Frenetic Bounds on the Entropy Production

NASA Astrophysics Data System (ADS)

Maes, Christian

2017-10-01

We give a systematic derivation of positive lower bounds for the expected entropy production (EP) rate in classical statistical mechanical systems obeying a dynamical large deviation principle. The logic is the same for the return to thermodynamic equilibrium as it is for steady nonequilibria working under the condition of local detailed balance. We recover there recently studied "uncertainty" relations for the EP, appearing in studies about the effectiveness of mesoscopic machines. In general our refinement of the positivity of the expected EP rate is obtained in terms of a positive and even function of the expected current(s) which measures the dynamical activity in the system, a time-symmetric estimate of the changes in the system's configuration. Also underdamped diffusions can be included in the analysis.

Real-time dynamic modelling for the design of a cluster-randomized phase 3 Ebola vaccine trial in Sierra Leone.

PubMed

Camacho, A; Eggo, R M; Goeyvaerts, N; Vandebosch, A; Mogg, R; Funk, S; Kucharski, A J; Watson, C H; Vangeneugden, T; Edmunds, W J

2017-01-23

Declining incidence and spatial heterogeneity complicated the design of phase 3 Ebola vaccine trials during the tail of the 2013-16 Ebola virus disease (EVD) epidemic in West Africa. Mathematical models can provide forecasts of expected incidence through time and can account for both vaccine efficacy in participants and effectiveness in populations. Determining expected disease incidence was critical to calculating power and determining trial sample size. In real-time, we fitted, forecasted, and simulated a proposed phase 3 cluster-randomized vaccine trial for a prime-boost EVD vaccine in three candidate regions in Sierra Leone. The aim was to forecast trial feasibility in these areas through time and guide study design planning. EVD incidence was highly variable during the epidemic, especially in the declining phase. Delays in trial start date were expected to greatly reduce the ability to discern an effect, particularly as a trial with an effective vaccine would cause the epidemic to go extinct more quickly in the vaccine arm. Real-time updates of the model allowed decision-makers to determine how trial feasibility changed with time. This analysis was useful for vaccine trial planning because we simulated effectiveness as well as efficacy, which is possible with a dynamic transmission model. It contributed to decisions on choice of trial location and feasibility of the trial. Transmission models should be utilised as early as possible in the design process to provide mechanistic estimates of expected incidence, with which decisions about sample size, location, timing, and feasibility can be determined. Copyright © 2016. Published by Elsevier Ltd.

Preliminary Findings from the First Two Waves of a Panel Study of Developing Career Expectations.

ERIC Educational Resources Information Center

Hotchkiss, Lawrence; Chiteji, Lisa

This report is an exploratory application of a dynamic mathematical model to express a theory of changes in youth's career expectations over time. Main content is divided into two focuses: (1) theoretical interpretations of the differential equations which embody the mathematical model and (2) reporting and discussion of the results of preliminary…

Gravitational field calculations on a dynamic lattice by distributed computing.

NASA Astrophysics Data System (ADS)

Mähönen, P.; Punkka, V.

A new method of calculating numerically time evolution of a gravitational field in general relativity is introduced. Vierbein (tetrad) formalism, dynamic lattice and massively parallelized computation are suggested as they are expected to speed up the calculations considerably and facilitate the solution of problems previously considered too hard to be solved, such as the time evolution of a system consisting of two or more black holes or the structure of worm holes.

Gravitation Field Calculations on a Dynamic Lattice by Distributed Computing

NASA Astrophysics Data System (ADS)

Mähönen, Petri; Punkka, Veikko

A new method of calculating numerically time evolution of a gravitational field in General Relatity is introduced. Vierbein (tetrad) formalism, dynamic lattice and massively parallelized computation are suggested as they are expected to speed up the calculations considerably and facilitate the solution of problems previously considered too hard to be solved, such as the time evolution of a system consisting of two or more black holes or the structure of worm holes.

Demonstrating vegetation dynamics using SIMPPLLE

Treesearch

Glenda Scott; Jimmie D. Chew

1997-01-01

Understanding vegetation dynamics, both spatially and temporally, is essential to the management of natural resources. SIMPPLLE has been designed to help us quantify and communicate these concepts: What levels of process, i.e., fire or insect and disease, to expect; how they spread; what the vegetative distribution and composition is over time; and how silvicultural...

Dynamics of Galaxy Clusters and Expectations from Astro-H

NASA Technical Reports Server (NTRS)

Markevitch, Maxim

2012-01-01

Galaxy clusters span a range of dynamical states, from violent mergers -- the most energetic events in the Universe -- to systems near hydrostatic equilibrium that allow us to map their dark matter distribution using X-ray observations of the intracluster gas. Accurate knowledge of the cluster physics, and in particular, the physics of the hot intracluster gas, is required to realize the full potential of clusters as cosmological probes. So far, we have been studying the cluster dynamics indirectly, deducing merger geometries, cluster masses, etc., using X-ray brightness and gas temperature mapping. For the first time, the calorimeter onboard Astro-H will provide direct measurements of line-of-sight velocities and turbulent broadening in the intracluster gas, testing many of our key assumptions about clusters. This talk will summarize expectations for cluster dynamic studies with this new instrument.

Post-hit dynamics of price limit hits in the Chinese stock markets

NASA Astrophysics Data System (ADS)

Wu, Ting; Wang, Yue; Li, Ming-Xia

2017-01-01

Price limit trading rules are useful to cool off traders short-term trading mania on individual stocks. The price dynamics approaching the limit boards are known as the magnet effect. However, the price dynamics after opening price limit hits are not well investigated. Here, we provide a detailed analysis on the price dynamics after the hits of up-limit or down-limit is open based on all A-share stocks traded in the Chinese stock markets. A "W" shape is found in the expected return, which reveals high probability of a continuous price limit hit on the following day. We also find that price dynamics after opening limit hits are dependent on the market trends. The time span of continuously hitting the price limit is found to an influence factor of the expected profit after the limit hit is open. Our analysis provides a better understanding of the price dynamics around the limit boards and contributes potential practical values for investors.

The impact of land use change and hydroclimatic variability on landscape connectivity dynamics across surface water networks at subcontinental scale

NASA Astrophysics Data System (ADS)

Tulbure, M. G.; Bishop-Taylor, R.; Broich, M.

2017-12-01

Land use (LU) change and hydroclimatic variability affect spatiotemporal landscape connectivity dynamics, important for species movement and dispersal. Despite the fact that LU change can strongly influence dispersal potential over time, prior research has only focused on the impacts of dynamic changes in the distribution of potential habitats. We used 8 time-steps of historical LU together with a Landsat-derived time-series of surface water habitat dynamics (1986-2011) over the Murray-Darling Basin (MDB), a region with extreme hydroclimatic variability, impacted by LU changes. To assess how changing LU and hydroclimatic variability affect landscape connectivity across time, we compared 4 scenarios, namely one where both climate and LU are dynamic over time, one where climate is kept steady (i.e. a median surface water extent layer), and two scenarios where LU is kept steady (i.e. resistance values associated with the most recent or the first LU layer). We used circuit theory to assign landscape features with `resistance' costs and graph theory network analysis, with surface water habitats as `nodes' connected by dispersal paths or `edges' Findings comparing a dry and an average season show high differences in number of nodes (14581 vs 21544) and resistance distances. The combined effect of LU change and landscape wetness was lower than expected, likely a function of the large, MDB-wide, aggregation scale. Spatially explicit analyses are expected to identify areas where the synergistic effect of LU change and landscape wetness greatly reduce or increase landscape connectivity, as well as areas where the two effects cancel each other out.

Real-time electron dynamics for massively parallel excited-state simulations

NASA Astrophysics Data System (ADS)

Andrade, Xavier

The simulation of the real-time dynamics of electrons, based on time dependent density functional theory (TDDFT), is a powerful approach to study electronic excited states in molecular and crystalline systems. What makes the method attractive is its flexibility to simulate different kinds of phenomena beyond the linear-response regime, including strongly-perturbed electronic systems and non-adiabatic electron-ion dynamics. Electron-dynamics simulations are also attractive from a computational point of view. They can run efficiently on massively parallel architectures due to the low communication requirements. Our implementations of electron dynamics, based on the codes Octopus (real-space) and Qball (plane-waves), allow us to simulate systems composed of thousands of atoms and to obtain good parallel scaling up to 1.6 million processor cores. Due to the versatility of real-time electron dynamics and its parallel performance, we expect it to become the method of choice to apply the capabilities of exascale supercomputers for the simulation of electronic excited states.

Universal fractal scaling in stream chemistry and its implications for solute transport and water quality trend detection

PubMed Central

Kirchner, James W.; Neal, Colin

2013-01-01

The chemical dynamics of lakes and streams affect their suitability as aquatic habitats and as water supplies for human needs. Because water quality is typically monitored only weekly or monthly, however, the higher-frequency dynamics of stream chemistry have remained largely invisible. To illuminate a wider spectrum of water quality dynamics, rainfall and streamflow were sampled in two headwater catchments at Plynlimon, Wales, at 7-h intervals for 1–2 y and weekly for over two decades, and were analyzed for 45 solutes spanning the periodic table from H+ to U. Here we show that in streamflow, all 45 of these solutes, including nutrients, trace elements, and toxic metals, exhibit fractal 1/fα scaling on time scales from hours to decades (α = 1.05 ± 0.15, mean ± SD). We show that this fractal scaling can arise through dispersion of random chemical inputs distributed across a catchment. These 1/f time series are non–self-averaging: monthly, yearly, or decadal averages are approximately as variable, one from the next, as individual measurements taken hours or days apart, defying naive statistical expectations. (By contrast, stream discharge itself is nonfractal, and self-averaging on time scales of months and longer.) In the solute time series, statistically significant trends arise much more frequently, on all time scales, than one would expect from conventional t statistics. However, these same trends are poor predictors of future trends—much poorer than one would expect from their calculated uncertainties. Our results illustrate how 1/f time series pose fundamental challenges to trend analysis and change detection in environmental systems. PMID:23842090

Universal fractal scaling in stream chemistry and its implications for solute transport and water quality trend detection

NASA Astrophysics Data System (ADS)

Kirchner, James W.; Neal, Colin

2013-07-01

The chemical dynamics of lakes and streams affect their suitability as aquatic habitats and as water supplies for human needs. Because water quality is typically monitored only weekly or monthly, however, the higher-frequency dynamics of stream chemistry have remained largely invisible. To illuminate a wider spectrum of water quality dynamics, rainfall and streamflow were sampled in two headwater catchments at Plynlimon, Wales, at 7-h intervals for 1-2 y and weekly for over two decades, and were analyzed for 45 solutes spanning the periodic table from H+ to U. Here we show that in streamflow, all 45 of these solutes, including nutrients, trace elements, and toxic metals, exhibit fractal 1/fα scaling on time scales from hours to decades (α = 1.05 ± 0.15, mean ± SD). We show that this fractal scaling can arise through dispersion of random chemical inputs distributed across a catchment. These 1/f time series are non-self-averaging: monthly, yearly, or decadal averages are approximately as variable, one from the next, as individual measurements taken hours or days apart, defying naive statistical expectations. (By contrast, stream discharge itself is nonfractal, and self-averaging on time scales of months and longer.) In the solute time series, statistically significant trends arise much more frequently, on all time scales, than one would expect from conventional t statistics. However, these same trends are poor predictors of future trends-much poorer than one would expect from their calculated uncertainties. Our results illustrate how 1/f time series pose fundamental challenges to trend analysis and change detection in environmental systems.

Quantum Dynamics of Multi Harmonic Oscillators Described by Time Variant Conic Hamiltonian and their Use in Contemporary Sciences

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

Demiralp, Metin

This work focuses on the dynamics of a system of quantum multi harmonic oscillators whose Hamiltonian is conic in positions and momenta with time variant coefficients. While it is simple, this system is useful for modeling the dynamics of a number of systems in contemporary sciences where the equations governing spatial or temporal changes are described by sets of ODEs. The dynamical causal models used readily in neuroscience can be indirectly described by these systems. In this work, we want to show that it is possible to describe these systems using quantum wave function type entities and expectations if themore » dynamic of the system is related to a set of ODEs.« less

Synchronous dynamics of zooplankton competitors prevail in temperate lake ecosystems.

PubMed

Vasseur, David A; Fox, Jeremy W; Gonzalez, Andrew; Adrian, Rita; Beisner, Beatrix E; Helmus, Matthew R; Johnson, Catherine; Kratina, Pavel; Kremer, Colin; de Mazancourt, Claire; Miller, Elizabeth; Nelson, William A; Paterson, Michael; Rusak, James A; Shurin, Jonathan B; Steiner, Christopher F

2014-08-07

Although competing species are expected to exhibit compensatory dynamics (negative temporal covariation), empirical work has demonstrated that competitive communities often exhibit synchronous dynamics (positive temporal covariation). This has led to the suggestion that environmental forcing dominates species dynamics; however, synchronous and compensatory dynamics may appear at different length scales and/or at different times, making it challenging to identify their relative importance. We compiled 58 long-term datasets of zooplankton abundance in north-temperate and sub-tropical lakes and used wavelet analysis to quantify general patterns in the times and scales at which synchronous/compensatory dynamics dominated zooplankton communities in different regions and across the entire dataset. Synchronous dynamics were far more prevalent at all scales and times and were ubiquitous at the annual scale. Although we found compensatory dynamics in approximately 14% of all combinations of time period/scale/lake, there were no consistent scales or time periods during which compensatory dynamics were apparent across different regions. Our results suggest that the processes driving compensatory dynamics may be local in their extent, while those generating synchronous dynamics operate at much larger scales. This highlights an important gap in our understanding of the interaction between environmental and biotic forces that structure communities. © 2014 The Author(s) Published by the Royal Society. All rights reserved.

Development and application of a time-history analysis for rotorcraft dynamics based on a component approach

NASA Technical Reports Server (NTRS)

Sopher, R.; Hallock, D. W.

1985-01-01

A time history analysis for rotorcraft dynamics based on dynamical substructures, and nonstructural mathematical and aerodynamic components is described. The analysis is applied to predict helicopter ground resonance and response to rotor damage. Other applications illustrate the stability and steady vibratory response of stopped and gimballed rotors, representative of new technology. Desirable attributes expected from modern codes are realized, although the analysis does not employ a complete set of techniques identified for advanced software. The analysis is able to handle a comprehensive set of steady state and stability problems with a small library of components.

Are there ergodic limits to evolution? Ergodic exploration of genome space and convergence

PubMed Central

McLeish, Tom C. B.

2015-01-01

We examine the analogy between evolutionary dynamics and statistical mechanics to include the fundamental question of ergodicity—the representative exploration of the space of possible states (in the case of evolution this is genome space). Several properties of evolutionary dynamics are identified that allow a generalization of the ergodic dynamics, familiar in dynamical systems theory, to evolution. Two classes of evolved biological structure then arise, differentiated by the qualitative duration of their evolutionary time scales. The first class has an ergodicity time scale (the time required for representative genome exploration) longer than available evolutionary time, and has incompletely explored the genotypic and phenotypic space of its possibilities. This case generates no expectation of convergence to an optimal phenotype or possibility of its prediction. The second, more interesting, class exhibits an evolutionary form of ergodicity—essentially all of the structural space within the constraints of slower evolutionary variables have been sampled; the ergodicity time scale for the system evolution is less than the evolutionary time. In this case, some convergence towards similar optima may be expected for equivalent systems in different species where both possess ergodic evolutionary dynamics. When the fitness maximum is set by physical, rather than co-evolved, constraints, it is additionally possible to make predictions of some properties of the evolved structures and systems. We propose four structures that emerge from evolution within genotypes whose fitness is induced from their phenotypes. Together, these result in an exponential speeding up of evolution, when compared with complete exploration of genomic space. We illustrate a possible case of application and a prediction of convergence together with attaining a physical fitness optimum in the case of invertebrate compound eye resolution. PMID:26640648

Are there ergodic limits to evolution? Ergodic exploration of genome space and convergence.

PubMed

McLeish, Tom C B

2015-12-06

We examine the analogy between evolutionary dynamics and statistical mechanics to include the fundamental question of ergodicity-the representative exploration of the space of possible states (in the case of evolution this is genome space). Several properties of evolutionary dynamics are identified that allow a generalization of the ergodic dynamics, familiar in dynamical systems theory, to evolution. Two classes of evolved biological structure then arise, differentiated by the qualitative duration of their evolutionary time scales. The first class has an ergodicity time scale (the time required for representative genome exploration) longer than available evolutionary time, and has incompletely explored the genotypic and phenotypic space of its possibilities. This case generates no expectation of convergence to an optimal phenotype or possibility of its prediction. The second, more interesting, class exhibits an evolutionary form of ergodicity-essentially all of the structural space within the constraints of slower evolutionary variables have been sampled; the ergodicity time scale for the system evolution is less than the evolutionary time. In this case, some convergence towards similar optima may be expected for equivalent systems in different species where both possess ergodic evolutionary dynamics. When the fitness maximum is set by physical, rather than co-evolved, constraints, it is additionally possible to make predictions of some properties of the evolved structures and systems. We propose four structures that emerge from evolution within genotypes whose fitness is induced from their phenotypes. Together, these result in an exponential speeding up of evolution, when compared with complete exploration of genomic space. We illustrate a possible case of application and a prediction of convergence together with attaining a physical fitness optimum in the case of invertebrate compound eye resolution.

Information Dynamics and Aspects of Musical Perception

NASA Astrophysics Data System (ADS)

Dubnov, Shlomo

Musical experience has been often suggested to be related to forming of expectations, their fulfillment or denial. In terms of information theory, expectancies and predictions serve to reduce uncertainty about the future and might be used to efficiently represent and "compress" data. In this chapter we present an information theoretic model of musical listening based on the idea that expectations that arise from past musical material are framing our appraisal of what comes next, and that this process eventually results in creation of emotions or feelings. Using a notion of "information rate" we can measure the amount of information between past and present in the musical signal on different time scales using statistics of sound spectral features. Several musical pieces are analyzed in terms of short and long term information rate dynamics and are compared to analysis of musical form and its structural functions. The findings suggest that a relation exists between information dynamics and musical structure that eventually leads to creation of human listening experience and feelings such as "wow" and "aha".

The fractional dynamics of quantum systems

NASA Astrophysics Data System (ADS)

Lu, Longzhao; Yu, Xiangyang

2018-05-01

The fractional dynamic process of a quantum system is a novel and complicated problem. The establishment of a fractional dynamic model is a significant attempt that is expected to reveal the mechanism of fractional quantum system. In this paper, a generalized time fractional Schrödinger equation is proposed. To study the fractional dynamics of quantum systems, we take the two-level system as an example and derive the time fractional equations of motion. The basic properties of the system are investigated by solving this set of equations in the absence of light field analytically. Then, when the system is subject to the light field, the equations are solved numerically. It shows that the two-level system described by the time fractional Schrödinger equation we proposed is a confirmable system.

Nonlinear spatio-temporal filtering of dynamic PET data using a four-dimensional Gaussian filter and expectation-maximization deconvolution

NASA Astrophysics Data System (ADS)

Floberg, J. M.; Holden, J. E.

2013-02-01

We introduce a method for denoising dynamic PET data, spatio-temporal expectation-maximization (STEM) filtering, that combines four-dimensional Gaussian filtering with EM deconvolution. The initial Gaussian filter suppresses noise at a broad range of spatial and temporal frequencies and EM deconvolution quickly restores the frequencies most important to the signal. We aim to demonstrate that STEM filtering can improve variance in both individual time frames and in parametric images without introducing significant bias. We evaluate STEM filtering with a dynamic phantom study, and with simulated and human dynamic PET studies of a tracer with reversible binding behaviour, [C-11]raclopride, and a tracer with irreversible binding behaviour, [F-18]FDOPA. STEM filtering is compared to a number of established three and four-dimensional denoising methods. STEM filtering provides substantial improvements in variance in both individual time frames and in parametric images generated with a number of kinetic analysis techniques while introducing little bias. STEM filtering does bias early frames, but this does not affect quantitative parameter estimates. STEM filtering is shown to be superior to the other simple denoising methods studied. STEM filtering is a simple and effective denoising method that could be valuable for a wide range of dynamic PET applications.

Expected Utility Distributions for Flexible, Contingent Execution

NASA Technical Reports Server (NTRS)

Bresina, John L.; Washington, Richard

2000-01-01

This paper presents a method for using expected utility distributions in the execution of flexible, contingent plans. A utility distribution maps the possible start times of an action to the expected utility of the plan suffix starting with that action. The contingent plan encodes a tree of possible courses of action and includes flexible temporal constraints and resource constraints. When execution reaches a branch point, the eligible option with the highest expected utility at that point in time is selected. The utility distributions make this selection sensitive to the runtime context, yet still efficient. Our approach uses predictions of action duration uncertainty as well as expectations of resource usage and availability to determine when an action can execute and with what probability. Execution windows and probabilities inevitably change as execution proceeds, but such changes do not invalidate the cached utility distributions, thus, dynamic updating of utility information is minimized.

Heisenberg operator approach for spin squeezing dynamics

NASA Astrophysics Data System (ADS)

Bhattacherjee, Aranya Bhuti; Sharma, Deepti; Pelster, Axel

2017-12-01

We reconsider the one-axis twisting Hamiltonian, which is commonly used for generating spin squeezing, and treat its dynamics within the Heisenberg operator approach. To this end we solve the underlying Heisenberg equations of motion perturbatively and evaluate the expectation values of the resulting time-dependent Heisenberg operators in order to determine approximately the dynamics of spin squeezing. Comparing our results with those originating from exact numerics reveals that they are more accurate than the commonly used frozen spin approximation.

Gigahertz dynamics of a strongly driven single quantum spin.

PubMed

Fuchs, G D; Dobrovitski, V V; Toyli, D M; Heremans, F J; Awschalom, D D

2009-12-11

Two-level systems are at the core of numerous real-world technologies such as magnetic resonance imaging and atomic clocks. Coherent control of the state is achieved with an oscillating field that drives dynamics at a rate determined by its amplitude. As the strength of the field is increased, a different regime emerges where linear scaling of the manipulation rate breaks down and complex dynamics are expected. By calibrating the spin rotation with an adiabatic passage, we have measured the room-temperature "strong-driving" dynamics of a single nitrogen vacancy center in diamond. With an adiabatic passage to calibrate the spin rotation, we observed dynamics on sub-nanosecond time scales. Contrary to conventional thinking, this breakdown of the rotating wave approximation provides opportunities for time-optimal quantum control of a single spin.

Dynamic programming for optimization of timber production and grazing in ponderosa pine

Treesearch

Kurt H. Riitters; J. Douglas Brodie; David W. Hann

1982-01-01

Dynamic programming procedures are presented for optimizing thinning and rotation of even-aged ponderosa pine by using the four descriptors: age, basal area, number of trees, and time since thinning. Because both timber yield and grazing yield are functions of stand density, the two outputs-forage and timber-can both be optimized. The soil expectation values for single...

Applicability of transfer tensor method for open quantum system dynamics.

PubMed

Gelzinis, Andrius; Rybakovas, Edvardas; Valkunas, Leonas

2017-12-21

Accurate simulations of open quantum system dynamics is a long standing issue in the field of chemical physics. Exact methods exist, but are costly, while perturbative methods are limited in their applicability. Recently a new black-box type method, called transfer tensor method (TTM), was proposed [J. Cerrillo and J. Cao, Phys. Rev. Lett. 112, 110401 (2014)]. It allows one to accurately simulate long time dynamics with a numerical cost of solving a time-convolution master equation, provided many initial system evolution trajectories are obtained from some exact method beforehand. The possible time-savings thus strongly depend on the ratio of total versus initial evolution lengths. In this work, we investigate the parameter regimes where an application of TTM would be most beneficial in terms of computational time. We identify several promising parameter regimes. Although some of them correspond to cases when perturbative theories could be expected to perform well, we find that the accuracy of such approaches depends on system parameters in a more complex way than it is commonly thought. We propose that the TTM should be applied whenever system evolution is expected to be long and accuracy of perturbative methods cannot be ensured or in cases when the system under consideration does not correspond to any single perturbative regime.

Super-Hubble de Sitter fluctuations and the dynamical RG

NASA Astrophysics Data System (ADS)

Burgess, C. P.; Leblond, L.; Holman, R.; Shandera, S.

2010-03-01

Perturbative corrections to correlation functions for interacting theories in de Sitter spacetime often grow secularly with time, due to the properties of fluctuations on super-Hubble scales. This growth can lead to a breakdown of perturbation theory at late times. We argue that Dynamical Renormalization Group (DRG) techniques provide a convenient framework for interpreting and resumming these secularly growing terms. In the case of a massless scalar field in de Sitter with quartic self-interaction, the resummed result is also less singular in the infrared, in precisely the manner expected if a dynamical mass is generated. We compare this improved infrared behavior with large-N expansions when applicable.

Delayed system response times affect immediate physiology and the dynamics of subsequent button press behavior.

PubMed

Kohrs, Christin; Hrabal, David; Angenstein, Nicole; Brechmann, André

2014-11-01

System response time research is an important issue in human-computer interactions. Experience with technical devices and general rules of human-human interactions determine the user's expectation, and any delay in system response time may lead to immediate physiological, emotional, and behavioral consequences. We investigated such effects on a trial-by-trial basis during a human-computer interaction by measuring changes in skin conductance (SC), heart rate (HR), and the dynamics of button press responses. We found an increase in SC and a deceleration of HR for all three delayed system response times (0.5, 1, 2 s). Moreover, the data on button press dynamics was highly informative since subjects repeated a button press with more force in response to delayed system response times. Furthermore, the button press dynamics could distinguish between correct and incorrect decisions and may thus even be used to infer the uncertainty of a user's decision. Copyright © 2014 Society for Psychophysiological Research.

The Dynamics of Crime and Punishment

NASA Astrophysics Data System (ADS)

Hausken, Kjell; Moxnes, John F.

This article analyzes crime development which is one of the largest threats in today's world, frequently referred to as the war on crime. The criminal commits crimes in his free time (when not in jail) according to a non-stationary Poisson process which accounts for fluctuations. Expected values and variances for crime development are determined. The deterrent effect of imprisonment follows from the amount of time in imprisonment. Each criminal maximizes expected utility defined as expected benefit (from crime) minus expected cost (imprisonment). A first-order differential equation of the criminal's utility-maximizing response to the given punishment policy is then developed. The analysis shows that if imprisonment is absent, criminal activity grows substantially. All else being equal, any equilibrium is unstable (labile), implying growth of criminal activity, unless imprisonment increases sufficiently as a function of criminal activity. This dynamic approach or perspective is quite interesting and has to our knowledge not been presented earlier. The empirical data material for crime intensity and imprisonment for Norway, England and Wales, and the US supports the model. Future crime development is shown to depend strongly on the societally chosen imprisonment policy. The model is intended as a valuable tool for policy makers who can envision arbitrarily sophisticated imprisonment functions and foresee the impact they have on crime development.

Does the continuum theory of dynamic fracture work?

NASA Astrophysics Data System (ADS)

Kessler, David A.; Levine, Herbert

2003-09-01

We investigate the validity of the linear elastic fracture mechanics approach to dynamic fracture. We first test the predictions in a lattice simulation, using a formula of Eshelby for the time-dependent stress intensity factor. Excellent agreement with the theory is found. We then use the same method to analyze the experiment of Sharon and Fineberg. The data here are not consistent with the theoretical expectation.

Dynamical Constraints on Non-Transiting Planets at Trappist-1

NASA Astrophysics Data System (ADS)

Jontof-Hutter, Daniel; Truong, Vinh; Ford, Eric; Robertson, Paul; Terrien, Ryan

2018-04-01

The outermost of the seven known planets of Trappist-1 orbits six times closer to its host star than Mercury orbits the sun. The architecture of this system beyond 0.07 AU remains unknown. While the presence of additional planets will ultimately be determined by observations, in the meantime, some constraints can be derived from dynamical models.We will firstly look at the expected signature of additional planets at Trappist-1 on the transit times of the known planets to determine at what distances putatuve planets can be ruled out.Secondly, the remarkably compact configuration of Trappist-1 ensures that the known planets are secularly coupled, keeping their mutual inclinations very small and making their cotransiting geometry likely if Trappist-1h transits. We determine the range of masses and orbital inclinations of a putatuve outer planet that would make the observed configuration unlikely, and compare these to these constraints to those expected from radial velocity observations.

Anomaly-Induced Dynamical Refringence in Strong-Field QED

NASA Astrophysics Data System (ADS)

Mueller, N.; Hebenstreit, F.; Berges, J.

2016-08-01

We investigate the impact of the Adler-Bell-Jackiw anomaly on the nonequilibrium evolution of strong-field quantum electrodynamics (QED) using real-time lattice gauge theory techniques. For field strengths exceeding the Schwinger limit for pair production, we encounter a highly absorptive medium with anomaly induced dynamical refractive properties. In contrast to earlier expectations based on equilibrium properties, where net anomalous effects vanish because of the trivial vacuum structure, we find that out-of-equilibrium conditions can have dramatic consequences for the presence of quantum currents with distinctive macroscopic signatures. We observe an intriguing tracking behavior, where the system spends longest times near collinear field configurations with maximum anomalous current. Apart from the potential relevance of our findings for future laser experiments, similar phenomena related to the chiral magnetic effect are expected to play an important role for strong QED fields during initial stages of heavy-ion collision experiments.

Age Identity in Context: Stress and the Subjective Side of Aging

ERIC Educational Resources Information Center

Schafer, Markus H.; Shippee, Tetyana Pylypiv

2010-01-01

The passage of time is fundamentally experienced through people's interaction with their social worlds. Life-course scholars acknowledge the multiple aspects of time-based experience but have given little attention to age identity in a dynamic context. Drawing from a stress-process model, we expected that turbulence within people's family…

Ecological history vs. social expectations: managing aquatic ecosystems.

Treesearch

Gordon H. Reeves; Sally L. Duncan

2009-01-01

The emerging perspective of ecosystems as both non-equilibrium and dynamic fits aquatic ecosystems as well as terrestrial systems. It is increasingly recognized that watersheds historically passed through different conditions over time. Habitat conditions varied in quantity and quality, primarily as a function of the time since the last major disturbance and the legacy...

Dynamic and accretive composition of patient engagement instruments for personalized plan generation.

PubMed

Hsueh, Pei-Yun S; Zhu, Xinxin; Deng, Vincent; Ramarishnan, Sreeram; Ball, Marion

2014-01-01

Patient engagement is important to help patients become more informed and active in managing their health. Effective patient engagement demands short, yet valid instruments for measuring self-efficacy in various care dimensions. However, the static instruments are often too lengthy to be effective for assessment purposes. Furthermore, these tests could neither account for the dynamicity of measurements over time, nor differentiate care dimensions that are more critical to certain sub-populations. To remedy these disadvantages, we devise a dynamic instrument composition approach that can model the measurement of patient self-efficacy over time and iteratively select critical care dimensions and appropriate assessment questions based on dynamic user categorization. The dynamically composed instruments are expected to guide patients through self-management reinforcement cycles within or across care dimensions, while tightly integrated into clinical workflow and standard care processes.

Generalized Green's function molecular dynamics for canonical ensemble simulations

NASA Astrophysics Data System (ADS)

Coluci, V. R.; Dantas, S. O.; Tewary, V. K.

2018-05-01

The need of small integration time steps (˜1 fs) in conventional molecular dynamics simulations is an important issue that inhibits the study of physical, chemical, and biological systems in real timescales. Additionally, to simulate those systems in contact with a thermal bath, thermostating techniques are usually applied. In this work, we generalize the Green's function molecular dynamics technique to allow simulations within the canonical ensemble. By applying this technique to one-dimensional systems, we were able to correctly describe important thermodynamic properties such as the temperature fluctuations, the temperature distribution, and the velocity autocorrelation function. We show that the proposed technique also allows the use of time steps one order of magnitude larger than those typically used in conventional molecular dynamics simulations. We expect that this technique can be used in long-timescale molecular dynamics simulations.

Free energy surface of an intrinsically disordered protein: comparison between temperature replica exchange molecular dynamics and bias-exchange metadynamics.

PubMed

Zerze, Gül H; Miller, Cayla M; Granata, Daniele; Mittal, Jeetain

2015-06-09

Intrinsically disordered proteins (IDPs), which are expected to be largely unstructured under physiological conditions, make up a large fraction of eukaryotic proteins. Molecular dynamics simulations have been utilized to probe structural characteristics of these proteins, which are not always easily accessible to experiments. However, exploration of the conformational space by brute force molecular dynamics simulations is often limited by short time scales. Present literature provides a number of enhanced sampling methods to explore protein conformational space in molecular simulations more efficiently. In this work, we present a comparison of two enhanced sampling methods: temperature replica exchange molecular dynamics and bias exchange metadynamics. By investigating both the free energy landscape as a function of pertinent order parameters and the per-residue secondary structures of an IDP, namely, human islet amyloid polypeptide, we found that the two methods yield similar results as expected. We also highlight the practical difference between the two methods by describing the path that we followed to obtain both sets of data.

Dynamic Object Representations in Infants with and without Fragile X Syndrome

PubMed Central

Farzin, Faraz; Rivera, Susan M.

2009-01-01

Our visual world is dynamic in nature. The ability to encode, mentally represent, and track an object's identity as it moves across time and space is critical for integrating and maintaining a complete and coherent view of the world. Here we investigated dynamic object processing in typically developing (TD) infants and infants with fragile X syndrome (FXS), a single-gene disorder associated with deficits in dorsal stream functioning. We used the violation of expectation method to assess infants’ visual response to expected versus unexpected outcomes following a brief dynamic (dorsal stream) or static (ventral stream) occlusion event. Consistent with previous reports of deficits in dorsal stream-mediated functioning in individuals with this disorder, these results reveal that, compared to mental age-matched TD infants, infants with FXS could maintain the identity of static, but not dynamic, object information during occlusion. These findings are the first to experimentally evaluate visual object processing skills in infants with FXS, and further support the hypothesis of dorsal stream difficulties in infants with this developmental disorder. PMID:20224809

Effects of Regularisation Priors and Anatomical Partial Volume Correction on Dynamic PET Data

NASA Astrophysics Data System (ADS)

Caldeira, Liliana L.; Silva, Nuno da; Scheins, Jürgen J.; Gaens, Michaela E.; Shah, N. Jon

2015-08-01

Dynamic PET provides temporal information about the tracer uptake. However, each PET frame has usually low statistics, resulting in noisy images. Furthermore, PET images suffer from partial volume effects. The goal of this study is to understand the effects of prior regularisation on dynamic PET data and subsequent anatomical partial volume correction. The Median Root Prior (MRP) regularisation method was used in this work during reconstruction. The quantification and noise in image-domain and time-domain (time-activity curves) as well as the impact on parametric images is assessed and compared with Ordinary Poisson Ordered Subset Expectation Maximisation (OP-OSEM) reconstruction with and without Gaussian filter. This study shows the improvement in PET images and time-activity curves (TAC) in terms of noise as well as in the parametric images when using prior regularisation in dynamic PET data. Anatomical partial volume correction improves the TAC and consequently, parametric images. Therefore, the use of MRP with anatomical partial volume correction is of interest for dynamic PET studies.

Great Expectations: How Role Expectations and Role Experiences Relate to Perceptions of Group Cohesion.

PubMed

Benson, Alex J; Eys, Mark A; Irving, P Gregory

2016-04-01

Many athletes experience a discrepancy between the roles they expect to fulfill and the roles they eventually occupy. Drawing from met expectations theory, we applied response surface methodology to examine how role expectations, in relation to role experiences, influence perceptions of group cohesion among Canadian Interuniversity Sport athletes (N = 153). On the basis of data from two time points, as athletes approached and exceeded their role contribution expectations, they reported higher perceptions of task cohesion. Furthermore, as athletes approached and exceeded their social involvement expectations, they reported higher perceptions of social cohesion. These response surface patterns-pertaining to task and social cohesion-were driven by the positive influence of role experiences. On the basis of the interplay between athletes' role experiences and their perception of the group environment, efforts to improve team dynamics may benefit from focusing on improving the quality of role experiences, in conjunction with developing realistic role expectations.

Aging and coarsening in isolated quantum systems after a quench: Exact results for the quantum O(N) model with N → ∞.

PubMed

Maraga, Anna; Chiocchetta, Alessio; Mitra, Aditi; Gambassi, Andrea

2015-10-01

The nonequilibrium dynamics of an isolated quantum system after a sudden quench to a dynamical critical point is expected to be characterized by scaling and universal exponents due to the absence of time scales. We explore these features for a quench of the parameters of a Hamiltonian with O(N) symmetry, starting from a ground state in the disordered phase. In the limit of infinite N, the exponents and scaling forms of the relevant two-time correlation functions can be calculated exactly. Our analytical predictions are confirmed by the numerical solution of the corresponding equations. Moreover, we find that the same scaling functions, yet with different exponents, also describe the coarsening dynamics for quenches below the dynamical critical point.

Induced fission of Pu 240 within a real-time microscopic framework

DOE PAGES

Bulgac, Aurel; Magierski, Piotr; Roche, Kenneth J.; ...

2016-03-25

Here, we describe the fissioning dynamics of 240Pu from a configuration in the proximity of the outer fission barrier to full scission and the formation of the fragments within an implementation of density functional theory extended to superfluid systems and real-time dynamics. The fission fragments emerge with properties similar to those determined experimentally, while the fission dynamics appears to be quite complex, with many excited shape and pairing modes. The evolution is found to be much slower than previously expected, and the ultimate role of the collective inertia is found to be negligible in this fully nonadiabatic treatment of nuclearmore » dynamics, where all collective degrees of freedom (CDOF) are included (unlike adiabatic treatments with a small number of CDOF).« less

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

Rivera-Durón, R. R., E-mail: roberto.rivera@ipicyt.edu.mx; Campos-Cantón, E., E-mail: eric.campos@ipicyt.edu.mx; Campos-Cantón, I.

We present the design of an autonomous time-delay Boolean network realized with readily available electronic components. Through simulations and experiments that account for the detailed nonlinear response of each circuit element, we demonstrate that a network with five Boolean nodes displays complex behavior. Furthermore, we show that the dynamics of two identical networks display near-instantaneous synchronization to a periodic state when forced by a common periodic Boolean signal. A theoretical analysis of the network reveals the conditions under which complex behavior is expected in an individual network and the occurrence of synchronization in the forced networks. This research will enablemore » future experiments on autonomous time-delay networks using readily available electronic components with dynamics on a slow enough time-scale so that inexpensive data collection systems can faithfully record the dynamics.« less

Matching-pursuit/split-operator-Fourier-transform computations of thermal correlation functions.

PubMed

Chen, Xin; Wu, Yinghua; Batista, Victor S

2005-02-08

A rigorous and practical methodology for evaluating thermal-equilibrium density matrices, finite-temperature time-dependent expectation values, and time-correlation functions is described. The method involves an extension of the matching-pursuit/split-operator-Fourier-transform method to the solution of the Bloch equation via imaginary-time propagation of the density matrix and the evaluation of Heisenberg time-evolution operators through real-time propagation in dynamically adaptive coherent-state representations.

Extended Lagrangian Excited State Molecular Dynamics

DOE PAGES

Bjorgaard, Josiah August; Sheppard, Daniel Glen; Tretiak, Sergei; ...

2018-01-09

In this work, an extended Lagrangian framework for excited state molecular dynamics (XL-ESMD) using time-dependent self-consistent field theory is proposed. The formulation is a generalization of the extended Lagrangian formulations for ground state Born–Oppenheimer molecular dynamics [Phys. Rev. Lett. 2008 100, 123004]. The theory is implemented, demonstrated, and evaluated using a time-dependent semiempirical model, though it should be generally applicable to ab initio theory. The simulations show enhanced energy stability and a significantly reduced computational cost associated with the iterative solutions of both the ground state and the electronically excited states. Relaxed convergence criteria can therefore be used both formore » the self-consistent ground state optimization and for the iterative subspace diagonalization of the random phase approximation matrix used to calculate the excited state transitions. In conclusion, the XL-ESMD approach is expected to enable numerically efficient excited state molecular dynamics for such methods as time-dependent Hartree–Fock (TD-HF), Configuration Interactions Singles (CIS), and time-dependent density functional theory (TD-DFT).« less

Extended Lagrangian Excited State Molecular Dynamics

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

Bjorgaard, Josiah August; Sheppard, Daniel Glen; Tretiak, Sergei

In this work, an extended Lagrangian framework for excited state molecular dynamics (XL-ESMD) using time-dependent self-consistent field theory is proposed. The formulation is a generalization of the extended Lagrangian formulations for ground state Born–Oppenheimer molecular dynamics [Phys. Rev. Lett. 2008 100, 123004]. The theory is implemented, demonstrated, and evaluated using a time-dependent semiempirical model, though it should be generally applicable to ab initio theory. The simulations show enhanced energy stability and a significantly reduced computational cost associated with the iterative solutions of both the ground state and the electronically excited states. Relaxed convergence criteria can therefore be used both formore » the self-consistent ground state optimization and for the iterative subspace diagonalization of the random phase approximation matrix used to calculate the excited state transitions. In conclusion, the XL-ESMD approach is expected to enable numerically efficient excited state molecular dynamics for such methods as time-dependent Hartree–Fock (TD-HF), Configuration Interactions Singles (CIS), and time-dependent density functional theory (TD-DFT).« less

Extended Lagrangian Excited State Molecular Dynamics.

PubMed

Bjorgaard, J A; Sheppard, D; Tretiak, S; Niklasson, A M N

2018-02-13

An extended Lagrangian framework for excited state molecular dynamics (XL-ESMD) using time-dependent self-consistent field theory is proposed. The formulation is a generalization of the extended Lagrangian formulations for ground state Born-Oppenheimer molecular dynamics [Phys. Rev. Lett. 2008 100, 123004]. The theory is implemented, demonstrated, and evaluated using a time-dependent semiempirical model, though it should be generally applicable to ab initio theory. The simulations show enhanced energy stability and a significantly reduced computational cost associated with the iterative solutions of both the ground state and the electronically excited states. Relaxed convergence criteria can therefore be used both for the self-consistent ground state optimization and for the iterative subspace diagonalization of the random phase approximation matrix used to calculate the excited state transitions. The XL-ESMD approach is expected to enable numerically efficient excited state molecular dynamics for such methods as time-dependent Hartree-Fock (TD-HF), Configuration Interactions Singles (CIS), and time-dependent density functional theory (TD-DFT).

Thin film strain gage development program

NASA Technical Reports Server (NTRS)

Grant, H. P.; Przybyszewski, J. S.; Anderson, W. L.; Claing, R. G.

1983-01-01

Sputtered thin-film dynamic strain gages of 2 millimeter (0.08 in) gage length and 10 micrometer (0.0004 in) thickness were fabricated on turbojet engine blades and tested in a simulated compressor environment. Four designs were developed, two for service to 600 K (600 F) and two for service to 900 K (1200 F). The program included a detailed study of guidelines for formulating strain-gage alloys to achieve superior dynamic and static gage performance. The tests included gage factor, fatigue, temperature cycling, spin to 100,000 G, and erosion. Since the installations are 30 times thinner than conventional wire strain gage installations, and any alteration of the aerodynamic, thermal, or structural performance of the blade is correspondingly reduced, dynamic strain measurement accuracy higher than that attained with conventional gages is expected. The low profile and good adherence of the thin film elements is expected to result in improved durability over conventional gage elements in engine tests.

Couplings between hierarchical conformational dynamics from multi-time correlation functions and two-dimensional lifetime spectra: Application to adenylate kinase

NASA Astrophysics Data System (ADS)

Ono, Junichi; Takada, Shoji; Saito, Shinji

2015-06-01

An analytical method based on a three-time correlation function and the corresponding two-dimensional (2D) lifetime spectrum is developed to elucidate the time-dependent couplings between the multi-timescale (i.e., hierarchical) conformational dynamics in heterogeneous systems such as proteins. In analogy with 2D NMR, IR, electronic, and fluorescence spectroscopies, the waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra can provide a quantitative description of the dynamical correlations between the conformational motions with different lifetimes. The present method is applied to intrinsic conformational changes of substrate-free adenylate kinase (AKE) using long-time coarse-grained molecular dynamics simulations. It is found that the hierarchical conformational dynamics arise from the intra-domain structural transitions among conformational substates of AKE by analyzing the one-time correlation functions and one-dimensional lifetime spectra for the donor-acceptor distances corresponding to single-molecule Förster resonance energy transfer experiments with the use of the principal component analysis. In addition, the complicated waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra for the donor-acceptor distances is attributed to the fact that the time evolution of the couplings between the conformational dynamics depends upon both the spatial and temporal characters of the system. The present method is expected to shed light on the biological relationship among the structure, dynamics, and function.

Couplings between hierarchical conformational dynamics from multi-time correlation functions and two-dimensional lifetime spectra: Application to adenylate kinase

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

Ono, Junichi; Takada, Shoji; Department of Biophysics, Graduate School of Science, Kyoto University, Kyoto 606-8502

2015-06-07

An analytical method based on a three-time correlation function and the corresponding two-dimensional (2D) lifetime spectrum is developed to elucidate the time-dependent couplings between the multi-timescale (i.e., hierarchical) conformational dynamics in heterogeneous systems such as proteins. In analogy with 2D NMR, IR, electronic, and fluorescence spectroscopies, the waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra can provide a quantitative description of the dynamical correlations between the conformational motions with different lifetimes. The present method is applied to intrinsic conformational changes of substrate-free adenylate kinase (AKE) using long-time coarse-grained molecular dynamics simulations. It is found that the hierarchicalmore » conformational dynamics arise from the intra-domain structural transitions among conformational substates of AKE by analyzing the one-time correlation functions and one-dimensional lifetime spectra for the donor-acceptor distances corresponding to single-molecule Förster resonance energy transfer experiments with the use of the principal component analysis. In addition, the complicated waiting-time dependence of the off-diagonal peaks in the 2D lifetime spectra for the donor-acceptor distances is attributed to the fact that the time evolution of the couplings between the conformational dynamics depends upon both the spatial and temporal characters of the system. The present method is expected to shed light on the biological relationship among the structure, dynamics, and function.« less

Nonperturbative Treatment of non-Markovian Dynamics of Open Quantum Systems

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Dynamical pairwise entanglement and two-point correlations in the three-ligand spin-star structure

NASA Astrophysics Data System (ADS)

Motamedifar, M.

2017-10-01

We consider the three-ligand spin-star structure through homogeneous Heisenberg interactions (XXX-3LSSS) in the framework of dynamical pairwise entanglement. It is shown that the time evolution of the central qubit ;one-particle; state (COPS) brings about the generation of quantum W states at periodical time instants. On the contrary, W states cannot be generated from the time evolution of a ligand ;one-particle; state (LOPS). We also investigate the dynamical behavior of two-point quantum correlations as well as the expectation values of the different spin-components for each element in the XXX-3LSSS. It is found that when a W state is generated, the same value of the concurrence between any two arbitrary qubits arises from the xx and yy two-point quantum correlations. On the opposite, zz quantum correlation between any two qubits vanishes at these time instants.

Linking melodic expectation to expressive performance timing and perceived musical tension.

PubMed

Gingras, Bruno; Pearce, Marcus T; Goodchild, Meghan; Dean, Roger T; Wiggins, Geraint; McAdams, Stephen

2016-04-01

This research explored the relations between the predictability of musical structure, expressive timing in performance, and listeners' perceived musical tension. Studies analyzing the influence of expressive timing on listeners' affective responses have been constrained by the fact that, in most pieces, the notated durations limit performers' interpretive freedom. To circumvent this issue, we focused on the unmeasured prelude, a semi-improvisatory genre without notated durations. In Experiment 1, 12 professional harpsichordists recorded an unmeasured prelude on a harpsichord equipped with a MIDI console. Melodic expectation was assessed using a probabilistic model (IDyOM [Information Dynamics of Music]) whose expectations have been previously shown to match closely those of human listeners. Performance timing information was extracted from the MIDI data using a score-performance matching algorithm. Time-series analyses showed that, in a piece with unspecified note durations, the predictability of melodic structure measurably influenced tempo fluctuations in performance. In Experiment 2, another 10 harpsichordists, 20 nonharpsichordist musicians, and 20 nonmusicians listened to the recordings from Experiment 1 and rated the perceived tension continuously. Granger causality analyses were conducted to investigate predictive relations among melodic expectation, expressive timing, and perceived tension. Although melodic expectation, as modeled by IDyOM, modestly predicted perceived tension for all participant groups, neither of its components, information content or entropy, was Granger causal. In contrast, expressive timing was a strong predictor and was Granger causal. However, because melodic expectation was also predictive of expressive timing, our results outline a complete chain of influence from predictability of melodic structure via expressive performance timing to perceived musical tension. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Detection of time delays and directional interactions based on time series from complex dynamical systems

NASA Astrophysics Data System (ADS)

Ma, Huanfei; Leng, Siyang; Tao, Chenyang; Ying, Xiong; Kurths, Jürgen; Lai, Ying-Cheng; Lin, Wei

2017-07-01

Data-based and model-free accurate identification of intrinsic time delays and directional interactions is an extremely challenging problem in complex dynamical systems and their networks reconstruction. A model-free method with new scores is proposed to be generally capable of detecting single, multiple, and distributed time delays. The method is applicable not only to mutually interacting dynamical variables but also to self-interacting variables in a time-delayed feedback loop. Validation of the method is carried out using physical, biological, and ecological models and real data sets. Especially, applying the method to air pollution data and hospital admission records of cardiovascular diseases in Hong Kong reveals the major air pollutants as a cause of the diseases and, more importantly, it uncovers a hidden time delay (about 30-40 days) in the causal influence that previous studies failed to detect. The proposed method is expected to be universally applicable to ascertaining and quantifying subtle interactions (e.g., causation) in complex systems arising from a broad range of disciplines.

Dependent Lifelengths Induced by Dynamic Environments

DTIC Science & Technology

1988-02-14

item has not failed at any time r, our assessment of the failure rate will increase since we expect that the dominant failure mechanism is governed ...of a dynamic environment on the system over a finite range [ 0, T’ ) can be captured through a polynomial environental factor function j7(r). We...Vol. 7, pp. 295- 306. Singpurwalla, N.D. (1988). Foundational issues in reliability and risk analysis. SIAM Review. To app.!ar. 85

Examining a scaled dynamical system of telomere shortening

NASA Astrophysics Data System (ADS)

Cyrenne, Benoit M.; Gooding, Robert J.

2015-02-01

A model of telomere dynamics is proposed and examined. Our model, which extends a previously introduced model that incorporates stem cells as progenitors of new cells, imposes the Hayflick limit, the maximum number of cell divisions that are possible. This new model leads to cell populations for which the average telomere length is not necessarily a monotonically decreasing function of time, in contrast to previously published models. We provide a phase diagram indicating where such results would be expected via the introduction of scaled populations, rate constants and time. The application of this model to available leukocyte baboon data is discussed.

Fast and High Dynamic Range Imaging with Superconducting Tunnel Junction Detectors

NASA Astrophysics Data System (ADS)

Matsuo, Hiroshi

2014-08-01

We have demonstrated a combined test of the submillimeter-wave SIS photon detectors and GaAs-JFET cryogenic integrated circuits. A relatively large background photo-current can be read out by fast-reset integrating amplifiers. An integration time of 1 ms enables fast frame rate readout and large dynamic range imaging, with an expected dynamic range of 8,000 in 1 ms. Ultimate fast and high dynamic range performance of superconducting tunnel junction detectors (STJ) will be obtained when photon counting capabilities are employed. In the terahertz frequencies, when input photon rate of 100 MHz is measured, the photon bunching gives us enough timing resolution to be used as phase information of intensity fluctuation. Application of photon statistics will be a new tool in the terahertz frequency region. The design parameters of STJ terahertz photon counting detectors are discussed.

Time delays in flight simulator visual displays

NASA Technical Reports Server (NTRS)

Crane, D. F.

1980-01-01

It is pointed out that the effects of delays of less than 100 msec in visual displays on pilot dynamic response and system performance are of particular interest at this time because improvements in the latest computer-generated imagery (CGI) systems are expected to reduce CGI displays delays to this range. Attention is given to data which quantify the effects of display delays in the range of 0-100 msec on system stability and performance, and pilot dynamic response for a particular choice of aircraft dynamics, display, controller, and task. The conventional control system design methods are reviewed, the pilot response data presented, and data for long delays, all suggest lead filter compensation of display delay. Pilot-aircraft system crossover frequency information guides compensation filter specification.

Dynamics of Lithium Polymer Electrolytes using X-ray Photon Correlation Spectroscopy and Rheology

NASA Astrophysics Data System (ADS)

Oparaji, Onyekachi; Narayanan, Suresh; Sandy, Alec; Hallinan, Daniel, Jr.

Polymer electrolytes are promising materials for high energy density rechargeable batteries. Battery fade can be caused by structural evolution in the battery electrode and loss of electrode/electrolyte adhesion during cycling. Both of these effects are dependent on polymer mechanical properties. In addition, cycling rate is dictated by the ion mobility of the polymer electrolyte. Lithium ion mobility is expected to be strongly coupled to polymer dynamics. Therefore, we investigate polymer dynamics as a function of salt concentration using X-ray Photon Correlation Spectroscopy (XPCS) and rheology. We report the influence of lithium salt concentration on the structural relaxation time (XPCS) and stress relaxation time (rheology) of high molecular weight poly(styrene - ethylene oxide) block copolymer membranes.

Dynamic situation assessment and prediction (DSAP)

NASA Astrophysics Data System (ADS)

Sisti, Alex F.

2003-09-01

The face of war has changed. We no longer have the luxury of planning campaigns against a known enemy operating under a well-understood doctrine, using conventional weapons and rules of engagement; all in a well-charted region. Instead, today's Air Force faces new, unforeseen enemies, asymmetric combat situations and unconventional warfare (Chem/Bio, co-location of military assets near civilian facilities, etc.). At the same time, the emergence of new Air Force doctrinal notions (e.g., Global Strike Task Force, Effects-Based Operations, the desire to minimize or eliminate any collateral damage, etc.)- while propounding the benefits that can be expected with the adoption of such concepts - also impose many new technical and operational challenges. Furthermore, future mission/battle commanders will need to assimilate a tremendous glut of available information, and still be expected to make quick-response decisions - and to quantify the effects of those decisions - all in the face of uncertainty. All these factors translate to the need for dramatic improvements in the way we plan, rehearse, execute and dynamically assess the status of military campaigns. This paper addresses these crucial and revolutionary requirements through the pursuit of a new simulation paradigm that allows a user to perform real-time dynamic situation assessment and prediction.

Bayesian inversion analysis of nonlinear dynamics in surface heterogeneous reactions.

PubMed

Omori, Toshiaki; Kuwatani, Tatsu; Okamoto, Atsushi; Hukushima, Koji

2016-09-01

It is essential to extract nonlinear dynamics from time-series data as an inverse problem in natural sciences. We propose a Bayesian statistical framework for extracting nonlinear dynamics of surface heterogeneous reactions from sparse and noisy observable data. Surface heterogeneous reactions are chemical reactions with conjugation of multiple phases, and they have the intrinsic nonlinearity of their dynamics caused by the effect of surface-area between different phases. We adapt a belief propagation method and an expectation-maximization (EM) algorithm to partial observation problem, in order to simultaneously estimate the time course of hidden variables and the kinetic parameters underlying dynamics. The proposed belief propagation method is performed by using sequential Monte Carlo algorithm in order to estimate nonlinear dynamical system. Using our proposed method, we show that the rate constants of dissolution and precipitation reactions, which are typical examples of surface heterogeneous reactions, as well as the temporal changes of solid reactants and products, were successfully estimated only from the observable temporal changes in the concentration of the dissolved intermediate product.

Optimal foraging in seasonal environments: implications for residency of Australian flying foxes in food-subsidized urban landscapes.

PubMed

Páez, David J; Restif, Olivier; Eby, Peggy; Plowright, Raina K

2018-05-05

Bats provide important ecosystem services such as pollination of native forests; they are also a source of zoonotic pathogens for humans and domestic animals. Human-induced changes to native habitats may have created more opportunities for bats to reside in urban settings, thus decreasing pollination services to native forests and increasing opportunities for zoonotic transmission. In Australia, fruit bats ( Pteropus spp. flying foxes) are increasingly inhabiting urban areas where they feed on anthropogenic food sources with nutritional characteristics and phenology that differ from native habitats. We use optimal foraging theory to investigate the relationship between bat residence time in a patch, the time it takes to search for a new patch (simulating loss of native habitat) and seasonal resource production. We show that it can be beneficial to reside in a patch, even when food productivity is low, as long as foraging intensity is low and the expected searching time is high. A small increase in the expected patch searching time greatly increases the residence time, suggesting nonlinear associations between patch residence and loss of seasonal native resources. We also found that sudden increases in resource consumption due to an influx of new bats has complex effects on patch departure times that again depend on expected searching times and seasonality. Our results suggest that the increased use of urban landscapes by bats may be a response to new spatial and temporal configurations of foraging opportunities. Given that bats are reservoir hosts of zoonotic diseases, our results provide a framework to study the effects of foraging ecology on disease dynamics.One contribution of 14 to a theme isssue 'Anthropogenic resource subsidies and host-parasite dynamics in wildlife'. © 2018 The Author(s).

Optimal rotation sequences for active perception

NASA Astrophysics Data System (ADS)

Nakath, David; Rachuy, Carsten; Clemens, Joachim; Schill, Kerstin

2016-05-01

One major objective of autonomous systems navigating in dynamic environments is gathering information needed for self localization, decision making, and path planning. To account for this, such systems are usually equipped with multiple types of sensors. As these sensors often have a limited field of view and a fixed orientation, the task of active perception breaks down to the problem of calculating alignment sequences which maximize the information gain regarding expected measurements. Action sequences that rotate the system according to the calculated optimal patterns then have to be generated. In this paper we present an approach for calculating these sequences for an autonomous system equipped with multiple sensors. We use a particle filter for multi- sensor fusion and state estimation. The planning task is modeled as a Markov decision process (MDP), where the system decides in each step, what actions to perform next. The optimal control policy, which provides the best action depending on the current estimated state, maximizes the expected cumulative reward. The latter is computed from the expected information gain of all sensors over time using value iteration. The algorithm is applied to a manifold representation of the joint space of rotation and time. We show the performance of the approach in a spacecraft navigation scenario where the information gain is changing over time, caused by the dynamic environment and the continuous movement of the spacecraft

Minimum expected delay-based routing protocol (MEDR) for Delay Tolerant Mobile Sensor Networks.

PubMed

Feng, Yong; Liu, Ming; Wang, Xiaomin; Gong, Haigang

2010-01-01

It is a challenging work to develop efficient routing protocols for Delay Tolerant Mobile Sensor Networks (DTMSNs), which have several unique characteristics such as sensor mobility, intermittent connectivity, energy limit, and delay tolerability. In this paper, we propose a new routing protocol called Minimum Expected Delay-based Routing (MEDR) tailored for DTMSNs. MEDR achieves a good routing performance by finding and using the connected paths formed dynamically by mobile sensors. In MEDR, each sensor maintains two important parameters: Minimum Expected Delay (MED) and its expiration time. According to MED, messages will be delivered to the sensor that has at least a connected path with their hosting nodes, and has the shortest expected delay to communication directly with the sink node. Because of the changing network topology, the path is fragile and volatile, so we use the expiration time of MED to indicate the valid time of the path, and avoid wrong transmissions. Simulation results show that the proposed MEDR achieves a higher message delivery ratio with lower transmission overhead and data delivery delay than other DTMSN routing approaches.

Long-term evolution of a small ice cap in Greenland: a dynamic perspective from numerical flow modelling

NASA Astrophysics Data System (ADS)

Vieli, Andreas; Lane, Timothy; Adamson, Kathryn

2017-04-01

Small ice caps at the periphery of the Greenland ice sheet are often close to the limit of existence and are therefore expected to respond more sensitively to climate change than the land-margin of the neighboring ice sheet. However, their past evolution and dynamic behavior is poorly understood and their use as climate indicators therefore remains so far limited. We here aim to provide a long-term dynamic reconstruction of Lyngmarksbraeen, a small (32km2) ice cap on Disko Island in West Greenland, with a particular focus on the little ice age (LIA, since 1200AD). We use a 2-dim. time-dependent numerical flow model (SIA) and a PDD-mass balance model in combination with historical observations, geomorphological mapping and exposure dating to simulate its long-term evolution and dynamic behaviour. We specifically focus on retreat since the LIA, which is well constrained by geomorphological evidence and historical maps and length records of several small outlet glaciers and data from local and regional climate stations (Qeqertarssuaq and Ilulisat). We also explore aspects related to flow dynamics and find that the dynamic state of this ice cap is, at any time, far from being balanced and is highly sensitive to the surface elevation mass balance feedback and results in an asynchronous response of the different outlets and hysteresis-type behaviour. The modelling is able to reproduce the observed LIA-extent and the almost continuous retreat over the last hundred years well. It further indicates that the ice cap was already dynamically inert since the 1960s. Today, the ice cap has lost almost its entire accumulation area and even without any further warming in the future, the ice cap is expected to vanish within a couple of decades.

Joint Chance-Constrained Dynamic Programming

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J. Bob

2012-01-01

This paper presents a novel dynamic programming algorithm with a joint chance constraint, which explicitly bounds the risk of failure in order to maintain the state within a specified feasible region. A joint chance constraint cannot be handled by existing constrained dynamic programming approaches since their application is limited to constraints in the same form as the cost function, that is, an expectation over a sum of one-stage costs. We overcome this challenge by reformulating the joint chance constraint into a constraint on an expectation over a sum of indicator functions, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the primal variables can be optimized by a standard dynamic programming, while the dual variable is optimized by a root-finding algorithm that converges exponentially. Error bounds on the primal and dual objective values are rigorously derived. We demonstrate the algorithm on a path planning problem, as well as an optimal control problem for Mars entry, descent and landing. The simulations are conducted using a real terrain data of Mars, with four million discrete states at each time step.

Coupled dynamic systems and Le Chatelier's principle in noise control

NASA Astrophysics Data System (ADS)

Maidanik, G.; Becker, K. J.

2004-05-01

Investigation of coupling an externally driven dynamic system-a master dynamic system-to a passive one-an adjunct dynamic system-reveals that the response of the adjunct dynamic system affects the precoupled response of the master dynamic system. The responses, in the two dynamic systems when coupled, are estimated by the stored energies (Es) and (E0), respectively. Since the adjunct dynamic system, prior to coupling, was with zero (0) stored energy, E0s=0, the precoupled stored energy (E00) in the master dynamic system is expected to be reduced to (E0) when coupling is instituted; i.e., one expects E0

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Women's Retirement Expectations: How Stable Are They?

PubMed Central

Hardy, Melissa A.

2009-01-01

Objective Using the National Longitudinal Survey of Mature Women, we examine between- and within-person differences in expected retirement age as a key element of the retirement planning process. The expectation typologies of 1,626 women born between 1923 and 1937 were classified jointly on the basis of specificity and consistency. Methods Latent class analysis was used to determine retirement expectation patterns over a 7-year span. Multinomial logistic regression analyses were employed to estimate the effects of demographic and status characteristics on the likelihood of reporting 4 distinct longitudinal patterns of retirement expectations. Results Substantial heterogeneity in reports of expected retirement age between and within individuals over the 7-year span was found. Demographic and status characteristics, specifically age, race, marital status, job tenure, and recent job change, sorted respondents into different retirement expectation patterns. Conclusions The frequent within-person fluctuations and substantial between-person heterogeneity in retirement expectations indicate uncertainty and variability in both expectations and process of expectation formation. Variability in respondents' reports suggests that studying retirement expectations at multiple time points better captures the dynamics of preretirement planning. PMID:19176483

Dynamic route and departure time choice model based on self-adaptive reference point and reinforcement learning

NASA Astrophysics Data System (ADS)

Li, Xue-yan; Li, Xue-mei; Yang, Lingrun; Li, Jing

2018-07-01

Most of the previous studies on dynamic traffic assignment are based on traditional analytical framework, for instance, the idea of Dynamic User Equilibrium has been widely used in depicting both the route choice and the departure time choice. However, some recent studies have demonstrated that the dynamic traffic flow assignment largely depends on travelers' rationality degree, travelers' heterogeneity and what the traffic information the travelers have. In this paper, we develop a new self-adaptive multi agent model to depict travelers' behavior in Dynamic Traffic Assignment. We use Cumulative Prospect Theory with heterogeneous reference points to illustrate travelers' bounded rationality. We use reinforcement-learning model to depict travelers' route and departure time choosing behavior under the condition of imperfect information. We design the evolution rule of travelers' expected arrival time and the algorithm of traffic flow assignment. Compared with the traditional model, the self-adaptive multi agent model we proposed in this paper can effectively help travelers avoid the rush hour. Finally, we report and analyze the effect of travelers' group behavior on the transportation system, and give some insights into the relation between travelers' group behavior and the performance of transportation system.

Internal models of target motion: expected dynamics overrides measured kinematics in timing manual interceptions.

PubMed

Zago, Myrka; Bosco, Gianfranco; Maffei, Vincenzo; Iosa, Marco; Ivanenko, Yuri P; Lacquaniti, Francesco

2004-04-01

Prevailing views on how we time the interception of a moving object assume that the visual inputs are informationally sufficient to estimate the time-to-contact from the object's kinematics. Here we present evidence in favor of a different view: the brain makes the best estimate about target motion based on measured kinematics and an a priori guess about the causes of motion. According to this theory, a predictive model is used to extrapolate time-to-contact from expected dynamics (kinetics). We projected a virtual target moving vertically downward on a wide screen with different randomized laws of motion. In the first series of experiments, subjects were asked to intercept this target by punching a real ball that fell hidden behind the screen and arrived in synchrony with the visual target. Subjects systematically timed their motor responses consistent with the assumption of gravity effects on an object's mass, even when the visual target did not accelerate. With training, the gravity model was not switched off but adapted to nonaccelerating targets by shifting the time of motor activation. In the second series of experiments, there was no real ball falling behind the screen. Instead the subjects were required to intercept the visual target by clicking a mousebutton. In this case, subjects timed their responses consistent with the assumption of uniform motion in the absence of forces, even when the target actually accelerated. Overall, the results are in accord with the theory that motor responses evoked by visual kinematics are modulated by a prior of the target dynamics. The prior appears surprisingly resistant to modifications based on performance errors.

A conceptual framework for dynamic extension of the red clearance interval as a countermeasure for red-light-running.

PubMed

Gates, Timothy J; Noyce, David A

2016-11-01

This manuscript describes the development and evaluation of a conceptual framework for real-time operation of dynamic on-demand extension of the red clearance interval as a countermeasure for red-light-running. The framework includes a decision process for determining, based on the real-time status of vehicles arriving at the intersection, when extension of the red clearance interval should occur and the duration of each extension. A zonal classification scheme was devised to assess whether an approaching vehicle requires additional time to safely clear the intersection based on the remaining phase time, type of vehicle, current speed, and current distance from the intersection. Expected performance of the conceptual framework was evaluated through modeling of replicated field operations using vehicular event data collected as part of this research. The results showed highly accurate classification of red-light-running vehicles needing additional clearance time and relatively few false extension calls from stopping vehicles, thereby minimizing the expected impacts to signal and traffic operations. Based on the recommended parameters, extension calls were predicted to occur once every 26.5cycles. Assuming a 90scycle, 1.5 extensions per hour were expected per approach, with an estimated extension time of 2.30s/h. Although field implementation was not performed, it is anticipated that long-term reductions in targeted red-light-running conflicts and crashes will likely occur if red clearance interval extension systems are implemented at locations where start-up delay on the conflicting approach is generally minimal, such as intersections with lag left-turn phasing. Copyright © 2015 Elsevier Ltd. All rights reserved.

A dynamical systems perspective on the absence of debris associated with the disappearance of flight MH370

NASA Astrophysics Data System (ADS)

García-Garrido, V. J.; Mancho, A. M.; Wiggins, S.; Mendoza, C.

2015-07-01

The disappearance of Malaysia Airlines flight MH370 on the morning of the 8 March 2014 is one of the great mysteries of our time. Perhaps the most relevant aspect of this mystery is that not a single piece of debris from the aircraft has been found. Difficulties in the search efforts, due to the uncertainty in the plane's final impact point and the time that has passed since the accident, bring the question on how the debris has scattered in an always moving ocean, for which there are multiple data sets that do not uniquely determine its state. Our approach to this problem is based on the use of Lagrangian Descriptors (LD), a novel mathematical tool coming from dynamical systems theory that identifies dynamic barriers and coherent structures governing transport. By combining publicly available information supplied by different ocean data sources with these mathematical techniques, we are able to assess the spatio-temporal state of the ocean in the priority search area at the time of impact and the following weeks. Using this information we propose a revised search strategy by showing why one might not have expected to find debris in some large search areas targeted by the Australian Maritime Safety Authority (AMSA), and determining regions where one might have expected impact debris to be located and that have not been subjected to any exploration.

Stardust Dynamic Science at Wild 2: First Look

NASA Technical Reports Server (NTRS)

Anderson, J. D.; Lau, E. L.; Clark, B. C.; Asmar, S. W.

2004-01-01

The Dynamic Science investigation on the STARDUST mission has been described previously. The data delivered by the STARDUST Project is multifold, but basically it consists of radio Doppler data from the Deep Space Network (DSN) and attitude control data (ACS) from the spacecraft. Doppler data were successfully recorded by JPL's Navigation System (closed-loop data) and also by its Radio Science System (open-loop data) at DSN stations DSS43 near Canberra Australia and at DSS14 at Goldstone California. Attitude control data were also successfully delivered to the Dynamic Science Team. Here we describe a preliminary analysis of the data. Beyond a closest approach distance of 150 km, a Doppler detection of a the Wild 2 nucleus mass was not expected. The current best estimate of the closest approach distance is 236.4 km, and as expected, any mass signal in the Doppler data is hopelessly buried in the noise. We have attempted to fit the data to a mass model with no success. However, analysis of the Doppler data and the ACS data for particle impacts on the spacecraft's Whipple shields is in progress, and will be reported at the meeting. The DSS43 closed-loop Doppler residuals are plotted as a function of time from the current best estimate of the time of Wild 2 closest approach, 2 January 2004, 19:43:11.7 UTC, Earth-receive time at the station.

Dynamics in a one-dimensional ferrogel model: relaxation, pairing, shock-wave propagation.

PubMed

Goh, Segun; Menzel, Andreas M; Löwen, Hartmut

2018-05-23

Ferrogels are smart soft materials, consisting of a polymeric network and embedded magnetic particles. Novel phenomena, such as the variation of the overall mechanical properties by external magnetic fields, emerge consequently. However, the dynamic behavior of ferrogels remains largely unveiled. In this paper, we consider a one-dimensional chain consisting of magnetic dipoles and elastic springs between them as a simple model for ferrogels. The model is evaluated by corresponding simulations. To probe the dynamics theoretically, we investigate a continuum limit of the energy governing the system and the corresponding equation of motion. We provide general classification scenarios for the dynamics, elucidating the touching/detachment dynamics of the magnetic particles along the chain. In particular, it is verified in certain cases that the long-time relaxation corresponds to solutions of shock-wave propagation, while formations of particle pairs underlie the initial stage of the dynamics. We expect that these results will provide insight into the understanding of the dynamics of more realistic models with randomness in parameters and time-dependent magnetic fields.

Load-sensitive dynamic workflow re-orchestration and optimisation for faster patient healthcare.

PubMed

Meli, Christopher L; Khalil, Ibrahim; Tari, Zahir

2014-01-01

Hospital waiting times are considerably long, with no signs of reducing any-time soon. A number of factors including population growth, the ageing population and a lack of new infrastructure are expected to further exacerbate waiting times in the near future. In this work, we show how healthcare services can be modelled as queueing nodes, together with healthcare service workflows, such that these workflows can be optimised during execution in order to reduce patient waiting times. Services such as X-ray, computer tomography, and magnetic resonance imaging often form queues, thus, by taking into account the waiting times of each service, the workflow can be re-orchestrated and optimised. Experimental results indicate average waiting time reductions are achievable by optimising workflows using dynamic re-orchestration. Crown Copyright © 2013. Published by Elsevier Ireland Ltd. All rights reserved.

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.

Dynamic facial expressions of emotion transmit an evolving hierarchy of signals over time.

PubMed

Jack, Rachael E; Garrod, Oliver G B; Schyns, Philippe G

2014-01-20

Designed by biological and social evolutionary pressures, facial expressions of emotion comprise specific facial movements to support a near-optimal system of signaling and decoding. Although highly dynamical, little is known about the form and function of facial expression temporal dynamics. Do facial expressions transmit diagnostic signals simultaneously to optimize categorization of the six classic emotions, or sequentially to support a more complex communication system of successive categorizations over time? Our data support the latter. Using a combination of perceptual expectation modeling, information theory, and Bayesian classifiers, we show that dynamic facial expressions of emotion transmit an evolving hierarchy of "biologically basic to socially specific" information over time. Early in the signaling dynamics, facial expressions systematically transmit few, biologically rooted face signals supporting the categorization of fewer elementary categories (e.g., approach/avoidance). Later transmissions comprise more complex signals that support categorization of a larger number of socially specific categories (i.e., the six classic emotions). Here, we show that dynamic facial expressions of emotion provide a sophisticated signaling system, questioning the widely accepted notion that emotion communication is comprised of six basic (i.e., psychologically irreducible) categories, and instead suggesting four. Copyright © 2014 Elsevier Ltd. All rights reserved.

Real-time observation of the conformational dynamics of mitochondrial Hsp70 by spFRET.

PubMed

Sikor, Martin; Mapa, Koyeli; von Voithenberg, Lena Voith; Mokranjac, Dejana; Lamb, Don C

2013-05-29

The numerous functions of the important class of molecular chaperones, heat shock proteins 70 (Hsp70), rely on cycles of intricate conformational changes driven by ATP-hydrolysis and regulated by cochaperones and substrates. Here, we used Förster resonance energy transfer to study the conformational dynamics of individual molecules of Ssc1, a mitochondrial Hsp70, in real time. The intrinsic dynamics of the substrate-binding domain of Ssc1 was observed to be uncoupled from the dynamic interactions between substrate- and nucleotide-binding domains. Analysis of the fluctuations in the interdomain separation revealed frequent transitions to a nucleotide-free state. The nucleotide-exchange factor Mge1 did not induce ADP release, as expected, but rather facilitated binding of ATP. These results indicate that the conformational cycle of Ssc1 is more elaborate than previously thought and provide insight into how the Hsp70s can perform a wide variety of functions.

Fractional Brownian motion and the critical dynamics of zipping polymers.

PubMed

Walter, J-C; Ferrantini, A; Carlon, E; Vanderzande, C

2012-03-01

We consider two complementary polymer strands of length L attached by a common-end monomer. The two strands bind through complementary monomers and at low temperatures form a double-stranded conformation (zipping), while at high temperature they dissociate (unzipping). This is a simple model of DNA (or RNA) hairpin formation. Here we investigate the dynamics of the strands at the equilibrium critical temperature T=T(c) using Monte Carlo Rouse dynamics. We find that the dynamics is anomalous, with a characteristic time scaling as τ∼L(2.26(2)), exceeding the Rouse time ∼L(2.18). We investigate the probability distribution function, velocity autocorrelation function, survival probability, and boundary behavior of the underlying stochastic process. These quantities scale as expected from a fractional Brownian motion with a Hurst exponent H=0.44(1). We discuss similarities to and differences from unbiased polymer translocation.

Entanglement spreading after a geometric quench in quantum spin chains

NASA Astrophysics Data System (ADS)

Alba, Vincenzo; Heidrich-Meisner, Fabian

2014-08-01

We investigate the entanglement spreading in the anisotropic spin-1/2 Heisenberg (XXZ) chain after a geometric quench. This corresponds to a sudden change of the geometry of the chain or, in the equivalent language of interacting fermions confined in a box trap, to a sudden increase of the trap size. The entanglement dynamics after the quench is associated with the ballistic propagation of a magnetization wave front. At the free fermion point (XX chain), the von Neumann entropy SA exhibits several intriguing dynamical regimes. Specifically, at short times a logarithmic increase is observed, similar to local quenches. This is accurately described by an analytic formula that we derive from heuristic arguments. At intermediate times partial revivals of the short-time dynamics are superposed with a power-law increase SA˜tα, with α <1. Finally, at very long times a steady state develops with constant entanglement entropy, apart from oscillations. As expected, since the model is integrable, we find that the steady state is nonthermal, although it exhibits extensive entanglement entropy. We also investigate the entanglement dynamics after the quench from a finite to the infinite chain (sudden expansion). While at long times the entanglement vanishes, we demonstrate that its relaxation dynamics exhibits a number of scaling properties. Finally, we discuss the short-time entanglement dynamics in the XXZ chain in the gapless phase. The same formula that describes the time dependence for the XX chain remains valid in the whole gapless phase.

Observers Exploit Stochastic Models of Sensory Change to Help Judge the Passage of Time

PubMed Central

Ahrens, Misha B.; Sahani, Maneesh

2011-01-01

Summary Sensory stimulation can systematically bias the perceived passage of time [1–5], but why and how this happens is mysterious. In this report, we provide evidence that such biases may ultimately derive from an innate and adaptive use of stochastically evolving dynamic stimuli to help refine estimates derived from internal timekeeping mechanisms [6–15]. A simplified statistical model based on probabilistic expectations of stimulus change derived from the second-order temporal statistics of the natural environment [16, 17] makes three predictions. First, random noise-like stimuli whose statistics violate natural expectations should induce timing bias. Second, a previously unexplored obverse of this effect is that similar noise stimuli with natural statistics should reduce the variability of timing estimates. Finally, this reduction in variability should scale with the interval being timed, so as to preserve the overall Weber law of interval timing. All three predictions are borne out experimentally. Thus, in the context of our novel theoretical framework, these results suggest that observers routinely rely on sensory input to augment their sense of the passage of time, through a process of Bayesian inference based on expectations of change in the natural environment. PMID:21256018

Diffusion of Small Sticky Nanoparticles in a Polymer Melt: A Dynamic Light Scattering Study

NASA Astrophysics Data System (ADS)

Carroll, Bobby; Bocharova, Vera; Cheng, Shiwang; Yamamoto, Umi; Kisliuk, Alex; Schweizer, Ken; Sokolov, Alexei

The study of dynamics in complex fluids such as polymers has gained a broad interest in advanced materials and biomedical applications. Of particular interest is the motion of nanoparticles in these systems, which influences the mechanical and structural properties of composite materials, properties of colloidal systems, and biochemical processes in biological systems. Theoretical work predicts a violation of Stokes-Einstein (SE) relationship for diffusion of small nanoparticles in strongly-entangled polymer melt systems, with diffusion of nanoparticles much faster than expected DSE. It is attributed to differences between local and macroscopic viscosity. In this study, the diffusion of nanoparticles in polymer melts below and above entanglement molecular weight is measured using dynamic light scattering. The measured results are compared with simulations that provide quantitative predictions for SE violations. Our results are two-fold: (1) diffusion at lower molecular weights is slower than expected DSE due to chain absorption; and (2) diffusion becomes much (20 times) faster than DSE, at higher entanglements due to a reduced local viscosity.

Gauge fields at finite temperatures—"Thermo field dynamics" and the KMS condition and their extension to gauge theories

NASA Astrophysics Data System (ADS)

Ojima, Izumi

1981-11-01

"Thermo field dynamics," allowing the Feynman diagram method to be applied to real-time causal Green's functions at finite temperatures ( not temperature Green's functions with imaginary times) expressed in the form of "vacuum" expectation values, is reconsidered in light of its connection with the algebraic formulation of statical machanics based upon the KMS condition. On the basis of so-obtained general basic formulae, the formalism is extended to the case of gauge theories, where the subsidiary condition specifying physical states, the notion of observables, and the structure of the physical subspace at finite temperatures are clarified.

Optimal Linear Responses for Markov Chains and Stochastically Perturbed Dynamical Systems

NASA Astrophysics Data System (ADS)

Antown, Fadi; Dragičević, Davor; Froyland, Gary

2018-03-01

The linear response of a dynamical system refers to changes to properties of the system when small external perturbations are applied. We consider the little-studied question of selecting an optimal perturbation so as to (i) maximise the linear response of the equilibrium distribution of the system, (ii) maximise the linear response of the expectation of a specified observable, and (iii) maximise the linear response of the rate of convergence of the system to the equilibrium distribution. We also consider the inhomogeneous, sequential, or time-dependent situation where the governing dynamics is not stationary and one wishes to select a sequence of small perturbations so as to maximise the overall linear response at some terminal time. We develop the theory for finite-state Markov chains, provide explicit solutions for some illustrative examples, and numerically apply our theory to stochastically perturbed dynamical systems, where the Markov chain is replaced by a matrix representation of an approximate annealed transfer operator for the random dynamical system.

Health Status and Health Dynamics in an Empirical Model of Expected Longevity*

PubMed Central

Benítez-Silva, Hugo; Ni, Huan

2010-01-01

Expected longevity is an important factor influencing older individuals’ decisions such as consumption, savings, purchase of life insurance and annuities, claiming of Social Security benefits, and labor supply. It has also been shown to be a good predictor of actual longevity, which in turn is highly correlated with health status. A relatively new literature on health investments under uncertainty, which builds upon the seminal work by Grossman (1972), has directly linked longevity with characteristics, behaviors, and decisions by utility maximizing agents. Our empirical model can be understood within that theoretical framework as estimating a production function of longevity. Using longitudinal data from the Health and Retirement Study, we directly incorporate health dynamics in explaining the variation in expected longevities, and compare two alternative measures of health dynamics: the self-reported health change, and the computed health change based on self-reports of health status. In 38% of the reports in our sample, computed health changes are inconsistent with the direct report on health changes over time. And another 15% of the sample can suffer from information losses if computed changes are used to assess changes in actual health. These potentially serious problems raise doubts regarding the use and interpretation of the computed health changes and even the lagged measures of self-reported health as controls for health dynamics in a variety of empirical settings. Our empirical results, controlling for both subjective and objective measures of health status and unobserved heterogeneity in reporting, suggest that self-reported health changes are a preferred measure of health dynamics. PMID:18187217

Prestimulus Inhibition of Saccades in Adults With and Without Attention-Deficit/Hyperactivity Disorder as an Index of Temporal Expectations.

PubMed

Dankner, Yarden; Shalev, Lilach; Carrasco, Marisa; Yuval-Greenberg, Shlomit

2017-07-01

Knowing when to expect important events to occur is critical for preparing context-appropriate behavior. However, anticipation is inherently complicated to assess because conventional measurements of behavior, such as accuracy and reaction time, are available only after the predicted event has occurred. Anticipatory processes, which occur prior to target onset, are typically measured only retrospectively by these methods. In this study, we utilized a novel approach for assessing temporal expectations through the dynamics of prestimulus saccades. Results showed that saccades of neurotypical participants were inhibited prior to the onset of stimuli that appeared at predictable compared with less predictable times. No such inhibition was found in most participants with attention-deficit/hyperactivity disorder (ADHD), and particularly not in those who experienced difficulties in sustaining attention over time. These findings suggest that individuals with ADHD, especially those with sustained-attention deficits, have diminished ability to benefit from temporal predictability, and this could account for some of their context-inappropriate behaviors.

Where does the water come from? Examining water stable isotopes across river basins

EPA Science Inventory

Global warming is expected to dramatically alter the timing and quantity of water within the nation’s river systems; however, these impacts will be heterogeneous both within river basins and across regions. A detailed understanding of the spatial and temporal dynamics of wa...

Modeling Noisy Data with Differential Equations Using Observed and Expected Matrices

ERIC Educational Resources Information Center

Deboeck, Pascal R.; Boker, Steven M.

2010-01-01

Complex intraindividual variability observed in psychology may be well described using differential equations. It is difficult, however, to apply differential equation models in psychological contexts, as time series are frequently short, poorly sampled, and have large proportions of measurement and dynamic error. Furthermore, current methods for…

Spatiotemporal neurodynamics of automatic temporal expectancy in 9-month old infants.

PubMed

Mento, Giovanni; Valenza, Eloisa

2016-11-04

Anticipating events occurrence (Temporal Expectancy) is a crucial capacity for survival. Yet, there is little evidence about the presence of cortical anticipatory activity from infancy. In this study we recorded the High-density electrophysiological activity in 9 month-old infants and adults undergoing an audio-visual S1-S2 paradigm simulating a lifelike "Peekaboo" game inducing automatic temporal expectancy of smiling faces. The results indicate in the S2-preceding Contingent Negative Variation (CNV) an early electrophysiological signature of expectancy-based anticipatory cortical activity. Moreover, the progressive CNV amplitude increasing across the task suggested that implicit temporal rule learning is at the basis of expectancy building-up over time. Cortical source reconstruction suggested a common CNV generator between adults and infants in the right prefrontal cortex. The decrease in the activity of this area across the task (time-on-task effect) further implied an early, core role of this region in implicit temporal rule learning. By contrast, a time-on-task activity boost was found in the supplementary motor area (SMA) in adults and in the temporoparietal regions in infants. Altogether, our findings suggest that the capacity of the human brain to translate temporal predictions into anticipatory neural activity emerges ontogenetically early, although the underlying spatiotemporal cortical dynamics change across development.

Slowing down single-molecule trafficking through a protein nanopore reveals intermediates for peptide translocation

NASA Astrophysics Data System (ADS)

Mereuta, Loredana; Roy, Mahua; Asandei, Alina; Lee, Jong Kook; Park, Yoonkyung; Andricioaei, Ioan; Luchian, Tudor

2014-01-01

The microscopic details of how peptides translocate one at a time through nanopores are crucial determinants for transport through membrane pores and important in developing nano-technologies. To date, the translocation process has been too fast relative to the resolution of the single molecule techniques that sought to detect its milestones. Using pH-tuned single-molecule electrophysiology and molecular dynamics simulations, we demonstrate how peptide passage through the α-hemolysin protein can be sufficiently slowed down to observe intermediate single-peptide sub-states associated to distinct structural milestones along the pore, and how to control residence time, direction and the sequence of spatio-temporal state-to-state dynamics of a single peptide. Molecular dynamics simulations of peptide translocation reveal the time- dependent ordering of intermediate structures of the translocating peptide inside the pore at atomic resolution. Calculations of the expected current ratios of the different pore-blocking microstates and their time sequencing are in accord with the recorded current traces.

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

Uncertainty, robustness, and the value of information in managing an expanding Arctic goose population

USGS Publications Warehouse

Johnson, Fred A.; Jensen, Gitte H.; Madsen, Jesper; Williams, Byron K.

2014-01-01

We explored the application of dynamic-optimization methods to the problem of pink-footed goose (Anser brachyrhynchus) management in western Europe. We were especially concerned with the extent to which uncertainty in population dynamics influenced an optimal management strategy, the gain in management performance that could be expected if uncertainty could be eliminated or reduced, and whether an adaptive or robust management strategy might be most appropriate in the face of uncertainty. We combined three alternative survival models with three alternative reproductive models to form a set of nine annual-cycle models for pink-footed geese. These models represent a wide range of possibilities concerning the extent to which demographic rates are density dependent or independent, and the extent to which they are influenced by spring temperatures. We calculated state-dependent harvest strategies for these models using stochastic dynamic programming and an objective function that maximized sustainable harvest, subject to a constraint on desired population size. As expected, attaining the largest mean objective value (i.e., the relative measure of management performance) depended on the ability to match a model-dependent optimal strategy with its generating model of population dynamics. The nine models suggested widely varying objective values regardless of the harvest strategy, with the density-independent models generally producing higher objective values than models with density-dependent survival. In the face of uncertainty as to which of the nine models is most appropriate, the optimal strategy assuming that both survival and reproduction were a function of goose abundance and spring temperatures maximized the expected minimum objective value (i.e., maxi–min). In contrast, the optimal strategy assuming equal model weights minimized the expected maximum loss in objective value. The expected value of eliminating model uncertainty was an increase in objective value of only 3.0%. This value represents the difference between the best that could be expected if the most appropriate model were known and the best that could be expected in the face of model uncertainty. The value of eliminating uncertainty about the survival process was substantially higher than that associated with the reproductive process, which is consistent with evidence that variation in survival is more important than variation in reproduction in relatively long-lived avian species. Comparing the expected objective value if the most appropriate model were known with that of the maxi–min robust strategy, we found the value of eliminating uncertainty to be an expected increase of 6.2% in objective value. This result underscores the conservatism of the maxi–min rule and suggests that risk-neutral managers would prefer the optimal strategy that maximizes expected value, which is also the strategy that is expected to minimize the maximum loss (i.e., a strategy based on equal model weights). The low value of information calculated for pink-footed geese suggests that a robust strategy (i.e., one in which no learning is anticipated) could be as nearly effective as an adaptive one (i.e., a strategy in which the relative credibility of models is assessed through time). Of course, an alternative explanation for the low value of information is that the set of population models we considered was too narrow to represent key uncertainties in population dynamics. Yet we know that questions about the presence of density dependence must be central to the development of a sustainable harvest strategy. And while there are potentially many environmental covariates that could help explain variation in survival or reproduction, our admission of models in which vital rates are drawn randomly from reasonable distributions represents a worst-case scenario for management. We suspect that much of the value of the various harvest strategies we calculated is derived from the fact that they are state dependent, such that appropriate harvest rates depend on population abundance and weather conditions, as well as our focus on an infinite time horizon for sustainability.

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

Experimental design for dynamics identification of cellular processes.

PubMed

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

2014-03-01

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

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

NASA Astrophysics Data System (ADS)

Bravi, B.; Sollich, P.

2017-06-01

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

Effects of communication burstiness on consensus formation and tipping points in social dynamics

NASA Astrophysics Data System (ADS)

Doyle, C.; Szymanski, B. K.; Korniss, G.

2017-06-01

Current models for opinion dynamics typically utilize a Poisson process for speaker selection, making the waiting time between events exponentially distributed. Human interaction tends to be bursty though, having higher probabilities of either extremely short waiting times or long periods of silence. To quantify the burstiness effects on the dynamics of social models, we place in competition two groups exhibiting different speakers' waiting-time distributions. These competitions are implemented in the binary naming game and show that the relevant aspect of the waiting-time distribution is the density of the head rather than that of the tail. We show that even with identical mean waiting times, a group with a higher density of short waiting times is favored in competition over the other group. This effect remains in the presence of nodes holding a single opinion that never changes, as the fraction of such committed individuals necessary for achieving consensus decreases dramatically when they have a higher head density than the holders of the competing opinion. Finally, to quantify differences in burstiness, we introduce the expected number of small-time activations and use it to characterize the early-time regime of the system.

(abstract) TOPEX/Poseidon: Four Years of Synoptic Oceanography

NASA Technical Reports Server (NTRS)

Fu, Lee-Lueng

1996-01-01

Exceeding all expectations of measurement precision and accuracy, the US/France TOPEX/Poseidon satellite mission is now in its 5th year. Returning more than 98 percent of the altimetric data, the measured global geocentric height of the sea surface has provided unprecedented opportunities to address a host of scientific problems ranging from the dynamics of ocean circulation to the distribution of internal tidal energy. Scientific highlights of this longest-running altimetric satellite mission include improvements in our understanding of the dynamics and thermodynamics of the large-scale ocean variability, such as, the properties of planetary waves; the energetics of basin-wide gyres; the heat budget of the ocean; and the ocean's response to wind forcing. For the first time, oceanographers have quantitative descriptions of a dynamic variable of the physical state of the global oceans available in near-real-time.

Slow dynamics of a protein backbone in molecular dynamics simulation revealed by time-structure based independent component analysis

NASA Astrophysics Data System (ADS)

Naritomi, Yusuke; Fuchigami, Sotaro

2013-12-01

We recently proposed the method of time-structure based independent component analysis (tICA) to examine the slow dynamics involved in conformational fluctuations of a protein as estimated by molecular dynamics (MD) simulation [Y. Naritomi and S. Fuchigami, J. Chem. Phys. 134, 065101 (2011)]. Our previous study focused on domain motions of the protein and examined its dynamics by using rigid-body domain analysis and tICA. However, the protein changes its conformation not only through domain motions but also by various types of motions involving its backbone and side chains. Some of these motions might occur on a slow time scale: we hypothesize that if so, we could effectively detect and characterize them using tICA. In the present study, we investigated slow dynamics of the protein backbone using MD simulation and tICA. The selected target protein was lysine-, arginine-, ornithine-binding protein (LAO), which comprises two domains and undergoes large domain motions. MD simulation of LAO in explicit water was performed for 1 μs, and the obtained trajectory of Cα atoms in the backbone was analyzed by tICA. This analysis successfully provided us with slow modes for LAO that represented either domain motions or local movements of the backbone. Further analysis elucidated the atomic details of the suggested local motions and confirmed that these motions truly occurred on the expected slow time scale.

Melting dynamics of ice in the mesoscopic regime

PubMed Central

Citroni, Margherita; Fanetti, Samuele; Falsini, Naomi; Foggi, Paolo; Bini, Roberto

2017-01-01

How does a crystal melt? How long does it take for melt nuclei to grow? The melting mechanisms have been addressed by several theoretical and experimental works, covering a subnanosecond time window with sample sizes of tens of nanometers and thus suitable to determine the onset of the process but unable to unveil the following dynamics. On the other hand, macroscopic observations of phase transitions, with millisecond or longer time resolution, account for processes occurring at surfaces and time limited by thermal contact with the environment. Here, we fill the gap between these two extremes, investigating the melting of ice in the entire mesoscopic regime. A bulk ice Ih or ice VI sample is homogeneously heated by a picosecond infrared pulse, which delivers all of the energy necessary for complete melting. The evolution of melt/ice interfaces thereafter is monitored by Mie scattering with nanosecond resolution, for all of the time needed for the sample to reequilibrate. The growth of the liquid domains, over distances of micrometers, takes hundreds of nanoseconds, a time orders of magnitude larger than expected from simple H-bond dynamics. PMID:28536197

A dynamical systems approach to the surface search for debris associated with the disappearance of flight MH370

NASA Astrophysics Data System (ADS)

García-Garrido, V. J.; Mancho, A. M.; Wiggins, S.; Mendoza, C.

2015-11-01

The disappearance of Malaysia Airlines flight MH370 on the morning of 8 March 2014 is one of the great mysteries of our time. Perhaps the most relevant aspect of this mystery is that not a single piece of debris from the aircraft was found during the intensive surface search carried out for roughly 2 months following the crash. Difficulties in the search efforts, due to the uncertainty of the plane's final impact point and the time that had passed since the accident, bring the question on how the debris scattered in an always moving ocean, for which there are multiple data sets that do not uniquely determine its state. Our approach to this problem is based on the use of Lagrangian descriptors (LD), a novel mathematical tool coming from dynamical systems theory that identifies dynamic barriers and coherent structures governing transport. By combining publicly available information supplied by different ocean data sources with these mathematical techniques, we are able to assess the spatio-temporal state of the ocean in the priority search area at the time of impact and the following weeks. Using this information we propose a revised search strategy by showing why one might not have expected to find debris in some large search areas targeted by the Australian Maritime Safety Authority (AMSA), and determining regions where one might have expected impact debris to be located, which were not subjected to any exploration.

The Role of Dialogic Pedagogy in Teaching Grammar

ERIC Educational Resources Information Center

Jones, Pauline; Chen, Honglin

2016-01-01

The inclusion of the Knowledge about Language strand in the recently introduced Australian Curriculum: English (AC:E) is both promising and challenging. For the first time, students across primary and secondary years of schooling are expected to develop "a coherent, dynamic, and evolving body of knowledge about the English language and how it…

Local and global analysis of a speculative housing market with production lag

NASA Astrophysics Data System (ADS)

Campisi, Giovanni; Naimzada, Ahmad K.; Tramontana, Fabio

2018-05-01

We extend the model of Dieci and Westerhoff [J. Evol. Econ. 22(2), 303-329 (2012)], where the authors analyse a speculative housing market populated by heterogeneous interacting agents described by a two dimensional nonlinear discrete time dynamical system. They show the emergence of complicated dynamics through the occurrence of bifurcations for particular parameter combinations. We enlarge their model in several ways. On one hand, we introduce time lag in the supply side and we consider two new scenarios characterised by agents' expectations formation. First, naive expectations instead of perfect foresight are considered, while in the second scenario, we study a mix between the model of Dieci and Westerhoff [J. Evol. Econ. 22(2), 303-329 (2012)] and the one we propose. As a consequence, we, analytically and numerically, explain the appearance of instability in the housing market providing conditions on the parameters that lead to a bifurcation. On the other hand, thanks to further numerical simulations, we conduct a global analysis providing the structure of the basin of attractions of the map showing coexistence of attractors.

Dynamic pricing of network goods with boundedly rational consumers.

PubMed

Radner, Roy; Radunskaya, Ami; Sundararajan, Arun

2014-01-07

We present a model of dynamic monopoly pricing for a good that displays network effects. In contrast with the standard notion of a rational-expectations equilibrium, we model consumers as boundedly rational and unable either to pay immediate attention to each price change or to make accurate forecasts of the adoption of the network good. Our analysis shows that the seller's optimal price trajectory has the following structure: The price is low when the user base is below a target level, is high when the user base is above the target, and is set to keep the user base stationary once the target level has been attained. We show that this pricing policy is robust to a number of extensions, which include the product's user base evolving over time and consumers basing their choices on a mixture of a myopic and a "stubborn" expectation of adoption. Our results differ significantly from those that would be predicted by a model based on rational-expectations equilibrium and are more consistent with the pricing of network goods observed in practice.

Load controller and method to enhance effective capacity of a photovotaic power supply using a dynamically determined expected peak loading

DOEpatents

Perez, Richard

2003-04-01

A load controller and method are provided for maximizing effective capacity of a non-controllable, renewable power supply coupled to a variable electrical load also coupled to a conventional power grid. Effective capacity is enhanced by monitoring power output of the renewable supply and loading, and comparing the loading against the power output and a load adjustment threshold determined from an expected peak loading. A value for a load adjustment parameter is calculated by subtracting the renewable supply output and the load adjustment parameter from the current load. This value is then employed to control the variable load in an amount proportional to the value of the load control parameter when the parameter is within a predefined range. By so controlling the load, the effective capacity of the non-controllable, renewable power supply is increased without any attempt at operational feedback control of the renewable supply. The expected peak loading of the variable load can be dynamically determined within a defined time interval with reference to variations in the variable load.

Dynamic pricing of network goods with boundedly rational consumers

PubMed Central

Radner, Roy; Radunskaya, Ami; Sundararajan, Arun

2014-01-01

We present a model of dynamic monopoly pricing for a good that displays network effects. In contrast with the standard notion of a rational-expectations equilibrium, we model consumers as boundedly rational and unable either to pay immediate attention to each price change or to make accurate forecasts of the adoption of the network good. Our analysis shows that the seller’s optimal price trajectory has the following structure: The price is low when the user base is below a target level, is high when the user base is above the target, and is set to keep the user base stationary once the target level has been attained. We show that this pricing policy is robust to a number of extensions, which include the product’s user base evolving over time and consumers basing their choices on a mixture of a myopic and a “stubborn” expectation of adoption. Our results differ significantly from those that would be predicted by a model based on rational-expectations equilibrium and are more consistent with the pricing of network goods observed in practice. PMID:24367101

Is seeing believing? Expectant parents’ outlooks on coparenting and later coparenting solidarity

PubMed Central

McHale, James P.; Rotman, Tamir

2007-01-01

This study examined short- and longer-term sequelae of parents’ prenatal expectations of their future family process, and traced subsequent stability in coparenting solidarity from infancy through the toddler years. 110 couples expecting a first child participated in prenatal assessments of coparenting expectations and differences, and in 3 month post-partum evaluations. 45 couples completed subsequent assessments at 12 and 30 months. At each time point multi-method evaluations of coparental adjustment were obtained. Men’s and women’s expectancies during the pregnancy and the degree of difference between their self-reported beliefs about parenting predicted post-baby coparental adjustment, with latent class analyses suggesting aftereffects of prenatal expectancies up through 30 months for some couples. Coparental solidarity was also stable from 3 to 12 and from 12 to 30 months. Data indicate that the lens parents bring to bear on their emerging family system is not immaterial, and that early-emerging coparenting dynamics portend longer term coparenting adjustment. PMID:17292781

Quantum Spectra and Dynamics

NASA Astrophysics Data System (ADS)

Arce, Julio Cesar

1992-01-01

This work focuses on time-dependent quantum theory and methods for the study of the spectra and dynamics of atomic and molecular systems. Specifically, we have addressed the following two problems: (i) Development of a time-dependent spectral method for the construction of spectra of simple quantum systems--This includes the calculation of eigenenergies, the construction of bound and continuum eigenfunctions, and the calculation of photo cross-sections. Computational applications include the quadrupole photoabsorption spectra and dissociation cross-sections of molecular hydrogen from various vibrational states in its ground electronic potential -energy curve. This method is seen to provide an advantageous alternative, both from the computational and conceptual point of view, to existing standard methods. (ii) Explicit time-dependent formulation of photoabsorption processes --Analytical solutions of the time-dependent Schrodinger equation are constructed and employed for the calculation of probability densities, momentum distributions, fluxes, transition rates, expectation values and correlation functions. These quantities are seen to establish the link between the dynamics and the calculated, or measured, spectra and cross-sections, and to clarify the dynamical nature of the excitation, transition and ejection processes. Numerical calculations on atomic and molecular hydrogen corroborate and complement the previous results, allowing the identification of different regimes during the photoabsorption process.

Quantum dynamics of nuclear spins and spin relaxation in organic semiconductors

NASA Astrophysics Data System (ADS)

Mkhitaryan, V. V.; Dobrovitski, V. V.

2017-06-01

We investigate the role of the nuclear-spin quantum dynamics in hyperfine-induced spin relaxation of hopping carriers in organic semiconductors. The fast-hopping regime, when the carrier spin does not rotate much between subsequent hops, is typical for organic semiconductors possessing long spin coherence times. We consider this regime and focus on a carrier random-walk diffusion in one dimension, where the effect of the nuclear-spin dynamics is expected to be the strongest. Exact numerical simulations of spin systems with up to 25 nuclear spins are performed using the Suzuki-Trotter decomposition of the evolution operator. Larger nuclear-spin systems are modeled utilizing the spin-coherent state P -representation approach developed earlier. We find that the nuclear-spin dynamics strongly influences the carrier spin relaxation at long times. If the random walk is restricted to a small area, it leads to the quenching of carrier spin polarization at a nonzero value at long times. If the random walk is unrestricted, the carrier spin polarization acquires a long-time tail, decaying as 1 /√{t } . Based on the numerical results, we devise a simple formula describing the effect quantitatively.

Investment Dynamics with Natural Expectations.

PubMed

Fuster, Andreas; Hebert, Benjamin; Laibson, David

2010-01-01

We study an investment model in which agents have the wrong beliefs about the dynamic properties of fundamentals. Specifically, we assume that agents underestimate the rate of mean reversion. The model exhibits the following six properties: (i) Beliefs are excessively optimistic in good times and excessively pessimistic in bad times. (ii) Asset prices are too volatile. (iii) Excess returns are negatively autocorrelated. (iv) High levels of corporate profits predict negative future excess returns. (v) Real economic activity is excessively volatile; the economy experiences amplified investment cycles. (vi) Corporate profits are positively autocorrelated in the short run and negatively autocorrelated in the medium run. The paper provides an illustrative model of animal spirits, amplified business cycles, and excess volatility.

Investment Dynamics with Natural Expectations*

PubMed Central

Fuster, Andreas; Hebert, Benjamin; Laibson, David

2012-01-01

We study an investment model in which agents have the wrong beliefs about the dynamic properties of fundamentals. Specifically, we assume that agents underestimate the rate of mean reversion. The model exhibits the following six properties: (i) Beliefs are excessively optimistic in good times and excessively pessimistic in bad times. (ii) Asset prices are too volatile. (iii) Excess returns are negatively autocorrelated. (iv) High levels of corporate profits predict negative future excess returns. (v) Real economic activity is excessively volatile; the economy experiences amplified investment cycles. (vi) Corporate profits are positively autocorrelated in the short run and negatively autocorrelated in the medium run. The paper provides an illustrative model of animal spirits, amplified business cycles, and excess volatility. PMID:23243469

The fast multipole method and point dipole moment polarizable force fields.

PubMed

Coles, Jonathan P; Masella, Michel

2015-01-14

We present an implementation of the fast multipole method for computing Coulombic electrostatic and polarization forces from polarizable force-fields based on induced point dipole moments. We demonstrate the expected O(N) scaling of that approach by performing single energy point calculations on hexamer protein subunits of the mature HIV-1 capsid. We also show the long time energy conservation in molecular dynamics at the nanosecond scale by performing simulations of a protein complex embedded in a coarse-grained solvent using a standard integrator and a multiple time step integrator. Our tests show the applicability of fast multipole method combined with state-of-the-art chemical models in molecular dynamical systems.

An Ad-Hoc Adaptive Pilot Model for Pitch Axis Gross Acquisition Tasks

NASA Technical Reports Server (NTRS)

Hanson, Curtis E.

2012-01-01

An ad-hoc algorithm is presented for real-time adaptation of the well-known crossover pilot model and applied to pitch axis gross acquisition tasks in a generic fighter aircraft. Off-line tuning of the crossover model to human pilot data gathered in a fixed-based high fidelity simulation is first accomplished for a series of changes in aircraft dynamics to provide expected values for model parameters. It is shown that in most cases, for this application, the traditional crossover model can be reduced to a gain and a time delay. The ad-hoc adaptive pilot gain algorithm is shown to have desirable convergence properties for most types of changes in aircraft dynamics.

Exploring the History of Time in an Integrated System: the Ramifications for Water

NASA Astrophysics Data System (ADS)

Green, M. B.; Adams, L. E.; Allen, T. L.; Arrigo, J. S.; Bain, D. J.; Bray, E. N.; Duncan, J. M.; Hermans, C. M.; Pastore, C.; Schlosser, C. A.; Vorosmarty, C. J.; Witherell, B. B.; Wollheim, W. M.; Wreschnig, A. J.

2009-12-01

Characteristic time scales are useful and simple descriptors of geophysical and socio-economic system dynamics. Focusing on the integrative nature of the hydrologic cycle, new insights into system couplings can be gained by compiling characteristic time scales of important processes driving these systems. There are many examples of changing characteristic time scales. Human life expectancy has increased over the recent history of medical advancement. The transport time of goods has decreased with the progression from horse to rail to car to plane. The transport time of information changed with the progression from letter to telegraph to telephone to networked computing. Soil residence time (pedogenesis to estuary deposition) has been influenced by changing agricultural technology, urbanization, and forest practices. Surface water residence times have varied as beaver dams have disappeared and been replaced with modern reservoirs, flood control works, and channelization. These dynamics raise the question of how these types of time scales interact with each other to form integrated Earth system dynamics? Here we explore the coupling of geophysical and socio-economic systems in the northeast United States over the 1600 to 2010 period by examining characteristic time scales. This visualization of many time scales serves as an exploratory analysis, producing new hypotheses about how the integrated system dynamics have evolved over the last 400 years. Specifically, exponential population growth and the evolving strategies to maintain that population appears as fundamental to many of the time scales.

Health status and health dynamics in an empirical model of expected longevity.

PubMed

Benítez-Silva, Hugo; Ni, Huan

2008-05-01

Expected longevity is an important factor influencing older individuals' decisions such as consumption, savings, purchase of life insurance and annuities, claiming of Social Security benefits, and labor supply. It has also been shown to be a good predictor of actual longevity, which in turn is highly correlated with health status. A relatively new literature on health investments under uncertainty, which builds upon the seminal work by Grossman [Grossman, M., 1972. On the concept of health capital and demand for health. Journal of Political Economy 80, 223-255] has directly linked longevity with characteristics, behaviors, and decisions by utility maximizing agents. Our empirical model can be understood within that theoretical framework as estimating a production function of longevity. Using longitudinal data from the Health and Retirement Study, we directly incorporate health dynamics in explaining the variation in expected longevities, and compare two alternative measures of health dynamics: the self-reported health change, and the computed health change based on self-reports of health status. In 38% of the reports in our sample, computed health changes are inconsistent with the direct report on health changes over time. And another 15% of the sample can suffer from information losses if computed changes are used to assess changes in actual health. These potentially serious problems raise doubts regarding the use and interpretation of the computed health changes and even the lagged measures of self-reported health as controls for health dynamics in a variety of empirical settings. Our empirical results, controlling for both subjective and objective measures of health status and unobserved heterogeneity in reporting, suggest that self-reported health changes are a preferred measure of health dynamics.

Dynamical resonance shift and unification of resonances in short-pulse laser-cluster interaction

NASA Astrophysics Data System (ADS)

Mahalik, S. S.; Kundu, M.

2018-06-01

Pronounced maximum absorption of laser light irradiating a rare-gas or metal cluster is widely expected during the linear resonance (LR) when Mie-plasma wavelength λM of electrons equals the laser wavelength λ . On the contrary, by performing molecular dynamics (MD) simulations of an argon cluster irradiated by short 5-fs (FWHM) laser pulses it is revealed that, for a given laser pulse energy and a cluster, at each peak intensity there exists a λ —shifted from the expected λM—that corresponds to a unified dynamical LR at which evolution of the cluster happens through very efficient unification of possible resonances in various stages, including (i) the LR in the initial time of plasma creation, (ii) the LR in the Coulomb expanding phase in the later time, and (iii) anharmonic resonance in the marginally overdense regime for a relatively longer pulse duration, leading to maximum laser absorption accompanied by maximum removal of electrons from cluster and also maximum allowed average charge states for the argon cluster. Increasing the laser intensity, the absorption maxima is found to shift to a higher wavelength in the band of λ ≈(1 -1.5 ) λM than permanently staying at the expected λM. A naive rigid sphere model also corroborates the wavelength shift of the absorption peak as found in MD and unequivocally proves that maximum laser absorption in a cluster happens at a shifted λ in the marginally overdense regime of λ ≈(1 -1.5 ) λM instead of λM of LR. The present study is important for guiding an optimal condition laser-cluster interaction experiment in the short-pulse regime.

A census of the expected properties of classical Milky Way dwarfs in Milgromian dynamics

NASA Astrophysics Data System (ADS)

Lüghausen, F.; Famaey, B.; Kroupa, P.

2014-07-01

Prompted by the recent successful predictions of the internal dynamics of Andromeda's satellite galaxies, we revisit the classical Milky Way dwarf spheroidal satellites Draco, Sculptor, Sextans, Carina and Fornax in the framework of Milgromian dynamics (MOND). We use for the first time a Poisson solver with adaptive mesh refinement (AMR) in order to account simultaneously for the gravitational influence of the Milky Way and its satellites. This allows us to rigorously model the important external field effect (EFE) of Milgromian dynamics, which can reduce the effective acceleration significantly. We make predictions on the dynamical mass-to-light ratio (Mdyn/L) expected to be measured by an observer who assumes Newtonian dynamics to be valid. We show that Milgromian dynamics predicts typical Mdyn/L ≈ 10-50 M⊙/L⊙. The results for the most luminous ones, Fornax and Sculptor, agree well with available velocity dispersion data. Moreover, the central power-law slopes of the dynamical masses agree exceedingly well with values inferred observationally from velocity dispersion measurements. The results for Sextans, Carina and Draco are low compared to usually quoted observational estimates, as already pointed out by Angus. For Milgromian dynamics to survive further observational tests in these objects, one would thus need that either (a) previous observational findings based on velocity dispersion measurements have overestimated the dynamical mass due to, e.g. binaries and contaminant outliers, (b) the satellites are not in virial equilibrium due to the Milky Way tidal field, or (c) the specific theory used here does not describe the EFE correctly (e.g. the EFE could be practically negligible in some other theories), or a combination of (a)-(c).

Time-Variable Transit Time Distributions in the Hyporheic Zone of a Headwater Mountain Stream

NASA Astrophysics Data System (ADS)

Ward, Adam S.; Schmadel, Noah M.; Wondzell, Steven M.

2018-03-01

Exchange of water between streams and their hyporheic zones is known to be dynamic in response to hydrologic forcing, variable in space, and to exist in a framework with nested flow cells. The expected result of heterogeneous geomorphic setting, hydrologic forcing, and between-feature interaction is hyporheic transit times that are highly variable in both space and time. Transit time distributions (TTDs) are important as they reflect the potential for hyporheic processes to impact biogeochemical transformations and ecosystems. In this study we simulate time-variable transit time distributions based on dynamic vertical exchange in a headwater mountain stream with observed, heterogeneous step-pool morphology. Our simulations include hyporheic exchange over a 600 m river corridor reach driven by continuously observed, time-variable hydrologic conditions for more than 1 year. We found that spatial variability at an instance in time is typically larger than temporal variation for the reach. Furthermore, we found reach-scale TTDs were marginally variable under all but the most extreme hydrologic conditions, indicating that TTDs are highly transferable in time. Finally, we found that aggregation of annual variation in space and time into a "master TTD" reasonably represents most of the hydrologic dynamics simulated, suggesting that this aggregation approach may provide a relevant basis for scaling from features or short reaches to entire networks.

Dynamic Changes in Nucleosome Occupancy Are Not Predictive of Gene Expression Dynamics but Are Linked to Transcription and Chromatin Regulators

PubMed Central

Huebert, Dana J.; Kuan, Pei-Fen; Keleş, Sündüz

2012-01-01

The response to stressful stimuli requires rapid, precise, and dynamic gene expression changes that must be coordinated across the genome. To gain insight into the temporal ordering of genome reorganization, we investigated dynamic relationships between changing nucleosome occupancy, transcription factor binding, and gene expression in Saccharomyces cerevisiae yeast responding to oxidative stress. We applied deep sequencing to nucleosomal DNA at six time points before and after hydrogen peroxide treatment and revealed many distinct dynamic patterns of nucleosome gain and loss. The timing of nucleosome repositioning was not predictive of the dynamics of downstream gene expression change but instead was linked to nucleosome position relative to transcription start sites and specific cis-regulatory elements. We measured genome-wide binding of the stress-activated transcription factor Msn2p over time and found that Msn2p binds different loci with different dynamics. Nucleosome eviction from Msn2p binding sites was common across the genome; however, we show that, contrary to expectation, nucleosome loss occurred after Msn2p binding and in fact required Msn2p. This negates the prevailing model that nucleosomes obscuring Msn2p sites regulate DNA access and must be lost before Msn2p can bind DNA. Together, these results highlight the complexities of stress-dependent chromatin changes and their effects on gene expression. PMID:22354995

A fractal approach to dynamic inference and distribution analysis

PubMed Central

van Rooij, Marieke M. J. W.; Nash, Bertha A.; Rajaraman, Srinivasan; Holden, John G.

2013-01-01

Event-distributions inform scientists about the variability and dispersion of repeated measurements. This dispersion can be understood from a complex systems perspective, and quantified in terms of fractal geometry. The key premise is that a distribution's shape reveals information about the governing dynamics of the system that gave rise to the distribution. Two categories of characteristic dynamics are distinguished: additive systems governed by component-dominant dynamics and multiplicative or interdependent systems governed by interaction-dominant dynamics. A logic by which systems governed by interaction-dominant dynamics are expected to yield mixtures of lognormal and inverse power-law samples is discussed. These mixtures are described by a so-called cocktail model of response times derived from human cognitive performances. The overarching goals of this article are twofold: First, to offer readers an introduction to this theoretical perspective and second, to offer an overview of the related statistical methods. PMID:23372552

Real-time observation of the conformational dynamics of mitochondrial Hsp70 by spFRET

PubMed Central

Sikor, Martin; Mapa, Koyeli; von Voithenberg, Lena Voith; Mokranjac, Dejana; Lamb, Don C

2013-01-01

The numerous functions of the important class of molecular chaperones, heat shock proteins 70 (Hsp70), rely on cycles of intricate conformational changes driven by ATP-hydrolysis and regulated by cochaperones and substrates. Here, we used Förster resonance energy transfer to study the conformational dynamics of individual molecules of Ssc1, a mitochondrial Hsp70, in real time. The intrinsic dynamics of the substrate-binding domain of Ssc1 was observed to be uncoupled from the dynamic interactions between substrate- and nucleotide-binding domains. Analysis of the fluctuations in the interdomain separation revealed frequent transitions to a nucleotide-free state. The nucleotide-exchange factor Mge1 did not induce ADP release, as expected, but rather facilitated binding of ATP. These results indicate that the conformational cycle of Ssc1 is more elaborate than previously thought and provide insight into how the Hsp70s can perform a wide variety of functions. PMID:23624933

Repeatability Modeling for Wind-Tunnel Measurements: Results for Three Langley Facilities

NASA Technical Reports Server (NTRS)

Hemsch, Michael J.; Houlden, Heather P.

2014-01-01

Data from extensive check standard tests of seven measurement processes in three NASA Langley Research Center wind tunnels are statistically analyzed to test a simple model previously presented in 2000 for characterizing short-term, within-test and across-test repeatability. The analysis is intended to support process improvement and development of uncertainty models for the measurements. The analysis suggests that the repeatability can be estimated adequately as a function of only the test section dynamic pressure over a two-orders- of-magnitude dynamic pressure range. As expected for low instrument loading, short-term coefficient repeatability is determined by the resolution of the instrument alone (air off). However, as previously pointed out, for the highest dynamic pressure range the coefficient repeatability appears to be independent of dynamic pressure, thus presenting a lower floor for the standard deviation for all three time frames. The simple repeatability model is shown to be adequate for all of the cases presented and for all three time frames.

Hamiltonian model and dynamic analyses for a hydro-turbine governing system with fractional item and time-lag

NASA Astrophysics Data System (ADS)

Xu, Beibei; Chen, Diyi; Zhang, Hao; Wang, Feifei; Zhang, Xinguang; Wu, Yonghong

2017-06-01

This paper focus on a Hamiltonian mathematical modeling for a hydro-turbine governing system including fractional item and time-lag. With regards to hydraulic pressure servo system, a universal dynamical model is proposed, taking into account the viscoelastic properties and low-temperature impact toughness of constitutive materials as well as the occurrence of time-lag in the signal transmissions. The Hamiltonian model of the hydro-turbine governing system is presented using the method of orthogonal decomposition. Furthermore, a novel Hamiltonian function that provides more detailed energy information is presented, since the choice of the Hamiltonian function is the key issue by putting the whole dynamical system to the theory framework of the generalized Hamiltonian system. From the numerical experiments based on a real large hydropower station, we prove that the Hamiltonian function can describe the energy variation of the hydro-turbine suitably during operation. Moreover, the effect of the fractional α and the time-lag τ on the dynamic variables of the hydro-turbine governing system are explored and their change laws identified, respectively. The physical meaning between fractional calculus and time-lag are also discussed in nature. All of the above theories and numerical results are expected to provide a robust background for the safe operation and control of large hydropower stations.

Thermalization and its mechanism for generic quantum isolated systems

NASA Astrophysics Data System (ADS)

Olshanii, Maxim; Dunjko, Vanja; Rigol, Marcos

2008-05-01

Time dynamics of isolated many-body quantum systems has long been an elusive subject, perhaps most urgently needed in the foundations of quantum statistical mechanics. In generic systems, one expects the nonequilibrium dynamics to lead to thermalization: a relaxation to states where the values of macroscopic quantities are stationary, universal with respect to widely differing initial conditions, and predictable through the time-tested recipe of statistical mechanics. The relaxation mechanism is not obvious, however; dynamical chaos cannot play the key role as it does in classical systems since quantum evolution is linear. Here we demonstrateootnotetextM. Rigol, V. Dunjko, and M. Olshanii, to appear in Nature (2008), using the results of an ab initio numerical experiment with 5 hard-core bosons moving in a 5x5 lattice, that in quantum systems thermalization happens not in course of time evolution but instead at the level of individual eigenstates, as first proposed by DeutschootnotetextJ. M. Deutsch, Phys.Rev. A 43, 2046 (1991) and SrednickiootnotetextM. Srednicki, Phys. Rev. E 50, 888 (1994).

Free-time and fixed end-point optimal control theory in dissipative media: application to entanglement generation and maintenance.

PubMed

Mishima, K; Yamashita, K

2009-07-07

We develop monotonically convergent free-time and fixed end-point optimal control theory (OCT) in the density-matrix representation to deal with quantum systems showing dissipation. Our theory is more general and flexible for tailoring optimal laser pulses in order to control quantum dynamics with dissipation than the conventional fixed-time and fixed end-point OCT in that the optimal temporal duration of laser pulses can also be optimized exactly. To show the usefulness of our theory, it is applied to the generation and maintenance of the vibrational entanglement of carbon monoxide adsorbed on the copper (100) surface, CO/Cu(100). We demonstrate the numerical results and clarify how to combat vibrational decoherence as much as possible by the tailored shapes of the optimal laser pulses. It is expected that our theory will be general enough to be applied to a variety of dissipative quantum dynamics systems because the decoherence is one of the quantum phenomena sensitive to the temporal duration of the quantum dynamics.

Fixation Times in Deme Structured, Finite Populations with Rare Migration

NASA Astrophysics Data System (ADS)

Hauert, Christoph; Chen, Yu-Ting; Imhof, Lorens A.

2014-08-01

Population structure affects both the outcome and the speed of evolutionary dynamics. Here we consider a finite population that is divided into subpopulations called demes. The dynamics within the demes are stochastic and frequency-dependent. Individuals can adopt one of two strategic types, or . The fitness of each individual is determined by interactions with other individuals in the same deme. With small probability, proportional to fitness, individuals migrate to other demes. The outcome of these dynamics has been studied earlier by analyzing the fixation probability of a single mutant in an otherwise homogeneous population. These results give only a partial picture of the dynamics, because the time when fixation occurs can be exceedingly large. In this paper, we study the impact of deme structures on the speed of evolution. We derive analytical approximations of fixation times in the limit of rare migration and rare mutation. In this limit, the conditional fixation time of a single mutant in a population is the same as that of a single in an population. For the prisoner's dilemma game, simulation results fit very well with our analytical predictions and demonstrate that fixation takes place in a moderate amount of time as compared to the expected waiting time until a mutant successfully invades and fixates. The simulations also confirm that the conditional fixation time of a single cooperator is indeed the same as that of a single defector.

Stability and diversity in collective adaptation

NASA Astrophysics Data System (ADS)

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

2005-10-01

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

Nonlinear evolution dynamics of holographic superconductor model with scalar self-interaction

NASA Astrophysics Data System (ADS)

Li, Ran; Zi, Tieguang; Zhang, Hongbao

2018-04-01

We investigate the holographic superconductor model that is described by the Einstein-Maxwell theory with the self-interaction term λ |Ψ |4 of complex scalar field in asymptotic anti-de Sitter (AdS) spacetime. Below critical temperature Tc, the planar Reissner-Nordström-AdS black hole is unstable due to the near-horizon scalar condensation instability. We study the full nonlinear development of this instability by numerically solving the gravitational dynamics in the asymptotic AdS spacetime, and observe a dynamical process from the perturbed Reissner-Nordström-AdS black hole to a hairy black hole when the initial black hole temperature T

Thermalization dynamics of two correlated bosonic quantum wires after a split

NASA Astrophysics Data System (ADS)

Huber, Sebastian; Buchhold, Michael; Schmiedmayer, Jörg; Diehl, Sebastian

2018-04-01

Cherently splitting a one-dimensional Bose gas provides an attractive, experimentally established platform to investigate many-body quantum dynamics. At short enough times, the dynamics is dominated by the dephasing of single quasiparticles, and well described by the relaxation towards a generalized Gibbs ensemble corresponding to the free Luttinger theory. At later times on the other hand, the approach to a thermal Gibbs ensemble is expected for a generic, interacting quantum system. Here, we go one step beyond the quadratic Luttinger theory and include the leading phonon-phonon interactions. By applying kinetic theory and nonequilibrium Dyson-Schwinger equations, we analyze the full relaxation dynamics beyond dephasing and determine the asymptotic thermalization process in the two-wire system for a symmetric splitting protocol. The major observables are the different phonon occupation functions and the experimentally accessible coherence factor, as well as the phase correlations between the two wires. We demonstrate that, depending on the splitting protocol, the presence of phonon collisions can have significant influence on the asymptotic evolution of these observables, which makes the corresponding thermalization dynamics experimentally accessible.

Understanding Unimer Exchange Processes in Block Copolymer Micelles using NMR Diffusometry, Time-Resolved NMR, and SANS

NASA Astrophysics Data System (ADS)

Madsen, Louis; Kidd, Bryce; Li, Xiuli; Miller, Katherine; Cooksey, Tyler; Robertson, Megan

Our team seeks to understand dynamic behaviors of block copolymer micelles and their interplay with encapsulated cargo molecules. Quantifying unimer and cargo exchange rates micelles can provide critical information for determining mechanisms of unimer exchange as well as designing systems for specific cargo release dynamics. We are exploring the utility of NMR spectroscopy and diffusometry techniques as complements to existing SANS and fluorescence methods. One promising new method involves time-resolved NMR spin relaxation measurements, wherein mixing of fully protonated and 2H-labeled PEO-b-PCL micelles solutions shows an increase in spin-lattice relaxation time (T1) with time after mixing. This is due to a weakening in magnetic environment surrounding 1H spins as 2H-bearing unimers join fully protonated micelles. We are measuring time constants for unimer exchange of minutes to hours, and we expect to resolve times of <1 min. This method can work on any solution NMR spectrometer and with minimal perturbation to chemical structure (as in dye-labelled fluorescence methods). Multimodal NMR can complement existing characterization tools, expanding and accelerating dynamics measurements for polymer micelle, nanogel, and nanoparticle developers.

Joint production and substitution in timber supply: a panel data analysis

Treesearch

Torjus F Bolkesjo; Joseph Buongiorno; Birger Solberg

2010-01-01

Supply equations for sawlog and pulpwood were developed with a panel of data from 102 Norwegian municipalities, observed from 1980 to 2000. Static and dynamic models were estimated by cross-section, time-series andpanel data methods. A static model estimated by first differencing gavethe best overall results in terms of theoretical expectations, pattern ofresiduals,...

The Dynamic Still-Face Effect: Do Infants Decrease Bidding over Time when Parents Are Not Responsive?

ERIC Educational Resources Information Center

Ekas, Naomi V.; Haltigan, John D.; Messinger, Daniel S.

2013-01-01

The still-face paradigm (SFP) was designed to assess infant expectations that parents will respond to infant communicative signals. During the still-face (SF) episode, the parent ceases interaction and maintains a neutral expression. Original, qualitative descriptions of infant behavior suggested changes within the SF episode: infants decrease…

Bulk viscosity of the Lennard-Jones fluid for a wide range of states computed by equilibrium molecular dynamics

NASA Astrophysics Data System (ADS)

Hoheisel, C.; Vogelsang, R.; Schoen, M.

1987-12-01

Accurate data for the bulk viscosity ηv have been obtained by molecular dynamics calculations. Many thermodynamic states of the Lennard-Jones fluid were considered. The Green-Kubo integrand of ηv is analyzed in terms of partial correlation functions constituting the total one. These partial functions behave rather differently from those found for the shear viscosity or the thermal conductivity. Generally the total autocorrelation function of ηv shows a steeper initial decay and a more pronounced long time form than those of the shear viscosity or the thermal conductivity. For states near transition to solid phases, like the pseudotriple point of argon, the Green-Kubo integrand of ηv has a significantly longer ranged time behavior than that of the shear viscosity. Hence, for the latter states, a systematic error is expected for ηv using equilibrium molecular dynamics for its computation.

Popularity and adolescent friendship networks: selection and influence dynamics.

PubMed

Dijkstra, Jan Kornelis; Cillessen, Antonius H N; Borch, Casey

2013-07-01

This study examined the dynamics of popularity in adolescent friendship networks across 3 years in middle school. Longitudinal social network modeling was used to identify selection and influence in the similarity of popularity among friends. It was argued that lower status adolescents strive to enhance their status through befriending higher status adolescents, whereas higher status adolescents strive to maintain their status by keeping lower status adolescents at a distance. The results largely supported these expectations. Selection partially accounted for similarity in popularity among friends; adolescents preferred to affiliate with similar-status or higher status peers, reinforcing the attractiveness of popular adolescents and explaining stability of popularity at the individual level. Influence processes also accounted for similarity in popularity over time, showing that peers increase in popularity and become more similar to their friends. The results showed how selection and influence processes account for popularity dynamics in adolescent networks over time.

Real-Time Minimization of Tracking Error for Aircraft Systems

NASA Technical Reports Server (NTRS)

Garud, Sumedha; Kaneshige, John T.; Krishnakumar, Kalmanje S.; Kulkarni, Nilesh V.; Burken, John

2013-01-01

This technology presents a novel, stable, discrete-time adaptive law for flight control in a Direct adaptive control (DAC) framework. Where errors are not present, the original control design has been tuned for optimal performance. Adaptive control works towards achieving nominal performance whenever the design has modeling uncertainties/errors or when the vehicle suffers substantial flight configuration change. The baseline controller uses dynamic inversion with proportional-integral augmentation. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to a dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. If the system senses that at least one aircraft component is experiencing an excursion and the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, then the neural network (NN) modeling of aircraft operation may be changed.

Spin noise spectroscopy of donor-bound electrons in ZnO

NASA Astrophysics Data System (ADS)

Horn, H.; Balocchi, A.; Marie, X.; Bakin, A.; Waag, A.; Oestreich, M.; Hübner, J.

2013-01-01

We investigate the intrinsic spin dynamics of electrons bound to Al impurities in bulk ZnO by optical spin noise spectroscopy. Spin noise spectroscopy enables us to investigate the longitudinal and transverse spin relaxation time with respect to nuclear and external magnetic fields in a single spectrum. On one hand, the spin dynamic is dominated by the intrinsic hyperfine interaction with the nuclear spins of the naturally occurring 67Zn isotope. We measure a typical spin dephasing time of 23 ns, in agreement with the expected theoretical values. On the other hand, we measure a third, very high spin dephasing rate which is attributed to a high defect density of the investigated ZnO material. Measurements of the spin dynamics under the influence of transverse as well as longitudinal external magnetic fields unambiguously reveal the intriguing connections of the electron spin with its nuclear and structural environment.

The dynamics of genetic draft in rapidly adapting populations.

PubMed

Kosheleva, Katya; Desai, Michael M

2013-11-01

The accumulation of beneficial mutations on competing genetic backgrounds in rapidly adapting populations has a striking impact on evolutionary dynamics. This effect, known as clonal interference, causes erratic fluctuations in the frequencies of observed mutations, randomizes the fixation times of successful mutations, and leaves distinct signatures on patterns of genetic variation. Here, we show how this form of "genetic draft" affects the forward-time dynamics of site frequencies in rapidly adapting asexual populations. We calculate the probability that mutations at individual sites shift in frequency over a characteristic timescale, extending Gillespie's original model of draft to the case where many strongly selected beneficial mutations segregate simultaneously. We then derive the sojourn time of mutant alleles, the expected fixation time of successful mutants, and the site frequency spectrum of beneficial and neutral mutations. Finally, we show how this form of draft affects inferences in the McDonald-Kreitman test and how it relates to recent observations that some aspects of genetic diversity are described by the Bolthausen-Sznitman coalescent in the limit of very rapid adaptation.

Dynamics of traffic flow with real-time traffic information

NASA Astrophysics Data System (ADS)

Yokoya, Yasushi

2004-01-01

We studied dynamics of traffic flow with real-time information provided. Provision of the real-time traffic information based on advancements in telecommunication technology is expected to facilitate the efficient utilization of available road capacity. This system has a potentiality of not only engineering for road usage but also the science of complexity series. In the system, the information plays a role of feedback connecting microscopic and macroscopic phenomena beyond the hierarchical structure of statistical physics. In this paper, we tried to clarify how the information works in a network of traffic flow from the perspective of statistical physics. The dynamical feature of the traffic flow is abstracted by a contrastive study between the nonequilibrium statistical physics and a computer simulation based on cellular automaton. We found that the information disrupts the local equilibrium of traffic flow by a characteristic dissipation process due to interaction between the information and individual vehicles. The dissipative structure was observed in the time evolution of traffic flow driven far from equilibrium as a consequence of the breakdown of the local-equilibrium hypothesis.

Expectation-maximization of the potential of mean force and diffusion coefficient in Langevin dynamics from single molecule FRET data photon by photon.

PubMed

Haas, Kevin R; Yang, Haw; Chu, Jhih-Wei

2013-12-12

The dynamics of a protein along a well-defined coordinate can be formally projected onto the form of an overdamped Lagevin equation. Here, we present a comprehensive statistical-learning framework for simultaneously quantifying the deterministic force (the potential of mean force, PMF) and the stochastic force (characterized by the diffusion coefficient, D) from single-molecule Förster-type resonance energy transfer (smFRET) experiments. The likelihood functional of the Langevin parameters, PMF and D, is expressed by a path integral of the latent smFRET distance that follows Langevin dynamics and realized by the donor and the acceptor photon emissions. The solution is made possible by an eigen decomposition of the time-symmetrized form of the corresponding Fokker-Planck equation coupled with photon statistics. To extract the Langevin parameters from photon arrival time data, we advance the expectation-maximization algorithm in statistical learning, originally developed for and mostly used in discrete-state systems, to a general form in the continuous space that allows for a variational calculus on the continuous PMF function. We also introduce the regularization of the solution space in this Bayesian inference based on a maximum trajectory-entropy principle. We use a highly nontrivial example with realistically simulated smFRET data to illustrate the application of this new method.

Anticipatory adjustments to abrupt changes of opposing forces.

PubMed

Rapp, Katrin; Heuer, Herbert

2015-01-01

Anticipatory adjustments to abrupt load changes are based on task-specific predictive information. The authors asked whether anticipatory adjustments to abrupt offsets of horizontal forces are related to expectancy. In two experiments participants held a position against an opposing force or moved against it. At force offset they had to stop rapidly. Duration of the opposing force or distance moved against it varied between blocks of trials and was constant within each block, or it varied from trial to trial. These two variations resulted in opposite changes of the expectancy of force offset with the passage of time or distance. With constant force durations or distances in each block of trials, anticipatory adjustments tended to be poorest with the longest duration or distance, but with variable force durations or distances they tended to be best with the longest duration or distance. Thus anticipatory adjustments were related to expectancy rather than time or distance per se. Anticipatory adjustments resulted in shorter peak amplitudes of the involuntary movements, accompanied by longer movement times in Experiment 1 and faster movement times in Experiment 2. Thus, for different states of the limb at abrupt dynamic changes anticipatory adjustments involve different mechanisms that modulate different mechanical characteristics.

The dynamic and indirect spatial effects of neighborhood conditions on land value, spatial panel dynamic econometrics model

NASA Astrophysics Data System (ADS)

Fitriani, Rahma; Sumarminingsih, Eni; Astutik, Suci

2017-05-01

Land value is the product of past decision of its use leading to its value, as well as the value of the surrounded land. It is also affected by the local characteristic and the spillover development demand of the previous time period. The effect of each factor on land value will have dynamic and spatial virtues. Thus, a spatial panel dynamic model is used to estimate the particular effects. The model will be useful for predicting the future land value or the effect of implemented policy on land value. The objective of this paper is to derive the dynamic and indirect spatial marginal effects of the land characteristic and the spillover development demand on land value. Each effect is the partial derivative of the expected land value based on the spatial dynamic model with respect to each variable, by considering different time period and different location. The results indicate that the instant change of local or neighborhood characteristics on land value affect the local and the immediate neighborhood land value. However, the longer the change take place, the effect will spread further, not only on the immediate neighborhood.

Hydration Dynamics of Hyaluronan and Dextran

PubMed Central

Hunger, Johannes; Bernecker, Anja; Bakker, Huib J.; Bonn, Mischa; Richter, Ralf P.

2012-01-01

Hyaluronan is a polysaccharide, which is ubiquitous in vertebrates and has been reported to be strongly hydrated in a biological environment. We study the hydration of hyaluronan in solution using the rotational dynamics of water as a probe. We measure these dynamics with polarization-resolved femtosecond-infrared and terahertz time-domain spectroscopies. Both experiments reveal that a subensemble of water molecules is slowed down in aqueous solutions of hyaluronan amounting to ∼15 water molecules per disaccharide unit. This quantity is consistent with what would be expected for the first hydration shell. Comparison of these results to the water dynamics in aqueous dextran solution, a structurally similar polysaccharide, yields remarkably similar results. This suggests that the observed interaction with water is a common feature for hydrophilic polysaccharides and is not specific to hyaluronan. PMID:22828349

Treatment expectations for cognitive-behavioral therapy and light therapy for seasonal affective disorder: Change across treatment and relation to outcome.

PubMed

Meyerhoff, Jonah; Rohan, Kelly J

2016-10-01

To examine the dynamic relationship between treatment expectations and treatment outcome over the course of a clinical trial for winter seasonal affective disorder (SAD). Currently depressed adults with Major Depression, Recurrent with Seasonal Pattern (N = 177) were randomized to 6 weeks of group-delivered cognitive-behavioral therapy for SAD (CBT-SAD) or light therapy (LT). The majority were female (83.6%) and white (92.1%), with a mean age of 45.6 years. Treatment expectations for CBT-SAD and LT were assessed using a modification of the Treatment Expectancy and Credibility Survey (Borkovec & Nau, 1972). Depression severity was assessed using the Beck Depression Inventory-Second Edition (Beck, Steer, & Brown, 1996). All measures were administered at pretreatment, midtreatment, and posttreatment. As treatment progressed, expectations for the treatment received increased across time steeply in CBT-SAD patients and moderately in LT patients. Collapsing across time, patients with higher treatment expectations had lower depression severity than those with lower treatment expectations. In a cross-lagged panel path analysis, there was a significant effect of treatment expectations at midtreatment on depression severity at posttreatment among CBT-SAD patients. Treatment expectations changed across treatment, affected outcome, and should be assessed and monitored repeatedly throughout treatment. Findings suggest that treatment expectations at midtreatment are a mechanism by which CBT-SAD reduces depression, which should be replicated in SAD samples and examined for generalizability to nonseasonal depression. These findings underscore the importance of further research examining treatment expectations in mediating CBT's effects in depression and other types of psychopathology. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Real-time emulation of neural images in the outer retinal circuit.

PubMed

Hasegawa, Jun; Yagi, Tetsuya

2008-12-01

We describe a novel real-time system that emulates the architecture and functionality of the vertebrate retina. This system reconstructs the neural images formed by the retinal neurons in real time by using a combination of analog and digital systems consisting of a neuromorphic silicon retina chip, a field-programmable gate array, and a digital computer. While the silicon retina carries out the spatial filtering of input images instantaneously, using the embedded resistive networks that emulate the receptive field structure of the outer retinal neurons, the digital computer carries out the temporal filtering of the spatially filtered images to emulate the dynamical properties of the outer retinal circuits. The emulations of the neural image, including 128 x 128 bipolar cells, are carried out at a frame rate of 62.5 Hz. The emulation of the response to the Hermann grid and a spot of light and an annulus of lights has demonstrated that the system responds as expected by previous physiological and psychophysical observations. Furthermore, the emulated dynamics of neural images in response to natural scenes revealed the complex nature of retinal neuron activity. We have concluded that the system reflects the spatiotemporal responses of bipolar cells in the vertebrate retina. The proposed emulation system is expected to aid in understanding the visual computation in the retina and the brain.

A neural network model of three-dimensional dynamic electron density in the inner magnetosphere

NASA Astrophysics Data System (ADS)

Chu, X.; Bortnik, J.; Li, W.; Ma, Q.; Denton, R.; Yue, C.; Angelopoulos, V.; Thorne, R. M.; Darrouzet, F.; Ozhogin, P.; Kletzing, C. A.; Wang, Y.; Menietti, J.

2017-09-01

A plasma density model of the inner magnetosphere is important for a variety of applications including the study of wave-particle interactions, and wave excitation and propagation. Previous empirical models have been developed under many limiting assumptions and do not resolve short-term variations, which are especially important during storms. We present a three-dimensional dynamic electron density (DEN3D) model developed using a feedforward neural network with electron densities obtained from four satellite missions. The DEN3D model takes spacecraft location and time series of solar and geomagnetic indices (F10.7, SYM-H, and AL) as inputs. It can reproduce the observed density with a correlation coefficient of 0.95 and predict test data set with error less than a factor of 2. Its predictive ability on out-of-sample data is tested on field-aligned density profiles from the IMAGE satellite. DEN3D's predictive ability provides unprecedented opportunities to gain insight into the 3-D behavior of the inner magnetospheric plasma density at any time and location. As an example, we apply DEN3D to a storm that occurred on 1 June 2013. It successfully reproduces various well-known dynamic features in three dimensions, such as plasmaspheric erosion and recovery, as well as plume formation. Storm time long-term density variations are consistent with expectations; short-term variations appear to be modulated by substorm activity or enhanced convection, an effect that requires further study together with multispacecraft in situ or imaging measurements. Investigating plasmaspheric refilling with the model, we find that it is not monotonic in time and is more complex than expected from previous studies, deserving further attention.

A Simple Network Architecture Accounts for Diverse Reward Time Responses in Primary Visual Cortex

PubMed Central

Hussain Shuler, Marshall G.; Shouval, Harel Z.

2015-01-01

Many actions performed by animals and humans depend on an ability to learn, estimate, and produce temporal intervals of behavioral relevance. Exemplifying such learning of cued expectancies is the observation of reward-timing activity in the primary visual cortex (V1) of rodents, wherein neural responses to visual cues come to predict the time of future reward as behaviorally experienced in the past. These reward-timing responses exhibit significant heterogeneity in at least three qualitatively distinct classes: sustained increase or sustained decrease in firing rate until the time of expected reward, and a class of cells that reach a peak in firing at the expected delay. We elaborate upon our existing model by including inhibitory and excitatory units while imposing simple connectivity rules to demonstrate what role these inhibitory elements and the simple architectures play in sculpting the response dynamics of the network. We find that simply adding inhibition is not sufficient for obtaining the different distinct response classes, and that a broad distribution of inhibitory projections is necessary for obtaining peak-type responses. Furthermore, although changes in connection strength that modulate the effects of inhibition onto excitatory units have a strong impact on the firing rate profile of these peaked responses, the network exhibits robustness in its overall ability to predict the expected time of reward. Finally, we demonstrate how the magnitude of expected reward can be encoded at the expected delay in the network and how peaked responses express this reward expectancy. SIGNIFICANCE STATEMENT Heterogeneity in single-neuron responses is a common feature of neuronal systems, although sometimes, in theoretical approaches, it is treated as a nuisance and seldom considered as conveying a different aspect of a signal. In this study, we focus on the heterogeneous responses in the primary visual cortex of rodents trained with a predictable delayed reward time. We describe under what conditions this heterogeneity can arise by self-organization, and what information it can convey. This study, while focusing on a specific system, provides insight onto how heterogeneity can arise in general while also shedding light onto mechanisms of reinforcement learning using realistic biological assumptions. PMID:26377457

Voter model with arbitrary degree dependence: clout, confidence and irreversibility

NASA Astrophysics Data System (ADS)

Fotouhi, Babak; Rabbat, Michael G.

2014-03-01

The voter model is widely used to model opinion dynamics in society. In this paper, we propose three modifications to incorporate heterogeneity into the model. We address the corresponding oversimplifications of the conventional voter model which are unrealistic. We first consider the voter model with popularity bias. The influence of each node on its neighbors depends on its degree. We find the consensus probabilities and expected consensus times for each of the states. We also find the fixation probability, which is the probability that a single node whose state differs from every other node imposes its state on the entire system. In addition, we find the expected fixation time. Then two other extensions to the model are proposed and the motivations behind them are discussed. The first one is confidence, where in addition to the states of neighbors, nodes take their own state into account at each update. We repeat the calculations for the augmented model and investigate the effects of adding confidence to the model. The second proposed extension is irreversibility, where one of the states is given the property that once nodes adopt it, they cannot switch back. This is motivated by applications where, agents take an irreversible action such as seeing a movie, purchasing a music album online, or buying a new product. The dynamics of densities, fixation times and consensus times are obtained.

HIV dynamics with multiple infections of target cells.

PubMed

Dixit, Narendra M; Perelson, Alan S

2005-06-07

The high incidence of multiple infections of cells by HIV sets the stage for rapid HIV evolution by means of recombination. Yet how HIV dynamics proceeds with multiple infections remains poorly understood. Here, we present a mathematical model that describes the dynamics of viral, target cell, and multiply infected cell subpopulations during HIV infection. Model calculations reproduce several experimental observations and provide key insights into the influence of multiple infections on HIV dynamics. We find that the experimentally observed scaling law, that the number of cells coinfected with two distinctly labeled viruses is proportional to the square of the total number of infected cells, can be generalized so that the number of triply infected cells is proportional to the cube of the number of infected cells, etc. Despite the expectation from Poisson statistics, we find that this scaling relationship only holds under certain conditions, which we predict. We also find that multiple infections do not influence viral dynamics when the rate of viral production from infected cells is independent of the number of times the cells are infected, a regime expected when viral production is limited by cellular rather than viral factors. This result may explain why extant models, which ignore multiple infections, successfully describe viral dynamics in HIV patients. Inhibiting CD4 down-modulation increases the average number of infections per cell. Consequently, altering CD4 down-modulation may allow for an experimental determination of whether viral or cellular factors limit viral production.

HIV dynamics with multiple infections of target cells

PubMed Central

Dixit, Narendra M.; Perelson, Alan S.

2005-01-01

The high incidence of multiple infections of cells by HIV sets the stage for rapid HIV evolution by means of recombination. Yet how HIV dynamics proceeds with multiple infections remains poorly understood. Here, we present a mathematical model that describes the dynamics of viral, target cell, and multiply infected cell subpopulations during HIV infection. Model calculations reproduce several experimental observations and provide key insights into the influence of multiple infections on HIV dynamics. We find that the experimentally observed scaling law, that the number of cells coinfected with two distinctly labeled viruses is proportional to the square of the total number of infected cells, can be generalized so that the number of triply infected cells is proportional to the cube of the number of infected cells, etc. Despite the expectation from Poisson statistics, we find that this scaling relationship only holds under certain conditions, which we predict. We also find that multiple infections do not influence viral dynamics when the rate of viral production from infected cells is independent of the number of times the cells are infected, a regime expected when viral production is limited by cellular rather than viral factors. This result may explain why extant models, which ignore multiple infections, successfully describe viral dynamics in HIV patients. Inhibiting CD4 down-modulation increases the average number of infections per cell. Consequently, altering CD4 down-modulation may allow for an experimental determination of whether viral or cellular factors limit viral production. PMID:15928092

Dynamic cross-correlations between entangled biofilaments as they diffuse

PubMed Central

Tsang, Boyce; Dell, Zachary E.; Jiang, Lingxiang; Schweizer, Kenneth S.; Granick, Steve

2017-01-01

Entanglement in polymer and biological physics involves a state in which linear interthreaded macromolecules in isotropic liquids diffuse in a spatially anisotropic manner beyond a characteristic mesoscopic time and length scale (tube diameter). The physical reason is that linear macromolecules become transiently localized in directions transverse to their backbone but diffuse with relative ease parallel to it. Within the resulting broad spectrum of relaxation times there is an extended period before the longest relaxation time when filaments occupy a time-averaged cylindrical space of near-constant density. Here we show its implication with experiments based on fluorescence tracking of dilutely labeled macromolecules. The entangled pairs of aqueous F-actin biofilaments diffuse with separation-dependent dynamic cross-correlations that exceed those expected from continuum hydrodynamics up to strikingly large spatial distances of ≈15 µm, which is more than 104 times the size of the solvent water molecules in which they are dissolved, and is more than 50 times the dynamic tube diameter, but is almost equal to the filament length. Modeling this entangled system as a collection of rigid rods, we present a statistical mechanical theory that predicts these long-range dynamic correlations as an emergent consequence of an effective long-range interpolymer repulsion due to the de Gennes correlation hole, which is a combined consequence of chain connectivity and uncrossability. The key physical assumption needed to make theory and experiment agree is that solutions of entangled biofilaments localized in tubes that are effectively dynamically incompressible over the relevant intermediate time and length scales. PMID:28283664

The temporal dynamics of reversal learning: P3 amplitude predicts valence-specific behavioral adjustment.

PubMed

Donaldson, Kayla R; Ait Oumeziane, Belel; Hélie, Sebastien; Foti, Dan

2016-07-01

Adapting behavior to dynamic stimulus-reward contingences is a core feature of reversal learning and a capacity thought to be critical to socio-emotional behavior. Impairment in reversal learning has been linked to multiple psychiatric outcomes, including depression, Parkinson's disorder, and substance abuse. A recent influential study introduced an innovative laboratory reversal-learning paradigm capable of disentangling the roles of feedback valence and expectancy. Here, we sought to use this paradigm in order to examine the time-course of reward and punishment learning using event-related potentials among a large, representative sample (N=101). Three distinct phases of processing were examined: initial feedback evaluation (reward positivity, or RewP), allocation of attention (P3), and sustained processing (late positive potential, or LPP). Results indicate a differential pattern of valence and expectancy across these processing stages: the RewP was uniquely related to valence (i.e., positive vs. negative feedback), the P3 was uniquely associated with expectancy (i.e., unexpected vs. expected feedback), and the LPP was sensitive to both valence and expectancy (i.e., main effects of each, but no interaction). The link between ERP amplitudes and behavioral performance was strongest for the P3, and this association was valence-specific. Overall, these findings highlight the potential utility of the P3 as a neural marker for feedback processing in reversal-based learning and establish a foundation for future research in clinical populations. Copyright © 2016 Elsevier Inc. All rights reserved.

Modes of Hoping: Understanding hope and expectation in the context of a clinical trial of complementary and alternative medicine for chronic pain

PubMed Central

Eaves, Emery R; Ritenbaugh, Cheryl; Nichter, Mark; Hopkins, Allison L.; Sherman, Karen J

2014-01-01

This article explores the role of hope in participants’ assessments of their expectations, experiences and treatment outcomes. Data analysis focused on semi-structured, open-ended interviews with 44 participants, interviewed 3-5 times each over the course of a study evaluating Traditional Chinese Medicine (TCM) for Temporomandibular Disorders (TMD, a form of chronic orofacial pain). Transcripts were coded and analyzed using qualitative and ethnographic methods. A “Modes of Hoping”1 framework informed our analysis. Five modes of hoping emerged from participant narratives: Realistic Hope; Wishful Hope; Utopian Hope; Technoscience Hope; and Transcendent Hope. Using this framework, hope is demonstrated as exerting a profound influence over how participants assess and report their expectations. This suggests that researchers interested in measuring expectations and understanding their role in treatment outcomes should consider hope as exercising a multifaceted and dynamic influence on participants’ reporting of expectations and their experience and evaluation of treatment. PMID:25037665

Modes of hoping: understanding hope and expectation in the context of a clinical trial of complementary and alternative medicine for chronic pain.

PubMed

Eaves, Emery R; Ritenbaugh, Cheryl; Nichter, Mark; Hopkins, Allison L; Sherman, Karen J

2014-01-01

This article explores the role of hope in participants' assessments of their expectations, experiences and treatment outcomes. Data analysis focused on semi-structured, open-ended interviews with 44 participants, interviewed 3-5 times each over the course of a study evaluating Traditional Chinese Medicine (TCM) for temporomandibular disorders (TMD), a form of chronic orofacial pain. Transcripts were coded and analyzed using qualitative and ethnographic methods. A "Modes of Hoping" (Webb, 2007)(1) framework informed our analysis. Five modes of hoping emerged from participant narratives: Realistic Hope, Wishful Hope, Utopian Hope, Technoscience Hope, and Transcendent Hope. Using this framework, hope is demonstrated as exerting a profound influence over how participants assess and report their expectations. This suggests that researchers interested in measuring expectations and understanding their role in treatment outcomes should consider hope as exercising a multi-faceted and dynamic influence on participants' reporting of expectations and their experience and evaluation of treatment. Copyright © 2014 Elsevier Inc. All rights reserved.

A spiking neural integrator model of the adaptive control of action by the medial prefrontal cortex.

PubMed

Bekolay, Trevor; Laubach, Mark; Eliasmith, Chris

2014-01-29

Subjects performing simple reaction-time tasks can improve reaction times by learning the expected timing of action-imperative stimuli and preparing movements in advance. Success or failure on the previous trial is often an important factor for determining whether a subject will attempt to time the stimulus or wait for it to occur before initiating action. The medial prefrontal cortex (mPFC) has been implicated in enabling the top-down control of action depending on the outcome of the previous trial. Analysis of spike activity from the rat mPFC suggests that neural integration is a key mechanism for adaptive control in precisely timed tasks. We show through simulation that a spiking neural network consisting of coupled neural integrators captures the neural dynamics of the experimentally recorded mPFC. Errors lead to deviations in the normal dynamics of the system, a process that could enable learning from past mistakes. We expand on this coupled integrator network to construct a spiking neural network that performs a reaction-time task by following either a cue-response or timing strategy, and show that it performs the task with similar reaction times as experimental subjects while maintaining the same spiking dynamics as the experimentally recorded mPFC.

Implicit methods for efficient musculoskeletal simulation and optimal control

PubMed Central

van den Bogert, Antonie J.; Blana, Dimitra; Heinrich, Dieter

2011-01-01

The ordinary differential equations for musculoskeletal dynamics are often numerically stiff and highly nonlinear. Consequently, simulations require small time steps, and optimal control problems are slow to solve and have poor convergence. In this paper, we present an implicit formulation of musculoskeletal dynamics, which leads to new numerical methods for simulation and optimal control, with the expectation that we can mitigate some of these problems. A first order Rosenbrock method was developed for solving forward dynamic problems using the implicit formulation. It was used to perform real-time dynamic simulation of a complex shoulder arm system with extreme dynamic stiffness. Simulations had an RMS error of only 0.11 degrees in joint angles when running at real-time speed. For optimal control of musculoskeletal systems, a direct collocation method was developed for implicitly formulated models. The method was applied to predict gait with a prosthetic foot and ankle. Solutions were obtained in well under one hour of computation time and demonstrated how patients may adapt their gait to compensate for limitations of a specific prosthetic limb design. The optimal control method was also applied to a state estimation problem in sports biomechanics, where forces during skiing were estimated from noisy and incomplete kinematic data. Using a full musculoskeletal dynamics model for state estimation had the additional advantage that forward dynamic simulations, could be done with the same implicitly formulated model to simulate injuries and perturbation responses. While these methods are powerful and allow solution of previously intractable problems, there are still considerable numerical challenges, especially related to the convergence of gradient-based solvers. PMID:22102983

A Dynamical System Approach to the Surface Search of Debris from MH370

NASA Astrophysics Data System (ADS)

Mancho, Ana M.; Garcia-Garrido, V. J.; Wiggins, S.; Mendoza, C.

2015-11-01

The disappearance of Malaysia Airlines flight MH370 on the morning of the 8th of March 2014 is one of the great mysteries of our time. One relevant aspect of this mystery is that not a single piece of debris from the aircraft was found during the intensive surface search carried out in the months following the crash. Difficulties in the search efforts, due to the uncertainty in the plane's final impact point and the time passed since the accident, brought the question on how the debris was scattered in an always moving ocean, for which there were multiple datasets that do not uniquely determined its state. Our approach to this problem is based on dynamical systems tools that identify dynamic barriers and coherent structures governing transport. By combining different ocean data with these mathematical techniques, we are able to assess the spatio-temporal state of the ocean in the priority search area at the time of impact and the following weeks. Using this information we propose a revised search strategy by showing why one might not have expected to find debris in some large search areas targeted by the search services and determining regions where one might have expected impact debris to be located and that have not been subjected to any exploration. This research has been supported by MINECO under grants MTM2014-56392-R and ICMAT Severo Ochoa project SEV-2011-0087 and ONR grant No. N00014- 01-1-0769. Computational support from CESGA is acknowledged.

Time-resolved orbital angular momentum spectroscopy

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

Noyan, Mehmet A.; Kikkawa, James M.

We introduce pump-probe magneto-orbital spectroscopy, wherein Laguerre-Gauss optical pump pulses impart orbital angular momentum to the electronic states of a material and subsequent dynamics are studied with 100 fs time resolution. The excitation uses vortex modes that distribute angular momentum over a macroscopic area determined by the spot size, and the optical probe studies the chiral imbalance of vortex modes reflected off the sample. First observations in bulk GaAs yield transients that evolve on time scales distinctly different from population and spin relaxation, as expected, but with surprisingly large lifetimes.

Optimal dynamic remapping of parallel computations

NASA Technical Reports Server (NTRS)

Nicol, David M.; Reynolds, Paul F., Jr.

1987-01-01

A large class of computations are characterized by a sequence of phases, with phase changes occurring unpredictably. The decision problem was considered regarding the remapping of workload to processors in a parallel computation when the utility of remapping and the future behavior of the workload is uncertain, and phases exhibit stable execution requirements during a given phase, but requirements may change radically between phases. For these problems a workload assignment generated for one phase may hinder performance during the next phase. This problem is treated formally for a probabilistic model of computation with at most two phases. The fundamental problem of balancing the expected remapping performance gain against the delay cost was addressed. Stochastic dynamic programming is used to show that the remapping decision policy minimizing the expected running time of the computation has an extremely simple structure. Because the gain may not be predictable, the performance of a heuristic policy that does not require estimnation of the gain is examined. The heuristic method's feasibility is demonstrated by its use on an adaptive fluid dynamics code on a multiprocessor. The results suggest that except in extreme cases, the remapping decision problem is essentially that of dynamically determining whether gain can be achieved by remapping after a phase change. The results also suggest that this heuristic is applicable to computations with more than two phases.

Modeling wildfire incident complexity dynamics.

PubMed

Thompson, Matthew P

2013-01-01

Wildfire management in the United States and elsewhere is challenged by substantial uncertainty regarding the location and timing of fire events, the socioeconomic and ecological consequences of these events, and the costs of suppression. Escalating U.S. Forest Service suppression expenditures is of particular concern at a time of fiscal austerity as swelling fire management budgets lead to decreases for non-fire programs, and as the likelihood of disruptive within-season borrowing potentially increases. Thus there is a strong interest in better understanding factors influencing suppression decisions and in turn their influence on suppression costs. As a step in that direction, this paper presents a probabilistic analysis of geographic and temporal variation in incident management team response to wildfires. The specific focus is incident complexity dynamics through time for fires managed by the U.S. Forest Service. The modeling framework is based on the recognition that large wildfire management entails recurrent decisions across time in response to changing conditions, which can be represented as a stochastic dynamic system. Daily incident complexity dynamics are modeled according to a first-order Markov chain, with containment represented as an absorbing state. A statistically significant difference in complexity dynamics between Forest Service Regions is demonstrated. Incident complexity probability transition matrices and expected times until containment are presented at national and regional levels. Results of this analysis can help improve understanding of geographic variation in incident management and associated cost structures, and can be incorporated into future analyses examining the economic efficiency of wildfire management.

Polymer chain dynamics under nanoscopic confinements.

PubMed

Kimmich, Rainer; Fatkullin, Nail; Mattea, Carlos; Fischer, Elmar

2005-02-01

It is shown that the confinement of polymer melts in nanopores leads to chain dynamics dramatically different from bulk behavior. This so-called corset effect occurs both above and below the critical molecular mass and induces the dynamic features predicted for reptation. A spinodal demixing technique was employed for the preparation of linear poly(ethylene oxide) (PEO) confined to nanoscopic strands that are in turn embedded in a quasi-solid and impenetrable methacrylate matrix. Both the molecular weight of the PEO and the mean diameter of the strands were varied to a certain degree. The chain dynamics of the PEO in the molten state was examined with the aid of field-gradient NMR diffusometry (time scale, 10(-2)-10(0) s) and field-cycling NMR relaxometry (time scale, 10(-9)-10(-4) s). The dominating mechanism for translational displacements probed in the nanoscopic strands by either technique is shown to be reptation. On the time scale of spin-lattice relaxation time measurements, the frequency dependence signature of reptation (i.e., T1 approximately nu(3/4)) showed up in all samples. A "tube" diameter of only 0.6 nm was concluded to be effective on this time scale even when the strand diameter was larger than the radius of gyration of the PEO random coils. This corset effect is traced back to the lack of the local fluctuation capacity of the free volume in nanoscopic confinements. The confinement dimension is estimated at which the crossover from confined to bulk chain dynamics is expected.

Optimal management of nutrient reserves in microorganisms under time-varying environmental conditions.

PubMed

Nev, Olga A; Nev, Oleg A; van den Berg, Hugo A

2017-09-21

Intracellular reserves are a conspicuous feature of many bacteria; such internal stores are often present in the form of inclusions in which polymeric storage compounds are accumulated. Such reserves tend to increase in times of plenty and be used up in times of scarcity. Mathematical models that describe the dynamical nature of reserve build-up and use are known as "cell quota," "dynamic energy/nutrient budget," or "variable-internal-stores" models. Here we present a stoichiometrically consistent macro-chemical model that accounts for variable stores as well as adaptive allocation of building blocks to various types of catalytic machinery. The model posits feedback loops linking expression of assimilatory machinery to reserve density. The precise form of the "regulatory law" at the heart of such a loop expresses how the cell manages internal stores. We demonstrate how this "regulatory law" can be recovered from experimental data using several empirical data sets. We find that stores should be expected to be negligibly small in stable growth-sustaining environments, but prominent in environments characterised by marked fluctuations on time scales commensurate with the inherent dynamic time scale of the organismal system. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dynamic decision making for dam-break emergency management - Part 1: Theoretical framework

NASA Astrophysics Data System (ADS)

Peng, M.; Zhang, L. M.

2013-02-01

An evacuation decision for dam breaks is a very serious issue. A late decision may lead to loss of lives and properties, but a very early evacuation will incur unnecessary expenses. This paper presents a risk-based framework of dynamic decision making for dam-break emergency management (DYDEM). The dam-break emergency management in both time scale and space scale is introduced first to define the dynamic decision problem. The probability of dam failure is taken as a stochastic process and estimated using a time-series analysis method. The flood consequences are taken as functions of warning time and evaluated with a human risk analysis model (HURAM) based on Bayesian networks. A decision criterion is suggested to decide whether to evacuate the population at risk (PAR) or to delay the decision. The optimum time for evacuating the PAR is obtained by minimizing the expected total loss, which integrates the time-related probabilities and flood consequences. When a delayed decision is chosen, the decision making can be updated with available new information. A specific dam-break case study is presented in a companion paper to illustrate the application of this framework to complex dam-breaching problems.

Proximity Networks and Epidemics

NASA Astrophysics Data System (ADS)

Guclu, Hasan; Toroczkai, Zoltán

2007-03-01

We presented the basis of a framework to account for the dynamics of contacts in epidemic processes, through the notion of dynamic proximity graphs. By varying the integration time-parameter T, which is the period of infectivity one can give a simple account for some of the differences in the observed contact networks for different diseases, such as smallpox, or AIDS. Our simplistic model also seems to shed some light on the shape of the degree distribution of the measured people-people contact network from the EPISIM data. We certainly do not claim that the simplistic graph integration model above is a good model for dynamic contact graphs. It only contains the essential ingredients for such processes to produce a qualitative agreement with some observations. We expect that further refinements and extensions to this picture, in particular deriving the link-probabilities in the dynamic proximity graph from more realistic contact dynamics should improve the agreement between models and data.

A real-time extension of density matrix embedding theory for non-equilibrium electron dynamics

NASA Astrophysics Data System (ADS)

Kretchmer, Joshua S.; Chan, Garnet Kin-Lic

2018-02-01

We introduce real-time density matrix embedding theory (DMET), a dynamical quantum embedding theory for computing non-equilibrium electron dynamics in strongly correlated systems. As in the previously developed static DMET, real-time DMET partitions the system into an impurity corresponding to the region of interest coupled to the surrounding environment, which is efficiently represented by a quantum bath of the same size as the impurity. In this work, we focus on a simplified single-impurity time-dependent formulation as a first step toward a multi-impurity theory. The equations of motion of the coupled impurity and bath embedding problem are derived using the time-dependent variational principle. The accuracy of real-time DMET is compared to that of time-dependent complete active space self-consistent field (TD-CASSCF) theory and time-dependent Hartree-Fock (TDHF) theory for a variety of quantum quenches in the single impurity Anderson model (SIAM), in which the Hamiltonian is suddenly changed (quenched) to induce a non-equilibrium state. Real-time DMET shows a marked improvement over the mean-field TDHF, converging to the exact answer even in the non-trivial Kondo regime of the SIAM. However, as expected from analogous behavior in static DMET, the constrained structure of the real-time DMET wavefunction leads to a slower convergence with respect to active space size, in the single-impurity formulation, relative to TD-CASSCF. Our initial results suggest that real-time DMET provides a promising framework to simulate non-equilibrium electron dynamics in which strong electron correlation plays an important role, and lays the groundwork for future multi-impurity formulations.

A real-time extension of density matrix embedding theory for non-equilibrium electron dynamics.

PubMed

Kretchmer, Joshua S; Chan, Garnet Kin-Lic

2018-02-07

We introduce real-time density matrix embedding theory (DMET), a dynamical quantum embedding theory for computing non-equilibrium electron dynamics in strongly correlated systems. As in the previously developed static DMET, real-time DMET partitions the system into an impurity corresponding to the region of interest coupled to the surrounding environment, which is efficiently represented by a quantum bath of the same size as the impurity. In this work, we focus on a simplified single-impurity time-dependent formulation as a first step toward a multi-impurity theory. The equations of motion of the coupled impurity and bath embedding problem are derived using the time-dependent variational principle. The accuracy of real-time DMET is compared to that of time-dependent complete active space self-consistent field (TD-CASSCF) theory and time-dependent Hartree-Fock (TDHF) theory for a variety of quantum quenches in the single impurity Anderson model (SIAM), in which the Hamiltonian is suddenly changed (quenched) to induce a non-equilibrium state. Real-time DMET shows a marked improvement over the mean-field TDHF, converging to the exact answer even in the non-trivial Kondo regime of the SIAM. However, as expected from analogous behavior in static DMET, the constrained structure of the real-time DMET wavefunction leads to a slower convergence with respect to active space size, in the single-impurity formulation, relative to TD-CASSCF. Our initial results suggest that real-time DMET provides a promising framework to simulate non-equilibrium electron dynamics in which strong electron correlation plays an important role, and lays the groundwork for future multi-impurity formulations.

The Role of the Dynamic Sensory Perception in the Reformulation of Shakes: Use of TDS for Studying the Effect of Milk, Fiber, and Flavor Addition.

PubMed

Tomadoni, Barbara; Fiszman, Susana; Moreira, María R; Tarrega, Amparo

2018-01-01

Various factors need to be taken into account when reformulating a food or beverage. The food components, not only macronutrients but also minor ingredients such as flavoring agents, could affect the perception of the sensory sensations, importantly their dynamic aspects, as rising and duration, which are not normally considered. The novelty of this approach is the study of the effects of the addition of several ingredients (fiber, extra milk powder, and strawberry flavoring) on the dynamic perception of a food item (strawberry shakes) using the temporal dominance of sensations (TDS) technique. The occurrence and duration of the key sensory sensations (acid, natural strawberry flavor, thick, sweet, candy strawberry flavor, and milk flavor) extracted from the TDS curves were analyzed and linked to the composition factors and liking and expectations of satiety scores. For example, the addition of flavoring increased the liking scores (increments ranging from 0.3 to 1.1) that was linked to the attenuation of acid sensation; and the addition of extra milk powder increased the expectation of satiety scores (increments ranging from 0.5 to 0.7) that was linked to the perception of early thick sensation in the mouth. In general, the more complex sensory profiles the higher liking and expectations of satiety. This work is a case study on how temporal sensory methods can contribute important information on the actual perception of food during consumption. Depending on the ingredients added these sensory properties appear at different times and with different dominance during evaluation affecting liking or fullness expectations. In consequence, the temporal sensory properties should be taken into account when designing or reformulating food. © 2017 Institute of Food Technologists®.

A sensitive slope: estimating landscape patterns of forest resilience in a changing climate

Treesearch

Jill F. Johnstone; Eliot J.B. McIntire; Eric J. Pedersen; Gregory King; Michael J.F. Pisaric

2010-01-01

Changes in Earth's environment are expected to stimulate changes in the composition and structure of ecosystems, but it is still unclear how the dynamics of these responses will play out over time. In long-lived forest systems, communities of established individuals may be resistant to respond to directional climate change, but may be highly sensitive to climate...

Emotional Valence and the Free-Energy Principle

PubMed Central

Joffily, Mateus; Coricelli, Giorgio

2013-01-01

The free-energy principle has recently been proposed as a unified Bayesian account of perception, learning and action. Despite the inextricable link between emotion and cognition, emotion has not yet been formulated under this framework. A core concept that permeates many perspectives on emotion is valence, which broadly refers to the positive and negative character of emotion or some of its aspects. In the present paper, we propose a definition of emotional valence in terms of the negative rate of change of free-energy over time. If the second time-derivative of free-energy is taken into account, the dynamics of basic forms of emotion such as happiness, unhappiness, hope, fear, disappointment and relief can be explained. In this formulation, an important function of emotional valence turns out to regulate the learning rate of the causes of sensory inputs. When sensations increasingly violate the agent's expectations, valence is negative and increases the learning rate. Conversely, when sensations increasingly fulfil the agent's expectations, valence is positive and decreases the learning rate. This dynamic interaction between emotional valence and learning rate highlights the crucial role played by emotions in biological agents' adaptation to unexpected changes in their world. PMID:23785269

Emotional valence and the free-energy principle.

PubMed

Joffily, Mateus; Coricelli, Giorgio

2013-01-01

The free-energy principle has recently been proposed as a unified Bayesian account of perception, learning and action. Despite the inextricable link between emotion and cognition, emotion has not yet been formulated under this framework. A core concept that permeates many perspectives on emotion is valence, which broadly refers to the positive and negative character of emotion or some of its aspects. In the present paper, we propose a definition of emotional valence in terms of the negative rate of change of free-energy over time. If the second time-derivative of free-energy is taken into account, the dynamics of basic forms of emotion such as happiness, unhappiness, hope, fear, disappointment and relief can be explained. In this formulation, an important function of emotional valence turns out to regulate the learning rate of the causes of sensory inputs. When sensations increasingly violate the agent's expectations, valence is negative and increases the learning rate. Conversely, when sensations increasingly fulfil the agent's expectations, valence is positive and decreases the learning rate. This dynamic interaction between emotional valence and learning rate highlights the crucial role played by emotions in biological agents' adaptation to unexpected changes in their world.

Flexible nano- and microliter injections on a single liquid chromatography-mass spectrometry system: Minimizing sample preparation and maximizing linear dynamic range.

PubMed

Lubin, Arnaud; Sheng, Sheng; Cabooter, Deirdre; Augustijns, Patrick; Cuyckens, Filip

2017-11-17

Lack of knowledge on the expected concentration range or insufficient linear dynamic range of the analytical method applied are common challenges for the analytical scientist. Samples that are above the upper limit of quantification are typically diluted and reanalyzed. The analysis of undiluted highly concentrated samples can cause contamination of the system, while the dilution step is time consuming and as the case for any sample preparation step, also potentially leads to precipitation, adsorption or degradation of the analytes. Copyright © 2017 Elsevier B.V. All rights reserved.

Parallel heterodyne detection of dynamic light-scattering spectra from gold nanoparticles diffusing in viscous fluids.

PubMed

Atlan, Michael; Desbiolles, Pierre; Gross, Michel; Coppey-Moisan, Maïté

2010-03-01

We developed a microscope intended to probe, using a parallel heterodyne receiver, the fluctuation spectrum of light quasi-elastically scattered by gold nanoparticles diffusing in viscous fluids. The cutoff frequencies of the recorded spectra scale up linearly with those expected from single-scattering formalism in a wide range of dynamic viscosities (1 to 15 times water viscosity at room temperature). Our scheme enables ensemble-averaged optical fluctuations measurements over multispeckle recordings in low light, at temporal frequencies up to 10 kHz, with a 12 Hz framerate array detector.

Approximate dynamic programming for optimal stationary control with control-dependent noise.

PubMed

Jiang, Yu; Jiang, Zhong-Ping

2011-12-01

This brief studies the stochastic optimal control problem via reinforcement learning and approximate/adaptive dynamic programming (ADP). A policy iteration algorithm is derived in the presence of both additive and multiplicative noise using Itô calculus. The expectation of the approximated cost matrix is guaranteed to converge to the solution of some algebraic Riccati equation that gives rise to the optimal cost value. Moreover, the covariance of the approximated cost matrix can be reduced by increasing the length of time interval between two consecutive iterations. Finally, a numerical example is given to illustrate the efficiency of the proposed ADP methodology.

Dynamic Aftershock Triggering Correlated with Cyclic Loading in the Slip Direction

NASA Astrophysics Data System (ADS)

Hardebeck, J.

2014-12-01

Dynamic stress changes have been shown to contribute to aftershock triggering, but the physical triggering mechanisms are not fully understood. Some proposed mechanisms are based on dynamic stress loading of the target fault in a direction that encourages earthquake slip (e.g. dynamic Coulomb stress triggering), while other mechanisms are based on fault weakening due to shaking. If dynamic stress loading in the fault slip direction plays a role in aftershock triggering, we would expect to see a relationship between the dynamic stress orientations and the aftershock focal mechanisms. Alternatively, if dynamic stress change triggering functions only through a fault weakening mechanism that is independent of the slip direction of the target fault, no such relationship is expected. I study aftershock sequences of 4 M≥6.7 mainshocks in southern California, and find a small but significant relationship between modeled dynamic stress direction and aftershock focal mechanisms. The mainshock dynamic stress changes have two observed impacts: changing the focal mechanisms in a given location to favor those aligned with the dynamic stress change, and changing the spatial distribution of seismicity to favor locations where the dynamic stress change aligns with the background stress. The aftershock focal mechanisms are significantly more aligned with the dynamic stress changes than the preshock mechanisms for only the first 0.5-1 year following most mainshocks, although for at least 10 years following Hector Mine. Dynamic stress effects on focal mechanisms are best observed at long periods (30-60 sec). Dynamic stress effects are only observed when using metrics based on repeated stress cycling in the same direction, for example considering the dominant stress orientation over the full time series, and not for the peak dynamic stress. These results imply that dynamic aftershock triggering operates at least in part through cyclic loading in the direction of fault slip, although non-directional fault weakening may be important as well. This suggests that the orientation of the dynamic stresses, as well as their amplitude, should be considered in the development of physics-based aftershock forecasting models.

Division H Commission 33: Structure & Dynamics of the Galactic System

NASA Astrophysics Data System (ADS)

Nordström, Birgitta; Bland-Hawthorn, Joss; Wyse, Rosemary; Athanassoula, Lia; Feltzing, Sofia; Jog, Chanda; Lockman, Jay; Minniti, Dante; Robin, Annie

2016-04-01

Research on the structure and dynamics of the Galactic System covers a large field of research, from formation scenarios to long-term evolution and secular processes. Today we speak of near-field cosmology where the oldest parts of the Galaxy are used to probe back to early times, e.g. studying the chemical signatures of the oldest star clusters and dwarf galaxies to learn about the byproducts of the first stars. Some of the most detailed work relates to the structure of the dark matter and baryons in order to compare with expectation from N-body models. Secular processes have been identified (e.g. stellar migration) where material within the Galaxy is being reorganized by dynamical resonances and feedback processes.

Dynamical photo-induced electronic properties of molecular junctions

NASA Astrophysics Data System (ADS)

Beltako, K.; Michelini, F.; Cavassilas, N.; Raymond, L.

2018-03-01

Nanoscale molecular-electronic devices and machines are emerging as promising functional elements, naturally flexible and efficient, for next-generation technologies. A deeper understanding of carrier dynamics in molecular junctions is expected to benefit many fields of nanoelectronics and power devices. We determine time-resolved charge current flowing at the donor-acceptor interface in molecular junctions connected to metallic electrodes by means of quantum transport simulations. The current is induced by the interaction of the donor with a Gaussian-shape femtosecond laser pulse. Effects of the molecular internal coupling, metal-molecule tunneling, and light-donor coupling on photocurrent are discussed. We then define the time-resolved local density of states which is proposed as an efficient tool to describe the absorbing molecule in contact with metallic electrodes. Non-equilibrium reorganization of hybridized molecular orbitals through the light-donor interaction gives rise to two phenomena: the dynamical Rabi shift and the appearance of Floquet-like states. Such insights into the dynamical photoelectronic structure of molecules are of strong interest for ultrafast spectroscopy and open avenues toward the possibility of analyzing and controlling the internal properties of quantum nanodevices with pump-push photocurrent spectroscopy.

Effective long wavelength scalar dynamics in de Sitter

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

Moss, Ian; Rigopoulos, Gerasimos, E-mail: ian.moss@newcastle.ac.uk, E-mail: gerasimos.rigopoulos@ncl.ac.uk

We discuss the effective infrared theory governing a light scalar's long wavelength dynamics in de Sitter spacetime. We show how the separation of scales around the physical curvature radius k / a ∼ H can be performed consistently with a window function and how short wavelengths can be integrated out in the Schwinger-Keldysh path integral formalism. At leading order, and for time scales Δ t >> H {sup −1}, this results in the well-known Starobinsky stochastic evolution. However, our approach allows for the computation of quantum UV corrections, generating an effective potential on which the stochastic dynamics takes place. Themore » long wavelength stochastic dynamical equations are now second order in time, incorporating temporal scales Δ t ∼ H {sup −1} and resulting in a Kramers equation for the probability distribution—more precisely the Wigner function—in contrast to the more usual Fokker-Planck equation. This feature allows us to non-perturbatively evaluate, within the stochastic formalism, not only expectation values of field correlators, but also the stress-energy tensor of φ.« less

Temporal dynamics of different cases of bi-stable figure-ground perception.

PubMed

Kogo, Naoki; Hermans, Lore; Stuer, David; van Ee, Raymond; Wagemans, Johan

2015-01-01

Segmentation of a visual scene in "figure" and "ground" is essential for perception of the three-dimensional layout of a scene. In cases of bi-stable perception, two distinct figure-ground interpretations alternate over time. We were interested in the temporal dynamics of these alternations, in particular when the same image is presented repeatedly, with short blank periods in-between. Surprisingly, we found that the intermittent presentation of Rubin's classical "face-or-vase" figure, which is frequently taken as a standard case of bi-stable figure-ground perception, often evoked perceptual switches during the short presentations and stabilization was not prominent. Interestingly, bi-stable perception of Kanizsa's anomalous transparency figure did strongly stabilize across blanks. We also found stabilization for the Necker cube, which we used for comparison. The degree of stabilization (and the lack of it) varied across stimuli and across individuals. Our results indicate, against common expectation, that the stabilization phenomenon cannot be generally evoked by intermittent presentation. We argue that top-down feedback factors such as familiarity, semantics, expectation, and perceptual bias contribute to the complex processes underlying the temporal dynamics of bi-stable figure-ground perception. Copyright © 2014 Elsevier Ltd. All rights reserved.

Nonlinear viscoelastic characterization of polymer materials using a dynamic-mechanical methodology

NASA Technical Reports Server (NTRS)

Strganac, Thomas W.; Payne, Debbie Flowers; Biskup, Bruce A.; Letton, Alan

1995-01-01

Polymer materials retrieved from LDEF exhibit nonlinear constitutive behavior; thus the authors present a method to characterize nonlinear viscoelastic behavior using measurements from dynamic (oscillatory) mechanical tests. Frequency-derived measurements are transformed into time-domain properties providing the capability to predict long term material performance without a lengthy experimentation program. Results are presented for thin-film high-performance polymer materials used in the fabrication of high-altitude scientific balloons. Predictions based upon a linear test and analysis approach are shown to deteriorate for moderate to high stress levels expected for extended applications. Tests verify that nonlinear viscoelastic response is induced by large stresses. Hence, an approach is developed in which the stress-dependent behavior is examined in a manner analogous to modeling temperature-dependent behavior with time-temperature correspondence and superposition principles. The development leads to time-stress correspondence and superposition of measurements obtained through dynamic mechanical tests. Predictions of material behavior using measurements based upon linear and nonlinear approaches are compared with experimental results obtained from traditional creep tests. Excellent agreement is shown for the nonlinear model.

Impact of cloud timing on surface temperature and related hydroclimatic dynamics

NASA Astrophysics Data System (ADS)

Porporato, A. M.; Yin, J.

2015-12-01

Cloud feedbacks have long been identified as one of the largest source of uncertainty in climate change predictions. Differences in the spatial distribution of clouds and the related impact on surface temperature and climate dynamics have been recently emphasized in quasi-equilibrium General Circulation Models (GCM). However, much less attention has been paid to the temporal variation of cloud presence and thickness. Clouds in fact shade the solar radiation during the daytime, but also acts as greenhouse gas to reduce the emission of longwave radiation to the outer space anytime of the day. Thus it is logical to expect that even small differences in timing and thickness of clouds could result in very different predictions in GCMs. In this study, these two effects of cloud dynamics are analyzed by tracking the cloud impacts on longwave and shortwave radiation in a minimalist transient thermal balance model of the land surface. The marked changes in surface temperature due to alterations in the timing of onset of clouds demonstrate that capturing temporal variation of cloud at sub-daily scale should be a priority in cloud parameterization schemes in GCMs.

High Fidelity, Fuel-Like Thermal Simulators for Non-Nuclear Testing: Analysis and Initial Test Results

NASA Technical Reports Server (NTRS)

Bragg-Sitton, Shannon M.; Dickens, Ricky; Dixon, David; Kapernick, Richard

2007-01-01

Non-nuclear testing can be a valuable tool in the development of a space nuclear power system, providing system characterization data and allowing one to work through various fabrication, assembly and integration issues without the cost and time associated with a full ground nuclear test. In a non-nuclear test bed, electric heaters are used to simulate the heat from nuclear fuel. Testing with non-optimized heater elements allows one to assess thermal, heat transfer. and stress related attributes of a given system, but fails to demonstrate the dynamic response that would be present in an integrated, fueled reactor system. High fidelity thermal simulators that match both the static and the dynamic fuel pin performance that would be observed in an operating, fueled nuclear reactor can vastly increase the value of non-nuclear test results. With optimized simulators, the integration of thermal hydraulic hardware tests with simulated neutronic response provides a bridge between electrically heated testing and fueled nuclear testing. By implementing a neutronic response model to simulate the dynamic response that would be expected in a fueled reactor system, one can better understand system integration issues, characterize integrated system response times and response characteristics and assess potential design improvements at relatively small fiscal investment. Initial conceptual thermal simulator designs are determined by simple one-dimensional analysis at a single axial location and at steady state conditions; feasible concepts are then input into a detailed three-dimensional model for comparison to expected fuel pin performance. Static and dynamic fuel pin performance for a proposed reactor design is determined using SINDA/FLUINT thermal analysis software, and comparison is made between the expected nuclear performance and the performance of conceptual thermal simulator designs. Through a series of iterative analyses, a conceptual high fidelity design is developed: this is followed by engineering design, fabrication, and testing to validate the overall design process. Test results presented in this paper correspond to a "first cut" simulator design for a potential liquid metal (NaK) cooled reactor design that could be applied for Lunar surface power. Proposed refinements to this simulator design are also presented.

Dynamic, physical-based landslide susceptibility modelling based on real-time weather data

NASA Astrophysics Data System (ADS)

Canli, Ekrem; Glade, Thomas

2016-04-01

By now there seem to be a broad consensus that due to human-induced global change the frequency and magnitude of precipitation intensities within extensive rainstorm events is expected to increase in certain parts of the world. Given the fact, that rainfall serves as one of the most common triggers for landslide initiation, also an increased landside activity might be expected. Landslide occurrence is a globally spread phenomenon that clearly needs to be handled by a variety of concepts, methods, and models. However, most of the research done with respect to landslides deals with retrospect cases, thus classical back-analysis approaches do not incorporate real-time data. This is remarkable, as most destructive landslides are related to immediate events due to external triggering factors. Only few works so far addressed real-time dynamic components for spatial landslide susceptibility and hazard assessment. Here we present an approach for integrating real-time web-based rainfall data from different sources into an automated workflow. Rain gauge measurements are interpolated into a continuous raster which in return is directly utilized in a dynamic, physical-based model. We use the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) model that was modified in a way that it is automatically updated with the most recent rainfall raster for producing hourly landslide susceptibility maps on a regional scale. To account for the uncertainties involved in spatial modelling, the model was further adjusted by not only applying single values for given geotechnical parameters, but ranges instead. The values are determined randomly between user-defined thresholds defining the parameter ranges. Consequently, a slope failure probability from a larger number of model runs is computed rather than just the distributed factor of safety. This will ultimately allow a near-real time spatial landslide alert for a given region.

Correlational signatures of time-reversal symmetry breaking in two-dimensional flow

NASA Astrophysics Data System (ADS)

Hogg, Charlie; Ouellette, Nicholas

2015-11-01

Classical turbulence theories posit that broken spatial symmetries should be (statistically) restored at small scales. But since turbulent flows are inherently dissipative, time reversal symmetry is expected to remain broken throughout the cascade. However, the precise dynamical signature of this broken symmetry is not well understood. Recent work has shed new light on this fundamental question by considering the Lagrangian structure functions of power. Here, we take a somewhat different approach by studying the Lagrangian correlation functions of velocity and acceleration. We measured these correlations using particle tracking velocimetry in a quasi-two-dimensional electromagnetically driven flow that displayed net inverse energy transfer. We show that the correlation functions of the velocity and acceleration magnitudes are not symmetric in time, and that the degree of asymmetry can be related to the flux of energy between scales, suggesting that the asymmetry has a dynamical origin.

On the Fate of Debris Associated with the Disappearance of Flight MH370: a Dynamical System Perspective

NASA Astrophysics Data System (ADS)

Mancho, A. M.; Garcia-Garrido, V. J.; Wiggins, S.; Mendoza, C.

2015-12-01

The disappearance of Malaysia Airlines flight MH370 on the morning of the 8th of March 2014 is one of the great mysteries of our time. One relevant aspect of this mystery is that not a single piece of debris from the aircraft was found during the intensive surface search carried out in the months following the crash. Difficulties in the search efforts were due to the uncertainty in the plane's final impact point and the time passed since the accident and rise the question on how the debris was scattered in an always moving ocean, for which there exist multiple datasets that do not uniquely determine its state. Our approach to this problem is based on dynamical systems tools that identify dynamic barriers and coherent structures governing transport. By combining publicly available information supplied by different ocean data sources with these mathematical techniques, we are able to assess the spatio-temporal state of the ocean in the priority search area at the time of impact and the following weeks. Using this information we propose a revised search strategy by showing why one might not have expected to find debris in some large search areas targeted by the search services and determining regions where one might have expected impact debris to be located and that were not subjected to any exploration. This research has been supported by MINECO under grants MTM2014-56392-R and ICMAT Severo Ochoa project SEV-2011-0087 and ONR grant No. N00014- 01-1-0769. Computational support from CESGA is acknowledged. References [1] V. J. García-Garrido, A. M. Mancho, S. Wiggins, and C. Mendoza. A dynamical systems perspective on the absence of debris associated with the disappearance of flight MH370. Nonlin. Processes Geophys. Discuss., 2,1197-1225, doi:10.5194/npgd-2-1197-2015, 2015

Fishing Quotas, Induced Allee Effect, and Fluctuation-Driven Extinction.

PubMed

Hastings, Harold M; Radin, Michael; Wiandt, Tamas

2017-01-01

We explore the potential of modifications to standard fishery models (for example Gordon-Schafer-Munro) to help understand events such as the collapse of the North Atlantic cod fishery. In particular we find that quota-driven and similar harvesting strategies induce an effective strong Allee effect (collapse if the population falls below a critical level). In the presence of environmental noise, fish population dynamics is similar to a random walk with (non-linear) drift. The expected survival time (first passage time to collapse) is shown to depend sensitively upon the amount of environmental noise and size of the 'safe zone' between the deterministic steady state population and the critical population level at which the system collapses; more precisely it is exponential in the cube of the size of the safe zone divided by the variance of the noise process. Similar scaling can be expected for more survival in more general systems with multiple steady states. Our calculations imply an amplification effect under which small increases in harvest yield large decreases in expected survival time, and one should be cautious in changes in harvesting, especially in fisheries with poor or limited data and fisheries affected by climate change.

Dynamical Friction in Multi-component Evolving Globular Clusters

NASA Astrophysics Data System (ADS)

Alessandrini, Emiliano; Lanzoni, Barbara; Miocchi, Paolo; Ciotti, Luca; Ferraro, Francesco R.

2014-11-01

We use the Chandrasekhar formalism and direct N-body simulations to study the effect of dynamical friction on a test object only slightly more massive than the field stars, orbiting a spherically symmetric background of particles with a mass spectrum. The main goal is to verify whether the dynamical friction time (t DF) develops a non-monotonic radial dependence that could explain the bimodality of the blue straggler radial distributions observed in globular clusters. In these systems, in fact, relaxation effects lead to a mass and velocity radial segregation of the different mass components, so that mass-spectrum effects on t DF are expected to be dependent on radius. We find that in spite of the presence of different masses, t DF is always a monotonic function of radius, at all evolutionary times and independently of the initial concentration of the simulated cluster. This is because the radial dependence of t DF is largely dominated by the total mass density profile of the background stars (which is monotonically decreasing with radius). Hence, a progressive temporal erosion of the blue straggler star (BSS) population at larger and larger distances from the cluster center remains the simplest and the most likely explanation of the shape of the observed BSS radial distributions, as suggested in previous works. We also confirm the theoretical expectation that approximating a multi-mass globular cluster as made of (averaged) equal-mass stars can lead to significant overestimations of t DF within the half-mass radius.

Effect of gold nanoparticles on structure and dynamics of binary Lennard-Jones liquid: Wave-vector space analysis

NASA Astrophysics Data System (ADS)

Separdar, L.; Davatolhagh, S.

2016-12-01

Molecular dynamics simulations at constant (N , V , T) are used to study the mutual effects of gold nanoparticles on the structure and dynamics of Kob-Andersen binary Lennard-Jones (BLJ) liquid within the framework of mode coupling theory of dynamic glass transition in the reciprocal space. The results show the 'softening' effect of the gold nanoparticles on the liquid dynamics in terms of (i) reducing the mode coupling crossover temperature Tc with respect to that of the bulk BLJ (i.e. BLJ without nanoparticles), (ii) decreasing the time interval of β-relaxation, and (iii) decreasing the exponent γ characterizing the power-law behavior of the α-relaxation time. This softening effect is explained in terms of the van der Waals attraction between the gold atoms comprising the nanoparticle and the BLJ host atoms, such that adsorption of host atoms onto the nanoparticle surface creates more space or free-volume for the other atoms to diffuse. By the same token interactions of purely excluded-volume-type are expected to result in the opposite effect. It is also noted that, much unlike BLJ host particles, the dynamics of gold nanoparticles is much less dependent on the wave-vector and that it exhibits a nearly exponential behavior in the α-relaxation regime.

Optimal satellite sampling to resolve global-scale dynamics in the I-T system

NASA Astrophysics Data System (ADS)

Rowland, D. E.; Zesta, E.; Connor, H. K.; Pfaff, R. F., Jr.

2016-12-01

The recent Decadal Survey highlighted the need for multipoint measurements of ion-neutral coupling processes to study the pathways by which solar wind energy drives dynamics in the I-T system. The emphasis in the Decadal Survey is on global-scale dynamics and processes, and in particular, mission concepts making use of multiple identical spacecraft in low earth orbit were considered for the GDC and DYNAMIC missions. This presentation will provide quantitative assessments of the optimal spacecraft sampling needed to significantly advance our knowledge of I-T dynamics on the global scale.We will examine storm time and quiet time conditions as simulated by global circulation models, and determine how well various candidate satellite constellations and satellite schemes can quantify the plasma and neutral convection patterns and global-scale distributions of plasma density, neutral density, and composition, and their response to changes in the IMF. While the global circulation models are data-starved, and do not contain all the physics that we might expect to observe with a global-scale constellation mission, they are nonetheless an excellent "starting point" for discussions of the implementation of such a mission. The result will be of great utility for the design of future missions, such as GDC, to study the global-scale dynamics of the I-T system.

AGN jet-driven stochastic cold accretion in cluster cores

NASA Astrophysics Data System (ADS)

Prasad, Deovrat; Sharma, Prateek; Babul, Arif

2017-10-01

Several arguments suggest that stochastic condensation of cold gas and its accretion on to the central supermassive black hole (SMBH) is essential for active galactic nuclei (AGNs) feedback to work in the most massive galaxies that lie at the centres of galaxy clusters. Our 3-D hydrodynamic AGN jet-ICM (intracluster medium) simulations, looking at the detailed angular momentum distribution of cold gas and its time variability for the first time, show that the angular momentum of the cold gas crossing ≲1 kpc is essentially isotropic. With almost equal mass in clockwise and counterclockwise orientations, we expect a cancellation of the angular momentum on roughly the dynamical time. This means that a compact accretion flow with a short viscous time ought to form, through which enough accretion power can be channeled into jet mechanical energy sufficiently quickly to prevent a cooling flow. The inherent stochasticity, expected in feedback cycles driven by cold gas condensation, gives rise to a large variation in the cold gas mass at the centres of galaxy clusters, for similar cluster and SMBH masses, in agreement with the observations. Such correlations are expected to be much tighter for the smoother hot/Bondi accretion. The weak correlation between cavity power and Bondi power obtained from our simulations also matches observations.

Treatment Expectations for Cognitive-Behavioral Therapy and Light Therapy for Seasonal Affective Disorder: Change Across Treatment and Relation to Outcome

PubMed Central

Meyerhoff, Jonah; Rohan, Kelly J.

2016-01-01

Objective To examine the dynamic relationship between treatment expectations and treatment outcome over the course of a clinical trial for winter seasonal affective disorder (SAD). Method Currently depressed adults with Major Depression, Recurrent with Seasonal Pattern (N = 177) were randomized to 6-weeks of group-delivered cognitive-behavioral therapy for SAD (CBT-SAD) or light therapy (LT). The majority was female (83.6%) and white (92.1%), with a mean age of 45.6 years. Treatment expectations for CBT-SAD and LT were assessed using a modification of the Treatment Expectancy and Credibility Survey (Borkovec & Nau, 1972). Depression severity was assessed using the Beck Depression Inventory-Second Edition (Beck, Steer, & Brown, 1996). All measures were administered at pre-treatment, mid-treatment, and post-treatment. Results As treatment progressed, expectations for the treatment received increased across time steeply in CBT-SAD patients and moderately in LT patients. Collapsing across time, patients with higher treatment expectations had lower depression severity than those with lower treatment expectations. In a cross-lagged panel path analysis, there was a significant effect of treatment expectations at mid-treatment on depression severity at post-treatment among CBT-SAD patients. Conclusions Treatment expectations changed across treatment, affected outcome, and should be assessed and monitored repeatedly throughout treatment. Findings suggest that treatment expectations at mid-treatment are a mechanism by which CBT-SAD reduces depression, which should be replicated in SAD samples and examined for generalizability to non-seasonal depression. These findings underscore the importance of further research examining treatment expectations in mediating CBT’s effects in depression and other types of psychopathology. Public Health Significance This study highlights the importance of monitoring treatment expectations repeatedly during treatment regardless of treatment type. Moreover, therapists administering cognitive-based therapy for depression should actively attend to the degree of patient “buy-in” early in treatment as it has clear indications for depression severity at treatment endpoint. PMID:27281373

Spatiotemporal periodicity of dislocation dynamics in a two-dimensional microfluidic crystal flowing in a tapered channel

DOE PAGES

Gai, Ya; Min Leong, Chia; Cai, Wei; ...

2016-10-10

When a many-body system is driven away from equilibrium, order can spontaneously emerge in places where disorder might be expected. Here we report an unexpected order in the flow of a concentrated emulsion in a tapered microfluidic channel. The velocity profiles of individual drops in the emulsion show periodic patterns in both space and time. Such periodic patterns appear surprising from both a fluid and a solid mechanics point of view. In particular, when the emulsion is considered as a soft crystal under extrusion, a disordered scenario might be expected based on the stochastic nature of dislocation dynamics in microscopicmore » crystals. However, an orchestrated sequence of dislocation nucleation and migration is observed to give rise to a highly ordered deformation mode. This discovery suggests that nanocrystals can be made to deform more controllably than previously thought. It can also lead to novel flow control and mixing strategies in droplet microfluidics.« less

Hamiltonian approach to Ehrenfest expectation values and Gaussian quantum states

PubMed Central

Bonet-Luz, Esther

2016-01-01

The dynamics of quantum expectation values is considered in a geometric setting. First, expectation values of the canonical observables are shown to be equivariant momentum maps for the action of the Heisenberg group on quantum states. Then, the Hamiltonian structure of Ehrenfest’s theorem is shown to be Lie–Poisson for a semidirect-product Lie group, named the Ehrenfest group. The underlying Poisson structure produces classical and quantum mechanics as special limit cases. In addition, quantum dynamics is expressed in the frame of the expectation values, in which the latter undergo canonical Hamiltonian motion. In the case of Gaussian states, expectation values dynamics couples to second-order moments, which also enjoy a momentum map structure. Eventually, Gaussian states are shown to possess a Lie–Poisson structure associated with another semidirect-product group, which is called the Jacobi group. This structure produces the energy-conserving variant of a class of Gaussian moment models that have previously appeared in the chemical physics literature. PMID:27279764

Micro-photoluminescence of GaAs/AlGaAs triple concentric quantum rings.

PubMed

Abbarchi, Marco; Cavigli, Lucia; Somaschini, Claudio; Bietti, Sergio; Gurioli, Massimo; Vinattieri, Anna; Sanguinetti, Stefano

2011-10-31

A systematic optical study, including micro, ensemble and time resolved photoluminescence of GaAs/AlGaAs triple concentric quantum rings, self-assembled via droplet epitaxy, is presented. Clear emission from localized states belonging to the ring structures is reported. The triple rings show a fast decay dynamics, around 40 ps, which is expected to be useful for ultrafast optical switching applications.

The influence of hydrologic residence time on lake carbon cycling dynamics following extreme precipitation events

Treesearch

Jacob A. Zwart; Stephen D. Sebestyen; Christopher T. Solomon; Stuart E. Jones

2016-01-01

The frequency and magnitude of extreme events are expected to increase in the future, yet little is known about effects of such events on ecosystem structure and function. We examined how extreme precipitation events affect exports of terrestrial dissolved organic carbon (t-DOC) from watersheds to lakes as well as in-lake heterotrophy in three north-temperate lakes....

Analytic Prediction of Emergent Dynamics for Autonomous Negotiating Team (ANT) Systems

DTIC Science & Technology

2003-11-01

it is determined that a “phase transition” behavior is to be expected. 15. NUMBER OF PAGES 140 14. SUBJECT TERMS autonomous negotiation...parameter. Crisis has the worst asymptotic behavior of the three strategies. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30 iv 3.7...deadline, as opposed to harder with increasing communication time. Again, we see that the crisis strategy has the worst asymptotic behavior over the

State Dependency of Chemosensory Coding in the Gustatory Thalamus (VPMpc) of Alert Rats

PubMed Central

Liu, Haixin

2015-01-01

The parvicellular portion of the ventroposteromedial nucleus (VPMpc) is the part of the thalamus that processes gustatory information. Anatomical evidence shows that the VPMpc receives ascending gustatory inputs from the parabrachial nucleus (PbN) in the brainstem and sends projections to the gustatory cortex (GC). Although taste processing in PbN and GC has been the subject of intense investigation in behaving rodents, much less is known on how VPMpc neurons encode gustatory information. Here we present results from single-unit recordings in the VPMpc of alert rats receiving multiple tastants. Thalamic neurons respond to taste with time-varying modulations of firing rates, consistent with those observed in GC and PbN. These responses encode taste quality as well as palatability. Comparing responses to tastants either passively delivered, or self-administered after a cue, unveiled the effects of general expectation on taste processing in VPMpc. General expectation led to an improvement of taste coding by modulating response dynamics, and single neuron ability to encode multiple tastants. Our results demonstrate that the time course of taste coding as well as single neurons' ability to encode for multiple qualities are not fixed but rather can be altered by the state of the animal. Together, the data presented here provide the first description that taste coding in VPMpc is dynamic and state-dependent. SIGNIFICANCE STATEMENT Over the past years, a great deal of attention has been devoted to understanding taste coding in the brainstem and cortex of alert rodents. Thanks to this research, we now know that taste coding is dynamic, distributed, and context-dependent. Alas, virtually nothing is known on how the gustatory thalamus (VPMpc) processes gustatory information in behaving rats. This manuscript investigates taste processing in the VPMpc of behaving rats. Our results show that thalamic neurons encode taste and palatability with time-varying patterns of activity and that thalamic coding of taste is modulated by general expectation. Our data will appeal not only to researchers interested in taste, but also to a broader audience of sensory and systems neuroscientists interested in the thalamocortical system. PMID:26609147

Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering

PubMed Central

Havlicek, Martin; Friston, Karl J.; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D.

2011-01-01

This paper presents a new approach to inverting (fitting) models of coupled dynamical systems based on state-of-the-art (cubature) Kalman filtering. Crucially, this inversion furnishes posterior estimates of both the hidden states and parameters of a system, including any unknown exogenous input. Because the underlying generative model is formulated in continuous time (with a discrete observation process) it can be applied to a wide variety of models specified with either ordinary or stochastic differential equations. These are an important class of models that are particularly appropriate for biological time-series, where the underlying system is specified in terms of kinetics or dynamics (i.e., dynamic causal models). We provide comparative evaluations with generalized Bayesian filtering (dynamic expectation maximization) and demonstrate marked improvements in accuracy and computational efficiency. We compare the schemes using a series of difficult (nonlinear) toy examples and conclude with a special focus on hemodynamic models of evoked brain responses in fMRI. Our scheme promises to provide a significant advance in characterizing the functional architectures of distributed neuronal systems, even in the absence of known exogenous (experimental) input; e.g., resting state fMRI studies and spontaneous fluctuations in electrophysiological studies. Importantly, unlike current Bayesian filters (e.g. DEM), our scheme provides estimates of time-varying parameters, which we will exploit in future work on the adaptation and enabling of connections in the brain. PMID:21396454

A Simple Network Architecture Accounts for Diverse Reward Time Responses in Primary Visual Cortex.

PubMed

Huertas, Marco A; Hussain Shuler, Marshall G; Shouval, Harel Z

2015-09-16

Many actions performed by animals and humans depend on an ability to learn, estimate, and produce temporal intervals of behavioral relevance. Exemplifying such learning of cued expectancies is the observation of reward-timing activity in the primary visual cortex (V1) of rodents, wherein neural responses to visual cues come to predict the time of future reward as behaviorally experienced in the past. These reward-timing responses exhibit significant heterogeneity in at least three qualitatively distinct classes: sustained increase or sustained decrease in firing rate until the time of expected reward, and a class of cells that reach a peak in firing at the expected delay. We elaborate upon our existing model by including inhibitory and excitatory units while imposing simple connectivity rules to demonstrate what role these inhibitory elements and the simple architectures play in sculpting the response dynamics of the network. We find that simply adding inhibition is not sufficient for obtaining the different distinct response classes, and that a broad distribution of inhibitory projections is necessary for obtaining peak-type responses. Furthermore, although changes in connection strength that modulate the effects of inhibition onto excitatory units have a strong impact on the firing rate profile of these peaked responses, the network exhibits robustness in its overall ability to predict the expected time of reward. Finally, we demonstrate how the magnitude of expected reward can be encoded at the expected delay in the network and how peaked responses express this reward expectancy. Heterogeneity in single-neuron responses is a common feature of neuronal systems, although sometimes, in theoretical approaches, it is treated as a nuisance and seldom considered as conveying a different aspect of a signal. In this study, we focus on the heterogeneous responses in the primary visual cortex of rodents trained with a predictable delayed reward time. We describe under what conditions this heterogeneity can arise by self-organization, and what information it can convey. This study, while focusing on a specific system, provides insight onto how heterogeneity can arise in general while also shedding light onto mechanisms of reinforcement learning using realistic biological assumptions. Copyright © 2015 the authors 0270-6474/15/3512659-14$15.00/0.

Real-time management of a multipurpose water reservoir with a heteroscedastic inflow model

NASA Astrophysics Data System (ADS)

Pianosi, F.; Soncini-Sessa, R.

2009-10-01

Stochastic dynamic programming has been extensively used as a method for designing optimal regulation policies for water reservoirs. However, the potential of this method is dramatically reduced by its computational burden, which often forces to introduce strong approximations in the model of the system, especially in the description of the reservoir inflow. In this paper, an approach to partially remedy this problem is proposed and applied to a real world case study. It foresees solving the management problem on-line, using a reduced model of the system and the inflow forecast provided by a dynamic model. By doing so, all the hydrometeorological information that is available in real-time is fully exploited. The model here proposed for the inflow forecasting is a nonlinear, heteroscedastic model that provides both the expected value and the standard deviation of the inflow through dynamic relations. The effectiveness of such model for the purpose of the reservoir regulation is evaluated through simulation and comparison with the results provided by conventional homoscedastic inflow models.

Glass transition of soft colloids

NASA Astrophysics Data System (ADS)

Philippe, Adrian-Marie; Truzzolillo, Domenico; Galvan-Myoshi, Julian; Dieudonné-George, Philippe; Trappe, Véronique; Berthier, Ludovic; Cipelletti, Luca

2018-04-01

We explore the glassy dynamics of soft colloids using microgels and charged particles interacting by steric and screened Coulomb interactions, respectively. In the supercooled regime, the structural relaxation time τα of both systems grows steeply with volume fraction, reminiscent of the behavior of colloidal hard spheres. Computer simulations confirm that the growth of τα on approaching the glass transition is independent of particle softness. By contrast, softness becomes relevant at very large packing fractions when the system falls out of equilibrium. In this nonequilibrium regime, τα depends surprisingly weakly on packing fraction, and time correlation functions exhibit a compressed exponential decay consistent with stress-driven relaxation. The transition to this novel regime coincides with the onset of an anomalous decrease in local order with increasing density typical of ultrasoft systems. We propose that these peculiar dynamics results from the combination of the nonequilibrium aging dynamics expected in the glassy state and the tendency of colloids interacting through soft potentials to refluidize at high packing fractions.

Experimental evidence for stochastic switching of supercooled phases in NdNiO3 nanostructures

NASA Astrophysics Data System (ADS)

Kumar, Devendra; Rajeev, K. P.; Alonso, J. A.

2018-03-01

A first-order phase transition is a dynamic phenomenon. In a multi-domain system, the presence of multiple domains of coexisting phases averages out the dynamical effects, making it nearly impossible to predict the exact nature of phase transition dynamics. Here, we report the metal-insulator transition in samples of sub-micrometer size NdNiO3 where the effect of averaging is minimized by restricting the number of domains under study. We observe the presence of supercooled metallic phases with supercooling of 40 K or more. The transformation from the supercooled metallic to the insulating state is a stochastic process that happens at different temperatures and times in different experimental runs. The experimental results are understood without incorporating material specific properties, suggesting that the behavior is of universal nature. The size of the sample needed to observe individual switching of supercooled domains, the degree of supercooling, and the time-temperature window of switching are expected to depend on the parameters such as quenched disorder, strain, and magnetic field.

Parallel replica dynamics method for bistable stochastic reaction networks: Simulation and sensitivity analysis

NASA Astrophysics Data System (ADS)

Wang, Ting; Plecháč, Petr

2017-12-01

Stochastic reaction networks that exhibit bistable behavior are common in systems biology, materials science, and catalysis. Sampling of stationary distributions is crucial for understanding and characterizing the long-time dynamics of bistable stochastic dynamical systems. However, simulations are often hindered by the insufficient sampling of rare transitions between the two metastable regions. In this paper, we apply the parallel replica method for a continuous time Markov chain in order to improve sampling of the stationary distribution in bistable stochastic reaction networks. The proposed method uses parallel computing to accelerate the sampling of rare transitions. Furthermore, it can be combined with the path-space information bounds for parametric sensitivity analysis. With the proposed methodology, we study three bistable biological networks: the Schlögl model, the genetic switch network, and the enzymatic futile cycle network. We demonstrate the algorithmic speedup achieved in these numerical benchmarks. More significant acceleration is expected when multi-core or graphics processing unit computer architectures and programming tools such as CUDA are employed.

Extended slow dynamical regime close to the many-body localization transition

NASA Astrophysics Data System (ADS)

Luitz, David J.; Laflorencie, Nicolas; Alet, Fabien

2016-02-01

Many-body localization is characterized by a slow logarithmic growth of the entanglement entropy after a global quantum quench while the local memory of an initial density imbalance remains at infinite time. We investigate how much the proximity of a many-body localized phase can influence the dynamics in the delocalized ergodic regime where thermalization is expected. Using an exact Krylov space technique, the out-of-equilibrium dynamics of the random-field Heisenberg chain is studied up to L =28 sites, starting from an initially unentangled high-energy product state. Within most of the delocalized phase, we find a sub-ballistic entanglement growth S (t ) ∝t1 /z with a disorder-dependent exponent z ≥1 , in contrast with the pure ballistic growth z =1 of clean systems. At the same time, anomalous relaxation is also observed for the spin imbalance I (t ) ∝t-ζ with a continuously varying disorder-dependent exponent ζ , vanishing at the transition. This provides a clear experimental signature for detecting this nonconventional regime.

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

DOE PAGES

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

2017-03-21

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

Why the null matters: statistical tests, random walks and evolution.

PubMed

Sheets, H D; Mitchell, C E

2001-01-01

A number of statistical tests have been developed to determine what type of dynamics underlie observed changes in morphology in evolutionary time series, based on the pattern of change within the time series. The theory of the 'scaled maximum', the 'log-rate-interval' (LRI) method, and the Hurst exponent all operate on the same principle of comparing the maximum change, or rate of change, in the observed dataset to the maximum change expected of a random walk. Less change in a dataset than expected of a random walk has been interpreted as indicating stabilizing selection, while more change implies directional selection. The 'runs test' in contrast, operates on the sequencing of steps, rather than on excursion. Applications of these tests to computer generated, simulated time series of known dynamical form and various levels of additive noise indicate that there is a fundamental asymmetry in the rate of type II errors of the tests based on excursion: they are all highly sensitive to noise in models of directional selection that result in a linear trend within a time series, but are largely noise immune in the case of a simple model of stabilizing selection. Additionally, the LRI method has a lower sensitivity than originally claimed, due to the large range of LRI rates produced by random walks. Examination of the published results of these tests show that they have seldom produced a conclusion that an observed evolutionary time series was due to directional selection, a result which needs closer examination in light of the asymmetric response of these tests.

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

PubMed

Giebel, S; Rainer, M

2010-01-01

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

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

PubMed Central

Truccolo, Wilson

2017-01-01

Point process generalized linear models (PP-GLMs) provide an important statistical framework for modeling spiking activity in single-neurons and neuronal networks. Stochastic stability is essential when sampling from these models, as done in computational neuroscience to analyze statistical properties of neuronal dynamics and in neuro-engineering to implement closed-loop applications. Here we show, however, that despite passing common goodness-of-fit tests, PP-GLMs estimated from data are often unstable, leading to divergent firing rates. The inclusion of absolute refractory periods is not a satisfactory solution since the activity then typically settles into unphysiological rates. To address these issues, we derive a framework for determining the existence and stability of fixed points of the expected conditional intensity function (CIF) for general PP-GLMs. Specifically, in nonlinear Hawkes PP-GLMs, the CIF is expressed as a function of the previous spike history and exogenous inputs. We use a mean-field quasi-renewal (QR) approximation that decomposes spike history effects into the contribution of the last spike and an average of the CIF over all spike histories prior to the last spike. Fixed points for stationary rates are derived as self-consistent solutions of integral equations. Bifurcation analysis and the number of fixed points predict that the original models can show stable, divergent, and metastable (fragile) dynamics. For fragile models, fluctuations of the single-neuron dynamics predict expected divergence times after which rates approach unphysiologically high values. This metric can be used to estimate the probability of rates to remain physiological for given time periods, e.g., for simulation purposes. We demonstrate the use of the stability framework using simulated single-neuron examples and neurophysiological recordings. Finally, we show how to adapt PP-GLM estimation procedures to guarantee model stability. Overall, our results provide a stability framework for data-driven PP-GLMs and shed new light on the stochastic dynamics of state-of-the-art statistical models of neuronal spiking activity. PMID:28234899

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

PubMed

Gerhard, Felipe; Deger, Moritz; Truccolo, Wilson

2017-02-01

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

Globular cluster formation - The fossil record

NASA Technical Reports Server (NTRS)

Murray, Stephen D.; Lin, Douglas N. C.

1992-01-01

Properties of globular clusters which have remained unchanged since their formation are used to infer the internal pressures, cooling times, and dynamical times of the protocluster clouds immediately prior to the onset of star formation. For all globular clusters examined, it is found that the cooling times are much less than the dynamical times, implying that the protoclusters must have been maintained in thermal equilibrium by external heat sources, with fluxes consistent with those found in previous work, and giving the observed rho-T relation. Self-gravitating clouds cannot be stably heated, so that the Jeans mass forms an upper limit to the cluster masses. The observed dependence of protocluster pressure upon galactocentric position implies that the protocluster clouds were in hydrostatic equilibrium after their formation. The pressure dependence is well fitted by that expected for a quasi-statically evolving background hot gas, shock heated to its virial temperature. The observations and inferences are combined with previous theoretical work to construct a picture of globular cluster formation.

Dynamic design of ecological monitoring networks for non-Gaussian spatio-temporal data

USGS Publications Warehouse

Wikle, C.K.; Royle, J. Andrew

2005-01-01

Many ecological processes exhibit spatial structure that changes over time in a coherent, dynamical fashion. This dynamical component is often ignored in the design of spatial monitoring networks. Furthermore, ecological variables related to processes such as habitat are often non-Gaussian (e.g. Poisson or log-normal). We demonstrate that a simulation-based design approach can be used in settings where the data distribution is from a spatio-temporal exponential family. The key random component in the conditional mean function from this distribution is then a spatio-temporal dynamic process. Given the computational burden of estimating the expected utility of various designs in this setting, we utilize an extended Kalman filter approximation to facilitate implementation. The approach is motivated by, and demonstrated on, the problem of selecting sampling locations to estimate July brood counts in the prairie pothole region of the U.S.

Estimation of Time-Varying, Intrinsic and Reflex Dynamic Joint Stiffness during Movement. Application to the Ankle Joint

PubMed Central

Guarín, Diego L.; Kearney, Robert E.

2017-01-01

Dynamic joint stiffness determines the relation between joint position and torque, and plays a vital role in the control of posture and movement. Dynamic joint stiffness can be quantified during quasi-stationary conditions using disturbance experiments, where small position perturbations are applied to the joint and the torque response is recorded. Dynamic joint stiffness is composed of intrinsic and reflex mechanisms that act and change together, so that nonlinear, mathematical models and specialized system identification techniques are necessary to estimate their relative contributions to overall joint stiffness. Quasi-stationary experiments have demonstrated that dynamic joint stiffness is heavily modulated by joint position and voluntary torque. Consequently, during movement, when joint position and torque change rapidly, dynamic joint stiffness will be Time-Varying (TV). This paper introduces a new method to quantify the TV intrinsic and reflex components of dynamic joint stiffness during movement. The algorithm combines ensemble and deterministic approaches for estimation of TV systems; and uses a TV, parallel-cascade, nonlinear system identification technique to separate overall dynamic joint stiffness into intrinsic and reflex components from position and torque records. Simulation studies of a stiffness model, whose parameters varied with time as is expected during walking, demonstrated that the new algorithm accurately tracked the changes in dynamic joint stiffness using as little as 40 gait cycles. The method was also used to estimate the intrinsic and reflex dynamic ankle stiffness from an experiment with a healthy subject during which ankle movements were imposed while the subject maintained a constant muscle contraction. The method identified TV stiffness model parameters that predicted the measured torque very well, accounting for more than 95% of its variance. Moreover, both intrinsic and reflex dynamic stiffness were heavily modulated through the movement in a manner that could not be predicted from quasi-stationary experiments. The new method provides the tool needed to explore the role of dynamic stiffness in the control of movement. PMID:28649196

Expectation-Based Control of Noise and Chaos

NASA Technical Reports Server (NTRS)

Zak, Michael

2006-01-01

A proposed approach to control of noise and chaos in dynamic systems would supplement conventional methods. The approach is based on fictitious forces composed of expectations governed by Fokker-Planck or Liouville equations that describe the evolution of the probability densities of the controlled parameters. These forces would be utilized as feedback control forces that would suppress the undesired diffusion of the controlled parameters. Examples of dynamic systems in which the approach is expected to prove beneficial include spacecraft, electronic systems, and coupled lasers.

Final Technical Report for DE-SC0008149

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

Buchanan, Kristen

The major goal of this project is to study spin waves in magnetic thin films, especially how spin waves respond to external stimuli. This is expected to lead to new insight into dynamic processes and new ideas for methods to control spin waves. Experimental studies are being done primarily using time- and spatially-resolved Brillouin light scattering (BLS) measurements on extended and patterned magnetic thin films. BLS is a versatile tool that provides a non-invasive probe of spin dynamics with frequencies of ~1 GHz to well over 100 GHz, diffraction-limited spatial resolution, 250-ps temporal resolution, and it is sensitive enough tomore » detect thermal magnons.« less

Self-optimized construction of transition rate matrices from accelerated atomistic simulations with Bayesian uncertainty quantification

NASA Astrophysics Data System (ADS)

Swinburne, Thomas D.; Perez, Danny

2018-05-01

A massively parallel method to build large transition rate matrices from temperature-accelerated molecular dynamics trajectories is presented. Bayesian Markov model analysis is used to estimate the expected residence time in the known state space, providing crucial uncertainty quantification for higher-scale simulation schemes such as kinetic Monte Carlo or cluster dynamics. The estimators are additionally used to optimize where exploration is performed and the degree of temperature acceleration on the fly, giving an autonomous, optimal procedure to explore the state space of complex systems. The method is tested against exactly solvable models and used to explore the dynamics of C15 interstitial defects in iron. Our uncertainty quantification scheme allows for accurate modeling of the evolution of these defects over timescales of several seconds.

Learning from Non-Linear Ecosystem Dynamics Is Vital for Achieving Land Degradation Neutrality

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

Sietz, Diana; Fleskens, Luuk; Stringer, Lindsay C.

Land Degradation Neutrality is one of the Sustainable Development Goal targets, requiring on-going degradation to be balanced by restoration and sustainable land management. However, restoration and efforts to prevent degradation have often failed to deliver expected benefits,despite enormous investments. Better acknowledging the close relationships between climate, land management and non-linear ecosystem dynamics can help restoration activities to meet their intended goals, while supporting climate change adaptation and mitigation. This paper is the first to link ecological theory of non-linear ecosystem dynamics to Land Degradation Neutrality offering essential insights into appropriate timings, climate-induced windows of opportunities and risks and the financialmore » viability of investments. These novel insights are pre-requisites for meaningful o and monitoring of progress towards Land Degradation Neutrality« less

Learning from Non-Linear Ecosystem Dynamics Is Vital for Achieving Land Degradation Neutrality

DOE PAGES

Sietz, Diana; Fleskens, Luuk; Stringer, Lindsay C.

2017-02-27

Land Degradation Neutrality is one of the Sustainable Development Goal targets, requiring on-going degradation to be balanced by restoration and sustainable land management. However, restoration and efforts to prevent degradation have often failed to deliver expected benefits,despite enormous investments. Better acknowledging the close relationships between climate, land management and non-linear ecosystem dynamics can help restoration activities to meet their intended goals, while supporting climate change adaptation and mitigation. This paper is the first to link ecological theory of non-linear ecosystem dynamics to Land Degradation Neutrality offering essential insights into appropriate timings, climate-induced windows of opportunities and risks and the financialmore » viability of investments. These novel insights are pre-requisites for meaningful o and monitoring of progress towards Land Degradation Neutrality« less

Dynamic Response of a Planetary Gear System Using a Finite Element/Contact Mechanics Model

NASA Technical Reports Server (NTRS)

Parker, Robert G.; Agashe, Vinayak; Vijayakar, Sandeep M.

2000-01-01

The dynamic response of a helicopter planetary gear system is examined over a wide range of operating speeds and torques. The analysis tool is a unique, semianalytical finite element formulation that admits precise representation of the tooth geometry and contact forces that are crucial in gear dynamics. Importantly, no a priori specification of static transmission error excitation or mesh frequency variation is required; the dynamic contact forces are evaluated internally at each time step. The calculated response shows classical resonances when a harmonic of mesh frequency coincides with a natural frequency. However, peculiar behavior occurs where resonances expected to be excited at a given speed are absent. This absence of particular modes is explained by analytical relationships that depend on the planetary configuration and mesh frequency harmonic. The torque sensitivity of the dynamic response is examined and compared to static analyses. Rotation mode response is shown to be more sensitive to input torque than translational mode response.

Micro-photoluminescence of GaAs/AlGaAs triple concentric quantum rings

PubMed Central

2011-01-01

A systematic optical study, including micro, ensemble and time resolved photoluminescence of GaAs/AlGaAs triple concentric quantum rings, self-assembled via droplet epitaxy, is presented. Clear emission from localized states belonging to the ring structures is reported. The triple rings show a fast decay dynamics, around 40 ps, which is expected to be useful for ultrafast optical switching applications. PMID:22039893

Probing dynamics in colloidal crystals with pump-probe experiments at LCLS: Methodology and analysis

DOE PAGES

Mukharamova, Nastasia; Lazarev, Sergey; Meijer, Janne -Mieke; ...

2017-05-19

We present results of the studies of dynamics in colloidal crystals performed by pump-probe experiments using an X-ray free-electron laser (XFEL). Colloidal crystals were pumped with an infrared laser at a wavelength of 800 nm with varying power and probed by XFEL pulses at an energy of 8 keV with a time delay up to 1000 ps. The positions of the Bragg peaks, and their radial and azimuthal widths were analyzed as a function of the time delay. The spectral analysis of the data did not reveal significant enhancement of frequencies expected in this experiment. As a result, this allowedmore » us to conclude that the amplitude of vibrational modes excited in colloidal crystals was less than the systematic error caused by the noise level.« less

Relating dynamic perception of reformulated cheese pies to consumers' expectations of satiating ability.

PubMed

Marcano, J; Varela, P; Cunha, L M; Fiszman, S

2015-12-01

Designing satiating food is not an easy task. Food reformulation is normally done by altering the proportion of basic ingredients or by adding new minor ingredients. In general, the texture varies concomitantly with these changes, altering the way the food is processed orally and the complete eating experience. This highlights the interest of discovering how variations in minor ingredients influence texture and how this affects the dynamics of the oral trajectory. Six cheese pie formulations were prepared: basic recipe (Base), no egg (-Egg), no corn starch (-Corn starch) no sugar (-Sugar), added diary cream (+Cream) and extra skimmed milk powder (+Milk powder). Temporal dominance of sensations was used to show that the appearance and disappearance of each texture sensation dominance experienced in the mouth during the eating process differed among the six pies, as did their relation to the consumers' expectation of satiating capacity scores and to the changes in composition. Two extreme behaviors were found: suppression of egg/addition of extra milk powder made the pies initially drier and harder, while suppression of corn starch/addition of cream gave the samples a soft, moist early sensation. The former elicited higher expectations of satiating capacity. In addition, overall liking, liking evolving with time (dynamic liking) and the level of several key texture attributes' divergence from those of an "ideal" cheese pie were evaluated on bipolar just-about-right scales and through penalty analysis to gain insights into potential directions for reformulating acceptable pies. Copyright © 2015 Elsevier Ltd. All rights reserved.

Theory of activated glassy dynamics in randomly pinned fluids.

PubMed

Phan, Anh D; Schweizer, Kenneth S

2018-02-07

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

Rapid evolution leads to differential population dynamics and top-down control in resurrected Daphnia populations.

PubMed

Goitom, Eyerusalem; Kilsdonk, Laurens J; Brans, Kristien; Jansen, Mieke; Lemmens, Pieter; De Meester, Luc

2018-01-01

There is growing evidence of rapid genetic adaptation of natural populations to environmental change, opening the perspective that evolutionary trait change may subsequently impact ecological processes such as population dynamics, community composition, and ecosystem functioning. To study such eco-evolutionary feedbacks in natural populations, however, requires samples across time. Here, we capitalize on a resurrection ecology study that documented rapid and adaptive evolution in a natural population of the water flea Daphnia magna in response to strong changes in predation pressure by fish, and carry out a follow-up mesocosm experiment to test whether the observed genetic changes influence population dynamics and top-down control of phytoplankton. We inoculated populations of the water flea D. magna derived from three time periods of the same natural population known to have genetically adapted to changes in predation pressure in replicate mesocosms and monitored both Daphnia population densities and phytoplankton biomass in the presence and absence of fish. Our results revealed differences in population dynamics and top-down control of algae between mesocosms harboring populations from the time period before, during, and after a peak in fish predation pressure caused by human fish stocking. The differences, however, deviated from our a priori expectations. An S-map approach on time series revealed that the interactions between adults and juveniles strongly impacted the dynamics of populations and their top-down control on algae in the mesocosms, and that the strength of these interactions was modulated by rapid evolution as it occurred in nature. Our study provides an example of an evolutionary response that fundamentally alters the processes structuring population dynamics and impacts ecosystem features.

Magnetohydrodynamic Convection in the Outer Core and its Geodynamic Consequences

NASA Technical Reports Server (NTRS)

Kuang, Weijia; Chao, Benjamin F.; Fang, Ming

2004-01-01

The Earth's fluid outer core is in vigorous convection through much of the Earth's history. In addition to generating and maintaining Earth s time-varying magnetic field (geodynamo), the core convection also generates mass redistribution in the core and a dynamical pressure field on the core-mantle boundary (CMB). All these shall result in various core-mantle interactions, and contribute to surface geodynamic observables. For example, electromagnetic core-mantle coupling arises from finite electrically conducting lower mantle; gravitational interaction occurs between the cores and the heterogeneous mantle; mechanical coupling may also occur when the CMB topography is aspherical. Besides changing the mantle rotation via the coupling torques, the mass-redistribution in the core shall produce a spatial-temporal gravity anomaly. Numerical modeling of the core dynamical processes contributes in several geophysical disciplines. It helps explain the physical causes of surface geodynamic observables via space geodetic techniques and other means, e.g. Earth's rotation variation on decadal time scales, and secular time-variable gravity. Conversely, identification of the sources of the observables can provide additional insights on the dynamics of the fluid core, leading to better constraints on the physics in the numerical modeling. In the past few years, our core dynamics modeling efforts, with respect to our MoSST model, have made significant progress in understanding individual geophysical consequences. However, integrated studies are desirable, not only because of more mature numerical core dynamics models, but also because of inter-correlation among the geophysical phenomena, e.g. mass redistribution in the outer core produces not only time-variable gravity, but also gravitational core-mantle coupling and thus the Earth's rotation variation. They are expected to further facilitate multidisciplinary studies of core dynamics and interactions of the core with other components of the Earth.

Theory of activated glassy dynamics in randomly pinned fluids

NASA Astrophysics Data System (ADS)

Phan, Anh D.; Schweizer, Kenneth S.

2018-02-01

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

Adjoint Fokker-Planck equation and runaway electron dynamics

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

Liu, Chang; Brennan, Dylan P.; Bhattacharjee, Amitava

2016-01-15

The adjoint Fokker-Planck equation method is applied to study the runaway probability function and the expected slowing-down time for highly relativistic runaway electrons, including the loss of energy due to synchrotron radiation. In direct correspondence to Monte Carlo simulation methods, the runaway probability function has a smooth transition across the runaway separatrix, which can be attributed to effect of the pitch angle scattering term in the kinetic equation. However, for the same numerical accuracy, the adjoint method is more efficient than the Monte Carlo method. The expected slowing-down time gives a novel method to estimate the runaway current decay timemore » in experiments. A new result from this work is that the decay rate of high energy electrons is very slow when E is close to the critical electric field. This effect contributes further to a hysteresis previously found in the runaway electron population.« less

Frequency-domain coherent multidimensional spectroscopy when dephasing rivals pulsewidth: Disentangling material and instrument response

DOE PAGES

Kohler, Daniel D.; Thompson, Blaise J.; Wright, John C.

2017-08-31

Ultrafast spectroscopy is often collected in the mixed frequency/time domain, where pulse durations are similar to system dephasing times. In these experiments, expectations derived from the familiar driven and impulsive limits are not valid. This work simulates the mixed-domain four-wave mixing response of a model system to develop expectations for this more complex field-matter interaction. We also explore frequency and delay axes. We show that these line shapes are exquisitely sensitive to excitation pulse widths and delays. Near pulse overlap, the excitation pulses induce correlations that resemble signatures of dynamic inhomogeneity. We describe these line shapes using an intuitive picturemore » that connects to familiar field-matter expressions. We develop strategies for distinguishing pulse-induced correlations from true system inhomogeneity. Our simulations provide a foundation for interpretation of ultrafast experiments in the mixed domain.« less

Catch bonding in the forced dissociation of a polymer endpoint

NASA Astrophysics Data System (ADS)

Vrusch, Cyril; Storm, Cornelis

2018-04-01

Applying a force to certain supramolecular bonds may initially stabilize them, manifested by a lower dissociation rate. We show that this behavior, known as catch bonding and by now broadly reported in numerous biophysics bonds, is generically expected when either or both the trapping potential and the force applied to the bond possess some degree of nonlinearity. We enumerate possible scenarios and for each identify the possibility and, if applicable, the criterion for catch bonding to occur. The effect is robustly predicted by Kramers theory and Mean First Passage Time theory and confirmed in direct molecular dynamics simulation. Among the catch scenarios, one plays out essentially any time the force on the bond originates in a polymeric object, implying that some degree of catch bond behavior is to be expected in many settings relevant to polymer network mechanics or optical tweezer experiments.

Alpha and theta band dynamics related to sentential constraint and word expectancy.

PubMed

Rommers, Joost; Dickson, Danielle S; Norton, James J S; Wlotko, Edward W; Federmeier, Kara D

2017-01-01

Despite strong evidence for prediction during language comprehension, the underlying mechanisms, and the extent to which they are specific to language, remain unclear. Re-analyzing an ERP study, we examined responses in the time-frequency domain to expected and unexpected (but plausible) words in strongly and weakly constraining sentences, and found results similar to those reported in nonverbal domains. Relative to expected words, unexpected words elicited an increase in the theta band (4-7 Hz) in strongly constraining contexts, suggesting the involvement of control processes to deal with the consequences of having a prediction disconfirmed. Prior to critical word onset, strongly constraining sentences exhibited a decrease in the alpha band (8-12 Hz) relative to weakly constraining sentences, suggesting that comprehenders can take advantage of predictive sentence contexts to prepare for the input. The results suggest that the brain recruits domain-general preparation and control mechanisms when making and assessing predictions during sentence comprehension.

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.

Autonomous Collision-Free Navigation of Microvehicles in Complex and Dynamically Changing Environments.

PubMed

Li, Tianlong; Chang, Xiaocong; Wu, Zhiguang; Li, Jinxing; Shao, Guangbin; Deng, Xinghong; Qiu, Jianbin; Guo, Bin; Zhang, Guangyu; He, Qiang; Li, Longqiu; Wang, Joseph

2017-09-26

Self-propelled micro- and nanoscale robots represent a rapidly emerging and fascinating robotics research area. However, designing autonomous and adaptive control systems for operating micro/nanorobotics in complex and dynamically changing environments, which is a highly demanding feature, is still an unmet challenge. Here we describe a smart microvehicle for precise autonomous navigation in complicated environments and traffic scenarios. The fully autonomous navigation system of the smart microvehicle is composed of a microscope-coupled CCD camera, an artificial intelligence planner, and a magnetic field generator. The microscope-coupled CCD camera provides real-time localization of the chemically powered Janus microsphere vehicle and environmental detection for path planning to generate optimal collision-free routes, while the moving direction of the microrobot toward a reference position is determined by the external electromagnetic torque. Real-time object detection offers adaptive path planning in response to dynamically changing environments. We demonstrate that the autonomous navigation system can guide the vehicle movement in complex patterns, in the presence of dynamically changing obstacles, and in complex biological environments. Such a navigation system for micro/nanoscale vehicles, relying on vision-based close-loop control and path planning, is highly promising for their autonomous operation in complex dynamic settings and unpredictable scenarios expected in a variety of realistic nanoscale scenarios.

Network structure shapes spontaneous functional connectivity dynamics.

PubMed

Shen, Kelly; Hutchison, R Matthew; Bezgin, Gleb; Everling, Stefan; McIntosh, Anthony R

2015-04-08

The structural organization of the brain constrains the range of interactions between different regions and shapes ongoing information processing. Therefore, it is expected that large-scale dynamic functional connectivity (FC) patterns, a surrogate measure of coordination between brain regions, will be closely tied to the fiber pathways that form the underlying structural network. Here, we empirically examined the influence of network structure on FC dynamics by comparing resting-state FC (rsFC) obtained using BOLD-fMRI in macaques (Macaca fascicularis) to structural connectivity derived from macaque axonal tract tracing studies. Consistent with predictions from simulation studies, the correspondence between rsFC and structural connectivity increased as the sample duration increased. Regions with reciprocal structural connections showed the most stable rsFC across time. The data suggest that the transient nature of FC is in part dependent on direct underlying structural connections, but also that dynamic coordination can occur via polysynaptic pathways. Temporal stability was found to be dependent on structural topology, with functional connections within the rich-club core exhibiting the greatest stability over time. We discuss these findings in light of highly variable functional hubs. The results further elucidate how large-scale dynamic functional coordination exists within a fixed structural architecture. Copyright © 2015 the authors 0270-6474/15/355579-10$15.00/0.

Parallel Decomposition of the Fictitious Lagrangian Algorithm and its Accuracy for Molecular Dynamics Simulations of Semiconductors.

NASA Astrophysics Data System (ADS)

Yeh, Mei-Ling

We have performed a parallel decomposition of the fictitious Lagrangian method for molecular dynamics with tight-binding total energy expression into the hypercube computer. This is the first time in literature that the dynamical simulation of semiconducting systems containing more than 512 silicon atoms has become possible with the electrons treated as quantum particles. With the utilization of the Intel Paragon system, our timing analysis predicts that our code is expected to perform realistic simulations on very large systems consisting of thousands of atoms with time requirements of the order of tens of hours. Timing results and performance analysis of our parallel code are presented in terms of calculation time, communication time, and setup time. The accuracy of the fictitious Lagrangian method in molecular dynamics simulation is also investigated, especially the energy conservation of the total energy of ions. We find that the accuracy of the fictitious Lagrangian scheme in small silicon cluster and very large silicon system simulations is good for as long as the simulations proceed, even though we quench the electronic coordinates to the Born-Oppenheimer surface only in the beginning of the run. The kinetic energy of electrons does not increase as time goes on, and the energy conservation of the ionic subsystem remains very good. This means that, as far as the ionic subsystem is concerned, the electrons are on the average in the true quantum ground states. We also tie up some odds and ends regarding a few remaining questions about the fictitious Lagrangian method, such as the difference between the results obtained from the Gram-Schmidt and SHAKE method of orthonormalization, and differences between simulations where the electrons are quenched to the Born -Oppenheimer surface only once compared with periodic quenching.

Data-driven Inference and Investigation of Thermosphere Dynamics and Variations

NASA Astrophysics Data System (ADS)

Mehta, P. M.; Linares, R.

2017-12-01

This paper presents a methodology for data-driven inference and investigation of thermosphere dynamics and variations. The approach uses data-driven modal analysis to extract the most energetic modes of variations for neutral thermospheric species using proper orthogonal decomposition, where the time-independent modes or basis represent the dynamics and the time-depedent coefficients or amplitudes represent the model parameters. The data-driven modal analysis approach combined with sparse, discrete observations is used to infer amplitues for the dynamic modes and to calibrate the energy content of the system. In this work, two different data-types, namely the number density measurements from TIMED/GUVI and the mass density measurements from CHAMP/GRACE are simultaneously ingested for an accurate and self-consistent specification of the thermosphere. The assimilation process is achieved with a non-linear least squares solver and allows estimation/tuning of the model parameters or amplitudes rather than the driver. In this work, we use the Naval Research Lab's MSIS model to derive the most energetic modes for six different species, He, O, N2, O2, H, and N. We examine the dominant drivers of variations for helium in MSIS and observe that seasonal latitudinal variation accounts for about 80% of the dynamic energy with a strong preference of helium for the winter hemisphere. We also observe enhanced helium presence near the poles at GRACE altitudes during periods of low solar activity (Feb 2007) as previously deduced. We will also examine the storm-time response of helium derived from observations. The results are expected to be useful in tuning/calibration of the physics-based models.

Rheological and micro-Raman time-series characterization of enzyme sol–gel solution toward morphological control of electrospun fibers

PubMed Central

Oriero, Dennis A; Weakley, Andrew T; Aston, D Eric

2012-01-01

Rheological and micro-Raman time-series characterizations were used to investigate the chemical evolutionary changes of silica sol–gel mixtures for electrospinning fibers to immobilize an enzyme (tyrosinase). Results of dynamic rheological measurements agreed with the expected structural transitions associated with reacting sol–gel systems. The electrospinning sols exhibited shear-thinning behavior typical of a power law model. Ultrafine (200–300 nm diameter) fibers were produced at early and late times within the reaction window of approximately one hour from initial mixing of sol solutions with and without enzyme; diameter distributions of these fibers showed much smaller deviations than expected. The enzyme markedly increased magnitudes of both elastic and viscous moduli but had no significant impact on final fiber diameters, suggesting that the shear-thinning behavior of both sol–gel mixtures is dominant in the fiber elongation process. The time course and scale for the electrospinning batch fabrication show strong correlations between the magnitudes in rheological property changes over time and the chemical functional group evolution obtained from micro-Raman time-series analysis of the reacting sol–gel systems. PMID:27877486

Subfemtosecond quantum nuclear dynamics in water isotopomers.

PubMed

Rao, B Jayachander; Varandas, A J C

2015-05-21

Subfemtosecond quantum dynamics studies of all water isotopomers in the X̃ (2)B1 and à (2)A1 electronic states of the cation formed by Franck-Condon ionization of the neutral ground electronic state are reported. Using the ratio of the autocorrelation functions for the isotopomers as obtained from the solution of the time-dependent Schrödinger equation in a grid representation, high-order harmonic generation signals are calculated as a function of time. The results are found to be in agreement with the available experimental findings and with our earlier study for D2O(+)/H2O(+). Maxima are predicted in the autocorrelation function ratio at various times. Their origin and occurrence is explained by calculating expectation values of the bond lengths and bond angle of the water isotopomers as a function of time. The values so calculated for the (2)B1 and (2)A1 electronic states of the cation show quasiperiodic oscillations that can be associated with the time at which the nuclear wave packet reaches the minima of the potential energy surface, there being responsible for the peaks in the HHG signals.

Dynamics of Disorder-Order Transitions in Hard Sphere Colloidal Dispersions in micro-g

NASA Technical Reports Server (NTRS)

Zhu, J. X.; Li, M.; Phan, S. E.; Russel, W. B.; Chaikin, Paul M.; Rogers, Rick; Meyers, W.

1996-01-01

We performed a series of experiments on 0.518 millimeter PMMA spheres suspended in an index matching mixture of decalin and tetralin the microgravity environment provided by the Shuttle Columbia on mission STS-73. The samples ranged in concentration from 0.49 to 0.62. volume fraction (phi) of spheres, which covers the range in which liquid, coexistence, solid and glass phases are expected from Earth bound experiments. Light scattering was used to probe the static structure, and the particle dynamics. Digital and 35 mm photos provided information on the morphology of the crystals. In general, the crystallites grew considerably larger (roughly an order of magnitude larger) than the same samples with identical treatment in 1 g. The dynamic light scattering shows the typical short time diffusion and long time caging effects found in 1 g. The surprises that were encountered in microgravity include the preponderance of random hexagonal close packed (RHCP) structures and the complete absence of the expected face centered cubic (FCC) structure, existence of large dendritic crystals floating in the coexistence samples (where liquid and solid phases coexist) and the rapid crystallization of samples which exist only in glass phase under the influence of one g. These results suggest that colloidal crystal growth is profoundly effected by gravity in yet unrecognized ways. We suspect that the RCHP structure is related to the nonequilibrium growth that is evident from the presence of dendrites. An analysis of the dendritic growth instabilities is presented within the framework of the Ackerson-Schatzel equation.

Non-Ideal Compressible-Fluid Dynamics of Fast-Response Pressure Probes for Unsteady Flow Measurements in Turbomachinery

NASA Astrophysics Data System (ADS)

Gori, G.; Molesini, P.; Persico, G.; Guardone, A.

2017-03-01

The dynamic response of pressure probes for unsteady flow measurements in turbomachinery is investigated numerically for fluids operating in non-ideal thermodynamic conditions, which are relevant for e.g. Organic Rankine Cycles (ORC) and super-critical CO2 applications. The step response of a fast-response pressure probe is investigated numerically in order to assess the expected time response when operating in the non-ideal fluid regime. Numerical simulations are carried out exploiting the Non-Ideal Compressible Fluid-Dynamics (NICFD) solver embedded in the open-source fluid dynamics code SU2. The computational framework is assessed against available experimental data for air in dilute conditions. Then, polytropic ideal gas (PIG), i.e. constant specific heats, and Peng-Robinson Stryjek-Vera (PRSV) models are applied to simulate the flow field within the probe operating with siloxane fluid octamethyltrisiloxane (MDM). The step responses are found to depend mainly on the speed of sound of the working fluid, indicating that molecular complexity plays a major role in determining the promptness of the measurement devices. According to the PRSV model, non-ideal effects can increase the step response time with respect to the acoustic theory predictions. The fundamental derivative of gas-dynamic is confirmed to be the driving parameter for evaluating non-ideal thermodynamic effects related to the dynamic calibration of fast-response aerodynamic pressure probes.

Transient dynamics in trial-offer markets with social influence: Trade-offs between appeal and quality

PubMed Central

Altszyler, Edgar; Berbeglia, Franco; Van Hentenryck, Pascal

2017-01-01

We study a trial-offer market where consumers may purchase one of two competing products. Consumer preferences are affected by the products quality, their appeal, and their popularity. While the asymptotic convergence or stationary states of these, and related dynamical systems, has been vastly studied, the literature regarding the transitory dynamics remains surprisingly sparse. To fill this gap, we derive a system of Ordinary Differential Equations, which is solved exactly to gain insight into the roles played by product qualities and appeals in the market behavior. We observe a logarithmic tradeoff between quality and appeal for medium and long-term marketing strategies: The expected market shares remain constant if a decrease in quality is followed by an exponential increase in the product appeal. However, for short time horizons, the trade-off is linear. Finally, we study the variability of the dynamics through Monte Carlo simulations and discover that low appeals may result in high levels of variability. The model results suggest effective marketing strategies for short and long time horizons and emphasize the significance of advertising early in the market life to increase sales and predictability. PMID:28746334

Transient dynamics in trial-offer markets with social influence: Trade-offs between appeal and quality.

PubMed

Altszyler, Edgar; Berbeglia, Franco; Berbeglia, Gerardo; Van Hentenryck, Pascal

2017-01-01

We study a trial-offer market where consumers may purchase one of two competing products. Consumer preferences are affected by the products quality, their appeal, and their popularity. While the asymptotic convergence or stationary states of these, and related dynamical systems, has been vastly studied, the literature regarding the transitory dynamics remains surprisingly sparse. To fill this gap, we derive a system of Ordinary Differential Equations, which is solved exactly to gain insight into the roles played by product qualities and appeals in the market behavior. We observe a logarithmic tradeoff between quality and appeal for medium and long-term marketing strategies: The expected market shares remain constant if a decrease in quality is followed by an exponential increase in the product appeal. However, for short time horizons, the trade-off is linear. Finally, we study the variability of the dynamics through Monte Carlo simulations and discover that low appeals may result in high levels of variability. The model results suggest effective marketing strategies for short and long time horizons and emphasize the significance of advertising early in the market life to increase sales and predictability.

Fuzzy CMAC With incremental Bayesian Ying-Yang learning and dynamic rule construction.

PubMed

Nguyen, M N

2010-04-01

Inspired by the philosophy of ancient Chinese Taoism, Xu's Bayesian ying-yang (BYY) learning technique performs clustering by harmonizing the training data (yang) with the solution (ying). In our previous work, the BYY learning technique was applied to a fuzzy cerebellar model articulation controller (FCMAC) to find the optimal fuzzy sets; however, this is not suitable for time series data analysis. To address this problem, we propose an incremental BYY learning technique in this paper, with the idea of sliding window and rule structure dynamic algorithms. Three contributions are made as a result of this research. First, an online expectation-maximization algorithm incorporated with the sliding window is proposed for the fuzzification phase. Second, the memory requirement is greatly reduced since the entire data set no longer needs to be obtained during the prediction process. Third, the rule structure dynamic algorithm with dynamically initializing, recruiting, and pruning rules relieves the "curse of dimensionality" problem that is inherent in the FCMAC. Because of these features, the experimental results of the benchmark data sets of currency exchange rates and Mackey-Glass show that the proposed model is more suitable for real-time streaming data analysis.

Exact and approximate many-body dynamics with stochastic one-body density matrix evolution

NASA Astrophysics Data System (ADS)

Lacroix, Denis

2005-06-01

We show that the dynamics of interacting fermions can be exactly replaced by a quantum jump theory in the many-body density matrix space. In this theory, jumps occur between densities formed of pairs of Slater determinants, Dab=|Φa><Φb|, where each state evolves according to the stochastic Schrödinger equation given by O. Juillet and Ph. Chomaz [Phys. Rev. Lett. 88, 142503 (2002)]. A stochastic Liouville-von Neumann equation is derived as well as the associated. Bogolyubov-Born-Green-Kirwood-Yvon hierarchy. Due to the specific form of the many-body density along the path, the presented theory is equivalent to a stochastic theory in one-body density matrix space, in which each density matrix evolves according to its own mean-field augmented by a one-body noise. Guided by the exact reformulation, a stochastic mean-field dynamics valid in the weak coupling approximation is proposed. This theory leads to an approximate treatment of two-body effects similar to the extended time-dependent Hartree-Fock scheme. In this stochastic mean-field dynamics, statistical mixing can be directly considered and jumps occur on a coarse-grained time scale. Accordingly, numerical effort is expected to be significantly reduced for applications.

Post-Newtonian evolution of massive black hole triplets in galactic nuclei - II. Survey of the parameter space

NASA Astrophysics Data System (ADS)

Bonetti, Matteo; Haardt, Francesco; Sesana, Alberto; Barausse, Enrico

2018-07-01

Massive black hole binaries (MBHBs) are expected to form at the centre of merging galaxies during the hierarchical assembly of the cosmic structure, and are expected to be the loudest sources of gravitational waves (GWs) in the low-frequency domain. However, because of the dearth of energy exchanges with background stars and gas, many of these MBHBs may stall at separations that are too large for GW emission to drive them to coalescence in less than a Hubble time. Triple MBH systems are then bound to form after a further galaxy merger, triggering a complex and rich dynamics that can eventually lead to MBH coalescence. Here, we report on the results of a large set of numerical simulations, where MBH triplets are set in spherical stellar potentials and MBH dynamics is followed through 2.5 post-Newtonian orders in the equations of motion. From our full suite of simulated systems, we find that a fraction ( ≃ 20-30 per cent) of the MBH binaries that would otherwise stall is led to coalesce within a Hubble time. The corresponding coalescence time-scale peaks around 300 Myr, while the eccentricity close to the plunge, albeit small, is non-negligible (≲0.1). We construct and discuss marginalized probability distributions of the main parameters involved and, in a companion paper of the series, we will use the results presented here to forecast the contribution of MBH triplets to the GW signal in the nHz regime probed by Pulsar Timing Array experiments.

On the contribution of a stochastic background of gravitational radiation to the timing noise of pulsars

NASA Technical Reports Server (NTRS)

Mashhoon, B.

1982-01-01

The influence of a stochastic and isotropic background of gravitational radiation on timing measurements of pulsars is investigated, and it is shown that pulsar timing noise may be used to establish a significant upper limit of about 10 to the -10th on the total energy density of very long-wavelength stochastic gravitational waves. This places restriction on the strength of very long wavelength gravitational waves in the Friedmann model, and such a background is expected to have no significant effect on the approximately 3 K electromagnetic background radiation or on the dynamics of a cluster of galaxies.

Independent Metrics for Protein Backbone and Side-Chain Flexibility: Time Scales and Effects of Ligand Binding.

PubMed

Fuchs, Julian E; Waldner, Birgit J; Huber, Roland G; von Grafenstein, Susanne; Kramer, Christian; Liedl, Klaus R

2015-03-10

Conformational dynamics are central for understanding biomolecular structure and function, since biological macromolecules are inherently flexible at room temperature and in solution. Computational methods are nowadays capable of providing valuable information on the conformational ensembles of biomolecules. However, analysis tools and intuitive metrics that capture dynamic information from in silico generated structural ensembles are limited. In standard work-flows, flexibility in a conformational ensemble is represented through residue-wise root-mean-square fluctuations or B-factors following a global alignment. Consequently, these approaches relying on global alignments discard valuable information on local dynamics. Results inherently depend on global flexibility, residue size, and connectivity. In this study we present a novel approach for capturing positional fluctuations based on multiple local alignments instead of one single global alignment. The method captures local dynamics within a structural ensemble independent of residue type by splitting individual local and global degrees of freedom of protein backbone and side-chains. Dependence on residue type and size in the side-chains is removed via normalization with the B-factors of the isolated residue. As a test case, we demonstrate its application to a molecular dynamics simulation of bovine pancreatic trypsin inhibitor (BPTI) on the millisecond time scale. This allows for illustrating different time scales of backbone and side-chain flexibility. Additionally, we demonstrate the effects of ligand binding on side-chain flexibility of three serine proteases. We expect our new methodology for quantifying local flexibility to be helpful in unraveling local changes in biomolecular dynamics.

Automated Flight Routing Using Stochastic Dynamic Programming

NASA Technical Reports Server (NTRS)

Ng, Hok K.; Morando, Alex; Grabbe, Shon

2010-01-01

Airspace capacity reduction due to convective weather impedes air traffic flows and causes traffic congestion. This study presents an algorithm that reroutes flights in the presence of winds, enroute convective weather, and congested airspace based on stochastic dynamic programming. A stochastic disturbance model incorporates into the reroute design process the capacity uncertainty. A trajectory-based airspace demand model is employed for calculating current and future airspace demand. The optimal routes minimize the total expected traveling time, weather incursion, and induced congestion costs. They are compared to weather-avoidance routes calculated using deterministic dynamic programming. The stochastic reroutes have smaller deviation probability than the deterministic counterpart when both reroutes have similar total flight distance. The stochastic rerouting algorithm takes into account all convective weather fields with all severity levels while the deterministic algorithm only accounts for convective weather systems exceeding a specified level of severity. When the stochastic reroutes are compared to the actual flight routes, they have similar total flight time, and both have about 1% of travel time crossing congested enroute sectors on average. The actual flight routes induce slightly less traffic congestion than the stochastic reroutes but intercept more severe convective weather.

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

NASA Astrophysics Data System (ADS)

Velásquez-Rojas, Fátima; Vazquez, Federico

2017-05-01

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

A state space approach for piecewise-linear recurrent neural networks for identifying computational dynamics from neural measurements.

PubMed

Durstewitz, Daniel

2017-06-01

The computational and cognitive properties of neural systems are often thought to be implemented in terms of their (stochastic) network dynamics. Hence, recovering the system dynamics from experimentally observed neuronal time series, like multiple single-unit recordings or neuroimaging data, is an important step toward understanding its computations. Ideally, one would not only seek a (lower-dimensional) state space representation of the dynamics, but would wish to have access to its statistical properties and their generative equations for in-depth analysis. Recurrent neural networks (RNNs) are a computationally powerful and dynamically universal formal framework which has been extensively studied from both the computational and the dynamical systems perspective. Here we develop a semi-analytical maximum-likelihood estimation scheme for piecewise-linear RNNs (PLRNNs) within the statistical framework of state space models, which accounts for noise in both the underlying latent dynamics and the observation process. The Expectation-Maximization algorithm is used to infer the latent state distribution, through a global Laplace approximation, and the PLRNN parameters iteratively. After validating the procedure on toy examples, and using inference through particle filters for comparison, the approach is applied to multiple single-unit recordings from the rodent anterior cingulate cortex (ACC) obtained during performance of a classical working memory task, delayed alternation. Models estimated from kernel-smoothed spike time data were able to capture the essential computational dynamics underlying task performance, including stimulus-selective delay activity. The estimated models were rarely multi-stable, however, but rather were tuned to exhibit slow dynamics in the vicinity of a bifurcation point. In summary, the present work advances a semi-analytical (thus reasonably fast) maximum-likelihood estimation framework for PLRNNs that may enable to recover relevant aspects of the nonlinear dynamics underlying observed neuronal time series, and directly link these to computational properties.

Dynamic modeling of neuronal responses in fMRI using cubature Kalman filtering.

PubMed

Havlicek, Martin; Friston, Karl J; Jan, Jiri; Brazdil, Milan; Calhoun, Vince D

2011-06-15

This paper presents a new approach to inverting (fitting) models of coupled dynamical systems based on state-of-the-art (cubature) Kalman filtering. Crucially, this inversion furnishes posterior estimates of both the hidden states and parameters of a system, including any unknown exogenous input. Because the underlying generative model is formulated in continuous time (with a discrete observation process) it can be applied to a wide variety of models specified with either ordinary or stochastic differential equations. These are an important class of models that are particularly appropriate for biological time-series, where the underlying system is specified in terms of kinetics or dynamics (i.e., dynamic causal models). We provide comparative evaluations with generalized Bayesian filtering (dynamic expectation maximization) and demonstrate marked improvements in accuracy and computational efficiency. We compare the schemes using a series of difficult (nonlinear) toy examples and conclude with a special focus on hemodynamic models of evoked brain responses in fMRI. Our scheme promises to provide a significant advance in characterizing the functional architectures of distributed neuronal systems, even in the absence of known exogenous (experimental) input; e.g., resting state fMRI studies and spontaneous fluctuations in electrophysiological studies. Importantly, unlike current Bayesian filters (e.g. DEM), our scheme provides estimates of time-varying parameters, which we will exploit in future work on the adaptation and enabling of connections in the brain. Copyright © 2011 Elsevier Inc. All rights reserved.

Minimum time search in uncertain dynamic domains with complex sensorial platforms.

PubMed

Lanillos, Pablo; Besada-Portas, Eva; Lopez-Orozco, Jose Antonio; de la Cruz, Jesus Manuel

2014-08-04

The minimum time search in uncertain domains is a searching task, which appears in real world problems such as natural disasters and sea rescue operations, where a target has to be found, as soon as possible, by a set of sensor-equipped searchers. The automation of this task, where the time to detect the target is critical, can be achieved by new probabilistic techniques that directly minimize the Expected Time (ET) to detect a dynamic target using the observation probability models and actual observations collected by the sensors on board the searchers. The selected technique, described in algorithmic form in this paper for completeness, has only been previously partially tested with an ideal binary detection model, in spite of being designed to deal with complex non-linear/non-differential sensorial models. This paper covers the gap, testing its performance and applicability over different searching tasks with searchers equipped with different complex sensors. The sensorial models under test vary from stepped detection probabilities to continuous/discontinuous differentiable/non-differentiable detection probabilities dependent on distance, orientation, and structured maps. The analysis of the simulated results of several static and dynamic scenarios performed in this paper validates the applicability of the technique with different types of sensor models.

Interfacial self-healing of nanocomposite hydrogels: Theory and experiment

NASA Astrophysics Data System (ADS)

Wang, Qiming; Gao, Zheming; Yu, Kunhao

2017-12-01

Polymers with dynamic bonds are able to self-heal their fractured interfaces and restore the mechanical strengths. It is largely elusive how to analytically model this self-healing behavior to construct the mechanistic relationship between the self-healing properties (e.g., healed interfacial strength and equilibrium healing time) and the material compositions and healing conditions. Here, we take a self-healable nanocomposite hydrogel as an example to illustrate an interfacial self-healing theory for hydrogels with dynamic bonds. In the theory, we consider the free polymer chains diffuse across the interface and reform crosslinks to bridge the interface. We analytically reveal that the healed strengths of nanocomposite hydrogels increase with the healing time in an error-function-like form. The equilibrium self-healing time of the full-strength recovery decreases with the temperature and increases with the nanoparticle concentration. We further analytically reveal that the healed interfacial strength decreases with increasing delaying time before the healing process. The theoretical results quantitatively match with our experiments on nanosilica hydrogels, and also agree well with other researchers' experiments on nanoclay hydrogels. We expect that this theory would open promising avenues for quantitative understanding of the self-healing mechanics of various polymers with dynamic bonds, and offer insights for designing high-performance self-healing polymers.

Minimum Time Search in Uncertain Dynamic Domains with Complex Sensorial Platforms

PubMed Central

Lanillos, Pablo; Besada-Portas, Eva; Lopez-Orozco, Jose Antonio; de la Cruz, Jesus Manuel

2014-01-01

The minimum time search in uncertain domains is a searching task, which appears in real world problems such as natural disasters and sea rescue operations, where a target has to be found, as soon as possible, by a set of sensor-equipped searchers. The automation of this task, where the time to detect the target is critical, can be achieved by new probabilistic techniques that directly minimize the Expected Time (ET) to detect a dynamic target using the observation probability models and actual observations collected by the sensors on board the searchers. The selected technique, described in algorithmic form in this paper for completeness, has only been previously partially tested with an ideal binary detection model, in spite of being designed to deal with complex non-linear/non-differential sensorial models. This paper covers the gap, testing its performance and applicability over different searching tasks with searchers equipped with different complex sensors. The sensorial models under test vary from stepped detection probabilities to continuous/discontinuous differentiable/non-differentiable detection probabilities dependent on distance, orientation, and structured maps. The analysis of the simulated results of several static and dynamic scenarios performed in this paper validates the applicability of the technique with different types of sensor models. PMID:25093345

Post-Newtonian evolution of massive black hole triplets in galactic nuclei - II. Survey of the parameter space

NASA Astrophysics Data System (ADS)

Bonetti, Matteo; Haardt, Francesco; Sesana, Alberto; Barausse, Enrico

2018-04-01

Massive black hole binaries (MBHBs) are expected to form at the centre of merging galaxies during the hierarchical assembly of the cosmic structure, and are expected to be the loudest sources of gravitational waves (GWs) in the low frequency domain. However, because of the dearth of energy exchanges with background stars and gas, many of these MBHBs may stall at separations too large for GW emission to drive them to coalescence in less than a Hubble time. Triple MBH systems are then bound to form after a further galaxy merger, triggering a complex and rich dynamics that can eventually lead to MBH coalescence. Here we report on the results of a large set of numerical simulations, where MBH triplets are set in spherical stellar potentials and MBH dynamics is followed through 2.5 post-Newtonian order in the equations of motion. From our full suite of simulated systems we find that a fraction ≃ 20 - 30 % of the MBH binaries that would otherwise stall are led to coalesce within a Hubble time. The corresponding coalescence timescale peaks around 300 Myr, while the eccentricity close to the plunge, albeit small, is non-negligible (≲ 0.1). We construct and discuss marginalised probability distributions of the main parameters involved and, in a companion paper of the series, we will use the results presented here to forecast the contribution of MBH triplets to the GW signal in the nHz regime probed by Pulsar Timing Array experiments.

Signature of Two-Component Advective Flow in several Black Hole candidates obtained through time-of-arrival analysis of RXTE/ASM Data

NASA Astrophysics Data System (ADS)

Ghosh, Arindam; Chakrabarti, Sandip K.

2018-05-01

We study several Galactic black hole candidates using long-time RXTE/ASM X-ray data to search for telltale signatures of differences in viscous timescales in the two components used in the Two-Component Advective Flow (TCAF) paradigm. In high-mass X-ray binaries (HMXBs) mainly winds are accreted. This nearly inviscid and dominant sub-Keplerian flow falls almost freely towards the black hole. A standard Keplerian disc can form out of this sub-Keplerian matter in presence of a significant viscosity and could be small in size. However, in low-mass X-ray binaries (LMXBs), highly viscous and larger Keplerian accretion disc is expected to form inside the sub-Keplerian disc due to the Roche-lobe overflow. Due to two viscous timescales in these two components, it is expected to have a larger lag between the times-of-arrival of these components in LMXBs than that in HMXBs. Direct cross-correlation between the photon fluxes will not reveal this lag since they lack linear dependence; however, they are coupled through the viscous processes which bring in both matter. To quantify the aforesaid time lag, we introduce an index (Θ), which is a proxy of the usual photon index (Γ). Thus, when Θ, being dynamically responsive to both fluxes, is considered as a reference, the arrival time lag between the two fluxes in LMXBs is found to be much larger than that in HMXBs. Our result establishes the presence of two dynamical components in accretion and shows that the Keplerian disc size indeed is smaller in HMXBs as compared to that in LMXBs.

Buffet test in the National Transonic Facility

NASA Technical Reports Server (NTRS)

Young, Clarence P., Jr.; Hergert, Dennis W.; Butler, Thomas W.; Herring, Fred M.

1992-01-01

A buffet test of a commercial transport model was accomplished in the National Transonic Facility at the NASA Langley Research Center. This aeroelastic test was unprecedented for this wind tunnel and posed a high risk to the facility. This paper presents the test results from a structural dynamics and aeroelastic response point of view and describes the activities required for the safety analysis and risk assessment. The test was conducted in the same manner as a flutter test and employed onboard dynamic instrumentation, real time dynamic data monitoring, automatic, and manual tunnel interlock systems for protecting the model. The procedures and test techniques employed for this test are expected to serve as the basis for future aeroelastic testing in the National Transonic Facility. This test program was a cooperative effort between the Boeing Commercial Airplane Company and the NASA Langley Research Center.

Filtering Using Nonlinear Expectations

DTIC Science & Technology

2016-04-16

gives a solution to estimating a Markov chain observed in Gaussian noise when the variance of the noise is unkown. This paper is accepted for the IEEE...Optimization, an A* journal. A short third paper discusses how to estimate a change in the transition dynamics of a noisily observed Markov chain ...The change point time is hidden in a hidden Markov chain , so a second level of discovery is involved. This paper is accepted for Communications in

Application of time series analysis on molecular dynamics simulations of proteins: a study of different conformational spaces by principal component analysis.

PubMed

Alakent, Burak; Doruker, Pemra; Camurdan, Mehmet C

2004-09-08

Time series analysis is applied on the collective coordinates obtained from principal component analysis of independent molecular dynamics simulations of alpha-amylase inhibitor tendamistat and immunity protein of colicin E7 based on the Calpha coordinates history. Even though the principal component directions obtained for each run are considerably different, the dynamics information obtained from these runs are surprisingly similar in terms of time series models and parameters. There are two main differences in the dynamics of the two proteins: the higher density of low frequencies and the larger step sizes for the interminima motions of colicin E7 than those of alpha-amylase inhibitor, which may be attributed to the higher number of residues of colicin E7 and/or the structural differences of the two proteins. The cumulative density function of the low frequencies in each run conforms to the expectations from the normal mode analysis. When different runs of alpha-amylase inhibitor are projected on the same set of eigenvectors, it is found that principal components obtained from a certain conformational region of a protein has a moderate explanation power in other conformational regions and the local minima are similar to a certain extent, while the height of the energy barriers in between the minima significantly change. As a final remark, time series analysis tools are further exploited in this study with the motive of explaining the equilibrium fluctuations of proteins. Copyright 2004 American Institute of Physics

Application of time series analysis on molecular dynamics simulations of proteins: A study of different conformational spaces by principal component analysis

NASA Astrophysics Data System (ADS)

Alakent, Burak; Doruker, Pemra; Camurdan, Mehmet C.

2004-09-01

Time series analysis is applied on the collective coordinates obtained from principal component analysis of independent molecular dynamics simulations of α-amylase inhibitor tendamistat and immunity protein of colicin E7 based on the Cα coordinates history. Even though the principal component directions obtained for each run are considerably different, the dynamics information obtained from these runs are surprisingly similar in terms of time series models and parameters. There are two main differences in the dynamics of the two proteins: the higher density of low frequencies and the larger step sizes for the interminima motions of colicin E7 than those of α-amylase inhibitor, which may be attributed to the higher number of residues of colicin E7 and/or the structural differences of the two proteins. The cumulative density function of the low frequencies in each run conforms to the expectations from the normal mode analysis. When different runs of α-amylase inhibitor are projected on the same set of eigenvectors, it is found that principal components obtained from a certain conformational region of a protein has a moderate explanation power in other conformational regions and the local minima are similar to a certain extent, while the height of the energy barriers in between the minima significantly change. As a final remark, time series analysis tools are further exploited in this study with the motive of explaining the equilibrium fluctuations of proteins.

Including trait-based early warning signals helps predict population collapse

PubMed Central

Clements, Christopher F.; Ozgul, Arpat

2016-01-01

Foreseeing population collapse is an on-going target in ecology, and this has led to the development of early warning signals based on expected changes in leading indicators before a bifurcation. Such signals have been sought for in abundance time-series data on a population of interest, with varying degrees of success. Here we move beyond these established methods by including parallel time-series data of abundance and fitness-related trait dynamics. Using data from a microcosm experiment, we show that including information on the dynamics of phenotypic traits such as body size into composite early warning indices can produce more accurate inferences of whether a population is approaching a critical transition than using abundance time-series alone. By including fitness-related trait information alongside traditional abundance-based early warning signals in a single metric of risk, our generalizable approach provides a powerful new way to assess what populations may be on the verge of collapse. PMID:27009968

Shear-stress fluctuations and relaxation in polymer glasses

NASA Astrophysics Data System (ADS)

Kriuchevskyi, I.; Wittmer, J. P.; Meyer, H.; Benzerara, O.; Baschnagel, J.

2018-01-01

We investigate by means of molecular dynamics simulation a coarse-grained polymer glass model focusing on (quasistatic and dynamical) shear-stress fluctuations as a function of temperature T and sampling time Δ t . The linear response is characterized using (ensemble-averaged) expectation values of the contributions (time averaged for each shear plane) to the stress-fluctuation relation μsf for the shear modulus and the shear-stress relaxation modulus G (t ) . Using 100 independent configurations, we pay attention to the respective standard deviations. While the ensemble-averaged modulus μsf(T ) decreases continuously with increasing T for all Δ t sampled, its standard deviation δ μsf(T ) is nonmonotonic with a striking peak at the glass transition. The question of whether the shear modulus is continuous or has a jump singularity at the glass transition is thus ill posed. Confirming the effective time-translational invariance of our systems, the Δ t dependence of μsf and related quantities can be understood using a weighted integral over G (t ) .

Asymmetric nanoparticle may go "active" at room temperature

NASA Astrophysics Data System (ADS)

Sheng, Nan; Tu, YuSong; Guo, Pan; Wan, RongZheng; Wang, ZuoWei; Fang, HaiPing

2017-04-01

Using molecular dynamics simulations, we show that an asymmetrically shaped nanoparticle in dilute solution possesses a spontaneously curved trajectory within a finite time interval, instead of the generally expected random walk. This unexpected dynamic behavior has a similarity to that of active matters, such as swimming bacteria, cells, or even fish, but is of a different physical origin. The key to the curved trajectory lies in the non-zero resultant force originated from the imbalance of the collision forces acted by surrounding solvent molecules on the asymmetrically shaped nanoparticle during its orientation regulation. Theoretical formulae based on microscopic observations have been derived to describe this non-zero force and the resulting motion of the asymmetrically shaped nanoparticle.

Optimal feedback scheme and universal time scaling for Hamiltonian parameter estimation.

PubMed

Yuan, Haidong; Fung, Chi-Hang Fred

2015-09-11

Time is a valuable resource and it is expected that a longer time period should lead to better precision in Hamiltonian parameter estimation. However, recent studies in quantum metrology have shown that in certain cases more time may even lead to worse estimations, which puts this intuition into question. In this Letter we show that by including feedback controls this intuition can be restored. By deriving asymptotically optimal feedback controls we quantify the maximal improvement feedback controls can provide in Hamiltonian parameter estimation and show a universal time scaling for the precision limit under the optimal feedback scheme. Our study reveals an intriguing connection between noncommutativity in the dynamics and the gain of feedback controls in Hamiltonian parameter estimation.

A dynamic model for organic waste management in Quebec (D-MOWIQ) as a tool to review environmental, societal and economic perspectives of a waste management policy.

PubMed

Hénault-Ethier, Louise; Martin, Jean-Philippe; Housset, Johann

2017-08-01

A dynamic systems model of organic waste management for the province of Quebec, Canada, was built. Six distinct modules taking into account social, economical and environmental issues and perspectives were included. Five scenarios were designed and tested to identify the potential consequences of different governmental and demographic combinations of decisions over time. Among these scenarios, one examines Quebec's organic waste management policy (2011-2015), while the other scenarios represent business as usual or emphasize ecology, economy or social benefits in the decision-making process. Model outputs suggest that the current governmental policy should yield favorable environmental benefits, energy production and waste valorization. The projections stemming from the current policy action plan approach the benefits gained by another scenario emphasizing the environmental aspects in the decision-making process. As expected, without the current policy and action plan in place, or business as usual, little improvements are expected in waste management compared to current trends, and strictly emphasizing economic imperatives does not favor sustainable organic waste management. Copyright © 2017. Published by Elsevier Ltd.

Observing the clustering properties of galaxy clusters in dynamical dark-energy cosmologies

NASA Astrophysics Data System (ADS)

Fedeli, C.; Moscardini, L.; Bartelmann, M.

2009-06-01

We study the clustering properties of galaxy clusters expected to be observed by various forthcoming surveys both in the X-ray and sub-mm regimes by the thermal Sunyaev-Zel'dovich effect. Several different background cosmological models are assumed, including the concordance ΛCDM and various cosmologies with dynamical evolution of the dark energy. Particular attention is paid to models with a significant contribution of dark energy at early times which affects the process of structure formation. Past light cone and selection effects in cluster catalogs are carefully modeled by realistic scaling relations between cluster mass and observables and by properly taking into account the selection functions of the different instruments. The results show that early dark-energy models are expected to produce significantly lower values of effective bias and both spatial and angular correlation amplitudes with respect to the standard ΛCDM model. Among the cluster catalogs studied in this work, it turns out that those based on eRosita, Planck, and South Pole Telescope observations are the most promising for distinguishing between various dark-energy models.

Perceptual grouping effects on cursor movement expectations.

PubMed

Dorneich, Michael C; Hamblin, Christopher J; Lancaster, Jeff A; Olofinboba, Olu

2014-05-01

Two studies were conducted to develop an understanding of factors that drive user expectations when navigating between discrete elements on a display via a limited degree-of-freedom cursor control device. For the Orion Crew Exploration Vehicle spacecraft, a free-floating cursor with a graphical user interface (GUI) would require an unachievable level of accuracy due to expected acceleration and vibration conditions during dynamic phases of flight. Therefore, Orion program proposed using a "caged" cursor to "jump" from one controllable element (node) on the GUI to another. However, nodes are not likely to be arranged on a rectilinear grid, and so movements between nodes are not obvious. Proximity between nodes, direction of nodes relative to each other, and context features may all contribute to user cursor movement expectations. In an initial study, we examined user expectations based on the nodes themselves. In a second study, we examined the effect of context features on user expectations. The studies established that perceptual grouping effects influence expectations to varying degrees. Based on these results, a simple rule set was developed to support users in building a straightforward mental model that closely matches their natural expectations for cursor movement. The results will help designers of display formats take advantage of the natural context-driven cursor movement expectations of users to reduce navigation errors, increase usability, and decrease access time. The rules set and guidelines tie theory to practice and can be applied in environments where vibration or acceleration are significant, including spacecraft, aircraft, and automobiles.

Romantic Relationship Dynamics of Urban African American Adolescents: Patterns of Monogamy, Commitment, and Trust.

PubMed

Towner, Senna L; Dolcini, M Margaret; Harper, Gary W

2015-05-01

Relationship dynamics develop early in life and are influenced by social environments. STI/HIV prevention programs need to consider romantic relationship dynamics that contribute to sexual health. The aim of this study was to examine monogamous patterns, commitment, and trust in African American adolescent romantic relationships. The authors also focused on the differences in these dynamics between and within gender. The way that such dynamics interplay in romantic relationships has the potential to influence STI/HIV acquisition risk. In-depth interviews were conducted with 28 African American adolescents aged 14 to 21 living in San Francisco. Our results discuss data related to monogamous behaviors, expectations, and values; trust and respect in romantic relationships; commitment to romantic relationships; and outcomes of mismatched relationship expectations. Incorporating gender-specific romantic relationships dynamics can enhance the effectiveness of prevention programs.

Reduced Dynamics of the Non-holonomic Whipple Bicycle

NASA Astrophysics Data System (ADS)

Boyer, Frédéric; Porez, Mathieu; Mauny, Johan

2018-06-01

Though the bicycle is a familiar object of everyday life, modeling its full nonlinear three-dimensional dynamics in a closed symbolic form is a difficult issue for classical mechanics. In this article, we address this issue without resorting to the usual simplifications on the bicycle kinematics nor its dynamics. To derive this model, we use a general reduction-based approach in the principal fiber bundle of configurations of the three-dimensional bicycle. This includes a geometrically exact model of the contacts between the wheels and the ground, the explicit calculation of the kernel of constraints, along with the dynamics of the system free of any external forces, and its projection onto the kernel of admissible velocities. The approach takes benefits of the intrinsic formulation of geometric mechanics. Along the path toward the final equations, we show that the exact model of the bicycle dynamics requires to cope with a set of non-symmetric constraints with respect to the structural group of its configuration fiber bundle. The final reduced dynamics are simulated on several examples representative of the bicycle. As expected the constraints imposed by the ground contacts, as well as the energy conservation, are satisfied, while the dynamics can be numerically integrated in real time.

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

PubMed

Tuljapurkar, Shripad; Horvitz, Carol C

2006-06-01

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

Momentum conserving Brownian dynamics propagator for complex soft matter fluids

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

Padding, J. T.; Briels, W. J.

2014-12-28

We present a Galilean invariant, momentum conserving first order Brownian dynamics scheme for coarse-grained simulations of highly frictional soft matter systems. Friction forces are taken to be with respect to moving background material. The motion of the background material is described by locally averaged velocities in the neighborhood of the dissolved coarse coordinates. The velocity variables are updated by a momentum conserving scheme. The properties of the stochastic updates are derived through the Chapman-Kolmogorov and Fokker-Planck equations for the evolution of the probability distribution of coarse-grained position and velocity variables, by requiring the equilibrium distribution to be a stationary solution.more » We test our new scheme on concentrated star polymer solutions and find that the transverse current and velocity time auto-correlation functions behave as expected from hydrodynamics. In particular, the velocity auto-correlation functions display a long time tail in complete agreement with hydrodynamics.« less

Output-Feedback Control of Unknown Linear Discrete-Time Systems With Stochastic Measurement and Process Noise via Approximate Dynamic Programming.

PubMed

Wang, Jun-Sheng; Yang, Guang-Hong

2017-07-25

This paper studies the optimal output-feedback control problem for unknown linear discrete-time systems with stochastic measurement and process noise. A dithered Bellman equation with the innovation covariance matrix is constructed via the expectation operator given in the form of a finite summation. On this basis, an output-feedback-based approximate dynamic programming method is developed, where the terms depending on the innovation covariance matrix are available with the aid of the innovation covariance matrix identified beforehand. Therefore, by iterating the Bellman equation, the resulting value function can converge to the optimal one in the presence of the aforementioned noise, and the nearly optimal control laws are delivered. To show the effectiveness and the advantages of the proposed approach, a simulation example and a velocity control experiment on a dc machine are employed.

Frequency-Swept Integrated and Stretched Solid Effect Dynamic Nuclear Polarization.

PubMed

Can, T V; McKay, J E; Weber, R T; Yang, C; Dubroca, T; van Tol, J; Hill, S; Griffin, R G

2018-06-21

We investigate a new time domain approach to dynamic nuclear polarization (DNP), the frequency-swept integrated solid effect (FS-ISE), utilizing a high power, broadband 94 GHz (3.35 T) pulse EPR spectrometer. The bandwidth of the spectrometer enabled measurement of the DNP Zeeman frequency/field profile that revealed two dominant polarization mechanisms, the expected ISE, and a recently observed mechanism, the stretched solid effect (S 2 E). At 94 GHz, despite the limitations in the microwave chirp pulse length (10 μs) and the repetition rate (2 kHz), we obtained signal enhancements up to ∼70 for the S 2 E and ∼50 for the ISE. The results successfully demonstrate the viability of the FS-ISE and S 2 E DNP at a frequency 10 times higher than previous studies. Our results also suggest that these approaches are candidates for implementation at higher magnetic fields.

Comment on “Symplectic integration of magnetic systems”: A proof that the Boris algorithm is not variational

DOE PAGES

Ellison, C. L.; Burby, J. W.; Qin, H.

2015-11-01

One popular technique for the numerical time advance of charged particles interacting with electric and magnetic fields according to the Lorentz force law [1], [2], [3] and [4] is the Boris algorithm. Its popularity stems from simple implementation, rapid iteration, and excellent long-term numerical fidelity [1] and [5]. Excellent long-term behavior strongly suggests the numerical dynamics exhibit conservation laws analogous to those governing the continuous Lorentz force system [6]. Moreover, without conserved quantities to constrain the numerical dynamics, algorithms typically dissipate or accumulate important observables such as energy and momentum over long periods of simulated time [6]. Identification of themore » conservative properties of an algorithm is important for establishing rigorous expectations on the long-term behavior; energy-preserving, symplectic, and volume-preserving methods each have particular implications for the qualitative numerical behavior [6], [7], [8], [9], [10] and [11].« less

Hemoglobin Dynamics in Red Blood Cells: Correlation to Body Temperature

PubMed Central

Stadler, A. M.; Digel, I.; Artmann, G. M.; Embs, J. P.; Zaccai, G.; Büldt, G.

2008-01-01

A transition in hemoglobin behavior at close to body temperature has been discovered recently by micropipette aspiration experiments on single red blood cells (RBCs) and circular dichroism spectroscopy on hemoglobin solutions. The transition temperature was directly correlated to the body temperatures of a variety of species. In an exploration of the molecular basis for the transition, we present neutron scattering measurements of the temperature dependence of hemoglobin dynamics in whole human RBCs in vivo. The data reveal a change in the geometry of internal protein motions at 36.9°C, at human body temperature. Above that temperature, amino acid side-chain motions occupy larger volumes than expected from normal temperature dependence, indicating partial unfolding of the protein. Global protein diffusion in RBCs was also measured and the findings compared favorably with theoretical predictions for short-time self-diffusion of noncharged hard-sphere colloids. The results demonstrated that changes in molecular dynamics in the picosecond time range and angstrom length scale might well be connected to a macroscopic effect on whole RBCs that occurs at body temperature. PMID:18708462

Self-Induced Switchings between Multiple Space-Time Patterns on Complex Networks of Excitable Units

NASA Astrophysics Data System (ADS)

Ansmann, Gerrit; Lehnertz, Klaus; Feudel, Ulrike

2016-01-01

We report on self-induced switchings between multiple distinct space-time patterns in the dynamics of a spatially extended excitable system. These switchings between low-amplitude oscillations, nonlinear waves, and extreme events strongly resemble a random process, although the system is deterministic. We show that a chaotic saddle—which contains all the patterns as well as channel-like structures that mediate the transitions between them—is the backbone of such a pattern-switching dynamics. Our analyses indicate that essential ingredients for the observed phenomena are that the system behaves like an inhomogeneous oscillatory medium that is capable of self-generating spatially localized excitations and that is dominated by short-range connections but also features long-range connections. With our findings, we present an alternative to the well-known ways to obtain self-induced pattern switching, namely, noise-induced attractor hopping, heteroclinic orbits, and adaptation to an external signal. This alternative way can be expected to improve our understanding of pattern switchings in spatially extended natural dynamical systems like the brain and the heart.

Hemoglobin dynamics in red blood cells: correlation to body temperature.

PubMed

Stadler, A M; Digel, I; Artmann, G M; Embs, J P; Zaccai, G; Büldt, G

2008-12-01

A transition in hemoglobin behavior at close to body temperature has been discovered recently by micropipette aspiration experiments on single red blood cells (RBCs) and circular dichroism spectroscopy on hemoglobin solutions. The transition temperature was directly correlated to the body temperatures of a variety of species. In an exploration of the molecular basis for the transition, we present neutron scattering measurements of the temperature dependence of hemoglobin dynamics in whole human RBCs in vivo. The data reveal a change in the geometry of internal protein motions at 36.9 degrees C, at human body temperature. Above that temperature, amino acid side-chain motions occupy larger volumes than expected from normal temperature dependence, indicating partial unfolding of the protein. Global protein diffusion in RBCs was also measured and the findings compared favorably with theoretical predictions for short-time self-diffusion of noncharged hard-sphere colloids. The results demonstrated that changes in molecular dynamics in the picosecond time range and angstrom length scale might well be connected to a macroscopic effect on whole RBCs that occurs at body temperature.

Analysis and Design of International Emission Trading Markets Applying System Dynamics Techniques

NASA Astrophysics Data System (ADS)

Hu, Bo; Pickl, Stefan

2010-11-01

The design and analysis of international emission trading markets is an important actual challenge. Time-discrete models are needed to understand and optimize these procedures. We give an introduction into this scientific area and present actual modeling approaches. Furthermore, we develop a model which is embedded in a holistic problem solution. Measures for energy efficiency are characterized. The economic time-discrete "cap-and-trade" mechanism is influenced by various underlying anticipatory effects. With a systematic dynamic approach the effects can be examined. First numerical results show that fair international emissions trading can only be conducted with the use of protective export duties. Furthermore a comparatively high price which evokes emission reduction inevitably has an inhibiting effect on economic growth according to our model. As it always has been expected it is not without difficulty to find a balance between economic growth and emission reduction. It can be anticipated using our System Dynamics model simulation that substantial changes must be taken place before international emissions trading markets can contribute to global GHG emissions mitigation.

Locally adaptive parallel temperature accelerated dynamics method

NASA Astrophysics Data System (ADS)

Shim, Yunsic; Amar, Jacques G.

2010-03-01

The recently-developed temperature-accelerated dynamics (TAD) method [M. Sørensen and A.F. Voter, J. Chem. Phys. 112, 9599 (2000)] along with the more recently developed parallel TAD (parTAD) method [Y. Shim et al, Phys. Rev. B 76, 205439 (2007)] allow one to carry out non-equilibrium simulations over extended time and length scales. The basic idea behind TAD is to speed up transitions by carrying out a high-temperature MD simulation and then use the resulting information to obtain event times at the desired low temperature. In a typical implementation, a fixed high temperature Thigh is used. However, in general one expects that for each configuration there exists an optimal value of Thigh which depends on the particular transition pathways and activation energies for that configuration. Here we present a locally adaptive high-temperature TAD method in which instead of using a fixed Thigh the high temperature is dynamically adjusted in order to maximize simulation efficiency. Preliminary results of the performance obtained from parTAD simulations of Cu/Cu(100) growth using the locally adaptive Thigh method will also be presented.

Dynamic evaluation of seismic hazard and risks based on the Unified Scaling Law for Earthquakes

NASA Astrophysics Data System (ADS)

Kossobokov, V. G.; Nekrasova, A.

2016-12-01

We continue applying the general concept of seismic risk analysis in a number of seismic regions worldwide by constructing seismic hazard maps based on the Unified Scaling Law for Earthquakes (USLE), i.e. log N(M,L) = A + B•(6 - M) + C•log L, where N(M,L) is the expected annual number of earthquakes of a certain magnitude M within an seismically prone area of linear dimension L, A characterizes the average annual rate of strong (M = 6) earthquakes, B determines the balance between magnitude ranges, and C estimates the fractal dimension of seismic locus in projection to the Earth surface. The parameters A, B, and C of USLE are used to assess, first, the expected maximum magnitude in a time interval at a seismically prone cell of a uniform grid that cover the region of interest, and then the corresponding expected ground shaking parameters. After a rigorous testing against the available seismic evidences in the past (e.g., the historically reported macro-seismic intensity or paleo data), such a seismic hazard map is used to generate maps of specific earthquake risks for population, cities, and infrastructures. The hazard maps for a given territory change dramatically, when the methodology is applied to a certain size moving time window, e.g. about a decade long for an intermediate-term regional assessment or exponentially increasing intervals for a daily local strong aftershock forecasting. The of dynamical seismic hazard and risks assessment is illustrated by applications to the territory of Greater Caucasus and Crimea and the two-year series of aftershocks of the 11 October 2008 Kurchaloy, Chechnya earthquake which case-history appears to be encouraging for further systematic testing as potential short-term forecasting tool.

Dynamical error bounds for continuum discretisation via Gauss quadrature rules—A Lieb-Robinson bound approach

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

Woods, M. P.; Centre for Quantum Technologies, National University of Singapore; QuTech, Delft University of Technology, Lorentzweg 1, 2611 CJ Delft

2016-02-15

Instances of discrete quantum systems coupled to a continuum of oscillators are ubiquitous in physics. Often the continua are approximated by a discrete set of modes. We derive error bounds on expectation values of system observables that have been time evolved under such discretised Hamiltonians. These bounds take on the form of a function of time and the number of discrete modes, where the discrete modes are chosen according to Gauss quadrature rules. The derivation makes use of tools from the field of Lieb-Robinson bounds and the theory of orthonormal polynomials.

Massive Black-Hole Binary Mergers: Dynamics, Environments & Expected Detections

NASA Astrophysics Data System (ADS)

Kelley, Luke Zoltan

2018-05-01

This thesis studies the populations and dynamics of massive black-hole binaries and their mergers, and explores the implications for electromagnetic and gravitational-wave signals that will be detected in the near future. Massive black-holes (MBH) reside in the centers of galaxies, and when galaxies merge, their MBH interact and often pair together. We base our study on the populations of MBH and galaxies from the `Illustris' cosmological hydrodynamic simulations. The bulk of the binary merger dynamics, however, are unresolved in cosmological simulations. We implement a suite of comprehensive physical models for the merger process, like dynamical friction and gravitational wave emission, which are added in post-processing. Contrary to many previous studies, we find that the most massive binaries with near equal-mass companions are the most efficient at coalescing; though the process still typically takes gigayears.From the data produced by these MBH binary populations and their dynamics, we calculate the expected gravitational wave (GW) signals: both the stochastic, GW background of countless unresolved sources, and the GW foreground of individually resolvable binaries which resound above the noise. Ongoing experiments, called pulsar timing arrays, are sensitive to both of these types of signals. We find that, while the current lack of detections is unsurprising, both the background and foreground will plausibly be detected in the next decade. Unlike previous studies which have predicted the foreground to be significantly harder to detect than the background, we find their typical amplitudes are comparable.With traditional electromagnetic observations, there has also been a dearth of confirmed detections of MBH binary systems. We use our binaries, combined with models of emission from accreting MBH systems, to make predictions for the occurrence rate of systems observable using photometric, periodic-variability surveys. These variables should be detectable in current surveys, and indeed, we expect many candidates recently identified to be true binaries - though a significant fraction are likely false positives. Overall, this thesis finds the science of MBH binaries at an exciting cusp: just before incredible breakthroughs in observations, both electromagnetically and in the new age of gravitational wave astrophysics.

Group Dynamics in Automatic Imitation

PubMed Central

Wilson, Neil; Reddy, Geetha; Catmur, Caroline

2016-01-01

Imitation–matching the configural body movements of another individual–plays a crucial part in social interaction. We investigated whether automatic imitation is not only influenced by who we imitate (ingroup vs. outgroup member) but also by the nature of an expected interaction situation (competitive vs. cooperative). In line with assumptions from Social Identity Theory), we predicted that both social group membership and the expected situation impact on the level of automatic imitation. We adopted a 2 (group membership target: ingroup, outgroup) x 2 (situation: cooperative, competitive) design. The dependent variable was the degree to which participants imitated the target in a reaction time automatic imitation task. 99 female students from two British Universities participated. We found a significant two-way interaction on the imitation effect. When interacting in expectation of cooperation, imitation was stronger for an ingroup target compared to an outgroup target. However, this was not the case in the competitive condition where imitation did not differ between ingroup and outgroup target. This demonstrates that the goal structure of an expected interaction will determine the extent to which intergroup relations influence imitation, supporting a social identity approach. PMID:27657926

Group Dynamics in Automatic Imitation.

PubMed

Gleibs, Ilka H; Wilson, Neil; Reddy, Geetha; Catmur, Caroline

Imitation-matching the configural body movements of another individual-plays a crucial part in social interaction. We investigated whether automatic imitation is not only influenced by who we imitate (ingroup vs. outgroup member) but also by the nature of an expected interaction situation (competitive vs. cooperative). In line with assumptions from Social Identity Theory), we predicted that both social group membership and the expected situation impact on the level of automatic imitation. We adopted a 2 (group membership target: ingroup, outgroup) x 2 (situation: cooperative, competitive) design. The dependent variable was the degree to which participants imitated the target in a reaction time automatic imitation task. 99 female students from two British Universities participated. We found a significant two-way interaction on the imitation effect. When interacting in expectation of cooperation, imitation was stronger for an ingroup target compared to an outgroup target. However, this was not the case in the competitive condition where imitation did not differ between ingroup and outgroup target. This demonstrates that the goal structure of an expected interaction will determine the extent to which intergroup relations influence imitation, supporting a social identity approach.

Picking battles wisely: plant behaviour under competition.

PubMed

Novoplansky, Ariel

2009-06-01

Plants are limited in their ability to choose their neighbours, but they are able to orchestrate a wide spectrum of rational competitive behaviours that increase their prospects to prevail under various ecological settings. Through the perception of neighbours, plants are able to anticipate probable competitive interactions and modify their competitive behaviours to maximize their long-term gains. Specifically, plants can minimize competitive encounters by avoiding their neighbours; maximize their competitive effects by aggressively confronting their neighbours; or tolerate the competitive effects of their neighbours. However, the adaptive values of these non-mutually exclusive options are expected to depend strongly on the plants' evolutionary background and to change dynamically according to their past development, and relative sizes and vigour. Additionally, the magnitude of competitive responsiveness is expected to be positively correlated with the reliability of the environmental information regarding the expected competitive interactions and the expected time left for further plastic modifications. Concurrent competition over external and internal resources and morphogenetic signals may enable some plants to increase their efficiency and external competitive performance by discriminately allocating limited resources to their more promising organs at the expense of failing or less successful organs.

Origin of two time-scale regimes in potentiometric titration of metal oxides. A replica kinetic Monte Carlo study.

PubMed

Zarzycki, Piotr; Rosso, Kevin M

2009-06-16

Replica kinetic Monte Carlo simulations were used to study the characteristic time scales of potentiometric titration of the metal oxides and (oxy)hydroxides. The effect of surface heterogeneity and surface transformation on the titration kinetics were also examined. Two characteristic relaxation times are often observed experimentally, with the trailing slower part attributed to surface nonuniformity, porosity, polymerization, amorphization, and other dynamic surface processes induced by unbalanced surface charge. However, our simulations show that these two characteristic relaxation times are intrinsic to the proton-binding reaction for energetically homogeneous surfaces, and therefore surface heterogeneity or transformation does not necessarily need to be invoked. However, all such second-order surface processes are found to intensify the separation and distinction of the two kinetic regimes. The effect of surface energetic-topographic nonuniformity, as well dynamic surface transformation, interface roughening/smoothing were described in a statistical fashion. Furthermore, our simulations show that a shift in the point-of-zero charge is expected from increased titration speed, and the pH-dependence of the titration measurement error is in excellent agreement with experimental studies.

Learning-based subject-specific estimation of dynamic maps of cortical morphology at missing time points in longitudinal infant studies.

PubMed

Meng, Yu; Li, Gang; Gao, Yaozong; Lin, Weili; Shen, Dinggang

2016-11-01

Longitudinal neuroimaging analysis of the dynamic brain development in infants has received increasing attention recently. Many studies expect a complete longitudinal dataset in order to accurately chart the brain developmental trajectories. However, in practice, a large portion of subjects in longitudinal studies often have missing data at certain time points, due to various reasons such as the absence of scan or poor image quality. To make better use of these incomplete longitudinal data, in this paper, we propose a novel machine learning-based method to estimate the subject-specific, vertex-wise cortical morphological attributes at the missing time points in longitudinal infant studies. Specifically, we develop a customized regression forest, named dynamically assembled regression forest (DARF), as the core regression tool. DARF ensures the spatial smoothness of the estimated maps for vertex-wise cortical morphological attributes and also greatly reduces the computational cost. By employing a pairwise estimation followed by a joint refinement, our method is able to fully exploit the available information from both subjects with complete scans and subjects with missing scans for estimation of the missing cortical attribute maps. The proposed method has been applied to estimating the dynamic cortical thickness maps at missing time points in an incomplete longitudinal infant dataset, which includes 31 healthy infant subjects, each having up to five time points in the first postnatal year. The experimental results indicate that our proposed framework can accurately estimate the subject-specific vertex-wise cortical thickness maps at missing time points, with the average error less than 0.23 mm. Hum Brain Mapp 37:4129-4147, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Hyporheic transport in headwater mountain streams is time-invariant in locations where geologic controls dominate hydrologic forcin

NASA Astrophysics Data System (ADS)

Ward, A. S.; Schmadel, N.; Wondzell, S. M.; Harman, C. J.; Gooseff, M. N.; Singha, K.

2015-12-01

Transport along riparian and hyporheic flowpaths is generally believed to integrate the responses of streams and aquifers to dynamic hydrological forcing. Although it is generally expected transport along these flow paths is time-variable, such dynamic responses have seldom been demonstrated. Further, we do not understand how hydrological forcing interacts with local geologic setting (i.e., valley and streambed morphology) We conducted a series of four stream solute tracer injections in each of two watersheds with contrasting valley morphology in the H.J. Andrews Experimental Forest, monitoring tracer concentrations in the stream and in a network of shallow wells in each watershed. Time series analyses were used to deconvolve transport along subsurface flowpaths from transport in the stream channel. We found time-invariant hyporheic transport in the narrow, bedrock-constrained valley and near large roughness elements (e.g., steps, logs) in the wider valley bottom despite order of magnitude changes in discharge, suggesting geologic controls dominate hyporheic transport in these locations. In contrast, we observed increases in mean arrival time and temporal variance with decreasing discharge at the riparian-hillslope transition, suggesting hydrological dynamics control transport in these locations. We pose several mechanisms by which dynamic hydrology and geologic setting interact that may explain the observed behavior. We interpret time-invariant transport as an indication that discharge in the surface stream is a poor predictor of exchange along the stream-hyporheic-riparian-hillslope continuum in headwater valleys. As such, models able to account for the transition from geologically-dominated processes in the near-stream subsurface to hydrologically-dominated processes near the hillslope are required to predict transport and fate in valley bottoms of headwater mountain streams.

X-38 Experimental Controls Laws

NASA Technical Reports Server (NTRS)

Munday, Steve; Estes, Jay; Bordano, Aldo J.

2000-01-01

X-38 Experimental Control Laws X-38 is a NASA JSC/DFRC experimental flight test program developing a series of prototypes for an International Space Station (ISS) Crew Return Vehicle, often called an ISS "lifeboat." X- 38 Vehicle 132 Free Flight 3, currently scheduled for the end of this month, will be the first flight test of a modem FCS architecture called Multi-Application Control-Honeywell (MACH), originally developed by the Honeywell Technology Center. MACH wraps classical P&I outer attitude loops around a modem dynamic inversion attitude rate loop. The dynamic inversion process requires that the flight computer have an onboard aircraft model of expected vehicle dynamics based upon the aerodynamic database. Dynamic inversion is computationally intensive, so some timing modifications were made to implement MACH on the slower flight computers of the subsonic test vehicles. In addition to linear stability margin analyses and high fidelity 6-DOF simulation, hardware-in-the-loop testing is used to verify the implementation of MACH and its robustness to aerodynamic and environmental uncertainties and disturbances.

Dynamics of the line-start reluctance motor with rotor made of SMC material

NASA Astrophysics Data System (ADS)

Smółka, Krzysztof; Gmyrek, Zbigniew

2017-12-01

Design and control of electric motors in such a way as to ensure the expected motor dynamics, are the problems studied for many years. Many researchers tried to solve this problem, for example by the design optimization or by the use of special control algorithms in electronic systems. In the case of low-power and fractional power motors, the manufacture cost of the final product is many times less than cost of electronic system powering them. The authors of this paper attempt to improve the dynamic of 120 W line-start synchronous reluctance motor, energized by 50 Hz mains (without any electronic systems). The authors seek a road enabling improvement of dynamics of the analyzed motor, by changing the shape and material of the rotor, in such a way to minimize the modification cost of the tools necessary for the motor production. After the initial selection, the analysis of four rotors having different tooth shapes, was conducted.

Quantifying nonergodicity in nonautonomous dissipative dynamical systems: An application to climate change

NASA Astrophysics Data System (ADS)

Drótos, Gábor; Bódai, Tamás; Tél, Tamás

2016-08-01

In nonautonomous dynamical systems, like in climate dynamics, an ensemble of trajectories initiated in the remote past defines a unique probability distribution, the natural measure of a snapshot attractor, for any instant of time, but this distribution typically changes in time. In cases with an aperiodic driving, temporal averages taken along a single trajectory would differ from the corresponding ensemble averages even in the infinite-time limit: ergodicity does not hold. It is worth considering this difference, which we call the nonergodic mismatch, by taking time windows of finite length for temporal averaging. We point out that the probability distribution of the nonergodic mismatch is qualitatively different in ergodic and nonergodic cases: its average is zero and typically nonzero, respectively. A main conclusion is that the difference of the average from zero, which we call the bias, is a useful measure of nonergodicity, for any window length. In contrast, the standard deviation of the nonergodic mismatch, which characterizes the spread between different realizations, exhibits a power-law decrease with increasing window length in both ergodic and nonergodic cases, and this implies that temporal and ensemble averages differ in dynamical systems with finite window lengths. It is the average modulus of the nonergodic mismatch, which we call the ergodicity deficit, that represents the expected deviation from fulfilling the equality of temporal and ensemble averages. As an important finding, we demonstrate that the ergodicity deficit cannot be reduced arbitrarily in nonergodic systems. We illustrate via a conceptual climate model that the nonergodic framework may be useful in Earth system dynamics, within which we propose the measure of nonergodicity, i.e., the bias, as an order-parameter-like quantifier of climate change.

Expectation of an upcoming large postural perturbation influences the recovery stepping response and outcome.

PubMed

Pater, Mackenzie L; Rosenblatt, Noah J; Grabiner, Mark D

2015-01-01

Tripping during locomotion, the leading cause of falls in older adults, generally occurs without prior warning and often while performing a secondary task. Prior warning can alter the state of physiological preparedness and beneficially influence the response to the perturbation. Previous studies have examined how altering the initial "preparedness" for an upcoming perturbation can affect kinematic responses following small disturbances that did not require a stepping response to restore dynamic stability. The purpose of this study was to examine how expectation affected fall outcome and recovery response kinematics following a large, treadmill-delivered perturbation simulating a trip and requiring at least one recovery step to avoid a fall. Following the perturbation, 47% of subjects fell when they were not expecting the perturbation whereas 12% fell when they were aware that the perturbation would occur "sometime in the next minute". The between-group differences were accompanied by slower reaction times in the non-expecting group (p < 0.01). Slower reaction times were associated with kinematics that have previously been shown to increase the likelihood of falling following a laboratory-induced trip. The results demonstrate the importance of considering the context under which recovery responses are assessed, and further, gives insight to the context during which task-specific perturbation training is administered. Copyright © 2014 Elsevier B.V. All rights reserved.

What dynamics can be expected for mixed states in two-slit experiments?

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

Luis, Alfredo; Sanz, Ángel S., E-mail: asanz@iff.csic.es

2015-06-15

Weak-measurement-based experiments (Kocsis et al., 2011) have shown that, at least for pure states, the average evolution of independent photons in Young’s two-slit experiment is in compliance with the trajectories prescribed by the Bohmian formulation of quantum mechanics. But, what happens if the same experiment is repeated assuming that the wave function associated with each particle is different, i.e., in the case of mixed (incoherent) states? This question is investigated here by means of two alternative numerical simulations of Young’s experiment, purposely devised to be easily implemented and tested in the laboratory. Contrary to what could be expected a priori, itmore » is found that even for conditions of maximal mixedness or incoherence (total lack of interference fringes), experimental data will render a puzzling and challenging outcome: the average particle trajectories will still display features analogous to those for pure states, i.e., independently of how mixedness arises, the associated dynamics is influenced by both slits at the same time. Physically this simply means that weak measurements are not able to discriminate how mixedness arises in the experiment, since they only provide information about the averaged system dynamics. - Highlights: • The dynamics associated with mixture states in investigated by means of two simple Young’s two-slit models. • The models are prepared to be easily implemented and tested in the laboratory by means of weak measurements. • Bohmian mechanics has been generalized to encompass statistical mixtures. • Even for conditions of maximal mixedness numerical simulations show that the dynamics is strongly influenced by both slits. • Accordingly, weak measurements are unable to discriminate how mixedness arises in an experiment.« less

Modeling nonstructural carbohydrate reserve dynamics in forest trees

NASA Astrophysics Data System (ADS)

Richardson, A. D.; Keenan, T. F.; Carbone, M. S.; Czimczik, C. I.; Hollinger, D. Y.; Murakami, P.; Schaberg, P.; Xu, X.

2012-12-01

Understanding the factors influencing the availability of nonstructural carbohydrate (NSC) reserves is essential for predicting the resilience of forests to climate change and environmental stress. However, carbon allocation processes remain poorly understood and many models either ignore NSC reserves, or use simple and untested representations of NSC allocation and pool dynamics. Using model-data fusion techniques, we combined a parsimonious model of forest ecosystem carbon cycling with novel field sampling and laboratory analyses of NSCs. Simulations were conducted for an evergreen conifer forest and a deciduous broadleaf forest in New England. We used radiocarbon methods based on the 14C "bomb spike" to estimate the age of NSC reserves, and used this to constrain the mean residence time of modeled NSCs. We used additional data, including tower-measured fluxes of CO2, soil and biomass carbon stocks, woody biomass increment, and leaf area index and litterfall, to further constrain the model's parameters and initial conditions. Three years of field measurements indicate that stemwood NSCs are highly dynamic on seasonal time scales. The modeled seasonal dynamics conform to expectations (accumulated in the growing season, depleted in the dormant season) but are inconsistent with the observational data (total stemwood NSC concentrations higher in March than November, lower in August than June). We interpret this contradiction to suggest that stemwood concentrations provide an incomplete picture of the whole-tree NSC budget. A two-pool model structure that accounted for both "fast" (active pool, MRT ≈1 y) and "slow" (passive pool, MRT ≥ 20 y) cycling reserves (1) gives reasonable estimates of the size and MRT of the total NSC pool; (2) greatly improves model predictions of interannual variability in woody biomass increment, compared to zero- or one-pool structures used in the majority of existing models; (3) provides a mechanism by which observations of a one-year lag between carbon uptake and growth can be explained; (4) reconciles the apparent contradiction of a reserve pool that is both highly dynamic over time, and also a decade old on average; and (5) shows how younger reserves can be preferentially used to support growth and metabolism, but allows for the older reserves to be drawn on if the younger reserves are depleted. The improved performance and greater realism of our model is achieved without requiring a substantial increase in model complexity. From the perspective of modeling forest responses to climate change, we expect that models incorporating dynamic stored reserves should be better able to represent the lagged effects of climate extremes and disturbance on ecosystem C fluxes.

Engineering incremental resistive switching in TaOx based memristors for brain-inspired computing

NASA Astrophysics Data System (ADS)

Wang, Zongwei; Yin, Minghui; Zhang, Teng; Cai, Yimao; Wang, Yangyuan; Yang, Yuchao; Huang, Ru

2016-07-01

Brain-inspired neuromorphic computing is expected to revolutionize the architecture of conventional digital computers and lead to a new generation of powerful computing paradigms, where memristors with analog resistive switching are considered to be potential solutions for synapses. Here we propose and demonstrate a novel approach to engineering the analog switching linearity in TaOx based memristors, that is, by homogenizing the filament growth/dissolution rate via the introduction of an ion diffusion limiting layer (DLL) at the TiN/TaOx interface. This has effectively mitigated the commonly observed two-regime conductance modulation behavior and led to more uniform filament growth (dissolution) dynamics with time, therefore significantly improving the conductance modulation linearity that is desirable in neuromorphic systems. In addition, the introduction of the DLL also served to reduce the power consumption of the memristor, and important synaptic learning rules in biological brains such as spike timing dependent plasticity were successfully implemented using these optimized devices. This study could provide general implications for continued optimizations of memristor performance for neuromorphic applications, by carefully tuning the dynamics involved in filament growth and dissolution.Brain-inspired neuromorphic computing is expected to revolutionize the architecture of conventional digital computers and lead to a new generation of powerful computing paradigms, where memristors with analog resistive switching are considered to be potential solutions for synapses. Here we propose and demonstrate a novel approach to engineering the analog switching linearity in TaOx based memristors, that is, by homogenizing the filament growth/dissolution rate via the introduction of an ion diffusion limiting layer (DLL) at the TiN/TaOx interface. This has effectively mitigated the commonly observed two-regime conductance modulation behavior and led to more uniform filament growth (dissolution) dynamics with time, therefore significantly improving the conductance modulation linearity that is desirable in neuromorphic systems. In addition, the introduction of the DLL also served to reduce the power consumption of the memristor, and important synaptic learning rules in biological brains such as spike timing dependent plasticity were successfully implemented using these optimized devices. This study could provide general implications for continued optimizations of memristor performance for neuromorphic applications, by carefully tuning the dynamics involved in filament growth and dissolution. Electronic supplementary information (ESI) available. See DOI: 10.1039/c6nr00476h

Romantic Relationship Dynamics of Urban African American Adolescents: Patterns of Monogamy, Commitment, and Trust

PubMed Central

Towner, Senna L.; Dolcini, M. Margaret; Harper, Gary W.

2013-01-01

Relationship dynamics develop early in life and are influenced by social environments. STI/HIV prevention programs need to consider romantic relationship dynamics that contribute to sexual health. The aim of this study was to examine monogamous patterns, commitment, and trust in African American adolescent romantic relationships. The authors also focused on the differences in these dynamics between and within gender. The way that such dynamics interplay in romantic relationships has the potential to influence STI/HIV acquisition risk. In-depth interviews were conducted with 28 African American adolescents aged 14 to 21 living in San Francisco. Our results discuss data related to monogamous behaviors, expectations, and values; trust and respect in romantic relationships; commitment to romantic relationships; and outcomes of mismatched relationship expectations. Incorporating gender-specific romantic relationships dynamics can enhance the effectiveness of prevention programs. PMID:26691404

A system dynamics analysis determining willingness to wait and pay for the implementation of data standards in clinical research

PubMed Central

2010-01-01

Background Industry standards provide rigorous descriptions of required data presentation, with the aim of ensuring compatibility across different clinical studies. However despite their crucial importance, these standards are often not used as expected in the development of clinical research. The reasons for this lack of compliance could be related to the high cost and time-intensive nature of the process of data standards implementation. The objective of this study was to evaluate the value of the extra time and cost required for different levels of data standardisation and the likelihood of researchers to comply with these levels. Since we believe that the cost and time necessary for the implementation of data standards can change over time, System Dynamics (SD) analysis was used to investigate how these variables interact and influence the adoption of data standards by clinical researchers. Methods Three levels of data standards implementation were defined through focus group discussion involving four clinical research investigators. Ten Brazilian and eighteen American investigators responded to an online questionnaire which presented possible standards implementation scenarios, with respondents asked to choose one of two options available in each scenario. A random effects ordered probit model was used to estimate the effect of cost and time on investigators' willingness to adhere to data standards. The SD model was used to demonstrate the relationship between degrees of data standardisation and subsequent variation in cost and time required to start the associated study. Results A preference for low cost and rapid implementation times was observed, with investigators more likely to incur costs than to accept a time delay in project start-up. SD analysis indicated that although initially extra time and cost are necessary for clinical study standardisation, there is a decrease in both over time. Conclusions Future studies should explore ways of creating mechanisms which decrease the time and cost associated with standardisation processes. In addition, the fact that the costs and time necessary for data standards implementation decrease with time should be made known to the wider research community. Policy makers should attempt to match their data standardisation policies better with the expectations of researchers. PMID:21194455

A system dynamics analysis determining willingness to wait and pay for the implementation of data standards in clinical research.

PubMed

Cofiel, Luciana; Zammar, Guilherme R; Zaveri, Amrapali J; Shah, Jatin Y; Carvalho, Elias; Nahm, Meredith; Kesselring, Gustavo; Pietrobon, Ricardo

2010-12-31

Industry standards provide rigorous descriptions of required data presentation, with the aim of ensuring compatibility across different clinical studies. However despite their crucial importance, these standards are often not used as expected in the development of clinical research. The reasons for this lack of compliance could be related to the high cost and time-intensive nature of the process of data standards implementation. The objective of this study was to evaluate the value of the extra time and cost required for different levels of data standardisation and the likelihood of researchers to comply with these levels. Since we believe that the cost and time necessary for the implementation of data standards can change over time, System Dynamics (SD) analysis was used to investigate how these variables interact and influence the adoption of data standards by clinical researchers. Three levels of data standards implementation were defined through focus group discussion involving four clinical research investigators. Ten Brazilian and eighteen American investigators responded to an online questionnaire which presented possible standards implementation scenarios, with respondents asked to choose one of two options available in each scenario. A random effects ordered probit model was used to estimate the effect of cost and time on investigators' willingness to adhere to data standards. The SD model was used to demonstrate the relationship between degrees of data standardisation and subsequent variation in cost and time required to start the associated study. A preference for low cost and rapid implementation times was observed, with investigators more likely to incur costs than to accept a time delay in project start-up. SD analysis indicated that although initially extra time and cost are necessary for clinical study standardisation, there is a decrease in both over time. Future studies should explore ways of creating mechanisms which decrease the time and cost associated with standardisation processes. In addition, the fact that the costs and time necessary for data standards implementation decrease with time should be made known to the wider research community. Policy makers should attempt to match their data standardisation policies better with the expectations of researchers.

Intrusive and Non-Intrusive Instruction in Dynamic Skill Training.

DTIC Science & Technology

1981-10-01

less sensitive to the processing load imposed by the dynaic task together with instructional feedback processing than were the decison - making and...betwee computer based instruction of knowledge systems and computer based instruction of dynamic skills. There is reason to expect that the findings of...knowledge 3Ytm and computer based instruction of dynlamic skill.. There is reason to expect that the findings of research on knowledge system

Expectation propagation for large scale Bayesian inference of non-linear molecular networks from perturbation data.

PubMed

Narimani, Zahra; Beigy, Hamid; Ahmad, Ashar; Masoudi-Nejad, Ali; Fröhlich, Holger

2017-01-01

Inferring the structure of molecular networks from time series protein or gene expression data provides valuable information about the complex biological processes of the cell. Causal network structure inference has been approached using different methods in the past. Most causal network inference techniques, such as Dynamic Bayesian Networks and ordinary differential equations, are limited by their computational complexity and thus make large scale inference infeasible. This is specifically true if a Bayesian framework is applied in order to deal with the unavoidable uncertainty about the correct model. We devise a novel Bayesian network reverse engineering approach using ordinary differential equations with the ability to include non-linearity. Besides modeling arbitrary, possibly combinatorial and time dependent perturbations with unknown targets, one of our main contributions is the use of Expectation Propagation, an algorithm for approximate Bayesian inference over large scale network structures in short computation time. We further explore the possibility of integrating prior knowledge into network inference. We evaluate the proposed model on DREAM4 and DREAM8 data and find it competitive against several state-of-the-art existing network inference methods.

Development of a realistic, dynamic digital brain phantom for CT perfusion validation

NASA Astrophysics Data System (ADS)

Divel, Sarah E.; Segars, W. Paul; Christensen, Soren; Wintermark, Max; Lansberg, Maarten G.; Pelc, Norbert J.

2016-03-01

Physicians rely on CT Perfusion (CTP) images and quantitative image data, including cerebral blood flow, cerebral blood volume, and bolus arrival delay, to diagnose and treat stroke patients. However, the quantification of these metrics may vary depending on the computational method used. Therefore, we have developed a dynamic and realistic digital brain phantom upon which CTP scans can be simulated based on a set of ground truth scenarios. Building upon the previously developed 4D extended cardiac-torso (XCAT) phantom containing a highly detailed brain model, this work consisted of expanding the intricate vasculature by semi-automatically segmenting existing MRA data and fitting nonuniform rational B-spline surfaces to the new vessels. Using time attenuation curves input by the user as reference, the contrast enhancement in the vessels changes dynamically. At each time point, the iodine concentration in the arteries and veins is calculated from the curves and the material composition of the blood changes to reflect the expected values. CatSim, a CT system simulator, generates simulated data sets of this dynamic digital phantom which can be further analyzed to validate CTP studies and post-processing methods. The development of this dynamic and realistic digital phantom provides a valuable resource with which current uncertainties and controversies surrounding the quantitative computations generated from CTP data can be examined and resolved.

Synchronization of mobile chaotic oscillator networks

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

Fujiwara, Naoya, E-mail: fujiwara@csis.u-tokyo.ac.jp; Kurths, Jürgen; Díaz-Guilera, Albert

We study synchronization of systems in which agents holding chaotic oscillators move in a two-dimensional plane and interact with nearby ones forming a time dependent network. Due to the uncertainty in observing other agents' states, we assume that the interaction contains a certain amount of noise that turns out to be relevant for chaotic dynamics. We find that a synchronization transition takes place by changing a control parameter. But this transition depends on the relative dynamic scale of motion and interaction. When the topology change is slow, we observe an intermittent switching between laminar and burst states close to themore » transition due to small noise. This novel type of synchronization transition and intermittency can happen even when complete synchronization is linearly stable in the absence of noise. We show that the linear stability of the synchronized state is not a sufficient condition for its stability due to strong fluctuations of the transverse Lyapunov exponent associated with a slow network topology change. Since this effect can be observed within the linearized dynamics, we can expect such an effect in the temporal networks with noisy chaotic oscillators, irrespective of the details of the oscillator dynamics. When the topology change is fast, a linearized approximation describes well the dynamics towards synchrony. These results imply that the fluctuations of the finite-time transverse Lyapunov exponent should also be taken into account to estimate synchronization of the mobile contact networks.« less

Global Genetic Response in a Cancer Cell: Self-Organized Coherent Expression Dynamics

PubMed Central

Tsuchiya, Masa; Hashimoto, Midori; Takenaka, Yoshiko; Motoike, Ikuko N.; Yoshikawa, Kenichi

2014-01-01

Understanding the basic mechanism of the spatio-temporal self-control of genome-wide gene expression engaged with the complex epigenetic molecular assembly is one of major challenges in current biological science. In this study, the genome-wide dynamical profile of gene expression was analyzed for MCF-7 breast cancer cells induced by two distinct ErbB receptor ligands: epidermal growth factor (EGF) and heregulin (HRG), which drive cell proliferation and differentiation, respectively. We focused our attention to elucidate how global genetic responses emerge and to decipher what is an underlying principle for dynamic self-control of genome-wide gene expression. The whole mRNA expression was classified into about a hundred groups according to the root mean square fluctuation (rmsf). These expression groups showed characteristic time-dependent correlations, indicating the existence of collective behaviors on the ensemble of genes with respect to mRNA expression and also to temporal changes in expression. All-or-none responses were observed for HRG and EGF (biphasic statistics) at around 10–20 min. The emergence of time-dependent collective behaviors of expression occurred through bifurcation of a coherent expression state (CES). In the ensemble of mRNA expression, the self-organized CESs reveals distinct characteristic expression domains for biphasic statistics, which exhibits notably the presence of criticality in the expression profile as a route for genomic transition. In time-dependent changes in the expression domains, the dynamics of CES reveals that the temporal development of the characteristic domains is characterized as autonomous bistable switch, which exhibits dynamic criticality (the temporal development of criticality) in the genome-wide coherent expression dynamics. It is expected that elucidation of the biophysical origin for such critical behavior sheds light on the underlying mechanism of the control of whole genome. PMID:24831017

Crude oil price dynamics: A study on effects of market expectation and strategic supply on price movements

NASA Astrophysics Data System (ADS)

Jin, Xin

Recent years have seen dramatic fluctuations in crude oil prices. This dissertation attempts to better understand price behavior. The first chapter studies the behavior of crude oil spot and futures prices. Oil prices, particularly spot and short-term futures prices, appear to have switched from I(0) to I(1) in early 2000s. To better understand this apparent change in persistence, a factor model of oil prices is proposed, where the prices are decomposed into long-term and short-term components. The change in the persistence behavior can be explained by changes in the relative volatility of the underlying components. Fitting the model to weekly data on WTI prices, the volatility of the persistent shocks increased substantially relative to other shocks. In addition, the risk premiums in futures prices have changed their signs and become more volatile. The estimated net marginal convenience yield using the model also shows changes in its behavior. These observations suggest that a dramatic fundamental change occurred in the period from 2002 to 2004 in the dynamics of the crude oil market. The second chapter explores the short-run price-inventory dynamics in the presence of different shocks. Classical competitive storage model states that inventory decision considers both current and future market condition, and thus interacts with spot and expected future spot prices. We study competitive storage holding in an equilibrium framework, focusing on the dynamic response of price and inventory to different shocks. We show that news shock generates response profile different from traditional contemporaneous shocks in price and inventory. The model is applied to world crude oil market, where the market expectation is estimated to experience a sharp change in early 2000s, together with a persisting constrained supply relative to demand. The expectation change has limited effect on crude oil spot price though. The world oil market structure has been studied extensively but no consensus has been reached on OPEC strategic behavior. In the third chapter, we are interested in the effects of supply-side market power on oil price dynamics in face of different demand shocks, and model the oil market as composed of a strategic dominant firm and several competitive fringe producers. In each period, the dominant firm makes decision while taking fringe's response into consideration. We consider two alternative pricing strategies for the dominant firm. Our results show that this dynamic strategic model improves the potential of dominant firm-competitive fringe model in fitting and explaining real world data. A regime switch after a permanent demand increase generates a time path for price that looks like the price movements in the recent years.

Orientational dynamics and dye-DNA interactions in a dye-labeled DNA aptamer.

PubMed

Unruh, Jay R; Gokulrangan, Giridharan; Lushington, G H; Johnson, Carey K; Wilson, George S

2005-05-01

We report the picosecond and nanosecond timescale rotational dynamics of a dye-labeled DNA oligonucleotide or "aptamer" designed to bind specifically to immunoglobulin E. Rotational dynamics in combination with fluorescence lifetime measurements provide information about dye-DNA interactions. Comparison of Texas Red (TR), fluorescein, and tetramethylrhodamine (TAMRA)-labeled aptamers reveals surprising differences with significant implications for biophysical studies employing such conjugates. Time-resolved anisotropy studies demonstrate that the TR- and TAMRA-aptamer anisotropy decays are dominated by the overall rotation of the aptamer, whereas the fluorescein-aptamer anisotropy decay displays a subnanosecond rotational correlation time much shorter than that expected for the overall rotation of the aptamer. Docking and molecular dynamics simulations suggest that the low mobility of TR is a result of binding in the groove of the DNA helix. Additionally, associated anisotropy analysis of the TAMRA-aptamer reveals both quenched and unquenched states that experience significant coupling to the DNA motion. Therefore, quenching of TAMRA by guanosine must depend on the configuration of the dye bound to the DNA. The strong coupling of TR to the rotational dynamics of the DNA aptamer, together with the absence of quenching of its fluorescence by DNA, makes it a good probe of DNA orientational dynamics. The understanding of the nature of dye-DNA interactions provides the basis for the development of bioconjugates optimized for specific biophysical measurements and is important for the sensitivity of anisotropy-based DNA-protein interaction studies employing such conjugates.

Orientational Dynamics and Dye-DNA Interactions in a Dye-Labeled DNA Aptamer

PubMed Central

Unruh, Jay R.; Gokulrangan, Giridharan; Lushington, G. H.; Johnson, Carey K.; Wilson, George S.

2005-01-01

We report the picosecond and nanosecond timescale rotational dynamics of a dye-labeled DNA oligonucleotide or “aptamer” designed to bind specifically to immunoglobulin E. Rotational dynamics in combination with fluorescence lifetime measurements provide information about dye-DNA interactions. Comparison of Texas Red (TR), fluorescein, and tetramethylrhodamine (TAMRA)-labeled aptamers reveals surprising differences with significant implications for biophysical studies employing such conjugates. Time-resolved anisotropy studies demonstrate that the TR- and TAMRA-aptamer anisotropy decays are dominated by the overall rotation of the aptamer, whereas the fluorescein-aptamer anisotropy decay displays a subnanosecond rotational correlation time much shorter than that expected for the overall rotation of the aptamer. Docking and molecular dynamics simulations suggest that the low mobility of TR is a result of binding in the groove of the DNA helix. Additionally, associated anisotropy analysis of the TAMRA-aptamer reveals both quenched and unquenched states that experience significant coupling to the DNA motion. Therefore, quenching of TAMRA by guanosine must depend on the configuration of the dye bound to the DNA. The strong coupling of TR to the rotational dynamics of the DNA aptamer, together with the absence of quenching of its fluorescence by DNA, makes it a good probe of DNA orientational dynamics. The understanding of the nature of dye-DNA interactions provides the basis for the development of bioconjugates optimized for specific biophysical measurements and is important for the sensitivity of anisotropy-based DNA-protein interaction studies employing such conjugates. PMID:15731389

Excess entropy scaling for the segmental and global dynamics of polyethylene melts.

PubMed

Voyiatzis, Evangelos; Müller-Plathe, Florian; Böhm, Michael C

2014-11-28

The range of validity of the Rosenfeld and Dzugutov excess entropy scaling laws is analyzed for unentangled linear polyethylene chains. We consider two segmental dynamical quantities, i.e. the bond and the torsional relaxation times, and two global ones, i.e. the chain diffusion coefficient and the viscosity. The excess entropy is approximated by either a series expansion of the entropy in terms of the pair correlation function or by an equation of state for polymers developed in the context of the self associating fluid theory. For the whole range of temperatures and chain lengths considered, the two estimates of the excess entropy are linearly correlated. The scaled bond and torsional relaxation times fall into a master curve irrespective of the chain length and the employed scaling scheme. Both quantities depend non-linearly on the excess entropy. For a fixed chain length, the reduced diffusion coefficient and viscosity scale linearly with the excess entropy. An empirical reduction to a chain length-independent master curve is accessible for both dynamic quantities. The Dzugutov scheme predicts an increased value of the scaled diffusion coefficient with increasing chain length which contrasts physical expectations. The origin of this trend can be traced back to the density dependence of the scaling factors. This finding has not been observed previously for Lennard-Jones chain systems (Macromolecules, 2013, 46, 8710-8723). Thus, it limits the applicability of the Dzugutov approach to polymers. In connection with diffusion coefficients and viscosities, the Rosenfeld scaling law appears to be of higher quality than the Dzugutov approach. An empirical excess entropy scaling is also proposed which leads to a chain length-independent correlation. It is expected to be valid for polymers in the Rouse regime.

Correlation functions from a unified variational principle: Trial Lie groups

NASA Astrophysics Data System (ADS)

Balian, R.; Vénéroni, M.

2015-11-01

Time-dependent expectation values and correlation functions for many-body quantum systems are evaluated by means of a unified variational principle. It optimizes a generating functional depending on sources associated with the observables of interest. It is built by imposing through Lagrange multipliers constraints that account for the initial state (at equilibrium or off equilibrium) and for the backward Heisenberg evolution of the observables. The trial objects are respectively akin to a density operator and to an operator involving the observables of interest and the sources. We work out here the case where trial spaces constitute Lie groups. This choice reduces the original degrees of freedom to those of the underlying Lie algebra, consisting of simple observables; the resulting objects are labeled by the indices of a basis of this algebra. Explicit results are obtained by expanding in powers of the sources. Zeroth and first orders provide thermodynamic quantities and expectation values in the form of mean-field approximations, with dynamical equations having a classical Lie-Poisson structure. At second order, the variational expression for two-time correlation functions separates-as does its exact counterpart-the approximate dynamics of the observables from the approximate correlations in the initial state. Two building blocks are involved: (i) a commutation matrix which stems from the structure constants of the Lie algebra; and (ii) the second-derivative matrix of a free-energy function. The diagonalization of both matrices, required for practical calculations, is worked out, in a way analogous to the standard RPA. The ensuing structure of the variational formulae is the same as for a system of non-interacting bosons (or of harmonic oscillators) plus, at non-zero temperature, classical Gaussian variables. This property is explained by mapping the original Lie algebra onto a simpler Lie algebra. The results, valid for any trial Lie group, fulfill consistency properties and encompass several special cases: linear responses, static and time-dependent fluctuations, zero- and high-temperature limits, static and dynamic stability of small deviations.

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

Balian, R., E-mail: roger.balian@cea.fr; Vénéroni, M.

Time-dependent expectation values and correlation functions for many-body quantum systems are evaluated by means of a unified variational principle. It optimizes a generating functional depending on sources associated with the observables of interest. It is built by imposing through Lagrange multipliers constraints that account for the initial state (at equilibrium or off equilibrium) and for the backward Heisenberg evolution of the observables. The trial objects are respectively akin to a density operator and to an operator involving the observables of interest and the sources. We work out here the case where trial spaces constitute Lie groups. This choice reduces themore » original degrees of freedom to those of the underlying Lie algebra, consisting of simple observables; the resulting objects are labeled by the indices of a basis of this algebra. Explicit results are obtained by expanding in powers of the sources. Zeroth and first orders provide thermodynamic quantities and expectation values in the form of mean-field approximations, with dynamical equations having a classical Lie–Poisson structure. At second order, the variational expression for two-time correlation functions separates–as does its exact counterpart–the approximate dynamics of the observables from the approximate correlations in the initial state. Two building blocks are involved: (i) a commutation matrix which stems from the structure constants of the Lie algebra; and (ii) the second-derivative matrix of a free-energy function. The diagonalization of both matrices, required for practical calculations, is worked out, in a way analogous to the standard RPA. The ensuing structure of the variational formulae is the same as for a system of non-interacting bosons (or of harmonic oscillators) plus, at non-zero temperature, classical Gaussian variables. This property is explained by mapping the original Lie algebra onto a simpler Lie algebra. The results, valid for any trial Lie group, fulfill consistency properties and encompass several special cases: linear responses, static and time-dependent fluctuations, zero- and high-temperature limits, static and dynamic stability of small deviations.« less

Ordered water structure at hydrophobic graphite interfaces observed by 4D, ultrafast electron crystallography

PubMed Central

Yang, Ding-Shyue; Zewail, Ahmed H.

2009-01-01

Interfacial water has unique properties in various functions. Here, using 4-dimensional (4D), ultrafast electron crystallography with atomic-scale spatial and temporal resolution, we report study of structure and dynamics of interfacial water assembly on a hydrophobic surface. Structurally, vertically stacked bilayers on highly oriented pyrolytic graphite surface were determined to be ordered, contrary to the expectation that the strong hydrogen bonding of water on hydrophobic surfaces would dominate with suppressed interfacial order. Because of its terrace morphology, graphite plays the role of a template. The dynamics is also surprising. After the excitation of graphite by an ultrafast infrared pulse, the interfacial ice structure undergoes nonequilibrium “phase transformation” identified in the hydrogen-bond network through the observation of structural isosbestic point. We provide the time scales involved, the nature of ice-graphite structural dynamics, and relevance to properties related to confined water. PMID:19246378

Leveraging Ensemble Dynamical Properties to Prioritize Exoplanet Follow-Up Observations

NASA Astrophysics Data System (ADS)

Ballard, Sarah

2017-01-01

The number of transiting exoplanets now exceeds several thousand, enabling ensemble studies of the dynamical properties of exoplanetary systems. We require a mixture model of dynamical conditions (whether frozen in from formation or sculpted by planet-planet interactions) to recover Kepler's yield of transiting planets. Around M dwarfs, which will be predominate sites of exoplanet follow-up atmospheric study in the next decade, even a modest orbital eccentricity can sterilize a planet. I will describe efforts to link cheap observables, such as number of transiting planets and presence of transit timing variations, to eccentricity and mutual inclination in exoplanet systems. The addition of a second transiting planet, for example, halves the expected orbital eccentricity. For the vast majority of TESS targets, the light curve alone will furnish the sum total of data about the exoplanet. Extracting information about orbital properties from these light curves will help prioritize precious follow-up resources.

Remote sensing of Gulf Stream using GEOS-3 radar altimeter

NASA Technical Reports Server (NTRS)

Leitao, C. D.; Huang, N. E.; Parra, C. G.

1978-01-01

Radar altimeter measurements from the GEOS-3 satellite to the ocean surface indicated the presence of expected geostrophic height differences across the the Gulf Stream. Dynamic sea surface heights were found by both editing and filtering the raw sea surface heights and then referencing these processed data to a 5 minute x 5 minute geoid. Any trend between the processed data and the geoid was removed by subtracting out a linear fit to the residuals in the open ocean. The mean current velocity of 107 + or - 29 cm/sec calculated from the dynamic heights for all orbits corresponded with velocities obtained from hydrographic methods. Also, dynamic topographic maps were produced for August, September, and October 1975. Results pointed out limitations in the accuracy of the geoid, height anomaly deteriorations due to filtering, and lack of dense time and space distribution of measurements.

Possibilities of identifying cyber attack in noisy space of n-dimensional abstract system

NASA Astrophysics Data System (ADS)

Jašek, Roman; Dvořák, Jiří; Janková, Martina; Sedláček, Michal

2016-06-01

This article briefly mentions some selected options of current concept for identifying cyber attacks from the perspective of the new cyberspace of real system. In the cyberspace, there is defined n-dimensional abstract system containing elements of the spatial arrangement of partial system elements such as micro-environment of cyber systems surrounded by other suitably arranged corresponding noise space. This space is also gradually supplemented by a new image of dynamic processes in a discreet environment, and corresponding again to n-dimensional expression of time space defining existence and also the prediction for expected cyber attacksin the noise space. Noises are seen here as useful and necessary for modern information and communication technologies (e.g. in processes of applied cryptography in ICT) and then the so-called useless noises designed for initial (necessary) filtering of this highly aggressive environment and in future expectedly offensive background in cyber war (e.g. the destruction of unmanned means of an electromagnetic pulse, or for destruction of new safety barriers created on principles of electrostatic field or on other principles of modern physics, etc.). The key to these new options is the expression of abstract systems based on the models of microelements of cyber systems and their hierarchical concept in structure of n-dimensional system in given cyberspace. The aim of this article is to highlight the possible systemic expression of cyberspace of abstract system and possible identification in time-spatial expression of real environment (on microelements of cyber systems and their surroundings with noise characteristics and time dimension in dynamic of microelements' own time and externaltime defined by real environment). The article was based on a partial task of faculty specific research.

Possibilities of identifying cyber attack in noisy space of n-dimensional abstract system

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

Jašek, Roman; Dvořák, Jiří; Janková, Martina

This article briefly mentions some selected options of current concept for identifying cyber attacks from the perspective of the new cyberspace of real system. In the cyberspace, there is defined n-dimensional abstract system containing elements of the spatial arrangement of partial system elements such as micro-environment of cyber systems surrounded by other suitably arranged corresponding noise space. This space is also gradually supplemented by a new image of dynamic processes in a discreet environment, and corresponding again to n-dimensional expression of time space defining existence and also the prediction for expected cyber attacksin the noise space. Noises are seen heremore » as useful and necessary for modern information and communication technologies (e.g. in processes of applied cryptography in ICT) and then the so-called useless noises designed for initial (necessary) filtering of this highly aggressive environment and in future expectedly offensive background in cyber war (e.g. the destruction of unmanned means of an electromagnetic pulse, or for destruction of new safety barriers created on principles of electrostatic field or on other principles of modern physics, etc.). The key to these new options is the expression of abstract systems based on the models of microelements of cyber systems and their hierarchical concept in structure of n-dimensional system in given cyberspace. The aim of this article is to highlight the possible systemic expression of cyberspace of abstract system and possible identification in time-spatial expression of real environment (on microelements of cyber systems and their surroundings with noise characteristics and time dimension in dynamic of microelements’ own time and externaltime defined by real environment). The article was based on a partial task of faculty specific research.« less

Global patterns of drought recovery.

PubMed

Schwalm, Christopher R; Anderegg, William R L; Michalak, Anna M; Fisher, Joshua B; Biondi, Franco; Koch, George; Litvak, Marcy; Ogle, Kiona; Shaw, John D; Wolf, Adam; Huntzinger, Deborah N; Schaefer, Kevin; Cook, Robert; Wei, Yaxing; Fang, Yuanyuan; Hayes, Daniel; Huang, Maoyi; Jain, Atul; Tian, Hanqin

2017-08-09

Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time-how long an ecosystem requires to revert to its pre-drought functional state-is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO 2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth's climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.

Using Dynamic Time Warping and Data Forensics to Examine Tradeoffs among Land-Energy-Water Networks Across the Conterminous United States

NASA Astrophysics Data System (ADS)

McManamay, R.; Allen, M. R.; Piburn, J.; Sanyal, J.; Stewart, R.; Bhaduri, B. L.

2017-12-01

Characterizing interdependencies among land-energy-water sectors, their vulnerabilities, and tipping points, is challenging, especially if all sectors are simultaneously considered. Because such holistic system behavior is uncertain, largely unmodeled, and in need of testable hypotheses of system drivers, these dynamics are conducive to exploratory analytics of spatiotemporal patterns, powered by tools, such as Dynamic Time Warping (DTW). Here, we conduct a retrospective analysis (1950 - 2010) of temporal trends in land use, energy use, and water use within US counties to identify commonalities in resource consumption and adaptation strategies to resource limitations. We combine existing and derived data from statistical downscaling to synthesize a temporally comprehensive land-energy-water dataset at the US county level and apply DTW and subsequent hierarchical clustering to examine similar temporal trends in resource typologies for land, energy, and water sectors. As expected, we observed tradeoffs among water uses (e.g., public supply vs irrigation) and land uses (e.g., urban vs ag). Strong associations between clusters amongst sectors reveal tight system interdependencies, whereas weak associations suggest unique behaviors and potential for human adaptations towards disruptive technologies and less resource-dependent population growth. Our framework is useful for exploring complex human-environmental system dynamics and generating hypotheses to guide subsequent energy-water-nexus research.

Temporal bird community dynamics are strongly affected by landscape fragmentation in a Central American tropical forest region

USGS Publications Warehouse

Blandón, A.C.; Perelman, S.B.; Ramírez, M.; López, A.; Javier, O.; Robbins, Chandler S.

2016-01-01

Habitat loss and fragmentation are considered the main causes of species extinctions, particularly in tropical ecosystems. The objective of this work was to evaluate the temporal dynamics of tropical bird communities in landscapes with different levels of fragmentation in eastern Guatemala. We evaluated five bird community dynamic parameters for forest specialists and generalists: (1) species extinction, (2) species turnover, (3) number of colonizing species, (4) relative species richness, and (5) a homogeneity index. For each of 24 landscapes, community dynamic parameters were estimated from bird point count data, for the 1998–1999 and 2008–2009 periods, accounting for species’ detection probability. Forest specialists had higher extinction rates and a smaller number of colonizing species in landscapes with higher fragmentation, thus having lower species richness in both time periods. Alternatively, forest generalists elicited a completely different pattern, showing a curvilinear association to forest fragmentation for most parameters. Thus, greater community dynamism for forest generalists was shown in landscapes with intermediate levels of fragmentation. Our study supports general theory regarding the expected negative effects of habitat loss and fragmentation on the temporal dynamics of biotic communities, particularly for forest specialists, providing strong evidence from understudied tropical bird communities.

The role of telomere dynamics in aging and cancer

NASA Astrophysics Data System (ADS)

Blagoev, Krastan; Goodwin, Edwin

2006-03-01

Telomere length changes are far more dynamic than previously thought. In addition to a gradual loss of ˜100 base pairs per telomere in each cell division, losses as well as gains may occur within a single cell cycle. We are investigating how telomere exchange, extension, and deletion affect the proliferative potential of telomerase-negative somatic cells. Experimental techniques are being devised to detect dynamic telomere processes and quantify both the frequency and length changes of each. In parallel, a ``dynamic telomere model'' is being used that incorporates telomere dynamics to study how the telomere size distribution evolves with time. This is an essential step towards understanding the role that telomere dynamics play in the normal aging of tissues and organisms. The model casts light on relationships not otherwise easily explained by a deterministic ``mitotic clock,'' or to what extent the shortest initial telomere determines the onset of senescence. We also expect to identify biomarkers that will correlate with aging better than average telomere length and to shed light on the transition to unlimited growth found in telomerase-negative tumor cells having the ALT (alternative lengthening of telomeres) phenotype, and to evaluate strategies to suppress the growth of these tumors.

A model to create an efficient and equitable admission policy for patients arriving to the cardiothoracic ICU.

PubMed

Yang, Muer; Fry, Michael J; Raikhelkar, Jayashree; Chin, Cynthia; Anyanwu, Anelechi; Brand, Jordan; Scurlock, Corey

2013-02-01

To develop queuing and simulation-based models to understand the relationship between ICU bed availability and operating room schedule to maximize the use of critical care resources and minimize case cancellation while providing equity to patients and surgeons. Retrospective analysis of 6-month unit admission data from a cohort of cardiothoracic surgical patients, to create queuing and simulation-based models of ICU bed flow. Three different admission policies (current admission policy, shortest-processing-time policy, and a dynamic policy) were then analyzed using simulation models, representing 10 yr worth of potential admissions. Important output data consisted of the "average waiting time," a proxy for unit efficiency, and the "maximum waiting time," a surrogate for patient equity. A cardiothoracic surgical ICU in a tertiary center in New York, NY. Six hundred thirty consecutive cardiothoracic surgical patients admitted to the cardiothoracic surgical ICU. None. Although the shortest-processing-time admission policy performs best in terms of unit efficiency (0.4612 days), it did so at expense of patient equity prolonging surgical waiting time by as much as 21 days. The current policy gives the greatest equity but causes inefficiency in unit bed-flow (0.5033 days). The dynamic policy performs at a level (0.4997 days) 8.3% below that of the shortest-processing-time in average waiting time; however, it balances this with greater patient equity (maximum waiting time could be shortened by 4 days compared to the current policy). Queuing theory and computer simulation can be used to model case flow through a cardiothoracic operating room and ICU. A dynamic admission policy that looks at current waiting time and expected ICU length of stay allows for increased equity between patients with only minimum losses of efficiency. This dynamic admission policy would seem to be a superior in maximizing case-flow. These results may be generalized to other surgical ICUs.

Chaotic dynamics of Comet 1P/Halley: Lyapunov exponent and survival time expectancy

NASA Astrophysics Data System (ADS)

Muñoz-Gutiérrez, M. A.; Reyes-Ruiz, M.; Pichardo, B.

2015-03-01

The orbital elements of Comet Halley are known to a very high precision, suggesting that the calculation of its future dynamical evolution is straightforward. In this paper we seek to characterize the chaotic nature of the present day orbit of Comet Halley and to quantify the time-scale over which its motion can be predicted confidently. In addition, we attempt to determine the time-scale over which its present day orbit will remain stable. Numerical simulations of the dynamics of test particles in orbits similar to that of Comet Halley are carried out with the MERCURY 6.2 code. On the basis of these we construct survival time maps to assess the absolute stability of Halley's orbit, frequency analysis maps to study the variability of the orbit, and we calculate the Lyapunov exponent for the orbit for variations in initial conditions at the level of the present day uncertainties in our knowledge of its orbital parameters. On the basis of our calculations of the Lyapunov exponent for Comet Halley, the chaotic nature of its motion is demonstrated. The e-folding time-scale for the divergence of initially very similar orbits is approximately 70 yr. The sensitivity of the dynamics on initial conditions is also evident in the self-similarity character of the survival time and frequency analysis maps in the vicinity of Halley's orbit, which indicates that, on average, it is unstable on a time-scale of hundreds of thousands of years. The chaotic nature of Halley's present day orbit implies that a precise determination of its motion, at the level of the present-day observational uncertainty, is difficult to predict on a time-scale of approximately 100 yr. Furthermore, we also find that the ejection of Halley from the Solar system or its collision with another body could occur on a time-scale as short as 10 000 yr.

Latitudinal variation in diapause duration and post-winter development in two pierid butterflies in relation to phenological specialization.

PubMed

Posledovich, Diana; Toftegaard, Tenna; Wiklund, Christer; Ehrlén, Johan; Gotthard, Karl

2015-01-01

Diapause plays a central role in insect life cycles by allowing survival during adverse seasonal conditions as well as synchronizing life cycles with the period of mate and food availability. Seasonal timing is expected to be particularly important for species that are dependent on resources available during a short time window-so-called phenological specialists-and latitudinal clines in seasonality are expected to favor local adaptation in phenological timing. However, to what degree latitudinal variation in diapause dynamics and post-winter development due to such local adaptation is influenced by the degree of phenological specialization is not well known. We experimentally studied two pierid butterfly species and found that the phenological specialist Anthocharis cardamines had shorter diapause duration than the phenological generalist Pieris napi along a latitudinal gradient in Sweden. Moreover, diapause duration increased with latitude in P. napi but not in A. cardamines. Sensitivity of the two species to winter thermal conditions also differed; additional cold temperature during the winter period shortened diapause duration for P. napi pupae but not for A. cardamines pupae. In both species, post-winter pupal development was faster after longer periods of cold conditions, and more southern populations developed faster than northern populations. Post-winter development was also invariably faster at higher temperatures in both species. We argue that the observed differences in diapause dynamics between the two species might be explained by the difference in phenological specialization that influences the costs of breaking diapause too early in the season.

Analyzing land surface temperature variations during Fogo Island (Cape Verde) 2014-2015 eruption with Landsat 8 images

NASA Astrophysics Data System (ADS)

Vieira, D.; Teodoro, A.; Gomes, A.

2016-10-01

Land Surface Temperature (LST) is an important parameter related to land surface processes that changes continuously through time. Assessing its dynamics during a volcanic eruption has both environmental and socio-economical interest. Lava flows and other volcanic materials produced and deposited throughout an eruption transform the landscape, contributing to its heterogeneity and altering LST measurements. This paper aims to assess variations of satellite-derived LST and to detect patterns during the latest Fogo Island (Cape Verde) eruption, extending from November 2014 through February 2015. LST data was obtained through four processed Landsat 8 images, focused on the caldera where Pico do Fogo volcano sits. QGIS' plugin Semi-Automatic Classification was used in order to apply atmospheric corrections and radiometric calibrations. The algorithm used to retrieve LST values is a single-channel method, in which emissivity values are known. The absence of in situ measurements is compensated by the use of MODIS sensor-derived LST data, used to compare with Landsat retrieved measurements. LST data analysis shows as expected that the highest LST values are located inside the caldera. High temperature values were also founded on the south-facing flank of the caldera. Although spatial patterns observed on the retrieved data remained roughly the same during the time period considered, temperature values changed throughout the area and over time, as it was also expected. LST values followed the eruption dynamic experiencing a growth followed by a decline. Moreover, it seems possible to recognize areas affected by lava flows of previous eruptions, due to well-defined LST spatial patterns.

Online compensation for target motion with scanned particle beams: simulation environment.

PubMed

Li, Qiang; Groezinger, Sven Oliver; Haberer, Thomas; Rietzel, Eike; Kraft, Gerhard

2004-07-21

Target motion is one of the major limitations of each high precision radiation therapy. Using advanced active beam delivery techniques, such as the magnetic raster scanning system for particle irradiation, the interplay between time-dependent beam and target position heavily distorts the applied dose distribution. This paper presents a simulation environment in which the time-dependent effect of target motion on heavy-ion irradiation can be calculated with dynamically scanned ion beams. In an extension of the existing treatment planning software for ion irradiation of static targets (TRiP) at GSI, the expected dose distribution is calculated as the sum of several sub-distributions for single target motion states. To investigate active compensation for target motion by adapting the position of the therapeutic beam during irradiation, the planned beam positions can be altered during the calculation. Applying realistic parameters to the planned motion-compensation methods at GSI, the effect of target motion on the expected dose uniformity can be simulated for different target configurations and motion conditions. For the dynamic dose calculation, experimentally measured profiles of the beam extraction in time were used. Initial simulations show the feasibility and consistency of an active motion compensation with the magnetic scanning system and reveal some strategies to improve the dose homogeneity inside the moving target. The simulation environment presented here provides an effective means for evaluating the dose distribution for a moving target volume with and without motion compensation. It contributes a substantial basis for the experimental research on the irradiation of moving target volumes with scanned ion beams at GSI which will be presented in upcoming papers.

Photogrammetry and Videogrammetry Methods Development for Solar Sail Structures. Masters Thesis awarded by George Washington Univ.

NASA Technical Reports Server (NTRS)

Pappa, Richard S. (Technical Monitor); Black, Jonathan T.

2003-01-01

This report discusses the development and application of metrology methods called photogrammetry and videogrammetry that make accurate measurements from photographs. These methods have been adapted for the static and dynamic characterization of gossamer structures, as four specific solar sail applications demonstrate. The applications prove that high-resolution, full-field, non-contact static measurements of solar sails using dot projection photogrammetry are possible as well as full-field, non-contact, dynamic characterization using dot projection videogrammetry. The accuracy of the measurement of the resonant frequencies and operating deflection shapes that were extracted surpassed expectations. While other non-contact measurement methods exist, they are not full-field and require significantly more time to take data.

Avoided ferromagnetic quantum critical point: unusual short-range ordered state in CeFePO.

PubMed

Lausberg, S; Spehling, J; Steppke, A; Jesche, A; Luetkens, H; Amato, A; Baines, C; Krellner, C; Brando, M; Geibel, C; Klauss, H-H; Steglich, F

2012-11-21

Cerium 4f electronic spin dynamics in single crystals of the heavy-fermion system CeFePO is studied by means of ac susceptibility, specific heat, and muon-spin relaxation (μSR). Short-range static magnetism occurs below the freezing temperature T(g) ≈ 0.7 K, which prevents the system from accessing a putative ferromagnetic quantum critical point. In the μSR, the sample-averaged muon asymmetry function is dominated by strongly inhomogeneous spin fluctuations below 10 K and exhibits a characteristic time-field scaling relation expected from glassy spin dynamics, strongly evidencing cooperative and critical spin fluctuations. The overall behavior can be ascribed neither to canonical spin glasses nor other disorder-driven mechanisms.

Ten year change in forest succession and composition measured by remote sensing

NASA Technical Reports Server (NTRS)

Hall, Forrest G.; Botkin, Daniel B.; Strebel, Donald E.; Woods, Kerry K.; Goetz, Scott J.

1987-01-01

Vegetation dynamics and changes in ecological patterns were measured by remote sensing over a 10 year period (1973 to 1983) for 148,406 landscape elements, covering more than 500 sq km in a protected forested wilderness. Quantitative measurements were made possible by methods to detect ecologically meaningful landscape units; these allowed measurement of ecological transition frequencies and calculation of expected recurrence times. Measured ecological transition frequencies reveal boreal forest wilderness as spatially heterogeneous and highly dynamic, with one-sixth of the area in clearings and early successional stages, consistent with recent postulates about the spatial and temporal patterns of natural ecosystems. Differences between managed forest areas and a protected wilderness allow assessment of different management regimes.

Expected Number of Fixed Points in Boolean Networks with Arbitrary Topology.

PubMed

Mori, Fumito; Mochizuki, Atsushi

2017-07-14

Boolean network models describe genetic, neural, and social dynamics in complex networks, where the dynamics depend generally on network topology. Fixed points in a genetic regulatory network are typically considered to correspond to cell types in an organism. We prove that the expected number of fixed points in a Boolean network, with Boolean functions drawn from probability distributions that are not required to be uniform or identical, is one, and is independent of network topology if only a feedback arc set satisfies a stochastic neutrality condition. We also demonstrate that the expected number is increased by the predominance of positive feedback in a cycle.

Welfare States, Labor Markets, Political Dynamics, and Population Health: A Time-Series Cross-Sectional Analysis Among East and Southeast Asian Nations.

PubMed

Ng, Edwin; Muntaner, Carles; Chung, Haejoo

2016-04-01

Recent scholarship offers different theories on how macrosocial determinants affect the population health of East and Southeast Asian nations. Dominant theories emphasize the effects of welfare regimes, welfare generosity, and labor market institutions. In this article, we conduct exploratory time-series cross-sectional analyses to generate new evidence on these theories while advancing a political explanation. Using unbalanced data of 7 East Asian countries and 11 Southeast Asian nations from 1960 to 2012, primary findings are 3-fold. First, welfare generosity measured as education and health spending has a positive impact on life expectancy, net of GDP. Second, life expectancy varies significantly by labor markets; however, these differences are explained by differences in welfare generosity. Third, as East and Southeast Asian countries become more democratic, welfare generosity increases, and population health improves. This study provides new evidence on the value of considering politics, welfare states, and labor markets within the same conceptual framework. © 2016 APJPH.

Molecular dynamics with rigid bodies: Alternative formulation and assessment of its limitations when employed to simulate liquid water

NASA Astrophysics Data System (ADS)

Silveira, Ana J.; Abreu, Charlles R. A.

2017-09-01

Sets of atoms collectively behaving as rigid bodies are often used in molecular dynamics to model entire molecules or parts thereof. This is a coarse-graining strategy that eliminates degrees of freedom and supposedly admits larger time steps without abandoning the atomistic character of a model. In this paper, we rely on a particular factorization of the rotation matrix to simplify the mechanical formulation of systems containing rigid bodies. We then propose a new derivation for the exact solution of torque-free rotations, which are employed as part of a symplectic numerical integration scheme for rigid-body dynamics. We also review methods for calculating pressure in systems of rigid bodies with pairwise-additive potentials and periodic boundary conditions. Finally, simulations of liquid phases, with special focus on water, are employed to analyze the numerical aspects of the proposed methodology. Our results show that energy drift is avoided for time step sizes up to 5 fs, but only if a proper smoothing is applied to the interatomic potentials. Despite this, the effects of discretization errors are relevant, even for smaller time steps. These errors induce, for instance, a systematic failure of the expected equipartition of kinetic energy between translational and rotational degrees of freedom.

Reliable oligonucleotide conformational ensemble generation in explicit solvent for force field assessment using reservoir replica exchange molecular dynamics simulations

PubMed Central

Henriksen, Niel M.; Roe, Daniel R.; Cheatham, Thomas E.

2013-01-01

Molecular dynamics force field development and assessment requires a reliable means for obtaining a well-converged conformational ensemble of a molecule in both a time-efficient and cost-effective manner. This remains a challenge for RNA because its rugged energy landscape results in slow conformational sampling and accurate results typically require explicit solvent which increases computational cost. To address this, we performed both traditional and modified replica exchange molecular dynamics simulations on a test system (alanine dipeptide) and an RNA tetramer known to populate A-form-like conformations in solution (single-stranded rGACC). A key focus is on providing the means to demonstrate that convergence is obtained, for example by investigating replica RMSD profiles and/or detailed ensemble analysis through clustering. We found that traditional replica exchange simulations still require prohibitive time and resource expenditures, even when using GPU accelerated hardware, and our results are not well converged even at 2 microseconds of simulation time per replica. In contrast, a modified version of replica exchange, reservoir replica exchange in explicit solvent, showed much better convergence and proved to be both a cost-effective and reliable alternative to the traditional approach. We expect this method will be attractive for future research that requires quantitative conformational analysis from explicitly solvated simulations. PMID:23477537

Reliable oligonucleotide conformational ensemble generation in explicit solvent for force field assessment using reservoir replica exchange molecular dynamics simulations.

PubMed

Henriksen, Niel M; Roe, Daniel R; Cheatham, Thomas E

2013-04-18

Molecular dynamics force field development and assessment requires a reliable means for obtaining a well-converged conformational ensemble of a molecule in both a time-efficient and cost-effective manner. This remains a challenge for RNA because its rugged energy landscape results in slow conformational sampling and accurate results typically require explicit solvent which increases computational cost. To address this, we performed both traditional and modified replica exchange molecular dynamics simulations on a test system (alanine dipeptide) and an RNA tetramer known to populate A-form-like conformations in solution (single-stranded rGACC). A key focus is on providing the means to demonstrate that convergence is obtained, for example, by investigating replica RMSD profiles and/or detailed ensemble analysis through clustering. We found that traditional replica exchange simulations still require prohibitive time and resource expenditures, even when using GPU accelerated hardware, and our results are not well converged even at 2 μs of simulation time per replica. In contrast, a modified version of replica exchange, reservoir replica exchange in explicit solvent, showed much better convergence and proved to be both a cost-effective and reliable alternative to the traditional approach. We expect this method will be attractive for future research that requires quantitative conformational analysis from explicitly solvated simulations.

Teacher Expectations and Student Literacy Engagement and Achievement

ERIC Educational Resources Information Center

Pantaleo, Sylvia

2016-01-01

Notwithstanding the complex and dynamic nature of teaching and learning in schools, over four decades of research findings have consistently revealed a correlation between teacher expectations and student achievement. Focusing on teacher expectations for the narrative structures created by young children, this article features a discussion of data…

From brain to earth and climate systems: small-world interaction networks or not?

PubMed

Bialonski, Stephan; Horstmann, Marie-Therese; Lehnertz, Klaus

2010-03-01

We consider recent reports on small-world topologies of interaction networks derived from the dynamics of spatially extended systems that are investigated in diverse scientific fields such as neurosciences, geophysics, or meteorology. With numerical simulations that mimic typical experimental situations, we have identified an important constraint when characterizing such networks: indications of a small-world topology can be expected solely due to the spatial sampling of the system along with the commonly used time series analysis based approaches to network characterization.

Stochastic Representation of Chaos using Terminal Attractors

NASA Technical Reports Server (NTRS)

Zak, Michail

2005-01-01

A nonlinear version of the Liouville equation based upon terminal attractors is proposed for describing post-instability motions of dynamical systems with exponential divergence of trajectories such as those leading to chaos and turbulence. As a result, the post-instability motions are represented by expectations, variances, and higher moments of the state variables as functions of time. The proposed approach can be applied to conservative chaos, and in particular, to n-bodies problem, as well as to dissipative systems, and in particular, to chaotic attractors and turbulence.

The Hubble Space Telescope high speed photometer

NASA Technical Reports Server (NTRS)

Vancitters, G. W., Jr.; Bless, R. C.; Dolan, J. F.; Elliot, J. L.; Robinson, E. L.; White, R. L.

1988-01-01

The Hubble Space Telescope will provide the opportunity to perform precise astronomical photometry above the disturbing effects of the atmosphere. The High Speed Photometer is designed to provide the observatory with a stable, precise photometer with wide dynamic range, broad wavelenth coverage, time resolution in the microsecond region, and polarimetric capability. Here, the scientific requirements for the instrument are examined, the unique design features of the photometer are explored, and the improvements to be expected over the performance of ground-based instruments are projected.

Tropical Cyclone Report: Joint Typhoon Warning Center Guam, Mariana Islands, 1991

DTIC Science & Technology

1991-01-01

provided by the weather unit supporting synoptic time plus three hours (0300Z, 0900Z, the 15th Air Base Wing , Hickam AFB, Hawaii. 1500Z and 2100Z). By...DYNAMIC 5.2.3.1 CLIMATOLOGY AND PERSISTENCE 5.2.4.1 NOGAPS VORTEX TRACKING ( CLIP ) - A statistical regression technique that ROUTINE (NGPS) - This...forecast skill of other in the expected vicinity of the storm is more sophisticated techniques. CLIP in the conducted every six hours through 72 hours

Short‐term time step convergence in a climate model

PubMed Central

Rasch, Philip J.; Taylor, Mark A.; Jablonowski, Christiane

2015-01-01

Abstract This paper evaluates the numerical convergence of very short (1 h) simulations carried out with a spectral‐element (SE) configuration of the Community Atmosphere Model version 5 (CAM5). While the horizontal grid spacing is fixed at approximately 110 km, the process‐coupling time step is varied between 1800 and 1 s to reveal the convergence rate with respect to the temporal resolution. Special attention is paid to the behavior of the parameterized subgrid‐scale physics. First, a dynamical core test with reduced dynamics time steps is presented. The results demonstrate that the experimental setup is able to correctly assess the convergence rate of the discrete solutions to the adiabatic equations of atmospheric motion. Second, results from full‐physics CAM5 simulations with reduced physics and dynamics time steps are discussed. It is shown that the convergence rate is 0.4—considerably slower than the expected rate of 1.0. Sensitivity experiments indicate that, among the various subgrid‐scale physical parameterizations, the stratiform cloud schemes are associated with the largest time‐stepping errors, and are the primary cause of slow time step convergence. While the details of our findings are model specific, the general test procedure is applicable to any atmospheric general circulation model. The need for more accurate numerical treatments of physical parameterizations, especially the representation of stratiform clouds, is likely common in many models. The suggested test technique can help quantify the time‐stepping errors and identify the related model sensitivities. PMID:27660669

Stereotypical modulations in dynamic functional connectivity explained by changes in BOLD variance.

PubMed

Glomb, Katharina; Ponce-Alvarez, Adrián; Gilson, Matthieu; Ritter, Petra; Deco, Gustavo

2018-05-01

Spontaneous activity measured in human subject under the absence of any task exhibits complex patterns of correlation that largely correspond to large-scale functional topographies obtained with a wide variety of cognitive and perceptual tasks. These "resting state networks" (RSNs) fluctuate over time, forming and dissolving on the scale of seconds to minutes. While these fluctuations, most prominently those of the default mode network, have been linked to cognitive function, it remains unclear whether they result from random noise or whether they index a nonstationary process which could be described as state switching. In this study, we use a sliding windows-approach to relate temporal dynamics of RSNs to global modulations in correlation and BOLD variance. We compare empirical data, phase-randomized surrogate data, and data simulated with a stationary model. We find that RSN time courses exhibit a large amount of coactivation in all three cases, and that the modulations in their activity are closely linked to global dynamics of the underlying BOLD signal. We find that many properties of the observed fluctuations in FC and BOLD, including their ranges and their correlations amongst each other, are explained by fluctuations around the average FC structure. However, we also report some interesting characteristics that clearly support nonstationary features in the data. In particular, we find that the brain spends more time in the troughs of modulations than can be expected from stationary dynamics. Copyright © 2018 Elsevier Inc. All rights reserved.

The Relationship between Pedal Force and Crank Angular Velocity in Sprint Cycling.

PubMed

Bobbert, Maarten Frank; Casius, L J Richard; Van Soest, Arthur J

2016-05-01

Relationships between tangential pedal force and crank angular velocity in sprint cycling tend to be linear. We set out to understand why they are not hyperbolic, like the intrinsic force-velocity relationship of muscles. We simulated isokinetic sprint cycling at crank angular velocities ranging from 30 to 150 rpm with a forward dynamic model of the human musculoskeletal system actuated by eight lower extremity muscle groups. The input of the model was muscle stimulation over time, which we optimized to maximize average power output over a cycle. Peak tangential pedal force was found to drop more with crank angular velocity than expected based on intrinsic muscle properties. This linearizing effect was not due to segmental dynamics but rather due to active state dynamics. Maximizing average power in cycling requires muscles to bring their active state from as high as possible during shortening to as low as possible during lengthening. Reducing the active state is a relatively slow process, and hence must be initiated a certain amount of time before lengthening starts. As crank angular velocity goes up, this amount of time corresponds to a greater angular displacement, so the instant of switching off extensor muscle stimulation must occur earlier relative to the angle at which pedal force was extracted for the force-velocity relationship. Relationships between pedal force and crank angular velocity in sprint cycling do not reflect solely the intrinsic force-velocity relationship of muscles but also the consequences of activation dynamics.

Optimal regulation in systems with stochastic time sampling

NASA Technical Reports Server (NTRS)

Montgomery, R. C.; Lee, P. S.

1980-01-01

An optimal control theory that accounts for stochastic variable time sampling in a distributed microprocessor based flight control system is presented. The theory is developed by using a linear process model for the airplane dynamics and the information distribution process is modeled as a variable time increment process where, at the time that information is supplied to the control effectors, the control effectors know the time of the next information update only in a stochastic sense. An optimal control problem is formulated and solved for the control law that minimizes the expected value of a quadratic cost function. The optimal cost obtained with a variable time increment Markov information update process where the control effectors know only the past information update intervals and the Markov transition mechanism is almost identical to that obtained with a known and uniform information update interval.

The temporal derivative of expected utility: a neural mechanism for dynamic decision-making.

PubMed

Zhang, Xian; Hirsch, Joy

2013-01-15

Real world tasks involving moving targets, such as driving a vehicle, are performed based on continuous decisions thought to depend upon the temporal derivative of the expected utility (∂V/∂t), where the expected utility (V) is the effective value of a future reward. However, the neural mechanisms that underlie dynamic decision-making are not well understood. This study investigates human neural correlates of both V and ∂V/∂t using fMRI and a novel experimental paradigm based on a pursuit-evasion game optimized to isolate components of dynamic decision processes. Our behavioral data show that players of the pursuit-evasion game adopt an exponential discounting function, supporting the expected utility theory. The continuous functions of V and ∂V/∂t were derived from the behavioral data and applied as regressors in fMRI analysis, enabling temporal resolution that exceeded the sampling rate of image acquisition, hyper-temporal resolution, by taking advantage of numerous trials that provide rich and independent manipulation of those variables. V and ∂V/∂t were each associated with distinct neural activity. Specifically, ∂V/∂t was associated with anterior and posterior cingulate cortices, superior parietal lobule, and ventral pallidum, whereas V was primarily associated with supplementary motor, pre and post central gyri, cerebellum, and thalamus. The association between the ∂V/∂t and brain regions previously related to decision-making is consistent with the primary role of the temporal derivative of expected utility in dynamic decision-making. Copyright © 2012 Elsevier Inc. All rights reserved.

The Temporal Derivative of Expected Utility: A Neural Mechanism for Dynamic Decision-making

PubMed Central

Zhang, Xian; Hirsch, Joy

2012-01-01

Real world tasks involving moving targets, such as driving a vehicle, are performed based on continuous decisions thought to depend upon the temporal derivative of the expected utility (∂V/∂t), where the expected utility (V) is the effective value of a future reward. However, those neural mechanisms that underlie dynamic decision-making are not well understood. This study investigates human neural correlates of both V and ∂V/∂t using fMRI and a novel experimental paradigm based on a pursuit-evasion game optimized to isolate components of dynamic decision processes. Our behavioral data show that players of the pursuit-evasion game adopt an exponential discounting function, supporting the expected utility theory. The continuous functions of V and ∂V/∂t were derived from the behavioral data and applied as regressors in fMRI analysis, enabling temporal resolution that exceeded the sampling rate of image acquisition, hyper-temporal resolution, by taking advantage of numerous trials that provide rich and independent manipulation of those variables. V and ∂V/∂t were each associated with distinct neural activity. Specifically, ∂V/∂t was associated with anterior and posterior cingulate cortices, superior parietal lobule, and ventral pallidum, whereas V was primarily associated with supplementary motor, pre and post central gyri, cerebellum, and thalamus. The association between the ∂V/∂t and brain regions previously related to decision-making is consistent with the primary role of the temporal derivative of expected utility in dynamic decision-making. PMID:22963852

Analysis of Accelerometer Data from a Woven Inflatable Creep Burst Test

NASA Technical Reports Server (NTRS)

James, George H.; Grygier, Michael; Selig, Molly M.

2015-01-01

Accelerometers were used to montor an inflatable test article during a creep test to failure. The test article experienced impulse events that were classified based on the response of the sensors and their time-dependent manifestation. These impulse events required specialized techniques to process the structural dynamics data. However, certain phenomena were defined as worthy of additional study. An assessment of one phenomena (a frequency near 1000Hz) showed a time dependent frequency and an amplitude that increased significantly near the end of the test. Hence, these observations are expected to drive future understanding of and utility in inflatable space structures.

Does Venus wobble

NASA Technical Reports Server (NTRS)

Yoder, C. F.; Ward, W. R.

1979-01-01

The free wobble damping time for Venus due to solar tides and rotational flexing is found to be approximately 700,000 times Q sub omega years, where Q sub omega is the dissipation function associated with the wobble frequency. The slow spin and expected small (nonhydrostatic) J2 predict a very long wobble period of about 100,000 years. As a result, a simple scaling of the earth's Chandler wobble excitation rate to that of Venus suggests that an appreciable wobble could exist. Detection (or lack thereof) of a free wobble may thus place constraints on the dynamic activity (e.g., mantle convection, Venusquakes, etc.) of the Venus interior.

Inferring the relative resilience of alternative states

USGS Publications Warehouse

Angeler, David G.; Allen, Craig R.; Rojo, Carmen; Alvarez-Cobelas, Miguel; Rodrigo, Maria A.; Sanchez-Carrillo, Salvador

2013-01-01

Ecological systems may occur in alternative states that differ in ecological structures, functions and processes. Resilience is the measure of disturbance an ecological system can absorb before changing states. However, how the intrinsic structures and processes of systems that characterize their states affects their resilience remains unclear. We analyzed time series of phytoplankton communities at three sites in a floodplain in central Spain to assess the dominant frequencies or “temporal scales” in community dynamics and compared the patterns between a wet and a dry alternative state. The identified frequencies and cross-scale structures are expected to arise from positive feedbacks that are thought to reinforce processes in alternative states of ecological systems and regulate emergent phenomena such as resilience. Our analyses show a higher species richness and diversity but lower evenness in the dry state. Time series modeling revealed a decrease in the importance of short-term variability in the communities, suggesting that community dynamics slowed down in the dry relative to the wet state. The number of temporal scales at which community dynamics manifested, and the explanatory power of time series models, was lower in the dry state. The higher diversity, reduced number of temporal scales and the lower explanatory power of time series models suggest that species dynamics tended to be more stochastic in the dry state. From a resilience perspective our results highlight a paradox: increasing species richness may not necessarily enhance resilience. The loss of cross-scale structure (i.e. the lower number of temporal scales) in community dynamics across sites suggests that resilience erodes during drought. Phytoplankton communities in the dry state are therefore likely less resilient than in the wet state. Our case study demonstrates the potential of time series modeling to assess attributes that mediate resilience. The approach is useful for assessing resilience of alternative states across ecological and other complex systems.

Global patterns of drought recovery

NASA Astrophysics Data System (ADS)

Schwalm, Christopher R.; Anderegg, William R. L.; Michalak, Anna M.; Fisher, Joshua B.; Biondi, Franco; Koch, George; Litvak, Marcy; Ogle, Kiona; Shaw, John D.; Wolf, Adam; Huntzinger, Deborah N.; Schaefer, Kevin; Cook, Robert; Wei, Yaxing; Fang, Yuanyuan; Hayes, Daniel; Huang, Maoyi; Jain, Atul; Tian, Hanqin

2017-08-01

Drought, a recurring phenomenon with major impacts on both human and natural systems, is the most widespread climatic extreme that negatively affects the land carbon sink. Although twentieth-century trends in drought regimes are ambiguous, across many regions more frequent and severe droughts are expected in the twenty-first century. Recovery time—how long an ecosystem requires to revert to its pre-drought functional state—is a critical metric of drought impact. Yet the factors influencing drought recovery and its spatiotemporal patterns at the global scale are largely unknown. Here we analyse three independent datasets of gross primary productivity and show that, across diverse ecosystems, drought recovery times are strongly associated with climate and carbon cycle dynamics, with biodiversity and CO2 fertilization as secondary factors. Our analysis also provides two key insights into the spatiotemporal patterns of drought recovery time: first, that recovery is longest in the tropics and high northern latitudes (both vulnerable areas of Earth’s climate system) and second, that drought impacts (assessed using the area of ecosystems actively recovering and time to recovery) have increased over the twentieth century. If droughts become more frequent, as expected, the time between droughts may become shorter than drought recovery time, leading to permanently damaged ecosystems and widespread degradation of the land carbon sink.

Time-dependent quantum transport and power-law decay of the transient current in a nano-relay and nano-oscillator

NASA Astrophysics Data System (ADS)

Cuansing, Eduardo C.; Liang, Gengchiau

2011-10-01

Time-dependent nonequilibrium Green's functions are used to study electron transport properties in a device consisting of two linear chain leads and a time-dependent interlead coupling that is switched on non-adiabatically. We derive a numerically exact expression for the particle current and examine its characteristics as it evolves in time from the transient regime to the long-time steady-state regime. We find that just after switch-on, the current initially overshoots the expected long-time steady-state value, oscillates and decays as a power law, and eventually settles to a steady-state value consistent with the value calculated using the Landauer formula. The power-law parameters depend on the values of the applied bias voltage, the strength of the couplings, and the speed of the switch-on. In particular, the oscillating transient current decays away longer for lower bias voltages. Furthermore, the power-law decay nature of the current suggests an equivalent series resistor-inductor-capacitor circuit wherein all of the components have time-dependent properties. Such dynamical resistive, inductive, and capacitive influences are generic in nano-circuits where dynamical switches are incorporated. We also examine the characteristics of the dynamical current in a nano-oscillator modeled by introducing a sinusoidally modulated interlead coupling between the two leads. We find that the current does not strictly follow the sinusoidal form of the coupling. In particular, the maximum current does not occur during times when the leads are exactly aligned. Instead, the times when the maximum current occurs depend on the values of the bias potential, nearest-neighbor coupling, and the interlead coupling.

Stable fiber-optic time transfer by active radio frequency phase locking.

PubMed

Yin, Feifei; Wu, Zhongle; Dai, Yitang; Ren, Tianpeng; Xu, Kun; Lin, Jintong; Tang, Geshi

2014-05-15

In this Letter we demonstrate a fiber link capable of stable time signal transfer utilizing our active long-distance radio frequency (RF) stabilization technology. Taking advantage of the chromatic dispersion in optical fiber, our scheme compensates dynamically the link delay variation by tuning the optical carrier wavelength to phase lock a round-trip RF reference. Since the time signal and the RF reference are carried by the same optical carrier, a highly stable time transfer is achieved at the same time. Experimentally, we demonstrate a stability of the time signal transfer over 50-km fiber with a time deviation of 40 ps at 1-s average and 2.3 ps at 1000-s average. The performance of the RF reference delivery is also tested, with an Allan deviation of 2×10(-15) at 1000-s average. According to our proposal, a simultaneous stable time and frequency transfer is expected.

Structures and Dynamics Division: Research and technology plans for FY 1983 and accomplishments for FY 1982

NASA Technical Reports Server (NTRS)

Bales, K. S.

1983-01-01

The objectives, expected results, approach, and milestones for research projects of the IPAD Project Office and the impact dynamics, structural mechanics, and structural dynamics branches of the Structures and Dynamics Division are presented. Research facilities are described. Topics covered include computer aided design; general aviation/transport crash dynamics; aircraft ground performance; composite structures; failure analysis, space vehicle dynamics; and large space structures.

Family Matters: Effects of Birth Order, Culture, and Family Dynamics on Surrogate Decision Making

PubMed Central

Su, Christopher T.; McMahan, Ryan D.; Williams, Brie A.; Sharma, Rashmi K.; Sudore, Rebecca L.

2014-01-01

Cultural attitudes about medical decision making and filial expectations may lead some surrogates to experience stress and family conflict. Thirteen focus groups with racially and ethnically diverse English- and Spanish-speakers from county and Veterans hospitals, senior centers, and cancer support groups were conducted to describe participants’ experiences making serious or end-of-life decisions for others. Filial expectations and family dynamics related to birth order and surrogate decision making were explored using qualitative, thematic content analysis and overarching themes from focus group transcripts were identified. The mean age of the 69 participants was 69 years ± 14 and 29% were African American, 26% were White, 26% were Asian/Pacific Islander, and 19% were Latino. Seventy percent of participants engaged in unprompted discussions about birth order and family dynamics. Six subthemes were identified within 3 overarching categories of communication, emotion, and conflict: Communication – (1) unspoken expectations and (2) discussion of death as taboo; Emotion – (3) emotional stress and (4) feelings of loneliness; and Conflict – (5) family conflict and (6) potential solutions to prevent conflict. These findings suggest that birth order and family dynamics can have profound effects on surrogate stress and coping. Clinicians should be aware of potential unspoken filial expectations for firstborns and help facilitate communication between the patient, surrogate, and extended family to reduce stress and conflict. PMID:24383459

Family matters: effects of birth order, culture, and family dynamics on surrogate decision-making.

PubMed

Su, Christopher T; McMahan, Ryan D; Williams, Brie A; Sharma, Rashmi K; Sudore, Rebecca L

2014-01-01

Cultural attitudes about medical decision-making and filial expectations may lead some surrogates to experience stress and family conflict. Thirteen focus groups with racially and ethnically diverse English and Spanish speakers from county and Veterans Affairs hospitals, senior centers, and cancer support groups were conducted to describe participants' experiences making serious or end-of-life decisions for others. Filial expectations and family dynamics related to birth order and surrogate decision-making were explored using qualitative, thematic content analysis, and overarching themes from focus group transcripts were identified. The mean age of the 69 participants was 69 ± 14, and 29% were African American, 26% were white, 26% were Asian or Pacific Islander, and 19% were Latino. Seventy percent of participants engaged in unprompted discussions about birth order and family dynamics. Six subthemes were identified within three overarching categories: communication (unspoken expectations and discussion of death as taboo), emotion (emotional stress and feelings of loneliness), and conflict (family conflict and potential solutions to prevent conflict). These findings suggest that birth order and family dynamics can have profound effects on surrogate stress and coping. Clinicians should be aware of potential unspoken filial expectations for firstborns and help facilitate communication between the patient, surrogate, and extended family to reduce stress and conflict. © Published 2013. This article is a U.S. Government work and is in the public domain in the U.S.A.

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

Zarzycki, Piotr P.; Rosso, Kevin M.

Replica Kinetic Monte Carlo simulations were used to study the characteristic time scales of potentiometric titration of the metal oxides and (oxy)hydroxides. The effect of surface heterogeneity and surface transformation on the titration kinetics were also examined. Two characteristic relaxation times are often observed experimentally, with the trailing slower part attributed to surface non-uniformity, porosity, polymerization, amorphization, and other dynamic surface processes induced by unbalanced surface charge. However, our simulations show that these two characteristic relaxation times are intrinsic to the proton binding reaction for energetically homogeneous surfaces, and therefore surface heterogeneity or transformation do not necessarily need to bemore » invoked. However, all such second-order surface processes are found to intensify the separation and distinction of the two kinetic regimes. The effect of surface energetic-topographic non-uniformity, as well dynamic surface transformation, interface roughening/smoothing were described in a statistical fashion. Furthermore, our simulations show that a shift in the point-of-zero charge is expected from increased titration speed and the pH-dependence of the titration measurement error is in excellent agreement with experimental studies.« less

Optimal stimulus scheduling for active estimation of evoked brain networks.

PubMed

Kafashan, MohammadMehdi; Ching, ShiNung

2015-12-01

We consider the problem of optimal probing to learn connections in an evoked dynamic network. Such a network, in which each edge measures an input-output relationship between sites in sensor/actuator-space, is relevant to emerging applications in neural mapping and neural connectivity estimation. We show that the problem of scheduling nodes to a probe (i.e., stimulate) amounts to a problem of optimal sensor scheduling. By formulating the evoked network in state-space, we show that the solution to the greedy probing strategy has a convenient form and, under certain conditions, is optimal over a finite horizon. We adopt an expectation maximization technique to update the state-space parameters in an online fashion and demonstrate the efficacy of the overall approach in a series of detailed numerical examples. The proposed method provides a principled means to actively probe time-varying connections in neuronal networks. The overall method can be implemented in real time and is particularly well-suited to applications in stimulation-based cortical mapping in which the underlying network dynamics are changing over time.

Simulating Descent and Landing of a Spacecraft

NASA Technical Reports Server (NTRS)

Balaram, J.; Jain, Abhinandan; Martin, Bryan; Lim, Christopher; Henriquez, David; McMahon, Elihu; Sohl, Garrett; Banerjee, Pranab; Steele, Robert; Bentley, Timothy

2005-01-01

The Dynamics Simulator for Entry, Descent, and Surface landing (DSENDS) software performs high-fidelity simulation of the Entry, Descent, and Landing (EDL) of a spacecraft into the atmosphere and onto the surface of a planet or a smaller body. DSENDS is an extension of the DShell and DARTS programs, which afford capabilities for mathematical modeling of the dynamics of a spacecraft as a whole and of its instruments, actuators, and other subsystems. DSENDS enables the modeling (including real-time simulation) of flight-train elements and all spacecraft responses during various phases of EDL. DSENDS provides high-fidelity models of the aerodynamics of entry bodies and parachutes plus supporting models of atmospheres. Terrain and real-time responses of terrain-imaging radar and lidar instruments can also be modeled. The program includes modules for simulation of guidance, navigation, hypersonic steering, and powered descent. Automated state-machine-driven model switching is used to represent spacecraft separations and reconfigurations. Models for computing landing contact and impact forces are expected to be added. DSENDS can be used as a stand-alone program or incorporated into a larger program that simulates operations in real time.

Optimal stimulus scheduling for active estimation of evoked brain networks

NASA Astrophysics Data System (ADS)

Kafashan, MohammadMehdi; Ching, ShiNung

2015-12-01

Objective. We consider the problem of optimal probing to learn connections in an evoked dynamic network. Such a network, in which each edge measures an input-output relationship between sites in sensor/actuator-space, is relevant to emerging applications in neural mapping and neural connectivity estimation. Approach. We show that the problem of scheduling nodes to a probe (i.e., stimulate) amounts to a problem of optimal sensor scheduling. Main results. By formulating the evoked network in state-space, we show that the solution to the greedy probing strategy has a convenient form and, under certain conditions, is optimal over a finite horizon. We adopt an expectation maximization technique to update the state-space parameters in an online fashion and demonstrate the efficacy of the overall approach in a series of detailed numerical examples. Significance. The proposed method provides a principled means to actively probe time-varying connections in neuronal networks. The overall method can be implemented in real time and is particularly well-suited to applications in stimulation-based cortical mapping in which the underlying network dynamics are changing over time.

Sensor Measurement Strategies for Monitoring Offshore Wind and Wave Energy Devices

NASA Astrophysics Data System (ADS)

O'Donnell, Deirdre; Srbinovsky, Bruno; Murphy, Jimmy; Popovici, Emanuel; Pakrashi, Vikram

2015-07-01

While the potential of offshore wind and wave energy devices is well established and accepted, operations and maintenance issues are still not very well researched or understood. In this regard, scaled model testing has gained popularity over time for such devices at various technological readiness levels. The dynamic response of these devices are typically measured by different instruments during such scaled tests but agreed sensor choice, measurement and placement guidelines are still not in place. This paper compared the dynamic responses of some of these sensors from a scaled ocean wave testing to highlight the importance of sensor measurement strategies. The possibility of using multiple, cheaper sensors of seemingly inferior performance as opposed to the deployment of a small number of expensive and accurate sensors are also explored. An energy aware adaptive sampling theory is applied to highlight the possibility of more efficient computing when large volumes of data are available from the tested structures. Efficient sensor measurement strategies are expected to have a positive impact on the development of an device at different technological readiness levels while it is expected to be helpful in reducing operation and maintenance costs if such an approach is considered for the devices when they are in operation.

A stable dynamic cohort analysis of installing cost-effective rollover protective structures (CROPS).

PubMed

Owusu-Edusei, K; Biddle, E A

2007-04-01

Cost-effective rollover protective structures (CROPS) are less costly model-specific rollover protective structure (ROPS) retrofits that are being developed and evaluated with the hope of increasing adoption and eventually preventing or mitigating injuries due to tractor overturns. A dynamic cohort of the estimated retrofittable non-ROPS tractors (accounting for attrition due to aging) was tracked over a 20-year period to determine the expected costs, as well as the expected number of fatal and non-fatal injuries resulting from tractor overturns. Two alternatives were tracked: No-ROPS and Install-CROPS. For a starting cohort size of 1,065,164 (an estimate for the year 2004), the Install-CROPS option prevented an estimated total of 878 (192 fatal and 686 non-fatal) injuries over the 20-year period. Expected costs were $513 million (cost of installing CROPS on all the non-ROPS tractors plus cost of the associated injuries) and $284 million (cost of injuries resulting from the No-ROPS option) over the same time period. Thus, the net cost per injury prevented was $260,820. When the cost of intervention ($1000 for purchasing, shipping, and installation of existing ROPS retrofit) was used in the analysis, the cost-effectiveness ratio was $927,000 per injury prevented over the 20-year period. Thus, installing CROPS instead of existing ROPS retrofits improved the cost-effectiveness ratio substantially, with a 72% reduction in the net cost per injury prevented.

High-speed nanoscale characterization of dewetting via dynamic transmission electron microscopy

NASA Astrophysics Data System (ADS)

Hihath, Sahar; Santala, Melissa K.; Campbell, Geoffrey; van Benthem, Klaus

2016-08-01

The dewetting of thin films can occur in either the solid or the liquid state for which different mass transport mechanisms are expected to control morphological changes. Traditionally, dewetting dynamics have been examined on time scales between several seconds to hours, and length scales ranging between nanometers and millimeters. The determination of mass transport mechanisms on the nanoscale, however, requires nanoscale spatial resolution and much shorter time scales. This study reports the high-speed observation of dewetting phenomena for kinetically constrained Ni thin films on crystalline SrTiO3 substrates. Movie-mode Dynamic Transmission Electron Microscopy (DTEM) was used for high-speed image acquisition during thin film dewetting at different temperatures. DTEM imaging confirmed that the initial stages of film agglomeration include edge retraction, hole formation, and growth. Finite element modeling was used to simulate temperature distributions within the DTEM samples after laser irradiation with different energies. For pulsed laser irradiation at 18 μJ, experimentally observed hole growth suggests that Marangoni flow dominates hole formation in the liquid nickel film. After irradiation with 13.8 μJ, however, the observations suggest that dewetting was initiated by nucleation of voids followed by hole growth through solid-state surface diffusion.

A minimization principle for the description of modes associated with finite-time instabilities

PubMed Central

Babaee, H.

2016-01-01

We introduce a minimization formulation for the determination of a finite-dimensional, time-dependent, orthonormal basis that captures directions of the phase space associated with transient instabilities. While these instabilities have finite lifetime, they can play a crucial role either by altering the system dynamics through the activation of other instabilities or by creating sudden nonlinear energy transfers that lead to extreme responses. However, their essentially transient character makes their description a particularly challenging task. We develop a minimization framework that focuses on the optimal approximation of the system dynamics in the neighbourhood of the system state. This minimization formulation results in differential equations that evolve a time-dependent basis so that it optimally approximates the most unstable directions. We demonstrate the capability of the method for two families of problems: (i) linear systems, including the advection–diffusion operator in a strongly non-normal regime as well as the Orr–Sommerfeld/Squire operator, and (ii) nonlinear problems, including a low-dimensional system with transient instabilities and the vertical jet in cross-flow. We demonstrate that the time-dependent subspace captures the strongly transient non-normal energy growth (in the short-time regime), while for longer times the modes capture the expected asymptotic behaviour. PMID:27118900

Measurement of nuclear resonant scattering on 61Ni with fast scintillation detector using proportional-mode silicon avalanche photodiode

NASA Astrophysics Data System (ADS)

Inoue, Keisuke; Kobayashi, Yasuhiro; Yoda, Yoshitaka; Koshimizu, Masanori; Nishikido, Fumihiko; Haruki, Rie; Kishimoto, Shunji

2018-02-01

We developed a new scintillation timing detector using a proportional-mode silicon avalanche photodiode (Si-APD) for synchrotron radiation nuclear resonant scattering. We report on the nuclear forward scattering measurement on 61Ni with a prototype detector using a lead-loaded plastic scintillator (EJ-256, 3 mm in diameter and 2 mm in thickness), mounted on a proportional-mode Si-APD. Using synchrotron X-rays of 67.41 keV, we successfully measured the time spectra of nuclear forward scattering on 61Ni enriched metal foil and 61Ni86V14 alloy. The prototype detector confirmed the expected dynamical beat structure with a time resolution of 0.53 ns (FWHM).

Monolayer phosphorene under time-dependent magnetic field

NASA Astrophysics Data System (ADS)

Nascimento, J. P. G.; Aguiar, V.; Guedes, I.

2018-02-01

We obtain the exact wave function of a monolayer phosphorene under a low-intensity time-dependent magnetic field using the dynamical invariant method. We calculate the quantum-mechanical energy expectation value and the transition probability for a constant and an oscillatory magnetic field. For the former we observe that the Landau level energy varies linearly with the quantum numbers n and m and the magnetic field intensity B0. No transition takes place. For the latter, we observe that the energy oscillates in time, increasing linearly with the Landau level n and m and nonlinearly with the magnetic field. The (k , l) →(n , m) transitions take place only for l = m. We investigate the (0,0) →(n , 0) and (1 , l) and (2 , l) probability transitions.

Impact of transient climate change upon Grouse population dynamics in the Italian Alps

NASA Astrophysics Data System (ADS)

Pirovano, Andrea; Bocchiola, Daniele

2010-05-01

Understanding the effect of short to medium term weather condition, and of transient global warming upon wildlife species life history is essential to predict the demographic consequences therein, and possibly develop adaptation strategies, especially in game species, where hunting mortality may play an important role in population dynamics. We carried out a preliminary investigation of observed impact of weather variables upon population dynamics indexes of three alpine Grouse species (i.e. Rock Ptarmigan, Lagopus Mutus, Black Grouse, Tetrao Tetrix, Rock Partridge, Alectoris Graeca), nested within central Italian Alps, based upon 15 years (1995-2009) of available censuses data, provided by the Sondrio Province authority. We used a set of climate variables already highlighted within recent literature for carrying considerable bearing on Grouse population dynamics, including e.g. temperature at hatching time and during winter, snow cover at nesting, and precipitation during nursing period. We then developed models of Grouses' population dynamics by explicitly driving population change according to their dependence upon the significant weather variables and population density and we evaluated objective indexes to assess the so obtained predictive power. Eventually, we develop projection of future local climate, based upon locally derived trends, and upon projections from GCMs (A2 IPCC storyline) already validated for the area, to project forward in time (until 2100 or so) the significant climatic variables, which we then use to force population dynamics models of the target species. The projected patterns obtained through this exercise are discussed and compared against those expected under stationary climate conditions at present, and preliminary conclusions are drawn.

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

PubMed

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

2018-05-30

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

Exploring the energy landscape of antibody-antigen complexes: protein dynamics, flexibility, and molecular recognition.

PubMed

Thielges, Megan C; Zimmermann, Jörg; Yu, Wayne; Oda, Masayuki; Romesberg, Floyd E

2008-07-08

The production of antibodies that selectively bind virtually any foreign compound is the hallmark of the immune system. While much is understood about how sequence diversity contributes to this remarkable feat of molecular recognition, little is known about how sequence diversity impacts antibody dynamics, which is also expected to contribute to molecular recognition. Toward this goal, we examined a panel of antibodies elicited to the chromophoric antigen fluorescein. On the basis of isothermal titration calorimetry, we selected six antibodies that bind fluorescein with diverse binding entropies, suggestive of varying contributions of dynamics to molecular recognition. Sequencing revealed that two pairs of antibodies employ homologous heavy chains that were derived from common germline genes, while the other two heavy chains and all six of the light chains were derived from different germline genes and are not homologous. Interestingly, more than half of all the somatic mutations acquired during affinity maturation among the six antibodies are located in positions unlikely to contact fluorescein directly. To quantify and compare the dynamics of the antibody-fluorescein complexes, three-pulse photon echo peak shift and transient grating spectroscopy were employed. All of the antibodies exhibited motions on three distinct time scales, ultrafast motions on the <100 fs time scale, diffusive motions on the picosecond time scale, and motions that occur on time scales longer than nanoseconds and thus appear static. However, the exact frequency of the picosecond time scale motion and the relative contribution of the different motions vary significantly among the antibody-chromophore complexes, revealing a high level of dynamic diversity. Using a hierarchical model, we relate the data to features of the antibodies' energy landscapes as well as their flexibility in terms of elasticity and plasticity. In all, the data provide a consistent picture of antibody flexibility, which interestingly appears to be correlated with binding entropy as well as with germline gene use and the mutations introduced during affinity maturation. The data also provide a gauge of the dynamic diversity of the antibody repertoire and suggest that this diversity might contribute to molecular recognition by facilitating the recognition of the broadest range of foreign molecules.

Slow-rotation dynamic SPECT with a temporal second derivative constraint.

PubMed

Humphries, T; Celler, A; Trummer, M

2011-08-01

Dynamic tracer behavior in the human body arises as a result of continuous physiological processes. Hence, the change in tracer concentration within a region of interest (ROI) should follow a smooth curve. The authors propose a modification to an existing slow-rotation dynamic SPECT reconstruction algorithm (dSPECT) with the goal of improving the smoothness of time activity curves (TACs) and other properties of the reconstructed image. The new method, denoted d2EM, imposes a constraint on the second derivative (concavity) of the TAC in every voxel of the reconstructed image, allowing it to change sign at most once. Further constraints are enforced to prevent other nonphysical behaviors from arising. The new method is compared with dSPECT using digital phantom simulations and experimental dynamic 99mTc -DTPA renal SPECT data, to assess any improvement in image quality. In both phantom simulations and healthy volunteer experiments, the d2EM method provides smoother TACs than dSPECT, with more consistent shapes in regions with dynamic behavior. Magnitudes of TACs within an ROI still vary noticeably in both dSPECT and d2EM images, but also in images produced using an OSEM approach that reconstructs each time frame individually, based on much more complete projection data. TACs produced by averaging over a region are similar using either method, even for small ROIs. Results for experimental renal data show expected behavior in images produced by both methods, with d2EM providing somewhat smoother mean TACs and more consistent TAC shapes. The d2EM method is successful in improving the smoothness of time activity curves obtained from the reconstruction, as well as improving consistency of TAC shapes within ROIs.

Dynamics of a high-current relativistic electron beam

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

Strelkov, P. S., E-mail: strelkov@fpl.gpi.ru; Tarakanov, V. P., E-mail: karat@gmail.ru; Ivanov, I. E., E-mail: iei@fpl.gpi.ru

2015-06-15

The dynamics of a high-current relativistic electron beam is studied experimentally and by numerical simulation. The beam is formed in a magnetically insulated diode with a transverse-blade explosive-emission cathode. It is found experimentally that the radius of a 500-keV beam with a current of 2 kA and duration of 500 ns decreases with time during the beam current pulse. The same effect was observed in numerical simulations. This effect is explained by a change in the shape of the cathode plasma during the current pulse, which, according to calculations, leads to a change in the beam parameters, such as themore » electron pitch angle and the spread over the longitudinal electron momentum. These parameters are hard to measure experimentally; however, the time evolution of the radial profile of the beam current density, which can be measured reliably, coincides with the simulation results. This allows one to expect that the behavior of the other beam parameters also agrees with numerical simulations.« less

An Indentation Technique for Nanoscale Dynamic Viscoelastic Measurements at Elevated Temperature

NASA Astrophysics Data System (ADS)

Ye, Jiping

2012-08-01

Determination of nano/micro-scale viscoelasticity is very important to understand the local rheological behavior and degradation phenomena of multifunctional polymer blend materials. This article reviews research results concerning the development of indentation techniques for making nanoscale dynamic viscoelastic measurements at elevated temperature. In the last decade, we have achieved breakthroughs in noise floor reduction in air and thermal load drift/noise reduction at high temperature before taking on the challenge of nanoscale viscoelastic measurements. A high-temperature indentation technique has been developed that facilitates viscoelastic measurements up to 200 °C in air and 500 °C in a vacuum. During the last year, two viscoelastic measurement methods have been developed by making a breakthrough in suppressing the contact area change at high temperature. One is a sharp-pointed time-dependent nanoindentation technique for microscale application and the other is a spherical time-dependent nanoindentation technique for nanoscale application. In the near future, we expect to lower the thermal load drift and load noise floor even more substantially.

Brain mechanisms controlling decision making and motor planning.

PubMed

Ramakrishnan, Arjun; Murthy, Aditya

2013-01-01

Accumulator models of decision making provide a unified framework to understand decision making and motor planning. In these models, the evolution of a decision is reflected in the accumulation of sensory information into a motor plan that reaches a threshold, leading to choice behavior. While these models provide an elegant framework to understand performance and reaction times, their ability to explain complex behaviors such as decision making and motor control of sequential movements in dynamic environments is unclear. To examine and probe the limits of online modification of decision making and motor planning, an oculomotor "redirect" task was used. Here, subjects were expected to change their eye movement plan when a new saccade target appeared. Based on task performance, saccade reaction time distributions, computational models of behavior, and intracortical microstimulation of monkey frontal eye fields, we show how accumulator models can be tested and extended to study dynamic aspects of decision making and motor control. Copyright © 2013 Elsevier B.V. All rights reserved.

Multistage modeling of protein dynamics with monomeric Myc oncoprotein as an example.

PubMed

Liu, Jiaojiao; Dai, Jin; He, Jianfeng; Niemi, Antti J; Ilieva, Nevena

2017-03-01

We propose to combine a mean-field approach with all-atom molecular dynamics (MD) into a multistage algorithm that can model protein folding and dynamics over very long time periods yet with atomic-level precision. As an example, we investigate an isolated monomeric Myc oncoprotein that has been implicated in carcinomas including those in colon, breast, and lungs. Under physiological conditions a monomeric Myc is presumed to be an example of intrinsically disordered proteins that pose a serious challenge to existing modeling techniques. We argue that a room-temperature monomeric Myc is in a dynamical state, it oscillates between different conformations that we identify. For this we adopt the Cα backbone of Myc in a crystallographic heteromer as an initial ansatz for the monomeric structure. We construct a multisoliton of the pertinent Landau free energy to describe the Cα profile with ultrahigh precision. We use Glauber dynamics to resolve how the multisoliton responds to repeated increases and decreases in ambient temperature. We confirm that the initial structure is unstable in isolation. We reveal a highly degenerate ground-state landscape, an attractive set towards which Glauber dynamics converges in the limit of vanishing ambient temperature. We analyze the thermal stability of this Glauber attractor using room-temperature molecular dynamics. We identify and scrutinize a particularly stable subset in which the two helical segments of the original multisoliton align in parallel next to each other. During the MD time evolution of a representative structure from this subset, we observe intermittent quasiparticle oscillations along the C-terminal α helix, some of which resemble a translating Davydov's Amide-I soliton. We propose that the presence of oscillatory motion is in line with the expected intrinsically disordered character of Myc.

Dispersal, density dependence, and population dynamics of a fungal microbe on leaf surfaces.

PubMed

Woody, Scott T; Ives, Anthony R; Nordheim, Erik V; Andrews, John H

2007-06-01

Despite the ubiquity and importance of microbes in nature, little is known about their natural population dynamics, especially for those that occupy terrestrial habitats. Here we investigate the dynamics of the yeast-like fungus Aureobasidium pullulans (Ap) on apple leaves in an orchard. We asked three questions. (1) Is variation in fungal population density among leaves caused by variation in leaf carrying capacities and strong density-dependent population growth that maintains densities near carrying capacity? (2) Do resident populations have competitive advantages over immigrant cells? (3) Do Ap dynamics differ at different times during the growing season? To address these questions, we performed two experiments at different times in the growing season. Both experiments used a 2 x 2 factorial design: treatment 1 removed fungal cells from leaves to reveal density-dependent population growth, and treatment 2 inoculated leaves with an Ap strain engineered to express green fluorescent protein (GFP), which made it possible to track the fate of immigrant cells. The experiments showed that natural populations of Ap vary greatly in density due to sustained differences in carrying capacities among leaves. The maintenance of populations close to carrying capacities indicates strong density-dependent processes. Furthermore, resident populations are strongly competitive against immigrants, while immigrants have little impact on residents. Finally, statistical models showed high population growth rates of resident cells in one experiment but not in the other, suggesting that Ap experiences relatively "good" and "bad" periods for population growth. This picture of Ap dynamics conforms to commonly held, but rarely demonstrated, expectations of microbe dynamics in nature. It also highlights the importance of local processes, as opposed to immigration, in determining the abundance and dynamics of microbes on surfaces in terrestrial systems.

A Linear Dynamical Systems Approach to Streamflow Reconstruction Reveals History of Regime Shifts in Northern Thailand

NASA Astrophysics Data System (ADS)

Nguyen, Hung T. T.; Galelli, Stefano

2018-03-01

Catchment dynamics is not often modeled in streamflow reconstruction studies; yet, the streamflow generation process depends on both catchment state and climatic inputs. To explicitly account for this interaction, we contribute a linear dynamic model, in which streamflow is a function of both catchment state (i.e., wet/dry) and paleoclimatic proxies. The model is learned using a novel variant of the Expectation-Maximization algorithm, and it is used with a paleo drought record—the Monsoon Asia Drought Atlas—to reconstruct 406 years of streamflow for the Ping River (northern Thailand). Results for the instrumental period show that the dynamic model has higher accuracy than conventional linear regression; all performance scores improve by 45-497%. Furthermore, the reconstructed trajectory of the state variable provides valuable insights about the catchment history—e.g., regime-like behavior—thereby complementing the information contained in the reconstructed streamflow time series. The proposed technique can replace linear regression, since it only requires information on streamflow and climatic proxies (e.g., tree-rings, drought indices); furthermore, it is capable of readily generating stochastic streamflow replicates. With a marginal increase in computational requirements, the dynamic model brings more desirable features and value to streamflow reconstructions.

Application of Simulated Reactivity Feedback in Nonnuclear Testing of a Direct-Drive Gas-Cooled Reactor

NASA Technical Reports Server (NTRS)

Bragg-Sitton, S. M.; Webster, K. L.

2007-01-01

Nonnuclear testing can be a valuable tool in the development of an in-space nuclear power or propulsion system. In a nonnuclear test facility, electric heaters are used to simulate heat from nuclear fuel. Standard testing allows one to fully assess thermal, heat transfer, and stress related attributes of a given system but fails to demonstrate the dynamic response that would be present in an integrated, fueled reactor system. The integration of thermal hydraulic hardware tests with simulated neutronic response provides a bridge between electrically heated testing and full nuclear testing. By implementing a neutronic response model to simulate the dynamic response that would be expected in a fueled reactor system, one can better understand system integration issues, characterize integrated system response times and response and response characteristics, and assess potential design improvements with a relatively small fiscal investment. Initial system dynamic response testing was demonstrated on the integrated SAFE 100a heat pipe cooled, electrically heated reactor and heat exchanger hardware. This Technical Memorandum discusses the status of the planned dynamic test methodology for implementation in the direct-drive gas-cooled reactor testing and assesses the additional instrumentation needed to implement high-fidelity dynamic testing.

Dynamical tunneling versus fast diffusion for a non-convex Hamiltonian

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

Pittman, S. M.; Tannenbaum, E.; Heller, E. J.

This paper attempts to resolve the issue of the nature of the 0.01-0.1 cm{sup −1} peak splittings observed in high-resolution IR spectra of polyatomic molecules. One hypothesis is that these splittings are caused by dynamical tunneling, a quantum-mechanical phenomenon whereby energy flows between two disconnected regions of phase-space across dynamical barriers. However, a competing classical mechanism for energy flow is Arnol’d diffusion, which connects different regions of phase-space by a resonance network known as the Arnol’d web. The speed of diffusion is bounded by the Nekhoroshev theorem, which guarantees stability on exponentially long time scales if the Hamiltonian is steep.more » Here we consider a non-convex Hamiltonian that contains the characteristics of a molecular Hamiltonian, but does not satisfy the Nekhoroshev theorem. The diffusion along the Arnol’d web is expected to be fast for a non-convex Hamiltonian. While fast diffusion is an unlikely competitor for longtime energy flow in molecules, we show how dynamical tunneling dominates compared to fast diffusion in the nearly integrable regime for a non-convex Hamiltonian, as well as present a new kind of dynamical tunneling.« less

Adaptive Actor-Critic Design-Based Integral Sliding-Mode Control for Partially Unknown Nonlinear Systems With Input Disturbances.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong

2016-01-01

This paper is concerned with the problem of integral sliding-mode control for a class of nonlinear systems with input disturbances and unknown nonlinear terms through the adaptive actor-critic (AC) control method. The main objective is to design a sliding-mode control methodology based on the adaptive dynamic programming (ADP) method, so that the closed-loop system with time-varying disturbances is stable and the nearly optimal performance of the sliding-mode dynamics can be guaranteed. In the first step, a neural network (NN)-based observer and a disturbance observer are designed to approximate the unknown nonlinear terms and estimate the input disturbances, respectively. Based on the NN approximations and disturbance estimations, the discontinuous part of the sliding-mode control is constructed to eliminate the effect of the disturbances and attain the expected equivalent sliding-mode dynamics. Then, the ADP method with AC structure is presented to learn the optimal control for the sliding-mode dynamics online. Reconstructed tuning laws are developed to guarantee the stability of the sliding-mode dynamics and the convergence of the weights of critic and actor NNs. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.

Structural model for fluctuations in financial markets

NASA Astrophysics Data System (ADS)

Anand, Kartik; Khedair, Jonathan; Kühn, Reimer

2018-05-01

In this paper we provide a comprehensive analysis of a structural model for the dynamics of prices of assets traded in a market which takes the form of an interacting generalization of the geometric Brownian motion model. It is formally equivalent to a model describing the stochastic dynamics of a system of analog neurons, which is expected to exhibit glassy properties and thus many metastable states in a large portion of its parameter space. We perform a generating functional analysis, introducing a slow driving of the dynamics to mimic the effect of slowly varying macroeconomic conditions. Distributions of asset returns over various time separations are evaluated analytically and are found to be fat-tailed in a manner broadly in line with empirical observations. Our model also allows us to identify collective, interaction-mediated properties of pricing distributions and it predicts pricing distributions which are significantly broader than their noninteracting counterparts, if interactions between prices in the model contain a ferromagnetic bias. Using simulations, we are able to substantiate one of the main hypotheses underlying the original modeling, viz., that the phenomenon of volatility clustering can be rationalized in terms of an interplay between the dynamics within metastable states and the dynamics of occasional transitions between them.

The UOSAT magnetometer experiment

NASA Technical Reports Server (NTRS)

Acuna, M. H.

1982-01-01

The magnetometer aboard the University of Surrey satellite (UOSAT) and its associated electronics are described. The basic fluxgate magnetometer employed has a dynamic range of plus or minus 8000 nT with outputs digitized by a 12-bit successive approximation A-D converter having a resolution of plus or minus 2 nT. Noise in the 3-13 Hz bandwidth is less than 1 nT. A bias field generator extends the dynamic range to plus or minus 64,000 nT with quantization steps of 8000 nT. The magnetometer experiment is expected to provide information on the secular variation of the geomagnetic field, and the decay rate of the dipole term. Special emphasis will be placed on the acquisition of real time and memory data over the poles which can be correlated with that from Magsat.

Ultrafast energy relaxation in single light-harvesting complexes

DOE PAGES

Maly, Pavel; Gruber, J. Michael; Cogdell, Richard J.; ...

2016-02-22

Energy relaxation in light-harvesting complexes has been extensively studied by various ultrafast spectroscopic techniques, the fastest processes being in the sub–100-fs range. At the same time, much slower dynamics have been observed in individual complexes by single-molecule fluorescence spectroscopy (SMS). In this work, we use a pump–probe-type SMS technique to observe the ultrafast energy relaxation in single light-harvesting complexes LH2 of purple bacteria. After excitation at 800 nm, the measured relaxation time distribution of multiple complexes has a peak at 95 fs and is asymmetric, with a tail at slower relaxation times. When tuning the excitation wavelength, the distribution changesmore » in both its shape and position. The observed behavior agrees with what is to be expected from the LH2 excited states structure. As we show by a Redfield theory calculation of the relaxation times, the distribution shape corresponds to the expected effect of Gaussian disorder of the pigment transition energies. By repeatedly measuring few individual complexes for minutes, we find that complexes sample the relaxation time distribution on a timescale of seconds. Furthermore, by comparing the distribution from a single long-lived complex with the whole ensemble, we demonstrate that, regarding the relaxation times, the ensemble can be considered ergodic. Lastly, our findings thus agree with the commonly used notion of an ensemble of identical LH2 complexes experiencing slow random fluctuations.« less

Ultrafast energy relaxation in single light-harvesting complexes.

PubMed

Malý, Pavel; Gruber, J Michael; Cogdell, Richard J; Mančal, Tomáš; van Grondelle, Rienk

2016-03-15

Energy relaxation in light-harvesting complexes has been extensively studied by various ultrafast spectroscopic techniques, the fastest processes being in the sub-100-fs range. At the same time, much slower dynamics have been observed in individual complexes by single-molecule fluorescence spectroscopy (SMS). In this work, we use a pump-probe-type SMS technique to observe the ultrafast energy relaxation in single light-harvesting complexes LH2 of purple bacteria. After excitation at 800 nm, the measured relaxation time distribution of multiple complexes has a peak at 95 fs and is asymmetric, with a tail at slower relaxation times. When tuning the excitation wavelength, the distribution changes in both its shape and position. The observed behavior agrees with what is to be expected from the LH2 excited states structure. As we show by a Redfield theory calculation of the relaxation times, the distribution shape corresponds to the expected effect of Gaussian disorder of the pigment transition energies. By repeatedly measuring few individual complexes for minutes, we find that complexes sample the relaxation time distribution on a timescale of seconds. Furthermore, by comparing the distribution from a single long-lived complex with the whole ensemble, we demonstrate that, regarding the relaxation times, the ensemble can be considered ergodic. Our findings thus agree with the commonly used notion of an ensemble of identical LH2 complexes experiencing slow random fluctuations.

Ultrafast energy relaxation in single light-harvesting complexes

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

Maly, Pavel; Gruber, J. Michael; Cogdell, Richard J.

Energy relaxation in light-harvesting complexes has been extensively studied by various ultrafast spectroscopic techniques, the fastest processes being in the sub–100-fs range. At the same time, much slower dynamics have been observed in individual complexes by single-molecule fluorescence spectroscopy (SMS). In this work, we use a pump–probe-type SMS technique to observe the ultrafast energy relaxation in single light-harvesting complexes LH2 of purple bacteria. After excitation at 800 nm, the measured relaxation time distribution of multiple complexes has a peak at 95 fs and is asymmetric, with a tail at slower relaxation times. When tuning the excitation wavelength, the distribution changesmore » in both its shape and position. The observed behavior agrees with what is to be expected from the LH2 excited states structure. As we show by a Redfield theory calculation of the relaxation times, the distribution shape corresponds to the expected effect of Gaussian disorder of the pigment transition energies. By repeatedly measuring few individual complexes for minutes, we find that complexes sample the relaxation time distribution on a timescale of seconds. Furthermore, by comparing the distribution from a single long-lived complex with the whole ensemble, we demonstrate that, regarding the relaxation times, the ensemble can be considered ergodic. Lastly, our findings thus agree with the commonly used notion of an ensemble of identical LH2 complexes experiencing slow random fluctuations.« less

Temporal fluctuations after a quantum quench: Many-particle dephasing

NASA Astrophysics Data System (ADS)

Marquardt, Florian; Kiendl, Thomas

After a quantum quench, the expectation values of observables continue to fluctuate in time. In the thermodynamic limit, one expects such fluctuations to decrease to zero, in order for standard statistical physics to hold. However, it is a challenge to determine analytically how the fluctuations decay as a function of system size. So far, there have been analytical predictions for integrable models (which are, naturally, somewhat special), analytical bounds for arbitrary systems, and numerical results for moderate-size systems. We have discovered a dynamical regime where the decrease of fluctuations is driven by many-particle dephasing, instead of a redistribution of occupation numbers. On the basis of this insight, we are able to provide exact analytical expressions for a model with weak integrability breaking (transverse Ising chain with additional terms). These predictions explicitly show how fluctuations are exponentially suppressed with system size.

Item parameters dissociate between expectation formats: a regression analysis of time-frequency decomposed EEG data

PubMed Central

Monsalve, Irene F.; Pérez, Alejandro; Molinaro, Nicola

2014-01-01

During language comprehension, semantic contextual information is used to generate expectations about upcoming items. This has been commonly studied through the N400 event-related potential (ERP), as a measure of facilitated lexical retrieval. However, the associative relationships in multi-word expressions (MWE) may enable the generation of a categorical expectation, leading to lexical retrieval before target word onset. Processing of the target word would thus reflect a target-identification mechanism, possibly indexed by a P3 ERP component. However, given their time overlap (200–500 ms post-stimulus onset), differentiating between N400/P3 ERP responses (averaged over multiple linguistically variable trials) is problematic. In the present study, we analyzed EEG data from a previous experiment, which compared ERP responses to highly expected words that were placed either in a MWE or a regular non-fixed compositional context, and to low predictability controls. We focused on oscillatory dynamics and regression analyses, in order to dissociate between the two contexts by modeling the electrophysiological response as a function of item-level parameters. A significant interaction between word position and condition was found in the regression model for power in a theta range (~7–9 Hz), providing evidence for the presence of qualitative differences between conditions. Power levels within this band were lower for MWE than compositional contexts when the target word appeared later on in the sentence, confirming that in the former lexical retrieval would have taken place before word onset. On the other hand, gamma-power (~50–70 Hz) was also modulated by predictability of the item in all conditions, which is interpreted as an index of a similar “matching” sub-step for both types of contexts, binding an expected representation and the external input. PMID:25161630

Major urinary protein (MUP) profiles show dynamic changes rather than individual ‘barcode’ signatures

PubMed Central

Thoß, M.; Luzynski, K.C.; Ante, M.; Miller, I.; Penn, D.J.

2016-01-01

House mice (Mus musculus) produce a variable number of major urinary proteins (MUPs), and studies suggest that each individual produces a unique MUP profile that provides a distinctive odor signature controlling individual and kin recognition. This ‘barcode hypothesis’ requires that MUP urinary profiles show high individual variability within populations and also high individual consistency over time, but tests of these assumptions are lacking. We analyzed urinary MUP profiles of 66 wild-caught house mice from eight populations using isoelectric focusing. We found that MUP profiles of wild male house mice are not individually unique, and though they were highly variable, closer inspection revealed that the variation strongly depended on MUP band type. The prominent (‘major) bands were surprisingly homogenous (and hence most MUPs are not polymorphic), but we also found inconspicuous (‘minor’) bands that were highly variable and therefore potential candidates for individual fingerprints. We also examined changes in urinary MUP profiles of 58 males over time (from 6 to 24 weeks of age), and found that individual MUP profiles and MUP concentration were surprisingly dynamic, and showed significant changes after puberty and during adulthood. Contrary to what we expected, however, the minor bands were the most variable over time, thus no good candidates for individual fingerprints. Although MUP profiles do not provide individual fingerprints, we found that MUP profiles were more similar among siblings than non-kin despite considerable fluctuation. Our findings show that MUP profiles are not highly stable over time, they do not show strong individual clustering, and thus challenge the barcode hypothesis. Within-individual dynamics of MUP profiles indicate a different function of MUPs in individual recognition than previously assumed and advocate an alternative hypothesis (‘dynamic changes’ hypothesis). PMID:26973837

Long-Term and Seasonal Dynamics of Dengue in Iquitos, Peru

PubMed Central

Stoddard, Steven T.; Wearing, Helen J.; Reiner, Robert C.; Morrison, Amy C.; Astete, Helvio; Vilcarromero, Stalin; Alvarez, Carlos; Ramal-Asayag, Cesar; Sihuincha, Moises; Rocha, Claudio; Halsey, Eric S.; Scott, Thomas W.; Kochel, Tadeusz J.; Forshey, Brett M.

2014-01-01

Introduction Long-term disease surveillance data provide a basis for studying drivers of pathogen transmission dynamics. Dengue is a mosquito-borne disease caused by four distinct, but related, viruses (DENV-1-4) that potentially affect over half the world's population. Dengue incidence varies seasonally and on longer time scales, presumably driven by the interaction of climate and host susceptibility. Precise understanding of dengue dynamics is constrained, however, by the relative paucity of laboratory-confirmed longitudinal data. Methods We studied 10 years (2000–2010) of laboratory-confirmed, clinic-based surveillance data collected in Iquitos, Peru. We characterized inter and intra-annual patterns of dengue dynamics on a weekly time scale using wavelet analysis. We explored the relationships of case counts to climatic variables with cross-correlation maps on annual and trimester bases. Findings Transmission was dominated by single serotypes, first DENV-3 (2001–2007) then DENV-4 (2008–2010). After 2003, incidence fluctuated inter-annually with outbreaks usually occurring between October and April. We detected a strong positive autocorrelation in case counts at a lag of ∼70 weeks, indicating a shift in the timing of peak incidence year-to-year. All climatic variables showed modest seasonality and correlated weakly with the number of reported dengue cases across a range of time lags. Cases were reduced after citywide insecticide fumigation if conducted early in the transmission season. Conclusions Dengue case counts peaked seasonally despite limited intra-annual variation in climate conditions. Contrary to expectations for this mosquito-borne disease, no climatic variable considered exhibited a strong relationship with transmission. Vector control operations did, however, appear to have a significant impact on transmission some years. Our results indicate that a complicated interplay of factors underlie DENV transmission in contexts such as Iquitos. PMID:25033412

Major urinary protein (MUP) profiles show dynamic changes rather than individual 'barcode' signatures.

PubMed

Thoß, M; Luzynski, K C; Ante, M; Miller, I; Penn, D J

2015-06-30

House mice ( Mus musculus) produce a variable number of major urinary proteins (MUPs), and studies suggest that each individual produces a unique MUP profile that provides a distinctive odor signature controlling individual and kin recognition. This 'barcode hypothesis' requires that MUP urinary profiles show high individual variability within populations and also high individual consistency over time, but tests of these assumptions are lacking. We analyzed urinary MUP profiles of 66 wild-caught house mice from eight populations using isoelectric focusing. We found that MUP profiles of wild male house mice are not individually unique, and though they were highly variable, closer inspection revealed that the variation strongly depended on MUP band type. The prominent ('major) bands were surprisingly homogenous (and hence most MUPs are not polymorphic), but we also found inconspicuous ('minor') bands that were highly variable and therefore potential candidates for individual fingerprints. We also examined changes in urinary MUP profiles of 58 males over time (from 6 to 24 weeks of age), and found that individual MUP profiles and MUP concentration were surprisingly dynamic, and showed significant changes after puberty and during adulthood. Contrary to what we expected, however, the minor bands were the most variable over time, thus no good candidates for individual fingerprints. Although MUP profiles do not provide individual fingerprints, we found that MUP profiles were more similar among siblings than non-kin despite considerable fluctuation. Our findings show that MUP profiles are not highly stable over time, they do not show strong individual clustering, and thus challenge the barcode hypothesis. Within-individual dynamics of MUP profiles indicate a different function of MUPs in individual recognition than previously assumed and advocate an alternative hypothesis ('dynamic changes' hypothesis).

76 FR 30422 - Agency Information Collection Activities: Request for Comments for a New Information Collection

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-25

... HOV lanes. These naturally occurring dynamic ridesharing systems operate by having drivers and riders... Houston, TX) to study the informal, dynamic carpooling systems in each city. The government expects the... (EAR) Program initial stage research on the topic of Dynamic Ridesharing. Background: The Exploratory...

Dynamic Response Testing in an Electrically Heated Reactor Test Facility

NASA Astrophysics Data System (ADS)

Bragg-Sitton, Shannon M.; Morton, T. J.

2006-01-01

Non-nuclear testing can be a valuable tool in the development of a space nuclear power or propulsion system. In a non-nuclear test bed, electric heaters are used to simulate the heat from nuclear fuel. Standard testing allows one to fully assess thermal, heat transfer, and stress related attributes of a given system, but fails to demonstrate the dynamic response that would be present in an integrated, fueled reactor system. The integration of thermal hydraulic hardware tests with simulated neutronic response provides a bridge between electrically heated testing and fueled nuclear testing. By implementing a neutronic response model to simulate the dynamic response that would be expected in a fueled reactor system, one can better understand system integration issues, characterize integrated system response times and response characteristics, and assess potential design improvements at a relatively small fiscal investment. Initial system dynamic response testing was demonstrated on the integrated SAFE-100a heat pipe (HP) cooled, electrically heated reactor and heat exchanger hardware, utilizing a one-group solution to the point kinetics equations to simulate the expected neutronic response of the system. Reactivity feedback calculations were then based on a bulk reactivity feedback coefficient and measured average core temperature. This paper presents preliminary results from similar dynamic testing of a direct drive gas cooled reactor system (DDG), demonstrating the applicability of the testing methodology to any reactor type and demonstrating the variation in system response characteristics in different reactor concepts. Although the HP and DDG designs both utilize a fast spectrum reactor, the method of cooling the reactor differs significantly, leading to a variable system response that can be demonstrated and assessed in a non-nuclear test facility. Planned system upgrades to allow implementation of higher fidelity dynamic testing are also discussed. Proposed DDG testing will utilize a higher fidelity point kinetics model to control core power transients, and reactivity feedback will be based on localized feedback coefficients and several independent temperature measurements taken within the core block. This paper presents preliminary test results and discusses the methodology that will be implemented in follow-on DDG testing and the additional instrumentation required to implement high fidelity dynamic testing.

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

PubMed Central

2013-01-01

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

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

PubMed

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

2013-10-02

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

Grip Force Adjustments Reflect Prediction of Dynamic Consequences in Varying Gravitoinertial Fields

PubMed Central

White, Olivier; Thonnard, Jean-Louis; Lefèvre, Philippe; Hermsdörfer, Joachim

2018-01-01

Humans have a remarkable ability to adjust the way they manipulate tools through a genuine regulation of grip force according to the task. However, rapid changes in the dynamical context may challenge this skill, as shown in many experimental approaches. Most experiments adopt perturbation paradigms that affect only one sensory modality. We hypothesize that very fast adaptation can occur if coherent information from multiple sensory modalities is provided to the central nervous system. Here, we test whether participants can switch between different and never experienced dynamical environments induced by centrifugation of the body. Seven participants lifted an object four times in a row successively in 1, 1.5, 2, 2.5, 2, 1.5, and 1 g. We continuously measured grip force, load force and the gravitoinertial acceleration that was aligned with body axis (perceived gravity). Participants adopted stereotyped grasping movements immediately upon entry in a new environment and needed only one trial to adapt grip forces to a stable performance in each new gravity environment. This result was underlined by good correlations between grip and load forces in the first trial. Participants predictively applied larger grip forces when they expected increasing gravity steps. They also decreased grip force when they expected decreasing gravity steps, but not as much as they could, indicating imperfect anticipation in that condition. The participants' performance could rather be explained by a combination of successful scaling of grip force according to gravity changes and a separate safety factor. The data suggest that in highly unfamiliar dynamic environments, grip force regulation is characterized by a combination of a successful anticipation of the experienced environmental condition, a safety factor reflecting strategic response to uncertainties about the environment and rapid feedback mechanisms to optimize performance under constant conditions. PMID:29527176

Odour-impact assessment around a landfill site from weather-type classification, complaint inventory and numerical simulation.

PubMed

Chemel, C; Riesenmey, C; Batton-Hubert, M; Vaillant, H

2012-01-01

Gases released from landfill sites into the atmosphere have the potential to cause olfactory nuisances within the surrounding communities. Landfill sites are often located over complex topography for convenience mainly related to waste disposal and environmental masking. Dispersion of odours is strongly conditioned by local atmospheric dynamics. Assessment of odour impacts needs to take into account the variability of local atmospheric dynamics. In this study, we discuss a method to assess odour impacts around a landfill site located over complex terrain in order to provide information to be used subsequently to identify management strategies to reduce olfactory nuisances in the residential neighbourhoods. A weather-type classification is defined in order to identify meteorological conditions under which olfactory nuisances are to be expected. A non-steady state Gaussian model and a full-physics meteorological model are used to predict olfactory nuisances, for both the winter and summer scenarios that lead to the majority of complaints in neighbourhoods surrounding the landfill site. Simulating representative scenarios rather than full years make a high resolution simulation of local atmospheric dynamics in space and time possible. Results underline the key role of local atmospheric dynamics in driving the dispersion of odours. The odour concentration simulated by the full-physics meteorological model is combined with the density of the population in order to calculate an average population exposure for the two scenarios. Results of this study are expected to provide helpful information to develop technical solutions for an effective management of landfill operations, which would reduce odour impacts within the surrounding communities. Copyright © 2011 Elsevier Ltd. All rights reserved.

Influence of periodic external fields in multiagent models with language dynamics

NASA Astrophysics Data System (ADS)

Palombi, Filippo; Ferriani, Stefano; Toti, Simona

2017-12-01

We investigate large-scale effects induced by external fields, phenomenologically interpreted as mass media, in multiagent models evolving with the microscopic dynamics of the binary naming game. In particular, we show that a single external field, broadcasting information at regular time intervals, can reverse the majority opinion of the population, provided the frequency and the effectiveness of the sent messages lie above well-defined thresholds. We study the phase structure of the model in the mean field approximation and in numerical simulations with several network topologies. We also investigate the influence on the agent dynamics of two competing external fields, periodically broadcasting different messages. In finite regions of the parameter space we observe periodic equilibrium states in which the average opinion densities are reversed with respect to naive expectations. Such equilibria occur in two cases: (i) when the frequencies of the competing messages are different but close to each other; (ii) when the frequencies are equal and the relative time shift of the messages does not exceed half a period. We interpret the observed phenomena as a result of the interplay between the external fields and the internal dynamics of the agents and conclude that, depending on the model parameters, the naming game is consistent with scenarios of first- or second-mover advantage (to borrow an expression from the jargon of business strategy).

Dynamic glucose enhanced (DGE) MRI for combined imaging of blood-brain barrier break down and increased blood volume in brain cancer.

PubMed

Xu, Xiang; Chan, Kannie W Y; Knutsson, Linda; Artemov, Dmitri; Xu, Jiadi; Liu, Guanshu; Kato, Yoshinori; Lal, Bachchu; Laterra, John; McMahon, Michael T; van Zijl, Peter C M

2015-12-01

Recently, natural d-glucose was suggested as a potential biodegradable contrast agent. The feasibility of using d-glucose for dynamic perfusion imaging was explored to detect malignant brain tumors based on blood brain barrier breakdown. Mice were inoculated orthotopically with human U87-EGFRvIII glioma cells. Time-resolved glucose signal changes were detected using chemical exchange saturation transfer (glucoCEST) MRI. Dynamic glucose enhanced (DGE) MRI was used to measure tissue response to an intravenous bolus of d-glucose. DGE images of mouse brains bearing human glioma showed two times higher and persistent changes in tumor compared with contralateral brain. Area-under-curve (AUC) analysis of DGE delineated blood vessels and tumor and had contrast comparable to the AUC determined using dynamic contrast enhanced (DCE) MRI with GdDTPA, both showing a significantly higher AUC in tumor than in brain (P < 0.005). Both CEST and relaxation effects contribute to the signal change. DGE MRI is a feasible technique for studying brain tumor enhancement reflecting differences in tumor blood volume and permeability with respect to normal brain. We expect DGE will provide a low-risk and less expensive alternative to DCE MRI for imaging cancer in vulnerable populations, such as children and patients with renal impairment. © 2015 Wiley Periodicals, Inc.

Dynamic Glucose Enhanced (DGE) MRI for Combined Imaging of Blood Brain Barrier Break Down and Increased Blood Volume in Brain Cancer

PubMed Central

Xu, Xiang; Chan, Kannie WY; Knutsson, Linda; Artemov, Dmitri; Xu, Jiadi; Liu, Guanshu; Kato, Yoshinori; Lal, Bachchu; Laterra, John; McMahon, Michael T.; van Zijl, Peter C.M.

2015-01-01

Purpose Recently, natural d-glucose was suggested as a potential biodegradable contrast agent. The feasibility of using d-glucose for dynamic perfusion imaging was explored to detect malignant brain tumors based on blood brain barrier breakdown. Methods Mice were inoculated orthotopically with human U87-EGFRvIII glioma cells. Time-resolved glucose signal changes were detected using chemical exchange saturation transfer (glucoCEST) MRI. Dynamic glucose enhanced (DGE) MRI was used to measure tissue response to an intravenous bolus of d-glucose. Results DGE images of mouse brains bearing human glioma showed two times higher and persistent changes in tumor compared to contralateral brain. Area-under-curve (AUC) analysis of DGE delineated blood vessels and tumor and had contrast comparable to the AUC determined using dynamic contrast enhanced (DCE) MRI with GdDTPA, both showing a significantly higher AUC in tumor than in brain (p<0.005). Both CEST and relaxation effects contribute to the signal change. Conclusion DGE MRI is a feasible technique for studying brain tumor enhancement reflecting differences in tumor blood volume and permeability with respect to normal brain. We expect DGE will provide a low-risk and less expensive alternative to DCE MRI for imaging cancer in vulnerable populations, such as children and patients with renal impairment. PMID:26404120

Zero-Point Energy Constraint for Unimolecular Dissociation Reactions. Giving Trajectories Multiple Chances To Dissociate Correctly.

PubMed

Paul, Amit K; Hase, William L

2016-01-28

A zero-point energy (ZPE) constraint model is proposed for classical trajectory simulations of unimolecular decomposition and applied to CH4* → H + CH3 decomposition. With this model trajectories are not allowed to dissociate unless they have ZPE in the CH3 product. If not, they are returned to the CH4* region of phase space and, if necessary, given additional opportunities to dissociate with ZPE. The lifetime for dissociation of an individual trajectory is the time it takes to dissociate with ZPE in CH3, including multiple possible returns to CH4*. With this ZPE constraint the dissociation of CH4* is exponential in time as expected for intrinsic RRKM dynamics and the resulting rate constant is in good agreement with the harmonic quantum value of RRKM theory. In contrast, a model that discards trajectories without ZPE in the reaction products gives a CH4* → H + CH3 rate constant that agrees with the classical and not quantum RRKM value. The rate constant for the purely classical simulation indicates that anharmonicity may be important and the rate constant from the ZPE constrained classical trajectory simulation may not represent the complete anharmonicity of the RRKM quantum dynamics. The ZPE constraint model proposed here is compared with previous models for restricting ZPE flow in intramolecular dynamics, and connecting product and reactant/product quantum energy levels in chemical dynamics simulations.

What goes up must . . . Keep going up? Cultural differences in cognitive styles influence evaluations of dynamic performance.

PubMed

Ferris, D Lance; Reb, Jochen; Lian, Huiwen; Sim, Samantha; Ang, Dionysius

2018-03-01

Past research on dynamic workplace performance evaluation has taken as axiomatic that temporal performance trends produce naïve extrapolation effects on performance ratings. That is, we naïvely assume that an individual whose performance has trended upward over time will continue to improve, and rate that individual more positively than an individual whose performance has trended downward over time-even if, on average, the 2 individuals have performed at an equivalent level. However, we argue that such naïve extrapolation effects are more pronounced in Western countries than Eastern countries, owing to Eastern countries having a more holistic cognitive style. To test our hypotheses, we examined the effect of performance trend on expectations of future performance and ratings of past performance across 2 studies: Study 1 compares the magnitude of naïve extrapolation effects among Singaporeans primed with either a more or less holistic cognitive style, and Study 2 examines holistic cognitive style as a mediating mechanism accounting for differences in the magnitude of naïve extrapolation effects between American and Chinese raters. Across both studies, we found support for our predictions that dynamic performance trends have less impact on the ratings of more holistic thinkers. Implications for the dynamic performance and naïve extrapolation literatures are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Dynamics of correlation-frozen antinodal quasiparticles in superconducting cuprates

PubMed Central

Cilento, Federico; Manzoni, Giulia; Sterzi, Andrea; Peli, Simone; Ronchi, Andrea; Crepaldi, Alberto; Boschini, Fabio; Cacho, Cephise; Chapman, Richard; Springate, Emma; Eisaki, Hiroshi; Greven, Martin; Berciu, Mona; Kemper, Alexander F.; Damascelli, Andrea; Capone, Massimo; Giannetti, Claudio; Parmigiani, Fulvio

2018-01-01

Many puzzling properties of high–critical temperature (Tc) superconducting (HTSC) copper oxides have deep roots in the nature of the antinodal quasiparticles, the elementary excitations with wave vector parallel to the Cu–O bonds. These electronic states are most affected by the onset of antiferromagnetic correlations and charge instabilities, and they host the maximum of the anisotropic superconducting gap and pseudogap. We use time-resolved extreme-ultraviolet photoemission with proper photon energy (18 eV) and time resolution (50 fs) to disclose the ultrafast dynamics of the antinodal states in a prototypical HTSC cuprate. After photoinducing a nonthermal charge redistribution within the Cu and O orbitals, we reveal a dramatic momentum-space differentiation of the transient electron dynamics. Whereas the nodal quasiparticle distribution is heated up as in a conventional metal, new quasiparticle states transiently emerge at the antinodes, similarly to what is expected for a photoexcited Mott insulator, where the frozen charges can be released by an impulsive excitation. This transient antinodal metallicity is mapped into the dynamics of the O-2p bands, thus directly demonstrating the intertwining between the low- and high-energy scales that is typical of correlated materials. Our results suggest that the correlation-driven freezing of the electrons moving along the Cu–O bonds, analogous to the Mott localization mechanism, constitutes the starting point for any model of high-Tc superconductivity and other exotic phases of HTSC cuprates. PMID:29507885

Normative evidence accumulation in unpredictable environments

PubMed Central

Glaze, Christopher M; Kable, Joseph W; Gold, Joshua I

2015-01-01

In our dynamic world, decisions about noisy stimuli can require temporal accumulation of evidence to identify steady signals, differentiation to detect unpredictable changes in those signals, or both. Normative models can account for learning in these environments but have not yet been applied to faster decision processes. We present a novel, normative formulation of adaptive learning models that forms decisions by acting as a leaky accumulator with non-absorbing bounds. These dynamics, derived for both discrete and continuous cases, depend on the expected rate of change of the statistics of the evidence and balance signal identification and change detection. We found that, for two different tasks, human subjects learned these expectations, albeit imperfectly, then used them to make decisions in accordance with the normative model. The results represent a unified, empirically supported account of decision-making in unpredictable environments that provides new insights into the expectation-driven dynamics of the underlying neural signals. DOI: http://dx.doi.org/10.7554/eLife.08825.001 PMID:26322383

Dynamics of Individual cilia to external loading- A simple one dimensional picture

NASA Astrophysics Data System (ADS)

Swaminathan, Vinay; Hill, David; Superfine, R.

2008-10-01

From being called the cellular janitors to swinging debauchers, cilia have captured the fascinations of researchers for over 200 years. In cystic fibrosis and chronic obstructive pulmonary disease where the cilia loses it's function, the protective mucus layer in the lung thickens and mucociliary clearance breaks down, leading to inflammation along the airways and an increased rate of infection. The mechanistic understanding of mucus clearance depends on a quantitative assessment of the axoneme dynamics and the maximum force the cilia are capable of generating and imparting to the mucus layer. Similar to the situation in molecular motors, detailed quantitative measurements of dynamics under applied load conditions are expected to be essential in developing predictive models. Based on our measurements of the dynamics of individual ciliary motion in the human bronchial epithelial cell under the application of an applied load, we present a simple one dimensional model for the axoneme dynamics and quantify the axoneme stiffness, the internal force generated by the axoneme, the stall force and show how the dynamics sheds insight on the time dependence of the internal force generation. The internal force generated by the axoneme is related to the ability of cilia to propel fluids and to their potential role in force sensing.

An information-theoretic approach to assess practical identifiability of parametric dynamical systems.

PubMed

Pant, Sanjay; Lombardi, Damiano

2015-10-01

A new approach for assessing parameter identifiability of dynamical systems in a Bayesian setting is presented. The concept of Shannon entropy is employed to measure the inherent uncertainty in the parameters. The expected reduction in this uncertainty is seen as the amount of information one expects to gain about the parameters due to the availability of noisy measurements of the dynamical system. Such expected information gain is interpreted in terms of the variance of a hypothetical measurement device that can measure the parameters directly, and is related to practical identifiability of the parameters. If the individual parameters are unidentifiable, correlation between parameter combinations is assessed through conditional mutual information to determine which sets of parameters can be identified together. The information theoretic quantities of entropy and information are evaluated numerically through a combination of Monte Carlo and k-nearest neighbour methods in a non-parametric fashion. Unlike many methods to evaluate identifiability proposed in the literature, the proposed approach takes the measurement-noise into account and is not restricted to any particular noise-structure. Whilst computationally intensive for large dynamical systems, it is easily parallelisable and is non-intrusive as it does not necessitate re-writing of the numerical solvers of the dynamical system. The application of such an approach is presented for a variety of dynamical systems--ranging from systems governed by ordinary differential equations to partial differential equations--and, where possible, validated against results previously published in the literature. Copyright © 2015 Elsevier Inc. All rights reserved.

Quantum dynamics of a particle with a spin-dependent velocity

NASA Astrophysics Data System (ADS)

Aslangul, Claude

2005-01-01

We study the dynamics of a particle in continuous time and space, the displacement of which is governed by an internal degree of freedom (spin). In one definite limit, the so-called quantum random walk is recovered but, although quite simple, the model possesses a rich variety of dynamics and goes far beyond this problem. Generally speaking, our framework can describe the motion of an electron in a magnetic sea near the Fermi level when linearization of the dispersion law is possible, coupled to a transverse magnetic field. Quite unexpected behaviours are obtained. In particular, we find that when the initial wave packet is fully localized in space, the Jz angular momentum component is frozen; this is an interesting example of an observable which, although it is not a constant of motion, has a constant expectation value. For a non-completely localized wave packet, the effect still occurs although less pronounced, and the spin keeps for ever memory of its initial state. Generally speaking, as time goes on, the spatial density profile looks rather complex, as a consequence of the competition between drift and precession, and displays various shapes according to the ratio between the Larmor period and the characteristic time of flight. The density profile gradually changes from a multimodal quickly moving distribution when the scattering rate is small, to a unimodal standing but flattening distribution in the opposite case.

A Regularized Linear Dynamical System Framework for Multivariate Time Series Analysis.

PubMed

Liu, Zitao; Hauskrecht, Milos

2015-01-01

Linear Dynamical System (LDS) is an elegant mathematical framework for modeling and learning Multivariate Time Series (MTS). However, in general, it is difficult to set the dimension of an LDS's hidden state space. A small number of hidden states may not be able to model the complexities of a MTS, while a large number of hidden states can lead to overfitting. In this paper, we study learning methods that impose various regularization penalties on the transition matrix of the LDS model and propose a regularized LDS learning framework (rLDS) which aims to (1) automatically shut down LDSs' spurious and unnecessary dimensions, and consequently, address the problem of choosing the optimal number of hidden states; (2) prevent the overfitting problem given a small amount of MTS data; and (3) support accurate MTS forecasting. To learn the regularized LDS from data we incorporate a second order cone program and a generalized gradient descent method into the Maximum a Posteriori framework and use Expectation Maximization to obtain a low-rank transition matrix of the LDS model. We propose two priors for modeling the matrix which lead to two instances of our rLDS. We show that our rLDS is able to recover well the intrinsic dimensionality of the time series dynamics and it improves the predictive performance when compared to baselines on both synthetic and real-world MTS datasets.

Simulations of Gamma-Ray Burst Jets in a Stratified External Medium: Dynamics, Afterglow Light Curves, Jet Breaks, and Radio Calorimetry

NASA Astrophysics Data System (ADS)

De Colle, Fabio; Ramirez-Ruiz, Enrico; Granot, Jonathan; Lopez-Camara, Diego

2012-05-01

The dynamics of gamma-ray burst (GRB) jets during the afterglow phase is most reliably and accurately modeled using hydrodynamic simulations. All published simulations so far, however, have considered only a uniform external medium, while a stratified external medium is expected around long duration GRB progenitors. Here, we present simulations of the dynamics of GRB jets and the resulting afterglow emission for both uniform and stratified external media with ρextvpropr -k for k = 0, 1, 2. The simulations are performed in two dimensions using the special relativistic version of the Mezcal code. Common to all calculations is the initiation of the GRB jet as a conical wedge of half-opening angle θ0 = 0.2 whose radial profile is taken from the self-similar Blandford-McKee solution. The dynamics for stratified external media (k = 1, 2) are broadly similar to those derived for expansion into a uniform external medium (k = 0). The jet half-opening angle is observed to start increasing logarithmically with time (or radius) once the Lorentz factor Γ drops below θ-1 0. For larger k values, however, the lateral expansion is faster at early times (when Γ > θ-1 0) and slower at late times with the jet expansion becoming Newtonian and slowly approaching spherical symmetry over progressively longer timescales. We find that, contrary to analytic expectations, there is a reasonably sharp jet break in the light curve for k = 2 (a wind-like external medium), although the shape of the break is affected more by the viewing angle (for θobs <= θ0) than by the slope of the external density profile (for 0 <= k <= 2). Steeper density profiles (i.e., increasing k values) are found to produce more gradual jet breaks while larger viewing angles cause smoother and later appearing jet breaks. The counterjet becomes visible as it becomes sub-relativistic, and for k = 0 this results in a clear bump-like feature in the light curve. However, for larger k values the jet decelerates more gradually, causing only a mild flattening in the radio light curve that might be hard to discern when k = 2. Late-time radio calorimetry, which makes use of a spherical flow approximation near the non-relativistic transition, is likely to consistently overestimate the true energy by up to a factor of a few for k = 2, but likely to either overpredict or underpredict it by a smaller factor for k = 0, 1.

Uncertainty analysis as essential step in the establishment of the dynamic Design Space of primary drying during freeze-drying.

PubMed

Mortier, Séverine Thérèse F C; Van Bockstal, Pieter-Jan; Corver, Jos; Nopens, Ingmar; Gernaey, Krist V; De Beer, Thomas

2016-06-01

Large molecules, such as biopharmaceuticals, are considered the key driver of growth for the pharmaceutical industry. Freeze-drying is the preferred way to stabilise these products when needed. However, it is an expensive, inefficient, time- and energy-consuming process. During freeze-drying, there are only two main process variables to be set, i.e. the shelf temperature and the chamber pressure, however preferably in a dynamic way. This manuscript focuses on the essential use of uncertainty analysis for the determination and experimental verification of the dynamic primary drying Design Space for pharmaceutical freeze-drying. Traditionally, the chamber pressure and shelf temperature are kept constant during primary drying, leading to less optimal process conditions. In this paper it is demonstrated how a mechanistic model of the primary drying step gives the opportunity to determine the optimal dynamic values for both process variables during processing, resulting in a dynamic Design Space with a well-known risk of failure. This allows running the primary drying process step as time efficient as possible, hereby guaranteeing that the temperature at the sublimation front does not exceed the collapse temperature. The Design Space is the multidimensional combination and interaction of input variables and process parameters leading to the expected product specifications with a controlled (i.e., high) probability. Therefore, inclusion of parameter uncertainty is an essential part in the definition of the Design Space, although it is often neglected. To quantitatively assess the inherent uncertainty on the parameters of the mechanistic model, an uncertainty analysis was performed to establish the borders of the dynamic Design Space, i.e. a time-varying shelf temperature and chamber pressure, associated with a specific risk of failure. A risk of failure acceptance level of 0.01%, i.e. a 'zero-failure' situation, results in an increased primary drying process time compared to the deterministic dynamic Design Space; however, the risk of failure is under control. Experimental verification revealed that only a risk of failure acceptance level of 0.01% yielded a guaranteed zero-defect quality end-product. The computed process settings with a risk of failure acceptance level of 0.01% resulted in a decrease of more than half of the primary drying time in comparison with a regular, conservative cycle with fixed settings. Copyright © 2016. Published by Elsevier B.V.

Response of GaAs charge storage devices to transient ionizing radiation

NASA Astrophysics Data System (ADS)

Hetherington, D. L.; Klem, J. F.; Hughes, R. C.; Weaver, H. T.

Charge storage devices in which non-equilibrium depletion regions represent stored charge are sensitive to ionizing radiation. This results since the radiation generates electron-hole pairs that neutralize excess ionized dopant charge. Silicon structures, such as dynamic RAM or CCD cells are particularly sensitive to radiation since carrier diffusion lengths in this material are often much longer than the depletion width, allowing collection of significant quantities of charge from quasi-neutral sections of the device. For GaAs the situation is somewhat different in that minority carrier diffusion lengths are shorter than in silicon, and although mobilities are higher, we expect a reduction of radiation sensitivity as suggested by observations of reduced quantum efficiency in GaAs solar cells. Dynamic memory cells in GaAs have potential increased retention times. In this paper, we report the response of a novel GaAs dynamic memory element to transient ionizing radiation. The charge readout technique is nondestructive over a reasonable applied voltage range and is more sensitive to stored charge than a simple capacitor.

[Effect of maternal death on family dynamics and infant survival].

PubMed

Reyes Frausto, S; Bobadilla Fernández, J L; Karchmer Krivitzky, S; Martínez González, L

1998-10-01

Family adjustments, which are generated by a maternal death, have been analysed previously in Mexico by using a reduced number of cases in rural areas. This study was design in order to establish changes in family dynamic generated b y a maternal death and to analyse child surviving after one year of birth. Family members of maternal deaths cases, which occurred during 1988-89 in the Federal District, were interviewed by first time in order to know information related to family dynamic and women's characteristics. A second interview was made after one year of birth for cases in which the newborn survived hospital discharge. Simple frequencies were calculated and using X2 test compared groups. Main consequences were family disintegration, child acquiring new roles and economic problems when woman was the main or the only one support of the family. Child surviving was higher than we expected considering other national or international reports. Children were mainly integrated to their grandparent's family.

Distributed Energy Resources and Dynamic Microgrid: An Integrated Assessment

NASA Astrophysics Data System (ADS)

Shang, Duo Rick

The overall goal of this thesis is to improve understanding in terms of the benefit of DERs to both utility and to electricity end-users when integrated in power distribution system. To achieve this goal, a series of two studies was conducted to assess the value of DERs when integrated with new power paradigms. First, the arbitrage value of DERs was examined in markets with time-variant electricity pricing rates (e.g., time of use, real time pricing) under a smart grid distribution paradigm. This study uses a stochastic optimization model to estimate the potential profit from electricity price arbitrage over a five-year period. The optimization process involves two types of PHEVs (PHEV-10, and PHEV-40) under three scenarios with different assumptions on technology performance, electricity market and PHEV owner types. The simulation results indicate that expected arbitrage profit is not a viable option to engage PHEVs in dispatching and in providing ancillary services without more favorable policy and PHEV battery technologies. Subsidy or change in electricity tariff or both are needed. Second, it examined the concept of dynamic microgrid as a measure to improve distribution resilience, and estimates the prices of this emerging service. An economic load dispatch (ELD) model is developed to estimate the market-clearing price in a hypothetical community with single bid auction electricity market. The results show that the electricity market clearing price on the dynamic microgrid is predominantly decided by power output and cost of electricity of each type of DGs. At circumstances where CHP is the only source, the electricity market clearing price in the island is even cheaper than the on-grid electricity price at normal times. Integration of PHEVs in the dynamic microgrid will increase electricity market clearing prices. It demonstrates that dynamic microgrid is an economically viable alternative to enhance grid resilience.

Interchain coupled chain dynamics of poly(ethylene oxide) in blends with poly(methyl methacrylate): coupling model analysis.

PubMed

Ngai, K L; Wang, Li-Min

2011-11-21

Quasielastic neutron scattering and molecular dynamics simulation data from poly(ethylene oxide) (PEO)/poly(methyl methacrylate) (PMMA) blends found that for short times the self-dynamics of PEO chain follows the Rouse model, but at longer times past t(c) = 1-2 ns it becomes slower and departs from the Rouse model in dependences on time, momentum transfer, and temperature. To explain the anomalies, others had proposed the random Rouse model (RRM) in which each monomer has different mobility taken from a broad log-normal distribution. Despite the success of the RRM, Diddens et al. [Eur. Phys. Lett. 95, 56003 (2011)] extracted the distribution of friction coefficients from the MD simulations of a PEO/PMMA blend and found that the distribution is much narrower than expected from the RRM. We propose a simpler alternative explanation of the data by utilizing alone the observed crossover of PEO chain dynamics at t(c). The present problem is just a special case of a general property of relaxation in interacting systems, which is the crossover from independent relaxation to coupled many-body relaxation at some t(c) determined by the interaction potential and intermolecular coupling/constraints. The generality is brought out vividly by pointing out that the crossover also had been observed by neutron scattering from entangled chains relaxation in monodisperse homopolymers, and from the segmental α-relaxation of PEO in blends with PMMA. The properties of all the relaxation processes in connection with the crossover are similar, despite the length scales of the relaxation in these systems are widely different.

Interchain coupled chain dynamics of poly(ethylene oxide) in blends with poly(methyl methacrylate): Coupling model analysis

NASA Astrophysics Data System (ADS)

Ngai, K. L.; Wang, Li-Min

2011-11-01

Quasielastic neutron scattering and molecular dynamics simulation data from poly(ethylene oxide) (PEO)/poly(methyl methacrylate) (PMMA) blends found that for short times the self-dynamics of PEO chain follows the Rouse model, but at longer times past tc = 1-2 ns it becomes slower and departs from the Rouse model in dependences on time, momentum transfer, and temperature. To explain the anomalies, others had proposed the random Rouse model (RRM) in which each monomer has different mobility taken from a broad log-normal distribution. Despite the success of the RRM, Diddens et al. [Eur. Phys. Lett. 95, 56003 (2011)] extracted the distribution of friction coefficients from the MD simulations of a PEO/PMMA blend and found that the distribution is much narrower than expected from the RRM. We propose a simpler alternative explanation of the data by utilizing alone the observed crossover of PEO chain dynamics at tc. The present problem is just a special case of a general property of relaxation in interacting systems, which is the crossover from independent relaxation to coupled many-body relaxation at some tc determined by the interaction potential and intermolecular coupling/constraints. The generality is brought out vividly by pointing out that the crossover also had been observed by neutron scattering from entangled chains relaxation in monodisperse homopolymers, and from the segmental α-relaxation of PEO in blends with PMMA. The properties of all the relaxation processes in connection with the crossover are similar, despite the length scales of the relaxation in these systems are widely different.

Many-Particle Dephasing after a Quench

NASA Astrophysics Data System (ADS)

Kiendl, Thomas; Marquardt, Florian

2017-03-01

After a quench in a quantum many-body system, expectation values tend to relax towards long-time averages. However, temporal fluctuations remain in the long-time limit, and it is crucial to study the suppression of these fluctuations with increasing system size. The particularly important case of nonintegrable models has been addressed so far only by numerics and conjectures based on analytical bounds. In this work, we are able to derive analytical predictions for the temporal fluctuations in a nonintegrable model (the transverse Ising chain with extra terms). Our results are based on identifying a dynamical regime of "many-particle dephasing," where quasiparticles do not yet relax but fluctuations are nonetheless suppressed exponentially by weak integrability breaking.

Many-Particle Dephasing after a Quench.

PubMed

Kiendl, Thomas; Marquardt, Florian

2017-03-31

After a quench in a quantum many-body system, expectation values tend to relax towards long-time averages. However, temporal fluctuations remain in the long-time limit, and it is crucial to study the suppression of these fluctuations with increasing system size. The particularly important case of nonintegrable models has been addressed so far only by numerics and conjectures based on analytical bounds. In this work, we are able to derive analytical predictions for the temporal fluctuations in a nonintegrable model (the transverse Ising chain with extra terms). Our results are based on identifying a dynamical regime of "many-particle dephasing," where quasiparticles do not yet relax but fluctuations are nonetheless suppressed exponentially by weak integrability breaking.

Finite horizon optimum control with and without a scrap value

NASA Astrophysics Data System (ADS)

Neck, R.; Blueschke-Nikolaeva, V.; Blueschke, D.

2017-06-01

In this paper, we study the effects of scrap values on the solutions of optimal control problems with finite time horizon. We show how to include a scrap value, either for the state variables or for the state and the control variables, in the OPTCON2 algorithm for the optimal control of dynamic economic systems. We ask whether the introduction of a scrap value can serve as a substitute for an infinite horizon in economic policy optimization problems where the latter option is not available. Using a simple numerical macroeconomic model, we demonstrate that the introduction of a scrap value cannot induce control policies which can be expected for problems with an infinite time horizon.

Dynamics of Acculturation, Enculturation, and Ethnic Identity: Influence of Psychocultural Constructs on Conscientiousness and Expectations of Higher Education among Latinos

ERIC Educational Resources Information Center

Cano, Miguel Angel; Castillo, Linda G.; Davis, Matthew J.; Lopez-Arenas, Araceli; Vaquero, Juana; Thompson, Keisha V.; Saldivar, Isaac M.

2012-01-01

This study investigated the influence of psychocultural variables (e.g., acculturation, enculturation, ethnic identity) and personality characteristics in relation to educational expectations among 345 Latino middle school students in the U.S. Results from a path model indicate that 24.4% of the variance of educational expectations was accounted…

Spatiotemporal heterogeneity in prey abundance and vulnerability shapes the foraging tactics of an omnivore.

PubMed

Rayl, Nathaniel D; Bastille-Rousseau, Guillaume; Organ, John F; Mumma, Matthew A; Mahoney, Shane P; Soulliere, Colleen E; Lewis, Keith P; Otto, Robert D; Murray, Dennis L; Waits, Lisette P; Fuller, Todd K

2018-05-01

Prey abundance and prey vulnerability vary across space and time, but we know little about how they mediate predator-prey interactions and predator foraging tactics. To evaluate the interplay between prey abundance, prey vulnerability and predator space use, we examined patterns of black bear (Ursus americanus) predation of caribou (Rangifer tarandus) neonates in Newfoundland, Canada using data from 317 collared individuals (9 bears, 34 adult female caribou, 274 caribou calves). During the caribou calving season, we predicted that landscape features would influence calf vulnerability to bear predation, and that bears would actively hunt calves by selecting areas associated with increased calf vulnerability. Further, we hypothesized that bears would dynamically adjust their foraging tactics in response to spatiotemporal changes in calf abundance and vulnerability (collectively, calf availability). Accordingly, we expected bears to actively hunt calves when they were most abundant and vulnerable, but switch to foraging on other resources as calf availability declined. As predicted, landscape heterogeneity influenced risk of mortality, and bears displayed the strongest selection for areas where they were most likely to kill calves, which suggested they were actively hunting caribou. Initially, the per-capita rate at which bears killed calves followed a type-I functional response, but as the calving season progressed and calf vulnerability declined, kill rates dissociated from calf abundance. In support of our hypothesis, bears adjusted their foraging tactics when they were less efficient at catching calves, highlighting the influence that predation phenology may have on predator space use. Contrary to our expectations, however, bears appeared to continue to hunt caribou as calf availability declined, but switched from a tactic of selecting areas of increased calf vulnerability to a tactic that maximized encounter rates with calves. Our results reveal that generalist predators can dynamically adjust their foraging tactics over short time-scales in response to changing prey abundance and vulnerability. Further, they demonstrate the utility of integrating temporal dynamics of prey availability into investigations of predator-prey interactions, and move towards a mechanistic understanding of the dynamic foraging tactics of a large omnivore. © 2018 The Authors. Journal of Animal Ecology © 2018 British Ecological Society.

On the expected relationships among apparent stress, static stress drop, effective shear fracture energy, and efficiency

USGS Publications Warehouse

Beeler, N.M.; Wong, T.-F.; Hickman, S.H.

2003-01-01

We consider expected relationships between apparent stress ??a and static stress drop ????s using a standard energy balance and find ??a = ????s (0.5 - ??), where ?? is stress overshoot. A simple implementation of this balance is to assume overshoot is constant; then apparent stress should vary linearly with stress drop, consistent with spectral theories (Brune, 1970) and dynamic crack models (Madariaga, 1976). Normalizing this expression by the static stress drop defines an efficiency ??sw = ??sa/????s as follows from Savage and Wood (1971). We use this measure of efficiency to analyze data from one of a number of observational studies that find apparent stress to increase with seismic moment, namely earthquakes recorded in the Cajon Pass borehole by Abercrombie (1995). Increases in apparent stress with event size could reflect an increase in seismic efficiency; however, ??sw for the Cajon earthquakes shows no such increase and is approximately constant over the entire moment range. Thus, apparent stress and stress drop co-vary, as expected from the energy balance at constant overshoot. The median value of ??sw for the Cajon earthquakes is four times lower than ??sw for laboratory events. Thus, these Cajon-recorded earthquakes have relatively low and approximately constant efficiency. As the energy balance requires ??sw = 0.5 - ??, overshoot can be estimated directly from the Savage-Wood efficiency; overshoot is positive for Cajon Pass earthquakes. Variations in apparent stress with seismic moment for these earthquakes result primarily from systematic variations in static stress drop with seismic moment and do not require a relative decrease in sliding resistance with increasing event size (dynamic weakening). Based on the comparison of field and lab determinations of the Savage-Wood efficiency, we suggest the criterion ??sw > 0.3 as a test for dynamic weakening in excess of that seen in the lab.

The Dynamic Multiprocess Framework: Evidence from Prospective Memory with Contextual Variability

PubMed Central

Scullin, Michael K.; McDaniel, Mark A.; Shelton, Jill Talley

2013-01-01

The ability to remember to execute delayed intentions is referred to as prospective memory. Previous theoretical and empirical work has focused on isolating whether a particular prospective memory task is supported either by effortful monitoring processes or by cue-driven spontaneous processes. In the present work, we advance the Dynamic Multiprocess Framework, which contends that both monitoring and spontaneous retrieval may be utilized dynamically to support prospective remembering. To capture the dynamic interplay between monitoring and spontaneous retrieval we had participants perform many ongoing tasks and told them that their prospective memory cue may occur in any context. Following either a 20-min or a 12-hr retention interval, the prospective memory cues were presented infrequently across three separate ongoing tasks. The monitoring patterns (measured as ongoing task cost relative to a between-subjects control condition) were consistent and robust across the three contexts. There was no evidence for monitoring prior to the initial prospective memory cue; however, individuals who successfully spontaneously retrieved the prospective memory intention, thereby realizing that prospective memory cues could be expected within that context, subsequently monitored. These data support the Dynamic Multiprocess Framework, which contends that individuals will engage monitoring when prospective memory cues are expected, disengage monitoring when cues are not expected, and that when monitoring is disengaged, a probabilistic spontaneous retrieval mechanism can support prospective remembering. PMID:23916951

Dissociable effects of reward and expectancy during evaluative feedback processing revealed by topographic ERP mapping analysis.

PubMed

Gheza, Davide; Paul, Katharina; Pourtois, Gilles

2017-11-24

Evaluative feedback provided during performance monitoring (PM) elicits either a positive or negative deflection ~250-300ms after its onset in the event-related potential (ERP) depending on whether the outcome is reward-related or not, as well as expected or not. However, it remains currently unclear whether these two deflections reflect a unitary process, or rather dissociable effects arising from non-overlapping brain networks. To address this question, we recorded 64-channel EEG in healthy adult participants performing a standard gambling task where valence and expectancy were manipulated in a factorial design. We analyzed the feedback-locked ERP data using a conventional ERP analysis, as well as an advanced topographic ERP mapping analysis supplemented with distributed source localization. Results reveal two main topographies showing opposing valence effects, and being differently modulated by expectancy. The first one was short-lived and sensitive to no-reward irrespective of expectancy. Source-estimation associated with this topographic map comprised mainly regions of the dorsal anterior cingulate cortex. The second one was primarily driven by reward, had a prolonged time-course and was monotonically influenced by expectancy. Moreover, this reward-related topographical map was best accounted for by intracranial generators estimated in the posterior cingulate cortex. These new findings suggest the existence of dissociable brain systems depending on feedback valence and expectancy. More generally, they inform about the added value of using topographic ERP mapping methods, besides conventional ERP measurements, to characterize qualitative changes occurring in the spatio-temporal dynamic of reward processing during PM. Copyright © 2017 Elsevier B.V. All rights reserved.

Gaia I: the Mission - the adventure begins

NASA Astrophysics Data System (ADS)

Altmann, M.

2015-10-01

The ESA Gaia satellite mission, launched on Dec. 19, 2013, will undoubtedly leave a profound impact on Galactic dynamics, revolutionising many aspects of the trade. Nine months later, with the commissioning phase over and the regular five year measuring phase of Gaia starting, it is time to give an overview of the mission, what to expect after the potential of the spacecraft has been fully assessed in situ. Moreover this paper will give a brief description of the mission as a whole, to be followed by a second contribution by Figueras (2015) focussing on Gaia science.

Experimental Observation of Two-Dimensional Anderson Localization with the Atomic Kicked Rotor.

PubMed

Manai, Isam; Clément, Jean-François; Chicireanu, Radu; Hainaut, Clément; Garreau, Jean Claude; Szriftgiser, Pascal; Delande, Dominique

2015-12-11

Dimension 2 is expected to be the lower critical dimension for Anderson localization in a time-reversal-invariant disordered quantum system. Using an atomic quasiperiodic kicked rotor-equivalent to a two-dimensional Anderson-like model-we experimentally study Anderson localization in dimension 2 and we observe localized wave function dynamics. We also show that the localization length depends exponentially on the disorder strength and anisotropy and is in quantitative agreement with the predictions of the self-consistent theory for the 2D Anderson localization.

Quench-induced Floquet topological p-wave superfluids.

PubMed

Foster, Matthew S; Gurarie, Victor; Dzero, Maxim; Yuzbashyan, Emil A

2014-08-15

Ultracold atomic gases in two dimensions tuned close to a p-wave Feshbach resonance were expected to exhibit topological superfluidity, but these were found to be experimentally unstable. We show that one can induce a topological Floquet superfluid if weakly interacting atoms are brought suddenly close ("quenched") to such a resonance, in the time before the instability kicks in. The resulting superfluid possesses Majorana edge modes, yet differs from a conventional Floquet system as it is not driven externally. Instead, the periodic modulation is self-generated by the dynamics.

Adjoint method and runaway electron avalanche

DOE PAGES

Liu, Chang; Brennan, Dylan P.; Boozer, Allen H.; ...

2016-12-16

The adjoint method for the study of runaway electron dynamics in momentum space Liu et al (2016 Phys. Plasmas 23 010702) is rederived using the Green's function method, for both the runaway probability function (RPF) and the expected loss time (ELT). The RPF and ELT obtained using the adjoint method are presented, both with and without the synchrotron radiation reaction force. In conclusion, the adjoint method is then applied to study the runaway electron avalanche. Both the critical electric field and the growth rate for the avalanche are calculated using this fast and novel approach.

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

PubMed Central

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

2014-01-01

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

Positioning navigation and timing service applications in cyber physical systems

NASA Astrophysics Data System (ADS)

Qu, Yi; Wu, Xiaojing; Zeng, Lingchuan

2017-10-01

The positioning navigation and timing (PNT) architecture was discussed in detail, whose history, evolvement, current status and future plan were presented, main technologies were listed, advantages and limitations of most technologies were compared, novel approaches were introduced, and future capacities were sketched. The concept of cyber-physical system (CPS) was described and their primary features were interpreted. Then the three-layer architecture of CPS was illustrated. Next CPS requirements on PNT services were analyzed, including requirements on position reference and time reference, requirements on temporal-spatial error monitor, requirements on dynamic services, real-time services, autonomous services, security services and standard services. Finally challenges faced by PNT applications in CPS were concluded. The conclusion was expected to facilitate PNT applications in CPS, and furthermore to provide references to the design and implementation of both architectures.

Dynamics of a magnetic active Brownian particle under a uniform magnetic field.

PubMed

Vidal-Urquiza, Glenn C; Córdova-Figueroa, Ubaldo M

2017-11-01

The dynamics of a magnetic active Brownian particle undergoing three-dimensional Brownian motion, both translation and rotation, under the influence of a uniform magnetic field is investigated. The particle self-propels at a constant speed along its magnetic dipole moment, which reorients due to the interplay between Brownian and magnetic torques, quantified by the Langevin parameter α. In this work, the time-dependent active diffusivity and the crossover time (τ^{cross})-from ballistic to diffusive regimes-are calculated through the time-dependent correlation function of the fluctuations of the propulsion direction. The results reveal that, for any value of α, the particle undergoes a directional (or ballistic) propulsive motion at very short times (t≪τ^{cross}). In this regime, the correlation function decreases linearly with time, and the active diffusivity increases with it. It the opposite time limit (t≫τ^{cross}), the particle moves in a purely diffusive regime with a correlation function that decays asymptotically to zero and an active diffusivity that reaches a constant value equal to the long-time active diffusivity of the particle. As expected in the absence of a magnetic field (α=0), the crossover time is equal to the characteristic time scale for rotational diffusion, τ_{rot}. In the presence of a magnetic field (α>0), the correlation function, the active diffusivity, and the crossover time decrease with increasing α. The magnetic field regulates the regimes of propulsion of the particle. Here, the field reduces the period of time at which the active particle undergoes a directional motion. Consequently, the active particle rapidly reaches a diffusive regime at τ^{cross}≪τ_{rot}. In the limit of weak fields (α≪1), the crossover time decreases quadratically with α, while in the limit of strong fields (α≫1) it decays asymptotically as α^{-1}. The results are in excellent agreement with those obtained by Brownian dynamics simulations.

Dynamics of a magnetic active Brownian particle under a uniform magnetic field

NASA Astrophysics Data System (ADS)

Vidal-Urquiza, Glenn C.; Córdova-Figueroa, Ubaldo M.

2017-11-01

The dynamics of a magnetic active Brownian particle undergoing three-dimensional Brownian motion, both translation and rotation, under the influence of a uniform magnetic field is investigated. The particle self-propels at a constant speed along its magnetic dipole moment, which reorients due to the interplay between Brownian and magnetic torques, quantified by the Langevin parameter α . In this work, the time-dependent active diffusivity and the crossover time (τcross)—from ballistic to diffusive regimes—are calculated through the time-dependent correlation function of the fluctuations of the propulsion direction. The results reveal that, for any value of α , the particle undergoes a directional (or ballistic) propulsive motion at very short times (t ≪τcross ). In this regime, the correlation function decreases linearly with time, and the active diffusivity increases with it. It the opposite time limit (t ≫τcross ), the particle moves in a purely diffusive regime with a correlation function that decays asymptotically to zero and an active diffusivity that reaches a constant value equal to the long-time active diffusivity of the particle. As expected in the absence of a magnetic field (α =0 ), the crossover time is equal to the characteristic time scale for rotational diffusion, τrot. In the presence of a magnetic field (α >0 ), the correlation function, the active diffusivity, and the crossover time decrease with increasing α . The magnetic field regulates the regimes of propulsion of the particle. Here, the field reduces the period of time at which the active particle undergoes a directional motion. Consequently, the active particle rapidly reaches a diffusive regime at τcross≪τrot . In the limit of weak fields (α ≪1 ), the crossover time decreases quadratically with α , while in the limit of strong fields (α ≫1 ) it decays asymptotically as α-1. The results are in excellent agreement with those obtained by Brownian dynamics simulations.

The Atlantic Meridional Overturning Circulation Stability Influenced by the Melting of the Greenland Ice Sheet under Various Warming Scenarios

NASA Astrophysics Data System (ADS)

Gierz, P.; Lohmann, G.; Wei, W.; Barbi, D.

2012-12-01

In this study, we aim to model melting processes of the Greenland ice sheet over the next 1000 years using the Earth system model COSMOS with a dynamic ice sheet module. Of primary interest is the resulting impact on the Atlantic meridional overturning circulation (GMOC/AMOC), which is expected to slow in response to a large freshwater (eg melt water) input. Six warming scenarios will be considered, one set corresponding to the IPCC's RPC Scenario 6, and another set corresponding to RPC Scenario 4.5, each time with 0.5, 1, and 2% increase of greenhouse gas concentration per year. It is expected that the freshwater input will slow down the AMOC overturning; each scenario producing a unique braking signal corresponding to how rapidly the Greenland ice sheet is forced to melt. It will be interesting to see if there is a CO2 threshold level at which the slowdown of the AMOC begins and the melting phenomena becomes unstable and positively reinforces itself or instead, as previous studies have demonstrated with a prescribed amount of melting, if the freshwater input always allows for an eventual recovery of the AMOC to a stable state regardless of the rapidity with which the salinity anomalies develop. The primary difference between this set of experiments and those in previous studies shall be the dynamic nature of the ice sheet model, as we will allow the Greenland ice sheet to melt solely based upon atmospheric conditions rather than prescribing a salinity change directly into the ocean model. It is expected that higher levels of greenhouse gases will result in more rapid melting, which in turn will have a stronger braking affect on the AMOC, possibly with longer recovery times to the starting equilibrium point. It will additionally be of interest to see if it is possible to create a shift in this equilibrium, suggesting that the rapidity with which density anomalies are introduced may create a new stable deep water formation rate. PRELIMINARY RESULTS - AMOC downwelling strength with changes in dynamically modeled Ice Sheet volume. AMOC seems to decrease with varying magnitudes depending upon the rate of carbon dioxide release and the amount of meltwater generated.

Financial heat machine

NASA Astrophysics Data System (ADS)

Khrennikov, Andrei

2005-05-01

We consider dynamics of financial markets as dynamics of expectations and discuss such a dynamics from the point of view of phenomenological thermodynamics. We describe a financial Carnot cycle and the financial analog of a heat machine. We see, that while in physics a perpetuum mobile is absolutely impossible, in economics such mobile may exist under some conditions.

Assessing global vegetation activity using spatio-temporal Bayesian modelling

NASA Astrophysics Data System (ADS)

Mulder, Vera L.; van Eck, Christel M.; Friedlingstein, Pierre; Regnier, Pierre A. G.

2016-04-01

This work demonstrates the potential of modelling vegetation activity using a hierarchical Bayesian spatio-temporal model. This approach allows modelling changes in vegetation and climate simultaneous in space and time. Changes of vegetation activity such as phenology are modelled as a dynamic process depending on climate variability in both space and time. Additionally, differences in observed vegetation status can be contributed to other abiotic ecosystem properties, e.g. soil and terrain properties. Although these properties do not change in time, they do change in space and may provide valuable information in addition to the climate dynamics. The spatio-temporal Bayesian models were calibrated at a regional scale because the local trends in space and time can be better captured by the model. The regional subsets were defined according to the SREX segmentation, as defined by the IPCC. Each region is considered being relatively homogeneous in terms of large-scale climate and biomes, still capturing small-scale (grid-cell level) variability. Modelling within these regions is hence expected to be less uncertain due to the absence of these large-scale patterns, compared to a global approach. This overall modelling approach allows the comparison of model behavior for the different regions and may provide insights on the main dynamic processes driving the interaction between vegetation and climate within different regions. The data employed in this study encompasses the global datasets for soil properties (SoilGrids), terrain properties (Global Relief Model based on SRTM DEM and ETOPO), monthly time series of satellite-derived vegetation indices (GIMMS NDVI3g) and climate variables (Princeton Meteorological Forcing Dataset). The findings proved the potential of a spatio-temporal Bayesian modelling approach for assessing vegetation dynamics, at a regional scale. The observed interrelationships of the employed data and the different spatial and temporal trends support our hypothesis. That is, the change of vegetation in space and time may be better understood when modelling vegetation change as both a dynamic and multivariate process. Therefore, future research will focus on a multivariate dynamical spatio-temporal modelling approach. This ongoing research is performed within the context of the project "Global impacts of hydrological and climatic extremes on vegetation" (project acronym: SAT-EX) which is part of the Belgian research programme for Earth Observation Stereo III.

Estimations of natural variability between satellite measurements of trace species concentrations

NASA Astrophysics Data System (ADS)

Sheese, P.; Walker, K. A.; Boone, C. D.; Degenstein, D. A.; Kolonjari, F.; Plummer, D. A.; von Clarmann, T.

2017-12-01

In order to validate satellite measurements of atmospheric states, it is necessary to understand the range of random and systematic errors inherent in the measurements. On occasions where the measurements do not agree within those errors, a common "go-to" explanation is that the unexplained difference can be chalked up to "natural variability". However, the expected natural variability is often left ambiguous and rarely quantified. This study will look to quantify the expected natural variability of both O3 and NO2 between two satellite instruments: ACE-FTS (Atmospheric Chemistry Experiment - Fourier Transform Spectrometer) and OSIRIS (Optical Spectrograph and Infrared Imaging System). By sampling the CMAM30 (30-year specified dynamics simulation of the Canadian Middle Atmosphere Model) climate chemistry model throughout the upper troposphere and stratosphere at times and geolocations of coincident ACE-FTS and OSIRIS measurements at varying coincidence criteria, height-dependent expected values of O3 and NO2 variability will be estimated and reported on. The results could also be used to better optimize the coincidence criteria used in satellite measurement validation studies.

Prediction of mortality rates using a model with stochastic parameters

NASA Astrophysics Data System (ADS)

Tan, Chon Sern; Pooi, Ah Hin

2016-10-01

Prediction of future mortality rates is crucial to insurance companies because they face longevity risks while providing retirement benefits to a population whose life expectancy is increasing. In the past literature, a time series model based on multivariate power-normal distribution has been applied on mortality data from the United States for the years 1933 till 2000 to forecast the future mortality rates for the years 2001 till 2010. In this paper, a more dynamic approach based on the multivariate time series will be proposed where the model uses stochastic parameters that vary with time. The resulting prediction intervals obtained using the model with stochastic parameters perform better because apart from having good ability in covering the observed future mortality rates, they also tend to have distinctly shorter interval lengths.

Reaction-diffusion on the fully-connected lattice: A+A\\rightarrow A

NASA Astrophysics Data System (ADS)

Turban, Loïc; Fortin, Jean-Yves

2018-04-01

Diffusion-coagulation can be simply described by a dynamic where particles perform a random walk on a lattice and coalesce with probability unity when meeting on the same site. Such processes display non-equilibrium properties with strong fluctuations in low dimensions. In this work we study this problem on the fully-connected lattice, an infinite-dimensional system in the thermodynamic limit, for which mean-field behaviour is expected. Exact expressions for the particle density distribution at a given time and survival time distribution for a given number of particles are obtained. In particular, we show that the time needed to reach a finite number of surviving particles (vanishing density in the scaling limit) displays strong fluctuations and extreme value statistics, characterized by a universal class of non-Gaussian distributions with singular behaviour.

Dephasing of LO-phonon-plasmon hybrid modes in n-type GaAs

NASA Astrophysics Data System (ADS)

Vallée, F.; Ganikhanov, F.; Bogani, F.

1997-11-01

The relaxation dynamics of coherent phononlike LO-phonon-plasmon hybrid modes is investigated in n-doped GaAs using an infrared time-resolved coherent anti-Stokes Raman scattering technique. Measurements performed for different crystal temperatures in the range 10-300 K as a function of the electron density injected by doping show a large reduction of the hybrid mode dephasing time compared to the bare LO-phonon one for densities larger than 1016 cm-3. The results are interpreted in terms of coherent decay of the LO-phonon-plasmon mixed mode in the weak-coupling regime and yield information on the plasmon and electron relaxation. The estimated average electron momentum relaxation times are smaller than those deduced from Hall mobility measurements, as expected from our theoretical model.

Mixture Hidden Markov Models in Finance Research

NASA Astrophysics Data System (ADS)

Dias, José G.; Vermunt, Jeroen K.; Ramos, Sofia

Finite mixture models have proven to be a powerful framework whenever unobserved heterogeneity cannot be ignored. We introduce in finance research the Mixture Hidden Markov Model (MHMM) that takes into account time and space heterogeneity simultaneously. This approach is flexible in the sense that it can deal with the specific features of financial time series data, such as asymmetry, kurtosis, and unobserved heterogeneity. This methodology is applied to model simultaneously 12 time series of Asian stock markets indexes. Because we selected a heterogeneous sample of countries including both developed and emerging countries, we expect that heterogeneity in market returns due to country idiosyncrasies will show up in the results. The best fitting model was the one with two clusters at country level with different dynamics between the two regimes.

Potential treatment mechanisms in a mindfulness-based intervention for people with progressive multiple sclerosis.

PubMed

Bogosian, Angeliki; Hughes, Alicia; Norton, Sam; Silber, Eli; Moss-Morris, Rona

2016-11-01

To explore putative mediators of a mindfulness-based intervention to decrease distress in people with multiple sclerosis (MS) and to explore the patients' perspectives on this intervention. We used an explanatory mixed methods design incorporating quantitative data from a pilot randomized control trial and a qualitative interview study with people who completed the mindfulness intervention. People with MS (n = 40) completed standardized measures of distress (outcome), and acceptance, decentring, self-compassion, and self-efficacy (potential mediators). Semi-structured interviews (n = 15) of patients' experiences of the mindfulness intervention were analysed deductively and inductively. Decentring post-intervention explained 13% of the 3-month change in distress and between 27% and 31% of concurrent changes in distress. Acceptance changed only slightly, and as a result, the indirect effect accounts for only 2% of future distress and between 3% and 11% of concurrent distress. Qualitative data showed that acceptance and self-compassion needed more time to develop, whereas decentring could be implemented readily after being introduced in the sessions. Self-efficacy also had a large mediating effect. Participants in their interviews talked about group dynamics and prior expectations as essential elements that determine their engagement with the course and their level of satisfaction. Mindfulness interventions for people with a chronic progressive condition may benefit from focusing on helping them to accept daily challenges and teach them to recognize their thoughts and feelings, allowing time for acceptance and self-compassion to develop. Group dynamics also play a fundamental role in the success of the mindfulness interventions. Statement of Contribution What is already known on this subject? Mindfulness courses improve psychological well-being for people with chronic conditions. Mindfulness courses have been successful in improving psychological well-being and symptom management for people with multiple sclerosis but we do not know how these courses work. What does this study add? Decentering and self-efficacy appear to be key mechanisms leading to reduced distress. Acceptance and self-compassion may need more time and practice to develop. Group dynamics and expectations of the mindfulness courses were also important elements of mindfulness. © 2016 The British Psychological Society.

Facial dynamics and emotional expressions in facial aging treatments.

PubMed

Michaud, Thierry; Gassia, Véronique; Belhaouari, Lakhdar

2015-03-01

Facial expressions convey emotions that form the foundation of interpersonal relationships, and many of these emotions promote and regulate our social linkages. Hence, the facial aging symptomatological analysis and the treatment plan must of necessity include knowledge of the facial dynamics and the emotional expressions of the face. This approach aims to more closely meet patients' expectations of natural-looking results, by correcting age-related negative expressions while observing the emotional language of the face. This article will successively describe patients' expectations, the role of facial expressions in relational dynamics, the relationship between facial structures and facial expressions, and the way facial aging mimics negative expressions. Eventually, therapeutic implications for facial aging treatment will be addressed. © 2015 Wiley Periodicals, Inc.

Structures and Dynamics Division research and technology plans for FY 1894 and accomplishments for FY 1982

NASA Technical Reports Server (NTRS)

Bales, K. S.

1984-01-01

The Objectives, Expected Results, Approach, and Fiscal Year FY 1984 Milestones for the Structures and Dynamics Division's research programs are examined. The FY 1983 Accomplishments are presented where applicable.

Dynamics of glass-forming liquids. XIX. Rise and decay of field induced anisotropy in the non-linear regime

NASA Astrophysics Data System (ADS)

Young-Gonzales, Amanda R.; Samanta, Subarna; Richert, Ranko

2015-09-01

For glycerol and three monohydroxy alcohols, we have measured the non-linear dielectric effects resulting from the application and removal of a high dc bias electric field. The field effects are detected by virtue of a small amplitude harmonic field, from which time resolved changes in the dielectric loss are derived. The changes in permittivity are dominated by modifications of the time constants (rather than amplitudes) which display two contributions: a heating-like decrease of relaxation times that originates from the time dependent field when the bias is switched on and off and a slowing down of the dynamics resulting from the field induced reduction of configurational entropy. As observed for the electro-optical Kerr effect, the rise of the entropy change is slower than its decay, a feature that we rationalize on the basis of the quadratic dependence of the entropy change on polarization. For glycerol, the observed steady state level of the field induced shift of the glass transition temperature (+84 mK) matches the expectation based on the entropy change and its impact on dynamics via the Adam-Gibbs relation (+88 mK). For the alcohols, these non-linear effects rise and decay on the time scales of the prominent dielectric Debye process, underscoring the relation of these features to polarization anisotropy, opposed to mechanical or enthalpy relaxation which are orders of magnitude faster in these systems. A model is discussed which captures the observed magnitudes as well as time dependences in a near quantitative fashion. It is demonstrated that the high bias field modifies the response of polarization to the ac field, including a temporary change in the low field susceptibility.

Model-based framework for multi-axial real-time hybrid simulation testing

NASA Astrophysics Data System (ADS)

Fermandois, Gaston A.; Spencer, Billie F.

2017-10-01

Real-time hybrid simulation is an efficient and cost-effective dynamic testing technique for performance evaluation of structural systems subjected to earthquake loading with rate-dependent behavior. A loading assembly with multiple actuators is required to impose realistic boundary conditions on physical specimens. However, such a testing system is expected to exhibit significant dynamic coupling of the actuators and suffer from time lags that are associated with the dynamics of the servo-hydraulic system, as well as control-structure interaction (CSI). One approach to reducing experimental errors considers a multi-input, multi-output (MIMO) controller design, yielding accurate reference tracking and noise rejection. In this paper, a framework for multi-axial real-time hybrid simulation (maRTHS) testing is presented. The methodology employs a real-time feedback-feedforward controller for multiple actuators commanded in Cartesian coordinates. Kinematic transformations between actuator space and Cartesian space are derived for all six-degrees-offreedom of the moving platform. Then, a frequency domain identification technique is used to develop an accurate MIMO transfer function of the system. Further, a Cartesian-domain model-based feedforward-feedback controller is implemented for time lag compensation and to increase the robustness of the reference tracking for given model uncertainty. The framework is implemented using the 1/5th-scale Load and Boundary Condition Box (LBCB) located at the University of Illinois at Urbana- Champaign. To demonstrate the efficacy of the proposed methodology, a single-story frame subjected to earthquake loading is tested. One of the columns in the frame is represented physically in the laboratory as a cantilevered steel column. For realtime execution, the numerical substructure, kinematic transformations, and controllers are implemented on a digital signal processor. Results show excellent performance of the maRTHS framework when six-degrees-of-freedom are controlled at the interface between substructures.

Robust optimization for nonlinear time-delay dynamical system of dha regulon with cost sensitivity constraint in batch culture

NASA Astrophysics Data System (ADS)

Yuan, Jinlong; Zhang, Xu; Liu, Chongyang; Chang, Liang; Xie, Jun; Feng, Enmin; Yin, Hongchao; Xiu, Zhilong

2016-09-01

Time-delay dynamical systems, which depend on both the current state of the system and the state at delayed times, have been an active area of research in many real-world applications. In this paper, we consider a nonlinear time-delay dynamical system of dha-regulonwith unknown time-delays in batch culture of glycerol bioconversion to 1,3-propanediol induced by Klebsiella pneumonia. Some important properties and strong positive invariance are discussed. Because of the difficulty in accurately measuring the concentrations of intracellular substances and the absence of equilibrium points for the time-delay system, a quantitative biological robustness for the concentrations of intracellular substances is defined by penalizing a weighted sum of the expectation and variance of the relative deviation between system outputs before and after the time-delays are perturbed. Our goal is to determine optimal values of the time-delays. To this end, we formulate an optimization problem in which the time delays are decision variables and the cost function is to minimize the biological robustness. This optimization problem is subject to the time-delay system, parameter constraints, continuous state inequality constraints for ensuring that the concentrations of extracellular and intracellular substances lie within specified limits, a quality constraint to reflect operational requirements and a cost sensitivity constraint for ensuring that an acceptable level of the system performance is achieved. It is approximated as a sequence of nonlinear programming sub-problems through the application of constraint transcription and local smoothing approximation techniques. Due to the highly complex nature of this optimization problem, the computational cost is high. Thus, a parallel algorithm is proposed to solve these nonlinear programming sub-problems based on the filled function method. Finally, it is observed that the obtained optimal estimates for the time-delays are highly satisfactory via numerical simulations.

Protein electron transfer: Dynamics and statistics

NASA Astrophysics Data System (ADS)

Matyushov, Dmitry V.

2013-07-01

Electron transfer between redox proteins participating in energy chains of biology is required to proceed with high energetic efficiency, minimizing losses of redox energy to heat. Within the standard models of electron transfer, this requirement, combined with the need for unidirectional (preferably activationless) transitions, is translated into the need to minimize the reorganization energy of electron transfer. This design program is, however, unrealistic for proteins whose active sites are typically positioned close to the polar and flexible protein-water interface to allow inter-protein electron tunneling. The high flexibility of the interfacial region makes both the hydration water and the surface protein layer act as highly polar solvents. The reorganization energy, as measured by fluctuations, is not minimized, but rather maximized in this region. Natural systems in fact utilize the broad breadth of interfacial electrostatic fluctuations, but in the ways not anticipated by the standard models based on equilibrium thermodynamics. The combination of the broad spectrum of static fluctuations with their dispersive dynamics offers the mechanism of dynamical freezing (ergodicity breaking) of subsets of nuclear modes on the time of reaction/residence of the electron at a redox cofactor. The separation of time-scales of nuclear modes coupled to electron transfer allows dynamical freezing. In particular, the separation between the relaxation time of electro-elastic fluctuations of the interface and the time of conformational transitions of the protein caused by changing redox state results in dynamical freezing of the latter for sufficiently fast electron transfer. The observable consequence of this dynamical freezing is significantly different reorganization energies describing the curvature at the bottom of electron-transfer free energy surfaces (large) and the distance between their minima (Stokes shift, small). The ratio of the two reorganization energies establishes the parameter by which the energetic efficiency of protein electron transfer is increased relative to the standard expectations, thus minimizing losses of energy to heat. Energetically efficient electron transfer occurs in a chain of conformationally quenched cofactors and is characterized by flattened free energy surfaces, reminiscent of the flat and rugged landscape at the stability basin of a folded protein.

Protein electron transfer: Dynamics and statistics.

PubMed

Matyushov, Dmitry V

2013-07-14

Electron transfer between redox proteins participating in energy chains of biology is required to proceed with high energetic efficiency, minimizing losses of redox energy to heat. Within the standard models of electron transfer, this requirement, combined with the need for unidirectional (preferably activationless) transitions, is translated into the need to minimize the reorganization energy of electron transfer. This design program is, however, unrealistic for proteins whose active sites are typically positioned close to the polar and flexible protein-water interface to allow inter-protein electron tunneling. The high flexibility of the interfacial region makes both the hydration water and the surface protein layer act as highly polar solvents. The reorganization energy, as measured by fluctuations, is not minimized, but rather maximized in this region. Natural systems in fact utilize the broad breadth of interfacial electrostatic fluctuations, but in the ways not anticipated by the standard models based on equilibrium thermodynamics. The combination of the broad spectrum of static fluctuations with their dispersive dynamics offers the mechanism of dynamical freezing (ergodicity breaking) of subsets of nuclear modes on the time of reaction/residence of the electron at a redox cofactor. The separation of time-scales of nuclear modes coupled to electron transfer allows dynamical freezing. In particular, the separation between the relaxation time of electro-elastic fluctuations of the interface and the time of conformational transitions of the protein caused by changing redox state results in dynamical freezing of the latter for sufficiently fast electron transfer. The observable consequence of this dynamical freezing is significantly different reorganization energies describing the curvature at the bottom of electron-transfer free energy surfaces (large) and the distance between their minima (Stokes shift, small). The ratio of the two reorganization energies establishes the parameter by which the energetic efficiency of protein electron transfer is increased relative to the standard expectations, thus minimizing losses of energy to heat. Energetically efficient electron transfer occurs in a chain of conformationally quenched cofactors and is characterized by flattened free energy surfaces, reminiscent of the flat and rugged landscape at the stability basin of a folded protein.

Glacier, Glacial Lake, and Ecological Response Dynamics of the Imja Glacier-Lake-Moraine System, Nepal

NASA Astrophysics Data System (ADS)

Kargel, J. S.; Shugar, D. H.; Leonard, G. J.; Haritashya, U. K.; Harrison, S.; Shrestha, A. B.; Mool, P. K.; Karki, A.; Regmi, D.

2016-12-01

Glacier response dynamics—involving a host of processes—produce a sequence of short- to long-term delayed responses to any step-wise, oscillating, or continuous trending climatic perturbation. We present analysis of Imja Lake, Nepal and examine its thinning and retreat and a sequence of the detachment of tributaries; the inception and growth of Imja Lake and concomitant glacier retreat, thinning, and stagnation, and relationships to lake dynamics; the response dynamics of the ice-cored moraine; the development of the local ecosystem; prediction of short-term dynamical responses to lake lowering (glacier lake outburst flood—GLOF—mitigation); and prospects for coming decades. The evolution of this glacier system provides a case study by which the global record of GLOFs can be assessed in terms of climate change attribution. We define three response times: glacier dynamical response time (for glacier retreat, thinning, and slowing of ice flow), limnological response time (lake growth), and GLOF trigger time (for a variety of hazardous trigger events). Lake lowering (to be completed in August 2016; see AGU abstract by D. Regmi et al.) will reduce hazards, but we expect that the elongation of the lake and retreat of the glacier will continue for decades after a pause in 2016-2017. The narrowing of the moraine dam due to thaw degradation of the ice-cored end moraine means that the hazard due to Imja Lake will soon again increase. We examine both long-term response dynamics, and two aspects of Himalayan glaciers that have very rapid responses: the area of Imja Lake fluctuates seasonally and even with subseasonal weather variations in response to changes in lake temperature and glacier meltback; and as known from other studies, glacier flow speed can vary between years and even on shorter timescales. The long-term development and stabilization of glacial moraines and small lacustrine plains in drained lake basins impacts the development of local ecosystems; satellite imaging reveals details of vegetational primary succession; and we will present an observations-constrained model of bird habitat in relationship to glacial geomorphology.

High Fidelity Thermal Simulators for Non-Nuclear Testing: Analysis and Initial Results

NASA Technical Reports Server (NTRS)

Bragg-Sitton, Shannon M.; Dickens, Ricky; Dixon, David

2007-01-01

Non-nuclear testing can be a valuable tool in the development of a space nuclear power system, providing system characterization data and allowing one to work through various fabrication, assembly and integration issues without the cost and time associated with a full ground nuclear test. In a non-nuclear test bed, electric heaters are used to simulate the heat from nuclear fuel. Testing with non-optimized heater elements allows one to assess thermal, heat transfer, and stress related attributes of a given system, but fails to demonstrate the dynamic response that would be present in an integrated, fueled reactor system. High fidelity thermal simulators that match both the static and the dynamic fuel pin performance that would be observed in an operating, fueled nuclear reactor can vastly increase the value of non-nuclear test results. With optimized simulators, the integration of thermal hydraulic hardware tests with simulated neutronie response provides a bridge between electrically heated testing and fueled nuclear testing, providing a better assessment of system integration issues, characterization of integrated system response times and response characteristics, and assessment of potential design improvements' at a relatively small fiscal investment. Initial conceptual thermal simulator designs are determined by simple one-dimensional analysis at a single axial location and at steady state conditions; feasible concepts are then input into a detailed three-dimensional model for comparison to expected fuel pin performance. Static and dynamic fuel pin performance for a proposed reactor design is determined using SINDA/FLUINT thermal analysis software, and comparison is made between the expected nuclear performance and the performance of conceptual thermal simulator designs. Through a series of iterative analyses, a conceptual high fidelity design can developed. Test results presented in this paper correspond to a "first cut" simulator design for a potential liquid metal (NaK) cooled reactor design that could be applied for Lunar surface power. Proposed refinements to this simulator design are also presented.

No evidence for consistent long-term growth stimulation of 13 tropical tree species: results from tree-ring analysis.

PubMed

Groenendijk, Peter; van der Sleen, Peter; Vlam, Mart; Bunyavejchewin, Sarayudh; Bongers, Frans; Zuidema, Pieter A

2015-10-01

The important role of tropical forests in the global carbon cycle makes it imperative to assess changes in their carbon dynamics for accurate projections of future climate-vegetation feedbacks. Forest monitoring studies conducted over the past decades have found evidence for both increasing and decreasing growth rates of tropical forest trees. The limited duration of these studies restrained analyses to decadal scales, and it is still unclear whether growth changes occurred over longer time scales, as would be expected if CO2 -fertilization stimulated tree growth. Furthermore, studies have so far dealt with changes in biomass gain at forest-stand level, but insights into species-specific growth changes - that ultimately determine community-level responses - are lacking. Here, we analyse species-specific growth changes on a centennial scale, using growth data from tree-ring analysis for 13 tree species (~1300 trees), from three sites distributed across the tropics. We used an established (regional curve standardization) and a new (size-class isolation) growth-trend detection method and explicitly assessed the influence of biases on the trend detection. In addition, we assessed whether aggregated trends were present within and across study sites. We found evidence for decreasing growth rates over time for 8-10 species, whereas increases were noted for two species and one showed no trend. Additionally, we found evidence for weak aggregated growth decreases at the site in Thailand and when analysing all sites simultaneously. The observed growth reductions suggest deteriorating growth conditions, perhaps due to warming. However, other causes cannot be excluded, such as recovery from large-scale disturbances or changing forest dynamics. Our findings contrast growth patterns that would be expected if elevated CO2 would stimulate tree growth. These results suggest that commonly assumed growth increases of tropical forests may not occur, which could lead to erroneous predictions of carbon dynamics of tropical forest under climate change. © 2015 John Wiley & Sons Ltd.

Dynamics of multiple-goal pursuit.

PubMed

Louro, Maria J; Pieters, Rik; Zeelenberg, Marcel

2007-08-01

The authors propose and test a model of multiple-goal pursuit that specifies how individuals allocate effort among multiple goals over time. The model predicts that whether individuals decide to step up effort, coast, abandon the current goal, or switch to pursue another goal is determined jointly by the emotions that flow from prior goal progress and the proximity to future goal attainment, and proximally determined by changes in expectancies about goal attainment. Results from a longitudinal diary study and 2 experiments show that positive and negative goal-related emotions can have diametrically opposing effects on goal-directed behavior, depending on the individual's proximity to goal attainment. The findings resolve contrasting predictions about the influence of positive and negative emotions in volitional behavior, critically amend the goal gradient hypothesis, and provide new insights into the dynamics and determinants of multiple-goal pursuit.

Molecular Dynamics Studies of Thermal Induced Chemistry in TATB

NASA Astrophysics Data System (ADS)

Quenneville, Jason; Germann, Timothy

2007-06-01

A reactive force field (ReaxFF^2) is used with molecular dynamics to probe the chemistry induced by intense heating (accelerated `cook-off') of 1,3,5-triamino-2,4,6-trinitrobenzene (TATB). Large-system simulations are desired for TATB because of the high degree of carbon clustering expected in this material. Using small, 800-atom, simulations, we will show the reaction rate as a function of temperature and density as well as the time evolution of reaction products. A larger simulation (with 14,000 atoms) will illustrate the effect of system size on both carbon clustering and reaction rate. Insight into the mechanisms of product formation will be given, as well as the chemical structure (graphitic or diamond-like) of the carbon clusters obtained. ^2 A. C. T. Van Duin, et al, J. Phys. Chem. A, 1005, 9396 (2001).

Spinon dynamics in quantum integrable antiferromagnets

NASA Astrophysics Data System (ADS)

Vlijm, R.; Caux, J.-S.

2016-05-01

The excitations of the Heisenberg antiferromagnetic spin chain in zero field are known as spinons. As pairwise-created fractionalized excitations, spinons are important in the understanding of inelastic neutron scattering experiments in (quasi-)one-dimensional materials. In the present paper, we consider the real space-time dynamics of spinons originating from a local spin flip on the antiferromagnetic ground state of the (an)isotropic Heisenberg spin-1/2 model and the Babujan-Takhtajan spin-1 model. By utilizing algebraic Bethe ansatz methods at finite system size to compute the expectation value of the local magnetization and spin-spin correlations, spinons are visualized as propagating domain walls in the antiferromagnetic spin ordering with anisotropy dependent behavior. The spin-spin correlation after the spin flip displays a light cone, satisfying the Lieb-Robinson bound for the propagation of correlations at the spinon velocity.

Unbinding Transition of Probes in Single-File Systems

NASA Astrophysics Data System (ADS)

Bénichou, Olivier; Démery, Vincent; Poncet, Alexis

2018-02-01

Single-file transport, arising in quasi-one-dimensional geometries where particles cannot pass each other, is characterized by the anomalous dynamics of a probe, notably its response to an external force. In these systems, the motion of several probes submitted to different external forces, although relevant to mixtures of charged and neutral or active and passive objects, remains unexplored. Here, we determine how several probes respond to external forces. We rely on a hydrodynamic description of the symmetric exclusion process to obtain exact analytical results at long times. We show that the probes can either move as a whole, or separate into two groups moving away from each other. In between the two regimes, they separate with a different dynamical exponent, as t1 /4. This unbinding transition also occurs in several continuous single-file systems and is expected to be observable.

Effect of N-Ethylmaleimide as a Blocker of Disulfide Crosslinks Formation on the Alkali-Cold Gelation of Whey Proteins

PubMed Central

Lei, Zhao; Chen, Xiao Dong

2016-01-01

N-ethylmaleimide (NEM) was used to verify that no new disulfide crosslinks were formed during the fascinating rheology of the alkali cold-gelation of whey proteins, which show Sol-Gel-Sol transitions with time at pH > 11.5. These dynamic transitions involve the formation and subsequent destruction of non-covalent interactions between soluble whey aggregates. Therefore, incubation of aggregates with NEM was expected not to affect much the rheology. Experiments show that very little additions of NEM, such as 0.5 mol per mol of protein, delayed and significantly strengthened the metastable gels formed. Interactions between whey protein aggregates were surprisingly enhanced during incubation with NEM as inferred from oscillatory rheometry at different protein concentrations, dynamic swelling, Trp fluorescence and SDS-PAGE measurements. PMID:27732644

Gate-Controlled Spin-Valley Locking of Resident Carriers in WSe2 Monolayers

NASA Astrophysics Data System (ADS)

Dey, P.; Yang, Luyi; Robert, C.; Wang, G.; Urbaszek, B.; Marie, X.; Crooker, S. A.

2017-09-01

Using time-resolved Kerr rotation, we measure the spin-valley dynamics of resident electrons and holes in single charge-tunable monolayers of the archetypal transition-metal dichalcogenide (TMD) semiconductor WSe2 . In the n -type regime, we observe long (˜130 ns ) polarization relaxation of electrons that is sensitive to in-plane magnetic fields By, indicating spin relaxation. In marked contrast, extraordinarily long (˜2 μ s ) polarization relaxation of holes is revealed in the p -type regime, which is unaffected by By, directly confirming long-standing expectations of strong spin-valley locking of holes in the valence band of monolayer TMDs. Supported by continuous-wave Kerr spectroscopy and Hanle measurements, these studies provide a unified picture of carrier polarization dynamics in monolayer TMDs, which can guide design principles for future valleytronic devices.

Force-free electrodynamics in dynamical curved spacetimes

NASA Astrophysics Data System (ADS)

McWilliams, Sean

2015-04-01

We present results on our study of force-free electrodynamics in curved spacetimes. Specifically, we present several improvements to what has become the established set of evolution equations, and we apply these to study the nonlinear stability of analytically known force-free solutions for the first time. We implement our method in a new pseudo-spectral code built on top of the SpEC code for evolving dynamic spacetimes. Finally, we revisit these known solutions and attempt to clarify some interesting properties that render them analytically tractable. Finally, we preview some new work that similarly revisits the established approach to solving another problem in numerical relativity: the post-merger recoil from asymmetric gravitational-wave emission. These new results may have significant implications for the parameter dependence of recoils, and consequently on the statistical expectations for recoil velocities of merged systems.

Dynamic elasticity measurement for prosthetic socket design.

PubMed

Kim, Yujin; Kim, Junghoon; Son, Hyeryon; Choi, Youngjin

2017-07-01

The paper proposes a novel apparatus to measure the dynamic elasticity of human limb in order to help the design and fabrication of the personalized prosthetic socket. To take measurements of the dynamic elasticity, the desired force generated as an exponential chirp signal in which the frequency increases and amplitude is maintained according to time progress is applied to human limb and then the skin deformation is recorded, ultimately, to obtain the frequency response of its elasticity. It is referred to as a Dynamic Elasticity Measurement Apparatus (DEMA) in the paper. It has three core components such as linear motor to provide the desired force, loadcell to implement the force feedback control, and potentiometer to record the skin deformation. After measuring the force/deformation and calculating the dynamic elasticity of the limb, it is visualized as 3D color map model of the limb so that the entire dynamic elasticity can be shown at a glance according to the locations and frequencies. For the visualization, the dynamic elasticities measured at specific locations and frequencies are embodied using the color map into 3D limb model acquired by using 3D scanner. To demonstrate the effectiveness, the visualized dynamic elasticities are suggested as outcome of the proposed system, although we do not have any opportunity to apply the proposed system to the amputees. Ultimately, it is expected that the proposed system can be utilized to design and fabricate the personalized prosthetic socket in order for releasing the wearing pain caused by the conventional prosthetic socket.

Mean-field analysis of an inductive reasoning game: Application to influenza vaccination

NASA Astrophysics Data System (ADS)

Breban, Romulus; Vardavas, Raffaele; Blower, Sally

2007-09-01

Recently we have introduced an inductive reasoning game of voluntary yearly vaccination to establish whether or not a population of individuals acting in their own self-interest would be able to prevent influenza epidemics. Here, we analyze our model to describe the dynamics of the collective yearly vaccination uptake. We discuss the mean-field equations of our model and first order effects of fluctuations. We explain why our model predicts that severe epidemics are periodically expected even without the introduction of pandemic strains. We find that fluctuations in the collective yearly vaccination uptake induce severe epidemics with an expected periodicity that depends on the number of independent decision makers in the population. The mean-field dynamics also reveal that there are conditions for which the dynamics become robust to the fluctuations. However, the transition between fluctuation-sensitive and fluctuation-robust dynamics occurs for biologically implausible parameters. We also analyze our model when incentive-based vaccination programs are offered. When a family-based incentive is offered, the expected periodicity of severe epidemics is increased. This results from the fact that the number of independent decision makers is reduced, increasing the effect of the fluctuations. However, incentives based on the number of years of prepayment of vaccination may yield fluctuation-robust dynamics where severe epidemics are prevented. In this case, depending on prepayment, the transition between fluctuation-sensitive and fluctuation-robust dynamics may occur for biologically plausible parameters. Our analysis provides a practical method for identifying how many years of free vaccination should be provided in order to successfully ameliorate influenza epidemics.

Mean-field analysis of an inductive reasoning game: application to influenza vaccination.

PubMed

Breban, Romulus; Vardavas, Raffaele; Blower, Sally

2007-09-01

Recently we have introduced an inductive reasoning game of voluntary yearly vaccination to establish whether or not a population of individuals acting in their own self-interest would be able to prevent influenza epidemics. Here, we analyze our model to describe the dynamics of the collective yearly vaccination uptake. We discuss the mean-field equations of our model and first order effects of fluctuations. We explain why our model predicts that severe epidemics are periodically expected even without the introduction of pandemic strains. We find that fluctuations in the collective yearly vaccination uptake induce severe epidemics with an expected periodicity that depends on the number of independent decision makers in the population. The mean-field dynamics also reveal that there are conditions for which the dynamics become robust to the fluctuations. However, the transition between fluctuation-sensitive and fluctuation-robust dynamics occurs for biologically implausible parameters. We also analyze our model when incentive-based vaccination programs are offered. When a family-based incentive is offered, the expected periodicity of severe epidemics is increased. This results from the fact that the number of independent decision makers is reduced, increasing the effect of the fluctuations. However, incentives based on the number of years of prepayment of vaccination may yield fluctuation-robust dynamics where severe epidemics are prevented. In this case, depending on prepayment, the transition between fluctuation-sensitive and fluctuation-robust dynamics may occur for biologically plausible parameters. Our analysis provides a practical method for identifying how many years of free vaccination should be provided in order to successfully ameliorate influenza epidemics.

Complex Dynamics in Nonequilibrium Economics and Chemistry

NASA Astrophysics Data System (ADS)

Wen, Kehong

Complex dynamics provides a new approach in dealing with economic complexity. We study interactively the empirical and theoretical aspects of business cycles. The way of exploring complexity is similar to that in the study of an oscillatory chemical system (BZ system)--a model for modeling complex behavior. We contribute in simulating qualitatively the complex periodic patterns observed from the controlled BZ experiments to narrow the gap between modeling and experiment. The gap between theory and reality is much wider in economics, which involves studies of human expectations and decisions, the essential difference from natural sciences. Our empirical and theoretical studies make substantial progress in closing this gap. With the help from the new development in nonequilibrium physics, i.e., the complex spectral theory, we advance our technique in detecting characteristic time scales from empirical economic data. We obtain correlation resonances, which give oscillating modes with decays for correlation decomposition, from different time series including S&P 500, M2, crude oil spot prices, and GNP. The time scales found are strikingly compatible with business experiences and other studies in business cycles. They reveal the non-Markovian nature of coherent markets. The resonances enhance the evidence of economic chaos obtained by using other tests. The evolving multi-humped distributions produced by the moving-time -window technique reveal the nonequilibrium nature of economic behavior. They reproduce the American economic history of booms and busts. The studies seem to provide a way out of the debate on chaos versus noise and unify the cyclical and stochastic approaches in explaining business fluctuations. Based on these findings and new expectation formulation, we construct a business cycle model which gives qualitatively compatible patterns to those found empirically. The soft-bouncing oscillator model provides a better alternative than the harmonic oscillator or the random walk model as the building block in business cycle theory. The mathematical structure of the model (delay differential equation) is studied analytically and numerically. The research pave the way toward sensible economic forecasting.

Effects of Cascaded Voltage Collapse and Protection of Many Induction Machine Loads upon Load Characteristics Viewed from Bulk Transmission System

NASA Astrophysics Data System (ADS)

Kumano, Teruhisa

As known well, two of the fundamental processes which give rise to voltage collapse in power systems are the on load tap changers of transformers and dynamic characteristics of loads such as induction machines. It has been well established that, comparing among these two, the former makes slower collapse while the latter makes faster. However, in realistic situations, the load level of each induction machine is not uniform and it is well expected that only a part of loads collapses first, followed by collapse process of each load which did not go into instability during the preceding collapses. In such situations the over all equivalent collapse behavior viewed from bulk transmission level becomes somewhat different from the simple collapse driven by one aggregated induction machine. This paper studies the process of cascaded voltage collapse among many induction machines by time simulation, where load distribution on a feeder line is modeled by several hundreds of induction machines and static impedance loads. It is shown that in some cases voltage collapse really cascades among induction machines, where the macroscopic load dynamics viewed from upper voltage level makes slower collapse than expected by the aggregated load model. Also shown is the effects of machine protection of induction machines, which also makes slower collapse.

Human Adaptive Behavior in Common Pool Resource Systems

PubMed Central

Brandt, Gunnar; Merico, Agostino; Vollan, Björn; Schlüter, Achim

2012-01-01

Overexploitation of common-pool resources, resulting from uncooperative harvest behavior, is a major problem in many social-ecological systems. Feedbacks between user behavior and resource productivity induce non-linear dynamics in the harvest and the resource stock that complicate the understanding and the prediction of the co-evolutionary system. With an adaptive model constrained by data from a behavioral economic experiment, we show that users’ expectations of future pay-offs vary as a result of the previous harvest experience, the time-horizon, and the ability to communicate. In our model, harvest behavior is a trait that adjusts to continuously changing potential returns according to a trade-off between the users’ current harvest and the discounted future productivity of the resource. Given a maximum discount factor, which quantifies the users’ perception of future pay-offs, the temporal dynamics of harvest behavior and ecological resource can be predicted. Our results reveal a non-linear relation between the previous harvest and current discount rates, which is most sensitive around a reference harvest level. While higher than expected returns resulting from cooperative harvesting in the past increase the importance of future resource productivity and foster sustainability, harvests below the reference level lead to a downward spiral of increasing overexploitation and disappointing returns. PMID:23285180

Measuring acoustic impedances using a semi-infinite waveguide reference: Applications to wind instruments and vocal tracts

NASA Astrophysics Data System (ADS)

Wolfe, Joe; Smith, John; Tann, John; France, Ryan

2002-11-01

Acoustic pressures may generally be measured with much greater sensitivity, dynamic range, and frequency response than acoustic currents. Consequently, most measurements of acoustic impedance consist of comparison with standard impedances. The method reported here uses a semi-infinite waveguide as the reference because its impedance is purely resistive, frequency independent and accurately known, independent of theories of the boundary layer. Waveguides are effectively infinite for pulses shorter than the echo return time, or if the attenuation due to wall losses (typically 80 dB) exceeds the dynamic range of the experiment. The measurement signal from a high output impedance source is calibrated to have Fourier components proportional to fn, where n may be 1 for convenience or chosen to improve the signal:noise ratio. The method has been used on diverse systems over the range 50 Hz to 13 kHz. When applied to systems with simple geometries, the technique yields results with a little higher wall losses than those expected from the calculations of Rayleigh and Benade. Discontinuities introduce further losses as well as the expected departures from simple one-dimensional models. Measurements on musical wind instruments and on the human vocal tract are reported. [Work supported by the Australian Research Council.

Towards the creation of a multi-institutional HF Radar Network in the Gulf of Mexico.

NASA Astrophysics Data System (ADS)

Flores-vidal, X.; Flament, P. J.; Durazo, R.; Navarro, L. F.; Salles, P.; Alvarez, P.; Carrillo, L.; Kurczyn, J. A.; Ulloa, M. J.; Rodriguez, I.; Toro Valencia, V. G.; Marin, M.; Perales, H.; Sanay, R.

2016-12-01

The Gulf of Mexico is source of important resources for both Mexico and USA, its beaches and coasts bring economical resources for these countries through the generation of jobs on the fisheries, touristic and industrial sectors. However, systematic monitoring is still necessary to evaluate its health and dynamics. This work is part of a multi-institutional project named "Implementation of oceanographic observational networks (physical, geochemical and ecological) to generate scenarios for possible contingencies related to the exploration and production of hydrocarbons in the deep waters of the Gulf of Mexico" (funded by SENER-CONACyT) which is an unprecedented Mexican joint effort to better understand the dynamics in the Gulf of Mexico. We will present the first actions towards the creation of the Mexican multi-Institutional HF Radar Network, which will allow us to synoptically map in real time the sea surface currents up to 200 km offshore. We expect to attract collaborations with the active or ongoing USA HF radar stations and institutions along the Gulf of Mexico, as well as to share methodologies and to evaluate standard data formats. The Radar Network in the Gulf of Mexico is planned to be active during 2017-2018, and it is expected to be permanent.

An extended ASLD trading system to enhance portfolio management.

PubMed

Hung, Kei-Keung; Cheung, Yiu-Ming; Xu, Lei

2003-01-01

An adaptive supervised learning decision (ASLD) trading system has been presented by Xu and Cheung (1997) to optimize the expected returns of investment without considering risks. In this paper, we propose an extension of the ASLD system (EASLD), which combines the ASLD with a portfolio optimization scheme to take a balance between the expected returns and risks. This new system not only keeps the learning adaptability of the ASLD, but also dynamically controls the risk in pursuit of great profits by diversifying the capital to a time-varying portfolio of N assets. Consequently, it is shown that: 1) the EASLD system gives the investment risk much smaller than the ASLD one; and 2) more returns are gained through the EASLD system in comparison with the two individual portfolio optimization schemes that statically determine the portfolio weights without adaptive learning. We have justified these two issues by the experiments.

Music and language perception: expectations, structural integration, and cognitive sequencing.

PubMed

Tillmann, Barbara

2012-10-01

Music can be described as sequences of events that are structured in pitch and time. Studying music processing provides insight into how complex event sequences are learned, perceived, and represented by the brain. Given the temporal nature of sound, expectations, structural integration, and cognitive sequencing are central in music perception (i.e., which sounds are most likely to come next and at what moment should they occur?). This paper focuses on similarities in music and language cognition research, showing that music cognition research provides insight into the understanding of not only music processing but also language processing and the processing of other structured stimuli. The hypothesis of shared resources between music and language processing and of domain-general dynamic attention has motivated the development of research to test music as a means to stimulate sensory, cognitive, and motor processes. Copyright © 2012 Cognitive Science Society, Inc.

Gambler's ruin problem on Erdős-Rényi graphs

NASA Astrophysics Data System (ADS)

Néda, Zoltán; Davidova, Larissa; Újvári, Szeréna; Istrate, Gabriel

2017-02-01

A multiagent ruin-game is studied on Erdős-Rényi type graphs. Initially the players have the same wealth. At each time step a monopolist game is played on all active links (links that connect nodes with nonzero wealth). In such a game each player puts a unit wealth in the pot and the pot is won with equal probability by one of the players. The game ends when there are no connected players such that both of them have non-zero wealth. In order to characterize the final state for dense graphs a compact formula is given for the expected number of the remaining players with non-zero wealth and the wealth distribution among these players. Theoretical predictions are given for the expected duration of the ruin game. The dynamics of the number of active players is also investigated. Validity of the theoretical predictions is investigated by Monte Carlo experiments.

Molecular Origins of Internal Friction Effects on Protein Folding Rates

PubMed Central

Sirur, Anshul

2014-01-01

Recent experiments on protein folding dynamics have revealed strong evidence for internal friction effects. That is, observed relaxation times are not simply proportional to the solvent viscosity as might be expected if the solvent were the only source of friction. However, a molecular interpretation of this remarkable phenomenon is currently lacking. Here, we use all-atom simulations of peptide and protein folding in explicit solvent, to probe the origin of the unusual viscosity dependence. We find that an important contribution to this effect, explaining the viscosity dependence of helix formation and the folding of a helix-containing protein, is the insensitivity of torsion angle isomerization to solvent friction. The influence of this landscape roughness can, in turn, be quantitatively explained by a rate theory including memory friction. This insensitivity of local barrier crossing to solvent friction is expected to contribute to the viscosity dependence of folding rates in larger proteins. PMID:24986114

Molecular origins of internal friction effects on protein-folding rates.

PubMed

de Sancho, David; Sirur, Anshul; Best, Robert B

2014-07-02

Recent experiments on protein-folding dynamics have revealed strong evidence for internal friction effects. That is, observed relaxation times are not simply proportional to the solvent viscosity as might be expected if the solvent were the only source of friction. However, a molecular interpretation of this remarkable phenomenon is currently lacking. Here, we use all-atom simulations of peptide and protein folding in explicit solvent, to probe the origin of the unusual viscosity dependence. We find that an important contribution to this effect, explaining the viscosity dependence of helix formation and the folding of a helix-containing protein, is the insensitivity of torsion angle isomerization to solvent friction. The influence of this landscape roughness can, in turn, be quantitatively explained by a rate theory including memory friction. This insensitivity of local barrier crossing to solvent friction is expected to contribute to the viscosity dependence of folding rates in larger proteins.

Volunteerism: Social Network Dynamics and Education

PubMed Central

Ajrouch, Kristine J.; Antonucci, Toni C.; Webster, Noah J.

2016-01-01

Objectives . We examine how changes in social networks influence volunteerism through bridging (diversity) and bonding (spending time) mechanisms. We further investigate whether social network change substitutes or amplifies the effects of education on volunteerism. Methods . Data (n = 543) are drawn from a two-wave survey of Social Relations and Health over the Life Course (SRHLC). Zero-inflated negative binomial regressions were conducted to test competing hypotheses about how changes in social network characteristics alone and in conjunction with education level predict likelihood and frequency of volunteering. Results . Changes in social networks were associated with volunteerism: as the proportion of family members decreased and the average number of network members living within a one-hour drive increased over time, participants reported higher odds of volunteering. The substitution hypothesis was supported: social networks that exhibited more geographic proximity and greater contact frequency over-time compensated for lower levels of education to predict volunteering more hours. Discussion . The dynamic role of social networks and the ways in which they may work through bridging and bonding to influence both likelihood and frequency of volunteering are discussed. The potential benefits of volunteerism in light of longer life expectancies and smaller families are also considered. PMID:25512570

Real-time monitoring of immune responses under pathogen invasion and drug interference by integrated microfluidic device coupled with worm-based biosensor.

PubMed

Hu, Liang; Ge, Anle; Wang, Xixian; Wang, Shanshan; Yue, Xinpei; Wang, Jie; Feng, Xiaojun; Du, Wei; Liu, Bi-Feng

2018-07-01

Immune response to environmental pathogen invasion is a complex process to prevent host from further damage. For quantitatively understanding immune responses and revealing the pathogenic environmental information, real-time monitoring of such a whole dynamic process with single-animal resolution in well-defined environments is highly desired. In this work, an integrated microfluidic device coupled with worm-based biosensor was proposed for in vivo studies of dynamic immune responses and antibiotics interference in infected C. elegans. Individual worms housed in chambers were exposed to the various pathogens and discontinuously manipulated for imaging with limited influence on physiological activities. The expression of immune responses gene (irg-1) was time-lapse measured in intact worms during pathogen infection. Results demonstrated that irg-1 gene could be induced in the presence of P. aeruginosa strain PA14 in a dose-dependent manner, and the survival of infected worm could be rescued under gentamicin or erythromycin treatments. We expect it to be a versatile platform to facilitate future studies on pathogenesis researches and rapid drug screen using C. elegans disease model. Copyright © 2018 Elsevier B.V. All rights reserved.

Foreign exchange market data analysis reveals statistical features that predict price movement acceleration.

PubMed

Nacher, Jose C; Ochiai, Tomoshiro

2012-05-01

Increasingly accessible financial data allow researchers to infer market-dynamics-based laws and to propose models that are able to reproduce them. In recent years, several stylized facts have been uncovered. Here we perform an extensive analysis of foreign exchange data that leads to the unveiling of a statistical financial law. First, our findings show that, on average, volatility increases more when the price exceeds the highest (or lowest) value, i.e., breaks the resistance line. We call this the breaking-acceleration effect. Second, our results show that the probability P(T) to break the resistance line in the past time T follows power law in both real data and theoretically simulated data. However, the probability calculated using real data is rather lower than the one obtained using a traditional Black-Scholes (BS) model. Taken together, the present analysis characterizes a different stylized fact of financial markets and shows that the market exceeds a past (historical) extreme price fewer times than expected by the BS model (the resistance effect). However, when the market does, we predict that the average volatility at that time point will be much higher. These findings indicate that any Markovian model does not faithfully capture the market dynamics.

Foreign exchange market data analysis reveals statistical features that predict price movement acceleration

NASA Astrophysics Data System (ADS)

Nacher, Jose C.; Ochiai, Tomoshiro

2012-05-01

Increasingly accessible financial data allow researchers to infer market-dynamics-based laws and to propose models that are able to reproduce them. In recent years, several stylized facts have been uncovered. Here we perform an extensive analysis of foreign exchange data that leads to the unveiling of a statistical financial law. First, our findings show that, on average, volatility increases more when the price exceeds the highest (or lowest) value, i.e., breaks the resistance line. We call this the breaking-acceleration effect. Second, our results show that the probability P(T) to break the resistance line in the past time T follows power law in both real data and theoretically simulated data. However, the probability calculated using real data is rather lower than the one obtained using a traditional Black-Scholes (BS) model. Taken together, the present analysis characterizes a different stylized fact of financial markets and shows that the market exceeds a past (historical) extreme price fewer times than expected by the BS model (the resistance effect). However, when the market does, we predict that the average volatility at that time point will be much higher. These findings indicate that any Markovian model does not faithfully capture the market dynamics.

Quasi-equilibria in reduced Liouville spaces.

PubMed

Halse, Meghan E; Dumez, Jean-Nicolas; Emsley, Lyndon

2012-06-14

The quasi-equilibrium behaviour of isolated nuclear spin systems in full and reduced Liouville spaces is discussed. We focus in particular on the reduced Liouville spaces used in the low-order correlations in Liouville space (LCL) simulation method, a restricted-spin-space approach to efficiently modelling the dynamics of large networks of strongly coupled spins. General numerical methods for the calculation of quasi-equilibrium expectation values of observables in Liouville space are presented. In particular, we treat the cases of a time-independent Hamiltonian, a time-periodic Hamiltonian (with and without stroboscopic sampling) and powder averaging. These quasi-equilibrium calculation methods are applied to the example case of spin diffusion in solid-state nuclear magnetic resonance. We show that there are marked differences between the quasi-equilibrium behaviour of spin systems in the full and reduced spaces. These differences are particularly interesting in the time-periodic-Hamiltonian case, where simulations carried out in the reduced space demonstrate ergodic behaviour even for small spins systems (as few as five homonuclei). The implications of this ergodic property on the success of the LCL method in modelling the dynamics of spin diffusion in magic-angle spinning experiments of powders is discussed.

Structures and Dynamics Division research and technology plans, fiscal year, 1981

NASA Technical Reports Server (NTRS)

Bales, K. S.

1981-01-01

The objectives, expected results, approach, and FY 81 milestones for the Structures and Dynamics Division's research program are presented. This information will be useful in program coordination with other government organizations in areas of mutual interest.

Fine-root growth in a forested bog is seasonally dynamic, but shallowly distributed in nutrient-poor peat

DOE PAGES

Iversen, Colleen M.; Childs, Joanne; Norby, Richard J.; ...

2017-03-30

Fine roots contribute to ecosystem carbon, water, and nutrient fluxes through resource acquisition, respiration, exudation, and turnover, but are understudied in peatlands. Here, we aimed to determine how the amount and timing of fine-root growth in a forested, ombrotrophic bog varied across gradients of vegetation density, peat microtopography, and changes in environmental conditions across the growing season and throughout the peat profile. We quantified fine-root peak standing crop and growth using non-destructive minirhizotron technology over a two-year period, focusing on the dominant woody species in the bog: Picea mariana, Larix laricina, Rhododendron groenlandicum, and Chamaedaphne calyculata. The fine roots ofmore » trees and shrubs were concentrated in raised hummock microtopography, with more tree roots associated with greater tree densities and a unimodal peak in shrub roots at intermediate tree densities. Fine-root growth tended to be seasonally dynamic, but shallowly distributed, in a thin layer of nutrient-poor, aerobic peat above the growing season water table level. Finally, the dynamics and distribution of fine roots in this forested ombrotrophic bog varied across space and time in response to biological, edaphic, and climatic conditions, and we expect these relationships to be sensitive to projected environmental changes in northern peatlands.« less

Impact of Coagulant and Flocculant Addition to an Anaerobic Dynamic Membrane Bioreactor (AnDMBR) Treating Waste-Activated Sludge.

PubMed

Kooijman, Guido; Lopes, Wilton; Zhou, Zhongbo; Guo, Hongxiao; de Kreuk, Merle; Spanjers, Henri; van Lier, Jules

2017-03-23

In this work, we investigated the effects of flocculation aid (FA) addition to an anaerobic dynamic membrane bioreactor (AnDMBR) (7 L, 35 °C) treating waste-activated sludge (WAS). The experiment consisted of three distinct periods. In period 1 (day 1-86), the reactor was operated as a conventional anaerobic digester with a solids retention time (SRT) and hydraulic retention time (HRT) of 24 days. In period 2 (day 86-303), the HRT was lowered to 18 days with the application of a dynamic membrane while the SRT was kept the same. In period 3 (day 303-386), a cationic FA in combination with FeCl₃ was added. The additions led to a lower viscosity, which was expected to lead to an increased digestion performance. However, the FAs caused irreversible binding of the substrate, lowering the volatile solids destruction from 32% in period 2 to 24% in period 3. An accumulation of small particulates was observed in the sludge, lowering the average particle size by 50%. These particulates likely caused pore blocking in the cake layer, doubling the trans-membrane pressure. The methanogenic consortia were unaffected. Dosing coagulants and flocculants into an AnDMBR treating sludge leads to a decreased cake layer permeability and decreased sludge degradation.

Statistical inference approach to structural reconstruction of complex networks from binary time series

NASA Astrophysics Data System (ADS)

Ma, Chuang; Chen, Han-Shuang; Lai, Ying-Cheng; Zhang, Hai-Feng

2018-02-01

Complex networks hosting binary-state dynamics arise in a variety of contexts. In spite of previous works, to fully reconstruct the network structure from observed binary data remains challenging. We articulate a statistical inference based approach to this problem. In particular, exploiting the expectation-maximization (EM) algorithm, we develop a method to ascertain the neighbors of any node in the network based solely on binary data, thereby recovering the full topology of the network. A key ingredient of our method is the maximum-likelihood estimation of the probabilities associated with actual or nonexistent links, and we show that the EM algorithm can distinguish the two kinds of probability values without any ambiguity, insofar as the length of the available binary time series is reasonably long. Our method does not require any a priori knowledge of the detailed dynamical processes, is parameter-free, and is capable of accurate reconstruction even in the presence of noise. We demonstrate the method using combinations of distinct types of binary dynamical processes and network topologies, and provide a physical understanding of the underlying reconstruction mechanism. Our statistical inference based reconstruction method contributes an additional piece to the rapidly expanding "toolbox" of data based reverse engineering of complex networked systems.

Dynamic imaging in electrical impedance tomography of the human chest with online transition matrix identification.

PubMed

Moura, Fernando Silva; Aya, Julio Cesar Ceballos; Fleury, Agenor Toledo; Amato, Marcelo Britto Passos; Lima, Raul Gonzalez

2010-02-01

One of the electrical impedance tomography objectives is to estimate the electrical resistivity distribution in a domain based only on electrical potential measurements at its boundary generated by an imposed electrical current distribution into the boundary. One of the methods used in dynamic estimation is the Kalman filter. In biomedical applications, the random walk model is frequently used as evolution model and, under this conditions, poor tracking ability of the extended Kalman filter (EKF) is achieved. An analytically developed evolution model is not feasible at this moment. The paper investigates the identification of the evolution model in parallel to the EKF and updating the evolution model with certain periodicity. The evolution model transition matrix is identified using the history of the estimated resistivity distribution obtained by a sensitivity matrix based algorithm and a Newton-Raphson algorithm. To numerically identify the linear evolution model, the Ibrahim time-domain method is used. The investigation is performed by numerical simulations of a domain with time-varying resistivity and by experimental data collected from the boundary of a human chest during normal breathing. The obtained dynamic resistivity values lie within the expected values for the tissues of a human chest. The EKF results suggest that the tracking ability is significantly improved with this approach.

Formal Definitions of Unbounded Evolution and Innovation Reveal Universal Mechanisms for Open-Ended Evolution in Dynamical Systems.

PubMed

Adams, Alyssa; Zenil, Hector; Davies, Paul C W; Walker, Sara Imari

2017-04-20

Open-ended evolution (OEE) is relevant to a variety of biological, artificial and technological systems, but has been challenging to reproduce in silico. Most theoretical efforts focus on key aspects of open-ended evolution as it appears in biology. We recast the problem as a more general one in dynamical systems theory, providing simple criteria for open-ended evolution based on two hallmark features: unbounded evolution and innovation. We define unbounded evolution as patterns that are non-repeating within the expected Poincare recurrence time of an isolated system, and innovation as trajectories not observed in isolated systems. As a case study, we implement novel variants of cellular automata (CA) where the update rules are allowed to vary with time in three alternative ways. Each is capable of generating conditions for open-ended evolution, but vary in their ability to do so. We find that state-dependent dynamics, regarded as a hallmark of life, statistically out-performs other candidate mechanisms, and is the only mechanism to produce open-ended evolution in a scalable manner, essential to the notion of ongoing evolution. This analysis suggests a new framework for unifying mechanisms for generating OEE with features distinctive to life and its artifacts, with broad applicability to biological and artificial systems.

Statistical inference approach to structural reconstruction of complex networks from binary time series.

PubMed

Ma, Chuang; Chen, Han-Shuang; Lai, Ying-Cheng; Zhang, Hai-Feng

2018-02-01

Complex networks hosting binary-state dynamics arise in a variety of contexts. In spite of previous works, to fully reconstruct the network structure from observed binary data remains challenging. We articulate a statistical inference based approach to this problem. In particular, exploiting the expectation-maximization (EM) algorithm, we develop a method to ascertain the neighbors of any node in the network based solely on binary data, thereby recovering the full topology of the network. A key ingredient of our method is the maximum-likelihood estimation of the probabilities associated with actual or nonexistent links, and we show that the EM algorithm can distinguish the two kinds of probability values without any ambiguity, insofar as the length of the available binary time series is reasonably long. Our method does not require any a priori knowledge of the detailed dynamical processes, is parameter-free, and is capable of accurate reconstruction even in the presence of noise. We demonstrate the method using combinations of distinct types of binary dynamical processes and network topologies, and provide a physical understanding of the underlying reconstruction mechanism. Our statistical inference based reconstruction method contributes an additional piece to the rapidly expanding "toolbox" of data based reverse engineering of complex networked systems.

Dark energy coupling with electromagnetism as seen from future low-medium redshift probes

NASA Astrophysics Data System (ADS)

Calabrese, E.; Martinelli, M.; Pandolfi, S.; Cardone, V. F.; Martins, C. J. A. P.; Spiro, S.; Vielzeuf, P. E.

2014-04-01

Beyond the standard cosmological model the late-time accelerated expansion of the Universe can be reproduced by the introduction of an additional dynamical scalar field. In this case, the field is expected to be naturally coupled to the rest of the theory's fields, unless a (still unknown) symmetry suppresses this coupling. Therefore, this would possibly lead to some observational consequences, such as space-time variations of nature's fundamental constants. In this paper we investigate the coupling between a dynamical dark energy model and the electromagnetic field, and the corresponding evolution of the fine structure constant (α) with respect to the standard local value α0. In particular, we derive joint constraints on two dynamical dark energy model parametrizations (the Chevallier-Polarski-Linder and early dark energy model) and on the coupling with electromagnetism ζ, forecasting future low-medium redshift observations. We combine supernovae and weak lensing measurements from the Euclid experiment with high-resolution spectroscopy measurements of fundamental couplings and the redshift drift from the European Extremely Large Telescope, highlighting the contribution of each probe. Moreover, we also consider the case where the field driving the α evolution is not the one responsible for cosmic acceleration and investigate how future observations can constrain this scenario.

Quantitative 4D analyses of epithelial folding during Drosophila gastrulation.

PubMed

Khan, Zia; Wang, Yu-Chiun; Wieschaus, Eric F; Kaschube, Matthias

2014-07-01

Understanding the cellular and mechanical processes that underlie the shape changes of individual cells and their collective behaviors in a tissue during dynamic and complex morphogenetic events is currently one of the major frontiers in developmental biology. The advent of high-speed time-lapse microscopy and its use in monitoring the cellular events in fluorescently labeled developing organisms demonstrate tremendous promise in establishing detailed descriptions of these events and could potentially provide a foundation for subsequent hypothesis-driven research strategies. However, obtaining quantitative measurements of dynamic shapes and behaviors of cells and tissues in a rapidly developing metazoan embryo using time-lapse 3D microscopy remains technically challenging, with the main hurdle being the shortage of robust imaging processing and analysis tools. We have developed EDGE4D, a software tool for segmenting and tracking membrane-labeled cells using multi-photon microscopy data. Our results demonstrate that EDGE4D enables quantification of the dynamics of cell shape changes, cell interfaces and neighbor relations at single-cell resolution during a complex epithelial folding event in the early Drosophila embryo. We expect this tool to be broadly useful for the analysis of epithelial cell geometries and movements in a wide variety of developmental contexts. © 2014. Published by The Company of Biologists Ltd.

High-speed nanoscale characterization of dewetting via dynamic transmission electron microscopy

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

Hihath, Sahar; Department of Physics, University of California, Davis, 1 Shields Ave., Davis, California 95616; Santala, Melissa K.

The dewetting of thin films can occur in either the solid or the liquid state for which different mass transport mechanisms are expected to control morphological changes. Traditionally, dewetting dynamics have been examined on time scales between several seconds to hours, and length scales ranging between nanometers and millimeters. The determination of mass transport mechanisms on the nanoscale, however, requires nanoscale spatial resolution and much shorter time scales. This study reports the high-speed observation of dewetting phenomena for kinetically constrained Ni thin films on crystalline SrTiO{sub 3} substrates. Movie-mode Dynamic Transmission Electron Microscopy (DTEM) was used for high-speed image acquisitionmore » during thin film dewetting at different temperatures. DTEM imaging confirmed that the initial stages of film agglomeration include edge retraction, hole formation, and growth. Finite element modeling was used to simulate temperature distributions within the DTEM samples after laser irradiation with different energies. For pulsed laser irradiation at 18 μJ, experimentally observed hole growth suggests that Marangoni flow dominates hole formation in the liquid nickel film. After irradiation with 13.8 μJ, however, the observations suggest that dewetting was initiated by nucleation of voids followed by hole growth through solid-state surface diffusion.« less

Structure and Dynamics of the Quasi-Biennial Oscillation in MERRA-2.

PubMed

Coy, Lawrence; Wargan, Krzysztof; Molod, Andrea M; McCarty, William R; Pawson, Steven

2016-07-01

The structure, dynamics, and ozone signal of the Quasi-Biennial Oscillation produced by the 35-year NASA MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications) reanalysis are examined based on monthly mean output. Along with the analysis of the QBO in assimilation winds and ozone, the QBO forcings created by assimilated observations, dynamics, parameterized gravity wave drag, and ozone chemistry parameterization are examined and compared with the original MERRA system. Results show that the MERRA-2 reanalysis produces a realistic QBO in the zonal winds, mean meridional circulation, and ozone over the 1980-2015 time period. In particular, the MERRA-2 zonal winds show improved representation of the QBO 50 hPa westerly phase amplitude at Singapore when compared to MERRA. The use of limb ozone observations creates improved vertical structure and realistic downward propagation of the ozone QBO signal during times when the MLS ozone limb observations are available (October 2004 to present). The increased equatorial GWD in MERRA-2 has reduced the zonal wind data analysis contribution compared to MERRA so that the QBO mean meridional circulation can be expected to be more physically forced and therefore more physically consistent. This can be important for applications in which MERRA-2 winds are used to drive transport experiments.

Structure and Dynamics of the Quasi-Biennial Oscillation in MERRA-2

PubMed Central

Coy, Lawrence; Wargan, Krzysztof; Molod, Andrea M.; McCarty, William R.; Pawson, Steven

2018-01-01

The structure, dynamics, and ozone signal of the Quasi-Biennial Oscillation produced by the 35-year NASA MERRA-2 (Modern-Era Retrospective Analysis for Research and Applications) reanalysis are examined based on monthly mean output. Along with the analysis of the QBO in assimilation winds and ozone, the QBO forcings created by assimilated observations, dynamics, parameterized gravity wave drag, and ozone chemistry parameterization are examined and compared with the original MERRA system. Results show that the MERRA-2 reanalysis produces a realistic QBO in the zonal winds, mean meridional circulation, and ozone over the 1980–2015 time period. In particular, the MERRA-2 zonal winds show improved representation of the QBO 50 hPa westerly phase amplitude at Singapore when compared to MERRA. The use of limb ozone observations creates improved vertical structure and realistic downward propagation of the ozone QBO signal during times when the MLS ozone limb observations are available (October 2004 to present). The increased equatorial GWD in MERRA-2 has reduced the zonal wind data analysis contribution compared to MERRA so that the QBO mean meridional circulation can be expected to be more physically forced and therefore more physically consistent. This can be important for applications in which MERRA-2 winds are used to drive transport experiments. PMID:29551854

Fine-root growth in a forested bog is seasonally dynamic, but shallowly distributed in nutrient-poor peat

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

Iversen, Colleen M.; Childs, Joanne; Norby, Richard J.

Fine roots contribute to ecosystem carbon, water, and nutrient fluxes through resource acquisition, respiration, exudation, and turnover, but are understudied in peatlands. Here, we aimed to determine how the amount and timing of fine-root growth in a forested, ombrotrophic bog varied across gradients of vegetation density, peat microtopography, and changes in environmental conditions across the growing season and throughout the peat profile. We quantified fine-root peak standing crop and growth using non-destructive minirhizotron technology over a two-year period, focusing on the dominant woody species in the bog: Picea mariana, Larix laricina, Rhododendron groenlandicum, and Chamaedaphne calyculata. The fine roots ofmore » trees and shrubs were concentrated in raised hummock microtopography, with more tree roots associated with greater tree densities and a unimodal peak in shrub roots at intermediate tree densities. Fine-root growth tended to be seasonally dynamic, but shallowly distributed, in a thin layer of nutrient-poor, aerobic peat above the growing season water table level. Finally, the dynamics and distribution of fine roots in this forested ombrotrophic bog varied across space and time in response to biological, edaphic, and climatic conditions, and we expect these relationships to be sensitive to projected environmental changes in northern peatlands.« less

Characterizing subcritical assemblies with time of flight fixed by energy estimation distributions

NASA Astrophysics Data System (ADS)

Monterial, Mateusz; Marleau, Peter; Pozzi, Sara

2018-04-01

We present the Time of Flight Fixed by Energy Estimation (TOFFEE) as a measure of the fission chain dynamics in subcritical assemblies. TOFFEE is the time between correlated gamma rays and neutrons, subtracted by the estimated travel time of the incident neutron from its proton recoil. The measured subcritical assembly was the BeRP ball, a 4.482 kg sphere of α-phase weapons grade plutonium metal, which came in five configurations: bare, 0.5, 1, and 1.5 in iron, and 1 in nickel closed fitting shell reflectors. We extend the measurement with MCNPX-PoliMi simulations of shells ranging up to 6 inches in thickness, and two new reflector materials: aluminum and tungsten. We also simulated the BeRP ball with different masses ranging from 1 to 8 kg. A two-region and single-region point kinetics models were used to model the behavior of the positive side of the TOFFEE distribution from 0 to 100 ns. The single region model of the bare cases gave positive linear correlations between estimated and expected neutron decay constants and leakage multiplications. The two-region model provided a way to estimate neutron multiplication for the reflected cases, which correlated positively with expected multiplication, but the nature of the correlation (sub or superlinear) changed between material types. Finally, we found that the areal density of the reflector shells had a linear correlation with the integral of the two-region model fit. Therefore, we expect that with knowledge of reflector composition, one could determine the shell thickness, or vice versa. Furthermore, up to a certain amount and thickness of the reflector, the two-region model provides a way of distinguishing bare and reflected plutonium assemblies.

Comparison among Reconstruction Algorithms for Quantitative Analysis of 11C-Acetate Cardiac PET Imaging.

PubMed

Shi, Ximin; Li, Nan; Ding, Haiyan; Dang, Yonghong; Hu, Guilan; Liu, Shuai; Cui, Jie; Zhang, Yue; Li, Fang; Zhang, Hui; Huo, Li

2018-01-01

Kinetic modeling of dynamic 11 C-acetate PET imaging provides quantitative information for myocardium assessment. The quality and quantitation of PET images are known to be dependent on PET reconstruction methods. This study aims to investigate the impacts of reconstruction algorithms on the quantitative analysis of dynamic 11 C-acetate cardiac PET imaging. Suspected alcoholic cardiomyopathy patients ( N = 24) underwent 11 C-acetate dynamic PET imaging after low dose CT scan. PET images were reconstructed using four algorithms: filtered backprojection (FBP), ordered subsets expectation maximization (OSEM), OSEM with time-of-flight (TOF), and OSEM with both time-of-flight and point-spread-function (TPSF). Standardized uptake values (SUVs) at different time points were compared among images reconstructed using the four algorithms. Time-activity curves (TACs) in myocardium and blood pools of ventricles were generated from the dynamic image series. Kinetic parameters K 1 and k 2 were derived using a 1-tissue-compartment model for kinetic modeling of cardiac flow from 11 C-acetate PET images. Significant image quality improvement was found in the images reconstructed using iterative OSEM-type algorithms (OSME, TOF, and TPSF) compared with FBP. However, no statistical differences in SUVs were observed among the four reconstruction methods at the selected time points. Kinetic parameters K 1 and k 2 also exhibited no statistical difference among the four reconstruction algorithms in terms of mean value and standard deviation. However, for the correlation analysis, OSEM reconstruction presented relatively higher residual in correlation with FBP reconstruction compared with TOF and TPSF reconstruction, and TOF and TPSF reconstruction were highly correlated with each other. All the tested reconstruction algorithms performed similarly for quantitative analysis of 11 C-acetate cardiac PET imaging. TOF and TPSF yielded highly consistent kinetic parameter results with superior image quality compared with FBP. OSEM was relatively less reliable. Both TOF and TPSF were recommended for cardiac 11 C-acetate kinetic analysis.

Mode coupling theory for nonequilibrium glassy dynamics of thermal self-propelled particles.

PubMed

Feng, Mengkai; Hou, Zhonghuai

2017-06-28

We present a mode coupling theory study for the relaxation and glassy dynamics of a system of strongly interacting self-propelled particles, wherein the self-propulsion force is described by Ornstein-Uhlenbeck colored noise and thermal noises are included. Our starting point is an effective Smoluchowski equation governing the distribution function of particle positions, from which we derive a memory function equation for the time dependence of density fluctuations in nonequilibrium steady states. With the basic assumption of the absence of macroscopic currents and standard mode coupling approximation, we can obtain expressions for the irreducible memory function and other relevant dynamic terms, wherein the nonequilibrium character of the active system is manifested through an averaged diffusion coefficient D[combining macron] and a nontrivial structural function S 2 (q) with q being the magnitude of wave vector q. D[combining macron] and S 2 (q) enter the frequency term and the vertex term for the memory function, and thus influence both the short time and the long time dynamics of the system. With these equations obtained, we study the glassy dynamics of this thermal self-propelled particle system by investigating the Debye-Waller factor f q and relaxation time τ α as functions of the persistence time τ p of self-propulsion, the single particle effective temperature T eff as well as the number density ρ. Consequently, we find the critical density ρ c for given τ p shifts to larger values with increasing magnitude of propulsion force or effective temperature, in good accordance with previously reported simulation work. In addition, the theory facilitates us to study the critical effective temperature T for fixed ρ as well as its dependence on τ p . We find that T increases with τ p and in the limit τ p → 0, it approaches the value for a simple passive Brownian system as expected. Our theory also well recovers the results for passive systems and can be easily extended to more complex systems such as active-passive mixtures.

The challenges to inferring the regulators of biodiversity in deep time.

PubMed

Ezard, Thomas H G; Quental, Tiago B; Benton, Michael J

2016-04-05

Attempts to infer the ecological drivers of macroevolution in deep time have long drawn inspiration from work on extant systems, but long-term evolutionary and geological changes complicate the simple extrapolation of such theory. Recent efforts to incorporate a more informed ecology into macroevolution have moved beyond the descriptive, seeking to isolate generating mechanisms and produce testable hypotheses of how groups of organisms usurp each other or coexist over vast timespans. This theme issue aims to exemplify this progress, providing a series of case studies of how novel modelling approaches are helping infer the regulators of biodiversity in deep time. In this Introduction, we explore the challenges of these new approaches. First, we discuss how our choices of taxonomic units have implications for the conclusions drawn. Second, we emphasize the need to embrace the interdependence of biotic and abiotic changes, because no living organism ignores its environment. Third, in the light of parts 1 and 2, we discuss the set of dynamic signatures that we might expect to observe in the fossil record. Finally, we ask whether these dynamics represent the most ecologically informative foci for research efforts aimed at inferring the regulators of biodiversity in deep time. The papers in this theme issue contribute in each of these areas. © 2016 The Author(s).