Transition Manifolds of Complex Metastable Systems: Theory and Data-Driven Computation of Effective Dynamics.

PubMed

Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof

2018-01-01

We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.

Robust control of combustion instabilities

NASA Astrophysics Data System (ADS)

Hong, Boe-Shong

Several interactive dynamical subsystems, each of which has its own time-scale and physical significance, are decomposed to build a feedback-controlled combustion- fluid robust dynamics. On the fast-time scale, the phenomenon of combustion instability is corresponding to the internal feedback of two subsystems: acoustic dynamics and flame dynamics, which are parametrically dependent on the slow-time-scale mean-flow dynamics controlled for global performance by a mean-flow controller. This dissertation constructs such a control system, through modeling, analysis and synthesis, to deal with model uncertainties, environmental noises and time- varying mean-flow operation. Conservation law is decomposed as fast-time acoustic dynamics and slow-time mean-flow dynamics, served for synthesizing LPV (linear parameter varying)- L2-gain robust control law, in which a robust observer is embedded for estimating and controlling the internal status, while achieving trade- offs among robustness, performances and operation. The robust controller is formulated as two LPV-type Linear Matrix Inequalities (LMIs), whose numerical solver is developed by finite-element method. Some important issues related to physical understanding and engineering application are discussed in simulated results of the control system.

Cycles, scaling and crossover phenomenon in length of the day (LOD) time series

NASA Astrophysics Data System (ADS)

Telesca, Luciano

2007-06-01

The dynamics of the temporal fluctuations of the length of the day (LOD) time series from January 1, 1962 to November 2, 2006 were investigated. The power spectrum of the whole time series has revealed annual, semi-annual, decadal and daily oscillatory behaviors, correlated with oceanic-atmospheric processes and interactions. The scaling behavior was analyzed by using the detrended fluctuation analysis (DFA), which has revealed two different scaling regimes, separated by a crossover timescale at approximately 23 days. Flicker-noise process can describe the dynamics of the LOD time regime involving intermediate and long timescales, while Brownian dynamics characterizes the LOD time series for small timescales.

Scaling properties in time-varying networks with memory

NASA Astrophysics Data System (ADS)

Kim, Hyewon; Ha, Meesoon; Jeong, Hawoong

2015-12-01

The formation of network structure is mainly influenced by an individual node's activity and its memory, where activity can usually be interpreted as the individual inherent property and memory can be represented by the interaction strength between nodes. In our study, we define the activity through the appearance pattern in the time-aggregated network representation, and quantify the memory through the contact pattern of empirical temporal networks. To address the role of activity and memory in epidemics on time-varying networks, we propose temporal-pattern coarsening of activity-driven growing networks with memory. In particular, we focus on the relation between time-scale coarsening and spreading dynamics in the context of dynamic scaling and finite-size scaling. Finally, we discuss the universality issue of spreading dynamics on time-varying networks for various memory-causality tests.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Transition Manifolds of Complex Metastable Systems

NASA Astrophysics Data System (ADS)

Bittracher, Andreas; Koltai, Péter; Klus, Stefan; Banisch, Ralf; Dellnitz, Michael; Schütte, Christof

2018-04-01

We consider complex dynamical systems showing metastable behavior, but no local separation of fast and slow time scales. The article raises the question of whether such systems exhibit a low-dimensional manifold supporting its effective dynamics. For answering this question, we aim at finding nonlinear coordinates, called reaction coordinates, such that the projection of the dynamics onto these coordinates preserves the dominant time scales of the dynamics. We show that, based on a specific reducibility property, the existence of good low-dimensional reaction coordinates preserving the dominant time scales is guaranteed. Based on this theoretical framework, we develop and test a novel numerical approach for computing good reaction coordinates. The proposed algorithmic approach is fully local and thus not prone to the curse of dimension with respect to the state space of the dynamics. Hence, it is a promising method for data-based model reduction of complex dynamical systems such as molecular dynamics.

Dynamic correlations at different time-scales with empirical mode decomposition

NASA Astrophysics Data System (ADS)

Nava, Noemi; Di Matteo, T.; Aste, Tomaso

2018-07-01

We introduce a simple approach which combines Empirical Mode Decomposition (EMD) and Pearson's cross-correlations over rolling windows to quantify dynamic dependency at different time scales. The EMD is a tool to separate time series into implicit components which oscillate at different time-scales. We apply this decomposition to intraday time series of the following three financial indices: the S&P 500 (USA), the IPC (Mexico) and the VIX (volatility index USA), obtaining time-varying multidimensional cross-correlations at different time-scales. The correlations computed over a rolling window are compared across the three indices, across the components at different time-scales and across different time lags. We uncover a rich heterogeneity of interactions, which depends on the time-scale and has important lead-lag relations that could have practical use for portfolio management, risk estimation and investment decisions.

Multi-Scale Scattering Transform in Music Similarity Measuring

NASA Astrophysics Data System (ADS)

Wang, Ruobai

Scattering transform is a Mel-frequency spectrum based, time-deformation stable method, which can be used in evaluating music similarity. Compared with Dynamic time warping, it has better performance in detecting similar audio signals under local time-frequency deformation. Multi-scale scattering means to combine scattering transforms of different window lengths. This paper argues that, multi-scale scattering transform is a good alternative of dynamic time warping in music similarity measuring. We tested the performance of multi-scale scattering transform against other popular methods, with data designed to represent different conditions.

Floquet–Magnus theory and generic transient dynamics in periodically driven many-body quantum systems

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

Kuwahara, Tomotaka, E-mail: tomotaka.phys@gmail.com; WPI, Advanced Institute for Materials Research, Tohoku University, Sendai 980-8577; Mori, Takashi

2016-04-15

This work explores a fundamental dynamical structure for a wide range of many-body quantum systems under periodic driving. Generically, in the thermodynamic limit, such systems are known to heat up to infinite temperature states in the long-time limit irrespective of dynamical details, which kills all the specific properties of the system. In the present study, instead of considering infinitely long-time scale, we aim to provide a general framework to understand the long but finite time behavior, namely the transient dynamics. In our analysis, we focus on the Floquet–Magnus (FM) expansion that gives a formal expression of the effective Hamiltonian onmore » the system. Although in general the full series expansion is not convergent in the thermodynamics limit, we give a clear relationship between the FM expansion and the transient dynamics. More precisely, we rigorously show that a truncated version of the FM expansion accurately describes the exact dynamics for a certain time-scale. Our theory reveals an experimental time-scale for which non-trivial dynamical phenomena can be reliably observed. We discuss several dynamical phenomena, such as the effect of small integrability breaking, efficient numerical simulation of periodically driven systems, dynamical localization and thermalization. Especially on thermalization, we discuss a generic scenario on the prethermalization phenomenon in periodically driven systems. -- Highlights: •A general framework to describe transient dynamics for periodically driven systems. •The theory is applicable to generic quantum many-body systems including long-range interacting systems. •Physical meaning of the truncation of the Floquet–Magnus expansion is rigorously established. •New mechanism of the prethermalization is proposed. •Revealing an experimental time-scale for which non-trivial dynamical phenomena can be reliably observed.« less

Collective motion of macroscopic spheres floating on capillary ripples: Dynamic heterogeneity and dynamic criticality

NASA Astrophysics Data System (ADS)

Sanlı, Ceyda; Saitoh, Kuniyasu; Luding, Stefan; van der Meer, Devaraj

2014-09-01

When a densely packed monolayer of macroscopic spheres floats on chaotic capillary Faraday waves, a coexistence of large scale convective motion and caging dynamics typical for glassy systems is observed. We subtract the convective mean flow using a coarse graining (homogenization) method and reveal subdiffusion for the caging time scales followed by a diffusive regime at later times. We apply the methods developed to study dynamic heterogeneity and show that the typical time and length scales of the fluctuations due to rearrangements of observed particle groups significantly increase when the system approaches its largest experimentally accessible packing concentration. To connect the system to the dynamic criticality literature, we fit power laws to our results. The resultant critical exponents are consistent with those found in densely packed suspensions of colloids.

Collective motion of macroscopic spheres floating on capillary ripples: dynamic heterogeneity and dynamic criticality.

PubMed

Sanlı, Ceyda; Saitoh, Kuniyasu; Luding, Stefan; van der Meer, Devaraj

2014-09-01

When a densely packed monolayer of macroscopic spheres floats on chaotic capillary Faraday waves, a coexistence of large scale convective motion and caging dynamics typical for glassy systems is observed. We subtract the convective mean flow using a coarse graining (homogenization) method and reveal subdiffusion for the caging time scales followed by a diffusive regime at later times. We apply the methods developed to study dynamic heterogeneity and show that the typical time and length scales of the fluctuations due to rearrangements of observed particle groups significantly increase when the system approaches its largest experimentally accessible packing concentration. To connect the system to the dynamic criticality literature, we fit power laws to our results. The resultant critical exponents are consistent with those found in densely packed suspensions of colloids.

Crossover from antipersistent to persistent behavior in time series possessing the generalyzed dynamic scaling law

NASA Astrophysics Data System (ADS)

Balankin, Alexander S.; Morales Matamoros, Oswaldo; Gálvez M., Ernesto; Pérez A., Alfonso

2004-03-01

The behavior of crude oil price volatility is analyzed within a conceptual framework of kinetic roughening of growing interfaces. We find that the persistent long-horizon volatilities satisfy the Family-Viscek dynamic scaling ansatz, whereas the mean-reverting in time short horizon volatilities obey the generalized scaling law with continuously varying scaling exponents. Furthermore we find that the crossover from antipersistent to persistent behavior is accompanied by a change in the type of volatility distribution. These phenomena are attributed to the complex avalanche dynamics of crude oil markets and so a similar behavior may be observed in a wide variety of physical systems governed by avalanche dynamics.

Translocation of polymers into crowded media with dynamic attractive nanoparticles.

PubMed

Cao, Wei-Ping; Ren, Qing-Bao; Luo, Meng-Bo

2015-07-01

The translocation of polymers through a small pore into crowded media with dynamic attractive nanoparticles is simulated. Results show that the nanoparticles at the trans side can affect the translocation by influencing the free-energy landscape and the diffusion of polymers. Thus the translocation time τ is dependent on the polymer-nanoparticle attraction strength ɛ and the mobility of nanoparticles V. We observe a power-law relation of τ with V, but the exponent is dependent on ɛ and nanoparticle concentration. In addition, we find that the effect of attractive dynamic nanoparticles on the dynamics of polymers is dependent on the time scale. At a short time scale, subnormal diffusion is observed at strong attraction and the diffusion is slowed down by the dynamic nanoparticles. However, the diffusion of polymers is normal at a long time scale and the diffusion constant increases with the increase in V.

Relationship between femtosecond-picosecond dynamics to enzyme catalyzed H-transfer

PubMed Central

Cheatum, Christopher M.; Kohen, Amnon

2015-01-01

At physiological temperatures, enzymes exhibit a broad spectrum of conformations, which interchange via thermally activated dynamics. These conformations are sampled differently in different complexes of the protein and its ligands, and the dynamics of exchange between these conformers depends on the mass of the group that is moving and the length scale of the motion, as well as restrictions imposed by the globular fold of the enzymatic complex. Many of these motions have been examined and their role in the enzyme function illuminated, yet most experimental tools applied so far have identified dynamics at time scales of seconds to nanoseconds, which are much slower than the time scale for H-transfer between two heavy atoms. This chemical conversion and other processes involving cleavage of covalent bonds occur on picosecond to femtosecond time scales, where slower processes mask both the kinetics and dynamics. Here we present a combination of kinetic and spectroscopic methods that may enable closer examination of the relationship between enzymatic C-H→C transfer and the dynamics of the active site environment at the chemically relevant time scale. These methods include kinetic isotope effects and their temperature dependence, which are used to study the kinetic nature of the H-transfer, and 2D IR spectroscopy, which is used to study the dynamics of transition-state- and ground-state-analog complexes. The combination of these tools is likely to provide a new approach to examine the protein dynamics that directly influence the chemical conversion catalyzed by enzymes. PMID:23539379

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

Mamontov, Eugene; Zolnierczuk, Piotr A.; Ohl, Michael E.

Using neutron spin-echo and backscattering spectroscopy, we have found that at low temperatures water molecules in an aqueous solution engage in center-of-mass dynamics that are different from both the main structural relaxations and the well-known localized motions in the transient cages of the nearest neighbor molecules. While the latter localized motions are known to take place on the picosecond time scale and Angstrom length scale, the slower motions that we have observed are found on the nanosecond time scale and nanometer length scale. They are associated with the slow secondary relaxations, or excess wing dynamics, in glass-forming liquids. Our approach,more » therefore, can be applied to probe the characteristic length scale of the dynamic entities associated with slow dynamics in glass-forming liquids, which presently cannot be studied by other experimental techniques.« less

Resolving Properties of Polymers and Nanoparticle Assembly through Coarse-Grained Computational Studies.

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

Grest, Gary S.

2017-09-01

Coupled length and time scales determine the dynamic behavior of polymers and polymer nanocomposites and underlie their unique properties. To resolve the properties over large time and length scales it is imperative to develop coarse grained models which retain the atomistic specificity. Here we probe the degree of coarse graining required to simultaneously retain significant atomistic details a nd access large length and time scales. The degree of coarse graining in turn sets the minimum length scale instrumental in defining polymer properties and dynamics. Using polyethylene as a model system, we probe how the coarse - graining scale affects themore » measured dynamics with different number methylene group s per coarse - grained beads. Using these models we simulate polyethylene melts for times over 500 ms to study the viscoelastic properties of well - entangled polymer melts and large nanoparticle assembly as the nanoparticles are driven close enough to form nanostructures.« less

Dynamic structural disorder in supported nanoscale catalysts

NASA Astrophysics Data System (ADS)

Rehr, J. J.; Vila, F. D.

2014-04-01

We investigate the origin and physical effects of "dynamic structural disorder" (DSD) in supported nano-scale catalysts. DSD refers to the intrinsic fluctuating, inhomogeneous structure of such nano-scale systems. In contrast to bulk materials, nano-scale systems exhibit substantial fluctuations in structure, charge, temperature, and other quantities, as well as large surface effects. The DSD is driven largely by the stochastic librational motion of the center of mass and fluxional bonding at the nanoparticle surface due to thermal coupling with the substrate. Our approach for calculating and understanding DSD is based on a combination of real-time density functional theory/molecular dynamics simulations, transient coupled-oscillator models, and statistical mechanics. This approach treats thermal and dynamic effects over multiple time-scales, and includes bond-stretching and -bending vibrations, and transient tethering to the substrate at longer ps time-scales. Potential effects on the catalytic properties of these clusters are briefly explored. Model calculations of molecule-cluster interactions and molecular dissociation reaction paths are presented in which the reactant molecules are adsorbed on the surface of dynamically sampled clusters. This model suggests that DSD can affect both the prefactors and distribution of energy barriers in reaction rates, and thus can significantly affect catalytic activity at the nano-scale.

Atomic and molecular dynamics triggered by ultrashort light pulses on the atto- to picosecond time scale

NASA Astrophysics Data System (ADS)

Pabst, Stefan

2013-04-01

Time-resolved investigations of ultrafast electronic and molecular dynamics were not possible until recently. The typical time scale of these processes is in the picosecond to attosecond realm. The tremendous technological progress in recent years made it possible to generate ultrashort pulses, which can be used to trigger, to watch, and to control atomic and molecular motion. This tutorial focuses on experimental and theoretical advances which are used to study the dynamics of electrons and molecules in the presence of ultrashort pulses. In the first part, the rotational dynamics of molecules, which happens on picosecond and femtosecond time scales, is reviewed. Well-aligned molecules are particularly suitable for angle-dependent investigations like x-ray diffraction or strong-field ionization experiments. In the second part, the ionization dynamics of atoms is studied. The characteristic time scale lies, here, in the attosecond to few-femtosecond regime. Although a one-particle picture has been successfully applied to many processes, many-body effects do constantly occur. After a broad overview of the main mechanisms and the most common tools in attosecond physics, examples of many-body dynamics in the attosecond world (e.g., in high-harmonic generation and attosecond transient absorption spectroscopy) are discussed.

Floquet-Magnus theory and generic transient dynamics in periodically driven many-body quantum systems

NASA Astrophysics Data System (ADS)

Kuwahara, Tomotaka; Mori, Takashi; Saito, Keiji

2016-04-01

This work explores a fundamental dynamical structure for a wide range of many-body quantum systems under periodic driving. Generically, in the thermodynamic limit, such systems are known to heat up to infinite temperature states in the long-time limit irrespective of dynamical details, which kills all the specific properties of the system. In the present study, instead of considering infinitely long-time scale, we aim to provide a general framework to understand the long but finite time behavior, namely the transient dynamics. In our analysis, we focus on the Floquet-Magnus (FM) expansion that gives a formal expression of the effective Hamiltonian on the system. Although in general the full series expansion is not convergent in the thermodynamics limit, we give a clear relationship between the FM expansion and the transient dynamics. More precisely, we rigorously show that a truncated version of the FM expansion accurately describes the exact dynamics for a certain time-scale. Our theory reveals an experimental time-scale for which non-trivial dynamical phenomena can be reliably observed. We discuss several dynamical phenomena, such as the effect of small integrability breaking, efficient numerical simulation of periodically driven systems, dynamical localization and thermalization. Especially on thermalization, we discuss a generic scenario on the prethermalization phenomenon in periodically driven systems.

Molecular dynamics of conformational substates for a simplified protein model

NASA Astrophysics Data System (ADS)

Grubmüller, Helmut; Tavan, Paul

1994-09-01

Extended molecular dynamics simulations covering a total of 0.232 μs have been carried out on a simplified protein model. Despite its simplified structure, that model exhibits properties similar to those of more realistic protein models. In particular, the model was found to undergo transitions between conformational substates at a time scale of several hundred picoseconds. The computed trajectories turned out to be sufficiently long as to permit a statistical analysis of that conformational dynamics. To check whether effective descriptions neglecting memory effects can reproduce the observed conformational dynamics, two stochastic models were studied. A one-dimensional Langevin effective potential model derived by elimination of subpicosecond dynamical processes could not describe the observed conformational transition rates. In contrast, a simple Markov model describing the transitions between but neglecting dynamical processes within conformational substates reproduced the observed distribution of first passage times. These findings suggest, that protein dynamics generally does not exhibit memory effects at time scales above a few hundred picoseconds, but confirms the existence of memory effects at a picosecond time scale.

Anomalous diffusion of a probe in a bath of active granular chains

NASA Astrophysics Data System (ADS)

Jerez, Michael Jade Y.; Confesor, Mark Nolan P.; Carpio-Bernido, M. Victoria; Bernido, Christopher C.

2017-08-01

We investigate the dynamics of a passive probe particle in a bath of active granular chains (AGC). The bath and the probe are enclosed in an experimental compartment with a sinusoidal boundary to prevent AGC congestion along the boundary while connected to an electrodynamic shaker. Single AGC trajectory analysis reveals a persistent type of motion compared to a purely Brownian motion as seen in its mean squared displacement (MSD). It was found that at small concentration, Φ ≤ 0.44, the MSD exhibits two dynamical regimes characterized by two different scaling exponents. For small time scales, the dynamics is superdiffusive (1.32-1.63) with the MSD scaling exponent increasing monotonically with increasing AGC concentration. On the other hand, at long time, we recover the Brownian dynamics regime, MSD = DΔt, where the mobility D ∝ Φ. We quantify the probe dynamics at short time scale by modeling it as a fractional Brownian motion. The analytical form of the MSD agrees with experimental results.

Shear banding leads to accelerated aging dynamics in a metallic glass

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

Küchemann, Stefan; Liu, Chaoyang; Dufresne, Eric M.

Traditionally, strain localization in metallic glasses is related to the thickness of the shear defect, which is confined to the nanometer scale. In this study, using site-specific x-ray photon correlation spectroscopy (XPCS), we reveal significantly accelerated relaxation dynamics around a shear band in a metallic glass at a length scale that is orders of magnitude larger than the defect itself. The relaxation time in the shear-band vicinity is up to ten-times smaller compared to the as-cast matrix, and the relaxation dynamics occurs in a characteristic three-stage aging response that manifests itself in the temperature-dependent shape parameter known from classical stretchedmore » exponential relaxation dynamics of disordered materials. We demonstrate that the time-dependent correlation functions describing the aging at different temperatures can be captured and collapsed using simple scaling functions. Finally, these insights highlight how an ubiquitous nano-scale strain-localization mechanism in metallic glasses leads to a fundamental change of the relaxation dynamics at the mesoscale.« less

Shear banding leads to accelerated aging dynamics in a metallic glass

DOE PAGES

Küchemann, Stefan; Liu, Chaoyang; Dufresne, Eric M.; ...

2018-01-11

Traditionally, strain localization in metallic glasses is related to the thickness of the shear defect, which is confined to the nanometer scale. In this study, using site-specific x-ray photon correlation spectroscopy (XPCS), we reveal significantly accelerated relaxation dynamics around a shear band in a metallic glass at a length scale that is orders of magnitude larger than the defect itself. The relaxation time in the shear-band vicinity is up to ten-times smaller compared to the as-cast matrix, and the relaxation dynamics occurs in a characteristic three-stage aging response that manifests itself in the temperature-dependent shape parameter known from classical stretchedmore » exponential relaxation dynamics of disordered materials. We demonstrate that the time-dependent correlation functions describing the aging at different temperatures can be captured and collapsed using simple scaling functions. Finally, these insights highlight how an ubiquitous nano-scale strain-localization mechanism in metallic glasses leads to a fundamental change of the relaxation dynamics at the mesoscale.« less

Hierarchical coarse-graining model for photosystem II including electron and excitation-energy transfer processes.

PubMed

Matsuoka, Takeshi; Tanaka, Shigenori; Ebina, Kuniyoshi

2014-03-01

We propose a hierarchical reduction scheme to cope with coupled rate equations that describe the dynamics of multi-time-scale photosynthetic reactions. To numerically solve nonlinear dynamical equations containing a wide temporal range of rate constants, we first study a prototypical three-variable model. Using a separation of the time scale of rate constants combined with identified slow variables as (quasi-)conserved quantities in the fast process, we achieve a coarse-graining of the dynamical equations reduced to those at a slower time scale. By iteratively employing this reduction method, the coarse-graining of broadly multi-scale dynamical equations can be performed in a hierarchical manner. We then apply this scheme to the reaction dynamics analysis of a simplified model for an illuminated photosystem II, which involves many processes of electron and excitation-energy transfers with a wide range of rate constants. We thus confirm a good agreement between the coarse-grained and fully (finely) integrated results for the population dynamics. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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

2016-04-13

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

Delay induced high order locking effects in semiconductor lasers

NASA Astrophysics Data System (ADS)

Kelleher, B.; Wishon, M. J.; Locquet, A.; Goulding, D.; Tykalewicz, B.; Huyet, G.; Viktorov, E. A.

2017-11-01

Multiple time scales appear in many nonlinear dynamical systems. Semiconductor lasers, in particular, provide a fertile testing ground for multiple time scale dynamics. For solitary semiconductor lasers, the two fundamental time scales are the cavity repetition rate and the relaxation oscillation frequency which is a characteristic of the field-matter interaction in the cavity. Typically, these two time scales are of very different orders, and mutual resonances do not occur. Optical feedback endows the system with a third time scale: the external cavity repetition rate. This is typically much longer than the device cavity repetition rate and suggests the possibility of resonances with the relaxation oscillations. We show that for lasers with highly damped relaxation oscillations, such resonances can be obtained and lead to spontaneous mode-locking. Two different laser types-—a quantum dot based device and a quantum well based device—are analysed experimentally yielding qualitatively identical dynamics. A rate equation model is also employed showing an excellent agreement with the experimental results.

Delay induced high order locking effects in semiconductor lasers.

PubMed

Kelleher, B; Wishon, M J; Locquet, A; Goulding, D; Tykalewicz, B; Huyet, G; Viktorov, E A

2017-11-01

Multiple time scales appear in many nonlinear dynamical systems. Semiconductor lasers, in particular, provide a fertile testing ground for multiple time scale dynamics. For solitary semiconductor lasers, the two fundamental time scales are the cavity repetition rate and the relaxation oscillation frequency which is a characteristic of the field-matter interaction in the cavity. Typically, these two time scales are of very different orders, and mutual resonances do not occur. Optical feedback endows the system with a third time scale: the external cavity repetition rate. This is typically much longer than the device cavity repetition rate and suggests the possibility of resonances with the relaxation oscillations. We show that for lasers with highly damped relaxation oscillations, such resonances can be obtained and lead to spontaneous mode-locking. Two different laser types--a quantum dot based device and a quantum well based device-are analysed experimentally yielding qualitatively identical dynamics. A rate equation model is also employed showing an excellent agreement with the experimental results.

Wavelet-based surrogate time series for multiscale simulation of heterogeneous catalysis

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

Savara, Aditya Ashi; Daw, C. Stuart; Xiong, Qingang

We propose a wavelet-based scheme that encodes the essential dynamics of discrete microscale surface reactions in a form that can be coupled with continuum macroscale flow simulations with high computational efficiency. This makes it possible to simulate the dynamic behavior of reactor-scale heterogeneous catalysis without requiring detailed concurrent simulations at both the surface and continuum scales using different models. Our scheme is based on the application of wavelet-based surrogate time series that encodes the essential temporal and/or spatial fine-scale dynamics at the catalyst surface. The encoded dynamics are then used to generate statistically equivalent, randomized surrogate time series, which canmore » be linked to the continuum scale simulation. As a result, we illustrate an application of this approach using two different kinetic Monte Carlo simulations with different characteristic behaviors typical for heterogeneous chemical reactions.« less

Wavelet-based surrogate time series for multiscale simulation of heterogeneous catalysis

DOE PAGES

Savara, Aditya Ashi; Daw, C. Stuart; Xiong, Qingang; ...

2016-01-28

We propose a wavelet-based scheme that encodes the essential dynamics of discrete microscale surface reactions in a form that can be coupled with continuum macroscale flow simulations with high computational efficiency. This makes it possible to simulate the dynamic behavior of reactor-scale heterogeneous catalysis without requiring detailed concurrent simulations at both the surface and continuum scales using different models. Our scheme is based on the application of wavelet-based surrogate time series that encodes the essential temporal and/or spatial fine-scale dynamics at the catalyst surface. The encoded dynamics are then used to generate statistically equivalent, randomized surrogate time series, which canmore » be linked to the continuum scale simulation. As a result, we illustrate an application of this approach using two different kinetic Monte Carlo simulations with different characteristic behaviors typical for heterogeneous chemical reactions.« less

Synchronization and Causality Across Time-scales: Complex Dynamics and Extremes in El Niño/Southern Oscillation

NASA Astrophysics Data System (ADS)

Jajcay, N.; Kravtsov, S.; Tsonis, A.; Palus, M.

2017-12-01

A better understanding of dynamics in complex systems, such as the Earth's climate is one of the key challenges for contemporary science and society. A large amount of experimental data requires new mathematical and computational approaches. Natural complex systems vary on many temporal and spatial scales, often exhibiting recurring patterns and quasi-oscillatory phenomena. The statistical inference of causal interactions and synchronization between dynamical phenomena evolving on different temporal scales is of vital importance for better understanding of underlying mechanisms and a key for modeling and prediction of such systems. This study introduces and applies information theory diagnostics to phase and amplitude time series of different wavelet components of the observed data that characterizes El Niño. A suite of significant interactions between processes operating on different time scales was detected, and intermittent synchronization among different time scales has been associated with the extreme El Niño events. The mechanisms of these nonlinear interactions were further studied in conceptual low-order and state-of-the-art dynamical, as well as statistical climate models. Observed and simulated interactions exhibit substantial discrepancies, whose understanding may be the key to an improved prediction. Moreover, the statistical framework which we apply here is suitable for direct usage of inferring cross-scale interactions in nonlinear time series from complex systems such as the terrestrial magnetosphere, solar-terrestrial interactions, seismic activity or even human brain dynamics.

Nonoscillatory solutions for system of neutral dynamic equations on time scales.

PubMed

Chen, Zhanhe; Sun, Taixiang; Wang, Qi; Xi, Hongjian

2014-01-01

We will discuss nonoscillatory solutions to the n-dimensional functional system of neutral type dynamic equations on time scales. We will establish some sufficient conditions for nonoscillatory solutions with the property lim(t → ∞) x(i) (t) = 0, i = 1, 2,…, n.

Extreme-volatility dynamics in crude oil markets

NASA Astrophysics Data System (ADS)

Jiang, Xiong-Fei; Zheng, Bo; Qiu, Tian; Ren, Fei

2017-02-01

Based on concepts and methods from statistical physics, we investigate extreme-volatility dynamics in the crude oil markets, using the high-frequency data from 2006 to 2010 and the daily data from 1986 to 2016. The dynamic relaxation of extreme volatilities is described by a power law, whose exponents usually depend on the magnitude of extreme volatilities. In particular, the relaxation before and after extreme volatilities is time-reversal symmetric at the high-frequency time scale, but time-reversal asymmetric at the daily time scale. This time-reversal asymmetry is mainly induced by exogenous events. However, the dynamic relaxation after exogenous events exhibits the same characteristics as that after endogenous events. An interacting herding model both with and without exogenous driving forces could qualitatively describe the extreme-volatility dynamics.

Multiscale functions, scale dynamics, and applications to partial differential equations

NASA Astrophysics Data System (ADS)

Cresson, Jacky; Pierret, Frédéric

2016-05-01

Modeling phenomena from experimental data always begins with a choice of hypothesis on the observed dynamics such as determinism, randomness, and differentiability. Depending on these choices, different behaviors can be observed. The natural question associated to the modeling problem is the following: "With a finite set of data concerning a phenomenon, can we recover its underlying nature? From this problem, we introduce in this paper the definition of multi-scale functions, scale calculus, and scale dynamics based on the time scale calculus [see Bohner, M. and Peterson, A., Dynamic Equations on Time Scales: An Introduction with Applications (Springer Science & Business Media, 2001)] which is used to introduce the notion of scale equations. These definitions will be illustrated on the multi-scale Okamoto's functions. Scale equations are analysed using scale regimes and the notion of asymptotic model for a scale equation under a particular scale regime. The introduced formalism explains why a single scale equation can produce distinct continuous models even if the equation is scale invariant. Typical examples of such equations are given by the scale Euler-Lagrange equation. We illustrate our results using the scale Newton's equation which gives rise to a non-linear diffusion equation or a non-linear Schrödinger equation as asymptotic continuous models depending on the particular fractional scale regime which is considered.

Nonadiabatic dynamics of electron transfer in solution: Explicit and implicit solvent treatments that include multiple relaxation time scales

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

Schwerdtfeger, Christine A.; Soudackov, Alexander V.; Hammes-Schiffer, Sharon, E-mail: shs3@illinois.edu

2014-01-21

The development of efficient theoretical methods for describing electron transfer (ET) reactions in condensed phases is important for a variety of chemical and biological applications. Previously, dynamical dielectric continuum theory was used to derive Langevin equations for a single collective solvent coordinate describing ET in a polar solvent. In this theory, the parameters are directly related to the physical properties of the system and can be determined from experimental data or explicit molecular dynamics simulations. Herein, we combine these Langevin equations with surface hopping nonadiabatic dynamics methods to calculate the rate constants for thermal ET reactions in polar solvents formore » a wide range of electronic couplings and reaction free energies. Comparison of explicit and implicit solvent calculations illustrates that the mapping from explicit to implicit solvent models is valid even for solvents exhibiting complex relaxation behavior with multiple relaxation time scales and a short-time inertial response. The rate constants calculated for implicit solvent models with a single solvent relaxation time scale corresponding to water, acetonitrile, and methanol agree well with analytical theories in the Golden rule and solvent-controlled regimes, as well as in the intermediate regime. The implicit solvent models with two relaxation time scales are in qualitative agreement with the analytical theories but quantitatively overestimate the rate constants compared to these theories. Analysis of these simulations elucidates the importance of multiple relaxation time scales and the inertial component of the solvent response, as well as potential shortcomings of the analytical theories based on single time scale solvent relaxation models. This implicit solvent approach will enable the simulation of a wide range of ET reactions via the stochastic dynamics of a single collective solvent coordinate with parameters that are relevant to experimentally accessible systems.« less

Fractal Dynamics of Heartbeat Interval Fluctuations in Health and Disease

NASA Astrophysics Data System (ADS)

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

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

Nonoscillatory Solutions for System of Neutral Dynamic Equations on Time Scales

PubMed Central

Chen, Zhanhe; Wang, Qi; Xi, Hongjian

2014-01-01

We will discuss nonoscillatory solutions to the n-dimensional functional system of neutral type dynamic equations on time scales. We will establish some sufficient conditions for nonoscillatory solutions with the property limt→∞ ⁡x i(t) = 0, i = 1, 2,…, n. PMID:24757436

Dynamics in entangled polyethylene melts [Multi time scale dynamics in entangled polyethylene melts

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

Salerno, K. Michael; Agrawal, Anupriya; Peters, Brandon L.

Polymer dynamics creates distinctive viscoelastic behavior as a result of a coupled interplay of motion at the atomic length scale and motion of the entire macromolecule. Capturing the broad time and length scales of polymeric motion however, remains a challenge. Using linear polyethylene as a model system, we probe the effects of the degree of coarse graining on polymer dynamics. Coarse-grained (CG) potentials are derived using iterative Boltzmann inversion with λ methylene groups per CG bead (denoted CGλ) with λ = 2,3,4 and 6 from a fully-atomistic polyethylene melt simulation. By rescaling time in the CG models by a factormore » α, the chain mobility for the atomistic and CG models match. We show that independent of the degree of coarse graining, all measured static and dynamic properties are essentially the same once the dynamic scaling factor α and a non-crossing constraint for the CG6 model are included. The speedup of the CG4 model is about 3 times that of the CG3 model and is comparable to that of the CG6 model. Furthermore, using these CG models we were able to reach times of over 500 μs, allowing us to measure a number of quantities, including the stress relaxation function, plateau modulus and shear viscosity, and compare directly to experiment.« less

Dynamics in entangled polyethylene melts [Multi time scale dynamics in entangled polyethylene melts

DOE PAGES

Salerno, K. Michael; Agrawal, Anupriya; Peters, Brandon L.; ...

2016-10-10

Polymer dynamics creates distinctive viscoelastic behavior as a result of a coupled interplay of motion at the atomic length scale and motion of the entire macromolecule. Capturing the broad time and length scales of polymeric motion however, remains a challenge. Using linear polyethylene as a model system, we probe the effects of the degree of coarse graining on polymer dynamics. Coarse-grained (CG) potentials are derived using iterative Boltzmann inversion with λ methylene groups per CG bead (denoted CGλ) with λ = 2,3,4 and 6 from a fully-atomistic polyethylene melt simulation. By rescaling time in the CG models by a factormore » α, the chain mobility for the atomistic and CG models match. We show that independent of the degree of coarse graining, all measured static and dynamic properties are essentially the same once the dynamic scaling factor α and a non-crossing constraint for the CG6 model are included. The speedup of the CG4 model is about 3 times that of the CG3 model and is comparable to that of the CG6 model. Furthermore, using these CG models we were able to reach times of over 500 μs, allowing us to measure a number of quantities, including the stress relaxation function, plateau modulus and shear viscosity, and compare directly to experiment.« less

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.

Entrenched time delays versus accelerating opinion dynamics: are advanced democracies inherently unstable?

NASA Astrophysics Data System (ADS)

Gros, Claudius

2017-11-01

Modern societies face the challenge that the time scale of opinion formation is continuously accelerating in contrast to the time scale of political decision making. With the latter remaining of the order of the election cycle we examine here the case that the political state of a society is determined by the continuously evolving values of the electorate. Given this assumption we show that the time lags inherent in the election cycle will inevitable lead to political instabilities for advanced democracies characterized both by an accelerating pace of opinion dynamics and by high sensibilities (political correctness) to deviations from mainstream values. Our result is based on the observation that dynamical systems become generically unstable whenever time delays become comparable to the time it takes to adapt to the steady state. The time needed to recover from external shocks grows in addition dramatically close to the transition. Our estimates for the order of magnitude of the involved time scales indicate that socio-political instabilities may develop once the aggregate time scale for the evolution of the political values of the electorate falls below 7-15 months.

Dynamic ocean management increases the efficiency and efficacy of fisheries management.

PubMed

Dunn, Daniel C; Maxwell, Sara M; Boustany, Andre M; Halpin, Patrick N

2016-01-19

In response to the inherent dynamic nature of the oceans and continuing difficulty in managing ecosystem impacts of fisheries, interest in the concept of dynamic ocean management, or real-time management of ocean resources, has accelerated in the last several years. However, scientists have yet to quantitatively assess the efficiency of dynamic management over static management. Of particular interest is how scale influences effectiveness, both in terms of how it reflects underlying ecological processes and how this relates to potential efficiency gains. Here, we address the empirical evidence gap and further the ecological theory underpinning dynamic management. We illustrate, through the simulation of closures across a range of spatiotemporal scales, that dynamic ocean management can address previously intractable problems at scales associated with coactive and social patterns (e.g., competition, predation, niche partitioning, parasitism, and social aggregations). Furthermore, it can significantly improve the efficiency of management: as the resolution of the closures used increases (i.e., as the closures become more targeted), the percentage of target catch forgone or displaced decreases, the reduction ratio (bycatch/catch) increases, and the total time-area required to achieve the desired bycatch reduction decreases. In the scenario examined, coarser scale management measures (annual time-area closures and monthly full-fishery closures) would displace up to four to five times the target catch and require 100-200 times more square kilometer-days of closure than dynamic measures (grid-based closures and move-on rules). To achieve similar reductions in juvenile bycatch, the fishery would forgo or displace between USD 15-52 million in landings using a static approach over a dynamic management approach.

Dynamics of an elastic sphere containing a thin creeping region and immersed in an acoustic region for similar viscous-elastic and acoustic time- and length-scales

NASA Astrophysics Data System (ADS)

Gat, Amir; Friedman, Yonathan

2017-11-01

The characteristic time of low-Reynolds number fluid-structure interaction scales linearly with the ratio of fluid viscosity to solid Young's modulus. For sufficiently large values of Young's modulus, both time- and length-scales of the viscous-elastic dynamics may be similar to acoustic time- and length-scales. However, the requirement of dominant viscous effects limits the validity of such regimes to micro-configurations. We here study the dynamics of an acoustic plane wave impinging on the surface of a layered sphere, immersed within an inviscid fluid, and composed of an inner elastic sphere, a creeping fluid layer and an external elastic shell. We focus on configurations with similar viscous-elastic and acoustic time- and length-scales, where the viscous-elastic speed of interaction between the creeping layer and the elastic regions is similar to the speed of sound. By expanding the linearized spherical Reynolds equation into the relevant spectral series solution for the hyperbolic elastic regions, a global stiffness matrix of the layered elastic sphere was obtained. This work relates viscous-elastic dynamics to acoustic scattering and may pave the way to the design of novel meta-materials with unique acoustic properties. ISF 818/13.

Dynamics of two-dimensional monolayer water confined in hydrophobic and charged environments.

PubMed

Kumar, Pradeep; Han, Sungho

2012-09-21

We perform molecular dynamics simulations to study the effect of charged surfaces on the intermediate and long time dynamics of water in nanoconfinements. Here, we use the transferable interaction potential with five points (TIP5P) model of a water molecule confined in both hydrophobic and charged surfaces. For a single molecular layer of water between the surfaces, we find that the temperature dependence of the lateral diffusion constant of water up to very high temperatures remains Arrhenius with a high activation energy. In case of charged surfaces, however, the dynamics of water in the intermediate time regime is drastically modified presumably due to the transient coupling of dipoles of water molecules with electric field fluctuations induced by charges on the confining surfaces. Specifically, the lateral mean square displacements display a distinct super-diffusive behavior at intermediate time scale, defined as the time scale between ballistic and diffusive regimes. This change in the intermediate time-scale dynamics in the charged confinement leads to the enhancement of long-time dynamics as reflected in increasing diffusion constant. We introduce a simple model for a possible explanation of the super-diffusive behavior and find it to be in good agreement with our simulation results. Furthermore, we find that confinement and the surface polarity enhance the low frequency vibration in confinement compared to bulk water. By introducing a new effective length scale of coupling between translational and orientational motions, we find that the length scale increases with the increasing strength of the surface polarity. Further, we calculate the correlation between the diffusion constant and the excess entropy and find a disordering effect of polar surfaces on the structure of water. Finally, we find that the empirical relation between the diffusion constant and the excess entropy holds for a monolayer of water in nanoconfinement.

Capturing Structural Dynamics in Crystalline Silicon Using Chirped Electrons from a Laser Wakefield Accelerator

PubMed Central

He, Z.-H.; Beaurepaire, B.; Nees, J. A.; Gallé, G.; Scott, S. A.; Pérez, J. R. Sánchez; Lagally, M. G.; Krushelnick, K.; Thomas, A. G. R.; Faure, J.

2016-01-01

Recent progress in laser wakefield acceleration has led to the emergence of a new generation of electron and X-ray sources that may have enormous benefits for ultrafast science. These novel sources promise to become indispensable tools for the investigation of structural dynamics on the femtosecond time scale, with spatial resolution on the atomic scale. Here, we demonstrate the use of laser-wakefield-accelerated electron bunches for time-resolved electron diffraction measurements of the structural dynamics of single-crystal silicon nano-membranes pumped by an ultrafast laser pulse. In our proof-of-concept study, we resolve the silicon lattice dynamics on a picosecond time scale by deflecting the momentum-time correlated electrons in the diffraction peaks with a static magnetic field to obtain the time-dependent diffraction efficiency. Further improvements may lead to femtosecond temporal resolution, with negligible pump-probe jitter being possible with future laser-wakefield-accelerator ultrafast-electron-diffraction schemes. PMID:27824086

Consistent View of Protein Fluctuations from All-Atom Molecular Dynamics and Coarse-Grained Dynamics with Knowledge-Based Force-Field.

PubMed

Jamroz, Michal; Orozco, Modesto; Kolinski, Andrzej; Kmiecik, Sebastian

2013-01-08

It is widely recognized that atomistic Molecular Dynamics (MD), a classical simulation method, captures the essential physics of protein dynamics. That idea is supported by a theoretical study showing that various MD force-fields provide a consensus picture of protein fluctuations in aqueous solution [Rueda, M. et al. Proc. Natl. Acad. Sci. U.S.A. 2007, 104, 796-801]. However, atomistic MD cannot be applied to most biologically relevant processes due to its limitation to relatively short time scales. Much longer time scales can be accessed by properly designed coarse-grained models. We demonstrate that the aforementioned consensus view of protein dynamics from short (nanosecond) time scale MD simulations is fairly consistent with the dynamics of the coarse-grained protein model - the CABS model. The CABS model employs stochastic dynamics (a Monte Carlo method) and a knowledge-based force-field, which is not biased toward the native structure of a simulated protein. Since CABS-based dynamics allows for the simulation of entire folding (or multiple folding events) in a single run, integration of the CABS approach with all-atom MD promises a convenient (and computationally feasible) means for the long-time multiscale molecular modeling of protein systems with atomistic resolution.

Time-dependent vibrational spectral analysis of first principles trajectory of methylamine with wavelet transform.

PubMed

Biswas, Sohag; Mallik, Bhabani S

2017-04-12

The fluctuation dynamics of amine stretching frequencies, hydrogen bonds, dangling N-D bonds, and the orientation profile of the amine group of methylamine (MA) were investigated under ambient conditions by means of dispersion-corrected density functional theory-based first principles molecular dynamics (FPMD) simulations. Along with the dynamical properties, various equilibrium properties such as radial distribution function, spatial distribution function, combined radial and angular distribution functions and hydrogen bonding were also calculated. The instantaneous stretching frequencies of amine groups were obtained by wavelet transform of the trajectory obtained from FPMD simulations. The frequency-structure correlation reveals that the amine stretching frequency is weakly correlated with the nearest nitrogen-deuterium distance. The frequency-frequency correlation function has a short time scale of around 110 fs and a longer time scale of about 1.15 ps. It was found that the short time scale originates from the underdamped motion of intact hydrogen bonds of MA pairs. However, the long time scale of the vibrational spectral diffusion of N-D modes is determined by the overall dynamics of hydrogen bonds as well as the dangling ND groups and the inertial rotation of the amine group of the molecule.

Evolution of correlation structure of industrial indices of U.S. equity markets.

PubMed

Buccheri, Giuseppe; Marmi, Stefano; Mantegna, Rosario N

2013-07-01

We investigate the dynamics of correlations present between pairs of industry indices of U.S. stocks traded in U.S. markets by studying correlation-based networks and spectral properties of the correlation matrix. The study is performed by using 49 industry index time series computed by K. French and E. Fama during the time period from July 1969 to December 2011, which spans more than 40 years. We show that the correlation between industry indices presents both a fast and a slow dynamics. The slow dynamics has a time scale longer than 5 years, showing that a different degree of diversification of the investment is possible in different periods of time. Moreover, we also detect a fast dynamics associated with exogenous or endogenous events. The fast time scale we use is a monthly time scale and the evaluation time period is a 3-month time period. By investigating the correlation dynamics monthly, we are able to detect two examples of fast variations in the first and second eigenvalue of the correlation matrix. The first occurs during the dot-com bubble (from March 1999 to April 2001) and the second occurs during the period of highest impact of the subprime crisis (from August 2008 to August 2009).

Evolution of correlation structure of industrial indices of U.S. equity markets

NASA Astrophysics Data System (ADS)

Buccheri, Giuseppe; Marmi, Stefano; Mantegna, Rosario N.

2013-07-01

We investigate the dynamics of correlations present between pairs of industry indices of U.S. stocks traded in U.S. markets by studying correlation-based networks and spectral properties of the correlation matrix. The study is performed by using 49 industry index time series computed by K. French and E. Fama during the time period from July 1969 to December 2011, which spans more than 40 years. We show that the correlation between industry indices presents both a fast and a slow dynamics. The slow dynamics has a time scale longer than 5 years, showing that a different degree of diversification of the investment is possible in different periods of time. Moreover, we also detect a fast dynamics associated with exogenous or endogenous events. The fast time scale we use is a monthly time scale and the evaluation time period is a 3-month time period. By investigating the correlation dynamics monthly, we are able to detect two examples of fast variations in the first and second eigenvalue of the correlation matrix. The first occurs during the dot-com bubble (from March 1999 to April 2001) and the second occurs during the period of highest impact of the subprime crisis (from August 2008 to August 2009).

Detecting transitions in protein dynamics using a recurrence quantification analysis based bootstrap method.

PubMed

Karain, Wael I

2017-11-28

Proteins undergo conformational transitions over different time scales. These transitions are closely intertwined with the protein's function. Numerous standard techniques such as principal component analysis are used to detect these transitions in molecular dynamics simulations. In this work, we add a new method that has the ability to detect transitions in dynamics based on the recurrences in the dynamical system. It combines bootstrapping and recurrence quantification analysis. We start from the assumption that a protein has a "baseline" recurrence structure over a given period of time. Any statistically significant deviation from this recurrence structure, as inferred from complexity measures provided by recurrence quantification analysis, is considered a transition in the dynamics of the protein. We apply this technique to a 132 ns long molecular dynamics simulation of the β-Lactamase Inhibitory Protein BLIP. We are able to detect conformational transitions in the nanosecond range in the recurrence dynamics of the BLIP protein during the simulation. The results compare favorably to those extracted using the principal component analysis technique. The recurrence quantification analysis based bootstrap technique is able to detect transitions between different dynamics states for a protein over different time scales. It is not limited to linear dynamics regimes, and can be generalized to any time scale. It also has the potential to be used to cluster frames in molecular dynamics trajectories according to the nature of their recurrence dynamics. One shortcoming for this method is the need to have large enough time windows to insure good statistical quality for the recurrence complexity measures needed to detect the transitions.

An Acrobatic Substrate Metamorphosis Reveals a Requirement for Substrate Conformational Dynamics in Trypsin Proteolysis*

PubMed Central

Kayode, Olumide; Wang, Ruiying; Pendlebury, Devon F.; Cohen, Itay; Henin, Rachel D.; Hockla, Alexandra; Soares, Alexei S.; Papo, Niv; Caulfield, Thomas R.; Radisky, Evette S.

2016-01-01

The molecular basis of enzyme catalytic power and specificity derives from dynamic interactions between enzyme and substrate during catalysis. Although considerable effort has been devoted to understanding how conformational dynamics within enzymes affect catalysis, the role of conformational dynamics within protein substrates has not been addressed. Here, we examine the importance of substrate dynamics in the cleavage of Kunitz-bovine pancreatic trypsin inhibitor protease inhibitors by mesotrypsin, finding that the varied conformational dynamics of structurally similar substrates can profoundly impact the rate of catalysis. A 1.4-Å crystal structure of a mesotrypsin-product complex formed with a rapidly cleaved substrate reveals a dramatic conformational change in the substrate upon proteolysis. By using long all-atom molecular dynamics simulations of acyl-enzyme intermediates with proteolysis rates spanning 3 orders of magnitude, we identify global and local dynamic features of substrates on the nanosecond-microsecond time scale that correlate with enzymatic rates and explain differential susceptibility to proteolysis. By integrating multiple enhanced sampling methods for molecular dynamics, we model a viable conformational pathway between substrate-like and product-like states, linking substrate dynamics on the nanosecond-microsecond time scale with large collective substrate motions on the much slower time scale of catalysis. Our findings implicate substrate flexibility as a critical determinant of catalysis. PMID:27810896

Small-time Scale Network Traffic Prediction Based on Complex-valued Neural Network

NASA Astrophysics Data System (ADS)

Yang, Bin

2017-07-01

Accurate models play an important role in capturing the significant characteristics of the network traffic, analyzing the network dynamic, and improving the forecasting accuracy for system dynamics. In this study, complex-valued neural network (CVNN) model is proposed to further improve the accuracy of small-time scale network traffic forecasting. Artificial bee colony (ABC) algorithm is proposed to optimize the complex-valued and real-valued parameters of CVNN model. Small-scale traffic measurements data namely the TCP traffic data is used to test the performance of CVNN model. Experimental results reveal that CVNN model forecasts the small-time scale network traffic measurement data very accurately

Rippling ultrafast dynamics of suspended 2D monolayers, graphene

PubMed Central

Hu, Jianbo; Vanacore, Giovanni M.; Cepellotti, Andrea; Marzari, Nicola; Zewail, Ahmed H.

2016-01-01

Here, using ultrafast electron crystallography (UEC), we report the observation of rippling dynamics in suspended monolayer graphene, the prototypical and most-studied 2D material. The high scattering cross-section for electron/matter interaction, the atomic-scale spatial resolution, and the ultrafast temporal resolution of UEC represent the key elements that make this technique a unique tool for the dynamic investigation of 2D materials, and nanostructures in general. We find that, at early time after the ultrafast optical excitation, graphene undergoes a lattice expansion on a time scale of 5 ps, which is due to the excitation of short-wavelength in-plane acoustic phonon modes that stretch the graphene plane. On a longer time scale, a slower thermal contraction with a time constant of 50 ps is observed and associated with the excitation of out-of-plane phonon modes, which drive the lattice toward thermal equilibrium with the well-known negative thermal expansion coefficient of graphene. From our results and first-principles lattice dynamics and out-of-equilibrium relaxation calculations, we quantitatively elucidate the deformation dynamics of the graphene unit cell. PMID:27791028

Rippling ultrafast dynamics of suspended 2D monolayers, graphene.

PubMed

Hu, Jianbo; Vanacore, Giovanni M; Cepellotti, Andrea; Marzari, Nicola; Zewail, Ahmed H

2016-10-25

Here, using ultrafast electron crystallography (UEC), we report the observation of rippling dynamics in suspended monolayer graphene, the prototypical and most-studied 2D material. The high scattering cross-section for electron/matter interaction, the atomic-scale spatial resolution, and the ultrafast temporal resolution of UEC represent the key elements that make this technique a unique tool for the dynamic investigation of 2D materials, and nanostructures in general. We find that, at early time after the ultrafast optical excitation, graphene undergoes a lattice expansion on a time scale of 5 ps, which is due to the excitation of short-wavelength in-plane acoustic phonon modes that stretch the graphene plane. On a longer time scale, a slower thermal contraction with a time constant of 50 ps is observed and associated with the excitation of out-of-plane phonon modes, which drive the lattice toward thermal equilibrium with the well-known negative thermal expansion coefficient of graphene. From our results and first-principles lattice dynamics and out-of-equilibrium relaxation calculations, we quantitatively elucidate the deformation dynamics of the graphene unit cell.

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.

Multiscale analysis of the intensity fluctuation in a time series of dynamic speckle patterns.

PubMed

Federico, Alejandro; Kaufmann, Guillermo H

2007-04-10

We propose the application of a method based on the discrete wavelet transform to detect, identify, and measure scaling behavior in dynamic speckle. The multiscale phenomena presented by a sample and displayed by its speckle activity are analyzed by processing the time series of dynamic speckle patterns. The scaling analysis is applied to the temporal fluctuation of the speckle intensity and also to the two derived data sets generated by its magnitude and sign. The application of the method is illustrated by analyzing paint-drying processes and bruising in apples. The results are discussed taking into account the different time organizations obtained for the scaling behavior of the magnitude and the sign of the intensity fluctuation.

Performance limitations of bilateral force reflection imposed by operator dynamic characteristics

NASA Technical Reports Server (NTRS)

Chapel, Jim D.

1989-01-01

A linearized, single-axis model is presented for bilateral force reflection which facilitates investigation into the effects of manipulator, operator, and task dynamics, as well as time delay and gain scaling. Structural similarities are noted between this model and impedance control. Stability results based upon this model impose requirements upon operator dynamic characteristics as functions of system time delay and environmental stiffness. An experimental characterization reveals the limited capabilities of the human operator to meet these requirements. A procedure is presented for determining the force reflection gain scaling required to provide stability and acceptable operator workload. This procedure is applied to a system with dynamics typical of a space manipulator, and the required gain scaling is presented as a function of environmental stiffness.

Is Earth F**ked? Dynamical Futility of Global Environmental Management and Possibilities for Sustainability via Direct Action Activism

NASA Astrophysics Data System (ADS)

wErnEr, B.

2012-12-01

Environmental challenges are dynamically generated within the dominant global culture principally by the mismatch between short-time-scale market and political forces driving resource extraction/use and longer-time-scale accommodations of the Earth system to these changes. Increasing resource demand is leading to the development of two-way, nonlinear interactions between human societies and environmental systems that are becoming global in extent, either through globalized markets and other institutions or through coupling to global environmental systems such as climate. These trends are further intensified by dissipation-reducing technological advances in transactions, communication and transport, which suppress emergence of longer-time-scale economic and political levels of description and facilitate long-distance connections, and by predictive environmental modeling, which strengthens human connections to a short-time-scale virtual Earth, and weakens connections to the longer time scales of the actual Earth. Environmental management seeks to steer fast scale economic and political interests of a coupled human-environmental system towards longer-time-scale consideration of benefits and costs by operating within the confines of the dominant culture using a linear, engineering-type connection to the system. Perhaps as evidenced by widespread inability to meaningfully address such global environmental challenges as climate change and soil degradation, nonlinear connections reduce the ability of managers to operate outside coupled human-environmental systems, decreasing their effectiveness in steering towards sustainable interactions and resulting in managers slaved to short-to-intermediate-term interests. In sum, the dynamics of the global coupled human-environmental system within the dominant culture precludes management for stable, sustainable pathways and promotes instability. Environmental direct action, resistance taken from outside the dominant culture, as in protests, blockades and sabotage by indigenous peoples, workers, anarchists and other activist groups, increases dissipation within the coupled system over fast to intermediate scales and pushes for changes in the dominant culture that favor transition to a stable, sustainable attractor. These dynamical relationships are illustrated and explored using a numerical model that simulates the short-, intermediate- and long-time-scale dynamics of the coupled human-environmental system. At fast scales, economic and political interests exploit environmental resources through a maze of environmental management and resistance, guided by virtual Earth predictions. At intermediate scales, managers become slaved to economic and political interests, which adapt to and repress resistance, and resistance is guided by patterns of environmental destruction. At slow scales, resistance interacts with the cultural context, which co-evolves with the environment. The transition from unstable dynamics to sustainability is sensitively dependent on the level of participation in and repression of resistance. Because of their differing impact inside and outside the dominant culture, virtual Earth predictions can either promote or oppose sustainability. Supported by the National Science Foundation, Geomorphology and Land Use Dynamics Program.

Phase ordering dynamics of reconstituting particles

NASA Astrophysics Data System (ADS)

Albarracín, F. A. Gómez; Rosales, H. D.; Grynberg, M. D.

2017-06-01

We consider the large-time dynamics of one-dimensional processes involving adsorption and desorption of extended hard-core particles (dimers, trimers, ..., k -mers), while interacting through their constituent monomers. Desorption can occur whether or not these latter adsorbed together, which leads to reconstitution of k -mers and the appearance of sectors of motion with nonlocal conservation laws for k ≥3 . Dynamic exponents of the sector including the empty chain are evaluated by finite-size scaling analyses of the relaxation times embodied in the spectral gaps of evolution operators. For attractive interactions it is found that in the low-temperature limit such time scales converge to those of the Glauber dynamics, thus suggesting a diffusive universality class for k ≥2 . This is also tested by simulated quenches down to T =0 , where a common scaling function emerges. By contrast, under repulsive interactions the low-temperature dynamics is characterized by metastable states which decay subdiffusively to a highly degenerate and partially jammed phase.

Shear banding leads to accelerated aging dynamics in a metallic glass

NASA Astrophysics Data System (ADS)

Küchemann, Stefan; Liu, Chaoyang; Dufresne, Eric M.; Shin, Jeremy; Maaß, Robert

2018-01-01

Traditionally, strain localization in metallic glasses is related to the thickness of the shear defect, which is confined to the nanometer scale. Using site-specific x-ray photon correlation spectroscopy, we reveal significantly accelerated relaxation dynamics around a shear band in a metallic glass at a length scale that is orders of magnitude larger than the defect itself. The relaxation time in the shear-band vicinity is up to ten times smaller compared to the as-cast matrix, and the relaxation dynamics occurs in a characteristic three-stage aging response that manifests itself in the temperature-dependent shape parameter known from classical stretched exponential relaxation dynamics of disordered materials. We demonstrate that the time-dependent correlation functions describing the aging at different temperatures can be captured and collapsed using simple scaling functions. These insights highlight how a ubiquitous nanoscale strain-localization mechanism in metallic glasses leads to a fundamental change of the relaxation dynamics at the mesoscale.

Communication: Polymer entanglement dynamics: Role of attractive interactions

DOE PAGES

Grest, Gary S.

2016-10-10

The coupled dynamics of entangled polymers, which span broad time and length scales, govern their unique viscoelastic properties. To follow chain mobility by numerical simulations from the intermediate Rouse and reptation regimes to the late time diffusive regime, highly coarse grained models with purely repulsive interactions between monomers are widely used since they are computationally the most efficient. In this paper, using large scale molecular dynamics simulations, the effect of including the attractive interaction between monomers on the dynamics of entangled polymer melts is explored for the first time over a wide temperature range. Attractive interactions have little effect onmore » the local packing for all temperatures T and on the chain mobility for T higher than about twice the glass transition T g. Finally, these results, across a broad range of molecular weight, show that to study the dynamics of entangled polymer melts, the interactions can be treated as pure repulsive, confirming a posteriori the validity of previous studies and opening the way to new large scale numerical simulations.« less

Shoreline Position Dynamics: Measurement and Analysis

NASA Astrophysics Data System (ADS)

Barton, C. C.; Rigling, B.; Hunter, N.; Tebbens, S. F.

2012-12-01

The dynamics of sandy shoreline position is a fundamental property of complex beach face processes and is characterized by the power scaling exponent. Spectral analysis was performed on the temporal position of four sandy shorelines extracted from four shore perpendicular profiles each resurveyed approximately seven times per year over twenty-seven years at the Field Research Facility (FRF) by the U.S. Army Corps of Engineers, located at Kitty Hawk, NC. The four shorelines we studied are mean-higher-high-water (MHHW), mean-high-water (MHW), and mean-low-water (MLW) and mean-lower-low-water (MLLW) with elevations of 0.75m, 0.65m, -0.33m, and -0.37m respectively, relative to the NGVD29 geodetic datum. Spectral analysis used to quantify scaling exponents requires data evenly spaced in time. Our previous studies of shoreline dynamics used the Lomb Periodogram method for spectral analysis, which we now show does not return the correct scaling exponent for unevenly spaced data. New to this study is the use of slotted resampling and a linear predictor to construct an evenly spaced data set from an unevenly spaced data set which has been shown with synthetic data to return correct values of the scaling exponents. A periodogram linear regression (PLR) estimate is used to determine the scaling exponent β of the constructed evenly spaced time series. This study shows that sandy shoreline position exhibits nonlinear self-affine dynamics through time. The times series of each of the four shorelines has scaling exponents ranging as follows: MHHW, β = 1.3-2.2; MHW, β = 1.3-2.1; MLW, β = 1.2-1.6; and MLLW, β = 1.2-1.6. Time series with β greater than 1 are non-stationary (mean and standard deviation are not constant through time) and are increasingly internally correlated with increasing β. The range of scaling exponents of the MLW and MLLW shorelines, near β = 1.5, is indicative of a diffusion process. The range of scaling exponents for the MHW and MHHW shorelines indicates spatially variable dynamics higher on the beach face.

Nonadiabatic nuclear dynamics of the ammonia cation studied by surface hopping classical trajectory calculations

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

Belyaev, Andrey K., E-mail: belyaev@herzen.spb.ru; Domcke, Wolfgang, E-mail: wolfgang.domcke@ch.tum.de; Lasser, Caroline, E-mail: classer@ma.tum.de

The Landau–Zener (LZ) type classical-trajectory surface-hopping algorithm is applied to the nonadiabatic nuclear dynamics of the ammonia cation after photoionization of the ground-state neutral molecule to the excited states of the cation. The algorithm employs a recently proposed formula for nonadiabatic LZ transition probabilities derived from the adiabatic potential energy surfaces. The evolution of the populations of the ground state and the two lowest excited adiabatic states is calculated up to 200 fs. The results agree well with quantum simulations available for the first 100 fs based on the same potential energy surfaces. Three different time scales are detected formore » the nuclear dynamics: Ultrafast Jahn–Teller dynamics between the excited states on a 5 fs time scale; fast transitions between the excited state and the ground state within a time scale of 20 fs; and relatively slow partial conversion of a first-excited-state population to the ground state within a time scale of 100 fs. Beyond 100 fs, the adiabatic electronic populations are nearly constant due to a dynamic equilibrium between the three states. The ultrafast nonradiative decay of the excited-state populations provides a qualitative explanation of the experimental evidence that the ammonia cation is nonfluorescent.« less

Dynamic and Thermal Turbulent Time Scale Modelling for Homogeneous Shear Flows

NASA Technical Reports Server (NTRS)

Schwab, John R.; Lakshminarayana, Budugur

1994-01-01

A new turbulence model, based upon dynamic and thermal turbulent time scale transport equations, is developed and applied to homogeneous shear flows with constant velocity and temperature gradients. The new model comprises transport equations for k, the turbulent kinetic energy; tau, the dynamic time scale; k(sub theta), the fluctuating temperature variance; and tau(sub theta), the thermal time scale. It offers conceptually parallel modeling of the dynamic and thermal turbulence at the two equation level, and eliminates the customary prescription of an empirical turbulent Prandtl number, Pr(sub t), thus permitting a more generalized prediction capability for turbulent heat transfer in complex flows and geometries. The new model also incorporates constitutive relations, based upon invariant theory, that allow the effects of nonequilibrium to modify the primary coefficients for the turbulent shear stress and heat flux. Predictions of the new model, along with those from two other similar models, are compared with experimental data for decaying homogeneous dynamic and thermal turbulence, homogeneous turbulence with constant temperature gradient, and homogeneous turbulence with constant temperature gradient and constant velocity gradient. The new model offers improvement in agreement with the data for most cases considered in this work, although it was no better than the other models for several cases where all the models performed poorly.

Prediction of Time Response of Electrowetting

NASA Astrophysics Data System (ADS)

Lee, Seung Jun; Hong, Jiwoo; Kang, Kwan Hyoung

2009-11-01

It is very important to predict the time response of electrowetting-based devices, such as liquid lenses, reflective displays, and optical switches. We investigated the time response of electrowetting, based on an analytical and a numerical method, to find out characteristic scales and a scaling law for the switching time. For this, spreading process of a sessile droplet was analyzed based on the domain perturbation method. First, we considered the case of weakly viscous fluids. The analytical result for the spreading process was compared with experimental results, which showed very good agreement in overall time response. It was shown that the overall dynamics is governed by P2 shape mode. We derived characteristic scales combining the droplet volume, density, and surface tension. The overall dynamic process was scaled quite well by the scales. A scaling law was derived from the analytical solution and was verified experimentally. We also suggest a scaling law for highly viscous liquids, based on results of numerical analysis for the electrowetting-actuated spreading process.

Oscillation criteria for half-linear dynamic equations on time scales

NASA Astrophysics Data System (ADS)

Hassan, Taher S.

2008-09-01

This paper is concerned with oscillation of the second-order half-linear dynamic equation(r(t)(x[Delta])[gamma])[Delta]+p(t)x[gamma](t)=0, on a time scale where [gamma] is the quotient of odd positive integers, r(t) and p(t) are positive rd-continuous functions on . Our results solve a problem posed by [R.P. Agarwal, D. O'Regan, S.H. Saker, Philos-type oscillation criteria for second-order half linear dynamic equations, Rocky Mountain J. Math. 37 (2007) 1085-1104; S.H. Saker, Oscillation criteria of second order half-linear dynamic equations on time scales, J. Comput. Appl. Math. 177 (2005) 375-387] and our results in the special cases when and involve and improve some oscillation results for second-order differential and difference equations; and when , and , etc., our oscillation results are essentially newE Some examples illustrating the importance of our results are also included.

Scaling Relations and Self-Similarity of 3-Dimensional Reynolds-Averaged Navier-Stokes Equations.

PubMed

Ercan, Ali; Kavvas, M Levent

2017-07-25

Scaling conditions to achieve self-similar solutions of 3-Dimensional (3D) Reynolds-Averaged Navier-Stokes Equations, as an initial and boundary value problem, are obtained by utilizing Lie Group of Point Scaling Transformations. By means of an open-source Navier-Stokes solver and the derived self-similarity conditions, we demonstrated self-similarity within the time variation of flow dynamics for a rigid-lid cavity problem under both up-scaled and down-scaled domains. The strength of the proposed approach lies in its ability to consider the underlying flow dynamics through not only from the governing equations under consideration but also from the initial and boundary conditions, hence allowing to obtain perfect self-similarity in different time and space scales. The proposed methodology can be a valuable tool in obtaining self-similar flow dynamics under preferred level of detail, which can be represented by initial and boundary value problems under specific assumptions.

Slow dynamics in protein fluctuations revealed by time-structure based independent component analysis: The case of domain motions

NASA Astrophysics Data System (ADS)

Naritomi, Yusuke; Fuchigami, Sotaro

2011-02-01

Protein dynamics on a long time scale was investigated using all-atom molecular dynamics (MD) simulation and time-structure based independent component analysis (tICA). We selected the lysine-, arginine-, ornithine-binding protein (LAO) as a target protein and focused on its domain motions in the open state. A MD simulation of the LAO in explicit water was performed for 600 ns, in which slow and large-amplitude domain motions of the LAO were observed. After extracting domain motions by rigid-body domain analysis, the tICA was applied to the obtained rigid-body trajectory, yielding slow modes of the LAO's domain motions in order of decreasing time scale. The slowest mode detected by the tICA represented not a closure motion described by a largest-amplitude mode determined by the principal component analysis but a twist motion with a time scale of tens of nanoseconds. The slow dynamics of the LAO were well described by only the slowest mode and were characterized by transitions between two basins. The results show that tICA is promising for describing and analyzing slow dynamics of proteins.

Slow dynamics in protein fluctuations revealed by time-structure based independent component analysis: the case of domain motions.

PubMed

Naritomi, Yusuke; Fuchigami, Sotaro

2011-02-14

Protein dynamics on a long time scale was investigated using all-atom molecular dynamics (MD) simulation and time-structure based independent component analysis (tICA). We selected the lysine-, arginine-, ornithine-binding protein (LAO) as a target protein and focused on its domain motions in the open state. A MD simulation of the LAO in explicit water was performed for 600 ns, in which slow and large-amplitude domain motions of the LAO were observed. After extracting domain motions by rigid-body domain analysis, the tICA was applied to the obtained rigid-body trajectory, yielding slow modes of the LAO's domain motions in order of decreasing time scale. The slowest mode detected by the tICA represented not a closure motion described by a largest-amplitude mode determined by the principal component analysis but a twist motion with a time scale of tens of nanoseconds. The slow dynamics of the LAO were well described by only the slowest mode and were characterized by transitions between two basins. The results show that tICA is promising for describing and analyzing slow dynamics of proteins.

Mapping hydration dynamics and coupled water-protein fluctuations around a protein surface

NASA Astrophysics Data System (ADS)

Zhang, Luyuan; Wang, Lijuan; Kao, Ya-Ting; Qiu, Weihong; Yang, Yi; Okobiah, Oghaghare; Zhong, Dongping

2009-03-01

Elucidation of the molecular mechanism of water-protein interactions is critical to understanding many fundamental aspects of protein science, such as protein folding and misfolding and enzyme catalysis. We recently carried out a global mapping of protein-surface hydration dynamics around a globular α-helical protein apomyoglobin. The intrinsic optical probe tryptophan was employed to scan the protein surface one at a time by site-specific mutagenesis. With femtosecond resolution, we mapped out the dynamics of water-protein interactions with more than 20 mutants and for two states, native and molten globular. A robust bimodal distribution of time scales was observed, representing two types of water motions: local relaxation and protein-coupled fluctuations. The time scales show a strong correlation with the local protein structural rigidity and chemical identity. We also resolved two distinct contributions to the overall Stokes-shifts from the two time scales. These results are significant to understanding the role of hydration water on protein structural stability, dynamics and function.

Identifying time scales for violation/preservation of Stokes-Einstein relation in supercooled water

PubMed Central

Kawasaki, Takeshi; Kim, Kang

2017-01-01

The violation of the Stokes-Einstein (SE) relation D ~ (η/T)−1 between the shear viscosity η and the translational diffusion constant D at temperature T is of great importance for characterizing anomalous dynamics of supercooled water. Determining which time scales play key roles in the SE violation remains elusive without the measurement of η. We provide comprehensive simulation results of the dynamic properties involving η and D in the TIP4P/2005 supercooled water. This enabled the thorough identification of the appropriate time scales for the SE relation Dη/T. In particular, it is demonstrated that the temperature dependence of various time scales associated with structural relaxation, hydrogen bond breakage, stress relaxation, and dynamic heterogeneities can be definitely classified into only two classes. That is, we propose the generalized SE relations that exhibit “violation” or “preservation.” The classification depends on the examined time scales that are coupled or decoupled with the diffusion. On the basis of the classification, we explain the physical origins of the violation in terms of the increase in the plateau modulus and the nonexponentiality of stress relaxation. This implies that the mechanism of SE violation is attributed to the attained solidity upon supercooling, which is in accord with the growth of non-Gaussianity and spatially heterogeneous dynamics. PMID:28835918

Centennial-scale fluctuations and regional complexity characterize Pacific salmon population dynamics over the past five centuries.

PubMed

Rogers, Lauren A; Schindler, Daniel E; Lisi, Peter J; Holtgrieve, Gordon W; Leavitt, Peter R; Bunting, Lynda; Finney, Bruce P; Selbie, Daniel T; Chen, Guangjie; Gregory-Eaves, Irene; Lisac, Mark J; Walsh, Patrick B

2013-01-29

Observational data from the past century have highlighted the importance of interdecadal modes of variability in fish population dynamics, but how these patterns of variation fit into a broader temporal and spatial context remains largely unknown. We analyzed time series of stable nitrogen isotopes from the sediments of 20 sockeye salmon nursery lakes across western Alaska to characterize temporal and spatial patterns in salmon abundance over the past ∼500 y. Although some stocks varied on interdecadal time scales (30- to 80-y cycles), centennial-scale variation, undetectable in modern-day catch records and survey data, has dominated salmon population dynamics over the past 500 y. Before 1900, variation in abundance was clearly not synchronous among stocks, and the only temporal signal common to lake sediment records from this region was the onset of commercial fishing in the late 1800s. Thus, historical changes in climate did not synchronize stock dynamics over centennial time scales, emphasizing that ecosystem complexity can produce a diversity of ecological responses to regional climate forcing. Our results show that marine fish populations may alternate between naturally driven periods of high and low abundance over time scales of decades to centuries and suggest that management models that assume time-invariant productivity or carrying capacity parameters may be poor representations of the biological reality in these systems.

Centennial-scale fluctuations and regional complexity characterize Pacific salmon population dynamics over the past five centuries

PubMed Central

Rogers, Lauren A.; Schindler, Daniel E.; Lisi, Peter J.; Holtgrieve, Gordon W.; Leavitt, Peter R.; Bunting, Lynda; Finney, Bruce P.; Selbie, Daniel T.; Chen, Guangjie; Gregory-Eaves, Irene; Lisac, Mark J.; Walsh, Patrick B.

2013-01-01

Observational data from the past century have highlighted the importance of interdecadal modes of variability in fish population dynamics, but how these patterns of variation fit into a broader temporal and spatial context remains largely unknown. We analyzed time series of stable nitrogen isotopes from the sediments of 20 sockeye salmon nursery lakes across western Alaska to characterize temporal and spatial patterns in salmon abundance over the past ∼500 y. Although some stocks varied on interdecadal time scales (30- to 80-y cycles), centennial-scale variation, undetectable in modern-day catch records and survey data, has dominated salmon population dynamics over the past 500 y. Before 1900, variation in abundance was clearly not synchronous among stocks, and the only temporal signal common to lake sediment records from this region was the onset of commercial fishing in the late 1800s. Thus, historical changes in climate did not synchronize stock dynamics over centennial time scales, emphasizing that ecosystem complexity can produce a diversity of ecological responses to regional climate forcing. Our results show that marine fish populations may alternate between naturally driven periods of high and low abundance over time scales of decades to centuries and suggest that management models that assume time-invariant productivity or carrying capacity parameters may be poor representations of the biological reality in these systems. PMID:23322737

Molecular dynamics on diffusive time scales from the phase-field-crystal equation.

PubMed

Chan, Pak Yuen; Goldenfeld, Nigel; Dantzig, Jon

2009-03-01

We extend the phase-field-crystal model to accommodate exact atomic configurations and vacancies by requiring the order parameter to be non-negative. The resulting theory dictates the number of atoms and describes the motion of each of them. By solving the dynamical equation of the model, which is a partial differential equation, we are essentially performing molecular dynamics simulations on diffusive time scales. To illustrate this approach, we calculate the two-point correlation function of a fluid.

Overcoming time scale and finite size limitations to compute nucleation rates from small scale well tempered metadynamics simulations.

PubMed

Salvalaglio, Matteo; Tiwary, Pratyush; Maggioni, Giovanni Maria; Mazzotti, Marco; Parrinello, Michele

2016-12-07

Condensation of a liquid droplet from a supersaturated vapour phase is initiated by a prototypical nucleation event. As such it is challenging to compute its rate from atomistic molecular dynamics simulations. In fact at realistic supersaturation conditions condensation occurs on time scales that far exceed what can be reached with conventional molecular dynamics methods. Another known problem in this context is the distortion of the free energy profile associated to nucleation due to the small, finite size of typical simulation boxes. In this work the problem of time scale is addressed with a recently developed enhanced sampling method while contextually correcting for finite size effects. We demonstrate our approach by studying the condensation of argon, and showing that characteristic nucleation times of the order of magnitude of hours can be reliably calculated. Nucleation rates spanning a range of 10 orders of magnitude are computed at moderate supersaturation levels, thus bridging the gap between what standard molecular dynamics simulations can do and real physical systems.

Overcoming time scale and finite size limitations to compute nucleation rates from small scale well tempered metadynamics simulations

NASA Astrophysics Data System (ADS)

Salvalaglio, Matteo; Tiwary, Pratyush; Maggioni, Giovanni Maria; Mazzotti, Marco; Parrinello, Michele

2016-12-01

Condensation of a liquid droplet from a supersaturated vapour phase is initiated by a prototypical nucleation event. As such it is challenging to compute its rate from atomistic molecular dynamics simulations. In fact at realistic supersaturation conditions condensation occurs on time scales that far exceed what can be reached with conventional molecular dynamics methods. Another known problem in this context is the distortion of the free energy profile associated to nucleation due to the small, finite size of typical simulation boxes. In this work the problem of time scale is addressed with a recently developed enhanced sampling method while contextually correcting for finite size effects. We demonstrate our approach by studying the condensation of argon, and showing that characteristic nucleation times of the order of magnitude of hours can be reliably calculated. Nucleation rates spanning a range of 10 orders of magnitude are computed at moderate supersaturation levels, thus bridging the gap between what standard molecular dynamics simulations can do and real physical systems.

Dynamics of Change and Change in Dynamics

PubMed Central

Boker, Steven M.; Staples, Angela D.; Hu, Yueqin

2017-01-01

A framework is presented for building and testing models of dynamic regulation by categorizing sources of differences between theories of dynamics. A distinction is made between the dynamics of change, i.e., how a system self–regulates on a short time scale, and change in dynamics, i.e., how those dynamics may themselves change over a longer time scale. In order to clarify the categories, models are first built to estimate individual differences in equilibrium value and equilibrium change. Next, models are presented in which there are individual differences in parameters of dynamics such as frequency of fluctuations, damping of fluctuations, and amplitude of fluctuations. Finally, models for within–person change in dynamics over time are proposed. Simulations demonstrating feasibility of these models are presented and OpenMx scripts for fitting these models have been made available in a downloadable archive along with scripts to simulate data so that a researcher may test a selected models’ feasibility within a chosen experimental design. PMID:29046764

Ultrafast dynamics of localized magnetic moments in the unconventional Mott insulator Sr 2IrO 4

DOE PAGES

Krupin, O.; Dakovski, G. L.; Kim, B. J.; ...

2016-06-16

Here, we report a time-resolved study of the ultrafast dynamics of the magnetic moments formed by themore » $${{J}_{\\text{eff}}}=1/2$$ states in Sr 2IrO 4 by directly probing the localized iridium 5d magnetic state through resonant x-ray diffraction. Using optical pump–hard x-ray probe measurements, two relaxation time scales were determined: a fast fluence-independent relaxation is found to take place on a time scale of 1.5 ps, followed by a slower relaxation on a time scale of 500 ps–1.5 ns.« less

Reaching extended length-scales with accelerated dynamics

NASA Astrophysics Data System (ADS)

Hubartt, Bradley; Shim, Yunsic; Amar, Jacques

2012-02-01

While temperature-accelerated dynamics (TAD) has been quite successful in extending the time-scales for non-equilibrium simulations of small systems, the computational time increases rapidly with system size. One possible solution to this problem, which we refer to as parTAD^1 is to use spatial decomposition combined with our previously developed semi-rigorous synchronous sublattice algorithm^2. However, while such an approach leads to significantly better scaling as a function of system-size, it also artificially limits the size of activated events and is not completely rigorous. Here we discuss progress we have made in developing an alternative approach in which localized saddle-point searches are combined with parallel GPU-based molecular dynamics in order to improve the scaling behavior. By using this method, along with the use of an adaptive method to determine the optimal high-temperature^3, we have been able to significantly increase the range of time- and length-scales over which accelerated dynamics simulations may be carried out. [1] Y. Shim et al, Phys. Rev. B 76, 205439 (2007); ibid, Phys. Rev. Lett. 101, 116101 (2008). [2] Y. Shim and J.G. Amar, Phys. Rev. B 71, 125432 (2005). [3] Y. Shim and J.G. Amar, J. Chem. Phys. 134, 054127 (2011).

Multi-scale Modeling of Chromosomal DNA in Living Cells

NASA Astrophysics Data System (ADS)

Spakowitz, Andrew

The organization and dynamics of chromosomal DNA play a pivotal role in a range of biological processes, including gene regulation, homologous recombination, replication, and segregation. Establishing a quantitative theoretical model of DNA organization and dynamics would be valuable in bridging the gap between the molecular-level packaging of DNA and genome-scale chromosomal processes. Our research group utilizes analytical theory and computational modeling to establish a predictive theoretical model of chromosomal organization and dynamics. In this talk, I will discuss our efforts to develop multi-scale polymer models of chromosomal DNA that are both sufficiently detailed to address specific protein-DNA interactions while capturing experimentally relevant time and length scales. I will demonstrate how these modeling efforts are capable of quantitatively capturing aspects of behavior of chromosomal DNA in both prokaryotic and eukaryotic cells. This talk will illustrate that capturing dynamical behavior of chromosomal DNA at various length scales necessitates a range of theoretical treatments that accommodate the critical physical contributions that are relevant to in vivo behavior at these disparate length and time scales. National Science Foundation, Physics of Living Systems Program (PHY-1305516).

Scale-Free Neural and Physiological Dynamics in Naturalistic Stimuli Processing

PubMed Central

Lin, Amy

2016-01-01

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

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

NASA Astrophysics Data System (ADS)

Rocha, Luis E. C.; Masuda, Naoki

2016-08-01

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

Ultra-fast relaxation, decoherence, and localization of photoexcited states in π-conjugated polymers

NASA Astrophysics Data System (ADS)

Mannouch, Jonathan R.; Barford, William; Al-Assam, Sarah

2018-01-01

The exciton relaxation dynamics of photoexcited electronic states in poly(p-phenylenevinylene) are theoretically investigated within a coarse-grained model, in which both the exciton and nuclear degrees of freedom are treated quantum mechanically. The Frenkel-Holstein Hamiltonian is used to describe the strong exciton-phonon coupling present in the system, while external damping of the internal nuclear degrees of freedom is accounted for by a Lindblad master equation. Numerically, the dynamics are computed using the time evolving block decimation and quantum jump trajectory techniques. The values of the model parameters physically relevant to polymer systems naturally lead to a separation of time scales, with the ultra-fast dynamics corresponding to energy transfer from the exciton to the internal phonon modes (i.e., the C-C bond oscillations), while the longer time dynamics correspond to damping of these phonon modes by the external dissipation. Associated with these time scales, we investigate the following processes that are indicative of the system relaxing onto the emissive chromophores of the polymer: (1) Exciton-polaron formation occurs on an ultra-fast time scale, with the associated exciton-phonon correlations present within half a vibrational time period of the C-C bond oscillations. (2) Exciton decoherence is driven by the decay in the vibrational overlaps associated with exciton-polaron formation, occurring on the same time scale. (3) Exciton density localization is driven by the external dissipation, arising from "wavefunction collapse" occurring as a result of the system-environment interactions. Finally, we show how fluorescence anisotropy measurements can be used to investigate the exciton decoherence process during the relaxation dynamics.

In Vivo Protein Dynamics on the Nanometer Length Scale and Nanosecond Time Scale

DOE PAGES

Anunciado, Divina B.; Nyugen, Vyncent P.; Hurst, Gregory B.; ...

2017-04-07

Selectively labeled GroEL protein was produced in living deuterated bacterial cells to enhance its neutron scattering signal above that of the intracellular milieu. Quasi-elastic neutron scattering shows that the in-cell diffusion coefficient of GroEL was (4.7 ± 0.3) × 10 –12 m 2/s, a factor of 4 slower than its diffusion coefficient in buffer solution. Furthermore, for internal protein dynamics we see a relaxation time of (65 ± 6) ps, a factor of 2 slower compared to the protein in solution. Comparison to the literature suggests that the effective diffusivity of proteins depends on the length and time scale beingmore » probed. Retardation of in-cell diffusion compared to the buffer becomes more significant with the increasing probe length scale, suggesting that intracellular diffusion of biomolecules is nonuniform over the cellular volume. This approach outlined here enables investigation of protein dynamics within living cells to open up new lines of research using “in-cell neutron scattering” to study the dynamics of complex biomolecular systems.« less

In Vivo Protein Dynamics on the Nanometer Length Scale and Nanosecond Time Scale

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

Anunciado, Divina B.; Nyugen, Vyncent P.; Hurst, Gregory B.

Selectively labeled GroEL protein was produced in living deuterated bacterial cells to enhance its neutron scattering signal above that of the intracellular milieu. Quasi-elastic neutron scattering shows that the in-cell diffusion coefficient of GroEL was (4.7 ± 0.3) × 10 –12 m 2/s, a factor of 4 slower than its diffusion coefficient in buffer solution. Furthermore, for internal protein dynamics we see a relaxation time of (65 ± 6) ps, a factor of 2 slower compared to the protein in solution. Comparison to the literature suggests that the effective diffusivity of proteins depends on the length and time scale beingmore » probed. Retardation of in-cell diffusion compared to the buffer becomes more significant with the increasing probe length scale, suggesting that intracellular diffusion of biomolecules is nonuniform over the cellular volume. This approach outlined here enables investigation of protein dynamics within living cells to open up new lines of research using “in-cell neutron scattering” to study the dynamics of complex biomolecular systems.« less

A derivation and scalable implementation of the synchronous parallel kinetic Monte Carlo method for simulating long-time dynamics

NASA Astrophysics Data System (ADS)

Byun, Hye Suk; El-Naggar, Mohamed Y.; Kalia, Rajiv K.; Nakano, Aiichiro; Vashishta, Priya

2017-10-01

Kinetic Monte Carlo (KMC) simulations are used to study long-time dynamics of a wide variety of systems. Unfortunately, the conventional KMC algorithm is not scalable to larger systems, since its time scale is inversely proportional to the simulated system size. A promising approach to resolving this issue is the synchronous parallel KMC (SPKMC) algorithm, which makes the time scale size-independent. This paper introduces a formal derivation of the SPKMC algorithm based on local transition-state and time-dependent Hartree approximations, as well as its scalable parallel implementation based on a dual linked-list cell method. The resulting algorithm has achieved a weak-scaling parallel efficiency of 0.935 on 1024 Intel Xeon processors for simulating biological electron transfer dynamics in a 4.2 billion-heme system, as well as decent strong-scaling parallel efficiency. The parallel code has been used to simulate a lattice of cytochrome complexes on a bacterial-membrane nanowire, and it is broadly applicable to other problems such as computational synthesis of new materials.

An Acrobatic Substrate Metamorphosis Reveals a Requirement for Substrate Conformational Dynamics in Trypsin Proteolysis.

PubMed

Kayode, Olumide; Wang, Ruiying; Pendlebury, Devon F; Cohen, Itay; Henin, Rachel D; Hockla, Alexandra; Soares, Alexei S; Papo, Niv; Caulfield, Thomas R; Radisky, Evette S

2016-12-16

The molecular basis of enzyme catalytic power and specificity derives from dynamic interactions between enzyme and substrate during catalysis. Although considerable effort has been devoted to understanding how conformational dynamics within enzymes affect catalysis, the role of conformational dynamics within protein substrates has not been addressed. Here, we examine the importance of substrate dynamics in the cleavage of Kunitz-bovine pancreatic trypsin inhibitor protease inhibitors by mesotrypsin, finding that the varied conformational dynamics of structurally similar substrates can profoundly impact the rate of catalysis. A 1.4-Å crystal structure of a mesotrypsin-product complex formed with a rapidly cleaved substrate reveals a dramatic conformational change in the substrate upon proteolysis. By using long all-atom molecular dynamics simulations of acyl-enzyme intermediates with proteolysis rates spanning 3 orders of magnitude, we identify global and local dynamic features of substrates on the nanosecond-microsecond time scale that correlate with enzymatic rates and explain differential susceptibility to proteolysis. By integrating multiple enhanced sampling methods for molecular dynamics, we model a viable conformational pathway between substrate-like and product-like states, linking substrate dynamics on the nanosecond-microsecond time scale with large collective substrate motions on the much slower time scale of catalysis. Our findings implicate substrate flexibility as a critical determinant of catalysis. © 2016 by The American Society for Biochemistry and Molecular Biology, Inc.

End-monomer Dynamics in Semiflexible Polymers

PubMed Central

Hinczewski, Michael; Schlagberger, Xaver; Rubinstein, Michael; Krichevsky, Oleg; Netz, Roland R.

2009-01-01

Spurred by an experimental controversy in the literature, we investigate the end-monomer dynamics of semiflexible polymers through Brownian hydrodynamic simulations and dynamic mean-field theory. Precise experimental observations over the last few years of end-monomer dynamics in the diffusion of double-stranded DNA have given conflicting results: one study indicated an unexpected Rouse-like scaling of the mean squared displacement (MSD) 〈r2(t)〉 ~ t1/2 at intermediate times, corresponding to fluctuations at length scales larger than the persistence length but smaller than the coil size; another study claimed the more conventional Zimm scaling 〈r2(t)〉 ~ t2/3 in the same time range. Using hydrodynamic simulations, analytical and scaling theories, we find a novel intermediate dynamical regime where the effective local exponent of the end-monomer MSD, α(t) = d log〈r2(t)〉/d log t, drops below the Zimm value of 2/3 for sufficiently long chains. The deviation from the Zimm prediction increases with chain length, though it does not reach the Rouse limit of 1/2. The qualitative features of this intermediate regime, found in simulations and in an improved mean-field theory for semiflexible polymers, in particular the variation of α(t) with chain and persistence lengths, can be reproduced through a heuristic scaling argument. Anomalously low values of the effective exponent α are explained by hydrodynamic effects related to the slow crossover from dynamics on length scales smaller than the persistence length to dynamics on larger length scales. PMID:21359118

Next Generation Extended Lagrangian Quantum-based Molecular Dynamics

NASA Astrophysics Data System (ADS)

Negre, Christian

2017-06-01

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

The temporal spectrum of adult mosquito population fluctuations: conceptual and modeling implications.

PubMed

Jian, Yun; Silvestri, Sonia; Brown, Jeff; Hickman, Rick; Marani, Marco

2014-01-01

An improved understanding of mosquito population dynamics under natural environmental forcing requires adequate field observations spanning the full range of temporal scales over which mosquito abundance fluctuates in natural conditions. Here we analyze a 9-year daily time series of uninterrupted observations of adult mosquito abundance for multiple mosquito species in North Carolina to identify characteristic scales of temporal variability, the processes generating them, and the representativeness of observations at different sampling resolutions. We focus in particular on Aedes vexans and Culiseta melanura and, using a combination of spectral analysis and modeling, we find significant population fluctuations with characteristic periodicity between 2 days and several years. Population dynamical modelling suggests that the observed fast fluctuations scales (2 days-weeks) are importantly affected by a varying mosquito activity in response to rapid changes in meteorological conditions, a process neglected in most representations of mosquito population dynamics. We further suggest that the range of time scales over which adult mosquito population variability takes place can be divided into three main parts. At small time scales (indicatively 2 days-1 month) observed population fluctuations are mainly driven by behavioral responses to rapid changes in weather conditions. At intermediate scales (1 to several month) environmentally-forced fluctuations in generation times, mortality rates, and density dependence determine the population characteristic response times. At longer scales (annual to multi-annual) mosquito populations follow seasonal and inter-annual environmental changes. We conclude that observations of adult mosquito populations should be based on a sub-weekly sampling frequency and that predictive models of mosquito abundance must include behavioral dynamics to separate the effects of a varying mosquito activity from actual changes in the abundance of the underlying population.

Reversible and Irreversible Behavior of Glass-forming Materials from the Standpoint of Hierarchical Dynamical Facilitation

NASA Astrophysics Data System (ADS)

Keys, Aaron

2013-03-01

Using molecular simulation and coarse-grained lattice models, we study the dynamics of glass-forming liquids above and below the glass transition temperature. In the supercooled regime, we study the structure, statistics, and dynamics of excitations responsible for structural relaxation for several atomistic models of glass-formers. Excitations (or soft spots) are detected in terms of persistent particle displacements. At supercooled conditions, we find that excitations are associated with correlated particle motions that are sparse and localized, and the statistics and dynamics of these excitations are facilitated and hierarchical. Excitations at one point in space facilitate the birth and death of excitations at neighboring locations, and space-time excitation structures are microcosms of heterogeneous dynamics at larger scales. Excitation-energy scales grow logarithmically with the characteristic size of the excitation, giving structural-relaxation times that can be predicted quantitatively from dynamics at short time scales. We demonstrate that these same physical principles govern the dynamics of glass-forming systems driven out-of-equilibrium by time-dependent protocols. For a system cooled and re-heated through the glass transition, non-equilibrium response functions, such as heat capacities, are notably asymmetric in time, and the response to melting a glass depends markedly on the cooling protocol by which the glass was formed. We introduce a quantitative description of this behavior based on the East model, with parameters determined from reversible transport data, that agrees well with irreversible differential scanning calorimetry. We find that the observed hysteresis and asymmetric response is a signature of an underlying dynamical transition between equilibrium melts with no trivial spatial correlations and non-equilibrium glasses with correlation lengths that are both large and dependent upon the rate at which the glass is prepared. The correlation length corresponds to the size of amorphous domains bounded by excitations that remain frozen on the observation time scale, thus forming stripes when viewed in space and time. We elucidate properties of the striped phase and show that glasses of this type, traditionally prepared through cooling, can be considered a finite-size realization of the inactive phase formed by the s-ensemble in the space-time thermodynamic limit.

Impact of an irregular friction formulation on dynamics of a minimal model for brake squeal

NASA Astrophysics Data System (ADS)

Stender, Merten; Tiedemann, Merten; Hoffmann, Norbert; Oberst, Sebastian

2018-07-01

Friction-induced vibrations are of major concern in the design of reliable, efficient and comfortable technical systems. Well-known examples for systems susceptible to self-excitation can be found in fluid structure interaction, disk brake squeal, rotor dynamics, hip implants noise and many more. While damping elements and amplitude reduction are well-understood in linear systems, nonlinear systems and especially self-excited dynamics still constitute a challenge for damping element design. Additionally, complex dynamical systems exhibit deterministic chaotic cores which add severe sensitivity to initial conditions to the system response. Especially the complex friction interface dynamics remain a challenging task for measurements and modeling. Today, mostly simple and regular friction models are investigated in the field of self-excited brake system vibrations. This work aims at investigating the effect of high-frequency irregular interface dynamics on the nonlinear dynamical response of a self-excited structure. Special focus is put on the characterization of the system response time series. A low-dimensional minimal model is studied which features self-excitation, gyroscopic effects and friction-induced damping. Additionally, the employed friction formulation exhibits temperature as inner variable and superposed chaotic fluctuations governed by a Lorenz attractor. The time scale of the irregular fluctuations is chosen one order smaller than the overall system dynamics. The influence of those fluctuations on the structural response is studied in various ways, i.e. in time domain and by means of recurrence analysis. The separate time scales are studied in detail and regimes of dynamic interactions are identified. The results of the irregular friction formulation indicate dynamic interactions on multiple time scales, which trigger larger vibration amplitudes as compared to regular friction formulations conventionally studied in the field of friction-induced vibrations.

Quantum Nuclear Dynamics Pumped and Probed by Ultrafast Polarization Controlled Steering of a Coherent Electronic State in LiH.

PubMed

Nikodem, Astrid; Levine, R D; Remacle, F

2016-05-19

The quantum wave packet dynamics following a coherent electronic excitation of LiH by an ultrashort, polarized, strong one-cycle infrared optical pulse is computed on several electronic states using a grid method. The coupling to the strong field of the pump and the probe pulses is included in the Hamiltonian used to solve the time-dependent Schrodinger equation. The polarization of the pump pulse allows us to control the localization in time and in space of the nonequilibrium coherent electronic motion and the subsequent nuclear dynamics. We show that transient absorption, resulting from the interaction of the total molecular dipole with the electric fields of the pump and the probe, is a very versatile probe of the different time scales of the vibronic dynamics. It allows probing both the ultrashort, femtosecond time scale of the electronic coherences as well as the longer dozens of femtoseconds time scales of the nuclear motion on the excited electronic states. The ultrafast beatings of the electronic coherences in space and in time are shown to be modulated by the different periods of the nuclear motion.

Endogenous and exogenous dynamics in the fluctuations of capital fluxes. An empirical analysis of the Chinese stock market

NASA Astrophysics Data System (ADS)

Jiang, Z.-Q.; Guo, L.; Zhou, W.-X.

2007-06-01

A phenomenological investigation of the endogenous and exogenous dynamics in the fluctuations of capital fluxes is carried out on the Chinese stock market using mean-variance analysis, fluctuation analysis, and their generalizations to higher orders. Non-universal dynamics have been found not only in the scaling exponent α, which is different from the universal values 1/2 and 1, but also in the distributions of the ratio η= σexo / σendo of individual stocks. Both the scaling exponent α of fluctuations and the Hurst exponent Hi increase in logarithmic form with the time scale Δt and the mean traded value per minute , respectively. We find that the scaling exponent αendo of the endogenous fluctuations is independent of the time scale. Multiscaling and multifractal features are observed in the data as well. However, the inhomogeneous impact model is not verified.

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.

The Relationship of Dynamical Heterogeneity to the Adam-Gibbs and Random First-Order Transition Theories of Glass Formation

NASA Astrophysics Data System (ADS)

Starr, Francis; Douglas, Jack; Sastry, Srikanth

2013-03-01

We examine measures of dynamical heterogeneity for a bead-spring polymer melt and test how these scales compare with the scales hypothesized by the Adam and Gibbs (AG) and random first-order transition (RFOT) theories. We show that the time scale of the high-mobility clusters and strings is associated with a diffusive time scale, while the low-mobility particles' time scale relates to a structural relaxation time. The difference of the characteristic times naturally explains the decoupling of diffusion and structural relaxation time scales. We examine the appropriateness of identifying the size scales of mobile particle clusters or strings with the size of cooperatively rearranging regions (CRR) in the AG and RFOT theories. We find that the string size appears to be the most consistent measure of CRR for both the AG and RFOT models. Identifying strings or clusters with the``mosaic'' length of the RFOT model relaxes the conventional assumption that the``entropic droplet'' are compact. We also confirm the validity of the entropy formulation of the AG theory, constraining the exponent values of the RFOT theory. This constraint, together with the analysis of size scales, enables us to estimate the characteristic exponents of RFOT.

Vibrational dynamics of aqueous hydroxide solutions probed using broadband 2DIR spectroscopy

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

Mandal, Aritra; Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139; Tokmakoff, Andrei, E-mail: tokmakoff@uchicago.edu

2015-11-21

We employed ultrafast transient absorption and broadband 2DIR spectroscopy to study the vibrational dynamics of aqueous hydroxide solutions by exciting the O–H stretch vibrations of the strongly hydrogen-bonded hydroxide solvation shell water and probing the continuum absorption of the solvated ion between 1500 and 3800 cm{sup −1}. We observe rapid vibrational relaxation processes on 150–250 fs time scales across the entire probed spectral region as well as slower vibrational dynamics on 1–2 ps time scales. Furthermore, the O–H stretch excitation loses its frequency memory in 180 fs, and vibrational energy exchange between bulk-like water vibrations and hydroxide-associated water vibrations occursmore » in ∼200 fs. The fast dynamics in this system originate in strong nonlinear coupling between intra- and intermolecular vibrations and are explained in terms of non-adiabatic vibrational relaxation. These measurements indicate that the vibrational dynamics of the aqueous hydroxide complex are faster than the time scales reported for long-range transport of protons in aqueous hydroxide solutions.« less

Photoluminescence decay dynamics in γ-Ga2O3 nanocrystals: The role of exclusion distance at short time scales

NASA Astrophysics Data System (ADS)

Fernandes, Brian; Hegde, Manu; Stanish, Paul C.; Mišković, Zoran L.; Radovanovic, Pavle V.

2017-09-01

We developed a comprehensive theoretical model describing the photoluminescence decay dynamics at short and long time scales based on the donor-acceptor defect interactions in γ-Ga2O3 nanocrystals, and quantitatively determined the importance of exclusion distance and spatial distribution of defects. We allowed for donors and acceptors to be adjacent to each other or separated by different exclusion distances. The optimal exclusion distance was found to be comparable to the donor Bohr radius and have a strong effect on the photoluminescence decay curve at short times. The importance of the exclusion distance at short time scales was confirmed by Monte Carlo simulations.

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.

Impact of stock market structure on intertrade time and price dynamics.

PubMed

Ivanov, Plamen Ch; Yuen, Ainslie; Perakakis, Pandelis

2014-01-01

We analyse times between consecutive transactions for a diverse group of stocks registered on the NYSE and NASDAQ markets, and we relate the dynamical properties of the intertrade times with those of the corresponding price fluctuations. We report that market structure strongly impacts the scale-invariant temporal organisation in the transaction timing of stocks, which we have observed to have long-range power-law correlations. Specifically, we find that, compared to NYSE stocks, stocks registered on the NASDAQ exhibit significantly stronger correlations in their transaction timing on scales within a trading day. Further, we find that companies that transfer from the NASDAQ to the NYSE show a reduction in the correlation strength of transaction timing on scales within a trading day, indicating influences of market structure. We also report a persistent decrease in correlation strength of intertrade times with increasing average intertrade time and with corresponding decrease in companies' market capitalization-a trend which is less pronounced for NASDAQ stocks. Surprisingly, we observe that stronger power-law correlations in intertrade times are coupled with stronger power-law correlations in absolute price returns and higher price volatility, suggesting a strong link between the dynamical properties of intertrade times and the corresponding price fluctuations over a broad range of time scales. Comparing the NYSE and NASDAQ markets, we demonstrate that the stronger correlations we find in intertrade times for NASDAQ stocks are associated with stronger correlations in absolute price returns and with higher volatility, suggesting that market structure may affect price behavior through information contained in transaction timing. These findings do not support the hypothesis of universal scaling behavior in stock dynamics that is independent of company characteristics and stock market structure. Further, our results have implications for utilising transaction timing patterns in price prediction and risk management optimization on different stock markets.

Impact of Stock Market Structure on Intertrade Time and Price Dynamics

PubMed Central

Ivanov, Plamen Ch.; Yuen, Ainslie; Perakakis, Pandelis

2014-01-01

We analyse times between consecutive transactions for a diverse group of stocks registered on the NYSE and NASDAQ markets, and we relate the dynamical properties of the intertrade times with those of the corresponding price fluctuations. We report that market structure strongly impacts the scale-invariant temporal organisation in the transaction timing of stocks, which we have observed to have long-range power-law correlations. Specifically, we find that, compared to NYSE stocks, stocks registered on the NASDAQ exhibit significantly stronger correlations in their transaction timing on scales within a trading day. Further, we find that companies that transfer from the NASDAQ to the NYSE show a reduction in the correlation strength of transaction timing on scales within a trading day, indicating influences of market structure. We also report a persistent decrease in correlation strength of intertrade times with increasing average intertrade time and with corresponding decrease in companies' market capitalization–a trend which is less pronounced for NASDAQ stocks. Surprisingly, we observe that stronger power-law correlations in intertrade times are coupled with stronger power-law correlations in absolute price returns and higher price volatility, suggesting a strong link between the dynamical properties of intertrade times and the corresponding price fluctuations over a broad range of time scales. Comparing the NYSE and NASDAQ markets, we demonstrate that the stronger correlations we find in intertrade times for NASDAQ stocks are associated with stronger correlations in absolute price returns and with higher volatility, suggesting that market structure may affect price behavior through information contained in transaction timing. These findings do not support the hypothesis of universal scaling behavior in stock dynamics that is independent of company characteristics and stock market structure. Further, our results have implications for utilising transaction timing patterns in price prediction and risk management optimization on different stock markets. PMID:24699376

Heterogeneous dynamics of ionic liquids: A four-point time correlation function approach

NASA Astrophysics Data System (ADS)

Liu, Jiannan; Willcox, Jon A. L.; Kim, Hyung J.

2018-05-01

Many ionic liquids show behavior similar to that of glassy systems, e.g., large and long-lasted deviations from Gaussian dynamics and clustering of "mobile" and "immobile" groups of ions. Herein a time-dependent four-point density correlation function—typically used to characterize glassy systems—is implemented for the ionic liquids, choline acetate, and 1-butyl-3-methylimidazolium acetate. Dynamic correlation beyond the first ionic solvation shell on the time scale of nanoseconds is found in the ionic liquids, revealing the cooperative nature of ion motions. The traditional solvent, acetonitrile, on the other hand, shows a much shorter length-scale that decays after a few picoseconds.

Coherent fifth-order visible-infrared spectroscopies: ultrafast nonequilibrium vibrational dynamics in solution.

PubMed

Lynch, Michael S; Slenkamp, Karla M; Cheng, Mark; Khalil, Munira

2012-07-05

Obtaining a detailed description of photochemical reactions in solution requires measuring time-evolving structural dynamics of transient chemical species on ultrafast time scales. Time-resolved vibrational spectroscopies are sensitive probes of molecular structure and dynamics in solution. In this work, we develop doubly resonant fifth-order nonlinear visible-infrared spectroscopies to probe nonequilibrium vibrational dynamics among coupled high-frequency vibrations during an ultrafast charge transfer process using a heterodyne detection scheme. The method enables the simultaneous collection of third- and fifth-order signals, which respectively measure vibrational dynamics occurring on electronic ground and excited states on a femtosecond time scale. Our data collection and analysis strategy allows transient dispersed vibrational echo (t-DVE) and dispersed pump-probe (t-DPP) spectra to be extracted as a function of electronic and vibrational population periods with high signal-to-noise ratio (S/N > 25). We discuss how fifth-order experiments can measure (i) time-dependent anharmonic vibrational couplings, (ii) nonequilibrium frequency-frequency correlation functions, (iii) incoherent and coherent vibrational relaxation and transfer dynamics, and (iv) coherent vibrational and electronic (vibronic) coupling as a function of a photochemical reaction.

Complexity analyses show two distinct types of nonlinear dynamics in short heart period variability recordings

PubMed Central

Porta, Alberto; Bari, Vlasta; Marchi, Andrea; De Maria, Beatrice; Cysarz, Dirk; Van Leeuwen, Peter; Takahashi, Anielle C. M.; Catai, Aparecida M.; Gnecchi-Ruscone, Tomaso

2015-01-01

Two diverse complexity metrics quantifying time irreversibility and local prediction, in connection with a surrogate data approach, were utilized to detect nonlinear dynamics in short heart period (HP) variability series recorded in fetuses, as a function of the gestational period, and in healthy humans, as a function of the magnitude of the orthostatic challenge. The metrics indicated the presence of two distinct types of nonlinear HP dynamics characterized by diverse ranges of time scales. These findings stress the need to render more specific the analysis of nonlinear components of HP dynamics by accounting for different temporal scales. PMID:25806002

Underlying dynamics of typical fluctuations of an emerging market price index: The Heston model from minutes to months

NASA Astrophysics Data System (ADS)

Vicente, Renato; de Toledo, Charles M.; Leite, Vitor B. P.; Caticha, Nestor

2006-02-01

We investigate the Heston model with stochastic volatility and exponential tails as a model for the typical price fluctuations of the Brazilian São Paulo Stock Exchange Index (IBOVESPA). Raw prices are first corrected for inflation and a period spanning 15 years characterized by memoryless returns is chosen for the analysis. Model parameters are estimated by observing volatility scaling and correlation properties. We show that the Heston model with at least two time scales for the volatility mean reverting dynamics satisfactorily describes price fluctuations ranging from time scales larger than 20 min to 160 days. At time scales shorter than 20 min we observe autocorrelated returns and power law tails incompatible with the Heston model. Despite major regulatory changes, hyperinflation and currency crises experienced by the Brazilian market in the period studied, the general success of the description provided may be regarded as an evidence for a general underlying dynamics of price fluctuations at intermediate mesoeconomic time scales well approximated by the Heston model. We also notice that the connection between the Heston model and Ehrenfest urn models could be exploited for bringing new insights into the microeconomic market mechanics.

Research on the F/A-18E/F Using a 22%-Dynamically-Scaled Drop Model

NASA Technical Reports Server (NTRS)

Croom, M.; Kenney, H.; Murri, D.; Lawson, K.

2000-01-01

Research on the F/A-18E/F configuration was conducted using a 22%-dynamically-scaled drop model to study flight dynamics in the subsonic regime. Several topics were investigated including longitudinal response, departure/spin resistance, developed spins and recoveries, and the failing leaf mode. Comparisons to full-scale flight test results were made and show the drop model strongly correlates to the airplane even under very dynamic conditions. The capability to use the drop model to expand on the information gained from full-scale flight testing is also discussed. Finally, a preliminary analysis of an unusual inclined spinning motion, dubbed the "cartwheel", is presented here for the first time.

Ultrafast carrier thermalization and cooling dynamics in few-layer MoS2.

PubMed

Nie, Zhaogang; Long, Run; Sun, Linfeng; Huang, Chung-Che; Zhang, Jun; Xiong, Qihua; Hewak, Daniel W; Shen, Zexiang; Prezhdo, Oleg V; Loh, Zhi-Heng

2014-10-28

Femtosecond optical pump-probe spectroscopy with 10 fs visible pulses is employed to elucidate the ultrafast carrier dynamics of few-layer MoS2. A nonthermal carrier distribution is observed immediately following the photoexcitation of the A and B excitonic transitions by the ultrashort, broadband laser pulse. Carrier thermalization occurs within 20 fs and proceeds via both carrier-carrier and carrier-phonon scattering, as evidenced by the observed dependence of the thermalization time on the carrier density and the sample temperature. The n(-0.37 ± 0.03) scaling of the thermalization time with carrier density suggests that equilibration of the nonthermal carrier distribution occurs via non-Markovian quantum kinetics. Subsequent cooling of the hot Fermi-Dirac carrier distribution occurs on the ∼ 0.6 ps time scale via carrier-phonon scattering. Temperature- and fluence-dependence studies reveal the involvement of hot phonons in the carrier cooling process. Nonadiabatic ab initio molecular dynamics simulations, which predict carrier-carrier and carrier-phonon scattering time scales of 40 fs and 0.5 ps, respectively, lend support to the assignment of the observed carrier dynamics.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Non-stationary dynamics in the bouncing ball: A wavelet perspective

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

Behera, Abhinna K., E-mail: abhinna@iiserkol.ac.in; Panigrahi, Prasanta K., E-mail: pprasanta@iiserkol.ac.in; Sekar Iyengar, A. N., E-mail: ansekar.iyengar@saha.ac.in

2014-12-01

The non-stationary dynamics of a bouncing ball, comprising both periodic as well as chaotic behavior, is studied through wavelet transform. The multi-scale characterization of the time series displays clear signatures of self-similarity, complex scaling behavior, and periodicity. Self-similar behavior is quantified by the generalized Hurst exponent, obtained through both wavelet based multi-fractal detrended fluctuation analysis and Fourier methods. The scale dependent variable window size of the wavelets aptly captures both the transients and non-stationary periodic behavior, including the phase synchronization of different modes. The optimal time-frequency localization of the continuous Morlet wavelet is found to delineate the scales corresponding tomore » neutral turbulence, viscous dissipation regions, and different time varying periodic modulations.« less

Ultrafast spectroscopy reveals subnanosecond peptide conformational dynamics and validates molecular dynamics simulation

NASA Astrophysics Data System (ADS)

Spörlein, Sebastian; Carstens, Heiko; Satzger, Helmut; Renner, Christian; Behrendt, Raymond; Moroder, Luis; Tavan, Paul; Zinth, Wolfgang; Wachtveitl, Josef

2002-06-01

Femtosecond time-resolved spectroscopy on model peptides with built-in light switches combined with computer simulation of light-triggered motions offers an attractive integrated approach toward the understanding of peptide conformational dynamics. It was applied to monitor the light-induced relaxation dynamics occurring on subnanosecond time scales in a peptide that was backbone-cyclized with an azobenzene derivative as optical switch and spectroscopic probe. The femtosecond spectra permit the clear distinguishing and characterization of the subpicosecond photoisomerization of the chromophore, the subsequent dissipation of vibrational energy, and the subnanosecond conformational relaxation of the peptide. The photochemical cis/trans-isomerization of the chromophore and the resulting peptide relaxations have been simulated with molecular dynamics calculations. The calculated reaction kinetics, as monitored by the energy content of the peptide, were found to match the spectroscopic data. Thus we verify that all-atom molecular dynamics simulations can quantitatively describe the subnanosecond conformational dynamics of peptides, strengthening confidence in corresponding predictions for longer time scales.

Oscillation criteria for a class of second-order Emden-Fowler delay dynamic equations on time scales

NASA Astrophysics Data System (ADS)

Han, Zhenlai; Sun, Shurong; Shi, Bao

2007-10-01

By means of Riccati transformation technique, we establish some new oscillation criteria for the second-order Emden-Fowler delay dynamic equationsx[Delta][Delta](t)+p(t)x[gamma]([tau](t))=0 on a time scale ; here [gamma] is a quotient of odd positive integers with p(t) real-valued positive rd-continuous functions defined on . To the best of our knowledge nothing is known regarding the qualitative behavior of these equations on time scales. Our results in this paper not only extend the results given in [R.P. Agarwal, M. Bohner, S.H. Saker, Oscillation of second-order delay dynamic equations, Can. Appl. Math. Q. 13 (1) (2005) 1-18] but also unify the oscillation of the second-order Emden-Fowler delay differential equation and the second-order Emden-Fowler delay difference equation.

Understanding the effect of vector dynamics in epidemic models using center manifold analysis

NASA Astrophysics Data System (ADS)

Rocha, Filipe; Aguiar, Maíra; Souza, Max; Stollenwerk, Nico

2012-09-01

In vector borne diseases the human hosts' epidemiology often acts on a much slower time scales than the one of the mosquitos which transmit the disease as a vector from human to human, due to their vastly different life cycles. We investigate in a model with susceptible (S), infected (I) and recovered (R) humans and susceptible (U) and infected (V) mosquitoes in how far the fast time scale of the mosquito epidemiology can be slaved by the slower human epidemiology, so that for the understanding of human disease data mainly the dynamics of the human time scale is essential and only slightly perturbed by the mosquito dynamics. This analysis of the SIRUV model is qualitatively in agreement with a previously investigated simpler SISUV model, hence a feature of vector-borne diseases in general.

Spatio-temporal hierarchy in the dynamics of a minimalist protein model

NASA Astrophysics Data System (ADS)

Matsunaga, Yasuhiro; Baba, Akinori; Li, Chun-Biu; Straub, John E.; Toda, Mikito; Komatsuzaki, Tamiki; Berry, R. Stephen

2013-12-01

A method for time series analysis of molecular dynamics simulation of a protein is presented. In this approach, wavelet analysis and principal component analysis are combined to decompose the spatio-temporal protein dynamics into contributions from a hierarchy of different time and space scales. Unlike the conventional Fourier-based approaches, the time-localized wavelet basis captures the vibrational energy transfers among the collective motions of proteins. As an illustrative vehicle, we have applied our method to a coarse-grained minimalist protein model. During the folding and unfolding transitions of the protein, vibrational energy transfers between the fast and slow time scales were observed among the large-amplitude collective coordinates while the other small-amplitude motions are regarded as thermal noise. Analysis employing a Gaussian-based measure revealed that the time scales of the energy redistribution in the subspace spanned by such large-amplitude collective coordinates are slow compared to the other small-amplitude coordinates. Future prospects of the method are discussed in detail.

Phase Transitions and Scaling in Systems Far from Equilibrium

NASA Astrophysics Data System (ADS)

Täuber, Uwe C.

2017-03-01

Scaling ideas and renormalization group approaches proved crucial for a deep understanding and classification of critical phenomena in thermal equilibrium. Over the past decades, these powerful conceptual and mathematical tools were extended to continuous phase transitions separating distinct nonequilibrium stationary states in driven classical and quantum systems. In concordance with detailed numerical simulations and laboratory experiments, several prominent dynamical universality classes have emerged that govern large-scale, long-time scaling properties both near and far from thermal equilibrium. These pertain to genuine specific critical points as well as entire parameter space regions for steady states that display generic scale invariance. The exploration of nonstationary relaxation properties and associated physical aging scaling constitutes a complementary potent means to characterize cooperative dynamics in complex out-of-equilibrium systems. This review describes dynamic scaling features through paradigmatic examples that include near-equilibrium critical dynamics, driven lattice gases and growing interfaces, correlation-dominated reaction-diffusion systems, and basic epidemic models.

Intelligent control of neurosurgical robot MM-3 using dynamic motion scaling.

PubMed

Ko, Sunho; Nakazawa, Atsushi; Kurose, Yusuke; Harada, Kanako; Mitsuishi, Mamoru; Sora, Shigeo; Shono, Naoyuki; Nakatomi, Hirofumi; Saito, Nobuhito; Morita, Akio

2017-05-01

OBJECTIVE Advanced and intelligent robotic control is necessary for neurosurgical robots, which require great accuracy and precision. In this article, the authors propose methods for dynamically and automatically controlling the motion-scaling ratio of a master-slave neurosurgical robotic system to reduce the task completion time. METHODS Three dynamic motion-scaling modes were proposed and compared with the conventional fixed motion-scaling mode. These 3 modes were defined as follows: 1) the distance between a target point and the tip of the slave manipulator, 2) the distance between the tips of the slave manipulators, and 3) the velocity of the master manipulator. Five test subjects, 2 of whom were neurosurgeons, sutured 0.3-mm artificial blood vessels using the MM-3 neurosurgical robot in each mode. RESULTS The task time, total path length, and helpfulness score were evaluated. Although no statistically significant differences were observed, the mode using the distance between the tips of the slave manipulators improves the suturing performance. CONCLUSIONS Dynamic motion scaling has great potential for the intelligent and accurate control of neurosurgical robots.

Space Technology 5 Multi-point Observations of Field-aligned Currents: Temporal Variability of Meso-Scale Structures

NASA Technical Reports Server (NTRS)

Le, Guan; Wang, Yongli; Slavin, James A.; Strangeway, Robert J.

2007-01-01

Space Technology 5 (ST5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that meso-scale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of - 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are approx. 1 min for meso-scale currents and approx. 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Nonequilibrium dynamic critical scaling of the quantum Ising chain.

PubMed

Kolodrubetz, Michael; Clark, Bryan K; Huse, David A

2012-07-06

We solve for the time-dependent finite-size scaling functions of the one-dimensional transverse-field Ising chain during a linear-in-time ramp of the field through the quantum critical point. We then simulate Mott-insulating bosons in a tilted potential, an experimentally studied system in the same equilibrium universality class, and demonstrate that universality holds for the dynamics as well. We find qualitatively athermal features of the scaling functions, such as negative spin correlations, and we show that they should be robustly observable within present cold atom experiments.

Single molecule translocation in smectics illustrates the challenge for time-mapping in simulations on multiple scales

NASA Astrophysics Data System (ADS)

Mukherjee, Biswaroop; Peter, Christine; Kremer, Kurt

2017-09-01

Understanding the connections between the characteristic dynamical time scales associated with a coarse-grained (CG) and a detailed representation is central to the applicability of the coarse-graining methods to understand molecular processes. The process of coarse graining leads to an accelerated dynamics, owing to the smoothening of the underlying free-energy landscapes. Often a single time-mapping factor is used to relate the time scales associated with the two representations. We critically examine this idea using a model system ideally suited for this purpose. Single molecular transport properties are studied via molecular dynamics simulations of the CG and atomistic representations of a liquid crystalline, azobenzene containing mesogen, simulated in the smectic and the isotropic phases. The out-of-plane dynamics in the smectic phase occurs via molecular hops from one smectic layer to the next. Hopping can occur via two mechanisms, with and without significant reorientation. The out-of-plane transport can be understood as a superposition of two (one associated with each mode of transport) independent continuous time random walks for which a single time-mapping factor would be rather inadequate. A comparison of the free-energy surfaces, relevant to the out-of-plane transport, qualitatively supports the above observations. Thus, this work underlines the need for building CG models that exhibit both structural and dynamical consistency to the underlying atomistic model.

Time Series Remote Sensing in Monitoring the Spatio-Temporal Dynamics of Plant Invasions: A Study of Invasive Saltcedar (Tamarix Spp.)

NASA Astrophysics Data System (ADS)

Diao, Chunyuan

In today's big data era, the increasing availability of satellite and airborne platforms at various spatial and temporal scales creates unprecedented opportunities to understand the complex and dynamic systems (e.g., plant invasion). Time series remote sensing is becoming more and more important to monitor the earth system dynamics and interactions. To date, most of the time series remote sensing studies have been conducted with the images acquired at coarse spatial scale, due to their relatively high temporal resolution. The construction of time series at fine spatial scale, however, is limited to few or discrete images acquired within or across years. The objective of this research is to advance the time series remote sensing at fine spatial scale, particularly to shift from discrete time series remote sensing to continuous time series remote sensing. The objective will be achieved through the following aims: 1) Advance intra-annual time series remote sensing under the pure-pixel assumption; 2) Advance intra-annual time series remote sensing under the mixed-pixel assumption; 3) Advance inter-annual time series remote sensing in monitoring the land surface dynamics; and 4) Advance the species distribution model with time series remote sensing. Taking invasive saltcedar as an example, four methods (i.e., phenological time series remote sensing model, temporal partial unmixing method, multiyear spectral angle clustering model, and time series remote sensing-based spatially explicit species distribution model) were developed to achieve the objectives. Results indicated that the phenological time series remote sensing model could effectively map saltcedar distributions through characterizing the seasonal phenological dynamics of plant species throughout the year. The proposed temporal partial unmixing method, compared to conventional unmixing methods, could more accurately estimate saltcedar abundance within a pixel by exploiting the adequate temporal signatures of saltcedar. The multiyear spectral angle clustering model could guide the selection of the most representative remotely sensed image for repetitive saltcedar mapping over space and time. Through incorporating spatial autocorrelation, the species distribution model developed in the study could identify the suitable habitats of saltcedar at a fine spatial scale and locate appropriate areas at high risk of saltcedar infestation. Among 10 environmental variables, the distance to the river and the phenological attributes summarized by the time series remote sensing were regarded as the most important. These methods developed in the study provide new perspectives on how the continuous time series can be leveraged under various conditions to investigate the plant invasion dynamics.

An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids.

PubMed

Dahlberg, Jerry; Tkacik, Peter T; Mullany, Brigid; Fleischhauer, Eric; Shahinian, Hossein; Azimi, Farzad; Navare, Jayesh; Owen, Spencer; Bisel, Tucker; Martin, Tony; Sholar, Jodie; Keanini, Russell G

2017-12-04

An analog, macroscopic method for studying molecular-scale hydrodynamic processes in dense gases and liquids is described. The technique applies a standard fluid dynamic diagnostic, particle image velocimetry (PIV), to measure: i) velocities of individual particles (grains), extant on short, grain-collision time-scales, ii) velocities of systems of particles, on both short collision-time- and long, continuum-flow-time-scales, iii) collective hydrodynamic modes known to exist in dense molecular fluids, and iv) short- and long-time-scale velocity autocorrelation functions, central to understanding particle-scale dynamics in strongly interacting, dense fluid systems. The basic system is composed of an imaging system, light source, vibrational sensors, vibrational system with a known media, and PIV and analysis software. Required experimental measurements and an outline of the theoretical tools needed when using the analog technique to study molecular-scale hydrodynamic processes are highlighted. The proposed technique provides a relatively straightforward alternative to photonic and neutron beam scattering methods traditionally used in molecular hydrodynamic studies.

Theoretical restrictions on longest implicit time scales in Markov state models of biomolecular dynamics

NASA Astrophysics Data System (ADS)

Sinitskiy, Anton V.; Pande, Vijay S.

2018-01-01

Markov state models (MSMs) have been widely used to analyze computer simulations of various biomolecular systems. They can capture conformational transitions much slower than an average or maximal length of a single molecular dynamics (MD) trajectory from the set of trajectories used to build the MSM. A rule of thumb claiming that the slowest implicit time scale captured by an MSM should be comparable by the order of magnitude to the aggregate duration of all MD trajectories used to build this MSM has been known in the field. However, this rule has never been formally proved. In this work, we present analytical results for the slowest time scale in several types of MSMs, supporting the above rule. We conclude that the slowest implicit time scale equals the product of the aggregate sampling and four factors that quantify: (1) how much statistics on the conformational transitions corresponding to the longest implicit time scale is available, (2) how good the sampling of the destination Markov state is, (3) the gain in statistics from using a sliding window for counting transitions between Markov states, and (4) a bias in the estimate of the implicit time scale arising from finite sampling of the conformational transitions. We demonstrate that in many practically important cases all these four factors are on the order of unity, and we analyze possible scenarios that could lead to their significant deviation from unity. Overall, we provide for the first time analytical results on the slowest time scales captured by MSMs. These results can guide further practical applications of MSMs to biomolecular dynamics and allow for higher computational efficiency of simulations.

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

D'Huys, Otti, E-mail: otti.dhuys@phy.duke.edu; Haynes, Nicholas D.; Lohmann, Johannes

Autonomous Boolean networks are commonly used to model the dynamics of gene regulatory networks and allow for the prediction of stable dynamical attractors. However, most models do not account for time delays along the network links and noise, which are crucial features of real biological systems. Concentrating on two paradigmatic motifs, the toggle switch and the repressilator, we develop an experimental testbed that explicitly includes both inter-node time delays and noise using digital logic elements on field-programmable gate arrays. We observe transients that last millions to billions of characteristic time scales and scale exponentially with the amount of time delaysmore » between nodes, a phenomenon known as super-transient scaling. We develop a hybrid model that includes time delays along network links and allows for stochastic variation in the delays. Using this model, we explain the observed super-transient scaling of both motifs and recreate the experimentally measured transient distributions.« less

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

Lu, Chun-Yaung; Perez, Danny; Voter, Arthur F., E-mail: afv@lanl.gov

Nuclear quantum effects are important for systems containing light elements, and the effects are more prominent in the low temperature regime where the dynamics also becomes sluggish. We show that parallel replica (ParRep) dynamics, an accelerated molecular dynamics approach for infrequent-event systems, can be effectively combined with ring-polymer molecular dynamics, a semiclassical trajectory approach that gives a good approximation to zero-point and tunneling effects in activated escape processes. The resulting RP-ParRep method is a powerful tool for reaching long time scales in complex infrequent-event systems where quantum dynamics are important. Two illustrative examples, symmetric Eckart barrier crossing and interstitial heliummore » diffusion in Fe and Fe–Cr alloy, are presented to demonstrate the accuracy and long-time scale capability of this approach.« less

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

Out-of-equilibrium dynamics driven by localized time-dependent perturbations at quantum phase transitions

NASA Astrophysics Data System (ADS)

Pelissetto, Andrea; Rossini, Davide; Vicari, Ettore

2018-03-01

We investigate the quantum dynamics of many-body systems subject to local (i.e., restricted to a limited space region) time-dependent perturbations. If the system crosses a quantum phase transition, an off-equilibrium behavior is observed, even for a very slow driving. We show that, close to the transition, time-dependent quantities obey scaling laws. In first-order transitions, the scaling behavior is universal, and some scaling functions can be computed exactly. For continuous transitions, the scaling laws are controlled by the standard critical exponents and by the renormalization-group dimension of the perturbation at the transition. Our protocol can be implemented in existing relatively small quantum simulators, paving the way for a quantitative probe of the universal off-equilibrium scaling behavior, without the need to manipulate systems close to the thermodynamic limit.

On The Ubiquity of Nonstationary Fluvial Suspended Sediment Dynamics: A Call for Long Term Monitoring and Dynamical Sediment Management Strategies

NASA Astrophysics Data System (ADS)

Gray, A. B.

2017-12-01

Watersheds with sufficient monitoring data have been predominantly found to display nonstationary suspended sediment dynamics, whereby the relationship between suspended sediment concentration and discharge changes over time. Despite the importance of suspended sediment as a keystone of geophysical and biochemical processes, and as a primary mediator of water quality, stationary behavior remains largely assumed in the context of these applications. This study presents an investigation into the time dependent behavior of small mountainous rivers draining the coastal ranges of the western continental US over interannual to interdecadal time scales. Of the 250+ small coastal (drainage area < 2x104 km2) watersheds in this region, only 23 have discharge associated suspended sediment concentration time series with base periods of 10 years or more. Event to interdecadal scale nonstationary suspended sediment dynamics were identified throughout these systems. Temporal patterns of non-stationary behavior provided some evidence for spatial coherence, which may be related to synoptic hydro-metrological patterns and regional scale changes in land use patterns. However, the results also highlight the complex, integrative nature of watershed scale fluvial suspended sediment dynamics. This underscores the need for in-depth, forensic approaches for initial processes identification, which require long term, high resolution monitoring efforts in order to adequately inform management. The societal implications of nonstationary sediment dynamics and their controls were further explored through the case of California, USA, where over 150 impairment listings have resulted in more than 50 sediment TMDLs, only 3 of which are flux based - none of which account for non-stationary behavior.

Two reference time scales for studying the dynamic cavitation of liquid films

NASA Technical Reports Server (NTRS)

Sun, D. C.; Brewe, D. E.

1992-01-01

Two formulas, one for the characteristic time of filling a void with the vapor of the surrounding liquid, and one of filling the void by diffusion of the dissolved gas in the liquid, are derived. By comparing these time scales with that of the dynamic operation of oil film bearings, it is concluded that the evaporation process is usually fast enough to fill the cavitation bubble with oil vapor; whereas the diffusion process is much too slow for the dissolved air to liberate itself and enter the cavitation bubble. These results imply that the formation of a two phase fluid in dynamically loaded bearings, as often reported in the literature, is caused by air entrainment. They further indicate a way to simplify the treatment of the dynamic problem of bubble evolution.

Space Technology 5 Multi-Point Observations of Temporal Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, Guan; Wang, Yongli; Slavin, James A.; Strangeway, Robert J.

2008-01-01

Space Technology 5 (ST5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that meso-scale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of approximately 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are approximately 1 min for meso-scale currents and approximately 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

A Dynamically Computed Convective Time Scale for the Kain–Fritsch Convective Parameterization Scheme

EPA Science Inventory

Many convective parameterization schemes define a convective adjustment time scale τ as the time allowed for dissipation of convective available potential energy (CAPE). The Kain–Fritsch scheme defines τ based on an estimate of the advective time period for deep con...

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

DOE PAGES

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.; ...

2016-10-20

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.« less

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

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

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.« less

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

PubMed Central

Sippel, Sebastian; Mahecha, Miguel D.; Hauhs, Michael; Bodesheim, Paul; Kaminski, Thomas; Gans, Fabian; Rosso, Osvaldo A.

2016-01-01

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. We demonstrate here that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics. PMID:27764187

Dispersion of Response Times Reveals Cognitive Dynamics

ERIC Educational Resources Information Center

Holden, John G.; Van Orden, Guy C.; Turvey, Michael T.

2009-01-01

Trial-to-trial variation in word-pronunciation times exhibits 1/f scaling. One explanation is that human performances are consequent on multiplicative interactions among interdependent processes-interaction dominant dynamics. This article describes simulated distributions of pronunciation times in a further test for multiplicative interactions and…

Using Wavelet Analysis To Assist in Identification of Significant Events in Molecular Dynamics Simulations.

PubMed

Heidari, Zahra; Roe, Daniel R; Galindo-Murillo, Rodrigo; Ghasemi, Jahan B; Cheatham, Thomas E

2016-07-25

Long time scale molecular dynamics (MD) simulations of biological systems are becoming increasingly commonplace due to the availability of both large-scale computational resources and significant advances in the underlying simulation methodologies. Therefore, it is useful to investigate and develop data mining and analysis techniques to quickly and efficiently extract the biologically relevant information from the incredible amount of generated data. Wavelet analysis (WA) is a technique that can quickly reveal significant motions during an MD simulation. Here, the application of WA on well-converged long time scale (tens of μs) simulations of a DNA helix is described. We show how WA combined with a simple clustering method can be used to identify both the physical and temporal locations of events with significant motion in MD trajectories. We also show that WA can not only distinguish and quantify the locations and time scales of significant motions, but by changing the maximum time scale of WA a more complete characterization of these motions can be obtained. This allows motions of different time scales to be identified or ignored as desired.

Scaling behavior of online human activity

NASA Astrophysics Data System (ADS)

Zhao, Zhi-Dan; Cai, Shi-Min; Huang, Junming; Fu, Yan; Zhou, Tao

2012-11-01

The rapid development of the Internet technology enables humans to explore the web and record the traces of online activities. From the analysis of these large-scale data sets (i.e., traces), we can get insights about the dynamic behavior of human activity. In this letter, the scaling behavior and complexity of human activity in the e-commerce, such as music, books, and movies rating, are comprehensively investigated by using the detrended fluctuation analysis technique and the multiscale entropy method. Firstly, the interevent time series of rating behaviors of these three types of media show similar scaling properties with exponents ranging from 0.53 to 0.58, which implies that the collective behaviors of rating media follow a process embodying self-similarity and long-range correlation. Meanwhile, by dividing the users into three groups based on their activities (i.e., rating per unit time), we find that the scaling exponents of the interevent time series in the three groups are different. Hence, these results suggest that a stronger long-range correlations exist in these collective behaviors. Furthermore, their information complexities vary in the three groups. To explain the differences of the collective behaviors restricted to the three groups, we study the dynamic behavior of human activity at the individual level, and find that the dynamic behaviors of a few users have extremely small scaling exponents associated with long-range anticorrelations. By comparing the interevent time distributions of four representative users, we can find that the bimodal distributions may bring forth the extraordinary scaling behaviors. These results of the analysis of the online human activity in the e-commerce may not only provide insight into its dynamic behaviors but may also be applied to acquire potential economic interest.

Nonlinear temperature effects on multifractal complexity of metabolic rate of mice

PubMed Central

Bogdanovich, Jose M.; Bozinovic, Francisco

2016-01-01

Complex physiological dynamics have been argued to be a signature of healthy physiological function. Here we test whether the complexity of metabolic rate fluctuations in small endotherms decreases with lower environmental temperatures. To do so, we examine the multifractal temporal scaling properties of the rate of change in oxygen consumption r(VO2), in the laboratory mouse Mus musculus, assessing their long range correlation properties across seven different environmental temperatures, ranging from 0 °C to 30 °C. To do so, we applied multifractal detrended fluctuation analysis (MF-DFA), finding that r(VO2) fluctuations show two scaling regimes. For small time scales below the crossover time (approximately 102 s), either monofractal or weak multifractal dynamics are observed depending on whether Ta < 15 °C or Ta > 15 °C respectively. For larger time scales, r(VO2) fluctuations are characterized by an asymptotic scaling exponent that indicates multifractal anti-persistent or uncorrelated dynamics. For both scaling regimes, a generalization of the multiplicative cascade model provides very good fits for the Renyi exponents τ(q), showing that the infinite number of exponents h(q) can be described by only two independent parameters, a and b. We also show that the long-range correlation structure of r(VO2) time series differs from randomly shuffled series, and may not be explained as an artifact of stochastic sampling of a linear frequency spectrum. These results show that metabolic rate dynamics in a well studied micro-endotherm are consistent with a highly non-linear feedback control system. PMID:27781179

Nonlinear temperature effects on multifractal complexity of metabolic rate of mice.

PubMed

Labra, Fabio A; Bogdanovich, Jose M; Bozinovic, Francisco

2016-01-01

Complex physiological dynamics have been argued to be a signature of healthy physiological function. Here we test whether the complexity of metabolic rate fluctuations in small endotherms decreases with lower environmental temperatures. To do so, we examine the multifractal temporal scaling properties of the rate of change in oxygen consumption r ( VO 2 ), in the laboratory mouse Mus musculus , assessing their long range correlation properties across seven different environmental temperatures, ranging from 0 °C to 30 °C. To do so, we applied multifractal detrended fluctuation analysis (MF-DFA), finding that r(VO 2 ) fluctuations show two scaling regimes. For small time scales below the crossover time (approximately 10 2 s), either monofractal or weak multifractal dynamics are observed depending on whether T a < 15 °C or T a > 15 °C respectively. For larger time scales, r(VO 2 ) fluctuations are characterized by an asymptotic scaling exponent that indicates multifractal anti-persistent or uncorrelated dynamics. For both scaling regimes, a generalization of the multiplicative cascade model provides very good fits for the Renyi exponents τ ( q ), showing that the infinite number of exponents h(q) can be described by only two independent parameters, a and b . We also show that the long-range correlation structure of r(VO 2 ) time series differs from randomly shuffled series, and may not be explained as an artifact of stochastic sampling of a linear frequency spectrum. These results show that metabolic rate dynamics in a well studied micro-endotherm are consistent with a highly non-linear feedback control system.

A challenge to chaotic itinerancy from brain dynamics

NASA Astrophysics Data System (ADS)

Kay, Leslie M.

2003-09-01

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

Association between stride time fractality and gait adaptability during unperturbed and asymmetric walking.

PubMed

Ducharme, Scott W; Liddy, Joshua J; Haddad, Jeffrey M; Busa, Michael A; Claxton, Laura J; van Emmerik, Richard E A

2018-04-01

Human locomotion is an inherently complex activity that requires the coordination and control of neurophysiological and biomechanical degrees of freedom across various spatiotemporal scales. Locomotor patterns must constantly be altered in the face of changing environmental or task demands, such as heterogeneous terrains or obstacles. Variability in stride times occurring at short time scales (e.g., 5-10 strides) is statistically correlated to larger fluctuations occurring over longer time scales (e.g., 50-100 strides). This relationship, known as fractal dynamics, is thought to represent the adaptive capacity of the locomotor system. However, this has not been tested empirically. Thus, the purpose of this study was to determine if stride time fractality during steady state walking associated with the ability of individuals to adapt their gait patterns when locomotor speed and symmetry are altered. Fifteen healthy adults walked on a split-belt treadmill at preferred speed, half of preferred speed, and with one leg at preferred speed and the other at half speed (2:1 ratio asymmetric walking). The asymmetric belt speed condition induced gait asymmetries that required adaptation of locomotor patterns. The slow speed manipulation was chosen in order to determine the impact of gait speed on stride time fractal dynamics. Detrended fluctuation analysis was used to quantify the correlation structure, i.e., fractality, of stride times. Cross-correlation analysis was used to measure the deviation from intended anti-phasing between legs as a measure of gait adaptation. Results revealed no association between unperturbed walking fractal dynamics and gait adaptability performance. However, there was a quadratic relationship between perturbed, asymmetric walking fractal dynamics and adaptive performance during split-belt walking, whereby individuals who exhibited fractal scaling exponents that deviated from 1/f performed the poorest. Compared to steady state preferred walking speed, fractal dynamics increased closer to 1/f when participants were exposed to asymmetric walking. These findings suggest there may not be a relationship between unperturbed preferred or slow speed walking fractal dynamics and gait adaptability. However, the emergent relationship between asymmetric walking fractal dynamics and limb phase adaptation may represent a functional reorganization of the locomotor system (i.e., improved interactivity between degrees of freedom within the system) to be better suited to attenuate externally generated perturbations at various spatiotemporal scales. Copyright © 2018 Elsevier B.V. All rights reserved.

Fast X-Ray Timing: A Window into the Strong-Field Regime

NASA Technical Reports Server (NTRS)

Strohmayer, Tod

2010-01-01

The dynamical time-scales in the vicinity of neutron star surfaces and black hole horizons are in the millisecond range. Over the past decade, timing signatures on such scales, either quasi-periodic oscillations (QPOs) and/or coherent pulsations, have been discovered and studied from both neutron stars and black holes with NASA's Rossi X-ray Timing Explorer, Although theoretical interpretations are still hotly debated, these timing properties almost certainly reflect the dynamics of matter in regions dominated by relativistic gravity. I will survey our current understanding of these timing properties, with a focus on how they might he used as probes of fundamental physics.

Scale relativity: from quantum mechanics to chaotic dynamics.

NASA Astrophysics Data System (ADS)

Nottale, L.

Scale relativity is a new approach to the problem of the origin of fundamental scales and of scaling laws in physics, which consists in generalizing Einstein's principle of relativity to the case of scale transformations of resolutions. We recall here how it leads one to the concept of fractal space-time, and to introduce a new complex time derivative operator which allows to recover the Schrödinger equation, then to generalize it. In high energy quantum physics, it leads to the introduction of a Lorentzian renormalization group, in which the Planck length is reinterpreted as a lowest, unpassable scale, invariant under dilatations. These methods are successively applied to two problems: in quantum mechanics, that of the mass spectrum of elementary particles; in chaotic dynamics, that of the distribution of planets in the Solar System.

Population shuffling between ground and high energy excited states

PubMed Central

Sabo, T Michael; Trent, John O; Lee, Donghan

2015-01-01

Stochastic processes powered by thermal energy lead to protein motions traversing time-scales from picoseconds to seconds. Fundamental to protein functionality is the utilization of these dynamics for tasks such as catalysis, folding, and allostery. A hierarchy of motion is hypothesized to connect and synergize fast and slow dynamics toward performing these essential activities. Population shuffling predicts a “top-down” temporal hierarchy, where slow time-scale conformational interconversion leads to a shuffling of the free energy landscape for fast time-scale events. Until now, population shuffling was only applied to interconverting ground states. Here, we extend the framework of population shuffling to be applicable for a system interconverting between low energy ground and high energy excited states, such as the SH3 domain mutants G48M and A39V/N53P/V55L from the Fyn tyrosine kinase, providing another tool for accessing the structural dynamics of high energy excited states. Our results indicate that the higher energy gauche− rotameric state for the leucine χ2 dihedral angle contributes significantly to the distribution of rotameric states in both the major and minor forms of the SH3 domain. These findings are corroborated with unrestrained molecular dynamics (MD) simulations on both the major and minor states of the SH3 domain demonstrating high correlations between experimental and back-calculated leucine χ2 rotameric populations. Taken together, we demonstrate how fast time-scale rotameric side-chain population distributions can be extracted from slow time-scale conformational exchange data further extending the scope and the applicability of the population shuffling model. PMID:26316263

Population shuffling between ground and high energy excited states.

PubMed

Sabo, T Michael; Trent, John O; Lee, Donghan

2015-11-01

Stochastic processes powered by thermal energy lead to protein motions traversing time-scales from picoseconds to seconds. Fundamental to protein functionality is the utilization of these dynamics for tasks such as catalysis, folding, and allostery. A hierarchy of motion is hypothesized to connect and synergize fast and slow dynamics toward performing these essential activities. Population shuffling predicts a "top-down" temporal hierarchy, where slow time-scale conformational interconversion leads to a shuffling of the free energy landscape for fast time-scale events. Until now, population shuffling was only applied to interconverting ground states. Here, we extend the framework of population shuffling to be applicable for a system interconverting between low energy ground and high energy excited states, such as the SH3 domain mutants G48M and A39V/N53P/V55L from the Fyn tyrosine kinase, providing another tool for accessing the structural dynamics of high energy excited states. Our results indicate that the higher energy gauche - rotameric state for the leucine χ2 dihedral angle contributes significantly to the distribution of rotameric states in both the major and minor forms of the SH3 domain. These findings are corroborated with unrestrained molecular dynamics (MD) simulations on both the major and minor states of the SH3 domain demonstrating high correlations between experimental and back-calculated leucine χ2 rotameric populations. Taken together, we demonstrate how fast time-scale rotameric side-chain population distributions can be extracted from slow time-scale conformational exchange data further extending the scope and the applicability of the population shuffling model. © 2015 The Protein Society.

Confined dynamics of grafted polymer chains in solutions of linear polymer

DOE PAGES

Poling-Skutvik, Ryan D.; Olafson, Katy N.; Narayanan, Suresh; ...

2017-09-11

Here, we measure the dynamics of high molecular weight polystyrene grafted to silica nanoparticles dispersed in semidilute solutions of linear polymer. Structurally, the linear free chains do not penetrate the grafted corona but increase the osmotic pressure of the solution, collapsing the grafted polymer and leading to eventual aggregation of the grafted particles at high matrix concentrations. Dynamically, the relaxations of the grafted polymer are controlled by the solvent viscosity according to the Zimm model on short time scales. On longer time scales, the grafted chains are confined by neighboring grafted chains, preventing full relaxation over the experimental time scale.more » Adding free linear polymer to the solution does not affect the initial Zimm relaxations of the grafted polymer but does increase the confinement of the grafted chains. Finally, our results elucidate the physics underlying the slow relaxations of grafted polymer.« less

Confined dynamics of grafted polymer chains in solutions of linear polymer

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

Poling-Skutvik, Ryan D.; Olafson, Katy N.; Narayanan, Suresh

Here, we measure the dynamics of high molecular weight polystyrene grafted to silica nanoparticles dispersed in semidilute solutions of linear polymer. Structurally, the linear free chains do not penetrate the grafted corona but increase the osmotic pressure of the solution, collapsing the grafted polymer and leading to eventual aggregation of the grafted particles at high matrix concentrations. Dynamically, the relaxations of the grafted polymer are controlled by the solvent viscosity according to the Zimm model on short time scales. On longer time scales, the grafted chains are confined by neighboring grafted chains, preventing full relaxation over the experimental time scale.more » Adding free linear polymer to the solution does not affect the initial Zimm relaxations of the grafted polymer but does increase the confinement of the grafted chains. Finally, our results elucidate the physics underlying the slow relaxations of grafted polymer.« less

ON THE STAR FORMATION LAW FOR SPIRAL AND IRREGULAR GALAXIES

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

Elmegreen, Bruce G., E-mail: bge@us.ibm.com

2015-12-01

A dynamical model for star formation on a galactic scale is proposed in which the interstellar medium is constantly condensing to star-forming clouds on the dynamical time of the average midplane density, and the clouds are constantly being disrupted on the dynamical timescale appropriate for their higher density. In this model, the areal star formation rate scales with the 1.5 power of the total gas column density throughout the main regions of spiral galaxies, and with a steeper power, 2, in the far outer regions and in dwarf irregular galaxies because of the flaring disks. At the same time, theremore » is a molecular star formation law that is linear in the main and outer parts of disks and in dIrrs because the duration of individual structures in the molecular phase is also the dynamical timescale, canceling the additional 0.5 power of surface density. The total gas consumption time scales directly with the midplane dynamical time, quenching star formation in the inner regions if there is no accretion, and sustaining star formation for ∼100 Gyr or more in the outer regions with no qualitative change in gas stability or molecular cloud properties. The ULIRG track follows from high densities in galaxy collisions.« less

Broadband Structural Dynamics: Understanding the Impulse-Response of Structures Across Multiple Length and Time Scales

DTIC Science & Technology

2010-08-18

Spectral domain response calculated • Time domain response obtained through inverse transform Approach 4: WASABI Wavelet Analysis of Structural Anomalies...differences at unity scale! Time Function Transform Apply Spectral Domain Transfer Function Time Function Inverse Transform Transform Transform  mtP

Thermal quantum time-correlation functions from classical-like dynamics

NASA Astrophysics Data System (ADS)

Hele, Timothy J. H.

2017-07-01

Thermal quantum time-correlation functions are of fundamental importance in quantum dynamics, allowing experimentally measurable properties such as reaction rates, diffusion constants and vibrational spectra to be computed from first principles. Since the exact quantum solution scales exponentially with system size, there has been considerable effort in formulating reliable linear-scaling methods involving exact quantum statistics and approximate quantum dynamics modelled with classical-like trajectories. Here, we review recent progress in the field with the development of methods including centroid molecular dynamics , ring polymer molecular dynamics (RPMD) and thermostatted RPMD (TRPMD). We show how these methods have recently been obtained from 'Matsubara dynamics', a form of semiclassical dynamics which conserves the quantum Boltzmann distribution. We also apply the Matsubara formalism to reaction rate theory, rederiving t → 0+ quantum transition-state theory (QTST) and showing that Matsubara-TST, like RPMD-TST, is equivalent to QTST. We end by surveying areas for future progress.

A new heterogeneous asynchronous explicit-implicit time integrator for nonsmooth dynamics

NASA Astrophysics Data System (ADS)

Fekak, Fatima-Ezzahra; Brun, Michael; Gravouil, Anthony; Depale, Bruno

2017-07-01

In computational structural dynamics, particularly in the presence of nonsmooth behavior, the choice of the time-step and the time integrator has a critical impact on the feasibility of the simulation. Furthermore, in some cases, as in the case of a bridge crane under seismic loading, multiple time-scales coexist in the same problem. In that case, the use of multi-time scale methods is suitable. Here, we propose a new explicit-implicit heterogeneous asynchronous time integrator (HATI) for nonsmooth transient dynamics with frictionless unilateral contacts and impacts. Furthermore, we present a new explicit time integrator for contact/impact problems where the contact constraints are enforced using a Lagrange multiplier method. In other words, the aim of this paper consists in using an explicit time integrator with a fine time scale in the contact area for reproducing high frequency phenomena, while an implicit time integrator is adopted in the other parts in order to reproduce much low frequency phenomena and to optimize the CPU time. In a first step, the explicit time integrator is tested on a one-dimensional example and compared to Moreau-Jean's event-capturing schemes. The explicit algorithm is found to be very accurate and the scheme has generally a higher order of convergence than Moreau-Jean's schemes and provides also an excellent energy behavior. Then, the two time scales explicit-implicit HATI is applied to the numerical example of a bridge crane under seismic loading. The results are validated in comparison to a fine scale full explicit computation. The energy dissipated in the implicit-explicit interface is well controlled and the computational time is lower than a full-explicit simulation.

Slow dynamics in translation-invariant quantum lattice models

NASA Astrophysics Data System (ADS)

Michailidis, Alexios A.; Žnidarič, Marko; Medvedyeva, Mariya; Abanin, Dmitry A.; Prosen, Tomaž; Papić, Z.

2018-03-01

Many-body quantum systems typically display fast dynamics and ballistic spreading of information. Here we address the open problem of how slow the dynamics can be after a generic breaking of integrability by local interactions. We develop a method based on degenerate perturbation theory that reveals slow dynamical regimes and delocalization processes in general translation invariant models, along with accurate estimates of their delocalization time scales. Our results shed light on the fundamental questions of the robustness of quantum integrable systems and the possibility of many-body localization without disorder. As an example, we construct a large class of one-dimensional lattice models where, despite the absence of asymptotic localization, the transient dynamics is exceptionally slow, i.e., the dynamics is indistinguishable from that of many-body localized systems for the system sizes and time scales accessible in experiments and numerical simulations.

A unified gas-kinetic scheme for continuum and rarefied flows IV: Full Boltzmann and model equations

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

Liu, Chang, E-mail: cliuaa@ust.hk; Xu, Kun, E-mail: makxu@ust.hk; Sun, Quanhua, E-mail: qsun@imech.ac.cn

Fluid dynamic equations are valid in their respective modeling scales, such as the particle mean free path scale of the Boltzmann equation and the hydrodynamic scale of the Navier–Stokes (NS) equations. With a variation of the modeling scales, theoretically there should have a continuous spectrum of fluid dynamic equations. Even though the Boltzmann equation is claimed to be valid in all scales, many Boltzmann solvers, including direct simulation Monte Carlo method, require the cell resolution to the order of particle mean free path scale. Therefore, they are still single scale methods. In order to study multiscale flow evolution efficiently, themore » dynamics in the computational fluid has to be changed with the scales. A direct modeling of flow physics with a changeable scale may become an appropriate approach. The unified gas-kinetic scheme (UGKS) is a direct modeling method in the mesh size scale, and its underlying flow physics depends on the resolution of the cell size relative to the particle mean free path. The cell size of UGKS is not limited by the particle mean free path. With the variation of the ratio between the numerical cell size and local particle mean free path, the UGKS recovers the flow dynamics from the particle transport and collision in the kinetic scale to the wave propagation in the hydrodynamic scale. The previous UGKS is mostly constructed from the evolution solution of kinetic model equations. Even though the UGKS is very accurate and effective in the low transition and continuum flow regimes with the time step being much larger than the particle mean free time, it still has space to develop more accurate flow solver in the region, where the time step is comparable with the local particle mean free time. In such a scale, there is dynamic difference from the full Boltzmann collision term and the model equations. This work is about the further development of the UGKS with the implementation of the full Boltzmann collision term in the region where it is needed. The central ingredient of the UGKS is the coupled treatment of particle transport and collision in the flux evaluation across a cell interface, where a continuous flow dynamics from kinetic to hydrodynamic scales is modeled. The newly developed UGKS has the asymptotic preserving (AP) property of recovering the NS solutions in the continuum flow regime, and the full Boltzmann solution in the rarefied regime. In the mostly unexplored transition regime, the UGKS itself provides a valuable tool for the non-equilibrium flow study. The mathematical properties of the scheme, such as stability, accuracy, and the asymptotic preserving, will be analyzed in this paper as well.« less

Capturing change: the duality of time-lapse imagery to acquire data and depict ecological dynamics

USGS Publications Warehouse

Brinley Buckley, Emma M.; Allen, Craig R.; Forsberg, Michael; Farrell, Michael; Caven, Andrew J.

2017-01-01

We investigate the scientific and communicative value of time-lapse imagery by exploring applications for data collection and visualization. Time-lapse imagery has a myriad of possible applications to study and depict ecosystems and can operate at unique temporal and spatial scales to bridge the gap between large-scale satellite imagery projects and observational field research. Time-lapse data sequences, linking time-lapse imagery with data visualization, have the ability to make data come alive for a wider audience by connecting abstract numbers to images that root data in time and place. Utilizing imagery from the Platte Basin Timelapse Project, water inundation and vegetation phenology metrics are quantified via image analysis and then paired with passive monitoring data, including streamflow and water chemistry. Dynamic and interactive time-lapse data sequences elucidate the visible and invisible ecological dynamics of a significantly altered yet internationally important river system in central Nebraska.

Stochastic partial differential fluid equations as a diffusive limit of deterministic Lagrangian multi-time dynamics.

PubMed

Cotter, C J; Gottwald, G A; Holm, D D

2017-09-01

In Holm (Holm 2015 Proc. R. Soc. A 471 , 20140963. (doi:10.1098/rspa.2014.0963)), stochastic fluid equations were derived by employing a variational principle with an assumed stochastic Lagrangian particle dynamics. Here we show that the same stochastic Lagrangian dynamics naturally arises in a multi-scale decomposition of the deterministic Lagrangian flow map into a slow large-scale mean and a rapidly fluctuating small-scale map. We employ homogenization theory to derive effective slow stochastic particle dynamics for the resolved mean part, thereby obtaining stochastic fluid partial equations in the Eulerian formulation. To justify the application of rigorous homogenization theory, we assume mildly chaotic fast small-scale dynamics, as well as a centring condition. The latter requires that the mean of the fluctuating deviations is small, when pulled back to the mean flow.

The scientific targets of the SCOPE mission

NASA Astrophysics Data System (ADS)

Fujimoto, M.; Saito, Y.; Tsuda, Y.; Shinohara, I.; Kojima, H.

Future Japanese magnetospheric mission "SCOPE" is now under study (planned to be launched in 2012). The main purpose of this mission is to investigate the dynamic behaviors of plasmas in the Earth's magnetosphere from the view-point of cross-scale coupling. Dynamical collisionless space plasma phenomena, be they large scale as a whole, are chracterized by coupling over various time and spatial scales. The best example would be the magnetic reconnection process, which is a large scale energy conversion process but has a small key region at the heart of its engine. Inside the key region, electron scale dynamics plays the key role in liberating the frozen-in constraint, by which reconnection is allowed to proceed. The SCOPE mission is composed of one large mother satellite and four small daughter satellites. The mother spacecraft will be equiped with the electron detector that has 10 msec time resolution so that scales down to the electron's will be resolved. Three of the four daughter satellites surround the mother satellite 3-dimensionally with the mutual distances between several km and several thousand km, which are varied during the mission. Plasma measurements on these spacecrafts will have 1 sec resolution and will provide information on meso-scale plasma structure. The fourth daughter satellite stays near the mother satellite with the distance less than 100km. By correlation between the two plasma wave instruments on the daughter and the mother spacecrafts, propagation of the waves and the information on the electron scale dynamics will be obtained. By this strategy, both meso- and micro-scale information on dynamics are obtained, that will enable us to investigate the physics of the space plasma from the cross-scale coupling point of view.

Space Technology 5 (ST-5) Observations of Field-Aligned Currents: Temporal Variability

NASA Technical Reports Server (NTRS)

Le, Guan

2010-01-01

Space Technology 5 (ST-5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from STS. The data demonstrate that masoscale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of about 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are about I min for meso-scale currents and about 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Space Technology 5 (ST-5) Multipoint Observations of Temporal and Spatial Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, Guan

2010-01-01

Space Technology 5 (ST-5) is a three micro-satellite constellation deployed into a 300 x 4500 km, dawn-dusk, sun-synchronous polar orbit from March 22 to June 21, 2006, for technology validations. In this paper, we present a study of the temporal variability of field-aligned currents using multi-point magnetic field measurements from ST5. The data demonstrate that mesoscale current structures are commonly embedded within large-scale field-aligned current sheets. The meso-scale current structures are very dynamic with highly variable current density and/or polarity in time scales of about 10 min. They exhibit large temporal variations during both quiet and disturbed times in such time scales. On the other hand, the data also shown that the time scales for the currents to be relatively stable are about 1 min for meso-scale currents and about 10 min for large scale current sheets. These temporal features are obviously associated with dynamic variations of their particle carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of meso-scale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Time Scale Hierarchies in the Functional Organization of Complex Behaviors

PubMed Central

Perdikis, Dionysios; Huys, Raoul; Jirsa, Viktor K.

2011-01-01

Traditional approaches to cognitive modelling generally portray cognitive events in terms of ‘discrete’ states (point attractor dynamics) rather than in terms of processes, thereby neglecting the time structure of cognition. In contrast, more recent approaches explicitly address this temporal dimension, but typically provide no entry points into cognitive categorization of events and experiences. With the aim to incorporate both these aspects, we propose a framework for functional architectures. Our approach is grounded in the notion that arbitrary complex (human) behaviour is decomposable into functional modes (elementary units), which we conceptualize as low-dimensional dynamical objects (structured flows on manifolds). The ensemble of modes at an agent’s disposal constitutes his/her functional repertoire. The modes may be subjected to additional dynamics (termed operational signals), in particular, instantaneous inputs, and a mechanism that sequentially selects a mode so that it temporarily dominates the functional dynamics. The inputs and selection mechanisms act on faster and slower time scales then that inherent to the modes, respectively. The dynamics across the three time scales are coupled via feedback, rendering the entire architecture autonomous. We illustrate the functional architecture in the context of serial behaviour, namely cursive handwriting. Subsequently, we investigate the possibility of recovering the contributions of functional modes and operational signals from the output, which appears to be possible only when examining the output phase flow (i.e., not from trajectories in phase space or time). PMID:21980278

Solute-defect interactions in Al-Mg alloys from diffusive variational Gaussian calculations

NASA Astrophysics Data System (ADS)

Dontsova, E.; Rottler, J.; Sinclair, C. W.

2014-11-01

Resolving atomic-scale defect topologies and energetics with accurate atomistic interaction models provides access to the nonlinear phenomena inherent at atomic length and time scales. Coarse graining the dynamics of such simulations to look at the migration of, e.g., solute atoms, while retaining the rich atomic-scale detail required to properly describe defects, is a particular challenge. In this paper, we present an adaptation of the recently developed "diffusive molecular dynamics" model to describe the energetics and kinetics of binary alloys on diffusive time scales. The potential of the technique is illustrated by applying it to the classic problems of solute segregation to a planar boundary (stacking fault) and edge dislocation in the Al-Mg system. Our approach provides fully dynamical solutions in situations with an evolving energy landscape in a computationally efficient way, where atomistic kinetic Monte Carlo simulations are difficult or impractical to perform.

Dynamic Ocean Management Increases the Efficiency and Efficacy of Fisheries Management

NASA Astrophysics Data System (ADS)

Dunn, D. C.; Maxwell, S.; Boustany, A. M.; Halpin, P. N.

2016-12-01

In response to the inherent dynamic nature of the oceans and continuing difficulty in managing ecosystem impacts of fisheries, interest in the concept of dynamic ocean management, or real-time management of ocean resources, has accelerated in the last several years. However, scientists have yet to quantitatively assess the efficiency of dynamic management over static management. Of particular interest is how scale influences effectiveness, both in terms of how it reflects underlying ecological processes and how this relates to potential efficiency gains. In this presentation, we attempt to address both the empirical evidence gap and further the ecological theory underpinning dynamic management. We illustrate, through the simulation of closures across a range of spatiotemporal scales, that dynamic ocean management can address previously intractable problems at scales associated with coactive and social patterns (e.g., competition, predation, niche partitioning, parasitism and social aggregations). Further, it can significantly improve the efficiency of management: as the resolution of the individual closures used increases (i.e., as the closures become more targeted) the percent of target catch forgone or displaced decreases, the reduction ratio (bycatch/catch) increases, and the total time-area required to achieve the desired bycatch reduction decreases. The coarser management measures (annual time-area closures and monthly full fishery closures) affected up to 4-5x the target catch and required 100-200x the time-area of the dynamic measures (grid-based closures and move-on rules). To achieve similar reductions in juvenile bycatch, the fishery would forgo or displace between USD 15-52 million in landings using a static approach over a dynamic management approach.

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

NASA Astrophysics Data System (ADS)

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

2009-07-01

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

Unification of small and large time scales for biological evolution: deviations from power law.

PubMed

Chowdhury, Debashish; Stauffer, Dietrich; Kunwar, Ambarish

2003-02-14

We develop a unified model that describes both "micro" and "macro" evolutions within a single theoretical framework. The ecosystem is described as a dynamic network; the population dynamics at each node of this network describes the "microevolution" over ecological time scales (i.e., birth, ageing, and natural death of individual organisms), while the appearance of new nodes, the slow changes of the links, and the disappearance of existing nodes accounts for the "macroevolution" over geological time scales (i.e., the origination, evolution, and extinction of species). In contrast to several earlier claims in the literature, we observe strong deviations from power law in the regime of long lifetimes.

Dynamics from Seconds to Hours in Hodgkin-Huxley Model with Time-Dependent Ion Concentrations and Buffer Reservoirs

PubMed Central

Hübel, Niklas; Dahlem, Markus A.

2014-01-01

The classical Hodgkin-Huxley (HH) model neglects the time-dependence of ion concentrations in spiking dynamics. The dynamics is therefore limited to a time scale of milliseconds, which is determined by the membrane capacitance multiplied by the resistance of the ion channels, and by the gating time constants. We study slow dynamics in an extended HH framework that includes time-dependent ion concentrations, pumps, and buffers. Fluxes across the neuronal membrane change intra- and extracellular ion concentrations, whereby the latter can also change through contact to reservoirs in the surroundings. Ion gain and loss of the system is identified as a bifurcation parameter whose essential importance was not realized in earlier studies. Our systematic study of the bifurcation structure and thus the phase space structure helps to understand activation and inhibition of a new excitability in ion homeostasis which emerges in such extended models. Also modulatory mechanisms that regulate the spiking rate can be explained by bifurcations. The dynamics on three distinct slow times scales is determined by the cell volume-to-surface-area ratio and the membrane permeability (seconds), the buffer time constants (tens of seconds), and the slower backward buffering (minutes to hours). The modulatory dynamics and the newly emerging excitable dynamics corresponds to pathological conditions observed in epileptiform burst activity, and spreading depression in migraine aura and stroke, respectively. PMID:25474648

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.

Identifying and correcting non-Markov states in peptide conformational dynamics

NASA Astrophysics Data System (ADS)

Nerukh, Dmitry; Jensen, Christian H.; Glen, Robert C.

2010-02-01

Conformational transitions in proteins define their biological activity and can be investigated in detail using the Markov state model. The fundamental assumption on the transitions between the states, their Markov property, is critical in this framework. We test this assumption by analyzing the transitions obtained directly from the dynamics of a molecular dynamics simulated peptide valine-proline-alanine-leucine and states defined phenomenologically using clustering in dihedral space. We find that the transitions are Markovian at the time scale of ≈50 ps and longer. However, at the time scale of 30-40 ps the dynamics loses its Markov property. Our methodology reveals the mechanism that leads to non-Markov behavior. It also provides a way of regrouping the conformations into new states that now possess the required Markov property of their dynamics.

Quantification of scaling exponent with Crossover type phenomena for different types of forcing in DC glow discharge plasma

NASA Astrophysics Data System (ADS)

Saha, Debajyoti; Shaw, Pankaj Kumar; Ghosh, Sabuj; Janaki, M. S.; Sekar Iyengar, A. N.

2018-01-01

We have carried out a detailed study of scaling region using detrended fractal analysis test by applying different forcing likewise noise, sinusoidal, square on the floating potential fluctuations acquired under different pressures in a DC glow discharge plasma. The transition in the dynamics is observed through recurrence plot techniques which is an efficient method to observe the critical regime transitions in dynamics. The complexity of the nonlinear fluctuation has been revealed with the help of recurrence quantification analysis which is a suitable tool for investigating recurrence, an ubiquitous feature providing a deep insight into the dynamics of real dynamical system. An informal test for stationarity which checks for the compatibility of nonlinear approximations to the dynamics made in different segments in a time series has been proposed. In case of sinusoidal, noise, square forcing applied on fluctuation acquired at P = 0.12 mbar only one dominant scaling region is observed whereas the forcing applied on fluctuation (P = 0.04 mbar) two prominent scaling regions have been explored reliably using different forcing amplitudes indicating the signature of crossover phenomena. Furthermore a persistence long range behavior has been observed in one of these scaling regions. A comprehensive study of the quantification of scaling exponents has been carried out with the increase in amplitude and frequency of sinusoidal, square type of forcings. The scalings exponent is envisaged to be the roughness of the time series. The method provides a single quantitative idea of the scaling exponent to quantify the correlation properties of a signal.

Large-amplitude jumps and non-Gaussian dynamics in highly concentrated hard sphere fluids.

PubMed

Saltzman, Erica J; Schweizer, Kenneth S

2008-05-01

Our microscopic stochastic nonlinear Langevin equation theory of activated dynamics has been employed to study the real-space van Hove function of dense hard sphere fluids and suspensions. At very short times, the van Hove function is a narrow Gaussian. At sufficiently high volume fractions, such that the entropic barrier to relaxation is greater than the thermal energy, its functional form evolves with time to include a rapidly decaying component at small displacements and a long-range exponential tail. The "jump" or decay length scale associated with the tail increases with time (or particle root-mean-square displacement) at fixed volume fraction, and with volume fraction at the mean alpha relaxation time. The jump length at the alpha relaxation time is predicted to be proportional to a measure of the decoupling of self-diffusion and structural relaxation. At long times corresponding to mean displacements of order a particle diameter, the volume fraction dependence of the decay length disappears. A good superposition of the exponential tail feature based on the jump length as a scaling variable is predicted at high volume fractions. Overall, the theoretical results are in good accord with recent simulations and experiments. The basic aspects of the theory are also compared with a classic jump model and a dynamically facilitated continuous time random-walk model. Decoupling of the time scales of different parts of the relaxation process predicted by the theory is qualitatively similar to facilitated dynamics models based on the concept of persistence and exchange times if the elementary event is assumed to be associated with transport on a length scale significantly smaller than the particle size.

Inferring changes in water cycle dynamics of intensively managed landscapes via the theory of time-variant travel time distributions

NASA Astrophysics Data System (ADS)

Danesh-Yazdi, Mohammad; Foufoula-Georgiou, Efi; Karwan, Diana L.; Botter, Gianluca

2016-10-01

Climatic trends and anthropogenic changes in land cover and land use are impacting the hydrology and water quality of streams at the field, watershed, and regional scales in complex ways. In poorly drained agricultural landscapes, subsurface drainage systems have been successful in increasing crop productivity by removing excess soil moisture. However, their hydroecological consequences are still debated in view of the observed increased concentrations of nitrate, phosphorus, and pesticides in many streams, as well as altered runoff volumes and timing. In this study, we employ the recently developed theory of time-variant travel time distributions within the StorAge Selection function framework to quantify changes in water cycle dynamics resulting from the combined climate and land use changes. Our results from analysis of a subbasin in the Minnesota River Basin indicate a significant decrease in the mean travel time of water in the shallow subsurface layer during the growing season under current conditions compared to the pre-1970s conditions. We also find highly damped year-to-year fluctuations in the mean travel time, which we attribute to the "homogenization" of the hydrologic response due to artificial drainage. The dependence of the mean travel time on the spatial heterogeneity of some soil characteristics as well as on the basin scale is further explored via numerical experiments. Simulations indicate that the mean travel time is independent of scale for spatial scales larger than approximately 200 km2, suggesting that hydrologic data from larger basins may be used to infer the average of smaller-scale-driven changes in water cycle dynamics.

Nonlinear analysis of pupillary dynamics.

PubMed

Onorati, Francesco; Mainardi, Luca Tommaso; Sirca, Fabiola; Russo, Vincenzo; Barbieri, Riccardo

2016-02-01

Pupil size reflects autonomic response to different environmental and behavioral stimuli, and its dynamics have been linked to other autonomic correlates such as cardiac and respiratory rhythms. The aim of this study is to assess the nonlinear characteristics of pupil size of 25 normal subjects who participated in a psychophysiological experimental protocol with four experimental conditions, namely “baseline”, “anger”, “joy”, and “sadness”. Nonlinear measures, such as sample entropy, correlation dimension, and largest Lyapunov exponent, were computed on reconstructed signals of spontaneous fluctuations of pupil dilation. Nonparametric statistical tests were performed on surrogate data to verify that the nonlinear measures are an intrinsic characteristic of the signals. We then developed and applied a piecewise linear regression model to detrended fluctuation analysis (DFA). Two joinpoints and three scaling intervals were identified: slope α0, at slow time scales, represents a persistent nonstationary long-range correlation, whereas α1 and α2, at middle and fast time scales, respectively, represent long-range power-law correlations, similarly to DFA applied to heart rate variability signals. Of the computed complexity measures, α0 showed statistically significant differences among experimental conditions (p<0.001). Our results suggest that (a) pupil size at constant light condition is characterized by nonlinear dynamics, (b) three well-defined and distinct long-memory processes exist at different time scales, and (c) autonomic stimulation is partially reflected in nonlinear dynamics. (c) autonomic stimulation is partially reflected in nonlinear dynamics.

Dynamical generalized Hurst exponent as a tool to monitor unstable periods in financial time series

NASA Astrophysics Data System (ADS)

Morales, Raffaello; Di Matteo, T.; Gramatica, Ruggero; Aste, Tomaso

2012-06-01

We investigate the use of the Hurst exponent, dynamically computed over a weighted moving time-window, to evaluate the level of stability/instability of financial firms. Financial firms bailed-out as a consequence of the 2007-2008 credit crisis show a neat increase with time of the generalized Hurst exponent in the period preceding the unfolding of the crisis. Conversely, firms belonging to other market sectors, which suffered the least throughout the crisis, show opposite behaviors. We find that the multifractality of the bailed-out firms increase at the crisis suggesting that the multi fractal properties of the time series are changing. These findings suggest the possibility of using the scaling behavior as a tool to track the level of stability of a firm. In this paper, we introduce a method to compute the generalized Hurst exponent which assigns larger weights to more recent events with respect to older ones. In this way large fluctuations in the remote past are less likely to influence the recent past. We also investigate the scaling associated with the tails of the log-returns distributions and compare this scaling with the scaling associated with the Hurst exponent, observing that the processes underlying the price dynamics of these firms are truly multi-scaling.

A Hierarchical and Dynamic Seascape Framework for Scaling and Comparing Ocean Biodiversity Observations

NASA Astrophysics Data System (ADS)

Kavanaugh, M.; Muller-Karger, F. E.; Montes, E.; Santora, J. A.; Chavez, F.; Messié, M.; Doney, S. C.

2016-02-01

The pelagic ocean is a complex system in which physical, chemical and biological processes interact to shape patterns on multiple spatial and temporal scales and levels of ecological organization. Monitoring and management of marine seascapes must consider a hierarchical and dynamic mosaic, where the boundaries, extent, and location of features change with time. As part of a Marine Biodiversity Observing Network demonstration project, we conducted a multiscale classification of dynamic coastal seascapes in the northeastern Pacific and Gulf of Mexico using multivariate satellite and modeled data. Synoptic patterns were validated using mooring and ship-based observations that spanned multiple trophic levels and were collected as part of several long-term monitoring programs, including the Monterey Bay and Florida Keys National Marine Sanctuaries. Seascape extent and habitat diversity varied as a function of both seasonal and interannual forcing. We discuss the patterns of in situ observations in the context of seascape dynamics and the effect on rarefaction, spatial patchiness, and tracking and comparing ecosystems through time. A seascape framework presents an effective means to translate local biodiversity measurements to broader spatiotemporal scales, scales relevant for modeling the effects of global change and enabling whole-ecosystem management in the dynamic ocean.

InfoSymbiotics/DDDAS - The power of Dynamic Data Driven Applications Systems for New Capabilities in Environmental -, Geo-, and Space- Sciences

NASA Astrophysics Data System (ADS)

Darema, F.

2016-12-01

InfoSymbiotics/DDDAS embodies the power of Dynamic Data Driven Applications Systems (DDDAS), a concept whereby an executing application model is dynamically integrated, in a feed-back loop, with the real-time data-acquisition and control components, as well as other data sources of the application system. Advanced capabilities can be created through such new computational approaches in modeling and simulations, and in instrumentation methods, and include: enhancing the accuracy of the application model; speeding-up the computation to allow faster and more comprehensive models of a system, and create decision support systems with the accuracy of full-scale simulations; in addition, the notion of controlling instrumentation processes by the executing application results in more efficient management of application-data and addresses challenges of how to architect and dynamically manage large sets of heterogeneous sensors and controllers, an advance over the static and ad-hoc ways of today - with DDDAS these sets of resources can be managed adaptively and in optimized ways. Large-Scale-Dynamic-Data encompasses the next wave of Big Data, and namely dynamic data arising from ubiquitous sensing and control in engineered, natural, and societal systems, through multitudes of heterogeneous sensors and controllers instrumenting these systems, and where opportunities and challenges at these "large-scales" relate not only to data size but the heterogeneity in data, data collection modalities, fidelities, and timescales, ranging from real-time data to archival data. In tandem with this important dimension of dynamic data, there is an extended view of Big Computing, which includes the collective computing by networked assemblies of multitudes of sensors and controllers, this range from the high-end to the real-time seamlessly integrated and unified, and comprising the Large-Scale-Big-Computing. InfoSymbiotics/DDDAS engenders transformative impact in many application domains, ranging from the nano-scale to the terra-scale and to the extra-terra-scale. The talk will address opportunities for new capabilities together with corresponding research challenges, with illustrative examples from several application areas including environmental sciences, geosciences, and space sciences.

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

PubMed Central

Ram, Nilam; Gerstorf, Denis

2009-01-01

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

Memory and betweenness preference in temporal networks induced from time series

NASA Astrophysics Data System (ADS)

Weng, Tongfeng; Zhang, Jie; Small, Michael; Zheng, Rui; Hui, Pan

2017-02-01

We construct temporal networks from time series via unfolding the temporal information into an additional topological dimension of the networks. Thus, we are able to introduce memory entropy analysis to unravel the memory effect within the considered signal. We find distinct patterns in the entropy growth rate of the aggregate network at different memory scales for time series with different dynamics ranging from white noise, 1/f noise, autoregressive process, periodic to chaotic dynamics. Interestingly, for a chaotic time series, an exponential scaling emerges in the memory entropy analysis. We demonstrate that the memory exponent can successfully characterize bifurcation phenomenon, and differentiate the human cardiac system in healthy and pathological states. Moreover, we show that the betweenness preference analysis of these temporal networks can further characterize dynamical systems and separate distinct electrocardiogram recordings. Our work explores the memory effect and betweenness preference in temporal networks constructed from time series data, providing a new perspective to understand the underlying dynamical systems.

Capturing Structural Dynamics in Crystalline Silicon Using Chirped Electrons from a Laser Wakefield Accelerator

DOE PAGES

He, Z. -H.; Beaurepaire, B.; Nees, J. A.; ...

2016-11-08

Recent progress in laser wakefield acceleration has led to the emergence of a new generation of electron and X-ray sources that may have enormous benefits for ultrafast science. These novel sources promise to become indispensable tools for the investigation of structural dynamics on the femtosecond time scale, with spatial resolution on the atomic scale. Here in this paper, we demonstrate the use of laser-wakefield-accelerated electron bunches for time-resolved electron diffraction measurements of the structural dynamics of single-crystal silicon nano-membranes pumped by an ultrafast laser pulse. In our proof-of-concept study, we resolve the silicon lattice dynamics on a picosecond time scalemore » by deflecting the momentum-time correlated electrons in the diffraction peaks with a static magnetic field to obtain the time-dependent diffraction efficiency. Further improvements may lead to femtosecond temporal resolution, with negligible pump-probe jitter being possible with future laser-wakefield-accelerator ultrafast-electron-diffraction schemes.« less

Forecasting of magnitude and duration of currency crises based on the analysis of distortions of fractal scaling in exchange rate fluctuations

NASA Astrophysics Data System (ADS)

Uritskaya, Olga Y.

2005-05-01

Results of fractal stability analysis of daily exchange rate fluctuations of more than 30 floating currencies for a 10-year period are presented. It is shown for the first time that small- and large-scale dynamical instabilities of national monetary systems correlate with deviations of the detrended fluctuation analysis (DFA) exponent from the value 1.5 predicted by the efficient market hypothesis. The observed dependence is used for classification of long-term stability of floating exchange rates as well as for revealing various forms of distortion of stable currency dynamics prior to large-scale crises. A normal range of DFA exponents consistent with crisis-free long-term exchange rate fluctuations is determined, and several typical scenarios of unstable currency dynamics with DFA exponents fluctuating beyond the normal range are identified. It is shown that monetary crashes are usually preceded by prolonged periods of abnormal (decreased or increased) DFA exponent, with the after-crash exponent tending to the value 1.5 indicating a more reliable exchange rate dynamics. Statistically significant regression relations (R=0.99, p<0.01) between duration and magnitude of currency crises and the degree of distortion of monofractal patterns of exchange rate dynamics are found. It is demonstrated that the parameters of these relations characterizing small- and large-scale crises are nearly equal, which implies a common instability mechanism underlying these events. The obtained dependences have been used as a basic ingredient of a forecasting technique which provided correct in-sample predictions of monetary crisis magnitude and duration over various time scales. The developed technique can be recommended for real-time monitoring of dynamical stability of floating exchange rate systems and creating advanced early-warning-system models for currency crisis prevention.

Fixation of competing strategies when interacting agents differ in the time scale of strategy updating

NASA Astrophysics Data System (ADS)

Zhang, Jianlei; Weissing, Franz J.; Cao, Ming

2016-09-01

A commonly used assumption in evolutionary game theory is that natural selection acts on individuals in the same time scale; e.g., players use the same frequency to update their strategies. Variation in learning rates within populations suggests that evolutionary game theory may not necessarily be restricted to uniform time scales associated with the game interaction and strategy adaption evolution. In this study, we remove this restricting assumption by dividing the population into fast and slow groups according to the players' strategy updating frequencies and investigate how different strategy compositions of one group influence the evolutionary outcome of the other's fixation probabilities of strategies within its own group. Analytical analysis and numerical calculations are performed to study the evolutionary dynamics of strategies in typical classes of two-player games (prisoner's dilemma game, snowdrift game, and stag-hunt game). The introduction of the heterogeneity in strategy-update time scales leads to substantial changes in the evolution dynamics of strategies. We provide an approximation formula for the fixation probability of mutant types in finite populations and study the outcome of strategy evolution under the weak selection. We find that although heterogeneity in time scales makes the collective evolutionary dynamics more complicated, the possible long-run evolutionary outcome can be effectively predicted under technical assumptions when knowing the population composition and payoff parameters.

Tetrahedron deformation and alignment of perceived vorticity and strain in a turbulent flow

NASA Astrophysics Data System (ADS)

Pumir, Alain; Bodenschatz, Eberhard; Xu, Haitao

2013-03-01

We describe the structure and dynamics of turbulence by the scale-dependent perceived velocity gradient tensor as supported by following four tracers, i.e., fluid particles, that initially form a regular tetrahedron. We report results from experiments in a von Kármán swirling water flow and from numerical simulations of the incompressible Navier-Stokes equation. We analyze the statistics and the dynamics of the perceived rate of strain tensor and vorticity for initially regular tetrahedron of size r0 from the dissipative to the integral scale. Just as for the true velocity gradient, at any instant, the perceived vorticity is also preferentially aligned with the intermediate eigenvector of the perceived rate of strain. However, in the perceived rate of strain eigenframe fixed at a given time t = 0, the perceived vorticity evolves in time such as to align with the strongest eigendirection at t = 0. This also applies to the true velocity gradient. The experimental data at the higher Reynolds number suggests the existence of a self-similar regime in the inertial range. In particular, the dynamics of alignment of the perceived vorticity and strain can be rescaled by t0, the turbulence time scale of the flow when the scale r0 is in the inertial range. For smaller Reynolds numbers we found the dynamics to be scale dependent.

Increasing the power of accelerated molecular dynamics methods and plans to exploit the coming exascale

NASA Astrophysics Data System (ADS)

Voter, Arthur

Many important materials processes take place on time scales that far exceed the roughly one microsecond accessible to molecular dynamics simulation. Typically, this long-time evolution is characterized by a succession of thermally activated infrequent events involving defects in the material. In the accelerated molecular dynamics (AMD) methodology, known characteristics of infrequent-event systems are exploited to make reactive events take place more frequently, in a dynamically correct way. For certain processes, this approach has been remarkably successful, offering a view of complex dynamical evolution on time scales of microseconds, milliseconds, and sometimes beyond. We have recently made advances in all three of the basic AMD methods (hyperdynamics, parallel replica dynamics, and temperature accelerated dynamics (TAD)), exploiting both algorithmic advances and novel parallelization approaches. I will describe these advances, present some examples of our latest results, and discuss what should be possible when exascale computing arrives in roughly five years. Funded by the U.S. Department of Energy, Office of Basic Energy Sciences, Materials Sciences and Engineering Division, and by the Los Alamos Laboratory Directed Research and Development program.

Galactic cannibalism. IV. The evidence-correlations between dynamical time scales and Bautz-Morgan type

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

McGlynn, T.A.; Ostriker, J.P.

1980-11-01

If the luminosity of supergiant cD galaxies in particular, and the Bautz-Morgan sequence of galaxy types in general, is produced by dynamical evolutionary processes, then one expects to find a correlation between dynamical times and ..delta..M/sub 12/, the magnitude difference between first and second brightest cluster members.

Land Use Induced Hydroclimatic Variability Over Large Deforested Areas in Southern Amazon Rainforest

NASA Astrophysics Data System (ADS)

Khanna, J.; Medvigy, D.

2017-12-01

Contemporary Amazonian deforestation, which occurs at scales of a few hundreds of kilometers, has been found to induce systematic changes in the regional dry season precipitation. The replacement of rough forest with smooth pasture induces a low level atmospheric convergence and uplift in the downwind and divergence and subsidence in the upwind deforested areas. The resulting precipitation change is about ±30% of the deforested area mean in the two regions respectively. Compared with the increase in non-precipitating cloudiness triggered by small scale clearings prevalent in the early phases of deforestation, this `dynamical mesoscale circulation' can have regional ecological impacts by altering precipitation seasonality and in turn ecosystem dynamics. However, the seasonality and variability of this phenomenon hasn't been studied. Using observations and numerical simulations this study investigates the relationships between the dynamical mechanism and the local- and continental-scale atmospheric conditions to understand the physical controls on this phenomenon on the inter-annual, inter-seasonal and daily time scales. We find that the strength of the dynamical mechanism is controlled mostly by regional scale thermal and dynamical conditions of the boundary layer and not the continental and global scale atmospheric state. The lifting condensation level (thermodynamic control) and wind speed (dynamic control) within the boundary layer have the largest and positive correlations with the dipole strength, which is true although not always significant across time scales. Due to this dependence it is found to be strongest during parts of the year when the atmosphere is relatively stable. Hence, overall this phenomenon is found to be the prevalent convective triggering mechanism during the dry and parts of transition seasons (especially spring), significantly affecting the hydroclimate during this period.

Population clocks: motor timing with neural dynamics

PubMed Central

Buonomano, Dean V.; Laje, Rodrigo

2010-01-01

An understanding of sensory and motor processing will require elucidation of the mechanisms by which the brain tells time. Open questions relate to whether timing relies on dedicated or intrinsic mechanisms and whether distinct mechanisms underlie timing across scales and modalities. Although experimental and theoretical studies support the notion that neural circuits are intrinsically capable of sensory timing on short scales, few general models of motor timing have been proposed. For one class of models, population clocks, it is proposed that time is encoded in the time-varying patterns of activity of a population of neurons. We argue that population clocks emerge from the internal dynamics of recurrently connected networks, are biologically realistic and account for many aspects of motor timing. PMID:20889368

Charge carrier recombination dynamics in perovskite and polymer solar cells

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

Paulke, Andreas; Kniepert, Juliane; Kurpiers, Jona

2016-03-14

Time-delayed collection field experiments are applied to planar organometal halide perovskite (CH{sub 3}NH{sub 3}PbI{sub 3}) based solar cells to investigate charge carrier recombination in a fully working solar cell at the nanosecond to microsecond time scale. Recombination of mobile (extractable) charges is shown to follow second-order recombination dynamics for all fluences and time scales tested. Most importantly, the bimolecular recombination coefficient is found to be time-dependent, with an initial value of ca. 10{sup −9} cm{sup 3}/s and a progressive reduction within the first tens of nanoseconds. Comparison to the prototypical organic bulk heterojunction device PTB7:PC{sub 71}BM yields important differences with regardmore » to the mechanism and time scale of free carrier recombination.« less

Coordinated Approaches to Quantify Long-Term Ecosystem dynamics in Response to Global Change

USDA-ARS?s Scientific Manuscript database

Climate change and its impact on ecosystems are usually assessed at decadal and century time scales. Ecological responses to climate change at those scales are strongly regulated by long-term processes, such as changes in species composition, carbon dynamics in soil and by big trees, and nutrient r...

Neural Computations in a Dynamical System with Multiple Time Scales.

PubMed

Mi, Yuanyuan; Lin, Xiaohan; Wu, Si

2016-01-01

Neural systems display rich short-term dynamics at various levels, e.g., spike-frequency adaptation (SFA) at the single-neuron level, and short-term facilitation (STF) and depression (STD) at the synapse level. These dynamical features typically cover a broad range of time scales and exhibit large diversity in different brain regions. It remains unclear what is the computational benefit for the brain to have such variability in short-term dynamics. In this study, we propose that the brain can exploit such dynamical features to implement multiple seemingly contradictory computations in a single neural circuit. To demonstrate this idea, we use continuous attractor neural network (CANN) as a working model and include STF, SFA and STD with increasing time constants in its dynamics. Three computational tasks are considered, which are persistent activity, adaptation, and anticipative tracking. These tasks require conflicting neural mechanisms, and hence cannot be implemented by a single dynamical feature or any combination with similar time constants. However, with properly coordinated STF, SFA and STD, we show that the network is able to implement the three computational tasks concurrently. We hope this study will shed light on the understanding of how the brain orchestrates its rich dynamics at various levels to realize diverse cognitive functions.

Stochastic partial differential fluid equations as a diffusive limit of deterministic Lagrangian multi-time dynamics

PubMed Central

Cotter, C. J.

2017-01-01

In Holm (Holm 2015 Proc. R. Soc. A 471, 20140963. (doi:10.1098/rspa.2014.0963)), stochastic fluid equations were derived by employing a variational principle with an assumed stochastic Lagrangian particle dynamics. Here we show that the same stochastic Lagrangian dynamics naturally arises in a multi-scale decomposition of the deterministic Lagrangian flow map into a slow large-scale mean and a rapidly fluctuating small-scale map. We employ homogenization theory to derive effective slow stochastic particle dynamics for the resolved mean part, thereby obtaining stochastic fluid partial equations in the Eulerian formulation. To justify the application of rigorous homogenization theory, we assume mildly chaotic fast small-scale dynamics, as well as a centring condition. The latter requires that the mean of the fluctuating deviations is small, when pulled back to the mean flow. PMID:28989316

Non-monotonicity and divergent time scale in Axelrod model dynamics

NASA Astrophysics Data System (ADS)

Vazquez, F.; Redner, S.

2007-04-01

We study the evolution of the Axelrod model for cultural diversity, a prototypical non-equilibrium process that exhibits rich dynamics and a dynamic phase transition between diversity and an inactive state. We consider a simple version of the model in which each individual possesses two features that can assume q possibilities. Within a mean-field description in which each individual has just a few interaction partners, we find a phase transition at a critical value qc between an active, diverse state for q < qc and a frozen state. For q lesssim qc, the density of active links is non-monotonic in time and the asymptotic approach to the steady state is controlled by a time scale that diverges as (q-qc)-1/2.

Wavepacket dynamics in one-dimensional system with long-range correlated disorder

NASA Astrophysics Data System (ADS)

Yamada, Hiroaki S.

2018-03-01

We numerically investigate dynamical property in the one-dimensional tight-binding model with long-range correlated disorder having power spectrum 1 /fα (α: spectrum exponent) generated by Fourier filtering method. For relatively small α <αc (=2) time-dependence of mean square displacement (MSD) of the initially localized wavepacket shows ballistic spread and localizes as time elapses. It is shown that α-dependence of the dynamical localization length determined by the MSD exhibits a simple scaling law in the localization regime for the relatively weak disorder strength W. Furthermore, scaled MSD by the dynamical localization length almost obeys an universal function from the ballistic to the localization regime in the various combinations of the parameters α and W.

Mapping hydration dynamics around a protein surface

PubMed Central

Zhang, Luyuan; Wang, Lijuan; Kao, Ya-Ting; Qiu, Weihong; Yang, Yi; Okobiah, Oghaghare; Zhong, Dongping

2007-01-01

Protein surface hydration is fundamental to its structure and activity. We report here the direct mapping of global hydration dynamics around a protein in its native and molten globular states, using a tryptophan scan by site-specific mutations. With 16 tryptophan mutants and in 29 different positions and states, we observed two robust, distinct water dynamics in the hydration layer on a few (≈1–8 ps) and tens to hundreds of picoseconds (≈20–200 ps), representing the initial local relaxation and subsequent collective network restructuring, respectively. Both time scales are strongly correlated with protein's structural and chemical properties. These results reveal the intimate relationship between hydration dynamics and protein fluctuations and such biologically relevant water–protein interactions fluctuate on picosecond time scales. PMID:18003912

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

NASA Astrophysics Data System (ADS)

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

2007-08-01

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

Multiple time-scales and the developmental dynamics of social systems

PubMed Central

Flack, Jessica C.

2012-01-01

To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the ‘coarseness’ of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems. PMID:22641819

Multiple time-scales and the developmental dynamics of social systems.

PubMed

Flack, Jessica C

2012-07-05

To build a theory of social complexity, we need to understand how aggregate social properties arise from individual interaction rules. Here, I review a body of work on the developmental dynamics of pigtailed macaque social organization and conflict management that provides insight into the mechanistic causes of multi-scale social systems. In this model system coarse-grained, statistical representations of collective dynamics are more predictive of the future state of the system than the constantly in-flux behavioural patterns at the individual level. The data suggest that individuals can perceive and use these representations for strategical decision-making. As an interaction history accumulates the coarse-grained representations consolidate. This constrains individual behaviour and provides the foundations for new levels of organization. The time-scales on which these representations change impact whether the consolidating higher-levels can be modified by individuals and collectively. The time-scales appear to be a function of the 'coarseness' of the representations and the character of the collective dynamics over which they are averages. The data suggest that an advantage of multiple timescales is that they allow social systems to balance tradeoffs between predictability and adaptability. I briefly discuss the implications of these findings for cognition, social niche construction and the evolution of new levels of organization in biological systems.

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.

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

De Marco, Luigi; Department of Chemistry, James Frank Institute, and The Institute for Biophysical Dynamics, The University of Chicago, 929 E 57th Street, Chicago, Illinois 60637; Fournier, Joseph A.

Water’s extended hydrogen-bond network results in rich and complex dynamics on the sub-picosecond time scale. In this paper, we present a comprehensive analysis of the two-dimensional infrared (2D IR) spectrum of O–H stretching vibrations in liquid H{sub 2}O and their interactions with bending and intermolecular vibrations. By exploring the dependence of the spectrum on waiting time, temperature, and laser polarization, we refine our molecular picture of water’s complex ultrafast dynamics. The spectral evolution following excitation of the O–H stretching resonance reveals vibrational dynamics on the 50–300 fs time scale that are dominated by intermolecular delocalization. These O–H stretch excitons aremore » a result of the anharmonicity of the nuclear potential energy surface that arises from the hydrogen-bonding interaction. The extent of O–H stretching excitons is characterized through 2D depolarization measurements that show spectrally dependent delocalization in agreement with theoretical predictions. Furthermore, we show that these dynamics are insensitive to temperature, indicating that the exciton dynamics alone set the important time scales in the system. Finally, we study the evolution of the O–H stretching mode, which shows highly non-adiabatic dynamics suggestive of vibrational conical intersections. We argue that the so-called heating, commonly observed within ∼1 ps in nonlinear IR spectroscopy of water, is a nonequilibrium state better described by a kinetic temperature rather than a Boltzmann distribution. Our conclusions imply that the collective nature of water vibrations should be considered in describing aqueous solvation.« less

Characteristic dynamics near two coalescing eigenvalues incorporating continuum threshold effects

NASA Astrophysics Data System (ADS)

Garmon, Savannah; Ordonez, Gonzalo

2017-06-01

It has been reported in the literature that the survival probability P(t) near an exceptional point where two eigenstates coalesce should generally exhibit an evolution P (t ) ˜t2e-Γ t, in which Γ is the decay rate of the coalesced eigenstate; this has been verified in a microwave billiard experiment [B. Dietz et al., Phys. Rev. E 75, 027201 (2007)]. However, the heuristic effective Hamiltonian that is usually employed to obtain this result ignores the possible influence of the continuum threshold on the dynamics. By contrast, in this work we employ an analytical approach starting from the microscopic Hamiltonian representing two simple models in order to show that the continuum threshold has a strong influence on the dynamics near exceptional points in a variety of circumstances. To report our results, we divide the exceptional points in Hermitian open quantum systems into two cases: at an EP2A two virtual bound states coalesce before forming a resonance, anti-resonance pair with complex conjugate eigenvalues, while at an EP2B two resonances coalesce before forming two different resonances. For the EP2B, which is the case studied in the microwave billiard experiment, we verify that the survival probability exhibits the previously reported modified exponential decay on intermediate time scales, but this is replaced with an inverse power law on very long time scales. Meanwhile, for the EP2A the influence from the continuum threshold is so strong that the evolution is non-exponential on all time scales and the heuristic approach fails completely. When the EP2A appears very near the threshold, we obtain the novel evolution P (t ) ˜1 -C1√{t } on intermediate time scales, while further away the parabolic decay (Zeno dynamics) on short time scales is enhanced.

Dynamics of Bottlebrush Networks

NASA Astrophysics Data System (ADS)

Cao, Zhen; Daniel, William; Vatankhah-Varnosfaderani, Mohammad; Sheiko, Sergei; Dobrynin, Andrey

The deformation dynamics of bottlebrush networks in a melt state is studied using a combination of theoretical, computational, and experimental techniques. Three main molecular relaxation processes are identified in these systems: (i) relaxation of the side chains, (ii) relaxation of the bottlebrush backbones on length scales shorter than the bottlebrush Kuhn length (bK) , and (iii) relaxation of the bottlebrush network strands between cross-links. The relaxation of side chains having a degree of polymerization (DP), nsc, dominates the network dynamics on the time scales τ0 < t <=τsc , where τ0 and τsc τ0 (nsc + 1)2 are the characteristic relaxation times of monomeric units and side chains, respectively. In this time interval, the shear modulus at small deformations decays with time as G0BB (t) t - 1 / 2. On time scales t >τsc, bottlebrush elastomers behave as networks of filaments with a shear modulus G0BB (t) (nsc + 1)- 1 / 4t - 1 / 2 . Finally, the response of the bottlebrush networks becomes time independent at times scales longer than the Rouse time of the bottlebrush network strands. In this time interval, the network shear modulus depends on the network molecular parameters as G0BB (t) (nsc + 1)-1N-1 . Analysis of the simulation data shows that the stress evolution in the bottlebrush networks during constant strain-rate deformation can be described by a universal function. NSF DMR-1409710, DMR-1407645, DMR-1624569, DMR-1436201.

Cardiac interbeat interval dynamics from childhood to senescence : comparison of conventional and new measures based on fractals and chaos theory

NASA Technical Reports Server (NTRS)

Pikkujamsa, S. M.; Makikallio, T. H.; Sourander, L. B.; Raiha, I. J.; Puukka, P.; Skytta, J.; Peng, C. K.; Goldberger, A. L.; Huikuri, H. V.

1999-01-01

BACKGROUND: New methods of R-R interval variability based on fractal scaling and nonlinear dynamics ("chaos theory") may give new insights into heart rate dynamics. The aims of this study were to (1) systematically characterize and quantify the effects of aging from early childhood to advanced age on 24-hour heart rate dynamics in healthy subjects; (2) compare age-related changes in conventional time- and frequency-domain measures with changes in newly derived measures based on fractal scaling and complexity (chaos) theory; and (3) further test the hypothesis that there is loss of complexity and altered fractal scaling of heart rate dynamics with advanced age. METHODS AND RESULTS: The relationship between age and cardiac interbeat (R-R) interval dynamics from childhood to senescence was studied in 114 healthy subjects (age range, 1 to 82 years) by measurement of the slope, beta, of the power-law regression line (log power-log frequency) of R-R interval variability (10(-4) to 10(-2) Hz), approximate entropy (ApEn), short-term (alpha(1)) and intermediate-term (alpha(2)) fractal scaling exponents obtained by detrended fluctuation analysis, and traditional time- and frequency-domain measures from 24-hour ECG recordings. Compared with young adults (<40 years old, n=29), children (<15 years old, n=27) showed similar complexity (ApEn) and fractal correlation properties (alpha(1), alpha(2), beta) of R-R interval dynamics despite lower spectral and time-domain measures. Progressive loss of complexity (decreased ApEn, r=-0.69, P<0.001) and alterations of long-term fractal-like heart rate behavior (increased alpha(2), r=0.63, decreased beta, r=-0.60, P<0.001 for both) were observed thereafter from middle age (40 to 60 years, n=29) to old age (>60 years, n=29). CONCLUSIONS: Cardiac interbeat interval dynamics change markedly from childhood to old age in healthy subjects. Children show complexity and fractal correlation properties of R-R interval time series comparable to those of young adults, despite lower overall heart rate variability. Healthy aging is associated with R-R interval dynamics showing higher regularity and altered fractal scaling consistent with a loss of complex variability.

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

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

Ghil, M.; Childress, S.

1987-01-01

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

Self-organization in leaky threshold systems: The influence of near-mean field dynamics and its implications for earthquakes, neurobiology, and forecasting

PubMed Central

Rundle, J. B.; Tiampo, K. F.; Klein, W.; Sá Martins, J. S.

2002-01-01

Threshold systems are known to be some of the most important nonlinear self-organizing systems in nature, including networks of earthquake faults, neural networks, superconductors and semiconductors, and the World Wide Web, as well as political, social, and ecological systems. All of these systems have dynamics that are strongly correlated in space and time, and all typically display a multiplicity of spatial and temporal scales. Here we discuss the physics of self-organization in earthquake threshold systems at two distinct scales: (i) The “microscopic” laboratory scale, in which consideration of results from simulations leads to dynamical equations that can be used to derive the results obtained from sliding friction experiments, and (ii) the “macroscopic” earthquake fault-system scale, in which the physics of strongly correlated earthquake fault systems can be understood by using time-dependent state vectors defined in a Hilbert space of eigenstates, similar in many respects to the mathematics of quantum mechanics. In all of these systems, long-range interactions induce the existence of locally ergodic dynamics. The existence of dissipative effects leads to the appearance of a “leaky threshold” dynamics, equivalent to a new scaling field that controls the size of nucleation events relative to the size of background fluctuations. At the macroscopic earthquake fault-system scale, these ideas show considerable promise as a means of forecasting future earthquake activity. PMID:11875204

Li-Yorke Chaos in Hybrid Systems on a Time Scale

NASA Astrophysics Data System (ADS)

Akhmet, Marat; Fen, Mehmet Onur

2015-12-01

By using the reduction technique to impulsive differential equations [Akhmet & Turan, 2006], we rigorously prove the presence of chaos in dynamic equations on time scales (DETS). The results of the present study are based on the Li-Yorke definition of chaos. This is the first time in the literature that chaos is obtained for DETS. An illustrative example is presented by means of a Duffing equation on a time scale.

Human dynamics: Darwin and Einstein correspondence patterns.

PubMed

Oliveira, João Gama; Barabási, Albert-László

2005-10-27

In an era when letters were the main means of exchanging scientific ideas and results, Charles Darwin (1809-82) and Albert Einstein (1879-1955) were notably prolific correspondents. But did their patterns of communication differ from those associated with the instant-access e-mail of modern times? Here we show that, although the means have changed, the communication dynamics have not: Darwin's and Einstein's patterns of correspondence and today's electronic exchanges follow the same scaling laws. However, the response times of their surface-mail communication is described by a different scaling exponent from e-mail communication, providing evidence for a new class of phenomena in human dynamics.

Multifractality and heteroscedastic dynamics: An application to time series analysis

NASA Astrophysics Data System (ADS)

Nascimento, C. M.; Júnior, H. B. N.; Jennings, H. D.; Serva, M.; Gleria, Iram; Viswanathan, G. M.

2008-01-01

An increasingly important problem in physics concerns scale invariance symmetry in diverse complex systems, often characterized by heteroscedastic dynamics. We investigate the nature of the relationship between the heteroscedastic and fractal aspects of the dynamics of complex systems, by analyzing the sensitivity to heteroscedasticity of the scaling properties of weakly nonstationary time series. By using multifractal detrended fluctuation analysis, we study the singularity spectra of currency exchange rate fluctuations, after partially or completely eliminating n-point correlations via data shuffling techniques. We conclude that heteroscedasticity can significantly increase multifractality and interpret these findings in the context of self-organizing and adaptive complex systems.

Interaction between Liénard and Ikeda dynamics in a nonlinear electro-optical oscillator with delayed bandpass feedback.

PubMed

Marquez, Bicky A; Larger, Laurent; Brunner, Daniel; Chembo, Yanne K; Jacquot, Maxime

2016-12-01

We report on experimental and theoretical analysis of the complex dynamics generated by a nonlinear time-delayed electro-optic bandpass oscillator. We investigate the interaction between the slow- and fast-scale dynamics of autonomous oscillations in the breather regime. We analyze in detail the coupling between the fast-scale behavior associated to a characteristic low-pass Ikeda behavior and the slow-scale dynamics associated to a Liénard limit-cycle. Finally, we show that when projected onto a two-dimensional phase space, the attractors corresponding to periodic and chaotic breathers display a spiral-like pattern, which strongly depends on the shape of the nonlinear function.

Direct comparison of elastic incoherent neutron scattering experiments with molecular dynamics simulations of DMPC phase transitions.

PubMed

Aoun, Bachir; Pellegrini, Eric; Trapp, Marcus; Natali, Francesca; Cantù, Laura; Brocca, Paola; Gerelli, Yuri; Demé, Bruno; Marek Koza, Michael; Johnson, Mark; Peters, Judith

2016-04-01

Neutron scattering techniques have been employed to investigate 1,2-dimyristoyl-sn -glycero-3-phosphocholine (DMPC) membranes in the form of multilamellar vesicles (MLVs) and deposited, stacked multilamellar-bilayers (MLBs), covering transitions from the gel to the liquid phase. Neutron diffraction was used to characterise the samples in terms of transition temperatures, whereas elastic incoherent neutron scattering (EINS) demonstrates that the dynamics on the sub-macromolecular length-scale and pico- to nano-second time-scale are correlated with the structural transitions through a discontinuity in the observed elastic intensities and the derived mean square displacements. Molecular dynamics simulations have been performed in parallel focussing on the length-, time- and temperature-scales of the neutron experiments. They correctly reproduce the structural features of the main gel-liquid phase transition. Particular emphasis is placed on the dynamical amplitudes derived from experiment and simulations. Two methods are used to analyse the experimental data and mean square displacements. They agree within a factor of 2 irrespective of the probed time-scale, i.e. the instrument utilized. Mean square displacements computed from simulations show a comparable level of agreement with the experimental values, albeit, the best match with the two methods varies for the two instruments. Consequently, experiments and simulations together give a consistent picture of the structural and dynamical aspects of the main lipid transition and provide a basis for future, theoretical modelling of dynamics and phase behaviour in membranes. The need for more detailed analytical models is pointed out by the remaining variation of the dynamical amplitudes derived in two different ways from experiments on the one hand and simulations on the other.

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

NASA Astrophysics Data System (ADS)

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

2008-07-01

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

System-level power optimization for real-time distributed embedded systems

NASA Astrophysics Data System (ADS)

Luo, Jiong

Power optimization is one of the crucial design considerations for modern electronic systems. In this thesis, we present several system-level power optimization techniques for real-time distributed embedded systems, based on dynamic voltage scaling, dynamic power management, and management of peak power and variance of the power profile. Dynamic voltage scaling has been widely acknowledged as an important and powerful technique to trade off dynamic power consumption and delay. Efficient dynamic voltage scaling requires effective variable-voltage scheduling mechanisms that can adjust voltages and clock frequencies adaptively based on workloads and timing constraints. For this purpose, we propose static variable-voltage scheduling algorithms utilizing criticalpath driven timing analysis for the case when tasks are assumed to have uniform switching activities, as well as energy-gradient driven slack allocation for a more general scenario. The proposed techniques can achieve closeto-optimal power savings with very low computational complexity, without violating any real-time constraints. We also present algorithms for power-efficient joint scheduling of multi-rate periodic task graphs along with soft aperiodic tasks. The power issue is addressed through both dynamic voltage scaling and power management. Periodic task graphs are scheduled statically. Flexibility is introduced into the static schedule to allow the on-line scheduler to make local changes to PE schedules through resource reclaiming and slack stealing, without interfering with the validity of the global schedule. We provide a unified framework in which the response times of aperiodic tasks and power consumption are dynamically optimized simultaneously. Interconnection network fabrics point to a new generation of power-efficient and scalable interconnection architectures for distributed embedded systems. As the system bandwidth continues to increase, interconnection networks become power/energy limited as well. Variable-frequency links have been designed by circuit designers for both parallel and serial links, which can adaptively regulate the supply voltage of transceivers to a desired link frequency, to exploit the variations in bandwidth requirement for power savings. We propose solutions for simultaneous dynamic voltage scaling of processors and links. The proposed solution considers real-time scheduling, flow control, and packet routing jointly. It can trade off the power consumption on processors and communication links via efficient slack allocation, and lead to more power savings than dynamic voltage scaling on processors alone. For battery-operated systems, the battery lifespan is an important concern. Due to the effects of discharge rate and battery recovery, the discharge pattern of batteries has an impact on the battery lifespan. Battery models indicate that even under the same average power consumption, reducing peak power current and variance in the power profile can increase the battery efficiency and thereby prolong battery lifetime. To take advantage of these effects, we propose battery-driven scheduling techniques for embedded applications, to reduce the peak power and the variance in the power profile of the overall system under real-time constraints. The proposed scheduling algorithms are also beneficial in addressing reliability and signal integrity concerns by effectively controlling peak power and variance of the power profile.

Real-time high-resolution heterodyne-based measurements of spectral dynamics in fibre lasers

PubMed Central

Sugavanam, Srikanth; Fabbri, Simon; Le, Son Thai; Lobach, Ivan; Kablukov, Sergey; Khorev, Serge; Churkin, Dmitry

2016-01-01

Conventional tools for measurement of laser spectra (e.g. optical spectrum analysers) capture data averaged over a considerable time period. However, the generation spectrum of many laser types may involve spectral dynamics whose relatively fast time scale is determined by their cavity round trip period, calling for instrumentation featuring both high temporal and spectral resolution. Such real-time spectral characterisation becomes particularly challenging if the laser pulses are long, or they have continuous or quasi-continuous wave radiation components. Here we combine optical heterodyning with a technique of spatio-temporal intensity measurements that allows the characterisation of such complex sources. Fast, round-trip-resolved spectral dynamics of cavity-based systems in real-time are obtained, with temporal resolution of one cavity round trip and frequency resolution defined by its inverse (85 ns and 24 MHz respectively are demonstrated). We also show how under certain conditions for quasi-continuous wave sources, the spectral resolution could be further increased by a factor of 100 by direct extraction of phase information from the heterodyned dynamics or by using double time scales within the spectrogram approach. PMID:26984634

Solar and interplanetary dynamics; Proceedings of the Symposium, Harvard University, Cambridge, Mass., August 27-31, 1979

NASA Technical Reports Server (NTRS)

Dryer, M. (Editor); Tandberg-Hanssen, E.

1980-01-01

The symposium focuses on solar phenomena as the source of transient events propagating through the solar system, and theoretical and observational assessments of the dynamic processes involved in these events. The topics discussed include the life history of coronal structures and fields, coronal and interplanetary responses to long time scale phenomena, solar transient phenomena affecting the corona and interplanetary medium, coronal and interplanetary responses to short time scale phenomena, and future directions.

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.

Determination of Protein Surface Hydration by Systematic Charge Mutations

NASA Astrophysics Data System (ADS)

Yang, Jin; Jia, Menghui; Qin, Yangzhong; Wang, Dihao; Pan, Haifeng; Wang, Lijuan; Xu, Jianhua; Zhong, Dongping; Dongping Zhong Collaboration; Jianhua Xu Collaboration

Protein surface hydration is critical to its structural stability, flexibility, dynamics and function. Recent observations of surface solvation on picosecond time scales have evoked debate on the origin of such relatively slow motions, from hydration water or protein charged sidechains, especially with molecular dynamics simulations. Here, we used a unique nuclease with a single tryptophan as a local probe and systematically mutated neighboring three charged residues to differentiate the contributions from hydration water and charged sidechains. By mutations of alternative one and two and all three charged residues, we observed slight increases in the total tryptophan Stokes shifts with less neighboring charged residue(s) and found insensitivity of charged sidechains to the relaxation patterns. The dynamics is correlated with hydration water relaxation with the slowest time in a dense charged environment and the fastest time at a hydrophobic site. On such picosecond time scales, the protein surface motion is restricted. The total Stokes shifts are dominantly from hydration water relaxation and the slow dynamics is from water-driven relaxation, coupled with local protein fluctuations.

Lorentzian symmetry predicts universality beyond scaling laws

NASA Astrophysics Data System (ADS)

Watson, Stephen J.

2017-06-01

We present a covariant theory for the ageing characteristics of phase-ordering systems that possess dynamical symmetries beyond mere scalings. A chiral spin dynamics which conserves the spin-up (+) and spin-down (-) fractions, μ+ and μ- , serves as the emblematic paradigm of our theory. Beyond a parabolic spatio-temporal scaling, we discover a hidden Lorentzian dynamical symmetry therein, and thereby prove that the characteristic length L of spin domains grows in time t according to L = \\fracβ{\\sqrt{1 - σ^2}}t\\frac{1{2}} , where σ:= μ+ - μ- (the invariant spin-excess) and β is a universal constant. Furthermore, the normalised length distributions of the spin-up and the spin-down domains each provably adopt a coincident universal (σ-independent) time-invariant form, and this supra-universal probability distribution is empirically verified to assume a form reminiscent of the Wigner surmise.

Effects of individual, community and landscape drivers on the dynamics of a wildland forest epidemic

Treesearch

Sarah E. Haas; J. Hall Cushman; Whalen W. Dillon; Nathan E. Rank; David M. Rizzo; Ross K. Meentemeyer

2016-01-01

The challenges posed by observing host-pathogen-environment interactions across large geographic extents and over meaningful time scales limit our ability to understand and manage wildland epidemics. We conducted a landscape-scale, longitudinal study designed to analyze the dynamics of sudden oak death (an emerging forest disease caused by Phytophthora...

Real-time quantum cascade laser-based infrared microspectroscopy in-vivo

NASA Astrophysics Data System (ADS)

Kröger-Lui, N.; Haase, K.; Pucci, A.; Schönhals, A.; Petrich, W.

2016-03-01

Infrared microscopy can be performed to observe dynamic processes on a microscopic scale. Fourier-transform infrared spectroscopy-based microscopes are bound to limitations regarding time resolution, which hampers their potential for imaging fast moving systems. In this manuscript we present a quantum cascade laser-based infrared microscope which overcomes these limitations and readily achieves standard video frame rates. The capabilities of our setup are demonstrated by observing dynamical processes at their specific time scales: fermentation, slow moving Amoeba Proteus and fast moving Caenorhabditis elegans. Mid-infrared sampling rates between 30 min and 20 ms are demonstrated.

Time-dependent, optically thick accretion onto a black hole

NASA Technical Reports Server (NTRS)

Gilden, D. L.; Wheeler, J. C.

1980-01-01

A fully relativistic hydrodynamics code which incorporates diffusive radiation transport is used to study time-dependent, spherically symmetric, optically thick accretion onto a black hole. It is found that matter free-falls into the hole regardless of whether the diffusion time scale is longer or shorter than the dynamical time. Nonadiabatic heating due to magnetic field reconnection is included. The internal energy thus generated affects the flow in a purely relativistic way, again ensuring free-fall collapse of the inflowing matter. Any matter enveloping a black hole will thus be swallowed on a dynamical time scale with relatively small net release of energy. The inclusion of angular momentum will not necessarily affect this conclusion.

Dynamic measurements and simulations of airborne picolitre-droplet coalescence in holographic optical tweezers

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

Bzdek, Bryan R.; Reid, Jonathan P., E-mail: j.p.reid@bristol.ac.uk; Collard, Liam

We report studies of the coalescence of pairs of picolitre aerosol droplets manipulated with holographic optical tweezers, probing the shape relaxation dynamics following coalescence by simultaneously monitoring the intensity of elastic backscattered light (EBL) from the trapping laser beam (time resolution on the order of 100 ns) while recording high frame rate camera images (time resolution <10 μs). The goals of this work are to: resolve the dynamics of droplet coalescence in holographic optical traps; assign the origin of key features in the time-dependent EBL intensity; and validate the use of the EBL alone to precisely determine droplet surface tensionmore » and viscosity. For low viscosity droplets, two sequential processes are evident: binary coalescence first results from the overlap of the optical traps on the time scale of microseconds followed by the recapture of the composite droplet in an optical trap on the time scale of milliseconds. As droplet viscosity increases, the relaxation in droplet shape eventually occurs on the same time scale as recapture, resulting in a convoluted evolution of the EBL intensity that inhibits quantitative determination of the relaxation time scale. Droplet coalescence was simulated using a computational framework to validate both experimental approaches. The results indicate that time-dependent monitoring of droplet shape from the EBL intensity allows for robust determination of properties such as surface tension and viscosity. Finally, the potential of high frame rate imaging to examine the coalescence of dissimilar viscosity droplets is discussed.« less

Hierarchical Biomolecular Dynamics: Picosecond Hydrogen Bonding Regulates Microsecond Conformational Transitions.

PubMed

Buchenberg, Sebastian; Schaudinnus, Norbert; Stock, Gerhard

2015-03-10

Biomolecules exhibit structural dynamics on a number of time scales, including picosecond (ps) motions of a few atoms, nanosecond (ns) local conformational transitions, and microsecond (μs) global conformational rearrangements. Despite this substantial separation of time scales, fast and slow degrees of freedom appear to be coupled in a nonlinear manner; for example, there is theoretical and experimental evidence that fast structural fluctuations are required for slow functional motion to happen. To elucidate a microscopic mechanism of this multiscale behavior, Aib peptide is adopted as a simple model system. Combining extensive molecular dynamics simulations with principal component analysis techniques, a hierarchy of (at least) three tiers of the molecule's free energy landscape is discovered. They correspond to chiral left- to right-handed transitions of the entire peptide that happen on a μs time scale, conformational transitions of individual residues that take about 1 ns, and the opening and closing of structure-stabilizing hydrogen bonds that occur within tens of ps and are triggered by sub-ps structural fluctuations. Providing a simple mechanism of hierarchical dynamics, fast hydrogen bond dynamics is found to be a prerequisite for the ns local conformational transitions, which in turn are a prerequisite for the slow global conformational rearrangement of the peptide. As a consequence of the hierarchical coupling, the various processes exhibit a similar temperature behavior which may be interpreted as a dynamic transition.

A Lagrangian dynamic subgrid-scale model turbulence

NASA Technical Reports Server (NTRS)

Meneveau, C.; Lund, T. S.; Cabot, W.

1994-01-01

A new formulation of the dynamic subgrid-scale model is tested in which the error associated with the Germano identity is minimized over flow pathlines rather than over directions of statistical homogeneity. This procedure allows the application of the dynamic model with averaging to flows in complex geometries that do not possess homogeneous directions. The characteristic Lagrangian time scale over which the averaging is performed is chosen such that the model is purely dissipative, guaranteeing numerical stability when coupled with the Smagorinsky model. The formulation is tested successfully in forced and decaying isotropic turbulence and in fully developed and transitional channel flow. In homogeneous flows, the results are similar to those of the volume-averaged dynamic model, while in channel flow, the predictions are superior to those of the plane-averaged dynamic model. The relationship between the averaged terms in the model and vortical structures (worms) that appear in the LES is investigated. Computational overhead is kept small (about 10 percent above the CPU requirements of the volume or plane-averaged dynamic model) by using an approximate scheme to advance the Lagrangian tracking through first-order Euler time integration and linear interpolation in space.

Cross-scale interactions, legacies, and spatial connectivity: integrating time and space to predict post-disturbance response across scales

USDA-ARS?s Scientific Manuscript database

Emergent properties and cross-scale interactions are important in driving landscape-scale dynamics during a disturbance event, such as wildfire. We used these concepts related to changing pattern-process relationships across scales to explain ecological responses following disturbance that resulted ...

Hybrid function projective synchronization in complex dynamical networks

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

Wei, Qiang; Wang, Xing-yuan, E-mail: wangxy@dlut.edu.cn; Hu, Xiao-peng

2014-02-15

This paper investigates hybrid function projective synchronization in complex dynamical networks. When the complex dynamical networks could be synchronized up to an equilibrium or periodic orbit, a hybrid feedback controller is designed to realize the different component of vector of node could be synchronized up to different desired scaling function in complex dynamical networks with time delay. Hybrid function projective synchronization (HFPS) in complex dynamical networks with constant delay and HFPS in complex dynamical networks with time-varying coupling delay are researched, respectively. Finally, the numerical simulations show the effectiveness of theoretical analysis.

Dispersion of response times reveals cognitive dynamics.

PubMed

Holden, John G; Van Orden, Guy C; Turvey, Michael T

2009-04-01

Trial-to-trial variation in word-pronunciation times exhibits 1/f scaling. One explanation is that human performances are consequent on multiplicative interactions among interdependent processes-interaction dominant dynamics. This article describes simulated distributions of pronunciation times in a further test for multiplicative interactions and interdependence. Individual participant distributions of approximately 1,100 word-pronunciation times were successfully mimicked for each participant in combinations of lognormal and power-law behavior. Successful hazard function simulations generalized these results to establish interaction dominant dynamics, in contrast with component dominant dynamics, as a likely mechanism for cognitive activity. (c) 2009 APA, all rights reserved

Dispersion of Response Times Reveals Cognitive Dynamics

PubMed Central

Holden, John G.; Van Orden, Guy C.; Turvey, Michael T.

2013-01-01

Trial to trial variation in word pronunciation times exhibits 1/f scaling. One explanation is that human performances are consequent on multiplicative interactions among interdependent processes – interaction dominant dynamics. This article describes simulated distributions of pronunciation times in a further test for multiplicative interactions and interdependence. Individual participant distributions of ≈1100 word pronunciation times are successfully mimicked for each participant in combinations of lognormal and power law behavior. Successful hazard function simulations generalize these results to establish interaction dominant dynamics, in contrast with component dominant dynamics, as a likely mechanism for cognitive activity. PMID:19348544

A nonlocal strain gradient model for dynamic deformation of orthotropic viscoelastic graphene sheets under time harmonic thermal load

NASA Astrophysics Data System (ADS)

Radwan, Ahmed F.; Sobhy, Mohammed

2018-06-01

This work presents a nonlocal strain gradient theory for the dynamic deformation response of a single-layered graphene sheet (SLGS) on a viscoelastic foundation and subjected to a time harmonic thermal load for various boundary conditions. Material of graphene sheets is presumed to be orthotropic and viscoelastic. The viscoelastic foundation is modeled as Kelvin-Voigt's pattern. Based on the two-unknown plate theory, the motion equations are obtained from the dynamic version of the virtual work principle. The nonlocal strain gradient theory is established from Eringen nonlocal and strain gradient theories, therefore, it contains two material scale parameters, which are nonlocal parameter and gradient coefficient. These scale parameters have two different effects on the graphene sheets. The obtained deflection is compared with that predicted in the literature. Additional numerical examples are introduced to illustrate the influences of the two length scale coefficients and other parameters on the dynamic deformation of the viscoelastic graphene sheets.

Synaptic Scaling Enables Dynamically Distinct Short- and Long-Term Memory Formation

PubMed Central

Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Tsodyks, Misha; Wörgötter, Florentin

2013-01-01

Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling – a slow process usually associated with the maintenance of activity homeostasis – combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes. PMID:24204240

Synaptic scaling enables dynamically distinct short- and long-term memory formation.

PubMed

Tetzlaff, Christian; Kolodziejski, Christoph; Timme, Marc; Tsodyks, Misha; Wörgötter, Florentin

2013-10-01

Memory storage in the brain relies on mechanisms acting on time scales from minutes, for long-term synaptic potentiation, to days, for memory consolidation. During such processes, neural circuits distinguish synapses relevant for forming a long-term storage, which are consolidated, from synapses of short-term storage, which fade. How time scale integration and synaptic differentiation is simultaneously achieved remains unclear. Here we show that synaptic scaling - a slow process usually associated with the maintenance of activity homeostasis - combined with synaptic plasticity may simultaneously achieve both, thereby providing a natural separation of short- from long-term storage. The interaction between plasticity and scaling provides also an explanation for an established paradox where memory consolidation critically depends on the exact order of learning and recall. These results indicate that scaling may be fundamental for stabilizing memories, providing a dynamic link between early and late memory formation processes.

Multiple-time-scale motion in molecularly linked nanoparticle arrays.

PubMed

George, Christopher; Szleifer, Igal; Ratner, Mark

2013-01-22

We explore the transport of electrons between electrodes that encase a two-dimensional array of metallic quantum dots linked by molecular bridges (such as α,ω alkaline dithiols). Because the molecules can move at finite temperatures, the entire transport structure comprising the quantum dots and the molecules is in dynamical motion while the charge is being transported. There are then several physical processes (physical excursions of molecules and quantum dots, electronic migration, ordinary vibrations), all of which influence electronic transport. Each can occur on a different time scale. It is therefore not appropriate to use standard approaches to this sort of electron transfer problem. Instead, we present a treatment in which three different theoretical approaches-kinetic Monte Carlo, classical molecular dynamics, and quantum transport-are all employed. In certain limits, some of the dynamical effects are unimportant. But in general, the transport seems to follow a sort of dynamic bond percolation picture, an approach originally introduced as formal models and later applied to polymer electrolytes. Different rate-determining steps occur in different limits. This approach offers a powerful scheme for dealing with multiple time scale transport problems, as will exist in many situations with several pathways through molecular arrays or even individual molecules that are dynamically disordered.

Nanosecond Dynamics at Protein Metal Sites: An Application of Perturbed Angular Correlation (PAC) of γ-Rays Spectroscopy.

PubMed

Chakraborty, Saumen; Pallada, Stavroula; Pedersen, Jeppe T; Jancso, Attila; Correia, Joao G; Hemmingsen, Lars

2017-09-19

Metalloproteins are essential to numerous reactions in nature, and constitute approximately one-third of all known proteins. Molecular dynamics of proteins has been elucidated with great success both by experimental and theoretical methods, revealing atomic level details of function involving the organic constituents on a broad spectrum of time scales. However, the characterization of dynamics at biomolecular metal sites on nanosecond time scales is scarce in the literature. The aqua ions of many biologically relevant metal ions exhibit exchange of water molecules on the nanosecond time scale or faster, often defining their reactivity in aqueous solution, and this is presumably also a relevant time scale for the making and breaking of coordination bonds between metal ions and ligands at protein metal sites. Ligand exchange dynamics is critical for a variety of elementary steps of reactions in metallobiochemistry, for example, association and dissociation of metal bound water, association of substrate and dissociation of product in the catalytic cycle of metalloenzymes, at regulatory metal sites which require binding and dissociation of metal ions, as well as in the transport of metal ions across cell membranes or between proteins involved in metal ion homeostasis. In Perturbed Angular Correlation of γ-rays (PAC) spectroscopy, the correlation in time and space of two γ-rays emitted successively in a nuclear decay is recorded, reflecting the hyperfine interactions of the PAC probe nucleus with the surroundings. This allows for characterization of molecular and electronic structure as well as nanosecond dynamics at the PAC probe binding site. Herein, selected examples describing the application of PAC spectroscopy in probing the dynamics at protein metal sites are presented, including (1) exchange of Cd 2+ bound water in de novo designed synthetic proteins, and the effect of remote mutations on metal site dynamics; (2) dynamics at the β-lactamase active site, where the metal ion appears to jump between the two adjacent sites; (3) structural relaxation in small blue copper proteins upon 111 Ag + to 111 Cd 2+ transformation in radioactive nuclear decay; (4) metal ion transfer between two HAH1 proteins with change in coordination number; and (5) metal ion sensor proteins with two coexisting metal site structures. With this Account, we hope to make our modest contribution to the field and perhaps spur additional interest in dynamics at protein metal sites, which we consider to be severely underexplored. Relatively little is known about detailed atomic motions at metal sites, for example, how ligand exchange processes affect protein function, and how the amino acid composition of the protein may control this facet of metal site characteristics. We also aim to provide the reader with a qualitative impression of the possibilities offered by PAC spectroscopy in bioinorganic chemistry, especially when elucidating dynamics at protein metal sites, and finally present data that may serve as benchmarks on a relevant time scale for development and tests of theoretical molecular dynamics methods applied to biomolecular metal sites.

Nonreciprocity in the dynamics of coupled oscillators with nonlinearity, asymmetry, and scale hierarchy

NASA Astrophysics Data System (ADS)

Moore, Keegan J.; Bunyan, Jonathan; Tawfick, Sameh; Gendelman, Oleg V.; Li, Shuangbao; Leamy, Michael; Vakakis, Alexander F.

2018-01-01

In linear time-invariant dynamical and acoustical systems, reciprocity holds by the Onsager-Casimir principle of microscopic reversibility, and this can be broken only by odd external biases, nonlinearities, or time-dependent properties. A concept is proposed in this work for breaking dynamic reciprocity based on irreversible nonlinear energy transfers from large to small scales in a system with nonlinear hierarchical internal structure, asymmetry, and intentional strong stiffness nonlinearity. The resulting nonreciprocal large-to-small scale energy transfers mimic analogous nonlinear energy transfer cascades that occur in nature (e.g., in turbulent flows), and are caused by the strong frequency-energy dependence of the essentially nonlinear small-scale components of the system considered. The theoretical part of this work is mainly based on action-angle transformations, followed by direct numerical simulations of the resulting system of nonlinear coupled oscillators. The experimental part considers a system with two scales—a linear large-scale oscillator coupled to a small scale by a nonlinear spring—and validates the theoretical findings demonstrating nonreciprocal large-to-small scale energy transfer. The proposed study promotes a paradigm for designing nonreciprocal acoustic materials harnessing strong nonlinearity, which in a future application will be implemented in designing lattices incorporating nonlinear hierarchical internal structures, asymmetry, and scale mixing.

Age-related alterations in the fractal scaling of cardiac interbeat interval dynamics

NASA Technical Reports Server (NTRS)

Iyengar, N.; Peng, C. K.; Morin, R.; Goldberger, A. L.; Lipsitz, L. A.

1996-01-01

We postulated that aging is associated with disruption in the fractallike long-range correlations that characterize healthy sinus rhythm cardiac interval dynamics. Ten young (21-34 yr) and 10 elderly (68-81 yr) rigorously screened healthy subjects underwent 120 min of continuous supine resting electrocardiographic recording. We analyzed the interbeat interval time series using standard time and frequency domain statistics and using a fractal measure, detrended fluctuation analysis, to quantify long-range correlation properties. In healthy young subjects, interbeat intervals demonstrated fractal scaling, with scaling exponents (alpha) from the fluctuation analysis close to a value of 1.0. In the group of healthy elderly subjects, the interbeat interval time series had two scaling regions. Over the short range, interbeat interval fluctuations resembled a random walk process (Brownian noise, alpha = 1.5), whereas over the longer range they resembled white noise (alpha = 0.5). Short (alpha s)- and long-range (alpha 1) scaling exponents were significantly different in the elderly subjects compared with young (alpha s = 1.12 +/- 0.19 vs. 0.90 +/- 0.14, respectively, P = 0.009; alpha 1 = 0.75 +/- 0.17 vs. 0.99 +/- 0.10, respectively, P = 0.002). The crossover behavior from one scaling region to another could be modeled as a first-order autoregressive process, which closely fit the data from four elderly subjects. This implies that a single characteristic time scale may be dominating heartbeat control in these subjects. The age-related loss of fractal organization in heartbeat dynamics may reflect the degradation of integrated physiological regulatory systems and may impair an individual's ability to adapt to stress.

Scaling laws and dynamics of bubble coalescence

NASA Astrophysics Data System (ADS)

Anthony, Christopher R.; Kamat, Pritish M.; Thete, Sumeet S.; Munro, James P.; Lister, John R.; Harris, Michael T.; Basaran, Osman A.

2017-08-01

The coalescence of bubbles and drops plays a central role in nature and industry. During coalescence, two bubbles or drops touch and merge into one as the neck connecting them grows from microscopic to macroscopic scales. The hydrodynamic singularity that arises when two bubbles or drops have just touched and the flows that ensue have been studied thoroughly when two drops coalesce in a dynamically passive outer fluid. In this paper, the coalescence of two identical and initially spherical bubbles, which are idealized as voids that are surrounded by an incompressible Newtonian liquid, is analyzed by numerical simulation. This problem has recently been studied (a) experimentally using high-speed imaging and (b) by asymptotic analysis in which the dynamics is analyzed by determining the growth of a hole in the thin liquid sheet separating the two bubbles. In the latter, advantage is taken of the fact that the flow in the thin sheet of nonconstant thickness is governed by a set of one-dimensional, radial extensional flow equations. While these studies agree on the power law scaling of the variation of the minimum neck radius with time, they disagree with respect to the numerical value of the prefactors in the scaling laws. In order to reconcile these differences and also provide insights into the dynamics that are difficult to probe by either of the aforementioned approaches, simulations are used to access both earlier times than has been possible in the experiments and also later times when asymptotic analysis is no longer applicable. Early times and extremely small length scales are attained in the new simulations through the use of a truncated domain approach. Furthermore, it is shown by direct numerical simulations in which the flow within the bubbles is also determined along with the flow exterior to them that idealizing the bubbles as passive voids has virtually no effect on the scaling laws relating minimum neck radius and time.

Examining Extreme Events Using Dynamically Downscaled 12-km WRF Simulations

EPA Science Inventory

Continued improvements in the speed and availability of computational resources have allowed dynamical downscaling of global climate model (GCM) projections to be conducted at increasingly finer grid scales and over extended time periods. The implementation of dynamical downscal...

Ultrafast carrier dynamics in the large-magnetoresistance material WTe 2

DOE PAGES

Dai, Y. M.; Bowlan, J.; Li, H.; ...

2015-10-07

In this study, ultrafast optical pump-probe spectroscopy is used to track carrier dynamics in the large-magnetoresistance material WTe 2. Our experiments reveal a fast relaxation process occurring on a subpicosecond time scale that is caused by electron-phonon thermalization, allowing us to extract the electron-phonon coupling constant. An additional slower relaxation process, occurring on a time scale of ~5–15 ps, is attributed to phonon-assisted electron-hole recombination. As the temperature decreases from 300 K, the time scale governing this process increases due to the reduction of the phonon population. However, below ~50 K, an unusual decrease of the recombination time sets in,more » most likely due to a change in the electronic structure that has been linked to the large magnetoresistance observed in this material.« less

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.

Entanglement dynamics following a sudden quench: An exact solution

NASA Astrophysics Data System (ADS)

Ghosh, Supriyo; Gupta, Kumar S.; Srivastava, Shashi C. L.

2017-12-01

We present an exact and fully analytical treatment of the entanglement dynamics for an isolated system of N coupled oscillators following a sudden quench of the system parameters. The system is analyzed using the solutions of the time-dependent Schrodinger's equation, which are obtained by solving the corresponding nonlinear Ermakov equations. The entanglement entropies exhibit a multi-oscillatory behaviour, where the number of dynamically generated time scales increases with N. The harmonic chains exhibit entanglement revival and for larger values of N (> 10), we find near-critical logarithmic scaling for the entanglement entropy, which is modulated by a time-dependent factor. The N = 2 case is equivalent to the two-site Bose-Hubbard model in the tunneling regime, which is amenable to empirical realization in cold-atom systems.

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.

Restricted lithium ion dynamics in PEO-based block copolymer electrolytes measured by high-field nuclear magnetic resonance relaxation

NASA Astrophysics Data System (ADS)

Huynh, Tan Vu; Messinger, Robert J.; Sarou-Kanian, Vincent; Fayon, Franck; Bouchet, Renaud; Deschamps, Michaël

2017-10-01

The intrinsic ionic conductivity of polyethylene oxide (PEO)-based block copolymer electrolytes is often assumed to be identical to the conductivity of the PEO homopolymer. Here, we use high-field 7Li nuclear magnetic resonance (NMR) relaxation and pulsed-field-gradient (PFG) NMR diffusion measurements to probe lithium ion dynamics over nanosecond and millisecond time scales in PEO and polystyrene (PS)-b-PEO-b-PS electrolytes containing the lithium salt LiTFSI. Variable-temperature longitudinal (T1) and transverse (T2) 7Li NMR relaxation rates were acquired at three magnetic field strengths and quantitatively analyzed for the first time at such fields, enabling us to distinguish two characteristic time scales that describe fluctuations of the 7Li nuclear electric quadrupolar interaction. Fast lithium motions [up to O (ns)] are essentially identical between the two polymer electrolytes, including sub-nanosecond vibrations and local fluctuations of the coordination polyhedra between lithium and nearby oxygen atoms. However, lithium dynamics over longer time scales [O (10 ns) and greater] are slower in the block copolymer compared to the homopolymer, as manifested experimentally by their different transverse 7Li NMR relaxation rates. Restricted dynamics and altered thermodynamic behavior of PEO chains anchored near PS domains likely explain these results.

Interplay between Functional Connectivity and Scale-Free Dynamics in Intrinsic fMRI Networks

PubMed Central

Ciuciu, Philippe; Abry, Patrice; He, Biyu J.

2014-01-01

Studies employing functional connectivity-type analyses have established that spontaneous fluctuations in functional magnetic resonance imaging (fMRI) signals are organized within large-scale brain networks. Meanwhile, fMRI signals have been shown to exhibit 1/f-type power spectra – a hallmark of scale-free dynamics. We studied the interplay between functional connectivity and scale-free dynamics in fMRI signals, utilizing the fractal connectivity framework – a multivariate extension of the univariate fractional Gaussian noise model, which relies on a wavelet formulation for robust parameter estimation. We applied this framework to fMRI data acquired from healthy young adults at rest and performing a visual detection task. First, we found that scale-invariance existed beyond univariate dynamics, being present also in bivariate cross-temporal dynamics. Second, we observed that frequencies within the scale-free range do not contribute evenly to inter-regional connectivity, with a systematically stronger contribution of the lowest frequencies, both at rest and during task. Third, in addition to a decrease of the Hurst exponent and inter-regional correlations, task performance modified cross-temporal dynamics, inducing a larger contribution of the highest frequencies within the scale-free range to global correlation. Lastly, we found that across individuals, a weaker task modulation of the frequency contribution to inter-regional connectivity was associated with better task performance manifesting as shorter and less variable reaction times. These findings bring together two related fields that have hitherto been studied separately – resting-state networks and scale-free dynamics, and show that scale-free dynamics of human brain activity manifest in cross-regional interactions as well. PMID:24675649

Nanoscopic length scale dependence of hydrogen bonded molecular associates’ dynamics in methanol

PubMed Central

Bertrand, C. E.; Self, J. L.; Copley, J. R. D.; Faraone, A.

2017-01-01

In a recent paper [C. E. Bertrand et al., J. Chem. Phys. 145, 014502 (2016)], we have shown that the collective dynamics of methanol shows a fast relaxation process related to the standard density-fluctuation heat mode and a slow non-Fickian mode originating from the hydrogen bonded molecular associates. Here we report on the length scale dependence of this slow relaxation process. Using quasielastic neutron scattering and molecular dynamics simulations, we show that the dynamics of the slow process is affected by the structuring of the associates, which is accessible through polarized neutron diffraction experiments. Using a series of partially deuterated samples, the dynamics of the associates is investigated and is found to have a similar time scale to the lifetime of hydrogen bonding in the system. Both the structural relaxation and the dynamics of the associates are thermally activated by the breaking of hydrogen bonding. PMID:28527447

Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems.

PubMed

Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei

2015-01-01

The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode.

Liquidity crises on different time scales

NASA Astrophysics Data System (ADS)

Corradi, Francesco; Zaccaria, Andrea; Pietronero, Luciano

2015-12-01

We present an empirical analysis of the microstructure of financial markets and, in particular, of the static and dynamic properties of liquidity. We find that on relatively large time scales (15 min) large price fluctuations are connected to the failure of the subtle mechanism of compensation between the flows of market and limit orders: in other words, the missed revelation of the latent order book breaks the dynamical equilibrium between the flows, triggering the large price jumps. On smaller time scales (30 s), instead, the static depletion of the limit order book is an indicator of an intrinsic fragility of the system, which is related to a strongly nonlinear enhancement of the response. In order to quantify this phenomenon we introduce a measure of the liquidity imbalance present in the book and we show that it is correlated to both the sign and the magnitude of the next price movement. These findings provide a quantitative definition of the effective liquidity, which proves to be strongly dependent on the considered time scales.

Liquidity crises on different time scales.

PubMed

Corradi, Francesco; Zaccaria, Andrea; Pietronero, Luciano

2015-12-01

We present an empirical analysis of the microstructure of financial markets and, in particular, of the static and dynamic properties of liquidity. We find that on relatively large time scales (15 min) large price fluctuations are connected to the failure of the subtle mechanism of compensation between the flows of market and limit orders: in other words, the missed revelation of the latent order book breaks the dynamical equilibrium between the flows, triggering the large price jumps. On smaller time scales (30 s), instead, the static depletion of the limit order book is an indicator of an intrinsic fragility of the system, which is related to a strongly nonlinear enhancement of the response. In order to quantify this phenomenon we introduce a measure of the liquidity imbalance present in the book and we show that it is correlated to both the sign and the magnitude of the next price movement. These findings provide a quantitative definition of the effective liquidity, which proves to be strongly dependent on the considered time scales.

From Points to Patterns - Functional Relations between Groundwater Connectivity and Catchment-scale Streamflow Response

NASA Astrophysics Data System (ADS)

Rinderer, M.; McGlynn, B. L.; van Meerveld, I. H. J.

2016-12-01

Groundwater measurements can help us to improve our understanding of runoff generation at the catchment-scale but typically only provide point-scale data. These measurements, therefore, need to be interpolated or upscaled in order to obtain information about catchment scale groundwater dynamics. Our approach used data from 51 spatially distributed groundwater monitoring sites in a Swiss pre-alpine catchment and time series clustering to define six groundwater response clusters. Each of the clusters was characterized by distinctly different site characteristics (i.e., Topographic Wetness Index and curvature), which allowed us to assign all unmonitored locations to one of these clusters. Time series modeling and the definition of response thresholds (i.e., the depth of more transmissive soil layers) allowed us to derive maps of the spatial distribution of active (i.e., responding) locations across the catchment at 15 min time intervals. Connectivity between all active locations and the stream network was determined using a graph theory approach. The extent of the active and connected areas differed during events and suggests that not all active locations directly contributed to streamflow. Gate keeper sites prevented connectivity of upslope locations to the channel network. Streamflow dynamics at the catchment outlet were correlated to catchment average connectivity dynamics. In a sensitivity analysis we tested six different groundwater levels for a site to be considered "active", which showed that the definition of the threshold did not significantly influence the conclusions drawn from our analysis. This study is the first one to derive patterns of groundwater dynamics based on empirical data (rather than interpolation) and provides insight into the spatio-temporal evolution of the active and connected runoff source areas at the catchment-scale that is critical to understanding the dynamics of water quantity and quality in streams.

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.

Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches

Treesearch

Scott L. Powell; Warren B. Cohen; Sean P. Healey; Robert E. Kennedy; Gretchen G. Moisen; Kenneth B. Pierce; Janet L. Ohmann

2010-01-01

Spatially and temporally explicit knowledge of biomass dynamics at broad scales is critical to understanding how forest disturbance and regrowth processes influence carbon dynamics. We modeled live, aboveground tree biomass using Forest Inventory and Analysis (FIA) field data and applied the models to 20+ year time-series of Landsat satellite imagery to...

Role of dynamics in enzyme catalysis: substantial versus semantic controversies.

PubMed

Kohen, Amnon

2015-02-17

CONSPECTUS: The role of the enzyme's dynamic motions in catalysis is at the center of heated contemporary debates among both theoreticians and experimentalists. Resolving these apparent disputes is of both intellectual and practical importance: incorporation of enzyme dynamics could be critical for any calculation of enzymatic function and may have profound implications for structure-based drug design and the design of biomimetic catalysts. Analysis of the literature suggests that while part of the dispute may reflect substantial differences between theoretical approaches, much of the debate is semantic. For example, the term "protein dynamics" is often used by some researchers when addressing motions that are in thermal equilibrium with their environment, while other researchers only use this term for nonequilibrium events. The last cases are those in which thermal energy is "stored" in a specific protein mode and "used" for catalysis before it can dissipate to its environment (i.e., "nonstatistical dynamics"). This terminology issue aside, a debate has arisen among theoreticians around the roles of nonstatistical vs statistical dynamics in catalysis. However, the author knows of no experimental findings available today that examined this question in enzyme catalyzed reactions. Another source of perhaps nonsubstantial argument might stem from the varying time scales of enzymatic motions, which range from seconds to femtoseconds. Motions at different time scales play different roles in the many events along the catalytic cascade (reactant binding, reprotonation of reactants, structural rearrangement toward the transition state, product release, etc.). In several cases, when various experimental tools have been used to probe catalytic events at differing time scales, illusory contradictions seem to have emerged. In this Account, recent attempts to sort the merits of those questions are discussed along with possible future directions. A possible summary of current studies could be that enzyme, substrate, and solvent dynamics contribute to enzyme catalyzed reactions in several ways: first via mutual "induced-fit" shifting of their conformational ensemble upon binding; then via thermal search of the conformational space toward the reaction's transition-state (TS) and the rare event of the barrier crossing toward products, which is likely to be on faster time scales then the first and following events; and finally via the dynamics associated with products release, which are rate-limiting for many enzymatic reactions. From a chemical perspective, close to the TS, enzymatic systems seem to stiffen, restricting motions orthogonal to the chemical coordinate and enabling dynamics along the reaction coordinate to occur selectively. Studies of how enzymes evolved to support those efficient dynamics at various time scales are still in their infancy, and further experiments and calculations are needed to reveal these phenomena in both enzymes and uncatalyzed reactions.

Variable diffusion in stock market fluctuations

NASA Astrophysics Data System (ADS)

Hua, Jia-Chen; Chen, Lijian; Falcon, Liberty; McCauley, Joseph L.; Gunaratne, Gemunu H.

2015-02-01

We analyze intraday fluctuations in several stock indices to investigate the underlying stochastic processes using techniques appropriate for processes with nonstationary increments. The five most actively traded stocks each contains two time intervals during the day where the variance of increments can be fit by power law scaling in time. The fluctuations in return within these intervals follow asymptotic bi-exponential distributions. The autocorrelation function for increments vanishes rapidly, but decays slowly for absolute and squared increments. Based on these results, we propose an intraday stochastic model with linear variable diffusion coefficient as a lowest order approximation to the real dynamics of financial markets, and to test the effects of time averaging techniques typically used for financial time series analysis. We find that our model replicates major stylized facts associated with empirical financial time series. We also find that ensemble averaging techniques can be used to identify the underlying dynamics correctly, whereas time averages fail in this task. Our work indicates that ensemble average approaches will yield new insight into the study of financial markets' dynamics. Our proposed model also provides new insight into the modeling of financial markets dynamics in microscopic time scales.

Simple scaling of catastrophic landslide dynamics.

PubMed

Ekström, Göran; Stark, Colin P

2013-03-22

Catastrophic landslides involve the acceleration and deceleration of millions of tons of rock and debris in response to the forces of gravity and dissipation. Their unpredictability and frequent location in remote areas have made observations of their dynamics rare. Through real-time detection and inverse modeling of teleseismic data, we show that landslide dynamics are primarily determined by the length scale of the source mass. When combined with geometric constraints from satellite imagery, the seismically determined landslide force histories yield estimates of landslide duration, momenta, potential energy loss, mass, and runout trajectory. Measurements of these dynamical properties for 29 teleseismogenic landslides are consistent with a simple acceleration model in which height drop and rupture depth scale with the length of the failing slope.

Application of Wavelet-Based Methods for Accelerating Multi-Time-Scale Simulation of Bistable Heterogeneous Catalysis

DOE PAGES

Gur, Sourav; Frantziskonis, George N.; Univ. of Arizona, Tucson, AZ; ...

2017-02-16

Here, we report results from a numerical study of multi-time-scale bistable dynamics for CO oxidation on a catalytic surface in a flowing, well-mixed gas stream. The problem is posed in terms of surface and gas-phase submodels that dynamically interact in the presence of stochastic perturbations, reflecting the impact of molecular-scale fluctuations on the surface and turbulence in the gas. Wavelet-based methods are used to encode and characterize the temporal dynamics produced by each submodel and detect the onset of sudden state shifts (bifurcations) caused by nonlinear kinetics. When impending state shifts are detected, a more accurate but computationally expensive integrationmore » scheme can be used. This appears to make it possible, at least in some cases, to decrease the net computational burden associated with simulating multi-time-scale, nonlinear reacting systems by limiting the amount of time in which the more expensive integration schemes are required. Critical to achieving this is being able to detect unstable temporal transitions such as the bistable shifts in the example problem considered here. Lastly, our results indicate that a unique wavelet-based algorithm based on the Lipschitz exponent is capable of making such detections, even under noisy conditions, and may find applications in critical transition detection problems beyond catalysis.« less

Degradation modeling of high temperature proton exchange membrane fuel cells using dual time scale simulation

NASA Astrophysics Data System (ADS)

Pohl, E.; Maximini, M.; Bauschulte, A.; vom Schloß, J.; Hermanns, R. T. E.

2015-02-01

HT-PEM fuel cells suffer from performance losses due to degradation effects. Therefore, the durability of HT-PEM is currently an important factor of research and development. In this paper a novel approach is presented for an integrated short term and long term simulation of HT-PEM accelerated lifetime testing. The physical phenomena of short term and long term effects are commonly modeled separately due to the different time scales. However, in accelerated lifetime testing, long term degradation effects have a crucial impact on the short term dynamics. Our approach addresses this problem by applying a novel method for dual time scale simulation. A transient system simulation is performed for an open voltage cycle test on a HT-PEM fuel cell for a physical time of 35 days. The analysis describes the system dynamics by numerical electrochemical impedance spectroscopy. Furthermore, a performance assessment is performed in order to demonstrate the efficiency of the approach. The presented approach reduces the simulation time by approximately 73% compared to conventional simulation approach without losing too much accuracy. The approach promises a comprehensive perspective considering short term dynamic behavior and long term degradation effects.

Fast time-resolved electrostatic force microscopy: Achieving sub-cycle time resolution

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

Karatay, Durmus U.; Harrison, Jeffrey S.; Glaz, Micah S.

The ability to measure microsecond- and nanosecond-scale local dynamics below the diffraction limit with widely available atomic force microscopy hardware would enable new scientific studies in fields ranging from biology to semiconductor physics. However, commercially available scanning-probe instruments typically offer the ability to measure dynamics only on time scales of milliseconds to seconds. Here, we describe in detail the implementation of fast time-resolved electrostatic force microscopy using an oscillating cantilever as a means to measure fast local dynamics following a perturbation to a sample. We show how the phase of the oscillating cantilever relative to the perturbation event is criticalmore » to achieving reliable sub-cycle time resolution. We explore how noise affects the achievable time resolution and present empirical guidelines for reducing noise and optimizing experimental parameters. Specifically, we show that reducing the noise on the cantilever by using photothermal excitation instead of piezoacoustic excitation further improves time resolution. We demonstrate the discrimination of signal rise times with time constants as fast as 10 ns, and simultaneous data acquisition and analysis for dramatically improved image acquisition times.« less

The glassy state of crambin and the THz time scale protein-solvent fluctuations possibly related to protein function

PubMed Central

2014-01-01

Background THz experiments have been used to characterize the picosecond time scale fluctuations taking place in the model, globular protein crambin. Results Using both hydration and temperature as an experimental parameter, we have identified collective fluctuations (<= 200 cm−1) in the protein. Observation of the protein dynamics in the THz spectrum from both below and above the glass transition temperature (Tg) has provided unique insight into the microscopic interactions and modes that permit the solvent to effectively couple to the protein thermal fluctuations. Conclusions Our findings suggest that the solvent dynamics on the picosecond time scale not only contribute to protein flexibility but may also delineate the types of fluctuations that are able to form within the protein structure. PMID:25184036

Road to MOND: A novel perspective

NASA Astrophysics Data System (ADS)

Milgrom, Mordehai

2015-08-01

Accepting that galactic mass discrepancies are due to modified dynamics, I show why it is specifically the Modified Newtonian dynamics (MOND) paradigm that is pointed to cogently. MOND is thus discussed here as a special case of a larger class of modified dynamics theories whereby galactic systems with large mass discrepancies are described by scale-invariant dynamics. This is a novel presentation that uses more recent, after-the-fact insights and data (largely predicted beforehand by MOND). Starting from a purist set of tenets, I follow the path that leads specifically to the MOND basic tenets. The main signposts are as follows: (i) Space-time scale invariance underlies the dynamics of systems with large mass discrepancies. (ii) In these dynamics, G must be replaced by a single "scale-invariant" gravitational constant, Q0 (in MOND, Q0=A0=G a0, where a0 is MOND's acceleration constant). (iii) Universality of free fall points to the constant q0≡Q0/G as the boundary between the G -controlled, standard dynamics, and the Q0-controlled, scale-invariant dynamics (in MOND, q0=a0). (iv) Data clinch the case for q0 being an acceleration (MOND).

Demographic disequilibrium caused by canopy gap expansion and recruitment failure triggers forest cover loss

Treesearch

Martin Barrette; Louis Bélanger; Louis De Grandpré; Alejandro A. Royo

2017-01-01

In the absence of large-scale stand replacing disturbances, boreal forests can remain in the old-growth stage over time because of a dynamic equilibrium between small-scale mortality and regeneration processes. Although this gap paradigm has been a cornerstone of forest dynamics theory and practice for decades, evidence suggests that it could be disrupted, threatening...

AirSTAR: A UAV Platform for Flight Dynamics and Control System Testing

NASA Technical Reports Server (NTRS)

Jordan, Thomas L.; Foster, John V.; Bailey, Roger M.; Belcastro, Christine M.

2006-01-01

As part of the NASA Aviation Safety Program at Langley Research Center, a dynamically scaled unmanned aerial vehicle (UAV) and associated ground based control system are being developed to investigate dynamics modeling and control of large transport vehicles in upset conditions. The UAV is a 5.5% (seven foot wingspan), twin turbine, generic transport aircraft with a sophisticated instrumentation and telemetry package. A ground based, real-time control system is located inside an operations vehicle for the research pilot and associated support personnel. The telemetry system supports over 70 channels of data plus video for the downlink and 30 channels for the control uplink. Data rates are in excess of 200 Hz. Dynamic scaling of the UAV, which includes dimensional, weight, inertial, actuation, and control system scaling, is required so that the sub-scale vehicle will realistically simulate the flight characteristics of the full-scale aircraft. This testbed will be utilized to validate modeling methods, flight dynamics characteristics, and control system designs for large transport aircraft, with the end goal being the development of technologies to reduce the fatal accident rate due to loss-of-control.

Revealing the fast atomic motion of network glasses.

PubMed

Ruta, B; Baldi, G; Chushkin, Y; Rufflé, B; Cristofolini, L; Fontana, A; Zanatta, M; Nazzani, F

2014-05-19

Still very little is known on the relaxation dynamics of glasses at the microscopic level due to the lack of experiments and theories. It is commonly believed that glasses are in a dynamical arrested state, with relaxation times too large to be observed on human time scales. Here we provide the experimental evidence that glasses display fast atomic rearrangements within a few minutes, even in the deep glassy state. Following the evolution of the structural relaxation in a sodium silicate glass, we find that this fast dynamics is accompanied by the absence of any detectable aging, suggesting a decoupling of the relaxation time and the viscosity in the glass. The relaxation time is strongly affected by the network structure with a marked increase at the mesoscopic scale associated with the ion-conducting pathways. Our results modify the conception of the glassy state and asks for a new microscopic theory.

Markov State Models Provide Insights into Dynamic Modulation of Protein Function

PubMed Central

2015-01-01

Conspectus Protein function is inextricably linked to protein dynamics. As we move from a static structural picture to a dynamic ensemble view of protein structure and function, novel computational paradigms are required for observing and understanding conformational dynamics of proteins and its functional implications. In principle, molecular dynamics simulations can provide the time evolution of atomistic models of proteins, but the long time scales associated with functional dynamics make it difficult to observe rare dynamical transitions. The issue of extracting essential functional components of protein dynamics from noisy simulation data presents another set of challenges in obtaining an unbiased understanding of protein motions. Therefore, a methodology that provides a statistical framework for efficient sampling and a human-readable view of the key aspects of functional dynamics from data analysis is required. The Markov state model (MSM), which has recently become popular worldwide for studying protein dynamics, is an example of such a framework. In this Account, we review the use of Markov state models for efficient sampling of the hierarchy of time scales associated with protein dynamics, automatic identification of key conformational states, and the degrees of freedom associated with slow dynamical processes. Applications of MSMs for studying long time scale phenomena such as activation mechanisms of cellular signaling proteins has yielded novel insights into protein function. In particular, from MSMs built using large-scale simulations of GPCRs and kinases, we have shown that complex conformational changes in proteins can be described in terms of structural changes in key structural motifs or “molecular switches” within the protein, the transitions between functionally active and inactive states of proteins proceed via multiple pathways, and ligand or substrate binding modulates the flux through these pathways. Finally, MSMs also provide a theoretical toolbox for studying the effect of nonequilibrium perturbations on conformational dynamics. Considering that protein dynamics in vivo occur under nonequilibrium conditions, MSMs coupled with nonequilibrium statistical mechanics provide a way to connect cellular components to their functional environments. Nonequilibrium perturbations of protein folding MSMs reveal the presence of dynamically frozen glass-like states in their conformational landscape. These frozen states are also observed to be rich in β-sheets, which indicates their possible role in the nucleation of β-sheet rich aggregates such as those observed in amyloid-fibril formation. Finally, we describe how MSMs have been used to understand the dynamical behavior of intrinsically disordered proteins such as amyloid-β, human islet amyloid polypeptide, and p53. While certainly not a panacea for studying functional dynamics, MSMs provide a rigorous theoretical foundation for understanding complex entropically dominated processes and a convenient lens for viewing protein motions. PMID:25625937

Generalized Master Equation with Non-Markovian Multichromophoric Förster Resonance Energy Transfer for Modular Exciton Densities

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

Jang, Seogjoo; Hoyer, Stephan; Fleming, Graham

2014-10-31

A generalized master equation (GME) governing quantum evolution of modular exciton density (MED) is derived for large scale light harvesting systems composed of weakly interacting modules of multiple chromophores. The GME-MED offers a practical framework to incorporate real time coherent quantum dynamics calculations of small length scales into dynamics over large length scales, and also provides a non-Markovian generalization and rigorous derivation of the Pauli master equation employing multichromophoric Förster resonance energy transfer rates. A test of the GME-MED for four sites of the Fenna-Matthews-Olson complex demonstrates how coherent dynamics of excitonic populations over coupled chromophores can be accurately describedmore » by transitions between subgroups (modules) of delocalized excitons. Application of the GME-MED to the exciton dynamics between a pair of light harvesting complexes in purple bacteria demonstrates its promise as a computationally efficient tool to investigate large scale exciton dynamics in complex environments.« less

The role of fanatics in consensus formation

NASA Astrophysics Data System (ADS)

Gündüç, Semra

2015-08-01

A model of opinion dynamics with two types of agents as social actors are presented, using the Ising thermodynamic model as the dynamics template. The agents are considered as opportunists which live at sites and interact with the neighbors, or fanatics/missionaries which move from site to site randomly in persuasion of converting agents of opposite opinion with the help of opportunists. Here, the moving agents act as an external influence on the opportunists to convert them to the opposite opinion. It is shown by numerical simulations that such dynamics of opinion formation may explain some details of consensus formation even when one of the opinions are held by a minority. Regardless the distribution of the opinion, different size societies exhibit different opinion formation behavior and time scales. In order to understand general behavior, the scaling relations obtained by comparing opinion formation processes observed in societies with varying population and number of randomly moving agents are studied. For the proposed model two types of scaling relations are observed. In fixed size societies, increasing the number of randomly moving agents give a scaling relation for the time scale of the opinion formation process. The second type of scaling relation is due to the size dependent information propagation in finite but large systems, namely finite-size scaling.

Quasi-coarse-grained dynamics: modelling of metallic materials at mesoscales

NASA Astrophysics Data System (ADS)

Dongare, Avinash M.

2014-12-01

A computationally efficient modelling method called quasi-coarse-grained dynamics (QCGD) is developed to expand the capabilities of molecular dynamics (MD) simulations to model behaviour of metallic materials at the mesoscales. This mesoscale method is based on solving the equations of motion for a chosen set of representative atoms from an atomistic microstructure and using scaling relationships for the atomic-scale interatomic potentials in MD simulations to define the interactions between representative atoms. The scaling relationships retain the atomic-scale degrees of freedom and therefore energetics of the representative atoms as would be predicted in MD simulations. The total energetics of the system is retained by scaling the energetics and the atomic-scale degrees of freedom of these representative atoms to account for the missing atoms in the microstructure. This scaling of the energetics renders improved time steps for the QCGD simulations. The success of the QCGD method is demonstrated by the prediction of the structural energetics, high-temperature thermodynamics, deformation behaviour of interfaces, phase transformation behaviour, plastic deformation behaviour, heat generation during plastic deformation, as well as the wave propagation behaviour, as would be predicted using MD simulations for a reduced number of representative atoms. The reduced number of atoms and the improved time steps enables the modelling of metallic materials at the mesoscale in extreme environments.

A dynamic multi-scale Markov model based methodology for remaining life prediction

NASA Astrophysics Data System (ADS)

Yan, Jihong; Guo, Chaozhong; Wang, Xing

2011-05-01

The ability to accurately predict the remaining life of partially degraded components is crucial in prognostics. In this paper, a performance degradation index is designed using multi-feature fusion techniques to represent deterioration severities of facilities. Based on this indicator, an improved Markov model is proposed for remaining life prediction. Fuzzy C-Means (FCM) algorithm is employed to perform state division for Markov model in order to avoid the uncertainty of state division caused by the hard division approach. Considering the influence of both historical and real time data, a dynamic prediction method is introduced into Markov model by a weighted coefficient. Multi-scale theory is employed to solve the state division problem of multi-sample prediction. Consequently, a dynamic multi-scale Markov model is constructed. An experiment is designed based on a Bently-RK4 rotor testbed to validate the dynamic multi-scale Markov model, experimental results illustrate the effectiveness of the methodology.

Cluster Morphology-Polymer Dynamics Correlations in Sulfonated Polystyrene Melts: Computational Study

DOE PAGES

Agrawal, Anupriya; Perahia, Dvora; Grest, Gary S.

2016-04-11

Reaching exceptionally long times up to 500 ns in equilibrium and nonequilibrium molecular dynamics simulations studies, we have attained a fundamental molecular understanding of the correlation of ionomer clusters structure and multiscale dynamics, providing new insight into one critical, long-standing challenge in ionic polymer physics. The cluster structure in melts of sulfonated polystyrene with Na + and Mg 2+ counterions are resolved and correlated with the dynamics on multiple length and time scales extracted from measurements of the dynamic structure factor and shear rheology. We find that as the morphology of the ionic clusters changes from ladderlike for Na +more » to disordered structures for Mg 2+, the dynamic structure factor is affected on the length scale corresponding to the ionic clusters. Lastly, rheology studies show that the viscosity for Mg 2+ melts is higher than for Na + ones for all shear rates, which is well correlated with the larger ionic clusters’ size for the Mg 2+ melts.« less

Polymer translocation through a nanopore: a showcase of anomalous diffusion.

PubMed

Milchev, A; Dubbeldam, Johan L A; Rostiashvili, Vakhtang G; Vilgis, Thomas A

2009-04-01

We investigate the translocation dynamics of a polymer chain threaded through a membrane nanopore by a chemical potential gradient that acts on the chain segments inside the pore. By means of diverse methods (scaling theory, fractional calculus, and Monte Carlo and molecular dynamics simulations), we demonstrate that the relevant dynamic variable, the transported number of polymer segments, s(t), displays an anomalous diffusive behavior, both with and without an external driving force being present. We show that in the absence of drag force the time tau, needed for a macromolecule of length N to thread from the cis into the trans side of a cell membrane, scales as tauN(2/alpha) with the chain length. The anomalous dynamics of the translocation process is governed by a universal exponent alpha= 2/(2nu + 2 - gamma(1)), which contains the basic universal exponents of polymer physics, nu (the Flory exponent) and gamma(1) (the surface entropic exponent). A closed analytic expression for the probability to find s translocated segments at time t in terms of chain length N and applied drag force f is derived from the fractional Fokker-Planck equation, and shown to provide analytic results for the time variation of the statistical moments and . It turns out that the average translocation time scales as tau proportional, f(-1)N(2/alpha-1). These results are tested and found to be in perfect agreement with extensive Monte Carlo and molecular dynamics computer simulations.

Enhanced sampling by multiple molecular dynamics trajectories: carbonmonoxy myoglobin 10 micros A0-->A(1-3) transition from ten 400 picosecond simulations.

PubMed

Loccisano, Anne E; Acevedo, Orlando; DeChancie, Jason; Schulze, Brita G; Evanseck, Jeffrey D

2004-05-01

The utility of multiple trajectories to extend the time scale of molecular dynamics simulations is reported for the spectroscopic A-states of carbonmonoxy myoglobin (MbCO). Experimentally, the A0-->A(1-3) transition has been observed to be 10 micros at 300 K, which is beyond the time scale of standard molecular dynamics simulations. To simulate this transition, 10 short (400 ps) and two longer time (1.2 ns) molecular dynamics trajectories, starting from five different crystallographic and solution phase structures with random initial velocities centered in a 37 A radius sphere of water, have been used to sample the native-fold of MbCO. Analysis of the ensemble of structures gathered over the cumulative 5.6 ns reveals two biomolecular motions involving the side chains of His64 and Arg45 to explain the spectroscopic states of MbCO. The 10 micros A0-->A(1-3) transition involves the motion of His64, where distance between His64 and CO is found to vary up to 8.8 +/- 1.0 A during the transition of His64 from the ligand (A(1-3)) to bulk solvent (A0). The His64 motion occurs within a single trajectory only once, however the multiple trajectories populate the spectroscopic A-states fully. Consequently, multiple independent molecular dynamics simulations have been found to extend biomolecular motion from 5 ns of total simulation to experimental phenomena on the microsecond time scale.

The dynamics of oceanic fronts. I - The Gulf Stream

NASA Technical Reports Server (NTRS)

Kao, T. W.

1980-01-01

The establishment and maintenance of the mean hydrographic properties of large-scale density fronts in the upper ocean is considered. The dynamics is studied by posing an initial value problem starting with a near-surface discharge of buoyant water with a prescribed density deficit into an ambient stationary fluid of uniform density; full time dependent diffusion and Navier-Stokes equations are then used with constant eddy diffusion and viscosity coefficients, together with a constant Coriolis parameter. Scaling analysis reveals three independent scales of the problem including the radius of deformation of the inertial length, buoyancy length, and diffusive length scales. The governing equations are then suitably scaled and the resulting normalized equations are shown to depend on the Ekman number alone for problems of oceanic interest. It is concluded that the mean Gulf Stream dynamics can be interpreted in terms of a solution of the Navier-Stokes and diffusion equations, with the cross-stream circulation responsible for the maintenance of the front; this mechanism is suggested for the maintenance of the Gulf Stream dynamics.

Time scales of supercooled water and implications for reversible polyamorphism

NASA Astrophysics Data System (ADS)

Limmer, David T.; Chandler, David

2015-09-01

Deeply supercooled water exhibits complex dynamics with large density fluctuations, ice coarsening and characteristic time scales extending from picoseconds to milliseconds. Here, we discuss implications of these time scales as they pertain to two-phase coexistence and to molecular simulations of supercooled water. Specifically, we argue that it is possible to discount liquid-liquid criticality because the time scales imply that correlation lengths for such behaviour would be bounded by no more than a few nanometres. Similarly, it is possible to discount two-liquid coexistence because the time scales imply a bounded interfacial free energy that cannot grow in proportion to a macroscopic surface area. From time scales alone, therefore, we see that coexisting domains of differing density in supercooled water can be no more than nanoscale transient fluctuations.

Environment spectrum and coherence behaviours in a rare-earth doped crystal for quantum memory.

PubMed

Gong, Bo; Tu, Tao; Zhou, Zhong-Quan; Zhu, Xing-Yu; Li, Chuan-Feng; Guo, Guang-Can

2017-12-21

We theoretically investigate the dynamics of environment and coherence behaviours of the central ion in a quantum memory based on a rare-earth doped crystal. The interactions between the central ion and the bath spins suppress the flip-flop rate of the neighbour bath spins and yield a specific environment spectral density S(ω). Under dynamical decoupling pulses, this spectrum provides a general scaling for the coherence envelope and coherence time, which significantly extend over a range on an hour-long time scale. The characterized environment spectrum with ultra-long coherence time can be used to implement various quantum communication and information processing protocols.

Thermodynamic scaling of dynamic properties of liquid crystals: Verifying the scaling parameters using a molecular model

NASA Astrophysics Data System (ADS)

Satoh, Katsuhiko

2013-08-01

The thermodynamic scaling of molecular dynamic properties of rotation and thermodynamic parameters in a nematic phase was investigated by a molecular dynamic simulation using the Gay-Berne potential. A master curve for the relaxation time of flip-flop motion was obtained using thermodynamic scaling, and the dynamic property could be solely expressed as a function of TV^{γ _τ }, where T and V are the temperature and volume, respectively. The scaling parameter γτ was in excellent agreement with the thermodynamic parameter Γ, which is the logarithm of the slope of a line plotted for the temperature and volume at constant P2. This line was fairly linear, and as good as the line for p-azoxyanisole or using the highly ordered small cluster model. The equivalence relation between Γ and γτ was compared with results obtained from the highly ordered small cluster model. The possibility of adapting the molecular model for the thermodynamic scaling of other dynamic rotational properties was also explored. The rotational diffusion constant and rotational viscosity coefficients, which were calculated using established theoretical and experimental expressions, were rescaled onto master curves with the same scaling parameters. The simulation illustrates the universal nature of the equivalence relation for liquid crystals.

Optimal dynamic voltage scaling for wireless sensor nodes with real-time constraints

NASA Astrophysics Data System (ADS)

Cassandras, Christos G.; Zhuang, Shixin

2005-11-01

Sensors are increasingly embedded in manufacturing systems and wirelessly networked to monitor and manage operations ranging from process and inventory control to tracking equipment and even post-manufacturing product monitoring. In building such sensor networks, a critical issue is the limited and hard to replenish energy in the devices involved. Dynamic voltage scaling is a technique that controls the operating voltage of a processor to provide desired performance while conserving energy and prolonging the overall network's lifetime. We consider such power-limited devices processing time-critical tasks which are non-preemptive, aperiodic and have uncertain arrival times. We treat voltage scaling as a dynamic optimization problem whose objective is to minimize energy consumption subject to hard or soft real-time execution constraints. In the case of hard constraints, we build on prior work (which engages a voltage scaling controller at task completion times) by developing an intra-task controller that acts at all arrival times of incoming tasks. We show that this optimization problem can be decomposed into two simpler ones whose solution leads to an algorithm that does not actually require solving any nonlinear programming problems. In the case of soft constraints, this decomposition must be partly relaxed, but it still leads to a scalable (linear in the number of tasks) algorithm. Simulation results are provided to illustrate performance improvements in systems with intra-task controllers compared to uncontrolled systems or those using inter-task control.

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.

Watershed-Scale Heterogeneity of the Biophysical Controls on Soil Respiration

NASA Astrophysics Data System (ADS)

Riveros, D. A.; Pacific, V. J.; McGlynn, B. L.; Welsch, D. L.; Epstein, H. E.; Muth, D. J.; Marshall, L.; Wraith, J.

2006-12-01

Large gaps exist in our understanding of the variability of soil respiration response to changing hydrologic conditions across spatial and temporal scales. Determining the linkages between the hydrologic cycle and the biophysical controls of soil respiration from the local point, to the plot, to the watershed scale is critical to understanding the dynamics of net ecosystem CO2 exchange (NEE). To study the biophysical controls of soil respiration, we measured soil CO2 concentration, soil CO2 flux, dissolved CO2 in stream water, soil moisture, soil temperature, groundwater dynamics, and precipitation at 20-minute intervals throughout the growing season at 4 sites and at weekly intervals at 62 sites covering the range of topographic position, slope, aspect, land cover, and upslope accumulated area conditions in a 555-ha subalpine watershed in central Montana. Our goal was to quantify watershed-scale heterogeneity in soil CO2 concentrations and surface efflux and gain understanding of the biophysical controls on soil respiration. We seek to improve our ability to evaluate and predict soil respiration responses to a dynamic hydrologic cycle across multiple temporal and spatial scales. We found that time lags between biophysical controls and soil respiration can occur from hourly to daily scales. The sensitivity of soil respiration to changes in environmental conditions is controlled by the antecedent soil moisture and by topographic position. At the watershed scale, significant differences in soil respiration exist between upland (dry) and lowland (wet) sites. However, differences in the magnitude and timing of soil respiration also exist within upland settings due to heterogeneity in soil temperature, soil moisture, and soil organic matter. Finally, we used a process-based model to simulate respiration at different times of the year across spatial locations. Our simulations highlight the importance of autotrophic and heterotrophic respiration (production) over diffusivity and soil physical properties (transport). Our work begins to address the disconnect between point, footprint, watershed scale estimates of ecosystem respiration and the role of a dynamic hydrologic cycle.

Adiabatic invariants in stellar dynamics. 1: Basic concepts

NASA Technical Reports Server (NTRS)

Weinberg, Martin D.

1994-01-01

The adiabatic criterion, widely used in astronomical dynamics, is based on the harmonic oscillator. It asserts that the change in action under a slowly varying perturbation is exponentially small. Recent mathematical results that precisely define the conditions for invariance show that this model does not apply in general. In particular, a slowly varying perturbation may cause significant evolution stellar dynamical systems even if its time scale is longer than any internal orbital time scale. This additional 'heating' may have serious implications for the evolution of star clusters and dwarf galaxies which are subject to long-term environmental forces. The mathematical developments leading to these results are reviewed, and the conditions for applicability to and further implications for stellar systems are discussed. Companion papers present a computational method for a general time-dependent disturbance and detailed example.

Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

DOE PAGES

Bordbar, Aarash; Yurkovich, James T.; Paglia, Giuseppe; ...

2017-04-07

In this study, the increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed “unsteady-state flux balance analysis” (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBAmore » predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.« less

Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

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

Bordbar, Aarash; Yurkovich, James T.; Paglia, Giuseppe

In this study, the increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed “unsteady-state flux balance analysis” (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBAmore » predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.« less

Multiscale analysis of information dynamics for linear multivariate processes.

PubMed

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

2016-08-01

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

Long-time atomistic dynamics through a new self-adaptive accelerated molecular dynamics method

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

Gao, N.; Yang, L.; Gao, F.

2017-02-27

A self-adaptive accelerated molecular dynamics method is developed to model infrequent atomic- scale events, especially those events that occur on a rugged free-energy surface. Key in the new development is the use of the total displacement of the system at a given temperature to construct a boost-potential, which is slowly increased to accelerate the dynamics. The temperature is slowly increased to accelerate the dynamics. By allowing the system to evolve from one steady-state con guration to another by overcoming the transition state, this self-evolving approach makes it possible to explore the coupled motion of species that migrate on vastly differentmore » time scales. The migrations of single vacancy (V) and small He-V clusters, and the growth of nano-sized He-V clusters in Fe for times in the order of seconds are studied by this new method. An interstitial- assisted mechanism is rst explored for the migration of a helium-rich He-V cluster, while a new two-component Ostwald ripening mechanism is suggested for He-V cluster growth.« less

Probing conformational dynamics by photoinduced electron transfer

NASA Astrophysics Data System (ADS)

Neuweiler, Hannes; Herten, Dirk P.; Marme, N.; Knemeyer, J. P.; Piestert, Oliver; Tinnefeld, Philip; Sauer, Marcus

2004-07-01

We demonstrate how photoinduced electron transfer (PET) reactions can be successfully applied to monitor conformational dynamics in individual biopolymers. Single-pair fluorescence resonance energy transfer (FRET) experiments are ideally suited to study conformational dynamics occurring on the nanometer scale, e.g. during protein folding or unfolding. In contrast, conformational dynamics with functional significance, for example occurring in enzymes at work, often appear on much smaller spatial scales of up to several Angströms. Our results demonstrate that selective PET-reactions between fluorophores and amino acids or DNA nucleotides represent a versatile tool to measure small-scale conformational dynamics in biopolymers on a wide range of time scales, extending from nanoseconds to seconds, at the single-molecule level under equilibrium conditions. That is, the monitoring of conformational dynamics of biopolymers with temporal resolutions comparable to those within reach using new techniques of molecular dynamic simulations. We present data about structural changes of single biomolecules like DNA hairpins and peptides by using quenching electron transfer reactions between guanosine or tryptophan residues in close proximity to fluorescent dyes. Furthermore, we demonstrate that the strong distance dependence of charge separation reactions on the sub-nanometer scale can be used to develop conformationally flexible PET-biosensors. These sensors enable the detection of specific target molecules in the sub-picomolar range and allow one to follow their molecular binding dynamics with temporal resolution.

Interpreting beta-diversity components over time to conserve metacommunities in highly dynamic ecosystems.

PubMed

Ruhí, Albert; Datry, Thibault; Sabo, John L

2017-12-01

The concept of metacommunity (i.e., a set of local communities linked by dispersal) has gained great popularity among community ecologists. However, metacommunity research mostly addresses questions on spatial patterns of biodiversity at the regional scale, whereas conservation planning requires quantifying temporal variation in those metacommunities and the contributions that individual (local) sites make to regional dynamics. We propose that recent advances in diversity-partitioning methods may allow for a better understanding of metacommunity dynamics and the identification of keystone sites. We used time series of the 2 components of beta diversity (richness and replacement) and the contributions of local sites to these components to examine which sites controlled source-sink dynamics in a highly dynamic model system (an intermittent river). The relative importance of the richness and replacement components of beta diversity fluctuated over time, and sample aggregation led to underestimation of beta diversity by up to 35%. Our literature review revealed that research on intermittent rivers would benefit greatly from examination of beta-diversity components over time. Adequately appraising spatiotemporal variability in community composition and identifying sites that are pivotal for maintaining biodiversity at the landscape scale are key needs for conservation prioritization and planning. Thus, our framework may be used to guide conservation actions in highly dynamic ecosystems when time-series data describing biodiversity across sites connected by dispersal are available. © 2017 Society for Conservation Biology.

A living mesoscopic cellular automaton made of skin scales.

PubMed

Manukyan, Liana; Montandon, Sophie A; Fofonjka, Anamarija; Smirnov, Stanislav; Milinkovitch, Michel C

2017-04-12

In vertebrates, skin colour patterns emerge from nonlinear dynamical microscopic systems of cell interactions. Here we show that in ocellated lizards a quasi-hexagonal lattice of skin scales, rather than individual chromatophore cells, establishes a green and black labyrinthine pattern of skin colour. We analysed time series of lizard scale colour dynamics over four years of their development and demonstrate that this pattern is produced by a cellular automaton (a grid of elements whose states are iterated according to a set of rules based on the states of neighbouring elements) that dynamically computes the colour states of individual mesoscopic skin scales to produce the corresponding macroscopic colour pattern. Using numerical simulations and mathematical derivation, we identify how a discrete von Neumann cellular automaton emerges from a continuous Turing reaction-diffusion system. Skin thickness variation generated by three-dimensional morphogenesis of skin scales causes the underlying reaction-diffusion dynamics to separate into microscopic and mesoscopic spatial scales, the latter generating a cellular automaton. Our study indicates that cellular automata are not merely abstract computational systems, but can directly correspond to processes generated by biological evolution.

A living mesoscopic cellular automaton made of skin scales

NASA Astrophysics Data System (ADS)

Manukyan, Liana; Montandon, Sophie A.; Fofonjka, Anamarija; Smirnov, Stanislav; Milinkovitch, Michel C.

2017-04-01

In vertebrates, skin colour patterns emerge from nonlinear dynamical microscopic systems of cell interactions. Here we show that in ocellated lizards a quasi-hexagonal lattice of skin scales, rather than individual chromatophore cells, establishes a green and black labyrinthine pattern of skin colour. We analysed time series of lizard scale colour dynamics over four years of their development and demonstrate that this pattern is produced by a cellular automaton (a grid of elements whose states are iterated according to a set of rules based on the states of neighbouring elements) that dynamically computes the colour states of individual mesoscopic skin scales to produce the corresponding macroscopic colour pattern. Using numerical simulations and mathematical derivation, we identify how a discrete von Neumann cellular automaton emerges from a continuous Turing reaction-diffusion system. Skin thickness variation generated by three-dimensional morphogenesis of skin scales causes the underlying reaction-diffusion dynamics to separate into microscopic and mesoscopic spatial scales, the latter generating a cellular automaton. Our study indicates that cellular automata are not merely abstract computational systems, but can directly correspond to processes generated by biological evolution.

Polymer Dynamics from Synthetic to Biological Macromolecules

NASA Astrophysics Data System (ADS)

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

2008-02-01

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

Time scale bridging in atomistic simulation of slow dynamics: viscous relaxation and defect activation

NASA Astrophysics Data System (ADS)

Kushima, A.; Eapen, J.; Li, Ju; Yip, S.; Zhu, T.

2011-08-01

Atomistic simulation methods are known for timescale limitations in resolving slow dynamical processes. Two well-known scenarios of slow dynamics are viscous relaxation in supercooled liquids and creep deformation in stressed solids. In both phenomena the challenge to theory and simulation is to sample the transition state pathways efficiently and follow the dynamical processes on long timescales. We present a perspective based on the biased molecular simulation methods such as metadynamics, autonomous basin climbing (ABC), strain-boost and adaptive boost simulations. Such algorithms can enable an atomic-level explanation of the temperature variation of the shear viscosity of glassy liquids, and the relaxation behavior in solids undergoing creep deformation. By discussing the dynamics of slow relaxation in two quite different areas of condensed matter science, we hope to draw attention to other complex problems where anthropological or geological-scale time behavior can be simulated at atomic resolution and understood in terms of micro-scale processes of molecular rearrangements and collective interactions. As examples of a class of phenomena that can be broadly classified as materials ageing, we point to stress corrosion cracking and cement setting as opportunities for atomistic modeling and simulations.

Intermolecular dynamics of substitued benzene and cyclohexane liquids, studied by femtosecond nonlinear-optical polarization spectroscopy

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

Chang, Y.J.; Castner, E.W. Jr.

Femtosecond time-resolved optical-heterodyne detected Raman-induced Kerr effect spectroscopy (OHD-RIKES) is shown to be a powerful and comprehensive tool for studying the intermolecular dynamics occurring in liquids. The observed dynamics include both the underdamped or coherent inertial motions, and the longer time scale diffusive relaxation. The inertial dynamics include phonon-like intermolecular vibrations, intermolecular collisions, and librational caging motions. Data are presented and analyzed for a series of five liquids: cyclohexane, methylcyclohexane, toluene, benzyl alcohol, and benzonitrile, listed in order of increasing polarity. We explore the effects of aromaticity (e.g., methylcyclohexane vs toluene), symmetry reduction (cyclohexane vs methylcyclohexane), and substitution effects (e.g.,more » substituted benzene series) on the ultrafast intermolecular dynamics, for a group of molecular liquids of similar size and volume. We analyze the intermolecular dynamics in both the time and frequency domains by means of Fourier transformations. When Fourier-transformed into the frequency domain, the OHD-RIKES ultrafast transients of the intermolecular dynamics can be directly compared with the frequency domain spectra obtained from the far-infrared absorption and depolarized Raman techniques. This is done using the Gaussian librational caging model of Lynden-Bell and Steele, which results in a power-law scaling relation between dipole and polarizability time correlation functions. 122 refs., 7 figs., 7 tabs.« less

Diffusive dynamics of nanoparticles in ultra-confined media

DOE PAGES

Jacob, Jack Deodato; Conrad, Jacinta; Krishnamoorti, Ramanan; ...

2015-08-10

Differential dynamic microscopy (DDM) was used to investigate the diffusive dynamics of nanoparticles of diameter 200 400 nm that were strongly confined in a periodic square array of cylindrical nanoposts. The minimum distance between posts was 1.3 5 times the diameter of the nanoparticles. The image structure functions obtained from the DDM analysis were isotropic and could be fit by a stretched exponential function. The relaxation time scaled diffusively across the range of wave vectors studied, and the corresponding scalar diffusivities decreased monotonically with increased confinement. The decrease in diffusivity could be described by models for hindered diffusion that accountedmore » for steric restrictions and hydrodynamic interactions. The stretching exponent decreased linearly as the nanoparticles were increasingly confined by the posts. Altogether, these results are consistent with a picture in which strongly confined nanoparticles experience a heterogeneous spatial environment arising from hydrodynamics and volume exclusion on time scales comparable to cage escape, leading to multiple relaxation processes and Fickian but non-Gaussian diffusive dynamics.« less

Slow quench dynamics of a one-dimensional Bose gas confined to an optical lattice.

PubMed

Bernier, Jean-Sébastien; Roux, Guillaume; Kollath, Corinna

2011-05-20

We analyze the effect of a linear time variation of the interaction strength on a trapped one-dimensional Bose gas confined to an optical lattice. The evolution of different observables such as the experimentally accessible on site particle distribution are studied as a function of the ramp time by using time-dependent numerical techniques. We find that the dynamics of a trapped system typically displays two regimes: For long ramp times, the dynamics is governed by density redistribution, while at short ramp times, local dynamics dominates as the evolution is identical to that of an homogeneous system. In the homogeneous limit, we also discuss the nontrivial scaling of the energy absorbed with the ramp time.

Role of Dispersive Fluorous Interaction in the Solvation Dynamics of the Perfluoro Group Containing Molecules.

PubMed

Mondal, Saptarsi; Chaterjee, Soumit; Halder, Ritaban; Jana, Biman; Singh, Prashant Chandra

2017-08-17

Perfluoro group containing molecules possess an important self-aggregation property through the fluorous (F···F) interaction which makes them useful for diverse applications such as medicinal chemistry, separation techniques, polymer technology, and biology. In this article, we have investigated the solvation dynamics of coumarin-153 (C153) and coumarin-6H (C6H) in ethanol (ETH), 2-fluoroethanol (MFE), and 2,2,2-trifluoroethanol (TFE) using the femtosecond upconversion technique and molecular dynamics (MD) simulation to understand the role of fluorous interaction between the solute and solvent molecules in the solvation dynamics of perfluoro group containing molecules. The femtosecond upconversion data show that the time scales of solvation dynamics of C6H in ETH, MFE, and TFE are approximately the same whereas the solvation dynamics of C153 in TFE is slow as compared to that of ETH and MFE. It has also been observed that the time scale of solvation dynamics of C6H in ETH and MFE is higher than that of C153 in the same solvents. MD simulation results show a qualitative agreement with the experimental data in terms of the time scale of the slow components of the solvation for all the systems. The experimental and simulation studies combined lead to the conclusion that the solvation dynamics of C6H in all solvents as well as C153 in ETH and MFE is mostly governed by the charge distribution of ester moieties (C═O and O) of dye molecules whereas the solvation of C153 in TFE is predominantly due to the dispersive fluorous interaction (F···F) between the perfluoro groups of the C153 and solvent molecules.

"Structure and dynamics in complex chemical systems: Gaining new insights through recent advances in time-resolved spectroscopies.” ACS Division of Physical Chemistry Symposium presented at the Fall National ACS Meeting in Boston, MA, August 2015

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

Crawford, Daniel

8-Session Symposium on STRUCTURE AND DYNAMICS IN COMPLEX CHEMICAL SYSTEMS: GAINING NEW INSIGHTS THROUGH RECENT ADVANCES IN TIME-RESOLVED SPECTROSCOPIES. The intricacy of most chemical, biochemical, and material processes and their applications are underscored by the complex nature of the environments in which they occur. Substantial challenges for building a global understanding of a heterogeneous system include (1) identifying unique signatures associated with specific structural motifs within the heterogeneous distribution, and (2) resolving the significance of each of multiple time scales involved in both small- and large-scale nuclear reorganization. This symposium focuses on the progress in our understanding of dynamics inmore » complex systems driven by recent innovations in time-resolved spectroscopies and theoretical developments. Such advancement is critical for driving discovery at the molecular level facilitating new applications. Broad areas of interest include: Structural relaxation and the impact of structure on dynamics in liquids, interfaces, biochemical systems, materials, and other heterogeneous environments.« less

Neural network adaptive control of wing-rock motion of aircraft model mounted on three-degree-of-freedom dynamic rig in wind tunnel

NASA Astrophysics Data System (ADS)

Ignatyev, D. I.

2018-06-01

High-angles-of-attack dynamics of aircraft are complicated with dangerous phenomena such as wing rock, stall, and spin. Autonomous dynamically scaled aircraft model mounted in three-degree-of-freedom (3DoF) dynamic rig is proposed for studying aircraft dynamics and prototyping of control laws in wind tunnel. Dynamics of the scaled aircraft model in 3DoF manoeuvre rig in wind tunnel is considered. The model limit-cycle oscillations are obtained at high angles of attack. A neural network (NN) adaptive control suppressing wing rock motion is designed. The wing rock suppression with the proposed control law is validated using nonlinear time-domain simulations.

Decorrelation of the static and dynamic length scales in hard-sphere glass formers.

PubMed

Charbonneau, Patrick; Tarjus, Gilles

2013-04-01

We show that, in the equilibrium phase of glass-forming hard-sphere fluids in three dimensions, the static length scales tentatively associated with the dynamical slowdown and the dynamical length characterizing spatial heterogeneities in the dynamics unambiguously decorrelate. The former grow at a much slower rate than the latter when density increases. This observation is valid for the dynamical range that is accessible to computer simulations, which roughly corresponds to that accessible in colloidal experiments. We also find that, in this same range, no one-to-one correspondence between relaxation time and point-to-set correlation length exists. These results point to the coexistence of several relaxation mechanisms in the dynamically accessible regime of three-dimensional hard-sphere glass formers.

Hysteresis, regime shifts, and non-stationarity in aquifer recharge-storage-discharge systems

NASA Astrophysics Data System (ADS)

Klammler, Harald; Jawitz, James; Annable, Michael; Hatfield, Kirk; Rao, Suresh

2016-04-01

Based on physical principles and geological information we develop a parsimonious aquifer model for Silver Springs, one of the largest karst springs in Florida. The model structure is linear and time-invariant with recharge, aquifer head (storage) and spring discharge as dynamic variables at the springshed (landscape) scale. Aquifer recharge is the hydrological driver with trends over a range of time scales from seasonal to multi-decadal. The freshwater-saltwater interaction is considered as a dynamic storage mechanism. Model results and observed time series show that aquifer storage causes significant rate-dependent hysteretic behavior between aquifer recharge and discharge. This leads to variable discharge per unit recharge over time scales up to decades, which may be interpreted as a gradual and cyclic regime shift in the aquifer drainage behavior. Based on field observations, we further amend the aquifer model by assuming vegetation growth in the spring run to be inversely proportional to stream velocity and to hinder stream flow. This simple modification introduces non-linearity into the dynamic system, for which we investigate the occurrence of rate-independent hysteresis and of different possible steady states with respective regime shifts between them. Results may contribute towards explaining observed non-stationary behavior potentially due to hydrological regime shifts (e.g., triggered by gradual, long-term changes in recharge or single extreme events) or long-term hysteresis (e.g., caused by aquifer storage). This improved understanding of the springshed hydrologic response dynamics is fundamental for managing the ecological, economic and social aspects at the landscape scale.

Clustering Effects on Dynamics in Ionomer Solutions: A Neutron Spin Echo Insight

NASA Astrophysics Data System (ADS)

Perahia, Dvora; Wijesinghe, Sidath; Senanayake, Manjula; Wickramasinghe, Anuradhi; Mohottalalage, Supun S.; Ohl, Michael

Ionizable blocks in ionomers associate into aggregates serving as physical cross-links and concurrently form transport pathways. The dynamics of ionomers underline their functionality. Incorporating small numbers of ionic groups into polymers significantly constraint their dynamics. Recent computational studies demonstrated a direct correlation between ionic cluster morphology and polymer dynamics. Here using neutron spin echo, we probe the segmental dynamics of polystyrene sulfonate (PSS) as the degree of sulfonation of the PSS and the solution dielectrics are varied. Specifically, 20Wt% PSS of 11,000 g/mol with polydispersity of 1.02 with 3% and 9% sulfonation were studies in toluene (dielectric constant ɛ = 2.8), a good solvent for polystyrene, and with 5Wt% of ethanol (ɛ = 24.3l) added. The dynamic structure factor S(q,t) was analyzed with a single exponential except for a limited q range where two time constants associated with constraint and mobile segments were detected. S(q,t) exhibits several distinctive time and length scales for the dynamics with a crossover appearing at the length scale of the ionic clusters. NSF DMR 1611136.

Extracting the time scales of conformational dynamics from single-molecule single-photon fluorescence statistics.

PubMed

Shang, Jianyuan; Geva, Eitan

2007-04-26

The quenching rate of a fluorophore attached to a macromolecule can be rather sensitive to its conformational state. The decay of the corresponding fluorescence lifetime autocorrelation function can therefore provide unique information on the time scales of conformational dynamics. The conventional way of measuring the fluorescence lifetime autocorrelation function involves evaluating it from the distribution of delay times between photoexcitation and photon emission. However, the time resolution of this procedure is limited by the time window required for collecting enough photons in order to establish this distribution with sufficient signal-to-noise ratio. Yang and Xie have recently proposed an approach for improving the time resolution, which is based on the argument that the autocorrelation function of the delay time between photoexcitation and photon emission is proportional to the autocorrelation function of the square of the fluorescence lifetime [Yang, H.; Xie, X. S. J. Chem. Phys. 2002, 117, 10965]. In this paper, we show that the delay-time autocorrelation function is equal to the autocorrelation function of the square of the fluorescence lifetime divided by the autocorrelation function of the fluorescence lifetime. We examine the conditions under which the delay-time autocorrelation function is approximately proportional to the autocorrelation function of the square of the fluorescence lifetime. We also investigate the correlation between the decay of the delay-time autocorrelation function and the time scales of conformational dynamics. The results are demonstrated via applications to a two-state model and an off-lattice model of a polypeptide.

The length and time scales of water's glass transitions

NASA Astrophysics Data System (ADS)

Limmer, David T.

2014-06-01

Using a general model for the equilibrium dynamics of supercooled liquids, I compute from molecular properties the emergent length and time scales that govern the nonequilibrium relaxation behavior of amorphous ice prepared by rapid cooling. Upon cooling, the liquid water falls out of equilibrium whereby the temperature dependence of its relaxation time is predicted to change from super-Arrhenius to Arrhenius. A consequence of this crossover is that the location of the apparent glass transition temperature depends logarithmically on cooling rate. Accompanying vitrification is the emergence of a dynamical length-scale, the size of which depends on the cooling rate and varies between angstroms and tens of nanometers. While this protocol dependence clarifies a number of previous experimental observations for amorphous ice, the arguments are general and can be extended to other glass forming liquids.

The length and time scales of water's glass transitions.

PubMed

Limmer, David T

2014-06-07

Using a general model for the equilibrium dynamics of supercooled liquids, I compute from molecular properties the emergent length and time scales that govern the nonequilibrium relaxation behavior of amorphous ice prepared by rapid cooling. Upon cooling, the liquid water falls out of equilibrium whereby the temperature dependence of its relaxation time is predicted to change from super-Arrhenius to Arrhenius. A consequence of this crossover is that the location of the apparent glass transition temperature depends logarithmically on cooling rate. Accompanying vitrification is the emergence of a dynamical length-scale, the size of which depends on the cooling rate and varies between angstroms and tens of nanometers. While this protocol dependence clarifies a number of previous experimental observations for amorphous ice, the arguments are general and can be extended to other glass forming liquids.

Scaling of Directed Dynamical Small-World Networks with Random Responses

NASA Astrophysics Data System (ADS)

Zhu, Chen-Ping; Xiong, Shi-Jie; Tian, Ying-Jie; Li, Nan; Jiang, Ke-Sheng

2004-05-01

A dynamical model of small-world networks, with directed links which describe various correlations in social and natural phenomena, is presented. Random responses of sites to the input message are introduced to simulate real systems. The interplay of these ingredients results in the collective dynamical evolution of a spinlike variable S(t) of the whole network. The global average spreading length s and average spreading time s are found to scale as p-αln(N with different exponents. Meanwhile, S(t) behaves in a duple scaling form for N≫N*: S˜f(p-βqγt˜), where p and q are rewiring and external parameters, α, β, and γ are scaling exponents, and f(t˜) is a universal function. Possible applications of the model are discussed.

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

Dynamics and Steady States in Excitable Mobile Agent Systems

NASA Astrophysics Data System (ADS)

Peruani, Fernando; Sibona, Gustavo J.

2008-04-01

We study the spreading of excitations in 2D systems of mobile agents where the excitation is transmitted when a quiescent agent keeps contact with an excited one during a nonvanishing time. We show that the steady states strongly depend on the spatial agent dynamics. Moreover, the coupling between exposition time (ω) and agent-agent contact rate (CR) becomes crucial to understand the excitation dynamics, which exhibits three regimes with CR: no excitation for low CR, an excited regime in which the number of quiescent agents (S) is inversely proportional to CR, and, for high CR, a novel third regime, model dependent, where S scales with an exponent ξ-1, with ξ being the scaling exponent of ω with CR.

Scaling behavior of sleep-wake transitions across species

NASA Astrophysics Data System (ADS)

Lo, Chung-Chuan; Chou, Thomas; Ivanov, Plamen Ch.; Penzel, Thomas; Mochizuki, Takatoshi; Scammell, Thomas; Saper, Clifford B.; Stanley, H. Eugene

2003-03-01

Uncovering the mechanisms controlling sleep is a fascinating scientific challenge. It can be viewed as transitions of states of a very complex system, the brain. We study the time dynamics of short awakenings during sleep for three species: humans, rats and mice. We find, for all three species, that wake durations follow a power-law distribution, and sleep durations follow exponential distributions. Surprisingly, all three species have the same power-law exponent for the distribution of wake durations, but the exponential time scale of the distributions of sleep durations varies across species. We suggest that the dynamics of short awakenings are related to species-independent fluctuations of the system, while the dynamics of sleep is related to system-dependent mechanisms which change with species.

Recombination dynamics of optically excited charge carriers in bulk MoS2

NASA Astrophysics Data System (ADS)

Völzer, Tim; Lütgens, Matthias; Fennel, Franziska; Lochbrunner, Stefan

2017-10-01

Transition metal dichalcogenides (TMDCs), such as MoS2, are promising candidates for optoelectronic or catalytic applications. On that account, a detailed characterization of the electronic dynamics in these materials is of pivotal importance. Here, we investigate the temporal evolution of an excited carrier population by all-optical pump-probe spectroscopy. On the sub-picosecond time scale we observe thermal relaxation of the excited carriers by electron-phonon coupling. The dynamics on the nanosecond time scale can be understood in terms of defect-assisted Auger recombination over a broad carrier density regime spanning more than one order of magnitude. Hence, our results emphasize the importance of defect states for electronic processes in TMDCs at room temperature.

Dynamic fracture of tantalum under extreme tensile stress.

PubMed

Albertazzi, Bruno; Ozaki, Norimasa; Zhakhovsky, Vasily; Faenov, Anatoly; Habara, Hideaki; Harmand, Marion; Hartley, Nicholas; Ilnitsky, Denis; Inogamov, Nail; Inubushi, Yuichi; Ishikawa, Tetsuya; Katayama, Tetsuo; Koyama, Takahisa; Koenig, Michel; Krygier, Andrew; Matsuoka, Takeshi; Matsuyama, Satoshi; McBride, Emma; Migdal, Kirill Petrovich; Morard, Guillaume; Ohashi, Haruhiko; Okuchi, Takuo; Pikuz, Tatiana; Purevjav, Narangoo; Sakata, Osami; Sano, Yasuhisa; Sato, Tomoko; Sekine, Toshimori; Seto, Yusuke; Takahashi, Kenjiro; Tanaka, Kazuo; Tange, Yoshinori; Togashi, Tadashi; Tono, Kensuke; Umeda, Yuhei; Vinci, Tommaso; Yabashi, Makina; Yabuuchi, Toshinori; Yamauchi, Kazuto; Yumoto, Hirokatsu; Kodama, Ryosuke

2017-06-01

The understanding of fracture phenomena of a material at extremely high strain rates is a key issue for a wide variety of scientific research ranging from applied science and technological developments to fundamental science such as laser-matter interaction and geology. Despite its interest, its study relies on a fine multiscale description, in between the atomic scale and macroscopic processes, so far only achievable by large-scale atomic simulations. Direct ultrafast real-time monitoring of dynamic fracture (spallation) at the atomic lattice scale with picosecond time resolution was beyond the reach of experimental techniques. We show that the coupling between a high-power optical laser pump pulse and a femtosecond x-ray probe pulse generated by an x-ray free electron laser allows detection of the lattice dynamics in a tantalum foil at an ultrahigh strain rate of [Formula: see text] ~2 × 10 8 to 3.5 × 10 8 s -1 . A maximal density drop of 8 to 10%, associated with the onset of spallation at a spall strength of ~17 GPa, was directly measured using x-ray diffraction. The experimental results of density evolution agree well with large-scale atomistic simulations of shock wave propagation and fracture of the sample. Our experimental technique opens a new pathway to the investigation of ultrahigh strain-rate phenomena in materials at the atomic scale, including high-speed crack dynamics and stress-induced solid-solid phase transitions.

Dynamic fracture of tantalum under extreme tensile stress

PubMed Central

Albertazzi, Bruno; Ozaki, Norimasa; Zhakhovsky, Vasily; Faenov, Anatoly; Habara, Hideaki; Harmand, Marion; Hartley, Nicholas; Ilnitsky, Denis; Inogamov, Nail; Inubushi, Yuichi; Ishikawa, Tetsuya; Katayama, Tetsuo; Koyama, Takahisa; Koenig, Michel; Krygier, Andrew; Matsuoka, Takeshi; Matsuyama, Satoshi; McBride, Emma; Migdal, Kirill Petrovich; Morard, Guillaume; Ohashi, Haruhiko; Okuchi, Takuo; Pikuz, Tatiana; Purevjav, Narangoo; Sakata, Osami; Sano, Yasuhisa; Sato, Tomoko; Sekine, Toshimori; Seto, Yusuke; Takahashi, Kenjiro; Tanaka, Kazuo; Tange, Yoshinori; Togashi, Tadashi; Tono, Kensuke; Umeda, Yuhei; Vinci, Tommaso; Yabashi, Makina; Yabuuchi, Toshinori; Yamauchi, Kazuto; Yumoto, Hirokatsu; Kodama, Ryosuke

2017-01-01

The understanding of fracture phenomena of a material at extremely high strain rates is a key issue for a wide variety of scientific research ranging from applied science and technological developments to fundamental science such as laser-matter interaction and geology. Despite its interest, its study relies on a fine multiscale description, in between the atomic scale and macroscopic processes, so far only achievable by large-scale atomic simulations. Direct ultrafast real-time monitoring of dynamic fracture (spallation) at the atomic lattice scale with picosecond time resolution was beyond the reach of experimental techniques. We show that the coupling between a high-power optical laser pump pulse and a femtosecond x-ray probe pulse generated by an x-ray free electron laser allows detection of the lattice dynamics in a tantalum foil at an ultrahigh strain rate of ε. ~2 × 108 to 3.5 × 108 s−1. A maximal density drop of 8 to 10%, associated with the onset of spallation at a spall strength of ~17 GPa, was directly measured using x-ray diffraction. The experimental results of density evolution agree well with large-scale atomistic simulations of shock wave propagation and fracture of the sample. Our experimental technique opens a new pathway to the investigation of ultrahigh strain-rate phenomena in materials at the atomic scale, including high-speed crack dynamics and stress-induced solid-solid phase transitions. PMID:28630909

Dynamic Functional Connectivity States Reflecting Psychotic-like Experiences.

PubMed

Barber, Anita D; Lindquist, Martin A; DeRosse, Pamela; Karlsgodt, Katherine H

2018-05-01

Psychotic-like experiences (PLEs) are associated with lower social and occupational functioning, and lower executive function. Emerging evidence also suggests that PLEs reflect neural dysfunction resembling that of psychotic disorders. The present study examined dynamic connectivity related to a measure of PLEs derived from the Achenbach Adult Self-Report, in an otherwise-healthy sample of adults from the Human Connectome Project. A total of 76 PLE-endorsing and 153 control participants were included in the final sample. To characterize network dysfunction, dynamic connectivity states were examined across large-scale resting-state networks using dynamic conditional correlation and k-means clustering. Three dynamic states were identified. The PLE-endorsing group spent more time than the control group in state 1, a state reflecting hyperconnectivity within visual regions and hypoconnectivity within the default mode network, and less time in state 2, a state characterized by robust within-network connectivity for all networks and strong default mode network anticorrelations. Within the PLE-endorsing group, worse executive function was associated with more time spent in and more transitions into state 1 and less time spent in and fewer transitions into state 3. PLEs are associated with altered large-scale brain dynamics, which tip the system away from spending more time in states reflecting more "typical" connectivity patterns toward more time in states reflecting visual hyperconnectivity and default mode hypoconnectivity. Copyright © 2017 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Space-time modeling of soil moisture

NASA Astrophysics Data System (ADS)

Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio

2017-11-01

A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.

Scaling Behavior in Mitochondrial Redox Fluctuations

PubMed Central

Ramanujan, V. Krishnan; Biener, Gabriel; Herman, Brian A.

2006-01-01

Scale-invariant long-range correlations have been reported in fluctuations of time-series signals originating from diverse processes such as heart beat dynamics, earthquakes, and stock market data. The common denominator of these apparently different processes is a highly nonlinear dynamics with competing forces and distinct feedback species. We report for the first time an experimental evidence for scaling behavior in NAD(P)H signal fluctuations in isolated mitochondria and intact cells isolated from the liver of a young (5-month-old) mouse. Time-series data were collected by two-photon imaging of mitochondrial NAD(P)H fluorescence and signal fluctuations were quantitatively analyzed for statistical correlations by detrended fluctuation analysis and spectral power analysis. Redox [NAD(P)H / NAD(P)+] fluctuations in isolated mitochondria and intact liver cells were found to display nonrandom, long-range correlations. These correlations are interpreted as arising due to the regulatory dynamics operative in Krebs' cycle enzyme network and electron transport chain in the mitochondria. This finding may provide a novel basis for understanding similar regulatory networks that govern the nonequilibrium properties of living cells. PMID:16565066

Molecular Dynamics Simulations and Kinetic Measurements to Estimate and Predict Protein-Ligand Residence Times.

PubMed

Mollica, Luca; Theret, Isabelle; Antoine, Mathias; Perron-Sierra, Françoise; Charton, Yves; Fourquez, Jean-Marie; Wierzbicki, Michel; Boutin, Jean A; Ferry, Gilles; Decherchi, Sergio; Bottegoni, Giovanni; Ducrot, Pierre; Cavalli, Andrea

2016-08-11

Ligand-target residence time is emerging as a key drug discovery parameter because it can reliably predict drug efficacy in vivo. Experimental approaches to binding and unbinding kinetics are nowadays available, but we still lack reliable computational tools for predicting kinetics and residence time. Most attempts have been based on brute-force molecular dynamics (MD) simulations, which are CPU-demanding and not yet particularly accurate. We recently reported a new scaled-MD-based protocol, which showed potential for residence time prediction in drug discovery. Here, we further challenged our procedure's predictive ability by applying our methodology to a series of glucokinase activators that could be useful for treating type 2 diabetes mellitus. We combined scaled MD with experimental kinetics measurements and X-ray crystallography, promptly checking the protocol's reliability by directly comparing computational predictions and experimental measures. The good agreement highlights the potential of our scaled-MD-based approach as an innovative method for computationally estimating and predicting drug residence times.

Scaling properties and universality of first-passage-time probabilities in financial markets

NASA Astrophysics Data System (ADS)

Perelló, Josep; Gutiérrez-Roig, Mario; Masoliver, Jaume

2011-12-01

Financial markets provide an ideal frame for the study of crossing or first-passage time events of non-Gaussian correlated dynamics, mainly because large data sets are available. Tick-by-tick data of six futures markets are herein considered, resulting in fat-tailed first-passage time probabilities. The scaling of the return with its standard deviation collapses the probabilities of all markets examined—and also for different time horizons—into single curves, suggesting that first-passage statistics is market independent (at least for high-frequency data). On the other hand, a very closely related quantity, the survival probability, shows, away from the center and tails of the distribution, a hyperbolic t-1/2 decay typical of a Markovian dynamics, albeit the existence of memory in markets. Modifications of the Weibull and Student distributions are good candidates for the phenomenological description of first-passage time properties under certain regimes. The scaling strategies shown may be useful for risk control and algorithmic trading.

Studying the dynamics of interbeat interval time series of healthy and congestive heart failure subjects using scale based symbolic entropy analysis

PubMed Central

Awan, Imtiaz; Aziz, Wajid; Habib, Nazneen; Alowibdi, Jalal S.; Saeed, Sharjil; Nadeem, Malik Sajjad Ahmed; Shah, Syed Ahsin Ali

2018-01-01

Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals because the length of the coarse-grained time series decreases with increasing scaling factor τ, however, MSE works well for long signals. To overcome the drawback of original MSE, various variants of this method have been proposed for evaluating complexity efficiently. In this study, we have proposed multiscale normalized corrected Shannon entropy (MNCSE), in which instead of using sample entropy, symbolic entropy measure NCSE has been used as an entropy estimate. The results of the study are compared with traditional MSE. The effectiveness of the proposed approach is demonstrated using noise signals as well as interbeat interval signals from healthy and pathological subjects. The preliminary results of the study indicate that MNCSE values are more stable and reliable than original MSE values. The results show that MNCSE based features lead to higher classification accuracies in comparison with the MSE based features. PMID:29771977

Studying the dynamics of interbeat interval time series of healthy and congestive heart failure subjects using scale based symbolic entropy analysis.

PubMed

Awan, Imtiaz; Aziz, Wajid; Shah, Imran Hussain; Habib, Nazneen; Alowibdi, Jalal S; Saeed, Sharjil; Nadeem, Malik Sajjad Ahmed; Shah, Syed Ahsin Ali

2018-01-01

Considerable interest has been devoted for developing a deeper understanding of the dynamics of healthy biological systems and how these dynamics are affected due to aging and disease. Entropy based complexity measures have widely been used for quantifying the dynamics of physical and biological systems. These techniques have provided valuable information leading to a fuller understanding of the dynamics of these systems and underlying stimuli that are responsible for anomalous behavior. The single scale based traditional entropy measures yielded contradictory results about the dynamics of real world time series data of healthy and pathological subjects. Recently the multiscale entropy (MSE) algorithm was introduced for precise description of the complexity of biological signals, which was used in numerous fields since its inception. The original MSE quantified the complexity of coarse-grained time series using sample entropy. The original MSE may be unreliable for short signals because the length of the coarse-grained time series decreases with increasing scaling factor τ, however, MSE works well for long signals. To overcome the drawback of original MSE, various variants of this method have been proposed for evaluating complexity efficiently. In this study, we have proposed multiscale normalized corrected Shannon entropy (MNCSE), in which instead of using sample entropy, symbolic entropy measure NCSE has been used as an entropy estimate. The results of the study are compared with traditional MSE. The effectiveness of the proposed approach is demonstrated using noise signals as well as interbeat interval signals from healthy and pathological subjects. The preliminary results of the study indicate that MNCSE values are more stable and reliable than original MSE values. The results show that MNCSE based features lead to higher classification accuracies in comparison with the MSE based features.

Coupling between populations of copepod taxa within an estuarine ecosystem and the adjacent offshore regions

NASA Astrophysics Data System (ADS)

McGinty, N.; Johnson, M. P.; Power, A. M.

2012-07-01

Population dynamics in open systems are complicated by the interactions of local demography and local environmental forcing with processes occurring at larger scales. A local system such as an estuary or bay may contain a zooplankton population that effectively becomes independent of regional dynamics or the local dynamics may be closely coupled to a broader scale pattern. As an alternative, the details of migration and advection may mean that dynamics in a local system are coupled to other specific areas rather than tracking the overall dynamics at a larger scale. We used a reconstructed time series (1973-1987) for copepod taxa to examine the extent to which zooplankton dynamics in Galway Bay reflect processes in broader areas of the NE Atlantic. Continuous Plankton Recorder (CPR) counts were used to establish time series for nine offshore ecoregions, with the regions themselves defined using underlying patterns of chlorophyll variability. The open nature of Galway Bay was reflected in strong associations between bay zooplankton counts and offshore CPR data in a majority of cases (7/10). For each zooplankton taxon, there were large differences among regions in the degree of association with Galway Bay time series. Akaike weights indicated that one ecoregion tended to be the dominant link for each taxon. This indicates that the zooplankton of the Bay reflect more than the local modification of a regional signal and that different zooplankton in the bay may have separate source regions. The data from Galway Bay also fall within a 'sampling shadow' of the CPR. Later years of the time series showed evidence for changes in phenology, with spring zooplankton peaks generally occurring earlier in the year for smaller species.

Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks

PubMed Central

Meyer-Bäse, Anke; Roberts, Rodney G.; Illan, Ignacio A.; Meyer-Bäse, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja

2017-01-01

Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary conditions for (1) area aggregation and time-scale modeling in brain networks and for (2) pinning observability of nodes in dynamic graph networks. Simulation examples are given to illustrate the theoretical concepts. PMID:29051730

Dynamical Graph Theory Networks Methods for the Analysis of Sparse Functional Connectivity Networks and for Determining Pinning Observability in Brain Networks.

PubMed

Meyer-Bäse, Anke; Roberts, Rodney G; Illan, Ignacio A; Meyer-Bäse, Uwe; Lobbes, Marc; Stadlbauer, Andreas; Pinker-Domenig, Katja

2017-01-01

Neuroimaging in combination with graph theory has been successful in analyzing the functional connectome. However almost all analysis are performed based on static graph theory. The derived quantitative graph measures can only describe a snap shot of the disease over time. Neurodegenerative disease evolution is poorly understood and treatment strategies are consequently only of limited efficiency. Fusing modern dynamic graph network theory techniques and modeling strategies at different time scales with pinning observability of complex brain networks will lay the foundation for a transformational paradigm in neurodegnerative diseases research regarding disease evolution at the patient level, treatment response evaluation and revealing some central mechanism in a network that drives alterations in these diseases. We model and analyze brain networks as two-time scale sparse dynamic graph networks with hubs (clusters) representing the fast sub-system and the interconnections between hubs the slow sub-system. Alterations in brain function as seen in dementia can be dynamically modeled by determining the clusters in which disturbance inputs have entered and the impact they have on the large-scale dementia dynamic system. Observing a small fraction of specific nodes in dementia networks such that the others can be recovered is accomplished by the novel concept of pinning observability. In addition, how to control this complex network seems to be crucial in understanding the progressive abnormal neural circuits in many neurodegenerative diseases. Detecting the controlling regions in the networks, which serve as key nodes to control the aberrant dynamics of the networks to a desired state and thus influence the progressive abnormal behavior, will have a huge impact in understanding and developing therapeutic solutions and also will provide useful information about the trajectory of the disease. In this paper, we present the theoretical framework and derive the necessary conditions for (1) area aggregation and time-scale modeling in brain networks and for (2) pinning observability of nodes in dynamic graph networks. Simulation examples are given to illustrate the theoretical concepts.

Large Scale Water Vapor Sources Relative to the October 2000 Piedmont Flood

NASA Technical Reports Server (NTRS)

Turato, Barbara; Reale, Oreste; Siccardi, Franco

2003-01-01

Very intense mesoscale or synoptic-scale rainfall events can occasionally be observed in the Mediterranean region without any deep cyclone developing over the areas affected by precipitation. In these perplexing cases the synoptic situation can superficially look similar to cases in which very little precipitation occurs. These situations could possibly baffle the operational weather forecasters. In this article, the major precipitation event that affected Piedmont (Italy) between 13 and 16 October 2000 is investigated. This is one of the cases in which no intense cyclone was observed within the Mediterranean region at any time, only a moderate system was present, and yet exceptional rainfall and flooding occurred. The emphasis of this study is on the moisture origin and transport. Moisture and energy balances are computed on different space- and time-scales, revealing that precipitation exceeds evaporation over an area inclusive of Piedmont and the northwestern Mediterranean region, on a time-scale encompassing the event and about two weeks preceding it. This is suggestive of an important moisture contribution originating from outside the region. A synoptic and dynamic analysis is then performed to outline the potential mechanisms that could have contributed to the large-scale moisture transport. The central part of the work uses a quasi-isentropic water-vapor back trajectory technique. The moisture sources obtained by this technique are compared with the results of the balances and with the synoptic situation, to unveil possible dynamic mechanisms and physical processes involved. It is found that moisture sources on a variety of atmospheric scales contribute to this event. First, an important contribution is caused by the extratropical remnants of former tropical storm Leslie. The large-scale environment related to this system allows a significant amount of moisture to be carried towards Europe. This happens on a time- scale of about 5-15 days preceding the Piedmont event. Second, water-vapor intrusions from the African Inter-Tropical Convergence Zone and evaporation from the eastern Atlantic contribute on the 2-5 day time-scale. The large-scale moist dynamics appears therefore to be one important factor enabling a moderate Mediterranean cyclone to produce heavy precipitation. Finally, local evaporation from the Mediterranean, water-vapor recycling, and orographically-induced low-level convergence enhance and concentrate the moisture over the area where heavy precipitation occurs. This happens on a 12-72 hour time-scale.

Dynamic Time Expansion and Compression Using Nonlinear Waveguides

DOEpatents

Findikoglu, Alp T.; Hahn, Sangkoo F.; Jia, Quanxi

2004-06-22

Dynamic time expansion or compression of a small amplitude input signal generated with an initial scale is performed using a nonlinear waveguide. A nonlinear waveguide having a variable refractive index is connected to a bias voltage source having a bias signal amplitude that is large relative to the input signal to vary the reflective index and concomitant speed of propagation of the nonlinear waveguide and an electrical circuit for applying the small amplitude signal and the large amplitude bias signal simultaneously to the nonlinear waveguide. The large amplitude bias signal with the input signal alters the speed of propagation of the small-amplitude signal with time in the nonlinear waveguide to expand or contract the initial time scale of the small-amplitude input signal.

Dynamic time expansion and compression using nonlinear waveguides

DOEpatents

Findikoglu, Alp T [Los Alamos, NM; Hahn, Sangkoo F [Los Alamos, NM; Jia, Quanxi [Los Alamos, NM

2004-06-22

Dynamic time expansion or compression of a small-amplitude input signal generated with an initial scale is performed using a nonlinear waveguide. A nonlinear waveguide having a variable refractive index is connected to a bias voltage source having a bias signal amplitude that is large relative to the input signal to vary the reflective index and concomitant speed of propagation of the nonlinear waveguide and an electrical circuit for applying the small-amplitude signal and the large amplitude bias signal simultaneously to the nonlinear waveguide. The large amplitude bias signal with the input signal alters the speed of propagation of the small-amplitude signal with time in the nonlinear waveguide to expand or contract the initial time scale of the small-amplitude input signal.

Generation of skeletal mechanism by means of projected entropy participation indices

NASA Astrophysics Data System (ADS)

Paolucci, Samuel; Valorani, Mauro; Ciottoli, Pietro Paolo; Galassi, Riccardo Malpica

2017-11-01

When the dynamics of reactive systems develop very-slow and very-fast time scales separated by a range of active time scales, with gaps in the fast/active and slow/active time scales, then it is possible to achieve multi-scale adaptive model reduction along-with the integration of the ODEs using the G-Scheme. The scheme assumes that the dynamics is decomposed into active, slow, fast, and invariant subspaces. We derive expressions that establish a direct link between time scales and entropy production by using estimates provided by the G-Scheme. To calculate the contribution to entropy production, we resort to a standard model of a constant pressure, adiabatic, batch reactor, where the mixture temperature of the reactants is initially set above the auto-ignition temperature. Numerical experiments show that the contribution to entropy production of the fast subspace is of the same magnitude as the error threshold chosen for the identification of the decomposition of the tangent space, and the contribution of the slow subspace is generally much smaller than that of the active subspace. The information on entropy production associated with reactions within each subspace is used to define an entropy participation index that is subsequently utilized for model reduction.

Homogenization techniques for population dynamics in strongly heterogeneous landscapes.

PubMed

Yurk, Brian P; Cobbold, Christina A

2018-12-01

An important problem in spatial ecology is to understand how population-scale patterns emerge from individual-level birth, death, and movement processes. These processes, which depend on local landscape characteristics, vary spatially and may exhibit sharp transitions through behavioural responses to habitat edges, leading to discontinuous population densities. Such systems can be modelled using reaction-diffusion equations with interface conditions that capture local behaviour at patch boundaries. In this work we develop a novel homogenization technique to approximate the large-scale dynamics of the system. We illustrate our approach, which also generalizes to multiple species, with an example of logistic growth within a periodic environment. We find that population persistence and the large-scale population carrying capacity is influenced by patch residence times that depend on patch preference, as well as movement rates in adjacent patches. The forms of the homogenized coefficients yield key theoretical insights into how large-scale dynamics arise from the small-scale features.

High-scale axions without isocurvature from inflationary dynamics

DOE PAGES

Kearney, John; Orlofsky, Nicholas; Pierce, Aaron

2016-05-31

Observable primordial tensor modes in the cosmic microwave background (CMB) would point to a high scale of inflation H I. If the scale of Peccei-Quinn (PQ) breaking f a is greater than H I/2π, CMB constraints on isocurvature naively rule out QCD axion dark matter. This assumes the potential of the axion is unmodified during inflation. We revisit models where inflationary dynamics modify the axion potential and discuss how isocurvature bounds can be relaxed. We find that models that rely solely on a larger PQ-breaking scale during inflation f I require either late-time dilution of the axion abundance or highlymore » super-Planckian f I that somehow does not dominate the inflationary energy density. Models that have enhanced explicit breaking of the PQ symmetry during inflation may allow f a close to the Planck scale. Lastly, avoiding disruption of inflationary dynamics provides important limits on the parameter space.« less

Scaling analysis of bilateral hand tremor movements in essential tremor patients.

PubMed

Blesic, S; Maric, J; Dragasevic, N; Milanovic, S; Kostic, V; Ljubisavljevic, Milos

2011-08-01

Recent evidence suggests that the dynamic-scaling behavior of the time-series of signals extracted from separate peaks of tremor spectra may reveal existence of multiple independent sources of tremor. Here, we have studied dynamic characteristics of the time-series of hand tremor movements in essential tremor (ET) patients using the detrended fluctuation analysis method. Hand accelerometry was recorded with (500 g) and without weight loading under postural conditions in 25 ET patients and 20 normal subjects. The time-series comprising peak-to-peak (PtP) intervals were extracted from regions around the first three main frequency components of power spectra (PwS) of the recorded tremors. The data were compared between the load and no-load condition on dominant (related to tremor severity) and non-dominant tremor side and with the normal (physiological) oscillations in healthy subjects. Our analysis shows that, in ET, the dynamic characteristics of the main frequency component of recorded tremors exhibit scaling behavior. Furthermore, they show that the two main components of ET tremor frequency spectra, otherwise indistinguishable without load, become significantly different after inertial loading and that they differ between the tremor sides (related to tremor severity). These results show that scaling, a time-domain analysis, helps revealing tremor features previously not revealed by frequency-domain analysis and suggest that distinct oscillatory central circuits may generate the tremor in ET patients.

Time evolution and dynamical phase transitions at a critical time in a system of one-dimensional bosons after a quantum quench.

PubMed

Mitra, Aditi

2012-12-28

A renormalization group approach is used to show that a one-dimensional system of bosons subject to a lattice quench exhibits a finite-time dynamical phase transition where an order parameter within a light cone increases as a nonanalytic function of time after a critical time. Such a transition is also found for a simultaneous lattice and interaction quench where the effective scaling dimension of the lattice becomes time dependent, crucially affecting the time evolution of the system. Explicit results are presented for the time evolution of the boson interaction parameter and the order parameter for the dynamical transition as well as for more general quenches.

Modal resonant dynamics of cables with a flexible support: A modulated diffraction problem

NASA Astrophysics Data System (ADS)

Guo, Tieding; Kang, Houjun; Wang, Lianhua; Liu, Qijian; Zhao, Yueyu

2018-06-01

Modal resonant dynamics of cables with a flexible support is defined as a modulated (wave) diffraction problem, and investigated by asymptotic expansions of the cable-support coupled system. The support-cable mass ratio, which is usually very large, turns out to be the key parameter for characterizing cable-support dynamic interactions. By treating the mass ratio's inverse as a small perturbation parameter and scaling the cable tension properly, both cable's modal resonant dynamics and the flexible support dynamics are asymptotically reduced by using multiple scale expansions, leading finally to a reduced cable-support coupled model (i.e., on a slow time scale). After numerical validations of the reduced coupled model, cable-support coupled responses and the flexible support induced coupling effects on the cable, are both fully investigated, based upon the reduced model. More explicitly, the dynamic effects on the cable's nonlinear frequency and force responses, caused by the support-cable mass ratio, the resonant detuning parameter and the support damping, are carefully evaluated.

3D ion-scale dynamics of BBFs and their associated emissions in Earth's magnetotail using 3D hybrid simulations and MMS multi-spacecraft observations

NASA Astrophysics Data System (ADS)

Breuillard, H.; Aunai, N.; Le Contel, O.; Catapano, F.; Alexandrova, A.; Retino, A.; Cozzani, G.; Gershman, D. J.; Giles, B. L.; Khotyaintsev, Y. V.; Lindqvist, P. A.; Ergun, R.; Strangeway, R. J.; Russell, C. T.; Magnes, W.; Plaschke, F.; Nakamura, R.; Fuselier, S. A.; Turner, D. L.; Schwartz, S. J.; Torbert, R. B.; Burch, J.

2017-12-01

Transient and localized jets of hot plasma, also known as Bursty Bulk Flows (BBFs), play a crucial role in Earth's magnetotail dynamics because the energy input from the solar wind is partly dissipated in their vicinity, notably in their embedded dipolarization front (DF). This dissipation is in the form of strong low-frequency waves that can heat and accelerate energetic particles up to the high-latitude plasma sheet. The ion-scale dynamics of BBFs have been revealed by the Cluster and THEMIS multi-spacecraft missions. However, the dynamics of BBF propagation in the magnetotail are still under debate due to instrumental limitations and spacecraft separation distances, as well as simulation limitations. The NASA/MMS fleet, which features unprecedented high time resolution instruments and four spacecraft separated by kinetic-scale distances, has also shown recently that the DF normal dynamics and its associated emissions are below the ion gyroradius scale in this region. Large variations in the dawn-dusk direction were also observed. However, most of large-scale simulations are using the MHD approach and are assumed 2D in the XZ plane. Thus, in this study we take advantage of both multi-spacecraft observations by MMS and large-scale 3D hybrid simulations to investigate the 3D dynamics of BBFs and their associated emissions at ion-scale in Earth's magnetotail, and their impact on particle heating and acceleration.

Universal scaling in the aging of the strong glass former SiO{sub 2}

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

Vollmayr-Lee, Katharina, E-mail: kvollmay@bucknell.edu; Gorman, Christopher H.; Castillo, Horacio E.

We show that the aging dynamics of a strong glass former displays a strikingly simple scaling behavior, connecting the average dynamics with its fluctuations, namely, the dynamical heterogeneities. We perform molecular dynamics simulations of SiO{sub 2} with van Beest-Kramer-van Santen interactions, quenching the system from high to low temperature, and study the evolution of the system as a function of the waiting time t{sub w} measured from the instant of the quench. We find that both the aging behavior of the dynamic susceptibility χ{sub 4} and the aging behavior of the probability distribution P(f{sub s,r}) of the local incoherent intermediatemore » scattering function f{sub s,r} can be described by simple scaling forms in terms of the global incoherent intermediate scattering function C. The scaling forms are the same that have been found to describe the aging of several fragile glass formers and that, in the case of P(f{sub s,r}), have been also predicted theoretically. A thorough study of the length scales involved highlights the importance of intermediate length scales. We also analyze directly the scaling dependence on particle type and on wavevector q and find that both the average and the fluctuations of the slow aging dynamics are controlled by a unique aging clock, which is not only independent of the wavevector q, but is also the same for O and Si atoms.« less

Cocaine addiction and personality: a mathematical model.

PubMed

Caselles, Antonio; Micó, Joan C; Amigó, Salvador

2010-05-01

The existence of a close relation between personality and drug consumption is recognized, but the corresponding causal connection is not well known. Neither is it well known whether personality exercises an influence predominantly at the beginning and development of addiction, nor whether drug consumption produces changes in personality. This paper presents a dynamic mathematical model of personality and addiction based on the unique personality trait theory (UPTT) and the general modelling methodology. This model attempts to integrate personality, the acute effect of drugs, and addiction. The UPTT states the existence of a unique trait of personality called extraversion, understood as a dimension that ranges from impulsive behaviour and sensation-seeking (extravert pole) to fearful and anxious behaviour (introvert pole). As a consequence of drug consumption, the model provides the main patterns of extraversion dynamics through a system of five coupled differential equations. It combines genetic extraversion, as a steady state, and dynamic extraversion in a unique variable measured on the hedonic scale. The dynamics of this variable describes the effects of stimulant drugs on a short-term time scale (typical of the acute effect); while its mean time value describes the effects of stimulant drugs on a long-term time scale (typical of the addiction effect). This understanding may help to develop programmes of prevention and intervention in drug misuse.

Ultrafast dynamics of defect-assisted electron-hole recombination in monolayer MoS2.

PubMed

Wang, Haining; Zhang, Changjian; Rana, Farhan

2015-01-14

In this Letter, we present nondegenerate ultrafast optical pump-probe studies of the carrier recombination dynamics in MoS2 monolayers. By tuning the probe to wavelengths much longer than the exciton line, we make the probe transmission sensitive to the total population of photoexcited electrons and holes. Our measurement reveals two distinct time scales over which the photoexcited electrons and holes recombine; a fast time scale that lasts ∼ 2 ps and a slow time scale that lasts longer than ∼ 100 ps. The temperature and the pump fluence dependence of the observed carrier dynamics are consistent with defect-assisted recombination as being the dominant mechanism for electron-hole recombination in which the electrons and holes are captured by defects via Auger processes. Strong Coulomb interactions in two-dimensional atomic materials, together with strong electron and hole correlations in two-dimensional metal dichalcogenides, make Auger processes particularly effective for carrier capture by defects. We present a model for carrier recombination dynamics that quantitatively explains all features of our data for different temperatures and pump fluences. The theoretical estimates for the rate constants for Auger carrier capture are in good agreement with the experimentally determined values. Our results underscore the important role played by Auger processes in two-dimensional atomic materials.

Practice and transfer of the frequency structures of continuous isometric force.

PubMed

King, Adam C; Newell, Karl M

2014-04-01

The present study examined the learning, retention and transfer of task outcome and the frequency-dependent properties of isometric force output dynamics. During practice participants produced isometric force to a moderately irregular target pattern either under a constant or variable presentation. Immediate and delayed retention tests examined the persistence of practice-induced changes of force output dynamics and transfer tests investigated performance to novel (low and high) irregular target patterns. The results showed that both constant and variable practice conditions exhibited similar reductions in task error but that the frequency-dependent properties were differentially modified across the entire bandwidth (0-12Hz) of force output dynamics as a function of practice. Task outcome exhibited persistent properties on the delayed retention test whereas the retention of faster time scales processes (i.e., 4-12Hz) of force output was mediated as a function of frequency structure. The structure of the force frequency components during early practice and following a rest interval was characterized by an enhanced emphasis on the slow time scales related to perceptual-motor feedback. The findings support the proposition that there are different time scales of learning at the levels of task outcome and the adaptive frequency bandwidths of force output dynamics. Copyright © 2014 Elsevier B.V. All rights reserved.

The proximal-to-distal sequence in upper-limb motions on multiple levels and time scales.

PubMed

Serrien, Ben; Baeyens, Jean-Pierre

2017-10-01

The proximal-to-distal sequence is a phenomenon that can be observed in a large variety of motions of the upper limbs in both humans and other mammals. The mechanisms behind this sequence are not completely understood and motor control theories able to explain this phenomenon are currently incomplete. The aim of this narrative review is to take a theoretical constraints-led approach to the proximal-to-distal sequence and provide a broad multidisciplinary overview of relevant literature. This sequence exists at multiple levels (brain, spine, muscles, kinetics and kinematics) and on multiple time scales (motion, motor learning and development, growth and possibly even evolution). We hypothesize that the proximodistal spatiotemporal direction on each time scale and level provides part of the organismic constraints that guide the dynamics at the other levels and time scales. The constraint-led approach in this review may serve as a first onset towards integration of evidence and a framework for further experimentation to reveal the dynamics of the proximal-to-distal sequence. Copyright © 2017 Elsevier B.V. All rights reserved.

Intrinsic Multi-Scale Dynamic Behaviors of Complex Financial Systems

PubMed Central

Ouyang, Fang-Yan; Zheng, Bo; Jiang, Xiong-Fei

2015-01-01

The empirical mode decomposition is applied to analyze the intrinsic multi-scale dynamic behaviors of complex financial systems. In this approach, the time series of the price returns of each stock is decomposed into a small number of intrinsic mode functions, which represent the price motion from high frequency to low frequency. These intrinsic mode functions are then grouped into three modes, i.e., the fast mode, medium mode and slow mode. The probability distribution of returns and auto-correlation of volatilities for the fast and medium modes exhibit similar behaviors as those of the full time series, i.e., these characteristics are rather robust in multi time scale. However, the cross-correlation between individual stocks and the return-volatility correlation are time scale dependent. The structure of business sectors is mainly governed by the fast mode when returns are sampled at a couple of days, while by the medium mode when returns are sampled at dozens of days. More importantly, the leverage and anti-leverage effects are dominated by the medium mode. PMID:26427063

Reduced linear noise approximation for biochemical reaction networks with time-scale separation: The stochastic tQSSA+

NASA Astrophysics Data System (ADS)

Herath, Narmada; Del Vecchio, Domitilla

2018-03-01

Biochemical reaction networks often involve reactions that take place on different time scales, giving rise to "slow" and "fast" system variables. This property is widely used in the analysis of systems to obtain dynamical models with reduced dimensions. In this paper, we consider stochastic dynamics of biochemical reaction networks modeled using the Linear Noise Approximation (LNA). Under time-scale separation conditions, we obtain a reduced-order LNA that approximates both the slow and fast variables in the system. We mathematically prove that the first and second moments of this reduced-order model converge to those of the full system as the time-scale separation becomes large. These mathematical results, in particular, provide a rigorous justification to the accuracy of LNA models derived using the stochastic total quasi-steady state approximation (tQSSA). Since, in contrast to the stochastic tQSSA, our reduced-order model also provides approximations for the fast variable stochastic properties, we term our method the "stochastic tQSSA+". Finally, we demonstrate the application of our approach on two biochemical network motifs found in gene-regulatory and signal transduction networks.

Time scales of relaxation dynamics during transient conditions in two-phase flow: RELAXATION DYNAMICS

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

Schlüter, Steffen; Berg, Steffen; Li, Tianyi

2017-06-01

The relaxation dynamics toward a hydrostatic equilibrium after a change in phase saturation in porous media is governed by fluid reconfiguration at the pore scale. Little is known whether a hydrostatic equilibrium in which all interfaces come to rest is ever reached and which microscopic processes govern the time scales of relaxation. Here we apply fast synchrotron-based X-ray tomography (X-ray CT) to measure the slow relaxation dynamics of fluid interfaces in a glass bead pack after fast drainage of the sample. The relaxation of interfaces triggers internal redistribution of fluids, reduces the surface energy stored in the fluid interfaces, andmore » relaxes the contact angle toward the equilibrium value while the fluid topology remains unchanged. The equilibration of capillary pressures occurs in two stages: (i) a quick relaxation within seconds in which most of the pressure drop that built up during drainage is dissipated, a process that is to fast to be captured with fast X-ray CT, and (ii) a slow relaxation with characteristic time scales of 1–4 h which manifests itself as a spontaneous imbibition process that is well described by the Washburn equation for capillary rise in porous media. The slow relaxation implies that a hydrostatic equilibrium is hardly ever attained in practice when conducting two-phase experiments in which a flux boundary condition is changed from flow to no-flow. Implications for experiments with pressure boundary conditions are discussed.« less

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Reaching extended length-scales with temperature-accelerated dynamics

NASA Astrophysics Data System (ADS)

Amar, Jacques G.; Shim, Yunsic

2013-03-01

In temperature-accelerated dynamics (TAD) a high-temperature molecular dynamics (MD) simulation is used to accelerate the search for the next low-temperature activated event. While TAD has been quite successful in extending the time-scales of simulations of non-equilibrium processes, due to the fact that the computational work scales approximately as the cube of the number of atoms, until recently only simulations of relatively small systems have been carried out. Recently, we have shown that by combining spatial decomposition with our synchronous sublattice algorithm, significantly improved scaling is possible. However, in this approach the size of activated events is limited by the processor size while the dynamics is not exact. Here we discuss progress in developing an alternate approach in which high-temperature parallel MD along with localized saddle-point (LSAD) calculations, are used to carry out TAD simulations without restricting the size of activated events while keeping the dynamics ``exact'' within the context of harmonic transition-state theory. In tests of our LSAD method applied to Ag/Ag(100) annealing and Cu/Cu(100) growth simulations we find significantly improved scaling of TAD, while maintaining a negligibly small error in the energy barriers. Supported by NSF DMR-0907399.

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.

Network Events on Multiple Space and Time Scales in Cultured Neural Networks and in a Stochastic Rate Model

PubMed Central

Gigante, Guido; Deco, Gustavo; Marom, Shimon; Del Giudice, Paolo

2015-01-01

Cortical networks, in-vitro as well as in-vivo, can spontaneously generate a variety of collective dynamical events such as network spikes, UP and DOWN states, global oscillations, and avalanches. Though each of them has been variously recognized in previous works as expression of the excitability of the cortical tissue and the associated nonlinear dynamics, a unified picture of the determinant factors (dynamical and architectural) is desirable and not yet available. Progress has also been partially hindered by the use of a variety of statistical measures to define the network events of interest. We propose here a common probabilistic definition of network events that, applied to the firing activity of cultured neural networks, highlights the co-occurrence of network spikes, power-law distributed avalanches, and exponentially distributed ‘quasi-orbits’, which offer a third type of collective behavior. A rate model, including synaptic excitation and inhibition with no imposed topology, synaptic short-term depression, and finite-size noise, accounts for all these different, coexisting phenomena. We find that their emergence is largely regulated by the proximity to an oscillatory instability of the dynamics, where the non-linear excitable behavior leads to a self-amplification of activity fluctuations over a wide range of scales in space and time. In this sense, the cultured network dynamics is compatible with an excitation-inhibition balance corresponding to a slightly sub-critical regime. Finally, we propose and test a method to infer the characteristic time of the fatigue process, from the observed time course of the network’s firing rate. Unlike the model, possessing a single fatigue mechanism, the cultured network appears to show multiple time scales, signalling the possible coexistence of different fatigue mechanisms. PMID:26558616

The Dynamic Earth.

ERIC Educational Resources Information Center

Siever, Raymond

1983-01-01

Discusses how the earth is a dynamic system that maintains itself in a steady state. Areas considered include large/small-scale earth motions, geologic time, rock and hydrologic cycles, and other aspects dealing with the changing face of the earth. (JN)

The Dynamic Surface Tension of Water

PubMed Central

2017-01-01

The surface tension of water is an important parameter for many biological or industrial processes, and roughly a factor of 3 higher than that of nonpolar liquids such as oils, which is usually attributed to hydrogen bonding and dipolar interactions. Here we show by studying the formation of water drops that the surface tension of a freshly created water surface is even higher (∼90 mN m–1) than under equilibrium conditions (∼72 mN m–1) with a relaxation process occurring on a long time scale (∼1 ms). Dynamic adsorption effects of protons or hydroxides may be at the origin of this dynamic surface tension. However, changing the pH does not significantly change the dynamic surface tension. It also seems unlikely that hydrogen bonding or dipole orientation effects play any role at the relatively long time scale probed in the experiments. PMID:28301160

The Dynamic Surface Tension of Water.

PubMed

Hauner, Ines M; Deblais, Antoine; Beattie, James K; Kellay, Hamid; Bonn, Daniel

2017-04-06

The surface tension of water is an important parameter for many biological or industrial processes, and roughly a factor of 3 higher than that of nonpolar liquids such as oils, which is usually attributed to hydrogen bonding and dipolar interactions. Here we show by studying the formation of water drops that the surface tension of a freshly created water surface is even higher (∼90 mN m -1 ) than under equilibrium conditions (∼72 mN m -1 ) with a relaxation process occurring on a long time scale (∼1 ms). Dynamic adsorption effects of protons or hydroxides may be at the origin of this dynamic surface tension. However, changing the pH does not significantly change the dynamic surface tension. It also seems unlikely that hydrogen bonding or dipole orientation effects play any role at the relatively long time scale probed in the experiments.

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.

Modeling the MJO rain rates using parameterized large scale dynamics: vertical structure, radiation, and horizontal advection of dry air

NASA Astrophysics Data System (ADS)

Wang, S.; Sobel, A. H.; Nie, J.

2015-12-01

Two Madden Julian Oscillation (MJO) events were observed during October and November 2011 in the equatorial Indian Ocean during the DYNAMO field campaign. Precipitation rates and large-scale vertical motion profiles derived from the DYNAMO northern sounding array are simulated in a small-domain cloud-resolving model using parameterized large-scale dynamics. Three parameterizations of large-scale dynamics --- the conventional weak temperature gradient (WTG) approximation, vertical mode based spectral WTG (SWTG), and damped gravity wave coupling (DGW) --- are employed. The target temperature profiles and radiative heating rates are taken from a control simulation in which the large-scale vertical motion is imposed (rather than directly from observations), and the model itself is significantly modified from that used in previous work. These methodological changes lead to significant improvement in the results.Simulations using all three methods, with imposed time -dependent radiation and horizontal moisture advection, capture the time variations in precipitation associated with the two MJO events well. The three methods produce significant differences in the large-scale vertical motion profile, however. WTG produces the most top-heavy and noisy profiles, while DGW's is smoother with a peak in midlevels. SWTG produces a smooth profile, somewhere between WTG and DGW, and in better agreement with observations than either of the others. Numerical experiments without horizontal advection of moisture suggest that that process significantly reduces the precipitation and suppresses the top-heaviness of large-scale vertical motion during the MJO active phases, while experiments in which the effect of cloud on radiation are disabled indicate that cloud-radiative interaction significantly amplifies the MJO. Experiments in which interactive radiation is used produce poorer agreement with observation than those with imposed time-varying radiative heating. Our results highlight the importance of both horizontal advection of moisture and cloud-radiative feedback to the dynamics of the MJO, as well as to accurate simulation and prediction of it in models.

Direct Observations of a Dynamically Driven Phase Transition with in situ X-Ray Diffraction in a Simple Ionic Crystal

NASA Astrophysics Data System (ADS)

Kalita, Patricia; Specht, Paul; Root, Seth; Sinclair, Nicholas; Schuman, Adam; White, Melanie; Cornelius, Andrew L.; Smith, Jesse; Sinogeikin, Stanislav

2017-12-01

We report real-time observations of a phase transition in the ionic solid CaF2 , a model A B2 structure in high-pressure physics. Synchrotron x-ray diffraction coupled with dynamic loading to 27.7 GPa, and separately with static compression, follows, in situ, the fluorite to cotunnite structural phase transition, both on nanosecond and on minute time scales. Using Rietveld refinement techniques, we examine the kinetics and hysteresis of the transition. Our results give insight into the kinetic time scale of the fluorite-cotunnite phase transition under shock compression, which is relevant to a number of isomorphic compounds.

Direct Observations of a Dynamically Driven Phase Transition with in situ X-Ray Diffraction in a Simple Ionic Crystal

DOE PAGES

Kalita, Patricia E.; Specht, Paul Elliot; Root, Seth; ...

2017-12-21

Here, we report real-time observations of a phase transition in the ionic solid CaF 2, a model AB 2 structure in high-pressure physics. Synchrotron x-ray diffraction coupled with dynamic loading to 27.7 GPa, and separately with static compression, follows, in situ, the fluorite to cotunnite structural phase transition, both on nanosecond and on minute time scales. Using Rietveld refinement techniques, we examine the kinetics and hysteresis of the transition. Our results give insight into the kinetic time scale of the fluorite-cotunnite phase transition under shock compression, which is relevant to a number of isomorphic compounds.

Nonequilibrium diffusive gas dynamics: Poiseuille microflow

NASA Astrophysics Data System (ADS)

Abramov, Rafail V.; Otto, Jasmine T.

2018-05-01

We test the recently developed hierarchy of diffusive moment closures for gas dynamics together with the near-wall viscosity scaling on the Poiseuille flow of argon and nitrogen in a one micrometer wide channel, and compare it against the corresponding Direct Simulation Monte Carlo computations. We find that the diffusive regularized Grad equations with viscosity scaling provide the most accurate approximation to the benchmark DSMC results. At the same time, the conventional Navier-Stokes equations without the near-wall viscosity scaling are found to be the least accurate among the tested closures.

Velocity and Hierarchical Spread of Epidemic Outbreaks in Scale-Free Networks

NASA Astrophysics Data System (ADS)

Barthélemy, Marc; Barrat, Alain; Pastor-Satorras, Romualdo; Vespignani, Alessandro

2004-04-01

We study the effect of the connectivity pattern of complex networks on the propagation dynamics of epidemics. The growth time scale of outbreaks is inversely proportional to the network degree fluctuations, signaling that epidemics spread almost instantaneously in networks with scale-free degree distributions. This feature is associated with an epidemic propagation that follows a precise hierarchical dynamics. Once the highly connected hubs are reached, the infection pervades the network in a progressive cascade across smaller degree classes. The present results are relevant for the development of adaptive containment strategies.

Dynamical tuning for MPC using population games: A water supply network application.

PubMed

Barreiro-Gomez, Julian; Ocampo-Martinez, Carlos; Quijano, Nicanor

2017-07-01

Model predictive control (MPC) is a suitable strategy for the control of large-scale systems that have multiple design requirements, e.g., multiple physical and operational constraints. Besides, an MPC controller is able to deal with multiple control objectives considering them within the cost function, which implies to determine a proper prioritization for each of the objectives. Furthermore, when the system has time-varying parameters and/or disturbances, the appropriate prioritization might vary along the time as well. This situation leads to the need of a dynamical tuning methodology. This paper addresses the dynamical tuning issue by using evolutionary game theory. The advantages of the proposed method are highlighted and tested over a large-scale water supply network with periodic time-varying disturbances. Finally, results are analyzed with respect to a multi-objective MPC controller that uses static tuning. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Lagrangian Statistics and Intermittency in Gulf of Mexico.

PubMed

Lin, Liru; Zhuang, Wei; Huang, Yongxiang

2017-12-12

Due to the nonlinear interaction between different flow patterns, for instance, ocean current, meso-scale eddies, waves, etc, the movement of ocean is extremely complex, where a multiscale statistics is then relevant. In this work, a high time-resolution velocity with a time step 15 minutes obtained by the Lagrangian drifter deployed in the Gulf of Mexico (GoM) from July 2012 to October 2012 is considered. The measured Lagrangian velocity correlation function shows a strong daily cycle due to the diurnal tidal cycle. The estimated Fourier power spectrum E(f) implies a dual-power-law behavior which is separated by the daily cycle. The corresponding scaling exponents are close to -1.75 and -2.75 respectively for the time scale larger (resp. 0.1 ≤ f ≤ 0.4 day -1 ) and smaller (resp. 2 ≤ f ≤ 8 day -1 ) than 1 day. A Hilbert-based approach is then applied to this data set to identify the possible multifractal property of the cascade process. The results show an intermittent dynamics for the time scale larger than 1 day, while a less intermittent dynamics for the time scale smaller than 1 day. It is speculated that the energy is partially injected via the diurnal tidal movement and then transferred to larger and small scales through a complex cascade process, which needs more studies in the near future.

Aspects of extratropical synoptic-scale processes in opposing ENSO phases

NASA Astrophysics Data System (ADS)

Schwierz, C.; Wernli, H.; Hess, D.

2003-04-01

Energy and momentum provided by anomalous tropical heating/cooling affect the circulation on the global scale. Pacific Sea surface temperature anomalies strongly force local conditions in the equatorial Pacific, but are also known to change the climate in the extratropics, particularly over the American continent. The impact on more remote areas such as the Atlantic-European region is less clear. There the observed effects in both analyses and model studies show dependence on the resolution of the model/data, as well as on the time scales under consideration (Merkel and Latif, 2002; Compo et al., 2001). Most of the previous studies focus on larger-scale processes and seasonal time scales (or longer). Here we concentrate on the impact of opposing ENSO phases on extratropical synoptic-scale dynamics. The investigation is undertaken for the Niño/Niña events of 1972/3 and 1973/4 respectively, for 5 winter months (NDJFM) using ECMWF ERA40 data with 1o× 1o horizontal resolution and 60 vertical levels. The examination of the resulting differences in terms of standard dynamical fields (temperature, sea level pressure, precipitation, geopotential) is complemented with additional diagnostic fields (e.g. potential vorticity (PV), anti-/cyclone tracks and frequencies, PV streamers/cut-offs, blocking) in an attempt to gain more insight into aspects of extratropical synoptic-scale dynamical processes associated with ENSO SST anomalies.

Time-dependent Schrödinger equation for molecular core-hole dynamics

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

Picón, A.

2017-02-01

X-ray spectroscopy is an important tool for the investigation of matter. X rays primarily interact with inner-shell electrons, creating core (inner-shell) holes that will decay on the time scale of attoseconds to a few femtoseconds through electron relaxations involving the emission of a photon or an electron. Furthermore, the advent of femtosecond x-ray pulses expands x-ray spectroscopy to the time domain and will eventually allow the control of core-hole population on time scales comparable to core-vacancy lifetimes. For both cases, a theoretical approach that accounts for the x-ray interaction while the electron relaxations occur is required. We describe a time-dependentmore » framework, based on solving the time-dependent Schrödinger equation, that is suitable for describing the induced electron and nuclear dynamics.« less

Multiscale Modeling of Multiphase Fluid Flow

DTIC Science & Technology

2016-08-01

the disparate time and length scales involved in modeling fluid flow and heat transfer. Molecular dynamics simulations were carried out to provide a...fluid dynamics methods were used to investigate the heat transfer process in open-cell micro-foam with phase change material; enhancement of natural...Computational fluid dynamics, Heat transfer, Phase change material in Micro-foam, Molecular Dynamics, Multiphase flow, Multiscale modeling, Natural

Toward a comprehensive landscape vegetation monitoring framework

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Role of Dynamics in Enzyme Catalysis: Substantial versus Semantic Controversies

PubMed Central

2015-01-01

Conspectus The role of the enzyme’s dynamic motions in catalysis is at the center of heated contemporary debates among both theoreticians and experimentalists. Resolving these apparent disputes is of both intellectual and practical importance: incorporation of enzyme dynamics could be critical for any calculation of enzymatic function and may have profound implications for structure-based drug design and the design of biomimetic catalysts. Analysis of the literature suggests that while part of the dispute may reflect substantial differences between theoretical approaches, much of the debate is semantic. For example, the term “protein dynamics” is often used by some researchers when addressing motions that are in thermal equilibrium with their environment, while other researchers only use this term for nonequilibrium events. The last cases are those in which thermal energy is “stored” in a specific protein mode and “used” for catalysis before it can dissipate to its environment (i.e., “nonstatistical dynamics”). This terminology issue aside, a debate has arisen among theoreticians around the roles of nonstatistical vs statistical dynamics in catalysis. However, the author knows of no experimental findings available today that examined this question in enzyme catalyzed reactions. Another source of perhaps nonsubstantial argument might stem from the varying time scales of enzymatic motions, which range from seconds to femtoseconds. Motions at different time scales play different roles in the many events along the catalytic cascade (reactant binding, reprotonation of reactants, structural rearrangement toward the transition state, product release, etc.). In several cases, when various experimental tools have been used to probe catalytic events at differing time scales, illusory contradictions seem to have emerged. In this Account, recent attempts to sort the merits of those questions are discussed along with possible future directions. A possible summary of current studies could be that enzyme, substrate, and solvent dynamics contribute to enzyme catalyzed reactions in several ways: first via mutual “induced-fit” shifting of their conformational ensemble upon binding; then via thermal search of the conformational space toward the reaction’s transition-state (TS) and the rare event of the barrier crossing toward products, which is likely to be on faster time scales then the first and following events; and finally via the dynamics associated with products release, which are rate-limiting for many enzymatic reactions. From a chemical perspective, close to the TS, enzymatic systems seem to stiffen, restricting motions orthogonal to the chemical coordinate and enabling dynamics along the reaction coordinate to occur selectively. Studies of how enzymes evolved to support those efficient dynamics at various time scales are still in their infancy, and further experiments and calculations are needed to reveal these phenomena in both enzymes and uncatalyzed reactions. PMID:25539442

From microscopic rules to macroscopic dynamics with active colloidal snakes

NASA Astrophysics Data System (ADS)

Zhang, Jie; Yan, Jing; Granick, Steve

Seeking to learn about self-assembly far from equilibrium, these imaging experiments inspect self-propelled colloidal particles whose heads and tails attract other particles reversibly as they swim. We observe processes akin to polymerization (short times) and chain scission and recombination (long times). The steady-state of dilute systems consists of discrete rings rotating in place with largely quenched dynamics, but when concentration is high, the system dynamics share features with turbulence. The dynamical rules of this model system appear to be scale-independent and hence potentially relevant more generally.

Electron-phonon thermalization in a scalable method for real-time quantum dynamics

NASA Astrophysics Data System (ADS)

Rizzi, Valerio; Todorov, Tchavdar N.; Kohanoff, Jorge J.; Correa, Alfredo A.

2016-01-01

We present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicit quantum dynamics.

2D IR spectra of cyanide in water investigated by molecular dynamics simulations

USGS Publications Warehouse

Lee, Myung Won; Carr, Joshua K.; Göllner, Michael; Hamm, Peter; Meuwly, Markus

2013-01-01

Using classical molecular dynamics simulations, the 2D infrared (IR) spectroscopy of CN− solvated in D2O is investigated. Depending on the force field parametrizations, most of which are based on multipolar interactions for the CN− molecule, the frequency-frequency correlation function and observables computed from it differ. Most notably, models based on multipoles for CN− and TIP3P for water yield quantitatively correct results when compared with experiments. Furthermore, the recent finding that T 1 times are sensitive to the van der Waals ranges on the CN− is confirmed in the present study. For the linear IR spectrum, the best model reproduces the full widths at half maximum almost quantitatively (13.0 cm−1 vs. 14.9 cm−1) if the rotational contribution to the linewidth is included. Without the rotational contribution, the lines are too narrow by about a factor of two, which agrees with Raman and IR experiments. The computed and experimental tilt angles (or nodal slopes) α as a function of the 2D IR waiting time compare favorably with the measured ones and the frequency fluctuation correlation function is invariably found to contain three time scales: a sub-ps, 1 ps, and one on the 10-ps time scale. These time scales are discussed in terms of the structural dynamics of the surrounding solvent and it is found that the longest time scale (≈10 ps) most likely corresponds to solvent exchange between the first and second solvation shell, in agreement with interpretations from nuclear magnetic resonance measurements.

Ultra-Long Time Dynamics of Contaminant Plume Mixing Induced by Transient Forcing Factors in Geologic Formations

NASA Astrophysics Data System (ADS)

Rajabi, F.; Battiato, I.

2016-12-01

Long term predictions of the impact of anthropogenic stressors on the environment is essential to reduce the risks associated with processes such as CO2 sequestration and nuclear waste storage in the subsurface. On the other hand, transient forcing factors (e.g. time-varying injection or pumping rate) with evolving heterogeneity of time scales spanning from days to years can influence transport phenomena at the pore scale. A comprehensive spatio-temporal prediction of reactive transport in porous media under time-dependent forcing factors for thousands of years requires the formulation of continuum scale models for time-averages. Yet, as every macroscopic model, time-averaged models can loose predictivity and accuracy when certain conditions are violated. This is true whenever lack of temporal and spatial scale separation occurs and it makes the continuum scale equation a poor assumption for the processes at the pore scale. In this work, we consider mass transport of a dissolved species undergoing a heterogeneous reaction and subject to time-varying boundary conditions in a periodic porous medium. By means of homogenization method and asymptotic expansion technique, we derive a macro-time continuum-scale equation as well as expressions for its effective properties. Our analysis demonstrates that the dynamics at the macro-scale is strongly influenced by the interplay between signal frequency at the boundary and transport processes at the pore level. In addition, we provide the conditions under which the space-time averaged equations accurately describe pore-scale processes. To validate our theoretical predictions, we consider a thin fracture with reacting walls and transient boundary conditions at the inlet. Our analysis shows a good agreement between numerical simulations and theoretical predictions. Furthermore, our numerical experiments show that mixing patterns of the contaminant plumes at the pore level strongly depend on the signal frequency.

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.

Evolution of intrinsic disorder in eukaryotic proteins.

PubMed

Ahrens, Joseph B; Nunez-Castilla, Janelle; Siltberg-Liberles, Jessica

2017-09-01

Conformational flexibility conferred though regions of intrinsic structural disorder allows proteins to behave as dynamic molecules. While it is well-known that intrinsically disordered regions can undergo disorder-to-order transitions in real-time as part of their function, we also are beginning to learn more about the dynamics of disorder-to-order transitions along evolutionary time-scales. Intrinsically disordered regions endow proteins with functional promiscuity, which is further enhanced by the ability of some of these regions to undergo real-time disorder-to-order transitions. Disorder content affects gene retention after whole genome duplication, but it is not necessarily conserved. Altered patterns of disorder resulting from evolutionary disorder-to-order transitions indicate that disorder evolves to modify function through refining stability, regulation, and interactions. Here, we review the evolution of intrinsically disordered regions in eukaryotic proteins. We discuss the interplay between secondary structure and disorder on evolutionary time-scales, the importance of disorder for eukaryotic proteome expansion and functional divergence, and the evolutionary dynamics of disorder.

Engineering and Scaling the Spontaneous Magnetization Reversal of Faraday Induced Magnetic Relaxation in Nano-Sized Amorphous Ni Coated on Crystalline Au.

PubMed

Li, Wen-Hsien; Lee, Chi-Hung; Kuo, Chen-Chen

2016-05-28

We report on the generation of large inverse remanent magnetizations in nano-sized core/shell structure of Au/Ni by turning off the applied magnetic field. The remanent magnetization is very sensitive to the field reduction rate as well as to the thermal and field processes before the switching off of the magnetic field. Spontaneous reversal in direction and increase in magnitude of the remanent magnetization in subsequent relaxations over time were found. All of the various types of temporal relaxation curves of the remanent magnetizations are successfully scaled by a stretched exponential decay profile, characterized by two pairs of relaxation times and dynamic exponents. The relaxation time is used to describe the reduction rate, while the dynamic exponent describes the dynamical slowing down of the relaxation through time evolution. The key to these effects is to have the induced eddy current running beneath the amorphous Ni shells through Faraday induction.

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.

Micron-scale coherence in interphase chromatin dynamics

PubMed Central

Zidovska, Alexandra; Weitz, David A.; Mitchison, Timothy J.

2013-01-01

Chromatin structure and dynamics control all aspects of DNA biology yet are poorly understood, especially at large length scales. We developed an approach, displacement correlation spectroscopy based on time-resolved image correlation analysis, to map chromatin dynamics simultaneously across the whole nucleus in cultured human cells. This method revealed that chromatin movement was coherent across large regions (4–5 µm) for several seconds. Regions of coherent motion extended beyond the boundaries of single-chromosome territories, suggesting elastic coupling of motion over length scales much larger than those of genes. These large-scale, coupled motions were ATP dependent and unidirectional for several seconds, perhaps accounting for ATP-dependent directed movement of single genes. Perturbation of major nuclear ATPases such as DNA polymerase, RNA polymerase II, and topoisomerase II eliminated micron-scale coherence, while causing rapid, local movement to increase; i.e., local motions accelerated but became uncoupled from their neighbors. We observe similar trends in chromatin dynamics upon inducing a direct DNA damage; thus we hypothesize that this may be due to DNA damage responses that physically relax chromatin and block long-distance communication of forces. PMID:24019504

Frontiers in Applied and Computational Mathematics 05’

DTIC Science & Technology

2005-03-01

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

Solvation of fluoro-acetonitrile in water by 2D-IR spectroscopy: A combined experimental-computational study

NASA Astrophysics Data System (ADS)

Cazade, Pierre-André; Tran, Halina; Bereau, Tristan; Das, Akshaya K.; Kläsi, Felix; Hamm, Peter; Meuwly, Markus

2015-06-01

The solvent dynamics around fluorinated acetonitrile is characterized by 2-dimensional infrared spectroscopy and atomistic simulations. The lineshape of the linear infrared spectrum is better captured by semiempirical (density functional tight binding) mixed quantum mechanical/molecular mechanics simulations, whereas force field simulations with multipolar interactions yield lineshapes that are significantly too narrow. For the solvent dynamics, a relatively slow time scale of 2 ps is found from the experiments and supported by the mixed quantum mechanical/molecular mechanics simulations. With multipolar force fields fitted to the available thermodynamical data, the time scale is considerably faster—on the 0.5 ps time scale. The simulations provide evidence for a well established CF-HOH hydrogen bond (population of 25%) which is found from the radial distribution function g(r) from both, force field and quantum mechanics/molecular mechanics simulations.

Scaling properties and symmetrical patterns in the epidemiology of rotavirus infection.

PubMed Central

José, Marco V; Bishop, Ruth F

2003-01-01

The rich epidemiological database of the incidence of rotavirus, as a cause of severe diarrhoea in young children, coupled with knowledge of the natural history of the infection, can make this virus a paradigm for studies of epidemic dynamics. The cyclic recurrence of childhood rotavirus epidemics in unvaccinated populations provides one of the best documented phenomena in population dynamics. This paper makes use of epidemiological data on rotavirus infection in young children admitted to hospital in Melbourne, Australia from 1977 to 2000. Several mathematical methods were used to characterize the overall dynamics of rotavirus infections as a whole and individually as serotypes G1, G2, G3, G4 and G9. These mathematical methods are as follows: seasonal autoregressive integrated moving-average (SARIMA) models, power spectral density (PSD), higher-order spectral analysis (HOSA) (bispectrum estimation and quadratic phase coupling (QPC)), detrended fluctuation analysis (DFA), wavelet analysis (WA) and a surrogate data analysis technique. Each of these techniques revealed different dynamic aspects of rotavirus epidemiology. In particular, we confirm the existence of an annual, biannual and a quinquennial period but additionally we found other embedded cycles (e.g. ca. 3 years). There seems to be an overall unique geometric and dynamic structure of the data despite the apparent changes in the dynamics of the last years. The inherent dynamics seems to be conserved regardless of the emergence of new serotypes, the re-emergence of old serotypes or the transient disappearance of a particular serotype. More importantly, the dynamics of all serotypes is multiple synchronized so that they behave as a single entity at the epidemic level. Overall, the whole dynamics follow a scale-free power-law fractal scaling behaviour. We found that there are three different scaling regions in the time-series, suggesting that processes influencing the epidemic dynamics of rotavirus over less than 12 months differ from those that operate between 1 and ca. 3 years, as well as those between 3 and ca. 5 years. To discard the possibility that the observed patterns could be due to artefacts, we applied a surrogate data analysis technique which enabled us to discern if only random components or linear features of the incidence of rotavirus contribute to its dynamics. The global dynamics of the epidemic is portrayed by wavelet-based incidence analysis. The resulting wavelet transform of the incidence of rotavirus crisply reveals a repeating pattern over time that looks similar on many scales (a property called self-similarity). Both the self-similar behaviour and the absence of a single characteristic scale of the power-law fractal-like scaling of the incidence of rotavirus infection imply that there is not a universal inherently more virulent serotype to which severe gastroenteritis can uniquely be ascribed. PMID:14561323

Modelling opinion formation driven communities in social networks

NASA Astrophysics Data System (ADS)

Iñiguez, Gerardo; Barrio, Rafael A.; Kertész, János; Kaski, Kimmo K.

2011-09-01

In a previous paper we proposed a model to study the dynamics of opinion formation in human societies by a co-evolution process involving two distinct time scales of fast transaction and slower network evolution dynamics. In the transaction dynamics we take into account short range interactions as discussions between individuals and long range interactions to describe the attitude to the overall mood of society. The latter is handled by a uniformly distributed parameter α, assigned randomly to each individual, as quenched personal bias. The network evolution dynamics is realised by rewiring the societal network due to state variable changes as a result of transaction dynamics. The main consequence of this complex dynamics is that communities emerge in the social network for a range of values in the ratio between time scales. In this paper we focus our attention on the attitude parameter α and its influence on the conformation of opinion and the size of the resulting communities. We present numerical studies and extract interesting features of the model that can be interpreted in terms of social behaviour.

Monitoring forest dynamics with multi-scale and time series imagery.

PubMed

Huang, Chunbo; Zhou, Zhixiang; Wang, Di; Dian, Yuanyong

2016-05-01

To learn the forest dynamics and evaluate the ecosystem services of forest effectively, a timely acquisition of spatial and quantitative information of forestland is very necessary. Here, a new method was proposed for mapping forest cover changes by combining multi-scale satellite remote-sensing imagery with time series data. Using time series Normalized Difference Vegetation Index products derived from the Moderate Resolution Imaging Spectroradiometer images (MODIS-NDVI) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images as data source, a hierarchy stepwise analysis from coarse scale to fine scale was developed for detecting the forest change area. At the coarse scale, MODIS-NDVI data with 1-km resolution were used to detect the changes in land cover types and a land cover change map was constructed using NDVI values at vegetation growing seasons. At the fine scale, based on the results at the coarse scale, Landsat TM/ETM+ data with 30-m resolution were used to precisely detect the forest change location and forest change trend by analyzing time series forest vegetation indices (IFZ). The method was tested using the data for Hubei Province, China. The MODIS-NDVI data from 2001 to 2012 were used to detect the land cover changes, and the overall accuracy was 94.02 % at the coarse scale. At the fine scale, the available TM/ETM+ images at vegetation growing seasons between 2001 and 2012 were used to locate and verify forest changes in the Three Gorges Reservoir Area, and the overall accuracy was 94.53 %. The accuracy of the two layer hierarchical monitoring results indicated that the multi-scale monitoring method is feasible and reliable.

Integrating macro and micro scale approaches in the agent-based modeling of residential dynamics

NASA Astrophysics Data System (ADS)

Saeedi, Sara

2018-06-01

With the advancement of computational modeling and simulation (M&S) methods as well as data collection technologies, urban dynamics modeling substantially improved over the last several decades. The complex urban dynamics processes are most effectively modeled not at the macro-scale, but following a bottom-up approach, by simulating the decisions of individual entities, or residents. Agent-based modeling (ABM) provides the key to a dynamic M&S framework that is able to integrate socioeconomic with environmental models, and to operate at both micro and macro geographical scales. In this study, a multi-agent system is proposed to simulate residential dynamics by considering spatiotemporal land use changes. In the proposed ABM, macro-scale land use change prediction is modeled by Artificial Neural Network (ANN) and deployed as the agent environment and micro-scale residential dynamics behaviors autonomously implemented by household agents. These two levels of simulation interacted and jointly promoted urbanization process in an urban area of Tehran city in Iran. The model simulates the behavior of individual households in finding ideal locations to dwell. The household agents are divided into three main groups based on their income rank and they are further classified into different categories based on a number of attributes. These attributes determine the households' preferences for finding new dwellings and change with time. The ABM environment is represented by a land-use map in which the properties of the land parcels change dynamically over the simulation time. The outputs of this model are a set of maps showing the pattern of different groups of households in the city. These patterns can be used by city planners to find optimum locations for building new residential units or adding new services to the city. The simulation results show that combining macro- and micro-level simulation can give full play to the potential of the ABM to understand the driving mechanism of urbanization and provide decision-making support for urban management.

Dynamic Long-Term Anticipation of Chaotic States

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

Voss, Henning U.

2001-07-02

Introducing a short time delay into the coupling of two synchronizing chaotic systems, it was shown recently that the driven system may anticipate the driving system in real time. Augmenting the phase space of the driven system, we accomplish anticipation times that are multiples of the coupling delay time and exceed characteristic time scales of the chaotic dynamics. The stability properties of the associated anticipatory synchronization manifold in certain cases turn out to be the same as for identically synchronizing oscillators.

Tree Circumference Dynamics in Four Forests Characterized Using Automated Dendrometer Bands

PubMed Central

McMahon, Sean M.; Detto, Matteo; Lutz, James A.; Davies, Stuart J.; Chang-Yang, Chia-Hao; Anderson-Teixeira, Kristina J.

2016-01-01

Stem diameter is one of the most commonly measured attributes of trees, forming the foundation of forest censuses and monitoring. Changes in tree stem circumference include both irreversible woody stem growth and reversible circumference changes related to water status, yet these fine-scale dynamics are rarely leveraged to understand forest ecophysiology and typically ignored in plot- or stand-scale estimates of tree growth and forest productivity. Here, we deployed automated dendrometer bands on 12–40 trees at four different forested sites—two temperate broadleaf deciduous, one temperate conifer, and one tropical broadleaf semi-deciduous—to understand how tree circumference varies on time scales of hours to months, how these dynamics relate to environmental conditions, and whether the structure of these variations might introduce substantive error into estimates of woody growth. Diurnal stem circumference dynamics measured over the bark commonly—but not consistently—exhibited daytime shrinkage attributable to transpiration-driven changes in stem water storage. The amplitude of this shrinkage was significantly correlated with climatic variables (daily temperature range, vapor pressure deficit, and radiation), sap flow and evapotranspiration. Diurnal variations were typically <0.5 mm circumference in amplitude and unlikely to be of concern to most studies of tree growth. Over time scales of multiple days, the bands captured circumference increases in response to rain events, likely driven by combinations of increased stem water storage and bark hydration. Particularly at the tropical site, these rain responses could be quite substantial, ranging up to 1.5 mm circumference expansion within 48 hours following a rain event. We conclude that over-bark measurements of stem circumference change sometimes correlate with but have limited potential for directly estimating daily transpiration, but that they can be valuable on time scales of days to weeks for characterizing changes in stem growth and hydration. PMID:28030646

Universal Scaling Laws in the Dynamics of a Homogeneous Unitary Bose Gas

NASA Astrophysics Data System (ADS)

Eigen, Christoph; Glidden, Jake A. P.; Lopes, Raphael; Navon, Nir; Hadzibabic, Zoran; Smith, Robert P.

2017-12-01

We study the dynamics of an initially degenerate homogeneous Bose gas after an interaction quench to the unitary regime at a magnetic Feshbach resonance. As the cloud decays and heats, it exhibits a crossover from degenerate- to thermal-gas behavior, both of which are characterized by universal scaling laws linking the particle-loss rate to the total atom number N . In the degenerate and thermal regimes, the per-particle loss rate is ∝N2 /3 and N26 /9, respectively. The crossover occurs at a universal kinetic energy per particle and at a universal time after the quench, in units of energy and time set by the gas density. By slowly sweeping the magnetic field away from the resonance and creating a mixture of atoms and molecules, we also map out the dynamics of correlations in the unitary gas, which display a universal temporal scaling with the gas density, and reach a steady state while the gas is still degenerate.

Universal Scaling Laws in the Dynamics of a Homogeneous Unitary Bose Gas.

PubMed

Eigen, Christoph; Glidden, Jake A P; Lopes, Raphael; Navon, Nir; Hadzibabic, Zoran; Smith, Robert P

2017-12-22

We study the dynamics of an initially degenerate homogeneous Bose gas after an interaction quench to the unitary regime at a magnetic Feshbach resonance. As the cloud decays and heats, it exhibits a crossover from degenerate- to thermal-gas behavior, both of which are characterized by universal scaling laws linking the particle-loss rate to the total atom number N. In the degenerate and thermal regimes, the per-particle loss rate is ∝N^{2/3} and N^{26/9}, respectively. The crossover occurs at a universal kinetic energy per particle and at a universal time after the quench, in units of energy and time set by the gas density. By slowly sweeping the magnetic field away from the resonance and creating a mixture of atoms and molecules, we also map out the dynamics of correlations in the unitary gas, which display a universal temporal scaling with the gas density, and reach a steady state while the gas is still degenerate.

[Interdependence of plankton spatial distribution and plancton biomass temporal oscillations: mathematical simulation].

PubMed

Medvedinskiĭ, A B; Tikhonova, I A; Li, B L; Malchow, H

2003-01-01

The dynamics of aquatic biological communities in a patchy environment is of great interest in respect to interrelations between phenomena at various spatial and time scales. To study the complex plankton dynamics in relation to variations of such a biologically essential parameter as the fish predation rate, we use a simple reaction-diffusion model of trophic interactions between phytoplankton, zooplankton, and fish. We suggest that plankton is distributed between two habitats one of which is fish-free due to hydrological inhomogeneity, while the other is fish-populated. We show that temporal variations in the fish predation rate do not violate the strong correspondence between the character of spatial distribution of plankton and changes of plankton biomass in time: regular temporal oscillations of plankton biomass correspond to large-scale plankton patches, while chaotic oscillations correspond to small-scale plankton patterns. As in the case of the constant fish predation rate, the chaotic plankton dynamics is characterized by coexistence of the chaotic attractor and limit cycle.

Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns

PubMed Central

Gonzalez-Castillo, Javier; Hoy, Colin W.; Handwerker, Daniel A.; Robinson, Meghan E.; Buchanan, Laura C.; Saad, Ziad S.; Bandettini, Peter A.

2015-01-01

Functional connectivity (FC) patterns in functional MRI exhibit dynamic behavior on the scale of seconds, with rich spatiotemporal structure and limited sets of whole-brain, quasi-stable FC configurations (FC states) recurring across time and subjects. Based on previous evidence linking various aspects of cognition to group-level, minute-to-minute FC changes in localized connections, we hypothesized that whole-brain FC states may reflect the global, orchestrated dynamics of cognitive processing on the scale of seconds. To test this hypothesis, subjects were continuously scanned as they engaged in and transitioned between mental states dictated by tasks. FC states computed within windows as short as 22.5 s permitted robust tracking of cognition in single subjects with near perfect accuracy. Accuracy dropped markedly for subjects with the lowest task performance. Spatially restricting FC information decreased accuracy at short time scales, emphasizing the distributed nature of whole-brain FC dynamics, beyond univariate magnitude changes, as valuable markers of cognition. PMID:26124112

Decoding the spatial signatures of multi-scale climate variability - a climate network perspective

NASA Astrophysics Data System (ADS)

Donner, R. V.; Jajcay, N.; Wiedermann, M.; Ekhtiari, N.; Palus, M.

2017-12-01

During the last years, the application of complex networks as a versatile tool for analyzing complex spatio-temporal data has gained increasing interest. Establishing this approach as a new paradigm in climatology has already provided valuable insights into key spatio-temporal climate variability patterns across scales, including novel perspectives on the dynamics of the El Nino Southern Oscillation or the emergence of extreme precipitation patterns in monsoonal regions. In this work, we report first attempts to employ network analysis for disentangling multi-scale climate variability. Specifically, we introduce the concept of scale-specific climate networks, which comprises a sequence of networks representing the statistical association structure between variations at distinct time scales. For this purpose, we consider global surface air temperature reanalysis data and subject the corresponding time series at each grid point to a complex-valued continuous wavelet transform. From this time-scale decomposition, we obtain three types of signals per grid point and scale - amplitude, phase and reconstructed signal, the statistical similarity of which is then represented by three complex networks associated with each scale. We provide a detailed analysis of the resulting connectivity patterns reflecting the spatial organization of climate variability at each chosen time-scale. Global network characteristics like transitivity or network entropy are shown to provide a new view on the (global average) relevance of different time scales in climate dynamics. Beyond expected trends originating from the increasing smoothness of fluctuations at longer scales, network-based statistics reveal different degrees of fragmentation of spatial co-variability patterns at different scales and zonal shifts among the key players of climate variability from tropically to extra-tropically dominated patterns when moving from inter-annual to decadal scales and beyond. The obtained results demonstrate the potential usefulness of systematically exploiting scale-specific climate networks, whose general patterns are in line with existing climatological knowledge, but provide vast opportunities for further quantifications at local, regional and global scales that are yet to be explored.

Stability analysis and backward whirl investigation of cracked rotors with time-varying stiffness

NASA Astrophysics Data System (ADS)

AL-Shudeifat, Mohammad A.

2015-07-01

The dynamic stability of dynamical systems with time-periodic stiffness is addressed here. Cracked rotor systems with time-periodic stiffness are well-known examples of such systems. Time-varying area moments of inertia at the cracked element cross-section of a cracked rotor have been used to formulate the time-periodic finite element stiffness matrix. The semi-infinite coefficient matrix obtained by applying the harmonic balance (HB) solution to the finite element (FE) equations of motion is employed here to study the dynamic stability of the system. Consequently, the sign of the determinant of a scaled version of a sub-matrix of this semi-infinite coefficient matrix at a finite number of harmonics in the HB solution is found to be sufficient for identifying the major unstable zones of the system in the parameter plane. Specifically, it is found that the negative determinant always corresponds to unstable zones in all of the systems considered. This approach is applied to a parametrically excited Mathieu's equation, a two degree-of-freedom linear time-periodic dynamical system, a cracked Jeffcott rotor and a finite element model of the cracked rotor system. Compared to the corresponding results obtained by Floquet's theory, the sign of the determinant of the scaled sub-matrix is found to be an efficient tool for identifying the major unstable zones of the linear time-periodic parametrically excited systems, especially large-scale FE systems. Moreover, it is found that the unstable zones for a FE cracked rotor with an open transverse crack model only appear at the backward whirl. The theoretical and experimental results have been found to agree well for verifying that the open crack model excites the backward whirl amplitudes at the critical backward whirling rotational speeds.

Timescales of Massive Human Entrainment

PubMed Central

Fusaroli, Riccardo; Perlman, Marcus; Mislove, Alan; Paxton, Alexandra; Matlock, Teenie; Dale, Rick

2015-01-01

The past two decades have seen an upsurge of interest in the collective behaviors of complex systems composed of many agents entrained to each other and to external events. In this paper, we extend the concept of entrainment to the dynamics of human collective attention. We conducted a detailed investigation of the unfolding of human entrainment—as expressed by the content and patterns of hundreds of thousands of messages on Twitter—during the 2012 US presidential debates. By time-locking these data sources, we quantify the impact of the unfolding debate on human attention at three time scales. We show that collective social behavior covaries second-by-second to the interactional dynamics of the debates: A candidate speaking induces rapid increases in mentions of his name on social media and decreases in mentions of the other candidate. Moreover, interruptions by an interlocutor increase the attention received. We also highlight a distinct time scale for the impact of salient content during the debates: Across well-known remarks in each debate, mentions in social media start within 5–10 seconds after it occurs; peak at approximately one minute; and slowly decay in a consistent fashion across well-known events during the debates. Finally, we show that public attention after an initial burst slowly decays through the course of the debates. Thus we demonstrate that large-scale human entrainment may hold across a number of distinct scales, in an exquisitely time-locked fashion. The methods and results pave the way for careful study of the dynamics and mechanisms of large-scale human entrainment. PMID:25880357

Report of the panel on earth rotation and reference frames, section 7

NASA Technical Reports Server (NTRS)

Dickey, Jean O.; Dickman, Steven R.; Eubanks, Marshall T.; Feissel, Martine; Herring, Thomas A.; Mueller, Ivan I.; Rosen, Richard D.; Schutz, Robert E.; Wahr, John M.; Wilson, Charles R.

1991-01-01

Objectives and requirements for Earth rotation and reference frame studies in the 1990s are discussed. The objectives are to observe and understand interactions of air and water with the rotational dynamics of the Earth, the effects of the Earth's crust and mantle on the dynamics and excitation of Earth rotation variations over time scales of hours to centuries, and the effects of the Earth's core on the rotational dynamics and the excitation of Earth rotation variations over time scales of a year or longer. Another objective is to establish, refine and maintain terrestrial and celestrial reference frames. Requirements include improvements in observations and analysis, improvements in celestial and terrestrial reference frames and reference frame connections, and improved observations of crustal motion and mass redistribution on the Earth.

Structure and Dynamics of Confined C-O-H Fluids Relevant to the Subsurface: Application of Magnetic Resonance, Neutron Scattering and Molecular Dynamics Simulations

NASA Astrophysics Data System (ADS)

Gautam, Siddharth S.; Ok, Salim; Cole, David R.

2017-06-01

Geo-fluids consisting of C-O-H volatiles are the main mode of transport of mass and energy throughout the lithosphere and are commonly found confined in pores, grain boundaries and fractures. The confinement of these fluids by porous media at the length scales of a few nanometers gives rise to numerous physical and chemical properties that deviate from the bulk behavior. Studying the structural and dynamical properties of these confined fluids at the length and time scales of nanometers and picoseconds respectively forms an important component of understanding their behavior. To study confined fluids, non-destructive penetrative probes are needed. Nuclear magnetic resonance (NMR) by virtue of its ability to monitor longitudinal and transverse magnetization relaxations of spins, and chemical shifts brought about by the chemical environment of a nucleus, and measuring diffusion coefficient provides a good opportunity to study dynamics and chemical structure at the molecular length and time scales. Another technique that gives insights into the dynamics and structure at these length and time scales is neutron scattering (NS). This is because the wavelength and energies of cold and thermal neutrons used in scattering experiments are in the same range as the spatial features and energies involved in the dynamical processes occurring at the molecular level. Molecular Dynamics (MD) simulations on the other hand help with the interpretation of the NMR and NS data. Simulations can also supplement the experiments by calculating quantities not easily accessible to experiments. Thus using NMR, NS and MD simulations in conjunction, a complete description of the molecular structure and dynamics of confined geo-fluids can be obtained. In the current review, our aim is to show how a synergistic use of these three techniques has helped shed light on the complex behavior of water, CO2, and low molecular weight hydrocarbons. After summarizing the theoretical backgrounds of the techniques, we will discuss some recent examples of the use of NMR, NS, and MD simulations to the study of confined fluids.

Data series embedding and scale invariant statistics.

PubMed

Michieli, I; Medved, B; Ristov, S

2010-06-01

Data sequences acquired from bio-systems such as human gait data, heart rate interbeat data, or DNA sequences exhibit complex dynamics that is frequently described by a long-memory or power-law decay of autocorrelation function. One way of characterizing that dynamics is through scale invariant statistics or "fractal-like" behavior. For quantifying scale invariant parameters of physiological signals several methods have been proposed. Among them the most common are detrended fluctuation analysis, sample mean variance analyses, power spectral density analysis, R/S analysis, and recently in the realm of the multifractal approach, wavelet analysis. In this paper it is demonstrated that embedding the time series data in the high-dimensional pseudo-phase space reveals scale invariant statistics in the simple fashion. The procedure is applied on different stride interval data sets from human gait measurements time series (Physio-Bank data library). Results show that introduced mapping adequately separates long-memory from random behavior. Smaller gait data sets were analyzed and scale-free trends for limited scale intervals were successfully detected. The method was verified on artificially produced time series with known scaling behavior and with the varying content of noise. The possibility for the method to falsely detect long-range dependence in the artificially generated short range dependence series was investigated. (c) 2009 Elsevier B.V. All rights reserved.

4D ground penetrating radar measurements as non-invasive means for hydrological process investigation

NASA Astrophysics Data System (ADS)

Jackisch, Conrad; Allroggen, Niklas

2017-04-01

The missing vision into the subsurface appears to be a major limiting factor for our hydrological process understanding and theory development. Today, hydrology-related sciences have collected tremendous evidence for soils acting as drainage network and retention stores simultaneously in structured and self-organising domains. However, our present observation technology relies mainly on point-scale sensors, which integrate over a volume of unknown structures and is blind for their distribution. Although heterogeneity is acknowledged at all scales, it is rarely seen as inherent system property. At small scales (soil moisture probe) and at large scales (neutron probe) our measurements leave quite some ambiguity. Consequently, spatially and temporally continuous measurement of soil water states is essential for advancing our understanding and development of subsurface process theories. We present results from several irrigation experiments accompanied by 2D and 3D time-lapse GPR for the development of a novel technique to visualise and quantify water dynamics in the subsurface. Through the comparison of TDR, tracer and gravimetric measurement of soil moisture it becomes apparent that all sensor-based techniques are capable to record temporal dynamics, but are challenged to precisely quantify the measurements and to extrapolate them in space. At the same time excavative methods are very limited in temporal and spatial resolution. The application of non-invasive 4D GPR measurements complements the existing techniques and reveals structural and temporal dynamics simultaneously. By consequently increasing the density of the GPR data recordings in time and space, we find means to process the data also in the time-dimension. This opens ways to quantitatively analyse soil water dynamics in complex settings.

Aminopolymer Mobility and Support Interactions in Silica-PEI Composites for CO 2 Capture Applications: A Quasielastic Neutron Scattering Study

DOE PAGES

Holewinski, Adam; Sakwa-Novak, Miles A.; Carrillo, Jan-Michael Y.; ...

2017-05-30

Composite gas sorbents, formed from an active polymer phase and a porous support, are promising materials for the separation of acid gases from a variety of gas streams. Significant changes in sorption performance (capacity, rate, stability etc.) can be achieved by tuning the properties of the polymer and the nature of interactions between polymer and support. We utilize quasielastic neutron scattering (QENS) and coarse-grained molecular dynamics (MD) simulations to characterize the dynamic behavior of the most commonly reported polymer in such materials, poly(ethylenimine) (PEI), both in bulk form and when supported in a mesoporous silica framework. The polymer chain dynamicsmore » (rotational and translational diffusion) are characterized using two neutron backscattering spectrometers that have overlapping time scales, ranging from picoseconds to a few nanoseconds. Two modes of motion are detected for the PEI molecule in QENS. At low energy transfers, a “slow process” on the time scale of ~200 ps is found and attributed to jump-mediated, center-of-mass diffusion. Second, a “fast process” at ~20 ps scale is also found and is attributed to a locally confined, jump-diffusion. Characteristic data (time scale and spectral weight) of these processes are compared to those characterized by MD, and reasonable agreement is found. For the nanopore-confined PEI, we observe a significant reduction in the time scale of polymer motion as compared to the bulk. The impacts of silica surface functionalization and of polymer fill fraction in the silica pores (controlling the portion of polymer molecules in contact with the pore walls), are both studied in detail. Hydrophobic functionalization of the silica leads to an increase of the PEI mobility above that in native silanol-terminated silica, but the dynamics are still slower than those in bulk PEI. Sorbents with faster PEI dynamics are also found to be more efficient for CO 2 capture, possibly because sorption sites are more accessible than those in systems with slower PEI dynamics. Therefore, this work supports the existence of a link between the affinity of the support for PEI and the accessibility of active sorbent functional groups.« less

The architecture of dynamic reservoir in the echo state network

NASA Astrophysics Data System (ADS)

Cui, Hongyan; Liu, Xiang; Li, Lixiang

2012-09-01

Echo state network (ESN) has recently attracted increasing interests because of its superior capability in modeling nonlinear dynamic systems. In the conventional echo state network model, its dynamic reservoir (DR) has a random and sparse topology, which is far from the real biological neural networks from both structural and functional perspectives. We hereby propose three novel types of echo state networks with new dynamic reservoir topologies based on complex network theory, i.e., with a small-world topology, a scale-free topology, and a mixture of small-world and scale-free topologies, respectively. We then analyze the relationship between the dynamic reservoir structure and its prediction capability. We utilize two commonly used time series to evaluate the prediction performance of the three proposed echo state networks and compare them to the conventional model. We also use independent and identically distributed time series to analyze the short-term memory and prediction precision of these echo state networks. Furthermore, we study the ratio of scale-free topology and the small-world topology in the mixed-topology network, and examine its influence on the performance of the echo state networks. Our simulation results show that the proposed echo state network models have better prediction capabilities, a wider spectral radius, but retain almost the same short-term memory capacity as compared to the conventional echo state network model. We also find that the smaller the ratio of the scale-free topology over the small-world topology, the better the memory capacities.

Electronic State Decomposition of Energetic Materials and Model Systems

DTIC Science & Technology

2010-11-17

Nitromethane at 226 nm and 271 nm at both Nanosecond and Femtosecond Temporal Scales," J. Phys. Chem. A 113, 85 (2009). Y. Q. Guo, A. Bhattacharya and E...less "energetic". 8. Photodissociation Dynamics of Nitromethane at 226 and 271 nm at Both Nanosecond and Femtosecond Time Scales Photodissociation...of nitromethane has been investigated for decades both theoretically and experimentally; however, as a whole picture, the dissociation dynamics for

Computational and Spectroscopic Investigations of the Molecular Scale Structure and Dynamics of Geologically Important Fluids and Mineral-Fluid Interfaces

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

R. James Kirkpatrick; Andrey G. Kalinichev

2008-11-25

Research supported by this grant focuses on molecular scale understanding of central issues related to the structure and dynamics of geochemically important fluids, fluid-mineral interfaces, and confined fluids using computational modeling and experimental methods. Molecular scale knowledge about fluid structure and dynamics, how these are affected by mineral surfaces and molecular-scale (nano-) confinement, and how water molecules and dissolved species interact with surfaces is essential to understanding the fundamental chemistry of a wide range of low-temperature geochemical processes, including sorption and geochemical transport. Our principal efforts are devoted to continued development of relevant computational approaches, application of these approaches tomore » important geochemical questions, relevant NMR and other experimental studies, and application of computational modeling methods to understanding the experimental results. The combination of computational modeling and experimental approaches is proving highly effective in addressing otherwise intractable problems. In 2006-2007 we have significantly advanced in new, highly promising research directions along with completion of on-going projects and final publication of work completed in previous years. New computational directions are focusing on modeling proton exchange reactions in aqueous solutions using ab initio molecular dynamics (AIMD), metadynamics (MTD), and empirical valence bond (EVB) approaches. Proton exchange is critical to understanding the structure, dynamics, and reactivity at mineral-water interfaces and for oxy-ions in solution, but has traditionally been difficult to model with molecular dynamics (MD). Our ultimate objective is to develop this capability, because MD is much less computationally demanding than quantum-chemical approaches. We have also extended our previous MD simulations of metal binding to natural organic matter (NOM) to a much longer time scale (up to 10 ns) for significantly larger systems. These calculations have allowed us, for the first time, to study the effects of metal cations with different charges and charge density on the NOM aggregation in aqueous solutions. Other computational work has looked at the longer-time-scale dynamical behavior of aqueous species at mineral-water interfaces investigated simultaneously by NMR spectroscopy. Our experimental NMR studies have focused on understanding the structure and dynamics of water and dissolved species at mineral-water interfaces and in two-dimensional nano-confinement within clay interlayers. Combined NMR and MD study of H2O, Na+, and Cl- interactions with the surface of quartz has direct implications regarding interpretation of sum frequency vibrational spectroscopic experiments for this phase and will be an important reference for future studies. We also used NMR to examine the behavior of K+ and H2O in the interlayer and at the surfaces of the clay minerals hectorite and illite-rich illite-smectite. This the first time K+ dynamics has been characterized spectroscopically in geochemical systems. Preliminary experiments were also performed to evaluate the potential of 75As NMR as a probe of arsenic geochemical behavior. The 75As NMR study used advanced signal enhancement methods, introduced a new data acquisition approach to minimize the time investment in ultra-wide-line NMR experiments, and provides the first evidence of a strong relationship between the chemical shift and structural parameters for this experimentally challenging nucleus. We have also initiated a series of inelastic and quasi-elastic neutron scattering measurements of water dynamics in the interlayers of clays and layered double hydroxides. The objective of these experiments is to probe the correlations of water molecular motions in confined spaces over the scale of times and distances most directly comparable to our MD simulations and on a time scale different than that probed by NMR. This work is being done in collaboration with Drs. C.-K. Loong, N. de Souza, and A.I. Kolesnikov at the Intense Pulsed Neutron Source facility of the Argonne National Lab, and Dr. A. Faraone at the NIST Center for Neutron Research. A manuscript reporting the first results of these experiments, which are highly complimentary to our previous NMR, X-ray, and infra-red results for these phases, is currently in preparation. In total, in 2006-2007 our work has resulted in the publication of 14 peer-reviewed research papers. We also devoted considerable effort to making our work known to a wide range of researchers, as indicated by the 24 contributed abstracts and 14 invited presentations.« less

Scale-dependent intrinsic entropies of complex time series.

PubMed

Yeh, Jia-Rong; Peng, Chung-Kang; Huang, Norden E

2016-04-13

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal's complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease. © 2016 The Author(s).

Dynamic fracture of tantalum under extreme tensile stress

DOE PAGES

Albertazzi, Bruno; Ozaki, Norimasa; Zhakhovsky, Vasily; ...

2017-06-02

The understanding of fracture phenomena of a material at extremely high strain rates is a key issue for a wide variety of scientific research ranging from applied science and technological developments to fundamental science such as laser-matter interaction and geology. Despite its interest, its study relies on a fine multiscale description, in between the atomic scale and macroscopic processes, so far only achievable by large-scale atomic simulations. Direct ultrafast real-time monitoring of dynamic fracture (spallation) at the atomic lattice scale with picosecond time resolution was beyond the reach of experimental techniques. We show that the coupling between a high-power opticalmore » laser pump pulse and a femtosecond x-ray probe pulse generated by an x-ray free electron laser allows detection of the lattice dynamics in a tantalum foil at an ultrahigh strain rate of Embedded Image ~2 × 10 8 to 3.5 × 10 8 s -1. A maximal density drop of 8 to 10%, associated with the onset of spallation at a spall strength of ~17 GPa, was directly measured using x-ray diffraction. The experimental results of density evolution agree well with large-scale atomistic simulations of shock wave propagation and fracture of the sample. Our experimental technique opens a new pathway to the investigation of ultrahigh strain-rate phenomena in materials at the atomic scale, including high-speed crack dynamics and stress-induced solid-solid phase transitions.« less

Explicit symplectic algorithms based on generating functions for relativistic charged particle dynamics in time-dependent electromagnetic field

NASA Astrophysics Data System (ADS)

Zhang, Ruili; Wang, Yulei; He, Yang; Xiao, Jianyuan; Liu, Jian; Qin, Hong; Tang, Yifa

2018-02-01

Relativistic dynamics of a charged particle in time-dependent electromagnetic fields has theoretical significance and a wide range of applications. The numerical simulation of relativistic dynamics is often multi-scale and requires accurate long-term numerical simulations. Therefore, explicit symplectic algorithms are much more preferable than non-symplectic methods and implicit symplectic algorithms. In this paper, we employ the proper time and express the Hamiltonian as the sum of exactly solvable terms and product-separable terms in space-time coordinates. Then, we give the explicit symplectic algorithms based on the generating functions of orders 2 and 3 for relativistic dynamics of a charged particle. The methodology is not new, which has been applied to non-relativistic dynamics of charged particles, but the algorithm for relativistic dynamics has much significance in practical simulations, such as the secular simulation of runaway electrons in tokamaks.

Dynamical equivalence, the origin of the Galactic field stellar and binary population, and the initial radius-mass relation of embedded clusters

NASA Astrophysics Data System (ADS)

Belloni, Diogo; Kroupa, Pavel; Rocha-Pinto, Helio J.; Giersz, Mirek

2018-03-01

In order to allow a better understanding of the origin of Galactic field populations, dynamical equivalence of stellar-dynamical systems has been postulated by Kroupa and Belloni et al. to allow mapping of solutions of the initial conditions of embedded clusters such that they yield, after a period of dynamical processing, the Galactic field population. Dynamically equivalent systems are defined to initially and finally have the same distribution functions of periods, mass ratios and eccentricities of binary stars. Here, we search for dynamically equivalent clusters using the MOCCA code. The simulations confirm that dynamically equivalent solutions indeed exist. The result is that the solution space is next to identical to the radius-mass relation of Marks & Kroupa, ( r_h/pc )= 0.1^{+0.07}_{-0.04} ( M_ecl/M_{⊙} )^{0.13± 0.04}. This relation is in good agreement with the oIMF. This is achieved by applying a similar procedurebserved density of molecular cloud clumps. According to the solutions, the time-scale to reach dynamical equivalence is about 0.5 Myr which is, interestingly, consistent with the lifetime of ultra-compact H II regions and the time-scale needed for gas expulsion to be active in observed very young clusters as based on their dynamical modelling.

Molecular dynamics study of thermodynamic scaling of the glass-transition dynamics in ionic liquids over wide temperature and pressure ranges.

PubMed

Habasaki, J; Casalini, R; Ngai, K L

2010-03-25

Experimentally, superpositioning of dynamic properties such as viscosity, relaxation times, or diffusion coefficients under different conditions of temperature T, pressure P, and volume V by the scaling variable TV(gamma) (where gamma is a material constant) has been reported as a general feature of many kinds of glass-forming materials. In the present work, molecular dynamics (MD) simulations have been performed to study the scaling of dynamics near the glass-transition regime of ionic liquids. Scaling in the simulated 1-ethyl-3-methylimidazolium nitrate (EMIM-NO(3)) system has been tested over wide ranges of temperatures and pressures. TV(gamma) scaling of the dynamics is well described by master curves with gamma = 4.0 +/- 0.2 and 3.8 +/- 0.2 for cation and anion, respectively. Structures and Coulombic terms of the corresponding states are found to be quite similar. The temperature and pressure dependence of the pair correlation function show similar trends and therefore can be superpositioned onto the master curve. Although the behaviors with gamma = 4 might be expected from the relation, gamma = n/3, for the dynamics with the soft-core-type potential U = epsilon(sigma/r)(n), with n = 12, pair potentials used in the MD simulation have a more complex form, and not all the repulsive terms can play their roles in the heterogeneous structures determined by ion-ion interactions. Scaling is related to the common part of effective potentials related to the pair correlation functions, including the many-body effect in real space.

Mesoscale Dynamical Regimes in the Midlatitudes

NASA Astrophysics Data System (ADS)

Craig, G. C.; Selz, T.

2018-01-01

The atmospheric mesoscales are characterized by a complex variety of meteorological phenomena that defy simple classification. Here a full space-time spectral analysis is carried out, based on a 7 day convection-permitting simulation of springtime midlatitude weather on a large domain. The kinetic energy is largest at synoptic scales, and on the mesoscale it is largely confined to an "advective band" where space and time scales are related by a constant of proportionality which corresponds to a velocity scale of about 10 m s-1. Computing the relative magnitude of different terms in the governing equations allows the identification of five dynamical regimes. These are tentatively identified as quasi-geostrophic flow, propagating gravity waves, stationary gravity waves related to orography, acoustic modes, and a weak temperature gradient regime, where vertical motions are forced by diabatic heating.

A multi-scale methodology for comparing GCM and RCM results over the Eastern Mediterranean

NASA Astrophysics Data System (ADS)

Samuels, Rana; Krichak, Simon; Breitgand, Joseph; Alpert, Pinhas

2010-05-01

The importance of skillful climate modeling is increasingly being realized as results are being incorporated into environmental, economic, and even business planning. Global circulation models (GCMs) employed by the IPCC provide results at spatial scales of hundreds of kilometers, which is useful for understanding global trends but not appropriate for use as input into regional and local impacts models used to inform policy and development. To address this shortcoming, regional climate models (RCMs) which dynamically downscale the results of the GCMs are used. In this study we present first results of a dynamically downscaled RCM focusing on the Eastern Mediterranean region. For the historical 1960-2000 time period, results at a spatial scale of both 25 km and 50 km are compared with historical station data from 5 locations across Israel as well as with the results of 3 GCM models (ECHAM5, NOAA GFDL, and CCCMA) at annual, monthly and daily time scales. Results from a recently completed Japanese GCM at a spatial scale of 20 km are also included. For the historical validation period, we show that as spatial scale increases the skill in capturing annual and inter-annual temperature and rainfall also increases. However, for intra-seasonal rainfall characteristics important for hydrological and agricultural planning (eg. dry and wet spells, number of rain days) the GCM results (including the 20 km Japanese model) capture the historical trends better than the dynamically downscaled RegCM. For future scenarios of temperature and precipitation changes, we compare results across the models for the available time periods, generating a range of future trends.

Utilizing the dynamic stark shift as a probe for dielectric relaxation in photosynthetic reaction centers during charge separation.

PubMed

Guo, Zhi; Lin, Su; Woodbury, Neal W

2013-09-26

In photosynthetic reaction centers, the electric field generated by light-induced charge separation produces electrochromic shifts in the transitions of reaction center pigments. The extent of this Stark shift indirectly reflects the effective field strength at a particular cofactor in the complex. The dynamics of the effective field strength near the two monomeric bacteriochlorophylls (BA and BB) in purple photosynthetic bacterial reaction centers has been explored near physiological temperature by monitoring the time-dependent Stark shift during charge separation (dynamic Stark shift). This dynamic Stark shift was determined through analysis of femtosecond time-resolved absorbance change spectra recorded in wild type reaction centers and in four mutants at position M210. In both wild type and the mutants, the kinetics of the dynamic Stark shift differ from those of electron transfer, though not in the same way. In wild type, the initial electron transfer and the increase in the effective field strength near the active-side monomer bacteriochlorophyll (BA) occur in synchrony, but the two signals diverge on the time scale of electron transfer to the quinone. In contrast, when tyrosine is replaced by aspartic acid at M210, the kinetics of the BA Stark shift and the initial electron transfer differ, but transfer to the quinone coincides with the decay of the Stark shift. This is interpreted in terms of differences in the dynamics of the local dielectric environment between the mutants and the wild type. In wild type, comparison of the Stark shifts associated with BA and BB on the two quasi-symmetric halves of the reaction center structure confirm that the effective dielectric constants near these cofactors are quite different when the reaction center is in the state P(+)QA(-), as previously determined by Steffen et al. at 1.5 K (Steffen, M. A.; et al. Science 1994, 264, 810-816). However, it is not possible to determine from static, low-temperature measurments if the difference in the effective dielectric constant between the two sides of the reaction center is manifest on the time scale of initial electron transfer. By comparing directly the Stark shift dynamics of the ground-state spectra of the two monomer bacteriochlorophylls, it is evident that there is, in fact, a large dielectric difference between protein environments of the two quasi-symmetric electron-transfer branches on the time scale of initial electron transfer and that the effective dielectric constant in the region continues to evolve on a time scale of hundreds of picoseconds.

Understanding the free energy barrier and multiple timescale dynamics of charge separation in organic photovoltaic cells.

PubMed

Yan, Yaming; Song, Linze; Shi, Qiang

2018-02-28

By employing several lattice model systems, we investigate the free energy barrier and real-time dynamics of charge separation in organic photovoltaic (OPV) cells. It is found that the combined effects of the external electric field, entropy, and charge delocalization reduce the free energy barrier significantly. The dynamic disorder reduces charge carrier delocalization and results in the increased charge separation barrier, while the effect of static disorder is more complicated. Simulation of the real-time dynamics indicates that the free charge generation process involves multiple time scales, including an ultrafast component within hundreds of femtoseconds, an intermediate component related to the relaxation of the hot charge transfer (CT) state, and a slow component on the time scale of tens of picoseconds from the thermally equilibrated CT state. Effects of hot exciton dissociation as well as its dependence on the energy offset between the Frenkel exciton and the CT state are also analyzed. The current results indicate that only a small energy offset between the band gap and the lowest energy CT state is needed to achieve efficient free charge generation in OPV devices, which agrees with recent experimental findings.

Understanding the free energy barrier and multiple timescale dynamics of charge separation in organic photovoltaic cells

NASA Astrophysics Data System (ADS)

Yan, Yaming; Song, Linze; Shi, Qiang

2018-02-01

By employing several lattice model systems, we investigate the free energy barrier and real-time dynamics of charge separation in organic photovoltaic (OPV) cells. It is found that the combined effects of the external electric field, entropy, and charge delocalization reduce the free energy barrier significantly. The dynamic disorder reduces charge carrier delocalization and results in the increased charge separation barrier, while the effect of static disorder is more complicated. Simulation of the real-time dynamics indicates that the free charge generation process involves multiple time scales, including an ultrafast component within hundreds of femtoseconds, an intermediate component related to the relaxation of the hot charge transfer (CT) state, and a slow component on the time scale of tens of picoseconds from the thermally equilibrated CT state. Effects of hot exciton dissociation as well as its dependence on the energy offset between the Frenkel exciton and the CT state are also analyzed. The current results indicate that only a small energy offset between the band gap and the lowest energy CT state is needed to achieve efficient free charge generation in OPV devices, which agrees with recent experimental findings.

Online Low-Rank Representation Learning for Joint Multi-subspace Recovery and Clustering.

PubMed

Li, Bo; Liu, Risheng; Cao, Junjie; Zhang, Jie; Lai, Yu-Kun; Liua, Xiuping

2017-10-06

Benefiting from global rank constraints, the lowrank representation (LRR) method has been shown to be an effective solution to subspace learning. However, the global mechanism also means that the LRR model is not suitable for handling large-scale data or dynamic data. For large-scale data, the LRR method suffers from high time complexity, and for dynamic data, it has to recompute a complex rank minimization for the entire data set whenever new samples are dynamically added, making it prohibitively expensive. Existing attempts to online LRR either take a stochastic approach or build the representation purely based on a small sample set and treat new input as out-of-sample data. The former often requires multiple runs for good performance and thus takes longer time to run, and the latter formulates online LRR as an out-ofsample classification problem and is less robust to noise. In this paper, a novel online low-rank representation subspace learning method is proposed for both large-scale and dynamic data. The proposed algorithm is composed of two stages: static learning and dynamic updating. In the first stage, the subspace structure is learned from a small number of data samples. In the second stage, the intrinsic principal components of the entire data set are computed incrementally by utilizing the learned subspace structure, and the low-rank representation matrix can also be incrementally solved by an efficient online singular value decomposition (SVD) algorithm. The time complexity is reduced dramatically for large-scale data, and repeated computation is avoided for dynamic problems. We further perform theoretical analysis comparing the proposed online algorithm with the batch LRR method. Finally, experimental results on typical tasks of subspace recovery and subspace clustering show that the proposed algorithm performs comparably or better than batch methods including the batch LRR, and significantly outperforms state-of-the-art online methods.

Statistical persistence of air pollutants (O3,SO2,NO2 and PM10) in Mexico City

NASA Astrophysics Data System (ADS)

Meraz, M.; Rodriguez, E.; Femat, R.; Echeverria, J. C.; Alvarez-Ramirez, J.

2015-06-01

The rescaled range (R / S) analysis was used for analyzing the statistical persistence of air pollutants in Mexico City. The air-pollution time series consisted of hourly observations of ozone, nitrogen dioxide, sulfur dioxide and particulate matter obtained at the Mexico City downtown monitoring station during 1999-2014. The results showed that long-range persistence is not a uniform property over a wide range of time scales, from days to months. In fact, although the air pollutant concentrations exhibit an average persistent behavior, environmental (e.g., daily and yearly) and socio-economic (e.g., daily and weekly) cycles are reflected in the dependence of the persistence strength as quantified in terms of the Hurst exponent. It was also found that the Hurst exponent exhibits time variations, with the ozone and nitrate oxide concentrations presenting some regularity, such as annual cycles. The persistence dynamics of the pollutant concentrations increased during the rainy season and decreased during the dry season. The time and scale dependences of the persistence properties provide some insights in the mechanisms involved in the internal dynamics of the Mexico City atmosphere for accumulating and dissipating dangerous air pollutants. While in the short-term individual pollutants dynamics seems to be governed by specific mechanisms, in the long-term (for monthly and higher scales) meteorological and seasonal mechanisms involved in atmospheric recirculation seem to dominate the dynamics of all air pollutant concentrations.

Incorporation of memory effects in coarse-grained modeling via the Mori-Zwanzig formalism

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

Li, Zhen; Bian, Xin; Karniadakis, George Em, E-mail: george-karniadakis@brown.edu

2015-12-28

The Mori-Zwanzig formalism for coarse-graining a complex dynamical system typically introduces memory effects. The Markovian assumption of delta-correlated fluctuating forces is often employed to simplify the formulation of coarse-grained (CG) models and numerical implementations. However, when the time scales of a system are not clearly separated, the memory effects become strong and the Markovian assumption becomes inaccurate. To this end, we incorporate memory effects into CG modeling by preserving non-Markovian interactions between CG variables, and the memory kernel is evaluated directly from microscopic dynamics. For a specific example, molecular dynamics (MD) simulations of star polymer melts are performed while themore » corresponding CG system is defined by grouping many bonded atoms into single clusters. Then, the effective interactions between CG clusters as well as the memory kernel are obtained from the MD simulations. The constructed CG force field with a memory kernel leads to a non-Markovian dissipative particle dynamics (NM-DPD). Quantitative comparisons between the CG models with Markovian and non-Markovian approximations indicate that including the memory effects using NM-DPD yields similar results as the Markovian-based DPD if the system has clear time scale separation. However, for systems with small separation of time scales, NM-DPD can reproduce correct short-time properties that are related to how the system responds to high-frequency disturbances, which cannot be captured by the Markovian-based DPD model.« less

Functional connectivity dynamically evolves on multiple time-scales over a static structural connectome: Models and mechanisms.

PubMed

Cabral, Joana; Kringelbach, Morten L; Deco, Gustavo

2017-10-15

Over the last decade, we have observed a revolution in brain structural and functional Connectomics. On one hand, we have an ever-more detailed characterization of the brain's white matter structural connectome. On the other, we have a repertoire of consistent functional networks that form and dissipate over time during rest. Despite the evident spatial similarities between structural and functional connectivity, understanding how different time-evolving functional networks spontaneously emerge from a single structural network requires analyzing the problem from the perspective of complex network dynamics and dynamical system's theory. In that direction, bottom-up computational models are useful tools to test theoretical scenarios and depict the mechanisms at the genesis of resting-state activity. Here, we provide an overview of the different mechanistic scenarios proposed over the last decade via computational models. Importantly, we highlight the need of incorporating additional model constraints considering the properties observed at finer temporal scales with MEG and the dynamical properties of FC in order to refresh the list of candidate scenarios. Copyright © 2017 Elsevier Inc. All rights reserved.

Antiferroelectric polarization switching and dynamic scaling of energy storage: A Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Huang, B. Y.; Lu, Z. X.; Zhang, Y.; Xie, Y. L.; Zeng, M.; Yan, Z. B.; Liu, J.-M.

2016-05-01

The polarization-electric field hysteresis loops and the dynamics of polarization switching in a two-dimensional antiferroelectric (AFE) lattice submitted to a time-oscillating electric field E(t) of frequency f and amplitude E0, is investigated using Monte Carlo simulation based on the Landau-Devonshire phenomenological theory on antiferroelectrics. It is revealed that the AFE double-loop hysteresis area A, i.e., the energy loss in one cycle of polarization switching, exhibits the single-peak frequency dispersion A(f), suggesting the unique characteristic time for polarization switching, which is independent of E0 as long as E0 is larger than the quasi-static coercive field for the antiferroelectric-ferroelectric transitions. However, the dependence of recoverable stored energy W on amplitude E0 seems to be complicated depending on temperature T and frequency f. A dynamic scaling behavior of the energy loss dispersion A(f) over a wide range of E0 is obtained, confirming the unique characteristic time for polarization switching of an AFE lattice. The present simulation may shed light on the dynamics of energy storage and release in AFE thin films.

A novel approach to the dynamical complexity of the Earth's magnetosphere at geomagnetic storm time-scales based on recurrences

NASA Astrophysics Data System (ADS)

Donner, Reik; Balasis, Georgios; Stolbova, Veronika; Wiedermann, Marc; Georgiou, Marina; Kurths, Jürgen

2016-04-01

Magnetic storms are the most prominent global manifestations of out-of-equilibrium magnetospheric dynamics. Investigating the dynamical complexity exhibited by geomagnetic observables can provide valuable insights into relevant physical processes as well as temporal scales associated with this phenomenon. In this work, we introduce several innovative data analysis techniques enabling a quantitative analysis of the Dst index non-stationary behavior. Using recurrence quantification analysis (RQA) and recurrence network analysis (RNA), we obtain a variety of complexity measures serving as markers of quiet- and storm-time magnetospheric dynamics. We additionally apply these techniques to the main driver of Dst index variations, the V BSouth coupling function and interplanetary medium parameters Bz and Pdyn in order to discriminate internal processes from the magnetosphere's response directly induced by the external forcing by the solar wind. The derived recurrence-based measures allow us to improve the accuracy with which magnetospheric storms can be classified based on ground-based observations. The new methodology presented here could be of significant interest for the space weather research community working on time series analysis for magnetic storm forecasts.

Dynamics of f(R) gravity models and asymmetry of time

NASA Astrophysics Data System (ADS)

Verma, Murli Manohar; Yadav, Bal Krishna

We solve the field equations of modified gravity for f(R) model in metric formalism. Further, we obtain the fixed points of the dynamical system in phase-space analysis of f(R) models, both with and without the effects of radiation. The stability of these points is studied against the perturbations in a smooth spatial background by applying the conditions on the eigenvalues of the matrix obtained in the linearized first-order differential equations. Following this, these fixed points are used for analyzing the dynamics of the system during the radiation, matter and acceleration-dominated phases of the universe. Certain linear and quadratic forms of f(R) are determined from the geometrical and physical considerations and the behavior of the scale factor is found for those forms. Further, we also determine the Hubble parameter H(t), the Ricci scalar R and the scale factor a(t) for these cosmic phases. We show the emergence of an asymmetry of time from the dynamics of the scalar field exclusively owing to the f(R) gravity in the Einstein frame that may lead to an arrow of time at a classical level.

Onboard Science Insights and Vehicle Dynamics from Scale-Model Trials of the Titan Mare Explorer (TiME) Capsule at Laguna Negra, Chile.

PubMed

Lorenz, Ralph D; Cabrol, Nathalie A

2018-05-01

A scale model of the proposed Titan Mare Explorer capsule was deployed at the Planetary Lake Lander field site at Laguna Negra, Chile. The tests served to calibrate models of wind-driven drift of the capsule and to understand its attitude motion in the wave field, as well as to identify dynamic and acoustic signatures of shoreline approach. This information enables formulation of onboard trigger criteria for near-shore science data acquisition. Key Words: Titan-Vehicle dynamics-Science autonomy-Lake. Astrobiology 18, 607-618.

A Multi-Scale, Integrated Approach to Representing Watershed Systems

NASA Astrophysics Data System (ADS)

Ivanov, Valeriy; Kim, Jongho; Fatichi, Simone; Katopodes, Nikolaos

2014-05-01

Understanding and predicting process dynamics across a range of scales are fundamental challenges for basic hydrologic research and practical applications. This is particularly true when larger-spatial-scale processes, such as surface-subsurface flow and precipitation, need to be translated to fine space-time scale dynamics of processes, such as channel hydraulics and sediment transport, that are often of primary interest. Inferring characteristics of fine-scale processes from uncertain coarse-scale climate projection information poses additional challenges. We have developed an integrated model simulating hydrological processes, flow dynamics, erosion, and sediment transport, tRIBS+VEGGIE-FEaST. The model targets to take the advantage of the current generation of wealth of data representing watershed topography, vegetation, soil, and landuse, as well as to explore the hydrological effects of physical factors and their feedback mechanisms over a range of scales. We illustrate how the modeling system connects precipitation-hydrologic runoff partition process to the dynamics of flow, erosion, and sedimentation, and how the soil's substrate condition can impact the latter processes, resulting in a non-unique response. We further illustrate an approach to using downscaled climate change information with a process-based model to infer the moments of hydrologic variables in future climate conditions and explore the impact of climate information uncertainty.

Dynamic Forces Between Two Deformable Oil Droplets in Water

NASA Astrophysics Data System (ADS)

Dagastine, Raymond R.; Manica, Rogério; Carnie, Steven L.; Chan, D. Y. C.; Stevens, Geoffrey W.; Grieser, Franz

2006-07-01

The understanding of static interactions in colloidal suspensions is well established, whereas dynamic interactions more relevant to biological and other suspended soft-matter systems are less well understood. We present the direct force measurement and quantitative theoretical description for dynamic forces for liquid droplets in another immiscible fluid. Analysis of this system demonstrates the strong link between interfacial deformation, static surface forces, and hydrodynamic drainage, which govern dynamic droplet-droplet interactions over the length scale of nanometers and over the time scales of Brownian collisions. The results and analysis have direct bearing on the control and manipulation of suspended droplets in soft-matter systems ranging from the emulsions in shampoo to cellular interactions.

Achieving Rigorous Accelerated Conformational Sampling in Explicit Solvent.

PubMed

Doshi, Urmi; Hamelberg, Donald

2014-04-03

Molecular dynamics simulations can provide valuable atomistic insights into biomolecular function. However, the accuracy of molecular simulations on general-purpose computers depends on the time scale of the events of interest. Advanced simulation methods, such as accelerated molecular dynamics, have shown tremendous promise in sampling the conformational dynamics of biomolecules, where standard molecular dynamics simulations are nonergodic. Here we present a sampling method based on accelerated molecular dynamics in which rotatable dihedral angles and nonbonded interactions are boosted separately. This method (RaMD-db) is a different implementation of the dual-boost accelerated molecular dynamics, introduced earlier. The advantage is that this method speeds up sampling of the conformational space of biomolecules in explicit solvent, as the degrees of freedom most relevant for conformational transitions are accelerated. We tested RaMD-db on one of the most difficult sampling problems - protein folding. Starting from fully extended polypeptide chains, two fast folding α-helical proteins (Trpcage and the double mutant of C-terminal fragment of Villin headpiece) and a designed β-hairpin (Chignolin) were completely folded to their native structures in very short simulation time. Multiple folding/unfolding transitions could be observed in a single trajectory. Our results show that RaMD-db is a promisingly fast and efficient sampling method for conformational transitions in explicit solvent. RaMD-db thus opens new avenues for understanding biomolecular self-assembly and functional dynamics occurring on long time and length scales.

The relationship of dynamical heterogeneity to the Adam-Gibbs and random first-order transition theories of glass formation.

PubMed

Starr, Francis W; Douglas, Jack F; Sastry, Srikanth

2013-03-28

We carefully examine common measures of dynamical heterogeneity for a model polymer melt and test how these scales compare with those hypothesized by the Adam and Gibbs (AG) and random first-order transition (RFOT) theories of relaxation in glass-forming liquids. To this end, we first analyze clusters of highly mobile particles, the string-like collective motion of these mobile particles, and clusters of relative low mobility. We show that the time scale of the high-mobility clusters and strings is associated with a diffusive time scale, while the low-mobility particles' time scale relates to a structural relaxation time. The difference of the characteristic times for the high- and low-mobility particles naturally explains the well-known decoupling of diffusion and structural relaxation time scales. Despite the inherent difference of dynamics between high- and low-mobility particles, we find a high degree of similarity in the geometrical structure of these particle clusters. In particular, we show that the fractal dimensions of these clusters are consistent with those of swollen branched polymers or branched polymers with screened excluded-volume interactions, corresponding to lattice animals and percolation clusters, respectively. In contrast, the fractal dimension of the strings crosses over from that of self-avoiding walks for small strings, to simple random walks for longer, more strongly interacting, strings, corresponding to flexible polymers with screened excluded-volume interactions. We examine the appropriateness of identifying the size scales of either mobile particle clusters or strings with the size of cooperatively rearranging regions (CRR) in the AG and RFOT theories. We find that the string size appears to be the most consistent measure of CRR for both the AG and RFOT models. Identifying strings or clusters with the "mosaic" length of the RFOT model relaxes the conventional assumption that the "entropic droplets" are compact. We also confirm the validity of the entropy formulation of the AG theory, constraining the exponent values of the RFOT theory. This constraint, together with the analysis of size scales, enables us to estimate the characteristic exponents of RFOT.

Stochastic dynamics of genetic broadcasting networks

NASA Astrophysics Data System (ADS)

Potoyan, Davit; Wolynes, Peter

The complex genetic programs of eukaryotic cells are often regulated by key transcription factors occupying or clearing out of a large number of genomic locations. Orchestrating the residence times of these factors is therefore important for the well organized functioning of a large network. The classic models of genetic switches sidestep this timing issue by assuming the binding of transcription factors to be governed entirely by thermodynamic protein-DNA affinities. Here we show that relying on passive thermodynamics and random release times can lead to a ''time-scale crisis'' of master genes that broadcast their signals to large number of binding sites. We demonstrate that this ''time-scale crisis'' can be resolved by actively regulating residence times through molecular stripping. We illustrate these ideas by studying the stochastic dynamics of the genetic network of the central eukaryotic master regulator NFκB which broadcasts its signals to many downstream genes that regulate immune response, apoptosis etc.

Trajectory Adjustments Underlying Task-Specific Intermittent Force Behaviors and Muscular Rhythms

PubMed Central

Chen, Yi-Ching; Lin, Yen-Ting; Huang, Chien-Ting; Shih, Chia-Li; Yang, Zong-Ru; Hwang, Ing-Shiou

2013-01-01

Force intermittency is one of the major causes of motor variability. Focusing on the dynamics of force intermittency, this study was undertaken to investigate how force trajectory is fine-tuned for static and dynamic force-tracking of a comparable physical load. Twenty-two healthy adults performed two unilateral resistance protocols (static force-tracking at 75% maximal effort and dynamic force-tracking in the range of 50%–100% maximal effort) using the left hand. The electromyographic activity and force profile of the designated hand were monitored. Gripping force was off-line decomposed into a primary movement spectrally identical to the target motion and a force intermittency profile containing numerous force pulses. The results showed that dynamic force-tracking exhibited greater intermittency amplitude and force pulse but a smaller amplitude ratio of primary movement to force intermittency than static force-tracking. Multi-scale entropy analysis revealed that force intermittency during dynamic force-tracking was more complex on a low time scale but more regular on a high time scale than that of static force-tracking. Together with task-dependent force intermittency properties, dynamic force-tracking exhibited a smaller 8–12 Hz muscular oscillation but a more potentiated muscular oscillation at 35–50 Hz than static force-tracking. In conclusion, force intermittency reflects differing trajectory controls for static and dynamic force-tracking. The target goal of dynamic tracking is achieved through trajectory adjustments that are more intricate and more frequent than those of static tracking, pertaining to differing organizations and functioning of muscular oscillations in the alpha and gamma bands. PMID:24098640

Collective hydration dynamics in some amino acid solutions: A combined GHz-THz spectroscopic study

NASA Astrophysics Data System (ADS)

Samanta, Nirnay; Das Mahanta, Debasish; Choudhury, Samiran; Barman, Anjan; Kumar Mitra, Rajib

2017-03-01

A detailed understanding of hydration of amino acids, the building units of protein, is a key step to realize the overall solvation processes in proteins. In the present contribution, we have made a combined GHz (0.2-50) to THz (0.3-2.0) experimental spectroscopic study to investigate the dynamics of water at room temperature in the presence of different amino acids (glycine, L-serine, L-lysine, L-tryptophan, L-arginine, and L-aspartic acid). The THz absorption coefficient, α(ν), of amino acids follows a trend defined by their solvent accessible surface area. The imaginary and real dielectric constants obtained in GHz and THz regions are fitted into multiple Debye model to obtain various relaxation times. The ˜100 ps time scale obtained in the GHz frequency region is attributed to the rotational motion of the amino acids. In the THz region, we obtain ˜8 ps and ˜200 fs time scales which are related to the cooperative dynamics of H-bond network and partial rotation or sudden jump of the under-coordinated water molecules. These time scales are found to be dependent on the amino acid type and the cooperative motion is found to be dependent on both the hydrophobic as well as the hydrophilic residue of amino acids.

Multiscale structure of time series revealed by the monotony spectrum.

PubMed

Vamoş, Călin

2017-03-01

Observation of complex systems produces time series with specific dynamics at different time scales. The majority of the existing numerical methods for multiscale analysis first decompose the time series into several simpler components and the multiscale structure is given by the properties of their components. We present a numerical method which describes the multiscale structure of arbitrary time series without decomposing them. It is based on the monotony spectrum defined as the variation of the mean amplitude of the monotonic segments with respect to the mean local time scale during successive averagings of the time series, the local time scales being the durations of the monotonic segments. The maxima of the monotony spectrum indicate the time scales which dominate the variations of the time series. We show that the monotony spectrum can correctly analyze a diversity of artificial time series and can discriminate the existence of deterministic variations at large time scales from the random fluctuations. As an application we analyze the multifractal structure of some hydrological time series.

Molecular dynamics investigation of dynamical heterogeneity and local structure in the supercooled liquid and glass states of Al

NASA Astrophysics Data System (ADS)

Li, Maozhi; Wang, Cai-Zhuang; Mendelev, Mikhail I.; Ho, Kai-Ming

2008-05-01

Molecular dynamics simulations are performed to study the structure and dynamical heterogeneity in the liquid and glass states of Al using a frequently employed embedded atom potential. While the pair correlation function of the glass and liquid states displays only minor differences, the icosahedral short-range order (ISRO) and the dynamics of the two states are very different. The ISRO is much stronger in the glass than in the liquid. It is also found that both the most mobile and the most immobile atoms in the glass state tend to form clusters, and the clusters formed by the immobile atoms are more compact. In order to investigate the local environment of each atom in the liquid and glass states, a local density is defined to characterize the local atomic packing. There is a strong correlation between the local packing density and the mobility of the atoms. These results indicate that dynamical heterogeneity in glasses is directly correlated to the local structure. We also analyze the diffusion mechanisms of atoms in the liquid and glass states. It is found that for the mobile atoms in the glass state, initially they are confined in the cages formed by their nearest neighbors and vibrating. On the time scale of β relaxation, the mobile atoms try to break up the cage confinement and hop into new cages. In the supercooled liquid states, however, atoms continuously diffuse. Furthermore, it is found that on the time scale of β relaxation, some of the mobile atoms in the glass state cooperatively hop, which is facilitated by the stringlike cluster structures. On the longer time scale, it is found that a certain fraction of atoms can simultaneously hop, although they are not nearest neighbors. Further analysis shows that these hopping atoms form big and more compact clusters than the characterized most mobile atoms. The cooperative rearrangement of these big compact clusters might facilitate the simultaneous hopping of atoms in the glass states on the long time scale.

Large fluctuations in anti-coordination games on scale-free graphs

NASA Astrophysics Data System (ADS)

Sabsovich, Daniel; Mobilia, Mauro; Assaf, Michael

2017-05-01

We study the influence of the complex topology of scale-free graphs on the dynamics of anti-coordination games (e.g. snowdrift games). These reference models are characterized by the coexistence (evolutionary stable mixed strategy) of two competing species, say ‘cooperators’ and ‘defectors’, and, in finite systems, by metastability and large-fluctuation-driven fixation. In this work, we use extensive computer simulations and an effective diffusion approximation (in the weak selection limit) to determine under which circumstances, depending on the individual-based update rules, the topology drastically affects the long-time behavior of anti-coordination games. In particular, we compute the variance of the number of cooperators in the metastable state and the mean fixation time when the dynamics is implemented according to the voter model (death-first/birth-second process) and the link dynamics (birth/death or death/birth at random). For the voter update rule, we show that the scale-free topology effectively renormalizes the population size and as a result the statistics of observables depend on the network’s degree distribution. In contrast, such a renormalization does not occur with the link dynamics update rule and we recover the same behavior as on complete graphs.

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.

GPI-anchored protein organization and dynamics at the cell surface

PubMed Central

Saha, Suvrajit; Anilkumar, Anupama Ambika; Mayor, Satyajit

2016-01-01

The surface of eukaryotic cells is a multi-component fluid bilayer in which glycosylphosphatidylinositol (GPI)-anchored proteins are an abundant constituent. In this review, we discuss the complex nature of the organization and dynamics of GPI-anchored proteins at multiple spatial and temporal scales. Different biophysical techniques have been utilized for understanding this organization, including fluorescence correlation spectroscopy, fluorescence recovery after photobleaching, single particle tracking, and a number of super resolution methods. Major insights into the organization and dynamics have also come from exploring the short-range interactions of GPI-anchored proteins by fluorescence (or Förster) resonance energy transfer microscopy. Based on the nanometer to micron scale organization, at the microsecond to the second time scale dynamics, a picture of the membrane bilayer emerges where the lipid bilayer appears inextricably intertwined with the underlying dynamic cytoskeleton. These observations have prompted a revision of the current models of plasma membrane organization, and suggest an active actin-membrane composite. PMID:26394904

Introduction: demography and cultural macroevolution.

PubMed

Steele, James; Shennan, Stephen

2009-04-01

The papers in this special issue of Human Biology, which derive from a conference sponsored by the Arts and Humanities Research Council (AHRC) Center for the Evolution of Cultural Diversity, lay some of the foundations for an empirical macroevolutionary analysis of cultural dynamics. Our premise here is that cultural dynamics-including the stability of traditions and the rate of origination of new variants-are influenced by independently occurring demographic processes (population size, structure, and distribution as these vary over time as a result of changes in rates of fertility, mortality, and migration). The contributors focus on three sets of problems relevant to empirical studies of cultural macroevolution: large-scale reconstruction of past population dynamics from archaeological and genetic data; juxtaposition of models and evidence of cultural dynamics using large-scale archaeological and historical data sets; and juxtaposition of models and evidence of cultural dynamics from large-scale linguistic data sets. In this introduction we outline some of the theoretical and methodological issues and briefly summarize the individual contributions.

Investigation of Propellant Sloshing and Zero Gravity Equilibrium for the Orion Service Module Propellant Tanks

NASA Astrophysics Data System (ADS)

Kreppel, Samantha

A scaled model of the downstream Orion service module propellant tank was constructed to asses the propellant dynamics under reduced and zero-gravity conditions. Flight and ground data from the experiment is currently being used to validate computational models of propel-lant dynamics in Orion-class propellant tanks. The high fidelity model includes the internal structures of the propellant management device (PMD) and the mass-gauging probe. Qualita-tive differences between experimental and CFD data are understood in terms of fluid dynamical scaling of inertial effects in the scaled system. Propellant configurations in zero-gravity were studied at a range of fill-fractions and the settling time for various docking maneuvers was determined. A clear understanding of the fluid dynamics within the tank is necessary to en-sure proper control of the spacecraft's flight and to maintain safe operation of this and future service modules. Understanding slosh dynamics in partially-filled propellant tanks is essential to assessing spacecraft stability.

GPI-anchored protein organization and dynamics at the cell surface.

PubMed

Saha, Suvrajit; Anilkumar, Anupama Ambika; Mayor, Satyajit

2016-02-01

The surface of eukaryotic cells is a multi-component fluid bilayer in which glycosylphosphatidylinositol (GPI)-anchored proteins are an abundant constituent. In this review, we discuss the complex nature of the organization and dynamics of GPI-anchored proteins at multiple spatial and temporal scales. Different biophysical techniques have been utilized for understanding this organization, including fluorescence correlation spectroscopy, fluorescence recovery after photobleaching, single particle tracking, and a number of super resolution methods. Major insights into the organization and dynamics have also come from exploring the short-range interactions of GPI-anchored proteins by fluorescence (or Förster) resonance energy transfer microscopy. Based on the nanometer to micron scale organization, at the microsecond to the second time scale dynamics, a picture of the membrane bilayer emerges where the lipid bilayer appears inextricably intertwined with the underlying dynamic cytoskeleton. These observations have prompted a revision of the current models of plasma membrane organization, and suggest an active actin-membrane composite. Copyright © 2016 by the American Society for Biochemistry and Molecular Biology, Inc.

A fault diagnosis scheme for planetary gearboxes using modified multi-scale symbolic dynamic entropy and mRMR feature selection

NASA Astrophysics Data System (ADS)

Li, Yongbo; Yang, Yuantao; Li, Guoyan; Xu, Minqiang; Huang, Wenhu

2017-07-01

Health condition identification of planetary gearboxes is crucial to reduce the downtime and maximize productivity. This paper aims to develop a novel fault diagnosis method based on modified multi-scale symbolic dynamic entropy (MMSDE) and minimum redundancy maximum relevance (mRMR) to identify the different health conditions of planetary gearbox. MMSDE is proposed to quantify the regularity of time series, which can assess the dynamical characteristics over a range of scales. MMSDE has obvious advantages in the detection of dynamical changes and computation efficiency. Then, the mRMR approach is introduced to refine the fault features. Lastly, the obtained new features are fed into the least square support vector machine (LSSVM) to complete the fault pattern identification. The proposed method is numerically and experimentally demonstrated to be able to recognize the different fault types of planetary gearboxes.

Space and time renormalization in phase transition dynamics

DOE PAGES

Francuz, Anna; Dziarmaga, Jacek; Gardas, Bartłomiej; ...

2016-02-18

Here, when a system is driven across a quantum critical point at a constant rate, its evolution must become nonadiabatic as the relaxation time τ diverges at the critical point. According to the Kibble-Zurek mechanism (KZM), the emerging post-transition excited state is characterized by a finite correlation length ξˆ set at the time tˆ=τˆ when the critical slowing down makes it impossible for the system to relax to the equilibrium defined by changing parameters. This observation naturally suggests a dynamical scaling similar to renormalization familiar from the equilibrium critical phenomena. We provide evidence for such KZM-inspired spatiotemporal scaling by investigatingmore » an exact solution of the transverse field quantum Ising chain in the thermodynamic limit.« less

Simulations of fluorescence solvatochromism in substituted PPV oligomers from excited state molecular dynamics with implicit solvent

DOE PAGES

Bjorgaard, J. A.; Nelson, T.; Kalinin, K.; ...

2015-04-28

In this study, an efficient method of treating solvent effects in excited state molecular dynamics (ESMD) is implemented and tested by exploring the solvatochromic effects in substituted p-phenylene vinylene oligomers. A continuum solvent model is used which has very little computational overhead. This allows simulations of ESMD with solvent effects on the scale of hundreds of picoseconds for systems of up to hundreds of atoms. At these time scales, solvatochromic shifts in fluoresence spectra can be described. Solvatochromic shifts in absorption and fluorescence spectra from ESMD are compared with time-dependent density functional theory calculations and experiments.

Dynamics of a linear system coupled to a chain of light nonlinear oscillators analyzed through a continuous approximation

NASA Astrophysics Data System (ADS)

Charlemagne, S.; Ture Savadkoohi, A.; Lamarque, C.-H.

2018-07-01

The continuous approximation is used in this work to describe the dynamics of a nonlinear chain of light oscillators coupled to a linear main system. A general methodology is applied to an example where the chain has local nonlinear restoring forces. The slow invariant manifold is detected at fast time scale. At slow time scale, equilibrium and singular points are sought around this manifold in order to predict periodic regimes and strongly modulated responses of the system. Analytical predictions are in good accordance with numerical results and represent a potent tool for designing nonlinear chains for passive control purposes.

The influence of cosmic rays on the stability and large-scale dynamics of the interstellar medium

NASA Astrophysics Data System (ADS)

Kuznetsov, V. D.

1986-06-01

The diffusion-convection formulation is used to study the influence of galactic cosmic rays on the stability and dynamics of the interstellar medium which is supposedly kept in equilibrium by the gravitational field of stars. It is shown that the influence of cosmic rays on the growth rate of MHD instability depends largely on a dimensionless parameter expressing the ratio of the characteristic acoustic time scale to the cosmic-ray diffusion time. If this parameter is small, the cosmic rays will decelerate the build-up of instabilities, thereby stabilizing the system; in contrast, if the parameter is large, the system will be destabilized.

Plasticity-mediated collapse and recrystallization in hollow copper nanowires: a molecular dynamics simulation.

PubMed

Dutta, Amlan; Raychaudhuri, Arup Kumar; Saha-Dasgupta, Tanusri

2016-01-01

We study the thermal stability of hollow copper nanowires using molecular dynamics simulation. We find that the plasticity-mediated structural evolution leads to transformation of the initial hollow structure to a solid wire. The process involves three distinct stages, namely, collapse, recrystallization and slow recovery. We calculate the time scales associated with different stages of the evolution process. Our findings suggest a plasticity-mediated mechanism of collapse and recrystallization. This contradicts the prevailing notion of diffusion driven transport of vacancies from the interior to outer surface being responsible for collapse, which would involve much longer time scales as compared to the plasticity-based mechanism.

Conjugate-Gradient Algorithms For Dynamics Of Manipulators

NASA Technical Reports Server (NTRS)

Fijany, Amir; Scheid, Robert E.

1993-01-01

Algorithms for serial and parallel computation of forward dynamics of multiple-link robotic manipulators by conjugate-gradient method developed. Parallel algorithms have potential for speedup of computations on multiple linked, specialized processors implemented in very-large-scale integrated circuits. Such processors used to stimulate dynamics, possibly faster than in real time, for purposes of planning and control.

Complex Processes from Dynamical Architectures with Time-Scale Hierarchy

PubMed Central

Perdikis, Dionysios; Huys, Raoul; Jirsa, Viktor

2011-01-01

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

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

Gur, Sourav; Frantziskonis, George N.; Univ. of Arizona, Tucson, AZ

Here, we report results from a numerical study of multi-time-scale bistable dynamics for CO oxidation on a catalytic surface in a flowing, well-mixed gas stream. The problem is posed in terms of surface and gas-phase submodels that dynamically interact in the presence of stochastic perturbations, reflecting the impact of molecular-scale fluctuations on the surface and turbulence in the gas. Wavelet-based methods are used to encode and characterize the temporal dynamics produced by each submodel and detect the onset of sudden state shifts (bifurcations) caused by nonlinear kinetics. When impending state shifts are detected, a more accurate but computationally expensive integrationmore » scheme can be used. This appears to make it possible, at least in some cases, to decrease the net computational burden associated with simulating multi-time-scale, nonlinear reacting systems by limiting the amount of time in which the more expensive integration schemes are required. Critical to achieving this is being able to detect unstable temporal transitions such as the bistable shifts in the example problem considered here. Lastly, our results indicate that a unique wavelet-based algorithm based on the Lipschitz exponent is capable of making such detections, even under noisy conditions, and may find applications in critical transition detection problems beyond catalysis.« less

Testing the paradigms of the glass transition in colloids

NASA Astrophysics Data System (ADS)

Zia, Roseanna; Wang, Jialun; Peng, Xiaoguang; Li, Qi; McKenna, Gregory

2017-11-01

Many molecular liquids freeze upon fast enough cooling. This so-called glass state is path dependent and out of equilibrium, as measured by the Kovacs signature experiments, i.e. intrinsic isotherms, asymmetry of approach and memory effect. The reasons for this path- and time-dependence are not fully understood, due to fast molecular relaxations. Colloids provide a natural way to model such behavior, owing to disparity in colloidal versus solvent time scales that can slow dynamics. To shed light on the ambiguity of glass transition, we study via large-scale dynamic simulation of hard-sphere colloidal glass after volume-fraction jumps, where particle size increases at fixed system volume followed by protocols of the McKenna-Kovacs signature experiments. During and following each jump, the positions, velocities, and particle-phase stress are tracked and utilized to characterize relaxation time scales. The impact of both quench depth and quench rate on arrested dynamics and ``state'' variables is explored. In addition, we expand our view to various structural signatures, and rearrangement mechanism is proposed. The results provide insight into not only the existence of an ``ideal'' glass transition, but also the role of structure in such a dense amorphous system.

Scaling and design of landslide and debris-flow experiments

USGS Publications Warehouse

Iverson, Richard M.

2015-01-01

Scaling plays a crucial role in designing experiments aimed at understanding the behavior of landslides, debris flows, and other geomorphic phenomena involving grain-fluid mixtures. Scaling can be addressed by using dimensional analysis or – more rigorously – by normalizing differential equations that describe the evolving dynamics of the system. Both of these approaches show that, relative to full-scale natural events, miniaturized landslides and debris flows exhibit disproportionately large effects of viscous shear resistance and cohesion as well as disproportionately small effects of excess pore-fluid pressure that is generated by debris dilation or contraction. This behavioral divergence grows in proportion to H3, where H is the thickness of a moving mass. Therefore, to maximize geomorphological relevance, experiments with wet landslides and debris flows must be conducted at the largest feasible scales. Another important consideration is that, unlike stream flows, landslides and debris flows accelerate from statically balanced initial states. Thus, no characteristic macroscopic velocity exists to guide experiment scaling and design. On the other hand, macroscopic gravity-driven motion of landslides and debris flows evolves over a characteristic time scale (L/g)1/2, where g is the magnitude of gravitational acceleration and L is the characteristic length of the moving mass. Grain-scale stress generation within the mass occurs on a shorter time scale, H/(gL)1/2, which is inversely proportional to the depth-averaged material shear rate. A separation of these two time scales exists if the criterion H/L < < 1 is satisfied, as is commonly the case. This time scale separation indicates that steady-state experiments can be used to study some details of landslide and debris-flow behavior but cannot be used to study macroscopic landslide or debris-flow dynamics.

MO-G-BRF-06: Radiotherapy and Prompt Oxygen Dynamics

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

Kissick, M; Campos, D; Adamson, E

Purpose: Adaptive radiotherapy requires a knowledge of the changing local tumor oxygen concentrations for times on the order of the treatment time, a time scale far shorter than cell death and proliferation. This knowledge will be needed to guide hypofractionated radiotherapy. Methods: A diffuse optical probe system was developed to spatially average over the whole interior of athymic Sprague Dawley nude mouse xenografts of human head and neck cancers. The blood volume and hemoglobin saturation was measured in real time. The quantities were measured with spectral fitting before and after 10 Gy of radiation is applied. An MRI BOLD scanmore » is acquired before and after 10 Gy that measures regional changes in R2* which is inversely proportional to oxygen availability. Simulations were performed to fit the blood oxygen dynamics and infer changes in hypoxia within the tumor. Results: The optical probe measured nearly constant blood volume and a significant drop in hemoglobin saturation of about 30% after 10 Gy over the time scale of less than 30 minutes. The averaged R2* within the tumor volume increased by 15% after the 10 Gy dose, which is consistent with the optical results. The simulations and experiments support likely dynamic metabolic changes and/or fast vasoconstrictive signals are occurring that change the oxygen concentrations significantly, but not cell death or proliferation. Conclusion: Significant oxygen changes were observed to occur within 30 minutes, coinciding with the treatment time scale. This dynamic is very important for patient specific adaptive therapy. For hypofractionated therapy, the local instantaneous oxygen content is likely the most important variable to control. The invention of a bedside device for the purpose of measuring the instantaneous response to large radiation doses would be an important step to future improvements in outcome.« less

Scale-dependent temporal variations in stream water geochemistry.

PubMed

Nagorski, Sonia A; Moore, Iohnnie N; McKinnon, Temple E; Smith, David B

2003-03-01

A year-long study of four western Montana streams (two impacted by mining and two "pristine") evaluated surface water geochemical dynamics on various time scales (monthly, daily, and bi-hourly). Monthly changes were dominated by snowmelt and precipitation dynamics. On the daily scale, post-rain surges in some solute and particulate concentrations were similar to those of early spring runoff flushing characteristics on the monthly scale. On the bi-hourly scale, we observed diel (diurnal-nocturnal) cycling for pH, dissolved oxygen, water temperature, dissolved inorganic carbon, total suspended sediment, and some total recoverable metals at some or all sites. A comparison of the cumulative geochemical variability within each of the temporal groups reveals that for many water quality parameters there were large overlaps of concentration ranges among groups. We found that short-term (daily and bi-hourly) variations of some geochemical parameters covered large proportions of the variations found on a much longer term (monthly) time scale. These results show the importance of nesting short-term studies within long-term geochemical study designs to separate signals of environmental change from natural variability.

Scale-dependent temporal variations in stream water geochemistry

USGS Publications Warehouse

Nagorski, S.A.; Moore, J.N.; McKinnon, Temple E.; Smith, D.B.

2003-01-01

A year-long study of four western Montana streams (two impacted by mining and two "pristine") evaluated surface water geochemical dynamics on various time scales (monthly, daily, and bi-hourly). Monthly changes were dominated by snowmelt and precipitation dynamics. On the daily scale, post-rain surges in some solute and particulate concentrations were similar to those of early spring runoff flushing characteristics on the monthly scale. On the bi-hourly scale, we observed diel (diurnal-nocturnal) cycling for pH, dissolved oxygen, water temperature, dissolved inorganic carbon, total suspended sediment, and some total recoverable metals at some or all sites. A comparison of the cumulative geochemical variability within each of the temporal groups reveals that for many water quality parameters there were large overlaps of concentration ranges among groups. We found that short-term (daily and bi-hourly) variations of some geochemical parameters covered large proportions of the variations found on a much longer term (monthly) time scale. These results show the importance of nesting short-term studies within long-term geochemical study designs to separate signals of environmental change from natural variability.

On the scaling features of high-latitude geomagnetic field fluctuations during a large geomagnetic storm

NASA Astrophysics Data System (ADS)

De Michelis, Paola; Federica Marcucci, Maria; Consolini, Giuseppe

2015-04-01

Recently we have investigated the spatial distribution of the scaling features of short-time scale magnetic field fluctuations using measurements from several ground-based geomagnetic observatories distributed in the northern hemisphere. We have found that the scaling features of fluctuations of the horizontal magnetic field component at time scales below 100 minutes are correlated with the geomagnetic activity level and with changes in the currents flowing in the ionosphere. Here, we present a detailed analysis of the dynamical changes of the magnetic field scaling features as a function of the geomagnetic activity level during the well-known large geomagnetic storm occurred on July, 15, 2000 (the Bastille event). The observed dynamical changes are discussed in relationship with the changes of the overall ionospheric polar convection and potential structure as reconstructed using SuperDARN data. This work is supported by the Italian National Program for Antarctic Research (PNRA) - Research Project 2013/AC3.08 and by the European Community's Seventh Framework Programme ([FP7/2007-2013]) under Grant no. 313038/STORM and

Electron-phonon thermalization in a scalable method for real-time quantum dynamics

DOE PAGES

Rizzi, Valerio; Todorov, Tchavdar N.; Kohanoff, Jorge J.; ...

2016-01-27

Here, we present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicitmore » quantum dynamics.« less

Theory of dynamic barriers, activated hopping, and the glass transition in polymer melts

NASA Astrophysics Data System (ADS)

Schweizer, Kenneth S.; Saltzman, Erica J.

2004-07-01

A statistical mechanical theory of collective dynamic barriers, slow segmental relaxation, and the glass transition of polymer melts is developed by combining, and in some aspects extending, methods of mode coupling, density functional, and activated hopping transport theories. A coarse-grained description of polymer chains is adopted and the melt is treated as a liquid of segments. The theory is built on the idea that collective density fluctuations on length scales considerably longer than the local cage scale are of primary importance in the deeply supercooled regime. The barrier hopping or segmental relaxation time is predicted to be a function primarily of a single parameter that is chemical structure, temperature, and pressure dependent. This parameter depends on the material-specific dimensionless amplitude of thermal density fluctuations (compressibility) and a reduced segmental density determined by the packing length and backbone characteristic ratio. Analytic results are derived for a crossover temperature Tc, collective barrier, and glass transition temperature Tg. The relation of these quantities to structural and thermodynamic properties of the polymer melt is established. A universal power-law scaling behavior of the relaxation time below Tc is predicted based on identification of a reduced temperature variable that quantifies the breadth of the supercooled regime. Connections between the ratio Tc/Tg, two measures of dynamic fragility, and the magnitude of the local relaxation time at Tg logically follow. Excellent agreement with experiment is found for these generic aspects, and the crucial importance of the experimentally observed near universality of the dynamic crossover time is established. Extensions of the theory to treat the full chain dynamics, heterogeneity, barrier fluctuations, and nonpolymeric thermal glass forming liquids are briefly discussed.

Foraminifera Record the Good Years More than the Bad

NASA Astrophysics Data System (ADS)

Hull, P. M.

2014-12-01

Past ocean conditions are primarily discerned from geochemical and community-based analyses of fossilized taxa, each of which have unique environmental niches and dynamics. A key requirement of such paleoceanographic studies is that some unbiased or well-constrained record of the living ecosystem and climate is deposited on the sea floor and preserved through the post-depositional processes that act to distort them. It is widely known that foraminiferal species exhibit varying seasonal preferences and that seasonality is a key variable to account for in paleoceanographic reconstructions. However, on longer time scales (> year), it is generally assumed that species record the 'average' environmental conditions or typical variance (e.g., El Nino intensity) that existed in a given, time-averaged sediment sample. Here I examine planktonic foraminiferal population dynamics on yearly and longer time scales, in order to quantify their effect on paleoceanographic reconstructions. Using a previously published record of >250 years of population dynamics in the Santa Barbara Basin sediments, I find that the majority of individuals in a given species lived during a small subset of the total years (~15- 37% of years depending on the species). Populations of shallow, mixed layer species primarily represent the warmest, youngest years, while thermocline species primarily represent the cooler, older years. Importantly, the seasonality of species does not always predict their interannual dynamics. The general importance of long time-scale population dynamics on paleoceanographic reconstructions will also be considered in a theoretical model parameterized with temporally explicit species co-variances and temperature variability. Such modeling is needed to constrain the relative impact that a very good year can have on our interpretation of the 'average' of hundreds to thousands of years.

Circadian clock and cardiac vulnerability: A time stamp on multi-scale neuroautonomic regulation

NASA Astrophysics Data System (ADS)

Ivanov, Plamen Ch.

2005-03-01

Cardiovascular vulnerability displays a 24-hour pattern with a peak between 9AM and 11AM. This daily pattern in cardiac risk is traditionally attributed to external factors including activity levels and sleep-wake cycles. However,influences from the endogenous circadian pacemaker independent from behaviors may also affect cardiac control. We investigate heartbeat dynamics in healthy subjects recorded throughout a 10-day protocol wherein the sleep/wake and behavior cycles are desynchronized from the endogenous circadian cycle,enabling assessment of circadian factors while controlling for behavior-related factors. We demonstrate that the scaling exponent characterizing temporal correlations in heartbeat dynamics over multiple time scales does exhibit a significant circadian rhythm with a sharp peak at the circadian phase corresponding to the period 9-11AM, and that this rhythm is independent from scheduled behaviors and mean heart rate. Our findings of strong circadian rhythms in the multi-scale heartbeat dynamics of healthy young subjects indicate that the underlying mechanism of cardiac regulation is strongly influenced by the endogenous circadian pacemaker. A similar circadian effect in vulnerable individuals with underlying cardiovascular disease would contribute to the morning peak of adverse cardiac events observed in epidemiological studies.

Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics

NASA Astrophysics Data System (ADS)

Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L.

2018-02-01

Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.

Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics.

PubMed

Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L

2018-02-07

Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.

Rupture dynamics along bimaterial interfaces: a parametric study of the coupling between interfacial sliding and normal traction perturbation

NASA Astrophysics Data System (ADS)

Scala, Antonio; Festa, Gaetano; Vilotte, Jean-Pierre

2017-04-01

Earthquake ruptures often develop along faults separating materials with dissimilar elastic properties. Due to the broken symmetry, the propagation of the rupture along the bimaterial interface is driven by the coupling between interfacial sliding and normal traction perturbations. We numerically investigate in-plane rupture growth along a planar interface, under slip weakening friction, separating two dissimilar isotropic linearly elastic half-spaces. We perform a parametric study of the classical Prakash-Clifton regularisation for different material contrasts. In particular mesh-dependence and regularisation-dependence of the numerical solutions are analysed in this parameter space. When regularisation involves a slip-rate dependent relaxation time, a characteristic sliding distance is identified below which numerical solutions no longer depend on the regularisation parameter, i.e. they are consistent solutions of the same physical problem. Such regularisation provides an adaptive high-frequency filter of the slip-induced normal traction perturbations, following the dynamic shrinking of the dissipation zone during the acceleration phase. In contrast, regularisation involving a constant relaxation time leads to numerical solutions that always depend on the regularisation parameter since it fails adapting to the shrinking of the process zone. Dynamic regularisation is further investigated using a non-local regularisation based on a relaxation time that depends on the dynamic length of the dissipation zone. Such reformulation is shown to provide similar results as the dynamic time scale regularisation proposed by Prakash-Clifton when slip rate is replaced by the maximum slip rate along the sliding interface. This leads to the identification of a dissipative length scale associated with the coupling between interfacial sliding and normal traction perturbations, together with a scaling law between the maximum slip rate and the dynamic size of the process zone during the rupture propagation. Dynamic time scale regularisation is show to provide mesh-independent and physically well-posed numerical solutions during the acceleration phase toward an asymptotic speed. When generalised Rayleigh wave does not exist, numerical solutions are shown to tend toward an asymptotic velocity higher than the slowest shear wave speed. When generalised Rayleigh wave speed exists, as numerical solutions tend toward this velocity, increasing spurious oscillations develop and solutions become unstable. In this regime regularisation dependent and unstable finite-size pulses may be generated. This instability is associated with the singular behaviour of the slip-induced normal traction perturbations, and of the slip rate at the rupture front, in relation with complete shrinking of the dissipation zone. This phase requires to be modelled either by more complex interface constitutive laws involving velocity-strengthening effects that may stabilize short wavelength interfacial propagating modes or by considering non-ideal interfaces that introduce a new length scale in the problem that may promote selection and stabilization of the slip pulses.

Space Technology 5 Multipoint Observations of Temporal and Spatial Variability of Field-Aligned Currents

NASA Technical Reports Server (NTRS)

Le, G.; Wang, Y.; Slavin, J. A.; Strangeway, R. L.

2009-01-01

Space Technology 5 (ST5) is a constellation mission consisting of three microsatellites. It provides the first multipoint magnetic field measurements in low Earth orbit, which enables us to separate spatial and temporal variations. In this paper, we present a study of the temporal variability of field-aligned currents using the ST5 data. We examine the field-aligned current observations during and after a geomagnetic storm and compare the magnetic field profiles at the three spacecraft. The multipoint data demonstrate that mesoscale current structures, commonly embedded within large-scale current sheets, are very dynamic with highly variable current density and/or polarity in approx.10 min time scales. On the other hand, the data also show that the time scales for the currents to be relatively stable are approx.1 min for mesoscale currents and approx.10 min for large-scale currents. These temporal features are very likely associated with dynamic variations of their charge carriers (mainly electrons) as they respond to the variations of the parallel electric field in auroral acceleration region. The characteristic time scales for the temporal variability of mesoscale field-aligned currents are found to be consistent with those of auroral parallel electric field.

Sediment dynamics over multiple time scales in Dyke Marsh Preserve (Potomac River, VA)

NASA Astrophysics Data System (ADS)

Palinkas, C. M.; Walters, D.

2010-12-01

Tidal freshwater marshes are critical components of fluvial and estuarine ecosystems, yet sediment dynamics within them have not received as much attention as their saltwater counterparts. This study examines sedimentation in Dyke Marsh Preserve, located on the Potomac River (VA), focusing on understanding the spatial variability present over multiple time scales. Bimonthly sediment data were collected using ceramic tiles, and seasonal- and decadal-scale sedimentation was determined via 7Be (half-life 53.3 days) and 210Pb (half-life 22.3 years), respectively. Results were also compared to SET data collected by the National Park Service since 2006. Preliminary data indicate that sites at lower elevations have higher sedimentation rates, likely related to their close proximity to the sediment source. Mass accumulation rates generally decreased with increasing time scale, such that the seasonal rates were greater than the SET-derived accretion rates, which were in turn greater than the decadal-scale rates. However, the bimonthly rates were the lowest observed, probably because the sampling period (May-October 2010) did not include the main depositional period of the year, which would be integrated by the other techniques.

Chaotic dynamics of large-scale double-diffusive convection in a porous medium

NASA Astrophysics Data System (ADS)

Kondo, Shutaro; Gotoda, Hiroshi; Miyano, Takaya; Tokuda, Isao T.

2018-02-01

We have studied chaotic dynamics of large-scale double-diffusive convection of a viscoelastic fluid in a porous medium from the viewpoint of dynamical systems theory. A fifth-order nonlinear dynamical system modeling the double-diffusive convection is theoretically obtained by incorporating the Darcy-Brinkman equation into transport equations through a physical dimensionless parameter representing porosity. We clearly show that the chaotic convective motion becomes much more complicated with increasing porosity. The degree of dynamic instability during chaotic convective motion is quantified by two important measures: the network entropy of the degree distribution in the horizontal visibility graph and the Kaplan-Yorke dimension in terms of Lyapunov exponents. We also present an interesting on-off intermittent phenomenon in the probability distribution of time intervals exhibiting nearly complete synchronization.

Dynamic Structure of a Molecular Liquid S0.5Cl0.5: Ab initio Molecular-Dynamics Simulations

NASA Astrophysics Data System (ADS)

Ohmura, Satoshi; Shimakura, Hironori; Kawakita, Yukinobu; Shimojo, Fuyuki; Yao, Makoto

2013-07-01

The static and dynamic structures of a molecular liquid S0.5Cl0.5 consisting of Cl--S--S--Cl (S2Cl2) type molecules are studied by means of ab initio molecular dynamics simulations. Both the calculated static and dynamic structure factors are in good agreement with experimental results. The dynamic structures are discussed based on van-Hove distinct correlation functions, molecular translational mean-square displacements (TMSD) and rotational mean-square displacements (RMSD). In the TMSD and RMSD, there are ballistic and diffusive regimes in the sub-picosecond and picosecond time regions, respectively. These time scales are consistent with the decay time observed experimentally. The interaction between molecules in the liquid is also discussed in comparison with that in another liquid chalcogen--halogen system Se0.5Cl0.5.

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

DOE PAGES

Lu, Ping; Yuan, Ren Liang; Ihlefeld, Jon F.; ...

2016-03-04

Chemical imaging at the atomic-scale provides a useful real-space approach to chemically investigate solid crystal structures, and has been recently demonstrated in aberration corrected scanning transmission electron microscopy (STEM). Atomic-scale chemical imaging by STEM using energy-dispersive X-ray spectroscopy (EDS) offers easy data interpretation with a one-to-one correspondence between image and structure but has a severe shortcoming due to the poor efficiency of X-ray generation and collection. As a result, it requires a long acquisition time of typical > few 100 seconds, limiting its potential applications. Here we describe the development of an atomic-scale STEM EDS chemical imaging technique that cutsmore » the acquisition time to one or a few seconds, efficiently reducing the acquisition time by more than 100 times. This method was demonstrated using LaAlO 3 (LAO) as a model crystal. Applying this method to the study of phase transformation induced by electron-beam radiation in a layered lithium transition-metal (TM) oxide, i.e., Li[Li 0.2Ni 0.2Mn 0.6]O 2 (LNMO), a cathode materials for lithium-ion batteries, we obtained a time-series of the atomic-scale chemical imaging, showing the transformation progressing by preferably jumping of Ni atoms from the TM layers into the Li-layers. The new capability offers an opportunity for temporal, atomic-scale chemical mapping of crystal structures for the investigation of materials susceptible to electron irradiation as well as phase transformation and dynamics at the atomic-scale.« less

Naming games in two-dimensional and small-world-connected random geometric networks.

PubMed

Lu, Qiming; Korniss, G; Szymanski, B K

2008-01-01

We investigate a prototypical agent-based model, the naming game, on two-dimensional random geometric networks. The naming game [Baronchelli, J. Stat. Mech.: Theory Exp. (2006) P06014] is a minimal model, employing local communications that captures the emergence of shared communication schemes (languages) in a population of autonomous semiotic agents. Implementing the naming games with local broadcasts on random geometric graphs, serves as a model for agreement dynamics in large-scale, autonomously operating wireless sensor networks. Further, it captures essential features of the scaling properties of the agreement process for spatially embedded autonomous agents. Among the relevant observables capturing the temporal properties of the agreement process, we investigate the cluster-size distribution and the distribution of the agreement times, both exhibiting dynamic scaling. We also present results for the case when a small density of long-range communication links are added on top of the random geometric graph, resulting in a "small-world"-like network and yielding a significantly reduced time to reach global agreement. We construct a finite-size scaling analysis for the agreement times in this case.

A Constructive Mean-Field Analysis of Multi-Population Neural Networks with Random Synaptic Weights and Stochastic Inputs

PubMed Central

Faugeras, Olivier; Touboul, Jonathan; Cessac, Bruno

2008-01-01

We deal with the problem of bridging the gap between two scales in neuronal modeling. At the first (microscopic) scale, neurons are considered individually and their behavior described by stochastic differential equations that govern the time variations of their membrane potentials. They are coupled by synaptic connections acting on their resulting activity, a nonlinear function of their membrane potential. At the second (mesoscopic) scale, interacting populations of neurons are described individually by similar equations. The equations describing the dynamical and the stationary mean-field behaviors are considered as functional equations on a set of stochastic processes. Using this new point of view allows us to prove that these equations are well-posed on any finite time interval and to provide a constructive method for effectively computing their unique solution. This method is proved to converge to the unique solution and we characterize its complexity and convergence rate. We also provide partial results for the stationary problem on infinite time intervals. These results shed some new light on such neural mass models as the one of Jansen and Rit (1995): their dynamics appears as a coarse approximation of the much richer dynamics that emerges from our analysis. Our numerical experiments confirm that the framework we propose and the numerical methods we derive from it provide a new and powerful tool for the exploration of neural behaviors at different scales. PMID:19255631

Dynamical quantum phase transitions in extended transverse Ising models

NASA Astrophysics Data System (ADS)

Bhattacharjee, Sourav; Dutta, Amit

2018-04-01

We study the dynamical quantum phase transitions (DQPTs) manifested in the subsequent unitary dynamics of an extended Ising model with an additional three spin interactions following a sudden quench. Revisiting the equilibrium phase diagram of the model, where different quantum phases are characterized by different winding numbers, we show that in some situations the winding number may not change across a gap closing point in the energy spectrum. Although, usually there exists a one-to-one correspondence between the change in winding number and the number of critical time scales associated with DQPTs, we show that the extended nature of interactions may lead to unusual situations. Importantly, we show that in the limit of the cluster Ising model, three critical modes associated with DQPTs become degenerate, thereby leading to a single critical time scale for a given sector of Fisher zeros.

Statistical mechanical approach to secondary processes and structural relaxation in glasses and glass formers: a leading model to describe the onset of Johari-Goldstein processes and their relationship with fully cooperative processes.

PubMed

Crisanti, A; Leuzzi, L; Paoluzzi, M

2011-09-01

The interrelation of dynamic processes active on separated time-scales in glasses and viscous liquids is investigated using a model displaying two time-scale bifurcations both between fast and secondary relaxation and between secondary and structural relaxation. The study of the dynamics allows for predictions on the system relaxation above the temperature of dynamic arrest in the mean-field approximation, that are compared with the outcomes of the equations of motion directly derived within the Mode Coupling Theory (MCT) for under-cooled viscous liquids. By varying the external thermodynamic parameters, a wide range of phenomenology can be represented, from a very clear separation of structural and secondary peak in the susceptibility loss to excess wing structures.

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 Fermi-Pasta-Ulam Problem and Its Underlying Integrable Dynamics

NASA Astrophysics Data System (ADS)

Benettin, G.; Christodoulidi, H.; Ponno, A.

2013-07-01

This paper is devoted to a numerical study of the familiar α+ β FPU model. Precisely, we here discuss, revisit and combine together two main ideas on the subject: (i) In the system, at small specific energy ɛ= E/ N, two well separated time-scales are present: in the former one a kind of metastable state is produced, while in the second much larger one, such an intermediate state evolves and reaches statistical equilibrium. (ii) FPU should be interpreted as a perturbed Toda model, rather than (as is typical) as a linear model perturbed by nonlinear terms. In the view we here present and support, the former time scale is the one in which FPU is essentially integrable, its dynamics being almost indistinguishable from the Toda dynamics: the Toda actions stay constant for FPU too (while the usual linear normal modes do not), the angles fill their almost invariant torus, and nothing else happens. The second time scale is instead the one in which the Toda actions significantly evolve, and statistical equilibrium is possible. We study both FPU-like initial states, in which only a few degrees of freedom are excited, and generic initial states extracted randomly from an (approximated) microcanonical distribution. The study is based on a close comparison between the behavior of FPU and Toda in various situations. The main technical novelty is the study of the correlation functions of the Toda constants of motion in the FPU dynamics; such a study allows us to provide a good definition of the equilibrium time τ, i.e. of the second time scale, for generic initial data. Our investigation shows that τ is stable in the thermodynamic limit, i.e. the limit of large N at fixed ɛ, and that by reducing ɛ (ideally, the temperature), τ approximately grows following a power law τ˜ ɛ - a , with a=5/2.

The impact of wave number selection and spin up time when using spectral nudging for dynamical downscaling applications

NASA Astrophysics Data System (ADS)

Gómez, Breogán; Miguez-Macho, Gonzalo

2017-04-01

Nudging techniques are commonly used to constrain the evolution of numerical models to a reference dataset that is typically of a lower resolution. The nudged model retains some of the features of the reference field while incorporating its own dynamics to the solution. These characteristics have made nudging very popular in dynamic downscaling applications that cover from shot range, single case studies, to multi-decadal regional climate simulations. Recently, a variation of this approach called Spectral Nudging, has gained popularity for its ability to maintain the higher temporal and spatial variability of the model results, while forcing the large scales in the solution with a coarser resolution field. In this work, we focus on a not much explored aspect of this technique: the impact of selecting different cut-off wave numbers and spin-up times. We perform four-day long simulations with the WRF model, daily for three different one-month periods that include a free run and several Spectral Nudging experiments with cut-off wave numbers ranging from the smallest to the largest possible (full Grid Nudging). Results show that Spectral Nudging is very effective at imposing the selected scales onto the solution, while allowing the limited area model to incorporate finer scale features. The model error diminishes rapidly as the nudging expands over broader parts of the spectrum, but this decreasing trend ceases sharply at cut-off wave numbers equivalent to a length scale of about 1000 km, and the error magnitude changes minimally thereafter. This scale corresponds to the Rossby Radius of deformation, separating synoptic from convective scales in the flow. When nudging above this value is applied, a shifting of the synoptic patterns can occur in the solution, yielding large model errors. However, when selecting smaller scales, the fine scale contribution of the model is damped, thus making 1000 km the appropriate scale threshold to nudge in order to balance both effects. Finally, we note that longer spin-up times are needed for model errors to stabilize when using Spectral Nudging than with Grid Nudging. Our results suggest that this time is between 36 and 48 hours.

A stochastic fractional dynamics model of space-time variability of rain

NASA Astrophysics Data System (ADS)

Kundu, Prasun K.; Travis, James E.

2013-09-01

varies in space and time in a highly irregular manner and is described naturally in terms of a stochastic process. A characteristic feature of rainfall statistics is that they depend strongly on the space-time scales over which rain data are averaged. A spectral model of precipitation has been developed based on a stochastic differential equation of fractional order for the point rain rate, which allows a concise description of the second moment statistics of rain at any prescribed space-time averaging scale. The model is thus capable of providing a unified description of the statistics of both radar and rain gauge data. The underlying dynamical equation can be expressed in terms of space-time derivatives of fractional orders that are adjusted together with other model parameters to fit the data. The form of the resulting spectrum gives the model adequate flexibility to capture the subtle interplay between the spatial and temporal scales of variability of rain but strongly constrains the predicted statistical behavior as a function of the averaging length and time scales. We test the model with radar and gauge data collected contemporaneously at the NASA TRMM ground validation sites located near Melbourne, Florida and on the Kwajalein Atoll, Marshall Islands in the tropical Pacific. We estimate the parameters by tuning them to fit the second moment statistics of radar data at the smaller spatiotemporal scales. The model predictions are then found to fit the second moment statistics of the gauge data reasonably well at these scales without any further adjustment.

Nonlinear and Stochastic Dynamics in the Heart

PubMed Central

Qu, Zhilin; Hu, Gang; Garfinkel, Alan; Weiss, James N.

2014-01-01

In a normal human life span, the heart beats about 2 to 3 billion times. Under diseased conditions, a heart may lose its normal rhythm and degenerate suddenly into much faster and irregular rhythms, called arrhythmias, which may lead to sudden death. The transition from a normal rhythm to an arrhythmia is a transition from regular electrical wave conduction to irregular or turbulent wave conduction in the heart, and thus this medical problem is also a problem of physics and mathematics. In the last century, clinical, experimental, and theoretical studies have shown that dynamical theories play fundamental roles in understanding the mechanisms of the genesis of the normal heart rhythm as well as lethal arrhythmias. In this article, we summarize in detail the nonlinear and stochastic dynamics occurring in the heart and their links to normal cardiac functions and arrhythmias, providing a holistic view through integrating dynamics from the molecular (microscopic) scale, to the organelle (mesoscopic) scale, to the cellular, tissue, and organ (macroscopic) scales. We discuss what existing problems and challenges are waiting to be solved and how multi-scale mathematical modeling and nonlinear dynamics may be helpful for solving these problems. PMID:25267872

On the stability of motion of N-body systems: a geometric approach.

NASA Astrophysics Data System (ADS)

El-Zant, A. A.

1997-10-01

Much of standard galaxy dynamics rests on the implicit assumption that the corresponding N-body problem is (near) integrable. This notion although leading to great simplification is by no means a fact. In particular, this assumption is unlikely to be satisfied for systems which display chaotic behaviour which manifests itself on short time-scales and for most initial conditions. It is therefore important to develop and test methods that can characterize this kind of behaviour in realistic situations. We examine here a method, pioneered by Krylov (1950, Studies on the Foundation of statistical Physics. Publ AN SSSR, Leningrad Eng. Trans. Princeton University Press. 1980) and first introduced to gravitational systems by Gurzadyan & Savvidy (1984SPhD...29..520G, 1986A&A...160..203G). It involves a metric on the configuration manifold which is then used to find local quantification of the divergence of trajectories and therefore appears to be suitable for short time characterization of chaotic behaviour. We present results of high precision N-body simulations of the dynamics of systems of 231 point particles over a few dynamical times. The Ricci (or mean) curvature is calculated along the trajectories. Once fluctuations due to close encounters are removed this quantity is found to be almost always negative and therefore all systems studied display local instability to random perturbations along their trajectories. However it is found that when significant softening is present the Ricci curvature is no longer negative. This suggests that smoothing significantly changes the structure of the 6N phase space of gravitational systems and casts doubts on the continuity of the transition from the large-N limit to the continuum limit. From the value of the negative curvature, evolution time-scales of systems displaying clear instabilities (for example collective instabilities or violent relaxation) are derived. We compare the predictions obtained from these calculations with the time-scales of the observed spatial evolution of the different systems and deduce that this is fairly well described. In all cases the results based on calculations of the scalar curvature qualitatively agree. These results suggest that future applications of these methods to realistic systems may be useful in characterizing their stability properties. One has to be careful however in relating the time-scales obtained to the time-scales of energy relaxation since different dynamical quantities may relax at different rates.

Dynamic Communicability Predicts Infectiousness

NASA Astrophysics Data System (ADS)

Mantzaris, Alexander V.; Higham, Desmond J.

Using real, time-dependent social interaction data, we look at correlations between some recently proposed dynamic centrality measures and summaries from large-scale epidemic simulations. The evolving network arises from email exchanges. The centrality measures, which are relatively inexpensive to compute, assign rankings to individual nodes based on their ability to broadcast information over the dynamic topology. We compare these with node rankings based on infectiousness that arise when a full stochastic SI simulation is performed over the dynamic network. More precisely, we look at the proportion of the network that a node is able to infect over a fixed time period, and the length of time that it takes for a node to infect half the network. We find that the dynamic centrality measures are an excellent, and inexpensive, proxy for the full simulation-based measures.

A dynamical systems approach to studying midlatitude weather extremes

NASA Astrophysics Data System (ADS)

Messori, Gabriele; Caballero, Rodrigo; Faranda, Davide

2017-04-01

Extreme weather occurrences carry enormous social and economic costs and routinely garner widespread scientific and media coverage. The ability to predict these events is therefore a topic of crucial importance. Here we propose a novel predictability pathway for extreme events, by building upon recent advances in dynamical systems theory. We show that simple dynamical systems metrics can be used to identify sets of large-scale atmospheric flow patterns with similar spatial structure and temporal evolution on time scales of several days to a week. In regions where these patterns favor extreme weather, they afford a particularly good predictability of the extremes. We specifically test this technique on the atmospheric circulation in the North Atlantic region, where it provides predictability of large-scale wintertime surface temperature extremes in Europe up to 1 week in advance.

Intrinsic vs. spurious long-range memory in high-frequency records of environmental radioactivity. Critical re-assessment and application to indoor 222Rn concentrations from Coimbra, Portugal

NASA Astrophysics Data System (ADS)

Donner, R. V.; Potirakis, S. M.; Barbosa, S. M.; Matos, J. A. O.; Pereira, A. J. S. C.; Neves, L. J. P. F.

2015-05-01

The presence or absence of long-range correlations in the environmental radioactivity fluctuations has recently attracted considerable interest. Among a multiplicity of practically relevant applications, identifying and disentangling the environmental factors controlling the variable concentrations of the radioactive noble gas radon is important for estimating its effect on human health and the efficiency of possible measures for reducing the corresponding exposition. In this work, we present a critical re-assessment of a multiplicity of complementary methods that have been previously applied for evaluating the presence of long-range correlations and fractal scaling in environmental radon variations with a particular focus on the specific properties of the underlying time series. As an illustrative case study, we subsequently re-analyze two high-frequency records of indoor radon concentrations from Coimbra, Portugal, each of which spans several weeks of continuous measurements at a high temporal resolution of five minutes.Our results reveal that at the study site, radon concentrations exhibit complex multi-scale dynamics with qualitatively different properties at different time-scales: (i) essentially white noise in the high-frequency part (up to time-scales of about one hour), (ii) spurious indications of a non-stationary, apparently long-range correlated process (at time scales between some hours and one day) arising from marked periodic components, and (iii) low-frequency variability indicating a true long-range dependent process. In the presence of such multi-scale variability, common estimators of long-range memory in time series are prone to fail if applied to the raw data without previous separation of time-scales with qualitatively different dynamics.

Multifractality Signatures in Quasars Time Series. I. 3C 273

NASA Astrophysics Data System (ADS)

Belete, A. Bewketu; Bravo, J. P.; Canto Martins, B. L.; Leão, I. C.; De Araujo, J. M.; De Medeiros, J. R.

2018-05-01

The presence of multifractality in a time series shows different correlations for different time scales as well as intermittent behaviour that cannot be captured by a single scaling exponent. The identification of a multifractal nature allows for a characterization of the dynamics and of the intermittency of the fluctuations in non-linear and complex systems. In this study, we search for a possible multifractal structure (multifractality signature) of the flux variability in the quasar 3C 273 time series for all electromagnetic wavebands at different observation points, and the origins for the observed multifractality. This study is intended to highlight how the scaling behaves across the different bands of the selected candidate which can be used as an additional new technique to group quasars based on the fractal signature observed in their time series and determine whether quasars are non-linear physical systems or not. The Multifractal Detrended Moving Average algorithm (MFDMA) has been used to study the scaling in non-linear, complex and dynamic systems. To achieve this goal, we applied the backward (θ = 0) MFDMA method for one-dimensional signals. We observe weak multifractal (close to monofractal) behaviour in some of the time series of our candidate except in the mm, UV and X-ray bands. The non-linear temporal correlation is the main source of the observed multifractality in the time series whereas the heaviness of the distribution contributes less.

Non-Markovian closure kinetics of flexible polymers with hydrodynamic interactions.

PubMed

Levernier, N; Dolgushev, M; Bénichou, O; Blumen, A; Guérin, T; Voituriez, R

2015-11-28

This paper presents a theoretical analysis of the closure kinetics of a polymer with hydrodynamic interactions. This analysis, which takes into account the non-Markovian dynamics of the end-to-end vector and relies on the preaveraging of the mobility tensor (Zimm dynamics), is shown to reproduce very accurately the results of numerical simulations of the complete nonlinear dynamics. It is found that Markovian treatments based on a Wilemski-Fixman approximation significantly overestimate cyclization times (up to a factor 2), showing the importance of memory effects in the dynamics. In addition, this analysis provides scaling laws of the mean first cyclization time (MFCT) with the polymer size N and capture radius b, which are identical in both Markovian and non-Markovian approaches. In particular, it is found that the scaling of the MFCT for large N is given by T ∼ N(3/2)ln(N/b(2)), which differs from the case of the Rouse dynamics where T ∼ N(2). The extension to the case of the reaction kinetics of a monomer of a Zimm polymer with an external target in a confined volume is also presented.

Analytical approach to impurity transport studies: Charge state dynamics in tokamak plasmas

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

Shurygin, V. A.

2006-08-15

Ionization and recombination of plasma impurities govern their charge state kinetics, which is imposed upon the dynamics of ions that implies a superposition of the appropriate probabilities and causes an impurity charge state dynamics. The latter is considered in terms of a vector field of conditional probabilities and presented by a vector charge state distribution function with coupled equations of the Kolmogorov type. Analytical solutions of a diffusion problem are derived with the basic spatial and temporal dimensionless parameters. Analysis shows that the empirical scaling D{sub A}{proportional_to}n{sub e}{sup -1} [K. Krieger, G. Fussmann, and the ASDEX Upgrade Team, Nucl. Fusionmore » 30, 2392 (1990)] can be explained by the ratio of the diffusive and kinetic terms, D{sub A}/(n{sub e}a{sup 2}), being used instead of diffusivity, D{sub A}. The derived time scales of charge state dynamics are given by a sum of the diffusive and kinetic times. Detailed simulations of charge state dynamics are performed for argon impurity and compared with the reference modeling.« less

Biogeochemistry from Gliders at the Hawaii Ocean Times-Series

NASA Astrophysics Data System (ADS)

Nicholson, D. P.; Barone, B.; Karl, D. M.

2016-02-01

At the Hawaii Ocean Time-series (HOT) autonomous, underwater gliders equipped with biogeochemical sensors observe the oceans for months at a time, sampling spatiotemporal scales missed by the ship-based programs. Over the last decade, glider data augmented by a foundation of time-series observations have shed light on biogeochemical dynamics occuring spatially at meso- and submesoscales and temporally on scales from diel to annual. We present insights gained from the synergy between glider observations, time-series measurements and remote sensing in the subtropical North Pacific. We focus on diel variability observed in dissolved oxygen and bio-optics and approaches to autonomously quantify net community production and gross primary production (GPP) as developed during the 2012 Hawaii Ocean Experiment - DYnamics of Light And Nutrients (HOE-DYLAN). Glider-based GPP measurements were extended to explore the relationship between GPP and mesoscale context over multiple years of Seaglider deployments.

Imaging Molecular Motion: Femtosecond X-Ray Scattering of an Electrocyclic Chemical Reaction

NASA Astrophysics Data System (ADS)

Minitti, M. P.; Budarz, J. M.; Kirrander, A.; Robinson, J. S.; Ratner, D.; Lane, T. J.; Zhu, D.; Glownia, J. M.; Kozina, M.; Lemke, H. T.; Sikorski, M.; Feng, Y.; Nelson, S.; Saita, K.; Stankus, B.; Northey, T.; Hastings, J. B.; Weber, P. M.

2015-06-01

Structural rearrangements within single molecules occur on ultrafast time scales. Many aspects of molecular dynamics, such as the energy flow through excited states, have been studied using spectroscopic techniques, yet the goal to watch molecules evolve their geometrical structure in real time remains challenging. By mapping nuclear motions using femtosecond x-ray pulses, we have created real-space representations of the evolving dynamics during a well-known chemical reaction and show a series of time-sorted structural snapshots produced by ultrafast time-resolved hard x-ray scattering. A computational analysis optimally matches the series of scattering patterns produced by the x rays to a multitude of potential reaction paths. In so doing, we have made a critical step toward the goal of viewing chemical reactions on femtosecond time scales, opening a new direction in studies of ultrafast chemical reactions in the gas phase.

Imaging Molecular Motion: Femtosecond X-Ray Scattering of an Electrocyclic Chemical Reaction.

PubMed

Minitti, M P; Budarz, J M; Kirrander, A; Robinson, J S; Ratner, D; Lane, T J; Zhu, D; Glownia, J M; Kozina, M; Lemke, H T; Sikorski, M; Feng, Y; Nelson, S; Saita, K; Stankus, B; Northey, T; Hastings, J B; Weber, P M

2015-06-26

Structural rearrangements within single molecules occur on ultrafast time scales. Many aspects of molecular dynamics, such as the energy flow through excited states, have been studied using spectroscopic techniques, yet the goal to watch molecules evolve their geometrical structure in real time remains challenging. By mapping nuclear motions using femtosecond x-ray pulses, we have created real-space representations of the evolving dynamics during a well-known chemical reaction and show a series of time-sorted structural snapshots produced by ultrafast time-resolved hard x-ray scattering. A computational analysis optimally matches the series of scattering patterns produced by the x rays to a multitude of potential reaction paths. In so doing, we have made a critical step toward the goal of viewing chemical reactions on femtosecond time scales, opening a new direction in studies of ultrafast chemical reactions in the gas phase.

Photoinduced electron-transfer in perylenediimide triphenylamine-based dendrimers: single photon timing and femtosecond transient absorption spectroscopy.

PubMed

Fron, Eduard; Pilot, Roberto; Schweitzer, Gerd; Qu, Jianqiang; Herrmann, Andreas; Müllen, Klaus; Hofkens, Johan; Van der Auweraer, Mark; De Schryver, Frans C

2008-05-01

The excited state dynamics of two generations perylenediimide chromophores substituted in the bay area with dendritic branches bearing triphenylamine units as well as those of the respective reference compounds are investigated. Using single photon timing and multi-pulse femtosecond transient absorption experiments a direct proof of a reversible charge transfer occurring from the peripheral triphenylamine to the electron acceptor perylenediimide core is revealed. Femtosecond pump-dump-probe experiments provide evidence for the ground state dynamics by populating excited vibronic levels. It is found by the means of both techniques that the rotational isomerization of the dendritic branches occurs on a time scale that ranges up to 1 ns. This time scale of the isomerization depends on the size of the dendritic arms and is similar both in the ground and excited state.

Delayed pull-in transitions in overdamped MEMS devices

NASA Astrophysics Data System (ADS)

Gomez, Michael; Moulton, Derek E.; Vella, Dominic

2018-01-01

We consider the dynamics of overdamped MEMS devices undergoing the pull-in instability. Numerous previous experiments and numerical simulations have shown a significant increase in the pull-in time under DC voltages close to the pull-in voltage. Here the transient dynamics slow down as the device passes through a meta-stable or bottleneck phase, but this slowing down is not well understood quantitatively. Using a lumped parallel-plate model, we perform a detailed analysis of the pull-in dynamics in this regime. We show that the bottleneck phenomenon is a type of critical slowing down arising from the pull-in transition. This allows us to show that the pull-in time obeys an inverse square-root scaling law as the transition is approached; moreover we determine an analytical expression for this pull-in time. We then compare our prediction to a wide range of pull-in time data reported in the literature, showing that the observed slowing down is well captured by our scaling law, which appears to be generic for overdamped pull-in under DC loads. This realization provides a useful design rule with which to tune dynamic response in applications, including state-of-the-art accelerometers and pressure sensors that use pull-in time as a sensing mechanism. We also propose a method to estimate the pull-in voltage based only on data of the pull-in times.

Short- and long-time diffusion and dynamic scaling in suspensions of charged colloidal particles

NASA Astrophysics Data System (ADS)

Banchio, Adolfo J.; Heinen, Marco; Holmqvist, Peter; Nägele, Gerhard

2018-04-01

We report on a comprehensive theory-simulation-experimental study of collective and self-diffusion in concentrated suspensions of charge-stabilized colloidal spheres. In theory and simulation, the spheres are assumed to interact directly by a hard-core plus screened Coulomb effective pair potential. The intermediate scattering function, fc(q, t), is calculated by elaborate accelerated Stokesian dynamics (ASD) simulations for Brownian systems where many-particle hydrodynamic interactions (HIs) are fully accounted for, using a novel extrapolation scheme to a macroscopically large system size valid for all correlation times. The study spans the correlation time range from the colloidal short-time to the long-time regime. Additionally, Brownian Dynamics (BD) simulation and mode-coupling theory (MCT) results of fc(q, t) are generated where HIs are neglected. Using these results, the influence of HIs on collective and self-diffusion and the accuracy of the MCT method are quantified. It is shown that HIs enhance collective and self-diffusion at intermediate and long times. At short times self-diffusion, and for wavenumbers outside the structure factor peak region also collective diffusion, are slowed down by HIs. MCT significantly overestimates the slowing influence of dynamic particle caging. The dynamic scattering functions obtained in the ASD simulations are in overall good agreement with our dynamic light scattering (DLS) results for a concentration series of charged silica spheres in an organic solvent mixture, in the experimental time window and wavenumber range. From the simulation data for the time derivative of the width function associated with fc(q, t), there is indication of long-time exponential decay of fc(q, t), for wavenumbers around the location of the static structure factor principal peak. The experimental scattering functions in the probed time range are consistent with a time-wavenumber factorization scaling behavior of fc(q, t) that was first reported by Segrè and Pusey [Phys. Rev. Lett. 77, 771 (1996)] for suspensions of hard spheres. Our BD simulation and MCT results predict a significant violation of exact factorization scaling which, however, is approximately restored according to the ASD results when HIs are accounted for, consistent with the experimental findings for fc(q, t). Our study of collective diffusion is amended by simulation and theoretical results for the self-intermediate scattering function, fs(q, t), and its non-Gaussian parameter α2(t) and for the particle mean squared displacement W(t) and its time derivative. Since self-diffusion properties are not assessed in standard DLS measurements, a method to deduce W(t) approximately from fc(q, t) is theoretically validated.

Scaling and universality in heart rate variability distributions

NASA Technical Reports Server (NTRS)

Rosenblum, M. G.; Peng, C. K.; Mietus, J. E.; Havlin, S.; Stanley, H. E.; Goldberger, A. L.

1998-01-01

We find that a universal homogeneous scaling form describes the distribution of cardiac variations for a group of healthy subjects, which is stable over a wide range of time scales. However, a similar scaling function does not exist for a group with a common cardiopulmonary instability associated with sleep apnea. Subtle differences in the distributions for the day- and night-phase dynamics for healthy subjects are detected.

Scaling and universality in heart rate variability distributions

NASA Astrophysics Data System (ADS)

Ivanov, P. Ch; Rosenblum, M. G.; Peng, C.-K.; Mietus, J. E.; Havlin, S.; Stanley, H. E.; Goldberger, A. L.

We find that a universal homogeneous scaling form describes the distributions of cardiac variations for a group of healthy subjects, which is stable over a wide range of time scales. However, a similar scaling function does not exist for a group with a common cardiopulmonary instability associated with sleep apnea. Subtle differences in the distributions for the day- and night-phase dynamics for healthy subjects are detected.

Dynamical Bayesian inference of time-evolving interactions: from a pair of coupled oscillators to networks of oscillators.

PubMed

Duggento, Andrea; Stankovski, Tomislav; McClintock, Peter V E; Stefanovska, Aneta

2012-12-01

Living systems have time-evolving interactions that, until recently, could not be identified accurately from recorded time series in the presence of noise. Stankovski et al. [Phys. Rev. Lett. 109, 024101 (2012)] introduced a method based on dynamical Bayesian inference that facilitates the simultaneous detection of time-varying synchronization, directionality of influence, and coupling functions. It can distinguish unsynchronized dynamics from noise-induced phase slips. The method is based on phase dynamics, with Bayesian inference of the time-evolving parameters being achieved by shaping the prior densities to incorporate knowledge of previous samples. We now present the method in detail using numerically generated data, data from an analog electronic circuit, and cardiorespiratory data. We also generalize the method to encompass networks of interacting oscillators and thus demonstrate its applicability to small-scale networks.

Simulation of FRET dyes allows quantitative comparison against experimental data

NASA Astrophysics Data System (ADS)

Reinartz, Ines; Sinner, Claude; Nettels, Daniel; Stucki-Buchli, Brigitte; Stockmar, Florian; Panek, Pawel T.; Jacob, Christoph R.; Nienhaus, Gerd Ulrich; Schuler, Benjamin; Schug, Alexander

2018-03-01

Fully understanding biomolecular function requires detailed insight into the systems' structural dynamics. Powerful experimental techniques such as single molecule Förster Resonance Energy Transfer (FRET) provide access to such dynamic information yet have to be carefully interpreted. Molecular simulations can complement these experiments but typically face limits in accessing slow time scales and large or unstructured systems. Here, we introduce a coarse-grained simulation technique that tackles these challenges. While requiring only few parameters, we maintain full protein flexibility and include all heavy atoms of proteins, linkers, and dyes. We are able to sufficiently reduce computational demands to simulate large or heterogeneous structural dynamics and ensembles on slow time scales found in, e.g., protein folding. The simulations allow for calculating FRET efficiencies which quantitatively agree with experimentally determined values. By providing atomically resolved trajectories, this work supports the planning and microscopic interpretation of experiments. Overall, these results highlight how simulations and experiments can complement each other leading to new insights into biomolecular dynamics and function.

Synaptic dynamics contribute to long-term single neuron response fluctuations.

PubMed

Reinartz, Sebastian; Biro, Istvan; Gal, Asaf; Giugliano, Michele; Marom, Shimon

2014-01-01

Firing rate variability at the single neuron level is characterized by long-memory processes and complex statistics over a wide range of time scales (from milliseconds up to several hours). Here, we focus on the contribution of non-stationary efficacy of the ensemble of synapses-activated in response to a given stimulus-on single neuron response variability. We present and validate a method tailored for controlled and specific long-term activation of a single cortical neuron in vitro via synaptic or antidromic stimulation, enabling a clear separation between two determinants of neuronal response variability: membrane excitability dynamics vs. synaptic dynamics. Applying this method we show that, within the range of physiological activation frequencies, the synaptic ensemble of a given neuron is a key contributor to the neuronal response variability, long-memory processes and complex statistics observed over extended time scales. Synaptic transmission dynamics impact on response variability in stimulation rates that are substantially lower compared to stimulation rates that drive excitability resources to fluctuate. Implications to network embedded neurons are discussed.

Formation and organization of protein domains in the immunological synapse

NASA Astrophysics Data System (ADS)

Carlson, Andreas; Mahadevan, L.

2014-11-01

The cellular basis for the adaptive immune response during antigen recognition relies on a specialized protein interface known as the immunological synapse. Here, we propose a minimal mathematical model for the dynamics of the IS that encompass membrane mechanics, hydrodynamics and protein kinetics. Simple scaling laws describe the dynamics of protein clusters as a function of membrane stiffness, rigidity of the adhesive proteins, and fluid flow in the synaptic cleft. Numerical simulations complement the scaling laws by quantifying the nucleation, growth and stabilization of proteins domains on the size of the cell. Direct comparison with experiment suggests that passive dynamics suffices to describe the short-time formation and organization of protein clusters, while the stabilization and long time dynamics of the synapse is likely determined by active cytoskeleton processes triggered by receptor binding. Our study reveals that the fluid flow generated by the interplay between membrane deformation and protein binding kinetics can assist immune cells in regulating protein sorting.

Multiscale Behavior of Viscous Fluids Dynamics: Experimental Observations

NASA Astrophysics Data System (ADS)

Arciniega-Ceballos, Alejandra; Spina, Laura; Scheu, Bettina; Dingwell, Donald B.

2016-04-01

The dynamics of Newtonian fluids with viscosities of mafic to intermediate silicate melts (10-1000 Pa s) during slow decompression present multi-time scale processes. To observe these processes we have performed several experiments on silicon oil saturated with Argon gas for 72 hours, in a Plexiglas autoclave. The slow decompression, dropping from 10 MPa to ambient pressure, acting as the excitation mechanism, triggered several processes with their own distinct timescales. These processes generate complex non-stationary microseismic signals, which have been recorded with 7 high-dynamic piezoelectric sensors located along the conduit flanked by high-speed video recordings. The analysis in time and frequency of these time series and their correlation with the associated high-speed imaging enables the characterization of distinct phases and the extraction of the individual processes during the evolution of decompression of these viscous fluids. We have observed fluid-solid elastic interaction, degassing, fluid mass expansion and flow, bubble nucleation, growth, coalescence and collapse, foam building and vertical wagging. All these processes (in fine and coarse scales) are sequentially coupled in time, occur within specific pressure intervals, and exhibit a localized distribution along the conduit. Their coexistence and interactions constitute the stress field and driving forces that determine the dynamics of the conduit system. Our observations point to the great potential of this experimental approach in the understanding of volcanic conduit dynamics and volcanic seismicity.

Understanding Pitch Perception as a Hierarchical Process with Top-Down Modulation

PubMed Central

Balaguer-Ballester, Emili; Clark, Nicholas R.; Coath, Martin; Krumbholz, Katrin; Denham, Susan L.

2009-01-01

Pitch is one of the most important features of natural sounds, underlying the perception of melody in music and prosody in speech. However, the temporal dynamics of pitch processing are still poorly understood. Previous studies suggest that the auditory system uses a wide range of time scales to integrate pitch-related information and that the effective integration time is both task- and stimulus-dependent. None of the existing models of pitch processing can account for such task- and stimulus-dependent variations in processing time scales. This study presents an idealized neurocomputational model, which provides a unified account of the multiple time scales observed in pitch perception. The model is evaluated using a range of perceptual studies, which have not previously been accounted for by a single model, and new results from a neurophysiological experiment. In contrast to other approaches, the current model contains a hierarchy of integration stages and uses feedback to adapt the effective time scales of processing at each stage in response to changes in the input stimulus. The model has features in common with a hierarchical generative process and suggests a key role for efferent connections from central to sub-cortical areas in controlling the temporal dynamics of pitch processing. PMID:19266015

How the propagation of heat-flux modulations triggers E × B flow pattern formation.

PubMed

Kosuga, Y; Diamond, P H; Gürcan, O D

2013-03-08

We propose a novel mechanism to describe E×B flow pattern formation based upon the dynamics of propagation of heat-flux modulations. The E × B flows of interest are staircases, which are quasiregular patterns of strong, localized shear layers and profile corrugations interspersed between regions of avalanching. An analogy of staircase formation to jam formation in traffic flow is used to develop an extended model of heat avalanche dynamics. The extension includes a flux response time, during which the instantaneous heat flux relaxes to the mean heat flux, determined by symmetry constraints. The response time introduced here is the counterpart of the drivers' response time in traffic, during which drivers adjust their speed to match the background traffic flow. The finite response time causes the growth of mesoscale temperature perturbations, which evolve to form profile corrugations. The length scale associated with the maximum growth rate scales as Δ(2) ~ (v(thi)/λT(i))ρ(i)sqrt[χ(neo)τ], where λT(i) is a typical heat pulse speed, χ(neo) is the neoclassical thermal diffusivity, and τ is the response time of the heat flux. The connection between the scale length Δ(2) and the staircase interstep scale is discussed.

Emergence of scaling in human-interest dynamics.

PubMed

Zhao, Zhi-Dan; Yang, Zimo; Zhang, Zike; Zhou, Tao; Huang, Zi-Gang; Lai, Ying-Cheng

2013-12-11

Human behaviors are often driven by human interests. Despite intense recent efforts in exploring the dynamics of human behaviors, little is known about human-interest dynamics, partly due to the extreme difficulty in accessing the human mind from observations. However, the availability of large-scale data, such as those from e-commerce and smart-phone communications, makes it possible to probe into and quantify the dynamics of human interest. Using three prototypical "Big Data" sets, we investigate the scaling behaviors associated with human-interest dynamics. In particular, from the data sets we uncover fat-tailed (possibly power-law) distributions associated with the three basic quantities: (1) the length of continuous interest, (2) the return time of visiting certain interest, and (3) interest ranking and transition. We argue that there are three basic ingredients underlying human-interest dynamics: preferential return to previously visited interests, inertial effect, and exploration of new interests. We develop a biased random-walk model, incorporating the three ingredients, to account for the observed fat-tailed distributions. Our study represents the first attempt to understand the dynamical processes underlying human interest, which has significant applications in science and engineering, commerce, as well as defense, in terms of specific tasks such as recommendation and human-behavior prediction.

Emergence of scaling in human-interest dynamics

NASA Astrophysics Data System (ADS)

Zhao, Zhi-Dan; Yang, Zimo; Zhang, Zike; Zhou, Tao; Huang, Zi-Gang; Lai, Ying-Cheng

2013-12-01

Human behaviors are often driven by human interests. Despite intense recent efforts in exploring the dynamics of human behaviors, little is known about human-interest dynamics, partly due to the extreme difficulty in accessing the human mind from observations. However, the availability of large-scale data, such as those from e-commerce and smart-phone communications, makes it possible to probe into and quantify the dynamics of human interest. Using three prototypical ``Big Data'' sets, we investigate the scaling behaviors associated with human-interest dynamics. In particular, from the data sets we uncover fat-tailed (possibly power-law) distributions associated with the three basic quantities: (1) the length of continuous interest, (2) the return time of visiting certain interest, and (3) interest ranking and transition. We argue that there are three basic ingredients underlying human-interest dynamics: preferential return to previously visited interests, inertial effect, and exploration of new interests. We develop a biased random-walk model, incorporating the three ingredients, to account for the observed fat-tailed distributions. Our study represents the first attempt to understand the dynamical processes underlying human interest, which has significant applications in science and engineering, commerce, as well as defense, in terms of specific tasks such as recommendation and human-behavior prediction.

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management.

PubMed

Malmstrom, Carolyn M; Butterfield, H Scott; Planck, Laura; Long, Christopher W; Eviner, Valerie T

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics.

Novel fine-scale aerial mapping approach quantifies grassland weed cover dynamics and response to management

PubMed Central

Butterfield, H. Scott; Planck, Laura; Long, Christopher W.; Eviner, Valerie T.

2017-01-01

Invasive weeds threaten the biodiversity and forage productivity of grasslands worldwide. However, management of these weeds is constrained by the practical difficulty of detecting small-scale infestations across large landscapes and by limits in understanding of landscape-scale invasion dynamics, including mechanisms that enable patches to expand, contract, or remain stable. While high-end hyperspectral remote sensing systems can effectively map vegetation cover, these systems are currently too costly and limited in availability for most land managers. We demonstrate application of a more accessible and cost-effective remote sensing approach, based on simple aerial imagery, for quantifying weed cover dynamics over time. In California annual grasslands, the target communities of interest include invasive weedy grasses (Aegilops triuncialis and Elymus caput-medusae) and desirable forage grass species (primarily Avena spp. and Bromus spp.). Detecting invasion of annual grasses into an annual-dominated community is particularly challenging, but we were able to consistently characterize these two communities based on their phenological differences in peak growth and senescence using maximum likelihood supervised classification of imagery acquired twice per year (in mid- and end-of season). This approach permitted us to map weed-dominated cover at a 1-m scale (correctly detecting 93% of weed patches across the landscape) and to evaluate weed cover change over time. We found that weed cover was more pervasive and persistent in management units that had no significant grazing for several years than in those that were grazed, whereas forage cover was more abundant and stable in the grazed units. This application demonstrates the power of this method for assessing fine-scale vegetation transitions across heterogeneous landscapes. It thus provides means for small-scale early detection of invasive species and for testing fundamental questions about landscape dynamics. PMID:29016604

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

PubMed Central

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

2013-01-01

It is well known that ecological processes such as population regulation and natural enemy interactions potentially occur over a range of spatial scales, and there is a substantial body of literature developing theoretical understanding of the interplay between these processes. However, there are comparatively few studies quantifying the long-term effects of spatial scaling in natural ecosystems. A key challenge is that trophic complexity in real-world biological communities quickly obscures the signal from a focal process. Seagrass meadows provide an excellent opportunity in this respect: in many instances, seagrasses effectively form extensive natural monocultures, in which hypotheses about endogenous dynamics can be formulated and tested. We present amongst the longest unbroken, spatially explict time series of seagrass abundance published to date. Data include annual measures of shoot density, total above-ground abundance, and associated epiphyte cover from five Zostera marina meadows distributed around the Isles of Scilly, UK, from 1996 to 2011. We explore empirical patterns at the local and metapopulation scale using standard time series analysis and develop a simple population dynamic model, testing the hypothesis that both local and metapopulation scale feedback processes are important. We find little evidence of an interaction between scales in seagrass dynamics but that both scales contribute approximately equally to observed local epiphyte abundance. By quantifying the long-term dynamics of seagrass-epiphyte interactions we show how measures of density and extent are both important in establishing baseline information relevant to predicting responses to environmental change and developing management plans. We hope that this study complements existing mechanistic studies of physiology, genetics and productivity in seagrass, whilst highlighting the potential of seagrass as a model ecosystem. More generally, this study provides a rare opportunity to test some of the predictions of ecological theory in a natural ecosystem of global conservation and economic value. PMID:23437313

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

PubMed

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

2013-01-01

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

Dynamics of a bilayer membrane coupled to a two-dimensional cytoskeleton: Scale transfers of membrane deformations

NASA Astrophysics Data System (ADS)

Okamoto, Ryuichi; Komura, Shigeyuki; Fournier, Jean-Baptiste

2017-07-01

We theoretically investigate the dynamics of a floating lipid bilayer membrane coupled with a two-dimensional cytoskeleton network, taking into account explicitly the intermonolayer friction, the discrete lattice structure of the cytoskeleton, and its prestress. The lattice structure breaks lateral continuous translational symmetry and couples Fourier modes with different wave vectors. It is shown that within a short time interval a long-wavelength deformation excites a collection of modes with wavelengths shorter than the lattice spacing. These modes relax slowly with a common renormalized rate originating from the long-wavelength mode. As a result, and because of the prestress, the slowest relaxation is governed by the intermonolayer friction. Conversely, and most interestingly, forces applied at the scale of the cytoskeleton for a sufficiently long time can cooperatively excite large-scale modes.

Monitoring vegetation phenology using MODIS

USGS Publications Warehouse

Zhang, Xiayong; Friedl, Mark A.; Schaaf, Crystal B.; Strahler, Alan H.; Hodges, John C.F.; Gao, Feng; Reed, Bradley C.; Huete, Alfredo

2003-01-01

Accurate measurements of regional to global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate–biosphere interactions. Since the mid-1980s, satellite data have been used to study these processes. In this paper, a new methodology to monitor global vegetation phenology from time series of satellite data is presented. The method uses series of piecewise logistic functions, which are fit to remotely sensed vegetation index (VI) data, to represent intra-annual vegetation dynamics. Using this approach, transition dates for vegetation activity within annual time series of VI data can be determined from satellite data. The method allows vegetation dynamics to be monitored at large scales in a fashion that it is ecologically meaningful and does not require pre-smoothing of data or the use of user-defined thresholds. Preliminary results based on an annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data for the northeastern United States demonstrate that the method is able to monitor vegetation phenology with good success.

A fragmentation model of earthquake-like behavior in internet access activity

NASA Astrophysics Data System (ADS)

Paguirigan, Antonino A.; Angco, Marc Jordan G.; Bantang, Johnrob Y.

We present a fragmentation model that generates almost any inverse power-law size distribution, including dual-scaled versions, consistent with the underlying dynamics of systems with earthquake-like behavior. We apply the model to explain the dual-scaled power-law statistics observed in an Internet access dataset that covers more than 32 million requests. The non-Poissonian statistics of the requested data sizes m and the amount of time τ needed for complete processing are consistent with the Gutenberg-Richter-law. Inter-event times δt between subsequent requests are also shown to exhibit power-law distributions consistent with the generalized Omori law. Thus, the dataset is similar to the earthquake data except that two power-law regimes are observed. Using the proposed model, we are able to identify underlying dynamics responsible in generating the observed dual power-law distributions. The model is universal enough for its applicability to any physical and human dynamics that is limited by finite resources such as space, energy, time or opportunity.

Stereocontrol of attosecond time-scale electron dynamics in ABCU using ultrafast laser pulses: a computational study.

PubMed

Mignolet, B; Gijsbertsen, A; Vrakking, M J J; Levine, R D; Remacle, F

2011-05-14

The attosecond time-scale electronic dynamics induced by an ultrashort laser pulse is computed using a multi configuration time dependent approach in ABCU (C(10)H(19)N), a medium size polyatomic molecule with a rigid cage geometry. The coupling between the electronic states induced by the strong pulse is included in the many electron Hamiltonian used to compute the electron dynamics. We show that it is possible to implement control of the electron density stereodynamics in this medium size molecule by varying the characteristics of the laser pulse, for example by polarizing the electric field either along the N-C axis of the cage, or in the plane perpendicular to it. The excitation produces an oscillatory, non-stationary, electronic state that exhibits localization of the electron density in different parts of the molecule both during and after the pulse. The coherent oscillations of the non-stationary electronic state are also demonstrated through the alternation of the dipole moment of the molecule.