and dissolving the mineral. The bacteria responsible produce organic acids as a by-product of their metabolism of fermentable carbohydrates. The caries process is a continuum resulting from many cycles of demineralization and remineralization. Demineralization begins at the atomic level at the crystal surface inside the enamel or dentine and can continue unless halted with the end-point being cavitation. There are many possibilities to intervene in this continuing process to arrest or reverse the progress of the lesion. Remineralization is the natural repair process for non-cavitated lesions, and relies on calcium and phosphate ions assisted by fluoride to rebuild a new surface on existing crystal remnants in subsurface lesions remaining after demineralization. These remineralized crystals are acid resistant, being much less soluble than the original mineral.

Competition of simple and complex adoption on interdependent networks

NASA Astrophysics Data System (ADS)

Czaplicka, Agnieszka; Toral, Raul; San Miguel, Maxi

2016-12-01

We consider the competition of two mechanisms for adoption processes: a so-called complex threshold dynamics and a simple susceptible-infected-susceptible (SIS) model. Separately, these mechanisms lead, respectively, to first-order and continuous transitions between nonadoption and adoption phases. We consider two interconnected layers. While all nodes on the first layer follow the complex adoption process, all nodes on the second layer follow the simple adoption process. Coupling between the two adoption processes occurs as a result of the inclusion of some additional interconnections between layers. We find that the transition points and also the nature of the transitions are modified in the coupled dynamics. In the complex adoption layer, the critical threshold required for extension of adoption increases with interlayer connectivity whereas in the case of an isolated single network it would decrease with average connectivity. In addition, the transition can become continuous depending on the detailed interlayer and intralayer connectivities. In the SIS layer, any interlayer connectivity leads to the extension of the adopter phase. Besides, a new transition appears as a sudden drop of the fraction of adopters in the SIS layer. The main numerical findings are described by a mean-field type analytical approach appropriately developed for the threshold-SIS coupled system.

A hybrid continuous-discrete method for stochastic reaction-diffusion processes.

PubMed

Lo, Wing-Cheong; Zheng, Likun; Nie, Qing

2016-09-01

Stochastic fluctuations in reaction-diffusion processes often have substantial effect on spatial and temporal dynamics of signal transductions in complex biological systems. One popular approach for simulating these processes is to divide the system into small spatial compartments assuming that molecules react only within the same compartment and jump between adjacent compartments driven by the diffusion. While the approach is convenient in terms of its implementation, its computational cost may become prohibitive when diffusive jumps occur significantly more frequently than reactions, as in the case of rapid diffusion. Here, we present a hybrid continuous-discrete method in which diffusion is simulated using continuous approximation while reactions are based on the Gillespie algorithm. Specifically, the diffusive jumps are approximated as continuous Gaussian random vectors with time-dependent means and covariances, allowing use of a large time step, even for rapid diffusion. By considering the correlation among diffusive jumps, the approximation is accurate for the second moment of the diffusion process. In addition, a criterion is obtained for identifying the region in which such diffusion approximation is required to enable adaptive calculations for better accuracy. Applications to a linear diffusion system and two nonlinear systems of morphogens demonstrate the effectiveness and benefits of the new hybrid method.

Time-resolved investigations of the non-thermal ablation process of graphite induced by femtosecond laser pulses

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

Kalupka, C., E-mail: christian.kalupka@llt.rwth-aachen.de; Finger, J.; Reininghaus, M.

2016-04-21

We report on the in-situ analysis of the ablation dynamics of the, so-called, laser induced non-thermal ablation process of graphite. A highly oriented pyrolytic graphite is excited by femtosecond laser pulses with fluences below the classic thermal ablation threshold. The ablation dynamics are investigated by axial pump-probe reflection measurements, transversal pump-probe shadowgraphy, and time-resolved transversal emission photography. The combination of the applied analysis methods allows for a continuous and detailed time-resolved observation of the non-thermal ablation dynamics from several picoseconds up to 180 ns. Formation of large, μm-sized particles takes place within the first 3.5 ns after irradiation. The following propagation ofmore » ablation products and the shock wave front are tracked by transversal shadowgraphy up to 16 ns. The comparison of ablation dynamics of different fluences by emission photography reveals thermal ablation products even for non-thermal fluences.« less

Dynamics of non-stationary processes that follow the maximum of the Rényi entropy principle.

PubMed

Shalymov, Dmitry S; Fradkov, Alexander L

2016-01-01

We propose dynamics equations which describe the behaviour of non-stationary processes that follow the maximum Rényi entropy principle. The equations are derived on the basis of the speed-gradient principle originated in the control theory. The maximum of the Rényi entropy principle is analysed for discrete and continuous cases, and both a discrete random variable and probability density function (PDF) are used. We consider mass conservation and energy conservation constraints and demonstrate the uniqueness of the limit distribution and asymptotic convergence of the PDF for both cases. The coincidence of the limit distribution of the proposed equations with the Rényi distribution is examined.

Dynamics of non-stationary processes that follow the maximum of the Rényi entropy principle

PubMed Central

2016-01-01

We propose dynamics equations which describe the behaviour of non-stationary processes that follow the maximum Rényi entropy principle. The equations are derived on the basis of the speed-gradient principle originated in the control theory. The maximum of the Rényi entropy principle is analysed for discrete and continuous cases, and both a discrete random variable and probability density function (PDF) are used. We consider mass conservation and energy conservation constraints and demonstrate the uniqueness of the limit distribution and asymptotic convergence of the PDF for both cases. The coincidence of the limit distribution of the proposed equations with the Rényi distribution is examined. PMID:26997886

Continuous care and patients' basic needs during weaning from mechanical ventilation: A qualitative study.

PubMed

Khalafi, Ali; Elahi, Nasrin; Ahmadi, Fazlollah

2016-12-01

Mechanical ventilation is associated with a number of risks and complications. Thus, rapid and safe weaning from mechanical ventilation is of great importance. Weaning is a complex and challenging process, requiring continuous care and knowledge of the patient. The aim of the present study was to describe the continuous care process during weaning as well as to analyse the facilitators and obstacles to the weaning process from start to finish from the perspective of intensive care unit (ICU) staff, particularly nurses. Twenty-two ICU staff members, including nurses and physicians, and three patients hospitalised in the ICU were enrolled in this qualitative study. Semi-structured interviews were used for data collection and the transcripts were analysed using qualitative content analysis. 'Continuous care' was found to be the patients' basic need during weaning from mechanical ventilation. Uninterrupted, stable, comprehensive and dynamic care and monitoring with immediate response to all physiological and psychological changes were features of continuous care. The three main themes identified by this study were time spent with the patient, comprehensive supervision and maintenance of the quality of care during shifts. Continuous and constant care should be provided during the weaning process. Such care will help to provide health care staff with a deeper understanding of the patient and his or her continuous changes, leading to a timely and favourable response during weaning. To achieve this goal, skill, communication and organisational changes are essential. Copyright © 2016 Elsevier Ltd. All rights reserved.

Mexican American Identity - A Multi-Cultural Legacy.

ERIC Educational Resources Information Center

Stoddard, Ellwyn R.

Investigating the background of Mexican American identify, the document determined that this identity is a dynamic image emerging from a continuous process of human development in which the genetic and cultural variations from European and indigenous peoples are combined within a complex historical situation. The combination includes: (1) the…

How Decisions Evolve: The Temporal Dynamics of Action Selection

ERIC Educational Resources Information Center

Scherbaum, Stefan; Dshemuchadse, Maja; Fischer, Rico; Goschke, Thomas

2010-01-01

To study the process of decision-making under conflict, researchers typically analyze response latency and accuracy. However, these tools provide little evidence regarding how the resolution of conflict unfolds over time. Here, we analyzed the trajectories of mouse movements while participants performed a continuous version of a spatial conflict…

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

Tan, Xiao-Dong; Xu, Yun-Bo, E-mail: yunbo_xu@126.com; Yang, Xiao-Long

Microstructures composed of lath martensite and retained austenite with volume fraction between 8.0 vol.% and 12.0 vol.% were obtained in a low-C low-Si Al-free steel through hot-rolling direct quenching and dynamical partitioning (HDQ&DP) processes. The austenite stabilization mechanism in the low-C low-Si Al-free steel under the special dynamical partitioning processes is investigated by analyzing the carbon partition behavior from martensite to austenite and the carbide precipitation-coarsening behavior in martensite laths combining with the possible hot rolling deformation inheritance. Results show that the satisfying retained austenite amount in currently studied low-Si Al-free HDQ&DP steel is caused by the high-efficiency carbon enrichmentmore » in the 30–80 nm thick regions of austenite near the interfaces in the hot-rolled ultra-fast cooled structure and the avoidance of serious carbides coarsening during the continuous cooling procedures. The excellent strength-elongation product reaching up to 26,000 MPa% shows that the involved HDQ&DP process is a promising method to develop a new generation of advanced high strength steel. - Highlights: • HDQ&DP processes were applied to a low-C low-Si Al-free steel. • Effective partitioning time during the continuous cooling processes is 1–220 s. • Retained austenite with volume fraction between 8.0 vol. % and 12.0 vol. % has been obtained. • The special austenite stabilization mechanism has been expounded.« less

Omega-3 production by fermentation of Yarrowia lipolytica: From fed-batch to continuous.

PubMed

Xie, Dongming; Miller, Edward; Sharpe, Pamela; Jackson, Ethel; Zhu, Quinn

2017-04-01

The omega-3 fatty acid, cis-5,8,11,14,17-eicosapentaenoic acid (C20:5; EPA) has wide-ranging benefits in improving heart health, immune function, and mental health. A sustainable source of EPA production through fermentation of metabolically engineered Yarrowia lipolytica has been developed. In this paper, key fed-batch fermentation conditions were identified to achieve 25% EPA in the yeast biomass, which is so far the highest EPA titer reported in the literature. Dynamic models of the EPA fermentation process were established for analyzing, optimizing, and scaling up the fermentation process. In addition, model simulations were used to develop a two-stage continuous process and compare to single-stage continuous and fed- batch processes. The two stage continuous process, which is equipped with a smaller growth fermentor (Stage 1) and a larger production fermentor (Stage 2), was found to be a superior process to achieve high titer, rate, and yield of EPA. A two-stage continuous fermentation experiment with Y. lipolytica strain Z7334 was designed using the model simulation and then tested in a 2 L and 5 L fermentation system for 1,008 h. Compared with the standard 2 L fed-batch process, the two-stage continuous fermentation process improved the overall EPA productivity by 80% and EPA concentration in the fermenter by 40% while achieving comparable EPA titer in biomass and similar conversion yield from glucose. During the long-term experiment it was also found that the Y. lipolytica strain evolved to reduce byproduct and increase lipid production. This is one of the few continuous fermentation examples that demonstrated improved productivity and concentration of a final product with similar conversion yield compared with a fed-batch process. This paper suggests the two-stage continuous fermentation could be an effective process to achieve improved production of omega-3 and other fermentation products where non-growth or partially growth associated kinetics characterize the process. Biotechnol. Bioeng. 2017;114: 798-812. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

[Homeostasis and Disorder of Musculoskeletal System.Cellular dynamics in musculoskeletal system visualized by intravital imaging techniques.

PubMed

Kikuta, Junichi; Ishii, Masaru

Bone is continually remodeled by bone-resorbing osteoclasts and bone-forming osteoblasts. Although it has long been believed that bone homeostasis is tightly regulated by communication between osteoclasts and osteoblasts, the fundamental process and dynamics have remained elusive. We originally established an advanced imaging system to visualize living bone tissues using intravital two-photon microscopy. By means of this system, we revealed the in vivo behavior of bone-resorbing osteoclasts and bone-forming osteoblasts in bone tissues. This approach facilitates investigation of cellular dynamics in the pathogenesis of musculoskeletal disorders, and would thus be useful for evaluating the efficacy of novel therapeutic agents.

ML-Space: Hybrid Spatial Gillespie and Particle Simulation of Multi-Level Rule-Based Models in Cell Biology.

PubMed

Bittig, Arne T; Uhrmacher, Adelinde M

2017-01-01

Spatio-temporal dynamics of cellular processes can be simulated at different levels of detail, from (deterministic) partial differential equations via the spatial Stochastic Simulation algorithm to tracking Brownian trajectories of individual particles. We present a spatial simulation approach for multi-level rule-based models, which includes dynamically hierarchically nested cellular compartments and entities. Our approach ML-Space combines discrete compartmental dynamics, stochastic spatial approaches in discrete space, and particles moving in continuous space. The rule-based specification language of ML-Space supports concise and compact descriptions of models and to adapt the spatial resolution of models easily.

Analysis of early thrombus dynamics in a humanized mouse laser injury model.

PubMed

Wang, Weiwei; Lindsey, John P; Chen, Jianchun; Diacovo, Thomas G; King, Michael R

2014-01-01

Platelet aggregation and thrombus formation at the site of injury is a dynamic process that involves the continuous addition of new platelets as well as thrombus rupture. In the early stages of hemostasis (within minutes after vessel injury) this process can be visualized by transfusing fluorescently labeled human platelets and observing their deposition and detachment. These two counterbalancing events help the developing thrombus reach a steady-state morphology, where it is large enough to cover the injured vessel surface but not too large to form a severe thrombotic occlusion. In this study, the spatial and temporal aspects of early stage thrombus dynamics which result from laser-induced injury on arterioles of cremaster muscle in the humanized mouse were visualized using fluorescent microscopy. It was found that rolling platelets show preference for the upstream region while tethering/detaching platelets were primarily found downstream. It was also determined that the platelet deposition rate is relatively steady, whereas the effective thrombus coverage area does not increase at a constant rate. By introducing a new method to graphically represent the real time in vivo physiological shear stress environment, we conclude that the thrombus continuously changes shape by regional growth and decay, and neither dominates in the high shear stress region.

Training trajectories by continuous recurrent multilayer networks.

PubMed

Leistritz, L; Galicki, M; Witte, H; Kochs, E

2002-01-01

This paper addresses the problem of training trajectories by means of continuous recurrent neural networks whose feedforward parts are multilayer perceptrons. Such networks can approximate a general nonlinear dynamic system with arbitrary accuracy. The learning process is transformed into an optimal control framework where the weights are the controls to be determined. A training algorithm based upon a variational formulation of Pontryagin's maximum principle is proposed for such networks. Computer examples demonstrating the efficiency of the given approach are also presented.

Nonlinear dynamics and quantum entanglement in optomechanical systems.

PubMed

Wang, Guanglei; Huang, Liang; Lai, Ying-Cheng; Grebogi, Celso

2014-03-21

To search for and exploit quantum manifestations of classical nonlinear dynamics is one of the most fundamental problems in physics. Using optomechanical systems as a paradigm, we address this problem from the perspective of quantum entanglement. We uncover strong fingerprints in the quantum entanglement of two common types of classical nonlinear dynamical behaviors: periodic oscillations and quasiperiodic motion. There is a transition from the former to the latter as an experimentally adjustable parameter is changed through a critical value. Accompanying this process, except for a small region about the critical value, the degree of quantum entanglement shows a trend of continuous increase. The time evolution of the entanglement measure, e.g., logarithmic negativity, exhibits a strong dependence on the nature of classical nonlinear dynamics, constituting its signature.

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.

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.

Cardea: Providing Support for Dynamic Resource Access in a Distributed Computing Environment

NASA Technical Reports Server (NTRS)

Lepro, Rebekah

2003-01-01

The environment framing the modem authorization process span domains of administration, relies on many different authentication sources, and manages complex attributes as part of the authorization process. Cardea facilitates dynamic access control within this environment as a central function of an inter-operable authorization framework. The system departs from the traditional authorization model by separating the authentication and authorization processes, distributing the responsibility for authorization data and allowing collaborating domains to retain control over their implementation mechanisms. Critical features of the system architecture and its handling of the authorization process differentiate the system from existing authorization components by addressing common needs not adequately addressed by existing systems. Continuing system research seeks to enhance the implementation of the current authorization model employed in Cardea, increase the robustness of current features, further the framework for establishing trust and promote interoperability with existing security mechanisms.

[The dual process model of addiction. Towards an integrated model?].

PubMed

Vandermeeren, R; Hebbrecht, M

2012-01-01

Neurobiology and cognitive psychology have provided us with a dual process model of addiction. According to this model, behavior is considered to be the dynamic result of a combination of automatic and controlling processes. In cases of addiction the balance between these two processes is severely disturbed. Automated processes will continue to produce impulses that ensure the continuance of addictive behavior. Weak, reflective or controlling processes are both the reason for and the result of the inability to forgo addiction. To identify features that are common to current neurocognitive insights into addiction and psychodynamic views on addiction. The picture that emerges from research is not clear. There is some evidence that attentional bias has a causal effect on addiction. There is no evidence that automatic associations have a causal effect, but there is some evidence that automatic action-tendencies do have a causal effect. Current neurocognitive views on the dual process model of addiction can be integrated with an evidence-based approach to addiction and with psychodynamic views on addiction.

Accurate hybrid stochastic simulation of a system of coupled chemical or biochemical reactions.

PubMed

Salis, Howard; Kaznessis, Yiannis

2005-02-01

The dynamical solution of a well-mixed, nonlinear stochastic chemical kinetic system, described by the Master equation, may be exactly computed using the stochastic simulation algorithm. However, because the computational cost scales with the number of reaction occurrences, systems with one or more "fast" reactions become costly to simulate. This paper describes a hybrid stochastic method that partitions the system into subsets of fast and slow reactions, approximates the fast reactions as a continuous Markov process, using a chemical Langevin equation, and accurately describes the slow dynamics using the integral form of the "Next Reaction" variant of the stochastic simulation algorithm. The key innovation of this method is its mechanism of efficiently monitoring the occurrences of slow, discrete events while simultaneously simulating the dynamics of a continuous, stochastic or deterministic process. In addition, by introducing an approximation in which multiple slow reactions may occur within a time step of the numerical integration of the chemical Langevin equation, the hybrid stochastic method performs much faster with only a marginal decrease in accuracy. Multiple examples, including a biological pulse generator and a large-scale system benchmark, are simulated using the exact and proposed hybrid methods as well as, for comparison, a previous hybrid stochastic method. Probability distributions of the solutions are compared and the weak errors of the first two moments are computed. In general, these hybrid methods may be applied to the simulation of the dynamics of a system described by stochastic differential, ordinary differential, and Master equations.

Obstructive sleep apnea alters sleep stage transition dynamics.

PubMed

Bianchi, Matt T; Cash, Sydney S; Mietus, Joseph; Peng, Chung-Kang; Thomas, Robert

2010-06-28

Enhanced characterization of sleep architecture, compared with routine polysomnographic metrics such as stage percentages and sleep efficiency, may improve the predictive phenotyping of fragmented sleep. One approach involves using stage transition analysis to characterize sleep continuity. We analyzed hypnograms from Sleep Heart Health Study (SHHS) participants using the following stage designations: wake after sleep onset (WASO), non-rapid eye movement (NREM) sleep, and REM sleep. We show that individual patient hypnograms contain insufficient number of bouts to adequately describe the transition kinetics, necessitating pooling of data. We compared a control group of individuals free of medications, obstructive sleep apnea (OSA), medical co-morbidities, or sleepiness (n = 374) with mild (n = 496) or severe OSA (n = 338). WASO, REM sleep, and NREM sleep bout durations exhibited multi-exponential temporal dynamics. The presence of OSA accelerated the "decay" rate of NREM and REM sleep bouts, resulting in instability manifesting as shorter bouts and increased number of stage transitions. For WASO bouts, previously attributed to a power law process, a multi-exponential decay described the data well. Simulations demonstrated that a multi-exponential process can mimic a power law distribution. OSA alters sleep architecture dynamics by decreasing the temporal stability of NREM and REM sleep bouts. Multi-exponential fitting is superior to routine mono-exponential fitting, and may thus provide improved predictive metrics of sleep continuity. However, because a single night of sleep contains insufficient transitions to characterize these dynamics, extended monitoring of sleep, probably at home, would be necessary for individualized clinical application.

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

PubMed

Giebel, S; Rainer, M

2010-01-01

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

Dynamic, continuous multitasking training leads to task-specific improvements but does not transfer across action selection tasks

NASA Astrophysics Data System (ADS)

Bender, Angela D.; Filmer, Hannah L.; Naughtin, Claire K.; Dux, Paul E.

2017-12-01

The ability to perform multiple tasks concurrently is an ever-increasing requirement in our information-rich world. Despite this, multitasking typically compromises performance due to the processing limitations associated with cognitive control and decision-making. While intensive dual-task training is known to improve multitasking performance, only limited evidence suggests that training-related performance benefits can transfer to untrained tasks that share overlapping processes. In the real world, however, coordinating and selecting several responses within close temporal proximity will often occur in high-interference environments. Over the last decade, there have been notable reports that training on video action games that require dynamic multitasking in a demanding environment can lead to transfer effects on aspects of cognition such as attention and working memory. Here, we asked whether continuous and dynamic multitasking training extends benefits to tasks that are theoretically related to the trained tasks. To examine this issue, we asked a group of participants to train on a combined continuous visuomotor tracking task and a perceptual discrimination task for six sessions, while an active control group practiced the component tasks in isolation. A battery of tests measuring response selection, response inhibition, and spatial attention was administered before and immediately after training to investigate transfer. Multitasking training resulted in substantial, task-specific gains in dual-task ability, but there was no evidence that these benefits generalized to other action control tasks. The findings suggest that training on a combined visuomotor tracking and discrimination task results in task-specific benefits but provides no additional value for untrained action selection tasks.

Time Alignment as a Necessary Step in the Analysis of Sleep Probabilistic Curves

NASA Astrophysics Data System (ADS)

Rošt'áková, Zuzana; Rosipal, Roman

2018-02-01

Sleep can be characterised as a dynamic process that has a finite set of sleep stages during the night. The standard Rechtschaffen and Kales sleep model produces discrete representation of sleep and does not take into account its dynamic structure. In contrast, the continuous sleep representation provided by the probabilistic sleep model accounts for the dynamics of the sleep process. However, analysis of the sleep probabilistic curves is problematic when time misalignment is present. In this study, we highlight the necessity of curve synchronisation before further analysis. Original and in time aligned sleep probabilistic curves were transformed into a finite dimensional vector space, and their ability to predict subjects' age or daily measures is evaluated. We conclude that curve alignment significantly improves the prediction of the daily measures, especially in the case of the S2-related sleep states or slow wave sleep.

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.

SAVA 3: A testbed for integration and control of visual processes

NASA Technical Reports Server (NTRS)

Crowley, James L.; Christensen, Henrik

1994-01-01

The development of an experimental test-bed to investigate the integration and control of perception in a continuously operating vision system is described. The test-bed integrates a 12 axis robotic stereo camera head mounted on a mobile robot, dedicated computer boards for real-time image acquisition and processing, and a distributed system for image description. The architecture was designed to: (1) be continuously operating, (2) integrate software contributions from geographically dispersed laboratories, (3) integrate description of the environment with 2D measurements, 3D models, and recognition of objects, (4) capable of supporting diverse experiments in gaze control, visual servoing, navigation, and object surveillance, and (5) dynamically reconfiguarable.

Use of soil moisture dynamics and patterns for the investigation of runoff generation processes with emphasis on preferential flow

NASA Astrophysics Data System (ADS)

Blume, T.; Zehe, E.; Bronstert, A.

2007-08-01

Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

Use of soil moisture dynamics and patterns at different spatio-temporal scales for the investigation of subsurface flow processes

NASA Astrophysics Data System (ADS)

Blume, T.; Zehe, E.; Bronstert, A.

2009-07-01

Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and binary indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.

Mechanistic modelling of infrared mediated energy transfer during the primary drying step of a continuous freeze-drying process.

PubMed

Van Bockstal, Pieter-Jan; Mortier, Séverine Thérèse F C; De Meyer, Laurens; Corver, Jos; Vervaet, Chris; Nopens, Ingmar; De Beer, Thomas

2017-05-01

Conventional pharmaceutical freeze-drying is an inefficient and expensive batch-wise process, associated with several disadvantages leading to an uncontrolled end product variability. The proposed continuous alternative, based on spinning the vials during freezing and on optimal energy supply during drying, strongly increases process efficiency and improves product quality (uniformity). The heat transfer during continuous drying of the spin frozen vials is provided via non-contact infrared (IR) radiation. The energy transfer to the spin frozen vials should be optimised to maximise the drying efficiency while avoiding cake collapse. Therefore, a mechanistic model was developed which allows computing the optimal, dynamic IR heater temperature in function of the primary drying progress and which, hence, also allows predicting the primary drying endpoint based on the applied dynamic IR heater temperature. The model was validated by drying spin frozen vials containing the model formulation (3.9mL in 10R vials) according to the computed IR heater temperature profile. In total, 6 validation experiments were conducted. The primary drying endpoint was experimentally determined via in-line near-infrared (NIR) spectroscopy and compared with the endpoint predicted by the model (50min). The mean ratio of the experimental drying time to the predicted value was 0.91, indicating a good agreement between the model predictions and the experimental data. The end product had an elegant product appearance (visual inspection) and an acceptable residual moisture content (Karl Fischer). Copyright © 2017 Elsevier B.V. All rights reserved.

Innovative Technics of Managing Engineers’ Global Competencies

NASA Astrophysics Data System (ADS)

Khoreshok, A. A.; Zhironkin, S. A.; Tyulenev, M. A.; Barysheva, G. A.; Blumenstein, V. Yu; Hellmer, M. C.; Potyagailov, S. V.

2016-08-01

Higher education modernization in the CIS countries takes place under the conditions of dynamic changes in economy and society. These changes are determined by the social and economic development of the country and the world globalization processes - cross-border intercultural communication, knowledge transparency, and the establishment of information society. Educational globalization is a continuous process of creating a unified global educational system, in which the distinctions between its member educational systems are being blended.

A study of tumour growth based on stoichiometric principles: a continuous model and its discrete analogue.

PubMed

Saleem, M; Agrawal, Tanuja; Anees, Afzal

2014-01-01

In this paper, we consider a continuous mathematically tractable model and its discrete analogue for the tumour growth. The model formulation is based on stoichiometric principles considering tumour-immune cell interactions in potassium (K (+))-limited environment. Our both continuous and discrete models illustrate 'cancer immunoediting' as a dynamic process having all three phases namely elimination, equilibrium and escape. The stoichiometric principles introduced into the model allow us to study its dynamics with the variation in the total potassium in the surrounding of the tumour region. It is found that an increase in the total potassium may help the patient fight the disease for a longer period of time. This result seems to be in line with the protective role of the potassium against the risk of pancreatic cancer as has been reported by Bravi et al. [Dietary intake of selected micronutrients and risk of pancreatic cancer: An Italian case-control study, Ann. Oncol. 22 (2011), pp. 202-206].

A study of tumour growth based on stoichiometric principles: a continuous model and its discrete analogue

PubMed Central

Saleem, M.; Agrawal, Tanuja; Anees, Afzal

2014-01-01

In this paper, we consider a continuous mathematically tractable model and its discrete analogue for the tumour growth. The model formulation is based on stoichiometric principles considering tumour-immune cell interactions in potassium (K +)-limited environment. Our both continuous and discrete models illustrate ‘cancer immunoediting’ as a dynamic process having all three phases namely elimination, equilibrium and escape. The stoichiometric principles introduced into the model allow us to study its dynamics with the variation in the total potassium in the surrounding of the tumour region. It is found that an increase in the total potassium may help the patient fight the disease for a longer period of time. This result seems to be in line with the protective role of the potassium against the risk of pancreatic cancer as has been reported by Bravi et al. [Dietary intake of selected micronutrients and risk of pancreatic cancer: An Italian case-control study, Ann. Oncol. 22 (2011), pp. 202–206]. PMID:24963981

The dynamic process of adherence to a renal therapeutic regimen: perspectives of patients undergoing continuous ambulatory peritoneal dialysis.

PubMed

Lam, Lai Wah; Lee, Diana T F; Shiu, Ann T Y

2014-06-01

The nature of end-stage renal disease and the need for continuous ambulatory peritoneal dialysis require patients to manage various aspects of the disease, its symptoms and treatment. After attending a training programme, patients are expected to adhere to the renal therapeutic regimen and manage their disease with the knowledge and skills learned. While patients are the stakeholders of their health and related behaviour, their perceptions of adherence and how they adhere to their renal therapeutic regimen remains unexplored. To understand adherence from patients' perspectives and to describe changes in adherence to a therapeutic regimen among patients undergoing continuous ambulatory peritoneal dialysis. This study used a mixed methods design with two phases - a survey in phase I and semi-structured interviews in phase II. This paper presents phase II of the study. The study was conducted at a renal unit of an acute hospital in Hong Kong. Based on the phase I survey results, maximum variation sampling was employed to purposively recruit 36 participants of different genders (18 males, 18 females), ages (35-76 years), and lengths of dialysis experience (11-103 months) for the phase II interviews. Data were collected by tape-recorded semi-structured interviews. Content analysis was employed to analyse the transcribed data. Data collection and analysis were conducted simultaneously. Adherence was a dynamic process with three stages. At the stage of initial adherence, participants attempted to follow instructions but found that strict persistent adherence was impossible. After the first 2-6 months of dialysis, participants entered the stage of subsequent adherence, when they adopted selective adherence through experimenting, monitoring and making continuous adjustments. The stage of long-term adherence commenced after 3-5 years of dialysis, when participants were able to assimilate the modified therapeutic regimen into everyday life. The process of adherence was dynamic as there were fluctuations at each stage of the participants' adherence. With reference to each stage identified, nursing interventions can be developed to help patients achieve smooth transition throughout all the stages. Copyright © 2013 Elsevier Ltd. All rights reserved.

Effects of collision cascade density on radiation defect dynamics in 3C-SiC

PubMed Central

Bayu Aji, L. B.; Wallace, J. B.; Kucheyev, S. O.

2017-01-01

Effects of the collision cascade density on radiation damage in SiC remain poorly understood. Here, we study damage buildup and defect interaction dynamics in 3C-SiC bombarded at 100 °C with either continuous or pulsed beams of 500 keV Ne, Ar, Kr, or Xe ions. We find that bombardment with heavier ions, which create denser collision cascades, results in a decrease in the dynamic annealing efficiency and an increase in both the amorphization cross-section constant and the time constant of dynamic annealing. The cascade density behavior of these parameters is non-linear and appears to be uncorrelated. These results demonstrate clearly (and quantitatively) an important role of the collision cascade density in dynamic radiation defect processes in 3C-SiC. PMID:28304397

Effects of collision cascade density on radiation defect dynamics in 3C-SiC

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

Bayu Aji, L. B.; Wallace, J. B.; Kucheyev, S. O.

Effects of the collision cascade density on radiation damage in SiC remain poorly understood. We study damage buildup and defect interaction dynamics in 3C-SiC bombarded at 100 °C with either continuous or pulsed beams of 500 keV Ne, Ar, Kr, or Xe ions. Here, we find that bombardment with heavier ions, which create denser collision cascades, results in a decrease in the dynamic annealing efficiency and an increase in both the amorphization cross-section constant and the time constant of dynamic annealing. The cascade density behavior of these parameters is non-linear and appears to be uncorrelated. Our results demonstrate clearly (andmore » quantitatively) an important role of the collision cascade density in dynamic radiation defect processes in 3C-SiC.« less

Effects of collision cascade density on radiation defect dynamics in 3C-SiC

DOE PAGES

Bayu Aji, L. B.; Wallace, J. B.; Kucheyev, S. O.

2017-03-17

Effects of the collision cascade density on radiation damage in SiC remain poorly understood. We study damage buildup and defect interaction dynamics in 3C-SiC bombarded at 100 °C with either continuous or pulsed beams of 500 keV Ne, Ar, Kr, or Xe ions. Here, we find that bombardment with heavier ions, which create denser collision cascades, results in a decrease in the dynamic annealing efficiency and an increase in both the amorphization cross-section constant and the time constant of dynamic annealing. The cascade density behavior of these parameters is non-linear and appears to be uncorrelated. Our results demonstrate clearly (andmore » quantitatively) an important role of the collision cascade density in dynamic radiation defect processes in 3C-SiC.« less

Fault tolerant control of multivariable processes using auto-tuning PID controller.

PubMed

Yu, Ding-Li; Chang, T K; Yu, Ding-Wen

2005-02-01

Fault tolerant control of dynamic processes is investigated in this paper using an auto-tuning PID controller. A fault tolerant control scheme is proposed composing an auto-tuning PID controller based on an adaptive neural network model. The model is trained online using the extended Kalman filter (EKF) algorithm to learn system post-fault dynamics. Based on this model, the PID controller adjusts its parameters to compensate the effects of the faults, so that the control performance is recovered from degradation. The auto-tuning algorithm for the PID controller is derived with the Lyapunov method and therefore, the model predicted tracking error is guaranteed to converge asymptotically. The method is applied to a simulated two-input two-output continuous stirred tank reactor (CSTR) with various faults, which demonstrate the applicability of the developed scheme to industrial processes.

Inference for dynamics of continuous variables: the extended Plefka expansion with hidden nodes

NASA Astrophysics Data System (ADS)

Bravi, B.; Sollich, P.

2017-06-01

We consider the problem of a subnetwork of observed nodes embedded into a larger bulk of unknown (i.e. hidden) nodes, where the aim is to infer these hidden states given information about the subnetwork dynamics. The biochemical networks underlying many cellular and metabolic processes are important realizations of such a scenario as typically one is interested in reconstructing the time evolution of unobserved chemical concentrations starting from the experimentally more accessible ones. We present an application to this problem of a novel dynamical mean field approximation, the extended Plefka expansion, which is based on a path integral description of the stochastic dynamics. As a paradigmatic model we study the stochastic linear dynamics of continuous degrees of freedom interacting via random Gaussian couplings. The resulting joint distribution is known to be Gaussian and this allows us to fully characterize the posterior statistics of the hidden nodes. In particular the equal-time hidden-to-hidden variance—conditioned on observations—gives the expected error at each node when the hidden time courses are predicted based on the observations. We assess the accuracy of the extended Plefka expansion in predicting these single node variances as well as error correlations over time, focussing on the role of the system size and the number of observed nodes.

A data driven nonlinear stochastic model for blood glucose dynamics.

PubMed

Zhang, Yan; Holt, Tim A; Khovanova, Natalia

2016-03-01

The development of adequate mathematical models for blood glucose dynamics may improve early diagnosis and control of diabetes mellitus (DM). We have developed a stochastic nonlinear second order differential equation to describe the response of blood glucose concentration to food intake using continuous glucose monitoring (CGM) data. A variational Bayesian learning scheme was applied to define the number and values of the system's parameters by iterative optimisation of free energy. The model has the minimal order and number of parameters to successfully describe blood glucose dynamics in people with and without DM. The model accounts for the nonlinearity and stochasticity of the underlying glucose-insulin dynamic process. Being data-driven, it takes full advantage of available CGM data and, at the same time, reflects the intrinsic characteristics of the glucose-insulin system without detailed knowledge of the physiological mechanisms. We have shown that the dynamics of some postprandial blood glucose excursions can be described by a reduced (linear) model, previously seen in the literature. A comprehensive analysis demonstrates that deterministic system parameters belong to different ranges for diabetes and controls. Implications for clinical practice are discussed. This is the first study introducing a continuous data-driven nonlinear stochastic model capable of describing both DM and non-DM profiles. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

MHD Simulation for Investigating the Dynamic State Transition Responsible for a Solar Eruption in Active Region 12158

NASA Astrophysics Data System (ADS)

Lee, Hwanhee; Magara, Tetsuya

2018-06-01

We present a magnetohydrodynamic model of solar eruption based on the dynamic state transition from the quasi-static state to the eruptive state of an active region (AR) magnetic field. For the quasi-static state before an eruption, we consider the existence of a slow solar wind originating from an AR, which may continuously make the AR magnetic field deviate from mechanical equilibrium. In this model, we perform a three-dimensional magnetohydrodynamic simulation of AR 12158 producing a coronal mass ejection, where the initial magnetic structure of the simulation is given by a nonlinear force-free field derived from an observed photospheric vector magnetic field. We then apply a pressure-driven outflow to the upper part of the magnetic structure to achieve a quasi-static pre-eruptive state. The simulation shows that the eruptive process observed in this AR may be caused by the dynamic state transition of an AR magnetic field, which is essentially different from the destabilization of a static magnetic field. The dynamic state transition is determined from the shape evolution of the magnetic field line according to the κH-mechanism. This work demonstrates how the mechanism works to produce a solar eruption in the dynamic solar corona governed by the gravitational field and the continuous outflows of solar wind.

Parameter prediction based on Improved Process neural network and ARMA error compensation in Evaporation Process

NASA Astrophysics Data System (ADS)

Qian, Xiaoshan

2018-01-01

The traditional model of evaporation process parameters have continuity and cumulative characteristics of the prediction error larger issues, based on the basis of the process proposed an adaptive particle swarm neural network forecasting method parameters established on the autoregressive moving average (ARMA) error correction procedure compensated prediction model to predict the results of the neural network to improve prediction accuracy. Taking a alumina plant evaporation process to analyze production data validation, and compared with the traditional model, the new model prediction accuracy greatly improved, can be used to predict the dynamic process of evaporation of sodium aluminate solution components.

Quantification of terrestrial ecosystem carbon dynamics in the conterminous United States combining a process-based biogeochemical model and MODIS and AmeriFlux data

USDA-ARS?s Scientific Manuscript database

Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynami...

Early Boost and Slow Consolidation in Motor Skill Learning

ERIC Educational Resources Information Center

Hotermans, Christophe; Peigneux, Philippe; de Noordhout, Alain Maertens; Moonen, Gustave; Maquet, Pierre

2006-01-01

Motor skill learning is a dynamic process that continues covertly after training has ended and eventually leads to delayed increments in performance. Current theories suggest that this off-line improvement takes time and appears only after several hours. Here we show an early transient and short-lived boost in performance, emerging as early as…

Understanding Physiological and Degenerative Natural Vision Mechanisms to Define Contrast and Contour Operators

PubMed Central

Demongeot, Jacques; Fouquet, Yannick; Tayyab, Muhammad; Vuillerme, Nicolas

2009-01-01

Background Dynamical systems like neural networks based on lateral inhibition have a large field of applications in image processing, robotics and morphogenesis modeling. In this paper, we will propose some examples of dynamical flows used in image contrasting and contouring. Methodology First we present the physiological basis of the retina function by showing the role of the lateral inhibition in the optical illusions and pathologic processes generation. Then, based on these biological considerations about the real vision mechanisms, we study an enhancement method for contrasting medical images, using either a discrete neural network approach, or its continuous version, i.e. a non-isotropic diffusion reaction partial differential system. Following this, we introduce other continuous operators based on similar biomimetic approaches: a chemotactic contrasting method, a viability contouring algorithm and an attentional focus operator. Then, we introduce the new notion of mixed potential Hamiltonian flows; we compare it with the watershed method and we use it for contouring. Conclusions We conclude by showing the utility of these biomimetic methods with some examples of application in medical imaging and computed assisted surgery. PMID:19547712

Dynamics of the microbial community during continuous methane fermentation in continuously stirred tank reactors.

PubMed

Tang, Yue-Qin; Shigematsu, Toru; Morimura, Shigeru; Kida, Kenji

2015-04-01

Methane fermentation is an attractive technology for the treatment of organic wastes and wastewaters. However, the process is difficult to control, and treatment rates and digestion efficiency require further optimization. Understanding the microbiology mechanisms of methane fermentation is of fundamental importance to improving this process. In this review, we summarize the dynamics of microbial communities in methane fermentation chemostats that are operated using completely stirred tank reactors (CSTRs). Each chemostat was supplied with one substrate as the sole carbon source. The substrates include acetate, propionate, butyrate, long-chain fatty acids, glycerol, protein, glucose, and starch. These carbon sources are general substrates and intermediates of methane fermentation. The factors that affect the structure of the microbial community are discussed. The carbon source, the final product, and the operation conditions appear to be the main factors that affect methane fermentation and determine the structure of the microbial community. Understanding the structure of the microbial community during methane fermentation will guide the design and operation of practical wastewater treatments. Copyright © 2014 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Consequences of nonclassical measurement for the algorithmic description of continuous dynamical systems

NASA Technical Reports Server (NTRS)

Fields, Chris

1989-01-01

Continuous dynamical systems intuitively seem capable of more complex behavior than discrete systems. If analyzed in the framework of the traditional theory of computation, a continuous dynamical system with countably many quasistable states has at least the computational power of a universal Turing machine. Such an analysis assumes, however, the classical notion of measurement. If measurement is viewed nonclassically, a continuous dynamical system cannot, even in principle, exhibit behavior that cannot be simulated by a universal Turing machine.

Consequences of nonclassical measurement for the algorithmic description of continuous dynamical systems

NASA Technical Reports Server (NTRS)

Fields, Chris

1989-01-01

Continuous dynamical systems intuitively seem capable of more complex behavior than discrete systems. If analyzed in the framework of the traditional theory of computation, a continuous dynamical system with countablely many quasistable states has at least the computational power of a universal Turing machine. Such an analyses assumes, however, the classical notion of measurement. If measurement is viewed nonclassically, a continuous dynamical system cannot, even in principle, exhibit behavior that cannot be simulated by a universal Turing machine.

Simulation-Based Prediction of Equivalent Continuous Noises during Construction Processes

PubMed Central

Zhang, Hong; Pei, Yun

2016-01-01

Quantitative prediction of construction noise is crucial to evaluate construction plans to help make decisions to address noise levels. Considering limitations of existing methods for measuring or predicting the construction noise and particularly the equivalent continuous noise level over a period of time, this paper presents a discrete-event simulation method for predicting the construction noise in terms of equivalent continuous level. The noise-calculating models regarding synchronization, propagation and equivalent continuous level are presented. The simulation framework for modeling the noise-affected factors and calculating the equivalent continuous noise by incorporating the noise-calculating models into simulation strategy is proposed. An application study is presented to demonstrate and justify the proposed simulation method in predicting the equivalent continuous noise during construction. The study contributes to provision of a simulation methodology to quantitatively predict the equivalent continuous noise of construction by considering the relevant uncertainties, dynamics and interactions. PMID:27529266

Simulation-Based Prediction of Equivalent Continuous Noises during Construction Processes.

PubMed

Zhang, Hong; Pei, Yun

2016-08-12

Quantitative prediction of construction noise is crucial to evaluate construction plans to help make decisions to address noise levels. Considering limitations of existing methods for measuring or predicting the construction noise and particularly the equivalent continuous noise level over a period of time, this paper presents a discrete-event simulation method for predicting the construction noise in terms of equivalent continuous level. The noise-calculating models regarding synchronization, propagation and equivalent continuous level are presented. The simulation framework for modeling the noise-affected factors and calculating the equivalent continuous noise by incorporating the noise-calculating models into simulation strategy is proposed. An application study is presented to demonstrate and justify the proposed simulation method in predicting the equivalent continuous noise during construction. The study contributes to provision of a simulation methodology to quantitatively predict the equivalent continuous noise of construction by considering the relevant uncertainties, dynamics and interactions.

Characterization of high-intensity, long-duration continuous auroral activity (HILDCAA) events using recurrence quantification analysis

NASA Astrophysics Data System (ADS)

Mendes, Odim; Oliveira Domingues, Margarete; Echer, Ezequiel; Hajra, Rajkumar; Everton Menconi, Varlei

2017-08-01

Considering the magnetic reconnection and the viscous interaction as the fundamental mechanisms for transfer particles and energy into the magnetosphere, we study the dynamical characteristics of auroral electrojet (AE) index during high-intensity, long-duration continuous auroral activity (HILDCAA) events, using a long-term geomagnetic database (1975-2012), and other distinct interplanetary conditions (geomagnetically quiet intervals, co-rotating interaction regions (CIRs)/high-speed streams (HSSs) not followed by HILDCAAs, and events of AE comprised in global intense geomagnetic disturbances). It is worth noting that we also study active but non-HILDCAA intervals. Examining the geomagnetic AE index, we apply a dynamics analysis composed of the phase space, the recurrence plot (RP), and the recurrence quantification analysis (RQA) methods. As a result, the quantification finds two distinct clusterings of the dynamical behaviours occurring in the interplanetary medium: one regarding a geomagnetically quiet condition regime and the other regarding an interplanetary activity regime. Furthermore, the HILDCAAs seem unique events regarding a visible, intense manifestations of interplanetary Alfvénic waves; however, they are similar to the other kinds of conditions regarding a dynamical signature (based on RQA), because it is involved in the same complex mechanism of generating geomagnetic disturbances. Also, by characterizing the proper conditions of transitions from quiescent conditions to weaker geomagnetic disturbances inside the magnetosphere and ionosphere system, the RQA method indicates clearly the two fundamental dynamics (geomagnetically quiet intervals and HILDCAA events) to be evaluated with magneto-hydrodynamics simulations to understand better the critical processes related to energy and particle transfer into the magnetosphere-ionosphere system. Finally, with this work, we have also reinforced the potential applicability of the RQA method for characterizing nonlinear geomagnetic processes related to the magnetic reconnection and the viscous interaction affecting the magnetosphere.

Dynamic peptide libraries for the discovery of supramolecular nanomaterials

NASA Astrophysics Data System (ADS)

Pappas, Charalampos G.; Shafi, Ramim; Sasselli, Ivan R.; Siccardi, Henry; Wang, Tong; Narang, Vishal; Abzalimov, Rinat; Wijerathne, Nadeesha; Ulijn, Rein V.

2016-11-01

Sequence-specific polymers, such as oligonucleotides and peptides, can be used as building blocks for functional supramolecular nanomaterials. The design and selection of suitable self-assembling sequences is, however, challenging because of the vast combinatorial space available. Here we report a methodology that allows the peptide sequence space to be searched for self-assembling structures. In this approach, unprotected homo- and heterodipeptides (including aromatic, aliphatic, polar and charged amino acids) are subjected to continuous enzymatic condensation, hydrolysis and sequence exchange to create a dynamic combinatorial peptide library. The free-energy change associated with the assembly process itself gives rise to selective amplification of self-assembling candidates. By changing the environmental conditions during the selection process, different sequences and consequent nanoscale morphologies are selected.

Dynamic peptide libraries for the discovery of supramolecular nanomaterials.

PubMed

Pappas, Charalampos G; Shafi, Ramim; Sasselli, Ivan R; Siccardi, Henry; Wang, Tong; Narang, Vishal; Abzalimov, Rinat; Wijerathne, Nadeesha; Ulijn, Rein V

2016-11-01

Sequence-specific polymers, such as oligonucleotides and peptides, can be used as building blocks for functional supramolecular nanomaterials. The design and selection of suitable self-assembling sequences is, however, challenging because of the vast combinatorial space available. Here we report a methodology that allows the peptide sequence space to be searched for self-assembling structures. In this approach, unprotected homo- and heterodipeptides (including aromatic, aliphatic, polar and charged amino acids) are subjected to continuous enzymatic condensation, hydrolysis and sequence exchange to create a dynamic combinatorial peptide library. The free-energy change associated with the assembly process itself gives rise to selective amplification of self-assembling candidates. By changing the environmental conditions during the selection process, different sequences and consequent nanoscale morphologies are selected.

In Situ Stoichiometry in a Large River: Continuous Measurement of Doc, NO3 and PO4 in the Sacramento River

NASA Astrophysics Data System (ADS)

Downing, B. D.; Pellerin, B. A.; Bergamaschi, B. A.; Saraceno, J.

2011-12-01

Studying controls on geochemical processes in rivers and streams is difficult because concentration and composition often changes rapidly in response to physical and biological forcings. Understanding biogeochemical dynamics in rivers will improve current understanding of the role of watershed sources to carbon cycling, river and stream ecology, and loads to estuaries and oceans. Continuous measurements of dissolved organic carbon (DOC), nitrate (NO3-) and soluble reactive phosphate (SRP) concentrations are now possible, along with some information about DOC composition. In situ sensors designed to measure these constituents provide high frequency, real-time data that can elucidate hydrologic and biogeochemical controls which are difficult to detect using more traditional sampling approaches. Here we present a coupled approach, using in situ optical instrumentation with discharge measurements to provide quantitative estimates of constituent loads to investigate C, NO3- and SRP sources and processing in the Sacramento River, CA, USA. Continuous measurement of DOC concentration was conducted by use of a miniature in situ fluorometer (Turner Designs Cyclops) designed to measure chromophoric dissolved organic matter fluorescence (FDOM) over the course of an entire year. Nitrate was measured concurrently using a Satlantic SUNA and phosphate was measured using a WETLabs model Cycle-P instrument for a two week period in July 2011. Continuous measurement from these instruments paired with continuous measurement of physical water quality variables such as temperature, pH, specific conductance, dissolved oxygen, and turbidity, were used to investigate physical and chemical dynamics of DOC, NO3-, SRP over varying time scales. Deploying these instruments at pre-existing USGS discharge gages allowed for calculation of instantaneous and integrated constituent fluxes, as well as filling in gaps in our understanding biogeochemical processes and transport. Results from the study show that diurnal, event driven and seasonal changes are key to calculating accurate watershed fluxes and detecting transient sources of DOC, NO3- and SRP.

Nonlinear Light Dynamics in Multi-Core Structures

DTIC Science & Technology

2017-02-27

be generated in continuous- discrete optical media such as multi-core optical fiber or waveguide arrays; localisation dynamics in a continuous... discrete nonlinear system. Detailed theoretical analysis is presented of the existence and stability of the discrete -continuous light bullets using a very...and pulse compression using wave collapse (self-focusing) energy localisation dynamics in a continuous- discrete nonlinear system, as implemented in a

Where do we stand after twenty years of dynamic triggering studies? (Invited)

NASA Astrophysics Data System (ADS)

Prejean, S. G.; Hill, D. P.

2013-12-01

In the past two decades, remote dynamic triggering of earthquakes by other earthquakes has been explored in a variety of physical environments with a wide array of observation and modeling techniques. These studies have significantly refined our understanding of the state of the crust and the physical conditions controlling earthquake nucleation. Despite an ever growing database of dynamic triggering observations, significant uncertainties remain and vigorous debate in almost all aspects of the science continues. For example, although dynamic earthquake triggering can occur with peak dynamic stresses as small as 1 kPa, triggering thresholds and their dependence on local stress state, hydrological environment, and frictional properties of faults are not well understood. Some studies find a simple threshold based on the peak amplitude of shaking while others find dependencies on frequency, recharge time, and other parameters. Considerable debate remains over the range of physical processes responsible for dynamic triggering, and the wide variation in dynamic triggering responses and time scales suggests triggering by multiple physical processes. Although Coulomb shear failure with various friction laws can often explain dynamic triggering, particularly instantaneous triggering, delayed dynamic triggering may be dependent on fluid transport and other slowly evolving aseismic processes. Although our understanding of the global distribution of dynamic triggering has improved, it is far from complete due to spatially uneven monitoring. A major challenge involves establishing statistical significance of potentially triggered earthquakes, particularly if they are isolated events or time-delayed with respect to triggering stresses. Here we highlight these challenges and opportunities with existing data. We focus on environmental dependence of dynamic triggering by large remote earthquakes particularly in volcanic and geothermal systems, as these systems often have high rates of background seismicity. In many volcanic and geothermal systems, such as the Geysers in Northern California, dynamic triggering of micro-earthquakes is frequent and predictable. In contrast, most active and even erupting volcanoes in Alaska (with the exception of the Katmai Volcanic Cluster) do not experience dynamic triggering. We explore why.

Parallel steady state studies on a milliliter scale accelerate fed-batch bioprocess design for recombinant protein production with Escherichia coli.

PubMed

Schmideder, Andreas; Cremer, Johannes H; Weuster-Botz, Dirk

2016-11-01

In general, fed-batch processes are applied for recombinant protein production with Escherichia coli (E. coli). However, state of the art methods for identifying suitable reaction conditions suffer from severe drawbacks, i.e. direct transfer of process information from parallel batch studies is often defective and sequential fed-batch studies are time-consuming and cost-intensive. In this study, continuously operated stirred-tank reactors on a milliliter scale were applied to identify suitable reaction conditions for fed-batch processes. Isopropyl β-d-1-thiogalactopyranoside (IPTG) induction strategies were varied in parallel-operated stirred-tank bioreactors to study the effects on the continuous production of the recombinant protein photoactivatable mCherry (PAmCherry) with E. coli. Best-performing induction strategies were transferred from the continuous processes on a milliliter scale to liter scale fed-batch processes. Inducing recombinant protein expression by dynamically increasing the IPTG concentration to 100 µM led to an increase in the product concentration of 21% (8.4 g L -1 ) compared to an implemented high-performance production process with the most frequently applied induction strategy by a single addition of 1000 µM IPGT. Thus, identifying feasible reaction conditions for fed-batch processes in parallel continuous studies on a milliliter scale was shown to be a powerful, novel method to accelerate bioprocess design in a cost-reducing manner. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1426-1435, 2016. © 2016 American Institute of Chemical Engineers.

Neuromorphic Learning From Noisy Data

NASA Technical Reports Server (NTRS)

Merrill, Walter C.; Troudet, Terry

1993-01-01

Two reports present numerical study of performance of feedforward neural network trained by back-propagation algorithm in learning continuous-valued mappings from data corrupted by noise. Two types of noise considered: plant noise which affects dynamics of controlled process and data-processing noise, which occurs during analog processing and digital sampling of signals. Study performed with view toward use of neural networks as neurocontrollers to substitute for, or enhance, performances of human experts in controlling mechanical devices in presence of sensor and actuator noise and to enhance performances of more-conventional digital feedback electronic process controllers in noisy environments.

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.

A stochastic agent-based model of pathogen propagation in dynamic multi-relational social networks

PubMed Central

Khan, Bilal; Dombrowski, Kirk; Saad, Mohamed

2015-01-01

We describe a general framework for modeling and stochastic simulation of epidemics in realistic dynamic social networks, which incorporates heterogeneity in the types of individuals, types of interconnecting risk-bearing relationships, and types of pathogens transmitted across them. Dynamism is supported through arrival and departure processes, continuous restructuring of risk relationships, and changes to pathogen infectiousness, as mandated by natural history; dynamism is regulated through constraints on the local agency of individual nodes and their risk behaviors, while simulation trajectories are validated using system-wide metrics. To illustrate its utility, we present a case study that applies the proposed framework towards a simulation of HIV in artificial networks of intravenous drug users (IDUs) modeled using data collected in the Social Factors for HIV Risk survey. PMID:25859056

Intermittent dynamics in complex systems driven to depletion.

PubMed

Escobar, Juan V; Pérez Castillo, Isaac

2018-03-19

When complex systems are driven to depletion by some external factor, their non-stationary dynamics can present an intermittent behaviour between relative tranquility and burst of activity whose consequences are often catastrophic. To understand and ultimately be able to predict such dynamics, we propose an underlying mechanism based on sharp thresholds of a local generalized energy density that naturally leads to negative feedback. We find a transition from a continuous regime to an intermittent one, in which avalanches can be predicted despite the stochastic nature of the process. This model may have applications in many natural and social complex systems where a rapid depletion of resources or generalized energy drives the dynamics. In particular, we show how this model accurately describes the time evolution and avalanches present in a real social system.

The dynamics of team cognition: A process-oriented theory of knowledge emergence in teams.

PubMed

Grand, James A; Braun, Michael T; Kuljanin, Goran; Kozlowski, Steve W J; Chao, Georgia T

2016-10-01

Team cognition has been identified as a critical component of team performance and decision-making. However, theory and research in this domain continues to remain largely static; articulation and examination of the dynamic processes through which collectively held knowledge emerges from the individual- to the team-level is lacking. To address this gap, we advance and systematically evaluate a process-oriented theory of team knowledge emergence. First, we summarize the core concepts and dynamic mechanisms that underlie team knowledge-building and represent our theory of team knowledge emergence (Step 1). We then translate this narrative theory into a formal computational model that provides an explicit specification of how these core concepts and mechanisms interact to produce emergent team knowledge (Step 2). The computational model is next instantiated into an agent-based simulation to explore how the key generative process mechanisms described in our theory contribute to improved knowledge emergence in teams (Step 3). Results from the simulations demonstrate that agent teams generate collectively shared knowledge more effectively when members are capable of processing information more efficiently and when teams follow communication strategies that promote equal rates of information sharing across members. Lastly, we conduct an empirical experiment with real teams participating in a collective knowledge-building task to verify that promoting these processes in human teams also leads to improved team knowledge emergence (Step 4). Discussion focuses on implications of the theory for examining team cognition processes and dynamics as well as directions for future research. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Continuous-Time Random Walk with multi-step memory: an application to market dynamics

NASA Astrophysics Data System (ADS)

Gubiec, Tomasz; Kutner, Ryszard

2017-11-01

An extended version of the Continuous-Time Random Walk (CTRW) model with memory is herein developed. This memory involves the dependence between arbitrary number of successive jumps of the process while waiting times between jumps are considered as i.i.d. random variables. This dependence was established analyzing empirical histograms for the stochastic process of a single share price on a market within the high frequency time scale. Then, it was justified theoretically by considering bid-ask bounce mechanism containing some delay characteristic for any double-auction market. Our model appeared exactly analytically solvable. Therefore, it enables a direct comparison of its predictions with their empirical counterparts, for instance, with empirical velocity autocorrelation function. Thus, the present research significantly extends capabilities of the CTRW formalism. Contribution to the Topical Issue "Continuous Time Random Walk Still Trendy: Fifty-year History, Current State and Outlook", edited by Ryszard Kutner and Jaume Masoliver.

Wrapping with a splash: High-speed encapsulation with ultrathin sheets

NASA Astrophysics Data System (ADS)

Kumar, Deepak; Paulsen, Joseph D.; Russell, Thomas P.; Menon, Narayanan

2018-02-01

Many complex fluids rely on surfactants to contain, protect, or isolate liquid drops in an immiscible continuous phase. Thin elastic sheets can wrap liquid drops in a spontaneous process driven by capillary forces. For encapsulation by sheets to be practically viable, a rapid, continuous, and scalable process is essential. We exploit the fast dynamics of droplet impact to achieve wrapping of oil droplets by ultrathin polymer films in a water phase. Despite the violence of splashing events, the process robustly yields wrappings that are optimally shaped to maximize the enclosed fluid volume and have near-perfect seams. We achieve wrappings of targeted three-dimensional (3D) shapes by tailoring the 2D boundary of the films and show the generality of the technique by producing both oil-in-water and water-in-oil wrappings.

A hybrid continuous-discrete method for stochastic reaction–diffusion processes

PubMed Central

Zheng, Likun; Nie, Qing

2016-01-01

Stochastic fluctuations in reaction–diffusion processes often have substantial effect on spatial and temporal dynamics of signal transductions in complex biological systems. One popular approach for simulating these processes is to divide the system into small spatial compartments assuming that molecules react only within the same compartment and jump between adjacent compartments driven by the diffusion. While the approach is convenient in terms of its implementation, its computational cost may become prohibitive when diffusive jumps occur significantly more frequently than reactions, as in the case of rapid diffusion. Here, we present a hybrid continuous-discrete method in which diffusion is simulated using continuous approximation while reactions are based on the Gillespie algorithm. Specifically, the diffusive jumps are approximated as continuous Gaussian random vectors with time-dependent means and covariances, allowing use of a large time step, even for rapid diffusion. By considering the correlation among diffusive jumps, the approximation is accurate for the second moment of the diffusion process. In addition, a criterion is obtained for identifying the region in which such diffusion approximation is required to enable adaptive calculations for better accuracy. Applications to a linear diffusion system and two nonlinear systems of morphogens demonstrate the effectiveness and benefits of the new hybrid method. PMID:27703710

Self-organizing biopsychosocial dynamics and the patient-healer relationship.

PubMed

Pincus, David

2012-01-01

The patient-healer relationship has an increasing area of interest for complementary and alternative medicine (CAM) researchers. This focus on the interpersonal context of treatment is not surprising as dismantling studies, clinical trials and other linear research designs continually point toward the critical role of context and the broadband biopsychosocial nature of therapeutic responses to CAM. Unfortunately, the same traditional research models and methods that fail to find simple and specific treatment-outcome relations are similarly failing to find simple and specific mechanisms to explain how interpersonal processes influence patient outcomes. This paper presents an overview of some of the key models and methods from nonlinear dynamical systems that are better equipped for empirical testing of CAM outcomes on broadband biopsychosocial processes. Suggestions are made for CAM researchers to assist in modeling the interactions among key process dynamics interacting across biopsychosocial scales: empathy, intra-psychic conflict, physiological arousal, and leukocyte telomerase activity. Finally, some speculations are made regarding the possibility for deeper cross-scale information exchange involving quantum temporal nonlocality. Copyright © 2012 S. Karger AG, Basel.

Modelling social interaction as perceptual crossing: an investigation into the dynamics of the interaction process

NASA Astrophysics Data System (ADS)

Froese, Tom; Di Paolo, Ezequiel A.

2010-03-01

This paper continues efforts to establish a mutually informative dialogue between psychology and evolutionary robotics in order to investigate the dynamics of social interaction. We replicate a recent simulation model of a minimalist experiment in perceptual crossing and confirm the results with significantly simpler artificial agents. A series of psycho-physical tests of their behaviour informs a hypothetical circuit model of their internal operation. However, a detailed study of the actual internal dynamics reveals this circuit model to be unfounded, thereby offering a tale of caution for those hypothesising about sub-personal processes in terms of behavioural observations. In particular, it is shown that the behaviour of the agents largely emerges out of the interaction process itself rather than being an individual achievement alone. We also extend the original simulation model in two novel directions in order to test further the extent to which perceptual crossing between agents can self-organise in a robust manner. These modelling results suggest new hypotheses that can become the basis for further psychological experiments.

Modeling of larch forest dynamics under a changing climate in eastern Siberia

NASA Astrophysics Data System (ADS)

Nakai, T.; Kumagai, T.; Iijima, Y.; Ohta, T.; Kotani, A.; Maximov, T. C.; Hiyama, T.

2017-12-01

According to the projection by an earth system model under RCP8.5 scenario, boreal forest in eastern Siberia (near Yakutsk) is predicted to experience significant changes in climate, in which the mean annual air temperature is projected to be positive and the annual precipitation will be doubled by the end of 21st century. Since the forest in this region is underlain by continuous permafrost, both increasing temperature and precipitation can affect the dynamics of forest through the soil water processes. To investigate such effects, we adopted a newly developed terrestrial ecosystem dynamics model named S-TEDy (SEIB-DGVM-originated Terrestrial Ecosystem Dynamics model), which mechanistically simulates "the way of life" of each individual tree and resulting tree mortality under the future climate conditions. This model was first developed for the simulation of the dynamics of a tropical rainforest in the Borneo Island, and successfully reproduced higher mortality of large trees due to a prolonged drought induced by ENSO event of 1997-1998. To apply this model to a larch forest in eastern Siberia, we are developing a soil submodel to consider the effect of thawing-freezing processes. We will present a simulation results using the future climate projection.

Software process improvement in the NASA software engineering laboratory

NASA Technical Reports Server (NTRS)

Mcgarry, Frank; Pajerski, Rose; Page, Gerald; Waligora, Sharon; Basili, Victor; Zelkowitz, Marvin

1994-01-01

The Software Engineering Laboratory (SEL) was established in 1976 for the purpose of studying and measuring software processes with the intent of identifying improvements that could be applied to the production of ground support software within the Flight Dynamics Division (FDD) at the National Aeronautics and Space Administration (NASA)/Goddard Space Flight Center (GSFC). The SEL has three member organizations: NASA/GSFC, the University of Maryland, and Computer Sciences Corporation (CSC). The concept of process improvement within the SEL focuses on the continual understanding of both process and product as well as goal-driven experimentation and analysis of process change within a production environment.

Two-time scale subordination in physical processes with long-term memory

NASA Astrophysics Data System (ADS)

Stanislavsky, Aleksander; Weron, Karina

2008-03-01

We describe dynamical processes in continuous media with a long-term memory. Our consideration is based on a stochastic subordination idea and concerns two physical examples in detail. First we study a temporal evolution of the species concentration in a trapping reaction in which a diffusing reactant is surrounded by a sea of randomly moving traps. The analysis uses the random-variable formalism of anomalous diffusive processes. We find that the empirical trapping-reaction law, according to which the reactant concentration decreases in time as a product of an exponential and a stretched exponential function, can be explained by a two-time scale subordination of random processes. Another example is connected with a state equation for continuous media with memory. If the pressure and the density of a medium are subordinated in two different random processes, then the ordinary state equation becomes fractional with two-time scales. This allows one to arrive at the Bagley-Torvik type of state equation.

Studying dynamic processes in liquids by TEM/STEM/DTEM

NASA Astrophysics Data System (ADS)

Abellan, Patricia; Evans, James; Woehl, Taylor; Jungjohann, Katherine; Parent, Lucas; Arslan, Ilke; Ristenpart, William; Browning, Nigel; Mater. Sci. Group Team; Microsc. Group Team; Catal. Sci. Group Collaboration; Ristenpart Res. Group Collaboration

2013-03-01

In order to study dynamic phenomena such as corrosion or catalysis, extreme environmental conditions must be reproduced around the specimen - these include high-temperatures, high-pressures, specific oxidizing/reducing atmospheres or a liquid environment. The use of environmental stages specifically designed to fit in any transmission electron microscope (TEM) allows us to apply the distinct capabilities of each instrument to study dynamic processes. Localized gas/fluid conditions are created around the sample and separated from the high vacuum inside the microscope using hermetically sealed windowed-cells. Advanced capabilities of these techniques include spatial resolutions of ~1 Angstrom or better in aberration corrected instruments or temporal resolutions in the microsecond-nanosecond range in a dynamic TEM (DTEM). Here, unique qualities of the DTEM that benefit the in-situ experiments with gas/fluid environmental cells will be discussed. We also present our results with a liquid stage allowing atomic resolution imaging of nanomaterials in a colloidal suspension, core EEL spectra acquisition, continuous flow, controlled growth of nanocrystals and systematic calibration of the effect of the electron dose on silver nuclei formation.

A heuristic method for consumable resource allocation in multi-class dynamic PERT networks

NASA Astrophysics Data System (ADS)

Yaghoubi, Saeed; Noori, Siamak; Mazdeh, Mohammad Mahdavi

2013-06-01

This investigation presents a heuristic method for consumable resource allocation problem in multi-class dynamic Project Evaluation and Review Technique (PERT) networks, where new projects from different classes (types) arrive to system according to independent Poisson processes with different arrival rates. Each activity of any project is operated at a devoted service station located in a node of the network with exponential distribution according to its class. Indeed, each project arrives to the first service station and continues its routing according to precedence network of its class. Such system can be represented as a queuing network, while the discipline of queues is first come, first served. On the basis of presented method, a multi-class system is decomposed into several single-class dynamic PERT networks, whereas each class is considered separately as a minisystem. In modeling of single-class dynamic PERT network, we use Markov process and a multi-objective model investigated by Azaron and Tavakkoli-Moghaddam in 2007. Then, after obtaining the resources allocated to service stations in every minisystem, the final resources allocated to activities are calculated by the proposed method.

Complex systems dynamics in aging: new evidence, continuing questions.

PubMed

Cohen, Alan A

2016-02-01

There have long been suggestions that aging is tightly linked to the complex dynamics of the physiological systems that maintain homeostasis, and in particular to dysregulation of regulatory networks of molecules. This review synthesizes recent work that is starting to provide evidence for the importance of such complex systems dynamics in aging. There is now clear evidence that physiological dysregulation--the gradual breakdown in the capacity of complex regulatory networks to maintain homeostasis--is an emergent property of these regulatory networks, and that it plays an important role in aging. It can be measured simply using small numbers of biomarkers. Additionally, there are indications of the importance during aging of emergent physiological processes, functional processes that cannot be easily understood through clear metabolic pathways, but can nonetheless be precisely quantified and studied. The overall role of such complex systems dynamics in aging remains an important open question, and to understand it future studies will need to distinguish and integrate related aspects of aging research, including multi-factorial theories of aging, systems biology, bioinformatics, network approaches, robustness, and loss of complexity.

Mirroring and beyond: coupled dynamics as a generalized framework for modelling social interactions

PubMed Central

Hasson, Uri; Frith, Chris D.

2016-01-01

When people observe one another, behavioural alignment can be detected at many levels, from the physical to the mental. Likewise, when people process the same highly complex stimulus sequences, such as films and stories, alignment is detected in the elicited brain activity. In early sensory areas, shared neural patterns are coupled to the low-level properties of the stimulus (shape, motion, volume, etc.), while in high-order brain areas, shared neural patterns are coupled to high-levels aspects of the stimulus, such as meaning. Successful social interactions require such alignments (both behavioural and neural), as communication cannot occur without shared understanding. However, we need to go beyond simple, symmetric (mirror) alignment once we start interacting. Interactions are dynamic processes, which involve continuous mutual adaptation, development of complementary behaviour and division of labour such as leader–follower roles. Here, we argue that interacting individuals are dynamically coupled rather than simply aligned. This broader framework for understanding interactions can encompass both processes by which behaviour and brain activity mirror each other (neural alignment), and situations in which behaviour and brain activity in one participant are coupled (but not mirrored) to the dynamics in the other participant. To apply these more sophisticated accounts of social interactions to the study of the underlying neural processes we need to develop new experimental paradigms and novel methods of data analysis PMID:27069044

How decisions emerge: action dynamics in intertemporal decision making.

PubMed

Dshemuchadse, Maja; Scherbaum, Stefan; Goschke, Thomas

2013-02-01

In intertemporal decision making, individuals prefer smaller rewards delivered sooner over larger rewards delivered later, often to an extent that seems irrational from an economical perspective. This behavior has been attributed to a lack of self-control and reflection, the nonlinearity of human time perception, and several other sources. Although an increasing number of models propose different mathematical descriptions of temporal discounting, the dynamics of the decision process behind temporal discounting are much less clear. In this study, we obtained further insights into the mechanisms of intertemporal decisions by observing choice action dynamics via a novel combination of continuously recorded mouse movements and a multiple regression approach. Participants had to choose between two hypothetical options (sooner/smaller vs. later/larger) by moving the mouse cursor from the bottom of the screen either to the top left or to the top right. We observed less direct mouse movements when participants chose later/larger rewards, indicating that participants had to overcome the attraction of the sooner/smaller reward first. Additionally, our results suggest that framing time information differently changes the weighting of value. We conclude that using a continuous process-oriented approach could further advance the understanding of intertemporal choice beyond the identification of the best fitted mathematical description of the discounting function by uncovering the way intertemporal decisions are performed. 2013 APA, all rights reserved

Microbiota Dynamics Associated with Environmental Conditions and Potential Roles of Cellulolytic Communities in Traditional Chinese Cereal Starter Solid-State Fermentation

PubMed Central

Li, Pan; Liang, Hebin; Lin, Wei-Tie; Feng, Feng

2015-01-01

Traditional Chinese solid-state fermented cereal starters contain highly complex microbial communities and enzymes. Very little is known, however, about the microbial dynamics related to environmental conditions, and cellulolytic communities have never been proposed to exist during cereal starter fermentation. In this study, we performed Illumina MiSeq sequencing combined with PCR-denaturing gradient gel electrophoresis to investigate microbiota, coupled with clone library construction to trace cellulolytic communities in both fermentation stages. A succession of microbial assemblages was observed during the fermentation of starters. Lactobacillales and Saccharomycetales dominated the initial stages, with a continuous decline in relative abundance. However, thermotolerant and drought-resistant Bacillales, Eurotiales, and Mucorales were considerably accelerated during the heating stages, and these organisms dominated until the end of fermentation. Enterobacteriales were consistently ubiquitous throughout the process. For the cellulolytic communities, only the genera Sanguibacter, Beutenbergia, Agrobacterium, and Erwinia dominated the initial fermentation stages. In contrast, stages at high incubation temperature induced the appearance and dominance of Bacillus, Aspergillus, and Mucor. The enzymatic dynamics of amylase and glucoamylase also showed a similar trend, with the activities clearly increased in the first 7 days and subsequently decreased until the end of fermentation. Furthermore, β-glucosidase activity continuously and significantly increased during the fermentation process. Evidently, cellulolytic potential can adapt to environmental conditions by changes in the community structure during the fermentation of starters. PMID:26002897

Qualitative Fault Isolation of Hybrid Systems: A Structural Model Decomposition-Based Approach

NASA Technical Reports Server (NTRS)

Bregon, Anibal; Daigle, Matthew; Roychoudhury, Indranil

2016-01-01

Quick and robust fault diagnosis is critical to ensuring safe operation of complex engineering systems. A large number of techniques are available to provide fault diagnosis in systems with continuous dynamics. However, many systems in aerospace and industrial environments are best represented as hybrid systems that consist of discrete behavioral modes, each with its own continuous dynamics. These hybrid dynamics make the on-line fault diagnosis task computationally more complex due to the large number of possible system modes and the existence of autonomous mode transitions. This paper presents a qualitative fault isolation framework for hybrid systems based on structural model decomposition. The fault isolation is performed by analyzing the qualitative information of the residual deviations. However, in hybrid systems this process becomes complex due to possible existence of observation delays, which can cause observed deviations to be inconsistent with the expected deviations for the current mode in the system. The great advantage of structural model decomposition is that (i) it allows to design residuals that respond to only a subset of the faults, and (ii) every time a mode change occurs, only a subset of the residuals will need to be reconfigured, thus reducing the complexity of the reasoning process for isolation purposes. To demonstrate and test the validity of our approach, we use an electric circuit simulation as the case study.

Individual heterogeneity in life histories and eco-evolutionary dynamics

PubMed Central

Vindenes, Yngvild; Langangen, Øystein

2015-01-01

Individual heterogeneity in life history shapes eco-evolutionary processes, and unobserved heterogeneity can affect demographic outputs characterising life history and population dynamical properties. Demographic frameworks like matrix models or integral projection models represent powerful approaches to disentangle mechanisms linking individual life histories and population-level processes. Recent developments have provided important steps towards their application to study eco-evolutionary dynamics, but so far individual heterogeneity has largely been ignored. Here, we present a general demographic framework that incorporates individual heterogeneity in a flexible way, by separating static and dynamic traits (discrete or continuous). First, we apply the framework to derive the consequences of ignoring heterogeneity for a range of widely used demographic outputs. A general conclusion is that besides the long-term growth rate lambda, all parameters can be affected. Second, we discuss how the framework can help advance current demographic models of eco-evolutionary dynamics, by incorporating individual heterogeneity. For both applications numerical examples are provided, including an empirical example for pike. For instance, we demonstrate that predicted demographic responses to climate warming can be reversed by increased heritability. We discuss how applications of this demographic framework incorporating individual heterogeneity can help answer key biological questions that require a detailed understanding of eco-evolutionary dynamics. PMID:25807980

Learning an intrinsic-variable preserving manifold for dynamic visual tracking.

PubMed

Qiao, Hong; Zhang, Peng; Zhang, Bo; Zheng, Suiwu

2010-06-01

Manifold learning is a hot topic in the field of computer science, particularly since nonlinear dimensionality reduction based on manifold learning was proposed in Science in 2000. The work has achieved great success. The main purpose of current manifold-learning approaches is to search for independent intrinsic variables underlying high dimensional inputs which lie on a low dimensional manifold. In this paper, a new manifold is built up in the training step of the process, on which the input training samples are set to be close to each other if the values of their intrinsic variables are close to each other. Then, the process of dimensionality reduction is transformed into a procedure of preserving the continuity of the intrinsic variables. By utilizing the new manifold, the dynamic tracking of a human who can move and rotate freely is achieved. From the theoretical point of view, it is the first approach to transfer the manifold-learning framework to dynamic tracking. From the application point of view, a new and low dimensional feature for visual tracking is obtained and successfully applied to the real-time tracking of a free-moving object from a dynamic vision system. Experimental results from a dynamic tracking system which is mounted on a dynamic robot validate the effectiveness of the new algorithm.

A Surrogate Technique for Investigating Deterministic Dynamics in Discrete Human Movement.

PubMed

Taylor, Paul G; Small, Michael; Lee, Kwee-Yum; Landeo, Raul; O'Meara, Damien M; Millett, Emma L

2016-10-01

Entropy is an effective tool for investigation of human movement variability. However, before applying entropy, it can be beneficial to employ analyses to confirm that observed data are not solely the result of stochastic processes. This can be achieved by contrasting observed data with that produced using surrogate methods. Unlike continuous movement, no appropriate method has been applied to discrete human movement. This article proposes a novel surrogate method for discrete movement data, outlining the processes for determining its critical values. The proposed technique reliably generated surrogates for discrete joint angle time series, destroying fine-scale dynamics of the observed signal, while maintaining macro structural characteristics. Comparison of entropy estimates indicated observed signals had greater regularity than surrogates and were not only the result of stochastic but also deterministic processes. The proposed surrogate method is both a valid and reliable technique to investigate determinism in other discrete human movement time series.

Effect of Alignment on L2 Written Production

ERIC Educational Resources Information Center

Wang, Chuming; Wang, Min

2015-01-01

This article aims to uncover how L2 writing is affected by alignment, a socio-cognitive process involving dynamic coordination and adaptation. For this, two studies were conducted. Study 1 required two groups of 24 learners of English as a foreign language (EFL) to continue in English two stories with their endings removed, both of which had a…

Collaborative Teaching: How Does It Work in a Graduate TEFL Class?

ERIC Educational Resources Information Center

Khabiri, Mona; Marashi, Hamid

2016-01-01

Collaborative teaching is a dynamic process in which educators are continuously engaged in restrategizing to fit their curricular goal. This article aims to describe how the use of collaborative teaching in a course on proposal writing benefited a group of graduate students studying teaching English as a foreign language. Throughout the study, two…

Graphical Man/Machine Communications

DTIC Science & Technology

Progress is reported concerning the use of computer controlled graphical displays in the areas of radiaton diffusion and hydrodynamics, general...ventricular dynamics. Progress is continuing on the use of computer graphics in architecture. Some progress in halftone graphics is reported with no basic...developments presented. Colored halftone perspective pictures are being used to represent multivariable situations. Nonlinear waveform processing is

Marketing small animal theriogenology services--one perspective.

PubMed

Barber, J A

2007-08-01

Once a decision is made to add small animal theriogenology services to a practice, marketing strategies must be developed and implemented to attract clients to the new services. Marketing strategies for the niche market of theriogenology include start-up marketing methods, referral programs, internal marketing, and continued marketing. Marketing theriogenology services is a dynamic, ongoing process that never ends.

Career Development in the Schools. Issues in Career Development

ERIC Educational Resources Information Center

Eliason, Grafton T., Ed.; Patrick, John, Ed.

2008-01-01

"Career Development in the Schools" describes a dynamic process that continues to evolve in its rationale and practice. In many schools and in a variety of scholarly writings, the status of career development is controversial. Some observers assert that career development should be seen as a by-product of all of the knowledge and activities that…

Relaxation model of the heat production

NASA Astrophysics Data System (ADS)

Zimin, B. A.; Zorin, I. S.; Sventitskaya, V. E.

2018-05-01

The work is devoted to the study of the heat generation process in the problem of the dynamics of oscillations of a one-dimensional chain simulating heat formation in an elastic continuous medium under mechanical influences. Formulas for estimating the effect of thermoelasticity are obtained and an analogy is made with the energy of damped oscillations of an anharmonic oscillator.

Revitalizing Young Adults through Leadership Training at Victory Presbyterian Church, Ilsan, Korea

ERIC Educational Resources Information Center

Noh, Kyeong Cheon

2009-01-01

This study has the aim of examining the effects obtained mainly through the leadership development process through small group dynamics for the purpose of making the youth group church, vitalized. The church reached the conclusion that the important problem for continuous church development was how to find a trained leader and to help the…

The Role of Educational Quality and Quantity in the Process of Economic Development

ERIC Educational Resources Information Center

Castello-Climent, Amparo; Hidalgo-Cabrillana, Ana

2012-01-01

We develop a theory of human capital investment to study the effects of school quality on student choices of education, and to understand its effect on economic growth. In a dynamic general equilibrium closed economy, primary education is mandatory but there is an opportunity to continue to secondary education and beyond. High-quality education…

Wavelet and adaptive methods for time dependent problems and applications in aerosol dynamics

NASA Astrophysics Data System (ADS)

Guo, Qiang

Time dependent partial differential equations (PDEs) are widely used as mathematical models of environmental problems. Aerosols are now clearly identified as an important factor in many environmental aspects of climate and radiative forcing processes, as well as in the health effects of air quality. The mathematical models for the aerosol dynamics with respect to size distribution are nonlinear partial differential and integral equations, which describe processes of condensation, coagulation and deposition. Simulating the general aerosol dynamic equations on time, particle size and space exhibits serious difficulties because the size dimension ranges from a few nanometer to several micrometer while the spatial dimension is usually described with kilometers. Therefore, it is an important and challenging task to develop efficient techniques for solving time dependent dynamic equations. In this thesis, we develop and analyze efficient wavelet and adaptive methods for the time dependent dynamic equations on particle size and further apply them to the spatial aerosol dynamic systems. Wavelet Galerkin method is proposed to solve the aerosol dynamic equations on time and particle size due to the fact that aerosol distribution changes strongly along size direction and the wavelet technique can solve it very efficiently. Daubechies' wavelets are considered in the study due to the fact that they possess useful properties like orthogonality, compact support, exact representation of polynomials to a certain degree. Another problem encountered in the solution of the aerosol dynamic equations results from the hyperbolic form due to the condensation growth term. We propose a new characteristic-based fully adaptive multiresolution numerical scheme for solving the aerosol dynamic equation, which combines the attractive advantages of adaptive multiresolution technique and the characteristics method. On the aspect of theoretical analysis, the global existence and uniqueness of solutions of continuous time wavelet numerical methods for the nonlinear aerosol dynamics are proved by using Schauder's fixed point theorem and the variational technique. Optimal error estimates are derived for both continuous and discrete time wavelet Galerkin schemes. We further derive reliable and efficient a posteriori error estimate which is based on stable multiresolution wavelet bases and an adaptive space-time algorithm for efficient solution of linear parabolic differential equations. The adaptive space refinement strategies based on the locality of corresponding multiresolution processes are proved to converge. At last, we develop efficient numerical methods by combining the wavelet methods proposed in previous parts and the splitting technique to solve the spatial aerosol dynamic equations. Wavelet methods along the particle size direction and the upstream finite difference method along the spatial direction are alternately used in each time interval. Numerical experiments are taken to show the effectiveness of our developed methods.

Statistical Analysis of the First Passage Path Ensemble of Jump Processes

NASA Astrophysics Data System (ADS)

von Kleist, Max; Schütte, Christof; Zhang, Wei

2018-02-01

The transition mechanism of jump processes between two different subsets in state space reveals important dynamical information of the processes and therefore has attracted considerable attention in the past years. In this paper, we study the first passage path ensemble of both discrete-time and continuous-time jump processes on a finite state space. The main approach is to divide each first passage path into nonreactive and reactive segments and to study them separately. The analysis can be applied to jump processes which are non-ergodic, as well as continuous-time jump processes where the waiting time distributions are non-exponential. In the particular case that the jump processes are both Markovian and ergodic, our analysis elucidates the relations between the study of the first passage paths and the study of the transition paths in transition path theory. We provide algorithms to numerically compute statistics of the first passage path ensemble. The computational complexity of these algorithms scales with the complexity of solving a linear system, for which efficient methods are available. Several examples demonstrate the wide applicability of the derived results across research areas.

Cellular Decision Making by Non-Integrative Processing of TLR Inputs.

PubMed

Kellogg, Ryan A; Tian, Chengzhe; Etzrodt, Martin; Tay, Savaş

2017-04-04

Cells receive a multitude of signals from the environment, but how they process simultaneous signaling inputs is not well understood. Response to infection, for example, involves parallel activation of multiple Toll-like receptors (TLRs) that converge on the nuclear factor κB (NF-κB) pathway. Although we increasingly understand inflammatory responses for isolated signals, it is not clear how cells process multiple signals that co-occur in physiological settings. We therefore examined a bacterial infection scenario involving co-stimulation of TLR4 and TLR2. Independent stimulation of these receptors induced distinct NF-κB dynamic profiles, although surprisingly, under co-stimulation, single cells continued to show ligand-specific dynamic responses characteristic of TLR2 or TLR4 signaling rather than a mixed response, comprising a cellular decision that we term "non-integrative" processing. Iterating modeling and microfluidic experiments revealed that non-integrative processing occurred through interaction of switch-like NF-κB activation, receptor-specific processing timescales, cell-to-cell variability, and TLR cross-tolerance mediated by multilayer negative feedback. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Perturbation Experiments: Approaches for Metabolic Pathway Analysis in Bioreactors.

PubMed

Weiner, Michael; Tröndle, Julia; Albermann, Christoph; Sprenger, Georg A; Weuster-Botz, Dirk

2016-01-01

In the last decades, targeted metabolic engineering of microbial cells has become one of the major tools in bioprocess design and optimization. For successful application, a detailed knowledge is necessary about the relevant metabolic pathways and their regulation inside the cells. Since in vitro experiments cannot display process conditions and behavior properly, process data about the cells' metabolic state have to be collected in vivo. For this purpose, special techniques and methods are necessary. Therefore, most techniques enabling in vivo characterization of metabolic pathways rely on perturbation experiments, which can be divided into dynamic and steady-state approaches. To avoid any process disturbance, approaches which enable perturbation of cell metabolism in parallel to the continuing production process are reasonable. Furthermore, the fast dynamics of microbial production processes amplifies the need of parallelized data generation. These points motivate the development of a parallelized approach for multiple metabolic perturbation experiments outside the operating production reactor. An appropriate approach for in vivo characterization of metabolic pathways is presented and applied exemplarily to a microbial L-phenylalanine production process on a 15 L-scale.

The Perception of Dynamic and Static Facial Expressions of Happiness and Disgust Investigated by ERPs and fMRI Constrained Source Analysis

PubMed Central

Trautmann-Lengsfeld, Sina Alexa; Domínguez-Borràs, Judith; Escera, Carles; Herrmann, Manfred; Fehr, Thorsten

2013-01-01

A recent functional magnetic resonance imaging (fMRI) study by our group demonstrated that dynamic emotional faces are more accurately recognized and evoked more widespread patterns of hemodynamic brain responses than static emotional faces. Based on this experimental design, the present study aimed at investigating the spatio-temporal processing of static and dynamic emotional facial expressions in 19 healthy women by means of multi-channel electroencephalography (EEG), event-related potentials (ERP) and fMRI-constrained regional source analyses. ERP analysis showed an increased amplitude of the LPP (late posterior positivity) over centro-parietal regions for static facial expressions of disgust compared to neutral faces. In addition, the LPP was more widespread and temporally prolonged for dynamic compared to static faces of disgust and happiness. fMRI constrained source analysis on static emotional face stimuli indicated the spatio-temporal modulation of predominantly posterior regional brain activation related to the visual processing stream for both emotional valences when compared to the neutral condition in the fusiform gyrus. The spatio-temporal processing of dynamic stimuli yielded enhanced source activity for emotional compared to neutral conditions in temporal (e.g., fusiform gyrus), and frontal regions (e.g., ventromedial prefrontal cortex, medial and inferior frontal cortex) in early and again in later time windows. The present data support the view that dynamic facial displays trigger more information reflected in complex neural networks, in particular because of their changing features potentially triggering sustained activation related to a continuing evaluation of those faces. A combined fMRI and EEG approach thus provides an advanced insight to the spatio-temporal characteristics of emotional face processing, by also revealing additional neural generators, not identifiable by the only use of an fMRI approach. PMID:23818974

Multi-Topic Tracking Model for dynamic social network

NASA Astrophysics Data System (ADS)

Li, Yuhua; Liu, Changzheng; Zhao, Ming; Li, Ruixuan; Xiao, Hailing; Wang, Kai; Zhang, Jun

2016-07-01

The topic tracking problem has attracted much attention in the last decades. However, existing approaches rarely consider network structures and textual topics together. In this paper, we propose a novel statistical model based on dynamic bayesian network, namely Multi-Topic Tracking Model for Dynamic Social Network (MTTD). It takes influence phenomenon, selection phenomenon, document generative process and the evolution of textual topics into account. Specifically, in our MTTD model, Gibbs Random Field is defined to model the influence of historical status of users in the network and the interdependency between them in order to consider the influence phenomenon. To address the selection phenomenon, a stochastic block model is used to model the link generation process based on the users' interests to topics. Probabilistic Latent Semantic Analysis (PLSA) is used to describe the document generative process according to the users' interests. Finally, the dependence on the historical topic status is also considered to ensure the continuity of the topic itself in topic evolution model. Expectation Maximization (EM) algorithm is utilized to estimate parameters in the proposed MTTD model. Empirical experiments on real datasets show that the MTTD model performs better than Popular Event Tracking (PET) and Dynamic Topic Model (DTM) in generalization performance, topic interpretability performance, topic content evolution and topic popularity evolution performance.

Lower pitch is larger, yet falling pitches shrink.

PubMed

Eitan, Zohar; Schupak, Asi; Gotler, Alex; Marks, Lawrence E

2014-01-01

Experiments using diverse paradigms, including speeded discrimination, indicate that pitch and visually-perceived size interact perceptually, and that higher pitch is congruent with smaller size. While nearly all of these studies used static stimuli, here we examine the interaction of dynamic pitch and dynamic size, using Garner's speeded discrimination paradigm. Experiment 1 examined the interaction of continuous rise/fall in pitch and increase/decrease in object size. Experiment 2 examined the interaction of static pitch and size (steady high/low pitches and large/small visual objects), using an identical procedure. Results indicate that static and dynamic auditory and visual stimuli interact in opposite ways. While for static stimuli (Experiment 2), higher pitch is congruent with smaller size (as suggested by earlier work), for dynamic stimuli (Experiment 1), ascending pitch is congruent with growing size, and descending pitch with shrinking size. In addition, while static stimuli (Experiment 2) exhibit both congruence and Garner effects, dynamic stimuli (Experiment 1) present congruence effects without Garner interference, a pattern that is not consistent with prevalent interpretations of Garner's paradigm. Our interpretation of these results focuses on effects of within-trial changes on processing in dynamic tasks and on the association of changes in apparent size with implied changes in distance. Results suggest that static and dynamic stimuli can differ substantially in their cross-modal mappings, and may rely on different processing mechanisms.

Ammonia Monitor

NASA Technical Reports Server (NTRS)

Sauer, Richard L. (Inventor); Akse, James R. (Inventor); Thompson, John O. (Inventor); Atwater, James E. (Inventor)

1999-01-01

Ammonia monitor and method of use are disclosed. A continuous, real-time determination of the concentration of ammonia in an aqueous process stream is possible over a wide dynamic range of concentrations. No reagents are required because pH is controlled by an in-line solid-phase base. Ammonia is selectively transported across a membrane from the process stream to an analytical stream to an analytical stream under pH control. The specific electrical conductance of the analytical stream is measured and used to determine the concentration of ammonia.

Early boost and slow consolidation in motor skill learning.

PubMed

Hotermans, Christophe; Peigneux, Philippe; Maertens de Noordhout, Alain; Moonen, Gustave; Maquet, Pierre

2006-01-01

Motorskill learning is a dynamic process that continues covertly after training has ended and eventually leads to delayed increments in performance. Current theories suggest that this off-line improvement takes time and appears only after several hours. Here we show an early transient and short-lived boost in performance, emerging as early as 5-30 min after training but no longer observed 4 h later. This early boost is predictive of the performance achieved 48 h later, suggesting its functional relevance for memory processes.

Chaos and unpredictability in evolution of cooperation in continuous time

NASA Astrophysics Data System (ADS)

You, Taekho; Kwon, Minji; Jo, Hang-Hyun; Jung, Woo-Sung; Baek, Seung Ki

2017-12-01

Cooperators benefit others with paying costs. Evolution of cooperation crucially depends on the cost-benefit ratio of cooperation, denoted as c . In this work, we investigate the infinitely repeated prisoner's dilemma for various values of c with four of the representative memory-one strategies, i.e., unconditional cooperation, unconditional defection, tit-for-tat, and win-stay-lose-shift. We consider replicator dynamics which deterministically describes how the fraction of each strategy evolves over time in an infinite-sized well-mixed population in the presence of implementation error and mutation among the four strategies. Our finding is that this three-dimensional continuous-time dynamics exhibits chaos through a bifurcation sequence similar to that of a logistic map as c varies. If mutation occurs with rate μ ≪1 , the position of the bifurcation sequence on the c axis is numerically found to scale as μ0.1, and such sensitivity to μ suggests that mutation may have nonperturbative effects on evolutionary paths. It demonstrates how the microscopic randomness of the mutation process can be amplified to macroscopic unpredictability by evolutionary dynamics.

Development of a method for fabricating metallic matrix composite shapes by a continuous mechanical process

NASA Technical Reports Server (NTRS)

Divecha, A. P.; Karmarkar, S. D.; Pawar, P. G.

1973-01-01

The continuing efforts in upscaling to produce larger diameter Al/B tubes are described. While the basic methodology remains unchanged, the larger volume of acrylic binder material and its removal by dissolution in toluene had to be performed by dynamic scrubbing. Similarly, the boron and MCF continuous length requirements increased when a 6 foot long by 7 inches wide mat was needed. These modifications and associated problems are described fully with schematics. Also included are seven experiments conducted to prepare larger tubes. The thermal profile, drawing speeds, and furnace positions in the draw bench bay are presented along with metallographic evidence of composite cross sections.

Improved Monitoring of Semi-Continuous Anaerobic Digestion of Sugarcane Waste: Effects of Increasing Organic Loading Rate on Methanogenic Community Dynamics

PubMed Central

Leite, Athaydes Francisco; Janke, Leandro; Lv, Zuopeng; Harms, Hauke; Richnow, Hans-Hermann; Nikolausz, Marcell

2015-01-01

The anaerobic digestion of filter cake and its co-digestion with bagasse, and the effect of gradual increase of the organic loading rate (OLR) from start-up to overload were investigated. Understanding the influence of environmental and technical parameters on the development of particular methanogenic pathway in the biogas process was an important aim for the prediction and prevention of process failure. The rapid accumulation of volatile organic acids at high OLR of 3.0 to 4.0 gvs·L−1·day−1 indicated strong process inhibition. Methanogenic community dynamics of the reactors was monitored by stable isotope composition of biogas and molecular biological analysis. A potential shift toward the aceticlastic methanogenesis was observed along with the OLR increase under stable reactor operating conditions. Reactor overloading and process failure were indicated by the tendency to return to a predominance of hydrogenotrophic methanogenesis with rising abundances of the orders Methanobacteriales and Methanomicrobiales and drop of the genus Methanosarcina abundance. PMID:26404240

Digital signal processing for velocity measurements in dynamical material's behaviour studies.

PubMed

Devlaminck, Julien; Luc, Jérôme; Chanal, Pierre-Yves

2014-03-01

In this work, we describe different configurations of optical fiber interferometers (types Michelson and Mach-Zehnder) used to measure velocities during dynamical material's behaviour studies. We detail the algorithms of processing developed and optimized to improve the performance of these interferometers especially in terms of time and frequency resolutions. Three methods of analysis of interferometric signals were studied. For Michelson interferometers, the time-frequency analysis of signals by Short-Time Fourier Transform (STFT) is compared to a time-frequency analysis by Continuous Wavelet Transform (CWT). The results have shown that the CWT was more suitable than the STFT for signals with low signal-to-noise, and low velocity and high acceleration areas. For Mach-Zehnder interferometers, the measurement is carried out by analyzing the phase shift between three interferometric signals (Triature processing). These three methods of digital signal processing were evaluated, their measurement uncertainties estimated, and their restrictions or operational limitations specified from experimental results performed on a pulsed power machine.

About one discrete model of splitting by the physical processes of a piezoconductive medium with gas hydrate inclusions

NASA Astrophysics Data System (ADS)

Poveshchenko, Yu A.; Podryga, V. O.; Rahimly, P. I.; Sharova, Yu S.

2018-01-01

The thermodynamically equilibrium model for splitting by the physical processes of a two-component three-phase filtration fluid dynamics with gas hydrate inclusions is considered in the paper, for which a family of two-layer completely conservative difference schemes of the support operators method with time weights profiled in space is constructed. On the irregular grids of the theory of the support-operators method applied to the specifics of the processes of transfer of saturations and internal energies of water and gas in a medium with gas hydrate inclusions, methods of directwind approximation of these processes are considered. These approximations preserve the continual properties of divergence-gradient operations in their difference form and are related to the velocity field providing saturations transfer and internal energies of fluids. Fluid dynamics with gas hydrate inclusions are also calculated on the basis of the proposed approach, in particular, in areas of severe pressure depression in the collector space.

Equidistribution for Nonuniformly Expanding Dynamical Systems, and Application to the Almost Sure Invariance Principle

NASA Astrophysics Data System (ADS)

Korepanov, Alexey

2017-12-01

Let {T : M \\to M} be a nonuniformly expanding dynamical system, such as logistic or intermittent map. Let {v : M \\to R^d} be an observable and {v_n = \\sum_{k=0}^{n-1} v circ T^k} denote the Birkhoff sums. Given a probability measure {μ} on M, we consider v n as a discrete time random process on the probability space {(M, μ)} . In smooth ergodic theory there are various natural choices of {μ} , such as the Lebesgue measure, or the absolutely continuous T-invariant measure. They give rise to different random processes. We investigate relation between such processes. We show that in a large class of measures, it is possible to couple (redefine on a new probability space) every two processes so that they are almost surely close to each other, with explicit estimates of "closeness". The purpose of this work is to close a gap in the proof of the almost sure invariance principle for nonuniformly hyperbolic transformations by Melbourne and Nicol.

Coherent diffractive imaging of time-evolving samples with improved temporal resolution

DOE PAGES

Ulvestad, A.; Tripathi, A.; Hruszkewycz, S. O.; ...

2016-05-19

Bragg coherent x-ray diffractive imaging is a powerful technique for investigating dynamic nanoscale processes in nanoparticles immersed in reactive, realistic environments. Its temporal resolution is limited, however, by the oversampling requirements of three-dimensional phase retrieval. Here, we show that incorporating the entire measurement time series, which is typically a continuous physical process, into phase retrieval allows the oversampling requirement at each time step to be reduced, leading to a subsequent improvement in the temporal resolution by a factor of 2-20 times. The increased time resolution will allow imaging of faster dynamics and of radiation-dose-sensitive samples. Furthermore, this approach, which wemore » call "chrono CDI," may find use in improving the time resolution in other imaging techniques.« less

Recovery after mass extinction: evolutionary assembly in large-scale biosphere dynamics.

PubMed Central

Solé, Ricard V; Montoya, José M; Erwin, Douglas H

2002-01-01

Biotic recoveries following mass extinctions are characterized by a process in which whole ecologies are reconstructed from low-diversity systems, often characterized by opportunistic groups. The recovery process provides an unexpected window to ecosystem dynamics. In many aspects, recovery is very similar to ecological succession, but important differences are also apparently linked to the innovative patterns of niche construction observed in the fossil record. In this paper, we analyse the similarities and differences between ecological succession and evolutionary recovery to provide a preliminary ecological theory of recoveries. A simple evolutionary model with three trophic levels is presented, and its properties (closely resembling those observed in the fossil record) are compared with characteristic patterns of ecological response to disturbances in continuous models of three-level ecosystems. PMID:12079530

Continuous-time system identification of a smoking cessation intervention

NASA Astrophysics Data System (ADS)

Timms, Kevin P.; Rivera, Daniel E.; Collins, Linda M.; Piper, Megan E.

2014-07-01

Cigarette smoking is a major global public health issue and the leading cause of preventable death in the United States. Toward a goal of designing better smoking cessation treatments, system identification techniques are applied to intervention data to describe smoking cessation as a process of behaviour change. System identification problems that draw from two modelling paradigms in quantitative psychology (statistical mediation and self-regulation) are considered, consisting of a series of continuous-time estimation problems. A continuous-time dynamic modelling approach is employed to describe the response of craving and smoking rates during a quit attempt, as captured in data from a smoking cessation clinical trial. The use of continuous-time models provide benefits of parsimony, ease of interpretation, and the opportunity to work with uneven or missing data.

Quantitation of Cellular Dynamics in Growing Arabidopsis Roots with Light Sheet Microscopy

PubMed Central

Birnbaum, Kenneth D.; Leibler, Stanislas

2011-01-01

To understand dynamic developmental processes, living tissues have to be imaged frequently and for extended periods of time. Root development is extensively studied at cellular resolution to understand basic mechanisms underlying pattern formation and maintenance in plants. Unfortunately, ensuring continuous specimen access, while preserving physiological conditions and preventing photo-damage, poses major barriers to measurements of cellular dynamics in growing organs such as plant roots. We present a system that integrates optical sectioning through light sheet fluorescence microscopy with hydroponic culture that enables us to image, at cellular resolution, a vertically growing Arabidopsis root every few minutes and for several consecutive days. We describe novel automated routines to track the root tip as it grows, to track cellular nuclei and to identify cell divisions. We demonstrate the system's capabilities by collecting data on divisions and nuclear dynamics. PMID:21731697

Nonlinear versus Ordinary Adaptive Control of Continuous Stirred-Tank Reactor

PubMed Central

Dostal, Petr

2015-01-01

Unfortunately, the major group of the systems in industry has nonlinear behavior and control of such processes with conventional control approaches with fixed parameters causes problems and suboptimal or unstable control results. An adaptive control is one way to how we can cope with nonlinearity of the system. This contribution compares classic adaptive control and its modification with Wiener system. This configuration divides nonlinear controller into the dynamic linear part and the static nonlinear part. The dynamic linear part is constructed with the use of polynomial synthesis together with the pole-placement method and the spectral factorization. The static nonlinear part uses static analysis of the controlled plant for introducing the mathematical nonlinear description of the relation between the controlled output and the change of the control input. Proposed controller is tested by the simulations on the mathematical model of the continuous stirred-tank reactor with cooling in the jacket as a typical nonlinear system. PMID:26346878

Critical behavior of a two-step contagion model with multiple seeds

NASA Astrophysics Data System (ADS)

Choi, Wonjun; Lee, Deokjae; Kahng, B.

2017-06-01

A two-step contagion model with a single seed serves as a cornerstone for understanding the critical behaviors and underlying mechanism of discontinuous percolation transitions induced by cascade dynamics. When the contagion spreads from a single seed, a cluster of infected and recovered nodes grows without any cluster merging process. However, when the contagion starts from multiple seeds of O (N ) where N is the system size, a node weakened by a seed can be infected more easily when it is in contact with another node infected by a different pathogen seed. This contagion process can be viewed as a cluster merging process in a percolation model. Here we show analytically and numerically that when the density of infectious seeds is relatively small but O (1 ) , the epidemic transition is hybrid, exhibiting both continuous and discontinuous behavior, whereas when it is sufficiently large and reaches a critical point, the transition becomes continuous. We determine the full set of critical exponents describing the hybrid and the continuous transitions. Their critical behaviors differ from those in the single-seed case.

Diffusion processes of fragmentary information on scale-free networks

NASA Astrophysics Data System (ADS)

Li, Xun; Cao, Lang

2016-05-01

Compartmental models of diffusion over contact networks have proven representative of real-life propagation phenomena among interacting individuals. However, there is a broad class of collective spreading mechanisms departing from compartmental representations, including those for diffusive objects capable of fragmentation and transmission unnecessarily as a whole. Here, we consider a continuous-state susceptible-infected-susceptible (SIS) model as an ideal limit-case of diffusion processes of fragmentary information on networks, where individuals possess fractions of the information content and update them by selectively exchanging messages with partners in the vicinity. Specifically, we incorporate local information, such as neighbors' node degrees and carried contents, into the individual partner choice, and examine the roles of a variety of such strategies in the information diffusion process, both qualitatively and quantitatively. Our method provides an effective and flexible route of modulating continuous-state diffusion dynamics on networks and has potential in a wide array of practical applications.

Observing fermionic statistics with photons in arbitrary processes

PubMed Central

Matthews, Jonathan C. F.; Poulios, Konstantinos; Meinecke, Jasmin D. A.; Politi, Alberto; Peruzzo, Alberto; Ismail, Nur; Wörhoff, Kerstin; Thompson, Mark G.; O'Brien, Jeremy L.

2013-01-01

Quantum mechanics defines two classes of particles-bosons and fermions-whose exchange statistics fundamentally dictate quantum dynamics. Here we develop a scheme that uses entanglement to directly observe the correlated detection statistics of any number of fermions in any physical process. This approach relies on sending each of the entangled particles through identical copies of the process and by controlling a single phase parameter in the entangled state, the correlated detection statistics can be continuously tuned between bosonic and fermionic statistics. We implement this scheme via two entangled photons shared across the polarisation modes of a single photonic chip to directly mimic the fermion, boson and intermediate behaviour of two-particles undergoing a continuous time quantum walk. The ability to simulate fermions with photons is likely to have applications for verifying boson scattering and for observing particle correlations in analogue simulation using any physical platform that can prepare the entangled state prescribed here. PMID:23531788

Conceptual Design Optimization of an Augmented Stability Aircraft Incorporating Dynamic Response Performance Constraints

NASA Technical Reports Server (NTRS)

Welstead, Jason

2014-01-01

This research focused on incorporating stability and control into a multidisciplinary de- sign optimization on a Boeing 737-class advanced concept called the D8.2b. A new method of evaluating the aircraft handling performance using quantitative evaluation of the sys- tem to disturbances, including perturbations, continuous turbulence, and discrete gusts, is presented. A multidisciplinary design optimization was performed using the D8.2b transport air- craft concept. The con guration was optimized for minimum fuel burn using a design range of 3,000 nautical miles. Optimization cases were run using xed tail volume coecients, static trim constraints, and static trim and dynamic response constraints. A Cessna 182T model was used to test the various dynamic analysis components, ensuring the analysis was behaving as expected. Results of the optimizations show that including stability and con- trol in the design process drastically alters the optimal design, indicating that stability and control should be included in conceptual design to avoid system level penalties later in the design process.

Dynamic regulation of mitochondrial fission through modification of the dynamin-related protein Drp1

PubMed Central

Chang, Chuang-Rung; Blackstone, Craig

2017-01-01

Mitochondria in cells comprise a tubulovesicular network shaped continuously by complementary fission and fusion events. The mammalian Drp1 protein plays a key role in fission, while Mfn1, Mfn2, and OPA1 are required for fusion. Shifts in the balance between these opposing processes can occur rapidly, indicating that modifications to these proteins may regulate mitochondrial membrane dynamics. We highlight posttranslational modifications of the mitochondrial fission protein Drp1, for which these regulatory mechanisms are best characterized. This dynamin-related GTPase undergoes a number of steps to mediate mitochondrial fission, including translocation from cytoplasm to the mitochondrial outer membrane, higher-order assembly into spirals, GTP hydrolysis associated with a conformational change and membrane deformation, and ultimately disassembly. Many of these steps may be influenced by covalent modification of Drp1. We discuss the dynamic nature of Drp1 modifications and how they contribute not only to the normal regulation of mitochondrial division, but also to neuropathologic processes. PMID:20649536

Nonlinear dynamics of global atmospheric and earth system processes

NASA Technical Reports Server (NTRS)

Zhang, Taiping; Verbitsky, Mikhail; Saltzman, Barry; Mann, Michael E.; Park, Jeffrey; Lall, Upmanu

1995-01-01

During the grant period, the authors continued ongoing studies aimed at enhancing their understanding of the operation of the atmosphere as a complex nonlinear system interacting with the hydrosphere, biosphere, and cryosphere in response to external radiative forcing. Five papers were completed with support from the grant, representing contributions in three main areas of study: (1) theoretical studies of the interactive atmospheric response to changed biospheric boundary conditions measurable from satellites; (2) statistical-observational studies of global-scale temperature variability on interannual to century time scales; and (3) dynamics of long-term earth system changes associated with ice sheet surges.

Nonlinear dynamics of a machining system with two interdependent delays

NASA Astrophysics Data System (ADS)

Gouskov, Alexander M.; Voronov, Sergey A.; Paris, Henri; Batzer, Stephen A.

2002-12-01

The dynamics of turning by a tool head with two rows, each containing several cutters, is considered. A mathematical model of a process with two interdependent delays with the possibility of cutting discontinuity is analyzed. The domains of dynamic instability are derived, and the influence of technological parameters on system response is presented. The numeric analysis show that there exists specific conditions for given regimes in which one row of cutters produces an intermittent chip form while the other row produces continuous chips. It is demonstrated that the contribution of parametric excitation by shape roughness of an imperfect (unmachined) cylindrical workpiece surface is not substantial due to the special filtering properties of cutters that are uniformly distributed circumferentially along the tool head.

Linking brain, mind and behavior.

PubMed

Makeig, Scott; Gramann, Klaus; Jung, Tzyy-Ping; Sejnowski, Terrence J; Poizner, Howard

2009-08-01

Cortical brain areas and dynamics evolved to organize motor behavior in our three-dimensional environment also support more general human cognitive processes. Yet traditional brain imaging paradigms typically allow and record only minimal participant behavior, then reduce the recorded data to single map features of averaged responses. To more fully investigate the complex links between distributed brain dynamics and motivated natural behavior, we propose the development of wearable mobile brain/body imaging (MoBI) systems that continuously capture the wearer's high-density electrical brain and muscle signals, three-dimensional body movements, audiovisual scene and point of regard, plus new data-driven analysis methods to model their interrelationships. The new imaging modality should allow new insights into how spatially distributed brain dynamics support natural human cognition and agency.

Reconciling Streamflow Uncertainty Estimation and River Bed Morphology Dynamics. Insights from a Probabilistic Assessment of Streamflow Uncertainties Using a Reliability Diagram

NASA Astrophysics Data System (ADS)

Morlot, T.; Mathevet, T.; Perret, C.; Favre Pugin, A. C.

2014-12-01

Streamflow uncertainty estimation has recently received a large attention in the literature. A dynamic rating curve assessment method has been introduced (Morlot et al., 2014). This dynamic method allows to compute a rating curve for each gauging and a continuous streamflow time-series, while calculating streamflow uncertainties. Streamflow uncertainty takes into account many sources of uncertainty (water level, rating curve interpolation and extrapolation, gauging aging, etc.) and produces an estimated distribution of streamflow for each days. In order to caracterise streamflow uncertainty, a probabilistic framework has been applied on a large sample of hydrometric stations of the Division Technique Générale (DTG) of Électricité de France (EDF) hydrometric network (>250 stations) in France. A reliability diagram (Wilks, 1995) has been constructed for some stations, based on the streamflow distribution estimated for a given day and compared to a real streamflow observation estimated via a gauging. To build a reliability diagram, we computed the probability of an observed streamflow (gauging), given the streamflow distribution. Then, the reliability diagram allows to check that the distribution of probabilities of non-exceedance of the gaugings follows a uniform law (i.e., quantiles should be equipropables). Given the shape of the reliability diagram, the probabilistic calibration is caracterised (underdispersion, overdispersion, bias) (Thyer et al., 2009). In this paper, we present case studies where reliability diagrams have different statistical properties for different periods. Compared to our knowledge of river bed morphology dynamic of these hydrometric stations, we show how reliability diagram gives us invaluable information on river bed movements, like a continuous digging or backfilling of the hydraulic control due to erosion or sedimentation processes. Hence, the careful analysis of reliability diagrams allows to reconcile statistics and long-term river bed morphology processes. This knowledge improves our real-time management of hydrometric stations, given a better caracterisation of erosion/sedimentation processes and the stability of hydrometric station hydraulic control.

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.

Achieving continuous manufacturing: technologies and approaches for synthesis, workup, and isolation of drug substance. May 20-21, 2014 Continuous Manufacturing Symposium.

PubMed

Baxendale, Ian R; Braatz, Richard D; Hodnett, Benjamin K; Jensen, Klavs F; Johnson, Martin D; Sharratt, Paul; Sherlock, Jon-Paul; Florence, Alastair J

2015-03-01

This whitepaper highlights current challenges and opportunities associated with continuous synthesis, workup, and crystallization of active pharmaceutical ingredients (drug substances). We describe the technologies and requirements at each stage and emphasize the different considerations for developing continuous processes compared with batch. In addition to the specific sequence of operations required to deliver the necessary chemical and physical transformations for continuous drug substance manufacture, consideration is also given to how adoption of continuous technologies may impact different manufacturing stages in development from discovery, process development, through scale-up and into full scale production. The impact of continuous manufacture on drug substance quality and the associated challenges for control and for process safety are also emphasized. In addition to the technology and operational considerations necessary for the adoption of continuous manufacturing (CM), this whitepaper also addresses the cultural, as well as skills and training, challenges that will need to be met by support from organizations in order to accommodate the new work flows. Specific action items for industry leaders are: Develop flow chemistry toolboxes, exploiting the advantages of flow processing and including highly selective chemistries that allow use of simple and effective continuous workup technologies. Availability of modular or plug and play type equipment especially for workup to assist in straightforward deployment in the laboratory. As with learning from other industries, standardization is highly desirable and will require cooperation across industry and academia to develop and implement. Implement and exploit process analytical technologies (PAT) for real-time dynamic control of continuous processes. Develop modeling and simulation techniques to support continuous process development and control. Progress is required in multiphase systems such as crystallization. Involve all parts of the organization from discovery, research and development, and manufacturing in the implementation of CM. Engage with academia to develop the training provision to support the skills base for CM, particularly in flow chemistry, physical chemistry, and chemical engineering skills at the chemistry-process interface. Promote and encourage publication and dissemination of examples of CM across the sector to demonstrate capability, engage with regulatory comment, and establish benchmarks for performance and highlight challenges. Develop the economic case for CM of drug substance. This will involve various stakeholders at project and business level, however establishing the critical economic drivers is critical to driving the transformation in manufacturing. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

Dynamic Database. Efficiently Convert Massive Quantities of Sensor Data into Actionable Information for Tactical Commanders

DTIC Science & Technology

2000-06-01

As the number of sensors, platforms, exploitation sites, and command and control nodes continues to grow in response to Joint Vision 2010 information ... dominance requirements, Commanders and analysts will have an ever increasing need to collect and process vast amounts of data over wide areas using a large number of disparate sensors and information gathering sources.

Nonlinear dynamics in low permittivity media: the impact of losses.

PubMed

Vincenti, M A; de Ceglia, D; Scalora, M

2013-12-02

Slabs of materials with near-zero permittivity display enhanced nonlinear processes. We show that field enhancement due to the continuity of the longitudinal component of the displacement field drastically enhances harmonic generation. We investigate the impact of losses with and without bulk nonlinearities and demonstrate that in the latter scenario surface, magnetic and quadrupolar nonlinear sources cannot always be ignored.

Dynamic Instructional Leadership to Support Student Learning and Development: The Field Guide to Comer Schools in Action

ERIC Educational Resources Information Center

Joyner, Edward T., Ed.; Ben-Avie, Michael, Ed.; Comer, James P., Ed.

2004-01-01

Schools are the only universally accessible institutions where there are enough adults to provide continuous support for children's growth, development, and success in life. Using the process pioneered by renowned child psychiatrist Dr. James P. Comer and his colleagues at the Yale School Development Program (SDP), this unique field guide offers…

Continuing education at the cutting edge: promoting transformative knowledge translation.

PubMed

McWilliam, Carol L

2007-01-01

As the evidence-based practice movement gains momentum, continuing education practitioners increasingly confront the challenge of developing and conducting opportunities for achieving research uptake. Recent thinking invites new approaches to continuing education for health professionals, with due consideration of what knowledge merits uptake by practitioners, who should play what role in the knowledge transfer process, and what educational approach should be used. This article presents an innovative theory-based strategy that encompasses this new perspective. Through a facilitated experience of perspective transformation, clinicians are engaged in an on-the-job process of developing a deeply felt interest in research findings relevant to everyday practice, as well as ownership of that knowledge and its application. The strategy becomes a sustainable, integrated part of clinical practice, fitting naturally within its dynamic, unique environment, context, and climate and overcoming the barrier of time. Clinician experience of a top-down push toward prescribed practice change is avoided. With an expanded role encompassing facilitation of active learning partnerships for practice change, the continuing educator fosters a learning organization culture across the institution. The resultant role changes and leadership and accountability issues are elaborated.

Reconsidering change and continuity in later life: toward an innovation theory of successful aging.

PubMed

Nimrod, Galit; Kleiber, Douglas A

2007-01-01

This article examines the patterns and meanings of innovation in the activities of a group of retirees with an eye toward understanding the place and value of innovation in the aging process. Starting with a consideration of continuity theory, as a perspective that simply describes typical patterns of activity, and activity theory that prescribes expansion of activities as a key to well-being, this article highlights the characteristics, meanings and perceived benefits of a wide variety of innovative activities. The study utilized in-depth semi-structured interviews with a purposive sample of 20 male and female retirees involved in a "Learning and Retirement" program. Innovations that both preserve a sense of self (internal continuity) as well as those that allow one to strike out in entirely new direction are described, and, using a process of constant comparison, their motivational dynamics are explored. Given previous arguments that activity can be indiscriminate and disintegrative in some circumstances, we nevertheless suggest that innovation can be growth producing and liberating, even in later life, while at the same time generally protecting a sense of internal continuity.

The significance of the amorphous potential energy landscape for dictating glassy dynamics and driving solid-state crystallisation.

PubMed

Ruggiero, Michael T; Krynski, Marcin; Kissi, Eric Ofosu; Sibik, Juraj; Markl, Daniel; Tan, Nicholas Y; Arslanov, Denis; van der Zande, Wim; Redlich, Britta; Korter, Timothy M; Grohganz, Holger; Löbmann, Korbinian; Rades, Thomas; Elliott, Stephen R; Zeitler, J Axel

2017-11-15

The fundamental origins surrounding the dynamics of disordered solids near their characteristic glass transitions continue to be fiercely debated, even though a vast number of materials can form amorphous solids, including small-molecule organic, inorganic, covalent, metallic, and even large biological systems. The glass-transition temperature, T g , can be readily detected by a diverse set of techniques, but given that these measurement modalities probe vastly different processes, there has been significant debate regarding the question of why T g can be detected across all of them. Here we show clear experimental and computational evidence in support of a theory that proposes that the shape and structure of the potential-energy surface (PES) is the fundamental factor underlying the glass-transition processes, regardless of the frequency that experimental methods probe. Whilst this has been proposed previously, we demonstrate, using ab initio molecular-dynamics (AIMD) simulations, that it is of critical importance to carefully consider the complete PES - both the intra-molecular and inter-molecular features - in order to fully understand the entire range of atomic-dynamical processes in disordered solids. Finally, we show that it is possible to utilise this dependence to directly manipulate and harness amorphous dynamics in order to control the behaviour of such solids by using high-powered terahertz pulses to induce crystallisation and preferential crystal-polymorph growth in glasses. Combined, these findings provide compelling evidence that the PES landscape, and the corresponding energy barriers, are the ultimate controlling feature behind the atomic and molecular dynamics of disordered solids, regardless of the frequency at which they occur.

Continuous and scalable polymer capsule processing for inertial fusion energy target shell fabrication using droplet microfluidics.

PubMed

Li, Jin; Lindley-Start, Jack; Porch, Adrian; Barrow, David

2017-07-24

High specification, polymer capsules, to produce inertial fusion energy targets, were continuously fabricated using surfactant-free, inertial centralisation, and ultrafast polymerisation, in a scalable flow reactor. Laser-driven, inertial confinement fusion depends upon the interaction of high-energy lasers and hydrogen isotopes, contained within small, spherical and concentric target shells, causing a nuclear fusion reaction at ~150 M°C. Potentially, targets will be consumed at ~1 M per day per reactor, demanding a 5000x unit cost reduction to ~$0.20, and is a critical, key challenge. Experimentally, double emulsions were used as templates for capsule-shells, and were formed at 20 Hz, on a fluidic chip. Droplets were centralised in a dynamic flow, and their shapes both evaluated, and mathematically modeled, before subsequent shell solidification. The shells were photo-cured individually, on-the-fly, with precisely-actuated, millisecond-length (70 ms), uniform-intensity UV pulses, delivered through eight, radially orchestrated light-pipes. The near 100% yield rate of uniform shells had a minimum 99.0% concentricity and sphericity, and the solidification processing period was significantly reduced, over conventional batch methods. The data suggest the new possibility of a continuous, on-the-fly, IFE target fabrication process, employing sequential processing operations within a continuous enclosed duct system, which may include cryogenic fuel-filling, and shell curing, to produce ready-to-use IFE targets.

Continuous-time random walks with reset events. Historical background and new perspectives

NASA Astrophysics Data System (ADS)

Montero, Miquel; Masó-Puigdellosas, Axel; Villarroel, Javier

2017-09-01

In this paper, we consider a stochastic process that may experience random reset events which relocate the system to its starting position. We focus our attention on a one-dimensional, monotonic continuous-time random walk with a constant drift: the process moves in a fixed direction between the reset events, either by the effect of the random jumps, or by the action of a deterministic bias. However, the orientation of its motion is randomly determined after each restart. As a result of these alternating dynamics, interesting properties do emerge. General formulas for the propagator as well as for two extreme statistics, the survival probability and the mean first-passage time, are also derived. The rigor of these analytical results is verified by numerical estimations, for particular but illuminating examples.

Mapping permafrost change hot-spots with Landsat time-series

NASA Astrophysics Data System (ADS)

Grosse, G.; Nitze, I.

2016-12-01

Recent and projected future climate warming strongly affects permafrost stability over large parts of the terrestrial Arctic with local, regional and global scale consequences. The monitoring and quantification of permafrost and associated land surface changes in these areas is crucial for the analysis of hydrological and biogeochemical cycles as well as vegetation and ecosystem dynamics. However, detailed knowledge of the spatial distribution and the temporal dynamics of these processes is scarce and likely key locations of permafrost landscape dynamics may remain unnoticed. As part of the ERC funded PETA-CARB and ESA GlobPermafrost projects, we developed an automated processing chain based on data from the entire Landsat archive (excluding MSS) for the detection of permafrost change related processes and hotspots. The automated method enables us to analyze thousands of Landsat scenes, which allows for a multi-scaled spatio-temporal analysis at 30 meter spatial resolution. All necessary processing steps are carried out automatically with minimal user interaction, including data extraction, masking, reprojection, subsetting, data stacking, and calculation of multi-spectral indices. These indices, e.g. Landsat Tasseled Cap and NDVI among others, are used as proxies for land surface conditions, such as vegetation status, moisture or albedo. Finally, a robust trend analysis is applied to each multi-spectral index and each pixel over the entire observation period of up to 30 years from 1985 to 2015, depending on data availability. Large transects of around 2 million km² across different permafrost types in Siberia and North America have been processed. Permafrost related or influencing landscape dynamics were detected within the trend analysis, including thermokarst lake dynamics, fires, thaw slumps, and coastal dynamics. The produced datasets will be distributed to the community as part of the ERC PETA-CARB and ESA GlobPermafrost projects. Users are encouraged to provide feedback and ground truth data for a continuous improvement of our methodology and datasets, which will lead to a better understanding of the spatial and temporal distribution of changes within the vulnerable permafrost zone.

Impulsive control of a continuous-culture and flocculation harvest chemostat model

NASA Astrophysics Data System (ADS)

Zhang, Tongqian; Ma, Wanbiao; Meng, Xinzhu

2017-12-01

In this paper, a new mathematical model describing the process of continuous culture and harvest of microalgaes is proposed. By inputting medium and flocculant at two different fixed moments periodically, continuous culture and harvest of microalgaes is implemented. The mathematical analysis is conducted and the whole dynamics of model is investigated by using theory of impulsive differential equations. We find that the model has a microalgaes-extinction periodic solution and it is globally asymptotically stable when some certain threshold value is less than the unit. And the model is permanent when some certain threshold value is larger than the unit. Then, according to the threshold, the control strategies of continuous culture and harvest of microalgaes are discussed. The results show that continuous culture and harvest of microalgaes can be archived by adjusting suitable input time, input amount of medium or flocculant. Finally, some numerical simulations are carried out to verify the control strategy.

Continuous measurement of two spatially separated superconducting qubits: quantum trajectories and statistics

NASA Astrophysics Data System (ADS)

Roch, Nicolas

2015-03-01

Measurement can be harnessed to probabilistically generate entanglement in the absence of local interactions, for example between spatially separated quantum objects. Continuous weak measurement allows us to observe the dynamics associated with this process. In particular, we perform joint dispersive readout of two superconducting transmon qubits separated by one meter of coaxial cable. We track the evolution of a joint quantum state under the influence of measurement, both as an ensemble and as a set of individual quantum trajectories. Analyzing the statistics of such quantum trajectories can shed new light on the underlying entangling mechanism.

4D-SFM Photogrammetry for Monitoring Sediment Dynamics in a Debris-Flow Catchment: Software Testing and Results Comparison

NASA Astrophysics Data System (ADS)

Cucchiaro, S.; Maset, E.; Fusiello, A.; Cazorzi, F.

2018-05-01

In recent years, the combination of Structure-from-Motion (SfM) algorithms and UAV-based aerial images has revolutionised 3D topographic surveys for natural environment monitoring, offering low-cost, fast and high quality data acquisition and processing. A continuous monitoring of the morphological changes through multi-temporal (4D) SfM surveys allows, e.g., to analyse the torrent dynamic also in complex topography environment like debris-flow catchments, provided that appropriate tools and procedures are employed in the data processing steps. In this work we test two different software packages (3DF Zephyr Aerial and Agisoft Photoscan) on a dataset composed of both UAV and terrestrial images acquired on a debris-flow reach (Moscardo torrent - North-eastern Italian Alps). Unlike other papers in the literature, we evaluate the results not only on the raw point clouds generated by the Structure-from- Motion and Multi-View Stereo algorithms, but also on the Digital Terrain Models (DTMs) created after post-processing. Outcomes show differences between the DTMs that can be considered irrelevant for the geomorphological phenomena under analysis. This study confirms that SfM photogrammetry can be a valuable tool for monitoring sediment dynamics, but accurate point cloud post-processing is required to reliably localize geomorphological changes.

Effect of small scale transport processes on phytoplankton distribution in coastal seas.

PubMed

Hernández-Carrasco, Ismael; Orfila, Alejandro; Rossi, Vincent; Garçon, Veronique

2018-06-05

Coastal ocean ecosystems are major contributors to the global biogeochemical cycles and biological productivity. Physical factors induced by the turbulent flow play a crucial role in regulating marine ecosystems. However, while large-scale open-ocean dynamics is well described by geostrophy, the role of multiscale transport processes in coastal regions is still poorly understood due to the lack of continuous high-resolution observations. Here, the influence of small-scale dynamics (O(3.5-25) km, i.e. spanning upper submesoscale and mesoscale processes) on surface phytoplankton derived from satellite chlorophyll-a (Chl-a) is studied using Lagrangian metrics computed from High-Frequency Radar currents. The combination of complementary Lagrangian diagnostics, including the Lagrangian divergence along fluid trajectories, provides an improved description of the 3D flow geometry which facilitates the interpretation of two non-exclusive physical mechanisms affecting phytoplankton dynamics and patchiness. Attracting small-scale fronts, unveiled by backwards Lagrangian Coherent Structures, are associated to negative divergence where particles and Chl-a standing stocks cluster. Filaments of positive divergence, representing large accumulated upward vertical velocities and suggesting accrued injection of subsurface nutrients, match areas with large Chl-a concentrations. Our findings demonstrate that an accurate characterization of small-scale transport processes is necessary to comprehend bio-physical interactions in coastal seas.

Toward a comprehensive landscape vegetation monitoring framework

NASA Astrophysics Data System (ADS)

Kennedy, Robert; Hughes, Joseph; Neeti, Neeti; Larrue, Tara; Gregory, Matthew; Roberts, Heather; Ohmann, Janet; Kane, Van; Kane, Jonathan; Hooper, Sam; Nelson, Peder; Cohen, Warren; Yang, Zhiqiang

2016-04-01

Blossoming Earth observation resources provide great opportunity to better understand land vegetation dynamics, but also require new techniques and frameworks to exploit their potential. Here, I describe several parallel projects that leverage time-series Landsat imagery to describe vegetation dynamics at regional and continental scales. At the core of these projects are the LandTrendr algorithms, which distill time-series earth observation data into periods of consistent long or short-duration dynamics. In one approach, we built an integrated, empirical framework to blend these algorithmically-processed time-series data with field data and lidar data to ascribe yearly change in forest biomass across the US states of Washington, Oregon, and California. In a separate project, we expanded from forest-only monitoring to full landscape land cover monitoring over the same regional scale, including both categorical class labels and continuous-field estimates. In these and other projects, we apply machine-learning approaches to ascribe all changes in vegetation to driving processes such as harvest, fire, urbanization, etc., allowing full description of both disturbance and recovery processes and drivers. Finally, we are moving toward extension of these same techniques to continental and eventually global scales using Google Earth Engine. Taken together, these approaches provide one framework for describing and understanding processes of change in vegetation communities at broad scales.

Dynamic occupancy models for explicit colonization processes

USGS Publications Warehouse

Broms, Kristin M.; Hooten, Mevin B.; Johnson, Devin S.; Altwegg, Res; Conquest, Loveday

2016-01-01

The dynamic, multi-season occupancy model framework has become a popular tool for modeling open populations with occupancies that change over time through local colonizations and extinctions. However, few versions of the model relate these probabilities to the occupancies of neighboring sites or patches. We present a modeling framework that incorporates this information and is capable of describing a wide variety of spatiotemporal colonization and extinction processes. A key feature of the model is that it is based on a simple set of small-scale rules describing how the process evolves. The result is a dynamic process that can account for complicated large-scale features. In our model, a site is more likely to be colonized if more of its neighbors were previously occupied and if it provides more appealing environmental characteristics than its neighboring sites. Additionally, a site without occupied neighbors may also become colonized through the inclusion of a long-distance dispersal process. Although similar model specifications have been developed for epidemiological applications, ours formally accounts for detectability using the well-known occupancy modeling framework. After demonstrating the viability and potential of this new form of dynamic occupancy model in a simulation study, we use it to obtain inference for the ongoing Common Myna (Acridotheres tristis) invasion in South Africa. Our results suggest that the Common Myna continues to enlarge its distribution and its spread via short distance movement, rather than long-distance dispersal. Overall, this new modeling framework provides a powerful tool for managers examining the drivers of colonization including short- vs. long-distance dispersal, habitat quality, and distance from source populations.

Discrete-state representation of ion permeation coupled to fast gating in a model of ClC chloride channels: comparison to multi-ion continuous space Brownian dynamics simulations.

PubMed

Coalson, Rob D; Cheng, Mary Hongying

2010-01-28

A discrete-state model of chloride ion motion in a ClC chloride channel is constructed, following a previously developed multi-ion continuous space model of the same system (Cheng, M. H.; Mamonov, A. B.; Dukes, J. W.; Coalson, R. D. J. Phys. Chem. B 2007, 111, 5956) that included a simplistic representation of the fast gate in this channel. The reducibility of the many-body continuous space to the eight discrete-state model considered in the present work is examined in detail by performing three-dimensional Brownian dynamics simulations of each allowed state-to-state transition in order to extract the appropriate rate constant for this process, and then inserting the pairwise rate constants thereby obtained into an appropriate set of kinetic master equations. Experimental properties of interest, including the rate of Cl(-) ion permeation through the open channel and the average rate of closing of the fast gate as a function of bulk Cl(-) ion concentrations in the intracellular and extracellular electrolyte reservoirs are computed. Good agreement is found between the results obtained via the eight discrete-state model versus the multi-ion continuous space model, thereby encouraging continued development of the discrete-state model to include more complex behaviors observed experimentally in these channels.

The ''self-stirred'' genome: Bulk and surface dynamics of the chromatin globule

NASA Astrophysics Data System (ADS)

Zidovska, Alexandra

Chromatin structure and dynamics control all aspects of DNA biology yet are poorly understood. In interphase, time between two cell divisions, chromatin fills the cell nucleus in its minimally condensed polymeric state. Chromatin serves as substrate to a number of biological processes, e.g. gene expression and DNA replication, which require it to become locally restructured. These are energy-consuming processes giving rise to non-equilibrium dynamics. Chromatin dynamics has been traditionally studied by imaging of fluorescently labeled nuclear proteins and single DNA-sites, thus focusing only on a small number of tracer particles. Recently, we developed an approach, displacement correlation spectroscopy (DCS) based on time-resolved image correlation analysis, to map chromatin dynamics simultaneously across the whole nucleus in cultured human cells. DCS revealed that chromatin movement was coherent across large regions (4-5 μm) for several seconds. Regions of coherent motion extended beyond the boundaries of single-chromosome territories, suggesting elastic coupling of motion over length scales much larger than those of genes. These large-scale, coupled motions were ATP-dependent and unidirectional for several seconds. Following these observations, we developed a hydrodynamic theory of active chromatin dynamics, using the two-fluid model and describing the content of cell nucleus as a chromatin solution, which is subject to both passive thermal fluctuations and active (ATP-consuming) scalar and vector events. In this work we continue in our efforts to elucidate the mechanism and function of the chromatin dynamics in interphase. We investigate the chromatin interactions with the nuclear envelope and compare the surface dynamics of the chromatin globule with its bulk dynamics.

A point process approach to identifying and tracking transitions in neural spiking dynamics in the subthalamic nucleus of Parkinson's patients

NASA Astrophysics Data System (ADS)

Deng, Xinyi; Eskandar, Emad N.; Eden, Uri T.

2013-12-01

Understanding the role of rhythmic dynamics in normal and diseased brain function is an important area of research in neural electrophysiology. Identifying and tracking changes in rhythms associated with spike trains present an additional challenge, because standard approaches for continuous-valued neural recordings—such as local field potential, magnetoencephalography, and electroencephalography data—require assumptions that do not typically hold for point process data. Additionally, subtle changes in the history dependent structure of a spike train have been shown to lead to robust changes in rhythmic firing patterns. Here, we propose a point process modeling framework to characterize the rhythmic spiking dynamics in spike trains, test for statistically significant changes to those dynamics, and track the temporal evolution of such changes. We first construct a two-state point process model incorporating spiking history and develop a likelihood ratio test to detect changes in the firing structure. We then apply adaptive state-space filters and smoothers to track these changes through time. We illustrate our approach with a simulation study as well as with experimental data recorded in the subthalamic nucleus of Parkinson's patients performing an arm movement task. Our analyses show that during the arm movement task, neurons underwent a complex pattern of modulation of spiking intensity characterized initially by a release of inhibitory control at 20-40 ms after a spike, followed by a decrease in excitatory influence at 40-60 ms after a spike.

Development of a Rolling Dynamic Deflectometer for Continuous Deflection Testing of Pavements

DOT National Transportation Integrated Search

1998-05-01

A rolling dynamic deflectometer (RDD) was developed as a nondestructive method for determining continuous deflection profiles of pavements. Unlike other commonly used pavement testing methods, the RDD performs continuous rather than discrete measurem...

Risk assessment of occupational exposure to benzene using numerical simulation in a complex geometry of a reforming unit of petroleum refinery.

PubMed

Bayatian, Majid; Ashrafi, Khosro; Azari, Mansour Rezazadeh; Jafari, Mohammad Javad; Mehrabi, Yadollah

2018-04-01

There has been an increasing concern about the continuous and the sudden release of volatile organic pollutants from petroleum refineries and occupational and environmental exposures. Benzene is one of the most prevalent volatile compounds, and it has been addressed by many authors for its potential toxicity in occupational and environmental settings. Due to the complexities of sampling and analysis of benzene in routine and accidental situations, a reliable estimation of the benzene concentration in the outdoor setting of refinery using a computational fluid dynamics (CFD) could be instrumental for risk assessment of occupational exposure. In the present work, a computational fluid dynamic model was applied for exposure risk assessment with consideration of benzene being released continuously from a reforming unit of a refinery. For simulation of benzene dispersion, GAMBIT, FLUENT, and CFD post software are used as preprocessing, processing, and post-processing, respectively. Computational fluid dynamic validation was carried out by comparing the computed data with the experimental measurements. Eventually, chronic daily intake and lifetime cancer risk for routine operations through the two seasons of a year are estimated through the simulation model. Root mean square errors are 0.19 and 0.17 for wind speed and concentration, respectively. Lifetime risk assessments of workers are 0.4-3.8 and 0.0096-0.25 per 1000 workers in stable and unstable atmospheric conditions, respectively. Exposure risk is unacceptable for the head of shift work, chief engineer, and general workers in 141 days (38.77%) in a year. The results of this study show that computational fluid dynamics is a useful tool for modeling of benzene exposure in a complex geometry and can be used to estimate lifetime risks of occupation groups in a refinery setting.

Portraying emotions at their unfolding: a multilayered approach for probing dynamics of neural networks.

PubMed

Raz, Gal; Winetraub, Yonatan; Jacob, Yael; Kinreich, Sivan; Maron-Katz, Adi; Shaham, Galit; Podlipsky, Ilana; Gilam, Gadi; Soreq, Eyal; Hendler, Talma

2012-04-02

Dynamic functional integration of distinct neural systems plays a pivotal role in emotional experience. We introduce a novel approach for studying emotion-related changes in the interactions within and between networks using fMRI. It is based on continuous computation of a network cohesion index (NCI), which is sensitive to both strength and variability of signal correlations between pre-defined regions. The regions encompass three clusters (namely limbic, medial prefrontal cortex (mPFC) and cognitive), each previously was shown to be involved in emotional processing. Two sadness-inducing film excerpts were viewed passively, and comparisons between viewer's rated sadness, parasympathetic, and inter-NCI and intra-NCI were obtained. Limbic intra-NCI was associated with reported sadness in both movies. However, the correlation between the parasympathetic-index, the rated sadness and the limbic-NCI occurred in only one movie, possibly related to a "deactivated" pattern of sadness. In this film, rated sadness intensity also correlated with the mPFC intra-NCI, possibly reflecting temporal correspondence between sadness and sympathy. Further, only for this movie, we found an association between sadness rating and the mPFC-limbic inter-NCI time courses. To the contrary, in the other film in which sadness was reported to commingle with horror and anger, dramatic events coincided with disintegration of these networks. Together, this may point to a difference between the cinematic experiences with regard to inter-network dynamics related to emotional regulation. These findings demonstrate the advantage of a multi-layered dynamic analysis for elucidating the uniqueness of emotional experiences with regard to an unguided processing of continuous and complex stimulation. Copyright © 2012 Elsevier Inc. All rights reserved.

Continuity equation for probability as a requirement of inference over paths

NASA Astrophysics Data System (ADS)

González, Diego; Díaz, Daniela; Davis, Sergio

2016-09-01

Local conservation of probability, expressed as the continuity equation, is a central feature of non-equilibrium Statistical Mechanics. In the existing literature, the continuity equation is always motivated by heuristic arguments with no derivation from first principles. In this work we show that the continuity equation is a logical consequence of the laws of probability and the application of the formalism of inference over paths for dynamical systems. That is, the simple postulate that a system moves continuously through time following paths implies the continuity equation. The translation between the language of dynamical paths to the usual representation in terms of probability densities of states is performed by means of an identity derived from Bayes' theorem. The formalism presented here is valid independently of the nature of the system studied: it is applicable to physical systems and also to more abstract dynamics such as financial indicators, population dynamics in ecology among others.

About the discrete-continuous nature of a hematopoiesis model for Chronic Myeloid Leukemia.

PubMed

Gaudiano, Marcos E; Lenaerts, Tom; Pacheco, Jorge M

2016-12-01

Blood of mammals is composed of a variety of cells suspended in a fluid medium known as plasma. Hematopoiesis is the biological process of birth, replication and differentiation of blood cells. Despite of being essentially a stochastic phenomenon followed by a huge number of discrete entities, blood formation has naturally an associated continuous dynamics, because the cellular populations can - on average - easily be described by (e.g.) differential equations. This deterministic dynamics by no means contemplates some important stochastic aspects related to abnormal hematopoiesis, that are especially significant for studying certain blood cancer deceases. For instance, by mere stochastic competition against the normal cells, leukemic cells sometimes do not reach the population thereshold needed to kill the organism. Of course, a pure discrete model able to follow the stochastic paths of billons of cells is computationally impossible. In order to avoid this difficulty, we seek a trade-off between the computationally feasible and the biologically realistic, deriving an equation able to size conveniently both the discrete and continuous parts of a model for hematopoiesis in terrestrial mammals, in the context of Chronic Myeloid Leukemia. Assuming the cancer is originated from a single stem cell inside of the bone marrow, we also deduce a theoretical formula for the probability of non-diagnosis as a function of the mammal average adult mass. In addition, this work cellular dynamics analysis may shed light on understanding Peto's paradox, which is shown here as an emergent property of the discrete-continuous nature of the system. Copyright © 2016 Elsevier Inc. All rights reserved.

Peregrine rogue waves induced by the interaction between a continuous wave and a soliton.

PubMed

Yang, Guangye; Li, Lu; Jia, Suotang

2012-04-01

Based on the soliton solution on a continuous wave background for an integrable Hirota equation, the reduction mechanism and the characteristics of the Peregrine rogue wave in the propagation of femtosecond pulses of optical fiber are discussed. The results show that there exist two processes of the formation of the Peregrine rogue wave: one is the localized process of the continuous wave background, and the other is the reduction process of the periodization of the bright soliton. The characteristics of the Peregrine rogue wave are exhibited by strong temporal and spatial localization. Also, various initial excitations of the Peregrine rogue wave are performed and the results show that the Peregrine rogue wave can be excited by a small localized (single peak) perturbation pulse of the continuous wave background, even for the nonintegrable case. The numerical simulations show that the Peregrine rogue wave is unstable. Finally, through a realistic example, the influence of the self-frequency shift to the dynamics of the Peregrine rogue wave is discussed. The results show that in the absence of the self-frequency shift, the Peregrine rogue wave can split into several subpulses; however, when the self-frequency shift is considered, the Peregrine rogue wave no longer splits and exhibits mainly a peak changing and an increasing evolution property of the field amplitude.

Psychophysiological whole-brain network clustering based on connectivity dynamics analysis in naturalistic conditions.

PubMed

Raz, Gal; Shpigelman, Lavi; Jacob, Yael; Gonen, Tal; Benjamini, Yoav; Hendler, Talma

2016-12-01

We introduce a novel method for delineating context-dependent functional brain networks whose connectivity dynamics are synchronized with the occurrence of a specific psychophysiological process of interest. In this method of context-related network dynamics analysis (CRNDA), a continuous psychophysiological index serves as a reference for clustering the whole-brain into functional networks. We applied CRNDA to fMRI data recorded during the viewing of a sadness-inducing film clip. The method reliably demarcated networks in which temporal patterns of connectivity related to the time series of reported emotional intensity. Our work successfully replicated the link between network connectivity and emotion rating in an independent sample group for seven of the networks. The demarcated networks have clear common functional denominators. Three of these networks overlap with distinct empathy-related networks, previously identified in distinct sets of studies. The other networks are related to sensorimotor processing, language, attention, and working memory. The results indicate that CRNDA, a data-driven method for network clustering that is sensitive to transient connectivity patterns, can productively and reliably demarcate networks that follow psychologically meaningful processes. Hum Brain Mapp 37:4654-4672, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Unfolding Visual Lexical Decision in Time

PubMed Central

Barca, Laura; Pezzulo, Giovanni

2012-01-01

Visual lexical decision is a classical paradigm in psycholinguistics, and numerous studies have assessed the so-called “lexicality effect" (i.e., better performance with lexical than non-lexical stimuli). Far less is known about the dynamics of choice, because many studies measured overall reaction times, which are not informative about underlying processes. To unfold visual lexical decision in (over) time, we measured participants' hand movements toward one of two item alternatives by recording the streaming x,y coordinates of the computer mouse. Participants categorized four kinds of stimuli as “lexical" or “non-lexical:" high and low frequency words, pseudowords, and letter strings. Spatial attraction toward the opposite category was present for low frequency words and pseudowords. Increasing the ambiguity of the stimuli led to greater movement complexity and trajectory attraction to competitors, whereas no such effect was present for high frequency words and letter strings. Results fit well with dynamic models of perceptual decision-making, which describe the process as a competition between alternatives guided by the continuous accumulation of evidence. More broadly, our results point to a key role of statistical decision theory in studying linguistic processing in terms of dynamic and non-modular mechanisms. PMID:22563419

Perception of oral food breakdown. The concept of sensory trajectory.

PubMed

Lenfant, Francine; Loret, Chrystel; Pineau, Nicolas; Hartmann, Christoph; Martin, Nathalie

2009-06-01

Texture perceived in mouth largely depends on the behaviour of the food when it is broken down and transformed by the mouth elements. Texture results from a dynamic process in which texture attributes are continuously analysed by the oral sensory systems during mastication. However, the particular sequence of perceptual events that occur during oral food breakdown remains unknown. The aim of the present study is to describe the succession of perceptual events that happen in mouth during mastication and to show that for each food a texture pathway can be built. This for, we used a sensory method enabling to evaluate the dynamics of texture perceptions during food consumption: the Temporal Dominance of Sensation. On different breakfast cereals, we measured the sensation dominating at each point of the mastication process. We showed that the dynamics of appearance and disappearance of each texture sensation experienced in mouth during the eating process differed among cereals. However, some common features in this sensory trajectory were also observed for the category of products studied. Hardness, crackliness and crispness were rather perceived at the beginning of the mastication period, brittleness and lightness in the middle and stickiness at the end.

Knapsack - TOPSIS Technique for Vertical Handover in Heterogeneous Wireless Network

PubMed Central

2015-01-01

In a heterogeneous wireless network, handover techniques are designed to facilitate anywhere/anytime service continuity for mobile users. Consistent best-possible access to a network with widely varying network characteristics requires seamless mobility management techniques. Hence, the vertical handover process imposes important technical challenges. Handover decisions are triggered for continuous connectivity of mobile terminals. However, bad network selection and overload conditions in the chosen network can cause fallout in the form of handover failure. In order to maintain the required Quality of Service during the handover process, decision algorithms should incorporate intelligent techniques. In this paper, a new and efficient vertical handover mechanism is implemented using a dynamic programming method from the operation research discipline. This dynamic programming approach, which is integrated with the Technique to Order Preference by Similarity to Ideal Solution (TOPSIS) method, provides the mobile user with the best handover decisions. Moreover, in this proposed handover algorithm a deterministic approach which divides the network into zones is incorporated into the network server in order to derive an optimal solution. The study revealed that this method is found to achieve better performance and QoS support to users and greatly reduce the handover failures when compared to the traditional TOPSIS method. The decision arrived at the zone gateway using this operational research analytical method (known as the dynamic programming knapsack approach together with Technique to Order Preference by Similarity to Ideal Solution) yields remarkably better results in terms of the network performance measures such as throughput and delay. PMID:26237221

Knapsack--TOPSIS Technique for Vertical Handover in Heterogeneous Wireless Network.

PubMed

Malathy, E M; Muthuswamy, Vijayalakshmi

2015-01-01

In a heterogeneous wireless network, handover techniques are designed to facilitate anywhere/anytime service continuity for mobile users. Consistent best-possible access to a network with widely varying network characteristics requires seamless mobility management techniques. Hence, the vertical handover process imposes important technical challenges. Handover decisions are triggered for continuous connectivity of mobile terminals. However, bad network selection and overload conditions in the chosen network can cause fallout in the form of handover failure. In order to maintain the required Quality of Service during the handover process, decision algorithms should incorporate intelligent techniques. In this paper, a new and efficient vertical handover mechanism is implemented using a dynamic programming method from the operation research discipline. This dynamic programming approach, which is integrated with the Technique to Order Preference by Similarity to Ideal Solution (TOPSIS) method, provides the mobile user with the best handover decisions. Moreover, in this proposed handover algorithm a deterministic approach which divides the network into zones is incorporated into the network server in order to derive an optimal solution. The study revealed that this method is found to achieve better performance and QoS support to users and greatly reduce the handover failures when compared to the traditional TOPSIS method. The decision arrived at the zone gateway using this operational research analytical method (known as the dynamic programming knapsack approach together with Technique to Order Preference by Similarity to Ideal Solution) yields remarkably better results in terms of the network performance measures such as throughput and delay.

Microbiota Dynamics Associated with Environmental Conditions and Potential Roles of Cellulolytic Communities in Traditional Chinese Cereal Starter Solid-State Fermentation.

PubMed

Li, Pan; Liang, Hebin; Lin, Wei-Tie; Feng, Feng; Luo, Lixin

2015-08-01

Traditional Chinese solid-state fermented cereal starters contain highly complex microbial communities and enzymes. Very little is known, however, about the microbial dynamics related to environmental conditions, and cellulolytic communities have never been proposed to exist during cereal starter fermentation. In this study, we performed Illumina MiSeq sequencing combined with PCR-denaturing gradient gel electrophoresis to investigate microbiota, coupled with clone library construction to trace cellulolytic communities in both fermentation stages. A succession of microbial assemblages was observed during the fermentation of starters. Lactobacillales and Saccharomycetales dominated the initial stages, with a continuous decline in relative abundance. However, thermotolerant and drought-resistant Bacillales, Eurotiales, and Mucorales were considerably accelerated during the heating stages, and these organisms dominated until the end of fermentation. Enterobacteriales were consistently ubiquitous throughout the process. For the cellulolytic communities, only the genera Sanguibacter, Beutenbergia, Agrobacterium, and Erwinia dominated the initial fermentation stages. In contrast, stages at high incubation temperature induced the appearance and dominance of Bacillus, Aspergillus, and Mucor. The enzymatic dynamics of amylase and glucoamylase also showed a similar trend, with the activities clearly increased in the first 7 days and subsequently decreased until the end of fermentation. Furthermore, β-glucosidase activity continuously and significantly increased during the fermentation process. Evidently, cellulolytic potential can adapt to environmental conditions by changes in the community structure during the fermentation of starters. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Exploratory Study for Continuous-time Parameter Estimation of Ankle Dynamics

NASA Technical Reports Server (NTRS)

Kukreja, Sunil L.; Boyle, Richard D.

2014-01-01

Recently, a parallel pathway model to describe ankle dynamics was proposed. This model provides a relationship between ankle angle and net ankle torque as the sum of a linear and nonlinear contribution. A technique to identify parameters of this model in discrete-time has been developed. However, these parameters are a nonlinear combination of the continuous-time physiology, making insight into the underlying physiology impossible. The stable and accurate estimation of continuous-time parameters is critical for accurate disease modeling, clinical diagnosis, robotic control strategies, development of optimal exercise protocols for longterm space exploration, sports medicine, etc. This paper explores the development of a system identification technique to estimate the continuous-time parameters of ankle dynamics. The effectiveness of this approach is assessed via simulation of a continuous-time model of ankle dynamics with typical parameters found in clinical studies. The results show that although this technique improves estimates, it does not provide robust estimates of continuous-time parameters of ankle dynamics. Due to this we conclude that alternative modeling strategies and more advanced estimation techniques be considered for future work.

Atomic oxygen durability of solar concentrator materials for Space Station Freedom

NASA Technical Reports Server (NTRS)

Degroh, Kim K.; Terlep, Judith A.; Dever, Therese M.

1990-01-01

The findings are reviewed of atomic oxygen exposure testing of candidate solar concentrator materials containing SiO2 and Al2O3 protective coatings for use on Space Station Freedom solar dynamic power modules. Both continuous and iterative atomic oxygen exposure tests were conducted. Iterative air plasma ashing resulted in larger specular reflectance decreases and solar absorptance increases than continuous ashing to the same fluence, and appears to provide a more severe environment than the continuous atomic oxygen exposure that would occur in the low Earth orbit environment. First generation concentrator fabrication techniques produced surface defects including scratches, macroscopic bumps, dendritic regions, porosity, haziness, and pin hole defects. Several of these defects appear to be preferential sites for atomic oxygen attack leading to erosive undercutting. Extensive undercutting and flaking of reflective and protective coatings were found to be promoted through an undercutting tearing propagation process. Atomic oxygen erosion processes and effects on optical performance is presented.

The Metastable Brain

PubMed Central

Tognoli, Emmanuelle; Kelso, J. A. Scott

2014-01-01

Neural ensembles oscillate across a broad range of frequencies and are transiently coupled or “bound” together when people attend to a stimulus, perceive, think and act. This is a dynamic, self-assembling process, with parts of the brain engaging and disengaging in time. But how is it done? The theory of Coordination Dynamics proposes a mechanism called metastability, a subtle blend of integration and segregation. Tendencies for brain regions to express their individual autonomy and specialized functions (segregation, modularity) coexist with tendencies to couple and coordinate globally for multiple functions (integration). Although metastability has garnered increasing attention, it has yet to be demonstrated and treated within a fully spatiotemporal perspective. Here, we illustrate metastability in continuous neural and behavioral recordings, and we discuss theory and experiments at multiple scales suggesting that metastable dynamics underlie the real-time coordination necessary for the brain's dynamic cognitive, behavioral and social functions. PMID:24411730

The Peace Mediator effect: Heterogeneous agents can foster consensus in continuous opinion models

NASA Astrophysics Data System (ADS)

Vilone, Daniele; Carletti, Timoteo; Bagnoli, Franco; Guazzini, Andrea

2016-11-01

Statistical mechanics has proven to be able to capture the fundamental rules underlying phenomena of social aggregation and opinion dynamics, well studied in disciplines like sociology and psychology. This approach is based on the underlying paradigm that the interesting dynamics of multi-agent systems emerge from the correct definition of few parameters governing the evolution of each individual. In this context, we propose a particular model of opinion dynamics based on the psychological construct named ;cognitive dissonance;. Our system is made of interacting individuals, the agents, each bearing only two dynamical variables (respectively ;opinion; and ;affinity;) self-consistently adjusted during time evolution. We also define two special classes of interacting entities, both acting for a peace mediation process but via different course of action: ;diplomats; and ;auctoritates;. The behavior of the system with and without peace mediators (PMs) is investigated and discussed with reference to corresponding psychological and social implications.

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

Microstructure evolution and texture development in a friction stir-processed AISI D2 tool steel

NASA Astrophysics Data System (ADS)

Yasavol, N.; Abdollah-zadeh, A.; Vieira, M. T.; Jafarian, H. R.

2014-02-01

Crystallographic texture developments during friction stir processing (FSP) of AISI D2 tool were studied with respect to grain sizes in different tool rotation rates. Comparison of the grain sizes in various rotation rates confirmed that grain refinement occurred progressively in higher rotation rates by severe plastic deformation. It was found that the predominant mechanism during FSP should be dynamic recovery (DRV) happened concurrently with continuous dynamic recrystallization (CDRX) caused by particle-stimulated nucleation (PSN). The developed shear texture relates to the ideal shear textures of D1 and D2 in bcc metals. The prevalence of highly dense arrangement of close-packed planes of bcc and the lowest Taylor factor showed the lowest compressive residual stress which is responsible for better mechanical properties compared with the grain-precipitate refinement.

Modeling Common-Sense Decisions in Artificial Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail

2010-01-01

A methodology has been conceived for efficient synthesis of dynamical models that simulate common-sense decision- making processes. This methodology is intended to contribute to the design of artificial-intelligence systems that could imitate human common-sense decision making or assist humans in making correct decisions in unanticipated circumstances. This methodology is a product of continuing research on mathematical models of the behaviors of single- and multi-agent systems known in biology, economics, and sociology, ranging from a single-cell organism at one extreme to the whole of human society at the other extreme. Earlier results of this research were reported in several prior NASA Tech Briefs articles, the three most recent and relevant being Characteristics of Dynamics of Intelligent Systems (NPO -21037), NASA Tech Briefs, Vol. 26, No. 12 (December 2002), page 48; Self-Supervised Dynamical Systems (NPO-30634), NASA Tech Briefs, Vol. 27, No. 3 (March 2003), page 72; and Complexity for Survival of Living Systems (NPO- 43302), NASA Tech Briefs, Vol. 33, No. 7 (July 2009), page 62. The methodology involves the concepts reported previously, albeit viewed from a different perspective. One of the main underlying ideas is to extend the application of physical first principles to the behaviors of living systems. Models of motor dynamics are used to simulate the observable behaviors of systems or objects of interest, and models of mental dynamics are used to represent the evolution of the corresponding knowledge bases. For a given system, the knowledge base is modeled in the form of probability distributions and the mental dynamics is represented by models of the evolution of the probability densities or, equivalently, models of flows of information. Autonomy is imparted to the decisionmaking process by feedback from mental to motor dynamics. This feedback replaces unavailable external information by information stored in the internal knowledge base. Representation of the dynamical models in a parameterized form reduces the task of common-sense-based decision making to a solution of the following hetero-associated-memory problem: store a set of m predetermined stochastic processes given by their probability distributions in such a way that when presented with an unexpected change in the form of an input out of the set of M inputs, the coupled motormental dynamics converges to the corresponding one of the m pre-assigned stochastic process, and a sample of this process represents the decision.

Continuous data assimilation for downscaling large-footprint soil moisture retrievals

NASA Astrophysics Data System (ADS)

Altaf, Muhammad U.; Jana, Raghavendra B.; Hoteit, Ibrahim; McCabe, Matthew F.

2016-10-01

Soil moisture is a key component of the hydrologic cycle, influencing processes leading to runoff generation, infiltration and groundwater recharge, evaporation and transpiration. Generally, the measurement scale for soil moisture is found to be different from the modeling scales for these processes. Reducing this mismatch between observation and model scales in necessary for improved hydrological modeling. An innovative approach to downscaling coarse resolution soil moisture data by combining continuous data assimilation and physically based modeling is presented. In this approach, we exploit the features of Continuous Data Assimilation (CDA) which was initially designed for general dissipative dynamical systems and later tested numerically on the incompressible Navier-Stokes equation, and the Benard equation. A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model's large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (HYDRUS) are subjected to data assimilation conditioned upon coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. Results show that the approach is feasible to generate fine scale soil moisture fields across large extents, based on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.

Magnetization Dynamics and Anisotropy in Ferromagnetic/Antiferromagnetic Ni/NiO Bilayers

NASA Astrophysics Data System (ADS)

Petersen, Andreas

We begin by defining the concept of `open' Markov processes, which are continuous-time Markov chains where probability can flow in and out through certain `boundary' states. We study open Markov processes which in the absence of such boundary flows admit equilibrium states satisfying detailed balance, meaning that the net flow of probability vanishes between all pairs of states. External couplings which fix the probabilities of boundary states can maintain such systems in non-equilibrium steady states in which non-zero probability currents flow. We show that these non-equilibrium steady states minimize a quadratic form which we call 'dissipation.' This is closely related to Prigogine's principle of minimum entropy production. We bound the rate of change of the entropy of a driven non-equilibrium steady state relative to the underlying equilibrium state in terms of the flow of probability through the boundary of the process. We then consider open Markov processes as morphisms in a symmetric monoidal category by splitting up their boundary states into certain sets of `inputs' and `outputs.' Composition corresponds to gluing the outputs of one such open Markov process onto the inputs of another so that the probability flowing out of the first process is equal to the probability flowing into the second. Tensoring in this category corresponds to placing two such systems side by side. We construct a `black-box' functor characterizing the behavior of an open Markov process in terms of the space of possible steady state probabilities and probability currents along the boundary. The fact that this is a functor means that the behavior of a composite open Markov process can be computed by composing the behaviors of the open Markov processes from which it is composed. We prove a similar black-boxing theorem for reaction networks whose dynamics are given by the non-linear rate equation. Along the way we describe a more general category of open dynamical systems where composition corresponds to gluing together open dynamical systems.

Microbial oceanography and the Hawaii Ocean Time-series programme.

PubMed

Karl, David M; Church, Matthew J

2014-10-01

The Hawaii Ocean Time-series (HOT) programme has been tracking microbial and biogeochemical processes in the North Pacific Subtropical Gyre since October 1988. The near-monthly time series observations have revealed previously undocumented phenomena within a temporally dynamic ecosystem that is vulnerable to climate change. Novel microorganisms, genes and unexpected metabolic pathways have been discovered and are being integrated into our evolving ecological paradigms. Continued research, including higher-frequency observations and at-sea experimentation, will help to provide a comprehensive scientific understanding of microbial processes in the largest biome on Earth.

Spatial price dynamics: From complex network perspective

NASA Astrophysics Data System (ADS)

Li, Y. L.; Bi, J. T.; Sun, H. J.

2008-10-01

The spatial price problem means that if the supply price plus the transportation cost is less than the demand price, there exists a trade. Thus, after an amount of exchange, the demand price will decrease. This process is continuous until an equilibrium state is obtained. However, how the trade network structure affects this process has received little attention. In this paper, we give a evolving model to describe the levels of spatial price on different complex network structures. The simulation results show that the network with shorter path length is sensitive to the variation of prices.

Dynamic Environmental Photosynthetic Imaging Reveals Emergent Phenotypes

DOE PAGES

Cruz, Jeffrey A.; Savage, Linda J.; Zegarac, Robert; ...

2016-06-22

Understanding and improving the productivity and robustness of plant photosynthesis requires high-throughput phenotyping under environmental conditions that are relevant to the field. Here we demonstrate the dynamic environmental photosynthesis imager (DEPI), an experimental platform for integrated, continuous, and high-throughput measurements of photosynthetic parameters during plant growth under reproducible yet dynamic environmental conditions. Using parallel imagers obviates the need to move plants or sensors, reducing artifacts and allowing simultaneous measurement on large numbers of plants. As a result, DEPI can reveal phenotypes that are not evident under standard laboratory conditions but emerge under progressively more dynamic illumination. We show examples inmore » mutants of Arabidopsis of such “emergent phenotypes” that are highly transient and heterogeneous, appearing in different leaves under different conditions and depending in complex ways on both environmental conditions and plant developmental age. Finally, these emergent phenotypes appear to be caused by a range of phenomena, suggesting that such previously unseen processes are critical for plant responses to dynamic environments.« less

Using T-Z plots as a graphical method to infer lithological variations from growth strata

NASA Astrophysics Data System (ADS)

Castelltort, Sébastien; Pochat, Stéphane; Van Den Driessche, Jean

2004-08-01

The 'T-Z plot' method consists of plotting the throw of sedimentary horizons across a growth fault versus their depth in the hanging wall. This method has been initially developed for the analysis of growth fault kinematics from seismic data. A brief analytical examination of such plots shows that they can also provide valuable information about the evolution of fault topography. When growth is a continuous process, stages of topography creation (fault scarp) and filling (of the space available in the hanging-wall) are related to non-dynamic (draping, mud-prone pelagic settling) and dynamic (sand-prone, dynamically deposited) sedimentation, respectively. In this case, the T-Z plot analysis becomes a powerful tool to predict major lithological variations on seismic profiles in faulted settings.

Kibble-Zurek scaling and string-net coarsening in topologically ordered systems.

PubMed

Chandran, Anushya; Burnell, F J; Khemani, Vedika; Sondhi, S L

2013-10-09

We consider the non-equilibrium dynamics of topologically ordered systems driven across a continuous phase transition into proximate phases with no, or reduced, topological order. This dynamics exhibits scaling in the spirit of Kibble and Zurek but now without the presence of symmetry breaking and a local order parameter. The late stages of the process are seen to exhibit a slow, coarsening dynamics for the string-net that underlies the physics of the topological phase, a potentially interesting signature of topological order. We illustrate these phenomena in the context of particular phase transitions out of the Abelian Z2 topologically ordered phase of the toric code/Z2 gauge theory, and the non-Abelian SU(2)k ordered phases of the relevant Levin-Wen models.

Discotic columnar liquid crystal studied in the bulk and nanoconfined states by molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Busselez, Rémi; Cerclier, Carole V.; Ndao, Makha; Ghoufi, Aziz; Lefort, Ronan; Morineau, Denis

2014-10-01

A prototypical Gay Berne discotic liquid crystal was studied by means of molecular dynamics simulations both in the bulk state and under confinement in a nanoporous channel. The phase behavior of the confined system strongly differs from its bulk counterpart: the bulk isotropic-to-columnar transition is replaced by a continuous ordering from a paranematic to a columnar phase. Moreover, a new transition is observed at a lower temperature in the confined state, which corresponds to a reorganization of the intercolumnar order. It reflects the competing effects of pore surface interaction and genuine hexagonal packing of the columns. The translational molecular dynamics in the different phases has been thoroughly studied and discussed in terms of collective relaxation modes, non-Gaussian behavior, and hopping processes.

Quantitative phase-contrast digital holographic microscopy for cell dynamic evaluation

NASA Astrophysics Data System (ADS)

Yu, Lingfeng; Mohanty, Samarendra; Berns, Michael W.; Chen, Zhongping

2009-02-01

The laser microbeam uses lasers to alter and/or to ablate intracellular organelles and cellular and tissue samples, and, today, has become an important tool for cell biologists to study the molecular mechanism of complex biological systems by removing individual cells or sub-cellular organelles. However, absolute quantitation of the localized alteration/damage to transparent phase objects, such as the cell membrane or chromosomes, was not possible using conventional phase-contrast or differential interference contrast microscopy. We report the development of phase-contrast digital holographic microscopy for quantitative evaluation of cell dynamic changes in real time during laser microsurgery. Quantitative phase images are recorded during the process of laser microsurgery and thus, the dynamic change in phase can be continuously evaluated. Out-of-focus organelles are re-focused by numerical reconstruction algorithms.

Every day I'm rufflin': Calcium sensing and actin dynamics in the growth factor-independent membrane ruffling of professional phagocytes.

PubMed

Schlam, Daniel; Canton, Johnathan

2017-04-03

Professional phagocytes continuously extend dynamic, actin-driven membrane protrusions. These protrusions, often referred to as membrane ruffles, serve a critical role in the essential phagocyte processes of macropinocytosis and phagocytosis. Small GTPases, such as RAC1/2, spatially and temporally regulate membrane ruffle formation. We have recently shown that extracellular calcium regulates the elaboration of membrane ruffles primarily through the synthesis of phosphatidic acid (PtdOH) at the plasma membrane. RAC1/2 guanine nucleotide exchange factors harbouring polybasic stretches are recruited by PtdOH to sites of ruffle formation. Here we discuss our findings and offer perspectives on how the regulation of dynamic actin structures at the plasma membrane by small GTPases is a critical component of phagocyte function.

Creating the Future: Research and Technology

NASA Technical Reports Server (NTRS)

1998-01-01

With the many different technical talents, Marshall Space Flight Center (MSFC) continues to be an important force behind many scientific breakthroughs. The MSFC's annual report reviews the technology developments, research in space and microgravity sciences, studies in space system concepts, and technology transfer. The technology development programs include development in: (1) space propulsion and fluid management, (2) structures and dynamics, (3) materials and processes and (4) avionics and optics.

Reaction-induced porosity fingering: Replacement dynamic and porosity evolution in the KBr-KCl system

NASA Astrophysics Data System (ADS)

Beaudoin, Nicolas; Hamilton, Andrea; Koehn, Daniel; Shipton, Zoe Kai; Kelka, Ulrich

2018-07-01

In this contribution, we use X-ray computed micro-tomography (X-CT) to observe and quantify dynamic pattern and porosity formation in a fluid-mediated replacement reaction. The evolution of connected porosity distribution helps to understand how fluid can migrate through a transforming rock, for example during dolomitization, a phenomenon extensively reported in sedimentary basins. Two types of experiment were carried out, in both cases a single crystal of KBr was immersed in a static bath of saturated aqueous KCl at room temperature and atmospheric pressure, and in both cases the replacement process was monitored in 3D using X-CT. In the first type of experiment a crystal of KBr was taken out, scanned, and returned to the solution in cycles (discontinuous replacement). In the second type of experiment, 3 samples of KBr were continuously reacted for 15, 55 min and 5.5 h respectively, with the latter being replaced completely (continuous replacement). X-CT of KBr-KCl replacement offers new insights into dynamic porosity development and transport mechanisms during replacement. As the reaction progresses the sample composition changes from KBr to KCl via a K(Br, Cl) solid solution series which generates porosity in the form of fingers that account for a final molar volume reduction of 13% when pure KCl is formed. These fingers form during an initial and transient advection regime followed by a diffusion dominated system, which is reflected by the reaction propagation, front morphology, and mass evolution. The porosity develops as fingers perpendicular to the sample walls, which allow a faster transport of reactant than in the rest of the crystal, before fingers coarsen and connect laterally. In the continuous experiment, finger coarsening has a dynamic behaviour consistent with fingering processes observed in nature. In the discontinuous experiment, which can be compared to rock weathering or to replacement driven by intermittent fluid contact, the pore structure changes from well-organized parallel fingers to a complex 3D connected network, shedding light on the alteration of reservoir properties during weathering.

A mathematical approach to HIV infection dynamics

NASA Astrophysics Data System (ADS)

Ida, A.; Oharu, S.; Oharu, Y.

2007-07-01

In order to obtain a comprehensive form of mathematical models describing nonlinear phenomena such as HIV infection process and AIDS disease progression, it is efficient to introduce a general class of time-dependent evolution equations in such a way that the associated nonlinear operator is decomposed into the sum of a differential operator and a perturbation which is nonlinear in general and also satisfies no global continuity condition. An attempt is then made to combine the implicit approach (usually adapted for convective diffusion operators) and explicit approach (more suited to treat continuous-type operators representing various physiological interactions), resulting in a semi-implicit product formula. Decomposing the operators in this way and considering their individual properties, it is seen that approximation-solvability of the original model is verified under suitable conditions. Once appropriate terms are formulated to describe treatment by antiretroviral therapy, the time-dependence of the reaction terms appears, and such product formula is useful for generating approximate numerical solutions to the governing equations. With this knowledge, a continuous model for HIV disease progression is formulated and physiological interpretations are provided. The abstract theory is then applied to show existence of unique solutions to the continuous model describing the behavior of the HIV virus in the human body and its reaction to treatment by antiretroviral therapy. The product formula suggests appropriate discrete models describing the dynamics of host pathogen interactions with HIV1 and is applied to perform numerical simulations based on the model of the HIV infection process and disease progression. Finally, the results of our numerical simulations are visualized and it is observed that our results agree with medical and physiological aspects.

Microscopic dynamics research on the "mature" process of dye-sensitized solar cells after injection of highly concentrated electrolyte.

PubMed

Liang, Zhongguan; Liu, Weiqing; Chen, Jun; Hu, Linhua; Dai, Songyuan

2015-01-21

After injection of electrolyte, the internal three-dimensional solid-liquid penetration system of dye-sensitized solar cells (DSCs) can take a period of time to reach "mature" state. This paper studies the changes of microscopic processes of DSCs including TiO2 energy-level movement, localized state distribution, charge accumulation, electron transport, and recombination dynamics, from the beginning of electrolyte injection to the time of reached mature state. The results show that the microscopic dynamics process of DSCs exhibited a time-dependent behavior and achieved maturity ∼12 h after injecting the electrolyte into DSCs. Within 0-12 h, several results were observed: (1) the conduction band edge of TiO2 moved slightly toward negative potential direction; (2) the localized states in the band gap of TiO2 was reduced according to the same distribution law; (3) the transport resistance in TiO2 film increased, and electron transport time was prolonged as the time of maturity went on, which indicated that the electron transport process is impeded gradually; (4) the recombination resistance at the TiO2/electrolyte (EL) interface increases, and electron lifetime gradually extends, therefore, the recombination process is continuously suppressed. Furthermore, results suggest that the parameters of EL/Pt-transparent conductive oxide (TCO) interface including the interfacial capacitance, electron-transfer resistance, and transfer time constant would change with time of maturity, indicating that the EL/Pt-TCO interface is a potential factor affecting the mature process of DSCs.

Assessing Measles Transmission in the United States Following a Large Outbreak in California

PubMed Central

Blumberg, Seth; Worden, Lee; Enanoria, Wayne; Ackley, Sarah; Deiner, Michael; Liu, Fengchen; Gao, Daozhou; Lietman, Thomas; Porco, Travis

2015-01-01

The recent increase in measles cases in California may raise questions regarding the continuing success of measles control. To determine whether the dynamics of measles is qualitatively different in comparison to previous years, we assess whether the 2014-2015 measles outbreak associated with an Anaheim theme park is consistent with subcriticality by calculating maximum-likelihood estimates for the effective reproduction numbe given this year’s outbreak, using the Galton-Watson branching process model. We find that the dynamics after the initial transmission event are consistent with prior transmission, but does not exclude the possibilty that the effective reproduction number has increased. PMID:26052471

A challenge to chaotic itinerancy from brain dynamics

NASA Astrophysics Data System (ADS)

Kay, Leslie M.

2003-09-01

Brain hermeneutics and chaotic itinerancy proposed by Tsuda are attractive characterizations of perceptual dynamics in the mammalian olfactory system. This theory proposes that perception occurs at the interface between itinerant neural representation and interaction with the environment. Quantifiable application of these dynamics has been hampered by the lack of definable history and action processes which characterize the changes induced by behavioral state, attention, and learning. Local field potentials measured from several brain areas were used to characterize dynamic activity patterns for their use as representations of history and action processes. The signals were recorded from olfactory areas (olfactory bulb, OB, and pyriform cortex) and hippocampal areas (entorhinal cortex and dentate gyrus, DG) in the brains of rats. During odor-guided behavior the system shows dynamics at three temporal scales. Short time-scale changes are system-wide and can occur in the space of a single sniff. They are predictable, associated with learned shifts in behavioral state and occur periodically on the scale of the intertrial interval. These changes occupy the theta (2-12 Hz), beta (15-30 Hz), and gamma (40-100 Hz) frequency bands within and between all areas. Medium time-scale changes occur relatively unpredictably, manifesting in these data as alterations in connection strength between the OB and DG. These changes are strongly correlated with performance in associated trial blocks (5-10 min) and may be due to fluctuations in attention, mood, or amount of reward received. Long time-scale changes are likely related to learning or decline due to aging or disease. These may be modeled as slow monotonic processes that occur within or across days or even weeks or years. The folding of different time scales is proposed as a mechanism for chaotic itinerancy, represented by dynamic processes instead of static connection strengths. Thus, the individual maintains continuity of experience within the stability of fast periodic and slow monotonic processes, while medium scale events alter experience and performance dramatically but temporarily. These processes together with as yet to be determined action effects from motor system feedback are proposed as an instantiation of brain hermeneutics and chaotic itinerancy.

Systematic Computation of Nonlinear Cellular and Molecular Dynamics with Low-Power CytoMimetic Circuits: A Simulation Study

PubMed Central

Papadimitriou, Konstantinos I.; Stan, Guy-Bart V.; Drakakis, Emmanuel M.

2013-01-01

This paper presents a novel method for the systematic implementation of low-power microelectronic circuits aimed at computing nonlinear cellular and molecular dynamics. The method proposed is based on the Nonlinear Bernoulli Cell Formalism (NBCF), an advanced mathematical framework stemming from the Bernoulli Cell Formalism (BCF) originally exploited for the modular synthesis and analysis of linear, time-invariant, high dynamic range, logarithmic filters. Our approach identifies and exploits the striking similarities existing between the NBCF and coupled nonlinear ordinary differential equations (ODEs) typically appearing in models of naturally encountered biochemical systems. The resulting continuous-time, continuous-value, low-power CytoMimetic electronic circuits succeed in simulating fast and with good accuracy cellular and molecular dynamics. The application of the method is illustrated by synthesising for the first time microelectronic CytoMimetic topologies which simulate successfully: 1) a nonlinear intracellular calcium oscillations model for several Hill coefficient values and 2) a gene-protein regulatory system model. The dynamic behaviours generated by the proposed CytoMimetic circuits are compared and found to be in very good agreement with their biological counterparts. The circuits exploit the exponential law codifying the low-power subthreshold operation regime and have been simulated with realistic parameters from a commercially available CMOS process. They occupy an area of a fraction of a square-millimetre, while consuming between 1 and 12 microwatts of power. Simulations of fabrication-related variability results are also presented. PMID:23393550

PP/EPDM-blends by dynamic vulcanization: Influence of increasing peroxide concentration on mechanical, morphological and rheological characteristics

NASA Astrophysics Data System (ADS)

Patermann, S.; Altstädt, V.

2014-05-01

Thermoplastic vulcanizates (TPVs) combine the elastic properties of thermoset cross-linked rubbers with the melt processability of thermoplastics. The most representative examples of this class are the TPVs based on polypropylene (PP) and ethylene-propylenediene terpolymer rubber (EPDM). The PP/EPDM blends were produced by dynamic vulcanization in a continuous extrusion process. The influence of different peroxide concentrations was studied with regard to cross-link density, compression set, tensile strength/elongation at break and morphology. With increasing peroxide concentration, the cross-link density increases, leading to a reduction of the compression set by 50 %. The cross-linked blends show smaller dispersed EPDM particles than the uncured one. With a peroxide concentration between 0.2 and 0.6 % a maximum in tensile strength and elongation at break was found and with increasing peroxide concentration, the complex viscosity of the TPVs decreases. Compared to batch processes, the results show nearly the same trends.

Boussinesq approximation of the Cahn-Hilliard-Navier-Stokes equations.

PubMed

Vorobev, Anatoliy

2010-11-01

We use the Cahn-Hilliard approach to model the slow dissolution dynamics of binary mixtures. An important peculiarity of the Cahn-Hilliard-Navier-Stokes equations is the necessity to use the full continuity equation even for a binary mixture of two incompressible liquids due to dependence of mixture density on concentration. The quasicompressibility of the governing equations brings a short time-scale (quasiacoustic) process that may not affect the slow dynamics but may significantly complicate the numerical treatment. Using the multiple-scale method we separate the physical processes occurring on different time scales and, ultimately, derive the equations with the filtered-out quasiacoustics. The derived equations represent the Boussinesq approximation of the Cahn-Hilliard-Navier-Stokes equations. This approximation can be further employed as a universal theoretical model for an analysis of slow thermodynamic and hydrodynamic evolution of the multiphase systems with strongly evolving and diffusing interfacial boundaries, i.e., for the processes involving dissolution/nucleation, evaporation/condensation, solidification/melting, polymerization, etc.

Unveiling the structural arrangements responsible for the atomic dynamics in metallic glasses during physical aging

NASA Astrophysics Data System (ADS)

Giordano, V. M.; Ruta, B.

2016-01-01

Understanding and controlling physical aging, that is, the spontaneous temporal evolution of out-of-equilibrium systems, represents one of the greatest tasks in material science. Recent studies have revealed the existence of a complex atomic motion in metallic glasses, with different aging regimes in contrast with the typical continuous aging observed in macroscopic quantities. By combining dynamical and structural synchrotron techniques, here for the first time we directly connect previously identified microscopic structural mechanisms with the peculiar atomic motion, providing a broader unique view of their complexity. We show that the atomic scale is dominated by the interplay between two processes: rearrangements releasing residual stresses related to a cascade mechanism of relaxation, and medium range ordering processes, which do not affect the local density, likely due to localized relaxations of liquid-like regions. As temperature increases, a surprising additional secondary relaxation process sets in, together with a faster medium range ordering, likely precursors of crystallization.

Postnatal brain development: Structural imaging of dynamic neurodevelopmental processes

PubMed Central

Jernigan, Terry L.; Baaré, William F. C.; Stiles, Joan; Madsen, Kathrine Skak

2013-01-01

After birth, there is striking biological and functional development of the brain’s fiber tracts as well as remodeling of cortical and subcortical structures. Behavioral development in children involves a complex and dynamic set of genetically guided processes by which neural structures interact constantly with the environment. This is a protracted process, beginning in the third week of gestation and continuing into early adulthood. Reviewed here are studies using structural imaging techniques, with a special focus on diffusion weighted imaging, describing age-related brain maturational changes in children and adolescents, as well as studies that link these changes to behavioral differences. Finally, we discuss evidence for effects on the brain of several factors that may play a role in mediating these brain–behavior associations in children, including genetic variation, behavioral interventions, and hormonal variation associated with puberty. At present longitudinal studies are few, and we do not yet know how variability in individual trajectories of biological development in specific neural systems map onto similar variability in behavioral trajectories. PMID:21489384

A mobile system for assessment of physiological response to posture transitions.

PubMed

Jovanov, Emil; Milosevic, Mladen; Milenković, Aleksandar

2013-01-01

Posture changes initiate a dynamic physiological response that can be used as an indicator of the overall health status. We introduce an inconspicuous mobile wellness monitoring system (imWell) that continuously assesses the dynamic physiological response to posture transitions during activities of daily living. imWell utilizes a Zephyr BioHarness 3 physiological monitor that continually reports heart activity and physical activity via Bluetooth to a personal device (e.g. smartphone). The personal device processes the reported activity data in real-time to recognize posture transitions from the accelerometer data and to characterize dynamic heart response to posture changes. It annotates, logs, and uploads the heart activity data to our mHealth server. In this paper we present algorithms for detection of posture transitions and heart activity characterization during a sit-to-stand transition. The proposed system was tested on seven healthy subjects performing a predefined protocol. The total average and standard deviation for sit-to-stand transition time is 2.7 ± 0.69 s, resulting in the change of heart rate of 27.36 ± 9.30 bpm (from 63.3 ± 9.02 bpm to 90.66 ± 10.09 bpm).

Virtualized Traffic: reconstructing traffic flows from discrete spatiotemporal data.

PubMed

Sewall, Jason; van den Berg, Jur; Lin, Ming C; Manocha, Dinesh

2011-01-01

We present a novel concept, Virtualized Traffic, to reconstruct and visualize continuous traffic flows from discrete spatiotemporal data provided by traffic sensors or generated artificially to enhance a sense of immersion in a dynamic virtual world. Given the positions of each car at two recorded locations on a highway and the corresponding time instances, our approach can reconstruct the traffic flows (i.e., the dynamic motions of multiple cars over time) between the two locations along the highway for immersive visualization of virtual cities or other environments. Our algorithm is applicable to high-density traffic on highways with an arbitrary number of lanes and takes into account the geometric, kinematic, and dynamic constraints on the cars. Our method reconstructs the car motion that automatically minimizes the number of lane changes, respects safety distance to other cars, and computes the acceleration necessary to obtain a smooth traffic flow subject to the given constraints. Furthermore, our framework can process a continuous stream of input data in real time, enabling the users to view virtualized traffic events in a virtual world as they occur. We demonstrate our reconstruction technique with both synthetic and real-world input. © 2011 IEEE Published by the IEEE Computer Society

The Use of Medicinal Plants by Migrant People: Adaptation, Maintenance, and Replacement

PubMed Central

de Medeiros, Patrícia Muniz; Soldati, Gustavo Taboada; Alencar, Nélson Leal; Vandebroek, Ina; Pieroni, Andrea; Hanazaki, Natalia; de Albuquerque, Ulysses Paulino

2012-01-01

Given the importance of studying the knowledge, beliefs, and practices of migrant communities to understand the dynamics of plant resource use, we reviewed the scientific literature concerning the use of medicinal plants by migrant populations engaged in international or long-distance migrations. We considered the importance of two processes: (1) adaptation to the new flora of the host country (i.e., substitution and incorporation of plants in the pharmacopoeia) and (2) continued use and acquisition of the original flora from migrants' home countries (i.e., importation, cultivation, and/or continued use of plants that grow in both host and home environments). We suggest that, depending on the specific context and conditions of migration, different processes that determine the use and/or selection of plants as herbal medicines may become predominant. PMID:22110548

A simple method to calculate first-passage time densities with arbitrary initial conditions

NASA Astrophysics Data System (ADS)

Nyberg, Markus; Ambjörnsson, Tobias; Lizana, Ludvig

2016-06-01

Numerous applications all the way from biology and physics to economics depend on the density of first crossings over a boundary. Motivated by the lack of general purpose analytical tools for computing first-passage time densities (FPTDs) for complex problems, we propose a new simple method based on the independent interval approximation (IIA). We generalise previous formulations of the IIA to include arbitrary initial conditions as well as to deal with discrete time and non-smooth continuous time processes. We derive a closed form expression for the FPTD in z and Laplace-transform space to a boundary in one dimension. Two classes of problems are analysed in detail: discrete time symmetric random walks (Markovian) and continuous time Gaussian stationary processes (Markovian and non-Markovian). Our results are in good agreement with Langevin dynamics simulations.

Utilizing multiple state variables to improve the dynamic range of analog switching in a memristor

NASA Astrophysics Data System (ADS)

Jeong, YeonJoo; Kim, Sungho; Lu, Wei D.

2015-10-01

Memristors and memristive systems have been extensively studied for data storage and computing applications such as neuromorphic systems. To act as synapses in neuromorphic systems, the memristor needs to exhibit analog resistive switching (RS) behavior with incremental conductance change. In this study, we show that the dynamic range of the analog RS behavior can be significantly enhanced in a tantalum-oxide-based memristor. By controlling different state variables enabled by different physical effects during the RS process, the gradual filament expansion stage can be selectively enhanced without strongly affecting the abrupt filament length growth stage. Detailed physics-based modeling further verified the observed experimental effects and revealed the roles of oxygen vacancy drift and diffusion processes, and how the diffusion process can be selectively enhanced during the filament expansion stage. These findings lead to more desirable and reliable memristor behaviors for analog computing applications. Additionally, the ability to selectively control different internal physical processes demonstrated in the current study provides guidance for continued device optimization of memristor devices in general.

Excursions in fluvial (dis)continuity

NASA Astrophysics Data System (ADS)

Grant, Gordon E.; O'Connor, Jim; Safran, Elizabeth

2017-01-01

Lurking below the twin concepts of connectivity and disconnectivity are their first, and in some ways, richer cousins: continuity and discontinuity. In this paper we explore how continuity and discontinuity represent fundamental and complementary perspectives in fluvial geomorphology, and how these perspectives inform and underlie our conceptions of connectivity in landscapes and rivers. We examine the historical roots of continuum and discontinuum thinking, and how much of our understanding of geomorphology rests on contrasting views of continuity and discontinuity. By continuum thinking we refer to a conception of geomorphic processes as well as geomorphic features that are expressed along continuous gradients without abrupt changes, transitions, or thresholds. Balance of forces, graded streams, and hydraulic geometry are all examples of this perspective. The continuum view has played a prominent role in diverse disciplinary fields, including ecology, paleontology, and evolutionary biology, in large part because it allows us to treat complex phenomena as orderly progressions and invoke or assume equilibrium processes that introduce order and prediction into our sciences. In contrast the discontinuous view is a distinct though complementary conceptual framework that incorporates non-uniform, non-progressive, and non-equilibrium thinking into understanding geomorphic processes and landscapes. We distinguish and discuss examples of three different ways in which discontinuous thinking can be expressed: 1) discontinuous spatial arrangements or singular events; 2) specific process domains generally associated with thresholds, either intrinsic or extrinsic; and 3) physical dynamics or changes in state, again often threshold-linked. In moving beyond the continuous perspective, a fertile set of ideas comes into focus: thresholds, non-equilibrium states, heterogeneity, catastrophe. The range of phenomena that is thereby opened up to scientific exploration similarly expands: punctuated episodes of cutting and filling, discretization of landscapes into hierarchies of structure and control, the work of extreme events. Orderly and progressive evolution towards a steady or ideal state is replaced by chaotic episodes of disturbance and recovery. Recent developments in the field of geomorphology suggest that we may be on the cusp of a new paradigm that recognizes that both continuous and discontinuous processes and mechanisms play a role in fluvial processes and landscape evolution with neither holding sway over the other and both needed to see rivers as they are.

Neural source dynamics of brain responses to continuous stimuli: Speech processing from acoustics to comprehension.

PubMed

Brodbeck, Christian; Presacco, Alessandro; Simon, Jonathan Z

2018-05-15

Human experience often involves continuous sensory information that unfolds over time. This is true in particular for speech comprehension, where continuous acoustic signals are processed over seconds or even minutes. We show that brain responses to such continuous stimuli can be investigated in detail, for magnetoencephalography (MEG) data, by combining linear kernel estimation with minimum norm source localization. Previous research has shown that the requirement to average data over many trials can be overcome by modeling the brain response as a linear convolution of the stimulus and a kernel, or response function, and estimating a kernel that predicts the response from the stimulus. However, such analysis has been typically restricted to sensor space. Here we demonstrate that this analysis can also be performed in neural source space. We first computed distributed minimum norm current source estimates for continuous MEG recordings, and then computed response functions for the current estimate at each source element, using the boosting algorithm with cross-validation. Permutation tests can then assess the significance of individual predictor variables, as well as features of the corresponding spatio-temporal response functions. We demonstrate the viability of this technique by computing spatio-temporal response functions for speech stimuli, using predictor variables reflecting acoustic, lexical and semantic processing. Results indicate that processes related to comprehension of continuous speech can be differentiated anatomically as well as temporally: acoustic information engaged auditory cortex at short latencies, followed by responses over the central sulcus and inferior frontal gyrus, possibly related to somatosensory/motor cortex involvement in speech perception; lexical frequency was associated with a left-lateralized response in auditory cortex and subsequent bilateral frontal activity; and semantic composition was associated with bilateral temporal and frontal brain activity. We conclude that this technique can be used to study the neural processing of continuous stimuli in time and anatomical space with the millisecond temporal resolution of MEG. This suggests new avenues for analyzing neural processing of naturalistic stimuli, without the necessity of averaging over artificially short or truncated stimuli. Copyright © 2018 Elsevier Inc. All rights reserved.

Excursions in fluvial (dis)continuity

USGS Publications Warehouse

Grant, Gordon E.; O'Connor, James E.; Safran, Elizabeth

2017-01-01

Lurking below the twin concepts of connectivity and disconnectivity are their first, and in some ways, richer cousins: continuity and discontinuity. In this paper we explore how continuity and discontinuity represent fundamental and complementary perspectives in fluvial geomorphology, and how these perspectives inform and underlie our conceptions of connectivity in landscapes and rivers. We examine the historical roots of continuum and discontinuum thinking, and how much of our understanding of geomorphology rests on contrasting views of continuity and discontinuity. By continuum thinking we refer to a conception of geomorphic processes as well as geomorphic features that are expressed along continuous gradients without abrupt changes, transitions, or thresholds. Balance of forces, graded streams, and hydraulic geometry are all examples of this perspective. The continuum view has played a prominent role in diverse disciplinary fields, including ecology, paleontology, and evolutionary biology, in large part because it allows us to treat complex phenomena as orderly progressions and invoke or assume equilibrium processes that introduce order and prediction into our sciences.In contrast the discontinuous view is a distinct though complementary conceptual framework that incorporates non-uniform, non-progressive, and non-equilibrium thinking into understanding geomorphic processes and landscapes. We distinguish and discuss examples of three different ways in which discontinuous thinking can be expressed: 1) discontinuous spatial arrangements or singular events; 2) specific process domains generally associated with thresholds, either intrinsic or extrinsic; and 3) physical dynamics or changes in state, again often threshold-linked. In moving beyond the continuous perspective, a fertile set of ideas comes into focus: thresholds, non-equilibrium states, heterogeneity, catastrophe. The range of phenomena that is thereby opened up to scientific exploration similarly expands: punctuated episodes of cutting and filling, discretization of landscapes into hierarchies of structure and control, the work of extreme events. Orderly and progressive evolution towards a steady or ideal state is replaced by chaotic episodes of disturbance and recovery. Recent developments in the field of geomorphology suggest that we may be on the cusp of a new paradigm that recognizes that both continuous and discontinuous processes and mechanisms play a role in fluvial processes and landscape evolution with neither holding sway over the other and both needed to see rivers as they are.

Comparing mesophilic and thermophilic anaerobic digestion of chicken manure: Microbial community dynamics and process resilience

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

Niu, Qigui; Takemura, Yasuyuki; Kubota, Kengo

Highlights: • Microbial community dynamics and process functional resilience were investigated. • The threshold of TAN in mesophilic reactor was higher than the thermophilic reactor. • The recoverable archaeal community dynamic sustained the process resilience. • Methanosarcina was more sensitive than Methanoculleus on ammonia inhibition. • TAN and FA effects the dynamic of hydrolytic and acidogenic bacteria obviously. - Abstract: While methane fermentation is considered as the most successful bioenergy treatment for chicken manure, the relationship between operational performance and the dynamic transition of archaeal and bacterial communities remains poorly understood. Two continuous stirred-tank reactors were investigated under thermophilic andmore » mesophilic conditions feeding with 10%TS. The tolerance of thermophilic reactor on total ammonia nitrogen (TAN) was found to be 8000 mg/L with free ammonia (FA) 2000 mg/L compared to 16,000 mg/L (FA1500 mg/L) of mesophilic reactor. Biomethane production was 0.29 L/gV S{sub in} in the steady stage and decreased following TAN increase. After serious inhibition, the mesophilic reactor was recovered successfully by dilution and washing stratagem compared to the unrecoverable of thermophilic reactor. The relationship between the microbial community structure, the bioreactor performance and inhibitors such as TAN, FA, and volatile fatty acid was evaluated by canonical correspondence analysis. The performance of methanogenic activity and substrate removal efficiency were changed significantly correlating with the community evenness and phylogenetic structure. The resilient archaeal community was found even after serious inhibition in both reactors. Obvious dynamics of bacterial communities were observed in acidogenic and hydrolytic functional bacteria following TAN variation in the different stages.« less

How can climate change and engineered water conveyance affect sediment dynamics in the San Francisco Bay-Delta system?

USGS Publications Warehouse

Achete, Fernanda; Van der Wegen, Mick; Roelvink, Jan Adriaan; Jaffe, Bruce E.

2017-01-01

Suspended sediment concentration is an important estuarine health indicator. Estuarine ecosystems rely on the maintenance of habitat conditions, which are changing due to direct human impact and climate change. This study aims to evaluate the impact of climate change relative to engineering measures on estuarine fine sediment dynamics and sediment budgets. We use the highly engineered San Francisco Bay-Delta system as a case study. We apply a process-based modeling approach (Delft3D-FM) to assess the changes in hydrodynamics and sediment dynamics resulting from climate change and engineering scenarios. The scenarios consider a direct human impact (shift in water pumping location), climate change (sea level rise and suspended sediment concentration decrease), and abrupt disasters (island flooding, possibly as the results of an earthquake). Levee failure has the largest impact on the hydrodynamics of the system. Reduction in sediment input from the watershed has the greatest impact on turbidity levels, which are key to primary production and define habitat conditions for endemic species. Sea level rise leads to more sediment suspension and a net sediment export if little room for accommodation is left in the system due to continuous engineering works. Mitigation measures like levee reinforcement are effective for addressing direct human impacts, but less effective for a persistent, widespread, and increasing threat like sea level rise. Progressive adaptive mitigation measures to the changes in sediment and flow dynamics resulting from sea level rise may be a more effective strategy. Our approach shows that a validated process-based model is a useful tool to address long-term (decades to centuries) changes in sediment dynamics in highly engineered estuarine systems. In addition, our modeling approach provides a useful basis for long-term, process-based studies addressing ecosystem dynamics and health.

Avulsion vs Continuous Shifting: the Dynamics of Delta Distributary Channels Controlled by Basin Water Depth

NASA Astrophysics Data System (ADS)

Muto, T.; Naruse, H.

2015-12-01

An open question in the experimental study of surface processes is how basin water depth controls the dynamics of delta distributary channels. A recently suggested idea as to the issue is that, if a set of peculiar conditions is assumed, all of delta progradation, channel migration, alluvial aggradation and attainment of, or how close to, alluvial grade can be given by an identical formula with the same numerical value that is specified with dimensionless basin water depth. As one step ahead from this notion, we here report the finding obtained from a new series of tank experiments that basin water depth can also affect the modes by which active distributary channels change their locations, i.e. which one of avulsion and continuous shifting is predominant over the other. The results of the experiments clearly indicate that continuous shifting tends to become more predominant over avulsion as basin water depth increases. This tendency is related to a progressive decrease/increase in rate of alluvial aggradation which directly controls avulsion frequency. The present experimental notion can be examined with stratigraphic records of river deltas that accumulated with increasing or decreasing basin water depth.

Landsat Data Continuity Mission (LDCM) Flight Dynamics System (FDS)

NASA Technical Reports Server (NTRS)

Good, Susan M.; Nicholson, Ann M.

2012-01-01

The Landsat Data Continuity Mission (LDCM) will be launched in January 2013 to continue the legacy of Landsat land imagery collection that has been on-going for the past 40 years. While the overall mission and science goals are designed to produce the SAME data over the years, the ground systems designed to support the mission objectives have evolved immensely. The LDCM Flight Dynamics System (FDS) currently being tested and deployed for operations is highly automated and well integrated with the other ground system elements. The FDS encompasses the full suite of flight dynamics functional areas, including orbit and attitude determination and prediction, orbit and attitude maneuver planning and execution, and planning product generation. The integration of the orbit, attitude, maneuver, and products functions allows a very smooth flow for daily operations support with minimal input needed from the operator. The system also provides a valuable real-time component that monitors the on-board orbit and attitude during every ground contact and will autonomously alert the Flight Operations Team (FOT) personnel when any violations are found. This paper provides an overview of the LDCM Flight Dynamics System and a detailed description of how it is used to support space operations. For the first time on a Goddard Space Flight Center (GSFC)-managed mission, the ground attitude and orbits systems are fully integrated into a cohesive package. The executive engine of the FDS permits three levels of automation: low, medium, and high. The high-level, which will be the standard mode for LDCM, represents nearly lights-out operations. The paper provides an in-depth look at these processes within the FDS in support of LDCM in all mission phases.

Nonlinear Socio-Ecological Dynamics and First Principles ofCollective Choice Behavior of ``Homo Socialis"

NASA Astrophysics Data System (ADS)

Sonis, M.

Socio-ecological dynamics emerged from the field of Mathematical SocialSciences and opened up avenues for re-examination of classical problems of collective behavior in Social and Spatial sciences. The ``engine" of this collective behavior is the subjective mental evaluation of level of utilities in the future, presenting sets of composite socio-economic-temporal-locational advantages. These dynamics present new laws of collective multi-population behavior which are the meso-level counterparts of the utility optimization individual behavior. The central core of the socio-ecological choice dynamics includes the following first principle of the collective choice behavior of ``Homo Socialis" based on the existence of ``collective consciousness": the choice behavior of ``Homo Socialis" is a collective meso-level choice behavior such that the relative changes in choice frequencies depend on the distribution of innovation alternatives between adopters of innovations. The mathematical basis of the Socio-Ecological Dynamics includes two complementary analytical approaches both based on the use of computer modeling as a theoretical and simulation tool. First approach is the ``continuous approach" --- the systems of ordinary and partial differential equations reflecting the continuous time Volterra ecological formalism in a form of antagonistic and/or cooperative collective hyper-games between different sub-sets of choice alternatives. Second approach is the ``discrete approach" --- systems of difference equations presenting a new branch of the non-linear discrete dynamics --- the Discrete Relative m-population/n-innovations Socio-Spatial Dynamics (Dendrinos and Sonis, 1990). The generalization of the Volterra formalism leads further to the meso-level variational principle of collective choice behavior determining the balance between the resulting cumulative social spatio-temporal interactions among the population of adopters susceptible to the choice alternatives and the cumulative equalization of the power of elites supporting different choice alternatives. This balance governs the dynamic innovation choice process and constitutes the dynamic meso-level counterpart of the micro-economic individual utility maximization principle.

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.

Optimising the design and operation of semi-continuous affinity chromatography for clinical and commercial manufacture.

PubMed

Pollock, James; Bolton, Glen; Coffman, Jon; Ho, Sa V; Bracewell, Daniel G; Farid, Suzanne S

2013-04-05

This paper presents an integrated experimental and modelling approach to evaluate the potential of semi-continuous chromatography for the capture of monoclonal antibodies (mAb) in clinical and commercial manufacture. Small-scale single-column experimental breakthrough studies were used to derive design equations for the semi-continuous affinity chromatography system. Verification runs with the semi-continuous 3-column and 4-column periodic counter current (PCC) chromatography system indicated the robustness of the design approach. The product quality profiles and step yields (after wash step optimisation) achieved were comparable to the standard batch process. The experimentally-derived design equations were incorporated into a decisional tool comprising dynamic simulation, process economics and sizing optimisation. The decisional tool was used to evaluate the economic and operational feasibility of whole mAb bioprocesses employing PCC affinity capture chromatography versus standard batch chromatography across a product's lifecycle from clinical to commercial manufacture. The tool predicted that PCC capture chromatography would offer more significant savings in direct costs for early-stage clinical manufacture (proof-of-concept) (∼30%) than for late-stage clinical (∼10-15%) or commercial (∼5%) manufacture. The evaluation also highlighted the potential facility fit issues that could arise with a capture resin (MabSelect) that experiences losses in binding capacity when operated in continuous mode over lengthy commercial campaigns. Consequently, the analysis explored the scenario of adopting the PCC system for clinical manufacture and switching to the standard batch process following product launch. The tool determined the PCC system design required to operate at commercial scale without facility fit issues and with similar costs to the standard batch process whilst pursuing a process change application. A retrofitting analysis established that the direct cost savings obtained by 8 proof-of-concept batches would be sufficient to pay back the investment cost of the pilot-scale semi-continuous chromatography system. Copyright © 2013 Elsevier B.V. All rights reserved.

The application of Markov decision process in restaurant delivery robot

NASA Astrophysics Data System (ADS)

Wang, Yong; Hu, Zhen; Wang, Ying

2017-05-01

As the restaurant delivery robot is often in a dynamic and complex environment, including the chairs inadvertently moved to the channel and customers coming and going. The traditional path planning algorithm is not very ideal. To solve this problem, this paper proposes the Markov dynamic state immediate reward (MDR) path planning algorithm according to the traditional Markov decision process. First of all, it uses MDR to plan a global path, then navigates along this path. When the sensor detects there is no obstructions in front state, increase its immediate state reward value; when the sensor detects there is an obstacle in front, plan a global path that can avoid obstacle with the current position as the new starting point and reduce its state immediate reward value. This continues until the target is reached. When the robot learns for a period of time, it can avoid those places where obstacles are often present when planning the path. By analyzing the simulation experiment, the algorithm has achieved good results in the global path planning under the dynamic environment.

Regulation of the actin cytoskeleton-plasma membrane interplay by phosphoinositides.

PubMed

Saarikangas, Juha; Zhao, Hongxia; Lappalainen, Pekka

2010-01-01

The plasma membrane and the underlying cortical actin cytoskeleton undergo continuous dynamic interplay that is responsible for many essential aspects of cell physiology. Polymerization of actin filaments against cellular membranes provides the force for a number of cellular processes such as migration, morphogenesis, and endocytosis. Plasma membrane phosphoinositides (especially phosphatidylinositol bis- and trisphosphates) play a central role in regulating the organization and dynamics of the actin cytoskeleton by acting as platforms for protein recruitment, by triggering signaling cascades, and by directly regulating the activities of actin-binding proteins. Furthermore, a number of actin-associated proteins, such as BAR domain proteins, are capable of directly deforming phosphoinositide-rich membranes to induce plasma membrane protrusions or invaginations. Recent studies have also provided evidence that the actin cytoskeleton-plasma membrane interactions are misregulated in a number of pathological conditions such as cancer and during pathogen invasion. Here, we summarize the wealth of knowledge on how the cortical actin cytoskeleton is regulated by phosphoinositides during various cell biological processes. We also discuss the mechanisms by which interplay between actin dynamics and certain membrane deforming proteins regulate the morphology of the plasma membrane.

Nemo regulates cell dynamics and represses the expression of miple, a midkine/pleiotrophin cytokine, during ommatidial rotation

PubMed Central

Muñoz-Soriano, Verónica; Ruiz, Carlos; Pérez-Alonso, Manuel; Mlodzik, Marek; Paricio, Nuria

2013-01-01

Ommatidial rotation is one of the most important events for correct patterning of the Drosophila eye. Although several signaling pathways are involved in this process, few genes have been shown to specifically affect it. One of them is nemo (nmo), which encodes a MAP-like protein kinase that regulates the rate of rotation throughout the entire process, and serves as a link between core planar cell polarity (PCP) factors and the E-cadherin–β-catenin complex. To determine more precisely the role of nmo in ommatidial rotation, live-imaging analyses in nmo mutant and wild-type early pupal eye discs were performed. We demonstrate that ommatidial rotation is not a continuous process, and that rotating and non-rotating interommatidial cells are very dynamic. Our in vivo analyses also show that nmo regulates the speed of rotation and is required in cone cells for correct ommatidial rotation, and that these cells as well as interommatidial cells are less dynamic in nmo mutants. Furthermore, microarray analyses of nmo and wild-type larval eye discs led us to identify new genes and signaling pathways related to nmo function during this process. One of them, miple, encodes the Drosophila ortholog of the midkine/pleiotrophin secreted cytokines that are involved in cell migration processes. miple is highly up-regulated in nmo mutant discs. Indeed, phenotypic analyses reveal that miple overexpression leads to ommatidial rotation defects. Genetic interaction assays suggest that miple is signaling through Ptp99A, the Drosophila ortholog of the vertebrate midkine/pleiotrophin PTPζ receptor. Accordingly, we propose that one of the roles of Nmo during ommatial rotation is to repress miple expression, which may in turn affect the dynamics in E-cadherin–β-catenin complexes. PMID:23428616

Dynamic competition account of men's perceptions of women's sexual interest.

PubMed

Smith, Jodi R; Treat, Teresa A; Farmer, Thomas A; McMurray, Bob

2018-05-01

This work applies a dynamic competition framework of decision making to the domain of sexual perception, which is linked theoretically and empirically to college men's risk for exhibiting sexual coercion and aggression toward female acquaintances. Within a mouse-tracking paradigm, 152 undergraduate men viewed full-body photographs of women who varied in affect (sexual interest or rejection), clothing style (provocative or conservative), and attractiveness, and decided whether each woman currently felt sexually interested or rejecting. Participants' mouse movements were recorded to capture competition dynamics during online processing (throughout the decisional process), and as an index of the final categorical decision (endpoint of the decisional process). Participants completed a measure of Rape-Supportive Attitudes (RSA), a well-established correlate of male-initiated sexual aggression toward female acquaintances. Mixed-effects analyses revealed greater curvature toward the incorrect response on conceptually incongruent trials (e.g., rejecting and dressed provocatively) than on congruent trials (e.g., rejecting and dressed conservatively). This suggests that the two decision alternatives are simultaneously active and compete continuously over time, consistent with a dynamic competition account. Congruence effects also emerged at the decisional endpoint; accuracy was typically lower when stimulus features were incongruent, rather than congruent. RSA potentiated online congruence effects (intermediate states of behavior) but not offline congruence effects (endpoint states of behavior). In a hierarchical regression analysis, online processing indices accounted for unique variability in RSA above and beyond offline accuracy rates. The process-based account of men's sexual-interest judgments ultimately may point to novel targets for prevention strategies designed to reduce acquaintance-initiated sexual aggression on college campuses. Copyright © 2018 Elsevier B.V. All rights reserved.

Visualizing dynamic geosciences phenomena using an octree-based view-dependent LOD strategy within virtual globes

NASA Astrophysics Data System (ADS)

Li, Jing; Wu, Huayi; Yang, Chaowei; Wong, David W.; Xie, Jibo

2011-09-01

Geoscientists build dynamic models to simulate various natural phenomena for a better understanding of our planet. Interactive visualizations of these geoscience models and their outputs through virtual globes on the Internet can help the public understand the dynamic phenomena related to the Earth more intuitively. However, challenges arise when the volume of four-dimensional data (4D), 3D in space plus time, is huge for rendering. Datasets loaded from geographically distributed data servers require synchronization between ingesting and rendering data. Also the visualization capability of display clients varies significantly in such an online visualization environment; some may not have high-end graphic cards. To enhance the efficiency of visualizing dynamic volumetric data in virtual globes, this paper proposes a systematic framework, in which an octree-based multiresolution data structure is implemented to organize time series 3D geospatial data to be used in virtual globe environments. This framework includes a view-dependent continuous level of detail (LOD) strategy formulated as a synchronized part of the virtual globe rendering process. Through the octree-based data retrieval process, the LOD strategy enables the rendering of the 4D simulation at a consistent and acceptable frame rate. To demonstrate the capabilities of this framework, data of a simulated dust storm event are rendered in World Wind, an open source virtual globe. The rendering performances with and without the octree-based LOD strategy are compared. The experimental results show that using the proposed data structure and processing strategy significantly enhances the visualization performance when rendering dynamic geospatial phenomena in virtual globes.

The impact of short term synaptic depression and stochastic vesicle dynamics on neuronal variability

PubMed Central

Reich, Steven

2014-01-01

Neuronal variability plays a central role in neural coding and impacts the dynamics of neuronal networks. Unreliability of synaptic transmission is a major source of neural variability: synaptic neurotransmitter vesicles are released probabilistically in response to presynaptic action potentials and are recovered stochastically in time. The dynamics of this process of vesicle release and recovery interacts with variability in the arrival times of presynaptic spikes to shape the variability of the postsynaptic response. We use continuous time Markov chain methods to analyze a model of short term synaptic depression with stochastic vesicle dynamics coupled with three different models of presynaptic spiking: one model in which the timing of presynaptic action potentials are modeled as a Poisson process, one in which action potentials occur more regularly than a Poisson process (sub-Poisson) and one in which action potentials occur more irregularly (super-Poisson). We use this analysis to investigate how variability in a presynaptic spike train is transformed by short term depression and stochastic vesicle dynamics to determine the variability of the postsynaptic response. We find that sub-Poisson presynaptic spiking increases the average rate at which vesicles are released, that the number of vesicles released over a time window is more variable for smaller time windows than larger time windows and that fast presynaptic spiking gives rise to Poisson-like variability of the postsynaptic response even when presynaptic spike times are non-Poisson. Our results complement and extend previously reported theoretical results and provide possible explanations for some trends observed in recorded data. PMID:23354693

Heat dissipation guides activation in signaling proteins.

PubMed

Weber, Jeffrey K; Shukla, Diwakar; Pande, Vijay S

2015-08-18

Life is fundamentally a nonequilibrium phenomenon. At the expense of dissipated energy, living things perform irreversible processes that allow them to propagate and reproduce. Within cells, evolution has designed nanoscale machines to do meaningful work with energy harnessed from a continuous flux of heat and particles. As dictated by the Second Law of Thermodynamics and its fluctuation theorem corollaries, irreversibility in nonequilibrium processes can be quantified in terms of how much entropy such dynamics produce. In this work, we seek to address a fundamental question linking biology and nonequilibrium physics: can the evolved dissipative pathways that facilitate biomolecular function be identified by their extent of entropy production in general relaxation processes? We here synthesize massive molecular dynamics simulations, Markov state models (MSMs), and nonequilibrium statistical mechanical theory to probe dissipation in two key classes of signaling proteins: kinases and G-protein-coupled receptors (GPCRs). Applying machinery from large deviation theory, we use MSMs constructed from protein simulations to generate dynamics conforming to positive levels of entropy production. We note the emergence of an array of peaks in the dynamical response (transient analogs of phase transitions) that draw the proteins between distinct levels of dissipation, and we see that the binding of ATP and agonist molecules modifies the observed dissipative landscapes. Overall, we find that dissipation is tightly coupled to activation in these signaling systems: dominant entropy-producing trajectories become localized near important barriers along known biological activation pathways. We go on to classify an array of equilibrium and nonequilibrium molecular switches that harmonize to promote functional dynamics.

Martian Dust Devil Electron Avalanche Process and Associated Electrochemistry

NASA Technical Reports Server (NTRS)

Jackson, Telana L.; Farrell, William M.; Delory, Gregory T.; Nithianandam, Jeyasingh

2010-01-01

Mars' dynamic atmosphere displays localized dust devils and larger, global dust storms. Based on terrestrial analog studies, electrostatic modeling, and laboratory work these features will contain large electrostatic fields formed via triboelectric processes. In the low-pressure Martian atmosphere, these fields may create an electron avalanche and collisional plasma due to an increase in electron density driven by the internal electrical forces. To test the hypothesis that an electron avalanche is sustained under these conditions, a self-consistent atmospheric process model is created including electron impact ionization sources and electron losses via dust absorption, electron dissociation attachment, and electron/ion recombination. This new model is called the Dust Devil Electron Avalanche Model (DDEAM). This model solves simultaneously nine continuity equations describing the evolution of the primary gaseous chemical species involved in the electrochemistry. DDEAM monitors the evolution of the electrons and primary gas constituents, including electron/water interactions. We especially focus on electron dynamics and follow the electrons as they evolve in the E field driven collisional gas. When sources and losses are self-consistently included in the electron continuity equation, the electron density grows exponentially with increasing electric field, reaching an equilibrium that forms a sustained time-stable collisional plasma. However, the character of this plasma differs depending upon the assumed growth rate saturation process (chemical saturation versus space charge). DDEAM also shows the possibility of the loss of atmospheric methane as a function of electric field due to electron dissociative attachment of the hydrocarbon. The methane destruction rates are presented and can be included in other larger atmospheric models.

Computer control of a microgravity mammalian cell bioreactor

NASA Technical Reports Server (NTRS)

Hall, William A.

1987-01-01

The initial steps taken in developing a completely menu driven and totally automated computer control system for a bioreactor are discussed. This bioreactor is an electro-mechanical cell growth system cell requiring vigorous control of slowly changing parameters, many of which are so dynamically interactive that computer control is a necessity. The process computer will have two main functions. First, it will provide continuous environmental control utilizing low signal level transducers as inputs and high powered control devices such as solenoids and motors as outputs. Secondly, it will provide continuous environmental monitoring, including mass data storage and periodic data dumps to a supervisory computer.

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.

Preliminary design of a high-intensity continuous-wave deuteron RFQ

NASA Astrophysics Data System (ADS)

Liu, X.; Kamigaito, O.; Sakamoto, N.; Yamada, K.

2017-07-01

A high-intensity deuteron linear accelerator is currently being studied as a promising candidate to treat high-level radioactive waste through the nuclear transmutation process. This paper presents the study on a design of a 75.5 MHz, 400 mA, continuous-wave deuteron radio-frequency quadrupole (RFQ), which is proposed as the front-end of such a linear accelerator. The results of the beam dynamics simulation suggest that the designed RFQ can accelerate a 400-mA deuteron beam from 100 keV to 2.5 MeV with a transmission rate of 92.0 ∼ 93.3%, depending on the assumed input transverse emittance.

Nonlinear response of mid-latitude weather to the changing Arctic

NASA Astrophysics Data System (ADS)

Overland, James E.; Dethloff, Klaus; Francis, Jennifer A.; Hall, Richard J.; Hanna, Edward; Kim, Seong-Joong; Screen, James A.; Shepherd, Theodore G.; Vihma, Timo

2016-11-01

Are continuing changes in the Arctic influencing wind patterns and the occurrence of extreme weather events in northern mid-latitudes? The chaotic nature of atmospheric circulation precludes easy answers. The topic is a major science challenge, as continued Arctic temperature increases are an inevitable aspect of anthropogenic climate change. We propose a perspective that rejects simple cause-and-effect pathways and notes diagnostic challenges in interpreting atmospheric dynamics. We present a way forward based on understanding multiple processes that lead to uncertainties in Arctic and mid-latitude weather and climate linkages. We emphasize community coordination for both scientific progress and communication to a broader public.

The dynamics of embodiment: a field theory of infant perseverative reaching.

PubMed

Thelen, E; Schöner, G; Scheier, C; Smith, L B

2001-02-01

The overall goal of this target article is to demonstrate a mechanism for an embodied cognition. The particular vehicle is a much-studied, but still widely debated phenomenon seen in 7-12 month-old-infants. In Piaget's classic "A-not-B error," infants who have successfully uncovered a toy at location "A" continue to reach to that location even after they watch the toy hidden in a nearby location "B." Here, we question the traditional explanations of the error as an indicator of infants' concepts of objects or other static mental structures. Instead, we demonstrate that the A-not-B error and its previously puzzling contextual variations can be understood by the coupled dynamics of the ordinary processes of goal-directed actions: looking, planning, reaching, and remembering. We offer a formal dynamic theory and model based on cognitive embodiment that both simulates the known A-not-B effects and offers novel predictions that match new experimental results. The demonstration supports an embodied view by casting the mental events involved in perception, planning, deciding, and remembering in the same analogic dynamic language as that used to describe bodily movement, so that they may be continuously meshed. We maintain that this mesh is a pre-eminently cognitive act of "knowing" not only in infancy but also in everyday activities throughout the life span.

Ocean Processes Revealing by Seasonal Dynamics of Surface Chlorophyll Concentration (by Satellite Data)

NASA Astrophysics Data System (ADS)

Shevyrnogov, Anatoly; Vysotskaya, Galina

Continuous monitoring of phytopigment concentrations in the ocean by space-borne methods makes possible to estimate ecological condition of biocenoses in critical areas. Unlike land vege-tation, hydrological processes largely determine phytoplankton dynamics, which may be either recurrent or random. The types of chlorophyll concentration dynamics can manifest as zones quasistationary by seasonal chlorophyll dynamics, perennial variations of phytopigment con-centrations, anomalous variations, etc., that makes possible revealing of hydrological structure of the ocean. While large-scale and frequently occurring phenomena have been much studied, the seldom-occurring changes of small size may be of interest for analysis of long-term processes and rare natural variations. Along with this, the ability to reflect consequences of anthropoge-nous impact or natural ecological disasters on the ocean biota makes the anomalous variations ecologically essential. Civilization aspiring for steady development and preservation of the bio-sphere, must have the knowledge of spatial distribution, seasonal dynamics and anomalies of the primary production process on the planet. In the papers of the authors (Shevyrnogov A.P., Vysotskaya G.S., Gitelzon J.I. Quasistationary areas of chlorophyll concentration in the world ocean as observed satellite data. Adv. Space Res. Vol. 18, No. 7, pp. 129-132, 1996) existence of zones, which are quasi-stationary with similar seasonal dynamics of chlorophyll concentration at surface layer of ocean, was shown. Results were obtained on the base of pro-cessing of time series of satellite images SeaWiFS. It was shown that fronts and frontal zones coincide with dividing lines between quasi-stationary areas, especially in areas of large oceanic streams. Biota of surface oceanic layer is more stable in comparison with quickly changing sur-face temperature. It gives a possibility to circumvent influence of high-frequency component (for example, a diurnal cycle) in investigation of dynamics of spatial distribution of surface streams. In addition, an analyses of nonstable ocean productivity phenomena, stood out time series of satellite images, showed existence of areas with different types of instability in the all Global ocean. They are observed as adjacent nonstationary zones of different size, which are associated by different ways with known oceanic phenomena. It is evident that dynamics of a spatial distribution of biological productivity can give an additional knowledge of complicated picture of surface oceanic layer hydrology.

Fluid dynamic analysis of a continuous stirred tank reactor for technical optimization of wastewater digestion.

PubMed

Hurtado, F J; Kaiser, A S; Zamora, B

2015-03-15

Continuous stirred tank reactors (CSTR) are widely used in wastewater treatment plants to reduce the organic matter and microorganism present in sludge by anaerobic digestion. The present study carries out a numerical analysis of the fluid dynamic behaviour of a CSTR in order to optimize the process energetically. The characterization of the sludge flow inside the digester tank, the residence time distribution and the active volume of the reactor under different criteria are determined. The effects of design and power of the mixing system on the active volume of the CSTR are analyzed. The numerical model is solved under non-steady conditions by examining the evolution of the flow during the stop and restart of the mixing system. An intermittent regime of the mixing system, which kept the active volume between 94% and 99%, is achieved. The results obtained can lead to the eventual energy optimization of the mixing system of the CSTR. Copyright © 2014 Elsevier Ltd. All rights reserved.

Floquet scalar dynamics in global AdS

NASA Astrophysics Data System (ADS)

Biasi, Anxo; Carracedo, Pablo; Mas, Javier; Musso, Daniele; Serantes, Alexandre

2018-04-01

We study periodically driven scalar fields and the resulting geometries with global AdS asymptotics. These solutions describe the strongly coupled dynamics of dual finite-size quantum systems under a periodic driving which we interpret as Floquet condensates. They span a continuous two-parameter space that extends the linearized solutions on AdS. We map the regions of stability in the solution space. In a significant portion of the unstable subspace, two very different endpoints are reached depending upon the sign of the perturbation. Collapse into a black hole occurs for one sign. For the opposite sign instead one attains a regular solution with periodic modulation. We also construct quenches where the driving frequency and amplitude are continuously varied. Quasistatic quenches can interpolate between pure AdS and sourced solutions with time periodic vev. By suitably choosing the quasistatic path one can obtain boson stars dual to Floquet condensates at zero driving field. We characterize the adiabaticity of the quenching processes. Besides, we speculate on the possible connections of this framework with time crystals.

An overview of flux braiding experiments

PubMed Central

Wilmot-Smith, A. L.

2015-01-01

In a number of papers dating back to the 1970s, Parker has hypothesized that, in a perfectly ideal environment, complex photospheric motions acting on a continuous magnetic field will result in the formation of tangential discontinuities corresponding to singular currents. I review direct numerical simulations of the problem and find that the evidence points to a tendency for thin but finite-thickness current layers to form, with thickness exponentially decreasing in time. Given a finite resistivity, these layers will eventually become important and cause the dynamical process of energy release. Accordingly, a body of work focuses on evolution under continual boundary driving. The coronal volume evolves into a highly dynamic but statistically steady state where quantities have a temporally and spatially intermittent nature and where the Poynting flux and dissipation are decoupled on short time scales. Although magnetic braiding is found to be a promising coronal heating mechanism, much work remains to determine its true viability. Some suggestions for future study are offered. PMID:25897088

Histories of poverty and self-rated health trajectories.

PubMed

McDonough, Peggy; Berglund, Pat

2003-06-01

This paper investigates the dynamic relationship between poverty histories and self-rated health trajectories. We are interested in patterns of change in individuals' health over time and the ways in which such patterns are structured by continuity and change in poverty experiences. Data, collected for adults aged 25 and older in 1984 (N = 7,258), are from the 1968-1996 annual waves of Panel Study of Income Dynamics (PSID). Individual growth curves allow us to investigate health trajectories as continuous processes, as well as individual and group heterogeneity in these trajectories. We find that, on average, health deteriorates slowly over time, but there is significant variation in health in 1984 and the rate at which health declines. Histories of poverty partly accounted for the sources of individual differences in self-rated health in 1984, but they were not related to health change over time. Although increasing incomes were better for self-rated health than falling incomes, current economic circumstances did not erase the health effects of earlier poverty experiences.

Measurement of intervertebral cervical motion by means of dynamic x-ray image processing and data interpolation.

PubMed

Bifulco, Paolo; Cesarelli, Mario; Romano, Maria; Fratini, Antonio; Sansone, Mario

2013-01-01

Accurate measurement of intervertebral kinematics of the cervical spine can support the diagnosis of widespread diseases related to neck pain, such as chronic whiplash dysfunction, arthritis, and segmental degeneration. The natural inaccessibility of the spine, its complex anatomy, and the small range of motion only permit concise measurement in vivo. Low dose X-ray fluoroscopy allows time-continuous screening of cervical spine during patient's spontaneous motion. To obtain accurate motion measurements, each vertebra was tracked by means of image processing along a sequence of radiographic images. To obtain a time-continuous representation of motion and to reduce noise in the experimental data, smoothing spline interpolation was used. Estimation of intervertebral motion for cervical segments was obtained by processing patient's fluoroscopic sequence; intervertebral angle and displacement and the instantaneous centre of rotation were computed. The RMS value of fitting errors resulted in about 0.2 degree for rotation and 0.2 mm for displacements.

Wrapping with a splash: High-speed encapsulation with ultrathin sheets.

PubMed

Kumar, Deepak; Paulsen, Joseph D; Russell, Thomas P; Menon, Narayanan

2018-02-16

Many complex fluids rely on surfactants to contain, protect, or isolate liquid drops in an immiscible continuous phase. Thin elastic sheets can wrap liquid drops in a spontaneous process driven by capillary forces. For encapsulation by sheets to be practically viable, a rapid, continuous, and scalable process is essential. We exploit the fast dynamics of droplet impact to achieve wrapping of oil droplets by ultrathin polymer films in a water phase. Despite the violence of splashing events, the process robustly yields wrappings that are optimally shaped to maximize the enclosed fluid volume and have near-perfect seams. We achieve wrappings of targeted three-dimensional (3D) shapes by tailoring the 2D boundary of the films and show the generality of the technique by producing both oil-in-water and water-in-oil wrappings. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

A Computer Model of the Evaporator for the Development of an Automatic Control System

NASA Astrophysics Data System (ADS)

Kozin, K. A.; Efremov, E. V.; Kabrysheva, O. P.; Grachev, M. I.

2016-08-01

For the implementation of a closed nuclear fuel cycle it is necessary to carry out a series of experimental studies to justify the choice of technology. In addition, the operation of the radiochemical plant is impossible without high-quality automatic control systems. In the technologies of spent nuclear fuel reprocessing, the method of continuous evaporation is often used for a solution conditioning. Therefore, the effective continuous technological process will depend on the operation of the evaporation equipment. Its essential difference from similar devices is a small size. In this paper the method of mathematic simulation is applied for the investigation of one-effect evaporator with an external heating chamber. Detailed modelling is quite difficult because the phase equilibrium dynamics of the evaporation process is not described. Moreover, there is a relationship with the other process units. The results proved that the study subject is a MIMO plant, nonlinear over separate control channels and not selfbalancing. Adequacy was tested using the experimental data obtained at the laboratory evaporation unit.

Properties of Rolled AZ31 Magnesium Alloy Sheet Fabricated by Continuous Variable Cross-Section Direct Extrusion

NASA Astrophysics Data System (ADS)

Liu, Yang; Li, Feng; Li, Xue Wen; Shi, Wen Yong

2018-03-01

Rolling is currently a widely used method for manufacturing and processing high-performance magnesium alloy sheets and has received widespread attention in recent years. Here, we combined continuous variable cross-section direct extrusion (CVCDE) and rolling processes. The microstructure and mechanical properties of the resulting sheets rolled at different temperatures from CVCDE extrudate were investigated by optical microscopy, scanning electron microscope, transmission electron microscopy and electron backscatter diffraction. The results showed that a fine-grained microstructure was present with an average grain size of 3.62 μm in sheets rolled from CVCDE extrudate at 623 K. Dynamic recrystallization and a large strain were induced by the multi-pass rolling, which resulted in grain refinement. In the 573-673 K range, the yield strength, tensile strength and elongation initially increased and then declined as the CVCDE temperature increased. The above results provide an important scientific basis of processing, manufacturing and the active control on microstructure and property for high-performance magnesium alloy sheet.

High-precision GPS autonomous platforms for sea ice dynamics and physical oceanography

NASA Astrophysics Data System (ADS)

Elosegui, P.; Wilkinson, J.; Olsson, M.; Rodwell, S.; James, A.; Hagan, B.; Hwang, B.; Forsberg, R.; Gerdes, R.; Johannessen, J.; Wadhams, P.; Nettles, M.; Padman, L.

2012-12-01

Project "Arctic Ocean sea ice and ocean circulation using satellite methods" (SATICE), is the first high-rate, high-precision, continuous GPS positioning experiment on sea ice in the Arctic Ocean. The SATICE systems collect continuous, dual-frequency carrier-phase GPS data while drifting on sea ice. Additional geophysical measurements also collected include ocean water pressure, ocean surface salinity, atmospheric pressure, snow-depth, air-ice-ocean temperature profiles, photographic imagery, and others, enabling sea ice drift, freeboard, weather, ice mass balance, and sea-level height determination. Relatively large volumes of data from each buoy are streamed over a satellite link to a central computer on the Internet in near real time, where they are processed to estimate the time-varying buoy positions. SATICE system obtains continuous GPS data at sub-minute intervals with a positioning precision of a few centimetres in all three dimensions. Although monitoring of sea ice motions goes back to the early days of satellite observations, these autonomous platforms bring out a level of spatio-temporal detail that has never been seen before, especially in the vertical axis. These high-resolution data allows us to address new polar science questions and challenge our present understanding of both sea ice dynamics and Arctic oceanography. We will describe the technology behind this new autonomous platform, which could also be adapted to other applications that require high resolution positioning information with sustained operations and observations in the polar marine environment, and present results pertaining to sea ice dynamics and physical oceanography.

The dynamic sustainability framework: addressing the paradox of sustainment amid ongoing change

PubMed Central

2013-01-01

Background Despite growth in implementation research, limited scientific attention has focused on understanding and improving sustainability of health interventions. Models of sustainability have been evolving to reflect challenges in the fit between intervention and context. Discussion We examine the development of concepts of sustainability, and respond to two frequent assumptions —'voltage drop,’ whereby interventions are expected to yield lower benefits as they move from efficacy to effectiveness to implementation and sustainability, and 'program drift,’ whereby deviation from manualized protocols is assumed to decrease benefit. We posit that these assumptions limit opportunities to improve care, and instead argue for understanding the changing context of healthcare to continuously refine and improve interventions as they are sustained. Sustainability has evolved from being considered as the endgame of a translational research process to a suggested 'adaptation phase’ that integrates and institutionalizes interventions within local organizational and cultural contexts. These recent approaches locate sustainability in the implementation phase of knowledge transfer, but still do not address intervention improvement as a central theme. We propose a Dynamic Sustainability Framework that involves: continued learning and problem solving, ongoing adaptation of interventions with a primary focus on fit between interventions and multi-level contexts, and expectations for ongoing improvement as opposed to diminishing outcomes over time. Summary A Dynamic Sustainability Framework provides a foundation for research, policy and practice that supports development and testing of falsifiable hypotheses and continued learning to advance the implementation, transportability and impact of health services research. PMID:24088228

The dynamic sustainability framework: addressing the paradox of sustainment amid ongoing change.

PubMed

Chambers, David A; Glasgow, Russell E; Stange, Kurt C

2013-10-02

Despite growth in implementation research, limited scientific attention has focused on understanding and improving sustainability of health interventions. Models of sustainability have been evolving to reflect challenges in the fit between intervention and context. We examine the development of concepts of sustainability, and respond to two frequent assumptions -'voltage drop,' whereby interventions are expected to yield lower benefits as they move from efficacy to effectiveness to implementation and sustainability, and 'program drift,' whereby deviation from manualized protocols is assumed to decrease benefit. We posit that these assumptions limit opportunities to improve care, and instead argue for understanding the changing context of healthcare to continuously refine and improve interventions as they are sustained. Sustainability has evolved from being considered as the endgame of a translational research process to a suggested 'adaptation phase' that integrates and institutionalizes interventions within local organizational and cultural contexts. These recent approaches locate sustainability in the implementation phase of knowledge transfer, but still do not address intervention improvement as a central theme. We propose a Dynamic Sustainability Framework that involves: continued learning and problem solving, ongoing adaptation of interventions with a primary focus on fit between interventions and multi-level contexts, and expectations for ongoing improvement as opposed to diminishing outcomes over time. A Dynamic Sustainability Framework provides a foundation for research, policy and practice that supports development and testing of falsifiable hypotheses and continued learning to advance the implementation, transportability and impact of health services research.

Needs assessment and implementation of an employee assistance program: promoting a healthier work force.

PubMed

Monfils, M K

1995-05-01

1. The functions of a continuous quality improvement tool used by Deming--the Plan, Do, Check, Act Cycle--can be applied to the assessment, implementation, and ongoing evaluation of an Employee Assistance Program (EAP). 2. Various methods are available to assess the need for an EAP. As much data as possible should be collected to qualify and quantify the need so that management can make an informed decision and develop measures to determine program effectiveness. 3. Once an EAP is implemented, it should be monitored continually against the effectiveness measures initially developed. Using a continuous quality improvement process, the occupational health nurse and the EAP provider can establish a dynamic relationship that allows for growth beyond the original design and increased effectiveness of service to employees.

Black holes by analytic continuation

NASA Astrophysics Data System (ADS)

Amati, D.; Russo, J. G.

1997-07-01

In the context of a two-dimensional exactly solvable model, the dynamics of quantum black holes is obtained by analytically continuing the description of the regime where no black hole is formed. The resulting spectrum of outgoing radiation departs from the one predicted by the Hawking model in the region where the outgoing modes arise from the horizon with Planck-order frequencies. This occurs early in the evaporation process, and the resulting physical picture is unconventional. The theory predicts that black holes will only radiate out an energy of Planck mass order, stabilizing after a transitory period. The continuation from a regime without black hole formation-accessible in the 1+1 gravity theory considered-is implicit in an S-matrix approach and suggests in this way a possible solution to the problem of information loss.

Membrane vesiculation induced by proteins of the dengue virus envelope studied by molecular dynamics simulations.

PubMed

de Oliveira Dos Santos Soares, Ricardo; Bortot, Leandro Oliveira; van der Spoel, David; Caliri, Antonio

2017-12-20

Biological membranes are continuously remodeled in the cell by specific membrane-shaping machineries to form, for example, tubes and vesicles. We examine fundamental mechanisms involved in the vesiculation processes induced by a cluster of envelope (E) and membrane (M) proteins of the dengue virus (DENV) using molecular dynamics simulations and a coarse-grained model. We show that an arrangement of three E-M heterotetramers (EM 3 ) works as a bending unit and an ordered cluster of five such units generates a closed vesicle, reminiscent of the virus budding process. In silico mutagenesis of two charged residues of the anchor helices of the envelope proteins of DENV shows that Arg-471 and Arg-60 are fundamental to produce bending stress on the membrane. The fine-tuning between the size of the EM 3 unit and its specific bending action suggests this protein unit is an important factor in determining the viral particle size.

Engagement: Looking beyond the mirror to understand action understanding.

PubMed

Reddy, Vasudevi; Uithol, Sebo

2016-03-01

In this paper, we argue that the current focus on mirroring as the route to explaining the development of action understanding is misleading and problematic. It facilitates a fundamentally spectatorial stance, ignoring engagement and dialogue; it focuses on similarity between self and other and neglects difference; and it succumbs to the static terminology of mechanism rather than a dynamic language of process. Contrary to this view, dialogic exchanges are evident from the start of life, revealing infants' ability to engage with and respond appropriately to actions that are outside their own motor repertoire. We suggest that engagement rather than mirroring better accounts for many current findings in action understanding. The neurological evidence to date shows that action perception involves a process of continuous synchronization and change, suggesting that it might be more fruitful for research and theory to look beyond mirroring and instead adopt dynamic processual explanations of action understanding within interaction. © 2015 The British Psychological Society.

Morpho-dynamics of mountain streams: from laboratory experiments to field observations

NASA Astrophysics Data System (ADS)

Mettra, François; Lane, Stuart Nicholas; Heyman, Joris; Ancey, Christophe

2017-04-01

Due to the complexity of mountain stream evolution and its causes, it is judicious to conduct flume experiments to better understand the morpho-dynamics of steep river channels. A series of long-term experiments under steady conditions revealed the high internal variability of transport processes (including erosion and deposition events). In particular, high fluctuations over time of the sediment volume stored in the channel (or released from the channel) were observed for the steepest channel experiments at intermittent transport conditions. These conditions imply an autogenic regulation of the sediment transport process. When these were extended to non-steady conditions, repeated flood events suggested a hysteresis effect on sediment transport but where the forcing frequency (of the repeated floods) plays an important role in the response of the channel system. The results are compared with preliminary field observations from continuous measurements in Swiss Alpine rivers. Simple mechanisms of steep river channel behavior are proposed.

The role of symmetry in the regulation of brain dynamics

NASA Astrophysics Data System (ADS)

Tang, Evelyn; Giusti, Chad; Cieslak, Matthew; Grafton, Scott; Bassett, Danielle

Synchronous neural processes regulate a wide range of behaviors from attention to learning. Yet structural constraints on these processes are far from understood. We draw on new theoretical links between structural symmetries and the control of synchronous function, to offer a reconceptualization of the relationships between brain structure and function in human and non-human primates. By classifying 3-node motifs in macaque connectivity data, we find the most prevalent motifs can theoretically ensure a diversity of function including strict synchrony as well as control to arbitrary states. The least prevalent motifs are theoretically controllable to arbitrary states, which may not be desirable in a biological system. In humans, regions with high topological similarity of connections (a continuous notion related to symmetry) are most commonly found in fronto-parietal systems, which may account for their critical role in cognitive control. Collectively, our work underscores the role of symmetry and topological similarity in regulating dynamics of brain function.

Membrane vesiculation induced by proteins of the dengue virus envelope studied by molecular dynamics simulations

NASA Astrophysics Data System (ADS)

de Oliveira dos Santos Soares, Ricardo; Oliveira Bortot, Leandro; van der Spoel, David; Caliri, Antonio

2017-12-01

Biological membranes are continuously remodeled in the cell by specific membrane-shaping machineries to form, for example, tubes and vesicles. We examine fundamental mechanisms involved in the vesiculation processes induced by a cluster of envelope (E) and membrane (M) proteins of the dengue virus (DENV) using molecular dynamics simulations and a coarse-grained model. We show that an arrangement of three E-M heterotetramers (EM3) works as a bending unit and an ordered cluster of five such units generates a closed vesicle, reminiscent of the virus budding process. In silico mutagenesis of two charged residues of the anchor helices of the envelope proteins of DENV shows that Arg-471 and Arg-60 are fundamental to produce bending stress on the membrane. The fine-tuning between the size of the EM3 unit and its specific bending action suggests this protein unit is an important factor in determining the viral particle size.

On the analysis of the double Hopf bifurcation in machining processes via centre manifold reduction

NASA Astrophysics Data System (ADS)

Molnar, T. G.; Dombovari, Z.; Insperger, T.; Stepan, G.

2017-11-01

The single-degree-of-freedom model of orthogonal cutting is investigated to study machine tool vibrations in the vicinity of a double Hopf bifurcation point. Centre manifold reduction and normal form calculations are performed to investigate the long-term dynamics of the cutting process. The normal form of the four-dimensional centre subsystem is derived analytically, and the possible topologies in the infinite-dimensional phase space of the system are revealed. It is shown that bistable parameter regions exist where unstable periodic and, in certain cases, unstable quasi-periodic motions coexist with the equilibrium. Taking into account the non-smoothness caused by loss of contact between the tool and the workpiece, the boundary of the bistable region is also derived analytically. The results are verified by numerical continuation. The possibility of (transient) chaotic motions in the global non-smooth dynamics is shown.

Flat-space quantum gravity in the AdS / CFT correspondence

DOE PAGES

Nomura, Yasunori; Sanches, Fabio; Weinberg, Sean J.

2016-03-22

Motivated by the task of understanding microscopic dynamics of an evolving black hole, we present a scheme describing gauge-fixed continuous time evolution of quantum gravitational processes in asymptotically flat spacetime using the algebra of conformal field theory operators. This allows us to study the microscopic dynamics of the Hawking emission process, although obtaining a full S-matrix may require a modification of the minimal scheme. The role of the operator product expansion is to physically interpret the resulting time evolution by decomposing the Hilbert space of the states for the entire system into those for smaller subsystems. We translate the picturemore » of an evaporating black hole previously proposed by the authors into predictions for nonperturbative properties of the conformal field theories that have weakly coupled dual gravitational descriptions. Finally, we also discuss a possible relationship between the present scheme and a reference frame change in the bulk.« less

Dynamic Black-Level Correction and Artifact Flagging for Kepler Pixel Time Series

NASA Technical Reports Server (NTRS)

Kolodziejczak, J. J.; Clarke, B. D.; Caldwell, D. A.

2011-01-01

Methods applied to the calibration stage of Kepler pipeline data processing [1] (CAL) do not currently use all of the information available to identify and correct several instrument-induced artifacts. These include time-varying crosstalk from the fine guidance sensor (FGS) clock signals, and manifestations of drifting moire pattern as locally correlated nonstationary noise, and rolling bands in the images which find their way into the time series [2], [3]. As the Kepler Mission continues to improve the fidelity of its science data products, we are evaluating the benefits of adding pipeline steps to more completely model and dynamically correct the FGS crosstalk, then use the residuals from these model fits to detect and flag spatial regions and time intervals of strong time-varying black-level which may complicate later processing or lead to misinterpretation of instrument behavior as stellar activity.

[A model for shared decision-making with frail older patients: consensus reached using Delphi technique].

PubMed

van de Pol, M H J; Fluit, C R M G; Lagro, J; Lagro-Janssen, A L M; Olde Rikkert, M G M

2017-01-01

To develop a model for shared decision-making with frail older patients. Online Delphi forum. We used a three-round Delphi technique to reach consensus on the structure of a model for shared decision-making with older patients. The expert panel consisted of 16 patients (round 1), and 59 professionals (rounds 1-3). In round 1, the panel of experts was asked about important steps in the process of shared decision-making and the draft model was introduced. Rounds 2 and 3 were used to adapt the model and test it for 'importance' and 'feasibility'. Consensus for the dynamic shared decision-making model as a whole was achieved for both importance (91% panel agreement) and feasibility (76% panel agreement). Shared decision-making with older patients is a dynamic process. It requires a continuous supportive dialogue between health care professional and patient.

Proceedings of a conference on sustainability of wetlands and water resources: how well can riverine wetlands continue to support society into the 21st century?

Treesearch

Marjorie M. Holland; Melvin L. Warren; John A. Stanturf; [Editors

2002-01-01

The conference focused on recent work in freshwater wetlands [both natural and constructed] with a view toward understanding wetland processes in a watershed context. Since humans have played important roles in watershed dynamics for years, attention was given to the human dimensions of wetland and watershed uses. Contributed sessions were organized on: biogeochemical...

Final Report for Dynamic Models for Causal Analysis of Panel Data. Models for Change in Quantitative Variables, Part II Scholastic Models. Part II, Chapter 4.

ERIC Educational Resources Information Center

Hannan, Michael T.

This document is part of a series of chapters described in SO 011 759. Stochastic models for the sociological analysis of change and the change process in quantitative variables are presented. The author lays groundwork for the statistical treatment of simple stochastic differential equations (SDEs) and discusses some of the continuities of…

Continuous Assessment, Mock Results and Gender as Predictors of Academic Performance of Chemistry Students in WASSCE and NECO Examinations in Ekiti State

ERIC Educational Resources Information Center

Adewumi, Adesoji Francis; Monisola, Kenni Amoke

2013-01-01

Education is one of the fundamental and critical indices of development in a nation or an individual. The challenges post by our fast changing and dynamic world informed the need to constantly access the educational process so as to guarantee quality of educational assessment; several factors have been identified to be responsible for students'…

Active Control of Complex Systems via Dynamic (Recurrent) Neural Networks

DTIC Science & Technology

1992-05-30

course, to on-going changes brought about by learning processes. As research in neurodynamics proceeded, the concept of reverberatory information flows...Microstructure of Cognition . Vol. 1: Foundations, M.I.T. Press, Cambridge, Massachusetts, pp. 354-361, 1986. 100 I Schwarz, G., "Estimating the dimension of a...Continually Running Fully Recurrent Neural Networks, ICS Report 8805, Institute of Cognitive Science, University of California at San Diego, 1988. 10 II

Enabling continuous-flow chemistry in microstructured devices for pharmaceutical and fine-chemical production.

PubMed

Kockmann, Norbert; Gottsponer, Michael; Zimmermann, Bertin; Roberge, Dominique M

2008-01-01

Microstructured devices offer unique transport capabilities for rapid mixing, enhanced heat and mass transfer and can handle small amounts of dangerous or unstable materials. The integration of reaction kinetics into fluid dynamics and transport phenomena is essential for successful application from process design in laboratory to chemical production. Strategies to implement production campaigns up to tons of pharmaceutical chemicals are discussed, based on Lonza projects.

Temporal Dynamics of Motivation-Cognitive Control Interactions Revealed by High-Resolution Pupillometry

PubMed Central

Chiew, Kimberly S.; Braver, Todd S.

2013-01-01

Motivational manipulations, such as the presence of performance-contingent reward incentives, can have substantial influences on cognitive control. Previous evidence suggests that reward incentives may enhance cognitive performance specifically through increased preparatory, or proactive, control processes. The present study examined reward influences on cognitive control dynamics in the AX-Continuous Performance Task (AX-CPT), using high-resolution pupillometry. In the AX-CPT, contextual cues must be actively maintained over a delay in order to appropriately respond to ambiguous target probes. A key feature of the task is that it permits dissociable characterization of preparatory, proactive control processes (i.e., utilization of context) and reactive control processes (i.e., target-evoked interference resolution). Task performance profiles suggested that reward incentives enhanced proactive control (context utilization). Critically, pupil dilation was also increased on reward incentive trials during context maintenance periods, suggesting trial-specific shifts in proactive control, particularly when context cues indicated the need to overcome the dominant target response bias. Reward incentives had both transient (i.e., trial-by-trial) and sustained (i.e., block-based) effects on pupil dilation, which may reflect distinct underlying processes. The transient pupillary effects were present even when comparing against trials matched in task performance, suggesting a unique motivational influence of reward incentives. These results suggest that pupillometry may be a useful technique for investigating reward motivational signals and their dynamic influence on cognitive control. PMID:23372557

Towards Quantification of Glacier Dynamic Ice Loss through Passive Seismic Monitoring

NASA Astrophysics Data System (ADS)

Köhler, A.; Nuth, C.; Weidle, C.; Schweitzer, J.; Kohler, J.; Buscaino, G.

2015-12-01

Global glaciers and ice caps loose mass through calving, while existing models are currently not equipped to realistically predict dynamic ice loss. This is mainly because long-term continuous calving records, that would help to better understand fine scale processes and key climatic-dynamic feedbacks between calving, climate, terminus evolution and marine conditions, do not exist. Combined passive seismic/acoustic strategies are the only technique able to capture rapid calving events continuously, independent of daylight or meteorological conditions. We have produced such a continuous calving record for Kronebreen, a tidewater glacier in Svalbard, using data from permanent seismic stations between 2001 and 2014. However, currently no method has been established in cryo-seismology to quantify the calving ice loss directly from seismic data. Independent calibration data is required to derive 1) a realistic estimation of the dynamic ice loss unobserved due to seismic noise and 2) a robust scaling of seismic calving signals to ice volumes. Here, we analyze the seismic calving record at Kronebreen and independent calving data in a first attempt to quantify ice loss directly from seismic records. We make use of a) calving flux data with weekly to monthly resolution obtained from satellite remote sensing and GPS data between 2007 and 2013, and b) direct, visual calving observations in two weeks in 2009 and 2010. Furthermore, the magnitude-scaling property of seismic calving events is analyzed. We derive and discuss an empirical relation between seismic calving events and calving flux which for the first time allows to estimate a time series of calving volumes more than one decade back in time. Improving our model requires to incorporate more precise, high-resolution calibration data. A new field campaign will combine innovative, multi-disciplinary monitoring techniques to measure calving ice volumes and dynamic ice-ocean interactions simultaneously with terrestrial laser scanning and a temporary seismic/underwater-acoustic network.

Real-time modulated nanoparticle separation with an ultra-large dynamic range.

PubMed

Zeming, Kerwin Kwek; Thakor, Nitish V; Zhang, Yong; Chen, Chia-Hung

2016-01-07

Nanoparticles exhibit size-dependent properties which make size-selective purification of proteins, DNA or synthetic nanoparticles essential for bio-analytics, clinical medicine, nano-plasmonics and nano-material sciences. Current purification methods of centrifugation, column chromatography and continuous-flow techniques suffer from particle aggregation, multi-stage process, complex setups and necessary nanofabrication. These increase process costs and time, reduce efficiency and limit dynamic range. Here, we achieve an unprecedented real-time nanoparticle separation (51-1500 nm) using a large-pore (2 μm) deterministic lateral displacement (DLD) device. No external force fields or nanofabrication are required. Instead, we investigated innate long-range electrostatic influences on nanoparticles within a fluid medium at different NaCl ionic concentrations. In this study we account for the electrostatic forces beyond Debye length and showed that they cannot be assumed as negligible especially for precise nanoparticle separation methods such as DLD. Our findings have enabled us to develop a model to simultaneously quantify and modulate the electrostatic force interactions between nanoparticle and micropore. By simply controlling buffer solutions, we achieve dynamic nanoparticle size separation on a single device with a rapid response time (<20 s) and an enlarged dynamic range (>1200%), outperforming standard benchtop centrifuge systems. This novel method and model combines device simplicity, isolation precision and dynamic flexibility, opening opportunities for high-throughput applications in nano-separation for industrial and biological applications.

Single molecule translocation in smectics illustrates the challenge for time-mapping in simulations on multiple scales

NASA Astrophysics Data System (ADS)

Mukherjee, Biswaroop; Peter, Christine; Kremer, Kurt

2017-09-01

Understanding the connections between the characteristic dynamical time scales associated with a coarse-grained (CG) and a detailed representation is central to the applicability of the coarse-graining methods to understand molecular processes. The process of coarse graining leads to an accelerated dynamics, owing to the smoothening of the underlying free-energy landscapes. Often a single time-mapping factor is used to relate the time scales associated with the two representations. We critically examine this idea using a model system ideally suited for this purpose. Single molecular transport properties are studied via molecular dynamics simulations of the CG and atomistic representations of a liquid crystalline, azobenzene containing mesogen, simulated in the smectic and the isotropic phases. The out-of-plane dynamics in the smectic phase occurs via molecular hops from one smectic layer to the next. Hopping can occur via two mechanisms, with and without significant reorientation. The out-of-plane transport can be understood as a superposition of two (one associated with each mode of transport) independent continuous time random walks for which a single time-mapping factor would be rather inadequate. A comparison of the free-energy surfaces, relevant to the out-of-plane transport, qualitatively supports the above observations. Thus, this work underlines the need for building CG models that exhibit both structural and dynamical consistency to the underlying atomistic model.

Bursts and heavy tails in temporal and sequential dynamics of foraging decisions.

PubMed

Jung, Kanghoon; Jang, Hyeran; Kralik, Jerald D; Jeong, Jaeseung

2014-08-01

A fundamental understanding of behavior requires predicting when and what an individual will choose. However, the actual temporal and sequential dynamics of successive choices made among multiple alternatives remain unclear. In the current study, we tested the hypothesis that there is a general bursting property in both the timing and sequential patterns of foraging decisions. We conducted a foraging experiment in which rats chose among four different foods over a continuous two-week time period. Regarding when choices were made, we found bursts of rapidly occurring actions, separated by time-varying inactive periods, partially based on a circadian rhythm. Regarding what was chosen, we found sequential dynamics in affective choices characterized by two key features: (a) a highly biased choice distribution; and (b) preferential attachment, in which the animals were more likely to choose what they had previously chosen. To capture the temporal dynamics, we propose a dual-state model consisting of active and inactive states. We also introduce a satiation-attainment process for bursty activity, and a non-homogeneous Poisson process for longer inactivity between bursts. For the sequential dynamics, we propose a dual-control model consisting of goal-directed and habit systems, based on outcome valuation and choice history, respectively. This study provides insights into how the bursty nature of behavior emerges from the interaction of different underlying systems, leading to heavy tails in the distribution of behavior over time and choices.

Solution of the Fokker-Planck equation with a logarithmic potential and mixed eigenvalue spectrum

NASA Astrophysics Data System (ADS)

Guarnieri, F.; Moon, W.; Wettlaufer, J. S.

2017-09-01

Motivated by a problem in climate dynamics, we investigate the solution of a Bessel-like process with a negative constant drift, described by a Fokker-Planck equation with a potential V (x ) =-[b ln(x ) +a x ] , for b >0 and a <0 . The problem belongs to a family of Fokker-Planck equations with logarithmic potentials closely related to the Bessel process that has been extensively studied for its applications in physics, biology, and finance. The Bessel-like process we consider can be solved by seeking solutions through an expansion into a complete set of eigenfunctions. The associated imaginary-time Schrödinger equation exhibits a mix of discrete and continuous eigenvalue spectra, corresponding to the quantum Coulomb potential describing the bound states of the hydrogen atom. We present a technique to evaluate the normalization factor of the continuous spectrum of eigenfunctions that relies solely upon their asymptotic behavior. We demonstrate the technique by solving the Brownian motion problem and the Bessel process both with a constant negative drift. We conclude with a comparison to other analytical methods and with numerical solutions.

Brokering: a process for establishing long-term and stable links with gay male communities for research and public health education.

PubMed

Silvestre, A J

1994-02-01

The success of efforts to prevent continued transmission of the human immunodeficiency virus (HIV) and to increase compliance with HIV prophylactic interventions among homosexual and bisexual men will depend in part on health care professionals' understanding of and ability to establish linkages with these men. In order to recruit men into a research project and an educational program, staff at the Pitt Men's Study, an epidemiological investigation of HIV infection, developed a process described here as "brokering," which was based on community organizing and marketing principles. Brokering is a dynamic process by which researchers and public health professionals exchange goods and services with formal and informal leaders of the gay community in order to establish strong, long-term linkages. To date, this process yielded 2,989 homosexual and bisexual recruits into the study, which began in 1983. After 8 years, 79% of those still alive continue to return for follow-up. While recruitment techniques will need to vary from city to city, the importance of establishing linkages with the local indigenous leadership remains of major importance.

Emergence of scaling in human-interest dynamics.

PubMed

Zhao, Zhi-Dan; Yang, Zimo; Zhang, Zike; Zhou, Tao; Huang, Zi-Gang; Lai, Ying-Cheng

2013-12-11

Human behaviors are often driven by human interests. Despite intense recent efforts in exploring the dynamics of human behaviors, little is known about human-interest dynamics, partly due to the extreme difficulty in accessing the human mind from observations. However, the availability of large-scale data, such as those from e-commerce and smart-phone communications, makes it possible to probe into and quantify the dynamics of human interest. Using three prototypical "Big Data" sets, we investigate the scaling behaviors associated with human-interest dynamics. In particular, from the data sets we uncover fat-tailed (possibly power-law) distributions associated with the three basic quantities: (1) the length of continuous interest, (2) the return time of visiting certain interest, and (3) interest ranking and transition. We argue that there are three basic ingredients underlying human-interest dynamics: preferential return to previously visited interests, inertial effect, and exploration of new interests. We develop a biased random-walk model, incorporating the three ingredients, to account for the observed fat-tailed distributions. Our study represents the first attempt to understand the dynamical processes underlying human interest, which has significant applications in science and engineering, commerce, as well as defense, in terms of specific tasks such as recommendation and human-behavior prediction.

Out-of-equilibrium dynamical mean-field equations for the perceptron model

NASA Astrophysics Data System (ADS)

Agoritsas, Elisabeth; Biroli, Giulio; Urbani, Pierfrancesco; Zamponi, Francesco

2018-02-01

Perceptrons are the building blocks of many theoretical approaches to a wide range of complex systems, ranging from neural networks and deep learning machines, to constraint satisfaction problems, glasses and ecosystems. Despite their applicability and importance, a detailed study of their Langevin dynamics has never been performed yet. Here we derive the mean-field dynamical equations that describe the continuous random perceptron in the thermodynamic limit, in a very general setting with arbitrary noise and friction kernels, not necessarily related by equilibrium relations. We derive the equations in two ways: via a dynamical cavity method, and via a path-integral approach in its supersymmetric formulation. The end point of both approaches is the reduction of the dynamics of the system to an effective stochastic process for a representative dynamical variable. Because the perceptron is formally very close to a system of interacting particles in a high dimensional space, the methods we develop here can be transferred to the study of liquid and glasses in high dimensions. Potentially interesting applications are thus the study of the glass transition in active matter, the study of the dynamics around the jamming transition, and the calculation of rheological properties in driven systems.

Emergence of scaling in human-interest dynamics

NASA Astrophysics Data System (ADS)

Zhao, Zhi-Dan; Yang, Zimo; Zhang, Zike; Zhou, Tao; Huang, Zi-Gang; Lai, Ying-Cheng

2013-12-01

Human behaviors are often driven by human interests. Despite intense recent efforts in exploring the dynamics of human behaviors, little is known about human-interest dynamics, partly due to the extreme difficulty in accessing the human mind from observations. However, the availability of large-scale data, such as those from e-commerce and smart-phone communications, makes it possible to probe into and quantify the dynamics of human interest. Using three prototypical ``Big Data'' sets, we investigate the scaling behaviors associated with human-interest dynamics. In particular, from the data sets we uncover fat-tailed (possibly power-law) distributions associated with the three basic quantities: (1) the length of continuous interest, (2) the return time of visiting certain interest, and (3) interest ranking and transition. We argue that there are three basic ingredients underlying human-interest dynamics: preferential return to previously visited interests, inertial effect, and exploration of new interests. We develop a biased random-walk model, incorporating the three ingredients, to account for the observed fat-tailed distributions. Our study represents the first attempt to understand the dynamical processes underlying human interest, which has significant applications in science and engineering, commerce, as well as defense, in terms of specific tasks such as recommendation and human-behavior prediction.

Using CASE to Exploit Process Modeling in Technology Transfer

NASA Technical Reports Server (NTRS)

Renz-Olar, Cheryl

2003-01-01

A successful business will be one that has processes in place to run that business. Creating processes, reengineering processes, and continually improving processes can be accomplished through extensive modeling. Casewise(R) Corporate Modeler(TM) CASE is a computer aided software engineering tool that will enable the Technology Transfer Department (TT) at NASA Marshall Space Flight Center (MSFC) to capture these abilities. After successful implementation of CASE, it could then go on to be applied in other departments at MSFC and other centers at NASA. The success of a business process is dependent upon the players working as a team and continuously improving the process. A good process fosters customer satisfaction as well as internal satisfaction in the organizational infrastructure. CASE provides a method for business process success through functions consisting of systems and processes business models; specialized diagrams; matrix management; simulation; report generation and publishing; and, linking, importing, and exporting documents and files. The software has an underlying repository or database to support these functions. The Casewise. manual informs us that dynamics modeling is a technique used in business design and analysis. Feedback is used as a tool for the end users and generates different ways of dealing with the process. Feedback on this project resulted from collection of issues through a systems analyst interface approach of interviews with process coordinators and Technical Points of Contact (TPOCs).

Remembering the dynamic changes in pain intensity and unpleasantness: a psychophysical study.

PubMed

Khoshnejad, Mina; Fortin, Marie C; Rohani, Farzan; Duncan, Gary H; Rainville, Pierre

2014-03-01

This study investigated the short-term memory of dynamic changes in acute pain using psychophysical methods. Pain intensity or unpleasantness induced by painful contact-heat stimuli of 8, 9, or 10s was rated continuously during the stimulus or after a 14-s delay using an electronic visual analog scale in 10 healthy volunteers. Because the continuous visual analog scale time courses contained large amounts of redundant information, a principal component analysis was applied to characterize the main features inherent to both the concurrent rating and retrospective evaluations. Three components explained about 90% of the total variance across all trials and subjects, with the first component reflecting the global perceptual profile, and the second and third components explaining finer perceptual aspects (eg, changes in slope at onset and offset and shifts in peak latency). We postulate that these 3 principal components may provide some information about the structure of the mental representations of what one perceives, stores, and remembers during the course of few seconds. Analysis performed on the components confirmed significant memory distortions and revealed that the discriminative information about pain dimensions in concurrent ratings was partly or completely lost in retrospective ratings. Importantly, our results highlight individual differences affecting these memory processes. These results provide further evidence of the important transformations underlying the processing of pain in explicit memory and raise fundamental questions about the conversion of dynamic nociceptive signals into a mental representation of pain in perception and memory. Copyright © 2013 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Cold chemistry with cold molecules

NASA Astrophysics Data System (ADS)

Shagam, Yuval

Low temperature chemistry has been predicted to be dominated by quantum effects, such as shape resonances, where colliding particles exhibit wave-like behavior and tunnel through potential barriers. Observation of these quantum effects provides valuable insight into the microscopic mechanism that governs scattering processes. Our recent advances in the control of neutral supersonic molecular beams, namely merged beam experiments, have enabled continuous tuning of collision energies from the classical regime at room temperature down to 0.01 kelvin, where a quantum description of the dynamics is necessary. I will discuss our use of this technique to study how the dynamics change when molecules participate in collisions, demonstrating the crucial role the molecular quantum rotor plays. We have found that at low temperatures rotational state of the molecule can strongly affect collision dynamics considerably changing reaction rates, due to the different symmetries of the molecular wavefunction.

Psychotherapy Is Chaotic—(Not Only) in a Computational World

PubMed Central

Schiepek, Günter K.; Viol, Kathrin; Aichhorn, Wolfgang; Hütt, Marc-Thorsten; Sungler, Katharina; Pincus, David; Schöller, Helmut J.

2017-01-01

Objective: The aim of this article is to outline the role of chaotic dynamics in psychotherapy. Besides some empirical findings of chaos at different time scales, the focus is on theoretical modeling of change processes explaining and simulating chaotic dynamics. It will be illustrated how some common factors of psychotherapeutic change and psychological hypotheses on motivation, emotion regulation, and information processing of the client's functioning can be integrated into a comprehensive nonlinear model of human change processes. Methods: The model combines 5 variables (intensity of emotions, problem intensity, motivation to change, insight and new perspectives, therapeutic success) and 4 parameters into a set of 5 coupled nonlinear difference equations. The results of these simulations are presented as time series, as phase space embedding of these time series (i.e., attractors), and as bifurcation diagrams. Results: The model creates chaotic dynamics, phase transition-like phenomena, bi- or multi-stability, and sensibility of the dynamic patterns on parameter drift. These features are predicted by chaos theory and by Synergetics and correspond to empirical findings. The spectrum of these behaviors illustrates the complexity of psychotherapeutic processes. Conclusion: The model contributes to the development of an integrative conceptualization of psychotherapy. It is consistent with the state of scientific knowledge of common factors, as well as other psychological topics, such as: motivation, emotion regulation, and cognitive processing. The role of chaos theory is underpinned, not only in the world of computer simulations, but also in practice. In practice, chaos demands technologies capable of real-time monitoring and reporting on the nonlinear features of the ongoing process (e.g., its stability or instability). Based on this monitoring, a client-centered, continuous, and cooperative process of feedback and control becomes possible. By contrast, restricted predictability and spontaneous changes challenge the usefulness of prescriptive treatment manuals or other predefined programs of psychotherapy. PMID:28484401

Psychotherapy Is Chaotic-(Not Only) in a Computational World.

PubMed

Schiepek, Günter K; Viol, Kathrin; Aichhorn, Wolfgang; Hütt, Marc-Thorsten; Sungler, Katharina; Pincus, David; Schöller, Helmut J

2017-01-01

Objective: The aim of this article is to outline the role of chaotic dynamics in psychotherapy. Besides some empirical findings of chaos at different time scales, the focus is on theoretical modeling of change processes explaining and simulating chaotic dynamics. It will be illustrated how some common factors of psychotherapeutic change and psychological hypotheses on motivation, emotion regulation, and information processing of the client's functioning can be integrated into a comprehensive nonlinear model of human change processes. Methods: The model combines 5 variables (intensity of emotions, problem intensity, motivation to change, insight and new perspectives, therapeutic success) and 4 parameters into a set of 5 coupled nonlinear difference equations. The results of these simulations are presented as time series, as phase space embedding of these time series (i.e., attractors), and as bifurcation diagrams. Results: The model creates chaotic dynamics, phase transition-like phenomena, bi- or multi-stability, and sensibility of the dynamic patterns on parameter drift. These features are predicted by chaos theory and by Synergetics and correspond to empirical findings. The spectrum of these behaviors illustrates the complexity of psychotherapeutic processes. Conclusion: The model contributes to the development of an integrative conceptualization of psychotherapy. It is consistent with the state of scientific knowledge of common factors, as well as other psychological topics, such as: motivation, emotion regulation, and cognitive processing. The role of chaos theory is underpinned, not only in the world of computer simulations, but also in practice. In practice, chaos demands technologies capable of real-time monitoring and reporting on the nonlinear features of the ongoing process (e.g., its stability or instability). Based on this monitoring, a client-centered, continuous, and cooperative process of feedback and control becomes possible. By contrast, restricted predictability and spontaneous changes challenge the usefulness of prescriptive treatment manuals or other predefined programs of psychotherapy.

Octree-based, GPU implementation of a continuous cellular automaton for the simulation of complex, evolving surfaces

NASA Astrophysics Data System (ADS)

Ferrando, N.; Gosálvez, M. A.; Cerdá, J.; Gadea, R.; Sato, K.

2011-03-01

Presently, dynamic surface-based models are required to contain increasingly larger numbers of points and to propagate them over longer time periods. For large numbers of surface points, the octree data structure can be used as a balance between low memory occupation and relatively rapid access to the stored data. For evolution rules that depend on neighborhood states, extended simulation periods can be obtained by using simplified atomistic propagation models, such as the Cellular Automata (CA). This method, however, has an intrinsic parallel updating nature and the corresponding simulations are highly inefficient when performed on classical Central Processing Units (CPUs), which are designed for the sequential execution of tasks. In this paper, a series of guidelines is presented for the efficient adaptation of octree-based, CA simulations of complex, evolving surfaces into massively parallel computing hardware. A Graphics Processing Unit (GPU) is used as a cost-efficient example of the parallel architectures. For the actual simulations, we consider the surface propagation during anisotropic wet chemical etching of silicon as a computationally challenging process with a wide-spread use in microengineering applications. A continuous CA model that is intrinsically parallel in nature is used for the time evolution. Our study strongly indicates that parallel computations of dynamically evolving surfaces simulated using CA methods are significantly benefited by the incorporation of octrees as support data structures, substantially decreasing the overall computational time and memory usage.

14 CFR Appendix G to Part 25 - Continuous Gust Design Criteria

Code of Federal Regulations, 2011 CFR

2011-01-01

... establishing the dynamic response of the airplane to vertical and lateral continuous turbulence unless a more... determined by dynamic analysis. The power spectral density of the atmospheric turbulence must be as given by... obtained by multiplying the Ā values determined by the dynamic analysis by the following values of the gust...

14 CFR Appendix G to Part 25 - Continuous Gust Design Criteria

Code of Federal Regulations, 2010 CFR

2010-01-01

... establishing the dynamic response of the airplane to vertical and lateral continuous turbulence unless a more... determined by dynamic analysis. The power spectral density of the atmospheric turbulence must be as given by... obtained by multiplying the Ā values determined by the dynamic analysis by the following values of the gust...

Neural dynamics underlying emotional transmissions between individuals

PubMed Central

Levit-Binnun, Nava; Hendler, Talma; Lerner, Yulia

2017-01-01

Abstract Emotional experiences are frequently shaped by the emotional responses of co-present others. Research has shown that people constantly monitor and adapt to the incoming social–emotional signals, even without face-to-face interaction. And yet, the neural processes underlying such emotional transmissions have not been directly studied. Here, we investigated how the human brain processes emotional cues which arrive from another, co-attending individual. We presented continuous emotional feedback to participants who viewed a movie in the scanner. Participants in the social group (but not in the control group) believed that the feedback was coming from another person who was co-viewing the same movie. We found that social–emotional feedback significantly affected the neural dynamics both in the core affect and in the medial pre-frontal regions. Specifically, the response time-courses in those regions exhibited increased similarity across recipients and increased neural alignment with the timeline of the feedback in the social compared with control group. Taken in conjunction with previous research, this study suggests that emotional cues from others shape the neural dynamics across the whole neural continuum of emotional processing in the brain. Moreover, it demonstrates that interpersonal neural alignment can serve as a neural mechanism through which affective information is conveyed between individuals. PMID:28575520

Monitoring cognitive and emotional processes through pupil and cardiac response during dynamic versus logical task.

PubMed

Causse, Mickaël; Sénard, Jean-Michel; Démonet, Jean François; Pastor, Josette

2010-06-01

The paper deals with the links between physiological measurements and cognitive and emotional functioning. As long as the operator is a key agent in charge of complex systems, the definition of metrics able to predict his performance is a great challenge. The measurement of the physiological state is a very promising way but a very acute comprehension is required; in particular few studies compare autonomous nervous system reactivity according to specific cognitive processes during task performance and task related psychological stress is often ignored. We compared physiological parameters recorded on 24 healthy subjects facing two neuropsychological tasks: a dynamic task that require problem solving in a world that continually evolves over time and a logical task representative of cognitive processes performed by operators facing everyday problem solving. Results showed that the mean pupil diameter change was higher during the dynamic task; conversely, the heart rate was more elevated during the logical task. Finally, the systolic blood pressure seemed to be strongly sensitive to psychological stress. A better taking into account of the precise influence of a given cognitive activity and both workload and related task-induced psychological stress during task performance is a promising way to better monitor operators in complex working situations to detect mental overload or pejorative stress factor of error.

Determination of differential cross sections and kinetic energy release of co-products from central sliced images in photo-initiated dynamic processes.

PubMed

Chen, Kuo-mei; Chen, Yu-wei

2011-04-07

For photo-initiated inelastic and reactive collisions, dynamic information can be extracted from central sliced images of state-selected Newton spheres of product species. An analysis framework has been established to determine differential cross sections and the kinetic energy release of co-products from experimental images. When one of the reactants exhibits a high recoil speed in a photo-initiated dynamic process, the present theory can be employed to analyze central sliced images from ion imaging or three-dimensional sliced fluorescence imaging experiments. It is demonstrated that the differential cross section of a scattering process can be determined from the central sliced image by a double Legendre moment analysis, for either a fixed or continuously distributed recoil speeds in the center-of-mass reference frame. Simultaneous equations which lead to the determination of the kinetic energy release of co-products can be established from the second-order Legendre moment of the experimental image, as soon as the differential cross section is extracted. The intensity distribution of the central sliced image, along with its outer and inner ring sizes, provide all the clues to decipher the differential cross section and the kinetic energy release of co-products.

Dynamic versus static allocation policies in multipurpose multireservoir systems

NASA Astrophysics Data System (ADS)

Tilmant, A.; Goor, Q.; Pinte, D.; van der Zaag, P.

2007-12-01

As the competition for water is likely to increase in the near future due to socioeconomic development and population growth, water resources managers will face hard choices when allocating water between competing users. Because water is a vital resource used in multiple sectors, including the environment, the allocation is inherently a political and social process, which is likely to become increasingly scrutinized as the competition grows between the different sectors. Since markets are usually absent or ineffective, the allocation of water between competing demands is achieved administratively taking into account key objectives such as economic efficiency, equity and maintaining the ecological integrity. When crop irrigation is involved, water is usually allocated by a system of annual rights to use a fixed, static, volume of water. In a fully-allocated basin, moving from a static to a dynamic allocation process, whereby the policies are regularly updated according to the hydrologic status of the river basin, is the first step towards the development of river basin management strategies that increase the productivity of water. More specifically, in a multipurpose multireservoir system, continuously adjusting release and withdrawal decisions based on the latest hydrologic information will increase the benefits derived from the system. However, the extent to which such an adjustment can be achieved results from complex spatial and temporal interactions between the physical characteristics of the water resources system (storage, natural flows), the economic and social consequences of rationing and the impacts on natural ecosystems. The complexity of the decision-making process, which requires the continuous evaluation of numerous trade-offs, calls for the use of integrated hydrologic-economic models. This paper compares static and dynamic management approaches for a cascade of hydropower-irrigation reservoirs using stochastic dual dynamic programming (SDDP) formulations. As its name indicates, SDDP is an extension of SDP that removes the curse of dimensionality found in discrete SDP and can therefore be used to analyze large-scale water resources systems. For the static approach, the multiobjective (irrigation-hydropower) optimization problem is solved using the constraint method, i.e. net benefits from hydropower generation are maximized and irrigation water withdrawals are additional constraints. In the dynamic approach, the SDDP model seeks to maximize the net benefits of both hydropower and irrigation crop production. A cascade of 8 reservoirs in the Turkish and Syrian parts of the Euphrates river basin is used as a case study.

System-wide hybrid MPC-PID control of a continuous pharmaceutical tablet manufacturing process via direct compaction.

PubMed

Singh, Ravendra; Ierapetritou, Marianthi; Ramachandran, Rohit

2013-11-01

The next generation of QbD based pharmaceutical products will be manufactured through continuous processing. This will allow the integration of online/inline monitoring tools, coupled with an efficient advanced model-based feedback control systems, to achieve precise control of process variables, so that the predefined product quality can be achieved consistently. The direct compaction process considered in this study is highly interactive and involves time delays for a number of process variables due to sensor placements, process equipment dimensions, and the flow characteristics of the solid material. A simple feedback regulatory control system (e.g., PI(D)) by itself may not be sufficient to achieve the tight process control that is mandated by regulatory authorities. The process presented herein comprises of coupled dynamics involving slow and fast responses, indicating the requirement of a hybrid control scheme such as a combined MPC-PID control scheme. In this manuscript, an efficient system-wide hybrid control strategy for an integrated continuous pharmaceutical tablet manufacturing process via direct compaction has been designed. The designed control system is a hybrid scheme of MPC-PID control. An effective controller parameter tuning strategy involving an ITAE method coupled with an optimization strategy has been used for tuning of both MPC and PID parameters. The designed hybrid control system has been implemented in a first-principles model-based flowsheet that was simulated in gPROMS (Process System Enterprise). Results demonstrate enhanced performance of critical quality attributes (CQAs) under the hybrid control scheme compared to only PID or MPC control schemes, illustrating the potential of a hybrid control scheme in improving pharmaceutical manufacturing operations. Copyright © 2013 Elsevier B.V. All rights reserved.

Dynamic Encoding of Acoustic Features in Neural Responses to Continuous Speech.

PubMed

Khalighinejad, Bahar; Cruzatto da Silva, Guilherme; Mesgarani, Nima

2017-02-22

Humans are unique in their ability to communicate using spoken language. However, it remains unclear how the speech signal is transformed and represented in the brain at different stages of the auditory pathway. In this study, we characterized electroencephalography responses to continuous speech by obtaining the time-locked responses to phoneme instances (phoneme-related potential). We showed that responses to different phoneme categories are organized by phonetic features. We found that each instance of a phoneme in continuous speech produces multiple distinguishable neural responses occurring as early as 50 ms and as late as 400 ms after the phoneme onset. Comparing the patterns of phoneme similarity in the neural responses and the acoustic signals confirms a repetitive appearance of acoustic distinctions of phonemes in the neural data. Analysis of the phonetic and speaker information in neural activations revealed that different time intervals jointly encode the acoustic similarity of both phonetic and speaker categories. These findings provide evidence for a dynamic neural transformation of low-level speech features as they propagate along the auditory pathway, and form an empirical framework to study the representational changes in learning, attention, and speech disorders. SIGNIFICANCE STATEMENT We characterized the properties of evoked neural responses to phoneme instances in continuous speech. We show that each instance of a phoneme in continuous speech produces several observable neural responses at different times occurring as early as 50 ms and as late as 400 ms after the phoneme onset. Each temporal event explicitly encodes the acoustic similarity of phonemes, and linguistic and nonlinguistic information are best represented at different time intervals. Finally, we show a joint encoding of phonetic and speaker information, where the neural representation of speakers is dependent on phoneme category. These findings provide compelling new evidence for dynamic processing of speech sounds in the auditory pathway. Copyright © 2017 Khalighinejad et al.

Landscape dynamics in the Otterbach catchment (Bavarian Forest, Southern Germany)

NASA Astrophysics Data System (ADS)

Schwindt, Daniel; Scheck, Sebastian; Scholz, Emanuel; Waltl, Peter; Völkel, Jörg

2017-04-01

As part of the TUM-CZO (TU-Munich Critical Zone Observatory), the Otterbach Valley has been focus of numerous research approaches, focusing on soil carbon dynamics, hydrological processes as well as landscape dynamics. Aim of this contribution is the reconstruction of the landscape evolution of the Otterbach catchment in context with anthropogenic land use and natural process dynamics. Therefore, studies focus on alluvial and colluvial sediments which are usually regarded as correlated with anthropogenically induced erosion. Located in the western Bavarian Forest the Otterbach is a creek of 2nd stream order and runs directly into the Danube River. Geologically, most parts of the catchment are composed of granitic rocks, mylonites and saprolites. While agricultural land use is dominant in the upper and lower reaches of the Otterbach, the steep middle reaches are forested, floodplains are used as grasslands. Settlement history points out that the forest of the so-called "Thiergarten", covering large parts of the catchment, has been used invariably for forestry, makes this study site valuable for the reconstruction of anthropogenic impact on landscape evolution. Characterization of the shallow subsurface is based on the analysis of soil pits (up to 2 m depth), core samples (up to 18 m depth) and geophysical measurements (electrical resistivity tomography, seismic refraction tomography). Temporal contextualization of sediments is achieved using radiocarbon dating. As a result of illuvial processes, clay curtains are observed almost continuously up to 18 m depth within the slope sediments, suggesting a genesis during Pleistocene warm stages. Radiocarbon dating in the alluvial floodplain point to pronounced sedimentary relocation processes between around 2.400 and 1.000 BP. This emphasizes the importance of naturally caused process dynamics as population density in the surroundings of the Otterbach catchment was low during this period and the area was mostly forested. With close proximity and interlockings between slope sediments relict river terraces and Holocene alluvial sediments investigations allow for a reconstruction of the palaeoenviroment in context with land use and human dynamics in the catchment of the Otterbach valley.

High-efficient and high-content cytotoxic recording via dynamic and continuous cell-based impedance biosensor technology.

PubMed

Hu, Ning; Fang, Jiaru; Zou, Ling; Wan, Hao; Pan, Yuxiang; Su, Kaiqi; Zhang, Xi; Wang, Ping

2016-10-01

Cell-based bioassays were effective method to assess the compound toxicity by cell viability, and the traditional label-based methods missed much information of cell growth due to endpoint detection, while the higher throughputs were demanded to obtain dynamic information. Cell-based biosensor methods can dynamically and continuously monitor with cell viability, however, the dynamic information was often ignored or seldom utilized in the toxin and drug assessment. Here, we reported a high-efficient and high-content cytotoxic recording method via dynamic and continuous cell-based impedance biosensor technology. The dynamic cell viability, inhibition ratio and growth rate were derived from the dynamic response curves from the cell-based impedance biosensor. The results showed that the biosensors has the dose-dependent manners to diarrhetic shellfish toxin, okadiac acid based on the analysis of the dynamic cell viability and cell growth status. Moreover, the throughputs of dynamic cytotoxicity were compared between cell-based biosensor methods and label-based endpoint methods. This cell-based impedance biosensor can provide a flexible, cost and label-efficient platform of cell viability assessment in the shellfish toxin screening fields.

Theoretical studies in interstellar cloud chemistry

NASA Technical Reports Server (NTRS)

Chiu, Y. T.; Prasad, S. S.

1993-01-01

This final report represents the completion of the three tasks under the purchase order no. SCPDE5620,1,2F. Chemical composition of gravitationally contracting, but otherwise quiescent, interstellar clouds and of interstellar clouds traversed by high velocity shocks, were modeled in a comprehensive manner that represents a significant progress in modeling these objects. The evolutionary chemical modeling, done under this NASA contract, represents a notable advance over the 'classical' fixed condition equilibrium models because the evolutionary models consider not only the chemical processes but also the dynamical processes by which the dark interstellar clouds may have assumed their present state. The shock calculations, being reported here, are important because they extend the limited chemical composition derivable from dynamical calculations for the total density and temperature structures behind the shock front. In order to be tractable, the dynamical calculations must severely simplify the chemistry. The present shock calculations take the shock profiles from the dynamical calculations and derive chemical composition in a comprehensive manner. The results of the present modeling study are still to be analyzed with reference to astronomical observational data and other contemporary model predictions. As far as humanly possible, this analysis will be continued with CRE's (Creative Research Enterprises's) IR&D resources, until a sponsor is found.

Design of nonlinear PID controller and nonlinear model predictive controller for a continuous stirred tank reactor.

PubMed

Prakash, J; Srinivasan, K

2009-07-01

In this paper, the authors have represented the nonlinear system as a family of local linear state space models, local PID controllers have been designed on the basis of linear models, and the weighted sum of the output from the local PID controllers (Nonlinear PID controller) has been used to control the nonlinear process. Further, Nonlinear Model Predictive Controller using the family of local linear state space models (F-NMPC) has been developed. The effectiveness of the proposed control schemes has been demonstrated on a CSTR process, which exhibits dynamic nonlinearity.

A Harris-Todaro Agent-Based Model to Rural-Urban Migration

NASA Astrophysics Data System (ADS)

Espíndola, Aquino L.; Silveira, Jaylson J.; Penna, T. J. P.

2006-09-01

The Harris-Todaro model of the rural-urban migration process is revisited under an agent-based approach. The migration of the workers is interpreted as a process of social learning by imitation, formalized by a computational model. By simulating this model, we observe a transitional dynamics with continuous growth of the urban fraction of overall population toward an equilibrium. Such an equilibrium is characterized by stabilization of rural-urban expected wages differential (generalized Harris-Todaro equilibrium condition), urban concentration and urban unemployment. These classic results obtained originally by Harris and Todaro are emergent properties of our model.

Dynamic modeling and parameter estimation of a radial and loop type distribution system network

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

Jun Qui; Heng Chen; Girgis, A.A.

1993-05-01

This paper presents a new identification approach to three-phase power system modeling and model reduction taking power system network as multi-input, multi-output (MIMO) processes. The model estimate can be obtained in discrete-time input-output form, discrete- or continuous-time state-space variable form, or frequency-domain impedance transfer function matrix form. An algorithm for determining the model structure of this MIMO process is described. The effect of measurement noise on the approach is also discussed. This approach has been applied on a sample system and simulation results are also presented in this paper.

Nonlocal continuous models for forced vibration analysis of two- and three-dimensional ensembles of single-walled carbon nanotubes

NASA Astrophysics Data System (ADS)

Kiani, Keivan

2014-06-01

Novel nonlocal discrete and continuous models are proposed for dynamic analysis of two- and three-dimensional ensembles of single-walled carbon nanotubes (SWCNTs). The generated extra van der Waals forces between adjacent SWCNTs due to their lateral motions are evaluated via Lennard-Jones potential function. Using a nonlocal Rayleigh beam model, the discrete and continuous models are developed for both two- and three-dimensional ensembles of SWCNTs acted upon by transverse dynamic loads. The capabilities of the proposed continuous models in capturing the vibration behavior of SWCNTs ensembles are then examined through various numerical simulations. A reasonably good agreement between the results of the continuous models and those of the discrete ones is also reported. The effects of the applied load frequency, intertube spaces, and small-scale parameter on the transverse dynamic responses of both two- and three-dimensional ensembles of SWCNTs are explained. The proposed continuous models would be very useful for dynamic analyses of large populated ensembles of SWCNTs whose discrete models suffer from both computational efforts and labor costs.

Development of a new continuous process for mixing of complex non-Newtonian fluids

NASA Astrophysics Data System (ADS)

Migliozzi, Simona; Mazzei, Luca; Sochon, Bob; Angeli, Panagiota; Thames Multiphase Team; Coral Project Collaboration

2017-11-01

Design of new continuous mixing operations poses many challenges, especially when dealing with highly viscous non-Newtonian fluids. Knowledge of complex rheological behaviour of the working mixture is crucial for development of an efficient process. In this work, we investigate the mixing performance of two different static mixers and the effects of the mixture rheology on the manufacturing of novel non-aqueous-based oral care products using experimental and computational fluid dynamic methods. The two liquid phases employed, i.e. a carbomer suspension in polyethylene glycol and glycerol, start to form a gel when they mix. We studied the structure evolution of the liquid mixture using time-resolved rheometry and we obtained viscosity rheograms at different phase ratios from pressure drop measurements in a customized mini-channel. The numerical results and rheological model were validated with experimental measurements carried out in a specifically designed setup. EPSRS-CORAL.

The Dynamics of Networks of Identical Theta Neurons.

PubMed

Laing, Carlo R

2018-02-05

We consider finite and infinite all-to-all coupled networks of identical theta neurons. Two types of synaptic interactions are investigated: instantaneous and delayed (via first-order synaptic processing). Extensive use is made of the Watanabe/Strogatz (WS) ansatz for reducing the dimension of networks of identical sinusoidally-coupled oscillators. As well as the degeneracy associated with the constants of motion of the WS ansatz, we also find continuous families of solutions for instantaneously coupled neurons, resulting from the reversibility of the reduced model and the form of the synaptic input. We also investigate a number of similar related models. We conclude that the dynamics of networks of all-to-all coupled identical neurons can be surprisingly complicated.

The Dynamic Range Paradox: A Central Auditory Model of Intensity Change Detection

PubMed Central

Simpson, Andrew J.R.; Reiss, Joshua D.

2013-01-01

In this paper we use empirical loudness modeling to explore a perceptual sub-category of the dynamic range problem of auditory neuroscience. Humans are able to reliably report perceived intensity (loudness), and discriminate fine intensity differences, over a very large dynamic range. It is usually assumed that loudness and intensity change detection operate upon the same neural signal, and that intensity change detection may be predicted from loudness data and vice versa. However, while loudness grows as intensity is increased, improvement in intensity discrimination performance does not follow the same trend and so dynamic range estimations of the underlying neural signal from loudness data contradict estimations based on intensity just-noticeable difference (JND) data. In order to account for this apparent paradox we draw on recent advances in auditory neuroscience. We test the hypothesis that a central model, featuring central adaptation to the mean loudness level and operating on the detection of maximum central-loudness rate of change, can account for the paradoxical data. We use numerical optimization to find adaptation parameters that fit data for continuous-pedestal intensity change detection over a wide dynamic range. The optimized model is tested on a selection of equivalent pseudo-continuous intensity change detection data. We also report a supplementary experiment which confirms the modeling assumption that the detection process may be modeled as rate-of-change. Data are obtained from a listening test (N = 10) using linearly ramped increment-decrement envelopes applied to pseudo-continuous noise with an overall level of 33 dB SPL. Increments with half-ramp durations between 5 and 50,000 ms are used. The intensity JND is shown to increase towards long duration ramps (p<10−6). From the modeling, the following central adaptation parameters are derived; central dynamic range of 0.215 sones, 95% central normalization, and a central loudness JND constant of 5.5×10−5 sones per ms. Through our findings, we argue that loudness reflects peripheral neural coding, and the intensity JND reflects central neural coding. PMID:23536749

Dynamic Load on Continuous Multi-Lane Bridge Deck from Moving Vehicles

NASA Astrophysics Data System (ADS)

ZHU, X. Q.; LAW, S. S.

2002-04-01

The dynamic loading on a multi-lane continuous bridge deck due to vehicles moving on top at a constant velocity is investigated. The bridge is modelled as a multi-span continuous orthotropic rectangular plate with line rigid intermediate supports. The vehicle is simulated as a two-axle three-dimensional vehicle model with seven degrees of freedom according to the H20-44 vehicle design loading (AASHTO LRFD Bridge Design Specifications 1998 American Association of State Highway and Transportation Officials [1]). The dynamic behavior of the bridge deck under single and several vehicles moving in different lanes is analyzed using the orthotropic plate theory and modal superposition technique. The dynamic loading is studied in terms of the dynamic impact factor of the bridge deck. The impact factor is found varying in an opposite trend as the dynamic responses for the different loading cases under study.

In situ monitoring of biomolecular processes in living systems using surface-enhanced Raman scattering

NASA Astrophysics Data System (ADS)

Altunbek, Mine; Kelestemur, Seda; Culha, Mustafa

2015-12-01

Surface-enhanced Raman scattering (SERS) continues to strive to gather molecular level information from dynamic biological systems. It is our ongoing effort to utilize the technique for understanding of the biomolecular processes in living systems such as eukaryotic and prokaryotic cells. In this study, the technique is investigated to identify cell death mechanisms in 2D and 3D in vitro cell culture models, which is a very important process in tissue engineering and pharmaceutical applications. Second, in situ biofilm formation monitoring is investigated to understand how microorganisms respond to the environmental stimuli, which inferred information can be used to interfere with biofilm formation and fight against their pathogenic activity.

A systematic petri net approach for multiple-scale modeling and simulation of biochemical processes.

PubMed

Chen, Ming; Hu, Minjie; Hofestädt, Ralf

2011-06-01

A method to exploit hybrid Petri nets for modeling and simulating biochemical processes in a systematic way was introduced. Both molecular biology and biochemical engineering aspects are manipulated. With discrete and continuous elements, the hybrid Petri nets can easily handle biochemical factors such as metabolites concentration and kinetic behaviors. It is possible to translate both molecular biological behavior and biochemical processes workflow into hybrid Petri nets in a natural manner. As an example, penicillin production bioprocess is modeled to illustrate the concepts of the methodology. Results of the dynamic of production parameters in the bioprocess were simulated and observed diagrammatically. Current problems and post-genomic perspectives were also discussed.

Fractional quantum mechanics on networks: Long-range dynamics and quantum transport

NASA Astrophysics Data System (ADS)

Riascos, A. P.; Mateos, José L.

2015-11-01

In this paper we study the quantum transport on networks with a temporal evolution governed by the fractional Schrödinger equation. We generalize the dynamics based on continuous-time quantum walks, with transitions to nearest neighbors on the network, to the fractional case that allows long-range displacements. By using the fractional Laplacian matrix of a network, we establish a formalism that combines a long-range dynamics with the quantum superposition of states; this general approach applies to any type of connected undirected networks, including regular, random, and complex networks, and can be implemented from the spectral properties of the Laplacian matrix. We study the fractional dynamics and its capacity to explore the network by means of the transition probability, the average probability of return, and global quantities that characterize the efficiency of this quantum process. As a particular case, we explore analytically these quantities for circulant networks such as rings, interacting cycles, and complete graphs.

Fractional quantum mechanics on networks: Long-range dynamics and quantum transport.

PubMed

Riascos, A P; Mateos, José L

2015-11-01

In this paper we study the quantum transport on networks with a temporal evolution governed by the fractional Schrödinger equation. We generalize the dynamics based on continuous-time quantum walks, with transitions to nearest neighbors on the network, to the fractional case that allows long-range displacements. By using the fractional Laplacian matrix of a network, we establish a formalism that combines a long-range dynamics with the quantum superposition of states; this general approach applies to any type of connected undirected networks, including regular, random, and complex networks, and can be implemented from the spectral properties of the Laplacian matrix. We study the fractional dynamics and its capacity to explore the network by means of the transition probability, the average probability of return, and global quantities that characterize the efficiency of this quantum process. As a particular case, we explore analytically these quantities for circulant networks such as rings, interacting cycles, and complete graphs.

Policy reconciliation for access control in dynamic cross-enterprise collaborations

NASA Astrophysics Data System (ADS)

Preuveneers, D.; Joosen, W.; Ilie-Zudor, E.

2018-03-01

In dynamic cross-enterprise collaborations, different enterprises form a - possibly temporary - business relationship. To integrate their business processes, enterprises may need to grant each other limited access to their information systems. Authentication and authorization are key to secure information handling. However, access control policies often rely on non-standardized attributes to describe the roles and permissions of their employees which convolutes cross-organizational authorization when business relationships evolve quickly. Our framework addresses the managerial overhead of continuous updates to access control policies for enterprise information systems to accommodate disparate attribute usage. By inferring attribute relationships, our framework facilitates attribute and policy reconciliation, and automatically aligns dynamic entitlements during the evaluation of authorization decisions. We validate our framework with a Industry 4.0 motivating scenario on networked production where such dynamic cross-enterprise collaborations are quintessential. The evaluation reveals the capabilities and performance of our framework, and illustrates the feasibility of liberating the security administrator from manually provisioning and aligning attributes, and verifying the consistency of access control policies for cross-enterprise collaborations.

The gravity model of labor migration behavior

NASA Astrophysics Data System (ADS)

Alexandr, Tarasyev; Alexandr, Tarasyev

2017-07-01

In this article, we present a dynamic inter-regional model, that is based on the gravity approach to migration and describes in continuous time the labor force dynamics between a number of conjugate regions. Our modification of the gravity migration model allows to explain the migration processes and to display the impact of migration on the regional economic development both for regions of origin and attraction. The application of our model allows to trace the dependency between salaries levels, total workforce, the number of vacancies and the number unemployed people in simulated regions. Due to the gravity component in our model the accuracy of prediction for migration flows is limited by the distance range between analyzed regions, so this model is tested on a number of conjugate neighbor regions. Future studies will be aimed at development of a multi-level dynamic model, which allows to construct a forecast for unemployment and vacancies trends on the first modeling level and to use these identified parameters on the second level for describing dynamic trajectories of migration flows.

Evolutionary Dynamics and Diversity in Microbial Populations

NASA Astrophysics Data System (ADS)

Thompson, Joel; Fisher, Daniel

2013-03-01

Diseases such as flu and cancer adapt at an astonishing rate. In large part, viruses and cancers are so difficult to prevent because they are continually evolving. Controlling such ``evolutionary diseases'' requires a better understanding of the underlying evolutionary dynamics. It is conventionally assumed that adaptive mutations are rare and therefore will occur and sweep through the population in succession. Recent experiments using modern sequencing technologies have illuminated the many ways in which real population sequence data does not conform to the predictions of conventional theory. We consider a very simple model of asexual evolution and perform simulations in a range of parameters thought to be relevant for microbes and cancer. Simulation results reveal complex evolutionary dynamics typified by competition between lineages with different sets of adaptive mutations. This dynamical process leads to a distribution of mutant gene frequencies different than expected under the conventional assumption that adaptive mutations are rare. Simulated gene frequencies share several conspicuous features with data collected from laboratory-evolved yeast and the worldwide population of influenza.

Dynamic Bayesian wavelet transform: New methodology for extraction of repetitive transients

NASA Astrophysics Data System (ADS)

Wang, Dong; Tsui, Kwok-Leung

2017-05-01

Thanks to some recent research works, dynamic Bayesian wavelet transform as new methodology for extraction of repetitive transients is proposed in this short communication to reveal fault signatures hidden in rotating machine. The main idea of the dynamic Bayesian wavelet transform is to iteratively estimate posterior parameters of wavelet transform via artificial observations and dynamic Bayesian inference. First, a prior wavelet parameter distribution can be established by one of many fast detection algorithms, such as the fast kurtogram, the improved kurtogram, the enhanced kurtogram, the sparsogram, the infogram, continuous wavelet transform, discrete wavelet transform, wavelet packets, multiwavelets, empirical wavelet transform, empirical mode decomposition, local mean decomposition, etc.. Second, artificial observations can be constructed based on one of many metrics, such as kurtosis, the sparsity measurement, entropy, approximate entropy, the smoothness index, a synthesized criterion, etc., which are able to quantify repetitive transients. Finally, given artificial observations, the prior wavelet parameter distribution can be posteriorly updated over iterations by using dynamic Bayesian inference. More importantly, the proposed new methodology can be extended to establish the optimal parameters required by many other signal processing methods for extraction of repetitive transients.

Smart Sensing and Recognition Based on Models of Neural Networks

DTIC Science & Technology

1990-11-15

9P-o ,yY𔄃-’. AD-A230 701 University of Pensylvania Philadelphia, PA 19104-6390 SMART SENSING AND RECOGNITION BASED ON MODELS OF NEURAL NETWORKS ... networks , photonic 1 implementations, nonlinear dynamical signal processing 9 ABSTRACT (Continue on reverse if necessary and identify by block number...not develop in isolation but in synergism with sensory organs and their feature forming networks . This means that development of artificial pattern

Optical sectioning in wide-field microscopy obtained by dynamic structured light illumination and detection based on a smart pixel detector array.

PubMed

Mitić, Jelena; Anhut, Tiemo; Meier, Matthias; Ducros, Mathieu; Serov, Alexander; Lasser, Theo

2003-05-01

Optical sectioning in wide-field microscopy is achieved by illumination of the object with a continuously moving single-spatial-frequency pattern and detecting the image with a smart pixel detector array. This detector performs an on-chip electronic signal processing that extracts the optically sectioned image. The optically sectioned image is directly observed in real time without any additional postprocessing.

Cognitive Radio Networks for Tactical Wireless Communications

DTIC Science & Technology

2014-12-01

exists. Instead, security is an evolving process, as we have seen in the context of WLANs and 2G / 3G networks. New system vulnerabilities continue to...in the network configuration and radio parameters take place due to mobility of platforms, and variation in other users of the RF environment. CRNs...dynamic spectrum access experimentally, and it represents the largest military Mobile Ad hoc Network (MANET) as of today. The WNaN demonstrator has been

Final Report for Dynamic Models for Causal Analysis of Panel Data. Models for Change in Quantitative Variables, Part I Deterministic Models. Part II, Chapter 3.

ERIC Educational Resources Information Center

Hannan, Michael T.

This document is part of a series of chapters described in SO 011 759. Addressing the question of effective models to measure change and the change process, the author suggests that linear structural equation systems may be viewed as steady state outcomes of continuous-change models and have rich sociological grounding. Two interpretations of the…

Data-based hybrid tension estimation and fault diagnosis of cold rolling continuous annealing processes.

PubMed

Liu, Qiang; Chai, Tianyou; Wang, Hong; Qin, Si-Zhao Joe

2011-12-01

The continuous annealing process line (CAPL) of cold rolling is an important unit to improve the mechanical properties of steel strips in steel making. In continuous annealing processes, strip tension is an important factor, which indicates whether the line operates steadily. Abnormal tension profile distribution along the production line can lead to strip break and roll slippage. Therefore, it is essential to estimate the whole tension profile in order to prevent the occurrence of faults. However, in real annealing processes, only a limited number of strip tension sensors are installed along the machine direction. Since the effects of strip temperature, gas flow, bearing friction, strip inertia, and roll eccentricity can lead to nonlinear tension dynamics, it is difficult to apply the first-principles induced model to estimate the tension profile distribution. In this paper, a novel data-based hybrid tension estimation and fault diagnosis method is proposed to estimate the unmeasured tension between two neighboring rolls. The main model is established by an observer-based method using a limited number of measured tensions, speeds, and currents of each roll, where the tension error compensation model is designed by applying neural networks principal component regression. The corresponding tension fault diagnosis method is designed using the estimated tensions. Finally, the proposed tension estimation and fault diagnosis method was applied to a real CAPL in a steel-making company, demonstrating the effectiveness of the proposed method.

Assessing the Impact of Permafrost Degradation on Lake Dynamics at Pan-Arctic Scale

NASA Astrophysics Data System (ADS)

Shah, C. A.; Sheng, Y.; Smith, L. C.; Li, J.; Lyons, E. A.

2009-12-01

Recent evidences of Arctic lake dynamics display consistent trends linked to climatic changes. Primary control on local hydrological processes in high-latitude regions is dictated by the presence or absence of permafrost. Though our understanding of permafrost hydrologic processes has advanced considerably in the past decades, the potential linkage between permafrost and the rate and direction of recent (~30 years) lake area change is the subject of ongoing debate. In response to accelerated climatic warming, the differential thawing of ice-rich permafrost has lead to the formation of thermokarst lakes in many lowland Arctic landscapes of North America and Eurasia. Lower albedo and additional heat advected into these lakes through runoff lead to accelerated subsurface thawing and subsequent lake expansion. In North American regions with continuous permafrost, most studies have found insignificant long-term trend in lake change, whereas a study in West Siberia reported substantial increase in the areal extent of continuous permafrost lakes. Lake drainage occurs when open taliks in degrading permafrost completely penetrate the underlying soil or connect to a subsurface layer. As a result, lake extents have been shown to decrease in discontinuous permafrost zones at varying rates across the pan-Arctic. Though it is certain that the lakes in isolated and sporadic permafrost zones are shrinking as well, we have limited knowledge about the rate of such ongoing changes. The disturbing circumpolar attrition of hydrometric and climatic monitoring networks has severely hampered our ability to study the ongoing hydrological changes. Although remote sensing broadens the spatial domain of analysis, caution must be observed in drawing conclusions from these images as satellite image analysis is often sensitive to sensor characteristics as well as to techniques used for processing these images. Hence, our objective is to perform a systematic assessment of multi-decadal pan-Arctic (above 45N) lake changes for advancing our existing knowledge on their distribution and extending our ability to monitor the effects of recent northern high latitude environment change on lake dynamics. Using Landsat images acquired circa 1970 (MSS) and 2000 (ETM+), we are currently mapping lakes within all the permafrost extents (continuous, discontinuous, isolated, and sporadic). High quality Landsat images with low cloud cover have been chosen for the summer season of hydrologically normal years. Based on the availability of spatially overlapping MSS and ETM+ images, our study area covers ~60% of permafrost regions throughout the pan-Arctic including Alaska, Canada, and Siberia. By comparing the lake maps for 1970 and 2000, we will be able to quantify the impact of permafrost degradation on lake dynamics. Furthermore, in the absence of temporally and spatially continuous measurements of active layer thickness and the total thickness of the underlying permafrost, rate of lake change can serve as a useful indicator of permafrost degradation. With a projected severe near surface permafrost degradation during the 21st century, our research is critical in understanding the ongoing changes and the likely future direction of permafrost hydrology.

Autogenic dynamics of debris-flow fans

NASA Astrophysics Data System (ADS)

van den Berg, Wilco; de Haas, Tjalling; Braat, Lisanne; Kleinhans, Maarten

2015-04-01

Alluvial fans develop their semi-conical shape by cyclic avulsion of their geomorphologically active sector from a fixed fan apex. These cyclic avulsions have been attributed to both allogenic and autogenic forcings and processes. Autogenic dynamics have been extensively studied on fluvial fans through physical scale experiments, and are governed by cyclic alternations of aggradation by unconfined sheet flow, fanhead incision leading to channelized flow, channel backfilling and avulsion. On debris-flow fans, however, autogenic dynamics have not yet been directly observed. We experimentally created debris-flow fans under constant extrinsic forcings, and show that autogenic dynamics are a fundamental intrinsic process on debris-flow fans. We found that autogenic cycles on debris-flow fans are driven by sequences of backfilling, avulsion and channelization, similar to the cycles on fluvial fans. However, the processes that govern these sequences are unique for debris-flow fans, and differ fundamentally from the processes that govern autogenic dynamics on fluvial fans. We experimentally observed that backfilling commenced after the debris flows reached their maximum possible extent. The next debris flows then progressively became shorter, driven by feedbacks on fan morphology and flow-dynamics. The progressively decreasing debris-flow length caused in-channel sedimentation, which led to increasing channel overflow and wider debris flows. This reduced the impulse of the liquefied flow body to the flow front, which then further reduced flow velocity and runout length, and induced further in-channel sedimentation. This commenced a positive feedback wherein debris flows became increasingly short and wide, until the channel was completely filled and the apex cross-profile was plano-convex. At this point, there was no preferential transport direction by channelization, and the debris flows progressively avulsed towards the steepest, preferential, flow path. Simultaneously, the debris flows started to channelize, forced by increasingly effective concentration of the flow impulse to the flow front, which caused more effective lateral levee formation and an increasingly well-defined channel. This process continued until the debris flows reached their maximum possible extent and the cycle was reverted. Channelization occurred in the absence of erosion, in contrast with fluvial fans. Backfilling and channelization cycles were gradual and symmetric, requiring multiple debris flows to be completed. These results add debris-flow fans to the spectrum of fan-shaped aqueous systems that are affected by autogenic dynamics, now ranging from low-gradient rivers systems to steep-gradient mass-flow fans.

Effect of irrigation regimes on mobilization of nonreactive tracers and dissolved and particulate phosphorus in slurry-injected soils

NASA Astrophysics Data System (ADS)

GlæSner, Nadia; Kjaergaard, Charlotte; RubæK, Gitte H.; Magid, Jakob

2011-12-01

Understanding the mobilization processes of phosphorus (P) in the plow layer are essential to quantify potential P losses and suggest management strategies to reduce P losses. This study is aimed at examining nonequilibrium exchange dynamics on the mobilization of slurry-amended Br-, and dissolved and particulate P in slurry-injected soils. We compared leaching from intact soil columns (20 cm diam., 20 cm high) under unsaturated flow (suction at the lower boundary of 5 hPa) subjected to continuous irrigation at 2 mm hr-1, and intermittent irrigation at 2 mm hr-1 and 10 mm hr-1 to with interruptions of 10 h duration simulate periodic precipitation events. Suction was increased to 20 hPa during interruptions to allow drainage of the largest pores. Irrigation interruptions induced fluctuations in leaching of nonreactive tracers, particles, and particulate P indicating nonequilibrium transport. A nonreactive tracer, 3H2O, applied with irrigation water, diffused from mobile to less mobile pore regions during interruptions, leading to a lower mass recovery during low-intermittent (76.4%) compared with continuous irrigation (86.6%). In contrast, mass recovery of slurry-injected Br- increased as Br- diffused from less mobile to mobile pore regions during low-intermittent (53%-64%) compared with continuous irrigation (42%-47%). Despite high fluctuations during the leaching of particles and particulate P during low-intermittent irrigation, accumulated values did not differ from continuous irrigation. Increased preferential flow during high-intermittent irrigation lowered the mass exchange between pore regions of nonreactive tracers, particles, and particulate P compared with low-intermittent irrigation. The leaching of dissolved inorganic and organic P was low during all of the experiments and scarcely affected by the irrigation regime. These results highlight that nonequilibrium exchange dynamics are important when evaluating processes affecting mobilization and transport in structured soils. Leaching experiments, including cycles of irrigation interruptions and gravitational drainage, thus, adds significantly to the understanding and interpretation of processes affecting mobilization and transport under natural conditions.

Flight Dynamics Performances of the MetOp A Satellite during the First Months of Operations

NASA Technical Reports Server (NTRS)

Righetti, Pier Luigi; Meixner, Hilda; Sancho, Francisco; Damiano, Antimo; Lazaro, David

2007-01-01

The 19th of October 2006 at 16:28 UTC the first MetOp satellite (MetOp A) was successfully launched from the Baykonur cosmodrome by a Soyuz/Fregat launcher. After only three days of LEOP operations, performed by ESOC, the satellite was handed over to EUMETSAT, who is since then taking care of all satellite operations. MetOp A is the first European operational satellite for meteorology flying in a Low Earth Orbit (LEO), all previous satellites operated by EUMETSAT, belonging to the METEOSAT family, being located in the Geo-stationary orbit. To ensure safe operations for a LEO satellite accurate and continuous commanding from ground of the on-board AOCS is required. That makes the operational transition at the end of the LEOP quite challenging, as the continuity of the Flight Dynamics operations is to be maintained. That means that the main functions of the Flight Dynamics have to be fully validated on-flight during the LEOP, before taking over the operational responsibility on the spacecraft, and continuously monitored during the entire mission. Due to the nature of a meteorological operational mission, very stringent requirements in terms of overall service availability (99 % of the collected data), timeliness of processing of the observation data (3 hours after sensing) and accuracy of the geo-location of the meteorological products (1 km) are to be fulfilled. That translates in tight requirements imposed to the Flight Dynamics facility (FDF) in terms of accuracy, timeliness and availability of the generated orbit and clock solutions; a detailed monitoring of the quality of these products is thus mandatory. Besides, being the accuracy of the image geo-location strongly related with the pointing performance of the platform and with the on-board timing stability, monitoring from ground of the behaviour of the on-board sensors and clock is needed. This paper presents an overview of the Flight Dynamics operations performed during the different phases of the MetOp A mission up to routine. The activities performed to validate all the Flight Dynamics functions, characterize the behaviour of the satellite and monitor the performances of the Flight Dynamics facility will be highlighted. The MetOp Flight Dynamics Operations team is led by Anders Meier Soerensen and composed by Pier Luigi Righetti, Francisco Sancho, Antimo Damiano and David Lazaro. The team is supported by Hilda Meixner, responsible for all Flight Dynamics validation activities.

Biological soil crusts exhibit a dynamic response to seasonal rain and release from grazing with implications for soil stability

USGS Publications Warehouse

Jimenez, Aguilar A.; Huber-Sannwald, E.; Belnap, J.; Smart, D.R.; Arredondo, Moreno J.T.

2009-01-01

In Northern Mexico, long-term grazing has substantially degraded semiarid landscapes. In semiarid systems, ecological and hydrological processes are strongly coupled by patchy plant distribution and biological soil crust (BSC) cover in plant-free interspaces. In this study, we asked: 1) how responsive are BSC cover/composition to a drying/wetting cycle and two-year grazing removal, and 2) what are the implications for soil erosion? We characterized BSC morphotypes and their influence on soil stability under grazed/non-grazed conditions during a dry and wet season. Light- and dark-colored cyanobacteria were dominant at the plant tussock and community level. Cover changes in these two groups differed after a rainy season and in response to grazing removal. Lichens with continuous thalli were more vulnerable to grazing than those with semi-continuous/discontinuous thalli after the dry season. Microsites around tussocks facilitated BSC colonization compared to interspaces. Lichen and cyanobacteria morphotypes differentially enhanced resistance to soil erosion; consequently, surface soil stability depends on the spatial distribution of BSC morphotypes, suggesting soil stability may be as dynamic as changes in the type of BSC cover. Longer-term spatially detailed studies are necessary to elicit spatiotemporal dynamics of BSC communities and their functional role in biotically and abiotically variable environments. ?? 2009 Elsevier Ltd.

Nonlinear system identification for prostate cancer and optimality of intermittent androgen suppression therapy.

PubMed

Suzuki, Taiji; Aihara, Kazuyuki

2013-09-01

These days prostate cancer is one of the most common types of malignant neoplasm in men. Androgen ablation therapy (hormone therapy) has been shown to be effective for advanced prostate cancer. However, continuous hormone therapy often causes recurrence. This results from the progression of androgen-dependent cancer cells to androgen-independent cancer cells during the continuous hormone therapy. One possible method to prevent the progression to the androgen-independent state is intermittent androgen suppression (IAS) therapy, which ceases dosing intermittently. In this paper, we propose two methods to estimate the dynamics of prostate cancer, and investigate the IAS therapy from the viewpoint of optimality. The two methods that we propose for dynamics estimation are a variational Bayesian method for a piecewise affine (PWA) system and a Gaussian process regression method. We apply the proposed methods to real clinical data and compare their predictive performances. Then, using the estimated dynamics of prostate cancer, we observe how prostate cancer behaves for various dosing schedules. It can be seen that the conventional IAS therapy is a way of imposing high cost for dosing while keeping the prostate cancer in a safe state. We would like to dedicate this paper to the memory of Professor Luigi M. Ricciardi. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

A dynamic response model for pressure sensors in continuum and high Knudsen number flows with large temperature gradients

NASA Technical Reports Server (NTRS)

Whitmore, Stephen A.; Petersen, Brian J.; Scott, David D.

1996-01-01

This paper develops a dynamic model for pressure sensors in continuum and rarefied flows with longitudinal temperature gradients. The model was developed from the unsteady Navier-Stokes momentum, energy, and continuity equations and was linearized using small perturbations. The energy equation was decoupled from momentum and continuity assuming a polytropic flow process. Rarefied flow conditions were accounted for using a slip flow boundary condition at the tubing wall. The equations were radially averaged and solved assuming gas properties remain constant along a small tubing element. This fundamental solution was used as a building block for arbitrary geometries where fluid properties may also vary longitudinally in the tube. The problem was solved recursively starting at the transducer and working upstream in the tube. Dynamic frequency response tests were performed for continuum flow conditions in the presence of temperature gradients. These tests validated the recursive formulation of the model. Model steady-state behavior was analyzed using the final value theorem. Tests were performed for rarefied flow conditions and compared to the model steady-state response to evaluate the regime of applicability. Model comparisons were excellent for Knudsen numbers up to 0.6. Beyond this point, molecular affects caused model analyses to become inaccurate.

Dynamic Radioactive Source for Evaluating and Demonstrating Time-dependent Performance of Continuous Air Monitors.

PubMed

McLean, Thomas D; Moore, Murray E; Justus, Alan L; Hudston, Jonathan A; Barbé, Benoît

2016-11-01

Evaluation of continuous air monitors in the presence of a plutonium aerosol is time intensive, expensive, and requires a specialized facility. The Radiation Protection Services Group at Los Alamos National Laboratory has designed a Dynamic Radioactive Source, intended to replace plutonium aerosol challenge testing. The Dynamic Radioactive Source is small enough to be inserted into the sampler filter chamber of a typical continuous air monitor. Time-dependent radioactivity is introduced from electroplated sources for real-time testing of a continuous air monitor where a mechanical wristwatch motor rotates a mask above an alpha-emitting electroplated disk source. The mask is attached to the watch's minute hand, and as it rotates, more of the underlying source is revealed. The measured alpha activity increases with time, simulating the arrival of airborne radioactive particulates at the air sampler inlet. The Dynamic Radioactive Source allows the temporal behavior of puff and chronic release conditions to be mimicked without the need for radioactive aerosols. The new system is configurable to different continuous air monitor designs and provides an in-house testing capability (benchtop compatible). It is a repeatable and reusable system and does not contaminate the tested air monitor. Test benefits include direct user control, realistic (plutonium) aerosol spectra, and iterative development of continuous air monitor alarm algorithms. Data obtained using the Dynamic Radioactive Source has been used to elucidate alarm algorithms and to compare the response time of two commercial continuous air monitors.

Dynamic Radioactive Source for Evaluating and Demonstrating Time-dependent Performance of Continuous Air Monitors

DOE PAGES

McLean, Thomas D.; Moore, Murray E.; Justus, Alan L.; ...

2016-01-01

Evaluation of continuous air monitors in the presence of a plutonium aerosol is time intensive, expensive, and requires a specialized facility. The Radiation Protection Services Group at Los Alamos National Laboratory has designed a Dynamic Radioactive Source, intended to replace plutonium aerosol challenge testing. Furthermore, the Dynamic Radioactive Source is small enough to be inserted into the sampler filter chamber of a typical continuous air monitor. Time-dependent radioactivity is introduced from electroplated sources for real-time testing of a continuous air monitor where a mechanical wristwatch motor rotates a mask above an alpha-emitting electroplated disk source. The mask is attached tomore » the watch’s minute hand, and as it rotates, more of the underlying source is revealed. The alpha activity we measured increases with time, simulating the arrival of airborne radioactive particulates at the air sampler inlet. The Dynamic Radioactive Source allows the temporal behavior of puff and chronic release conditions to be mimicked without the need for radioactive aerosols. The new system is configurable to different continuous air monitor designs and provides an in-house testing capability (benchtop compatible). It is a repeatable and reusable system and does not contaminate the tested air monitor. Test benefits include direct user control, realistic (plutonium) aerosol spectra, and iterative development of continuous air monitor alarm algorithms. We also used data obtained using the Dynamic Radioactive Source to elucidate alarm algorithms and to compare the response time of two commercial continuous air monitors.« less

Influence of fluid dynamics on anaerobic digestion of food waste for biogas production.

PubMed

Wang, Fengping; Zhang, Cunsheng; Huo, Shuhao

2017-05-01

To enhance the stability and efficiency of an anaerobic process, the influences of fluid dynamics on the performance of anaerobic digestion and sludge granulation were investigated using computational fluid dynamics (CFD). Four different propeller speeds (20, 60, 100, 140 r/min) were adopted for anaerobic digestion of food waste in a 30 L continuously stirred tank reactor (CSTR). Experimental results indicated that the methane yield increased with increasing the propeller speed within the experimental range. Results from CFD simulation and sludge granulation showed that the optimum propeller speed for anaerobic digestion was 100 r/min. Lower propeller speed (20 r/min) inhibited mass transfer and resulted in the failure of anaerobic digestion, while higher propeller speed (140 r/min) would lead to higher energy loss and system instability. Under this condition, anaerobic digestion could work effectively with higher efficiency of mass transfer which facilitated sludge granulation and biogas production. The corresponding mean liquid velocity and shear strain rate were 0.082 m/s and 10.48 s -1 , respectively. Moreover, compact granular sludge could be formed, with lower energy consumption. CFD was successfully used to study the influence of fluid dynamics on the anaerobic digestion process. The key parameters of the optimum mixing condition for anaerobic digestion of food waste in a 30 L CSTR including liquid velocity and shear strain rate were obtained using CFD, which were of paramount significance for the scale-up of the bioreactor. This study provided a new way for the optimization and scale-up of the anaerobic digestion process in CSTR based on the fluid dynamics analysis.

Continuous Firefly Algorithm for Optimal Tuning of Pid Controller in Avr System

NASA Astrophysics Data System (ADS)

Bendjeghaba, Omar

2014-01-01

This paper presents a tuning approach based on Continuous firefly algorithm (CFA) to obtain the proportional-integral- derivative (PID) controller parameters in Automatic Voltage Regulator system (AVR). In the tuning processes the CFA is iterated to reach the optimal or the near optimal of PID controller parameters when the main goal is to improve the AVR step response characteristics. Conducted simulations show the effectiveness and the efficiency of the proposed approach. Furthermore the proposed approach can improve the dynamic of the AVR system. Compared with particle swarm optimization (PSO), the new CFA tuning method has better control system performance in terms of time domain specifications and set-point tracking.

Liquid Microjunction Surface Sampling Probe Fluid Dynamics: Computational and Experimental Analysis of Coaxial Intercapillary Positioning Effects on Sample Manipulation

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

ElNaggar, Mariam S; Barbier, Charlotte N; Van Berkel, Gary J

A coaxial geometry liquid microjunction surface sampling probe (LMJ-SSP) enables direct extraction of analytes from surfaces for subsequent analysis by techniques like mass spectrometry. Solution dynamics at the probe-to-sample surface interface in the LMJ-SSP has been suspected to influence sampling efficiency and dispersion but has not been rigorously investigated. The effect on flow dynamics and analyte transport to the mass spectrometer caused by coaxial retraction of the inner and outer capillaries from each other and the surface during sampling with a LMJ-SSP was investigated using computational fluid dynamics and experimentation. A transparent LMJ-SSP was constructed to provide the means formore » visual observation of the dynamics of the surface sampling process. Visual observation, computational fluid dynamics (CFD) analysis, and experimental results revealed that inner capillary axial retraction from the flush position relative to the outer capillary transitioned the probe from a continuous sampling and injection mode through an intermediate regime to sample plug formationmode caused by eddy currents at the sampling end of the probe. The potential for analytical implementation of these newly discovered probe operational modes is discussed.« less

4D ground penetrating radar measurements as non-invasive means for hydrological process investigation

NASA Astrophysics Data System (ADS)

Jackisch, Conrad; Allroggen, Niklas

2017-04-01

The missing vision into the subsurface appears to be a major limiting factor for our hydrological process understanding and theory development. Today, hydrology-related sciences have collected tremendous evidence for soils acting as drainage network and retention stores simultaneously in structured and self-organising domains. However, our present observation technology relies mainly on point-scale sensors, which integrate over a volume of unknown structures and is blind for their distribution. Although heterogeneity is acknowledged at all scales, it is rarely seen as inherent system property. At small scales (soil moisture probe) and at large scales (neutron probe) our measurements leave quite some ambiguity. Consequently, spatially and temporally continuous measurement of soil water states is essential for advancing our understanding and development of subsurface process theories. We present results from several irrigation experiments accompanied by 2D and 3D time-lapse GPR for the development of a novel technique to visualise and quantify water dynamics in the subsurface. Through the comparison of TDR, tracer and gravimetric measurement of soil moisture it becomes apparent that all sensor-based techniques are capable to record temporal dynamics, but are challenged to precisely quantify the measurements and to extrapolate them in space. At the same time excavative methods are very limited in temporal and spatial resolution. The application of non-invasive 4D GPR measurements complements the existing techniques and reveals structural and temporal dynamics simultaneously. By consequently increasing the density of the GPR data recordings in time and space, we find means to process the data also in the time-dimension. This opens ways to quantitatively analyse soil water dynamics in complex settings.

Microstructure evolution and dynamic recrystallization behavior of a powder metallurgy Ti-22Al-25Nb alloy during hot compression

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

Jia, Jianbo

The flow behavior of a powder metallurgy (P/M) Ti-22Al-25Nb alloy during hot compression tests has been investigated at a strain rate of 0.01 s{sup −1} and a temperature range of 980–1100 °C up to various true strains from 0.1 to 0.9. The effects of deformation temperature and strain on microstructure characterization and nucleation mechanisms of dynamic recrystallization (DRX) were assessed by means of Optical microscope (OM), electron backscatter diffraction (EBSD) and transmission electron microscope (TEM) techniques, respectively. The results indicated that the process of DRX was promoted by increasing deformation temperature and strain. By regression analysis, a power exponent relationshipmore » between peak stresses and sizes of stable DRX grains was developed. In addition, it is suggested that the discontinuous dynamic recrystallization (DDRX) and continuous dynamic recrystallization (CDRX) controlled nucleation mechanisms for DRX grains operated simultaneously during the whole hot process, and which played the leading role varied with hot process parameters of temperature and strain. It was further demonstrated that the CDRX featured by progressive subgrain rotation was weakened by elevating deformation temperatures. - Highlights: •Flow behavior of a P/M Ti-22Al-25Nb is studied by hot compression tests. •Microstructure evolution of alloy is affected by deformation temperature and strain. •The relationship between peak stress and stable DRX grain size was developed. •The process of DRX was promoted by increasing deformation temperature and strain. •Nucleation mechanisms of DRX were identified by EBSD analysis and TEM observation.« less

Shoreline dynamics of the active Yellow River delta since the implementation of Water-Sediment Regulation Scheme: A remote-sensing and statistics-based approach

NASA Astrophysics Data System (ADS)

Fan, Yaoshen; Chen, Shenliang; Zhao, Bo; Pan, Shunqi; Jiang, Chao; Ji, Hongyu

2018-01-01

The Active Yellow River (Huanghe) Delta (AYRD) is a complex landform in which rapid deposition takes place due to its geologic formation and evolution. Continuous monitoring of shoreline dynamics at high-temporal frequency is crucial for understanding the processes and the driving factors behind this rapidly changing coast. Great efforts have been devoted to map the changing shoreline of the Yellow River delta and explain such changes through remote sensing data. However, the temporal frequency of shoreline in the obtained datasets are generally not fine enough to reflect the detailed or subtly variable processes of shoreline retreat and advance. To overcome these limitations, we continuously monitored the dynamics of this shoreline using time series of Landsat data based on tidal-level calibration model and orthogonal-transect method. The Abrupt Change Value (ACV) results indicated that the retreat-advance patterns had a significant impact regardless of season or year. The Water-Sediment Regulation Scheme (WSRS) plays a dominant role in delivering river sediment discharge to the sea and has an impact on the annual average maximum ACV, especially at the mouth of the river. The positive relationship among the average ACV, runoff and sediment load are relatively obvious; however, we found that the Relative Exposure Index (REI) that measures wave energy was able to explain only approximately 20% of the variation in the data. Based on the abrupt change at the shoreline of the AYRD, river flow and time, we developed a binary regression model to calculate the critical sediment load and water discharge for maintaining the equilibrium of the active delta from 2002 to 2015. These values were approximately 0.48 × 108 t/yr and 144.37 × 108 m3/yr. If the current water and sediment proportions released from the Xiaolangdi Reservoir during the WSRS remain stable, the erosion-accretion patterns of the active delta will shift from rapid accretion to a dynamic balance.

Integrating Ecosystem Carbon Dynamics into State-and-Transition Simulation Models of Land Use/Land Cover Change

NASA Astrophysics Data System (ADS)

Sleeter, B. M.; Daniel, C.; Frid, L.; Fortin, M. J.

2016-12-01

State-and-transition simulation models (STSMs) provide a general approach for incorporating uncertainty into forecasts of landscape change. Using a Monte Carlo approach, STSMs generate spatially-explicit projections of the state of a landscape based upon probabilistic transitions defined between states. While STSMs are based on the basic principles of Markov chains, they have additional properties that make them applicable to a wide range of questions and types of landscapes. A current limitation of STSMs is that they are only able to track the fate of discrete state variables, such as land use/land cover (LULC) classes. There are some landscape modelling questions, however, for which continuous state variables - for example carbon biomass - are also required. Here we present a new approach for integrating continuous state variables into spatially-explicit STSMs. Specifically we allow any number of continuous state variables to be defined for each spatial cell in our simulations; the value of each continuous variable is then simulated forward in discrete time as a stochastic process based upon defined rates of change between variables. These rates can be defined as a function of the realized states and transitions of each cell in the STSM, thus providing a connection between the continuous variables and the dynamics of the landscape. We demonstrate this new approach by (1) developing a simple IPCC Tier 3 compliant model of ecosystem carbon biomass, where the continuous state variables are defined as terrestrial carbon biomass pools and the rates of change as carbon fluxes between pools, and (2) integrating this carbon model with an existing LULC change model for the state of Hawaii, USA.

Single step high-speed printing of continuous silver lines by laser-induced forward transfer

NASA Astrophysics Data System (ADS)

Puerto, D.; Biver, E.; Alloncle, A.-P.; Delaporte, Ph.

2016-06-01

The development of high-speed ink printing process by Laser-Induced Forward Transfer (LIFT) is of great interest for the printing community. To address the problems and the limitations of this process that have been previously identified, we have performed an experimental study on laser micro-printing of silver nanoparticle inks by LIFT and demonstrated for the first time the printing of continuous conductive lines in a single pass at velocities of 17 m/s using a 1 MHz repetition rate laser. We investigated the printing process by means of a time-resolved imaging technique to visualize the ejection dynamics of single and adjacent jets. The control of the donor film properties is of prime importance to achieve single step printing of continuous lines at high velocities. We use a 30 ps pulse duration laser with a wavelength of 343 nm and a repetition rate from 0.2 to 1 MHz. A galvanometric mirror head controls the distance between two consecutives jets by scanning the focused beam along an ink-coated donor substrate at different velocities. Droplets and lines of silver inks are laser-printed on glass and PET flexible substrates and we characterized their morphological quality by atomic force microscope (AFM) and optical microscope.

Will a category cue attract you? Motor output reveals dynamic competition across person construal.

PubMed

Freeman, Jonathan B; Ambady, Nalini; Rule, Nicholas O; Johnson, Kerri L

2008-11-01

People use social categories to perceive others, extracting category cues to glean membership. Growing evidence for continuous dynamics in real-time cognition suggests, contrary to prevailing social psychological accounts, that person construal may involve dynamic competition between simultaneously active representations. To test this, the authors examined social categorization in real-time by streaming the x, y coordinates of hand movements as participants categorized typical and atypical faces by sex. Though judgments of atypical targets were largely accurate, online motor output exhibited a continuous spatial attraction toward the opposite sex category, indicating dynamic competition between multiple social category alternatives. The authors offer a dynamic continuity account of social categorization and provide converging evidence across categorizations of real male and female faces (containing a typical or an atypical sex-specifying cue) and categorizations of computer-generated male and female faces (with subtly morphed sex-typical or sex-atypical features). In 3 studies, online motor output revealed continuous dynamics underlying person construal, in which multiple simultaneously and partially active category representations gradually cascade into social categorical judgments. Such evidence is challenging for discrete stage-based accounts. (c) 2008 APA, all rights reserved

Quantitative phase imaging characterization of tumor-associated blood vessel formation on a chip

NASA Astrophysics Data System (ADS)

Guo, Peng; Huang, Jing; Moses, Marsha A.

2018-02-01

Angiogenesis, the formation of new blood vessels from existing ones, is a biological process that has an essential role in solid tumor growth, development, and progression. Recent advances in Lab-on-a-Chip technology has created an opportunity for scientists to observe endothelial cell (EC) behaviors during the dynamic process of angiogenesis using a simple and economical in vitro platform that recapitulates in vivo blood vessel formation. Here, we use quantitative phase imaging (QPI) microscopy to continuously and non-invasively characterize the dynamic process of tumor cell-induced angiogenic sprout formation on a microfluidic chip. The live tumor cell-induced angiogenic sprouts are generated by multicellular endothelial sprouting into 3 dimensional (3D) Matrigel using human umbilical vein endothelial cells (HUVECs). By using QPI, we quantitatively measure a panel of cellular morphological and behavioral parameters of each individual EC participating in this sprouting. In this proof-of-principle study, we demonstrate that QPI is a powerful tool that can provide real-time quantitative analysis of biological processes in in vitro 3D biomimetic devices, which, in turn, can improve our understanding of the biology underlying functional tissue engineering.

Characterizing fluid dynamics in a bubble column aimed for the determination of reactive mass transfer

NASA Astrophysics Data System (ADS)

Kováts, Péter; Thévenin, Dominique; Zähringer, Katharina

2018-02-01

Bubble column reactors are multiphase reactors that are used in many process engineering applications. In these reactors a gas phase comes into contact with a fluid phase to initiate or support reactions. The transport process from the gas to the liquid phase is often the limiting factor. Characterizing this process is therefore essential for the optimization of multiphase reactors. For a better understanding of the transfer mechanisms and subsequent chemical reactions, a laboratory-scale bubble column reactor was investigated. First, to characterize the flow field in the reactor, two different methods have been applied. The shadowgraphy technique is used for the characterisation of the bubbles (bubble diameter, velocity, shape or position) for various process conditions. This technique is based on particle recognition with backlight illumination, combined with particle tracking velocimetry (PTV). The bubble trajectories in the column can also be obtained in this manner. Secondly, the liquid phase flow has been analysed by particle image velocimetry (PIV). The combination of both methods, delivering relevant information concerning disperse (bubbles) and continuous (liquid) phases, leads to a complete fluid dynamical characterization of the reactor, which is the pre-condition for the analysis of mass transfer between both phases.

Parametric identification of the process of preparing ceramic mixture as an object of control

NASA Astrophysics Data System (ADS)

Galitskov, Stanislav; Nazarov, Maxim; Galitskov, Konstantin

2017-10-01

Manufacture of ceramic materials and products largely depends on the preparation of clay raw materials. The main process here is the process of mixing, which in industrial production is mostly done in cross-compound clay mixers of continuous operation with steam humidification. The authors identified features of dynamics of this technological stage, which in itself is a non-linear control object with distributed parameters. When solving practical tasks for automation of a certain class of ceramic materials production it is important to make parametric identification of moving clay. In this paper the task is solved with the use of computational models, approximated to a particular section of a clay mixer along its length. The research introduces a methodology of computational experiments as applied to the designed computational model. Parametric identification of dynamic links was carried out according to transient characteristics. The experiments showed that the control object in question is to a great extent a non-stationary one. The obtained results are problematically oriented on synthesizing a multidimensional automatic control system for preparation of ceramic mixture with specified values of humidity and temperature exposed to the technological process of major disturbances.

A Stochastic Tick-Borne Disease Model: Exploring the Probability of Pathogen Persistence.

PubMed

Maliyoni, Milliward; Chirove, Faraimunashe; Gaff, Holly D; Govinder, Keshlan S

2017-09-01

We formulate and analyse a stochastic epidemic model for the transmission dynamics of a tick-borne disease in a single population using a continuous-time Markov chain approach. The stochastic model is based on an existing deterministic metapopulation tick-borne disease model. We compare the disease dynamics of the deterministic and stochastic models in order to determine the effect of randomness in tick-borne disease dynamics. The probability of disease extinction and that of a major outbreak are computed and approximated using the multitype Galton-Watson branching process and numerical simulations, respectively. Analytical and numerical results show some significant differences in model predictions between the stochastic and deterministic models. In particular, we find that a disease outbreak is more likely if the disease is introduced by infected deer as opposed to infected ticks. These insights demonstrate the importance of host movement in the expansion of tick-borne diseases into new geographic areas.

Computational fluid dynamics: Transition to design applications

NASA Technical Reports Server (NTRS)

Bradley, R. G.; Bhateley, I. C.; Howell, G. A.

1987-01-01

The development of aerospace vehicles, over the years, was an evolutionary process in which engineering progress in the aerospace community was based, generally, on prior experience and data bases obtained through wind tunnel and flight testing. Advances in the fundamental understanding of flow physics, wind tunnel and flight test capability, and mathematical insights into the governing flow equations were translated into improved air vehicle design. The modern day field of Computational Fluid Dynamics (CFD) is a continuation of the growth in analytical capability and the digital mathematics needed to solve the more rigorous form of the flow equations. Some of the technical and managerial challenges that result from rapidly developing CFD capabilites, some of the steps being taken by the Fort Worth Division of General Dynamics to meet these challenges, and some of the specific areas of application for high performance air vehicles are presented.

Transitioning NWChem to the Next Generation of Manycore Machines

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

Bylaska, Eric J.; Apra, Edoardo; Kowalski, Karol

The NorthWest Chemistry (NWChem) modeling software is a popular molecular chemistry simulation software that was designed from the start to work on massively parallel processing supercomputers[6, 28, 49]. It contains an umbrella of modules that today includes Self Consistent Field (SCF), second order Mller-Plesset perturbation theory (MP2), Coupled Cluster, multi-conguration selfconsistent eld (MCSCF), selected conguration interaction (CI), tensor contraction engine (TCE) many body methods, density functional theory (DFT), time-dependent density functional theory (TDDFT), real time time-dependent density functional theory, pseudopotential plane-wave density functional theory (PSPW), band structure (BAND), ab initio molecular dynamics, Car-Parrinello molecular dynamics, classical molecular dynamics (MD), QM/MM,more » AIMD/MM, GIAO NMR, COSMO, COSMO-SMD, and RISM solvation models, free energy simulations, reaction path optimization, parallel in time, among other capabilities[ 22]. Moreover new capabilities continue to be added with each new release.« less

Bridge helix bending promotes RNA polymerase II backtracking through a critical and conserved threonine residue

NASA Astrophysics Data System (ADS)

da, Lin-Tai; Pardo-Avila, Fátima; Xu, Liang; Silva, Daniel-Adriano; Zhang, Lu; Gao, Xin; Wang, Dong; Huang, Xuhui

2016-04-01

The dynamics of the RNA polymerase II (Pol II) backtracking process is poorly understood. We built a Markov State Model from extensive molecular dynamics simulations to identify metastable intermediate states and the dynamics of backtracking at atomistic detail. Our results reveal that Pol II backtracking occurs in a stepwise mode where two intermediate states are involved. We find that the continuous bending motion of the Bridge helix (BH) serves as a critical checkpoint, using the highly conserved BH residue T831 as a sensing probe for the 3'-terminal base paring of RNA:DNA hybrid. If the base pair is mismatched, BH bending can promote the RNA 3'-end nucleotide into a frayed state that further leads to the backtracked state. These computational observations are validated by site-directed mutagenesis and transcript cleavage assays, and provide insights into the key factors that regulate the preferences of the backward translocation.

Strength and failure of a damaged material

DOE PAGES

Cerreta, Ellen K.; Gray III, George T.; Trujillo, Carl P.; ...

2015-09-07

Under complex, dynamic loading conditions, damage can occur within a material. Should this damage not lead to catastrophic failure, the material can continue to sustain further loading. But, little is understood about how to represent the mechanical response of a material that has experienced dynamic loading leading to incipient damage. We examine this effect in copper. Copper is shock loaded to impart an incipient state of damage to the material. Thereafter compression and tensile specimens were sectioned from the dynamically damaged specimen to quantify the subsequent properties of the material in the region of intense incipient damage and in regionsmore » far from the damage. Finally, we observed that enhanced yield stresses result from the damaged material even over material, which has simply been shock loaded and not damaged. These results are rationalized in terms of stored plastic work due to the damage process.« less

Strength and failure of a damaged material

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

Cerreta, Ellen K.; Gray III, George T.; Trujillo, Carl P.

Under complex, dynamic loading conditions, damage can occur within a material. Should this damage not lead to catastrophic failure, the material can continue to sustain further loading. But, little is understood about how to represent the mechanical response of a material that has experienced dynamic loading leading to incipient damage. We examine this effect in copper. Copper is shock loaded to impart an incipient state of damage to the material. Thereafter compression and tensile specimens were sectioned from the dynamically damaged specimen to quantify the subsequent properties of the material in the region of intense incipient damage and in regionsmore » far from the damage. Finally, we observed that enhanced yield stresses result from the damaged material even over material, which has simply been shock loaded and not damaged. These results are rationalized in terms of stored plastic work due to the damage process.« less

Visualization of Notch signaling oscillation in cells and tissues.

PubMed

Shimojo, Hiromi; Harima, Yukiko; Kageyama, Ryoichiro

2014-01-01

The Notch signaling effectors Hes1 and Hes7 exhibit oscillatory expression with a period of about 2-3 h during embryogenesis. Hes1 oscillation is important for proliferation and differentiation of neural stem cells, whereas Hes7 oscillation regulates periodic formation of somites. Continuous expression of Hes1 and Hes7 inhibits these developmental processes. Thus, expression dynamics are very important for gene functions, but it is difficult to distinguish between oscillatory and persistent expression by conventional methods such as in situ hybridization and immunostaining. Here, we describe time-lapse imaging methods using destabilized luciferase reporters and a highly sensitive cooled charge-coupled device camera, which can monitor dynamic gene expression. Furthermore, the expression of two genes can be examined simultaneously by a dual reporter system using two-color luciferase reporters. Time-lapse imaging analyses reveal how dynamically gene expression changes in many biological events.

[Psychological features of the motivation component in the training of doctors in the system of postgraduate education].

PubMed

Koshova, Svitlana; Horachuk, Viktoriia; Pishchykov, Valerii

2018-01-01

Introduction: Тhe problem of motivating adult learning in postgraduate education has so far been the subject of study primarily in methodological and pedagogical studies. They focus on the analysis of the content side of the motivation of adult learning activities. As for the problem of the dynamics of motivation for adult learning activities, including for doctors in the system of postgraduate medical education with continuous professional development, it has not been sufficiently studied so far. The aim: This work is to analyze information and psychological features of the motivational sphere of doctors, which contribute to their successful training during continuous professional development in the system of postgraduate medical education. Materials and methods: In the work is used a range of methods: content analysis, bibliosemantic, systematic approach, analysis of products of activity. Review: At the present stage of social and economic transformations in Ukraine, the development of the general abilities of a person, his professional self-awareness, motivation for postgraduate education and obtaining a new specialization (E.О. Klimov, N.S. Glukhanyuk, I.V. Dubrovin, D.N. Zabrodin, T.V. Kudryavtsev, V.D. Shadrikov, etc.) The existing system of professional retraining does not pay enough attention to the study of conscious motives in adult learning activity. The practical relevance of this problem is determined, on the one hand, by the dynamic processes in the system of vocational training and retraining, the requirements for high efficiency of the results of the work of trained specialists. On the other hand, there is need to create conditions in the system of continuing education, the result of which is the effectiveness of adult learning activities. Conclusions: The study of the dynamics of motivation of adult learning activities is, in our opinion, relevant and has great theoretical as well as practical interest. It will allow to expand the idea of dynamics as the most important characteristic of motivation of educational activity. In addition, the knowledge of the features of the dynamics of the motivation of the learning activity of the adult factors that determine it will become in the hands of the practical teachers the lever through which it will be possible to control the motivation of adults during the educational activity with continuous postgraduate education.

Competitive exclusion over broad spatial extents is a slow process: Evidence and implications for species distribution modeling

USGS Publications Warehouse

Yackulic, Charles B.

2016-01-01

There is considerable debate about the role of competition in shaping species distributions over broad spatial extents. This debate has practical implications because predicting changes in species' geographic ranges in response to ongoing environmental change would be simpler if competition could be ignored. While this debate has been the subject of many reviews, recent literature has not addressed the rates of relevant processes. This omission is surprising in that ecologists hypothesized decades ago that regional competitive exclusion is a slow process. The goal of this review is to reassess the debate under the hypothesis that competitive exclusion over broad spatial extents is a slow process.Available evidence, including simulations presented for the first time here, suggests that competitive exclusion over broad spatial extents occurs slowly over temporal extents of many decades to millennia. Ecologists arguing against an important role for competition frequently study modern patterns and/or range dynamics over periods of decades, while much of the evidence for competition shaping geographic ranges at broad spatial extents comes from paleoecological studies over time scales of centuries or longer. If competition is slow, as evidence suggests, the geographic distributions of some, perhaps many species, would continue to change over time scales of decades to millennia, even if environmental conditions did not continue to change. If the distributions of competing species are at equilibrium it is possible to predict species distributions based on observed species–environment relationships. However, disequilibrium is widespread as a result of competition and many other processes. Studies whose goal is accurate predictions over intermediate time scales (decades to centuries) should focus on factors associated with range expansion (colonization) and loss (local extinction), as opposed to current patterns. In general, understanding of modern range dynamics would be enhanced by considering the rates of relevant processes.

Instrumentation for measuring dynamic spinal load moment exposures in the workplace.

PubMed

Marras, William S; Lavender, Steven A; Ferguson, Sue A; Splittstoesser, Riley E; Yang, Gang; Schabo, Pete

2010-02-01

Prior research has shown the load moment exposure to be one of the strongest predictors of low back disorder risk in manufacturing jobs. However, to extend these finding to the manual lifting and handling of materials in distribution centers, where the layout of the lifting task changes from one lift to the next and the lifts are highly dynamic, would be very challenging without an automated means of quantifying reach distances and item weights. The purpose of this paper is to describe the development and validation of automated instrumentation, the Moment Exposure Tracking System (METS), designed to capture the dynamic load moment exposures and spine postures used in distribution center jobs. This multiphase process started by obtaining baseline data describing the accuracy of existing manual methods for obtaining moment arms during the observation of dynamic lifting for the purposes of benchmarking the automated system. The process continued with the development and calibration of an ultrasonic system to track hand location and the development of load sensing handles that could be used to assess item weights. The final version of the system yielded an average absolute error in the load's moment arm of 4.1cm under the conditions of trunk flexion and load asymmetry. This compares well with the average absolute error of 10.9cm obtained using manual methods of measuring moment arms. With the item mass estimates being within half a kilogram, the instrumentation provides a reliable and valid means for assessing dynamic load moment exposures in dynamic distribution center lifting tasks.

Application of stochastic processes in random growth and evolutionary dynamics

NASA Astrophysics Data System (ADS)

Oikonomou, Panagiotis

We study the effect of power-law distributed randomness on the dynamical behavior of processes such as stochastic growth patterns and evolution. First, we examine the geometrical properties of random shapes produced by a generalized stochastic Loewner Evolution driven by a superposition of a Brownian motion and a stable Levy process. The situation is defined by the usual stochastic Loewner Evolution parameter, kappa, as well as alpha which defines the power-law tail of the stable Levy distribution. We show that the properties of these patterns change qualitatively and singularly at critical values of kappa and alpha. It is reasonable to call such changes "phase transitions". These transitions occur as kappa passes through four and as alpha passes through one. Numerical simulations are used to explore the global scaling behavior of these patterns in each "phase". We show both analytically and numerically that the growth continues indefinitely in the vertical direction for alpha greater than 1, goes as logarithmically with time for alpha equals to 1, and saturates for alpha smaller than 1. The probability density has two different scales corresponding to directions along and perpendicular to the boundary. Scaling functions for the probability density are given for various limiting cases. Second, we study the effect of the architecture of biological networks on their evolutionary dynamics. In recent years, studies of the architecture of large networks have unveiled a common topology, called scale-free, in which a majority of the elements are poorly connected except for a small fraction of highly connected components. We ask how networks with distinct topologies can evolve towards a pre-established target phenotype through a process of random mutations and selection. We use networks of Boolean components as a framework to model a large class of phenotypes. Within this approach, we find that homogeneous random networks and scale-free networks exhibit drastically different evolutionary paths. While homogeneous random networks accumulate neutral mutations and evolve by sparse punctuated steps, scale-free networks evolve rapidly and continuously towards the target phenotype. Moreover, we show that scale-free networks always evolve faster than homogeneous random networks; remarkably, this property does not depend on the precise value of the topological parameter. By contrast, homogeneous random networks require a specific tuning of their topological parameter in order to optimize their fitness. This model suggests that the evolutionary paths of biological networks, punctuated or continuous, may solely be determined by the network topology.

Chemistry, Dynamics, and Radiation of Ozone Loss: Airborne Measurements of OH, HO2, NO2, ClO, BrO, IO, ClONO2, BrONO2, ClOOCl, and H2O

NASA Technical Reports Server (NTRS)

Anderson, James G.

2005-01-01

This grant continued the research initially funded under NAG1-01095. This research addresses, through a combination of in situ and remote aircraft-borne instruments, the following scientific questions: Which mechanisms are responsible for the continuing erosion of ozone over midlatitudes of the Northern Hemisphere? Will the rapid loss of ozone over the Arctic in late winter continue to worsen over the next two decades? Are these large losses dynamically coupled to midlatitudes? Which mechanisms dictate the rate of exchange of material between the troposphere and stratosphere? How will these processes change in response to changes in climate? Will regional scale pollution episodes, that are emerging as predictable seasonal events, significantly affect the middle-to-upper troposphere chemical composition. If so, how will these changes alter the chemical composition of the middle world? What changes are predicted for the overworld? Why has the arctic stratosphere become colder in the late winter phase in recent years? Have increases in tropical upper troposphere temperatures increased the temperature gradient such as to change the trajectories of vertically propagating waves, thus reducing the effectiveness of the meridional circulation for transport of heat, momentum and ozone from the tropics to high latitudes?

The real-time link between person perception and action: Brain potential evidence for dynamic continuity

PubMed Central

Freeman, Jonathan B.; Ambady, Nalini; Midgley, Katherine J.; Holcomb, Phillip J.

2010-01-01

Using event-related potentials, we investigated how the brain extracts information from another’s face and translates it into relevant action in real-time. In Study 1, participants made between-hand sex categorizations of sex-typical and sex-atypical faces. Sex-atypical faces evoked negativity between 250-550 ms (N300/N400 effects), reflecting the integration of accumulating sex-category knowledge into a coherent sex-category interpretation. Additionally, the lateralized readiness potential (LRP) revealed that the motor cortex began preparing for a correct hand response while social category knowledge was still gradually evolving in parallel. In Study 2, participants made between-hand eye-color categorizations as part of go/no-go trials that were contingent on a target’s sex. On no-go trials, although the hand did not actually move, information about eye color partially prepared the motor cortex to move the hand before perception of sex had finalized. Together, these findings demonstrate the dynamic continuity between person perception and action, such that ongoing results from face processing are immediately and continuously cascaded into the motor system over time. The preparation of action begins based on tentative perceptions of another’s face before perceivers have finished interpreting what they just saw. PMID:20602284

The stochastic system approach for estimating dynamic treatments effect.

PubMed

Commenges, Daniel; Gégout-Petit, Anne

2015-10-01

The problem of assessing the effect of a treatment on a marker in observational studies raises the difficulty that attribution of the treatment may depend on the observed marker values. As an example, we focus on the analysis of the effect of a HAART on CD4 counts, where attribution of the treatment may depend on the observed marker values. This problem has been treated using marginal structural models relying on the counterfactual/potential response formalism. Another approach to causality is based on dynamical models, and causal influence has been formalized in the framework of the Doob-Meyer decomposition of stochastic processes. Causal inference however needs assumptions that we detail in this paper and we call this approach to causality the "stochastic system" approach. First we treat this problem in discrete time, then in continuous time. This approach allows incorporating biological knowledge naturally. When working in continuous time, the mechanistic approach involves distinguishing the model for the system and the model for the observations. Indeed, biological systems live in continuous time, and mechanisms can be expressed in the form of a system of differential equations, while observations are taken at discrete times. Inference in mechanistic models is challenging, particularly from a numerical point of view, but these models can yield much richer and reliable results.

The real-time link between person perception and action: brain potential evidence for dynamic continuity.

PubMed

Freeman, Jonathan B; Ambady, Nalini; Midgley, Katherine J; Holcomb, Phillip J

2011-01-01

Using event-related potentials, we investigated how the brain extracts information from another's face and translates it into relevant action in real time. In Study 1, participants made between-hand sex categorizations of sex-typical and sex-atypical faces. Sex-atypical faces evoked negativity between 250 and 550 ms (N300/N400 effects), reflecting the integration of accumulating sex-category knowledge into a coherent sex-category interpretation. Additionally, the lateralized readiness potential revealed that the motor cortex began preparing for a correct hand response while social category knowledge was still gradually evolving in parallel. In Study 2, participants made between-hand eye-color categorizations as part of go/no-go trials that were contingent on a target's sex. On no-go trials, although the hand did not actually move, information about eye color partially prepared the motor cortex to move the hand before perception of sex had finalized. Together, these findings demonstrate the dynamic continuity between person perception and action, such that ongoing results from face processing are immediately and continuously cascaded into the motor system over time. The preparation of action begins based on tentative perceptions of another's face before perceivers have finished interpreting what they just saw. © 2010 Psychology Press, an imprint of the Taylor & Francis Group, an Informa business

Aging and Emotion Recognition: Not Just a Losing Matter

PubMed Central

Sze, Jocelyn A.; Goodkind, Madeleine S.; Gyurak, Anett; Levenson, Robert W.

2013-01-01

Past studies on emotion recognition and aging have found evidence of age-related decline when emotion recognition was assessed by having participants detect single emotions depicted in static images of full or partial (e.g., eye region) faces. These tests afford good experimental control but do not capture the dynamic nature of real-world emotion recognition, which is often characterized by continuous emotional judgments and dynamic multi-modal stimuli. Research suggests that older adults often perform better under conditions that better mimic real-world social contexts. We assessed emotion recognition in young, middle-aged, and older adults using two traditional methods (single emotion judgments of static images of faces and eyes) and an additional method in which participants made continuous emotion judgments of dynamic, multi-modal stimuli (videotaped interactions between young, middle-aged, and older couples). Results revealed an age by test interaction. Largely consistent with prior research, we found some evidence that older adults performed worse than young adults when judging single emotions from images of faces (for sad and disgust faces only) and eyes (for older eyes only), with middle-aged adults falling in between. In contrast, older adults did better than young adults on the test involving continuous emotion judgments of dyadic interactions, with middle-aged adults falling in between. In tests in which target stimuli differed in age, emotion recognition was not facilitated by an age match between participant and target. These findings are discussed in terms of theoretical and methodological implications for the study of aging and emotional processing. PMID:22823183

Modelling the dynamics and hazards of explosive eruptions: Where we are now, and confronting the next challenges (Sergey Soloviev Medal Lecture)

NASA Astrophysics Data System (ADS)

Neri, Augusto

2017-04-01

Understanding of explosive eruption dynamics and assessment of their hazards continue to represent challenging issues to the present-day volcanology community. This is largely due to the complex and diverse nature of the phenomena, and the variability and unpredictability of volcanic processes. Nevertheless, important and continuing progress has been made in the last few decades in understanding fundamental processes and in forecasting the occurrences of these phenomena, thanks to significant advances in field, experimental and theoretical modeling investigations. For over four decades, for example, volcanologists have made major progress in the description of the nature of explosive eruptions, considerably aided by the development, improvement, and application of physical-mathematical models. Integral steady-state homogeneous flow models were first used to investigate the different controlling mechanisms and to infer the genesis and evolution of the phenomena. Through continuous improvements and quantum-leap developments, a variety of transient, 3D, multiphase flow models of volcanic phenomena now can implement state-of-the-art formulations of the underlying physics, new-generation analytical and experimental data, as well as high-performance computational techniques. These numerical models have proved to be able to provide key insights in the understanding of the dynamics of explosive eruptions (e.g. convective plumes, collapsing columns, pyroclastic density currents, short-lived explosions, etc.), as well as to represent a valuable tool in the quantification of potential eruptive scenarios and associated hazards. Simplified models based on a reduction of the system complexity have been also proved useful, combined with Monte Carlo and statistical methods, to generate quantitative probabilistic hazard maps at different space and time scales, some including the quantification of important sources of uncertainty. Nevertheless, the development of physical models able to accurately replicate, within acceptable statistical uncertainty, the evolution of explosive eruptions remains a challenging goal still to be achieved. Testing of the developed models versus large-scale experimental data and well-measured real events, real-time assimilation of observational data to forecast the process nature and evolution, as well as the quantification of the uncertainties affecting our system and modelling representations appear key next steps to further progress volcanological research and its essential contribution to the mitigation of volcanic risk.

Phase Transitions in Geomorphology

NASA Astrophysics Data System (ADS)

Ortiz, C. P.; Jerolmack, D. J.

2015-12-01

Landscapes are patterns in a dynamic steady-state, due to competing processes that smooth or sharpen features over large distances and times. Geomorphic transport laws have been developed to model the mass-flux due to different processes, but are unreasonably effective at recovering the scaling relations of landscape features. Using a continuum approximation to compare experimental landscapes and the observed landscapes of the earth, one finds they share similar morphodynamics despite a breakdown of classical dynamical similarity between the two. We propose the origin of this effectiveness is a different kind of dynamic similarity in the statistics of initiation and cessation of motion of groups of grains, which is common to disordered systems of grains under external driving. We will show how the existing data of sediment transport points to common signatures with dynamical phase transitions between "mobile" and "immobile" phases in other disordered systems, particularly granular materials, colloids, and foams. Viewing landscape evolution from the lens of non-equilibrium statistical physics of disordered systems leads to predictions that the transition of bulk measurements such as particle flux is continuous from one phase to another, that the collective nature of the particle dynamics leads to very slow aging of bulk properties, and that the dynamics are history-dependent. Recent results from sediment transport experiments support these predictions, suggesting that existing geomorphic transport laws may need to be replaced by a new generation of stochastic models with ingredients based on the physics of disordered phase transitions. We discuss possible strategies for extracting the necessary information to develop these models from measurements of geomorphic transport noise by connecting particle-scale collective dynamics and space-time fluctuations over landscape features.

Quantitative high-throughput population dynamics in continuous-culture by automated microscopy.

PubMed

Merritt, Jason; Kuehn, Seppe

2016-09-12

We present a high-throughput method to measure abundance dynamics in microbial communities sustained in continuous-culture. Our method uses custom epi-fluorescence microscopes to automatically image single cells drawn from a continuously-cultured population while precisely controlling culture conditions. For clonal populations of Escherichia coli our instrument reveals history-dependent resilience and growth rate dependent aggregation.