Facilitating Students' Interaction with Real Gas Properties Using a Discovery-Based Approach and Molecular Dynamics Simulations

ERIC Educational Resources Information Center

Sweet, Chelsea; Akinfenwa, Oyewumi; Foley, Jonathan J., IV

2018-01-01

We present an interactive discovery-based approach to studying the properties of real gases using simple, yet realistic, molecular dynamics software. Use of this approach opens up a variety of opportunities for students to interact with the behaviors and underlying theories of real gases. Students can visualize gas behavior under a variety of…

A Single-Cell Biochemistry Approach Reveals PAR Complex Dynamics during Cell Polarization.

PubMed

Dickinson, Daniel J; Schwager, Francoise; Pintard, Lionel; Gotta, Monica; Goldstein, Bob

2017-08-21

Regulated protein-protein interactions are critical for cell signaling, differentiation, and development. For the study of dynamic regulation of protein interactions in vivo, there is a need for techniques that can yield time-resolved information and probe multiple protein binding partners simultaneously, using small amounts of starting material. Here we describe a single-cell protein interaction assay. Single-cell lysates are generated at defined time points and analyzed using single-molecule pull-down, yielding information about dynamic protein complex regulation in vivo. We established the utility of this approach by studying PAR polarity proteins, which mediate polarization of many animal cell types. We uncovered striking regulation of PAR complex composition and stoichiometry during Caenorhabditis elegans zygote polarization, which takes place in less than 20 min. PAR complex dynamics are linked to the cell cycle by Polo-like kinase 1 and govern the movement of PAR proteins to establish polarity. Our results demonstrate an approach to study dynamic biochemical events in vivo. Copyright © 2017 Elsevier Inc. All rights reserved.

Computational dynamics of soft machines

NASA Astrophysics Data System (ADS)

Hu, Haiyan; Tian, Qiang; Liu, Cheng

2017-06-01

Soft machine refers to a kind of mechanical system made of soft materials to complete sophisticated missions, such as handling a fragile object and crawling along a narrow tunnel corner, under low cost control and actuation. Hence, soft machines have raised great challenges to computational dynamics. In this review article, recent studies of the authors on the dynamic modeling, numerical simulation, and experimental validation of soft machines are summarized in the framework of multibody system dynamics. The dynamic modeling approaches are presented first for the geometric nonlinearities of coupled overall motions and large deformations of a soft component, the physical nonlinearities of a soft component made of hyperelastic or elastoplastic materials, and the frictional contacts/impacts of soft components, respectively. Then the computation approach is outlined for the dynamic simulation of soft machines governed by a set of differential-algebraic equations of very high dimensions, with an emphasis on the efficient computations of the nonlinear elastic force vector of finite elements. The validations of the proposed approaches are given via three case studies, including the locomotion of a soft quadrupedal robot, the spinning deployment of a solar sail of a spacecraft, and the deployment of a mesh reflector of a satellite antenna, as well as the corresponding experimental studies. Finally, some remarks are made for future studies.

A Mathematical Framework for the Complex System Approach to Group Dynamics: The Case of Recovery House Social Integration.

PubMed

Light, John M; Jason, Leonard A; Stevens, Edward B; Callahan, Sarah; Stone, Ariel

2016-03-01

The complex system conception of group social dynamics often involves not only changing individual characteristics, but also changing within-group relationships. Recent advances in stochastic dynamic network modeling allow these interdependencies to be modeled from data. This methodology is discussed within a context of other mathematical and statistical approaches that have been or could be applied to study the temporal evolution of relationships and behaviors within small- to medium-sized groups. An example model is presented, based on a pilot study of five Oxford House recovery homes, sober living environments for individuals following release from acute substance abuse treatment. This model demonstrates how dynamic network modeling can be applied to such systems, examines and discusses several options for pooling, and shows how results are interpreted in line with complex system concepts. Results suggest that this approach (a) is a credible modeling framework for studying group dynamics even with limited data, (b) improves upon the most common alternatives, and (c) is especially well-suited to complex system conceptions. Continuing improvements in stochastic models and associated software may finally lead to mainstream use of these techniques for the study of group dynamics, a shift already occurring in related fields of behavioral science.

Dynamic isoperimetry and the geometry of Lagrangian coherent structures

NASA Astrophysics Data System (ADS)

Froyland, Gary

2015-10-01

The study of transport and mixing processes in dynamical systems is particularly important for the analysis of mathematical models of physical systems. We propose a novel, direct geometric method to identify subsets of phase space that remain strongly coherent over a finite time duration. This new method is based on a dynamic extension of classical (static) isoperimetric problems; the latter are concerned with identifying submanifolds with the smallest boundary size relative to their volume. The present work introduces dynamic isoperimetric problems; the study of sets with small boundary size relative to volume as they are evolved by a general dynamical system. We formulate and prove dynamic versions of the fundamental (static) isoperimetric (in)equalities; a dynamic Federer-Fleming theorem and a dynamic Cheeger inequality. We introduce a new dynamic Laplace operator and describe a computational method to identify coherent sets based on eigenfunctions of the dynamic Laplacian. Our results include formal mathematical statements concerning geometric properties of finite-time coherent sets, whose boundaries can be regarded as Lagrangian coherent structures. The computational advantages of our new approach are a well-separated spectrum for the dynamic Laplacian, and flexibility in appropriate numerical approximation methods. Finally, we demonstrate that the dynamic Laplace operator can be realised as a zero-diffusion limit of a newly advanced probabilistic transfer operator method [9] for finding coherent sets, which is based on small diffusion. Thus, the present approach sits naturally alongside the probabilistic approach [9], and adds a formal geometric interpretation.

Improving Quality in Education: Dynamic Approaches to School Improvement

ERIC Educational Resources Information Center

Creemers, Bert P. M.; Kyriakides, Leonidas

2011-01-01

This book explores an approach to school improvement that merges the traditions of educational effectiveness research and school improvement efforts. It displays how the dynamic model, which is theoretical and empirically validated, can be used in both traditions. Each chapter integrates evidence from international and national studies, showing…

Neural networks with excitatory and inhibitory components: Direct and inverse problems by a mean-field approach

NASA Astrophysics Data System (ADS)

di Volo, Matteo; Burioni, Raffaella; Casartelli, Mario; Livi, Roberto; Vezzani, Alessandro

2016-01-01

We study the dynamics of networks with inhibitory and excitatory leak-integrate-and-fire neurons with short-term synaptic plasticity in the presence of depressive and facilitating mechanisms. The dynamics is analyzed by a heterogeneous mean-field approximation, which allows us to keep track of the effects of structural disorder in the network. We describe the complex behavior of different classes of excitatory and inhibitory components, which give rise to a rich dynamical phase diagram as a function of the fraction of inhibitory neurons. Using the same mean-field approach, we study and solve a global inverse problem: reconstructing the degree probability distributions of the inhibitory and excitatory components and the fraction of inhibitory neurons from the knowledge of the average synaptic activity field. This approach unveils new perspectives on the numerical study of neural network dynamics and the possibility of using these models as a test bed for the analysis of experimental data.

A systematic review of dynamics in climate risk and vulnerability assessments

NASA Astrophysics Data System (ADS)

Jurgilevich, Alexandra; Räsänen, Aleksi; Groundstroem, Fanny; Juhola, Sirkku

2017-01-01

Understanding climate risk is crucial for effective adaptation action, and a number of assessment methodologies have emerged. We argue that the dynamics of the individual components in climate risk and vulnerability assessments has received little attention. In order to highlight this, we systematically reviewed 42 sub-national climate risk and vulnerability assessments. We analysed the assessments using an analytical framework with which we evaluated (1) the conceptual approaches to vulnerability and exposure used, (2) if current or future risks were assessed, and (3) if and how changes over time (i.e. dynamics) were considered. Of the reviewed assessments, over half addressed future risks or vulnerability; and of these future-oriented studies, less than 1/3 considered both vulnerability and exposure dynamics. While the number of studies that include dynamics is growing, and while all studies included socio-economic aspects, often only biophysical dynamics was taken into account. We discuss the challenges of assessing socio-economic and spatial dynamics, particularly the poor availability of data and methods. We suggest that future-oriented studies assessing risk dynamics would benefit from larger stakeholder involvement, discussion of the assessment purpose, the use of multiple methods, inclusion of uncertainty/sensitivity analyses and pathway approaches.

Dynamics of Complexity and Accuracy: A Longitudinal Case Study of Advanced Untutored Development

ERIC Educational Resources Information Center

Polat, Brittany; Kim, Youjin

2014-01-01

This longitudinal case study follows a dynamic systems approach to investigate an under-studied research area in second language acquisition, the development of complexity and accuracy for an advanced untutored learner of English. Using the analytical tools of dynamic systems theory (Verspoor et al. 2011) within the framework of complexity,…

Dynamic analysis of multirigid-body system based on the Gauss principle

NASA Astrophysics Data System (ADS)

Lilov, L.; Lorer, M.

Two different approaches can be used for solving the basic dynamic problem in the case of a multirigid body system. The first approach is based on the derivation of the nonlinear equations of motion of the mechanical system, while the second approach is concerned with the direct derivation of the unknown accelerations. Using the Gauss principle, the accelerations can be determined by using the condition for the minimum of a functional. The present investigation is concerned with an algorithm for a dynamical study of a multibody system on the basis of the Gauss principle. The system may contain an arbitrary number of closed loops. The main purpose of the proposed algorithm is the investigation of the dynamics of industrial manipulators, robots, and similar mechanisms.

Development of a Dynamic Energy Budget Modeling Approach to Investigate the Effects of Temperature and Resource Limitation on Mercury Bioaccumulation in Fundulus Heteroclitus

EPA Science Inventory

Dynamic energy budget (DEB) theory provides a generalizable and broadly applicable framework to connect sublethal toxic effects on individuals to changes in population persistence and growth. To explore this approach, we are conducting growth and bioaccumulation studies that cont...

Development of a dynamic energy budget modeling approach to investigate the effects of temperature and resource limitation on mercury bioaccumulation in Fundulus heteroclitus-presentation

EPA Science Inventory

Dynamic energy budget (DEB) theory provides a generalizable and broadly applicable framework to connect sublethal toxic effects on individuals to changes in population survival and growth. To explore this approach, we are conducting growth and bioaccumulation studies that contrib...

Development of a dynamic energy budget modeling approach to investigate the effects of temperature and resource limitation on mercury bioaccumulation in Fundulus heteroclitus.

EPA Science Inventory

Dynamic energy budget (DEB) theory provides a generalizable and broadly applicable framework to connect sublethal toxic effects on individuals to changes in population survival and growth. To explore this approach, we are developing growth and bioaccumulation studies that contrib...

Similarity recognition of online data curves based on dynamic spatial time warping for the estimation of lithium-ion battery capacity

NASA Astrophysics Data System (ADS)

Tao, Laifa; Lu, Chen; Noktehdan, Azadeh

2015-10-01

Battery capacity estimation is a significant recent challenge given the complex physical and chemical processes that occur within batteries and the restrictions on the accessibility of capacity degradation data. In this study, we describe an approach called dynamic spatial time warping, which is used to determine the similarities of two arbitrary curves. Unlike classical dynamic time warping methods, this approach can maintain the invariance of curve similarity to the rotations and translations of curves, which is vital in curve similarity search. Moreover, it utilizes the online charging or discharging data that are easily collected and do not require special assumptions. The accuracy of this approach is verified using NASA battery datasets. Results suggest that the proposed approach provides a highly accurate means of estimating battery capacity at less time cost than traditional dynamic time warping methods do for different individuals and under various operating conditions.

Minimalist approach to perceptual interactions.

PubMed

Lenay, Charles; Stewart, John

2012-01-01

WORK AIMED AT STUDYING SOCIAL COGNITION IN AN INTERACTIONIST PERSPECTIVE OFTEN ENCOUNTERS SUBSTANTIAL THEORETICAL AND METHODOLOGICAL DIFFICULTIES: identifying the significant behavioral variables; recording them without disturbing the interaction; and distinguishing between: (a) the necessary and sufficient contributions of each individual partner for a collective dynamics to emerge; (b) features which derive from this collective dynamics and escape from the control of the individual partners; and (c) the phenomena arising from this collective dynamics which are subsequently appropriated and used by the partners. We propose a minimalist experimental paradigm as a basis for this conceptual discussion: by reducing the sensory inputs to a strict minimum, we force a spatial and temporal deployment of the perceptual activities, which makes it possible to obtain a complete recording and control of the dynamics of interaction. After presenting the principles of this minimalist approach to perception, we describe a series of experiments on two major questions in social cognition: recognizing the presence of another intentional subject; and phenomena of imitation. In both cases, we propose explanatory schema which render an interactionist approach to social cognition clear and explicit. Starting from our earlier work on perceptual crossing we present a new experiment on the mechanisms of reciprocal recognition of the perceptual intentionality of the other subject: the emergent collective dynamics of the perceptual crossing can be appropriated by each subject. We then present an experimental study of opaque imitation (when the subjects cannot see what they themselves are doing). This study makes it possible to characterize what a properly interactionist approach to imitation might be. In conclusion, we draw on these results, to show how an interactionist approach can contribute to a fully social approach to social cognition.

Minimalist Approach to Perceptual Interactions

PubMed Central

Lenay, Charles; Stewart, John

2012-01-01

Work aimed at studying social cognition in an interactionist perspective often encounters substantial theoretical and methodological difficulties: identifying the significant behavioral variables; recording them without disturbing the interaction; and distinguishing between: (a) the necessary and sufficient contributions of each individual partner for a collective dynamics to emerge; (b) features which derive from this collective dynamics and escape from the control of the individual partners; and (c) the phenomena arising from this collective dynamics which are subsequently appropriated and used by the partners. We propose a minimalist experimental paradigm as a basis for this conceptual discussion: by reducing the sensory inputs to a strict minimum, we force a spatial and temporal deployment of the perceptual activities, which makes it possible to obtain a complete recording and control of the dynamics of interaction. After presenting the principles of this minimalist approach to perception, we describe a series of experiments on two major questions in social cognition: recognizing the presence of another intentional subject; and phenomena of imitation. In both cases, we propose explanatory schema which render an interactionist approach to social cognition clear and explicit. Starting from our earlier work on perceptual crossing we present a new experiment on the mechanisms of reciprocal recognition of the perceptual intentionality of the other subject: the emergent collective dynamics of the perceptual crossing can be appropriated by each subject. We then present an experimental study of opaque imitation (when the subjects cannot see what they themselves are doing). This study makes it possible to characterize what a properly interactionist approach to imitation might be. In conclusion, we draw on these results, to show how an interactionist approach can contribute to a fully social approach to social cognition. PMID:22582041

Theoretical approaches for dynamical ordering of biomolecular systems.

PubMed

Okumura, Hisashi; Higashi, Masahiro; Yoshida, Yuichiro; Sato, Hirofumi; Akiyama, Ryo

2018-02-01

Living systems are characterized by the dynamic assembly and disassembly of biomolecules. The dynamical ordering mechanism of these biomolecules has been investigated both experimentally and theoretically. The main theoretical approaches include quantum mechanical (QM) calculation, all-atom (AA) modeling, and coarse-grained (CG) modeling. The selected approach depends on the size of the target system (which differs among electrons, atoms, molecules, and molecular assemblies). These hierarchal approaches can be combined with molecular dynamics (MD) simulation and/or integral equation theories for liquids, which cover all size hierarchies. We review the framework of quantum mechanical/molecular mechanical (QM/MM) calculations, AA MD simulations, CG modeling, and integral equation theories. Applications of these methods to the dynamical ordering of biomolecular systems are also exemplified. The QM/MM calculation enables the study of chemical reactions. The AA MD simulation, which omits the QM calculation, can follow longer time-scale phenomena. By reducing the number of degrees of freedom and the computational cost, CG modeling can follow much longer time-scale phenomena than AA modeling. Integral equation theories for liquids elucidate the liquid structure, for example, whether the liquid follows a radial distribution function. These theoretical approaches can analyze the dynamic behaviors of biomolecular systems. They also provide useful tools for exploring the dynamic ordering systems of biomolecules, such as self-assembly. This article is part of a Special Issue entitled "Biophysical Exploration of Dynamical Ordering of Biomolecular Systems" edited by Dr. Koichi Kato. Copyright © 2017 Elsevier B.V. All rights reserved.

Recent NASA Research on Aerodynamic Modeling of Post-Stall and Spin Dynamics of Large Transport Airplanes

NASA Technical Reports Server (NTRS)

Murch, Austin M.; Foster, John V.

2007-01-01

A simulation study was conducted to investigate aerodynamic modeling methods for prediction of post-stall flight dynamics of large transport airplanes. The research approach involved integrating dynamic wind tunnel data from rotary balance and forced oscillation testing with static wind tunnel data to predict aerodynamic forces and moments during highly dynamic departure and spin motions. Several state-of-the-art aerodynamic modeling methods were evaluated and predicted flight dynamics using these various approaches were compared. Results showed the different modeling methods had varying effects on the predicted flight dynamics and the differences were most significant during uncoordinated maneuvers. Preliminary wind tunnel validation data indicated the potential of the various methods for predicting steady spin motions.

Dynamical Systems in Psychology: Linguistic Approaches

NASA Astrophysics Data System (ADS)

Sulis, William

Major goals for psychoanalysis and psychology are the description, analysis, prediction, and control of behaviour. Natural language has long provided the medium for the formulation of our theoretical understanding of behavior. But with the advent of nonlinear dynamics, a new language has appeared which offers promise to provide a quantitative theory of behaviour. In this paper, some of the limitations of natural and formal languages are discussed. Several approaches to understanding the links between natural and formal languages, as applied to the study of behavior, are discussed. These include symbolic dynamics, Moore's generalized shifts, Crutchfield's ɛ machines, and dynamical automata.

Metabolic modeling of dynamic brain 13C NMR multiplet data: Concepts and simulations with a two-compartment neuronal-glial model

PubMed Central

Shestov, Alexander A.; Valette, Julien; Deelchand, Dinesh K.; Uğurbil, Kâmil; Henry, Pierre-Gilles

2016-01-01

Metabolic modeling of dynamic 13C labeling curves during infusion of 13C-labeled substrates allows quantitative measurements of metabolic rates in vivo. However metabolic modeling studies performed in the brain to date have only modeled time courses of total isotopic enrichment at individual carbon positions (positional enrichments), not taking advantage of the additional dynamic 13C isotopomer information available from fine-structure multiplets in 13C spectra. Here we introduce a new 13C metabolic modeling approach using the concept of bonded cumulative isotopomers, or bonded cumomers. The direct relationship between bonded cumomers and 13C multiplets enables fitting of the dynamic multiplet data. The potential of this new approach is demonstrated using Monte-Carlo simulations with a brain two-compartment neuronal-glial model. The precision of positional and cumomer approaches are compared for two different metabolic models (with and without glutamine dilution) and for different infusion protocols ([1,6-13C2]glucose, [1,2-13C2]acetate, and double infusion [1,6-13C2]glucose + [1,2-13C2]acetate). In all cases, the bonded cumomer approach gives better precision than the positional approach. In addition, of the three different infusion protocols considered here, the double infusion protocol combined with dynamic bonded cumomer modeling appears the most robust for precise determination of all fluxes in the model. The concepts and simulations introduced in the present study set the foundation for taking full advantage of the available dynamic 13C multiplet data in metabolic modeling. PMID:22528840

The dynamic effects of sea level rise on low-gradient coastal landscapes: A review

USGS Publications Warehouse

Passeri, Davina L.; Hagen, Scott C.; Medeiros, Stephen C.; Bilskie, Matthew V.; Alizad, Karim; Wang, Dingbao

2015-01-01

Coastal responses to sea level rise (SLR) include inundation of wetlands, increased shoreline erosion, and increased flooding during storm events. Hydrodynamic parameters such as tidal ranges, tidal prisms, tidal asymmetries, increased flooding depths and inundation extents during storm events respond nonadditively to SLR. Coastal morphology continually adapts toward equilibrium as sea levels rise, inducing changes in the landscape. Marshes may struggle to keep pace with SLR and rely on sediment accumulation and the availability of suitable uplands for migration. Whether hydrodynamic, morphologic, or ecologic, the impacts of SLR are interrelated. To plan for changes under future sea levels, coastal managers need information and data regarding the potential effects of SLR to make informed decisions for managing human and natural communities. This review examines previous studies that have accounted for the dynamic, nonlinear responses of hydrodynamics, coastal morphology, and marsh ecology to SLR by implementing more complex approaches rather than the simplistic “bathtub” approach. These studies provide an improved understanding of the dynamic effects of SLR on coastal environments and contribute to an overall paradigm shift in how coastal scientists and engineers approach modeling the effects of SLR, transitioning away from implementing the “bathtub” approach. However, it is recommended that future studies implement a synergetic approach that integrates the dynamic interactions between physical and ecological environments to better predict the impacts of SLR on coastal systems.

Performance recovery of a class of uncertain non-affine systems with unmodelled dynamics: an indirect dynamic inversion method

NASA Astrophysics Data System (ADS)

Yi, Bowen; Lin, Shuyi; Yang, Bo; Zhang, Weidong

2018-02-01

This paper presents an output feedback indirect dynamic inversion (IDI) approach for a class of uncertain nonaffine systems with input unmodelled dynamics. Compared with previous approaches to achieve performance recovery, the proposed method aims at dealing with a broader class of nonaffine-in-control systems with triangular structure. An IDI state feedback law is designed first, in which less knowledge of the model plant is needed compared to earlier approximate dynamic inversion methods, thus yielding more robust performance. After that, an extended high-gain observer is designed to accomplish the task with output feedback. Finally, we prove that the designed IDI controller is equivalent to an adaptive proportional-integral (PI) controller, with respect to both time response equivalence and robustness equivalence. The conclusion implies that for the studied strict-feedback non-affine systems with unmodelled dynamics, there always exits a PI controller to stabilise the systems. The effectiveness and benefits of the designed approach are verified by three examples.

Observability of nonlinear dynamics: normalized results and a time-series approach.

PubMed

Aguirre, Luis A; Bastos, Saulo B; Alves, Marcela A; Letellier, Christophe

2008-03-01

This paper investigates the observability of nonlinear dynamical systems. Two difficulties associated with previous studies are dealt with. First, a normalized degree observability is defined. This permits the comparison of different systems, which was not generally possible before. Second, a time-series approach is proposed based on omnidirectional nonlinear correlation functions to rank a set of time series of a system in terms of their potential use to reconstruct the original dynamics without requiring the knowledge of the system equations. The two approaches proposed in this paper and a former method were applied to five benchmark systems and an overall agreement of over 92% was found.

Investigating the Structural Impacts of I64T and P311S Mutations in APE1-DNA Complex: A Molecular Dynamics Approach

PubMed Central

Doss, C. George Priya; NagaSundaram, N.

2012-01-01

Background Elucidating the molecular dynamic behavior of Protein-DNA complex upon mutation is crucial in current genomics. Molecular dynamics approach reveals the changes on incorporation of variants that dictate the structure and function of Protein-DNA complexes. Deleterious mutations in APE1 protein modify the physicochemical property of amino acids that affect the protein stability and dynamic behavior. Further, these mutations disrupt the binding sites and prohibit the protein to form complexes with its interacting DNA. Principal Findings In this study, we developed a rapid and cost-effective method to analyze variants in APE1 gene that are associated with disease susceptibility and evaluated their impacts on APE1-DNA complex dynamic behavior. Initially, two different in silico approaches were used to identify deleterious variants in APE1 gene. Deleterious scores that overlap in these approaches were taken in concern and based on it, two nsSNPs with IDs rs61730854 (I64T) and rs1803120 (P311S) were taken further for structural analysis. Significance Different parameters such as RMSD, RMSF, salt bridge, H-bonds and SASA applied in Molecular dynamic study reveals that predicted deleterious variants I64T and P311S alters the structure as well as affect the stability of APE1-DNA interacting functions. This study addresses such new methods for validating functional polymorphisms of human APE1 which is critically involved in causing deficit in repair capacity, which in turn leads to genetic instability and carcinogenesis. PMID:22384055

Dynamic deformation of soft soil media: Experimental studies and mathematical modeling

NASA Astrophysics Data System (ADS)

Balandin, V. V.; Bragov, A. M.; Igumnov, L. A.; Konstantinov, A. Yu.; Kotov, V. L.; Lomunov, A. K.

2015-05-01

A complex experimental-theoretical approach to studying the problem of high-rate strain of soft soil media is presented. This approach combines the following contemporary methods of dynamical tests: the modified Hopkinson-Kolsky method applied tomedium specimens contained in holders and the method of plane wave shock experiments. The following dynamic characteristics of sand soils are obtained: shock adiabatic curves, bulk compressibility curves, and shear resistance curves. The obtained experimental data are used to study the high-rate strain process in the system of a split pressure bar, and the constitutive relations of Grigoryan's mathematical model of soft soil medium are verified by comparing the results of computational and natural test experiments of impact and penetration.

The Impact of a Three-Year Teacher Professional Development Course on Quality of Teaching: Strengths and Limitations of the Dynamic Approach

ERIC Educational Resources Information Center

Kyriakides, L.; Christoforidou, M.; Panayiotou, A.; Creemers, B. P. M.

2017-01-01

The dynamic approach (DA) suggests that professional development should be differentiated to meet teachers' individual needs while engaging participants into systematic and guided critical reflection. Previous experimental studies demonstrated that one-year interventions based on the DA have a positive impact on teacher effectiveness. The study…

"Faces" and Complexities of Continuing Higher Education Units: A Postmodern Approach

ERIC Educational Resources Information Center

Stephenson, Sandria S.

2010-01-01

This study examines the dynamics of continuing higher education units within the sociopolitical context of higher education institutions. A qualitative approach to data collection and analysis was the study's design, while the theoretical frame was a postmodern, symbolic, theoretical approach to organizational studies. Results show that continuing…

A recurrence network approach for the analysis of skin blood flow dynamics in response to loading pressure.

PubMed

Liao, Fuyuan; Jan, Yih-Kuen

2012-06-01

This paper presents a recurrence network approach for the analysis of skin blood flow dynamics in response to loading pressure. Recurrence is a fundamental property of many dynamical systems, which can be explored in phase spaces constructed from observational time series. A visualization tool of recurrence analysis called recurrence plot (RP) has been proved to be highly effective to detect transitions in the dynamics of the system. However, it was found that delay embedding can produce spurious structures in RPs. Network-based concepts have been applied for the analysis of nonlinear time series recently. We demonstrate that time series with different types of dynamics exhibit distinct global clustering coefficients and distributions of local clustering coefficients and that the global clustering coefficient is robust to the embedding parameters. We applied the approach to study skin blood flow oscillations (BFO) response to loading pressure. The results showed that global clustering coefficients of BFO significantly decreased in response to loading pressure (p<0.01). Moreover, surrogate tests indicated that such a decrease was associated with a loss of nonlinearity of BFO. Our results suggest that the recurrence network approach can practically quantify the nonlinear dynamics of BFO.

MODELING MICROBUBBLE DYNAMICS IN BIOMEDICAL APPLICATIONS*

PubMed Central

CHAHINE, Georges L.; HSIAO, Chao-Tsung

2012-01-01

Controlling microbubble dynamics to produce desirable biomedical outcomes when and where necessary and avoid deleterious effects requires advanced knowledge, which can be achieved only through a combination of experimental and numerical/analytical techniques. The present communication presents a multi-physics approach to study the dynamics combining viscous- in-viscid effects, liquid and structure dynamics, and multi bubble interaction. While complex numerical tools are developed and used, the study aims at identifying the key parameters influencing the dynamics, which need to be included in simpler models. PMID:22833696

Quantum wavepacket ab initio molecular dynamics: an approach for computing dynamically averaged vibrational spectra including critical nuclear quantum effects.

PubMed

Sumner, Isaiah; Iyengar, Srinivasan S

2007-10-18

We have introduced a computational methodology to study vibrational spectroscopy in clusters inclusive of critical nuclear quantum effects. This approach is based on the recently developed quantum wavepacket ab initio molecular dynamics method that combines quantum wavepacket dynamics with ab initio molecular dynamics. The computational efficiency of the dynamical procedure is drastically improved (by several orders of magnitude) through the utilization of wavelet-based techniques combined with the previously introduced time-dependent deterministic sampling procedure measure to achieve stable, picosecond length, quantum-classical dynamics of electrons and nuclei in clusters. The dynamical information is employed to construct a novel cumulative flux/velocity correlation function, where the wavepacket flux from the quantized particle is combined with classical nuclear velocities to obtain the vibrational density of states. The approach is demonstrated by computing the vibrational density of states of [Cl-H-Cl]-, inclusive of critical quantum nuclear effects, and our results are in good agreement with experiment. A general hierarchical procedure is also provided, based on electronic structure harmonic frequencies, classical ab initio molecular dynamics, computation of nuclear quantum-mechanical eigenstates, and employing quantum wavepacket ab initio dynamics to understand vibrational spectroscopy in hydrogen-bonded clusters that display large degrees of anharmonicities.

Immunity-Based Optimal Estimation Approach for a New Real Time Group Elevator Dynamic Control Application for Energy and Time Saving

PubMed Central

Baygin, Mehmet; Karakose, Mehmet

2013-01-01

Nowadays, the increasing use of group elevator control systems owing to increasing building heights makes the development of high-performance algorithms necessary in terms of time and energy saving. Although there are many studies in the literature about this topic, they are still not effective enough because they are not able to evaluate all features of system. In this paper, a new approach of immune system-based optimal estimate is studied for dynamic control of group elevator systems. The method is mainly based on estimation of optimal way by optimizing all calls with genetic, immune system and DNA computing algorithms, and it is evaluated with a fuzzy system. The system has a dynamic feature in terms of the situation of calls and the option of the most appropriate algorithm, and it also adaptively works in terms of parameters such as the number of floors and cabins. This new approach which provides both time and energy saving was carried out in real time. The experimental results comparatively demonstrate the effects of method. With dynamic and adaptive control approach in this study carried out, a significant progress on group elevator control systems has been achieved in terms of time and energy efficiency according to traditional methods. PMID:23935433

A dynamic feedback-control toll pricing methodology : a case study on Interstate 95 managed lanes.

DOT National Transportation Integrated Search

2013-06-01

Recently, congestion pricing emerged as a cost-effective and efficient strategy to mitigate the congestion problem on freeways. This study develops a feedback-control based dynamic toll approach to formulate and solve for optimal tolls. The study com...

Dynamic Blowout Risk Analysis Using Loss Functions.

PubMed

Abimbola, Majeed; Khan, Faisal

2018-02-01

Most risk analysis approaches are static; failing to capture evolving conditions. Blowout, the most feared accident during a drilling operation, is a complex and dynamic event. The traditional risk analysis methods are useful in the early design stage of drilling operation while falling short during evolving operational decision making. A new dynamic risk analysis approach is presented to capture evolving situations through dynamic probability and consequence models. The dynamic consequence models, the focus of this study, are developed in terms of loss functions. These models are subsequently integrated with the probability to estimate operational risk, providing a real-time risk analysis. The real-time evolving situation is considered dependent on the changing bottom-hole pressure as drilling progresses. The application of the methodology and models are demonstrated with a case study of an offshore drilling operation evolving to a blowout. © 2017 Society for Risk Analysis.

Neurobiologically Inspired Approaches to Nonlinear Process Control and Modeling

DTIC Science & Technology

1999-12-31

incorporates second messenger reaction kinetics and calcium dynamics to represent the nonlinear dynamics and the crucial role of neuromodulation in local...reflex). The dynamic neuromodulation as a mechanism for the nonlinear attenuation is the novel result of this study. Ear- lier simulations have shown

A centroid molecular dynamics study of liquid para-hydrogen and ortho-deuterium.

PubMed

Hone, Tyler D; Voth, Gregory A

2004-10-01

Centroid molecular dynamics (CMD) is applied to the study of collective and single-particle dynamics in liquid para-hydrogen at two state points and liquid ortho-deuterium at one state point. The CMD results are compared with the results of classical molecular dynamics, quantum mode coupling theory, a maximum entropy analytic continuation approach, pair-product forward- backward semiclassical dynamics, and available experimental results. The self-diffusion constants are in excellent agreement with the experimental measurements for all systems studied. Furthermore, it is shown that the method is able to adequately describe both the single-particle and collective dynamics of quantum liquids. (c) 2004 American Institute of Physics

Peculiarities of Vibration Characteristics of Amorphous Ices

NASA Astrophysics Data System (ADS)

Gets, Kirill V.; Subbotin, Oleg S.; Belosludov, Vladimir R.

2012-03-01

Dynamic properties of low (LDA), high (HDA) and very high (VHDA) density amorphous ices were investigated within the approach based on Lattice Dynamics simulations. In this approach, we assume that the short-range molecular order mainly determines the dynamic and thermodynamic properties of amorphous ices. Simulation cell of 512 water molecules with periodical boundary conditions and disordering allows us to study dynamical properties and dispersion curves in the Brillouin zone of pseudo-crystal. Existence of collective phenomena in amorphous ices which is usual for crystals but anomalous for disordered phase was confirmed in our simulations. Molecule amplitudes of delocalized (collective) as well as localized vibrations have been considered.

Nonperturbative Quantum Nature of the Dislocation–Phonon Interaction

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

Li, Mingda; Ding, Zhiwei; Meng, Qingping

Despite the long history of dislocation–phonon interaction studies, there are many problems that have not been fully resolved during this development. These include an incompatibility between a perturbative approach and the long-range nature of a dislocation, the relation between static and dynamic scattering, and their capability of dealing with thermal transport phenomena for bulk material only. Here in this paper, by utilizing a fully quantized dislocation field, which we called a “dislon”, a phonon interacting with a dislocation is renormalized as a quasi-phonon, with shifted quasi-phonon energy, and accompanied by a finite quasi-phonon lifetime, which are reducible to classical results.more » A series of outstanding legacy issues including those above can be directly explained within this unified phonon renormalization approach. For instance, a renormalized phonon naturally resolves the decade-long debate between dynamic and static dislocation–phonon scattering approaches, as two limiting cases. In particular, at nanoscale, both the dynamic and static approaches break down, while the present renormalization approach remains valid by capturing the size effect, showing good agreement with lattice dynamics simulations.« less

Nonperturbative Quantum Nature of the Dislocation–Phonon Interaction

DOE PAGES

Li, Mingda; Ding, Zhiwei; Meng, Qingping; ...

2017-01-31

Despite the long history of dislocation–phonon interaction studies, there are many problems that have not been fully resolved during this development. These include an incompatibility between a perturbative approach and the long-range nature of a dislocation, the relation between static and dynamic scattering, and their capability of dealing with thermal transport phenomena for bulk material only. Here in this paper, by utilizing a fully quantized dislocation field, which we called a “dislon”, a phonon interacting with a dislocation is renormalized as a quasi-phonon, with shifted quasi-phonon energy, and accompanied by a finite quasi-phonon lifetime, which are reducible to classical results.more » A series of outstanding legacy issues including those above can be directly explained within this unified phonon renormalization approach. For instance, a renormalized phonon naturally resolves the decade-long debate between dynamic and static dislocation–phonon scattering approaches, as two limiting cases. In particular, at nanoscale, both the dynamic and static approaches break down, while the present renormalization approach remains valid by capturing the size effect, showing good agreement with lattice dynamics simulations.« less

Decoding brain cancer dynamics: a quantitative histogram-based approach using temporal MRI

NASA Astrophysics Data System (ADS)

Zhou, Mu; Hall, Lawrence O.; Goldgof, Dmitry B.; Russo, Robin; Gillies, Robert J.; Gatenby, Robert A.

2015-03-01

Brain tumor heterogeneity remains a challenge for probing brain cancer evolutionary dynamics. In light of evolution, it is a priority to inspect the cancer system from a time-domain perspective since it explicitly tracks the dynamics of cancer variations. In this paper, we study the problem of exploring brain tumor heterogeneity from temporal clinical magnetic resonance imaging (MRI) data. Our goal is to discover evidence-based knowledge from such temporal imaging data, where multiple clinical MRI scans from Glioblastoma multiforme (GBM) patients are generated during therapy. In particular, we propose a quantitative histogram-based approach that builds a prediction model to measure the difference in histograms obtained from pre- and post-treatment. The study could significantly assist radiologists by providing a metric to identify distinctive patterns within each tumor, which is crucial for the goal of providing patient-specific treatments. We examine the proposed approach for a practical application - clinical survival group prediction. Experimental results show that our approach achieved 90.91% accuracy.

An experimental study of nonlinear dynamic system identification

NASA Technical Reports Server (NTRS)

Stry, Greselda I.; Mook, D. Joseph

1990-01-01

A technique for robust identification of nonlinear dynamic systems is developed and illustrated using both simulations and analog experiments. The technique is based on the Minimum Model Error optimal estimation approach. A detailed literature review is included in which fundamental differences between the current approach and previous work is described. The most significant feature of the current work is the ability to identify nonlinear dynamic systems without prior assumptions regarding the form of the nonlinearities, in constrast to existing nonlinear identification approaches which usually require detailed assumptions of the nonlinearities. The example illustrations indicate that the method is robust with respect to prior ignorance of the model, and with respect to measurement noise, measurement frequency, and measurement record length.

GPU accelerated dynamic functional connectivity analysis for functional MRI data.

PubMed

Akgün, Devrim; Sakoğlu, Ünal; Esquivel, Johnny; Adinoff, Bryon; Mete, Mutlu

2015-07-01

Recent advances in multi-core processors and graphics card based computational technologies have paved the way for an improved and dynamic utilization of parallel computing techniques. Numerous applications have been implemented for the acceleration of computationally-intensive problems in various computational science fields including bioinformatics, in which big data problems are prevalent. In neuroimaging, dynamic functional connectivity (DFC) analysis is a computationally demanding method used to investigate dynamic functional interactions among different brain regions or networks identified with functional magnetic resonance imaging (fMRI) data. In this study, we implemented and analyzed a parallel DFC algorithm based on thread-based and block-based approaches. The thread-based approach was designed to parallelize DFC computations and was implemented in both Open Multi-Processing (OpenMP) and Compute Unified Device Architecture (CUDA) programming platforms. Another approach developed in this study to better utilize CUDA architecture is the block-based approach, where parallelization involves smaller parts of fMRI time-courses obtained by sliding-windows. Experimental results showed that the proposed parallel design solutions enabled by the GPUs significantly reduce the computation time for DFC analysis. Multicore implementation using OpenMP on 8-core processor provides up to 7.7× speed-up. GPU implementation using CUDA yielded substantial accelerations ranging from 18.5× to 157× speed-up once thread-based and block-based approaches were combined in the analysis. Proposed parallel programming solutions showed that multi-core processor and CUDA-supported GPU implementations accelerated the DFC analyses significantly. Developed algorithms make the DFC analyses more practical for multi-subject studies with more dynamic analyses. Copyright © 2015 Elsevier Ltd. All rights reserved.

Evaluating Dynamic Bivariate Correlations in Resting-state fMRI: A comparison study and a new approach

PubMed Central

Lindquist, Martin A.; Xu, Yuting; Nebel, Mary Beth; Caffo, Brain S.

2014-01-01

To date, most functional Magnetic Resonance Imaging (fMRI) studies have assumed that the functional connectivity (FC) between time series from distinct brain regions is constant across time. However, recently, there has been increased interest in quantifying possible dynamic changes in FC during fMRI experiments, as it is thought this may provide insight into the fundamental workings of brain networks. In this work we focus on the specific problem of estimating the dynamic behavior of pair-wise correlations between time courses extracted from two different regions of the brain. We critique the commonly used sliding-windows technique, and discuss some alternative methods used to model volatility in the finance literature that could also prove useful in the neuroimaging setting. In particular, we focus on the Dynamic Conditional Correlation (DCC) model, which provides a model-based approach towards estimating dynamic correlations. We investigate the properties of several techniques in a series of simulation studies and find that DCC achieves the best overall balance between sensitivity and specificity in detecting dynamic changes in correlations. We also investigate its scalability beyond the bivariate case to demonstrate its utility for studying dynamic correlations between more than two brain regions. Finally, we illustrate its performance in an application to test-retest resting state fMRI data. PMID:24993894

Insights into nuclear dynamics using live-cell imaging approaches.

PubMed

Bigley, Rachel B; Payumo, Alexander Y; Alexander, Jeffrey M; Huang, Guo N

2017-03-01

The nucleus contains the genetic blueprint of the cell and myriad interactions within this subcellular structure are required for gene regulation. In the current scientific era, characterization of these gene regulatory networks through biochemical techniques coupled with systems-wide 'omic' approaches has become commonplace. However, these strategies are limited because they represent a mere snapshot of the cellular state. To obtain a holistic understanding of nuclear dynamics, relevant molecules must be studied in their native contexts in living systems. Live-cell imaging approaches are capable of providing quantitative assessment of the dynamics of gene regulatory interactions within the nucleus. We survey recent insights into what live-cell imaging approaches have provided the field of nuclear dynamics. In this review, we focus on interactions of DNA with other DNA loci, proteins, RNA, and the nuclear envelope. WIREs Syst Biol Med 2017, 9:e1372. doi: 10.1002/wsbm.1372 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.

LOGISTIC NETWORK REGRESSION FOR SCALABLE ANALYSIS OF NETWORKS WITH JOINT EDGE/VERTEX DYNAMICS

PubMed Central

Almquist, Zack W.; Butts, Carter T.

2015-01-01

Change in group size and composition has long been an important area of research in the social sciences. Similarly, interest in interaction dynamics has a long history in sociology and social psychology. However, the effects of endogenous group change on interaction dynamics are a surprisingly understudied area. One way to explore these relationships is through social network models. Network dynamics may be viewed as a process of change in the edge structure of a network, in the vertex set on which edges are defined, or in both simultaneously. Although early studies of such processes were primarily descriptive, recent work on this topic has increasingly turned to formal statistical models. Although showing great promise, many of these modern dynamic models are computationally intensive and scale very poorly in the size of the network under study and/or the number of time points considered. Likewise, currently used models focus on edge dynamics, with little support for endogenously changing vertex sets. Here, the authors show how an existing approach based on logistic network regression can be extended to serve as a highly scalable framework for modeling large networks with dynamic vertex sets. The authors place this approach within a general dynamic exponential family (exponential-family random graph modeling) context, clarifying the assumptions underlying the framework (and providing a clear path for extensions), and they show how model assessment methods for cross-sectional networks can be extended to the dynamic case. Finally, the authors illustrate this approach on a classic data set involving interactions among windsurfers on a California beach. PMID:26120218

LOGISTIC NETWORK REGRESSION FOR SCALABLE ANALYSIS OF NETWORKS WITH JOINT EDGE/VERTEX DYNAMICS.

PubMed

Almquist, Zack W; Butts, Carter T

2014-08-01

Change in group size and composition has long been an important area of research in the social sciences. Similarly, interest in interaction dynamics has a long history in sociology and social psychology. However, the effects of endogenous group change on interaction dynamics are a surprisingly understudied area. One way to explore these relationships is through social network models. Network dynamics may be viewed as a process of change in the edge structure of a network, in the vertex set on which edges are defined, or in both simultaneously. Although early studies of such processes were primarily descriptive, recent work on this topic has increasingly turned to formal statistical models. Although showing great promise, many of these modern dynamic models are computationally intensive and scale very poorly in the size of the network under study and/or the number of time points considered. Likewise, currently used models focus on edge dynamics, with little support for endogenously changing vertex sets. Here, the authors show how an existing approach based on logistic network regression can be extended to serve as a highly scalable framework for modeling large networks with dynamic vertex sets. The authors place this approach within a general dynamic exponential family (exponential-family random graph modeling) context, clarifying the assumptions underlying the framework (and providing a clear path for extensions), and they show how model assessment methods for cross-sectional networks can be extended to the dynamic case. Finally, the authors illustrate this approach on a classic data set involving interactions among windsurfers on a California beach.

Contemplative Neuroscience as an Approach to Volitional Consciousness

NASA Astrophysics Data System (ADS)

Thompson, Evan

This chapter presents a methodological approach to volitional consciousness for cognitive neuroscience based on studying the voluntary self-generation and self-regulation of mental states in meditation. Called contemplative neuroscience, this approach views attention, awareness, and emotion regulation as flexible and trainable skills, and works with experimental participants who have undergone training in contemplative practices designed to hone these skills. Drawing from research on the dynamical neural correlates of contemplative mental states and theories of large-scale neural coordination dynamics, I argue for the importance of global system causation in brain activity and present an "interventionist" approach to intentional causation.

Mathematical modeling and computational prediction of cancer drug resistance.

PubMed

Sun, Xiaoqiang; Hu, Bin

2017-06-23

Diverse forms of resistance to anticancer drugs can lead to the failure of chemotherapy. Drug resistance is one of the most intractable issues for successfully treating cancer in current clinical practice. Effective clinical approaches that could counter drug resistance by restoring the sensitivity of tumors to the targeted agents are urgently needed. As numerous experimental results on resistance mechanisms have been obtained and a mass of high-throughput data has been accumulated, mathematical modeling and computational predictions using systematic and quantitative approaches have become increasingly important, as they can potentially provide deeper insights into resistance mechanisms, generate novel hypotheses or suggest promising treatment strategies for future testing. In this review, we first briefly summarize the current progress of experimentally revealed resistance mechanisms of targeted therapy, including genetic mechanisms, epigenetic mechanisms, posttranslational mechanisms, cellular mechanisms, microenvironmental mechanisms and pharmacokinetic mechanisms. Subsequently, we list several currently available databases and Web-based tools related to drug sensitivity and resistance. Then, we focus primarily on introducing some state-of-the-art computational methods used in drug resistance studies, including mechanism-based mathematical modeling approaches (e.g. molecular dynamics simulation, kinetic model of molecular networks, ordinary differential equation model of cellular dynamics, stochastic model, partial differential equation model, agent-based model, pharmacokinetic-pharmacodynamic model, etc.) and data-driven prediction methods (e.g. omics data-based conventional screening approach for node biomarkers, static network approach for edge biomarkers and module biomarkers, dynamic network approach for dynamic network biomarkers and dynamic module network biomarkers, etc.). Finally, we discuss several further questions and future directions for the use of computational methods for studying drug resistance, including inferring drug-induced signaling networks, multiscale modeling, drug combinations and precision medicine. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A Force Balanced Fragmentation Method for ab Initio Molecular Dynamic Simulation of Protein.

PubMed

Xu, Mingyuan; Zhu, Tong; Zhang, John Z H

2018-01-01

A force balanced generalized molecular fractionation with conjugate caps (FB-GMFCC) method is proposed for ab initio molecular dynamic simulation of proteins. In this approach, the energy of the protein is computed by a linear combination of the QM energies of individual residues and molecular fragments that account for the two-body interaction of hydrogen bond between backbone peptides. The atomic forces on the caped H atoms were corrected to conserve the total force of the protein. Using this approach, ab initio molecular dynamic simulation of an Ace-(ALA) 9 -NME linear peptide showed the conservation of the total energy of the system throughout the simulation. Further a more robust 110 ps ab initio molecular dynamic simulation was performed for a protein with 56 residues and 862 atoms in explicit water. Compared with the classical force field, the ab initio molecular dynamic simulations gave better description of the geometry of peptide bonds. Although further development is still needed, the current approach is highly efficient, trivially parallel, and can be applied to ab initio molecular dynamic simulation study of large proteins.

Pattern Recognition Approaches for Breast Cancer DCE-MRI Classification: A Systematic Review.

PubMed

Fusco, Roberta; Sansone, Mario; Filice, Salvatore; Carone, Guglielmo; Amato, Daniela Maria; Sansone, Carlo; Petrillo, Antonella

2016-01-01

We performed a systematic review of several pattern analysis approaches for classifying breast lesions using dynamic, morphological, and textural features in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). Several machine learning approaches, namely artificial neural networks (ANN), support vector machines (SVM), linear discriminant analysis (LDA), tree-based classifiers (TC), and Bayesian classifiers (BC), and features used for classification are described. The findings of a systematic review of 26 studies are presented. The sensitivity and specificity are respectively 91 and 83 % for ANN, 85 and 82 % for SVM, 96 and 85 % for LDA, 92 and 87 % for TC, and 82 and 85 % for BC. The sensitivity and specificity are respectively 82 and 74 % for dynamic features, 93 and 60 % for morphological features, 88 and 81 % for textural features, 95 and 86 % for a combination of dynamic and morphological features, and 88 and 84 % for a combination of dynamic, morphological, and other features. LDA and TC have the best performance. A combination of dynamic and morphological features gives the best performance.

A nonlinear dynamics approach for incorporating wind-speed patterns into wind-power project evaluation.

PubMed

Huffaker, Ray; Bittelli, Marco

2015-01-01

Wind-energy production may be expanded beyond regions with high-average wind speeds (such as the Midwest U.S.A.) to sites with lower-average speeds (such as the Southeast U.S.A.) by locating favorable regional matches between natural wind-speed and energy-demand patterns. A critical component of wind-power evaluation is to incorporate wind-speed dynamics reflecting documented diurnal and seasonal behavioral patterns. Conventional probabilistic approaches remove patterns from wind-speed data. These patterns must be restored synthetically before they can be matched with energy-demand patterns. How to accurately restore wind-speed patterns is a vexing problem spurring an expanding line of papers. We propose a paradigm shift in wind power evaluation that employs signal-detection and nonlinear-dynamics techniques to empirically diagnose whether synthetic pattern restoration can be avoided altogether. If the complex behavior of observed wind-speed records is due to nonlinear, low-dimensional, and deterministic system dynamics, then nonlinear dynamics techniques can reconstruct wind-speed dynamics from observed wind-speed data without recourse to conventional probabilistic approaches. In the first study of its kind, we test a nonlinear dynamics approach in an application to Sugarland Wind-the first utility-scale wind project proposed in Florida, USA. We find empirical evidence of a low-dimensional and nonlinear wind-speed attractor characterized by strong temporal patterns that match up well with regular daily and seasonal electricity demand patterns.

Coarse-Grained Clustering Dynamics of Heterogeneously Coupled Neurons.

PubMed

Moon, Sung Joon; Cook, Katherine A; Rajendran, Karthikeyan; Kevrekidis, Ioannis G; Cisternas, Jaime; Laing, Carlo R

2015-12-01

The formation of oscillating phase clusters in a network of identical Hodgkin-Huxley neurons is studied, along with their dynamic behavior. The neurons are synaptically coupled in an all-to-all manner, yet the synaptic coupling characteristic time is heterogeneous across the connections. In a network of N neurons where this heterogeneity is characterized by a prescribed random variable, the oscillatory single-cluster state can transition-through [Formula: see text] (possibly perturbed) period-doubling and subsequent bifurcations-to a variety of multiple-cluster states. The clustering dynamic behavior is computationally studied both at the detailed and the coarse-grained levels, and a numerical approach that can enable studying the coarse-grained dynamics in a network of arbitrarily large size is suggested. Among a number of cluster states formed, double clusters, composed of nearly equal sub-network sizes are seen to be stable; interestingly, the heterogeneity parameter in each of the double-cluster components tends to be consistent with the random variable over the entire network: Given a double-cluster state, permuting the dynamical variables of the neurons can lead to a combinatorially large number of different, yet similar "fine" states that appear practically identical at the coarse-grained level. For weak heterogeneity we find that correlations rapidly develop, within each cluster, between the neuron's "identity" (its own value of the heterogeneity parameter) and its dynamical state. For single- and double-cluster states we demonstrate an effective coarse-graining approach that uses the Polynomial Chaos expansion to succinctly describe the dynamics by these quickly established "identity-state" correlations. This coarse-graining approach is utilized, within the equation-free framework, to perform efficient computations of the neuron ensemble dynamics.

Quantum Fragment Based ab Initio Molecular Dynamics for Proteins.

PubMed

Liu, Jinfeng; Zhu, Tong; Wang, Xianwei; He, Xiao; Zhang, John Z H

2015-12-08

Developing ab initio molecular dynamics (AIMD) methods for practical application in protein dynamics is of significant interest. Due to the large size of biomolecules, applying standard quantum chemical methods to compute energies for dynamic simulation is computationally prohibitive. In this work, a fragment based ab initio molecular dynamics approach is presented for practical application in protein dynamics study. In this approach, the energy and forces of the protein are calculated by a recently developed electrostatically embedded generalized molecular fractionation with conjugate caps (EE-GMFCC) method. For simulation in explicit solvent, mechanical embedding is introduced to treat protein interaction with explicit water molecules. This AIMD approach has been applied to MD simulations of a small benchmark protein Trpcage (with 20 residues and 304 atoms) in both the gas phase and in solution. Comparison to the simulation result using the AMBER force field shows that the AIMD gives a more stable protein structure in the simulation, indicating that quantum chemical energy is more reliable. Importantly, the present fragment-based AIMD simulation captures quantum effects including electrostatic polarization and charge transfer that are missing in standard classical MD simulations. The current approach is linear-scaling, trivially parallel, and applicable to performing the AIMD simulation of proteins with a large size.

Considering time in LCA: dynamic LCA and its application to global warming impact assessments.

PubMed

Levasseur, Annie; Lesage, Pascal; Margni, Manuele; Deschênes, Louise; Samson, Réjean

2010-04-15

The lack of temporal information is an important limitation of life cycle assessment (LCA). A dynamic LCA approach is proposed to improve the accuracy of LCA by addressing the inconsistency of temporal assessment. This approach consists of first computing a dynamic life cycle inventory (LCI), considering the temporal profile of emissions. Then, time-dependent characterization factors are calculated to assess the dynamic LCI in real-time impact scores for any given time horizon. Although generally applicable to any impact category, this approach is developed here for global warming, based on the radiative forcing concept. This case study demonstrates that the use of global warming potentials for a given time horizon to characterize greenhouse gas emissions leads to an inconsistency between the time frame chosen for the analysis and the time period covered by the LCA results. Dynamic LCA is applied to the US EPA LCA on renewable fuels, which compares the life cycle greenhouse gas emissions of different biofuels with fossil fuels including land-use change emissions. The comparison of the results obtained with both traditional and dynamic LCA approaches shows that the difference can be important enough to change the conclusions on whether or not a biofuel meets some given global warming reduction targets.

Dynamics modelling and Hybrid Suppression Control of space robots performing cooperative object manipulation

NASA Astrophysics Data System (ADS)

Zarafshan, P.; Moosavian, S. Ali A.

2013-10-01

Dynamics modelling and control of multi-body space robotic systems composed of rigid and flexible elements is elaborated here. Control of such systems is highly complicated due to severe under-actuated condition caused by flexible elements, and an inherent uneven nonlinear dynamics. Therefore, developing a compact dynamics model with the requirement of limited computations is extremely useful for controller design, also to develop simulation studies in support of design improvement, and finally for practical implementations. In this paper, the Rigid-Flexible Interactive dynamics Modelling (RFIM) approach is introduced as a combination of Lagrange and Newton-Euler methods, in which the motion equations of rigid and flexible members are separately developed in an explicit closed form. These equations are then assembled and solved simultaneously at each time step by considering the mutual interaction and constraint forces. The proposed approach yields a compact model rather than common accumulation approach that leads to a massive set of equations in which the dynamics of flexible elements is united with the dynamics equations of rigid members. To reveal such merits of this new approach, a Hybrid Suppression Control (HSC) for a cooperative object manipulation task will be proposed, and applied to usual space systems. A Wheeled Mobile Robotic (WMR) system with flexible appendages as a typical space rover is considered which contains a rigid main body equipped with two manipulating arms and two flexible solar panels, and next a Space Free Flying Robotic system (SFFR) with flexible members is studied. Modelling verification of these complicated systems is vigorously performed using ANSYS and ADAMS programs, while the limited computations of RFIM approach provides an efficient tool for the proposed controller design. Furthermore, it will be shown that the vibrations of the flexible solar panels results in disturbing forces on the base which may produce undesirable errors and perturb the object manipulation task. So, it is shown that these effects can be significantly eliminated by the proposed Hybrid Suppression Control algorithm.

Studying Dynamics by Magic-Angle Spinning Solid-State NMR Spectroscopy: Principles and Applications to Biomolecules

PubMed Central

Schanda, Paul; Ernst, Matthias

2016-01-01

Magic-angle spinning solid-state NMR spectroscopy is an important technique to study molecular structure, dynamics and interactions, and is rapidly gaining importance in biomolecular sciences. Here we provide an overview of experimental approaches to study molecular dynamics by MAS solid-state NMR, with an emphasis on the underlying theoretical concepts and differences of MAS solid-state NMR compared to solution-state NMR. The theoretical foundations of nuclear spin relaxation are revisited, focusing on the particularities of spin relaxation in solid samples under magic-angle spinning. We discuss the range of validity of Redfield theory, as well as the inherent multi-exponential behavior of relaxation in solids. Experimental challenges for measuring relaxation parameters in MAS solid-state NMR and a few recently proposed relaxation approaches are discussed, which provide information about time scales and amplitudes of motions ranging from picoseconds to milliseconds. We also discuss the theoretical basis and experimental measurements of anisotropic interactions (chemical-shift anisotropies, dipolar and quadrupolar couplings), which give direct information about the amplitude of motions. The potential of combining relaxation data with such measurements of dynamically-averaged anisotropic interactions is discussed. Although the focus of this review is on the theoretical foundations of dynamics studies rather than their application, we close by discussing a small number of recent dynamics studies, where the dynamic properties of proteins in crystals are compared to those in solution. PMID:27110043

Comparison of candidate solar array maximum power utilization approaches. [for spacecraft propulsion

NASA Technical Reports Server (NTRS)

Costogue, E. N.; Lindena, S.

1976-01-01

A study was made of five potential approaches that can be utilized to detect the maximum power point of a solar array while sustaining operations at or near maximum power and without endangering stability or causing array voltage collapse. The approaches studied included: (1) dynamic impedance comparator, (2) reference array measurement, (3) onset of solar array voltage collapse detection, (4) parallel tracker, and (5) direct measurement. The study analyzed the feasibility and adaptability of these approaches to a future solar electric propulsion (SEP) mission, and, specifically, to a comet rendezvous mission. Such missions presented the most challenging requirements to a spacecraft power subsystem in terms of power management over large solar intensity ranges of 1.0 to 3.5 AU. The dynamic impedance approach was found to have the highest figure of merit, and the reference array approach followed closely behind. The results are applicable to terrestrial solar power systems as well as to other than SEP space missions.

Re-animation of muscle flaps for improved function in dynamic myoplasty.

PubMed

Stremel, R W; Zonnevijlle, E D

2001-01-01

The authors report on a series of experiments designed to produce a skeletal muscle contraction functional for dynamic myoplasties. Conventional stimulation techniques recruit all or most of the muscle fibers simultaneously and with maximal strength. This approach has limitations in free dynamic muscle flap transfers that require the muscle to contract immediately after transfer and before re-innervation. Sequential stimulation of segments of the transferred muscle provides a means of producing non-fatiguing contractions of the muscle in the presence or absence of innervation. The muscles studied were the canine gracilis, and all experiments were acute studies in anesthetized animals. Comparison of conventional and sequential segmental neuromuscular stimulation revealed an increase in muscle fatigue resistance and muscle blood flow with the new approach. This approach offers the opportunity for development of physiologically animated tissue and broadening the abilities of reconstructive surgeons in the repair of functional defects. Copyright 2001 Wiley-Liss, Inc.

A dynamical-systems approach for computing ice-affected streamflow

USGS Publications Warehouse

Holtschlag, David J.

1996-01-01

A dynamical-systems approach was developed and evaluated for computing ice-affected streamflow. The approach provides for dynamic simulation and parameter estimation of site-specific equations relating ice effects to routinely measured environmental variables. Comparison indicates that results from the dynamical-systems approach ranked higher than results from 11 analytical methods previously investigated on the basis of accuracy and feasibility criteria. Additional research will likely lead to further improvements in the approach.

In vivo imaging of emerging endocrine cells reveals a requirement for PI3K-regulated motility in pancreatic islet morphogenesis

PubMed Central

Freudenblum, Julia; Iglesias, José A.; Hermann, Martin; Walsen, Tanja; Wilfinger, Armin; Meyer, Dirk

2018-01-01

ABSTRACT The three-dimensional architecture of the pancreatic islet is integral to beta cell function, but the process of islet formation remains poorly understood due to the difficulties of imaging internal organs with cellular resolution. Within transparent zebrafish larvae, the developing pancreas is relatively superficial and thus amenable to live imaging approaches. We performed in vivo time-lapse and longitudinal imaging studies to follow islet development, visualizing both naturally occurring islet cells and cells arising with an accelerated timecourse following an induction approach. These studies revealed previously unappreciated fine dynamic protrusions projecting between neighboring and distant endocrine cells. Using pharmacological compound and toxin interference approaches, and single-cell analysis of morphology and cell dynamics, we determined that endocrine cell motility is regulated by phosphoinositide 3-kinase (PI3K) and G-protein-coupled receptor (GPCR) signaling. Linking cell dynamics to islet formation, perturbation of protrusion formation disrupted endocrine cell coalescence, and correlated with decreased islet cell differentiation. These studies identified novel cell behaviors contributing to islet morphogenesis, and suggest a model in which dynamic exploratory filopodia establish cell-cell contacts that subsequently promote cell clustering. PMID:29386244

A synergic simulation-optimization approach for analyzing biomolecular dynamics in living organisms.

PubMed

Sadegh Zadeh, Kouroush

2011-01-01

A synergic duo simulation-optimization approach was developed and implemented to study protein-substrate dynamics and binding kinetics in living organisms. The forward problem is a system of several coupled nonlinear partial differential equations which, with a given set of kinetics and diffusion parameters, can provide not only the commonly used bleached area-averaged time series in fluorescence microscopy experiments but more informative full biomolecular/drug space-time series and can be successfully used to study dynamics of both Dirac and Gaussian fluorescence-labeled biomacromolecules in vivo. The incomplete Cholesky preconditioner was coupled with the finite difference discretization scheme and an adaptive time-stepping strategy to solve the forward problem. The proposed approach was validated with analytical as well as reference solutions and used to simulate dynamics of GFP-tagged glucocorticoid receptor (GFP-GR) in mouse cancer cell during a fluorescence recovery after photobleaching experiment. Model analysis indicates that the commonly practiced bleach spot-averaged time series is not an efficient approach to extract physiological information from the fluorescence microscopy protocols. It was recommended that experimental biophysicists should use full space-time series, resulting from experimental protocols, to study dynamics of biomacromolecules and drugs in living organisms. It was also concluded that in parameterization of biological mass transfer processes, setting the norm of the gradient of the penalty function at the solution to zero is not an efficient stopping rule to end the inverse algorithm. Theoreticians should use multi-criteria stopping rules to quantify model parameters by optimization. Copyright © 2010 Elsevier Ltd. All rights reserved.

a System Dynamics Model to Study the Importance of Infrastructure Facilities on Quality of Primary Education System in Developing Countries

NASA Astrophysics Data System (ADS)

Pedamallu, Chandra Sekhar; Ozdamar, Linet; Weber, Gerhard-Wilhelm; Kropat, Erik

2010-06-01

The system dynamics approach is a holistic way of solving problems in real-time scenarios. This is a powerful methodology and computer simulation modeling technique for framing, analyzing, and discussing complex issues and problems. System dynamics modeling and simulation is often the background of a systemic thinking approach and has become a management and organizational development paradigm. This paper proposes a system dynamics approach for study the importance of infrastructure facilities on quality of primary education system in developing nations. The model is proposed to be built using the Cross Impact Analysis (CIA) method of relating entities and attributes relevant to the primary education system in any given community. We offer a survey to build the cross-impact correlation matrix and, hence, to better understand the primary education system and importance of infrastructural facilities on quality of primary education. The resulting model enables us to predict the effects of infrastructural facilities on the access of primary education by the community. This may support policy makers to take more effective actions in campaigns.

A Practical Approach to Implementing Real-Time Semantics

NASA Technical Reports Server (NTRS)

Luettgen, Gerald; Bhat, Girish; Cleaveland, Rance

1999-01-01

This paper investigates implementations of process algebras which are suitable for modeling concurrent real-time systems. It suggests an approach for efficiently implementing real-time semantics using dynamic priorities. For this purpose a proces algebra with dynamic priority is defined, whose semantics corresponds one-to-one to traditional real-time semantics. The advantage of the dynamic-priority approach is that it drastically reduces the state-space sizes of the systems in question while preserving all properties of their functional and real-time behavior. The utility of the technique is demonstrated by a case study which deals with the formal modeling and verification of the SCSI-2 bus-protocol. The case study is carried out in the Concurrency Workbench of North Carolina, an automated verification tool in which the process algebra with dynamic priority is implemented. It turns out that the state space of the bus-protocol model is about an order of magnitude smaller than the one resulting from real-time semantics. The accuracy of the model is proved by applying model checking for verifying several mandatory properties of the bus protocol.

Using ultrashort terahertz pulses to directly probe spin dynamics in insulating antiferromagnets

NASA Astrophysics Data System (ADS)

Bowlan, P.; Trugman, S. A.; Yarotski, D. A.; Taylor, A. J.; Prasankumar, R. P.

2018-05-01

Terahertz pulses are a direct and general probe of ultrafast spin dynamics in insulating antiferromagnets (AFM). This is shown by using optical-pump, THz-probe spectroscopy to directly track AFM spin dynamics in the hexagonal multiferroic HoMnO3 and the orthorhombic multiferroic TbMnO3. Our studies show that despite the different structural and spin orders in these materials, THz pulses can unambiguously resolve spin dynamics after optical photoexcitation. We believe that this approach is quite general and can be applied to a broad range of materials with different AFM spin alignments, providing a novel non-contact approach for probing AFM order with femtosecond temporal resolution.

Relaxation dynamics of a multihierarchical polymer network

NASA Astrophysics Data System (ADS)

Jurjiu, Aurel; Biter, Teodor Lucian; Turcu, Flaviu

2017-01-01

In this work, we study the relaxation dynamics of a multihierarchical polymer network built by replicating the Vicsek fractal in dendrimer shape. The relaxation dynamics is investigated in the framework of the generalized Gaussian structure model by employing both Rouse and Zimm approaches. In the Rouse-type approach, we show the iterative procedure whereby the whole eigenvalue spectrum of the connectivity matrix of the multihierarchical structure can be obtained. Remarkably, the general picture that emerges from both approaches, even though we have a mixed growth algorithm, is that the obtained multihierarchical structure preserves the individual relaxation behaviors of its components. The theoretical findings with respect to the splitting of the intermediate domain of the relaxation quantities are well supported by experimental results.

Three-Dimensional Water and Carbon Cycle Modeling at High Spatial-Temporal Resolutions

NASA Astrophysics Data System (ADS)

Liao, C.; Zhuang, Q.

2017-12-01

Terrestrial ecosystems in cryosphere are very sensitive to the global climate change due to the presence of snow covers, mountain glaciers and permafrost, especially when the increase in near surface air temperature is almost twice as large as the global average. However, few studies have investigated the water and carbon cycle dynamics using process-based hydrological and biogeochemistry modeling approach. In this study, we used three-dimensional modeling approach at high spatial-temporal resolutions to investigate the water and carbon cycle dynamics for the Tanana Flats Basin in interior Alaska with emphases on dissolved organic carbon (DOC) dynamics. The results have shown that: (1) lateral flow plays an important role in water and carbon cycle, especially in dissolved organic carbon (DOC) dynamics. (2) approximately 2.0 × 104 kg C yr-1 DOC is exported to the hydrological networks and it compromises 1% and 0.01% of total annual gross primary production (GPP) and total organic carbon stored in soil, respectively. This study has established an operational and flexible framework to investigate and predict the water and carbon cycle dynamics under the changing climate.

Non-equilibrium coherence dynamics in one-dimensional Bose gases.

PubMed

Hofferberth, S; Lesanovsky, I; Fischer, B; Schumm, T; Schmiedmayer, J

2007-09-20

Low-dimensional systems provide beautiful examples of many-body quantum physics. For one-dimensional (1D) systems, the Luttinger liquid approach provides insight into universal properties. Much is known of the equilibrium state, both in the weakly and strongly interacting regimes. However, it remains a challenge to probe the dynamics by which this equilibrium state is reached. Here we present a direct experimental study of the coherence dynamics in both isolated and coupled degenerate 1D Bose gases. Dynamic splitting is used to create two 1D systems in a phase coherent state. The time evolution of the coherence is revealed through local phase shifts of the subsequently observed interference patterns. Completely isolated 1D Bose gases are observed to exhibit universal sub-exponential coherence decay, in excellent agreement with recent predictions. For two coupled 1D Bose gases, the coherence factor is observed to approach a non-zero equilibrium value, as predicted by a Bogoliubov approach. This coupled-system decay to finite coherence is the matter wave equivalent of phase-locking two lasers by injection. The non-equilibrium dynamics of superfluids has an important role in a wide range of physical systems, such as superconductors, quantum Hall systems, superfluid helium and spin systems. Our experiments studying coherence dynamics show that 1D Bose gases are ideally suited for investigating this class of phenomena.

The dynamical systems approach to numerical integration

NASA Astrophysics Data System (ADS)

Wisdom, Jack

2018-03-01

The dynamical systems approach to numerical integration is reviewed and extended. The new method is compared to some alternative methods based on the Lie series approach. The test problem is the motion of the outer planets. The algorithms developed using the dynamical systems approach perform well.

Live dynamic analysis of the developing cardiovascular system in mice

NASA Astrophysics Data System (ADS)

Lopez, Andrew L.; Wang, Shang; Larin, Kirill V.; Larina, Irina V.

2017-02-01

The study of the developing cardiovascular system in mice is important for understanding human cardiogenesis and congenital heart defects. Our research focuses on imaging early development in the mouse embryo to specifically understand cardiovascular development under the regulation of dynamic factors like contractile force and blood flow using optical coherence tomography (OCT). We have previously developed an OCT based approach that combines static embryo culture and advanced image processing with computational modeling to live-image mouse embryos and obtain 4D (3D+time) cardiodynamic datasets. Here we present live 4D dynamic blood flow imaging of the early embryonic mouse heart in correlation with heart wall movement. We are using this approach to understand how specific mutations impact heart wall dynamics, and how this influences flow patterns and cardiogenesis. We perform studies in mutant embryos with cardiac phenotypes such as myosin regulatory light chain 2, atrial isoform (Mlc2a). This work is brings us closer to understanding the connections between dynamic mechanical factors and gene programs responsible for early cardiovascular development.

Approaches for modeling within subject variability in pharmacometric count data analysis: dynamic inter-occasion variability and stochastic differential equations.

PubMed

Deng, Chenhui; Plan, Elodie L; Karlsson, Mats O

2016-06-01

Parameter variation in pharmacometric analysis studies can be characterized as within subject parameter variability (WSV) in pharmacometric models. WSV has previously been successfully modeled using inter-occasion variability (IOV), but also stochastic differential equations (SDEs). In this study, two approaches, dynamic inter-occasion variability (dIOV) and adapted stochastic differential equations, were proposed to investigate WSV in pharmacometric count data analysis. These approaches were applied to published count models for seizure counts and Likert pain scores. Both approaches improved the model fits significantly. In addition, stochastic simulation and estimation were used to explore further the capability of the two approaches to diagnose and improve models where existing WSV is not recognized. The results of simulations confirmed the gain in introducing WSV as dIOV and SDEs when parameters vary randomly over time. Further, the approaches were also informative as diagnostics of model misspecification, when parameters changed systematically over time but this was not recognized in the structural model. The proposed approaches in this study offer strategies to characterize WSV and are not restricted to count data.

Dynamic Measurement: The Crossroad of Area and Multiplication

ERIC Educational Resources Information Center

Panorkou, Nicole

2017-01-01

In this exploratory study, our goal was to engage students in dynamic experiences of area as a continuous quantity that can be measured by multiplicatively composing two linear measures (lengths), an approach we refer to as 'dynamic measurement,' or DYME. In this paper, we present the learning trajectory constructed from two cycles of teaching…

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…

The Dynamic Systems Approach as Metatheory for Developmental Psychology

ERIC Educational Resources Information Center

Witherington, David C.

2007-01-01

The dynamic systems perspective has been touted as an integrative metatheoretical framework for the study of stability and change in development. However, two dynamic systems camps exist with respect to the role higher-order form, once emergent, plays in the process of development. This paper evaluates these two camps in terms of the overarching…

Social Dynamics in the Preschool

ERIC Educational Resources Information Center

Martin, Carol Lynn; Fabes, Richard A.; Hanish, Laura D.; Hollenstein, Tom

2005-01-01

In this paper, we consider how concepts from dynamic systems (such as attractors, repellors, and self-organization) can be applied to the study of young children's peer relationships. We also consider how these concepts can be used to explore basic issues involving early peer processes. We use the dynamical systems approach called state space grid…

Principles for the dynamic maintenance of cortical polarity

PubMed Central

Marco, Eugenio; Wedlich-Soldner, Roland; Li, Rong; Altschuler, Steven J.; Wu, Lani F.

2007-01-01

Summary Diverse cell types require the ability to dynamically maintain polarized membrane protein distributions through balancing transport and diffusion. However, design principles underlying dynamically maintained cortical polarity are not well understood. Here we constructed a mathematical model for characterizing the morphology of dynamically polarized protein distributions. We developed analytical approaches for measuring all model parameters from single-cell experiments. We applied our methods to a well-characterized system for studying polarized membrane proteins: budding yeast cells expressing activated Cdc42. We found that balanced diffusion and colocalized transport to and from the plasma membrane were sufficient for accurately describing polarization morphologies. Surprisingly, the model predicts that polarized regions are defined with a precision that is nearly optimal for measured transport rates, and that polarity can be dynamically stabilized through positive feedback with directed transport. Our approach provides a step towards understanding how biological systems shape spatially precise, unambiguous cortical polarity domains using dynamic processes. PMID:17448998

Dynamic waste management (DWM): towards an evolutionary decision-making approach.

PubMed

Rojo, Gabriel; Glaus, Mathias; Laforest, Valerie; Laforest, Valérie; Bourgois, Jacques; Bourgeois, Jacques; Hausler, Robert

2013-12-01

To guarantee sustainable and dynamic waste management, the dynamic waste management approach (DWM) suggests an evolutionary new approach that maintains a constant flow towards the most favourable waste treatment processes (facilities) within a system. To that end, DWM is based on the law of conservation of energy, which allows the balancing of a network, while considering the constraints of incoming (h1 ) and outgoing (h2 ) loads, as well as the distribution network (ΔH) characteristics. The developed approach lies on the identification of the prioritization index (PI) for waste generators (analogy to h1 ), a global allocation index for each of the treatment processes (analogy to h2 ) and the linear index load loss (ΔH) associated with waste transport. To demonstrate the scope of DWM, we outline this approach, and then present an example of its application. The case study shows that the variable monthly waste from the three considered sources is dynamically distributed in priority to the more favourable processes. Moreover, the reserve (stock) helps temporarily store waste in order to ease the global load of the network and favour a constant feeding of the treatment processes. The DWM approach serves as a decision-making tool by evaluating new waste treatment processes, as well as their location and new means of transport for waste.

Dynamic neuroanatomy at subcellular resolution in the zebrafish.

PubMed

Faucherre, Adèle; López-Schier, Hernán

2014-01-01

Genetic means to visualize and manipulate neuronal circuits in the intact animal have revolutionized neurobiology. "Dynamic neuroanatomy" defines a range of approaches aimed at quantifying the architecture or subcellular organization of neurons over time during their development, regeneration, or degeneration. A general feature of these approaches is their reliance on the optical isolation of defined neurons in toto by genetically expressing markers in one or few cells. Here we use the afferent neurons of the lateral line as an example to describe a simple method for the dynamic neuroanatomical study of axon terminals in the zebrafish by laser-scanning confocal microscopy.

Testability of evolutionary game dynamics based on experimental economics data

NASA Astrophysics Data System (ADS)

Wang, Yijia; Chen, Xiaojie; Wang, Zhijian

In order to better understand the dynamic processes of a real game system, we need an appropriate dynamics model, so to evaluate the validity of a model is not a trivial task. Here, we demonstrate an approach, considering the dynamical macroscope patterns of angular momentum and speed as the measurement variables, to evaluate the validity of various dynamics models. Using the data in real time Rock-Paper-Scissors (RPS) games experiments, we obtain the experimental dynamic patterns, and then derive the related theoretical dynamic patterns from a series of typical dynamics models respectively. By testing the goodness-of-fit between the experimental and theoretical patterns, the validity of the models can be evaluated. One of the results in our study case is that, among all the nonparametric models tested, the best-known Replicator dynamics model performs almost worst, while the Projection dynamics model performs best. Besides providing new empirical macroscope patterns of social dynamics, we demonstrate that the approach can be an effective and rigorous tool to test game dynamics models. Fundamental Research Funds for the Central Universities (SSEYI2014Z) and the National Natural Science Foundation of China (Grants No. 61503062).

Linear modal stability analysis of bowed-strings.

PubMed

Debut, V; Antunes, J; Inácio, O

2017-03-01

Linearised models are often invoked as a starting point to study complex dynamical systems. Besides their attractive mathematical simplicity, they have a central role for determining the stability properties of static or dynamical states, and can often shed light on the influence of the control parameters on the system dynamical behaviour. While the bowed string dynamics has been thoroughly studied from a number of points of view, mainly by time-domain computer simulations, this paper proposes to explore its dynamical behaviour adopting a linear framework, linearising the friction force near an equilibrium state in steady sliding conditions, and using a modal representation of the string dynamics. Starting from the simplest idealisation of the friction force given by Coulomb's law with a velocity-dependent friction coefficient, the linearised modal equations of the bowed string are presented, and the dynamical changes of the system as a function of the bowing parameters are studied using linear stability analysis. From the computed complex eigenvalues and eigenvectors, several plots of the evolution of the modal frequencies, damping values, and modeshapes with the bowing parameters are produced, as well as stability charts for each system mode. By systematically exploring the influence of the parameters, this approach appears as a preliminary numerical characterisation of the bifurcations of the bowed string dynamics, with the advantage of being very simple compared to sophisticated numerical approaches which demand the regularisation of the nonlinear interaction force. To fix the idea about the potential of the proposed approach, the classic one-degree-of-freedom friction-excited oscillator is first considered, and then the case of the bowed string. Even if the actual stick-slip behaviour is rather far from the linear description adopted here, the results show that essential musical features of bowed string vibrations can be interpreted from this simple approach, at least qualitatively. Notably, the technique provides an instructive and original picture of bowed motions, in terms of groups of well-defined unstable modes, which is physically intuitive to discuss tonal changes observed in real bowed string.

Dynamical cluster approximation plus semiclassical approximation study for a Mott insulator and d-wave pairing

NASA Astrophysics Data System (ADS)

Kim, SungKun; Lee, Hunpyo

2017-06-01

Via a dynamical cluster approximation with N c = 4 in combination with a semiclassical approximation (DCA+SCA), we study the doped two-dimensional Hubbard model. We obtain a plaquette antiferromagnetic (AF) Mott insulator, a plaquette AF ordered metal, a pseudogap (or d-wave superconductor) and a paramagnetic metal by tuning the doping concentration. These features are similar to the behaviors observed in copper-oxide superconductors and are in qualitative agreement with the results calculated by the cluster dynamical mean field theory with the continuous-time quantum Monte Carlo (CDMFT+CTQMC) approach. The results of our DCA+SCA differ from those of the CDMFT+CTQMC approach in that the d-wave superconducting order parameters are shown even in the high doped region, unlike the results of the CDMFT+CTQMC approach. We think that the strong plaquette AF orderings in the dynamical cluster approximation (DCA) with N c = 4 suppress superconducting states with increasing doping up to strongly doped region, because frozen dynamical fluctuations in a semiclassical approximation (SCA) approach are unable to destroy those orderings. Our calculation with short-range spatial fluctuations is initial research, because the SCA can manage long-range spatial fluctuations in feasible computational times beyond the CDMFT+CTQMC tool. We believe that our future DCA+SCA calculations should supply information on the fully momentum-resolved physical properties, which could be compared with the results measured by angle-resolved photoemission spectroscopy experiments.

Forced canonical thermalization in a hadronic transport approach at high density

NASA Astrophysics Data System (ADS)

Oliinychenko, Dmytro; Petersen, Hannah

2017-03-01

Hadronic transport approaches based on an effective solution of the relativistic Boltzmann equation are widely applied for the dynamical description of heavy ion reactions at low beam energies. At high densities, the assumption of binary interactions often used in hadronic transport approaches may not be applicable anymore. Therefore, we effectively simulate the high-density regime using the local forced canonical thermalization. This framework provides the opportunity to interpolate in a dynamical way between two different limits of kinetic theory: the dilute gas approximation and the ideal fluid case. This approach will be important for studies of the dynamical evolution of heavy ion collisions at low and intermediate energies as experimentally investigated at the beam energy scan program at RHIC, and in the future at FAIR and NICA. On the other hand, this new way of modeling hot and dense strongly interacting matter might be relevant for small systems at high energies (LHC and RHIC) as well.

Classical Dynamics of Fullerenes

NASA Astrophysics Data System (ADS)

Sławianowski, Jan J.; Kotowski, Romuald K.

2017-06-01

The classical mechanics of large molecules and fullerenes is studied. The approach is based on the model of collective motion of these objects. The mixed Lagrangian (material) and Eulerian (space) description of motion is used. In particular, the Green and Cauchy deformation tensors are geometrically defined. The important issue is the group-theoretical approach to describing the affine deformations of the body. The Hamiltonian description of motion based on the Poisson brackets methodology is used. The Lagrange and Hamilton approaches allow us to formulate the mechanics in the canonical form. The method of discretization in analytical continuum theory and in classical dynamics of large molecules and fullerenes enable us to formulate their dynamics in terms of the polynomial expansions of configurations. Another approach is based on the theory of analytical functions and on their approximations by finite-order polynomials. We concentrate on the extremely simplified model of affine deformations or on their higher-order polynomial perturbations.

Divergence compensation for hardware-in-the-loop simulation of stiffness-varying discrete contact in space

NASA Astrophysics Data System (ADS)

Qi, Chenkun; Zhao, Xianchao; Gao, Feng; Ren, Anye; Hu, Yan

2016-11-01

The hardware-in-the-loop (HIL) contact simulation for flying objects in space is challenging due to the divergence caused by the time delay. In this study, a divergence compensation approach is proposed for the stiffness-varying discrete contact. The dynamic response delay of the motion simulator and the force measurement delay are considered. For the force measurement delay, a phase lead based force compensation approach is used. For the dynamic response delay of the motion simulator, a response error based force compensation approach is used, where the compensation force is obtained from the real-time identified contact stiffness and real-time measured position response error. The dynamic response model of the motion simulator is not required. The simulations and experiments show that the simulation divergence can be compensated effectively and satisfactorily by using the proposed approach.

An integrated approach to infer dynamic protein-gene interactions - A case study of the human P53 protein.

PubMed

Wang, Junbai; Wu, Qianqian; Hu, Xiaohua Tony; Tian, Tianhai

2016-11-01

Investigating the dynamics of genetic regulatory networks through high throughput experimental data, such as microarray gene expression profiles, is a very important but challenging task. One of the major hindrances in building detailed mathematical models for genetic regulation is the large number of unknown model parameters. To tackle this challenge, a new integrated method is proposed by combining a top-down approach and a bottom-up approach. First, the top-down approach uses probabilistic graphical models to predict the network structure of DNA repair pathway that is regulated by the p53 protein. Two networks are predicted, namely a network of eight genes with eight inferred interactions and an extended network of 21 genes with 17 interactions. Then, the bottom-up approach using differential equation models is developed to study the detailed genetic regulations based on either a fully connected regulatory network or a gene network obtained by the top-down approach. Model simulation error, parameter identifiability and robustness property are used as criteria to select the optimal network. Simulation results together with permutation tests of input gene network structures indicate that the prediction accuracy and robustness property of the two predicted networks using the top-down approach are better than those of the corresponding fully connected networks. In particular, the proposed approach reduces computational cost significantly for inferring model parameters. Overall, the new integrated method is a promising approach for investigating the dynamics of genetic regulation. Copyright © 2016 Elsevier Inc. All rights reserved.

Hamiltonian approach to continuum dynamics

NASA Astrophysics Data System (ADS)

Isaev, A. A.; Kovalevskii, M. Yu.; Peletminskii, S. V.

1995-02-01

A study is made of the problem of obtaining the Poisson-bracket algebra of the dynamical variables of continuous media on the basis of specification of the kinematic part of the Lagrangian in terms of generalized coordinates and momenta. Within this algebra, subalgebras of variables corresponding to the description of elastic media, the hydrodynamics of ordinary liquids, and the dynamics of some phases of liquid crystals are identified. The differential conservation laws associated with the symmetries of the Hamiltonian of the system are studied. The dynamics of nematics is considered, and features of the dynamics of the cholesteric, smectic, and discotic phases are noted.

A Dynamical Approach Toward Understanding Mechanisms of Team Science: Change, Kinship, Tension, and Heritage in a Transdisciplinary Team

PubMed Central

2013-01-01

Abstract Since the concept of team science gained recognition among biomedical researchers, social scientists have been challenged with investigating evidence of team mechanisms and functional dynamics within transdisciplinary teams. Identification of these mechanisms has lacked substantial research using grounded theory models to adequately describe their dynamical qualities. Research trends continue to favor the measurement of teams by isolating occurrences of production over relational mechanistic team tendencies. This study uses a social constructionist‐grounded multilevel mixed methods approach to identify social dynamics and mechanisms within a transdisciplinary team. A National Institutes of Health—funded research team served as a sample. Data from observations, interviews, and focus groups were qualitatively coded to generate micro/meso level analyses. Social mechanisms operative within this biomedical scientific team were identified. Dynamics that support such mechanisms were documented and explored. Through theoretical and emergent coding, four social mechanisms dominated in the analysis—change, kinship, tension, and heritage. Each contains relational social dynamics. This micro/meso level study suggests such mechanisms and dynamics are key features of team science and as such can inform problems of integration, praxis, and engagement in teams. PMID:23919361

A dynamical approach toward understanding mechanisms of team science: change, kinship, tension, and heritage in a transdisciplinary team.

PubMed

Lotrecchiano, Gaetano R

2013-08-01

Since the concept of team science gained recognition among biomedical researchers, social scientists have been challenged with investigating evidence of team mechanisms and functional dynamics within transdisciplinary teams. Identification of these mechanisms has lacked substantial research using grounded theory models to adequately describe their dynamical qualities. Research trends continue to favor the measurement of teams by isolating occurrences of production over relational mechanistic team tendencies. This study uses a social constructionist-grounded multilevel mixed methods approach to identify social dynamics and mechanisms within a transdisciplinary team. A National Institutes of Health-funded research team served as a sample. Data from observations, interviews, and focus groups were qualitatively coded to generate micro/meso level analyses. Social mechanisms operative within this biomedical scientific team were identified. Dynamics that support such mechanisms were documented and explored. Through theoretical and emergent coding, four social mechanisms dominated in the analysis-change, kinship, tension, and heritage. Each contains relational social dynamics. This micro/meso level study suggests such mechanisms and dynamics are key features of team science and as such can inform problems of integration, praxis, and engagement in teams. © 2013 Wiley Periodicals, Inc.

Rail vehicle dynamic response to a nonlinear physical 'in-service' model of its secondary suspension hydraulic dampers

NASA Astrophysics Data System (ADS)

Wang, W. L.; Zhou, Z. R.; Yu, D. S.; Qin, Q. H.; Iwnicki, S.

2017-10-01

A full nonlinear physical 'in-service' model was built for a rail vehicle secondary suspension hydraulic damper with shim-pack-type valves. In the modelling process, a shim pack deflection theory with an equivalent-pressure correction factor was proposed, and a Finite Element Analysis (FEA) approach was applied. Bench test results validated the damper model over its full velocity range and thus also proved that the proposed shim pack deflection theory and the FEA-based parameter identification approach are effective. The validated full damper model was subsequently incorporated into a detailed vehicle dynamics simulation to study how its key in-service parameter variations influence the secondary-suspension-related vehicle system dynamics. The obtained nonlinear physical in-service damper model and the vehicle dynamic response characteristics in this study could be used in the product design optimization and nonlinear optimal specifications of high-speed rail hydraulic dampers.

Stochastic Simulation of Biomolecular Networks in Dynamic Environments

PubMed Central

Voliotis, Margaritis; Thomas, Philipp; Grima, Ramon; Bowsher, Clive G.

2016-01-01

Simulation of biomolecular networks is now indispensable for studying biological systems, from small reaction networks to large ensembles of cells. Here we present a novel approach for stochastic simulation of networks embedded in the dynamic environment of the cell and its surroundings. We thus sample trajectories of the stochastic process described by the chemical master equation with time-varying propensities. A comparative analysis shows that existing approaches can either fail dramatically, or else can impose impractical computational burdens due to numerical integration of reaction propensities, especially when cell ensembles are studied. Here we introduce the Extrande method which, given a simulated time course of dynamic network inputs, provides a conditionally exact and several orders-of-magnitude faster simulation solution. The new approach makes it feasible to demonstrate—using decision-making by a large population of quorum sensing bacteria—that robustness to fluctuations from upstream signaling places strong constraints on the design of networks determining cell fate. Our approach has the potential to significantly advance both understanding of molecular systems biology and design of synthetic circuits. PMID:27248512

Effect of the Prevalence of HIV/AIDS and the Life Expectancy Rate on Economic Growth in SSA Countries: Difference GMM Approach.

PubMed

Waziri, Salisu Ibrahim; Mohamed Nor, Norashidah; Raja Abdullah, Nik Mustapha; Adamu, Peter

2015-09-01

The productivity of countries around the globe is adversely affected by the health-related problems of their labour force. This study examined the effect of the prevalence of human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS) and life expectancy on the economic growth of 33 Sub-Saharan African (SSA) countries over a period of 11 years (2002-2012). The study employed a dynamic panel approach as opposed to the static traditional approach utilised in the literature. The dynamic approach became eminent because of the fact that HIV/AIDS is a dynamic variable as its prevalence today depends on the previous years. The result revealed that HIV/AIDS is negatively correlated with economic growth in the region, with a coefficient of 0.014, and significant at the 1% level. That is, a 10% increase in HIV/AIDS prevalence leads to a 0.14% decrease in the GDP of the region. Tackling HIV/AIDS is therefore imperative to the developing Sub-Saharan African region and all hands must be on deck to end the menace globally.

Effect of the Prevalence of HIV/AIDS and the Life Expectancy Rate on Economic Growth in SSA Countries: Difference GMM Approach

PubMed Central

Waziri, Salisu Ibrahim; Nor, Norashidah Mohamed; Abdullah, Nik Mustapha Raja; Adamu, Peter

2016-01-01

The productivity of countries around the globe is adversely affected by the health-related problems of their labour force. This study examined the effect of the prevalence of human immunodeficiency virus/acquired immune deficiency syndrome (HIV/AIDS) and life expectancy on the economic growth of 33 Sub-Saharan African (SSA) countries over a period of 11 years (2002–2012). The study employed a dynamic panel approach as opposed to the static traditional approach utilised in the literature. The dynamic approach became eminent because of the fact that HIV/AIDS is a dynamic variable as its prevalence today depends on the previous years. The result revealed that HIV/AIDS is negatively correlated with economic growth in the region, with a coefficient of 0.014, and significant at the 1% level. That is, a 10% increase in HIV/AIDS prevalence leads to a 0.14% decrease in the GDP of the region. Tackling HIV/AIDS is therefore imperative to the developing Sub-Saharan African region and all hands must be on deck to end the menace globally. PMID:26573032

A Nonlinear Dynamics Approach for Incorporating Wind-Speed Patterns into Wind-Power Project Evaluation

PubMed Central

Huffaker, Ray; Bittelli, Marco

2015-01-01

Wind-energy production may be expanded beyond regions with high-average wind speeds (such as the Midwest U.S.A.) to sites with lower-average speeds (such as the Southeast U.S.A.) by locating favorable regional matches between natural wind-speed and energy-demand patterns. A critical component of wind-power evaluation is to incorporate wind-speed dynamics reflecting documented diurnal and seasonal behavioral patterns. Conventional probabilistic approaches remove patterns from wind-speed data. These patterns must be restored synthetically before they can be matched with energy-demand patterns. How to accurately restore wind-speed patterns is a vexing problem spurring an expanding line of papers. We propose a paradigm shift in wind power evaluation that employs signal-detection and nonlinear-dynamics techniques to empirically diagnose whether synthetic pattern restoration can be avoided altogether. If the complex behavior of observed wind-speed records is due to nonlinear, low-dimensional, and deterministic system dynamics, then nonlinear dynamics techniques can reconstruct wind-speed dynamics from observed wind-speed data without recourse to conventional probabilistic approaches. In the first study of its kind, we test a nonlinear dynamics approach in an application to Sugarland Wind—the first utility-scale wind project proposed in Florida, USA. We find empirical evidence of a low-dimensional and nonlinear wind-speed attractor characterized by strong temporal patterns that match up well with regular daily and seasonal electricity demand patterns. PMID:25617767

An Analytical Dynamics Approach to the Control of Mechanical Systems

NASA Astrophysics Data System (ADS)

Mylapilli, Harshavardhan

A new and novel approach to the control of nonlinear mechanical systems is presented in this study. The approach is inspired by recent results in analytical dynamics that deal with the theory of constrained motion. The control requirements on the dynamical system are viewed from an analytical dynamics perspective and the theory of constrained motion is used to recast these control requirements as constraints on the dynamical system. Explicit closed form expressions for the generalized nonlinear control forces are obtained by using the fundamental equation of mechanics. The control so obtained is optimal at each instant of time and causes the constraints to be exactly satisfied. No linearizations and/or approximations of the nonlinear dynamical system are made, and no a priori structure is imposed on the nature of nonlinear controller. Three examples dealing with highly nonlinear complex dynamical systems that are chosen from diverse areas of discrete and continuum mechanics are presented to demonstrate the control approach. The first example deals with the energy control of underactuated inhomogeneous nonlinear lattices (or chains), the second example deals with the synchronization of the motion of multiple coupled slave gyros with that of a master gyro, and the final example deals with the control of incompressible hyperelastic rubber-like thin cantilever beams. Numerical simulations accompanying these examples show the ease, simplicity and the efficacy with which the control methodology can be applied and the accuracy with which the desired control objectives can be met.

Kinetics of the chiral phase transition in a linear σ model

NASA Astrophysics Data System (ADS)

Wesp, Christian; van Hees, Hendrik; Meistrenko, Alex; Greiner, Carsten

2018-02-01

We study the dynamics of the chiral phase transition in a linear quark-meson σ model using a novel approach based on semiclassical wave-particle duality. The quarks are treated as test particles in a Monte Carlo simulation of elastic collisions and the coupling to the σ meson, which is treated as a classical field, via a kinetic approach motivated by wave-particle duality. The exchange of energy and momentum between particles and fields is described in terms of appropriate Gaussian wave packets. It has been demonstrated that energy-momentum conservation and the principle of detailed balance are fulfilled, and that the dynamics leads to the correct equilibrium limit. First schematic studies of the dynamics of matter produced in heavy-ion collisions are presented.

Micromagnetic computer simulations of spin waves in nanometre-scale patterned magnetic elements

NASA Astrophysics Data System (ADS)

Kim, Sang-Koog

2010-07-01

Current needs for further advances in the nanotechnologies of information-storage and -processing devices have attracted a great deal of interest in spin (magnetization) dynamics in nanometre-scale patterned magnetic elements. For instance, the unique dynamic characteristics of non-uniform magnetic microstructures such as various types of domain walls, magnetic vortices and antivortices, as well as spin wave dynamics in laterally restricted thin-film geometries, have been at the centre of extensive and intensive researches. Understanding the fundamentals of their unique spin structure as well as their robust and novel dynamic properties allows us to implement new functionalities into existing or future devices. Although experimental tools and theoretical approaches are effective means of understanding the fundamentals of spin dynamics and of gaining new insights into them, the limitations of those same tools and approaches have left gaps of unresolved questions in the pertinent physics. As an alternative, however, micromagnetic modelling and numerical simulation has recently emerged as a powerful tool for the study of a variety of phenomena related to spin dynamics of nanometre-scale magnetic elements. In this review paper, I summarize the recent results of simulations of the excitation and propagation and other novel wave characteristics of spin waves, highlighting how the micromagnetic computer simulation approach contributes to an understanding of spin dynamics of nanomagnetism and considering some of the merits of numerical simulation studies. Many examples of micromagnetic modelling for numerical calculations, employing various dimensions and shapes of patterned magnetic elements, are given. The current limitations of continuum micromagnetic modelling and of simulations based on the Landau-Lifshitz-Gilbert equation of motion of magnetization are also discussed, along with further research directions for spin-wave studies.

Simulating coupled dynamics of a rigid-flexible multibody system and compressible fluid

NASA Astrophysics Data System (ADS)

Hu, Wei; Tian, Qiang; Hu, HaiYan

2018-04-01

As a subsequent work of previous studies of authors, a new parallel computation approach is proposed to simulate the coupled dynamics of a rigid-flexible multibody system and compressible fluid. In this approach, the smoothed particle hydrodynamics (SPH) method is used to model the compressible fluid, the natural coordinate formulation (NCF) and absolute nodal coordinate formulation (ANCF) are used to model the rigid and flexible bodies, respectively. In order to model the compressible fluid properly and efficiently via SPH method, three measures are taken as follows. The first is to use the Riemann solver to cope with the fluid compressibility, the second is to define virtual particles of SPH to model the dynamic interaction between the fluid and the multibody system, and the third is to impose the boundary conditions of periodical inflow and outflow to reduce the number of SPH particles involved in the computation process. Afterwards, a parallel computation strategy is proposed based on the graphics processing unit (GPU) to detect the neighboring SPH particles and to solve the dynamic equations of SPH particles in order to improve the computation efficiency. Meanwhile, the generalized-alpha algorithm is used to solve the dynamic equations of the multibody system. Finally, four case studies are given to validate the proposed parallel computation approach.

Quantum electron-vibrational dynamics at finite temperature: Thermo field dynamics approach

NASA Astrophysics Data System (ADS)

Borrelli, Raffaele; Gelin, Maxim F.

2016-12-01

Quantum electron-vibrational dynamics in molecular systems at finite temperature is described using an approach based on the thermo field dynamics theory. This formulation treats temperature effects in the Hilbert space without introducing the Liouville space. A comparison with the theoretically equivalent density matrix formulation shows the key numerical advantages of the present approach. The solution of thermo field dynamics equations with a novel technique for the propagation of tensor trains (matrix product states) is discussed. Numerical applications to model spin-boson systems show that the present approach is a promising tool for the description of quantum dynamics of complex molecular systems at finite temperature.

Understanding system dynamics of an adaptive enzyme network from globally profiled kinetic parameters.

PubMed

Chiang, Austin W T; Liu, Wei-Chung; Charusanti, Pep; Hwang, Ming-Jing

2014-01-15

A major challenge in mathematical modeling of biological systems is to determine how model parameters contribute to systems dynamics. As biological processes are often complex in nature, it is desirable to address this issue using a systematic approach. Here, we propose a simple methodology that first performs an enrichment test to find patterns in the values of globally profiled kinetic parameters with which a model can produce the required system dynamics; this is then followed by a statistical test to elucidate the association between individual parameters and different parts of the system's dynamics. We demonstrate our methodology on a prototype biological system of perfect adaptation dynamics, namely the chemotaxis model for Escherichia coli. Our results agreed well with those derived from experimental data and theoretical studies in the literature. Using this model system, we showed that there are motifs in kinetic parameters and that these motifs are governed by constraints of the specified system dynamics. A systematic approach based on enrichment statistical tests has been developed to elucidate the relationships between model parameters and the roles they play in affecting system dynamics of a prototype biological network. The proposed approach is generally applicable and therefore can find wide use in systems biology modeling research.

Nonequilibrium magnetic properties in a two-dimensional kinetic mixed Ising system within the effective-field theory and Glauber-type stochastic dynamics approach.

PubMed

Ertaş, Mehmet; Deviren, Bayram; Keskin, Mustafa

2012-11-01

Nonequilibrium magnetic properties in a two-dimensional kinetic mixed spin-2 and spin-5/2 Ising system in the presence of a time-varying (sinusoidal) magnetic field are studied within the effective-field theory (EFT) with correlations. The time evolution of the system is described by using Glauber-type stochastic dynamics. The dynamic EFT equations are derived by employing the Glauber transition rates for two interpenetrating square lattices. We investigate the time dependence of the magnetizations for different interaction parameter values in order to find the phases in the system. We also study the thermal behavior of the dynamic magnetizations, the hysteresis loop area, and dynamic correlation. The dynamic phase diagrams are presented in the reduced magnetic field amplitude and reduced temperature plane and we observe that the system exhibits dynamic tricritical and reentrant behaviors. Moreover, the system also displays a double critical end point (B), a zero-temperature critical point (Z), a critical end point (E), and a triple point (TP). We also performed a comparison with the mean-field prediction in order to point out the effects of correlations and found that some of the dynamic first-order phase lines, which are artifacts of the mean-field approach, disappeared.

Indonesia’s Electricity Demand Dynamic Modelling

NASA Astrophysics Data System (ADS)

Sulistio, J.; Wirabhuana, A.; Wiratama, M. G.

2017-06-01

Electricity Systems modelling is one of the emerging area in the Global Energy policy studies recently. System Dynamics approach and Computer Simulation has become one the common methods used in energy systems planning and evaluation in many conditions. On the other hand, Indonesia experiencing several major issues in Electricity system such as fossil fuel domination, demand - supply imbalances, distribution inefficiency, and bio-devastation. This paper aims to explain the development of System Dynamics modelling approaches and computer simulation techniques in representing and predicting electricity demand in Indonesia. In addition, this paper also described the typical characteristics and relationship of commercial business sector, industrial sector, and family / domestic sector as electricity subsystems in Indonesia. Moreover, it will be also present direct structure, behavioural, and statistical test as model validation approach and ended by conclusions.

Thermodynamics and kinetics of Na+/K+-formate ion pairs association in polarizable water: A molecular dynamics study

NASA Astrophysics Data System (ADS)

Nguyen, Phuong T. M.; Nguyen, Van T.; Annapureddy, Harsha V. R.; Dang, Liem X.; Do, D. D.

2012-12-01

To enhance our understanding of ion specific activity in biological systems, the potential of mean force approach was utilized to study solvent effects on the interactions between two alkali cations (Na+ and K+) with a formate anion in water. A very complex free energy landscape was observed, much more so than alkali-halide ion pairs. Furthermore, a stronger binding between the Na+-formate pair was found in comparison to the K+-formate pair in water, which is in agreement with experimental and theoretical studies [1-4]. The kinetics of ion-pair inter-conversions was studied using the transition rate theory, along with a number of theoretical approaches such as the Kramers and Grote-Hynes theories. These kinetic results were used to predict solvent effects on dynamical features of ion-pair association, in which we have found that the dynamics of K+-formate pairs is faster than Na+-formate pairs.

Patterns of gender development.

PubMed

Martin, Carol Lynn; Ruble, Diane N

2010-01-01

A comprehensive theory of gender development must describe and explain long-term developmental patterning and changes and how gender is experienced in the short term. This review considers multiple views on gender patterning, illustrated with contemporary research. First, because developmental research involves understanding normative patterns of change with age, several theoretically important topics illustrate gender development: how children come to recognize gender distinctions and understand stereotypes, and the emergence of prejudice and sexism. Second, developmental researchers study the stability of individual differences over time, which elucidates developmental processes. We review stability in two domains-sex segregation and activities/interests. Finally, a new approach advances understanding of developmental patterns, based on dynamic systems theory. Dynamic systems theory is a metatheoretical framework for studying stability and change, which developed from the study of complex and nonlinear systems in physics and mathematics. Some major features and examples show how dynamic approaches have been and could be applied in studying gender development.

Patterns of Gender Development

PubMed Central

Martin, Carol Lynn; Ruble, Diane N.

2013-01-01

A comprehensive theory of gender development must describe and explain long-term developmental patterning and changes and how gender is experienced in the short term. This review considers multiple views on gender patterning, illustrated with contemporary research. First, because developmental research involves understanding normative patterns of change with age, several theoretically important topics illustrate gender development: how children come to recognize gender distinctions and understand stereotypes, and the emergence of prejudice and sexism. Second, developmental researchers study the stability of individual differences over time, which elucidates developmental processes. We review stability in two domains—sex segregation and activities/interests. Finally, a new approach advances understanding of developmental patterns, based on dynamic systems theory. Dynamic systems theory is a metatheoretical framework for studying stability and change, which developed from the study of complex and nonlinear systems in physics and mathematics. Some major features and examples show how dynamic approaches have been and could be applied in studying gender development. PMID:19575615

Nonlinear dynamics in the study of birdsong

NASA Astrophysics Data System (ADS)

Mindlin, Gabriel B.

2017-09-01

Birdsong, a rich and complex behavior, is a stellar model to understand a variety of biological problems, from motor control to learning. It also enables us to study how behavior emerges when a nervous system, a biomechanical device and the environment interact. In this review, I will show that many questions in the field can benefit from the approach of nonlinear dynamics, and how birdsong can inspire new directions for research in dynamics.

Application of dynamic traffic assignment to advanced managed lane modeling.

DOT National Transportation Integrated Search

2013-11-01

In this study, a demand estimation framework is developed for assessing the managed lane (ML) : strategies by utilizing dynamic traffic assignment (DTA) modeling, instead of the traditional : approaches that are based on the static traffic assignment...

Motor Coordination Dynamics Underlying Graphic Motion in 7- to 11-Year-Old Children

ERIC Educational Resources Information Center

Danna, Jeremy; Enderli, Fabienne; Athenes, Sylvie; Zanone, Pier-Giorgio

2012-01-01

Using concepts and tools of a dynamical system approach in order to understand motor coordination underlying graphomotor skills, the aim of the current study was to establish whether the basic coordination dynamics found in adults is already established in children at elementary school, when handwriting is trained and eventually acquired. In the…

Identifying Complex Dynamics in Social Systems: A New Methodological Approach Applied to Study School Segregation

ERIC Educational Resources Information Center

Spaiser, Viktoria; Hedström, Peter; Ranganathan, Shyam; Jansson, Kim; Nordvik, Monica K.; Sumpter, David J. T.

2018-01-01

It is widely recognized that segregation processes are often the result of complex nonlinear dynamics. Empirical analyses of complex dynamics are however rare, because there is a lack of appropriate empirical modeling techniques that are capable of capturing complex patterns and nonlinearities. At the same time, we know that many social phenomena…

Model-based functional neuroimaging using dynamic neural fields: An integrative cognitive neuroscience approach

PubMed Central

Wijeakumar, Sobanawartiny; Ambrose, Joseph P.; Spencer, John P.; Curtu, Rodica

2017-01-01

A fundamental challenge in cognitive neuroscience is to develop theoretical frameworks that effectively span the gap between brain and behavior, between neuroscience and psychology. Here, we attempt to bridge this divide by formalizing an integrative cognitive neuroscience approach using dynamic field theory (DFT). We begin by providing an overview of how DFT seeks to understand the neural population dynamics that underlie cognitive processes through previous applications and comparisons to other modeling approaches. We then use previously published behavioral and neural data from a response selection Go/Nogo task as a case study for model simulations. Results from this study served as the ‘standard’ for comparisons with a model-based fMRI approach using dynamic neural fields (DNF). The tutorial explains the rationale and hypotheses involved in the process of creating the DNF architecture and fitting model parameters. Two DNF models, with similar structure and parameter sets, are then compared. Both models effectively simulated reaction times from the task as we varied the number of stimulus-response mappings and the proportion of Go trials. Next, we directly simulated hemodynamic predictions from the neural activation patterns from each model. These predictions were tested using general linear models (GLMs). Results showed that the DNF model that was created by tuning parameters to capture simultaneously trends in neural activation and behavioral data quantitatively outperformed a Standard GLM analysis of the same dataset. Further, by using the GLM results to assign functional roles to particular clusters in the brain, we illustrate how DNF models shed new light on the neural populations’ dynamics within particular brain regions. Thus, the present study illustrates how an interactive cognitive neuroscience model can be used in practice to bridge the gap between brain and behavior. PMID:29118459

Dynamic cone beam CT angiography of carotid and cerebral arteries using canine model

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

Cai Weixing; Zhao Binghui; Conover, David

2012-01-15

Purpose: This research is designed to develop and evaluate a flat-panel detector-based dynamic cone beam CT system for dynamic angiography imaging, which is able to provide both dynamic functional information and dynamic anatomic information from one multirevolution cone beam CT scan. Methods: A dynamic cone beam CT scan acquired projections over four revolutions within a time window of 40 s after contrast agent injection through a femoral vein to cover the entire wash-in and wash-out phases. A dynamic cone beam CT reconstruction algorithm was utilized and a novel recovery method was developed to correct the time-enhancement curve of contrast flow.more » From the same data set, both projection-based subtraction and reconstruction-based subtraction approaches were utilized and compared to remove the background tissues and visualize the 3D vascular structure to provide the dynamic anatomic information. Results: Through computer simulations, the new recovery algorithm for dynamic time-enhancement curves was optimized and showed excellent accuracy to recover the actual contrast flow. Canine model experiments also indicated that the recovered time-enhancement curves from dynamic cone beam CT imaging agreed well with that of an IV-digital subtraction angiography (DSA) study. The dynamic vascular structures reconstructed using both projection-based subtraction and reconstruction-based subtraction were almost identical as the differences between them were comparable to the background noise level. At the enhancement peak, all the major carotid and cerebral arteries and the Circle of Willis could be clearly observed. Conclusions: The proposed dynamic cone beam CT approach can accurately recover the actual contrast flow, and dynamic anatomic imaging can be obtained with high isotropic 3D resolution. This approach is promising for diagnosis and treatment planning of vascular diseases and strokes.« less

Fast Atomic-Scale Chemical Imaging of Crystalline Materials and Dynamic Phase Transformations.

PubMed

Lu, Ping; Yuan, Ren Liang; Ihlefeld, Jon F; Spoerke, Erik David; Pan, Wei; Zuo, Jian Min

2016-04-13

Atomic-scale phenomena fundamentally influence materials form and function that makes the ability to locally probe and study these processes critical to advancing our understanding and development of materials. Atomic-scale chemical imaging by scanning transmission electron microscopy (STEM) using energy-dispersive X-ray spectroscopy (EDS) is a powerful approach to investigate solid crystal structures. Inefficient X-ray emission and collection, however, require long acquisition times (typically hundreds of seconds), making the technique incompatible with electron-beam sensitive materials and study of dynamic material phenomena. Here we describe an atomic-scale STEM-EDS chemical imaging technique that decreases the acquisition time to as little as one second, a reduction of more than 100 times. We demonstrate this new approach using LaAlO3 single crystal and study dynamic phase transformation in beam-sensitive Li[Li0.2Ni0.2Mn0.6]O2 (LNMO) lithium ion battery cathode material. By capturing a series of time-lapsed chemical maps, we show for the first time clear atomic-scale evidence of preferred Ni-mobility in LNMO transformation, revealing new kinetic mechanisms. These examples highlight the potential of this approach toward temporal, atomic-scale mapping of crystal structure and chemistry for investigating dynamic material phenomena.

Dominant and Emerging Approaches in the Study of Higher Education Policy Change

ERIC Educational Resources Information Center

Saarinen, Taina; Ursin, Jani

2012-01-01

The purpose of the article is to analyse recent literature on higher education policy change. Based on the review, three different approaches are distinguished: structural, actor and agency. In the structural approach the dynamic of policy change originates in well-established structures. The actor approach focuses on either individual or…

Nonlinear dynamics and numerical uncertainties in CFD

NASA Technical Reports Server (NTRS)

Yee, H. C.; Sweby, P. K.

1996-01-01

The application of nonlinear dynamics to improve the understanding of numerical uncertainties in computational fluid dynamics (CFD) is reviewed. Elementary examples in the use of dynamics to explain the nonlinear phenomena and spurious behavior that occur in numerics are given. The role of dynamics in the understanding of long time behavior of numerical integrations and the nonlinear stability, convergence, and reliability of using time-marching, approaches for obtaining steady-state numerical solutions in CFD is explained. The study is complemented with spurious behavior observed in CFD computations.

Estimating rates of local extinction and colonization in colonial species and an extension to the metapopulation and community levels

USGS Publications Warehouse

Barbraud, C.; Nichols, J.D.; Hines, J.E.; Hafner, H.

2003-01-01

Coloniality has mainly been studied from an evolutionary perspective, but relatively few studies have developed methods for modelling colony dynamics. Changes in number of colonies over time provide a useful tool for predicting and evaluating the responses of colonial species to management and to environmental disturbance. Probabilistic Markov process models have been recently used to estimate colony site dynamics using presence-absence data when all colonies are detected in sampling efforts. Here, we define and develop two general approaches for the modelling and analysis of colony dynamics for sampling situations in which all colonies are, and are not, detected. For both approaches, we develop a general probabilistic model for the data and then constrain model parameters based on various hypotheses about colony dynamics. We use Akaike's Information Criterion (AIC) to assess the adequacy of the constrained models. The models are parameterised with conditional probabilities of local colony site extinction and colonization. Presence-absence data arising from Pollock's robust capture-recapture design provide the basis for obtaining unbiased estimates of extinction, colonization, and detection probabilities when not all colonies are detected. This second approach should be particularly useful in situations where detection probabilities are heterogeneous among colony sites. The general methodology is illustrated using presence-absence data on two species of herons (Purple Heron, Ardea purpurea and Grey Heron, Ardea cinerea). Estimates of the extinction and colonization rates showed interspecific differences and strong temporal and spatial variations. We were also able to test specific predictions about colony dynamics based on ideas about habitat change and metapopulation dynamics. We recommend estimators based on probabilistic modelling for future work on colony dynamics. We also believe that this methodological framework has wide application to problems in animal ecology concerning metapopulation and community dynamics.

Organizational Learning and Power Dynamics: A Study in a Brazilian University

ERIC Educational Resources Information Center

Santos, Jane Lucia Silva; Steil, Andrea Valéria

2015-01-01

Purpose: This paper aims to describe and analyze organizational learning processes and power dynamics during the adoption and use of an information system (IS) at a Brazilian public organization. Design/methodology/approach: A case study was chosen as the research method. Data were gathered from documents and interviews with key informants.…

Understanding the Influence of Organizational Culture and Group Dynamics on Organizational Change and Learning

ERIC Educational Resources Information Center

Lucas, Colleen; Kline, Theresa

2008-01-01

Purpose: The purpose of this study is to investigate the relationship between organizational culture, group dynamics, and organizational learning in the context of organizational change. Design/methodology/approach: A case study was used to examine cultural and group level factors that potentially influence groups' learning in the context of…

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities.

PubMed

Frelat, Romain; Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs.

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.

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).

Combined phosphorescence-holographic approach for singlet oxygen detection in biological media

NASA Astrophysics Data System (ADS)

Semenova, I. V.; Belashov, A. V.; Beltukova, D. M.; Petrov, N. V.; Vasyutinskii, O. S.

2015-06-01

The paper presents a novel combined approach aimed to detect and monitor singlet oxygen molecules in biological specimens by means of the simultaneous recording and monitoring of their deactivation dynamics in the two complementary channels: radiative and nonradiative. The approach involves both the direct registration of phosphorescence at the wavelength of about 1270 nm caused by radiative relaxation of excited singlet oxygen molecules and holographic recording of thermal disturbances in the medium produced by their nonradiative relaxation. The data provides a complete set of information on singlet oxygen location and dynamics in the medium. The approach was validated in the case study of photosensitized generation of singlet oxygen in onion cell structures.

A system dynamic modeling approach for evaluating municipal solid waste generation, landfill capacity and related cost management issues.

PubMed

Kollikkathara, Naushad; Feng, Huan; Yu, Danlin

2010-11-01

As planning for sustainable municipal solid waste management has to address several inter-connected issues such as landfill capacity, environmental impacts and financial expenditure, it becomes increasingly necessary to understand the dynamic nature of their interactions. A system dynamics approach designed here attempts to address some of these issues by fitting a model framework for Newark urban region in the US, and running a forecast simulation. The dynamic system developed in this study incorporates the complexity of the waste generation and management process to some extent which is achieved through a combination of simpler sub-processes that are linked together to form a whole. The impact of decision options on the generation of waste in the city, on the remaining landfill capacity of the state, and on the economic cost or benefit actualized by different waste processing options are explored through this approach, providing valuable insights into the urban waste-management process. Copyright © 2010 Elsevier Ltd. All rights reserved.

Capacity planning for waste management systems: an interval fuzzy robust dynamic programming approach.

PubMed

Nie, Xianghui; Huang, Guo H; Li, Yongping

2009-11-01

This study integrates the concepts of interval numbers and fuzzy sets into optimization analysis by dynamic programming as a means of accounting for system uncertainty. The developed interval fuzzy robust dynamic programming (IFRDP) model improves upon previous interval dynamic programming methods. It allows highly uncertain information to be effectively communicated into the optimization process through introducing the concept of fuzzy boundary interval and providing an interval-parameter fuzzy robust programming method for an embedded linear programming problem. Consequently, robustness of the optimization process and solution can be enhanced. The modeling approach is applied to a hypothetical problem for the planning of waste-flow allocation and treatment/disposal facility expansion within a municipal solid waste (MSW) management system. Interval solutions for capacity expansion of waste management facilities and relevant waste-flow allocation are generated and interpreted to provide useful decision alternatives. The results indicate that robust and useful solutions can be obtained, and the proposed IFRDP approach is applicable to practical problems that are associated with highly complex and uncertain information.

A system dynamic modeling approach for evaluating municipal solid waste generation, landfill capacity and related cost management issues

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

Kollikkathara, Naushad, E-mail: naushadkp@gmail.co; Feng Huan; Yu Danlin

2010-11-15

As planning for sustainable municipal solid waste management has to address several inter-connected issues such as landfill capacity, environmental impacts and financial expenditure, it becomes increasingly necessary to understand the dynamic nature of their interactions. A system dynamics approach designed here attempts to address some of these issues by fitting a model framework for Newark urban region in the US, and running a forecast simulation. The dynamic system developed in this study incorporates the complexity of the waste generation and management process to some extent which is achieved through a combination of simpler sub-processes that are linked together to formmore » a whole. The impact of decision options on the generation of waste in the city, on the remaining landfill capacity of the state, and on the economic cost or benefit actualized by different waste processing options are explored through this approach, providing valuable insights into the urban waste-management process.« less

Order reduction, identification and localization studies of dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Xianghong

In this thesis methods are developed for performing order reduction, system identification and induction of nonlinear localization in complex mechanical dynamic systems. General techniques are proposed for constructing low-order models of linear and nonlinear mechanical systems; in addition, novel mechanical designs are considered for inducing nonlinear localization phenomena for the purpose of enhancing their dynamical performance. The thesis is in three major parts. In the first part, the transient dynamics of an impulsively loaded multi-bay truss is numerically computed by employing the Direct Global Matrix (DGM) approach. The approach is applicable to large-scale flexible structures with periodicity. Karhunen-Loeve (K-L) decomposition is used to discretize the dynamics of the truss and to create the low-order models of the truss. The leading order K-L modes are recovered by an experiment, which shows the feasibility of K-L based order reduction technique. In the second part of the thesis, nonlinear localization in dynamical systems is studied through two applications. In the seismic base isolation study, it is shown that the dynamics are sensitive to the presence of nonlinear elements and that passive motion confinement can be induced under proper design. In the coupled rod system, numerical simulation of the transient dynamics shows that a nonlinear backlash spring can induce either nonlinear localization or delocalization in the form of beat phenomena. K-L decomposition and poincare maps are utilized to study the nonlinear effects. The study shows that nonlinear localization can be induced in complex structures through backlash. In the third and final part of the thesis, a new technique based on Green!s function method is proposed to identify the dynamics of practical bolted joints. By modeling the difference between the dynamics of the bolted structure and the corresponding unbolted one, one constructs a nonparametric model for the joint dynamics. Two applications are given with a bolted beam and a truss joint in order to show the applicability of the technique.

Assessment of dynamic effects on aircraft design loads: The landing impact case

NASA Astrophysics Data System (ADS)

Bronstein, Michael; Feldman, Esther; Vescovini, Riccardo; Bisagni, Chiara

2015-10-01

This paper addresses the potential benefits due to a fully dynamic approach to determine the design loads of a mid-size business jet. The study is conducted by considering the fuselage midsection of the DAEDALOS aircraft model with landing impact conditions. The comparison is presented in terms of stress levels between the novel dynamic approach and the standard design practice based on the use of equivalent static loads. The results illustrate that a slight reduction of the load levels can be achieved, but careful modeling of the damping level is needed. Guidelines for an improved load definition are discussed, and suggestions for future research activities are provided.

A PetriNet-Based Approach for Supporting Traceability in Cyber-Physical Manufacturing Systems

PubMed Central

Huang, Jiwei; Zhu, Yeping; Cheng, Bo; Lin, Chuang; Chen, Junliang

2016-01-01

With the growing popularity of complex dynamic activities in manufacturing processes, traceability of the entire life of every product has drawn significant attention especially for food, clinical materials, and similar items. This paper studies the traceability issue in cyber-physical manufacturing systems from a theoretical viewpoint. Petri net models are generalized for formulating dynamic manufacturing processes, based on which a detailed approach for enabling traceability analysis is presented. Models as well as algorithms are carefully designed, which can trace back the lifecycle of a possibly contaminated item. A practical prototype system for supporting traceability is designed, and a real-life case study of a quality control system for bee products is presented to validate the effectiveness of the approach. PMID:26999141

A PetriNet-Based Approach for Supporting Traceability in Cyber-Physical Manufacturing Systems.

PubMed

Huang, Jiwei; Zhu, Yeping; Cheng, Bo; Lin, Chuang; Chen, Junliang

2016-03-17

With the growing popularity of complex dynamic activities in manufacturing processes, traceability of the entire life of every product has drawn significant attention especially for food, clinical materials, and similar items. This paper studies the traceability issue in cyber-physical manufacturing systems from a theoretical viewpoint. Petri net models are generalized for formulating dynamic manufacturing processes, based on which a detailed approach for enabling traceability analysis is presented. Models as well as algorithms are carefully designed, which can trace back the lifecycle of a possibly contaminated item. A practical prototype system for supporting traceability is designed, and a real-life case study of a quality control system for bee products is presented to validate the effectiveness of the approach.

Quantifying non-linear dynamics of mass-springs in series oscillators via asymptotic approach

NASA Astrophysics Data System (ADS)

Starosta, Roman; Sypniewska-Kamińska, Grażyna; Awrejcewicz, Jan

2017-05-01

Dynamical regular response of an oscillator with two serially connected springs with nonlinear characteristics of cubic type and governed by a set of differential-algebraic equations (DAEs) is studied. The classical approach of the multiple scales method (MSM) in time domain has been employed and appropriately modified to solve the governing DAEs of two systems, i.e. with one- and two degrees-of-freedom. The approximate analytical solutions have been verified by numerical simulations.

Modal Response of Trapezoidal Wing Structures Using Second Order Shape Sensitivities

NASA Technical Reports Server (NTRS)

Liu, Youhua; Kapania, Rakesh K.

2000-01-01

The modal response of wing structures is very important for assessing their dynamic response including dynamic aeroelastic instabilities. Moreover, in a recent study an efficient structural optimization approach was developed using structural modes to represent the static aeroelastic wing response (both displacement and stress). In this paper, the modal response of general trapezoidal wing structures is approximated using shape sensitivities up to the 2nd order. Also different approaches of computing the derivatives are investigated.

Evaluation of Student Models on Current Socio-Scientific Topics Based on System Dynamics

ERIC Educational Resources Information Center

Nuhoglu, Hasret

2014-01-01

This study aims to 1) enable primary school students to develop models that will help them understand and analyze a system, through a learning process based on system dynamics approach, 2) examine and evaluate students' models related to socio-scientific issues using certain criteria. The research method used is a case study. The study sample…

Dynamic output feedback control of a flexible air-breathing hypersonic vehicle via T-S fuzzy approach

NASA Astrophysics Data System (ADS)

Hu, Xiaoxiang; Wu, Ligang; Hu, Changhua; Wang, Zhaoqiang; Gao, Huijun

2014-08-01

By utilising Takagi-Sugeno (T-S) fuzzy set approach, this paper addresses the robust H∞ dynamic output feedback control for the non-linear longitudinal model of flexible air-breathing hypersonic vehicles (FAHVs). The flight control of FAHVs is highly challenging due to the unique dynamic characteristics, and the intricate couplings between the engine and fight dynamics and external disturbance. Because of the dynamics' enormous complexity, currently, only the longitudinal dynamics models of FAHVs have been used for controller design. In this work, T-S fuzzy modelling technique is utilised to approach the non-linear dynamics of FAHVs, then a fuzzy model is developed for the output tracking problem of FAHVs. The fuzzy model contains parameter uncertainties and disturbance, which can approach the non-linear dynamics of FAHVs more exactly. The flexible models of FAHVs are difficult to measure because of the complex dynamics and the strong couplings, thus a full-order dynamic output feedback controller is designed for the fuzzy model. A robust H∞ controller is designed for the obtained closed-loop system. By utilising the Lyapunov functional approach, sufficient solvability conditions for such controllers are established in terms of linear matrix inequalities. Finally, the effectiveness of the proposed T-S fuzzy dynamic output feedback control method is demonstrated by numerical simulations.

Mechanical Analyses for coupled Vegetation-Flow System

NASA Astrophysics Data System (ADS)

Chen, L.; Acharya, K.; Stone, M.

2010-12-01

Vegetation in riparian areas plays important roles in hydrology, geomorphology and ecology in local environment. Mechanical response of the aquatic vegetation to hydraulic forces and its impact on flow hydraulics have received considerable attention due to implications for flood control, habitat restoration, and water resources management. This study aims to advance understanding of the mechanical properties of in-stream vegetation including drag force, moment and stress. Dynamic changes of these properties under various flow conditions largely determine vegetation affected flow field and dynamic resistance with progressive bending, and hydraulic conditions for vegetation failure (rupture or wash-out) thus are critical for understanding the coupled vegetation-flow system. A new approach combining fluid and material mechanics is developed in this study to examine the behavior of both rigid and flexible vegetation. The major advantage of this approach is its capability to treat large deflection (bending) of plants and associated changes of mechanical properties in both vegetation and flow. Starting from simple emergent vegetation, both static and dynamic formulations of the problem are presented and the solutions are compared. Results show the dynamic behavior of a simplified system mimicking complex and real systems, implying the approach is able to disclose the physical essence of the coupled system. The approach is extended to complex vegetation under both submerged and emergent conditions using more realistic representation of biomechanical properties for vegetation.

Artificial neural networks for efficient clustering of conformational ensembles and their potential for medicinal chemistry.

PubMed

Pandini, Alessandro; Fraccalvieri, Domenico; Bonati, Laura

2013-01-01

The biological function of proteins is strictly related to their molecular flexibility and dynamics: enzymatic activity, protein-protein interactions, ligand binding and allosteric regulation are important mechanisms involving protein motions. Computational approaches, such as Molecular Dynamics (MD) simulations, are now routinely used to study the intrinsic dynamics of target proteins as well as to complement molecular docking approaches. These methods have also successfully supported the process of rational design and discovery of new drugs. Identification of functionally relevant conformations is a key step in these studies. This is generally done by cluster analysis of the ensemble of structures in the MD trajectory. Recently Artificial Neural Network (ANN) approaches, in particular methods based on Self-Organising Maps (SOMs), have been reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data-mining problems. In the specific case of conformational analysis, SOMs have been successfully used to compare multiple ensembles of protein conformations demonstrating a potential in efficiently detecting the dynamic signatures central to biological function. Moreover, examples of the use of SOMs to address problems relevant to other stages of the drug-design process, including clustering of docking poses, have been reported. In this contribution we review recent applications of ANN algorithms in analysing conformational and structural ensembles and we discuss their potential in computer-based approaches for medicinal chemistry.

IPET and FETR: Experimental Approach for Studying Molecular Structure Dynamics by Cryo-Electron Tomography of a Single-Molecule Structure

PubMed Central

Zhang, Lei; Ren, Gang

2012-01-01

The dynamic personalities and structural heterogeneity of proteins are essential for proper functioning. Structural determination of dynamic/heterogeneous proteins is limited by conventional approaches of X-ray and electron microscopy (EM) of single-particle reconstruction that require an average from thousands to millions different molecules. Cryo-electron tomography (cryoET) is an approach to determine three-dimensional (3D) reconstruction of a single and unique biological object such as bacteria and cells, by imaging the object from a series of tilting angles. However, cconventional reconstruction methods use large-size whole-micrographs that are limited by reconstruction resolution (lower than 20 Å), especially for small and low-symmetric molecule (<400 kDa). In this study, we demonstrated the adverse effects from image distortion and the measuring tilt-errors (including tilt-axis and tilt-angle errors) both play a major role in limiting the reconstruction resolution. Therefore, we developed a “focused electron tomography reconstruction” (FETR) algorithm to improve the resolution by decreasing the reconstructing image size so that it contains only a single-instance protein. FETR can tolerate certain levels of image-distortion and measuring tilt-errors, and can also precisely determine the translational parameters via an iterative refinement process that contains a series of automatically generated dynamic filters and masks. To describe this method, a set of simulated cryoET images was employed; to validate this approach, the real experimental images from negative-staining and cryoET were used. Since this approach can obtain the structure of a single-instance molecule/particle, we named it individual-particle electron tomography (IPET) as a new robust strategy/approach that does not require a pre-given initial model, class averaging of multiple molecules or an extended ordered lattice, but can tolerate small tilt-errors for high-resolution single “snapshot” molecule structure determination. Thus, FETR/IPET provides a completely new opportunity for a single-molecule structure determination, and could be used to study the dynamic character and equilibrium fluctuation of macromolecules. PMID:22291925

Relevance of deterministic chaos theory to studies in functioning of dynamical systems

NASA Astrophysics Data System (ADS)

Glagolev, S. N.; Bukhonova, S. M.; Chikina, E. D.

2018-03-01

The paper considers chaotic behavior of dynamical systems typical for social and economic processes. Approaches to analysis and evaluation of system development processes are studies from the point of view of controllability and determinateness. Explanations are given for necessity to apply non-standard mathematical tools to explain states of dynamical social and economic systems on the basis of fractal theory. Features of fractal structures, such as non-regularity, self-similarity, dimensionality and fractionality are considered.

Motional timescale predictions by molecular dynamics simulations: case study using proline and hydroxyproline sidechain dynamics.

PubMed

Aliev, Abil E; Kulke, Martin; Khaneja, Harmeet S; Chudasama, Vijay; Sheppard, Tom D; Lanigan, Rachel M

2014-02-01

We propose a new approach for force field optimizations which aims at reproducing dynamics characteristics using biomolecular MD simulations, in addition to improved prediction of motionally averaged structural properties available from experiment. As the source of experimental data for dynamics fittings, we use (13) C NMR spin-lattice relaxation times T1 of backbone and sidechain carbons, which allow to determine correlation times of both overall molecular and intramolecular motions. For structural fittings, we use motionally averaged experimental values of NMR J couplings. The proline residue and its derivative 4-hydroxyproline with relatively simple cyclic structure and sidechain dynamics were chosen for the assessment of the new approach in this work. Initially, grid search and simplexed MD simulations identified large number of parameter sets which fit equally well experimental J couplings. Using the Arrhenius-type relationship between the force constant and the correlation time, the available MD data for a series of parameter sets were analyzed to predict the value of the force constant that best reproduces experimental timescale of the sidechain dynamics. Verification of the new force-field (termed as AMBER99SB-ILDNP) against NMR J couplings and correlation times showed consistent and significant improvements compared to the original force field in reproducing both structural and dynamics properties. The results suggest that matching experimental timescales of motions together with motionally averaged characteristics is the valid approach for force field parameter optimization. Such a comprehensive approach is not restricted to cyclic residues and can be extended to other amino acid residues, as well as to the backbone. Copyright © 2013 Wiley Periodicals, Inc.

Evaluating complementary networks of restoration plantings for landscape-scale occurrence of temporally dynamic species.

PubMed

Ikin, Karen; Tulloch, Ayesha; Gibbons, Philip; Ansell, Dean; Seddon, Julian; Lindenmayer, David

2016-10-01

Multibillion dollar investments in land restoration make it critical that conservation goals are achieved cost-effectively. Approaches developed for systematic conservation planning offer opportunities to evaluate landscape-scale, temporally dynamic biodiversity outcomes from restoration and improve on traditional approaches that focus on the most species-rich plantings. We investigated whether it is possible to apply a complementarity-based approach to evaluate the extent to which an existing network of restoration plantings meets representation targets. Using a case study of woodland birds of conservation concern in southeastern Australia, we compared complementarity-based selections of plantings based on temporally dynamic species occurrences with selections based on static species occurrences and selections based on ranking plantings by species richness. The dynamic complementarity approach, which incorporated species occurrences over 5 years, resulted in higher species occurrences and proportion of targets met compared with the static complementarity approach, in which species occurrences were taken at a single point in time. For equivalent cost, the dynamic complementarity approach also always resulted in higher average minimum percent occurrence of species maintained through time and a higher proportion of the bird community meeting representation targets compared with the species-richness approach. Plantings selected under the complementarity approaches represented the full range of planting attributes, whereas those selected under the species-richness approach were larger in size. Our results suggest that future restoration policy should not attempt to achieve all conservation goals within individual plantings, but should instead capitalize on restoration opportunities as they arise to achieve collective value of multiple plantings across the landscape. Networks of restoration plantings with complementary attributes of age, size, vegetation structure, and landscape context lead to considerably better outcomes than conventional restoration objectives of site-scale species richness and are crucial for allocating restoration investment wisely to reach desired conservation goals. © 2016 Society for Conservation Biology.

Entangled trajectories Hamiltonian dynamics for treating quantum nuclear effects

NASA Astrophysics Data System (ADS)

Smith, Brendan; Akimov, Alexey V.

2018-04-01

A simple and robust methodology, dubbed Entangled Trajectories Hamiltonian Dynamics (ETHD), is developed to capture quantum nuclear effects such as tunneling and zero-point energy through the coupling of multiple classical trajectories. The approach reformulates the classically mapped second-order Quantized Hamiltonian Dynamics (QHD-2) in terms of coupled classical trajectories. The method partially enforces the uncertainty principle and facilitates tunneling. The applicability of the method is demonstrated by studying the dynamics in symmetric double well and cubic metastable state potentials. The methodology is validated using exact quantum simulations and is compared to QHD-2. We illustrate its relationship to the rigorous Bohmian quantum potential approach, from which ETHD can be derived. Our simulations show a remarkable agreement of the ETHD calculation with the quantum results, suggesting that ETHD may be a simple and inexpensive way of including quantum nuclear effects in molecular dynamics simulations.

Archetypal dynamics, emergent situations, and the reality game.

PubMed

Sulis, William

2010-07-01

The classical approach to the modeling of reality is founded upon its objectification. Although successful dealing with inanimate matter, objectification has proven to be much less successful elsewhere, sometimes to the point of paradox. This paper discusses an approach to the modeling of reality based upon the concept of process as formulated within the framework of archetypal dynamics. Reality is conceptualized as an intermingling of information-transducing systems, together with the semantic frames that effectively describe and ascribe meaning to each system, along with particular formal representations of same which constitute the archetypes. Archetypal dynamics is the study of the relationships between systems, frames and their representations and the flow of information among these different entities. In this paper a specific formal representation of archetypal dynamics using tapestries is given, and a dynamics is founded upon this representation in the form of a combinatorial game called a reality game. Some simple examples are presented.

Optimal placement of unified power flow controllers to improve dynamic voltage stability using power system variable based voltage stability indices.

PubMed

Albatsh, Fadi M; Ahmad, Shameem; Mekhilef, Saad; Mokhlis, Hazlie; Hassan, M A

2015-01-01

This study examines a new approach to selecting the locations of unified power flow controllers (UPFCs) in power system networks based on a dynamic analysis of voltage stability. Power system voltage stability indices (VSIs) including the line stability index (LQP), the voltage collapse proximity indicator (VCPI), and the line stability index (Lmn) are employed to identify the most suitable locations in the system for UPFCs. In this study, the locations of the UPFCs are identified by dynamically varying the loads across all of the load buses to represent actual power system conditions. Simulations were conducted in a power system computer-aided design (PSCAD) software using the IEEE 14-bus and 39- bus benchmark power system models. The simulation results demonstrate the effectiveness of the proposed method. When the UPFCs are placed in the locations obtained with the new approach, the voltage stability improves. A comparison of the steady-state VSIs resulting from the UPFCs placed in the locations obtained with the new approach and with particle swarm optimization (PSO) and differential evolution (DE), which are static methods, is presented. In all cases, the UPFC locations given by the proposed approach result in better voltage stability than those obtained with the other approaches.

Optimal Placement of Unified Power Flow Controllers to Improve Dynamic Voltage Stability Using Power System Variable Based Voltage Stability Indices

PubMed Central

Albatsh, Fadi M.; Ahmad, Shameem; Mekhilef, Saad; Mokhlis, Hazlie; Hassan, M. A.

2015-01-01

This study examines a new approach to selecting the locations of unified power flow controllers (UPFCs) in power system networks based on a dynamic analysis of voltage stability. Power system voltage stability indices (VSIs) including the line stability index (LQP), the voltage collapse proximity indicator (VCPI), and the line stability index (Lmn) are employed to identify the most suitable locations in the system for UPFCs. In this study, the locations of the UPFCs are identified by dynamically varying the loads across all of the load buses to represent actual power system conditions. Simulations were conducted in a power system computer-aided design (PSCAD) software using the IEEE 14-bus and 39- bus benchmark power system models. The simulation results demonstrate the effectiveness of the proposed method. When the UPFCs are placed in the locations obtained with the new approach, the voltage stability improves. A comparison of the steady-state VSIs resulting from the UPFCs placed in the locations obtained with the new approach and with particle swarm optimization (PSO) and differential evolution (DE), which are static methods, is presented. In all cases, the UPFC locations given by the proposed approach result in better voltage stability than those obtained with the other approaches. PMID:25874560

High resolution imaging of the dynamics of nanoparticles in/on liquids

NASA Astrophysics Data System (ADS)

Kim, Paul; Ribbe, Alexander; Russell, Thomas; Hoagland, David

Electron microscopy for the study of nanoscale structure and dynamics in solvated soft materials has only recently been proposed, and since this technique requires high vacuum, significant challenges must be confronted. Specimens can be encapsulated in vacuum-sealed devices for TEM but this approach is not without difficulties, including beam damage, cumbersome specimen handling, and propensity for wall artifacts. Here, we report an alternative SEM approach, obviating need for a liquid cell by exploiting the nonvolatility of ionic liquids, which is illustrated by visualizations of nanoscale dynamics for two solvated systems, dispersed nanospheres and nanorods in/on thin, free-standing IL films. The translational and rotational Brownian of these nanoparticles were quantitatively tracked. In ultra-thin films, a striking and unanticipated dynamical pairing of the nanospheres was observed, manifesting a balance of capillary and hydrodynamic interactions. Concentrated nanorods were seen to assemble into finite stacks that could be tracked over their entire lifetimes. Broadly applicable to solvated soft nanoscopic materials, the new imaging protocol offers a breakthrough in the study of their structure and dynamics.

Adaptive measurements of urban runoff quality

NASA Astrophysics Data System (ADS)

Wong, Brandon P.; Kerkez, Branko

2016-11-01

An approach to adaptively measure runoff water quality dynamics is introduced, focusing specifically on characterizing the timing and magnitude of urban pollutographs. Rather than relying on a static schedule or flow-weighted sampling, which can miss important water quality dynamics if parameterized inadequately, novel Internet-enabled sensor nodes are used to autonomously adapt their measurement frequency to real-time weather forecasts and hydrologic conditions. This dynamic approach has the potential to significantly improve the use of constrained experimental resources, such as automated grab samplers, which continue to provide a strong alternative to sampling water quality dynamics when in situ sensors are not available. Compared to conventional flow-weighted or time-weighted sampling schemes, which rely on preset thresholds, a major benefit of the approach is the ability to dynamically adapt to features of an underlying hydrologic signal. A 28 km2 urban watershed was studied to characterize concentrations of total suspended solids (TSS) and total phosphorus. Water quality samples were autonomously triggered in response to features in the underlying hydrograph and real-time weather forecasts. The study watershed did not exhibit a strong first flush and intraevent concentration variability was driven by flow acceleration, wherein the largest loadings of TSS and total phosphorus corresponded with the steepest rising limbs of the storm hydrograph. The scalability of the proposed method is discussed in the context of larger sensor network deployments, as well the potential to improving control of urban water quality.

Dynamic optical imaging of vascular and metabolic reactivity in rheumatoid joints.

PubMed

Lasker, Joseph M; Fong, Christopher J; Ginat, Daniel T; Dwyer, Edward; Hielscher, Andreas H

2007-01-01

Dynamic optical imaging is increasingly applied to clinically relevant areas such as brain and cancer imaging. In this approach, some external stimulus is applied and changes in relevant physiological parameters (e.g., oxy- or deoxyhemoglobin concentrations) are determined. The advantage of this approach is that the prestimulus state can be used as a reference or baseline against which the changes can be calibrated. Here we present the first application of this method to the problem of characterizing joint diseases, especially effects of rheumatoid arthritis (RA) in the proximal interphalangeal finger joints. Using a dual-wavelength tomographic imaging system together with previously implemented model-based iterative image reconstruction schemes, we have performed initial dynamic imaging case studies on a limited number of healthy volunteers and patients diagnosed with RA. Focusing on three cases studies, we illustrated our major finds. These studies support our hypothesis that differences in the vascular reactivity exist between affected and unaffected joints.

Debt and growth: A non-parametric approach

NASA Astrophysics Data System (ADS)

Brida, Juan Gabriel; Gómez, David Matesanz; Seijas, Maria Nela

2017-11-01

In this study, we explore the dynamic relationship between public debt and economic growth by using a non-parametric approach based on data symbolization and clustering methods. The study uses annual data of general government consolidated gross debt-to-GDP ratio and gross domestic product for sixteen countries between 1977 and 2015. Using symbolic sequences, we introduce a notion of distance between the dynamical paths of different countries. Then, a Minimal Spanning Tree and a Hierarchical Tree are constructed from time series to help detecting the existence of groups of countries sharing similar economic performance. The main finding of the study appears for the period 2008-2016 when several countries surpassed the 90% debt-to-GDP threshold. During this period, three groups (clubs) of countries are obtained: high, mid and low indebted countries, suggesting that the employed debt-to-GDP threshold drives economic dynamics for the selected countries.

Student-Centred Teaching Methods: Can They Optimise Students' Approaches to Learning in Professional Higher Education?

ERIC Educational Resources Information Center

Baeten, Marlies; Struyven, Katrien; Dochy, Filip

2013-01-01

This paper investigates dynamics in approaches to learning within different learning environments. Two quasi-experimental studies were conducted with first-year student teachers (N[subscript Study 1] = 496, N[subscript Study 2] = 1098) studying a child development course. Data collection was carried out using a pre-test/post-test design by means…

Next Generation Extended Lagrangian Quantum-based Molecular Dynamics

NASA Astrophysics Data System (ADS)

Negre, Christian

2017-06-01

A new framework for extended Lagrangian first-principles molecular dynamics simulations is presented, which overcomes shortcomings of regular, direct Born-Oppenheimer molecular dynamics, while maintaining important advantages of the unified extended Lagrangian formulation of density functional theory pioneered by Car and Parrinello three decades ago. The new framework allows, for the first time, energy conserving, linear-scaling Born-Oppenheimer molecular dynamics simulations, which is necessary to study larger and more realistic systems over longer simulation times than previously possible. Expensive, self-consinstent-field optimizations are avoided and normal integration time steps of regular, direct Born-Oppenheimer molecular dynamics can be used. Linear scaling electronic structure theory is presented using a graph-based approach that is ideal for parallel calculations on hybrid computer platforms. For the first time, quantum based Born-Oppenheimer molecular dynamics simulation is becoming a practically feasible approach in simulations of +100,000 atoms-representing a competitive alternative to classical polarizable force field methods. In collaboration with: Anders Niklasson, Los Alamos National Laboratory.

Longitudinal magnetization dynamics in Heisenberg magnets: Spin Green functions approach (Review Article)

NASA Astrophysics Data System (ADS)

Krivoruchko, V. N.

2017-11-01

In spite of the fact that dynamical properties of magnets have been extensively studied over the past years, the longitudinal magnetization dynamics is still much less understood than transverse one even in the equilibrium state of a system. In this paper, we give a review of existing, based on quantum-mechanical approach, theoretical descriptions of the longitudinal magnetization dynamics for ferro-, ferri- and antiferromagnetic dielectrics. The aim is to reveal specific features of this type of magnetization vibrations under description a system within the framework of one of the basic model theory of magnetism—the Heisenberg model. Related experimental investigations as well as open questions are also briefly discussed. We hope that understanding of the longitudinal magnetization dynamics distinctive features in the equilibrium state have to be a reference point for a theory uncovering the physical mechanisms that govern ultrafast spin dynamics after femtosecond laser pulse demagnetization when a system is far beyond an equilibrium state.

Brownian dynamics and dynamic Monte Carlo simulations of isotropic and liquid crystal phases of anisotropic colloidal particles: a comparative study.

PubMed

Patti, Alessandro; Cuetos, Alejandro

2012-07-01

We report on the diffusion of purely repulsive and freely rotating colloidal rods in the isotropic, nematic, and smectic liquid crystal phases to probe the agreement between Brownian and Monte Carlo dynamics under the most general conditions. By properly rescaling the Monte Carlo time step, being related to any elementary move via the corresponding self-diffusion coefficient, with the acceptance rate of simultaneous trial displacements and rotations, we demonstrate the existence of a unique Monte Carlo time scale that allows for a direct comparison between Monte Carlo and Brownian dynamics simulations. To estimate the validity of our theoretical approach, we compare the mean square displacement of rods, their orientational autocorrelation function, and the self-intermediate scattering function, as obtained from Brownian dynamics and Monte Carlo simulations. The agreement between the results of these two approaches, even under the condition of heterogeneous dynamics generally observed in liquid crystalline phases, is excellent.

Dynamic modelling of n-of-1 data: powerful and flexible data analytics applied to individualised studies.

PubMed

Vieira, Rute; McDonald, Suzanne; Araújo-Soares, Vera; Sniehotta, Falko F; Henderson, Robin

2017-09-01

N-of-1 studies are based on repeated observations within an individual or unit over time and are acknowledged as an important research method for generating scientific evidence about the health or behaviour of an individual. Statistical analyses of n-of-1 data require accurate modelling of the outcome while accounting for its distribution, time-related trend and error structures (e.g., autocorrelation) as well as reporting readily usable contextualised effect sizes for decision-making. A number of statistical approaches have been documented but no consensus exists on which method is most appropriate for which type of n-of-1 design. We discuss the statistical considerations for analysing n-of-1 studies and briefly review some currently used methodologies. We describe dynamic regression modelling as a flexible and powerful approach, adaptable to different types of outcomes and capable of dealing with the different challenges inherent to n-of-1 statistical modelling. Dynamic modelling borrows ideas from longitudinal and event history methodologies which explicitly incorporate the role of time and the influence of past on future. We also present an illustrative example of the use of dynamic regression on monitoring physical activity during the retirement transition. Dynamic modelling has the potential to expand researchers' access to robust and user-friendly statistical methods for individualised studies.

Applications of Fourier Transform Ion Cyclotron Resonance (FT-ICR) and Orbitrap Based High Resolution Mass Spectrometry in Metabolomics and Lipidomics.

PubMed

Ghaste, Manoj; Mistrik, Robert; Shulaev, Vladimir

2016-05-25

Metabolomics, along with other "omics" approaches, is rapidly becoming one of the major approaches aimed at understanding the organization and dynamics of metabolic networks. Mass spectrometry is often a technique of choice for metabolomics studies due to its high sensitivity, reproducibility and wide dynamic range. High resolution mass spectrometry (HRMS) is a widely practiced technique in analytical and bioanalytical sciences. It offers exceptionally high resolution and the highest degree of structural confirmation. Many metabolomics studies have been conducted using HRMS over the past decade. In this review, we will explore the latest developments in Fourier transform mass spectrometry (FTMS) and Orbitrap based metabolomics technology, its advantages and drawbacks for using in metabolomics and lipidomics studies, and development of novel approaches for processing HRMS data.

Applications of Fourier Transform Ion Cyclotron Resonance (FT-ICR) and Orbitrap Based High Resolution Mass Spectrometry in Metabolomics and Lipidomics

PubMed Central

Ghaste, Manoj; Mistrik, Robert; Shulaev, Vladimir

2016-01-01

Metabolomics, along with other “omics” approaches, is rapidly becoming one of the major approaches aimed at understanding the organization and dynamics of metabolic networks. Mass spectrometry is often a technique of choice for metabolomics studies due to its high sensitivity, reproducibility and wide dynamic range. High resolution mass spectrometry (HRMS) is a widely practiced technique in analytical and bioanalytical sciences. It offers exceptionally high resolution and the highest degree of structural confirmation. Many metabolomics studies have been conducted using HRMS over the past decade. In this review, we will explore the latest developments in Fourier transform mass spectrometry (FTMS) and Orbitrap based metabolomics technology, its advantages and drawbacks for using in metabolomics and lipidomics studies, and development of novel approaches for processing HRMS data. PMID:27231903

A methodological approach to studying resilience mechanisms: demonstration of utility in age and Alzheimer's disease-related brain pathology.

PubMed

Wolf, Dominik; Fischer, Florian Udo; Fellgiebel, Andreas

2018-05-01

The present work aims at providing a methodological approach for the investigation of resilience factors and mechanisms in normal aging, Alzheimer's disease (AD) and other neurodegenerative disorders. By expanding and re-conceptualizing traditional regression approaches, we propose an approach that not only aims at identifying potential resilience factors but also allows for a differentiation between general and dynamic resilience factors in terms of their association with pathology. Dynamic resilience factors are characterized by an increasing relevance with increasing levels of pathology, while the relevance of general resilience factors is independent of the amount of pathology. Utility of the approach is demonstrated in age and AD-related brain pathology by investigating widely accepted resilience factors, including education and brain volume. Moreover, the approach is used to test hippocampal volume as potential resilience factor. Education and brain volume could be identified as general resilience factors against age and AD-related pathology. Beyond that, analyses highlighted that hippocampal volume may not only be disease target but also serve as a potential resilience factor in age and AD-related pathology, particularly at higher levels of tau-pathology (i.e. dynamic resilience factor). Given its unspecific and superordinate nature the approach is suitable for the investigation of a wide range of potential resilience factors in normal aging, AD and other neurodegenerative disorders. Consequently, it may find a wide application and thereby promote the comparability between studies.

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

USGS Publications Warehouse

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

2017-01-01

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

Constructions of Dynamic Geometry: A Study of the Interpretative Flexibility of Educational Software in Classroom Practice

ERIC Educational Resources Information Center

Ruthven, Kenneth; Hennessy, Sara; Deaney, Rosemary

2008-01-01

The idea of "interpretative flexibility" underpins new approaches to studying technological artefacts and curricular resources in use. This paper opens by reviewing, in this light, the evolving design of dynamic geometry, its pioneering use within classroom projects, and early sketches of its mainstream use in ordinary classrooms. After…

Daily Emotional Dynamics in Depressed Youth: A Cell Phone Ecological Momentary Assessment Study

ERIC Educational Resources Information Center

Silk, Jennifer S.; Forbes, Erika E.; Whalen, Diana J.; Jakubcak, Jennifer L.; Thompson, Wesley K.; Ryan, Neal D.; Axelson, David A.; Birmaher, Boris; Dahl, Ronald E.

2011-01-01

This study used a new cell phone ecological momentary assessment approach to investigate daily emotional dynamics in 47 youths with major depressive disorder (MDD) and 32 no-psychopathology controls (CON) (ages 7-17 years). Information about emotional experience in the natural environment was obtained using answer-only cell phones, while MDD…

Molecular Dynamics Analysis of Lysozyme Protein in Ethanol-Water Mixed Solvent Environment

NASA Astrophysics Data System (ADS)

Ochije, Henry Ikechukwu

Effect of protein-solvent interaction on the protein structure is widely studied using both experimental and computational techniques. Despite such extensive studies molecular level understanding of proteins and some simple solvents is still not fully understood. This work focuses on detailed molecular dynamics simulations to study of solvent effect on lysozyme protein, using water, alcohol and different concentrations of water-alcohol mixtures as solvents. The lysozyme protein structure in water, alcohol and alcohol-water mixture (0-12% alcohol) was studied using GROMACS molecular dynamics simulation code. Compared to water environment, the lysozome structure showed remarkable changes in solvents with increasing alcohol concentration. In particular, significant changes were observed in the protein secondary structure involving alpha helices. The influence of alcohol on the lysozyme protein was investigated by studying thermodynamic and structural properties. With increasing ethanol concentration we observed a systematic increase in total energy, enthalpy, root mean square deviation (RMSD), and radius of gyration. a polynomial interpolation approach. Using the resulting polynomial equation, we could determine above quantities for any intermediate alcohol percentage. In order to validate this approach, we selected an intermediate ethanol percentage and carried out full MD simulation. The results from MD simulation were in reasonably good agreement with that obtained using polynomial approach. Hence, the polynomial approach based method proposed here eliminates the need for computationally intensive full MD analysis for the concentrations within the range (0-12%) studied in this work.

Dynamic clearance measure to evaluate locomotor and perceptuo-motor strategies used for obstacle circumvention in a virtual environment.

PubMed

Darekar, Anuja; Lamontagne, Anouk; Fung, Joyce

2015-04-01

Circumvention around an obstacle entails a dynamic interaction with the obstacle to maintain a safe clearance. We used a novel mathematical interpolation method based on the modified Shepard's method of Inverse Distance Weighting to compute dynamic clearance that reflected this interaction as well as minimal clearance. This proof-of-principle study included seven young healthy, four post-stroke and four healthy age-matched individuals. A virtual environment designed to assess obstacle circumvention was used to administer a locomotor (walking) and a perceptuo-motor (navigation with a joystick) task. In both tasks, participants were asked to navigate towards a target while avoiding collision with a moving obstacle that approached from either head-on, or 30° left or right. Among young individuals, dynamic clearance did not differ significantly between obstacle approach directions in both tasks. Post-stroke individuals maintained larger and smaller dynamic clearance during the locomotor and the perceptuo-motor task respectively as compared to age-matched controls. Dynamic clearance was larger than minimal distance from the obstacle irrespective of the group, task and obstacle approach direction. Also, in contrast to minimal distance, dynamic clearance can respond differently to different avoidance behaviors. Such a measure can be beneficial in contrasting obstacle avoidance behaviors in different populations with mobility problems. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluation of a grid based molecular dynamics approach for polypeptide simulations.

PubMed

Merelli, Ivan; Morra, Giulia; Milanesi, Luciano

2007-09-01

Molecular dynamics is very important for biomedical research because it makes possible simulation of the behavior of a biological macromolecule in silico. However, molecular dynamics is computationally rather expensive: the simulation of some nanoseconds of dynamics for a large macromolecule such as a protein takes very long time, due to the high number of operations that are needed for solving the Newton's equations in the case of a system of thousands of atoms. In order to obtain biologically significant data, it is desirable to use high-performance computation resources to perform these simulations. Recently, a distributed computing approach based on replacing a single long simulation with many independent short trajectories has been introduced, which in many cases provides valuable results. This study concerns the development of an infrastructure to run molecular dynamics simulations on a grid platform in a distributed way. The implemented software allows the parallel submission of different simulations that are singularly short but together bring important biological information. Moreover, each simulation is divided into a chain of jobs to avoid data loss in case of system failure and to contain the dimension of each data transfer from the grid. The results confirm that the distributed approach on grid computing is particularly suitable for molecular dynamics simulations thanks to the elevated scalability.

Model-order reduction of lumped parameter systems via fractional calculus

NASA Astrophysics Data System (ADS)

Hollkamp, John P.; Sen, Mihir; Semperlotti, Fabio

2018-04-01

This study investigates the use of fractional order differential models to simulate the dynamic response of non-homogeneous discrete systems and to achieve efficient and accurate model order reduction. The traditional integer order approach to the simulation of non-homogeneous systems dictates the use of numerical solutions and often imposes stringent compromises between accuracy and computational performance. Fractional calculus provides an alternative approach where complex dynamical systems can be modeled with compact fractional equations that not only can still guarantee analytical solutions, but can also enable high levels of order reduction without compromising on accuracy. Different approaches are explored in order to transform the integer order model into a reduced order fractional model able to match the dynamic response of the initial system. Analytical and numerical results show that, under certain conditions, an exact match is possible and the resulting fractional differential models have both a complex and frequency-dependent order of the differential operator. The implications of this type of approach for both model order reduction and model synthesis are discussed.

The results of a limited study of approaches to the design, fabrication, and testing of a dynamic model of the NASA IOC space station. Executive summary

NASA Technical Reports Server (NTRS)

Brooks, George W.

1985-01-01

The options for the design, construction, and testing of a dynamic model of the space station were evaluated. Since the definition of the space station structure is still evolving, the Initial Operating Capacity (IOC) reference configuration was used as the general guideline. The results of the studies treat: general considerations of the need for and use of a dynamic model; factors which deal with the model design and construction; and a proposed system for supporting the dynamic model in the planned Large Spacecraft Laboratory.

Using a Complexity Approach to Study the Interpersonal Dynamics in Teacher-­Student Interactions: A Case Study of Two Teachers

ERIC Educational Resources Information Center

Pennings, Helena J. M.

2017-01-01

In the present study, complex dynamic systems theory and interpersonal theory are combined to describe the teacher-student interactions of two teachers with different interpersonal styles. The aim was to show and explain the added value of looking at different steps in the analysis of behavioral time-series data (i.e., observations of teacher and…

Dynamic transcriptional signatures and network responses for clinical symptoms in influenza-infected human subjects using systems biology approaches.

PubMed

Linel, Patrice; Wu, Shuang; Deng, Nan; Wu, Hulin

2014-10-01

Recent studies demonstrate that human blood transcriptional signatures may be used to support diagnosis and clinical decisions for acute respiratory viral infections such as influenza. In this article, we propose to use a newly developed systems biology approach for time course gene expression data to identify significant dynamically response genes and dynamic gene network responses to viral infection. We illustrate the methodological pipeline by reanalyzing the time course gene expression data from a study with healthy human subjects challenged by live influenza virus. We observed clear differences in the number of significant dynamic response genes (DRGs) between the symptomatic and asymptomatic subjects and also identified DRG signatures for symptomatic subjects with influenza infection. The 505 common DRGs shared by the symptomatic subjects have high consistency with the signature genes for predicting viral infection identified in previous works. The temporal response patterns and network response features were carefully analyzed and investigated.

Extended Phase-Space Methods for Enhanced Sampling in Molecular Simulations: A Review.

PubMed

Fujisaki, Hiroshi; Moritsugu, Kei; Matsunaga, Yasuhiro; Morishita, Tetsuya; Maragliano, Luca

2015-01-01

Molecular Dynamics simulations are a powerful approach to study biomolecular conformational changes or protein-ligand, protein-protein, and protein-DNA/RNA interactions. Straightforward applications, however, are often hampered by incomplete sampling, since in a typical simulated trajectory the system will spend most of its time trapped by high energy barriers in restricted regions of the configuration space. Over the years, several techniques have been designed to overcome this problem and enhance space sampling. Here, we review a class of methods that rely on the idea of extending the set of dynamical variables of the system by adding extra ones associated to functions describing the process under study. In particular, we illustrate the Temperature Accelerated Molecular Dynamics (TAMD), Logarithmic Mean Force Dynamics (LogMFD), and Multiscale Enhanced Sampling (MSES) algorithms. We also discuss combinations with techniques for searching reaction paths. We show the advantages presented by this approach and how it allows to quickly sample important regions of the free-energy landscape via automatic exploration.

An ensemble of dynamic neural network identifiers for fault detection and isolation of gas turbine engines.

PubMed

Amozegar, M; Khorasani, K

2016-04-01

In this paper, a new approach for Fault Detection and Isolation (FDI) of gas turbine engines is proposed by developing an ensemble of dynamic neural network identifiers. For health monitoring of the gas turbine engine, its dynamics is first identified by constructing three separate or individual dynamic neural network architectures. Specifically, a dynamic multi-layer perceptron (MLP), a dynamic radial-basis function (RBF) neural network, and a dynamic support vector machine (SVM) are trained to individually identify and represent the gas turbine engine dynamics. Next, three ensemble-based techniques are developed to represent the gas turbine engine dynamics, namely, two heterogeneous ensemble models and one homogeneous ensemble model. It is first shown that all ensemble approaches do significantly improve the overall performance and accuracy of the developed system identification scheme when compared to each of the stand-alone solutions. The best selected stand-alone model (i.e., the dynamic RBF network) and the best selected ensemble architecture (i.e., the heterogeneous ensemble) in terms of their performances in achieving an accurate system identification are then selected for solving the FDI task. The required residual signals are generated by using both a single model-based solution and an ensemble-based solution under various gas turbine engine health conditions. Our extensive simulation studies demonstrate that the fault detection and isolation task achieved by using the residuals that are obtained from the dynamic ensemble scheme results in a significantly more accurate and reliable performance as illustrated through detailed quantitative confusion matrix analysis and comparative studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multiscale molecular dynamics simulations of rotary motor proteins.

PubMed

Ekimoto, Toru; Ikeguchi, Mitsunori

2018-04-01

Protein functions require specific structures frequently coupled with conformational changes. The scale of the structural dynamics of proteins spans from the atomic to the molecular level. Theoretically, all-atom molecular dynamics (MD) simulation is a powerful tool to investigate protein dynamics because the MD simulation is capable of capturing conformational changes obeying the intrinsically structural features. However, to study long-timescale dynamics, efficient sampling techniques and coarse-grained (CG) approaches coupled with all-atom MD simulations, termed multiscale MD simulations, are required to overcome the timescale limitation in all-atom MD simulations. Here, we review two examples of rotary motor proteins examined using free energy landscape (FEL) analysis and CG-MD simulations. In the FEL analysis, FEL is calculated as a function of reaction coordinates, and the long-timescale dynamics corresponding to conformational changes is described as transitions on the FEL surface. Another approach is the utilization of the CG model, in which the CG parameters are tuned using the fluctuation matching methodology with all-atom MD simulations. The long-timespan dynamics is then elucidated straightforwardly by using CG-MD simulations.

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

Wang, Shaobu; Lu, Shuai; Zhou, Ning

In interconnected power systems, dynamic model reduction can be applied on generators outside the area of interest to mitigate the computational cost with transient stability studies. This paper presents an approach of deriving the reduced dynamic model of the external area based on dynamic response measurements, which comprises of three steps, dynamic-feature extraction, attribution and reconstruction (DEAR). In the DEAR approach, a feature extraction technique, such as singular value decomposition (SVD), is applied to the measured generator dynamics after a disturbance. Characteristic generators are then identified in the feature attribution step for matching the extracted dynamic features with the highestmore » similarity, forming a suboptimal ‘basis’ of system dynamics. In the reconstruction step, generator state variables such as rotor angles and voltage magnitudes are approximated with a linear combination of the characteristic generators, resulting in a quasi-nonlinear reduced model of the original external system. Network model is un-changed in the DEAR method. Tests on several IEEE standard systems show that the proposed method gets better reduction ratio and response errors than the traditional coherency aggregation methods.« less

Brain Dynamics: Methodological Issues and Applications in Psychiatric and Neurologic Diseases

NASA Astrophysics Data System (ADS)

Pezard, Laurent

The human brain is a complex dynamical system generating the EEG signal. Numerical methods developed to study complex physical dynamics have been used to characterize EEG since the mid-eighties. This endeavor raised several issues related to the specificity of EEG. Firstly, theoretical and methodological studies should address the major differences between the dynamics of the human brain and physical systems. Secondly, this approach of EEG signal should prove to be relevant for dealing with physiological or clinical problems. A set of studies performed in our group is presented here within the context of these two problematic aspects. After the discussion of methodological drawbacks, we review numerical simulations related to the high dimension and spatial extension of brain dynamics. Experimental studies in neurologic and psychiatric disease are then presented. We conclude that if it is now clear that brain dynamics changes in relation with clinical situations, methodological problems remain largely unsolved.

Improving dynamic phytoplankton reserve-utilization models with an indirect proxy for internal nitrogen.

PubMed

Malerba, Martino E; Heimann, Kirsten; Connolly, Sean R

2016-09-07

Ecologists have often used indirect proxies to represent variables that are difficult or impossible to measure directly. In phytoplankton, the internal concentration of the most limiting nutrient in a cell determines its growth rate. However, directly measuring the concentration of nutrients within cells is inaccurate, expensive, destructive, and time-consuming, substantially impairing our ability to model growth rates in nutrient-limited phytoplankton populations. The red chlorophyll autofluorescence (hereafter "red fluorescence") signal emitted by a cell is highly correlated with nitrogen quota in nitrogen-limited phytoplankton species. The aim of this study was to evaluate the reliability of including flow cytometric red fluorescence as a proxy for internal nitrogen status to model phytoplankton growth rates. To this end, we used the classic Quota model and designed three approaches to calibrate its model parameters to data: where empirical observations on cell internal nitrogen quota were used to fit the model ("Nitrogen-Quota approach"), where quota dynamics were inferred only from changes in medium nutrient depletion and population density ("Virtual-Quota approach"), or where red fluorescence emission of a cell was used as an indirect proxy for its internal nitrogen quota ("Fluorescence-Quota approach"). Two separate analyses were carried out. In the first analysis, stochastic model simulations were parameterized from published empirical relationships and used to generate dynamics of phytoplankton communities reared under nitrogen-limited conditions. Quota models were fitted to the dynamics of each simulated species with the three different approaches and the performance of each model was compared. In the second analysis, we fit Quota models to laboratory time-series and we calculate the ability of each calibration approach to describe the observed trajectories of internal nitrogen quota in the culture. Results from both analyses concluded that the Fluorescence-Quota approach including per-cell red fluorescence as a proxy of internal nitrogen substantially improved the ability of Quota models to describe phytoplankton dynamics, while still accounting for the biologically important process of cell nitrogen storage. More broadly, many population models in ecology implicitly recognize the importance of accounting for storage mechanisms to describe the dynamics of individual organisms. Hence, the approach documented here with phytoplankton dynamics may also be useful for evaluating the potential of indirect proxies in other ecological systems. Copyright © 2016 Elsevier Ltd. All rights reserved.

Some Aspects of Nonlinear Dynamics and CFD

NASA Technical Reports Server (NTRS)

Yee, Helen C.; Merriam, Marshal (Technical Monitor)

1996-01-01

The application of nonlinear dynamics to improve the understanding of numerical uncertainties in computational fluid dynamics (CFD) is reviewed. Elementary examples in the use of dynamics to explain the nonlinear phenomena and spurious behavior that occur in numerics are given. The role of dynamics in the understanding of long time behavior of numerical integrations and the nonlinear stability, convergence, and reliability of using time-marching approaches for obtaining steady-state numerical solutions in CFD is explained. The study is complemented with examples of spurious behavior observed in CFD computations.

A new approach for describing glass transition kinetics.

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

Vasin, N. M.; Shchelkachev, M. G.; Vinokur, V. M.

2010-04-01

We use a functional integral technique generalizing the Keldysh diagram technique to describe glass transition kinetics. We show that the Keldysh functional approach takes the dynamical determinant arising in the glass dynamics into account exactly and generalizes the traditional approach based on using the supersymmetric dynamic generating functional method. In contrast to the supersymmetric method, this approach allows avoiding additional Grassmannian fields and tracking the violation of the fluctuation-dissipation theorem explicitly. We use this method to describe the dynamics of an Edwards-Anderson soft spin-glass-type model near the paramagnet-glass transition. We show that a Vogel-Fulcher-type dynamics arises in the fluctuation regionmore » only if the fluctuation-dissipation theorem is violated in the process of dynamical renormalization of the Keldysh action in the replica space.« less

Stage-by-Stage and Parallel Flow Path Compressor Modeling for a Variable Cycle Engine, NASA Advanced Air Vehicles Program - Commercial Supersonic Technology Project - AeroServoElasticity

NASA Technical Reports Server (NTRS)

Kopasakis, George; Connolly, Joseph W.; Cheng, Larry

2015-01-01

This paper covers the development of stage-by-stage and parallel flow path compressor modeling approaches for a Variable Cycle Engine. The stage-by-stage compressor modeling approach is an extension of a technique for lumped volume dynamics and performance characteristic modeling. It was developed to improve the accuracy of axial compressor dynamics over lumped volume dynamics modeling. The stage-by-stage compressor model presented here is formulated into a parallel flow path model that includes both axial and rotational dynamics. This is done to enable the study of compressor and propulsion system dynamic performance under flow distortion conditions. The approaches utilized here are generic and should be applicable for the modeling of any axial flow compressor design accurate time domain simulations. The objective of this work is as follows. Given the parameters describing the conditions of atmospheric disturbances, and utilizing the derived formulations, directly compute the transfer function poles and zeros describing these disturbances for acoustic velocity, temperature, pressure, and density. Time domain simulations of representative atmospheric turbulence can then be developed by utilizing these computed transfer functions together with the disturbance frequencies of interest.

Approaches in Health Human Resource Forecasting: A Roadmap for Improvement.

PubMed

Rafiei, Sima; Mohebbifar, Rafat; Hashemi, Fariba; Ezzatabadi, Mohammad Ranjbar; Farzianpour, Fereshteh

2016-09-01

Forecasting the demand and supply of health manpower in an accurate manner makes appropriate planning possible. The aim of this paper was to review approaches and methods for health manpower forecasting and consequently propose the features that improve the effectiveness of this important process of health manpower planning. A literature review was conducted for studies published in English from 1990-2014 using Pub Med, Science Direct, Pro Quest, and Google Scholar databases. Review articles, qualitative studies, retrospective and prospective studies describing or applying various types of forecasting approaches and methods in health manpower forecasting were included in the review. The authors designed an extraction data sheet based on study questions to collect data on studies' references, designs, and types of forecasting approaches, whether discussed or applied, with their strengths and weaknesses. Forty studies were included in the review. As a result, two main categories of approaches (conceptual and analytical) for health manpower forecasting were identified. Each approach had several strengths and weaknesses. As a whole, most of them were faced with some challenges, such as being static and unable to capture dynamic variables in manpower forecasting and causal relationships. They also lacked the capacity to benefit from scenario making to assist policy makers in effective decision making. An effective forecasting approach is supposed to resolve all the deficits that exist in current approaches and meet the key features found in the literature in order to develop an open system and a dynamic and comprehensive method necessary for today complex health care systems.

Community ecology in 3D: Tensor decomposition reveals spatio-temporal dynamics of large ecological communities

PubMed Central

Lindegren, Martin; Denker, Tim Spaanheden; Floeter, Jens; Fock, Heino O.; Sguotti, Camilla; Stäbler, Moritz; Otto, Saskia A.; Möllmann, Christian

2017-01-01

Understanding spatio-temporal dynamics of biotic communities containing large numbers of species is crucial to guide ecosystem management and conservation efforts. However, traditional approaches usually focus on studying community dynamics either in space or in time, often failing to fully account for interlinked spatio-temporal changes. In this study, we demonstrate and promote the use of tensor decomposition for disentangling spatio-temporal community dynamics in long-term monitoring data. Tensor decomposition builds on traditional multivariate statistics (e.g. Principal Component Analysis) but extends it to multiple dimensions. This extension allows for the synchronized study of multiple ecological variables measured repeatedly in time and space. We applied this comprehensive approach to explore the spatio-temporal dynamics of 65 demersal fish species in the North Sea, a marine ecosystem strongly altered by human activities and climate change. Our case study demonstrates how tensor decomposition can successfully (i) characterize the main spatio-temporal patterns and trends in species abundances, (ii) identify sub-communities of species that share similar spatial distribution and temporal dynamics, and (iii) reveal external drivers of change. Our results revealed a strong spatial structure in fish assemblages persistent over time and linked to differences in depth, primary production and seasonality. Furthermore, we simultaneously characterized important temporal distribution changes related to the low frequency temperature variability inherent in the Atlantic Multidecadal Oscillation. Finally, we identified six major sub-communities composed of species sharing similar spatial distribution patterns and temporal dynamics. Our case study demonstrates the application and benefits of using tensor decomposition for studying complex community data sets usually derived from large-scale monitoring programs. PMID:29136658

Nonlinear dynamics and predictability in the atmospheric sciences

NASA Technical Reports Server (NTRS)

Ghil, M.; Kimoto, M.; Neelin, J. D.

1991-01-01

Systematic applications of nonlinear dynamics to studies of the atmosphere and climate are reviewed for the period 1987-1990. Problems discussed include paleoclimatic applications, low-frequency atmospheric variability, and interannual variability of the ocean-atmosphere system. Emphasis is placed on applications of the successive bifurcation approach and the ergodic theory of dynamical systems to understanding and prediction of intraseasonal, interannual, and Quaternary climate changes.

Predictability and Coupled Dynamics of MJO During DYNAMO

DTIC Science & Technology

2013-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Predictability and Coupled Dynamics of MJO During DYNAMO ... DYNAMO time period. APPROACH We are working as a team to study MJO dynamics and predictability using several models as team members of the ONR DRI...associated with the DYNAMO experiment. This is a fundamentally collaborative proposal that involves close collaboration with Dr. Hyodae Seo of the

Dynamics of Coupled Electron-Boson Systems with the Multiple Davydov D1 Ansatz and the Generalized Coherent State.

PubMed

Chen, Lipeng; Borrelli, Raffaele; Zhao, Yang

2017-11-22

The dynamics of a coupled electron-boson system is investigated by employing a multitude of the Davydov D 1 trial states, also known as the multi-D 1 Ansatz, and a second trial state based on a superposition of the time-dependent generalized coherent state (GCS Ansatz). The two Ansätze are applied to study population dynamics in the spin-boson model and the Holstein molecular crystal model, and a detailed comparison with numerically exact results obtained by the (multilayer) multiconfiguration time-dependent Hartree method and the hierarchy equations of motion approach is drawn. It is found that the two methodologies proposed here have significantly improved over that with the single D 1 Ansatz, yielding quantitatively accurate results even in the critical cases of large energy biases and large transfer integrals. The two methodologies provide new effective tools for accurate, efficient simulation of many-body quantum dynamics thanks to a relatively small number of parameters which characterize the electron-nuclear wave functions. The wave-function-based approaches are capable of tracking explicitly detailed bosonic dynamics, which is absent by construct in approaches based on the reduced density matrix. The efficiency and flexibility of our methods are also advantages as compared with numerically exact approaches such as QUAPI and HEOM, especially at low temperatures and in the strong coupling regime.

Role of lake-wide prey fish survey in understanding ecosystem dynamics and managing fisheries of Lake Michigan

USGS Publications Warehouse

Madenjian, Charles P.; Edsall, T.; Munawar, M.

2005-01-01

With this study, the role of this lake-wide prey fish survey in both understanding the dynamics of the Lake Michigan ecosystem and managing Lake Michigan fisheries was documented. The complexity of ecosystems is such that long-term study is required before the dynamics of the ecosystem can be understoond. Furthermore, long-term observation is needed before important or meaningful questions about ecosystem dynamics can be asked. My approach is to first illustrate, by example, the usefulness of the survey results in providing insights into the dynamics of the Lake Michigan ecosystem. Then, examples of direct application of the survey results toward Lake Michigan fisheries management are presented.

Potential energy surfaces and reaction dynamics of polyatomic molecules

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

Chang, Yan-Tyng

A simple empirical valence bond (EVB) model approach is suggested for constructing global potential energy surfaces for reactions of polyatomic molecular systems. This approach produces smooth and continuous potential surfaces which can be directly utilized in a dynamical study. Two types of reactions are of special interest, the unimolecular dissociation and the unimolecular isomerization. For the first type, the molecular dissociation dynamics of formaldehyde on the ground electronic surface is investigated through classical trajectory calculations on EVB surfaces. The product state distributions and vector correlations obtained from this study suggest very similar behaviors seen in the experiments. The intramolecular hydrogenmore » atom transfer in the formic acid dimer is an example of the isomerization reaction. High level ab initio quantum chemistry calculations are performed to obtain optimized equilibrium and transition state dimer geometries and also the harmonic frequencies.« less

Redox condition in molten salts and solute behavior: A first-principles molecular dynamics study

NASA Astrophysics Data System (ADS)

Nam, Hyo On; Morgan, Dane

2015-10-01

Molten salts technology is of significant interest for nuclear, solar, and other energy systems. In this work, first-principles molecular dynamics (FPMD) was used to model the solute behavior in eutectic LiCl-KCl and FLiBe (Li2BeF4) melts at 773 K and 973 K, respectively. The thermo-kinetic properties for solute systems such as the redox potential, solute diffusion coefficients and structural information surrounding the solute were predicted from FPMD modeling and the calculated properties are generally in agreement with the experiments. In particular, we formulate an approach to model redox energetics vs. chlorine (or fluorine) potential from first-principles approaches. This study develops approaches for, and demonstrates the capabilities of, FPMD to model solute properties in molten salts.

Theory of the dynamical thermal conductivity of metals

NASA Astrophysics Data System (ADS)

Bhalla, Pankaj; Kumar, Pradeep; Das, Nabyendu; Singh, Navinder

2016-09-01

The Mori's projection method, known as the memory function method, is an important theoretical formalism to study various transport coefficients. In the present work, we calculate the dynamical thermal conductivity in the case of metals using the memory function formalism. We introduce thermal memory functions for the first time and discuss the behavior of thermal conductivity in both the zero frequency limit and in the case of nonzero frequencies. We compare our results for the zero frequency case with the results obtained by the Bloch-Boltzmann kinetic approach and find that both approaches agree with each other. Motivated by some recent experimental advancements, we obtain several new results for the ac or the dynamical thermal conductivity.

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

NASA Astrophysics Data System (ADS)

Kang, Yuncheol; Prabhu, Vittal

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

Moving to higher ground: The dynamic field theory and the dynamics of visual cognition

PubMed Central

Johnson, Jeffrey S.; Spencer, John P.; Schöner, Gregor

2009-01-01

In the present report, we describe a new dynamic field theory that captures the dynamics of visuo-spatial cognition. This theory grew out of the dynamic systems approach to motor control and development, and is grounded in neural principles. The initial application of dynamic field theory to issues in visuo-spatial cognition extended concepts of the motor approach to decision making in a sensori-motor context, and, more recently, to the dynamics of spatial cognition. Here we extend these concepts still further to address topics in visual cognition, including visual working memory for non-spatial object properties, the processes that underlie change detection, and the ‘binding problem’ in vision. In each case, we demonstrate that the general principles of the dynamic field approach can unify findings in the literature and generate novel predictions. We contend that the application of these concepts to visual cognition avoids the pitfalls of reductionist approaches in cognitive science, and points toward a formal integration of brains, bodies, and behavior. PMID:19173013

Inverse Transformation: Unleashing Spatially Heterogeneous Dynamics with an Alternative Approach to XPCS Data Analysis.

PubMed

Andrews, Ross N; Narayanan, Suresh; Zhang, Fan; Kuzmenko, Ivan; Ilavsky, Jan

2018-02-01

X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables probing dynamics in a broad array of materials with XPCS, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fails. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. In this paper, we propose an alternative analysis scheme based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. Using XPCS data measured from colloidal gels, we demonstrate the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS.

Inverse Transformation: Unleashing Spatially Heterogeneous Dynamics with an Alternative Approach to XPCS Data Analysis

PubMed Central

Andrews, Ross N.; Narayanan, Suresh; Zhang, Fan; Kuzmenko, Ivan; Ilavsky, Jan

2018-01-01

X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables probing dynamics in a broad array of materials with XPCS, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fails. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. In this paper, we propose an alternative analysis scheme based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. Using XPCS data measured from colloidal gels, we demonstrate the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS. PMID:29875506

Rhythm is it: effects of dynamic body feedback on affect and attitudes

PubMed Central

Koch, Sabine C.

2014-01-01

Body feedback is the proprioceptive feedback that denominates the afferent information from position and movement of the body to the central nervous system. It is crucial in experiencing emotions, in forming attitudes and in regulating emotions and behavior. This paper investigates effects of dynamic body feedback on affect and attitudes, focusing on the impact of movement rhythms with smooth vs. sharp reversals as one basic category of movement qualities. It relates those qualities to already explored effects of approach vs. avoidance motor behavior as one basic category of movement shape. Studies 1 and 2 tested the effects of one of two basic movement qualities (smooth vs. sharp rhythms) on affect and cognition. The third study tested those movement qualities in combination with movement shape (approach vs. avoidance motor behavior) and the effects of those combinations on affect and attitudes toward initially valence-free stimuli. Results suggest that movement rhythms influence affect (studies 1 and 2), and attitudes (study 3), and moderate the impact of approach and avoidance motor behavior on attitudes (study 3). Extending static body feedback research with a dynamic account, findings indicate that movement qualities – next to movement shape – play an important role, when movement of the lived body is an independent variable. PMID:24959153

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

PubMed Central

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

2012-01-01

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

Structural stability of nonlinear population dynamics.

PubMed

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.

Structural stability of nonlinear population dynamics

NASA Astrophysics Data System (ADS)

Cenci, Simone; Saavedra, Serguei

2018-01-01

In population dynamics, the concept of structural stability has been used to quantify the tolerance of a system to environmental perturbations. Yet, measuring the structural stability of nonlinear dynamical systems remains a challenging task. Focusing on the classic Lotka-Volterra dynamics, because of the linearity of the functional response, it has been possible to measure the conditions compatible with a structurally stable system. However, the functional response of biological communities is not always well approximated by deterministic linear functions. Thus, it is unclear the extent to which this linear approach can be generalized to other population dynamics models. Here, we show that the same approach used to investigate the classic Lotka-Volterra dynamics, which is called the structural approach, can be applied to a much larger class of nonlinear models. This class covers a large number of nonlinear functional responses that have been intensively investigated both theoretically and experimentally. We also investigate the applicability of the structural approach to stochastic dynamical systems and we provide a measure of structural stability for finite populations. Overall, we show that the structural approach can provide reliable and tractable information about the qualitative behavior of many nonlinear dynamical systems.

Motional timescale predictions by molecular dynamics simulations: Case study using proline and hydroxyproline sidechain dynamics

PubMed Central

Aliev, Abil E; Kulke, Martin; Khaneja, Harmeet S; Chudasama, Vijay; Sheppard, Tom D; Lanigan, Rachel M

2014-01-01

We propose a new approach for force field optimizations which aims at reproducing dynamics characteristics using biomolecular MD simulations, in addition to improved prediction of motionally averaged structural properties available from experiment. As the source of experimental data for dynamics fittings, we use 13C NMR spin-lattice relaxation times T1 of backbone and sidechain carbons, which allow to determine correlation times of both overall molecular and intramolecular motions. For structural fittings, we use motionally averaged experimental values of NMR J couplings. The proline residue and its derivative 4-hydroxyproline with relatively simple cyclic structure and sidechain dynamics were chosen for the assessment of the new approach in this work. Initially, grid search and simplexed MD simulations identified large number of parameter sets which fit equally well experimental J couplings. Using the Arrhenius-type relationship between the force constant and the correlation time, the available MD data for a series of parameter sets were analyzed to predict the value of the force constant that best reproduces experimental timescale of the sidechain dynamics. Verification of the new force-field (termed as AMBER99SB-ILDNP) against NMR J couplings and correlation times showed consistent and significant improvements compared to the original force field in reproducing both structural and dynamics properties. The results suggest that matching experimental timescales of motions together with motionally averaged characteristics is the valid approach for force field parameter optimization. Such a comprehensive approach is not restricted to cyclic residues and can be extended to other amino acid residues, as well as to the backbone. Proteins 2014; 82:195–215. © 2013 Wiley Periodicals, Inc. PMID:23818175

Structural domains and main-chain flexibility in prion proteins.

PubMed

Blinov, N; Berjanskii, M; Wishart, D S; Stepanova, M

2009-02-24

In this study we describe a novel approach to define structural domains and to characterize the local flexibility in both human and chicken prion proteins. The approach we use is based on a comprehensive theory of collective dynamics in proteins that was recently developed. This method determines the essential collective coordinates, which can be found from molecular dynamics trajectories via principal component analysis. Under this particular framework, we are able to identify the domains where atoms move coherently while at the same time to determine the local main-chain flexibility for each residue. We have verified this approach by comparing our results for the predicted dynamic domain systems with the computed main-chain flexibility profiles and the NMR-derived random coil indexes for human and chicken prion proteins. The three sets of data show excellent agreement. Additionally, we demonstrate that the dynamic domains calculated in this fashion provide a highly sensitive measure of protein collective structure and dynamics. Furthermore, such an analysis is capable of revealing structural and dynamic properties of proteins that are inaccessible to the conventional assessment of secondary structure. Using the collective dynamic simulation approach described here along with a high-temperature simulations of unfolding of human prion protein, we have explored whether locations of relatively low stability could be identified where the unfolding process could potentially be facilitated. According to our analysis, the locations of relatively low stability may be associated with the beta-sheet formed by strands S1 and S2 and the adjacent loops, whereas helix HC appears to be a relatively stable part of the protein. We suggest that this kind of structural analysis may provide a useful background for a more quantitative assessment of potential routes of spontaneous misfolding in prion proteins.

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.

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

Two dissimilar approaches to dynamical systems on hyper MV -algebras and their information entropy

NASA Astrophysics Data System (ADS)

Mehrpooya, Adel; Ebrahimi, Mohammad; Davvaz, Bijan

2017-09-01

Measuring the flow of information that is related to the evolution of a system which is modeled by applying a mathematical structure is of capital significance for science and usually for mathematics itself. Regarding this fact, a major issue in concern with hyperstructures is their dynamics and the complexity of the varied possible dynamics that exist over them. Notably, the dynamics and uncertainty of hyper MV -algebras which are hyperstructures and extensions of a central tool in infinite-valued Lukasiewicz propositional calculus that models many valued logics are of primary concern. Tackling this problem, in this paper we focus on the subject of dynamical systems on hyper MV -algebras and their entropy. In this respect, we adopt two varied approaches. One is the set-based approach in which hyper MV -algebra dynamical systems are developed by employing set functions and set partitions. By the other method that is based on points and point partitions, we establish the concept of hyper injective dynamical systems on hyper MV -algebras. Next, we study the notion of entropy for both kinds of systems. Furthermore, we consider essential ergodic characteristics of those systems and their entropy. In particular, we introduce the concept of isomorphic hyper injective and hyper MV -algebra dynamical systems, and we demonstrate that isomorphic systems have the same entropy. We present a couple of theorems in order to help calculate entropy. In particular, we prove a contemporary version of addition and Kolmogorov-Sinai Theorems. Furthermore, we provide a comparison between the indispensable properties of hyper injective and semi-independent dynamical systems. Specifically, we present and prove theorems that draw comparisons between the entropies of such systems. Lastly, we discuss some possible relationships between the theories of hyper MV -algebra and MV -algebra dynamical systems.

Human seizures self-terminate across spatial scales via a critical transition.

PubMed

Kramer, Mark A; Truccolo, Wilson; Eden, Uri T; Lepage, Kyle Q; Hochberg, Leigh R; Eskandar, Emad N; Madsen, Joseph R; Lee, Jong W; Maheshwari, Atul; Halgren, Eric; Chu, Catherine J; Cash, Sydney S

2012-12-18

Why seizures spontaneously terminate remains an unanswered fundamental question of epileptology. Here we present evidence that seizures self-terminate via a discontinuous critical transition or bifurcation. We show that human brain electrical activity at various spatial scales exhibits common dynamical signatures of an impending critical transition--slowing, increased correlation, and flickering--in the approach to seizure termination. In contrast, prolonged seizures (status epilepticus) repeatedly approach, but do not cross, the critical transition. To support these results, we implement a computational model that demonstrates that alternative stable attractors, representing the ictal and postictal states, emulate the observed dynamics. These results suggest that self-terminating seizures end through a common dynamical mechanism. This description constrains the specific biophysical mechanisms underlying seizure termination, suggests a dynamical understanding of status epilepticus, and demonstrates an accessible system for studying critical transitions in nature.

Qualitative Research and Educational Leadership: Essential Dynamics to Consider When Designing and Conducting Studies

ERIC Educational Resources Information Center

Brooks, Jeffrey S.; Normore, Anthony H.

2015-01-01

Purpose: The purpose of this paper is to highlight issues relayed to appropriate design and conduct of qualitative studies in educational leadership. Design/Methodology/Approach: The paper is a conceptual/logical argument that centers around the notion that while scholars in the field have at times paid attention to such dynamics, it is important…

Dynamics of Inequalities in Access to Higher Education: Bulgaria in a Comparative Perspective

ERIC Educational Resources Information Center

Ilieva-Trichkova, Petya; Boyadjieva, Pepka

2014-01-01

This paper aims at studying the dynamics of inequalities in access to higher education (HE) both in a historical and a comparative perspective. It uses Bulgaria as a case study and places it among five other countries such as Estonia, Hungary, Poland, Slovakia and Slovenia. The adopted approach differentiates between equity in HE and inequalities…

Microbial dynamics and biodiversity in table olive fermentation: culture-dependent and -independent approaches

PubMed Central

Botta, Cristian; Cocolin, Luca

2012-01-01

The microbial ecology of the table olive fermentation process is a complex set of dynamics in which the roles of the lactic acid bacteria (LAB) and yeast populations are closely related, and this synergism is of fundamental importance to obtain high quality products. Several studies on the ecology of table olives, both in spontaneous fermentations and in inoculated ones, have focused on the identification and characterization of yeasts, as they play a key role in the definition of the final organoleptic profiles through the production of volatile compounds. Moreover, these are able to promote the growth of LAB, which is responsible for the stabilization of the final product through the acidification activity and the inhibition of the growth of pathogenic bacteria. The current empirical production process of table olives could be improved through the development of mixed starter cultures. These can only be developed after a deep study of the population dynamics of yeasts and LAB by means of molecular methods. Until now, most studies have exploited culture-dependent approaches to define the natural microbiota of brine and olives. These approaches have identified two main species of LAB, namely Lactobacillus plantarum and L. pentosus, while, as far as yeasts are concerned, the most frequently isolated genera are Candida, Pichia, and Saccharomyces. However, there are a few studies in literature in which a culture-independent approach has been employed. This review summarizes the state of the art of the microbial ecology of table olive fermentations and it focuses on the different approaches and molecular methods that have been applied. PMID:22783248

The Dynamics of Opportunity and Threat Management in Turbulent Environments: The Role of Information Technologies

ERIC Educational Resources Information Center

Park, Young Ki

2011-01-01

This study explains the role of information technologies in enabling organizations to successfully sense and manage opportunities and threats and achieve competitive advantage in turbulent environments. I use two approaches, a set-theoretic configurational theory approach and a variance theory approach, which are theoretically and methodologically…

The Teaching-Learning Environment, an Information-Dynamic Approach

ERIC Educational Resources Information Center

De Blasio, Cataldo; Järvinen, Mika

2014-01-01

In the present study a generalized approach is given for the description of acquisition procedures with a particular focus on the knowledge acquisition process. The learning progression is given as an example here letting the theory to be applied to different situations. An analytical approach is performed starting from the generalized fundamental…

Simulating Food Web Dynamics along a Gradient: Quantifying Human Influence

PubMed Central

Jordán, Ferenc; Gjata, Nerta; Mei, Shu; Yule, Catherine M.

2012-01-01

Realistically parameterized and dynamically simulated food-webs are useful tool to explore the importance of the functional diversity of ecosystems, and in particular relations between the dynamics of species and the whole community. We present a stochastic dynamical food web simulation for the Kelian River (Borneo). The food web was constructed for six different locations, arrayed along a gradient of increasing human perturbation (mostly resulting from gold mining activities) along the river. Along the river, the relative importance of grazers, filterers and shredders decreases with increasing disturbance downstream, while predators become more dominant in governing eco-dynamics. Human activity led to increased turbidity and sedimentation which adversely impacts primary productivity. Since the main difference between the study sites was not the composition of the food webs (structure is quite similar) but the strengths of interactions and the abundance of the trophic groups, a dynamical simulation approach seemed to be useful to better explain human influence. In the pristine river (study site 1), when comparing a structural version of our model with the dynamical model we found that structurally central groups such as omnivores and carnivores were not the most important ones dynamically. Instead, primary consumers such as invertebrate grazers and shredders generated a greater dynamical response. Based on the dynamically most important groups, bottom-up control is replaced by the predominant top-down control regime as distance downstream and human disturbance increased. An important finding, potentially explaining the poor structure to dynamics relationship, is that indirect effects are at least as important as direct ones during the simulations. We suggest that our approach and this simulation framework could serve systems-based conservation efforts. Quantitative indicators on the relative importance of trophic groups and the mechanistic modeling of eco-dynamics could greatly contribute to understanding various aspects of functional diversity. PMID:22768346

A coupled human-water system from a systems dynamics perspective

NASA Astrophysics Data System (ADS)

Kuil, Linda; Blöschl, Günter; Carr, Gemma

2013-04-01

Traditionally, models used in hydrological studies have frequently assumed stationarity. Moreover, human-induced water resources management activities are often included as external forcings in water cycle dynamics. However, considering humans' current impact on the water cycle in terms of a growing population, river basins increasingly being managed and a climate considerably changing, it has recently been questioned whether this is still correct. Furthermore, research directed at the evolution of water resources and society has shown that the components constituting the human-water system are changing interdependently. Goal of this study is therefore to approach water cycle dynamics from an integrated perspective in which humans are considered as endogenous forces to the system. The method used to model a coupled, urban human-water system is system dynamics. In system dynamics, particular emphasis is placed on feedback loops resulting in dynamic behavior. Time delays and non-linearity can relatively easily be included, making the method appropriate for studying complex systems that change over time. The approach of this study is as follows. First, a conceptual model is created incorporating the key components of the urban human-water system. Subsequently, only those components are selected that are both relevant and show causal loop behavior. Lastly, the causal narratives are translated into mathematical relationships. The outcome will be a simple model that shows only those characteristics with which we are able to explore the two-way coupling between the societal behavior and the water system we depend on.

Instantaneous Transfer Entropy for the Study of Cardiovascular and Cardiorespiratory Nonstationary Dynamics.

PubMed

Valenza, Gaetano; Faes, Luca; Citi, Luca; Orini, Michele; Barbieri, Riccardo

2018-05-01

Measures of transfer entropy (TE) quantify the direction and strength of coupling between two complex systems. Standard approaches assume stationarity of the observations, and therefore are unable to track time-varying changes in nonlinear information transfer with high temporal resolution. In this study, we aim to define and validate novel instantaneous measures of TE to provide an improved assessment of complex nonstationary cardiorespiratory interactions. We here propose a novel instantaneous point-process TE (ipTE) and validate its assessment as applied to cardiovascular and cardiorespiratory dynamics. In particular, heartbeat and respiratory dynamics are characterized through discrete time series, and modeled with probability density functions predicting the time of the next physiological event as a function of the past history. Likewise, nonstationary interactions between heartbeat and blood pressure dynamics are characterized as well. Furthermore, we propose a new measure of information transfer, the instantaneous point-process information transfer (ipInfTr), which is directly derived from point-process-based definitions of the Kolmogorov-Smirnov distance. Analysis on synthetic data, as well as on experimental data gathered from healthy subjects undergoing postural changes confirms that ipTE, as well as ipInfTr measures are able to dynamically track changes in physiological systems coupling. This novel approach opens new avenues in the study of hidden, transient, nonstationary physiological states involving multivariate autonomic dynamics in cardiovascular health and disease. The proposed method can also be tailored for the study of complex multisystem physiology (e.g., brain-heart or, more in general, brain-body interactions).

Cracks dynamics under tensional stress - a DEM approach

NASA Astrophysics Data System (ADS)

Debski, Wojciech; Klejment, Piotr; Kosmala, Alicja; Foltyn, Natalia; Szpindler, Maciej

2017-04-01

Breaking and fragmentation of solid materials is an extremely complex process involving scales ranging from an atomic scale (breaking inter-atomic bounds) up to thousands of kilometers in case of catastrophic earthquakes (in energy scale it ranges from single eV up to 1024 J). Such a large scale span of breaking processes opens lot of questions like, for example, scaling of breaking processes, existence of factors controlling final size of broken area, existence of precursors, dynamics of fragmentation, to name a few. The classical approach to study breaking process at seismological scales, i.e., physical processes in earthquake foci, is essentially based on two factors: seismic data (mostly) and the continuum mechanics (including the linear fracture mechanics). Such approach has been gratefully successful in developing kinematic (first) and dynamic (recently) models of seismic rupture and explaining many of earthquake features observed all around the globe. However, such approach will sooner or latter face a limitation due to a limited information content of seismic data and inherit limitations of the fracture mechanics principles. A way of avoiding this expected limitation is turning an attention towards a well established in physics method of computational simulations - a powerful branch of contemporary physics. In this presentation we discuss preliminary results of analysis of fracturing dynamics under external tensional forces using the Discrete Element Method approach. We demonstrate that even under a very simplified tensional conditions, the fragmentation dynamics is a very complex process, including multi-fracturing, spontaneous fracture generation and healing, etc. We also emphasis a role of material heterogeneity on the fragmentation process.

A Bottom-Up Approach to Understanding Protein Layer Formation at Solid-Liquid Interfaces

PubMed Central

Kastantin, Mark; Langdon, Blake B.; Schwartz, Daniel K.

2014-01-01

A common goal across different fields (e.g. separations, biosensors, biomaterials, pharmaceuticals) is to understand how protein behavior at solid-liquid interfaces is affected by environmental conditions. Temperature, pH, ionic strength, and the chemical and physical properties of the solid surface, among many factors, can control microscopic protein dynamics (e.g. adsorption, desorption, diffusion, aggregation) that contribute to macroscopic properties like time-dependent total protein surface coverage and protein structure. These relationships are typically studied through a top-down approach in which macroscopic observations are explained using analytical models that are based upon reasonable, but not universally true, simplifying assumptions about microscopic protein dynamics. Conclusions connecting microscopic dynamics to environmental factors can be heavily biased by potentially incorrect assumptions. In contrast, more complicated models avoid several of the common assumptions but require many parameters that have overlapping effects on predictions of macroscopic, average protein properties. Consequently, these models are poorly suited for the top-down approach. Because the sophistication incorporated into these models may ultimately prove essential to understanding interfacial protein behavior, this article proposes a bottom-up approach in which direct observations of microscopic protein dynamics specify parameters in complicated models, which then generate macroscopic predictions to compare with experiment. In this framework, single-molecule tracking has proven capable of making direct measurements of microscopic protein dynamics, but must be complemented by modeling to combine and extrapolate many independent microscopic observations to the macro-scale. The bottom-up approach is expected to better connect environmental factors to macroscopic protein behavior, thereby guiding rational choices that promote desirable protein behaviors. PMID:24484895

A study of the Space Station Freedom response to the disturbance environment

NASA Technical Reports Server (NTRS)

Suleman, Afzal; Modi, V. J.; Venkayya, V. B.

1994-01-01

A relatively general formulation for studying the dynamics and control of an arbitrary spacecraft with interconnected flexible bodies has been developed. This self-contained and comprehensive numerical algorithm using system modes is applicable to a large class of spacecraft configurations of contemporary and future interest. Here, versatility of the approach is demonstrated through the dynamics and control studies aimed at the evolving Space Station Freedom.

Efficient Personalized Mispronunciation Detection of Taiwanese-Accented English Speech Based on Unsupervised Model Adaptation and Dynamic Sentence Selection

ERIC Educational Resources Information Center

Wu, Chung-Hsien; Su, Hung-Yu; Liu, Chao-Hong

2013-01-01

This study presents an efficient approach to personalized mispronunciation detection of Taiwanese-accented English. The main goal of this study was to detect frequently occurring mispronunciation patterns of Taiwanese-accented English instead of scoring English pronunciations directly. The proposed approach quickly identifies personalized…

Dynamics of active sites in biological macromolecules using a Green-function approach: An application to heme vibrational dynamics in myoglobin

NASA Astrophysics Data System (ADS)

Rai, Brajesh; Prohofsky, Earl

2003-03-01

Dynamics of functionally active regions of biological macromolecules can be studied using a Green-function technique. This approach uses the fact that in most cases one has a good set of force constants for active sites, and rather poorly defined force field parameters for other regions of the macromolecule. The Green-function method is applied to study the iron vibrational modes of the heme active site in myoglobin. In this approach, the heme active site is viewed as a system interacting with surrounding globin, which acts as an excitation bath. The normal modes of heme and globin are separately calculated using the best available force fields for the two entities. The iron vibrational spectrum of myoglobin is then obtained using the solutions of the heme and globin, and by considering physically meaningful interactions between the two units. The refinement of the Green-function calculations to the experimental data from an x-ray synchrotron-based Nuclear Resonance Vibrational Spectroscopy provides important insights into the character of iron normal modes of myoglobin.

The implementation of an AR (augmented reality) approach to support mammographic interpretation training: an initial feasibility study

NASA Astrophysics Data System (ADS)

Tang, Qiang; Chen, Yan; Gale, Alastair G.

2017-03-01

Appropriate feedback plays an important role in optimising mammographic interpretation training whilst also ensuring good interpretation performance. The traditional keyboard, mouse and workstation technical approach has a critical limitation in providing supplementary image-related information and providing complex feedback in real time. Augmented Reality (AR) provides a possible superior approach in this situation, as feedback can be provided directly overlaying the displayed mammographic images so making a generic approach which can also be vendor neutral. In this study, radiological feedback was dynamically remapped virtually into the real world, using perspective transformation, in order to provide a richer user experience in mammographic interpretation training. This is an initial attempt of an AR approach to dynamically superimpose pre-defined feedback information of a DICOM image on top of a radiologist's view, whilst the radiologist is examining images on a clinical workstation. The study demonstrates the feasibility of the approach, although there are limitations on interactive operations which are due to the hardware used. The results of this fully functional approach provide appropriate feedback/image correspondence in a simulated mammographic interpretation environment. Thus, it is argued that employing AR is a feasible way to provide rich feedback in the delivery of mammographic interpretation training.

Treating powerless minorities through an ecosystem approach.

PubMed

Chung, W S; Pardeck, J T

1997-01-01

An ecological approach to social work practice for a minority based on an ecosystem-oriented assessment-intervention model is presented. Strengths and limitations of the ecological perspective for practice are emphasized (in the context of power dynamics). A case study is presented.

The Interplay between Language, Gesture, and Affect during Communicative Transition: A Dynamic Systems Approach

ERIC Educational Resources Information Center

Parlade, Meaghan V.; Iverson, Jana M.

2011-01-01

From a dynamic systems perspective, transition points in development are times of increased instability, during which behavioral patterns are susceptible to temporary decoupling. This study investigated the impact of the vocabulary spurt on existing patterns of communicative coordination. Eighteen typically developing infants were videotaped at…

Exploring the effects of temperature and resource limitation on mercury bioaccumulation in Fundulus heteroclitus using dynamic energy budget modeling

EPA Science Inventory

Dynamic energy budget (DEB) theory provides a generalizable and broadly applicable framework to connect sublethal toxic effects on individuals to changes in population survival and growth. To explore this approach, we conducted growth and bioaccumulation studies that contribute t...

Predictability and Coupled Dynamics of MJO During DYNAMO

DTIC Science & Technology

2013-09-30

1 DISTRIBUTION STATEMENT A. Approved for public release; distribution is unlimited. Predictability and Coupled Dynamics of MJO During DYNAMO ...Model (LIM) for MJO predictions and apply it in retrospective cross-validated forecast mode to the DYNAMO time period. APPROACH We are working as...a team to study MJO dynamics and predictability using several models as team members of the ONR DRI associated with the DYNAMO experiment. This is a

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

NASA Technical Reports Server (NTRS)

Hong, Steven W.; Curtiss, H. C., Jr.

1993-01-01

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

An analytic modeling and system identification study of rotor/fuselage dynamics at hover

NASA Technical Reports Server (NTRS)

Hong, Steven W.; Curtiss, H. C., Jr.

1993-01-01

A combination of analytic modeling and system identification methods have been used to develop an improved dynamic model describing the response of articulated rotor helicopters to control inputs. A high-order linearized model of coupled rotor/body dynamics including flap and lag degrees of freedom and inflow dynamics with literal coefficients is compared to flight test data from single rotor helicopters in the near hover trim condition. The identification problem was formulated using the maximum likelihood function in the time domain. The dynamic model with literal coefficients was used to generate the model states, and the model was parametrized in terms of physical constants of the aircraft rather than the stability derivatives, resulting in a significant reduction in the number of quantities to be identified. The likelihood function was optimized using the genetic algorithm approach. This method proved highly effective in producing an estimated model from flight test data which included coupled fuselage/rotor dynamics. Using this approach it has been shown that blade flexibility is a significant contributing factor to the discrepancies between theory and experiment shown in previous studies. Addition of flexible modes, properly incorporating the constraint due to the lag dampers, results in excellent agreement between flight test and theory, especially in the high frequency range.

A novel molecular dynamics approach to evaluate the effect of phosphorylation on multimeric protein interface: the αB-Crystallin case study.

PubMed

Chiappori, Federica; Mattiazzi, Luca; Milanesi, Luciano; Merelli, Ivan

2016-03-02

Phosphorylation is one of the most important post-translational modifications (PTM) employed by cells to regulate several cellular processes. Studying the effects of phosphorylations on protein structures allows to investigate the modulation mechanisms of several proteins including chaperones, like the small HSPs, which display different multimeric structures according to the phosphorylation of a few serine residues. In this context, the proposed study is aimed at finding a method to correlate different PTM patterns (in particular phosphorylations at the monomers interface of multimeric complexes) with the dynamic behaviour of the complex, using physicochemical parameters derived from molecular dynamics simulations in the timescale of nanoseconds. We have developed a methodology relying on computing nine physicochemical parameters, derived from the analysis of short MD simulations, and combined with N identifiers that characterize the PTMs of the analysed protein. The nine general parameters were validated on three proteins, with known post-translational modified conformation and unmodified conformation. Then, we applied this approach to the case study of αB-Crystallin, a chaperone which multimeric state (up to 40 units) is supposed to be controlled by phosphorylation of Ser45 and Ser59. Phosphorylation of serines at the dimer interface induces the release of hexamers, the active state of αB-Crystallin. 30 ns of MD simulation were obtained for each possible combination of dimer phosphorylation state and average values of structural, dynamic, energetic and functional features were calculated on the equilibrated portion of the trajectories. Principal Component Analysis was applied to the parameters and the first five Principal Components, which summed up to 84 % of the total variance, were finally considered. The validation of this approach on multimeric proteins, which structures were known both modified and unmodified, allowed us to propose a new approach that can be used to predict the impact of PTM patterns in multi-modified proteins using data collected from short molecular dynamics simulations. Analysis on the αB-Crystallin case study clusters together all-P dimers with all-P hexamers and no-P dimer with no-P hexamer and results suggest a great influence of Ser59 phosphorylation on chain B.

Peroxisystem: harnessing systems cell biology to study peroxisomes.

PubMed

Schuldiner, Maya; Zalckvar, Einat

2015-04-01

In recent years, high-throughput experimentation with quantitative analysis and modelling of cells, recently dubbed systems cell biology, has been harnessed to study the organisation and dynamics of simple biological systems. Here, we suggest that the peroxisome, a fascinating dynamic organelle, can be used as a good candidate for studying a complete biological system. We discuss several aspects of peroxisomes that can be studied using high-throughput systematic approaches and be integrated into a predictive model. Such approaches can be used in the future to study and understand how a more complex biological system, like a cell and maybe even ultimately a whole organism, works. © 2015 Société Française des Microscopies and Société de Biologie Cellulaire de France. Published by John Wiley & Sons Ltd.

Understanding healthcare innovation systems: the Stockholm region case.

PubMed

Larisch, Lisa-Marie; Amer-Wåhlin, Isis; Hidefjäll, Patrik

2016-11-21

Purpose There is an increasing interest in understanding how innovation processes can address current challenges in healthcare. The purpose of this paper is to analyze the wider socio-economic context and conditions for such innovation processes in the Stockholm region, using the functional dynamics approach to innovation systems (ISs). Design/methodology/approach The analysis is based on triangulation using data from 16 in-depth interviews, two workshops, and additional documents. Using the functional dynamics approach, critical structural and functional components of the healthcare IS were analyzed. Findings The analysis revealed several mechanisms blocking innovation processes such as fragmentation, lack of clear leadership, as well as insufficient involvement of patients and healthcare professionals. Furthermore, innovation is expected to occur linearly as a result of research. Restrictive rules for collaboration with industry, reimbursement, and procurement mechanisms limit entrepreneurial experimentation, commercialization, and spread of innovations. Research limitations/implications In this study, the authors analyzed how certain functions of the functional dynamics approach to ISs related to each other. The authors grouped knowledge creation, resource mobilization, and legitimacy as they jointly constitute conditions for needs articulation and entrepreneurial experimentation. The economic effects of entrepreneurial experimentation and needs articulation are mainly determined by the stage of market formation and existence of positive externalities. Social implications Stronger user involvement; a joint innovation strategy for healthcare, academia, and industry; and institutional reform are necessary to remove blocking mechanisms that today prevent innovation from occurring. Originality/value This study is the first to provide an analysis of the system of innovation in healthcare using a functional dynamics approach, which has evolved as a tool for public policy making. A better understanding of ISs in general, and in healthcare in particular, may provide the basis for designing and evaluating innovation policy.

Knowledge mobilisation for policy development: implementing systems approaches through participatory dynamic simulation modelling.

PubMed

Freebairn, Louise; Rychetnik, Lucie; Atkinson, Jo-An; Kelly, Paul; McDonnell, Geoff; Roberts, Nick; Whittall, Christine; Redman, Sally

2017-10-02

Evidence-based decision-making is an important foundation for health policy and service planning decisions, yet there remain challenges in ensuring that the many forms of available evidence are considered when decisions are being made. Mobilising knowledge for policy and practice is an emergent process, and one that is highly relational, often messy and profoundly context dependent. Systems approaches, such as dynamic simulation modelling can be used to examine both complex health issues and the context in which they are embedded, and to develop decision support tools. This paper reports on the novel use of participatory simulation modelling as a knowledge mobilisation tool in Australian real-world policy settings. We describe how this approach combined systems science methodology and some of the core elements of knowledge mobilisation best practice. We describe the strategies adopted in three case studies to address both technical and socio-political issues, and compile the experiential lessons derived. Finally, we consider the implications of these knowledge mobilisation case studies and provide evidence for the feasibility of this approach in policy development settings. Participatory dynamic simulation modelling builds on contemporary knowledge mobilisation approaches for health stakeholders to collaborate and explore policy and health service scenarios for priority public health topics. The participatory methods place the decision-maker at the centre of the process and embed deliberative methods and co-production of knowledge. The simulation models function as health policy and programme dynamic decision support tools that integrate diverse forms of evidence, including research evidence, expert knowledge and localised contextual information. Further research is underway to determine the impact of these methods on health service decision-making.

Dynamic heterogeneity in the folding/unfolding transitions of FiP35

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

Mori, Toshifumi, E-mail: mori@ims.ac.jp; Saito, Shinji, E-mail: shinji@ims.ac.jp

Molecular dynamics simulations have become an important tool in studying protein dynamics over the last few decades. Atomistic simulations on the order of micro- to milliseconds are becoming feasible and are used to study the state-of-the-art experiments in atomistic detail. Yet, analyzing the high-dimensional-long-temporal trajectory data is still a challenging task and sometimes leads to contradictory results depending on the analyses. To reveal the dynamic aspect of the trajectory, here we propose a simple approach which uses a time correlation function matrix and apply to the folding/unfolding trajectory of FiP35 WW domain [Shaw et al., Science 330, 341 (2010)]. Themore » approach successfully characterizes the slowest mode corresponding to the folding/unfolding transitions and determines the free energy barrier indicating that FiP35 is not an incipient downhill folder. The transition dynamics analysis further reveals that the folding/unfolding transition is highly heterogeneous, e.g., the transition path time varies by ∼100 fold. We identify two misfolded states and show that the dynamic heterogeneity in the folding/unfolding transitions originates from the trajectory being trapped in the misfolded and half-folded intermediate states rather than the diffusion driven by a thermal noise. The current results help reconcile the conflicting interpretations of the folding mechanism and highlight the complexity in the folding dynamics. This further motivates the need to understand the transition dynamics beyond a simple free energy picture using simulations and single-molecule experiments.« less

Integrating dynamic stereo-radiography and surface-based motion data for subject-specific musculoskeletal dynamic modeling.

PubMed

Zheng, Liying; Li, Kang; Shetye, Snehal; Zhang, Xudong

2014-09-22

This manuscript presents a new subject-specific musculoskeletal dynamic modeling approach that integrates high-accuracy dynamic stereo-radiography (DSX) joint kinematics and surface-based full-body motion data. We illustrate this approach by building a model in OpenSim for a patient who participated in a meniscus transplantation efficacy study, incorporating DSX data of the tibiofemoral joint kinematics. We compared this DSX-incorporated (DSXI) model to a default OpenSim model built using surface-measured data alone. The architectures and parameters of the two models were identical, while the differences in (time-averaged) tibiofemoral kinematics were of the order of magnitude of 10° in rotation and 10mm in translation. Model-predicted tibiofemoral compressive forces and knee muscle activations were compared against literature data acquired from instrumented total knee replacement components (Fregly et al., 2012) and the patient's EMG recording. The comparison demonstrated that the incorporation of DSX data improves the veracity of musculoskeletal dynamic modeling. Copyright © 2014 Elsevier Ltd. All rights reserved.

Integrating dynamic stereo-radiography and surface-based motion data for subject-specific musculoskeletal dynamic modeling

PubMed Central

Zheng, Liying; Li, Kang; Shetye, Snehal; Zhang, Xudong

2014-01-01

This paper presents a new subject-specific musculoskeletal dynamic modeling approach that integrates high-accuracy dynamic stereo-radiography (DSX) joint kinematics and surface-based full-body motion data. We illustrate this approach by building a model in OpenSim for a patient who participated in a meniscus transplantation efficacy study, incorporating DSX data of the tibiofemoral joint kinematics. We compared this DSX-incorporated (DSXI) model to a default OpenSim model built using surface-measured data alone. The architectures and parameters of the two models were identical, while the differences in (time-averaged) tibiofemoral kinematics were of the order of magnitude of 10° in rotation and 10 mm in translation. Model-predicted tibiofemoral compressive forces and knee muscle activations were compared against literature data acquired from instrumented total knee replacement components (Fregly et al., 2012) and the patient's EMG recording. The comparison demonstrated that the incorporation of DSX data improves the veracity of musculoskeletal dynamic modeling. PMID:25169658

Conformational ensembles of RNA oligonucleotides from integrating NMR and molecular simulations.

PubMed

Bottaro, Sandro; Bussi, Giovanni; Kennedy, Scott D; Turner, Douglas H; Lindorff-Larsen, Kresten

2018-05-01

RNA molecules are key players in numerous cellular processes and are characterized by a complex relationship between structure, dynamics, and function. Despite their apparent simplicity, RNA oligonucleotides are very flexible molecules, and understanding their internal dynamics is particularly challenging using experimental data alone. We show how to reconstruct the conformational ensemble of four RNA tetranucleotides by combining atomistic molecular dynamics simulations with nuclear magnetic resonance spectroscopy data. The goal is achieved by reweighting simulations using a maximum entropy/Bayesian approach. In this way, we overcome problems of current simulation methods, as well as in interpreting ensemble- and time-averaged experimental data. We determine the populations of different conformational states by considering several nuclear magnetic resonance parameters and point toward properties that are not captured by state-of-the-art molecular force fields. Although our approach is applied on a set of model systems, it is fully general and may be used to study the conformational dynamics of flexible biomolecules and to detect inaccuracies in molecular dynamics force fields.

Influence of the leaving group on the dynamics of a gas-phase SN2 reaction

NASA Astrophysics Data System (ADS)

Stei, Martin; Carrascosa, Eduardo; Kainz, Martin A.; Kelkar, Aditya H.; Meyer, Jennifer; Szabó, István; Czakó, Gábor; Wester, Roland

2016-02-01

In addition to the nucleophile and solvent, the leaving group has a significant influence on SN2 nucleophilic substitution reactions. Its role is frequently discussed with respect to reactivity, but its influence on the reaction dynamics remains unclear. Here, we uncover the influence of the leaving group on the gas-phase dynamics of SN2 reactions in a combined approach of crossed-beam imaging and dynamics simulations. We have studied the reaction F- + CH3Cl and compared it to F- + CH3I. For the two leaving groups, Cl and I, we find very similar structures and energetics, but the dynamics show qualitatively different features. Simple scaling of the leaving group mass does not explain these differences. Instead, the relevant impact parameters for the reaction mechanisms are found to be crucial and the differences are attributed to the relative orientation of the approaching reactants. This effect occurs on short timescales and may also prevail in solution-phase conditions.

Influence of the leaving group on the dynamics of a gas-phase SN2 reaction.

PubMed

Stei, Martin; Carrascosa, Eduardo; Kainz, Martin A; Kelkar, Aditya H; Meyer, Jennifer; Szabó, István; Czakó, Gábor; Wester, Roland

2016-02-01

In addition to the nucleophile and solvent, the leaving group has a significant influence on SN2 nucleophilic substitution reactions. Its role is frequently discussed with respect to reactivity, but its influence on the reaction dynamics remains unclear. Here, we uncover the influence of the leaving group on the gas-phase dynamics of SN2 reactions in a combined approach of crossed-beam imaging and dynamics simulations. We have studied the reaction F(-) + CH3Cl and compared it to F(-) + CH3I. For the two leaving groups, Cl and I, we find very similar structures and energetics, but the dynamics show qualitatively different features. Simple scaling of the leaving group mass does not explain these differences. Instead, the relevant impact parameters for the reaction mechanisms are found to be crucial and the differences are attributed to the relative orientation of the approaching reactants. This effect occurs on short timescales and may also prevail in solution-phase conditions.

Value for money - recasting the problem in terms of dynamic access prioritisation.

PubMed

Taylor, William J; Laking, George

2010-01-01

To develop an approach for achieving value for money in rehabilitation based on dynamic prioritisation of access to services according to individual capacity to benefit. A critical review of economic evaluation and adaptation of a prioritisation method used in determining access to elective surgical services in New Zealand to a rehabilitation context. The cost-effectiveness frontier is not straight but curved, suggesting that some people benefit more from a given intervention than others. An approach that identifies those most likely to benefit from inpatient rehabilitation following stroke (as an example) and enables access in order of capacity to benefit is presented in the context of a quality improvement programme. The approach is operationalised as a prioritisation tool that is dynamic in the sense that is can be reapplied subject to changes in the patient's clinical status. The steps proposed to develop such a tool include qualitative research with expert clinicians, pair-wise comparison of alternative scenarios (1000Minds survey), construction of an economic model of the tool's operation and an observational cohort study to help populate the model and calibrate the tool. A dynamic prioritisation approach to guide access to scarce health-care resources (such as inpatient rehabilitation following stroke) offers a transparent and equitable way of achieving value for money in the delivery of rehabilitation services.

An investigation of emotion dynamics in major depressive disorder patients and healthy persons using sparse longitudinal networks.

PubMed

de Vos, Stijn; Wardenaar, Klaas J; Bos, Elisabeth H; Wit, Ernst C; Bouwmans, Mara E J; de Jonge, Peter

2017-01-01

Differences in within-person emotion dynamics may be an important source of heterogeneity in depression. To investigate these dynamics, researchers have previously combined multilevel regression analyses with network representations. However, sparse network methods, specifically developed for longitudinal network analyses, have not been applied. Therefore, this study used this approach to investigate population-level and individual-level emotion dynamics in healthy and depressed persons and compared this method with the multilevel approach. Time-series data were collected in pair-matched healthy persons and major depressive disorder (MDD) patients (n = 54). Seven positive affect (PA) and seven negative affect (NA) items were administered electronically at 90 times (30 days; thrice per day). The population-level (healthy vs. MDD) and individual-level time series were analyzed using a sparse longitudinal network model based on vector autoregression. The population-level model was also estimated with a multilevel approach. Effects of different preprocessing steps were evaluated as well. The characteristics of the longitudinal networks were investigated to gain insight into the emotion dynamics. In the population-level networks, longitudinal network connectivity was strongest in the healthy group, with nodes showing more and stronger longitudinal associations with each other. Individually estimated networks varied strongly across individuals. Individual variations in network connectivity were unrelated to baseline characteristics (depression status, neuroticism, severity). A multilevel approach applied to the same data showed higher connectivity in the MDD group, which seemed partly related to the preprocessing approach. The sparse network approach can be useful for the estimation of networks with multiple nodes, where overparameterization is an issue, and for individual-level networks. However, its current inability to model random effects makes it less useful as a population-level approach in case of large heterogeneity. Different preprocessing strategies appeared to strongly influence the results, complicating inferences about network density.

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.

Mixed state dynamical quantum phase transitions

NASA Astrophysics Data System (ADS)

Bhattacharya, Utso; Bandyopadhyay, Souvik; Dutta, Amit

2017-11-01

Preparing an integrable system in a mixed state described by a thermal density matrix, we subject it to a sudden quench and explore the subsequent unitary dynamics. To address the question of whether the nonanalyticities, namely, the dynamical quantum phase transitions (DQPTs), persist when the initial state is mixed, we consider two versions of the generalized Loschmidt overlap amplitude (GLOA). Our study shows that the GLOA constructed using the Uhlmann approach does not show any signature of DQPTs at any nonzero initial temperature. On the other hand, a GLOA defined in the interferometric phase approach through the purifications of the time-evolved density matrix, indeed shows that nonanalyiticies in the corresponding "dynamical free-energy density" persist, thereby establishing the existence of mixed state dynamical quantum phase transitions (MSDQPTs). Our work provides a framework that perfectly reproduces both the nonanalyticities and also the emergent topological structure in the pure state limit. These claims are corroborated by analyzing the nonequilibrium dynamics of a transverse Ising chain initially prepared in a thermal state and subjected to a sudden quench of the transverse field.

Obesity prevention: Comparison of techniques and potential solution

NASA Astrophysics Data System (ADS)

Zulkepli, Jafri; Abidin, Norhaslinda Zainal; Zaibidi, Nerda Zura

2014-12-01

Over the years, obesity prevention has been a broadly studied subject by both academicians and practitioners. It is one of the most serious public health issue as it can cause numerous chronic health and psychosocial problems. Research is needed to suggest a population-based strategy for obesity prevention. In the academic environment, the importance of obesity prevention has triggered various problem solving approaches. A good obesity prevention model, should comprehend and cater all complex and dynamics issues. Hence, the main purpose of this paper is to discuss the qualitative and quantitative approaches on obesity prevention study and to provide an extensive literature review on various recent modelling techniques for obesity prevention. Based on these literatures, the comparison of both quantitative and qualitative approahes are highlighted and the justification on the used of system dynamics technique to solve the population of obesity is discussed. Lastly, a potential framework solution based on system dynamics modelling is proposed.

Multidimensional joint coupling: a case study visualisation approach to movement coordination and variability.

PubMed

Irwin, Gareth; Kerwin, David G; Williams, Genevieve; Van Emmerik, Richard E A; Newell, Karl M; Hamill, Joseph

2018-06-18

A case study visualisation approach to examining the coordination and variability of multiple interacting segments is presented using a whole-body gymnastic skill as the task example. One elite male gymnast performed 10 trials of 10 longswings whilst three-dimensional locations of joint centres were tracked using a motion analysis system. Segment angles were used to define coupling between the arms and trunk, trunk and thighs and thighs and shanks. Rectified continuous relative phase profiles for each interacting couple for 80 longswings were produced. Graphical representations of coordination couplings are presented that include the traditional single coupling, followed by the relational dynamics of two couplings and finally three couplings simultaneously plotted. This method highlights the power of visualisation of movement dynamics and identifies properties of the global interacting segmental couplings that a more formal analysis may not reveal. Visualisation precedes and informs the appropriate qualitative and quantitative analysis of the dynamics.

Common cold outbreaks: A network theory approach

NASA Astrophysics Data System (ADS)

Vishkaie, Faranak Rajabi; Bakouie, Fatemeh; Gharibzadeh, Shahriar

2014-11-01

In this study, at first we evaluated the network structure in social encounters by which respiratory diseases can spread. We considered common-cold and recorded a sample of human population and actual encounters between them. Our results show that the database structure presents a great value of clustering. In the second step, we evaluated dynamics of disease spread with SIR model by assigning a function to each node of the structural network. The rate of disease spread in networks was observed to be inversely correlated with characteristic path length. Therefore, the shortcuts have a significant role in increasing spread rate. We conclude that the dynamics of social encounters' network stands between the random and the lattice in network spectrum. Although in this study we considered the period of common-cold disease for network dynamics, it seems that similar approaches may be useful for other airborne diseases such as SARS.

Dynamic analysis for solid waste management systems: an inexact multistage integer programming approach.

PubMed

Li, Yongping; Huang, Guohe

2009-03-01

In this study, a dynamic analysis approach based on an inexact multistage integer programming (IMIP) model is developed for supporting municipal solid waste (MSW) management under uncertainty. Techniques of interval-parameter programming and multistage stochastic programming are incorporated within an integer-programming framework. The developed IMIP can deal with uncertainties expressed as probability distributions and interval numbers, and can reflect the dynamics in terms of decisions for waste-flow allocation and facility-capacity expansion over a multistage context. Moreover, the IMIP can be used for analyzing various policy scenarios that are associated with different levels of economic consequences. The developed method is applied to a case study of long-term waste-management planning. The results indicate that reasonable solutions have been generated for binary and continuous variables. They can help generate desired decisions of system-capacity expansion and waste-flow allocation with a minimized system cost and maximized system reliability.

Optimal control of underactuated mechanical systems: A geometric approach

NASA Astrophysics Data System (ADS)

Colombo, Leonardo; Martín De Diego, David; Zuccalli, Marcela

2010-08-01

In this paper, we consider a geometric formalism for optimal control of underactuated mechanical systems. Our techniques are an adaptation of the classical Skinner and Rusk approach for the case of Lagrangian dynamics with higher-order constraints. We study a regular case where it is possible to establish a symplectic framework and, as a consequence, to obtain a unique vector field determining the dynamics of the optimal control problem. These developments will allow us to develop a new class of geometric integrators based on discrete variational calculus.

Space construction base control system

NASA Technical Reports Server (NTRS)

Kaczynski, R. F.

1979-01-01

Several approaches for an attitude control system are studied and developed for a large space construction base that is structurally flexible. Digital simulations were obtained using the following techniques: (1) the multivariable Nyquist array method combined with closed loop pole allocation, (2) the linear quadratic regulator method. Equations for the three-axis simulation using the multilevel control method were generated and are presented. Several alternate control approaches are also described. A technique is demonstrated for obtaining the dynamic structural properties of a vehicle which is constructed of two or more submodules of known dynamic characteristics.

Inverse transformation: unleashing spatially heterogeneous dynamics with an alternative approach to XPCS data analysis

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

Andrews, Ross N.; Narayanan, Suresh; Zhang, Fan

X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering-vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables XPCS to probe the dynamics in a broad array of materials, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fail. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. This paper proposes an alternative analysis schememore » based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. In conclusion, using XPCS data measured from colloidal gels, it is demonstrated that the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS.« less

A phenomenological approach to modeling chemical dynamics in nonlinear and two-dimensional spectroscopy.

PubMed

Ramasesha, Krupa; De Marco, Luigi; Horning, Andrew D; Mandal, Aritra; Tokmakoff, Andrei

2012-04-07

We present an approach for calculating nonlinear spectroscopic observables, which overcomes the approximations inherent to current phenomenological models without requiring the computational cost of performing molecular dynamics simulations. The trajectory mapping method uses the semi-classical approximation to linear and nonlinear response functions, and calculates spectra from trajectories of the system's transition frequencies and transition dipole moments. It rests on identifying dynamical variables important to the problem, treating the dynamics of these variables stochastically, and then generating correlated trajectories of spectroscopic quantities by mapping from the dynamical variables. This approach allows one to describe non-Gaussian dynamics, correlated dynamics between variables of the system, and nonlinear relationships between spectroscopic variables of the system and the bath such as non-Condon effects. We illustrate the approach by applying it to three examples that are often not adequately treated by existing analytical models--the non-Condon effect in the nonlinear infrared spectra of water, non-Gaussian dynamics inherent to strongly hydrogen bonded systems, and chemical exchange processes in barrier crossing reactions. The methods described are generally applicable to nonlinear spectroscopy throughout the optical, infrared and terahertz regions.

Inverse transformation: unleashing spatially heterogeneous dynamics with an alternative approach to XPCS data analysis

DOE PAGES

Andrews, Ross N.; Narayanan, Suresh; Zhang, Fan; ...

2018-02-01

X-ray photon correlation spectroscopy (XPCS), an extension of dynamic light scattering (DLS) in the X-ray regime, detects temporal intensity fluctuations of coherent speckles and provides scattering-vector-dependent sample dynamics at length scales smaller than DLS. The penetrating power of X-rays enables XPCS to probe the dynamics in a broad array of materials, including polymers, glasses and metal alloys, where attempts to describe the dynamics with a simple exponential fit usually fail. In these cases, the prevailing XPCS data analysis approach employs stretched or compressed exponential decay functions (Kohlrausch functions), which implicitly assume homogeneous dynamics. This paper proposes an alternative analysis schememore » based upon inverse Laplace or Gaussian transformation for elucidating heterogeneous distributions of dynamic time scales in XPCS, an approach analogous to the CONTIN algorithm widely accepted in the analysis of DLS from polydisperse and multimodal systems. In conclusion, using XPCS data measured from colloidal gels, it is demonstrated that the inverse transform approach reveals hidden multimodal dynamics in materials, unleashing the full potential of XPCS.« less

Investigating Conversational Dynamics: Interactive Alignment, Interpersonal Synergy, and Collective Task Performance

ERIC Educational Resources Information Center

Fusaroli, Riccardo; Tylén, Kristian

2016-01-01

This study investigates interpersonal processes underlying dialog by comparing two approaches, "interactive alignment" and "interpersonal synergy", and assesses how they predict collective performance in a joint task. While the interactive alignment approach highlights imitative patterns between interlocutors, the synergy…

The Conceptual Change Approach to Teaching Chemical Equilibrium

ERIC Educational Resources Information Center

Canpolat, Nurtac; Pinarbasi, Tacettin; Bayrakceken, Samih; Geban, Omer

2006-01-01

This study investigates the effect of a conceptual change approach over traditional instruction on students' understanding of chemical equilibrium concepts (e.g. dynamic nature of equilibrium, definition of equilibrium constant, heterogeneous equilibrium, qualitative interpreting of equilibrium constant, changing the reaction conditions). This…

Structural Transformation Detection Contributes to Screening of Behaviorally Active Compounds: Dynamic Binding Process Analysis of DhelOBP21 from Dastarcus helophoroides.

PubMed

Yang, Rui-Nan; Li, Dong-Zhen; Yu, Guangqiang; Yi, Shan-Cheng; Zhang, Yinan; Kong, De-Xin; Wang, Man-Qun

2017-12-01

In light of reverse chemical ecology, the fluorescence competitive binding assays of functional odorant binding proteins (OBPs) is a recent advanced approach for screening behaviorally active compounds of insects. Previous research on Dastareus helophoroides identified a minus-C OBP, DhelOBP21, which preferably binds to several ligands. In this study, only (+)-β-pinene proved attractive to unmated adult beetles. To obtain a more in-depth explanation of the lack of behavioral activity of other ligands we selected compounds with high (camphor) and low (β-caryophyllene) binding affinities. The structural transformation of OBPs was investigated using well-established approaches for studying binding processes, such as fluorescent quenching assays, circular dichroism, and molecular dynamics. The dynamic binding process revealed that the flexibility of DhelOBP21 seems conducive to binding specific ligands, as opposed to broad substrate binding. The compound (+)-β-pinene and DhelOBP21 formed a stable complex through a secondary structural transformation of DhelOBP21, in which its amino-terminus transformed from random coil to an α-helix to cover the binding pocket. On the other hand, camphor could not efficiently induce a stable structural transformation, and its high binding affinities were due to strong hydrogen-bonding, compromising the structure of the protein. The other compound, β-caryophyllene, only collided with DhelOBP21 and could not be positioned in the binding pocket. Studying structural transformation of these proteins through examining the dynamic binding process rather than using approaches that just measure binding affinities such as fluorescence competitive binding assays can provide a more efficient and reliable approach for screening behaviorally active compounds.

Quasistationary areas of NDVI trend dynamics is a powerful research tool for studying spatial patterns of land vegetation

NASA Astrophysics Data System (ADS)

Shevyrnogov, Anatoly; Larko, Aleksandr

The most important task for humankind is to study and understand global processes on Earth. Large factual material on the dynamics of the optical spectral characteristics of the land surface has been accumulated in recent decades. This has been only made possible due to the use of satellite information. The development of satellite measurement technologies and new methods for pre-processing and interpretation of satellite data allowed the research adequate to the scale of the Earth. This adequacy includes the compliance of scale terrestrial objects to the scale of satellite measurements. Research is not limited by any latitude or longitude of the objects studied. The second most important quality is the adequacy of the technologies used to velocities of processes on Earth. This is enabled by long-term continuous satellite measurements at almost all latitudes. Effectiveness of this approach to the study of natural systems has been shown by the authors in ASR publications (AP Shevyrnogov, GS Vysotskaya, JI Gitelson, Quasistationary areas of chlorophyll concentration in the world ocean as observed satellite data Advances in Space Research, Volume 18, Issue 7, Pages 129-132, 1996), which reported a method for determining the ocean surface quasistationary zones. This approach allowed us to identify different types of phytopigment dynamics and the hydrological structure of the ocean. We proposed a similar approach for the study of land vegetation. In some aspects, it is similar to the previously published approach, despite the different nature of terrestrial and aquatic ecosystems. The results are based on the processing of satellite data from 1981 to 2006. Dynamics is the most interesting and important parameter of ecosystems, especially their trends. Therefore, it has been chosen for the analysis of spatial patterns of plant biota. The first results showed great heterogeneity of variances in nonlinear trends of the study areas of the Earth's surface. They corresponded to different natural systems. Various scales of temporal and spatial windows highlight different features of land vegetation. Methods for normalization of the initial information are also effective for highlighting the features of the spatial structure of vegetation. Thus, we have a powerful tool to analyze the spatial distribution and dynamics of terrestrial vegetation based on satellite data. This approach provides a great opportunity to get fundamental knowledge on the functioning of the biosphere. This is global warming, shifts in permafrost boundaries, global gas exchange, etc. It can be used for practical applications in various fields of human activity: forestry, environmental protection, agriculture, etc. We show the illustration of this method: the global maps of land surface dynamics of trends with different parameters of data processing.

E-Learning Personalization Using Triple-Factor Approach in Standard-Based Education

NASA Astrophysics Data System (ADS)

Laksitowening, K. A.; Santoso, H. B.; Hasibuan, Z. A.

2017-01-01

E-Learning can be a tool in monitoring learning process and progress towards the targeted competency. Process and progress on every learner can be different one to another, since every learner may have different learning type. Learning type itself can be identified by taking into account learning style, motivation, and knowledge ability. This study explores personalization for learning type based on Triple-Factor Approach. Considering that factors in Triple-Factor Approach are dynamic, the personalization system needs to accommodate the changes that may occurs. Originated from the issue, this study proposed personalization that guides learner progression dynamically towards stages of their learning process. The personalization is implemented in the form of interventions that trigger learner to access learning contents and discussion forums more often as well as improve their level of knowledge ability based on their state of learning type.

Time Series Expression Analyses Using RNA-seq: A Statistical Approach

PubMed Central

Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P.

2013-01-01

RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis. PMID:23586021

Time series expression analyses using RNA-seq: a statistical approach.

PubMed

Oh, Sunghee; Song, Seongho; Grabowski, Gregory; Zhao, Hongyu; Noonan, James P

2013-01-01

RNA-seq is becoming the de facto standard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis.

Single walled boron nitride nanotube-based biosensor: an atomistic finite element modelling approach.

PubMed

Panchal, Mitesh B; Upadhyay, Sanjay H

2014-09-01

The unprecedented dynamic characteristics of nanoelectromechanical systems make them suitable for nanoscale mass sensing applications. Owing to superior biocompatibility, boron nitride nanotubes (BNNTs) are being increasingly used for such applications. In this study, the feasibility of single walled BNNT (SWBNNT)-based bio-sensor has been explored. Molecular structural mechanics-based finite element (FE) modelling approach has been used to analyse the dynamic behaviour of SWBNNT-based biosensors. The application of an SWBNNT-based mass sensing for zeptogram level of mass has been reported. Also, the effect of size of the nanotube in terms of length as well as different chiral atomic structures of SWBNNT has been analysed for their sensitivity analysis. The vibrational behaviour of SWBNNT has been analysed for higher-order modes of vibrations to identify the intermediate landing position of biological object of zeptogram scale. The present molecular structural mechanics-based FE modelling approach is found to be very effectual to incorporate different chiralities of the atomic structures. Also, different boundary conditions can be effectively simulated using the present approach to analyse the dynamic behaviour of the SWBNNT-based mass sensor. The presented study has explored the potential of SWBNNT, as a nanobiosensor having the capability of zeptogram level mass sensing.

Dynamic Emulation Modelling (DEMo) of large physically-based environmental models

NASA Astrophysics Data System (ADS)

Galelli, S.; Castelletti, A.

2012-12-01

In environmental modelling large, spatially-distributed, physically-based models are widely adopted to describe the dynamics of physical, social and economic processes. Such an accurate process characterization comes, however, to a price: the computational requirements of these models are considerably high and prevent their use in any problem requiring hundreds or thousands of model runs to be satisfactory solved. Typical examples include optimal planning and management, data assimilation, inverse modelling and sensitivity analysis. An effective approach to overcome this limitation is to perform a top-down reduction of the physically-based model by identifying a simplified, computationally efficient emulator, constructed from and then used in place of the original model in highly resource-demanding tasks. The underlying idea is that not all the process details in the original model are equally important and relevant to the dynamics of the outputs of interest for the type of problem considered. Emulation modelling has been successfully applied in many environmental applications, however most of the literature considers non-dynamic emulators (e.g. metamodels, response surfaces and surrogate models), where the original dynamical model is reduced to a static map between input and the output of interest. In this study we focus on Dynamic Emulation Modelling (DEMo), a methodological approach that preserves the dynamic nature of the original physically-based model, with consequent advantages in a wide variety of problem areas. In particular, we propose a new data-driven DEMo approach that combines the many advantages of data-driven modelling in representing complex, non-linear relationships, but preserves the state-space representation typical of process-based models, which is both particularly effective in some applications (e.g. optimal management and data assimilation) and facilitates the ex-post physical interpretation of the emulator structure, thus enhancing the credibility of the model to stakeholders and decision-makers. Numerical results from the application of the approach to the reduction of 3D coupled hydrodynamic-ecological models in several real world case studies, including Marina Reservoir (Singapore) and Googong Reservoir (Australia), are illustrated.

A comprehensive inversion approach for feedforward compensation of piezoactuator system at high frequency

NASA Astrophysics Data System (ADS)

Tian, Lizhi; Xiong, Zhenhua; Wu, Jianhua; Ding, Han

2016-09-01

Motion control of the piezoactuator system over broadband frequencies is limited due to its inherent hysteresis and system dynamics. One of the suggested ways is to use feedforward controller to linearize the input-output relationship of the piezoactuator system. Although there have been many feedforward approaches, it is still a challenge to develop feedforward controller for the piezoactuator system at high frequency. Hence, this paper presents a comprehensive inversion approach in consideration of the coupling of hysteresis and dynamics. In this work, the influence of dynamics compensation on the input-output relationship of the piezoactuator system is investigated first. With system dynamics compensation, the input-output relationship of the piezoactuator system will be further represented as rate-dependent nonlinearity due to the inevitable dynamics compensation error, especially at high frequency. Base on this result, the feedforward controller composed by a cascade of linear dynamics inversion and rate-dependent nonlinearity inversion is developed. Then, the system identification of the comprehensive inversion approach is proposed. Finally, experimental results show that the proposed approach can improve the performance on tracking of both periodic and non-periodic trajectories at medium and high frequency compared with the conventional feedforward approaches.

Model-Based Prognostics of Hybrid Systems

NASA Technical Reports Server (NTRS)

Daigle, Matthew; Roychoudhury, Indranil; Bregon, Anibal

2015-01-01

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

First-Principles Lattice Dynamics Method for Strongly Anharmonic Crystals

NASA Astrophysics Data System (ADS)

Tadano, Terumasa; Tsuneyuki, Shinji

2018-04-01

We review our recent development of a first-principles lattice dynamics method that can treat anharmonic effects nonperturbatively. The method is based on the self-consistent phonon theory, and temperature-dependent phonon frequencies can be calculated efficiently by incorporating recent numerical techniques to estimate anharmonic force constants. The validity of our approach is demonstrated through applications to cubic strontium titanate, where overall good agreement with experimental data is obtained for phonon frequencies and lattice thermal conductivity. We also show the feasibility of highly accurate calculations based on a hybrid exchange-correlation functional within the present framework. Our method provides a new way of studying lattice dynamics in severely anharmonic materials where the standard harmonic approximation and the perturbative approach break down.

Numeric, Agent-based or System Dynamics Model? Which Modeling Approach is the Best for Vast Population Simulation?

PubMed

Cimler, Richard; Tomaskova, Hana; Kuhnova, Jitka; Dolezal, Ondrej; Pscheidl, Pavel; Kuca, Kamil

2018-01-01

Alzheimer's disease is one of the most common mental illnesses. It is posited that more than 25% of the population is affected by some mental disease during their lifetime. Treatment of each patient draws resources from the economy concerned. Therefore, it is important to quantify the potential economic impact. Agent-based, system dynamics and numerical approaches to dynamic modeling of the population of the European Union and its patients with Alzheimer's disease are presented in this article. Simulations, their characteristics, and the results from different modeling tools are compared. The results of these approaches are compared with EU population growth predictions from the statistical office of the EU by Eurostat. The methodology of a creation of the models is described and all three modeling approaches are compared. The suitability of each modeling approach for the population modeling is discussed. In this case study, all three approaches gave us the results corresponding with the EU population prediction. Moreover, we were able to predict the number of patients with AD and, based on the modeling method, we were also able to monitor different characteristics of the population. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Cortical oscillatory dynamics in a social interaction model.

PubMed

Knyazev, Gennady G; Slobodskoj-Plusnin, Jaroslav Y; Bocharov, Andrey V; Pylkova, Liudmila V

2013-03-15

In this study we sought to investigate cortical oscillatory dynamics accompanying three major kinds of social behavior: aggressive, friendly, and avoidant. Behavioral and EEG data were collected in 48 participants during a computer game modeling social interactions with virtual 'persons'. 3D source reconstruction and independent component analysis were applied to EEG data. Results showed that social behavior was partly reactive and partly proactive with subject's personality playing an important role in shaping this behavior. Most salient differences were found between avoidance and approach behaviors, whereas the two kinds of approach behavior (i.e., aggression and friendship) did not differ from each other. Comparative to avoidance, approach behaviors were associated with higher induced responses in most frequency bands which were mostly observed in cortical areas overlapping with the default mode network. The difference between approach- and avoidance-related oscillatory dynamics was more salient in subjects predisposed to approach behaviors (i.e., in aggressive or sociable subjects) and was less pronounced in subjects predisposed to avoidance behavior (i.e., in high trait anxiety scorers). There was a trend to higher low frequency phase-locking in motor area in approach than in avoid condition. Results are discussed in light of the concept linking induced responses with top-down and evoked responses with bottom-up processes. Copyright © 2012 Elsevier B.V. All rights reserved.

Market Orientation within University Schools of Business: Can a Dynamical Systems Viewpoint Applied to a Non-Temporal Data Set Yield Valuable Insights for University Managers?

ERIC Educational Resources Information Center

Cox, John C.; Webster, Robert L.; Hammond, Kevin L.

2009-01-01

This study investigates the use of using complexity theory--the study of nonlinear dynamical systems of which chaos and catastrophe theory are subsets--in the analysis of a non temporal data set to derive valuable insights into the functioning of university schools of business. The approach is unusual in that studies of nonlinearity in complex…

Dynamic performance of maximum power point tracking circuits using sinusoidal extremum seeking control for photovoltaic generation

NASA Astrophysics Data System (ADS)

Leyva, R.; Artillan, P.; Cabal, C.; Estibals, B.; Alonso, C.

2011-04-01

The article studies the dynamic performance of a family of maximum power point tracking circuits used for photovoltaic generation. It revisits the sinusoidal extremum seeking control (ESC) technique which can be considered as a particular subgroup of the Perturb and Observe algorithms. The sinusoidal ESC technique consists of adding a small sinusoidal disturbance to the input and processing the perturbed output to drive the operating point at its maximum. The output processing involves a synchronous multiplication and a filtering stage. The filter instance determines the dynamic performance of the MPPT based on sinusoidal ESC principle. The approach uses the well-known root-locus method to give insight about damping degree and settlement time of maximum-seeking waveforms. This article shows the transient waveforms in three different filter instances to illustrate the approach. Finally, an experimental prototype corroborates the dynamic analysis.

Modeling of Receptor Tyrosine Kinase Signaling: Computational and Experimental Protocols.

PubMed

Fey, Dirk; Aksamitiene, Edita; Kiyatkin, Anatoly; Kholodenko, Boris N

2017-01-01

The advent of systems biology has convincingly demonstrated that the integration of experiments and dynamic modelling is a powerful approach to understand the cellular network biology. Here we present experimental and computational protocols that are necessary for applying this integrative approach to the quantitative studies of receptor tyrosine kinase (RTK) signaling networks. Signaling by RTKs controls multiple cellular processes, including the regulation of cell survival, motility, proliferation, differentiation, glucose metabolism, and apoptosis. We describe methods of model building and training on experimentally obtained quantitative datasets, as well as experimental methods of obtaining quantitative dose-response and temporal dependencies of protein phosphorylation and activities. The presented methods make possible (1) both the fine-grained modeling of complex signaling dynamics and identification of salient, course-grained network structures (such as feedback loops) that bring about intricate dynamics, and (2) experimental validation of dynamic models.

Dynamic tire pressure sensor for measuring ground vibration.

PubMed

Wang, Qi; McDaniel, James Gregory; Wang, Ming L

2012-11-07

This work presents a convenient and non-contact acoustic sensing approach for measuring ground vibration. This approach, which uses an instantaneous dynamic tire pressure sensor (DTPS), possesses the capability to replace the accelerometer or directional microphone currently being used for inspecting pavement conditions. By measuring dynamic pressure changes inside the tire, ground vibration can be amplified and isolated from environmental noise. In this work, verifications of the DTPS concept of sensing inside the tire have been carried out. In addition, comparisons between a DTPS, ground-mounted accelerometer, and directional microphone are made. A data analysis algorithm has been developed and optimized to reconstruct ground acceleration from DTPS data. Numerical and experimental studies of this DTPS reveal a strong potential for measuring ground vibration caused by a moving vehicle. A calibration of transfer function between dynamic tire pressure change and ground acceleration may be needed for different tire system or for more accurate application.

The modern temperature-accelerated dynamics approach

DOE PAGES

Zamora, Richard J.; Uberuaga, Blas P.; Perez, Danny; ...

2016-06-01

Accelerated molecular dynamics (AMD) is a class of MD-based methods used to simulate atomistic systems in which the metastable state-to-state evolution is slow compared with thermal vibrations. Temperature-accelerated dynamics (TAD) is a particularly efficient AMD procedure in which the predicted evolution is hastened by elevating the temperature of the system and then recovering the correct state-to-state dynamics at the temperature of interest. TAD has been used to study various materials applications, often revealing surprising behavior beyond the reach of direct MD. This success has inspired several algorithmic performance enhancements, as well as the analysis of its mathematical framework. Recently, thesemore » enhancements have leveraged parallel programming techniques to enhance both the spatial and temporal scaling of the traditional approach. Here, we review the ongoing evolution of the modern TAD method and introduce the latest development: speculatively parallel TAD.« less

Dynamic Tire Pressure Sensor for Measuring Ground Vibration

PubMed Central

Wang, Qi; McDaniel, James Gregory; Wang, Ming L.

2012-01-01

This work presents a convenient and non-contact acoustic sensing approach for measuring ground vibration. This approach, which uses an instantaneous dynamic tire pressure sensor (DTPS), possesses the capability to replace the accelerometer or directional microphone currently being used for inspecting pavement conditions. By measuring dynamic pressure changes inside the tire, ground vibration can be amplified and isolated from environmental noise. In this work, verifications of the DTPS concept of sensing inside the tire have been carried out. In addition, comparisons between a DTPS, ground-mounted accelerometer, and directional microphone are made. A data analysis algorithm has been developed and optimized to reconstruct ground acceleration from DTPS data. Numerical and experimental studies of this DTPS reveal a strong potential for measuring ground vibration caused by a moving vehicle. A calibration of transfer function between dynamic tire pressure change and ground acceleration may be needed for different tire system or for more accurate application. PMID:23202206

Using the Spatial Distribution of Installers to Define Solar Photovoltaic Markets

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

O'Shaughnessy, Eric; Nemet, Gregory F.; Darghouth, Naim

2016-09-01

Solar PV market research to date has largely relied on arbitrary jurisdictional boundaries, such as counties, to study solar PV market dynamics. This paper seeks to improve solar PV market research by developing a methodology to define solar PV markets. The methodology is based on the spatial distribution of solar PV installers. An algorithm is developed and applied to a rich dataset of solar PV installations to study the outcomes of the installer-based market definitions. The installer-based approach exhibits several desirable properties. Specifically, the higher market granularity of the installer-based approach will allow future PV market research to study themore » relationship between market dynamics and pricing with more precision.« less

Physical characteristics of cometary dust from dynamical studies - A review

NASA Technical Reports Server (NTRS)

Sekanina, Z.

1980-01-01

Progress made in the determination of the physical characteristics of cometary dust particles from studies of dust tail dynamics is reviewed. Applications of the combined dynamical photometric approach of Finson and Probstein (1968) to studies of cometary tails exhibiting continuous light intensity variations are discussed, with attention given to determinations of the particle-size-related distribution function of the solar radiation pressure exerted on the particles, the contribution of comets to the interplanetary dust, calculations of dust ejection rates and a Monte Carlo approach to the analysis of dust tails. Investigations of dust streamers and striae, which are believed to be related to comet outbursts entailing brief but sharp enhancements of dust production, are then reviewed, with particular attention given to observations of Comet West 1976 VI. Finally, the question of cometary particle type is addressed, and it is pointed out that the presence of submicron absorbing particles in the striae of Comet West is not incompatible with the presence of micron-size dielectric particles in the inner coma.

Understanding rapid evolution in predator‐prey interactions using the theory of fast‐slow dynamical systems.

PubMed

Cortez, Michael H; Ellner, Stephen P

2010-11-01

The accumulation of evidence that ecologically important traits often evolve at the same time and rate as ecological dynamics (e.g., changes in species' abundances or spatial distributions) has outpaced theory describing the interplay between ecological and evolutionary processes with comparable timescales. The disparity between experiment and theory is partially due to the high dimensionality of models that include both evolutionary and ecological dynamics. Here we show how the theory of fast-slow dynamical systems can be used to reduce model dimension, and we use that body of theory to study a general predator-prey system exhibiting fast evolution in either the predator or the prey. Our approach yields graphical methods with predictive power about when new and unique dynamics (e.g., completely out-of-phase oscillations and cryptic dynamics) can arise in ecological systems exhibiting fast evolution. In addition, we derive analytical expressions for determining when such behavior arises and how evolution affects qualitative properties of the ecological dynamics. Finally, while the theory requires a separation of timescales between the ecological and evolutionary processes, our approach yields insight into systems where the rates of those processes are comparable and thus is a step toward creating a general ecoevolutionary theory.

Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study

PubMed Central

You, Hongzhi; Wang, Da-Hui

2017-01-01

Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems. PMID:28223913

Finite temperature dynamics of a Holstein polaron: The thermo-field dynamics approach

NASA Astrophysics Data System (ADS)

Chen, Lipeng; Zhao, Yang

2017-12-01

Combining the multiple Davydov D2 Ansatz with the method of thermo-field dynamics, we study finite temperature dynamics of a Holstein polaron on a lattice. It has been demonstrated, using the hierarchy equations of motion method as a benchmark, that our approach provides an efficient, robust description of finite temperature dynamics of the Holstein polaron in the simultaneous presence of diagonal and off-diagonal exciton-phonon coupling. The method of thermo-field dynamics handles temperature effects in the Hilbert space with key numerical advantages over other treatments of finite-temperature dynamics based on quantum master equations in the Liouville space or wave function propagation with Monte Carlo importance sampling. While for weak to moderate diagonal coupling temperature increases inhibit polaron mobility, it is found that off-diagonal coupling induces phonon-assisted transport that dominates at high temperatures. Results on the mean square displacements show that band-like transport features dominate the diagonal coupling cases, and there exists a crossover from band-like to hopping transport with increasing temperature when including off-diagonal coupling. As a proof of concept, our theory provides a unified treatment of coherent and incoherent transport in molecular crystals and is applicable to any temperature.

Neuromorphic Implementation of Attractor Dynamics in a Two-Variable Winner-Take-All Circuit with NMDARs: A Simulation Study.

PubMed

You, Hongzhi; Wang, Da-Hui

2017-01-01

Neural networks configured with winner-take-all (WTA) competition and N-methyl-D-aspartate receptor (NMDAR)-mediated synaptic dynamics are endowed with various dynamic characteristics of attractors underlying many cognitive functions. This paper presents a novel method for neuromorphic implementation of a two-variable WTA circuit with NMDARs aimed at implementing decision-making, working memory and hysteresis in visual perceptions. The method proposed is a dynamical system approach of circuit synthesis based on a biophysically plausible WTA model. Notably, slow and non-linear temporal dynamics of NMDAR-mediated synapses was generated. Circuit simulations in Cadence reproduced ramping neural activities observed in electrophysiological recordings in experiments of decision-making, the sustained activities observed in the prefrontal cortex during working memory, and classical hysteresis behavior during visual discrimination tasks. Furthermore, theoretical analysis of the dynamical system approach illuminated the underlying mechanisms of decision-making, memory capacity and hysteresis loops. The consistence between the circuit simulations and theoretical analysis demonstrated that the WTA circuit with NMDARs was able to capture the attractor dynamics underlying these cognitive functions. Their physical implementations as elementary modules are promising for assembly into integrated neuromorphic cognitive systems.

Phase transitions in trajectories of a superconducting single-electron transistor coupled to a resonator.

PubMed

Genway, Sam; Garrahan, Juan P; Lesanovsky, Igor; Armour, Andrew D

2012-05-01

Recent progress in the study of dynamical phase transitions has been made with a large-deviation approach to study trajectories of stochastic jumps using a thermodynamic formalism. We study this method applied to an open quantum system consisting of a superconducting single-electron transistor, near the Josephson quasiparticle resonance, coupled to a resonator. We find that the dynamical behavior shown in rare trajectories can be rich even when the mean dynamical activity is small, and thus the formalism gives insights into the form of fluctuations. The structure of the dynamical phase diagram found from the quantum-jump trajectories of the resonator is studied, and we see that sharp transitions in the dynamical activity may be related to the appearance and disappearance of bistabilities in the state of the resonator as system parameters are changed. We also demonstrate that for a fast resonator, the trajectories of quasiparticles are similar to the resonator trajectories.

New Approach for Investigating Reaction Dynamics and Rates with Ab Initio Calculations.

PubMed

Fleming, Kelly L; Tiwary, Pratyush; Pfaendtner, Jim

2016-01-21

Herein, we demonstrate a convenient approach to systematically investigate chemical reaction dynamics using the metadynamics (MetaD) family of enhanced sampling methods. Using a symmetric SN2 reaction as a model system, we applied infrequent metadynamics, a theoretical framework based on acceleration factors, to quantitatively estimate the rate of reaction from biased and unbiased simulations. A systematic study of the algorithm and its application to chemical reactions was performed by sampling over 5000 independent reaction events. Additionally, we quantitatively reweighed exhaustive free-energy calculations to obtain the reaction potential-energy surface and showed that infrequent metadynamics works to effectively determine Arrhenius-like activation energies. Exact agreement with unbiased high-temperature kinetics is also shown. The feasibility of using the approach on actual ab initio molecular dynamics calculations is then presented by using Car-Parrinello MD+MetaD to sample the same reaction using only 10-20 calculations of the rare event. Owing to the ease of use and comparatively low-cost of computation, the approach has extensive potential applications for catalysis, combustion, pyrolysis, and enzymology.

Multi-Dimensional Calibration of Impact Dynamic Models

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Reaves, Mercedes C.; Annett, Martin S.; Jackson, Karen E.

2011-01-01

NASA Langley, under the Subsonic Rotary Wing Program, recently completed two helicopter tests in support of an in-house effort to study crashworthiness. As part of this effort, work is on-going to investigate model calibration approaches and calibration metrics for impact dynamics models. Model calibration of impact dynamics problems has traditionally assessed model adequacy by comparing time histories from analytical predictions to test at only a few critical locations. Although this approach provides for a direct measure of the model predictive capability, overall system behavior is only qualitatively assessed using full vehicle animations. In order to understand the spatial and temporal relationships of impact loads as they migrate throughout the structure, a more quantitative approach is needed. In this work impact shapes derived from simulated time history data are used to recommend sensor placement and to assess model adequacy using time based metrics and orthogonality multi-dimensional metrics. An approach for model calibration is presented that includes metric definitions, uncertainty bounds, parameter sensitivity, and numerical optimization to estimate parameters to reconcile test with analysis. The process is illustrated using simulated experiment data.

An integrated approach to evaluate policies for controlling traffic law violations.

PubMed

Mehmood, Arif

2010-03-01

Modeling dynamics of the driver behavior is a complex problem. In this paper a system approach is introduced to model and to analyze the driver behavior related to traffic law violations in the Emirate of Abu Dhabi. This paper demonstrates how the theoretical relationships between different factors can be expressed formally, and how the resulting model can assist in evaluating potential benefits of various policies to control the traffic law violations Using system approach, an integrated dynamic simulation model is developed, and model is tested to simulate the driver behavior for violating traffic laws during 2002-2007 in the Emirate of Abu Dhabi. The dynamic simulation model attempts to address the questions: (1) "what" interventions should be implemented to reduce and eventually control traffic violations which will lead to improving road safety and (2) "how" to justify those interventions will be effective or ineffective to control the violations in different transportation conditions. The simulation results reveal promising capability of applying system approach in the policy evaluation studies. Copyright 2009 Elsevier Ltd. All rights reserved.

Hillslope threshold response to rainfall: (1) a field based forensic approach

Treesearch

Chris B. Graham; Ross A. Woods; Jeffrey J. McDonnell

2010-01-01

Hillslope threshold response to storm rainfall is poorly understood. Basic questions regarding the type, location, and flow dynamics of lateral, subsurface flow remain unanswered, even at our most intensively studied field sites. Here we apply a forensic approach where we combined irrigation and excavation experiments at the well studied Maimai hillslope to determine...

Dynamics of Intersubject Brain Networks during Anxious Anticipation

PubMed Central

Najafi, Mahshid; Kinnison, Joshua; Pessoa, Luiz

2017-01-01

How do large-scale brain networks reorganize during the waxing and waning of anxious anticipation? Here, threat was dynamically modulated during human functional MRI as two circles slowly meandered on the screen; if they touched, an unpleasant shock was delivered. We employed intersubject correlation analysis, which allowed the investigation of network-level functional connectivity across brains, and sought to determine how network connectivity changed during periods of approach (circles moving closer) and periods of retreat (circles moving apart). Analysis of positive connection weights revealed that dynamic threat altered connectivity within and between the salience, executive, and task-negative networks. For example, dynamic functional connectivity increased within the salience network during approach and decreased during retreat. The opposite pattern was found for the functional connectivity between the salience and task-negative networks: decreases during approach and increases during approach. Functional connections between subcortical regions and the salience network also changed dynamically during approach and retreat periods. Subcortical regions exhibiting such changes included the putative periaqueductal gray, putative habenula, and putative bed nucleus of the stria terminalis. Additional analysis of negative functional connections revealed dynamic changes, too. For example, negative weights within the salience network decreased during approach and increased during retreat, opposite what was found for positive weights. Together, our findings unraveled dynamic features of functional connectivity of large-scale networks and subcortical regions across participants while threat levels varied continuously, and demonstrate the potential of characterizing emotional processing at the level of dynamic networks. PMID:29209184

Revealing the Link between Structural Relaxation and Dynamic Heterogeneity in Glass-Forming Liquids

NASA Astrophysics Data System (ADS)

Wang, Lijin; Xu, Ning; Wang, W. H.; Guan, Pengfei

2018-03-01

Despite the use of glasses for thousands of years, the nature of the glass transition is still mysterious. On approaching the glass transition, the growth of dynamic heterogeneity has long been thought to play a key role in explaining the abrupt slowdown of structural relaxation. However, it still remains elusive whether there is an underlying link between structural relaxation and dynamic heterogeneity. Here, we unravel the link by introducing a characteristic time scale hiding behind an identical dynamic heterogeneity for various model glass-forming liquids. We find that the time scale corresponds to the kinetic fragility of liquids. Moreover, it leads to scaling collapse of both the structural relaxation time and dynamic heterogeneity for all liquids studied, together with a characteristic temperature associated with the same dynamic heterogeneity. Our findings imply that studying the glass transition from the viewpoint of dynamic heterogeneity is more informative than expected.

Simple Kinematic Pathway Approach (KPA) to Catchment-scale Travel Time and Water Age Distributions

NASA Astrophysics Data System (ADS)

Soltani, S. S.; Cvetkovic, V.; Destouni, G.

2017-12-01

The distribution of catchment-scale water travel times is strongly influenced by morphological dispersion and is partitioned between hillslope and larger, regional scales. We explore whether hillslope travel times are predictable using a simple semi-analytical "kinematic pathway approach" (KPA) that accounts for dispersion on two levels of morphological and macro-dispersion. The study gives new insights to shallow (hillslope) and deep (regional) groundwater travel times by comparing numerical simulations of travel time distributions, referred to as "dynamic model", with corresponding KPA computations for three different real catchment case studies in Sweden. KPA uses basic structural and hydrological data to compute transient water travel time (forward mode) and age (backward mode) distributions at the catchment outlet. Longitudinal and morphological dispersion components are reflected in KPA computations by assuming an effective Peclet number and topographically driven pathway length distributions, respectively. Numerical simulations of advective travel times are obtained by means of particle tracking using the fully-integrated flow model MIKE SHE. The comparison of computed cumulative distribution functions of travel times shows significant influence of morphological dispersion and groundwater recharge rate on the compatibility of the "kinematic pathway" and "dynamic" models. Zones of high recharge rate in "dynamic" models are associated with topographically driven groundwater flow paths to adjacent discharge zones, e.g. rivers and lakes, through relatively shallow pathway compartments. These zones exhibit more compatible behavior between "dynamic" and "kinematic pathway" models than the zones of low recharge rate. Interestingly, the travel time distributions of hillslope compartments remain almost unchanged with increasing recharge rates in the "dynamic" models. This robust "dynamic" model behavior suggests that flow path lengths and travel times in shallow hillslope compartments are controlled by topography, and therefore application and further development of the simple "kinematic pathway" approach is promising for their modeling.

Respiratory muscle function and exercise limitation in patients with chronic obstructive pulmonary disease: a review.

PubMed

Charususin, Noppawan; Dacha, Sauwaluk; Gosselink, Rik; Decramer, Marc; Von Leupoldt, Andreas; Reijnders, Thomas; Louvaris, Zafeiris; Langer, Daniel

2018-01-01

Respiratory muscle dysfunction is common and contributes to dyspnea and exercise limitation in patients with chronic obstructive pulmonary disease (COPD). Improving dynamic function of respiratory muscles during exercise might help to reduce symptoms and improve exercise capacity. Areas covered: The aims of this review are to 1) summarize physiological mechanisms linking respiratory muscle dysfunction to dyspnea and exercise limitation; 2) provide an overview of available therapeutic approaches to better maintain load-capacity balance of respiratory muscles during exercise; and 3) to summarize current knowledge on potential mechanisms explaining effects of interventions aimed at optimizing dynamic respiratory muscle function with a special focus on inspiratory muscle training. Expert commentary: Several mechanisms which are potentially linking improvements in dynamic respiratory muscle function to symptomatic and functional benefits have not been studied so far in COPD patients. Examples of underexplored areas include the study of neural processes related to the relief of acute dyspnea and the competition between respiratory and peripheral muscles for limited energy supplies during exercise. Novel methodologies are available to non-invasively study these mechanisms. Better insights into the consequences of dynamic respiratory muscle dysfunction will hopefully contribute to further refine and individualize therapeutic approaches in patients with COPD.

Dynamic versus isometric electromechanical delay in non-fatigued and fatigued muscle: A combined electromyographic, mechanomyographic, and force approach.

PubMed

Smith, Cory M; Housh, Terry J; Hill, Ethan C; Johnson, Glen O; Schmidt, Richard J

2017-04-01

This study used a combined electromyographic, mechanomyographic, and force approach to identify electromechanical delay (EMD) from the onsets of the electromyographic to force signals (EMD E-F ), onsets of the electromyographic to mechanomyogrpahic signals (EMD E-M ), and onsets of mechanomyographic to force signals (EMD M-F ). The purposes of the current study were to examine: (1) the differences in EMD E-F , EMD E-M , and EMD M-F from the vastus lateralis during maximal, voluntary dynamic (1 repetition maximum [1-RM]) and isometric (maximal voluntary isometric contraction [MVIC]) muscle actions; and (2) the effects of fatigue on EMD E-F , EMD M-F , and EMD E-M . Ten men performed pretest and posttest 1-RM and MVIC leg extension muscle actions. The fatiguing workbout consisted of 70% 1-RM dynamic constant external resistance leg extension muscle actions to failure. The results indicated that there were no significant differences between 1-RM and MVIC EMD E-F , EMD E-M , or EMD M-F. There were, however, significant fatigue-induced increases in EMD E-F (94% and 63%), EMD E-M (107%), and EMD M-F (63%) for both the 1-RM and MVIC measurements. Therefore, these findings demonstrated the effects of fatigue on EMD measures and supported comparisons among studies which examined dynamic or isometric EMD measures from the vastus lateralis using a combined electromyographic, mechanomyographic, and force approach. Copyright © 2017 Elsevier Ltd. All rights reserved.

Temporal genetic analysis of the endangered tidewater goby: extinction-colonization dynamics or drift in isolation?

PubMed

Kinziger, Andrew P; Hellmair, Michael; McCraney, W Tyler; Jacobs, David K; Goldsmith, Greg

2015-11-01

Extinction and colonization dynamics are critical to understanding the evolution and conservation of metapopulations. However, traditional field studies of extinction-colonization are potentially fraught with detection bias and have rarely been validated. Here, we provide a comparison of molecular and field-based approaches for assessment of the extinction-colonization dynamics of tidewater goby (Eucyclogobius newberryi) in northern California. Our analysis of temporal genetic variation across 14 northern California tidewater goby populations failed to recover genetic change expected with extinction-colonization cycles. Similarly, analysis of site occupancy data from field studies (94 sites) indicated that extinction and colonization are very infrequent for our study populations. Comparison of the approaches indicated field data were subject to imperfect detection, and falsely implied extinction-colonization cycles in several instances. For northern California populations of tidewater goby, we interpret the strong genetic differentiation between populations and high degree of within-site temporal stability as consistent with a model of drift in the absence of migration, at least over the past 20-30 years. Our findings show that tidewater goby exhibit different population structures across their geographic range (extinction-colonization dynamics in the south vs. drift in isolation in the north). For northern populations, natural dispersal is too infrequent to be considered a viable approach for recolonizing extirpated populations, suggesting that species recovery will likely depend on artificial translocation in this region. More broadly, this work illustrates that temporal genetic analysis can be used in combination with field data to strengthen inference of extinction-colonization dynamics or as a stand-alone tool when field data are lacking. © 2015 John Wiley & Sons Ltd.

Dynamic vapor sorption isotherms of medium grain rice varieties

USDA-ARS?s Scientific Manuscript database

It is known that the two popular medium rice varieties, namely M202 and M206, in California have different fissuring resistances. Therefore, the main goal of this study was to investigate the sorption behavior of these two varieties by a new approach using dynamic vapor sorption (DVS) method for elu...

Dynamic Assessment of EFL Reading: Revealing Hidden Aspects at Different Proficiency Levels

ERIC Educational Resources Information Center

Ajideh, Parviz; Farrokhi, Farahman; Nourdad, Nava

2012-01-01

Dynamic assessment as a complementary approach to traditional static assessment emphasizes the learning process and accounts for the amount and nature of examiner investment. The present qualitative study analyzed interactions for 270 reading test items which were recorded and tape scripted. The reading ability of 9 EFL participants at three…

Contextual Dynamics in Foreign Language Learning Motivation

ERIC Educational Resources Information Center

Kozaki, Yoko; Ross, Steven J.

2011-01-01

Learning context has increasingly been postulated to exert an influence on the dynamics of individual differences in language learning. In a longitudinal design that tested the proficiency gains of 1,682 learners over a 2-year foreign language program, a multilevel modeling approach was deployed in this study to account for variation in second…

Teaching Group Dynamics through an Application-Based Learning Approach

ERIC Educational Resources Information Center

Harper, Melinda S.; Allegretti, Christine L.

2015-01-01

The purpose of this study was to demonstrate how a structured experiential course can be used to teach students to lead group discussions. Group dynamics and leadership skills were taught through two teaching strategies in the course: the first method required junior- and senior-level undergraduate students to participate in a process-oriented…

Early Maternal Employment and Children's Vocabulary and Inductive Reasoning Ability: A Dynamic Approach

ERIC Educational Resources Information Center

Kühhirt, Michael; Klein, Markus

2018-01-01

This study investigates the relationship between early maternal employment history and children's vocabulary and inductive reasoning ability at age 5, drawing on longitudinal information on 2,200 children from the Growing Up in Scotland data. Prior research rarely addresses dynamics in maternal employment and the methodological ramifications of…

Investigating Teachers' Understanding of the Salt Dissolution Process: A Multi-Media Approach in Education

ERIC Educational Resources Information Center

Malkoc, Ummuhan

2017-01-01

Animations of molecular structure and dynamics are repeatedly applied to support student comprehension in the theoretical ideas of chemistry. However, students' understanding the dynamics of the phenomena is directly related to the understanding of teachers as instructors. Therefore, this study aimed to investigate how the features of three…

Teacher Guidance to Mediate Student Inquiry through Interactive Dynamic Visualizations

ERIC Educational Resources Information Center

Chang, Hsin-Yi

2013-01-01

The purpose of this study is to investigate how three teachers guided their students to learn science using interactive dynamic visualizations incorporated in an inquiry digital unit. The results show that the teachers' guidance varied in frequency, occasion, and content type. Each teacher demonstrated a different instructional approach in…

Dynamic design and control of a high-speed pneumatic jet actuator

NASA Astrophysics Data System (ADS)

Misyurin, S. Yu; Ivlev, V. I.; Kreinin, G. V.

2017-12-01

Mathematical model of an actuator, consisting of a pneumatic (gas) high-speed jet engine, transfer mechanism, and a control device used for switching the ball valve is worked out. The specific attention was paid to the transition (normalization) of the dynamic model into the dimensionless form. Its dynamic simulation criteria are determined, and dynamics study of an actuator was carried out. The simple control algorithm of relay action with a velocity feedback enabling the valve plug to be turned with a smooth nonstop and continuous approach to the final position is demonstrated

A Bayesian nonparametric approach to dynamical noise reduction

NASA Astrophysics Data System (ADS)

Kaloudis, Konstantinos; Hatjispyros, Spyridon J.

2018-06-01

We propose a Bayesian nonparametric approach for the noise reduction of a given chaotic time series contaminated by dynamical noise, based on Markov Chain Monte Carlo methods. The underlying unknown noise process (possibly) exhibits heavy tailed behavior. We introduce the Dynamic Noise Reduction Replicator model with which we reconstruct the unknown dynamic equations and in parallel we replicate the dynamics under reduced noise level dynamical perturbations. The dynamic noise reduction procedure is demonstrated specifically in the case of polynomial maps. Simulations based on synthetic time series are presented.

Nonlinear electromechanical modelling and dynamical behavior analysis of a satellite reaction wheel

NASA Astrophysics Data System (ADS)

Aghalari, Alireza; Shahravi, Morteza

2017-12-01

The present research addresses the satellite reaction wheel (RW) nonlinear electromechanical coupling dynamics including dynamic eccentricity of brushless dc (BLDC) motor and gyroscopic effects, as well as dry friction of shaft-bearing joints (relative small slip) and bearing friction. In contrast to other studies, the rotational velocity of the flywheel is considered to be controllable, so it is possible to study the reaction wheel dynamical behavior in acceleration stages. The RW is modeled as a three-phases BLDC motor as well as flywheel with unbalances on a rigid shaft and flexible bearings. Improved Lagrangian dynamics for electromechanical systems is used to obtain the mathematical model of the system. The developed model can properly describe electromechanical nonlinear coupled dynamical behavior of the satellite RW. Numerical simulations show the effectiveness of the presented approach.

Dynamic neural networks based on-line identification and control of high performance motor drives

NASA Technical Reports Server (NTRS)

Rubaai, Ahmed; Kotaru, Raj

1995-01-01

In the automated and high-tech industries of the future, there wil be a need for high performance motor drives both in the low-power range and in the high-power range. To meet very straight demands of tracking and regulation in the two quadrants of operation, advanced control technologies are of a considerable interest and need to be developed. In response a dynamics learning control architecture is developed with simultaneous on-line identification and control. the feature of the proposed approach, to efficiently combine the dual task of system identification (learning) and adaptive control of nonlinear motor drives into a single operation is presented. This approach, therefore, not only adapts to uncertainties of the dynamic parameters of the motor drives but also learns about their inherent nonlinearities. In fact, most of the neural networks based adaptive control approaches in use have an identification phase entirely separate from the control phase. Because these approaches separate the identification and control modes, it is not possible to cope with dynamic changes in a controlled process. Extensive simulation studies have been conducted and good performance was observed. The robustness characteristics of neuro-controllers to perform efficiently in a noisy environment is also demonstrated. With this initial success, the principal investigator believes that the proposed approach with the suggested neural structure can be used successfully for the control of high performance motor drives. Two identification and control topologies based on the model reference adaptive control technique are used in this present analysis. No prior knowledge of load dynamics is assumed in either topology while the second topology also assumes no knowledge of the motor parameters.

Multi-scale compositionality: identifying the compositional structures of social dynamics using deep learning.

PubMed

Peng, Huan-Kai; Marculescu, Radu

2015-01-01

Social media exhibit rich yet distinct temporal dynamics which cover a wide range of different scales. In order to study this complex dynamics, two fundamental questions revolve around (1) the signatures of social dynamics at different time scales, and (2) the way in which these signatures interact and form higher-level meanings. In this paper, we propose the Recursive Convolutional Bayesian Model (RCBM) to address both of these fundamental questions. The key idea behind our approach consists of constructing a deep-learning framework using specialized convolution operators that are designed to exploit the inherent heterogeneity of social dynamics. RCBM's runtime and convergence properties are guaranteed by formal analyses. Experimental results show that the proposed method outperforms the state-of-the-art approaches both in terms of solution quality and computational efficiency. Indeed, by applying the proposed method on two social network datasets, Twitter and Yelp, we are able to identify the compositional structures that can accurately characterize the complex social dynamics from these two social media. We further show that identifying these patterns can enable new applications such as anomaly detection and improved social dynamics forecasting. Finally, our analysis offers new insights on understanding and engineering social media dynamics, with direct applications to opinion spreading and online content promotion.

Multi-Scale Compositionality: Identifying the Compositional Structures of Social Dynamics Using Deep Learning

PubMed Central

Peng, Huan-Kai; Marculescu, Radu

2015-01-01

Objective Social media exhibit rich yet distinct temporal dynamics which cover a wide range of different scales. In order to study this complex dynamics, two fundamental questions revolve around (1) the signatures of social dynamics at different time scales, and (2) the way in which these signatures interact and form higher-level meanings. Method In this paper, we propose the Recursive Convolutional Bayesian Model (RCBM) to address both of these fundamental questions. The key idea behind our approach consists of constructing a deep-learning framework using specialized convolution operators that are designed to exploit the inherent heterogeneity of social dynamics. RCBM’s runtime and convergence properties are guaranteed by formal analyses. Results Experimental results show that the proposed method outperforms the state-of-the-art approaches both in terms of solution quality and computational efficiency. Indeed, by applying the proposed method on two social network datasets, Twitter and Yelp, we are able to identify the compositional structures that can accurately characterize the complex social dynamics from these two social media. We further show that identifying these patterns can enable new applications such as anomaly detection and improved social dynamics forecasting. Finally, our analysis offers new insights on understanding and engineering social media dynamics, with direct applications to opinion spreading and online content promotion. PMID:25830775

Estimating net joint torques from kinesiological data using optimal linear system theory.

PubMed

Runge, C F; Zajac, F E; Allum, J H; Risher, D W; Bryson, A E; Honegger, F

1995-12-01

Net joint torques (NJT) are frequently computed to provide insights into the motor control of dynamic biomechanical systems. An inverse dynamics approach is almost always used, whereby the NJT are computed from 1) kinematic measurements (e.g., position of the segments), 2) kinetic measurements (e.g., ground reaction forces) that are, in effect, constraints defining unmeasured kinematic quantities based on a dynamic segmental model, and 3) numerical differentiation of the measured kinematics to estimate velocities and accelerations that are, in effect, additional constraints. Due to errors in the measurements, the segmental model, and the differentiation process, estimated NJT rarely produce the observed movement in a forward simulation when the dynamics of the segmental system are inherently unstable (e.g., human walking). Forward dynamic simulations are, however, essential to studies of muscle coordination. We have developed an alternative approach, using the linear quadratic follower (LQF) algorithm, which computes the NJT such that a stable simulation of the observed movement is produced and the measurements are replicated as well as possible. The LQF algorithm does not employ constraints depending on explicit differentiation of the kinematic data, but rather employs those depending on specification of a cost function, based on quantitative assumptions about data confidence. We illustrate the usefulness of the LQF approach by using it to estimate NJT exerted by standing humans perturbed by support-surface movements. We show that unless the number of kinematic and force variables recorded is sufficiently high, the confidence that can be placed in the estimates of the NJT, obtained by any method (e.g., LQF, or the inverse dynamics approach), may be unsatisfactorily low.

Approaches in Health Human Resource Forecasting: A Roadmap for Improvement

PubMed Central

Rafiei, Sima; Mohebbifar, Rafat; Hashemi, Fariba; Ezzatabadi, Mohammad Ranjbar; Farzianpour, Fereshteh

2016-01-01

Introduction Forecasting the demand and supply of health manpower in an accurate manner makes appropriate planning possible. The aim of this paper was to review approaches and methods for health manpower forecasting and consequently propose the features that improve the effectiveness of this important process of health manpower planning. Methods A literature review was conducted for studies published in English from 1990–2014 using Pub Med, Science Direct, Pro Quest, and Google Scholar databases. Review articles, qualitative studies, retrospective and prospective studies describing or applying various types of forecasting approaches and methods in health manpower forecasting were included in the review. The authors designed an extraction data sheet based on study questions to collect data on studies’ references, designs, and types of forecasting approaches, whether discussed or applied, with their strengths and weaknesses Results Forty studies were included in the review. As a result, two main categories of approaches (conceptual and analytical) for health manpower forecasting were identified. Each approach had several strengths and weaknesses. As a whole, most of them were faced with some challenges, such as being static and unable to capture dynamic variables in manpower forecasting and causal relationships. They also lacked the capacity to benefit from scenario making to assist policy makers in effective decision making. Conclusions An effective forecasting approach is supposed to resolve all the deficits that exist in current approaches and meet the key features found in the literature in order to develop an open system and a dynamic and comprehensive method necessary for today complex health care systems. PMID:27790343

Coarse-Grained Descriptions of Dynamics for Networks with Both Intrinsic and Structural Heterogeneities

PubMed Central

Bertalan, Tom; Wu, Yan; Laing, Carlo; Gear, C. William; Kevrekidis, Ioannis G.

2017-01-01

Finding accurate reduced descriptions for large, complex, dynamically evolving networks is a crucial enabler to their simulation, analysis, and ultimately design. Here, we propose and illustrate a systematic and powerful approach to obtaining good collective coarse-grained observables—variables successfully summarizing the detailed state of such networks. Finding such variables can naturally lead to successful reduced dynamic models for the networks. The main premise enabling our approach is the assumption that the behavior of a node in the network depends (after a short initial transient) on the node identity: a set of descriptors that quantify the node properties, whether intrinsic (e.g., parameters in the node evolution equations) or structural (imparted to the node by its connectivity in the particular network structure). The approach creates a natural link with modeling and “computational enabling technology” developed in the context of Uncertainty Quantification. In our case, however, we will not focus on ensembles of different realizations of a problem, each with parameters randomly selected from a distribution. We will instead study many coupled heterogeneous units, each characterized by randomly assigned (heterogeneous) parameter value(s). One could then coin the term Heterogeneity Quantification for this approach, which we illustrate through a model dynamic network consisting of coupled oscillators with one intrinsic heterogeneity (oscillator individual frequency) and one structural heterogeneity (oscillator degree in the undirected network). The computational implementation of the approach, its shortcomings and possible extensions are also discussed. PMID:28659781

Noise Source Identification and Dynamic Modeling of a Pneumatic Nailing Device =

NASA Astrophysics Data System (ADS)

Nili Ahmadabadi, Zahra

Exposure to hazardous noise levels emitted by pneumatic nailing devices contributes significantly to risk of hearing damage among the construction workers throughout the world. This health problem comes from the lack of appropriate technology such as low noise devices which in turn results from the lack of scientific knowledge about designing reduced noise devices. This study contributes to the design improvement of pneumatic nailing devices through identifying the noise sources and developing the simulation tool required to redesign the pneumatic nailing device. To identify the noise sources, the study uses a combination of two complementary experimental approaches. The first makes use of time-synchronized data analysis of several variables during the machine operation. This strategy allows identifying the physical processes and provides a detailed separation of the noise generation mechanisms in successive time sequences. However, since multiple noise sources radiate at the same time, this observation approach is not sufficient for noise source identification and ranking. Thus, it is completed by a selective wrapping and muffler procedure. This technique provides overall generated noise associated with each process, as well as ranking of the three major sources: (1) exhaust noise, (2) machine body vibrations, and (3) workpiece vibrations. A special investigation is conducted on this third one with two cases: a workpiece/worktable setup representative of the actual field usage of a nailing device and a workpiece/sandbox setup used in a standardized laboratory test. The study evaluates the efficiency of the workpiece/sandbox setup in reducing the workpiece radiation and obtains a typical workpiece contribution on an actual worksite. To provide a simulation tool, a dynamic model of the pneumatic nailing device needs to be developed. Dynamic modeling of the nailing device requires mathematical modeling of the physical processes involved in its operation. All of these processes can be described through already existing mathematical relations, except for the penetration resistance force (PRF) imposed on the nails when penetrating the wood. The PRF depends on various factors. This study follows two approaches in parallel to develop an empirical prediction law for the PRF: quasi-static and high-speed. The quasi-static approach provides a rapid and precise representation of the law at quasistatic penetration velocities. The law covers the entire displacement range, various nail geometries and sizes, and wood types. The high-speed approach aims to provide a law which covers a much wider range of penetration velocities. The approach is complicated since it requires a sophisticated test machine to conduct the nail driving tests at high penetration velocities. The study designs and fabricates an advanced test machine to later extend the prediction range of the PRF law. The last part of this study develops the dynamic model of a nail gun while integrating the quasi-static PRF law. The model includes dynamics of all the air chambers and the moving parts, and interactions and impacts/contacts between different parts. The study integrates a comprehensive experimental validation of the model. Future improvements in the dynamic model precision will be possible by using the extended version of the PRF law.

Constraint Embedding for Multibody System Dynamics

NASA Technical Reports Server (NTRS)

Jain, Abhinandan

2009-01-01

This paper describes a constraint embedding approach for the handling of local closure constraints in multibody system dynamics. The approach uses spatial operator techniques to eliminate local-loop constraints from the system and effectively convert the system into tree-topology systems. This approach allows the direct derivation of recursive O(N) techniques for solving the system dynamics and avoiding the expensive steps that would otherwise be required for handling the closedchain dynamics. The approach is very effective for systems where the constraints are confined to small-subgraphs within the system topology. The paper provides background on the spatial operator O(N) algorithms, the extensions for handling embedded constraints, and concludes with some examples of such constraints.

Non-adiabatic excited state molecular dynamics of phenylene ethynylene dendrimer using a multiconfigurational Ehrenfest approach

DOE PAGES

Fernandez-Alberti, Sebastian; Makhov, Dmitry V.; Tretiak, Sergei; ...

2016-03-10

Photoinduced dynamics of electronic and vibrational unidirectional energy transfer between meta-linked building blocks in a phenylene ethynylene dendrimer is simulated using a multiconfigurational Ehrenfest in time-dependent diabatic basis (MCE-TDDB) method, a new variant of the MCE approach developed by us for dynamics involving multiple electronic states with numerous abrupt crossings. Excited-state energies, gradients and non-adiabatic coupling terms needed for dynamics simulation are calculated on-the-fly using the Collective Electron Oscillator (CEO) approach. In conclusion, a comparative analysis of our results obtained using MCE-TDDB, the conventional Ehrenfest method and the surface-hopping approach with and without decoherence corrections is presented.

Optimal dimensionality reduction of complex dynamics: the chess game as diffusion on a free-energy landscape.

PubMed

Krivov, Sergei V

2011-07-01

Dimensionality reduction is ubiquitous in the analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed low-dimensional space does not provide a complete and accurate description of the dynamics. Here I describe how to perform dimensionality reduction while preserving the essential properties of the dynamics. The approach is illustrated by analyzing the chess game--the archetype of complex dynamics. A variable that provides complete and accurate description of chess dynamics is constructed. The winning probability is predicted by describing the game as a random walk on the free-energy landscape associated with the variable. The approach suggests a possible way of obtaining a simple yet accurate description of many important complex phenomena. The analysis of the chess game shows that the approach can quantitatively describe the dynamics of processes where human decision-making plays a central role, e.g., financial and social dynamics.

Optimal dimensionality reduction of complex dynamics: The chess game as diffusion on a free-energy landscape

NASA Astrophysics Data System (ADS)

Krivov, Sergei V.

2011-07-01

Dimensionality reduction is ubiquitous in the analysis of complex dynamics. The conventional dimensionality reduction techniques, however, focus on reproducing the underlying configuration space, rather than the dynamics itself. The constructed low-dimensional space does not provide a complete and accurate description of the dynamics. Here I describe how to perform dimensionality reduction while preserving the essential properties of the dynamics. The approach is illustrated by analyzing the chess game—the archetype of complex dynamics. A variable that provides complete and accurate description of chess dynamics is constructed. The winning probability is predicted by describing the game as a random walk on the free-energy landscape associated with the variable. The approach suggests a possible way of obtaining a simple yet accurate description of many important complex phenomena. The analysis of the chess game shows that the approach can quantitatively describe the dynamics of processes where human decision-making plays a central role, e.g., financial and social dynamics.

Application of the algebraic difference approach for developing self-referencing specific gravity and biomass equations

Treesearch

Lewis Jordan; Ray Souter; Bernard Parresol; Richard F. Daniels

2006-01-01

Biomass estimation is critical for looking at ecosystem processes and as a measure of stand yield. The density-integral approach allows for coincident estimation of stem profile and biomass. The algebraic difference approach (ADA) permits the derivation of dynamic or nonstatic functions. In this study we applied the ADA to develop a self-referencing specific gravity...

Two-tiered design analysis of a radiator for a solar dynamic powered Stirling engine

NASA Technical Reports Server (NTRS)

Hainley, Donald C.

1989-01-01

Two separate design approaches for a pumped loop radiator used to transfer heat from the cold end of a solar dynamic powered Stirling engine are described. The first approach uses a standard method to determine radiator requirements to meet specified end of mission conditions. Trade-off studies conducted for the analysis are included. Justification of this concept within the specified parameters of the analysis is provided. The second design approach determines the life performance of the radiator/Stirling system. In this approach, the system performance was altered by reducing the radiator heat transfer area. Performance effects and equilibrium points were determined as radiator segments were removed. This simulates the effect of loss of radiator sections due to micro-meteoroid and space debris penetration. The two designs were compared on the basis of overall system requirements and goals.

Two-tiered design analysis of a radiator for a solar dynamic powered Stirling engine

NASA Technical Reports Server (NTRS)

Hainley, Donald C.

1989-01-01

Two separate design approaches for a pumped loop radiator used to transfer heat from the cold end of a solar dynamic powered Stirling engine are described. The first approach uses a standard method to determine radiator requirements to meet specified end of mission conditions. Trade-off studies conducted for the analysis are included. Justification of this concept within the specified parameters of the analysis is provided. The second design approach determines the life performance of the radiator/Stirling system. In this approach, the system performance was altered by reducing the radiator heat transfer area. Performance effects and equilibrium points were determined as radiator segments were removed. This simulates the effect of loss of radiator sections due to micro-meteoroid and space debris penetration. The two designs are compared on the basis of overall system requirements and goals.

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.

Modelling the dynamics of traits involved in fighting-predators-prey system.

PubMed

Kooi, B W

2015-12-01

We study the dynamics of a predator-prey system where predators fight for captured prey besides searching for and handling (and digestion) of the prey. Fighting for prey is modelled by a continuous time hawk-dove game dynamics where the gain depends on the amount of disputed prey while the costs for fighting is constant per fighting event. The strategy of the predator-population is quantified by a trait being the proportion of the number of predator-individuals playing hawk tactics. The dynamics of the trait is described by two models of adaptation: the replicator dynamics (RD) and the adaptive dynamics (AD). In the RD-approach a variant individual with an adapted trait value changes the population's strategy, and consequently its trait value, only when its payoff is larger than the population average. In the AD-approach successful replacement of the resident population after invasion of a rare variant population with an adapted trait value is a step in a sequence changing the population's strategy, and hence its trait value. The main aim is to compare the consequences of the two adaptation models. In an equilibrium predator-prey system this will lead to convergence to a neutral singular strategy, while in the oscillatory system to a continuous singular strategy where in this endpoint the resident population is not invasible by any variant population. In equilibrium (low prey carrying capacity) RD and AD-approach give the same results, however not always in a periodically oscillating system (high prey carrying-capacity) where the trait is density-dependent. For low costs the predator population is monomorphic (only hawks) while for high costs dimorphic (hawks and doves). These results illustrate that intra-specific trait dynamics matters in predator-prey dynamics.

An improved EMD method for modal identification and a combined static-dynamic method for damage detection

NASA Astrophysics Data System (ADS)

Yang, Jinping; Li, Peizhen; Yang, Youfa; Xu, Dian

2018-04-01

Empirical mode decomposition (EMD) is a highly adaptable signal processing method. However, the EMD approach has certain drawbacks, including distortions from end effects and mode mixing. In the present study, these two problems are addressed using an end extension method based on the support vector regression machine (SVRM) and a modal decomposition method based on the characteristics of the Hilbert transform. The algorithm includes two steps: using the SVRM, the time series data are extended at both endpoints to reduce the end effects, and then, a modified EMD method using the characteristics of the Hilbert transform is performed on the resulting signal to reduce mode mixing. A new combined static-dynamic method for identifying structural damage is presented. This method combines the static and dynamic information in an equilibrium equation that can be solved using the Moore-Penrose generalized matrix inverse. The combination method uses the differences in displacements of the structure with and without damage and variations in the modal force vector. Tests on a four-story, steel-frame structure were conducted to obtain static and dynamic responses of the structure. The modal parameters are identified using data from the dynamic tests and improved EMD method. The new method is shown to be more accurate and effective than the traditional EMD method. Through tests with a shear-type test frame, the higher performance of the proposed static-dynamic damage detection approach, which can detect both single and multiple damage locations and the degree of the damage, is demonstrated. For structures with multiple damage, the combined approach is more effective than either the static or dynamic method. The proposed EMD method and static-dynamic damage detection method offer improved modal identification and damage detection, respectively, in structures.

68Ga-PSMA-11 Dynamic PET/CT Imaging in Primary Prostate Cancer.

PubMed

Sachpekidis, Christos; Kopka, Klaus; Eder, Matthias; Hadaschik, Boris A; Freitag, Martin T; Pan, Leyun; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2016-11-01

The aim of our study is to assess the pharmacokinetics and biodistribution of Ga-PSMA-11 in patients suffering from primary prostate cancer (PC) by means of dynamic and whole-body PET/CT. Twenty-four patients with primary, previously untreated PC were enrolled in the study. All patients underwent dynamic PET/CT (dPET/CT) scanning of the pelvis and whole-body PET/CT studies with Ga-PSMA-11. The evaluation of dPET/CT studies was based on qualitative evaluation, SUV calculation, and quantitative analysis based on two-tissue compartment modeling and a noncompartmental approach leading to the extraction of fractal dimension (FD). A total of 23/24 patients (95.8%) were Ga-PSMA-11 positive. In 9/24 patients (37.5%), metastatic lesions were detected. PC-associated lesions demonstrated the following mean values: SUVaverage = 14.3, SUVmax = 23.4, K1 = 0.24 (1/min), k3 = 0.34 (1/min), influx = 0.15 (1/min), and FD = 1.27. The parameters SUVaverage, SUVmax, k3, influx, and FD derived from PC-associated lesions were significantly higher than respective values derived from reference prostate tissue. Time-activity curves derived from PC-associated lesions revealed an increasing Ga-PSMA-11 accumulation during dynamic PET acquisition. Correlation analysis revealed a moderate but significant correlation between PSA levels and SUVaverage (r = 0.60) and SUVmax (r = 0.57), and a weak but significant correlation between Gleason score and SUVaverage (r = 0.33) and SUVmax (r = 0.28). Ga-PSMA-11 PET/CT confirmed its capacity in detecting primary PC with a detection rate of 95.8%. Dynamic PET/CT studies of the pelvis revealed an increase in tracer uptake in PC-associated lesions during the 60 minutes of dynamic PET acquisition, a finding with potential applications in anti-PSMA approaches.

Experiments on Analysing Voice Production: Excised (Human, Animal) and In Vivo (Animal) Approaches

PubMed Central

Döllinger, Michael; Kobler, James; Berry, David A.; Mehta, Daryush D.; Luegmair, Georg; Bohr, Christopher

2015-01-01

Experiments on human and on animal excised specimens as well as in vivo animal preparations are so far the most realistic approaches to simulate the in vivo process of human phonation. These experiments do not have the disadvantage of limited space within the neck and enable studies of the actual organ necessary for phonation, i.e., the larynx. The studies additionally allow the analysis of flow, vocal fold dynamics, and resulting acoustics in relation to well-defined laryngeal alterations. Purpose of Review This paper provides an overview of the applications and usefulness of excised (human/animal) specimen and in vivo animal experiments in voice research. These experiments have enabled visualization and analysis of dehydration effects, vocal fold scarring, bifurcation and chaotic vibrations, three-dimensional vibrations, aerodynamic effects, and mucosal wave propagation along the medial surface. Quantitative data will be shown to give an overview of measured laryngeal parameter values. As yet, a full understanding of all existing interactions in voice production has not been achieved, and thus, where possible, we try to indicate areas needing further study. Recent Findings A further motivation behind this review is to highlight recent findings and technologies related to the study of vocal fold dynamics and its applications. For example, studies of interactions between vocal tract airflow and generation of acoustics have recently shown that airflow superior to the glottis is governed by not only vocal fold dynamics but also by subglottal and supraglottal structures. In addition, promising new methods to investigate kinematics and dynamics have been reported recently, including dynamic optical coherence tomography, X-ray stroboscopy and three-dimensional reconstruction with laser projection systems. Finally, we touch on the relevance of vocal fold dynamics to clinical laryngology and to clinically-oriented research. PMID:26581597

A self-cognizant dynamic system approach for prognostics and health management

NASA Astrophysics Data System (ADS)

Bai, Guangxing; Wang, Pingfeng; Hu, Chao

2015-03-01

Prognostics and health management (PHM) is an emerging engineering discipline that diagnoses and predicts how and when a system will degrade its performance and lose its partial or whole functionality. Due to the complexity and invisibility of rules and states of most dynamic systems, developing an effective approach to track evolving system states becomes a major challenge. This paper presents a new self-cognizant dynamic system (SCDS) approach that incorporates artificial intelligence into dynamic system modeling for PHM. A feed-forward neural network (FFNN) is selected to approximate a complex system response which is challenging task in general due to inaccessible system physics. The trained FFNN model is then embedded into a dual extended Kalman filter algorithm to track down system dynamics. A recursive computation technique used to update the FFNN model using online measurements is also derived. To validate the proposed SCDS approach, a battery dynamic system is considered as an experimental application. After modeling the battery system by a FFNN model and a state-space model, the state-of-charge (SoC) and state-of-health (SoH) are estimated by updating the FFNN model using the proposed approach. Experimental results suggest that the proposed approach improves the efficiency and accuracy for battery health management.

The behavioral dynamics of clinical trials.

PubMed

Leventhal, H; Nerenz, D R; Leventhal, E A; Love, R R; Bendena, L M

1991-01-01

Two ways of approaching the design of long-term clinical trials are presented and contrasted. The first, termed the "static" view, emphasizes close adherence to formal rules of study design. The second, termed the "dynamic" view, emphasizes the behavioral aspects of patient participation in trials of long duration. The dynamic view is discussed in detail, with discussion of how recruitment of participants, random assignment to conditions, compliance with protocol, and measurement of outcomes are affected by behavioral dynamics. Data from a recently completed tamoxifen toxicity trial are used to illustrate the points and to focus the discussion of behavioral dynamics on the design of a chemoprevention trial for breast cancer using tamoxifen.

Integrating stochastic time-dependent travel speed in solution methods for the dynamic dial-a-ride problem.

PubMed

Schilde, M; Doerner, K F; Hartl, R F

2014-10-01

In urban areas, logistic transportation operations often run into problems because travel speeds change, depending on the current traffic situation. If not accounted for, time-dependent and stochastic travel speeds frequently lead to missed time windows and thus poorer service. Especially in the case of passenger transportation, it often leads to excessive passenger ride times as well. Therefore, time-dependent and stochastic influences on travel speeds are relevant for finding feasible and reliable solutions. This study considers the effect of exploiting statistical information available about historical accidents, using stochastic solution approaches for the dynamic dial-a-ride problem (dynamic DARP). The authors propose two pairs of metaheuristic solution approaches, each consisting of a deterministic method (average time-dependent travel speeds for planning) and its corresponding stochastic version (exploiting stochastic information while planning). The results, using test instances with up to 762 requests based on a real-world road network, show that in certain conditions, exploiting stochastic information about travel speeds leads to significant improvements over deterministic approaches.

A logic-based dynamic modeling approach to explicate the evolution of the central dogma of molecular biology.

PubMed

Jafari, Mohieddin; Ansari-Pour, Naser; Azimzadeh, Sadegh; Mirzaie, Mehdi

It is nearly half a century past the age of the introduction of the Central Dogma (CD) of molecular biology. This biological axiom has been developed and currently appears to be all the more complex. In this study, we modified CD by adding further species to the CD information flow and mathematically expressed CD within a dynamic framework by using Boolean network based on its present-day and 1965 editions. We show that the enhancement of the Dogma not only now entails a higher level of complexity, but it also shows a higher level of robustness, thus far more consistent with the nature of biological systems. Using this mathematical modeling approach, we put forward a logic-based expression of our conceptual view of molecular biology. Finally, we show that such biological concepts can be converted into dynamic mathematical models using a logic-based approach and thus may be useful as a framework for improving static conceptual models in biology.

Formalization and analysis of reasoning by assumption.

PubMed

Bosse, Tibor; Jonker, Catholijn M; Treur, Jan

2006-01-02

This article introduces a novel approach for the analysis of the dynamics of reasoning processes and explores its applicability for the reasoning pattern called reasoning by assumption. More specifically, for a case study in the domain of a Master Mind game, it is shown how empirical human reasoning traces can be formalized and automatically analyzed against dynamic properties they fulfill. To this end, for the pattern of reasoning by assumption a variety of dynamic properties have been specified, some of which are considered characteristic for the reasoning pattern, whereas some other properties can be used to discriminate among different approaches to the reasoning. These properties have been automatically checked for the traces acquired in experiments undertaken. The approach turned out to be beneficial from two perspectives. First, checking characteristic properties contributes to the empirical validation of a theory on reasoning by assumption. Second, checking discriminating properties allows the analyst to identify different classes of human reasoners. 2006 Lawrence Erlbaum Associates, Inc.

A logic-based dynamic modeling approach to explicate the evolution of the central dogma of molecular biology

PubMed Central

Jafari, Mohieddin; Ansari-Pour, Naser; Azimzadeh, Sadegh; Mirzaie, Mehdi

2017-01-01

It is nearly half a century past the age of the introduction of the Central Dogma (CD) of molecular biology. This biological axiom has been developed and currently appears to be all the more complex. In this study, we modified CD by adding further species to the CD information flow and mathematically expressed CD within a dynamic framework by using Boolean network based on its present-day and 1965 editions. We show that the enhancement of the Dogma not only now entails a higher level of complexity, but it also shows a higher level of robustness, thus far more consistent with the nature of biological systems. Using this mathematical modeling approach, we put forward a logic-based expression of our conceptual view of molecular biology. Finally, we show that such biological concepts can be converted into dynamic mathematical models using a logic-based approach and thus may be useful as a framework for improving static conceptual models in biology. PMID:29267315

Moving From Static to Dynamic Models of the Onset of Mental Disorder: A Review.

PubMed

Nelson, Barnaby; McGorry, Patrick D; Wichers, Marieke; Wigman, Johanna T W; Hartmann, Jessica A

2017-05-01

In recent years, there has been increased focus on subthreshold stages of mental disorders, with attempts to model and predict which individuals will progress to full-threshold disorder. Given this research attention and the clinical significance of the issue, this article analyzes the assumptions of the theoretical models in the field. Psychiatric research into predicting the onset of mental disorder has shown an overreliance on one-off sampling of cross-sectional data (ie, a snapshot of clinical state and other risk markers) and may benefit from taking dynamic changes into account in predictive modeling. Cross-disciplinary approaches to complex system structures and changes, such as dynamical systems theory, network theory, instability mechanisms, chaos theory, and catastrophe theory, offer potent models that can be applied to the emergence (or decline) of psychopathology, including psychosis prediction, as well as to transdiagnostic emergence of symptoms. Psychiatric research may benefit from approaching psychopathology as a system rather than as a category, identifying dynamics of system change (eg, abrupt vs gradual psychosis onset), and determining the factors to which these systems are most sensitive (eg, interpersonal dynamics and neurochemical change) and the individual variability in system architecture and change. These goals can be advanced by testing hypotheses that emerge from cross-disciplinary models of complex systems. Future studies require repeated longitudinal assessment of relevant variables through either (or a combination of) micro-level (momentary and day-to-day) and macro-level (month and year) assessments. Ecological momentary assessment is a data collection technique appropriate for micro-level assessment. Relevant statistical approaches are joint modeling and time series analysis, including metric-based and model-based methods that draw on the mathematical principles of dynamical systems. This next generation of prediction studies may more accurately model the dynamic nature of psychopathology and system change as well as have treatment implications, such as introducing a means of identifying critical periods of risk for mental state deterioration.

Dynamic Maternal Gradients Control Timing and Shift-Rates for Drosophila Gap Gene Expression

PubMed Central

Verd, Berta; Crombach, Anton

2017-01-01

Pattern formation during development is a highly dynamic process. In spite of this, few experimental and modelling approaches take into account the explicit time-dependence of the rules governing regulatory systems. We address this problem by studying dynamic morphogen interpretation by the gap gene network in Drosophila melanogaster. Gap genes are involved in segment determination during early embryogenesis. They are activated by maternal morphogen gradients encoded by bicoid (bcd) and caudal (cad). These gradients decay at the same time-scale as the establishment of the antero-posterior gap gene pattern. We use a reverse-engineering approach, based on data-driven regulatory models called gene circuits, to isolate and characterise the explicitly time-dependent effects of changing morphogen concentrations on gap gene regulation. To achieve this, we simulate the system in the presence and absence of dynamic gradient decay. Comparison between these simulations reveals that maternal morphogen decay controls the timing and limits the rate of gap gene expression. In the anterior of the embyro, it affects peak expression and leads to the establishment of smooth spatial boundaries between gap domains. In the posterior of the embryo, it causes a progressive slow-down in the rate of gap domain shifts, which is necessary to correctly position domain boundaries and to stabilise the spatial gap gene expression pattern. We use a newly developed method for the analysis of transient dynamics in non-autonomous (time-variable) systems to understand the regulatory causes of these effects. By providing a rigorous mechanistic explanation for the role of maternal gradient decay in gap gene regulation, our study demonstrates that such analyses are feasible and reveal important aspects of dynamic gene regulation which would have been missed by a traditional steady-state approach. More generally, it highlights the importance of transient dynamics for understanding complex regulatory processes in development. PMID:28158178

Dynamic Maternal Gradients Control Timing and Shift-Rates for Drosophila Gap Gene Expression.

PubMed

Verd, Berta; Crombach, Anton; Jaeger, Johannes

2017-02-01

Pattern formation during development is a highly dynamic process. In spite of this, few experimental and modelling approaches take into account the explicit time-dependence of the rules governing regulatory systems. We address this problem by studying dynamic morphogen interpretation by the gap gene network in Drosophila melanogaster. Gap genes are involved in segment determination during early embryogenesis. They are activated by maternal morphogen gradients encoded by bicoid (bcd) and caudal (cad). These gradients decay at the same time-scale as the establishment of the antero-posterior gap gene pattern. We use a reverse-engineering approach, based on data-driven regulatory models called gene circuits, to isolate and characterise the explicitly time-dependent effects of changing morphogen concentrations on gap gene regulation. To achieve this, we simulate the system in the presence and absence of dynamic gradient decay. Comparison between these simulations reveals that maternal morphogen decay controls the timing and limits the rate of gap gene expression. In the anterior of the embyro, it affects peak expression and leads to the establishment of smooth spatial boundaries between gap domains. In the posterior of the embryo, it causes a progressive slow-down in the rate of gap domain shifts, which is necessary to correctly position domain boundaries and to stabilise the spatial gap gene expression pattern. We use a newly developed method for the analysis of transient dynamics in non-autonomous (time-variable) systems to understand the regulatory causes of these effects. By providing a rigorous mechanistic explanation for the role of maternal gradient decay in gap gene regulation, our study demonstrates that such analyses are feasible and reveal important aspects of dynamic gene regulation which would have been missed by a traditional steady-state approach. More generally, it highlights the importance of transient dynamics for understanding complex regulatory processes in development.

Implementing the Project Approach: A Case Study of Hybrid Pedagogy in a Hong Kong Kindergarten

ERIC Educational Resources Information Center

Chen, Jennifer J.; Li, Hui; Wang, Jing-ying

2017-01-01

The Project Approach has been promoted in Hong Kong kindergartens since the 1990s. However, the dynamic processes and underlying mechanisms involved in the teachers' implementation of this pedagogical method there have not yet been fully investigated. This case study of one typical kindergarten in Hong Kong documented how and why eight teachers…

An optimal strategy for functional mapping of dynamic trait loci.

PubMed

Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling

2010-02-01

As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.

Ab initio implementation of quantum trajectory mean-field approach and dynamical simulation of the N{sub 2}CO photodissociation

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

Xie, Binbin; Liu, Lihong; Cui, Ganglong

2015-11-21

In this work, the recently introduced quantum trajectory mean-field (QTMF) approach is implemented and employed to explore photodissociation dynamics of diazirinone (N{sub 2}CO), which are based on the high-level ab initio calculation. For comparison, the photodissociation process has been simulated as well with the fewest-switches surface hopping (FSSH) and the ab initio multiple spawning (AIMS) methods. Overall, the dynamical behavior predicted by the three methods is consistent. The N{sub 2}CO photodissociation at λ > 335 nm is an ultrafast process and the two C—N bonds are broken in a stepwise way, giving birth to CO and N{sub 2} as themore » final products in the ground state. Meanwhile, some noticeable differences were found in the QTMF, FSSH, and AIMS simulated time constants for fission of the C—N bonds, excited-state lifetime, and nonadiabatic transition ratios in different intersection regions. These have been discussed in detail. The present study provides a clear evidence that direct ab initio QTMF approach is one of the reliable tools for simulating nonadiabatic dynamics processes.« less

Protein displacements under external forces: An atomistic Langevin dynamics approach.

PubMed

Gnandt, David; Utz, Nadine; Blumen, Alexander; Koslowski, Thorsten

2009-02-28

We present a fully atomistic Langevin dynamics approach as a method to simulate biopolymers under external forces. In the harmonic regime, this approach permits the computation of the long-term dynamics using only the eigenvalues and eigenvectors of the Hessian matrix of second derivatives. We apply this scheme to identify polymorphs of model proteins by their mechanical response fingerprint, and we relate the averaged dynamics of proteins to their biological functionality, with the ion channel gramicidin A, a phosphorylase, and neuropeptide Y as examples. In an environment akin to dilute solutions, even small proteins show relaxation times up to 50 ns. Atomically resolved Langevin dynamics computations have been performed for the stretched gramicidin A ion channel.

Dynamics of Biomarkers in Relation to Aging and Mortality

PubMed Central

Arbeev, Konstantin G.; Ukraintseva, Svetlana V.; Yashin, Anatoliy I.

2016-01-01

Contemporary longitudinal studies collect repeated measurements of biomarkers allowing one to analyze their dynamics in relation to mortality, morbidity, or other health-related outcomes. Rich and diverse data collected in such studies provide opportunities to investigate how various socioeconomic, demographic, behavioral and other variables can interact with biological and genetic factors to produce differential rates of aging in individuals. In this paper, we review some recent publications investigating dynamics of biomarkers in relation to mortality, which use single biomarkers as well as cumulative measures combining information from multiple biomarkers. We also discuss the analytical approach, the stochastic process models, which conceptualizes several aging-related mechanisms in the structure of the model and allows evaluating “hidden” characteristics of aging-related changes indirectly from available longitudinal data on biomarkers and follow-up on mortality or onset of diseases taking into account other relevant factors (both genetic and non-genetic). We also discuss an extension of the approach, which considers ranges of “optimal values” of biomarkers rather than a single optimal value as in the original model. We discuss practical applications of the approach to single biomarkers and cumulative measures highlighting that the potential of applications to cumulative measures is still largely underused. PMID:27138087

Innovation diffusion on time-varying activity driven networks

NASA Astrophysics Data System (ADS)

Rizzo, Alessandro; Porfiri, Maurizio

2016-01-01

Since its introduction in the 1960s, the theory of innovation diffusion has contributed to the advancement of several research fields, such as marketing management and consumer behavior. The 1969 seminal paper by Bass [F.M. Bass, Manag. Sci. 15, 215 (1969)] introduced a model of product growth for consumer durables, which has been extensively used to predict innovation diffusion across a range of applications. Here, we propose a novel approach to study innovation diffusion, where interactions among individuals are mediated by the dynamics of a time-varying network. Our approach is based on the Bass' model, and overcomes key limitations of previous studies, which assumed timescale separation between the individual dynamics and the evolution of the connectivity patterns. Thus, we do not hypothesize homogeneous mixing among individuals or the existence of a fixed interaction network. We formulate our approach in the framework of activity driven networks to enable the analysis of the concurrent evolution of the interaction and individual dynamics. Numerical simulations offer a systematic analysis of the model behavior and highlight the role of individual activity on market penetration when targeted advertisement campaigns are designed, or a competition between two different products takes place.

Evaluation of uncertainty for regularized deconvolution: A case study in hydrophone measurements.

PubMed

Eichstädt, S; Wilkens, V

2017-06-01

An estimation of the measurand in dynamic metrology usually requires a deconvolution based on a dynamic calibration of the measuring system. Since deconvolution is, mathematically speaking, an ill-posed inverse problem, some kind of regularization is required to render the problem stable and obtain usable results. Many approaches to regularized deconvolution exist in the literature, but the corresponding evaluation of measurement uncertainties is, in general, an unsolved issue. In particular, the uncertainty contribution of the regularization itself is a topic of great importance, because it has a significant impact on the estimation result. Here, a versatile approach is proposed to express prior knowledge about the measurand based on a flexible, low-dimensional modeling of an upper bound on the magnitude spectrum of the measurand. This upper bound allows the derivation of an uncertainty associated with the regularization method in line with the guidelines in metrology. As a case study for the proposed method, hydrophone measurements in medical ultrasound with an acoustic working frequency of up to 7.5 MHz are considered, but the approach is applicable for all kinds of estimation methods in dynamic metrology, where regularization is required and which can be expressed as a multiplication in the frequency domain.

A Multiscale Survival Process for Modeling Human Activity Patterns.

PubMed

Zhang, Tianyang; Cui, Peng; Song, Chaoming; Zhu, Wenwu; Yang, Shiqiang

2016-01-01

Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

A variational conformational dynamics approach to the selection of collective variables in metadynamics.

PubMed

McCarty, James; Parrinello, Michele

2017-11-28

In this paper, we combine two powerful computational techniques, well-tempered metadynamics and time-lagged independent component analysis. The aim is to develop a new tool for studying rare events and exploring complex free energy landscapes. Metadynamics is a well-established and widely used enhanced sampling method whose efficiency depends on an appropriate choice of collective variables. Often the initial choice is not optimal leading to slow convergence. However by analyzing the dynamics generated in one such run with a time-lagged independent component analysis and the techniques recently developed in the area of conformational dynamics, we obtain much more efficient collective variables that are also better capable of illuminating the physics of the system. We demonstrate the power of this approach in two paradigmatic examples.

A variational conformational dynamics approach to the selection of collective variables in metadynamics

NASA Astrophysics Data System (ADS)

McCarty, James; Parrinello, Michele

2017-11-01

In this paper, we combine two powerful computational techniques, well-tempered metadynamics and time-lagged independent component analysis. The aim is to develop a new tool for studying rare events and exploring complex free energy landscapes. Metadynamics is a well-established and widely used enhanced sampling method whose efficiency depends on an appropriate choice of collective variables. Often the initial choice is not optimal leading to slow convergence. However by analyzing the dynamics generated in one such run with a time-lagged independent component analysis and the techniques recently developed in the area of conformational dynamics, we obtain much more efficient collective variables that are also better capable of illuminating the physics of the system. We demonstrate the power of this approach in two paradigmatic examples.

Voronoi Diagram Based Optimization of Dynamic Reactive Power Sources

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

Huang, Weihong; Sun, Kai; Qi, Junjian

2015-01-01

Dynamic var sources can effectively mitigate fault-induced delayed voltage recovery (FIDVR) issues or even voltage collapse. This paper proposes a new approach to optimization of the sizes of dynamic var sources at candidate locations by a Voronoi diagram based algorithm. It first disperses sample points of potential solutions in a searching space, evaluates a cost function at each point by barycentric interpolation for the subspaces around the point, and then constructs a Voronoi diagram about cost function values over the entire space. Accordingly, the final optimal solution can be obtained. Case studies on the WSCC 9-bus system and NPCC 140-busmore » system have validated that the new approach can quickly identify the boundary of feasible solutions in searching space and converge to the global optimal solution.« less

Factors influencing crime rates: an econometric analysis approach

NASA Astrophysics Data System (ADS)

Bothos, John M. A.; Thomopoulos, Stelios C. A.

2016-05-01

The scope of the present study is to research the dynamics that determine the commission of crimes in the US society. Our study is part of a model we are developing to understand urban crime dynamics and to enhance citizens' "perception of security" in large urban environments. The main targets of our research are to highlight dependence of crime rates on certain social and economic factors and basic elements of state anticrime policies. In conducting our research, we use as guides previous relevant studies on crime dependence, that have been performed with similar quantitative analyses in mind, regarding the dependence of crime on certain social and economic factors using statistics and econometric modelling. Our first approach consists of conceptual state space dynamic cross-sectional econometric models that incorporate a feedback loop that describes crime as a feedback process. In order to define dynamically the model variables, we use statistical analysis on crime records and on records about social and economic conditions and policing characteristics (like police force and policing results - crime arrests), to determine their influence as independent variables on crime, as the dependent variable of our model. The econometric models we apply in this first approach are an exponential log linear model and a logit model. In a second approach, we try to study the evolvement of violent crime through time in the US, independently as an autonomous social phenomenon, using autoregressive and moving average time-series econometric models. Our findings show that there are certain social and economic characteristics that affect the formation of crime rates in the US, either positively or negatively. Furthermore, the results of our time-series econometric modelling show that violent crime, viewed solely and independently as a social phenomenon, correlates with previous years crime rates and depends on the social and economic environment's conditions during previous years.

Implementing a GPU-based numerical algorithm for modelling dynamics of a high-speed train

NASA Astrophysics Data System (ADS)

Sytov, E. S.; Bratus, A. S.; Yurchenko, D.

2018-04-01

This paper discusses the initiative of implementing a GPU-based numerical algorithm for studying various phenomena associated with dynamics of a high-speed railway transport. The proposed numerical algorithm for calculating a critical speed of the bogie is based on the first Lyapunov number. Numerical algorithm is validated by analytical results, derived for a simple model. A dynamic model of a carriage connected to a new dual-wheelset flexible bogie is studied for linear and dry friction damping. Numerical results obtained by CPU, MPU and GPU approaches are compared and appropriateness of these methods is discussed.

Single-particle dynamics of the Anderson model: a local moment approach

NASA Astrophysics Data System (ADS)

Glossop, Matthew T.; Logan, David E.

2002-07-01

A non-perturbative local moment approach to single-particle dynamics of the general asymmetric Anderson impurity model is developed. The approach encompasses all energy scales and interaction strengths. It captures thereby strong coupling Kondo behaviour, including the resultant universal scaling behaviour of the single-particle spectrum; as well as the mixed valence and essentially perturbative empty orbital regimes. The underlying approach is physically transparent and innately simple, and as such is capable of practical extension to lattice-based models within the framework of dynamical mean-field theory.

The Role of Dynamic Software in the Identification and Construction of Mathematical Relationships

ERIC Educational Resources Information Center

Santos-Trigo, Manuel

2004-01-01

What features of mathematical thinking do students exhibit when they use dynamic software in their problem solving approaches? To what extent does the systematic use of technology favour students' development of problem solving competences? What type of reasoning do students develop as a result of using a particular tool? This study documents…

Emerging High School Students' Problem Solving Trajectories Based on the Use of Dynamic Software

ERIC Educational Resources Information Center

Santos-Trigo, Manuel; Cristobal-Escalante, Cesar

2008-01-01

This study documents problem solving approaches that high school students develop as a result of using systematically Cabri-Geometry software. Results show that the use of the software becomes an important tool for students to construct dynamic representations of the problems that were used to identify and examine different mathematical relations.…

A dynamical systems approach to actin-based motility in Listeria monocytogenes

NASA Astrophysics Data System (ADS)

Hotton, S.

2010-11-01

A simple kinematic model for the trajectories of Listeria monocytogenes is generalized to a dynamical system rich enough to exhibit the resonant Hopf bifurcation structure of excitable media and simple enough to be studied geometrically. It is shown how L. monocytogenes trajectories and meandering spiral waves are organized by the same type of attracting set.

Potential Originality and Effectiveness: The Dynamic Definition of Creativity

ERIC Educational Resources Information Center

Corazza, Giovanni Emanuele

2016-01-01

Given the central role of creativity in the future post-information society, a call for a pragmatist approach to the study of creativity is advocated, that brings as a consequence the recognition of the dynamic nature of this phenomenon. At the foundation of the proposed new theoretical framework lies the definition of creativity itself, which is…

Beyond "on" or "with": Questioning Power Dynamics and Knowledge Production in "Child-Oriented" Research Methodology

ERIC Educational Resources Information Center

Hunleth, Jean

2011-01-01

By taking a reflexive approach to research methodology, this article contributes to discussions on power dynamics and knowledge production in the social studies of children. The author describes and analyzes three research methods that she used with children--drawing, child-led tape-recording and focus group discussions. These methods were carried…

Dynamics of Language Contact in China: Ethnolinguistic Diversity and Variation in Yunnan

ERIC Educational Resources Information Center

Gao, Katie B.

2017-01-01

The study of language contact epitomizes the dynamics of language as a system of human communication. The competing linguistic forces at work when speakers of different language varieties come into contact can be narrowed down to two basic concepts--convergence and divergence. Looking at linguistic areas using a macro approach, languages in…

U(1)-invariant membranes: The geometric formulation, Abel, and pendulum differential equations

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

Zheltukhin, A. A.; Fysikum, AlbaNova, Stockholm University, 106 91 Stockholm; NORDITA, Roslagstullsbacken 23, 106 91 Stockholm

The geometric approach to study the dynamics of U(1)-invariant membranes is developed. The approach reveals an important role of the Abel nonlinear differential equation of the first type with variable coefficients depending on time and one of the membrane extendedness parameters. The general solution of the Abel equation is constructed. Exact solutions of the whole system of membrane equations in the D=5 Minkowski space-time are found and classified. It is shown that if the radial component of the membrane world vector is only time dependent, then the dynamics is described by the pendulum equation.

Thermodynamics of a time-dependent and dissipative oval billiard: A heat transfer and billiard approach.

PubMed

Leonel, Edson D; Galia, Marcus Vinícius Camillo; Barreiro, Luiz Antonio; Oliveira, Diego F M

2016-12-01

We study some statistical properties for the behavior of the average squared velocity-hence the temperature-for an ensemble of classical particles moving in a billiard whose boundary is time dependent. We assume the collisions of the particles with the boundary of the billiard are inelastic, leading the average squared velocity to reach a steady-state dynamics for large enough time. The description of the stationary state is made by using two different approaches: (i) heat transfer motivated by the Fourier law and (ii) billiard dynamics using either numerical simulations and theoretical description.

An alternative way to track the hot money in turbulent times

NASA Astrophysics Data System (ADS)

Sensoy, Ahmet

2015-02-01

During recent years, networks have proven to be an efficient way to characterize and investigate a wide range of complex financial systems. In this study, we first obtain the dynamic conditional correlations between filtered exchange rates (against US dollar) of several countries and introduce a time-varying threshold correlation level to define dynamic strong correlations between these exchange rates. Then, using evolving networks obtained from strong correlations, we propose an alternative approach to track the hot money in turbulent times. The approach is demonstrated for the time period including the financial turmoil of 2008. Other applications are also discussed.

Emergent Vortex Patterns in Systems of Self-Propelled, Chiral Particles

NASA Astrophysics Data System (ADS)

Huber, Lorenz; Denk, Jonas; Reithmann, Emanuel; Frey, Erwin

Self-organization of FtsZ polymers is vital for Z-ring assembly during bacterial cell division, and has been studied using reconstituted in vitro model systems. Employing Brownian dynamics simulations and a Boltzmann approach, we model FtsZ polymers as active particles moving along chiral circular paths. With both theoretical approaches we find self-organization into vortex structures and characterize different states in parameter states. Our work demonstrates that these patterns are robust and are generic for active chiral matter. Moreover, we show that the dynamics at the onset of pattern formation is described by a generalized complex Ginzburg-Landau equation.

Structural uncertainty of downscaled climate model output in a difficult-to-resolve environment: data sparseness and parameterization error contribution to statistical and dynamical downscaling output in the U.S. Caribbean region

NASA Astrophysics Data System (ADS)

Terando, A. J.; Grade, S.; Bowden, J.; Henareh Khalyani, A.; Wootten, A.; Misra, V.; Collazo, J.; Gould, W. A.; Boyles, R.

2016-12-01

Sub-tropical island nations may be particularly vulnerable to anthropogenic climate change because of predicted changes in the hydrologic cycle that would lead to significant drying in the future. However, decision makers in these regions have seen their adaptation planning efforts frustrated by the lack of island-resolving climate model information. Recently, two investigations have used statistical and dynamical downscaling techniques to develop climate change projections for the U.S. Caribbean region (Puerto Rico and U.S. Virgin Islands). We compare the results from these two studies with respect to three commonly downscaled CMIP5 global climate models (GCMs). The GCMs were dynamically downscaled at a convective-permitting scale using two different regional climate models. The statistical downscaling approach was conducted at locations with long-term climate observations and then further post-processed using climatologically aided interpolation (yielding two sets of projections). Overall, both approaches face unique challenges. The statistical approach suffers from a lack of observations necessary to constrain the model, particularly at the land-ocean boundary and in complex terrain. The dynamically downscaled model output has a systematic dry bias over the island despite ample availability of moisture in the atmospheric column. Notwithstanding these differences, both approaches are consistent in projecting a drier climate that is driven by the strong global-scale anthropogenic forcing.

A control-oriented lithium-ion battery pack model for plug-in hybrid electric vehicle cycle-life studies and system design with consideration of health management

NASA Astrophysics Data System (ADS)

Cordoba-Arenas, Andrea; Onori, Simona; Rizzoni, Giorgio

2015-04-01

A crucial step towards the large-scale introduction of plug-in hybrid electric vehicles (PHEVs) in the market is to reduce the cost of its battery systems. Currently, battery cycle- and calendar-life represents one of the greatest uncertainties in the total life-cycle cost of battery systems. The field of battery aging modeling and prognosis has seen progress with respect to model-based and data-driven approaches to describe the aging of battery cells. However, in real world applications cells are interconnected and aging propagates. The propagation of aging from one cell to others exhibits itself in a reduced battery system life. This paper proposes a control-oriented battery pack model that describes the propagation of aging and its effect on the life span of battery systems. The modeling approach is such that it is able to predict pack aging, thermal, and electrical dynamics under actual PHEV operation, and includes consideration of random variability of the cells, electrical topology and thermal management. The modeling approach is based on the interaction between dynamic system models of the electrical and thermal dynamics, and dynamic models of cell aging. The system-level state-of-health (SOH) is assessed based on knowledge of individual cells SOH, pack electrical topology and voltage equalization approach.

Many-body excitations and deexcitations in trapped ultracold bosonic clouds

NASA Astrophysics Data System (ADS)

Theisen, Marcus; Streltsov, Alexej I.

2016-11-01

We employ the multiconfigurational time-dependent Hartree for bosons (MCTDHB) method to study excited states of interacting Bose-Einstein condensates confined by harmonic and double-well trap potentials. Two approaches to access excitations, one static and the other dynamic, are investigated and contrasted. In static simulations the low-lying excitations are computed by utilizing a linear-response theory constructed on top of a static MCTDHB solution (LR-MCTDHB). Complimentarily, we propose two dynamic protocols that address excitations by propagating the MCTDHB wave function. In particular, we investigate dipolelike oscillations induced by shifting the origin of the confining potential and breathinglike excitations by quenching the frequency of a parabolic part of the trap. To contrast static predictions and dynamic results we compute the time evolution and regard the respective Fourier transform of several local and nonlocal observables. Namely, we study the expectation value of the position operator , its variance Var [x (t )] , and a local density computed at selected positions. We find that the variance is the most sensitive and informative quantity: Along with excitations it contains information about deexcitations even in a linear regime of the induced dynamics. The dynamic protocols are found to access the many-body excitations predicted by the static LR-MCTDHB approach.

Engineering Risk Assessment of Space Thruster Challenge Problem

NASA Technical Reports Server (NTRS)

Mathias, Donovan L.; Mattenberger, Christopher J.; Go, Susie

2014-01-01

The Engineering Risk Assessment (ERA) team at NASA Ames Research Center utilizes dynamic models with linked physics-of-failure analyses to produce quantitative risk assessments of space exploration missions. This paper applies the ERA approach to the baseline and extended versions of the PSAM Space Thruster Challenge Problem, which investigates mission risk for a deep space ion propulsion system with time-varying thruster requirements and operations schedules. The dynamic mission is modeled using a combination of discrete and continuous-time reliability elements within the commercially available GoldSim software. Loss-of-mission (LOM) probability results are generated via Monte Carlo sampling performed by the integrated model. Model convergence studies are presented to illustrate the sensitivity of integrated LOM results to the number of Monte Carlo trials. A deterministic risk model was also built for the three baseline and extended missions using the Ames Reliability Tool (ART), and results are compared to the simulation results to evaluate the relative importance of mission dynamics. The ART model did a reasonable job of matching the simulation models for the baseline case, while a hybrid approach using offline dynamic models was required for the extended missions. This study highlighted that state-of-the-art techniques can adequately adapt to a range of dynamic problems.

Si amorphization by focused ion beam milling: Point defect model with dynamic BCA simulation and experimental validation.

PubMed

Huang, J; Loeffler, M; Muehle, U; Moeller, W; Mulders, J J L; Kwakman, L F Tz; Van Dorp, W F; Zschech, E

2018-01-01

A Ga focused ion beam (FIB) is often used in transmission electron microscopy (TEM) analysis sample preparation. In case of a crystalline Si sample, an amorphous near-surface layer is formed by the FIB process. In order to optimize the FIB recipe by minimizing the amorphization, it is important to predict the amorphous layer thickness from simulation. Molecular Dynamics (MD) simulation has been used to describe the amorphization, however, it is limited by computational power for a realistic FIB process simulation. On the other hand, Binary Collision Approximation (BCA) simulation is able and has been used to simulate ion-solid interaction process at a realistic scale. In this study, a Point Defect Density approach is introduced to a dynamic BCA simulation, considering dynamic ion-solid interactions. We used this method to predict the c-Si amorphization caused by FIB milling on Si. To validate the method, dedicated TEM studies are performed. It shows that the amorphous layer thickness predicted by the numerical simulation is consistent with the experimental data. In summary, the thickness of the near-surface Si amorphization layer caused by FIB milling can be well predicted using the Point Defect Density approach within the dynamic BCA model. Copyright © 2017 Elsevier B.V. All rights reserved.

Man/Machine Interaction Dynamics And Performance (MMIDAP) capability

NASA Technical Reports Server (NTRS)

Frisch, Harold P.

1991-01-01

The creation of an ability to study interaction dynamics between a machine and its human operator can be approached from a myriad of directions. The Man/Machine Interaction Dynamics and Performance (MMIDAP) project seeks to create an ability to study the consequences of machine design alternatives relative to the performance of both machine and operator. The class of machines to which this study is directed includes those that require the intelligent physical exertions of a human operator. While Goddard's Flight Telerobotic's program was expected to be a major user, basic engineering design and biomedical applications reach far beyond telerobotics. Ongoing efforts are outlined of the GSFC and its University and small business collaborators to integrate both human performance and musculoskeletal data bases with analysis capabilities necessary to enable the study of dynamic actions, reactions, and performance of coupled machine/operator systems.

Going the Second Mile. One Way of Looking at It

ERIC Educational Resources Information Center

Van Til, William

1974-01-01

Desegregation, still in process, constituted the first mile. Now desegregation is making few major gains. Through the approaches of "community study, democratic atmosphere, curriculum permeation, and group dynamics," joined by the current emphasis on the "direct experience" approach, perhaps the second mile can be traveled to achieve integration.…

The Dynamic Interplay among EFL Learners' Ambiguity Tolerance, Adaptability, Cultural Intelligence, Learning Approach, and Language Achievement

ERIC Educational Resources Information Center

Alahdadi, Shadi; Ghanizadeh, Afsaneh

2017-01-01

A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and…

System identification principles in studies of forest dynamics.

Treesearch

Rolfe A. Leary

1970-01-01

Shows how it is possible to obtain governing equation parameter estimates on the basis of observed system states. The approach used represents a constructive alternative to regression techniques for models expressed as differential equations. This approach allows scientists to more completely quantify knowledge of forest development processes, to express theories in...

Research in Distance Education: A System Modeling Approach.

ERIC Educational Resources Information Center

Saba, Farhad; Twitchell, David

1988-01-01

Describes how a computer simulation research method can be used for studying distance education systems. Topics discussed include systems research in distance education; a technique of model development using the System Dynamics approach and DYNAMO simulation language; and a computer simulation of a prototype model. (18 references) (LRW)

Computed Tomography Studies of Lung Mechanics

PubMed Central

Simon, Brett A.; Christensen, Gary E.; Low, Daniel A.; Reinhardt, Joseph M.

2005-01-01

The study of lung mechanics has progressed from global descriptions of lung pressure and volume relationships to the high-resolution, three-dimensional, quantitative measurement of dynamic regional mechanical properties and displacements. X-ray computed tomography (CT) imaging is ideally suited to the study of regional lung mechanics in intact subjects because of its high spatial and temporal resolution, correlation of functional data with anatomic detail, increasing volumetric data acquisition, and the unique relationship between CT density and lung air content. This review presents an overview of CT measurement principles and limitations for the study of regional mechanics, reviews some of the early work that set the stage for modern imaging approaches and impacted the understanding and management of patients with acute lung injury, and presents evolving novel approaches for the analysis and application of dynamic volumetric lung image data. PMID:16352757

Ultrafast electron diffraction and electron microscopy: present status and future prospects

NASA Astrophysics Data System (ADS)

Ishchenko, A. A.; Aseyev, S. A.; Bagratashvili, V. N.; Panchenko, V. Ya; Ryabov, E. A.

2014-07-01

Acting as complementary research tools, high time-resolved spectroscopy and diffractometry techniques proceeding from various physical principles open up new possibilities for studying matter with necessary integration of the 'structure-dynamics-function' triad in physics, chemistry, biology and materials science. Since the 1980s, a new field of research has started at the leading research laboratories, aimed at developing means of filming the coherent dynamics of nuclei in molecules and fast processes in biological objects ('atomic and molecular movies'). The utilization of ultrashort laser pulse sources has significantly modified traditional electron beam approaches to and provided high space-time resolution for the study of materials. Diffraction methods using frame-by-frame filming and the development of the main principles of the study of coherent dynamics of atoms have paved the way to observing wave packet dynamics, the intermediate states of reaction centers, and the dynamics of electrons in molecules, thus allowing a transition from the kinetics to the dynamics of the phase trajectories of molecules in the investigation of chemical reactions.

Studying Cellular Signal Transduction with OMIC Technologies.

PubMed

Landry, Benjamin D; Clarke, David C; Lee, Michael J

2015-10-23

In the gulf between genotype and phenotype exists proteins and, in particular, protein signal transduction systems. These systems use a relatively limited parts list to respond to a much longer list of extracellular, environmental, and/or mechanical cues with rapidity and specificity. Most signaling networks function in a highly non-linear and often contextual manner. Furthermore, these processes occur dynamically across space and time. Because of these complexities, systems and "OMIC" approaches are essential for the study of signal transduction. One challenge in using OMIC-scale approaches to study signaling is that the "signal" can take different forms in different situations. Signals are encoded in diverse ways such as protein-protein interactions, enzyme activities, localizations, or post-translational modifications to proteins. Furthermore, in some cases, signals may be encoded only in the dynamics, duration, or rates of change of these features. Accordingly, systems-level analyses of signaling may need to integrate multiple experimental and/or computational approaches. As the field has progressed, the non-triviality of integrating experimental and computational analyses has become apparent. Successful use of OMIC methods to study signaling will require the "right" experiments and the "right" modeling approaches, and it is critical to consider both in the design phase of the project. In this review, we discuss common OMIC and modeling approaches for studying signaling, emphasizing the philosophical and practical considerations for effectively merging these two types of approaches to maximize the probability of obtaining reliable and novel insights into signaling biology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatial operator algebra for flexible multibody dynamics

NASA Technical Reports Server (NTRS)

Jain, A.; Rodriguez, G.

1993-01-01

This paper presents an approach to modeling the dynamics of flexible multibody systems such as flexible spacecraft and limber space robotic systems. A large number of degrees of freedom and complex dynamic interactions are typical in these systems. This paper uses spatial operators to develop efficient recursive algorithms for the dynamics of these systems. This approach very efficiently manages complexity by means of a hierarchy of mathematical operations.

Online optimization of storage ring nonlinear beam dynamics

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

Huang, Xiaobiao; Safranek, James

2015-08-01

We propose to optimize the nonlinear beam dynamics of existing and future storage rings with direct online optimization techniques. This approach may have crucial importance for the implementation of diffraction limited storage rings. In this paper considerations and algorithms for the online optimization approach are discussed. We have applied this approach to experimentally improve the dynamic aperture of the SPEAR3 storage ring with the robust conjugate direction search method and the particle swarm optimization method. The dynamic aperture was improved by more than 5 mm within a short period of time. Experimental setup and results are presented.

A qualitative approach for recovering relative depths in dynamic scenes

NASA Technical Reports Server (NTRS)

Haynes, S. M.; Jain, R.

1987-01-01

This approach to dynamic scene analysis is a qualitative one. It computes relative depths using very general rules. The depths calculated are qualitative in the sense that the only information obtained is which object is in front of which others. The motion is qualitative in the sense that the only required motion data is whether objects are moving toward or away from the camera. Reasoning, which takes into account the temporal character of the data and the scene, is qualitative. This approach to dynamic scene analysis can tolerate imprecise data because in dynamic scenes the data are redundant.

Inferring Ice Thickness from a Glacier Dynamics Model and Multiple Surface Datasets.

NASA Astrophysics Data System (ADS)

Guan, Y.; Haran, M.; Pollard, D.

2017-12-01

The future behavior of the West Antarctic Ice Sheet (WAIS) may have a major impact on future climate. For instance, ice sheet melt may contribute significantly to global sea level rise. Understanding the current state of WAIS is therefore of great interest. WAIS is drained by fast-flowing glaciers which are major contributors to ice loss. Hence, understanding the stability and dynamics of glaciers is critical for predicting the future of the ice sheet. Glacier dynamics are driven by the interplay between the topography, temperature and basal conditions beneath the ice. A glacier dynamics model describes the interactions between these processes. We develop a hierarchical Bayesian model that integrates multiple ice sheet surface data sets with a glacier dynamics model. Our approach allows us to (1) infer important parameters describing the glacier dynamics, (2) learn about ice sheet thickness, and (3) account for errors in the observations and the model. Because we have relatively dense and accurate ice thickness data from the Thwaites Glacier in West Antarctica, we use these data to validate the proposed approach. The long-term goal of this work is to have a general model that may be used to study multiple glaciers in the Antarctic.

Validity of the top-down approach of inverse dynamics analysis in fast and large rotational trunk movements.

PubMed

Iino, Yoichi; Kojima, Takeji

2012-08-01

This study investigated the validity of the top-down approach of inverse dynamics analysis in fast and large rotational movements of the trunk about three orthogonal axes of the pelvis for nine male collegiate students. The maximum angles of the upper trunk relative to the pelvis were approximately 47°, 49°, 32°, and 55° for lateral bending, flexion, extension, and axial rotation, respectively, with maximum angular velocities of 209°/s, 201°/s, 145°/s, and 288°/s, respectively. The pelvic moments about the axes during the movements were determined using the top-down and bottom-up approaches of inverse dynamics and compared between the two approaches. Three body segment inertial parameter sets were estimated using anthropometric data sets (Ae et al., Biomechanism 11, 1992; De Leva, J Biomech, 1996; Dumas et al., J Biomech, 2007). The root-mean-square errors of the moments and the absolute errors of the peaks of the moments were generally smaller than 10 N·m. The results suggest that the pelvic moment in motions involving fast and large trunk movements can be determined with a certain level of validity using the top-down approach in which the trunk is modeled as two or three rigid-link segments.

A scale-based approach to interdisciplinary research and expertise in sports.

PubMed

Ibáñez-Gijón, Jorge; Buekers, Martinus; Morice, Antoine; Rao, Guillaume; Mascret, Nicolas; Laurin, Jérome; Montagne, Gilles

2017-02-01

After more than 20 years since the introduction of ecological and dynamical approaches in sports research, their promising opportunity for interdisciplinary research has not been fulfilled yet. The complexity of the research process and the theoretical and empirical difficulties associated with an integrated ecological-dynamical approach have been the major factors hindering the generalisation of interdisciplinary projects in sports sciences. To facilitate this generalisation, we integrate the major concepts from the ecological and dynamical approaches to study behaviour as a multi-scale process. Our integration gravitates around the distinction between functional (ecological) and execution (organic) scales, and their reciprocal intra- and inter-scale constraints. We propose an (epistemological) scale-based definition of constraints that accounts for the concept of synergies as emergent coordinative structures. To illustrate how we can operationalise the notion of multi-scale synergies we use an interdisciplinary model of locomotor pointing. To conclude, we show the value of this approach for interdisciplinary research in sport sciences, as we discuss two examples of task-specific dimensionality reduction techniques in the context of an ongoing project that aims to unveil the determinants of expertise in basketball free throw shooting. These techniques provide relevant empirical evidence to help bootstrap the challenging modelling efforts required in sport sciences.

A multi-omics and imaging approach to understand soil organic matter composition and its interaction with microbes.

NASA Astrophysics Data System (ADS)

Tfaily, M. M.; Walker, L. R.; Kyle, J. E.; Chu, R. K.; Dohnalkova, A.; Tolic, N.; Orton, D.; Robinson, E. R.; Paša-Tolić, L.; Hess, N. J.

2015-12-01

The focus on soil C dynamics is currently relevant as researchers and policymakers strive to understand the feedbacks between ecosystem stress and climate change. Successful development of molecular profiles that link soil microbiology with soil carbon (C) dynamics to ascertain soil vulnerability and resilience to climate change would have great impact on assessments of soil ecosystems in response to climate change. Additionally, a better understanding of the soil C dynamics would improve climate modeling, and fate and transport of carbon across terrestrial, subsurface and atmospheric interfaces. Unravelling the wide range of possible interactions between and within the microbial communities, with minerals and organic compounds in the terrestrial ecosystem requires a multimodal, molecular approach. Here we report on the use of a combination of several molecular 'omics' approaches: metabolomics, metallomics, lipidomics, and proteomics coupled with a suite of high resolution imaging, and X-ray diffraction crystallographic techniques, as a novel methodology to understand SOM composition, and its interaction with microbial communities in different ecosystems, including C associated with mineral surfaces. The findings of these studies provide insights into the SOM persistence and microbial stabilization of carbon in ecosystems and reveal the powerful coupling of a multi-scale of techniques. Examples of this approach will be presented from field studies of simulated climate change, and laboratory column-grown Pinus resinosa mesocosms.

Moving alcohol prevention research forward-Part II: new directions grounded in community-based system dynamics modeling.

PubMed

Apostolopoulos, Yorghos; Lemke, Michael K; Barry, Adam E; Lich, Kristen Hassmiller

2018-02-01

Given the complexity of factors contributing to alcohol misuse, appropriate epistemologies and methodologies are needed to understand and intervene meaningfully. We aimed to (1) provide an overview of computational modeling methodologies, with an emphasis on system dynamics modeling; (2) explain how community-based system dynamics modeling can forge new directions in alcohol prevention research; and (3) present a primer on how to build alcohol misuse simulation models using system dynamics modeling, with an emphasis on stakeholder involvement, data sources and model validation. Throughout, we use alcohol misuse among college students in the United States as a heuristic example for demonstrating these methodologies. System dynamics modeling employs a top-down aggregate approach to understanding dynamically complex problems. Its three foundational properties-stocks, flows and feedbacks-capture non-linearity, time-delayed effects and other system characteristics. As a methodological choice, system dynamics modeling is amenable to participatory approaches; in particular, community-based system dynamics modeling has been used to build impactful models for addressing dynamically complex problems. The process of community-based system dynamics modeling consists of numerous stages: (1) creating model boundary charts, behavior-over-time-graphs and preliminary system dynamics models using group model-building techniques; (2) model formulation; (3) model calibration; (4) model testing and validation; and (5) model simulation using learning-laboratory techniques. Community-based system dynamics modeling can provide powerful tools for policy and intervention decisions that can result ultimately in sustainable changes in research and action in alcohol misuse prevention. © 2017 Society for the Study of Addiction.

Photon statistics and speckle visibility spectroscopy with partially coherent X-rays.

PubMed

Li, Luxi; Kwaśniewski, Paweł; Orsi, Davide; Wiegart, Lutz; Cristofolini, Luigi; Caronna, Chiara; Fluerasu, Andrei

2014-11-01

A new approach is proposed for measuring structural dynamics in materials from multi-speckle scattering patterns obtained with partially coherent X-rays. Coherent X-ray scattering is already widely used at high-brightness synchrotron lightsources to measure dynamics using X-ray photon correlation spectroscopy, but in many situations this experimental approach based on recording long series of images (i.e. movies) is either not adequate or not practical. Following the development of visible-light speckle visibility spectroscopy, the dynamic information is obtained instead by analyzing the photon statistics and calculating the speckle contrast in single scattering patterns. This quantity, also referred to as the speckle visibility, is determined by the properties of the partially coherent beam and other experimental parameters, as well as the internal motions in the sample (dynamics). As a case study, Brownian dynamics in a low-density colloidal suspension is measured and an excellent agreement is found between correlation functions measured by X-ray photon correlation spectroscopy and the decay in speckle visibility with integration time obtained from the analysis presented here.

Space shuttle flying qualities and criteria assessment

NASA Technical Reports Server (NTRS)

Myers, T. T.; Johnston, D. E.; Mcruer, Duane T.

1987-01-01

Work accomplished under a series of study tasks for the Flying Qualities and Flight Control Systems Design Criteria Experiment (OFQ) of the Shuttle Orbiter Experiments Program (OEX) is summarized. The tasks involved review of applicability of existing flying quality and flight control system specification and criteria for the Shuttle; identification of potentially crucial flying quality deficiencies; dynamic modeling of the Shuttle Orbiter pilot/vehicle system in the terminal flight phases; devising a nonintrusive experimental program for extraction and identification of vehicle dynamics, pilot control strategy, and approach and landing performance metrics, and preparation of an OEX approach to produce a data archive and optimize use of the data to develop flying qualities for future space shuttle craft in general. Analytic modeling of the Orbiter's unconventional closed-loop dynamics in landing, modeling pilot control strategies, verification of vehicle dynamics and pilot control strategy from flight data, review of various existent or proposed aircraft flying quality parameters and criteria in comparison with the unique dynamic characteristics and control aspects of the Shuttle in landing; and finally a summary of conclusions and recommendations for developing flying quality criteria and design guides for future Shuttle craft.

Dynamic Reconfiguration of Security Policies in Wireless Sensor Networks

PubMed Central

Pinto, Mónica; Gámez, Nadia; Fuentes, Lidia; Amor, Mercedes; Horcas, José Miguel; Ayala, Inmaculada

2015-01-01

Providing security and privacy to wireless sensor nodes (WSNs) is very challenging, due to the heterogeneity of sensor nodes and their limited capabilities in terms of energy, processing power and memory. The applications for these systems run in a myriad of sensors with different low-level programming abstractions, limited capabilities and different routing protocols. This means that applications for WSNs need mechanisms for self-adaptation and for self-protection based on the dynamic adaptation of the algorithms used to provide security. Dynamic software product lines (DSPLs) allow managing both variability and dynamic software adaptation, so they can be considered a key technology in successfully developing self-protected WSN applications. In this paper, we propose a self-protection solution for WSNs based on the combination of the INTER-TRUST security framework (a solution for the dynamic negotiation and deployment of security policies) and the FamiWare middleware (a DSPL approach to automatically configure and reconfigure instances of a middleware for WSNs). We evaluate our approach using a case study from the intelligent transportation system domain. PMID:25746093

Representing perturbed dynamics in biological network models

NASA Astrophysics Data System (ADS)

Stoll, Gautier; Rougemont, Jacques; Naef, Felix

2007-07-01

We study the dynamics of gene activities in relatively small size biological networks (up to a few tens of nodes), e.g., the activities of cell-cycle proteins during the mitotic cell-cycle progression. Using the framework of deterministic discrete dynamical models, we characterize the dynamical modifications in response to structural perturbations in the network connectivities. In particular, we focus on how perturbations affect the set of fixed points and sizes of the basins of attraction. Our approach uses two analytical measures: the basin entropy H and the perturbation size Δ , a quantity that reflects the distance between the set of fixed points of the perturbed network and that of the unperturbed network. Applying our approach to the yeast-cell-cycle network introduced by Li [Proc. Natl. Acad. Sci. U.S.A. 101, 4781 (2004)] provides a low-dimensional and informative fingerprint of network behavior under large classes of perturbations. We identify interactions that are crucial for proper network function, and also pinpoint functionally redundant network connections. Selected perturbations exemplify the breadth of dynamical responses in this cell-cycle model.

Fast "Feast/Famine" Cycles for Studying Microbial Physiology Under Dynamic Conditions: A Case Study with Saccharomyces cerevisiae.

PubMed

Suarez-Mendez, Camilo A; Sousa, Andre; Heijnen, Joseph J; Wahl, Aljoscha

2014-05-15

Microorganisms are constantly exposed to rapidly changing conditions, under natural as well as industrial production scale environments, especially due to large-scale substrate mixing limitations. In this work, we present an experimental approach based on a dynamic feast/famine regime (400 s) that leads to repetitive cycles with moderate changes in substrate availability in an aerobic glucose cultivation of Saccharomyces cerevisiae. After a few cycles, the feast/famine produced a stable and repetitive pattern with a reproducible metabolic response in time, thus providing a robust platform for studying the microorganism's physiology under dynamic conditions. We found that the biomass yield was slightly reduced (-5%) under the feast/famine regime, while the averaged substrate and oxygen consumption as well as the carbon dioxide production rates were comparable. The dynamic response of the intracellular metabolites showed specific differences in comparison to other dynamic experiments (especially stimulus-response experiments, SRE). Remarkably, the frequently reported ATP paradox observed in single pulse experiments was not present during the repetitive perturbations applied here. We found that intracellular dynamic accumulations led to an uncoupling of the substrate uptake rate (up to 9-fold change at 20 s.) Moreover, the dynamic profiles of the intracellular metabolites obtained with the feast/famine suggest the presence of regulatory mechanisms that resulted in a delayed response. With the feast famine setup many cellular states can be measured at high frequency given the feature of reproducible cycles. The feast/famine regime is thus a versatile platform for systems biology approaches, which can help us to identify and investigate metabolite regulations under realistic conditions (e.g., large-scale bioreactors or natural environments).

Fast “Feast/Famine” Cycles for Studying Microbial Physiology Under Dynamic Conditions: A Case Study with Saccharomyces cerevisiae

PubMed Central

Suarez-Mendez, Camilo A.; Sousa, Andre; Heijnen, Joseph J.; Wahl, Aljoscha

2014-01-01

Microorganisms are constantly exposed to rapidly changing conditions, under natural as well as industrial production scale environments, especially due to large-scale substrate mixing limitations. In this work, we present an experimental approach based on a dynamic feast/famine regime (400 s) that leads to repetitive cycles with moderate changes in substrate availability in an aerobic glucose cultivation of Saccharomyces cerevisiae. After a few cycles, the feast/famine produced a stable and repetitive pattern with a reproducible metabolic response in time, thus providing a robust platform for studying the microorganism’s physiology under dynamic conditions. We found that the biomass yield was slightly reduced (−5%) under the feast/famine regime, while the averaged substrate and oxygen consumption as well as the carbon dioxide production rates were comparable. The dynamic response of the intracellular metabolites showed specific differences in comparison to other dynamic experiments (especially stimulus-response experiments, SRE). Remarkably, the frequently reported ATP paradox observed in single pulse experiments was not present during the repetitive perturbations applied here. We found that intracellular dynamic accumulations led to an uncoupling of the substrate uptake rate (up to 9-fold change at 20 s.) Moreover, the dynamic profiles of the intracellular metabolites obtained with the feast/famine suggest the presence of regulatory mechanisms that resulted in a delayed response. With the feast famine setup many cellular states can be measured at high frequency given the feature of reproducible cycles. The feast/famine regime is thus a versatile platform for systems biology approaches, which can help us to identify and investigate metabolite regulations under realistic conditions (e.g., large-scale bioreactors or natural environments). PMID:24957030

Machine learning approaches to evaluate correlation patterns in allosteric signaling: A case study of the PDZ2 domain

NASA Astrophysics Data System (ADS)

Botlani, Mohsen; Siddiqui, Ahnaf; Varma, Sameer

2018-06-01

Many proteins are regulated by dynamic allostery wherein regulator-induced changes in structure are comparable with thermal fluctuations. Consequently, understanding their mechanisms requires assessment of relationships between and within conformational ensembles of different states. Here we show how machine learning based approaches can be used to simplify this high-dimensional data mining task and also obtain mechanistic insight. In particular, we use these approaches to investigate two fundamental questions in dynamic allostery. First, how do regulators modify inter-site correlations in conformational fluctuations (Cij)? Second, how are regulator-induced shifts in conformational ensembles at two different sites in a protein related to each other? We address these questions in the context of the human protein tyrosine phosphatase 1E's PDZ2 domain, which is a model protein for studying dynamic allostery. We use molecular dynamics to generate conformational ensembles of the PDZ2 domain in both the regulator-bound and regulator-free states. The employed protocol reproduces methyl deuterium order parameters from NMR. Results from unsupervised clustering of Cij combined with flow analyses of weighted graphs of Cij show that regulator binding significantly alters the global signaling network in the protein; however, not by altering the spatial arrangement of strongly interacting amino acid clusters but by modifying the connectivity between clusters. Additionally, we find that regulator-induced shifts in conformational ensembles, which we evaluate by repartitioning ensembles using supervised learning, are, in fact, correlated. This correlation Δij is less extensive compared to Cij, but in contrast to Cij, Δij depends inversely on the distance from the regulator binding site. Assuming that Δij is an indicator of the transduction of the regulatory signal leads to the conclusion that the regulatory signal weakens with distance from the regulatory site. Overall, this work provides new approaches to analyze high-dimensional molecular simulation data and also presents applications that yield new insight into dynamic allostery.

The Dynamics of Perception and Action

ERIC Educational Resources Information Center

Warren, William H.

2006-01-01

How might one account for the organization in behavior without attributing it to an internal control structure? The present article develops a theoretical framework called behavioral dynamics that integrates an information-based approach to perception with a dynamical systems approach to action. For a given task, the agent and its environment are…

Polarization-dependent exciton dynamics in tetracene single crystals

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

Zhang, Bo; Zhang, Chunfeng, E-mail: cfzhang@nju.edu.cn; Xu, Yanqing

2014-12-28

We conduct polarization-dependent ultrafast spectroscopy to study the dynamics of singlet fission (SF) in tetracene single crystals. The spectrotemporal species for singlet and triplet excitons in transient absorption spectra are found to be strongly dependent on probe polarization. By carefully analyzing the polarization dependence, the signals contributed by different transitions related to singlet excitons have been disentangled, which is further applied to construct the correlation between dynamics of singlet and triplet excitons. The anisotropy of exciton dynamics provides an alternative approach to tackle the long-standing challenge in understanding the mechanism of singlet fission in organic semiconductors.

A dynamic model of functioning of a bank

NASA Astrophysics Data System (ADS)

Malafeyev, Oleg; Awasthi, Achal; Zaitseva, Irina; Rezenkov, Denis; Bogdanova, Svetlana

2018-04-01

In this paper, we analyze dynamic programming as a novel approach to solve the problem of maximizing the profits of a bank. The mathematical model of the problem and the description of bank's work is described in this paper. The problem is then approached using the method of dynamic programming. Dynamic programming makes sure that the solutions obtained are globally optimal and numerically stable. The optimization process is set up as a discrete multi-stage decision process and solved with the help of dynamic programming.

Trend Motif: A Graph Mining Approach for Analysis of Dynamic Complex Networks

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

Jin, R; McCallen, S; Almaas, E

2007-05-28

Complex networks have been used successfully in scientific disciplines ranging from sociology to microbiology to describe systems of interacting units. Until recently, studies of complex networks have mainly focused on their network topology. However, in many real world applications, the edges and vertices have associated attributes that are frequently represented as vertex or edge weights. Furthermore, these weights are often not static, instead changing with time and forming a time series. Hence, to fully understand the dynamics of the complex network, we have to consider both network topology and related time series data. In this work, we propose a motifmore » mining approach to identify trend motifs for such purposes. Simply stated, a trend motif describes a recurring subgraph where each of its vertices or edges displays similar dynamics over a userdefined period. Given this, each trend motif occurrence can help reveal significant events in a complex system; frequent trend motifs may aid in uncovering dynamic rules of change for the system, and the distribution of trend motifs may characterize the global dynamics of the system. Here, we have developed efficient mining algorithms to extract trend motifs. Our experimental validation using three disparate empirical datasets, ranging from the stock market, world trade, to a protein interaction network, has demonstrated the efficiency and effectiveness of our approach.« less

Faster protein folding using enhanced conformational sampling of molecular dynamics simulation.

PubMed

Kamberaj, Hiqmet

2018-05-01

In this study, we applied swarm particle-like molecular dynamics (SPMD) approach to enhance conformational sampling of replica exchange simulations. In particular, the approach showed significant improvement in sampling efficiency of conformational phase space when combined with replica exchange method (REM) in computer simulation of peptide/protein folding. First we introduce the augmented dynamical system of equations, and demonstrate the stability of the algorithm. Then, we illustrate the approach by using different fully atomistic and coarse-grained model systems, comparing them with the standard replica exchange method. In addition, we applied SPMD simulation to calculate the time correlation functions of the transitions in a two dimensional surface to demonstrate the enhancement of transition path sampling. Our results showed that folded structure can be obtained in a shorter simulation time using the new method when compared with non-augmented dynamical system. Typically, in less than 0.5 ns using replica exchange runs assuming that native folded structure is known and within simulation time scale of 40 ns in the case of blind structure prediction. Furthermore, the root mean square deviations from the reference structures were less than 2Å. To demonstrate the performance of new method, we also implemented three simulation protocols using CHARMM software. Comparisons are also performed with standard targeted molecular dynamics simulation method. Copyright © 2018 Elsevier Inc. All rights reserved.

Dynamics of multi-frequency oscillator ensembles with resonant coupling

NASA Astrophysics Data System (ADS)

Lück, S.; Pikovsky, A.

2011-07-01

We study dynamics of populations of resonantly coupled oscillators having different frequencies. Starting from the coupled van der Pol equations we derive the Kuramoto-type phase model for the situation, where the natural frequencies of two interacting subpopulations are in relation 2:1. Depending on the parameter of coupling, ensembles can demonstrate fully synchronous clusters, partial synchrony (only one subpopulation synchronizes), or asynchrony in both subpopulations. Theoretical description of the dynamics based on the Watanabe-Strogatz approach is developed.

Computational fluid mechanics utilizing the variational principle of modeling damping seals

NASA Technical Reports Server (NTRS)

Abernathy, J. M.

1986-01-01

A computational fluid dynamics code for application to traditional incompressible flow problems has been developed. The method is actually a slight compressibility approach which takes advantage of the bulk modulus and finite sound speed of all real fluids. The finite element numerical analog uses a dynamic differencing scheme based, in part, on a variational principle for computational fluid dynamics. The code was developed in order to study the feasibility of damping seals for high speed turbomachinery. Preliminary seal analyses have been performed.

Flight dynamics research for highly agile aircraft

NASA Technical Reports Server (NTRS)

Nguyen, Luat T.

1989-01-01

This paper highlights recent results of research conducted at the NASA Langley Research Center as part of a broad flight dynamics program aimed at developing technology that will enable future combat aircraft to achieve greatly enhanced agility capability at subsonic combat conditions. Studies of advanced control concepts encompassing both propulsive and aerodynamic approaches are reviewed. Dynamic stall phenomena and their potential impact on maneuvering performance and stability are summarized. Finally, issues of mathematical modeling of complex aerodynamics occurring during rapid, large amplitude maneuvers are discussed.

Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems With Switching [Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems

DOE PAGES

Zhang, Hong; Abhyankar, Shrirang; Constantinescu, Emil; ...

2017-01-24

Sensitivity analysis is an important tool for describing power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this paper, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating sensitivities of larger systems and is consistent, within machine precision, with the function whosemore » sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as dc exciters, by deriving and implementing the adjoint jump conditions that arise from state-dependent and time-dependent switchings. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach. In conclusion, this paper focuses primarily on the power system dynamics, but the approach is general and can be applied to hybrid dynamical systems in a broader range of fields.« less

Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems With Switching [Discrete Adjoint Sensitivity Analysis of Hybrid Dynamical Systems

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

Zhang, Hong; Abhyankar, Shrirang; Constantinescu, Emil

Sensitivity analysis is an important tool for describing power system dynamic behavior in response to parameter variations. It is a central component in preventive and corrective control applications. The existing approaches for sensitivity calculations, namely, finite-difference and forward sensitivity analysis, require a computational effort that increases linearly with the number of sensitivity parameters. In this paper, we investigate, implement, and test a discrete adjoint sensitivity approach whose computational effort is effectively independent of the number of sensitivity parameters. The proposed approach is highly efficient for calculating sensitivities of larger systems and is consistent, within machine precision, with the function whosemore » sensitivity we are seeking. This is an essential feature for use in optimization applications. Moreover, our approach includes a consistent treatment of systems with switching, such as dc exciters, by deriving and implementing the adjoint jump conditions that arise from state-dependent and time-dependent switchings. The accuracy and the computational efficiency of the proposed approach are demonstrated in comparison with the forward sensitivity analysis approach. In conclusion, this paper focuses primarily on the power system dynamics, but the approach is general and can be applied to hybrid dynamical systems in a broader range of fields.« less

Geometric effects in microfluidics on heterogeneous cell stress using an Eulerian-Lagrangian approach.

PubMed

Warren, K M; Mpagazehe, J N; LeDuc, P R; Higgs, C F

2016-02-07

The response of individual cells at the micro-scale in cell mechanics is important in understanding how they are affected by changing environments. To control cell stresses, microfluidics can be implemented since there is tremendous control over the geometry of the devices. Designing microfluidic devices to induce and manipulate stress levels on biological cells can be aided by computational modeling approaches. Such approaches serve as an efficient precursor to fabricating various microfluidic geometries that induce predictable levels of stress on biological cells, based on their mechanical properties. Here, a three-dimensional, multiphase computational fluid dynamics (CFD) modeling approach was implemented for soft biological materials. The computational model incorporates the physics of the particle dynamics, fluid dynamics and solid mechanics, which allows us to study how stresses affect the cells. By using an Eulerian-Lagrangian approach to treat the fluid domain as a continuum in the microfluidics, we are conducting studies of the cells' movement and the stresses applied to the cell. As a result of our studies, we were able to determine that a channel with periodically alternating columns of obstacles was capable of stressing cells at the highest rate, and that microfluidic systems can be engineered to impose heterogenous cell stresses through geometric configuring. We found that when using controlled geometries of the microfluidics channels with staggered obstructions, we could increase the maximum cell stress by nearly 200 times over cells flowing through microfluidic channels with no obstructions. Incorporating computational modeling in the design of microfluidic configurations for controllable cell stressing could help in the design of microfludic devices for stressing cells such as cell homogenizers.

Stochastic approach to equilibrium and nonequilibrium thermodynamics.

PubMed

Tomé, Tânia; de Oliveira, Mário J

2015-04-01

We develop the stochastic approach to thermodynamics based on stochastic dynamics, which can be discrete (master equation) and continuous (Fokker-Planck equation), and on two assumptions concerning entropy. The first is the definition of entropy itself and the second the definition of entropy production rate, which is non-negative and vanishes in thermodynamic equilibrium. Based on these assumptions, we study interacting systems with many degrees of freedom in equilibrium or out of thermodynamic equilibrium and how the macroscopic laws are derived from the stochastic dynamics. These studies include the quasiequilibrium processes; the convexity of the equilibrium surface; the monotonic time behavior of thermodynamic potentials, including entropy; the bilinear form of the entropy production rate; the Onsager coefficients and reciprocal relations; and the nonequilibrium steady states of chemical reactions.

Local Dynamic Stability Associated with Load Carrying

PubMed Central

Lockhart, Thurmon E

2013-01-01

Objectives Load carrying tasks are recognized as one of the primary occupational factors leading to slip and fall injuries. Nevertheless, the mechanisms associated with load carrying and walking stability remain illusive. The objective of the current study was to apply local dynamic stability measure in walking while carrying a load, and to investigate the possible adaptive gait stability changes. Methods Current study involved 25 young adults in a biomechanics research laboratory. One tri-axial accelerometer was used to measure three-dimensional low back acceleration during continuous treadmill walking. Local dynamic stability was quantified by the maximum Lyapunov exponent (maxLE) from a nonlinear dynamics approach. Results Long term maxLE was found to be significant higher under load condition than no-load condition in all three reference axes, indicating the declined local dynamic stability associated with load carrying. Conclusion Current study confirmed the sensitivity of local dynamic stability measure in load carrying situation. It was concluded that load carrying tasks were associated with declined local dynamic stability, which may result in increased risk of fall accident. This finding has implications in preventing fall accidents associated with occupational load carrying. PMID:23515183

A tutorial on dynamical systems concepts applied to Lagrangian transport in oceanic flows defined as finite time data sets: Theoretical and computational issues

NASA Astrophysics Data System (ADS)

Mancho, Ana M.; Small, Des; Wiggins, Stephen

2006-12-01

In the past 15 years the framework and ideas from dynamical systems theory have been applied to a variety of transport and mixing problems in oceanic flows. The motivation for this approach comes directly from advances in observational capabilities in oceanography (e.g., drifter deployments, remote sensing capabilities, satellite imagery, etc.) which reveal space-time structures that are highly suggestive of the structures one visualizes in the global, geometrical study of dynamical systems theory. In this tutorial, we motivate this approach by showing the relationship between fluid transport in two-dimensional time-periodic incompressible flows and the geometrical structures that exist for two-dimensional area-preserving maps, such as hyperbolic periodic orbits, their stable and unstable manifolds and KAM (Kolmogorov-Arnold-Moser) tori. This serves to set the stage for the attempt to “transfer” this approach to more realistic flows modelling the ocean. However, in order to accomplish this several difficulties must be overcome. The first difficulty that confronts us that any attempt to carry out a dynamical systems approach to transport requires us to obtain the appropriate “dynamical system”, which is the velocity field describing the fluid flow. In general, adequate model velocity fields are obtained by numerical solution of appropriate partial differential equations describing the dynamical evolution of the velocity field. Numerical solution of the partial differential equations can only be done for a finite time interval, and since the ocean is generally not time-periodic, this leads to a new type of dynamical system: a finite-time, aperiodically time-dependent velocity field defined as a data set on a space-time grid. The global, geometrical analysis of transport in such dynamical systems requires both new concepts and new analytical and computational tools, as well as the necessity to discard some of the standard ideas and results from dynamical systems theory. The purpose of this tutorial is to describe these new concepts and analytical tools first using simple dynamical systems where quantities can be computed exactly. We then discuss their computational implications and implementation in the context of a model geophysical flow: a turbulent wind-driven double-gyre in the quasigeostrophic approximation.

Dynamical self-arrest in symmetric and asymmetric diblock copolymer melts using a replica approach within a local theory.

PubMed

Wu, Sangwook

2009-03-01

We investigate dynamical self-arrest in a diblock copolymer melt using a replica approach within a self-consistent local method based on dynamical mean-field theory (DMFT). The local replica approach effectively predicts (chiN)_{A} for dynamical self-arrest in a block copolymer melt for symmetric and asymmetric cases. We discuss the competition of the cubic and quartic interactions in the Landau free energy for a block copolymer melt in stabilizing a glassy state depending on the chain length. Our local replica theory provides a universal value for the dynamical self-arrest in block copolymer melts with (chiN)_{A} approximately 10.5+64N;{-3/10} for the symmetric case.

Velocity measurements of heterogeneous RBC flow in capillary vessels using dynamic laser speckle signal.

PubMed

Li, Chenxi; Wang, Ruikang

2017-04-01

We propose an approach to measure heterogeneous velocities of red blood cells (RBCs) in capillary vessels using full-field time-varying dynamic speckle signals. The approach utilizes a low coherent laser speckle imaging system to record the instantaneous speckle pattern, followed by an eigen-decomposition-based filtering algorithm to extract dynamic speckle signal due to the moving RBCs. The velocity of heterogeneous RBC flows is determined by cross-correlating the temporal dynamic speckle signals obtained at adjacent locations. We verify the approach by imaging mouse pinna in vivo, demonstrating its capability for full-field RBC flow mapping and quantifying flow pattern with high resolution. It is expected to investigate the dynamic action of RBCs flow in capillaries under physiological changes.

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

Lu, Chun-Yaung; Perez, Danny; Voter, Arthur F., E-mail: afv@lanl.gov

Nuclear quantum effects are important for systems containing light elements, and the effects are more prominent in the low temperature regime where the dynamics also becomes sluggish. We show that parallel replica (ParRep) dynamics, an accelerated molecular dynamics approach for infrequent-event systems, can be effectively combined with ring-polymer molecular dynamics, a semiclassical trajectory approach that gives a good approximation to zero-point and tunneling effects in activated escape processes. The resulting RP-ParRep method is a powerful tool for reaching long time scales in complex infrequent-event systems where quantum dynamics are important. Two illustrative examples, symmetric Eckart barrier crossing and interstitial heliummore » diffusion in Fe and Fe–Cr alloy, are presented to demonstrate the accuracy and long-time scale capability of this approach.« less

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

PubMed Central

Truccolo, Wilson

2017-01-01

This review presents a perspective on capturing collective dynamics in recorded neuronal ensembles based on multivariate point process models, inference of low-dimensional dynamics and coarse graining of spatiotemporal measurements. A general probabilistic framework for continuous time point processes reviewed, with an emphasis on multivariate nonlinear Hawkes processes with exogenous inputs. A point process generalized linear model (PP-GLM) framework for the estimation of discrete time multivariate nonlinear Hawkes processes is described. The approach is illustrated with the modeling of collective dynamics in neocortical neuronal ensembles recorded in human and non-human primates, and prediction of single-neuron spiking. A complementary approach to capture collective dynamics based on low-dimensional dynamics (“order parameters”) inferred via latent state-space models with point process observations is presented. The approach is illustrated by inferring and decoding low-dimensional dynamics in primate motor cortex during naturalistic reach and grasp movements. Finally, we briefly review hypothesis tests based on conditional inference and spatiotemporal coarse graining for assessing collective dynamics in recorded neuronal ensembles. PMID:28336305

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

PubMed

Truccolo, Wilson

2016-11-01

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

Transformational Education for Psychotherapy and Counselling: A Relational Dynamic Approach

ERIC Educational Resources Information Center

Macaskie, Jane; Meekums, Bonnie; Nolan, Greg

2013-01-01

An evolving relational dynamic approach to psychotherapy and counselling education is described. Key themes integrated within the approach are the learning community and transformational relationships. Learning is a reciprocal change process involving students, teachers, supervisors and therapists in overlapping learning communities. Drawing on…

Degree-Pruning Dynamic Programming Approaches to Central Time Series Minimizing Dynamic Time Warping Distance.

PubMed

Sun, Tao; Liu, Hongbo; Yu, Hong; Chen, C L Philip

2016-06-28

The central time series crystallizes the common patterns of the set it represents. In this paper, we propose a global constrained degree-pruning dynamic programming (g(dp)²) approach to obtain the central time series through minimizing dynamic time warping (DTW) distance between two time series. The DTW matching path theory with global constraints is proved theoretically for our degree-pruning strategy, which is helpful to reduce the time complexity and computational cost. Our approach can achieve the optimal solution between two time series. An approximate method to the central time series of multiple time series [called as m_g(dp)²] is presented based on DTW barycenter averaging and our g(dp)² approach by considering hierarchically merging strategy. As illustrated by the experimental results, our approaches provide better within-group sum of squares and robustness than other relevant algorithms.

The Fragility of Individual-Based Explanations of Social Hierarchies: A Test Using Animal Pecking Orders

PubMed Central

2016-01-01

The standard approach in accounting for hierarchical differentiation in biology and the social sciences considers a hierarchy as a static distribution of individuals possessing differing amounts of some valued commodity, assumes that the hierarchy is generated by micro-level processes involving individuals, and attempts to reverse engineer the processes that produced the hierarchy. However, sufficient experimental and analytical results are available to evaluate this standard approach in the case of animal dominance hierarchies (pecking orders). Our evaluation using evidence from hierarchy formation in small groups of both hens and cichlid fish reveals significant deficiencies in the three tenets of the standard approach in accounting for the organization of dominance hierarchies. In consequence, we suggest that a new approach is needed to explain the organization of pecking orders and, very possibly, by implication, for other kinds of social hierarchies. We develop an example of such an approach that considers dominance hierarchies to be dynamic networks, uses dynamic sequences of interaction (dynamic network motifs) to explain the organization of dominance hierarchies, and derives these dynamic sequences directly from observation of hierarchy formation. We test this dynamical explanation using computer simulation and find a good fit with actual dynamics of hierarchy formation in small groups of hens. We hypothesize that the same dynamic sequences are used in small groups of many other animal species forming pecking orders, and we discuss the data required to evaluate our hypothesis. Finally, we briefly consider how our dynamic approach may be generalized to other kinds of social hierarchies using the example of the distribution of empty gastropod (snail) shells occupied in populations of hermit crabs. PMID:27410230

Computational and Spectroscopic Investigations of the Molecular Scale Structure and Dynamics of Geologically Important Fluids and Mineral-Fluid Interfaces

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

R. James Kirkpatrick; Andrey G. Kalinichev

2008-11-25

Research supported by this grant focuses on molecular scale understanding of central issues related to the structure and dynamics of geochemically important fluids, fluid-mineral interfaces, and confined fluids using computational modeling and experimental methods. Molecular scale knowledge about fluid structure and dynamics, how these are affected by mineral surfaces and molecular-scale (nano-) confinement, and how water molecules and dissolved species interact with surfaces is essential to understanding the fundamental chemistry of a wide range of low-temperature geochemical processes, including sorption and geochemical transport. Our principal efforts are devoted to continued development of relevant computational approaches, application of these approaches tomore » important geochemical questions, relevant NMR and other experimental studies, and application of computational modeling methods to understanding the experimental results. The combination of computational modeling and experimental approaches is proving highly effective in addressing otherwise intractable problems. In 2006-2007 we have significantly advanced in new, highly promising research directions along with completion of on-going projects and final publication of work completed in previous years. New computational directions are focusing on modeling proton exchange reactions in aqueous solutions using ab initio molecular dynamics (AIMD), metadynamics (MTD), and empirical valence bond (EVB) approaches. Proton exchange is critical to understanding the structure, dynamics, and reactivity at mineral-water interfaces and for oxy-ions in solution, but has traditionally been difficult to model with molecular dynamics (MD). Our ultimate objective is to develop this capability, because MD is much less computationally demanding than quantum-chemical approaches. We have also extended our previous MD simulations of metal binding to natural organic matter (NOM) to a much longer time scale (up to 10 ns) for significantly larger systems. These calculations have allowed us, for the first time, to study the effects of metal cations with different charges and charge density on the NOM aggregation in aqueous solutions. Other computational work has looked at the longer-time-scale dynamical behavior of aqueous species at mineral-water interfaces investigated simultaneously by NMR spectroscopy. Our experimental NMR studies have focused on understanding the structure and dynamics of water and dissolved species at mineral-water interfaces and in two-dimensional nano-confinement within clay interlayers. Combined NMR and MD study of H2O, Na+, and Cl- interactions with the surface of quartz has direct implications regarding interpretation of sum frequency vibrational spectroscopic experiments for this phase and will be an important reference for future studies. We also used NMR to examine the behavior of K+ and H2O in the interlayer and at the surfaces of the clay minerals hectorite and illite-rich illite-smectite. This the first time K+ dynamics has been characterized spectroscopically in geochemical systems. Preliminary experiments were also performed to evaluate the potential of 75As NMR as a probe of arsenic geochemical behavior. The 75As NMR study used advanced signal enhancement methods, introduced a new data acquisition approach to minimize the time investment in ultra-wide-line NMR experiments, and provides the first evidence of a strong relationship between the chemical shift and structural parameters for this experimentally challenging nucleus. We have also initiated a series of inelastic and quasi-elastic neutron scattering measurements of water dynamics in the interlayers of clays and layered double hydroxides. The objective of these experiments is to probe the correlations of water molecular motions in confined spaces over the scale of times and distances most directly comparable to our MD simulations and on a time scale different than that probed by NMR. This work is being done in collaboration with Drs. C.-K. Loong, N. de Souza, and A.I. Kolesnikov at the Intense Pulsed Neutron Source facility of the Argonne National Lab, and Dr. A. Faraone at the NIST Center for Neutron Research. A manuscript reporting the first results of these experiments, which are highly complimentary to our previous NMR, X-ray, and infra-red results for these phases, is currently in preparation. In total, in 2006-2007 our work has resulted in the publication of 14 peer-reviewed research papers. We also devoted considerable effort to making our work known to a wide range of researchers, as indicated by the 24 contributed abstracts and 14 invited presentations.« less

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.

2n-emission from 205Pb* nucleus using clusterization approach at Ebeam˜14-20 MeV

NASA Astrophysics Data System (ADS)

Kaur, Amandeep; Sandhu, Kiran; Sharma, Manoj Kumar

2016-05-01

The dynamics involved in n-induced reaction with 204Pb target is analyzed and the decay of the composite system 205Pb* is governed within the collective clusterization approach of the Dynamical Cluster-decay Model (DCM). The experimental data for 2n-evaporation channel is available for neutron energy range of 14-20 MeV and is addressed by optimizing the only parameter of the model, the neck-length parameter (ΔR). The calculations are done by taking the quadrupole (β2) deformations of the decaying fragments and the calculated 2n-emission cross-sections find nice agreement with available data. An effort is made to study the role of level density parameter in the decay of hot-rotating nucleus, and the mass dependence in level density parameter is exercised for the first time in DCM based calculations. It is to be noted that the effect of deformation, temperature and angular momentum etc. is studied to extract better description of the dynamics involved.

Ultra-Small-Angle X-ray Scattering – X-ray Photon Correlation Spectroscopy Studies of Incipient Structural Changes in Amorphous Calcium Phosphate Based Dental Composites

PubMed Central

Zhang, F.; Allen, A.J.; Levine, L.E.; Espinal, L.; Antonucci, J.M.; Skrtic, D.; O’Donnell, J.N.R.; Ilavsky, J.

2012-01-01

The local structural changes in amorphous calcium phosphate (ACP) based dental composites were studied under isothermal conditions using both static, bulk measurement techniques and a recently developed methodology based on combined ultra-small angle X-ray scattering – X-ray photon correlation spectroscopy (USAXS-XPCS), which permits a dynamic approach. While results from conventional bulk measurements do not show clear signs of structural change, USAXS-XPCS results reveal unambiguous evidence for local structural variations on a similar time scale to that of water loss in the ACP fillers. A thermal-expansion based simulation indicates that thermal behavior alone does not account for the observed dynamics. Together, these results suggest that changes in the water content of ACP affect the composite morphology due to changes in ACP structure that occur without an amorphous-to-crystalline conversion. It is also noted that biomedical materials research could benefit greatly from USAXS-XPCS, a dynamic approach. PMID:22374649

Chatter detection in turning using persistent homology

NASA Astrophysics Data System (ADS)

Khasawneh, Firas A.; Munch, Elizabeth

2016-03-01

This paper describes a new approach for ascertaining the stability of stochastic dynamical systems in their parameter space by examining their time series using topological data analysis (TDA). We illustrate the approach using a nonlinear delayed model that describes the tool oscillations due to self-excited vibrations in turning. Each time series is generated using the Euler-Maruyama method and a corresponding point cloud is obtained using the Takens embedding. The point cloud can then be analyzed using a tool from TDA known as persistent homology. The results of this study show that the described approach can be used for analyzing datasets of delay dynamical systems generated both from numerical simulation and experimental data. The contributions of this paper include presenting for the first time a topological approach for investigating the stability of a class of nonlinear stochastic delay equations, and introducing a new application of TDA to machining processes.

Dynamic sensory description of Rioja Alavesa red wines made by different winemaking practices by using Temporal Dominance of Sensations.

PubMed

Etaio, Iñaki; Meillon, Sophie; Pérez-Elortondo, Francisco J; Schlich, Pascal

2016-08-01

Although sensory description of wines in scientific literature is very large, there is an evident lack of studies describing wines from a dynamic approach. The objective of this study was to describe the evolution of the sensations perceived in red wines from Rioja Alavesa by using Temporal Dominance of Sensations (TDS) and also to compare wines made with the two winemaking procedures used in Rioja Alavesa: carbonic maceration (CM) and destemming (DS). Ten sensory attributes were evaluated in eight wines (four CM and four DS wines) in triplicate by a panel of 16 trained assessors. Red/black berry and woody aromas were dominant firstly, whereas heat, astringent, bitter and pungent sensations were dominant later. CM wines showed higher dominance for woody, spicy, pungent and acid sensations and lower dominance for red/black berry aroma and astringency than DS wines. This study is the first to describe Rioja wines from a dynamic approach and it also provides information about the dynamic sensory differences between wines made by CM or by DS. In this sense, this work shows the usefulness of TDS to describe and differentiate wines and to provide additional information to the conventional static descriptive analysis. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

Tracking interface and common curve dynamics for two-fluid flow in porous media

DOE PAGES

Mcclure, James E.; Miller, Cass T.; Gray, W. G.; ...

2016-04-29

Pore-scale studies of multiphase flow in porous medium systems can be used to understand transport mechanisms and quantitatively determine closure relations that better incorporate microscale physics into macroscale models. Multiphase flow simulators constructed using the lattice Boltzmann method provide a means to conduct such studies, including both the equilibrium and dynamic aspects. Moving, storing, and analyzing the large state space presents a computational challenge when highly-resolved models are applied. We present an approach to simulate multiphase flow processes in which in-situ analysis is applied to track multiphase flow dynamics at high temporal resolution. We compute a comprehensive set of measuresmore » of the phase distributions and the system dynamics, which can be used to aid fundamental understanding and inform closure relations for macroscale models. The measures computed include microscale point representations and macroscale averages of fluid saturations, the pressure and velocity of the fluid phases, interfacial areas, interfacial curvatures, interface and common curve velocities, interfacial orientation tensors, phase velocities and the contact angle between the fluid-fluid interface and the solid surface. Test cases are studied to validate the approach and illustrate how measures of system state can be obtained and used to inform macroscopic theory.« less

A systematic approach to selecting task relevant neurons.

PubMed

Kahn, Kevin; Saxena, Shreya; Eskandar, Emad; Thakor, Nitish; Schieber, Marc; Gale, John T; Averbeck, Bruno; Eden, Uri; Sarma, Sridevi V

2015-04-30

Since task related neurons cannot be specifically targeted during surgery, a critical decision to make is to select which neurons are task-related when performing data analysis. Including neurons unrelated to the task degrade decoding accuracy and confound neurophysiological results. Traditionally, task-related neurons are selected as those with significant changes in firing rate when a stimulus is applied. However, this assumes that neurons' encoding of stimuli are dominated by their firing rate with little regard to temporal dynamics. This paper proposes a systematic approach for neuron selection, which uses a likelihood ratio test to capture the contribution of stimulus to spiking activity while taking into account task-irrelevant intrinsic dynamics that affect firing rates. This approach is denoted as the model deterioration excluding stimulus (MDES) test. MDES is compared to firing rate selection in four case studies: a simulation, a decoding example, and two neurophysiology examples. The MDES rankings in the simulation match closely with ideal rankings, while firing rate rankings are skewed by task-irrelevant parameters. For decoding, 95% accuracy is achieved using the top 8 MDES-ranked neurons, while the top 12 firing-rate ranked neurons are needed. In the neurophysiological examples, MDES matches published results when firing rates do encode salient stimulus information, and uncovers oscillatory modulations in task-related neurons that are not captured when neurons are selected using firing rates. These case studies illustrate the importance of accounting for intrinsic dynamics when selecting task-related neurons and following the MDES approach accomplishes that. MDES selects neurons that encode task-related information irrespective of these intrinsic dynamics which can bias firing rate based selection. Copyright © 2015 Elsevier B.V. All rights reserved.

Analysis of 15N-1H NMR relaxation in proteins by a combined experimental and molecular dynamics simulation approach: picosecond-nanosecond dynamics of the Rho GTPase binding domain of plexin-B1 in the dimeric state indicates allosteric pathways.

PubMed

Zerbetto, Mirco; Anderson, Ross; Bouguet-Bonnet, Sabine; Rech, Mariano; Zhang, Liqun; Meirovitch, Eva; Polimeno, Antonino; Buck, Matthias

2013-01-10

We investigate picosecond–nanosecond dynamics of the Rho-GTPase Binding Domain (RBD) of plexin-B1, which plays a key role in plexin-mediated cell signaling. Backbone 15N relaxation data of the dimeric RBD are analyzed with the model-free (MF) method, and with the slowly relaxing local structure/molecular dynamics (SRLS-MD) approach. Independent analysis of the MD trajectories, based on the MF paradigm, is also carried out. MF is a widely popular and simple method, SRLS is a general approach, and SRLS-MD is an integrated approach we developed recently. Corresponding parameters from the RBD dimer, a previously studied RBD monomer mutant, and the previously studied complex of the latter with the GTPase Rac1, are compared. The L2, L3, and L4 loops of the plexin-B1 RBD are involved in interactions with other plexin domains, GTPase binding, and RBD dimerization, respectively. Peptide groups in the loops of both the monomeric and dimeric RBD are found to experience weak and moderately asymmetric local ordering centered approximately at the C(i–1)(α)–C(i)(α) axes, and nanosecond backbone motion. Peptide groups in the α-helices and the β-strands of the dimer (the β-strands of the monomer) experience strong and highly asymmetric local ordering centered approximately at the C(i–1)(α)–C(i)(α) axes (N–H bonds). N–H fluctuations occur on the picosecond time scale. An allosteric pathway for GTPase binding, providing new insights into plexin function, is delineated.

Application of snakes and dynamic programming optimisation technique in modeling of buildings in informal settlement areas

NASA Astrophysics Data System (ADS)

Rüther, Heinz; Martine, Hagai M.; Mtalo, E. G.

This paper presents a novel approach to semiautomatic building extraction in informal settlement areas from aerial photographs. The proposed approach uses a strategy of delineating buildings by optimising their approximate building contour position. Approximate building contours are derived automatically by locating elevation blobs in digital surface models. Building extraction is then effected by means of the snakes algorithm and the dynamic programming optimisation technique. With dynamic programming, the building contour optimisation problem is realized through a discrete multistage process and solved by the "time-delayed" algorithm, as developed in this work. The proposed building extraction approach is a semiautomatic process, with user-controlled operations linking fully automated subprocesses. Inputs into the proposed building extraction system are ortho-images and digital surface models, the latter being generated through image matching techniques. Buildings are modeled as "lumps" or elevation blobs in digital surface models, which are derived by altimetric thresholding of digital surface models. Initial windows for building extraction are provided by projecting the elevation blobs centre points onto an ortho-image. In the next step, approximate building contours are extracted from the ortho-image by region growing constrained by edges. Approximate building contours thus derived are inputs into the dynamic programming optimisation process in which final building contours are established. The proposed system is tested on two study areas: Marconi Beam in Cape Town, South Africa, and Manzese in Dar es Salaam, Tanzania. Sixty percent of buildings in the study areas have been extracted and verified and it is concluded that the proposed approach contributes meaningfully to the extraction of buildings in moderately complex and crowded informal settlement areas.

How to interpret the results of medical time series data analysis: Classical statistical approaches versus dynamic Bayesian network modeling.

PubMed

Onisko, Agnieszka; Druzdzel, Marek J; Austin, R Marshall

2016-01-01

Classical statistics is a well-established approach in the analysis of medical data. While the medical community seems to be familiar with the concept of a statistical analysis and its interpretation, the Bayesian approach, argued by many of its proponents to be superior to the classical frequentist approach, is still not well-recognized in the analysis of medical data. The goal of this study is to encourage data analysts to use the Bayesian approach, such as modeling with graphical probabilistic networks, as an insightful alternative to classical statistical analysis of medical data. This paper offers a comparison of two approaches to analysis of medical time series data: (1) classical statistical approach, such as the Kaplan-Meier estimator and the Cox proportional hazards regression model, and (2) dynamic Bayesian network modeling. Our comparison is based on time series cervical cancer screening data collected at Magee-Womens Hospital, University of Pittsburgh Medical Center over 10 years. The main outcomes of our comparison are cervical cancer risk assessments produced by the three approaches. However, our analysis discusses also several aspects of the comparison, such as modeling assumptions, model building, dealing with incomplete data, individualized risk assessment, results interpretation, and model validation. Our study shows that the Bayesian approach is (1) much more flexible in terms of modeling effort, and (2) it offers an individualized risk assessment, which is more cumbersome for classical statistical approaches.

A Novel Experimental and Analytical Approach to the Multimodal Neural Decoding of Intent During Social Interaction in Freely-behaving Human Infants.

PubMed

Cruz-Garza, Jesus G; Hernandez, Zachery R; Tse, Teresa; Caducoy, Eunice; Abibullaev, Berdakh; Contreras-Vidal, Jose L

2015-10-04

Understanding typical and atypical development remains one of the fundamental questions in developmental human neuroscience. Traditionally, experimental paradigms and analysis tools have been limited to constrained laboratory tasks and contexts due to technical limitations imposed by the available set of measuring and analysis techniques and the age of the subjects. These limitations severely limit the study of developmental neural dynamics and associated neural networks engaged in cognition, perception and action in infants performing "in action and in context". This protocol presents a novel approach to study infants and young children as they freely organize their own behavior, and its consequences in a complex, partly unpredictable and highly dynamic environment. The proposed methodology integrates synchronized high-density active scalp electroencephalography (EEG), inertial measurement units (IMUs), video recording and behavioral analysis to capture brain activity and movement non-invasively in freely-behaving infants. This setup allows for the study of neural network dynamics in the developing brain, in action and context, as these networks are recruited during goal-oriented, exploration and social interaction tasks.

Energy Landscape of the Prion Protein Helix 1 Probed by Metadynamics and NMR

PubMed Central

Camilloni, Carlo; Schaal, Daniel; Schweimer, Kristian; Schwarzinger, Stephan; De Simone, Alfonso

2012-01-01

The characterization of the structural dynamics of proteins, including those that present a substantial degree of disorder, is currently a major scientific challenge. These dynamics are biologically relevant and govern the majority of functional and pathological processes. We exploited a combination of enhanced molecular simulations of metadynamics and NMR measurements to study heterogeneous states of proteins and peptides. In this way, we determined the structural ensemble and free-energy landscape of the highly dynamic helix 1 of the prion protein (PrP-H1), whose misfolding and aggregation are intimately connected to a group of neurodegenerative disorders known as transmissible spongiform encephalopathies. Our combined approach allowed us to dissect the factors that govern the conformational states of PrP-H1 in solution, and the implications of these factors for prion protein misfolding and aggregation. The results underline the importance of adopting novel integrated approaches that take advantage of experiments and theory to achieve a comprehensive characterization of the structure and dynamics of biological macromolecules. PMID:22225810

Eigenstates and dynamics of Hooke's atom: Exact results and path integral simulations

NASA Astrophysics Data System (ADS)

Gholizadehkalkhoran, Hossein; Ruokosenmäki, Ilkka; Rantala, Tapio T.

2018-05-01

The system of two interacting electrons in one-dimensional harmonic potential or Hooke's atom is considered, again. On one hand, it appears as a model for quantum dots in a strong confinement regime, and on the other hand, it provides us with a hard test bench for new methods with the "space splitting" arising from the one-dimensional Coulomb potential. Here, we complete the numerous previous studies of the ground state of Hooke's atom by including the excited states and dynamics, not considered earlier. With the perturbation theory, we reach essentially exact eigenstate energies and wave functions for the strong confinement regime as novel results. We also consider external perturbation induced quantum dynamics in a simple separable case. Finally, we test our novel numerical approach based on real-time path integrals (RTPIs) in reproducing the above. The RTPI turns out to be a straightforward approach with exact account of electronic correlations for solving the eigenstates and dynamics without the conventional restrictions of electronic structure methods.

Coherence penalty functional: A simple method for adding decoherence in Ehrenfest dynamics

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

Akimov, Alexey V., E-mail: alexvakimov@gmail.com, E-mail: oleg.prezhdo@rochester.edu; Chemistry Department, Brookhaven National Laboratory, Upton, New York 11973; Long, Run

2014-05-21

We present a new semiclassical approach for description of decoherence in electronically non-adiabatic molecular dynamics. The method is formulated on the grounds of the Ehrenfest dynamics and the Meyer-Miller-Thoss-Stock mapping of the time-dependent Schrödinger equation onto a fully classical Hamiltonian representation. We introduce a coherence penalty functional (CPF) that accounts for decoherence effects by randomizing the wavefunction phase and penalizing development of coherences in regions of strong non-adiabatic coupling. The performance of the method is demonstrated with several model and realistic systems. Compared to other semiclassical methods tested, the CPF method eliminates artificial interference and improves agreement with the fullymore » quantum calculations on the models. When applied to study electron transfer dynamics in the nanoscale systems, the method shows an improved accuracy of the predicted time scales. The simplicity and high computational efficiency of the CPF approach make it a perfect practical candidate for applications in realistic systems.« less

Finite-temperature time-dependent variation with multiple Davydov states

NASA Astrophysics Data System (ADS)

Wang, Lu; Fujihashi, Yuta; Chen, Lipeng; Zhao, Yang

2017-03-01

The Dirac-Frenkel time-dependent variational approach with Davydov Ansätze is a sophisticated, yet efficient technique to obtain an accurate solution to many-body Schrödinger equations for energy and charge transfer dynamics in molecular aggregates and light-harvesting complexes. We extend this variational approach to finite temperature dynamics of the spin-boson model by adopting a Monte Carlo importance sampling method. In order to demonstrate the applicability of this approach, we compare calculated real-time quantum dynamics of the spin-boson model with that from numerically exact iterative quasiadiabatic propagator path integral (QUAPI) technique. The comparison shows that our variational approach with the single Davydov Ansätze is in excellent agreement with the QUAPI method at high temperatures, while the two differ at low temperatures. Accuracy in dynamics calculations employing a multitude of Davydov trial states is found to improve substantially over the single Davydov Ansatz, especially at low temperatures. At a moderate computational cost, our variational approach with the multiple Davydov Ansatz is shown to provide accurate spin-boson dynamics over a wide range of temperatures and bath spectral densities.

Predicting and downscaling ENSO impacts on intraseasonal precipitation statistics in California: The 1997/98 event

USGS Publications Warehouse

Gershunov, A.; Barnett, T.P.; Cayan, D.R.; Tubbs, T.; Goddard, L.

2000-01-01

Three long-range forecasting methods have been evaluated for prediction and downscaling of seasonal and intraseasonal precipitation statistics in California. Full-statistical, hybrid-dynamical - statistical and full-dynamical approaches have been used to forecast El Nin??o - Southern Oscillation (ENSO) - related total precipitation, daily precipitation frequency, and average intensity anomalies during the January - March season. For El Nin??o winters, the hybrid approach emerges as the best performer, while La Nin??a forecasting skill is poor. The full-statistical forecasting method features reasonable forecasting skill for both La Nin??a and El Nin??o winters. The performance of the full-dynamical approach could not be evaluated as rigorously as that of the other two forecasting schemes. Although the full-dynamical forecasting approach is expected to outperform simpler forecasting schemes in the long run, evidence is presented to conclude that, at present, the full-dynamical forecasting approach is the least viable of the three, at least in California. The authors suggest that operational forecasting of any intraseasonal temperature, precipitation, or streamflow statistic derivable from the available records is possible now for ENSO-extreme years.

New insights into the nonadiabatic state population dynamics of model proton-coupled electron transfer reactions from the mixed quantum-classical Liouville approach

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

Shakib, Farnaz A.; Hanna, Gabriel, E-mail: gabriel.hanna@ualberta.ca

In a previous study [F. A. Shakib and G. Hanna, J. Chem. Phys. 141, 044122 (2014)], we investigated a model proton-coupled electron transfer (PCET) reaction via the mixed quantum-classical Liouville (MQCL) approach and found that the trajectories spend the majority of their time on the mean of two coherently coupled adiabatic potential energy surfaces. This suggested a need for mean surface evolution to accurately simulate observables related to ultrafast PCET processes. In this study, we simulate the time-dependent populations of the three lowest adiabatic states in the ET-PT (i.e., electron transfer preceding proton transfer) version of the same PCET modelmore » via the MQCL approach and compare them to the exact quantum results and those obtained via the fewest switches surface hopping (FSSH) approach. We find that the MQCL population profiles are in good agreement with the exact quantum results and show a significant improvement over the FSSH results. All of the mean surfaces are shown to play a direct role in the dynamics of the state populations. Interestingly, our results indicate that the population transfer to the second-excited state can be mediated by dynamics on the mean of the ground and second-excited state surfaces, as part of a sequence of nonadiabatic transitions that bypasses the first-excited state surface altogether. This is made possible through nonadiabatic transitions between different mean surfaces, which is the manifestation of coherence transfer in MQCL dynamics. We also investigate the effect of the strength of the coupling between the proton/electron and the solvent coordinate on the state population dynamics. Drastic changes in the population dynamics are observed, which can be understood in terms of the changes in the potential energy surfaces and the nonadiabatic couplings. Finally, we investigate the state population dynamics in the PT-ET (i.e., proton transfer preceding electron transfer) and concerted versions of the model. The PT-ET results confirm the participation of all of the mean surfaces, albeit in different proportions compared to the ET-PT case, while the concerted results indicate that the mean of the ground- and first-excited state surfaces only plays a role, due to the large energy gaps between the ground- and second-excited state surfaces.« less

Out-of-plane dynamic stability analysis of curved beams subjected to uniformly distributed radial loading

NASA Astrophysics Data System (ADS)

Sabuncu, M.; Ozturk, H.; Cimen; S.

2011-04-01

In this study, out-of-plane stability analysis of tapered cross-sectioned thin curved beams under uniformly distributed radial loading is performed by using the finite-element method. Solutions referred to as Bolotin's approach are analysed for dynamic stability, and the first unstable regions are examined. Out-of-plane vibration and out-of-plane buckling analyses are also studied. In addition, the results obtained in this study are compared with the published results of other researchers for the fundamental frequency and critical lateral buckling load. The effects of subtended angle, variations of cross-section, and dynamic load parameter on the stability regions are shown in graphics

Quasi-Dynamic Versus Fully-Dynamic Simulations of Slip Accumulation on Faults with Enhanced Dynamic Weakening

NASA Astrophysics Data System (ADS)

Lapusta, N.; Thomas, M.; Noda, H.; Avouac, J.

2012-12-01

Long-term simulations that incorporate both seismic events and aseismic slip are quite important for studies of earthquake physics but challenging computationally. To study long deformation histories, most simulation methods do not incorporate full inertial effects (wave propagation) during simulated earthquakes, using quasi-dynamic approximations instead. Here we compare the results of quasi-dynamic simulations to the fully dynamic ones for a range of problems to determine the applicability of the quasi-dynamic approach. Intuitively, the quasi-dynamic approach should do relatively well in problems where wave-mediated effects are relatively simple but should have substantially different (and hence wrong) response when the wave-mediated stress transfers dominate the character of the seismic events. This is exactly what we observe in our simulations. We consider a 2D model of a rate-and-state fault with a seismogenic (steady-state velocity-weakening) zone surrounded by creeping (steady-state velocity-strengthening) areas. If the seismogenic zone is described by the standard Dieterich-Ruina rate-and-state friction, the resulting earthquake sequences consist of relatively simple crack-like ruptures, and the inclusion of true wave-propagation effects mostly serves to concentrate stress more efficiently at the rupture front. Hence, in such models, rupture speeds and slip rates are significantly (several times) lower in the quasi-dynamic simulations compared to the fully dynamic ones, but the total slip, the crack-like nature of seismic events, and the overall pattern of earthquake sequences is comparable, consistently with prior studies. Such behavior can be classified as qualitatively similar but quantitatively different, and it motivates the popularity of the quasi-dynamic methods in simulations. However, the comparison changes dramatically once we consider a model with enhanced dynamic weakening in the seismogenic zone in the form of flash heating. In this case, the fully dynamic simulations produce seismic ruptures in the form of short-duration slip pulses, where the pulses form due to a combination of enhanced weakening and wave effects. The quasi-dynamic simulations in the same model produce completely different results, with large crack-like ruptures, different total slips, different rupture patterns, and different prestress state before large, model-spanning events. Such qualitative differences between the quasi-dynamic and fully-dynamic simulation should result in any model where inertial effects lead to qualitative differences, such as cases with supershear transition or fault with different materials on the two sides. We will present results on our current work on how the quasi-dynamic and fully dynamic simulations compare for the cases with heterogeneous fault properties.

A spectral-Tchebychev solution for three-dimensional dynamics of curved beams under mixed boundary conditions

NASA Astrophysics Data System (ADS)

Bediz, Bekir; Aksoy, Serdar

2018-01-01

This paper presents the application of the spectral-Tchebychev (ST) technique for solution of three-dimensional dynamics of curved beams/structures having variable and arbitrary cross-section under mixed boundary conditions. To accurately capture the vibrational behavior of curved structures, a three-dimensional (3D) solution approach is required since these structures generally exhibit coupled motions. In this study, the integral boundary value problem (IBVP) governing the dynamics of the curved structures is found using extended Hamilton's principle where the strain energy is expressed using 3D linear elasticity equation. To solve the IBVP numerically, the 3D spectral Tchebychev (3D-ST) approach is used. To evaluate the integral and derivative operations defined by the IBVP and to render the complex geometry into an equivalent straight beam with rectangular cross-section, a series of coordinate transformations are applied. To validate and assess the performance of the presented solution approach, two case studies are performed: (i) curved beam with rectangular cross-section, (ii) curved and pretwisted beam with airfoil cross-section. In both cases, the results (natural frequencies and mode shapes) are also found using a finite element (FE) solution approach. It is shown that the difference in predicted natural frequencies are less than 1%, and the mode shapes are in excellent agreement based on the modal assurance criteria (MAC) analyses; however, the presented spectral-Tchebychev solution approach significantly reduces the computational burden. Therefore, it can be concluded that the presented solution approach can capture the 3D vibrational behavior of curved beams as accurately as an FE solution, but for a fraction of the computational cost.

A Supervised Approach to Windowing Detection on Dynamic Networks

DTIC Science & Technology

2017-07-01

A supervised approach to windowing detection on dynamic networks Benjamin Fish University of Illinois at Chicago 1200 W. Harrison St. Chicago...Using this framework, we introduce windowing algorithms that take a supervised approach : they leverage ground truth on training data to find a good...windowing of the test data. We compare the supervised approach to previous approaches and several baselines on real data. ACM Reference format: Benjamin

Summary and Findings of the ARL Dynamic Failure Forum

DTIC Science & Technology

2016-09-29

short beam shear, quasi -static indentation, depth of penetration, and V50 limit velocity. o Experimental technique suggestions for improvement included...art in experimental , theoretical, and computational studies of dynamic failure. The forum also focused on identifying technologies and approaches...Army-specific problems. Experimental exploration of material behavior and an improved ability to parameterize material models is essential to improving

Implementation of Abstract Data Types in Dynamic Sketches for Learning Geometry

ERIC Educational Resources Information Center

Jasute, Egle; Dagiene, Valentina

2014-01-01

A long-term observation of students' usage of a dynamic geometry in a classroom at all grade levels has challenged to develop an approach for learning and understanding mathematics in an easier way for both students and teachers. The paper deals with the results of a study that investigates the process and outcomes of the implementation of…

Exact Solution of Gas Dynamics Equations Through Reduced Differential Transform and Sumudu Transform Linked with Pades Approximants

NASA Astrophysics Data System (ADS)

Rao, T. R. Ramesh

2018-04-01

In this paper, we study the analytical method based on reduced differential transform method coupled with sumudu transform through Pades approximants. The proposed method may be considered as alternative approach for finding exact solution of Gas dynamics equation in an effective manner. This method does not require any discretization, linearization and perturbation.

Handling qualities of large flexible control-configured aircraft

NASA Technical Reports Server (NTRS)

Swaim, R. L.

1979-01-01

The approach to an analytical study of flexible airplane longitudinal handling qualities was to parametrically vary the natural frequencies of two symmetric elastic modes to induce mode interactions with the rigid body dynamics. Since the structure of the pilot model was unknown for such dynamic interactions, the optimal control pilot modeling method is being applied and used in conjunction with pilot rating method.

Clay Caterpillar Whodunit: A Customizable Method for Studying Predator-Prey Interactions in the Field

ERIC Educational Resources Information Center

Curtis, Rachel; Klemens, Jeffrey A.; Agosta, Salvatore J.; Bartlow, Andrew W.; Wood, Steve; Carlson, Jason A.; Stratford, Jeffrey A.; Steele, Michael A.

2013-01-01

Predator-prey dynamics are an important concept in ecology, often serving as an introduction to the field of community ecology. However, these dynamics are difficult for students to observe directly. We describe a methodology that employs model caterpillars made of clay to estimate rates of predator attack on a prey species. This approach can be…

Endangered Butterflies as a Model System for Managing Source Sink Dynamics on Department of Defense Lands

DTIC Science & Technology

patches to cycle from sink to source status and back.Objective: Through a combination of field studies and state-of-the-art quantitative models, we...landscapes with dynamic changes in habitat quality due to management. We also validated our general approach by comparing patterns in our focal species to general, cross-taxa, patterns.

Computational fluid dynamics research

NASA Technical Reports Server (NTRS)

Chandra, Suresh; Jones, Kenneth; Hassan, Hassan; Mcrae, David Scott

1992-01-01

The focus of research in the computational fluid dynamics (CFD) area is two fold: (1) to develop new approaches for turbulence modeling so that high speed compressible flows can be studied for applications to entry and re-entry flows; and (2) to perform research to improve CFD algorithm accuracy and efficiency for high speed flows. Research activities, faculty and student participation, publications, and financial information are outlined.

Applying differential dynamic logic to reconfigurable biological networks.

PubMed

Figueiredo, Daniel; Martins, Manuel A; Chaves, Madalena

2017-09-01

Qualitative and quantitative modeling frameworks are widely used for analysis of biological regulatory networks, the former giving a preliminary overview of the system's global dynamics and the latter providing more detailed solutions. Another approach is to model biological regulatory networks as hybrid systems, i.e., systems which can display both continuous and discrete dynamic behaviors. Actually, the development of synthetic biology has shown that this is a suitable way to think about biological systems, which can often be constructed as networks with discrete controllers, and present hybrid behaviors. In this paper we discuss this approach as a special case of the reconfigurability paradigm, well studied in Computer Science (CS). In CS there are well developed computational tools to reason about hybrid systems. We argue that it is worth applying such tools in a biological context. One interesting tool is differential dynamic logic (dL), which has recently been developed by Platzer and applied to many case-studies. In this paper we discuss some simple examples of biological regulatory networks to illustrate how dL can be used as an alternative, or also as a complement to methods already used. Copyright © 2017 Elsevier Inc. All rights reserved.

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity.

PubMed

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity.

Agent-Based Modeling of Mitochondria Links Sub-Cellular Dynamics to Cellular Homeostasis and Heterogeneity

PubMed Central

Dalmasso, Giovanni; Marin Zapata, Paula Andrea; Brady, Nathan Ryan; Hamacher-Brady, Anne

2017-01-01

Mitochondria are semi-autonomous organelles that supply energy for cellular biochemistry through oxidative phosphorylation. Within a cell, hundreds of mobile mitochondria undergo fusion and fission events to form a dynamic network. These morphological and mobility dynamics are essential for maintaining mitochondrial functional homeostasis, and alterations both impact and reflect cellular stress states. Mitochondrial homeostasis is further dependent on production (biogenesis) and the removal of damaged mitochondria by selective autophagy (mitophagy). While mitochondrial function, dynamics, biogenesis and mitophagy are highly-integrated processes, it is not fully understood how systemic control in the cell is established to maintain homeostasis, or respond to bioenergetic demands. Here we used agent-based modeling (ABM) to integrate molecular and imaging knowledge sets, and simulate population dynamics of mitochondria and their response to environmental energy demand. Using high-dimensional parameter searches we integrated experimentally-measured rates of mitochondrial biogenesis and mitophagy, and using sensitivity analysis we identified parameter influences on population homeostasis. By studying the dynamics of cellular subpopulations with distinct mitochondrial masses, our approach uncovered system properties of mitochondrial populations: (1) mitochondrial fusion and fission activities rapidly establish mitochondrial sub-population homeostasis, and total cellular levels of mitochondria alter fusion and fission activities and subpopulation distributions; (2) restricting the directionality of mitochondrial mobility does not alter morphology subpopulation distributions, but increases network transmission dynamics; and (3) maintaining mitochondrial mass homeostasis and responding to bioenergetic stress requires the integration of mitochondrial dynamics with the cellular bioenergetic state. Finally, (4) our model suggests sources of, and stress conditions amplifying, cell-to-cell variability of mitochondrial morphology and energetic stress states. Overall, our modeling approach integrates biochemical and imaging knowledge, and presents a novel open-modeling approach to investigate how spatial and temporal mitochondrial dynamics contribute to functional homeostasis, and how subcellular organelle heterogeneity contributes to the emergence of cell heterogeneity. PMID:28060865

Molecular dynamics simulations of large macromolecular complexes.

PubMed

Perilla, Juan R; Goh, Boon Chong; Cassidy, C Keith; Liu, Bo; Bernardi, Rafael C; Rudack, Till; Yu, Hang; Wu, Zhe; Schulten, Klaus

2015-04-01

Connecting dynamics to structural data from diverse experimental sources, molecular dynamics simulations permit the exploration of biological phenomena in unparalleled detail. Advances in simulations are moving the atomic resolution descriptions of biological systems into the million-to-billion atom regime, in which numerous cell functions reside. In this opinion, we review the progress, driven by large-scale molecular dynamics simulations, in the study of viruses, ribosomes, bioenergetic systems, and other diverse applications. These examples highlight the utility of molecular dynamics simulations in the critical task of relating atomic detail to the function of supramolecular complexes, a task that cannot be achieved by smaller-scale simulations or existing experimental approaches alone. Copyright © 2015 Elsevier Ltd. All rights reserved.

A domain decomposition approach to implementing fault slip in finite-element models of quasi-static and dynamic crustal deformation

USGS Publications Warehouse

Aagaard, Brad T.; Knepley, M.G.; Williams, C.A.

2013-01-01

We employ a domain decomposition approach with Lagrange multipliers to implement fault slip in a finite-element code, PyLith, for use in both quasi-static and dynamic crustal deformation applications. This integrated approach to solving both quasi-static and dynamic simulations leverages common finite-element data structures and implementations of various boundary conditions, discretization schemes, and bulk and fault rheologies. We have developed a custom preconditioner for the Lagrange multiplier portion of the system of equations that provides excellent scalability with problem size compared to conventional additive Schwarz methods. We demonstrate application of this approach using benchmarks for both quasi-static viscoelastic deformation and dynamic spontaneous rupture propagation that verify the numerical implementation in PyLith.

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty.

PubMed

Mdluli, Thembi; Buzzard, Gregery T; Rundell, Ann E

2015-09-01

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm's scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements.

A meta-model for computer executable dynamic clinical safety checklists.

PubMed

Nan, Shan; Van Gorp, Pieter; Lu, Xudong; Kaymak, Uzay; Korsten, Hendrikus; Vdovjak, Richard; Duan, Huilong

2017-12-12

Safety checklist is a type of cognitive tool enforcing short term memory of medical workers with the purpose of reducing medical errors caused by overlook and ignorance. To facilitate the daily use of safety checklists, computerized systems embedded in the clinical workflow and adapted to patient-context are increasingly developed. However, the current hard-coded approach of implementing checklists in these systems increase the cognitive efforts of clinical experts and coding efforts for informaticists. This is due to the lack of a formal representation format that is both understandable by clinical experts and executable by computer programs. We developed a dynamic checklist meta-model with a three-step approach. Dynamic checklist modeling requirements were extracted by performing a domain analysis. Then, existing modeling approaches and tools were investigated with the purpose of reusing these languages. Finally, the meta-model was developed by eliciting domain concepts and their hierarchies. The feasibility of using the meta-model was validated by two case studies. The meta-model was mapped to specific modeling languages according to the requirements of hospitals. Using the proposed meta-model, a comprehensive coronary artery bypass graft peri-operative checklist set and a percutaneous coronary intervention peri-operative checklist set have been developed in a Dutch hospital and a Chinese hospital, respectively. The result shows that it is feasible to use the meta-model to facilitate the modeling and execution of dynamic checklists. We proposed a novel meta-model for the dynamic checklist with the purpose of facilitating creating dynamic checklists. The meta-model is a framework of reusing existing modeling languages and tools to model dynamic checklists. The feasibility of using the meta-model is validated by implementing a use case in the system.

Conformational Dynamics of Mechanically Compliant DNA Nanostructures from Coarse-Grained Molecular Dynamics Simulations.

PubMed

Shi, Ze; Castro, Carlos E; Arya, Gaurav

2017-05-23

Structural DNA nanotechnology, the assembly of rigid 3D structures of complex yet precise geometries, has recently been used to design dynamic, mechanically compliant nanostructures with tunable equilibrium conformations and conformational distributions. Here we use coarse-grained molecular dynamics simulations to provide insights into the conformational dynamics of a set of mechanically compliant DNA nanostructures-DNA hinges that use single-stranded DNA "springs" to tune the equilibrium conformation of a layered double-stranded DNA "joint" connecting two stiff "arms" constructed from DNA helix bundles. The simulations reproduce the experimentally measured equilibrium angles between hinge arms for a range of hinge designs. The hinges are found to be structurally stable, except for some fraying of the open ends of the DNA helices comprising the hinge arms and some loss of base-pairing interactions in the joint regions coinciding with the crossover junctions, especially in hinges designed to exhibit a small bending angle that exhibit large local stresses resulting in strong kinks in their joints. Principal component analysis reveals that while the hinge dynamics are dominated by bending motion, some twisting and sliding of hinge arms relative to each other also exists. Forced deformation of the hinges reveals distinct bending mechanisms for hinges with short, inextensible springs versus those with longer, more extensible springs. Lastly, we introduce an approach for rapidly predicting equilibrium hinge angles from individual force-deformation behaviors of its single- and double-stranded DNA components. Taken together, these results demonstrate that coarse-grained modeling is a promising approach for designing, predicting, and studying the dynamics of compliant DNA nanostructures, where conformational fluctuations become important, multiple deformation mechanisms exist, and continuum approaches may not yield accurate properties.

Efficient Optimization of Stimuli for Model-Based Design of Experiments to Resolve Dynamical Uncertainty

PubMed Central

Mdluli, Thembi; Buzzard, Gregery T.; Rundell, Ann E.

2015-01-01

This model-based design of experiments (MBDOE) method determines the input magnitudes of an experimental stimuli to apply and the associated measurements that should be taken to optimally constrain the uncertain dynamics of a biological system under study. The ideal global solution for this experiment design problem is generally computationally intractable because of parametric uncertainties in the mathematical model of the biological system. Others have addressed this issue by limiting the solution to a local estimate of the model parameters. Here we present an approach that is independent of the local parameter constraint. This approach is made computationally efficient and tractable by the use of: (1) sparse grid interpolation that approximates the biological system dynamics, (2) representative parameters that uniformly represent the data-consistent dynamical space, and (3) probability weights of the represented experimentally distinguishable dynamics. Our approach identifies data-consistent representative parameters using sparse grid interpolants, constructs the optimal input sequence from a greedy search, and defines the associated optimal measurements using a scenario tree. We explore the optimality of this MBDOE algorithm using a 3-dimensional Hes1 model and a 19-dimensional T-cell receptor model. The 19-dimensional T-cell model also demonstrates the MBDOE algorithm’s scalability to higher dimensions. In both cases, the dynamical uncertainty region that bounds the trajectories of the target system states were reduced by as much as 86% and 99% respectively after completing the designed experiments in silico. Our results suggest that for resolving dynamical uncertainty, the ability to design an input sequence paired with its associated measurements is particularly important when limited by the number of measurements. PMID:26379275

Dynamic Group Formation Based on a Natural Phenomenon

ERIC Educational Resources Information Center

Zedadra, Amina; Lafifi, Yacine; Zedadra, Ouarda

2016-01-01

This paper presents a new approach of learners grouping in collaborative learning systems. This grouping process is based on traces left by learners. The goal is the circular dynamic grouping to achieve collaborative projects. The proposed approach consists of two main algorithms: (1) the circular grouping algorithm and (2) the dynamic grouping…

Review and evaluation of recent developments in melic inlet dynamic flow distortion prediction and computer program documentation and user's manual estimating maximum instantaneous inlet flow distortion from steady-state total pressure measurements with full, limited, or no dynamic data

NASA Technical Reports Server (NTRS)

Schweikhard, W. G.; Dennon, S. R.

1986-01-01

A review of the Melick method of inlet flow dynamic distortion prediction by statistical means is provided. These developments include the general Melick approach with full dynamic measurements, a limited dynamic measurement approach, and a turbulence modelling approach which requires no dynamic rms pressure fluctuation measurements. These modifications are evaluated by comparing predicted and measured peak instantaneous distortion levels from provisional inlet data sets. A nonlinear mean-line following vortex model is proposed and evaluated as a potential criterion for improving the peak instantaneous distortion map generated from the conventional linear vortex of the Melick method. The model is simplified to a series of linear vortex segments which lay along the mean line. Maps generated with this new approach are compared with conventionally generated maps, as well as measured peak instantaneous maps. Inlet data sets include subsonic, transonic, and supersonic inlets under various flight conditions.

Historical dynamics in ecosystem service bundles.

PubMed

Renard, Delphine; Rhemtulla, Jeanine M; Bennett, Elena M

2015-10-27

Managing multiple ecosystem services (ES), including addressing trade-offs between services and preventing ecological surprises, is among the most pressing areas for sustainability research. These challenges require ES research to go beyond the currently common approach of snapshot studies limited to one or two services at a single point in time. We used a spatiotemporal approach to examine changes in nine ES and their relationships from 1971 to 2006 across 131 municipalities in a mixed-use landscape in Quebec, Canada. We show how an approach that incorporates time and space can improve our understanding of ES dynamics. We found an increase in the provision of most services through time; however, provision of ES was not uniformly enhanced at all locations. Instead, each municipality specialized in providing a bundle (set of positively correlated ES) dominated by just a few services. The trajectory of bundle formation was related to changes in agricultural policy and global trends; local biophysical and socioeconomic characteristics explained the bundles' increasing spatial clustering. Relationships between services varied through time, with some provisioning and cultural services shifting from a trade-off or no relationship in 1971 to an apparent synergistic relationship by 2006. By implementing a spatiotemporal perspective on multiple services, we provide clear evidence of the dynamic nature of ES interactions and contribute to identifying processes and drivers behind these changing relationships. Our study raises questions about using snapshots of ES provision at a single point in time to build our understanding of ES relationships in complex and dynamic social-ecological systems.

Detecting Brain State Changes via Fiber-Centered Functional Connectivity Analysis

PubMed Central

Li, Xiang; Lim, Chulwoo; Li, Kaiming; Guo, Lei; Liu, Tianming

2013-01-01

Diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) have been widely used to study structural and functional brain connectivity in recent years. A common assumption used in many previous functional brain connectivity studies is the temporal stationarity. However, accumulating literature evidence has suggested that functional brain connectivity is under temporal dynamic changes in different time scales. In this paper, a novel and intuitive approach is proposed to model and detect dynamic changes of functional brain states based on multimodal fMRI/DTI data. The basic idea is that functional connectivity patterns of all fiber-connected cortical voxels are concatenated into a descriptive functional feature vector to represent the brain’s state, and the temporal change points of brain states are decided by detecting the abrupt changes of the functional vector patterns via the sliding window approach. Our extensive experimental results have shown that meaningful brain state change points can be detected in task-based fMRI/DTI, resting state fMRI/DTI, and natural stimulus fMRI/DTI data sets. Particularly, the detected change points of functional brain states in task-based fMRI corresponded well to the external stimulus paradigm administered to the participating subjects, thus partially validating the proposed brain state change detection approach. The work in this paper provides novel perspective on the dynamic behaviors of functional brain connectivity and offers a starting point for future elucidation of the complex patterns of functional brain interactions and dynamics. PMID:22941508

It's positive to be negative: Achilles tendon work loops during human locomotion.

PubMed

Zelik, Karl E; Franz, Jason R

2017-01-01

Ultrasound imaging is increasingly used with motion and force data to quantify tendon dynamics during human movement. Frequently, tendon dynamics are estimated indirectly from muscle fascicle kinematics (by subtracting muscle from muscle-tendon unit length), but there is mounting evidence that this Indirect approach yields implausible tendon work loops. Since tendons are passive viscoelastic structures, when they undergo a loading-unloading cycle they must exhibit a negative work loop (i.e., perform net negative work). However, prior studies using this Indirect approach report large positive work loops, often estimating that tendons return 2-5 J of elastic energy for every 1 J of energy stored. More direct ultrasound estimates of tendon kinematics have emerged that quantify tendon elongations by tracking either the muscle-tendon junction or localized tendon tissue. However, it is unclear if these yield more plausible estimates of tendon dynamics. Our objective was to compute tendon work loops and hysteresis losses using these two Direct tendon kinematics estimates during human walking. We found that Direct estimates generally resulted in negative work loops, with average tendon hysteresis losses of 2-11% at 1.25 m/s and 33-49% at 0.75 m/s (N = 8), alluding to 0.51-0.98 J of tendon energy returned for every 1 J stored. We interpret this finding to suggest that Direct approaches provide more plausible estimates than the Indirect approach, and may be preferable for understanding tendon energy storage and return. However, the Direct approaches did exhibit speed-dependent trends that are not consistent with isolated, in vitro tendon hysteresis losses of about 5-10%. These trends suggest that Direct estimates also contain some level of error, albeit much smaller than Indirect estimates. Overall, this study serves to highlight the complexity and difficulty of estimating tendon dynamics non-invasively, and the care that must be taken to interpret biological function from current ultrasound-based estimates.

Machine learning–enabled identification of material phase transitions based on experimental data: Exploring collective dynamics in ferroelectric relaxors

DOE PAGES

Li, Linglong; Yang, Yaodong; Zhang, Dawei; ...

2018-03-30

Exploration of phase transitions and construction of associated phase diagrams are of fundamental importance for condensed matter physics and materials science alike, and remain the focus of extensive research for both theoretical and experimental studies. For the latter, comprehensive studies involving scattering, thermodynamics, and modeling are typically required. We present a new approach to data mining multiple realizations of collective dynamics, measured through piezoelectric relaxation studies, to identify the onset of a structural phase transition in nanometer-scale volumes, that is, the probed volume of an atomic force microscope tip. Machine learning is used to analyze the multidimensional data sets describingmore » relaxation to voltage and thermal stimuli, producing the temperature-bias phase diagram for a relaxor crystal without the need to measure (or know) the order parameter. The suitability of the approach to determine the phase diagram is shown with simulations based on a two-dimensional Ising model. Finally, these results indicate that machine learning approaches can be used to determine phase transitions in ferroelectrics, providing a general, statistically significant, and robust approach toward determining the presence of critical regimes and phase boundaries.« less

Mathematical and computational approaches can complement experimental studies of host-pathogen interactions.

PubMed

Kirschner, Denise E; Linderman, Jennifer J

2009-04-01

In addition to traditional and novel experimental approaches to study host-pathogen interactions, mathematical and computer modelling have recently been applied to address open questions in this area. These modelling tools not only offer an additional avenue for exploring disease dynamics at multiple biological scales, but also complement and extend knowledge gained via experimental tools. In this review, we outline four examples where modelling has complemented current experimental techniques in a way that can or has already pushed our knowledge of host-pathogen dynamics forward. Two of the modelling approaches presented go hand in hand with articles in this issue exploring fluorescence resonance energy transfer and two-photon intravital microscopy. Two others explore virtual or 'in silico' deletion and depletion as well as a new method to understand and guide studies in genetic epidemiology. In each of these examples, the complementary nature of modelling and experiment is discussed. We further note that multi-scale modelling may allow us to integrate information across length (molecular, cellular, tissue, organism, population) and time (e.g. seconds to lifetimes). In sum, when combined, these compatible approaches offer new opportunities for understanding host-pathogen interactions.

Machine learning–enabled identification of material phase transitions based on experimental data: Exploring collective dynamics in ferroelectric relaxors

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

Li, Linglong; Yang, Yaodong; Zhang, Dawei

Exploration of phase transitions and construction of associated phase diagrams are of fundamental importance for condensed matter physics and materials science alike, and remain the focus of extensive research for both theoretical and experimental studies. For the latter, comprehensive studies involving scattering, thermodynamics, and modeling are typically required. We present a new approach to data mining multiple realizations of collective dynamics, measured through piezoelectric relaxation studies, to identify the onset of a structural phase transition in nanometer-scale volumes, that is, the probed volume of an atomic force microscope tip. Machine learning is used to analyze the multidimensional data sets describingmore » relaxation to voltage and thermal stimuli, producing the temperature-bias phase diagram for a relaxor crystal without the need to measure (or know) the order parameter. The suitability of the approach to determine the phase diagram is shown with simulations based on a two-dimensional Ising model. Finally, these results indicate that machine learning approaches can be used to determine phase transitions in ferroelectrics, providing a general, statistically significant, and robust approach toward determining the presence of critical regimes and phase boundaries.« less

Landslide Hazard from Coupled Inherent and Dynamic Probabilities

NASA Astrophysics Data System (ADS)

Strauch, R. L.; Istanbulluoglu, E.; Nudurupati, S. S.

2015-12-01

Landslide hazard research has typically been conducted independently from hydroclimate research. We sought to unify these two lines of research to provide regional scale landslide hazard information for risk assessments and resource management decision-making. Our approach couples an empirical inherent landslide probability, based on a frequency ratio analysis, with a numerical dynamic probability, generated by combining subsurface water recharge and surface runoff from the Variable Infiltration Capacity (VIC) macro-scale land surface hydrologic model with a finer resolution probabilistic slope stability model. Landslide hazard mapping is advanced by combining static and dynamic models of stability into a probabilistic measure of geohazard prediction in both space and time. This work will aid resource management decision-making in current and future landscape and climatic conditions. The approach is applied as a case study in North Cascade National Park Complex in northern Washington State.

An introduction to NMR-based approaches for measuring protein dynamics

PubMed Central

Kleckner, Ian R; Foster, Mark P

2010-01-01

Proteins are inherently flexible at ambient temperature. At equilibrium, they are characterized by a set of conformations that undergo continuous exchange within a hierarchy of spatial and temporal scales ranging from nanometers to micrometers and femtoseconds to hours. Dynamic properties of proteins are essential for describing the structural bases of their biological functions including catalysis, binding, regulation and cellular structure. Nuclear magnetic resonance (NMR) spectroscopy represents a powerful technique for measuring these essential features of proteins. Here we provide an introduction to NMR-based approaches for studying protein dynamics, highlighting eight distinct methods with recent examples, contextualized within a common experimental and analytical framework. The selected methods are (1) Real-time NMR, (2) Exchange spectroscopy, (3) Lineshape analysis, (4) CPMG relaxation dispersion, (5) Rotating frame relaxation dispersion, (6) Nuclear spin relaxation, (7) Residual dipolar coupling, (8) Paramagnetic relaxation enhancement. PMID:21059410

Multilayer-MCTDH approach to the energy transfer dynamics in the LH2 antenna complex

NASA Astrophysics Data System (ADS)

Shibl, Mohamed F.; Schulze, Jan; Al-Marri, Mohammed J.; Kühn, Oliver

2017-09-01

The multilayer multiconfiguration time-dependent Hartree method is used to study the coupled exciton-vibrational dynamics in a high-dimensional nonameric model of the LH2 antenna complex of purple bacteria. The exciton-vibrational coupling is parametrized within the Huang-Rhys model according to phonon and intramolecular vibrational modes derived from an experimental bacteriochlorophyll spectral density. In contrast to reduced density matrix approaches, the Schrödinger equation is solved explicitly, giving access to the full wave function. This facilitates an unbiased analysis in terms of the coupled dynamics of excitonic and vibrational degrees of freedom. For the present system, we identify spectator modes for the B800 to B800 transfer and we find a non-additive effect of phonon and intramolecular vibrational modes on the B800 to B850 exciton transfer.

Using Imaging Methods to Interrogate Radiation-Induced Cell Signaling

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

Shankaran, Harish; Weber, Thomas J.; Freiin von Neubeck, Claere H.

2012-04-01

There is increasing emphasis on the use of systems biology approaches to define radiation induced responses in cells and tissues. Such approaches frequently rely on global screening using various high throughput 'omics' platforms. Although these methods are ideal for obtaining an unbiased overview of cellular responses, they often cannot reflect the inherent heterogeneity of the system or provide detailed spatial information. Additionally, performing such studies with multiple sampling time points can be prohibitively expensive. Imaging provides a complementary method with high spatial and temporal resolution capable of following the dynamics of signaling processes. In this review, we utilize specific examplesmore » to illustrate how imaging approaches have furthered our understanding of radiation induced cellular signaling. Particular emphasis is placed on protein co-localization, and oscillatory and transient signaling dynamics.« less

SMA Hybrid Composites for Dynamic Response Abatement Applications

NASA Technical Reports Server (NTRS)

Turner, Travis L.

2000-01-01

A recently developed constitutive model and a finite element formulation for predicting the thermomechanical response of Shape Memory Alloy (SMA) hybrid composite (SMAHC) structures is briefly described. Attention is focused on constrained recovery behavior in this study, but the constitutive formulation is also capable of modeling restrained or free recovery. Numerical results are shown for glass/epoxy panel specimens with embedded Nitinol actuators subjected to thermal and acoustic loads. Control of thermal buckling, random response, sonic fatigue, and transmission loss are demonstrated and compared to conventional approaches including addition of conventional composite layers and a constrained layer damping treatment. Embedded SMA actuators are shown to be significantly more effective in dynamic response abatement applications than the conventional approaches and are attractive for combination with other passive and/or active approaches.

On the sighting of unicorns: A variational approach to computing invariant sets in dynamical systems

NASA Astrophysics Data System (ADS)

Junge, Oliver; Kevrekidis, Ioannis G.

2017-06-01

We propose to compute approximations to invariant sets in dynamical systems by minimizing an appropriate distance between a suitably selected finite set of points and its image under the dynamics. We demonstrate, through computational experiments, that this approach can successfully converge to approximations of (maximal) invariant sets of arbitrary topology, dimension, and stability, such as, e.g., saddle type invariant sets with complicated dynamics. We further propose to extend this approach by adding a Lennard-Jones type potential term to the objective function, which yields more evenly distributed approximating finite point sets, and illustrate the procedure through corresponding numerical experiments.

On the sighting of unicorns: A variational approach to computing invariant sets in dynamical systems.

PubMed

Junge, Oliver; Kevrekidis, Ioannis G

2017-06-01

We propose to compute approximations to invariant sets in dynamical systems by minimizing an appropriate distance between a suitably selected finite set of points and its image under the dynamics. We demonstrate, through computational experiments, that this approach can successfully converge to approximations of (maximal) invariant sets of arbitrary topology, dimension, and stability, such as, e.g., saddle type invariant sets with complicated dynamics. We further propose to extend this approach by adding a Lennard-Jones type potential term to the objective function, which yields more evenly distributed approximating finite point sets, and illustrate the procedure through corresponding numerical experiments.

MEXICANS IN THE UNITED STATES--A PROBLEM IN SOCIAL DIFFERENTIATION.

ERIC Educational Resources Information Center

BROOM, LEONARD; SHEVKY, ESHREF

AN ANALYTIC EMPIRICAL APPROACH TO THE STUDY OF MEXICANS IN THE UNITED STATES IS PRESENTED. MEXICAN-AMERICANS FORM AN IMPORTANT ETHNIC GROUP BY VIRTUE OF NUMBERS, REGIONAL CONCENTRATION, SOCIAL POSITION, AND DYNAMIC CHARACTER. FINDINGS SHOULD BE AMENABLE TO COMPARATIVE TREATMENT WITH OTHER STATUS AND ETHNIC GROUPS. THE APPROACH INVOLVES A SERIES OF…

Toward a Common Structure in Demographic Educational Modeling and Simulation: A Complex Systems Approach

ERIC Educational Resources Information Center

Guevara, Porfirio

2014-01-01

This article identifies elements and connections that seem to be relevant to explain persistent aggregate behavioral patterns in educational systems when using complex dynamical systems modeling and simulation approaches. Several studies have shown what factors are at play in educational fields, but confusion still remains about the underlying…

Global dynamic optimization approach to predict activation in metabolic pathways.

PubMed

de Hijas-Liste, Gundián M; Klipp, Edda; Balsa-Canto, Eva; Banga, Julio R

2014-01-06

During the last decade, a number of authors have shown that the genetic regulation of metabolic networks may follow optimality principles. Optimal control theory has been successfully used to compute optimal enzyme profiles considering simple metabolic pathways. However, applying this optimal control framework to more general networks (e.g. branched networks, or networks incorporating enzyme production dynamics) yields problems that are analytically intractable and/or numerically very challenging. Further, these previous studies have only considered a single-objective framework. In this work we consider a more general multi-objective formulation and we present solutions based on recent developments in global dynamic optimization techniques. We illustrate the performance and capabilities of these techniques considering two sets of problems. First, we consider a set of single-objective examples of increasing complexity taken from the recent literature. We analyze the multimodal character of the associated non linear optimization problems, and we also evaluate different global optimization approaches in terms of numerical robustness, efficiency and scalability. Second, we consider generalized multi-objective formulations for several examples, and we show how this framework results in more biologically meaningful results. The proposed strategy was used to solve a set of single-objective case studies related to unbranched and branched metabolic networks of different levels of complexity. All problems were successfully solved in reasonable computation times with our global dynamic optimization approach, reaching solutions which were comparable or better than those reported in previous literature. Further, we considered, for the first time, multi-objective formulations, illustrating how activation in metabolic pathways can be explained in terms of the best trade-offs between conflicting objectives. This new methodology can be applied to metabolic networks with arbitrary topologies, non-linear dynamics and constraints.

Analysing spatio-temporal land degradation dynamics in dry rangelands using landscape metrics and satellite time series data

NASA Astrophysics Data System (ADS)

von Keyserlingk, Jennifer; Paton, Eva Nora; Förster, Saskia; Bronstert, Axel

2017-04-01

Many of the dry rangelands of Southern Europe are threatened by land degradation. This process not only reduces the land's ecological functioning, but also its capacity to provide ecosystem goods and services for local land users. In rangelands, one important aspect is vegetation degradation, which reduces the land's capacity to support livestock. Thus, there is an urgent need to understand the complex dynamics and drivers of land degradation. In the past, both have been difficult to study due to the extensive spatial and temporal scales involved. In the last decade, a large number of remotely sensed imageries has become available for free, which enables a new approach to this topic. The aim of this research is to study land degradation as a multidimensional process incorporating its spatial and temporal components. We developed a methodological approach that makes use of long-term satellite Landsat data. Here, we use imagery of a typical degraded Mediterranean rangeland in Southern Cyprus (Randi Forest) for the years 1998-2015. We have chosen the NDVI as a proxy for vegetation greenness and applied different spatial landscape metrics to calculate changes in vegetation patterns over time. Further, we applied a time-series based approach (BFAST) on selected pixels, to look for sudden changes and trends in the vegetation dynamics. The results promoted our knowledge on how land degradation dynamics in Mediterranean rangelands can be captured through spatio-temporal vegetation dynamics and allowed us to select the most suitable metrics for further analysis. In the long-term, we aim at using Landsat satellite data covering 30 years. To gain a functional understanding of land degradation, we want to overlay our results from the remotely sensed data with results of an eco-hydrological model (SWAT).

Metaheuristics for the dynamic stochastic dial-a-ride problem with expected return transports.

PubMed

Schilde, M; Doerner, K F; Hartl, R F

2011-12-01

The problem of transporting patients or elderly people has been widely studied in literature and is usually modeled as a dial-a-ride problem (DARP). In this paper we analyze the corresponding problem arising in the daily operation of the Austrian Red Cross. This nongovernmental organization is the largest organization performing patient transportation in Austria. The aim is to design vehicle routes to serve partially dynamic transportation requests using a fixed vehicle fleet. Each request requires transportation from a patient's home location to a hospital (outbound request) or back home from the hospital (inbound request). Some of these requests are known in advance. Some requests are dynamic in the sense that they appear during the day without any prior information. Finally, some inbound requests are stochastic. More precisely, with a certain probability each outbound request causes a corresponding inbound request on the same day. Some stochastic information about these return transports is available from historical data. The purpose of this study is to investigate, whether using this information in designing the routes has a significant positive effect on the solution quality. The problem is modeled as a dynamic stochastic dial-a-ride problem with expected return transports. We propose four different modifications of metaheuristic solution approaches for this problem. In detail, we test dynamic versions of variable neighborhood search (VNS) and stochastic VNS (S-VNS) as well as modified versions of the multiple plan approach (MPA) and the multiple scenario approach (MSA). Tests are performed using 12 sets of test instances based on a real road network. Various demand scenarios are generated based on the available real data. Results show that using the stochastic information on return transports leads to average improvements of around 15%. Moreover, improvements of up to 41% can be achieved for some test instances.

Increasing BCI Communication Rates with Dynamic Stopping Towards More Practical Use: An ALS Study

PubMed Central

Mainsah, B. O.; Collins, L. M.; Colwell, K. A.; Sellers, E. W.; Ryan, D. B.; Caves, K.; Throckmorton, C. S.

2015-01-01

Objective The P300 speller is a brain-computer interface (BCI) that can possibly restore communication abilities to individuals with severe neuromuscular disabilities, such as amyotrophic lateral sclerosis (ALS), by exploiting elicited brain signals in electroencephalography data. However, accurate spelling with BCIs is slow due to the need to average data over multiple trials to increase the signal-to-noise ratio of the elicited brain signals. Probabilistic approaches to dynamically control data collection have shown improved performance in non-disabled populations; however, validation of these approaches in a target BCI user population has not occurred. Approach We have developed a data-driven algorithm for the P300 speller based on Bayesian inference that improves spelling time by adaptively selecting the number of trials based on the acute signal-to-noise ratio of a user’s electroencephalography data. We further enhanced the algorithm by incorporating information about the user’s language. In this current study, we test and validate the algorithms online in a target BCI user population, by comparing the performance of the dynamic stopping (or early stopping) algorithms against the current state-of-the-art method, static data collection, where the amount of data collected is fixed prior to online operation. Main Results Results from online testing of the dynamic stopping algorithms in participants with ALS demonstrate a significant increase in communication rate as measured in bits/sec (100-300%), and theoretical bit rate (100-550%), while maintaining selection accuracy. Participants also overwhelmingly preferred the dynamic stopping algorithms. Significance We have developed a viable BCI algorithm that has been tested in a target BCI population which has the potential for translation to improve BCI speller performance towards more practical use for communication. PMID:25588137

Using Motor Imagery to Study the Neural Substrates of Dynamic Balance

PubMed Central

Ferraye, Murielle Ursulla; Debû, Bettina; Heil, Lieke; Carpenter, Mark; Bloem, Bastiaan Roelof; Toni, Ivan

2014-01-01

This study examines the cerebral structures involved in dynamic balance using a motor imagery (MI) protocol. We recorded cerebral activity with functional magnetic resonance imaging while subjects imagined swaying on a balance board along the sagittal plane to point a laser at target pairs of different sizes (small, large). We used a matched visual imagery (VI) control task and recorded imagery durations during scanning. MI and VI durations were differentially influenced by the sway accuracy requirement, indicating that MI of balance is sensitive to the increased motor control necessary to point at a smaller target. Compared to VI, MI of dynamic balance recruited additional cortical and subcortical portions of the motor system, including frontal cortex, basal ganglia, cerebellum and mesencephalic locomotor region, the latter showing increased effective connectivity with the supplementary motor area. The regions involved in MI of dynamic balance were spatially distinct but contiguous to those involved in MI of gait (Bakker et al., 2008; Snijders et al., 2011; Crémers et al., 2012), in a pattern consistent with existing somatotopic maps of the trunk (for balance) and legs (for gait). These findings validate a novel, quantitative approach for studying the neural control of balance in humans. This approach extends previous reports on MI of static stance (Jahn et al., 2004, 2008), and opens the way for studying gait and balance impairments in patients with neurodegenerative disorders. PMID:24663383

Using motor imagery to study the neural substrates of dynamic balance.

PubMed

Ferraye, Murielle Ursulla; Debû, Bettina; Heil, Lieke; Carpenter, Mark; Bloem, Bastiaan Roelof; Toni, Ivan

2014-01-01

This study examines the cerebral structures involved in dynamic balance using a motor imagery (MI) protocol. We recorded cerebral activity with functional magnetic resonance imaging while subjects imagined swaying on a balance board along the sagittal plane to point a laser at target pairs of different sizes (small, large). We used a matched visual imagery (VI) control task and recorded imagery durations during scanning. MI and VI durations were differentially influenced by the sway accuracy requirement, indicating that MI of balance is sensitive to the increased motor control necessary to point at a smaller target. Compared to VI, MI of dynamic balance recruited additional cortical and subcortical portions of the motor system, including frontal cortex, basal ganglia, cerebellum and mesencephalic locomotor region, the latter showing increased effective connectivity with the supplementary motor area. The regions involved in MI of dynamic balance were spatially distinct but contiguous to those involved in MI of gait (Bakker et al., 2008; Snijders et al., 2011; Crémers et al., 2012), in a pattern consistent with existing somatotopic maps of the trunk (for balance) and legs (for gait). These findings validate a novel, quantitative approach for studying the neural control of balance in humans. This approach extends previous reports on MI of static stance (Jahn et al., 2004, 2008), and opens the way for studying gait and balance impairments in patients with neurodegenerative disorders.

Dynamic optimization of metabolic networks coupled with gene expression.

PubMed

Waldherr, Steffen; Oyarzún, Diego A; Bockmayr, Alexander

2015-01-21

The regulation of metabolic activity by tuning enzyme expression levels is crucial to sustain cellular growth in changing environments. Metabolic networks are often studied at steady state using constraint-based models and optimization techniques. However, metabolic adaptations driven by changes in gene expression cannot be analyzed by steady state models, as these do not account for temporal changes in biomass composition. Here we present a dynamic optimization framework that integrates the metabolic network with the dynamics of biomass production and composition. An approximation by a timescale separation leads to a coupled model of quasi-steady state constraints on the metabolic reactions, and differential equations for the substrate concentrations and biomass composition. We propose a dynamic optimization approach to determine reaction fluxes for this model, explicitly taking into account enzyme production costs and enzymatic capacity. In contrast to the established dynamic flux balance analysis, our approach allows predicting dynamic changes in both the metabolic fluxes and the biomass composition during metabolic adaptations. Discretization of the optimization problems leads to a linear program that can be efficiently solved. We applied our algorithm in two case studies: a minimal nutrient uptake network, and an abstraction of core metabolic processes in bacteria. In the minimal model, we show that the optimized uptake rates reproduce the empirical Monod growth for bacterial cultures. For the network of core metabolic processes, the dynamic optimization algorithm predicted commonly observed metabolic adaptations, such as a diauxic switch with a preference ranking for different nutrients, re-utilization of waste products after depletion of the original substrate, and metabolic adaptation to an impending nutrient depletion. These examples illustrate how dynamic adaptations of enzyme expression can be predicted solely from an optimization principle. Copyright © 2014 Elsevier Ltd. All rights reserved.

Frequency-response identification of XV-15 tilt-rotor aircraft dynamics

NASA Technical Reports Server (NTRS)

Tischler, Mark B.

1987-01-01

The timely design and development of the next generation of tilt-rotor aircraft (JVX) depend heavily on the in-depth understanding of existing XV-15 dynamics and the availability of fully validated simulation models. Previous studies have considered aircraft and simulation trim characteristics, but analyses of basic flight vehicle dynamics were limited to qualitative pilot evaluation. The present study has the following objectives: documentation and evaluation of XV-15 bare-airframe dynamics; comparison of aircraft and simulation responses; and development of a validated transfer-function description of the XV-15 needed for future studies. A nonparametric frequency-response approach is used which does not depend on assumed model order or structure. Transfer-function representations are subsequently derived which fit the frequency responses in the bandwidth of greatest concern for piloted handling-qualities and control-system applications.

A computational study on choline benzoate and choline salicylate ionic liquids in the pure state and after CO2 adsorption.

PubMed

Aparicio, Santiago; Atilhan, Mert

2012-08-02

Choline-based ionic liquids show very adequate environmental, toxicological, and economical profiles for their application in many different technological areas. We report in this work a computational study on the properties of choline benzoate and choline salicylate ionic liquids, as representatives of this family of compounds, in the pure state and after CO(2) adsorption. Quantum chemistry calculations using the density functional theory approach for ionic pairs and ions, CO(2) pairs, were carried out, and the results analyzed using natural bond orbital and atoms in a molecule approaches. Classical molecular dynamics simulations of ionic liquids were done as a function of pressure, temperature, and CO(2) concentration. Microscopic structuring and intermolecular forces are analyzed together with the dynamic behavior of the studied fluids.

Dynamic modeling and hierarchical compound control of a novel 2-DOF flexible parallel manipulator with multiple actuation modes

NASA Astrophysics Data System (ADS)

Liang, Dong; Song, Yimin; Sun, Tao; Jin, Xueying

2018-03-01

This paper addresses the problem of rigid-flexible coupling dynamic modeling and active control of a novel flexible parallel manipulator (PM) with multiple actuation modes. Firstly, based on the flexible multi-body dynamics theory, the rigid-flexible coupling dynamic model (RFDM) of system is developed by virtue of the augmented Lagrangian multipliers approach. For completeness, the mathematical models of permanent magnet synchronous motor (PMSM) and piezoelectric transducer (PZT) are further established and integrated with the RFDM of mechanical system to formulate the electromechanical coupling dynamic model (ECDM). To achieve the trajectory tracking and vibration suppression, a hierarchical compound control strategy is presented. Within this control strategy, the proportional-differential (PD) feedback controller is employed to realize the trajectory tracking of end-effector, while the strain and strain rate feedback (SSRF) controller is developed to restrain the vibration of the flexible links using PZT. Furthermore, the stability of the control algorithm is demonstrated based on the Lyapunov stability theory. Finally, two simulation case studies are performed to illustrate the effectiveness of the proposed approach. The results indicate that, under the redundant actuation mode, the hierarchical compound control strategy can guarantee the flexible PM achieves singularity-free motion and vibration attenuation within task workspace simultaneously. The systematic methodology proposed in this study can be conveniently extended for the dynamic modeling and efficient controller design of other flexible PMs, especially the emerging ones with multiple actuation modes.

Visualization and Analysis of Microtubule Dynamics Using Dual Color-Coded Display of Plus-End Labels

PubMed Central

Garrison, Amy K.; Xia, Caihong; Wang, Zheng; Ma, Le

2012-01-01

Investigating spatial and temporal control of microtubule dynamics in live cells is critical to understanding cell morphogenesis in development and disease. Tracking fluorescently labeled plus-end-tracking proteins over time has become a widely used method to study microtubule assembly. Here, we report a complementary approach that uses only two images of these labels to visualize and analyze microtubule dynamics at any given time. Using a simple color-coding scheme, labeled plus-ends from two sequential images are pseudocolored with different colors and then merged to display color-coded ends. Based on object recognition algorithms, these colored ends can be identified and segregated into dynamic groups corresponding to four events, including growth, rescue, catastrophe, and pause. Further analysis yields not only their spatial distribution throughout the cell but also provides measurements such as growth rate and direction for each labeled end. We have validated the method by comparing our results with ground-truth data derived from manual analysis as well as with data obtained using the tracking method. In addition, we have confirmed color-coded representation of different dynamic events by analyzing their history and fate. Finally, we have demonstrated the use of the method to investigate microtubule assembly in cells and provided guidance in selecting optimal image acquisition conditions. Thus, this simple computer vision method offers a unique and quantitative approach to study spatial regulation of microtubule dynamics in cells. PMID:23226282

Dynamic Assessment: An Approach Toward Reducing Test Bias.

ERIC Educational Resources Information Center

Carlson, Jerry S.; Wiedl, Karl Heinz

Through dynamic testing (the notion that tailored testing can be extended to the use of a learning oriented approach to assessment), analysis were made of how motivational, personality, and cognitive style factors interact with assessment approaches to yield performance data. Testing procedures involving simple feedback, elaborated feedback, and…

An Ecological Approach to Learning Dynamics

ERIC Educational Resources Information Center

Normak, Peeter; Pata, Kai; Kaipainen, Mauri

2012-01-01

New approaches to emergent learner-directed learning design can be strengthened with a theoretical framework that considers learning as a dynamic process. We propose an approach that models a learning process using a set of spatial concepts: learning space, position of a learner, niche, perspective, step, path, direction of a step and step…

Theoretical investigation of polarization effects in solution: Importance of solvent collective motions

NASA Astrophysics Data System (ADS)

Ishida, Tateki

2015-01-01

Recent theoretical studies on interesting topics related to polarization effects in solutions are presented. As one of interesting topics, ionic liquids (ILs) solvents are focused on. The collective dynamics of electronic polarizability through interionic dynamics and the effect of polarization in ILs, 1-butyl-3-methylimidazolium hexafluorophosphate ([BMIm][PF6]), are studied with molecular dynamics simulation. Also, the time-dependent polarization effect on the probe betaine dye molecule, pyridinium N-phenoxide, in water is investigated by a time-dependent reference interaction site model self-consistent field (time-dependent RISM-SCF) approach. The importance of considering polarization effects on solution systems related to solvent collective motions is shown.

Beam dynamics validation of the Halbach Technology FFAG Cell for Cornell-BNL Energy Recovery Linac

NASA Astrophysics Data System (ADS)

Méot, F.; Tsoupas, N.; Brooks, S.; Trbojevic, D.

2018-07-01

The Cornell-BNL Electron Test Accelerator (CBETA), a 150 MeV energy recovery linac (ERL) now in construction at Cornell, employs a fixed-field alternating gradient optics return loop: a single beam line comprised of FFAG cells, which accepts four recirculated energies. CBETA FFAG cell uses Halbach permanent magnet technology, its design studies have covered an extended period of time supported by extensive particle dynamics simulations using computed 3-D field map models. This approach is discussed, and illustrated here, based on the final stage in these beam dynamics studies, namely the validation of a ultimate, optimized design of the Halbach cell.

Parallel realities: exploring poverty dynamics using mixed methods in rural Bangladesh.

PubMed

Davisa, Peter; Baulch, Bob

2011-01-01

This paper explores the implications of using two methodological approaches to study poverty dynamics in rural Bangladesh. Using data from a unique longitudinal study, we show how different methods lead to very different assessments of socio-economic mobility. We suggest five ways of reconciling these differences: considering assets in addition to expenditures, proximity to the poverty line, other aspects of well-being, household division, and qualitative recall errors. Considering assets and proximity to the poverty line along with expenditures resolves three-fifths of the qualitative and quantitative differences. Use of such integrated mixed-methods can therefore improve the reliability of poverty dynamics research.

N-ROSS: The dynamics and control issues

NASA Technical Reports Server (NTRS)

Lindberg, Robert E.

1986-01-01

The Navy Remote Ocean Sensing System (N-ROSS) Dynamic Stability Study team concluded that the frozen April 1985 design was viable and contained no show stoppers, although it was also clear from the study results that the configuration required further optimization. While the frozen N-ROSS configuration used has since been superceded, and the vehicle is now under competitive procurement, several other results remain from the study that will have lasting value to the N-ROSS program. The importance of constructing an integrated simulation, to serve as a design and verification aid, has been clearly established. The two team approach to the study afforded the Navy a higher degree of confidence in the results than could have been accomplished by a single simulation, and the approach led to results that highlighted subtleties in the model and simulation development that surely would have been overlookded without the benefit of an independent companion simulation with which to compare it.

Peptide dynamics by molecular dynamics simulation and diffusion theory method with improved basis sets

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

Hsu, Po Jen; Lai, S. K., E-mail: sklai@coll.phy.ncu.edu.tw; Rapallo, Arnaldo

Improved basis sets for the study of polymer dynamics by means of the diffusion theory, and tests on a melt of cis-1,4-polyisoprene decamers, and a toluene solution of a 71-mer syndiotactic trans-1,2-polypentadiene were presented recently [R. Gaspari and A. Rapallo, J. Chem. Phys. 128, 244109 (2008)]. The proposed hybrid basis approach (HBA) combined two techniques, the long time sorting procedure and the maximum correlation approximation. The HBA takes advantage of the strength of these two techniques, and its basis sets proved to be very effective and computationally convenient in describing both local and global dynamics in cases of flexible syntheticmore » polymers where the repeating unit is a unique type of monomer. The question then arises if the same efficacy continues when the HBA is applied to polymers of different monomers, variable local stiffness along the chain and with longer persistence length, which have different local and global dynamical properties against the above-mentioned systems. Important examples of this kind of molecular chains are the proteins, so that a fragment of the protein transthyretin is chosen as the system of the present study. This peptide corresponds to a sequence that is structured in β-sheets of the protein and is located on the surface of the channel with thyroxin. The protein transthyretin forms amyloid fibrils in vivo, whereas the peptide fragment has been shown [C. P. Jaroniec, C. E. MacPhee, N. S. Astrof, C. M. Dobson, and R. G. Griffin, Proc. Natl. Acad. Sci. U.S.A. 99, 16748 (2002)] to form amyloid fibrils in vitro in extended β-sheet conformations. For these reasons the latter is given considerable attention in the literature and studied also as an isolated fragment in water solution where both experimental and theoretical efforts have indicated the propensity of the system to form β turns or α helices, but is otherwise predominantly unstructured. Differing from previous computational studies that employed implicit solvent, we performed in this work the classical molecular dynamics simulation on a realistic model solution with the peptide embedded in an explicit water environment, and calculated its dynamic properties both as an outcome of the simulations, and by the diffusion theory in reduced statistical-mechanical approach within HBA on the premise that the mode-coupling approach to the diffusion theory can give both the long-range and local dynamics starting from equilibrium averages which were obtained from detailed atomistic simulations.« less

A New Approach on the Long Term Dynamics of NEO's Under Yarkovsky Effect.

NASA Astrophysics Data System (ADS)

Peláez, Jesús; Urrutxua, Hodei; Bombardelli, Claudio; Perez-Grande, Isabel

2011-12-01

A classical approach to the many-body problem is that of using special perturbation methods. Nowadays and due to the availability of high-speed computers is an essential tool in Space Dynamics which exhibits a great advantage: it is applicable to any orbit involving any number of bodies and all sorts of astrodynamical problems, especially when these problems fall into regions in which general perturbation theories are absent. One such case is, for example, that Near Earth Objects (NEO's) dynamics. In this field, the Group of Tether Dynamics of UPM (GDT) has developed a new regularisation scheme - called DROMO - which is characterised by only 8 ODE. This new regularisation scheme allows a new approach to the dynamics of NEO's in the long term, specially appropriated to consider the influence of the anisotropic thermal emission (Yarkovsky and YORP effects) on the dynamics. A new project, called NEODROMO, has been started in GDT that aims to provide a reliable tool for the long term dynamics of NEO's.

Langevin Equation for DNA Dynamics

NASA Astrophysics Data System (ADS)

Grych, David; Copperman, Jeremy; Guenza, Marina

Under physiological conditions, DNA oligomers can contain well-ordered helical regions and also flexible single-stranded regions. We describe the site-specific motion of DNA with a modified Rouse-Zimm Langevin equation formalism that describes DNA as a coarse-grained polymeric chain with global structure and local flexibility. The approach has successfully described the protein dynamics in solution and has been extended to nucleic acids. Our approach provides diffusive mode analytical solutions for the dynamics of global rotational diffusion and internal motion. The internal DNA dynamics present a rich energy landscape that accounts for an interior where hydrogen bonds and base-stacking determine structure and experience limited solvent exposure. We have implemented several models incorporating different coarse-grained sites with anisotropic rotation, energy barrier crossing, and local friction coefficients that include a unique internal viscosity and our models reproduce dynamics predicted by atomistic simulations. The models reproduce bond autocorrelation along the sequence as compared to that directly calculated from atomistic molecular dynamics simulations. The Langevin equation approach captures the essence of DNA dynamics without a cumbersome atomistic representation.

Analysis of friction and instability by the centre manifold theory for a non-linear sprag-slip model

NASA Astrophysics Data System (ADS)

Sinou, J.-J.; Thouverez, F.; Jezequel, L.

2003-08-01

This paper presents the research devoted to the study of instability phenomena in non-linear model with a constant brake friction coefficient. Indeed, the impact of unstable oscillations can be catastrophic. It can cause vehicle control problems and component degradation. Accordingly, complex stability analysis is required. This paper outlines stability analysis and centre manifold approach for studying instability problems. To put it more precisely, one considers brake vibrations and more specifically heavy trucks judder where the dynamic characteristics of the whole front axle assembly is concerned, even if the source of judder is located in the brake system. The modelling introduces the sprag-slip mechanism based on dynamic coupling due to buttressing. The non-linearity is expressed as a polynomial with quadratic and cubic terms. This model does not require the use of brake negative coefficient, in order to predict the instability phenomena. Finally, the centre manifold approach is used to obtain equations for the limit cycle amplitudes. The centre manifold theory allows the reduction of the number of equations of the original system in order to obtain a simplified system, without loosing the dynamics of the original system as well as the contributions of non-linear terms. The goal is the study of the stability analysis and the validation of the centre manifold approach for a complex non-linear model by comparing results obtained by solving the full system and by using the centre manifold approach. The brake friction coefficient is used as an unfolding parameter of the fundamental Hopf bifurcation point.

Charge and energy migration in molecular clusters: A stochastic Schrödinger equation approach.

PubMed

Plehn, Thomas; May, Volkhard

2017-01-21

The performance of stochastic Schrödinger equations for simulating dynamic phenomena in large scale open quantum systems is studied. Going beyond small system sizes, commonly used master equation approaches become inadequate. In this regime, wave function based methods profit from their inherent scaling benefit and present a promising tool to study, for example, exciton and charge carrier dynamics in huge and complex molecular structures. In the first part of this work, a strict analytic derivation is presented. It starts with the finite temperature reduced density operator expanded in coherent reservoir states and ends up with two linear stochastic Schrödinger equations. Both equations are valid in the weak and intermediate coupling limit and can be properly related to two existing approaches in literature. In the second part, we focus on the numerical solution of these equations. The main issue is the missing norm conservation of the wave function propagation which may lead to numerical discrepancies. To illustrate this, we simulate the exciton dynamics in the Fenna-Matthews-Olson complex in direct comparison with the data from literature. Subsequently a strategy for the proper computational handling of the linear stochastic Schrödinger equation is exposed particularly with regard to large systems. Here, we study charge carrier transfer kinetics in realistic hybrid organic/inorganic para-sexiphenyl/ZnO systems of different extension.

Charge and energy migration in molecular clusters: A stochastic Schrödinger equation approach

NASA Astrophysics Data System (ADS)

Plehn, Thomas; May, Volkhard

2017-01-01

The performance of stochastic Schrödinger equations for simulating dynamic phenomena in large scale open quantum systems is studied. Going beyond small system sizes, commonly used master equation approaches become inadequate. In this regime, wave function based methods profit from their inherent scaling benefit and present a promising tool to study, for example, exciton and charge carrier dynamics in huge and complex molecular structures. In the first part of this work, a strict analytic derivation is presented. It starts with the finite temperature reduced density operator expanded in coherent reservoir states and ends up with two linear stochastic Schrödinger equations. Both equations are valid in the weak and intermediate coupling limit and can be properly related to two existing approaches in literature. In the second part, we focus on the numerical solution of these equations. The main issue is the missing norm conservation of the wave function propagation which may lead to numerical discrepancies. To illustrate this, we simulate the exciton dynamics in the Fenna-Matthews-Olson complex in direct comparison with the data from literature. Subsequently a strategy for the proper computational handling of the linear stochastic Schrödinger equation is exposed particularly with regard to large systems. Here, we study charge carrier transfer kinetics in realistic hybrid organic/inorganic para-sexiphenyl/ZnO systems of different extension.

Velocity measurements of heterogeneous RBC flow in capillary vessels using dynamic laser speckle signal

PubMed Central

Li, Chenxi; Wang, Ruikang

2017-01-01

Abstract. We propose an approach to measure heterogeneous velocities of red blood cells (RBCs) in capillary vessels using full-field time-varying dynamic speckle signals. The approach utilizes a low coherent laser speckle imaging system to record the instantaneous speckle pattern, followed by an eigen-decomposition-based filtering algorithm to extract dynamic speckle signal due to the moving RBCs. The velocity of heterogeneous RBC flows is determined by cross-correlating the temporal dynamic speckle signals obtained at adjacent locations. We verify the approach by imaging mouse pinna in vivo, demonstrating its capability for full-field RBC flow mapping and quantifying flow pattern with high resolution. It is expected to investigate the dynamic action of RBCs flow in capillaries under physiological changes. PMID:28384709

Policy analysis of the budget used in training program for reducing lower back pain among heavy equipment operators in the construction industry: System dynamics approach

NASA Astrophysics Data System (ADS)

Vitharana, V. H. P.; Chinda, T.

2018-04-01

Lower back pain (LBP), prevalence is high among the heavy equipment operators leading to high compensation cost in the construction industry. It is found that proper training program assists in reducing chances of having LBP. This study, therefore aims to examine different safety related budget available to support LBP related training program for different age group workers, utilizing system dynamics modeling approach. The simulation results show that at least 2.5% of the total budget must be allocated in the safety and health budget to reduce the chances of having LBP cases.

Simplified and advanced modelling of traction control systems of heavy-haul locomotives

NASA Astrophysics Data System (ADS)

Spiryagin, Maksym; Wolfs, Peter; Szanto, Frank; Cole, Colin

2015-05-01

Improving tractive effort is a very complex task in locomotive design. It requires the development of not only mechanical systems but also power systems, traction machines and traction algorithms. At the initial design stage, traction algorithms can be verified by means of a simulation approach. A simple single wheelset simulation approach is not sufficient because all locomotive dynamics are not fully taken into consideration. Given that many traction control strategies exist, the best solution is to use more advanced approaches for such studies. This paper describes the modelling of a locomotive with a bogie traction control strategy based on a co-simulation approach in order to deliver more accurate results. The simplified and advanced modelling approaches of a locomotive electric power system are compared in this paper in order to answer a fundamental question. What level of modelling complexity is necessary for the investigation of the dynamic behaviours of a heavy-haul locomotive running under traction? The simulation results obtained provide some recommendations on simulation processes and the further implementation of advanced and simplified modelling approaches.

Dynamics of sustained use and abandonment of clean cooking systems: study protocol for community-based system dynamics modeling.

PubMed

Kumar, Praveen; Chalise, Nishesh; Yadama, Gautam N

2016-04-26

More than 3 billion of the world's population are affected by household air pollution from relying on unprocessed solid fuels for heating and cooking. Household air pollution is harmful to human health, climate, and environment. Sustained uptake and use of cleaner cooking technologies and fuels are proposed as solutions to this problem. In this paper, we present our study protocol aimed at understanding multiple interacting feedback mechanisms involved in the dynamic behavior between social, ecological, and technological systems driving sustained use or abandonment of cleaner cooking technologies among the rural poor in India. This study uses a comparative case study design to understand the dynamics of sustained use or abandonment of cleaner cooking technologies and fuels in four rural communities of Rajasthan, India. The study adopts a community based system dynamics modeling approach. We describe our approach of using community based system dynamics with rural communities to delineate the feedback mechanisms involved in the uptake and sustainment of clean cooking technologies. We develop a reference mode with communities showing the trend over time of use or abandonment of cleaner cooking technologies and fuels in these communities. Subsequently, the study develops a system dynamics model with communities to understand the complex sub-systems driving the behavior in these communities as reflected in the reference mode. We use group model building techniques to facilitate participation of relevant stakeholders in the four communities and elicit a narrative describing the feedback mechanisms underlying sustained adoption or abandonment of cleaner cooking technologies. In understanding the dynamics of feedback mechanisms in the uptake and exclusive use of cleaner cooking systems, we increase the likelihood of dissemination and implementation of efficacious interventions into everyday settings to improve the health and wellbeing of women and children most affected by household air pollution. The challenge is not confined to developing robust technical solutions to reduce household air pollution and exposure to improve respiratory health, and prevent associated diseases. The bigger challenge is to disseminate and implement cleaner cooking technologies and fuels in the context of various social, behavioral, and economic constraints faced by poor households and communities. The Institutional Review Board of Washington University in St. Louis has exempted community based system dynamics modeling from review.

STED microscopy: A simplified method for liver sinusoidal endothelial fenestrae analysis.

PubMed

Martino, Julie Di; Mascalchi, Patrice; Legros, Philippe; Lacomme, Sabrina; Gontier, Etienne; Bioulac-Sage, Paulette; Balabaud, Charles; Moreau, Violaine; Saltel, Frédéric

2018-05-29

Liver sinusoidal endothelial cells (LSECs) possess fenestrae, open transcellular pores with an average diameter of 100nm. These fenestrae allow for the exchange between blood and hepatocytes. Alterations in their number or diameter in liver diseases have important implications for hepatic microcirculation and function. Although decades of studies, fenestrae are still observed into fixed cells and we have poor knowledge of their dynamics. Using stimulated emission depletion (STED) super-resolution microscopy, we have established a faster and simplest method to observe and quantify fenestrae. Indeed, using cytochalasin D, an actin depolymerizing agent known to promote fenestrae formation we measure the increase of fenestrae number. We adapted this methodology to develop an automated method to study fenestrae dynamics. Moreover, with two colors STED analysis we shown that this approach could be useful to study LSECs fenestrae molecular composition. Our approach demonstrate that STED microscopy is suitable for LSEC fenestrae study. This new way of analyzing LSEC fenestrae will allow for expedited investigation of their dynamics, molecular composition and functions to better understand their function in liver pathophysiology. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Preliminary results on the dynamics of large and flexible space structures in Halo orbits

NASA Astrophysics Data System (ADS)

Colagrossi, Andrea; Lavagna, Michèle

2017-05-01

The global exploration roadmap suggests, among other ambitious future space programmes, a possible manned outpost in lunar vicinity, to support surface operations and further astronaut training for longer and deeper space missions and transfers. In particular, a Lagrangian point orbit location - in the Earth- Moon system - is suggested for a manned cis-lunar infrastructure; proposal which opens an interesting field of study from the astrodynamics perspective. Literature offers a wide set of scientific research done on orbital dynamics under the Three-Body Problem modelling approach, while less of it includes the attitude dynamics modelling as well. However, whenever a large space structure (ISS-like) is considered, not only the coupled orbit-attitude dynamics should be modelled to run more accurate analyses, but the structural flexibility should be included too. The paper, starting from the well-known Circular Restricted Three-Body Problem formulation, presents some preliminary results obtained by adding a coupled orbit-attitude dynamical model and the effects due to the large structure flexibility. In addition, the most relevant perturbing phenomena, such as the Solar Radiation Pressure (SRP) and the fourth-body (Sun) gravity, are included in the model as well. A multi-body approach has been preferred to represent possible configurations of the large cis-lunar infrastructure: interconnected simple structural elements - such as beams, rods or lumped masses linked by springs - build up the space segment. To better investigate the relevance of the flexibility effects, the lumped parameters approach is compared with a distributed parameters semi-analytical technique. A sensitivity analysis of system dynamics, with respect to different configurations and mechanical properties of the extended structure, is also presented, in order to highlight drivers for the lunar outpost design. Furthermore, a case study for a large and flexible space structure in Halo orbits around one of the Earth-Moon collinear Lagrangian points, L1 or L2, is discussed to point out some relevant outcomes for the potential implementation of such a mission.

Dynamic Neural State Identification in Deep Brain Local Field Potentials of Neuropathic Pain.

PubMed

Luo, Huichun; Huang, Yongzhi; Du, Xueying; Zhang, Yunpeng; Green, Alexander L; Aziz, Tipu Z; Wang, Shouyan

2018-01-01

In neuropathic pain, the neurophysiological and neuropathological function of the ventro-posterolateral nucleus of the thalamus (VPL) and the periventricular gray/periaqueductal gray area (PVAG) involves multiple frequency oscillations. Moreover, oscillations related to pain perception and modulation change dynamically over time. Fluctuations in these neural oscillations reflect the dynamic neural states of the nucleus. In this study, an approach to classifying the synchronization level was developed to dynamically identify the neural states. An oscillation extraction model based on windowed wavelet packet transform was designed to characterize the activity level of oscillations. The wavelet packet coefficients sparsely represented the activity level of theta and alpha oscillations in local field potentials (LFPs). Then, a state discrimination model was designed to calculate an adaptive threshold to determine the activity level of oscillations. Finally, the neural state was represented by the activity levels of both theta and alpha oscillations. The relationship between neural states and pain relief was further evaluated. The performance of the state identification approach achieved sensitivity and specificity beyond 80% in simulation signals. Neural states of the PVAG and VPL were dynamically identified from LFPs of neuropathic pain patients. The occurrence of neural states based on theta and alpha oscillations were correlated to the degree of pain relief by deep brain stimulation. In the PVAG LFPs, the occurrence of the state with high activity levels of theta oscillations independent of alpha and the state with low-level alpha and high-level theta oscillations were significantly correlated with pain relief by deep brain stimulation. This study provides a reliable approach to identifying the dynamic neural states in LFPs with a low signal-to-noise ratio by using sparse representation based on wavelet packet transform. Furthermore, it may advance closed-loop deep brain stimulation based on neural states integrating multiple neural oscillations.

Dynamic Neural State Identification in Deep Brain Local Field Potentials of Neuropathic Pain

PubMed Central

Luo, Huichun; Huang, Yongzhi; Du, Xueying; Zhang, Yunpeng; Green, Alexander L.; Aziz, Tipu Z.; Wang, Shouyan

2018-01-01

In neuropathic pain, the neurophysiological and neuropathological function of the ventro-posterolateral nucleus of the thalamus (VPL) and the periventricular gray/periaqueductal gray area (PVAG) involves multiple frequency oscillations. Moreover, oscillations related to pain perception and modulation change dynamically over time. Fluctuations in these neural oscillations reflect the dynamic neural states of the nucleus. In this study, an approach to classifying the synchronization level was developed to dynamically identify the neural states. An oscillation extraction model based on windowed wavelet packet transform was designed to characterize the activity level of oscillations. The wavelet packet coefficients sparsely represented the activity level of theta and alpha oscillations in local field potentials (LFPs). Then, a state discrimination model was designed to calculate an adaptive threshold to determine the activity level of oscillations. Finally, the neural state was represented by the activity levels of both theta and alpha oscillations. The relationship between neural states and pain relief was further evaluated. The performance of the state identification approach achieved sensitivity and specificity beyond 80% in simulation signals. Neural states of the PVAG and VPL were dynamically identified from LFPs of neuropathic pain patients. The occurrence of neural states based on theta and alpha oscillations were correlated to the degree of pain relief by deep brain stimulation. In the PVAG LFPs, the occurrence of the state with high activity levels of theta oscillations independent of alpha and the state with low-level alpha and high-level theta oscillations were significantly correlated with pain relief by deep brain stimulation. This study provides a reliable approach to identifying the dynamic neural states in LFPs with a low signal-to-noise ratio by using sparse representation based on wavelet packet transform. Furthermore, it may advance closed-loop deep brain stimulation based on neural states integrating multiple neural oscillations. PMID:29695951

Dynamical model of binary asteroid systems through patched three-body problems

NASA Astrophysics Data System (ADS)

Ferrari, Fabio; Lavagna, Michèle; Howell, Kathleen C.

2016-08-01

The paper presents a strategy for trajectory design in the proximity of a binary asteroid pair. A novel patched approach has been used to design trajectories in the binary system, which is modeled by means of two different three-body systems. The model introduces some degrees of freedom with respect to a classical two-body approach and it is intended to model to higher accuracy the peculiar dynamical properties of such irregular and low gravity field bodies, while keeping the advantages of having a full analytical formulation and low computational cost required. The neighborhood of the asteroid couple is split into two regions of influence where two different three-body problems describe the dynamics of the spacecraft. These regions have been identified by introducing the concept of surface of equivalence (SOE), a three-dimensional surface that serves as boundary between the regions of influence of each dynamical model. A case of study is presented, in terms of potential scenario that may benefit of such an approach in solving its mission analysis. Cost-effective solutions to land a vehicle on the surface of a low gravity body are selected by generating Poincaré maps on the SOE, seeking intersections between stable and unstable manifolds of the two patched three-body systems.

A study on predicting network corrections in PPP-RTK processing

NASA Astrophysics Data System (ADS)

Wang, Kan; Khodabandeh, Amir; Teunissen, Peter

2017-10-01

In PPP-RTK processing, the network corrections including the satellite clocks, the satellite phase biases and the ionospheric delays are provided to the users to enable fast single-receiver integer ambiguity resolution. To solve the rank deficiencies in the undifferenced observation equations, the estimable parameters are formed to generate full-rank design matrix. In this contribution, we firstly discuss the interpretation of the estimable parameters without and with a dynamic satellite clock model incorporated in a Kalman filter during the network processing. The functionality of the dynamic satellite clock model is tested in the PPP-RTK processing. Due to the latency generated by the network processing and data transfer, the network corrections are delayed for the real-time user processing. To bridge the latencies, we discuss and compare two prediction approaches making use of the network corrections without and with the dynamic satellite clock model, respectively. The first prediction approach is based on the polynomial fitting of the estimated network parameters, while the second approach directly follows the dynamic model in the Kalman filter of the network processing and utilises the satellite clock drifts estimated in the network processing. Using 1 Hz data from two networks in Australia, the influences of the two prediction approaches on the user positioning results are analysed and compared for latencies ranging from 3 to 10 s. The accuracy of the positioning results decreases with the increasing latency of the network products. For a latency of 3 s, the RMS of the horizontal and the vertical coordinates (with respect to the ground truth) do not show large differences applying both prediction approaches. For a latency of 10 s, the prediction approach making use of the satellite clock model has generated slightly better positioning results with the differences of the RMS at mm-level. Further advantages and disadvantages of both prediction approaches are also discussed in this contribution.

OBSERVING LYAPUNOV EXPONENTS OF INFINITE-DIMENSIONAL DYNAMICAL SYSTEMS

PubMed Central

OTT, WILLIAM; RIVAS, MAURICIO A.; WEST, JAMES

2016-01-01

Can Lyapunov exponents of infinite-dimensional dynamical systems be observed by projecting the dynamics into ℝN using a ‘typical’ nonlinear projection map? We answer this question affirmatively by developing embedding theorems for compact invariant sets associated with C1 maps on Hilbert spaces. Examples of such discrete-time dynamical systems include time-T maps and Poincaré return maps generated by the solution semigroups of evolution partial differential equations. We make every effort to place hypotheses on the projected dynamics rather than on the underlying infinite-dimensional dynamical system. In so doing, we adopt an empirical approach and formulate checkable conditions under which a Lyapunov exponent computed from experimental data will be a Lyapunov exponent of the infinite-dimensional dynamical system under study (provided the nonlinear projection map producing the data is typical in the sense of prevalence). PMID:28066028

OBSERVING LYAPUNOV EXPONENTS OF INFINITE-DIMENSIONAL DYNAMICAL SYSTEMS.

PubMed

Ott, William; Rivas, Mauricio A; West, James

2015-12-01

Can Lyapunov exponents of infinite-dimensional dynamical systems be observed by projecting the dynamics into ℝ N using a 'typical' nonlinear projection map? We answer this question affirmatively by developing embedding theorems for compact invariant sets associated with C 1 maps on Hilbert spaces. Examples of such discrete-time dynamical systems include time- T maps and Poincaré return maps generated by the solution semigroups of evolution partial differential equations. We make every effort to place hypotheses on the projected dynamics rather than on the underlying infinite-dimensional dynamical system. In so doing, we adopt an empirical approach and formulate checkable conditions under which a Lyapunov exponent computed from experimental data will be a Lyapunov exponent of the infinite-dimensional dynamical system under study (provided the nonlinear projection map producing the data is typical in the sense of prevalence).

Understanding Digital Learning from the Perspective of Systems Dynamics

ERIC Educational Resources Information Center

Kok, Ayse

2009-01-01

The System Dynamics approach can be seen as a new way of understanding dynamical phenonema (natural, physical, biological, etc.) that occur in our daily lives taking into consideration not only single pairs of cause-effect variables, but the functioning of the system as a whole. This approach also provides the students with a new understanding in…

Plenary Speech: Researching Complex Dynamic Systems--"Retrodictive Qualitative Modelling" in the Language Classroom

ERIC Educational Resources Information Center

Dörnyei, Zoltán

2014-01-01

While approaching second language acquisition from a complex dynamic systems perspective makes a lot of intuitive sense, it is difficult for a number of reasons to operationalise such a dynamic approach in research terms. For example, the most common research paradigms in the social sciences tend to examine variables in relative isolation rather…

Creative-Dynamics Approach To Neural Intelligence

NASA Technical Reports Server (NTRS)

Zak, Michail A.

1992-01-01

Paper discusses approach to mathematical modeling of artificial neural networks exhibiting complicated behaviors reminiscent of creativity and intelligence of biological neural networks. Neural network treated as non-Lipschitzian dynamical system - as described in "Non-Lipschitzian Dynamics For Modeling Neural Networks" (NPO-17814). System serves as tool for modeling of temporal-pattern memories and recognition of complicated spatial patterns.

A comparative study of two statistical approaches for the analysis of real seismicity sequences and synthetic seismicity generated by a stick-slip experimental model

NASA Astrophysics Data System (ADS)

Flores-Marquez, Leticia Elsa; Ramirez Rojaz, Alejandro; Telesca, Luciano

2015-04-01

The study of two statistical approaches is analyzed for two different types of data sets, one is the seismicity generated by the subduction processes occurred at south Pacific coast of Mexico between 2005 and 2012, and the other corresponds to the synthetic seismic data generated by a stick-slip experimental model. The statistical methods used for the present study are the visibility graph in order to investigate the time dynamics of the series and the scaled probability density function in the natural time domain to investigate the critical order of the system. This comparison has the purpose to show the similarities between the dynamical behaviors of both types of data sets, from the point of view of critical systems. The observed behaviors allow us to conclude that the experimental set up globally reproduces the behavior observed in the statistical approaches used to analyses the seismicity of the subduction zone. The present study was supported by the Bilateral Project Italy-Mexico Experimental Stick-slip models of tectonic faults: innovative statistical approaches applied to synthetic seismic sequences, jointly funded by MAECI (Italy) and AMEXCID (Mexico) in the framework of the Bilateral Agreement for Scientific and Technological Cooperation PE 2014-2016.

Dynamic Tunnel Usability Study: Format Recommendations for Synthetic Vision System Primary Flight Displays

NASA Technical Reports Server (NTRS)

Arthur, Jarvis J., III; Prinzel, Lawrence J., III; Kramer, Lynda J.; Bailey, Randall E.

2006-01-01

A usability study evaluating dynamic tunnel concepts has been completed under the Aviation Safety and Security Program, Synthetic Vision Systems Project. The usability study was conducted in the Visual Imaging Simulator for Transport Aircraft Systems (VISTAS) III simulator in the form of questionnaires and pilot-in-the-loop simulation sessions. Twelve commercial pilots participated in the study to determine their preferences via paired comparisons and subjective rankings regarding the color, line thickness and sensitivity of the dynamic tunnel. The results of the study showed that color was not significant in pilot preference paired comparisons or in pilot rankings. Line thickness was significant for both pilot preference paired comparisons and in pilot rankings. The preferred line/halo thickness combination was a line width of 3 pixels and a halo of 4 pixels. Finally, pilots were asked their preference for the current dynamic tunnel compared to a less sensitive dynamic tunnel. The current dynamic tunnel constantly gives feedback to the pilot with regard to path error while the less sensitive tunnel only changes as the path error approaches the edges of the tunnel. The tunnel sensitivity comparison results were not statistically significant.