Comparison of Laminar and Linear Eddy Model Closures for Combustion Instability Simulations

DTIC Science & Technology

2015-07-01

14. ABSTRACT Unstable liquid rocket engines can produce highly complex dynamic flowfields with features such as rapid changes in temperature and...applicability. In the present study, the linear eddy model (LEM) is applied to an unstable single element liquid rocket engine to assess its performance and to...Sankaran‡ Air Force Research Laboratory, Edwards AFB, CA, 93524 Unstable liquid rocket engines can produce highly complex dynamic flowfields with features

Simple deterministic models and applications. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Yang, Hyun Mo

2015-12-01

Currently, discrete modellings are largely accepted due to the access to computers with huge storage capacity and high performance processors and easy implementation of algorithms, allowing to develop and simulate increasingly sophisticated models. Wang et al. [7] present a review of dynamics in complex networks, focusing on the interaction between disease dynamics and human behavioral and social dynamics. By doing an extensive review regarding to the human behavior responding to disease dynamics, the authors briefly describe the complex dynamics found in the literature: well-mixed populations networks, where spatial structure can be neglected, and other networks considering heterogeneity on spatially distributed populations. As controlling mechanisms are implemented, such as social distancing due 'social contagion', quarantine, non-pharmaceutical interventions and vaccination, adaptive behavior can occur in human population, which can be easily taken into account in the dynamics formulated by networked populations.

Complex Phenomena Understanding in Electricity through Dynamically Linked Concrete and Abstract Representations

ERIC Educational Resources Information Center

Taramopoulos, A.; Psillos, D.

2017-01-01

The present study investigates the impact of utilizing virtual laboratory environments combining dynamically linked concrete and abstract representations in investigative activities on the ability of students to comprehend simple and complex phenomena in the field of electric circuits. Forty-two 16- to 17-year-old high school students participated…

A First Approach to Filament Dynamics

ERIC Educational Resources Information Center

Silva, P. E. S.; de Abreu, F. Vistulo; Simoes, R.; Dias, R. G.

2010-01-01

Modelling elastic filament dynamics is a topic of high interest due to the wide range of applications. However, it has reached a high level of complexity in the literature, making it unaccessible to a beginner. In this paper we explain the main steps involved in the computational modelling of the dynamics of an elastic filament. We first derive…

A Complex Systems Investigation of Group Work Dynamics in L2 Interactive Tasks

ERIC Educational Resources Information Center

Poupore, Glen

2018-01-01

Working with Korean university-level learners of English, this study provides a detailed analytical comparison of 2 task work groups that were video-recorded, with 1 group scoring very high and the other relatively low based on the results of a Group Work Dynamic (GWD) measuring instrument. Adopting a complexity theory (CT) perspective and…

Large-scale systems: Complexity, stability, reliability

NASA Technical Reports Server (NTRS)

Siljak, D. D.

1975-01-01

After showing that a complex dynamic system with a competitive structure has highly reliable stability, a class of noncompetitive dynamic systems for which competitive models can be constructed is defined. It is shown that such a construction is possible in the context of the hierarchic stability analysis. The scheme is based on the comparison principle and vector Liapunov functions.

Effective control of complex turbulent dynamical systems through statistical functionals.

PubMed

Majda, Andrew J; Qi, Di

2017-05-30

Turbulent dynamical systems characterized by both a high-dimensional phase space and a large number of instabilities are ubiquitous among complex systems in science and engineering, including climate, material, and neural science. Control of these complex systems is a grand challenge, for example, in mitigating the effects of climate change or safe design of technology with fully developed shear turbulence. Control of flows in the transition to turbulence, where there is a small dimension of instabilities about a basic mean state, is an important and successful discipline. In complex turbulent dynamical systems, it is impossible to track and control the large dimension of instabilities, which strongly interact and exchange energy, and new control strategies are needed. The goal of this paper is to propose an effective statistical control strategy for complex turbulent dynamical systems based on a recent statistical energy principle and statistical linear response theory. We illustrate the potential practical efficiency and verify this effective statistical control strategy on the 40D Lorenz 1996 model in forcing regimes with various types of fully turbulent dynamics with nearly one-half of the phase space unstable.

Organization and Dynamics of Receptor Proteins in a Plasma Membrane.

PubMed

Koldsø, Heidi; Sansom, Mark S P

2015-11-25

The interactions of membrane proteins are influenced by their lipid environment, with key lipid species able to regulate membrane protein function. Advances in high-resolution microscopy can reveal the organization and dynamics of proteins and lipids within living cells at resolutions <200 nm. Parallel advances in molecular simulations provide near-atomic-resolution models of the dynamics of the organization of membranes of in vivo-like complexity. We explore the dynamics of proteins and lipids in crowded and complex plasma membrane models, thereby closing the gap in length and complexity between computations and experiments. Our simulations provide insights into the mutual interplay between lipids and proteins in determining mesoscale (20-100 nm) fluctuations of the bilayer, and in enabling oligomerization and clustering of membrane proteins.

Three-dimensional plant architecture and sunlit-shaded patterns: a stochastic model of light dynamics in canopies.

PubMed

Retkute, Renata; Townsend, Alexandra J; Murchie, Erik H; Jensen, Oliver E; Preston, Simon P

2018-05-25

Diurnal changes in solar position and intensity combined with the structural complexity of plant architecture result in highly variable and dynamic light patterns within the plant canopy. This affects productivity through the complex ways that photosynthesis responds to changes in light intensity. Current methods to characterize light dynamics, such as ray-tracing, are able to produce data with excellent spatio-temporal resolution but are computationally intensive and the resulting data are complex and high-dimensional. This necessitates development of more economical models for summarizing the data and for simulating realistic light patterns over the course of a day. High-resolution reconstructions of field-grown plants are assembled in various configurations to form canopies, and a forward ray-tracing algorithm is applied to the canopies to compute light dynamics at high (1 min) temporal resolution. From the ray-tracer output, the sunlit or shaded state for each patch on the plants is determined, and these data are used to develop a novel stochastic model for the sunlit-shaded patterns. The model is designed to be straightforward to fit to data using maximum likelihood estimation, and fast to simulate from. For a wide range of contrasting 3-D canopies, the stochastic model is able to summarize, and replicate in simulations, key features of the light dynamics. When light patterns simulated from the stochastic model are used as input to a model of photoinhibition, the predicted reduction in carbon gain is similar to that from calculations based on the (extremely costly) ray-tracer data. The model provides a way to summarize highly complex data in a small number of parameters, and a cost-effective way to simulate realistic light patterns. Simulations from the model will be particularly useful for feeding into larger-scale photosynthesis models for calculating how light dynamics affects the photosynthetic productivity of canopies.

Data based identification and prediction of nonlinear and complex dynamical systems

NASA Astrophysics Data System (ADS)

Wang, Wen-Xu; Lai, Ying-Cheng; Grebogi, Celso

2016-07-01

The problem of reconstructing nonlinear and complex dynamical systems from measured data or time series is central to many scientific disciplines including physical, biological, computer, and social sciences, as well as engineering and economics. The classic approach to phase-space reconstruction through the methodology of delay-coordinate embedding has been practiced for more than three decades, but the paradigm is effective mostly for low-dimensional dynamical systems. Often, the methodology yields only a topological correspondence of the original system. There are situations in various fields of science and engineering where the systems of interest are complex and high dimensional with many interacting components. A complex system typically exhibits a rich variety of collective dynamics, and it is of great interest to be able to detect, classify, understand, predict, and control the dynamics using data that are becoming increasingly accessible due to the advances of modern information technology. To accomplish these goals, especially prediction and control, an accurate reconstruction of the original system is required. Nonlinear and complex systems identification aims at inferring, from data, the mathematical equations that govern the dynamical evolution and the complex interaction patterns, or topology, among the various components of the system. With successful reconstruction of the system equations and the connecting topology, it may be possible to address challenging and significant problems such as identification of causal relations among the interacting components and detection of hidden nodes. The "inverse" problem thus presents a grand challenge, requiring new paradigms beyond the traditional delay-coordinate embedding methodology. The past fifteen years have witnessed rapid development of contemporary complex graph theory with broad applications in interdisciplinary science and engineering. The combination of graph, information, and nonlinear dynamical systems theories with tools from statistical physics, optimization, engineering control, applied mathematics, and scientific computing enables the development of a number of paradigms to address the problem of nonlinear and complex systems reconstruction. In this Review, we describe the recent advances in this forefront and rapidly evolving field, with a focus on compressive sensing based methods. In particular, compressive sensing is a paradigm developed in recent years in applied mathematics, electrical engineering, and nonlinear physics to reconstruct sparse signals using only limited data. It has broad applications ranging from image compression/reconstruction to the analysis of large-scale sensor networks, and it has become a powerful technique to obtain high-fidelity signals for applications where sufficient observations are not available. We will describe in detail how compressive sensing can be exploited to address a diverse array of problems in data based reconstruction of nonlinear and complex networked systems. The problems include identification of chaotic systems and prediction of catastrophic bifurcations, forecasting future attractors of time-varying nonlinear systems, reconstruction of complex networks with oscillatory and evolutionary game dynamics, detection of hidden nodes, identification of chaotic elements in neuronal networks, reconstruction of complex geospatial networks and nodal positioning, and reconstruction of complex spreading networks with binary data.. A number of alternative methods, such as those based on system response to external driving, synchronization, and noise-induced dynamical correlation, will also be discussed. Due to the high relevance of network reconstruction to biological sciences, a special section is devoted to a brief survey of the current methods to infer biological networks. Finally, a number of open problems including control and controllability of complex nonlinear dynamical networks are discussed. The methods outlined in this Review are principled on various concepts in complexity science and engineering such as phase transitions, bifurcations, stabilities, and robustness. The methodologies have the potential to significantly improve our ability to understand a variety of complex dynamical systems ranging from gene regulatory systems to social networks toward the ultimate goal of controlling such systems.

Reduced Perceptual Exclusivity during Object and Grating Rivalry in Autism

PubMed Central

Freyberg, J.; Robertson, C.E.; Baron-Cohen, S.

2015-01-01

Background The dynamics of binocular rivalry may be a behavioural footprint of excitatory and inhibitory neural transmission in visual cortex. Given the presence of atypical visual features in Autism Spectrum Conditions (ASC), and evidence in support of the idea of an imbalance in excitatory/inhibitory neural transmission in ASC, we hypothesized that binocular rivalry might prove a simple behavioural marker of such a transmission imbalance in the autistic brain. In support of this hypothesis, we previously reported a slower rate of rivalry in ASC, driven by reduced perceptual exclusivity. Methods We tested whether atypical dynamics of binocular rivalry in ASC are specific to certain stimulus features. 53 participants (26 with ASC, matched for age, sex and IQ) participated in binocular rivalry experiments in which the dynamics of rivalry were measured at two levels of stimulus complexity, low (grayscale gratings) and high (coloured objects). Results Individuals with ASC experienced a slower rate of rivalry, driven by longer transitional states between dominant percepts. These exaggerated transitional states were present at both low and high levels of stimulus complexity, suggesting that atypical rivalry dynamics in autism are robust with respect to stimulus choice. Interactions between stimulus properties and rivalry dynamics in autism indicate that achromatic grating stimuli produce stronger group differences. Conclusion These results confirm the finding of atypical dynamics of binocular rivalry in ASC. These dynamics were present for stimuli of both low and high levels of visual complexity, suggesting an imbalance in competitive interactions throughout the visual system of individuals with ASC. PMID:26382002

Semiconductor Laser Complex Dynamics: From Optical Neurons to Optical Rogue Waves

DTIC Science & Technology

2017-02-11

laser dynamics for innovative applications. The results of the project were published in 5 high- impact journal papers and were presented as invited or...stochastic phenomena and ii) to exploit the laser dynamics for innovative applications. The results of the project were published in 5 high-impact...RESULTS AND DISCUSSION The results of our research were published in 5 articles in high-impact journals in the fields of photonics and nonlinear physics

Estimation of Dynamic Systems for Gene Regulatory Networks from Dependent Time-Course Data.

PubMed

Kim, Yoonji; Kim, Jaejik

2018-06-15

Dynamic system consisting of ordinary differential equations (ODEs) is a well-known tool for describing dynamic nature of gene regulatory networks (GRNs), and the dynamic features of GRNs are usually captured through time-course gene expression data. Owing to high-throughput technologies, time-course gene expression data have complex structures such as heteroscedasticity, correlations between genes, and time dependence. Since gene experiments typically yield highly noisy data with small sample size, for a more accurate prediction of the dynamics, the complex structures should be taken into account in ODE models. Hence, this study proposes an ODE model considering such data structures and a fast and stable estimation method for the ODE parameters based on the generalized profiling approach with data smoothing techniques. The proposed method also provides statistical inference for the ODE estimator and it is applied to a zebrafish retina cell network.

Off-fault plasticity in three-dimensional dynamic rupture simulations using a modal Discontinuous Galerkin method on unstructured meshes: Implementation, verification, and application

NASA Astrophysics Data System (ADS)

Wollherr, Stephanie; Gabriel, Alice-Agnes; Uphoff, Carsten

2018-05-01

The dynamics and potential size of earthquakes depend crucially on rupture transfers between adjacent fault segments. To accurately describe earthquake source dynamics, numerical models can account for realistic fault geometries and rheologies such as nonlinear inelastic processes off the slip interface. We present implementation, verification, and application of off-fault Drucker-Prager plasticity in the open source software SeisSol (www.seissol.org). SeisSol is based on an arbitrary high-order derivative modal Discontinuous Galerkin (ADER-DG) method using unstructured, tetrahedral meshes specifically suited for complex geometries. Two implementation approaches are detailed, modelling plastic failure either employing sub-elemental quadrature points or switching to nodal basis coefficients. At fine fault discretizations the nodal basis approach is up to 6 times more efficient in terms of computational costs while yielding comparable accuracy. Both methods are verified in community benchmark problems and by three dimensional numerical h- and p-refinement studies with heterogeneous initial stresses. We observe no spectral convergence for on-fault quantities with respect to a given reference solution, but rather discuss a limitation to low-order convergence for heterogeneous 3D dynamic rupture problems. For simulations including plasticity, a high fault resolution may be less crucial than commonly assumed, due to the regularization of peak slip rate and an increase of the minimum cohesive zone width. In large-scale dynamic rupture simulations based on the 1992 Landers earthquake, we observe high rupture complexity including reverse slip, direct branching, and dynamic triggering. The spatio-temporal distribution of rupture transfers are altered distinctively by plastic energy absorption, correlated with locations of geometrical fault complexity. Computational cost increases by 7% when accounting for off-fault plasticity in the demonstrating application. Our results imply that the combination of fully 3D dynamic modelling, complex fault geometries, and off-fault plastic yielding is important to realistically capture dynamic rupture transfers in natural fault systems.

Self-assembly of polyelectrolyte surfactant complexes using large scale MD simulation

NASA Astrophysics Data System (ADS)

Goswami, Monojoy; Sumpter, Bobby

2014-03-01

Polyelectrolytes (PE) and surfactants are known to form interesting structures with varied properties in aqueous solutions. The morphological details of the PE-surfactant complexes depend on a combination of polymer backbone, electrostatic interactions and hydrophobic interactions. We study the self-assembly of cationic PE and anionic surfactants complexes in dilute condition. The importance of such complexes of PE with oppositely charged surfactants can be found in biological systems, such as immobilization of enzymes in polyelectrolyte complexes or nonspecific association of DNA with protein. Many useful properties of PE surfactant complexes come from the highly ordered structures of surfactant self-assembly inside the PE aggregate which has applications in industry. We do large scale molecular dynamics simulation using LAMMPS to understand the structure and dynamics of PE-surfactant systems. Our investigation shows highly ordered pearl-necklace structures that have been observed experimentally in biological systems. We investigate many different properties of PE-surfactant complexation for different parameter ranges that are useful for pharmaceutical, engineering and biological applications.

Coarse-grained molecular dynamics simulations for giant protein-DNA complexes

NASA Astrophysics Data System (ADS)

Takada, Shoji

Biomolecules are highly hierarchic and intrinsically flexible. Thus, computational modeling calls for multi-scale methodologies. We have been developing a coarse-grained biomolecular model where on-average 10-20 atoms are grouped into one coarse-grained (CG) particle. Interactions among CG particles are tuned based on atomistic interactions and the fluctuation matching algorithm. CG molecular dynamics methods enable us to simulate much longer time scale motions of much larger molecular systems than fully atomistic models. After broad sampling of structures with CG models, we can easily reconstruct atomistic models, from which one can continue conventional molecular dynamics simulations if desired. Here, we describe our CG modeling methodology for protein-DNA complexes, together with various biological applications, such as the DNA duplication initiation complex, model chromatins, and transcription factor dynamics on chromatin-like environment.

Research and test facilities

NASA Technical Reports Server (NTRS)

1993-01-01

A description is given of each of the following Langley research and test facilities: 0.3-Meter Transonic Cryogenic Tunnel, 7-by 10-Foot High Speed Tunnel, 8-Foot Transonic Pressure Tunnel, 13-Inch Magnetic Suspension & Balance System, 14-by 22-Foot Subsonic Tunnel, 16-Foot Transonic Tunnel, 16-by 24-Inch Water Tunnel, 20-Foot Vertical Spin Tunnel, 30-by 60-Foot Wind Tunnel, Advanced Civil Transport Simulator (ACTS), Advanced Technology Research Laboratory, Aerospace Controls Research Laboratory (ACRL), Aerothermal Loads Complex, Aircraft Landing Dynamics Facility (ALDF), Avionics Integration Research Laboratory, Basic Aerodynamics Research Tunnel (BART), Compact Range Test Facility, Differential Maneuvering Simulator (DMS), Enhanced/Synthetic Vision & Spatial Displays Laboratory, Experimental Test Range (ETR) Flight Research Facility, General Aviation Simulator (GAS), High Intensity Radiated Fields Facility, Human Engineering Methods Laboratory, Hypersonic Facilities Complex, Impact Dynamics Research Facility, Jet Noise Laboratory & Anechoic Jet Facility, Light Alloy Laboratory, Low Frequency Antenna Test Facility, Low Turbulence Pressure Tunnel, Mechanics of Metals Laboratory, National Transonic Facility (NTF), NDE Research Laboratory, Polymers & Composites Laboratory, Pyrotechnic Test Facility, Quiet Flow Facility, Robotics Facilities, Scientific Visualization System, Scramjet Test Complex, Space Materials Research Laboratory, Space Simulation & Environmental Test Complex, Structural Dynamics Research Laboratory, Structural Dynamics Test Beds, Structures & Materials Research Laboratory, Supersonic Low Disturbance Pilot Tunnel, Thermal Acoustic Fatigue Apparatus (TAFA), Transonic Dynamics Tunnel (TDT), Transport Systems Research Vehicle, Unitary Plan Wind Tunnel, and the Visual Motion Simulator (VMS).

Mitochondrial Dynamics Tracking with Two-Photon Phosphorescent Terpyridyl Iridium(III) Complexes

NASA Astrophysics Data System (ADS)

Huang, Huaiyi; Zhang, Pingyu; Qiu, Kangqiang; Huang, Juanjuan; Chen, Yu; Ji, Liangnian; Chao, Hui

2016-02-01

Mitochondrial dynamics, including fission and fusion, control the morphology and function of mitochondria, and disruption of mitochondrial dynamics leads to Parkinson’s disease, Alzheimer’s disease, metabolic diseases, and cancers. Currently, many types of commercial mitochondria probes are available, but high excitation energy and low photo-stability render them unsuitable for tracking mitochondrial dynamics in living cells. Therefore, mitochondrial targeting agents that exhibit superior anti-photo-bleaching ability, deep tissue penetration and intrinsically high three-dimensional resolutions are urgently needed. Two-photon-excited compounds that use low-energy near-infrared excitation lasers have emerged as non-invasive tools for cell imaging. In this work, terpyridyl cyclometalated Ir(III) complexes (Ir1-Ir3) are demonstrated as one- and two-photon phosphorescent probes for real-time imaging and tracking of mitochondrial morphology changes in living cells.

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics.

PubMed

Arampatzis, Georgios; Katsoulakis, Markos A; Rey-Bellet, Luc

2016-03-14

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

NASA Astrophysics Data System (ADS)

Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc

2016-03-01

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systems with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.

Efficient estimators for likelihood ratio sensitivity indices of complex stochastic dynamics

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

Arampatzis, Georgios; Katsoulakis, Markos A.; Rey-Bellet, Luc

2016-03-14

We demonstrate that centered likelihood ratio estimators for the sensitivity indices of complex stochastic dynamics are highly efficient with low, constant in time variance and consequently they are suitable for sensitivity analysis in long-time and steady-state regimes. These estimators rely on a new covariance formulation of the likelihood ratio that includes as a submatrix a Fisher information matrix for stochastic dynamics and can also be used for fast screening of insensitive parameters and parameter combinations. The proposed methods are applicable to broad classes of stochastic dynamics such as chemical reaction networks, Langevin-type equations and stochastic models in finance, including systemsmore » with a high dimensional parameter space and/or disparate decorrelation times between different observables. Furthermore, they are simple to implement as a standard observable in any existing simulation algorithm without additional modifications.« less

Evolutionary fields can explain patterns of high-dimensional complexity in ecology

NASA Astrophysics Data System (ADS)

Wilsenach, James; Landi, Pietro; Hui, Cang

2017-04-01

One of the properties that make ecological systems so unique is the range of complex behavioral patterns that can be exhibited by even the simplest communities with only a few species. Much of this complexity is commonly attributed to stochastic factors that have very high-degrees of freedom. Orthodox study of the evolution of these simple networks has generally been limited in its ability to explain complexity, since it restricts evolutionary adaptation to an inertia-free process with few degrees of freedom in which only gradual, moderately complex behaviors are possible. We propose a model inspired by particle-mediated field phenomena in classical physics in combination with fundamental concepts in adaptation, which suggests that small but high-dimensional chaotic dynamics near to the adaptive trait optimum could help explain complex properties shared by most ecological datasets, such as aperiodicity and pink, fractal noise spectra. By examining a simple predator-prey model and appealing to real ecological data, we show that this type of complexity could be easily confused for or confounded by stochasticity, especially when spurred on or amplified by stochastic factors that share variational and spectral properties with the underlying dynamics.

Molecular dynamic simulation of weakly magnetized complex plasmas

NASA Astrophysics Data System (ADS)

Funk, Dylan; Konopka, Uwe; Thomas, Edward

2017-10-01

A complex plasma consists of the usual plasma components (electrons, ions and neutrals), as well as a heavier component made of solid, micrometer-sized particles. The particles are in general highly charged as a result of the interaction with the other plasma components. The static and dynamic properties of a complex plasma such as its crystal structure or wave properties are influenced by many forces acting on the individual particles such as the dust particle interaction (a screened Coulomb interaction), neutral (Epstein) drag, the particle inertia and various plasma drag or thermophoretic forces. To study the behavior of complex plasmas we setup an experiment accompanying molecular dynamic simulation. We will present the approach taken in our simulation and give an overview of experimental situations that we want to cover with our simulation such as the particle charge under microgravity condition as performed on the PK-4 space experiment, or to study the detailed influences of high magnetic fields. This work was supported by the US Dept. of Energy (DE-SC0016330), NSF (PHY-1613087) and JPL/NASA (JPL-RSA 1571699).

Advanced Kalman Filter for Real-Time Responsiveness in Complex Systems

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

Welch, Gregory Francis; Zhang, Jinghe

2014-06-10

Complex engineering systems pose fundamental challenges in real-time operations and control because they are highly dynamic systems consisting of a large number of elements with severe nonlinearities and discontinuities. Today’s tools for real-time complex system operations are mostly based on steady state models, unable to capture the dynamic nature and too slow to prevent system failures. We developed advanced Kalman filtering techniques and the formulation of dynamic state estimation using Kalman filtering techniques to capture complex system dynamics in aiding real-time operations and control. In this work, we looked at complex system issues including severe nonlinearity of system equations, discontinuitiesmore » caused by system controls and network switches, sparse measurements in space and time, and real-time requirements of power grid operations. We sought to bridge the disciplinary boundaries between Computer Science and Power Systems Engineering, by introducing methods that leverage both existing and new techniques. While our methods were developed in the context of electrical power systems, they should generalize to other large-scale scientific and engineering applications.« less

Structure/function implications in a dynamic complex of the intrinsically disordered Sic1 with the Cdc4 subunit of an SCF ubiquitin ligase

PubMed Central

Mittag, Tanja; Marsh, Joseph; Grishaev, Alexander; Orlicky, Stephen; Lin, Hong; Sicheri, Frank; Tyers, Mike; Forman-Kay, Julie D.

2010-01-01

Summary Intrinsically disordered proteins can form highly dynamic complexes with partner proteins. One such dynamic complex involves the intrinsically disordered Sic1 with its partner Cdc4 in regulation of yeast cell cycle progression. Phosphorylation of six N-terminal Sic1 sites leads to equilibrium engagement of each phosphorylation site with the primary binding pocket in Cdc4, the substrate recognition subunit of a ubiquitin ligase. ENSEMBLE calculations utilizing experimental NMR and small-angle x-ray scattering data reveal significant transient structure in both phosphorylation states of the isolated ensembles (Sic1 and pSic1) that modulates their electrostatic potential, suggesting a structural basis for the proposed strong contribution of electrostatics to binding. A structural model of the dynamic pSic1-Cdc4 complex demonstrates the spatial arrangements in the ubiquitin ligase complex. These results provide a physical picture of a protein that is predominantly disordered in both its free and bound states, enabling aspects of its structure/function relationship to be elucidated. PMID:20399186

Chaos in the classical mechanics of bound and quasi-bound HX-4He complexes with X = F, Cl, Br, CN.

PubMed

Gamboa, Antonio; Hernández, Henar; Ramilowski, Jordan A; Losada, J C; Benito, R M; Borondo, F; Farrelly, David

2009-10-01

The classical dynamics of weakly bound floppy van der Waals complexes have been extensively studied in the past except for the weakest of all, i.e., those involving He atoms. These complexes are of considerable current interest in light of recent experimental work focussed on the study of molecules trapped in small droplets of the quantum solvent (4)He. Despite a number of quantum investigations, details on the dynamics of how quantum solvation occurs remain unclear. In this paper, the classical rotational dynamics of a series of van der Waals complexes, HX-(4)He with X = F, Cl, Br, CN, are studied. In all cases, the ground state dynamics are found to be almost entirely chaotic, in sharp contrast to other floppy complexes, such as HCl-Ar, for which chaos sets in only at relatively high energies. The consequences of this result for quantum solvation are discussed. We also investigate rotationally excited states with J = 1 which, except for HCN-(4)He, are actually resonances that decay by rotational pre-dissociation.

Dynamics of harpooning studied by transition state spectroscopy. II. LiṡṡFH

NASA Astrophysics Data System (ADS)

Hudson, A. J.; Oh, H. B.; Polanyi, J. C.; Piecuch, P.

2000-12-01

The van der Waals complex LiṡṡFH was formed in crossed beams and the transition state of the excited-state reaction, Li*(2p 2P)+HF→LiF+H, was accessed by photoexcitation of this complex. The dynamics of the excited-state reaction were probed by varying the excitation wavelength over the range 570-970 nm while recording the photodepletion of the complex. The findings were interpreted using high-level ab initio calculations of the ground and lowest excited-state potential-energy surfaces.

Persistent model order reduction for complex dynamical systems using smooth orthogonal decomposition

NASA Astrophysics Data System (ADS)

Ilbeigi, Shahab; Chelidze, David

2017-11-01

Full-scale complex dynamic models are not effective for parametric studies due to the inherent constraints on available computational power and storage resources. A persistent reduced order model (ROM) that is robust, stable, and provides high-fidelity simulations for a relatively wide range of parameters and operating conditions can provide a solution to this problem. The fidelity of a new framework for persistent model order reduction of large and complex dynamical systems is investigated. The framework is validated using several numerical examples including a large linear system and two complex nonlinear systems with material and geometrical nonlinearities. While the framework is used for identifying the robust subspaces obtained from both proper and smooth orthogonal decompositions (POD and SOD, respectively), the results show that SOD outperforms POD in terms of stability, accuracy, and robustness.

Complex Dynamics in a Model of Common Fishery Resource Harvested by Multiagents with Heterogeneous Strategy

NASA Astrophysics Data System (ADS)

Gu, En-Guo

In this paper, we formulate a dynamical model of common fishery resource harvested by multiagents with heterogeneous strategy: profit maximizers and gradient learners. Special attention is paid to the problem of heterogeneity of strategic behaviors. We mainly study the existence and the local stability of non-negative equilibria for the model through mathematical analysis. We analyze local bifurcations and complex dynamics such as coexisting attractors by numerical simulations. We also study the local and global dynamics of the exclusive gradient learners as a special case of the model. We discover that when adjusting the speed to be slightly high, the increasing ratio of gradient learners may lead to instability of the fixed point and makes the system sink into complicated dynamics such as quasiperiodic or chaotic attractor. The results reveal that gradient learners with high adjusting speed may ultimately be more harmful to the sustainable use of fish stock than the profit maximizers.

Data-Driven Modeling of Complex Systems by means of a Dynamical ANN

NASA Astrophysics Data System (ADS)

Seleznev, A.; Mukhin, D.; Gavrilov, A.; Loskutov, E.; Feigin, A.

2017-12-01

The data-driven methods for modeling and prognosis of complex dynamical systems become more and more popular in various fields due to growth of high-resolution data. We distinguish the two basic steps in such an approach: (i) determining the phase subspace of the system, or embedding, from available time series and (ii) constructing an evolution operator acting in this reduced subspace. In this work we suggest a novel approach combining these two steps by means of construction of an artificial neural network (ANN) with special topology. The proposed ANN-based model, on the one hand, projects the data onto a low-dimensional manifold, and, on the other hand, models a dynamical system on this manifold. Actually, this is a recurrent multilayer ANN which has internal dynamics and capable of generating time series. Very important point of the proposed methodology is the optimization of the model allowing us to avoid overfitting: we use Bayesian criterion to optimize the ANN structure and estimate both the degree of evolution operator nonlinearity and the complexity of nonlinear manifold which the data are projected on. The proposed modeling technique will be applied to the analysis of high-dimensional dynamical systems: Lorenz'96 model of atmospheric turbulence, producing high-dimensional space-time chaos, and quasi-geostrophic three-layer model of the Earth's atmosphere with the natural orography, describing the dynamics of synoptical vortexes as well as mesoscale blocking systems. The possibility of application of the proposed methodology to analyze real measured data is also discussed. The study was supported by the Russian Science Foundation (grant #16-12-10198).

Human systems dynamics: Toward a computational model

NASA Astrophysics Data System (ADS)

Eoyang, Glenda H.

2012-09-01

A robust and reliable computational model of complex human systems dynamics could support advancements in theory and practice for social systems at all levels, from intrapersonal experience to global politics and economics. Models of human interactions have evolved from traditional, Newtonian systems assumptions, which served a variety of practical and theoretical needs of the past. Another class of models has been inspired and informed by models and methods from nonlinear dynamics, chaos, and complexity science. None of the existing models, however, is able to represent the open, high dimension, and nonlinear self-organizing dynamics of social systems. An effective model will represent interactions at multiple levels to generate emergent patterns of social and political life of individuals and groups. Existing models and modeling methods are considered and assessed against characteristic pattern-forming processes in observed and experienced phenomena of human systems. A conceptual model, CDE Model, based on the conditions for self-organizing in human systems, is explored as an alternative to existing models and methods. While the new model overcomes the limitations of previous models, it also provides an explanatory base and foundation for prospective analysis to inform real-time meaning making and action taking in response to complex conditions in the real world. An invitation is extended to readers to engage in developing a computational model that incorporates the assumptions, meta-variables, and relationships of this open, high dimension, and nonlinear conceptual model of the complex dynamics of human systems.

Combustion and Magnetohydrodynamic Processes in Advanced Pulse Detonation Rocket Engines

DTIC Science & Technology

2012-10-01

use of high-order numerical methods can also be a powerful tool in the analysis of such complex flows, but we need to understand the interaction of...computational physics, 43(2):357372, 1981. [47] B. Einfeldt. On godunov-type methods for gas dynamics . SIAM Journal on Numerical Analysis , pages 294...dimensional effects with complex reaction kinetics, the simple one-dimensional detonation structure provides a rich spectrum of dynamical features which are

Dynamic Skin Patterns in Cephalopods

PubMed Central

How, Martin J.; Norman, Mark D.; Finn, Julian; Chung, Wen-Sung; Marshall, N. Justin

2017-01-01

Cephalopods are unrivaled in the natural world in their ability to alter their visual appearance. These mollusks have evolved a complex system of dermal units under neural, hormonal, and muscular control to produce an astonishing variety of body patterns. With parallels to the pixels on a television screen, cephalopod chromatophores can be coordinated to produce dramatic, dynamic, and rhythmic displays, defined collectively here as “dynamic patterns.” This study examines the nature, context, and potential functions of dynamic patterns across diverse cephalopod taxa. Examples are presented for 21 species, including 11 previously unreported in the scientific literature. These range from simple flashing or flickering patterns, to highly complex passing wave patterns involving multiple skin fields. PMID:28674500

A combinatorial framework to quantify peak/pit asymmetries in complex dynamics.

PubMed

Hasson, Uri; Iacovacci, Jacopo; Davis, Ben; Flanagan, Ryan; Tagliazucchi, Enzo; Laufs, Helmut; Lacasa, Lucas

2018-02-23

We explore a combinatorial framework which efficiently quantifies the asymmetries between minima and maxima in local fluctuations of time series. We first showcase its performance by applying it to a battery of synthetic cases. We find rigorous results on some canonical dynamical models (stochastic processes with and without correlations, chaotic processes) complemented by extensive numerical simulations for a range of processes which indicate that the methodology correctly distinguishes different complex dynamics and outperforms state of the art metrics in several cases. Subsequently, we apply this methodology to real-world problems emerging across several disciplines including cases in neurobiology, finance and climate science. We conclude that differences between the statistics of local maxima and local minima in time series are highly informative of the complex underlying dynamics and a graph-theoretic extraction procedure allows to use these features for statistical learning purposes.

Mantle dynamics and seismic tomography

PubMed Central

Tanimoto, Toshiro; Lay, Thorne

2000-01-01

Three-dimensional imaging of the Earth's interior, called seismic tomography, has achieved breakthrough advances in the last two decades, revealing fundamental geodynamical processes throughout the Earth's mantle and core. Convective circulation of the entire mantle is taking place, with subducted oceanic lithosphere sinking into the lower mantle, overcoming the resistance to penetration provided by the phase boundary near 650-km depth that separates the upper and lower mantle. The boundary layer at the base of the mantle has been revealed to have complex structure, involving local stratification, extensive structural anisotropy, and massive regions of partial melt. The Earth's high Rayleigh number convective regime now is recognized to be much more interesting and complex than suggested by textbook cartoons, and continued advances in seismic tomography, geodynamical modeling, and high-pressure–high-temperature mineral physics will be needed to fully quantify the complex dynamics of our planet's interior. PMID:11035784

Heterogeneous Intracellular Trafficking Dynamics of Brain-Derived Neurotrophic Factor Complexes in the Neuronal Soma Revealed by Single Quantum Dot Tracking

PubMed Central

Vermehren-Schmaedick, Anke; Krueger, Wesley; Jacob, Thomas; Ramunno-Johnson, Damien; Balkowiec, Agnieszka; Lidke, Keith A.; Vu, Tania Q.

2014-01-01

Accumulating evidence underscores the importance of ligand-receptor dynamics in shaping cellular signaling. In the nervous system, growth factor-activated Trk receptor trafficking serves to convey biochemical signaling that underlies fundamental neural functions. Focus has been placed on axonal trafficking but little is known about growth factor-activated Trk dynamics in the neuronal soma, particularly at the molecular scale, due in large part to technical hurdles in observing individual growth factor-Trk complexes for long periods of time inside live cells. Quantum dots (QDs) are intensely fluorescent nanoparticles that have been used to study the dynamics of ligand-receptor complexes at the plasma membrane but the value of QDs for investigating ligand-receptor intracellular dynamics has not been well exploited. The current study establishes that QD conjugated brain-derived neurotrophic factor (QD-BDNF) binds to TrkB receptors with high specificity, activates TrkB downstream signaling, and allows single QD tracking capability for long recording durations deep within the soma of live neurons. QD-BDNF complexes undergo internalization, recycling, and intracellular trafficking in the neuronal soma. These trafficking events exhibit little time-synchrony and diverse heterogeneity in underlying dynamics that include phases of sustained rapid motor transport without pause as well as immobility of surprisingly long-lasting duration (several minutes). Moreover, the trajectories formed by dynamic individual BDNF complexes show no apparent end destination; BDNF complexes can be found meandering over long distances of several microns throughout the expanse of the neuronal soma in a circuitous fashion. The complex, heterogeneous nature of neuronal soma trafficking dynamics contrasts the reported linear nature of axonal transport data and calls for models that surpass our generally limited notions of nuclear-directed transport in the soma. QD-ligand probes are poised to provide understanding of how the molecular mechanisms underlying intracellular ligand-receptor trafficking shape cell signaling under conditions of both healthy and dysfunctional neurological disease models. PMID:24732948

Molecular organization and dynamics of micellar phase of polyelectrolyte-surfactant complexes: ESR spin probe study

NASA Astrophysics Data System (ADS)

Wasserman, A. M.; Kasaikin, V. A.; Zakharova, Yu. A.; Aliev, I. I.; Baranovsky, V. Yu.; Doseva, V.; Yasina, L. L.

2002-04-01

Molecular dynamics and organization of the micellar phase of complexes of linear polyelectrolytes with ionogenic and non-ionogenic surfactants was studied by the ESR spin probe method. Complexes of polyacrylic acid (PAA) and sodium polystyrenesulfonate (PSS) with alkyltrimethylammonium bromides (ATAB), as well as complexes of poly- N, N'-dimethyldiallylammonium chloride (PDACL) with sodium dodecylsulfate (SDS) were studied. The micellar phase of such complexes is highly organized molecular system, molecular ordering of which near the polymeric chain is much higher than in the 'center' of the micelle, it depends on the polymer-detergent interaction, flexibility of polymeric chain and length of carbonic part of the detergent molecule. Complexes of polymethacrylic acid (PMAA) with non-ionic detergent (dodecyl-substituted polyethyleneglycol), show that the local mobility of surfactant in such complexes is significantly lower than in 'free' micelles and depends on the number of micellar particles participating in formation of complexes.

Intramolecular Hydrogen Bonding Restricts Gd-Aqua-Ligand Dynamics [The Day the Water Stood Still: Intramolecular Hydrogen Bonding to Restrict Gd-Aqua Ligand Dynamics

DOE PAGES

Boros, Eszter; Srinivas, Raja; Kim, Hee -Kyung; ...

2017-04-11

Aqua ligands can undergo rapid internal rotation about the M-O bond. For magnetic resonance contrast agents, this rotation results in diminished relaxivity. Herein, we show that an intramolecular hydrogen bond to the aqua ligand can reduce this internal rotation and increase relaxivity. Molecular modeling was used to design a series of four Gd complexes capable of forming an intramolecular H-bond to the coordinated water ligand, and these complexes had anomalously high relaxivities compared to similar complexes lacking a H-bond acceptor. Molecular dynamics simulations supported the formation of a stable intramolecular H-bond, while alternative hypotheses that could explain the higher relaxivitymore » were systematically ruled out. Finally, intramolecular H-bonding represents a useful strategy to limit internal water rotational motion and increase relaxivity of Gd complexes.« less

Dynamics of water around the complex structures formed between the KH domains of far upstream element binding protein and single-stranded DNA molecules

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

Chakraborty, Kaushik; Bandyopadhyay, Sanjoy, E-mail: sanjoy@chem.iitkgp.ernet.in

2015-07-28

Single-stranded DNA (ss-DNA) binding proteins specifically bind to the single-stranded regions of the DNA and protect it from premature annealing, thereby stabilizing the DNA structure. We have carried out atomistic molecular dynamics simulations of the aqueous solutions of two DNA binding K homology (KH) domains (KH3 and KH4) of the far upstream element binding protein complexed with two short ss-DNA segments. Attempts have been made to explore the influence of the formation of such complex structures on the microscopic dynamics and hydrogen bond properties of the interfacial water molecules. It is found that the water molecules involved in bridging themore » ss-DNA segments and the protein domains form a highly constrained thin layer with extremely retarded mobility. These water molecules play important roles in freezing the conformational oscillations of the ss-DNA oligomers and thereby forming rigid complex structures. Further, it is demonstrated that the effect of complexation on the slow long-time relaxations of hydrogen bonds at the interface is correlated with hindered motions of the surrounding water molecules. Importantly, it is observed that the highly restricted motions of the water molecules bridging the protein and the DNA components in the complexed forms originate from more frequent hydrogen bond reformations.« less

Modeling and simulation of dynamic ant colony's labor division for task allocation of UAV swarm

NASA Astrophysics Data System (ADS)

Wu, Husheng; Li, Hao; Xiao, Renbin; Liu, Jie

2018-02-01

The problem of unmanned aerial vehicle (UAV) task allocation not only has the intrinsic attribute of complexity, such as highly nonlinear, dynamic, highly adversarial and multi-modal, but also has a better practicability in various multi-agent systems, which makes it more and more attractive recently. In this paper, based on the classic fixed response threshold model (FRTM), under the idea of "problem centered + evolutionary solution" and by a bottom-up way, the new dynamic environmental stimulus, response threshold and transition probability are designed, and a dynamic ant colony's labor division (DACLD) model is proposed. DACLD allows a swarm of agents with a relatively low-level of intelligence to perform complex tasks, and has the characteristic of distributed framework, multi-tasks with execution order, multi-state, adaptive response threshold and multi-individual response. With the proposed model, numerical simulations are performed to illustrate the effectiveness of the distributed task allocation scheme in two situations of UAV swarm combat (dynamic task allocation with a certain number of enemy targets and task re-allocation due to unexpected threats). Results show that our model can get both the heterogeneous UAVs' real-time positions and states at the same time, and has high degree of self-organization, flexibility and real-time response to dynamic environments.

iMarNet: an ocean biogeochemistry model inter-comparison project within a common physical ocean modelling framework

NASA Astrophysics Data System (ADS)

Kwiatkowski, L.; Yool, A.; Allen, J. I.; Anderson, T. R.; Barciela, R.; Buitenhuis, E. T.; Butenschön, M.; Enright, C.; Halloran, P. R.; Le Quéré, C.; de Mora, L.; Racault, M.-F.; Sinha, B.; Totterdell, I. J.; Cox, P. M.

2014-07-01

Ocean biogeochemistry (OBGC) models span a wide range of complexities from highly simplified, nutrient-restoring schemes, through nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, through to models that represent a broader trophic structure by grouping organisms as plankton functional types (PFT) based on their biogeochemical role (Dynamic Green Ocean Models; DGOM) and ecosystem models which group organisms by ecological function and trait. OBGC models are now integral components of Earth System Models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here, we present an inter-comparison of six OBGC models that were candidates for implementation within the next UK Earth System Model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the Nucleus for the European Modelling of the Ocean (NEMO) ocean general circulation model (GCM), and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform or underperform all other models across all metrics. Nonetheless, the simpler models that are easier to tune are broadly closer to observations across a number of fields, and thus offer a high-efficiency option for ESMs that prioritise high resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low resolution climate dynamics and high complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry-climate interactions.

iMarNet: an ocean biogeochemistry model intercomparison project within a common physical ocean modelling framework

NASA Astrophysics Data System (ADS)

Kwiatkowski, L.; Yool, A.; Allen, J. I.; Anderson, T. R.; Barciela, R.; Buitenhuis, E. T.; Butenschön, M.; Enright, C.; Halloran, P. R.; Le Quéré, C.; de Mora, L.; Racault, M.-F.; Sinha, B.; Totterdell, I. J.; Cox, P. M.

2014-12-01

Ocean biogeochemistry (OBGC) models span a wide variety of complexities, including highly simplified nutrient-restoring schemes, nutrient-phytoplankton-zooplankton-detritus (NPZD) models that crudely represent the marine biota, models that represent a broader trophic structure by grouping organisms as plankton functional types (PFTs) based on their biogeochemical role (dynamic green ocean models) and ecosystem models that group organisms by ecological function and trait. OBGC models are now integral components of Earth system models (ESMs), but they compete for computing resources with higher resolution dynamical setups and with other components such as atmospheric chemistry and terrestrial vegetation schemes. As such, the choice of OBGC in ESMs needs to balance model complexity and realism alongside relative computing cost. Here we present an intercomparison of six OBGC models that were candidates for implementation within the next UK Earth system model (UKESM1). The models cover a large range of biological complexity (from 7 to 57 tracers) but all include representations of at least the nitrogen, carbon, alkalinity and oxygen cycles. Each OBGC model was coupled to the ocean general circulation model Nucleus for European Modelling of the Ocean (NEMO) and results from physically identical hindcast simulations were compared. Model skill was evaluated for biogeochemical metrics of global-scale bulk properties using conventional statistical techniques. The computing cost of each model was also measured in standardised tests run at two resource levels. No model is shown to consistently outperform all other models across all metrics. Nonetheless, the simpler models are broadly closer to observations across a number of fields and thus offer a high-efficiency option for ESMs that prioritise high-resolution climate dynamics. However, simpler models provide limited insight into more complex marine biogeochemical processes and ecosystem pathways, and a parallel approach of low-resolution climate dynamics and high-complexity biogeochemistry is desirable in order to provide additional insights into biogeochemistry-climate interactions.

Functional complexity emerging from anatomical constraints in the brain: the significance of network modularity and rich-clubs

NASA Astrophysics Data System (ADS)

Zamora-López, Gorka; Chen, Yuhan; Deco, Gustavo; Kringelbach, Morten L.; Zhou, Changsong

2016-12-01

The large-scale structural ingredients of the brain and neural connectomes have been identified in recent years. These are, similar to the features found in many other real networks: the arrangement of brain regions into modules and the presence of highly connected regions (hubs) forming rich-clubs. Here, we examine how modules and hubs shape the collective dynamics on networks and we find that both ingredients lead to the emergence of complex dynamics. Comparing the connectomes of C. elegans, cats, macaques and humans to surrogate networks in which either modules or hubs are destroyed, we find that functional complexity always decreases in the perturbed networks. A comparison between simulated and empirically obtained resting-state functional connectivity indicates that the human brain, at rest, lies in a dynamical state that reflects the largest complexity its anatomical connectome can host. Last, we generalise the topology of neural connectomes into a new hierarchical network model that successfully combines modular organisation with rich-club forming hubs. This is achieved by centralising the cross-modular connections through a preferential attachment rule. Our network model hosts more complex dynamics than other hierarchical models widely used as benchmarks.

Functional complexity emerging from anatomical constraints in the brain: the significance of network modularity and rich-clubs

PubMed Central

Zamora-López, Gorka; Chen, Yuhan; Deco, Gustavo; Kringelbach, Morten L.; Zhou, Changsong

2016-01-01

The large-scale structural ingredients of the brain and neural connectomes have been identified in recent years. These are, similar to the features found in many other real networks: the arrangement of brain regions into modules and the presence of highly connected regions (hubs) forming rich-clubs. Here, we examine how modules and hubs shape the collective dynamics on networks and we find that both ingredients lead to the emergence of complex dynamics. Comparing the connectomes of C. elegans, cats, macaques and humans to surrogate networks in which either modules or hubs are destroyed, we find that functional complexity always decreases in the perturbed networks. A comparison between simulated and empirically obtained resting-state functional connectivity indicates that the human brain, at rest, lies in a dynamical state that reflects the largest complexity its anatomical connectome can host. Last, we generalise the topology of neural connectomes into a new hierarchical network model that successfully combines modular organisation with rich-club forming hubs. This is achieved by centralising the cross-modular connections through a preferential attachment rule. Our network model hosts more complex dynamics than other hierarchical models widely used as benchmarks. PMID:27917958

Deciphering deterioration mechanisms of complex diseases based on the construction of dynamic networks and systems analysis

NASA Astrophysics Data System (ADS)

Li, Yuanyuan; Jin, Suoqin; Lei, Lei; Pan, Zishu; Zou, Xiufen

2015-03-01

The early diagnosis and investigation of the pathogenic mechanisms of complex diseases are the most challenging problems in the fields of biology and medicine. Network-based systems biology is an important technique for the study of complex diseases. The present study constructed dynamic protein-protein interaction (PPI) networks to identify dynamical network biomarkers (DNBs) and analyze the underlying mechanisms of complex diseases from a systems level. We developed a model-based framework for the construction of a series of time-sequenced networks by integrating high-throughput gene expression data into PPI data. By combining the dynamic networks and molecular modules, we identified significant DNBs for four complex diseases, including influenza caused by either H3N2 or H1N1, acute lung injury and type 2 diabetes mellitus, which can serve as warning signals for disease deterioration. Function and pathway analyses revealed that the identified DNBs were significantly enriched during key events in early disease development. Correlation and information flow analyses revealed that DNBs effectively discriminated between different disease processes and that dysfunctional regulation and disproportional information flow may contribute to the increased disease severity. This study provides a general paradigm for revealing the deterioration mechanisms of complex diseases and offers new insights into their early diagnoses.

The MYO6 interactome reveals adaptor complexes coordinating early endosome and cytoskeletal dynamics.

PubMed

O'Loughlin, Thomas; Masters, Thomas A; Buss, Folma

2018-04-01

The intracellular functions of myosin motors requires a number of adaptor molecules, which control cargo attachment, but also fine-tune motor activity in time and space. These motor-adaptor-cargo interactions are often weak, transient or highly regulated. To overcome these problems, we use a proximity labelling-based proteomics strategy to map the interactome of the unique minus end-directed actin motor MYO6. Detailed biochemical and functional analysis identified several distinct MYO6-adaptor modules including two complexes containing RhoGEFs: the LIFT (LARG-Induced F-actin for Tethering) complex that controls endosome positioning and motility through RHO-driven actin polymerisation; and the DISP (DOCK7-Induced Septin disPlacement) complex, a novel regulator of the septin cytoskeleton. These complexes emphasise the role of MYO6 in coordinating endosome dynamics and cytoskeletal architecture. This study provides the first in vivo interactome of a myosin motor protein and highlights the power of this approach in uncovering dynamic and functionally diverse myosin motor complexes. © 2018 The Authors. Published under the terms of the CC BY 4.0 license.

Reactive immunization on complex networks

NASA Astrophysics Data System (ADS)

Alfinito, Eleonora; Beccaria, Matteo; Fachechi, Alberto; Macorini, Guido

2017-01-01

Epidemic spreading on complex networks depends on the topological structure as well as on the dynamical properties of the infection itself. Generally speaking, highly connected individuals play the role of hubs and are crucial to channel information across the network. On the other hand, static topological quantities measuring the connectivity structure are independent of the dynamical mechanisms of the infection. A natural question is therefore how to improve the topological analysis by some kind of dynamical information that may be extracted from the ongoing infection itself. In this spirit, we propose a novel vaccination scheme that exploits information from the details of the infection pattern at the moment when the vaccination strategy is applied. Numerical simulations of the infection process show that the proposed immunization strategy is effective and robust on a wide class of complex networks.

Single molecule tracking fluorescence microscopy in mitochondria reveals highly dynamic but confined movement of Tom40

NASA Astrophysics Data System (ADS)

Kuzmenko, Anton; Tankov, Stoyan; English, Brian P.; Tarassov, Ivan; Tenson, Tanel; Kamenski, Piotr; Elf, Johan; Hauryliuk, Vasili

2011-12-01

Tom40 is an integral protein of the mitochondrial outer membrane, which as the central component of the Translocase of the Outer Membrane (TOM) complex forms a channel for protein import. We characterize the diffusion properties of individual Tom40 molecules fused to the photoconvertable fluorescent protein Dendra2 with millisecond temporal resolution. By imaging individual Tom40 molecules in intact isolated yeast mitochondria using photoactivated localization microscopy with sub-diffraction limited spatial precision, we demonstrate that Tom40 movement in the outer mitochondrial membrane is highly dynamic but confined in nature, suggesting anchoring of the TOM complex as a whole.

Directional RNA-seq reveals highly complex condition-dependent transcriptomes in E. coli K12 through accurate full-length transcripts assembling.

PubMed

Li, Shan; Dong, Xia; Su, Zhengchang

2013-07-30

Although prokaryotic gene transcription has been studied over decades, many aspects of the process remain poorly understood. Particularly, recent studies have revealed that transcriptomes in many prokaryotes are far more complex than previously thought. Genes in an operon are often alternatively and dynamically transcribed under different conditions, and a large portion of genes and intergenic regions have antisense RNA (asRNA) and non-coding RNA (ncRNA) transcripts, respectively. Ironically, similar studies have not been conducted in the model bacterium E coli K12, thus it is unknown whether or not the bacterium possesses similar complex transcriptomes. Furthermore, although RNA-seq becomes the major method for analyzing the complexity of prokaryotic transcriptome, it is still a challenging task to accurately assemble full length transcripts using short RNA-seq reads. To fill these gaps, we have profiled the transcriptomes of E. coli K12 under different culture conditions and growth phases using a highly specific directional RNA-seq technique that can capture various types of transcripts in the bacterial cells, combined with a highly accurate and robust algorithm and tool TruHMM (http://bioinfolab.uncc.edu/TruHmm_package/) for assembling full length transcripts. We found that 46.9 ~ 63.4% of expressed operons were utilized in their putative alternative forms, 72.23 ~ 89.54% genes had putative asRNA transcripts and 51.37 ~ 72.74% intergenic regions had putative ncRNA transcripts under different culture conditions and growth phases. As has been demonstrated in many other prokaryotes, E. coli K12 also has a highly complex and dynamic transcriptomes under different culture conditions and growth phases. Such complex and dynamic transcriptomes might play important roles in the physiology of the bacterium. TruHMM is a highly accurate and robust algorithm for assembling full-length transcripts in prokaryotes using directional RNA-seq short reads.

Directional RNA-seq reveals highly complex condition-dependent transcriptomes in E. coli K12 through accurate full-length transcripts assembling

PubMed Central

2013-01-01

Background Although prokaryotic gene transcription has been studied over decades, many aspects of the process remain poorly understood. Particularly, recent studies have revealed that transcriptomes in many prokaryotes are far more complex than previously thought. Genes in an operon are often alternatively and dynamically transcribed under different conditions, and a large portion of genes and intergenic regions have antisense RNA (asRNA) and non-coding RNA (ncRNA) transcripts, respectively. Ironically, similar studies have not been conducted in the model bacterium E coli K12, thus it is unknown whether or not the bacterium possesses similar complex transcriptomes. Furthermore, although RNA-seq becomes the major method for analyzing the complexity of prokaryotic transcriptome, it is still a challenging task to accurately assemble full length transcripts using short RNA-seq reads. Results To fill these gaps, we have profiled the transcriptomes of E. coli K12 under different culture conditions and growth phases using a highly specific directional RNA-seq technique that can capture various types of transcripts in the bacterial cells, combined with a highly accurate and robust algorithm and tool TruHMM (http://bioinfolab.uncc.edu/TruHmm_package/) for assembling full length transcripts. We found that 46.9 ~ 63.4% of expressed operons were utilized in their putative alternative forms, 72.23 ~ 89.54% genes had putative asRNA transcripts and 51.37 ~ 72.74% intergenic regions had putative ncRNA transcripts under different culture conditions and growth phases. Conclusions As has been demonstrated in many other prokaryotes, E. coli K12 also has a highly complex and dynamic transcriptomes under different culture conditions and growth phases. Such complex and dynamic transcriptomes might play important roles in the physiology of the bacterium. TruHMM is a highly accurate and robust algorithm for assembling full-length transcripts in prokaryotes using directional RNA-seq short reads. PMID:23899370

A study on the anisole-water complex by molecular beam-electronic spectroscopy and molecular mechanics calculations.

PubMed

Becucci, M; Pietraperzia, G; Pasquini, M; Piani, G; Zoppi, A; Chelli, R; Castellucci, E; Demtroeder, W

2004-03-22

An experimental and theoretical study is made on the anisole-water complex. It is the first van der Waals complex studied by high resolution electronic spectroscopy in which the water is seen acting as an acid. Vibronically and rotationally resolved electronic spectroscopy experiments and molecular mechanics calculations are used to elucidate the structure of the complex in the ground and first electronic excited state. Some internal dynamics in the system is revealed by high resolution spectroscopy. (c) 2004 American Institute of Physics

Cryo-EM of dynamic protein complexes in eukaryotic DNA replication.

PubMed

Sun, Jingchuan; Yuan, Zuanning; Bai, Lin; Li, Huilin

2017-01-01

DNA replication in Eukaryotes is a highly dynamic process that involves several dozens of proteins. Some of these proteins form stable complexes that are amenable to high-resolution structure determination by cryo-EM, thanks to the recent advent of the direct electron detector and powerful image analysis algorithm. But many of these proteins associate only transiently and flexibly, precluding traditional biochemical purification. We found that direct mixing of the component proteins followed by 2D and 3D image sorting can capture some very weakly interacting complexes. Even at 2D average level and at low resolution, EM images of these flexible complexes can provide important biological insights. It is often necessary to positively identify the feature-of-interest in a low resolution EM structure. We found that systematically fusing or inserting maltose binding protein (MBP) to selected proteins is highly effective in these situations. In this chapter, we describe the EM studies of several protein complexes involved in the eukaryotic DNA replication over the past decade or so. We suggest that some of the approaches used in these studies may be applicable to structural analysis of other biological systems. © 2016 The Protein Society.

Conformational dynamics of bacterial trigger factor in apo and ribosome-bound states.

PubMed

Can, Mehmet Tarik; Kurkcuoglu, Zeynep; Ezeroglu, Gokce; Uyar, Arzu; Kurkcuoglu, Ozge; Doruker, Pemra

2017-01-01

The chaperone trigger factor (TF) binds to the ribosome exit tunnel and helps cotranslational folding of nascent chains (NC) in bacterial cells and chloroplasts. In this study, we aim to investigate the functional dynamics of fully-atomistic apo TF and its complex with 50S. As TF accomodates a high percentage of charged residues on its surface, the effect of ionic strength on TF dynamics is assessed here by performing five independent molecular dynamics (MD) simulations (total of 1.3 micro-second duration) at 29 mM and 150 mM ionic strengths. At both concentrations, TF exhibits high inter- and intra-domain flexibility related to its binding (BD), core (CD), and head (HD) domains. Even though large oscillations in gyration radius exist during each run, we do not detect the so-called 'fully collapsed' state with both HD and BD collapsed upon the core. In fact, the extended conformers with relatively open HD and BD are highly populated at the physiological concentration of 150 mM. More importantly, extended TF snapshots stand out in terms of favorable docking onto the 50S subunit. Elastic network modeling (ENM) indicates significant changes in TF's functional dynamics and domain decomposition depending on its conformation and positioning on the 50S. The most dominant slow motions are the lateral sweeping and vertical opening/closing of HD relative to 50S. Finally, our ENM-based efficient technique -ClustENM- is used to sample atomistic conformers starting with an extended TF-50S complex. Specifically, BD and CD motions are restricted near the tunnel exit, while HD is highly mobile. The atomistic conformers generated without an NC are in agreement with the cryo-EM maps available for TF-ribosome-NC complex.

Does Leisure Time as a Stress Coping Resource Increase Affective Complexity? Applying the Dynamic Model of Affect (DMA).

PubMed

Qian, Xinyi Lisa; Yarnal, Careen M; Almeida, David M

2013-01-01

Affective complexity, a manifestation of psychological well-being, refers to the relative independence between positive and negative affect (PA, NA). According to the Dynamic Model of Affect (DMA), stressful situations lead to highly inverse PA-NA relationship, reducing affective complexity. Meanwhile, positive events can sustain affective complexity by restoring PA-NA independence. Leisure, a type of positive events, has been identified as a coping resource. This study used the DMA to assess whether leisure time helps restore affective complexity on stressful days. We found that on days with more leisure time than usual, an individual experienced less negative PA-NA relationship after daily stressful events. The finding demonstrates the value of leisure time as a coping resource and the DMA's contribution to coping research.

Magnetic storms and solar flares: can be analysed within similar mathematical framework with other extreme events?

NASA Astrophysics Data System (ADS)

Balasis, Georgios; Potirakis, Stelios M.; Papadimitriou, Constantinos; Zitis, Pavlos I.; Eftaxias, Konstantinos

2015-04-01

The field of study of complex systems considers that the dynamics of complex systems are founded on universal principles that may be used to describe a great variety of scientific and technological approaches of different types of natural, artificial, and social systems. We apply concepts of the nonextensive statistical physics, on time-series data of observable manifestations of the underlying complex processes ending up to different extreme events, in order to support the suggestion that a dynamical analogy characterizes the generation of a single magnetic storm, solar flare, earthquake (in terms of pre-seismic electromagnetic signals) , epileptic seizure, and economic crisis. The analysis reveals that all the above mentioned different extreme events can be analyzed within similar mathematical framework. More precisely, we show that the populations of magnitudes of fluctuations included in all the above mentioned pulse-like-type time series follow the traditional Gutenberg-Richter law as well as a nonextensive model for earthquake dynamics, with similar nonextensive q-parameter values. Moreover, based on a multidisciplinary statistical analysis we show that the extreme events are characterized by crucial common symptoms, namely: (i) high organization, high compressibility, low complexity, high information content; (ii) strong persistency; and (iii) existence of clear preferred direction of emerged activities. These symptoms clearly discriminate the appearance of the extreme events under study from the corresponding background noise.

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

NASA Astrophysics Data System (ADS)

Pezard, Laurent

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

Integrative Perspectives of Academic Motivation

NASA Astrophysics Data System (ADS)

Chittum, Jessica Rebecca

My overall objective in this dissertation was to develop more integrative perspectives of several aspects of academic motivation. Rarely have researchers and theorists examined a more comprehensive model of academic motivation that pools multiple constructs that interact in a complex and dynamic fashion (Kaplan, Katz, & Flum, 2012; Turner, Christensen, Kackar-Cam, Trucano, & Fulmer, 2014). The more common trend in motivation research and theory has been to identify and explain only a few motivation constructs and their linear relationships rather than examine complex relationships involving "continuously emerging systems of dynamically interrelated components" (Kaplan et al., 2014, para. 4). In this dissertation, my co-author and I focused on a more integrative perspective of academic motivation by first reviewing varying characterizations of one motivation construct (Manuscript 1) and then empirically testing dynamic interactions among multiple motivation constructs using a person-centered methodological approach (Manuscript 2). Within the first manuscript (Chapter 2), a theoretical review paper, we summarized multiple perspectives of the need for autonomy and similar constructs in academic motivation, primarily autonomy in self-determination theory, autonomy supports, and choice. We provided an integrative review and extrapolated practical teaching implications. We concluded with recommendations for researchers and instructors, including a call for more integrated perspectives of academic motivation and autonomy that focus on complex and dynamic patterns in individuals' motivational beliefs. Within the second manuscript (Chapter 3), we empirically investigated students' motivation in science class as a complex, dynamic, and context-bound phenomenon that incorporates multiple motivation constructs. Following a person-centered approach, we completed cluster analyses of students' perceptions of 5 well-known motivation constructs (autonomy, utility value, expectancy, interest, and caring) in science class to determine whether or not the students grouped into meaningful "motivation profiles." 5 stable profiles emerged: (1) low motivation; (2) low value and high support; (3) somewhat high motivation; (4) somewhat high empowerment and values, and high support; and (5) high motivation. As this study serves as a proof of concept, we concluded by describing the 5 clusters. Together, these studies represent a focus on more integrative and person-centered approaches to studying and understanding academic motivation.

Dynamics and Novel Mechanisms of SN2 Reactions on ab Initio Analytical Potential Energy Surfaces.

PubMed

Szabó, István; Czakó, Gábor

2017-11-30

We describe a novel theoretical approach to the bimolecular nucleophilic substitution (S N 2) reactions that is based on analytical potential energy surfaces (PESs) obtained by fitting a few tens of thousands high-level ab initio energy points. These PESs allow computing millions of quasi-classical trajectories thereby providing unprecedented statistical accuracy for S N 2 reactions, as well as performing high-dimensional quantum dynamics computations. We developed full-dimensional ab initio PESs for the F - + CH 3 Y [Y = F, Cl, I] systems, which describe the direct and indirect, complex-forming Walden-inversion, the frontside attack, and the new double-inversion pathways as well as the proton-transfer channels. Reaction dynamics simulations on the new PESs revealed (a) a novel double-inversion S N 2 mechanism, (b) frontside complex formation, (c) the dynamics of proton transfer, (d) vibrational and rotational mode specificity, (e) mode-specific product vibrational distributions, (f) agreement between classical and quantum dynamics, (g) good agreement with measured scattering angle and product internal energy distributions, and (h) significant leaving group effect in accord with experiments.

Constitutive equations for multiphase TRIP steels at high rates of strain

NASA Astrophysics Data System (ADS)

van Slycken, J.; Verleysen, P.; Degrieck, J.; Bouquerel, J.

2006-08-01

Multiphase TRansformation Induced Plasticity (TRIP) steels show an excellent combination of high strength and high strain values, making them ideally suited for use in vehicle body structures. A complex synergy of three different phases (ferrite, bainite and austenite) on the one hand, and the meta-stable character of the austenite on the other hand, give the material indeed a high energy absorption potential. The knowledge and understanding of the dynamic behaviour of these sheet steels is essential to investigate the impact-dynamic characteristics of the structures. Therefore split Hopkinson tensile tests are performed in a strain rate range of 500 to 2000 s-1. Three TRIP steel grades with a different Al and Si content were studied. The experimental results show that these steels preserve their excellent shock-absorbing properties in dynamic conditions. The typical high strain rate loading conditions and the complex behaviour of TRIP steels offer a unique investigation opportunity. This behaviour can be described with phenomenological material models that can be used for numerical simulations of car crashes. The Johnson-Cook model, a frequently used model in finite element codes, is well-suited to describe the dynamic behaviour of the investigated TRIP steels. This model is compared to the Rusinek-Klepaczko model.

A frequency averaging framework for the solution of complex dynamic systems

PubMed Central

Lecomte, Christophe

2014-01-01

A frequency averaging framework is proposed for the solution of complex linear dynamic systems. It is remarkable that, while the mid-frequency region is usually very challenging, a smooth transition from low- through mid- and high-frequency ranges is possible and all ranges can now be considered in a single framework. An interpretation of the frequency averaging in the time domain is presented and it is explained that the average may be evaluated very efficiently in terms of system solutions. PMID:24910518

Revealing physical interaction networks from statistics of collective dynamics

PubMed Central

Nitzan, Mor; Casadiego, Jose; Timme, Marc

2017-01-01

Revealing physical interactions in complex systems from observed collective dynamics constitutes a fundamental inverse problem in science. Current reconstruction methods require access to a system’s model or dynamical data at a level of detail often not available. We exploit changes in invariant measures, in particular distributions of sampled states of the system in response to driving signals, and use compressed sensing to reveal physical interaction networks. Dynamical observations following driving suffice to infer physical connectivity even if they are temporally disordered, are acquired at large sampling intervals, and stem from different experiments. Testing various nonlinear dynamic processes emerging on artificial and real network topologies indicates high reconstruction quality for existence as well as type of interactions. These results advance our ability to reveal physical interaction networks in complex synthetic and natural systems. PMID:28246630

Transposable elements as a molecular evolutionary force

NASA Technical Reports Server (NTRS)

Fedoroff, N. V.

1999-01-01

This essay addresses the paradoxes of the complex and highly redundant genomes. The central theses developed are that: (1) the distinctive feature of complex genomes is the existence of epigenetic mechanisms that permit extremely high levels of both tandem and dispersed redundancy; (2) the special contribution of transposable elements is to modularize the genome; and (3) the labilizing forces of recombination and transposition are just barely contained, giving a dynamic genetic system of ever increasing complexity that verges on the chaotic.

Single-Molecule Interfacial Electron Transfer

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

Lu, H. Peter

This project is focused on the use of single-molecule high spatial and temporal resolved techniques to study molecular dynamics in condensed phase and at interfaces, especially, the complex reaction dynamics associated with electron and energy transfer rate processes. The complexity and inhomogeneity of the interfacial ET dynamics often present a major challenge for a molecular level comprehension of the intrinsically complex systems, which calls for both higher spatial and temporal resolutions at ultimate single-molecule and single-particle sensitivities. Combined single-molecule spectroscopy and electrochemical atomic force microscopy approaches are unique for heterogeneous and complex interfacial electron transfer systems because the static andmore » dynamic inhomogeneities can be identified and characterized by studying one molecule at a specific nanoscale surface site at a time. The goal of our project is to integrate and apply these spectroscopic imaging and topographic scanning techniques to measure the energy flow and electron flow between molecules and substrate surfaces as a function of surface site geometry and molecular structure. We have been primarily focusing on studying interfacial electron transfer under ambient condition and electrolyte solution involving both single crystal and colloidal TiO 2 and related substrates. The resulting molecular level understanding of the fundamental interfacial electron transfer processes will be important for developing efficient light harvesting systems and broadly applicable to problems in fundamental chemistry and physics. We have made significant advancement on deciphering the underlying mechanism of the complex and inhomogeneous interfacial electron transfer dynamics in dyesensitized TiO 2 nanoparticle systems that strongly involves with and regulated by molecule-surface interactions. We have studied interfacial electron transfer on TiO 2 nanoparticle surfaces by using ultrafast single-molecule spectroscopy and electrochemical AFM metal tip scanning microscopy, focusing on understanding the interfacial electron transfer dynamics at specific nanoscale electron transfer sites with high-spatially and temporally resolved topographic-and-spectroscopic characterization at individual molecule basis, characterizing single-molecule rate processes, reaction driving force, and molecule-substrate electronic coupling. One of the most significant characteristics of our new approach is that we are able to interrogate the complex interfacial electron transfer dynamics by actively pin-point energetic manipulation of the surface interaction and electronic couplings, beyond the conventional excitation and observation.« less

Simulation of the Vortex Dynamics in a Real Pinning Landscape of YBa 2 Cu 3 O 7 - δ Coated Conductors

DOE PAGES

Sadovskyy, I. A.; Koshelev, A. E.; Glatz, A.; ...

2016-01-01

The ability of high-temperature superconductors (HTSs) to carry very large currents with almost no dissipation makes them irreplaceable for high-power applications. The development and further improvement of HTS-based cables require an in-depth understanding of the superconducting vortex dynamics in the presence of complex pinning landscapes. We present a critical current analysis of a real HTS sample in a magnetic field by combining state-of-the-art large-scale Ginzburg-Landau simulations with reconstructive three-dimensional scanning-transmission-electron-microscopy tomography of the pinning landscape in Dy-doped YBa 2Cu 3O 7-δ. This methodology provides a unique look at the vortex dynamics in the presence of a complex pinning landscape responsiblemore » for the high-current-carrying-capacity characteristic of commercial HTS wires. Finally, our method demonstrates very good functional and quantitative agreement of the critical current between simulation and experiment, providing a new predictive tool for HTS wire designs.« less

Simulation of the Vortex Dynamics in a Real Pinning Landscape of YBa 2 Cu 3 O 7 - δ Coated Conductors

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

Sadovskyy, I. A.; Koshelev, A. E.; Glatz, A.

The ability of high-temperature superconductors (HTSs) to carry very large currents with almost no dissipation makes them irreplaceable for high-power applications. The development and further improvement of HTS-based cables require an in-depth understanding of the superconducting vortex dynamics in the presence of complex pinning landscapes. We present a critical current analysis of a real HTS sample in a magnetic field by combining state-of-the-art large-scale Ginzburg-Landau simulations with reconstructive three-dimensional scanning-transmission-electron-microscopy tomography of the pinning landscape in Dy-doped YBa 2Cu 3O 7-δ. This methodology provides a unique look at the vortex dynamics in the presence of a complex pinning landscape responsiblemore » for the high-current-carrying-capacity characteristic of commercial HTS wires. Finally, our method demonstrates very good functional and quantitative agreement of the critical current between simulation and experiment, providing a new predictive tool for HTS wire designs.« less

Simulation of the Vortex Dynamics in a Real Pinning Landscape of YBa 2 Cu 3 O 7 - δ Coated Conductors

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

Sadovskyy, I. A.; Koshelev, A. E.; Glatz, A.

Tmore » he ability of high-temperature superconductors (HSs) to carry very large currents with almost no dissipation makes them irreplaceable for high-power applications. he development and further improvement of HS-based cables require an in-depth understanding of the superconducting vortex dynamics in the presence of complex pinning landscapes. Here, we present a critical current analysis of a real HS sample in a magnetic field by combining state-of-the-art large-scale Ginzburg-Landau simulations with reconstructive three-dimensional scanning-transmission-electron-microscopy tomography of the pinning landscape in Dy-doped YBa 2 Cu 3 O 7 - δ . his methodology provides a unique look at the vortex dynamics in the presence of a complex pinning landscape responsible for the high-current-carrying-capacity characteristic of commercial HS wires. Our method demonstrates very good functional and quantitative agreement of the critical current between simulation and experiment, providing a new predictive tool for HS wire designs.« less

Improving Ecological Forecasting: Data Assimilation Enhances the Ecological Forecast Horizon of a Complex Food Web

NASA Astrophysics Data System (ADS)

Massoud, E. C.; Huisman, J.; Benincà, E.; Bouten, W.; Vrugt, J. A.

2017-12-01

Species abundances in ecological communities can display chaotic non-equilibrium dynamics. A characteristic feature of chaotic systems is that long-term prediction of the system's trajectory is fundamentally impossible. How then should we make predictions for complex multi-species communities? We explore data assimilation (DA) with the Ensemble Kalman Filter (EnKF) to fuse a two-predator-two-prey model with abundance data from a long term experiment of a plankton community which displays chaotic dynamics. The results show that DA improves substantially the predictability and ecological forecast horizon of complex community dynamics. In addition, we show that DA helps provide guidance on measurement design, for instance on defining the frequency of observations. The study presented here is highly innovative, because DA methods at the current stage are almost unknown in ecology.

Applications of fidelity measures to complex quantum systems

PubMed Central

2016-01-01

We revisit fidelity as a measure for the stability and the complexity of the quantum motion of single-and many-body systems. Within the context of cold atoms, we present an overview of applications of two fidelities, which we call static and dynamical fidelity, respectively. The static fidelity applies to quantum problems which can be diagonalized since it is defined via the eigenfunctions. In particular, we show that the static fidelity is a highly effective practical detector of avoided crossings characterizing the complexity of the systems and their evolutions. The dynamical fidelity is defined via the time-dependent wave functions. Focusing on the quantum kicked rotor system, we highlight a few practical applications of fidelity measurements in order to better understand the large variety of dynamical regimes of this paradigm of a low-dimensional system with mixed regular–chaotic phase space. PMID:27140967

Deciphering complex dynamics of water counteraction around secondary structural elements of allosteric protein complex: Case study of SAP-SLAM system in signal transduction cascade

NASA Astrophysics Data System (ADS)

Samanta, Sudipta; Mukherjee, Sanchita

2018-01-01

The first hydration shell of a protein exhibits heterogeneous behavior owing to several attributes, majorly local polarity and structural flexibility as revealed by solvation dynamics of secondary structural elements. We attempt to recognize the change in complex water counteraction generated due to substantial alteration in flexibility during protein complex formation. The investigation is carried out with the signaling lymphocytic activation molecule (SLAM) family of receptors, expressed by an array of immune cells, and interacting with SLAM-associated protein (SAP), composed of one SH2 domain. All atom molecular dynamics simulations are employed to the aqueous solutions of free SAP and SLAM-peptide bound SAP. We observed that water dynamics around different secondary structural elements became highly affected as well as nicely correlated with the SLAM-peptide induced change in structural rigidity obtained by thermodynamic quantification. A few instances of contradictory dynamic features of water to the change in structural flexibility are explained by means of occluded polar residues by the peptide. For βD, EFloop, and BGloop, both structural flexibility and solvent accessibility of the residues confirm the obvious contribution. Most importantly, we have quantified enhanced restriction in water dynamics around the second Fyn-binding site of the SAP due to SAP-SLAM complexation, even prior to the presence of Fyn. This observation leads to a novel argument that SLAM induced more restricted water molecules could offer more water entropic contribution during the subsequent Fyn binding and provide enhanced stability to the SAP-Fyn complex in the signaling cascade. Finally, SLAM induced water counteraction around the second binding site of the SAP sheds light on the allosteric property of the SAP, which becomes an integral part of the underlying signal transduction mechanism.

Deciphering complex dynamics of water counteraction around secondary structural elements of allosteric protein complex: Case study of SAP-SLAM system in signal transduction cascade.

PubMed

Samanta, Sudipta; Mukherjee, Sanchita

2018-01-28

The first hydration shell of a protein exhibits heterogeneous behavior owing to several attributes, majorly local polarity and structural flexibility as revealed by solvation dynamics of secondary structural elements. We attempt to recognize the change in complex water counteraction generated due to substantial alteration in flexibility during protein complex formation. The investigation is carried out with the signaling lymphocytic activation molecule (SLAM) family of receptors, expressed by an array of immune cells, and interacting with SLAM-associated protein (SAP), composed of one SH2 domain. All atom molecular dynamics simulations are employed to the aqueous solutions of free SAP and SLAM-peptide bound SAP. We observed that water dynamics around different secondary structural elements became highly affected as well as nicely correlated with the SLAM-peptide induced change in structural rigidity obtained by thermodynamic quantification. A few instances of contradictory dynamic features of water to the change in structural flexibility are explained by means of occluded polar residues by the peptide. For βD, EFloop, and BGloop, both structural flexibility and solvent accessibility of the residues confirm the obvious contribution. Most importantly, we have quantified enhanced restriction in water dynamics around the second Fyn-binding site of the SAP due to SAP-SLAM complexation, even prior to the presence of Fyn. This observation leads to a novel argument that SLAM induced more restricted water molecules could offer more water entropic contribution during the subsequent Fyn binding and provide enhanced stability to the SAP-Fyn complex in the signaling cascade. Finally, SLAM induced water counteraction around the second binding site of the SAP sheds light on the allosteric property of the SAP, which becomes an integral part of the underlying signal transduction mechanism.

Loss of 'complexity' and aging. Potential applications of fractals and chaos theory to senescence

NASA Technical Reports Server (NTRS)

Lipsitz, L. A.; Goldberger, A. L.

1992-01-01

The concept of "complexity," derived from the field of nonlinear dynamics, can be adapted to measure the output of physiologic processes that generate highly variable fluctuations resembling "chaos." We review data suggesting that physiologic aging is associated with a generalized loss of such complexity in the dynamics of healthy organ system function and hypothesize that such loss of complexity leads to an impaired ability to adapt to physiologic stress. This hypothesis is supported by observations showing an age-related loss of complex variability in multiple physiologic processes including cardiovascular control, pulsatile hormone release, and electroencephalographic potentials. If further research supports this hypothesis, measures of complexity based on chaos theory and the related geometric concept of fractals may provide new ways to monitor senescence and test the efficacy of specific interventions to modify the age-related decline in adaptive capacity.

Does Leisure Time as a Stress Coping Resource Increase Affective Complexity? Applying the Dynamic Model of Affect (DMA)

PubMed Central

Qian, Xinyi (Lisa); Yarnal, Careen M.; Almeida, David M.

2013-01-01

Affective complexity, a manifestation of psychological well-being, refers to the relative independence between positive and negative affect (PA, NA). According to the Dynamic Model of Affect (DMA), stressful situations lead to highly inverse PA-NA relationship, reducing affective complexity. Meanwhile, positive events can sustain affective complexity by restoring PA-NA independence. Leisure, a type of positive events, has been identified as a coping resource. This study used the DMA to assess whether leisure time helps restore affective complexity on stressful days. We found that on days with more leisure time than usual, an individual experienced less negative PA-NA relationship after daily stressful events. The finding demonstrates the value of leisure time as a coping resource and the DMA’s contribution to coping research. PMID:24659826

Restricted Complexity Framework for Nonlinear Adaptive Control in Complex Systems

NASA Astrophysics Data System (ADS)

Williams, Rube B.

2004-02-01

Control law adaptation that includes implicit or explicit adaptive state estimation, can be a fundamental underpinning for the success of intelligent control in complex systems, particularly during subsystem failures, where vital system states and parameters can be impractical or impossible to measure directly. A practical algorithm is proposed for adaptive state filtering and control in nonlinear dynamic systems when the state equations are unknown or are too complex to model analytically. The state equations and inverse plant model are approximated by using neural networks. A framework for a neural network based nonlinear dynamic inversion control law is proposed, as an extrapolation of prior developed restricted complexity methodology used to formulate the adaptive state filter. Examples of adaptive filter performance are presented for an SSME simulation with high pressure turbine failure to support extrapolations to adaptive control problems.

Characterizing complex networks through statistics of Möbius transformations

NASA Astrophysics Data System (ADS)

Jaćimović, Vladimir; Crnkić, Aladin

2017-04-01

It is well-known now that dynamics of large populations of globally (all-to-all) coupled oscillators can be reduced to low-dimensional submanifolds (WS transformation and OA ansatz). Marvel et al. (2009) described an intriguing algebraic structure standing behind this reduction: oscillators evolve by the action of the group of Möbius transformations. Of course, dynamics in complex networks of coupled oscillators is highly complex and not reducible. Still, closer look unveils that even in complex networks some (possibly overlapping) groups of oscillators evolve by Möbius transformations. In this paper, we study properties of the network by identifying Möbius transformations in the dynamics of oscillators. This enables us to introduce some new (statistical) concepts that characterize the network. In particular, the notion of coherence of the network (or subnetwork) is proposed. This conceptual approach is meaningful for the broad class of networks, including those with time-delayed, noisy or mixed interactions. In this paper, several simple (random) graphs are studied illustrating the meaning of the concepts introduced in the paper.

Revisiting the Quantum Brain Hypothesis: Toward Quantum (Neuro)biology?

PubMed Central

Jedlicka, Peter

2017-01-01

The nervous system is a non-linear dynamical complex system with many feedback loops. A conventional wisdom is that in the brain the quantum fluctuations are self-averaging and thus functionally negligible. However, this intuition might be misleading in the case of non-linear complex systems. Because of an extreme sensitivity to initial conditions, in complex systems the microscopic fluctuations may be amplified and thereby affect the system’s behavior. In this way quantum dynamics might influence neuronal computations. Accumulating evidence in non-neuronal systems indicates that biological evolution is able to exploit quantum stochasticity. The recent rise of quantum biology as an emerging field at the border between quantum physics and the life sciences suggests that quantum events could play a non-trivial role also in neuronal cells. Direct experimental evidence for this is still missing but future research should address the possibility that quantum events contribute to an extremely high complexity, variability and computational power of neuronal dynamics. PMID:29163041

Revisiting the Quantum Brain Hypothesis: Toward Quantum (Neuro)biology?

PubMed

Jedlicka, Peter

2017-01-01

The nervous system is a non-linear dynamical complex system with many feedback loops. A conventional wisdom is that in the brain the quantum fluctuations are self-averaging and thus functionally negligible. However, this intuition might be misleading in the case of non-linear complex systems. Because of an extreme sensitivity to initial conditions, in complex systems the microscopic fluctuations may be amplified and thereby affect the system's behavior. In this way quantum dynamics might influence neuronal computations. Accumulating evidence in non-neuronal systems indicates that biological evolution is able to exploit quantum stochasticity. The recent rise of quantum biology as an emerging field at the border between quantum physics and the life sciences suggests that quantum events could play a non-trivial role also in neuronal cells. Direct experimental evidence for this is still missing but future research should address the possibility that quantum events contribute to an extremely high complexity, variability and computational power of neuronal dynamics.

Understanding wheel dynamics.

PubMed

Proffitt, D R; Kaiser, M K; Whelan, S M

1990-07-01

In five experiments, assessments were made of people's understandings about the dynamics of wheels. It was found that undergraduates make highly erroneous dynamical judgments about the motions of this commonplace event, both in explicit problem-solving contexts and when viewing ongoing events. These problems were also presented to bicycle racers and high-school physics teachers; both groups were found to exhibit misunderstandings similar to those of naive undergraduates. Findings were related to our account of dynamical event complexity. The essence of this account is that people encounter difficulties when evaluating the dynamics of any mechanical system that has more than one dynamically relevant object parameter. A rotating wheel is multidimensional in this respect: in addition to the motion of its center of mass, its mass distribution is also of dynamical relevance. People do not spontaneously form the essential multidimensional quantities required to adequately evaluate wheel dynamics.

Forecasting transitions in systems with high-dimensional stochastic complex dynamics: a linear stability analysis of the tangled nature model.

PubMed

Cairoli, Andrea; Piovani, Duccio; Jensen, Henrik Jeldtoft

2014-12-31

We propose a new procedure to monitor and forecast the onset of transitions in high-dimensional complex systems. We describe our procedure by an application to the tangled nature model of evolutionary ecology. The quasistable configurations of the full stochastic dynamics are taken as input for a stability analysis by means of the deterministic mean-field equations. Numerical analysis of the high-dimensional stability matrix allows us to identify unstable directions associated with eigenvalues with a positive real part. The overlap of the instantaneous configuration vector of the full stochastic system with the eigenvectors of the unstable directions of the deterministic mean-field approximation is found to be a good early warning of the transitions occurring intermittently.

CellCognition: time-resolved phenotype annotation in high-throughput live cell imaging.

PubMed

Held, Michael; Schmitz, Michael H A; Fischer, Bernd; Walter, Thomas; Neumann, Beate; Olma, Michael H; Peter, Matthias; Ellenberg, Jan; Gerlich, Daniel W

2010-09-01

Fluorescence time-lapse imaging has become a powerful tool to investigate complex dynamic processes such as cell division or intracellular trafficking. Automated microscopes generate time-resolved imaging data at high throughput, yet tools for quantification of large-scale movie data are largely missing. Here we present CellCognition, a computational framework to annotate complex cellular dynamics. We developed a machine-learning method that combines state-of-the-art classification with hidden Markov modeling for annotation of the progression through morphologically distinct biological states. Incorporation of time information into the annotation scheme was essential to suppress classification noise at state transitions and confusion between different functional states with similar morphology. We demonstrate generic applicability in different assays and perturbation conditions, including a candidate-based RNA interference screen for regulators of mitotic exit in human cells. CellCognition is published as open source software, enabling live-cell imaging-based screening with assays that directly score cellular dynamics.

Characterization of Early Partial Seizure Onset: Frequency, Complexity and Entropy

PubMed Central

Jouny, Christophe C.; Bergey, Gregory K.

2011-01-01

Objective A clear classification of partial seizures onset features is not yet established. Complexity and entropy have been very widely used to describe dynamical systems, but a systematic evaluation of these measures to characterize partial seizures has never been performed. Methods Eighteen different measures including power in frequency bands up to 300Hz, Gabor atom density (GAD), Higuchi fractal dimension (HFD), Lempel-Ziv complexity, Shannon entropy, sample entropy, and permutation entropy, were selected to test sensitivity to partial seizure onset. Intracranial recordings from forty-five patients with mesial temporal, neocortical temporal and neocortical extratemporal seizure foci were included (331 partial seizures). Results GAD, Lempel-Ziv complexity, HFD, high frequency activity, and sample entropy were the most reliable measures to assess early seizure onset. Conclusions Increases in complexity and occurrence of high-frequency components appear to be commonly associated with early stages of partial seizure evolution from all regions. The type of measure (frequency-based, complexity or entropy) does not predict the efficiency of the method to detect seizure onset. Significance Differences between measures such as GAD and HFD highlight the multimodal nature of partial seizure onsets. Improved methods for early seizure detection may be achieved from a better understanding of these underlying dynamics. PMID:21872526

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.

Live Theatre: A Dynamic Medium for Engaging with Intercultural Education Research

ERIC Educational Resources Information Center

Nelson, Cynthia D.

2013-01-01

In this paper, I discuss live theatre as a highly effective and dynamic medium for facilitating meaningful engagement with research on intercultural education. I make the case that ethnographic, or research-based, theatre can productively showcase challenging social issues and the sometimes confusing, poignant and humorous complexities of…

Molecular dynamics studies on troponin (TnI-TnT-TnC) complexes: insight into the regulation of muscle contraction.

PubMed

Varughese, Jayson F; Chalovich, Joseph M; Li, Yumin

2010-10-01

Mutations of any subunit of the troponin complex may lead to serious disorders. Rational approaches to managing these disorders require knowledge of the complex interactions among the three subunits that are required for proper function. Molecular dynamics (MD) simulations were performed for both skeletal (sTn) and cardiac (cTn) troponin. The interactions and correlated motions among the three components of the troponin complex were analyzed using both Molecular Mechanics-Generalized Born Surface Area (MMGBSA) and cross-correlation techniques. The TnTH2 helix was strongly positively correlated with the two long helices of TnI. The C domain of TnC was positively correlated with TnI and TnT. The N domain of TnC was negatively correlated with TnI and TnT in cTn, but not in sTn. The two C-domain calcium-binding sites of TnC were dynamically correlated. The two regulatory N-domain calcium-binding sites of TnC were dynamically correlated, even though the calcium-binding site I is dysfunctional. The strong interaction residue pairs and the strong dynamically correlated residues pairs among the three components of troponin complexes were identified. These correlated motions are consistent with the idea that there is a high degree of cooperativity among the components of the regulatory complex in response to Ca(2+) and other effectors. This approach may give insight into the mechanism by which mutations of troponin cause disease. It is interesting that some observed disease causing mutations fall within regions of troponin that are strongly correlated or interacted.

The complex interplay between mitochondrial dynamics and cardiac metabolism

PubMed Central

Parra, Valentina; Verdejo, Hugo; del Campo, Andrea; Pennanen, Christian; Kuzmicic, Jovan; Iglewski, Myriam; Hill, Joseph A.; Rothermel, Beverly A.

2012-01-01

Mitochondria are highly dynamic organelles, capable of undergoing constant fission and fusion events, forming networks. These dynamic events allow the transmission of chemical and physical messengers and the exchange of metabolites within the cell. In this article we review the signaling mechanisms controlling mitochondrial fission and fusion, and its relationship with cell bioenergetics, especially in the heart. Furthermore we also discuss how defects in mitochondrial dynamics might be involved in the pathogenesis of metabolic cardiac diseases. PMID:21258852

Rapid identifying high-influence nodes in complex networks

NASA Astrophysics Data System (ADS)

Song, Bo; Jiang, Guo-Ping; Song, Yu-Rong; Xia, Ling-Ling

2015-10-01

A tiny fraction of influential individuals play a critical role in the dynamics on complex systems. Identifying the influential nodes in complex networks has theoretical and practical significance. Considering the uncertainties of network scale and topology, and the timeliness of dynamic behaviors in real networks, we propose a rapid identifying method (RIM) to find the fraction of high-influential nodes. Instead of ranking all nodes, our method only aims at ranking a small number of nodes in network. We set the high-influential nodes as initial spreaders, and evaluate the performance of RIM by the susceptible-infected-recovered (SIR) model. The simulations show that in different networks, RIM performs well on rapid identifying high-influential nodes, which is verified by typical ranking methods, such as degree, closeness, betweenness, and eigenvector centrality methods. Project supported by the National Natural Science Foundation of China (Grant Nos. 61374180 and 61373136), the Ministry of Education Research in the Humanities and Social Sciences Planning Fund Project, China (Grant No. 12YJAZH120), and the Six Projects Sponsoring Talent Summits of Jiangsu Province, China (Grant No. RLD201212).

Inverse Tone Mapping Based upon Retina Response

PubMed Central

Huo, Yongqing; Yang, Fan; Brost, Vincent

2014-01-01

The development of high dynamic range (HDR) display arouses the research of inverse tone mapping methods, which expand dynamic range of the low dynamic range (LDR) image to match that of HDR monitor. This paper proposed a novel physiological approach, which could avoid artifacts occurred in most existing algorithms. Inspired by the property of the human visual system (HVS), this dynamic range expansion scheme performs with a low computational complexity and a limited number of parameters and obtains high-quality HDR results. Comparisons with three recent algorithms in the literature also show that the proposed method reveals more important image details and produces less contrast loss and distortion. PMID:24744678

Solution-Phase Dynamic Assembly of Permanently Interlocked Aryleneethynylene Cages through Alkyne Metathesis

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

Wang, Qi; Yu, Chao; Long, Hai

2015-05-08

Highly stable permanently interlocked aryleneethynylene molecular cages were synthesized from simple triyne monomers using dynamic alkyne metathesis. The interlocked complexes are predominantly formed in the reaction solution in the absence of any recognition motif and were isolated in a pure form using column chromatography. This study is the first example of the thermodynamically controlled solution-phase synthesis of interlocked organic cages with high stability.

Adaptive sampling strategies with high-throughput molecular dynamics

NASA Astrophysics Data System (ADS)

Clementi, Cecilia

Despite recent significant hardware and software developments, the complete thermodynamic and kinetic characterization of large macromolecular complexes by molecular simulations still presents significant challenges. The high dimensionality of these systems and the complexity of the associated potential energy surfaces (creating multiple metastable regions connected by high free energy barriers) does not usually allow to adequately sample the relevant regions of their configurational space by means of a single, long Molecular Dynamics (MD) trajectory. Several different approaches have been proposed to tackle this sampling problem. We focus on the development of ensemble simulation strategies, where data from a large number of weakly coupled simulations are integrated to explore the configurational landscape of a complex system more efficiently. Ensemble methods are of increasing interest as the hardware roadmap is now mostly based on increasing core counts, rather than clock speeds. The main challenge in the development of an ensemble approach for efficient sampling is in the design of strategies to adaptively distribute the trajectories over the relevant regions of the systems' configurational space, without using any a priori information on the system global properties. We will discuss the definition of smart adaptive sampling approaches that can redirect computational resources towards unexplored yet relevant regions. Our approaches are based on new developments in dimensionality reduction for high dimensional dynamical systems, and optimal redistribution of resources. NSF CHE-1152344, NSF CHE-1265929, Welch Foundation C-1570.

Automated Design of Complex Dynamic Systems

PubMed Central

Hermans, Michiel; Schrauwen, Benjamin; Bienstman, Peter; Dambre, Joni

2014-01-01

Several fields of study are concerned with uniting the concept of computation with that of the design of physical systems. For example, a recent trend in robotics is to design robots in such a way that they require a minimal control effort. Another example is found in the domain of photonics, where recent efforts try to benefit directly from the complex nonlinear dynamics to achieve more efficient signal processing. The underlying goal of these and similar research efforts is to internalize a large part of the necessary computations within the physical system itself by exploiting its inherent non-linear dynamics. This, however, often requires the optimization of large numbers of system parameters, related to both the system's structure as well as its material properties. In addition, many of these parameters are subject to fabrication variability or to variations through time. In this paper we apply a machine learning algorithm to optimize physical dynamic systems. We show that such algorithms, which are normally applied on abstract computational entities, can be extended to the field of differential equations and used to optimize an associated set of parameters which determine their behavior. We show that machine learning training methodologies are highly useful in designing robust systems, and we provide a set of both simple and complex examples using models of physical dynamical systems. Interestingly, the derived optimization method is intimately related to direct collocation a method known in the field of optimal control. Our work suggests that the application domains of both machine learning and optimal control have a largely unexplored overlapping area which envelopes a novel design methodology of smart and highly complex physical systems. PMID:24497969

New approaches to the analysis of complex samples using fluorescence lifetime techniques and organized media

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

Hertz, P.R.

Fluorescence spectroscopy is a highly sensitive and selective tool for the analysis of complex systems. In order to investigate the efficacy of several steady state and dynamic techniques for the analysis of complex systems, this work focuses on two types of complex, multicomponent samples: petrolatums and coal liquids. It is shown in these studies dynamic, fluorescence lifetime-based measurements provide enhanced discrimination between complex petrolatum samples. Additionally, improved quantitative analysis of multicomponent systems is demonstrated via incorporation of organized media in coal liquid samples. This research provides the first systematic studies of (1) multifrequency phase-resolved fluorescence spectroscopy for dynamic fluorescence spectralmore » fingerprinting of complex samples, and (2) the incorporation of bile salt micellar media to improve accuracy and sensitivity for characterization of complex systems. In the petroleum studies, phase-resolved fluorescence spectroscopy is used to combine spectral and lifetime information through the measurement of phase-resolved fluorescence intensity. The intensity is collected as a function of excitation and emission wavelengths, angular modulation frequency, and detector phase angle. This multidimensional information enhances the ability to distinguish between complex samples with similar spectral characteristics. Examination of the eigenvalues and eigenvectors from factor analysis of phase-resolved and steady state excitation-emission matrices, using chemometric methods of data analysis, confirms that phase-resolved fluorescence techniques offer improved discrimination between complex samples as compared with conventional steady state methods.« less

A Framework for Simulating Turbine-Based Combined-Cycle Inlet Mode-Transition

NASA Technical Reports Server (NTRS)

Le, Dzu K.; Vrnak, Daniel R.; Slater, John W.; Hessel, Emil O.

2012-01-01

A simulation framework based on the Memory-Mapped-Files technique was created to operate multiple numerical processes in locked time-steps and send I/O data synchronously across to one-another to simulate system-dynamics. This simulation scheme is currently used to study the complex interactions between inlet flow-dynamics, variable-geometry actuation mechanisms, and flow-controls in the transition from the supersonic to hypersonic conditions and vice-versa. A study of Mode-Transition Control for a high-speed inlet wind-tunnel model with this MMF-based framework is presented to illustrate this scheme and demonstrate its usefulness in simulating supersonic and hypersonic inlet dynamics and controls or other types of complex systems.

Recurrence quantity analysis based on matrix eigenvalues

NASA Astrophysics Data System (ADS)

Yang, Pengbo; Shang, Pengjian

2018-06-01

Recurrence plots is a powerful tool for visualization and analysis of dynamical systems. Recurrence quantification analysis (RQA), based on point density and diagonal and vertical line structures in the recurrence plots, is considered to be alternative measures to quantify the complexity of dynamical systems. In this paper, we present a new measure based on recurrence matrix to quantify the dynamical properties of a given system. Matrix eigenvalues can reflect the basic characteristics of the complex systems, so we show the properties of the system by exploring the eigenvalues of the recurrence matrix. Considering that Shannon entropy has been defined as a complexity measure, we propose the definition of entropy of matrix eigenvalues (EOME) as a new RQA measure. We confirm that EOME can be used as a metric to quantify the behavior changes of the system. As a given dynamical system changes from a non-chaotic to a chaotic regime, the EOME will increase as well. The bigger EOME values imply higher complexity and lower predictability. We also study the effect of some factors on EOME,including data length, recurrence threshold, the embedding dimension, and additional noise. Finally, we demonstrate an application in physiology. The advantage of this measure lies in a high sensitivity and simple computation.

Thermal proximity coaggregation for system-wide profiling of protein complex dynamics in cells.

PubMed

Tan, Chris Soon Heng; Go, Ka Diam; Bisteau, Xavier; Dai, Lingyun; Yong, Chern Han; Prabhu, Nayana; Ozturk, Mert Burak; Lim, Yan Ting; Sreekumar, Lekshmy; Lengqvist, Johan; Tergaonkar, Vinay; Kaldis, Philipp; Sobota, Radoslaw M; Nordlund, Pär

2018-03-09

Proteins differentially interact with each other across cellular states and conditions, but an efficient proteome-wide strategy to monitor them is lacking. We report the application of thermal proximity coaggregation (TPCA) for high-throughput intracellular monitoring of protein complex dynamics. Significant TPCA signatures observed among well-validated protein-protein interactions correlate positively with interaction stoichiometry and are statistically observable in more than 350 annotated human protein complexes. Using TPCA, we identified many complexes without detectable differential protein expression, including chromatin-associated complexes, modulated in S phase of the cell cycle. Comparison of six cell lines by TPCA revealed cell-specific interactions even in fundamental cellular processes. TPCA constitutes an approach for system-wide studies of protein complexes in nonengineered cells and tissues and might be used to identify protein complexes that are modulated in diseases. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

GPU-enabled molecular dynamics simulations of ankyrin kinase complex

NASA Astrophysics Data System (ADS)

Gautam, Vertika; Chong, Wei Lim; Wisitponchai, Tanchanok; Nimmanpipug, Piyarat; Zain, Sharifuddin M.; Rahman, Noorsaadah Abd.; Tayapiwatana, Chatchai; Lee, Vannajan Sanghiran

2014-10-01

The ankyrin repeat (AR) protein can be used as a versatile scaffold for protein-protein interactions. It has been found that the heterotrimeric complex between integrin-linked kinase (ILK), PINCH, and parvin is an essential signaling platform, serving as a convergence point for integrin and growth-factor signaling and regulating cell adhesion, spreading, and migration. Using ILK-AR with high affinity for the PINCH1 as our model system, we explored a structure-based computational protocol to probe and characterize binding affinity hot spots at protein-protein interfaces. In this study, the long time scale dynamics simulations with GPU accelerated molecular dynamics (MD) simulations in AMBER12 have been performed to locate the hot spots of protein-protein interaction by the analysis of the Molecular Mechanics-Poisson-Boltzmann Surface Area/Generalized Born Solvent Area (MM-PBSA/GBSA) of the MD trajectories. Our calculations suggest good binding affinity of the complex and also the residues critical in the binding.

Complexity of EEG-signal in Time Domain - Possible Biomedical Application

NASA Astrophysics Data System (ADS)

Klonowski, Wlodzimierz; Olejarczyk, Elzbieta; Stepien, Robert

2002-07-01

Human brain is a highly complex nonlinear system. So it is not surprising that in analysis of EEG-signal, which represents overall activity of the brain, the methods of Nonlinear Dynamics (or Chaos Theory as it is commonly called) can be used. Even if the signal is not chaotic these methods are a motivating tool to explore changes in brain activity due to different functional activation states, e.g. different sleep stages, or to applied therapy, e.g. exposure to chemical agents (drugs) and physical factors (light, magnetic field). The methods supplied by Nonlinear Dynamics reveal signal characteristics that are not revealed by linear methods like FFT. Better understanding of principles that govern dynamics and complexity of EEG-signal can help to find `the signatures' of different physiological and pathological states of human brain, quantitative characteristics that may find applications in medical diagnostics.

Novel Mycobacterium tuberculosis complex pathogen, M. mungi.

PubMed

Alexander, Kathleen A; Laver, Pete N; Michel, Anita L; Williams, Mark; van Helden, Paul D; Warren, Robin M; Gey van Pittius, Nicolaas C

2010-08-01

Seven outbreaks involving increasing numbers of banded mongoose troops and high death rates have been documented. We identified a Mycobacterium tuberculosis complex pathogen, M. mungi sp. nov., as the causative agent among banded mongooses that live near humans in Chobe District, Botswana. Host spectrum and transmission dynamics remain unknown.

The complexity of gene expression dynamics revealed by permutation entropy

PubMed Central

2010-01-01

Background High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation Entropy (PE) first introduced in dynamical systems theory. The analysis of gene expression data has so far focused primarily on the identification of differentially expressed genes, or on the elucidation of pathway and regulatory relationships. We aim to study gene expression time series data from the viewpoint of complexity. Results Applying the PE complexity metric to abiotic stress response time series data in Arabidopsis thaliana, genes involved in stress response and signaling were found to be associated with the highest complexity not only under stress, but surprisingly, also under reference, non-stress conditions. Genes with house-keeping functions exhibited lower PE complexity. Compared to reference conditions, the PE of temporal gene expression patterns generally increased upon stress exposure. High-complexity genes were found to have longer upstream intergenic regions and more cis-regulatory motifs in their promoter regions indicative of a more complex regulatory apparatus needed to orchestrate their expression, and to be associated with higher correlation network connectivity degree. Arabidopsis genes also present in other plant species were observed to exhibit decreased PE complexity compared to Arabidopsis specific genes. Conclusions We show that Permutation Entropy is a simple yet robust and powerful approach to identify temporal gene expression profiles of varying complexity that is equally applicable to other types of molecular profile data. PMID:21176199

Demystifying the Complexities of Gravity Wave Dynamics in the Middle Atmosphere: a Roadmap to Improved Weather Forecasts through High-Fidelity Modeling

NASA Astrophysics Data System (ADS)

Mixa, T.; Fritts, D. C.; Bossert, K.; Laughman, B.; Wang, L.; Lund, T.; Kantha, L. H.

2017-12-01

Gravity waves play a profound role in the mixing of the atmosphere, transporting vast amounts of momentum and energy among different altitudes as they propagate vertically. Above 60km in the middle atmosphere, high wave amplitudes enable a series of complex, nonlinear interactions with the background environment that produce highly-localized wind and temperature variations which alter the layering structure of the atmosphere. These small-scale interactions account for a significant portion of energy transport in the middle atmosphere, but they are difficult to characterize, occurring at spatial scales that are both challenging to observe with ground instruments and prohibitively small to include in weather forecasting models. Using high fidelity numerical simulations, these nuanced wave interactions are analyzed to better our understanding of these dynamics and improve the accuracy of long-term weather forecasting.

Stable and rigid DTPA-like paramagnetic tags suitable for in vitro and in situ protein NMR analysis.

PubMed

Chen, Jia-Liang; Zhao, Yu; Gong, Yan-Jun; Pan, Bin-Bin; Wang, Xiao; Su, Xun-Cheng

2018-02-01

Organic synthesis of a ligand with high binding affinities for paramagnetic lanthanide ions is an effective way of generating paramagnetic effects on proteins. These paramagnetic effects manifested in high-resolution NMR spectroscopy are valuable dynamic and structural restraints of proteins and protein-ligand complexes. A paramagnetic tag generally contains a metal chelating moiety and a reactive group for protein modification. Herein we report two new DTPA-like tags, 4PS-PyDTTA and 4PS-6M-PyDTTA that can be site-specifically attached to a protein with a stable thioether bond. Both protein-tag adducts form stable lanthanide complexes, of which the binding affinities and paramagnetic tensors are tunable with respect to the 6-methyl group in pyridine. Paramagnetic relaxation enhancement (PRE) effects of Gd(III) complex on protein-tag adducts were evaluated in comparison with pseudocontact shift (PCS), and the results indicated that both 4PS-PyDTTA and 4PS-6M-PyDTTA tags are rigid and present high-quality PREs that are crucially important in elucidation of the dynamics and interactions of proteins and protein-ligand complexes. We also show that these two tags are suitable for in-situ protein NMR analysis.

High refuge availability on coral reefs increases the vulnerability of reef-associated predators to overexploitation.

PubMed

Rogers, Alice; Blanchard, Julia L; Newman, Steven P; Dryden, Charlie S; Mumby, Peter J

2018-02-01

Refuge availability and fishing alter predator-prey interactions on coral reefs, but our understanding of how they interact to drive food web dynamics, community structure and vulnerability of different trophic groups is unclear. Here, we apply a size-based ecosystem model of coral reefs, parameterized with empirical measures of structural complexity, to predict fish biomass, productivity and community structure in reef ecosystems under a broad range of refuge availability and fishing regimes. In unfished ecosystems, the expected positive correlation between reef structural complexity and biomass emerges, but a non-linear effect of predation refuges is observed for the productivity of predatory fish. Reefs with intermediate complexity have the highest predator productivity, but when refuge availability is high and prey are less available, predator growth rates decrease, with significant implications for fisheries. Specifically, as fishing intensity increases, predators in habitats with high refuge availability exhibit vulnerability to over-exploitation, resulting in communities dominated by herbivores. Our study reveals mechanisms for threshold dynamics in predators living in complex habitats and elucidates how predators can be food-limited when most of their prey are able to hide. We also highlight the importance of nutrient recycling via the detrital pathway, to support high predator biomasses on coral reefs. © 2018 by the Ecological Society of America.

From phase transitions to the topological renaissance. Comment on "Topodynamics of metastable brains" by Arturo Tozzi et al.

NASA Astrophysics Data System (ADS)

Somogyvári, Zoltán; Érdi, Péter

2017-07-01

The neural topodynamics theory of Tozzi et al. [13] has two main foci: metastable brain dynamics and the topological approach based on the Borsuk-Ulam theorem (BUT). Briefly, metastable brain dynamics theory hypothesizes that temporary stable synchronization and desynchronization of large number of individual dynamical systems, formed by local neural circuits, are responsible for coding of complex concepts in the brain and sudden changes of these synchronization patterns correspond to operational steps. But what dynamical network could form the substrate for this metastable dynamics, capable of entering into a combinatorially high number of metastable synchronization patterns and exhibit rapid transient changes between them? The general problem is related to the discrimination between ;Black Swans; and ;Dragon Kings;. While BSs are related to the theory of self-organized criticality, and suggests that high-impact extreme events are unpredictable, Dragon-kings are associated with the occurrence of a phase transition, whose emergent organization is based on intermittent criticality [9]. Widening the limits of predictability is one of the big open problems in the theory and practice of complex systems (Sect. 9.3 of Érdi [2]).

Extended dynamic range of Doppler OCT by application of a new method to high density B-scans using a MHz FDML swept laser source (Conference Presentation)

NASA Astrophysics Data System (ADS)

Elahi, Sahar; Thrane, Lars; Rollins, Andrew M.; Jenkins, Michael W.

2017-02-01

The limited dynamic range of optical coherence tomography (OCT) Doppler velocity measurements makes it difficult to conduct experiments on samples requiring a large dynamic range without phase wrapping at high velocities or loss of sensitivity at slow velocities. Hemodynamics and wall motion undergo significant increases in velocity as the embryonic heart develops. Experimental studies indicate that altered hemodynamics in early-stage embryonic hearts can lead to congenital heart diseases (CHDs), motivating close monitoring of blood flow over several stages of development. We have built a high-speed OCT system using an FDML laser (Optores GmbH, Germany) at a sweep rate of 1.68 MHz (axial resolution - 12 μm, sensitivity - 105 dB, phase stability - 17 mrad). The speed of this OCT system allows us to acquire high-density B-scans to obtain an extended velocity dynamic range without sacrificing the frame rate (100 Hz). The extended dynamic range within a frame is achieved by varying the A-scan interval at which the phase difference is found, enabling detection of velocities ranging from tens of microns per second to hundreds of millimeters per second. The extra lines in a frame can also be utilized to improve the structural and Doppler images via complex averaging. In structural images where the presence of blood causes additional scattering, complex averaging helps retrieve features located deeper in the tissue. Moreover, high-density frames can be registered to 4D volumes to determine the orthogonal direction of flow for calculating shear stress as well as estimating the cardiac output. In conclusion, high density B-scans acquired by our high-speed OCT system enable image enhancement and direct measurement of biological parameters in cohort studies.

Supramolecular reactivity in the gas phase: investigating the intrinsic properties of non-covalent complexes.

PubMed

Cera, Luca; Schalley, Christoph A

2014-03-21

The high vacuum inside a mass spectrometer offers unique conditions to broaden our view on the reactivity of supramolecules. Because dynamic exchange processes between complexes are efficiently suppressed, the intrinsic and intramolecular reactivity of the complexes of interest is observed. Besides this, the significantly higher strength of non-covalent interactions in the absence of competing solvent allows processes to occur that are unable to compete in solution. The present review highlights a series of examples illustrating different aspects of supramolecular gas-phase reactivity ranging from the dissociation and formation of covalent bonds in non-covalent complexes through the reactivity in the restricted inner phase of container molecules and step-by-step mechanistic studies of organocatalytic reaction cycles to cage contraction reactions, processes induced by electron capture, and finally dynamic molecular motion within non-covalent complexes as unravelled by hydrogen-deuterium exchange processes performed in the gas phase.

Dynamically reconfigurable complex emulsions via tunable interfacial tensions

PubMed Central

Zarzar, Lauren D.; Sresht, Vishnu; Sletten, Ellen M.; Kalow, Julia A.; Blankschtein, Daniel; Swager, Timothy M.

2015-01-01

Emulsification is a powerful, well-known technique for mixing and dispersing immiscible components within a continuous liquid phase. Consequently, emulsions are central components of medicine, food and performance materials. Complex emulsions, including multiple emulsions and Janus droplets which contain hemispheres of differing material, are of increasing importance1 in pharmaceuticals and medical diagnostics2, in the fabrication of microparticles and capsules3–5 for food6, in chemical separations7, in cosmetics8, and in dynamic optics9. Because complex emulsion properties and functions are related to the droplet geometry and composition, the development of rapid, simple fabrication approaches allowing precise control over the droplets’ physical and chemical characteristics is critical. Significant advances in the fabrication of complex emulsions have been made using a number of procedures, ranging from large-scale, less precise techniques that give compositional heterogeneity using high-shear mixers and membranes10, to small-volume but more precise microfluidic methods11,12. However, such approaches have yet to create droplet morphologies that can be controllably altered after emulsification. Reconfigurable complex liquids potentially have greatly increased utility as dynamically tunable materials. Here we describe an approach to the one-step fabrication of three- and four-phase complex emulsions with highly controllable and reconfigurable morphologies. The fabrication makes use of the temperature-sensitive miscibility of hydrocarbon, silicone and fluorocarbon liquids, and is applied to both the microfluidic and the scalable batch production of complex droplets. We demonstrate that droplet geometries can be alternated between encapsulated and Janus configurations by varying the interfacial tensions using hydrocarbon and fluorinated surfactants including stimuli-responsive and cleavable surfactants. This yields a generalizable strategy for the fabrication of multiphase emulsions with controllably reconfigurable morphologies and the potential to create a wide range of responsive materials. PMID:25719669

Dynamically reconfigurable complex emulsions via tunable interfacial tensions.

PubMed

Zarzar, Lauren D; Sresht, Vishnu; Sletten, Ellen M; Kalow, Julia A; Blankschtein, Daniel; Swager, Timothy M

2015-02-26

Emulsification is a powerful, well-known technique for mixing and dispersing immiscible components within a continuous liquid phase. Consequently, emulsions are central components of medicine, food and performance materials. Complex emulsions, including Janus droplets (that is, droplets with faces of differing chemistries) and multiple emulsions, are of increasing importance in pharmaceuticals and medical diagnostics, in the fabrication of microparticles and capsules for food, in chemical separations, in cosmetics, and in dynamic optics. Because complex emulsion properties and functions are related to the droplet geometry and composition, the development of rapid, simple fabrication approaches allowing precise control over the droplets' physical and chemical characteristics is critical. Significant advances in the fabrication of complex emulsions have been made using a number of procedures, ranging from large-scale, less precise techniques that give compositional heterogeneity using high-shear mixers and membranes, to small-volume but more precise microfluidic methods. However, such approaches have yet to create droplet morphologies that can be controllably altered after emulsification. Reconfigurable complex liquids potentially have great utility as dynamically tunable materials. Here we describe an approach to the one-step fabrication of three- and four-phase complex emulsions with highly controllable and reconfigurable morphologies. The fabrication makes use of the temperature-sensitive miscibility of hydrocarbon, silicone and fluorocarbon liquids, and is applied to both the microfluidic and the scalable batch production of complex droplets. We demonstrate that droplet geometries can be alternated between encapsulated and Janus configurations by varying the interfacial tensions using hydrocarbon and fluorinated surfactants including stimuli-responsive and cleavable surfactants. This yields a generalizable strategy for the fabrication of multiphase emulsions with controllably reconfigurable morphologies and the potential to create a wide range of responsive materials.

Dynamically reconfigurable complex emulsions via tunable interfacial tensions

NASA Astrophysics Data System (ADS)

Zarzar, Lauren D.; Sresht, Vishnu; Sletten, Ellen M.; Kalow, Julia A.; Blankschtein, Daniel; Swager, Timothy M.

2015-02-01

Emulsification is a powerful, well-known technique for mixing and dispersing immiscible components within a continuous liquid phase. Consequently, emulsions are central components of medicine, food and performance materials. Complex emulsions, including Janus droplets (that is, droplets with faces of differing chemistries) and multiple emulsions, are of increasing importance in pharmaceuticals and medical diagnostics, in the fabrication of microparticles and capsules for food, in chemical separations, in cosmetics, and in dynamic optics. Because complex emulsion properties and functions are related to the droplet geometry and composition, the development of rapid, simple fabrication approaches allowing precise control over the droplets' physical and chemical characteristics is critical. Significant advances in the fabrication of complex emulsions have been made using a number of procedures, ranging from large-scale, less precise techniques that give compositional heterogeneity using high-shear mixers and membranes, to small-volume but more precise microfluidic methods. However, such approaches have yet to create droplet morphologies that can be controllably altered after emulsification. Reconfigurable complex liquids potentially have great utility as dynamically tunable materials. Here we describe an approach to the one-step fabrication of three- and four-phase complex emulsions with highly controllable and reconfigurable morphologies. The fabrication makes use of the temperature-sensitive miscibility of hydrocarbon, silicone and fluorocarbon liquids, and is applied to both the microfluidic and the scalable batch production of complex droplets. We demonstrate that droplet geometries can be alternated between encapsulated and Janus configurations by varying the interfacial tensions using hydrocarbon and fluorinated surfactants including stimuli-responsive and cleavable surfactants. This yields a generalizable strategy for the fabrication of multiphase emulsions with controllably reconfigurable morphologies and the potential to create a wide range of responsive materials.

Small Modifications to Network Topology Can Induce Stochastic Bistable Spiking Dynamics in a Balanced Cortical Model

PubMed Central

McDonnell, Mark D.; Ward, Lawrence M.

2014-01-01

Abstract Directed random graph models frequently are used successfully in modeling the population dynamics of networks of cortical neurons connected by chemical synapses. Experimental results consistently reveal that neuronal network topology is complex, however, in the sense that it differs statistically from a random network, and differs for classes of neurons that are physiologically different. This suggests that complex network models whose subnetworks have distinct topological structure may be a useful, and more biologically realistic, alternative to random networks. Here we demonstrate that the balanced excitation and inhibition frequently observed in small cortical regions can transiently disappear in otherwise standard neuronal-scale models of fluctuation-driven dynamics, solely because the random network topology was replaced by a complex clustered one, whilst not changing the in-degree of any neurons. In this network, a small subset of cells whose inhibition comes only from outside their local cluster are the cause of bistable population dynamics, where different clusters of these cells irregularly switch back and forth from a sparsely firing state to a highly active state. Transitions to the highly active state occur when a cluster of these cells spikes sufficiently often to cause strong unbalanced positive feedback to each other. Transitions back to the sparsely firing state rely on occasional large fluctuations in the amount of non-local inhibition received. Neurons in the model are homogeneous in their intrinsic dynamics and in-degrees, but differ in the abundance of various directed feedback motifs in which they participate. Our findings suggest that (i) models and simulations should take into account complex structure that varies for neuron and synapse classes; (ii) differences in the dynamics of neurons with similar intrinsic properties may be caused by their membership in distinctive local networks; (iii) it is important to identify neurons that share physiological properties and location, but differ in their connectivity. PMID:24743633

Introduction to State Estimation of High-Rate System Dynamics.

PubMed

Hong, Jonathan; Laflamme, Simon; Dodson, Jacob; Joyce, Bryan

2018-01-13

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer's convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model.

Characterising Dynamic Instability in High Water-Cut Oil-Water Flows Using High-Resolution Microwave Sensor Signals

NASA Astrophysics Data System (ADS)

Liu, Weixin; Jin, Ningde; Han, Yunfeng; Ma, Jing

2018-06-01

In the present study, multi-scale entropy algorithm was used to characterise the complex flow phenomena of turbulent droplets in high water-cut oil-water two-phase flow. First, we compared multi-scale weighted permutation entropy (MWPE), multi-scale approximate entropy (MAE), multi-scale sample entropy (MSE) and multi-scale complexity measure (MCM) for typical nonlinear systems. The results show that MWPE presents satisfied variability with scale and anti-noise ability. Accordingly, we conducted an experiment of vertical upward oil-water two-phase flow with high water-cut and collected the signals of a high-resolution microwave resonant sensor, based on which two indexes, the entropy rate and mean value of MWPE, were extracted. Besides, the effects of total flow rate and water-cut on these two indexes were analysed. Our researches show that MWPE is an effective method to uncover the dynamic instability of oil-water two-phase flow with high water-cut.

Decoding the dynamics of cellular metabolism and the action of 3-bromopyruvate and 2-deoxyglucose using pulsed stable isotope-resolved metabolomics.

PubMed

Pietzke, Matthias; Zasada, Christin; Mudrich, Susann; Kempa, Stefan

2014-01-01

Cellular metabolism is highly dynamic and continuously adjusts to the physiological program of the cell. The regulation of metabolism appears at all biological levels: (post-) transcriptional, (post-) translational, and allosteric. This regulatory information is expressed in the metabolome, but in a complex manner. To decode such complex information, new methods are needed in order to facilitate dynamic metabolic characterization at high resolution. Here, we describe pulsed stable isotope-resolved metabolomics (pSIRM) as a tool for the dynamic metabolic characterization of cellular metabolism. We have adapted gas chromatography-coupled mass spectrometric methods for metabolomic profiling and stable isotope-resolved metabolomics. In addition, we have improved robustness and reproducibility and implemented a strategy for the absolute quantification of metabolites. By way of examples, we have applied this methodology to characterize central carbon metabolism of a panel of cancer cell lines and to determine the mode of metabolic inhibition of glycolytic inhibitors in times ranging from minutes to hours. Using pSIRM, we observed that 2-deoxyglucose is a metabolic inhibitor, but does not directly act on the glycolytic cascade.

Multifractal Approach to the Analysis of Crime Dynamics: Results for Burglary in San Francisco

NASA Astrophysics Data System (ADS)

Melgarejo, Miguel; Obregon, Nelson

This paper provides evidence of fractal, multifractal and chaotic behaviors in urban crime by computing key statistical attributes over a long data register of criminal activity. Fractal and multifractal analyses based on power spectrum, Hurst exponent computation, hierarchical power law detection and multifractal spectrum are considered ways to characterize and quantify the footprint of complexity of criminal activity. Moreover, observed chaos analysis is considered a second step to pinpoint the nature of the underlying crime dynamics. This approach is carried out on a long database of burglary activity reported by 10 police districts of San Francisco city. In general, interarrival time processes of criminal activity in San Francisco exhibit fractal and multifractal patterns. The behavior of some of these processes is close to 1/f noise. Therefore, a characterization as deterministic, high-dimensional, chaotic phenomena is viable. Thus, the nature of crime dynamics can be studied from geometric and chaotic perspectives. Our findings support that crime dynamics may be understood from complex systems theories like self-organized criticality or highly optimized tolerance.

Molecular dynamics simulation of the structure and dynamics of 5-HT3 serotonin receptor

NASA Astrophysics Data System (ADS)

Antonov, M. Yu.; Popinako, A. V.; Prokopiev, G. A.

2016-10-01

In this work, we investigated structure, dynamics and ion transportation in transmembrane domain of the 5-HT3 serotonin receptor. High-resolution (0.35 nm) structure of the 5-HT3 receptor in complex with stabilizing nanobodies was determined by protein crystallography in 2014 (Protein data bank (PDB) code 4PIR). Transmembrane domain of the structure was prepared in complex with explicit membrane environment (1-palmitoyl-2-oleoyl-sn-glycero-3-phosphatidylcholine (POPC)) and solvent (TIP3P water model). Molecular dynamics protocols for simulation and stabilization of the transmembrane domain of the 5-HT3 receptor model were developed and 60 ns simulation of the structure was conducted in order to explore structural parameters of the system. We estimated the mean force profile for Na+ ions using umbrella sampling method.

Memory-induced nonlinear dynamics of excitation in cardiac diseases.

PubMed

Landaw, Julian; Qu, Zhilin

2018-04-01

Excitable cells, such as cardiac myocytes, exhibit short-term memory, i.e., the state of the cell depends on its history of excitation. Memory can originate from slow recovery of membrane ion channels or from accumulation of intracellular ion concentrations, such as calcium ion or sodium ion concentration accumulation. Here we examine the effects of memory on excitation dynamics in cardiac myocytes under two diseased conditions, early repolarization and reduced repolarization reserve, each with memory from two different sources: slow recovery of a potassium ion channel and slow accumulation of the intracellular calcium ion concentration. We first carry out computer simulations of action potential models described by differential equations to demonstrate complex excitation dynamics, such as chaos. We then develop iterated map models that incorporate memory, which accurately capture the complex excitation dynamics and bifurcations of the action potential models. Finally, we carry out theoretical analyses of the iterated map models to reveal the underlying mechanisms of memory-induced nonlinear dynamics. Our study demonstrates that the memory effect can be unmasked or greatly exacerbated under certain diseased conditions, which promotes complex excitation dynamics, such as chaos. The iterated map models reveal that memory converts a monotonic iterated map function into a nonmonotonic one to promote the bifurcations leading to high periodicity and chaos.

Memory-induced nonlinear dynamics of excitation in cardiac diseases

NASA Astrophysics Data System (ADS)

Landaw, Julian; Qu, Zhilin

2018-04-01

Excitable cells, such as cardiac myocytes, exhibit short-term memory, i.e., the state of the cell depends on its history of excitation. Memory can originate from slow recovery of membrane ion channels or from accumulation of intracellular ion concentrations, such as calcium ion or sodium ion concentration accumulation. Here we examine the effects of memory on excitation dynamics in cardiac myocytes under two diseased conditions, early repolarization and reduced repolarization reserve, each with memory from two different sources: slow recovery of a potassium ion channel and slow accumulation of the intracellular calcium ion concentration. We first carry out computer simulations of action potential models described by differential equations to demonstrate complex excitation dynamics, such as chaos. We then develop iterated map models that incorporate memory, which accurately capture the complex excitation dynamics and bifurcations of the action potential models. Finally, we carry out theoretical analyses of the iterated map models to reveal the underlying mechanisms of memory-induced nonlinear dynamics. Our study demonstrates that the memory effect can be unmasked or greatly exacerbated under certain diseased conditions, which promotes complex excitation dynamics, such as chaos. The iterated map models reveal that memory converts a monotonic iterated map function into a nonmonotonic one to promote the bifurcations leading to high periodicity and chaos.

Broad frequency band full field measurements for advanced applications: Point-wise comparisons between optical technologies

NASA Astrophysics Data System (ADS)

Zanarini, Alessandro

2018-01-01

The progress of optical systems gives nowadays at disposal on lightweight structures complex dynamic measurements and modal tests, each with its own advantages, drawbacks and preferred usage domains. It is thus more easy than before to obtain highly spatially defined vibration patterns for many applications in vibration engineering, testing and general product development. The potential of three completely different technologies is here benchmarked on a common test rig and advanced applications. SLDV, dynamic ESPI and hi-speed DIC are here first deployed in a complex and unique test on the estimation of FRFs with high spatial accuracy from a thin vibrating plate. The latter exhibits a broad band dynamics and high modal density in the common frequency domain where the techniques can find an operative intersection. A peculiar point-wise comparison is here addressed by means of discrete geometry transforms to put all the three technologies on trial at each physical point of the surface. Full field measurement technologies cannot estimate only displacement fields on a refined grid, but can exploit the spatial consistency of the results through neighbouring locations by means of numerical differentiation operators in the spatial domain to obtain rotational degrees of freedom and superficial dynamic strain distributions, with enhanced quality, compared to other technologies in literature. Approaching the task with the aid of superior quality receptance maps from the three different full field gears, this work calculates and compares rotational and dynamic strain FRFs. Dynamic stress FRFs can be modelled directly from the latter, by means of a constitutive model, avoiding the costly and time-consuming steps of building and tuning a numerical dynamic model of a flexible component or a structure in real life conditions. Once dynamic stress FRFs are obtained, spectral fatigue approaches can try to predict the life of a component in many excitation conditions. Different spectral shaping of the excitation can easily be used to enhance the comparison in the framework of any of the spectral approaches for fatigue life calculations, highlighting benefits and drawbacks of a direct experimental approach to failure and risk assessment in structural dynamics when dealing with complex patterns in real-life testing. Are optical measurements and spatially dense datasets really effective in advanced model updating of lightweight structures with complex structural dynamics? The noise shown in the raw signal of some experiments may pose issues in proficiently exploiting the added data in a fruitful model updating procedure. Model updating results are here compared between scanning and native full field technologies, with comments and details on the test rig, on the advantages and drawbacks of the approaches. The identification of EMA models highlights the increasing quality of shapes that can be obtained from native full field high resolution gears, against that (some time unexpectedly poor) of SLDV tested.

Deconvolution of reacting-flow dynamics using proper orthogonal and dynamic mode decompositions

NASA Astrophysics Data System (ADS)

Roy, Sukesh; Hua, Jia-Chen; Barnhill, Will; Gunaratne, Gemunu H.; Gord, James R.

2015-01-01

Analytical and computational studies of reacting flows are extremely challenging due in part to nonlinearities of the underlying system of equations and long-range coupling mediated by heat and pressure fluctuations. However, many dynamical features of the flow can be inferred through low-order models if the flow constituents (e.g., eddies or vortices) and their symmetries, as well as the interactions among constituents, are established. Modal decompositions of high-frequency, high-resolution imaging, such as measurements of species-concentration fields through planar laser-induced florescence and of velocity fields through particle-image velocimetry, are the first step in the process. A methodology is introduced for deducing the flow constituents and their dynamics following modal decomposition. Proper orthogonal (POD) and dynamic mode (DMD) decompositions of two classes of problems are performed and their strengths compared. The first problem involves a cellular state generated in a flat circular flame front through symmetry breaking. The state contains two rings of cells that rotate clockwise at different rates. Both POD and DMD can be used to deconvolve the state into the two rings. In POD the contribution of each mode to the flow is quantified using the energy. Each DMD mode can be associated with an energy as well as a unique complex growth rate. Dynamic modes with the same spatial symmetry but different growth rates are found to be combined into a single POD mode. Thus, a flow can be approximated by a smaller number of POD modes. On the other hand, DMD provides a more detailed resolution of the dynamics. Two classes of reacting flows behind symmetric bluff bodies are also analyzed. In the first, symmetric pairs of vortices are released periodically from the two ends of the bluff body. The second flow contains von Karman vortices also, with a vortex being shed from one end of the bluff body followed by a second shedding from the opposite end. The way in which DMD can be used to deconvolve the second flow into symmetric and von Karman vortices is demonstrated. The analyses performed illustrate two distinct advantages of DMD: (1) Unlike proper orthogonal modes, each dynamic mode is associated with a unique complex growth rate. By comparing DMD spectra from multiple nominally identical experiments, it is possible to identify "reproducible" modes in a flow. We also find that although most high-energy modes are reproducible, some are not common between experimental realizations; in the examples considered, energy fails to differentiate between reproducible and nonreproducible modes. Consequently, it may not be possible to differentiate reproducible and nonreproducible modes in POD. (2) Time-dependent coefficients of dynamic modes are complex. Even in noisy experimental data, the dynamics of the phase of these coefficients (but not their magnitude) are highly regular. The phase represents the angular position of a rotating ring of cells and quantifies the downstream displacement of vortices in reacting flows. Thus, it is suggested that the dynamical characterizations of complex flows are best made through the phase dynamics of reproducible DMD modes.

Information driven self-organization of complex robotic behaviors.

PubMed

Martius, Georg; Der, Ralf; Ay, Nihat

2013-01-01

Information theory is a powerful tool to express principles to drive autonomous systems because it is domain invariant and allows for an intuitive interpretation. This paper studies the use of the predictive information (PI), also called excess entropy or effective measure complexity, of the sensorimotor process as a driving force to generate behavior. We study nonlinear and nonstationary systems and introduce the time-local predicting information (TiPI) which allows us to derive exact results together with explicit update rules for the parameters of the controller in the dynamical systems framework. In this way the information principle, formulated at the level of behavior, is translated to the dynamics of the synapses. We underpin our results with a number of case studies with high-dimensional robotic systems. We show the spontaneous cooperativity in a complex physical system with decentralized control. Moreover, a jointly controlled humanoid robot develops a high behavioral variety depending on its physics and the environment it is dynamically embedded into. The behavior can be decomposed into a succession of low-dimensional modes that increasingly explore the behavior space. This is a promising way to avoid the curse of dimensionality which hinders learning systems to scale well.

Dynamic analysis of heartbeat rate signals of epileptics using multidimensional phase space reconstruction approach

NASA Astrophysics Data System (ADS)

Su, Zhi-Yuan; Wu, Tzuyin; Yang, Po-Hua; Wang, Yeng-Tseng

2008-04-01

The heartbeat rate signal provides an invaluable means of assessing the sympathetic-parasympathetic balance of the human autonomic nervous system and thus represents an ideal diagnostic mechanism for detecting a variety of disorders such as epilepsy, cardiac disease and so forth. The current study analyses the dynamics of the heartbeat rate signal of known epilepsy sufferers in order to obtain a detailed understanding of the heart rate pattern during a seizure event. In the proposed approach, the ECG signals are converted into heartbeat rate signals and the embedology theorem is then used to construct the corresponding multidimensional phase space. The dynamics of the heartbeat rate signal are then analyzed before, during and after an epileptic seizure by examining the maximum Lyapunov exponent and the correlation dimension of the attractors in the reconstructed phase space. In general, the results reveal that the heartbeat rate signal transits from an aperiodic, highly-complex behaviour before an epileptic seizure to a low dimensional chaotic motion during the seizure event. Following the seizure, the signal trajectories return to a highly-complex state, and the complex signal patterns associated with normal physiological conditions reappear.

Predictability, Force and (Anti-)Resonance in Complex Object Control.

PubMed

Maurice, Pauline; Hogan, Neville; Sternad, Dagmar

2018-04-18

Manipulation of complex objects as in tool use is ubiquitous and has given humans an evolutionary advantage. This study examined the strategies humans choose when manipulating an object with underactuated internal dynamics, such as a cup of coffee. The object's dynamics renders the temporal evolution complex, possibly even chaotic, and difficult to predict. A cart-and-pendulum model, loosely mimicking coffee sloshing in a cup, was implemented in a virtual environment with a haptic interface. Participants rhythmically manipulated the virtual cup containing a rolling ball; they could choose the oscillation frequency, while the amplitude was prescribed. Three hypotheses were tested: 1) humans decrease interaction forces between hand and object; 2) humans increase the predictability of the object dynamics; 3) humans exploit the resonances of the coupled object-hand system. Analysis revealed that humans chose either a high-frequency strategy with anti-phase cup-and-ball movements or a low-frequency strategy with in-phase cup-and-ball movements. Counter Hypothesis 1, they did not decrease interaction force; instead, they increased the predictability of the interaction dynamics, quantified by mutual information, supporting Hypothesis 2. To address Hypothesis 3, frequency analysis of the coupled hand-object system revealed two resonance frequencies separated by an anti-resonance frequency. The low-frequency strategy exploited one resonance, while the high-frequency strategy afforded more choice, consistent with the frequency response of the coupled system; both strategies avoided the anti-resonance. Hence, humans did not prioritize interaction force, but rather strategies that rendered interactions predictable. These findings highlight that physical interactions with complex objects pose control challenges not present in unconstrained movements.

Real-time high dynamic range laser scanning microscopy

NASA Astrophysics Data System (ADS)

Vinegoni, C.; Leon Swisher, C.; Fumene Feruglio, P.; Giedt, R. J.; Rousso, D. L.; Stapleton, S.; Weissleder, R.

2016-04-01

In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging.

Engineering science research issues in high power density transmission dynamics for aerospace applications. [rotorcraft geared rotors

NASA Technical Reports Server (NTRS)

Singh, Rajendra; Houser, Donald R.

1993-01-01

This paper discusses analytical and experimental approaches that will be needed to understand dynamic, vibro-acoustic and design characteristics of high power density rotorcraft transmissions. Complexities associated with mathematical modeling of such systems will be discussed. An overview of research work planned during the next several years will be presented, with emphasis on engineering science issues such as gear contact mechanics, multi-mesh drive dynamics, parameter uncertainties, vibration transmission through bearings, and vibro-acoustic characteristics of geared rotor systems and housing-mount structures. A few examples of work in progress are cited.

Grid-converged solution and analysis of the unsteady viscous flow in a two-dimensional shock tube

NASA Astrophysics Data System (ADS)

Zhou, Guangzhao; Xu, Kun; Liu, Feng

2018-01-01

The flow in a shock tube is extremely complex with dynamic multi-scale structures of sharp fronts, flow separation, and vortices due to the interaction of the shock wave, the contact surface, and the boundary layer over the side wall of the tube. Prediction and understanding of the complex fluid dynamics are of theoretical and practical importance. It is also an extremely challenging problem for numerical simulation, especially at relatively high Reynolds numbers. Daru and Tenaud ["Evaluation of TVD high resolution schemes for unsteady viscous shocked flows," Comput. Fluids 30, 89-113 (2001)] proposed a two-dimensional model problem as a numerical test case for high-resolution schemes to simulate the flow field in a square closed shock tube. Though many researchers attempted this problem using a variety of computational methods, there is not yet an agreed-upon grid-converged solution of the problem at the Reynolds number of 1000. This paper presents a rigorous grid-convergence study and the resulting grid-converged solutions for this problem by using a newly developed, efficient, and high-order gas-kinetic scheme. Critical data extracted from the converged solutions are documented as benchmark data. The complex fluid dynamics of the flow at Re = 1000 are discussed and analyzed in detail. Major phenomena revealed by the numerical computations include the downward concentration of the fluid through the curved shock, the formation of the vortices, the mechanism of the shock wave bifurcation, the structure of the jet along the bottom wall, and the Kelvin-Helmholtz instability near the contact surface. Presentation and analysis of those flow processes provide important physical insight into the complex flow physics occurring in a shock tube.

Dynamics Determine Signaling in a Multicomponent System Associated with Rheumatoid Arthritis.

PubMed

Lindgren, Cecilia; Tyagi, Mohit; Viljanen, Johan; Toms, Johannes; Ge, Changrong; Zhang, Naru; Holmdahl, Rikard; Kihlberg, Jan; Linusson, Anna

2018-05-24

Strategies that target multiple components are usually required for treatment of diseases originating from complex biological systems. The multicomponent system consisting of the DR4 major histocompatibility complex type II molecule, the glycopeptide CII259-273 from type II collagen, and a T-cell receptor is associated with development of rheumatoid arthritis (RA). We introduced non-native amino acids and amide bond isosteres into CII259-273 and investigated the effect on binding to DR4 and the subsequent T-cell response. Molecular dynamics simulations revealed that complexes between DR4 and derivatives of CII259-273 were highly dynamic. Signaling in the overall multicomponent system was found to depend on formation of an appropriate number of dynamic intramolecular hydrogen bonds between DR4 and CII259-273, together with the positioning of the galactose moiety of CII259-273 in the DR4 binding groove. Interestingly, the system tolerated modifications at several positions in CII259-273, indicating opportunities to use analogues to increase our understanding of how rheumatoid arthritis develops and for evaluation as vaccines to treat RA.

Automating the generation of finite element dynamical cores with Firedrake

NASA Astrophysics Data System (ADS)

Ham, David; Mitchell, Lawrence; Homolya, Miklós; Luporini, Fabio; Gibson, Thomas; Kelly, Paul; Cotter, Colin; Lange, Michael; Kramer, Stephan; Shipton, Jemma; Yamazaki, Hiroe; Paganini, Alberto; Kärnä, Tuomas

2017-04-01

The development of a dynamical core is an increasingly complex software engineering undertaking. As the equations become more complete, the discretisations more sophisticated and the hardware acquires ever more fine-grained parallelism and deeper memory hierarchies, the problem of building, testing and modifying dynamical cores becomes increasingly complex. Here we present Firedrake, a code generation system for the finite element method with specialist features designed to support the creation of geoscientific models. Using Firedrake, the dynamical core developer writes the partial differential equations in weak form in a high level mathematical notation. Appropriate function spaces are chosen and time stepping loops written at the same high level. When the programme is run, Firedrake generates high performance C code for the resulting numerics which are executed in parallel. Models in Firedrake typically take a tiny fraction of the lines of code required by traditional hand-coding techniques. They support more sophisticated numerics than are easily achieved by hand, and the resulting code is frequently higher performance. Critically, debugging, modifying and extending a model written in Firedrake is vastly easier than by traditional methods due to the small, highly mathematical code base. Firedrake supports a wide range of key features for dynamical core creation: A vast range of discretisations, including both continuous and discontinuous spaces and mimetic (C-grid-like) elements which optimally represent force balances in geophysical flows. High aspect ratio layered meshes suitable for ocean and atmosphere domains. Curved elements for high accuracy representations of the sphere. Support for non-finite element operators, such as parametrisations. Access to PETSc, a world-leading library of programmable linear and nonlinear solvers. High performance adjoint models generated automatically by symbolically reasoning about the forward model. This poster will present the key features of the Firedrake system, as well as those of Gusto, an atmospheric dynamical core, and Thetis, a coastal ocean model, both of which are written in Firedrake.

Development of nanoscale structure in LAT-based signaling complexes

PubMed Central

2016-01-01

ABSTRACT The adapter molecule linker for activation of T cells (LAT) plays a crucial role in forming signaling complexes induced by stimulation of the T cell receptor (TCR). These multi-molecular complexes are dynamic structures that activate highly regulated signaling pathways. Previously, we have demonstrated nanoscale structure in LAT-based complexes where the adapter SLP-76 (also known as LCP2) localizes to the periphery of LAT clusters. In this study, we show that initially LAT and SLP-76 are randomly dispersed throughout the clusters that form upon TCR engagement. The segregation of LAT and SLP-76 develops near the end of the spreading process. The local concentration of LAT also increases at the same time. Both changes require TCR activation and an intact actin cytoskeleton. These results demonstrate that the nanoscale organization of LAT-based signaling complexes is dynamic and indicates that different kinds of LAT-based complexes appear at different times during T cell activation. PMID:27875277

From precision polymers to complex materials and systems

NASA Astrophysics Data System (ADS)

Lutz, Jean-François; Lehn, Jean-Marie; Meijer, E. W.; Matyjaszewski, Krzysztof

2016-05-01

Complex chemical systems, such as living biological matter, are highly organized structures based on discrete molecules in constant dynamic interactions. These natural materials can evolve and adapt to their environment. By contrast, man-made materials exhibit simpler properties. In this Review, we highlight that most of the necessary elements for the development of more complex synthetic matter are available today. Using modern strategies, such as controlled radical polymerizations, supramolecular polymerizations or stepwise synthesis, polymers with precisely controlled molecular structures can be synthesized. Moreover, such tailored polymers can be folded or self-assembled into defined nanoscale morphologies. These self-organized macromolecular objects can be at thermal equilibrium or can be driven out of equilibrium. Recently, in the latter case, interesting dynamic materials have been developed. However, this is just a start, and more complex adaptive materials are anticipated.

Time Factor in the Theory of Anthropogenic Risk Prediction in Complex Dynamic Systems

NASA Astrophysics Data System (ADS)

Ostreikovsky, V. A.; Shevchenko, Ye N.; Yurkov, N. K.; Kochegarov, I. I.; Grishko, A. K.

2018-01-01

The article overviews the anthropogenic risk models that take into consideration the development of different factors in time that influence the complex system. Three classes of mathematical models have been analyzed for the use in assessing the anthropogenic risk of complex dynamic systems. These models take into consideration time factor in determining the prospect of safety change of critical systems. The originality of the study is in the analysis of five time postulates in the theory of anthropogenic risk and the safety of highly important objects. It has to be stressed that the given postulates are still rarely used in practical assessment of equipment service life of critically important systems. That is why, the results of study presented in the article can be used in safety engineering and analysis of critically important complex technical systems.

Weighted fractional permutation entropy and fractional sample entropy for nonlinear Potts financial dynamics

NASA Astrophysics Data System (ADS)

Xu, Kaixuan; Wang, Jun

2017-02-01

In this paper, recently introduced permutation entropy and sample entropy are further developed to the fractional cases, weighted fractional permutation entropy (WFPE) and fractional sample entropy (FSE). The fractional order generalization of information entropy is utilized in the above two complexity approaches, to detect the statistical characteristics of fractional order information in complex systems. The effectiveness analysis of proposed methods on the synthetic data and the real-world data reveals that tuning the fractional order allows a high sensitivity and more accurate characterization to the signal evolution, which is useful in describing the dynamics of complex systems. Moreover, the numerical research on nonlinear complexity behaviors is compared between the returns series of Potts financial model and the actual stock markets. And the empirical results confirm the feasibility of the proposed model.

Organizational Agility and Complex Enterprise System Innovations: A Mixed Methods Study of the Effects of Enterprise Systems on Organizational Agility

ERIC Educational Resources Information Center

Kharabe, Amol T.

2012-01-01

Over the last two decades, firms have operated in "increasingly" accelerated "high-velocity" dynamic markets, which require them to become "agile." During the same time frame, firms have increasingly deployed complex enterprise systems--large-scale packaged software "innovations" that integrate and automate…

Aerodynamic calculations of the Sienna towers buildings complex with respect to human vibrations comfort of their users

NASA Astrophysics Data System (ADS)

Krajewski, Piotr; Flaga, Łukasz; Flaga, Andrzej

2018-01-01

The paper presents aerodynamic calculations of the Sienna Towers high buildings complex in Warsaw using authors mathematical model of the considered issue. Human vibrations comfort criteria were checked according to ISO/6897. Dynamic coefficients used in the calculations were obtained from wind tunnel tests.

Complementarity of stability patches at the interfaces of protein complexes: Implication for the structural organization of energetic hot spots.

PubMed

Kuttner, Yosef Y; Engel, Stanislav

2018-02-01

A rational design of protein complexes with defined functionalities and of drugs aimed at disrupting protein-protein interactions requires fundamental understanding of the mechanisms underlying the formation of specific protein complexes. Efforts to develop efficient small-molecule or protein-based binders often exploit energetic hot spots on protein surfaces, namely, the interfacial residues that provide most of the binding free energy in the complex. The molecular basis underlying the unusually high energy contribution of the hot spots remains obscure, and its elucidation would facilitate the design of interface-targeted drugs. To study the nature of the energetic hot spots, we analyzed the backbone dynamic properties of contact surfaces in several protein complexes. We demonstrate that, in most complexes, the backbone dynamic landscapes of interacting surfaces form complementary "stability patches," in which static areas from the opposing surfaces superimpose, and that these areas are predominantly located near the geometric center of the interface. We propose that a diminished enthalpy-entropy compensation effect augments the degree to which residues positioned within the complementary stability patches contribute to complex affinity, thereby giving rise to the energetic hot spots. These findings offer new insights into the nature of energetic hot spots and the role that backbone dynamics play in facilitating intermolecular recognition. Mapping the interfacial stability patches may provide guidance for protein engineering approaches aimed at improving the stability of protein complexes and could facilitate the design of ligands that target complex interfaces. © 2017 Wiley Periodicals, Inc.

Dynamics driving function: new insights from electron transferring flavoproteins and partner complexes.

PubMed

Toogood, Helen S; Leys, David; Scrutton, Nigel S

2007-11-01

Electron transferring flavoproteins (ETFs) are soluble heterodimeric FAD-containing proteins that function primarily as soluble electron carriers between various flavoprotein dehydrogenases. ETF is positioned at a key metabolic branch point, responsible for transferring electrons from up to 10 primary dehydrogenases to the membrane-bound respiratory chain. Clinical mutations of ETF result in the often fatal disease glutaric aciduria type II. Structural and biophysical studies of ETF in complex with partner proteins have shown that ETF partitions the functions of partner binding and electron transfer between (a) a 'recognition loop', which acts as a static anchor at the ETF-partner interface, and (b) a highly mobile redox-active FAD domain. Together, this enables the FAD domain of ETF to sample a range of conformations, some compatible with fast interprotein electron transfer. This 'conformational sampling' enables ETF to recognize structurally distinct partners, whilst also maintaining a degree of specificity. Complex formation triggers mobility of the FAD domain, an 'induced disorder' mechanism contrasting with the more generally accepted models of protein-protein interaction by induced fit mechanisms. We discuss the implications of the highly dynamic nature of ETFs in biological interprotein electron transfer. ETF complexes point to mechanisms of electron transfer in which 'dynamics drive function', a feature that is probably widespread in biology given the modular assembly and flexible nature of biological electron transfer systems.

Dynamic pathway modeling of signal transduction networks: a domain-oriented approach.

PubMed

Conzelmann, Holger; Gilles, Ernst-Dieter

2008-01-01

Mathematical models of biological processes become more and more important in biology. The aim is a holistic understanding of how processes such as cellular communication, cell division, regulation, homeostasis, or adaptation work, how they are regulated, and how they react to perturbations. The great complexity of most of these processes necessitates the generation of mathematical models in order to address these questions. In this chapter we provide an introduction to basic principles of dynamic modeling and highlight both problems and chances of dynamic modeling in biology. The main focus will be on modeling of s transduction pathways, which requires the application of a special modeling approach. A common pattern, especially in eukaryotic signaling systems, is the formation of multi protein signaling complexes. Even for a small number of interacting proteins the number of distinguishable molecular species can be extremely high. This combinatorial complexity is due to the great number of distinct binding domains of many receptors and scaffold proteins involved in signal transduction. However, these problems can be overcome using a new domain-oriented modeling approach, which makes it possible to handle complex and branched signaling pathways.

Watching cellular machinery in action, one molecule at a time.

PubMed

Monachino, Enrico; Spenkelink, Lisanne M; van Oijen, Antoine M

2017-01-02

Single-molecule manipulation and imaging techniques have become important elements of the biologist's toolkit to gain mechanistic insights into cellular processes. By removing ensemble averaging, single-molecule methods provide unique access to the dynamic behavior of biomolecules. Recently, the use of these approaches has expanded to the study of complex multiprotein systems and has enabled detailed characterization of the behavior of individual molecules inside living cells. In this review, we provide an overview of the various force- and fluorescence-based single-molecule methods with applications both in vitro and in vivo, highlighting these advances by describing their applications in studies on cytoskeletal motors and DNA replication. We also discuss how single-molecule approaches have increased our understanding of the dynamic behavior of complex multiprotein systems. These methods have shown that the behavior of multicomponent protein complexes is highly stochastic and less linear and deterministic than previously thought. Further development of single-molecule tools will help to elucidate the molecular dynamics of these complex systems both inside the cell and in solutions with purified components. © 2017 Monachino et al.

Large eddy simulation of a boundary layer with concave streamwise curvature

NASA Technical Reports Server (NTRS)

Lund, Thomas S.

1993-01-01

One of the most exciting recent developments in the field of large eddy simulation (LES) is the dynamic subgrid-scale model. The dynamic model concept is a general procedure for evaluating model constants by sampling a band of the smallest scales actually resolved in the simulation. To date, the procedure has been used primarily in conjunction with the Smagorinsky model. The dynamic procedure has the advantage that the value of the model constant need not be specified a priori, but rather is calculated as a function of space and time as the simulation progresses. This feature makes the dynamic model especially attractive for flows in complex geometries where it is difficult or impossible to calibrate model constants. The dynamic model was highly successful in benchmark tests involving homogeneous and channel flows. Having demonstrated the potential of the dynamic model in these simple flows, the overall direction of the LES effort at CTR shifted toward an evaluation of the model in more complex situations. The current test cases are basic engineering-type flows for which Reynolds averaged approaches were unable to model the turbulence to within engineering accuracy. Flows currently under investigation include a backward-facing step, wake behind a circular cylinder, airfoil at high angles of attack, separated flow in a diffuser, and boundary layer over a concave surface. Preliminary results from the backward-facing step and cylinder wake simulations are encouraging. Progress on the LES of a boundary layer on a concave surface is discussed. Although the geometry of a concave wall is not very complex, the boundary layer that develops on its surface is difficult to model due to the presence of streamwise Taylor-Gortler vortices. These vortices arise as a result of a centrifugal instability associated with the convex curvature.

High-Order Ca(II)-Chloro Complexes in Mixed CaCl2-LiCl Aqueous Solution: Insights from Density Functional Theory and Molecular Dynamics Simulations.

PubMed

Wang, Yu-Lin; Wang, Ying; Yi, Hai-Bo

2016-07-21

In this study, the structural characteristics of high-coordinated Ca-Cl complexes present in mixed CaCl2-LiCl aqueous solution were investigated using density functional theory (DFT) and molecular dynamics (MD) simulations. The DFT results show that [CaClx](2-x) (x = 4-6) clusters are quite unstable in the gas phase, but these clusters become metastable when hydration is considered. The MD simulations show that high-coordinated Ca-chloro complexes are possible transient species that exist for up to nanoseconds in concentrated (11.10 mol·kg(-1)) Cl(-) solution at 273 and 298 K. As the temperature increases to 423 K, these high-coordinated structures tend to disassociate and convert into smaller clusters and single free ions. The presence of high-order Ca-Cl species in concentrated LiCl solution can be attributed to their enhanced hydration shell and the inadequate hydration of ions. The probability of the [CaClx](2-x)aq (x = 4-6) species being present in concentrated LiCl solution decreases greatly with increasing temperature, which also indicates that the formation of the high-coordinated Ca-Cl structure is related to its hydration characteristics.

High-fidelity simulation capability for virtual testing of seismic and acoustic sensors

NASA Astrophysics Data System (ADS)

Wilson, D. Keith; Moran, Mark L.; Ketcham, Stephen A.; Lacombe, James; Anderson, Thomas S.; Symons, Neill P.; Aldridge, David F.; Marlin, David H.; Collier, Sandra L.; Ostashev, Vladimir E.

2005-05-01

This paper describes development and application of a high-fidelity, seismic/acoustic simulation capability for battlefield sensors. The purpose is to provide simulated sensor data so realistic that they cannot be distinguished by experts from actual field data. This emerging capability provides rapid, low-cost trade studies of unattended ground sensor network configurations, data processing and fusion strategies, and signatures emitted by prototype vehicles. There are three essential components to the modeling: (1) detailed mechanical signature models for vehicles and walkers, (2) high-resolution characterization of the subsurface and atmospheric environments, and (3) state-of-the-art seismic/acoustic models for propagating moving-vehicle signatures through realistic, complex environments. With regard to the first of these components, dynamic models of wheeled and tracked vehicles have been developed to generate ground force inputs to seismic propagation models. Vehicle models range from simple, 2D representations to highly detailed, 3D representations of entire linked-track suspension systems. Similarly detailed models of acoustic emissions from vehicle engines are under development. The propagation calculations for both the seismics and acoustics are based on finite-difference, time-domain (FDTD) methodologies capable of handling complex environmental features such as heterogeneous geologies, urban structures, surface vegetation, and dynamic atmospheric turbulence. Any number of dynamic sources and virtual sensors may be incorporated into the FDTD model. The computational demands of 3D FDTD simulation over tactical distances require massively parallel computers. Several example calculations of seismic/acoustic wave propagation through complex atmospheric and terrain environments are shown.

Backbone dynamics in an intramolecular prolylpeptide-SH3 complex from the diphtheria toxin repressor, DtxR

PubMed Central

Bhattacharya, Nilakshee; Yi, Myunggi; Zhou, Huan-Xiang; Logan, Timothy M.

2008-01-01

Summary The diphtheria toxin repressor contains an SH3-like domain that forms an intramolecular complex with a proline-rich (Pr) peptide segment and stabilizes the inactive state of the repressor. Upon activation of DtxR by transition metals, this intramolecular complex must dissociate as the SH3 domain and Pr segment form different interactions in the active repressor. In this study we investigate the dynamics of this intramolecular complex using backbone amide nuclear spin relaxation rates determined using NMR spectroscopy and molecular dynamics trajectories. The SH3 domain in the unbound and bound states showed typical dynamics in that the secondary structures were fairly ordered with high generalized order parameters and low effective correlation times while residues in the loops connecting β-strands exhibited reduced generalized order parameters and required additional motional terms to adequately model the relaxation rates. Residues forming the Pr segment exhibited low order parameters with internal rotational correlation times on the order of 0.6 – 1 ns. Further analysis showed that the SH3 domain was rich in millisecond timescale motions while the Pr segment was rich in motions on the 100s μs timescale. Molecular dynamics simultations indicated structural rearrangements that may contribute to the observed relaxation rates and, together with the observed relaxation rate data, suggested that the Pr segment exhibits a binding ↔ unbinding equilibrium. The results of this study provide new insights into the nature of the intramolecular complex and provide a better understanding of the biological role of the SH3 domain in regulating DtxR activity. PMID:17976643

Satellite remote sensing of landscape freeze/thaw state dynamics for complex Topography and Fire Disturbance Areas Using multi-sensor radar and SRTM digital elevation models

NASA Technical Reports Server (NTRS)

Podest, Erika; McDonald, Kyle; Kimball, John; Randerson, James

2003-01-01

We characterize differences in radar-derived freeze/thaw state, examining transitions over complex terrain and landscape disturbance regimes. In areas of complex terrain, we explore freezekhaw dynamics related to elevation, slope aspect and varying landcover. In the burned regions, we explore the timing of seasonal freeze/thaw transition as related to the recovering landscape, relative to that of a nearby control site. We apply in situ biophysical measurements, including flux tower measurements to validate and interpret the remotely sensed parameters. A multi-scale analysis is performed relating high-resolution SAR backscatter and moderate resolution scatterometer measurements to assess trade-offs in spatial and temporal resolution in the remotely sensed fields.

Environmental variation, vegetation distribution, carbon dynamics and water/energy exchange at high latitudes

USGS Publications Warehouse

McGuire, A.D.; Wirth, C.; Apps, M.; Beringer, J.; Clein, J.; Epstein, H.; Kicklighter, D.W.; Bhatti, J.; Chapin, F. S.; De Groot, B.; Efremov, D.; Eugster, W.; Fukuda, M.; Gower, T.; Hinzman, L.; Huntley, B.; Jia, G.J.; Kasischke, E.; Melillo, J.; Romanovsky, V.; Shvidenko, A.; Vaganov, E.; Walker, D.

2002-01-01

The responses of high latitude ecosystems to global change involve complex interactions among environmental variables, vegetation distribution, carbon dynamics, and water and energy exchange. These responses may have important consequences for the earth system. In this study, we evaluated how vegetation distribution, carbon stocks and turnover, and water and energy exchange are related to environmental variation spanned by the network of the IGBP high latitude transects. While the most notable feature of the high latitude transects is that they generally span temperature gradients from southern to northern latitudes, there are substantial differences in temperature among the transects. Also, along each transect temperature co-varies with precipitation and photosynthetically active radiation, which are also variable among the transects. Both climate and disturbance interact to influence latitudinal patterns of vegetation and soil carbon storage among the transects, and vegetation distribution appears to interact with climate to determine exchanges of heat and moisture in high latitudes. Despite limitations imposed by the data we assembled, the analyses in this study have taken an important step toward clarifying the complexity of interactions among environmental variables, vegetation distribution, carbon stocks and turnover, and water and energy exchange in high latitude regions. This study reveals the need to conduct coordinated global change studies in high latitudes to further elucidate how interactions among climate, disturbance, and vegetation distribution influence carbon dynamics and water and energy exchange in high latitudes.

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

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

All-atom molecular dynamics simulation of a photosystem i/detergent complex.

PubMed

Harris, Bradley J; Cheng, Xiaolin; Frymier, Paul

2014-10-09

All-atom molecular dynamics (MD) simulation was used to investigate the solution structure and dynamics of the photosynthetic pigment-protein complex photosystem I (PSI) from Thermosynechococcus elongatus embedded in a toroidal belt of n-dodecyl-β-d-maltoside (DDM) detergent. Evaluation of root-mean-square deviations (RMSDs) relative to the known crystal structure show that the protein complex surrounded by DDM molecules is stable during the 200 ns simulation time, and root-mean-square fluctuation (RMSF) analysis indicates that regions of high local mobility correspond to solvent-exposed regions such as turns in the transmembrane α-helices and flexible loops on the stromal and lumenal faces. Comparing the protein-detergent complex to a pure detergent micelle, the detergent surrounding the PSI trimer is found to be less densely packed but with more ordered detergent tails, contrary to what is seen in most lipid bilayer models. We also investigated any functional implications for the observed conformational dynamics and protein-detergent interactions, discovering interesting structural changes in the psaL subunits associated with maintaining the trimeric structure of the protein. Importantly, we find that the docking of soluble electron mediators such as cytochrome c6 and ferredoxin to PSI is not significantly impacted by the solubilization of PSI in detergent.

Nonlinear optical oscillation dynamics in high-Q lithium niobate microresonators.

PubMed

Sun, Xuan; Liang, Hanxiao; Luo, Rui; Jiang, Wei C; Zhang, Xi-Cheng; Lin, Qiang

2017-06-12

Recent advance of lithium niobate microphotonic devices enables the exploration of intriguing nonlinear optical effects. We show complex nonlinear oscillation dynamics in high-Q lithium niobate microresonators that results from unique competition between the thermo-optic nonlinearity and the photorefractive effect, distinctive to other device systems and mechanisms ever reported. The observed phenomena are well described by our theory. This exploration helps understand the nonlinear optical behavior of high-Q lithium niobate microphotonic devices which would be crucial for future application of on-chip nonlinear lithium niobate photonics.

Domain Specific vs Domain General: Implications for Dynamic Assessment

ERIC Educational Resources Information Center

Kaniel, Shlomo

2010-01-01

The article responds to the need for evidence-based dynamic assessment. The article is divided into two sections: In Part 1 we examine the scientific answer to the question of how far human mental activities and capabilities are domain general (DG) / domain specific (DS). A highly complex answer emerges from the literature review of domains such…

Introduction to State Estimation of High-Rate System Dynamics

PubMed Central

Dodson, Jacob; Joyce, Bryan

2018-01-01

Engineering systems experiencing high-rate dynamic events, including airbags, debris detection, and active blast protection systems, could benefit from real-time observability for enhanced performance. However, the task of high-rate state estimation is challenging, in particular for real-time applications where the rate of the observer’s convergence needs to be in the microsecond range. This paper identifies the challenges of state estimation of high-rate systems and discusses the fundamental characteristics of high-rate systems. A survey of applications and methods for estimators that have the potential to produce accurate estimations for a complex system experiencing highly dynamic events is presented. It is argued that adaptive observers are important to this research. In particular, adaptive data-driven observers are advantageous due to their adaptability and lack of dependence on the system model. PMID:29342855

Pricing the Services in Dynamic Environment: Agent Pricing Model

NASA Astrophysics Data System (ADS)

Žagar, Drago; Rupčić, Slavko; Rimac-Drlje, Snježana

New Internet applications and services as well as new user demands open many new issues concerning dynamic management of quality of service and price for received service, respectively. The main goals of Internet service providers are to maximize profit and maintain a negotiated quality of service. From the users' perspective the main goal is to maximize ratio of received QoS and costs of service. However, achieving these objectives could become very complex if we know that Internet service users might during the session become highly dynamic and proactive. This connotes changes in user profile or network provider/s profile caused by high level of user mobility or variable level of user demands. This paper proposes a new agent based pricing architecture for serving the highly dynamic customers in context of dynamic user/network environment. The proposed architecture comprises main aspects and basic parameters that will enable objective and transparent assessment of the costs for the service those Internet users receive while dynamically change QoS demands and cost profile.

Controlled Detonation Dynamics in Additively Manufactured High Explosives

NASA Astrophysics Data System (ADS)

Schmalzer, Andrew; Tappan, Bryce; Bowden, Patrick; Manner, Virginia; Clements, Brad; Menikoff, Ralph; Ionita, Axinte; Branch, Brittany; Dattelbaum, Dana; Espy, Michelle; Patterson, Brian; Wu, Ruilian; Mueller, Alexander

2017-06-01

The effect of structure in explosives has long been a subject of interest to explosives engineers and scientists. Through structure, detonation dynamics in explosives can be manipulated, introducing a new level of safety and directed performance into these previously difficult to control materials. New advances in additive manufacturing (AM) allow the deliberate introduction of exact internal structures at dimensions approaching the mesoscale of these energetic materials. We show through simulation and experiment that this structure can be used to control detonation behavior by manipulating complex shockwave interactions. We use high-speed video and shorting mag-wires to determine the detonation velocity in AM generated explosive structures, demonstrating, for the first time, a method of controlling the directional propagation of reactive flow through the controlled introduction of structure within a high explosive. With ongoing improvement in the AM methods available coupled with guidance through modeling and simulations, more complex interactions are being explored. LANL LDRD Office.

Large-scale inference of protein tissue origin in gram-positive sepsis plasma using quantitative targeted proteomics

PubMed Central

Malmström, Erik; Kilsgård, Ola; Hauri, Simon; Smeds, Emanuel; Herwald, Heiko; Malmström, Lars; Malmström, Johan

2016-01-01

The plasma proteome is highly dynamic and variable, composed of proteins derived from surrounding tissues and cells. To investigate the complex processes that control the composition of the plasma proteome, we developed a mass spectrometry-based proteomics strategy to infer the origin of proteins detected in murine plasma. The strategy relies on the construction of a comprehensive protein tissue atlas from cells and highly vascularized organs using shotgun mass spectrometry. The protein tissue atlas was transformed to a spectral library for highly reproducible quantification of tissue-specific proteins directly in plasma using SWATH-like data-independent mass spectrometry analysis. We show that the method can determine drastic changes of tissue-specific protein profiles in blood plasma from mouse animal models with sepsis. The strategy can be extended to several other species advancing our understanding of the complex processes that contribute to the plasma proteome dynamics. PMID:26732734

Conformational changes in intact dengue virus reveal serotype-specific expansion

PubMed Central

Lim, Xin-Xiang; Chandramohan, Arun; Lim, Xin Ying Elisa; Bag, Nirmalya; Sharma, Kamal Kant; Wirawan, Melissa; Wohland, Thorsten; Lok, Shee-Mei; Anand, Ganesh S.

2017-01-01

Dengue virus serotype 2 (DENV2) alone undergoes structural expansion at 37 °C (associated with host entry), despite high sequence and structural homology among the four known serotypes. The basis for this differential expansion across strains and serotypes is unknown and necessitates mapping of the dynamics of dengue whole viral particles to describe their coordinated motions and conformational changes when exposed to host-like environments. Here we capture the dynamics of intact viral particles of two serotypes, DENV1 and DENV2, by amide hydrogen/deuterium exchange mass spectrometry (HDXMS) and time resolved Förster Resonance Energy Transfer. Our results show temperature-dependent dynamics hotspots on DENV2 and DENV1 particles with DENV1 showing expansion at 40 °C but not at 37 °C. HDXMS measurement of virion dynamics in solution offers a powerful approach to identify potential epitopes, map virus-antibody complex structure and dynamics, and test effects of multiple host-specific perturbations on viruses and virus-antibody complexes. PMID:28186093

A photo-cross-linking approach to monitor folding and assembly of newly synthesized proteins in a living cell.

PubMed

Miyazaki, Ryoji; Myougo, Naomi; Mori, Hiroyuki; Akiyama, Yoshinori

2018-01-12

Many proteins form multimeric complexes that play crucial roles in various cellular processes. Studying how proteins are correctly folded and assembled into such complexes in a living cell is important for understanding the physiological roles and the qualitative and quantitative regulation of the complex. However, few methods are suitable for analyzing these rapidly occurring processes. Site-directed in vivo photo-cross-linking is an elegant technique that enables analysis of protein-protein interactions in living cells with high spatial resolution. However, the conventional site-directed in vivo photo-cross-linking method is unsuitable for analyzing dynamic processes. Here, by combining an improved site-directed in vivo photo-cross-linking technique with a pulse-chase approach, we developed a new method that can analyze the folding and assembly of a newly synthesized protein with high spatiotemporal resolution. We demonstrate that this method, named the pulse-chase and in vivo photo-cross-linking experiment (PiXie), enables the kinetic analysis of the formation of an Escherichia coli periplasmic (soluble) protein complex (PhoA). We also used our new technique to investigate assembly/folding processes of two membrane complexes (SecD-SecF in the inner membrane and LptD-LptE in the outer membrane), which provided new insights into the biogenesis of these complexes. Our PiXie method permits analysis of the dynamic behavior of various proteins and enables examination of protein-protein interactions at the level of individual amino acid residues. We anticipate that our new technique will have valuable utility for studies of protein dynamics in many organisms. © 2018 by The American Society for Biochemistry and Molecular Biology, Inc.

COMPARISON OF CHAOTIC AND FRACTAL PROPERTIES OF POLAR FACULAE WITH SUNSPOT ACTIVITY

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

Deng, L. H.; Xiang, Y. Y.; Dun, G. T.

The solar magnetic activity is governed by a complex dynamo mechanism and exhibits a nonlinear dissipation behavior in nature. The chaotic and fractal properties of solar time series are of great importance to understanding the solar dynamo actions, especially with regard to the nonlinear dynamo theories. In the present work, several nonlinear analysis approaches are proposed to investigate the nonlinear dynamical behavior of the polar faculae and sunspot activity for the time interval from 1951 August to 1998 December. The following prominent results are found: (1) both the high- and the low-latitude solar activity are governed by a three-dimensional chaoticmore » attractor, and the chaotic behavior of polar faculae is the most complex, followed by that of the sunspot areas, and then the sunspot numbers; (2) both the high- and low-latitude solar activity exhibit a high degree of persistent behavior, and their fractal nature is due to such long-range correlation; (3) the solar magnetic activity cycle is predictable in nature, but the high-accuracy prediction should only be done for short- to mid-term due to its intrinsically dynamical complexity. With the help of the Babcock–Leighton dynamo model, we suggest that the nonlinear coupling of the polar magnetic fields with strong active-region fields exhibits a complex manner, causing the statistical similarities and differences between the polar faculae and the sunspot-related indicators.« less

Event- and Time-Driven Techniques Using Parallel CPU-GPU Co-processing for Spiking Neural Networks

PubMed Central

Naveros, Francisco; Garrido, Jesus A.; Carrillo, Richard R.; Ros, Eduardo; Luque, Niceto R.

2017-01-01

Modeling and simulating the neural structures which make up our central neural system is instrumental for deciphering the computational neural cues beneath. Higher levels of biological plausibility usually impose higher levels of complexity in mathematical modeling, from neural to behavioral levels. This paper focuses on overcoming the simulation problems (accuracy and performance) derived from using higher levels of mathematical complexity at a neural level. This study proposes different techniques for simulating neural models that hold incremental levels of mathematical complexity: leaky integrate-and-fire (LIF), adaptive exponential integrate-and-fire (AdEx), and Hodgkin-Huxley (HH) neural models (ranged from low to high neural complexity). The studied techniques are classified into two main families depending on how the neural-model dynamic evaluation is computed: the event-driven or the time-driven families. Whilst event-driven techniques pre-compile and store the neural dynamics within look-up tables, time-driven techniques compute the neural dynamics iteratively during the simulation time. We propose two modifications for the event-driven family: a look-up table recombination to better cope with the incremental neural complexity together with a better handling of the synchronous input activity. Regarding the time-driven family, we propose a modification in computing the neural dynamics: the bi-fixed-step integration method. This method automatically adjusts the simulation step size to better cope with the stiffness of the neural model dynamics running in CPU platforms. One version of this method is also implemented for hybrid CPU-GPU platforms. Finally, we analyze how the performance and accuracy of these modifications evolve with increasing levels of neural complexity. We also demonstrate how the proposed modifications which constitute the main contribution of this study systematically outperform the traditional event- and time-driven techniques under increasing levels of neural complexity. PMID:28223930

Real-time high dynamic range laser scanning microscopy

PubMed Central

Vinegoni, C.; Leon Swisher, C.; Fumene Feruglio, P.; Giedt, R. J.; Rousso, D. L.; Stapleton, S.; Weissleder, R.

2016-01-01

In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging. PMID:27032979

Stability Result For Dynamic Inversion Devised to Control Large Flexible Aircraft

NASA Technical Reports Server (NTRS)

Gregory, Irene M.

2001-01-01

High performance aircraft of the future will be designed lighter, more maneuverable, and operate over an ever expanding flight envelope. One of the largest differences from the flight control perspective between current and future advanced aircraft is elasticity. Over the last decade, dynamic inversion methodology has gained considerable popularity in application to highly maneuverable fighter aircraft, which were treated as rigid vehicles. This paper is an initial attempt to establish global stability results for dynamic inversion methodology as applied to a large, flexible aircraft. This work builds on a previous result for rigid fighter aircraft and adds a new level of complexity that is the flexible aircraft dynamics, which cannot be ignored even in the most basic flight control. The results arise from observations of the control laws designed for a new generation of the High-Speed Civil Transport aircraft.

The dynamic origins of positive health and wellbeing

PubMed Central

Cloninger, C. Robert; Salloum, Ihsan M.; Mezzich, Juan E.

2015-01-01

The causes of wellbeing and illbeing interact with feedback dynamics resulting in the same set of traits giving rise to a variety of health outcomes (multi-finality) and different traits giving rise to the same health outcome (equi-finality). As a result, a full understanding of health and its disorders must be in terms of a complex adaptive system of causes, rather than in terms of categorical diagnoses or sets of symptoms. The three domains of person-centered integrative diagnosis (PID) are considered here as interacting components of a complex adaptive system comprised of health status (functioning/wellness versus disability/disorder), experience of health (self-awareness/fulfillment versus misunderstanding/suffering) and contributors to health (protective versus risk factors). The PID domains thereby allow healthcare and health promotion to be understood in terms of measurable components of a complex adaptive system. Three major concepts of health are examined in detail to identify their dynamic origins: Psychological Maturity, Flourishing and Resilience. In humanistic psychology, psychological maturity (i.e. healthy personality, mental wellbeing) involves the development of high self-directedness, high co-operativeness and high self-transcendence, but self-transcendence is nevertheless devalued in individualistic and materialistic cultures except when people must face adversity and ultimate situations like suffering or the threat of death. Psychological Maturity develops through two complementary processes often labeled as Flourishing and Resilience. Flourishing is the development of one’s potential to live optimally, especially as the result of favorable circumstances, whereas Resilience is positive adaptation to life despite adverse circumstances. As a result of the complex feedback dynamics between the processes of flourishing and resilience, each person is a unique individual who has a variety of paths for achieving positive health and wellbeing open to him or her. Person-centered health promotion and care can thereby be approached as a creative life project that can be conducted with the assistance of healthcare workers who are both therapeutic allies and well-informed experts. PMID:26140189

The relationship between structure and function in locally observed complex networks

NASA Astrophysics Data System (ADS)

Comin, Cesar H.; Viana, Matheus P.; Costa, Luciano da F.

2013-01-01

Recently, studies looking at the small scale interactions taking place in complex networks have started to unveil the wealth of interactions that occur between groups of nodes. Such findings make the claim for a new systematic methodology to quantify, at node level, how dynamics are influenced (or differentiated) by the structure of the underlying system. Here we define a new measure that, based on the dynamical characteristics obtained for a large set of initial conditions, compares the dynamical behavior of the nodes present in the system. Through this measure, we find that the geographic and Barabási-Albert models have a high capacity for generating networks that exhibit groups of nodes with distinct dynamics compared to the rest of the network. The application of our methodology is illustrated with respect to two real systems. In the first we use the neuronal network of the nematode Caenorhabditis elegans to show that the interneurons of the ventral cord of the nematode present a very large dynamical differentiation when compared to the rest of the network. The second application concerns the SIS epidemic model on an airport network, where we quantify how different the distribution of infection times of high and low degree nodes can be, when compared to the expected value for the network.

Frequency analysis of stress relaxation dynamics in model asphalts

NASA Astrophysics Data System (ADS)

Masoori, Mohammad; Greenfield, Michael L.

2014-09-01

Asphalt is an amorphous or semi-crystalline material whose mechanical performance relies on viscoelastic responses to applied strain or stress. Chemical composition and its effect on the viscoelastic properties of model asphalts have been investigated here by computing complex modulus from molecular dynamics simulation results for two different model asphalts whose compositions each resemble the Strategic Highway Research Program AAA-1 asphalt in different ways. For a model system that contains smaller molecules, simulation results for storage and loss modulus at 443 K reach both the low and high frequency scaling limits of the Maxwell model. Results for a model system composed of larger molecules (molecular weights 300-900 g/mol) with longer branches show a quantitatively higher complex modulus that decreases significantly as temperature increases over 400-533 K. Simulation results for its loss modulus approach the low frequency scaling limit of the Maxwell model at only the highest temperature simulated. A Black plot or van Gurp-Palman plot of complex modulus vs. phase angle for the system of larger molecules suggests some overlap among results at different temperatures for less high frequencies, with an interdependence consistent with the empirical Christensen-Anderson-Marasteanu model. Both model asphalts are thermorheologically complex at very high frequencies, where they show a loss peak that appears to be independent of temperature and density.

Complex Plasmas under free fall conditions aboard the International Space Station

NASA Astrophysics Data System (ADS)

Konopka, Uwe; Thomas, Edward, Jr.; Funk, Dylan; Doyle, Brandon; Williams, Jeremiah; Knapek, Christina; Thomas, Hubertus

2017-10-01

Complex Plasmas are dynamically dominated by massive, highly negatively charged, micron-sized particles. They are usually strongly coupled and as a result can show fluid-like behavior or undergo phase transitions to form crystalline structures. The dynamical time scale of these systems is easily accessible in experiments because of the relatively high mass/inertia of the particles. However, the high mass also leads to sedimentation effects and as a result prevents the conduction of large scale, fully three dimensional experiments that are necessary to utilize complex plasmas as model systems in the transition to continuous media. To reduce sedimentation influences it becomes necessary to perform experiments in a free-fall (``microgravity'') environment, such as the ISS based experiment facility ``Plasma-Kristall-4'' (``PK-4''). In our paper we will present our recently started research activities to investigate the basic properties of complex plasmas by utilizing the PK-4 experiment facility aboard the ISS. We further give an overview of developments towards the next generation experiment facility ``Ekoplasma'' (formerly named ``PlasmaLab'') and discuss potential additional small-scale space-based experiment scenarios. This work was supported by the JPL/NASA (JPL-RSA 1571699), the US Dept. of Energy (DE-SC0016330) and the NSF (PHY-1613087).

Mathematics Teachers' Visualization of Complex Number Multiplication and the Roots of Unity in a Dynamic Geometry Environment

ERIC Educational Resources Information Center

Caglayan, Gunhan

2016-01-01

This qualitative research, drawing on the theoretical frameworks by Even (1990, 1993) and Sfard (2007), investigated five high school mathematics teachers' geometric interpretations of complex number multiplication along with the roots of unity. The main finding was that mathematics teachers constructed the modulus, the argument, and the conjugate…

Resting and Task-Modulated High-Frequency Brain Rhythms Measured by Scalp Encephalography in Infants with Tuberous Sclerosis Complex

ERIC Educational Resources Information Center

Stamoulis, Catherine; Vogel-Farley, Vanessa; Degregorio, Geneva; Jeste, Shafali S.; Nelson, Charles A.

2015-01-01

The electrophysiological correlates of cognitive deficits in tuberous sclerosis complex (TSC) are not well understood, and modulations of neural dynamics by neuroanatomical abnormalities that characterize the disorder remain elusive. Neural oscillations (rhythms) are a fundamental aspect of brain function, and have dominant frequencies in a wide…

Hydrogen exchange mass spectrometry of functional membrane-bound chemotaxis receptor complexes.

PubMed

Koshy, Seena S; Eyles, Stephen J; Weis, Robert M; Thompson, Lynmarie K

2013-12-10

The transmembrane signaling mechanism of bacterial chemotaxis receptors is thought to involve changes in receptor conformation and dynamics. The receptors function in ternary complexes with two other proteins, CheA and CheW, that form extended membrane-bound arrays. Previous studies have shown that attractant binding induces a small (∼2 Å) piston displacement of one helix of the periplasmic and transmembrane domains toward the cytoplasm, but it is not clear how this signal propagates through the cytoplasmic domain to control the kinase activity of the CheA bound at the membrane-distal tip, nearly 200 Å away. The cytoplasmic domain has been shown to be highly dynamic, which raises the question of how a small piston motion could propagate through a dynamic domain to control CheA kinase activity. To address this, we have developed a method for measuring dynamics of the receptor cytoplasmic fragment (CF) in functional complexes with CheA and CheW. Hydrogen-deuterium exchange mass spectrometry (HDX-MS) measurements of global exchange of the CF demonstrate that the CF exhibits significantly slower exchange in functional complexes than in solution. Because the exchange rates in functional complexes are comparable to those of other proteins with similar structures, the CF appears to be a well-structured protein within these complexes, which is compatible with its role in propagating a signal that appears to be a tiny conformational change in the periplasmic and transmembrane domains of the receptor. We also demonstrate the feasibility of this protocol for local exchange measurements by incorporating a pepsin digest step to produce peptides with 87% sequence coverage and only 20% back exchange. This method extends HDX-MS to membrane-bound functional complexes without detergents that may perturb the stability or structure of the system.

Hydrogen Exchange Mass Spectrometry of Functional Membrane-bound Chemotaxis Receptor Complexes

PubMed Central

Koshy, Seena S.; Eyles, Stephen J.; Weis, Robert M.; Thompson, Lynmarie K.

2014-01-01

The transmembrane signaling mechanism of bacterial chemotaxis receptors is thought to involve changes in receptor conformation and dynamics. The receptors function in ternary complexes with two other proteins, CheA and CheW, that form extended membrane-bound arrays. Previous studies have shown that attractant binding induces a small (~2 Å) piston displacement of one helix of the periplasmic and transmembrane domains towards the cytoplasm, but it is not clear how this signal propagates through the cytoplasmic domain to control the kinase activity of the CheA bound at the membrane-distal tip, nearly 200 Å away. The cytoplasmic domain has been shown to be highly dynamic, which raises the question of how a small piston motion could propagate through a dynamic domain to control CheA kinase activity. To address this, we have developed a method for measuring dynamics of the receptor cytoplasmic fragment (CF) in functional complexes with CheA and CheW. Hydrogen exchange mass spectrometry (HDX-MS) measurements of global exchange of CF demonstrate that CF exhibits significantly slower exchange in functional complexes than in solution. Since the exchange rates in functional complexes are comparable to that of other proteins of similar structure, the CF appears to be a well-structured protein within these complexes, which is compatible with its role in propagating a signal that appears to be a tiny conformational change in the periplasmic and transmembrane domains of the receptor. We also demonstrate the feasibility of this protocol for local exchange measurements, by incorporating a pepsin digest step to produce peptides with 87% sequence coverage and only 20% back exchange. This method extends HDX-MS to membrane-bound functional complexes without detergents that may perturb the stability or structure of the system. PMID:24274333

Periodically sheared 2D Yukawa systems

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

Kovács, Anikó Zsuzsa; Hartmann, Peter; Center for Astrophysics, Space Physics and Engineering Research

2015-10-15

We present non-equilibrium molecular dynamics simulation studies on the dynamic (complex) shear viscosity of a 2D Yukawa system. We have identified a non-monotonic frequency dependence of the viscosity at high frequencies and shear rates, an energy absorption maximum (local resonance) at the Einstein frequency of the system at medium shear rates, an enhanced collective wave activity, when the excitation is near the plateau frequency of the longitudinal wave dispersion, and the emergence of significant configurational anisotropy at small frequencies and high shear rates.

DNA-Based Dynamic Reaction Networks.

PubMed

Fu, Ting; Lyu, Yifan; Liu, Hui; Peng, Ruizi; Zhang, Xiaobing; Ye, Mao; Tan, Weihong

2018-05-21

Deriving from logical and mechanical interactions between DNA strands and complexes, DNA-based artificial reaction networks (RNs) are attractive for their high programmability, as well as cascading and fan-out ability, which are similar to the basic principles of electronic logic gates. Arising from the dream of creating novel computing mechanisms, researchers have placed high hopes on the development of DNA-based dynamic RNs and have strived to establish the basic theories and operative strategies of these networks. This review starts by looking back on the evolution of DNA dynamic RNs; in particular' the most significant applications in biochemistry occurring in recent years. Finally, we discuss the perspectives of DNA dynamic RNs and give a possible direction for the development of DNA circuits. Copyright © 2018. Published by Elsevier Ltd.

Molecular Dynamics Simulations of Shear Induced Transformations in Nitromethane

NASA Astrophysics Data System (ADS)

Larentzos, James; Steele, Brad

2017-06-01

Recent experiments demonstrate that NM undergoes explosive chemical initiation under compressive shear stress. The atomistic dynamics of the shear response of single-crystalline and bi-crystalline nitromethane (NM) are simulated using molecular dynamics simulations under high pressure conditions to aid in interpreting these experiments. The atomic interactions are described using a recently re-optimized ReaxFF-lg potential trained specifically for NM under pressure. The simulations demonstrate that the NM crystal transforms into a disordered state upon sufficient application of shear stress; its maximum value, shear angle, and atomic-scale dynamics being highly dependent on crystallographic orientation of the applied shear. Shear simulations in bi-crystalline NM show more complex behavior resulting in the appearance of the disordered state at the grain boundary.

Molecular Dynamics Simulations of Shear Induced Transformations in Nitromethane

NASA Astrophysics Data System (ADS)

Larentzos, James; Steele, Brad

Recent experiments demonstrate that NM undergoes explosive chemical initiation under compressive shear stress. The atomistic dynamics of the shear response of single-crystalline and bi-crystalline nitromethane (NM) are simulated using molecular dynamics simulations under high pressure conditions to aid in interpreting these experiments. The atomic interactions are described using a recently re-optimized ReaxFF-lg potential trained specifically for NM under pressure. The simulations demonstrate that the NM crystal transforms into a disordered state upon sufficient application of shear stress; its maximum value, shear angle, and atomic-scale dynamics being highly dependent on crystallographic orientation of the applied shear. Shear simulations in bi-crystalline NM show more complex behavior resulting in the appearance of the disordered state at the grain boundary.

How proteins bind to DNA: target discrimination and dynamic sequence search by the telomeric protein TRF1

PubMed Central

2017-01-01

Abstract Target search as performed by DNA-binding proteins is a complex process, in which multiple factors contribute to both thermodynamic discrimination of the target sequence from overwhelmingly abundant off-target sites and kinetic acceleration of dynamic sequence interrogation. TRF1, the protein that binds to telomeric tandem repeats, faces an intriguing variant of the search problem where target sites are clustered within short fragments of chromosomal DNA. In this study, we use extensive (>0.5 ms in total) MD simulations to study the dynamical aspects of sequence-specific binding of TRF1 at both telomeric and non-cognate DNA. For the first time, we describe the spontaneous formation of a sequence-specific native protein–DNA complex in atomistic detail, and study the mechanism by which proteins avoid off-target binding while retaining high affinity for target sites. Our calculated free energy landscapes reproduce the thermodynamics of sequence-specific binding, while statistical approaches allow for a comprehensive description of intermediate stages of complex formation. PMID:28633355

Modeling microbial community structure and functional diversity across time and space.

PubMed

Larsen, Peter E; Gibbons, Sean M; Gilbert, Jack A

2012-07-01

Microbial communities exhibit exquisitely complex structure. Many aspects of this complexity, from the number of species to the total number of interactions, are currently very difficult to examine directly. However, extraordinary efforts are being made to make these systems accessible to scientific investigation. While recent advances in high-throughput sequencing technologies have improved accessibility to the taxonomic and functional diversity of complex communities, monitoring the dynamics of these systems over time and space - using appropriate experimental design - is still expensive. Fortunately, modeling can be used as a lens to focus low-resolution observations of community dynamics to enable mathematical abstractions of functional and taxonomic dynamics across space and time. Here, we review the approaches for modeling bacterial diversity at both the very large and the very small scales at which microbial systems interact with their environments. We show that modeling can help to connect biogeochemical processes to specific microbial metabolic pathways. © 2012 Federation of European Microbiological Societies. Published by Blackwell Publishing Ltd. All rights reserved.

Numerical investigations with WRF about atmospheric features leading to heavy precipitation and flood events over the Central Andes' complex topography

NASA Astrophysics Data System (ADS)

Zamuriano, Marcelo; Brönnimann, Stefan

2017-04-01

It's known that some extremes such as heavy rainfalls, flood events, heatwaves and droughts depend largely on the atmospheric circulation and local features. Bolivia is no exception and while the large scale dynamics over the Amazon has been largely investigated, the local features driven by the Andes Cordillera and the Altiplano is still poorly documented. New insights on the regional atmospheric dynamics preceding heavy precipitation and flood events over the complex topography of the Andes-Amazon interface are added through numerical investigations of several case events: flash flood episodes over La Paz city and the extreme 2014 flood in south-western Amazon basin. Large scale atmospheric water transport is dynamically downscaled in order to take into account the complex topography forcing and local features as modulators of these events. For this purpose, a series of high resolution numerical experiments with the WRF-ARW model is conducted using various global datasets and parameterizations. While several mechanisms have been suggested to explain the dynamics of these episodes, they have not been tested yet through numerical modelling experiments. The simulations captures realistically the local water transport and the terrain influence over atmospheric circulation, even though the precipitation intensity is in general unrealistic. Nevertheless, the results show that Dynamical Downscaling over the tropical Andes' complex terrain provides useful meteorological data for a variety of studies and contributes to a better understanding of physical processes involved in the configuration of these events.

Dynamic traversal of large gaps by insects and legged robots reveals a template.

PubMed

Gart, Sean W; Yan, Changxin; Othayoth, Ratan; Ren, Zhiyi; Li, Chen

2018-02-02

It is well known that animals can use neural and sensory feedback via vision, tactile sensing, and echolocation to negotiate obstacles. Similarly, most robots use deliberate or reactive planning to avoid obstacles, which relies on prior knowledge or high-fidelity sensing of the environment. However, during dynamic locomotion in complex, novel, 3D terrains, such as a forest floor and building rubble, sensing and planning suffer bandwidth limitation and large noise and are sometimes even impossible. Here, we study rapid locomotion over a large gap-a simple, ubiquitous obstacle-to begin to discover the general principles of the dynamic traversal of large 3D obstacles. We challenged the discoid cockroach and an open-loop six-legged robot to traverse a large gap of varying length. Both the animal and the robot could dynamically traverse a gap as large as one body length by bridging the gap with its head, but traversal probability decreased with gap length. Based on these observations, we developed a template that accurately captured body dynamics and quantitatively predicted traversal performance. Our template revealed that a high approach speed, initial body pitch, and initial body pitch angular velocity facilitated dynamic traversal, and successfully predicted a new strategy for using body pitch control that increased the robot's maximal traversal gap length by 50%. Our study established the first template of dynamic locomotion beyond planar surfaces, and is an important step in expanding terradynamics into complex 3D terrains.

Predictability of Extreme Climate Events via a Complex Network Approach

NASA Astrophysics Data System (ADS)

Muhkin, D.; Kurths, J.

2017-12-01

We analyse climate dynamics from a complex network approach. This leads to an inverse problem: Is there a backbone-like structure underlying the climate system? For this we propose a method to reconstruct and analyze a complex network from data generated by a spatio-temporal dynamical system. This approach enables us to uncover relations to global circulation patterns in oceans and atmosphere. This concept is then applied to Monsoon data; in particular, we develop a general framework to predict extreme events by combining a non-linear synchronization technique with complex networks. Applying this method, we uncover a new mechanism of extreme floods in the eastern Central Andes which could be used for operational forecasts. Moreover, we analyze the Indian Summer Monsoon (ISM) and identify two regions of high importance. By estimating an underlying critical point, this leads to an improved prediction of the onset of the ISM; this scheme was successful in 2016 and 2017.

Insights into cellulosome assembly and dynamics: from dissection to reconstruction of the supramolecular enzyme complex.

PubMed

Smith, Steven P; Bayer, Edward A

2013-10-01

Cellulosomes are multi-enzyme complexes produced by anaerobic bacteria for the efficient deconstruction of plant cell wall polysaccharides. The assembly of enzymatic subunits onto a central non-catalytic scaffoldin subunit is mediated by a highly specific interaction between the enzyme-bearing dockerin modules and the resident cohesin modules of the scaffoldin, which affords their catalytic activities to work synergistically. The scaffoldin also imparts substrate-binding and bacterial-anchoring properties, the latter of which involves a second cohesin-dockerin interaction. Recent structure-function studies reveal an ever-growing array of unique and increasingly complex cohesin-dockerin complexes and cellulosomal enzymes with novel activities. A 'build' approach involving multimodular cellulosomal segments has provided a structural model of an organized yet conformationally dynamic supramolecular assembly with the potential to form higher order structures. Copyright © 2013. Published by Elsevier Ltd.

Hierarchic spatio-temporal dynamics in glycolysis

NASA Astrophysics Data System (ADS)

Shinjyo, Takahiro; Nakagawa, Yoshiyuki; Ueda, Tetsuo

Yeast extracts exhibit oscillations when the glycolytic system is far away from equilibrium. Spatio-temporal dynamics in this system was studied in the newly developed gel as well as in the solution. Small regions (about 10 um) with very complex shape with high or low concentrations of NADH appeared, and upon these small structures large-scale dynamics were superimposed. Concentration waves propagated, and the source of wave was induced by contact with high ADP. Sink of waves was generated by contacting the reaction gel to two small gels rich in ADP. Upon these spatio-temporal dynamics were superimposed much slower global oscillations throughout the system with a period of about 40 min. Similar dynamics was seen in a solution of yeast extract, but the size of domains was about ten times larger than that in the gel. In this way, the multi-enzyme system of glycolysis exhibits self-organization of hierarchy in spatio-temporal dynamics.

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

PubMed

Valenza, Gaetano; Citi, Luca; Barbieri, Riccardo

2013-01-01

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

Ultrafast X-Ray Spectroscopy of Conical Intersections

NASA Astrophysics Data System (ADS)

Neville, Simon P.; Chergui, Majed; Stolow, Albert; Schuurman, Michael S.

2018-06-01

Ongoing developments in ultrafast x-ray sources offer powerful new means of probing the complex nonadiabatically coupled structural and electronic dynamics of photoexcited molecules. These non-Born-Oppenheimer effects are governed by general electronic degeneracies termed conical intersections, which play a key role, analogous to that of a transition state, in the electronic-nuclear dynamics of excited molecules. Using high-level ab initio quantum dynamics simulations, we studied time-resolved x-ray absorption (TRXAS) and photoelectron spectroscopy (TRXPS) of the prototypical unsaturated organic chromophore, ethylene, following excitation to its S2(π π*) state. The TRXAS, in particular, is highly sensitive to all aspects of the ensuing dynamics. These x-ray spectroscopies provide a clear signature of the wave packet dynamics near conical intersections, related to charge localization effects driven by the nuclear dynamics. Given the ubiquity of charge localization in excited state dynamics, we believe that ultrafast x-ray spectroscopies offer a unique and powerful route to the direct observation of dynamics around conical intersections.

Regulation of the Dynamic Live Load Factor for Calculation of Bridge Structures on High-Speed Railway Mainlines

NASA Astrophysics Data System (ADS)

Dyachenko, Leonid K.; Benin, Andrey V.

2017-06-01

When the high-speed railway traffic is being organized, it becomes necessary to elaborate bridge design standards for high-speed railways (HSR). Methodology of studying the issues of HSR bridge design is based on the comprehensive analysis of domestic research as well as international experience in design, construction and operation of high-speed railways. Serious requirements are imposed on the HSR artificial structures, which raise a number of scientific tasks associated mainly with the issues of the dynamic interaction of the rolling stock and the bridge elements. To ensure safety of traffic and reliability of bridges during the whole period of operation one needs to resolve the dynamic problems of various types of high-speed trains moving along the structures. The article analyses dependences of the magnitude of inertial response on the external stress parameters and proposes a simplified method of determination of the dynamic live load factor caused by the passage of high-speed trains. The usefulness of the given research arises from the reduction of complexity of the complicated dynamic calculations needed to describe a high-speed train travelling along the artificial structures.

Two Studies of Complex Nonlinear Systems: Engineered Granular Crystals and Coarse-Graining Optimization Problems

NASA Astrophysics Data System (ADS)

Pozharskiy, Dmitry

In recent years a nonlinear, acoustic metamaterial, named granular crystals, has gained prominence due to its high accessibility, both experimentally and computationally. The observation of a wide range of dynamical phenomena in the system, due to its inherent nonlinearities, has suggested its importance in many engineering applications related to wave propagation. In the first part of this dissertation, we explore the nonlinear dynamics of damped-driven granular crystals. In one case, we consider a highly nonlinear setting, also known as a sonic vacuum, and derive a nonlinear analogue of a linear spectrum, corresponding to resonant periodic propagation and antiresonances. Experimental studies confirm the computational findings and the assimilation of experimental data into a numerical model is demonstrated. In the second case, global bifurcations in a precompressed granular crystal are examined, and their involvement in the appearance of chaotic dynamics is demonstrated. Both results highlight the importance of exploring the nonlinear dynamics, to gain insight into how a granular crystal responds to different external excitations. In the second part, we borrow established ideas from coarse-graining of dynamical systems, and extend them to optimization problems. We combine manifold learning algorithms, such as Diffusion Maps, with stochastic optimization methods, such as Simulated Annealing, and show that we can retrieve an ensemble, of few, important parameters that should be explored in detail. This framework can lead to acceleration of convergence when dealing with complex, high-dimensional optimization, and could potentially be applied to design engineered granular crystals.

Thinking about complexity in health: A systematic review of the key systems thinking and complexity ideas in health.

PubMed

Rusoja, Evan; Haynie, Deson; Sievers, Jessica; Mustafee, Navonil; Nelson, Fred; Reynolds, Martin; Sarriot, Eric; Swanson, Robert Chad; Williams, Bob

2018-01-30

As the Sustainable Development Goals are rolled out worldwide, development leaders will be looking to the experiences of the past to improve implementation in the future. Systems thinking and complexity science (ST/CS) propose that health and the health system are composed of dynamic actors constantly evolving in response to each other and their context. While offering practical guidance for steering the next development agenda, there is no consensus as to how these important ideas are discussed in relation to health. This systematic review sought to identify and describe some of the key terms, concepts, and methods in recent ST/CS literature. Using the search terms "systems thinkin * AND health OR complexity theor* AND health OR complex adaptive system* AND health," we identified 516 relevant full texts out of 3982 titles across the search period (2002-2015). The peak number of articles were published in 2014 (83) with journals specifically focused on medicine/healthcare (265) and particularly the Journal of Evaluation in Clinical Practice (37) representing the largest number by volume. Dynamic/dynamical systems (n = 332), emergence (n = 294), complex adaptive system(s) (n = 270), and interdependent/interconnected (n = 263) were the most common terms with systems dynamic modelling (58) and agent-based modelling (43) as the most common methods. The review offered several important conclusions. First, while there was no core ST/CS "canon," certain terms appeared frequently across the reviewed texts. Second, even as these ideas are gaining traction in academic and practitioner communities, most are concentrated in a few journals. Finally, articles on ST/CS remain largely theoretical illustrating the need for further study and practical application. Given the challenge posed by the next phase of development, gaining a better understanding of ST/CS ideas and their use may lead to improvements in the implementation and practice of the Sustainable Development Goals. Key messages Systems thinking and complexity science, theories that acknowledge the dynamic, connected, and context-dependent nature of health, are highly relevant to the post-millennium development goal era yet lack consensus on their use in relation to health Although heterogeneous, terms, and concepts like emergence, dynamic/dynamical Systems, nonlinear(ity), and interdependent/interconnected as well as methods like systems dynamic modelling and agent-based modelling that comprise systems thinking and complexity science in the health literature are shared across an increasing number of publications within medical/healthcare disciplines Planners, practitioners, and theorists that can better understand these key systems thinking and complexity science concepts will be better equipped to tackle the challenges of the upcoming development goals. © 2018 John Wiley & Sons, Ltd.

Redox Conditions Affect Ultrafast Exciton Transport in Photosynthetic Pigment-Protein Complexes.

PubMed

Allodi, Marco A; Otto, John P; Sohail, Sara H; Saer, Rafael G; Wood, Ryan E; Rolczynski, Brian S; Massey, Sara C; Ting, Po-Chieh; Blankenship, Robert E; Engel, Gregory S

2018-01-04

Pigment-protein complexes in photosynthetic antennae can suffer oxidative damage from reactive oxygen species generated during solar light harvesting. How the redox environment of a pigment-protein complex affects energy transport on the ultrafast light-harvesting time scale remains poorly understood. Using two-dimensional electronic spectroscopy, we observe differences in femtosecond energy-transfer processes in the Fenna-Matthews-Olson (FMO) antenna complex under different redox conditions. We attribute these differences in the ultrafast dynamics to changes to the system-bath coupling around specific chromophores, and we identify a highly conserved tyrosine/tryptophan chain near the chromophores showing the largest changes. We discuss how the mechanism of tyrosine/tryptophan chain oxidation may contribute to these differences in ultrafast dynamics that can moderate energy transfer to downstream complexes where reactive oxygen species are formed. These results highlight the importance of redox conditions on the ultrafast transport of energy in photosynthesis. Tailoring the redox environment may enable energy transport engineering in synthetic light-harvesting systems.

[Situational awareness: you won't see it unless you understand it].

PubMed

Graafland, Maurits; Schijven, Marlies P

2015-01-01

In dynamic, high-risk environments such as the modern operating theatre, healthcare providers are required to identify a multitude of signals correctly and in time. Errors resulting from failure to identify or interpret signals correctly lead to calamities. Medical training curricula focus largely on teaching technical skills and knowledge, not on the cognitive skills needed to interact appropriately with fast-changing, complex environments in practice. The term 'situational awareness' describes the dynamic process of receiving, interpreting and processing information in such dynamic environments. Improving situational awareness in high-risk environments should be part of medical curricula. In addition, the flood of information in high-risk environments should be presented more clearly and effectively. It is important that physicians become more involved in this regard.

Speculative behavior and asset price dynamics.

PubMed

Westerhoff, Frank

2003-07-01

This paper deals with speculative trading. Guided by empirical observations, a nonlinear deterministic asset pricing model is developed in which traders repeatedly choose between technical and fundamental analysis to determine their orders. The interaction between the trading rules produces complex dynamics. The model endogenously replicates the stylized facts of excess volatility, high trading volumes, shifts in the level of asset prices, and volatility clustering.

On the Unsteady Shock Wave Interaction with a Backward-Facing Step: Viscous Analysis

NASA Astrophysics Data System (ADS)

Mendoza, N.; Bowersox, R. D. W.

Unsteady shock propagation through ducts with varying cross-sectional area occurs in many engineering applications, such as explosions in underground tunnels, blast shelter design, engine exhaust systems, and high-speed propulsion systems. These complex, transient flows are rich in fundamental fluid-dynamic phenomena and are excellent testbeds for improving our understanding of unsteady fluid dynamics

Biological conservation law as an emerging functionality in dynamical neuronal networks.

PubMed

Podobnik, Boris; Jusup, Marko; Tiganj, Zoran; Wang, Wen-Xu; Buldú, Javier M; Stanley, H Eugene

2017-11-07

Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law-the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective.

Biological conservation law as an emerging functionality in dynamical neuronal networks

PubMed Central

Podobnik, Boris; Tiganj, Zoran; Wang, Wen-Xu; Buldú, Javier M.

2017-01-01

Scientists strive to understand how functionalities, such as conservation laws, emerge in complex systems. Living complex systems in particular create high-ordered functionalities by pairing up low-ordered complementary processes, e.g., one process to build and the other to correct. We propose a network mechanism that demonstrates how collective statistical laws can emerge at a macro (i.e., whole-network) level even when they do not exist at a unit (i.e., network-node) level. Drawing inspiration from neuroscience, we model a highly stylized dynamical neuronal network in which neurons fire either randomly or in response to the firing of neighboring neurons. A synapse connecting two neighboring neurons strengthens when both of these neurons are excited and weakens otherwise. We demonstrate that during this interplay between the synaptic and neuronal dynamics, when the network is near a critical point, both recurrent spontaneous and stimulated phase transitions enable the phase-dependent processes to replace each other and spontaneously generate a statistical conservation law—the conservation of synaptic strength. This conservation law is an emerging functionality selected by evolution and is thus a form of biological self-organized criticality in which the key dynamical modes are collective. PMID:29078286

Time-resolved multi-mass ion imaging: Femtosecond UV-VUV pump-probe spectroscopy with the PImMS camera.

PubMed

Forbes, Ruaridh; Makhija, Varun; Veyrinas, Kévin; Stolow, Albert; Lee, Jason W L; Burt, Michael; Brouard, Mark; Vallance, Claire; Wilkinson, Iain; Lausten, Rune; Hockett, Paul

2017-07-07

The Pixel-Imaging Mass Spectrometry (PImMS) camera allows for 3D charged particle imaging measurements, in which the particle time-of-flight is recorded along with (x, y) position. Coupling the PImMS camera to an ultrafast pump-probe velocity-map imaging spectroscopy apparatus therefore provides a route to time-resolved multi-mass ion imaging, with both high count rates and large dynamic range, thus allowing for rapid measurements of complex photofragmentation dynamics. Furthermore, the use of vacuum ultraviolet wavelengths for the probe pulse allows for an enhanced observation window for the study of excited state molecular dynamics in small polyatomic molecules having relatively high ionization potentials. Herein, preliminary time-resolved multi-mass imaging results from C 2 F 3 I photolysis are presented. The experiments utilized femtosecond VUV and UV (160.8 nm and 267 nm) pump and probe laser pulses in order to demonstrate and explore this new time-resolved experimental ion imaging configuration. The data indicate the depth and power of this measurement modality, with a range of photofragments readily observed, and many indications of complex underlying wavepacket dynamics on the excited state(s) prepared.

Decay of Complex-Time Determinantal and Pfaffian Correlation Functionals in Lattices

NASA Astrophysics Data System (ADS)

Aza, N. J. B.; Bru, J.-B.; de Siqueira Pedra, W.

2018-04-01

We supplement the determinantal and Pfaffian bounds of Sims and Warzel (Commun Math Phys 347:903-931, 2016) for many-body localization of quasi-free fermions, by considering the high dimensional case and complex-time correlations. Our proof uses the analyticity of correlation functions via the Hadamard three-line theorem. We show that the dynamical localization for the one-particle system yields the dynamical localization for the many-point fermionic correlation functions, with respect to the Hausdorff distance in the determinantal case. In Sims and Warzel (2016), a stronger notion of decay for many-particle configurations was used but only at dimension one and for real times. Considering determinantal and Pfaffian correlation functionals for complex times is important in the study of weakly interacting fermions.

Decay of Complex-Time Determinantal and Pfaffian Correlation Functionals in Lattices

NASA Astrophysics Data System (ADS)

Aza, N. J. B.; Bru, J.-B.; de Siqueira Pedra, W.

2018-06-01

We supplement the determinantal and Pfaffian bounds of Sims and Warzel (Commun Math Phys 347:903-931, 2016) for many-body localization of quasi-free fermions, by considering the high dimensional case and complex-time correlations. Our proof uses the analyticity of correlation functions via the Hadamard three-line theorem. We show that the dynamical localization for the one-particle system yields the dynamical localization for the many-point fermionic correlation functions, with respect to the Hausdorff distance in the determinantal case. In Sims and Warzel (2016), a stronger notion of decay for many-particle configurations was used but only at dimension one and for real times. Considering determinantal and Pfaffian correlation functionals for complex times is important in the study of weakly interacting fermions.

CuCl Complexation in the Vapor Phase: Insights from Ab Initio Molecular Dynamics Simulations

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

Mei, Yuan; Liu, Weihua; Migdiov, A. A.

We invesmore » tigated the hydration of the CuCl 0 complex in HCl-bearing water vapor at 350°C and a vapor-like fluid density between 0.02 and 0.09 g/cm 3 using ab initio molecular dynamics (MD) simulations. The simulations reveal that one water molecule is strongly bonded to Cu(I) (first coordination shell), forming a linear [H 2O-Cu-Cl] 0 moiety. The second hydration shell is highly dynamic in nature, and individual configurations have short life-spans in such low-density vapors, resulting in large fluctuations in instantaneous hydration numbers over a timescale of picoseconds. The average hydration number in the second shell (m) increased from ~0.5 to ~3.5 and the calculated number of hydrogen bonds per water molecule increased from 0.09 to 0.25 when fluid density (which is correlated to water activity) increased from 0.02 to 0.09 g/cm 3 ( f H 2O 1.72 to 2.05). These changes of hydration number are qualitatively consistent with previous solubility studies under similar conditions, although the absolute hydration numbers from MD were much lower than the values inferred by correlating experimental Cu fugacity with water fugacity. This could be due to the uncertainties in the MD simulations and uncertainty in the estimation of the fugacity coefficients for these highly nonideal “vapors” in the experiments. Finally, our study provides the first theoretical confirmation that beyond-first-shell hydrated metal complexes play an important role in metal transport in low-density hydrothermal fluids, even if it is highly disordered and dynamic in nature.« less

CuCl Complexation in the Vapor Phase: Insights from Ab Initio Molecular Dynamics Simulations

DOE PAGES

Mei, Yuan; Liu, Weihua; Migdiov, A. A.; ...

2018-05-02

We invesmore » tigated the hydration of the CuCl 0 complex in HCl-bearing water vapor at 350°C and a vapor-like fluid density between 0.02 and 0.09 g/cm 3 using ab initio molecular dynamics (MD) simulations. The simulations reveal that one water molecule is strongly bonded to Cu(I) (first coordination shell), forming a linear [H 2O-Cu-Cl] 0 moiety. The second hydration shell is highly dynamic in nature, and individual configurations have short life-spans in such low-density vapors, resulting in large fluctuations in instantaneous hydration numbers over a timescale of picoseconds. The average hydration number in the second shell (m) increased from ~0.5 to ~3.5 and the calculated number of hydrogen bonds per water molecule increased from 0.09 to 0.25 when fluid density (which is correlated to water activity) increased from 0.02 to 0.09 g/cm 3 ( f H 2O 1.72 to 2.05). These changes of hydration number are qualitatively consistent with previous solubility studies under similar conditions, although the absolute hydration numbers from MD were much lower than the values inferred by correlating experimental Cu fugacity with water fugacity. This could be due to the uncertainties in the MD simulations and uncertainty in the estimation of the fugacity coefficients for these highly nonideal “vapors” in the experiments. Finally, our study provides the first theoretical confirmation that beyond-first-shell hydrated metal complexes play an important role in metal transport in low-density hydrothermal fluids, even if it is highly disordered and dynamic in nature.« less

Plasma and Electro-energetic Physics

DTIC Science & Technology

2012-03-07

Dynamical Equations (with complex surfaces ): Relativistic Lorentz Force Law for relativistic momentum p and velocity u: tDcJcH tBcE   /)/1()/4...0.1-1 s • 3D, high-fidelity, parallel modeling of high energy density fields and particles in complex geometry with some surface effects...cathodes (500 µm separation) Tang, AFRL/RD 12 DISTRIBUTION A: Approved for public release; distribution is unlimited. ICEPIC simulations Equipotential

Flight dynamics research for highly agile aircraft

NASA Technical Reports Server (NTRS)

Nguyen, Luat T.

1989-01-01

This paper highlights recent results of research conducted at the NASA Langley Research Center as part of a broad flight dynamics program aimed at developing technology that will enable future combat aircraft to achieve greatly enhanced agility capability at subsonic combat conditions. Studies of advanced control concepts encompassing both propulsive and aerodynamic approaches are reviewed. Dynamic stall phenomena and their potential impact on maneuvering performance and stability are summarized. Finally, issues of mathematical modeling of complex aerodynamics occurring during rapid, large amplitude maneuvers are discussed.

Large-scale glacitectonic deformation in response to active ice sheet retreat across Dogger Bank (southern central North Sea) during the Last Glacial Maximum

NASA Astrophysics Data System (ADS)

Phillips, Emrys; Cotterill, Carol; Johnson, Kirstin; Crombie, Kirstin; James, Leo; Carr, Simon; Ruiter, Astrid

2018-01-01

High resolution seismic data from the Dogger Bank in the central southern North Sea has revealed that the Dogger Bank Formation records a complex history of sedimentation and penecontemporaneous, large-scale, ice-marginal to proglacial glacitectonic deformation. These processes led to the development of a large thrust-block moraine complex which is buried beneath a thin sequence of Holocene sediments. This buried glacitectonic landsystem comprises a series of elongate, arcuate moraine ridges (200 m up to > 15 km across; over 40-50 km long) separated by low-lying ice marginal to proglacial sedimentary basins and/or meltwater channels, preserving the shape of the margin of this former ice sheet. The moraines are composed of highly deformed (folded and thrust) Dogger Bank Formation with the lower boundary of the deformed sequence (up to 40-50 m thick) being marked by a laterally extensive décollement. The ice-distal parts of the thrust moraine complex are interpreted as a "forward" propagating imbricate thrust stack developed in response to S/SE-directed ice-push. The more complex folding and thrusting within the more ice-proximal parts of the thrust-block moraines record the accretion of thrust slices of highly deformed sediment as the ice repeatedly reoccupied this ice marginal position. Consequently, the internal structure of the Dogger Bank thrust-moraine complexes can be directly related to ice sheet dynamics, recording the former positions of a highly dynamic, oscillating Weichselian ice sheet margin as it retreated northwards at the end of the Last Glacial Maximum.

Brownian Dynamics Simulation of Nucleocytoplasmic Transport: A Coarse-Grained Model for the Functional State of the Nuclear Pore Complex

PubMed Central

Moussavi-Baygi, Ruhollah; Jamali, Yousef; Karimi, Reza; Mofrad, Mohammad R. K.

2011-01-01

The nuclear pore complex (NPC) regulates molecular traffic across the nuclear envelope (NE). Selective transport happens on the order of milliseconds and the length scale of tens of nanometers; however, the transport mechanism remains elusive. Central to the transport process is the hydrophobic interactions between karyopherins (kaps) and Phe-Gly (FG) repeat domains. Taking into account the polymeric nature of FG-repeats grafted on the elastic structure of the NPC, and the kap-FG hydrophobic affinity, we have established a coarse-grained model of the NPC structure that mimics nucleocytoplasmic transport. To establish a foundation for future works, the methodology and biophysical rationale behind the model is explained in details. The model predicts that the first-passage time of a 15 nm cargo-complex is about 2.6±0.13 ms with an inverse Gaussian distribution for statistically adequate number of independent Brownian dynamics simulations. Moreover, the cargo-complex is primarily attached to the channel wall where it interacts with the FG-layer as it passes through the central channel. The kap-FG hydrophobic interaction is highly dynamic and fast, which ensures an efficient translocation through the NPC. Further, almost all eight hydrophobic binding spots on kap-β are occupied simultaneously during transport. Finally, as opposed to intact NPCs, cytoplasmic filaments-deficient NPCs show a high degree of permeability to inert cargos, implying the defining role of cytoplasmic filaments in the selectivity barrier. PMID:21673865

Beyond Contagion: Reality Mining Reveals Complex Patterns of Social Influence.

PubMed

Alshamsi, Aamena; Pianesi, Fabio; Lepri, Bruno; Pentland, Alex; Rahwan, Iyad

2015-01-01

Contagion, a concept from epidemiology, has long been used to characterize social influence on people's behavior and affective (emotional) states. While it has revealed many useful insights, it is not clear whether the contagion metaphor is sufficient to fully characterize the complex dynamics of psychological states in a social context. Using wearable sensors that capture daily face-to-face interaction, combined with three daily experience sampling surveys, we collected the most comprehensive data set of personality and emotion dynamics of an entire community of work. From this high-resolution data about actual (rather than self-reported) face-to-face interaction, a complex picture emerges where contagion (that can be seen as adaptation of behavioral responses to the behavior of other people) cannot fully capture the dynamics of transitory states. We found that social influence has two opposing effects on states: adaptation effects that go beyond mere contagion, and complementarity effects whereby individuals' behaviors tend to complement the behaviors of others. Surprisingly, these effects can exhibit completely different directions depending on the stable personality or emotional dispositions (stable traits) of target individuals. Our findings provide a foundation for richer models of social dynamics, and have implications on organizational engineering and workplace well-being.

Outlier-resilient complexity analysis of heartbeat dynamics

NASA Astrophysics Data System (ADS)

Lo, Men-Tzung; Chang, Yi-Chung; Lin, Chen; Young, Hsu-Wen Vincent; Lin, Yen-Hung; Ho, Yi-Lwun; Peng, Chung-Kang; Hu, Kun

2015-03-01

Complexity in physiological outputs is believed to be a hallmark of healthy physiological control. How to accurately quantify the degree of complexity in physiological signals with outliers remains a major barrier for translating this novel concept of nonlinear dynamic theory to clinical practice. Here we propose a new approach to estimate the complexity in a signal by analyzing the irregularity of the sign time series of its coarse-grained time series at different time scales. Using surrogate data, we show that the method can reliably assess the complexity in noisy data while being highly resilient to outliers. We further apply this method to the analysis of human heartbeat recordings. Without removing any outliers due to ectopic beats, the method is able to detect a degradation of cardiac control in patients with congestive heart failure and a more degradation in critically ill patients whose life continuation relies on extracorporeal membrane oxygenator (ECMO). Moreover, the derived complexity measures can predict the mortality of ECMO patients. These results indicate that the proposed method may serve as a promising tool for monitoring cardiac function of patients in clinical settings.

Conformational analysis of oligosaccharides and polysaccharides using molecular dynamics simulations.

PubMed

Frank, Martin

2015-01-01

Complex carbohydrates usually have a large number of rotatable bonds and consequently a large number of theoretically possible conformations can be generated (combinatorial explosion). The application of systematic search methods for conformational analysis of carbohydrates is therefore limited to disaccharides and trisaccharides in a routine analysis. An alternative approach is to use Monte-Carlo methods or (high-temperature) molecular dynamics (MD) simulations to explore the conformational space of complex carbohydrates. This chapter describes how to use MD simulation data to perform a conformational analysis (conformational maps, hydrogen bonds) of oligosaccharides and how to build realistic 3D structures of large polysaccharides using Conformational Analysis Tools (CAT).

Molecular Dynamics Simulation of Telomere and TRF1

NASA Astrophysics Data System (ADS)

Kaburagi, Masaaki; Fukuda, Masaki; Yamada, Hironao; Miyakawa, Takeshi; Morikawa, Ryota; Takasu, Masako; Kato, Takamitsu A.; Uesaka, Mitsuru

Telomeres play a central role in determining longevity of a cell. Our study focuses on the interaction between telomeric guanines and TRF1 as a means to observe the telomeric based mechanism of the genome protection. In this research, we performed molecular dynamics simulations of a telomeric DNA and TRF1. Our results show a stable structure with a high affinity for the specific protein. Additionally, we calculated the distance between guanines and the protein in their complex state. From this comparison, we found the calculated values of distance to be very similar, and the angle of guanines in their complex states was larger than that in their single state.

Molecular dynamics reveal BCR-ABL1 polymutants as a unique mechanism of resistance to PAN-BCR-ABL1 kinase inhibitor therapy

PubMed Central

Gibbons, Don L.; Pricl, Sabrina; Posocco, Paola; Laurini, Erik; Fermeglia, Maurizio; Sun, Hanshi; Talpaz, Moshe; Donato, Nicholas; Quintás-Cardama, Alfonso

2014-01-01

The acquisition of mutations within the BCR-ABL1 kinase domain is frequently associated with tyrosine kinase inhibitor (TKI) failure in chronic myeloid leukemia. Sensitive sequencing techniques have revealed a high prevalence of compound BCR-ABL1 mutations (polymutants) in patients failing TKI therapy. To investigate the molecular consequences of such complex mutant proteins with regards to TKI resistance, we determined by cloning techniques the presence of polymutants in a cohort of chronic-phase patients receiving imatinib followed by dasatinib therapy. The analysis revealed a high frequency of polymutant BCR-ABL1 alleles even after failure of frontline imatinib, and also the progressive exhaustion of the pool of unmutated BCR-ABL1 alleles over the course of sequential TKI therapy. Molecular dynamics analyses of the most frequent polymutants in complex with TKIs revealed the basis of TKI resistance. Modeling of BCR-ABL1 in complex with the potent pan-BCR-ABL1 TKI ponatinib highlighted potentially effective therapeutic strategies for patients carrying these recalcitrant and complex BCR-ABL1 mutant proteins while unveiling unique mechanisms of escape to ponatinib therapy. PMID:24550512

Hysteresis in DNA compaction by Dps is described by an Ising model

PubMed Central

Vtyurina, Natalia N.; Dulin, David; Docter, Margreet W.; Meyer, Anne S.; Dekker, Nynke H.; Abbondanzieri, Elio A.

2016-01-01

In all organisms, DNA molecules are tightly compacted into a dynamic 3D nucleoprotein complex. In bacteria, this compaction is governed by the family of nucleoid-associated proteins (NAPs). Under conditions of stress and starvation, an NAP called Dps (DNA-binding protein from starved cells) becomes highly up-regulated and can massively reorganize the bacterial chromosome. Although static structures of Dps–DNA complexes have been documented, little is known about the dynamics of their assembly. Here, we use fluorescence microscopy and magnetic-tweezers measurements to resolve the process of DNA compaction by Dps. Real-time in vitro studies demonstrated a highly cooperative process of Dps binding characterized by an abrupt collapse of the DNA extension, even under applied tension. Surprisingly, we also discovered a reproducible hysteresis in the process of compaction and decompaction of the Dps–DNA complex. This hysteresis is extremely stable over hour-long timescales despite the rapid binding and dissociation rates of Dps. A modified Ising model is successfully applied to fit these kinetic features. We find that long-lived hysteresis arises naturally as a consequence of protein cooperativity in large complexes and provides a useful mechanism for cells to adopt unique epigenetic states. PMID:27091987

Concept of a Cloud Service for Data Preparation and Computational Control on Custom HPC Systems in Application to Molecular Dynamics

NASA Astrophysics Data System (ADS)

Puzyrkov, Dmitry; Polyakov, Sergey; Podryga, Viktoriia; Markizov, Sergey

2018-02-01

At the present stage of computer technology development it is possible to study the properties and processes in complex systems at molecular and even atomic levels, for example, by means of molecular dynamics methods. The most interesting are problems related with the study of complex processes under real physical conditions. Solving such problems requires the use of high performance computing systems of various types, for example, GRID systems and HPC clusters. Considering the time consuming computational tasks, the need arises of software for automatic and unified monitoring of such computations. A complex computational task can be performed over different HPC systems. It requires output data synchronization between the storage chosen by a scientist and the HPC system used for computations. The design of the computational domain is also quite a problem. It requires complex software tools and algorithms for proper atomistic data generation on HPC systems. The paper describes the prototype of a cloud service, intended for design of atomistic systems of large volume for further detailed molecular dynamic calculations and computational management for this calculations, and presents the part of its concept aimed at initial data generation on the HPC systems.

The Dynamics of Coalition Formation on Complex Networks

NASA Astrophysics Data System (ADS)

Auer, S.; Heitzig, J.; Kornek, U.; Schöll, E.; Kurths, J.

2015-08-01

Complex networks describe the structure of many socio-economic systems. However, in studies of decision-making processes the evolution of the underlying social relations are disregarded. In this report, we aim to understand the formation of self-organizing domains of cooperation (“coalitions”) on an acquaintance network. We include both the network’s influence on the formation of coalitions and vice versa how the network adapts to the current coalition structure, thus forming a social feedback loop. We increase complexity from simple opinion adaptation processes studied in earlier research to more complex decision-making determined by costs and benefits, and from bilateral to multilateral cooperation. We show how phase transitions emerge from such coevolutionary dynamics, which can be interpreted as processes of great transformations. If the network adaptation rate is high, the social dynamics prevent the formation of a grand coalition and therefore full cooperation. We find some empirical support for our main results: Our model develops a bimodal coalition size distribution over time similar to those found in social structures. Our detection and distinguishing of phase transitions may be exemplary for other models of socio-economic systems with low agent numbers and therefore strong finite-size effects.

Dynamic Environmental Photosynthetic Imaging Reveals Emergent Phenotypes

DOE PAGES

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

2016-06-22

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

Complexity and time asymmetry of heart rate variability are altered in acute mental stress.

PubMed

Visnovcova, Z; Mestanik, M; Javorka, M; Mokra, D; Gala, M; Jurko, A; Calkovska, A; Tonhajzerova, I

2014-07-01

We aimed to study the complexity and time asymmetry of short-term heart rate variability (HRV) as an index of complex neurocardiac control in response to stress using symbolic dynamics and time irreversibility methods. ECG was recorded at rest and during and after two stressors (Stroop, arithmetic test) in 70 healthy students. Symbolic dynamics parameters (NUPI, NCI, 0V%, 1V%, 2LV%, 2UV%), and time irreversibility indices (P%, G%, E) were evaluated. Additionally, HRV magnitude was quantified by linear parameters: spectral powers in low (LF) and high frequency (HF) bands. Our results showed a reduction of HRV complexity in stress (lower NUPI with both stressors, lower NCI with Stroop). Pattern classification analysis revealed significantly higher 0V% and lower 2LV% with both stressors, indicating a shift in sympathovagal balance, and significantly higher 1V% and lower 2UV% with Stroop. An unexpected result was found in time irreversibility: significantly lower G% and E with both stressors, P% index significantly declined only with arithmetic test. Linear HRV analysis confirmed vagal withdrawal (lower HF) with both stressors; LF significantly increased with Stroop and decreased with arithmetic test. Correlation analysis revealed no significant associations between symbolic dynamics and time irreversibility. Concluding, symbolic dynamics and time irreversibility could provide independent information related to alterations of neurocardiac control integrity in stress-related disease.

An Adaptive Complex Network Model for Brain Functional Networks

PubMed Central

Gomez Portillo, Ignacio J.; Gleiser, Pablo M.

2009-01-01

Brain functional networks are graph representations of activity in the brain, where the vertices represent anatomical regions and the edges their functional connectivity. These networks present a robust small world topological structure, characterized by highly integrated modules connected sparsely by long range links. Recent studies showed that other topological properties such as the degree distribution and the presence (or absence) of a hierarchical structure are not robust, and show different intriguing behaviors. In order to understand the basic ingredients necessary for the emergence of these complex network structures we present an adaptive complex network model for human brain functional networks. The microscopic units of the model are dynamical nodes that represent active regions of the brain, whose interaction gives rise to complex network structures. The links between the nodes are chosen following an adaptive algorithm that establishes connections between dynamical elements with similar internal states. We show that the model is able to describe topological characteristics of human brain networks obtained from functional magnetic resonance imaging studies. In particular, when the dynamical rules of the model allow for integrated processing over the entire network scale-free non-hierarchical networks with well defined communities emerge. On the other hand, when the dynamical rules restrict the information to a local neighborhood, communities cluster together into larger ones, giving rise to a hierarchical structure, with a truncated power law degree distribution. PMID:19738902

Imaging dynamic and selective low-complexity domain interactions that control gene transcription.

PubMed

Chong, Shasha; Dugast-Darzacq, Claire; Liu, Zhe; Dong, Peng; Dailey, Gina M; Cattoglio, Claudia; Heckert, Alec; Banala, Sambashiva; Lavis, Luke; Darzacq, Xavier; Tjian, Robert

2018-06-21

Many eukaryotic transcription factors (TFs) contain intrinsically disordered low-complexity domains (LCDs), but how they drive transactivation remains unclear. Here, live-cell single-molecule imaging reveals that TF-LCDs form local high-concentration interaction hubs at synthetic and endogenous genomic loci. TF-LCD hubs stabilize DNA binding, recruit RNA polymerase II (Pol II), and activate transcription. LCD-LCD interactions within hubs are highly dynamic, display selectivity with binding partners, and are differentially sensitive to disruption by hexanediols. Under physiological conditions, rapid and reversible LCD-LCD interactions occur between TFs and the Pol II machinery without detectable phase separation. Our findings reveal fundamental mechanisms underpinning transcriptional control and suggest a framework for developing single-molecule imaging screens for novel drugs targeting gene regulatory interactions implicated in disease. Copyright © 2018, American Association for the Advancement of Science.

Sparsity enabled cluster reduced-order models for control

NASA Astrophysics Data System (ADS)

Kaiser, Eurika; Morzyński, Marek; Daviller, Guillaume; Kutz, J. Nathan; Brunton, Bingni W.; Brunton, Steven L.

2018-01-01

Characterizing and controlling nonlinear, multi-scale phenomena are central goals in science and engineering. Cluster-based reduced-order modeling (CROM) was introduced to exploit the underlying low-dimensional dynamics of complex systems. CROM builds a data-driven discretization of the Perron-Frobenius operator, resulting in a probabilistic model for ensembles of trajectories. A key advantage of CROM is that it embeds nonlinear dynamics in a linear framework, which enables the application of standard linear techniques to the nonlinear system. CROM is typically computed on high-dimensional data; however, access to and computations on this full-state data limit the online implementation of CROM for prediction and control. Here, we address this key challenge by identifying a small subset of critical measurements to learn an efficient CROM, referred to as sparsity-enabled CROM. In particular, we leverage compressive measurements to faithfully embed the cluster geometry and preserve the probabilistic dynamics. Further, we show how to identify fewer optimized sensor locations tailored to a specific problem that outperform random measurements. Both of these sparsity-enabled sensing strategies significantly reduce the burden of data acquisition and processing for low-latency in-time estimation and control. We illustrate this unsupervised learning approach on three different high-dimensional nonlinear dynamical systems from fluids with increasing complexity, with one application in flow control. Sparsity-enabled CROM is a critical facilitator for real-time implementation on high-dimensional systems where full-state information may be inaccessible.

Living-Cell Microarrays

PubMed Central

Yarmush, Martin L.; King, Kevin R.

2011-01-01

Living cells are remarkably complex. To unravel this complexity, living-cell assays have been developed that allow delivery of experimental stimuli and measurement of the resulting cellular responses. High-throughput adaptations of these assays, known as living-cell microarrays, which are based on microtiter plates, high-density spotting, microfabrication, and microfluidics technologies, are being developed for two general applications: (a) to screen large-scale chemical and genomic libraries and (b) to systematically investigate the local cellular microenvironment. These emerging experimental platforms offer exciting opportunities to rapidly identify genetic determinants of disease, to discover modulators of cellular function, and to probe the complex and dynamic relationships between cells and their local environment. PMID:19413510

Double symbolic joint entropy in nonlinear dynamic complexity analysis

NASA Astrophysics Data System (ADS)

Yao, Wenpo; Wang, Jun

2017-07-01

Symbolizations, the base of symbolic dynamic analysis, are classified as global static and local dynamic approaches which are combined by joint entropy in our works for nonlinear dynamic complexity analysis. Two global static methods, symbolic transformations of Wessel N. symbolic entropy and base-scale entropy, and two local ones, namely symbolizations of permutation and differential entropy, constitute four double symbolic joint entropies that have accurate complexity detections in chaotic models, logistic and Henon map series. In nonlinear dynamical analysis of different kinds of heart rate variability, heartbeats of healthy young have higher complexity than those of the healthy elderly, and congestive heart failure (CHF) patients are lowest in heartbeats' joint entropy values. Each individual symbolic entropy is improved by double symbolic joint entropy among which the combination of base-scale and differential symbolizations have best complexity analysis. Test results prove that double symbolic joint entropy is feasible in nonlinear dynamic complexity analysis.

Understanding the Complexity of Temperature Dynamics in Xinjiang, China, from Multitemporal Scale and Spatial Perspectives

PubMed Central

Chen, Yaning; Li, Weihong; Liu, Zuhan; Wei, Chunmeng; Tang, Jie

2013-01-01

Based on the observed data from 51 meteorological stations during the period from 1958 to 2012 in Xinjiang, China, we investigated the complexity of temperature dynamics from the temporal and spatial perspectives by using a comprehensive approach including the correlation dimension (CD), classical statistics, and geostatistics. The main conclusions are as follows (1) The integer CD values indicate that the temperature dynamics are a complex and chaotic system, which is sensitive to the initial conditions. (2) The complexity of temperature dynamics decreases along with the increase of temporal scale. To describe the temperature dynamics, at least 3 independent variables are needed at daily scale, whereas at least 2 independent variables are needed at monthly, seasonal, and annual scales. (3) The spatial patterns of CD values at different temporal scales indicate that the complex temperature dynamics are derived from the complex landform. PMID:23843732

Detecting recurrence domains of dynamical systems by symbolic dynamics.

PubMed

beim Graben, Peter; Hutt, Axel

2013-04-12

We propose an algorithm for the detection of recurrence domains of complex dynamical systems from time series. Our approach exploits the characteristic checkerboard texture of recurrence domains exhibited in recurrence plots. In phase space, recurrence plots yield intersecting balls around sampling points that could be merged into cells of a phase space partition. We construct this partition by a rewriting grammar applied to the symbolic dynamics of time indices. A maximum entropy principle defines the optimal size of intersecting balls. The final application to high-dimensional brain signals yields an optimal symbolic recurrence plot revealing functional components of the signal.

Asymmetry and basic pathways in sleep-stage transitions

NASA Astrophysics Data System (ADS)

Lo, Chung-Chuan; Bartsch, Ronny P.; Ivanov, Plamen Ch.

2013-04-01

We study dynamical aspects of sleep micro-architecture. We find that sleep dynamics exhibits a high degree of asymmetry, and that the entire class of sleep-stage transition pathways underlying the complexity of sleep dynamics throughout the night can be characterized by two independent asymmetric transition paths. These basic pathways remain stable under sleep disorders, even though the degree of asymmetry is significantly reduced. Our findings demonstrate an intriguing temporal organization in sleep micro-architecture at short time scales that is typical for physical systems exhibiting self-organized criticality (SOC), and indicates nonequilibrium critical dynamics in brain activity during sleep.

Large Eddy Simulation of High Reynolds Number Complex Flows

NASA Astrophysics Data System (ADS)

Verma, Aman

Marine configurations are subject to a variety of complex hydrodynamic phenomena affecting the overall performance of the vessel. The turbulent flow affects the hydrodynamic drag, propulsor performance and structural integrity, control-surface effectiveness, and acoustic signature of the marine vessel. Due to advances in massively parallel computers and numerical techniques, an unsteady numerical simulation methodology such as Large Eddy Simulation (LES) is well suited to study such complex turbulent flows whose Reynolds numbers (Re) are typically on the order of 10. 6. LES also promises increasedaccuracy over RANS based methods in predicting unsteady phenomena such as cavitation and noise production. This dissertation develops the capability to enable LES of high Re flows in complex geometries (e.g. a marine vessel) on unstructured grids and provide physical insight into the turbulent flow. LES is performed to investigate the geometry induced separated flow past a marine propeller attached to a hull, in an off-design condition called crashback. LES shows good quantitative agreement with experiments and provides a physical mechanism to explain the increase in side-force on the propeller blades below an advance ratio of J=-0.7. Fundamental developments in the dynamic subgrid-scale model for LES are pursued to improve the LES predictions, especially for complex flows on unstructured grids. A dynamic procedure is proposed to estimate a Lagrangian time scale based on a surrogate correlation without any adjustable parameter. The proposed model is applied to turbulent channel, cylinder and marine propeller flows and predicts improved results over other model variants due to a physically consistent Lagrangian time scale. A wall model is proposed for application to LES of high Reynolds number wall-bounded flows. The wall model is formulated as the minimization of a generalized constraint in the dynamic model for LES and applied to LES of turbulent channel flow at various Reynolds numbers up to Reτ=10000 and coarse grid resolutions to obtain significant improvement.

High accuracy mantle convection simulation through modern numerical methods - II: realistic models and problems

NASA Astrophysics Data System (ADS)

Heister, Timo; Dannberg, Juliane; Gassmöller, Rene; Bangerth, Wolfgang

2017-08-01

Computations have helped elucidate the dynamics of Earth's mantle for several decades already. The numerical methods that underlie these simulations have greatly evolved within this time span, and today include dynamically changing and adaptively refined meshes, sophisticated and efficient solvers, and parallelization to large clusters of computers. At the same time, many of the methods - discussed in detail in a previous paper in this series - were developed and tested primarily using model problems that lack many of the complexities that are common to the realistic models our community wants to solve today. With several years of experience solving complex and realistic models, we here revisit some of the algorithm designs of the earlier paper and discuss the incorporation of more complex physics. In particular, we re-consider time stepping and mesh refinement algorithms, evaluate approaches to incorporate compressibility, and discuss dealing with strongly varying material coefficients, latent heat, and how to track chemical compositions and heterogeneities. Taken together and implemented in a high-performance, massively parallel code, the techniques discussed in this paper then allow for high resolution, 3-D, compressible, global mantle convection simulations with phase transitions, strongly temperature dependent viscosity and realistic material properties based on mineral physics data.

Billion frames per second spectrum measurement for high-repetition-rate optical pulses based on time stretching technique

NASA Astrophysics Data System (ADS)

Furukawa, Hideaki; Makino, Takeshi; Asghari, Mohammad H.; Trinh, Paul; Jalali, Bahram; Wang, Xiaomin; Kobayashi, Tetsuya; Man, Wai S.; Tsang, Kwong Shing; Wada, Naoya

2017-02-01

Single-shot and long record length spectrum measurements of high-repetition-rate optical pulses are essential for research on nonlinear dynamics as well as for applications in sensing and communication. To achieve a continuous measurements we employ the Time Stretch Dispersive Fourier Transform. We show single-shot measurements of millions of sequential pulses at high repetition rate of 1 Giga spectra per second. Results were obtained using -100 ps/nm dispersive Fourier transform module and a 50 Gsample/s real-time digitizer of 16 GHz bandwidth. Single-shot spectroscopy of 1 GHz optical pulse train was achieved with the wavelength resolution of approximately 150 pm. This instrument is ideal for observation of complex nonlinear dynamics such as switching, mode locking and soliton dynamics in high repetition rate lasers.

Dynamics of Charged Species in Ionic-Neutral Block Copolymer and Surfactant Complexes [Structural Relaxation and Dynamics of Ionic-Neutral Block Copolymer Surfactant Complexes

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

Borreguero, Jose M.; Pincus, Philip A.; Sumpter, Bobby G.

Structure–property relationships of ionic block copolymer (BCP) surfactant complexes are critical toward the progress of favorable engineering design of efficient charge-transport materials. In this paper, molecular dynamics simulations are used to understand the dynamics of charged-neutral BCP and surfactant complexes. The dynamics are examined for two different systems: charged-neutral double-hydrophilic and hydrophobic–hydrophilic block copolymers with oppositely charged surfactant moieties. The dynamics of the surfactant head, tails, and charges are studied for five different BCP volume fractions. We observe that the dynamics of the different species solely depend on the balance between electrostatic and entropic interactions between the charged species andmore » the neutral monomers. The favorable hydrophobic–hydrophobic interactions and the unfavorable hydrophobic–hydrophilic interactions determine the mobilities of the monomers. The dynamical properties of the charge species influence complex formation. Structural relaxations exhibit length-scale dependent behavior, with slower relaxation at the radius of gyration length-scale and faster relaxation at the segmental length-scale, consistent with previous results. The dynamical analysis correlates ion-exchange kinetics to the self-assembly behavior of the complexes.« less

Dynamics of Charged Species in Ionic-Neutral Block Copolymer and Surfactant Complexes [Structural Relaxation and Dynamics of Ionic-Neutral Block Copolymer Surfactant Complexes

DOE PAGES

Borreguero, Jose M.; Pincus, Philip A.; Sumpter, Bobby G.; ...

2017-06-21

Structure–property relationships of ionic block copolymer (BCP) surfactant complexes are critical toward the progress of favorable engineering design of efficient charge-transport materials. In this paper, molecular dynamics simulations are used to understand the dynamics of charged-neutral BCP and surfactant complexes. The dynamics are examined for two different systems: charged-neutral double-hydrophilic and hydrophobic–hydrophilic block copolymers with oppositely charged surfactant moieties. The dynamics of the surfactant head, tails, and charges are studied for five different BCP volume fractions. We observe that the dynamics of the different species solely depend on the balance between electrostatic and entropic interactions between the charged species andmore » the neutral monomers. The favorable hydrophobic–hydrophobic interactions and the unfavorable hydrophobic–hydrophilic interactions determine the mobilities of the monomers. The dynamical properties of the charge species influence complex formation. Structural relaxations exhibit length-scale dependent behavior, with slower relaxation at the radius of gyration length-scale and faster relaxation at the segmental length-scale, consistent with previous results. The dynamical analysis correlates ion-exchange kinetics to the self-assembly behavior of the complexes.« less

Atomic-scale Modeling of the Structure and Dynamics of Dislocations in Complex Alloys at High Temperatures

NASA Technical Reports Server (NTRS)

Daw, Murray S.; Mills, Michael J.

2003-01-01

We report on the progress made during the first year of the project. Most of the progress at this point has been on the theoretical and computational side. Here are the highlights: (1) A new code, tailored for high-end desktop computing, now combines modern Accelerated Dynamics (AD) with the well-tested Embedded Atom Method (EAM); (2) The new Accelerated Dynamics allows the study of relatively slow, thermally-activated processes, such as diffusion, which are much too slow for traditional Molecular Dynamics; (3) We have benchmarked the new AD code on a rather simple and well-known process: vacancy diffusion in copper; and (4) We have begun application of the AD code to the diffusion of vacancies in ordered intermetallics.

Sparse Additive Ordinary Differential Equations for Dynamic Gene Regulatory Network Modeling.

PubMed

Wu, Hulin; Lu, Tao; Xue, Hongqi; Liang, Hua

2014-04-02

The gene regulation network (GRN) is a high-dimensional complex system, which can be represented by various mathematical or statistical models. The ordinary differential equation (ODE) model is one of the popular dynamic GRN models. High-dimensional linear ODE models have been proposed to identify GRNs, but with a limitation of the linear regulation effect assumption. In this article, we propose a sparse additive ODE (SA-ODE) model, coupled with ODE estimation methods and adaptive group LASSO techniques, to model dynamic GRNs that could flexibly deal with nonlinear regulation effects. The asymptotic properties of the proposed method are established and simulation studies are performed to validate the proposed approach. An application example for identifying the nonlinear dynamic GRN of T-cell activation is used to illustrate the usefulness of the proposed method.

Hierarchical cluster-based partial least squares regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models.

PubMed

Tøndel, Kristin; Indahl, Ulf G; Gjuvsland, Arne B; Vik, Jon Olav; Hunter, Peter; Omholt, Stig W; Martens, Harald

2011-06-01

Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR), where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR) and ordinary least squares (OLS) regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback loops. HC-PLSR is a promising approach for metamodelling in systems biology, especially for highly nonlinear or non-monotone parameter to phenotype maps. The algorithm can be flexibly adjusted to suit the complexity of the dynamic model behaviour, inviting automation in the metamodelling of complex systems.

Hierarchical Cluster-based Partial Least Squares Regression (HC-PLSR) is an efficient tool for metamodelling of nonlinear dynamic models

PubMed Central

2011-01-01

Background Deterministic dynamic models of complex biological systems contain a large number of parameters and state variables, related through nonlinear differential equations with various types of feedback. A metamodel of such a dynamic model is a statistical approximation model that maps variation in parameters and initial conditions (inputs) to variation in features of the trajectories of the state variables (outputs) throughout the entire biologically relevant input space. A sufficiently accurate mapping can be exploited both instrumentally and epistemically. Multivariate regression methodology is a commonly used approach for emulating dynamic models. However, when the input-output relations are highly nonlinear or non-monotone, a standard linear regression approach is prone to give suboptimal results. We therefore hypothesised that a more accurate mapping can be obtained by locally linear or locally polynomial regression. We present here a new method for local regression modelling, Hierarchical Cluster-based PLS regression (HC-PLSR), where fuzzy C-means clustering is used to separate the data set into parts according to the structure of the response surface. We compare the metamodelling performance of HC-PLSR with polynomial partial least squares regression (PLSR) and ordinary least squares (OLS) regression on various systems: six different gene regulatory network models with various types of feedback, a deterministic mathematical model of the mammalian circadian clock and a model of the mouse ventricular myocyte function. Results Our results indicate that multivariate regression is well suited for emulating dynamic models in systems biology. The hierarchical approach turned out to be superior to both polynomial PLSR and OLS regression in all three test cases. The advantage, in terms of explained variance and prediction accuracy, was largest in systems with highly nonlinear functional relationships and in systems with positive feedback loops. Conclusions HC-PLSR is a promising approach for metamodelling in systems biology, especially for highly nonlinear or non-monotone parameter to phenotype maps. The algorithm can be flexibly adjusted to suit the complexity of the dynamic model behaviour, inviting automation in the metamodelling of complex systems. PMID:21627852

Single-Molecule Spectroscopy and Imaging Studies of Protein Dynamics

NASA Astrophysics Data System (ADS)

Lu, H. Peter

2012-04-01

Enzymatic reactions and protein-protein interactions are traditionally studied at the ensemble level, despite significant static and dynamic inhomogeneities. Subtle conformational changes play a crucial role in protein functions, and these protein conformations are highly dynamic rather than being static. We applied AFM-enhanced single-molecule spectroscopy to study the mechanisms and dynamics of enzymatic reactions involved with kinase and lysozyme proteins. Enzymatic reaction turnovers and the associated structure changes of individual protein molecules were observed simultaneously in real-time by single-molecule FRET detections. Our single-molecule spectroscopy measurements of T4 lysozyme and HPPK enzymatic conformational dynamics have revealed time bunching effect and intermittent coherence in conformational state change dynamics involving in enzymatic reaction cycles. The coherent conformational state dynamics suggests that the enzymatic catalysis involves a multi-step conformational motion along the coordinates of substrate-enzyme complex formation and product releasing, presenting as an extreme dynamic behavior intrinsically related to the time bunching effect that we have reported previously. Our results of HPPK interaction with substrate support a multiple-conformational state model, being consistent with a complementary conformation selection and induced-fit enzymatic loop-gated conformational change mechanism in substrate-enzyme active complex formation. Our new approach is applicable to a wide range of single-molecule FRET measurements for protein conformational changes under enzymatic reactions.

Multilayer-MCTDH approach to the energy transfer dynamics in the LH2 antenna complex

NASA Astrophysics Data System (ADS)

Shibl, Mohamed F.; Schulze, Jan; Al-Marri, Mohammed J.; Kühn, Oliver

2017-09-01

The multilayer multiconfiguration time-dependent Hartree method is used to study the coupled exciton-vibrational dynamics in a high-dimensional nonameric model of the LH2 antenna complex of purple bacteria. The exciton-vibrational coupling is parametrized within the Huang-Rhys model according to phonon and intramolecular vibrational modes derived from an experimental bacteriochlorophyll spectral density. In contrast to reduced density matrix approaches, the Schrödinger equation is solved explicitly, giving access to the full wave function. This facilitates an unbiased analysis in terms of the coupled dynamics of excitonic and vibrational degrees of freedom. For the present system, we identify spectator modes for the B800 to B800 transfer and we find a non-additive effect of phonon and intramolecular vibrational modes on the B800 to B850 exciton transfer.

Computational Study of the Genomic and Epigenomic Phenomena

NASA Astrophysics Data System (ADS)

Yang, Wenjing

Biological systems are perhaps the ultimate complex systems, uniquely capable of processing and communicating information, reproducing in their lifetimes, and adapting in evolutionary time scales. My dissertation research focuses on using computational approaches to understand the biocomplexity manifested in the multitude of length scales and time scales. At the molecular and cellular level, central to the complex behavior of a biological system is the regulatory network. My research study focused on epigenetics, which is essential for multicellular organisms to establish cellular identity during development or in response to intracellular and environmental stimuli. My computational study of epigenomics is greatly facilitated by recent advances in high-throughput sequencing technology, which enables high-resolution snapshots of epigenomes and transcriptomes. Using human CD4+ T cell as a model system, the dynamical changes in epigenome and transcriptome pertinent to T cell activation were investigated at the genome scale. Going beyond traditional focus on transcriptional regulation, I provided evidences that post-transcriptional regulation may serve as a major component of the regulatory network. In addition, I explored alternative polyadenylation, another novel aspect of gene regulation, and how it cross-talks with the local chromatin structure. As the renowned theoretical biologist Theodosius Dobzhansky said eloquently, "Nothing in biology makes sense except in the light of evolution''. To better understand this ubiquitous driving force in the biological world, I went beyond molecular events in a single organism, and investigated the dynamical changes of population structure along the evolutionary time scale. To this end, we used HIV virus population dynamics in the host immune system as a model system. The evolution of HIV viral population plays a key role in AIDS immunopathogenesis with its exceptionally high mutation rate. However, the theoretical studies of the effect of recombination have been rather limited. Given the phylogenetic and experimental evidences for the high recombination rate and its important role in HIV evolution and epidemics, I established a mathematical model to study the effect of recombination, and explored the complex behavior of this dynamics system.

Quantification of dynamic protein complexes using Renilla luciferase fragment complementation applied to protein kinase A activities in vivo.

PubMed

Stefan, E; Aquin, S; Berger, N; Landry, C R; Nyfeler, B; Bouvier, M; Michnick, S W

2007-10-23

The G protein-coupled receptor (GPCR) superfamily represents the most important class of pharmaceutical targets. Therefore, the characterization of receptor cascades and their ligands is a prerequisite to discovering novel drugs. Quantification of agonist-induced second messengers and downstream-coupled kinase activities is central to characterization of GPCRs or other pathways that converge on GPCR-mediated signaling. Furthermore, there is a need for simple, cell-based assays that would report on direct or indirect actions on GPCR-mediated effectors of signaling. More generally, there is a demand for sensitive assays to quantify alterations of protein complexes in vivo. We describe the development of a Renilla luciferase (Rluc)-based protein fragment complementation assay (PCA) that was designed specifically to investigate dynamic protein complexes. We demonstrate these features for GPCR-induced disassembly of protein kinase A (PKA) regulatory and catalytic subunits, a key effector of GPCR signaling. Taken together, our observations show that the PCA allows for direct and accurate measurements of live changes of absolute values of protein complex assembly and disassembly as well as cellular imaging and dynamic localization of protein complexes. Moreover, the Rluc-PCA has a sufficiently high signal-to-background ratio to identify endogenously expressed Galpha(s) protein-coupled receptors. We provide pharmacological evidence that the phosphodiesterase-4 family selectively down-regulates constitutive beta-2 adrenergic- but not vasopressin-2 receptor-mediated PKA activities. Our results show that the sensitivity of the Rluc-PCA simplifies the recording of pharmacological profiles of GPCR-based candidate drugs and could be extended to high-throughput screens to identify novel direct modulators of PKA or upstream components of GPCR signaling cascades.

Dynamic rupture scenarios from Sumatra to Iceland - High-resolution earthquake source physics on natural fault systems

NASA Astrophysics Data System (ADS)

Gabriel, A. A.; Madden, E. H.; Ulrich, T.; Wollherr, S.

2016-12-01

Capturing the observed complexity of earthquake sources in dynamic rupture simulations may require: non-linear fault friction, thermal and fluid effects, heterogeneous fault stress and strength initial conditions, fault curvature and roughness, on- and off-fault non-elastic failure. All of these factors have been independently shown to alter dynamic rupture behavior and thus possibly influence the degree of realism attainable via simulated ground motions. In this presentation we will show examples of high-resolution earthquake scenarios, e.g. based on the 2004 Sumatra-Andaman Earthquake and a potential rupture of the Husavik-Flatey fault system in Northern Iceland. The simulations combine a multitude of representations of source complexity at the necessary spatio-temporal resolution enabled by excellent scalability on modern HPC systems. Such simulations allow an analysis of the dominant factors impacting earthquake source physics and ground motions given distinct tectonic settings or distinct focuses of seismic hazard assessment. Across all simulations, we find that fault geometry concurrently with the regional background stress state provide a first order influence on source dynamics and the emanated seismic wave field. The dynamic rupture models are performed with SeisSol, a software package based on an ADER-Discontinuous Galerkin scheme for solving the spontaneous dynamic earthquake rupture problem with high-order accuracy in space and time. Use of unstructured tetrahedral meshes allows for a realistic representation of the non-planar fault geometry, subsurface structure and bathymetry. The results presented highlight the fact that modern numerical methods are essential to further our understanding of earthquake source physics and complement both physic-based ground motion research and empirical approaches in seismic hazard analysis.

Dynamic rupture scenarios from Sumatra to Iceland - High-resolution earthquake source physics on natural fault systems

NASA Astrophysics Data System (ADS)

Gabriel, Alice-Agnes; Madden, Elizabeth H.; Ulrich, Thomas; Wollherr, Stephanie

2017-04-01

Capturing the observed complexity of earthquake sources in dynamic rupture simulations may require: non-linear fault friction, thermal and fluid effects, heterogeneous fault stress and fault strength initial conditions, fault curvature and roughness, on- and off-fault non-elastic failure. All of these factors have been independently shown to alter dynamic rupture behavior and thus possibly influence the degree of realism attainable via simulated ground motions. In this presentation we will show examples of high-resolution earthquake scenarios, e.g. based on the 2004 Sumatra-Andaman Earthquake, the 1994 Northridge earthquake and a potential rupture of the Husavik-Flatey fault system in Northern Iceland. The simulations combine a multitude of representations of source complexity at the necessary spatio-temporal resolution enabled by excellent scalability on modern HPC systems. Such simulations allow an analysis of the dominant factors impacting earthquake source physics and ground motions given distinct tectonic settings or distinct focuses of seismic hazard assessment. Across all simulations, we find that fault geometry concurrently with the regional background stress state provide a first order influence on source dynamics and the emanated seismic wave field. The dynamic rupture models are performed with SeisSol, a software package based on an ADER-Discontinuous Galerkin scheme for solving the spontaneous dynamic earthquake rupture problem with high-order accuracy in space and time. Use of unstructured tetrahedral meshes allows for a realistic representation of the non-planar fault geometry, subsurface structure and bathymetry. The results presented highlight the fact that modern numerical methods are essential to further our understanding of earthquake source physics and complement both physic-based ground motion research and empirical approaches in seismic hazard analysis.

Identification of atomic-level mechanisms for gas-phase X- + CH3Y SN2 reactions by combined experiments and simulations.

PubMed

Xie, Jing; Otto, Rico; Mikosch, Jochen; Zhang, Jiaxu; Wester, Roland; Hase, William L

2014-10-21

For the traditional model of gas-phase X(-) + CH3Y SN2 reactions, C3v ion-dipole pre- and postreaction complexes X(-)---CH3Y and XCH3---Y(-), separated by a central barrier, are formed. Statistical intramolecular dynamics are assumed for these complexes, so that their unimolecular rate constants are given by RRKM theory. Both previous simulations and experiments have shown that the dynamics of these complexes are not statistical and of interest is how these nonstatistical dynamics affect the SN2 rate constant. This work also found there was a transition from an indirect, nonstatistical, complex forming mechanism, to a direct mechanism, as either the vibrational and/or relative translational energy of the reactants was increased. The current Account reviews recent collaborative studies involving molecular beam ion-imaging experiments and direct (on-the-fly) dynamics simulations of the SN2 reactions for which Cl(-), F(-), and OH(-) react with CH3I. Also considered are reactions of the microsolvated anions OH(-)(H2O) and OH(-)(H2O)2 with CH3I. These studies have provided a detailed understanding of the atomistic mechanisms for these SN2 reactions. Overall, the atomistic dynamics for the Cl(-) + CH3I SN2 reaction follows those found in previous studies. The reaction is indirect, complex forming at low reactant collision energies, and then there is a transition to direct reaction between 0.2 and 0.4 eV. The direct reaction may occur by rebound mechanism, in which the ClCH3 product rebounds backward from the I(-) product or a stripping mechanism in which Cl(-) strips CH3 from the I atom and scatters in the forward direction. A similar indirect to direct mechanistic transition was observed in previous work for the Cl(-) + CH3Cl and Cl(-) + CH3Br SN2 reactions. At the high collision energy of 1.9 eV, a new indirect mechanism, called the roundabout, was discovered. For the F(-) + CH3I reaction, there is not a transition from indirect to direct reaction as Erel is increased. The indirect mechanism, with prereaction complex formation, is important at all the Erel investigated, contributing up ∼60% of the reaction. The remaining direct reaction occurs by the rebound and stripping mechanisms. Though the potential energy curve for the OH(-) + CH3I reaction is similar to that for F(-) + CH3I, the two reactions have different dynamics. They are akin, in that for both there is not a transition from an indirect to direct reaction. However, for F(-) + CH3I indirect reaction dominates at all Erel, but it is less important for OH(-) + CH3I and becomes negligible as Erel is increased. Stripping is a minor channel for F(-) + CH3I, but accounts for more than 60% of the OH(-) + CH3I reaction at high Erel. Adding one or two H2O molecules to OH(-) alters the reaction dynamics from that for unsolvated OH(-). Adding one H2O molecule enhances indirect reaction at low Erel, and changes the reaction mechanism from primarily stripping to rebound at high Erel. With two H2O molecules the dynamics is indirect and isotropic at all collision energies.

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

Transcriptome complexity in cardiac development and diseases--an expanding universe between genome and phenome.

PubMed

Gao, Chen; Wang, Yibin

2014-01-01

With the advancement of transcriptome profiling by micro-arrays and high-throughput RNA-sequencing, transcriptome complexity and its dynamics are revealed at different levels in cardiovascular development and diseases. In this review, we will highlight the recent progress in our knowledge of cardiovascular transcriptome complexity contributed by RNA splicing, RNA editing and noncoding RNAs. The emerging importance of many of these previously under-explored aspects of gene regulation in cardiovascular development and pathology will be discussed.

Mapping mechanical force propagation through biomolecular complexes

DOE PAGES

Schoeler, Constantin; Bernardi, Rafael C.; Malinowska, Klara H.; ...

2015-08-11

In this paper, we employ single-molecule force spectroscopy with an atomic force microscope (AFM) and steered molecular dynamics (SMD) simulations to reveal force propagation pathways through a mechanically ultrastable multidomain cellulosome protein complex. We demonstrate a new combination of network-based correlation analysis supported by AFM directional pulling experiments, which allowed us to visualize stiff paths through the protein complex along which force is transmitted. Finally, the results implicate specific force-propagation routes nonparallel to the pulling axis that are advantageous for achieving high dissociation forces.

EvoGraph: On-The-Fly Efficient Mining of Evolving Graphs on GPU

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

Sengupta, Dipanjan; Song, Shuaiwen

With the prevalence of the World Wide Web and social networks, there has been a growing interest in high performance analytics for constantly-evolving dynamic graphs. Modern GPUs provide massive AQ1 amount of parallelism for efficient graph processing, but the challenges remain due to their lack of support for the near real-time streaming nature of dynamic graphs. Specifically, due to the current high volume and velocity of graph data combined with the complexity of user queries, traditional processing methods by first storing the updates and then repeatedly running static graph analytics on a sequence of versions or snapshots are deemed undesirablemore » and computational infeasible on GPU. We present EvoGraph, a highly efficient and scalable GPU- based dynamic graph analytics framework.« less

NASTRAN analysis of the 1/8-scale space shuttle dynamic model

NASA Technical Reports Server (NTRS)

Bernstein, M.; Mason, P. W.; Zalesak, J.; Gregory, D. J.; Levy, A.

1973-01-01

The space shuttle configuration has more complex structural dynamic characteristics than previous launch vehicles primarily because of the high model density at low frequencies and the high degree of coupling between the lateral and longitudinal motions. An accurate analytical representation of these characteristics is a primary means for treating structural dynamics problems during the design phase of the shuttle program. The 1/8-scale model program was developed to explore the adequacy of available analytical modeling technology and to provide the means for investigating problems which are more readily treated experimentally. The basic objectives of the 1/8-scale model program are: (1) to provide early verification of analytical modeling procedures on a shuttle-like structure, (2) to demonstrate important vehicle dynamic characteristics of a typical shuttle design, (3) to disclose any previously unanticipated structural dynamic characteristics, and (4) to provide for development and demonstration of cost effective prototype testing procedures.

ls1 mardyn: The Massively Parallel Molecular Dynamics Code for Large Systems.

PubMed

Niethammer, Christoph; Becker, Stefan; Bernreuther, Martin; Buchholz, Martin; Eckhardt, Wolfgang; Heinecke, Alexander; Werth, Stephan; Bungartz, Hans-Joachim; Glass, Colin W; Hasse, Hans; Vrabec, Jadran; Horsch, Martin

2014-10-14

The molecular dynamics simulation code ls1 mardyn is presented. It is a highly scalable code, optimized for massively parallel execution on supercomputing architectures and currently holds the world record for the largest molecular simulation with over four trillion particles. It enables the application of pair potentials to length and time scales that were previously out of scope for molecular dynamics simulation. With an efficient dynamic load balancing scheme, it delivers high scalability even for challenging heterogeneous configurations. Presently, multicenter rigid potential models based on Lennard-Jones sites, point charges, and higher-order polarities are supported. Due to its modular design, ls1 mardyn can be extended to new physical models, methods, and algorithms, allowing future users to tailor it to suit their respective needs. Possible applications include scenarios with complex geometries, such as fluids at interfaces, as well as nonequilibrium molecular dynamics simulation of heat and mass transfer.

Effects of constant immigration on the dynamics and persistence of stable and unstable Drosophila populations

PubMed Central

Dey, Snigdhadip; Joshi, Amitabh

2013-01-01

Constant immigration can stabilize population size fluctuations but its effects on extinction remain unexplored. We show that constant immigration significantly reduced extinction in fruitfly populations with relatively stable or unstable dynamics. In unstable populations with oscillations of amplitude around 1.5 times the mean population size, persistence and constancy were unrelated. Low immigration enhanced persistence without affecting constancy whereas high immigration increased constancy without enhancing persistence. In relatively stable populations with erratic fluctuations of amplitude close to the mean population size, both low and high immigration enhanced persistence. In these populations, the amplitude of fluctuations relative to mean population size went down due to immigration, and their dynamics were altered to low-period cycles. The effects of immigration on the population size distribution and intrinsic dynamics of stable versus unstable populations differed considerably, suggesting that the mechanisms by which immigration reduced extinction risk depended on underlying dynamics in complex ways. PMID:23470546

The diminishing role of hubs in dynamical processes on complex networks.

PubMed

Quax, Rick; Apolloni, Andrea; Sloot, Peter M A

2013-11-06

It is notoriously difficult to predict the behaviour of a complex self-organizing system, where the interactions among dynamical units form a heterogeneous topology. Even if the dynamics of each microscopic unit is known, a real understanding of their contributions to the macroscopic system behaviour is still lacking. Here, we develop information-theoretical methods to distinguish the contribution of each individual unit to the collective out-of-equilibrium dynamics. We show that for a system of units connected by a network of interaction potentials with an arbitrary degree distribution, highly connected units have less impact on the system dynamics when compared with intermediately connected units. In an equilibrium setting, the hubs are often found to dictate the long-term behaviour. However, we find both analytically and experimentally that the instantaneous states of these units have a short-lasting effect on the state trajectory of the entire system. We present qualitative evidence of this phenomenon from empirical findings about a social network of product recommendations, a protein-protein interaction network and a neural network, suggesting that it might indeed be a widespread property in nature.

High performance computing in biology: multimillion atom simulations of nanoscale systems

PubMed Central

Sanbonmatsu, K. Y.; Tung, C.-S.

2007-01-01

Computational methods have been used in biology for sequence analysis (bioinformatics), all-atom simulation (molecular dynamics and quantum calculations), and more recently for modeling biological networks (systems biology). Of these three techniques, all-atom simulation is currently the most computationally demanding, in terms of compute load, communication speed, and memory load. Breakthroughs in electrostatic force calculation and dynamic load balancing have enabled molecular dynamics simulations of large biomolecular complexes. Here, we report simulation results for the ribosome, using approximately 2.64 million atoms, the largest all-atom biomolecular simulation published to date. Several other nanoscale systems with different numbers of atoms were studied to measure the performance of the NAMD molecular dynamics simulation program on the Los Alamos National Laboratory Q Machine. We demonstrate that multimillion atom systems represent a 'sweet spot' for the NAMD code on large supercomputers. NAMD displays an unprecedented 85% parallel scaling efficiency for the ribosome system on 1024 CPUs. We also review recent targeted molecular dynamics simulations of the ribosome that prove useful for studying conformational changes of this large biomolecular complex in atomic detail. PMID:17187988

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

PubMed

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

2018-05-01

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

Reaction Analysis of Shocked Nitromethane using Extended Lagrangian Born-Oppenheimer Molecular Dynamics

NASA Astrophysics Data System (ADS)

Perriot, Romain; Kober, Ed; Mniszewski, Sue; Martinez, Enrique; Niklasson, Anders; Yang, Ping; McGrane, Shawn; Cawkwell, Marc

2017-06-01

Characterizing the complex, rapid reactions of energetic materials under conditions of high temperatures and pressures presents strong experimental and computational challenges. The recently developed extended Lagrangian Born-Oppenheimer molecular dynamics formalism enables the long-term conservation of the total energy in microcanonical trajectories, and using a density functional tight binding formulation provides good chemical accuracy. We use this combined approach to study the evolution of temperature, pressure, and chemical species in shock-compressed liquid nitromethane over hundreds of picoseconds. The chemical species seen in nitromethane under shock compression are compared with those seen under static high temperature conditions. A reduced-order representation of the complex sequence of chemical reactions that characterize this system has been developed from the molecular dynamics simulations by focusing on classes of chemical reactions rather than specific molecular species. Time-resolved infra-red vibrational spectra were also computed from the molecular trajectories and compared to the chemical analysis. These spectra provide a time history of the species present in the system that can be compared directly with recent experiments at LANL.

The interplay of ion crosslinking, free ion content, and polymer mobility in PEO-based single-ion conductors

NASA Astrophysics Data System (ADS)

Lin, Kan-Ju; Maranas, Janna

2010-03-01

We use molecular dynamics simulation to study ion clustering and dynamics in ion containing polymers. This PEO based single-ion conducting ionomer serves as a model system for understanding cation transport in solid state polymer electrolytes (SPEs). Although small-angle x-ray scattering does not show an ionomer peak, we observer various cation-anion complexes in the simulation, suggesting ionomer backbones are crosslinked through ion complexes. These crosslinks reduce the adjacent PEO mobility resulting in a symmetric mobility gradient along the PEO chain. We vary the cation-anion interaction in the simulation to observe the interplay of cation-anion association, polymer mobility and cation motion. Cation-anion association controls the number of free ions, which is important in ionic conductivity when these materials are used as SPEs. Polymer mobility controls how fast the free ions are able to move through the SPE. High conductivity requires both a high free ion content and fast polymer motion. To understand the connection between the two, we ``tune'' the force field in order to manipulate the free ion content and observe the influence on PEO dynamics.

Identifying Dynamic Protein Complexes Based on Gene Expression Profiles and PPI Networks

PubMed Central

Li, Min; Chen, Weijie; Wang, Jianxin; Pan, Yi

2014-01-01

Identification of protein complexes from protein-protein interaction networks has become a key problem for understanding cellular life in postgenomic era. Many computational methods have been proposed for identifying protein complexes. Up to now, the existing computational methods are mostly applied on static PPI networks. However, proteins and their interactions are dynamic in reality. Identifying dynamic protein complexes is more meaningful and challenging. In this paper, a novel algorithm, named DPC, is proposed to identify dynamic protein complexes by integrating PPI data and gene expression profiles. According to Core-Attachment assumption, these proteins which are always active in the molecular cycle are regarded as core proteins. The protein-complex cores are identified from these always active proteins by detecting dense subgraphs. Final protein complexes are extended from the protein-complex cores by adding attachments based on a topological character of “closeness” and dynamic meaning. The protein complexes produced by our algorithm DPC contain two parts: static core expressed in all the molecular cycle and dynamic attachments short-lived. The proposed algorithm DPC was applied on the data of Saccharomyces cerevisiae and the experimental results show that DPC outperforms CMC, MCL, SPICi, HC-PIN, COACH, and Core-Attachment based on the validation of matching with known complexes and hF-measures. PMID:24963481

Characterizing the complexity of spontaneous motor unit patterns of amyotrophic lateral sclerosis using approximate entropy

NASA Astrophysics Data System (ADS)

Zhou, Ping; Barkhaus, Paul E.; Zhang, Xu; Zev Rymer, William

2011-10-01

This paper presents a novel application of the approximate entropy (ApEn) measurement for characterizing spontaneous motor unit activity of amyotrophic lateral sclerosis (ALS) patients. High-density surface electromyography (EMG) was used to record spontaneous motor unit activity bilaterally from the thenar muscles of nine ALS subjects. Three distinct patterns of spontaneous motor unit activity (sporadic spikes, tonic spikes and high-frequency repetitive spikes) were observed. For each pattern, complexity was characterized by calculating the ApEn values of the representative signal segments. A sliding window over each segment was also introduced to quantify the dynamic changes in complexity for the different spontaneous motor unit patterns. We found that the ApEn values for the sporadic spikes were the highest, while those of the high-frequency repetitive spikes were the lowest. There is a significant difference in mean ApEn values between two arbitrary groups of the three spontaneous motor unit patterns (P < 0.001). The dynamic ApEn curve from the sliding window analysis is capable of tracking variations in EMG activity, thus providing a vivid, distinctive description for different patterns of spontaneous motor unit action potentials in terms of their complexity. These findings expand the existing knowledge of spontaneous motor unit activity in ALS beyond what was previously obtained using conventional linear methods such as firing rate or inter-spike interval statistics.

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

ERIC Educational Resources Information Center

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

2018-01-01

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

Highly Luminescent Lanthanide Complexes of 1 Hydroxy-2-pyridinones

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

University of California, Berkeley; Lawrence National Laboratory; Raymond, Kenneth

2007-11-01

The synthesis, X-ray structure, stability, and photophysical properties of several trivalent lanthanide complexes formed from two differing bis-bidentate ligands incorporating either alkyl or alkyl ether linkages and featuring the 1-hydroxy-2-pyridinone (1,2-HOPO) chelate group in complex with Eu(III), Sm(III) and Gd(III) are reported. The Eu(III) complexes are among some of the best examples, pairing highly efficient emission ({Phi}{sub tot}{sup Eu} {approx} 21.5%) with high stability (pEu {approx} 18.6) in aqueous solution, and are excellent candidates for use in biological assays. A comparison of the observed behavior of the complexes with differing backbone linkages shows remarkable similarities, both in stability and photophysicalmore » properties. Low temperature photophysical measurements for a Gd(III) complex were also used to gain insight into the electronic structure, and were found to agree with corresponding TD-DFT calculations for a model complex. A comparison of the high resolution Eu(III) emission spectra in solution and from single crystals also revealed a more symmetric coordination geometry about the metal ion in solution due to dynamic rotation of the observed solid state structure.« less

Coupled, circumferential motions of the cell wall synthesis machinery and MreB filaments in B. subtilis.

PubMed

Garner, Ethan C; Bernard, Remi; Wang, Wenqin; Zhuang, Xiaowei; Rudner, David Z; Mitchison, Tim

2011-07-08

Rod-shaped bacteria elongate by the action of cell wall synthesis complexes linked to underlying dynamic MreB filaments. To understand how the movements of these filaments relate to cell wall synthesis, we characterized the dynamics of MreB and the cell wall elongation machinery using high-precision particle tracking in Bacillus subtilis. We found that MreB and the elongation machinery moved circumferentially around the cell, perpendicular to its length, with nearby synthesis complexes and MreB filaments moving independently in both directions. Inhibition of cell wall synthesis by various methods blocked the movement of MreB. Thus, bacteria elongate by the uncoordinated, circumferential movements of synthetic complexes that insert radial hoops of new peptidoglycan during their transit, possibly driving the motion of the underlying MreB filaments.

Heteroleptic copper(I) complexes prepared from phenanthroline and bis-phosphine ligands.

PubMed

Kaeser, Adrien; Mohankumar, Meera; Mohanraj, John; Monti, Filippo; Holler, Michel; Cid, Juan-José; Moudam, Omar; Nierengarten, Iwona; Karmazin-Brelot, Lydia; Duhayon, Carine; Delavaux-Nicot, Béatrice; Armaroli, Nicola; Nierengarten, Jean-François

2013-10-21

Preparation of [Cu(NN)(PP)](+) derivatives has been systematically investigated starting from two libraries of phenanthroline (NN) derivatives and bis-phosphine (PP) ligands, namely, (A) 1,10-phenanthroline (phen), neocuproine (2,9-dimethyl-1,10-phenanthroline, dmp), bathophenanthroline (4,7-diphenyl-1,10-phenanthroline, Bphen), 2,9-diphenethyl-1,10-phenanthroline (dpep), and 2,9-diphenyl-1,10-phenanthroline (dpp); (B) bis(diphenylphosphino)methane (dppm), 1,2-bis(diphenylphosphino)ethane (dppe), 1,3-bis(diphenylphosphino)propane (dppp), 1,2-bis(diphenylphosphino)benzene (dppb), 1,1'-bis(diphenylphosphino)ferrocene (dppFc), and bis[(2-diphenylphosphino)phenyl] ether (POP). Whatever the bis-phosphine ligand, stable heteroleptic [Cu(NN)(PP)](+) complexes are obtained from the 2,9-unsubstituted-1,10-phenanthroline ligands (phen and Bphen). By contrast, heteroleptic complexes obtained from dmp and dpep are stable in the solid state, but a dynamic ligand exchange reaction is systematically observed in solution, and the homoleptic/heteroleptic ratio is highly dependent on the bis-phosphine ligand. Detailed analysis revealed that the dynamic equilibrium resulting from ligand exchange reactions is mainly influenced by the relative thermodynamic stability of the different possible complexes. Finally, in the case of dpp, only homoleptic complexes were obtained whatever the bis-phosphine ligand. Obviously, steric effects resulting from the presence of the bulky phenyl rings on the dpp ligand destabilize the heteroleptic [Cu(NN)(PP)](+) complexes. In addition to the remarkable thermodynamic stability of [Cu(dpp)2]BF4, this negative steric effect drives the dynamic complexation scenario toward almost exclusive formation of homoleptic [Cu(NN)2](+) and [Cu(PP)2](+) complexes. This work provides the definitive rationalization of the stability of [Cu(NN)(PP)](+) complexes, marking the way for future developments in this field.

Dynamical importance of van der Waals saddle and excited potential surface in C(1D)+D2 complex-forming reaction

PubMed Central

Shen, Zhitao; Ma, Haitao; Zhang, Chunfang; Fu, Mingkai; Wu, Yanan; Bian, Wensheng; Cao, Jianwei

2017-01-01

Encouraged by recent advances in revealing significant effects of van der Waals wells on reaction dynamics, many people assume that van der Waals wells are inevitable in chemical reactions. Here we find that the weak long-range forces cause van der Waals saddles in the prototypical C(1D)+D2 complex-forming reaction that have very different dynamical effects from van der Waals wells at low collision energies. Accurate quantum dynamics calculations on our highly accurate ab initio potential energy surfaces with van der Waals saddles yield cross-sections in close agreement with crossed-beam experiments, whereas the same calculations on an earlier surface with van der Waals wells produce much smaller cross-sections at low energies. Further trajectory calculations reveal that the van der Waals saddle leads to a torsion then sideways insertion reaction mechanism, whereas the well suppresses reactivity. Quantum diffraction oscillations and sharp resonances are also predicted based on our ground- and excited-state potential energy surfaces. PMID:28094253

Collaborative Research. Damage and Burst Dynamics in Failure of Complex Geomaterials. A Statistical Physics Approach to Understanding the Complex Emergent Dynamics in Near Mean-Field Geological Materials

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

Rundle, John B.; Klein, William

We have carried out research to determine the dynamics of failure in complex geomaterials, specifically focusing on the role of defects, damage and asperities in the catastrophic failure processes (now popularly termed “Black Swan events”). We have examined fracture branching and flow processes using models for invasion percolation, focusing particularly on the dynamics of bursts in the branching process. We have achieved a fundamental understanding of the dynamics of nucleation in complex geomaterials, specifically in the presence of inhomogeneous structures.

Regulation of calreticulin–major histocompatibility complex (MHC) class I interactions by ATP

PubMed Central

Wijeyesakere, Sanjeeva Joseph; Gagnon, Jessica K.; Arora, Karunesh; Brooks, Charles L.; Raghavan, Malini

2015-01-01

The MHC class I peptide loading complex (PLC) facilitates the assembly of MHC class I molecules with peptides, but factors that regulate the stability and dynamics of the assembly complex are largely uncharacterized. Based on initial findings that ATP, in addition to MHC class I-specific peptide, is able to induce MHC class I dissociation from the PLC, we investigated the interaction of ATP with the chaperone calreticulin, an endoplasmic reticulum (ER) luminal, calcium-binding component of the PLC that is known to bind ATP. We combined computational and experimental measurements to identify residues within the globular domain of calreticulin, in proximity to the high-affinity calcium-binding site, that are important for high-affinity ATP binding and for ATPase activity. High-affinity calcium binding by calreticulin is required for optimal nucleotide binding, but both ATP and ADP destabilize enthalpy-driven high-affinity calcium binding to calreticulin. ATP also selectively destabilizes the interaction of calreticulin with cellular substrates, including MHC class I molecules. Calreticulin mutants that affect ATP or high-affinity calcium binding display prolonged associations with monoglucosylated forms of cellular MHC class I, delaying MHC class I dissociation from the PLC and their transit through the secretory pathway. These studies reveal central roles for ATP and calcium binding as regulators of calreticulin–substrate interactions and as key determinants of PLC dynamics. PMID:26420867

Probing Biomolecular Structures and Dynamics of Single Molecules Using In-Gel Alternating-Laser Excitation

PubMed Central

Santoso, Yusdi; Kapanidis, Achillefs N.

2009-01-01

Gel electrophoresis is a standard biochemical technique used for separating biomolecules on the basis of size and charge. Despite the use of gels in early single-molecule experiments, gel electrophoresis has not been widely adopted for single-molecule fluorescence spectroscopy. We present a novel method that combines gel electrophoresis and single-molecule fluorescence spectroscopy to simultaneously purify and analyze biomolecules in a gel matrix. Our method, in-gel ALEX, uses non-denaturing gels to purify biomolecular complexes of interest from free components, aggregates, and non-specific complexes. The gel matrix also slows down translational diffusion of molecules, giving rise to long, high-resolution time traces without surface immobilization, which allow extended observations of conformational dynamics in a biologically friendly environment. We demonstrated the compatibility of this method with different types of single molecule spectroscopy techniques, including confocal detection and fluorescence-correlation spectroscopy. We demonstrated that in-gel ALEX can be used to study conformational dynamics at the millisecond timescale; by studying a DNA hairpin in gels, we directly observed fluorescence fluctuations due to conformational interconversion between folded and unfolded states. Our method is amenable to the addition of small molecules that can alter the equilibrium and dynamic properties of the system. In-gel ALEX will be a versatile tool for studying structures and dynamics of complex biomolecules and their assemblies. PMID:19863108

Extreme scale multi-physics simulations of the tsunamigenic 2004 Sumatra megathrust earthquake

NASA Astrophysics Data System (ADS)

Ulrich, T.; Gabriel, A. A.; Madden, E. H.; Wollherr, S.; Uphoff, C.; Rettenberger, S.; Bader, M.

2017-12-01

SeisSol (www.seissol.org) is an open-source software package based on an arbitrary high-order derivative Discontinuous Galerkin method (ADER-DG). It solves spontaneous dynamic rupture propagation on pre-existing fault interfaces according to non-linear friction laws, coupled to seismic wave propagation with high-order accuracy in space and time (minimal dispersion errors). SeisSol exploits unstructured meshes to account for complex geometries, e.g. high resolution topography and bathymetry, 3D subsurface structure, and fault networks. We present the up-to-date largest (1500 km of faults) and longest (500 s) dynamic rupture simulation modeling the 2004 Sumatra-Andaman earthquake. We demonstrate the need for end-to-end-optimization and petascale performance of scientific software to realize realistic simulations on the extreme scales of subduction zone earthquakes: Considering the full complexity of subduction zone geometries leads inevitably to huge differences in element sizes. The main code improvements include a cache-aware wave propagation scheme and optimizations of the dynamic rupture kernels using code generation. In addition, a novel clustered local-time-stepping scheme for dynamic rupture has been established. Finally, asynchronous output has been implemented to overlap I/O and compute time. We resolve the frictional sliding process on the curved mega-thrust and a system of splay faults, as well as the seismic wave field and seafloor displacement with frequency content up to 2.2 Hz. We validate the scenario by geodetic, seismological and tsunami observations. The resulting rupture dynamics shed new light on the activation and importance of splay faults.

Aging and the complexity of cardiovascular dynamics

NASA Technical Reports Server (NTRS)

Kaplan, D. T.; Furman, M. I.; Pincus, S. M.; Ryan, S. M.; Lipsitz, L. A.; Goldberger, A. L.

1991-01-01

Biomedical signals often vary in a complex and irregular manner. Analysis of variability in such signals generally does not address directly their complexity, and so may miss potentially useful information. We analyze the complexity of heart rate and beat-to-beat blood pressure using two methods motivated by nonlinear dynamics (chaos theory). A comparison of a group of healthy elderly subjects with healthy young adults indicates that the complexity of cardiovascular dynamics is reduced with aging. This suggests that complexity of variability may be a useful physiological marker.

Dynamic hydro-climatic networks in pristine and regulated rivers

NASA Astrophysics Data System (ADS)

Botter, G.; Basso, S.; Lazzaro, G.; Doulatyari, B.; Biswal, B.; Schirmer, M.; Rinaldo, A.

2014-12-01

Flow patterns observed at-a-station are the dynamical byproduct of a cascade of processes involving different compartments of the hydro-climatic network (e.g., climate, rainfall, soil, vegetation) that regulates the transformation of rainfall into streamflows. In complex branching rivers, flow regimes result from the heterogeneous arrangement around the stream network of multiple hydrologic cascades that simultaneously occur within distinct contributing areas. As such, flow regimes are seen as the integrated output of a complex "network of networks", which can be properly characterized by its degree of temporal variability and spatial heterogeneity. Hydrologic networks that generate river flow regimes are dynamic in nature. In pristine rivers, the time-variance naturally emerges at multiple timescales from climate variability (namely, seasonality and inter-annual fluctuations), implying that the magnitude (and the features) of the water flow between two nodes may be highly variable across different seasons and years. Conversely, the spatial distribution of river flow regimes within pristine rivers involves scale-dependent transport features, as well as regional climatic and soil use gradients, which in small and meso-scale catchments (A < 103 km2) are usually mild enough to guarantee quite uniform flow regimes and high spatial correlations. Human-impacted rivers, instead, constitute hybrid networks where observed spatio-temporal patterns are dominated by anthropogenic shifts, such as landscape alterations and river regulation. In regulated rivers, the magnitude and the features of water flows from node to node may change significantly through time due to damming and withdrawals. However, regulation may impact river regimes in a spatially heterogeneous manner (e.g. in localized river reaches), with a significant decrease of spatial correlations and network connectivity. Provided that the spatial and temporal dynamics of flow regimes in complex rivers may strongly impact important biotic processes involved in the river food web (e.g. biofilm and riparian vegetation dynamics), the study of rivers as dynamic networks provides important clues to water management strategies and freshwater ecosystem studies.

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

PubMed

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

2014-01-20

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

Exponential rise of dynamical complexity in quantum computing through projections.

PubMed

Burgarth, Daniel Klaus; Facchi, Paolo; Giovannetti, Vittorio; Nakazato, Hiromichi; Pascazio, Saverio; Yuasa, Kazuya

2014-10-10

The ability of quantum systems to host exponentially complex dynamics has the potential to revolutionize science and technology. Therefore, much effort has been devoted to developing of protocols for computation, communication and metrology, which exploit this scaling, despite formidable technical difficulties. Here we show that the mere frequent observation of a small part of a quantum system can turn its dynamics from a very simple one into an exponentially complex one, capable of universal quantum computation. After discussing examples, we go on to show that this effect is generally to be expected: almost any quantum dynamics becomes universal once 'observed' as outlined above. Conversely, we show that any complex quantum dynamics can be 'purified' into a simpler one in larger dimensions. We conclude by demonstrating that even local noise can lead to an exponentially complex dynamics.

Management of complex dynamical systems

NASA Astrophysics Data System (ADS)

MacKay, R. S.

2018-02-01

Complex dynamical systems are systems with many interdependent components which evolve in time. One might wish to control their trajectories, but a more practical alternative is to control just their statistical behaviour. In many contexts this would be both sufficient and a more realistic goal, e.g. climate and socio-economic systems. I refer to it as ‘management’ of complex dynamical systems. In this paper, some mathematics for management of complex dynamical systems is developed in the weakly dependent regime, and questions are posed for the strongly dependent regime.

Chaperone-client complexes: A dynamic liaison

NASA Astrophysics Data System (ADS)

Hiller, Sebastian; Burmann, Björn M.

2018-04-01

Living cells contain molecular chaperones that are organized in intricate networks to surveil protein homeostasis by avoiding polypeptide misfolding, aggregation, and the generation of toxic species. In addition, cellular chaperones also fulfill a multitude of alternative functionalities: transport of clients towards a target location, help them fold, unfold misfolded species, resolve aggregates, or deliver clients towards proteolysis machineries. Until recently, the only available source of atomic resolution information for virtually all chaperones were crystal structures of their client-free, apo-forms. These structures were unable to explain details of the functional mechanisms underlying chaperone-client interactions. The difficulties to crystallize chaperones in complexes with clients arise from their highly dynamic nature, making solution NMR spectroscopy the method of choice for their study. With the advent of advanced solution NMR techniques, in the past few years a substantial number of structural and functional studies on chaperone-client complexes have been resolved, allowing unique insight into the chaperone-client interaction. This review summarizes the recent insights provided by advanced high-resolution NMR-spectroscopy to understand chaperone-client interaction mechanisms at the atomic scale.

Computational reacting gas dynamics

NASA Technical Reports Server (NTRS)

Lam, S. H.

1993-01-01

In the study of high speed flows at high altitudes, such as that encountered by re-entry spacecrafts, the interaction of chemical reactions and other non-equilibrium processes in the flow field with the gas dynamics is crucial. Generally speaking, problems of this level of complexity must resort to numerical methods for solutions, using sophisticated computational fluid dynamics (CFD) codes. The difficulties introduced by reacting gas dynamics can be classified into three distinct headings: (1) the usually inadequate knowledge of the reaction rate coefficients in the non-equilibrium reaction system; (2) the vastly larger number of unknowns involved in the computation and the expected stiffness of the equations; and (3) the interpretation of the detailed reacting CFD numerical results. The research performed accepts the premise that reacting flows of practical interest in the future will in general be too complex or 'untractable' for traditional analytical developments. The power of modern computers must be exploited. However, instead of focusing solely on the construction of numerical solutions of full-model equations, attention is also directed to the 'derivation' of the simplified model from the given full-model. In other words, the present research aims to utilize computations to do tasks which have traditionally been done by skilled theoreticians: to reduce an originally complex full-model system into an approximate but otherwise equivalent simplified model system. The tacit assumption is that once the appropriate simplified model is derived, the interpretation of the detailed numerical reacting CFD numerical results will become much easier. The approach of the research is called computational singular perturbation (CSP).

Fast regional readout CMOS Image Sensor for dynamic MLC tracking

NASA Astrophysics Data System (ADS)

Zin, H.; Harris, E.; Osmond, J.; Evans, P.

2014-03-01

Advanced radiotherapy techniques such as volumetric modulated arc therapy (VMAT) require verification of the complex beam delivery including tracking of multileaf collimators (MLC) and monitoring the dose rate. This work explores the feasibility of a prototype Complementary metal-oxide semiconductor Image Sensor (CIS) for tracking these complex treatments by utilising fast, region of interest (ROI) read out functionality. An automatic edge tracking algorithm was used to locate the MLC leaves edges moving at various speeds (from a moving triangle field shape) and imaged with various sensor frame rates. The CIS demonstrates successful edge detection of the dynamic MLC motion within accuracy of 1.0 mm. This demonstrates the feasibility of the sensor to verify treatment delivery involving dynamic MLC up to ~400 frames per second (equivalent to the linac pulse rate), which is superior to any current techniques such as using electronic portal imaging devices (EPID). CIS provides the basis to an essential real-time verification tool, useful in accessing accurate delivery of complex high energy radiation to the tumour and ultimately to achieve better cure rates for cancer patients.

High-resolution method for evolving complex interface networks

NASA Astrophysics Data System (ADS)

Pan, Shucheng; Hu, Xiangyu Y.; Adams, Nikolaus A.

2018-04-01

In this paper we describe a high-resolution transport formulation of the regional level-set approach for an improved prediction of the evolution of complex interface networks. The novelty of this method is twofold: (i) construction of local level sets and reconstruction of a global level set, (ii) local transport of the interface network by employing high-order spatial discretization schemes for improved representation of complex topologies. Various numerical test cases of multi-region flow problems, including triple-point advection, single vortex flow, mean curvature flow, normal driven flow, dry foam dynamics and shock-bubble interaction show that the method is accurate and suitable for a wide range of complex interface-network evolutions. Its overall computational cost is comparable to the Semi-Lagrangian regional level-set method while the prediction accuracy is significantly improved. The approach thus offers a viable alternative to previous interface-network level-set method.

Modeling dynamic interactions and coherence between marine zooplankton and fishes linked to environmental variability

NASA Astrophysics Data System (ADS)

Liu, Hui; Fogarty, Michael J.; Hare, Jonathan A.; Hsieh, Chih-hao; Glaser, Sarah M.; Ye, Hao; Deyle, Ethan; Sugihara, George

2014-03-01

The dynamics of marine fishes are closely related to lower trophic levels and the environment. Quantitatively understanding ecosystem dynamics linking environmental variability and prey resources to exploited fishes is crucial for ecosystem-based management of marine living resources. However, standard statistical models typically grounded in the concept of linear system may fail to capture the complexity of ecological processes. We have attempted to model ecosystem dynamics using a flexible, nonparametric class of nonlinear forecasting models. We analyzed annual time series of four environmental indices, 22 marine copepod taxa, and four ecologically and commercially important fish species during 1977 to 2009 on Georges Bank, a highly productive and intensively studied area of the northeast U.S. continental shelf ecosystem. We examined the underlying dynamic features of environmental indices and copepods, quantified the dynamic interactions and coherence with fishes, and explored the potential control mechanisms of ecosystem dynamics from a nonlinear perspective. We found: (1) the dynamics of marine copepods and environmental indices exhibiting clear nonlinearity; (2) little evidence of complex dynamics across taxonomic levels of copepods; (3) strong dynamic interactions and coherence between copepods and fishes; and (4) the bottom-up forcing of fishes and top-down control of copepods coexisting as target trophic levels vary. These findings highlight the nonlinear interactions among ecosystem components and the importance of marine zooplankton to fish populations which point to two forcing mechanisms likely interactively regulating the ecosystem dynamics on Georges Bank under a changing environment.

Potent New Small-Molecule Inhibitor of Botulinum Neurotoxin Serotype A Endopeptidase Developed by Synthesis-Based Computer-Aided Molecular Design

DTIC Science & Technology

2009-11-01

dynamics of the complex predicted by multiple molecular dynamics simulations , and discuss further structural optimization to achieve better in vivo efficacy...complex with BoNTAe and the dynamics of the complex predicted by multiple molecular dynamics simulations (MMDSs). On the basis of the 3D model, we discuss...is unlimited whereas AHP exhibited 54% inhibition under the same conditions (Table 1). Computer Simulation Twenty different molecular dynamics

Moral motivation based on multiple developmental structures: an exploration of cognitive and emotional dynamics.

PubMed

Kaplan, Ulas; Tivnan, Terrence

2014-01-01

Intrapersonal variability and multiplicity in the complexity of moral motivation were examined from Dynamic Systems and Self-Determination Theory perspectives. L. Kohlberg's (1969) stages of moral development are reconceptualized as soft-assembled and dynamically transformable process structures of motivation that may operate simultaneously within person in different degrees. Moral motivation is conceptualized as the real-time process of self-organization of cognitive and emotional dynamics out of which moral judgment and action emerge. A detailed inquiry into intrapersonal variation in moral motivation is carried out based on the differential operation of multiple motivational structures. A total of 74 high school students and 97 college students participated in the study by completing a new questionnaire, involving 3 different hypothetical moral judgments. As hypothesized, findings revealed significant multiplicity in the within-person operation of developmental stage structures, and intrapersonal variability in the degrees to which stages were used. Developmental patterns were found in terms of different distributions of multiple stages between high school and college samples, as well as the association between age and overall motivation scores. Differential relations of specific emotions to moral motivation revealed and confirmed the value of differentiating multiple emotions. Implications of the present theoretical perspective and the findings for understanding the complexity of moral judgment and motivation are discussed.

Tracking single particle rotation: Probing dynamics in four dimensions

DOE PAGES

Anthony, Stephen Michael; Yu, Yan

2015-04-29

Direct visualization and tracking of small particles at high spatial and temporal resolution provides a powerful approach to probing complex dynamics and interactions in chemical and biological processes. Analysis of the rotational dynamics of particles adds a new dimension of information that is otherwise impossible to obtain with conventional 3-D particle tracking. In this review, we survey recent advances in single-particle rotational tracking, with highlights on the rotational tracking of optically anisotropic Janus particles. Furthermore, strengths and weaknesses of the various particle tracking methods, and their applications are discussed.

Dshell++: A Component Based, Reusable Space System Simulation Framework

NASA Technical Reports Server (NTRS)

Lim, Christopher S.; Jain, Abhinandan

2009-01-01

This paper describes the multi-mission Dshell++ simulation framework for high fidelity, physics-based simulation of spacecraft, robotic manipulation and mobility systems. Dshell++ is a C++/Python library which uses modern script driven object-oriented techniques to allow component reuse and a dynamic run-time interface for complex, high-fidelity simulation of spacecraft and robotic systems. The goal of the Dshell++ architecture is to manage the inherent complexity of physicsbased simulations while supporting component model reuse across missions. The framework provides several features that support a large degree of simulation configurability and usability.

Methylation-regulated decommissioning of multimeric PP2A complexes

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

Wu, Cheng-Guo; Zheng, Aiping; Jiang, Li

2017-12-01

Dynamic assembly/disassembly of signaling complexes are crucial for cellular functions. Specialized latency and activation chaperones control the biogenesis of protein phosphatase 2A (PP2A) holoenzymes that contain a common scaffold and catalytic subunits and a variable regulatory subunit. Here we show that the butterfly-shaped TIPRL (TOR signaling pathway regulator) makes highly integrative multibranching contacts with the PP2A catalytic subunit, selective for the unmethylated tail and perturbing/inactivating the phosphatase active site. TIPRL also makes unusual wobble contacts with the scaffold subunit, allowing TIPRL, but not the overlapping regulatory subunits, to tolerate disease-associated PP2A mutations, resulting in reduced holoenzyme assembly and enhanced inactivationmore » of mutant PP2A. Strikingly, TIPRL and the latency chaperone, α4, coordinate to disassemble active holoenzymes into latent PP2A, strictly controlled by methylation. Our study reveals a mechanism for methylation-responsive inactivation and holoenzyme disassembly, illustrating the complexity of regulation/signaling, dynamic complex disassembly, and disease mutations in cancer and intellectual disability.« less

“Agility” - Complexity Description in a New Dimension applied for Laser Cutting

NASA Astrophysics Data System (ADS)

Bartels, F.; Suess, B.; Wagner, A.; Hauptmann, J.; Wetzig, A.; Beyer, E.

How to describe or to compare the complexity of industrial upcoming part geometries in laser-cutting? This question is essential for defining machine dynamics or kinematic structures for efficient use of the technological cutting-potential which is given by modern beam sources. Solid-state lasers as well as CO2 lasers offer, especially in thin materials, the opportunity of high cutting velocities. Considering the mean velocity on cutting geometries, it is significantly below the technological limitations. The characterization of cutting geometries by means of the agility as well as the application for laser-cutting will be introduced. The identification of efficient dynamic constellations will be shown as basic principle for designing future machine structures.

Proteolytic turnover of the Gal4 transcription factor is not required for function in vivo.

PubMed

Nalley, Kip; Johnston, Stephen Albert; Kodadek, Thomas

2006-08-31

Transactivator-promoter complexes are essential intermediates in the activation of eukaryotic gene expression. Recent studies of these complexes have shown that some are quite dynamic in living cells owing to rapid and reversible disruption of activator-promoter complexes by molecular chaperones, or a slower, ubiquitin-proteasome-pathway-mediated turnover of DNA-bound activator. These mechanisms may act to ensure continued responsiveness of activators to signalling cascades by limiting the lifetime of the active protein-DNA complex. Furthermore, the potency of some activators is compromised by proteasome inhibition, leading to the suggestion that periodic clearance of activators from a promoter is essential for high-level expression. Here we describe a variant of the chromatin immunoprecipitation assay that has allowed direct observation of the kinetic stability of native Gal4-promoter complexes in yeast. Under non-inducing conditions, the complex is dynamic, but on induction the Gal4-promoter complexes 'lock in' and exhibit long half-lives. Inhibition of proteasome-mediated proteolysis had little or no effect on Gal4-mediated gene expression. These studies, combined with earlier data, show that the lifetimes of different transactivator-promoter complexes in vivo can vary widely and that proteasome-mediated turnover is not a general requirement for transactivator function.

Changes in conformational dynamics of basic side chains upon protein–DNA association

PubMed Central

Esadze, Alexandre; Chen, Chuanying; Zandarashvili, Levani; Roy, Sourav; Pettitt, B. Montgometry; Iwahara, Junji

2016-01-01

Basic side chains play major roles in recognition of nucleic acids by proteins. However, dynamic properties of these positively charged side chains are not well understood. In this work, we studied changes in conformational dynamics of basic side chains upon protein–DNA association for the zinc-finger protein Egr-1. By nuclear magnetic resonance (NMR) spectroscopy, we characterized the dynamics of all side-chain cationic groups in the free protein and in the complex with target DNA. Our NMR order parameters indicate that the arginine guanidino groups interacting with DNA bases are strongly immobilized, forming rigid interfaces. Despite the strong short-range electrostatic interactions, the majority of the basic side chains interacting with the DNA phosphates exhibited high mobility, forming dynamic interfaces. In particular, the lysine side-chain amino groups exhibited only small changes in the order parameters upon DNA-binding. We found a similar trend in the molecular dynamics (MD) simulations for the free Egr-1 and the Egr-1–DNA complex. Using the MD trajectories, we also analyzed side-chain conformational entropy. The interfacial arginine side chains exhibited substantial entropic loss upon binding to DNA, whereas the interfacial lysine side chains showed relatively small changes in conformational entropy. These data illustrate different dynamic characteristics of the interfacial arginine and lysine side chains. PMID:27288446

An Application of Attachment Theory: Mentoring Relationship Dynamics and Ethical Concerns

ERIC Educational Resources Information Center

Gormley, Barbara

2008-01-01

In this theoretical paper, mentoring relationships are conceptualized as close relationships that occur along a spectrum from highly functional to highly dysfunctional, with most occurring in between. A complex set of factors describe the functioning level of mentoring relationships: (a) the attachment styles of the mentors and mentees; (b)…

Development of bimolecular fluorescence complementation using rsEGFP2 for detection and super-resolution imaging of protein-protein interactions in live cells

PubMed Central

Wang, Sheng; Ding, Miao; Chen, Xuanze; Chang, Lei; Sun, Yujie

2017-01-01

Direct visualization of protein-protein interactions (PPIs) at high spatial and temporal resolution in live cells is crucial for understanding the intricate and dynamic behaviors of signaling protein complexes. Recently, bimolecular fluorescence complementation (BiFC) assays have been combined with super-resolution imaging techniques including PALM and SOFI to visualize PPIs at the nanometer spatial resolution. RESOLFT nanoscopy has been proven as a powerful live-cell super-resolution imaging technique. With regard to the detection and visualization of PPIs in live cells with high temporal and spatial resolution, here we developed a BiFC assay using split rsEGFP2, a highly photostable and reversibly photoswitchable fluorescent protein previously developed for RESOLFT nanoscopy. Combined with parallelized RESOLFT microscopy, we demonstrated the high spatiotemporal resolving capability of a rsEGFP2-based BiFC assay by detecting and visualizing specifically the heterodimerization interactions between Bcl-xL and Bak as well as the dynamics of the complex on mitochondria membrane in live cells. PMID:28663931

Dynamic perfusion assessment during perforator flap surgery: an up-to-date

PubMed Central

MUNTEAN, MAXIMILIAN VLAD; MUNTEAN, VALENTIN; ARDELEAN, FILIP; GEORGESCU, ALEXANDRU

2015-01-01

Flap monitoring technology has progressed alongside flap design. The highly variable vascular anatomy and the complexity associated with modern perforator flaps demands dynamic, real-time, intraoperative information about the vessel location, perfusion patterns and flap physiology. Although most surgeons still assess flap perfusion and viability based solely on clinical experience, studies have shown that results may be highly variable and often misleading. Poor judgment of intraoperative perfusion leads to major complications. Employing dynamic perfusion imaging during flap reconstruction has led to a reduced complication rate, lower morbidity, shorter hospital stay, and an overall better result. With the emergence of multiple systems capable of intraoperative flap evaluation, the purpose of this article is to review the two systems that have been widely accepted and are currently used by plastic surgeons: Indocyanine green angiography (ICGA) and dynamic infrared thermography (DIRT). PMID:26609259

Controlling toughness and dynamics of polymer networks via mussel-inspired dynamical bonds

NASA Astrophysics Data System (ADS)

Filippidi, Emmanouela

For dry, thermoset, polymer systems increasing the degree of cross-linking increases the elastic modulus. However, it simultaneously compromises the elongation under tension, usually reducing the overall total energy dissipated before fracture (toughness). Dynamic reformable bonds and complex network topologies have been used to circumnavigate this issue with moderate success, mainly in hydrated network systems. Hydration, however, which swells these networks limits how far one could increase the modulus, while their chemistry prevents improvement of the mechanics upon drying. Employing the mussel byssus-inspired strategy of iron-catechol coordination bonds, we have synthesized and studied epoxy networks comprising covalently attached catechol moieties capable of forming additional iron-catechol complex cross-links that still function in dry conditions. In such a fashion, we create a high modulus, high elongation, high toughness material. The iron-catechol coordination bonds play multiple roles that enhance the mechanical performance of the system: at low strain and fast strain rates, they act like permanent cross-links with bonding strength similar to covalent bonds, but start disassociating at high elongation. They are also reformable, enabling material self-healing in a matter of minutes in the absence of load. Finally, the dissociative crosslink cleavage alters the local chain topology, creating length scales that unfold upon elongation. The elegance of this system lies on its general versatility. Both the polymer and metal ion can be used as control parameters to study the interplay of covalent and dynamical bonds as well as explore the limits of the design of elastomers with enhanced toughness. MRSEC of NSF Award No. DMR-1121053.

All-atom molecular dynamics simulation of a photosystem I/detergent complex

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

Harris, Bradley J.; Cheng, Xiaolin; Frymier, Paul

2014-09-18

All-atom molecular dynamics (MD) simulation was used to investigate the solution structure and dynamics of the photosynthetic pigment protein complex photosystem I (PSI) from Thermosynechococcus elongatus embedded in a toroidal belt of n-dodecyl-β-d-maltoside (DDM) detergent. Evaluation of root-mean-square deviations (RMSDs) relative to the known crystal structure show that the protein complex surrounded by DDM molecules is stable during the 200 ns simulation time, and root-mean-square fluctuation (RMSF) analysis indicates that regions of high local mobility correspond to solvent-exposed regions such as turns in the transmembrane α-helices and flexible loops on the stromal and lumenal faces. Comparing the protein detergent complexmore » to a pure detergent micelle, the detergent surrounding the PSI trimer is found to be less densely packed but with more ordered detergent tails, contrary to what is seen in most lipid bilayer models. We also investigated any functional implications for the observed conformational dynamics and protein detergent interactions, discovering interesting structural changes in the psaL subunits associated with maintaining the trimeric structure of the protein. Moreover, we find that the docking of soluble electron mediators such as cytochrome c 6 and ferredoxin to PSI is not significantly impacted by the solubilization of PSI in detergent.« less

Modelling of high-frequency structure-borne sound transmission on FEM grids using the Discrete Flow Mapping technique

NASA Astrophysics Data System (ADS)

Hartmann, Timo; Tanner, Gregor; Xie, Gang; Chappell, David; Bajars, Janis

2016-09-01

Dynamical Energy Analysis (DEA) combined with the Discrete Flow Mapping technique (DFM) has recently been introduced as a mesh-based high frequency method modelling structure borne sound for complex built-up structures. This has proven to enhance vibro-acoustic simulations considerably by making it possible to work directly on existing finite element meshes circumventing time-consuming and costly re-modelling strategies. In addition, DFM provides detailed spatial information about the vibrational energy distribution within a complex structure in the mid-to-high frequency range. We will present here progress in the development of the DEA method towards handling complex FEM-meshes including Rigid Body Elements. In addition, structure borne transmission paths due to spot welds are considered. We will present applications for a car floor structure.

Dynamics of aesthetic appreciation

NASA Astrophysics Data System (ADS)

Carbon, Claus-Christian

2012-03-01

Aesthetic appreciation is a complex cognitive processing with inherent aspects of cold as well as hot cognition. Research from the last decades of empirical has shown that evaluations of aesthetic appreciation are highly reliable. Most frequently, facial attractiveness was used as the corner case for investigating aesthetic appreciation. Evaluating facial attractiveness shows indeed high internal consistencies and impressively high inter-rater reliabilities, even across cultures. Although this indicates general and stable mechanisms underlying aesthetic appreciation, it is also obvious that our taste for specific objects changes dynamically. Aesthetic appreciation on artificial object categories, such as fashion, design or art is inherently very dynamic. Gaining insights into the cognitive mechanisms that trigger and enable corresponding changes of aesthetic appreciation is of particular interest for research as this will provide possibilities to modeling aesthetic appreciation for longer durations and from a dynamic perspective. The present paper refers to a recent two-step model ("the dynamical two-step-model of aesthetic appreciation"), dynamically adapting itself, which accounts for typical dynamics of aesthetic appreciation found in different research areas such as art history, philosophy and psychology. The first step assumes singular creative sources creating and establishing innovative material towards which, in a second step, people adapt by integrating it into their visual habits. This inherently leads to dynamic changes of the beholders' aesthetic appreciation.

Noise focusing and the emergence of coherent activity in neuronal cultures

NASA Astrophysics Data System (ADS)

Orlandi, Javier G.; Soriano, Jordi; Alvarez-Lacalle, Enrique; Teller, Sara; Casademunt, Jaume

2013-09-01

At early stages of development, neuronal cultures in vitro spontaneously reach a coherent state of collective firing in a pattern of nearly periodic global bursts. Although understanding the spontaneous activity of neuronal networks is of chief importance in neuroscience, the origin and nature of that pulsation has remained elusive. By combining high-resolution calcium imaging with modelling in silico, we show that this behaviour is controlled by the propagation of waves that nucleate randomly in a set of points that is specific to each culture and is selected by a non-trivial interplay between dynamics and topology. The phenomenon is explained by the noise focusing effect--a strong spatio-temporal localization of the noise dynamics that originates in the complex structure of avalanches of spontaneous activity. Results are relevant to neuronal tissues and to complex networks with integrate-and-fire dynamics and metric correlations, for instance, in rumour spreading on social networks.

Complex social contagion makes networks more vulnerable to disease outbreaks.

PubMed

Campbell, Ellsworth; Salathé, Marcel

2013-01-01

Social network analysis is now widely used to investigate the dynamics of infectious disease spread. Vaccination dramatically disrupts disease transmission on a contact network, and indeed, high vaccination rates can potentially halt disease transmission altogether. Here, we build on mounting evidence that health behaviors - such as vaccination, and refusal thereof - can spread across social networks through a process of complex contagion that requires social reinforcement. Using network simulations that model health behavior and infectious disease spread, we find that under otherwise identical conditions, the process by which the health behavior spreads has a very strong effect on disease outbreak dynamics. This dynamic variability results from differences in the topology within susceptible communities that arise during the health behavior spreading process, which in turn depends on the topology of the overall social network. Our findings point to the importance of health behavior spread in predicting and controlling disease outbreaks.

A Complex Endomembrane System in the Archaeon Ignicoccus hospitalis Tapped by Nanoarchaeum equitans

DOE PAGES

Heimerl, Thomas; Flechsler, Jennifer; Pickl, Carolin; ...

2017-06-13

Based on serial sectioning, focused ion beam scanning electron microscopy (FIB/SEM), and electron tomography, we depict in detail the highly unusual anatomy of the marine hyperthermophilic crenarchaeon, Ignicoccus hospitalis. Our data support a complex and dynamic endomembrane system consisting of cytoplasmic protrusions, and with secretory function. Moreover, we reveal that the cytoplasm of the putative archaeal ectoparasite Nanoarchaeum equitans can get in direct contact with this endomembrane system, complementing and explaining recent proteomic, transcriptomic and metabolomic data on this inter-archaeal relationship. In addition, we identified a matrix of filamentous structures and/or tethers in the voluminous inter-membrane compartment (IMC) of I.more » hospitalis, which might be responsible for membrane dynamics. Overall, this unusual cellular compartmentalization, ultrastructure and dynamics in an archaeon that belongs to the recently proposed TACK superphylum prompts speculation that the eukaryotic endomembrane system might originate from Archaea.« less

Applying Structural Systems Thinking to Frame Perspectives on Social Work Innovation.

PubMed

Stringfellow, Erin J

2017-03-01

Innovation will be key to the success of the Grand Challenges Initiative in social work. A structural systems framework based in system dynamics could be useful for considering how to advance innovation. Diagrams using system dynamics conventions were developed to link common themes across concept papers written by social work faculty members and graduate students ( N = 19). Transdisciplinary teams and ethical partnerships with communities and practitioners will be needed to responsibly develop high-quality innovative solutions. A useful next step would be to clarify to what extent factors that could "make or break" these partnerships arise from within versus outside of the field of social work and how this has changed over time. Advancing innovation in social work will mean making decisions in a complex, ever-changing system. Principles and tools from methods that account for complexity, such as system dynamics, can help improve this decision-making process.

Applying Structural Systems Thinking to Frame Perspectives on Social Work Innovation

PubMed Central

Stringfellow, Erin J.

2017-01-01

Objective Innovation will be key to the success of the Grand Challenges Initiative in social work. A structural systems framework based in system dynamics could be useful for considering how to advance innovation. Method Diagrams using system dynamics conventions were developed to link common themes across concept papers written by social work faculty members and graduate students (N = 19). Results Transdisciplinary teams and ethical partnerships with communities and practitioners will be needed to responsibly develop high-quality innovative solutions. A useful next step would be to clarify to what extent factors that could “make or break” these partnerships arise from within versus outside of the field of social work and how this has changed over time. Conclusions Advancing innovation in social work will mean making decisions in a complex, ever-changing system. Principles and tools from methods that account for complexity, such as system dynamics, can help improve this decision-making process. PMID:28298877

Self-Organized Dynamic Flocking Behavior from a Simple Deterministic Map

NASA Astrophysics Data System (ADS)

Krueger, Wesley

2007-10-01

Coherent motion exhibiting large-scale order, such as flocking, swarming, and schooling behavior in animals, can arise from simple rules applied to an initial random array of self-driven particles. We present a completely deterministic dynamic map that exhibits emergent, collective, complex motion for a group of particles. Each individual particle is driven with a constant speed in two dimensions adopting the average direction of a fixed set of non-spatially related partners. In addition, the particle changes direction by π as it reaches a circular boundary. The dynamical patterns arising from these rules range from simple circular-type convective motion to highly sophisticated, complex, collective behavior which can be easily interpreted as flocking, schooling, or swarming depending on the chosen parameters. We present the results as a series of short movies and we also explore possible order parameters and correlation functions capable of quantifying the resulting coherence.

T-cell epitope prediction and immune complex simulation using molecular dynamics: state of the art and persisting challenges

PubMed Central

2010-01-01

Atomistic Molecular Dynamics provides powerful and flexible tools for the prediction and analysis of molecular and macromolecular systems. Specifically, it provides a means by which we can measure theoretically that which cannot be measured experimentally: the dynamic time-evolution of complex systems comprising atoms and molecules. It is particularly suitable for the simulation and analysis of the otherwise inaccessible details of MHC-peptide interaction and, on a larger scale, the simulation of the immune synapse. Progress has been relatively tentative yet the emergence of truly high-performance computing and the development of coarse-grained simulation now offers us the hope of accurately predicting thermodynamic parameters and of simulating not merely a handful of proteins but larger, longer simulations comprising thousands of protein molecules and the cellular scale structures they form. We exemplify this within the context of immunoinformatics. PMID:21067546

Effects of littoral habitat complexity and sunfish composition on fish production

USGS Publications Warehouse

Carey, Michael P.; Maloney, K.O.; Chipps, S.R.; Wahl, David H.

2010-01-01

Habitat complexity is a key driver of food web dynamics because physical structure dictates resource availability to a community. Changes in fish diversity can also alter trophic interactions and energy pathways in food webs. Few studies have examined the direct, indirect, and interactive effects of biodiversity and habitat complexity on fish production. We explored the effects of habitat complexity (simulated vegetation), sunfish diversity (intra‐ vs. inter‐specific sunfish), and their interaction using a mesocosm experiment. Total fish production was examined across two levels of habitat complexity (low: 161 strands m−2 and high: 714 strands m−2) and two sunfish diversity treatments: bluegill only (Lepomis macrochirus) and bluegill, redear sunfish (Lepomis microlophus), and green sunfish (Lepomis cyanellus) combination. We also measured changes in total phosphorus, phytoplankton, periphyton, and invertebrates to explain patterns in fish production. Bluegill and total fish production were unaffected by the sunfish treatments. Habitat complexity had a large influence on food web structure by shifting primary productivity from pelagic to a more littoral pathway in the high habitat treatments. Periphyton was higher with dense vegetation, leading to reductions in total phosphorus, phytoplankton, cladoceran abundance and fish biomass. In tanks with low vegetation, bluegill exhibited increased growth. Habitat complexity can alter energy flow through food webs ultimately influencing higher trophic levels. The lack of an effect of sunfish diversity on fish production does not imply that conserving biodiversity is unimportant; rather, we suggest that understanding the context in which biodiversity is important to food web dynamics is critical to conservation planning

Is a Universal Science of Complexity Conceivable?

NASA Astrophysics Data System (ADS)

West, Geoffrey B.

Over the past quarter of a century, terms like complex adaptive system, the science of complexity, emergent behavior, self-organization, and adaptive dynamics have entered the literature, reflecting the rapid growth in collaborative, trans-disciplinary research on fundamental problems in complex systems ranging across the entire spectrum of science from the origin and dynamics of organisms and ecosystems to financial markets, corporate dynamics, urbanization and the human brain...

Automated assessment of blood flow in developing embryonic hearts by extending dynamic range of Doppler OCT using a MHz FDML swept laser source (Conference Presentation)

NASA Astrophysics Data System (ADS)

Elahi, Sahar; Thrane, Lars; Rollins, Andrew M.; Jenkins, Michael W.

2017-02-01

Altered hemodynamics in developing embryonic hearts lead to congenital heart diseases, motivating close monitoring of blood flow over several stages of development. Doppler OCT can assess blood flow in tubular hearts, but the maximum velocity increases drastically during the period of cardiac cushion (valve precursors) formation. Therefore, the limited dynamic range of Doppler OCT velocity measurement makes it difficult to conduct longitudinal studies without phase wrapping at high velocities or loss of sensitivity to slow velocities. We have built a high-speed OCT system using an FDML laser (Optores GmbH, Germany) at a sweep rate of 1.68 MHz (axial resolution - 12 μm, sensitivity - 105 dB, phase stability - 17 mrad). The speed of this OCT system allows us to acquire high-density B-scans to obtain an extended velocity dynamic range without sacrificing the frame rate. The extended dynamic range within a frame is achieved by varying the A-scan interval at which the phase difference is found, enabling detection of velocities ranging from tens of microns per second to hundreds of mm per second. The extra lines in a frame can also be utilized to improve the structural and Doppler images via complex averaging. In structural images where presence of blood causes additional scattering, complex averaging helps retrieve features located deeper in the tissue. Moreover, high-density frames can be registered to 4D volumes to determine the orthogonal direction of flow and calculate shear stress. In conclusion, our high-speed OCT system will enable automated Doppler imaging of embryonic hearts in cohort studies.

Vibrational dynamics of thiocyanate and selenocyanate bound to horse heart myoglobin

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

Maj, Michał; Oh, Younjun; Park, Kwanghee

2014-06-21

The structure and vibrational dynamics of SCN- and SeCN-bound myoglobin have been investigated using polarization-controlled IR pump-probe measurements and quantum chemistry calculations. The complexes are found to be in low and high spin states, with the dominant contribution from the latter. In addition, the Mb:SCN high spin complex exhibits a doublet feature in the thiocyanate stretch IR absorption spectra, indicating two distinct molecular conformations around the heme pocket. The binding mode of the high spin complexes was assigned to occur through the nitrogen atom, contrary to the binding through the sulfur atom that was observed in myoglobin derived from Aplysiamore » Limacina. The vibrational energy relaxation process has been found to occur substantially faster than those of free SCN{sup −} and SeCN{sup −} ions and neutral SCN- and SeCN-derivatized molecules reported previously. This supports the N-bound configurations of MbNCS and MbNCSe, because S- and Se-bound configurations are expected to have significantly long lifetimes due to the insulation effect by heavy bridge atom like S and Se in such IR probes. Nonetheless, even though their lifetimes are much shorter than those of corresponding free ions in water, the vibrational lifetimes determined for MbNCS and MbNCSe are still fairly long compared to those of azide and cyanide myoglobin systems studied before. Thus, thiocyanate and selenocyanate can be good local probes of local electrostatic environment in the heme pocket. The globin dependence on binding mode and vibrational dynamics is also discussed.« less

Molecular dynamics simulation of shock wave and spallation phenomena in metal foils irradiated by femtosecond laser pulse

NASA Astrophysics Data System (ADS)

Zhakhovsky, Vasily; Demaske, Brian; Inogamov, Nail; Oleynik, Ivan

2010-03-01

Femtosecond laser irradiation of metals is an effective technique to create a high-pressure frontal layer of 100-200 nm thickness. The associated ablation and spallation phenomena can be studied in the laser pump-probe experiments. We present results of a large-scale MD simulation of ablation and spallation dynamics developing in 1,2,3μm thick Al and Au foils irradiated by a femtosecond laser pulse. Atomic-scale mechanisms of laser energy deposition, transition from pressure wave to shock, reflection of the shock from the rear-side of the foil, and the nucleation of cracks in the reflected tensile wave, having a very high strain rate, were all studied. To achieve a realistic description of the complex phenomena induced by strong compression and rarefaction waves, we developed new embedded atom potentials for Al and Au based on cold pressure curves. MD simulations revealed the complex interplay between spallation and ablation processes: dynamics of spallation depends on the pressure profile formed in the ablated zone at the early stage of laser energy absorption. It is shown that the essential information such as material properties at high strain rate and spall strength can be extracted from the simulated rear-side surface velocity as a function of time.

Experiments and Analyses of Data Transfers Over Wide-Area Dedicated Connections

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

Rao, Nageswara S.; Liu, Qiang; Sen, Satyabrata

Dedicated wide-area network connections are increasingly employed in high-performance computing and big data scenarios. One might expect the performance and dynamics of data transfers over such connections to be easy to analyze due to the lack of competing traffic. However, non-linear transport dynamics and end-system complexities (e.g., multi-core hosts and distributed filesystems) can in fact make analysis surprisingly challenging. We present extensive measurements of memory-to-memory and disk-to-disk file transfers over 10 Gbps physical and emulated connections with 0–366 ms round trip times (RTTs). For memory-to-memory transfers, profiles of both TCP and UDT throughput as a function of RTT show concavemore » and convex regions; large buffer sizes and more parallel flows lead to wider concave regions, which are highly desirable. TCP and UDT both also display complex throughput dynamics, as indicated by their Poincare maps and Lyapunov exponents. For disk-to-disk transfers, we determine that high throughput can be achieved via a combination of parallel I/O threads, parallel network threads, and direct I/O mode. Our measurements also show that Lustre filesystems can be mounted over long-haul connections using LNet routers, although challenges remain in jointly optimizing file I/O and transport method parameters to achieve peak throughput.« less

Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model

NASA Astrophysics Data System (ADS)

Palacz, A. P.; St. John, M. A.; Brewin, R. J. W.; Hirata, T.; Gregg, W. W.

2013-11-01

Modeling and monitoring plankton functional types (PFTs) is challenged by the insufficient amount of field measurements of ground truths in both plankton models and bio-optical algorithms. In this study, we combine remote sensing data and a dynamic plankton model to simulate an ecologically sound spatial and temporal distribution of phyto-PFTs. We apply an innovative ecological indicator approach to modeling PFTs and focus on resolving the question of diatom-coccolithophore coexistence in the subpolar high-nitrate and low-chlorophyll regions. We choose an artificial neural network as our modeling framework because it has the potential to interpret complex nonlinear interactions governing complex adaptive systems, of which marine ecosystems are a prime example. Using ecological indicators that fulfill the criteria of measurability, sensitivity and specificity, we demonstrate that our diagnostic model correctly interprets some basic ecological rules similar to ones emerging from dynamic models. Our time series highlight a dynamic phyto-PFT community composition in all high-latitude areas and indicate seasonal coexistence of diatoms and coccolithophores. This observation, though consistent with in situ and remote sensing measurements, has so far not been captured by state-of-the-art dynamic models, which struggle to resolve this "paradox of the plankton". We conclude that an ecological indicator approach is useful for ecological modeling of phytoplankton and potentially higher trophic levels. Finally, we speculate that it could serve as a powerful tool in advancing ecosystem-based management of marine resources.

Distribution of phytoplankton functional types in high-nitrate low-chlorophyll waters in a new diagnostic ecological indicator model

NASA Astrophysics Data System (ADS)

Palacz, A. P.; St. John, M. A.; Brewin, R. J. W.; Hirata, T.; Gregg, W. W.

2013-05-01

Modeling and monitoring plankton functional types (PFTs) is challenged by insufficient amount of field measurements to ground-truth both plankton models and bio-optical algorithms. In this study, we combine remote sensing data and a dynamic plankton model to simulate an ecologically-sound spatial and temporal distribution of phyto-PFTs. We apply an innovative ecological indicator approach to modeling PFTs, and focus on resolving the question of diatom-coccolithophore co-existence in the subpolar high-nitrate and low-chlorophyll regions. We choose an artificial neural network as our modeling framework because it has the potential to interpret complex nonlinear interactions governing complex adaptive systems, of which marine ecosystems are a prime example. Using ecological indicators that fulfill the criteria of measurability, sensitivity and specificity, we demonstrate that our diagnostic model correctly interprets some basic ecological rules similar to ones emerging from dynamic models. Our time series highlight a dynamic phyto-PFT community composition in all high latitude areas, and indicate seasonal co-existence of diatoms and coccolithophores. This observation, though consistent with in situ and remote sensing measurements, was so far not captured by state-of-the-art dynamic models which struggle to resolve this "paradox of the plankton". We conclude that an ecological indicator approach is useful for ecological modeling of phytoplankton and potentially higher trophic levels. Finally, we speculate that it could serve as a powerful tool in advancing ecosystem-based management of marine resources.

Islands of spatially discordant APD alternans underlie arrhythmogenesis by promoting electrotonic dyssynchrony in models of fibrotic rat ventricular myocardium

NASA Astrophysics Data System (ADS)

Majumder, Rupamanjari; Engels, Marc C.; de Vries, Antoine A. F.; Panfilov, Alexander V.; Pijnappels, Daniël A.

2016-04-01

Fibrosis and altered gap junctional coupling are key features of ventricular remodelling and are associated with abnormal electrical impulse generation and propagation. Such abnormalities predispose to reentrant electrical activity in the heart. In the absence of tissue heterogeneity, high-frequency impulse generation can also induce dynamic electrical instabilities leading to reentrant arrhythmias. However, because of the complexity and stochastic nature of such arrhythmias, the combined effects of tissue heterogeneity and dynamical instabilities in these arrhythmias have not been explored in detail. Here, arrhythmogenesis was studied using in vitro and in silico monolayer models of neonatal rat ventricular tissue with 30% randomly distributed cardiac myofibroblasts and systematically lowered intercellular coupling achieved in vitro through graded knockdown of connexin43 expression. Arrhythmia incidence and complexity increased with decreasing intercellular coupling efficiency. This coincided with the onset of a specialized type of spatially discordant action potential duration alternans characterized by island-like areas of opposite alternans phase, which positively correlated with the degree of connexinx43 knockdown and arrhythmia complexity. At higher myofibroblast densities, more of these islands were formed and reentrant arrhythmias were more easily induced. This is the first study exploring the combinatorial effects of myocardial fibrosis and dynamic electrical instabilities on reentrant arrhythmia initiation and complexity.

3D fault curvature and fractal roughness: Insights for rupture dynamics and ground motions using a Discontinous Galerkin method

NASA Astrophysics Data System (ADS)

Ulrich, Thomas; Gabriel, Alice-Agnes

2017-04-01

Natural fault geometries are subject to a large degree of uncertainty. Their geometrical structure is not directly observable and may only be inferred from surface traces, or geophysical measurements. Most studies aiming at assessing the potential seismic hazard of natural faults rely on idealised shaped models, based on observable large-scale features. Yet, real faults are wavy at all scales, their geometric features presenting similar statistical properties from the micro to the regional scale. Dynamic rupture simulations aim to capture the observed complexity of earthquake sources and ground-motions. From a numerical point of view, incorporating rough faults in such simulations is challenging - it requires optimised codes able to run efficiently on high-performance computers and simultaneously handle complex geometries. Physics-based rupture dynamics hosted by rough faults appear to be much closer to source models inverted from observation in terms of complexity. Moreover, the simulated ground-motions present many similarities with observed ground-motions records. Thus, such simulations may foster our understanding of earthquake source processes, and help deriving more accurate seismic hazard estimates. In this presentation, the software package SeisSol (www.seissol.org), based on an ADER-Discontinuous Galerkin scheme, is used to solve the spontaneous dynamic earthquake rupture problem. The usage of tetrahedral unstructured meshes naturally allows for complicated fault geometries. However, SeisSol's high-order discretisation in time and space is not particularly suited for small-scale fault roughness. We will demonstrate modelling conditions under which SeisSol resolves rupture dynamics on rough faults accurately. The strong impact of the geometric gradient of the fault surface on the rupture process is then shown in 3D simulations. Following, the benefits of explicitly modelling fault curvature and roughness, in distinction to prescribing heterogeneous initial stress conditions on a planar fault, is demonstrated. Furthermore, we show that rupture extend, rupture front coherency and rupture speed are highly dependent on the initial amplitude of stress acting on the fault, defined by the normalized prestress factor R, the ratio of the potential stress drop over the breakdown stress drop. The effects of fault complexity are particularly pronounced for lower R. By low-pass filtering a rough fault at several cut-off wavelengths, we then try to capture rupture complexity using a simplified fault geometry. We find that equivalent source dynamics can only be obtained using a scarcely filtered fault associated with a reduced stress level. To investigate the wavelength-dependent roughness effect, the fault geometry is bandpass-filtered over several spectral ranges. We show that geometric fluctuations cause rupture velocity fluctuations of similar length scale. The impact of fault geometry is especially pronounced when the rupture front velocity is near supershear. Roughness fluctuations significantly smaller than the rupture front characteristic dimension (cohesive zone size) affect only macroscopic rupture properties, thus, posing a minimum length scale limiting the required resolution of 3D fault complexity. Lastly, the effect of fault curvature and roughness on the simulated ground-motions is assessed. Despite employing a simple linear slip weakening friction law, the simulated ground-motions compare well with estimates from ground motions prediction equations, even at relatively high frequencies.

Mixing Silicate Melts with High Viscosity Contrast by Chaotic Dynamics: Results from a New Experimental Device

NASA Astrophysics Data System (ADS)

de Campos, Cristina; Perugini, Diego; Ertel-Ingrisch, Werner; Dingwell, Donald B.; Poli, Giampiero

2010-05-01

A new experimental device has been developed to perform chaotic mixing between high viscosity melts under controlled fluid-dynamic conditions. The apparatus is based on the Journal Bearing System (JBS). It consists of an outer cylinder hosting the melts of interest and an inner cylinder, which is eccentrically located. Both cylinders can be independently moved to generate chaotic streamlines in the mixing system. Two experiments were performed using as end-members different proportions of a peralkaline haplogranite and a mafic melt, corresponding to the 1 atm eutectic composition in the An-Di binary system. The two melts were stirred together in the JBS for ca. two hours, at 1,400° C and under laminar fluid dynamic condition (Re of the order of 10-7). The viscosity ratio between the two melts, at the beginning of the experiment, was of the order of 103. Optical analyses of experimental samples revealed, at short length scale (of the order of μm), a complex pattern of mixed structures. These consisted of an intimate distribution of filaments; a complex inter-fingering of the two melts. Such features are typically observed in rocks thought to be produced by magma mixing processes. Stretching and folding dynamics between the melts induced chaotic flow fields and generated wide compositional interfaces. In this way, chemical diffusion processes become more efficient, producing melts with highly heterogeneous compositions. A remarkable modulation of compositional fields has been obtained by performing short time-scale experiments and using melts with a high viscosity ratio. This indicates that chaotic mixing of magmas can be a very efficient process in modulating compositional variability in igneous systems, especially under high viscosity ratios and laminar fluid-dynamic regimes. Our experimental device may replicate magma mixing features, observed in natural rocks, and therefore open new frontiers in the study of this important petrologic and volcanological process.

[Evaluation of the clinical efficacy of a new composition of tizol with triamcinolon in complex treatment of patients with erosive ulcerous form of lichen planus of the oral mucosa].

PubMed

Ron', G I; Akmalova, G M; Emel'yanova, I V

2015-01-01

The most significant of the primary stages of complex therapy of oral lichen planus (OLP), among causal and pathogenetic therapy is a local conservative treatment. The aim of the study was to evaluate the clinical efficacy of the local use of the new compositions TIZOL with triamcinolon in complex therapy of erosive-ulcerous forms OLP oral mucosa. The study was performed with 47 patients with lichen planus in age from 24 to 70 years with erosive-ulcerous form OLP whose diagnosis was confirmed histologically. The first group included 25 patients in the complex treatment of locally applied composition TIZOL with triamcinolon. The second group of 22 people, who in the complex treatment applied locally 0.5% prednisone ointment. The high efficiency of topical TIZOL with a highly topical steroid in the complex therapy of erosive-ulcerous forms OLP, which was confirmed by the positive clinical dynamics in all patients (100%) and high self-esteem of patients (84% positive ratings), reduced life complete epithelialization of erosions.

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

PubMed

Krivov, Sergei V

2011-07-01

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

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

NASA Astrophysics Data System (ADS)

Krivov, Sergei V.

2011-07-01

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

Unsteady, one-dimensional gas dynamics computations using a TVD type sequential solver

NASA Technical Reports Server (NTRS)

Thakur, Siddharth; Shyy, Wei

1992-01-01

The efficacy of high resolution convection schemes to resolve sharp gradient in unsteady, 1D flows is examined using the TVD concept based on a sequential solution algorithm. Two unsteady flow problems are considered which include the problem involving the interaction of the various waves in a shock tube with closed reflecting ends and the problem involving the unsteady gas dynamics in a tube with closed ends subject to an initial pressure perturbation. It is concluded that high accuracy convection schemes in a sequential solution framework are capable of resolving discontinuities in unsteady flows involving complex gas dynamics. However, a sufficient amount of dissipation is required to suppress oscillations near discontinuities in the sequential approach, which leads to smearing of the solution profiles.

Reversibly constraining spliceosome-substrate complexes by engineering disulfide crosslinks.

PubMed

McCarthy, Patrick; Garside, Erin; Meschede-Krasa, Yonatan; MacMillan, Andrew; Pomeranz Krummel, Daniel

2017-08-01

The spliceosome is a highly dynamic mega-Dalton enzyme, formed in part by assembly of U snRNPs onto its pre-mRNA substrate transcripts. Early steps in spliceosome assembly are challenging to study biochemically and structurally due to compositional and conformational dynamics. We detail an approach to covalently and reversibly constrain or trap non-covalent pre-mRNA/protein spliceosome complexes. This approach involves engineering a single disulfide bond between a thiol-bearing cysteine sidechain and a proximal backbone phosphate of the pre-mRNA, site-specifically modified with an N-thioalkyl moiety. When distance and angle between reactants is optimal, the sidechain will react with the single N-thioalkyl to form a crosslink upon oxidation. We provide protocols detailing how this has been applied successfully to trap an 11-subunit RNA-protein assembly, the human U1 snRNP, in complex with a pre-mRNA. Copyright © 2017 Elsevier Inc. All rights reserved.

Modelling and identification for control of gas bearings

NASA Astrophysics Data System (ADS)

Theisen, Lukas R. S.; Niemann, Hans H.; Santos, Ilmar F.; Galeazzi, Roberto; Blanke, Mogens

2016-03-01

Gas bearings are popular for their high speed capabilities, low friction and clean operation, but suffer from poor damping, which poses challenges for safe operation in presence of disturbances. Feedback control can achieve enhanced damping but requires low complexity models of the dominant dynamics over its entire operating range. Models from first principles are complex and sensitive to parameter uncertainty. This paper presents an experimental technique for "in situ" identification of a low complexity model of a rotor-bearing-actuator system and demonstrates identification over relevant ranges of rotational speed and gas injection pressure. This is obtained using parameter-varying linear models that are found to capture the dominant dynamics. The approach is shown to be easily applied and to suit subsequent control design. Based on the identified models, decentralised proportional control is designed and shown to obtain the required damping in theory and in a laboratory test rig.

Indirect dynamics in SN2@N: insight into the influence of central atoms.

PubMed

Liu, Xu; Zhao, Chenyang; Yang, Li; Zhang, Jiaxu; Sun, Rui

2017-08-30

Central atoms have a significant influence on the reaction kinetics and dynamics of nucleophilic substitution (S N 2). Herein, atomistic dynamics of a prototype S N 2@N reaction F - + NH 2 Cl is uncovered employing direct dynamics simulations that show strikingly distinct features from those determined for a S N 2@C congener F - + CH 3 Cl. Indirect scattering is found to prevail, which proceeds predominantly through a hydrogen-bonded F - -HNHCl complex in the reactant entrance channel. This unexpected finding of a pronounced contribution of indirect reaction dynamics, even at a high collision energy, is in strong contrast to a general evolution from indirect to direct dynamics with enhanced energy that characterizes S N 2@C. This result suggests that the relative importance of different atomic-level mechanisms may depend essentially on the interaction potential of reactive encounters and the coupling between inter- and intramolecular modes of the pre-reaction complex. For F - + NH 2 Cl the proton transfer pathway is less competitive than S N 2. A remarkable finding is that the more favorable energetics for NH 2 Cl proton transfer, as compared to that for CH 3 Cl, does not manifest itself in the reaction dynamics. The present work sheds light on the underlying reaction dynamics of S N 2@N, which remain largely unclear compared to well-studied S N 2@C.

Advanced laser modeling with BLAZE multiphysics

NASA Astrophysics Data System (ADS)

Palla, Andrew D.; Carroll, David L.; Gray, Michael I.; Suzuki, Lui

2017-01-01

The BLAZE Multiphysics™ software simulation suite was specifically developed to model highly complex multiphysical systems in a computationally efficient and highly scalable manner. These capabilities are of particular use when applied to the complexities associated with high energy laser systems that combine subsonic/transonic/supersonic fluid dynamics, chemically reacting flows, laser electronics, heat transfer, optical physics, and in some cases plasma discharges. In this paper we present detailed cw and pulsed gas laser calculations using the BLAZE model with comparisons to data. Simulations of DPAL, XPAL, ElectricOIL (EOIL), and the optically pumped rare gas laser were found to be in good agreement with experimental data.

The New Maia Detector System: Methods For High Definition Trace Element Imaging Of Natural Material

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

Ryan, C. G.; School of Physics, University of Melbourne, Parkville VIC; CODES Centre of Excellence, University of Tasmania, Hobart TAS

2010-04-06

Motivated by the need for megapixel high definition trace element imaging to capture intricate detail in natural material, together with faster acquisition and improved counting statistics in elemental imaging, a large energy-dispersive detector array called Maia has been developed by CSIRO and BNL for SXRF imaging on the XFM beamline at the Australian Synchrotron. A 96 detector prototype demonstrated the capacity of the system for real-time deconvolution of complex spectral data using an embedded implementation of the Dynamic Analysis method and acquiring highly detailed images up to 77 M pixels spanning large areas of complex mineral sample sections.

The New Maia Detector System: Methods For High Definition Trace Element Imaging Of Natural Material

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

Ryan, C.G.; Siddons, D.P.; Kirkham, R.

2010-05-25

Motivated by the need for megapixel high definition trace element imaging to capture intricate detail in natural material, together with faster acquisition and improved counting statistics in elemental imaging, a large energy-dispersive detector array called Maia has been developed by CSIRO and BNL for SXRF imaging on the XFM beamline at the Australian Synchrotron. A 96 detector prototype demonstrated the capacity of the system for real-time deconvolution of complex spectral data using an embedded implementation of the Dynamic Analysis method and acquiring highly detailed images up to 77 M pixels spanning large areas of complex mineral sample sections.

Onset of Cooperative Dynamics in an Equilibrium Glass-Forming Metallic Liquid

DOE PAGES

Jaiswal, Abhishek; O’Keeffe, Stephanie; Mills, Rebecca; ...

2016-01-22

Onset of cooperative dynamics has been observed in many molecular liquids, colloids, and granular materials in the metastable regime on approaching their respective glass or jamming transition points, and is considered to play a significant role in the emergence of the slow dynamics. However, the nature of such dynamical cooperativity remains elusive in multicomponent metallic liquids characterized by complex many-body interactions and high mixing entropy. Herein, we report evidence of onset of cooperative dynamics in an equilibrium glass-forming metallic liquid (LM601: Zr 51Cu 36Ni 4Al 9). This is revealed by deviation of the mean effective diffusion coefficient from its high-temperaturemore » Arrhenius behavior below T A ≈ 1300 K, i.e., a crossover from uncorrelated dynamics above T A to landscape-influenced correlated dynamics below T A. Moreover, the onset/ crossover temperature T A in such a multicomponent bulk metallic glass-forming liquid is observed at approximately twice of its calorimetric glass transition temperature (T g ≈ 697 K) and in its stable liquid phase, unlike many molecular liquids.« less

Water Dynamics in Shewanella oneidensis at Ambient and High Pressure using Quasi-Elastic Neutron Scattering

NASA Astrophysics Data System (ADS)

Foglia, Fabrizia; Hazael, Rachael; Simeoni, Giovanna G.; Appavou, Marie-Sousai; Moulin, Martine; Haertlein, Michael; Trevor Forsyth, V.; Seydel, Tilo; Daniel, Isabelle; Meersman, Filip; McMillan, Paul F.

2016-01-01

Quasielastic neutron scattering (QENS) is an ideal technique for studying water transport and relaxation dynamics at pico- to nanosecond timescales and at length scales relevant to cellular dimensions. Studies of high pressure dynamic effects in live organisms are needed to understand Earth’s deep biosphere and biotechnology applications. Here we applied QENS to study water transport in Shewanella oneidensis at ambient (0.1 MPa) and high (200 MPa) pressure using H/D isotopic contrast experiments for normal and perdeuterated bacteria and buffer solutions to distinguish intracellular and transmembrane processes. The results indicate that intracellular water dynamics are comparable with bulk diffusion rates in aqueous fluids at ambient conditions but a significant reduction occurs in high pressure mobility. We interpret this as due to enhanced interactions with macromolecules in the nanoconfined environment. Overall diffusion rates across the cell envelope also occur at similar rates but unexpected narrowing of the QENS signal appears between momentum transfer values Q = 0.7-1.1 Å-1 corresponding to real space dimensions of 6-9 Å. The relaxation time increase can be explained by correlated dynamics of molecules passing through Aquaporin water transport complexes located within the inner or outer membrane structures.

Water Dynamics in Shewanella oneidensis at Ambient and High Pressure using Quasi-Elastic Neutron Scattering.

PubMed

Foglia, Fabrizia; Hazael, Rachael; Simeoni, Giovanna G; Appavou, Marie-Sousai; Moulin, Martine; Haertlein, Michael; Trevor Forsyth, V; Seydel, Tilo; Daniel, Isabelle; Meersman, Filip; McMillan, Paul F

2016-01-07

Quasielastic neutron scattering (QENS) is an ideal technique for studying water transport and relaxation dynamics at pico- to nanosecond timescales and at length scales relevant to cellular dimensions. Studies of high pressure dynamic effects in live organisms are needed to understand Earth's deep biosphere and biotechnology applications. Here we applied QENS to study water transport in Shewanella oneidensis at ambient (0.1 MPa) and high (200 MPa) pressure using H/D isotopic contrast experiments for normal and perdeuterated bacteria and buffer solutions to distinguish intracellular and transmembrane processes. The results indicate that intracellular water dynamics are comparable with bulk diffusion rates in aqueous fluids at ambient conditions but a significant reduction occurs in high pressure mobility. We interpret this as due to enhanced interactions with macromolecules in the nanoconfined environment. Overall diffusion rates across the cell envelope also occur at similar rates but unexpected narrowing of the QENS signal appears between momentum transfer values Q = 0.7-1.1 Å(-1) corresponding to real space dimensions of 6-9 Å. The relaxation time increase can be explained by correlated dynamics of molecules passing through Aquaporin water transport complexes located within the inner or outer membrane structures.

A review of human factors challenges of complex adaptive systems: discovering and understanding chaos in human performance.

PubMed

Karwowski, Waldemar

2012-12-01

In this paper, the author explores a need for a greater understanding of the true nature of human-system interactions from the perspective of the theory of complex adaptive systems, including the essence of complexity, emergent properties of system behavior, nonlinear systems dynamics, and deterministic chaos. Human performance, more often than not, constitutes complex adaptive phenomena with emergent properties that exhibit nonlinear dynamical (chaotic) behaviors. The complexity challenges in the design and management of contemporary work systems, including service systems, are explored. Examples of selected applications of the concepts of nonlinear dynamics to the study of human physical performance are provided. Understanding and applications of the concepts of theory of complex adaptive and dynamical systems should significantly improve the effectiveness of human-centered design efforts of a large system of systems. Performance of many contemporary work systems and environments may be sensitive to the initial conditions and may exhibit dynamic nonlinear properties and chaotic system behaviors. Human-centered design of emergent human-system interactions requires application of the theories of nonlinear dynamics and complex adaptive system. The success of future human-systems integration efforts requires the fusion of paradigms, knowledge, design principles, and methodologies of human factors and ergonomics with those of the science of complex adaptive systems as well as modern systems engineering.

Effects of Pacing Site and Stimulation History on Alternans Dynamics and the Development of Complex Spatiotemporal Patterns in Cardiac Tissue

PubMed Central

Gizzi, Alessio; Cherry, Elizabeth M.; Gilmour, Robert F.; Luther, Stefan; Filippi, Simonetta; Fenton, Flavio H.

2013-01-01

Alternans of action potential duration has been associated with T wave alternans and the development of arrhythmias because it produces large gradients of repolarization. However, little is known about alternans dynamics in large mammalian hearts. Using optical mapping to record electrical activations simultaneously from the epicardium and endocardium of 9 canine right ventricles, we demonstrate novel arrhythmogenic complex spatiotemporal dynamics. (i) Alternans predominantly develops first on the endocardium. (ii) The postulated simple progression from normal rhythm to concordant to discordant alternans is not always observed; concordant alternans can develop from discordant alternans as the pacing period is decreased. (iii) In contrast to smaller tissue preparations, multiple stationary nodal lines may exist and need not be perpendicular to the pacing site or to each other. (iv) Alternans has fully three-dimensional dynamics and the epicardium and endocardium can show significantly different dynamics: multiple nodal surfaces can be transmural or intramural and can form concave/convex surfaces resulting in islands of discordant alternans. (v) The complex spatiotemporal patterns observed during alternans are very sensitive to both the site of stimulation and the stimulation history. Alternans in canine ventricles not only exhibit larger amplitudes and persist for longer cycle length regimes compared to those found in smaller mammalian hearts, but also show novel dynamics not previously described that enhance dispersion and show high sensitivity to initial conditions. This indicates some underlying predisposition to chaos and can help to guide the design of new drugs and devices controlling and preventing arrhythmic events. PMID:23637684

Conceptualizing Teacher Identity as a Complex Dynamic System: The Inner Dynamics of Transformations during a Practicum

ERIC Educational Resources Information Center

Henry, Alastair

2016-01-01

Currently, the inner dynamics of teacher identity transformations remain a "black box." Conceptualizing preservice teacher identity as a complex dynamic system, and the notion of "being someone who teaches" in dialogical terms as involving shifts between different teacher voices, the study investigates the dynamical processes…

Dynamical complexity of short and noisy time series. Compression-Complexity vs. Shannon entropy

NASA Astrophysics Data System (ADS)

Nagaraj, Nithin; Balasubramanian, Karthi

2017-07-01

Shannon entropy has been extensively used for characterizing complexity of time series arising from chaotic dynamical systems and stochastic processes such as Markov chains. However, for short and noisy time series, Shannon entropy performs poorly. Complexity measures which are based on lossless compression algorithms are a good substitute in such scenarios. We evaluate the performance of two such Compression-Complexity Measures namely Lempel-Ziv complexity (LZ) and Effort-To-Compress (ETC) on short time series from chaotic dynamical systems in the presence of noise. Both LZ and ETC outperform Shannon entropy (H) in accurately characterizing the dynamical complexity of such systems. For very short binary sequences (which arise in neuroscience applications), ETC has higher number of distinct complexity values than LZ and H, thus enabling a finer resolution. For two-state ergodic Markov chains, we empirically show that ETC converges to a steady state value faster than LZ. Compression-Complexity measures are promising for applications which involve short and noisy time series.

ReaDDy - A Software for Particle-Based Reaction-Diffusion Dynamics in Crowded Cellular Environments

PubMed Central

Schöneberg, Johannes; Noé, Frank

2013-01-01

We introduce the software package ReaDDy for simulation of detailed spatiotemporal mechanisms of dynamical processes in the cell, based on reaction-diffusion dynamics with particle resolution. In contrast to other particle-based reaction kinetics programs, ReaDDy supports particle interaction potentials. This permits effects such as space exclusion, molecular crowding and aggregation to be modeled. The biomolecules simulated can be represented as a sphere, or as a more complex geometry such as a domain structure or polymer chain. ReaDDy bridges the gap between small-scale but highly detailed molecular dynamics or Brownian dynamics simulations and large-scale but little-detailed reaction kinetics simulations. ReaDDy has a modular design that enables the exchange of the computing core by efficient platform-specific implementations or dynamical models that are different from Brownian dynamics. PMID:24040218

Deconstructing the core dynamics from a complex time-lagged regulatory biological circuit.

PubMed

Eriksson, O; Brinne, B; Zhou, Y; Björkegren, J; Tegnér, J

2009-03-01

Complex regulatory dynamics is ubiquitous in molecular networks composed of genes and proteins. Recent progress in computational biology and its application to molecular data generate a growing number of complex networks. Yet, it has been difficult to understand the governing principles of these networks beyond graphical analysis or extensive numerical simulations. Here the authors exploit several simplifying biological circumstances which thereby enable to directly detect the underlying dynamical regularities driving periodic oscillations in a dynamical nonlinear computational model of a protein-protein network. System analysis is performed using the cell cycle, a mathematically well-described complex regulatory circuit driven by external signals. By introducing an explicit time delay and using a 'tearing-and-zooming' approach the authors reduce the system to a piecewise linear system with two variables that capture the dynamics of this complex network. A key step in the analysis is the identification of functional subsystems by identifying the relations between state-variables within the model. These functional subsystems are referred to as dynamical modules operating as sensitive switches in the original complex model. By using reduced mathematical representations of the subsystems the authors derive explicit conditions on how the cell cycle dynamics depends on system parameters, and can, for the first time, analyse and prove global conditions for system stability. The approach which includes utilising biological simplifying conditions, identification of dynamical modules and mathematical reduction of the model complexity may be applicable to other well-characterised biological regulatory circuits. [Includes supplementary material].

Computational strategies to address chromatin structure problems

NASA Astrophysics Data System (ADS)

Perišić, Ognjen; Schlick, Tamar

2016-06-01

While the genetic information is contained in double helical DNA, gene expression is a complex multilevel process that involves various functional units, from nucleosomes to fully formed chromatin fibers accompanied by a host of various chromatin binding enzymes. The chromatin fiber is a polymer composed of histone protein complexes upon which DNA wraps, like yarn upon many spools. The nature of chromatin structure has been an open question since the beginning of modern molecular biology. Many experiments have shown that the chromatin fiber is a highly dynamic entity with pronounced structural diversity that includes properties of idealized zig-zag and solenoid models, as well as other motifs. This diversity can produce a high packing ratio and thus inhibit access to a majority of the wound DNA. Despite much research, chromatin’s dynamic structure has not yet been fully described. Long stretches of chromatin fibers exhibit puzzling dynamic behavior that requires interpretation in the light of gene expression patterns in various tissue and organisms. The properties of chromatin fiber can be investigated with experimental techniques, like in vitro biochemistry, in vivo imagining, and high-throughput chromosome capture technology. Those techniques provide useful insights into the fiber’s structure and dynamics, but they are limited in resolution and scope, especially regarding compact fibers and chromosomes in the cellular milieu. Complementary but specialized modeling techniques are needed to handle large floppy polymers such as the chromatin fiber. In this review, we discuss current approaches in the chromatin structure field with an emphasis on modeling, such as molecular dynamics and coarse-grained computational approaches. Combinations of these computational techniques complement experiments and address many relevant biological problems, as we will illustrate with special focus on epigenetic modulation of chromatin structure.

New Insights on Insect's Silent Flight. Part I: Vortex Dynamics and Wing Morphing

NASA Astrophysics Data System (ADS)

Ren, Yan; Liu, Geng; Dong, Haibo; Geng, Biao; Zheng, Xudong; Xue, Qian

2016-11-01

Insects are capable of conducting silent flights. This is attributed to its specially designed wing material properties for the control of vibration and surface morphing during the flapping flight. In current work, we focus on the roles of dynamic wing morphing on the unsteady vortex dynamics of a cicada in steady flight. A 3D image-based surface reconstruction method is used to obtain kinematical and morphological data of cicada wings from high-quality high-speed videos. The observed morphing wing kinematics is highly complex and a singular value decomposition method is used to decompose the wing motion to several dominant modes with distinct motion features. A high-fidelity immersed-boundary-based flow solver is then used to study the vortex dynamics in details. The results show that vortical structures closely relate to the morphing mode, which plays key role in the development and attachment of leading-edge vortex (LEV), thus helps the silent flapping of the cicada wings. This work is supported by AFOSR FA9550-12-1-0071 and NSF CBET-1313217.

Development and validation of a 48-target analytical method for high-throughput monitoring of genetically modified organisms.

PubMed

Li, Xiaofei; Wu, Yuhua; Li, Jun; Li, Yunjing; Long, Likun; Li, Feiwu; Wu, Gang

2015-01-05

The rapid increase in the number of genetically modified (GM) varieties has led to a demand for high-throughput methods to detect genetically modified organisms (GMOs). We describe a new dynamic array-based high throughput method to simultaneously detect 48 targets in 48 samples on a Fludigm system. The test targets included species-specific genes, common screening elements, most of the Chinese-approved GM events, and several unapproved events. The 48 TaqMan assays successfully amplified products from both single-event samples and complex samples with a GMO DNA amount of 0.05 ng, and displayed high specificity. To improve the sensitivity of detection, a preamplification step for 48 pooled targets was added to enrich the amount of template before performing dynamic chip assays. This dynamic chip-based method allowed the synchronous high-throughput detection of multiple targets in multiple samples. Thus, it represents an efficient, qualitative method for GMO multi-detection.

Development and Validation of A 48-Target Analytical Method for High-throughput Monitoring of Genetically Modified Organisms

PubMed Central

Li, Xiaofei; Wu, Yuhua; Li, Jun; Li, Yunjing; Long, Likun; Li, Feiwu; Wu, Gang

2015-01-01

The rapid increase in the number of genetically modified (GM) varieties has led to a demand for high-throughput methods to detect genetically modified organisms (GMOs). We describe a new dynamic array-based high throughput method to simultaneously detect 48 targets in 48 samples on a Fludigm system. The test targets included species-specific genes, common screening elements, most of the Chinese-approved GM events, and several unapproved events. The 48 TaqMan assays successfully amplified products from both single-event samples and complex samples with a GMO DNA amount of 0.05 ng, and displayed high specificity. To improve the sensitivity of detection, a preamplification step for 48 pooled targets was added to enrich the amount of template before performing dynamic chip assays. This dynamic chip-based method allowed the synchronous high-throughput detection of multiple targets in multiple samples. Thus, it represents an efficient, qualitative method for GMO multi-detection. PMID:25556930

How Complex, Probable, and Predictable is Genetically Driven Red Queen Chaos?

PubMed

Duarte, Jorge; Rodrigues, Carla; Januário, Cristina; Martins, Nuno; Sardanyés, Josep

2015-12-01

Coevolution between two antagonistic species has been widely studied theoretically for both ecologically- and genetically-driven Red Queen dynamics. A typical outcome of these systems is an oscillatory behavior causing an endless series of one species adaptation and others counter-adaptation. More recently, a mathematical model combining a three-species food chain system with an adaptive dynamics approach revealed genetically driven chaotic Red Queen coevolution. In the present article, we analyze this mathematical model mainly focusing on the impact of species rates of evolution (mutation rates) in the dynamics. Firstly, we analytically proof the boundedness of the trajectories of the chaotic attractor. The complexity of the coupling between the dynamical variables is quantified using observability indices. By using symbolic dynamics theory, we quantify the complexity of genetically driven Red Queen chaos computing the topological entropy of existing one-dimensional iterated maps using Markov partitions. Co-dimensional two bifurcation diagrams are also built from the period ordering of the orbits of the maps. Then, we study the predictability of the Red Queen chaos, found in narrow regions of mutation rates. To extend the previous analyses, we also computed the likeliness of finding chaos in a given region of the parameter space varying other model parameters simultaneously. Such analyses allowed us to compute a mean predictability measure for the system in the explored region of the parameter space. We found that genetically driven Red Queen chaos, although being restricted to small regions of the analyzed parameter space, might be highly unpredictable.

Ultrafast Energy Flow and Equilibration Dynamics in Photosynthetic Light-Harvesting Complexes

NASA Astrophysics Data System (ADS)

Maiuri, Margherita; Lüer, Larry; Henry, Sarah; Carey, Anne-Marie; Cogdell, Richard J.; Cerullo, Giulio; Polli, Dario

We disentangle various energy transfer pathways in the bacterio-chlorophyll excitation cascade from LH2 to LH1 in Chromatium vinosum grown under high-light or low-light illumination using tunable narrowband selective excitation and broadband infrared probing.

Dynamical complexity changes during two forms of meditation

NASA Astrophysics Data System (ADS)

Li, Jin; Hu, Jing; Zhang, Yinhong; Zhang, Xiaofeng

2011-06-01

Detection of dynamical complexity changes in natural and man-made systems has deep scientific and practical meaning. We use the base-scale entropy method to analyze dynamical complexity changes for heart rate variability (HRV) series during specific traditional forms of Chinese Chi and Kundalini Yoga meditation techniques in healthy young adults. The results show that dynamical complexity decreases in meditation states for two forms of meditation. Meanwhile, we detected changes in probability distribution of m-words during meditation and explained this changes using probability distribution of sine function. The base-scale entropy method may be used on a wider range of physiologic signals.

EYE MOVEMENT RECORDING AND NONLINEAR DYNAMICS ANALYSIS – THE CASE OF SACCADES#

PubMed Central

Aştefănoaei, Corina; Pretegiani, Elena; Optican, L.M.; Creangă, Dorina; Rufa, Alessandra

2015-01-01

Evidence of a chaotic behavioral trend in eye movement dynamics was examined in the case of a saccadic temporal series collected from a healthy human subject. Saccades are highvelocity eye movements of very short duration, their recording being relatively accessible, so that the resulting data series could be studied computationally for understanding the neural processing in a motor system. The aim of this study was to assess the complexity degree in the eye movement dynamics. To do this we analyzed the saccadic temporal series recorded with an infrared camera eye tracker from a healthy human subject in a special experimental arrangement which provides continuous records of eye position, both saccades (eye shifting movements) and fixations (focusing over regions of interest, with rapid, small fluctuations). The semi-quantitative approach used in this paper in studying the eye functioning from the viewpoint of non-linear dynamics was accomplished by some computational tests (power spectrum, portrait in the state space and its fractal dimension, Hurst exponent and largest Lyapunov exponent) derived from chaos theory. A high complexity dynamical trend was found. Lyapunov largest exponent test suggested bi-stability of cellular membrane resting potential during saccadic experiment. PMID:25698889

Dynamically variable negative stiffness structures.

PubMed

Churchill, Christopher B; Shahan, David W; Smith, Sloan P; Keefe, Andrew C; McKnight, Geoffrey P

2016-02-01

Variable stiffness structures that enable a wide range of efficient load-bearing and dexterous activity are ubiquitous in mammalian musculoskeletal systems but are rare in engineered systems because of their complexity, power, and cost. We present a new negative stiffness-based load-bearing structure with dynamically tunable stiffness. Negative stiffness, traditionally used to achieve novel response from passive structures, is a powerful tool to achieve dynamic stiffness changes when configured with an active component. Using relatively simple hardware and low-power, low-frequency actuation, we show an assembly capable of fast (<10 ms) and useful (>100×) dynamic stiffness control. This approach mitigates limitations of conventional tunable stiffness structures that exhibit either small (<30%) stiffness change, high friction, poor load/torque transmission at low stiffness, or high power active control at the frequencies of interest. We experimentally demonstrate actively tunable vibration isolation and stiffness tuning independent of supported loads, enhancing applications such as humanoid robotic limbs and lightweight adaptive vibration isolators.

Quantitative imaging of heterogeneous dynamics in drying and aging paints

PubMed Central

van der Kooij, Hanne M.; Fokkink, Remco; van der Gucht, Jasper; Sprakel, Joris

2016-01-01

Drying and aging paint dispersions display a wealth of complex phenomena that make their study fascinating yet challenging. To meet the growing demand for sustainable, high-quality paints, it is essential to unravel the microscopic mechanisms underlying these phenomena. Visualising the governing dynamics is, however, intrinsically difficult because the dynamics are typically heterogeneous and span a wide range of time scales. Moreover, the high turbidity of paints precludes conventional imaging techniques from reaching deep inside the paint. To address these challenges, we apply a scattering technique, Laser Speckle Imaging, as a versatile and quantitative tool to elucidate the internal dynamics, with microscopic resolution and spanning seven decades of time. We present a toolbox of data analysis and image processing methods that allows a tailored investigation of virtually any turbid dispersion, regardless of the geometry and substrate. Using these tools we watch a variety of paints dry and age with unprecedented detail. PMID:27682840

On the dynamics of StemBells: Microbubble-conjugated stem cells for ultrasound-controlled delivery

NASA Astrophysics Data System (ADS)

Kokhuis, Tom J. A.; Naaijkens, Benno A.; Juffermans, Lynda J. M.; Kamp, Otto; van der Steen, Antonius F. W.; Versluis, Michel; de Jong, Nico

2017-07-01

The use of stem cells for regenerative tissue repair is promising but hampered by the low number of cells delivered to the site of injury. To increase the delivery, we propose a technique in which stem cells are linked to functionalized microbubbles, creating echogenic complex dubbed StemBells. StemBells are highly susceptible to acoustic radiation force which can be employed after injection to push the StemBells locally to the treatment site. To optimally benefit from the delivery technique, a thorough characterization of the dynamics of StemBells during ultrasound exposure is needed. Using high-speed optical imaging, we study the dynamics of StemBells as a function of the applied frequency from which resonance curves were constructed. A theoretical model, based on a modified Rayleigh-Plesset type equation, captured the experimental resonance characteristics and radial dynamics in detail.

Effect of salt intake on beat-to-beat blood pressure nonlinear dynamics and entropy in salt-sensitive versus salt-protected rats.

PubMed

Fares, Souha A; Habib, Joseph R; Engoren, Milo C; Badr, Kamal F; Habib, Robert H

2016-06-01

Blood pressure exhibits substantial short- and long-term variability (BPV). We assessed the hypothesis that the complexity of beat-to-beat BPV will be differentially altered in salt-sensitive hypertensive Dahl rats (SS) versus rats protected from salt-induced hypertension (SSBN13) maintained on high-salt versus low-salt diet. Beat-to-beat systolic and diastolic BP series from nine SS and six SSBN13 rats (http://www.physionet.org) were analyzed following 9 weeks on low salt and repeated after 2 weeks on high salt. BP complexity was quantified by detrended fluctuation analysis (DFA), short- and long-range scaling exponents (αS and αL), sample entropy (SampEn), and traditional standard deviation (SD) and coefficient of variation (CV(%)). Mean systolic and diastolic BP increased on high-salt diet (P < 0.01) particularly for SS rats. SD and CV(%) were similar across groups irrespective of diet. Salt-sensitive and -protected rats exhibited similar complexity indices on low-salt diet. On high salt, (1) SS rats showed increased scaling exponents or smoother, systolic (P = 0.007 [αL]) and diastolic (P = 0.008 [αL]) BP series; (2) salt-protected rats showed lower SampEn (less complex) systolic and diastolic BP (P = 0.046); and (3) compared to protected SSBN13 rats, SS showed higher αL for systolic (P = 0.01) and diastolic (P = 0.005) BP Hypertensive SS rats are more susceptible to high salt with a greater rise in mean BP and reduced complexity. Comparable mean pressures in sensitive and protective rats when on low-salt diet coupled with similar BPV dynamics suggest a protective role of low-salt intake in hypertensive rats. This effect likely reflects better coupling of biologic oscillators. © 2016 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.

Complex collective dynamics of active torque-driven colloids at interfaces

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

Snezhko, Alexey

Modern self-assembly techniques aiming to produce complex structural order or functional diversity often rely on non-equilibrium conditions in the system. Light, electric, or magnetic fields are predominantly used to modify interaction profiles of colloidal particles during self-assembly or induce complex out-of-equilibrium dynamic ordering. The energy injection rate, properties of the environment are important control parameters that influence the outcome of active (dynamic) self-assembly. The current review is focused on a case of collective dynamics and self-assembly of particles with externally driven torques coupled to a liquid or solid interface. The complexity of interactions in such systems is further enriched bymore » strong hydrodynamic coupling between particles. Unconventionally ordered dynamic self-assembled patterns, spontaneous symmetry breaking phenomena, self-propulsion, and collective transport have been reported in torque-driven colloids. Some of the features of the complex collective behavior and dynamic pattern formation in those active systems have been successfully captured in simulations.« less

Dynamic Fracture Behavior of Plastic-Bonded Explosives

NASA Astrophysics Data System (ADS)

Fu, Hua; Li, Jun-Ling; Tan, Duo-Wang; Ifp, Caep Team

2011-06-01

Plastic-Bonded Explosives (PBX) are used as important energetic materials in nuclear or conventional weapons. Arms Warhead in the service process and the ballistic phase, may experience complex process such as long pulse and higher loading, compresson, tension and reciprocating compression - tension, friction with the projectile shell, which would lead to explosive deformation and fracture.And the dynamic deformation and fracture behavior of PBX subsequently affect reaction characteristics and initiation mechanism in explosives, then having influence on explosives safety. The dynamic fracure behavior of PBX are generally complex and not well studied or understood. In this paper, the dynamic fracture of explosives are conducted using a Kolsky bar. The Brazilian test, also known as a indirect tensile test or splitting test, is chosen as the test method. Tensile strength under different strain rates are obtained using quartz crystal embedded in rod end. The dynamic deformation and fracture process are captured in real-time by high-speed digital camera, and the displacement and strain fields distribution before specimen fracture are obtained by digital correlation method. Considering the non-uniform microstructure of explosives,the dynamic fracture behavior of explosive are simulated by discrete element method, the simulation results can reproduce the deformation and fracture process in Brazilian test using a maximum tensile strain criterion.

Allosteric Regulation of the Hsp90 Dynamics and Stability by Client Recruiter Cochaperones: Protein Structure Network Modeling

PubMed Central

Blacklock, Kristin; Verkhivker, Gennady M.

2014-01-01

The fundamental role of the Hsp90 chaperone in supporting functional activity of diverse protein clients is anchored by specific cochaperones. A family of immune sensing client proteins is delivered to the Hsp90 system with the aid of cochaperones Sgt1 and Rar1 that act cooperatively with Hsp90 to form allosterically regulated dynamic complexes. In this work, functional dynamics and protein structure network modeling are combined to dissect molecular mechanisms of Hsp90 regulation by the client recruiter cochaperones. Dynamic signatures of the Hsp90-cochaperone complexes are manifested in differential modulation of the conformational mobility in the Hsp90 lid motif. Consistent with the experiments, we have determined that targeted reorganization of the lid dynamics is a unifying characteristic of the client recruiter cochaperones. Protein network analysis of the essential conformational space of the Hsp90-cochaperone motions has identified structurally stable interaction communities, interfacial hubs and key mediating residues of allosteric communication pathways that act concertedly with the shifts in conformational equilibrium. The results have shown that client recruiter cochaperones can orchestrate global changes in the dynamics and stability of the interaction networks that could enhance the ATPase activity and assist in the client recruitment. The network analysis has recapitulated a broad range of structural and mutagenesis experiments, particularly clarifying the elusive role of Rar1 as a regulator of the Hsp90 interactions and a stability enhancer of the Hsp90-cochaperone complexes. Small-world organization of the interaction networks in the Hsp90 regulatory complexes gives rise to a strong correspondence between highly connected local interfacial hubs, global mediator residues of allosteric interactions and key functional hot spots of the Hsp90 activity. We have found that cochaperone-induced conformational changes in Hsp90 may be determined by specific interaction networks that can inhibit or promote progression of the ATPase cycle and thus control the recruitment of client proteins. PMID:24466147

Allosteric regulation of the Hsp90 dynamics and stability by client recruiter cochaperones: protein structure network modeling.

PubMed

Blacklock, Kristin; Verkhivker, Gennady M

2014-01-01

The fundamental role of the Hsp90 chaperone in supporting functional activity of diverse protein clients is anchored by specific cochaperones. A family of immune sensing client proteins is delivered to the Hsp90 system with the aid of cochaperones Sgt1 and Rar1 that act cooperatively with Hsp90 to form allosterically regulated dynamic complexes. In this work, functional dynamics and protein structure network modeling are combined to dissect molecular mechanisms of Hsp90 regulation by the client recruiter cochaperones. Dynamic signatures of the Hsp90-cochaperone complexes are manifested in differential modulation of the conformational mobility in the Hsp90 lid motif. Consistent with the experiments, we have determined that targeted reorganization of the lid dynamics is a unifying characteristic of the client recruiter cochaperones. Protein network analysis of the essential conformational space of the Hsp90-cochaperone motions has identified structurally stable interaction communities, interfacial hubs and key mediating residues of allosteric communication pathways that act concertedly with the shifts in conformational equilibrium. The results have shown that client recruiter cochaperones can orchestrate global changes in the dynamics and stability of the interaction networks that could enhance the ATPase activity and assist in the client recruitment. The network analysis has recapitulated a broad range of structural and mutagenesis experiments, particularly clarifying the elusive role of Rar1 as a regulator of the Hsp90 interactions and a stability enhancer of the Hsp90-cochaperone complexes. Small-world organization of the interaction networks in the Hsp90 regulatory complexes gives rise to a strong correspondence between highly connected local interfacial hubs, global mediator residues of allosteric interactions and key functional hot spots of the Hsp90 activity. We have found that cochaperone-induced conformational changes in Hsp90 may be determined by specific interaction networks that can inhibit or promote progression of the ATPase cycle and thus control the recruitment of client proteins.

PREFACE: Topics in the application of scattering methods to investigate the structure and dynamics of soft condensed matter

NASA Astrophysics Data System (ADS)

Chen, Sow-Hsin; Baglioni, Piero

2006-09-01

This special issue of Journal of Physics: Condensed Matter gathers together a series of contributions presented at the workshop entitled `Topics in the Application of Scattering Methods to Investigate the Structure and Dynamics of Soft Condensed Matter' held at Pensione Bencista, Fiesole, Italy, a wonderful Italian jewel tucked high in the hills above Florence. This immaculate 14th century villa is a feast for the eyes with antiques and original artwork everywhere you turn, and a stunning view of Florence, overlooking numerous villas and groves of olive trees. The meeting consisted of about 40 invited talks delivered by a selected group of prominent physicists and chemists from the USA, Mexico, Europe and Asia working in the fields of complex and glassy liquids. The topics covered by the talks included: simulations on the liquid-liquid transition phenomenon dynamic crossover in deeply supercooled confined water thermodynamics and dynamics of complex fluids dynamics of interfacial water structural arrest transitions in colloidal systems structure and dynamics in complex systems structure of supramolecular assemblies The choice of topics is obviously heavily biased toward the current interests of the two organizers of the workshop, in view of the fact that one of the incentives for organizing the meeting was to celebrate Sow-Hsin Chen’s life-long scientific activities on the occasion of his 70th birthday. The 21 articles presented in this issue are a state-of-the-art description of the different aspects reported at the workshop from all points of view---experimental, theoretical and numerical. The interdisciplinary nature of the talks should make this special issue of interest to a broad community of scientists involved in the study of the properties of complex fluids, soft condensed matter and disordered glassy systems. We are grateful to the Consorzio per lo Sviluppo dei Sistemi a Grande Interfase (CSGI), Florence, Italy and to the Materials Science Program of the US Department of Energy for their support of the workshop.

Regulation of T cell receptor complex-mediated signaling by ubiquitin and ubiquitin-like modifications.

PubMed

Friend, Samantha F; Deason-Towne, Francina; Peterson, Lisa K; Berger, Allison J; Dragone, Leonard L

2014-01-01

Post-translational protein modifications are a dynamic method of regulating protein function in response to environmental signals. As with any cellular process, T cell receptor (TCR) complex-mediated signaling is highly regulated, since the strength and duration of TCR-generated signals governs T cell development and activation. While regulation of TCR complex-mediated signaling by phosphorylation has been well studied, regulation by ubiquitin and ubiquitin-like modifiers is still an emerging area of investigation. This review will examine how ubiquitin, E3 ubiquitin ligases, and other ubiquitin-like modifications such as SUMO and NEDD8 regulate TCR complex-mediated signaling.

Regulation of T cell receptor complex-mediated signaling by ubiquitin and ubiquitin-like modifications

PubMed Central

Friend, Samantha F; Deason-Towne, Francina; Peterson, Lisa K; Berger, Allison J; Dragone, Leonard L

2014-01-01

Post-translational protein modifications are a dynamic method of regulating protein function in response to environmental signals. As with any cellular process, T cell receptor (TCR) complex-mediated signaling is highly regulated, since the strength and duration of TCR-generated signals governs T cell development and activation. While regulation of TCR complex-mediated signaling by phosphorylation has been well studied, regulation by ubiquitin and ubiquitin-like modifiers is still an emerging area of investigation. This review will examine how ubiquitin, E3 ubiquitin ligases, and other ubiquitin-like modifications such as SUMO and NEDD8 regulate TCR complex-mediated signaling. PMID:25628960

Information processing using a single dynamical node as complex system

PubMed Central

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

2011-01-01

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

A Constraint Embedding Approach for Complex Vehicle Suspension Dynamics

DTIC Science & Technology

2015-04-24

Complex Vehicle Suspension Dynamics ECCOMAS Thematic Conference on Multibody Dynamics 2015 Abhinandan Jain∗, Calvin Kuo#, Paramsothy Jayakumar †, Jonathan...Suspension Dynamics ECCOMAS Thematic Conference on Multibody Dynamics 2015 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6...13. SUPPLEMENTARY NOTES ECCOMAS Thematic Conference on Multibody Dynamics 2015, June 29-July 2, 2015, Barcelona, Catalonia, Spain 14. ABSTRACT See

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

PubMed Central

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-01-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays. PMID:27452732

A high-content image-based method for quantitatively studying context-dependent cell population dynamics

NASA Astrophysics Data System (ADS)

Garvey, Colleen M.; Spiller, Erin; Lindsay, Danika; Chiang, Chun-Te; Choi, Nathan C.; Agus, David B.; Mallick, Parag; Foo, Jasmine; Mumenthaler, Shannon M.

2016-07-01

Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context, and are unable to perform multiplex phenotypic profiling of cell populations. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses; and (2) changes in morphological features over time and in response to perturbation. These important features can directly influence tumor evolution and clinical outcome. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays.

Practical Measurement of Complexity In Dynamic Systems

DTIC Science & Technology

2012-01-01

policies that produce highly complex behaviors , yet yield no benefit. 21Jason B. Clark and David R. Jacques / Procedia Computer Science 8 (2012) 14... Procedia Computer Science 8 (2012) 14 – 21 1877-0509 © 2012 Published by Elsevier B.V. doi:10.1016/j.procs.2012.01.008 Available online at...www.sciencedirect.com Procedia Computer Science Procedia Computer Science 00 (2012) 000–000 www.elsevier.com/locate/ procedia Available online at

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

ERIC Educational Resources Information Center

Polat, Brittany; Kim, Youjin

2014-01-01

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

Methodologies for Verification and Validation of Space Launch System (SLS) Structural Dynamic Models: Appendices

NASA Technical Reports Server (NTRS)

Coppolino, Robert N.

2018-01-01

Verification and validation (V&V) is a highly challenging undertaking for SLS structural dynamics models due to the magnitude and complexity of SLS subassemblies and subassemblies. Responses to challenges associated with V&V of Space Launch System (SLS) structural dynamics models are presented in Volume I of this paper. Four methodologies addressing specific requirements for V&V are discussed. (1) Residual Mode Augmentation (RMA). (2) Modified Guyan Reduction (MGR) and Harmonic Reduction (HR, introduced in 1976). (3) Mode Consolidation (MC). Finally, (4) Experimental Mode Verification (EMV). This document contains the appendices to Volume I.

Persistence and stochastic periodicity in the intensity dynamics of a fiber laser during the transition to optical turbulence

NASA Astrophysics Data System (ADS)

Carpi, Laura; Masoller, Cristina

2018-02-01

Many natural systems display transitions among different dynamical regimes, which are difficult to identify when the data are noisy and high dimensional. A technologically relevant example is a fiber laser, which can display complex dynamical behaviors that involve nonlinear interactions of millions of cavity modes. Here we study the laminar-turbulence transition that occurs when the laser pump power is increased. By applying various data analysis tools to empirical intensity time series we characterize their persistence and demonstrate that at the transition temporal correlations can be precisely represented by a surprisingly simple model.

A computational model of amoeboid cell swimming in unbounded medium and through obstacles

NASA Astrophysics Data System (ADS)

Campbell, Eric; Bagchi, Prosenjit

2017-11-01

Pseudopod-driven motility is commonly observed in eukaryotic cells. Pseudopodia are actin-rich protrusions of the cellular membrane which extend, bifurcate, and retract in cycles resulting in amoeboid locomotion. While actin-myosin interactions are responsible for pseudopod generation, cell deformability is crucial concerning pseudopod dynamics. Because pseudopodia are highly dynamic, cells are capable of deforming into complex shapes over time. Pseudopod-driven motility represents a multiscale and complex process, coupling cell deformation, protein biochemistry, and cytoplasmic and extracellular fluid motion. In this work, we present a 3D computational model of amoeboid cell swimming in an extracellular medium (ECM). The ECM is represented as a fluid medium with or without obstacles. The model integrates full cell deformation, a coarse-grain reaction-diffusion system for protein dynamics, and fluid interaction. Our model generates pseudopodia which bifurcate and retract, showing remarkable similarity to experimental observations. Influence of cell deformation, protein diffusivity and cytoplasmic viscosity on the swimming speed is analyzed in terms of altered pseudopod dynamics. Insights into the role of matrix porosity and obstacle size on cell motility are also provided. Funded by NSF CBET 1438255.

Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes.

PubMed

Kürten, Charlotte; Syrén, Per-Olof

2016-01-16

Enzyme catalysis evolved in an aqueous environment. The influence of solvent dynamics on catalysis is, however, currently poorly understood and usually neglected. The study of water dynamics in enzymes and the associated thermodynamical consequences is highly complex and has involved computer simulations, nuclear magnetic resonance (NMR) experiments, and calorimetry. Water tunnels that connect the active site with the surrounding solvent are key to solvent displacement and dynamics. The protocol herein allows for the engineering of these motifs for water transport, which affects specificity, activity and thermodynamics. By providing a biophysical framework founded on theory and experiments, the method presented herein can be used by researchers without previous expertise in computer modeling or biophysical chemistry. The method will advance our understanding of enzyme catalysis on the molecular level by measuring the enthalpic and entropic changes associated with catalysis by enzyme variants with obstructed water tunnels. The protocol can be used for the study of membrane-bound enzymes and other complex systems. This will enhance our understanding of the importance of solvent reorganization in catalysis as well as provide new catalytic strategies in protein design and engineering.

Multiscale Support Vector Learning With Projection Operator Wavelet Kernel for Nonlinear Dynamical System Identification.

PubMed

Lu, Zhao; Sun, Jing; Butts, Kenneth

2016-02-03

A giant leap has been made in the past couple of decades with the introduction of kernel-based learning as a mainstay for designing effective nonlinear computational learning algorithms. In view of the geometric interpretation of conditional expectation and the ubiquity of multiscale characteristics in highly complex nonlinear dynamic systems [1]-[3], this paper presents a new orthogonal projection operator wavelet kernel, aiming at developing an efficient computational learning approach for nonlinear dynamical system identification. In the framework of multiresolution analysis, the proposed projection operator wavelet kernel can fulfill the multiscale, multidimensional learning to estimate complex dependencies. The special advantage of the projection operator wavelet kernel developed in this paper lies in the fact that it has a closed-form expression, which greatly facilitates its application in kernel learning. To the best of our knowledge, it is the first closed-form orthogonal projection wavelet kernel reported in the literature. It provides a link between grid-based wavelets and mesh-free kernel-based methods. Simulation studies for identifying the parallel models of two benchmark nonlinear dynamical systems confirm its superiority in model accuracy and sparsity.

Rheological principles of development hetero-modulus and hetero-viscous complex materials with extreme dynamic strength

NASA Astrophysics Data System (ADS)

Gömze, L. A.; Gömze, L. N.

2017-02-01

Materials with different crystalline and morphological compositions have different chemical, physical, mechanical and rheological properties, including wear protection, melting temperature, module of elasticity and viscosity. Examining the material structures and behaviors of differentceramic bodies and CMCs under high speed collisions in several years the authors have understood the advantages of hetero-modulus and hetero-viscous complex material systems to absorb and dissipate the kinetic energy of objects during high speed collisions. Applying the rheo-mechanical principles the authors successfully developed a new family of hetero-modulus and hetero-viscous alumina matrix composite materials with extreme mechanical properties including dynamic strength. These new corundum-matrix composite materials reinforced with Si2ON 2, Si3N4 , SiAlON and AlN submicron and nanoparticles have excellent dynamic strength during collisions with high density metallic bodies with speeds about 1000 m/sec or more. At the same time in the alumina matrix composites can be observed a phase transformation of submicron and nanoparticles of alpha and beta silicone-nitride crystals into cubicc-Si3N4 diamond-like particles can be observed, when the high speed collision processes are taken place in vacuum or oxygen-free atmosphere. Using the rheological principles and the energy engorgement by fractures, heating and melting of components the authors successfully developed several new hetero-modulus, hetero-viscous and hetero-plastic complex materials. These materials generally are based on ceramic matrixes and components having different melting temperatures and modules of elasticity from low values like carbon and light metals (Mg, Al, Ti, Si) up to very high values like boride, nitride and carbide ceramics. Analytical methods applied in this research were scanning electron microscopy, X-ray diffractions and energy dispersive spectrometry. Digital image analysis was applied to microscopy results to enhance the results of transformations.

Sensitivity Analysis of Multidisciplinary Rotorcraft Simulations

NASA Technical Reports Server (NTRS)

Wang, Li; Diskin, Boris; Biedron, Robert T.; Nielsen, Eric J.; Bauchau, Olivier A.

2017-01-01

A multidisciplinary sensitivity analysis of rotorcraft simulations involving tightly coupled high-fidelity computational fluid dynamics and comprehensive analysis solvers is presented and evaluated. An unstructured sensitivity-enabled Navier-Stokes solver, FUN3D, and a nonlinear flexible multibody dynamics solver, DYMORE, are coupled to predict the aerodynamic loads and structural responses of helicopter rotor blades. A discretely-consistent adjoint-based sensitivity analysis available in FUN3D provides sensitivities arising from unsteady turbulent flows and unstructured dynamic overset meshes, while a complex-variable approach is used to compute DYMORE structural sensitivities with respect to aerodynamic loads. The multidisciplinary sensitivity analysis is conducted through integrating the sensitivity components from each discipline of the coupled system. Numerical results verify accuracy of the FUN3D/DYMORE system by conducting simulations for a benchmark rotorcraft test model and comparing solutions with established analyses and experimental data. Complex-variable implementation of sensitivity analysis of DYMORE and the coupled FUN3D/DYMORE system is verified by comparing with real-valued analysis and sensitivities. Correctness of adjoint formulations for FUN3D/DYMORE interfaces is verified by comparing adjoint-based and complex-variable sensitivities. Finally, sensitivities of the lift and drag functions obtained by complex-variable FUN3D/DYMORE simulations are compared with sensitivities computed by the multidisciplinary sensitivity analysis, which couples adjoint-based flow and grid sensitivities of FUN3D and FUN3D/DYMORE interfaces with complex-variable sensitivities of DYMORE structural responses.

Arctic systems in the Quaternary: ecological collision, faunal mosaics and the consequences of a wobbling climate.

PubMed

Hoberg, E P; Cook, J A; Agosta, S J; Boeger, W; Galbreath, K E; Laaksonen, S; Kutz, S J; Brooks, D R

2017-07-01

Climate oscillations and episodic processes interact with evolution, ecology and biogeography to determine the structure and complex mosaic that is the biosphere. Parasites and parasite-host assemblages are key components in a general explanatory paradigm for global biodiversity. We explore faunal assembly in the context of Quaternary time frames of the past 2.6 million years, a period dominated by episodic shifts in climate. Climate drivers cross a continuum from geological to contemporary timescales and serve to determine the structure and distribution of complex biotas. Cycles within cycles are apparent, with drivers that are layered, multifactorial and complex. These cycles influence the dynamics and duration of shifts in environmental structure on varying temporal and spatial scales. An understanding of the dynamics of high-latitude systems, the history of the Beringian nexus (the intermittent land connection linking Eurasia and North America) and downstream patterns of diversity depend on teasing apart the complexity of biotic assembly and persistence. Although climate oscillations have dominated the Quaternary, contemporary dynamics are driven by tipping points and shifting balances emerging from anthropogenic forces that are disrupting ecological structure. Climate change driven by anthropogenic forcing has supplanted a history of episodic variation and is eliminating ecological barriers and constraints on development and distribution for pathogen transmission. A framework to explore interactions of episodic processes on faunal structure and assembly is the Stockholm Paradigm, which appropriately shifts the focus from cospeciation to complexity and contingency in explanations of diversity.

Inferring topologies via driving-based generalized synchronization of two-layer networks

NASA Astrophysics Data System (ADS)

Wang, Yingfei; Wu, Xiaoqun; Feng, Hui; Lu, Jun-an; Xu, Yuhua

2016-05-01

The interaction topology among the constituents of a complex network plays a crucial role in the network’s evolutionary mechanisms and functional behaviors. However, some network topologies are usually unknown or uncertain. Meanwhile, coupling delays are ubiquitous in various man-made and natural networks. Hence, it is necessary to gain knowledge of the whole or partial topology of a complex dynamical network by taking into consideration communication delay. In this paper, topology identification of complex dynamical networks is investigated via generalized synchronization of a two-layer network. Particularly, based on the LaSalle-type invariance principle of stochastic differential delay equations, an adaptive control technique is proposed by constructing an auxiliary layer and designing proper control input and updating laws so that the unknown topology can be recovered upon successful generalized synchronization. Numerical simulations are provided to illustrate the effectiveness of the proposed method. The technique provides a certain theoretical basis for topology inference of complex networks. In particular, when the considered network is composed of systems with high-dimension or complicated dynamics, a simpler response layer can be constructed, which is conducive to circuit design. Moreover, it is practical to take into consideration perturbations caused by control input. Finally, the method is applicable to infer topology of a subnetwork embedded within a complex system and locate hidden sources. We hope the results can provide basic insight into further research endeavors on understanding practical and economical topology inference of networks.

Troxerutin attenuates diet-induced oxidative stress, impairment of mitochondrial biogenesis and respiratory chain complexes in mice heart.

PubMed

Rajagopalan, Geetha; Chandrasekaran, Sathiya Priya; Carani Venkatraman, Anuradha

2017-01-01

Mitochondrial abnormality is thought to play a key role in cardiac disease originating from the metabolic syndrome (MS). We evaluated the effect of troxerutin (TX), a semi-synthetic derivative of the natural bioflavanoid rutin, on the respiratory chain complex activity, oxidative stress, mitochondrial biogenesis and dynamics in heart of high fat, high fructose diet (HFFD) -induced mouse model of MS. Adult male Mus musculus mice of body weight 25-30 g were fed either control diet or HFFD for 60 days. Mice from each dietary regimen were divided into two groups on the 16th day and were treated or untreated with TX (150 mg/kg body weight [bw], per oral) for the next 45 days. At the end of experimental period, respiratory chain complex activity, uncoupling proteins (UCP)-2 and -3, mtDNA content, mitochondrial biogenesis and dynamics, oxidative stress markers and reactive oxygen species (ROS) generation were analyzed. Reduced mtDNA abundance with alterations in the expression of genes related to mitochondrial biogenesis and fission and fusion processes were observed in HFFD-fed mice. Disorganized and smaller mitochondria, reduction in complexes I, III and IV activities (by about 55%) and protein levels of UCP-2 (52%) and UCP-3 (46%) were noted in these mice. TX administration suppressed oxidative stress, improved the oxidative capacity and biogenesis and restored fission/fusion imbalance in the cardiac mitochondria of HFFD-fed mice. TX protects the myocardium by modulating the putative molecules of mitochondrial biogenesis and dynamics and by its anti-oxidant function in a mouse model of MS. © 2016 John Wiley & Sons Australia, Ltd.

Hydrological Dynamics In High Mountain Catchment Areas of Central Norway

NASA Astrophysics Data System (ADS)

Löffler, J.; Rössler, O.

Large-scaled landscape structure is regarded as a mosaic of ecotopes where pro- cess dynamics of water and energy fluxes are analysed due to its effects on ecosys- tem functioning. The investigations have been carried out in the continental most Vågå/Oppland high mountains in central Norway since 1994 (LÖFFLER WUN- DRAM 1999, 2000, 2001). Additionally, comparable investigations started in 2000 dealing with the oceanic high mountain landscapes on same latitudes (LÖFFLER et al. 2001). The theoretical and methodological framework of the project is given by the Landscape-Ecological Complex Analysis (MOSIMANN 1984, 1985) and its variations due to technical and principle methodical challenges in this high moun- tain landscape (KÖHLER et al. 1994, LÖFFLER 1998). The aim of the project is to characterize high mountain ecosystem structure, functioning and dynamics within small catchment areas, that are chosen in two different altitudinal belts each in the eastern continental and the western oceanic region of central Norway. In the frame of this research project hydrological and meteorological measurements on ground water, percolation and soil moisture dynamics as well as on evaporation, air humidity and air-, surface- and soil-temperatures have been conducted. On the basis of large-scaled landscape-ecological mappings (LÖFFLER 1997) one basic meteorological station and several major data logger run stations have been installed in representative sites of each two catchment areas in the low and mid alpine belts of the investigation re- gions (JUNG et al. 1997, LÖFFLER WUNDRAM 1997). Moreover, spatial differ- entiations of groundwater level, soil moisture and temperature profiles have been in- vestigated by means of hand held measurements at different times of the day, during different climatic situations and different seasons. Daily and annual air-, surface- and soil-temperature dynamics are demonstrated by means of thermoisopleth-diagrams for different types of ecotopes of the different altitudinal belts. The local differences of temperature dynamics are illustrated in a map as an example of the low alpine al- titudinal belt showing a 4-dimensional characterization (in space and time) of high mountain ecosystem functioning. Hydrological aspects derived from those results are presented showing the large-scaled hydrological dynamics of high mountain catch- ment basins in central Norway. The results of the process analysis of hydrological dynamics in the central Norwegian high mountains are discussed within the frame of 1 investigations on altitudinal changes of mountain ecosystem structure and function- ing (LÖFFLER WUNDRAM [in print]). The poster illustrates the theoretical and methodological conception, methods and techniques, examples from complex data material as well as general outcomes of the project (RÖSSLER [in prep.]. 2

Assessing the Extent of Influence Subglacial Hydrology Has on Dynamic Ice Sheet Behavior

NASA Astrophysics Data System (ADS)

Babonis, G. S.; Csatho, B. M.

2012-12-01

Numerous recent studies have done an excellent job capturing and quantifying the complex pattern of dynamic changes of the Greenland Ice Sheet (GrIS) over the past several decades. The timing of changes in ice velocities and mass balance indicate that the mechanisms controlling these behaviors, both external and internal, act over variable spatial and temporal regimes, can change in rapid and complex fashion, and have significant effect on ice sheet behavior as well as sea level rise. With roughly half of the estimated ice loss from the GrIS attributed to dynamic processes, these changes account for about 250 Gt/yr (2003-2008), equivalence to 0.6 mm/yr sea level rise. One of the primary influences of dynamic ice behavior is ice sheet hydrology, including the storage and transport of water from the supraglacial to subglacial environment, and the subsequent development of water transport pathways, thus demonstrating the need for further characterization of the subglacial environment. Enhanced dynamic flow of ice due to the influence of meltwater distribution on the subglacial environment has been reported, including In-SAR observations of large velocity increases over short periods of time, suggesting regions where dynamic changes are likely being caused by changes in hydrology. Additionally, building upon the 1993-2011 laser altimetry record, analyzed by our Surface Elevation Reconstruction And Change detection (SERAC) procedure, we have detected complex patterns of rapid thickening and thinning patterns over several outlet glaciers. This study presents a comprehensive investigation of hydrologic control on dynamic glacier behavior for several key sites in Greenland. We combine a high resolution surface digital elevation model (DEM) derived by fusing space- and airborne laser altimetry observations and SPIRIT SPOT DEMs, with a high resolution, hydrologically-corrected bedrock DEM derived from a combination of CResIS and Operation Icebridge ice penetrating radar data for generating potentiometric maps for each region of interest. Using these potentiometric maps, along with surficial DEMs, supra- and subglacial routing paths, as well as potential sites for discrete supraglacial hydrologic input sources are identified. Comparison of hydrologic drainage networks with the spatial distribution of recent rapid dynamic changes detected by altimetry allows for the assessment of the extent of influence that subglacial hydrology has on ice sheet behavior.

Heterogeneous delivering capability promotes traffic efficiency in complex networks

NASA Astrophysics Data System (ADS)

Zhu, Yan-Bo; Guan, Xiang-Min; Zhang, Xue-Jun

2015-12-01

Traffic is one of the most fundamental dynamical processes in networked systems. With the homogeneous delivery capability of nodes, the global dynamic routing strategy proposed by Ling et al. [Phys. Rev. E81, 016113 (2010)] adequately uses the dynamic information during the process and thus it can reach a quite high network capacity. In this paper, based on the global dynamic routing strategy, we proposed a heterogeneous delivery allocation strategy of nodes on scale-free networks with consideration of nodes degree. It is found that the network capacity as well as some other indexes reflecting transportation efficiency are further improved. Our work may be useful for the design of more efficient routing strategies in communication or transportation systems.

Impact of seasonality upon the dynamics of a novel pathogen in a seabird colony

NASA Astrophysics Data System (ADS)

O'Regan, S. M.

2008-11-01

A seasonally perturbed variant of the basic Susceptible-Infected-Recovered (SIR) model in epidemiology is considered in this paper. The effect of seasonality on an IR system of ordinary differential equations describing the dynamics of a novel pathogen, e.g., highly pathogenic avian influenza, in a seabird colony is investigated. The method of Lyapunov functions is used to determine the long-term behaviour of this system. Numerical simulations of the seasonally perturbed IR system indicate that the system exhibits complex dynamics as the amplitude of the seasonal perturbation term is increased. These findings suggest that seasonality may exert a considerable effect on the dynamics of epidemics in a seabird colony.

Changes in conformational dynamics of basic side chains upon protein-DNA association.

PubMed

Esadze, Alexandre; Chen, Chuanying; Zandarashvili, Levani; Roy, Sourav; Pettitt, B Montgometry; Iwahara, Junji

2016-08-19

Basic side chains play major roles in recognition of nucleic acids by proteins. However, dynamic properties of these positively charged side chains are not well understood. In this work, we studied changes in conformational dynamics of basic side chains upon protein-DNA association for the zinc-finger protein Egr-1. By nuclear magnetic resonance (NMR) spectroscopy, we characterized the dynamics of all side-chain cationic groups in the free protein and in the complex with target DNA. Our NMR order parameters indicate that the arginine guanidino groups interacting with DNA bases are strongly immobilized, forming rigid interfaces. Despite the strong short-range electrostatic interactions, the majority of the basic side chains interacting with the DNA phosphates exhibited high mobility, forming dynamic interfaces. In particular, the lysine side-chain amino groups exhibited only small changes in the order parameters upon DNA-binding. We found a similar trend in the molecular dynamics (MD) simulations for the free Egr-1 and the Egr-1-DNA complex. Using the MD trajectories, we also analyzed side-chain conformational entropy. The interfacial arginine side chains exhibited substantial entropic loss upon binding to DNA, whereas the interfacial lysine side chains showed relatively small changes in conformational entropy. These data illustrate different dynamic characteristics of the interfacial arginine and lysine side chains. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Dynamics of nanoparticle-protein corona complex formation: analytical results from population balance equations.

PubMed

Darabi Sahneh, Faryad; Scoglio, Caterina; Riviere, Jim

2013-01-01

Nanoparticle-protein corona complex formation involves absorption of protein molecules onto nanoparticle surfaces in a physiological environment. Understanding the corona formation process is crucial in predicting nanoparticle behavior in biological systems, including applications of nanotoxicology and development of nano drug delivery platforms. This paper extends the modeling work in to derive a mathematical model describing the dynamics of nanoparticle corona complex formation from population balance equations. We apply nonlinear dynamics techniques to derive analytical results for the composition of nanoparticle-protein corona complex, and validate our results through numerical simulations. The model presented in this paper exhibits two phases of corona complex dynamics. In the first phase, proteins rapidly bind to the free surface of nanoparticles, leading to a metastable composition. During the second phase, continuous association and dissociation of protein molecules with nanoparticles slowly changes the composition of the corona complex. Given sufficient time, composition of the corona complex reaches an equilibrium state of stable composition. We find analytical approximate formulae for metastable and stable compositions of corona complex. Our formulae are very well-structured to clearly identify important parameters determining corona composition. The dynamics of biocorona formation constitute vital aspect of interactions between nanoparticles and living organisms. Our results further understanding of these dynamics through quantitation of experimental conditions, modeling results for in vitro systems to better predict behavior for in vivo systems. One potential application would involve a single cell culture medium related to a complex protein medium, such as blood or tissue fluid.

Patient-Specific Computational Modeling of Human Phonation

NASA Astrophysics Data System (ADS)

Xue, Qian; Zheng, Xudong; University of Maine Team

2013-11-01

Phonation is a common biological process resulted from the complex nonlinear coupling between glottal aerodynamics and vocal fold vibrations. In the past, the simplified symmetric straight geometric models were commonly employed for experimental and computational studies. The shape of larynx lumen and vocal folds are highly three-dimensional indeed and the complex realistic geometry produces profound impacts on both glottal flow and vocal fold vibrations. To elucidate the effect of geometric complexity on voice production and improve the fundamental understanding of human phonation, a full flow-structure interaction simulation is carried out on a patient-specific larynx model. To the best of our knowledge, this is the first patient-specific flow-structure interaction study of human phonation. The simulation results are well compared to the established human data. The effects of realistic geometry on glottal flow and vocal fold dynamics are investigated. It is found that both glottal flow and vocal fold dynamics present a high level of difference from the previous simplified model. This study also paved the important step toward the development of computer model for voice disease diagnosis and surgical planning. The project described was supported by Grant Number ROlDC007125 from the National Institute on Deafness and Other Communication Disorders (NIDCD).

New understanding of rhizosphere processes enabled by advances in molecular and spatially resolved techniques

DOE PAGES

Hess, Nancy J.; Pasa-Tolic, Ljiljana; Bailey, Vanessa L.; ...

2017-04-12

Understanding the role played by microorganisms within soil systems is challenged by the unique intersection of physics, chemistry, mineralogy and biology in fostering habitat for soil microbial communities. To address these challenges will require observations across multiple spatial and temporal scales to capture the dynamics and emergent behavior from complex and interdependent processes. The heterogeneity and complexity of the rhizosphere require advanced techniques that press the simultaneous frontiers of spatial resolution, analyte sensitivity and specificity, reproducibility, large dynamic range, and high throughput. Fortunately many exciting technical advancements are now available to inform and guide the development of new hypotheses. Themore » aim of this Special issue is to provide a holistic view of the rhizosphere in the perspective of modern molecular biology methodologies that enabled a highly-focused, detailed view on the processes in the rhizosphere, including numerous, strong and complex interactions between plant roots, soil constituents and microorganisms. We discuss the current rhizosphere research challenges and knowledge gaps, as well as perspectives and approaches using newly available state-of-the-art toolboxes. These new approaches and methodologies allow the study of rhizosphere processes and properties, and rhizosphere as a central component of ecosystems and biogeochemical cycles.« less

New understanding of rhizosphere processes enabled by advances in molecular and spatially resolved techniques

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

Hess, Nancy J.; Paša-Tolić, Ljiljana; Bailey, Vanessa L.

Understanding the role played by microorganisms within soil systems is challenged by the unique intersection of physics, chemistry, mineralogy and biology in fostering habitat for soil microbial communities. To address these challenges will require observations across multiple spatial and temporal scales to capture the dynamics and emergent behavior from complex and interdependent processes. The heterogeneity and complexity of the rhizosphere require advanced techniques that press the simultaneous frontiers of spatial resolution, analyte sensitivity and specificity, reproducibility, large dynamic range, and high throughput. Fortunately many exciting technical advancements are now available to inform and guide the development of new hypotheses. Themore » aim of this Special issue is to provide a holistic view of the rhizosphere in the perspective of modern molecular biology methodologies that enabled a highly-focused, detailed view on the processes in the rhizosphere, including numerous, strong and complex interactions between plant roots, soil constituents and microorganisms. We discuss the current rhizosphere research challenges and knowledge gaps, as well as perspectives and approaches using newly available state-of-the-art toolboxes. These new approaches and methodologies allow the study of rhizosphere processes and properties, and rhizosphere as a central component of ecosystems and biogeochemical cycles.« less

Photophysical dynamics of the efficient emission and photosensitization of [Ir(pqi)2(NN)]+ complexes.

PubMed

Zanoni, Kassio P S; Ito, Akitaka; Grüner, Malte; Murakami Iha, Neyde Y; de Camargo, Andrea S S

2018-01-23

The photophysical dynamics of three complexes in the highly-emissive [Ir(pqi) 2 (NN)] + series were investigated aiming at unique photophysical features and applications in light-emitting and singlet oxygen sensitizing research fields. Rational elucidation and Franck-Condon analyses of the observed emission spectra in nitrile solutions at 298 and 77 K reveal the true emissive nature of the lowest-lying triplet excited state (T 1 ), consisting of a hybrid 3 MLCT/LC Ir(pqi)→pqi state. Emissive deactivations from T 1 occur mainly by very intense, yellow-orange phosphorescence with high quantum yields and radiative rates. The emission nature experimentally verified is corroborated by theoretical calculations (TD-DFT), with T 1 arising from a mixing of several transitions induced by the spin-orbit coupling, majorly ascribed to 3 MLCT/LC Ir(pqi)→pqi and increasing contributions of 3 MLCT/LLCT Ir(pqi)→NN . The microsecond-lived emission of T 1 is rapidly quenched by molecular oxygen, with an efficient generation of singlet oxygen. Our findings show that the photophysics of [Ir(pqi) 2 (NN)][PF 6 ] complexes is suitable for many applications, from the active layer of electroluminescent devices to photosensitizers for photodynamic therapy and theranostics.

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

Hess, Nancy J.; Pasa-Tolic, Ljiljana; Bailey, Vanessa L.

Understanding the role played by microorganisms within soil systems is challenged by the unique intersection of physics, chemistry, mineralogy and biology in fostering habitat for soil microbial communities. To address these challenges will require observations across multiple spatial and temporal scales to capture the dynamics and emergent behavior from complex and interdependent processes. The heterogeneity and complexity of the rhizosphere require advanced techniques that press the simultaneous frontiers of spatial resolution, analyte sensitivity and specificity, reproducibility, large dynamic range, and high throughput. Fortunately many exciting technical advancements are now available to inform and guide the development of new hypotheses. Themore » aim of this Special issue is to provide a holistic view of the rhizosphere in the perspective of modern molecular biology methodologies that enabled a highly-focused, detailed view on the processes in the rhizosphere, including numerous, strong and complex interactions between plant roots, soil constituents and microorganisms. We discuss the current rhizosphere research challenges and knowledge gaps, as well as perspectives and approaches using newly available state-of-the-art toolboxes. These new approaches and methodologies allow the study of rhizosphere processes and properties, and rhizosphere as a central component of ecosystems and biogeochemical cycles.« less

Probing the Energetics of Antigen-Antibody Recognition by Titration Microcalorimetry

PubMed

Jelesarov; Leder; Bosshard

1996-06-01

Our understanding of the energetics that govern antigen-antibody recognition lags behind the increasingly rapid accumulation of structural information on antigen-antibody complexes. Thanks to the development of highly sensitive microcalorimeters, the thermodynamic parameters of antigen-antibody interactions can now be measured with precision and using only nanomole quantities of protein. The method of choice is isothermal titration calorimetry, in which a solution of the antibody (or antigen) is titrated with small aliquots of the antigen (or antibody) and the heat change accompanying the formation of the antigen-antibody complex is measured with a sensitivity as high as 0.1 μcal s-1. The free energy of binding (DeltaG), the binding enthalpy (DeltaH), and the binding entropy (DeltaS) are usually obtained from a single experiment, and no spectroscopic or radioactive label must be introduced into the antigen or antibody. The often large and negative change in heat capacity (DeltaCp) accompanying the formation of an antigen-antibody complex is obtained from DeltaH measured at different temperatures. The basic theory and the principle of the measurements are reviewed and illustrated by examples. The thermodynamic parameters relate to the dynamic physical forces that govern the association of the freely moving antigen and antibody into a well-structured and unique complex. This information complements the static picture of the antigen-antibody complex that results from X-ray diffraction analysis. Attempts to correlate dynamic and static aspects are discussed briefly.

Force and Stress along Simulated Dissociation Pathways of Cucurbituril-Guest Systems.

PubMed

Velez-Vega, Camilo; Gilson, Michael K

2012-03-13

The field of host-guest chemistry provides computationally tractable yet informative model systems for biomolecular recognition. We applied molecular dynamics simulations to study the forces and mechanical stresses associated with forced dissociation of aqueous cucurbituril-guest complexes with high binding affinities. First, the unbinding transitions were modeled with constant velocity pulling (steered dynamics) and a soft spring constant, to model atomic force microscopy (AFM) experiments. The computed length-force profiles yield rupture forces in good agreement with available measurements. We also used steered dynamics with high spring constants to generate paths characterized by a tight control over the specified pulling distance; these paths were then equilibrated via umbrella sampling simulations and used to compute time-averaged mechanical stresses along the dissociation pathways. The stress calculations proved to be informative regarding the key interactions determining the length-force profiles and rupture forces. In particular, the unbinding transition of one complex is found to be a stepwise process, which is initially dominated by electrostatic interactions between the guest's ammoniums and the host's carbonyl groups, and subsequently limited by the extraction of the guest's bulky bicyclooctane moiety; the latter step requires some bond stretching at the cucurbituril's extraction portal. Conversely, the dissociation of a second complex with a more slender guest is mainly driven by successive electrostatic interactions between the different guest's ammoniums and the host's carbonyl groups. The calculations also provide information on the origins of thermodynamic irreversibilities in these forced dissociation processes.

Dynamic stiffness characteristics of high eccentricity ratio bearings and seals by perturbation testing

NASA Technical Reports Server (NTRS)

Bently, D. E.; Muszynska, A.

1984-01-01

The complex behavior of cylindrical bearings and seals that are statically loaded to eccentricities in excess of 0.7 are examined. The stiffness algorithms as a function of static load are developed from perturbation methodology by empirical modeling.

Learning Kinetic Monte Carlo Models of Condensed Phase High Temperature Chemistry from Molecular Dynamics

NASA Astrophysics Data System (ADS)

Yang, Qian; Sing-Long, Carlos; Chen, Enze; Reed, Evan

2017-06-01

Complex chemical processes, such as the decomposition of energetic materials and the chemistry of planetary interiors, are typically studied using large-scale molecular dynamics simulations that run for weeks on high performance parallel machines. These computations may involve thousands of atoms forming hundreds of molecular species and undergoing thousands of reactions. It is natural to wonder whether this wealth of data can be utilized to build more efficient, interpretable, and predictive models. In this talk, we will use techniques from statistical learning to develop a framework for constructing Kinetic Monte Carlo (KMC) models from molecular dynamics data. We will show that our KMC models can not only extrapolate the behavior of the chemical system by as much as an order of magnitude in time, but can also be used to study the dynamics of entirely different chemical trajectories with a high degree of fidelity. Then, we will discuss three different methods for reducing our learned KMC models, including a new and efficient data-driven algorithm using L1-regularization. We demonstrate our framework throughout on a system of high-temperature high-pressure liquid methane, thought to be a major component of gas giant planetary interiors.

Sterols in spermatogenesis and sperm maturation

PubMed Central

Keber, Rok; Rozman, Damjana; Horvat, Simon

2013-01-01

Mammalian spermatogenesis is a complex developmental program in which a diploid progenitor germ cell transforms into highly specialized spermatozoa. One intriguing aspect of sperm production is the dynamic change in membrane lipid composition that occurs throughout spermatogenesis. Cholesterol content, as well as its intermediates, differs vastly between the male reproductive system and nongonadal tissues. Accumulation of cholesterol precursors such as testis meiosis-activating sterol and desmosterol is observed in testes and spermatozoa from several mammalian species. Moreover, cholesterogenic genes, especially meiosis-activating sterol-producing enzyme cytochrome P450 lanosterol 14α-demethylase, display stage-specific expression patterns during spermatogenesis. Discrepancies in gene expression patterns suggest a complex temporal and cell-type specific regulation of sterol compounds during spermatogenesis, which also involves dynamic interactions between germ and Sertoli cells. The functional importance of sterol compounds in sperm production is further supported by the modulation of sterol composition in spermatozoal membranes during epididymal transit and in the female reproductive tract, which is a prerequisite for successful fertilization. However, the exact role of sterols in male reproduction is unknown. This review discusses sterol dynamics in sperm maturation and describes recent methodological advances that will help to illuminate the complexity of sperm formation and function. PMID:23093550

Molecular Dynamics of the ZIKA Virus NS3 Helicase

NASA Astrophysics Data System (ADS)

Raubenolt, Bryan; Rick, Steven; The Rick Group Team

The recent outbreaks of the ZIKA virus (ZIKV) and its connection to microcephaly in newborns has raised its awareness as a global threat and many scientific research efforts are currently underway in attempt to create a vaccine. Molecular Dynamics is a powerful method of investigating the physical behavior of protein complexes. ZIKV is comprised of 3 structural and 7 nonstructural proteins. The NS3 helicase protein appears to play a significant role in the replication complex and its inhibition could be a crucial source of antiviral drug design. This research primarily focuses on studying the structural dynamics, over the course of few hundred nanoseconds, of NS3 helicase in the free state, as well as in complex form with human ssRNA, ATP, and an analogue of GTP. RMSD and RMSF plots of each simulation will provide details on the forces involved in the overall stability of the active and inactive states. Furthermore, free energy calculations on a per residue level will reveal the most interactive residues between states and ultimately the primary driving force behind these interactions. Together these analyses will provide highly relevant information on the binding surface chemistry and thus serve as the basis for potential drug design.

Insights into the functional role of protonation states in the HIV-1 protease-BEA369 complex: molecular dynamics simulations and free energy calculations.

PubMed

Chen, Jianzhong; Yang, Maoyou; Hu, Guodong; Shi, Shuhua; Yi, Changhong; Zhang, Qinggang

2009-10-01

The molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) method combined with molecular dynamics (MD) simulations were used to investigate the functional role of protonation in human immunodeficiency virus type 1 (HIV-1) protease complexed with the inhibitor BEA369. Our results demonstrate that protonation of two aspartic acids (Asp25/Asp25') has a strong influence on the dynamics behavior of the complex, the binding free energy of BEA369, and inhibitor-residue interactions. Relative binding free energies calculated using the MM-PBSA method show that protonation of Asp25 results in the strongest binding of BEA369 to HIV-1 protease. Inhibitor-residue interactions computed by the theory of free energy decomposition also indicate that protonation of Asp25 has the most favorable effect on binding of BEA369. In addition, hydrogen-bond analysis based on the trajectories of the MD simulations shows that protonation of Asp25 strongly influences the water-mediated link of a conserved water molecule, Wat301. We expect that the results of this study will contribute significantly to binding calculations for BEA369, and to the design of high affinity inhibitors.

Research on simulation technology of full-path infrared tail flame tracking of photoelectric theodolite in complicated environment

NASA Astrophysics Data System (ADS)

Wu, Hai-ying; Zhang, San-xi; Liu, Biao; Yue, Peng; Weng, Ying-hui

2018-02-01

The photoelectric theodolite is an important scheme to realize the tracking, detection, quantitative measurement and performance evaluation of weapon systems in ordnance test range. With the improvement of stability requirements for target tracking in complex environment, infrared scene simulation with high sense of reality and complex interference has become an indispensable technical way to evaluate the track performance of photoelectric theodolite. And the tail flame is the most important infrared radiation source of the weapon system. The dynamic tail flame with high reality is a key element for the photoelectric theodolite infrared scene simulation and imaging tracking test. In this paper, an infrared simulation method for the full-path tracking of tail flame by photoelectric theodolite is proposed aiming at the faint boundary, irregular, multi-regulated points. In this work, real tail images are employed. Simultaneously, infrared texture conversion technology is used to generate DDS texture for a particle system map. Thus, dynamic real-time tail flame simulation results with high fidelity from the theodolite perspective can be gained in the tracking process.

Multiscale X-ray and Proton Imaging of Bismuth-Tin Solidification

NASA Astrophysics Data System (ADS)

Gibbs, P. J.; Imhoff, S. D.; Morris, C. L.; Merrill, F. E.; Wilde, C. H.; Nedrow, P.; Mariam, F. G.; Fezzaa, K.; Lee, W.-K.; Clarke, A. J.

2014-08-01

The formation of structural patterns during metallic solidification is complex and multiscale in nature, ranging from the nanometer scale, where solid-liquid interface properties are important, to the macroscale, where casting mold filling and intended heat transfer are crucial. X-ray and proton imaging can directly interrogate structure, solute, and fluid flow development in metals from the microscale to the macroscale. X-rays permit high spatio-temporal resolution imaging of microscopic solidification dynamics in thin metal sections. Similarly, high-energy protons permit imaging of mesoscopic and macroscopic solidification dynamics in large sample volumes. In this article, we highlight multiscale x-ray and proton imaging of bismuth-tin alloy solidification to illustrate dynamic measurement of crystal growth rates and solute segregation profiles that can be that can be acquired using these techniques.

The dynamic relationship between cerebellar Purkinje cell simple spikes and the spikelet number of complex spikes

PubMed Central

Burroughs, Amelia; Wise, Andrew K.; Xiao, Jianqiang; Houghton, Conor; Tang, Tianyu; Suh, Colleen Y.; Lang, Eric J.

2016-01-01

Key points Purkinje cells are the sole output of the cerebellar cortex and fire two distinct types of action potential: simple spikes and complex spikes.Previous studies have mainly considered complex spikes as unitary events, even though the waveform is composed of varying numbers of spikelets.The extent to which differences in spikelet number affect simple spike activity (and vice versa) remains unclear.We found that complex spikes with greater numbers of spikelets are preceded by higher simple spike firing rates but, following the complex spike, simple spikes are reduced in a manner that is graded with spikelet number.This dynamic interaction has important implications for cerebellar information processing, and suggests that complex spike spikelet number may maintain Purkinje cells within their operational range. Abstract Purkinje cells are central to cerebellar function because they form the sole output of the cerebellar cortex. They exhibit two distinct types of action potential: simple spikes and complex spikes. It is widely accepted that interaction between these two types of impulse is central to cerebellar cortical information processing. Previous investigations of the interactions between simple spikes and complex spikes have mainly considered complex spikes as unitary events. However, complex spikes are composed of an initial large spike followed by a number of secondary components, termed spikelets. The number of spikelets within individual complex spikes is highly variable and the extent to which differences in complex spike spikelet number affects simple spike activity (and vice versa) remains poorly understood. In anaesthetized adult rats, we have found that Purkinje cells recorded from the posterior lobe vermis and hemisphere have high simple spike firing frequencies that precede complex spikes with greater numbers of spikelets. This finding was also evident in a small sample of Purkinje cells recorded from the posterior lobe hemisphere in awake cats. In addition, complex spikes with a greater number of spikelets were associated with a subsequent reduction in simple spike firing rate. We therefore suggest that one important function of spikelets is the modulation of Purkinje cell simple spike firing frequency, which has implications for controlling cerebellar cortical output and motor learning. PMID:27265808

Key Structures and Interactions for Binding of Mycobacterium tuberculosis Protein Kinase B Inhibitors from Molecular Dynamics Simulation.

PubMed

Punkvang, Auradee; Kamsri, Pharit; Saparpakorn, Patchreenart; Hannongbua, Supa; Wolschann, Peter; Irle, Stephan; Pungpo, Pornpan

2015-07-01

Substituted aminopyrimidine inhibitors have recently been introduced as antituberculosis agents. These inhibitors show impressive activity against protein kinase B, a Ser/Thr protein kinase that is essential for cell growth of M. tuberculosis. However, up to now, X-ray structures of the protein kinase B enzyme complexes with the substituted aminopyrimidine inhibitors are currently unavailable. Consequently, structural details of their binding modes are questionable, prohibiting the structural-based design of more potent protein kinase B inhibitors in the future. Here, molecular dynamics simulations, in conjunction with molecular mechanics/Poisson-Boltzmann surface area binding free-energy analysis, were employed to gain insight into the complex structures of the protein kinase B inhibitors and their binding energetics. The complex structures obtained by the molecular dynamics simulations show binding free energies in good agreement with experiment. The detailed analysis of molecular dynamics results shows that Glu93, Val95, and Leu17 are key residues responsible to the binding of the protein kinase B inhibitors. The aminopyrazole group and the pyrimidine core are the crucial moieties of substituted aminopyrimidine inhibitors for interaction with the key residues. Our results provide a structural concept that can be used as a guide for the future design of protein kinase B inhibitors with highly increased antagonistic activity. © 2014 John Wiley & Sons A/S.

Fluctuation-Driven Neural Dynamics Reproduce Drosophila Locomotor Patterns

PubMed Central

Cruchet, Steeve; Gustafson, Kyle; Benton, Richard; Floreano, Dario

2015-01-01

The neural mechanisms determining the timing of even simple actions, such as when to walk or rest, are largely mysterious. One intriguing, but untested, hypothesis posits a role for ongoing activity fluctuations in neurons of central action selection circuits that drive animal behavior from moment to moment. To examine how fluctuating activity can contribute to action timing, we paired high-resolution measurements of freely walking Drosophila melanogaster with data-driven neural network modeling and dynamical systems analysis. We generated fluctuation-driven network models whose outputs—locomotor bouts—matched those measured from sensory-deprived Drosophila. From these models, we identified those that could also reproduce a second, unrelated dataset: the complex time-course of odor-evoked walking for genetically diverse Drosophila strains. Dynamical models that best reproduced both Drosophila basal and odor-evoked locomotor patterns exhibited specific characteristics. First, ongoing fluctuations were required. In a stochastic resonance-like manner, these fluctuations allowed neural activity to escape stable equilibria and to exceed a threshold for locomotion. Second, odor-induced shifts of equilibria in these models caused a depression in locomotor frequency following olfactory stimulation. Our models predict that activity fluctuations in action selection circuits cause behavioral output to more closely match sensory drive and may therefore enhance navigation in complex sensory environments. Together these data reveal how simple neural dynamics, when coupled with activity fluctuations, can give rise to complex patterns of animal behavior. PMID:26600381

Efficient statistically accurate algorithms for the Fokker-Planck equation in large dimensions

NASA Astrophysics Data System (ADS)

Chen, Nan; Majda, Andrew J.

2018-02-01

Solving the Fokker-Planck equation for high-dimensional complex turbulent dynamical systems is an important and practical issue. However, most traditional methods suffer from the curse of dimensionality and have difficulties in capturing the fat tailed highly intermittent probability density functions (PDFs) of complex systems in turbulence, neuroscience and excitable media. In this article, efficient statistically accurate algorithms are developed for solving both the transient and the equilibrium solutions of Fokker-Planck equations associated with high-dimensional nonlinear turbulent dynamical systems with conditional Gaussian structures. The algorithms involve a hybrid strategy that requires only a small number of ensembles. Here, a conditional Gaussian mixture in a high-dimensional subspace via an extremely efficient parametric method is combined with a judicious non-parametric Gaussian kernel density estimation in the remaining low-dimensional subspace. Particularly, the parametric method provides closed analytical formulae for determining the conditional Gaussian distributions in the high-dimensional subspace and is therefore computationally efficient and accurate. The full non-Gaussian PDF of the system is then given by a Gaussian mixture. Different from traditional particle methods, each conditional Gaussian distribution here covers a significant portion of the high-dimensional PDF. Therefore a small number of ensembles is sufficient to recover the full PDF, which overcomes the curse of dimensionality. Notably, the mixture distribution has significant skill in capturing the transient behavior with fat tails of the high-dimensional non-Gaussian PDFs, and this facilitates the algorithms in accurately describing the intermittency and extreme events in complex turbulent systems. It is shown in a stringent set of test problems that the method only requires an order of O (100) ensembles to successfully recover the highly non-Gaussian transient PDFs in up to 6 dimensions with only small errors.

Probing the structural dynamics of the CRISPR-Cas9 RNA-guided DNA-cleavage system by coarse-grained modeling.

PubMed

Zheng, Wenjun

2017-02-01

In the adaptive immune systems of many bacteria and archaea, the Cas9 endonuclease forms a complex with specific guide/scaffold RNA to identify and cleave complementary target sequences in foreign DNA. This DNA targeting machinery has been exploited in numerous applications of genome editing and transcription control. However, the molecular mechanism of the Cas9 system is still obscure. Recently, high-resolution structures have been solved for Cas9 in different structural forms (e.g., unbound forms, RNA-bound binary complexes, and RNA-DNA-bound tertiary complexes, corresponding to an inactive state, a pre-target-bound state, and a cleavage-competent or product state), which offered key structural insights to the Cas9 mechanism. To further probe the structural dynamics of Cas9 interacting with RNA and DNA at the amino-acid level of details, we have performed systematic coarse-grained modeling using an elastic network model and related analyses. Our normal mode analysis predicted a few key modes of collective motions that capture the observed conformational changes featuring large domain motions triggered by binding of RNA and DNA. Our flexibility analysis identified specific regions with high or low flexibility that coincide with key functional sites (such as DNA/RNA-binding sites, nuclease cleavage sites, and key hinges). We also identified a small set of hotspot residues that control the energetics of functional motions, which overlap with known functional sites and offer promising targets for future mutagenesis efforts to improve the specificity of Cas9. Finally, we modeled the conformational transitions of Cas9 from the unbound form to the binary complex and then the tertiary complex, and predicted a distinct sequence of domain motions. In sum, our findings have offered rich structural and dynamic details relevant to the Cas9 machinery, and will guide future investigation and engineering of the Cas9 systems. Proteins 2017; 85:342-353. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Transcription closed and open complex dynamics studies reveal balance between genetic determinants and co-factors

NASA Astrophysics Data System (ADS)

Sala, Adrien; Shoaib, Muhammad; Anufrieva, Olga; Mutharasu, Gnanavel; Jahan Hoque, Rawnak; Yli-Harja, Olli; Kandhavelu, Meenakshisundaram

2015-05-01

In E. coli, promoter closed and open complexes are key steps in transcription initiation, where magnesium-dependent RNA polymerase catalyzes RNA synthesis. However, the exact mechanism of initiation remains to be fully elucidated. Here, using single mRNA detection and dual reporter studies, we show that increased intracellular magnesium concentration affects Plac initiation complex formation resulting in a highly dynamic process over the cell growth phases. Mg2+ regulates transcription transition, which modulates bimodality of mRNA distribution in the exponential phase. We reveal that Mg2+ regulates the size and frequency of the mRNA burst by changing the open complex duration. Moreover, increasing magnesium concentration leads to higher intrinsic and extrinsic noise in the exponential phase. RNAP-Mg2+ interaction simulation reveals critical movements creating a shorter contact distance between aspartic acid residues and Nucleotide Triphosphate residues and increasing electrostatic charges in the active site. Our findings provide unique biophysical insights into the balanced mechanism of genetic determinants and magnesium ion in transcription initiation regulation during cell growth.

Computational Workbench for Multibody Dynamics

NASA Technical Reports Server (NTRS)

Edmonds, Karina

2007-01-01

PyCraft is a computer program that provides an interactive, workbenchlike computing environment for developing and testing algorithms for multibody dynamics. Examples of multibody dynamic systems amenable to analysis with the help of PyCraft include land vehicles, spacecraft, robots, and molecular models. PyCraft is based on the Spatial-Operator- Algebra (SOA) formulation for multibody dynamics. The SOA operators enable construction of simple and compact representations of complex multibody dynamical equations. Within the Py-Craft computational workbench, users can, essentially, use the high-level SOA operator notation to represent the variety of dynamical quantities and algorithms and to perform computations interactively. PyCraft provides a Python-language interface to underlying C++ code. Working with SOA concepts, a user can create and manipulate Python-level operator classes in order to implement and evaluate new dynamical quantities and algorithms. During use of PyCraft, virtually all SOA-based algorithms are available for computational experiments.

Reservoir Computing Properties of Neural Dynamics in Prefrontal Cortex

PubMed Central

Procyk, Emmanuel; Dominey, Peter Ford

2016-01-01

Primates display a remarkable ability to adapt to novel situations. Determining what is most pertinent in these situations is not always possible based only on the current sensory inputs, and often also depends on recent inputs and behavioral outputs that contribute to internal states. Thus, one can ask how cortical dynamics generate representations of these complex situations. It has been observed that mixed selectivity in cortical neurons contributes to represent diverse situations defined by a combination of the current stimuli, and that mixed selectivity is readily obtained in randomly connected recurrent networks. In this context, these reservoir networks reproduce the highly recurrent nature of local cortical connectivity. Recombining present and past inputs, random recurrent networks from the reservoir computing framework generate mixed selectivity which provides pre-coded representations of an essentially universal set of contexts. These representations can then be selectively amplified through learning to solve the task at hand. We thus explored their representational power and dynamical properties after training a reservoir to perform a complex cognitive task initially developed for monkeys. The reservoir model inherently displayed a dynamic form of mixed selectivity, key to the representation of the behavioral context over time. The pre-coded representation of context was amplified by training a feedback neuron to explicitly represent this context, thereby reproducing the effect of learning and allowing the model to perform more robustly. This second version of the model demonstrates how a hybrid dynamical regime combining spatio-temporal processing of reservoirs, and input driven attracting dynamics generated by the feedback neuron, can be used to solve a complex cognitive task. We compared reservoir activity to neural activity of dorsal anterior cingulate cortex of monkeys which revealed similar network dynamics. We argue that reservoir computing is a pertinent framework to model local cortical dynamics and their contribution to higher cognitive function. PMID:27286251

Structural Dynamics Investigation of Human Family 1 & 2 Cystatin-Cathepsin L1 Interaction: A Comparison of Binding Modes.

PubMed

Nandy, Suman Kumar; Seal, Alpana

2016-01-01

Cystatin superfamily is a large group of evolutionarily related proteins involved in numerous physiological activities through their inhibitory activity towards cysteine proteases. Despite sharing the same cystatin fold, and inhibiting cysteine proteases through the same tripartite edge involving highly conserved N-terminal region, L1 and L2 loop; cystatins differ widely in their inhibitory affinity towards C1 family of cysteine proteases and molecular details of these interactions are still elusive. In this study, inhibitory interactions of human family 1 & 2 cystatins with cathepsin L1 are predicted and their stability and viability are verified through protein docking & comparative molecular dynamics. An overall stabilization effect is observed in all cystatins on complex formation. Complexes are mostly dominated by van der Waals interaction but the relative participation of the conserved regions varied extensively. While van der Waals contacts prevail in L1 and L2 loop, N-terminal segment chiefly acts as electrostatic interaction site. In fact the comparative dynamics study points towards the instrumental role of L1 loop in directing the total interaction profile of the complex either towards electrostatic or van der Waals contacts. The key amino acid residues surfaced via interaction energy, hydrogen bonding and solvent accessible surface area analysis for each cystatin-cathepsin L1 complex influence the mode of binding and thus control the diverse inhibitory affinity of cystatins towards cysteine proteases.

Network cosmology.

PubMed

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology.

Network Cosmology

PubMed Central

Krioukov, Dmitri; Kitsak, Maksim; Sinkovits, Robert S.; Rideout, David; Meyer, David; Boguñá, Marián

2012-01-01

Prediction and control of the dynamics of complex networks is a central problem in network science. Structural and dynamical similarities of different real networks suggest that some universal laws might accurately describe the dynamics of these networks, albeit the nature and common origin of such laws remain elusive. Here we show that the causal network representing the large-scale structure of spacetime in our accelerating universe is a power-law graph with strong clustering, similar to many complex networks such as the Internet, social, or biological networks. We prove that this structural similarity is a consequence of the asymptotic equivalence between the large-scale growth dynamics of complex networks and causal networks. This equivalence suggests that unexpectedly similar laws govern the dynamics of complex networks and spacetime in the universe, with implications to network science and cosmology. PMID:23162688

Putting Humpty-Dumpty Together: Clustering the Functional Dynamics of Single Biomolecular Machines Such as the Spliceosome.

PubMed

Rohlman, C E; Blanco, M R; Walter, N G

2016-01-01

The spliceosome is a biomolecular machine that, in all eukaryotes, accomplishes site-specific splicing of introns from precursor messenger RNAs (pre-mRNAs) with high fidelity. Operating at the nanometer scale, where inertia and friction have lost the dominant role they play in the macroscopic realm, the spliceosome is highly dynamic and assembles its active site around each pre-mRNA anew. To understand the structural dynamics underlying the molecular motors, clocks, and ratchets that achieve functional accuracy in the yeast spliceosome (a long-standing model system), we have developed single-molecule fluorescence resonance energy transfer (smFRET) approaches that report changes in intra- and intermolecular interactions in real time. Building on our work using hidden Markov models (HMMs) to extract kinetic and conformational state information from smFRET time trajectories, we recognized that HMM analysis of individual state transitions as independent stochastic events is insufficient for a biomolecular machine as complex as the spliceosome. In this chapter, we elaborate on the recently developed smFRET-based Single-Molecule Cluster Analysis (SiMCAn) that dissects the intricate conformational dynamics of a pre-mRNA through the splicing cycle in a model-free fashion. By leveraging hierarchical clustering techniques developed for Bioinformatics, SiMCAn efficiently analyzes large datasets to first identify common molecular behaviors. Through a second level of clustering based on the abundance of dynamic behaviors exhibited by defined functional intermediates that have been stalled by biochemical or genetic tools, SiMCAn then efficiently assigns pre-mRNA FRET states and transitions to specific splicing complexes, with the potential to find heretofore undescribed conformations. SiMCAn thus arises as a general tool to analyze dynamic cellular machines more broadly. © 2016 Elsevier Inc. All rights reserved.

Dynamic Density: An Air Traffic Management Metric

NASA Technical Reports Server (NTRS)

Laudeman, I. V.; Shelden, S. G.; Branstrom, R.; Brasil, C. L.

1998-01-01

The definition of a metric of air traffic controller workload based on air traffic characteristics is essential to the development of both air traffic management automation and air traffic procedures. Dynamic density is a proposed concept for a metric that includes both traffic density (a count of aircraft in a volume of airspace) and traffic complexity (a measure of the complexity of the air traffic in a volume of airspace). It was hypothesized that a metric that includes terms that capture air traffic complexity will be a better measure of air traffic controller workload than current measures based only on traffic density. A weighted linear dynamic density function was developed and validated operationally. The proposed dynamic density function includes a traffic density term and eight traffic complexity terms. A unit-weighted dynamic density function was able to account for an average of 22% of the variance in observed controller activity not accounted for by traffic density alone. A comparative analysis of unit weights, subjective weights, and regression weights for the terms in the dynamic density equation was conducted. The best predictor of controller activity was the dynamic density equation with regression-weighted complexity terms.

Dynamic complexity: plant receptor complexes at the plasma membrane.

PubMed

Burkart, Rebecca C; Stahl, Yvonne

2017-12-01

Plant receptor complexes at the cell surface perceive many different external and internal signalling molecules and relay these signals into the cell to regulate development, growth and immunity. Recent progress in the analyses of receptor complexes using different live cell imaging approaches have shown that receptor complex formation and composition are dynamic and take place at specific microdomains at the plasma membrane. In this review we focus on three prominent examples of Arabidopsis thaliana receptor complexes and how their dynamic spatio-temporal distribution at the PM has been studied recently. We will elaborate on the newly emerging concept of plasma membrane microdomains as potential hubs for specific receptor complex assembly and signalling outputs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Enhancement tuning and control for high dynamic range images in multi-scale locally adaptive contrast enhancement algorithms

NASA Astrophysics Data System (ADS)

Cvetkovic, Sascha D.; Schirris, Johan; de With, Peter H. N.

2009-01-01

For real-time imaging in surveillance applications, visibility of details is of primary importance to ensure customer confidence. If we display High Dynamic-Range (HDR) scenes whose contrast spans four or more orders of magnitude on a conventional monitor without additional processing, results are unacceptable. Compression of the dynamic range is therefore a compulsory part of any high-end video processing chain because standard monitors are inherently Low- Dynamic Range (LDR) devices with maximally two orders of display dynamic range. In real-time camera processing, many complex scenes are improved with local contrast enhancements, bringing details to the best possible visibility. In this paper, we show how a multi-scale high-frequency enhancement scheme, in which gain is a non-linear function of the detail energy, can be used for the dynamic range compression of HDR real-time video camera signals. We also show the connection of our enhancement scheme to the processing way of the Human Visual System (HVS). Our algorithm simultaneously controls perceived sharpness, ringing ("halo") artifacts (contrast) and noise, resulting in a good balance between visibility of details and non-disturbance of artifacts. The overall quality enhancement, suitable for both HDR and LDR scenes, is based on a careful selection of the filter types for the multi-band decomposition and a detailed analysis of the signal per frequency band.

Dynamic Target Acquisition: Empirical Models of Operator Performance.

DTIC Science & Technology

1980-08-01

for 30,000 Ft Initial Slant Range VARIABLES MEAN Signature X Scene Complexity Low Medium High Active Target FLIR 22794 20162 20449 Inactive Target...Interactions for 30,000 Ft Initial Slant Range I Signature X Scene Complexity V * ORDERED MEANS 14867 18076 18079 18315 19105 19643 20162 20449 22794...14867 18076 1 183159 19105* 1 19643 20162* 20449 * 1 22794Signature X Speed I ORDERED MEANS 13429 15226 16604 17344 19033 20586 22641 24033 24491 1

Laboratory Experiments to Simulate and Investigate the Physics Underlying the Dynamics of Merging Solar Corona Structures

DTIC Science & Technology

2016-06-05

have attended and made presen- tations at the annual APS Division of Plasma Physics Meeting, the bi-annual High Energy Laboratory Astrophysics meeting...the AFOSR Space Science Pro- gram Review, the SHINE solar physics meeting, the International Astrophysics Conference, and the workshop “Complex plasma...tor k and Resolving Space-time Ambiguity. GR-Space Physics . submitted. Bellan, P. M., Zhai, X., Chai, K. B., & Ha, B. N. 2015. Complex astrophysical

Mucoadhesion vs mucus permeability of thiolated chitosan polymers and their resulting nanoparticles using a quartz crystal microbalance with dissipation (QCM-D).

PubMed

Oh, Sejin; Borrós, Salvador

2016-11-01

The aim of this present study was to evaluate the combination properties between mucoadhesion/mucus permeability of thiolated chitosans (TC) and their resulting nanoparticles using a quartz crystal microbalance with dissipation (QCM-D). The QCM-D experiments were conducted at pH 4 or 6.8 to assess the interaction between thiolated polymers, with low (TCL), medium (TCM) and high (TCH) contents of free thiol groups, and native porcine gastric mucin (NPGM). TCL was chosen for further carriers as it showed higher permeability into the NPGM layer compared to TCM and TCH. In this study, we describe a formulation of a novel carrier comprised by positively charged TCL, negatively charged DNA and degradable oligopeptide-modified poly(β-amino ester)s (PBAEs), which were employed in order to approach for tuning particle size and surface charge of complexes. TCL/PBAE complexes with or without DNA were characterized using dynamic light scattering. Mechanism of adsorption or permeation of the TCL/PBAE/DNA complexes into the NPGM barrier was investigated with QCM-D, which is a highly sensitive technique for studying nanomechanical (viscoelastic) changes of the substrates. This work might provide that the QCM-D technique would be a promising method to monitor the dynamic behaviour between complexes and NPGM. Copyright © 2016 Elsevier B.V. All rights reserved.

Student Leadership in Small Group Science Inquiry

ERIC Educational Resources Information Center

Oliveira, Alandeom W.; Boz, Umit; Broadwell, George A.; Sadler, Troy D.

2014-01-01

Background: Science educators have sought to structure collaborative inquiry learning through the assignment of static group roles. This structural approach to student grouping oversimplifies the complexities of peer collaboration and overlooks the highly dynamic nature of group activity. Purpose: This study addresses this issue of…

Stochastic Convection Parameterizations

NASA Technical Reports Server (NTRS)

Teixeira, Joao; Reynolds, Carolyn; Suselj, Kay; Matheou, Georgios

2012-01-01

computational fluid dynamics, radiation, clouds, turbulence, convection, gravity waves, surface interaction, radiation interaction, cloud and aerosol microphysics, complexity (vegetation, biogeochemistry, radiation versus turbulence/convection stochastic approach, non-linearities, Monte Carlo, high resolutions, large-Eddy Simulations, cloud structure, plumes, saturation in tropics, forecasting, parameterizations, stochastic, radiation-clod interaction, hurricane forecasts

Macroscopic modeling of freeway traffic using an artificial neural network

DOT National Transportation Integrated Search

1997-01-01

Traffic flow on freeways is a complex process that often is described by a set of highly nonlinear, dynamic equations in the form of a macroscopic traffic flow model. However, some of the existing macroscopic models have been found to exhibit instabi...

Numerical Simulation of Regional Circulation in the Monterey Bay Region

NASA Technical Reports Server (NTRS)

Tseng, Y. H.; Dietrich, D. E.; Ferziger, J. H.

2003-01-01

The objective of this study is to produce a high-resolution numerical model of Mon- terey Bay area in which the dynamics are determined by the complex geometry of the coastline, steep bathymetry, and the in uence of the water masses that constitute the CCS. Our goal is to simulate the regional-scale ocean response with realistic dynamics (annual cycle), forcing, and domain. In particular, we focus on non-hydrostatic e ects (by comparing the results of hydrostatic and non-hydrostatic models) and the role of complex geometry, i.e. the bay and submarine canyon, on the nearshore circulation. To the best of our knowledge, the current study is the rst to simulate the regional circulation in the vicinity of Monterey Bay using a non-hydrostatic model. Section 2 introduces the high resolution Monterey Bay area regional model (MBARM). Section 3 provides the results and veri cation with mooring and satellite data. Section 4 compares the results of hydrostatic and non-hydrostatic models.

Parallel Adaptive High-Order CFD Simulations Characterizing Cavity Acoustics for the Complete SOFIA Aircraft

NASA Technical Reports Server (NTRS)

Barad, Michael F.; Brehm, Christoph; Kiris, Cetin C.; Biswas, Rupak

2014-01-01

This paper presents one-of-a-kind MPI-parallel computational fluid dynamics simulations for the Stratospheric Observatory for Infrared Astronomy (SOFIA). SOFIA is an airborne, 2.5-meter infrared telescope mounted in an open cavity in the aft of a Boeing 747SP. These simulations focus on how the unsteady flow field inside and over the cavity interferes with the optical path and mounting of the telescope. A temporally fourth-order Runge-Kutta, and spatially fifth-order WENO-5Z scheme was used to perform implicit large eddy simulations. An immersed boundary method provides automated gridding for complex geometries and natural coupling to a block-structured Cartesian adaptive mesh refinement framework. Strong scaling studies using NASA's Pleiades supercomputer with up to 32,000 cores and 4 billion cells shows excellent scaling. Dynamic load balancing based on execution time on individual AMR blocks addresses irregularities caused by the highly complex geometry. Limits to scaling beyond 32K cores are identified, and targeted code optimizations are discussed.

Simple rules for passive diffusion through the nuclear pore complex

PubMed Central

Mironska, Roxana; Kim, Seung Joong

2016-01-01

Passive macromolecular diffusion through nuclear pore complexes (NPCs) is thought to decrease dramatically beyond a 30–60-kD size threshold. Using thousands of independent time-resolved fluorescence microscopy measurements in vivo, we show that the NPC lacks such a firm size threshold; instead, it forms a soft barrier to passive diffusion that intensifies gradually with increasing molecular mass in both the wild-type and mutant strains with various subsets of phenylalanine-glycine (FG) domains and different levels of baseline passive permeability. Brownian dynamics simulations replicate these findings and indicate that the soft barrier results from the highly dynamic FG repeat domains and the diffusing macromolecules mutually constraining and competing for available volume in the interior of the NPC, setting up entropic repulsion forces. We found that FG domains with exceptionally high net charge and low hydropathy near the cytoplasmic end of the central channel contribute more strongly to obstruction of passive diffusion than to facilitated transport, revealing a compartmentalized functional arrangement within the NPC. PMID:27697925

Propagating waves can explain irregular neural dynamics.

PubMed

Keane, Adam; Gong, Pulin

2015-01-28

Cortical neurons in vivo fire quite irregularly. Previous studies about the origin of such irregular neural dynamics have given rise to two major models: a balanced excitation and inhibition model, and a model of highly synchronized synaptic inputs. To elucidate the network mechanisms underlying synchronized synaptic inputs and account for irregular neural dynamics, we investigate a spatially extended, conductance-based spiking neural network model. We show that propagating wave patterns with complex dynamics emerge from the network model. These waves sweep past neurons, to which they provide highly synchronized synaptic inputs. On the other hand, these patterns only emerge from the network with balanced excitation and inhibition; our model therefore reconciles the two major models of irregular neural dynamics. We further demonstrate that the collective dynamics of propagating wave patterns provides a mechanistic explanation for a range of irregular neural dynamics, including the variability of spike timing, slow firing rate fluctuations, and correlated membrane potential fluctuations. In addition, in our model, the distributions of synaptic conductance and membrane potential are non-Gaussian, consistent with recent experimental data obtained using whole-cell recordings. Our work therefore relates the propagating waves that have been widely observed in the brain to irregular neural dynamics. These results demonstrate that neural firing activity, although appearing highly disordered at the single-neuron level, can form dynamical coherent structures, such as propagating waves at the population level. Copyright © 2015 the authors 0270-6474/15/351591-15$15.00/0.

Heterobimetallic porphyrin complexes displaying triple dynamics: coupled metal motions controlled by constitutional evolution.

PubMed

Le Gac, Stéphane; Fusaro, Luca; Roisnel, Thierry; Boitrel, Bernard

2014-05-07

A bis-strap porphyrin ligand (1), with an overhanging carboxylic acid group on each side of the macrocycle, has been investigated toward the formation of dynamic libraries of bimetallic complexes with Hg(II), Cd(II), and Pb(II). Highly heteroselective metalation processes occurred in the presence of Pb(II), with Hg(II) or Cd(II) bound out-of-plane to the N-core and "PbOAc" bound to a carboxylate group of a strap on the opposite side. The resulting complexes, 1(Hg)·PbOAc and 1(Cd)·PbOAc, display three levels of dynamics. The first is strap-level (interactional dynamics), where the PbOAc moiety swings between the left and right side of the strap owing to a second sphere of coordination with lateral amide functions. The second is ligand-level (motional dynamics), where 1(Hg)·PbOAc and 1(Cd)·PbOAc exist as two degenerate states in equilibrium controlled by a chemical effector (AcO(-)). The process corresponds to a double translocation of the metal ions according to an intramolecular migration of Hg(II) or Cd(II) through the N-core, oscillating between the two equivalent overhanging carbonyl groups, coupled to an intermolecular pathway for PbOAc exchanging between the two equivalent overhanging carboxylate groups (N-core(up) ⇆ N-core(down) coupled to strap(down) ⇆ strap(up), i.e., coupled motion #1 in the abstract graphic). The third is library-level (constitutional dynamics), where a dynamic constitutional evolution of the system was achieved by the successive addition of two chemical effectors (DMAP and then AcO(-)). It allowed shifting equilibrium forward and backward between 1(Hg)·PbOAc and the corresponding homobimetallic complexes 1(Hg2)·DMAP and 1(Pb)·PbOAc. The latter displays a different ligand-level dynamics, in the form of an intraligand coupled migration of the Pb(II) ions (N-core(up) ⇆ strap(up) coupled to strap(down) ⇆ N-core(down), i.e., coupled motion #2 in the abstract graphic). In addition, the neutral "bridged" complexes 1HgPb and 1CdPb, with the metal ions on opposite sides both bound to the N-core and to a carboxylate of a strap, were structurally characterized. These results establish an unprecedented approach in supramolecular coordination chemistry, by considering the reversible interaction of a metal ion with the porphyrin N-core as a new source of self-organization processes. This work should provide new inspirations for the design of innovative adaptative materials and devices.

Modeling and complexity of stochastic interacting Lévy type financial price dynamics

NASA Astrophysics Data System (ADS)

Wang, Yiduan; Zheng, Shenzhou; Zhang, Wei; Wang, Jun; Wang, Guochao

2018-06-01

In attempt to reproduce and investigate nonlinear dynamics of security markets, a novel nonlinear random interacting price dynamics, which is considered as a Lévy type process, is developed and investigated by the combination of lattice oriented percolation and Potts dynamics, which concerns with the instinctive random fluctuation and the fluctuation caused by the spread of the investors' trading attitudes, respectively. To better understand the fluctuation complexity properties of the proposed model, the complexity analyses of random logarithmic price return and corresponding volatility series are preformed, including power-law distribution, Lempel-Ziv complexity and fractional sample entropy. In order to verify the rationality of the proposed model, the corresponding studies of actual security market datasets are also implemented for comparison. The empirical results reveal that this financial price model can reproduce some important complexity features of actual security markets to some extent. The complexity of returns decreases with the increase of parameters γ1 and β respectively, furthermore, the volatility series exhibit lower complexity than the return series

Nonlinear stochastic interacting dynamics and complexity of financial gasket fractal-like lattice percolation

NASA Astrophysics Data System (ADS)

Zhang, Wei; Wang, Jun

2018-05-01

A novel nonlinear stochastic interacting price dynamics is proposed and investigated by the bond percolation on Sierpinski gasket fractal-like lattice, aim to make a new approach to reproduce and study the complexity dynamics of real security markets. Fractal-like lattices correspond to finite graphs with vertices and edges, which are similar to fractals, and Sierpinski gasket is a well-known example of fractals. Fractional ordinal array entropy and fractional ordinal array complexity are introduced to analyze the complexity behaviors of financial signals. To deeper comprehend the fluctuation characteristics of the stochastic price evolution, the complexity analysis of random logarithmic returns and volatility are preformed, including power-law distribution, fractional sample entropy and fractional ordinal array complexity. For further verifying the rationality and validity of the developed stochastic price evolution, the actual security market dataset are also studied with the same statistical methods for comparison. The empirical results show that this stochastic price dynamics can reconstruct complexity behaviors of the actual security markets to some extent.

How Markovian is exciton dynamics in purple bacteria?

NASA Astrophysics Data System (ADS)

Vaughan, Felix; Linden, Noah; Manby, Frederick R.

2017-03-01

We investigate the extent to which the dynamics of excitons in the light-harvesting complex LH2 of purple bacteria can be described using a Markovian approximation. To analyse the degree of non-Markovianity in these systems, we introduce a measure based on fitting Lindblad dynamics, as well as employing a recently introduced trace-distance measure. We apply these measures to a chromophore-dimer model of exciton dynamics and use the hierarchical equation-of-motion method to take into account the broad, low-frequency phonon bath. With a smooth phonon bath, small amounts of non-Markovianity are present according to the trace-distance measure, but the dynamics is poorly described by a Lindblad master equation unless the excitonic dimer coupling strength is modified. Inclusion of underdamped, high-frequency modes leads to significant deviations from Markovian evolution in both measures. In particular, we find that modes that are nearly resonant with gaps in the excitonic spectrum produce dynamics that deviate most strongly from the Lindblad approximation, despite the trace distance measuring larger amounts of non-Markovianity for higher frequency modes. Overall we find that the detailed structure in the high-frequency region of the spectral density has a significant impact on the nature of the dynamics of excitons.

Out-of-equilibrium dynamical mean-field equations for the perceptron model

NASA Astrophysics Data System (ADS)

Agoritsas, Elisabeth; Biroli, Giulio; Urbani, Pierfrancesco; Zamponi, Francesco

2018-02-01

Perceptrons are the building blocks of many theoretical approaches to a wide range of complex systems, ranging from neural networks and deep learning machines, to constraint satisfaction problems, glasses and ecosystems. Despite their applicability and importance, a detailed study of their Langevin dynamics has never been performed yet. Here we derive the mean-field dynamical equations that describe the continuous random perceptron in the thermodynamic limit, in a very general setting with arbitrary noise and friction kernels, not necessarily related by equilibrium relations. We derive the equations in two ways: via a dynamical cavity method, and via a path-integral approach in its supersymmetric formulation. The end point of both approaches is the reduction of the dynamics of the system to an effective stochastic process for a representative dynamical variable. Because the perceptron is formally very close to a system of interacting particles in a high dimensional space, the methods we develop here can be transferred to the study of liquid and glasses in high dimensions. Potentially interesting applications are thus the study of the glass transition in active matter, the study of the dynamics around the jamming transition, and the calculation of rheological properties in driven systems.

Complex Problem Solving in Teams: The Impact of Collective Orientation on Team Process Demands.

PubMed

Hagemann, Vera; Kluge, Annette

2017-01-01

Complex problem solving is challenging and a high-level cognitive process for individuals. When analyzing complex problem solving in teams, an additional, new dimension has to be considered, as teamwork processes increase the requirements already put on individual team members. After introducing an idealized teamwork process model, that complex problem solving teams pass through, and integrating the relevant teamwork skills for interdependently working teams into the model and combining it with the four kinds of team processes (transition, action, interpersonal, and learning processes), the paper demonstrates the importance of fulfilling team process demands for successful complex problem solving within teams. Therefore, results from a controlled team study within complex situations are presented. The study focused on factors that influence action processes, like coordination, such as emergent states like collective orientation, cohesion, and trust and that dynamically enable effective teamwork in complex situations. Before conducting the experiments, participants were divided by median split into two-person teams with either high ( n = 58) or low ( n = 58) collective orientation values. The study was conducted with the microworld C3Fire, simulating dynamic decision making, and acting in complex situations within a teamwork context. The microworld includes interdependent tasks such as extinguishing forest fires or protecting houses. Two firefighting scenarios had been developed, which takes a maximum of 15 min each. All teams worked on these two scenarios. Coordination within the team and the resulting team performance were calculated based on a log-file analysis. The results show that no relationships between trust and action processes and team performance exist. Likewise, no relationships were found for cohesion. Only collective orientation of team members positively influences team performance in complex environments mediated by action processes such as coordination within the team. The results are discussed in relation to previous empirical findings and to learning processes within the team with a focus on feedback strategies.

Complex Problem Solving in Teams: The Impact of Collective Orientation on Team Process Demands

PubMed Central

Hagemann, Vera; Kluge, Annette

2017-01-01

Complex problem solving is challenging and a high-level cognitive process for individuals. When analyzing complex problem solving in teams, an additional, new dimension has to be considered, as teamwork processes increase the requirements already put on individual team members. After introducing an idealized teamwork process model, that complex problem solving teams pass through, and integrating the relevant teamwork skills for interdependently working teams into the model and combining it with the four kinds of team processes (transition, action, interpersonal, and learning processes), the paper demonstrates the importance of fulfilling team process demands for successful complex problem solving within teams. Therefore, results from a controlled team study within complex situations are presented. The study focused on factors that influence action processes, like coordination, such as emergent states like collective orientation, cohesion, and trust and that dynamically enable effective teamwork in complex situations. Before conducting the experiments, participants were divided by median split into two-person teams with either high (n = 58) or low (n = 58) collective orientation values. The study was conducted with the microworld C3Fire, simulating dynamic decision making, and acting in complex situations within a teamwork context. The microworld includes interdependent tasks such as extinguishing forest fires or protecting houses. Two firefighting scenarios had been developed, which takes a maximum of 15 min each. All teams worked on these two scenarios. Coordination within the team and the resulting team performance were calculated based on a log-file analysis. The results show that no relationships between trust and action processes and team performance exist. Likewise, no relationships were found for cohesion. Only collective orientation of team members positively influences team performance in complex environments mediated by action processes such as coordination within the team. The results are discussed in relation to previous empirical findings and to learning processes within the team with a focus on feedback strategies. PMID:29033886

Dynamics of Nanoparticle-Protein Corona Complex Formation: Analytical Results from Population Balance Equations

PubMed Central

Darabi Sahneh, Faryad; Scoglio, Caterina; Riviere, Jim

2013-01-01

Background Nanoparticle-protein corona complex formation involves absorption of protein molecules onto nanoparticle surfaces in a physiological environment. Understanding the corona formation process is crucial in predicting nanoparticle behavior in biological systems, including applications of nanotoxicology and development of nano drug delivery platforms. Method This paper extends the modeling work in to derive a mathematical model describing the dynamics of nanoparticle corona complex formation from population balance equations. We apply nonlinear dynamics techniques to derive analytical results for the composition of nanoparticle-protein corona complex, and validate our results through numerical simulations. Results The model presented in this paper exhibits two phases of corona complex dynamics. In the first phase, proteins rapidly bind to the free surface of nanoparticles, leading to a metastable composition. During the second phase, continuous association and dissociation of protein molecules with nanoparticles slowly changes the composition of the corona complex. Given sufficient time, composition of the corona complex reaches an equilibrium state of stable composition. We find analytical approximate formulae for metastable and stable compositions of corona complex. Our formulae are very well-structured to clearly identify important parameters determining corona composition. Conclusion The dynamics of biocorona formation constitute vital aspect of interactions between nanoparticles and living organisms. Our results further understanding of these dynamics through quantitation of experimental conditions, modeling results for in vitro systems to better predict behavior for in vivo systems. One potential application would involve a single cell culture medium related to a complex protein medium, such as blood or tissue fluid. PMID:23741371

Effect of Rho-kinase inhibition on complexity of breathing pattern in a guinea pig model of asthma

PubMed Central

Pazhoohan, Saeed; Javan, Mohammad; Hajizadeh, Sohrab

2017-01-01

Asthma represents an episodic and fluctuating behavior characterized with decreased complexity of respiratory dynamics. Several evidence indicate that asthma severity or control is associated with alteration in variability of lung function. The pathophysiological basis of alteration in complexity of breathing pattern in asthma has remained poorly understood. Regarding the point that Rho-kinase is involved in pathophysiology of asthma, in present study we investigated the effect of Rho-kinase inhibition on complexity of respiratory dynamics in a guinea pig model of asthma. Male Dunkin Hartley guinea pigs were exposed to 12 series of inhalations with ovalbumin or saline. Animals were treated by the Rho-kinase inhibitor Y-27632 (1mM aerosols) prior to each allergen challenge. We recorded respiration of conscious animals using whole-body plethysmography. Exposure to ovalbumin induced lung inflammation, airway hyperresponsiveness and remodeling including goblet cell hyperplasia, increase in the thickness of airways smooth muscles and subepithelial collagen deposition. Complexity analysis of respiratory dynamics revealed a dramatic decrease in irregularity of respiratory rhythm representing less complexity in asthmatic guinea pigs. Inhibition of Rho-kinase reduced the airway remodeling and hyperreponsiveness, but had no significant effect on lung inflammation and complexity of respiratory dynamics in asthmatic animals. It seems that airway hyperresponsiveness and remodeling do not significantly affect the complexity of respiratory dynamics. Our results suggest that inflammation might be the probable cause of shift in the respiratory dynamics away from the normal fluctuation in asthma. PMID:29088265

Decreased resting-state brain activity complexity in schizophrenia characterized by both increased regularity and randomness.

PubMed

Yang, Albert C; Hong, Chen-Jee; Liou, Yin-Jay; Huang, Kai-Lin; Huang, Chu-Chung; Liu, Mu-En; Lo, Men-Tzung; Huang, Norden E; Peng, Chung-Kang; Lin, Ching-Po; Tsai, Shih-Jen

2015-06-01

Schizophrenia is characterized by heterogeneous pathophysiology. Using multiscale entropy (MSE) analysis, which enables capturing complex dynamics of time series, we characterized MSE patterns of blood-oxygen-level-dependent (BOLD) signals across different time scales and determined whether BOLD activity in patients with schizophrenia exhibits increased complexity (increased entropy in all time scales), decreased complexity toward regularity (decreased entropy in all time scales), or decreased complexity toward uncorrelated randomness (high entropy in short time scales followed by decayed entropy as the time scale increases). We recruited 105 patients with schizophrenia with an age of onset between 18 and 35 years and 210 age- and sex-matched healthy volunteers. Results showed that MSE of BOLD signals in patients with schizophrenia exhibited two routes of decreased BOLD complexity toward either regular or random patterns. Reduced BOLD complexity toward regular patterns was observed in the cerebellum and temporal, middle, and superior frontal regions, and reduced BOLD complexity toward randomness was observed extensively in the inferior frontal, occipital, and postcentral cortices as well as in the insula and middle cingulum. Furthermore, we determined that the two types of complexity change were associated differently with psychopathology; specifically, the regular type of BOLD complexity change was associated with positive symptoms of schizophrenia, whereas the randomness type of BOLD complexity was associated with negative symptoms of the illness. These results collectively suggested that resting-state dynamics in schizophrenia exhibit two routes of pathologic change toward regular or random patterns, which contribute to the differences in syndrome domains of psychosis in patients with schizophrenia. © 2015 Wiley Periodicals, Inc.

High dimensional model representation method for fuzzy structural dynamics

NASA Astrophysics Data System (ADS)

Adhikari, S.; Chowdhury, R.; Friswell, M. I.

2011-03-01

Uncertainty propagation in multi-parameter complex structures possess significant computational challenges. This paper investigates the possibility of using the High Dimensional Model Representation (HDMR) approach when uncertain system parameters are modeled using fuzzy variables. In particular, the application of HDMR is proposed for fuzzy finite element analysis of linear dynamical systems. The HDMR expansion is an efficient formulation for high-dimensional mapping in complex systems if the higher order variable correlations are weak, thereby permitting the input-output relationship behavior to be captured by the terms of low-order. The computational effort to determine the expansion functions using the α-cut method scales polynomically with the number of variables rather than exponentially. This logic is based on the fundamental assumption underlying the HDMR representation that only low-order correlations among the input variables are likely to have significant impacts upon the outputs for most high-dimensional complex systems. The proposed method is first illustrated for multi-parameter nonlinear mathematical test functions with fuzzy variables. The method is then integrated with a commercial finite element software (ADINA). Modal analysis of a simplified aircraft wing with fuzzy parameters has been used to illustrate the generality of the proposed approach. In the numerical examples, triangular membership functions have been used and the results have been validated against direct Monte Carlo simulations. It is shown that using the proposed HDMR approach, the number of finite element function calls can be reduced without significantly compromising the accuracy.

Model-order reduction of lumped parameter systems via fractional calculus

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Energy transfer dynamics in Light-Harvesting Dendrimers

NASA Astrophysics Data System (ADS)

Melinger, Joseph S.; McMorrow, Dale; Kleiman, Valeria D.

2002-03-01

We explore energy transfer dynamics in light-harvesting phenylacetylene symmetric and asymmetric dendrimers. Femtosecond pump-probe spectroscopy is used to probe the ultrafast dynamics of electronic excitations in these dendrimers. The backbone of the macromolecule consists of branches of increasing conjugation length, creating an energy gradient, which funnels energy to an accepting perylene trap. In the case of the symmetric dendrimer (nanostar), the energy transfer efficiency is known to approach nearly unity, although the nature and timescale of the energy transfer process is still unknown. For the asymmetric dendrimers, energy transfer efficiencies are very high, with the possibility of more complex transfer processes. We experimentally monitor the transport of excitons through the light-harvesting dendrimer. The transients show a number of components, with timescales ranging from <300fs to several tens of picoseconds, revealing the complex photophysics taking place in these macromolecules. We interpret our results in terms of the Förster mechanism in which energy transfer occurs through dipole-dipole interactions.

Drug resistance conferred by mutations outside the active site through alterations in the dynamic and structural ensemble of HIV-1 protease.

PubMed

Ragland, Debra A; Nalivaika, Ellen A; Nalam, Madhavi N L; Prachanronarong, Kristina L; Cao, Hong; Bandaranayake, Rajintha M; Cai, Yufeng; Kurt-Yilmaz, Nese; Schiffer, Celia A

2014-08-27

HIV-1 protease inhibitors are part of the highly active antiretroviral therapy effectively used in the treatment of HIV infection and AIDS. Darunavir (DRV) is the most potent of these inhibitors, soliciting drug resistance only when a complex combination of mutations occur both inside and outside the protease active site. With few exceptions, the role of mutations outside the active site in conferring resistance remains largely elusive. Through a series of DRV-protease complex crystal structures, inhibition assays, and molecular dynamics simulations, we find that single and double site mutations outside the active site often associated with DRV resistance alter the structure and dynamic ensemble of HIV-1 protease active site. These alterations correlate with the observed inhibitor binding affinities for the mutants, and suggest a network hypothesis on how the effect of distal mutations are propagated to pivotal residues at the active site and may contribute to conferring drug resistance.

Fundamental structures of dynamic social networks.

PubMed

Sekara, Vedran; Stopczynski, Arkadiusz; Lehmann, Sune

2016-09-06

Social systems are in a constant state of flux, with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding the spreading of influence or diseases, formation of friendships, and the productivity of teams. Although there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the microdynamics of social networks. Here, we explore the dynamic social network of a densely-connected population of ∼1,000 individuals and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geolocation, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection unnecessary. Starting from 5-min time slices, we uncover dynamic social structures expressed on multiple timescales. On the hourly timescale, we find that gatherings are fluid, with members coming and going, but organized via a stable core of individuals. Each core represents a social context. Cores exhibit a pattern of recurring meetings across weeks and months, each with varying degrees of regularity. Taken together, these findings provide a powerful simplification of the social network, where cores represent fundamental structures expressed with strong temporal and spatial regularity. Using this framework, we explore the complex interplay between social and geospatial behavior, documenting how the formation of cores is preceded by coordination behavior in the communication networks and demonstrating that social behavior can be predicted with high precision.

Fundamental structures of dynamic social networks

PubMed Central

Sekara, Vedran; Stopczynski, Arkadiusz; Lehmann, Sune

2016-01-01

Social systems are in a constant state of flux, with dynamics spanning from minute-by-minute changes to patterns present on the timescale of years. Accurate models of social dynamics are important for understanding the spreading of influence or diseases, formation of friendships, and the productivity of teams. Although there has been much progress on understanding complex networks over the past decade, little is known about the regularities governing the microdynamics of social networks. Here, we explore the dynamic social network of a densely-connected population of ∼1,000 individuals and their interactions in the network of real-world person-to-person proximity measured via Bluetooth, as well as their telecommunication networks, online social media contacts, geolocation, and demographic data. These high-resolution data allow us to observe social groups directly, rendering community detection unnecessary. Starting from 5-min time slices, we uncover dynamic social structures expressed on multiple timescales. On the hourly timescale, we find that gatherings are fluid, with members coming and going, but organized via a stable core of individuals. Each core represents a social context. Cores exhibit a pattern of recurring meetings across weeks and months, each with varying degrees of regularity. Taken together, these findings provide a powerful simplification of the social network, where cores represent fundamental structures expressed with strong temporal and spatial regularity. Using this framework, we explore the complex interplay between social and geospatial behavior, documenting how the formation of cores is preceded by coordination behavior in the communication networks and demonstrating that social behavior can be predicted with high precision. PMID:27555584

Spatial operator factorization and inversion of the manipulator mass matrix

NASA Technical Reports Server (NTRS)

Rodriguez, Guillermo; Kreutz-Delgado, Kenneth

1992-01-01

This paper advances two linear operator factorizations of the manipulator mass matrix. Embedded in the factorizations are many of the techniques that are regarded as very efficient computational solutions to inverse and forward dynamics problems. The operator factorizations provide a high-level architectural understanding of the mass matrix and its inverse, which is not visible in the detailed algorithms. They also lead to a new approach to the development of computer programs or organize complexity in robot dynamics.

Dissecting the Calcium-Induced Differentiation of Human Primary Keratinocytes Stem Cells by Integrative and Structural Network Analyses

PubMed Central

Toufighi, Kiana; Yang, Jae-Seong; Luis, Nuno Miguel; Aznar Benitah, Salvador; Lehner, Ben; Serrano, Luis; Kiel, Christina

2015-01-01

The molecular details underlying the time-dependent assembly of protein complexes in cellular networks, such as those that occur during differentiation, are largely unexplored. Focusing on the calcium-induced differentiation of primary human keratinocytes as a model system for a major cellular reorganization process, we look at the expression of genes whose products are involved in manually-annotated protein complexes. Clustering analyses revealed only moderate co-expression of functionally related proteins during differentiation. However, when we looked at protein complexes, we found that the majority (55%) are composed of non-dynamic and dynamic gene products (‘di-chromatic’), 19% are non-dynamic, and 26% only dynamic. Considering three-dimensional protein structures to predict steric interactions, we found that proteins encoded by dynamic genes frequently interact with a common non-dynamic protein in a mutually exclusive fashion. This suggests that during differentiation, complex assemblies may also change through variation in the abundance of proteins that compete for binding to common proteins as found in some cases for paralogous proteins. Considering the example of the TNF-α/NFκB signaling complex, we suggest that the same core complex can guide signals into diverse context-specific outputs by addition of time specific expressed subunits, while keeping other cellular functions constant. Thus, our analysis provides evidence that complex assembly with stable core components and competition could contribute to cell differentiation. PMID:25946651

Robust co-regulation of tyrosine phosphorylation sites on proteins reveals novel protein interactions†

PubMed Central

Naegle, Kristen M.; White, Forest M.; Lauffenburger, Douglas A.; Yaffe, Michael B.

2012-01-01

Cell signaling networks propagate information from extracellular cues via dynamic modulation of protein–protein interactions in a context-dependent manner. Networks based on receptor tyrosine kinases (RTKs), for example, phosphorylate intracellular proteins in response to extracellular ligands, resulting in dynamic protein–protein interactions that drive phenotypic changes. Most commonly used methods for discovering these protein–protein interactions, however, are optimized for detecting stable, longer-lived complexes, rather than the type of transient interactions that are essential components of dynamic signaling networks such as those mediated by RTKs. Substrate phosphorylation downstream of RTK activation modifies substrate activity and induces phospho-specific binding interactions, resulting in the formation of large transient macromolecular signaling complexes. Since protein complex formation should follow the trajectory of events that drive it, we reasoned that mining phosphoproteomic datasets for highly similar dynamic behavior of measured phosphorylation sites on different proteins could be used to predict novel, transient protein–protein interactions that had not been previously identified. We applied this method to explore signaling events downstream of EGFR stimulation. Our computational analysis of robustly co-regulated phosphorylation sites, based on multiple clustering analysis of quantitative time-resolved mass-spectrometry phosphoproteomic data, not only identified known sitewise-specific recruitment of proteins to EGFR, but also predicted novel, a priori interactions. A particularly intriguing prediction of EGFR interaction with the cytoskeleton-associated protein PDLIM1 was verified within cells using co-immunoprecipitation and in situ proximity ligation assays. Our approach thus offers a new way to discover protein–protein interactions in a dynamic context- and phosphorylation site-specific manner. PMID:22851037

Complexity, Chaos, and Nonlinear Dynamics: A New Perspective on Career Development Theory

ERIC Educational Resources Information Center

Bloch, Deborah P.

2005-01-01

The author presents a theory of career development drawing on nonlinear dynamics and chaos and complexity theories. Career is presented as a complex adaptive entity, a fractal of the human entity. Characteristics of complex adaptive entities, including (a) autopiesis, or self-regeneration; (b) open exchange; (c) participation in networks; (d)…

Heptameric (L12)6/L10 rather than canonical pentameric complexes are found by tandem MS of intact ribosomes from thermophilic bacteria.

PubMed

Ilag, Leopold L; Videler, Hortense; McKay, Adam R; Sobott, Frank; Fucini, Paola; Nierhaus, Knud H; Robinson, Carol V

2005-06-07

Ribosomes are universal translators of the genetic code into protein and represent macromolecular structures that are asymmetric, often heterogeneous, and contain dynamic regions. These properties pose considerable challenges for modern-day structural biology. Despite these obstacles, high-resolution x-ray structures of the 30S and 50S subunits have revealed the RNA architecture and its interactions with proteins for ribosomes from Thermus thermophilus, Deinococcus radiodurans, and Haloarcula marismortui. Some regions, however, remain inaccessible to these high-resolution approaches because of their high conformational dynamics and potential heterogeneity, specifically the so-called L7/L12 stalk complex. This region plays a vital role in protein synthesis by interacting with GTPase factors in translation. Here, we apply tandem MS, an approach widely applied to peptide sequencing for proteomic applications but not previously applied to MDa complexes. Isolation and activation of ions assigned to intact 30S and 50S subunits releases proteins S6 and L12, respectively. Importantly, this process reveals, exclusively while attached to ribosomes, a phosphorylation of L12, the protein located in multiple copies at the tip of the stalk complex. Moreover, through tandem MS we discovered a stoichiometry for the stalk protuberance on Thermus thermophilus and other thermophiles and contrast this assembly with the analogous one on ribosomes from mesophiles. Together with evidence for a potential interaction with the degradosome, these results show that important findings on ribosome structure, interactions, and modifications can be discovered by tandem MS, even on well studied ribosomes from Thermus thermophilus.

Heptameric (L12)6/L10 rather than canonical pentameric complexes are found by tandem MS of intact ribosomes from thermophilic bacteria

PubMed Central

Ilag, Leopold L.; Videler, Hortense; McKay, Adam R.; Sobott, Frank; Fucini, Paola; Nierhaus, Knud H.; Robinson, Carol V.

2005-01-01

Ribosomes are universal translators of the genetic code into protein and represent macromolecular structures that are asymmetric, often heterogeneous, and contain dynamic regions. These properties pose considerable challenges for modern-day structural biology. Despite these obstacles, high-resolution x-ray structures of the 30S and 50S subunits have revealed the RNA architecture and its interactions with proteins for ribosomes from Thermus thermophilus, Deinococcus radiodurans, and Haloarcula marismortui. Some regions, however, remain inaccessible to these high-resolution approaches because of their high conformational dynamics and potential heterogeneity, specifically the so-called L7/L12 stalk complex. This region plays a vital role in protein synthesis by interacting with GTPase factors in translation. Here, we apply tandem MS, an approach widely applied to peptide sequencing for proteomic applications but not previously applied to MDa complexes. Isolation and activation of ions assigned to intact 30S and 50S subunits releases proteins S6 and L12, respectively. Importantly, this process reveals, exclusively while attached to ribosomes, a phosphorylation of L12, the protein located in multiple copies at the tip of the stalk complex. Moreover, through tandem MS we discovered a stoichiometry for the stalk protuberance on Thermus thermophilus and other thermophiles and contrast this assembly with the analogous one on ribosomes from mesophiles. Together with evidence for a potential interaction with the degradosome, these results show that important findings on ribosome structure, interactions, and modifications can be discovered by tandem MS, even on well studied ribosomes from Thermus thermophilus. PMID:15923259

Dynamics of functional failures and recovery in complex road networks

NASA Astrophysics Data System (ADS)

Zhan, Xianyuan; Ukkusuri, Satish V.; Rao, P. Suresh C.

2017-11-01

We propose a new framework for modeling the evolution of functional failures and recoveries in complex networks, with traffic congestion on road networks as the case study. Differently from conventional approaches, we transform the evolution of functional states into an equivalent dynamic structural process: dual-vertex splitting and coalescing embedded within the original network structure. The proposed model successfully explains traffic congestion and recovery patterns at the city scale based on high-resolution data from two megacities. Numerical analysis shows that certain network structural attributes can amplify or suppress cascading functional failures. Our approach represents a new general framework to model functional failures and recoveries in flow-based networks and allows understanding of the interplay between structure and function for flow-induced failure propagation and recovery.

OFMTutor: An operator function model intelligent tutoring system

NASA Technical Reports Server (NTRS)

Jones, Patricia M.

1989-01-01

The design, implementation, and evaluation of an Operator Function Model intelligent tutoring system (OFMTutor) is presented. OFMTutor is intended to provide intelligent tutoring in the context of complex dynamic systems for which an operator function model (OFM) can be constructed. The human operator's role in such complex, dynamic, and highly automated systems is that of a supervisory controller whose primary responsibilities are routine monitoring and fine-tuning of system parameters and occasional compensation for system abnormalities. The automated systems must support the human operator. One potentially useful form of support is the use of intelligent tutoring systems to teach the operator about the system and how to function within that system. Previous research on intelligent tutoring systems (ITS) is considered. The proposed design for OFMTutor is presented, and an experimental evaluation is described.

Application of Nonlinear Systems Inverses to Automatic Flight Control Design: System Concepts and Flight Evaluations

NASA Technical Reports Server (NTRS)

Meyer, G.; Cicolani, L.

1981-01-01

A practical method for the design of automatic flight control systems for aircraft with complex characteristics and operational requirements, such as the powered lift STOL and V/STOL configurations, is presented. The method is effective for a large class of dynamic systems requiring multi-axis control which have highly coupled nonlinearities, redundant controls, and complex multidimensional operational envelopes. It exploits the concept of inverse dynamic systems, and an algorithm for the construction of inverse is given. A hierarchic structure for the total control logic with inverses is presented. The method is illustrated with an application to the Augmentor Wing Jet STOL Research Aircraft equipped with a digital flight control system. Results of flight evaluation of the control concept on this aircraft are presented.

Langevin Dynamics Deciphers the Motility Pattern of Swimming Parasites

NASA Astrophysics Data System (ADS)

Zaburdaev, Vasily; Uppaluri, Sravanti; Pfohl, Thomas; Engstler, Markus; Friedrich, Rudolf; Stark, Holger

2011-05-01

The parasite African trypanosome swims in the bloodstream of mammals and causes the highly dangerous human sleeping sickness. Cell motility is essential for the parasite’s survival within the mammalian host. We present an analysis of the random-walk pattern of a swimming trypanosome. From experimental time-autocorrelation functions for the direction of motion we identify two relaxation times that differ by an order of magnitude. They originate from the rapid deformations of the cell body and a slower rotational diffusion of the average swimming direction. Velocity fluctuations are athermal and increase for faster cells whose trajectories are also straighter. We demonstrate that such a complex dynamics is captured by two decoupled Langevin equations that decipher the complex trajectory pattern by referring it to the microscopic details of cell behavior.

Methods for the Analysis of Protein Phosphorylation-Mediated Cellular Signaling Networks

NASA Astrophysics Data System (ADS)

White, Forest M.; Wolf-Yadlin, Alejandro

2016-06-01

Protein phosphorylation-mediated cellular signaling networks regulate almost all aspects of cell biology, including the responses to cellular stimulation and environmental alterations. These networks are highly complex and comprise hundreds of proteins and potentially thousands of phosphorylation sites. Multiple analytical methods have been developed over the past several decades to identify proteins and protein phosphorylation sites regulating cellular signaling, and to quantify the dynamic response of these sites to different cellular stimulation. Here we provide an overview of these methods, including the fundamental principles governing each method, their relative strengths and weaknesses, and some examples of how each method has been applied to the analysis of complex signaling networks. When applied correctly, each of these techniques can provide insight into the topology, dynamics, and regulation of protein phosphorylation signaling networks.

Vibrational energy transfer dynamics in ruthenium polypyridine transition metal complexes.

PubMed

Fedoseeva, Marina; Delor, Milan; Parker, Simon C; Sazanovich, Igor V; Towrie, Michael; Parker, Anthony W; Weinstein, Julia A

2015-01-21

Understanding the dynamics of the initial stages of vibrational energy transfer in transition metal complexes is a challenging fundamental question which is also of crucial importance for many applications, such as improving the performance of solar devices or photocatalysis. The present study investigates vibrational energy transport in the ground and the electronic excited state of Ru(4,4'-(COOEt)2-2,2-bpy)2(NCS)2, a close relative of the efficient "N3" dye used in dye-sensitized solar cells. Using the emerging technique of ultrafast two-dimensional infrared spectroscopy, we show that, similarly to other transition-metal complexes, the central Ru heavy atom acts as a "bottleneck" making the energy transfer from small ligands with high energy vibrational stretching frequencies less favorable and thereby affecting the efficiency of vibrational energy flow in the complex. Comparison of the vibrational relaxation times in the electronic ground and excited state of Ru(4,4'-(COOEt)2-2,2-bpy)2(NCS)2 shows that it is dramatically faster in the latter. We propose to explain this observation by the intramolecular electrostatic interactions between the thiocyanate group and partially oxidised Ru metal center, which increase the degree of vibrational coupling between CN and Ru-N modes in the excited state thus reducing structural and thermodynamic barriers that slow down vibrational relaxation and energy transport in the electronic ground state. As a very similar behavior was earlier observed in another transition-metal complex, Re(4,4'-(COOEt)2-2,2'-bpy)(CO)3Cl, we suggest that this effect in vibrational energy dynamics might be common for transition-metal complexes with heavy central atoms.

Simulation Study on Missile Penetration Based on LS - DYNA

NASA Astrophysics Data System (ADS)

Tang, Jue; Sun, Xinli

2017-12-01

Penetrating the shell armor is an effective means of destroying hard targets with multiple layers of protection. The penetration process is a high-speed impact dynamics research category, involving high pressure, high temperature, high speed and internal material damage, including plugging, penetration, spalling, caving, splashing and other complex forms, therefore, Analysis is one of the difficulties in the study of impact dynamics. In this paper, the Lagrang algorithm and the SPH algorithm are used to analyze the penetrating steel plate, and the penetration model of the rocket penetrating the steel plate, the failure mode of the steel plate and the missile and the advantages and disadvantages of Lagrang algorithm and SPH algorithm in the simulation of high-speed collision problem are analyzed and compared, which provides a reference for the study of simulation collision problem.

Hot Spots in a Network of Functional Sites

PubMed Central

Ozbek, Pemra; Soner, Seren; Haliloglu, Turkan

2013-01-01

It is of significant interest to understand how proteins interact, which holds the key phenomenon in biological functions. Using dynamic fluctuations in high frequency modes, we show that the Gaussian Network Model (GNM) predicts hot spot residues with success rates ranging between S 8–58%, C 84–95%, P 5–19% and A 81–92% on unbound structures and S 8–51%, C 97–99%, P 14–50%, A 94–97% on complex structures for sensitivity, specificity, precision and accuracy, respectively. High specificity and accuracy rates with a single property on unbound protein structures suggest that hot spots are predefined in the dynamics of unbound structures and forming the binding core of interfaces, whereas the prediction of other functional residues with similar dynamic behavior explains the lower precision values. The latter is demonstrated with the case studies; ubiquitin, hen egg-white lysozyme and M2 proton channel. The dynamic fluctuations suggest a pseudo network of residues with high frequency fluctuations, which could be plausible for the mechanism of biological interactions and allosteric regulation. PMID:24023934

Markets on Networks

NASA Astrophysics Data System (ADS)

Toroczkai, Zoltan; Anghel, Marian; Bassler, Kevin; Korniss, Gyorgy

2003-03-01

The dynamics of human, and most biological populations is characterized by competition for resources. By its own nature, this dynamics creates the group of "elites", formed by those agents who have strategies that are the most successful in the given situation, and therefore the rest of the agents will tend to follow, imitate, or interact with them, creating a social structure of leadership in the agent society. These inter-agent communications generate a complex social network with small-world character which itself forms the substrate for a second network, the action network. The latter is a highly dynamic, adaptive, directed network, defined by those inter-agent communication links on the substrate along which the passed information /prediction is acted upon by the other agents. By using the minority game for competition dynamics, here we show that when the substrate network is highly connected, the action network spontaneously develops hubs with a broad distribution of out-degrees, defining a robust leadership structure that is scale-free. Furthermore, in certain, realistic parameter ranges, facilitated by information passing on the action network, agents can spontaneously generate a high degree of cooperation making the collective almost maximally efficient.

Dynamic Multi-Coil Shimming of the Human Brain at 7 Tesla

PubMed Central

Juchem, Christoph; Nixon, Terence W.; McIntyre, Scott; Boer, Vincent O.; Rothman, Douglas L.; de Graaf, Robin A.

2011-01-01

High quality magnetic field homogenization of the human brain (i.e. shimming) for MR imaging and spectroscopy is a demanding task. The susceptibility differences between air and tissue are a longstanding problem as they induce complex field distortions in the prefrontal cortex and the temporal lobes. To date, the theoretical gains of high field MR have only been realized partially in the human brain due to limited magnetic field homogeneity. A novel shimming technique for the human brain is presented that is based on the combination of non-orthogonal basis fields from 48 individual, circular coils. Custom-built amplifier electronics enabled the dynamic application of the multi-coil shim fields in a slice-specific fashion. Dynamic multi-coil (DMC) shimming is shown to eliminate most of the magnetic field inhomogeneity apparent in the human brain at 7 Tesla and provided improved performance compared to state-of-the-art dynamic shim updating with zero through third order spherical harmonic functions. The novel technique paves the way for high field MR applications of the human brain for which excellent magnetic field homogeneity is a prerequisite. PMID:21824794

A Method for Predicting Protein Complexes from Dynamic Weighted Protein-Protein Interaction Networks.

PubMed

Liu, Lizhen; Sun, Xiaowu; Song, Wei; Du, Chao

2018-06-01

Predicting protein complexes from protein-protein interaction (PPI) network is of great significance to recognize the structure and function of cells. A protein may interact with different proteins under different time or conditions. Existing approaches only utilize static PPI network data that may lose much temporal biological information. First, this article proposed a novel method that combines gene expression data at different time points with traditional static PPI network to construct different dynamic subnetworks. Second, to further filter out the data noise, the semantic similarity based on gene ontology is regarded as the network weight together with the principal component analysis, which is introduced to deal with the weight computing by three traditional methods. Third, after building a dynamic PPI network, a predicting protein complexes algorithm based on "core-attachment" structural feature is applied to detect complexes from each dynamic subnetworks. Finally, it is revealed from the experimental results that our method proposed in this article performs well on detecting protein complexes from dynamic weighted PPI networks.

Reconstructing Interlaced High-Dynamic-Range Video Using Joint Learning.

PubMed

Inchang Choi; Seung-Hwan Baek; Kim, Min H

2017-11-01

For extending the dynamic range of video, it is a common practice to capture multiple frames sequentially with different exposures and combine them to extend the dynamic range of each video frame. However, this approach results in typical ghosting artifacts due to fast and complex motion in nature. As an alternative, video imaging with interlaced exposures has been introduced to extend the dynamic range. However, the interlaced approach has been hindered by jaggy artifacts and sensor noise, leading to concerns over image quality. In this paper, we propose a data-driven approach for jointly solving two specific problems of deinterlacing and denoising that arise in interlaced video imaging with different exposures. First, we solve the deinterlacing problem using joint dictionary learning via sparse coding. Since partial information of detail in differently exposed rows is often available via interlacing, we make use of the information to reconstruct details of the extended dynamic range from the interlaced video input. Second, we jointly solve the denoising problem by tailoring sparse coding to better handle additive noise in low-/high-exposure rows, and also adopt multiscale homography flow to temporal sequences for denoising. We anticipate that the proposed method will allow for concurrent capture of higher dynamic range video frames without suffering from ghosting artifacts. We demonstrate the advantages of our interlaced video imaging compared with the state-of-the-art high-dynamic-range video methods.

Hamiltonian approach to slip-stacking dynamics

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

Lee, S. Y.; Ng, K. Y.

Hamiltonian dynamics has been applied to study the slip-stacking dynamics. The canonical-perturbation method is employed to obtain the second-harmonic correction term in the slip-stacking Hamiltonian. The Hamiltonian approach provides a clear optimal method for choosing the slip-stacking parameter and improving stacking efficiency. The dynamics are applied specifically to the Fermilab Booster-Recycler complex. As a result, the dynamics can also be applied to other accelerator complexes.

Hamiltonian approach to slip-stacking dynamics

DOE PAGES

Lee, S. Y.; Ng, K. Y.

2017-06-29

Hamiltonian dynamics has been applied to study the slip-stacking dynamics. The canonical-perturbation method is employed to obtain the second-harmonic correction term in the slip-stacking Hamiltonian. The Hamiltonian approach provides a clear optimal method for choosing the slip-stacking parameter and improving stacking efficiency. The dynamics are applied specifically to the Fermilab Booster-Recycler complex. As a result, the dynamics can also be applied to other accelerator complexes.

Multivalency regulates activity in an intrinsically disordered transcription factor

PubMed Central

Clark, Sarah; Myers, Janette B; King, Ashleigh; Fiala, Radovan; Novacek, Jiri; Pearce, Grant; Heierhorst, Jörg; Reichow, Steve L

2018-01-01

The transcription factor ASCIZ (ATMIN, ZNF822) has an unusually high number of recognition motifs for the product of its main target gene, the hub protein LC8 (DYNLL1). Using a combination of biophysical methods, structural analysis by NMR and electron microscopy, and cellular transcription assays, we developed a model that proposes a concerted role of intrinsic disorder and multiple LC8 binding events in regulating LC8 transcription. We demonstrate that the long intrinsically disordered C-terminal domain of ASCIZ binds LC8 to form a dynamic ensemble of complexes with a gradient of transcriptional activity that is inversely proportional to LC8 occupancy. The preference for low occupancy complexes at saturating LC8 concentrations with both human and Drosophila ASCIZ indicates that negative cooperativity is an important feature of ASCIZ-LC8 interactions. The prevalence of intrinsic disorder and multivalency among transcription factors suggests that formation of heterogeneous, dynamic complexes is a widespread mechanism for tuning transcriptional regulation. PMID:29714690

Transcriptional activation by the thyroid hormone receptor through ligand-dependent receptor recruitment and chromatin remodelling.

PubMed

Grøntved, Lars; Waterfall, Joshua J; Kim, Dong Wook; Baek, Songjoon; Sung, Myong-Hee; Zhao, Li; Park, Jeong Won; Nielsen, Ronni; Walker, Robert L; Zhu, Yuelin J; Meltzer, Paul S; Hager, Gordon L; Cheng, Sheue-yann

2015-04-28

A bimodal switch model is widely used to describe transcriptional regulation by the thyroid hormone receptor (TR). In this model, the unliganded TR forms stable, chromatin-bound complexes with transcriptional co-repressors to repress transcription. Binding of hormone dissociates co-repressors and facilitates recruitment of co-activators to activate transcription. Here we show that in addition to hormone-independent TR occupancy, ChIP-seq against endogenous TR in mouse liver tissue demonstrates considerable hormone-induced TR recruitment to chromatin associated with chromatin remodelling and activated gene transcription. Genome-wide footprinting analysis using DNase-seq provides little evidence for TR footprints both in the absence and presence of hormone, suggesting that unliganded TR engagement with repressive complexes on chromatin is, similar to activating receptor complexes, a highly dynamic process. This dynamic and ligand-dependent interaction with chromatin is likely shared by all steroid hormone receptors regardless of their capacity to repress transcription in the absence of ligand.

Dynamic clustering of dynamin-amphiphysin helices regulates membrane constriction and fission coupled with GTP hydrolysis

PubMed Central

Kozai, Toshiya; Yang, Huiran; Ishikuro, Daiki; Seyama, Kaho; Kumagai, Yusuke; Abe, Tadashi; Yamada, Hiroshi; Uchihashi, Takayuki

2018-01-01

Dynamin is a mechanochemical GTPase essential for membrane fission during clathrin-mediated endocytosis. Dynamin forms helical complexes at the neck of clathrin-coated pits and their structural changes coupled with GTP hydrolysis drive membrane fission. Dynamin and its binding protein amphiphysin cooperatively regulate membrane remodeling during the fission, but its precise mechanism remains elusive. In this study, we analyzed structural changes of dynamin-amphiphysin complexes during the membrane fission using electron microscopy (EM) and high-speed atomic force microscopy (HS-AFM). Interestingly, HS-AFM analyses show that the dynamin-amphiphysin helices are rearranged to form clusters upon GTP hydrolysis and membrane constriction occurs at protein-uncoated regions flanking the clusters. We also show a novel function of amphiphysin in size control of the clusters to enhance biogenesis of endocytic vesicles. Our approaches using combination of EM and HS-AFM clearly demonstrate new mechanistic insights into the dynamics of dynamin-amphiphysin complexes during membrane fission. PMID:29357276

Mathematical Models to Determine Stable Behavior of Complex Systems

NASA Astrophysics Data System (ADS)

Sumin, V. I.; Dushkin, A. V.; Smolentseva, T. E.

2018-05-01

The paper analyzes a possibility to predict functioning of a complex dynamic system with a significant amount of circulating information and a large number of random factors impacting its functioning. Functioning of the complex dynamic system is described as a chaotic state, self-organized criticality and bifurcation. This problem may be resolved by modeling such systems as dynamic ones, without applying stochastic models and taking into account strange attractors.

Quantifying chaotic dynamics from integrate-and-fire processes

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

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

2015-01-15

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

Novice High School Science Teachers: Lesson Plan Adaptations

ERIC Educational Resources Information Center

Scharon, Aracelis Janelle

2013-01-01

The Next Generation Science Standards (NRC, 2013) positions teachers as responsible for necessary decision making about how their intended science lesson plan content supports continuous student science learning. Teachers interact with their instructional lesson plans in dynamic and constructive ways. Adapting lesson plans is complex. This process…

The Emergent Power of Teacher Leaders

ERIC Educational Resources Information Center

Safir, Shane

2018-01-01

"Coming from complexity science, the term emergence describes the dynamic and unpredictable ways through which change unfolds in organizations," writes Shane Safir in this article about how teacher leaders can transform a school's climate and culture. Using Berkeley High School in California as an example, Safir explains how successful…

Multistate and phase change selection in constitutional multivalent systems.

PubMed

Barboiu, Mihail

2012-01-01

Molecular architectures and materials can be constitutionally self-sorted in the presence of different biomolecular targets or external physical stimuli or chemical effectors, thus responding to an external selection pressure. The high selectivity and specificity of different bioreceptors or self-correlated internal interactions may be used to describe the complex constitutional behaviors through multistate component selection from a dynamic library. The self-selection may result in the dynamic amplification of self-optimized architectures during the phase change process. The sol-gel resolution of dynamic molecular/supramolecular libraries leads to higher self-organized constitutional hybrid materials, in which organic (supramolecular)/inorganic domains are reversibily connected.

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.

The Influence of Information Acquisition on the Complex Dynamics of Market Competition

NASA Astrophysics Data System (ADS)

Guo, Zhanbing; Ma, Junhai

In this paper, we build a dynamical game model with three bounded rational players (firms) to study the influence of information on the complex dynamics of market competition, where useful information is about rival’s real decision. In this dynamical game model, one information-sharing team is composed of two firms, they acquire and share the information about their common competitor, however, they make their own decisions separately, where the amount of information acquired by this information-sharing team will determine the estimation accuracy about the rival’s real decision. Based on this dynamical game model and some creative 3D diagrams, the influence of the amount of information on the complex dynamics of market competition such as local dynamics, global dynamics and profits is studied. These results have significant theoretical and practical values to realize the influence of information.

Modeling Endoplasmic Reticulum Network Maintenance in a Plant Cell.

PubMed

Lin, Congping; White, Rhiannon R; Sparkes, Imogen; Ashwin, Peter

2017-07-11

The endoplasmic reticulum (ER) in plant cells forms a highly dynamic network of complex geometry. ER network morphology and dynamics are influenced by a number of biophysical processes, including filament/tubule tension, viscous forces, Brownian diffusion, and interactions with many other organelles and cytoskeletal elements. Previous studies have indicated that ER networks can be thought of as constrained minimal-length networks acted on by a variety of forces that perturb and/or remodel the network. Here, we study two specific biophysical processes involved in remodeling. One is the dynamic relaxation process involving a combination of tubule tension and viscous forces. The other is the rapid creation of cross-connection tubules by direct or indirect interactions with cytoskeletal elements. These processes are able to remodel the ER network: the first reduces network length and complexity whereas the second increases both. Using live cell imaging of ER network dynamics in tobacco leaf epidermal cells, we examine these processes on ER network dynamics. Away from regions of cytoplasmic streaming, we suggest that the dynamic network structure is a balance between the two processes, and we build an integrative model of the two processes for network remodeling. This model produces quantitatively similar ER networks to those observed in experiments. We use the model to explore the effect of parameter variation on statistical properties of the ER network. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

A role for low-order system dynamics models in urban health policy making.

PubMed

Newell, Barry; Siri, José

2016-10-01

Cities are complex adaptive systems whose responses to policy initiatives emerge from feedback interactions between their parts. Urban policy makers must routinely deal with both detail and dynamic complexity, coupled with high levels of diversity, uncertainty and contingency. In such circumstances, it is difficult to generate reliable predictions of health-policy outcomes. In this paper we explore the potential for low-order system dynamics (LOSD) models to make a contribution towards meeting this challenge. By definition, LOSD models have few state variables (≤5), illustrate the non-linear effects caused by feedback and accumulation, and focus on endogenous dynamics generated within well-defined boundaries. We suggest that experience with LOSD models can help practitioners to develop an understanding of basic principles of system dynamics, giving them the ability to 'see with new eyes'. Because efforts to build a set of LOSD models can help a transdisciplinary group to develop a shared, coherent view of the problems that they seek to tackle, such models can also become the foundations of 'powerful ideas'. Powerful ideas are conceptual metaphors that provide the members of a policy-making group with the a priori shared context required for effective communication, the co-production of knowledge, and the collaborative development of effective public health policies. Copyright © 2016 Elsevier Ltd. All rights reserved.

The Dynamics of the Human Leukocyte Antigen Head Domain Modulates Its Recognition by the T-Cell Receptor.

PubMed

García-Guerrero, Estefanía; Pérez-Simón, José Antonio; Sánchez-Abarca, Luis Ignacio; Díaz-Moreno, Irene; De la Rosa, Miguel A; Díaz-Quintana, Antonio

2016-01-01

Generating the immune response requires the discrimination of peptides presented by the human leukocyte antigen complex (HLA) through the T-cell receptor (TCR). However, how a single amino acid substitution in the antigen bonded to HLA affects the response of T cells remains uncertain. Hence, we used molecular dynamics computations to analyze the molecular interactions between peptides, HLA and TCR. We compared immunologically reactive complexes with non-reactive and weakly reactive complexes. MD trajectories were produced to simulate the behavior of isolated components of the various p-HLA-TCR complexes. Analysis of the fluctuations showed that p-HLA binding barely restrains TCR motions, and mainly affects the CDR3 loops. Conversely, inactive p-HLA complexes displayed significant drop in their dynamics when compared with its free versus ternary forms (p-HLA-TCR). In agreement, the free non-reactive p-HLA complexes showed a lower amount of salt bridges than the responsive ones. This resulted in differences between the electrostatic potentials of reactive and inactive p-HLA species and larger vibrational entropies in non-elicitor complexes. Analysis of the ternary p-HLA-TCR complexes also revealed a larger number of salt bridges in the responsive complexes. To summarize, our computations indicate that the affinity of each p-HLA complex towards TCR is intimately linked to both, the dynamics of its free species and its ability to form specific intermolecular salt-bridges in the ternary complexes. Of outstanding interest is the emerging concept of antigen reactivity involving its interplay with the HLA head sidechain dynamics by rearranging its salt-bridges.

Dynamic two-photon imaging of the immune response to Toxoplasma gondii infection.

PubMed

Luu, L; Coombes, J L

2015-03-01

Toxoplasma gondii is a highly successful parasite that can manipulate host immune responses to optimize its persistence and spread. As a result, a highly complex relationship exists between T. gondii and the immune system of the host. Advances in imaging techniques, and in particular, the application of two-photon microscopy to mouse infection models, have made it possible to directly visualize interactions between parasites and the host immune system as they occur in living tissues. Here, we will discuss how dynamic imaging techniques have provided unexpected new insight into (i) how immune responses are dynamically regulated by cells and structures in the local tissue environment, (ii) how protective responses to T. gondii are generated and (iii) how the parasite exploits the immune system for its own benefit. © 2014 John Wiley & Sons Ltd.

Multichannel high-order harmonic generation from solids

NASA Astrophysics Data System (ADS)

Du, Tao-Yuan; Tang, Dong; Huang, Xiao-Huan; Bian, Xue-Bin

2018-04-01

We studied the ultrafast dynamics of high-order harmonic generation (HHG) from solids numerically. It is found that a superposition of Bloch oscillation in the same band and Zenner tunneling to its neighboring conduction band (i.e., Bloch-Zener oscillation effect) play significant roles in HHG when the Bloch electrons cross the boundary of the first Brillouin zone. It increases the number of the harmonic emission channels. These multichannel signals extend the cutoff energy of the plateau in the HHG spectra and enhance both the intra- and interband contributions. The interference of different channels makes the structure of the HHG spectra complex. The multichannel dynamics in the monochromatic and two-color laser fields are demonstrated in a periodic potential model and single-crystal MgO, respectively. It provides an alternative way to control the ultrafast electron dynamics and HHG emission processes in solids.

High-Speed Systolic Array Testbed.

DTIC Science & Technology

1987-10-01

applications since the concept was introduced by H.T. Kung In 1978. This highly parallel architecture of nearet neighbor data communciation and...must be addressed. For instance, should bit-serial or bit parallei computation be utilized. Does the dynamic range of the candidate applications or...numericai stability of the algorithms used require computations In fixed point and Integer format or the architecturally more complex and slower floating

Automatic network coupling analysis for dynamical systems based on detailed kinetic models.

PubMed

Lebiedz, Dirk; Kammerer, Julia; Brandt-Pollmann, Ulrich

2005-10-01

We introduce a numerical complexity reduction method for the automatic identification and analysis of dynamic network decompositions in (bio)chemical kinetics based on error-controlled computation of a minimal model dimension represented by the number of (locally) active dynamical modes. Our algorithm exploits a generalized sensitivity analysis along state trajectories and subsequent singular value decomposition of sensitivity matrices for the identification of these dominant dynamical modes. It allows for a dynamic coupling analysis of (bio)chemical species in kinetic models that can be exploited for the piecewise computation of a minimal model on small time intervals and offers valuable functional insight into highly nonlinear reaction mechanisms and network dynamics. We present results for the identification of network decompositions in a simple oscillatory chemical reaction, time scale separation based model reduction in a Michaelis-Menten enzyme system and network decomposition of a detailed model for the oscillatory peroxidase-oxidase enzyme system.

Experimental Study of Slabbing and Rockburst Induced by True-Triaxial Unloading and Local Dynamic Disturbance

NASA Astrophysics Data System (ADS)

Du, Kun; Tao, Ming; Li, Xi-bing; Zhou, Jian

2016-09-01

Slabbing/spalling and rockburst are unconventional types of failure of hard rocks under conditions of unloading and various dynamic loads in environments with high and complex initial stresses. In this study, the failure behaviors of different rock types (granite, red sandstone, and cement mortar) were investigated using a novel testing system coupled to true-triaxial static loads and local dynamic disturbances. An acoustic emission system and a high-speed camera were used to record the real-time fracturing processes. The true-triaxial unloading test results indicate that slabbing occurred in the granite and sandstone, whereas the cement mortar underwent shear failure. Under local dynamically disturbed loading, none of the specimens displayed obvious fracturing at low-amplitude local dynamic loading; however, the degree of rock failure increased as the local dynamic loading amplitude increased. The cement mortar displayed no failure during testing, showing a considerable load-carrying capacity after testing. The sandstone underwent a relatively stable fracturing process, whereas violent rockbursts occurred in the granite specimen. The fracturing process does not appear to depend on the direction of local dynamic loading, and the acoustic emission count rate during rock fragmentation shows that similar crack evolution occurred under the two test scenarios (true-triaxial unloading and local dynamically disturbed loading).

Variable input observer for state estimation of high-rate dynamics

NASA Astrophysics Data System (ADS)

Hong, Jonathan; Cao, Liang; Laflamme, Simon; Dodson, Jacob

2017-04-01

High-rate systems operating in the 10 μs to 10 ms timescale are likely to experience damaging effects due to rapid environmental changes (e.g., turbulence, ballistic impact). Some of these systems could benefit from real-time state estimation to enable their full potential. Examples of such systems include blast mitigation strategies, automotive airbag technologies, and hypersonic vehicles. Particular challenges in high-rate state estimation include: 1) complex time varying nonlinearities of system (e.g. noise, uncertainty, and disturbance); 2) rapid environmental changes; 3) requirement of high convergence rate. Here, we propose using a Variable Input Observer (VIO) concept to vary the input space as the event unfolds. When systems experience high-rate dynamics, rapid changes in the system occur. To investigate the VIO's potential, a VIO-based neuro-observer is constructed and studied using experimental data collected from a laboratory impact test. Results demonstrate that the input space is unique to different impact conditions, and that adjusting the input space throughout the dynamic event produces better estimations than using a traditional fixed input space strategy.

COMBINED DELAY AND GRAPH EMBEDDING OF EPILEPTIC DISCHARGES IN EEG REVEALS COMPLEX AND RECURRENT NONLINEAR DYNAMICS.

PubMed

Erem, B; Hyde, D E; Peters, J M; Duffy, F H; Brooks, D H; Warfield, S K

2015-04-01

The dynamical structure of the brain's electrical signals contains valuable information about its physiology. Here we combine techniques for nonlinear dynamical analysis and manifold identification to reveal complex and recurrent dynamics in interictal epileptiform discharges (IEDs). Our results suggest that recurrent IEDs exhibit some consistent dynamics, which may only last briefly, and so individual IED dynamics may need to be considered in order to understand their genesis. This could potentially serve to constrain the dynamics of the inverse source localization problem.

Dynamic rupture simulations of the 2016 Mw7.8 Kaikōura earthquake: a cascading multi-fault event

NASA Astrophysics Data System (ADS)

Ulrich, T.; Gabriel, A. A.; Ampuero, J. P.; Xu, W.; Feng, G.

2017-12-01

The Mw7.8 Kaikōura earthquake struck the Northern part of New Zealand's South Island roughly one year ago. It ruptured multiple segments of the contractional North Canterbury fault zone and of the Marlborough fault system. Field observations combined with satellite data suggest a rupture path involving partly unmapped faults separated by large stepover distances larger than 5 km, the maximum distance usually considered by the latest seismic hazard assessment methods. This might imply distant rupture transfer mechanisms generally not considered in seismic hazard assessment. We present high-resolution 3D dynamic rupture simulations of the Kaikōura earthquake under physically self-consistent initial stress and strength conditions. Our simulations are based on recent finite-fault slip inversions that constrain fault system geometry and final slip distribution from remote sensing, surface rupture and geodetic data (Xu et al., 2017). We assume a uniform background stress field, without lateral fault stress or strength heterogeneity. We use the open-source software SeisSol (www.seissol.org) which is based on an arbitrary high-order accurate DERivative Discontinuous Galerkin method (ADER-DG). Our method can account for complex fault geometries, high resolution topography and bathymetry, 3D subsurface structure, off-fault plasticity and modern friction laws. It enables the simulation of seismic wave propagation with high-order accuracy in space and time in complex media. We show that a cascading rupture driven by dynamic triggering can break all fault segments that were involved in this earthquake without mechanically requiring an underlying thrust fault. Our prefered fault geometry connects most fault segments: it does not features stepover larger than 2 km. The best scenario matches the main macroscopic characteristics of the earthquake, including its apparently slow rupture propagation caused by zigzag cascading, the moment magnitude and the overall inferred slip distribution. We observe a high sensitivity of cascading dynamics on fault-step over distance and off-fault energy dissipation.

Improved methods of performing coherent optical correlation

NASA Technical Reports Server (NTRS)

Husain-Abidi, A. S.

1972-01-01

Coherent optical correlators are described in which complex spatial filters are recorded by a quasi-Fourier transform method. The high-pass spatial filtering effects (due to the dynamic range of photographic films) normally encountered in Vander Lugt type complex filters are not present in this system. Experimental results for both transmittive as well as reflective objects are presented. Experiments are also performed by illuminating the object with diffused light. A correlator using paraboloidal mirror segments as the Fourier-transforming element is also described.

Lifetimes of the Vibrational States of DNA Molecules in Functionalized Complexes of Semiconductor Quantum Dots

NASA Astrophysics Data System (ADS)

Bayramov, F. B.; Poloskin, E. D.; Chernev, A. L.; Toporov, V. V.; Dubina, M. V.; Sprung, C.; Lipsanen, H. K.; Bairamov, B. Kh.

2018-01-01

Results of studying nanocrystalline nc-Si/SiO2 quantum dots (QDs) functionalized by short oligonucleotides show that complexes of isolated crystalline semiconductor QDs are unique objects for detecting the manifestation of new quantum confinement phenomena. It is established that narrow lines observed in high-resolution spectra of inelastic light scattering can be used for determining the characteristic time scale of vibrational excitations of separate nucleotide molecules and for studying structural-dynamic properties of fast oscillatory processes in biomacromolecules.

[Questions concerning humanitarian action].

PubMed

Simonnot, C

2002-01-01

Although development of humanitarian action is rooted historical events, the dynamics behind today's international relief organizations can only be understood within the context of the modern world. Relief organizations are currently confronted with major challenges and paradoxes. The challenges include the need to enhance professionalization and standardization of assistance operations and exposure to greater risks. The paradoxes involve the need to implement complex, highly publicized programs in a simplistic manner and problems involved in managing the complex relationship between relief workers and victims, tainted with the almighty powers of the actors.

Intelligent classifier for dynamic fault patterns based on hidden Markov model

NASA Astrophysics Data System (ADS)

Xu, Bo; Feng, Yuguang; Yu, Jinsong

2006-11-01

It's difficult to build precise mathematical models for complex engineering systems because of the complexity of the structure and dynamics characteristics. Intelligent fault diagnosis introduces artificial intelligence and works in a different way without building the analytical mathematical model of a diagnostic object, so it's a practical approach to solve diagnostic problems of complex systems. This paper presents an intelligent fault diagnosis method, an integrated fault-pattern classifier based on Hidden Markov Model (HMM). This classifier consists of dynamic time warping (DTW) algorithm, self-organizing feature mapping (SOFM) network and Hidden Markov Model. First, after dynamic observation vector in measuring space is processed by DTW, the error vector including the fault feature of being tested system is obtained. Then a SOFM network is used as a feature extractor and vector quantization processor. Finally, fault diagnosis is realized by fault patterns classifying with the Hidden Markov Model classifier. The importing of dynamic time warping solves the problem of feature extracting from dynamic process vectors of complex system such as aeroengine, and makes it come true to diagnose complex system by utilizing dynamic process information. Simulating experiments show that the diagnosis model is easy to extend, and the fault pattern classifier is efficient and is convenient to the detecting and diagnosing of new faults.

Dynamical arrest with zero complexity: The unusual behavior of the spherical Blume-Emery-Griffiths disordered model

NASA Astrophysics Data System (ADS)

Rainone, Corrado; Ferrari, Ulisse; Paoluzzi, Matteo; Leuzzi, Luca

2015-12-01

The short- and long-time dynamics of model systems undergoing a glass transition with apparent inversion of Kauzmann and dynamical arrest glass transition lines is investigated. These models belong to the class of the spherical mean-field approximation of a spin-1 model with p -body quenched disordered interaction, with p >2 , termed spherical Blume-Emery-Griffiths models. Depending on temperature and chemical potential the system is found in a paramagnetic or in a glassy phase and the transition between these phases can be of a different nature. In specific regions of the phase diagram coexistence of low-density and high-density paramagnets can occur, as well as the coexistence of spin-glass and paramagnetic phases. The exact static solution for the glassy phase is known to be obtained by the one-step replica symmetry breaking ansatz. Different scenarios arise for both the dynamic and the thermodynamic transitions. These include: (i) the usual random first-order transition (Kauzmann-like) for mean-field glasses preceded by a dynamic transition, (ii) a thermodynamic first-order transition with phase coexistence and latent heat, and (iii) a regime of apparent inversion of static transition line and dynamic transition lines, the latter defined as a nonzero complexity line. The latter inversion, though, turns out to be preceded by a dynamical arrest line at higher temperature. Crossover between different regimes is analyzed by solving mode-coupling-theory equations near the boundaries of paramagnetic solutions and the relationship with the underlying statics is discussed.

Theoretical fluid dynamics

NASA Astrophysics Data System (ADS)

Shivamoggi, B. K.

This book is concerned with a discussion of the dynamical behavior of a fluid, and is addressed primarily to graduate students and researchers in theoretical physics and applied mathematics. A review of basic concepts and equations of fluid dynamics is presented, taking into account a fluid model of systems, the objective of fluid dynamics, the fluid state, description of the flow field, volume forces and surface forces, relative motion near a point, stress-strain relation, equations of fluid flows, surface tension, and a program for analysis of the governing equations. The dynamics of incompressible fluid flows is considered along with the dynamics of compressible fluid flows, the dynamics of viscous fluid flows, hydrodynamic stability, and dynamics of turbulence. Attention is given to the complex-variable method, three-dimensional irrotational flows, vortex flows, rotating flows, water waves, applications to aerodynamics, shock waves, potential flows, the hodograph method, flows at low and high Reynolds numbers, the Jeffrey-Hamel flow, and the capillary instability of a liquid jet.

Noise and poise: Enhancement of postural complexity in the elderly with a stochastic-resonance based therapy

NASA Astrophysics Data System (ADS)

Costa, M.; Priplata, A. A.; Lipsitz, L. A.; Wu, Z.; Huang, N. E.; Goldberger, A. L.; Peng, C.-K.

2007-03-01

Pathologic states are associated with a loss of dynamical complexity. Therefore, therapeutic interventions that increase physiologic complexity may enhance health status. Using multiscale entropy analysis, we show that the postural sway dynamics of healthy young and healthy elderly subjects are more complex than that of elderly subjects with a history of falls. Application of subsensory noise to the feet has been demonstrated to improve postural stability in the elderly. We next show that this therapy significantly increases the multiscale complexity of sway fluctuations in healthy elderly subjects. Quantification of changes in dynamical complexity of biologic variability may be the basis of a new approach to assessing risk and to predicting the efficacy of clinical interventions, including noise-based therapies.

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

Borreguero, Jose M.; Pincus, Philip A.; Sumpter, Bobby G.

Structure–property relationships of ionic block copolymer (BCP) surfactant complexes are critical toward the progress of favorable engineering design of efficient charge-transport materials. In this paper, molecular dynamics simulations are used to understand the dynamics of charged-neutral BCP and surfactant complexes. The dynamics are examined for two different systems: charged-neutral double-hydrophilic and hydrophobic–hydrophilic block copolymers with oppositely charged surfactant moieties. The dynamics of the surfactant head, tails, and charges are studied for five different BCP volume fractions. We observe that the dynamics of the different species solely depend on the balance between electrostatic and entropic interactions between the charged species andmore » the neutral monomers. The favorable hydrophobic–hydrophobic interactions and the unfavorable hydrophobic–hydrophilic interactions determine the mobilities of the monomers. The dynamical properties of the charge species influence complex formation. Structural relaxations exhibit length-scale dependent behavior, with slower relaxation at the radius of gyration length-scale and faster relaxation at the segmental length-scale, consistent with previous results. The dynamical analysis correlates ion-exchange kinetics to the self-assembly behavior of the complexes.« less

A framework for stochastic simulations and visualization of biological electron-transfer dynamics

NASA Astrophysics Data System (ADS)

Nakano, C. Masato; Byun, Hye Suk; Ma, Heng; Wei, Tao; El-Naggar, Mohamed Y.

2015-08-01

Electron transfer (ET) dictates a wide variety of energy-conversion processes in biological systems. Visualizing ET dynamics could provide key insight into understanding and possibly controlling these processes. We present a computational framework named VizBET to visualize biological ET dynamics, using an outer-membrane Mtr-Omc cytochrome complex in Shewanella oneidensis MR-1 as an example. Starting from X-ray crystal structures of the constituent cytochromes, molecular dynamics simulations are combined with homology modeling, protein docking, and binding free energy computations to sample the configuration of the complex as well as the change of the free energy associated with ET. This information, along with quantum-mechanical calculations of the electronic coupling, provides inputs to kinetic Monte Carlo (KMC) simulations of ET dynamics in a network of heme groups within the complex. Visualization of the KMC simulation results has been implemented as a plugin to the Visual Molecular Dynamics (VMD) software. VizBET has been used to reveal the nature of ET dynamics associated with novel nonequilibrium phase transitions in a candidate configuration of the Mtr-Omc complex due to electron-electron interactions.

Single-molecule visualization of Saccharomyces cerevisiae leading-strand synthesis reveals dynamic interaction between MTC and the replisome

PubMed Central

Lewis, Jacob S.; Spenkelink, Lisanne M.; Schauer, Grant D.; Hill, Flynn R.; Georgescu, Roxanna E.; O’Donnell, Michael E.; van Oijen, Antoine M.

2017-01-01

The replisome, the multiprotein system responsible for genome duplication, is a highly dynamic complex displaying a large number of different enzyme activities. Recently, the Saccharomyces cerevisiae minimal replication reaction has been successfully reconstituted in vitro. This provided an opportunity to uncover the enzymatic activities of many of the components in a eukaryotic system. Their dynamic behavior and interactions in the context of the replisome, however, remain unclear. We use a tethered-bead assay to provide real-time visualization of leading-strand synthesis by the S. cerevisiae replisome at the single-molecule level. The minimal reconstituted leading-strand replisome requires 24 proteins, forming the CMG helicase, the Pol ε DNA polymerase, the RFC clamp loader, the PCNA sliding clamp, and the RPA single-stranded DNA binding protein. We observe rates and product lengths similar to those obtained from ensemble biochemical experiments. At the single-molecule level, we probe the behavior of two components of the replication progression complex and characterize their interaction with active leading-strand replisomes. The Minichromosome maintenance protein 10 (Mcm10), an important player in CMG activation, increases the number of productive replication events in our assay. Furthermore, we show that the fork protection complex Mrc1–Tof1–Csm3 (MTC) enhances the rate of the leading-strand replisome threefold. The introduction of periods of fast replication by MTC leads to an average rate enhancement of a factor of 2, similar to observations in cellular studies. We observe that the MTC complex acts in a dynamic fashion with the moving replisome, leading to alternating phases of slow and fast replication. PMID:28923950

Nonlinear dynamics behavior analysis of the spatial configuration of a tendril-bearing plant

NASA Astrophysics Data System (ADS)

Feng, Jingjing; Zhang, Qichang; Wang, Wei; Hao, Shuying

2017-03-01

Tendril-bearing plants appear to have a spiraling shape when tendrils climb along a support during growth. The growth characteristics of a tendril-bearer can be simplified to a model of a thin elastic rod with a cylindrical constraint. In this paper, the connection between some typical configuration characteristics of tendrils and complex nonlinear dynamic behavior are qualitatively analyzed. The space configuration problem of tendrils can be explained through the study of the nonlinear dynamic behavior of the thin elastic rod system equation. In this study, the complex non-Z2 symmetric critical orbits in the system equation under critical parameters were presented. A new function transformation method that can effectively maintain the critical orbit properties was proposed, and a new nonlinear differential equations system containing complex nonlinear terms can been obtained to describe the cross section position and direction of a rod during climbing. Numerical simulation revealed that the new system can describe the configuration of a rod with reasonable accuracy. To adequately explain the growing regulation of the rod shape, the critical orbit and configuration of rod are connected in a direct way. The high precision analytical expressions of these complex non-Z2 symmetric critical orbits are obtained by introducing a suitable analytical method, and then these expressions are used to draw the corresponding three-dimensional configuration figures of an elastic thin rod. Combined with actual tendrils on a live plant, the space configuration of the winding knots of tendril is explained by the concept of heteroclinic orbit from the perspective of nonlinear dynamics, and correctness of the theoretical analysis was verified. This theoretical analysis method could also be effectively applied to other similar slender structures.

Molecular dynamics study of HIV-1 RT-DNA-nevirapine complexes explains NNRTI inhibition and resistance by connection mutations.

PubMed

Vijayan, R S K; Arnold, Eddy; Das, Kalyan

2014-05-01

HIV-1 reverse transcriptase (RT) is a multifunctional enzyme that is targeted by nucleoside analogs (NRTIs) and non-nucleoside RT inhibitors (NNRTIs). NNRTIs are allosteric inhibitors of RT, and constitute an integral part of several highly active antiretroviral therapy regimens. Under selective pressure, HIV-1 acquires resistance against NNRTIs primarily by selecting mutations around the NNRTI pocket. Complete RT sequencing of clinical isolates revealed that spatially distal mutations arising in connection and the RNase H domain also confer NNRTI resistance and contribute to NRTI resistance. However, the precise structural mechanism by which the connection domain mutations confer NNRTI resistance is poorly understood. We performed 50-ns molecular dynamics (MD) simulations, followed by essential dynamics, free-energy landscape analyses, and network analyses of RT-DNA, RT-DNA-nevirapine (NVP), and N348I/T369I mutant RT-DNA-NVP complexes. MD simulation studies revealed altered global motions and restricted conformational landscape of RT upon NVP binding. Analysis of protein structure network parameters demonstrated a dissortative hub pattern in the RT-DNA complex and an assortative hub pattern in the RT-DNA-NVP complex suggesting enhanced rigidity of RT upon NVP binding. The connection subdomain mutations N348I/T369I did not induce any significant structural change; rather, these mutations modulate the conformational dynamics and alter the long-range allosteric communication network between the connection subdomain and NNRTI pocket. Insights from the present study provide a structural basis for the biochemical and clinical findings on drug resistance caused by the connection and RNase H mutations. Copyright © 2013 Wiley Periodicals, Inc.

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.

αE-catenin regulates actin dynamics independently of cadherin-mediated cell–cell adhesion

PubMed Central

Benjamin, Jacqueline M.; Kwiatkowski, Adam V.; Yang, Changsong; Korobova, Farida; Pokutta, Sabine; Svitkina, Tatyana

2010-01-01

αE-catenin binds the cell–cell adhesion complex of E-cadherin and β-catenin (β-cat) and regulates filamentous actin (F-actin) dynamics. In vitro, binding of αE-catenin to the E-cadherin–β-cat complex lowers αE-catenin affinity for F-actin, and αE-catenin alone can bind F-actin and inhibit Arp2/3 complex–mediated actin polymerization. In cells, to test whether αE-catenin regulates actin dynamics independently of the cadherin complex, the cytosolic αE-catenin pool was sequestered to mitochondria without affecting overall levels of αE-catenin or the cadherin–catenin complex. Sequestering cytosolic αE-catenin to mitochondria alters lamellipodia architecture and increases membrane dynamics and cell migration without affecting cell–cell adhesion. In contrast, sequestration of cytosolic αE-catenin to the plasma membrane reduces membrane dynamics. These results demonstrate that the cytosolic pool of αE-catenin regulates actin dynamics independently of cell–cell adhesion. PMID:20404114

Entropy for the Complexity of Physiological Signal Dynamics.

PubMed

Zhang, Xiaohua Douglas

2017-01-01

Recently, the rapid development of large data storage technologies, mobile network technology, and portable medical devices makes it possible to measure, record, store, and track analysis of biological dynamics. Portable noninvasive medical devices are crucial to capture individual characteristics of biological dynamics. The wearable noninvasive medical devices and the analysis/management of related digital medical data will revolutionize the management and treatment of diseases, subsequently resulting in the establishment of a new healthcare system. One of the key features that can be extracted from the data obtained by wearable noninvasive medical device is the complexity of physiological signals, which can be represented by entropy of biological dynamics contained in the physiological signals measured by these continuous monitoring medical devices. Thus, in this chapter I present the major concepts of entropy that are commonly used to measure the complexity of biological dynamics. The concepts include Shannon entropy, Kolmogorov entropy, Renyi entropy, approximate entropy, sample entropy, and multiscale entropy. I also demonstrate an example of using entropy for the complexity of glucose dynamics.

Dynamics of Defects and Dopants in Complex Systems: Si and Oxide Surfaces and Interfaces

NASA Astrophysics Data System (ADS)

Kirichenko, Taras; Yu, Decai; Banarjee, Sanjay; Hwang, Gyeong

2004-10-01

Fabrication of forthcoming nanometer scale electronic devices faces many difficulties including formation of extremely shallow and highly doped junctions. At present, ultra-low-energy ion implantation followed by high-temperature thermal annealing is most widely used to fabricate such ultra-shallow junctions. In the process, a great challenge lies in achieving precise control of redistribution and electrical activation of dopant impurities. Native defects (such as vacancies and interstitials) generated during implantation are known to be mainly responsible for the TED and also influence significantly the electrical activation/deactivation. Defect-dopant dynamics is rather well understood in crystalline Si and SiO2. However, little is known about their diffusion and annihilation (or precipitation) at the surfaces and interfaces, despite its growing importance in determining junction profiles as device dimensions get smaller. In this talk, we will present our density functional theory calculation results on the atomic and electronic structure and dynamical behavior of native defects and dopant-defect complexes in disordered/strained Si and oxide systems, such as i) clean and absorbent-modified Si(100) surface and subsurface layers, ii) amorphous-crystalline Si interfaces and iii) amorphous SiO2/Si interfaces. The fundamental understanding and data is essential in developing a comprehensive kinetic model for junction formation, which would contribute greatly in improving current process technologies.

A global "imaging'' view on systems approaches in immunology.

PubMed

Ludewig, Burkhard; Stein, Jens V; Sharpe, James; Cervantes-Barragan, Luisa; Thiel, Volker; Bocharov, Gennady

2012-12-01

The immune system exhibits an enormous complexity. High throughput methods such as the "-omic'' technologies generate vast amounts of data that facilitate dissection of immunological processes at ever finer resolution. Using high-resolution data-driven systems analysis, causal relationships between complex molecular processes and particular immunological phenotypes can be constructed. However, processes in tissues, organs, and the organism itself (so-called higher level processes) also control and regulate the molecular (lower level) processes. Reverse systems engineering approaches, which focus on the examination of the structure, dynamics and control of the immune system, can help to understand the construction principles of the immune system. Such integrative mechanistic models can properly describe, explain, and predict the behavior of the immune system in health and disease by combining both higher and lower level processes. Moving from molecular and cellular levels to a multiscale systems understanding requires the development of methodologies that integrate data from different biological levels into multiscale mechanistic models. In particular, 3D imaging techniques and 4D modeling of the spatiotemporal dynamics of immune processes within lymphoid tissues are central for such integrative approaches. Both dynamic and global organ imaging technologies will be instrumental in facilitating comprehensive multiscale systems immunology analyses as discussed in this review. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Src SH2 domain interacts dynamically with the focal adhesion kinase binding site as demonstrated by paramagnetic NMR spectroscopy.

PubMed

Lindfors, Hanna E; Drijfhout, Jan Wouter; Ubbink, Marcellus

2012-06-01

The interaction between the tyrosine kinases Src and focal adhesion kinase (FAK) is a key step in signaling processes from focal adhesions. The phosphorylated tyrosine residue 397 in FAK is able to bind the Src SH2 domain. To establish the extent of the FAK binding motif, the binding affinity of the SH2 domain for phosphorylated and unphosphorylated FAK-derived peptides of increasing length was determined and compared with that of the internal Src SH2 binding site. It is shown that the FAK peptides have higher affinity than the internal binding site and that seven negative residues adjacent to the core SH2 binding motif increase the binding constant 30-fold. A rigid spin-label incorporated in the FAK peptides was used to establish on the basis of paramagnetic relaxation enhancement whether the peptide-protein complex is well defined. A large spread of the paramagnetic effects on the surface of the SH2 domain suggests that the peptide-protein complex exhibits dynamics, despite the high affinity of the peptide. The strong electrostatic interaction between the positive side of the SH2 domain and the negative peptide results in a high affinity but may also favor a dynamic interaction. Copyright © 2012 Wiley Periodicals, Inc.

Desolvation-Driven 100-Fold Slow-down of Tunneling Relaxation Rate in Co(II)-Dy(III) Single-Molecule Magnets through a Single-Crystal-to-Single-Crystal Process

NASA Astrophysics Data System (ADS)

Liu, Jun-Liang; Wu, Jie-Yi; Huang, Guo-Zhang; Chen, Yan-Cong; Jia, Jian-Hua; Ungur, Liviu; Chibotaru, Liviu F.; Chen, Xiao-Ming; Tong, Ming-Liang

2015-11-01

Single-molecule magnets (SMMs) are regarded as a class of promising materials for spintronic and ultrahigh-density storage devices. Tuning the magnetic dynamics of single-molecule magnets is a crucial challenge for chemists. Lanthanide ions are not only highly magnetically anisotropic but also highly sensitive to the changes in the coordination environments. We developed a feasible approach to understand parts of the magneto-structure correlations and propose to regulate the relaxation behaviors via rational design. A series of Co(II)-Dy(III)-Co(II) complexes were obtained using in situ synthesis; in this system of complexes, the relaxation dynamics can be greatly improved, accompanied with desolvation, via single-crystal to single-crystal transformation. The effective energy barrier can be increased from 293 cm-1 (422 K) to 416 cm-1 (600 K), and the tunneling relaxation time can be grown from 8.5 × 10-4 s to 7.4 × 10-2 s. These remarkable improvements are due to the change in the coordination environments of Dy(III) and Co(II). Ab initio calculations were performed to better understand the magnetic dynamics.

Dynamics of Disordered PI-PtBS Diblock Copolymer

NASA Astrophysics Data System (ADS)

Watanabe, Hiroshi

2009-03-01

Viscoelastic (G^*) and dielectric (ɛ'') data were examined for a LCST-type diblock copolymer composed of polyisoprene (PI; M = 53K) and poly(p-tert- butyl styrene) (PtBS; M = 42K) blocks disordered at T <=120 C^o. Only PI had the type-A dipole parallel along the chain backbone. Thus, the ɛ'' data reflected the global motion of the PI block, while the G^* data detected the motion of the copolymer chain as a whole. Comparison of these data indicated that the PI block relaxed much faster than the PtBS block at low T and the dynamic heterogeneity due to PtBS was effectively quenched to give a frictional nonuniformity for the PI block relaxation. The ɛ'' data were thermo-rheologically complex at low T, partly due to this nonuniformity. However, the block connectivity could have also led to the complexity. For testing this effect, the ɛ'' data were reduced at the iso- frictional state defined with respect to bulk PI. In this state, the ɛ'' data of the copolymer at low and high T, respectively, were close to the data for the star-branched and linear bulk PI. Thus, the PI block appeared to be effectively tethered in space at low T thereby behaving similarly to the star arm while the PI block tended to move cooperatively with the PtBS block at high T to behave similarly to the linear PI, which led to the complexity of the ɛ'' data. The PtBS block also exhibited the complexity (noted from the G^* data), which was well correlated with the complexity of the PI block.

Batch-mode Reinforcement Learning for improved hydro-environmental systems management

NASA Astrophysics Data System (ADS)

Castelletti, A.; Galelli, S.; Restelli, M.; Soncini-Sessa, R.

2010-12-01

Despite the great progresses made in the last decades, the optimal management of hydro-environmental systems still remains a very active and challenging research area. The combination of multiple, often conflicting interests, high non-linearities of the physical processes and the management objectives, strong uncertainties in the inputs, and high dimensional state makes the problem challenging and intriguing. Stochastic Dynamic Programming (SDP) is one of the most suitable methods for designing (Pareto) optimal management policies preserving the original problem complexity. However, it suffers from a dual curse, which, de facto, prevents its practical application to even reasonably complex water systems. (i) Computational requirement grows exponentially with state and control dimension (Bellman's curse of dimensionality), so that SDP can not be used with water systems where the state vector includes more than few (2-3) units. (ii) An explicit model of each system's component is required (curse of modelling) to anticipate the effects of the system transitions, i.e. any information included into the SDP framework can only be either a state variable described by a dynamic model or a stochastic disturbance, independent in time, with the associated pdf. Any exogenous information that could effectively improve the system operation cannot be explicitly considered in taking the management decision, unless a dynamic model is identified for each additional information, thus adding to the problem complexity through the curse of dimensionality (additional state variables). To mitigate this dual curse, the combined use of batch-mode Reinforcement Learning (bRL) and Dynamic Model Reduction (DMR) techniques is explored in this study. bRL overcomes the curse of modelling by replacing explicit modelling with an external simulator and/or historical observations. The curse of dimensionality is averted using a functional approximation of the SDP value function based on proper non-linear regressors. DMR reduces the complexity and the associated computational requirements of non-linear distributed process based models, making them suitable for being included into optimization schemes. Results from real world applications of the approach are also presented, including reservoir operation with both quality and quantity targets.

A framework to observe and evaluate the sustainability of human-natural systems in a complex dynamic context.

PubMed

Satanarachchi, Niranji; Mino, Takashi

2014-01-01

This paper aims to explore the prominent implications of the process of observing complex dynamics linked to sustainability in human-natural systems and to propose a framework for sustainability evaluation by introducing the concept of sustainability boundaries. Arguing that both observing and evaluating sustainability should engage awareness of complex dynamics from the outset, we try to embody this idea in the framework by two complementary methods, namely, the layer view- and dimensional view-based methods, which support the understanding of a reflexive and iterative sustainability process. The framework enables the observation of complex dynamic sustainability contexts, which we call observation metastructures, and enable us to map the contexts to sustainability boundaries.

Code Samples Used for Complexity and Control

NASA Astrophysics Data System (ADS)

Ivancevic, Vladimir G.; Reid, Darryn J.

2015-11-01

The following sections are included: * MathematicaⓇ Code * Generic Chaotic Simulator * Vector Differential Operators * NLS Explorer * 2C++ Code * C++ Lambda Functions for Real Calculus * Accelerometer Data Processor * Simple Predictor-Corrector Integrator * Solving the BVP with the Shooting Method * Linear Hyperbolic PDE Solver * Linear Elliptic PDE Solver * Method of Lines for a Set of the NLS Equations * C# Code * Iterative Equation Solver * Simulated Annealing: A Function Minimum * Simple Nonlinear Dynamics * Nonlinear Pendulum Simulator * Lagrangian Dynamics Simulator * Complex-Valued Crowd Attractor Dynamics * Freeform Fortran Code * Lorenz Attractor Simulator * Complex Lorenz Attractor * Simple SGE Soliton * Complex Signal Presentation * Gaussian Wave Packet * Hermitian Matrices * Euclidean L2-Norm * Vector/Matrix Operations * Plain C-Code: Levenberg-Marquardt Optimizer * Free Basic Code: 2D Crowd Dynamics with 3000 Agents

CFD: computational fluid dynamics or confounding factor dissemination? The role of hemodynamics in intracranial aneurysm rupture risk assessment.

PubMed

Xiang, J; Tutino, V M; Snyder, K V; Meng, H

2014-10-01

Image-based computational fluid dynamics holds a prominent position in the evaluation of intracranial aneurysms, especially as a promising tool to stratify rupture risk. Current computational fluid dynamics findings correlating both high and low wall shear stress with intracranial aneurysm growth and rupture puzzle researchers and clinicians alike. These conflicting findings may stem from inconsistent parameter definitions, small datasets, and intrinsic complexities in intracranial aneurysm growth and rupture. In Part 1 of this 2-part review, we proposed a unifying hypothesis: both high and low wall shear stress drive intracranial aneurysm growth and rupture through mural cell-mediated and inflammatory cell-mediated destructive remodeling pathways, respectively. In the present report, Part 2, we delineate different wall shear stress parameter definitions and survey recent computational fluid dynamics studies, in light of this mechanistic heterogeneity. In the future, we expect that larger datasets, better analyses, and increased understanding of hemodynamic-biologic mechanisms will lead to more accurate predictive models for intracranial aneurysm risk assessment from computational fluid dynamics. © 2014 by American Journal of Neuroradiology.

Ratcheting rotation or speedy spinning: EPR and dynamics of Sc3C2@C80.

PubMed

Roukala, Juho; Straka, Michal; Taubert, Stefan; Vaara, Juha; Lantto, Perttu

2017-08-08

Besides their technological applications, endohedral fullerenes provide ideal conditions for investigating molecular dynamics in restricted geometries. A representative of this class of systems, Sc 3 C 2 @C 80 displays complex intramolecular dynamics. The motion of the 45 Sc trimer has a remarkable effect on its electron paramagnetic resonance (EPR) spectrum, which changes from a symmetric 22-peak pattern at high temperature to a single broad lineshape at low temperature. The scandium trimer consists of two equivalent and one inequivalent metal atom, due to the carbon dimer rocking through the Sc 3 triangle. We demonstrate through first-principles molecular dynamics (MD), EPR parameter tensor averaging, and spectral modelling that, at high temperatures, three-dimensional movement of the enclosed Sc 3 C 2 moiety takes place, which renders the metal centers equivalent and their magnetic parameters effectively isotropic. In contrast, at low temperatures the dynamics becomes restricted to two dimensions within the equatorial belt of the I h symmetric C 80 host fullerene. This restores the inequivalence of the scandium centers and causes their anisotropic hyperfine couplings to broaden the experimental spectrum.

Major Histocompatibility Complex (MHC) Class I and MHC Class II Proteins: Conformational Plasticity in Antigen Presentation

PubMed Central

Wieczorek, Marek; Abualrous, Esam T.; Sticht, Jana; Álvaro-Benito, Miguel; Stolzenberg, Sebastian; Noé, Frank; Freund, Christian

2017-01-01

Antigen presentation by major histocompatibility complex (MHC) proteins is essential for adaptive immunity. Prior to presentation, peptides need to be generated from proteins that are either produced by the cell’s own translational machinery or that are funneled into the endo-lysosomal vesicular system. The prolonged interaction between a T cell receptor and specific pMHC complexes, after an extensive search process in secondary lymphatic organs, eventually triggers T cells to proliferate and to mount a specific cellular immune response. Once processed, the peptide repertoire presented by MHC proteins largely depends on structural features of the binding groove of each particular MHC allelic variant. Additionally, two peptide editors—tapasin for class I and HLA-DM for class II—contribute to the shaping of the presented peptidome by favoring the binding of high-affinity antigens. Although there is a vast amount of biochemical and structural information, the mechanism of the catalyzed peptide exchange for MHC class I and class II proteins still remains controversial, and it is not well understood why certain MHC allelic variants are more susceptible to peptide editing than others. Recent studies predict a high impact of protein intermediate states on MHC allele-specific peptide presentation, which implies a profound influence of MHC dynamics on the phenomenon of immunodominance and the development of autoimmune diseases. Here, we review the recent literature that describe MHC class I and II dynamics from a theoretical and experimental point of view and we highlight the similarities between MHC class I and class II dynamics despite the distinct functions they fulfill in adaptive immunity. PMID:28367149

Double dynamic scaling in human communication dynamics

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Flow networks for Ocean currents

NASA Astrophysics Data System (ADS)

Tupikina, Liubov; Molkenthin, Nora; Marwan, Norbert; Kurths, Jürgen

2014-05-01

Complex networks have been successfully applied to various systems such as society, technology, and recently climate. Links in a climate network are defined between two geographical locations if the correlation between the time series of some climate variable is higher than a threshold. Therefore, network links are considered to imply heat exchange. However, the relationship between the oceanic and atmospheric flows and the climate network's structure is still unclear. Recently, a theoretical approach verifying the correlation between ocean currents and surface air temperature networks has been introduced, where the Pearson correlation networks were constructed from advection-diffusion dynamics on an underlying flow. Since the continuous approach has its limitations, i.e., by its high computational complexity, we here introduce a new, discrete construction of flow-networks, which is then applied to static and dynamic velocity fields. Analyzing the flow-networks of prototypical flows we find that our approach can highlight the zones of high velocity by degree and transition zones by betweenness, while the combination of these network measures can uncover how the flow propagates within time. We also apply the method to time series data of the Equatorial Pacific Ocean Current and the Gulf Stream ocean current for the changing velocity fields, which could not been done before, and analyse the properties of the dynamical system. Flow-networks can be powerful tools to theoretically understand the step from system's dynamics to network's topology that can be analyzed using network measures and is used for shading light on different climatic phenomena.

Multi-step cure kinetic model of ultra-thin glass fiber epoxy prepreg exhibiting both autocatalytic and diffusion-controlled regimes under isothermal and dynamic-heating conditions

NASA Astrophysics Data System (ADS)

Kim, Ye Chan; Min, Hyunsung; Hong, Sungyong; Wang, Mei; Sun, Hanna; Park, In-Kyung; Choi, Hyouk Ryeol; Koo, Ja Choon; Moon, Hyungpil; Kim, Kwang J.; Suhr, Jonghwan; Nam, Jae-Do

2017-08-01

As packaging technologies are demanded that reduce the assembly area of substrate, thin composite laminate substrates require the utmost high performance in such material properties as the coefficient of thermal expansion (CTE), and stiffness. Accordingly, thermosetting resin systems, which consist of multiple fillers, monomers and/or catalysts in thermoset-based glass fiber prepregs, are extremely complicated and closely associated with rheological properties, which depend on the temperature cycles for cure. For the process control of these complex systems, it is usually required to obtain a reliable kinetic model that could be used for the complex thermal cycles, which usually includes both the isothermal and dynamic-heating segments. In this study, an ultra-thin prepreg with highly loaded silica beads and glass fibers in the epoxy/amine resin system was investigated as a model system by isothermal/dynamic heating experiments. The maximum degree of cure was obtained as a function of temperature. The curing kinetics of the model prepreg system exhibited a multi-step reaction and a limited conversion as a function of isothermal curing temperatures, which are often observed in epoxy cure system because of the rate-determining diffusion of polymer chain growth. The modified kinetic equation accurately described the isothermal behavior and the beginning of the dynamic-heating behavior by integrating the obtained maximum degree of cure into the kinetic model development.

Dimensionality and entropy of spontaneous and evoked rate activity

NASA Astrophysics Data System (ADS)

Engelken, Rainer; Wolf, Fred

Cortical circuits exhibit complex activity patterns both spontaneously and evoked by external stimuli. Finding low-dimensional structure in population activity is a challenge. What is the diversity of the collective neural activity and how is it affected by an external stimulus? Using concepts from ergodic theory, we calculate the attractor dimensionality and dynamical entropy production of these networks. We obtain these two canonical measures of the collective network dynamics from the full set of Lyapunov exponents. We consider a randomly-wired firing-rate network that exhibits chaotic rate fluctuations for sufficiently strong synaptic weights. We show that dynamical entropy scales logarithmically with synaptic coupling strength, while the attractor dimensionality saturates. Thus, despite the increasing uncertainty, the diversity of collective activity saturates for strong coupling. We find that a time-varying external stimulus drastically reduces both entropy and dimensionality. Finally, we analytically approximate the full Lyapunov spectrum in several limiting cases by random matrix theory. Our study opens a novel avenue to characterize the complex dynamics of rate networks and the geometric structure of the corresponding high-dimensional chaotic attractor. received funding from Evangelisches Studienwerk Villigst, DFG through CRC 889 and Volkswagen Foundation.

The Wisdom of Tacit Knowing-in-Action and Mission Command

ERIC Educational Resources Information Center

Moilanen, Jon H.

2015-01-01

Adult learners regularly confront complex and dynamic challenges in moments of crisis that require self-efficacy of intuition and immediate decision. Such "snap decision-making" requires highly developed critical thinking skills to effectively operate in the midst of chaos. This decisiveness is particularly challenging in the military…