Application of dynamic milling in stainless steel processing

NASA Astrophysics Data System (ADS)

Shan, Wenju

2017-09-01

This paper mainly introduces the method of parameter setting for NC programming of stainless steel parts by dynamic milling. Stainless steel is of high plasticity and toughness, serious hard working, large cutting force, high temperature in cutting area and easy wear of tool. It is difficult to process material. Dynamic motion technology is the newest NC programming technology of Mastercam software. It is an advanced machining idea. The tool path generated by the dynamic motion technology is more smooth, more efficient and more stable in the machining process. Dynamic motion technology is very suitable for cutting hard machining materials.

Toward understanding dynamic annealing processes in irradiated ceramics

NASA Astrophysics Data System (ADS)

Myers, Michael Thomas

High energy particle irradiation inevitably generates defects in solids in the form of collision cascades. The ballistic formation and thermalization of cascades occur rapidly and are believed to be reasonably well understood. However, knowledge of the evolution of defects after damage cascade thermalization, referred to as dynamic annealing, is quite limited. Unraveling the mechanisms associated with dynamic an- nealing is crucial since such processes play an important role in the formation of stable post-irradiation disorder in ion-beam-processed semiconductors and determines the "radiation tolerance" of many nuclear materials. The purpose of this dissertation is to further our understanding of the processes involved in dynamic annealing. In order to achieve this, two main tasks are undertaken. First, the effects of dynamic annealing are investigated in ZnO, a technologically relevant material that exhibits very high dynamic defect annealing at room temper- ature. Such high dynamic annealing leads to unusual defect accumulation in heavy ion bombarded ZnO. Through this work, the puzzling features that were observed more than a decade ago in ion-channeling spectra have finally been explained. We show that the presence of a polar surface substantially alters damage accumulation. Non-polar surface terminations of ZnO are shown to exhibit enhanced dynamic an- nealing compared to polar surface terminated ZnO. Additionally, we demonstrate one method to reduce radiation damage in polar surface terminated ZnO by means of a surface modification. These results advance our efforts in the long-sought-after goal of understanding complex radiation damage processes in ceramics. Second, a pulsed-ion-beam method is developed and demonstrated in the case of Si as a prototypical non-metallic target. Such a method is shown to be a novel experimental technique for direct extraction of dynamic annealing parameters. The relaxation times and effective diffusion lengths of mobile defects

Dynamics of biomolecular processes

NASA Astrophysics Data System (ADS)

Behringer, Hans; Eichhorn, Ralf; Wallin, Stefan

2013-05-01

The last few years have seen enormous progress in the availability of computational resources, so that the size and complexity of physical systems that can be investigated numerically has increased substantially. The physical mechanisms behind the processes creating life, such as those in a living cell, are of foremost interest in biophysical research. A main challenge here is that complexity not only emerges from interactions of many macro-molecular compounds, but is already evident at the level of a single molecule. An exciting recent development in this context is, therefore, that detailed atomistic level characterization of large-scale dynamics of individual bio-macromolecules, such as proteins and DNA, is starting to become feasible in some cases. This has contributed to a better understanding of the molecular mechanisms of, e.g. protein folding and aggregation, as well as DNA dynamics. Nevertheless, simulations of the dynamical behaviour of complex multicomponent cellular processes at an all-atom level will remain beyond reach for the foreseeable future, and may not even be desirable. Ultimate understanding of many biological processes will require the development of methods targeting different time and length scales and, importantly, ways to bridge these in multiscale approaches. At the scientific programme Dynamics of biomolecular processes: from atomistic representations to coarse-grained models held between 27 February and 23 March 2012, and hosted by the Nordic Institute for Theoretical Physics, new modelling approaches and results for particular biological systems were presented and discussed. The programme was attended by around 30 scientists from the Nordic countries and elsewhere. It also included a PhD and postdoc 'winter school', where basic theoretical concepts and techniques of biomolecular modelling and simulations were presented. One to two decades ago, the biomolecular modelling field was dominated by two widely different and largely

Analysis of dynamic system response to product random processes

NASA Technical Reports Server (NTRS)

Sidwell, K.

1978-01-01

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

Multiscale analysis of information dynamics for linear multivariate processes.

PubMed

Faes, Luca; Montalto, Alessandro; Stramaglia, Sebastiano; Nollo, Giandomenico; Marinazzo, Daniele

2016-08-01

In the study of complex physical and physiological systems represented by multivariate time series, an issue of great interest is the description of the system dynamics over a range of different temporal scales. While information-theoretic approaches to the multiscale analysis of complex dynamics are being increasingly used, the theoretical properties of the applied measures are poorly understood. This study introduces for the first time a framework for the analytical computation of information dynamics for linear multivariate stochastic processes explored at different time scales. After showing that the multiscale processing of a vector autoregressive (VAR) process introduces a moving average (MA) component, we describe how to represent the resulting VARMA process using statespace (SS) models and how to exploit the SS model parameters to compute analytical measures of information storage and information transfer for the original and rescaled processes. The framework is then used to quantify multiscale information dynamics for simulated unidirectionally and bidirectionally coupled VAR processes, showing that rescaling may lead to insightful patterns of information storage and transfer but also to potentially misleading behaviors.

Autonomous Agents for Dynamic Process Planning in the Flexible Manufacturing System

NASA Astrophysics Data System (ADS)

Nik Nejad, Hossein Tehrani; Sugimura, Nobuhiro; Iwamura, Koji; Tanimizu, Yoshitaka

Rapid changes of market demands and pressures of competition require manufacturers to maintain highly flexible manufacturing systems to cope with a complex manufacturing environment. This paper deals with development of an agent-based architecture of dynamic systems for incremental process planning in the manufacturing systems. In consideration of alternative manufacturing processes and machine tools, the process plans and the schedules of the manufacturing resources are generated incrementally and dynamically. A negotiation protocol is discussed, in this paper, to generate suitable process plans for the target products real-timely and dynamically, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks discussed in the previous paper, and the suitable process plans are searched and generated to cope with both the dynamic changes of the product specifications and the disturbances of the manufacturing resources. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans in the dynamic manufacturing environment.

Biomolecular Modeling in a Process Dynamics and Control Course

ERIC Educational Resources Information Center

Gray, Jeffrey J.

2006-01-01

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

Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes

PubMed Central

Kuang, Zheng; Ji, Zhicheng

2018-01-01

Abstract Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes. PMID:29325176

Dynamic motif occupancy (DynaMO) analysis identifies transcription factors and their binding sites driving dynamic biological processes.

PubMed

Kuang, Zheng; Ji, Zhicheng; Boeke, Jef D; Ji, Hongkai

2018-01-09

Biological processes are usually associated with genome-wide remodeling of transcription driven by transcription factors (TFs). Identifying key TFs and their spatiotemporal binding patterns are indispensable to understanding how dynamic processes are programmed. However, most methods are designed to predict TF binding sites only. We present a computational method, dynamic motif occupancy analysis (DynaMO), to infer important TFs and their spatiotemporal binding activities in dynamic biological processes using chromatin profiling data from multiple biological conditions such as time-course histone modification ChIP-seq data. In the first step, DynaMO predicts TF binding sites with a random forests approach. Next and uniquely, DynaMO infers dynamic TF binding activities at predicted binding sites using their local chromatin profiles from multiple biological conditions. Another landmark of DynaMO is to identify key TFs in a dynamic process using a clustering and enrichment analysis of dynamic TF binding patterns. Application of DynaMO to the yeast ultradian cycle, mouse circadian clock and human neural differentiation exhibits its accuracy and versatility. We anticipate DynaMO will be generally useful for elucidating transcriptional programs in dynamic processes. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

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

PubMed

Hovick, Torre J; Allred, Brady W; Elmore, R Dwayne; Fuhlendorf, Samuel D; Hamilton, Robert G; Breland, Amber

2015-01-01

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

Hierarchical Heteroclinics in Dynamical Model of Cognitive Processes: Chunking

NASA Astrophysics Data System (ADS)

Afraimovich, Valentin S.; Young, Todd R.; Rabinovich, Mikhail I.

Combining the results of brain imaging and nonlinear dynamics provides a new hierarchical vision of brain network functionality that is helpful in understanding the relationship of the network to different mental tasks. Using these ideas it is possible to build adequate models for the description and prediction of different cognitive activities in which the number of variables is usually small enough for analysis. The dynamical images of different mental processes depend on their temporal organization and, as a rule, cannot be just simple attractors since cognition is characterized by transient dynamics. The mathematical image for a robust transient is a stable heteroclinic channel consisting of a chain of saddles connected by unstable separatrices. We focus here on hierarchical chunking dynamics that can represent several cognitive activities. Chunking is the dynamical phenomenon that means dividing a long information chain into shorter items. Chunking is known to be important in many processes of perception, learning, memory and cognition. We prove that in the phase space of the model that describes chunking there exists a new mathematical object — heteroclinic sequence of heteroclinic cycles — using the technique of slow-fast approximations. This new object serves as a skeleton of motions reflecting sequential features of hierarchical chunking dynamics and is an adequate image of the chunking processing.

Detection of microparticles in dynamic processes

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

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.

Developmental Dynamics of Emotion and Cognition Processes in Preschoolers

PubMed Central

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

2012-01-01

Dynamic relations during the preschool years across processes of control and understanding in the domains of emotion and cognition were examined. Participants were 263 children (42% non-white) and their mothers who were seen first when the children were 3 years old and again when they were 4. Results indicated dynamic dependence among the processes studied. Specifically, change in cognitive processes of control and understanding were dependent upon initial levels of the other processes. Changes in emotion control and understanding were not predicted by earlier performance in the other processes. Findings are discussed with regard to the constructs of control and understanding and the developmental interrelations among emotion and cognitive processes. PMID:22925076

Oculometric Assessment of Dynamic Visual Processing

NASA Technical Reports Server (NTRS)

Liston, Dorion Bryce; Stone, Lee

2014-01-01

Eye movements are the most frequent (3 per second), shortest-latency (150-250 ms), and biomechanically simplest (1 joint, no inertial complexities) voluntary motor behavior in primates, providing a model system to assess sensorimotor disturbances arising from trauma, fatigue, aging, or disease states (e.g., Diefendorf and Dodge, 1908). We developed a 15-minute behavioral tracking protocol consisting of randomized stepramp radial target motion to assess several aspects of the behavioral response to dynamic visual motion, including pursuit initiation, steadystate tracking, direction-tuning, and speed-tuning thresholds. This set of oculomotor metrics provide valid and reliable measures of dynamic visual performance (Stone and Krauzlis, 2003; Krukowski and Stone, 2005; Stone et al, 2009; Liston and Stone, 2014), and may prove to be a useful assessment tool for functional impairments of dynamic visual processing.

Fluid-Solid Interaction and Multiscale Dynamic Processes: Experimental Approach

NASA Astrophysics Data System (ADS)

Arciniega-Ceballos, Alejandra; Spina, Laura; Mendo-Pérez, Gerardo M.; Guzmán-Vázquez, Enrique; Scheu, Bettina; Sánchez-Sesma, Francisco J.; Dingwell, Donald B.

2017-04-01

The speed and the style of a pressure drop in fluid-filled conduits determines the dynamics of multiscale processes and the elastic interaction between the fluid and the confining solid. To observe this dynamics we performed experiments using fluid-filled transparent tubes (15-50 cm long, 2-4 cm diameter and 0.3-1 cm thickness) instrumented with high-dynamic piezoelectric sensors and filmed the evolution of these processes with a high speed camera. We analyzed the response of Newtonian fluids to slow and sudden pressure drops from 3 bar-10 MPa to ambient pressure. We used fluids with viscosities of mafic to intermediate silicate melts of 1 to 1000 Pa s and water. The processes observed are fluid mass expansion, fluid flow, jets, bubbles nucleation, growth, coalescence and collapse, degassing, foam building at the surface and vertical wagging. All these processes (in fine and coarse scales) are triggered by the pressure drop and are sequentially coupled in time while interacting with the solid. During slow decompression, the multiscale processes are recognized occurring within specific pressure intervals, and exhibit a localized distribution along the conduit. In this, degassing predominates near the surface and may present piston-like oscillations. In contrast, during sudden decompression the fluid-flow reaches higher velocities, the dynamics is dominated by a sequence of gas-packet pulses driving jets of the gas-fluid mixture. The evolution of this multiscale phenomenon generates complex non-stationary microseismic signals recorded along the conduit. We discuss distinctive characteristics of these signals depending on the decompression style and compare them with synthetics. These synthetics are obtained numerically under an averaging modeling scheme, that accounted for the stress-strain of the cyclic dynamic interaction between the fluid and the solid wall, assuming an incompressible and viscous fluid that flows while the elastic solid responds oscillating

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

PubMed

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Modeling Dynamic Regulatory Processes in Stroke.

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

McDermott, Jason E.; Jarman, Kenneth D.; Taylor, Ronald C.

2012-10-11

The ability to examine in silico the behavior of biological systems can greatly accelerate the pace of discovery in disease pathologies, such as stroke, where in vivo experimentation is lengthy and costly. In this paper we describe an approach to in silico examination of blood genomic responses to neuroprotective agents and subsequent stroke through the development of dynamic models of the regulatory processes observed in the experimental gene expression data. First, we identified functional gene clusters from these data. Next, we derived ordinary differential equations (ODEs) relating regulators and functional clusters from the data. These ODEs were used to developmore » dynamic models that simulate the expression of regulated functional clusters using system dynamics as the modeling paradigm. The dynamic model has the considerable advantage of only requiring an initial starting state, and does not require measurement of regulatory influences at each time point in order to make accurate predictions. The manipulation of input model parameters, such as changing the magnitude of gene expression, made it possible to assess the behavior of the networks through time under varying conditions. We report that an optimized dynamic model can provide accurate predictions of overall system behavior under several different preconditioning paradigms.« less

Information processing and dynamics in minimally cognitive agents.

PubMed

Beer, Randall D; Williams, Paul L

2015-01-01

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

Deciphering Dynamical Patterns of Growth Processes

ERIC Educational Resources Information Center

Kolakowska, A.

2009-01-01

Large systems of statistical physics often display properties that are independent of particulars that characterize their microscopic components. Universal dynamical patterns are manifested by the presence of scaling laws, which provides a common insight into governing physics of processes as vastly diverse as, e.g., growth of geological…

Programed dynamical ordering in self-organization processes of a nanocube: a molecular dynamics study.

PubMed

Harada, Ryuhei; Mashiko, Takako; Tachikawa, Masanori; Hiraoka, Shuichi; Shigeta, Yasuteru

2018-04-04

Self-organization processes of a gear-shaped amphiphile molecule (1) to form a hexameric structure (nanocube, 16) were inferred from sequential dissociation processes by using molecular dynamics (MD) simulations. Our MD study unveiled that programed dynamic ordering exists in the dissociation processes of 16. According to the dissociation processes, it is proposed that triple π-stacking among three 3-pyridyl groups and other weak molecular interactions such as CH-π and van der Waals interactions, some of which arise from the solvophobic effect, were sequentially formed in stable and transient oligomeric states in the self-organization processes, i.e.12, 13, 14, and 15. By subsequent analyses on structural stabilities, it was found that 13 and 14 are stable intermediate oligomers, whereas 12 and 15 are transient ones. Thus, the formation of 13 from three monomers and of 16 from 14 and two monomers via corresponding transients is time consuming in the self-assembly process.

Dynamic biogas upgrading based on the Sabatier process: thermodynamic and dynamic process simulation.

PubMed

Jürgensen, Lars; Ehimen, Ehiaze Augustine; Born, Jens; Holm-Nielsen, Jens Bo

2015-02-01

This study aimed to investigate the feasibility of substitute natural gas (SNG) generation using biogas from anaerobic digestion and hydrogen from renewable energy systems. Using thermodynamic equilibrium analysis, kinetic reactor modeling and transient simulation, an integrated approach for the operation of a biogas-based Sabatier process was put forward, which was then verified using a lab scale heterogenous methanation reactor. The process simulation using a kinetic reactor model demonstrated the feasibility of the production of SNG at gas grid standards using a single reactor setup. The Wobbe index, CO2 content and calorific value were found to be controllable by the H2/CO2 ratio fed the methanation reactor. An optimal H2/CO2 ratio of 3.45-3.7 was seen to result in a product gas with high calorific value and Wobbe index. The dynamic reactor simulation verified that the process start-up was feasible within several minutes to facilitate surplus electricity use from renewable energy systems. Copyright © 2014 Elsevier Ltd. All rights reserved.

Process Modeling and Dynamic Simulation for EAST Helium Refrigerator

NASA Astrophysics Data System (ADS)

Lu, Xiaofei; Fu, Peng; Zhuang, Ming; Qiu, Lilong; Hu, Liangbing

2016-06-01

In this paper, the process modeling and dynamic simulation for the EAST helium refrigerator has been completed. The cryogenic process model is described and the main components are customized in detail. The process model is controlled by the PLC simulator, and the realtime communication between the process model and the controllers is achieved by a customized interface. Validation of the process model has been confirmed based on EAST experimental data during the cool down process of 300-80 K. Simulation results indicate that this process simulator is able to reproduce dynamic behaviors of the EAST helium refrigerator very well for the operation of long pulsed plasma discharge. The cryogenic process simulator based on control architecture is available for operation optimization and control design of EAST cryogenic systems to cope with the long pulsed heat loads in the future. supported by National Natural Science Foundation of China (No. 51306195) and Key Laboratory of Cryogenics, Technical Institute of Physics and Chemistry, CAS (No. CRYO201408)

Traffic dynamics of carnival processions

NASA Astrophysics Data System (ADS)

Polichronidis, Petros; Wegerle, Dominik; Dieper, Alexander; Schreckenberg, Michael

2018-03-01

The traffic dynamics of processions are described in this study. GPS data from participating groups in the Cologne Rose Monday processions 2014–2017 are used to analyze the kinematic characteristics. The preparation of the measured data requires an adjustment by a specially adapted algorithm for the map matching method. A higher average velocity is observed for the last participant, the Carnival Prince, than for the leading participant of the parade. Based on the results of the data analysis, for the first time a model can be established for defilading parade groups as a modified Nagel-Schreckenberg model. This model can reproduce the observed characteristics in simulations. They can be explained partly by the constantly moving vehicle driving ahead of the parade leaving the pathway and partly due to a spatial contraction of the parade during the procession.

Group Dynamic Processes in Email Groups

ERIC Educational Resources Information Center

Alpay, Esat

2005-01-01

Discussion is given on the relevance of group dynamic processes in promoting decision-making in email discussion groups. General theories on social facilitation and social loafing are considered in the context of email groups, as well as the applicability of psychodynamic and interaction-based models. It is argued that such theories may indeed…

Dynamic Noise and its Role in Understanding Epidemiological Processes

NASA Astrophysics Data System (ADS)

Stollenwerk, Nico; Aguiar, Maíra

2010-09-01

We investigate the role of dynamic noise in understanding epidemiological systems, such as influenza or dengue fever by deriving stochastic ordinary differential equations from markov processes for discrete populations. This approach allows for an easy analysis of dynamical noise transitions between co-existing attractors.

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.

Electrophysiological spatiotemporal dynamics during implicit visual threat processing.

PubMed

DeLaRosa, Bambi L; Spence, Jeffrey S; Shakal, Scott K M; Motes, Michael A; Calley, Clifford S; Calley, Virginia I; Hart, John; Kraut, Michael A

2014-11-01

Numerous studies have found evidence for corticolimbic theta band electroencephalographic (EEG) oscillations in the neural processing of visual stimuli perceived as threatening. However, varying temporal and topographical patterns have emerged, possibly due to varying arousal levels of the stimuli. In addition, recent studies suggest neural oscillations in delta, theta, alpha, and beta-band frequencies play a functional role in information processing in the brain. This study implemented a data-driven PCA based analysis investigating the spatiotemporal dynamics of electroencephalographic delta, theta, alpha, and beta-band frequencies during an implicit visual threat processing task. While controlling for the arousal dimension (the intensity of emotional activation), we found several spatial and temporal differences for threatening compared to nonthreatening visual images. We detected an early posterior increase in theta power followed by a later frontal increase in theta power, greatest for the threatening condition. There was also a consistent left lateralized beta desynchronization for the threatening condition. Our results provide support for a dynamic corticolimbic network, with theta and beta band activity indexing processes pivotal in visual threat processing. Published by Elsevier Inc.

Qualitative dynamics semantics for SBGN process description.

PubMed

Rougny, Adrien; Froidevaux, Christine; Calzone, Laurence; Paulevé, Loïc

2016-06-16

Qualitative dynamics semantics provide a coarse-grain modeling of networks dynamics by abstracting away kinetic parameters. They allow to capture general features of systems dynamics, such as attractors or reachability properties, for which scalable analyses exist. The Systems Biology Graphical Notation Process Description language (SBGN-PD) has become a standard to represent reaction networks. However, no qualitative dynamics semantics taking into account all the main features available in SBGN-PD had been proposed so far. We propose two qualitative dynamics semantics for SBGN-PD reaction networks, namely the general semantics and the stories semantics, that we formalize using asynchronous automata networks. While the general semantics extends standard Boolean semantics of reaction networks by taking into account all the main features of SBGN-PD, the stories semantics allows to model several molecules of a network by a unique variable. The obtained qualitative models can be checked against dynamical properties and therefore validated with respect to biological knowledge. We apply our framework to reason on the qualitative dynamics of a large network (more than 200 nodes) modeling the regulation of the cell cycle by RB/E2F. The proposed semantics provide a direct formalization of SBGN-PD networks in dynamical qualitative models that can be further analyzed using standard tools for discrete models. The dynamics in stories semantics have a lower dimension than the general one and prune multiple behaviors (which can be considered as spurious) by enforcing the mutual exclusiveness between the activity of different nodes of a same story. Overall, the qualitative semantics for SBGN-PD allow to capture efficiently important dynamical features of reaction network models and can be exploited to further refine them.

Information Processing and Dynamics in Minimally Cognitive Agents

ERIC Educational Resources Information Center

Beer, Randall D.; Williams, Paul L.

2015-01-01

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

Identifying and tracking dynamic processes in social networks

NASA Astrophysics Data System (ADS)

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

2006-05-01

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

On Cognition, Structured Sequence Processing, and Adaptive Dynamical Systems

NASA Astrophysics Data System (ADS)

Petersson, Karl Magnus

2008-11-01

Cognitive neuroscience approaches the brain as a cognitive system: a system that functionally is conceptualized in terms of information processing. We outline some aspects of this concept and consider a physical system to be an information processing device when a subclass of its physical states can be viewed as representational/cognitive and transitions between these can be conceptualized as a process operating on these states by implementing operations on the corresponding representational structures. We identify a generic and fundamental problem in cognition: sequentially organized structured processing. Structured sequence processing provides the brain, in an essential sense, with its processing logic. In an approach addressing this problem, we illustrate how to integrate levels of analysis within a framework of adaptive dynamical systems. We note that the dynamical system framework lends itself to a description of asynchronous event-driven devices, which is likely to be important in cognition because the brain appears to be an asynchronous processing system. We use the human language faculty and natural language processing as a concrete example through out.

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

NASA Technical Reports Server (NTRS)

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

2012-01-01

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

Developmental Dynamics of Emotion and Cognition Processes in Preschoolers

ERIC Educational Resources Information Center

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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.

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

PubMed

Seidl, Roman

2015-12-01

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

Exogenic geomorphic processes dynamics at the Black Sea coast, Russia

NASA Astrophysics Data System (ADS)

Kuznetsova, Yulia; Tsvetkova, Daria

2017-04-01

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

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

PubMed

Liu, Ping; Li, Guodong; Liu, Xinggao

2015-09-01

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

Analytically Solvable Model of Spreading Dynamics with Non-Poissonian Processes

NASA Astrophysics Data System (ADS)

Jo, Hang-Hyun; Perotti, Juan I.; Kaski, Kimmo; Kertész, János

2014-01-01

Non-Poissonian bursty processes are ubiquitous in natural and social phenomena, yet little is known about their effects on the large-scale spreading dynamics. In order to characterize these effects, we devise an analytically solvable model of susceptible-infected spreading dynamics in infinite systems for arbitrary inter-event time distributions and for the whole time range. Our model is stationary from the beginning, and the role of the lower bound of inter-event times is explicitly considered. The exact solution shows that for early and intermediate times, the burstiness accelerates the spreading as compared to a Poisson-like process with the same mean and same lower bound of inter-event times. Such behavior is opposite for late-time dynamics in finite systems, where the power-law distribution of inter-event times results in a slower and algebraic convergence to a fully infected state in contrast to the exponential decay of the Poisson-like process. We also provide an intuitive argument for the exponent characterizing algebraic convergence.

Integrated Dynamic Process Planning and Scheduling in Flexible Manufacturing Systems via Autonomous Agents

NASA Astrophysics Data System (ADS)

Nejad, Hossein Tehrani Nik; Sugimura, Nobuhiro; Iwamura, Koji; Tanimizu, Yoshitaka

Process planning and scheduling are important manufacturing planning activities which deal with resource utilization and time span of manufacturing operations. The process plans and the schedules generated in the planning phase shall be modified in the execution phase due to the disturbances in the manufacturing systems. This paper deals with a multi-agent architecture of an integrated and dynamic system for process planning and scheduling for multi jobs. A negotiation protocol is discussed, in this paper, to generate the process plans and the schedules of the manufacturing resources and the individual jobs, dynamically and incrementally, based on the alternative manufacturing processes. The alternative manufacturing processes are presented by the process plan networks discussed in the previous paper, and the suitable process plans and schedules are searched and generated to cope with both the dynamic status and the disturbances of the manufacturing systems. We initiatively combine the heuristic search algorithms of the process plan networks with the negotiation protocols, in order to generate suitable process plans and schedules in the dynamic manufacturing environment. A simulation software has been developed to carry out case studies, aimed at verifying the performance of the proposed multi-agent architecture.

Quantifying chaotic dynamics from integrate-and-fire processes

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

Pavlov, A. N.; Saratov State Technical University, Politehnicheskaya Str. 77, 410054 Saratov; Pavlova, O. N.

2015-01-15

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

Impaired neural processing of dynamic faces in left-onset Parkinson's disease.

PubMed

Garrido-Vásquez, Patricia; Pell, Marc D; Paulmann, Silke; Sehm, Bernhard; Kotz, Sonja A

2016-02-01

Parkinson's disease (PD) affects patients beyond the motor domain. According to previous evidence, one mechanism that may be impaired in the disease is face processing. However, few studies have investigated this process at the neural level in PD. Moreover, research using dynamic facial displays rather than static pictures is scarce, but highly warranted due to the higher ecological validity of dynamic stimuli. In the present study we aimed to investigate how PD patients process emotional and non-emotional dynamic face stimuli at the neural level using event-related potentials. Since the literature has revealed a predominantly right-lateralized network for dynamic face processing, we divided the group into patients with left (LPD) and right (RPD) motor symptom onset (right versus left cerebral hemisphere predominantly affected, respectively). Participants watched short video clips of happy, angry, and neutral expressions and engaged in a shallow gender decision task in order to avoid confounds of task difficulty in the data. In line with our expectations, the LPD group showed significant face processing deficits compared to controls. While there were no group differences in early, sensory-driven processing (fronto-central N1 and posterior P1), the vertex positive potential, which is considered the fronto-central counterpart of the face-specific posterior N170 component, had a reduced amplitude and delayed latency in the LPD group. This may indicate disturbances of structural face processing in LPD. Furthermore, the effect was independent of the emotional content of the videos. In contrast, static facial identity recognition performance in LPD was not significantly different from controls, and comprehensive testing of cognitive functions did not reveal any deficits in this group. We therefore conclude that PD, and more specifically the predominant right-hemispheric affection in left-onset PD, is associated with impaired processing of dynamic facial expressions

Analysis of coherent dynamical processes through computer vision

NASA Astrophysics Data System (ADS)

Hack, M. J. Philipp

2016-11-01

Visualizations of turbulent boundary layers show an abundance of characteristic arc-shaped structures whose apparent similarity suggests a common origin in a coherent dynamical process. While the structures have been likened to the hairpin vortices observed in the late stages of transitional flow, a consistent description of the underlying mechanism has remained elusive. Detailed studies are complicated by the chaotic nature of turbulence which modulates each manifestation of the process and which renders the isolation of individual structures a challenging task. The present study applies methods from the field of computer vision to capture the time evolution of turbulent flow features and explore the associated physical mechanisms. The algorithm uses morphological operations to condense the structure of the turbulent flow field into a graph described by nodes and links. The low-dimensional geometric information is stored in a database and allows the identification and analysis of equivalent dynamical processes across multiple scales. The framework is not limited to turbulent boundary layers and can also be applied to different types of flows as well as problems from other fields of science.

Dynamic Monte Carlo description of thermal desorption processes

NASA Astrophysics Data System (ADS)

Weinketz, Sieghard

1994-07-01

The applicability of the dynamic Monte Carlo method of Fichthorn and Weinberg, in which the time evolution of a system is described in terms of the absolute number of different microscopic possible events and their associated transition rates, is discussed for the case of thermal desorption simulations. It is shown that the definition of the time increment at each successful event leads naturally to the macroscopic differential equation of desorption, in the case of simple first- and second-order processes in which the only possible events are desorption and diffusion. This equivalence is numerically demonstrated for a second-order case. In the sequence, the equivalence of this method with the Monte Carlo method of Sales and Zgrablich for more complex desorption processes, allowing for lateral interactions between adsorbates, is shown, even though the dynamic Monte Carlo method does not bear their limitation of a rapid surface diffusion condition, thus being able to describe a more complex ``kinetics'' of surface reactive processes, and therefore be applied to a wider class of phenomena, such as surface catalysis.

Nonlinear dynamics that appears in the dynamical model of drying process of a polymer solution coated on a flat substrate

NASA Astrophysics Data System (ADS)

Kagami, Hiroyuki

2007-01-01

We have proposed and modified the dynamical model of drying process of polymer solution coated on a flat substrate for flat polymer film fabrication and have presented the fruits through some meetings and so on. Though basic equations of the dynamical model have characteristic nonlinearity, character of the nonlinearity has not been studied enough yet. In this paper, at first, we derive nonlinear equations from the dynamical model of drying process of polymer solution. Then we introduce results of numerical simulations of the nonlinear equations and consider roles of various parameters. Some of them are indirectly concerned in strength of non-equilibriumity. Through this study, we approach essential qualities of nonlinearity in non-equilibrium process of drying process.

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

PubMed

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

2015-01-01

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

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

PubMed Central

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

2015-01-01

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

An organization of a digital subsystem for generating spacecraft timing and control signals

NASA Technical Reports Server (NTRS)

Perlman, M.

1972-01-01

A modulo-M counter (of clock pulses) is decomposed into parallel modulo-m sub i counters, where each m sub i is a prime power divisor of M. The modulo-p sub i counters are feedback shift registers which cycle through p sub i distinct states. By this organization, every possible nontrivial data frame subperiod and delayed subperiod may be derived. The number of clock pulses required to bring every modulo-p sub i counter to a respective designated state or count is determined by the Chinese remainder theorem. This corresponds to the solution of simultaneous congruences over relatively prime moduli.

Network Dynamics of Innovation Processes.

PubMed

Iacopini, Iacopo; Milojević, Staša; Latora, Vito

2018-01-26

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

Network Dynamics of Innovation Processes

NASA Astrophysics Data System (ADS)

Iacopini, Iacopo; Milojević, Staša; Latora, Vito

2018-01-01

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

Dynamic screening in a two-species asymmetric exclusion process

NASA Astrophysics Data System (ADS)

Kim, Kyung Hyuk; den Nijs, Marcel

2007-08-01

The dynamic scaling properties of the one-dimensional Burgers equation are expected to change with the inclusion of additional conserved degrees of freedom. We study this by means of one-dimensional (1D) driven lattice gas models that conserve both mass and momentum. The most elementary version of this is the Arndt-Heinzel-Rittenberg (AHR) process, which is usually presented as a two-species diffusion process, with particles of opposite charge hopping in opposite directions and with a variable passing probability. From the hydrodynamics perspective this can be viewed as two coupled Burgers equations, with the number of positive and negative momentum quanta individually conserved. We determine the dynamic scaling dimension of the AHR process from the time evolution of the two-point correlation functions, and find numerically that the dynamic critical exponent is consistent with simple Kardar-Parisi-Zhang- (KPZ) type scaling. We establish that this is the result of perfect screening of fluctuations in the stationary state. The two-point correlations decay exponentially in our simulations and in such a manner that in terms of quasiparticles, fluctuations fully screen each other at coarse grained length scales. We prove this screening rigorously using the analytic matrix product structure of the stationary state. The proof suggests the existence of a topological invariant. The process remains in the KPZ universality class but only in the sense of a factorization, as (KPZ)2 . The two Burgers equations decouple at large length scales due to the perfect screening.

Experimental design for dynamics identification of cellular processes.

PubMed

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

2014-03-01

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

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

PubMed

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

2017-03-01

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

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

NASA Technical Reports Server (NTRS)

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

2011-01-01

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

Dynamic information processing states revealed through neurocognitive models of object semantics

PubMed Central

Clarke, Alex

2015-01-01

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

Diagnosis of dynamic process over rainband of landfall typhoon

NASA Astrophysics Data System (ADS)

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

2010-07-01

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

Multidimensional biochemical information processing of dynamical patterns

NASA Astrophysics Data System (ADS)

Hasegawa, Yoshihiko

2018-02-01

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

Multidimensional biochemical information processing of dynamical patterns.

PubMed

Hasegawa, Yoshihiko

2018-02-01

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

All-optical signal processing using dynamic Brillouin gratings

PubMed Central

Santagiustina, Marco; Chin, Sanghoon; Primerov, Nicolay; Ursini, Leonora; Thévenaz, Luc

2013-01-01

The manipulation of dynamic Brillouin gratings in optical fibers is demonstrated to be an extremely flexible technique to achieve, with a single experimental setup, several all-optical signal processing functions. In particular, all-optical time differentiation, time integration and true time reversal are theoretically predicted, and then numerically and experimentally demonstrated. The technique can be exploited to process both photonic and ultra-wide band microwave signals, so enabling many applications in photonics and in radio science. PMID:23549159

Applying Parallel Processing Techniques to Tether Dynamics Simulation

NASA Technical Reports Server (NTRS)

Wells, B. Earl

1996-01-01

The focus of this research has been to determine the effectiveness of applying parallel processing techniques to a sizable real-world problem, the simulation of the dynamics associated with a tether which connects two objects in low earth orbit, and to explore the degree to which the parallelization process can be automated through the creation of new software tools. The goal has been to utilize this specific application problem as a base to develop more generally applicable techniques.

Dynamic metrology and data processing for precision freeform optics fabrication and testing

NASA Astrophysics Data System (ADS)

Aftab, Maham; Trumper, Isaac; Huang, Lei; Choi, Heejoo; Zhao, Wenchuan; Graves, Logan; Oh, Chang Jin; Kim, Dae Wook

2017-06-01

Dynamic metrology holds the key to overcoming several challenging limitations of conventional optical metrology, especially with regards to precision freeform optical elements. We present two dynamic metrology systems: 1) adaptive interferometric null testing; and 2) instantaneous phase shifting deflectometry, along with an overview of a gradient data processing and surface reconstruction technique. The adaptive null testing method, utilizing a deformable mirror, adopts a stochastic parallel gradient descent search algorithm in order to dynamically create a null testing condition for unknown freeform optics. The single-shot deflectometry system implemented on an iPhone uses a multiplexed display pattern to enable dynamic measurements of time-varying optical components or optics in vibration. Experimental data, measurement accuracy / precision, and data processing algorithms are discussed.

Dynamic force signal processing system of a robot manipulator

NASA Technical Reports Server (NTRS)

Uchiyama, M.; Kitagaki, K.; Hakomori, K.

1987-01-01

If dynamic noises such as those caused by the inertia forces of the hand can be eliminated from the signal of the force sensor installed on the wrist of the robot manipulator and if the necessary information of the external force can be detected with high sensitivity and high accuracy, a fine force feedback control for robots used in high speed and various fields will be possible. As the dynamic force sensing system, an external force estimate method with the extended Kalman filter is suggested and simulations and tests for a one axis force were performed. Later a dynamic signal processing system of six axes was composed and tested. The results are presented.

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

Dynamic evolution of interface roughness during friction and wear processes.

PubMed

Kubiak, K J; Bigerelle, M; Mathia, T G; Dubois, A; Dubar, L

2014-01-01

Dynamic evolution of surface roughness and influence of initial roughness (S(a) = 0.282-6.73 µm) during friction and wear processes has been analyzed experimentally. The mirror polished and rough surfaces (28 samples in total) have been prepared by surface polishing on Ti-6Al-4V and AISI 1045 samples. Friction and wear have been tested in classical sphere/plane configuration using linear reciprocating tribometer with very small displacement from 130 to 200 µm. After an initial period of rapid degradation, dynamic evolution of surface roughness converges to certain level specific to a given tribosystem. However, roughness at such dynamic interface is still increasing and analysis of initial roughness influence revealed that to certain extent, a rheology effect of interface can be observed and dynamic evolution of roughness will depend on initial condition and history of interface roughness evolution. Multiscale analysis shows that morphology created in wear process is composed from nano, micro, and macro scale roughness. Therefore, mechanical parts working under very severe contact conditions, like rotor/blade contact, screws, clutch, etc. with poor initial surface finishing are susceptible to have much shorter lifetime than a quality finished parts. © Wiley Periodicals, Inc.

Complex Processes from Dynamical Architectures with Time-Scale Hierarchy

PubMed Central

Perdikis, Dionysios; Huys, Raoul; Jirsa, Viktor

2011-01-01

The idea that complex motor, perceptual, and cognitive behaviors are composed of smaller units, which are somehow brought into a meaningful relation, permeates the biological and life sciences. However, no principled framework defining the constituent elementary processes has been developed to this date. Consequently, functional configurations (or architectures) relating elementary processes and external influences are mostly piecemeal formulations suitable to particular instances only. Here, we develop a general dynamical framework for distinct functional architectures characterized by the time-scale separation of their constituents and evaluate their efficiency. Thereto, we build on the (phase) flow of a system, which prescribes the temporal evolution of its state variables. The phase flow topology allows for the unambiguous classification of qualitatively distinct processes, which we consider to represent the functional units or modes within the dynamical architecture. Using the example of a composite movement we illustrate how different architectures can be characterized by their degree of time scale separation between the internal elements of the architecture (i.e. the functional modes) and external interventions. We reveal a tradeoff of the interactions between internal and external influences, which offers a theoretical justification for the efficient composition of complex processes out of non-trivial elementary processes or functional modes. PMID:21347363

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.

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

ERIC Educational Resources Information Center

Brymer, Eric; Davids, Keith

2014-01-01

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

Dynamic Facial Expressions Prime the Processing of Emotional Prosody.

PubMed

Garrido-Vásquez, Patricia; Pell, Marc D; Paulmann, Silke; Kotz, Sonja A

2018-01-01

Evidence suggests that emotion is represented supramodally in the human brain. Emotional facial expressions, which often precede vocally expressed emotion in real life, can modulate event-related potentials (N100 and P200) during emotional prosody processing. To investigate these cross-modal emotional interactions, two lines of research have been put forward: cross-modal integration and cross-modal priming. In cross-modal integration studies, visual and auditory channels are temporally aligned, while in priming studies they are presented consecutively. Here we used cross-modal emotional priming to study the interaction of dynamic visual and auditory emotional information. Specifically, we presented dynamic facial expressions (angry, happy, neutral) as primes and emotionally-intoned pseudo-speech sentences (angry, happy) as targets. We were interested in how prime-target congruency would affect early auditory event-related potentials, i.e., N100 and P200, in order to shed more light on how dynamic facial information is used in cross-modal emotional prediction. Results showed enhanced N100 amplitudes for incongruently primed compared to congruently and neutrally primed emotional prosody, while the latter two conditions did not significantly differ. However, N100 peak latency was significantly delayed in the neutral condition compared to the other two conditions. Source reconstruction revealed that the right parahippocampal gyrus was activated in incongruent compared to congruent trials in the N100 time window. No significant ERP effects were observed in the P200 range. Our results indicate that dynamic facial expressions influence vocal emotion processing at an early point in time, and that an emotional mismatch between a facial expression and its ensuing vocal emotional signal induces additional processing costs in the brain, potentially because the cross-modal emotional prediction mechanism is violated in case of emotional prime-target incongruency.

DDS-Suite - A Dynamic Data Acquisition, Processing, and Analysis System for Wind Tunnel Testing

NASA Technical Reports Server (NTRS)

Burnside, Jathan J.

2012-01-01

Wind Tunnels have optimized their steady-state data systems for acquisition and analysis and even implemented large dynamic-data acquisition systems, however development of near real-time processing and analysis tools for dynamic-data have lagged. DDS-Suite is a set of tools used to acquire, process, and analyze large amounts of dynamic data. Each phase of the testing process: acquisition, processing, and analysis are handled by separate components so that bottlenecks in one phase of the process do not affect the other, leading to a robust system. DDS-Suite is capable of acquiring 672 channels of dynamic data at rate of 275 MB / s. More than 300 channels of the system use 24-bit analog-to-digital cards and are capable of producing data with less than 0.01 of phase difference at 1 kHz. System architecture, design philosophy, and examples of use during NASA Constellation and Fundamental Aerodynamic tests are discussed.

Fractal dimension and nonlinear dynamical processes

NASA Astrophysics Data System (ADS)

McCarty, Robert C.; Lindley, John P.

1993-11-01

Mandelbrot, Falconer and others have demonstrated the existence of dimensionally invariant geometrical properties of non-linear dynamical processes known as fractals. Barnsley defines fractal geometry as an extension of classical geometry. Such an extension, however, is not mathematically trivial Of specific interest to those engaged in signal processing is the potential use of fractal geometry to facilitate the analysis of non-linear signal processes often referred to as non-linear time series. Fractal geometry has been used in the modeling of non- linear time series represented by radar signals in the presence of ground clutter or interference generated by spatially distributed reflections around the target or a radar system. It was recognized by Mandelbrot that the fractal geometries represented by man-made objects had different dimensions than the geometries of the familiar objects that abound in nature such as leaves, clouds, ferns, trees, etc. The invariant dimensional property of non-linear processes suggests that in the case of acoustic signals (active or passive) generated within a dispersive medium such as the ocean environment, there exists much rich structure that will aid in the detection and classification of various objects, man-made or natural, within the medium.

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

PubMed

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

2011-09-01

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

Classical molecular dynamics simulation of electronically non-adiabatic processes.

PubMed

Miller, William H; Cotton, Stephen J

2016-12-22

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

Absolute phase estimation: adaptive local denoising and global unwrapping.

PubMed

Bioucas-Dias, Jose; Katkovnik, Vladimir; Astola, Jaakko; Egiazarian, Karen

2008-10-10

The paper attacks absolute phase estimation with a two-step approach: the first step applies an adaptive local denoising scheme to the modulo-2 pi noisy phase; the second step applies a robust phase unwrapping algorithm to the denoised modulo-2 pi phase obtained in the first step. The adaptive local modulo-2 pi phase denoising is a new algorithm based on local polynomial approximations. The zero-order and the first-order approximations of the phase are calculated in sliding windows of varying size. The zero-order approximation is used for pointwise adaptive window size selection, whereas the first-order approximation is used to filter the phase in the obtained windows. For phase unwrapping, we apply the recently introduced robust (in the sense of discontinuity preserving) PUMA unwrapping algorithm [IEEE Trans. Image Process.16, 698 (2007)] to the denoised wrapped phase. Simulations give evidence that the proposed algorithm yields state-of-the-art performance, enabling strong noise attenuation while preserving image details. (c) 2008 Optical Society of America

Laser-enhanced dynamics in molecular rate processes

NASA Technical Reports Server (NTRS)

George, T. F.; Zimmerman, I. H.; Devries, P. L.; Yuan, J.-M.; Lam, K.-S.; Bellum, J. C.; Lee, H.-W.; Slutsky, M. S.

1978-01-01

The present discussion deals with some theoretical aspects associated with the description of molecular rate processes in the presence of intense laser radiation, where the radiation actually interacts with the molecular dynamics. Whereas for weak and even moderately intense radiation, the absorption and stimulated emission of photons by a molecular system can be described by perturbative methods, for intense radiation, perturbation theory is usually not adequate. Limiting the analysis to the gas phase, an attempt is made to describe nonperturbative approaches applicable to the description of such processes (in the presence of intense laser radiation) as electronic energy transfer in molecular (in particular atom-atom) collisions; collision-induced ionization and emission; and unimolecular dissociation.

Dynamic Processes in Nanostructured Crystals Under Ion Irradiation

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Forest forming process and dynamic vegetation models under global change

Treesearch

A. Shvidenko; E. Gustafson

2009-01-01

The paper analyzes mathematical models that are used to project the dynamics of forest ecosystems on different spatial and temporal scales. Landscape disturbance and succession models (LDSMs) are of a particular interest for studying the forest forming process in Northern Eurasia. They have a solid empirical background and are able to model ecological processes under...

Dynamic response analysis of structure under time-variant interval process model

NASA Astrophysics Data System (ADS)

Xia, Baizhan; Qin, Yuan; Yu, Dejie; Jiang, Chao

2016-10-01

Due to the aggressiveness of the environmental factor, the variation of the dynamic load, the degeneration of the material property and the wear of the machine surface, parameters related with the structure are distinctly time-variant. Typical model for time-variant uncertainties is the random process model which is constructed on the basis of a large number of samples. In this work, we propose a time-variant interval process model which can be effectively used to deal with time-variant uncertainties with limit information. And then two methods are presented for the dynamic response analysis of the structure under the time-variant interval process model. The first one is the direct Monte Carlo method (DMCM) whose computational burden is relative high. The second one is the Monte Carlo method based on the Chebyshev polynomial expansion (MCM-CPE) whose computational efficiency is high. In MCM-CPE, the dynamic response of the structure is approximated by the Chebyshev polynomials which can be efficiently calculated, and then the variational range of the dynamic response is estimated according to the samples yielded by the Monte Carlo method. To solve the dependency phenomenon of the interval operation, the affine arithmetic is integrated into the Chebyshev polynomial expansion. The computational effectiveness and efficiency of MCM-CPE is verified by two numerical examples, including a spring-mass-damper system and a shell structure.

Towards A Synthesis Of Land Dynamics And Hydrological Processes Across Central Asia

NASA Astrophysics Data System (ADS)

Sokolik, I. N.; Tatarskii, V.; Shiklomanov, A. I.; Henebry, G. M.; de Beurs, K.; Laruelle, M.

2016-12-01

We present results from an ongoing project that aims to synthesize land dynamics, hydrological processes, and socio-economic changes across the five countries of Central Asia. We have developed a fully coupled model that takes into account the reconstructed land cover and land use dynamics to simulate dust emissions. A comparable model has been developed to model smoke emissions from wildfires. Both models incorporate land dynamics explicitly. We also present a characterization of land surface change based on a suite of MODIS products including vegetation indices, evapotranspiration, land surface temperature, and albedo. These results are connected with ongoing land privatization reforms that different across the region. We also present a regional analysis of water resources, including the significant impact of using surface water for irrigation in an arid landscape. We applied the University of New Hampshire hydrological model to understand the consequences of changes in climate, water, and land use on regional hydrological processes and water use. Water security and its dynamic have been estimated through an analysis of multiple indices and variables characterizing the water availability and water use. The economic consequences of the water privatization processes will be presented.

The golden ratio and Loshu-Fibonacci Diagram: novel research view on relationship of Chinese medicine and modern biology.

PubMed

Chen, Zhao-xue; Huang, Yun-kun; Sun, Ying

2014-02-01

Associating geometric arrangements of 9 Loshu numbers modulo 5, investigating property of golden rectangles and characteristics of Fibonacci sequence modulo 10 as well as the two subsequences of its modular sequence by modulo 5, the Loshu-Fibonacci Diagram is created based on strict logical deduction in this paper, which can disclose inherent relationship among Taiji sign, Loshu and Fibonacci sequence modulo 10 perfectly and unite such key ideas of holism, symmetry, holographic thought and yin-yang balance pursuit from Chinese medicine as a whole. Based on further analysis and reasoning, the authors discover that taking the golden ratio and Loshu-Fibonacci Diagram as a link, there is profound and universal association existing between researches of Chinese medicine and modern biology.

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

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

Li, Minjing; Gao, Yuqian; Qian, Wei-Jun

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

Emotions are emergent processes: they require a dynamic computational architecture

PubMed Central

Scherer, Klaus R.

2009-01-01

Emotion is a cultural and psychobiological adaptation mechanism which allows each individual to react flexibly and dynamically to environmental contingencies. From this claim flows a description of the elements theoretically needed to construct a virtual agent with the ability to display human-like emotions and to respond appropriately to human emotional expression. This article offers a brief survey of the desirable features of emotion theories that make them ideal blueprints for agent models. In particular, the component process model of emotion is described, a theory which postulates emotion-antecedent appraisal on different levels of processing that drive response system patterning predictions. In conclusion, investing seriously in emergent computational modelling of emotion using a nonlinear dynamic systems approach is suggested. PMID:19884141

Microscopic information processing and communication in crowd dynamics

NASA Astrophysics Data System (ADS)

Henein, Colin Marc; White, Tony

2010-11-01

Due, perhaps, to the historical division of crowd dynamics research into psychological and engineering approaches, microscopic crowd models have tended toward modelling simple interchangeable particles with an emphasis on the simulation of physical factors. Despite the fact that people have complex (non-panic) behaviours in crowd disasters, important human factors in crowd dynamics such as information discovery and processing, changing goals and communication have not yet been well integrated at the microscopic level. We use our Microscopic Human Factors methodology to fuse a microscopic simulation of these human factors with a popular microscopic crowd model. By tightly integrating human factors with the existing model we can study the effects on the physical domain (movement, force and crowd safety) when human behaviour (information processing and communication) is introduced. In a large-room egress scenario with ample exits, information discovery and processing yields a crowd of non-interchangeable individuals who, despite close proximity, have different goals due to their different beliefs. This crowd heterogeneity leads to complex inter-particle interactions such as jamming transitions in open space; at high crowd energies, we found a freezing by heating effect (reminiscent of the disaster at Central Lenin Stadium in 1982) in which a barrier formation of naïve individuals trying to reach blocked exits prevented knowledgeable ones from exiting. Communication, when introduced, reduced this barrier formation, increasing both exit rates and crowd safety.

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

PubMed

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

2015-04-01

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

Identification of FOPDT and SOPDT process dynamics using closed loop test.

PubMed

Bajarangbali, Raghunath; Majhi, Somanath; Pandey, Saurabh

2014-07-01

In this paper, identification of stable and unstable first order, second order overdamped and underdamped process dynamics with time delay is presented. Relay with hysteresis is used to induce a limit cycle output and using this information, unknown process model parameters are estimated. State space based generalized analytical expressions are derived to achieve accurate results. To show the performance of the proposed method expressions are also derived for systems with a zero. In real time systems, measurement noise is an important issue during identification of process dynamics. A relay with hysteresis reduces the effect of measurement noise, in addition a new multiloop control strategy is proposed to recover the original limit cycle. Simulation results are included to validate the effectiveness of the proposed method. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

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

ERIC Educational Resources Information Center

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

1983-01-01

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

Corrosion And Thermal Processing In Cold Gas Dynamic Spray Deposited Austenitic Stainless Steel Coatings

DTIC Science & Technology

2016-06-01

Novosibirsk during the 1980s [14]. In this process, particles of the coating material are accelerated by entrainment in a supersonic jet of gas ...THERMAL PROCESSING IN COLD GAS DYNAMIC SPRAY DEPOSITED AUSTENITIC STAINLESS STEEL COATINGS by John A Luhn June 2016 Thesis Advisor: Sarath...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE CORROSION AND THERMAL PROCESSING IN COLD GAS DYNAMIC SPRAY DEPOSITED AUSTENITIC

Dynamic Stimuli And Active Processing In Human Visual Perception

NASA Astrophysics Data System (ADS)

Haber, Ralph N.

1990-03-01

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

A dynamic dual process model of risky decision making.

PubMed

Diederich, Adele; Trueblood, Jennifer S

2018-03-01

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

Free energy reconstruction from steered dynamics without post-processing

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

Athenes, Manuel, E-mail: Manuel.Athenes@cea.f; Condensed Matter and Materials Division, Physics and Life Sciences Directorate, LLNL, Livermore, CA 94551; Marinica, Mihai-Cosmin

2010-09-20

Various methods achieving importance sampling in ensembles of nonequilibrium trajectories enable one to estimate free energy differences and, by maximum-likelihood post-processing, to reconstruct free energy landscapes. Here, based on Bayes theorem, we propose a more direct method in which a posterior likelihood function is used both to construct the steered dynamics and to infer the contribution to equilibrium of all the sampled states. The method is implemented with two steering schedules. First, using non-autonomous steering, we calculate the migration barrier of the vacancy in Fe-{alpha}. Second, using an autonomous scheduling related to metadynamics and equivalent to temperature-accelerated molecular dynamics, wemore » accurately reconstruct the two-dimensional free energy landscape of the 38-atom Lennard-Jones cluster as a function of an orientational bond-order parameter and energy, down to the solid-solid structural transition temperature of the cluster and without maximum-likelihood post-processing.« less

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

PubMed

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

2009-12-01

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

State machine analysis of sensor data from dynamic processes

DOEpatents

Cook, William R.; Brabson, John M.; Deland, Sharon M.

2003-12-23

A state machine model analyzes sensor data from dynamic processes at a facility to identify the actual processes that were performed at the facility during a period of interest for the purpose of remote facility inspection. An inspector can further input the expected operations into the state machine model and compare the expected, or declared, processes to the actual processes to identify undeclared processes at the facility. The state machine analysis enables the generation of knowledge about the state of the facility at all levels, from location of physical objects to complex operational concepts. Therefore, the state machine method and apparatus may benefit any agency or business with sensored facilities that stores or manipulates expensive, dangerous, or controlled materials or information.

Unpacking team process dynamics and emergent phenomena: Challenges, conceptual advances, and innovative methods.

PubMed

Kozlowski, Steve W J; Chao, Georgia T

2018-01-01

Psychologists have studied small-group and team effectiveness for decades, and although there has been considerable progress, there remain significant challenges. Meta-analyses and systematic research have provided solid evidence for core team cognitive, motivational, affective, and behavioral processes that contribute to team effectiveness and empirical support for interventions that enhance team processes (e.g., team design, composition, training, and leadership); there has been substantial evidence for a science of team effectiveness. Nonetheless, there have also been concerns that team processes, which are inherently dynamic, have primarily been assessed as static constructs. Team-level processes and outcomes are multilevel phenomena that emerge, bottom-up from the interactions among team members over time, under the shifting demands of a work context. Thus, theoretical development that appropriately conceptualizes the multiple levels, process dynamics, and emergence of team phenomena over time are essential to advance understanding. Moreover, these conceptual advances necessitate innovative research methodologies to better capture team process dynamics. We explicate this foundation and then describe 2 promising streams of scientific inquiry-team interaction sensors and computational modeling-that are advancing new, unobtrusive measurement techniques and process-oriented research methods focused on understanding the dynamics of cohesion and cognition in teamwork. These are distinct lines of research, each endeavoring to advance the science, but doing so through the development of very different methodologies. We close by discussing the near-term research challenges and the potential long-term evolution of these innovative methods, with an eye toward the future for process-oriented theory and research on team effectiveness. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Scale-Free Neural and Physiological Dynamics in Naturalistic Stimuli Processing

PubMed Central

Lin, Amy

2016-01-01

Abstract Neural activity recorded at multiple spatiotemporal scales is dominated by arrhythmic fluctuations without a characteristic temporal periodicity. Such activity often exhibits a 1/f-type power spectrum, in which power falls off with increasing frequency following a power-law function: P(f)∝1/fβ, which is indicative of scale-free dynamics. Two extensively studied forms of scale-free neural dynamics in the human brain are slow cortical potentials (SCPs)—the low-frequency (<5 Hz) component of brain field potentials—and the amplitude fluctuations of α oscillations, both of which have been shown to carry important functional roles. In addition, scale-free dynamics characterize normal human physiology such as heartbeat dynamics. However, the exact relationships among these scale-free neural and physiological dynamics remain unclear. We recorded simultaneous magnetoencephalography and electrocardiography in healthy subjects in the resting state and while performing a discrimination task on scale-free dynamical auditory stimuli that followed different scale-free statistics. We observed that long-range temporal correlation (captured by the power-law exponent β) in SCPs positively correlated with that of heartbeat dynamics across time within an individual and negatively correlated with that of α-amplitude fluctuations across individuals. In addition, across individuals, long-range temporal correlation of both SCP and α-oscillation amplitude predicted subjects’ discrimination performance in the auditory task, albeit through antagonistic relationships. These findings reveal interrelations among different scale-free neural and physiological dynamics and initial evidence for the involvement of scale-free neural dynamics in the processing of natural stimuli, which often exhibit scale-free dynamics. PMID:27822495

Synthesis and review: African environmental processes and water-cycle dynamics.

PubMed

Ichoku, Charles; Adegoke, Jimmy

2016-12-01

Africa's vast landmass harbors a variety of physical processes that affect the environment and the water cycle. This focus issue on 'African Environmental Processes and Water-Cycle Dynamics' contains eight articles that address these phenomena from different but complementary perspectives. Fires used for agricultural and related purposes play a major role in land-cover change, surface albedo modifications, and smoke emission; all of which affect the environment and the water cycle in different ways. However, emissions of aerosols and trace gases are not restricted to fires, but also emanate from other natural and human activities. The African water cycle undergoes significant perturbations that are attributable to several factors, including the aforesaid environmental processes. These changes in the water cycle have produced severe drought and flooding events in recent decades that affect societal wellbeing across sub-Saharan Africa. The combined effects of the environmental processes and water-cycle dynamics affect and are affected by climate variability and can be propagated beyond the continent. Future studies should utilize the wealth of observations and modeling tools that are constantly improving to clearly elucidate the interrelationships between all of these phenomena for the benefit of society.

Electromagnetic induction sensor for dynamic testing of coagulation process.

PubMed

Wang, Zhe; Yu, Yuanhua; Yu, Zhanjiang; Chen, Qimeng

2018-03-01

With the increasing demand for coagulation POCT for patients in the surgery department or the ICU, rapid coagulation testing techniques and methods have drawn widespread attention from scholars and businessmen. This paper proposes the use of electromagnetic induction sensor probe for detection of dynamic process causing changes in the blood viscosity and density before and after coagulation based on the damped vibration principle, in order to evaluate the coagulation status. Utilizing the dynamic principle, the differential equation of vibration system comprising elastic support and electromagnetic induction device is established through sensor dynamic modeling. The structural parameters of elastic support are optimized, and the circular sheet spring is designed. Furthermore, harmonic response analysis and vibration fatigue coupling analysis are performed on the elastic support of the sensor by considering the natural frequency of the system, and the electromagnetic induction sensor testing device is set up. Using the device and coagulation reagent, the standard curve for coagulation POCT is plotted, and the blood sample application in clinical patients is established, which are methodologically compared with the imported POCT coagulation analyzer. The results show that the sensor designed in this paper has a first-order natural frequency of 11.368 Hz, which can withstand 5.295 × 10 2 million times of compressions and rebounds. Its correlation with the results of SONOCLOT analyzer reaches 0.996, and the reproducibility 0.002. The electromagnetic induction coagulation testing sensor designed has good elasticity and anti-fatigue, which can meet the accuracy requirement of clinical detection. This study provides the core technology for developing the electromagnetic induction POCT instrument for dynamic testing of coagulation process.

A dynamic scheduling algorithm for singe-arm two-cluster tools with flexible processing times

NASA Astrophysics Data System (ADS)

Li, Xin; Fung, Richard Y. K.

2018-02-01

This article presents a dynamic algorithm for job scheduling in two-cluster tools producing multi-type wafers with flexible processing times. Flexible processing times mean that the actual times for processing wafers should be within given time intervals. The objective of the work is to minimize the completion time of the newly inserted wafer. To deal with this issue, a two-cluster tool is decomposed into three reduced single-cluster tools (RCTs) in a series based on a decomposition approach proposed in this article. For each single-cluster tool, a dynamic scheduling algorithm based on temporal constraints is developed to schedule the newly inserted wafer. Three experiments have been carried out to test the dynamic scheduling algorithm proposed, comparing with the results the 'earliest starting time' heuristic (EST) adopted in previous literature. The results show that the dynamic algorithm proposed in this article is effective and practical.

Early chemo-dynamical evolution of dwarf galaxies deduced from enrichment of r-process elements

NASA Astrophysics Data System (ADS)

Hirai, Yutaka; Ishimaru, Yuhri; Saitoh, Takayuki R.; Fujii, Michiko S.; Hidaka, Jun; Kajino, Toshitaka

2017-04-01

The abundance of elements synthesized by the rapid neutron-capture process (r-process elements) of extremely metal-poor (EMP) stars in the Local Group galaxies gives us clues to clarify the early evolutionary history of the Milky Way halo. The Local Group dwarf galaxies would have similarly evolved with building blocks of the Milky Way halo. However, how the chemo-dynamical evolution of the building blocks affects the abundance of r-process elements is not yet clear. In this paper, we perform a series of simulations using dwarf galaxy models with various dynamical times and total mass, which determine star formation histories. We find that galaxies with dynamical times longer than 100 Myr have star formation rates less than 10-3 M⊙ yr-1 and slowly enrich metals in their early phase. These galaxies can explain the observed large scatters of r-process abundance in EMP stars in the Milky Way halo regardless of their total mass. On the other hand, the first neutron star merger appears at a higher metallicity in galaxies with a dynamical time shorter than typical neutron star merger times. The scatters of r-process elements mainly come from the inhomogeneity of the metals in the interstellar medium whereas the scatters of α-elements are mostly due to the difference in the yield of each supernova. Our results demonstrate that the future observations of r-process elements in EMP stars will be able to constrain the early chemo-dynamical evolution of the Local Group galaxies.

Generalized Dynamic Equations Related to Condensation and Freezing Processes

NASA Astrophysics Data System (ADS)

Wang, Xingrong; Huang, Yong

2018-01-01

The generalized thermodynamic equation related to condensation and freezing processes was derived by introducing the condensation and freezing probability function into the dynamic framework based on the statistical thermodynamic fluctuation theory. As a result, the physical mechanism of some weather phenomena covered by using δ(0,1) can in turn be studied and uncovered. From the generalized dynamic equations, the tendency equation of the generalized potential vorticity (GPV) is derived. From the discussion of tendency equation of GPV, in some very thin transitional areas, GPV is found nonconserved because of the introduction of the condensation and freezing probability function, even in frictionless and moist adiabatic air motion.

Dynamic Statistical Characterization of Variation in Source Processes of Microseismic Events

NASA Astrophysics Data System (ADS)

Smith-Boughner, L.; Viegas, G. F.; Urbancic, T.; Baig, A. M.

2015-12-01

During a hydraulic fracture, water is pumped at high pressure into a formation. A proppant, typically sand is later injected in the hope that it will make its way into a fracture, keep it open and provide a path for the hydrocarbon to enter the well. This injection can create micro-earthquakes, generated by deformation within the reservoir during treatment. When these injections are monitored, thousands of microseismic events are recorded within several hundred cubic meters. For each well-located event, many source parameters are estimated e.g. stress drop, Savage-Wood efficiency and apparent stress. However, because we are evaluating outputs from a power-law process, the extent to which the failure is impacted by fluid injection or stress triggering is not immediately clear. To better detect differences in source processes, we use a set of dynamic statistical parameters which characterize various force balance assumptions using the average distance to the nearest event, event rate, volume enclosed by the events, cumulative moment and energy from a group of events. One parameter, the Fracability index, approximates the ratio of viscous to elastic forcing and highlights differences in the response time of a rock to changes in stress. These dynamic parameters are applied to a database of more than 90 000 events in a shale-gas play in the Horn River Basin to characterize spatial-temporal variations in the source processes. In order to resolve these differences, a moving window, nearest neighbour approach was used. First, the center of mass of the local distribution was estimated for several source parameters. Then, a set of dynamic parameters, which characterize the response of the rock were estimated. These techniques reveal changes in seismic efficiency and apparent stress and often coincide with marked changes in the Fracability index and other dynamic statistical parameters. Utilizing these approaches allowed for the characterization of fluid injection related

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

PubMed

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

2018-02-01

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

Collisional and dynamical processes in moon and planet formation

NASA Technical Reports Server (NTRS)

Chapman, C. R.; Davis, D. R.; Weidenschilling, S. J.; Hartmann, W. K.; Spaute, D.

1987-01-01

Research on a variety of dynamical processes relevant to the formation of planets, satellites and ring systems is discussed. The main focus is on studies of accretionary formation of early protoplanets using a numerical model, structures and evolution of ring systems and individual bodies within planetary rings, and theories of lunar origin.

Blurred Star Image Processing for Star Sensors under Dynamic Conditions

PubMed Central

Zhang, Weina; Quan, Wei; Guo, Lei

2012-01-01

The precision of star point location is significant to identify the star map and to acquire the aircraft attitude for star sensors. Under dynamic conditions, star images are not only corrupted by various noises, but also blurred due to the angular rate of the star sensor. According to different angular rates under dynamic conditions, a novel method is proposed in this article, which includes a denoising method based on adaptive wavelet threshold and a restoration method based on the large angular rate. The adaptive threshold is adopted for denoising the star image when the angular rate is in the dynamic range. Then, the mathematical model of motion blur is deduced so as to restore the blurred star map due to large angular rate. Simulation results validate the effectiveness of the proposed method, which is suitable for blurred star image processing and practical for attitude determination of satellites under dynamic conditions. PMID:22778666

Note: Quasi-real-time analysis of dynamic near field scattering data using a graphics processing unit

NASA Astrophysics Data System (ADS)

Cerchiari, G.; Croccolo, F.; Cardinaux, F.; Scheffold, F.

2012-10-01

We present an implementation of the analysis of dynamic near field scattering (NFS) data using a graphics processing unit. We introduce an optimized data management scheme thereby limiting the number of operations required. Overall, we reduce the processing time from hours to minutes, for typical experimental conditions. Previously the limiting step in such experiments, the processing time is now comparable to the data acquisition time. Our approach is applicable to various dynamic NFS methods, including shadowgraph, Schlieren and differential dynamic microscopy.

Multiscale regression modeling in mouse supraspinatus tendons reveals that dynamic processes act as mediators in structure-function relationships.

PubMed

Connizzo, Brianne K; Adams, Sheila M; Adams, Thomas H; Jawad, Abbas F; Birk, David E; Soslowsky, Louis J

2016-06-14

Recent advances in technology have allowed for the measurement of dynamic processes (re-alignment, crimp, deformation, sliding), but only a limited number of studies have investigated their relationship with mechanical properties. The overall objective of this study was to investigate the role of composition, structure, and the dynamic response to load in predicting tendon mechanical properties in a multi-level fashion mimicking native hierarchical collagen structure. Multiple linear regression models were investigated to determine the relationships between composition/structure, dynamic processes, and mechanical properties. Mediation was then used to determine if dynamic processes mediated structure-function relationships. Dynamic processes were strong predictors of mechanical properties. These predictions were location-dependent, with the insertion site utilizing all four dynamic responses and the midsubstance responding primarily with fibril deformation and sliding. In addition, dynamic processes were moderately predicted by composition and structure in a regionally-dependent manner. Finally, dynamic processes were partial mediators of the relationship between composition/structure and mechanical function, and results suggested that mediation is likely shared between multiple dynamic processes. In conclusion, the mechanical properties at the midsubstance of the tendon are controlled primarily by fibril structure and this region responds to load via fibril deformation and sliding. Conversely, the mechanical function at the insertion site is controlled by many other important parameters and the region responds to load via all four dynamic mechanisms. Overall, this study presents a strong foundation on which to design future experimental and modeling efforts in order to fully understand the complex structure-function relationships present in tendon. Copyright © 2016 Elsevier Ltd. All rights reserved.

Nonlinear dynamics of global atmospheric and Earth system processes

NASA Technical Reports Server (NTRS)

Saltzman, Barry

1993-01-01

During the past eight years, we have been engaged in a NASA-supported program of research aimed at establishing the connection between satellite signatures of the earth's environmental state and the nonlinear dynamics of the global weather and climate system. Thirty-five publications and four theses have resulted from this work, which included contributions in five main areas of study: (1) cloud and latent heat processes in finite-amplitude baroclinic waves; (2) application of satellite radiation data in global weather analysis; (3) studies of planetary waves and low-frequency weather variability; (4) GCM studies of the atmospheric response to variable boundary conditions measurable from satellites; and (5) dynamics of long-term earth system changes. Significant accomplishments from the three main lines of investigation pursued during the past year are presented and include the following: (1) planetary atmospheric waves and low frequency variability; (2) GCM studies of the atmospheric response to changed boundary conditions; and (3) dynamics of long-term changes in the global earth system.

Dynamic Emotional Processing in Experiential Therapy: Two Steps Forward, One Step Back

ERIC Educational Resources Information Center

Pascual-Leone, Antonio

2009-01-01

The study of dynamic and nonlinear change has been a valuable development in psychotherapy process research. However, little advancement has been made in describing how moment-by-moment affective processes contribute to larger units of change. The purpose of this study was to examine observable moment-by-moment sequences in emotional processing as…

Self-Organized Information Processing in Neuronal Networks: Replacing Layers in Deep Networks by Dynamics

NASA Astrophysics Data System (ADS)

Kirst, Christoph

It is astonishing how the sub-parts of a brain co-act to produce coherent behavior. What are mechanism that coordinate information processing and communication and how can those be changed flexibly in order to cope with variable contexts? Here we show that when information is encoded in the deviations around a collective dynamical reference state of a recurrent network the propagation of these fluctuations is strongly dependent on precisely this underlying reference. Information here 'surfs' on top of the collective dynamics and switching between states enables fast and flexible rerouting of information. This in turn affects local processing and consequently changes in the global reference dynamics that re-regulate the distribution of information. This provides a generic mechanism for self-organized information processing as we demonstrate with an oscillatory Hopfield network that performs contextual pattern recognition. Deep neural networks have proven to be very successful recently. Here we show that generating information channels via collective reference dynamics can effectively compress a deep multi-layer architecture into a single layer making this mechanism a promising candidate for the organization of information processing in biological neuronal networks.

System for generating timing and control signals

NASA Technical Reports Server (NTRS)

Perlman, M.; Rousey, W. J.; Messner, A. (Inventor)

1975-01-01

A system capable of generating every possible data frame subperiod and delayed subperiod of a data frame of length of M clock pulse intervals (CPIs) comprised of parallel modulo-m sub i counters is presented. Each m sub i is a prime power divisor of M and a cascade of alpha sub i identical modulo-p sub i counters. The modulo-p sub i counters are feedback shift registers which cycle through p sub i distinct states. Every possible nontrivial data frame subperiod and delayed subperiod is derived and a specific CPI in the data frame is detected. The number of clock pulses required to bring every modulo-p sub i counter to a respective designated state or count is determined by the Chinese remainder theorem. This corresponds to the solution of simultaneous congruences over relatively prime moduli.

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

PubMed

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

2011-12-01

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

F*** Yeah Fluid Dynamics: Inside the science communication process

NASA Astrophysics Data System (ADS)

Sharp, Nicole

2016-11-01

Communicating scientific research to general audiences may seem daunting, but it does not have to be. For six years, fluid dynamics outreach blog FYFD has been sharing the community's scientific output with an audience of nearly a quarter of a million readers and viewers of all ages and backgrounds. This talk will focus on the process behind science communication and some of the steps and exercises that can help scientists communicate to broad audiences more effectively. Using examples from the FYFD blog and YouTube channel, the talk will illustrate this communication process in action.

r-process nucleosynthesis in dynamic helium-burning environments

NASA Technical Reports Server (NTRS)

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

1985-01-01

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

[A novel quantitative approach to study dynamic anaerobic process at micro scale].

PubMed

Zhang, Zhong-Liang; Wu, Jing; Jiang, Jian-Kai; Jiang, Jie; Li, Huai-Zhi

2012-11-01

Anaerobic digestion is attracting more and more interests because of its advantages such as low cost and recovery of clean energy etc. In order to overcome the drawbacks of the existed methods to study the dynamic anaerobic process, a novel microscopical quantitative approach at the granule level was developed combining both the microdevice and the quantitative image analysis techniques. This experiment displayed the process and characteristics of the gas production at static state for the first time and the results indicated that the method was of satisfactory repeatability. The gas production process at static state could be divided into three stages including rapid linear increasing stage, decelerated increasing stage and slow linear increasing stage. The rapid linear increasing stage was long and the biogas rate was high under high initial organic loading rate. The results showed that it was feasible to make the anaerobic process to be carried out in the microdevice; furthermore this novel method was reliable and could clearly display the dynamic process of the anaerobic reaction at the micro scale. The results are helpful to understand the anaerobic process.

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

PubMed

Lewis, F L; Vamvoudakis, Kyriakos G

2011-02-01

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

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.

Accelerating Molecular Dynamic Simulation on Graphics Processing Units

PubMed Central

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

2009-01-01

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

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

ERIC Educational Resources Information Center

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

2009-01-01

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

Dynamic control and information processing in chemical reaction systems by tuning self-organization behavior

NASA Astrophysics Data System (ADS)

Lebiedz, Dirk; Brandt-Pollmann, Ulrich

2004-09-01

Specific external control of chemical reaction systems and both dynamic control and signal processing as central functions in biochemical reaction systems are important issues of modern nonlinear science. For example nonlinear input-output behavior and its regulation are crucial for the maintainance of the life process that requires extensive communication between cells and their environment. An important question is how the dynamical behavior of biochemical systems is controlled and how they process information transmitted by incoming signals. But also from a general point of view external forcing of complex chemical reaction processes is important in many application areas ranging from chemical engineering to biomedicine. In order to study such control issues numerically, here, we choose a well characterized chemical system, the CO oxidation on Pt(110), which is interesting per se as an externally forced chemical oscillator model. We show numerically that tuning of temporal self-organization by input signals in this simple nonlinear chemical reaction exhibiting oscillatory behavior can in principle be exploited for both specific external control of dynamical system behavior and processing of complex information.

Individual-based approach to epidemic processes on arbitrary dynamic contact networks

NASA Astrophysics Data System (ADS)

Rocha, Luis E. C.; Masuda, Naoki

2016-08-01

The dynamics of contact networks and epidemics of infectious diseases often occur on comparable time scales. Ignoring one of these time scales may provide an incomplete understanding of the population dynamics of the infection process. We develop an individual-based approximation for the susceptible-infected-recovered epidemic model applicable to arbitrary dynamic networks. Our framework provides, at the individual-level, the probability flow over time associated with the infection dynamics. This computationally efficient framework discards the correlation between the states of different nodes, yet provides accurate results in approximating direct numerical simulations. It naturally captures the temporal heterogeneities and correlations of contact sequences, fundamental ingredients regulating the timing and size of an epidemic outbreak, and the number of secondary infections. The high accuracy of our approximation further allows us to detect the index individual of an epidemic outbreak in real-life network data.

Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks.

PubMed

Herrera, Mauricio; Armelini, Guillermo; Salvaj, Erica

2015-01-01

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

Understanding Social Contagion in Adoption Processes Using Dynamic Social Networks

PubMed Central

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

Vanicat, Matthieu

2018-04-01

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

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.

Extending topological surgery to natural processes and dynamical systems.

PubMed

Antoniou, Stathis; Lambropoulou, Sofia

2017-01-01

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

Stationary States of Boundary Driven Exclusion Processes with Nonreversible Boundary Dynamics

NASA Astrophysics Data System (ADS)

Erignoux, C.; Landim, C.; Xu, T.

2018-05-01

We prove a law of large numbers for the empirical density of one-dimensional, boundary driven, symmetric exclusion processes with different types of non-reversible dynamics at the boundary. The proofs rely on duality techniques.

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

PubMed

Kovaříček, Petr; Lehn, Jean-Marie

2012-06-06

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

Dynamics of Lamin-A Processing Following Precursor Accumulation

PubMed Central

Liu, Qian; Kim, Dae In; Syme, Janet; LuValle, Phyllis; Burke, Brian; Roux, Kyle J.

2010-01-01

Lamin A (LaA) is a component of the nuclear lamina, an intermediate filament meshwork that underlies the inner nuclear membrane (INM) of the nuclear envelope (NE). Newly synthesized prelamin A (PreA) undergoes extensive processing involving C-terminal farnesylation followed by proteolysis yielding non-farnesylated mature lamin A. Different inhibitors of these processing events are currently used therapeutically. Hutchinson-Gilford Progeria Syndrome (HGPS) is most commonly caused by mutations leading to an accumulation of a farnesylated LaA isoform, prompting a clinical trial using farnesyltransferase inhibitors (FTI) to reduce this modification. At therapeutic levels, HIV protease inhibitors (PI) can unexpectedly inhibit the final processing step in PreA maturation. We have examined the dynamics of LaA processing and associated cellular effects during PI or FTI treatment and following inhibitor washout. While PI reversibility was rapid, with respect to both LaA maturation and associated cellular phenotype, recovery from FTI treatment was more gradual. FTI reversibility is influenced by both cell type and rate of proliferation. These results suggest a less static lamin network than has previously been observed. PMID:20526372

Ecological and Dynamical Study of the Creative Process and Affects of Scientific Students Working in Groups

ERIC Educational Resources Information Center

Peilloux, Aurélien; Botella, Marion

2016-01-01

Although creativity has drawn the attention of researchers during the past century, collaborative processes have barely been investigated. In this article, the collective dimension of a creative process is investigated, based on a dynamic and ecological approach that includes an affective component. "Dynamic" means that the creative…

Robust Modulo Remaindering and Applications in Radar and Sensor Signal Processing

DTIC Science & Technology

2015-08-27

Chinese Remainder Theorem in FDD Systems, Science China -- Information Sciences, vol.55, no.7, pp. 1605 -1616, July 2012. 3) Y. Liu, X.-G. Xia, and H. L...Sciences, vol.55, no.7, pp. 1605 -1616, July 2012. 3) Y. Liu, X.-G. Xia, and H. L. Zhang, Distributed Space-Time Coding for Full-DuplexAsynchronous

Local Competition and Metapopulation Processes Drive Long-Term Seagrass-Epiphyte Population Dynamics

PubMed Central

Lobelle, Delphine; Kenyon, Emma J.; Cook, Kevan J.; Bull, James C.

2013-01-01

It is well known that ecological processes such as population regulation and natural enemy interactions potentially occur over a range of spatial scales, and there is a substantial body of literature developing theoretical understanding of the interplay between these processes. However, there are comparatively few studies quantifying the long-term effects of spatial scaling in natural ecosystems. A key challenge is that trophic complexity in real-world biological communities quickly obscures the signal from a focal process. Seagrass meadows provide an excellent opportunity in this respect: in many instances, seagrasses effectively form extensive natural monocultures, in which hypotheses about endogenous dynamics can be formulated and tested. We present amongst the longest unbroken, spatially explict time series of seagrass abundance published to date. Data include annual measures of shoot density, total above-ground abundance, and associated epiphyte cover from five Zostera marina meadows distributed around the Isles of Scilly, UK, from 1996 to 2011. We explore empirical patterns at the local and metapopulation scale using standard time series analysis and develop a simple population dynamic model, testing the hypothesis that both local and metapopulation scale feedback processes are important. We find little evidence of an interaction between scales in seagrass dynamics but that both scales contribute approximately equally to observed local epiphyte abundance. By quantifying the long-term dynamics of seagrass-epiphyte interactions we show how measures of density and extent are both important in establishing baseline information relevant to predicting responses to environmental change and developing management plans. We hope that this study complements existing mechanistic studies of physiology, genetics and productivity in seagrass, whilst highlighting the potential of seagrass as a model ecosystem. More generally, this study provides a rare opportunity to test

Local competition and metapopulation processes drive long-term seagrass-epiphyte population dynamics.

PubMed

Lobelle, Delphine; Kenyon, Emma J; Cook, Kevan J; Bull, James C

2013-01-01

It is well known that ecological processes such as population regulation and natural enemy interactions potentially occur over a range of spatial scales, and there is a substantial body of literature developing theoretical understanding of the interplay between these processes. However, there are comparatively few studies quantifying the long-term effects of spatial scaling in natural ecosystems. A key challenge is that trophic complexity in real-world biological communities quickly obscures the signal from a focal process. Seagrass meadows provide an excellent opportunity in this respect: in many instances, seagrasses effectively form extensive natural monocultures, in which hypotheses about endogenous dynamics can be formulated and tested. We present amongst the longest unbroken, spatially explict time series of seagrass abundance published to date. Data include annual measures of shoot density, total above-ground abundance, and associated epiphyte cover from five Zostera marina meadows distributed around the Isles of Scilly, UK, from 1996 to 2011. We explore empirical patterns at the local and metapopulation scale using standard time series analysis and develop a simple population dynamic model, testing the hypothesis that both local and metapopulation scale feedback processes are important. We find little evidence of an interaction between scales in seagrass dynamics but that both scales contribute approximately equally to observed local epiphyte abundance. By quantifying the long-term dynamics of seagrass-epiphyte interactions we show how measures of density and extent are both important in establishing baseline information relevant to predicting responses to environmental change and developing management plans. We hope that this study complements existing mechanistic studies of physiology, genetics and productivity in seagrass, whilst highlighting the potential of seagrass as a model ecosystem. More generally, this study provides a rare opportunity to test

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

PubMed

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

2017-11-28

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

Radiation Pressure Cooling as a Quantum Dynamical Process

NASA Astrophysics Data System (ADS)

He, Bing; Yang, Liu; Lin, Qing; Xiao, Min

2017-06-01

One of the most fundamental problems in optomechanical cooling is how small the thermal phonon number of a mechanical oscillator can be achieved under the radiation pressure of a proper cavity field. Different from previous theoretical predictions, which were based on an optomechanical system's time-independent steady states, we treat such cooling as a dynamical process of driving the mechanical oscillator from its initial thermal state, due to its thermal equilibrium with the environment, to a stabilized quantum state of higher purity. We find that the stabilized thermal phonon number left in the end actually depends on how fast the cooling process could be. The cooling speed is decided by an effective optomechanical coupling intensity, which constitutes an essential parameter for cooling, in addition to the sideband resolution parameter that has been considered in other theoretical studies. The limiting thermal phonon number that any cooling process cannot surpass exhibits a discontinuous jump across a certain value of the parameter.

Deterministic processes guide long-term synchronised population dynamics in replicate anaerobic digesters

PubMed Central

Vanwonterghem, Inka; Jensen, Paul D; Dennis, Paul G; Hugenholtz, Philip; Rabaey, Korneel; Tyson, Gene W

2014-01-01

A replicate long-term experiment was conducted using anaerobic digestion (AD) as a model process to determine the relative role of niche and neutral theory on microbial community assembly, and to link community dynamics to system performance. AD is performed by a complex network of microorganisms and process stability relies entirely on the synergistic interactions between populations belonging to different functional guilds. In this study, three independent replicate anaerobic digesters were seeded with the same diverse inoculum, supplied with a model substrate, α-cellulose, and operated for 362 days at a 10-day hydraulic residence time under mesophilic conditions. Selective pressure imposed by the operational conditions and model substrate caused large reproducible changes in community composition including an overall decrease in richness in the first month of operation, followed by synchronised population dynamics that correlated with changes in reactor performance. This included the synchronised emergence and decline of distinct Ruminococcus phylotypes at day 148, and emergence of a Clostridium and Methanosaeta phylotype at day 178, when performance became stable in all reactors. These data suggest that many dynamic functional niches are predictably filled by phylogenetically coherent populations over long time scales. Neutral theory would predict that a complex community with a high degree of recognised functional redundancy would lead to stochastic changes in populations and community divergence over time. We conclude that deterministic processes may play a larger role in microbial community dynamics than currently appreciated, and under controlled conditions it may be possible to reliably predict community structural and functional changes over time. PMID:24739627

The wiper model: avalanche dynamics in an exclusion process

NASA Astrophysics Data System (ADS)

Politi, Antonio; Romano, M. Carmen

2013-10-01

The exclusion-process model (Ciandrini et al 2010 Phys. Rev. E 81 051904) describing traffic of particles with internal stepping dynamics reveals the presence of strong correlations in realistic regimes. Here we study such a model in the limit of an infinitely fast translocation time, where the evolution can be interpreted as a ‘wiper’ that moves to dry neighbouring sites. We trace back the existence of long-range correlations to the existence of avalanches, where many sites are dried at once. At variance with self-organized criticality, in the wiper model avalanches have a typical size equal to the logarithm of the lattice size. In the thermodynamic limit, we find that the hydrodynamic behaviour is a mixture of stochastic (diffusive) fluctuations and increasingly coherent periodic oscillations that are reminiscent of a collective dynamics.

Modelling of dynamic contact length in rail grinding process

NASA Astrophysics Data System (ADS)

Zhi, Shaodan; Li, Jianyong; Zarembski, A. M.

2014-09-01

Rails endure frequent dynamic loads from the passing trains for supporting trains and guiding wheels. The accumulated stress concentrations will cause the plastic deformation of rail towards generating corrugations, contact fatigue cracks and also other defects, resulting in more dangerous status even the derailment risks. So the rail grinding technology has been invented with rotating grinding stones pressed on the rail with defects removal. Such rail grinding works are directed by experiences rather than scientifically guidance, lacking of flexible and scientific operating methods. With grinding control unit holding the grinding stones, the rail grinding process has the characteristics not only the surface grinding but also the running railway vehicles. First of all, it's important to analyze the contact length between the grinding stone and the rail, because the contact length is a critical parameter to measure the grinding capabilities of stones. Moreover, it's needed to build up models of railway vehicle unit bonded with the grinding stone to represent the rail grinding car. Therefore the theoretical model for contact length is developed based on the geometrical analysis. And the calculating models are improved considering the grinding car's dynamic behaviors during the grinding process. Eventually, results are obtained based on the models by taking both the operation parameters and the structure parameters into the calculation, which are suitable for revealing the process of rail grinding by combining the grinding mechanism and the railway vehicle systems.

Dynamic Simulation on the Installation Process of HGIS in Transformer Substation

NASA Astrophysics Data System (ADS)

Lin, Tao; Li, Shaohua; Wang, Hu; Che, Deyong; Qi, Guangcai; Yao, Jianfeng; Zhang, Qingzhe

The technological requirements of Hypid Gas Insulated Switchgear (HGIS) installation in transformer substation is high and the control points of quality is excessive. Most of the engineers and technicians in the construction enterprises are not familiar with equipments of HGIS. In order to solve these problem, equipments of HGIS is modeled on the computer by SolidWorks software. Installation process of civil foundation and closed-type equipments is optimized dynamically with virtual assemble technology. Announcements and application work are composited into animation file. Skills of modeling and simulation is tidied classify as well. The result of the visual dynamic simulation can instruct the actual construction process of HGIS to a certain degree and can promote reasonable construction planning and management. It can also improve the method and quality of staff training for electric power construction enterprises.

Hierarchical Process Composition: Dynamic Maintenance of Structure in a Distributed Environment

DTIC Science & Technology

1988-01-01

One prominent hne of research stresses the independence of address space and thread of control, and the resulting efficiencies due to shared memory...cooperating processes. StarOS focuses on case of use and a general capability mechanism, while Medusa stresses the effect of distributed hardware on system...process structure and the asynchrony among agents and between agents and sources of failure. By stressing dynamic structure, we are led to adopt an

Determination of Dynamic Recrystallization Process by Equivalent Strain

NASA Astrophysics Data System (ADS)

Qin, Xiaomei; Deng, Wei

Based on Tpнoвckiй's displacement field, equivalent strain expression was derived. And according to the dynamic recrystallization (DRX) critical strain, DRX process was determined by equivalent strain. It was found that equivalent strain distribution in deformed specimen is inhomogeneous, and it increases with increasing true strain. Under a certain true strain, equivalent strains at the center, demisemi radius or on tangential plane just below the surface of the specimen are higher than the true strain. Thus, micrographs at those positions can not exactly reflect the true microstructures under the certain true strain. With increasing strain rate, the initial and finish time of DRX decrease. The frozen microstructures of 20Mn23AlV steel with the experimental condition validate the feasibility of predicting DRX process by equivalent strain.

Extending topological surgery to natural processes and dynamical systems

PubMed Central

Antoniou, Stathis; Lambropoulou, Sofia

2017-01-01

Topological surgery is a mathematical technique used for creating new manifolds out of known ones. We observe that it occurs in natural phenomena where a sphere of dimension 0 or 1 is selected, forces are applied and the manifold in which they occur changes type. For example, 1-dimensional surgery happens during chromosomal crossover, DNA recombination and when cosmic magnetic lines reconnect, while 2-dimensional surgery happens in the formation of tornadoes, in the phenomenon of Falaco solitons, in drop coalescence and in the cell mitosis. Inspired by such phenomena, we introduce new theoretical concepts which enhance topological surgery with the observed forces and dynamics. To do this, we first extend the formal definition to a continuous process caused by local forces. Next, for modeling phenomena which do not happen on arcs or surfaces but are 2-dimensional or 3-dimensional, we fill in the interior space by defining the notion of solid topological surgery. We further introduce the notion of embedded surgery in S3 for modeling phenomena which involve more intrinsically the ambient space, such as the appearance of knotting in DNA and phenomena where the causes and effect of the process lies beyond the initial manifold, such as the formation of black holes. Finally, we connect these new theoretical concepts with a dynamical system and we present it as a model for both 2-dimensional 0-surgery and natural phenomena exhibiting a ‘hole drilling’ behavior. We hope that through this study, topology and dynamics of many natural phenomena, as well as topological surgery itself, will be better understood. PMID:28915271

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

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

PubMed

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

2017-08-16

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

Dynamic wavefront creation for processing units using a hybrid compactor

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

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

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

Dynamical processes and epidemic threshold on nonlinear coupled multiplex networks

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Quantum correlation dynamics in photosynthetic processes assisted by molecular vibrations

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

Giorgi, G.L., E-mail: g.giorgi@inrim.it; Roncaglia, M.; Raffa, F.A.

2015-10-15

During the long course of evolution, nature has learnt how to exploit quantum effects. In fact, recent experiments reveal the existence of quantum processes whose coherence extends over unexpectedly long time and space ranges. In particular, photosynthetic processes in light-harvesting complexes display a typical oscillatory dynamics ascribed to quantum coherence. Here, we consider the simple model where a dimer made of two chromophores is strongly coupled with a quasi-resonant vibrational mode. We observe the occurrence of wide oscillations of genuine quantum correlations, between electronic excitations and the environment, represented by vibrational bosonic modes. Such a quantum dynamics has been unveiledmore » through the calculation of the negativity of entanglement and the discord, indicators widely used in quantum information for quantifying the resources needed to realize quantum technologies. We also discuss the possibility of approximating additional weakly-coupled off-resonant vibrational modes, simulating the disturbances induced by the rest of the environment, by a single vibrational mode. Within this approximation, one can show that the off-resonant bath behaves like a classical source of noise.« less

Dynamics of molecular motors with finite processivity on heterogeneous tracks.

PubMed

Kafri, Yariv; Lubensky, David K; Nelson, David R

2005-04-01

The dynamics of molecular motors which occasionally detach from a heterogeneous track like DNA or RNA is considered. Motivated by recent single-molecule experiments, we study a simple model for a motor moving along a disordered track using chemical energy while an external force opposes its motion. The motors also have finite processivity, i.e., they can leave the track with a position-dependent rate. We show that the response of the system to disorder in the hopping-off rate depends on the value of the external force. For most values of the external force, strong disorder causes the motors which survive for long times on the track to be localized at preferred positions. However, near the stall force, localization occurs for any amount of disorder. To obtain these results, we study the complex eigenvalue spectrum of the time evolution operator. Existence of localized states near the top of the band implies a stretched exponential contribution to the decay of the survival probability. A similar spectral analysis also provides a very efficient method for studying the dynamics of motors with infinite processivity.

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

NASA Technical Reports Server (NTRS)

Hsieh, Shang-Hsien

1993-01-01

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

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

PubMed

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

2011-02-28

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

Switching Dynamics and the Stress Process

PubMed Central

Cornwell, Benjamin

2014-01-01

This paper shows how maintaining social relationships can be a daily hassle that has implications for the stress process, depending on how often individuals transition, or “switch,” between their various social roles and social settings throughout the day. I use nationally representative time diary data on 7,662 respondents from the 2010 American Time Use Survey to measure individual rates of this switching behavior and to examine how this relates to perceived stress. Regression analysis shows that, net of how many social roles they play and settings they visit on a given day, individuals who switch more frequently between these elements report higher levels of stress. This finding holds for women but not men, suggesting that switching dynamics are disproportionately stressful for women. I close by discussing the implications of the findings for research on gender and health. PMID:25110381

Markov and non-Markov processes in complex systems by the dynamical information entropy

NASA Astrophysics Data System (ADS)

Yulmetyev, R. M.; Gafarov, F. M.

1999-12-01

We consider the Markov and non-Markov processes in complex systems by the dynamical information Shannon entropy (DISE) method. The influence and important role of the two mutually dependent channels of entropy alternation (creation or generation of correlation) and anti-correlation (destroying or annihilation of correlation) have been discussed. The developed method has been used for the analysis of the complex systems of various natures: slow neutron scattering in liquid cesium, psychology (short-time numeral and pattern human memory and effect of stress on the dynamical taping-test), random dynamics of RR-intervals in human ECG (problem of diagnosis of various disease of the human cardio-vascular systems), chaotic dynamics of the parameters of financial markets and ecological systems.

Inhomogeneous Point-Processes to Instantaneously Assess Affective Haptic Perception through Heartbeat Dynamics Information

NASA Astrophysics Data System (ADS)

Valenza, G.; Greco, A.; Citi, L.; Bianchi, M.; Barbieri, R.; Scilingo, E. P.

2016-06-01

This study proposes the application of a comprehensive signal processing framework, based on inhomogeneous point-process models of heartbeat dynamics, to instantaneously assess affective haptic perception using electrocardiogram-derived information exclusively. The framework relies on inverse-Gaussian point-processes with Laguerre expansion of the nonlinear Wiener-Volterra kernels, accounting for the long-term information given by the past heartbeat events. Up to cubic-order nonlinearities allow for an instantaneous estimation of the dynamic spectrum and bispectrum of the considered cardiovascular dynamics, as well as for instantaneous measures of complexity, through Lyapunov exponents and entropy. Short-term caress-like stimuli were administered for 4.3-25 seconds on the forearms of 32 healthy volunteers (16 females) through a wearable haptic device, by selectively superimposing two levels of force, 2 N and 6 N, and two levels of velocity, 9.4 mm/s and 65 mm/s. Results demonstrated that our instantaneous linear and nonlinear features were able to finely characterize the affective haptic perception, with a recognition accuracy of 69.79% along the force dimension, and 81.25% along the velocity dimension.

Inhomogeneous Point-Processes to Instantaneously Assess Affective Haptic Perception through Heartbeat Dynamics Information

PubMed Central

Valenza, G.; Greco, A.; Citi, L.; Bianchi, M.; Barbieri, R.; Scilingo, E. P.

2016-01-01

This study proposes the application of a comprehensive signal processing framework, based on inhomogeneous point-process models of heartbeat dynamics, to instantaneously assess affective haptic perception using electrocardiogram-derived information exclusively. The framework relies on inverse-Gaussian point-processes with Laguerre expansion of the nonlinear Wiener-Volterra kernels, accounting for the long-term information given by the past heartbeat events. Up to cubic-order nonlinearities allow for an instantaneous estimation of the dynamic spectrum and bispectrum of the considered cardiovascular dynamics, as well as for instantaneous measures of complexity, through Lyapunov exponents and entropy. Short-term caress-like stimuli were administered for 4.3–25 seconds on the forearms of 32 healthy volunteers (16 females) through a wearable haptic device, by selectively superimposing two levels of force, 2 N and 6 N, and two levels of velocity, 9.4 mm/s and 65 mm/s. Results demonstrated that our instantaneous linear and nonlinear features were able to finely characterize the affective haptic perception, with a recognition accuracy of 69.79% along the force dimension, and 81.25% along the velocity dimension. PMID:27357966

Graphene-assisted multiple-input high-base optical computing

PubMed Central

Hu, Xiao; Wang, Andong; Zeng, Mengqi; Long, Yun; Zhu, Long; Fu, Lei; Wang, Jian

2016-01-01

We propose graphene-assisted multiple-input high-base optical computing. We fabricate a nonlinear optical device based on a fiber pigtail cross-section coated with a single-layer graphene grown by chemical vapor deposition (CVD) method. An approach to implementing modulo 4 operations of three-input hybrid addition and subtraction of quaternary base numbers in the optical domain using multiple non-degenerate four-wave mixing (FWM) processes in graphene coated optical fiber device and (differential) quadrature phase-shift keying ((D)QPSK) signals is presented. We demonstrate 10-Gbaud modulo 4 operations of three-input quaternary hybrid addition and subtraction (A + B − C, A + C − B, B + C − A) in the experiment. The measured optical signal-to-noise ratio (OSNR) penalties for modulo 4 operations of three-input quaternary hybrid addition and subtraction (A + B − C, A + C − B, B + C − A) are measured to be less than 7 dB at a bit-error rate (BER) of 2 × 10−3. The BER performance as a function of the relative time offset between three signals (signal offset) is also evaluated showing favorable performance. PMID:27604866

Dynamics of Ranking Processes in Complex Systems

NASA Astrophysics Data System (ADS)

Blumm, Nicholas; Ghoshal, Gourab; Forró, Zalán; Schich, Maximilian; Bianconi, Ginestra; Bouchaud, Jean-Philippe; Barabási, Albert-László

2012-09-01

The world is addicted to ranking: everything, from the reputation of scientists, journals, and universities to purchasing decisions is driven by measured or perceived differences between them. Here, we analyze empirical data capturing real time ranking in a number of systems, helping to identify the universal characteristics of ranking dynamics. We develop a continuum theory that not only predicts the stability of the ranking process, but shows that a noise-induced phase transition is at the heart of the observed differences in ranking regimes. The key parameters of the continuum theory can be explicitly measured from data, allowing us to predict and experimentally document the existence of three phases that govern ranking stability.

Review of computational fluid dynamics applications in biotechnology processes.

PubMed

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

2011-01-01

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

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.

A Process for Comparing Dynamics of Distributed Space Systems Simulations

NASA Technical Reports Server (NTRS)

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

2009-01-01

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

Molecular dynamics studies on the DNA-binding process of ERG.

PubMed

Beuerle, Matthias G; Dufton, Neil P; Randi, Anna M; Gould, Ian R

2016-11-15

The ETS family of transcription factors regulate gene targets by binding to a core GGAA DNA-sequence. The ETS factor ERG is required for homeostasis and lineage-specific functions in endothelial cells, some subset of haemopoietic cells and chondrocytes; its ectopic expression is linked to oncogenesis in multiple tissues. To date details of the DNA-binding process of ERG including DNA-sequence recognition outside the core GGAA-sequence are largely unknown. We combined available structural and experimental data to perform molecular dynamics simulations to study the DNA-binding process of ERG. In particular we were able to reproduce the ERG DNA-complex with a DNA-binding simulation starting in an unbound configuration with a final root-mean-square-deviation (RMSD) of 2.1 Å to the core ETS domain DNA-complex crystal structure. This allowed us to elucidate the relevance of amino acids involved in the formation of the ERG DNA-complex and to identify Arg385 as a novel key residue in the DNA-binding process. Moreover we were able to show that water-mediated hydrogen bonds are present between ERG and DNA in our simulations and that those interactions have the potential to achieve sequence recognition outside the GGAA core DNA-sequence. The methodology employed in this study shows the promising capabilities of modern molecular dynamics simulations in the field of protein DNA-interactions.

Multiple sensor fault diagnosis for dynamic processes.

PubMed

Li, Cheng-Chih; Jeng, Jyh-Cheng

2010-10-01

Modern industrial plants are usually large scaled and contain a great amount of sensors. Sensor fault diagnosis is crucial and necessary to process safety and optimal operation. This paper proposes a systematic approach to detect, isolate and identify multiple sensor faults for multivariate dynamic systems. The current work first defines deviation vectors for sensor observations, and further defines and derives the basic sensor fault matrix (BSFM), consisting of the normalized basic fault vectors, by several different methods. By projecting a process deviation vector to the space spanned by BSFM, this research uses a vector with the resulted weights on each direction for multiple sensor fault diagnosis. This study also proposes a novel monitoring index and derives corresponding sensor fault detectability. The study also utilizes that vector to isolate and identify multiple sensor faults, and discusses the isolatability and identifiability. Simulation examples and comparison with two conventional PCA-based contribution plots are presented to demonstrate the effectiveness of the proposed methodology. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Modeling Dynamic Food Choice Processes to Understand Dietary Intervention Effects.

PubMed

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

2018-02-17

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

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

PubMed Central

McElree, Brian; Carrasco, Marisa

2012-01-01

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

Dynamic optimization of chemical processes using ant colony framework.

PubMed

Rajesh, J; Gupta, K; Kusumakar, H S; Jayaraman, V K; Kulkarni, B D

2001-11-01

Ant colony framework is illustrated by considering dynamic optimization of six important bench marking examples. This new computational tool is simple to implement and can tackle problems with state as well as terminal constraints in a straightforward fashion. It requires fewer grid points to reach the global optimum at relatively very low computational effort. The examples with varying degree of complexities, analyzed here, illustrate its potential for solving a large class of process optimization problems in chemical engineering.

Identity in agent-based models : modeling dynamic multiscale social processes.

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

Ozik, J.; Sallach, D. L.; Macal, C. M.

Identity-related issues play central roles in many current events, including those involving factional politics, sectarianism, and tribal conflicts. Two popular models from the computational-social-science (CSS) literature - the Threat Anticipation Program and SharedID models - incorporate notions of identity (individual and collective) and processes of identity formation. A multiscale conceptual framework that extends some ideas presented in these models and draws other capabilities from the broader CSS literature is useful in modeling the formation of political identities. The dynamic, multiscale processes that constitute and transform social identities can be mapped to expressive structures of the framework

Dynamic Characteristics of Buildings from Signal Processing of Ambient Vibration

NASA Astrophysics Data System (ADS)

Dobre, Daniela; Sorin Dragomir, Claudiu

2017-10-01

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

Functional data analysis for dynamical system identification of behavioral processes.

PubMed

Trail, Jessica B; Collins, Linda M; Rivera, Daniel E; Li, Runze; Piper, Megan E; Baker, Timothy B

2014-06-01

Efficient new technology has made it straightforward for behavioral scientists to collect anywhere from several dozen to several thousand dense, repeated measurements on one or more time-varying variables. These intensive longitudinal data (ILD) are ideal for examining complex change over time but present new challenges that illustrate the need for more advanced analytic methods. For example, in ILD the temporal spacing of observations may be irregular, and individuals may be sampled at different times. Also, it is important to assess both how the outcome changes over time and the variation between participants' time-varying processes to make inferences about a particular intervention's effectiveness within the population of interest. The methods presented in this article integrate 2 innovative ILD analytic techniques: functional data analysis and dynamical systems modeling. An empirical application is presented using data from a smoking cessation clinical trial. Study participants provided 42 daily assessments of pre-quit and post-quit withdrawal symptoms. Regression splines were used to approximate smooth functions of craving and negative affect and to estimate the variables' derivatives for each participant. We then modeled the dynamics of nicotine craving using standard input-output dynamical systems models. These models provide a more detailed characterization of the post-quit craving process than do traditional longitudinal models, including information regarding the type, magnitude, and speed of the response to an input. The results, in conjunction with standard engineering control theory techniques, could potentially be used by tobacco researchers to develop a more effective smoking intervention. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Functional Data Analysis for Dynamical System Identification of Behavioral Processes

PubMed Central

Trail, Jessica B.; Collins, Linda M.; Rivera, Daniel E.; Li, Runze; Piper, Megan E.; Baker, Timothy B.

2014-01-01

Efficient new technology has made it straightforward for behavioral scientists to collect anywhere from several dozen to several thousand dense, repeated measurements on one or more time-varying variables. These intensive longitudinal data (ILD) are ideal for examining complex change over time, but present new challenges that illustrate the need for more advanced analytic methods. For example, in ILD the temporal spacing of observations may be irregular, and individuals may be sampled at different times. Also, it is important to assess both how the outcome changes over time and the variation between participants' time-varying processes to make inferences about a particular intervention's effectiveness within the population of interest. The methods presented in this article integrate two innovative ILD analytic techniques: functional data analysis and dynamical systems modeling. An empirical application is presented using data from a smoking cessation clinical trial. Study participants provided 42 daily assessments of pre-quit and post-quit withdrawal symptoms. Regression splines were used to approximate smooth functions of craving and negative affect and to estimate the variables' derivatives for each participant. We then modeled the dynamics of nicotine craving using standard input-output dynamical systems models. These models provide a more detailed characterization of the post-quit craving process than do traditional longitudinal models, including information regarding the type, magnitude, and speed of the response to an input. The results, in conjunction with standard engineering control theory techniques, could potentially be used by tobacco researchers to develop a more effective smoking intervention. PMID:24079929

Helicity in dynamic atmospheric processes

NASA Astrophysics Data System (ADS)

Kurgansky, M. V.

2017-03-01

An overview on the helicity of the velocity field and the role played by this concept in modern research in the field of geophysical fluid dynamics and dynamic meteorology is given. Different (both previously known in the literature and first presented) formulations of the equation of helicity balance in atmospheric motions (including those with allowance for effects of air compressibility and Earth's rotation) are brought together. Equations and relationships are given which are valid in different approximations accepted in dynamic meteorology: Boussinesq approximation, quasi-static approximation, and quasi-geostrophic approximation. Emphasis is placed on the analysis of helicity budget in large-scale quasi-geostrophic systems of motion; a formula for the helicity flux across the upper boundary of the nonlinear Ekman boundary layer is given, and this flux is shown to be exactly compensated for by the helicity destruction inside the Ekman boundary layer.

Information processing using a single dynamical node as complex system

PubMed Central

Appeltant, L.; Soriano, M.C.; Van der Sande, G.; Danckaert, J.; Massar, S.; Dambre, J.; Schrauwen, B.; Mirasso, C.R.; Fischer, I.

2011-01-01

Novel methods for information processing are highly desired in our information-driven society. Inspired by the brain's ability to process information, the recently introduced paradigm known as 'reservoir computing' shows that complex networks can efficiently perform computation. Here we introduce a novel architecture that reduces the usually required large number of elements to a single nonlinear node with delayed feedback. Through an electronic implementation, we experimentally and numerically demonstrate excellent performance in a speech recognition benchmark. Complementary numerical studies also show excellent performance for a time series prediction benchmark. These results prove that delay-dynamical systems, even in their simplest manifestation, can perform efficient information processing. This finding paves the way to feasible and resource-efficient technological implementations of reservoir computing. PMID:21915110

Microbial Community Structures and Dynamics in the O3/BAC Drinking Water Treatment Process

PubMed Central

Tian, Jian; Lu, Jun; Zhang, Yu; Li, Jian-Cheng; Sun, Li-Chen; Hu, Zhang-Li

2014-01-01

Effectiveness of drinking water treatment, in particular pathogen control during the water treatment process, is always a major public health concern. In this investigation, the application of PCR-DGGE technology to the analysis of microbial community structures and dynamics in the drinking water treatment process revealed several dominant microbial populations including: α-Proteobacteria, β-Proteobacteria, γ-Proteobacteria, Bacteroidetes, Actinobacteria Firmicutes and Cyanobacteria. α-Proteobacteria and β-Proteobacteria were the dominant bacteria during the whole process. Bacteroidetes and Firmicutes were the dominant bacteria before and after treatment, respectively. Firmicutes showed season-dependent changes in population dynamics. Importantly, γ-Proteobacteria, which is a class of medically important bacteria, was well controlled by the O3/biological activated carbon (BAC) treatment, resulting in improved effluent water bio-safety. PMID:24937529

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

PubMed Central

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

2007-01-01

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

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

PubMed

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

2007-11-22

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

Dynamics of the process boom machine working equipment under the real law of the hydraulic distributor electric spool control

NASA Astrophysics Data System (ADS)

Tarasov, V. N.; Boyarkina, I. V.

2017-06-01

Analytical calculation methods of dynamic processes of the self-propelled boom hydraulic machines working equipment are more preferable in comparison with numerical methods. The analytical research method of dynamic processes of the boom hydraulic machines working equipment by means of differential equations of acceleration and braking of the working equipment is proposed. The real control law of a hydraulic distributor electric spool is considered containing the linear law of the electric spool activation and stepped law of the electric spool deactivation. Dependences of dynamic processes of the working equipment on reduced mass, stiffness of hydraulic power cylinder, viscous drag coefficient, piston acceleration, pressure in hydraulic cylinders, inertia force are obtained. Definite recommendations relative to the reduction of dynamic loads, appearing during the working equipment control are considered as the research result. The nature and rate of parameter variations of the speed and piston acceleration dynamic process depend on the law of the ports opening and closure of the hydraulic distributor electric spool. Dynamic loads in the working equipment are decreased during a smooth linear activation of the hydraulic distributor electric spool.

Spin-vibronic quantum dynamics for ultrafast excited-state processes.

PubMed

Eng, Julien; Gourlaouen, Christophe; Gindensperger, Etienne; Daniel, Chantal

2015-03-17

Ultrafast intersystem crossing (ISC) processes coupled to nuclear relaxation and solvation dynamics play a central role in the photophysics and photochemistry of a wide range of transition metal complexes. These phenomena occurring within a few hundred femtoseconds are investigated experimentally by ultrafast picosecond and femtosecond transient absorption or luminescence spectroscopies, and optical laser pump-X-ray probe techniques using picosecond and femtosecond X-ray pulses. The interpretation of ultrafast structural changes, time-resolved spectra, quantum yields, and time scales of elementary processes or transient lifetimes needs robust theoretical tools combining state-of-the-art quantum chemistry and developments in quantum dynamics for solving the electronic and nuclear problems. Multimode molecular dynamics beyond the Born-Oppenheimer approximation has been successfully applied to many small polyatomic systems. Its application to large molecules containing a transition metal atom is still a challenge because of the nuclear dimensionality of the problem, the high density of electronic excited states, and the spin-orbit coupling effects. Rhenium(I) α-diimine carbonyl complexes, [Re(L)(CO)3(N,N)](n+) are thermally and photochemically robust and highly flexible synthetically. Structural variations of the N,N and L ligands affect the spectroscopy, the photophysics, and the photochemistry of these chromophores easily incorporated into a complex environment. Visible light absorption opens the route to a wide range of applications such as sensors, probes, or emissive labels for imaging biomolecules. Halide complexes [Re(X)(CO)3(bpy)] (X = Cl, Br, or I; bpy = 2,2'-bipyridine) exhibit complex electronic structure and large spin-orbit effects that do not correlate with the heavy atom effects. Indeed, the (1)MLCT → (3)MLCT intersystem crossing (ISC) kinetics is slower than in [Ru(bpy)3](2+) or [Fe(bpy)3](2+) despite the presence of a third-row transition metal

A modified dynamical model of drying process of polymer blend solution coated on a flat substrate

NASA Astrophysics Data System (ADS)

Kagami, Hiroyuki

2008-05-01

We have proposed and modified a model of drying process of polymer solution coated on a flat substrate for flat polymer film fabrication. And for example numerical simulation of the model reproduces a typical thickness profile of the polymer film formed after drying. Then we have clarified dependence of distribution of polymer molecules on a flat substrate on a various parameters based on analysis of numerical simulations. Then we drove nonlinear equations of drying process from the dynamical model and the fruits were reported. The subject of above studies was limited to solution having one kind of solute though the model could essentially deal with solution having some kinds of solutes. But nowadays discussion of drying process of a solution having some kinds of solutes is needed because drying process of solution having some kinds of solutes appears in many industrial scenes. Polymer blend solution is one instance. And typical resist consists of a few kinds of polymers. Then we introduced a dynamical model of drying process of polymer blend solution coated on a flat substrate and results of numerical simulations of the dynamical model. But above model was the simplest one. In this study, we modify above dynamical model of drying process of polymer blend solution adding effects that some parameters change with time as functions of some variables to it. Then we consider essence of drying process of polymer blend solution through comparison between results of numerical simulations of the modified model and those of the former model.

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

DOE PAGES

Trivedi, Niraj; Ramahi, Joseph S.; Karakaya, Mahmut; ...

2014-12-02

During brain development, neurons migrate from germinal zones to their final positions to assemble neural circuits. A unique saltatory cadence involving cyclical organelle movement (e.g., centrosome motility) and leading-process actomyosin enrichment prior to nucleokinesis organizes neuronal migration. While functional evidence suggests that leading-process actomyosin is essential for centrosome motility, the role of the actin-enriched leading process in globally organizing organelle transport or traction forces remains unexplored. Our results show that myosin ii motors and F-actin dynamics are required for Golgi apparatus positioning before nucleokinesis in cerebellar granule neurons (CGNs) migrating along glial fibers. Moreover, we show that primary cilia aremore » motile organelles, localized to the leading-process F-actin-rich domain and immobilized by pharmacological inhibition of myosin ii and F-actin dynamics. Finally, leading process adhesion dynamics are dependent on myosin ii and F-actin. In conclusion, we propose that actomyosin coordinates the overall polarity of migrating CGNs by controlling asymmetric organelle positioning and cell-cell contacts as these cells move along their glial guides.« less

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

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

Trivedi, Niraj; Ramahi, Joseph S.; Karakaya, Mahmut

During brain development, neurons migrate from germinal zones to their final positions to assemble neural circuits. A unique saltatory cadence involving cyclical organelle movement (e.g., centrosome motility) and leading-process actomyosin enrichment prior to nucleokinesis organizes neuronal migration. While functional evidence suggests that leading-process actomyosin is essential for centrosome motility, the role of the actin-enriched leading process in globally organizing organelle transport or traction forces remains unexplored. Our results show that myosin ii motors and F-actin dynamics are required for Golgi apparatus positioning before nucleokinesis in cerebellar granule neurons (CGNs) migrating along glial fibers. Moreover, we show that primary cilia aremore » motile organelles, localized to the leading-process F-actin-rich domain and immobilized by pharmacological inhibition of myosin ii and F-actin dynamics. Finally, leading process adhesion dynamics are dependent on myosin ii and F-actin. In conclusion, we propose that actomyosin coordinates the overall polarity of migrating CGNs by controlling asymmetric organelle positioning and cell-cell contacts as these cells move along their glial guides.« less

Neural pathways in processing of sexual arousal: a dynamic causal modeling study.

PubMed

Seok, J-W; Park, M-S; Sohn, J-H

2016-09-01

Three decades of research have investigated brain processing of visual sexual stimuli with neuroimaging methods. These researchers have found that sexual arousal stimuli elicit activity in a broad neural network of cortical and subcortical brain areas that are known to be associated with cognitive, emotional, motivational and physiological components. However, it is not completely understood how these neural systems integrate and modulated incoming information. Therefore, we identify cerebral areas whose activations were correlated with sexual arousal using event-related functional magnetic resonance imaging and used the dynamic causal modeling method for searching the effective connectivity about the sexual arousal processing network. Thirteen heterosexual males were scanned while they passively viewed alternating short trials of erotic and neutral pictures on a monitor. We created a subset of seven models based on our results and previous studies and selected a dominant connectivity model. Consequently, we suggest a dynamic causal model of the brain processes mediating the cognitive, emotional, motivational and physiological factors of human male sexual arousal. These findings are significant implications for the neuropsychology of male sexuality.

Collisional and dynamical processes in moon and planet formation

NASA Technical Reports Server (NTRS)

1979-01-01

The collisional and dynamical processes in moon and planet formation are discussed. A hydrodynamic code of collision calculations, the orbital element changes due to gravitational scattering, a validation of the mass shifting algorithm, a theory of rotations, and the origin of asteroids are studied. A numerical model of planet growth is discussed and a methodology to evaluate the rate at which megaregolith increases its depth as a function of total accumulate number of impacts on an initially smooth, coherent surface is described.

Attractor Dynamics and Semantic Neighborhood Density: Processing Is Slowed by Near Neighbors and Speeded by Distant Neighbors

PubMed Central

Mirman, Daniel; Magnuson, James S.

2008-01-01

The authors investigated semantic neighborhood density effects on visual word processing to examine the dynamics of activation and competition among semantic representations. Experiment 1 validated feature-based semantic representations as a basis for computing semantic neighborhood density and suggested that near and distant neighbors have opposite effects on word processing. Experiment 2 confirmed these results: Word processing was slower for dense near neighborhoods and faster for dense distant neighborhoods. Analysis of a computational model showed that attractor dynamics can produce this pattern of neighborhood effects. The authors argue for reconsideration of traditional models of neighborhood effects in terms of attractor dynamics, which allow both inhibitory and facilitative effects to emerge. PMID:18194055

A Dynamic Process Model for Optimizing the Hospital Environment Cash-Flow

NASA Astrophysics Data System (ADS)

Pater, Flavius; Rosu, Serban

2011-09-01

In this article is presented a new approach to some fundamental techniques of solving dynamic programming problems with the use of functional equations. We will analyze the problem of minimizing the cost of treatment in a hospital environment. Mathematical modeling of this process leads to an optimal control problem with a finite horizon.

Mammal population regulation, keystone processes and ecosystem dynamics.

PubMed Central

Sinclair, A R E

2003-01-01

The theory of regulation in animal populations is fundamental to understanding the dynamics of populations, the causes of mortality and how natural selection shapes the life history of species. In mammals, the great range in body size allows us to see how allometric relationships affect the mode of regulation. Resource limitation is the fundamental cause of regulation. Top-down limitation through predators is determined by four factors: (i). body size; (ii). the diversity of predators and prey in the system; (iii). whether prey are resident or migratory; and (iv). the presence of alternative prey for predators. Body size in mammals has two important consequences. First, mammals, particularly large species, can act as keystones that determine the diversity of an ecosystem. I show how keystone processes can, in principle, be measured using the example of the wildebeest in the Serengeti ecosystem. Second, mammals act as ecological landscapers by altering vegetation succession. Mammals alter physical structure, ecological function and species diversity in most terrestrial biomes. In general, there is a close interaction between allometry, population regulation, life history and ecosystem dynamics. These relationships are relevant to applied aspects of conservation and pest management. PMID:14561329

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).

Signal Processing for Determining Water Height in Steam Pipes with Dynamic Surface Conditions

NASA Technical Reports Server (NTRS)

Lih, Shyh-Shiuh; Lee, Hyeong Jae; Bar-Cohen, Yoseph

2015-01-01

An enhanced signal processing method based on the filtered Hilbert envelope of the auto-correlation function of the wave signal has been developed to monitor the height of condensed water through the steel wall of steam pipes with dynamic surface conditions. The developed signal processing algorithm can also be used to estimate the thickness of the pipe to determine the cut-off frequency for the low pass filter frequency of the Hilbert Envelope. Testing and analysis results by using the developed technique for dynamic surface conditions are presented. A multiple array of transducers setup and methodology are proposed for both the pulse-echo and pitch-catch signals to monitor the fluctuation of the water height due to disturbance, water flow, and other anomaly conditions.

Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.

PubMed

Shi, Junxing; Wen, Haiguang; Zhang, Yizhen; Han, Kuan; Liu, Zhongming

2018-05-01

The human visual cortex extracts both spatial and temporal visual features to support perception and guide behavior. Deep convolutional neural networks (CNNs) provide a computational framework to model cortical representation and organization for spatial visual processing, but unable to explain how the brain processes temporal information. To overcome this limitation, we extended a CNN by adding recurrent connections to different layers of the CNN to allow spatial representations to be remembered and accumulated over time. The extended model, or the recurrent neural network (RNN), embodied a hierarchical and distributed model of process memory as an integral part of visual processing. Unlike the CNN, the RNN learned spatiotemporal features from videos to enable action recognition. The RNN better predicted cortical responses to natural movie stimuli than the CNN, at all visual areas, especially those along the dorsal stream. As a fully observable model of visual processing, the RNN also revealed a cortical hierarchy of temporal receptive window, dynamics of process memory, and spatiotemporal representations. These results support the hypothesis of process memory, and demonstrate the potential of using the RNN for in-depth computational understanding of dynamic natural vision. © 2018 Wiley Periodicals, Inc.

Does dynamic information about the speaker's face contribute to semantic speech processing? ERP evidence.

PubMed

Hernández-Gutiérrez, David; Abdel Rahman, Rasha; Martín-Loeches, Manuel; Muñoz, Francisco; Schacht, Annekathrin; Sommer, Werner

2018-07-01

Face-to-face interactions characterize communication in social contexts. These situations are typically multimodal, requiring the integration of linguistic auditory input with facial information from the speaker. In particular, eye gaze and visual speech provide the listener with social and linguistic information, respectively. Despite the importance of this context for an ecological study of language, research on audiovisual integration has mainly focused on the phonological level, leaving aside effects on semantic comprehension. Here we used event-related potentials (ERPs) to investigate the influence of facial dynamic information on semantic processing of connected speech. Participants were presented with either a video or a still picture of the speaker, concomitant to auditory sentences. Along three experiments, we manipulated the presence or absence of the speaker's dynamic facial features (mouth and eyes) and compared the amplitudes of the semantic N400 elicited by unexpected words. Contrary to our predictions, the N400 was not modulated by dynamic facial information; therefore, semantic processing seems to be unaffected by the speaker's gaze and visual speech. Even though, during the processing of expected words, dynamic faces elicited a long-lasting late posterior positivity compared to the static condition. This effect was significantly reduced when the mouth of the speaker was covered. Our findings may indicate an increase of attentional processing to richer communicative contexts. The present findings also demonstrate that in natural communicative face-to-face encounters, perceiving the face of a speaker in motion provides supplementary information that is taken into account by the listener, especially when auditory comprehension is non-demanding. Copyright © 2018 Elsevier Ltd. All rights reserved.

Reduced-order model for dynamic optimization of pressure swing adsorption processes

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

Agarwal, A.; Biegler, L.; Zitney, S.

2007-01-01

Over the past decades, pressure swing adsorption (PSA) processes have been widely used as energy-efficient gas and liquid separation techniques, especially for high purity hydrogen purification from refinery gases. The separation processes are based on solid-gas equilibrium and operate under periodic transient conditions. Models for PSA processes are therefore multiple instances of partial differential equations (PDEs) in time and space with periodic boundary conditions that link the processing steps together. The solution of this coupled stiff PDE system is governed by steep concentrations and temperature fronts moving with time. As a result, the optimization of such systems for either designmore » or operation represents a significant computational challenge to current differential algebraic equation (DAE) optimization techniques and nonlinear programming algorithms. Model reduction is one approach to generate cost-efficient low-order models which can be used as surrogate models in the optimization problems. The study develops a reduced-order model (ROM) based on proper orthogonal decomposition (POD), which is a low-dimensional approximation to a dynamic PDE-based model. Initially, a representative ensemble of solutions of the dynamic PDE system is constructed by solving a higher-order discretization of the model using the method of lines, a two-stage approach that discretizes the PDEs in space and then integrates the resulting DAEs over time. Next, the ROM method applies the Karhunen-Loeve expansion to derive a small set of empirical eigenfunctions (POD modes) which are used as basis functions within a Galerkin's projection framework to derive a low-order DAE system that accurately describes the dominant dynamics of the PDE system. The proposed method leads to a DAE system of significantly lower order, thus replacing the one obtained from spatial discretization before and making optimization problem computationally-efficient. The method has been applied to the

Evolution in Mind: Evolutionary Dynamics, Cognitive Processes, and Bayesian Inference.

PubMed

Suchow, Jordan W; Bourgin, David D; Griffiths, Thomas L

2017-07-01

Evolutionary theory describes the dynamics of population change in settings affected by reproduction, selection, mutation, and drift. In the context of human cognition, evolutionary theory is most often invoked to explain the origins of capacities such as language, metacognition, and spatial reasoning, framing them as functional adaptations to an ancestral environment. However, evolutionary theory is useful for understanding the mind in a second way: as a mathematical framework for describing evolving populations of thoughts, ideas, and memories within a single mind. In fact, deep correspondences exist between the mathematics of evolution and of learning, with perhaps the deepest being an equivalence between certain evolutionary dynamics and Bayesian inference. This equivalence permits reinterpretation of evolutionary processes as algorithms for Bayesian inference and has relevance for understanding diverse cognitive capacities, including memory and creativity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Unraveling the sub-processes of selective attention: insights from dynamic modeling and continuous behavior.

PubMed

Frisch, Simon; Dshemuchadse, Maja; Görner, Max; Goschke, Thomas; Scherbaum, Stefan

2015-11-01

Selective attention biases information processing toward stimuli that are relevant for achieving our goals. However, the nature of this bias is under debate: Does it solely rely on the amplification of goal-relevant information or is there a need for additional inhibitory processes that selectively suppress currently distracting information? Here, we explored the processes underlying selective attention with a dynamic, modeling-based approach that focuses on the continuous evolution of behavior over time. We present two dynamic neural field models incorporating the diverging theoretical assumptions. Simulations with both models showed that they make similar predictions with regard to response times but differ markedly with regard to their continuous behavior. Human data observed via mouse tracking as a continuous measure of performance revealed evidence for the model solely based on amplification but no indication of persisting selective distracter inhibition.

Living in the branches: population dynamics and ecological processes in dendritic networks

USGS Publications Warehouse

Grant, E.H.C.; Lowe, W.H.; Fagan, W.F.

2007-01-01

Spatial structure regulates and modifies processes at several levels of ecological organization (e.g. individual/genetic, population and community) and is thus a key component of complex systems, where knowledge at a small scale can be insufficient for understanding system behaviour at a larger scale. Recent syntheses outline potential applications of network theory to ecological systems, but do not address the implications of physical structure for network dynamics. There is a specific need to examine how dendritic habitat structure, such as that found in stream, hedgerow and cave networks, influences ecological processes. Although dendritic networks are one type of ecological network, they are distinguished by two fundamental characteristics: (1) both the branches and the nodes serve as habitat, and (2) the specific spatial arrangement and hierarchical organization of these elements interacts with a species' movement behaviour to alter patterns of population distribution and abundance, and community interactions. Here, we summarize existing theory relating to ecological dynamics in dendritic networks, review empirical studies examining the population- and community-level consequences of these networks, and suggest future research integrating spatial pattern and processes in dendritic systems.

Dynamic deformation image de-blurring and image processing for digital imaging correlation measurement

NASA Astrophysics Data System (ADS)

Guo, X.; Li, Y.; Suo, T.; Liu, H.; Zhang, C.

2017-11-01

This paper proposes a method for de-blurring of images captured in the dynamic deformation of materials. De-blurring is achieved based on the dynamic-based approach, which is used to estimate the Point Spread Function (PSF) during the camera exposure window. The deconvolution process involving iterative matrix calculations of pixels, is then performed on the GPU to decrease the time cost. Compared to the Gauss method and the Lucy-Richardson method, it has the best result of the image restoration. The proposed method has been evaluated by using the Hopkinson bar loading system. In comparison to the blurry image, the proposed method has successfully restored the image. It is also demonstrated from image processing applications that the de-blurring method can improve the accuracy and the stability of the digital imaging correlation measurement.

Instantaneous nonlinear assessment of complex cardiovascular dynamics by Laguerre-Volterra point process models.

PubMed

Valenza, Gaetano; Citi, Luca; Barbieri, Riccardo

2013-01-01

We report an exemplary study of instantaneous assessment of cardiovascular dynamics performed using point-process nonlinear models based on Laguerre expansion of the linear and nonlinear Wiener-Volterra kernels. As quantifiers, instantaneous measures such as high order spectral features and Lyapunov exponents can be estimated from a quadratic and cubic autoregressive formulation of the model first order moment, respectively. Here, these measures are evaluated on heartbeat series coming from 16 healthy subjects and 14 patients with Congestive Hearth Failure (CHF). Data were gathered from the on-line repository PhysioBank, which has been taken as landmark for testing nonlinear indices. Results show that the proposed nonlinear Laguerre-Volterra point-process methods are able to track the nonlinear and complex cardiovascular dynamics, distinguishing significantly between CHF and healthy heartbeat series.

Analysis of the Implementation of a Dynamic Assessment Device of Processes Involved in Reading with Learning-Disabled Children

ERIC Educational Resources Information Center

Navarro, Juan-Jose; Mora, Joaquin

2011-01-01

The renewed interest in the dynamic assessment of specific domains has led to reconsideration of this theory and the technique's contribution to the learning-teaching process. In this article, we analyze some elements concerning the internal structure of a dynamic assessment device of processes involved in reading tasks, establishing some of the…

Effect of river flow fluctuations on riparian vegetation dynamics: Processes and models

NASA Astrophysics Data System (ADS)

Vesipa, Riccardo; Camporeale, Carlo; Ridolfi, Luca

2017-12-01

Several decades of field observations, laboratory experiments and mathematical modelings have demonstrated that the riparian environment is a disturbance-driven ecosystem, and that the main source of disturbance is river flow fluctuations. The focus of the present work has been on the key role that flow fluctuations play in determining the abundance, zonation and species composition of patches of riparian vegetation. To this aim, the scientific literature on the subject, over the last 20 years, has been reviewed. First, the most relevant ecological, morphological and chemical mechanisms induced by river flow fluctuations are described from a process-based perspective. The role of flow variability is discussed for the processes that affect the recruitment of vegetation, the vegetation during its adult life, and the morphological and nutrient dynamics occurring in the riparian habitat. Particular emphasis has been given to studies that were aimed at quantifying the effect of these processes on vegetation, and at linking them to the statistical characteristics of the river hydrology. Second, the advances made, from a modeling point of view, have been considered and discussed. The main models that have been developed to describe the dynamics of riparian vegetation have been presented. Different modeling approaches have been compared, and the corresponding advantages and drawbacks have been pointed out. Finally, attention has been paid to identifying the processes considered by the models, and these processes have been compared with those that have actually been observed or measured in field/laboratory studies.

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.

Extended Closed-form Expressions for the Robust Symmetrical Number System Dynamic Range and an Efficient Algorithm for its Computation

DTIC Science & Technology

2014-01-01

and distance between all of the vector ambiguity pairs for the combined N−sequences. To simplify our derivation, we define the center of ambiguity (COA...modulo N . The resulting structure of the N sequences ensures that two successive RSNS vectors (paired terms from all N sequences) when considered...represented by a vector , Xh = [x1,h, x2,h, . . . , xN,h] T , of N paired integers from each se- quence at h. For example, a left-shifted, three-sequence

Explosive synchronization as a process of explosive percolation in dynamical phase space

PubMed Central

Zhang, Xiyun; Zou, Yong; Boccaletti, S.; Liu, Zonghua

2014-01-01

Explosive synchronization and explosive percolation are currently two independent phenomena occurring in complex networks, where the former takes place in dynamical phase space while the latter in configuration space. It has been revealed that the mechanism of EP can be explained by the Achlioptas process, where the formation of a giant component is controlled by a suppressive rule. We here introduce an equivalent suppressive rule for ES. Before the critical point of ES, the suppressive rule induces the presence of multiple, small sized, synchronized clusters, while inducing the abrupt formation of a giant cluster of synchronized oscillators at the critical coupling strength. We also show how the explosive character of ES degrades into a second-order phase transition when the suppressive rule is broken. These results suggest that our suppressive rule can be considered as a dynamical counterpart of the Achlioptas process, indicating that ES and EP can be unified into a same framework. PMID:24903808

Dynamic Computation of Change Operations in Version Management of Business Process Models

NASA Astrophysics Data System (ADS)

Küster, Jochen Malte; Gerth, Christian; Engels, Gregor

Version management of business process models requires that changes can be resolved by applying change operations. In order to give a user maximal freedom concerning the application order of change operations, position parameters of change operations must be computed dynamically during change resolution. In such an approach, change operations with computed position parameters must be applicable on the model and dependencies and conflicts of change operations must be taken into account because otherwise invalid models can be constructed. In this paper, we study the concept of partially specified change operations where parameters are computed dynamically. We provide a formalization for partially specified change operations using graph transformation and provide a concept for their applicability. Based on this, we study potential dependencies and conflicts of change operations and show how these can be taken into account within change resolution. Using our approach, a user can resolve changes of business process models without being unnecessarily restricted to a certain order.

Computational fluid dynamics modelling of hydraulics and sedimentation in process reactors during aeration tank settling.

PubMed

Jensen, M D; Ingildsen, P; Rasmussen, M R; Laursen, J

2006-01-01

Aeration tank settling is a control method allowing settling in the process tank during high hydraulic load. The control method is patented. Aeration tank settling has been applied in several waste water treatment plants using the present design of the process tanks. Some process tank designs have shown to be more effective than others. To improve the design of less effective plants, computational fluid dynamics (CFD) modelling of hydraulics and sedimentation has been applied. This paper discusses the results at one particular plant experiencing problems with partly short-circuiting of the inlet and outlet causing a disruption of the sludge blanket at the outlet and thereby reducing the retention of sludge in the process tank. The model has allowed us to establish a clear picture of the problems arising at the plant during aeration tank settling. Secondly, several process tank design changes have been suggested and tested by means of computational fluid dynamics modelling. The most promising design changes have been found and reported.

Interacting Learning Processes during Skill Acquisition: Learning to control with gradually changing system dynamics.

PubMed

Ludolph, Nicolas; Giese, Martin A; Ilg, Winfried

2017-10-16

There is increasing evidence that sensorimotor learning under real-life conditions relies on a composition of several learning processes. Nevertheless, most studies examine learning behaviour in relation to one specific learning mechanism. In this study, we examined the interaction between reward-based skill acquisition and motor adaptation to changes of object dynamics. Thirty healthy subjects, split into two groups, acquired the skill of balancing a pole on a cart in virtual reality. In one group, we gradually increased the gravity, making the task easier in the beginning and more difficult towards the end. In the second group, subjects had to acquire the skill on the maximum, most difficult gravity level. We hypothesized that the gradual increase in gravity during skill acquisition supports learning despite the necessary adjustments to changes in cart-pole dynamics. We found that the gradual group benefits from the slow increment, although overall improvement was interrupted by the changes in gravity and resulting system dynamics, which caused short-term degradations in performance and timing of actions. In conclusion, our results deliver evidence for an interaction of reward-based skill acquisition and motor adaptation processes, which indicates the importance of both processes for the development of optimized skill acquisition schedules.

Processes and Dynamics behind Whole-School Reform: Nine-Year Journeys of Four Primary Schools

ERIC Educational Resources Information Center

Li, Yuk Yung

2017-01-01

Despite decades of research, little is known about the dynamics of sustaining change in school reform and how the process of change unfolds. By tracing the nine-year reform journeys of four primary schools in Hong Kong (using multiyear interview, observational, and archival data), this study uncovers the micro-processes the schools experienced…

Alignment of process compliance and monitoring requirements in dynamic business collaborations

NASA Astrophysics Data System (ADS)

Comuzzi, Marco

2017-07-01

Dynamic business collaborations are intrinsically characterised by change because processes can be distributed or outsourced and partners may be substituted by new ones with enhanced or different capabilities. In this context, compliance requirements management becomes particularly challenging. Partners in a collaboration may join and leave dynamically and tasks over which compliance requirements are specified may be consequently distributed or delegated to new partners. This article considers the issue of aligning compliance requirements in a dynamic business collaboration with the monitoring requirements induced on the collaborating partners when change occurs. We first provide a conceptual model of business collaborations and their compliance requirements, introducing the concept of monitoring capabilities induced by compliance requirements. Then, we present a set of mechanisms to ensure consistency between monitoring and compliance requirements in the presence of change, e.g. when tasks are delegated or backsourced in-house. We also discuss a set of metrics to evaluate the status of a collaboration in respect of compliance monitorability. Finally, we discuss a prototype implementation of our framework.

Cortical processing of dynamic sound envelope transitions.

PubMed

Zhou, Yi; Wang, Xiaoqin

2010-12-08

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

Reactive Molecular Dynamics Investigations of Alkoxysilane Sol-Gel and Surface Coating Processes

NASA Astrophysics Data System (ADS)

Deetz, Joshua David

The ability to generate nanostructured materials with tailored morphology or chemistry is of great technological interest. One proven method of generating metal-oxide materials, and chemically modifying metal-oxide surfaces is through the reactions of molecular building blocks known as alkoxysilanes. Alkoxysilanes are a class of chemicals which contain one or more organic alkoxy groups bonded to silicon atoms. Alkoxysilane (Si-O-R) chemical groups can undergo reactions to form bridges (Si-O-M) with metal oxides. Due to their ability to "attach" to metal-oxides through condensation reactions, alkoxysilanes have a number of interesting applications, such as: the generation of synthetic siloxane materials through the sol-gel process, and the formation of functionalized surface coatings on metal-oxide surfaces. Despite widespread study of sol-gel and surface coatings processes, it is difficult to predict the morphology of the final products due to the large number of process variables involved, such as precursor molecule structure, solvent effects, solution composition, temperature, and pH. To determine the influence of these variables on the products of sol-gel and coatings processes reactive molecular dynamics simulations are used. A reactive force field was used (ReaxFF) to allow the chemical bonds in simulation to dynamically form and break. The force field parameters were optimized using a parallel optimization scheme with a combination of experimental information, and density functional theory calculations. Polycondensation of alkoxysilanes in mixtures of alcohol and water were studied. Steric effects were observed to influence the rates of hydrolysis and condensation in solutions containing different precursor monomers. By restricting the access of nucleophiles to the central silicon atom, the nucleation rate of siloxanes can be controlled. The influence of solution precursor, water, and methanol composition on reaction rates was explored. It was determined that

Transfer RNA Post-Transcriptional Processing, Turnover, and Subcellular Dynamics in the Yeast Saccharomyces cerevisiae

PubMed Central

Hopper, Anita K.

2013-01-01

Transfer RNAs (tRNAs) are essential for protein synthesis. In eukaryotes, tRNA biosynthesis employs a specialized RNA polymerase that generates initial transcripts that must be subsequently altered via a multitude of post-transcriptional steps before the tRNAs beome mature molecules that function in protein synthesis. Genetic, genomic, biochemical, and cell biological approaches possible in the powerful Saccharomyces cerevisiae system have led to exciting advances in our understandings of tRNA post-transcriptional processing as well as to novel insights into tRNA turnover and tRNA subcellular dynamics. tRNA processing steps include removal of transcribed leader and trailer sequences, addition of CCA to the 3′ mature sequence and, for tRNAHis, addition of a 5′ G. About 20% of yeast tRNAs are encoded by intron-containing genes. The three-step splicing process to remove the introns surprisingly occurs in the cytoplasm in yeast and each of the splicing enzymes appears to moonlight in functions in addition to tRNA splicing. There are 25 different nucleoside modifications that are added post-transcriptionally, creating tRNAs in which ∼15% of the residues are nucleosides other than A, G, U, or C. These modified nucleosides serve numerous important functions including tRNA discrimination, translation fidelity, and tRNA quality control. Mature tRNAs are very stable, but nevertheless yeast cells possess multiple pathways to degrade inappropriately processed or folded tRNAs. Mature tRNAs are also dynamic in cells, moving from the cytoplasm to the nucleus and back again to the cytoplasm; the mechanism and function of this retrograde process is poorly understood. Here, the state of knowledge for tRNA post-transcriptional processing, turnover, and subcellular dynamics is addressed, highlighting the questions that remain. PMID:23633143

All-digital signal-processing open-loop fiber-optic gyroscope with enlarged dynamic range.

PubMed

Wang, Qin; Yang, Chuanchuan; Wang, Xinyue; Wang, Ziyu

2013-12-15

We propose and realize a new open-loop fiber-optic gyroscope (FOG) with an all-digital signal-processing (DSP) system where an all-digital phase-locked loop is employed for digital demodulation to eliminate the variation of the source intensity and suppress the bias drift. A Sagnac phase-shift tracking method is proposed to enlarge the dynamic range, and, with its aid, a new open-loop FOG, which can achieve a large dynamic range and high sensitivity at the same time, is realized. The experimental results show that compared with the conventional open-loop FOG with the same fiber coil and optical devices, the proposed FOG reduces the bias instability from 0.259 to 0.018 deg/h, and the angle random walk from 0.031 to 0.006 deg/h(1/2), moreover, enlarges the dynamic range to ±360 deg/s, exceeding the maximum dynamic range ±63 deg/s of the conventional open-loop FOG.

Markov Processes: Exploring the Use of Dynamic Visualizations to Enhance Student Understanding

ERIC Educational Resources Information Center

Pfannkuch, Maxine; Budgett, Stephanie

2016-01-01

Finding ways to enhance introductory students' understanding of probability ideas and theory is a goal of many first-year probability courses. In this article, we explore the potential of a prototype tool for Markov processes using dynamic visualizations to develop in students a deeper understanding of the equilibrium and hitting times…

Aerosol processing of materials: Aerosol dynamics and microstructure evolution

NASA Astrophysics Data System (ADS)

Gurav, Abhijit Shankar

Spray pyrolysis is an aerosol process commonly used to synthesize a wide variety of materials in powder or film forms including metals, metal oxides and non-oxide ceramics. It is capable of producing high purity, unagglomerated, and micrometer to submicron-size powders, and scale-up has been demonstrated. This dissertation deals with the study of aerosol dynamics during spray pyrolysis of multicomponent systems involving volatile phases/components, and aspects involved with using fuel additives during spray processes to break apart droplets and particles in order to produce powders with smaller sizes. The gas-phase aerosol dynamics and composition size distributions were measured during spray pyrolysis of (Bi, Pb)-Sr-Ca-Cu-O, and Sr-Ru-O and Bi-Ru-O at different temperatures. A differential mobility analyzer (DMA) was used in conjunction with a condensation particle counter (CPC) to monitor the gas-phase particle size distributions, and a Berner-type low-pressure impactor was used to obtain mass size distributions and size-classified samples for chemical analysis. (Bi, Pb)-Sr-Ca-Cu-O powders made at temperatures up to 700sp°C maintained their initial stoichiometry over the whole range of particle sizes monitored, however, those made at 800sp°C and above were heavily depleted in lead in the size range 0.5-5.0 mum. When the reactor temperature was raised from 700 and 800sp°C to 900sp°C, a large number ({˜}10sp7\\ #/cmsp3) of new ultrafine particles were formed from PbO vapor released from the particles and the reactor walls at the beginning of high temperature runs (at 900sp°C). The metal ruthenate systems showed generation of ultrafine particles (<40-50 nm) at the beginning of runs at 800-900sp°C and also as a steady state process at a reactor temperature of 1000sp°C. The methods of aerosol dynamics measurements were also used to monitor the gas-phase particle size distributions during the generation of fullerene (Csb{60}) nano-particles (30 to 50 nm size

Fuzzy and process modelling of contour ridge water dynamics

NASA Astrophysics Data System (ADS)

Mhizha, Alexander; Ndiritu, John

2018-05-01

Contour ridges are an in-situ rainwater harvesting technology developed initially for soil erosion control but are currently also widely promoted for rainwater harvesting. The effectiveness of contour ridges depends on geophysical, hydro-climatic and socio economic factors that are highly varied in time and space. Furthermore, field-scale data on these factors are often unavailable. This together with the complexity of hydrological processes at field scale limits the application of classical distributed process modelling to highly-instrumented experimental fields. This paper presents a framework that combines fuzzy logic and process-based approach for modelling contour ridges for rainwater harvesting where detailed field data are not available. Water balance for a representative contour-ridged field incorporating the water flow processes across the boundaries is integrated with fuzzy logic to incorporate the uncertainties in estimating runoff. The model is tested using data collected during the 2009/2010 and 2010/2011 rainfall seasons from two contour-ridged fields in Zhulube located in the semi-arid parts of Zimbabwe. The model is found to replicate soil moisture in the root zone reasonably well (NSE = 0.55 to 0.66 and PBIAS = -1.3 to 6.1 %). The results show that combining fuzzy logic and process based approaches can adequately model soil moisture in a contour ridged-field and could help to assess the water dynamics in contour ridged fields.

Studies of dynamic processes in biomedicine by high-speed spectral optical coherence tomography

NASA Astrophysics Data System (ADS)

Wojtkowski, M.; Kowalczyk, A.

2007-02-01

This contribution demonstrates potential of Spectral Optical Coherence Tomography (SOCT) for studies of dynamic processes in biomedicine occurring at various time scales. Several examples from ophthalmology, optometry, surgery, neurology are given to illustrate the extension of SOCT beyond pure morphological investigations.

Systemic Case Formulation, Individualized Process Monitoring, and State Dynamics in a Case of Dissociative Identity Disorder.

PubMed

Schiepek, Günter K; Stöger-Schmidinger, Barbara; Aichhorn, Wolfgang; Schöller, Helmut; Aas, Benjamin

2016-01-01

Objective: The aim of this case report is to demonstrate the feasibility of a systemic procedure (synergetic process management) including modeling of the idiographic psychological system and continuous high-frequency monitoring of change dynamics in a case of dissociative identity disorder. The psychotherapy was realized in a day treatment center with a female client diagnosed with borderline personality disorder (BPD) and dissociative identity disorder. Methods: A three hour long co-creative session at the beginning of the treatment period allowed for modeling the systemic network of the client's dynamics of cognitions, emotions, and behavior. The components (variables) of this idiographic system model (ISM) were used to create items for an individualized process questionnaire for the client. The questionnaire was administered daily through an internet-based monitoring tool (Synergetic Navigation System, SNS), to capture the client's individual change process continuously throughout the therapy and after-care period. The resulting time series were reflected by therapist and client in therapeutic feedback sessions. Results: For the client it was important to see how the personality states dominating her daily life were represented by her idiographic system model and how the transitions between each state could be explained and understood by the activating and inhibiting relations between the cognitive-emotional components of that system. Continuous monitoring of her cognitions, emotions, and behavior via SNS allowed for identification of important triggers, dynamic patterns, and psychological mechanisms behind seemingly erratic state fluctuations. These insights enabled a change in management of the dynamics and an intensified trauma-focused therapy. Conclusion: By making use of the systemic case formulation technique and subsequent daily online monitoring, client and therapist continuously refer to detailed visualizations of the mental and behavioral network and

Dynamic frontotemporal systems process space and time in working memory

PubMed Central

Adams, Jenna N.; Solbakk, Anne-Kristin; Endestad, Tor; Larsson, Pål G.; Ivanovic, Jugoslav; Meling, Torstein R.; Lin, Jack J.; Knight, Robert T.

2018-01-01

How do we rapidly process incoming streams of information in working memory, a cognitive mechanism central to human behavior? Dominant views of working memory focus on the prefrontal cortex (PFC), but human hippocampal recordings provide a neurophysiological signature distinct from the PFC. Are these regions independent, or do they interact in the service of working memory? We addressed this core issue in behavior by recording directly from frontotemporal sites in humans performing a visuospatial working memory task that operationalizes the types of identity and spatiotemporal information we encounter every day. Theta band oscillations drove bidirectional interactions between the PFC and medial temporal lobe (MTL; including the hippocampus). MTL theta oscillations directed the PFC preferentially during the processing of spatiotemporal information, while PFC theta oscillations directed the MTL for all types of information being processed in working memory. These findings reveal an MTL theta mechanism for processing space and time and a domain-general PFC theta mechanism, providing evidence that rapid, dynamic MTL–PFC interactions underlie working memory for everyday experiences. PMID:29601574

A molecular dynamics simulation study of dynamic process and mesoscopic structure in liquid mixture systems

NASA Astrophysics Data System (ADS)

Yang, Peng

The focus of this dissertation is the Molecular Dynamics (MD) simulation study of two different systems. In thefirst system, we study the dynamic process of graphene exfoliation, particularly graphene dispersion using ionic surfactants (Chapter 2). In the second system, we investigate the mesoscopic structure of binary solute/ionic liquid (IL) mixtures through the comparison between simulations and corresponding experiments (Chapter 3 and 4). In the graphene exfoliation study, we consider two separation mechanisms: changing the interlayer distance and sliding away the relative distance of two single-layer graphene sheets. By calculating the energy barrier as a function of separation (interlayer or sliding-away) distance and performing sodium dodecyl sulfate (SDS) structure analysis around graphene surface in SDS surfactant/water + bilayer graphene mixture systems, we find that the sliding-away mechanism is the dominant, feasible separation process. In this process, the SDS-graphene interaction gradually replaces the graphene-graphene Van der Waals (VdW) interaction, and decreases the energy barrier until almost zero at critical SDS concentration. In solute/IL study, we investigate nonpolar (CS2) and dipolar (CH 3CN) solute/IL mixture systems. MD simulation shows that at low concentrations, IL is nanosegregated into an ionic network and nonpolar domain. It is also found that CS2 molecules tend to be localized into the nonpolar domain, while CH3CN interacts with nonpolar domain as well as with the charged head groups in the ionic network because of its amphiphilicity. At high concentrations, CH3CN molecules eventually disrupt the nanostructural organization. This dissertation is organized in four chapters: (1) introduction to graphene, ionic liquids and the methodology of MD; (2) MD simulation of graphene exfoliation; (3) Nanostructural organization in acetonitrile/IL mixtures; (4) Nanostructural organization in carbon disulfide/IL mixtures; (5) Conclusions. Results

Dynamic laser beam shaping for material processing using hybrid holograms

NASA Astrophysics Data System (ADS)

Liu, Dun; Wang, Yutao; Zhai, Zhongsheng; Fang, Zheng; Tao, Qing; Perrie, Walter; Edwarson, Stuart P.; Dearden, Geoff

2018-06-01

A high quality, dynamic laser beam shaping method is demonstrated by displaying a series of hybrid holograms onto a spatial light modulator (SLM), while each one of the holograms consists of a binary grating and a geometric mask. A diffraction effect around the shaped beam has been significantly reduced. Beam profiles of arbitrary shape, such as square, ring, triangle, pentagon and hexagon, can be conveniently obtained by loading the corresponding holograms on the SLM. The shaped beam can be reconstructed in the range of 0.5 mm at the image plane. Ablation on a polished stainless steel sample at the image plane are consistent with the beam shape at the diffraction near-field. The ±1st order and higher order beams can be completely removed when the grating period is smaller than 160 μm. The local energy ratio of the shaped beam observed by the CCD camera is up to 77.67%. Dynamic processing at 25 Hz using different shapes has also been achieved.

Characteristics and Concepts of Dynamic Hub Proteins in DNA Processing Machinery from Studies of RPA

PubMed Central

Sugitani, Norie; Chazin, Walter J.

2015-01-01

DNA replication, damage response and repair require the coordinated action of multi-domain proteins operating within dynamic multi-protein machines that act upon the DNA substrate. These modular proteins contain flexible linkers of various lengths, which enable changes in the spatial distribution of the globular domains (architecture) that harbor their essential biochemical functions. This mobile architecture is uniquely suited to follow the evolving substrate landscape present over the course of the specific process performed by the multi-protein machinery. A fundamental advance in understanding of protein machinery is the realization of the pervasive role of dynamics. Not only is the machine undergoing dynamic transformations, but the proteins themselves are flexible and constantly adapting to the progression through the steps of the overall process. Within this dynamic context the activity of the constituent proteins must be coordinated, a role typically played by hub proteins. A number of important characteristics of modular proteins and concepts about the operation of dynamic machinery have been discerned. These provide the underlying basis for the action of the machinery that reads DNA, and responds to and repairs DNA damage. Here, we introduce a number of key characteristics and concepts, including the modularity of the proteins, linkage of weak binding sites, direct competition between sites, and allostery, using the well recognized hub protein replication protein A (RPA). PMID:25542993

Pre-eruptive magmatic processes re-timed using a non-isothermal approach to magma chamber dynamics.

PubMed

Petrone, Chiara Maria; Bugatti, Giuseppe; Braschi, Eleonora; Tommasini, Simone

2016-10-05

Constraining the timescales of pre-eruptive magmatic processes in active volcanic systems is paramount to understand magma chamber dynamics and the triggers for volcanic eruptions. Temporal information of magmatic processes is locked within the chemical zoning profiles of crystals but can be accessed by means of elemental diffusion chronometry. Mineral compositional zoning testifies to the occurrence of substantial temperature differences within magma chambers, which often bias the estimated timescales in the case of multi-stage zoned minerals. Here we propose a new Non-Isothermal Diffusion Incremental Step model to take into account the non-isothermal nature of pre-eruptive processes, deconstructing the main core-rim diffusion profiles of multi-zoned crystals into different isothermal steps. The Non-Isothermal Diffusion Incremental Step model represents a significant improvement in the reconstruction of crystal lifetime histories. Unravelling stepwise timescales at contrasting temperatures provides a novel approach to constraining pre-eruptive magmatic processes and greatly increases our understanding of magma chamber dynamics.

Pre-eruptive magmatic processes re-timed using a non-isothermal approach to magma chamber dynamics

PubMed Central

Petrone, Chiara Maria; Bugatti, Giuseppe; Braschi, Eleonora; Tommasini, Simone

2016-01-01

Constraining the timescales of pre-eruptive magmatic processes in active volcanic systems is paramount to understand magma chamber dynamics and the triggers for volcanic eruptions. Temporal information of magmatic processes is locked within the chemical zoning profiles of crystals but can be accessed by means of elemental diffusion chronometry. Mineral compositional zoning testifies to the occurrence of substantial temperature differences within magma chambers, which often bias the estimated timescales in the case of multi-stage zoned minerals. Here we propose a new Non-Isothermal Diffusion Incremental Step model to take into account the non-isothermal nature of pre-eruptive processes, deconstructing the main core-rim diffusion profiles of multi-zoned crystals into different isothermal steps. The Non-Isothermal Diffusion Incremental Step model represents a significant improvement in the reconstruction of crystal lifetime histories. Unravelling stepwise timescales at contrasting temperatures provides a novel approach to constraining pre-eruptive magmatic processes and greatly increases our understanding of magma chamber dynamics. PMID:27703141

Software tools for data modelling and processing of human body temperature circadian dynamics.

PubMed

Petrova, Elena S; Afanasova, Anastasia I

2015-01-01

This paper is presenting a software development for simulating and processing thermometry data. The motivation of this research is the miniaturization of actuators attached to human body which allow frequent temperature measurements and improve the medical diagnosis procedures related to circadian dynamics.

Process-product dynamics: the role of Otherness in cultural cultivation.

PubMed

Lyra, Maria C D P

2014-06-01

Carriere (2013) presents a stimulating perspective on the cultural phenomena aiming to recover the role of the external products of culture to imbalance the currently popular emphasis on subject's process of cultivation highlighted by semiotic developmental cultural psychology. The excessive focus on subject's internal processes dismissing a better consideration of products of culture and the compelling objective realities of other dimensions of culture are pointed out. By this way the author's proposes a better dialogue with others perspectives on (cross)cultural psychology. These arguments are analyzed through a closer consideration of I-Other perennial movement. A dialogical view of process-product dynamics is then proposed. The role of Otherness--the one that (partially)shares and the one as witness, approving or disapproving subject's products of cultivation--is discussed through the analysis of a concrete episode of the cultivation of the subject. It is concluded that a semiotic developmental cultural psychology and (cross) cultural psychology have different objects of knowledge comprising distinct interests and research fields.

The Package-Based Development Process in the Flight Dynamics Division

NASA Technical Reports Server (NTRS)

Parra, Amalia; Seaman, Carolyn; Basili, Victor; Kraft, Stephen; Condon, Steven; Burke, Steven; Yakimovich, Daniil

1997-01-01

The Software Engineering Laboratory (SEL) has been operating for more than two decades in the Flight Dynamics Division (FDD) and has adapted to the constant movement of the software development environment. The SEL's Improvement Paradigm shows that process improvement is an iterative process. Understanding, Assessing and Packaging are the three steps that are followed in this cyclical paradigm. As the improvement process cycles back to the first step, after having packaged some experience, the level of understanding will be greater. In the past, products resulting from the packaging step have been large process documents, guidebooks, and training programs. As the technical world moves toward more modularized software, we have made a move toward more modularized software development process documentation, as such the products of the packaging step are becoming smaller and more frequent. In this manner, the QIP takes on a more spiral approach rather than a waterfall. This paper describes the state of the FDD in the area of software development processes, as revealed through the understanding and assessing activities conducted by the COTS study team. The insights presented include: (1) a characterization of a typical FDD Commercial Off the Shelf (COTS) intensive software development life-cycle process, (2) lessons learned through the COTS study interviews, and (3) a description of changes in the SEL due to the changing and accelerating nature of software development in the FDD.

Study of thermite mixture consolidated by the cold gas dynamic spray process

NASA Astrophysics Data System (ADS)

Bacciochini, A.; Maines, G.; Poupart, C.; Akbarnejad, H.; Radulescu, M.; Jodoin, B.; Zhang, F.; Lee, J. J.

2014-05-01

The present study focused on the cold gas dynamic spray process for manufacturing porosity free, finely structured energetic materials with high reactivity and structural integrity. The experiments have focused the reaction between the aluminium and metal oxide, such as Al-CuO system. The consolidation of the materials used the cold gas dynamic spray technique, where the particles are accelerated to high speeds and consolidated via plastic deformation upon impact. Reactive composites are formed in arbitrary shapes with close to zero porosity and without any reactions during the consolidation phase. Reactivity of mixtures has been investigated through flame propagation analysis on cold sprayed samples and compacted powder mixture. Deflagration tests showed the influence of porosity on the reactivity.

Spatio-temporal Dynamics of Audiovisual Speech Processing

PubMed Central

Bernstein, Lynne E.; Auer, Edward T.; Wagner, Michael; Ponton, Curtis W.

2007-01-01

The cortical processing of auditory-alone, visual-alone, and audiovisual speech information is temporally and spatially distributed, and functional magnetic resonance imaging (fMRI) cannot adequately resolve its temporal dynamics. In order to investigate a hypothesized spatio-temporal organization for audiovisual speech processing circuits, event-related potentials (ERPs) were recorded using electroencephalography (EEG). Stimuli were congruent audiovisual /bα/, incongruent auditory /bα/ synchronized with visual /gα/, auditory-only /bα/, and visual-only /bα/ and /gα/. Current density reconstructions (CDRs) of the ERP data were computed across the latency interval of 50-250 milliseconds. The CDRs demonstrated complex spatio-temporal activation patterns that differed across stimulus conditions. The hypothesized circuit that was investigated here comprised initial integration of audiovisual speech by the middle superior temporal sulcus (STS), followed by recruitment of the intraparietal sulcus (IPS), followed by activation of Broca's area (Miller and d'Esposito, 2005). The importance of spatio-temporally sensitive measures in evaluating processing pathways was demonstrated. Results showed, strikingly, early (< 100 msec) and simultaneous activations in areas of the supramarginal and angular gyrus (SMG/AG), the IPS, the inferior frontal gyrus, and the dorsolateral prefrontal cortex. Also, emergent left hemisphere SMG/AG activation, not predicted based on the unisensory stimulus conditions was observed at approximately 160 to 220 msec. The STS was neither the earliest nor most prominent activation site, although it is frequently considered the sine qua non of audiovisual speech integration. As discussed here, the relatively late activity of the SMG/AG solely under audiovisual conditions is a possible candidate audiovisual speech integration response. PMID:17920933

Extracting relevant information for cancer diagnosis from dynamic full field OCT through image processing and learning

NASA Astrophysics Data System (ADS)

Apelian, Clément; Gastaud, Clément; Boccara, A. Claude

2017-02-01

For a large number of cancer surgeries, the lack of reliable intraoperative diagnosis leads to reoperations or bad outcomes for the patients. To deliver better diagnosis, we developed Dynamic Full Field OCT (D-FFOCT) as a complement to FFOCT. FFOCT already presents interesting results for cancer diagnosis e.g. Mohs surgery and reaching 96% accuracy on prostate cancer. D-FFOCT accesses the dynamic processes of metabolism and gives new tools to diagnose the state of a tissue at the cellular level to complement FFOCT contrast. We developed a processing framework that intends to maximize the information provided by the FFOCT technology as well as D-FFOCT and synthetize this as a meaningful image. We use different time processing to generate metrics (standard deviation of time signals, decorrelation times and more) and spatial processing to sort out structures and the corresponding imaging modality, which is the most appropriate. Sorting was achieved through quadratic discriminant analysis in a N-dimension parametric space corresponding to our metrics. Combining the best imaging modalities for each structure leads to a rich morphology image. This image displaying the morphology is then colored to represent the dynamic behavior of these structures (slow or fast) and to be quickly analyzed by doctors. Therefore, we achieved a micron resolved image, rich of both FFOCT ability of imaging fixed and highly backscattering structures as well as D-FFOCT ability of imaging low level scattering cellular level details. We believe that this morphological contrast close to histology and the dynamic behavior contrast will push forward the limits of intraoperative diagnosis further on.

Working Memory Capacity as a Dynamic Process

PubMed Central

Simmering, Vanessa R.; Perone, Sammy

2013-01-01

A well-known characteristic of working memory (WM) is its limited capacity. The source of such limitations, however, is a continued point of debate. Developmental research is positioned to address this debate by jointly identifying the source(s) of limitations and the mechanism(s) underlying capacity increases. Here we provide a cross-domain survey of studies and theories of WM capacity development, which reveals a complex picture: dozens of studies from 50 papers show nearly universal increases in capacity estimates with age, but marked variation across studies, tasks, and domains. We argue that the full pattern of performance cannot be captured through traditional approaches emphasizing single causes, or even multiple separable causes, underlying capacity development. Rather, we consider WM capacity as a dynamic process that emerges from a unified cognitive system flexibly adapting to the context and demands of each task. We conclude by enumerating specific challenges for researchers and theorists that will need to be met in order to move our understanding forward. PMID:23335902

Important to investigate the dynamics of the stigma process.

PubMed

Angermeyer, Matthias

2004-01-01

Studies have shown that the stigma of the most common mental disorder, namely depression, expose people with these disorders to a substantial amount of stigmatization in the workplace. Apart from the descriptive assessment of the magnitude of stigma, it is also important to investigate the dynamics of the stigma process. Agreeing with Dr. Stuart, three approaches to research on stigma and the workplace are proposed. The first is the dimension of social stigma, i.e., knowledge, attitudes and practices of employers. The second is the perspectives of the patients, i.e., self- stigmatization. The third is legal and policy frameworks, i.e., structural discrimination.

Simulation of dynamic processes when machining transition surfaces of stepped shafts

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

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

Song, Hyun-Seob; Thomas, Dennis G.; Stegen, James C.

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community’s traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accountedmore » for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators.« less

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.

Hydro-dynamic and geotechnical effects in bridge scour processes

NASA Astrophysics Data System (ADS)

Radice, Alessio; Ballio, Francesco; Tran, Chau

2010-05-01

Local pier and abutment scour is a crucial topic in hydraulic engineering, due to the significant social and economical impact of bridge failure. Therefore, reliable tools for scour prediction are necessary for both design and vulnerability evaluation of the structures. In recent years, phenomenological studies of the local scour dynamics have been undertaken, to yield insight over the small scale mechanisms of the process. Experimental measurement and numerical modelling of the scouring flow field have shown the horseshoe vortex and the principal vortex as the most evident features of the flow pattern at piers and abutments, respectively. The vortex structure near the obstacles typically presents a high turbulence level compared to that of the incoming flow, and the temporal fluctuations in water velocity make the coherent vortical structures unstable in time. Furthermore, the statistical distributions of velocity values in junction flows often present a bimodal shape. The kinematics of the bottom grains reflects the unsteadiness of the flow pattern. Indeed, recent detailed measurements of particle motion in an abutment scour hole proved that a succession of opposite motion events takes place at several locations within the hole. Events of sediment motion directed away from the obstacles can be attributed to sediment pickup and transport by the turbulent flow field, whilst those with motion towards the abutment can be associated to sediment sliding along the slopes of the hole due to geotechnical instability. On a qualitative basis the presence of geotechnical effects is indeed relatively acknowledged. Despite the general agreement on the qualitative features of the scour process, a quantitative definition of the relevance of sliding for the sediment kinematics in a local scour process is still lacking. Therefore, the purpose of the present work has been to make a specific analysis of the different types of sediment motion events, aimed to a quantification of the

Quantitative confocal fluorescence microscopy of dynamic processes by multifocal fluorescence correlation spectroscopy

NASA Astrophysics Data System (ADS)

Krmpot, Aleksandar J.; Nikolić, Stanko N.; Vitali, Marco; Papadopoulos, Dimitrios K.; Oasa, Sho; Thyberg, Per; Tisa, Simone; Kinjo, Masataka; Nilsson, Lennart; Gehring, Walter J.; Terenius, Lars; Rigler, Rudolf; Vukojevic, Vladana

2015-07-01

Quantitative confocal fluorescence microscopy imaging without scanning is developed for the study of fast dynamical processes. The method relies on the use of massively parallel Fluorescence Correlation Spectroscopy (mpFCS). Simultaneous excitation of fluorescent molecules across the specimen is achieved by passing a single laser beam through a Diffractive Optical Element (DOE) to generate a quadratic illumination matrix of 32×32 light sources. Fluorescence from 1024 illuminated spots is detected in a confocal arrangement by a matching matrix detector consisting of the same number of single-photon avalanche photodiodes (SPADs). Software was developed for data acquisition and fast autoand cross-correlation analysis by parallel signal processing using a Graphic Processing Unit (GPU). Instrumental performance was assessed using a conventional single-beam FCS instrument as a reference. Versatility of the approach for application in biomedical research was evaluated using ex vivo salivary glands from Drosophila third instar larvae expressing a fluorescently-tagged transcription factor Sex Combs Reduced (Scr) and live PC12 cells stably expressing the fluorescently tagged mu-opioid receptor (MOPeGFP). We show that quantitative mapping of local concentration and mobility of transcription factor molecules across the specimen can be achieved using this approach, which paves the way for future quantitative characterization of dynamical reaction-diffusion landscapes across live cells/tissue with a submillisecond temporal resolution (presently 21 μs/frame) and single-molecule sensitivity.

Subduction and Restratification Along an Eddy Edge: The Role of Ekman Dynamics and Submesoscale Processes

NASA Astrophysics Data System (ADS)

Lucas, A.; Sengupta, D.; D'Asaro, E. A.; Nash, J. D.; Shroyer, E.; Mahadevan, A.; Tandon, A.; MacKinnon, J. A.; Pinkel, R.

2016-02-01

The exchange of heat between the atmosphere and ocean depends sensitively on the structure and extent of the oceanic boundary layer. Heat fluxes into and out of the ocean in turn influence atmospheric processes, and, in the northern Indian Ocean, impact the dominant regional weather pattern (the southwest Monsoon). In late 2015, measurements of the physical structure of the oceanic boundary layer were collected from a pair of research vessels and an array of autonomous assets in the Bay of Bengal as part of an India-U.S. scientific collaboration. Repeated CTD casts by a specialized shipboard system to 200m with a repeat rate of <3 min and a lateral spacing of < 200m, as well as near-surface sampling acoustic current profilers, showed how on the edge of an oceanic mesoscale eddy, the interaction of the mesoscale strain field, Ekman dynamics, and nonlinear submesoscale processes acted to subduct relative saline water under a very thin layer of fresher water derived from riverine sources. Our detailed surveys of the front between the overriding thin, fresh layer, and subducting adjacent more saline water demonstrated the important of small-scale physical dynamics to frontal slumping and the resulting re-stratification processes. These processes were strongly 3-dimensional and time-dependent. Such dynamics ultimately influence air-sea interactions by creating strongly stratified and very thin oceanic boundary layers in the Bay of Bengal, and allow the development of strong, persistent subsurface temperature maxima.

Synthesis and review: African environmental processes and water-cycle dynamics

PubMed Central

Ichoku, Charles; Adegoke, Jimmy

2018-01-01

Africa’s vast landmass harbors a variety of physical processes that affect the environment and the water cycle. This focus issue on ‘African Environmental Processes and Water-Cycle Dynamics’ contains eight articles that address these phenomena from different but complementary perspectives. Fires used for agricultural and related purposes play a major role in land-cover change, surface albedo modifications, and smoke emission; all of which affect the environment and the water cycle in different ways. However, emissions of aerosols and trace gases are not restricted to fires, but also emanate from other natural and human activities. The African water cycle undergoes significant perturbations that are attributable to several factors, including the aforesaid environmental processes. These changes in the water cycle have produced severe drought and flooding events in recent decades that affect societal wellbeing across sub-Saharan Africa. The combined effects of the environmental processes and water-cycle dynamics affect and are affected by climate variability and can be propagated beyond the continent. Future studies should utilize the wealth of observations and modeling tools that are constantly improving to clearly elucidate the interrelationships between all of these phenomena for the benefit of society. PMID:29682001

Synthesis and review: African environmental processes and water-cycle dynamics

NASA Astrophysics Data System (ADS)

Ichoku, Charles; Adegoke, Jimmy

2016-12-01

Africa’s vast landmass harbors a variety of physical processes that affect the environment and the water cycle. This focus issue on ‘African Environmental Processes and Water-Cycle Dynamics’ contains eight articles that address these phenomena from different but complementary perspectives. Fires used for agricultural and related purposes play a major role in land-cover change, surface albedo modifications, and smoke emission; all of which affect the environment and the water cycle in different ways. However, emissions of aerosols and trace gases are not restricted to fires, but also emanate from other natural and human activities. The African water cycle undergoes significant perturbations that are attributable to several factors, including the aforesaid environmental processes. These changes in the water cycle have produced severe drought and flooding events in recent decades that affect societal wellbeing across sub-Saharan Africa. The combined effects of the environmental processes and water-cycle dynamics affect and are affected by climate variability and can be propagated beyond the continent. Future studies should utilize the wealth of observations and modeling tools that are constantly improving to clearly elucidate the interrelationships between all of these phenomena for the benefit of society.

Dynamic Processes of Conceptual Change: Analysis of Constructing Mental Models of Chemical Equilibrium.

ERIC Educational Resources Information Center

Chiu, Mei-Hung; Chou, Chin-Cheng; Liu, Chia-Ju

2002-01-01

Investigates students' mental models of chemical equilibrium using dynamic science assessments. Reports that students at various levels have misconceptions about chemical equilibrium. Involves 10th grade students (n=30) in the study doing a series of hands-on chemical experiments. Focuses on the process of constructing mental models, dynamic…

Evidence for a hierarchical transcriptional circuit in Drosophila male germline involving testis-specific TAF and two gene-specific transcription factors, Mod and Acj6.

PubMed

Jiang, Mei; Gao, Zhengliang; Wang, Jian; Nurminsky, Dmitry I

2018-01-01

To analyze transcription factors involved in gene regulation by testis-specific TAF (tTAF), tTAF-dependent promoters were mapped and analyzed in silico. Core promoters show decreased AT content, paucity of classical promoter motifs, and enrichment with translation control element CAAAATTY. Scanning of putative regulatory regions for known position frequency matrices identified 19 transcription regulators possibly contributing to tTAF-driven gene expression. Decreased male fertility associated with mutation in one of the regulators, Acj6, indicates its involvement in male reproduction. Transcriptome study of testes from male mutants for tTAF, Acj6, and previously characterized tTAF-interacting factor Modulo implies the existence of a regulatory hierarchy of tTAF, Modulo and Acj6, in which Modulo and/or Acj6 regulate one-third of tTAF-dependent genes. © 2017 Federation of European Biochemical Societies.

Using process algebra to develop predator-prey models of within-host parasite dynamics.

PubMed

McCaig, Chris; Fenton, Andy; Graham, Andrea; Shankland, Carron; Norman, Rachel

2013-07-21

As a first approximation of immune-mediated within-host parasite dynamics we can consider the immune response as a predator, with the parasite as its prey. In the ecological literature of predator-prey interactions there are a number of different functional responses used to describe how a predator reproduces in response to consuming prey. Until recently most of the models of the immune system that have taken a predator-prey approach have used simple mass action dynamics to capture the interaction between the immune response and the parasite. More recently Fenton and Perkins (2010) employed three of the most commonly used prey-dependent functional response terms from the ecological literature. In this paper we make use of a technique from computing science, process algebra, to develop mathematical models. The novelty of the process algebra approach is to allow stochastic models of the population (parasite and immune cells) to be developed from rules of individual cell behaviour. By using this approach in which individual cellular behaviour is captured we have derived a ratio-dependent response similar to that seen in the previous models of immune-mediated parasite dynamics, confirming that, whilst this type of term is controversial in ecological predator-prey models, it is appropriate for models of the immune system. Copyright © 2013 Elsevier Ltd. All rights reserved.

Dynamic feature analysis for Voyager at the Image Processing Laboratory

NASA Technical Reports Server (NTRS)

Yagi, G. M.; Lorre, J. J.; Jepsen, P. L.

1978-01-01

Voyager 1 and 2 were launched from Cape Kennedy to Jupiter, Saturn, and beyond on September 5, 1977 and August 20, 1977. The role of the Image Processing Laboratory is to provide the Voyager Imaging Team with the necessary support to identify atmospheric features (tiepoints) for Jupiter and Saturn data, and to analyze and display them in a suitable form. This support includes the software needed to acquire and store tiepoints, the hardware needed to interactively display images and tiepoints, and the general image processing environment necessary for decalibration and enhancement of the input images. The objective is an understanding of global circulation in the atmospheres of Jupiter and Saturn. Attention is given to the Voyager imaging subsystem, the Voyager imaging science objectives, hardware, software, display monitors, a dynamic feature study, decalibration, navigation, and data base.

The internal processes and behavioral dynamics of hospital boards: an exploration of differences between high- and low-performing hospitals.

PubMed

Kane, Nancy M; Clark, Jonathan R; Rivenson, Howard L

2009-01-01

Nonprofit hospital boards are under increasing pressure to improve financial, clinical, and charitable and community benefit performance. Most research on board effectiveness focuses on variables measuring board structure and attributes associated with competing ideal models of board roles. However, the results do not provide clear evidence that one role is superior to another and suggest that in practice boards pursue hybrid roles. Board dynamics and processes have received less attention from researchers, but emerging theoretical frameworks highlight them as key to effective corporate governance. We explored differences in board processes and behavioral dynamics between financially high- and low-performing hospitals, with the goal of developing a better understanding of the best board practices in nonprofit hospitals. A comparative case study approach allowed for in-depth, qualitative assessments of how the internal workings of boards differ between low- and high-performing facilities. Boards of hospitals with strong financial performance exhibited behavioral dynamics and internal processes that differed in important ways from those of hospitals with poor financial performance. Boards need to actively attend to key processes and foster positive group dynamics in decision making to be more effective in governing hospitals.

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

NASA Astrophysics Data System (ADS)

Kuschmierz, Robert; Filippatos, Angelos; Günther, Philipp; Langkamp, Albert; Hufenbach, Werner; Czarske, Jürgen; Fischer, Andreas

2015-03-01

Polymer composite rotors are lightweight and offer great perspectives in high-speed applications such as turbo machinery. Currently, novel rotor structures and materials are investigated for the purpose of increasing machine efficiency and lifetime, as well as allowing for higher dynamic loads. However, due to the complexity of the composite materials an in-process measurement system is required. This allows for monitoring the evolution of damages under dynamic loads, for testing and predicting the structural integrity of composite rotors in process. In rotor design, it can be used for calibrating and improving models, simulating the dynamic behaviour of polymer composite rotors. The measurement system is to work non-invasive, offer micron uncertainty, as well as a high measurement rate of several tens of kHz. Furthermore, it must be applicable at high surface speeds and under technical vacuum. In order to fulfil these demands a novel laser distance measurement system was developed. It provides the angle resolved measurement of the biaxial deformation of a fibre-reinforced polymer composite rotor with micron uncertainty at surface speeds of more than 300 m/s. Furthermore, a simulation procedure combining a finite element model and a damage mechanics model is applied. A comparison of the measured data and the numerically calculated data is performed to validate the simulation towards rotor expansion. This validating procedure can be used for a model calibration in the future. The simulation procedure could be used to investigate different damage-test cases of the rotor, in order to define its structural behaviour without further experiments.

Dynamic neutron scattering from conformational dynamics. I. Theory and Markov models

NASA Astrophysics Data System (ADS)

Lindner, Benjamin; Yi, Zheng; Prinz, Jan-Hendrik; Smith, Jeremy C.; Noé, Frank

2013-11-01

The dynamics of complex molecules can be directly probed by inelastic neutron scattering experiments. However, many of the underlying dynamical processes may exist on similar timescales, which makes it difficult to assign processes seen experimentally to specific structural rearrangements. Here, we show how Markov models can be used to connect structural changes observed in molecular dynamics simulation directly to the relaxation processes probed by scattering experiments. For this, a conformational dynamics theory of dynamical neutron and X-ray scattering is developed, following our previous approach for computing dynamical fingerprints of time-correlation functions [F. Noé, S. Doose, I. Daidone, M. Löllmann, J. Chodera, M. Sauer, and J. Smith, Proc. Natl. Acad. Sci. U.S.A. 108, 4822 (2011)]. Markov modeling is used to approximate the relaxation processes and timescales of the molecule via the eigenvectors and eigenvalues of a transition matrix between conformational substates. This procedure allows the establishment of a complete set of exponential decay functions and a full decomposition into the individual contributions, i.e., the contribution of every atom and dynamical process to each experimental relaxation process.

Physical Processes Dictate Early Biogeochemical Dynamics of Soil Pyrogenic Organic Matter in a Subtropical Forest Ecosystem

NASA Astrophysics Data System (ADS)

Stuart, Jason M.; Anderson, Russell; Lazzarino, Patrick; Kuehn, Kevin A.; Harvey, Omar R.

2018-05-01

Quantifying links between pyOM dynamics, environmental factors and processes is central to predicting ecosystem function and response to future perturbations. In this study, changes in carbon (TC), nitrogen (TN) , pH and relative recalcitrance (R50) for pine- and cordgrass-derived pyOM were measured at 3-6 weeks intervals throughout the first year of burial in the soil. Objectives were to 1) identify key environmental factors and processes driving early-stage pyOM dynamics, and 2) develop quantitative relationships between environmental factors and changes in pyOM properties. The study was conducted in sandy soils of a forested ecosystem in the Longleaf pine range, US with a focus on links between changes in pyOM properties, fire history (FH), cumulative precipitation (Pcum), average temperature (Tavg) and soil residence time (SRT). Pcum, SRT and Tavg were the main factors controlling TC and TN accounting for 77-91% and 64-96% of their respective variability. Fire history, along with Pcum, SRT and Tavg, exhibited significant controlling effects on pyOM, pH and R50 - accounting for 48-91% and 88-93% of respective variability. Volatilization of volatiles and leaching of water-soluble components (in summer) and the sorption of exogenous organic matter (fall through spring) were most plausibly controlling pyOM dynamics in this study. Overall, our results point to climatic and land management factors and physicochemical process as the main drivers of pyOM dynamics in the pine ecosystems of the Southeastern US.

Photonic single nonlinear-delay dynamical node for information processing

NASA Astrophysics Data System (ADS)

Ortín, Silvia; San-Martín, Daniel; Pesquera, Luis; Gutiérrez, José Manuel

2012-06-01

An electro-optical system with a delay loop based on semiconductor lasers is investigated for information processing by performing numerical simulations. This system can replace a complex network of many nonlinear elements for the implementation of Reservoir Computing. We show that a single nonlinear-delay dynamical system has the basic properties to perform as reservoir: short-term memory and separation property. The computing performance of this system is evaluated for two prediction tasks: Lorenz chaotic time series and nonlinear auto-regressive moving average (NARMA) model. We sweep the parameters of the system to find the best performance. The results achieved for the Lorenz and the NARMA-10 tasks are comparable to those obtained by other machine learning methods.

Accommodating Dynamic Oceanographic Processes and Pelagic Biodiversity in Marine Conservation Planning

PubMed Central

Grantham, Hedley S.; Game, Edward T.; Lombard, Amanda T.; Hobday, Alistair J.; Richardson, Anthony J.; Beckley, Lynnath E.; Pressey, Robert L.; Huggett, Jenny A.; Coetzee, Janet C.; van der Lingen, Carl D.; Petersen, Samantha L.; Merkle, Dagmar; Possingham, Hugh P.

2011-01-01

Pelagic ecosystems support a significant and vital component of the ocean's productivity and biodiversity. They are also heavily exploited and, as a result, are the focus of numerous spatial planning initiatives. Over the past decade, there has been increasing enthusiasm for protected areas as a tool for pelagic conservation, however, few have been implemented. Here we demonstrate an approach to plan protected areas that address the physical and biological dynamics typical of the pelagic realm. Specifically, we provide an example of an approach to planning protected areas that integrates pelagic and benthic conservation in the southern Benguela and Agulhas Bank ecosystems off South Africa. Our aim was to represent species of importance to fisheries and species of conservation concern within protected areas. In addition to representation, we ensured that protected areas were designed to consider pelagic dynamics, characterized from time-series data on key oceanographic processes, together with data on the abundance of small pelagic fishes. We found that, to have the highest likelihood of reaching conservation targets, protected area selection should be based on time-specific data rather than data averaged across time. More generally, we argue that innovative methods are needed to conserve ephemeral and dynamic pelagic biodiversity. PMID:21311757

Dynamic actuation of a novel laser-processed NiTi linear actuator

NASA Astrophysics Data System (ADS)

Pequegnat, A.; Daly, M.; Wang, J.; Zhou, Y.; Khan, M. I.

2012-09-01

A novel laser processing technique, capable of locally modifying the shape memory effect, was applied to enhance the functionality of a NiTi linear actuator. By altering local transformation temperatures, an additional memory was imparted into a monolithic NiTi wire to enable dynamic actuation via controlled resistive heating. Characterizations of the actuator load, displacement and cyclic properties were conducted using a custom-built spring-biased test set-up. Monotonic tensile testing was also implemented to characterize the deformation behaviour of the martensite phase. Observed differences in the deformation behaviour of laser-processed material were found to affect the magnitude of the active strain. Furthermore, residual strain during cyclic actuation testing was found to stabilize after 150 cycles while the recoverable strain remained constant. This laser-processed actuator will allow for the realization of new applications and improved control methods for shape memory alloys.

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.

Time correlation functions of simple liquids: A new insight on the underlying dynamical processes

NASA Astrophysics Data System (ADS)

Garberoglio, Giovanni; Vallauri, Renzo; Bafile, Ubaldo

2018-05-01

Extensive molecular dynamics simulations of liquid sodium have been carried out to evaluate correlation functions of several dynamical quantities. We report the results of a novel analysis of the longitudinal and transverse correlation functions obtained by evaluating directly their self- and distinct contributions at different wavevectors k. It is easily recognized that the self-contribution remains close to its k → 0 limit, which turns out to be exactly the autocorrelation function of the single particle velocity. The wavevector dependence of the longitudinal and transverse spectra and their self- and distinct parts is also presented. By making use of the decomposition of the velocity autocorrelation spectrum in terms of longitudinal and transverse parts, our analysis is able to recognize the effect of different dynamical processes in different frequency ranges.

Point process modeling and estimation: Advances in the analysis of dynamic neural spiking data

NASA Astrophysics Data System (ADS)

Deng, Xinyi

2016-08-01

A common interest of scientists in many fields is to understand the relationship between the dynamics of a physical system and the occurrences of discrete events within such physical system. Seismologists study the connection between mechanical vibrations of the Earth and the occurrences of earthquakes so that future earthquakes can be better predicted. Astrophysicists study the association between the oscillating energy of celestial regions and the emission of photons to learn the Universe's various objects and their interactions. Neuroscientists study the link between behavior and the millisecond-timescale spike patterns of neurons to understand higher brain functions. Such relationships can often be formulated within the framework of state-space models with point process observations. The basic idea is that the dynamics of the physical systems are driven by the dynamics of some stochastic state variables and the discrete events we observe in an interval are noisy observations with distributions determined by the state variables. This thesis proposes several new methodological developments that advance the framework of state-space models with point process observations at the intersection of statistics and neuroscience. In particular, we develop new methods 1) to characterize the rhythmic spiking activity using history-dependent structure, 2) to model population spike activity using marked point process models, 3) to allow for real-time decision making, and 4) to take into account the need for dimensionality reduction for high-dimensional state and observation processes. We applied these methods to a novel problem of tracking rhythmic dynamics in the spiking of neurons in the subthalamic nucleus of Parkinson's patients with the goal of optimizing placement of deep brain stimulation electrodes. We developed a decoding algorithm that can make decision in real-time (for example, to stimulate the neurons or not) based on various sources of information present in

Time-Structured and Net Intraindividual Variability: Tools for Examining the Development of Dynamic Characteristics and Processes

PubMed Central

Ram, Nilam; Gerstorf, Denis

2009-01-01

The study of intraindividual variability is the study of fluctuations, oscillations, adaptations, and “noise” in behavioral outcomes that manifest on micro-time scales. This paper provides a descriptive frame for the combined study of intraindividual variability and aging/development. At the conceptual level, we highlight that the study of intraindividual variability provides access to dynamic characteristics – construct-level descriptions of individuals' capacities for change (e.g., lability), and dynamic processes – the systematic changes individuals' exhibit in response to endogenous and exogenous influences (e.g., regulation). At the methodological level, we review how quantifications of net intraindividual variability (e.g., iSD) and models of time-structured intraindividual variability (e.g., time-series) are being used to measure and describe dynamic characteristics and processes. At the research design level, we point to the benefits of measurement burst study designs, wherein data are obtained across multiple time scales, for the study of development. PMID:20025395

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics

NASA Astrophysics Data System (ADS)

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

Sparse dynamical Boltzmann machine for reconstructing complex networks with binary dynamics.

PubMed

Chen, Yu-Zhong; Lai, Ying-Cheng

2018-03-01

Revealing the structure and dynamics of complex networked systems from observed data is a problem of current interest. Is it possible to develop a completely data-driven framework to decipher the network structure and different types of dynamical processes on complex networks? We develop a model named sparse dynamical Boltzmann machine (SDBM) as a structural estimator for complex networks that host binary dynamical processes. The SDBM attains its topology according to that of the original system and is capable of simulating the original binary dynamical process. We develop a fully automated method based on compressive sensing and a clustering algorithm to construct the SDBM. We demonstrate, for a variety of representative dynamical processes on model and real world complex networks, that the equivalent SDBM can recover the network structure of the original system and simulates its dynamical behavior with high precision.

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

Critical Moments in the Process of Educational Change: Understanding the Dynamics of Change among Teacher Educators

ERIC Educational Resources Information Center

Brody, David L.; Hadar, Linor Lea

2018-01-01

This study examines the complex process of change among teacher educators who have chosen to improve their practice in a professional development community. Storyline methodology was used to reveal the dynamic process which teacher educators undergo when they consider adopting innovative pedagogy. Findings reveal critical moments in professional…

Nonlinear dynamic failure process of tunnel-fault system in response to strong seismic event

NASA Astrophysics Data System (ADS)

Yang, Zhihua; Lan, Hengxing; Zhang, Yongshuang; Gao, Xing; Li, Langping

2013-03-01

Strong earthquakes and faults have significant effect on the stability capability of underground tunnel structures. This study used a 3-Dimensional Discrete Element model and the real records of ground motion in the Wenchuan earthquake to investigate the dynamic response of tunnel-fault system. The typical tunnel-fault system was composed of one planned railway tunnel and one seismically active fault. The discrete numerical model was prudentially calibrated by means of the comparison between the field survey and numerical results of ground motion. It was then used to examine the detailed quantitative information on the dynamic response characteristics of tunnel-fault system, including stress distribution, strain, vibration velocity and tunnel failure process. The intensive tunnel-fault interaction during seismic loading induces the dramatic stress redistribution and stress concentration in the intersection of tunnel and fault. The tunnel-fault system behavior is characterized by the complicated nonlinear dynamic failure process in response to a real strong seismic event. It can be qualitatively divided into 5 main stages in terms of its stress, strain and rupturing behaviors: (1) strain localization, (2) rupture initiation, (3) rupture acceleration, (4) spontaneous rupture growth and (5) stabilization. This study provides the insight into the further stability estimation of underground tunnel structures under the combined effect of strong earthquakes and faults.

Dynamic recrystallization and texture evolution of Mg–Y–Zn alloy during hot extrusion process

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

Tong, L.B.; Li, X.; Guangzhou Research Institute of Non-ferrous Metals, Guangzhou 510651

2014-06-01

The microstructure and texture evolution of Mg{sub 98.5}Y{sub 1}Zn{sub 0.5} and Mg{sub 92.5}Y{sub 5}Zn{sub 2.5} (atomic percent) alloys during hot extrusion were systematically investigated. The coarse LPSO phases with higher volume fraction (∼ 57%) suppressed the twinning generation in the initial stage of extrusion, and accelerated the dynamic recrystallization through the particle deformation zones. Therefore, the volume fraction of DRXed grains in as-extruded Mg{sub 92.5}Y{sub 5}Zn{sub 2.5} alloy was much higher than that of Mg{sub 98.5}Y{sub 1}Zn{sub 0.5} alloy. The intensive recrystallization process resulted in the conventional basal texture weakening, although the texture evolution was mainly dominated by flow behavior.more » The dynamic recrystallization behavior in Mg{sub 92.5}Y{sub 5}Zn{sub 2.5} alloy restricted the formation of deformation texture, and thus the more random texture was observed during the whole extrusion process. - Highlights: • The densely coarse LPSO phases suppressed the twinning deformation. • Coarse LPSO phases induced the particle stimulated nucleation effect. • Dynamic recrystallization resulted in the basal texture weakening effect.« less

General purpose molecular dynamics simulations fully implemented on graphics processing units

NASA Astrophysics Data System (ADS)

Anderson, Joshua A.; Lorenz, Chris D.; Travesset, A.

2008-05-01

Graphics processing units (GPUs), originally developed for rendering real-time effects in computer games, now provide unprecedented computational power for scientific applications. In this paper, we develop a general purpose molecular dynamics code that runs entirely on a single GPU. It is shown that our GPU implementation provides a performance equivalent to that of fast 30 processor core distributed memory cluster. Our results show that GPUs already provide an inexpensive alternative to such clusters and discuss implications for the future.

A normal tissue dose response model of dynamic repair processes.

PubMed

Alber, Markus; Belka, Claus

2006-01-07

A model is presented for serial, critical element complication mechanisms for irradiated volumes from length scales of a few millimetres up to the entire organ. The central element of the model is the description of radiation complication as the failure of a dynamic repair process. The nature of the repair process is seen as reestablishing the structural organization of the tissue, rather than mere replenishment of lost cells. The interactions between the cells, such as migration, involved in the repair process are assumed to have finite ranges, which limits the repair capacity and is the defining property of a finite-sized reconstruction unit. Since the details of the repair processes are largely unknown, the development aims to make the most general assumptions about them. The model employs analogies and methods from thermodynamics and statistical physics. An explicit analytical form of the dose response of the reconstruction unit for total, partial and inhomogeneous irradiation is derived. The use of the model is demonstrated with data from animal spinal cord experiments and clinical data about heart, lung and rectum. The three-parameter model lends a new perspective to the equivalent uniform dose formalism and the established serial and parallel complication models. Its implications for dose optimization are discussed.

Modeling Heterogeneity in Momentary Interpersonal and Affective Dynamic Processes in Borderline Personality Disorder

PubMed Central

Wright, Aidan G. C.; Hallquist, Michael N.; Stepp, Stephanie D.; Scott, Lori N.; Beeney, Joseph E.; Lazarus, Sophie A.; Pilkonis, Paul A.

2016-01-01

Borderline personality disorder (BPD) is a diagnosis defined by impairments in several dynamic processes (e.g., interpersonal relating, affect regulation, behavioral control). Theories of BPD emphasize that these impairments appear in specific contexts, and emerging results confirm this view. At the same time, BPD is a complex construct that encompasses individuals with heterogeneous pathology. These features—dynamic processes, situational specificity, and individual heterogeneity—pose significant assessment challenges. In the current study, we demonstrate assessment and analytic methods that capture both between-person differences and within-person changes over time. Twenty-five participants diagnosed with BPD completed event-contingent, ambulatory assessment protocols over 21 days. We used p-technique factor analyses to identify person-specific psychological structures consistent with clinical theories of personality. Five exemplar cases are selected and presented in detail to showcase the potential utility of these methods. The presented cases' factor structures reflect not only heterogeneity but also suggest points of convergence. The factors also demonstrated significant associations with important clinical targets (self-harm, interpersonal violence). PMID:27317561

High-throughput process development: determination of dynamic binding capacity using microtiter filter plates filled with chromatography resin.

PubMed

Bergander, Tryggve; Nilsson-Välimaa, Kristina; Oberg, Katarina; Lacki, Karol M

2008-01-01

Steadily increasing demand for more efficient and more affordable biomolecule-based therapies put a significant burden on biopharma companies to reduce the cost of R&D activities associated with introduction of a new drug to the market. Reducing the time required to develop a purification process would be one option to address the high cost issue. The reduction in time can be accomplished if more efficient methods/tools are available for process development work, including high-throughput techniques. This paper addresses the transitions from traditional column-based process development to a modern high-throughput approach utilizing microtiter filter plates filled with a well-defined volume of chromatography resin. The approach is based on implementing the well-known batch uptake principle into microtiter plate geometry. Two variants of the proposed approach, allowing for either qualitative or quantitative estimation of dynamic binding capacity as a function of residence time, are described. Examples of quantitative estimation of dynamic binding capacities of human polyclonal IgG on MabSelect SuRe and of qualitative estimation of dynamic binding capacity of amyloglucosidase on a prototype of Capto DEAE weak ion exchanger are given. The proposed high-throughput method for determination of dynamic binding capacity significantly reduces time and sample consumption as compared to a traditional method utilizing packed chromatography columns without sacrificing the accuracy of data obtained.

Investigation of Dynamic and Physical Processes in the Upper Troposphere and Lower Stratosphere

NASA Technical Reports Server (NTRS)

Selkirk, Henry B.; Pfister, Leonhard (Technical Monitor)

2002-01-01

Research under this Cooperative Agreement has been funded by several NASA Earth Science programs: the Atmospheric Effects of Radiation Program (AEAP), the Upper Atmospheric Research Program (UARP), and most recently the Atmospheric Chemistry and Modeling Assessment Program (ACMAP). The purpose of the AEAP was to understand the impact of the present and future fleets of conventional jet traffic on the upper troposphere and lower stratosphere, while complementary airborne observations under UARP seek to understand the complex interactions of dynamical and chemical processes that affect the ozone layer. The ACMAP is a more general program of modeling and data analysis in the general area of atmospheric chemistry and dynamics, and the Radiation Sciences program.

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.

Conformational analysis of processivity clamps in solution demonstrates that tertiary structure does not correlate with protein dynamics.

PubMed

Fang, Jing; Nevin, Philip; Kairys, Visvaldas; Venclovas, Česlovas; Engen, John R; Beuning, Penny J

2014-04-08

The relationship between protein sequence, structure, and dynamics has been elusive. Here, we report a comprehensive analysis using an in-solution experimental approach to study how the conservation of tertiary structure correlates with protein dynamics. Hydrogen exchange measurements of eight processivity clamp proteins from different species revealed that, despite highly similar three-dimensional structures, clamp proteins display a wide range of dynamic behavior. Differences were apparent both for structurally similar domains within proteins and for corresponding domains of different proteins. Several of the clamps contained regions that underwent local unfolding with different half-lives. We also observed a conserved pattern of alternating dynamics of the α helices lining the inner pore of the clamps as well as a correlation between dynamics and the number of salt bridges in these α helices. Our observations reveal that tertiary structure and dynamics are not directly correlated and that primary structure plays an important role in dynamics. Copyright © 2014 Elsevier Ltd. All rights reserved.

Pattern does not equal process: what does patch occupancy really tell us about metapopulation dynamics?

PubMed

Clinchy, Michael; Haydon, Daniel T; Smith, Andrew T

2002-04-01

Patch occupancy surveys are commonly used to parameterize metapopulation models. If isolation predicts patch occupancy, this is generally attributed to a balance between distance-dependent recolonization and spatially independent extinctions. We investigated whether similar patterns could also be generated by a process of spatially correlated extinctions following a unique colonization event (analogous to nonequilibrium processes in island biogeography). We simulated effects of spatially correlated extinctions on patterns of patch occupancy among pikas (Ochotona princeps) at Bodie, California, using randomly located extinction disks to represent the likely effects of predation. Our simulations produced similar patterns to those cited as evidence of balanced metapopulation dynamics. Simulations using a variety of disk sizes and patch configurations confirmed that our results are potentially applicable to a broad range of species and sites. Analyses of the observed patterns of patch occupancy at Bodie revealed little evidence of rescue effects and strong evidence that most recolonizations are ephemeral in nature. Persistence will be overestimated if static or declining patterns of patch occupancy are mistakenly attributed to dynamically stable metapopulation processes. Consequently, simple patch occupancy surveys should not be considered as substitutes for detailed experimental tests of hypothesized population processes, particularly when conservation concerns are involved.

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

NASA Astrophysics Data System (ADS)

Li, Huanhuan; Chen, Diyi; Zhang, Hao; Wang, Feifei; Ba, Duoduo

2016-12-01

In order to study the nonlinear dynamic behaviors of a hydro-turbine governing system in the process of sudden load increase transient, we establish a novel nonlinear dynamic model of the hydro-turbine governing system which considers the elastic water-hammer model of the penstock and the second-order model of the generator. The six nonlinear dynamic transfer coefficients of the hydro-turbine are innovatively proposed by utilizing internal characteristics and analyzing the change laws of the characteristic parameters of the hydro-turbine governing system. Moreover, from the point of view of engineering, the nonlinear dynamic behaviors of the above system are exhaustively investigated based on bifurcation diagrams and time waveforms. More importantly, all of the above analyses supply theoretical basis for allowing a hydropower station to maintain a stable operation in the process of sudden load increase transient.

A dynamic systems approach to psychotherapy: A meta-theoretical framework for explaining psychotherapy change processes.

PubMed

Gelo, Omar Carlo Gioacchino; Salvatore, Sergio

2016-07-01

Notwithstanding the many methodological advances made in the field of psychotherapy research, at present a metatheoretical, school-independent framework to explain psychotherapy change processes taking into account their dynamic and complex nature is still lacking. Over the last years, several authors have suggested that a dynamic systems (DS) approach might provide such a framework. In the present paper, we review the main characteristics of a DS approach to psychotherapy. After an overview of the general principles of the DS approach, we describe the extent to which psychotherapy can be considered as a self-organizing open complex system, whose developmental change processes are described in terms of a dialectic dynamics between stability and change over time. Empirical evidence in support of this conceptualization is provided and discussed. Finally, we propose a research design strategy for the empirical investigation of psychotherapy from a DS approach, together with a research case example. We conclude that a DS approach may provide a metatheoretical, school-independent framework allowing us to constructively rethink and enhance the way we conceptualize and empirically investigate psychotherapy. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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

In Situ XRD Studies of the Process Dynamics During Annealing in Cold-Rolled Copper

NASA Astrophysics Data System (ADS)

Dey, Santu; Gayathri, N.; Bhattacharya, M.; Mukherjee, P.

2016-12-01

The dynamics of the release of stored energy during annealing along two different crystallographic planes, i.e., {111} and {220}, in deformed copper have been investigated using in situ X-ray diffraction measurements at 458 K and 473 K (185 °C and 200 °C). The study has been carried out on 50 and 80 pct cold-rolled Cu sheets. The microstructures of the rolled samples have been characterized using optical microscopy and electron backscattered diffraction measurements. The microstructural parameters were evaluated from the X-ray diffractogram using the Scherrer equation and the modified Rietveld method. The stored energy along different planes was determined using the modified Stibitz formula from the X-ray peak broadening, and the bulk stored energy was evaluated using differential scanning calorimetry. The process dynamics of recovery and recrystallization as observed through the release of stored energy have been modeled as the second-order and first-order processes, respectively.

Spatiotemporal dynamics of landscape pattern and hydrologic process in watershed systems

NASA Astrophysics Data System (ADS)

Randhir, Timothy O.; Tsvetkova, Olga

2011-06-01

SummaryLand use change is influenced by spatial and temporal factors that interact with watershed resources. Modeling these changes is critical to evaluate emerging land use patterns and to predict variation in water quantity and quality. The objective of this study is to model the nature and emergence of spatial patterns in land use and water resource impacts using a spatially explicit and dynamic landscape simulation. Temporal changes are predicted using a probabilistic Markovian process and spatial interaction through cellular automation. The MCMC (Monte Carlo Markov Chain) analysis with cellular automation is linked to hydrologic equations to simulate landscape patterns and processes. The spatiotemporal watershed dynamics (SWD) model is applied to a subwatershed in the Blackstone River watershed of Massachusetts to predict potential land use changes and expected runoff and sediment loading. Changes in watershed land use and water resources are evaluated over 100 years at a yearly time step. Results show high potential for rapid urbanization that could result in lowering of groundwater recharge and increased storm water peaks. The watershed faces potential decreases in agricultural and forest area that affect open space and pervious cover of the watershed system. Water quality deteriorated due to increased runoff which can also impact stream morphology. While overland erosion decreased, instream erosion increased from increased runoff from urban areas. Use of urban best management practices (BMPs) in sensitive locations, preventive strategies, and long-term conservation planning will be useful in sustaining the watershed system.

A Dynamic Causal Modeling Analysis of the Effective Connectivities Underlying Top-Down Letter Processing

ERIC Educational Resources Information Center

Liu, Jiangang; Li, Jun; Rieth, Cory A.; Huber, David E.; Tian, Jie; Lee, Kang

2011-01-01

The present study employed dynamic causal modeling to investigate the effective functional connectivity between regions of the neural network involved in top-down letter processing. We used an illusory letter detection paradigm in which participants detected letters while viewing pure noise images. When participants detected letters, the response…

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.

Impulse processing: A dynamical systems model of incremental eye movements in the visual world paradigm

PubMed Central

Kukona, Anuenue; Tabor, Whitney

2011-01-01

The visual world paradigm presents listeners with a challenging problem: they must integrate two disparate signals, the spoken language and the visual context, in support of action (e.g., complex movements of the eyes across a scene). We present Impulse Processing, a dynamical systems approach to incremental eye movements in the visual world that suggests a framework for integrating language, vision, and action generally. Our approach assumes that impulses driven by the language and the visual context impinge minutely on a dynamical landscape of attractors corresponding to the potential eye-movement behaviors of the system. We test three unique predictions of our approach in an empirical study in the visual world paradigm, and describe an implementation in an artificial neural network. We discuss the Impulse Processing framework in relation to other models of the visual world paradigm. PMID:21609355

How does "not left" become "right"? Electrophysiological evidence for a dynamic conflict-bound negation processing account.

PubMed

Dudschig, Carolin; Kaup, Barbara

2018-05-01

Human thought and language is traditionally considered as abstract, amodal, and symbolic. However, recent theories propose that high-level human cognition is directly linked to basic, modal biological systems such as sensorimotor areas. Despite this influential representational debate very little is known regarding whether the mechanisms involved in sensorimotor control are also shared with higher-level cognitive processes, such as language comprehension. We investigated negation as a universal of human language, addressing two key questions: (a) Does negation result in a conflict-like representation? (b) Does negation trigger executive control adjustments in a similar manner as standard information processing conflicts do (e.g., Simon, Flanker)? Electrophysiological data indicated that phrases such as "not left/not right" result in initial activation of the to-be-negated information and subsequently the outcome of the negation process. More importantly, our findings also suggest that negation triggers conflict-related adjustments in information processing in line with traditional conflict tasks. Trial-by-trial conflict adaptation patterns in both behavioral and electrophysiological data indicated that negation processing dynamically changes depending on the current cognitive state. In summary, negation processing results in cognitive conflict, and dynamic influences of the cognitive state determine conflict resolution, that is, negation implementation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Sourdough microbial community dynamics: An analysis during French organic bread-making processes.

PubMed

Lhomme, Emilie; Urien, Charlotte; Legrand, Judith; Dousset, Xavier; Onno, Bernard; Sicard, Delphine

2016-02-01

Natural sourdoughs are commonly used in bread-making processes, especially for organic bread. Despite its role in bread flavor and dough rise, the stability of the sourdough microbial community during and between bread-making processes is debated. We investigated the dynamics of lactic acid bacteria (LAB) and yeast communities in traditional organic sourdoughs of five French bakeries during the bread-making process and several months apart using classical and molecular microbiology techniques. Sourdoughs were sampled at four steps of the bread-making process with repetition. The analysis of microbial density over 68 sourdough/dough samples revealed that both LAB and yeast counts changed along the bread-making process and between bread-making runs. The species composition was less variable. A total of six LAB and nine yeast species was identified from 520 and 1675 isolates, respectively. The dominant LAB species was Lactobacillus sanfranciscensis, found for all bakeries and each bread-making run. The dominant yeast species changed only once between bread-making processes but differed between bakeries. They mostly belonged to the Kazachstania clade. Overall, this study highlights the change of population density within the bread-making process and between bread-making runs and the relative stability of the sourdough species community during bread-making process. Copyright © 2014 Elsevier Ltd. All rights reserved.

Stochastic dynamics of small ensembles of non-processive molecular motors: The parallel cluster model

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

Erdmann, Thorsten; Albert, Philipp J.; Schwarz, Ulrich S.

2013-11-07

Non-processive molecular motors have to work together in ensembles in order to generate appreciable levels of force or movement. In skeletal muscle, for example, hundreds of myosin II molecules cooperate in thick filaments. In non-muscle cells, by contrast, small groups with few tens of non-muscle myosin II motors contribute to essential cellular processes such as transport, shape changes, or mechanosensing. Here we introduce a detailed and analytically tractable model for this important situation. Using a three-state crossbridge model for the myosin II motor cycle and exploiting the assumptions of fast power stroke kinetics and equal load sharing between motors inmore » equivalent states, we reduce the stochastic reaction network to a one-step master equation for the binding and unbinding dynamics (parallel cluster model) and derive the rules for ensemble movement. We find that for constant external load, ensemble dynamics is strongly shaped by the catch bond character of myosin II, which leads to an increase of the fraction of bound motors under load and thus to firm attachment even for small ensembles. This adaptation to load results in a concave force-velocity relation described by a Hill relation. For external load provided by a linear spring, myosin II ensembles dynamically adjust themselves towards an isometric state with constant average position and load. The dynamics of the ensembles is now determined mainly by the distribution of motors over the different kinds of bound states. For increasing stiffness of the external spring, there is a sharp transition beyond which myosin II can no longer perform the power stroke. Slow unbinding from the pre-power-stroke state protects the ensembles against detachment.« less

The Creative Chaos: Speculations on the Connection Between Non-Linear Dynamics and the Creative Process

NASA Astrophysics Data System (ADS)

Zausner, Tobi

Chaos theory may provide models for creativity and for the personality of the artist. A collection of speculative hypotheses examines the connection between art and such fundamentals of non-linear dynamics as iteration, dissipative processes, open systems, entropy, sensitivity to stimuli, autocatalysis, subsystems, bifurcations, randomness, unpredictability, irreversibility, increasing levels of organization, far-from-equilibrium conditions, strange attractors, period doubling, intermittency and self-similar fractal organization. Non-linear dynamics may also explain why certain individuals suffer mental disorders while others remain intact during a lifetime of sustained creative output.

Concurrent remote entanglement with quantum error correction against photon losses

NASA Astrophysics Data System (ADS)

Roy, Ananda; Stone, A. Douglas; Jiang, Liang

2016-09-01

Remote entanglement of distant, noninteracting quantum entities is a key primitive for quantum information processing. We present a protocol to remotely entangle two stationary qubits by first entangling them with propagating ancilla qubits and then performing a joint two-qubit measurement on the ancillas. Subsequently, single-qubit measurements are performed on each of the ancillas. We describe two continuous variable implementations of the protocol using propagating microwave modes. The first implementation uses propagating Schr o ̈ dinger cat states as the flying ancilla qubits, a joint-photon-number-modulo-2 measurement of the propagating modes for the two-qubit measurement, and homodyne detections as the final single-qubit measurements. The presence of inefficiencies in realistic quantum systems limit the success rate of generating high fidelity Bell states. This motivates us to propose a second continuous variable implementation, where we use quantum error correction to suppress the decoherence due to photon loss to first order. To that end, we encode the ancilla qubits in superpositions of Schrödinger cat states of a given photon-number parity, use a joint-photon-number-modulo-4 measurement as the two-qubit measurement, and homodyne detections as the final single-qubit measurements. We demonstrate the resilience of our quantum-error-correcting remote entanglement scheme to imperfections. Further, we describe a modification of our error-correcting scheme by incorporating additional individual photon-number-modulo-2 measurements of the ancilla modes to improve the success rate of generating high-fidelity Bell states. Our protocols can be straightforwardly implemented in state-of-the-art superconducting circuit-QED systems.

Describing the dynamics of processes consisting simultaneously of Poissonian and non-Poissonian kinetics

NASA Astrophysics Data System (ADS)

Eule, S.; Friedrich, R.

2013-03-01

Dynamical processes exhibiting non-Poissonian kinetics with nonexponential waiting times are frequently encountered in nature. Examples are biochemical processes like gene transcription which are known to involve multiple intermediate steps. However, often a second process, obeying Poissonian statistics, affects the first one simultaneously, such as the degradation of mRNA in the above example. The aim of the present article is to provide a concise treatment of such random systems which are affected by regular and non-Poissonian kinetics at the same time. We derive the governing master equation and provide a controlled approximation scheme for this equation. The simplest approximation leads to generalized reaction rate equations. For a simple model of gene transcription we solve the resulting equation and show how the time evolution is influenced significantly by the type of waiting time distribution assumed for the non-Poissonian process.

Implications of fractured Arctic perennial ice cover on thermodynamic and dynamic sea ice processes

NASA Astrophysics Data System (ADS)

Asplin, Matthew G.; Scharien, Randall; Else, Brent; Howell, Stephen; Barber, David G.; Papakyriakou, Tim; Prinsenberg, Simon

2014-04-01

Decline of the Arctic summer minimum sea ice extent is characterized by large expanses of open water in the Siberian, Laptev, Chukchi, and Beaufort Seas, and introduces large fetch distances in the Arctic Ocean. Long waves can propagate deep into the pack ice, thereby causing flexural swell and failure of the sea ice. This process shifts the floe size diameter distribution smaller, increases floe surface area, and thereby affects sea ice dynamic and thermodynamic processes. The results of Radarsat-2 imagery analysis show that a flexural fracture event which occurred in the Beaufort Sea region on 6 September 2009 affected ˜40,000 km2. Open water fractional area in the area affected initially decreased from 3.7% to 2.7%, but later increased to ˜20% following wind-forced divergence of the ice pack. Energy available for lateral melting was assessed by estimating the change in energy entrainment from longwave and shortwave radiation in the mixed-layer of the ocean following flexural fracture. 11.54 MJ m-2 of additional energy for lateral melting of ice floes was identified in affected areas. The impact of this process in future Arctic sea ice melt seasons was assessed using estimations of earlier occurrences of fracture during the melt season, and is discussed in context with ocean heat fluxes, atmospheric mixing of the ocean mixed layer, and declining sea ice cover. We conclude that this process is an important positive feedback to Arctic sea ice loss, and timing of initiation is critical in how it affects sea ice thermodynamic and dynamic processes.

Inferring Instantaneous, Multivariate and Nonlinear Sensitivities for the Analysis of Feedback Processes in a Dynamical System: Lorenz Model Case Study

NASA Technical Reports Server (NTRS)

Aires, Filipe; Rossow, William B.; Hansen, James E. (Technical Monitor)

2001-01-01

A new approach is presented for the analysis of feedback processes in a nonlinear dynamical system by observing its variations. The new methodology consists of statistical estimates of the sensitivities between all pairs of variables in the system based on a neural network modeling of the dynamical system. The model can then be used to estimate the instantaneous, multivariate and nonlinear sensitivities, which are shown to be essential for the analysis of the feedbacks processes involved in the dynamical system. The method is described and tested on synthetic data from the low-order Lorenz circulation model where the correct sensitivities can be evaluated analytically.

Real-time image processing for non-contact monitoring of dynamic displacements using smartphone technologies

NASA Astrophysics Data System (ADS)

Min, Jae-Hong; Gelo, Nikolas J.; Jo, Hongki

2016-04-01

The newly developed smartphone application, named RINO, in this study allows measuring absolute dynamic displacements and processing them in real time using state-of-the-art smartphone technologies, such as high-performance graphics processing unit (GPU), in addition to already powerful CPU and memories, embedded high-speed/ resolution camera, and open-source computer vision libraries. A carefully designed color-patterned target and user-adjustable crop filter enable accurate and fast image processing, allowing up to 240fps for complete displacement calculation and real-time display. The performances of the developed smartphone application are experimentally validated, showing comparable accuracy with those of conventional laser displacement sensor.

Yeast population dynamics of industrial fuel-ethanol fermentation process assessed by PCR-fingerprinting.

PubMed

da Silva-Filho, Eurípedes Alves; Brito dos Santos, Scheila Karina; Resende, Alecsandra do Monte; de Morais, José Otamar Falcão; de Morais, Marcos Antonio; Ardaillon Simões, Diogo

2005-07-01

Yeast population used in industrial production of fuel-ethanol may vary according to the plant process condition and to the environmental stresses imposed to yeast cells. Therefore, yeast strains isolated from a particular industrial process may be adapted to such conditions and should be used as starter strain instead of less adapted commercial strains. This work reports the use of PCR-fingerprinting method based on microsatellite primer (GTG)5 to characterize the yeast population dynamics along the fermentation period in six distilleries. The results show that indigenous fermenting strains present in the crude substrate can be more adapted to the industrial process than commercial strains. We also identified new strains that dominate the yeast population and were more present either in molasses or sugar cane fermenting distilleries. Those strains were proposed to be used as starters in those industrial processes. This is the first report on the use of molecular markers to discriminate Saccharomyces cerevisiae strains from fuel-ethanol producing process.

Introduction to focus issue: intrinsic and designed computation: information processing in dynamical systems--beyond the digital hegemony.

PubMed

Crutchfield, James P; Ditto, William L; Sinha, Sudeshna

2010-09-01

How dynamical systems store and process information is a fundamental question that touches a remarkably wide set of contemporary issues: from the breakdown of Moore's scaling laws--that predicted the inexorable improvement in digital circuitry--to basic philosophical problems of pattern in the natural world. It is a question that also returns one to the earliest days of the foundations of dynamical systems theory, probability theory, mathematical logic, communication theory, and theoretical computer science. We introduce the broad and rather eclectic set of articles in this Focus Issue that highlights a range of current challenges in computing and dynamical systems.

The instrumental genesis process in future primary teachers using Dynamic Geometry Software

NASA Astrophysics Data System (ADS)

Ruiz-López, Natalia

2018-05-01

This paper, which describes a study undertaken with pairs of future primary teachers using GeoGebra software to solve geometry problems, includes a brief literature review, the theoretical framework and methodology used. An analysis of the instrumental genesis process for a pair participating in the case study is also provided. This analysis addresses the techniques and types of dragging used, the obstacles to learning encountered, a description of the interaction between the pair and their interaction with the teacher, and the type of language used. Based on this analysis, possibilities and limitations of the instrumental genesis process are identified for the development of geometric competencies such as conjecture creation, property checking and problem researching. It is also suggested that the methodology used in the analysis of the problem solving process may be useful for those teachers and researchers who want to integrate Dynamic Geometry Software (DGS) in their classrooms.

Correlation of bistranded clustered abasic DNA lesion processing with structural and dynamic DNA helix distortion

PubMed Central

Bignon, Emmanuelle; Gattuso, Hugo; Morell, Christophe; Dehez, François; Georgakilas, Alexandros G.; Monari, Antonio; Dumont, Elise

2016-01-01

Clustered apurinic/apyrimidinic (AP; abasic) DNA lesions produced by ionizing radiation are by far more cytotoxic than isolated AP lesion entities. The structure and dynamics of a series of seven 23-bp oligonucleotides featuring simple bistranded clustered damage sites, comprising of two AP sites, zero, one, three or five bases 3′ or 5′ apart from each other, were investigated through 400 ns explicit solvent molecular dynamics simulations. They provide representative structures of synthetically engineered multiply damage sites-containing oligonucleotides whose repair was investigated experimentally (Nucl. Acids Res. 2004, 32:5609-5620; Nucl. Acids Res. 2002, 30: 2800–2808). The inspection of extrahelical positioning of the AP sites, bulge and non Watson–Crick hydrogen bonding corroborates the experimental measurements of repair efficiencies by bacterial or human AP endonucleases Nfo and APE1, respectively. This study provides unprecedented knowledge into the structure and dynamics of clustered abasic DNA lesions, notably rationalizing the non-symmetry with respect to 3′ to 5′ position. In addition, it provides strong mechanistic insights and basis for future studies on the effects of clustered DNA damage on the recognition and processing of these lesions by bacterial or human DNA repair enzymes specialized in the processing of such lesions. PMID:27587587

On the degree distribution of horizontal visibility graphs associated with Markov processes and dynamical systems: diagrammatic and variational approaches

NASA Astrophysics Data System (ADS)

Lacasa, Lucas

2014-09-01

Dynamical processes can be transformed into graphs through a family of mappings called visibility algorithms, enabling the possibility of (i) making empirical time series analysis and signal processing and (ii) characterizing classes of dynamical systems and stochastic processes using the tools of graph theory. Recent works show that the degree distribution of these graphs encapsulates much information on the signals' variability, and therefore constitutes a fundamental feature for statistical learning purposes. However, exact solutions for the degree distributions are only known in a few cases, such as for uncorrelated random processes. Here we analytically explore these distributions in a list of situations. We present a diagrammatic formalism which computes for all degrees their corresponding probability as a series expansion in a coupling constant which is the number of hidden variables. We offer a constructive solution for general Markovian stochastic processes and deterministic maps. As case tests we focus on Ornstein-Uhlenbeck processes, fully chaotic and quasiperiodic maps. Whereas only for certain degree probabilities can all diagrams be summed exactly, in the general case we show that the perturbation theory converges. In a second part, we make use of a variational technique to predict the complete degree distribution for special classes of Markovian dynamics with fast-decaying correlations. In every case we compare the theory with numerical experiments.

Face processing regions are sensitive to distinct aspects of temporal sequence in facial dynamics.

PubMed

Reinl, Maren; Bartels, Andreas

2014-11-15

Facial movement conveys important information for social interactions, yet its neural processing is poorly understood. Computational models propose that shape- and temporal sequence sensitive mechanisms interact in processing dynamic faces. While face processing regions are known to respond to facial movement, their sensitivity to particular temporal sequences has barely been studied. Here we used fMRI to examine the sensitivity of human face-processing regions to two aspects of directionality in facial movement trajectories. We presented genuine movie recordings of increasing and decreasing fear expressions, each of which were played in natural or reversed frame order. This two-by-two factorial design matched low-level visual properties, static content and motion energy within each factor, emotion-direction (increasing or decreasing emotion) and timeline (natural versus artificial). The results showed sensitivity for emotion-direction in FFA, which was timeline-dependent as it only occurred within the natural frame order, and sensitivity to timeline in the STS, which was emotion-direction-dependent as it only occurred for decreased fear. The occipital face area (OFA) was sensitive to the factor timeline. These findings reveal interacting temporal sequence sensitive mechanisms that are responsive to both ecological meaning and to prototypical unfolding of facial dynamics. These mechanisms are temporally directional, provide socially relevant information regarding emotional state or naturalness of behavior, and agree with predictions from modeling and predictive coding theory. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Comparison of ensemble post-processing approaches, based on empirical and dynamical error modelisation of rainfall-runoff model forecasts

NASA Astrophysics Data System (ADS)

Chardon, J.; Mathevet, T.; Le Lay, M.; Gailhard, J.

2012-04-01

In the context of a national energy company (EDF : Electricité de France), hydro-meteorological forecasts are necessary to ensure safety and security of installations, meet environmental standards and improve water ressources management and decision making. Hydrological ensemble forecasts allow a better representation of meteorological and hydrological forecasts uncertainties and improve human expertise of hydrological forecasts, which is essential to synthesize available informations, coming from different meteorological and hydrological models and human experience. An operational hydrological ensemble forecasting chain has been developed at EDF since 2008 and is being used since 2010 on more than 30 watersheds in France. This ensemble forecasting chain is characterized ensemble pre-processing (rainfall and temperature) and post-processing (streamflow), where a large human expertise is solicited. The aim of this paper is to compare 2 hydrological ensemble post-processing methods developed at EDF in order improve ensemble forecasts reliability (similar to Monatanari &Brath, 2004; Schaefli et al., 2007). The aim of the post-processing methods is to dress hydrological ensemble forecasts with hydrological model uncertainties, based on perfect forecasts. The first method (called empirical approach) is based on a statistical modelisation of empirical error of perfect forecasts, by streamflow sub-samples of quantile class and lead-time. The second method (called dynamical approach) is based on streamflow sub-samples of quantile class and streamflow variation, and lead-time. On a set of 20 watersheds used for operational forecasts, results show that both approaches are necessary to ensure a good post-processing of hydrological ensemble, allowing a good improvement of reliability, skill and sharpness of ensemble forecasts. The comparison of the empirical and dynamical approaches shows the limits of the empirical approach which is not able to take into account hydrological

Bioattractors: dynamical systems theory and the evolution of regulatory processes.

PubMed

Jaeger, Johannes; Monk, Nick

2014-06-01

In this paper, we illustrate how dynamical systems theory can provide a unifying conceptual framework for evolution of biological regulatory systems. Our argument is that the genotype-phenotype map can be characterized by the phase portrait of the underlying regulatory process. The features of this portrait--such as attractors with associated basins and their bifurcations--define the regulatory and evolutionary potential of a system. We show how the geometric analysis of phase space connects Waddington's epigenetic landscape to recent computational approaches for the study of robustness and evolvability in network evolution. We discuss how the geometry of phase space determines the probability of possible phenotypic transitions. Finally, we demonstrate how the active, self-organizing role of the environment in phenotypic evolution can be understood in terms of dynamical systems concepts. This approach yields mechanistic explanations that go beyond insights based on the simulation of evolving regulatory networks alone. Its predictions can now be tested by studying specific, experimentally tractable regulatory systems using the tools of modern systems biology. A systematic exploration of such systems will enable us to understand better the nature and origin of the phenotypic variability, which provides the substrate for evolution by natural selection. © 2014 The Authors. The Journal of Physiology © 2014 The Physiological Society.

Bioattractors: dynamical systems theory and the evolution of regulatory processes

PubMed Central

Jaeger, Johannes; Monk, Nick

2014-01-01

In this paper, we illustrate how dynamical systems theory can provide a unifying conceptual framework for evolution of biological regulatory systems. Our argument is that the genotype–phenotype map can be characterized by the phase portrait of the underlying regulatory process. The features of this portrait – such as attractors with associated basins and their bifurcations – define the regulatory and evolutionary potential of a system. We show how the geometric analysis of phase space connects Waddington's epigenetic landscape to recent computational approaches for the study of robustness and evolvability in network evolution. We discuss how the geometry of phase space determines the probability of possible phenotypic transitions. Finally, we demonstrate how the active, self-organizing role of the environment in phenotypic evolution can be understood in terms of dynamical systems concepts. This approach yields mechanistic explanations that go beyond insights based on the simulation of evolving regulatory networks alone. Its predictions can now be tested by studying specific, experimentally tractable regulatory systems using the tools of modern systems biology. A systematic exploration of such systems will enable us to understand better the nature and origin of the phenotypic variability, which provides the substrate for evolution by natural selection. PMID:24882812

Dynamic global model of oxide Czochralski process with weighing control

NASA Astrophysics Data System (ADS)

Mamedov, V. M.; Vasiliev, M. G.; Yuferev, V. S.

2011-03-01

A dynamic model of oxide Czochralski growth with weighing control has been developed for the first time. A time-dependent approach is used for the calculation of temperature fields in different parts of a crystallization set-up and convection patterns in a melt, while internal radiation in crystal is considered in a quasi-steady approximation. A special algorithm is developed for the calculation of displacement of a triple point and simulation of a crystal surface formation. To calculate variations in the heat generation, a model of weighing control with a commonly used PID regulator is applied. As an example, simulation of the growth process of gallium-gadolinium garnet (GGG) crystals starting from the stage of seeding is performed.

Fixed and dynamic predictors of treatment process in therapeutic communities for substance abusers in Belgium.

PubMed

Goethals, Ilse; Vanderplasschen, Wouter; Vandevelde, Stijn; Broekaert, Eric

2012-10-11

Research on substance abuse treatment services in general reflects substantial attention to the notion of treatment process. Despite the growing popularity of process studies, only a few researchers have used instruments specifically tailored to measure the therapeutic community (TC) treatment process, and even fewer have investigated client attributes in relation to early TC treatment process experiences. The aim of the current study is to address this gap by exploring clients' early in-treatment experiences and to determine the predictors that are related to the treatment process, using a TC-specific multidimensional instrument. Data was gathered among 157 adults in five TCs in Flanders (Belgium). Descriptive statistics were used to explore clients' early in-treatment experiences and multiple linear regressions were conducted to determine the fixed and dynamic predictors of Community Environment and Personal Development and Change (two indicators of TC treatment process). Clients reveal a more positive first-month response to TC social processes than to personal-development processes that require self-reflection and insight. The variance in clients' ratings of Community Environment was primarily due to dynamic client factors, while the variance in clients' ratings of Personal Development and Change was only related to fixed client factors. Suitability for treatment was the strongest predictor of Community Environment ratings, whereas a judicial referral more strongly predicted Personal Development and Change scores. Special attention should be devoted to suitability for treatment as part of motivational assessment as this seems to be a very strong predictor of how clients react to the initiation stage of TC treatment. To help improve clients' (meta-)cognitive skills needed to achieve insight and self-reflection and perhaps speed up the process of recovery, the authors suggest the introduction of (meta-)cognitive training strategies in the pre-program and/or the

Dynamic control of remelting processes

DOEpatents

Bertram, Lee A.; Williamson, Rodney L.; Melgaard, David K.; Beaman, Joseph J.; Evans, David G.

2000-01-01

An apparatus and method of controlling a remelting process by providing measured process variable values to a process controller; estimating process variable values using a process model of a remelting process; and outputting estimated process variable values from the process controller. Feedback and feedforward control devices receive the estimated process variable values and adjust inputs to the remelting process. Electrode weight, electrode mass, electrode gap, process current, process voltage, electrode position, electrode temperature, electrode thermal boundary layer thickness, electrode velocity, electrode acceleration, slag temperature, melting efficiency, cooling water temperature, cooling water flow rate, crucible temperature profile, slag skin temperature, and/or drip short events are employed, as are parameters representing physical constraints of electroslag remelting or vacuum arc remelting, as applicable.

Acquisition and Analysis of Dynamic Responses of a Historic Pedestrian Bridge using Video Image Processing

NASA Astrophysics Data System (ADS)

O'Byrne, Michael; Ghosh, Bidisha; Schoefs, Franck; O'Donnell, Deirdre; Wright, Robert; Pakrashi, Vikram

2015-07-01

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalisedcross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.

Acquisition and Analysis of Dynamic Responses of a Historic Pedestrian Bridge using Video Image Processing

NASA Astrophysics Data System (ADS)

O'Byrne, Michael; Ghosh, Bidisha; Schoefs, Franck; O'Donnell, Deirdre; Wright, Robert; Pakrashi, Vikram

2015-07-01

Video based tracking is capable of analysing bridge vibrations that are characterised by large amplitudes and low frequencies. This paper presents the use of video images and associated image processing techniques to obtain the dynamic response of a pedestrian suspension bridge in Cork, Ireland. This historic structure is one of the four suspension bridges in Ireland and is notable for its dynamic nature. A video camera is mounted on the river-bank and the dynamic responses of the bridge have been measured from the video images. The dynamic response is assessed without the need of a reflector on the bridge and in the presence of various forms of luminous complexities in the video image scenes. Vertical deformations of the bridge were measured in this regard. The video image tracking for the measurement of dynamic responses of the bridge were based on correlating patches in time-lagged scenes in video images and utilisinga zero mean normalised cross correlation (ZNCC) metric. The bridge was excited by designed pedestrian movement and by individual cyclists traversing the bridge. The time series data of dynamic displacement responses of the bridge were analysedto obtain the frequency domain response. Frequencies obtained from video analysis were checked against accelerometer data from the bridge obtained while carrying out the same set of experiments used for video image based recognition.

The dynamic nature of the reconsolidation process and its boundary conditions: Evidence based on human tests.

PubMed

Fernández, Rodrigo S; Bavassi, Luz; Forcato, Cecilia; Pedreira, María E

2016-04-01

The reconsolidation process is the mechanism by which the strength and/or content of consolidated memories are updated. This process is triggered by the presentation of a reminder (training cues). It is not always possible to trigger the reconsolidation process. For example, memory age and strength are boundary conditions for the reconsolidation process. Here, we investigated the dynamic changes in these conditions. We propose that the boundary conditions of the reconsolidation process are not fixed and vary as a consequence of the interaction between memory features and reminder characteristics. To modify memory properties, participants received a threatening social protocol that improves memory acquisition or a control condition (fake, without social interaction) prior to learning pairs of meaningless syllables. To determine whether a strong young or old declarative memory undergoes the reconsolidation process, we used an interference task (a second list of pairs of meaningless syllables) to disrupt memory re-stabilization. To assess whether the older memory could be strengthened, we repeated the triggering of reconsolidation. Strong young or old memories modulated by a threatening experience could be interfered during reconsolidation and updated (strengthened) by reconsolidation. Rather than being fixed, boundary conditions vary according to the memory features (strong memory), which indicates the dynamic nature of the reconsolidation process. Our findings demonstrate that it is possible to modify these limits by recruiting the reconsolidation process and making it functionally operative again. This novel scenario opens the possibility to new therapeutically approaches that take into account the reconsolidation process. Copyright © 2016 Elsevier Inc. All rights reserved.

High speed imaging of dynamic processes with a switched source x-ray CT system

NASA Astrophysics Data System (ADS)

Thompson, William M.; Lionheart, William R. B.; Morton, Edward J.; Cunningham, Mike; Luggar, Russell D.

2015-05-01

Conventional x-ray computed tomography (CT) scanners are limited in their scanning speed by the mechanical constraints of their rotating gantries and as such do not provide the necessary temporal resolution for imaging of fast-moving dynamic processes, such as moving fluid flows. The Real Time Tomography (RTT) system is a family of fast cone beam CT scanners which instead use multiple fixed discrete sources and complete rings of detectors in an offset geometry. We demonstrate the potential of this system for use in the imaging of such high speed dynamic processes and give results using simulated and real experimental data. The unusual scanning geometry results in some challenges in image reconstruction, which are overcome using algebraic iterative reconstruction techniques and explicit regularisation. Through the use of a simple temporal regularisation term and by optimising the source firing pattern, we show that temporal resolution of the system may be increased at the expense of spatial resolution, which may be advantageous in some situations. Results are given showing temporal resolution of approximately 500 µs with simulated data and 3 ms with real experimental data.

Evolution of continental-scale drainage in response to mantle dynamics and surface processes: An example from the Ethiopian Highlands

NASA Astrophysics Data System (ADS)

Sembroni, Andrea; Molin, Paola; Pazzaglia, Frank J.; Faccenna, Claudio; Abebe, Bekele

2016-05-01

Ethiopia offers an excellent opportunity to study the effects and linkage between mantle dynamics and surface processes on landscape evolution. The Ethiopian Highlands (NW Ethiopia), characterized by a huge basaltic plateau, is part of the African Superswell, a wide region of dynamically-supported anomalously high topography related to the rising of the Afar plume. The initiation and steadiness of dynamic support beneath Ethiopia has been explored in several studies. However the presence, role, and timing of dynamic support beneath Ethiopia and its relationship with continental flood basalts volcanism and surface processes are poorly defined. Here, we present a geomorphological analysis of the Ethiopian Highlands supplying new constraints on the evolution of river network. We investigated the general topographic features (filtered topography, swath profiles, local relief) and the river network (river longitudinal profiles) of the study area. We also apply a knickpoint celerity model in order to provide a chronological framework to the evolution of the river network. The results trace the long-term progressive capture of the Ethiopian Highlands drainage system and confirm the long-term dynamic support of the area, documenting its impact on the contrasting development of the Blue Nile and Tekeze basins.

Evolution of continental-scale drainage in response to mantle dynamics and surface processes: an example from the Ethiopian Highlands.

NASA Astrophysics Data System (ADS)

Sembroni, Andrea; Molin, Paola; Pazzaglia, Frank J.; Faccenna, Claudio; Abebe, Bekele

2016-04-01

Ethiopia offers an excellent opportunity to study the effects and linkage between mantle dynamics and surface processes on landscape evolution. The Ethiopian Highlands (NW Ethiopia), characterized by a huge basaltic plateau, is part of the African Superswell, a wide region of dynamically-supported anomalously high topography related to the rising of the Afar plume. The initiation and steadiness of dynamic support beneath Ethiopia has been explored in several studies. However the presence, role, and timing of dynamic support beneath Ethiopia and its relationship with continental flood basalts volcanism and surface processes are poorly defined. Here, we present a geomorphological analysis of the Ethiopian Highlands supplying new constrains on the evolution of river network. We investigated the general topographic features (filtered topography, swath profiles, local relief) and the river network (river longitudinal profiles) of the study area. We also apply a knickpoint celerity model in order to provide a chronological framework to the evolution of the river network. The results trace the long-term progressive capture of the Ethiopian Highlands drainage system and confirm the long-term dynamic support of the area, documenting its impact on the contrasting development of the Blue Nile and Tekeze basins.

Key Process Uncertainties in Soil Carbon Dynamics: Comparing Multiple Model Structures and Observational Meta-analysis

NASA Astrophysics Data System (ADS)

Sulman, B. N.; Moore, J.; Averill, C.; Abramoff, R. Z.; Bradford, M.; Classen, A. T.; Hartman, M. D.; Kivlin, S. N.; Luo, Y.; Mayes, M. A.; Morrison, E. W.; Riley, W. J.; Salazar, A.; Schimel, J.; Sridhar, B.; Tang, J.; Wang, G.; Wieder, W. R.

2016-12-01

Soil carbon (C) dynamics are crucial to understanding and predicting C cycle responses to global change and soil C modeling is a key tool for understanding these dynamics. While first order model structures have historically dominated this area, a recent proliferation of alternative model structures representing different assumptions about microbial activity and mineral protection is providing new opportunities to explore process uncertainties related to soil C dynamics. We conducted idealized simulations of soil C responses to warming and litter addition using models from five research groups that incorporated different sets of assumptions about processes governing soil C decomposition and stabilization. We conducted a meta-analysis of published warming and C addition experiments for comparison with simulations. Assumptions related to mineral protection and microbial dynamics drove strong differences among models. In response to C additions, some models predicted long-term C accumulation while others predicted transient increases that were counteracted by accelerating decomposition. In experimental manipulations, doubling litter addition did not change soil C stocks in studies spanning as long as two decades. This result agreed with simulations from models with strong microbial growth responses and limited mineral sorption capacity. In observations, warming initially drove soil C loss via increased CO2 production, but in some studies soil C rebounded and increased over decadal time scales. In contrast, all models predicted sustained C losses under warming. The disagreement with experimental results could be explained by physiological or community-level acclimation, or by warming-related changes in plant growth. In addition to the role of microbial activity, assumptions related to mineral sorption and protected C played a key role in driving long-term model responses. In general, simulations were similar in their initial responses to perturbations but diverged over

Near infrared spectroscopy based monitoring of extraction processes of raw material with the help of dynamic predictive modeling

NASA Astrophysics Data System (ADS)

Wang, Haixia; Suo, Tongchuan; Wu, Xiaolin; Zhang, Yue; Wang, Chunhua; Yu, Heshui; Li, Zheng

2018-03-01

The control of batch-to-batch quality variations remains a challenging task for pharmaceutical industries, e.g., traditional Chinese medicine (TCM) manufacturing. One difficult problem is to produce pharmaceutical products with consistent quality from raw material of large quality variations. In this paper, an integrated methodology combining the near infrared spectroscopy (NIRS) and dynamic predictive modeling is developed for the monitoring and control of the batch extraction process of licorice. With the spectra data in hand, the initial state of the process is firstly estimated with a state-space model to construct a process monitoring strategy for the early detection of variations induced by the initial process inputs such as raw materials. Secondly, the quality property of the end product is predicted at the mid-course during the extraction process with a partial least squares (PLS) model. The batch-end-time (BET) is then adjusted accordingly to minimize the quality variations. In conclusion, our study shows that with the help of the dynamic predictive modeling, NIRS can offer the past and future information of the process, which enables more accurate monitoring and control of process performance and product quality.

Improving predictions of large scale soil carbon dynamics: Integration of fine-scale hydrological and biogeochemical processes, scaling, and benchmarking

NASA Astrophysics Data System (ADS)

Riley, W. J.; Dwivedi, D.; Ghimire, B.; Hoffman, F. M.; Pau, G. S. H.; Randerson, J. T.; Shen, C.; Tang, J.; Zhu, Q.

2015-12-01

Numerical model representations of decadal- to centennial-scale soil-carbon dynamics are a dominant cause of uncertainty in climate change predictions. Recent attempts by some Earth System Model (ESM) teams to integrate previously unrepresented soil processes (e.g., explicit microbial processes, abiotic interactions with mineral surfaces, vertical transport), poor performance of many ESM land models against large-scale and experimental manipulation observations, and complexities associated with spatial heterogeneity highlight the nascent nature of our community's ability to accurately predict future soil carbon dynamics. I will present recent work from our group to develop a modeling framework to integrate pore-, column-, watershed-, and global-scale soil process representations into an ESM (ACME), and apply the International Land Model Benchmarking (ILAMB) package for evaluation. At the column scale and across a wide range of sites, observed depth-resolved carbon stocks and their 14C derived turnover times can be explained by a model with explicit representation of two microbial populations, a simple representation of mineralogy, and vertical transport. Integrating soil and plant dynamics requires a 'process-scaling' approach, since all aspects of the multi-nutrient system cannot be explicitly resolved at ESM scales. I will show that one approach, the Equilibrium Chemistry Approximation, improves predictions of forest nitrogen and phosphorus experimental manipulations and leads to very different global soil carbon predictions. Translating model representations from the site- to ESM-scale requires a spatial scaling approach that either explicitly resolves the relevant processes, or more practically, accounts for fine-resolution dynamics at coarser scales. To that end, I will present recent watershed-scale modeling work that applies reduced order model methods to accurately scale fine-resolution soil carbon dynamics to coarse-resolution simulations. Finally, we

Some uses of wavelets for imaging dynamic processes in live cochlear structures

NASA Astrophysics Data System (ADS)

Boutet de Monvel, J.

2007-09-01

A variety of image and signal processing algorithms based on wavelet filtering tools have been developed during the last few decades, that are well adapted to the experimental variability typically encountered in live biological microscopy. A number of processing tools are reviewed, that use wavelets for adaptive image restoration and for motion or brightness variation analysis by optical flow computation. The usefulness of these tools for biological imaging is illustrated in the context of the restoration of images of the inner ear and the analysis of cochlear motion patterns in two and three dimensions. I also report on recent work that aims at capturing fluorescence intensity changes associated with vesicle dynamics at synaptic zones of sensory hair cells. This latest application requires one to separate the intensity variations associated with the physiological process under study from the variations caused by motion of the observed structures. A wavelet optical flow algorithm for doing this is presented, and its effectiveness is demonstrated on artificial and experimental image sequences.

Oscillatory brain dynamics associated with the automatic processing of emotion in words.

PubMed

Wang, Lin; Bastiaansen, Marcel

2014-10-01

This study examines the automaticity of processing the emotional aspects of words, and characterizes the oscillatory brain dynamics that accompany this automatic processing. Participants read emotionally negative, neutral and positive nouns while performing a color detection task in which only perceptual-level analysis was required. Event-related potentials and time frequency representations were computed from the concurrently measured EEG. Negative words elicited a larger P2 and a larger late positivity than positive and neutral words, indicating deeper semantic/evaluative processing of negative words. In addition, sustained alpha power suppressions were found for the emotional compared to neutral words, in the time range from 500 to 1000ms post-stimulus. These results suggest that sustained attention was allocated to the emotional words, whereas the attention allocated to the neutral words was released after an initial analysis. This seems to hold even when the emotional content of the words is task-irrelevant. Copyright © 2014 Elsevier Inc. All rights reserved.

Heat Exchange Processes and Thermal Dynamics of a Glacier-Fed Stream

NASA Astrophysics Data System (ADS)

Khamis, K.; Hannah, D. M.; Brown, L. E.; Milner, A. M.

2012-12-01

Glacier-fed river thermal regimes vary markedly in space and time. However, knowledge is limited of fundamental processes controlling alpine stream temperature dynamics. The few studies have not sufficiently characterised above-stream micro-climate and have been limited to single melt seasons. To address the research gap, this study quantified heat exchanges at the water surface and bed of a glacier fed stream over two summers to improve understanding of factors and processes driving thermal dynamics. An automatic weather station and river gauge were set up on a stream 1.5 km from the Taillon Glacier, French Pyrénées. Hydro-meteorological observations were recorded at 15-min intervals between 16 June-2 September 2010 and 2011. Energy balance components were measured [net radiation (Q*); bed heat flux (Qbhf)] or estimated based on site-specific data [sensible heat transfer (Qh); latent heat (Qe); fluid friction (Qf)]. During 2010, snowline altitude was lower and glacier ablation occurred in late season. During 2010, the mean snowline altitude was lower and ablation of glacier ice occurred later in the season Mean water temperature was lower (-0.8°C), precipitation greater (+87mm) and daily discharge variation lower (-0.03 m3s-1) than 2011. The net heat budget was strongly positive in both summers, with the majority of energy exchanged at the air-water interface. Averaged over the seasons, Q* was the largest heat source (~80% of total flux); Qh (~13%) and Qf (~3%) were also sources. Qe displayed inter-annual variability; during 2010 (2011) it contributed 5.2% (0.03%) of the total heat budget due to windier, drier conditions that offset early season condensation gains with late season evaporative losses. Energy exchanges at the channel - river bed interface comprised <1% of the heat budget; Qbhf was a sink (source) during 2010 (2011). Daily flux totals were used to characterize sub-seasonal dynamics. Declines in net radiation receipt and total energy available to

Dynamic Optimization

NASA Technical Reports Server (NTRS)

Laird, Philip

1992-01-01

We distinguish static and dynamic optimization of programs: whereas static optimization modifies a program before runtime and is based only on its syntactical structure, dynamic optimization is based on the statistical properties of the input source and examples of program execution. Explanation-based generalization is a commonly used dynamic optimization method, but its effectiveness as a speedup-learning method is limited, in part because it fails to separate the learning process from the program transformation process. This paper describes a dynamic optimization technique called a learn-optimize cycle that first uses a learning element to uncover predictable patterns in the program execution and then uses an optimization algorithm to map these patterns into beneficial transformations. The technique has been used successfully for dynamic optimization of pure Prolog.

The Role of Linkers in the Excited-State Dynamic Planarization Processes of Macrocyclic Oligothiophene 12-Mers.

PubMed

Kim, Woojae; Sung, Jooyoung; Park, Kyu Hyung; Shimizu, Hideyuki; Imamura, Mika; Han, Minwoo; Sim, Eunji; Iyoda, Masahiko; Kim, Dongho

2015-11-05

Linkers adjoining chromophores play an important role in modulating the structure of conjugated systems, which is bound up with their photophysical properties. However, to date, the focus of works dealing with linker effects was limited only to linear π-conjugated materials, and there have been no detailed studies on cyclic counterparts. Herein we report the linker effects on the dynamic planarization processes of π-conjugated macrocyclic oligothiophene 12-mers, where the different ratio between ethynylene and vinylene linkers was chosen to control the backbone rigidity. By analyzing transient fluorescence spectra, we demonstrate that the connecting linkers play a crucial role in the excited-state dynamics of cyclic conjugated systems. Faster dynamic planarization, longer exciton delocalization length, and higher degree of planarity were observed in vinylene inserted cyclic oligothiophenes. Molecular dynamics simulations and density functional theory calculations also stress the importance of the role of linkers in modulating the structure of cyclic oligothiophenes.

Reconstruction of dynamical systems from resampled point processes produced by neuron models

NASA Astrophysics Data System (ADS)

Pavlova, Olga N.; Pavlov, Alexey N.

2018-04-01

Characterization of dynamical features of chaotic oscillations from point processes is based on embedding theorems for non-uniformly sampled signals such as the sequences of interspike intervals (ISIs). This theoretical background confirms the ability of attractor reconstruction from ISIs generated by chaotically driven neuron models. The quality of such reconstruction depends on the available length of the analyzed dataset. We discuss how data resampling improves the reconstruction for short amount of data and show that this effect is observed for different types of mechanisms for spike generation.

On the stability and dynamics of stochastic spiking neuron models: Nonlinear Hawkes process and point process GLMs

PubMed Central

Truccolo, Wilson

2017-01-01

Point process generalized linear models (PP-GLMs) provide an important statistical framework for modeling spiking activity in single-neurons and neuronal networks. Stochastic stability is essential when sampling from these models, as done in computational neuroscience to analyze statistical properties of neuronal dynamics and in neuro-engineering to implement closed-loop applications. Here we show, however, that despite passing common goodness-of-fit tests, PP-GLMs estimated from data are often unstable, leading to divergent firing rates. The inclusion of absolute refractory periods is not a satisfactory solution since the activity then typically settles into unphysiological rates. To address these issues, we derive a framework for determining the existence and stability of fixed points of the expected conditional intensity function (CIF) for general PP-GLMs. Specifically, in nonlinear Hawkes PP-GLMs, the CIF is expressed as a function of the previous spike history and exogenous inputs. We use a mean-field quasi-renewal (QR) approximation that decomposes spike history effects into the contribution of the last spike and an average of the CIF over all spike histories prior to the last spike. Fixed points for stationary rates are derived as self-consistent solutions of integral equations. Bifurcation analysis and the number of fixed points predict that the original models can show stable, divergent, and metastable (fragile) dynamics. For fragile models, fluctuations of the single-neuron dynamics predict expected divergence times after which rates approach unphysiologically high values. This metric can be used to estimate the probability of rates to remain physiological for given time periods, e.g., for simulation purposes. We demonstrate the use of the stability framework using simulated single-neuron examples and neurophysiological recordings. Finally, we show how to adapt PP-GLM estimation procedures to guarantee model stability. Overall, our results provide a

On the stability and dynamics of stochastic spiking neuron models: Nonlinear Hawkes process and point process GLMs.

PubMed

Gerhard, Felipe; Deger, Moritz; Truccolo, Wilson

2017-02-01

Point process generalized linear models (PP-GLMs) provide an important statistical framework for modeling spiking activity in single-neurons and neuronal networks. Stochastic stability is essential when sampling from these models, as done in computational neuroscience to analyze statistical properties of neuronal dynamics and in neuro-engineering to implement closed-loop applications. Here we show, however, that despite passing common goodness-of-fit tests, PP-GLMs estimated from data are often unstable, leading to divergent firing rates. The inclusion of absolute refractory periods is not a satisfactory solution since the activity then typically settles into unphysiological rates. To address these issues, we derive a framework for determining the existence and stability of fixed points of the expected conditional intensity function (CIF) for general PP-GLMs. Specifically, in nonlinear Hawkes PP-GLMs, the CIF is expressed as a function of the previous spike history and exogenous inputs. We use a mean-field quasi-renewal (QR) approximation that decomposes spike history effects into the contribution of the last spike and an average of the CIF over all spike histories prior to the last spike. Fixed points for stationary rates are derived as self-consistent solutions of integral equations. Bifurcation analysis and the number of fixed points predict that the original models can show stable, divergent, and metastable (fragile) dynamics. For fragile models, fluctuations of the single-neuron dynamics predict expected divergence times after which rates approach unphysiologically high values. This metric can be used to estimate the probability of rates to remain physiological for given time periods, e.g., for simulation purposes. We demonstrate the use of the stability framework using simulated single-neuron examples and neurophysiological recordings. Finally, we show how to adapt PP-GLM estimation procedures to guarantee model stability. Overall, our results provide a

Neural dynamics of feedforward and feedback processing in figure-ground segregation

PubMed Central

Layton, Oliver W.; Mingolla, Ennio; Yazdanbakhsh, Arash

2014-01-01

Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation) is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedback plays a crucial role in disambiguating a figure's interior and exterior. We introduce a processing strategy whereby jitter in RF center locations and variation in RF sizes is exploited to enhance and suppress neural activity inside and outside of figures, respectively. Feedforward projections emanate from units that model cells in V4 known to respond to the curvature of boundary contours (curved contour cells), and feedback projections from units predicted to exist in IT that strategically group neurons with different RF sizes and RF center locations (teardrop cells). Neurons (convex cells) that preferentially respond when centered on a figure dynamically balance feedforward (bottom-up) information and feedback from higher visual areas. The activation is enhanced when an interior portion of a figure is in the RF via feedback from units that detect closure in the boundary contours of a figure. Our model produces maximal activity along the medial axis of well-known figures with and without concavities, and inside algorithmically generated shapes. Our results suggest that the dynamic balancing of feedforward signals with the specific feedback mechanisms proposed by the model is crucial for figure-ground segregation. PMID:25346703

Neural dynamics of feedforward and feedback processing in figure-ground segregation.

PubMed

Layton, Oliver W; Mingolla, Ennio; Yazdanbakhsh, Arash

2014-01-01

Determining whether a region belongs to the interior or exterior of a shape (figure-ground segregation) is a core competency of the primate brain, yet the underlying mechanisms are not well understood. Many models assume that figure-ground segregation occurs by assembling progressively more complex representations through feedforward connections, with feedback playing only a modulatory role. We present a dynamical model of figure-ground segregation in the primate ventral stream wherein feedback plays a crucial role in disambiguating a figure's interior and exterior. We introduce a processing strategy whereby jitter in RF center locations and variation in RF sizes is exploited to enhance and suppress neural activity inside and outside of figures, respectively. Feedforward projections emanate from units that model cells in V4 known to respond to the curvature of boundary contours (curved contour cells), and feedback projections from units predicted to exist in IT that strategically group neurons with different RF sizes and RF center locations (teardrop cells). Neurons (convex cells) that preferentially respond when centered on a figure dynamically balance feedforward (bottom-up) information and feedback from higher visual areas. The activation is enhanced when an interior portion of a figure is in the RF via feedback from units that detect closure in the boundary contours of a figure. Our model produces maximal activity along the medial axis of well-known figures with and without concavities, and inside algorithmically generated shapes. Our results suggest that the dynamic balancing of feedforward signals with the specific feedback mechanisms proposed by the model is crucial for figure-ground segregation.

Mathematical and experimental modelling of the dynamic bubble processes occurring in a two-phase cyclonic separation device

NASA Astrophysics Data System (ADS)

Schrage, Dean Stewart

1998-11-01

This dissertation presents a combined mathematical and experimental analysis of the fluid dynamics of a gas- liquid, dispersed-phase cyclonic separation device. The global objective of this research is to develop a simulation model of separation process in order to predict the void fraction field within a cyclonic separation device. The separation process is approximated by analyzing the dynamic motion of many single-bubbles, moving under the influence of the far-field, interacting with physical boundaries and other bubbles. The dynamic motion of the bubble is described by treating the bubble as a point-mass and writing an inertial force balance, equating the force applied to the bubble-point-location to the inertial acceleration of the bubble mass (also applied to the point-location). The forces which are applied to the bubble are determined by an integration of the surface pressure over the bubble. The surface pressure is coupled to the intrinsic motion of the bubble, and is very difficult to obtain exactly. However, under moderate Reynolds number, the wake trailing a bubble is small and the near-field flow field can be approximated as an inviscid flow field. Unconventional potential flow techniques are employed to solve for the surface pressure; the hydrodyamic forces are described as a hydrodynamic mass tensor operating on the bubble acceleration vector. The inviscid flow model is augmented with adjunct forces which describe: drag forces, dynamic lift, far-field pressure forces. The dynamic equations of motion are solved both analytically and numerically for the bubble trajectory in specific flow field examples. A validation of these equations is performed by comparing to an experimentally-derived trajectory of a single- bubble, which is released into a cylindrical Couette flow field (inner cylinder rotating) at varying positions. Finally, a simulation of a cyclonic separation device is performed by extending the single-bubble dynamic model to a multi

Bayesian dynamic mediation analysis.

PubMed

Huang, Jing; Yuan, Ying

2017-12-01

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

Comparison of multichannel wide dynamic range compression and ChannelFree processing in open canal hearing instruments.

PubMed

Plyler, Patrick N; Reber, Monika Bertges; Kovach, Amanda; Galloway, Elisabeth; Humphrey, Elizabeth

2013-02-01

Multichannel wide dynamic range compression (WDRC) and ChannelFree processing have similar goals yet differ significantly in terms of signal processing. Multichannel WDRC devices divide the input signal into separate frequency bands; a separate level is determined within each frequency band; and compression in each band is based on the level within each band. ChannelFree processing detects the wideband level, and gain adjustments are based on the wideband signal level and adjusted up to 20,000 times per second. Although both signal processing strategies are currently available in hearing aids, it is unclear if differences in these signal processing strategies affect the performance and/or preference of the end user. The purpose of the research was to determine the effects of multichannel wide dynamic range compression and ChannelFree processing on performance and/or preference of listeners using open-canal hearing instruments. An experimental study in which subjects were exposed to a repeated measures design was utilized. Fourteen adult listeners with mild sloping to moderately severe sensorineural hearing loss participated (mean age 67 yr). Participants completed two 5 wk trial periods for each signal processing strategy. Probe microphone, behavioral and subjective measures were conducted unaided and aided at the end of each trial period. Behavioral and subjective results for both signal processing strategies were significantly better than unaided results; however, behavioral and subjective results were not significantly different between the signal processing strategies. Multichannel WDRC and ChannelFree processing are both effective signal processing strategies that provide significant benefit for hearing instrument users. Overall preference between the strategies may be related to the degree of hearing loss of the user, high-frequency in-situ levels, and/or acceptance of background noise. American Academy of Audiology.

Modelling nitrite dynamics and associated feedback processes in the Benguela oxygen minimum zone

NASA Astrophysics Data System (ADS)

Mashifane, T. B.; Vichi, M.; Waldron, H. N.; Machu, E.; Garçonc, V.

2016-08-01

Understanding nitrite dynamics in oxygen minimum zones (OMZs) is a challenge as it represents an intermediary nitrogen species with a short turnover time. Nitrite is also reduced to nitrogen in OMZs, preventing its accumulation. This creates difficulties in detecting nitrite with colorimetric methods as concentrations may occur below detection limits in some regions. Nitrite concentrations are key to understanding intermediate nitrogen processes and their implication for nitrogen loss in OMZs. A coupled physical-biogeochemical model is applied in the Benguela OMZ to study nitrite dynamics and its associated feedback processes. Simulated results show occurrence of primary and secondary nitrite maxima in the Benguela shelf waters. The primary nitrite maxima in the Benguela are attributed to nitrification and nitrate assimilation as they occur in association with the nitracline. Secondary nitrite maxima accumulate in the Angola-Benguela Front (ABF) OMZ and are attributed to denitrification. The secondary nitrite maxima are consumed by anaerobic ammonium oxidation (anammox) off Walvis Bay. Nitrite maxima are restricted to the shelf off Walvis Bay and advected offshore in the ABF region. Interchanges between the poleward South Atlantic Central Water (SACW) and the equatorward, well-aerated Eastern South Atlantic Central Water (ESACW) drive the seasonality of nitrogen processes in the Benguela. Subsequent nitrite reduction in the Benguela OMZ leads to nitrous oxide production, with high concentrations occurring in the ABF region as a result of nitrification and denitrification. Off Walvis Bay, nitrous oxide production is low since nitrite is consumed by anammox. Nitrous oxide production occurs in thermocline, intermediate and deeper water masses in the ABF region. High N fluxes in the Benguela are attributed to nitrification as compared to anammox and denitrification. Results from this study demonstrate the role of intermediate nitrogen species in nitrogen feedback

Photoinduced Single- and Multiple-Electron Dynamics Processes Enhanced by Quantum Confinement in Lead Halide Perovskite Quantum Dots

DOE PAGES

Vogel, Dayton J.; Kryjevski, Andrei; Inerbaev, Talgat; ...

2017-03-21

Methylammonium lead iodide perovskite (MAPbI 3) is a promising material for photovoltaic devices. A modification of MAPbI 3 into confined nanostructures is expected to further increase efficiency of solar energy conversion. Photoexcited dynamic processes in a MAPbI3 quantum dot (QD) have been modeled by many-body perturbation theory and nonadiabatic dynamics. A photoexcitation is followed by either exciton cooling (EC), its radiative (RR) or nonradiative recombination (NRR), or multiexciton generation (MEG) processes. Computed times of these processes fall in the order of MEG < EC < RR < NRR, where MEG is on the order of a few femtoseconds, EC ismore » in the picosecond range, while RR and NRR are on the order of nanoseconds. Computed time scales indicate which electronic transition pathways can contribute to increase in charge collection efficiency. Simulated mechanisms of relaxation and their rates show that quantum confinement promotes MEG in MAPbI 3 QDs.« less

Dynamic processes of the microbiota - from metagenomics to biofilms

NASA Astrophysics Data System (ADS)

Wingreen, Ned

The extent, origin, and impact of microbial diversity is a central question in biology. We expect that physical processes contribute to this diversity, but we are only beginning to explore the nature of these interactions. I will briefly discuss two approaches to this question, one based on metagenomics the other on observation of bacterial biofilms. First, I will address the challenge of identifying the constituents of microbial systems by presenting a new approach to analyzing community sequencing data that identifies microbial subpopulations while avoiding problematic clustering-based methods. Using data from a time-series study of human tongue microbiota, we were able to resolve within the standard definition of a ``species'' up to 20 ecologically distinct subpopulations with tag sequences differing by as little as one nucleotide (99.2% similarity). This fine resolution allowed us decouple sequence similarity from dynamical similarity, and to resolve dynamics on multiple time scales, including the slow appearance and disappearance of strains over months. Second, I will present recent results on the growth and competition of bacteria within biofilms. We imaged the growth ofliving biofilms of Vibrio choleraefrom single founder cells to ten thousand cells at single cell spatial resolution and with temporal resolution of one cell cycle. We discovered a transition from a branched 2D colony to a dense 3D cluster, in which cells at the biofilm center exhibit collective vertical alignment and local nematic packing. Our results suggest that biofilm cells exploit mechanics to simultaneously achieve strong surface adhesion, access to 3D space, resistance to invasion, and dominance over surface territory.

Dynamics of a new family of iterative processes for quadratic polynomials

NASA Astrophysics Data System (ADS)

Gutiérrez, J. M.; Hernández, M. A.; Romero, N.

2010-03-01

In this work we show the presence of the well-known Catalan numbers in the study of the convergence and the dynamical behavior of a family of iterative methods for solving nonlinear equations. In fact, we introduce a family of methods, depending on a parameter . These methods reach the order of convergence m+2 when they are applied to quadratic polynomials with different roots. Newton's and Chebyshev's methods appear as particular choices of the family appear for m=0 and m=1, respectively. We make both analytical and graphical studies of these methods, which give rise to rational functions defined in the extended complex plane. Firstly, we prove that the coefficients of the aforementioned family of iterative processes can be written in terms of the Catalan numbers. Secondly, we make an incursion into its dynamical behavior. In fact, we show that the rational maps related to these methods can be written in terms of the entries of the Catalan triangle. Next we analyze its general convergence, by including some computer plots showing the intricate structure of the Universal Julia sets associated with the methods.

Dynamic modeling of sludge compaction and consolidation processes in wastewater secondary settling tanks.

PubMed

Abusam, A; Keesman, K J

2009-01-01

The double exponential settling model is the widely accepted model for wastewater secondary settling tanks. However, this model does not estimate accurately solids concentrations in the settler underflow stream, mainly because sludge compression and consolidation processes are not considered. In activated sludge systems, accurate estimation of the solids in the underflow stream will facilitate the calibration process and can lead to correct estimates of particularly kinetic parameters related to biomass growth. Using principles of compaction and consolidation, as in soil mechanics, a dynamic model of the sludge consolidation processes taking place in the secondary settling tanks is developed and incorporated to the commonly used double exponential settling model. The modified double exponential model is calibrated and validated using data obtained from a full-scale wastewater treatment plant. Good agreement between predicted and measured data confirmed the validity of the modified model.

EEG source reconstruction reveals frontal-parietal dynamics of spatial conflict processing.

PubMed

Cohen, Michael X; Ridderinkhof, K Richard

2013-01-01

Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (∼200 ms post-stimulus) conflict modulation in stimulus-contralateral parietal gamma (30-50 Hz), followed by a later alpha-band (8-12 Hz) conflict modulation, suggesting an early detection of spatial conflict and inhibition of spatial location processing. Inter-regional connectivity analyses assessed via cross-frequency coupling of theta (4-8 Hz), alpha, and gamma power revealed conflict-induced shifts in cortical network interactions: Congruent trials (relative to incongruent trials) had stronger coupling between frontal theta and stimulus-contrahemifield parietal alpha/gamma power, whereas incongruent trials had increased theta coupling between medial frontal and lateral frontal regions. These findings shed new light into the large-scale network dynamics of spatial conflict processing, and how those networks are shaped by oscillatory interactions.

EEG Source Reconstruction Reveals Frontal-Parietal Dynamics of Spatial Conflict Processing

PubMed Central

Cohen, Michael X; Ridderinkhof, K. Richard

2013-01-01

Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (∼200 ms post-stimulus) conflict modulation in stimulus-contralateral parietal gamma (30–50 Hz), followed by a later alpha-band (8–12 Hz) conflict modulation, suggesting an early detection of spatial conflict and inhibition of spatial location processing. Inter-regional connectivity analyses assessed via cross-frequency coupling of theta (4–8 Hz), alpha, and gamma power revealed conflict-induced shifts in cortical network interactions: Congruent trials (relative to incongruent trials) had stronger coupling between frontal theta and stimulus-contrahemifield parietal alpha/gamma power, whereas incongruent trials had increased theta coupling between medial frontal and lateral frontal regions. These findings shed new light into the large-scale network dynamics of spatial conflict processing, and how those networks are shaped by oscillatory interactions. PMID:23451201

Profiling of dynamic changes in the microbial community during the soy sauce fermentation process.

PubMed

Wei, Quanzeng; Wang, Hongbin; Chen, Zhixin; Lv, Zhijia; Xie, Yufeng; Lu, Fuping

2013-10-01

Soy sauce is a traditional condiment manufactured by natural inoculation and mixed culture fermentation. As is well known, it is the microbial community that plays an important role in the formation of its flavors. However, to date, its dynamic changes during the long period of fermentation process are still unclear, intensively constraining the improvement and control of the soy sauce quality. In this work, we revealed the dynamic changes of the microbial community by combining a cultured dependent method and a cultured independent method of polymerase chain reaction (PCR)-denaturing gradient gel electrophoresis. Results indicated that the two methods verified and complemented each other in profiling microbial community, and that significant dynamics of the microbial community existed during the fermentation process, especially the strong inhibition of the growth of most of the microbes when entering into the mash stage from the koji stage. In the analysis of bacterial community, Staphylococcus and Bacillus were found to be the dominant bacteria and detected in the whole fermentation process. Kurthia and Klebsiella began to appear in the koji stage and then fade away in the early stage of the mash fermentation. In the analysis of fungal community, Aspergillus sojae and Zygosaccharomyces rouxii were found to be the dominant fungi in the koji and mash fermentation, respectively. It was clearly shown that when A. sojae decreased and disappeared in the middle stage of the mash fermentation, Z. rouxii appeared and increased at the meantime. Aspergillus parasiticus, Trichosporon ovoides and Trichosporon asahii also appeared in the koji and the early period of the mash fermentation and disappeared thereafter. Similar to Z. rouxii, Millerozyma farinosa and Peronospora farinosa were also found spontaneously which appeared in the mid-late period of the mash fermentation. The principal component analysis suggested that the microbial community underwent significant changes in

Double dynamic scaling in human communication dynamics

NASA Astrophysics Data System (ADS)

Wang, Shengfeng; Feng, Xin; Wu, Ye; Xiao, Jinhua

2017-05-01

In the last decades, human behavior has been deeply understanding owing to the huge quantities data of human behavior available for study. The main finding in human dynamics shows that temporal processes consist of high-activity bursty intervals alternating with long low-activity periods. A model, assuming the initiator of bursty follow a Poisson process, is widely used in the modeling of human behavior. Here, we provide further evidence for the hypothesis that different bursty intervals are independent. Furthermore, we introduce a special threshold to quantitatively distinguish the time scales of complex dynamics based on the hypothesis. Our results suggest that human communication behavior is a composite process of double dynamics with midrange memory length. The method for calculating memory length would enhance the performance of many sequence-dependent systems, such as server operation and topic identification.

Multibody dynamical modeling for spacecraft docking process with spring-damper buffering device: A new validation approach

NASA Astrophysics Data System (ADS)

Daneshjou, Kamran; Alibakhshi, Reza

2018-01-01

In the current manuscript, the process of spacecraft docking, as one of the main risky operations in an on-orbit servicing mission, is modeled based on unconstrained multibody dynamics. The spring-damper buffering device is utilized here in the docking probe-cone system for micro-satellites. Owing to the impact occurs inevitably during docking process and the motion characteristics of multibody systems are remarkably affected by this phenomenon, a continuous contact force model needs to be considered. Spring-damper buffering device, keeping the spacecraft stable in an orbit when impact occurs, connects a base (cylinder) inserted in the chaser satellite and the end of docking probe. Furthermore, by considering a revolute joint equipped with torsional shock absorber, between base and chaser satellite, the docking probe can experience both translational and rotational motions simultaneously. Although spacecraft docking process accompanied by the buffering mechanisms may be modeled by constrained multibody dynamics, this paper deals with a simple and efficient formulation to eliminate the surplus generalized coordinates and solve the impact docking problem based on unconstrained Lagrangian mechanics. By an example problem, first, model verification is accomplished by comparing the computed results with those recently reported in the literature. Second, according to a new alternative validation approach, which is based on constrained multibody problem, the accuracy of presented model can be also evaluated. This proposed verification approach can be applied to indirectly solve the constrained multibody problems by minimum required effort. The time history of impact force, the influence of system flexibility and physical interaction between shock absorber and penetration depth caused by impact are the issues followed in this paper. Third, the MATLAB/SIMULINK multibody dynamic analysis software will be applied to build impact docking model to validate computed results and

Detailed conformation dynamics and activation process of wild type c-Abl and T315I mutant

NASA Astrophysics Data System (ADS)

Yang, Li-Jun; Zhao, Wen-Hua; Liu, Qian

2014-10-01

Bcr-Abl is an important target for therapy against chronic myelogenous leukemia (CML) and acute lymphocytic leukemia (ALL). The synergistic effect between myristyl pocket and the ATP pocket has been found. But its detailed information based on molecular level still has not been achieved. In this study, conventional molecular dynamics (CMD) and target molecular dynamics (TMD) simulations were performed to explore the effect of T315I mutation on dynamics and activation process of Abl containing the N-terminal cap (Ncap). The CMD simulation results reveal the increasing flexibility of ATP pocket in kinase domain (KD) after T315I mutation which confirms the disability of ATP-pocket inhibitors to the Abl-T315I mutant. On the contrary, the T315I mutation decreased the flexibility of remote helix αI which suggests the synergistic effect between them. The mobility of farther regions containing Ncap, SH3, SH2 and SH2-KD linker were not affected by T315I mutation. The TMD simulation results show that the activation process of wild type Abl and Abl-T315I mutant experienced global conformation change. Their differences were elucidated by the activation motion of subsegments including A-loop, P-loop and Ncap. Besides, the T315I mutation caused decreasing energy barrier and increasing intermediate number in activation process, which results easier activation process. The TMD and CMD results indicate that a drug targeting only the ATP pocket is not enough to inhibit the Abl-T315I mutant. An effective way to inhibit the abnormal activity of Abl-T315I mutant is to combine the ATP-pocket inhibitors with inhibitors binding at non-ATP pockets mainly related to Ncap, SH2-KD linker and myristyl pocket.

Metaphors in Mathematics Classrooms: Analyzing the Dynamic Process of Teaching and Learning of Graph Functions

ERIC Educational Resources Information Center

Font, Vicenc; Bolite, Janete; Acevedo, Jorge

2010-01-01

This article presents an analysis of a phenomenon that was observed within the dynamic processes of teaching and learning to read and elaborate Cartesian graphs for functions at high-school level. Two questions were considered during this investigation: What types of metaphors does the teacher use to explain the graphic representation of functions…

On-line surveillance of a dynamic process by a moving system based on pulsed digital holographic interferometry.

PubMed

Pedrini, Giancarlo; Alexeenko, Igor; Osten, Wolfgang; Schnars, Ulf

2006-02-10

A method based on pulsed digital holographic interferometry for the measurement of dynamic deformations of a surface by using a moving system is presented. The measuring system may move with a speed of several meters per minute and can measure deformation of the surface with an accuracy of better than 50 nm. The deformation is obtained by comparison of the wavefronts recorded at different times with different laser pulses produced by a Nd:YAG laser. The effect due to the movement of the measuring system is compensated for by digital processing of the different holograms. The system is well suited for on-line surveillance of a dynamic process such as laser welding and friction stir welding. Experimental results are presented, and the advantages of the method are discussed.

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

Stochastic Evolution Dynamic of the Rock-Scissors-Paper Game Based on a Quasi Birth and Death Process

NASA Astrophysics Data System (ADS)

Yu, Qian; Fang, Debin; Zhang, Xiaoling; Jin, Chen; Ren, Qiyu

2016-06-01

Stochasticity plays an important role in the evolutionary dynamic of cyclic dominance within a finite population. To investigate the stochastic evolution process of the behaviour of bounded rational individuals, we model the Rock-Scissors-Paper (RSP) game as a finite, state dependent Quasi Birth and Death (QBD) process. We assume that bounded rational players can adjust their strategies by imitating the successful strategy according to the payoffs of the last round of the game, and then analyse the limiting distribution of the QBD process for the game stochastic evolutionary dynamic. The numerical experiments results are exhibited as pseudo colour ternary heat maps. Comparisons of these diagrams shows that the convergence property of long run equilibrium of the RSP game in populations depends on population size and the parameter of the payoff matrix and noise factor. The long run equilibrium is asymptotically stable, neutrally stable and unstable respectively according to the normalised parameters in the payoff matrix. Moreover, the results show that the distribution probability becomes more concentrated with a larger population size. This indicates that increasing the population size also increases the convergence speed of the stochastic evolution process while simultaneously reducing the influence of the noise factor.

Stochastic Evolution Dynamic of the Rock-Scissors-Paper Game Based on a Quasi Birth and Death Process.

PubMed

Yu, Qian; Fang, Debin; Zhang, Xiaoling; Jin, Chen; Ren, Qiyu

2016-06-27

Stochasticity plays an important role in the evolutionary dynamic of cyclic dominance within a finite population. To investigate the stochastic evolution process of the behaviour of bounded rational individuals, we model the Rock-Scissors-Paper (RSP) game as a finite, state dependent Quasi Birth and Death (QBD) process. We assume that bounded rational players can adjust their strategies by imitating the successful strategy according to the payoffs of the last round of the game, and then analyse the limiting distribution of the QBD process for the game stochastic evolutionary dynamic. The numerical experiments results are exhibited as pseudo colour ternary heat maps. Comparisons of these diagrams shows that the convergence property of long run equilibrium of the RSP game in populations depends on population size and the parameter of the payoff matrix and noise factor. The long run equilibrium is asymptotically stable, neutrally stable and unstable respectively according to the normalised parameters in the payoff matrix. Moreover, the results show that the distribution probability becomes more concentrated with a larger population size. This indicates that increasing the population size also increases the convergence speed of the stochastic evolution process while simultaneously reducing the influence of the noise factor.

Microbial dynamics in mixed culture biofilms of bacteria surviving sanitation of conveyor belts in salmon-processing plants.

PubMed

Langsrud, S; Moen, B; Møretrø, T; Løype, M; Heir, E

2016-02-01

The microbiota surviving sanitation of salmon-processing conveyor belts was identified and its growth dynamics further investigated in a model mimicking processing surfaces in such plants. A diverse microbiota dominated by Gram-negative bacteria was isolated after regular sanitation in three salmon processing plants. A cocktail of 14 bacterial isolates representing all genera isolated from conveyor belts (Listeria, Pseudomonas, Stenotrophomonas, Brochothrix, Serratia, Acinetobacter, Rhodococcus and Chryseobacterium) formed stable biofilms on steel coupons (12°C, salmon broth) of about 10(9) CFU cm(-2) after 2 days. High-throughput sequencing showed that Listeria monocytogenes represented 0·1-0·01% of the biofilm population and that Pseudomonas spp dominated. Interestingly, both Brochothrix sp. and a Pseudomonas sp. dominated in the surrounding suspension. The microbiota surviving sanitation is dominated by Pseudomonas spp. The background microbiota in biofilms inhibit, but do not eliminate L. monocytogenes. The results highlights that sanitation procedures have to been improved in the salmon-processing industry, as high numbers of a diverse microbiota survived practical sanitation. High-throughput sequencing enables strain level studies of population dynamics in biofilm. © 2015 The Society for Applied Microbiology.

Gaussian process inference for estimating pharmacokinetic parameters of dynamic contrast-enhanced MR images.

PubMed

Wang, Shijun; Liu, Peter; Turkbey, Baris; Choyke, Peter; Pinto, Peter; Summers, Ronald M

2012-01-01

In this paper, we propose a new pharmacokinetic model for parameter estimation of dynamic contrast-enhanced (DCE) MRI by using Gaussian process inference. Our model is based on the Tofts dual-compartment model for the description of tracer kinetics and the observed time series from DCE-MRI is treated as a Gaussian stochastic process. The parameter estimation is done through a maximum likelihood approach and we propose a variant of the coordinate descent method to solve this likelihood maximization problem. The new model was shown to outperform a baseline method on simulated data. Parametric maps generated on prostate DCE data with the new model also provided better enhancement of tumors, lower intensity on false positives, and better boundary delineation when compared with the baseline method. New statistical parameter maps from the process model were also found to be informative, particularly when paired with the PK parameter maps.

Molecular dynamic approach to the study of the intense heat and mass transfer processes on the vapor-liquid interface

NASA Astrophysics Data System (ADS)

Levashov, V. Yu; Kamenov, P. K.

2017-10-01

The paper is devoted to research of the heat and mass transfer processes on the vapor-liquid interface. These processes can be realized for example at metal tempering, accidents at nuclear power stations, followed by the release of the corium into the heat carrier, getting hot magma into the water during volcanic eruptions and other. In all these examples the vapor film can arise on the heated body surface. In this paper the vapor film formation process will be considered with help of molecular dynamics simulation methods. The main attention during this process modeling will be focused on the subject of the fluid and vapor interactions with the heater surface. Another direction of this work is to study of the processes inside the droplet that may take place as result of impact of the high-power laser radiation. Such impact can lead to intensive evaporation and explosive destruction of the droplet. At that the duration of heat and mass transfer processes in droplet substance is tens of femtoseconds. Thus, the methods of molecular dynamics simulation can give the possibilities describe the heat and mass transfer processes in the droplet and the vapor phase formation.

Discrete Dynamical Modeling.

ERIC Educational Resources Information Center

Sandefur, James T.

1991-01-01

Discussed is the process of translating situations involving changing quantities into mathematical relationships. This process, called dynamical modeling, allows students to learn new mathematics while sharpening their algebraic skills. A description of dynamical systems, problem-solving methods, a graphical analysis, and available classroom…

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.

Image processing pipeline for segmentation and material classification based on multispectral high dynamic range polarimetric images.

PubMed

Martínez-Domingo, Miguel Ángel; Valero, Eva M; Hernández-Andrés, Javier; Tominaga, Shoji; Horiuchi, Takahiko; Hirai, Keita

2017-11-27

We propose a method for the capture of high dynamic range (HDR), multispectral (MS), polarimetric (Pol) images of indoor scenes using a liquid crystal tunable filter (LCTF). We have included the adaptive exposure estimation (AEE) method to fully automatize the capturing process. We also propose a pre-processing method which can be applied for the registration of HDR images after they are already built as the result of combining different low dynamic range (LDR) images. This method is applied to ensure a correct alignment of the different polarization HDR images for each spectral band. We have focused our efforts in two main applications: object segmentation and classification into metal and dielectric classes. We have simplified the segmentation using mean shift combined with cluster averaging and region merging techniques. We compare the performance of our segmentation with that of Ncut and Watershed methods. For the classification task, we propose to use information not only in the highlight regions but also in their surrounding area, extracted from the degree of linear polarization (DoLP) maps. We present experimental results which proof that the proposed image processing pipeline outperforms previous techniques developed specifically for MSHDRPol image cubes.

Diagnosis of Processes Controlling Dissolved Organic Carbon (DOC) Export in a Subarctic Region by a Dynamic Ecosystem Model

NASA Astrophysics Data System (ADS)

Tang, J.

2015-12-01

Permafrost thawing in high latitudes allows more soil organic carbon (SOC) to become hydrologically accessible. This can increase dissolved organic carbon (DOC) exports and carbon release to the atmosphere as CO2 and CH4, with a positive feedback to regional and global climate warming. However, this portion of carbon loss through DOC export is often neglected in ecosystem models. In this paper, we incorporate a set of DOC-related processes (DOC production, mineralization, diffusion, sorption-desorption and leaching) into an Arctic-enabled version of the dynamic ecosystem model LPJ-GUESS (LPJ-GUESS WHyMe) to mechanistically model the DOC export, and to link this flux to other ecosystem processes. The extended LPJ-GUESS WHyMe with these DOC processes is applied to the Stordalen catchment in northern Sweden. The relative importance of different DOC-related processes for mineral and peatland soils for this region have been explored at both monthly and annual scales based on a detailed variance-based Sobol sensitivity analysis. For mineral soils, the annual DOC export is dominated by DOC fluxes in snowmelt seasons and the peak in spring is related to the runoff passing through top organic rich layers. Two processes, DOC sorption-desorption and production, are found to contribute most to the annual variance in DOC export. For peatland soils, the DOC export during snowmelt seasons is constrained by frozen soils and the processes of DOC production and mineralization, determining the magnitudes of DOC desorption in snowmelt seasons as well as DOC sorption in the rest of months, play the most important role in annual variances of DOC export. Generally, the seasonality of DOC fluxes is closely correlated with runoff seasonality in this region. The current implementation has demonstrated that DOC-related processes in the framework of LPJ-GUESS WHyMe are at an appropriate level of complexity to represent the main mechanism of DOC dynamics in soils. The quantified contributions

Boolean Modeling of Neural Systems with Point-Process Inputs and Outputs. Part I: Theory and Simulations

PubMed Central

Marmarelis, Vasilis Z.; Zanos, Theodoros P.; Berger, Theodore W.

2010-01-01

This paper presents a new modeling approach for neural systems with point-process (spike) inputs and outputs that utilizes Boolean operators (i.e. modulo 2 multiplication and addition that correspond to the logical AND and OR operations respectively, as well as the AND_NOT logical operation representing inhibitory effects). The form of the employed mathematical models is akin to a “Boolean-Volterra” model that contains the product terms of all relevant input lags in a hierarchical order, where terms of order higher than first represent nonlinear interactions among the various lagged values of each input point-process or among lagged values of various inputs (if multiple inputs exist) as they reflect on the output. The coefficients of this Boolean-Volterra model are also binary variables that indicate the presence or absence of the respective term in each specific model/system. Simulations are used to explore the properties of such models and the feasibility of their accurate estimation from short data-records in the presence of noise (i.e. spurious spikes). The results demonstrate the feasibility of obtaining reliable estimates of such models, with excitatory and inhibitory terms, in the presence of considerable noise (spurious spikes) in the outputs and/or the inputs in a computationally efficient manner. A pilot application of this approach to an actual neural system is presented in the companion paper (Part II). PMID:19517238

Supporting Teachers' Understanding of Nature of Science and Inquiry Through Personal Experience and Perception of Inquiry as a Dynamic Process

NASA Astrophysics Data System (ADS)

Zion, Michal; Schwartz, Renee S.; Rimerman-Shmueli, Esther; Adler, Idit

2018-05-01

One of today's challenges in science education involves the development of appropriate conceptions of inquiry teaching and realizing how these experiences can support students' understanding of the nature of science and inquiry (NOS and NOSI). To meet this challenge, we developed a course for in-service science teachers, in which explicit-reflective instruction of NOS was coupled with an open inquiry process. This process included documentation tools adjusted to emphasize the dynamic, logical, and reflective aspects of scientific inquiry. Teachers' documentations, reflections, and questionnaires were examined for indications of perceptual connection between comprehending the essence of dynamic open inquiry and understanding certain NOS tenets. The results indicated that the in-service teachers experienced all criteria of dynamic open inquiry, however not to the same extent. By focusing on four teachers who clearly addressed changes in their perspective of NOS and NOSI, we were able to examine the nature of those changes, and relate them to the teachers' personal experiences and perceptions of the characteristics of dynamic open inquiry. Our results suggest that the participants' personal experiences and perceptions of the dynamic characteristics of open inquiry play a crucial role in shaping their understanding of NOS and NOSI. The findings of this research underscore the importance of enhancing teachers' personal experiences and perceptions of the dynamic characteristics of open inquiry, as a vehicle to improve their understanding of NOS and NOSI.

Greenhouse gas emission and microbial community dynamics during simultaneous nitrification and denitrification process.

PubMed

Kong, Qiang; Wang, Zhi-Bin; Niu, Peng-Fei; Miao, Ming-Sheng

2016-06-01

This study evaluates greenhouse gas emission and the microbial community dynamics during simultaneous nitrification and denitrification (SND) process. Based on CO2 equivalents, the SND reactor released 4.28g of greenhouse gases each cycle. 2.91% of the incoming nitrogen load was emitted as N2O. The CO2 and N2O emissions mainly occurred in the aerobic stage and CH4 emissions were consistently near zero. Extracellular polymeric substance (EPS) contents in activated sludge increased during start-up the SND process. High-throughput sequencing showed increases in bacterial species richness, leading to changes in EPS content and composition observed using 3D-EEM fluorescence spectra. For denitrifying bacteria, the relative abundance of Pseudomonas significantly increased during the SND process, while Paracoccus decreased significantly. For phosphorus-accumulating bacteria, the relative abundance of Rhodocyclaceae also significantly increased. The relative abundance of other functional microbes, such as Nitrosomonadaceae (ammonia oxidizer), Nitrospirales (nitrite oxidizer) and Planctomyces (anammox) decreased significantly during the SND process. Copyright © 2016 Elsevier Ltd. All rights reserved.

A system dynamic model to estimate hydrological processes and water use in a eucalypt plantation

Treesearch

Ying Ouyang; Daping Xu; Ted Leininger; Ningnan Zhang

2016-01-01

Eucalypts have been identified as one of the best feedstocks for bioenergy production due to theirfast-growth rate and coppicing ability. However, their water use efficiency along with the adverse envi-ronmental impacts is still a controversial issue. In this study, a system dynamic model was developed toestimate the hydrological processes and water use in a eucalyptus...

Efficacy of identifying neural components in the face and emotion processing system in schizophrenia using a dynamic functional localizer.

PubMed

Arnold, Aiden E G F; Iaria, Giuseppe; Goghari, Vina M

2016-02-28

Schizophrenia is associated with deficits in face perception and emotion recognition. Despite consistent behavioural results, the neural mechanisms underlying these cognitive abilities have been difficult to isolate, in part due to differences in neuroimaging methods used between studies for identifying regions in the face processing system. Given this problem, we aimed to validate a recently developed fMRI-based dynamic functional localizer task for use in studies of psychiatric populations and specifically schizophrenia. Previously, this functional localizer successfully identified each of the core face processing regions (i.e. fusiform face area, occipital face area, superior temporal sulcus), and regions within an extended system (e.g. amygdala) in healthy individuals. In this study, we tested the functional localizer success rate in 27 schizophrenia patients and in 24 community controls. Overall, the core face processing regions were localized equally between both the schizophrenia and control group. Additionally, the amygdala, a candidate brain region from the extended system, was identified in nearly half the participants from both groups. These results indicate the effectiveness of a dynamic functional localizer at identifying regions of interest associated with face perception and emotion recognition in schizophrenia. The use of dynamic functional localizers may help standardize the investigation of the facial and emotion processing system in this and other clinical populations. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Connection stiffness and dynamical docking process of flux pinned spacecraft modules

NASA Astrophysics Data System (ADS)

Lu, Yong; Zhang, Mingliang; Gao, Dong

2014-02-01

This paper describes a novel kind of potential flux pinned docking system that consists of guidance navigation and control system, the traditional extrusion type propulsion system, and a flux pinned docking interface. Because of characteristics of passive stability of flux pinning, the docking control strategy of flux pinned docking system only needs a series of sequential control rather than necessary active feedback control, as well as avoidance of hazardous collision accident. The flux pinned force between YBaCuO (YBCO) high temperature superconductor bulk and permanent magnet is able to be given vent based on the identical current loop model and improved image dipole model, which can be validated experimentally. Thus, the connection stiffness between two flux pinned spacecraft modules can be calculated based on Hooke's law. This connection stiffness matrix at the equilibrium position has the positive definite performance, which can validate the passively stable connection of two flux pinned spacecraft modules theoretically. Furthermore, the relative orbital dynamical equation of two flux pinned spacecraft modules can be established based on Clohessy-Wiltshire's equations and improved image dipole model. The dynamical docking process between two flux pinned spacecraft modules can be obtained by way of numerical simulation, which suggests the feasibility of flux pinned docking system.

Connection stiffness and dynamical docking process of flux pinned spacecraft modules

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

Lu, Yong; Zhang, Mingliang, E-mail: niudun12@126.com; Gao, Dong

2014-02-14

This paper describes a novel kind of potential flux pinned docking system that consists of guidance navigation and control system, the traditional extrusion type propulsion system, and a flux pinned docking interface. Because of characteristics of passive stability of flux pinning, the docking control strategy of flux pinned docking system only needs a series of sequential control rather than necessary active feedback control, as well as avoidance of hazardous collision accident. The flux pinned force between YBaCuO (YBCO) high temperature superconductor bulk and permanent magnet is able to be given vent based on the identical current loop model and improvedmore » image dipole model, which can be validated experimentally. Thus, the connection stiffness between two flux pinned spacecraft modules can be calculated based on Hooke's law. This connection stiffness matrix at the equilibrium position has the positive definite performance, which can validate the passively stable connection of two flux pinned spacecraft modules theoretically. Furthermore, the relative orbital dynamical equation of two flux pinned spacecraft modules can be established based on Clohessy-Wiltshire's equations and improved image dipole model. The dynamical docking process between two flux pinned spacecraft modules can be obtained by way of numerical simulation, which suggests the feasibility of flux pinned docking system.« less

Imaging dynamic redox processes with genetically encoded probes.

PubMed

Ezeriņa, Daria; Morgan, Bruce; Dick, Tobias P

2014-08-01

Redox signalling plays an important role in many aspects of physiology, including that of the cardiovascular system. Perturbed redox regulation has been associated with numerous pathological conditions; nevertheless, the causal relationships between redox changes and pathology often remain unclear. Redox signalling involves the production of specific redox species at specific times in specific locations. However, until recently, the study of these processes has been impeded by a lack of appropriate tools and methodologies that afford the necessary redox species specificity and spatiotemporal resolution. Recently developed genetically encoded fluorescent redox probes now allow dynamic real-time measurements, of defined redox species, with subcellular compartment resolution, in intact living cells. Here we discuss the available genetically encoded redox probes in terms of their sensitivity and specificity and highlight where uncertainties or controversies currently exist. Furthermore, we outline major goals for future probe development and describe how progress in imaging methodologies will improve our ability to employ genetically encoded redox probes in a wide range of situations. This article is part of a special issue entitled "Redox Signalling in the Cardiovascular System." Copyright © 2014 Elsevier Ltd. All rights reserved.

Dynamic simulation solves process control problem in Oman

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

NONE

1998-11-16

A dynamic simulation study solved the process control problems for a Saih Rawl, Oman, gas compressor station operated by Petroleum Development of Oman (PDO). PDO encountered persistent compressor failure that caused frequent facility shutdowns, oil production deferment, and gas flaring. It commissioned MSE (Consultants) Ltd., U.K., to find a solution for the problem. Saih Rawl, about 40 km from Qarn Alam, produces oil and associated gas from a large number of low and high-pressure wells. Oil and gas are separated in three separators. The oil is pumped to Qarn Alam for treatment and export. Associated gas is compressed in twomore » parallel trains. Train K-1115 is a 350,000 standard cu m/day, four-stage reciprocating compressor driven by a fixed-speed electric motor. Train K-1120 is a 1 million standard cu m/day, four-stage reciprocating compressor driven by a fixed-speed electric motor. Train K-1120 is a 1 million standard cu m/day, four-stage centrifugal compressor driven by a variable-speed motor. The paper describes tripping and surging problems with the gas compressor and the control simplifications that solved the problem.« less

Carbon-Flow-Based Modeling of Ecophysiological Processes and Biomass Dynamics of Submersed Aquatic Plants

DTIC Science & Technology

2007-09-01

simulation modeling approach to describing carbon- flow-based, ecophysiological processes and biomass dynamics of fresh- water submersed aquatic plant...the distribution and abundance of SAV. In aquatic systems a small part of the irradiance can be reflected by the water surface, and further...to the fact that water temperatures in the lake were relatively low compared to air tem- peratures because of the large inflow of groundwater (Titus

A large-scale circuit mechanism for hierarchical dynamical processing in the primate cortex

PubMed Central

Chaudhuri, Rishidev; Knoblauch, Kenneth; Gariel, Marie-Alice; Kennedy, Henry; Wang, Xiao-Jing

2015-01-01

We developed a large-scale dynamical model of the macaque neocortex, which is based on recently acquired directed- and weighted-connectivity data from tract-tracing experiments, and which incorporates heterogeneity across areas. A hierarchy of timescales naturally emerges from this system: sensory areas show brief, transient responses to input (appropriate for sensory processing), whereas association areas integrate inputs over time and exhibit persistent activity (suitable for decision-making and working memory). The model displays multiple temporal hierarchies, as evidenced by contrasting responses to visual versus somatosensory stimulation. Moreover, slower prefrontal and temporal areas have a disproportionate impact on global brain dynamics. These findings establish a circuit mechanism for “temporal receptive windows” that are progressively enlarged along the cortical hierarchy, suggest an extension of time integration in decision-making from local to large circuits, and should prompt a re-evaluation of the analysis of functional connectivity (measured by fMRI or EEG/MEG) by taking into account inter-areal heterogeneity. PMID:26439530

Dynamical synapses enhance neural information processing: gracefulness, accuracy, and mobility.

PubMed

Fung, C C Alan; Wong, K Y Michael; Wang, He; Wu, Si

2012-05-01

Experimental data have revealed that neuronal connection efficacy exhibits two forms of short-term plasticity: short-term depression (STD) and short-term facilitation (STF). They have time constants residing between fast neural signaling and rapid learning and may serve as substrates for neural systems manipulating temporal information on relevant timescales. This study investigates the impact of STD and STF on the dynamics of continuous attractor neural networks and their potential roles in neural information processing. We find that STD endows the network with slow-decaying plateau behaviors: the network that is initially being stimulated to an active state decays to a silent state very slowly on the timescale of STD rather than on that of neuralsignaling. This provides a mechanism for neural systems to hold sensory memory easily and shut off persistent activities gracefully. With STF, we find that the network can hold a memory trace of external inputs in the facilitated neuronal interactions, which provides a way to stabilize the network response to noisy inputs, leading to improved accuracy in population decoding. Furthermore, we find that STD increases the mobility of the network states. The increased mobility enhances the tracking performance of the network in response to time-varying stimuli, leading to anticipative neural responses. In general, we find that STD and STP tend to have opposite effects on network dynamics and complementary computational advantages, suggesting that the brain may employ a strategy of weighting them differentially depending on the computational purpose.

The Temporal and Dynamic Nature of Self-Regulatory Processes during Independent and Externally Assisted Hypermedia Learning

ERIC Educational Resources Information Center

Johnson, Amy M.; Azevedo, Roger; D'Mello, Sidney K.

2011-01-01

This study examined the temporal and dynamic nature of students' self-regulatory processes while learning about the circulatory system with hypermedia. A total of 74 undergraduate students were randomly assigned to 1 of 2 conditions: independent learning or externally assisted learning. Participants in the independent learning condition used a…

Dynamic Processes of Speech Development by Seven Adult Learners of Japanese in a Domestic Immersion Context

ERIC Educational Resources Information Center

Fukuda, Makiko

2014-01-01

The present study revealed the dynamic process of speech development in a domestic immersion program by seven adult beginning learners of Japanese. The speech data were analyzed with fluency, accuracy, and complexity measurements at group, interindividual, and intraindividual levels. The results revealed the complex nature of language development…

A dynamic process of health risk assessment for business continuity management during the World Exposition Shanghai, China, 2010.

PubMed

Sun, Xiaodong; Keim, Mark; Dong, Chen; Mahany, Mollie; Guo, Xiang

2014-01-01

Reports of health issues related to mass gatherings around the world have indicated a potential for public health and medical emergencies to occur on a scale that could place a significant impact on business continuity for national and international organisations. This paper describes a risk assessment process for business continuity management that was performed as part of the planning efforts related to the World Expo 2010 Shanghai China (Expo), the world's largest mass gathering to date. Altogether, 73 million visitors attended the Expo, generating over US$2bn of revenue. During 2008 to 2010, the Shanghai Municipal Center for Disease Control and Prevention performed a dynamic series of four disaster risk assessments before and during the Expo. The purpose of this assessment process was to identify, analyse and evaluate risks for public health security during different stages of the Expo. This paper describes an overview of the novel approach for this multiple and dynamic process of assessment of health security risk for ensuring business continuity.

Computational fluid dynamics modeling of bun baking process under different oven load conditions.

PubMed

Tank, A; Chhanwal, N; Indrani, D; Anandharamakrishnan, C

2014-09-01

A computational fluid dynamics (CFD) model was developed to study the temperature profile of the bun during baking process. Evaporation-condensation mechanism and effect of the latent heat during phase change of water was incorporated in this model to represent actual bun baking process. Simulation results were validated with experimental measurements of bun temperature at two different positions. Baking process is completed within 20 min, after the temperature of crumb become stable at 98 °C. Further, this study was extended to investigate the effect of partially (two baking trays) loaded and fully loaded (eight baking trays) oven on temperature profile of bun. Velocity and temperature profile differs in partially loaded and fully loaded oven. Bun placed in top rack showed rapid baking while bun placed in bottom rack showed slower baking due to uneven temperature distribution in the oven. Hence, placement of bun inside the oven affects temperature of bun and consequently, the quality of the product.

Topics in geophysical fluid dynamics: Atmospheric dynamics, dynamo theory, and climate dynamics

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

Ghil, M.; Childress, S.

1987-01-01

This text is the first study to apply systematically the successive bifurcations approach to complex time-dependent processes in large scale atmospheric dynamics, geomagnetism, and theoretical climate dynamics. The presentation of recent results on planetary-scale phenomena in the earth's atmosphere, ocean, cryosphere, mantle and core provides an integral account of mathematical theory and methods together with physical phenomena and processes. The authors address a number of problems in rapidly developing areas of geophysics, bringing into closer contact the modern tools of nonlinear mathematics and the novel problems of global change in the environment.

A dynamic intron retention program enriched in RNA processing genes regulates gene expression during terminal erythropoiesis

DOE PAGES

Pimentel, Harold; Parra, Marilyn; Gee, Sherry L.; ...

2015-11-03

Differentiating erythroblasts execute a dynamic alternative splicing program shown here to include extensive and diverse intron retention (IR) events. Cluster analysis revealed hundreds of developmentallydynamic introns that exhibit increased IR in mature erythroblasts, and are enriched in functions related to RNA processing such as SF3B1 spliceosomal factor. Distinct, developmentally-stable IR clusters are enriched in metal-ion binding functions and include mitoferrin genes SLC25A37 and SLC25A28 that are critical for iron homeostasis. Some IR transcripts are abundant, e.g. comprising ~50% of highly-expressed SLC25A37 and SF3B1 transcripts in late erythroblasts, and thereby limiting functional mRNA levels. IR transcripts tested were predominantly nuclearlocalized. Splicemore » site strength correlated with IR among stable but not dynamic intron clusters, indicating distinct regulation of dynamically-increased IR in late erythroblasts. Retained introns were preferentially associated with alternative exons with premature termination codons (PTCs). High IR was observed in disease-causing genes including SF3B1 and the RNA binding protein FUS. Comparative studies demonstrated that the intron retention program in erythroblasts shares features with other tissues but ultimately is unique to erythropoiesis. Finally, we conclude that IR is a multi-dimensional set of processes that post-transcriptionally regulate diverse gene groups during normal erythropoiesis, misregulation of which could be responsible for human disease.« less

Application of Non-Kolmogorovian Probability and Quantum Adaptive Dynamics to Unconscious Inference in Visual Perception Process

NASA Astrophysics Data System (ADS)

Accardi, Luigi; Khrennikov, Andrei; Ohya, Masanori; Tanaka, Yoshiharu; Yamato, Ichiro

2016-07-01

Recently a novel quantum information formalism — quantum adaptive dynamics — was developed and applied to modelling of information processing by bio-systems including cognitive phenomena: from molecular biology (glucose-lactose metabolism for E.coli bacteria, epigenetic evolution) to cognition, psychology. From the foundational point of view quantum adaptive dynamics describes mutual adapting of the information states of two interacting systems (physical or biological) as well as adapting of co-observations performed by the systems. In this paper we apply this formalism to model unconscious inference: the process of transition from sensation to perception. The paper combines theory and experiment. Statistical data collected in an experimental study on recognition of a particular ambiguous figure, the Schröder stairs, support the viability of the quantum(-like) model of unconscious inference including modelling of biases generated by rotation-contexts. From the probabilistic point of view, we study (for concrete experimental data) the problem of contextuality of probability, its dependence on experimental contexts. Mathematically contextuality leads to non-Komogorovness: probability distributions generated by various rotation contexts cannot be treated in the Kolmogorovian framework. At the same time they can be embedded in a “big Kolmogorov space” as conditional probabilities. However, such a Kolmogorov space has too complex structure and the operational quantum formalism in the form of quantum adaptive dynamics simplifies the modelling essentially.

A dynamic intron retention program enriched in RNA processing genes regulates gene expression during terminal erythropoiesis

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

Pimentel, Harold; Parra, Marilyn; Gee, Sherry L.

Differentiating erythroblasts execute a dynamic alternative splicing program shown here to include extensive and diverse intron retention (IR) events. Cluster analysis revealed hundreds of developmentallydynamic introns that exhibit increased IR in mature erythroblasts, and are enriched in functions related to RNA processing such as SF3B1 spliceosomal factor. Distinct, developmentally-stable IR clusters are enriched in metal-ion binding functions and include mitoferrin genes SLC25A37 and SLC25A28 that are critical for iron homeostasis. Some IR transcripts are abundant, e.g. comprising ~50% of highly-expressed SLC25A37 and SF3B1 transcripts in late erythroblasts, and thereby limiting functional mRNA levels. IR transcripts tested were predominantly nuclearlocalized. Splicemore » site strength correlated with IR among stable but not dynamic intron clusters, indicating distinct regulation of dynamically-increased IR in late erythroblasts. Retained introns were preferentially associated with alternative exons with premature termination codons (PTCs). High IR was observed in disease-causing genes including SF3B1 and the RNA binding protein FUS. Comparative studies demonstrated that the intron retention program in erythroblasts shares features with other tissues but ultimately is unique to erythropoiesis. Finally, we conclude that IR is a multi-dimensional set of processes that post-transcriptionally regulate diverse gene groups during normal erythropoiesis, misregulation of which could be responsible for human disease.« less

Dynamic variation of bioactive compounds and aflatoxins in contaminated Radix Astragali during extraction process.

PubMed

Hu, Yichen; Kong, Weijun; Luo, Hongli; Zhao, Lianhua; Yang, Meihua

2016-03-30

Although increasing attention has been paid to the health threat caused by mycotoxins in commodities such as food or medicines, mycotoxin transfer processes from crude material to products have raised little concern so far. Radix Astragali is a commonly used edible and medicinal herbal plant that is susceptible to contamination with aflatoxins from Aspergillus flavus. There have been no studies on mycotoxin transfer into pharmaceutical preparations or derivative products. To facilitate the aflatoxin reduction and bioactivity retention, the dynamic variations of aflatoxins as well as herbal compounds, namely calycosin-7-glucoside, astragaloside and formononetin, in Radix Astragali contaminated by A. flavus during water decoction and ethanol refluxing treatments were evaluated simultaneously by an ultra-fast liquid chromatography-triple quadrupole linear ion trap mass spectrometry method. After the extraction processes, although the amount of alfatoxins was reduced remarkably, aflatoxin residuals in preparation still exceed recommended limits, manifesting the great need to establish a limit for aflatoxins in herbal extractions or derivative products. Meanwhile, due to the hydrolysis of glucoside, water decoction period should be no longer than 4 h. This investigation would benefit from the determination of the dynamic variation of aflatoxins in infected herbs in preparation treatments, in order to further develop aflatoxin limits in herbal preparations. © 2015 Society of Chemical Industry.

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

PubMed Central

Chen, Zhe; Purdon, Patrick L.; Brown, Emery N.; Barbieri, Riccardo

2012-01-01

In recent years, time-varying inhomogeneous point process models have been introduced for assessment of instantaneous heartbeat dynamics as well as specific cardiovascular control mechanisms and hemodynamics. Assessment of the model’s statistics is established through the Wiener-Volterra theory and a multivariate autoregressive (AR) structure. A variety of instantaneous cardiovascular metrics, such as heart rate (HR), heart rate variability (HRV), respiratory sinus arrhythmia (RSA), and baroreceptor-cardiac reflex (baroreflex) sensitivity (BRS), are derived within a parametric framework and instantaneously updated with adaptive and local maximum likelihood estimation algorithms. Inclusion of second-order non-linearities, with subsequent bispectral quantification in the frequency domain, further allows for definition of instantaneous metrics of non-linearity. We here present a comprehensive review of the devised methods as applied to experimental recordings from healthy subjects during propofol anesthesia. Collective results reveal interesting dynamic trends across the different pharmacological interventions operated within each anesthesia session, confirming the ability of the algorithm to track important changes in cardiorespiratory elicited interactions, and pointing at our mathematical approach as a promising monitoring tool for an accurate, non-invasive assessment in clinical practice. We also discuss the limitations and other alternative modeling strategies of our point process approach. PMID:22375120

Study of Effect of Impacting Direction on Abrasive Nanometric Cutting Process with Molecular Dynamics

NASA Astrophysics Data System (ADS)

Li, Junye; Meng, Wenqing; Dong, Kun; Zhang, Xinming; Zhao, Weihong

2018-01-01

Abrasive flow polishing plays an important part in modern ultra-precision machining. Ultrafine particles suspended in the medium of abrasive flow removes the material in nanoscale. In this paper, three-dimensional molecular dynamics (MD) simulations are performed to investigate the effect of impacting direction on abrasive cutting process during abrasive flow polishing. The molecular dynamics simulation software Lammps was used to simulate the cutting of single crystal copper with SiC abrasive grains at different cutting angles (0o-45o). At a constant friction coefficient, we found a direct relation between cutting angle and cutting force, which ultimately increases the number of dislocation during abrasive flow machining. Our theoretical study reveal that a small cutting angle is beneficial for improving surface quality and reducing internal defects in the workpiece. However, there is no obvious relationship between cutting angle and friction coefficient.

Study of Effect of Impacting Direction on Abrasive Nanometric Cutting Process with Molecular Dynamics.

PubMed

Li, Junye; Meng, Wenqing; Dong, Kun; Zhang, Xinming; Zhao, Weihong

2018-01-11

Abrasive flow polishing plays an important part in modern ultra-precision machining. Ultrafine particles suspended in the medium of abrasive flow removes the material in nanoscale. In this paper, three-dimensional molecular dynamics (MD) simulations are performed to investigate the effect of impacting direction on abrasive cutting process during abrasive flow polishing. The molecular dynamics simulation software Lammps was used to simulate the cutting of single crystal copper with SiC abrasive grains at different cutting angles (0 o -45 o ). At a constant friction coefficient, we found a direct relation between cutting angle and cutting force, which ultimately increases the number of dislocation during abrasive flow machining. Our theoretical study reveal that a small cutting angle is beneficial for improving surface quality and reducing internal defects in the workpiece. However, there is no obvious relationship between cutting angle and friction coefficient.

Standard random number generation for MBASIC

NASA Technical Reports Server (NTRS)

Tausworthe, R. C.

1976-01-01

A machine-independent algorithm is presented and analyzed for generating pseudorandom numbers suitable for the standard MBASIC system. The algorithm used is the polynomial congruential or linear recurrence modulo 2 method. Numbers, formed as nonoverlapping adjacent 28-bit words taken from the bit stream produced by the formula a sub m + 532 = a sub m + 37 + a sub m (modulo 2), do not repeat within the projected age of the solar system, show no ensemble correlation, exhibit uniform distribution of adjacent numbers up to 19 dimensions, and do not deviate from random runs-up and runs-down behavior.

Dynamic modeling and validation of a lignocellulosic enzymatic hydrolysis process--a demonstration scale study.

PubMed

Prunescu, Remus Mihail; Sin, Gürkan

2013-12-01

The enzymatic hydrolysis process is one of the key steps in second generation biofuel production. After being thermally pretreated, the lignocellulosic material is liquefied by enzymes prior to fermentation. The scope of this paper is to evaluate a dynamic model of the hydrolysis process on a demonstration scale reactor. The following novel features are included: the application of the Convection-Diffusion-Reaction equation to a hydrolysis reactor to assess transport and mixing effects; the extension of a competitive kinetic model with enzymatic pH dependency and hemicellulose hydrolysis; a comprehensive pH model; and viscosity estimations during the course of reaction. The model is evaluated against real data extracted from a demonstration scale biorefinery throughout several days of operation. All measurements are within predictions uncertainty and, therefore, the model constitutes a valuable tool to support process optimization, performance monitoring, diagnosis and process control at full-scale studies. Copyright © 2013 Elsevier Ltd. All rights reserved.

On the equivalence among stress tensors in a gauge-fluid system

NASA Astrophysics Data System (ADS)

Mitra, Arpan Krishna; Banerjee, Rabin; Ghosh, Subir

2017-12-01

In this paper, we bring out the subtleties involved in the study of a first-order relativistic field theory with auxiliary field variables playing an essential role. In particular, we discuss the nonisentropic Eulerian (or Hamiltonian) fluid model. Interactions are introduced by coupling the fluid to a dynamical Maxwell (U(1)) gauge field. This dynamical nature of the gauge field is crucial in showing the equivalence, on the physical subspace, of the stress tensor derived from two definitions, i.e. the canonical (Noether) one and the symmetric one. In the conventional equal-time formalism, we have shown that the generators of the space-time transformations obtained from these two definitions agree modulo the Gauss constraint. This equivalence in the physical sector has been achieved only because of the dynamical nature of the gauge fields. Subsequently, we have explicitly demonstrated the validity of the Schwinger condition. A detailed analysis of the model in lightcone formalism has also been done where several interesting features are revealed.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Supramolecular assembly/reassembly processes: molecular motors and dynamers operating at surfaces.

PubMed

Ciesielski, Artur; Samorì, Paolo

2011-04-01

Among the many significant advances within the field of supramolecular chemistry over the past decades, the development of the so-called "dynamers" features a direct relevance to materials science. Defined as "combinatorial dynamic polymers", dynamers are constitutional dynamic systems and materials resulting from the application of the principles of supramolecular chemistry to polymer science. Like supramolecular materials in general, dynamers are reversible dynamic multifunctional architectures, capable of modifying their constitution by exchanging, recombining, incorporating components. They may exhibit a variety of novel properties and behave as adaptive materials. In this review we focus on the design of responsive switchable monolayers, i.e. monolayers capable to undergo significant changes in their physical or chemical properties as a result of external stimuli. Scanning tunneling microscopy studies provide direct evidence with a sub-nanometre resolution, on the formation and dynamic response of these self-assembled systems featuring controlled geometries and properties.

Comparing the temporal dynamics of thematic and taxonomic processing using event-related potentials.

PubMed

Savic, Olivera; Savic, Andrej M; Kovic, Vanja

2017-01-01

We report the results of a study comparing the temporal dynamics of thematic and taxonomic knowledge activation in a picture-word priming paradigm using event-related potentials. Although we found no behavioral differences between thematic and taxonomic processing, ERP data revealed distinct patterns of N400 and P600 amplitude modulation for thematic and taxonomic priming. Thematically related target stimuli elicited less negativity than taxonomic targets between 280-460 ms after stimulus onset, suggesting easier semantic processing of thematic than taxonomic relationships. Moreover, P600 mean amplitude was significantly increased for taxonomic targets between 520-600 ms, consistent with a greater need for stimulus reevaluation in that condition. These results offer novel evidence in favor of a dissociation between thematic and taxonomic thinking in the early phases of conceptual evaluation.

Comparing the temporal dynamics of thematic and taxonomic processing using event-related potentials

PubMed Central

Savic, Olivera; Savic, Andrej M.; Kovic, Vanja

2017-01-01

We report the results of a study comparing the temporal dynamics of thematic and taxonomic knowledge activation in a picture-word priming paradigm using event-related potentials. Although we found no behavioral differences between thematic and taxonomic processing, ERP data revealed distinct patterns of N400 and P600 amplitude modulation for thematic and taxonomic priming. Thematically related target stimuli elicited less negativity than taxonomic targets between 280–460 ms after stimulus onset, suggesting easier semantic processing of thematic than taxonomic relationships. Moreover, P600 mean amplitude was significantly increased for taxonomic targets between 520–600 ms, consistent with a greater need for stimulus reevaluation in that condition. These results offer novel evidence in favor of a dissociation between thematic and taxonomic thinking in the early phases of conceptual evaluation. PMID:29236767

Passive demodulation of miniature fiber-optic-based interferometric sensors using a time-multiplexing technique.

PubMed

Santos, J L; Jackson, D A

1991-08-01

A passive demodulation technique suitable for interferometric interrogation of short optical cavities is described. It is based on time multiplexing of two low-finesse Fabry-Perot interferometers subject to the same measurand and with a differential optical phase of pi/2 (modulo 2pi). Independently of the cavity length, two optical outputs in quadrature are generated, which permits signal reading free of fading. The concept is demonstrated for the measurement of vibration using a simple processing scheme.

Nonlinear digital signal processing in mental health: characterization of major depression using instantaneous entropy measures of heartbeat dynamics.

PubMed

Valenza, Gaetano; Garcia, Ronald G; Citi, Luca; Scilingo, Enzo P; Tomaz, Carlos A; Barbieri, Riccardo

2015-01-01

Nonlinear digital signal processing methods that address system complexity have provided useful computational tools for helping in the diagnosis and treatment of a wide range of pathologies. More specifically, nonlinear measures have been successful in characterizing patients with mental disorders such as Major Depression (MD). In this study, we propose the use of instantaneous measures of entropy, namely the inhomogeneous point-process approximate entropy (ipApEn) and the inhomogeneous point-process sample entropy (ipSampEn), to describe a novel characterization of MD patients undergoing affective elicitation. Because these measures are built within a nonlinear point-process model, they allow for the assessment of complexity in cardiovascular dynamics at each moment in time. Heartbeat dynamics were characterized from 48 healthy controls and 48 patients with MD while emotionally elicited through either neutral or arousing audiovisual stimuli. Experimental results coming from the arousing tasks show that ipApEn measures are able to instantaneously track heartbeat complexity as well as discern between healthy subjects and MD patients. Conversely, standard heart rate variability (HRV) analysis performed in both time and frequency domains did not show any statistical significance. We conclude that measures of entropy based on nonlinear point-process models might contribute to devising useful computational tools for care in mental health.

[Dynamic Wavelength Characteristics of Semiconductor Laser in Electric Current Tuning Process].

PubMed

Liu, Jing-wang; Li, Zhong-yang; Zhang, Wei-zhong; Wang, Qing-chuan; An, Ying; Li, Yong-hui

2015-11-01

In order to measure the dynamic wavelength of semiconductor lasers under current tuning, an improved method of fi- ber delay self-heterodyne interferometer was proposed. The measurement principle, as well the beat frequency and dynamic wavelength of recursive relations are theoretically analyzed. The application of the experimental system measured the dynamic wavelength characteristics of distributed feedback semiconductor laser and the static wavelength characteristics measurement by the spectrometer. The comparison between the two values indicates that both dynamic and static wavelength characteristic with the current tuning are the similar non-linear curve. In 20-100 mA current tuning range, the difference of them is less than 0.002 nm. At the same time, according to the absorption lines of CO2 gas, and HITRAN spectrum library, we can identify the dynamic wavelength of the laser. Comparing it with dynamic wavelength calculated by the beat signal, the difference is only 0.001 nm, which verifies the reliability of the experimental system to measure the dynamic wavelength.

The effect of cross-linking on the molecular dynamics of the segmental and β Johari-Goldstein processes in polyvinylpyrrolidone-based copolymers.

PubMed

Redondo-Foj, Belén; Sanchis, María Jesús; Ortiz-Serna, Pilar; Carsí, Marta; García, José Miguel; García, Félix Clemente

2015-09-28

The effect of the cross-link density on the molecular dynamics of copolymers composed of vinylpyrrolidone (VP) and butyl acrylate (BA) was studied using differential scanning calorimetry (DSC) and dielectric relaxation spectroscopy (DRS). A single glass transition was detected by DSC measurements. The dielectric spectra exhibit conductive processes and three dipolar relaxations labeled as α, β and γ in the decreasing order of temperatures. The cross-linker content affects both α and β processes, but the fastest γ process is relatively unaffected. An increase of cross-linking produces a typical effect on the α process dynamics: (i) the glass transition temperature is increased, (ii) the dispersion is broadened, (iii) its strength is decreased and (iv) the relaxation times are increased. However, the β process, which possesses typical features of a pure Johari-Goldstein relaxation, unexpectedly loses the intermolecular character for the highest cross-linker content.

Nonlinear dynamic processes in modified ionospheric plasma

NASA Astrophysics Data System (ADS)

Kochetov, A.; Terina, G.

Presented work is a contribution to the experimental and theoretical study of nonlinear effects arising on ionospheric plasma under the action of powerful radio emission (G.I. Terina, J. Atm. Terr. Phys., 1995, v.57, p.273; A.V. Kochetov et. al., Advances in Space Research, 2002, in press). The experimental results were obtained by the method of sounding of artificially disturbed ionosphere by short radio pulses. The amplitude and phase characteristics of scattered signal as of "caviton" type (CS) (analogy of narrow-band component of stimulation electromagnetic emission (SEE)) as the main signal (MS) of probing transmitter are considered. The theoretical model is based on numerical solution of driven nonlinear Shrödinger equation (NSE) in inhomogeneous plasma. The simulation allows us to study a self-consistent spatial-temporal dynamics of field and plasma. The observed evolution of phase characteristics of MS and CS qualitatively correspond to the results of numerical simulation and demonstrate the penetration processes of powerful electromagnetic wave in supercritical (in linear approach) plasma regions. The modeling results explain also the periodic generation of CS, the travel CS maximum down to density gradient, the aftereffect of CS. The obtained results show the excitation of strong turbulence and allow us to interpret CS, NC and so far inexplicable phenomena as "spikes" too. The work was supported in part by Russian Foundation for Basic Research (grants Nos. 99-02-16642, 99-02- 16399).

Parallel processing of real-time dynamic systems simulation on OSCAR (Optimally SCheduled Advanced multiprocessoR)

NASA Technical Reports Server (NTRS)

Kasahara, Hironori; Honda, Hiroki; Narita, Seinosuke

1989-01-01

Parallel processing of real-time dynamic systems simulation on a multiprocessor system named OSCAR is presented. In the simulation of dynamic systems, generally, the same calculation are repeated every time step. However, we cannot apply to Do-all or the Do-across techniques for parallel processing of the simulation since there exist data dependencies from the end of an iteration to the beginning of the next iteration and furthermore data-input and data-output are required every sampling time period. Therefore, parallelism inside the calculation required for a single time step, or a large basic block which consists of arithmetic assignment statements, must be used. In the proposed method, near fine grain tasks, each of which consists of one or more floating point operations, are generated to extract the parallelism from the calculation and assigned to processors by using optimal static scheduling at compile time in order to reduce large run time overhead caused by the use of near fine grain tasks. The practicality of the scheme is demonstrated on OSCAR (Optimally SCheduled Advanced multiprocessoR) which has been developed to extract advantageous features of static scheduling algorithms to the maximum extent.

Temporal dynamics of biogeochemical processes at the Norman Landfill site

USGS Publications Warehouse

Arora, Bhavna; Mohanty, Binayak P.; McGuire, Jennifer T.; Cozzarelli, Isabelle M.

2013-01-01

The temporal variability observed in redox sensitive species in groundwater can be attributed to coupled hydrological, geochemical, and microbial processes. These controlling processes are typically nonstationary, and distributed across various time scales. Therefore, the purpose of this study is to investigate biogeochemical data sets from a municipal landfill site to identify the dominant modes of variation and determine the physical controls that become significant at different time scales. Data on hydraulic head, specific conductance, δ2H, chloride, sulfate, nitrate, and nonvolatile dissolved organic carbon were collected between 1998 and 2000 at three wells at the Norman Landfill site in Norman, OK. Wavelet analysis on this geochemical data set indicates that variations in concentrations of reactive and conservative solutes are strongly coupled to hydrologic variability (water table elevation and precipitation) at 8 month scales, and to individual eco-hydrogeologic framework (such as seasonality of vegetation, surface-groundwater dynamics) at 16 month scales. Apart from hydrologic variations, temporal variability in sulfate concentrations can be associated with different sources (FeS cycling, recharge events) and sinks (uptake by vegetation) depending on the well location and proximity to the leachate plume. Results suggest that nitrate concentrations show multiscale behavior across temporal scales for different well locations, and dominant variability in dissolved organic carbon for a closed municipal landfill can be larger than 2 years due to its decomposition and changing content. A conceptual framework that explains the variability in chemical concentrations at different time scales as a function of hydrologic processes, site-specific interactions, and/or coupled biogeochemical effects is also presented.

Dynamic classification of fetal heart rates by hierarchical Dirichlet process mixture models.

PubMed

Yu, Kezi; Quirk, J Gerald; Djurić, Petar M

2017-01-01

In this paper, we propose an application of non-parametric Bayesian (NPB) models for classification of fetal heart rate (FHR) recordings. More specifically, we propose models that are used to differentiate between FHR recordings that are from fetuses with or without adverse outcomes. In our work, we rely on models based on hierarchical Dirichlet processes (HDP) and the Chinese restaurant process with finite capacity (CRFC). Two mixture models were inferred from real recordings, one that represents healthy and another, non-healthy fetuses. The models were then used to classify new recordings and provide the probability of the fetus being healthy. First, we compared the classification performance of the HDP models with that of support vector machines on real data and concluded that the HDP models achieved better performance. Then we demonstrated the use of mixture models based on CRFC for dynamic classification of the performance of (FHR) recordings in a real-time setting.

Dynamic classification of fetal heart rates by hierarchical Dirichlet process mixture models

PubMed Central

Yu, Kezi; Quirk, J. Gerald

2017-01-01

In this paper, we propose an application of non-parametric Bayesian (NPB) models for classification of fetal heart rate (FHR) recordings. More specifically, we propose models that are used to differentiate between FHR recordings that are from fetuses with or without adverse outcomes. In our work, we rely on models based on hierarchical Dirichlet processes (HDP) and the Chinese restaurant process with finite capacity (CRFC). Two mixture models were inferred from real recordings, one that represents healthy and another, non-healthy fetuses. The models were then used to classify new recordings and provide the probability of the fetus being healthy. First, we compared the classification performance of the HDP models with that of support vector machines on real data and concluded that the HDP models achieved better performance. Then we demonstrated the use of mixture models based on CRFC for dynamic classification of the performance of (FHR) recordings in a real-time setting. PMID:28953927

Incorporating Social System Dynamics into the Food-Energy-Water System Resilience-Sustainability Modeling Process

NASA Astrophysics Data System (ADS)

Givens, J.; Padowski, J.; Malek, K.; Guzman, C.; Boll, J.; Adam, J. C.; Witinok-Huber, R.

2017-12-01

In the face of climate change and multi-scalar governance objectives, achieving resilience of food-energy-water (FEW) systems requires interdisciplinary approaches. Through coordinated modeling and management efforts, we study "Innovations in the Food-Energy-Water Nexus (INFEWS)" through a case-study in the Columbia River Basin. Previous research on FEW system management and resilience includes some attention to social dynamics (e.g., economic, governance); however, more research is needed to better address social science perspectives. Decisions ultimately taken in this river basin would occur among stakeholders encompassing various institutional power structures including multiple U.S. states, tribal lands, and sovereign nations. The social science lens draws attention to the incompatibility between the engineering definition of resilience (i.e., return to equilibrium or a singular stable state) and the ecological and social system realities, more explicit in the ecological interpretation of resilience (i.e., the ability of a system to move into a different, possibly more resilient state). Social science perspectives include but are not limited to differing views on resilience as normative, system persistence versus transformation, and system boundary issues. To expand understanding of resilience and objectives for complex and dynamic systems, concepts related to inequality, heterogeneity, power, agency, trust, values, culture, history, conflict, and system feedbacks must be more tightly integrated into FEW research. We identify gaps in knowledge and data, and the value and complexity of incorporating social components and processes into systems models. We posit that socio-biophysical system resilience modeling would address important complex, dynamic social relationships, including non-linear dynamics of social interactions, to offer an improved understanding of sustainable management in FEW systems. Conceptual modeling that is presented in our study, represents

Boostream: a dynamic fluid flow process to assemble nanoparticles at liquid interface

NASA Astrophysics Data System (ADS)

Delléa, Olivier; Lebaigue, Olivier

2017-12-01

CEA-LITEN develops an original process called Boostream® to manipulate, assemble and connect micro- or nanoparticles of various materials, sizes, shapes and functions to obtain monolayer colloidal crystals (MCCs). This process uses the upper surface of a liquid film flowing down a ramp to assemble particles in a manner that is close to the horizontal situation of a Langmuir-Blodgett film construction. In presence of particles at the liquid interface, the film down-flow configuration exhibits an unusual hydraulic jump which results from the fluid flow accommodation to the particle monolayer. In order to master our process, the fluid flow has been modeled and experimentally characterized by optical means, such as with the moiré technique that consists in observing the reflection of a succession of periodic black-and-red fringes on the liquid surface mirror. The fringe images are deformed when reflected by the curved liquid surface associated with the hydraulic jump, the fringe deformation being proportional to the local slope of the surface. This original experimental setup allowed us to get the surface profile in the jump region and to measure it along with the main process parameters (liquid flow rate, slope angle, temperature sensitive fluid properties such as dynamic viscosity or surface tension, particle sizes). This work presents the experimental setup and its simple model, the different experimental characterization techniques used and will focus on the way the hydraulic jump relies on the process parameters.

Attractor Dynamics and Semantic Neighborhood Density: Processing Is Slowed by Near Neighbors and Speeded by Distant Neighbors

ERIC Educational Resources Information Center

Mirman, Daniel; Magnuson, James S.

2008-01-01

The authors investigated semantic neighborhood density effects on visual word processing to examine the dynamics of activation and competition among semantic representations. Experiment 1 validated feature-based semantic representations as a basis for computing semantic neighborhood density and suggested that near and distant neighbors have…

The Contribution of GGOS to Understanding Dynamic Earth Processes

NASA Astrophysics Data System (ADS)

Gross, Richard

2017-04-01

Geodesy is the science of the Earth's shape, size, gravity and rotation, including their evolution in time. Geodetic observations play a major role in the solid Earth sciences because they are fundamental for the understanding and modeling of Earth system processes. Changes in the Earth's shape, its gravitational field, and its rotation are caused by external forces acting on the Earth system and internal processes involving mass transfer and exchange of angular and linear momentum. Thus, variations in these geodetic quantities of the Earth reflect and constrain mechanical and thermo-dynamic processes in the Earth system. Mitigating the impact on human life and property of natural hazards such as earthquakes, volcanic eruptions, debris flows, landslides, land subsidence, sea level change, tsunamis, floods, storm surges, hurricanes and extreme weather is an important scientific task to which geodetic observations make fundamental contributions. Geodetic observations can be used to monitor the pre-eruptive deformation of volcanoes and the pre-seismic deformation of earthquake fault zones, aiding in the issuance of volcanic eruption and earthquake warnings. They can also be used to rapidly estimate earthquake fault motion, aiding in the modeling of tsunami genesis and the issuance of tsunami warnings. Geodetic observations are also used in other areas of the Earth sciences, not just the solid Earth sciences. For example, geodesy contributes to atmospheric science by supporting both observation and prediction of the weather by geo-referencing meteorological observing data and by globally tracking change in stratospheric mass and lower tropospheric water vapor fields. Geodetic measurements of refraction profiles derived from satellite occultation data are routinely assimilated into numerical weather prediction models. Geodesy contributes to hydrologic studies by providing a unique global reference system for measurements of: sub-seasonal, seasonal and secular movements

Nonadiabatic Dynamics of Photoinduced Proton-Coupled Electron Transfer Processes

DTIC Science & Technology

devices and photoelectrochemical cells. Theoretical methodology for simulating the nonadiabatic dynamics of photoinduced PCET reactions in solution has...tuning and control of the ultrafast dynamics is crucial for designing renewable and sustainable energy sources, such as artificial photosynthesis...describes the solute with a multiconfigurational method in a bath of explicit solvent molecules. The transferring hydrogen nucleus is represented as a

Spatiotemporal Dynamics of Argument Retrieval and Reordering: An fMRI and EEG Study on Sentence Processing

PubMed Central

Meyer, Lars; Obleser, Jonas; Kiebel, Stefan J.; Friederici, Angela D.

2012-01-01

In sentence processing, it is still unclear how the neural language network successfully establishes argument–verb dependencies in its spatiotemporal neuronal dynamics. Previous work has suggested that the establishment of subject–verb and object–verb dependencies requires argument retrieval from working memory, and that dependency establishment in object-first sentences additionally necessitates argument reordering. We examine the spatiotemporal neuronal dynamics of the brain regions that subserve these sub-processes by crossing an argument reordering factor (i.e., subject-first versus object-first sentences) with an argument retrieval factor (i.e., short versus long argument–verb dependencies) in German. Using functional magnetic resonance imaging (fMRI), we found that reordering demands focally activate the left pars opercularis (Broca’s area), while storage and retrieval demands activated left temporo-parietal (TP) regions. In addition, when analyzing the time course of fMRI-informed equivalent current dipole sources in the EEG at the subcategorizing verb, we found that activity in the TP-region occurs relatively early (40–180 ms), followed by activity in Broca’s area (300–500 ms). These findings were matched by topographical correlation analyses of fMRI activations in EEG sensor space, showing that, in the scalp potential, TP-region activity surfaces as an early positivity and IFG activity as a later positivity in the scalp potential. These results provide fine-grained evidence for spatiotemporally separable sub-processes of argument retrieval and reordering in sentence processing. PMID:23248607

Modeling Physiological Processes That Relate Toxicant Exposure and Bacterial Population Dynamics

PubMed Central

Klanjscek, Tin; Nisbet, Roger M.; Priester, John H.; Holden, Patricia A.

2012-01-01

Quantifying effects of toxicant exposure on metabolic processes is crucial to predicting microbial growth patterns in different environments. Mechanistic models, such as those based on Dynamic Energy Budget (DEB) theory, can link physiological processes to microbial growth. Here we expand the DEB framework to include explicit consideration of the role of reactive oxygen species (ROS). Extensions considered are: (i) additional terms in the equation for the “hazard rate” that quantifies mortality risk; (ii) a variable representing environmental degradation; (iii) a mechanistic description of toxic effects linked to increase in ROS production and aging acceleration, and to non-competitive inhibition of transport channels; (iv) a new representation of the “lag time” based on energy required for acclimation. We estimate model parameters using calibrated Pseudomonas aeruginosa optical density growth data for seven levels of cadmium exposure. The model reproduces growth patterns for all treatments with a single common parameter set, and bacterial growth for treatments of up to 150 mg(Cd)/L can be predicted reasonably well using parameters estimated from cadmium treatments of 20 mg(Cd)/L and lower. Our approach is an important step towards connecting levels of biological organization in ecotoxicology. The presented model reveals possible connections between processes that are not obvious from purely empirical considerations, enables validation and hypothesis testing by creating testable predictions, and identifies research required to further develop the theory. PMID:22328915

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.

Monitoring dynamic electrochemical processes with in situ ptychography

NASA Astrophysics Data System (ADS)

Kourousias, George; Bozzini, Benedetto; Jones, Michael W. M.; Van Riessen, Grant A.; Dal Zilio, Simone; Billè, Fulvio; Kiskinova, Maya; Gianoncelli, Alessandra

2018-03-01

The present work reports novel soft X-ray Fresnel CDI ptychography results, demonstrating the potential of this method for dynamic in situ studies. Specifically, in situ ptychography experiments explored the electrochemical fabrication of Co-doped Mn-oxide/polypyrrole nanocomposites for sustainable and cost-effective fuel-cell air-electrodes. Oxygen-reduction catalysts based on Mn-oxides exhibit relatively high activity, but poor durability: doping with Co has been shown to improve both reduction rate and stability. In this study, we examine the chemical state distribution of the catalytically crucial Co dopant to elucidate details of the Co dopant incorporation into the Mn/polymer matrix. The measurements were performed using a custom-made three-electrode thin-layer microcell, developed at the TwinMic beamline of Elettra Synchrotron during a series of experiments that were continued at the SXRI beamline of the Australian Synchrotron. Our time-resolved ptychography-based investigation was carried out in situ after two representative growth steps, controlled by electrochemical bias. In addition to the observation of morphological changes, we retrieved the spectroscopic information, provided by multiple ptychographic energy scans across Co L3-edge, shedding light on the doping mechanism and demonstrating a general approach for the molecular-level investigation complex multimaterial electrodeposition processes.

Use of simulated satellite radiances from a mesoscale numerical model to understand kinematic and dynamic processes

NASA Technical Reports Server (NTRS)

Kalb, Michael; Robertson, Franklin; Jedlovec, Gary; Perkey, Donald

1987-01-01

Techniques by which mesoscale numerical weather prediction model output and radiative transfer codes are combined to simulate the radiance fields that a given passive temperature/moisture satellite sensor would see if viewing the evolving model atmosphere are introduced. The goals are to diagnose the dynamical atmospheric processes responsible for recurring patterns in observed satellite radiance fields, and to develop techniques to anticipate the ability of satellite sensor systems to depict atmospheric structures and provide information useful for numerical weather prediction (NWP). The concept of linking radiative transfer and dynamical NWP codes is demonstrated with time sequences of simulated radiance imagery in the 24 TIROS vertical sounder channels derived from model integrations for March 6, 1982.

Dynamic mechanical properties of hydroxyapatite/polyethylene oxide nanocomposites: characterizing isotropic and post-processing microstructures

NASA Astrophysics Data System (ADS)

Shofner, Meisha; Lee, Ji Hoon

2012-02-01

Compatible component interfaces in polymer nanocomposites can be used to facilitate a dispersed morphology and improved physical properties as has been shown extensively in experimental results concerning amorphous matrix nanocomposites. In this research, a block copolymer compatibilized interface is employed in a semi-crystalline matrix to prevent large scale nanoparticle clustering and enable microstructure construction with post-processing drawing. The specific materials used are hydroxyapatite nanoparticles coated with a polyethylene oxide-b-polymethacrylic acid block copolymer and a polyethylene oxide matrix. Two particle shapes are used: spherical and needle-shaped. Characterization of the dynamic mechanical properties indicated that the two nanoparticle systems provided similar levels of reinforcement to the matrix. For the needle-shaped nanoparticles, the post-processing step increased matrix crystallinity and changed the thermomechanical reinforcement trends. These results will be used to further refine the post-processing parameters to achieve a nanocomposite microstructure with triangulated arrays of nanoparticles.

Interannual Variations in Tropical Upper-Tropospheric Humidity: Understanding Tropical Convective and Dynamical Processes

NASA Technical Reports Server (NTRS)

Robertson, Franklin R.; Fitzjarrald, Dan E.; Miller, Timothy L.

2005-01-01

Uncertainty remains as to what extent variability in mid to upper tropospheric moisture, especially over the tropics, behaves as constant relative humidity during interannual climate variations associated with ENSO. Systematic variations in HIRS 6.7 micron and MLS 205 GHz suggest that dry subtropical regions evolving during warm SST events depress relative humidity, but the interpretation of these events is still uncertain. Additional specific concerns have to do with regional signatures of convective processes: How does the origin of dry air in the eastern subtropical N. Pacific differ in ENSO warm versus cold years? The dynamics of Rossby wave forcing by convective heating, subtropical jet stream dynamics, and dynamics driven subsidence all come into play here. How variations in precipitating ice hydrometeors from tropical anvils relate to variations in UTH is also a subject of debate? Do variations in precipitating ice, cloud cover and water vapor behavior show any support for the Iris-hypothesis mechanism? Here we examine historical records of SSM/T-2 data to gain a better physical understanding of the effects of deep convective moisture sources and dynamically-induced vertical circulations on UTH. These high frequency microwave measurements (183.3 GHz) take advantage of far less sensitivity to cloud hydrometeors than the 6.7 micron data to yield a record of upper tropospheric relative humidity. Furthermore, signatures of precipitating ice from these channels facilitate comparisons to TRMM hydrometeors detected by radar. In analyzing these observations, we isolate water vapor and temperature change components that affect brightness temperatures and the inferred relative humidity. Trajectory modeling is also used to understand interannual humidity anomalies in terms of outflow fbm convective regions and history of diabatically-driven sinking which modifies relative humidity.

Dynamic Socialized Gaussian Process Models for Human Behavior Prediction in a Health Social Network

PubMed Central

Shen, Yelong; Phan, NhatHai; Xiao, Xiao; Jin, Ruoming; Sun, Junfeng; Piniewski, Brigitte; Kil, David; Dou, Dejing

2016-01-01

Modeling and predicting human behaviors, such as the level and intensity of physical activity, is a key to preventing the cascade of obesity and helping spread healthy behaviors in a social network. In our conference paper, we have developed a social influence model, named Socialized Gaussian Process (SGP), for socialized human behavior modeling. Instead of explicitly modeling social influence as individuals' behaviors influenced by their friends' previous behaviors, SGP models the dynamic social correlation as the result of social influence. The SGP model naturally incorporates personal behavior factor and social correlation factor (i.e., the homophily principle: Friends tend to perform similar behaviors) into a unified model. And it models the social influence factor (i.e., an individual's behavior can be affected by his/her friends) implicitly in dynamic social correlation schemes. The detailed experimental evaluation has shown the SGP model achieves better prediction accuracy compared with most of baseline methods. However, a Socialized Random Forest model may perform better at the beginning compared with the SGP model. One of the main reasons is the dynamic social correlation function is purely based on the users' sequential behaviors without considering other physical activity-related features. To address this issue, we further propose a novel “multi-feature SGP model” (mfSGP) which improves the SGP model by using multiple physical activity-related features in the dynamic social correlation learning. Extensive experimental results illustrate that the mfSGP model clearly outperforms all other models in terms of prediction accuracy and running time. PMID:27746515

Numerical Procedures for Analyzing Dynamical Processes.

DTIC Science & Technology

1992-02-29

different in nature and can be of the third coordinate of the numerically calcu- called crnamic in that information about the dy- lated solution. Such...recover the matrix A by changing coordinates back to the original basis. "The points x, are points on the attractor which are not For example, if we...the attractor contained witun a small distance (of rotate the coordinate axes by 45’, The dynamics Xrer. In this notation. x, and y, are consecutive

An applicational process for dynamic balancing of turbomachinery shafting

NASA Technical Reports Server (NTRS)

Verhoff, Vincent G.

1990-01-01

The NASA Lewis Research Center has developed and implemented a time-efficient methodology for dynamically balancing turbomachinery shafting. This methodology minimizes costly facility downtime by using a balancing arbor (mandrel) that simulates the turbomachinery (rig) shafting. The need for precision dynamic balancing of turbomachinery shafting and for a dynamic balancing methodology is discussed in detail. Additionally, the inherent problems (and their causes and effects) associated with unbalanced turbomachinery shafting as a function of increasing shaft rotational speeds are discussed. Included are the design criteria concerning rotor weight differentials for rotors made of different materials that have similar parameters and shafting. The balancing methodology for applications where rotor replaceability is a requirement is also covered. This report is intended for use as a reference when designing, fabricating, and troubleshooting turbomachinery shafting.

Exploring Verbal, Visual and Schematic Learners' Static and Dynamic Mental Images of Scientific Species and Processes in Relation to Their Spatial Ability

ERIC Educational Resources Information Center

Al-Balushi, Sulaiman M.; Coll, Richard Kevin

2013-01-01

The current study compared different learners' static and dynamic mental images of unseen scientific species and processes in relation to their spatial ability. Learners were classified into verbal, visual and schematic. Dynamic images were classified into: appearing/disappearing, linear-movement, and rotation. Two types of scientific entities and…

Male veterans with PTSD exhibit aberrant neural dynamics during working memory processing: an MEG study

PubMed Central

McDermott, Timothy J.; Badura-Brack, Amy S.; Becker, Katherine M.; Ryan, Tara J.; Khanna, Maya M.; Heinrichs-Graham, Elizabeth; Wilson, Tony W.

2016-01-01

Background Posttraumatic stress disorder (PTSD) is associated with executive functioning deficits, including disruptions in working memory. In this study, we examined the neural dynamics of working memory processing in veterans with PTSD and a matched healthy control sample using magnetoencephalography (MEG). Methods Our sample of recent combat veterans with PTSD and demographically matched participants without PTSD completed a working memory task during a 306-sensor MEG recording. The MEG data were preprocessed and transformed into the time-frequency domain. Significant oscillatory brain responses were imaged using a beamforming approach to identify spatiotemporal dynamics. Results Fifty-one men were included in our analyses: 27 combat veterans with PTSD and 24 controls. Across all participants, a dynamic wave of neural activity spread from posterior visual cortices to left frontotemporal regions during encoding, consistent with a verbal working memory task, and was sustained throughout maintenance. Differences related to PTSD emerged during early encoding, with patients exhibiting stronger α oscillatory responses than controls in the right inferior frontal gyrus (IFG). Differences spread to the right supramarginal and temporal cortices during later encoding where, along with the right IFG, they persisted throughout the maintenance period. Limitations This study focused on men with combat-related PTSD using a verbal working memory task. Future studies should evaluate women and the impact of various traumatic experiences using diverse tasks. Conclusion Posttraumatic stress disorder is associated with neurophysiological abnormalities during working memory encoding and maintenance. Veterans with PTSD engaged a bilateral network, including the inferior prefrontal cortices and supramarginal gyri. Right hemispheric neural activity likely reflects compensatory processing, as veterans with PTSD work to maintain accurate performance despite known cognitive deficits

A Competency Model for Process Dynamics and Control and Its Use for Test Construction at University Level

ERIC Educational Resources Information Center

Taskinen, Päivi H.; Steimel, Jochen; Gräfe, Linda; Engell, Sebastian; Frey, Andreas

2015-01-01

This study examined students' competencies in engineering education at the university level. First, we developed a competency model in one specific field of engineering: process dynamics and control. Then, the theoretical model was used as a frame to construct test items to measure students' competencies comprehensively. In the empirical…

Methodology in the assessment of complex human performance : the effects of signal rate on monitoring a dynamic process.

DOT National Transportation Integrated Search

1969-04-01

Male subjects were tested after extensive training as two five-man 'crews' in an experiment designed to examine the effects of signal rate on the performance of a task involving the monitoring of a dynamic process. Performance was measured using thre...

Recurrent connectivity can account for the dynamics of disparity processing in V1

PubMed Central

Samonds, Jason M.; Potetz, Brian R.; Tyler, Christopher W.; Lee, Tai Sing

2013-01-01

Disparity tuning measured in the primary visual cortex (V1) is described well by the disparity energy model, but not all aspects of disparity tuning are fully explained by the model. Such deviations from the disparity energy model provide us with insight into how network interactions may play a role in disparity processing and help to solve the stereo correspondence problem. Here, we propose a neuronal circuit model with recurrent connections that provides a simple account of the observed deviations. The model is based on recurrent connections inferred from neurophysiological observations on spike timing correlations, and is in good accord with existing data on disparity tuning dynamics. We further performed two additional experiments to test predictions of the model. First, we increased the size of stimuli to drive more neurons and provide a stronger recurrent input. Our model predicted sharper disparity tuning for larger stimuli. Second, we displayed anti-correlated stereograms, where dots of opposite luminance polarity are matched between the left- and right-eye images and result in inverted disparity tuning in the disparity energy model. In this case, our model predicted reduced sharpening and strength of inverted disparity tuning. For both experiments, the dynamics of disparity tuning observed from the neurophysiological recordings in macaque V1 matched model simulation predictions. Overall, the results of this study support the notion that, while the disparity energy model provides a primary account of disparity tuning in V1 neurons, neural disparity processing in V1 neurons is refined by recurrent interactions among elements in the neural circuit. PMID:23407952

Reactive molecular dynamics simulations of switching processes of azobenzene-based monolayer on surface

NASA Astrophysics Data System (ADS)

Tian, Ziqi; Wen, Jin; Ma, Jing

2013-07-01

It is a challenge to simulate the switching process of functional self-assembled monolayers (SAMs) on metal surfaces, since the systems consist of thousands of atoms and the switching is triggered by quantum-mechanical events. Herein a molecular dynamics simulation with a reactive rotation potential of N=N bond is implemented to investigate the dynamic conformational changes and packing effects on the stimuli-responsive isomerization of the terminally thiol functionalized azobiphenyls (AZOs), which are bound on the Au(111) surface. To, respectively, distinguish the time evolutions that start from cis and trans initial configurations, two different functions are established to model the potential energy curves for cis-to-trans and trans-to-cis transitions, instead of the only one cosine function used in the conventional non-reactive force fields. In order to simulate the conformation transitions of the AZO film on surface, a random switching function, depending on the N=N twisting angle, is constructed to consider both forward and backward cis/trans isomerization events and to trigger the reaction by changing the N atom types automatically. The factors that will influence the isomerization process, including the choice of ensembles and thermostat algorithms, the time intervals separating each switching, and the forms of the switching function, are systematically tested. Most AZO molecules switch from the cis to trans configuration with a coverage of 5.76 × 10-6 mol/m2 on a picosecond time scale, and a low coverage might make the switching irreversible, which is in agreement with the experiments.

Process and dynamics of traditional selling wild edible mushrooms in tropical Mexico

PubMed Central

Ruán-Soto, Felipe; Garibay-Orijel, Roberto; Cifuentes, Joaquín

2006-01-01

Background More than twelve temperate-inhabitant Mexican ethnic groups are considered to be mycophilic and to have extensive traditional mycological knowledge. In contrast, inhabitants of tropical lands have been studied only superficially and their mycological knowledge is less well known. In this paper, we report the results of an ethnomycological research in markets of a wide area of the Mexican tropics. Our aims were to describe the dynamics related to the traditional selling process of wild mushrooms and to determine the tendencies of informants toward mushrooms (mycophily vs. mycophoby). Methods We visited 25 markets of 12 different settlements in the states of Oaxaca, Tabasco and Veracruz and collected information by participant observation as well as by 291 non-structured and semi-structured interviews. Results Mushroom selling was observed in four towns in Oaxaca and in two in Tabasco. Women represented 81.82% of sellers, while indigenous people (Chinantecos, Chontales, Ch'oles and Zoques) comprised 68.18%. Mushroom commercialization took place in secondary mobile markets and only in peasant stands. Mushroom collectors gather the resource in places with secondary vegetation, farmed areas and cattle fields. Because of land tenure restrictions mushroom sellers did not normally collect mushrooms themselves. In Oaxaca, we observed economic dynamics not based on capitalism, such as exchange, reciprocity and barter. Conclusion The sale of some wild edible mushrooms, the large amounts of commercialization of Schizophyllum commune, the complicated intermediary process, as well as the insertion of mushrooms into different informal economic practices are all evidence of an existent mycophily in a sector of the population of this region of the Mexican tropics. Among our informants, urban mestizo people were mycophobic, rural mestizo people were non-mycophilic and indigenous people were true mycophilic. PMID:16393345

Modeling Academic Education Processes by Dynamic Storyboarding

ERIC Educational Resources Information Center

Sakurai, Yoshitaka; Dohi, Shinichi; Tsuruta, Setsuo; Knauf, Rainer

2009-01-01

In high-level education such as university studies, there is a flexible but complicated system of subject offerings and registration rules such as prerequisite subjects. Those offerings, connected with registration rules, should be matched to the students' learning needs and desires, which change dynamically. Students need assistance in such a…

First-principles modeling of laser-matter interaction and plasma dynamics in nanosecond pulsed laser shock processing

NASA Astrophysics Data System (ADS)

Zhang, Zhongyang; Nian, Qiong; Doumanidis, Charalabos C.; Liao, Yiliang

2018-02-01

Nanosecond pulsed laser shock processing (LSP) techniques, including laser shock peening, laser peen forming, and laser shock imprinting, have been employed for widespread industrial applications. In these processes, the main beneficial characteristic is the laser-induced shockwave with a high pressure (in the order of GPa), which leads to the plastic deformation with an ultrahigh strain rate (105-106/s) on the surface of target materials. Although LSP processes have been extensively studied by experiments, few efforts have been put on elucidating underlying process mechanisms through developing a physics-based process model. In particular, development of a first-principles model is critical for process optimization and novel process design. This work aims at introducing such a theoretical model for a fundamental understanding of process mechanisms in LSP. Emphasis is placed on the laser-matter interaction and plasma dynamics. This model is found to offer capabilities in predicting key parameters including electron and ion temperatures, plasma state variables (temperature, density, and pressure), and the propagation of the laser shockwave. The modeling results were validated by experimental data.

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

USGS Publications Warehouse

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Interactions and Feedbacks Between Land Surface Processes and Water Cycle Dynamics in Africa

NASA Astrophysics Data System (ADS)

Prince, S. D.; Xue, Y.; Song, G.; Cox, P. M.

2012-12-01

In the past three decades, numerous modeling sensitivity studies have established the importance of detailed vegetation and atmosphere interactions in West African water cycle dynamics. Recently, new evidence has emerged from satellite data analyses that indicate a fully coupled process is needed to explain the relationships discovered in these analyses. In order to elucidate the processes, we have applied the off-line Simplified Simple Biosphere Model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID). SSiB4 is a biophysical model based on surface water and energy balance which interacts with TRIFFID by providing the carbon assimilation. TRIFFID is a dynamic vegetation model based on carbon balance. The offline SSiB4/TRIFFID was integrated using the observed precipitation and reanalysis-based meteorological forcing from 1948 to 2006 over West Africa. West Africa has diverse climate and ecosystem regions. It suffered the most severe and longest drought in the world during the 20th century, and has the most pronounced decadal water cycle variability in the planet. The simulation results indicate that the water cycle variability has significant effects on the spatial distributions and temporal variations of plant functional types and leaf area index (LAI), which are generally consistent with those observed from satellites since the 1980s. The simulated vegetation conditions over Sahel region exhibited seasonal, inter-annual variations, consistent with West Africa monsoon variability, and the simulated inter-decadal variability in vegetation was consistent with the Sahel drought in the 1970s and 1980s and partial recovery in the 1990s and 2000s. To further understand the cause of decadal variability of climate, water cycle and vegetation dynamics, experiments were conducted to investigate the relationship between the LAI, atmospheric carbon dioxide increase and global warming. In one experiment, the 1948

I. Advances in NMR Signal Processing. II. Spin Dynamics in Quantum Dissipative Systems

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

Lin, Yung-Ya

1998-11-01

Part I. Advances in IVMR Signal Processing. Improvements of sensitivity and resolution are two major objects in the development of NMR/MRI. A signal enhancement method is first presented which recovers signal from noise by a judicious combination of a priordmowledge to define the desired feasible solutions and a set theoretic estimation for restoring signal properties that have been lost due to noise contamination. The effect of noise can be significantly mitigated through the process of iteratively modifying the noisy data set to the smallest degree necessary so that it possesses a collection of prescribed properties and also lies closest tomore » the original data set. A novel detection-estimation scheme is then introduced to analyze noisy and/or strongly damped or truncated FIDs. Based on exponential modeling, the number of signals is detected based on information estimated using the matrix pencil method. theory and the spectral parameters are Part II. Spin Dynamics in body dipole-coupled systems Quantum Dissipative Systems. Spin dynamics in manyconstitutes one of the most fundamental problems in magnetic resonance and condensed-matter physics. Its many-spin nature precludes any rigorous treatment. ‘Therefore, the spin-boson model is adopted to describe in the rotating frame the influence of the dipolar local fields on a tagged spin. Based on the polaronic transform and a perturbation treatment, an analytical solution is derived, suggesting the existence of self-trapped states in the. strong coupling limit, i.e., when transverse local field >> longitudinal local field. Such nonlinear phenomena originate from the joint action of the lattice fluctuations and the reaction field. Under semiclassical approximation, it is found that the main effect of the reaction field is the renormalization of the Hamiltonian of interest. Its direct consequence is the two-step relaxation process: the spin is initially localized in a quasiequilibrium state, which is later

Dynamic Data Management Based on Archival Process Integration at the Centre for Environmental Data Archival

NASA Astrophysics Data System (ADS)

Conway, Esther; Waterfall, Alison; Pepler, Sam; Newey, Charles

2015-04-01

In this paper we decribe a business process modelling approach to the integration of exisiting archival activities. We provide a high level overview of existing practice and discuss how procedures can be extended and supported through the description of preservation state. The aim of which is to faciliate the dynamic controlled management of scientific data through its lifecycle. The main types of archival processes considered are: • Management processes that govern the operation of an archive. These management processes include archival governance (preservation state management, selection of archival candidates and strategic management) . • Operational processes that constitute the core activities of the archive which maintain the value of research assets. These operational processes are the acquisition, ingestion, deletion, generation of metadata and preservation actvities, • Supporting processes, which include planning, risk analysis and monitoring of the community/preservation environment. We then proceed by describing the feasability testing of extended risk management and planning procedures which integrate current practices. This was done through the CEDA Archival Format Audit which inspected British Atmospherics Data Centre and National Earth Observation Data Centre Archival holdings. These holdings are extensive, comprising of around 2PB of data and 137 million individual files which were analysed and characterised in terms of format based risk. We are then able to present an overview of the risk burden faced by a large scale archive attempting to maintain the usability of heterogeneous environmental data sets. We conclude by presenting a dynamic data management information model that is capable of describing the preservation state of archival holdings throughout the data lifecycle. We provide discussion of the following core model entities and their relationships: • Aspirational entities, which include Data Entity definitions and their associated

Resolving molecule-specific information in dynamic lipid membrane processes with multi-resonant infrared metasurfaces.

PubMed

Rodrigo, Daniel; Tittl, Andreas; Ait-Bouziad, Nadine; John-Herpin, Aurelian; Limaj, Odeta; Kelly, Christopher; Yoo, Daehan; Wittenberg, Nathan J; Oh, Sang-Hyun; Lashuel, Hilal A; Altug, Hatice

2018-06-04

A multitude of biological processes are enabled by complex interactions between lipid membranes and proteins. To understand such dynamic processes, it is crucial to differentiate the constituent biomolecular species and track their individual time evolution without invasive labels. Here, we present a label-free mid-infrared biosensor capable of distinguishing multiple analytes in heterogeneous biological samples with high sensitivity. Our technology leverages a multi-resonant metasurface to simultaneously enhance the different vibrational fingerprints of multiple biomolecules. By providing up to 1000-fold near-field intensity enhancement over both amide and methylene bands, our sensor resolves the interactions of lipid membranes with different polypeptides in real time. Significantly, we demonstrate that our label-free chemically specific sensor can analyze peptide-induced neurotransmitter cargo release from synaptic vesicle mimics. Our sensor opens up exciting possibilities for gaining new insights into biological processes such as signaling or transport in basic research as well as provides a valuable toolkit for bioanalytical and pharmaceutical applications.

Ferroelectric molecular field-switch based on double proton transfer process: Static and dynamical simulations

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

Rode, Michał F.; Sobolewski, Andrzej L.; Jankowska, Joanna

2016-04-07

In this work, we present a reversible ferroelectric molecular switch controlled by an external electric field. The studied (2Z)-1-(6-((Z)-2-hydroxy-2-phenylvinyl)pyridin-3-yl)-2-(pyridin-2(1H) -ylidene)ethanone (DSA) molecule is polarized by two uniaxial intramolecular hydrogen bonds. Two protons can be transferred along hydrogen bonds upon an electric field applied along the main molecular axis. The process results in reversion of the dipole moment of the system. Static ab initio and on-the-fly dynamical simulations of the DSA molecule placed in an external electric field give insight into the mechanism of the double proton transfer (DPT) in the system and allow for estimation of the time scale ofmore » this process. The results indicate that with increasing strength of the electric field, the step-wise mechanism of DPT changes into the downhill barrierless process in which the synchronous and asynchronous DPTs compete with each other.« less

Efficient molecular dynamics simulations with many-body potentials on graphics processing units

NASA Astrophysics Data System (ADS)

Fan, Zheyong; Chen, Wei; Vierimaa, Ville; Harju, Ari

2017-09-01

Graphics processing units have been extensively used to accelerate classical molecular dynamics simulations. However, there is much less progress on the acceleration of force evaluations for many-body potentials compared to pairwise ones. In the conventional force evaluation algorithm for many-body potentials, the force, virial stress, and heat current for a given atom are accumulated within different loops, which could result in write conflict between different threads in a CUDA kernel. In this work, we provide a new force evaluation algorithm, which is based on an explicit pairwise force expression for many-body potentials derived recently (Fan et al., 2015). In our algorithm, the force, virial stress, and heat current for a given atom can be accumulated within a single thread and is free of write conflicts. We discuss the formulations and algorithms and evaluate their performance. A new open-source code, GPUMD, is developed based on the proposed formulations. For the Tersoff many-body potential, the double precision performance of GPUMD using a Tesla K40 card is equivalent to that of the LAMMPS (Large-scale Atomic/Molecular Massively Parallel Simulator) molecular dynamics code running with about 100 CPU cores (Intel Xeon CPU X5670 @ 2.93 GHz).

Automating the parallel processing of fluid and structural dynamics calculations

NASA Technical Reports Server (NTRS)

Arpasi, Dale J.; Cole, Gary L.

1987-01-01

The NASA Lewis Research Center is actively involved in the development of expert system technology to assist users in applying parallel processing to computational fluid and structural dynamic analysis. The goal of this effort is to eliminate the necessity for the physical scientist to become a computer scientist in order to effectively use the computer as a research tool. Programming and operating software utilities have previously been developed to solve systems of ordinary nonlinear differential equations on parallel scalar processors. Current efforts are aimed at extending these capabilities to systems of partial differential equations, that describe the complex behavior of fluids and structures within aerospace propulsion systems. This paper presents some important considerations in the redesign, in particular, the need for algorithms and software utilities that can automatically identify data flow patterns in the application program and partition and allocate calculations to the parallel processors. A library-oriented multiprocessing concept for integrating the hardware and software functions is described.

Evaluation of linearly solvable Markov decision process with dynamic model learning in a mobile robot navigation task.

PubMed

Kinjo, Ken; Uchibe, Eiji; Doya, Kenji

2013-01-01

Linearly solvable Markov Decision Process (LMDP) is a class of optimal control problem in which the Bellman's equation can be converted into a linear equation by an exponential transformation of the state value function (Todorov, 2009b). In an LMDP, the optimal value function and the corresponding control policy are obtained by solving an eigenvalue problem in a discrete state space or an eigenfunction problem in a continuous state using the knowledge of the system dynamics and the action, state, and terminal cost functions. In this study, we evaluate the effectiveness of the LMDP framework in real robot control, in which the dynamics of the body and the environment have to be learned from experience. We first perform a simulation study of a pole swing-up task to evaluate the effect of the accuracy of the learned dynamics model on the derived the action policy. The result shows that a crude linear approximation of the non-linear dynamics can still allow solution of the task, despite with a higher total cost. We then perform real robot experiments of a battery-catching task using our Spring Dog mobile robot platform. The state is given by the position and the size of a battery in its camera view and two neck joint angles. The action is the velocities of two wheels, while the neck joints were controlled by a visual servo controller. We test linear and bilinear dynamic models in tasks with quadratic and Guassian state cost functions. In the quadratic cost task, the LMDP controller derived from a learned linear dynamics model performed equivalently with the optimal linear quadratic regulator (LQR). In the non-quadratic task, the LMDP controller with a linear dynamics model showed the best performance. The results demonstrate the usefulness of the LMDP framework in real robot control even when simple linear models are used for dynamics learning.

Examination of the Nonlinear Dynamic Systems Associated with Science Student Cognition While Engaging in Science Information Processing

ERIC Educational Resources Information Center

Lamb, Richard; Cavagnetto, Andy; Akmal, Tariq

2016-01-01

A critical problem with the examination of learning in education is that there is an underlying assumption that the dynamic systems associated with student information processing can be measured using static linear assessments. This static linear approach does not provide sufficient ability to characterize learning. Much of the modern research…

Face processing in autism: Reduced integration of cross-feature dynamics.

PubMed

Shah, Punit; Bird, Geoffrey; Cook, Richard

2016-02-01

Characteristic problems with social interaction have prompted considerable interest in the face processing of individuals with Autism Spectrum Disorder (ASD). Studies suggest that reduced integration of information from disparate facial regions likely contributes to difficulties recognizing static faces in this population. Recent work also indicates that observers with ASD have problems using patterns of facial motion to judge identity and gender, and may be less able to derive global motion percepts. These findings raise the possibility that feature integration deficits also impact the perception of moving faces. To test this hypothesis, we examined whether observers with ASD exhibit susceptibility to a new dynamic face illusion, thought to index integration of moving facial features. When typical observers view eye-opening and -closing in the presence of asynchronous mouth-opening and -closing, the concurrent mouth movements induce a strong illusory slowing of the eye transitions. However, we find that observers with ASD are not susceptible to this illusion, suggestive of weaker integration of cross-feature dynamics. Nevertheless, observers with ASD and typical controls were equally able to detect the physical differences between comparison eye transitions. Importantly, this confirms that observers with ASD were able to fixate the eye-region, indicating that the striking group difference has a perceptual, not attentional origin. The clarity of the present results contrasts starkly with the modest effect sizes and equivocal findings seen throughout the literature on static face perception in ASD. We speculate that differences in the perception of facial motion may be a more reliable feature of this condition. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

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.

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.

Dynamic coordinated control during mode transition process for a compound power-split hybrid electric vehicle

NASA Astrophysics Data System (ADS)

Su, Yanzhao; Hu, Minghui; Su, Ling; Qin, Datong; Zhang, Tong; Fu, Chunyun

2018-07-01

The fuel economy of the hybrid electric vehicles (HEVs) can be effectively improved by the mode transition (MT). However, for a power-split powertrain whose power-split transmission is directly connected to the engine, the engine ripple torque (ERT), inconsistent dynamic characteristics (IDC) of engine and motors, model estimation inaccuracies (MEI), system parameter uncertainties (SPU) can cause jerk and vibration of transmission system during the MT process, which will reduce the driving comfort and the life of the drive parts. To tackle these problems, a dynamic coordinated control strategy (DCCS), including a staged engine torque feedforward and feedback estimation (ETFBC) and an active damping feedback compensation (ADBC) based on drive shaft torque estimation (DSTE), is proposed. And the effectiveness of this strategy is verified using a plant model. Firstly, the powertrain plant model is established, and the MT process and problems are analyzed. Secondly, considering the characteristics of the engine torque estimation (ETE) model before and after engine ignition, a motor torque compensation control based on the staged ERT estimation is developed. Then, considering the MEI, SPU and the load change, an ADBC based on a real-time nonlinear reduced-order robust observer of the DSTE is designed. Finally, the simulation results show that the proposed DCCS can effectively improve the driving comfort.