Specialized CFD Grid Generation Methods for Near-Field Sonic Boom Prediction

NASA Technical Reports Server (NTRS)

Park, Michael A.; Campbell, Richard L.; Elmiligui, Alaa; Cliff, Susan E.; Nayani, Sudheer N.

2014-01-01

Ongoing interest in analysis and design of low sonic boom supersonic transports re- quires accurate and ecient Computational Fluid Dynamics (CFD) tools. Specialized grid generation techniques are employed to predict near- eld acoustic signatures of these con- gurations. A fundamental examination of grid properties is performed including grid alignment with ow characteristics and element type. The issues a ecting the robustness of cylindrical surface extrusion are illustrated. This study will compare three methods in the extrusion family of grid generation methods that produce grids aligned with the freestream Mach angle. These methods are applied to con gurations from the First AIAA Sonic Boom Prediction Workshop.

Hybrid robust predictive optimization method of power system dispatch

DOEpatents

Chandra, Ramu Sharat [Niskayuna, NY; Liu, Yan [Ballston Lake, NY; Bose, Sumit [Niskayuna, NY; de Bedout, Juan Manuel [West Glenville, NY

2011-08-02

A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

Unbalance Response Analysis and Experimental Validation of an Ultra High Speed Motor-Generator for Microturbine Generators Considering Balancing

PubMed Central

Hong, Do-Kwan; Joo, Dae-Suk; Woo, Byung-Chul; Koo, Dae-Hyun; Ahn, Chan-Woo

2014-01-01

The objective of the present study was to deal with the rotordynamics of the rotor of an ultra-high speed PM type synchronous motor-generator for a 500 W rated micro gas turbine generator. This paper introduces dynamic analysis, and experiments on the motor-generator. The focus is placed on an analytical approach considering the mechanical dynamic problems. It is essential to deal with dynamic stability at ultra-high speeds. Unbalance response analysis is performed by calculating the unbalance with and without balancing using a balancing machine. Critical speed analysis is performed to determine the operating speed with sufficient separation margin. The unbalance response analysis is compared with the experimental results considering the balancing grade (ISO 1940-1) and predicted vibration displacement with and without balancing. Based on these results, a high-speed motor-generator was successfully developed. PMID:25177804

Quantitative theory of driven nonlinear brain dynamics.

PubMed

Roberts, J A; Robinson, P A

2012-09-01

Strong periodic stimuli such as bright flashing lights evoke nonlinear responses in the brain and interact nonlinearly with ongoing cortical activity, but the underlying mechanisms for these phenomena are poorly understood at present. The dominant features of these experimentally observed dynamics are reproduced by the dynamics of a quantitative neural field model subject to periodic drive. Model power spectra over a range of drive frequencies show agreement with multiple features of experimental measurements, exhibiting nonlinear effects including entrainment over a range of frequencies around the natural alpha frequency f(α), subharmonic entrainment near 2f(α), and harmonic generation. Further analysis of the driven dynamics as a function of the drive parameters reveals rich nonlinear dynamics that is predicted to be observable in future experiments at high drive amplitude, including period doubling, bistable phase-locking, hysteresis, wave mixing, and chaos indicated by positive Lyapunov exponents. Moreover, photosensitive seizures are predicted for physiologically realistic model parameters yielding bistability between healthy and seizure dynamics. These results demonstrate the applicability of neural field models to the new regime of periodically driven nonlinear dynamics, enabling interpretation of experimental data in terms of specific generating mechanisms and providing new tests of the theory. Copyright © 2012 Elsevier Inc. All rights reserved.

Spectral simplicity of apparent complexity. I. The nondiagonalizable metadynamics of prediction

NASA Astrophysics Data System (ADS)

Riechers, Paul M.; Crutchfield, James P.

2018-03-01

Virtually all questions that one can ask about the behavioral and structural complexity of a stochastic process reduce to a linear algebraic framing of a time evolution governed by an appropriate hidden-Markov process generator. Each type of question—correlation, predictability, predictive cost, observer synchronization, and the like—induces a distinct generator class. Answers are then functions of the class-appropriate transition dynamic. Unfortunately, these dynamics are generically nonnormal, nondiagonalizable, singular, and so on. Tractably analyzing these dynamics relies on adapting the recently introduced meromorphic functional calculus, which specifies the spectral decomposition of functions of nondiagonalizable linear operators, even when the function poles and zeros coincide with the operator's spectrum. Along the way, we establish special properties of the spectral projection operators that demonstrate how they capture the organization of subprocesses within a complex system. Circumventing the spurious infinities of alternative calculi, this leads in the sequel, Part II [P. M. Riechers and J. P. Crutchfield, Chaos 28, 033116 (2018)], to the first closed-form expressions for complexity measures, couched either in terms of the Drazin inverse (negative-one power of a singular operator) or the eigenvalues and projection operators of the appropriate transition dynamic.

Dynamically generated N* and {Lambda}* resonances in the hidden charm sector around 4.3 GeV

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

Wu Jiajun; Departamento de Fisica Teorica and IFIC, Centro Mixto Universidad de Valencia-CSIC, Institutos de Investigacion de Paterna, Aptdo. 22085, E-46071 Valencia; Molina, R.

2011-07-15

The interactions of D-bar{Sigma}{sub c}-D-bar{Lambda}{sub c}, D-bar*{Sigma}{sub c}-D-bar*{Lambda}{sub c}, and related strangeness channels, are studied within the framework of the coupled-channel unitary approach with the local hidden gauge formalism. A series of meson-baryon dynamically generated relatively narrow N* and {Lambda}* resonances are predicted around 4.3 GeV in the hidden charm sector. We make estimates of production cross sections of these predicted resonances in p-barp collisions for the experiment of antiproton annihilation at Darmstadt (PANDA) at the forthcoming GSI Facility for Antiproton and Ion Research (FAIR) facility.

Inferior olive mirrors joint dynamics to implement an inverse controller.

PubMed

Alvarez-Icaza, Rodrigo; Boahen, Kwabena

2012-10-01

To produce smooth and coordinated motion, our nervous systems need to generate precisely timed muscle activation patterns that, due to axonal conduction delay, must be generated in a predictive and feedforward manner. Kawato proposed that the cerebellum accomplishes this by acting as an inverse controller that modulates descending motor commands to predictively drive the spinal cord such that the musculoskeletal dynamics are canceled out. This and other cerebellar theories do not, however, account for the rich biophysical properties expressed by the olivocerebellar complex's various cell types, making these theories difficult to verify experimentally. Here we propose that a multizonal microcomplex's (MZMC) inferior olivary neurons use their subthreshold oscillations to mirror a musculoskeletal joint's underdamped dynamics, thereby achieving inverse control. We used control theory to map a joint's inverse model onto an MZMC's biophysics, and we used biophysical modeling to confirm that inferior olivary neurons can express the dynamics required to mirror biomechanical joints. We then combined both techniques to predict how experimentally injecting current into the inferior olive would affect overall motor output performance. We found that this experimental manipulation unmasked a joint's natural dynamics, as observed by motor output ringing at the joint's natural frequency, with amplitude proportional to the amount of current. These results support the proposal that the cerebellum-in particular an MZMC-is an inverse controller; the results also provide a biophysical implementation for this controller and allow one to make an experimentally testable prediction.

Neural dynamics of reward probability coding: a Magnetoencephalographic study in humans

PubMed Central

Thomas, Julie; Vanni-Mercier, Giovanna; Dreher, Jean-Claude

2013-01-01

Prediction of future rewards and discrepancy between actual and expected outcomes (prediction error) are crucial signals for adaptive behavior. In humans, a number of fMRI studies demonstrated that reward probability modulates these two signals in a large brain network. Yet, the spatio-temporal dynamics underlying the neural coding of reward probability remains unknown. Here, using magnetoencephalography, we investigated the neural dynamics of prediction and reward prediction error computations while subjects learned to associate cues of slot machines with monetary rewards with different probabilities. We showed that event-related magnetic fields (ERFs) arising from the visual cortex coded the expected reward value 155 ms after the cue, demonstrating that reward value signals emerge early in the visual stream. Moreover, a prediction error was reflected in ERF peaking 300 ms after the rewarded outcome and showing decreasing amplitude with higher reward probability. This prediction error signal was generated in a network including the anterior and posterior cingulate cortex. These findings pinpoint the spatio-temporal characteristics underlying reward probability coding. Together, our results provide insights into the neural dynamics underlying the ability to learn probabilistic stimuli-reward contingencies. PMID:24302894

Dynamic Modeling of Solar Dynamic Components and Systems

NASA Technical Reports Server (NTRS)

Hochstein, John I.; Korakianitis, T.

1992-01-01

The purpose of this grant was to support NASA in modeling efforts to predict the transient dynamic and thermodynamic response of the space station solar dynamic power generation system. In order to meet the initial schedule requirement of providing results in time to support installation of the system as part of the initial phase of space station, early efforts were executed with alacrity and often in parallel. Initially, methods to predict the transient response of a Rankine as well as a Brayton cycle were developed. Review of preliminary design concepts led NASA to select a regenerative gas-turbine cycle using a helium-xenon mixture as the working fluid and, from that point forward, the modeling effort focused exclusively on that system. Although initial project planning called for a three year period of performance, revised NASA schedules moved system installation to later and later phases of station deployment. Eventually, NASA selected to halt development of the solar dynamic power generation system for space station and to reduce support for this project to two-thirds of the original level.

Effects of the infectious period distribution on predicted transitions in childhood disease dynamics

PubMed Central

Krylova, Olga; Earn, David J. D.

2013-01-01

The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced ‘susceptible–exposed–infectious–removed’ (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible–infectious–removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions. PMID:23676892

Effects of the infectious period distribution on predicted transitions in childhood disease dynamics.

PubMed

Krylova, Olga; Earn, David J D

2013-07-06

The population dynamics of infectious diseases occasionally undergo rapid qualitative changes, such as transitions from annual to biennial cycles or to irregular dynamics. Previous work, based on the standard seasonally forced 'susceptible-exposed-infectious-removed' (SEIR) model has found that transitions in the dynamics of many childhood diseases result from bifurcations induced by slow changes in birth and vaccination rates. However, the standard SEIR formulation assumes that the stage durations (latent and infectious periods) are exponentially distributed, whereas real distributions are narrower and centred around the mean. Much recent work has indicated that realistically distributed stage durations strongly affect the dynamical structure of seasonally forced epidemic models. We investigate whether inferences drawn from previous analyses of transitions in patterns of measles dynamics are robust to the shapes of the stage duration distributions. As an illustrative example, we analyse measles dynamics in New York City from 1928 to 1972. We find that with a fixed mean infectious period in the susceptible-infectious-removed (SIR) model, the dynamical structure and predicted transitions vary substantially as a function of the shape of the infectious period distribution. By contrast, with fixed mean latent and infectious periods in the SEIR model, the shapes of the stage duration distributions have a less dramatic effect on model dynamical structure and predicted transitions. All these results can be understood more easily by considering the distribution of the disease generation time as opposed to the distributions of individual disease stages. Numerical bifurcation analysis reveals that for a given mean generation time the dynamics of the SIR and SEIR models for measles are nearly equivalent and are insensitive to the shapes of the disease stage distributions.

Conformal completion of the standard model with a fourth generation

NASA Astrophysics Data System (ADS)

Ho, Chiu Man; Hung, Pham Q.; Kephart, Thomas W.

2012-06-01

We study dynamical electroweak symmetry breaking with a fourth generation within the Z n orbifolded AdS 5 ⊗ S 5 framework. A realistic Z 7 example is discussed. The initial theory reduces dynamically, due to the induced condensates, to a four-family trinification near a TeV-scale conformal fixed point where the gauge hierarchy problem does not exist. We predict new gauge bosons and bifundamental fermions and scalars accessible by the LHC.

Wind Turbine Dynamics

NASA Technical Reports Server (NTRS)

Thresher, R. W. (Editor)

1981-01-01

Recent progress in the analysis and prediction of the dynamic behavior of wind turbine generators is discussed. The following areas were addressed: (1) the adequacy of state of the art analysis tools for designing the next generation of wind power systems; (2) the use of state of the art analysis tools designers; and (3) verifications of theory which might be lacking or inadequate. Summaries of these informative discussions as well as the questions and answers which followed each paper are documented in the proceedings.

Bioinactivation: Software for modelling dynamic microbial inactivation.

PubMed

Garre, Alberto; Fernández, Pablo S; Lindqvist, Roland; Egea, Jose A

2017-03-01

This contribution presents the bioinactivation software, which implements functions for the modelling of isothermal and non-isothermal microbial inactivation. This software offers features such as user-friendliness, modelling of dynamic conditions, possibility to choose the fitting algorithm and generation of prediction intervals. The software is offered in two different formats: Bioinactivation core and Bioinactivation SE. Bioinactivation core is a package for the R programming language, which includes features for the generation of predictions and for the fitting of models to inactivation experiments using non-linear regression or a Markov Chain Monte Carlo algorithm (MCMC). The calculations are based on inactivation models common in academia and industry (Bigelow, Peleg, Mafart and Geeraerd). Bioinactivation SE supplies a user-friendly interface to selected functions of Bioinactivation core, namely the model fitting of non-isothermal experiments and the generation of prediction intervals. The capabilities of bioinactivation are presented in this paper through a case study, modelling the non-isothermal inactivation of Bacillus sporothermodurans. This study has provided a full characterization of the response of the bacteria to dynamic temperature conditions, including confidence intervals for the model parameters and a prediction interval of the survivor curve. We conclude that the MCMC algorithm produces a better characterization of the biological uncertainty and variability than non-linear regression. The bioinactivation software can be relevant to the food and pharmaceutical industry, as well as to regulatory agencies, as part of a (quantitative) microbial risk assessment. Copyright © 2017 Elsevier Ltd. All rights reserved.

Ramping and Uncertainty Prediction Tool - Analysis and Visualization of Wind Generation Impact on Electrical Grid

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

Etingov, Pavel; Makarov, PNNL Yuri; Subbarao, PNNL Kris

RUT software is designed for use by the Balancing Authorities to predict and display additional requirements caused by the variability and uncertainty in load and generation. The prediction is made for the next operating hours as well as for the next day. The tool predicts possible deficiencies in generation capability and ramping capability. This deficiency of balancing resources can cause serious risks to power system stability and also impact real-time market energy prices. The tool dynamically and adaptively correlates changing system conditions with the additional balancing needs triggered by the interplay between forecasted and actual load and output of variablemore » resources. The assessment is performed using a specially developed probabilistic algorithm incorporating multiple sources of uncertainty including wind, solar and load forecast errors. The tool evaluates required generation for a worst case scenario, with a user-specified confidence level.« less

Dynamic Testing of a Subscale Sunshield for the Next Generation Space Telescope (NGST)

NASA Technical Reports Server (NTRS)

Lienard, Sebastien; Johnston, John D.; Ross, Brian; Smith, James; Brodeur, Steve (Technical Monitor)

2001-01-01

The NGST sunshield is a lightweight, flexible structure consisting of multiple layers of pretensioned, thin-film membranes supported by deployable booms. The structural dynamic behavior of the sunshield must be well understood in order to predict its influence on observatory performance. Ground tests were carried out in a vacuum environment to characterize the structural dynamic behavior of a one-tenth scale model of the sunshield. Results from the tests will be used to validate analytical modeling techniques that can be used in conjunction with scaling laws to predict the performance of the full-sized structure. This paper summarizes the ground tests and presents representative results for the dynamic behavior of the sunshield.

Modeling effects of environmental change on wolf population dynamics, trait evolution, and life history.

PubMed

Coulson, Tim; MacNulty, Daniel R; Stahler, Daniel R; vonHoldt, Bridgett; Wayne, Robert K; Smith, Douglas W

2011-12-02

Environmental change has been observed to generate simultaneous responses in population dynamics, life history, gene frequencies, and morphology in a number of species. But how common are such eco-evolutionary responses to environmental change likely to be? Are they inevitable, or do they require a specific type of change? Can we accurately predict eco-evolutionary responses? We address these questions using theory and data from the study of Yellowstone wolves. We show that environmental change is expected to generate eco-evolutionary change, that changes in the average environment will affect wolves to a greater extent than changes in how variable it is, and that accurate prediction of the consequences of environmental change will probably prove elusive.

Multiple frequency interference in photorefractive media

NASA Technical Reports Server (NTRS)

Cox, David E.; Welch, Sharon S.

1992-01-01

The paper describes the use of a numerical simulation to predict the dynamic behavior of a photorefractive crystal exposed to interfering light waves at two different frequencies. Unlike static recording media, photorefractive materials allow for the simultaneous diffraction from and generation of refractive index gratings. The grating properties are evaluated in terms of their effect on the performance of a dynamic distributed sensor which uses the crystal as a holographic recording medium. Experimental results are presented which support the behavior predicted by simulation.

A dynamic spatio-temporal model for spatial data

USGS Publications Warehouse

Hefley, Trevor J.; Hooten, Mevin B.; Hanks, Ephraim M.; Russell, Robin; Walsh, Daniel P.

2017-01-01

Analyzing spatial data often requires modeling dependencies created by a dynamic spatio-temporal data generating process. In many applications, a generalized linear mixed model (GLMM) is used with a random effect to account for spatial dependence and to provide optimal spatial predictions. Location-specific covariates are often included as fixed effects in a GLMM and may be collinear with the spatial random effect, which can negatively affect inference. We propose a dynamic approach to account for spatial dependence that incorporates scientific knowledge of the spatio-temporal data generating process. Our approach relies on a dynamic spatio-temporal model that explicitly incorporates location-specific covariates. We illustrate our approach with a spatially varying ecological diffusion model implemented using a computationally efficient homogenization technique. We apply our model to understand individual-level and location-specific risk factors associated with chronic wasting disease in white-tailed deer from Wisconsin, USA and estimate the location the disease was first introduced. We compare our approach to several existing methods that are commonly used in spatial statistics. Our spatio-temporal approach resulted in a higher predictive accuracy when compared to methods based on optimal spatial prediction, obviated confounding among the spatially indexed covariates and the spatial random effect, and provided additional information that will be important for containing disease outbreaks.

Working memory dynamics bias the generation of beliefs: the influence of data presentation rate on hypothesis generation.

PubMed

Lange, Nicholas D; Thomas, Rick P; Buttaccio, Daniel R; Illingworth, David A; Davelaar, Eddy J

2013-02-01

Although temporal dynamics are inherent aspects of diagnostic tasks, few studies have investigated how various aspects of time course influence hypothesis generation. An experiment is reported that demonstrates that working memory dynamics operating during serial data acquisition bias hypothesis generation. The presentation rate (and order) of a sequence of serially presented symptoms was manipulated to be either fast (180 ms per symptom) or slow (1,500 ms per symptom) in a simulated medical diagnosis task. When the presentation rate was slow, participants chose the disease hypothesis consistent with the symptoms appearing later in the sequence. When the presentation rate was fast, however, participants chose the disease hypothesis consistent with the symptoms appearing earlier in the sequence, therefore representing a novel primacy effect. We predicted and account for this effect through competitive working memory dynamics governing information acquisition and the contribution of maintained information to the retrieval of hypotheses from long-term memory.

Generation separation in simple structured life cycles: models and 48 years of field data on a tea tortrix moth.

PubMed

Yamanaka, Takehiko; Nelson, William A; Uchimura, Koichiro; Bjørnstad, Ottar N

2012-01-01

Population cycles have fascinated ecologists since the early nineteenth century, and the dynamics of insect populations have been central to understanding the intrinsic and extrinsic biological processes responsible for these cycles. We analyzed an extraordinary long-term data set (every 5 days for 48 years) of a tea tortrix moth (Adoxophyes honmai) that exhibits two dominant cycles: an annual cycle with a conspicuous pattern of four or five single-generation cycles superimposed on it. General theory offers several candidate mechanisms for generation cycles. To evaluate these, we construct and parameterize a series of temperature-dependent, stage-structured models that include intraspecific competition, parasitism, mate-finding Allee effects, and adult senescence, all in the context of a seasonal environment. By comparing the observed dynamics with predictions from the models, we find that even weak larval competition in the presence of seasonal temperature forcing predicts the two cycles accurately. None of the other mechanisms predicts the dynamics. Detailed dissection of the results shows that a short reproductive life span and differential winter mortality among stages are the additional life-cycle characteristics that permit the sustained cycles. Our general modeling approach is applicable to a wide range of organisms with temperature-dependent life histories and is likely to prove particularly useful in temperate systems where insect pest outbreaks are both density and temperature dependent. © 2011 by The University of Chicago.

Structural characterization of a first-generation articulated-truss joint for space crane application

NASA Technical Reports Server (NTRS)

Sutter, Thomas R.; Wu, K. Chauncey; Riutort, Kevin T.; Laufer, Joseph B.; Phelps, James E.

1992-01-01

A first-generation space crane articulated-truss joint was statically and dynamically characterized in a configuration that approximated an operational environment. The articulated-truss joint was integrated into a test-bed for structural characterization. Static characterization was performed by applying known loads and measuring the corresponding deflections to obtain load-deflection curves. Dynamic characterization was performed using modal testing to experimentally determine the first six mode shapes, frequencies, and modal damping values. Static and dynamic characteristics were also determined for a reference truss that served as a characterization baseline. Load-deflection curves and experimental frequency response functions are presented for the reference truss and the articulated-truss joint mounted in the test-bed. The static and dynamic experimental results are compared with analytical predictions obtained from finite element analyses. Load-deflection response is also presented for one of the linear actuators used in the articulated-truss joint. Finally, an assessment is presented for the predictability of the truss hardware used in the reference truss and articulated-truss joint based upon hardware stiffness properties that were previously obtained during the Precision Segmented Reflector (PSR) Technology Development Program.

Near real-time traffic routing

NASA Technical Reports Server (NTRS)

Yang, Chaowei (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor); Cao, Ying (Inventor)

2012-01-01

A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.

Short-term Temperature Prediction Using Adaptive Computing on Dynamic Scales

NASA Astrophysics Data System (ADS)

Hu, W.; Cervone, G.; Jha, S.; Balasubramanian, V.; Turilli, M.

2017-12-01

When predicting temperature, there are specific places and times when high accuracy predictions are harder. For example, not all the sub-regions in the domain require the same amount of computing resources to generate an accurate prediction. Plateau areas might require less computing resources than mountainous areas because of the steeper gradient of temperature change in the latter. However, it is difficult to estimate beforehand the optimal allocation of computational resources because several parameters play a role in determining the accuracy of the forecasts, in addition to orography. The allocation of resources to perform simulations can become a bottleneck because it requires human intervention to stop jobs or start new ones. The goal of this project is to design and develop a dynamic approach to generate short-term temperature predictions that can automatically determines the required computing resources and the geographic scales of the predictions based on the spatial and temporal uncertainties. The predictions and the prediction quality metrics are computed using a numeric weather prediction model, Analog Ensemble (AnEn), and the parallelization on high performance computing systems is accomplished using Ensemble Toolkit, one component of the RADICAL-Cybertools family of tools. RADICAL-Cybertools decouple the science needs from the computational capabilities by building an intermediate layer to run general ensemble patterns, regardless of the science. In this research, we show how the ensemble toolkit allows generating high resolution temperature forecasts at different spatial and temporal resolution. The AnEn algorithm is run using NAM analysis and forecasts data for the continental United States for a period of 2 years. AnEn results show that temperature forecasts perform well according to different probabilistic and deterministic statistical tests.

Comprehensive Forced Response Analysis of J2X Turbine Bladed-Discs with 360 Degree Variation in CFD Loading

NASA Technical Reports Server (NTRS)

Elrod, David; Christensen, Eric; Brown, Andrew

2011-01-01

The temporal frequency content of the dynamic pressure predicted by a 360 degree computational fluid dynamics (CFD) analysis of a turbine flow field provides indicators of forcing function excitation frequencies (e.g., multiples of blade pass frequency) for turbine components. For the Pratt and Whitney Rocketdyne J-2X engine turbopumps, Campbell diagrams generated using these forcing function frequencies and the results of NASTRAN modal analyses show a number of components with modes in the engine operating range. As a consequence, forced response and static analyses are required for the prediction of combined stress, high cycle fatigue safety factors (HCFSF). Cyclically symmetric structural models have been used to analyze turbine vane and blade rows, not only in modal analyses, but also in forced response and static analyses. Due to the tortuous flow pattern in the turbine, dynamic pressure loading is not cyclically symmetric. Furthermore, CFD analyses predict dynamic pressure waves caused by adjacent and non-adjacent blade/vane rows upstream and downstream of the row analyzed. A MATLAB script has been written to calculate displacements due to the complex cyclically asymmetric dynamic pressure components predicted by CFD analysis, for all grids in a blade/vane row, at a chosen turbopump running speed. The MATLAB displacements are then read into NASTRAN, and dynamic stresses are calculated, including an adjustment for possible mistuning. In a cyclically symmetric NASTRAN static analysis, static stresses due to centrifugal, thermal, and pressure loading at the mode running speed are calculated. MATLAB is used to generate the HCFSF at each grid in the blade/vane row. When compared to an approach assuming cyclic symmetry in the dynamic flow field, the current approach provides better assurance that the worst case safety factor has been identified. An extended example for a J-2X turbopump component is provided.

Applicability of effective fragment potential version 2 - Molecular dynamics (EFP2-MD) simulations for predicting excess properties of mixed solvents

NASA Astrophysics Data System (ADS)

Kuroki, Nahoko; Mori, Hirotoshi

2018-02-01

Effective fragment potential version 2 - molecular dynamics (EFP2-MD) simulations, where the EFP2 is a polarizable force field based on ab initio electronic structure calculations were applied to water-methanol binary mixture. Comparing EFP2s defined with (aug-)cc-pVXZ (X = D,T) basis sets, it was found that large sets are necessary to generate sufficiently accurate EFP2 for predicting mixture properties. It was shown that EFP2-MD could predict the excess molar volume. Since the computational cost of EFP2-MD are far less than ab initio MD, the results presented herein demonstrate that EFP2-MD is promising for predicting physicochemical properties of novel mixed solvents.

Modeling and control of magnetorheological fluid dampers using neural networks

NASA Astrophysics Data System (ADS)

Wang, D. H.; Liao, W. H.

2005-02-01

Due to the inherent nonlinear nature of magnetorheological (MR) fluid dampers, one of the challenging aspects for utilizing these devices to achieve high system performance is the development of accurate models and control algorithms that can take advantage of their unique characteristics. In this paper, the direct identification and inverse dynamic modeling for MR fluid dampers using feedforward and recurrent neural networks are studied. The trained direct identification neural network model can be used to predict the damping force of the MR fluid damper on line, on the basis of the dynamic responses across the MR fluid damper and the command voltage, and the inverse dynamic neural network model can be used to generate the command voltage according to the desired damping force through supervised learning. The architectures and the learning methods of the dynamic neural network models and inverse neural network models for MR fluid dampers are presented, and some simulation results are discussed. Finally, the trained neural network models are applied to predict and control the damping force of the MR fluid damper. Moreover, validation methods for the neural network models developed are proposed and used to evaluate their performance. Validation results with different data sets indicate that the proposed direct identification dynamic model using the recurrent neural network can be used to predict the damping force accurately and the inverse identification dynamic model using the recurrent neural network can act as a damper controller to generate the command voltage when the MR fluid damper is used in a semi-active mode.

Metapopulation responses to patch connectivity and quality are masked by successional habitat dynamics.

PubMed

Hodgson, Jenny A; Moilanen, Atte; Thomas, Chris D

2009-06-01

Many species have to track changes in the spatial distribution of suitable habitat from generation to generation. Understanding the dynamics of such species will likely require spatially explicit models, and patch-based metapopulation models are potentially appropriate. However, relatively little attention has been paid to developing metapopulation models that include habitat dynamics, and very little to testing the predictions of these models. We tested three predictions from theory about the differences between dynamic habitat metapopulations and their static counterparts using long-term survey data from two metapopulations of the butterfly Plebejus argus. As predicted, we showed first that the metapopulation inhabiting dynamic habitat had a lower level of habitat occupancy, which could not be accounted for by other differences between the metapopulations. Secondly, we found that patch occupancy did not significantly increase with increasing patch connectivity in dynamic habitat, whereas there was a strong positive connectivity-occupancy relationship in static habitat. Thirdly, we found no significant relationship between patch occupancy and patch quality in dynamic habitat, whereas there was a strong, positive quality-occupancy relationship in static habitat. Modeling confirmed that the differences in mean patch occupancy and connectivity-occupancy slope could arise without changing the species' metapopulation parameters-importantly, without changing the dependence of colonization upon connectivity. We found that, for a range of landscape scenarios, successional simulations always produced a lower connectivity-occupancy slope than comparable simulations with static patches, whether compared like-for-like or controlling for mean occupancy. We conclude that landscape-scale studies may often underestimate the importance of connectivity for species occurrence and persistence because habitat turnover can obscure the connectivity-occupancy relationship in commonly available snapshot data.

Modeling and Analysis of Structural Dynamics for a One-Tenth Scale Model NGST Sunshield

NASA Technical Reports Server (NTRS)

Johnston, John; Lienard, Sebastien; Brodeur, Steve (Technical Monitor)

2001-01-01

New modeling and analysis techniques have been developed for predicting the dynamic behavior of the Next Generation Space Telescope (NGST) sunshield. The sunshield consists of multiple layers of pretensioned, thin-film membranes supported by deployable booms. Modeling the structural dynamic behavior of the sunshield is a challenging aspect of the problem due to the effects of membrane wrinkling. A finite element model of the sunshield was developed using an approximate engineering approach, the cable network method, to account for membrane wrinkling effects. Ground testing of a one-tenth scale model of the NGST sunshield were carried out to provide data for validating the analytical model. A series of analyses were performed to predict the behavior of the sunshield under the ground test conditions. Modal analyses were performed to predict the frequencies and mode shapes of the test article and transient response analyses were completed to simulate impulse excitation tests. Comparison was made between analytical predictions and test measurements for the dynamic behavior of the sunshield. In general, the results show good agreement with the analytical model correctly predicting the approximate frequency and mode shapes for the significant structural modes.

Response of a tethered aerostat to simulated turbulence

NASA Astrophysics Data System (ADS)

Stanney, Keith A.; Rahn, Christopher D.

2006-09-01

Aerostats are lighter-than-air vehicles tethered to the ground by a cable and used for broadcasting, communications, surveillance, and drug interdiction. The dynamic response of tethered aerostats subject to extreme atmospheric turbulence often dictates survivability. This paper develops a theoretical model that predicts the planar response of a tethered aerostat subject to atmospheric turbulence and simulates the response to 1000 simulated hurricane scale turbulent time histories. The aerostat dynamic model assumes the aerostat hull to be a rigid body with non-linear fluid loading, instantaneous weathervaning for planar response, and a continuous tether. Galerkin's method discretizes the coupled aerostat and tether partial differential equations to produce a non-linear initial value problem that is integrated numerically given initial conditions and wind inputs. The proper orthogonal decomposition theorem generates, based on Hurricane Georges wind data, turbulent time histories that possess the sequential behavior of actual turbulence, are spectrally accurate, and have non-Gaussian density functions. The generated turbulent time histories are simulated to predict the aerostat response to severe turbulence. The resulting probability distributions for the aerostat position, pitch angle, and confluence point tension predict the aerostat behavior in high gust environments. The dynamic results can be up to twice as large as a static analysis indicating the importance of dynamics in aerostat modeling. The results uncover a worst case wind input consisting of a two-pulse vertical gust.

Operational improvements of long-term predicted ephemerides of the Tracking and Data Relay Satellites (TDRSs)

NASA Technical Reports Server (NTRS)

Kostoff, J. L.; Ward, D. T.; Cuevas, O. O.; Beckman, R. M.

1995-01-01

Tracking and Data Relay Satellite (TDRS) orbit determination and prediction are supported by the Flight Dynamics Facility (FDF) of the Goddard Space Flight Center (GSFC) Flight Dynamics Division (FDD). TDRS System (TDRSS)-user satellites require predicted TDRS ephemerides that are up to 10 weeks in length. Previously, long-term ephemerides generated by the FDF included predictions from the White Sands Complex (WSC), which plans and executes TDRS maneuvers. TDRSs typically have monthly stationkeeping maneuvers, and predicted postmaneuver state vectors are received from WSC up to a month in advance. This paper presents the results of an analysis performed in the FDF to investigate more accurate and economical long-term ephemerides for the TDRSs. As a result of this analysis, two new methods for generating long-term TDRS ephemeris predictions have been implemented by the FDF. The Center-of-Box (COB) method models a TDRS as fixed at the center of its stationkeeping box. Using this method, long-term ephemeris updates are made semiannually instead of weekly. The impulse method is used to model more maneuvers. The impulse method yields better short-term accuracy than the COB method, especially for larger stationkeeping boxes. The accuracy of the impulse method depends primarily on the accuracy of maneuver date forecasting.

Nonlinear dynamics of laser systems with elements of a chaos: Advanced computational code

NASA Astrophysics Data System (ADS)

Buyadzhi, V. V.; Glushkov, A. V.; Khetselius, O. Yu; Kuznetsova, A. A.; Buyadzhi, A. A.; Prepelitsa, G. P.; Ternovsky, V. B.

2017-10-01

A general, uniform chaos-geometric computational approach to analysis, modelling and prediction of the non-linear dynamics of quantum and laser systems (laser and quantum generators system etc) with elements of the deterministic chaos is briefly presented. The approach is based on using the advanced generalized techniques such as the wavelet analysis, multi-fractal formalism, mutual information approach, correlation integral analysis, false nearest neighbour algorithm, the Lyapunov’s exponents analysis, and surrogate data method, prediction models etc There are firstly presented the numerical data on the topological and dynamical invariants (in particular, the correlation, embedding, Kaplan-York dimensions, the Lyapunov’s exponents, Kolmogorov’s entropy and other parameters) for laser system (the semiconductor GaAs/GaAlAs laser with a retarded feedback) dynamics in a chaotic and hyperchaotic regimes.

Generating a Dynamic Synthetic Population – Using an Age-Structured Two-Sex Model for Household Dynamics

PubMed Central

Namazi-Rad, Mohammad-Reza; Mokhtarian, Payam; Perez, Pascal

2014-01-01

Generating a reliable computer-simulated synthetic population is necessary for knowledge processing and decision-making analysis in agent-based systems in order to measure, interpret and describe each target area and the human activity patterns within it. In this paper, both synthetic reconstruction (SR) and combinatorial optimisation (CO) techniques are discussed for generating a reliable synthetic population for a certain geographic region (in Australia) using aggregated- and disaggregated-level information available for such an area. A CO algorithm using the quadratic function of population estimators is presented in this paper in order to generate a synthetic population while considering a two-fold nested structure for the individuals and households within the target areas. The baseline population in this study is generated from the confidentialised unit record files (CURFs) and 2006 Australian census tables. The dynamics of the created population is then projected over five years using a dynamic micro-simulation model for individual- and household-level demographic transitions. This projection is then compared with the 2011 Australian census. A prediction interval is provided for the population estimates obtained by the bootstrapping method, by which the variability structure of a predictor can be replicated in a bootstrap distribution. PMID:24733522

Dynamics of Individual cilia to external loading- A simple one dimensional picture

NASA Astrophysics Data System (ADS)

Swaminathan, Vinay; Hill, David; Superfine, R.

2008-10-01

From being called the cellular janitors to swinging debauchers, cilia have captured the fascinations of researchers for over 200 years. In cystic fibrosis and chronic obstructive pulmonary disease where the cilia loses it's function, the protective mucus layer in the lung thickens and mucociliary clearance breaks down, leading to inflammation along the airways and an increased rate of infection. The mechanistic understanding of mucus clearance depends on a quantitative assessment of the axoneme dynamics and the maximum force the cilia are capable of generating and imparting to the mucus layer. Similar to the situation in molecular motors, detailed quantitative measurements of dynamics under applied load conditions are expected to be essential in developing predictive models. Based on our measurements of the dynamics of individual ciliary motion in the human bronchial epithelial cell under the application of an applied load, we present a simple one dimensional model for the axoneme dynamics and quantify the axoneme stiffness, the internal force generated by the axoneme, the stall force and show how the dynamics sheds insight on the time dependence of the internal force generation. The internal force generated by the axoneme is related to the ability of cilia to propel fluids and to their potential role in force sensing.

Aeroacoustics of large wind turbines

NASA Technical Reports Server (NTRS)

Hubbard, Harvey H.; Shepherd, Kevin P.

1991-01-01

This paper reviews published information on aerodynamically generated noise from large horizontal axis wind turbines operated for electric power generation. Methods are presented for predicting both the discrete frequency rotational noise components and the broadband noise components, and results are compared with measurements. Refraction effects that result in the formation of high-frequency shadow zones in the upwind direction and channeling effects for the low frequencies in the downwind direction are illustrated. Special topics such as distributed source effects in prediction and the role of building dynamics in perception are also included.

Predicting Adaptive Behavior in the Environment from Central Nervous System Dynamics

PubMed Central

Proekt, Alex; Wong, Jane; Zhurov, Yuriy; Kozlova, Nataliya; Weiss, Klaudiusz R.; Brezina, Vladimir

2008-01-01

To generate adaptive behavior, the nervous system is coupled to the environment. The coupling constrains the dynamical properties that the nervous system and the environment must have relative to each other if adaptive behavior is to be produced. In previous computational studies, such constraints have been used to evolve controllers or artificial agents to perform a behavioral task in a given environment. Often, however, we already know the controller, the real nervous system, and its dynamics. Here we propose that the constraints can also be used to solve the inverse problem—to predict from the dynamics of the nervous system the environment to which they are adapted, and so reconstruct the production of the adaptive behavior by the entire coupled system. We illustrate how this can be done in the feeding system of the sea slug Aplysia. At the core of this system is a central pattern generator (CPG) that, with dynamics on both fast and slow time scales, integrates incoming sensory stimuli to produce ingestive and egestive motor programs. We run models embodying these CPG dynamics—in effect, autonomous Aplysia agents—in various feeding environments and analyze the performance of the entire system in a realistic feeding task. We find that the dynamics of the system are tuned for optimal performance in a narrow range of environments that correspond well to those that Aplysia encounter in the wild. In these environments, the slow CPG dynamics implement efficient ingestion of edible seaweed strips with minimal sensory information about them. The fast dynamics then implement a switch to a different behavioral mode in which the system ignores the sensory information completely and follows an internal “goal,” emergent from the dynamics, to egest again a strip that proves to be inedible. Key predictions of this reconstruction are confirmed in real feeding animals. PMID:18989362

High accuracy satellite drag model (HASDM)

NASA Astrophysics Data System (ADS)

Storz, M.; Bowman, B.; Branson, J.

The dominant error source in the force models used to predict low perigee satellite trajectories is atmospheric drag. Errors in operational thermospheric density models cause significant errors in predicted satellite positions, since these models do not account for dynamic changes in atmospheric drag for orbit predictions. The Air Force Space Battlelab's High Accuracy Satellite Drag Model (HASDM) estimates and predicts (out three days) a dynamically varying high-resolution density field. HASDM includes the Dynamic Calibration Atmosphere (DCA) algorithm that solves for the phases and amplitudes of the diurnal, semidiurnal and terdiurnal variations of thermospheric density near real-time from the observed drag effects on a set of Low Earth Orbit (LEO) calibration satellites. The density correction is expressed as a function of latitude, local solar time and altitude. In HASDM, a time series prediction filter relates the extreme ultraviolet (EUV) energy index E10.7 and the geomagnetic storm index a p to the DCA density correction parameters. The E10.7 index is generated by the SOLAR2000 model, the first full spectrum model of solar irradiance. The estimated and predicted density fields will be used operationally to significantly improve the accuracy of predicted trajectories for all low perigee satellites.

High accuracy satellite drag model (HASDM)

NASA Astrophysics Data System (ADS)

Storz, Mark F.; Bowman, Bruce R.; Branson, Major James I.; Casali, Stephen J.; Tobiska, W. Kent

The dominant error source in force models used to predict low-perigee satellite trajectories is atmospheric drag. Errors in operational thermospheric density models cause significant errors in predicted satellite positions, since these models do not account for dynamic changes in atmospheric drag for orbit predictions. The Air Force Space Battlelab's High Accuracy Satellite Drag Model (HASDM) estimates and predicts (out three days) a dynamically varying global density field. HASDM includes the Dynamic Calibration Atmosphere (DCA) algorithm that solves for the phases and amplitudes of the diurnal and semidiurnal variations of thermospheric density near real-time from the observed drag effects on a set of Low Earth Orbit (LEO) calibration satellites. The density correction is expressed as a function of latitude, local solar time and altitude. In HASDM, a time series prediction filter relates the extreme ultraviolet (EUV) energy index E10.7 and the geomagnetic storm index ap, to the DCA density correction parameters. The E10.7 index is generated by the SOLAR2000 model, the first full spectrum model of solar irradiance. The estimated and predicted density fields will be used operationally to significantly improve the accuracy of predicted trajectories for all low-perigee satellites.

Preliminary analysis of the PreFlexMS molten salt once-through steam generator dynamics and control strategy

NASA Astrophysics Data System (ADS)

Trabucchi, Stefano; Casella, Francesco; Maioli, Tommaso; Elsido, Cristina; Franzini, Davide; Ramond, Mathieu

2017-06-01

Concentrated Solar Power plants (CSP) coupled with thermal storage have the potential to guarantee both flexible and continuous energy production, thus being competitive with conventional fossil fuel and hydro power plants, in terms of dispatchability and provision of ancillary services. Hence, the plant equipment and control design have to be focused on flexible operation on one hand, and on plant safety concerning the molten salt freezing on the other hand. The PreFlexMS European project aims to introduce a molten salt Once-Through Steam Generator (OTSG) within a Rankine cycle based power unit, a technology that has greater flexibility potential if compared to steam drum boilers, currently used in CSP plants. The dynamic modelling and simulation from the early design stages is, thus, of paramount importance, to assess the plant dynamic behavior and controllability, and to predict the achievable closed-loop dynamic performance, potentially saving money and time during the detailed design, construction and commissioning phases. The present paper reports the main results of the analysis carried out during the first part of the project, regarding the system analysis and control design. In particular, two different control systems have been studied and tested with the plant dynamic model: a decentralized control strategy based on PI controllers and a Linear Model Predictive Control (LMPC).

Dynamic Leidenfrost temperature on micro-textured surfaces: Acoustic wave absorption into thin vapor layer

NASA Astrophysics Data System (ADS)

Jerng, Dong Wook; Kim, Dong Eok

2018-01-01

The dynamic Leidenfrost phenomenon is governed by three types of pressure potentials induced via vapor hydrodynamics, liquid dynamic pressure, and the water hammer effect resulting from the generation of acoustic waves at the liquid-vapor interface. The prediction of the Leidenfrost temperature for a dynamic droplet needs quantitative evaluation and definition for each of the pressure fields. In particular, the textures on a heated surface can significantly affect the vapor hydrodynamics and the water hammer pressure. We present a quantitative model for evaluating the water hammer pressure on micro-textured surfaces taking into account the absorption of acoustic waves into the thin vapor layer. The model demonstrates that the strength of the acoustic flow into the liquid droplet, which directly contributes to the water hammer pressure, depends on the magnitude of the acoustic resistance (impedance) in the droplet and the vapor region. In consequence, the micro-textures of the surface and the increased spacing between them reduce the water hammer coefficient ( kh ) defined as the ratio of the acoustic flow into the droplet to total generated flow. Aided by numerical calculations that solve the laminar Navier-Stokes equation for the vapor flow, we also predict the dynamic Leidenfrost temperature on a micro-textured surface with reliable accuracy consistent with the experimental data.

Comparison of RF spectrum prediction methods for dynamic spectrum access

NASA Astrophysics Data System (ADS)

Kovarskiy, Jacob A.; Martone, Anthony F.; Gallagher, Kyle A.; Sherbondy, Kelly D.; Narayanan, Ram M.

2017-05-01

Dynamic spectrum access (DSA) refers to the adaptive utilization of today's busy electromagnetic spectrum. Cognitive radio/radar technologies require DSA to intelligently transmit and receive information in changing environments. Predicting radio frequency (RF) activity reduces sensing time and energy consumption for identifying usable spectrum. Typical spectrum prediction methods involve modeling spectral statistics with Hidden Markov Models (HMM) or various neural network structures. HMMs describe the time-varying state probabilities of Markov processes as a dynamic Bayesian network. Neural Networks model biological brain neuron connections to perform a wide range of complex and often non-linear computations. This work compares HMM, Multilayer Perceptron (MLP), and Recurrent Neural Network (RNN) algorithms and their ability to perform RF channel state prediction. Monte Carlo simulations on both measured and simulated spectrum data evaluate the performance of these algorithms. Generalizing spectrum occupancy as an alternating renewal process allows Poisson random variables to generate simulated data while energy detection determines the occupancy state of measured RF spectrum data for testing. The results suggest that neural networks achieve better prediction accuracy and prove more adaptable to changing spectral statistics than HMMs given sufficient training data.

Model-Based Analysis of Cell Cycle Responses to Dynamically Changing Environments

PubMed Central

Seaton, Daniel D; Krishnan, J

2016-01-01

Cell cycle progression is carefully coordinated with a cell’s intra- and extracellular environment. While some pathways have been identified that communicate information from the environment to the cell cycle, a systematic understanding of how this information is dynamically processed is lacking. We address this by performing dynamic sensitivity analysis of three mathematical models of the cell cycle in Saccharomyces cerevisiae. We demonstrate that these models make broadly consistent qualitative predictions about cell cycle progression under dynamically changing conditions. For example, it is shown that the models predict anticorrelated changes in cell size and cell cycle duration under different environments independently of the growth rate. This prediction is validated by comparison to available literature data. Other consistent patterns emerge, such as widespread nonmonotonic changes in cell size down generations in response to parameter changes. We extend our analysis by investigating glucose signalling to the cell cycle, showing that known regulation of Cln3 translation and Cln1,2 transcription by glucose is sufficient to explain the experimentally observed changes in cell cycle dynamics at different glucose concentrations. Together, these results provide a framework for understanding the complex responses the cell cycle is capable of producing in response to dynamic environments. PMID:26741131

Action perception as hypothesis testing.

PubMed

Donnarumma, Francesco; Costantini, Marcello; Ambrosini, Ettore; Friston, Karl; Pezzulo, Giovanni

2017-04-01

We present a novel computational model that describes action perception as an active inferential process that combines motor prediction (the reuse of our own motor system to predict perceived movements) and hypothesis testing (the use of eye movements to disambiguate amongst hypotheses). The system uses a generative model of how (arm and hand) actions are performed to generate hypothesis-specific visual predictions, and directs saccades to the most informative places of the visual scene to test these predictions - and underlying hypotheses. We test the model using eye movement data from a human action observation study. In both the human study and our model, saccades are proactive whenever context affords accurate action prediction; but uncertainty induces a more reactive gaze strategy, via tracking the observed movements. Our model offers a novel perspective on action observation that highlights its active nature based on prediction dynamics and hypothesis testing. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

An empirical comparison of a dynamic software testability metric to static cyclomatic complexity

NASA Technical Reports Server (NTRS)

Voas, Jeffrey M.; Miller, Keith W.; Payne, Jeffrey E.

1993-01-01

This paper compares the dynamic testability prediction technique termed 'sensitivity analysis' to the static testability technique termed cyclomatic complexity. The application that we chose in this empirical study is a CASE generated version of a B-737 autoland system. For the B-737 system we analyzed, we isolated those functions that we predict are more prone to hide errors during system/reliability testing. We also analyzed the code with several other well-known static metrics. This paper compares and contrasts the results of sensitivity analysis to the results of the static metrics.

Understanding Collagen Organization in Breast Tumors to Predict and Prevent Metastasis

DTIC Science & Technology

2014-09-01

Harmonic Generation to Image the Extracellular Matrix During Tumor Progression. Invited Perspective Intravital Manuscript Submitted. Sullivan K...harmonic generation (the SHG “F/B ratio”) in thick intact tissue, with a single image scan. This will be necessary for us to pursue our goal of...quantifying matrix changes dynamically, in intact tumor models. The first method determines F/B by generating a series of backscattered images using a series

Redundancy, Self-Motion, and Motor Control

PubMed Central

Martin, V.; Scholz, J. P.; Schöner, G.

2011-01-01

Outside the laboratory, human movement typically involves redundant effector systems. How the nervous system selects among the task-equivalent solutions may provide insights into how movement is controlled. We propose a process model of movement generation that accounts for the kinematics of goal-directed pointing movements performed with a redundant arm. The key element is a neuronal dynamics that generates a virtual joint trajectory. This dynamics receives input from a neuronal timer that paces end-effector motion along its path. Within this dynamics, virtual joint velocity vectors that move the end effector are dynamically decoupled from velocity vectors that do not. Moreover, the sensed real joint configuration is coupled back into this neuronal dynamics, updating the virtual trajectory so that it yields to task-equivalent deviations from the dynamic movement plan. Experimental data from participants who perform in the same task setting as the model are compared in detail to the model predictions. We discover that joint velocities contain a substantial amount of self-motion that does not move the end effector. This is caused by the low impedance of muscle joint systems and by coupling among muscle joint systems due to multiarticulatory muscles. Back-coupling amplifies the induced control errors. We establish a link between the amount of self-motion and how curved the end-effector path is. We show that models in which an inverse dynamics cancels interaction torques predict too little self-motion and too straight end-effector paths. PMID:19718817

Climate-based models for pulsed resources improve predictability of consumer population dynamics: outbreaks of house mice in forest ecosystems.

PubMed

Holland, E Penelope; James, Alex; Ruscoe, Wendy A; Pech, Roger P; Byrom, Andrea E

2015-01-01

Accurate predictions of the timing and magnitude of consumer responses to episodic seeding events (masts) are important for understanding ecosystem dynamics and for managing outbreaks of invasive species generated by masts. While models relating consumer populations to resource fluctuations have been developed successfully for a range of natural and modified ecosystems, a critical gap that needs addressing is better prediction of resource pulses. A recent model used change in summer temperature from one year to the next (ΔT) for predicting masts for forest and grassland plants in New Zealand. We extend this climate-based method in the framework of a model for consumer-resource dynamics to predict invasive house mouse (Mus musculus) outbreaks in forest ecosystems. Compared with previous mast models based on absolute temperature, the ΔT method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ΔT on the likelihood of an outbreak occurring. The improved climate-based method for predicting resource pulses and consumer responses provides a straightforward rule of thumb for determining, with one year's advance warning, whether management intervention might be required in invaded ecosystems. The approach could be applied to consumer-resource systems worldwide where climatic variables are used to model the size and duration of resource pulses, and may have particular relevance for ecosystems where global change scenarios predict increased variability in climatic events.

Synaptic State Matching: A Dynamical Architecture for Predictive Internal Representation and Feature Detection

PubMed Central

Tavazoie, Saeed

2013-01-01

Here we explore the possibility that a core function of sensory cortex is the generation of an internal simulation of sensory environment in real-time. A logical elaboration of this idea leads to a dynamical neural architecture that oscillates between two fundamental network states, one driven by external input, and the other by recurrent synaptic drive in the absence of sensory input. Synaptic strength is modified by a proposed synaptic state matching (SSM) process that ensures equivalence of spike statistics between the two network states. Remarkably, SSM, operating locally at individual synapses, generates accurate and stable network-level predictive internal representations, enabling pattern completion and unsupervised feature detection from noisy sensory input. SSM is a biologically plausible substrate for learning and memory because it brings together sequence learning, feature detection, synaptic homeostasis, and network oscillations under a single unifying computational framework. PMID:23991161

Study on cavitation effect of mechanical seals with laser-textured porous surface

NASA Astrophysics Data System (ADS)

Liu, T.; Chen, H. l.; Liu, Y. H.; Wang, Q.; Liu, Z. B.; Hou, D. H.

2012-11-01

Study on the mechanisms underlying generation of hydrodynamic pressure effect associated with laser-textured porous surface on mechanical seal, is the key to seal and lubricant properties. The theory model of mechanical seals with laser-textured porous surface (LES-MS) based on cavitation model was established. The LST-MS was calculated and analyzed by using Fluent software with full cavitation model and non-cavitation model and film thickness was predicted by the dynamic mesh technique. The results indicate that the effect of hydrodynamic pressure and cavitation are the important reasons to generate liquid film opening force on LST-MS; Cavitation effect can enhance hydrodynamic pressure effect of LST-MS; The thickness of liquid film could be well predicted with the method of dynamic mesh technique on Fluent and it becomes larger as the increasing of shaft speed and the decreasing of pressure.

Cloud computing approaches for prediction of ligand binding poses and pathways.

PubMed

Lawrenz, Morgan; Shukla, Diwakar; Pande, Vijay S

2015-01-22

We describe an innovative protocol for ab initio prediction of ligand crystallographic binding poses and highly effective analysis of large datasets generated for protein-ligand dynamics. We include a procedure for setup and performance of distributed molecular dynamics simulations on cloud computing architectures, a model for efficient analysis of simulation data, and a metric for evaluation of model convergence. We give accurate binding pose predictions for five ligands ranging in affinity from 7 nM to > 200 μM for the immunophilin protein FKBP12, for expedited results in cases where experimental structures are difficult to produce. Our approach goes beyond single, low energy ligand poses to give quantitative kinetic information that can inform protein engineering and ligand design.

Using integrated modeling for generating watershed-scale dynamic flood maps for Hurricane Harvey

NASA Astrophysics Data System (ADS)

Saksena, S.; Dey, S.; Merwade, V.; Singhofen, P. J.

2017-12-01

Hurricane Harvey, which was categorized as a 1000-year return period event, produced unprecedented rainfall and flooding in Houston. Although the expected rainfall was forecasted much before the event, there was no way to identify which regions were at higher risk of flooding, the magnitude of flooding, and when the impacts of rainfall would be highest. The inability to predict the location, duration, and depth of flooding created uncertainty over evacuation planning and preparation. This catastrophic event highlighted that the conventional approach to managing flood risk using 100-year static flood inundation maps is inadequate because of its inability to predict flood duration and extents for 500-year or 1000-year return period events in real-time. The purpose of this study is to create models that can dynamically predict the impacts of rainfall and subsequent flooding, so that necessary evacuation and rescue efforts can be planned in advance. This study uses a 2D integrated surface water-groundwater model called ICPR (Interconnected Channel and Pond Routing) to simulate both the hydrology and hydrodynamics for Hurricane Harvey. The methodology involves using the NHD stream network to create a 2D model that incorporates rainfall, land use, vadose zone properties and topography to estimate streamflow and generate dynamic flood depths and extents. The results show that dynamic flood mapping captures the flood hydrodynamics more accurately and is able to predict the magnitude, extent and time of occurrence for extreme events such as Hurricane Harvey. Therefore, integrated modeling has the potential to identify regions that are more susceptible to flooding, which is especially useful for large-scale planning and allocation of resources for protection against future flood risk.

Prediction of Ground Vibration from Freight Trains

NASA Astrophysics Data System (ADS)

Jones, C. J. C.; Block, J. R.

1996-05-01

Heavy freight trains emit ground vibration with predominant frequency components in the range 4-30 Hz. If the amplitude is sufficient, this may be felt by lineside residents, giving rise to disturbance and concern over possible damage to their property. In order to establish the influence of parameters of the track and rolling stock and thereby enable the design of a low vibration railway, a theoretical model of both the generation and propagation of vibration is required. The vibration is generated as a combination of the effects of dynamic forces, due to the unevenness of the track, and the effects of the track deformation under successive axle loads. A prediction scheme, which combines these effects, has been produced. A vehicle model is used to predict the dynamic forces at the wheels. This includes the non-linear effects of friction damped suspensions. The loaded track profile is measured by using a track recording coach. The dynamic loading and the effects of the moving axles are combined in a track response model. The predicted track vibration is compared to measurements. The transfer functions from the track to a point in the ground can be calculated by using a coupled track and a three-dimensional layered ground model. The propagation effects of the ground layers are important but the computation of the transfer function from each sleeper, which would be required for a phase coherent summation of the vibration in the ground, would be prohibitive. A compromise summation is used and results are compared with measurements.

Generation of diurnal variation for influent data for dynamic simulation.

PubMed

Langergraber, G; Alex, J; Weissenbacher, N; Woerner, D; Ahnert, M; Frehmann, T; Halft, N; Hobus, I; Plattes, M; Spering, V; Winkler, S

2008-01-01

When using dynamic simulation for fine tuning of the design of activated sludge (AS) plants diurnal variations of influent data are required. For this application usually only data from the design process and no measured data are available. In this paper a simple method to generate diurnal variations of wastewater flow and concentrations is described. The aim is to generate realistic influent data in terms of flow, concentrations and TKN/COD ratios and not to predict the influent of the AS plant in detail. The work has been prepared within the framework of HSG-Sim (Hochschulgruppe Simulation, http://www.hsgsim.org), a group of researchers from Germany, Austria, Luxembourg, Poland, the Netherlands and Switzerland. (c) IWA Publishing 2008.

Development tests for the 2.5 megawatt Mod-2 wind turbine generator

NASA Technical Reports Server (NTRS)

Andrews, J. S.; Baskin, J. M.

1982-01-01

The 2.5 megawatt MOD-2 wind turbine generator test program is discussed. The development of the 2.5 megawatt MOD-2 wind turbine generator included an extensive program of testing which encompassed verification of analytical procedures, component development, and integrated system verification. The test program was to assure achievement of the thirty year design operational life of the wind turbine system as well as to minimize costly design modifications which would otherwise have been required during on site system testing. Computer codes were modified, fatigue life of structure and dynamic components were verified, mechanical and electrical component and subsystems were functionally checked and modified where necessary to meet system specifications, and measured dynamic responses of coupled systems confirmed analytical predictions.

Controlling infectious disease through the targeted manipulation of contact network structure

PubMed Central

Gates, M. Carolyn; Woolhouse, Mark E.J.

2015-01-01

Individuals in human and animal populations are linked through dynamic contact networks with characteristic structural features that drive the epidemiology of directly transmissible infectious diseases. Using animal movement data from the British cattle industry as an example, this analysis explores whether disease dynamics can be altered by placing targeted restrictions on contact formation to reconfigure network topology. This was accomplished using a simple network generation algorithm that combined configuration wiring with stochastic block modelling techniques to preserve the weighted in- and out-degree of individual nodes (farms) as well as key demographic characteristics of the individual network connections (movement date, livestock market, and animal production type). We then tested a control strategy based on introducing additional constraints into the network generation algorithm to prevent farms with a high in-degree from selling cattle to farms with a high out-degree as these particular network connections are predicted to have a disproportionately strong role in spreading disease. Results from simple dynamic disease simulation models predicted significantly lower endemic disease prevalences on the trade restricted networks compared to the baseline generated networks. As expected, the relative magnitude of the predicted changes in endemic prevalence was greater for diseases with short infectious periods and low transmission probabilities. Overall, our study findings demonstrate that there is significant potential for controlling multiple infectious diseases simultaneously by manipulating networks to have more epidemiologically favourable topological configurations. Further research is needed to determine whether the economic and social benefits of controlling disease can justify the costs of restricting contact formation. PMID:26342238

Controlling infectious disease through the targeted manipulation of contact network structure.

PubMed

Gates, M Carolyn; Woolhouse, Mark E J

2015-09-01

Individuals in human and animal populations are linked through dynamic contact networks with characteristic structural features that drive the epidemiology of directly transmissible infectious diseases. Using animal movement data from the British cattle industry as an example, this analysis explores whether disease dynamics can be altered by placing targeted restrictions on contact formation to reconfigure network topology. This was accomplished using a simple network generation algorithm that combined configuration wiring with stochastic block modelling techniques to preserve the weighted in- and out-degree of individual nodes (farms) as well as key demographic characteristics of the individual network connections (movement date, livestock market, and animal production type). We then tested a control strategy based on introducing additional constraints into the network generation algorithm to prevent farms with a high in-degree from selling cattle to farms with a high out-degree as these particular network connections are predicted to have a disproportionately strong role in spreading disease. Results from simple dynamic disease simulation models predicted significantly lower endemic disease prevalences on the trade restricted networks compared to the baseline generated networks. As expected, the relative magnitude of the predicted changes in endemic prevalence was greater for diseases with short infectious periods and low transmission probabilities. Overall, our study findings demonstrate that there is significant potential for controlling multiple infectious diseases simultaneously by manipulating networks to have more epidemiologically favourable topological configurations. Further research is needed to determine whether the economic and social benefits of controlling disease can justify the costs of restricting contact formation. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

Models of charge pair generation in organic solar cells.

PubMed

Few, Sheridan; Frost, Jarvist M; Nelson, Jenny

2015-01-28

Efficient charge pair generation is observed in many organic photovoltaic (OPV) heterojunctions, despite nominal electron-hole binding energies which greatly exceed the average thermal energy. Empirically, the efficiency of this process appears to be related to the choice of donor and acceptor materials, the resulting sequence of excited state energy levels and the structure of the interface. In order to establish a suitable physical model for the process, a range of different theoretical studies have addressed the nature and energies of the interfacial states, the energetic profile close to the heterojunction and the dynamics of excited state transitions. In this paper, we review recent developments underpinning the theory of charge pair generation and phenomena, focussing on electronic structure calculations, electrostatic models and approaches to excited state dynamics. We discuss the remaining challenges in achieving a predictive approach to charge generation efficiency.

HART-II Acoustic Predictions using a Coupled CFD/CSD Method

NASA Technical Reports Server (NTRS)

Boyd, D. Douglas, Jr.

2009-01-01

This paper documents results to date from the Rotorcraft Acoustic Characterization and Mitigation activity under the NASA Subsonic Rotary Wing Project. The primary goal of this activity is to develop a NASA rotorcraft impulsive noise prediction capability which uses first principles fluid dynamics and structural dynamics. During this effort, elastic blade motion and co-processing capabilities have been included in a recent version of the computational fluid dynamics code (CFD). The CFD code is loosely coupled to computational structural dynamics (CSD) code using new interface codes. The CFD/CSD coupled solution is then used to compute impulsive noise on a plane under the rotor using the Ffowcs Williams-Hawkings solver. This code system is then applied to a range of cases from the Higher Harmonic Aeroacoustic Rotor Test II (HART-II) experiment. For all cases presented, the full experimental configuration (i.e., rotor and wind tunnel sting mount) are used in the coupled CFD/CSD solutions. Results show good correlation between measured and predicted loading and loading time derivative at the only measured radial station. A contributing factor for a typically seen loading mean-value offset between measured data and predictions data is examined. Impulsive noise predictions on the measured microphone plane under the rotor compare favorably with measured mid-frequency noise for all cases. Flow visualization of the BL and MN cases shows that vortex structures generated in the prediction method are consist with measurements. Future application of the prediction method is discussed.

Euler Technology Assessment for Preliminary Aircraft Design: Compressibility Predictions by Employing the Cartesian Unstructured Grid SPLITFLOW Code

NASA Technical Reports Server (NTRS)

Finley, Dennis B.; Karman, Steve L., Jr.

1996-01-01

The objective of the second phase of the Euler Technology Assessment program was to evaluate the ability of Euler computational fluid dynamics codes to predict compressible flow effects over a generic fighter wind tunnel model. This portion of the study was conducted by Lockheed Martin Tactical Aircraft Systems, using an in-house Cartesian-grid code called SPLITFLOW. The Cartesian grid technique offers several advantages, including ease of volume grid generation and reduced number of cells compared to other grid schemes. SPLITFLOW also includes grid adaption of the volume grid during the solution to resolve high-gradient regions. The SPLITFLOW code predictions of configuration forces and moments are shown to be adequate for preliminary design, including predictions of sideslip effects and the effects of geometry variations at low and high angles-of-attack. The transonic pressure prediction capabilities of SPLITFLOW are shown to be improved over subsonic comparisons. The time required to generate the results from initial surface data is on the order of several hours, including grid generation, which is compatible with the needs of the design environment.

Shortened acquisition protocols for the quantitative assessment of the 2-tissue-compartment model using dynamic PET/CT 18F-FDG studies.

PubMed

Strauss, Ludwig G; Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2011-03-01

(18)F-FDG kinetics are quantified by a 2-tissue-compartment model. The routine use of dynamic PET is limited because of this modality's 1-h acquisition time. We evaluated shortened acquisition protocols up to 0-30 min regarding the accuracy for data analysis with the 2-tissue-compartment model. Full dynamic series for 0-60 min were analyzed using a 2-tissue-compartment model. The time-activity curves and the resulting parameters for the model were stored in a database. Shortened acquisition data were generated from the database using the following time intervals: 0-10, 0-16, 0-20, 0-25, and 0-30 min. Furthermore, the impact of adding a 60-min uptake value to the dynamic series was evaluated. The datasets were analyzed using dedicated software to predict the results of the full dynamic series. The software is based on a modified support vector machines (SVM) algorithm and predicts the compartment parameters of the full dynamic series. The SVM-based software provides user-independent results and was accurate at predicting the compartment parameters of the full dynamic series. If a squared correlation coefficient of 0.8 (corresponding to 80% explained variance of the data) was used as a limit, a shortened acquisition of 0-16 min was accurate at predicting the 60-min 2-tissue-compartment parameters. If a limit of 0.9 (90% explained variance) was used, a dynamic series of at least 0-20 min together with the 60-min uptake values is required. Shortened acquisition protocols can be used to predict the parameters of the 2-tissue-compartment model. Either a dynamic PET series of 0-16 min or a combination of a dynamic PET/CT series of 0-20 min and a 60-min uptake value is accurate for analysis with a 2-tissue-compartment model.

Data center thermal management

DOEpatents

Hamann, Hendrik F.; Li, Hongfei

2016-02-09

Historical high-spatial-resolution temperature data and dynamic temperature sensor measurement data may be used to predict temperature. A first formulation may be derived based on the historical high-spatial-resolution temperature data for determining a temperature at any point in 3-dimensional space. The dynamic temperature sensor measurement data may be calibrated based on the historical high-spatial-resolution temperature data at a corresponding historical time. Sensor temperature data at a plurality of sensor locations may be predicted for a future time based on the calibrated dynamic temperature sensor measurement data. A three-dimensional temperature spatial distribution associated with the future time may be generated based on the forecasted sensor temperature data and the first formulation. The three-dimensional temperature spatial distribution associated with the future time may be projected to a two-dimensional temperature distribution, and temperature in the future time for a selected space location may be forecasted dynamically based on said two-dimensional temperature distribution.

Silent Expectations: Dynamic Causal Modeling of Cortical Prediction and Attention to Sounds That Weren't.

PubMed

Chennu, Srivas; Noreika, Valdas; Gueorguiev, David; Shtyrov, Yury; Bekinschtein, Tristan A; Henson, Richard

2016-08-10

There is increasing evidence that human perception is realized by a hierarchy of neural processes in which predictions sent backward from higher levels result in prediction errors that are fed forward from lower levels, to update the current model of the environment. Moreover, the precision of prediction errors is thought to be modulated by attention. Much of this evidence comes from paradigms in which a stimulus differs from that predicted by the recent history of other stimuli (generating a so-called "mismatch response"). There is less evidence from situations where a prediction is not fulfilled by any sensory input (an "omission" response). This situation arguably provides a more direct measure of "top-down" predictions in the absence of confounding "bottom-up" input. We applied Dynamic Causal Modeling of evoked electromagnetic responses recorded by EEG and MEG to an auditory paradigm in which we factorially crossed the presence versus absence of "bottom-up" stimuli with the presence versus absence of "top-down" attention. Model comparison revealed that both mismatch and omission responses were mediated by increased forward and backward connections, differing primarily in the driving input. In both responses, modeling results suggested that the presence of attention selectively modulated backward "prediction" connections. Our results provide new model-driven evidence of the pure top-down prediction signal posited in theories of hierarchical perception, and highlight the role of attentional precision in strengthening this prediction. Human auditory perception is thought to be realized by a network of neurons that maintain a model of and predict future stimuli. Much of the evidence for this comes from experiments where a stimulus unexpectedly differs from previous ones, which generates a well-known "mismatch response." But what happens when a stimulus is unexpectedly omitted altogether? By measuring the brain's electromagnetic activity, we show that it also generates an "omission response" that is contingent on the presence of attention. We model these responses computationally, revealing that mismatch and omission responses only differ in the location of inputs into the same underlying neuronal network. In both cases, we show that attention selectively strengthens the brain's prediction of the future. Copyright © 2016 Chennu et al.

Prediction of X-33 Engine Dynamic Environments

NASA Technical Reports Server (NTRS)

Shi, John J.

1999-01-01

Rocket engines normally have two primary sources of dynamic excitation. The first source is the injector and the combustion chambers that generate wide band random vibration. The second source is the turbopumps, which produce lower levels of wide band random vibration as well as sinusoidal vibration at frequencies related to the rotating speed and multiples thereof. Additionally, the pressure fluctuations due to flow turbulence and acoustics represent secondary sources of excitation. During the development stage, in order to design/size the rocket engine components, the local dynamic environments as well as dynamic interface loads have to be defined.

Nonlinear Model Predictive Control with Constraint Satisfactions for a Quadcopter

NASA Astrophysics Data System (ADS)

Wang, Ye; Ramirez-Jaime, Andres; Xu, Feng; Puig, Vicenç

2017-01-01

This paper presents a nonlinear model predictive control (NMPC) strategy combined with constraint satisfactions for a quadcopter. The full dynamics of the quadcopter describing the attitude and position are nonlinear, which are quite sensitive to changes of inputs and disturbances. By means of constraint satisfactions, partial nonlinearities and modeling errors of the control-oriented model of full dynamics can be transformed into the inequality constraints. Subsequently, the quadcopter can be controlled by an NMPC controller with the updated constraints generated by constraint satisfactions. Finally, the simulation results applied to a quadcopter simulator are provided to show the effectiveness of the proposed strategy.

Dynamic Integration of Value Information into a Common Probability Currency as a Theory for Flexible Decision Making

PubMed Central

Christopoulos, Vassilios; Schrater, Paul R.

2015-01-01

Decisions involve two fundamental problems, selecting goals and generating actions to pursue those goals. While simple decisions involve choosing a goal and pursuing it, humans evolved to survive in hostile dynamic environments where goal availability and value can change with time and previous actions, entangling goal decisions with action selection. Recent studies suggest the brain generates concurrent action-plans for competing goals, using online information to bias the competition until a single goal is pursued. This creates a challenging problem of integrating information across diverse types, including both the dynamic value of the goal and the costs of action. We model the computations underlying dynamic decision-making with disparate value types, using the probability of getting the highest pay-off with the least effort as a common currency that supports goal competition. This framework predicts many aspects of decision behavior that have eluded a common explanation. PMID:26394299

Information model of trainee characteristics with definition of stochastic behavior of dynamic system

NASA Astrophysics Data System (ADS)

Sumin, V. I.; Smolentseva, T. E.; Belokurov, S. V.; Lankin, O. V.

2018-03-01

In the work the process of formation of trainee characteristics with their subsequent change is analyzed and analyzed. Characteristics of trainees were obtained as a result of testing for each section of information on the chosen discipline. The results obtained during testing were input to the dynamic system. The area of control actions consisting of elements of the dynamic system is formed. The limit of deterministic predictability of element trajectories in dynamical systems based on local or global attractors is revealed. The dimension of the phase space of the dynamic system is determined, which allows estimating the parameters of the initial system. On the basis of time series of observations, it is possible to determine the predictability interval of all parameters, which make it possible to determine the behavior of the system discretely in time. Then the measure of predictability will be the sum of Lyapunov’s positive indicators, which are a quantitative measure for all elements of the system. The components for the formation of an algorithm allowing to determine the correlation dimension of the attractor for known initial experimental values of the variables are revealed. The generated algorithm makes it possible to carry out an experimental study of the dynamics of changes in the trainee’s parameters with initial uncertainty.

Universality in the dynamical properties of seismic vibrations

NASA Astrophysics Data System (ADS)

Chatterjee, Soumya; Barat, P.; Mukherjee, Indranil

2018-02-01

We have studied the statistical properties of the observed magnitudes of seismic vibration data in discrete time in an attempt to understand the underlying complex dynamical processes. The observed magnitude data are taken from six different geographical locations. All possible magnitudes are considered in the analysis including catastrophic vibrations, foreshocks, aftershocks and commonplace daily vibrations. The probability distribution functions of these data sets obey scaling law and display a certain universality characteristic. To investigate the universality features in the observed data generated by a complex process, we applied Random Matrix Theory (RMT) in the framework of Gaussian Orthogonal Ensemble (GOE). For all these six places the observed data show a close fit with the predictions of RMT. This reinforces the idea of universality in the dynamical processes generating seismic vibrations.

Holograms of a dynamical top quark

NASA Astrophysics Data System (ADS)

Clemens, Will; Evans, Nick; Scott, Marc

2017-09-01

We present holographic descriptions of dynamical electroweak symmetry breaking models that incorporate the top mass generation mechanism. The models allow computation of the spectrum in the presence of large anomalous dimensions due to walking and strong Nambu-Jona-Lasinio interactions. Technicolor and QCD dynamics are described by the bottom-up Dynamic AdS/QCD model for arbitrary gauge groups and numbers of quark flavors. An assumption about the running of the anomalous dimension of the quark bilinear operator is input, and the model then predicts the spectrum and decay constants for the mesons. We add Nambu-Jona-Lasinio interactions responsible for flavor physics from extended technicolor, top-color, etc., using Witten's multitrace prescription. We show the key behaviors of a top condensation model can be reproduced. We study generation of the top mass in (walking) one doublet and one family technicolor models and with strong extended technicolor interactions. The models clearly reveal the tensions between the large top mass and precision data for δ ρ . The necessary tunings needed to generate a model compatible with precision constraints are simply demonstrated.

Charge generation by heavy ions in power MOSFETs, burnout space predictions, and dynamic SEB sensitivity

NASA Technical Reports Server (NTRS)

Stassinopoulos, E. G.; Brucker, G. J.; Calvel, P.; Baiget, A.; Peyrotte, C.; Gaillard, R.

1992-01-01

The transport, energy loss, and charge production of heavy ions in the sensitive regions of IRF 150 power MOSFETs are described. The dependence and variation of transport parameters with ion type and energy relative to the requirements for single event burnout in this part type are discussed. Test data taken with this power MOSFET are used together with analyses by means of a computer code of the ion energy loss and charge production in the device to establish criteria for burnout and parameters for space predictions. These parameters are then used in an application to predict burnout rates in a geostationary orbit for power converters operating in a dynamic mode. Comparisons of rates for different geometries in simulating SEU (single event upset) sensitive volumes are presented.

Dynamic Analysis and Test Results for an STC Stirling Generator

NASA Astrophysics Data System (ADS)

Qiu, Songgang; Peterson, Allen A.

2004-02-01

Long-life, high-efficiency generators based on free-piston Stirling machines are a future energy-conversion solution for both space and commercial applications. To aid in design and system integration efforts, Stirling Technology Company (STC) has developed dynamic simulation models for the internal moving subassemblies and for complete Stirling convertor assemblies. These dynamic models have been validated using test data from operating prototypes. Simplified versions of these models are presented to help explain the operating characteristics of the Stirling convertor. Power spectrum analysis is presented for the test data for casing acceleration, piston motion, displacer motion, and controller current/voltage during full power operation. The harmonics of a Stirling convertor and its moving components are identified for the STC zener-diode control scheme. The dynamic behavior of each moving component and its contribution to the system dynamics and resultant vibration forces are discussed. Additionally, the effects of a passive balancer and external suspension are predicted by another simplified system model.

Next Generation Community Based Unified Global Modeling System Development and Operational Implementation Strategies at NCEP

NASA Astrophysics Data System (ADS)

Tallapragada, V.

2017-12-01

NOAA's Next Generation Global Prediction System (NGGPS) has provided the unique opportunity to develop and implement a non-hydrostatic global model based on Geophysical Fluid Dynamics Laboratory (GFDL) Finite Volume Cubed Sphere (FV3) Dynamic Core at National Centers for Environmental Prediction (NCEP), making a leap-step advancement in seamless prediction capabilities across all spatial and temporal scales. Model development efforts are centralized with unified model development in the NOAA Environmental Modeling System (NEMS) infrastructure based on Earth System Modeling Framework (ESMF). A more sophisticated coupling among various earth system components is being enabled within NEMS following National Unified Operational Prediction Capability (NUOPC) standards. The eventual goal of unifying global and regional models will enable operational global models operating at convective resolving scales. Apart from the advanced non-hydrostatic dynamic core and coupling to various earth system components, advanced physics and data assimilation techniques are essential for improved forecast skill. NGGPS is spearheading ambitious physics and data assimilation strategies, concentrating on creation of a Common Community Physics Package (CCPP) and Joint Effort for Data Assimilation Integration (JEDI). Both initiatives are expected to be community developed, with emphasis on research transitioning to operations (R2O). The unified modeling system is being built to support the needs of both operations and research. Different layers of community partners are also established with specific roles/responsibilities for researchers, core development partners, trusted super-users, and operations. Stakeholders are engaged at all stages to help drive the direction of development, resources allocations and prioritization. This talk presents the current and future plans of unified model development at NCEP for weather, sub-seasonal, and seasonal climate prediction applications with special emphasis on implementation of NCEP FV3 Global Forecast System (GFS) and Global Ensemble Forecast System (GEFS) into operations by 2019.

Generating Dynamic Persistence in the Time Domain

NASA Astrophysics Data System (ADS)

Guerrero, A.; Smith, L. A.; Smith, L. A.; Kaplan, D. T.

2001-12-01

Many dynamical systems present long-range correlations. Physically, these systems vary from biological to economical, including geological or urban systems. Important geophysical candidates for this type of behaviour include weather (or climate) and earthquake sequences. Persistence is characterised by slowly decaying correlation function; that, in theory, never dies out. The Persistence exponent reflects the degree of memory in the system and much effort has been expended creating and analysing methods that successfully estimate this parameter and model data that exhibits persistence. The most widely used methods for generating long correlated time series are not dynamical systems in the time domain, but instead are derived from a given spectral density. Little attention has been drawn to modelling persistence in the time domain. The time domain approach has the advantage that an observation at certain time can be calculated using previous observations which is particularly suitable when investigating the predictability of a long memory process. We will describe two of these methods in the time domain. One is a traditional approach using fractional ARIMA (autoregressive and moving average) models; the second uses a novel approach to extending a given series using random Fourier basis functions. The statistical quality of the two methods is compared, and they are contrasted with weather data which shows, reportedly, persistence. The suitability of this approach both for estimating predictability and for making predictions is discussed.

Indexing sensory plasticity: Evidence for distinct Predictive Coding and Hebbian learning mechanisms in the cerebral cortex.

PubMed

Spriggs, M J; Sumner, R L; McMillan, R L; Moran, R J; Kirk, I J; Muthukumaraswamy, S D

2018-04-30

The Roving Mismatch Negativity (MMN), and Visual LTP paradigms are widely used as independent measures of sensory plasticity. However, the paradigms are built upon fundamentally different (and seemingly opposing) models of perceptual learning; namely, Predictive Coding (MMN) and Hebbian plasticity (LTP). The aim of the current study was to compare the generative mechanisms of the MMN and visual LTP, therefore assessing whether Predictive Coding and Hebbian mechanisms co-occur in the brain. Forty participants were presented with both paradigms during EEG recording. Consistent with Predictive Coding and Hebbian predictions, Dynamic Causal Modelling revealed that the generation of the MMN modulates forward and backward connections in the underlying network, while visual LTP only modulates forward connections. These results suggest that both Predictive Coding and Hebbian mechanisms are utilized by the brain under different task demands. This therefore indicates that both tasks provide unique insight into plasticity mechanisms, which has important implications for future studies of aberrant plasticity in clinical populations. Copyright © 2018 Elsevier Inc. All rights reserved.

Experimental test of an eco-evolutionary dynamic feedback loop between evolution and population density in the green peach aphid.

PubMed

Turcotte, Martin M; Reznick, David N; Daniel Hare, J

2013-05-01

An eco-evolutionary feedback loop is defined as the reciprocal impacts of ecology on evolutionary dynamics and evolution on ecological dynamics on contemporary timescales. We experimentally tested for an eco-evolutionary feedback loop in the green peach aphid, Myzus persicae, by manipulating initial densities and evolution. We found strong evidence that initial aphid density alters the rate and direction of evolution, as measured by changes in genotype frequencies through time. We also found that evolution of aphids within only 16 days, or approximately three generations, alters the rate of population growth and predicts density compared to nonevolving controls. The impact of evolution on population dynamics also depended on density. In one evolution treatment, evolution accelerated population growth by up to 10.3% at high initial density or reduced it by up to 6.4% at low initial density. The impact of evolution on population growth was as strong as or stronger than that caused by a threefold change in intraspecific density. We found that, taken together, ecological condition, here intraspecific density, alters evolutionary dynamics, which in turn alter concurrent population growth rate (ecological dynamics) in an eco-evolutionary feedback loop. Our results suggest that ignoring evolution in studies predicting population dynamics might lead us to over- or underestimate population density and that we cannot predict the evolutionary outcome within aphid populations without considering population size.

Dynamics and control of quadcopter using linear model predictive control approach

NASA Astrophysics Data System (ADS)

Islam, M.; Okasha, M.; Idres, M. M.

2017-12-01

This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators’ saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory.

Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation.

PubMed

Zhang, Fan; Liu, Runsheng; Zheng, Jie

2016-12-23

Linking computational models of signaling pathways to predicted cellular responses such as gene expression regulation is a major challenge in computational systems biology. In this work, we present Sig2GRN, a Cytoscape plugin that is able to simulate time-course gene expression data given the user-defined external stimuli to the signaling pathways. A generalized logical model is used in modeling the upstream signaling pathways. Then a Boolean model and a thermodynamics-based model are employed to predict the downstream changes in gene expression based on the simulated dynamics of transcription factors in signaling pathways. Our empirical case studies show that the simulation of Sig2GRN can predict changes in gene expression patterns induced by DNA damage signals and drug treatments. As a software tool for modeling cellular dynamics, Sig2GRN can facilitate studies in systems biology by hypotheses generation and wet-lab experimental design. http://histone.scse.ntu.edu.sg/Sig2GRN/.

Improvement of PM concentration predictability using WRF-CMAQ-DLM coupled system and its applications

NASA Astrophysics Data System (ADS)

Lee, Soon Hwan; Kim, Ji Sun; Lee, Kang Yeol; Shon, Keon Tae

2017-04-01

Air quality due to increasing Particulate Matter(PM) in Korea in Asia is getting worse. At present, the PM forecast is announced based on the PM concentration predicted from the air quality prediction numerical model. However, forecast accuracy is not as high as expected due to various uncertainties for PM physical and chemical characteristics. The purpose of this study was to develop a numerical-statistically ensemble models to improve the accuracy of prediction of PM10 concentration. Numerical models used in this study are the three dimensional atmospheric model Weather Research and Forecasting(WRF) and the community multiscale air quality model (CMAQ). The target areas for the PM forecast are Seoul, Busan, Daegu, and Daejeon metropolitan areas in Korea. The data used in the model development are PM concentration and CMAQ predictions and the data period is 3 months (March 1 - May 31, 2014). The dynamic-statistical technics for reducing the systematic error of the CMAQ predictions was applied to the dynamic linear model(DLM) based on the Baysian Kalman filter technic. As a result of applying the metrics generated from the dynamic linear model to the forecasting of PM concentrations accuracy was improved. Especially, at the high PM concentration where the damage is relatively large, excellent improvement results are shown.

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

NASA Technical Reports Server (NTRS)

Lin, Shian-Jiann; Atlas, Robert (Technical Monitor)

2002-01-01

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 km or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed-shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

High-Efficiency High-Resolution Global Model Developments at the NASA Goddard Data Assimilation Office

NASA Technical Reports Server (NTRS)

Lin, Shian-Jiann; Atlas, Robert (Technical Monitor)

2002-01-01

The Data Assimilation Office (DAO) has been developing a new generation of ultra-high resolution General Circulation Model (GCM) that is suitable for 4-D data assimilation, numerical weather predictions, and climate simulations. These three applications have conflicting requirements. For 4-D data assimilation and weather predictions, it is highly desirable to run the model at the highest possible spatial resolution (e.g., 55 kin or finer) so as to be able to resolve and predict socially and economically important weather phenomena such as tropical cyclones, hurricanes, and severe winter storms. For climate change applications, the model simulations need to be carried out for decades, if not centuries. To reduce uncertainty in climate change assessments, the next generation model would also need to be run at a fine enough spatial resolution that can at least marginally simulate the effects of intense tropical cyclones. Scientific problems (e.g., parameterization of subgrid scale moist processes) aside, all three areas of application require the model's computational performance to be dramatically improved as compared to the previous generation. In this talk, I will present the current and future developments of the "finite-volume dynamical core" at the Data Assimilation Office. This dynamical core applies modem monotonicity preserving algorithms and is genuinely conservative by construction, not by an ad hoc fixer. The "discretization" of the conservation laws is purely local, which is clearly advantageous for resolving sharp gradient flow features. In addition, the local nature of the finite-volume discretization also has a significant advantage on distributed memory parallel computers. Together with a unique vertically Lagrangian control volume discretization that essentially reduces the dimension of the computational problem from three to two, the finite-volume dynamical core is very efficient, particularly at high resolutions. I will also present the computational design of the dynamical core using a hybrid distributed- shared memory programming paradigm that is portable to virtually any of today's high-end parallel super-computing clusters.

Extended-Range Prediction with Low-Dimensional, Stochastic-Dynamic Models: A Data-driven Approach

DTIC Science & Technology

2013-09-30

statistically extratropical storms and extremes, and link these to LFV modes. Mingfang Ting, Yochanan Kushnir, Andrew W. Robertson, Lei Wang...forecast models, as well as in the understanding they have generated. Adam Sobel, Daehyun Kim and Shuguang Wang. Extratropical variability and...predictability. Determine the extent to which extratropical monthly and seasonal low-frequency variability (LFV, i.e. PNA, NAO, as well as other regional

Analytical and experimental vibration analysis of a faulty gear system

NASA Astrophysics Data System (ADS)

Choy, F. K.; Braun, M. J.; Polyshchuk, V.; Zakrajsek, J. J.; Townsend, D. P.; Handschuh, R. F.

1994-10-01

A comprehensive analytical procedure was developed for predicting faults in gear transmission systems under normal operating conditions. A gear tooth fault model is developed to simulate the effects of pitting and wear on the vibration signal under normal operating conditions. The model uses changes in the gear mesh stiffness to simulate the effects of gear tooth faults. The overall dynamics of the gear transmission system is evaluated by coupling the dynamics of each individual gear-rotor system through gear mesh forces generated between each gear-rotor system and the bearing forces generated between the rotor and the gearbox structures. The predicted results were compared with experimental results obtained from a spiral bevel gear fatigue test rig at NASA Lewis Research Center. The Wigner-Ville Distribution (WVD) was used to give a comprehensive comparison of the predicted and experimental results. The WVD method applied to the experimental results were also compared to other fault detection techniques to verify the WVD's ability to detect the pitting damage, and to determine its relative performance. Overall results show good correlation between the experimental vibration data of the damaged test gear and the predicted vibration from the model with simulated gear tooth pitting damage. Results also verified that the WVD method can successfully detect and locate gear tooth wear and pitting damage.

Analytical and experimental vibration analysis of a faulty gear system

NASA Astrophysics Data System (ADS)

Choy, F. K.; Braun, M. J.; Polyshchuk, V.; Zakrajsek, J. J.; Townsend, D. P.; Handschuh, R. F.

1994-10-01

A comprehensive analytical procedure was developed for predicting faults in gear transmission systems under normal operating conditions. A gear tooth fault model is developed to simulate the effects of pitting and wear on the vibration signal under normal operating conditions. The model uses changes in the gear mesh stiffness to simulate the effects of gear tooth faults. The overall dynamics of the gear transmission system is evaluated by coupling the dynamics of each individual gear-rotor system through gear mesh forces generated between each gear-rotor system and the bearing forces generated between the rotor and the gearbox structure. The predicted results were compared with experimental results obtained from a spiral bevel gear fatigue test rig at NASA Lewis Research Center. The Wigner-Ville distribution (WVD) was used to give a comprehensive comparison of the predicted and experimental results. The WVD method applied to the experimental results were also compared to other fault detection techniques to verify the WVD's ability to detect the pitting damage, and to determine its relative performance. Overall results show good correlation between the experimental vibration data of the damaged test gear and the predicted vibration from the model with simulated gear tooth pitting damage. Results also verified that the WVD method can successfully detect and locate gear tooth wear and pitting damage.

Analytical and Experimental Vibration Analysis of a Faulty Gear System

NASA Technical Reports Server (NTRS)

Choy, F. K.; Braun, M. J.; Polyshchuk, V.; Zakrajsek, J. J.; Townsend, D. P.; Handschuh, R. F.

1994-01-01

A comprehensive analytical procedure was developed for predicting faults in gear transmission systems under normal operating conditions. A gear tooth fault model is developed to simulate the effects of pitting and wear on the vibration signal under normal operating conditions. The model uses changes in the gear mesh stiffness to simulate the effects of gear tooth faults. The overall dynamics of the gear transmission system is evaluated by coupling the dynamics of each individual gear-rotor system through gear mesh forces generated between each gear-rotor system and the bearing forces generated between the rotor and the gearbox structure. The predicted results were compared with experimental results obtained from a spiral bevel gear fatigue test rig at NASA Lewis Research Center. The Wigner-Ville distribution (WVD) was used to give a comprehensive comparison of the predicted and experimental results. The WVD method applied to the experimental results were also compared to other fault detection techniques to verify the WVD's ability to detect the pitting damage, and to determine its relative performance. Overall results show good correlation between the experimental vibration data of the damaged test gear and the predicted vibration from the model with simulated gear tooth pitting damage. Results also verified that the WVD method can successfully detect and locate gear tooth wear and pitting damage.

Distributed collaborative decision support environments for predictive awareness

NASA Astrophysics Data System (ADS)

McQuay, William K.; Stilman, Boris; Yakhnis, Vlad

2005-05-01

The past decade has produced significant changes in the conduct of military operations: asymmetric warfare, the reliance on dynamic coalitions, stringent rules of engagement, increased concern about collateral damage, and the need for sustained air operations. Mission commanders need to assimilate a tremendous amount of information, rapidly assess the enemy"s course of action (eCOA) or possible actions and promulgate their own course of action (COA) - a need for predictive awareness. Decision support tools in a distributed collaborative environment offer the capability of decomposing complex multitask processes and distributing them over a dynamic set of execution assets that include modeling, simulations, and analysis tools. Revolutionary new approaches to strategy generation and assessment such as Linguistic Geometry (LG) permit the rapid development of COA vs. enemy COA (eCOA). LG tools automatically generate and permit the operators to take advantage of winning strategies and tactics for mission planning and execution in near real-time. LG is predictive and employs deep "look-ahead" from the current state and provides a realistic, reactive model of adversary reasoning and behavior. Collaborative environments provide the framework and integrate models, simulations, and domain specific decision support tools for the sharing and exchanging of data, information, knowledge, and actions. This paper describes ongoing research efforts in applying distributed collaborative environments to decision support for predictive mission awareness.

Unsteady-Pressure and Dynamic-Deflection Measurements on an Aeroelastic Supercritical Wing

NASA Technical Reports Server (NTRS)

Seidel, David A.; Sandford, Maynard C.; Eckstrom, Clinton V.

1991-01-01

Transonic steady and unsteady pressure tests were conducted on a large elastic wing. The wing has a supercritical airfoil, a full span aspect ratio of 10.3, a leading edge sweepback angle of 28.8 degrees, and two inboard and one outboard trailing edge control surfaces. Only the outboard control surface was deflected statically and dynamically to generate steady and unsteady flow over the wing. The unsteady surface pressure and dynamic deflection measurements of this elastic wing are presented to permit correlations of the experimental data with theoretical predictions.

Computational Model of Secondary Palate Fusion and Disruption

EPA Science Inventory

Morphogenetic events are driven by cell-generated physical forces and complex cellular dynamics. To improve our capacity to predict developmental effects from cellular alterations, we built a multi-cellular agent-based model in CompuCell3D that recapitulates the cellular networks...

Dynamic thermal signature prediction for real-time scene generation

NASA Astrophysics Data System (ADS)

Christie, Chad L.; Gouthas, Efthimios (Themie); Williams, Owen M.; Swierkowski, Leszek

2013-05-01

At DSTO, a real-time scene generation framework, VIRSuite, has been developed in recent years, within which trials data are predominantly used for modelling the radiometric properties of the simulated objects. Since in many cases the data are insufficient, a physics-based simulator capable of predicting the infrared signatures of objects and their backgrounds has been developed as a new VIRSuite module. It includes transient heat conduction within the materials, and boundary conditions that take into account the heat fluxes due to solar radiation, wind convection and radiative transfer. In this paper, an overview is presented, covering both the steady-state and transient performance.

Viable dark matter via radiative symmetry breaking in a scalar singlet Higgs portal extension of the standard model.

PubMed

Steele, T G; Wang, Zhi-Wei; Contreras, D; Mann, R B

2014-05-02

We consider the generation of dark matter mass via radiative electroweak symmetry breaking in an extension of the conformal standard model containing a singlet scalar field with a Higgs portal interaction. Generating the mass from a sequential process of radiative electroweak symmetry breaking followed by a conventional Higgs mechanism can account for less than 35% of the cosmological dark matter abundance for dark matter mass M(s)>80 GeV. However, in a dynamical approach where both Higgs and scalar singlet masses are generated via radiative electroweak symmetry breaking, we obtain much higher levels of dark matter abundance. At one-loop level we find abundances of 10%-100% with 106 GeV80 GeV detection region of the next generation XENON experiment.

Development of a dynamic computational model of social cognitive theory.

PubMed

Riley, William T; Martin, Cesar A; Rivera, Daniel E; Hekler, Eric B; Adams, Marc A; Buman, Matthew P; Pavel, Misha; King, Abby C

2016-12-01

Social cognitive theory (SCT) is among the most influential theories of behavior change and has been used as the conceptual basis of health behavior interventions for smoking cessation, weight management, and other health behaviors. SCT and other behavior theories were developed primarily to explain differences between individuals, but explanatory theories of within-person behavioral variability are increasingly needed as new technologies allow for intensive longitudinal measures and interventions adapted from these inputs. These within-person explanatory theoretical applications can be modeled as dynamical systems. SCT constructs, such as reciprocal determinism, are inherently dynamical in nature, but SCT has not been modeled as a dynamical system. This paper describes the development of a dynamical system model of SCT using fluid analogies and control systems principles drawn from engineering. Simulations of this model were performed to assess if the model performed as predicted based on theory and empirical studies of SCT. This initial model generates precise and testable quantitative predictions for future intensive longitudinal research. Dynamic modeling approaches provide a rigorous method for advancing health behavior theory development and refinement and for guiding the development of more potent and efficient interventions.

Evaluating mallard adaptive management models with time series

USGS Publications Warehouse

Conn, P.B.; Kendall, W.L.

2004-01-01

Wildlife practitioners concerned with midcontinent mallard (Anas platyrhynchos) management in the United States have instituted a system of adaptive harvest management (AHM) as an objective format for setting harvest regulations. Under the AHM paradigm, predictions from a set of models that reflect key uncertainties about processes underlying population dynamics are used in coordination with optimization software to determine an optimal set of harvest decisions. Managers use comparisons of the predictive abilities of these models to gauge the relative truth of different hypotheses about density-dependent recruitment and survival, with better-predicting models giving more weight to the determination of harvest regulations. We tested the effectiveness of this strategy by examining convergence rates of 'predictor' models when the true model for population dynamics was known a priori. We generated time series for cases when the a priori model was 1 of the predictor models as well as for several cases when the a priori model was not in the model set. We further examined the addition of different levels of uncertainty into the variance structure of predictor models, reflecting different levels of confidence about estimated parameters. We showed that in certain situations, the model-selection process favors a predictor model that incorporates the hypotheses of additive harvest mortality and weakly density-dependent recruitment, even when the model is not used to generate data. Higher levels of predictor model variance led to decreased rates of convergence to the model that generated the data, but model weight trajectories were in general more stable. We suggest that predictive models should incorporate all sources of uncertainty about estimated parameters, that the variance structure should be similar for all predictor models, and that models with different functional forms for population dynamics should be considered for inclusion in predictor model! sets. All of these suggestions should help lower the probability of erroneous learning in mallard ABM and adaptive management in general.

Linking genetic and environmental factors in amphibian disease risk

PubMed Central

Savage, Anna E; Becker, Carlos G; Zamudio, Kelly R

2015-01-01

A central question in evolutionary biology is how interactions between organisms and the environment shape genetic differentiation. The pathogen Batrachochytrium dendrobatidis (Bd) has caused variable population declines in the lowland leopard frog (Lithobates yavapaiensis); thus, disease has potentially shaped, or been shaped by, host genetic diversity. Environmental factors can also influence both amphibian immunity and Bd virulence, confounding our ability to assess the genetic effects on disease dynamics. Here, we used genetics, pathogen dynamics, and environmental data to characterize L. yavapaiensis populations, estimate migration, and determine relative contributions of genetic and environmental factors in predicting Bd dynamics. We found that the two uninfected populations belonged to a single genetic deme, whereas each infected population was genetically unique. We detected an outlier locus that deviated from neutral expectations and was significantly correlated with mortality within populations. Across populations, only environmental variables predicted infection intensity, whereas environment and genetics predicted infection prevalence, and genetic diversity alone predicted mortality. At one locality with geothermally elevated water temperatures, migration estimates revealed source–sink dynamics that have likely prevented local adaptation. We conclude that integrating genetic and environmental variation among populations provides a better understanding of Bd spatial epidemiology, generating more effective conservation management strategies for mitigating amphibian declines. PMID:26136822

Analysis of factors influencing hydration site prediction based on molecular dynamics simulations.

PubMed

Yang, Ying; Hu, Bingjie; Lill, Markus A

2014-10-27

Water contributes significantly to the binding of small molecules to proteins in biochemical systems. Molecular dynamics (MD) simulation based programs such as WaterMap and WATsite have been used to probe the locations and thermodynamic properties of hydration sites at the surface or in the binding site of proteins generating important information for structure-based drug design. However, questions associated with the influence of the simulation protocol on hydration site analysis remain. In this study, we use WATsite to investigate the influence of factors such as simulation length and variations in initial protein conformations on hydration site prediction. We find that 4 ns MD simulation is appropriate to obtain a reliable prediction of the locations and thermodynamic properties of hydration sites. In addition, hydration site prediction can be largely affected by the initial protein conformations used for MD simulations. Here, we provide a first quantification of this effect and further indicate that similar conformations of binding site residues (RMSD < 0.5 Å) are required to obtain consistent hydration site predictions.

Generation of Rab-based transgenic lines for in vivo studies of endosome biology in zebrafish

PubMed Central

Clark, Brian S.; Winter, Mark; Cohen, Andrew R.; Link, Brian A.

2011-01-01

The Rab family of small GTPases function as molecular switches regulating membrane and protein trafficking. Individual Rab isoforms define and are required for specific endosomal compartments. To facilitate in vivo investigation of specific Rab proteins, and endosome biology in general, we have generated transgenic zebrafish lines to mark and manipulate Rab proteins. We also developed software to track and quantify endosome dynamics within time-lapse movies. The established transgenic lines ubiquitously express EGFP fusions of Rab5c (early endosomes), Rab11a (recycling endosomes), and Rab7 (late endosomes) to study localization and dynamics during development. Additionally, we generated UAS-based transgenic lines expressing constitutive active (CA) and dominant negative (DN) versions for each of these Rab proteins. Predicted localization and functional consequences for each line were verified through a variety of assays, including lipophilic dye uptake and Crumbs2a localization. In summary, we have established a toolset for in vivo analyses of endosome dynamics and functions. PMID:21976318

A blueprint for using climate change predictions in an eco-hydrological study

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.

2009-12-01

There is a growing interest to extend climate change predictions to smaller, catchment-size scales and identify their implications on hydrological and ecological processes. Small scale processes are, in fact, expected to mediate climate changes, producing local effects and feedbacks that can interact with the principal consequences of the change. This is particularly applicable, when a complex interaction, such as the inter-relationship between the hydrological cycle and vegetation dynamics, is considered. This study presents a blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the catchment scale. Climate conditions, present or future, are imposed through input hydrometeorological variables for hydrological and eco-hydrological models. These variables are simulated with an hourly weather generator as an outcome of a stochastic downscaling technique. The generator is parameterized to reproduce the climate of southwestern Arizona for present (1961-2000) and future (2081-2100) conditions. The methodology provides the capability to generate ensemble realizations for the future that take into account the heterogeneous nature of climate predictions from different models. The generated time series of meteorological variables for the two scenarios corresponding to the current and mean expected future serve as input to a coupled hydrological and vegetation dynamics model, “Tethys-Chloris”. The hydrological model reproduces essential components of the land-surface hydrological cycle, solving the mass and energy budget equations. The vegetation model parsimoniously parameterizes essential plant life-cycle processes, including photosynthesis, phenology, carbon allocation, and tissue turnover. The results for the two mean scenarios are compared and discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity The need to account for uncertainties in projections of future climate is discussed and a methodology for propagating these uncertainties into the probability density functions of changes in eco-hydrological variables is presented.

Application of dynamic models to estimate greenhouse gas emission by wastewater treatment plants of the pulp and paper industry.

PubMed

Ashrafi, Omid; Yerushalmi, Laleh; Haghighat, Fariborz

2013-03-01

Greenhouse gas (GHG) emission in wastewater treatment plants of the pulp-and-paper industry was estimated by using a dynamic mathematical model. Significant variations were shown in the magnitude of GHG generation in response to variations in operating parameters, demonstrating the limited capacity of steady-state models in predicting the time-dependent emissions of these harmful gases. The examined treatment systems used aerobic, anaerobic, and hybrid-anaerobic/aerobic-biological processes along with chemical coagulation/flocculation, anaerobic digester, nitrification and denitrification processes, and biogas recovery. The pertinent operating parameters included the influent substrate concentration, influent flow rate, and temperature. Although the average predictions by the dynamic model were only 10 % different from those of steady-state model during 140 days of operation of the examined systems, the daily variations of GHG emissions were different up to ± 30, ± 19, and ± 17 % in the aerobic, anaerobic, and hybrid systems, respectively. The variations of process variables caused fluctuations in energy generation from biogas recovery by ± 6, ± 7, and ± 4 % in the three examined systems, respectively. The lowest variations were observed in the hybrid system, showing the stability of this particular process design.

Oscillatory Protein Expression Dynamics Endows Stem Cells with Robust Differentiation Potential

PubMed Central

Kaneko, Kunihiko

2011-01-01

The lack of understanding of stem cell differentiation and proliferation is a fundamental problem in developmental biology. Although gene regulatory networks (GRNs) for stem cell differentiation have been partially identified, the nature of differentiation dynamics and their regulation leading to robust development remain unclear. Herein, using a dynamical system modeling cell approach, we performed simulations of the developmental process using all possible GRNs with a few genes, and screened GRNs that could generate cell type diversity through cell-cell interactions. We found that model stem cells that both proliferated and differentiated always exhibited oscillatory expression dynamics, and the differentiation frequency of such stem cells was regulated, resulting in a robust number distribution. Moreover, we uncovered the common regulatory motifs for stem cell differentiation, in which a combination of regulatory motifs that generated oscillatory expression dynamics and stabilized distinct cellular states played an essential role. These findings may explain the recently observed heterogeneity and dynamic equilibrium in cellular states of stem cells, and can be used to predict regulatory networks responsible for differentiation in stem cell systems. PMID:22073296

Effects of dynamic long-period ocean tides on changes in earth's rotation rate

NASA Technical Reports Server (NTRS)

Nam, Young; Dickman, S. R.

1990-01-01

As a generalization of the zonal response coefficient first introduced by Agnew and Farrell (1978), the zonal response function kappa of the solid earth-ocean system is defined as the ratio, in the frequency domain, of the tidal change in earth's rotation rate to the tide-generating potential. Amplitudes and phases of kappa for the monthly, fortnightly, and nine-day lunar tides are estimated from 2 1/2 years of VLBI UT1 observations, corrected for atmospheric angular momentum effects using NMC wind and pressure series. Using the dynamic ocean tide model of Dickman (1988, 1989), amplitudes and phases of kappa for an elastic earth-ocean system are predicted. The predictions confirm earlier results which found that dynamic effects of the longer-period ocean tides reduce the amplitude of kappa by about 1 percent.

Ab initio molecular dynamics simulation of aqueous solution of nitric oxide in different formal oxidation states

NASA Astrophysics Data System (ADS)

Venâncio, Mateus F.; Rocha, Willian R.

2015-10-01

Ab initio molecular dynamics simulations were used to investigate the early chemical events involved in the dynamics of nitric oxide (NOrad), nitrosonium cation (NO+) and nitroxide anion (NO-) in aqueous solution. The NO+ ion is very reactive in aqueous solution having a lifetime of ∼4 × 10-13 s, which is shorter than the value of 3 × 10-10 s predicted experimentally. The NO+ reacts generating the nitrous acid as an intermediate and the NO2- ion as the final product. The dynamics of NOrad revealed the reversibly formation of a transient anion radical species HONOrad -.

Local adaptation in transgenerational responses to predators

PubMed Central

Walsh, Matthew R.; Castoe, Todd; Holmes, Julian; Packer, Michelle; Biles, Kelsey; Walsh, Melissa; Munch, Stephan B.; Post, David M.

2016-01-01

Environmental signals can induce phenotypic changes that span multiple generations. Along with phenotypic responses that occur during development (i.e. ‘within-generation’ plasticity), such ‘transgenerational plasticity’ (TGP) has been documented in a diverse array of taxa spanning many environmental perturbations. New theory predicts that temporal stability is a key driver of the evolution of TGP. We tested this prediction using natural populations of zooplankton from lakes in Connecticut that span a large gradient in the temporal dynamics of predator-induced mortality. We reared more than 120 clones of Daphnia ambigua from nine lakes for multiple generations in the presence/absence of predator cues. We found that temporal variation in mortality selects for within-generation plasticity while consistently strong (or weak) mortality selects for increased TGP. Such results provide us the first evidence for local adaptation in TGP and argue that divergent ecological conditions select for phenotypic responses within and across generations. PMID:26817775

Detection of dominant runoff generation processes for catchment classification

NASA Astrophysics Data System (ADS)

Gioia, A.; Manfreda, S.; Iacobellis, V.; Fiorentino, M.

2009-04-01

The identification of similar hydroclimatic regions in order to reduce the uncertainty on flood prediction in ungauged basins, represents one of the most exciting challenges faced by hydrologists in the last few years (e.g., IAHS Decade on Predictions in Ungauged Basins (PUB) - Sivapalan et al. [2003]). In this context, the investigation of the dominant runoff generation mechanisms may provide a strategy for catchment classification and identification of hydrologically homogeneous group of basins. In particular, the present study focuses on two classical schemes responsible of runoff production: saturation and infiltration excess. Thus, in principle, the occurrence of either mechanism may be detected in the same basin according to the climatic forcing. Here the dynamics of runoff generation are investigated over a set of basins in order to identify the dynamics which are responsible of the transition between the two schemes and to recognize homogeneous group of basins. We exploit a basin characterization obtained by means of a theoretical flood probability distribution, which was applied on a broad number of arid and humid river basins belonging to the Southern Italy region, with aim to describe the effect of different runoff production mechanisms in the generation of ordinary and extraordinary flood events. Sivapalan, M., Takeuchi, K., Franks, S. W., Gupta, V. K., Karambiri, H., Lakshmi, V., Liang, X., McDonnell, J. J., Mendiondo, E. M., O'Connell, P. E., Oki, T., Pomeroy, J. W., Schertzer, D., Uhlenbrook, S. and Zehe, E.: IAHS Decade on Predictions in Ungauged Basins (PUB), 2003-2012: Shaping an exciting future for the hydrological sciences, Hydrol. Sci. J., 48(6), 857-880, 2003.

Genetic training of network using chaos concept: application to QSAR studies of vibration modes of tetrahedral halides.

PubMed

Lu, Qingzhang; Shen, Guoli; Yu, Ruqin

2002-11-15

The chaotic dynamical system is introduced in genetic algorithm to train ANN to formulate the CGANN algorithm. Logistic mapping as one of the most important chaotic dynamic mappings provides each new generation a high chance to hold GA's population diversity. This enhances the ability to overcome overfitting in training an ANN. The proposed CGANN has been used for QSAR studies to predict the tetrahedral modes (nu(1)(A1) and nu(2)(E)) of halides [MX(4)](epsilon). The frequencies predicted by QSAR were compared with those calculated by quantum chemistry methods including PM3, AM1, and MNDO/d. The possibility of improving the predictive ability of QSAR by including quantum chemistry parameters as feature variables has been investigated using tetrahedral tetrahalide examples. Copyright 2002 Wiley Periodicals, Inc.

Prediction of Narrow N* and {Lambda}* Resonances with Hidden Charm above 4 GeV

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

Wu Jiajun; Departamento de Fisica Teorica and IFIC, Centro Mixto Universidad de Valencia-CSIC, Institutos de Investigacion de Paterna, Apartado 22085, 46071 Valencia; Molina, R.

2010-12-03

The interaction between various charmed mesons and charmed baryons is studied within the framework of the coupled-channel unitary approach with the local hidden gauge formalism. Several meson-baryon dynamically generated narrow N{sup *} and {Lambda}{sup *} resonances with hidden charm are predicted with mass above 4 GeV and width smaller than 100 MeV. The predicted new resonances definitely cannot be accommodated by quark models with three constituent quarks and can be looked for in the forthcoming PANDA/FAIR experiments.

Chaos and unpredictability in evolution.

PubMed

Doebeli, Michael; Ispolatov, Iaroslav

2014-05-01

The possibility of complicated dynamic behavior driven by nonlinear feedbacks in dynamical systems has revolutionized science in the latter part of the last century. Yet despite examples of complicated frequency dynamics, the possibility of long-term evolutionary chaos is rarely considered. The concept of "survival of the fittest" is central to much evolutionary thinking and embodies a perspective of evolution as a directional optimization process exhibiting simple, predictable dynamics. This perspective is adequate for simple scenarios, when frequency-independent selection acts on scalar phenotypes. However, in most organisms many phenotypic properties combine in complicated ways to determine ecological interactions, and hence frequency-dependent selection. Therefore, it is natural to consider models for evolutionary dynamics generated by frequency-dependent selection acting simultaneously on many different phenotypes. Here we show that complicated, chaotic dynamics of long-term evolutionary trajectories in phenotype space is very common in a large class of such models when the dimension of phenotype space is large, and when there are selective interactions between the phenotypic components. Our results suggest that the perspective of evolution as a process with simple, predictable dynamics covers only a small fragment of long-term evolution. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Predicting Culex pipiens/restuans population dynamics by interval lagged weather data

PubMed Central

2013-01-01

Background Culex pipiens/restuans mosquitoes are important vectors for a variety of arthropod borne viral infections. In this study, the associations between 20 years of mosquito capture data and the time lagged environmental quantities daytime length, temperature, precipitation, relative humidity and wind speed were used to generate a predictive model for the population dynamics of this vector species. Methods Mosquito population in the study area was represented by averaged time series of mosquitos counts captured at 6 sites in Cook County (Illinois, USA). Cross-correlation maps (CCMs) were compiled to investigate the association between mosquito abundances and environmental quantities. The results obtained from the CCMs were incorporated into a Poisson regression to generate a predictive model. To optimize the predictive model the time lags obtained from the CCMs were adjusted using a genetic algorithm. Results CCMs for weekly data showed a highly positive correlation of mosquito abundances with daytime length 4 to 5 weeks prior to capture (quantified by a Spearman rank order correlation of rS = 0.898) and with temperature during 2 weeks prior to capture (rS = 0.870). Maximal negative correlations were found for wind speed averaged over 3 week prior to capture (rS = −0.621). Cx. pipiens/restuans population dynamics was predicted by integrating the CCM results in Poisson regression models. They were used to simulate the average seasonal cycle of the mosquito abundance. Verification with observations resulted in a correlation of rS = 0.899 for daily and rS = 0.917 for weekly data. Applying the optimized models to the entire 20-years time series also resulted in a suitable fit with rS = 0.876 for daily and rS = 0.899 for weekly data. Conclusions The study demonstrates the application of interval lagged weather data to predict mosquito abundances with a feasible accuracy, especially when related to weekly Cx. pipiens/restuans populations. PMID:23634763

Improving Geostationary Satellite GPS Positioning Error Using Dynamic Two-Way Time Transfer Measurements

DTIC Science & Technology

2007-11-01

P. Y. C. Hwang . 1997, Introduction to Random Signals and Applied Kalman Filtering (John Wiley & Sons, New York). [7] S. Hutsell, 1995, “Fine Tuning...data to generate pseudorange and TWTT measurements for a geostationary satellite. The kalman function inputs the generated measurements into a... Kalman filter and predicts the state of the satellite at each epoch in the simulation. The analyze_results function takes the results of the Kalman

Influence Of Momentum Excess On The Pattern And Dynamics Of Intermediate-Range Stratified Wakes

DTIC Science & Technology

2016-06-01

excess in order to model the fundamental differences between signatures generated by towed and self- propelled bodies in various ocean states. In cases...which can be used on the operational level for developing and improving algorithms for non- acoustic signature prediction and detection. 14. SUBJECT...order to model the fundamental differences between signatures generated by towed and self- propelled bodies in various ocean states. In cases where

The dynamics of transmission and the dynamics of networks.

PubMed

Farine, Damien

2017-05-01

A toy example depicted here highlighting the results of a study in this issue of the Journal of Animal Ecology that investigates the impact of network dynamics on potential disease outbreaks. Infections (stars) that spread by contact only (left) reduce the predicted outbreak size compared to situations where individuals can become infected by moving through areas that previously contained infected individuals (right). This is potentially important in species where individuals, or in this case groups, have overlapping ranges (as depicted on the top right). Incorporating network dynamics that maintain information about the ordering of contacts (central blocks; including the ordering of spatial overlap as noted by the arrows that highlight the blue group arriving after the red group in top-right of the figure) is important for capturing how a disease might not have the opportunity to spread to all individuals. By contrast, a static or 'average' network (lower blocks) does not capture any of these dynamics. Interestingly, although static networks generally predict larger outbreak sizes, the authors find that in cases when transmission probability is low, this prediction can switch as a result of changes in the estimated intensity of contacts among individuals. [Colour figure can be viewed at wileyonlinelibrary.com]. Springer, A., Kappeler, P.M. & Nunn, C.L. (2017) Dynamic vs. static social networks in models of parasite transmission: Predicting Cryptosporidium spread in wild lemurs. Journal of Animal Ecology, 86, 419-433. The spread of disease or information through networks can be affected by several factors. Whether and how these factors are accounted for can fundamentally change the predicted impact of a spreading epidemic. Springer, Kappeler & Nunn () investigate the role of different modes of transmission and network dynamics on the predicted size of a disease outbreak across several groups of Verreaux's sifakas, a group-living species of lemur. While some factors, such as seasonality, led to consistent differences in the structure of social networks, using dynamic vs. static representations of networks generated differences in the predicted outbreak size of an emergent disease. These findings highlight some of the challenges associated with studying disease dynamics in animal populations, and the importance of continuing efforts to develop the network tools needed to study disease spread. © 2017 The Author. Journal of Animal Ecology © 2017 British Ecological Society.

Observing Clonal Dynamics across Spatiotemporal Axes: A Prelude to Quantitative Fitness Models for Cancer.

PubMed

McPherson, Andrew W; Chan, Fong Chun; Shah, Sohrab P

2018-02-01

The ability to accurately model evolutionary dynamics in cancer would allow for prediction of progression and response to therapy. As a prelude to quantitative understanding of evolutionary dynamics, researchers must gather observations of in vivo tumor evolution. High-throughput genome sequencing now provides the means to profile the mutational content of evolving tumor clones from patient biopsies. Together with the development of models of tumor evolution, reconstructing evolutionary histories of individual tumors generates hypotheses about the dynamics of evolution that produced the observed clones. In this review, we provide a brief overview of the concepts involved in predicting evolutionary histories, and provide a workflow based on bulk and targeted-genome sequencing. We then describe the application of this workflow to time series data obtained for transformed and progressed follicular lymphomas (FL), and contrast the observed evolutionary dynamics between these two subtypes. We next describe results from a spatial sampling study of high-grade serous (HGS) ovarian cancer, propose mechanisms of disease spread based on the observed clonal mixtures, and provide examples of diversification through subclonal acquisition of driver mutations and convergent evolution. Finally, we state implications of the techniques discussed in this review as a necessary but insufficient step on the path to predictive modelling of disease dynamics. Copyright © 2018 Cold Spring Harbor Laboratory Press; all rights reserved.

Prediction and validation of protein intermediate states from structurally rich ensembles and coarse-grained simulations

NASA Astrophysics Data System (ADS)

Orellana, Laura; Yoluk, Ozge; Carrillo, Oliver; Orozco, Modesto; Lindahl, Erik

2016-08-01

Protein conformational changes are at the heart of cell functions, from signalling to ion transport. However, the transient nature of the intermediates along transition pathways hampers their experimental detection, making the underlying mechanisms elusive. Here we retrieve dynamic information on the actual transition routes from principal component analysis (PCA) of structurally-rich ensembles and, in combination with coarse-grained simulations, explore the conformational landscapes of five well-studied proteins. Modelling them as elastic networks in a hybrid elastic-network Brownian dynamics simulation (eBDIMS), we generate trajectories connecting stable end-states that spontaneously sample the crystallographic motions, predicting the structures of known intermediates along the paths. We also show that the explored non-linear routes can delimit the lowest energy passages between end-states sampled by atomistic molecular dynamics. The integrative methodology presented here provides a powerful framework to extract and expand dynamic pathway information from the Protein Data Bank, as well as to validate sampling methods in general.

Modulator Dynamics Shape the Design Space for Stepwise-Elution Simulated Moving Bed Chromatographic Separations.

PubMed

Wayne, Chris J; Velayudhan, Ajoy

2018-03-31

For proteins and other biological macromolecules, SMB chromatography is best operated non-isocratically. However, traditional modes of non-isocratic SMB operation generate significant mobile-phase modulator dynamics. The mechanisms by which these modulator dynamics affect a separation's success, and thus frame the design space, have yet to be explained quantitatively. Here, the dynamics of the modulator (e.g., salts in ion exchange and hydrophobic interaction chromatography) are explicitly accounted for. This leads to the elucidation of two new design constraints, presented as dimensionless numbers, which quantify the effects of the modulator phenomena and thus predict the success of a non-isocratic SMB separation. Consequently, these two new design constraints re-define the SMB design space. Computational and experimental studies at the boundaries of this design space corroborate the theoretical predictions. The design of efficient and robust operating conditions through use of the new design space is also demonstrated. © 2018 The Authors. Biotechnology Journal Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

G12V Kras mutations in cervical cancer under virtual microscope of molecular dynamics simulations.

PubMed

Chen, X P; Xu, W H; Xu, D F; Fu, S M; Ma, Z C

2016-01-01

Kras mutations and cancers are common and their role in the progression of cancer is well known and elucidated. The present work is searching for the most deleterious mutation of the four found at codon 12 and 13 of Kras in cervical cancers using prediction servers; different servers were used to look into different factors that govern the protein function. The in silico results predicted G12V to be the most devastating; this particular mutation was then subjected to molecular dynamics simulation (MDS) for further analysis. The authors' approach of MDSs helped them to place the native and mutant structure under virtual microscope and observe their dynamics over time. The results generated are enlightening the effect of G12V variation on the dynamics of Kras. The structural variation between the native and mutant Kras over 50 nanoseconds (ns) run varied at every parameter checked and the results are in excellent agreement with the available experimental data.

Past makes future: role of pFC in prediction.

PubMed

Fuster, Joaquín M; Bressler, Steven L

2015-04-01

The pFC enables the essential human capacities for predicting future events and preadapting to them. These capacities rest on both the structure and dynamics of the human pFC. Structurally, pFC, together with posterior association cortex, is at the highest hierarchical level of cortical organization, harboring neural networks that represent complex goal-directed actions. Dynamically, pFC is at the highest level of the perception-action cycle, the circular processing loop through the cortex that interfaces the organism with the environment in the pursuit of goals. In its predictive and preadaptive roles, pFC supports cognitive functions that are critical for the temporal organization of future behavior, including planning, attentional set, working memory, decision-making, and error monitoring. These functions have a common future perspective and are dynamically intertwined in goal-directed action. They all utilize the same neural infrastructure: a vast array of widely distributed, overlapping, and interactive cortical networks of personal memory and semantic knowledge, named cognits, which are formed by synaptic reinforcement in learning and memory acquisition. From this cortex-wide reservoir of memory and knowledge, pFC generates purposeful, goal-directed actions that are preadapted to predicted future events.

Identification of Predictive Cis-Regulatory Elements Using a Discriminative Objective Function and a Dynamic Search Space

PubMed Central

Karnik, Rahul; Beer, Michael A.

2015-01-01

The generation of genomic binding or accessibility data from massively parallel sequencing technologies such as ChIP-seq and DNase-seq continues to accelerate. Yet state-of-the-art computational approaches for the identification of DNA binding motifs often yield motifs of weak predictive power. Here we present a novel computational algorithm called MotifSpec, designed to find predictive motifs, in contrast to over-represented sequence elements. The key distinguishing feature of this algorithm is that it uses a dynamic search space and a learned threshold to find discriminative motifs in combination with the modeling of motifs using a full PWM (position weight matrix) rather than k-mer words or regular expressions. We demonstrate that our approach finds motifs corresponding to known binding specificities in several mammalian ChIP-seq datasets, and that our PWMs classify the ChIP-seq signals with accuracy comparable to, or marginally better than motifs from the best existing algorithms. In other datasets, our algorithm identifies novel motifs where other methods fail. Finally, we apply this algorithm to detect motifs from expression datasets in C. elegans using a dynamic expression similarity metric rather than fixed expression clusters, and find novel predictive motifs. PMID:26465884

Identification of Predictive Cis-Regulatory Elements Using a Discriminative Objective Function and a Dynamic Search Space.

PubMed

Karnik, Rahul; Beer, Michael A

2015-01-01

The generation of genomic binding or accessibility data from massively parallel sequencing technologies such as ChIP-seq and DNase-seq continues to accelerate. Yet state-of-the-art computational approaches for the identification of DNA binding motifs often yield motifs of weak predictive power. Here we present a novel computational algorithm called MotifSpec, designed to find predictive motifs, in contrast to over-represented sequence elements. The key distinguishing feature of this algorithm is that it uses a dynamic search space and a learned threshold to find discriminative motifs in combination with the modeling of motifs using a full PWM (position weight matrix) rather than k-mer words or regular expressions. We demonstrate that our approach finds motifs corresponding to known binding specificities in several mammalian ChIP-seq datasets, and that our PWMs classify the ChIP-seq signals with accuracy comparable to, or marginally better than motifs from the best existing algorithms. In other datasets, our algorithm identifies novel motifs where other methods fail. Finally, we apply this algorithm to detect motifs from expression datasets in C. elegans using a dynamic expression similarity metric rather than fixed expression clusters, and find novel predictive motifs.

Study on the Reduced Traffic Congestion Method Based on Dynamic Guidance Information

NASA Astrophysics Data System (ADS)

Li, Shu-Bin; Wang, Guang-Min; Wang, Tao; Ren, Hua-Ling; Zhang, Lin

2018-05-01

This paper studies how to generate the reasonable information of travelers’ decision in real network. This problem is very complex because the travelers’ decision is constrained by different human behavior. The network conditions can be predicted by using the advanced dynamic OD (Origin-Destination, OD) estimation techniques. Based on the improved mesoscopic traffic model, the predictable dynamic traffic guidance information can be obtained accurately. A consistency algorithm is designed to investigate the travelers’ decision by simulating the dynamic response to guidance information. The simulation results show that the proposed method can provide the best guidance information. Further, a case study is conducted to verify the theoretical results and to draw managerial insights into the potential of dynamic guidance strategy in improving traffic performance. Supported by National Natural Science Foundation of China under Grant Nos. 71471104, 71771019, 71571109, and 71471167; The University Science and Technology Program Funding Projects of Shandong Province under Grant No. J17KA211; The Project of Public Security Department of Shandong Province under Grant No. GATHT2015-236; The Major Social and Livelihood Special Project of Jinan under Grant No. 20150905

Star tracking method based on multiexposure imaging for intensified star trackers.

PubMed

Yu, Wenbo; Jiang, Jie; Zhang, Guangjun

2017-07-20

The requirements for the dynamic performance of star trackers are rapidly increasing with the development of space exploration technologies. However, insufficient knowledge of the angular acceleration has largely decreased the performance of the existing star tracking methods, and star trackers may even fail to track under highly dynamic conditions. This study proposes a star tracking method based on multiexposure imaging for intensified star trackers. The accurate estimation model of the complete motion parameters, including the angular velocity and angular acceleration, is established according to the working characteristic of multiexposure imaging. The estimation of the complete motion parameters is utilized to generate the predictive star image accurately. Therefore, the correct matching and tracking between stars in the real and predictive star images can be reliably accomplished under highly dynamic conditions. Simulations with specific dynamic conditions are conducted to verify the feasibility and effectiveness of the proposed method. Experiments with real starry night sky observation are also conducted for further verification. Simulations and experiments demonstrate that the proposed method is effective and shows excellent performance under highly dynamic conditions.

Three-Dimensional Dynamic Deformation Measurements Using Stereoscopic Imaging and Digital Speckle Photography

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

Prentice, H. J.; Proud, W. G.

2006-07-28

A technique has been developed to determine experimentally the three-dimensional displacement field on the rear surface of a dynamically deforming plate. The technique combines speckle analysis with stereoscopy, using a modified angular-lens method: this incorporates split-frame photography and a simple method by which the effective lens separation can be adjusted and calibrated in situ. Whilst several analytical models exist to predict deformation in extended or semi-infinite targets, the non-trivial nature of the wave interactions complicates the generation and development of analytical models for targets of finite depth. By interrogating specimens experimentally to acquire three-dimensional strain data points, both analytical andmore » numerical model predictions can be verified more rigorously. The technique is applied to the quasi-static deformation of a rubber sheet and dynamically to Mild Steel sheets of various thicknesses.« less

Dimensionless embedding for nonlinear time series analysis

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; Aihara, Kazuyuki

2017-09-01

Recently, infinite-dimensional delay coordinates (InDDeCs) have been proposed for predicting high-dimensional dynamics instead of conventional delay coordinates. Although InDDeCs can realize faster computation and more accurate short-term prediction, it is still not well-known whether InDDeCs can be used in other applications of nonlinear time series analysis in which reconstruction is needed for the underlying dynamics from a scalar time series generated from a dynamical system. Here, we give theoretical support for justifying the use of InDDeCs and provide numerical examples to show that InDDeCs can be used for various applications for obtaining the recurrence plots, correlation dimensions, and maximal Lyapunov exponents, as well as testing directional couplings and extracting slow-driving forces. We demonstrate performance of the InDDeCs using the weather data. Thus, InDDeCs can eventually realize "dimensionless embedding" while we enjoy faster and more reliable computations.

Prediction of flow dynamics using point processes

NASA Astrophysics Data System (ADS)

Hirata, Yoshito; Stemler, Thomas; Eroglu, Deniz; Marwan, Norbert

2018-01-01

Describing a time series parsimoniously is the first step to study the underlying dynamics. For a time-discrete system, a generating partition provides a compact description such that a time series and a symbolic sequence are one-to-one. But, for a time-continuous system, such a compact description does not have a solid basis. Here, we propose to describe a time-continuous time series using a local cross section and the times when the orbit crosses the local cross section. We show that if such a series of crossing times and some past observations are given, we can predict the system's dynamics with fine accuracy. This reconstructability neither depends strongly on the size nor the placement of the local cross section if we have a sufficiently long database. We demonstrate the proposed method using the Lorenz model as well as the actual measurement of wind speed.

On the impact index of synchronous generator displaced by DFIG on power system small-signal stability

NASA Astrophysics Data System (ADS)

Bi, J. T.; Du, W. J.; Wang, H. F.; Song, Y. T.; Wang, Q.; Ding, J.; Chen, D. Z.; Wei, W.

2017-05-01

As the maturity of wind power technology and the ageing and retirement of conventional synchronous generators, the displacement of synchronous generators by wind power generators would be a trend in the next few decades. The power system small-signal angular stability caused by the displacement is an urgent problem to be studied. The displacement of the SG by the DFIG includes withdrawing the dynamic interactions of the displaced SG and adding the dynamic interactions of the displacing DFIG. Based on this fact, a new index is proposed to predict the impact of the SG to be displaced by the DFIG on power system oscillation modes. The sensitivity index of the oscillation modes to the constant inertia of the displaced SGs, proposed in early literatures to estimate the dynamic impact of the SG being displaced by the DFIG, is also compared with the proposed index. The modified New England power system is adopted to show various results and conclusions. The proposed index can correctly identify the most dangerous and beneficial displacement to power system small-signal angular stability, and is very useful in practical applications.

On the scaling and dynamics of periodically generated vortex rings

NASA Astrophysics Data System (ADS)

Asadi, Hossein; Asgharzadeh, Hafez; Borazjani, Iman; Scientific Computing; Biofluids Team

2017-11-01

Periodically generated vortex rings are observed in nature, e.g., left ventricle or jellyfish, but their scaling and dynamics is not completely well understood. We are interested in identifying the main parameters governing the propagation and dynamics of periodically generated vortex rings. Therefore, vortex rings, generated periodically through a circular cylinder into a tank, is numerically investigated for a range of Reynolds numbers (Re), non-dimensional periods (T), and stroke ratios (stroke time to period) for a simple square wave. Based on the results, by using the averaged inflow velocity in definition of Reynolds number and non-dimensional period, vortex ring velocity becomes approximately independent of the stroke ratio. The results also show that reducing Reynolds number or increasing non-dimensional period increases the translational velocity of vortex ring. Based on our test cases, an empirical relation is proposed to predict the location of vortex cores propagating into domain which shows good agreement with other experimental data. The vortex instabilities and interactions are also visualized and discussed. This work was supported by AHA Grant 13SDG17220022, NIH Grant R03EB014860, and the Center of Computational Research (CCR) of University at Buffalo.

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

PubMed

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

2017-05-01

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

A nonlinear autoregressive Volterra model of the Hodgkin-Huxley equations.

PubMed

Eikenberry, Steffen E; Marmarelis, Vasilis Z

2013-02-01

We propose a new variant of Volterra-type model with a nonlinear auto-regressive (NAR) component that is a suitable framework for describing the process of AP generation by the neuron membrane potential, and we apply it to input-output data generated by the Hodgkin-Huxley (H-H) equations. Volterra models use a functional series expansion to describe the input-output relation for most nonlinear dynamic systems, and are applicable to a wide range of physiologic systems. It is difficult, however, to apply the Volterra methodology to the H-H model because is characterized by distinct subthreshold and suprathreshold dynamics. When threshold is crossed, an autonomous action potential (AP) is generated, the output becomes temporarily decoupled from the input, and the standard Volterra model fails. Therefore, in our framework, whenever membrane potential exceeds some threshold, it is taken as a second input to a dual-input Volterra model. This model correctly predicts membrane voltage deflection both within the subthreshold region and during APs. Moreover, the model naturally generates a post-AP afterpotential and refractory period. It is known that the H-H model converges to a limit cycle in response to a constant current injection. This behavior is correctly predicted by the proposed model, while the standard Volterra model is incapable of generating such limit cycle behavior. The inclusion of cross-kernels, which describe the nonlinear interactions between the exogenous and autoregressive inputs, is found to be absolutely necessary. The proposed model is general, non-parametric, and data-derived.

Teaching the principles of statistical dynamics

PubMed Central

Ghosh, Kingshuk; Dill, Ken A.; Inamdar, Mandar M.; Seitaridou, Effrosyni; Phillips, Rob

2012-01-01

We describe a simple framework for teaching the principles that underlie the dynamical laws of transport: Fick’s law of diffusion, Fourier’s law of heat flow, the Newtonian viscosity law, and the mass-action laws of chemical kinetics. In analogy with the way that the maximization of entropy over microstates leads to the Boltzmann distribution and predictions about equilibria, maximizing a quantity that E. T. Jaynes called “caliber” over all the possible microtrajectories leads to these dynamical laws. The principle of maximum caliber also leads to dynamical distribution functions that characterize the relative probabilities of different microtrajectories. A great source of recent interest in statistical dynamics has resulted from a new generation of single-particle and single-molecule experiments that make it possible to observe dynamics one trajectory at a time. PMID:23585693

Teaching the principles of statistical dynamics.

PubMed

Ghosh, Kingshuk; Dill, Ken A; Inamdar, Mandar M; Seitaridou, Effrosyni; Phillips, Rob

2006-02-01

We describe a simple framework for teaching the principles that underlie the dynamical laws of transport: Fick's law of diffusion, Fourier's law of heat flow, the Newtonian viscosity law, and the mass-action laws of chemical kinetics. In analogy with the way that the maximization of entropy over microstates leads to the Boltzmann distribution and predictions about equilibria, maximizing a quantity that E. T. Jaynes called "caliber" over all the possible microtrajectories leads to these dynamical laws. The principle of maximum caliber also leads to dynamical distribution functions that characterize the relative probabilities of different microtrajectories. A great source of recent interest in statistical dynamics has resulted from a new generation of single-particle and single-molecule experiments that make it possible to observe dynamics one trajectory at a time.

Hemolytic potential of hydrodynamic cavitation.

PubMed

Chambers, S D; Bartlett, R H; Ceccio, S L

2000-08-01

The purpose of this study was to determine the hemolytic potentials of discrete bubble cavitation and attached cavitation. To generate controlled cavitation events, a venturigeometry hydrodynamic device, called a Cavitation Susceptibility Meter (CSM), was constructed. A comparison between the hemolytic potential of discrete bubble cavitation and attached cavitation was investigated with a single-pass flow apparatus and a recirculating flow apparatus, both utilizing the CSM. An analytical model, based on spherical bubble dynamics, was developed for predicting the hemolysis caused by discrete bubble cavitation. Experimentally, discrete bubble cavitation did not correlate with a measurable increase in plasma-free hemoglobin (PFHb), as predicted by the analytical model. However, attached cavitation did result in significant PFHb generation. The rate of PFHb generation scaled inversely with the Cavitation number at a constant flow rate, suggesting that the size of the attached cavity was the dominant hemolytic factor.

Effects of dynamic long-period ocean tides on changes in Earth's rotation rate

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

Nam, Y.S.; Dickman, S.R.

1990-05-10

As a generalization of the zonal response coefficient first introduced by Agnew and Farrell (1978), the authors define the zonal response function k of the solid earth-ocean system as the ratio, in the frequency domain, of the tidal change in Earth's rotation rate to the tide-generating potential. Amplitudes and phases of k for the monthly, fortnightly, and 9-day lunar tides are estimated from 2 1/2 years of very long baseline interferometry UTI observations (both 5-day and daily time series), corrected for atmospheric angular momentum effects using NMC wind and pressure series. Using the dynamic ocean tide model of Dickman (1988a,more » 1989a), the authors predict amplitudes and phases of k for an elastic earth-ocean system. The predictions confirm earlier results which found that dynamic effects of the longer-period ocean tides reduce the amplitude of k by about 1%. However, agreement with the observed k is best achieved for all three tides if the predicted tide amplitudes are combined with the much larger satellite-observed ocean tide phases; in these cases the dynamic tidal effects reduce k by up to 8%. Finally, comparison between the observed and predicted amplitudes of k implies that anelastic effects on Earth's rotation at periods less than fortnightly cannot exceed 2%.« less

Energy prediction using spatiotemporal pattern networks

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

Jiang, Zhanhong; Liu, Chao; Akintayo, Adedotun

This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamical filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependencies among different sub-systems. To quantify causal dependencies, a mutual information based metric is presented and an energy prediction approach is subsequently proposed based on the STPN framework. To validate the proposed scheme, two case studies are presented, one involving wind turbine power prediction (supply side energy) using the Western Wind Integration data set generated bymore » the National Renewable Energy Laboratory (NREL) for identifying spatiotemporal characteristics, and the other, residential electric energy disaggregation (demand side energy) using the Building America 2010 data set from NREL for exploring temporal features. In the energy disaggregation context, convex programming techniques beyond the STPN framework are developed and applied to achieve improved disaggregation performance.« less

Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

NASA Technical Reports Server (NTRS)

Liu, Yi; Anusonti-Inthra, Phuriwat; Diskin, Boris

2011-01-01

A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

Ultra-high-frequency chaos in a time-delay electronic device with band-limited feedback.

PubMed

Illing, Lucas; Gauthier, Daniel J

2006-09-01

We report an experimental study of ultra-high-frequency chaotic dynamics generated in a delay-dynamical electronic device. It consists of a transistor-based nonlinearity, commercially-available amplifiers, and a transmission-line for feedback. The feedback is band-limited, allowing tuning of the characteristic time-scales of both the periodic and high-dimensional chaotic oscillations that can be generated with the device. As an example, periodic oscillations ranging from 48 to 913 MHz are demonstrated. We develop a model and use it to compare the experimentally observed Hopf bifurcation of the steady-state to existing theory [Illing and Gauthier, Physica D 210, 180 (2005)]. We find good quantitative agreement of the predicted and the measured bifurcation threshold, bifurcation type and oscillation frequency. Numerical integration of the model yields quasiperiodic and high dimensional chaotic solutions (Lyapunov dimension approximately 13), which match qualitatively the observed device dynamics.

Binary black hole merger dynamics and waveforms

NASA Technical Reports Server (NTRS)

Baker, John G.; Centrella, Joan; Choi, Dae-II; Koppitz, Michael; vanMeter, James

2006-01-01

We apply recently developed techniques for simulations of moving black holes to study dynamics and radiation generation in the last few orbits and merger of a binary black hole system. Our analysis produces a consistent picture from the gravitational wave forms and dynamical black hole trajectories for a set of simulations with black holes beginning on circular-orbit trajectories at a variety of initial separations. We find profound agreement at the level of 1% among the simulations for the last orbit, merger and ringdown, resulting in a final black hole with spin parameter a/m = 0.69. Consequently, we are confident that this part of our waveform result accurately represents the predictions from Einstein's General Relativity for the final burst of gravitational radiation resulting from the merger of an astrophysical system of equal-mass non-spinning black holes. We also find good agreement at a level of roughly 10% for the radiation generated in the preceding few orbits.

Predicting the Dynamic Crushing Response of a Composite Honeycomb Energy Absorber Using Solid-Element-Based Models in LS-DYNA

NASA Technical Reports Server (NTRS)

Jackson, Karen E.

2010-01-01

This paper describes an analytical study that was performed as part of the development of an externally deployable energy absorber (DEA) concept. The concept consists of a composite honeycomb structure that can be stowed until needed to provide energy attenuation during a crash event, much like an external airbag system. One goal of the DEA development project was to generate a robust and reliable Finite Element Model (FEM) of the DEA that could be used to accurately predict its crush response under dynamic loading. The results of dynamic crush tests of 50-, 104-, and 68-cell DEA components are presented, and compared with simulation results from a solid-element FEM. Simulations of the FEM were performed in LS-DYNA(Registered TradeMark) to compare the capabilities of three different material models: MAT 63 (crushable foam), MAT 26 (honeycomb), and MAT 126 (modified honeycomb). These material models are evaluated to determine if they can be used to accurately predict both the uniform crushing and final compaction phases of the DEA for normal and off-axis loading conditions

Finite Element Analysis of Wrinkled Membrane Structures for Sunshield Applications

NASA Technical Reports Server (NTRS)

Johnston, John D.; Brodeur, Stephen J. (Technical Monitor)

2002-01-01

The deployable sunshield is an example of a gossamer structure envisioned for use on future space telescopes. The basic structure consists of multiple layers of pretensioned, thin-film membranes supported by deployable booms. The prediction and verification of sunshield dynamics has been identified as an area in need of technology development due to the difficulties inherent in predicting nonlinear structural behavior of the membranes and because of the challenges involved. in ground testing of the full-scale structure. This paper describes a finite element analysis of a subscale sunshield that has been subjected to ground testing in support of the Next Generation Space Telescope (NGST) program. The analysis utilizes a nonlinear material model that accounts for wrinkling of the membranes. Results are presented from a nonlinear static preloading analysis and subsequent dynamics analyses to illustrate baseline sunshield structural characteristics. Studies are then described which provide further insight into the effect of membrane. preload on sunshield dynamics and the performance of different membrane modeling techniques. Lastly, a comparison of analytical predictions and ground test results is presented.

The movement ecology and dynamics of plant communities in fragmented landscapes.

PubMed

Damschen, Ellen I; Brudvig, Lars A; Haddad, Nick M; Levey, Douglas J; Orrock, John L; Tewksbury, Joshua J

2008-12-09

A conceptual model of movement ecology has recently been advanced to explain all movement by considering the interaction of four elements: internal state, motion capacity, navigation capacities, and external factors. We modified this framework to generate predictions for species richness dynamics of fragmented plant communities and tested them in experimental landscapes across a 7-year time series. We found that two external factors, dispersal vectors and habitat features, affected species colonization and recolonization in habitat fragments and their effects varied and depended on motion capacity. Bird-dispersed species richness showed connectivity effects that reached an asymptote over time, but no edge effects, whereas wind-dispersed species richness showed steadily accumulating edge and connectivity effects, with no indication of an asymptote. Unassisted species also showed increasing differences caused by connectivity over time, whereas edges had no effect. Our limited use of proxies for movement ecology (e.g., dispersal mode as a proxy for motion capacity) resulted in moderate predictive power for communities and, in some cases, highlighted the importance of a more complete understanding of movement ecology for predicting how landscape conservation actions affect plant community dynamics.

Dynamic Field and Current Distributions in Multifilamentary YBa2Cu3O7-delta Thin Films with Magnetic Coupling (POSTPRINT)

DTIC Science & Technology

2010-03-01

INTRODUCTION The separation of high-temperature superconducting HTS tapes into filaments is a viable approach to reduce ac and hysteretic losses in...generation HTS coated conductors. However, ac losses of finely striated tapes can still be larger than desired as predicted by analytical expressions.6...necessitates an in-depth understanding of the flux and current dynamics in multifilamentary HTS structures as both depend strongly on temperature and history of

NASA Computational Fluid Dynamics Conference. Volume 1: Sessions 1-6

NASA Technical Reports Server (NTRS)

1989-01-01

Presentations given at the NASA Computational Fluid Dynamics (CFD) Conference held at the NASA Ames Research Center, Moffett Field, California, March 7-9, 1989 are given. Topics covered include research facility overviews of CFD research and applications, validation programs, direct simulation of compressible turbulence, turbulence modeling, advances in Runge-Kutta schemes for solving 3-D Navier-Stokes equations, grid generation and invicid flow computation around aircraft geometries, numerical simulation of rotorcraft, and viscous drag prediction for rotor blades.

Sampling-based real-time motion planning under state uncertainty for autonomous micro-aerial vehicles in GPS-denied environments.

PubMed

Li, Dachuan; Li, Qing; Cheng, Nong; Song, Jingyan

2014-11-18

This paper presents a real-time motion planning approach for autonomous vehicles with complex dynamics and state uncertainty. The approach is motivated by the motion planning problem for autonomous vehicles navigating in GPS-denied dynamic environments, which involves non-linear and/or non-holonomic vehicle dynamics, incomplete state estimates, and constraints imposed by uncertain and cluttered environments. To address the above motion planning problem, we propose an extension of the closed-loop rapid belief trees, the closed-loop random belief trees (CL-RBT), which incorporates predictions of the position estimation uncertainty, using a factored form of the covariance provided by the Kalman filter-based estimator. The proposed motion planner operates by incrementally constructing a tree of dynamically feasible trajectories using the closed-loop prediction, while selecting candidate paths with low uncertainty using efficient covariance update and propagation. The algorithm can operate in real-time, continuously providing the controller with feasible paths for execution, enabling the vehicle to account for dynamic and uncertain environments. Simulation results demonstrate that the proposed approach can generate feasible trajectories that reduce the state estimation uncertainty, while handling complex vehicle dynamics and environment constraints.

Oceanic island biogeography through the lens of the general dynamic model: assessment and prospect.

PubMed

Borregaard, Michael K; Amorim, Isabel R; Borges, Paulo A V; Cabral, Juliano S; Fernández-Palacios, José M; Field, Richard; Heaney, Lawrence R; Kreft, Holger; Matthews, Thomas J; Olesen, Jens M; Price, Jonathan; Rigal, Francois; Steinbauer, Manuel J; Triantis, Konstantinos A; Valente, Luis; Weigelt, Patrick; Whittaker, Robert J

2017-05-01

The general dynamic model of oceanic island biogeography (GDM) has added a new dimension to theoretical island biogeography in recognizing that geological processes are key drivers of the evolutionary processes of diversification and extinction within remote islands. It provides a dynamic and essentially non-equilibrium framework generating novel predictions for emergent diversity properties of oceanic islands and archipelagos. Its publication in 2008 coincided with, and spurred on, renewed attention to the dynamics of remote islands. We review progress, both in testing the GDM's predictions and in developing and enhancing ecological-evolutionary understanding of oceanic island systems through the lens of the GDM. In particular, we focus on four main themes: (i) macroecological tests using a space-for-time rationale; (ii) extensions of theory to islands following different patterns of ontogeny; (iii) the implications of GDM dynamics for lineage diversification and trait evolution; and (iv) the potential for downscaling GDM dynamics to local-scale ecological patterns and processes within islands. We also consider the implications of the GDM for understanding patterns of non-native species diversity. We demonstrate the vitality of the field of island biogeography by identifying a range of potentially productive lines for future research. © 2016 Cambridge Philosophical Society.

Sampling-Based Real-Time Motion Planning under State Uncertainty for Autonomous Micro-Aerial Vehicles in GPS-Denied Environments

PubMed Central

Li, Dachuan; Li, Qing; Cheng, Nong; Song, Jingyan

2014-01-01

This paper presents a real-time motion planning approach for autonomous vehicles with complex dynamics and state uncertainty. The approach is motivated by the motion planning problem for autonomous vehicles navigating in GPS-denied dynamic environments, which involves non-linear and/or non-holonomic vehicle dynamics, incomplete state estimates, and constraints imposed by uncertain and cluttered environments. To address the above motion planning problem, we propose an extension of the closed-loop rapid belief trees, the closed-loop random belief trees (CL-RBT), which incorporates predictions of the position estimation uncertainty, using a factored form of the covariance provided by the Kalman filter-based estimator. The proposed motion planner operates by incrementally constructing a tree of dynamically feasible trajectories using the closed-loop prediction, while selecting candidate paths with low uncertainty using efficient covariance update and propagation. The algorithm can operate in real-time, continuously providing the controller with feasible paths for execution, enabling the vehicle to account for dynamic and uncertain environments. Simulation results demonstrate that the proposed approach can generate feasible trajectories that reduce the state estimation uncertainty, while handling complex vehicle dynamics and environment constraints. PMID:25412217

Gas dynamics in strong centrifugal fields

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

Bogovalov, S.V.; Kislov, V.A.; Tronin, I.V.

2015-03-10

Dynamics of waves generated by scopes in gas centrifuges (GC) for isotope separation is considered. The centrifugal acceleration in the GC reaches values of the order of 106g. The centrifugal and Coriolis forces modify essentially the conventional sound waves. Three families of the waves with different polarisation and dispersion exist in these conditions. Dynamics of the flow in the model GC Iguasu is investigated numerically. Comparison of the results of the numerical modelling of the wave dynamics with the analytical predictions is performed. New phenomena of the resonances in the GC is found. The resonances occur for the waves polarizedmore » along the rotational axis having the smallest dumping due to the viscosity.« less

Applying Parallel Adaptive Methods with GeoFEST/PYRAMID to Simulate Earth Surface Crustal Dynamics

NASA Technical Reports Server (NTRS)

Norton, Charles D.; Lyzenga, Greg; Parker, Jay; Glasscoe, Margaret; Donnellan, Andrea; Li, Peggy

2006-01-01

This viewgraph presentation reviews the use Adaptive Mesh Refinement (AMR) in simulating the Crustal Dynamics of Earth's Surface. AMR simultaneously improves solution quality, time to solution, and computer memory requirements when compared to generating/running on a globally fine mesh. The use of AMR in simulating the dynamics of the Earth's Surface is spurred by future proposed NASA missions, such as InSAR for Earth surface deformation and other measurements. These missions will require support for large-scale adaptive numerical methods using AMR to model observations. AMR was chosen because it has been successful in computation fluid dynamics for predictive simulation of complex flows around complex structures.

How uncertain is model-based prediction of copper loads in stormwater runoff?

PubMed

Lindblom, E; Ahlman, S; Mikkelsen, P S

2007-01-01

In this paper, we conduct a systematic analysis of the uncertainty related with estimating the total load of pollution (copper) from a separate stormwater drainage system, conditioned on a specific combination of input data, a dynamic conceptual pollutant accumulation-washout model and measurements (runoff volumes and pollutant masses). We use the generalized likelihood uncertainty estimation (GLUE) methodology and generate posterior parameter distributions that result in model outputs encompassing a significant number of the highly variable measurements. Given the applied pollution accumulation-washout model and a total of 57 measurements during one month, the total predicted copper masses can be predicted within a range of +/-50% of the median value. The message is that this relatively large uncertainty should be acknowledged in connection with posting statements about micropollutant loads as estimated from dynamic models, even when calibrated with on-site concentration data.

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.

The habenula encodes negative motivational value associated with primary punishment in humans.

PubMed

Lawson, Rebecca P; Seymour, Ben; Loh, Eleanor; Lutti, Antoine; Dolan, Raymond J; Dayan, Peter; Weiskopf, Nikolaus; Roiser, Jonathan P

2014-08-12

Learning what to approach, and what to avoid, involves assigning value to environmental cues that predict positive and negative events. Studies in animals indicate that the lateral habenula encodes the previously learned negative motivational value of stimuli. However, involvement of the habenula in dynamic trial-by-trial aversive learning has not been assessed, and the functional role of this structure in humans remains poorly characterized, in part, due to its small size. Using high-resolution functional neuroimaging and computational modeling of reinforcement learning, we demonstrate positive habenula responses to the dynamically changing values of cues signaling painful electric shocks, which predict behavioral suppression of responses to those cues across individuals. By contrast, negative habenula responses to monetary reward cue values predict behavioral invigoration. Our findings show that the habenula plays a key role in an online aversive learning system and in generating associated motivated behavior in humans.

A model of cell-wall dynamics during sporulation in Bacillus subtilis

NASA Astrophysics Data System (ADS)

Yap, Li-Wei; Endres, Robert G.

To survive starvation, Bacillus subtilis forms durable spores. After asymmetric cell division, the septum grows around the forespore in a process called engulfment, but the mechanism of force generation is unknown. Here, we derived a novel biophysical model for the dynamics of cell-wall remodeling during engulfment based on a balancing of dissipative, active, and mechanical forces. By plotting phase diagrams, we predict that sporulation is promoted by a line tension from the attachment of the septum to the outer cell wall, as well as by an imbalance in turgor pressures in the mother-cell and forespore compartments. We also predict that significant mother-cell growth hinders engulfment. Hence, relatively simple physical principles may guide this complex biological process.

Nano-particle drag prediction at low Reynolds number using a direct Boltzmann-BGK solution approach

NASA Astrophysics Data System (ADS)

Evans, B.

2018-01-01

This paper outlines a novel approach for solution of the Boltzmann-BGK equation describing molecular gas dynamics applied to the challenging problem of drag prediction of a 2D circular nano-particle at transitional Knudsen number (0.0214) and low Reynolds number (0.25-2.0). The numerical scheme utilises a discontinuous-Galerkin finite element discretisation for the physical space representing the problem particle geometry and a high order discretisation for molecular velocity space describing the molecular distribution function. The paper shows that this method produces drag predictions that are aligned well with the range of drag predictions for this problem generated from the alternative numerical approaches of molecular dynamics codes and a modified continuum scheme. It also demonstrates the sensitivity of flow-field solutions and therefore drag predictions to the wall absorption parameter used to construct the solid wall boundary condition used in the solver algorithm. The results from this work has applications in fields ranging from diagnostics and therapeutics in medicine to the fields of semiconductors and xerographics.

Physics-based Space Weather Forecasting in the Project for Solar-Terrestrial Environment Prediction (PSTEP) in Japan

NASA Astrophysics Data System (ADS)

Kusano, K.

2016-12-01

Project for Solar-Terrestrial Environment Prediction (PSTEP) is a Japanese nation-wide research collaboration, which was recently launched. PSTEP aims to develop a synergistic interaction between predictive and scientific studies of the solar-terrestrial environment and to establish the basis for next-generation space weather forecasting using the state-of-the-art observation systems and the physics-based models. For this project, we coordinate the four research groups, which develop (1) the integration of space weather forecast system, (2) the physics-based solar storm prediction, (3) the predictive models of magnetosphere and ionosphere dynamics, and (4) the model of solar cycle activity and its impact on climate, respectively. In this project, we will build the coordinated physics-based model to answer the fundamental questions concerning the onset of solar eruptions and the mechanism for radiation belt dynamics in the Earth's magnetosphere. In this paper, we will show the strategy of PSTEP, and discuss about the role and prospect of the physics-based space weather forecasting system being developed by PSTEP.

Analysis of Factors Influencing Hydration Site Prediction Based on Molecular Dynamics Simulations

PubMed Central

2015-01-01

Water contributes significantly to the binding of small molecules to proteins in biochemical systems. Molecular dynamics (MD) simulation based programs such as WaterMap and WATsite have been used to probe the locations and thermodynamic properties of hydration sites at the surface or in the binding site of proteins generating important information for structure-based drug design. However, questions associated with the influence of the simulation protocol on hydration site analysis remain. In this study, we use WATsite to investigate the influence of factors such as simulation length and variations in initial protein conformations on hydration site prediction. We find that 4 ns MD simulation is appropriate to obtain a reliable prediction of the locations and thermodynamic properties of hydration sites. In addition, hydration site prediction can be largely affected by the initial protein conformations used for MD simulations. Here, we provide a first quantification of this effect and further indicate that similar conformations of binding site residues (RMSD < 0.5 Å) are required to obtain consistent hydration site predictions. PMID:25252619

Integrating Unified Gravity Wave Physics into the NOAA Next Generation Global Prediction System

NASA Astrophysics Data System (ADS)

Alpert, J. C.; Yudin, V.; Fuller-Rowell, T. J.; Akmaev, R. A.

2017-12-01

The Unified Gravity Wave Physics (UGWP) project for the Next Generation Global Prediction System (NGGPS) is a NOAA collaborative effort between the National Centers for Environmental Prediction (NCEP), Environemntal Modeling Center (EMC) and the University of Colorado, Cooperative Institute for Research in Environmental Sciences (CU-CIRES) to support upgrades and improvements of GW dynamics (resolved scales) and physics (sub-grid scales) in the NOAA Environmental Modeling System (NEMS)†. As envisioned the global climate, weather and space weather models of NEMS will substantially improve their predictions and forecasts with the resolution-sensitive (scale-aware) formulations planned under the UGWP framework for both orographic and non-stationary waves. In particular, the planned improvements for the Global Forecast System (GFS) model of NEMS are: calibration of model physics for higher vertical and horizontal resolution and an extended vertical range of simulations, upgrades to GW schemes, including the turbulent heating and eddy mixing due to wave dissipation and breaking, and representation of the internally-generated QBO. The main priority of the UGWP project is unified parameterization of orographic and non-orographic GW effects including momentum deposition in the middle atmosphere and turbulent heating and eddies due to wave dissipation and breaking. The latter effects are not currently represented in NOAA atmosphere models. The team has tested and evaluated four candidate GW solvers integrating the selected GW schemes into the NGGPS model. Our current work and planned activity is to implement the UGWP schemes in the first available GFS/FV3 (open FV3) configuration including adapted GFDL modification for sub-grid orography in GFS. Initial global model results will be shown for the operational and research GFS configuration for spectral and FV3 dynamical cores. †http://www.emc.ncep.noaa.gov/index.php?branch=NEMS

Protein-protein structure prediction by scoring molecular dynamics trajectories of putative poses.

PubMed

Sarti, Edoardo; Gladich, Ivan; Zamuner, Stefano; Correia, Bruno E; Laio, Alessandro

2016-09-01

The prediction of protein-protein interactions and their structural configuration remains a largely unsolved problem. Most of the algorithms aimed at finding the native conformation of a protein complex starting from the structure of its monomers are based on searching the structure corresponding to the global minimum of a suitable scoring function. However, protein complexes are often highly flexible, with mobile side chains and transient contacts due to thermal fluctuations. Flexibility can be neglected if one aims at finding quickly the approximate structure of the native complex, but may play a role in structure refinement, and in discriminating solutions characterized by similar scores. We here benchmark the capability of some state-of-the-art scoring functions (BACH-SixthSense, PIE/PISA and Rosetta) in discriminating finite-temperature ensembles of structures corresponding to the native state and to non-native configurations. We produce the ensembles by running thousands of molecular dynamics simulations in explicit solvent starting from poses generated by rigid docking and optimized in vacuum. We find that while Rosetta outperformed the other two scoring functions in scoring the structures in vacuum, BACH-SixthSense and PIE/PISA perform better in distinguishing near-native ensembles of structures generated by molecular dynamics in explicit solvent. Proteins 2016; 84:1312-1320. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

ADEPT, a dynamic next generation sequencing data error-detection program with trimming

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

Feng, Shihai; Lo, Chien-Chi; Li, Po-E

Illumina is the most widely used next generation sequencing technology and produces millions of short reads that contain errors. These sequencing errors constitute a major problem in applications such as de novo genome assembly, metagenomics analysis and single nucleotide polymorphism discovery. In this study, we present ADEPT, a dynamic error detection method, based on the quality scores of each nucleotide and its neighboring nucleotides, together with their positions within the read and compares this to the position-specific quality score distribution of all bases within the sequencing run. This method greatly improves upon other available methods in terms of the truemore » positive rate of error discovery without affecting the false positive rate, particularly within the middle of reads. We conclude that ADEPT is the only tool to date that dynamically assesses errors within reads by comparing position-specific and neighboring base quality scores with the distribution of quality scores for the dataset being analyzed. The result is a method that is less prone to position-dependent under-prediction, which is one of the most prominent issues in error prediction. The outcome is that ADEPT improves upon prior efforts in identifying true errors, primarily within the middle of reads, while reducing the false positive rate.« less

ADEPT, a dynamic next generation sequencing data error-detection program with trimming

DOE PAGES

Feng, Shihai; Lo, Chien-Chi; Li, Po-E; ...

2016-02-29

Illumina is the most widely used next generation sequencing technology and produces millions of short reads that contain errors. These sequencing errors constitute a major problem in applications such as de novo genome assembly, metagenomics analysis and single nucleotide polymorphism discovery. In this study, we present ADEPT, a dynamic error detection method, based on the quality scores of each nucleotide and its neighboring nucleotides, together with their positions within the read and compares this to the position-specific quality score distribution of all bases within the sequencing run. This method greatly improves upon other available methods in terms of the truemore » positive rate of error discovery without affecting the false positive rate, particularly within the middle of reads. We conclude that ADEPT is the only tool to date that dynamically assesses errors within reads by comparing position-specific and neighboring base quality scores with the distribution of quality scores for the dataset being analyzed. The result is a method that is less prone to position-dependent under-prediction, which is one of the most prominent issues in error prediction. The outcome is that ADEPT improves upon prior efforts in identifying true errors, primarily within the middle of reads, while reducing the false positive rate.« less

Actin cable distribution and dynamics arising from cross-linking, motor pulling, and filament turnover

PubMed Central

Tang, Haosu; Laporte, Damien; Vavylonis, Dimitrios

2014-01-01

The growth of fission yeast relies on the polymerization of actin filaments nucleated by formin For3p, which localizes at tip cortical sites. These actin filaments bundle to form actin cables that span the cell and guide the movement of vesicles toward the cell tips. A big challenge is to develop a quantitative understanding of these cellular actin structures. We used computer simulations to study the spatial and dynamical properties of actin cables. We simulated individual actin filaments as semiflexible polymers in three dimensions composed of beads connected with springs. Polymerization out of For3p cortical sites, bundling by cross-linkers, pulling by type V myosin, and severing by cofilin are simulated as growth, cross-linking, pulling, and turnover of the semiflexible polymers. With the foregoing mechanisms, the model generates actin cable structures and dynamics similar to those observed in live-cell experiments. Our simulations reproduce the particular actin cable structures in myoVΔ cells and predict the effect of increased myosin V pulling. Increasing cross-linking parameters generates thicker actin cables. It also leads to antiparallel and parallel phases with straight or curved cables, consistent with observations of cells overexpressing α-actinin. Finally, the model predicts that clustering of formins at cell tips promotes actin cable formation. PMID:25103242

Dynamics of mode-coupling-induced microresonator frequency combs in normal dispersion

NASA Astrophysics Data System (ADS)

Jang, Jae K.; Okawachi, Yoshitomo; Yu, Mengjie; Luke, Kevin; Ji, Xingchen; Lipson, Michal; Gaeta, Alexander L.

2016-12-01

We experimentally and theoretically investigate the dynamics of microresonator-based frequency comb generation assisted by mode coupling in the normal group-velocity dispersion (GVD) regime. We show that mode coupling can initiate intracavity modulation instability (MI) by directly perturbing the pump-resonance mode. We also observe the formation of a low-noise comb as the pump frequency is tuned further into resonance from the MI point. We determine the phase-matching conditions that accurately predict all the essential features of the MI and comb spectra, and extend the existing analogy between mode coupling and high-order dispersion to the normal GVD regime. We discuss the applicability of our analysis to the possibility of broadband comb generation in the normal GVD regime.

The importance of including dynamic social networks when modeling epidemics of airborne infections: does increasing complexity increase accuracy?

PubMed

Blower, Sally; Go, Myong-Hyun

2011-07-19

Mathematical models are useful tools for understanding and predicting epidemics. A recent innovative modeling study by Stehle and colleagues addressed the issue of how complex models need to be to ensure accuracy. The authors collected data on face-to-face contacts during a two-day conference. They then constructed a series of dynamic social contact networks, each of which was used to model an epidemic generated by a fast-spreading airborne pathogen. Intriguingly, Stehle and colleagues found that increasing model complexity did not always increase accuracy. Specifically, the most detailed contact network and a simplified version of this network generated very similar results. These results are extremely interesting and require further exploration to determine their generalizability.

Picosecond acoustic phonon dynamics in LaF3:Pr3+

NASA Astrophysics Data System (ADS)

Kirkpatrick, Sean M.; Yang, Ho-Soon; Dennis, W. M.

1998-09-01

A plasma switching technique is used to generate subnanosecond, far-infrared (FIR) pulses with frequency 113 cm-1. The generation of subnanosecond FIR pulses enables us to improve the time resolution of phonon spectroscopic measurements from 50 ns to 350 ps. As an application of this technique, we investigate the subnanosecond dynamics of high-frequency phonons in 0.5% LaF3:Pr3+. In particular, we report on the generation and detection of a subnanosecond nonequilibrium phonon population at 113 cm-1, and the temporal evolution of the resulting decay products. The frequency dependence of the phonon relaxation rates of acoustic phonons in this material is found to deviate from the ω5 frequency dependence predicted by an isotropic model with linear dispersion. A more realistic model based on the actual dispersion curves of the material is presented and compared with the data.

System and methods for predicting transmembrane domains in membrane proteins and mining the genome for recognizing G-protein coupled receptors

DOEpatents

Trabanino, Rene J; Vaidehi, Nagarajan; Hall, Spencer E; Goddard, William A; Floriano, Wely

2013-02-05

The invention provides computer-implemented methods and apparatus implementing a hierarchical protocol using multiscale molecular dynamics and molecular modeling methods to predict the presence of transmembrane regions in proteins, such as G-Protein Coupled Receptors (GPCR), and protein structural models generated according to the protocol. The protocol features a coarse grain sampling method, such as hydrophobicity analysis, to provide a fast and accurate procedure for predicting transmembrane regions. Methods and apparatus of the invention are useful to screen protein or polynucleotide databases for encoded proteins with transmembrane regions, such as GPCRs.

Nonlinear Dynamic Modeling of Neuron Action Potential Threshold During Synaptically Driven Broadband Intracellular Activity

PubMed Central

Roach, Shane M.; Song, Dong; Berger, Theodore W.

2012-01-01

Activity-dependent variation of neuronal thresholds for action potential (AP) generation is one of the key determinants of spike-train temporal-pattern transformations from presynaptic to postsynaptic spike trains. In this study, we model the nonlinear dynamics of the threshold variation during synaptically driven broadband intracellular activity. First, membrane potentials of single CA1 pyramidal cells were recorded under physiologically plausible broadband stimulation conditions. Second, a method was developed to measure AP thresholds from the continuous recordings of membrane potentials. It involves measuring the turning points of APs by analyzing the third-order derivatives of the membrane potentials. Four stimulation paradigms with different temporal patterns were applied to validate this method by comparing the measured AP turning points and the actual AP thresholds estimated with varying stimulation intensities. Results show that the AP turning points provide consistent measurement of the AP thresholds, except for a constant offset. It indicates that 1) the variation of AP turning points represents the nonlinearities of threshold dynamics; and 2) an optimization of the constant offset is required to achieve accurate spike prediction. Third, a nonlinear dynamical third-order Volterra model was built to describe the relations between the threshold dynamics and the AP activities. Results show that the model can predict threshold accurately based on the preceding APs. Finally, the dynamic threshold model was integrated into a previously developed single neuron model and resulted in a 33% improvement in spike prediction. PMID:22156947

Numerical tools to predict the environmental loads for offshore structures under extreme weather conditions

NASA Astrophysics Data System (ADS)

Wu, Yanling

2018-05-01

In this paper, the extreme waves were generated using the open source computational fluid dynamic (CFD) tools — OpenFOAM and Waves2FOAM — using linear and nonlinear NewWave input. They were used to conduct the numerical simulation of the wave impact process. Numerical tools based on first-order (with and without stretching) and second-order NewWave are investigated. The simulation to predict force loading for the offshore platform under the extreme weather condition is implemented and compared.

Evaluation of the Interactionist Model of Socioeconomic Status and Problem Behavior: A Developmental Cascade across Generations

PubMed Central

Martin, Monica J.; Conger, Rand D.; Schofield, Thomas J.; Dogan, Shannon J.; Widaman, Keith F.; Donnellan, M. Brent; Neppl, Tricia K.

2010-01-01

The current multigenerational study evaluates the utility of the Interactionist Model of Socioeconomic Influence on human development (IMSI) in explaining problem behaviors across generations. The IMSI proposes that the association between socioeconomic status (SES) and human development involves a dynamic interplay that includes both social causation (SES influences human development) and social selection (individual characteristics affect SES). As part of the developmental cascade proposed by the IMSI, the findings from this investigation showed that G1 adolescent problem behavior predicted later G1 SES, family stress, and parental emotional investments, as well as the next generation of children's problem behavior. These results are consistent with a social selection view. Consistent with the social causation perspective, we found a significant relation between G1 SES and family stress, and in turn, family stress predicted G2 problem behavior. Finally, G1 adult SES predicted both material and emotional investments in the G2 child. In turn, emotional investments predicted G2 problem behavior, as did material investments. Some of the predicted pathways varied by G1 parent gender. The results are consistent with the view that processes of both social selection and social causation account for the association between SES and human development. PMID:20576188

Emergency Department Visit Forecasting and Dynamic Nursing Staff Allocation Using Machine Learning Techniques With Readily Available Open-Source Software.

PubMed

Zlotnik, Alexander; Gallardo-Antolín, Ascensión; Cuchí Alfaro, Miguel; Pérez Pérez, María Carmen; Montero Martínez, Juan Manuel

2015-08-01

Although emergency department visit forecasting can be of use for nurse staff planning, previous research has focused on models that lacked sufficient resolution and realistic error metrics for these predictions to be applied in practice. Using data from a 1100-bed specialized care hospital with 553,000 patients assigned to its healthcare area, forecasts with different prediction horizons, from 2 to 24 weeks ahead, with an 8-hour granularity, using support vector regression, M5P, and stratified average time-series models were generated with an open-source software package. As overstaffing and understaffing errors have different implications, error metrics and potential personnel monetary savings were calculated with a custom validation scheme, which simulated subsequent generation of predictions during a 4-year period. Results were then compared with a generalized estimating equation regression. Support vector regression and M5P models were found to be superior to the stratified average model with a 95% confidence interval. Our findings suggest that medium and severe understaffing situations could be reduced in more than an order of magnitude and average yearly savings of up to €683,500 could be achieved if dynamic nursing staff allocation was performed with support vector regression instead of the static staffing levels currently in use.

Dynamics of short pulses and phase matched second harmonic generation in negative index materials.

PubMed

Scalora, Michael; D'Aguanno, Giuseppe; Bloemer, Mark; Centini, Marco; de Ceglia, Domenico; Mattiucci, Nadia; Kivshar, Yuri S

2006-05-29

We study pulsed second harmonic generation in metamaterials under conditions of significant absorption. Tuning the pump in the negative index range, a second harmonic signal is generated in the positive index region, such that the respective indices of refraction have the same magnitudes but opposite signs. This insures that a forward-propagating pump is exactly phase matched to the backward-propagating second harmonic signal. Using peak intensities of ~500 MW/cm(2), assuming chi((2))~80pm/V, we predict conversion efficiencies of 12% and 0.2% for attenuation lengths of 50 and 5microm, respectively.

An implementation of an aeroacoustic prediction model for broadband noise from a vertical axis wind turbine using a CFD informed methodology

NASA Astrophysics Data System (ADS)

Botha, J. D. M.; Shahroki, A.; Rice, H.

2017-12-01

This paper presents an enhanced method for predicting aerodynamically generated broadband noise produced by a Vertical Axis Wind Turbine (VAWT). The method improves on existing work for VAWT noise prediction and incorporates recently developed airfoil noise prediction models. Inflow-turbulence and airfoil self-noise mechanisms are both considered. Airfoil noise predictions are dependent on aerodynamic input data and time dependent Computational Fluid Dynamics (CFD) calculations are carried out to solve for the aerodynamic solution. Analytical flow methods are also benchmarked against the CFD informed noise prediction results to quantify errors in the former approach. Comparisons to experimental noise measurements for an existing turbine are encouraging. A parameter study is performed and shows the sensitivity of overall noise levels to changes in inflow velocity and inflow turbulence. Noise sources are characterised and the location and mechanism of the primary sources is determined, inflow-turbulence noise is seen to be the dominant source. The use of CFD calculations is seen to improve the accuracy of noise predictions when compared to the analytic flow solution as well as showing that, for inflow-turbulence noise sources, blade generated turbulence dominates the atmospheric inflow turbulence.

Computational approach on PEB process in EUV resist: multi-scale simulation

NASA Astrophysics Data System (ADS)

Kim, Muyoung; Moon, Junghwan; Choi, Joonmyung; Lee, Byunghoon; Jeong, Changyoung; Kim, Heebom; Cho, Maenghyo

2017-03-01

For decades, downsizing has been a key issue for high performance and low cost of semiconductor, and extreme ultraviolet lithography is one of the promising candidates to achieve the goal. As a predominant process in extreme ultraviolet lithography on determining resolution and sensitivity, post exposure bake has been mainly studied by experimental groups, but development of its photoresist is at the breaking point because of the lack of unveiled mechanism during the process. Herein, we provide theoretical approach to investigate underlying mechanism on the post exposure bake process in chemically amplified resist, and it covers three important reactions during the process: acid generation by photo-acid generator dissociation, acid diffusion, and deprotection. Density functional theory calculation (quantum mechanical simulation) was conducted to quantitatively predict activation energy and probability of the chemical reactions, and they were applied to molecular dynamics simulation for constructing reliable computational model. Then, overall chemical reactions were simulated in the molecular dynamics unit cell, and final configuration of the photoresist was used to predict the line edge roughness. The presented multiscale model unifies the phenomena of both quantum and atomic scales during the post exposure bake process, and it will be helpful to understand critical factors affecting the performance of the resulting photoresist and design the next-generation material.

Horizontal visibility graphs generated by type-I intermittency

NASA Astrophysics Data System (ADS)

Núñez, Ángel M.; Luque, Bartolo; Lacasa, Lucas; Gómez, Jose Patricio; Robledo, Alberto

2013-05-01

The type-I intermittency route to (or out of) chaos is investigated within the horizontal visibility (HV) graph theory. For that purpose, we address the trajectories generated by unimodal maps close to an inverse tangent bifurcation and construct their associated HV graphs. We show how the alternation of laminar episodes and chaotic bursts imprints a fingerprint in the resulting graph structure. Accordingly, we derive a phenomenological theory that predicts quantitative values for several network parameters. In particular, we predict that the characteristic power-law scaling of the mean length of laminar trend sizes is fully inherited by the variance of the graph degree distribution, in good agreement with the numerics. We also report numerical evidence on how the characteristic power-law scaling of the Lyapunov exponent as a function of the distance to the tangent bifurcation is inherited in the graph by an analogous scaling of block entropy functionals defined on the graph. Furthermore, we are able to recast the full set of HV graphs generated by intermittent dynamics into a renormalization-group framework, where the fixed points of its graph-theoretical renormalization-group flow account for the different types of dynamics. We also establish that the nontrivial fixed point of this flow coincides with the tangency condition and that the corresponding invariant graph exhibits extremal entropic properties.

SmaggIce User Guide. 1.0

NASA Technical Reports Server (NTRS)

Baez, Marivell; Vickerman, Mary; Choo, Yung

2000-01-01

SmaggIce (Surface Modeling And Grid Generation for Iced Airfoils) is one of NASNs aircraft icing research codes developed at the Glenn Research Center. It is a software toolkit used in the process of aerodynamic performance prediction of iced airfoils. It includes tools which complement the 2D grid-based Computational Fluid Dynamics (CFD) process: geometry probing; surface preparation for gridding: smoothing and re-discretization of geometry. Future releases will also include support for all aspects of gridding: domain decomposition; perimeter discretization; grid generation and modification.

Population dynamics of Varroa destructor (Acari: Varroidae) in commercial honey bee colonies and implications for control

USDA-ARS?s Scientific Manuscript database

Treatment schedules to maintain low levels of Varroa mites in honey bee colonies were tested in hives started from either package bees or splits of larger colonies. The schedules were developed based on predictions of Varroa population growth generated from a mathematical model of honey bee colony ...

Developing predictive approaches to characterize adaptive responses of the reproductive endocrine axis to aromatase inhibition: I. Data generation in a small fish model

EPA Science Inventory

Adaptive or compensatory responses to chemical exposure can significantly influence in vivo concentration-duration-response relationships. The aim of this study was to provide data to support development of a computational dynamic model of the hypothalamic-pituitary-gonadal axis ...

RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis.

PubMed

Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

2012-01-01

RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. http://www.cemb.edu.pk/sw.html RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language.

Modal Survey of ETM-3, A 5-Segment Derivative of the Space Shuttle Solid Rocket Booster

NASA Technical Reports Server (NTRS)

Nielsen, D.; Townsend, J.; Kappus, K.; Driskill, T.; Torres, I.; Parks, R.

2005-01-01

The complex interactions between internal motor generated pressure oscillations and motor structural vibration modes associated with the static test configuration of a Reusable Solid Rocket Motor have potential to generate significant dynamic thrust loads in the 5-segment configuration (Engineering Test Motor 3). Finite element model load predictions for worst-case conditions were generated based on extrapolation of a previously correlated 4-segment motor model. A modal survey was performed on the largest rocket motor to date, Engineering Test Motor #3 (ETM-3), to provide data for finite element model correlation and validation of model generated design loads. The modal survey preparation included pretest analyses to determine an efficient analysis set selection using the Effective Independence Method and test simulations to assure critical test stand component loads did not exceed design limits. Historical Reusable Solid Rocket Motor modal testing, ETM-3 test analysis model development and pre-test loads analyses, as well as test execution, and a comparison of results to pre-test predictions are discussed.

Acquisition of Inertia by a Moving Crack

NASA Astrophysics Data System (ADS)

Goldman, Tamar; Livne, Ariel; Fineberg, Jay

2010-03-01

We experimentally investigate the dynamics of “simple” tensile cracks. Within an effectively infinite medium, a crack’s dynamics perfectly correspond to inertialess behavior predicted by linear elastic fracture mechanics. Once a crack interacts with waves that it generated at earlier times, this description breaks down. Cracks then acquire inertia and sluggishly accelerate. Crack inertia increases with crack speed v and diverges as v approaches its limiting value. We show that these dynamics are in excellent accord with an equation of motion derived in the limit of an infinite strip [M. Marder, Phys. Rev. Lett. 66, 2484 (1991)PRLTAO0031-900710.1103/PhysRevLett.66.2484].

Real-Time Observation of Internal Motion within Ultrafast Dissipative Optical Soliton Molecules

NASA Astrophysics Data System (ADS)

Krupa, Katarzyna; Nithyanandan, K.; Andral, Ugo; Tchofo-Dinda, Patrice; Grelu, Philippe

2017-06-01

Real-time access to the internal ultrafast dynamics of complex dissipative optical systems opens new explorations of pulse-pulse interactions and dynamic patterns. We present the first direct experimental evidence of the internal motion of a dissipative optical soliton molecule generated in a passively mode-locked erbium-doped fiber laser. We map the internal motion of a soliton pair molecule by using a dispersive Fourier-transform imaging technique, revealing different categories of internal pulsations, including vibrationlike and phase drifting dynamics. Our experiments agree well with numerical predictions and bring insights to the analogy between self-organized states of lights and states of the matter.

Computational hydrodynamic comparison of a mini vessel and a USP 2 dissolution testing system to predict the dynamic operating conditions for similarity of dissolution performance.

PubMed

Wang, Bing; Bredael, Gerard; Armenante, Piero M

2018-03-25

The hydrodynamic characteristics of a mini vessel and a USP 2 dissolution testing system were obtained and compared to predict the tablet-liquid mass transfer coefficient from velocity distributions near the tablet and establish the dynamic operating conditions under which dissolution in mini vessels could be conducted to generate concentration profiles similar to those in the USP 2. Velocity profiles were obtained experimentally using Particle Image Velocimetry (PIV). Computational Fluid Dynamics (CFD) was used to predict the velocity distribution and strain rate around a model tablet. A CFD-based mass transfer model was also developed. When plotted against strain rate, the predicted tablet-liquid mass transfer coefficient was found to be independent of the system where it was obtained, implying that a tablet would dissolve at the same rate in both systems provided that the concentration gradient between the tablet surface and the bulk is the same, the tablet surface area per unit liquid volume is identical, and the two systems are operated at the appropriate agitation speeds specified in this work. The results of this work will help dissolution scientists operate mini vessels so as to predict the dissolution profiles in the USP 2, especially during the early stages of drug development. Copyright © 2018 Elsevier B.V. All rights reserved.

Evolution of proliferation and the angiogenic switch in tumors with high clonal diversity.

PubMed

Bickel, Scott T; Juliano, Joseph D; Nagy, John D

2014-01-01

Natural selection among tumor cell clones is thought to produce hallmark properties of malignancy. Efforts to understand evolution of one such hallmark--the angiogenic switch--has suggested that selection for angiogenesis can "run away" and generate a hypertumor, a form of evolutionary suicide by extreme vascular hypo- or hyperplasia. This phenomenon is predicted by models of tumor angiogenesis studied with the techniques of adaptive dynamics. These techniques also predict that selection drives tumor proliferative potential towards an evolutionarily stable strategy (ESS) that is also convergence-stable. However, adaptive dynamics are predicated on two key assumptions: (i) no more than two distinct clones or evolutionary strategies can exist in the tumor at any given time; and (ii) mutations cause small phenotypic changes. Here we show, using a stochastic simulation, that relaxation of these assumptions has no effect on the predictions of adaptive dynamics in this case. In particular, selection drives proliferative potential towards, and angiogenic potential away from, their respective ESSs. However, these simulations also show that tumor behavior is highly contingent on mutational history, particularly for angiogenesis. Individual tumors frequently grow to lethal size before the evolutionary endpoint is approached. In fact, most tumor dynamics are predicted to be in the evolutionarily transient regime throughout their natural history, so that clinically, the ESS is often largely irrelevant. In addition, we show that clonal diversity as measured by the Shannon Information Index correlates with the speed of approach to the evolutionary endpoint. This observation dovetails with results showing that clonal diversity in Barrett's esophagus predicts progression to malignancy.

Projecting pest population dynamics under global warming: the combined effect of inter- and intra-annual variations.

PubMed

Zidon, Royi; Tsueda, Hirotsugu; Morin, Efrat; Morin, Shai

2016-06-01

The typical short generation length of insects makes their population dynamics highly sensitive not only to mean annual temperatures but also to their intra-annual variations. To consider the combined effect of both thermal factors under global warming, we propose a modeling framework that links general circulation models (GCMs) with a stochastic weather generator and population dynamics models to predict species population responses to inter- and intra-annual temperature changes. This framework was utilized to explore future changes in populations of Bemisia tabaci, an invasive insect pest-species that affects multiple agricultural systems in the Mediterranean region. We considered three locations representing different pest status and climatic conditions: Montpellier (France), Seville (Spain), and Beit-Jamal (Israel). We produced ensembles of local daily temperature realizations representing current and future (mid-21st century) climatic conditions under two emission scenarios for the three locations. Our simulations predicted a significant increase in the average number of annual generations and in population size, and a significant lengthening of the growing season in all three locations. A negative effect was found only in Seville for the summer season, where future temperatures lead to a reduction in population size. High variability in population size was observed between years with similar annual mean temperatures, suggesting a strong effect of intra-annual temperature variation. Critical periods were from late spring to late summer in Montpellier and from late winter to early summer in Seville and Beit-Jamal. Although our analysis suggested that earlier seasonal activity does not necessarily lead to increased populations load unless an additional generation is produced, it is highly likely that the insect will become a significant pest of open-fields at Mediterranean latitudes above 40° during the next 50 years. Our simulations also implied that current predictions based on mean temperature anomalies are relatively conservative and it is better to apply stochastic tools to resolve complex responses to climate change while taking natural variability into account. In summary, we propose a modeling framework capable of determining distinct intra-annual temperature patterns leading to large or small population sizes, for pest risk assessment and management planning of both natural and agricultural ecosystems.

Sonic boom predictions using a modified Euler code

NASA Technical Reports Server (NTRS)

Siclari, Michael J.

1992-01-01

The environmental impact of a next generation fleet of high-speed civil transports (HSCT) is of great concern in the evaluation of the commercial development of such a transport. One of the potential environmental impacts of a high speed civilian transport is the sonic boom generated by the aircraft and its effects on the population, wildlife, and structures in the vicinity of its flight path. If an HSCT aircraft is restricted from flying overland routes due to excessive booms, the commercial feasibility of such a venture may be questionable. NASA has taken the lead in evaluating and resolving the issues surrounding the development of a high speed civilian transport through its High-Speed Research Program (HSRP). The present paper discusses the usage of a Computational Fluid Dynamics (CFD) nonlinear code in predicting the pressure signature and ultimately the sonic boom generated by a high speed civilian transport. NASA had designed, built, and wind tunnel tested two low boom configurations for flight at Mach 2 and Mach 3. Experimental data was taken at several distances from these models up to a body length from the axis of the aircraft. The near field experimental data serves as a test bed for computational fluid dynamic codes in evaluating their accuracy and reliability for predicting the behavior of future HSCT designs. Sonic boom prediction methodology exists which is based on modified linear theory. These methods can be used reliably if near field signatures are available at distances from the aircraft where nonlinear and three dimensional effects have diminished in importance. Up to the present time, the only reliable method to obtain this data was via the wind tunnel with costly model construction and testing. It is the intent of the present paper to apply a modified three dimensional Euler code to predict the near field signatures of the two low boom configurations recently tested by NASA.

Discovering novel phenotypes with automatically inferred dynamic models: a partial melanocyte conversion in Xenopus

NASA Astrophysics Data System (ADS)

Lobo, Daniel; Lobikin, Maria; Levin, Michael

2017-01-01

Progress in regenerative medicine requires reverse-engineering cellular control networks to infer perturbations with desired systems-level outcomes. Such dynamic models allow phenotypic predictions for novel perturbations to be rapidly assessed in silico. Here, we analyzed a Xenopus model of conversion of melanocytes to a metastatic-like phenotype only previously observed in an all-or-none manner. Prior in vivo genetic and pharmacological experiments showed that individual animals either fully convert or remain normal, at some characteristic frequency after a given perturbation. We developed a Machine Learning method which inferred a model explaining this complex, stochastic all-or-none dataset. We then used this model to ask how a new phenotype could be generated: animals in which only some of the melanocytes converted. Systematically performing in silico perturbations, the model predicted that a combination of altanserin (5HTR2 inhibitor), reserpine (VMAT inhibitor), and VP16-XlCreb1 (constitutively active CREB) would break the all-or-none concordance. Remarkably, applying the predicted combination of three reagents in vivo revealed precisely the expected novel outcome, resulting in partial conversion of melanocytes within individuals. This work demonstrates the capability of automated analysis of dynamic models of signaling networks to discover novel phenotypes and predictively identify specific manipulations that can reach them.

Internal exposure dynamics drive the Adverse Outcome Pathways of synthetic glucocorticoids in fish

NASA Astrophysics Data System (ADS)

Margiotta-Casaluci, Luigi; Owen, Stewart F.; Huerta, Belinda; Rodríguez-Mozaz, Sara; Kugathas, Subramanian; Barceló, Damià; Rand-Weaver, Mariann; Sumpter, John P.

2016-02-01

The Adverse Outcome Pathway (AOP) framework represents a valuable conceptual tool to systematically integrate existing toxicological knowledge from a mechanistic perspective to facilitate predictions of chemical-induced effects across species. However, its application for decision-making requires the transition from qualitative to quantitative AOP (qAOP). Here we used a fish model and the synthetic glucocorticoid beclomethasone dipropionate (BDP) to investigate the role of chemical-specific properties, pharmacokinetics, and internal exposure dynamics in the development of qAOPs. We generated a qAOP network based on drug plasma concentrations and focused on immunodepression, skin androgenisation, disruption of gluconeogenesis and reproductive performance. We showed that internal exposure dynamics and chemical-specific properties influence the development of qAOPs and their predictive power. Comparing the effects of two different glucocorticoids, we highlight how relatively similar in vitro hazard-based indicators can lead to different in vivo risk. This discrepancy can be predicted by their different uptake potential, pharmacokinetic (PK) and pharmacodynamic (PD) profiles. We recommend that the development phase of qAOPs should include the application of species-species uptake and physiologically-based PK/PD models. This integration will significantly enhance the predictive power, enabling a more accurate assessment of the risk and the reliable transferability of qAOPs across chemicals.

Population Dynamics and Flight Phenology Model of Codling Moth Differ between Commercial and Abandoned Apple Orchard Ecosystems.

PubMed

Joshi, Neelendra K; Rajotte, Edwin G; Naithani, Kusum J; Krawczyk, Greg; Hull, Larry A

2016-01-01

Apple orchard management practices may affect development and phenology of arthropod pests, such as the codling moth (CM), Cydia pomonella (L.) (Lepidoptera: Tortricidae), which is a serious internal fruit-feeding pest of apples worldwide. Estimating population dynamics and accurately predicting the timing of CM development and phenology events (for instance, adult flight, and egg-hatch) allows growers to understand and control local populations of CM. Studies were conducted to compare the CM flight phenology in commercial and abandoned apple orchard ecosystems using a logistic function model based on degree-days accumulation. The flight models for these orchards were derived from the cumulative percent moth capture using two types of commercially available CM lure baited traps. Models from both types of orchards were also compared to another model known as PETE (prediction extension timing estimator) that was developed in 1970s to predict life cycle events for many fruit pests including CM across different fruit growing regions of the United States. We found that the flight phenology of CM was significantly different in commercial and abandoned orchards. CM male flight patterns for first and second generations as predicted by the constrained and unconstrained PCM (Pennsylvania Codling Moth) models in commercial and abandoned orchards were different than the flight patterns predicted by the currently used CM model (i.e., PETE model). In commercial orchards, during the first and second generations, the PCM unconstrained model predicted delays in moth emergence compared to current model. In addition, the flight patterns of females were different between commercial and abandoned orchards. Such differences in CM flight phenology between commercial and abandoned orchard ecosystems suggest potential impact of orchard environment and crop management practices on CM biology.

Population Dynamics and Flight Phenology Model of Codling Moth Differ between Commercial and Abandoned Apple Orchard Ecosystems

PubMed Central

Joshi, Neelendra K.; Rajotte, Edwin G.; Naithani, Kusum J.; Krawczyk, Greg; Hull, Larry A.

2016-01-01

Apple orchard management practices may affect development and phenology of arthropod pests, such as the codling moth (CM), Cydia pomonella (L.) (Lepidoptera: Tortricidae), which is a serious internal fruit-feeding pest of apples worldwide. Estimating population dynamics and accurately predicting the timing of CM development and phenology events (for instance, adult flight, and egg-hatch) allows growers to understand and control local populations of CM. Studies were conducted to compare the CM flight phenology in commercial and abandoned apple orchard ecosystems using a logistic function model based on degree-days accumulation. The flight models for these orchards were derived from the cumulative percent moth capture using two types of commercially available CM lure baited traps. Models from both types of orchards were also compared to another model known as PETE (prediction extension timing estimator) that was developed in 1970s to predict life cycle events for many fruit pests including CM across different fruit growing regions of the United States. We found that the flight phenology of CM was significantly different in commercial and abandoned orchards. CM male flight patterns for first and second generations as predicted by the constrained and unconstrained PCM (Pennsylvania Codling Moth) models in commercial and abandoned orchards were different than the flight patterns predicted by the currently used CM model (i.e., PETE model). In commercial orchards, during the first and second generations, the PCM unconstrained model predicted delays in moth emergence compared to current model. In addition, the flight patterns of females were different between commercial and abandoned orchards. Such differences in CM flight phenology between commercial and abandoned orchard ecosystems suggest potential impact of orchard environment and crop management practices on CM biology. PMID:27713702

Towards pattern generation and chaotic series prediction with photonic reservoir computers

NASA Astrophysics Data System (ADS)

Antonik, Piotr; Hermans, Michiel; Duport, François; Haelterman, Marc; Massar, Serge

2016-03-01

Reservoir Computing is a bio-inspired computing paradigm for processing time dependent signals that is particularly well suited for analog implementations. Our team has demonstrated several photonic reservoir computers with performance comparable to digital algorithms on a series of benchmark tasks such as channel equalisation and speech recognition. Recently, we showed that our opto-electronic reservoir computer could be trained online with a simple gradient descent algorithm programmed on an FPGA chip. This setup makes it in principle possible to feed the output signal back into the reservoir, and thus highly enrich the dynamics of the system. This will allow to tackle complex prediction tasks in hardware, such as pattern generation and chaotic and financial series prediction, which have so far only been studied in digital implementations. Here we report simulation results of our opto-electronic setup with an FPGA chip and output feedback applied to pattern generation and Mackey-Glass chaotic series prediction. The simulations take into account the major aspects of our experimental setup. We find that pattern generation can be easily implemented on the current setup with very good results. The Mackey-Glass series prediction task is more complex and requires a large reservoir and more elaborate training algorithm. With these adjustments promising result are obtained, and we now know what improvements are needed to match previously reported numerical results. These simulation results will serve as basis of comparison for experiments we will carry out in the coming months.

Fixing the fixed-point system—Applying Dynamic Renormalization Group to systems with long-range interactions

NASA Astrophysics Data System (ADS)

Katzav, Eytan

2013-04-01

In this paper, a mode of using the Dynamic Renormalization Group (DRG) method is suggested in order to cope with inconsistent results obtained when applying it to a continuous family of one-dimensional nonlocal models. The key observation is that the correct fixed-point dynamical system has to be identified during the analysis in order to account for all the relevant terms that are generated under renormalization. This is well established for static problems, however poorly implemented in dynamical ones. An application of this approach to a nonlocal extension of the Kardar-Parisi-Zhang equation resolves certain problems in one-dimension. Namely, obviously problematic predictions are eliminated and the existing exact analytic results are recovered.

Chronic contamination decreases disease spread: a Daphnia–fungus–copper case study

PubMed Central

Civitello, David J.; Forys, Philip; Johnson, Adam P.; Hall, Spencer R.

2012-01-01

Chemical contamination and disease outbreaks have increased in many ecosystems. However, connecting pollution to disease spread remains difficult, in part, because contaminants can simultaneously exert direct and multi-generational effects on several host and parasite traits. To address these challenges, we parametrized a model using a zooplankton–fungus–copper system. In individual-level assays, we considered three sublethal contamination scenarios: no contamination, single-generation contamination (hosts and parasites exposed only during the assays) and multi-generational contamination (hosts and parasites exposed for several generations prior to and during the assays). Contamination boosted transmission by increasing contact of hosts with parasites. However, it diminished parasite reproduction by reducing the size and lifespan of infected hosts. Multi-generational contamination further reduced parasite reproduction. The parametrized model predicted that a single generation of contamination would enhance disease spread (via enhanced transmission), whereas multi-generational contamination would inhibit epidemics relative to unpolluted conditions (through greatly depressed parasite reproduction). In a population-level experiment, multi-generational contamination reduced the size of experimental epidemics but did not affect Daphnia populations without disease. This result highlights the importance of multi-generational effects for disease dynamics. Such integration of models with experiments can provide predictive power for disease problems in contaminated environments. PMID:22593104

Identification of human-generated forces on wheelchairs during total-body extensor thrusts.

PubMed

Hong, Seong-Wook; Patrangenaru, Vlad; Singhose, William; Sprigle, Stephen

2006-10-01

Involuntary extensor thrust experienced by wheelchair users with neurological disorders may cause injuries via impact with the wheelchair, lead to the occupant sliding out of the seat, and also damage the wheelchair. The concept of a dynamic seat, which allows movement of a seat with respect to the wheelchair frame, has been suggested as a potential solution to provide greater freedom and safety. Knowledge of the human-generated motion and forces during unconstrained extensor thrust events is of great importance in developing more comfortable and effective dynamic seats. The objective of this study was to develop a method to identify human-generated motions and forces during extensor thrust events. This information can be used to design the triggering system for a dynamic seat. An experimental system was developed to automatically track the motions of the wheelchair user using a video camera and also measure the forces at the footrest. An inverse dynamic approach was employed along with a three-link human body model and the experimental data to predict the human-generated forces. Two kinds of experiments were performed: the first experiment validated the proposed model and the second experiment showed the effects of the extensor thrust speed, the footrest angle, and the seatback angle. The proposed method was tested using a sensitivity analysis, from which a performance index was deduced to help indicate the robust region of the force identification. A system to determine human-generated motions and forces during unconstrained extensor thrusts was developed. Through experiments and simulations, the effectiveness and reliability of the developed system was established.

Temperature-driven regime shifts in the dynamics of size-structured populations.

PubMed

Ohlberger, Jan; Edeline, Eric; Vøllestad, Leif Asbjørn; Stenseth, Nils C; Claessen, David

2011-02-01

Global warming impacts virtually all biota and ecosystems. Many of these impacts are mediated through direct effects of temperature on individual vital rates. Yet how this translates from the individual to the population level is still poorly understood, hampering the assessment of global warming impacts on population structure and dynamics. Here, we study the effects of temperature on intraspecific competition and cannibalism and the population dynamical consequences in a size-structured fish population. We use a physiologically structured consumer-resource model in which we explicitly model the temperature dependencies of the consumer vital rates and the resource population growth rate. Our model predicts that increased temperature decreases resource density despite higher resource growth rates, reflecting stronger intraspecific competition among consumers. At a critical temperature, the consumer population dynamics destabilize and shift from a stable equilibrium to competition-driven generation cycles that are dominated by recruits. As a consequence, maximum age decreases and the proportion of younger and smaller-sized fish increases. These model predictions support the hypothesis of decreasing mean body sizes due to increased temperatures. We conclude that in size-structured fish populations, global warming may increase competition, favor smaller size classes, and induce regime shifts that destabilize population and community dynamics.

Dynamic self-cleaning in gecko setae via digital hyperextension

PubMed Central

Hu, Shihao; Lopez, Stephanie; Niewiarowski, Peter H.; Xia, Zhenhai

2012-01-01

Gecko toe pads show strong adhesion on various surfaces yet remain remarkably clean around everyday contaminants. An understanding of how geckos clean their toe pads while being in motion is essential for the elucidation of animal behaviours as well as the design of biomimetic devices with optimal performance. Here, we test the self-cleaning of geckos during locomotion. We provide, to our knowledge, the first evidence that geckos clean their feet through a unique dynamic self-cleaning mechanism via digital hyperextension. When walking naturally with hyperextension, geckos shed dirt from their toes twice as fast as they would if walking without hyperextension, returning their feet to nearly 80 per cent of their original stickiness in only four steps. Our dynamic model predicts that when setae suddenly release from the attached substrate, they generate enough inertial force to dislodge dirt particles from the attached spatulae. The predicted cleaning force on dirt particles significantly increases when the dynamic effect is included. The extraordinary design of gecko toe pads perfectly combines dynamic self-cleaning with repeated attachment/detachment, making gecko feet sticky yet clean. This work thus provides a new mechanism to be considered for biomimetic design of highly reuseable and reliable dry adhesives and devices. PMID:22696482

Asymptotic theory of time-varying social networks with heterogeneous activity and tie allocation.

PubMed

Ubaldi, Enrico; Perra, Nicola; Karsai, Márton; Vezzani, Alessandro; Burioni, Raffaella; Vespignani, Alessandro

2016-10-24

The dynamic of social networks is driven by the interplay between diverse mechanisms that still challenge our theoretical and modelling efforts. Amongst them, two are known to play a central role in shaping the networks evolution, namely the heterogeneous propensity of individuals to i) be socially active and ii) establish a new social relationships with their alters. Here, we empirically characterise these two mechanisms in seven real networks describing temporal human interactions in three different settings: scientific collaborations, Twitter mentions, and mobile phone calls. We find that the individuals' social activity and their strategy in choosing ties where to allocate their social interactions can be quantitatively described and encoded in a simple stochastic network modelling framework. The Master Equation of the model can be solved in the asymptotic limit. The analytical solutions provide an explicit description of both the system dynamic and the dynamical scaling laws characterising crucial aspects about the evolution of the networks. The analytical predictions match with accuracy the empirical observations, thus validating the theoretical approach. Our results provide a rigorous dynamical system framework that can be extended to include other processes shaping social dynamics and to generate data driven predictions for the asymptotic behaviour of social networks.

Asymptotic theory of time-varying social networks with heterogeneous activity and tie allocation

NASA Astrophysics Data System (ADS)

Ubaldi, Enrico; Perra, Nicola; Karsai, Márton; Vezzani, Alessandro; Burioni, Raffaella; Vespignani, Alessandro

2016-10-01

The dynamic of social networks is driven by the interplay between diverse mechanisms that still challenge our theoretical and modelling efforts. Amongst them, two are known to play a central role in shaping the networks evolution, namely the heterogeneous propensity of individuals to i) be socially active and ii) establish a new social relationships with their alters. Here, we empirically characterise these two mechanisms in seven real networks describing temporal human interactions in three different settings: scientific collaborations, Twitter mentions, and mobile phone calls. We find that the individuals’ social activity and their strategy in choosing ties where to allocate their social interactions can be quantitatively described and encoded in a simple stochastic network modelling framework. The Master Equation of the model can be solved in the asymptotic limit. The analytical solutions provide an explicit description of both the system dynamic and the dynamical scaling laws characterising crucial aspects about the evolution of the networks. The analytical predictions match with accuracy the empirical observations, thus validating the theoretical approach. Our results provide a rigorous dynamical system framework that can be extended to include other processes shaping social dynamics and to generate data driven predictions for the asymptotic behaviour of social networks.

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.

Numerical investigation of unsteady cavitation around a NACA 66 hydrofoil using OpenFOAM

NASA Astrophysics Data System (ADS)

Hidalgo, V. H.; Luo, X. W.; Escaler, X.; Ji, J.; Aguinaga, A.

2014-03-01

The prediction and control of cavitation damage in pumps, propellers, hydro turbines and fluid machinery in general is necessary during the design stage. The present paper deals with a numerical investigation of unsteady cloud cavitation around a NACA 66 hydrofoil. The current study is focused on understanding the dynamic pressures generated during the cavity collapses as a fundamental characteristic in cavitation erosion. A 2D and 3D unsteady flow simulation has been carried out using OpenFOAM. Then, Paraview and Python programming language have been used to characterize dynamic pressure field. Adapted Large Eddy Simulation (LES) and Zwart cavitation model have been implemented to improve the analysis of cloud motion and to visualize the bubble expansions. Additional results also confirm the correlation between cavity formation and generated pressures.

Development of hierarchical structures for actions and motor imagery: a constructivist view from synthetic neuro-robotics study.

PubMed

Nishimoto, Ryunosuke; Tani, Jun

2009-07-01

The current paper shows a neuro-robotics experiment on developmental learning of goal-directed actions. The robot was trained to predict visuo-proprioceptive flow of achieving a set of goal-directed behaviors through iterative tutor training processes. The learning was conducted by employing a dynamic neural network model which is characterized by their multiple time-scale dynamics. The experimental results showed that functional hierarchical structures emerge through stages of developments where behavior primitives are generated in earlier stages and their sequences of achieving goals appear in later stages. It was also observed that motor imagery is generated in earlier stages compared to actual behaviors. Our claim that manipulatable inner representation should emerge through the sensory-motor interactions is corresponded to Piaget's constructivist view.

Short and long term investor synchronization caused by decoupling.

PubMed

Roszczynska-Kurasinska, Magda; Nowak, Andrzej; Kamieniarz, Daniel; Solomon, Sorin; Andersen, Jørgen Vitting

2012-01-01

The dynamics of collective decision making is not yet well understood. Its practical relevance however can be of utmost importance, as experienced by people who lost their fortunes in turbulent moments of financial markets. In this paper we show how spontaneous collective "moods" or "biases" emerge dynamically among human participants playing a trading game in a simple model of the stock market. Applying theory and computer simulations to the experimental data generated by humans, we are able to predict the onset of such moments before they actually happen.

Accurate Dynamic Response Predictions of Plug-and-Play Sat I

DTIC Science & Technology

2010-03-01

damping. The foam pads are necessary to damp out the s ystem b etween s trikes f rom t he s haker . Elevating t he f oam p ads p rovides i ncreased... haker set to a ct as an au tomatic p ing h ammer ( Figure 15) provides impulse like excitiations. A Hewlett Packard 33120A 15MHz/Arbitray...n M B Dynamics C al50 E xciter el ectrodynamic s haker b eing d riven b y a H ewlett P ackard 33120A 15M Hz/Arbitrary waveform generator p

Short and Long Term Investor Synchronization Caused by Decoupling

PubMed Central

Roszczynska-Kurasinska, Magda; Nowak, Andrzej; Kamieniarz, Daniel; Solomon, Sorin; Andersen, Jørgen Vitting

2012-01-01

The dynamics of collective decision making is not yet well understood. Its practical relevance however can be of utmost importance, as experienced by people who lost their fortunes in turbulent moments of financial markets. In this paper we show how spontaneous collective “moods” or “biases” emerge dynamically among human participants playing a trading game in a simple model of the stock market. Applying theory and computer simulations to the experimental data generated by humans, we are able to predict the onset of such moments before they actually happen. PMID:23236385

Internal character dictates transition dynamics between isolation and cohesive grouping

NASA Astrophysics Data System (ADS)

Manrique, Pedro D.; Hui, Pak Ming; Johnson, Neil F.

2015-12-01

We show that accounting for internal character among interacting heterogeneous entities generates rich transition behavior between isolation and cohesive dynamical grouping. Our analytical and numerical calculations reveal different critical points arising for different character-dependent grouping mechanisms. These critical points move in opposite directions as the population's diversity decreases. Our analytical theory may help explain why a particular class of universality is so common in the real world, despite the fundamental differences in the underlying entities. It also correctly predicts the nonmonotonic temporal variation in connectivity observed recently in one such system.

Simulating Picosecond X-ray Diffraction from shocked crystals by Post-processing Molecular Dynamics Calculations

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

Kimminau, G; Nagler, B; Higginbotham, A

2008-06-19

Calculations of the x-ray diffraction patterns from shocked crystals derived from the results of Non-Equilibrium-Molecular-Dynamics (NEMD) simulations are presented. The atomic coordinates predicted by the NEMD simulations combined with atomic form factors are used to generate a discrete distribution of electron density. A Fast-Fourier-Transform (FFT) of this distribution provides an image of the crystal in reciprocal space, which can be further processed to produce quantitative simulated data for direct comparison with experiments that employ picosecond x-ray diffraction from laser-irradiated crystalline targets.

Quantitative myocardial perfusion from static cardiac and dynamic arterial CT

NASA Astrophysics Data System (ADS)

Bindschadler, Michael; Branch, Kelley R.; Alessio, Adam M.

2018-05-01

Quantitative myocardial blood flow (MBF) estimation by dynamic contrast enhanced cardiac computed tomography (CT) requires multi-frame acquisition of contrast transit through the blood pool and myocardium to inform the arterial input and tissue response functions. Both the input and the tissue response functions for the entire myocardium are sampled with each acquisition. However, the long breath holds and frequent sampling can result in significant motion artifacts and relatively high radiation dose. To address these limitations, we propose and evaluate a new static cardiac and dynamic arterial (SCDA) quantitative MBF approach where (1) the input function is well sampled using either prediction from pre-scan timing bolus data or measured from dynamic thin slice ‘bolus tracking’ acquisitions, and (2) the whole-heart tissue response data is limited to one contrast enhanced CT acquisition. A perfusion model uses the dynamic arterial input function to generate a family of possible myocardial contrast enhancement curves corresponding to a range of MBF values. Combined with the timing of the single whole-heart acquisition, these curves generate a lookup table relating myocardial contrast enhancement to quantitative MBF. We tested the SCDA approach in 28 patients that underwent a full dynamic CT protocol both at rest and vasodilator stress conditions. Using measured input function plus single (enhanced CT only) or plus double (enhanced and contrast free baseline CT’s) myocardial acquisitions yielded MBF estimates with root mean square (RMS) error of 1.2 ml/min/g and 0.35 ml/min/g, and radiation dose reductions of 90% and 83%, respectively. The prediction of the input function based on timing bolus data and the static acquisition had an RMS error compared to the measured input function of 26.0% which led to MBF estimation errors greater than threefold higher than using the measured input function. SCDA presents a new, simplified approach for quantitative perfusion imaging with an acquisition strategy offering substantial radiation dose and computational complexity savings over dynamic CT.

Unexpected Nongenetic Individual Heterogeneity and Trait Covariance in Daphnia and Its Consequences for Ecological and Evolutionary Dynamics.

PubMed

Cressler, Clayton E; Bengtson, Stefan; Nelson, William A

2017-07-01

Individual differences in genetics, age, or environment can cause tremendous differences in individual life-history traits. This individual heterogeneity generates demographic heterogeneity at the population level, which is predicted to have a strong impact on both ecological and evolutionary dynamics. However, we know surprisingly little about the sources of individual heterogeneity for particular taxa or how different sources scale up to impact ecological and evolutionary dynamics. Here we experimentally study the individual heterogeneity that emerges from both genetic and nongenetic sources in a species of freshwater zooplankton across a large gradient of food quality. Despite the tight control of environment, we still find that the variation from nongenetic sources is greater than that from genetic sources over a wide range of food quality and that this variation has strong positive covariance between growth and reproduction. We evaluate the general consequences of genetic and nongenetic covariance for ecological and evolutionary dynamics theoretically and find that increasing nongenetic variation slows evolution independent of the correlation in heritable life-history traits but that the impact on ecological dynamics depends on both nongenetic and genetic covariance. Our results demonstrate that variation in the relative magnitude of nongenetic versus genetic sources of variation impacts the predicted ecological and evolutionary dynamics.

Mining data from CFD simulation for aneurysm and carotid bifurcation models.

PubMed

Miloš, Radović; Dejan, Petrović; Nenad, Filipović

2011-01-01

Arterial geometry variability is present both within and across individuals. To analyze the influence of geometric parameters, blood density, dynamic viscosity and blood velocity on wall shear stress (WSS) distribution in the human carotid artery bifurcation and aneurysm, the computer simulations were run to generate the data pertaining to this phenomenon. In our work we evaluate two prediction models for modeling these relationships: neural network model and k-nearest neighbor model. The results revealed that both models have high prediction ability for this prediction task. The achieved results represent progress in assessment of stroke risk for a given patient data in real time.

Three-Wave Gas Journal Bearing Behavior With Shaft Runout

NASA Technical Reports Server (NTRS)

Dimofte, Florin; Hendricks, Robert C.

1997-01-01

Experimental orbits of a free-mounted, three-wave gas journal bearing housing were recorded and compared to transient predicted orbits. The shaft was mounted eccentric with a fixed runout. Experimental observations for both the absolute bearing housing center orbits and the relative bearing housing center to shaft center orbits are in good agreement with the predictions. The sub-synchronous whirl motion generated by the fluid film was found experimentally and predicted theoretically for certain speeds. A three-wave journal bearing can run stably under dynamic loads with orbits well inside the bearing clearance. Moreover, the orbits are almost circular free of the influence of bearing wave shape.

Changes in fire regime break the legacy lock on successional trajectories in Alaskan boreal forest

Treesearch

Jill F. Johnstone; Teresa N. Hollingsworth; F. Stuart Chapin; Michelle C. Mack

2009-01-01

Predicting plant community responses to changing environmental conditions is a key element of forecasting and mitigating the effects of global change. Disturbance can play an important role in these dynamics, by initiating cycles of secondary succession and generating opportunities for communities of long-lived organisms to reorganize in alternative configurations....

CEINMS: a toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks

PubMed Central

Pizzolato, Claudio; Lloyd, David G.; Sartori, Massimo; Ceseracciu, Elena; Besier, Thor F.; Fregly, Benjamin J.; Reggiani, Monica

2015-01-01

Personalized neuromusculoskeletal (NMS) models can represent the neurological, physiological, and anatomical characteristics of an individual and can be used to estimate the forces generated inside the human body. Currently, publicly available software to calculate muscle forces are restricted to static and dynamic optimisation methods, or limited to isometric tasks only. We have created and made freely available for the research community the Calibrated EMG-Informed NMS Modelling Toolbox (CEINMS), an OpenSim plug-in that enables investigators to predict different neural control solutions for the same musculoskeletal geometry and measured movements. CEINMS comprises EMG-driven and EMG-informed algorithms that have been previously published and tested. It operates on dynamic skeletal models possessing any number of degrees of freedom and musculotendon units and can be calibrated to the individual to predict measured joint moments and EMG patterns. In this paper we describe the components of CEINMS and its integration with OpenSim. We then analyse how EMG-driven, EMG-assisted, and static optimisation neural control solutions affect the estimated joint moments, muscle forces, and muscle excitations, including muscle co-contraction. PMID:26522621

Balancing exploration and exploitation in population-based sampling improves fragment-based de novo protein structure prediction.

PubMed

Simoncini, David; Schiex, Thomas; Zhang, Kam Y J

2017-05-01

Conformational search space exploration remains a major bottleneck for protein structure prediction methods. Population-based meta-heuristics typically enable the possibility to control the search dynamics and to tune the balance between local energy minimization and search space exploration. EdaFold is a fragment-based approach that can guide search by periodically updating the probability distribution over the fragment libraries used during model assembly. We implement the EdaFold algorithm as a Rosetta protocol and provide two different probability update policies: a cluster-based variation (EdaRose c ) and an energy-based one (EdaRose en ). We analyze the search dynamics of our new Rosetta protocols and show that EdaRose c is able to provide predictions with lower C αRMSD to the native structure than EdaRose en and Rosetta AbInitio Relax protocol. Our software is freely available as a C++ patch for the Rosetta suite and can be downloaded from http://www.riken.jp/zhangiru/software/. Our protocols can easily be extended in order to create alternative probability update policies and generate new search dynamics. Proteins 2017; 85:852-858. © 2016 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

The application of tailor-made force fields and molecular dynamics for NMR crystallography: a case study of free base cocaine

PubMed Central

Neumann, Marcus A.

2017-01-01

Motional averaging has been proven to be significant in predicting the chemical shifts in ab initio solid-state NMR calculations, and the applicability of motional averaging with molecular dynamics has been shown to depend on the accuracy of the molecular mechanical force field. The performance of a fully automatically generated tailor-made force field (TMFF) for the dynamic aspects of NMR crystallography is evaluated and compared with existing benchmarks, including static dispersion-corrected density functional theory calculations and the COMPASS force field. The crystal structure of free base cocaine is used as an example. The results reveal that, even though the TMFF outperforms the COMPASS force field for representing the energies and conformations of predicted structures, it does not give significant improvement in the accuracy of NMR calculations. Further studies should direct more attention to anisotropic chemical shifts and development of the method of solid-state NMR calculations. PMID:28250956

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

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Automated chemical kinetic modeling via hybrid reactive molecular dynamics and quantum chemistry simulations.

PubMed

Döntgen, Malte; Schmalz, Felix; Kopp, Wassja A; Kröger, Leif C; Leonhard, Kai

2018-06-13

An automated scheme for obtaining chemical kinetic models from scratch using reactive molecular dynamics and quantum chemistry simulations is presented. This methodology combines the phase space sampling of reactive molecular dynamics with the thermochemistry and kinetics prediction capabilities of quantum mechanics. This scheme provides the NASA polynomial and modified Arrhenius equation parameters for all species and reactions that are observed during the simulation and supplies them in the ChemKin format. The ab initio level of theory for predictions is easily exchangeable and the presently used G3MP2 level of theory is found to reliably reproduce hydrogen and methane oxidation thermochemistry and kinetics data. Chemical kinetic models obtained with this approach are ready-to-use for, e.g., ignition delay time simulations, as shown for hydrogen combustion. The presented extension of the ChemTraYzer approach can be used as a basis for methodologically advancing chemical kinetic modeling schemes and as a black-box approach to generate chemical kinetic models.

Using dynamic population simulations to extend resource selection analyses and prioritize habitats for conservation

USGS Publications Warehouse

Heinrichs, Julie; Aldridge, Cameron L.; O'Donnell, Michael; Schumaker, Nathan

2017-01-01

Prioritizing habitats for conservation is a challenging task, particularly for species with fluctuating populations and seasonally dynamic habitat needs. Although the use of resource selection models to identify and prioritize habitat for conservation is increasingly common, their ability to characterize important long-term habitats for dynamic populations are variable. To examine how habitats might be prioritized differently if resource selection was directly and dynamically linked with population fluctuations and movement limitations among seasonal habitats, we constructed a spatially explicit individual-based model for a dramatically fluctuating population requiring temporally varying resources. Using greater sage-grouse (Centrocercus urophasianus) in Wyoming as a case study, we used resource selection function maps to guide seasonal movement and habitat selection, but emergent population dynamics and simulated movement limitations modified long-term habitat occupancy. We compared priority habitats in RSF maps to long-term simulated habitat use. We examined the circumstances under which the explicit consideration of movement limitations, in combination with population fluctuations and trends, are likely to alter predictions of important habitats. In doing so, we assessed the future occupancy of protected areas under alternative population and habitat conditions. Habitat prioritizations based on resource selection models alone predicted high use in isolated parcels of habitat and in areas with low connectivity among seasonal habitats. In contrast, results based on more biologically-informed simulations emphasized central and connected areas near high-density populations, sometimes predicted to be low selection value. Dynamic models of habitat use can provide additional biological realism that can extend, and in some cases, contradict habitat use predictions generated from short-term or static resource selection analyses. The explicit inclusion of population dynamics and movement propensities via spatial simulation modeling frameworks may provide an informative means of predicting long-term habitat use, particularly for fluctuating populations with complex seasonal habitat needs. Importantly, our results indicate the possible need to consider habitat selection models as a starting point rather than the common end point for refining and prioritizing habitats for protection for cyclic and highly variable populations.

The Next Generation of High-Speed Dynamic Stability Wind Tunnel Testing (Invited)

NASA Technical Reports Server (NTRS)

Tomek, Deborah M.; Sewall, William G.; Mason, Stan E.; Szchur, Bill W. A.

2006-01-01

Throughout industry, accurate measurement and modeling of dynamic derivative data at high-speed conditions has been an ongoing challenge. The expansion of flight envelopes and non-conventional vehicle design has greatly increased the demand for accurate prediction and modeling of vehicle dynamic behavior. With these issues in mind, NASA Langley Research Center (LaRC) embarked on the development and shakedown of a high-speed dynamic stability test technique that addresses the longstanding problem of accurately measuring dynamic derivatives outside the low-speed regime. The new test technique was built upon legacy technology, replacing an antiquated forced oscillation system, and greatly expanding the capabilities beyond classic forced oscillation testing at both low and high speeds. The modern system is capable of providing a snapshot of dynamic behavior over a periodic cycle for varying frequencies, not just a damping derivative term at a single frequency.

A novel multilayer model for missing link prediction and future link forecasting in dynamic complex networks

NASA Astrophysics Data System (ADS)

Yasami, Yasser; Safaei, Farshad

2018-02-01

The traditional complex network theory is particularly focused on network models in which all network constituents are dealt with equivalently, while fail to consider the supplementary information related to the dynamic properties of the network interactions. This is a main constraint leading to incorrect descriptions of some real-world phenomena or incomplete capturing the details of certain real-life problems. To cope with the problem, this paper addresses the multilayer aspects of dynamic complex networks by analyzing the properties of intrinsically multilayered co-authorship networks, DBLP and Astro Physics, and presenting a novel multilayer model of dynamic complex networks. The model examines the layers evolution (layers birth/death process and lifetime) throughout the network evolution. Particularly, this paper models the evolution of each node's membership in different layers by an Infinite Factorial Hidden Markov Model considering feature cascade, and thereby formulates the link generation process for intra-layer and inter-layer links. Although adjacency matrixes are useful to describe the traditional single-layer networks, such a representation is not sufficient to describe and analyze the multilayer dynamic networks. This paper also extends a generalized mathematical infrastructure to address the problems issued by multilayer complex networks. The model inference is performed using some Markov Chain Monte Carlo sampling strategies, given synthetic and real complex networks data. Experimental results indicate a tremendous improvement in the performance of the proposed multilayer model in terms of sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, F1-score, Matthews correlation coefficient, and accuracy for two important applications of missing link prediction and future link forecasting. The experimental results also indicate the strong predictivepower of the proposed model for the application of cascade prediction in terms of accuracy.

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation

PubMed Central

Meduru, Harika; Wang, Yeng-Tseng; Tsai, Jeffrey J. P.; Chen, Yu-Ching

2016-01-01

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes. PMID:27304951

Finding a Potential Dipeptidyl Peptidase-4 (DPP-4) Inhibitor for Type-2 Diabetes Treatment Based on Molecular Docking, Pharmacophore Generation, and Molecular Dynamics Simulation.

PubMed

Meduru, Harika; Wang, Yeng-Tseng; Tsai, Jeffrey J P; Chen, Yu-Ching

2016-06-13

Dipeptidyl peptidase-4 (DPP-4) is the vital enzyme that is responsible for inactivating intestinal peptides glucagon like peptide-1 (GLP-1) and Gastric inhibitory polypeptide (GIP), which stimulates a decline in blood glucose levels. The aim of this study was to explore the inhibition activity of small molecule inhibitors to DPP-4 following a computational strategy based on docking studies and molecular dynamics simulations. The thorough docking protocol we applied allowed us to derive good correlation parameters between the predicted binding affinities (pKi) of the DPP-4 inhibitors and the experimental activity values (pIC50). Based on molecular docking receptor-ligand interactions, pharmacophore generation was carried out in order to identify the binding modes of structurally diverse compounds in the receptor active site. Consideration of the permanence and flexibility of DPP-4 inhibitor complexes by means of molecular dynamics (MD) simulation specified that the inhibitors maintained the binding mode observed in the docking study. The present study helps generate new information for further structural optimization and can influence the development of new DPP-4 inhibitors discoveries in the treatment of type-2 diabetes.

Fit to predict? Eco-informatics for predicting the catchability of a pelagic fish in near real time.

PubMed

Scales, Kylie L; Hazen, Elliott L; Maxwell, Sara M; Dewar, Heidi; Kohin, Suzanne; Jacox, Michael G; Edwards, Christopher A; Briscoe, Dana K; Crowder, Larry B; Lewison, Rebecca L; Bograd, Steven J

2017-12-01

The ocean is a dynamic environment inhabited by a diverse array of highly migratory species, many of which are under direct exploitation in targeted fisheries. The timescales of variability in the marine realm coupled with the extreme mobility of ocean-wandering species such as tuna and billfish complicates fisheries management. Developing eco-informatics solutions that allow for near real-time prediction of the distributions of highly mobile marine species is an important step towards the maturation of dynamic ocean management and ecological forecasting. Using 25 yr (1990-2014) of NOAA fisheries' observer data from the California drift gillnet fishery, we model relative probability of occurrence (presence-absence) and catchability (total catch per gillnet set) of broadbill swordfish Xiphias gladius in the California Current System. Using freely available environmental data sets and open source software, we explore the physical drivers of regional swordfish distribution. Comparing models built upon remotely sensed data sets with those built upon a data-assimilative configuration of the Regional Ocean Modelling System (ROMS), we explore trade-offs in model construction, and address how physical data can affect predictive performance and operational capacity. Swordfish catchability was found to be highest in deeper waters (>1,500 m) with surface temperatures in the 14-20°C range, isothermal layer depth (ILD) of 20-40 m, positive sea surface height (SSH) anomalies, and during the new moon (<20% lunar illumination). We observed a greater influence of mesoscale variability (SSH, wind speed, isothermal layer depth, eddy kinetic energy) in driving swordfish catchability (total catch) than was evident in predicting the relative probability of presence (presence-absence), confirming the utility of generating spatiotemporally dynamic predictions. Data-assimilative ROMS circumvent the limitations of satellite remote sensing in providing physical data fields for species distribution models (e.g., cloud cover, variable resolution, subsurface data), and facilitate broad-scale prediction of dynamic species distributions in near real time. © 2017 by the Ecological Society of America.

Evaluation of a computer-generated perspective tunnel display for flight path following

NASA Technical Reports Server (NTRS)

Grunwald, A. J.; Robertson, J. B.; Hatfield, J. J.

1980-01-01

The display was evaluated by monitoring pilot performance in a fixed base simulator with the vehicle dynamics of a CH-47 tandem rotor helicopter. Superposition of the predicted future vehicle position on the tunnel image was also investigated to determine whether, and to what extent, it contributes to better system performance (the best predicted future vehicle position was sought). Three types of simulator experiments were conducted: following a desired trajectory in the presence of disturbances; entering the trajectory from a random position, outside the trajectory; detecting and correcting failures in automatic flight. The tunnel display with superimposed predictor/director symbols was shown to be a very successful combination, which outperformed the other two displays in all three experiments. A prediction time of 4 to 7 sec. was found to optimize trajectory tracking for the given vehicle dynamics and flight condition. Pilot acceptance of the tunnel plus predictor/director display was found to be favorable and the time the pilot needed for familiarization with the display was found to be relatively short.

Host–parasite fluctuating selection in the absence of specificity

PubMed Central

Ashby, Ben; White, Andy; Bowers, Roger; Buckling, Angus; Koskella, Britt

2017-01-01

Fluctuating selection driven by coevolution between hosts and parasites is important for the generation of host and parasite diversity across space and time. Theory has focused primarily on infection genetics, with highly specific ‘matching-allele’ frameworks more likely to generate fluctuating selection dynamics (FSD) than ‘gene-for-gene’ (generalist–specialist) frameworks. However, the environment, ecological feedbacks and life-history characteristics may all play a role in determining when FSD occurs. Here, we develop eco-evolutionary models with explicit ecological dynamics to explore the ecological, epidemiological and host life-history drivers of FSD. Our key result is to demonstrate for the first time, to our knowledge, that specificity between hosts and parasites is not required to generate FSD. Furthermore, highly specific host–parasite interactions produce unstable, less robust stochastic fluctuations in contrast to interactions that lack specificity altogether or those that vary from generalist to specialist, which produce predictable limit cycles. Given the ubiquity of ecological feedbacks and the variation in the nature of specificity in host–parasite interactions, our work emphasizes the underestimated potential for host–parasite coevolution to generate fluctuating selection. PMID:29093222

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

PubMed Central

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

2009-01-01

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

AC-driven bilayer graphene: quasienergy spectrum of electrons and generation of soliton-like electromagnetic pulse

NASA Astrophysics Data System (ADS)

Kukhar, Egor I.

2018-01-01

Quasienergy spectrum of electrons in biased bigraphene subjected to the linear polarized high-frequency electromagnetic radiation has been derived. Quasienergy bands of ac-driven bigraphene have been investigated. Dynamical appearing of the saddle points in band structure of biased bigraphene and energy gap modification have been predicted. Electromagnetic field equation has been written using obtained quasienergy spectrum. The solution corresponding to the soliton-like electromagnetic wave has been obtained. The conditions of soliton-like wave generation in ac-driven bigraphene have been discussed.

Neural Dynamics Underlying Event-Related Potentials

NASA Technical Reports Server (NTRS)

Shah, Ankoor S.; Bressler, Steven L.; Knuth, Kevin H.; Ding, Ming-Zhou; Mehta, Ashesh D.; Ulbert, Istvan; Schroeder, Charles E.

2003-01-01

There are two opposing hypotheses about the brain mechanisms underlying sensory event-related potentials (ERPs). One holds that sensory ERPs are generated by phase resetting of ongoing electroencephalographic (EEG) activity, and the other that they result from signal averaging of stimulus-evoked neural responses. We tested several contrasting predictions of these hypotheses by direct intracortical analysis of neural activity in monkeys. Our findings clearly demonstrate evoked response contributions to the sensory ERP in the monkey, and they suggest the likelihood that a mixed (Evoked/Phase Resetting) model may account for the generation of scalp ERPs in humans.

Multiple pure tone noise prediction

NASA Astrophysics Data System (ADS)

Han, Fei; Sharma, Anupam; Paliath, Umesh; Shieh, Chingwei

2014-12-01

This paper presents a fully numerical method for predicting multiple pure tones, also known as “Buzzsaw” noise. It consists of three steps that account for noise source generation, nonlinear acoustic propagation with hard as well as lined walls inside the nacelle, and linear acoustic propagation outside the engine. Noise generation is modeled by steady, part-annulus computational fluid dynamics (CFD) simulations. A linear superposition algorithm is used to construct full-annulus shock/pressure pattern just upstream of the fan from part-annulus CFD results. Nonlinear wave propagation is carried out inside the duct using a pseudo-two-dimensional solution of Burgers' equation. Scattering from nacelle lip as well as radiation to farfield is performed using the commercial solver ACTRAN/TM. The proposed prediction process is verified by comparing against full-annulus CFD simulations as well as against static engine test data for a typical high bypass ratio aircraft engine with hardwall as well as lined inlets. Comparisons are drawn against nacelle unsteady pressure transducer measurements at two axial locations as well as against near- and far-field microphone array measurements outside the duct. This is the first fully numerical approach (no experimental or empirical input is required) to predict multiple pure tone noise generation, in-duct propagation and far-field radiation. It uses measured blade coordinates to calculate MPT noise.

The applicability of a computer model for predicting head injury incurred during actual motor vehicle collisions.

PubMed

Moran, Stephan G; Key, Jason S; McGwin, Gerald; Keeley, Jason W; Davidson, James S; Rue, Loring W

2004-07-01

Head injury is a significant cause of both morbidity and mortality. Motor vehicle collisions (MVCs) are the most common source of head injury in the United States. No studies have conclusively determined the applicability of computer models for accurate prediction of head injuries sustained in actual MVCs. This study sought to determine the applicability of such models for predicting head injuries sustained by MVC occupants. The Crash Injury Research and Engineering Network (CIREN) database was queried for restrained drivers who sustained a head injury. These collisions were modeled using occupant dynamic modeling (MADYMO) software, and head injury scores were generated. The computer-generated head injury scores then were evaluated with respect to the actual head injuries sustained by the occupants to determine the applicability of MADYMO computer modeling for predicting head injury. Five occupants meeting the selection criteria for the study were selected from the CIREN database. The head injury scores generated by MADYMO were lower than expected given the actual injuries sustained. In only one case did the computer analysis predict a head injury of a severity similar to that actually sustained by the occupant. Although computer modeling accurately simulates experimental crash tests, it may not be applicable for predicting head injury in actual MVCs. Many complicating factors surrounding actual MVCs make accurate computer modeling difficult. Future modeling efforts should consider variables such as age of the occupant and should account for a wider variety of crash scenarios.

Muscle Synergies May Improve Optimization Prediction of Knee Contact Forces During Walking

PubMed Central

Walter, Jonathan P.; Kinney, Allison L.; Banks, Scott A.; D'Lima, Darryl D.; Besier, Thor F.; Lloyd, David G.; Fregly, Benjamin J.

2014-01-01

The ability to predict patient-specific joint contact and muscle forces accurately could improve the treatment of walking-related disorders. Muscle synergy analysis, which decomposes a large number of muscle electromyographic (EMG) signals into a small number of synergy control signals, could reduce the dimensionality and thus redundancy of the muscle and contact force prediction process. This study investigated whether use of subject-specific synergy controls can improve optimization prediction of knee contact forces during walking. To generate the predictions, we performed mixed dynamic muscle force optimizations (i.e., inverse skeletal dynamics with forward muscle activation and contraction dynamics) using data collected from a subject implanted with a force-measuring knee replacement. Twelve optimization problems (three cases with four subcases each) that minimized the sum of squares of muscle excitations were formulated to investigate how synergy controls affect knee contact force predictions. The three cases were: (1) Calibrate+Match where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously matched, (2) Precalibrate+Predict where experimental knee contact forces were predicted using precalibrated muscle model parameters values from the first case, and (3) Calibrate+Predict where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously predicted, all while matching inverse dynamic loads at the hip, knee, and ankle. The four subcases used either 44 independent controls or five synergy controls with and without EMG shape tracking. For the Calibrate+Match case, all four subcases closely reproduced the measured medial and lateral knee contact forces (R2 ≥ 0.94, root-mean-square (RMS) error < 66 N), indicating sufficient model fidelity for contact force prediction. For the Precalibrate+Predict and Calibrate+Predict cases, synergy controls yielded better contact force predictions (0.61 < R2 < 0.90, 83 N < RMS error < 161 N) than did independent controls (-0.15 < R2 < 0.79, 124 N < RMS error < 343 N) for corresponding subcases. For independent controls, contact force predictions improved when precalibrated model parameter values or EMG shape tracking was used. For synergy controls, contact force predictions were relatively insensitive to how model parameter values were calibrated, while EMG shape tracking made lateral (but not medial) contact force predictions worse. For the subject and optimization cost function analyzed in this study, use of subject-specific synergy controls improved the accuracy of knee contact force predictions, especially for lateral contact force when EMG shape tracking was omitted, and reduced prediction sensitivity to uncertainties in muscle model parameter values. PMID:24402438

Muscle synergies may improve optimization prediction of knee contact forces during walking.

PubMed

Walter, Jonathan P; Kinney, Allison L; Banks, Scott A; D'Lima, Darryl D; Besier, Thor F; Lloyd, David G; Fregly, Benjamin J

2014-02-01

The ability to predict patient-specific joint contact and muscle forces accurately could improve the treatment of walking-related disorders. Muscle synergy analysis, which decomposes a large number of muscle electromyographic (EMG) signals into a small number of synergy control signals, could reduce the dimensionality and thus redundancy of the muscle and contact force prediction process. This study investigated whether use of subject-specific synergy controls can improve optimization prediction of knee contact forces during walking. To generate the predictions, we performed mixed dynamic muscle force optimizations (i.e., inverse skeletal dynamics with forward muscle activation and contraction dynamics) using data collected from a subject implanted with a force-measuring knee replacement. Twelve optimization problems (three cases with four subcases each) that minimized the sum of squares of muscle excitations were formulated to investigate how synergy controls affect knee contact force predictions. The three cases were: (1) Calibrate+Match where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously matched, (2) Precalibrate+Predict where experimental knee contact forces were predicted using precalibrated muscle model parameters values from the first case, and (3) Calibrate+Predict where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously predicted, all while matching inverse dynamic loads at the hip, knee, and ankle. The four subcases used either 44 independent controls or five synergy controls with and without EMG shape tracking. For the Calibrate+Match case, all four subcases closely reproduced the measured medial and lateral knee contact forces (R2 ≥ 0.94, root-mean-square (RMS) error < 66 N), indicating sufficient model fidelity for contact force prediction. For the Precalibrate+Predict and Calibrate+Predict cases, synergy controls yielded better contact force predictions (0.61 < R2 < 0.90, 83 N < RMS error < 161 N) than did independent controls (-0.15 < R2 < 0.79, 124 N < RMS error < 343 N) for corresponding subcases. For independent controls, contact force predictions improved when precalibrated model parameter values or EMG shape tracking was used. For synergy controls, contact force predictions were relatively insensitive to how model parameter values were calibrated, while EMG shape tracking made lateral (but not medial) contact force predictions worse. For the subject and optimization cost function analyzed in this study, use of subject-specific synergy controls improved the accuracy of knee contact force predictions, especially for lateral contact force when EMG shape tracking was omitted, and reduced prediction sensitivity to uncertainties in muscle model parameter values.

Subharmonic Oscillations and Chaos in Dynamic Atomic Force Microscopy

NASA Technical Reports Server (NTRS)

Cantrell, John H.; Cantrell, Sean A.

2015-01-01

The increasing use of dynamic atomic force microscopy (d-AFM) for nanoscale materials characterization calls for a deeper understanding of the cantilever dynamics influencing scan stability, predictability, and image quality. Model development is critical to such understanding. Renormalization of the equations governing d- AFM provides a simple interpretation of cantilever dynamics as a single spring and mass system with frequency dependent cantilever stiffness and damping parameters. The renormalized model is sufficiently robust to predict the experimentally observed splitting of the free-space cantilever resonance into multiple resonances upon cantilever-sample contact. Central to the model is the representation of the cantilever sample interaction force as a polynomial expansion with coefficients F(sub ij) (i,j = 0, 1, 2) that account for the effective interaction stiffness parameter, the cantilever-to-sample energy transfer, and the amplitude of cantilever oscillation. Application of the Melnikov method to the model equation is shown to predict a homoclinic bifurcation of the Smale horseshoe type leading to a cascade of period doublings with increasing drive displacement amplitude culminating in chaos and loss of image quality. The threshold value of the drive displacement amplitude necessary to initiate subharmonic generation depends on the acoustic drive frequency, the effective damping coefficient, and the nonlinearity of the cantilever-sample interaction force. For parameter values leading to displacement amplitudes below threshold for homoclinic bifurcation other bifurcation scenarios can occur, some of which lead to chaos.

Cryptic chytridiomycosis linked to climate and genetic variation in amphibian populations of the southeastern United States

PubMed Central

Hoffman, Eric A.; Tye, Matthew R.; Hether, Tyler D.; Savage, Anna E.

2017-01-01

North American amphibians have recently been impacted by two major emerging pathogens, the fungus Batrachochytrium dendrobatidis (Bd) and iridoviruses in the genus Ranavirus (Rv). Environmental factors and host genetics may play important roles in disease dynamics, but few studies incorporate both of these components into their analyses. Here, we investigated the role of environmental and genetic factors in driving Bd and Rv infection prevalence and severity in a biodiversity hot spot, the southeastern United States. We used quantitative PCR to characterize Bd and Rv dynamics in natural populations of three amphibian species: Notophthalmus perstriatus, Hyla squirella and Pseudacris ornata. We combined pathogen data, genetic diversity metrics generated from neutral markers, and environmental variables into general linear models to evaluate how these factors impact infectious disease dynamics. Occurrence, prevalence and intensity of Bd and Rv varied across species and populations, but only one species, Pseudacris ornata, harbored high Bd intensities in the majority of sampled populations. Genetic diversity and climate variables both predicted Bd prevalence, whereas climatic variables alone predicted infection intensity. We conclude that Bd is more abundant in the southeastern United States than previously thought and that genetic and environmental factors are both important for predicting amphibian pathogen dynamics. Incorporating both genetic and environmental information into conservation plans for amphibians is necessary for the development of more effective management strategies to mitigate the impact of emerging infectious diseases. PMID:28448517

Multiscale Analysis of Structurally-Graded Microstructures Using Molecular Dynamics, Discrete Dislocation Dynamics and Continuum Crystal Plasticity

NASA Technical Reports Server (NTRS)

Saether, Erik; Hochhalter, Jacob D.; Glaessgen, Edward H.; Mishin, Yuri

2014-01-01

A multiscale modeling methodology is developed for structurally-graded material microstructures. Molecular dynamic (MD) simulations are performed at the nanoscale to determine fundamental failure mechanisms and quantify material constitutive parameters. These parameters are used to calibrate material processes at the mesoscale using discrete dislocation dynamics (DD). Different grain boundary interactions with dislocations are analyzed using DD to predict grain-size dependent stress-strain behavior. These relationships are mapped into crystal plasticity (CP) parameters to develop a computationally efficient finite element-based DD/CP model for continuum-level simulations and complete the multiscale analysis by predicting the behavior of macroscopic physical specimens. The present analysis is focused on simulating the behavior of a graded microstructure in which grain sizes are on the order of nanometers in the exterior region and transition to larger, multi-micron size in the interior domain. This microstructural configuration has been shown to offer improved mechanical properties over homogeneous coarse-grained materials by increasing yield stress while maintaining ductility. Various mesoscopic polycrystal models of structurally-graded microstructures are generated, analyzed and used as a benchmark for comparison between multiscale DD/CP model and DD predictions. A final series of simulations utilize the DD/CP analysis method exclusively to study macroscopic models that cannot be analyzed by MD or DD methods alone due to the model size.

Computational Fluid Dynamics Simulation of Hydrodynamics and Stresses in the PhEur/USP Disintegration Tester Under Fed and Fasted Fluid Characteristics.

PubMed

Kindgen, Sarah; Wachtel, Herbert; Abrahamsson, Bertil; Langguth, Peter

2015-09-01

Disintegration of oral solid dosage forms is a prerequisite for drug dissolution and absorption and is to a large extent dependent on the pressures and hydrodynamic conditions in the solution that the dosage form is exposed to. In this work, the hydrodynamics in the PhEur/USP disintegration tester were investigated using computational fluid dynamics (CFD). Particle image velocimetry was used to validate the CFD predictions. The CFD simulations were performed with different Newtonian and non-Newtonian fluids, representing fasted and fed states. The results indicate that the current design and operating conditions of the disintegration test device, given by the pharmacopoeias, are not reproducing the in vivo situation. This holds true for the hydrodynamics in the disintegration tester that generates Reynolds numbers dissimilar to the reported in vivo situation. Also, when using homogenized US FDA meal, representing the fed state, too high viscosities and relative pressures are generated. The forces acting on the dosage form are too small for all fluids compared to the in vivo situation. The lack of peristaltic contractions, which generate hydrodynamics and shear stress in vivo, might be the major drawback of the compendial device resulting in the observed differences between predicted and in vivo measured hydrodynamics. © 2015 Wiley Periodicals, Inc. and the American Pharmacists Association.

A master equation approach to actin polymerization applied to endocytosis in yeast.

PubMed

Wang, Xinxin; Carlsson, Anders E

2017-12-01

We present a Master Equation approach to calculating polymerization dynamics and force generation by branched actin networks at membranes. The method treats the time evolution of the F-actin distribution in three dimensions, with branching included as a directional spreading term. It is validated by comparison with stochastic simulations of force generation by actin polymerization at obstacles coated with actin "nucleation promoting factors" (NPFs). The method is then used to treat the dynamics of actin polymerization and force generation during endocytosis in yeast, using a model in which NPFs form a ring around the endocytic site, centered by a spot of molecules attaching the actin network strongly to the membrane. We find that a spontaneous actin filament nucleation mechanism is required for adequate forces to drive the process, that partial inhibition of branching and polymerization lead to different characteristic responses, and that a limited range of polymerization-rate values provide effective invagination and obtain correct predictions for the effects of mutations in the active regions of the NPFs.

Flame extinction limit and particulates formation in fuel blends

NASA Astrophysics Data System (ADS)

Subramanya, Mahesh

Many fuels used in material processing and power generation applications are generally a blend of various hydrocarbons. Although the combustion and aerosol formation dynamics of individual fuels is well understood, the flame dynamics of fuel blends are yet to be characterized. This research uses a twin flame counterflow burner to measure flame velocity, flame extinction, particulate formation and particulate morphology of hydrogen fuel blend flames at different H2 concentration, oscillation frequencies and stretch conditions. Phase resolved spectroscopic measurements (emission spectra) of OH, H, O and CH radical/atom concentrations is used to characterize the heat release processes of the flame. In addition flame generated particulates are collected using thermophoretic sample technique and are qualitative analyzed using Raman Spectroscopy and SEM. Such measurements are essential for the development of advanced computational tools capable of predicting fuel blend flame characteristics at realistic combustor conditions. The data generated through the measurements of this research are representative, and yet accurate, with unique well defined boundary conditions which can be reproduced in numerical computations for kinetic code validations.

A master equation approach to actin polymerization applied to endocytosis in yeast

PubMed Central

Wang, Xinxin

2017-01-01

We present a Master Equation approach to calculating polymerization dynamics and force generation by branched actin networks at membranes. The method treats the time evolution of the F-actin distribution in three dimensions, with branching included as a directional spreading term. It is validated by comparison with stochastic simulations of force generation by actin polymerization at obstacles coated with actin “nucleation promoting factors” (NPFs). The method is then used to treat the dynamics of actin polymerization and force generation during endocytosis in yeast, using a model in which NPFs form a ring around the endocytic site, centered by a spot of molecules attaching the actin network strongly to the membrane. We find that a spontaneous actin filament nucleation mechanism is required for adequate forces to drive the process, that partial inhibition of branching and polymerization lead to different characteristic responses, and that a limited range of polymerization-rate values provide effective invagination and obtain correct predictions for the effects of mutations in the active regions of the NPFs. PMID:29240771

Modeling and Assessing Insect Disturbance on Boreal Forests in the Krasnoyarsk region of Russia by Employing the FAREAST Gap Model and Local Forest Inventory and Disturbance Data.

NASA Astrophysics Data System (ADS)

Erler, A. E.; Shuman, J. K.; Soukhavolosky, V.; Kovalev, A.; Stevens, T.; Shugart, H. H.

2008-12-01

FAREAST: an individual-based forest dynamics model was initially developed to simulate the forested region around Changbai Mountain in northern China. In recent years the model has been expanded across Siberia. The model output for biomass (tCha-1) has been verified against forest inventory data for a number of sites across Russia. With this success, an additional module for the model was written by Anton Kovalev to predict the impact of insect disturbance on the Boreal forests. This model predicts the probability of an insect outbreak occurring, and then, by assessing each individual tree in a modeled stand, predicts whether a tree will be killed as a result of insect predation. From this, a disturbance index is calculated that includes lost biomass as a result of insect disturbance and subsequent species composition. This disturbance "fingerprint" is being compared to forest inventory and insect disturbance data from the Usolsky forests in the Krasnoyarsk region of central Siberia. Silkworm disturbance is expressed in this geo- database as a percentage of trees damaged or killed in a stand. The forest inventory data allows us to calculate a biomass estimate that will be compared to the biomass outputs generated by the model post insect disturbance. The validation of simulated biomass with independent inventory data confirms that FAREAST is a robust model of Russian forest dynamics. Effective validation of the insect disturbance model will allow us to generate a more complete picture of the changing ecology of the Siberian Boreal landscape. The economic cost of lumber lost as a result of Silkworm damage has been enormous, if verified, FAREAST will afford us the opportunity to estimate the extent of that loss and predict the changing ecological dynamics of the Boreal forest system under the worlds evolving climate.

What can numerical simulations say about Jupiter’s deep, long-lived anticyclones?

NASA Astrophysics Data System (ADS)

Chan, Kwing L.

2017-10-01

If Jupiter’s long-lived anticyclones, GRS being the most prominent example, are indeed deep as indicated, the study of their dynamics would be much more difficult than if they were shallow. A shallow phenomenon limited to the troposphere can be modeled by general circulation models like those used in weather prediction for Earth’s atmosphere, as the layer overall is convectively stable (hydrostatic approximation can be applied) and the time scales (advection and radiation) are relatively short. If the dynamics involve the deep convective envelop below, the time scales for thermal relaxation and spin-up would be many orders of magnitudes longer. At the same time, the requirements for handling stratification, turbulence, compressibility, fast rotation, spatial resolution, and numerical stability conditions are not forgiving. Currently, numerical studies of long-lived vortices generated in convection zone are limited to ‘numerical experiments’ having internal energy fluxes many orders of magnitudes greater than that of Jupiter (for faster thermal and dynamical relaxation). Though these experiments cannot predict quantitative values for direct observational comparison, their information on the spatial distributions and connections among velocity, temperature, pressure etc. can tell a lot about what a deep-seated model can predict or describe. We are going to present the results of our latest fully compressible, large-eddy-simulation model for generation of long-lived anticyclones in deep convection zone. The high turbulence and complex internal structures of the vortices can naturally be explained. One prediction for observation is: While fluctuations of temperature and vertical velocity dissipate relative fast with height in the troposphere (stable region), the horizontal velocities (vortical motions) drop much slower; they hardly decrease by a factor of two in four pressure scale heights in the overshoot region. Acknowledgement: This research is supported by FDCT of Macau 039/2013/A2 and 080/2015/A3.

Comparative study of chaotic features in hourly wind speed using recurrence quantification analysis

NASA Astrophysics Data System (ADS)

Adeniji, A. E.; Olusola, O. I.; Njah, A. N.

2018-02-01

Due to the shortage in electricity supply in Nigeria, there is a need to improve the alternative power generation from wind energy by analysing the wind speed data available in some parts of the country, for a better understanding of its underlying dynamics for the purpose of good prediction and modelling. The wind speed data used in this study were collected over a period of two years by National Space Research and Development Agency (NASRDA) from five different stations in the tropics namely; Abuja (7050'02.09"N and 6004'29.97"E), Akungba (6059'05.40"N and 5035'52.23"E), Nsukka (6051'28.14"N and 7024'28.15"E), Port Harcourt (4047'05.41"N and 6059'30.62"E), and Yola (9017'33.58"N and 12023'26.69"E). In this paper, recurrence plot (RP) and recurrence quantification analysis (RQA) are applied to investigate a non-linear deterministic dynamical process and non-stationarity in hourly wind speed data from the study areas. Using RQA for each month of the two years, it is observed that wind speed data for the wet months exhibit higher chaoticity than that of the dry months for all the stations, due to strong and weak monsoonal effect during the wet and dry seasons respectively. The results show that recurrence techniques are able to identify areas and periods for which the harvest of wind energy for power generation is good (high predictability) and poor (low predictability) in the study areas. This work also validates the RQA measures (Lmax, DET and ENT) used and establishes that they are similar/related as they give similar results for the dynamical characterization of the wind speed data.

Simulations of photochemical smog formation in complex urban areas

NASA Astrophysics Data System (ADS)

Muilwijk, C.; Schrijvers, P. J. C.; Wuerz, S.; Kenjereš, S.

2016-12-01

In the present study we numerically investigated the dispersion of photochemical reactive pollutants in complex urban areas by applying an integrated Computational Fluid Dynamics (CFD) and Computational Reaction Dynamics (CRD) approach. To model chemical reactions involved in smog generation, the Generic Reaction Set (GRS) approach is used. The GRS model was selected since it does not require detailed modeling of a large set of reactive components. Smog formation is modeled first in the case of an intensive traffic emission, subjected to low to moderate wind conditions in an idealized two-dimensional street canyon with a building aspect ratio (height/width) of one. It is found that Reactive Organic Components (ROC) play an important role in the chemistry of smog formation. In contrast to the NOx/O3 photochemical steady state model that predicts a depletion of the (ground level) ozone, the GRS model predicts generation of ozone. Secondly, the effect of direct sunlight and shadow within the street canyon on the chemical reaction dynamics is investigated for three characteristic solar angles (morning, midday and afternoon). Large differences of up to one order of magnitude are found in the ozone production for different solar angles. As a proof of concept for real urban areas, the integrated CFD/CRD approach is applied for a real scale (1 × 1 km2) complex urban area (a district of the city of Rotterdam, The Netherlands) with high traffic emissions. The predicted pollutant concentration levels give realistic values that correspond to moderate to heavy smog. It is concluded that the integrated CFD/CRD method with the GRS model of chemical reactions is both accurate and numerically robust, and can be used for modeling of smog formation in complex urban areas.

Physico-Chemical Dynamics of Nanoparticle Formation during Laser Decontamination

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

Cheng, M.D.

2005-06-01

Laser-ablation based decontamination is a new and effective approach for simultaneous removal and characterization of contaminants from surfaces (e.g., building interior and exterior walls, ground floors, etc.). The scientific objectives of this research are to: (1) characterize particulate matter generated during the laser-ablation based decontamination, (2) develop a technique for simultaneous cleaning and spectroscopic verification, and (3) develop an empirical model for predicting particle generation for the size range from 10 nm to tens of micrometers. This research project provides fundamental data obtained through a systematic study on the particle generation mechanism, and also provides a working model for predictionmore » of particle generation such that an effective operational strategy can be devised to facilitate worker protection.« less

X-33 Aerodynamic and Aeroheating Computations for Wind Tunnel and Flight Conditions

NASA Technical Reports Server (NTRS)

Hollis, Brian R.; Thompson, Richard A.; Murphy, Kelly J.; Nowak, Robert J.; Riley, Christopher J.; Wood, William A.; Alter, Stephen J.; Prabhu, Ramadas K.

1999-01-01

This report provides an overview of hypersonic Computational Fluid Dynamics research conducted at the NASA Langley Research Center to support the Phase II development of the X-33 vehicle. The X-33, which is being developed by Lockheed-Martin in partnership with NASA, is an experimental Single-Stage-to-Orbit demonstrator that is intended to validate critical technologies for a full-scale Reusable Launch Vehicle. As part of the development of the X-33, CFD codes have been used to predict the aerodynamic and aeroheating characteristics of the vehicle. Laminar and turbulent predictions were generated for the X 33 vehicle using two finite- volume, Navier-Stokes solvers. Inviscid solutions were also generated with an Euler code. Computations were performed for Mach numbers of 4.0 to 10.0 at angles-of-attack from 10 deg to 48 deg with body flap deflections of 0, 10 and 20 deg. Comparisons between predictions and wind tunnel aerodynamic and aeroheating data are presented in this paper. Aeroheating and aerodynamic predictions for flight conditions are also presented.

Isolated Open Rotor Noise Prediction Assessment Using the F31A31 Historical Blade Set

NASA Technical Reports Server (NTRS)

Nark, Douglas M.; Jones, William T.; Boyd, D. Douglas, Jr.; Zawodny, Nikolas S.

2016-01-01

In an effort to mitigate next-generation fuel efficiency and environmental impact concerns for aviation, open rotor propulsion systems have received renewed interest. However, maintaining the high propulsive efficiency while simultaneously meeting noise goals has been one of the challenges in making open rotor propulsion a viable option. Improvements in prediction tools and design methodologies have opened the design space for next generation open rotor designs that satisfy these challenging objectives. As such, validation of aerodynamic and acoustic prediction tools has been an important aspect of open rotor research efforts. This paper describes validation efforts of a combined computational fluid dynamics and Ffowcs Williams and Hawkings equation methodology for open rotor aeroacoustic modeling. Performance and acoustic predictions were made for a benchmark open rotor blade set and compared with measurements over a range of rotor speeds and observer angles. Overall, the results indicate that the computational approach is acceptable for assessing low-noise open rotor designs. Additionally, this approach may be used to provide realistic incident source fields for acoustic shielding/scattering studies on various aircraft configurations.

Generation of synthetic influent data to perform (micro)pollutant wastewater treatment modelling studies.

PubMed

Snip, L J P; Flores-Alsina, X; Aymerich, I; Rodríguez-Mozaz, S; Barceló, D; Plósz, B G; Corominas, Ll; Rodriguez-Roda, I; Jeppsson, U; Gernaey, K V

2016-11-01

The use of process models to simulate the fate of micropollutants in wastewater treatment plants is constantly growing. However, due to the high workload and cost of measuring campaigns, many simulation studies lack sufficiently long time series representing realistic wastewater influent dynamics. In this paper, the feasibility of the Benchmark Simulation Model No. 2 (BSM2) influent generator is tested to create realistic dynamic influent (micro)pollutant disturbance scenarios. The presented set of models is adjusted to describe the occurrence of three pharmaceutical compounds and one of each of its metabolites with samples taken every 2-4h: the anti-inflammatory drug ibuprofen (IBU), the antibiotic sulfamethoxazole (SMX) and the psychoactive carbamazepine (CMZ). Information about type of excretion and total consumption rates forms the basis for creating the data-defined profiles used to generate the dynamic time series. In addition, the traditional influent characteristics such as flow rate, ammonium, particulate chemical oxygen demand and temperature are also modelled using the same framework with high frequency data. The calibration is performed semi-automatically with two different methods depending on data availability. The 'traditional' variables are calibrated with the Bootstrap method while the pharmaceutical loads are estimated with a least squares approach. The simulation results demonstrate that the BSM2 influent generator can describe the dynamics of both traditional variables and pharmaceuticals. Lastly, the study is complemented with: 1) the generation of longer time series for IBU following the same catchment principles; 2) the study of the impact of in-sewer SMX biotransformation when estimating the average daily load; and, 3) a critical discussion of the results, and the future opportunities of the presented approach balancing model structure/calibration procedure complexity versus predictive capabilities. Copyright © 2016. Published by Elsevier B.V.

A Diffusion-Based and Dynamic 3D-Printed Device That Enables Parallel in Vitro Pharmacokinetic Profiling of Molecules

PubMed Central

Lockwood, Sarah Y.; Meisel, Jayda E.; Monsma, Frederick J.; Spence, Dana M.

2016-01-01

The process of bringing a drug to market involves many steps, including the preclinical stage, where various properties of the drug candidate molecule are determined. These properties, which include drug absorption, distribution, metabolism, and excretion, are often displayed in a pharmacokinetic (PK) profile. While PK profiles are determined in animal models, in vitro systems that model in vivo processes are available, although each possesses shortcomings. Here, we present a 3D-printed, diffusion-based, and dynamic in vitro PK device. The device contains six flow channels, each with integrated porous membrane-based insert wells. The pores of these membranes enable drugs to freely diffuse back and forth between the flow channels and the inserts, thus enabling both loading and clearance portions of a standard PK curve to be generated. The device is designed to work with 96-well plate technology and consumes single-digit milliliter volumes to generate multiple PK profiles, simultaneously. Generation of PK profiles by use of the device was initially performed with fluorescein as a test molecule. Effects of such parameters as flow rate, loading time, volume in the insert well, and initial concentration of the test molecule were investigated. A prediction model was generated from this data, enabling the user to predict the concentration of the test molecule at any point along the PK profile within a coefficient of variation of ~5%. Depletion of the analyte from the well was characterized and was determined to follow first-order rate kinetics, indicated by statistically equivalent (p > 0.05) depletion half-lives that were independent of the starting concentration. A PK curve for an approved antibiotic, levofloxacin, was generated to show utility beyond the fluorescein test molecule. PMID:26727249

Percolation mechanism drives actin gels to the critically connected state

NASA Astrophysics Data System (ADS)

Lee, Chiu Fan; Pruessner, Gunnar

2016-05-01

Cell motility and tissue morphogenesis depend crucially on the dynamic remodeling of actomyosin networks. An actomyosin network consists of an actin polymer network connected by cross-linker proteins and motor protein myosins that generate internal stresses on the network. A recent discovery shows that for a range of experimental parameters, actomyosin networks contract to clusters with a power-law size distribution [J. Alvarado, Nat. Phys. 9, 591 (2013), 10.1038/nphys2715]. Here, we argue that actomyosin networks can exhibit a robust critical signature without fine-tuning because the dynamics of the system can be mapped onto a modified version of percolation with trapping (PT), which is known to show critical behavior belonging to the static percolation universality class without the need for fine-tuning of a control parameter. We further employ our PT model to generate experimentally testable predictions.

Palm: Easing the Burden of Analytical Performance Modeling

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

Tallent, Nathan R.; Hoisie, Adolfy

2014-06-01

Analytical (predictive) application performance models are critical for diagnosing performance-limiting resources, optimizing systems, and designing machines. Creating models, however, is difficult because they must be both accurate and concise. To ease the burden of performance modeling, we developed Palm, a modeling tool that combines top-down (human-provided) semantic insight with bottom-up static and dynamic analysis. To express insight, Palm defines a source code modeling annotation language. By coordinating models and source code, Palm's models are `first-class' and reproducible. Unlike prior work, Palm formally links models, functions, and measurements. As a result, Palm (a) uses functions to either abstract or express complexitymore » (b) generates hierarchical models (representing an application's static and dynamic structure); and (c) automatically incorporates measurements to focus attention, represent constant behavior, and validate models. We discuss generating models for three different applications.« less

Development of a 3D log sawing optimization system for small sawmills in central Appalachia, US

Treesearch

Wenshu Lin; Jingxin Wang; Edward Thomas

2011-01-01

A 3D log sawing optimization system was developed to perform log generation, opening face determination, sawing simulation, and lumber grading using 3D modeling techniques. Heuristic and dynamic programming algorithms were used to determine opening face and grade sawing optimization. Positions and shapes of internal log defects were predicted using a model developed by...

A comparative analysis of numerical approaches to the mechanics of elastic sheets

NASA Astrophysics Data System (ADS)

Taylor, Michael; Davidovitch, Benny; Qiu, Zhanlong; Bertoldi, Katia

2015-06-01

Numerically simulating deformations in thin elastic sheets is a challenging problem in computational mechanics due to destabilizing compressive stresses that result in wrinkling. Determining the location, structure, and evolution of wrinkles in these problems has important implications in design and is an area of increasing interest in the fields of physics and engineering. In this work, several numerical approaches previously proposed to model equilibrium deformations in thin elastic sheets are compared. These include standard finite element-based static post-buckling approaches as well as a recently proposed method based on dynamic relaxation, which are applied to the problem of an annular sheet with opposed tractions where wrinkling is a key feature. Numerical solutions are compared to analytic predictions of the ground state, enabling a quantitative evaluation of the predictive power of the various methods. Results indicate that static finite element approaches produce local minima that are highly sensitive to initial imperfections, relying on a priori knowledge of the equilibrium wrinkling pattern to generate optimal results. In contrast, dynamic relaxation is much less sensitive to initial imperfections and can generate low-energy solutions for a wide variety of loading conditions without requiring knowledge of the equilibrium solution beforehand.

Study on characteristics of EMR signals induced from fracture of rock samples and their application in rockburst prediction in copper mine

NASA Astrophysics Data System (ADS)

Liu, Xiaofei; Wang, Enyuan

2018-06-01

A rockburst is a dynamic disaster that occurs during underground excavation or mining which has been a serious threat to safety. Rockburst prediction and control are as important as any other underground engineering in deep mines. For this paper, we tested electromagnetic radiation (EMR) signals generated during the deformation and fracture of rock samples from a copper mine under uniaxial compression, tension, and cycle-loading experiments, analyzed the changes in the EMR intensity, pulse number, and frequency corresponding to the loading, and a high correlation between these EMR parameters and the applied loading was observed. EMR apparently reflects the deformation and fracture status to the loaded rock. Based on this experimental work, we invented the KBD5-type EMR monitor and used it to test EMR signals generated in the rock surrounding the Hongtoushan copper mine. From the test results, it is determined the responding characteristics of EMR signals generated by changes in mine-generated stresses and stress concentrations and it is proposed that this EMR monitoring method can be used to provide early warning for rockbursts.

Comparing predictions of extinction risk using models and subjective judgement

NASA Astrophysics Data System (ADS)

McCarthy, Michael A.; Keith, David; Tietjen, Justine; Burgman, Mark A.; Maunder, Mark; Master, Larry; Brook, Barry W.; Mace, Georgina; Possingham, Hugh P.; Medellin, Rodrigo; Andelman, Sandy; Regan, Helen; Regan, Tracey; Ruckelshaus, Mary

2004-10-01

Models of population dynamics are commonly used to predict risks in ecology, particularly risks of population decline. There is often considerable uncertainty associated with these predictions. However, alternatives to predictions based on population models have not been assessed. We used simulation models of hypothetical species to generate the kinds of data that might typically be available to ecologists and then invited other researchers to predict risks of population declines using these data. The accuracy of the predictions was assessed by comparison with the forecasts of the original model. The researchers used either population models or subjective judgement to make their predictions. Predictions made using models were only slightly more accurate than subjective judgements of risk. However, predictions using models tended to be unbiased, while subjective judgements were biased towards over-estimation. Psychology literature suggests that the bias of subjective judgements is likely to vary somewhat unpredictably among people, depending on their stake in the outcome. This will make subjective predictions more uncertain and less transparent than those based on models.

Gender dimorphic ACL strain in response to combined dynamic 3D knee joint loading: implications for ACL injury risk.

PubMed

Mizuno, Kiyonori; Andrish, Jack T; van den Bogert, Antonie J; McLean, Scott G

2009-12-01

While gender-based differences in knee joint anatomies/laxities are well documented, the potential for them to precipitate gender-dimorphic ACL loading and resultant injury risk has not been considered. To this end, we generated gender-specific models of ACL strain as a function of any six degrees of freedom (6DOF) knee joint load state via a combined cadaveric and analytical approach. Continuously varying joint forces and torques were applied to five male and five female cadaveric specimens and recorded along with synchronous knee flexion and ACL strain data. All data (approximately 10,000 samples) were submitted to specimen-specific regression analyses, affording ACL strain predictions as a function of the combined 6 DOF knee loads. Following individual model verifications, generalized gender-specific models were generated and subjected to 6 DOF external load scenarios consistent with both a clinical examination and a dynamic sports maneuver. The ensuing model-based strain predictions were subsequently examined for gender-based discrepancies. Male and female specimen-specific models predicted ACL strain within 0.51%+/-0.10% and 0.52%+/-0.07% of the measured data respectively, and explained more than 75% of the associated variance in each case. Predicted female ACL strains were also significantly larger than respective male values for both simulated 6 DOF load scenarios. Outcomes suggest that the female ACL will rupture in response to comparatively smaller external load applications. Future work must address the underlying anatomical/laxity contributions to knee joint mechanical and resultant ACL loading, ultimately affording prevention strategies that may cater to individual joint vulnerabilities.

RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis

PubMed Central

Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

2012-01-01

RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. Availability http://www.cemb.edu.pk/sw.html Abbreviations RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language. PMID:23055611

Hierarchical nonlinear dynamics of human attention.

PubMed

Rabinovich, Mikhail I; Tristan, Irma; Varona, Pablo

2015-08-01

Attention is the process of focusing mental resources on a specific cognitive/behavioral task. Such brain dynamics involves different partially overlapping brain functional networks whose interconnections change in time according to the performance stage, and can be stimulus-driven or induced by an intrinsically generated goal. The corresponding activity can be described by different families of spatiotemporal discrete patterns or sequential dynamic modes. Since mental resources are finite, attention modalities compete with each other at all levels of the hierarchy, from perception to decision making and behavior. Cognitive activity is a dynamical process and attention possesses some universal dynamical characteristics. Thus, it is time to apply nonlinear dynamical theory for the description and prediction of hierarchical attentional tasks. Such theory has to include the analyses of attentional control stability, the time cost of attention switching, the finite capacity of informational resources in the brain, and the normal and pathological bifurcations of attention sequential dynamics. In this paper we have integrated today's knowledge, models and results in these directions. Copyright © 2015 Elsevier Ltd. All rights reserved.

Dynamic modelling of microRNA regulation during mesenchymal stem cell differentiation.

PubMed

Weber, Michael; Sotoca, Ana M; Kupfer, Peter; Guthke, Reinhard; van Zoelen, Everardus J

2013-11-12

Network inference from gene expression data is a typical approach to reconstruct gene regulatory networks. During chondrogenic differentiation of human mesenchymal stem cells (hMSCs), a complex transcriptional network is active and regulates the temporal differentiation progress. As modulators of transcriptional regulation, microRNAs (miRNAs) play a critical role in stem cell differentiation. Integrated network inference aimes at determining interrelations between miRNAs and mRNAs on the basis of expression data as well as miRNA target predictions. We applied the NetGenerator tool in order to infer an integrated gene regulatory network. Time series experiments were performed to measure mRNA and miRNA abundances of TGF-beta1+BMP2 stimulated hMSCs. Network nodes were identified by analysing temporal expression changes, miRNA target gene predictions, time series correlation and literature knowledge. Network inference was performed using NetGenerator to reconstruct a dynamical regulatory model based on the measured data and prior knowledge. The resulting model is robust against noise and shows an optimal trade-off between fitting precision and inclusion of prior knowledge. It predicts the influence of miRNAs on the expression of chondrogenic marker genes and therefore proposes novel regulatory relations in differentiation control. By analysing the inferred network, we identified a previously unknown regulatory effect of miR-524-5p on the expression of the transcription factor SOX9 and the chondrogenic marker genes COL2A1, ACAN and COL10A1. Genome-wide exploration of miRNA-mRNA regulatory relationships is a reasonable approach to identify miRNAs which have so far not been associated with the investigated differentiation process. The NetGenerator tool is able to identify valid gene regulatory networks on the basis of miRNA and mRNA time series data.

Coupled in silico platform: Computational fluid dynamics (CFD) and physiologically-based pharmacokinetic (PBPK) modelling.

PubMed

Vulović, Aleksandra; Šušteršič, Tijana; Cvijić, Sandra; Ibrić, Svetlana; Filipović, Nenad

2018-02-15

One of the critical components of the respiratory drug delivery is the manner in which the inhaled aerosol is deposited in respiratory tract compartments. Depending on formulation properties, device characteristics and breathing pattern, only a certain fraction of the dose will reach the target site in the lungs, while the rest of the drug will deposit in the inhalation device or in the mouth-throat region. The aim of this study was to link the Computational fluid dynamics (CFD) with physiologically-based pharmacokinetic (PBPK) modelling in order to predict aerolisolization of different dry powder formulations, and estimate concomitant in vivo deposition and absorption of amiloride hydrochloride. Drug physicochemical properties were experimentally determined and used as inputs for the CFD simulations of particle flow in the generated 3D geometric model of Aerolizer® dry powder inhaler (DPI). CFD simulations were used to simulate air flow through Aerolizer® inhaler and Discrete Phase Method (DPM) was used to simulate aerosol particles deposition within the fluid domain. The simulated values for the percent emitted dose were comparable to the values obtained using Andersen cascade impactor (ACI). However, CFD predictions indicated that aerosolized DPI have smaller particle size and narrower size distribution than assumed based on ACI measurements. Comparison with the literature in vivo data revealed that the constructed drug-specific PBPK model was able to capture amiloride absorption pattern following oral and inhalation administration. The PBPK simulation results, based on the CFD generated particle distribution data as input, illustrated the influence of formulation properties on the expected drug plasma concentration profiles. The model also predicted the influence of potential changes in physiological parameters on the extent of inhaled amiloride absorption. Overall, this study demonstrated the potential of the combined CFD-PBPK approach to model inhaled drug bioperformance, and suggested that CFD generated results might serve as input for the prediction of drug deposition pattern in vivo. Copyright © 2017 Elsevier B.V. All rights reserved.

Median regression spline modeling of longitudinal FEV1 measurements in cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) patients.

PubMed

Conrad, Douglas J; Bailey, Barbara A; Hardie, Jon A; Bakke, Per S; Eagan, Tomas M L; Aarli, Bernt B

2017-01-01

Clinical phenotyping, therapeutic investigations as well as genomic, airway secretion metabolomic and metagenomic investigations can benefit from robust, nonlinear modeling of FEV1 in individual subjects. We demonstrate the utility of measuring FEV1 dynamics in representative cystic fibrosis (CF) and chronic obstructive pulmonary disease (COPD) populations. Individual FEV1 data from CF and COPD subjects were modeled by estimating median regression splines and their predicted first and second derivatives. Classes were created from variables that capture the dynamics of these curves in both cohorts. Nine FEV1 dynamic variables were identified from the splines and their predicted derivatives in individuals with CF (n = 177) and COPD (n = 374). Three FEV1 dynamic classes (i.e. stable, intermediate and hypervariable) were generated and described using these variables from both cohorts. In the CF cohort, the FEV1 hypervariable class (HV) was associated with a clinically unstable, female-dominated phenotypes while stable FEV1 class (S) individuals were highly associated with the male-dominated milder clinical phenotype. In the COPD cohort, associations were found between the FEV1 dynamic classes, the COPD GOLD grades, with exacerbation frequency and symptoms. Nonlinear modeling of FEV1 with splines provides new insights and is useful in characterizing CF and COPD clinical phenotypes.

Contributions of Dynamic Systems Theory to Cognitive Development

PubMed Central

Spencer, John P.; Austin, Andrew; Schutte, Anne R.

2015-01-01

This paper examines the contributions of dynamic systems theory to the field of cognitive development, focusing on modeling using dynamic neural fields. A brief overview highlights the contributions of dynamic systems theory and the central concepts of dynamic field theory (DFT). We then probe empirical predictions and findings generated by DFT around two examples—the DFT of infant perseverative reaching that explains the Piagetian A-not-B error, and the DFT of spatial memory that explain changes in spatial cognition in early development. A systematic review of the literature around these examples reveals that computational modeling is having an impact on empirical research in cognitive development; however, this impact does not extend to neural and clinical research. Moreover, there is a tendency for researchers to interpret models narrowly, anchoring them to specific tasks. We conclude on an optimistic note, encouraging both theoreticians and experimentalists to work toward a more theory-driven future. PMID:26052181

Frequency combs with weakly lasing exciton-polariton condensates.

PubMed

Rayanov, K; Altshuler, B L; Rubo, Y G; Flach, S

2015-05-15

We predict the spontaneous modulated emission from a pair of exciton-polariton condensates due to coherent (Josephson) and dissipative coupling. We show that strong polariton-polariton interaction generates complex dynamics in the weak-lasing domain way beyond Hopf bifurcations. As a result, the exciton-polariton condensates exhibit self-induced oscillations and emit an equidistant frequency comb light spectrum. A plethora of possible emission spectra with asymmetric peak distributions appears due to spontaneously broken time-reversal symmetry. The lasing dynamics is affected by the shot noise arising from the influx of polaritons. That results in a complex inhomogeneous line broadening.

Prediction of narrow N* and {Lambda}* with hidden charm

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

Wu Jiajun; Departamento de Fisica Teorica and IFIC, Centro Mixto Universidad de Valencia-CSIC, Institutos de Investigacion de Paterna, Aptdo. 22085, 46071 Valencia; Molina, R.

2011-10-24

The interaction between various charmed mesons and charmed baryons, such as D-bar{Sigma}{sub c}-D-bar{Lambda}{sub c}, D-bar*{Sigma}{sub c}-D-bar*{Lambda}{sub c}, and related strangeness channels, are studied within the framework of the coupled channel unitary approach with the local hidden gauge formalism. Six narrow N* and {Lambda}* resonances are dynamically generated with mass above 4 GeV and width smaller than 100 MeV. These predicted new resonances definitely cannot be accommodated by quark models with three constituent quarks. We make estimates of production cross sections of these predicted resonances in p-barp collisions for PANDA at the forthcoming FAIR facility.

Extended active disturbance rejection controller

NASA Technical Reports Server (NTRS)

Tian, Gang (Inventor); Gao, Zhiqiang (Inventor)

2012-01-01

Multiple designs, systems, methods and processes for controlling a system or plant using an extended active disturbance rejection control (ADRC) based controller are presented. The extended ADRC controller accepts sensor information from the plant. The sensor information is used in conjunction with an extended state observer in combination with a predictor that estimates and predicts the current state of the plant and a co-joined estimate of the system disturbances and system dynamics. The extended state observer estimates and predictions are used in conjunction with a control law that generates an input to the system based in part on the extended state observer estimates and predictions as well as a desired trajectory for the plant to follow.

Extended Active Disturbance Rejection Controller

NASA Technical Reports Server (NTRS)

Gao, Zhiqiang (Inventor); Tian, Gang (Inventor)

2016-01-01

Multiple designs, systems, methods and processes for controlling a system or plant using an extended active disturbance rejection control (ADRC) based controller are presented. The extended ADRC controller accepts sensor information from the plant. The sensor information is used in conjunction with an extended state observer in combination with a predictor that estimates and predicts the current state of the plant and a co-joined estimate of the system disturbances and system dynamics. The extended state observer estimates and predictions are used in conjunction with a control law that generates an input to the system based in part on the extended state observer estimates and predictions as well as a desired trajectory for the plant to follow.

Extended Active Disturbance Rejection Controller

NASA Technical Reports Server (NTRS)

Tian, Gang (Inventor); Gao, Zhiqiang (Inventor)

2014-01-01

Multiple designs, systems, methods and processes for controlling a system or plant using an extended active disturbance rejection control (ADRC) based controller are presented. The extended ADRC controller accepts sensor information from the plant. The sensor information is used in conjunction with an extended state observer in combination with a predictor that estimates and predicts the current state of the plant and a co-joined estimate of the system disturbances and system dynamics. The extended state observer estimates and predictions are used in conjunction with a control law that generates an input to the system based in part on the extended state observer estimates and predictions as well as a desired trajectory for the plant to follow.

Mesoscale atmospheric modeling for emergency response

NASA Astrophysics Data System (ADS)

Osteen, B. L.; Fast, J. D.

Atmospheric transport models for emergency response have traditionally utilized meteorological fields interpolated from sparse data to predict contaminant transport. Often these fields are adjusted to satisfy constraints derived from the governing equations of geophysical fluid dynamics, e.g. mass continuity. Gaussian concentration distributions or stochastic models are then used to represent turbulent diffusion of a contaminant in the diagnosed meteorological fields. The popularity of these models derives from their relative simplicity, ability to make reasonable short-term predictions, and, most important, execution speed. The ability to generate a transport prediction for an accidental release from the Savannah River Site in a time frame which will allow protective action to be taken is essential in an emergency response operation.

Assessing predictability of a hydrological stochastic-dynamical system

NASA Astrophysics Data System (ADS)

Gelfan, Alexander

2014-05-01

The water cycle includes the processes with different memory that creates potential for predictability of hydrological system based on separating its long and short memory components and conditioning long-term prediction on slower evolving components (similar to approaches in climate prediction). In the face of the Panta Rhei IAHS Decade questions, it is important to find a conceptual approach to classify hydrological system components with respect to their predictability, define predictable/unpredictable patterns, extend lead-time and improve reliability of hydrological predictions based on the predictable patterns. Representation of hydrological systems as the dynamical systems subjected to the effect of noise (stochastic-dynamical systems) provides possible tool for such conceptualization. A method has been proposed for assessing predictability of hydrological system caused by its sensitivity to both initial and boundary conditions. The predictability is defined through a procedure of convergence of pre-assigned probabilistic measure (e.g. variance) of the system state to stable value. The time interval of the convergence, that is the time interval during which the system losses memory about its initial state, defines limit of the system predictability. The proposed method was applied to assess predictability of soil moisture dynamics in the Nizhnedevitskaya experimental station (51.516N; 38.383E) located in the agricultural zone of the central European Russia. A stochastic-dynamical model combining a deterministic one-dimensional model of hydrothermal regime of soil with a stochastic model of meteorological inputs was developed. The deterministic model describes processes of coupled heat and moisture transfer through unfrozen/frozen soil and accounts for the influence of phase changes on water flow. The stochastic model produces time series of daily meteorological variables (precipitation, air temperature and humidity), whose statistical properties are similar to those of the corresponding series of the actual data measured at the station. Beginning from the initial conditions and being forced by Monte-Carlo generated synthetic meteorological series, the model simulated diverging trajectories of soil moisture characteristics (water content of soil column, moisture of different soil layers, etc.). Limit of predictability of the specific characteristic was determined through time of stabilization of variance of the characteristic between the trajectories, as they move away from the initial state. Numerical experiments were carried out with the stochastic-dynamical model to analyze sensitivity of the soil moisture predictability assessments to uncertainty in the initial conditions, to determine effects of the soil hydraulic properties and processes of soil freezing on the predictability. It was found, particularly, that soil water content predictability is sensitive to errors in the initial conditions and strongly depends on the hydraulic properties of soil under both unfrozen and frozen conditions. Even if the initial conditions are "well-established", the assessed predictability of water content of unfrozen soil does not exceed 30-40 days, while for frozen conditions it may be as long as 3-4 months. The latter creates opportunity for utilizing the autumn water content of soil as the predictor for spring snowmelt runoff in the region under consideration.

Eco-evolutionary feedbacks, adaptive dynamics and evolutionary rescue theory

PubMed Central

Ferriere, Regis; Legendre, Stéphane

2013-01-01

Adaptive dynamics theory has been devised to account for feedbacks between ecological and evolutionary processes. Doing so opens new dimensions to and raises new challenges about evolutionary rescue. Adaptive dynamics theory predicts that successive trait substitutions driven by eco-evolutionary feedbacks can gradually erode population size or growth rate, thus potentially raising the extinction risk. Even a single trait substitution can suffice to degrade population viability drastically at once and cause ‘evolutionary suicide’. In a changing environment, a population may track a viable evolutionary attractor that leads to evolutionary suicide, a phenomenon called ‘evolutionary trapping’. Evolutionary trapping and suicide are commonly observed in adaptive dynamics models in which the smooth variation of traits causes catastrophic changes in ecological state. In the face of trapping and suicide, evolutionary rescue requires that the population overcome evolutionary threats generated by the adaptive process itself. Evolutionary repellors play an important role in determining how variation in environmental conditions correlates with the occurrence of evolutionary trapping and suicide, and what evolutionary pathways rescue may follow. In contrast with standard predictions of evolutionary rescue theory, low genetic variation may attenuate the threat of evolutionary suicide and small population sizes may facilitate escape from evolutionary traps. PMID:23209163

Myosin II Dynamics during Embryo Morphogenesis

NASA Astrophysics Data System (ADS)

Kasza, Karen

2013-03-01

During embryonic morphogenesis, the myosin II motor protein generates forces that help to shape tissues, organs, and the overall body form. In one dramatic example in the Drosophila melanogaster embryo, the epithelial tissue that will give rise to the body of the adult animal elongates more than two-fold along the head-to-tail axis in less than an hour. This elongation is accomplished primarily through directional rearrangements of cells within the plane of the tissue. Just prior to elongation, polarized assemblies of myosin II accumulate perpendicular to the elongation axis. The contractile forces generated by myosin activity orient cell movements along a common axis, promoting local cell rearrangements that contribute to global tissue elongation. The molecular and mechanical mechanisms by which myosin drives this massive change in embryo shape are poorly understood. To investigate these mechanisms, we generated a collection of transgenic flies expressing variants of myosin II with altered motor function and regulation. We found that variants that are predicted to have increased myosin activity cause defects in tissue elongation. Using biophysical approaches, we found that these myosin variants also have decreased turnover dynamics within cells. To explore the mechanisms by which molecular-level myosin dynamics are translated into tissue-level elongation, we are using time-lapse confocal imaging to observe cell movements in embryos with altered myosin activity. We are utilizing computational approaches to quantify the dynamics and directionality of myosin localization and cell rearrangements. These studies will help elucidate how myosin-generated forces control cell movements within tissues. This work is in collaboration with J. Zallen at the Sloan-Kettering Institute.

Ensemble Kalman Filter for Dynamic State Estimation of Power Grids Stochastically Driven by Time-correlated Mechanical Input Power

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

Rosenthal, William Steven; Tartakovsky, Alex; Huang, Zhenyu

State and parameter estimation of power transmission networks is important for monitoring power grid operating conditions and analyzing transient stability. Wind power generation depends on fluctuating input power levels, which are correlated in time and contribute to uncertainty in turbine dynamical models. The ensemble Kalman filter (EnKF), a standard state estimation technique, uses a deterministic forecast and does not explicitly model time-correlated noise in parameters such as mechanical input power. However, this uncertainty affects the probability of fault-induced transient instability and increased prediction bias. Here a novel approach is to model input power noise with time-correlated stochastic fluctuations, and integratemore » them with the network dynamics during the forecast. While the EnKF has been used to calibrate constant parameters in turbine dynamical models, the calibration of a statistical model for a time-correlated parameter has not been investigated. In this study, twin experiments on a standard transmission network test case are used to validate our time-correlated noise model framework for state estimation of unsteady operating conditions and transient stability analysis, and a methodology is proposed for the inference of the mechanical input power time-correlation length parameter using time-series data from PMUs monitoring power dynamics at generator buses.« less

Ensemble Kalman Filter for Dynamic State Estimation of Power Grids Stochastically Driven by Time-correlated Mechanical Input Power

DOE PAGES

Rosenthal, William Steven; Tartakovsky, Alex; Huang, Zhenyu

2017-10-31

State and parameter estimation of power transmission networks is important for monitoring power grid operating conditions and analyzing transient stability. Wind power generation depends on fluctuating input power levels, which are correlated in time and contribute to uncertainty in turbine dynamical models. The ensemble Kalman filter (EnKF), a standard state estimation technique, uses a deterministic forecast and does not explicitly model time-correlated noise in parameters such as mechanical input power. However, this uncertainty affects the probability of fault-induced transient instability and increased prediction bias. Here a novel approach is to model input power noise with time-correlated stochastic fluctuations, and integratemore » them with the network dynamics during the forecast. While the EnKF has been used to calibrate constant parameters in turbine dynamical models, the calibration of a statistical model for a time-correlated parameter has not been investigated. In this study, twin experiments on a standard transmission network test case are used to validate our time-correlated noise model framework for state estimation of unsteady operating conditions and transient stability analysis, and a methodology is proposed for the inference of the mechanical input power time-correlation length parameter using time-series data from PMUs monitoring power dynamics at generator buses.« less

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.

Real-time stylistic prediction for whole-body human motions.

PubMed

Matsubara, Takamitsu; Hyon, Sang-Ho; Morimoto, Jun

2012-01-01

The ability to predict human motion is crucial in several contexts such as human tracking by computer vision and the synthesis of human-like computer graphics. Previous work has focused on off-line processes with well-segmented data; however, many applications such as robotics require real-time control with efficient computation. In this paper, we propose a novel approach called real-time stylistic prediction for whole-body human motions to satisfy these requirements. This approach uses a novel generative model to represent a whole-body human motion including rhythmic motion (e.g., walking) and discrete motion (e.g., jumping). The generative model is composed of a low-dimensional state (phase) dynamics and a two-factor observation model, allowing it to capture the diversity of motion styles in humans. A real-time adaptation algorithm was derived to estimate both state variables and style parameter of the model from non-stationary unlabeled sequential observations. Moreover, with a simple modification, the algorithm allows real-time adaptation even from incomplete (partial) observations. Based on the estimated state and style, a future motion sequence can be accurately predicted. In our implementation, it takes less than 15 ms for both adaptation and prediction at each observation. Our real-time stylistic prediction was evaluated for human walking, running, and jumping behaviors. Copyright © 2011 Elsevier Ltd. All rights reserved.

Mixed models and reduction method for dynamic analysis of anisotropic shells

NASA Technical Reports Server (NTRS)

Noor, A. K.; Peters, J. M.

1985-01-01

A time-domain computational procedure is presented for predicting the dynamic response of laminated anisotropic shells. The two key elements of the procedure are: (1) use of mixed finite element models having independent interpolation (shape) functions for stress resultants and generalized displacements for the spatial discretization of the shell, with the stress resultants allowed to be discontinuous at interelement boundaries; and (2) use of a dynamic reduction method, with the global approximation vectors consisting of the static solution and an orthogonal set of Lanczos vectors. The dynamic reduction is accomplished by means of successive application of the finite element method and the classical Rayleigh-Ritz technique. The finite element method is first used to generate the global approximation vectors. Then the Rayleigh-Ritz technique is used to generate a reduced system of ordinary differential equations in the amplitudes of these modes. The temporal integration of the reduced differential equations is performed by using an explicit half-station central difference scheme (Leap-frog method). The effectiveness of the proposed procedure is demonstrated by means of a numerical example and its advantages over reduction methods used with the displacement formulation are discussed.

Character convergence under competition for nutritionally essential resources.

PubMed

Fox, Jeremy W; Vasseur, David A

2008-11-01

Resource competition is thought to drive divergence in resource use traits (character displacement) by generating selection favoring individuals able to use resources unavailable to others. However, this picture assumes nutritionally substitutable resources (e.g., different prey species). When species compete for nutritionally essential resources (e.g., different nutrients), theory predicts that selection drives character convergence. We used models of two species competing for two essential resources to address several issues not considered by existing theory. The models incorporated either slow evolutionary change in resource use traits or fast physiological or behavioral change. We report four major results. First, competition always generates character convergence, but differences in resource requirements prevent competitors from evolving identical resource use traits. Second, character convergence promotes coexistence. Competing species always attain resource use traits that allow coexistence, and adaptive trait change stabilizes the ecological equilibrium. In contrast, adaptation in allopatry never preadapts species to coexist in sympatry. Third, feedbacks between ecological dynamics and trait dynamics lead to surprising dynamical trajectories such as transient divergence in resource use traits followed by subsequent convergence. Fourth, under sufficiently slow trait change, ecological dynamics often drive one of the competitors to near extinction, which would prevent realization of long-term character convergence in practice.

Ensemble forecast of human West Nile virus cases and mosquito infection rates

NASA Astrophysics Data System (ADS)

Defelice, Nicholas B.; Little, Eliza; Campbell, Scott R.; Shaman, Jeffrey

2017-02-01

West Nile virus (WNV) is now endemic in the continental United States; however, our ability to predict spillover transmission risk and human WNV cases remains limited. Here we develop a model depicting WNV transmission dynamics, which we optimize using a data assimilation method and two observed data streams, mosquito infection rates and reported human WNV cases. The coupled model-inference framework is then used to generate retrospective ensemble forecasts of historical WNV outbreaks in Long Island, New York for 2001-2014. Accurate forecasts of mosquito infection rates are generated before peak infection, and >65% of forecasts accurately predict seasonal total human WNV cases up to 9 weeks before the past reported case. This work provides the foundation for implementation of a statistically rigorous system for real-time forecast of seasonal outbreaks of WNV.

Ensemble forecast of human West Nile virus cases and mosquito infection rates.

PubMed

DeFelice, Nicholas B; Little, Eliza; Campbell, Scott R; Shaman, Jeffrey

2017-02-24

West Nile virus (WNV) is now endemic in the continental United States; however, our ability to predict spillover transmission risk and human WNV cases remains limited. Here we develop a model depicting WNV transmission dynamics, which we optimize using a data assimilation method and two observed data streams, mosquito infection rates and reported human WNV cases. The coupled model-inference framework is then used to generate retrospective ensemble forecasts of historical WNV outbreaks in Long Island, New York for 2001-2014. Accurate forecasts of mosquito infection rates are generated before peak infection, and >65% of forecasts accurately predict seasonal total human WNV cases up to 9 weeks before the past reported case. This work provides the foundation for implementation of a statistically rigorous system for real-time forecast of seasonal outbreaks of WNV.

The Generation of Harmonic Distortion and Distortion Products in a Computational Model of the Cochlea

NASA Astrophysics Data System (ADS)

Meaud, Julien; Li, Yizeng; Grosh, Karl

2011-11-01

It is generally agreed that the nonlinear response of the cochlea is due to the forward transduction of the outer hair cell (OHC) hair bundle (HB) and subsequent alteration of the active force applied to the cochlear structures, including the basilar membrane (BM). A mechanical-acoustical-electrical model of the cochlea with three-dimensional fluid representation, and feedback from OHC somatic motility coupled to nonlinear HB mechanotransduction is used to predict nonlinear distortion of the BM response to acoustic stimulus. An efficient alternating frequency time scheme is implemented to solve for the nonlinear stationary dynamics of the cochlea. The model is used to predict the location of maximum generation of nonlinear distortion during pure tone and two-tone stimulation as well as the propagation of the distortion components on the BM.

ARPA-E: Advancing the Electric Grid

ScienceCinema

Lemmon, John; Ruiz, Pablo; Sommerer, Tim; Aziz, Michael

2018-06-07

The electric grid was designed with the assumption that all energy generation sources would be relatively controllable, and grid operators would always be able to predict when and where those sources would be located. With the addition of renewable energy sources like wind and solar, which can be installed faster than traditional generation technologies, this is no longer the case. Furthermore, the fact that renewable energy sources are imperfectly predictable means that the grid has to adapt in real-time to changing patterns of power flow. We need a dynamic grid that is far more flexible. This video highlights three ARPA-E-funded approaches to improving the grid's flexibility: topology control software from Boston University that optimizes power flow, gas tube switches from General Electric that provide efficient power conversion, and flow batteries from Harvard University that offer grid-scale energy storage.

Tectonic predictions with mantle convection models

NASA Astrophysics Data System (ADS)

Coltice, Nicolas; Shephard, Grace E.

2018-04-01

Over the past 15 yr, numerical models of convection in Earth's mantle have made a leap forward: they can now produce self-consistent plate-like behaviour at the surface together with deep mantle circulation. These digital tools provide a new window into the intimate connections between plate tectonics and mantle dynamics, and can therefore be used for tectonic predictions, in principle. This contribution explores this assumption. First, initial conditions at 30, 20, 10 and 0 Ma are generated by driving a convective flow with imposed plate velocities at the surface. We then compute instantaneous mantle flows in response to the guessed temperature fields without imposing any boundary conditions. Plate boundaries self-consistently emerge at correct locations with respect to reconstructions, except for small plates close to subduction zones. As already observed for other types of instantaneous flow calculations, the structure of the top boundary layer and upper-mantle slab is the dominant character that leads to accurate predictions of surface velocities. Perturbations of the rheological parameters have little impact on the resulting surface velocities. We then compute fully dynamic model evolution from 30 and 10 to 0 Ma, without imposing plate boundaries or plate velocities. Contrary to instantaneous calculations, errors in kinematic predictions are substantial, although the plate layout and kinematics in several areas remain consistent with the expectations for the Earth. For these calculations, varying the rheological parameters makes a difference for plate boundary evolution. Also, identified errors in initial conditions contribute to first-order kinematic errors. This experiment shows that the tectonic predictions of dynamic models over 10 My are highly sensitive to uncertainties of rheological parameters and initial temperature field in comparison to instantaneous flow calculations. Indeed, the initial conditions and the rheological parameters can be good enough for an accurate prediction of instantaneous flow, but not for a prediction after 10 My of evolution. Therefore, inverse methods (sequential or data assimilation methods) using short-term fully dynamic evolution that predict surface kinematics are promising tools for a better understanding of the state of the Earth's mantle.

Evolutionary models of interstellar chemistry

NASA Technical Reports Server (NTRS)

Prasad, Sheo S.

1987-01-01

The goal of evolutionary models of interstellar chemistry is to understand how interstellar clouds came to be the way they are, how they will change with time, and to place them in an evolutionary sequence with other celestial objects such as stars. An improved Mark II version of an earlier model of chemistry in dynamically evolving clouds is presented. The Mark II model suggests that the conventional elemental C/O ratio less than one can explain the observed abundances of CI and the nondetection of O2 in dense clouds. Coupled chemical-dynamical models seem to have the potential to generate many observable discriminators of the evolutionary tracks. This is exciting, because, in general, purely dynamical models do not yield enough verifiable discriminators of the predicted tracks.

Microtubule dynamics in cell division: exploring living cells with polarized light microscopy.

PubMed

Inoué, Shinya

2008-01-01

This Perspective is an account of my early experience while I studied the dynamic organization and behavior of the mitotic spindle and its submicroscopic filaments using polarized light microscopy. The birefringence of spindle filaments in normally dividing plant and animal cells, and those treated by various agents, revealed (a) the reality of spindle fibers and fibrils in healthy living cells; (b) the labile, dynamic nature of the molecular filaments making up the spindle fibers; (c) the mode of fibrogenesis and action of orienting centers; and (d) force-generating properties based on the disassembly and assembly of the fibrils. These studies, which were carried out directly on living cells using improved polarizing microscopes, in fact predicted the reversible assembly properties of microtubules.

Direct numerical simulation of axisymmetric turbulence

NASA Astrophysics Data System (ADS)

Qu, Bo; Bos, Wouter J. T.; Naso, Aurore

2017-09-01

The dynamics of decaying, strictly axisymmetric, incompressible turbulence is investigated using direct numerical simulations. It is found that the angular momentum is a robust invariant of the system. It is further shown that long-lived coherent structures are generated by the flow. These structures can be associated with stationary solutions of the Euler equations. The structures obey relations in agreement with predictions from selective decay principles, compatible with the decay laws of the system. Two different types of decay scenarios are highlighted. The first case results in a quasi-two-dimensional flow with a dynamical behavior in the poloidal plane similar to freely decaying two-dimensional turbulence. In a second regime, the long-time dynamics is dominated by a single three-dimensional mode.

Investigation of propagation dynamics of truncated vector vortex beams.

PubMed

Srinivas, P; Perumangatt, C; Lal, Nijil; Singh, R P; Srinivasan, B

2018-06-01

In this Letter, we experimentally investigate the propagation dynamics of truncated vector vortex beams generated using a Sagnac interferometer. Upon focusing, the truncated vector vortex beam is found to regain its original intensity structure within the Rayleigh range. In order to explain such behavior, the propagation dynamics of a truncated vector vortex beam is simulated by decomposing it into the sum of integral charge beams with associated complex weights. We also show that the polarization of the truncated composite vector vortex beam is preserved all along the propagation axis. The experimental observations are consistent with theoretical predictions based on previous literature and are in good agreement with our simulation results. The results hold importance as vector vortex modes are eigenmodes of the optical fiber.

Patterns of waste generation: A gradient boosting model for short-term waste prediction in New York City.

PubMed

Johnson, Nicholas E; Ianiuk, Olga; Cazap, Daniel; Liu, Linglan; Starobin, Daniel; Dobler, Gregory; Ghandehari, Masoud

2017-04-01

Historical municipal solid waste (MSW) collection data supplied by the New York City Department of Sanitation (DSNY) was used in conjunction with other datasets related to New York City to forecast municipal solid waste generation across the city. Spatiotemporal tonnage data from the DSNY was combined with external data sets, including the Longitudinal Employer Household Dynamics data, the American Community Survey, the New York City Department of Finance's Primary Land Use and Tax Lot Output data, and historical weather data to build a Gradient Boosting Regression Model. The model was trained on historical data from 2005 to 2011 and validation was performed both temporally and spatially. With this model, we are able to accurately (R2>0.88) forecast weekly MSW generation tonnages for each of the 232 geographic sections in NYC across three waste streams of refuse, paper and metal/glass/plastic. Importantly, the model identifies regularity of urban waste generation and is also able to capture very short timescale fluctuations associated to holidays, special events, seasonal variations, and weather related events. This research shows New York City's waste generation trends and the importance of comprehensive data collection (especially weather patterns) in order to accurately predict waste generation. Copyright © 2017. Published by Elsevier Ltd.

Structure and Relaxation in Solutions of Monoclonal Antibodies.

PubMed

Wang, Gang; Varga, Zsigmond; Hofmann, Jennifer; Zarraga, Isidro E; Swan, James W

2018-03-22

Reversible self-association of therapeutic antibodies is a key factor in high protein solution viscosities. In the present work, a coarse-grained computational model accounting for electrostatic, dispersion, and long-ranged hydrodynamic interactions of two model monoclonal antibodies is applied to understand the nature of self-association, predicting the solution microstructure and resulting transport properties of the solution. For the proteins investigated, the structure factor across a range of solution conditions shows quantitative agreement with neutron-scattering experiments. We observe a homogeneous, dynamical association of the antibodies with no evidence of phase separation. Calculations of self-diffusivity and viscosity from coarse-grained dynamic simulations show the appropriate trends with concentration but, respectively, over- and under-predict the experimentally measured values. By adding constraints to the self-associated clusters that rigidify them under flow, prediction of the transport properties is significantly improved with respect to experimental measurements. We hypothesize that these rigidity constraints are associated with missing degrees of freedom in the coarse-grained model resulting from patchy and heterogeneous interactions among coarse-grained domains. These results demonstrate how structural anisotropy and anisotropy of interactions generated by features at the 2-5 nm length scale in antibodies are sufficient to recover the dynamics and rheological properties of these important macromolecular solutions.

CEINMS: A toolbox to investigate the influence of different neural control solutions on the prediction of muscle excitation and joint moments during dynamic motor tasks.

PubMed

Pizzolato, Claudio; Lloyd, David G; Sartori, Massimo; Ceseracciu, Elena; Besier, Thor F; Fregly, Benjamin J; Reggiani, Monica

2015-11-05

Personalized neuromusculoskeletal (NMS) models can represent the neurological, physiological, and anatomical characteristics of an individual and can be used to estimate the forces generated inside the human body. Currently, publicly available software to calculate muscle forces are restricted to static and dynamic optimisation methods, or limited to isometric tasks only. We have created and made freely available for the research community the Calibrated EMG-Informed NMS Modelling Toolbox (CEINMS), an OpenSim plug-in that enables investigators to predict different neural control solutions for the same musculoskeletal geometry and measured movements. CEINMS comprises EMG-driven and EMG-informed algorithms that have been previously published and tested. It operates on dynamic skeletal models possessing any number of degrees of freedom and musculotendon units and can be calibrated to the individual to predict measured joint moments and EMG patterns. In this paper we describe the components of CEINMS and its integration with OpenSim. We then analyse how EMG-driven, EMG-assisted, and static optimisation neural control solutions affect the estimated joint moments, muscle forces, and muscle excitations, including muscle co-contraction. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.

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

NASA Astrophysics Data System (ADS)

Dongare, Avinash M.

2014-12-01

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

Three-dimensional data-tracking dynamic optimization simulations of human locomotion generated by direct collocation.

PubMed

Lin, Yi-Chung; Pandy, Marcus G

2017-07-05

The aim of this study was to perform full-body three-dimensional (3D) dynamic optimization simulations of human locomotion by driving a neuromusculoskeletal model toward in vivo measurements of body-segmental kinematics and ground reaction forces. Gait data were recorded from 5 healthy participants who walked at their preferred speeds and ran at 2m/s. Participant-specific data-tracking dynamic optimization solutions were generated for one stride cycle using direct collocation in tandem with an OpenSim-MATLAB interface. The body was represented as a 12-segment, 21-degree-of-freedom skeleton actuated by 66 muscle-tendon units. Foot-ground interaction was simulated using six contact spheres under each foot. The dynamic optimization problem was to find the set of muscle excitations needed to reproduce 3D measurements of body-segmental motions and ground reaction forces while minimizing the time integral of muscle activations squared. Direct collocation took on average 2.7±1.0h and 2.2±1.6h of CPU time, respectively, to solve the optimization problems for walking and running. Model-computed kinematics and foot-ground forces were in good agreement with corresponding experimental data while the calculated muscle excitation patterns were consistent with measured EMG activity. The results demonstrate the feasibility of implementing direct collocation on a detailed neuromusculoskeletal model with foot-ground contact to accurately and efficiently generate 3D data-tracking dynamic optimization simulations of human locomotion. The proposed method offers a viable tool for creating feasible initial guesses needed to perform predictive simulations of movement using dynamic optimization theory. The source code for implementing the model and computational algorithm may be downloaded at http://simtk.org/home/datatracking. Copyright © 2017 Elsevier Ltd. All rights reserved.

A Hybrid Approach To Tandem Cylinder Noise

NASA Technical Reports Server (NTRS)

Lockard, David P.

2004-01-01

Aeolian tone generation from tandem cylinders is predicted using a hybrid approach. A standard computational fluid dynamics (CFD) code is used to compute the unsteady flow around the cylinders, and the acoustics are calculated using the acoustic analogy. The CFD code is nominally second order in space and time and includes several turbulence models, but the SST k - omega model is used for most of the calculations. Significant variation is observed between laminar and turbulent cases, and with changes in the turbulence model. A two-dimensional implementation of the Ffowcs Williams-Hawkings (FW-H) equation is used to predict the far-field noise.

Theoretical predictions of vibration-rotation-tunneling dynamics of the weakly bound trimer (H 2O) 2HCl

NASA Astrophysics Data System (ADS)

Struniewicz, Cezary; Korona, Tatiana; Moszynski, Robert; Milet, Anne

2001-08-01

In this Letter we report a theoretical study of the vibration-rotation-tunneling (VRT) states of the (H 2O) 2HCl trimer. Five degrees of freedom are considered: two angles corresponding to the torsional (flipping) motions of the free, non-hydrogen-bonded, hydrogen atoms in the complex, and three angles describing the overall rotation of the trimer in the space. A two-dimensional potential energy surface is generated ab initio by symmetry-adapted perturbation theory (SAPT). Tunneling splittings, frequencies of the intermolecular vibrations, and vibrational line strengths of spectroscopic transitions are predicted.

Surface flux and ocean heat transport convergence contributions to seasonal and interannual variations of ocean heat content

NASA Astrophysics Data System (ADS)

Roberts, C. D.; Palmer, M. D.; Allan, R. P.; Desbruyeres, D. G.; Hyder, P.; Liu, C.; Smith, D.

2017-01-01

We present an observation-based heat budget analysis for seasonal and interannual variations of ocean heat content (H) in the mixed layer (Hmld) and full-depth ocean (Htot). Surface heat flux and ocean heat content estimates are combined using a novel Kalman smoother-based method. Regional contributions from ocean heat transport convergences are inferred as a residual and the dominant drivers of Hmld and Htot are quantified for seasonal and interannual time scales. We find that non-Ekman ocean heat transport processes dominate Hmld variations in the equatorial oceans and regions of strong ocean currents and substantial eddy activity. In these locations, surface temperature anomalies generated by ocean dynamics result in turbulent flux anomalies that drive the overlying atmosphere. In addition, we find large regions of the Atlantic and Pacific oceans where heat transports combine with local air-sea fluxes to generate mixed layer temperature anomalies. In all locations, except regions of deep convection and water mass transformation, interannual variations in Htot are dominated by the internal rearrangement of heat by ocean dynamics rather than the loss or addition of heat at the surface. Our analysis suggests that, even in extratropical latitudes, initialization of ocean dynamical processes could be an important source of skill for interannual predictability of Hmld and Htot. Furthermore, we expect variations in Htot (and thus thermosteric sea level) to be more predictable than near surface temperature anomalies due to the increased importance of ocean heat transport processes for full-depth heat budgets.

Simulated GOLD Observations of Atmospheric Waves

NASA Astrophysics Data System (ADS)

Correira, J.; Evans, J. S.; Lumpe, J. D.; Rusch, D. W.; Chandran, A.; Eastes, R.; Codrescu, M.

2016-12-01

The Global-scale Observations of the Limb and Disk (GOLD) mission will measure structures in the Earth's airglow layer due to dynamical forcing by vertically and horizontally propagating waves. These measurements focus on global-scale structures, including compositional and temperature responses resulting from dynamical forcing. Daytime observations of far-UV emissions by GOLD will be used to generate two-dimensional maps of the ratio of atomic oxygen and molecular nitrogen column densities (ΣO/N2 ) as well as neutral temperature that provide signatures of large-scale spatial structure. In this presentation, we use simulations to demonstrate GOLD's capability to deduce periodicities and spatial dimensions of large-scale waves from the spatial and temporal evolution observed in composition and temperature maps. Our simulations include sophisticated forward modeling of the upper atmospheric airglow that properly accounts for anisotropy in neutral and ion composition, temperature, and solar illumination. Neutral densities and temperatures used in the simulations are obtained from global circulation and climatology models that have been perturbed by propagating waves with a range of amplitudes, periods, and sources of excitation. Modeling of airglow emission and predictions of ΣO/N2 and neutral temperatures are performed with the Atmospheric Ultraviolet Radiance Integrated Code (AURIC) and associated derived product algorithms. Predicted structure in ΣO/N2 and neutral temperature due to dynamical forcing by propagating waves is compared to existing observations. Realistic GOLD Level 2 data products are generated from simulated airglow emission using algorithm code that will be implemented operationally at the GOLD Science Data Center.

Emergent multicellular life cycles in filamentous bacteria owing to density-dependent population dynamics.

PubMed

Rossetti, Valentina; Filippini, Manuela; Svercel, Miroslav; Barbour, A D; Bagheri, Homayoun C

2011-12-07

Filamentous bacteria are the oldest and simplest known multicellular life forms. By using computer simulations and experiments that address cell division in a filamentous context, we investigate some of the ecological factors that can lead to the emergence of a multicellular life cycle in filamentous life forms. The model predicts that if cell division and death rates are dependent on the density of cells in a population, a predictable cycle between short and long filament lengths is produced. During exponential growth, there will be a predominance of multicellular filaments, while at carrying capacity, the population converges to a predominance of short filaments and single cells. Model predictions are experimentally tested and confirmed in cultures of heterotrophic and phototrophic bacterial species. Furthermore, by developing a formulation of generation time in bacterial populations, it is shown that changes in generation time can alter length distributions. The theory predicts that given the same population growth curve and fitness, species with longer generation times have longer filaments during comparable population growth phases. Characterization of the environmental dependence of morphological properties such as length, and the number of cells per filament, helps in understanding the pre-existing conditions for the evolution of developmental cycles in simple multicellular organisms. Moreover, the theoretical prediction that strains with the same fitness can exhibit different lengths at comparable growth phases has important implications. It demonstrates that differences in fitness attributed to morphology are not the sole explanation for the evolution of life cycles dominated by multicellularity.

Frontal Theta Reflects Uncertainty and Unexpectedness during Exploration and Exploitation

PubMed Central

Figueroa, Christina M.; Cohen, Michael X; Frank, Michael J.

2012-01-01

In order to understand the exploitation/exploration trade-off in reinforcement learning, previous theoretical and empirical accounts have suggested that increased uncertainty may precede the decision to explore an alternative option. To date, the neural mechanisms that support the strategic application of uncertainty-driven exploration remain underspecified. In this study, electroencephalography (EEG) was used to assess trial-to-trial dynamics relevant to exploration and exploitation. Theta-band activities over middle and lateral frontal areas have previously been implicated in EEG studies of reinforcement learning and strategic control. It was hypothesized that these areas may interact during top-down strategic behavioral control involved in exploratory choices. Here, we used a dynamic reward–learning task and an associated mathematical model that predicted individual response times. This reinforcement-learning model generated value-based prediction errors and trial-by-trial estimates of exploration as a function of uncertainty. Mid-frontal theta power correlated with unsigned prediction error, although negative prediction errors had greater power overall. Trial-to-trial variations in response-locked frontal theta were linearly related to relative uncertainty and were larger in individuals who used uncertainty to guide exploration. This finding suggests that theta-band activities reflect prefrontal-directed strategic control during exploratory choices. PMID:22120491

Predictive rhythmic tapping to isochronous and tempo changing metronomes in the nonhuman primate.

PubMed

Gámez, Jorge; Yc, Karyna; Ayala, Yaneri A; Dotov, Dobromir; Prado, Luis; Merchant, Hugo

2018-04-30

Beat entrainment is the ability to entrain one's movements to a perceived periodic stimulus, such as a metronome or a pulse in music. Humans have a capacity to predictively respond to a periodic pulse and to dynamically adjust their movement timing to match the varying music tempos. Previous studies have shown that monkeys share some of the human capabilities for rhythmic entrainment, such as tapping regularly at the period of isochronous stimuli. However, it is still unknown whether monkeys can predictively entrain to dynamic tempo changes like humans. To address this question, we trained monkeys in three tapping tasks and compared their rhythmic entrainment abilities with those of humans. We found that, when immediate feedback about the timing of each movement is provided, monkeys can predictively entrain to an isochronous beat, generating tapping movements in anticipation of the metronome pulse. This ability also generalized to a novel untrained tempo. Notably, macaques can modify their tapping tempo by predicting the beat changes of accelerating and decelerating visual metronomes in a manner similar to humans. Our findings support the notion that nonhuman primates share with humans the ability of temporal anticipation during tapping to isochronous and smoothly changing sequences of stimuli. © 2018 New York Academy of Sciences.

Phylogenies support out-of-equilibrium models of biodiversity.

PubMed

Manceau, Marc; Lambert, Amaury; Morlon, Hélène

2015-04-01

There is a long tradition in ecology of studying models of biodiversity at equilibrium. These models, including the influential Neutral Theory of Biodiversity, have been successful at predicting major macroecological patterns, such as species abundance distributions. But they have failed to predict macroevolutionary patterns, such as those captured in phylogenetic trees. Here, we develop a model of biodiversity in which all individuals have identical demographic rates, metacommunity size is allowed to vary stochastically according to population dynamics, and speciation arises naturally from the accumulation of point mutations. We show that this model generates phylogenies matching those observed in nature if the metacommunity is out of equilibrium. We develop a likelihood inference framework that allows fitting our model to empirical phylogenies, and apply this framework to various mammalian families. Our results corroborate the hypothesis that biodiversity dynamics are out of equilibrium. © 2015 John Wiley & Sons Ltd/CNRS.

Towards 3rd generation organic tandem solar cells with 20% efficiency: Accelerated discovery and rational design of carbon-based photovoltaic materials through massive distributed volunteer computing

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

Aspuru-Guzik, Alan

2016-11-04

Clean, affordable, and renewable energy sources are urgently needed to satisfy the 10s of terawatts (TW) energy need of human beings. Solar cells are one promising choice to replace traditional energy sources. Our broad efforts have expanded the knowledge of possible donor materials for organic photovoltaics, while increasing access of our results to the world through the Clean Energy Project database (www.molecularspace.org). Machine learning techniques, including Gaussian Processes have been used to calibrate frontier molecular orbital energies, and OPV bulk properties (open-circuit voltage, percent conversion efficiencies, and short-circuit current). This grant allowed us to delve into the solid-state properties ofmore » OPVs (charge-carrier dynamics). One particular example allowed us to predict charge-carrier dynamics and make predictions about future hydrogen-bonded materials.« less

Predictive and Reactive Distribution of Vaccines and Antivirals during Cross-Regional Pandemic Outbreaks

PubMed Central

Uribe-Sánchez, Andrés; Savachkin, Alex

2011-01-01

As recently pointed out by the Institute of Medicine, the existing pandemic mitigation models lack the dynamic decision support capability. We develop a large-scale simulation-driven optimization model for generating dynamic predictive distribution of vaccines and antivirals over a network of regional pandemic outbreaks. The model incorporates measures of morbidity, mortality, and social distancing, translated into the cost of lost productivity and medical expenses. The performance of the strategy is compared to that of the reactive myopic policy, using a sample outbreak in Fla, USA, with an affected population of over four millions. The comparison is implemented at different levels of vaccine and antiviral availability and administration capacity. Sensitivity analysis is performed to assess the impact of variability of some critical factors on policy performance. The model is intended to support public health policy making for effective distribution of limited mitigation resources. PMID:23074658

Fluid dynamic modeling of nano-thermite reactions

NASA Astrophysics Data System (ADS)

Martirosyan, Karen S.; Zyskin, Maxim; Jenkins, Charles M.; Yuki Horie, Yasuyuki

2014-03-01

This paper presents a direct numerical method based on gas dynamic equations to predict pressure evolution during the discharge of nanoenergetic materials. The direct numerical method provides for modeling reflections of the shock waves from the reactor walls that generates pressure-time fluctuations. The results of gas pressure prediction are consistent with the experimental evidence and estimates based on the self-similar solution. Artificial viscosity provides sufficient smoothing of shock wave discontinuity for the numerical procedure. The direct numerical method is more computationally demanding and flexible than self-similar solution, in particular it allows study of a shock wave in its early stage of reaction and allows the investigation of "slower" reactions, which may produce weaker shock waves. Moreover, numerical results indicate that peak pressure is not very sensitive to initial density and reaction time, providing that all the material reacts well before the shock wave arrives at the end of the reactor.

Fluid dynamic modeling of nano-thermite reactions

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

Martirosyan, Karen S., E-mail: karen.martirosyan@utb.edu; Zyskin, Maxim; Jenkins, Charles M.

2014-03-14

This paper presents a direct numerical method based on gas dynamic equations to predict pressure evolution during the discharge of nanoenergetic materials. The direct numerical method provides for modeling reflections of the shock waves from the reactor walls that generates pressure-time fluctuations. The results of gas pressure prediction are consistent with the experimental evidence and estimates based on the self-similar solution. Artificial viscosity provides sufficient smoothing of shock wave discontinuity for the numerical procedure. The direct numerical method is more computationally demanding and flexible than self-similar solution, in particular it allows study of a shock wave in its early stagemore » of reaction and allows the investigation of “slower” reactions, which may produce weaker shock waves. Moreover, numerical results indicate that peak pressure is not very sensitive to initial density and reaction time, providing that all the material reacts well before the shock wave arrives at the end of the reactor.« less

Observational and numerical particle tracking to examine sediment dynamics in a Mississippi River delta diversion

NASA Astrophysics Data System (ADS)

Allison, Mead A.; Yuill, Brendan T.; Meselhe, Ehab A.; Marsh, Jonathan K.; Kolker, Alexander S.; Ameen, Alexander D.

2017-07-01

River diversions may serve as useful restoration tools along coastal deltas experiencing land loss due to high rates of relative sea-level rise and the disruption of natural sediment supply. Diversions mitigate land loss by serving as new sediment sources for land building areas in basins proximal to river channels. However, because of the paucity of active diversions, little is known about how diversion receiving-basins evacuate or retain the sediment required to build new land. This study uses observational and numerical particle tracking to investigate the behavior of riverine sand and silt as it enters and passes through the West Bay diversion receiving-basin located on the lowermost Mississippi River delta, USA. Fluorescent sediment tracer was deployed and tracked within the bed sediment over a five-month period to identify locations of sediment deposition in the receiving-basin and nearby river channel. A computational fluid dynamics model with a Lagrangian sediment transport module was employed to predict selective pathways for riverine flow and sand and silt particles through the receiving-basin. Observations of the fluorescent tracer provides snapshots of the integrated sediment response to the full range of drivers in the natural system; the numerical model results offer a continuous map of sediment advection vectors through the receiving basin in response to river-generated currents. Together, these methods provide insight into local and basin-wide values of sediment retention as influenced by grain size, transport time, and basin morphology. Results show that after two weeks of low Mississippi River discharge, basin silt retention was approximately 60% but was reduced to 4% at the conclusion of the study. Riverine sand retention was approximately near 100% at two weeks and 40% over the study period. Modeled sediment storage was predicted to be greatest at the margins of the primary basin transport pathway; this matched the observed dynamics of the silt tracer but did not match the behavior of the sand tracer. The degree to which the observational measurements deviate from the model predictions may indicate the relative influence of physical processes other than the mean riverine generated currents, such as tides, wind generated currents, and waves.

System dynamics model for predicting floods from snowmelt in North American prairie watersheds

NASA Astrophysics Data System (ADS)

Li, L.; Simonovic, S. P.

2002-09-01

This study uses a system dynamics approach to explore hydrological processes in the geographic locations where the main contribution to flooding is coming from the snowmelt. Temperature is identified as a critical factor that affects watershed hydrological processes. Based on the dynamic processes of the hydrologic cycle occurring in a watershed, the feedback relationships linking the watershed structure, as well as the climate factors, to the streamflow generation were identified prior to the development of a system dynamics model. The model is used to simulate flood patterns generated by snowmelt under temperature change in the spring. Model structure captures a vertical water balance using five tanks representing snow, interception, surface, subsurface and groundwater storage. Calibration and verification results show that temperature change and snowmelt play a key role in flood generation. Results indicate that simulated values match observed data very well. The goodness-of-fit between simulated and observed peak flow data is measured using coefficient of efficiency, coefficient of determination and square of the residual mass curve coefficient. For the Assiniboine River all three measures were in the interval between 0·92 and 0·96 and for the Red River between 0·89 and 0·97. The model is capable of capturing the essential dynamics of streamflow formation. Model input requires a set of initial values for all state variables and the time series of daily temperature and precipitation information. Data from the Red River Basin, shared by Canada and the USA, are used in the model development and testing.

Molecular dynamics simulations of the Bcl-2 protein to predict the structure of its unordered flexible loop domain.

PubMed

Raghav, Pawan Kumar; Verma, Yogesh Kumar; Gangenahalli, Gurudutta U

2012-05-01

B-cell lymphoma (Bcl-2) protein is an anti-apoptotic member of the Bcl-2 family. It is functionally demarcated into four Bcl-2 homology (BH) domains: BH1, BH2, BH3, BH4, one flexible loop domain (FLD), a transmembrane domain (TM), and an X domain. Bcl-2's BH domains have clearly been elucidated from a structural perspective, whereas the conformation of FLD has not yet been predicted, despite its important role in regulating apoptosis through its interactions with JNK-1, PKC, PP2A phosphatase, caspase 3, MAP kinase, ubiquitin, PS1, and FKBP38. Many important residues that regulate Bcl-2 anti-apoptotic activity are present in this domain, for example Asp34, Thr56, Thr69, Ser70, Thr74, and Ser87. The structural elucidation of the FLD would likely help in attempts to accurately predict the effect of mutating these residues on the overall structure of the protein and the interactions of other proteins in this domain. Therefore, we have generated an increased quality model of the Bcl-2 protein including the FLD through modeling. Further, molecular dynamics (MD) simulations were used for FLD optimization, to predict the flexibility, and to determine the stability of the folded FLD. In addition, essential dynamics (ED) was used to predict the collective motions and the essential subspace relevant to Bcl-2 protein function. The predicted average structure and ensemble of MD-simulated structures were submitted to the Protein Model Database (PMDB), and the Bcl-2 structures obtained exhibited enhanced quality. This study should help to elucidate the structural basis for Bcl-2 anti-apoptotic activity regulation through its binding to other proteins via the FLD.

Transfer of Dynamic Learning Across Postures

PubMed Central

Wolpert, Daniel M.

2009-01-01

When learning a difficult motor task, we often decompose the task so that the control of individual body segments is practiced in isolation. But on re-composition, the combined movements can result in novel and possibly complex internal forces between the body segments that were not experienced (or did not need to be compensated for) during isolated practice. Here we investigate whether dynamics learned in isolation by one part of the body can be used by other parts of the body to immediately predict and compensate for novel forces between body segments. Subjects reached to targets while holding the handle of a robotic, force-generating manipulandum. One group of subjects was initially exposed to the novel robot dynamics while seated and was then tested in a standing position. A second group was tested in the reverse order: standing then sitting. Both groups adapted their arm dynamics to the novel environment, and this movement learning transferred between seated and standing postures and vice versa. Both groups also generated anticipatory postural adjustments when standing and exposed to the force field for several trials. In the group that had learned the dynamics while seated, the appropriate postural adjustments were observed on the very first reach on standing. These results suggest that the CNS can immediately anticipate the effect of learned movement dynamics on a novel whole-body posture. The results support the existence of separate mappings for posture and movement, which encode similar dynamics but can be adapted independently. PMID:19710374

Altered predictive capability of the brain network EEG model in schizophrenia during cognition.

PubMed

Gomez-Pilar, Javier; Poza, Jesús; Gómez, Carlos; Northoff, Georg; Lubeiro, Alba; Cea-Cañas, Benjamín B; Molina, Vicente; Hornero, Roberto

2018-05-12

The study of the mechanisms involved in cognition is of paramount importance for the understanding of the neurobiological substrates in psychiatric disorders. Hence, this research is aimed at exploring the brain network dynamics during a cognitive task. Specifically, we analyze the predictive capability of the pre-stimulus theta activity to ascertain the functional brain dynamics during cognition in both healthy and schizophrenia subjects. Firstly, EEG recordings were acquired during a three-tone oddball task from fifty-one healthy subjects and thirty-five schizophrenia patients. Secondly, phase-based coupling measures were used to generate the time-varying functional network for each subject. Finally, pre-stimulus network connections were iteratively modified according to different models of network reorganization. This adjustment was applied by minimizing the prediction error through recurrent iterations, following the predictive coding approach. Both controls and schizophrenia patients follow a reinforcement of the secondary neural pathways (i.e., pathways between cortical brain regions weakly connected during pre-stimulus) for most of the subjects, though the ratio of controls that exhibited this behavior was statistically significant higher than for patients. These findings suggest that schizophrenia is associated with an impaired ability to modify brain network configuration during cognition. Furthermore, we provide direct evidence that the changes in phase-based brain network parameters from pre-stimulus to cognitive response in the theta band are closely related to the performance in important cognitive domains. Our findings not only contribute to the understanding of healthy brain dynamics, but also shed light on the altered predictive neuronal substrates in schizophrenia. Copyright © 2018 Elsevier B.V. All rights reserved.

Population dynamics can be more important than physiological limits for determining range shifts under climate change.

PubMed

Fordham, Damien A; Mellin, Camille; Russell, Bayden D; Akçakaya, Reşit H; Bradshaw, Corey J A; Aiello-Lammens, Matthew E; Caley, Julian M; Connell, Sean D; Mayfield, Stephen; Shepherd, Scoresby A; Brook, Barry W

2013-10-01

Evidence is accumulating that species' responses to climate changes are best predicted by modelling the interaction of physiological limits, biotic processes and the effects of dispersal-limitation. Using commercially harvested blacklip (Haliotis rubra) and greenlip abalone (Haliotis laevigata) as case studies, we determine the relative importance of accounting for interactions among physiology, metapopulation dynamics and exploitation in predictions of range (geographical occupancy) and abundance (spatially explicit density) under various climate change scenarios. Traditional correlative ecological niche models (ENM) predict that climate change will benefit the commercial exploitation of abalone by promoting increased abundances without any reduction in range size. However, models that account simultaneously for demographic processes and physiological responses to climate-related factors result in future (and present) estimates of area of occupancy (AOO) and abundance that differ from those generated by ENMs alone. Range expansion and population growth are unlikely for blacklip abalone because of important interactions between climate-dependent mortality and metapopulation processes; in contrast, greenlip abalone should increase in abundance despite a contraction in AOO. The strongly non-linear relationship between abalone population size and AOO has important ramifications for the use of ENM predictions that rely on metrics describing change in habitat area as proxies for extinction risk. These results show that predicting species' responses to climate change often require physiological information to understand climatic range determinants, and a metapopulation model that can make full use of this data to more realistically account for processes such as local extirpation, demographic rescue, source-sink dynamics and dispersal-limitation. © 2013 John Wiley & Sons Ltd.

Spontaneous Contractility-Mediated Cortical Flow Generates Cell Migration in Three-Dimensional Environments

PubMed Central

Hawkins, Rhoda J.; Poincloux, Renaud; Bénichou, Olivier; Piel, Matthieu; Chavrier, Philippe; Voituriez, Raphaël

2011-01-01

We present a model of cell motility generated by actomyosin contraction of the cell cortex. We identify, analytically, dynamical instabilities of the cortex and show that they yield steady-state cortical flows, which, in turn, can induce cell migration in three-dimensional environments. This mechanism relies on the regulation of contractility by myosin, whose transport is explicitly taken into account in the model. Theoretical predictions are compared to experimental data of tumor cells migrating in three-dimensional matrigel and suggest that this mechanism could be a general mode of cell migration in three-dimensional environments. PMID:21889440

Modeling of urban solid waste management system: The case of Dhaka city

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

Sufian, M.A.; Bala, B.K.

2007-07-01

This paper presents a system dynamics computer model to predict solid waste generation, collection capacity and electricity generation from solid waste and to assess the needs for waste management of the urban city of Dhaka, Bangladesh. Simulated results show that solid waste generation, collection capacity and electricity generation potential from solid waste increase with time. Population, uncleared waste, untreated waste, composite index and public concern are projected to increase with time for Dhaka city. Simulated results also show that increasing the budget for collection capacity alone does not improve environmental quality; rather an increased budget is required for both collectionmore » and treatment of solid wastes of Dhaka city. Finally, this model can be used as a computer laboratory for urban solid waste management (USWM) policy analysis.« less

Temperature-dependent electrochemical heat generation in a commercial lithium-ion battery

NASA Astrophysics Data System (ADS)

Bandhauer, Todd M.; Garimella, Srinivas; Fuller, Thomas F.

2014-02-01

Lithium-ion batteries suffer from inherent thermal limitations (i.e., capacity fade and thermal runaway); thus, it is critical to understand heat generation experienced in the batteries under normal operation. In the current study, reversible and irreversible electrochemical heat generation rates were measured experimentally on a small commercially available C/LiFePO4 lithium-ion battery designed for high-rate applications. The battery was tested over a wide range of temperatures (10-60 °C) and discharge and charge rates (∼C/4-5C) to elucidate their effects. Two samples were tested in a specially designed wind tunnel to maintain constant battery surface temperature within a maximum variation of ±0.88 °C. A data normalization technique was employed to account for the observed capacity fade, which was largest at the highest rates. The heat rate was shown to increase with both increasing rate and decreasing temperature, and the reversible heat rate was shown to be significant even at the highest rate and temperature (7.4% at 5C and 55 °C). Results from cycling the battery using a dynamic power profile also showed that constant-current data predict the dynamic performance data well. In addition, the reversible heat rate in the dynamic simulation was shown to be significant, especially for charge-depleting HEV applications.

Preliminary design, analysis, and costing of a dynamic scale model of the NASA space station

NASA Technical Reports Server (NTRS)

Gronet, M. J.; Pinson, E. D.; Voqui, H. L.; Crawley, E. F.; Everman, M. R.

1987-01-01

The difficulty of testing the next generation of large flexible space structures on the ground places an emphasis on other means for validating predicted on-orbit dynamic behavior. Scale model technology represents one way of verifying analytical predictions with ground test data. This study investigates the preliminary design, scaling and cost trades for a Space Station dynamic scale model. The scaling of nonlinear joint behavior is studied from theoretical and practical points of view. Suspension system interaction trades are conducted for the ISS Dual Keel Configuration and Build-Up Stages suspended in the proposed NASA/LaRC Large Spacecraft Laboratory. Key issues addressed are scaling laws, replication vs. simulation of components, manufacturing, suspension interactions, joint behavior, damping, articulation capability, and cost. These issues are the subject of parametric trades versus the scale model factor. The results of these detailed analyses are used to recommend scale factors for four different scale model options, each with varying degrees of replication. Potential problems in constructing and testing the scale model are identified, and recommendations for further study are outlined.

Uncovering low dimensional macroscopic chaotic dynamics of large finite size complex systems

NASA Astrophysics Data System (ADS)

Skardal, Per Sebastian; Restrepo, Juan G.; Ott, Edward

2017-08-01

In the last decade, it has been shown that a large class of phase oscillator models admit low dimensional descriptions for the macroscopic system dynamics in the limit of an infinite number N of oscillators. The question of whether the macroscopic dynamics of other similar systems also have a low dimensional description in the infinite N limit has, however, remained elusive. In this paper, we show how techniques originally designed to analyze noisy experimental chaotic time series can be used to identify effective low dimensional macroscopic descriptions from simulations with a finite number of elements. We illustrate and verify the effectiveness of our approach by applying it to the dynamics of an ensemble of globally coupled Landau-Stuart oscillators for which we demonstrate low dimensional macroscopic chaotic behavior with an effective 4-dimensional description. By using this description, we show that one can calculate dynamical invariants such as Lyapunov exponents and attractor dimensions. One could also use the reconstruction to generate short-term predictions of the macroscopic dynamics.

Discrete dynamic modeling of cellular signaling networks.

PubMed

Albert, Réka; Wang, Rui-Sheng

2009-01-01

Understanding signal transduction in cellular systems is a central issue in systems biology. Numerous experiments from different laboratories generate an abundance of individual components and causal interactions mediating environmental and developmental signals. However, for many signal transduction systems there is insufficient information on the overall structure and the molecular mechanisms involved in the signaling network. Moreover, lack of kinetic and temporal information makes it difficult to construct quantitative models of signal transduction pathways. Discrete dynamic modeling, combined with network analysis, provides an effective way to integrate fragmentary knowledge of regulatory interactions into a predictive mathematical model which is able to describe the time evolution of the system without the requirement for kinetic parameters. This chapter introduces the fundamental concepts of discrete dynamic modeling, particularly focusing on Boolean dynamic models. We describe this method step-by-step in the context of cellular signaling networks. Several variants of Boolean dynamic models including threshold Boolean networks and piecewise linear systems are also covered, followed by two examples of successful application of discrete dynamic modeling in cell biology.

Dynamics of bubble collapse under vessel confinement in 2D hydrodynamic experiments

NASA Astrophysics Data System (ADS)

Shpuntova, Galina; Austin, Joanna

2013-11-01

One trauma mechanism in biomedical treatment techniques based on the application of cumulative pressure pulses generated either externally (as in shock-wave lithotripsy) or internally (by laser-induced plasma) is the collapse of voids. However, prediction of void-collapse driven tissue damage is a challenging problem, involving complex and dynamic thermomechanical processes in a heterogeneous material. We carry out a series of model experiments to investigate the hydrodynamic processes of voids collapsing under dynamic loading in configurations designed to model cavitation with vessel confinement. The baseline case of void collapse near a single interface is also examined. Thin sheets of tissue-surrogate polymer materials with varying acoustic impedance are used to create one or two parallel material interfaces near the void. Shadowgraph photography and two-color, single-frame particle image velocimetry quantify bubble collapse dynamics including jetting, interface dynamics and penetration, and the response of the surrounding material. Research supported by NSF Award #0954769, ``CAREER: Dynamics and damage of void collapse in biological materials under stress wave loading.''

Hebbian learning in a model with dynamic rate-coded neurons: an alternative to the generative model approach for learning receptive fields from natural scenes.

PubMed

Hamker, Fred H; Wiltschut, Jan

2007-09-01

Most computational models of coding are based on a generative model according to which the feedback signal aims to reconstruct the visual scene as close as possible. We here explore an alternative model of feedback. It is derived from studies of attention and thus, probably more flexible with respect to attentive processing in higher brain areas. According to this model, feedback implements a gain increase of the feedforward signal. We use a dynamic model with presynaptic inhibition and Hebbian learning to simultaneously learn feedforward and feedback weights. The weights converge to localized, oriented, and bandpass filters similar as the ones found in V1. Due to presynaptic inhibition the model predicts the organization of receptive fields within the feedforward pathway, whereas feedback primarily serves to tune early visual processing according to the needs of the task.

Recurrence plots revisited

NASA Astrophysics Data System (ADS)

Casdagli, M. C.

1997-09-01

We show that recurrence plots (RPs) give detailed characterizations of time series generated by dynamical systems driven by slowly varying external forces. For deterministic systems we show that RPs of the time series can be used to reconstruct the RP of the driving force if it varies sufficiently slowly. If the driving force is one-dimensional, its functional form can then be inferred up to an invertible coordinate transformation. The same results hold for stochastic systems if the RP of the time series is suitably averaged and transformed. These results are used to investigate the nonlinear prediction of time series generated by dynamical systems driven by slowly varying external forces. We also consider the problem of detecting a small change in the driving force, and propose a surrogate data technique for assessing statistical significance. Numerically simulated time series and a time series of respiration rates recorded from a subject with sleep apnea are used as illustrative examples.

Experimental Study of Airfoil Trailing Edge Noise: Instrumentation, Methodology and Initial Results. M.S. Thesis

NASA Technical Reports Server (NTRS)

Manley, M. B.

1980-01-01

The mechanisms of aerodynamic noise generation at the trailing edge of an airfoil is investigated. Instrumentation was designed, a miniature semiconductor strain-gauge pressure transducer and associated electronic amplifier circuitry were designed and tested and digital signal analysis techniques applied to gain insight into the relationship between the dynamic pressure close to the trailing edge and the sound in the acoustic far-field. Attempts are made to verify some trailing-edge noise generation characteristics as theoretically predicted by several contemporary acousticians. It is found that the noise detected in the far-field is comprised of the sum of many uncorrelated emissions radiating from the vicinity of the trailing edge. These emissions appear to be the result of acoustic energy radiation which has been converted by the trailing-edge noise mechanism from the dynamic fluid energy of independent streamwise 'strips' of the turbulent boundary layer flow.

Dissecting single-molecule signal transduction in carbon nanotube circuits with protein engineering

PubMed Central

Choi, Yongki; Olsen, Tivoli J.; Sims, Patrick C.; Moody, Issa S.; Corso, Brad L.; Dang, Mytrang N.; Weiss, Gregory A.; Collins, Philip G.

2013-01-01

Single molecule experimental methods have provided new insights into biomolecular function, dynamic disorder, and transient states that are all invisible to conventional measurements. A novel, non-fluorescent single molecule technique involves attaching single molecules to single-walled carbon nanotube field-effective transistors (SWNT FETs). These ultrasensitive electronic devices provide long-duration, label-free monitoring of biomolecules and their dynamic motions. However, generalization of the SWNT FET technique first requires design rules that can predict the success and applicability of these devices. Here, we report on the transduction mechanism linking enzymatic processivity to electrical signal generation by a SWNT FET. The interaction between SWNT FETs and the enzyme lysozyme was systematically dissected using eight different lysozyme variants synthesized by protein engineering. The data prove that effective signal generation can be accomplished using a single charged amino acid, when appropriately located, providing a foundation to widely apply SWNT FET sensitivity to other biomolecular systems. PMID:23323846

Estimating long-wavelength dynamic topographic change of passive continental margins since the Early Cretaceous

NASA Astrophysics Data System (ADS)

Müller, Dietmar; Hassan, Rakib; Gurnis, Michael; Flament, Nicolas; Williams, Simon

2017-04-01

The influence of mantle convection on dynamic topographic change along continental margins is difficult to unravel, because their stratigraphic record is dominated by tectonic subsidence caused by rifting. Yet, dynamic topography can potentially introduce significant depth anomalies along passive margins, influencing their water depth, sedimentary environments and geohistory. Here we follow a three-fold approach to estimate changes in dynamic topography along both continental interiors and passive margins based on a set of seven global mantle convection models. These models include different methodologies (forward and hybrid backward-forward methods), different plate reconstructions and alternative mantle rheologies. We demonstrate that a geodynamic forward model that includes adiabatic heating in addition to internal heating from radiogenic sources, and a mantle viscosity profile with a gradual increase in viscosity below the mantle transition zone, provides a greatly improved match to the spectral range of residual topography end-members as compared with previous models at very long wavelengths (spherical degrees 2-3). We combine global sea level estimates with predicted surface dynamic topography to evaluate the match between predicted continental flooding patterns and published paleo-coastlines by comparing predicted versus geologically reconstructed land fractions and spatial overlaps of flooded regions for individual continents since 140 Ma. Modelled versus geologically reconstructed land fractions match within 10% for most models, and the spatial overlaps of inundated regions are mostly between 85% and 100% for the Cenozoic, dropping to about 75-100% in the Cretaceous. We categorise the evolution of modelled dynamic topography in both continental interiors and along passive margins using cluster analysis to investigate how clusters of similar dynamic topography time series are distributed spatially. A subdivision of four clusters is found to best reveal end-members of dynamic topography evolution along passive margins and their hinterlands, differentiating topographic stability, long-term pronounced subsidence, initial stability over a dynamic high followed by moderate subsidence and regions that are relatively proximal to subduction zones with varied dynamic topography histories. Along passive continental margins the most commonly observed process is a gradual move from dynamic highs towards lows during the fragmentation of Pangea, reflecting that many passive margins now overly slabs sinking in the lower mantle. Our best-fit model results in up to 500 ±150 m of total dynamic subsidence of continental interiors while along passive margins the maximum predicted dynamic topographic change over 140 million years is about 350 ±150 m of subsidence. Models with plumes exhibit clusters of transient passive margin uplift of about 200 ±200m. The good overall match between predicted dynamic topography and geologically mapped paleo-coastlines makes a convincing case that mantle-driven topographic change is a critical component of relative sea level change, and one of the main driving forces generating the observed geometries and timings of large-scale shifts in paleo-coastlines.

The HART II International Workshop: An Assessment of the State-of-the-Art in Comprehensive Code Prediction

NASA Technical Reports Server (NTRS)

vanderWall, Berend G.; Lim, Joon W.; Smith, Marilyn J.; Jung, Sung N.; Bailly, Joelle; Baeder, James D.; Boyd, D. Douglas, Jr.

2013-01-01

Significant advancements in computational fluid dynamics (CFD) and their coupling with computational structural dynamics (CSD, or comprehensive codes) for rotorcraft applications have been achieved recently. Despite this, CSD codes with their engineering level of modeling the rotor blade dynamics, the unsteady sectional aerodynamics and the vortical wake are still the workhorse for the majority of applications. This is especially true when a large number of parameter variations is to be performed and their impact on performance, structural loads, vibration and noise is to be judged in an approximate yet reliable and as accurate as possible manner. In this article, the capabilities of such codes are evaluated using the HART II International Workshop database, focusing on a typical descent operating condition which includes strong blade-vortex interactions. A companion article addresses the CFD/CSD coupled approach. Three cases are of interest: the baseline case and two cases with 3/rev higher harmonic blade root pitch control (HHC) with different control phases employed. One setting is for minimum blade-vortex interaction noise radiation and the other one for minimum vibration generation. The challenge is to correctly predict the wake physics-especially for the cases with HHC-and all the dynamics, aerodynamics, modifications of the wake structure and the aero-acoustics coming with it. It is observed that the comprehensive codes used today have a surprisingly good predictive capability when they appropriately account for all of the physics involved. The minimum requirements to obtain these results are outlined.

An Assessment of Comprehensive Code Prediction State-of-the-Art Using the HART II International Workshop Data

NASA Technical Reports Server (NTRS)

vanderWall, Berend G.; Lim, Joon W.; Smith, Marilyn J.; Jung, Sung N.; Bailly, Joelle; Baeder, James D.; Boyd, D. Douglas, Jr.

2012-01-01

Despite significant advancements in computational fluid dynamics and their coupling with computational structural dynamics (= CSD, or comprehensive codes) for rotorcraft applications, CSD codes with their engineering level of modeling the rotor blade dynamics, the unsteady sectional aerodynamics and the vortical wake are still the workhorse for the majority of applications. This is especially true when a large number of parameter variations is to be performed and their impact on performance, structural loads, vibration and noise is to be judged in an approximate yet reliable and as accurate as possible manner. In this paper, the capabilities of such codes are evaluated using the HART II Inter- national Workshop data base, focusing on a typical descent operating condition which includes strong blade-vortex interactions. Three cases are of interest: the baseline case and two cases with 3/rev higher harmonic blade root pitch control (HHC) with different control phases employed. One setting is for minimum blade-vortex interaction noise radiation and the other one for minimum vibration generation. The challenge is to correctly predict the wake physics - especially for the cases with HHC - and all the dynamics, aerodynamics, modifications of the wake structure and the aero-acoustics coming with it. It is observed that the comprehensive codes used today have a surprisingly good predictive capability when they appropriately account for all of the physics involved. The minimum requirements to obtain these results are outlined.

Discrete Molecular Dynamics Can Predict Helical Prestructured Motifs in Disordered Proteins

PubMed Central

Han, Kyou-Hoon; Dokholyan, Nikolay V.; Tompa, Péter; Kalmár, Lajos; Hegedűs, Tamás

2014-01-01

Intrinsically disordered proteins (IDPs) lack a stable tertiary structure, but their short binding regions termed Pre-Structured Motifs (PreSMo) can form transient secondary structure elements in solution. Although disordered proteins are crucial in many biological processes and designing strategies to modulate their function is highly important, both experimental and computational tools to describe their conformational ensembles and the initial steps of folding are sparse. Here we report that discrete molecular dynamics (DMD) simulations combined with replica exchange (RX) method efficiently samples the conformational space and detects regions populating α-helical conformational states in disordered protein regions. While the available computational methods predict secondary structural propensities in IDPs based on the observation of protein-protein interactions, our ab initio method rests on physical principles of protein folding and dynamics. We show that RX-DMD predicts α-PreSMos with high confidence confirmed by comparison to experimental NMR data. Moreover, the method also can dissect α-PreSMos in close vicinity to each other and indicate helix stability. Importantly, simulations with disordered regions forming helices in X-ray structures of complexes indicate that a preformed helix is frequently the binding element itself, while in other cases it may have a role in initiating the binding process. Our results indicate that RX-DMD provides a breakthrough in the structural and dynamical characterization of disordered proteins by generating the structural ensembles of IDPs even when experimental data are not available. PMID:24763499

Bistable energy harvesting enhancement with an auxiliary linear oscillator

NASA Astrophysics Data System (ADS)

Harne, R. L.; Thota, M.; Wang, K. W.

2013-12-01

Recent work has indicated that linear vibrational energy harvesters with an appended degree-of-freedom (DOF) may be advantageous for introducing new dynamic forms to extend the operational bandwidth. Given the additional interest in bistable harvester designs, which exhibit a propitious snap through effect from one stable state to the other, it is a logical extension to explore the influence of an added DOF to a bistable system. However, bistable snap through is not a resonant phenomenon, which tempers the presumption that the dynamics induced by an additional DOF on bistable designs would inherently be beneficial as for linear systems. This paper presents two analytical formulations to assess the fundamental and superharmonic steady-state dynamics of an excited bistable energy harvester to which is attached an auxiliary linear oscillator. From an energy harvesting perspective, the model predicts that the additional linear DOF uniformly amplifies the bistable harvester response magnitude and generated power for excitation frequencies less than the attachment’s resonance while improved power density spans a bandwidth below this frequency. Analyses predict bandwidths having co-existent responses composed of a unique proportion of fundamental and superharmonic dynamics. Experiments validate key analytical predictions and observe the ability for the coupled system to develop an advantageous multi-harmonic interwell response when the initial conditions are insufficient for continuous high-energy orbit at the excitation frequency. Overall, the addition of an auxiliary linear oscillator to a bistable harvester is found to be an effective means of enhancing the energy harvesting performance and robustness.

Screech Noise Generation From Supersonic Underexpanded Jets Investigated

NASA Technical Reports Server (NTRS)

Panda, Jayanta; Seasholtz, Richard G.

2000-01-01

Many supersonic military aircraft and some of the modern civilian aircraft (such as the Boeing 777) produce shock-associated noise. This noise is generated from the jet engine plume when the engine nozzle is operated beyond the subsonic operation limit to gain additional thrust. At these underexpanded conditions, a series of shock waves appear in the plume. The turbulent vortices present in the jet interact with the shock waves and produce the additional shock-associated noise. Screech belongs to this noise category, where sound is generated in single or multiple pure tones. The high dynamic load associated with screech can damage the tailplane. One purpose of this study at the NASA Glenn Research Center at Lewis Field was to provide an accurate data base for validating various computational fluid dynamics (CFD) codes. These codes will be used to predict the frequency and amplitude of screech tones. A second purpose was to advance the fundamental physical understanding of how shock-turbulence interactions generate sound. Previously, experiments on shock-turbulence interaction were impossible to perform because no suitable technique was available. As one part of this program, an optical Rayleigh-scattering measurement technique was devised to overcome this difficulty.

Nonspherical laser-induced cavitation bubbles

NASA Astrophysics Data System (ADS)

Lim, Kang Yuan; Quinto-Su, Pedro A.; Klaseboer, Evert; Khoo, Boo Cheong; Venugopalan, Vasan; Ohl, Claus-Dieter

2010-01-01

The generation of arbitrarily shaped nonspherical laser-induced cavitation bubbles is demonstrated with a optical technique. The nonspherical bubbles are formed using laser intensity patterns shaped by a spatial light modulator using linear absorption inside a liquid gap with a thickness of 40μm . In particular we demonstrate the dynamics of elliptic, toroidal, square, and V-shaped bubbles. The bubble dynamics is recorded with a high-speed camera at framing rates of up to 300000 frames per second. The observed bubble evolution is compared to predictions from an axisymmetric boundary element simulation which provides good qualitative agreement. Interesting dynamic features that are observed in both the experiment and simulation include the inversion of the major and minor axis for elliptical bubbles, the rotation of the shape for square bubbles, and the formation of a unidirectional jet for V-shaped bubbles. Further we demonstrate that specific bubble shapes can either be formed directly through the intensity distribution of a single laser focus, or indirectly using secondary bubbles that either confine the central bubble or coalesce with the main bubble. The former approach provides the ability to generate in principle any complex bubble geometry.

Glassy dynamics in three-dimensional embryonic tissues

PubMed Central

Schötz, Eva-Maria; Lanio, Marcos; Talbot, Jared A.; Manning, M. Lisa

2013-01-01

Many biological tissues are viscoelastic, behaving as elastic solids on short timescales and fluids on long timescales. This collective mechanical behaviour enables and helps to guide pattern formation and tissue layering. Here, we investigate the mechanical properties of three-dimensional tissue explants from zebrafish embryos by analysing individual cell tracks and macroscopic mechanical response. We find that the cell dynamics inside the tissue exhibit features of supercooled fluids, including subdiffusive trajectories and signatures of caging behaviour. We develop a minimal, three-parameter mechanical model for these dynamics, which we calibrate using only information about cell tracks. This model generates predictions about the macroscopic bulk response of the tissue (with no fit parameters) that are verified experimentally, providing a strong validation of the model. The best-fit model parameters indicate that although the tissue is fluid-like, it is close to a glass transition, suggesting that small changes to single-cell parameters could generate a significant change in the viscoelastic properties of the tissue. These results provide a robust framework for quantifying and modelling mechanically driven pattern formation in tissues. PMID:24068179

Time-dependent inertia analysis of vehicle mechanisms

NASA Astrophysics Data System (ADS)

Salmon, James Lee

Two methods for performing transient inertia analysis of vehicle hardware systems are developed in this dissertation. The analysis techniques can be used to predict the response of vehicle mechanism systems to the accelerations associated with vehicle impacts. General analytical methods for evaluating translational or rotational system dynamics are generated and evaluated for various system characteristics. The utility of the derived techniques are demonstrated by applying the generalized methods to two vehicle systems. Time dependent acceleration measured during a vehicle to vehicle impact are used as input to perform a dynamic analysis of an automobile liftgate latch and outside door handle. Generalized Lagrange equations for a non-conservative system are used to formulate a second order nonlinear differential equation defining the response of the components to the transient input. The differential equation is solved by employing the fourth order Runge-Kutta method. The events are then analyzed using commercially available two dimensional rigid body dynamic analysis software. The results of the two analytical techniques are compared to experimental data generated by high speed film analysis of tests of the two components performed on a high G acceleration sled at Ford Motor Company.

Mechanistic, Mathematical Model to Predict the Dynamics of Tissue Genesis in Bone Defects via Mechanical Feedback and Mediation of Biochemical Factors

PubMed Central

Moore, Shannon R.; Saidel, Gerald M.; Knothe, Ulf; Knothe Tate, Melissa L.

2014-01-01

The link between mechanics and biology in the generation and the adaptation of bone has been well studied in context of skeletal development and fracture healing. Yet, the prediction of tissue genesis within - and the spatiotemporal healing of - postnatal defects, necessitates a quantitative evaluation of mechano-biological interactions using experimental and clinical parameters. To address this current gap in knowledge, this study aims to develop a mechanistic mathematical model of tissue genesis using bone morphogenetic protein (BMP) to represent of a class of factors that may coordinate bone healing. Specifically, we developed a mechanistic, mathematical model to predict the dynamics of tissue genesis by periosteal progenitor cells within a long bone defect surrounded by periosteum and stabilized via an intramedullary nail. The emergent material properties and mechanical environment associated with nascent tissue genesis influence the strain stimulus sensed by progenitor cells within the periosteum. Using a mechanical finite element model, periosteal surface strains are predicted as a function of emergent, nascent tissue properties. Strains are then input to a mechanistic mathematical model, where mechanical regulation of BMP-2 production mediates rates of cellular proliferation, differentiation and tissue production, to predict healing outcomes. A parametric approach enables the spatial and temporal prediction of endochondral tissue regeneration, assessed as areas of cartilage and mineralized bone, as functions of radial distance from the periosteum and time. Comparing model results to histological outcomes from two previous studies of periosteum-mediated bone regeneration in a common ovine model, it was shown that mechanistic models incorporating mechanical feedback successfully predict patterns (spatial) and trends (temporal) of bone tissue regeneration. The novel model framework presented here integrates a mechanistic feedback system based on the mechanosensitivity of periosteal progenitor cells, which allows for modeling and prediction of tissue regeneration on multiple length and time scales. Through combination of computational, physical and engineering science approaches, the model platform provides a means to test new hypotheses in silico and to elucidate conditions conducive to endogenous tissue genesis. Next generation models will serve to unravel intrinsic differences in bone genesis by endochondral and intramembranous mechanisms. PMID:24967742

Correlation of Amine Swingbed On-Orbit CO2 Performance with a Hardware Independent Predictive Model

NASA Technical Reports Server (NTRS)

Papale, William; Sweterlitsch, Jeffery

2015-01-01

The Amine Swingbed Payload is an experimental system deployed on the International Space Station (ISS) that includes a two-bed, vacuum regenerated, amine-based carbon dioxide (CO2) removal subsystem as the principal item under investigation. The aminebased subsystem, also described previously in various publications as CAMRAS 3, was originally designed, fabricated and tested by Hamilton Sundstrand Space Systems International, Inc. (HSSSI) and delivered to NASA in November 2008. The CAMRAS 3 unit was subsequently designed into a flight payload experiment in 2010 and 2011, with flight test integration activities accomplished on-orbit between January 2012 and March 2013. Payload activation was accomplished in May 2013 followed by a 1000 hour experimental period. The experimental nature of the Payload and the interaction with the dynamic ISS environment present unique scientific and engineering challenges, in particular to the verification and validation of the expected Payload CO2 removal performance. A modeling and simulation approach that incorporates principles of chemical reaction engineering has been developed for the amine-based system to predict the dynamic cabin CO2 partial pressure with given inputs of sorbent bed size, process air flow, operating temperature, half-cycle time, CO2 generation rate, cabin volume and the magnitude of vacuum available. Simulation runs using the model to predict ambient CO2 concentrations show good correlation to on-orbit performance measurements and ISS dynamic concentrations for the assumed operating conditions. The dynamic predictive modelling could benefit operational planning to help ensure ISS CO2 concentrations are maintained below prescribed limits and for the Orion vehicle to simulate various operating conditions, scenarios and transients.

Dynamics of a radially expanding liquid sheet: Experiments

NASA Astrophysics Data System (ADS)

Majumdar, Nayanika; Tirumkudulu, Mahesh

2017-11-01

A recent theory predicts that sinuous waves generated at the center of a radially expanding liquid sheet grow spatially even in absence of a surrounding gas phase. Unlike flat liquid sheets, the thickness of a radially expanding liquid sheet varies inversely with distance from the center of the sheet. To test the predictions of the theory, experiments were carried out on a horizontal, radially expanding liquid sheet formed by collision of a single jet on a solid impactor. The latter was placed on a speaker-vibrator with controlled amplitude and frequency. The growth of sinuous waves was determined by measuring the wave surface inclination angle using reflected laser light under both atmospheric and sub-atmospheric pressure conditions. It is shown that the measured growth rate matches with the predictions of the theory over a large range of Weber numbers for both pressure conditions suggesting that the thinning of the liquid sheet plays a dominant role in setting the growth rate of sinuous waves with minimal influence of the surrounding gas phase on its dynamics. IIT Bombay.

Plasticity and Kinky Chemistry of Carbon Nanotubes

NASA Technical Reports Server (NTRS)

Srivastava, Deepak; Dzegilenko, Fedor

2000-01-01

Since their discovery in 1991, carbon nanotubes have been the subject of intense research interest based on early predictions of their unique mechanical, electronic, and chemical properties. Materials with the predicted unique properties of carbon nanotubes are of great interest for use in future generations of aerospace vehicles. For their structural properties, carbon nanotubes could be used as reinforcing fibers in ultralight multifunctional composites. For their electronic properties, carbon nanotubes offer the potential of very high-speed, low-power computing elements, high-density data storage, and unique sensors. In a continuing effort to model and predict the properties of carbon nanotubes, Ames accomplished three significant results during FY99. First, accurate values of the nanomechanics and plasticity of carbon nanotubes based on quantum molecular dynamics simulations were computed. Second, the concept of mechanical deformation catalyzed-kinky-chemistry as a means to control local chemistry of nanotubes was discovered. Third, the ease of nano-indentation of silicon surfaces with carbon nanotubes was established. The elastic response and plastic failure mechanisms of single-wall nanotubes were investigated by means of quantum molecular dynamics simulations.

Rupture Dynamics and Seismic Radiation on Rough Faults for Simulation-Based PSHA

NASA Astrophysics Data System (ADS)

Mai, P. M.; Galis, M.; Thingbaijam, K. K. S.; Vyas, J. C.; Dunham, E. M.

2017-12-01

Simulation-based ground-motion predictions may augment PSHA studies in data-poor regions or provide additional shaking estimations, incl. seismic waveforms, for critical facilities. Validation and calibration of such simulation approaches, based on observations and GMPE's, is important for engineering applications, while seismologists push to include the precise physics of the earthquake rupture process and seismic wave propagation in 3D heterogeneous Earth. Geological faults comprise both large-scale segmentation and small-scale roughness that determine the dynamics of the earthquake rupture process and its radiated seismic wavefield. We investigate how different parameterizations of fractal fault roughness affect the rupture evolution and resulting near-fault ground motions. Rupture incoherence induced by fault roughness generates realistic ω-2 decay for high-frequency displacement amplitude spectra. Waveform characteristics and GMPE-based comparisons corroborate that these rough-fault rupture simulations generate realistic synthetic seismogram for subsequent engineering application. Since dynamic rupture simulations are computationally expensive, we develop kinematic approximations that emulate the observed dynamics. Simplifying the rough-fault geometry, we find that perturbations in local moment tensor orientation are important, while perturbations in local source location are not. Thus, a planar fault can be assumed if the local strike, dip, and rake are maintained. The dynamic rake angle variations are anti-correlated with local dip angles. Based on a dynamically consistent Yoffe source-time function, we show that the seismic wavefield of the approximated kinematic rupture well reproduces the seismic radiation of the full dynamic source process. Our findings provide an innovative pseudo-dynamic source characterization that captures fault roughness effects on rupture dynamics. Including the correlations between kinematic source parameters, we present a new pseudo-dynamic rupture modeling approach for computing broadband ground-motion time-histories for simulation-based PSHA

Finite Element Modeling of In-Situ Stresses near Salt Bodies

NASA Astrophysics Data System (ADS)

Sanz, P.; Gray, G.; Albertz, M.

2011-12-01

The in-situ stress field is modified around salt bodies because salt rock has no ability to sustain shear stresses. A reliable prediction of stresses near salt is important for planning safe and economic drilling programs. A better understanding of in-situ stresses before drilling can be achieved using finite element models that account for the creeping salt behavior and the elastoplastic response of the surrounding sediments. Two different geomechanical modeling techniques can be distinguished: "dynamic" modeling and "static" modeling. "Dynamic" models, also known as forward models, simulate the development of structural processes in geologic time. This technique provides the evolution of stresses and so it is used to simulate the initiation and development of structural features, such as, faults, folds, fractures, and salt diapers. The original or initial configuration and the unknown final configuration of forward models are usually significantly different therefore geometric non-linearities need to be considered. These models may be difficult to constrain when different tectonic, deposition, and erosion events, and the timing among them, needs to be accounted for. While dynamic models provide insight into the stress evolution, in many cases is very challenging, if not impossible, to forward model a configuration to its known present-day geometry; particularly in the case of salt layers that evolve into highly irregular and complex geometries. Alternatively, "static" models use the present-day geometry and present-day far-field stresses to estimate the present-day in-situ stress field inside a domain. In this case, it is appropriate to use a small deformation approach because initial and final configurations should be very similar, and more important, because the equilibrium of stresses should be stated in the present-day initial configuration. The initial stresses and the applied boundary conditions are constrained by the geologic setting and available data. This modeling technique does not predict the evolution of structural elements or stresses with time; therefore it does not provide any insight into the formation of fractures that were previously developed under a different stress condition or the development of overpressure generated by a high sedimentation rate. This work provides a validation for predicting in-situ stresses near salt using "static" models. We compare synthetic examples using both modeling techniques and show that stresses near salt predicted with "static" models are comparable to the ones generated by "dynamic" models.

A predictive model of nuclear power plant crew decision-making and performance in a dynamic simulation environment

NASA Astrophysics Data System (ADS)

Coyne, Kevin Anthony

The safe operation of complex systems such as nuclear power plants requires close coordination between the human operators and plant systems. In order to maintain an adequate level of safety following an accident or other off-normal event, the operators often are called upon to perform complex tasks during dynamic situations with incomplete information. The safety of such complex systems can be greatly improved if the conditions that could lead operators to make poor decisions and commit erroneous actions during these situations can be predicted and mitigated. The primary goal of this research project was the development and validation of a cognitive model capable of simulating nuclear plant operator decision-making during accident conditions. Dynamic probabilistic risk assessment methods can improve the prediction of human error events by providing rich contextual information and an explicit consideration of feedback arising from man-machine interactions. The Accident Dynamics Simulator paired with the Information, Decision, and Action in a Crew context cognitive model (ADS-IDAC) shows promise for predicting situational contexts that might lead to human error events, particularly knowledge driven errors of commission. ADS-IDAC generates a discrete dynamic event tree (DDET) by applying simple branching rules that reflect variations in crew responses to plant events and system status changes. Branches can be generated to simulate slow or fast procedure execution speed, skipping of procedure steps, reliance on memorized information, activation of mental beliefs, variations in control inputs, and equipment failures. Complex operator mental models of plant behavior that guide crew actions can be represented within the ADS-IDAC mental belief framework and used to identify situational contexts that may lead to human error events. This research increased the capabilities of ADS-IDAC in several key areas. The ADS-IDAC computer code was improved to support additional branching events and provide a better representation of the IDAC cognitive model. An operator decision-making engine capable of responding to dynamic changes in situational context was implemented. The IDAC human performance model was fully integrated with a detailed nuclear plant model in order to realistically simulate plant accident scenarios. Finally, the improved ADS-IDAC model was calibrated, validated, and updated using actual nuclear plant crew performance data. This research led to the following general conclusions: (1) A relatively small number of branching rules are capable of efficiently capturing a wide spectrum of crew-to-crew variabilities. (2) Compared to traditional static risk assessment methods, ADS-IDAC can provide a more realistic and integrated assessment of human error events by directly determining the effect of operator behaviors on plant thermal hydraulic parameters. (3) The ADS-IDAC approach provides an efficient framework for capturing actual operator performance data such as timing of operator actions, mental models, and decision-making activities.

Gender Dimorphic ACL Strain In Response to Combined Dynamic 3D Knee Joint Loading: Implications for ACL Injury Risk

PubMed Central

Mizuno, Kiyonori; Andrish, Jack T.; van den Bogert, Antonie J.; McLean, Scott G.

2009-01-01

While gender-based differences in knee joint anatomies/laxities are well documented, the potential for them to precipitate gender-dimorphic ACL loading and resultant injury risk has not been considered. To this end, we generated gender-specific models of ACL strain as a function of any six degrees of freedom (6DOF) knee joint load state via a combined cadaveric and analytical approach. Continuously varying joint forces and torques were applied to five male and five female cadaveric specimens and recorded along with synchronous knee flexion and ACL strain data. All data (~10,000 samples) were submitted to specimen-specific regression analyses, affording ACL strain predictions as a function of the combined 6 DOF knee loads. Following individual model verifications, generalized gender-specific models were generated and subjected to 6 DOF external load scenarios consistent with both a clinical examination and a dynamic sports maneuver. The ensuing model-based strain predictions were subsequently examined for gender-based discrepancies. Male and female specimen specific models predicted ACL strain within 0.51% ± 0.10% and 0.52% ± 0.07% of the measured data respectively, and explained more than 75% of the associated variance in each case. Predicted female ACL strains were also significantly larger than respective male values for both of simulated 6 DOF load scenarios. Outcomes suggest that the female ACL will rupture in response to comparatively smaller external load applications. Future work must address the underlying anatomical/laxity contributions to knee joint mechanical and resultant ACL loading, ultimately affording prevention strategies that may cater to individual joint vulnerabilities. PMID:19464897

DCE-MRI Parameters Have Potential to Predict Response of Locally Advanced Breast Cancer Patients to Neoadjuvant Chemotherapy and Hyperthermia: A Pilot Study

PubMed Central

Craciunescu, Oana I.; Blackwell, Kimberly L.; Jones, Ellen L.; MacFall, James R.; Yu, Daohai; Vujaskovic, Zeljko; Wong, Terence Z.; Liotcheva, Vlayka; Rosen, Eric L.; Prosnitz, Leonard R.; Samulski, Thaddeus V.; Dewhirst, Mark W.

2009-01-01

Purpose To use a novel Morpho-Physiological Tumor Score (MPTS) generated from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to predict response to treatment. Materials and Methods A protocol was designed to acquire DCE-MRI images of 20 locally advanced breast cancer (LABC) patients treated with neoadjuvant chemotherapy (NA ChT) and hyperthermia (HT). Imaging was done over 30 minutes following bolus injection of Gd-based contrast agent. Parametric maps were generated by fitting the signal intensity to a double exponential curve and were used to derive a morphological characterization of the lesions. Enhancement-variance dynamics parameters, washin and washout parameters (WiP, WoP) were extracted. The morphological characterization and the WiP and WoP were combined into a MPTS with the intent of achieving better prognostic efficacy. The MPTS was correlated with response to NA therapy as determined by pathologic residual tumor and MRI imaging. Results The contrast agent in all tumors typically peaked in the first 1–4 minutes. The tumors WiP and WoP varied considerably. The MPTS was highly correlated with whether the patients had a pathologic response. This scoring system has a specificity of 78% and a sensitivity of 91% for predicting response to NA chemotherapy. The kappa was 0.69 with a 95% confidence interval of [0.38, 1.0] and a p-value of 0.002. Conclusions This pilot study shows that the MPTS derived using pre-treatment MRI images has the potential to predict response to NA ChT and HT in LABC patients. Further prospective studies are needed to confirm the validity of these results. PMID:19657852

Epigenetic legacy of parental experiences: Dynamic and interactive pathways to inheritance.

PubMed

Champagne, Frances A

2016-11-01

The quality of the environment experienced by an individual across his or her lifespan can result in a unique developmental trajectory with consequences for adult phenotype and reproductive success. However, it is also evident that these experiences can impact the development of offspring with continued effect on subsequent generations. Epigenetic mechanisms have been proposed as a mediator of both these within- and across-generation effects, and there is increasing evidence to support the role of environmentally induced changes in DNA methylation, posttranslational histone modifications, and noncoding RNAs in predicting these outcomes. Advances in our understanding of these molecular modifications contribute to increasingly nuanced perspectives on plasticity and transmission of phenotypes across generations. A challenge that emerges from this research is in how we integrate these "new" perspectives with traditional views of development, reproduction, and inheritance. This paper will highlight evidence suggestive of an epigenetic impact of the environment on mothers, fathers, and their offspring, and illustrate the importance of considering the dynamic nature of reproduction and development and inclusive views of inheritance within the evolving field of behavioral and environmental epigenetics.

Towards data warehousing and mining of protein unfolding simulation data.

PubMed

Berrar, Daniel; Stahl, Frederic; Silva, Candida; Rodrigues, J Rui; Brito, Rui M M; Dubitzky, Werner

2005-10-01

The prediction of protein structure and the precise understanding of protein folding and unfolding processes remains one of the greatest challenges in structural biology and bioinformatics. Computer simulations based on molecular dynamics (MD) are at the forefront of the effort to gain a deeper understanding of these complex processes. Currently, these MD simulations are usually on the order of tens of nanoseconds, generate a large amount of conformational data and are computationally expensive. More and more groups run such simulations and generate a myriad of data, which raises new challenges in managing and analyzing these data. Because the vast range of proteins researchers want to study and simulate, the computational effort needed to generate data, the large data volumes involved, and the different types of analyses scientists need to perform, it is desirable to provide a public repository allowing researchers to pool and share protein unfolding data. To adequately organize, manage, and analyze the data generated by unfolding simulation studies, we designed a data warehouse system that is embedded in a grid environment to facilitate the seamless sharing of available computer resources and thus enable many groups to share complex molecular dynamics simulations on a more regular basis. To gain insight into the conformational fluctuations and stability of the monomeric forms of the amyloidogenic protein transthyretin (TTR), molecular dynamics unfolding simulations of the monomer of human TTR have been conducted. Trajectory data and meta-data of the wild-type (WT) protein and the highly amyloidogenic variant L55P-TTR represent the test case for the data warehouse. Web and grid services, especially pre-defined data mining services that can run on or 'near' the data repository of the data warehouse, are likely to play a pivotal role in the analysis of molecular dynamics unfolding data.

Reference Computational Meshing Strategy for Computational Fluid Dynamics Simulation of Departure from Nucleate BoilingReference Computational Meshing Strategy for Computational Fluid Dynamics Simulation of Departure from Nucleate Boiling

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

Pointer, William David

The objective of this effort is to establish a strategy and process for generation of suitable computational mesh for computational fluid dynamics simulations of departure from nucleate boiling in a 5 by 5 fuel rod assembly held in place by PWR mixing vane spacer grids. This mesh generation process will support ongoing efforts to develop, demonstrate and validate advanced multi-phase computational fluid dynamics methods that enable more robust identification of dryout conditions and DNB occurrence.Building upon prior efforts and experience, multiple computational meshes were developed using the native mesh generation capabilities of the commercial CFD code STAR-CCM+. These meshes weremore » used to simulate two test cases from the Westinghouse 5 by 5 rod bundle facility. The sensitivity of predicted quantities of interest to the mesh resolution was then established using two evaluation methods, the Grid Convergence Index method and the Least Squares method. This evaluation suggests that the Least Squares method can reliably establish the uncertainty associated with local parameters such as vector velocity components at a point in the domain or surface averaged quantities such as outlet velocity magnitude. However, neither method is suitable for characterization of uncertainty in global extrema such as peak fuel surface temperature, primarily because such parameters are not necessarily associated with a fixed point in space. This shortcoming is significant because the current generation algorithm for identification of DNB event conditions relies on identification of such global extrema. Ongoing efforts to identify DNB based on local surface conditions will address this challenge« less

Multi-paradigm simulation at nanoscale: Methodology and application to functional carbon material

NASA Astrophysics Data System (ADS)

Su, Haibin

2012-12-01

Multiparadigm methods to span the scales from quantum mechanics to practical issues of functional nanoassembly and nanofabrication are enabling first principles predictions to guide and complement the experimental developments by designing and optimizing computationally the materials compositions and structures to assemble nanoscale systems with the requisite properties. In this talk, we employ multi-paradigm approaches to investigate functional carbon materials with versatile character, including fullerene, carbon nanotube (CNT), graphene, and related hybrid structures, which have already created an enormous impact on next generation nano devices. The topics will cover the reaction dynamics of C60 dimerization and the more challenging complex tubular fullerene formation process in the peapod structures; the computational design of a new generation of peapod nano-oscillators, the predicted magnetic state in Nano Buds; opto-electronic properties of graphene nanoribbons; and disorder / vibronic effects on transport in carbonrich materials.

[Artificial Intelligence in Drug Discovery].

PubMed

Fujiwara, Takeshi; Kamada, Mayumi; Okuno, Yasushi

2018-04-01

According to the increase of data generated from analytical instruments, application of artificial intelligence(AI)technology in medical field is indispensable. In particular, practical application of AI technology is strongly required in "genomic medicine" and "genomic drug discovery" that conduct medical practice and novel drug development based on individual genomic information. In our laboratory, we have been developing a database to integrate genome data and clinical information obtained by clinical genome analysis and a computational support system for clinical interpretation of variants using AI. In addition, with the aim of creating new therapeutic targets in genomic drug discovery, we have been also working on the development of a binding affinity prediction system for mutated proteins and drugs by molecular dynamics simulation using supercomputer "Kei". We also have tackled for problems in a drug virtual screening. Our developed AI technology has successfully generated virtual compound library, and deep learning method has enabled us to predict interaction between compound and target protein.

Integrated PK-PD and agent-based modeling in oncology.

PubMed

Wang, Zhihui; Butner, Joseph D; Cristini, Vittorio; Deisboeck, Thomas S

2015-04-01

Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed.

Integrated PK-PD and Agent-Based Modeling in Oncology

PubMed Central

Wang, Zhihui; Butner, Joseph D.; Cristini, Vittorio

2016-01-01

Mathematical modeling has become a valuable tool that strives to complement conventional biomedical research modalities in order to predict experimental outcome, generate new medical hypotheses, and optimize clinical therapies. Two specific approaches, pharmacokinetic-pharmacodynamic (PK-PD) modeling, and agent-based modeling (ABM), have been widely applied in cancer research. While they have made important contributions on their own (e.g., PK-PD in examining chemotherapy drug efficacy and resistance, and ABM in describing and predicting tumor growth and metastasis), only a few groups have started to combine both approaches together in an effort to gain more insights into the details of drug dynamics and the resulting impact on tumor growth. In this review, we focus our discussion on some of the most recent modeling studies building on a combined PK-PD and ABM approach that have generated experimentally testable hypotheses. Some future directions are also discussed. PMID:25588379

Comparison of measured and calculated dynamic loads for the Mod-2 2.5 mW wind turbine system

NASA Technical Reports Server (NTRS)

Zimmerman, D. K.; Shipley, S. A.; Miller, R. D.

1995-01-01

The Boeing Company, under contract to the Electric Power Research Institute (EPRI), has completed a test program on the Mod-2 wind turbines at Goodnoe Hills, Washington. The objectives were to update fatigue load spectra, discern site and machine differences, measure vortex generator effects, and to evaluate rotational sampling techniques. This paper shows the test setup and loads instrumentation, loads data comparisons and test/analysis correlations. Test data are correlated with DYLOSAT predictions using both the NASA interim turbulence model and rotationally sampled winds as inputs. The latter is demonstrated to have the potential to improve the test/analysis correlations. The paper concludes with an assessment of the importance of vortex generators, site dependence, and machine differences on fatigue loads. The adequacy of prediction techniques used are evaluated and recommendations are made for improvements to the methodology.

Characterizing and Modeling the Cost of Rework in a Library of Reusable Software Components

NASA Technical Reports Server (NTRS)

Basili, Victor R.; Condon, Steven E.; ElEmam, Khaled; Hendrick, Robert B.; Melo, Walcelio

1997-01-01

In this paper we characterize and model the cost of rework in a Component Factory (CF) organization. A CF is responsible for developing and packaging reusable software components. Data was collected on corrective maintenance activities for the Generalized Support Software reuse asset library located at the Flight Dynamics Division of NASA's GSFC. We then constructed a predictive model of the cost of rework using the C4.5 system for generating a logical classification model. The predictor variables for the model are measures of internal software product attributes. The model demonstrates good prediction accuracy, and can be used by managers to allocate resources for corrective maintenance activities. Furthermore, we used the model to generate proscriptive coding guidelines to improve programming, practices so that the cost of rework can be reduced in the future. The general approach we have used is applicable to other environments.

Model predictive control system and method for integrated gasification combined cycle power generation

DOEpatents

Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa

2013-04-09

Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.

Structure-based energetics of protein interfaces guide Foot-and-Mouth Disease virus vaccine design

PubMed Central

Scott, Katherine; Burman, Alison; Loureiro, Silvia; Ren, Jingshan; Porta, Claudine; Ginn, Helen M.; Jackson, Terry; Perez-Martin, Eva; Siebert, C. Alistair; Paul, Guntram; Huiskonen, Juha T.; Jones, Ian M.; Esnouf, Robert M.; Fry, Elizabeth E.; Maree, Francois F.; Charleston, Bryan; Stuart, David I.

2018-01-01

Summary Virus capsids are primed for disassembly yet capsid integrity is key to generating a protective immune response. Here we devise a computational method to assess relative stability of protein-protein interfaces and use it to design improved candidate vaccines for two of the least stable, but globally important, serotypes of Foot-and-Mouth Disease virus (FMDV), O and SAT2. FMDV capsids comprise identical pentameric protein subunits held together by tenuous non-covalent interactions, and are often unstable. Chemically inactivated or recombinant empty capsids, which could form the basis of future vaccines, are even less stable than live virus. We use a novel restrained molecular dynamics strategy, to rank mutations predicted to strengthen the pentamer interfaces to produce stabilized capsids. Structural analyses and stability assays confirmed the predictions, and vaccinated animals generated improved neutralising antibody responses to stabilised particles over parental viruses and wild-type capsids. PMID:26389739

Multiscale Systems Analysis of Root Growth and Development: Modeling Beyond the Network and Cellular Scales

PubMed Central

Band, Leah R.; Fozard, John A.; Godin, Christophe; Jensen, Oliver E.; Pridmore, Tony; Bennett, Malcolm J.; King, John R.

2012-01-01

Over recent decades, we have gained detailed knowledge of many processes involved in root growth and development. However, with this knowledge come increasing complexity and an increasing need for mechanistic modeling to understand how those individual processes interact. One major challenge is in relating genotypes to phenotypes, requiring us to move beyond the network and cellular scales, to use multiscale modeling to predict emergent dynamics at the tissue and organ levels. In this review, we highlight recent developments in multiscale modeling, illustrating how these are generating new mechanistic insights into the regulation of root growth and development. We consider how these models are motivating new biological data analysis and explore directions for future research. This modeling progress will be crucial as we move from a qualitative to an increasingly quantitative understanding of root biology, generating predictive tools that accelerate the development of improved crop varieties. PMID:23110897

Next-Generation Pathology.

PubMed

Caie, Peter D; Harrison, David J

2016-01-01

The field of pathology is rapidly transforming from a semiquantitative and empirical science toward a big data discipline. Large data sets from across multiple omics fields may now be extracted from a patient's tissue sample. Tissue is, however, complex, heterogeneous, and prone to artifact. A reductionist view of tissue and disease progression, which does not take this complexity into account, may lead to single biomarkers failing in clinical trials. The integration of standardized multi-omics big data and the retention of valuable information on spatial heterogeneity are imperative to model complex disease mechanisms. Mathematical modeling through systems pathology approaches is the ideal medium to distill the significant information from these large, multi-parametric, and hierarchical data sets. Systems pathology may also predict the dynamical response of disease progression or response to therapy regimens from a static tissue sample. Next-generation pathology will incorporate big data with systems medicine in order to personalize clinical practice for both prognostic and predictive patient care.

Assessment of Near-Field Sonic Boom Simulation Tools

NASA Technical Reports Server (NTRS)

Casper, J. H.; Cliff, S. E.; Thomas, S. D.; Park, M. A.; McMullen, M. S.; Melton, J. E.; Durston, D. A.

2008-01-01

A recent study for the Supersonics Project, within the National Aeronautics and Space Administration, has been conducted to assess current in-house capabilities for the prediction of near-field sonic boom. Such capabilities are required to simulate the highly nonlinear flow near an aircraft, wherein a sonic-boom signature is generated. There are many available computational fluid dynamics codes that could be used to provide the near-field flow for a sonic boom calculation. However, such codes have typically been developed for applications involving aerodynamic configuration, for which an efficiently generated computational mesh is usually not optimum for a sonic boom prediction. Preliminary guidelines are suggested to characterize a state-of-the-art sonic boom prediction methodology. The available simulation tools that are best suited to incorporate into that methodology are identified; preliminary test cases are presented in support of the selection. During this phase of process definition and tool selection, parallel research was conducted in an attempt to establish criteria that link the properties of a computational mesh to the accuracy of a sonic boom prediction. Such properties include sufficient grid density near shocks and within the zone of influence, which are achieved by adaptation and mesh refinement strategies. Prediction accuracy is validated by comparison with wind tunnel data.

Species Turnover through Time: Colonization and Extinction Dynamics across Metacommunities.

PubMed

Nuvoloni, Felipe Micali; Feres, Reinaldo José Fazzio; Gilbert, Benjamin

2016-06-01

Island biogeography and metacommunity theory often use equilibrium assumptions to predict local diversity, yet nonequilibrium dynamics are common in nature. In nonequilibrium communities, local diversity fluctuates through time as the relative importance of colonization and extinction change. Here, we test the prevalence and causes of nonequilibrium dynamics in metacommunities of mites associated with rubber trees distributed over large spatial (>1,000 km) and temporal (>30-60 generations) scales in Brazil. We measured colonization and extinction rates to test species turnover and nonequilibrium dynamics over a growing season. Mite metacommunities exhibited nonequilibrium dynamics for most months of the year, and these dynamics tracked climatic conditions. Monthly shifts in temperature of more than 1°C resulted in nonequilibrium dynamics, as did mean temperatures outside of two critical ranges. Nonequilibrium dynamics were caused by a change in colonization with temperature change and changes in both colonization and extinction with absolute temperature. Species turnover showed different trends; high relative humidity increased both colonization and extinction rates, increasing turnover but not nonequilibrium dynamics. Our study illustrates that testing nonequilibrium dynamics can provide new insights into the drivers of colonization, extinction, and diversity fluctuations in metacommunities.

Research on Aero-Thermodynamic Distortion Induced Structural Dynamic Response of Multistage Compressor Blading

DTIC Science & Technology

1992-03-01

of realistic reduced frequency values for the ftost time. 14. SUIUECT TEIEMS IS. NUMBER OF PAGES Unsteady Aerodynamic, 143 Flow Induced Vibrations 16...Flat Plate APPENDIX X. Prediction of Turbulence Generated Random Vibrational 106 Response of Turbomachinery Blading 3 APPENDIX XI. Viscous Oscillating...failure is fatigue caused by vibrations at levels exceeding3 material endurance limits. These vibrations occur when a periodic forcing function, with

Double-multiple streamtube model for studying vertical-axis wind turbines

NASA Astrophysics Data System (ADS)

Paraschivoiu, Ion

1988-08-01

This work describes the present state-of-the-art in double-multiple streamtube method for modeling the Darrieus-type vertical-axis wind turbine (VAWT). Comparisons of the analytical results with the other predictions and available experimental data show a good agreement. This method, which incorporates dynamic-stall and secondary effects, can be used for generating a suitable aerodynamic-load model for structural design analysis of the Darrieus rotor.

Nonlinear dynamic analysis of voices before and after surgical excision of vocal polyps

NASA Astrophysics Data System (ADS)

Zhang, Yu; McGilligan, Clancy; Zhou, Liang; Vig, Mark; Jiang, Jack J.

2004-05-01

Phase space reconstruction, correlation dimension, and second-order entropy, methods from nonlinear dynamics, are used to analyze sustained vowels generated by patients before and after surgical excision of vocal polyps. Two conventional acoustic perturbation parameters, jitter and shimmer, are also employed to analyze voices before and after surgery. Presurgical and postsurgical analyses of jitter, shimmer, correlation dimension, and second-order entropy are statistically compared. Correlation dimension and second-order entropy show a statistically significant decrease after surgery, indicating reduced complexity and higher predictability of postsurgical voice dynamics. There is not a significant postsurgical difference in shimmer, although jitter shows a significant postsurgical decrease. The results suggest that jitter and shimmer should be applied to analyze disordered voices with caution; however, nonlinear dynamic methods may be useful for analyzing abnormal vocal function and quantitatively evaluating the effects of surgical excision of vocal polyps.

Environmental structure and competitive scoring advantages in team competitions.

PubMed

Merritt, Sears; Clauset, Aaron

2013-10-29

In most professional sports, playing field structure is kept neutral so that scoring imbalances may be attributed to differences in team skill. It thus remains unknown what impact environmental heterogeneities can have on scoring dynamics or competitive advantages. Applying a novel generative model of scoring dynamics to roughly 10 million team competitions drawn from an online game, we quantify the relationship between the structure within a competition and its scoring dynamics, while controlling the impact of chance. Despite wide structural variations, we observe a common three-phase pattern in the tempo of events. Tempo and balance are highly predictable from a competition's structural features alone and teams exploit environmental heterogeneities for sustained competitive advantage. Surprisingly, the most balanced competitions are associated with specific environmental heterogeneities, not from equally skilled teams. These results shed new light on the design principles of balanced competition, and illustrate the potential of online game data for investigating social dynamics and competition.

Analysis of helicopter flight dynamics through modeling and simulation of primary flight control actuation system

NASA Astrophysics Data System (ADS)

Nelson, Hunter Barton

A simplified second-order transfer function actuator model used in most flight dynamics applications cannot easily capture the effects of different actuator parameters. The present work integrates a nonlinear actuator model into a nonlinear state space rotorcraft model to determine the effect of actuator parameters on key flight dynamics. The completed actuator model was integrated with a swashplate kinematics where step responses were generated over a range of key hydraulic parameters. The actuator-swashplate system was then introduced into a nonlinear state space rotorcraft simulation where flight dynamics quantities such as bandwidth and phase delay analyzed. Frequency sweeps were simulated for unique actuator configurations using the coupled nonlinear actuator-rotorcraft system. The software package CIFER was used for system identification and compared directly to the linearized models. As the actuator became rate saturated, the effects on bandwidth and phase delay were apparent on the predicted handling qualities specifications.

Global, quantitative and dynamic mapping of protein subcellular localization.

PubMed

Itzhak, Daniel N; Tyanova, Stefka; Cox, Jürgen; Borner, Georg Hh

2016-06-09

Subcellular localization critically influences protein function, and cells control protein localization to regulate biological processes. We have developed and applied Dynamic Organellar Maps, a proteomic method that allows global mapping of protein translocation events. We initially used maps statically to generate a database with localization and absolute copy number information for over 8700 proteins from HeLa cells, approaching comprehensive coverage. All major organelles were resolved, with exceptional prediction accuracy (estimated at >92%). Combining spatial and abundance information yielded an unprecedented quantitative view of HeLa cell anatomy and organellar composition, at the protein level. We subsequently demonstrated the dynamic capabilities of the approach by capturing translocation events following EGF stimulation, which we integrated into a quantitative model. Dynamic Organellar Maps enable the proteome-wide analysis of physiological protein movements, without requiring any reagents specific to the investigated process, and will thus be widely applicable in cell biology.

Environmental structure and competitive scoring advantages in team competitions

NASA Astrophysics Data System (ADS)

Merritt, Sears; Clauset, Aaron

2013-10-01

In most professional sports, playing field structure is kept neutral so that scoring imbalances may be attributed to differences in team skill. It thus remains unknown what impact environmental heterogeneities can have on scoring dynamics or competitive advantages. Applying a novel generative model of scoring dynamics to roughly 10 million team competitions drawn from an online game, we quantify the relationship between the structure within a competition and its scoring dynamics, while controlling the impact of chance. Despite wide structural variations, we observe a common three-phase pattern in the tempo of events. Tempo and balance are highly predictable from a competition's structural features alone and teams exploit environmental heterogeneities for sustained competitive advantage. Surprisingly, the most balanced competitions are associated with specific environmental heterogeneities, not from equally skilled teams. These results shed new light on the design principles of balanced competition, and illustrate the potential of online game data for investigating social dynamics and competition.

Switching moving boundary models for two-phase flow evaporators and condensers

NASA Astrophysics Data System (ADS)

Bonilla, Javier; Dormido, Sebastián; Cellier, François E.

2015-03-01

The moving boundary method is an appealing approach for the design, testing and validation of advanced control schemes for evaporators and condensers. When it comes to advanced control strategies, not only accurate but fast dynamic models are required. Moving boundary models are fast low-order dynamic models, and they can describe the dynamic behavior with high accuracy. This paper presents a mathematical formulation based on physical principles for two-phase flow moving boundary evaporator and condenser models which support dynamic switching between all possible flow configurations. The models were implemented in a library using the equation-based object-oriented Modelica language. Several integrity tests in steady-state and transient predictions together with stability tests verified the models. Experimental data from a direct steam generation parabolic-trough solar thermal power plant is used to validate and compare the developed moving boundary models against finite volume models.

Tearing mode dynamics and sawtooth oscillation in Hall-MHD

NASA Astrophysics Data System (ADS)

Ma, Zhiwei; Zhang, Wei; Wang, Sheng

2017-10-01

Tearing mode instability is one of the most important dynamic processes in space and laboratory plasmas. Hall effects, resulted from the decoupling of electron and ion motions, could cause the fast development and perturbation structure rotation of the tearing mode and become non-negligible. We independently developed high accuracy nonlinear MHD code (CLT) to study Hall effects on the dynamic evolution of tearing modes with Tokamak geometries. It is found that the rotation frequency of the mode in the electron diamagnetic direction is in a good agreement with analytical prediction. The linear growth rate increases with increase of the ion inertial length, which is contradictory to analytical solution in the slab geometry. We further find that the self-consistently generated rotation largely alters the dynamic behavior of the double tearing mode and the sawtooth oscillation. National Magnetic Confinement Fusion Science Program of China under Grant No. 2013GB104004 and 2013GB111004.

Piezoelectric diaphragm for vibration energy harvesting.

PubMed

Minazara, E; Vasic, D; Costa, F; Poulin, G

2006-12-22

This paper presents a technique of electric energy generation using a mechanically excited unimorph piezoelectric membrane transducer. The electrical characteristics of the piezoelectric power generator are investigated under dynamic conditions. The electromechanical model of the generator is presented and used to predict its electrical performances. The experiments was performed with a piezoelectric actuator (shaker) moving a macroscopic 25 mm diameter piezoelectric membrane. A power of 0.65 mW was generated at the resonance frequency (1.71 kHz) across a 5.6 kOmega optimal resistor and for a 80 N force. A special electronic circuit has been conceived in order to increase the power harvested by the piezoelectric transducer. This electrical converter applies the SSHI (synchronized switch harvesting on inductor) technique, and leads to remarkable results: under the same actuation conditions the generated power reaches 1.7 mW, which is sufficient to supply a large range of low consumption sensors.

Optimization of polyphenol removal from kiwifruit juice using a macroporous resin.

PubMed

Gao, Zhenpeng; Yu, Zhifang; Yue, Tianli; Quek, Siew Young

2017-06-01

The separation of polyphenols from kiwifruit juice is essential for enhancing sensory properties and prevent the browning reaction in juice during processing and storage. The present study investigated the dynamic adsorption and desorption of polyphenols in kiwifruit juice using AB-8 resin. The model obtained could be successfully applied to predict the experimental results of dynamic adsorption capacity (DAC) and dynamic desorption quantity (DDQ). The results showed that dynamic adsorption of polyphenols could be optimised in a juice concentration of 19 °Brix, with a feed flow-rate of 1.3 mL min -1 and a feed volume of 7 bed volume (BV). The optimum conditions for dynamic desorption of polyphenols from the AB-8 resin were an ethanol concentration of 43% (v/v), an elute flow-rate of 2.2 mL min -1 and an elute volume of 3 BV. The optimized DAC value was 3.16 g of polyphenols kg -1 resin, whereas that for DDQ was 917.5 g kg -1 , with both values being consistent with the predicted values generated by the regression models. The major polyphenols in the dynamic desorption solution consisted of seven compositions. The present study could be scaled-up using a continuous column system for industrial application, thus contributing to the improved flavor and color of kiwifruit juice. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

A Coarse-Grained Elastic Network Atom Contact Model and Its Use in the Simulation of Protein Dynamics and the Prediction of the Effect of Mutations

PubMed Central

Frappier, Vincent; Najmanovich, Rafael J.

2014-01-01

Normal mode analysis (NMA) methods are widely used to study dynamic aspects of protein structures. Two critical components of NMA methods are coarse-graining in the level of simplification used to represent protein structures and the choice of potential energy functional form. There is a trade-off between speed and accuracy in different choices. In one extreme one finds accurate but slow molecular-dynamics based methods with all-atom representations and detailed atom potentials. On the other extreme, fast elastic network model (ENM) methods with Cα−only representations and simplified potentials that based on geometry alone, thus oblivious to protein sequence. Here we present ENCoM, an Elastic Network Contact Model that employs a potential energy function that includes a pairwise atom-type non-bonded interaction term and thus makes it possible to consider the effect of the specific nature of amino-acids on dynamics within the context of NMA. ENCoM is as fast as existing ENM methods and outperforms such methods in the generation of conformational ensembles. Here we introduce a new application for NMA methods with the use of ENCoM in the prediction of the effect of mutations on protein stability. While existing methods are based on machine learning or enthalpic considerations, the use of ENCoM, based on vibrational normal modes, is based on entropic considerations. This represents a novel area of application for NMA methods and a novel approach for the prediction of the effect of mutations. We compare ENCoM to a large number of methods in terms of accuracy and self-consistency. We show that the accuracy of ENCoM is comparable to that of the best existing methods. We show that existing methods are biased towards the prediction of destabilizing mutations and that ENCoM is less biased at predicting stabilizing mutations. PMID:24762569

Quantumness-generating capability of quantum dynamics

NASA Astrophysics Data System (ADS)

Li, Nan; Luo, Shunlong; Mao, Yuanyuan

2018-04-01

We study quantumness-generating capability of quantum dynamics, where quantumness refers to the noncommutativity between the initial state and the evolving state. In terms of the commutator of the square roots of the initial state and the evolving state, we define a measure to quantify the quantumness-generating capability of quantum dynamics with respect to initial states. Quantumness-generating capability is absent in classical dynamics and hence is a fundamental characteristic of quantum dynamics. For qubit systems, we present an analytical form for this measure, by virtue of which we analyze several prototypical dynamics such as unitary dynamics, phase damping dynamics, amplitude damping dynamics, and random unitary dynamics (Pauli channels). Necessary and sufficient conditions for the monotonicity of quantumness-generating capability are also identified. Finally, we compare these conditions for the monotonicity of quantumness-generating capability with those for various Markovianities and illustrate that quantumness-generating capability and quantum Markovianity are closely related, although they capture different aspects of quantum dynamics.

Influence of neuromuscular noise and walking speed on fall risk and dynamic stability in a 3D dynamic walking model.

PubMed

Roos, Paulien E; Dingwell, Jonathan B

2013-06-21

Older adults and those with increased fall risk tend to walk slower. They may do this voluntarily to reduce their fall risk. However, both slower and faster walking speeds can predict increased risk of different types of falls. The mechanisms that contribute to fall risk across speeds are not well known. Faster walking requires greater forward propulsion, generated by larger muscle forces. However, greater muscle activation induces increased signal-dependent neuromuscular noise. These speed-related increases in neuromuscular noise may contribute to the increased fall risk observed at faster walking speeds. Using a 3D dynamic walking model, we systematically varied walking speed without and with physiologically-appropriate neuromuscular noise. We quantified how actual fall risk changed with gait speed, how neuromuscular noise affected speed-related changes in fall risk, and how well orbital and local dynamic stability measures predicted changes in fall risk across speeds. When we included physiologically-appropriate noise to the 'push-off' force in our model, fall risk increased with increasing walking speed. Changes in kinematic variability, orbital, and local dynamic stability did not predict these speed-related changes in fall risk. Thus, the increased neuromuscular variability that results from increased signal-dependent noise that is necessitated by the greater muscular force requirements of faster walking may contribute to the increased fall risk observed at faster walking speeds. The lower fall risk observed at slower speeds supports experimental evidence that slowing down can be an effective strategy to reduce fall risk. This may help explain the slower walking speeds observed in older adults and others. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed Central

McLeish, Tom C. B.

2015-01-01

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

Environmental modeling in data-sparse regions: Mozambique demonstrator case

NASA Astrophysics Data System (ADS)

Schumann, G.; Niebuhr, E.; Rashid, K.; Escobar, V. M.; Andreadis, K.; Njoku, E. G.; Neal, J. C.; Voisin, N.; Pappenberger, F.; Phanthuwongpakdee, N.; Bates, P. D.; Chao, Y.; Moller, D.; Paron, P.

2014-12-01

Long time-series computations of seasonal and flood event inundation volumes from archived forecast rainfall events for the Lower Zambezi basin (Mozambique), using a coupled hydrology-hydrodynamic model, are correlated and regressed with satellite soil moisture observations and NWP rainfall forecasts as predictors for inundation volumes. This dynamic library of volume predictions can then be re-projected onto the topography to generate the corresponding floodplain and wetland inundation dynamics, including periods of flood and low flows. Especially for data-poor regions, the application potential of such a library of data is invaluable as the modeling chain is greatly simplified and readily available. The library is flexible, portable and transitional. Furthermore, deriving environmental indicators from this dynamic look-up catalogue would be relatively straightforward. Application fields are various and here we present conceptually a few that we plan to research in more detail and on some of which we already collaborate with other scientists and international institutions, though at the moment largely on an unfunded basis. The primary application is to implement an early warning system for flood inundation relief operations and flood inundation mitigation and resilience. Having this flood inundation warning system set up adequately would also allow looking into long-term predictions of crop productivity and consequently food security. Another potentially high-impact application is to relate flood inundation dynamics to disease modeling for public health monitoring and prediction, in particular focusing on Malaria. Last but not least, the dynamic inundation library we are building can be validated and complemented with advanced airborne radar imagery of flooding and inundated wetlands to study changes in wetland ecology and biodiversity with unprecedented detail in data-poor regions, in this case in particular the important wetlands of the Zambezi Delta.

Mathematical modeling and computational prediction of cancer drug resistance.

PubMed

Sun, Xiaoqiang; Hu, Bin

2017-06-23

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

Influence of Neuromuscular Noise and Walking Speed on Fall Risk and Dynamic Stability in a 3D Dynamic Walking Model

PubMed Central

Roos, Paulien E.; Dingwell, Jonathan B.

2013-01-01

Older adults and those with increased fall risk tend to walk slower. They may do this voluntarily to reduce their fall risk. However, both slower and faster walking speeds can predict increased risk of different types of falls. The mechanisms that contribute to fall risk across speeds are not well known. Faster walking requires greater forward propulsion, generated by larger muscle forces. However, greater muscle activation induces increased signal-dependent neuromuscular noise. These speed-related increases in neuromuscular noise may contribute to the increased fall risk observed at faster walking speeds. Using a 3D dynamic walking model, we systematically varied walking speed without and with physiologically-appropriate neuromuscular noise. We quantified how actual fall risk changed with gait speed, how neuromuscular noise affected speed-related changes in fall risk, and how well orbital and local dynamic stability measures predicted changes in fall risk across speeds. When we included physiologically-appropriate noise to the ‘push-off’ force in our model, fall risk increased with increasing walking speed. Changes in kinematic variability, orbital, and local dynamic stability did not predict these speed-related changes in fall risk. Thus, the increased neuromuscular variability that results from increased signal-dependent noise that is necessitated by the greater muscular force requirements of faster walking may contribute to the increased fall risk observed at faster walking speeds. The lower fall risk observed at slower speeds supports experimental evidence that slowing down can be an effective strategy to reduce fall risk. This may help explain the slower walking speeds observed in older adults and others. PMID:23659911

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

PubMed

McLeish, Tom C B

2015-12-06

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

Numerical simulation and experimentation of adjusting the curvatures of micro-cantilevers using the water-confined laser-generated plasma

NASA Astrophysics Data System (ADS)

Gu, Chunxing; Shen, Zongbao; Liu, Huixia; Li, Pin; Lu, Mengmeng; Zhao, Yinxin; Wang, Xiao

2013-04-01

This paper describes a precise and non-contact adjustment technique using the water-confined laser-generated plasma to adjust the curvature of micro-components (micro-mechanical cantilevers). A series of laser shock micro-adjustment experiments were conducted on 0.4 mm-thick Al samples using pulsed Nd:YAG lasers operating at 1064 nm wavelengths to verify the technical feasibility. Systematic study was carried out in the term of effects of various factors on the adjusting results, including laser energies, laser focus positions, laser shock times and confined regime configuration. The research results have shown that the different bending angles and bending directions can be obtained by changing the laser processing parameters. And, for the adjustment process, the absence of confined regime configuration could also generate suitable bending deformation. But, in the case of larger energy, the final surfaces would have the sign of ablation, hence resulting in poor surface quality. An analysis procedure including dynamic analysis performed by ANSYS/LS-DYNA and static analysis performed by ANSYS is presented in detail to attain the simulation of laser shock micro-adjustment to predict the final bending deformation. The predicted bending profiles is well correlated with the available experimental data, showing the finite element analysis can predict the final curvatures of the micro-cantilevers properly.

Euler Technology Assessment program for preliminary aircraft design employing SPLITFLOW code with Cartesian unstructured grid method

NASA Technical Reports Server (NTRS)

Finley, Dennis B.

1995-01-01

This report documents results from the Euler Technology Assessment program. The objective was to evaluate the efficacy of Euler computational fluid dynamics (CFD) codes for use in preliminary aircraft design. Both the accuracy of the predictions and the rapidity of calculations were to be assessed. This portion of the study was conducted by Lockheed Fort Worth Company, using a recently developed in-house Cartesian-grid code called SPLITFLOW. The Cartesian grid technique offers several advantages for this study, including ease of volume grid generation and reduced number of cells compared to other grid schemes. SPLITFLOW also includes grid adaptation of the volume grid during the solution convergence to resolve high-gradient flow regions. This proved beneficial in resolving the large vortical structures in the flow for several configurations examined in the present study. The SPLITFLOW code predictions of the configuration forces and moments are shown to be adequate for preliminary design analysis, including predictions of sideslip effects and the effects of geometry variations at low and high angles of attack. The time required to generate the results from initial surface definition is on the order of several hours, including grid generation, which is compatible with the needs of the design environment.

Characteristics of subgrid-resolved-scale dynamics in anisotropic turbulence, with application to rough-wall boundary layers

NASA Astrophysics Data System (ADS)

Juneja, Anurag; Brasseur, James G.

1999-10-01

Large-eddy simulation (LES) of the atmospheric boundary layer (ABL) using eddy viscosity subgrid-scale (SGS) models is known to poorly predict mean shear at the first few grid cells near the ground, a rough surface with no viscous sublayer. It has recently been shown that convective motions carry this localized error vertically to infect the entire ABL, and that the error is more a consequence of the SGS model than grid resolution in the near-surface inertial layer. Our goal was to determine what first-order errors in the predicted SGS terms lead to spurious expectation values, and what basic dynamics in the filtered equation for resolved scale (RS) velocity must be captured by SGS models to correct the deficiencies. Our analysis is of general relevance to LES of rough-wall high Reynolds number boundary layers, where the essential difficulty in the closure is the importance of the SGS acceleration terms, a consequence of necessary under-resolution of relevant energy-containing motions at the first few grid levels, leading to potentially strong couplings between the anisotropies in resolved velocity and predicted SGS dynamics. We analyze these two issues (under-resolution and anisotropy) in the absence of a wall using two direct numerical simulation datasets of homogeneous turbulence with very different anisotropic structure characteristic of the near-surface ABL: shear- and buoyancy-generated turbulence. We uncover three important issues which should be addressed in the design of SGS closures near rough walls and we provide a priori tests for the SGS model. First, we identify a strong spurious coupling between the anisotropic structure of the resolved velocity field and predicted SGS dynamics which can create a feedback loop to incorrectly enhance certain components of the predicted velocity field. Second, we find that eddy viscosity and "similarity" SGS models do not contain enough degrees of freedom to capture, at a sufficient level of accuracy, both RS-SGS energy flux and SGS-RS dynamics. Third, to correctly capture pressure transport near a wall, closures must be made more flexible to accommodate proper partitioning between SGS stress divergence and SGS pressure gradient.

Generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB.

PubMed

Lee, Leng-Feng; Umberger, Brian R

2016-01-01

Computer modeling, simulation and optimization are powerful tools that have seen increased use in biomechanics research. Dynamic optimizations can be categorized as either data-tracking or predictive problems. The data-tracking approach has been used extensively to address human movement problems of clinical relevance. The predictive approach also holds great promise, but has seen limited use in clinical applications. Enhanced software tools would facilitate the application of predictive musculoskeletal simulations to clinically-relevant research. The open-source software OpenSim provides tools for generating tracking simulations but not predictive simulations. However, OpenSim includes an extensive application programming interface that permits extending its capabilities with scripting languages such as MATLAB. In the work presented here, we combine the computational tools provided by MATLAB with the musculoskeletal modeling capabilities of OpenSim to create a framework for generating predictive simulations of musculoskeletal movement based on direct collocation optimal control techniques. In many cases, the direct collocation approach can be used to solve optimal control problems considerably faster than traditional shooting methods. Cyclical and discrete movement problems were solved using a simple 1 degree of freedom musculoskeletal model and a model of the human lower limb, respectively. The problems could be solved in reasonable amounts of time (several seconds to 1-2 hours) using the open-source IPOPT solver. The problems could also be solved using the fmincon solver that is included with MATLAB, but the computation times were excessively long for all but the smallest of problems. The performance advantage for IPOPT was derived primarily by exploiting sparsity in the constraints Jacobian. The framework presented here provides a powerful and flexible approach for generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB. This should allow researchers to more readily use predictive simulation as a tool to address clinical conditions that limit human mobility.

Generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB

PubMed Central

Lee, Leng-Feng

2016-01-01

Computer modeling, simulation and optimization are powerful tools that have seen increased use in biomechanics research. Dynamic optimizations can be categorized as either data-tracking or predictive problems. The data-tracking approach has been used extensively to address human movement problems of clinical relevance. The predictive approach also holds great promise, but has seen limited use in clinical applications. Enhanced software tools would facilitate the application of predictive musculoskeletal simulations to clinically-relevant research. The open-source software OpenSim provides tools for generating tracking simulations but not predictive simulations. However, OpenSim includes an extensive application programming interface that permits extending its capabilities with scripting languages such as MATLAB. In the work presented here, we combine the computational tools provided by MATLAB with the musculoskeletal modeling capabilities of OpenSim to create a framework for generating predictive simulations of musculoskeletal movement based on direct collocation optimal control techniques. In many cases, the direct collocation approach can be used to solve optimal control problems considerably faster than traditional shooting methods. Cyclical and discrete movement problems were solved using a simple 1 degree of freedom musculoskeletal model and a model of the human lower limb, respectively. The problems could be solved in reasonable amounts of time (several seconds to 1–2 hours) using the open-source IPOPT solver. The problems could also be solved using the fmincon solver that is included with MATLAB, but the computation times were excessively long for all but the smallest of problems. The performance advantage for IPOPT was derived primarily by exploiting sparsity in the constraints Jacobian. The framework presented here provides a powerful and flexible approach for generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB. This should allow researchers to more readily use predictive simulation as a tool to address clinical conditions that limit human mobility. PMID:26835184

Dynamic Scheduling for Veterans Health Administration Patients using Geospatial Dynamic Overbooking.

PubMed

Adams, Stephen; Scherer, William T; White, K Preston; Payne, Jason; Hernandez, Oved; Gerber, Mathew S; Whitehead, N Peter

2017-10-12

The Veterans Health Administration (VHA) is plagued by abnormally high no-show and cancellation rates that reduce the productivity and efficiency of its medical outpatient clinics. We address this issue by developing a dynamic scheduling system that utilizes mobile computing via geo-location data to estimate the likelihood of a patient arriving on time for a scheduled appointment. These likelihoods are used to update the clinic's schedule in real time. When a patient's arrival probability falls below a given threshold, the patient's appointment is canceled. This appointment is immediately reassigned to another patient drawn from a pool of patients who are actively seeking an appointment. The replacement patients are prioritized using their arrival probability. Real-world data were not available for this study, so synthetic patient data were generated to test the feasibility of the design. The method for predicting the arrival probability was verified on a real set of taxicab data. This study demonstrates that dynamic scheduling using geo-location data can reduce the number of unused appointments with minimal risk of double booking resulting from incorrect predictions. We acknowledge that there could be privacy concerns with regards to government possession of one's location and offer strategies for alleviating these concerns in our conclusion.

Modeling of Dynamic Behavior of Carbon Fiber-Reinforced Polymer (CFRP) Composite under X-ray Radiation.

PubMed

Zhang, Kun; Tang, Wenhui; Fu, Kunkun

2018-01-16

Carbon fiber-reinforced polymer (CFRP) composites have been increasingly used in spacecraft applications. Spacecraft may encounter highenergy-density X-ray radiation in outer space that can cause severe damage. To protect spacecraft from such unexpected damage, it is essential to predict the dynamic behavior of CFRP composites under X-ray radiation. In this study, we developed an in-house three-dimensional explicit finite element (FEM) code to investigate the dynamic responses of CFRP composite under X-ray radiation for the first time, by incorporating a modified PUFF equation-of-state. First, the blow-off impulse (BOI) momentum of an aluminum panel was predicted by our FEM code and compared with an existing radiation experiment. Then, the FEM code was utilized to determine the dynamic behavior of a CFRP composite under various radiation conditions. It was found that the numerical result was comparable with the experimental one. Furthermore, the CFRP composite was more effective than the aluminum panel in reducing radiation-induced pressure and BOI momentum. The numerical results also revealed that a 1 keV X-ray led to vaporization of surface materials and a high-magnitude compressive stress wave, whereas a low-magnitude stress wave was generated with no surface vaporization when a 3 keV X-ray was applied.

Modeling of Dynamic Behavior of Carbon Fiber-Reinforced Polymer (CFRP) Composite under X-ray Radiation

PubMed Central

Zhang, Kun; Tang, Wenhui; Fu, Kunkun

2018-01-01

Carbon fiber-reinforced polymer (CFRP) composites have been increasingly used in spacecraft applications. Spacecraft may encounter highenergy-density X-ray radiation in outer space that can cause severe damage. To protect spacecraft from such unexpected damage, it is essential to predict the dynamic behavior of CFRP composites under X-ray radiation. In this study, we developed an in-house three-dimensional explicit finite element (FEM) code to investigate the dynamic responses of CFRP composite under X-ray radiation for the first time, by incorporating a modified PUFF equation-of-state. First, the blow-off impulse (BOI) momentum of an aluminum panel was predicted by our FEM code and compared with an existing radiation experiment. Then, the FEM code was utilized to determine the dynamic behavior of a CFRP composite under various radiation conditions. It was found that the numerical result was comparable with the experimental one. Furthermore, the CFRP composite was more effective than the aluminum panel in reducing radiation-induced pressure and BOI momentum. The numerical results also revealed that a 1 keV X-ray led to vaporization of surface materials and a high-magnitude compressive stress wave, whereas a low-magnitude stress wave was generated with no surface vaporization when a 3 keV X-ray was applied. PMID:29337891

Ultra-fast quantum randomness generation by accelerated phase diffusion in a pulsed laser diode.

PubMed

Abellán, C; Amaya, W; Jofre, M; Curty, M; Acín, A; Capmany, J; Pruneri, V; Mitchell, M W

2014-01-27

We demonstrate a high bit-rate quantum random number generator by interferometric detection of phase diffusion in a gain-switched DFB laser diode. Gain switching at few-GHz frequencies produces a train of bright pulses with nearly equal amplitudes and random phases. An unbalanced Mach-Zehnder interferometer is used to interfere subsequent pulses and thereby generate strong random-amplitude pulses, which are detected and digitized to produce a high-rate random bit string. Using established models of semiconductor laser field dynamics, we predict a regime of high visibility interference and nearly complete vacuum-fluctuation-induced phase diffusion between pulses. These are confirmed by measurement of pulse power statistics at the output of the interferometer. Using a 5.825 GHz excitation rate and 14-bit digitization, we observe 43 Gbps quantum randomness generation.

Carbon deposition model for oxygen-hydrocarbon combustion. Task 6: Data analysis and formulation of an empirical model

NASA Technical Reports Server (NTRS)

Makel, Darby B.; Rosenberg, Sanders D.

1990-01-01

The formation and deposition of carbon (soot) was studied in the Carbon Deposition Model for Oxygen-Hydrocarbon Combustion Program. An empirical, 1-D model for predicting soot formation and deposition in LO2/hydrocarbon gas generators/preburners was derived. The experimental data required to anchor the model were identified and a test program to obtain the data was defined. In support of the model development, cold flow mixing experiments using a high injection density injector were performed. The purpose of this investigation was to advance the state-of-the-art in LO2/hydrocarbon gas generator design by developing a reliable engineering model of gas generator operation. The model was formulated to account for the influences of fluid dynamics, chemical kinetics, and gas generator hardware design on soot formation and deposition.

Modeling thrombin generation: plasma composition based approach.

PubMed

Brummel-Ziedins, Kathleen E; Everse, Stephen J; Mann, Kenneth G; Orfeo, Thomas

2014-01-01

Thrombin has multiple functions in blood coagulation and its regulation is central to maintaining the balance between hemorrhage and thrombosis. Empirical and computational methods that capture thrombin generation can provide advancements to current clinical screening of the hemostatic balance at the level of the individual. In any individual, procoagulant and anticoagulant factor levels together act to generate a unique coagulation phenotype (net balance) that is reflective of the sum of its developmental, environmental, genetic, nutritional and pharmacological influences. Defining such thrombin phenotypes may provide a means to track disease progression pre-crisis. In this review we briefly describe thrombin function, methods for assessing thrombin dynamics as a phenotypic marker, computationally derived thrombin phenotypes versus determined clinical phenotypes, the boundaries of normal range thrombin generation using plasma composition based approaches and the feasibility of these approaches for predicting risk.

Measurement of dijet azimuthal decorrelation in pp collisions at √{s}=8 TeV

NASA Astrophysics Data System (ADS)

Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Knünz, V.; König, A.; Krammer, M.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rad, N.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Schöfbeck, R.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Gonzalez, J. Suarez; Alderweireldt, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Lauwers, J.; Luyckx, S.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Zeid, S. Abu; Blekman, F.; D'Hondt, J.; Daci, N.; De Bruyn, I.; Deroover, K.; Heracleous, N.; Keaveney, J.; Lowette, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Van Parijs, I.; Barria, P.; Brun, H.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Léonard, A.; Maerschalk, T.; Marinov, A.; Perniè, L.; Randle-conde, A.; Seva, T.; Velde, C. Vander; Vanlaer, P.; Yonamine, R.; Zenoni, F.; Zhang, F.; Beernaert, K.; Benucci, L.; Cimmino, A.; Crucy, S.; Dobur, D.; Fagot, A.; Garcia, G.; Gul, M.; Mccartin, J.; Rios, A. A. Ocampo; Poyraz, D.; Ryckbosch, D.; Salva, S.; Sigamani, M.; Tytgat, M.; Van Driessche, W.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; Ceard, L.; Delaere, C.; Favart, D.; Forthomme, L.; Giammanco, A.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Mertens, A.; Musich, M.; Nuttens, C.; Perrini, L.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Marono, M. Vidal; Beliy, N.; Hammad, G. H.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Hamer, M.; Hensel, C.; Moraes, A.; Pol, M. E.; Teles, P. Rebello; Chagas, E. Belchior Batista Das; Carvalho, W.; Chinellato, J.; Custódio, A.; Costa, E. M. Da; Damiao, D. De Jesus; Martins, C. De Oliveira; De Souza, S. Fonseca; Guativa, L. M. Huertas; Malbouisson, H.; Figueiredo, D. Matos; Herrera, C. Mora; Mundim, L.; Nogima, H.; Silva, W. L. Prado Da; Santoro, A.; Sznajder, A.; Manganote, E. J. Tonelli; Pereira, A. Vilela; Ahuja, S.; Bernardes, C. A.; Santos, A. De Souza; Dogra, S.; Tomei, T. R. Fernandez Perez; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Abad, D. Romero; Vargas, J. C. Ruiz; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Cheng, T.; Du, R.; Jiang, C. H.; Leggat, D.; Plestina, R.; Romeo, F.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Zhang, H.; Asawatangtrakuldee, C.; Ban, Y.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Sierra, L. F. Chaparro; Florez, C.; Gomez, J. P.; Moreno, B. Gomez; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Puljak, I.; Cipriano, P. M. Ribeiro; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Kadija, K.; Luetic, J.; Micanovic, S.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Bodlak, M.; Finger, M.; Finger, M.; El-khateeb, E.; Elkafrawy, T.; Mohamed, A.; Salama, E.; Calpas, B.; Kadastik, M.; Murumaa, M.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Peltola, T.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; de Monchenault, G. Hamel; Jarry, P.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Zghiche, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Davignon, O.; Filipovic, N.; de Cassagnac, R. Granier; Jo, M.; Lisniak, S.; Mastrolorenzo, L.; Miné, P.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Goetzmann, C.; Bihan, A.-C. Le; Merlin, J. A.; Skovpen, K.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Bouvier, E.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; Mamouni, H. El; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Alvarez, J. D. Ruiz; Sabes, D.; Sgandurra, L.; Sordini, V.; Donckt, M. Vander; Verdier, P.; Viret, S.; Toriashvili, T.; Bagaturia, I.; Autermann, C.; Beranek, S.; Feld, L.; Heister, A.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Ostapchuk, A.; Preuten, M.; Raupach, F.; Schael, S.; Schulte, J. F.; Verlage, T.; Weber, H.; Zhukov, V.; Ata, M.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Kreuzer, P.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Papacz, P.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Hoehle, F.; Kargoll, B.; Kress, T.; Künsken, A.; Lingemann, J.; Nehrkorn, A.; Nowack, A.; Nugent, I. M.; Pistone, C.; Pooth, O.; Stahl, A.; Martin, M. Aldaya; Asin, I.; Bartosik, N.; Behnke, O.; Behrens, U.; Borras, K.; Burgmeier, A.; Campbell, A.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Dooling, S.; Dorland, T.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Flucke, G.; Gallo, E.; Garcia, J. 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M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; Field, R. D.; Furic, I. K.; Gleyzer, S. V.; Konigsberg, J.; Korytov, A.; Kotov, K.; Ma, P.; Matchev, K.; Mei, H.; Milenovic, P.; Mitselmakher, G.; Rank, D.; Rossin, R.; Shchutska, L.; Snowball, M.; Sperka, D.; Terentyev, N.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, J. R.; Adams, T.; Askew, A.; Bein, S.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Khatiwada, A.; Prosper, H.; Weinberg, M.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Kalakhety, H.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Kurt, P.; O'Brien, C.; Sandoval Gonzalez, I. D.; Turner, P.; Varelas, N.; Wu, Z.; Zakaria, M.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Anderson, I.; Barnett, B. A.; Blumenfeld, B.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Osherson, M.; Roskes, J.; Sady, A.; Sarica, U.; Swartz, M.; Xiao, M.; Xin, Y.; You, C.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Kenny, R. P.; Majumder, D.; Malek, M.; Mcbrayer, W.; Murray, M.; Sanders, S.; Stringer, R.; Wang, Q.; Ivanov, A.; Kaadze, K.; Khalil, S.; Makouski, M.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Lange, D.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Gomez, J. A.; Hadley, N. J.; Jabeen, S.; Kellogg, R. G.; Kolberg, T.; Kunkle, J.; Lu, Y.; Mignerey, A. C.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Baty, A.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; Demiragli, Z.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Sumorok, K.; Varma, M.; Velicanu, D.; Veverka, J.; Wang, J.; Wang, T. W.; Wyslouch, B.; Yang, M.; Zhukova, V.; Benvenuti, A. C.; Dahmes, B.; Evans, A.; Finkel, A.; Gude, A.; Hansen, P.; Kalafut, S.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bartek, R.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Knowlton, D.; Kravchenko, I.; Meier, F.; Monroy, J.; Ratnikov, F.; Siado, J. E.; Snow, G. R.; Alyari, M.; Dolen, J.; George, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Kaisen, J.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; De Lima, R. Teixeira; Trocino, D.; Wang, R.-J.; Wood, D.; Zhang, J.; Bhattacharya, S.; Hahn, K. A.; Kubik, A.; Low, J. F.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Smith, G.; Taroni, S.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hart, A.; Hill, C.; Hughes, R.; Ji, W.; Ling, T. Y.; Liu, B.; Luo, W.; Puigh, D.; Rodenburg, M.; Winer, B. L.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Tully, C.; Zuranski, A.; Malik, S.; Barker, A.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Jung, K.; Kumar, A.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. 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P.; Contreras-Campana, E.; Ferencek, D.; Gershtein, Y.; Halkiadakis, E.; Heindl, M.; Hidas, D.; Hughes, E.; Kaplan, S.; Kunnawalkam Elayavalli, R.; Lath, A.; Nash, K.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Foerster, M.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Castaneda Hernandez, A.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Kamon, T.; Krutelyov, V.; Mueller, R.; Osipenkov, I.; Pakhotin, Y.; Patel, R.; Perloff, A.; Rose, A.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Undleeb, S.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Wood, J.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Don, C. Kottachchi Kankanamge; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ruggles, T.; Sarangi, T.; Savin, A.; Sharma, A.; Smith, N.; Smith, W. H.; Taylor, D.; Verwilligen, P.; Woods, N.; CMS Collaboration

2016-10-01

A measurement of the decorrelation of azimuthal angles between the two jets with the largest transverse momenta is presented for seven regions of leading jet transverse momentum up to 2.2 TeV. The analysis is based on the proton-proton collision data collected with the CMS experiment at a centre-of-mass energy of 8 TeV corresponding to an integrated luminosity of 19.7 {fb}^{-1}. The dijet azimuthal decorrelation is caused by the radiation of additional jets and probes the dynamics of multijet production. The results are compared to fixed-order predictions of perturbative quantum chromodynamics (QCD), and to simulations using Monte Carlo event generators that include parton showers, hadronization, and multiparton interactions. Event generators with only two outgoing high transverse momentum partons fail to describe the measurement, even when supplemented with next-to-leading-order QCD corrections and parton showers. Much better agreement is achieved when at least three outgoing partons are complemented through either next-to-leading-order predictions or parton showers. This observation emphasizes the need to improve predictions for multijet production.

Arc Jet Facility Test Condition Predictions Using the ADSI Code

NASA Technical Reports Server (NTRS)

Palmer, Grant; Prabhu, Dinesh; Terrazas-Salinas, Imelda

2015-01-01

The Aerothermal Design Space Interpolation (ADSI) tool is used to interpolate databases of previously computed computational fluid dynamic solutions for test articles in a NASA Ames arc jet facility. The arc jet databases are generated using an Navier-Stokes flow solver using previously determined best practices. The arc jet mass flow rates and arc currents used to discretize the database are chosen to span the operating conditions possible in the arc jet, and are based on previous arc jet experimental conditions where possible. The ADSI code is a database interpolation, manipulation, and examination tool that can be used to estimate the stagnation point pressure and heating rate for user-specified values of arc jet mass flow rate and arc current. The interpolation is performed in the other direction (predicting mass flow and current to achieve a desired stagnation point pressure and heating rate). ADSI is also used to generate 2-D response surfaces of stagnation point pressure and heating rate as a function of mass flow rate and arc current (or vice versa). Arc jet test data is used to assess the predictive capability of the ADSI code.

Measurement of dijet azimuthal decorrelation in pp collisions at [Formula: see text].

PubMed

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De Sá, R Lopes; Lykken, J; Maeshima, K; Marraffino, J M; Maruyama, S; Mason, D; McBride, P; Merkel, P; Mrenna, S; Nahn, S; Newman-Holmes, C; O'Dell, V; Pedro, K; Prokofyev, O; Rakness, G; Sexton-Kennedy, E; Soha, A; Spalding, W J; Spiegel, L; Stoynev, S; Strobbe, N; Taylor, L; Tkaczyk, S; Tran, N V; Uplegger, L; Vaandering, E W; Vernieri, C; Verzocchi, M; Vidal, R; Wang, M; Weber, H A; Whitbeck, A; Acosta, D; Avery, P; Bortignon, P; Bourilkov, D; Brinkerhoff, A; Carnes, A; Carver, M; Curry, D; Das, S; Field, R D; Furic, I K; Gleyzer, S V; Konigsberg, J; Korytov, A; Kotov, K; Ma, P; Matchev, K; Mei, H; Milenovic, P; Mitselmakher, G; Rank, D; Rossin, R; Shchutska, L; Snowball, M; Sperka, D; Terentyev, N; Thomas, L; Wang, J; Wang, S; Yelton, J; Hewamanage, S; Linn, S; Markowitz, P; Martinez, G; Rodriguez, J L; Ackert, A; Adams, J R; Adams, T; Askew, A; Bein, S; Bochenek, J; Diamond, B; Haas, J; Hagopian, S; Hagopian, V; Johnson, K F; Khatiwada, A; Prosper, H; Weinberg, M; Baarmand, M M; Bhopatkar, V; Colafranceschi, S; Hohlmann, M; Kalakhety, H; Noonan, D; Roy, T; Yumiceva, F; Adams, M R; Apanasevich, L; Berry, D; Betts, R R; Bucinskaite, I; Cavanaugh, R; Evdokimov, O; Gauthier, L; Gerber, C E; Hofman, D J; Kurt, P; O'Brien, C; Sandoval Gonzalez, I D; Turner, P; Varelas, N; Wu, Z; Zakaria, M; Zhang, J; Bilki, B; Clarida, W; Dilsiz, K; Durgut, S; Gandrajula, R P; Haytmyradov, M; Khristenko, V; Merlo, J-P; Mermerkaya, H; Mestvirishvili, A; Moeller, A; Nachtman, J; Ogul, H; Onel, Y; Ozok, F; Penzo, A; Snyder, C; Tiras, E; Wetzel, J; Yi, K; Anderson, I; Barnett, B A; Blumenfeld, B; Eminizer, N; Fehling, D; Feng, L; Gritsan, A V; Maksimovic, P; Osherson, M; Roskes, J; Sady, A; Sarica, U; Swartz, M; Xiao, M; Xin, Y; You, C; Baringer, P; Bean, A; Benelli, G; Bruner, C; Kenny, R P; Majumder, D; Malek, M; Mcbrayer, W; Murray, M; Sanders, S; Stringer, R; Wang, Q; Ivanov, A; Kaadze, K; Khalil, S; Makouski, M; Maravin, Y; Mohammadi, A; Saini, L K; Skhirtladze, N; Toda, S; Lange, D; Rebassoo, F; Wright, D; Anelli, C; Baden, A; Baron, O; Belloni, A; Calvert, B; Eno, S C; Ferraioli, C; Gomez, J A; Hadley, N J; Jabeen, S; Kellogg, R G; Kolberg, T; Kunkle, J; Lu, Y; Mignerey, A C; Shin, Y H; Skuja, A; Tonjes, M B; Tonwar, S C; Apyan, A; Barbieri, R; Baty, A; Bierwagen, K; Brandt, S; Busza, W; Cali, I A; Demiragli, Z; Di Matteo, L; Gomez Ceballos, G; Goncharov, M; Gulhan, D; Iiyama, Y; Innocenti, G M; Klute, M; Kovalskyi, D; Lai, Y S; Lee, Y-J; Levin, A; Luckey, P D; Marini, A C; Mcginn, C; Mironov, C; Narayanan, S; Niu, X; Paus, C; Roland, C; Roland, G; Salfeld-Nebgen, J; Stephans, G S F; Sumorok, K; Varma, M; Velicanu, D; Veverka, J; Wang, J; Wang, T W; Wyslouch, B; Yang, M; Zhukova, V; Benvenuti, A C; Dahmes, B; Evans, A; Finkel, A; Gude, A; Hansen, P; Kalafut, S; Kao, S C; Klapoetke, K; Kubota, Y; Lesko, Z; Mans, J; Nourbakhsh, S; Ruckstuhl, N; Rusack, R; Tambe, N; Turkewitz, J; Acosta, J G; Oliveros, S; Avdeeva, E; Bartek, R; Bloom, K; Bose, S; Claes, D R; Dominguez, A; Fangmeier, C; Gonzalez Suarez, R; Kamalieddin, R; Knowlton, D; Kravchenko, I; Meier, F; Monroy, J; Ratnikov, F; Siado, J E; Snow, G R; Alyari, M; Dolen, J; George, J; Godshalk, A; Harrington, C; Iashvili, I; Kaisen, J; Kharchilava, A; Kumar, A; Rappoccio, S; Roozbahani, B; Alverson, G; Barberis, E; Baumgartel, D; Chasco, M; Hortiangtham, A; Massironi, A; Morse, D M; Nash, D; Orimoto, T; De Lima, R Teixeira; Trocino, D; Wang, R-J; Wood, D; Zhang, J; Bhattacharya, S; Hahn, K A; Kubik, A; Low, J F; Mucia, N; Odell, N; Pollack, B; Schmitt, M; Sung, K; Trovato, M; Velasco, M; Dev, N; Hildreth, M; Jessop, C; Karmgard, D J; Kellams, N; Lannon, K; Marinelli, N; Meng, F; Mueller, C; Musienko, Y; Planer, M; Reinsvold, A; Ruchti, R; Smith, G; Taroni, S; Valls, N; Wayne, M; Wolf, M; Woodard, A; Antonelli, L; Brinson, J; Bylsma, B; Durkin, L S; Flowers, S; Hart, A; Hill, C; Hughes, R; Ji, W; Ling, T Y; Liu, B; Luo, W; Puigh, D; Rodenburg, M; Winer, B L; Wulsin, H W; Driga, O; Elmer, P; Hardenbrook, J; Hebda, P; Koay, S A; Lujan, P; Marlow, D; Medvedeva, T; Mooney, M; Olsen, J; Palmer, C; Piroué, P; Stickland, D; Tully, C; Zuranski, A; Malik, S; Barker, A; Barnes, V E; Benedetti, D; Bortoletto, D; Gutay, L; Jha, M K; Jones, M; Jung, A W; Jung, K; Kumar, A; Miller, D H; Neumeister, N; Radburn-Smith, B C; Shi, X; Shipsey, I; Silvers, D; Sun, J; Svyatkovskiy, A; Wang, F; Xie, W; Xu, L; Parashar, N; Stupak, J; Adair, A; Akgun, B; Chen, Z; Ecklund, K M; Geurts, F J M; Guilbaud, M; Li, W; Michlin, B; Northup, M; Padley, B P; Redjimi, R; Roberts, J; Rorie, J; Tu, Z; Zabel, J; Betchart, B; Bodek, A; de Barbaro, P; Demina, R; Eshaq, Y; Ferbel, T; Galanti, M; Garcia-Bellido, A; Han, J; Harel, A; Hindrichs, O; Khukhunaishvili, A; Lo, K H; Petrillo, G; Tan, P; Verzetti, M; Chou, J P; Contreras-Campana, E; Ferencek, D; Gershtein, Y; Halkiadakis, E; Heindl, M; Hidas, D; Hughes, E; Kaplan, S; Kunnawalkam Elayavalli, R; Lath, A; Nash, K; Saka, H; Salur, S; Schnetzer, S; Sheffield, D; Somalwar, S; Stone, R; Thomas, S; Thomassen, P; Walker, M; Foerster, M; Riley, G; Rose, K; Spanier, S; Thapa, K; Bouhali, O; Castaneda Hernandez, A; Celik, A; Dalchenko, M; De Mattia, M; Delgado, A; Dildick, S; Eusebi, R; Gilmore, J; Huang, T; Kamon, T; Krutelyov, V; Mueller, R; Osipenkov, I; Pakhotin, Y; Patel, R; Perloff, A; Rose, A; Safonov, A; Tatarinov, A; Ulmer, K A; Akchurin, N; Cowden, C; Damgov, J; Dragoiu, C; Dudero, P R; Faulkner, J; Kunori, S; Lamichhane, K; Lee, S W; Libeiro, T; Undleeb, S; Volobouev, I; Appelt, E; Delannoy, A G; Greene, S; Gurrola, A; Janjam, R; Johns, W; Maguire, C; Mao, Y; Melo, A; Ni, H; Sheldon, P; Tuo, S; Velkovska, J; Xu, Q; Arenton, M W; Cox, B; Francis, B; Goodell, J; Hirosky, R; Ledovskoy, A; Li, H; Lin, C; Neu, C; Sinthuprasith, T; Sun, X; Wang, Y; Wolfe, E; Wood, J; Xia, F; Clarke, C; Harr, R; Karchin, P E; Don, C Kottachchi Kankanamge; Lamichhane, P; Sturdy, J; Belknap, D A; Carlsmith, D; Cepeda, M; Dasu, S; Dodd, L; Duric, S; Gomber, B; Grothe, M; Herndon, M; Hervé, A; Klabbers, P; Lanaro, A; Levine, A; Long, K; Loveless, R; Mohapatra, A; Ojalvo, I; Perry, T; Pierro, G A; Polese, G; Ruggles, T; Sarangi, T; Savin, A; Sharma, A; Smith, N; Smith, W H; Taylor, D; Verwilligen, P; Woods, N; Collaboration, Authorinst The Cms

2016-01-01

A measurement of the decorrelation of azimuthal angles between the two jets with the largest transverse momenta is presented for seven regions of leading jet transverse momentum up to 2.2[Formula: see text]. The analysis is based on the proton-proton collision data collected with the CMS experiment at a centre-of-mass energy of 8[Formula: see text] corresponding to an integrated luminosity of 19.7[Formula: see text]. The dijet azimuthal decorrelation is caused by the radiation of additional jets and probes the dynamics of multijet production. The results are compared to fixed-order predictions of perturbative quantum chromodynamics (QCD), and to simulations using Monte Carlo event generators that include parton showers, hadronization, and multiparton interactions. Event generators with only two outgoing high transverse momentum partons fail to describe the measurement, even when supplemented with next-to-leading-order QCD corrections and parton showers. Much better agreement is achieved when at least three outgoing partons are complemented through either next-to-leading-order predictions or parton showers. This observation emphasizes the need to improve predictions for multijet production.

An ITPA joint experiment to study runaway electron generation and suppression

DOE PAGES

Granetz, Robert S.; Esposito, B.; Kim, J. H.; ...

2014-07-11

Recent results from an ITPA joint experiment to study the onset, growth, and decay of relativistic electrons (REs) indicate that loss mechanisms other than collisional damping may play a dominant role in the dynamics of the RE population, even during the quiescent Ip flattop. Understanding the physics of RE growth and mitigation is motivated by the theoretical prediction that disruptions of full-current (15 MA) ITER discharges could generate up to 10 MA of REs with 10-20 MeV energies. The ITPA MHD group is conducting a joint experiment to measure the RE detection threshold conditions on a number of tokamaks undermore » quasi-steady-state conditions in which V loop, n e, and REs can be well-diagnosed and compared to collisional theory. Data from DIII-D, C-Mod, FTU, KSTAR, and TEXTOR have been obtained so far, and the consensus to date is that the threshold E-field is significantly higher than predicted by relativistic collisional theory, or conversely, the density required to damp REs is significantly less than predicted, which could have significant implications for RE mitigation on ITER.« less

Entropy analysis of frequency and shape change in horseshoe bat biosonar

NASA Astrophysics Data System (ADS)

Gupta, Anupam K.; Webster, Dane; Müller, Rolf

2018-06-01

Echolocating bats use ultrasonic pulses to collect information about their environments. Some of this information is encoded at the baffle structures—noseleaves (emission) and pinnae (reception)—that act as interfaces between the bats' biosonar systems and the external world. The baffle beam patterns encode the direction-dependent sensory information as a function of frequency and hence represent a view of the environment. To generate diverse views of the environment, the bats can vary beam patterns by changes to (1) the wavelengths of the pulses or (2) the baffle geometries. Here we compare the variability in sensory information encoded by just the use of frequency or baffle shape dynamics in horseshoe bats. For this, we use digital and physical prototypes of both noseleaf and pinnae. The beam patterns for all prototypes were either measured or numerically predicted. Entropy was used as a measure to compare variability as a measure of sensory information encoding capacity. It was found that new information was acquired as a result of shape dynamics. Furthermore, the overall variability available for information encoding was similar in the case of frequency or shape dynamics. Thus, shape dynamics allows the horseshoe bats to generate diverse views of the environment in the absence of broadband biosonar signals.

Defect dynamics and coarsening dynamics in smectic-C films

NASA Astrophysics Data System (ADS)

Pargellis, A. N.; Finn, P.; Goodby, J. W.; Panizza, P.; Yurke, B.; Cladis, P. E.

1992-12-01

We study the dynamics of defects generated in free-standing films of liquid crystals following a thermal quench from the smectic-A phase to the smectic-C phase. The defects are type-1 disclinations, and the strain field between defect pairs is confined to 2π walls. We compare our observations with a phenomenological model that includes dipole coupling of the director field to an external ordering field. This model is able to account for both the observed coalescence dynamics and the observed ordering dynamics. In the absence of an ordering field, our model predicts the defect density ρ to scale with time t as ρ lnρ~t-1. When the dipole coupling of the director field to an external ordering field is included, both the model and experiments show the defect coarsening proceeds as ρ~e-αt with the strain field confined to 2π walls. The external ordering field most likely arises from the director's tendency to align with edge dislocations within the liquid-crystal film.

Gas Generator Feedline Orifice Sizing Methodology: Effects of Unsteadiness and Non-Axisymmetric Flow

NASA Technical Reports Server (NTRS)

Rothermel, Jeffry; West, Jeffrey S.

2011-01-01

Engine LH2 and LO2 gas generator feed assemblies were modeled with computational fluid dynamics (CFD) methods at 100% rated power level, using on-center square- and round-edge orifices. The purpose of the orifices is to regulate the flow of fuel and oxidizer to the gas generator, enabling optimal power supply to the turbine and pump assemblies. The unsteady Reynolds-Averaged Navier-Stokes equations were solved on unstructured grids at second-order spatial and temporal accuracy. The LO2 model was validated against published experimental data and semi-empirical relationships for thin-plate orifices over a range of Reynolds numbers. Predictions for the LO2 square- and round-edge orifices precisely match experiment and semi-empirical formulas, despite complex feedline geometry whereby a portion of the flow from the engine main feedlines travels at a right-angle through a smaller-diameter pipe containing the orifice. Predictions for LH2 square- and round-edge orifice designs match experiment and semi-empirical formulas to varying degrees depending on the semi-empirical formula being evaluated. LO2 mass flow rate through the square-edge orifice is predicted to be 25 percent less than the flow rate budgeted in the original engine balance, which was subsequently modified. LH2 mass flow rate through the square-edge orifice is predicted to be 5 percent greater than the flow rate budgeted in the engine balance. Since CFD predictions for LO2 and LH2 square-edge orifice pressure loss coefficients, K, both agree with published data, the equation for K has been used to define a procedure for orifice sizing.

Firing Costs and Flexibility: Evidence from Firms’ Employment Responses to Shocks in India*

PubMed Central

Adhvaryu, Achyuta; Chari, A. V.; Sharma, Siddharth

2013-01-01

A key prediction of dynamic labor demand models is that firing restrictions attenuate firms’ employment responses to economic fluctuations. We provide the first direct test of this prediction using data from India. We exploit the fact that rainfall fluctuations, through their effects on agricultural productivity, generate variation in local demand within districts over time. Consistent with the theory, we find that industrial employment is more sensitive to shocks where labor regulation is less restrictive. Our results are robust to controlling for endogenous firm placement and vary across factory size in a pattern consistent with institutional features of Indian labor law. PMID:24357882

Test results of a 40-kW Stirling engine and comparison with the NASA Lewis computer code predictions

NASA Technical Reports Server (NTRS)

Allen, David J.; Cairelli, James E.

1988-01-01

A Stirling engine was tested without auxiliaries at Nasa-Lewis. Three different regenerator configurations were tested with hydrogen. The test objectives were: (1) to obtain steady-state and dynamic engine data, including indicated power, for validation of an existing computer model for this engine; and (2) to evaluate structurally the use of silicon carbide regenerators. This paper presents comparisons of the measured brake performance, indicated mean effective pressure, and cyclic pressure variations from those predicted by the code. The silicon carbide foam generators appear to be structurally suitable, but the foam matrix showed severely reduced performance.

Defect-induced solid state amorphization of molecular crystals

NASA Astrophysics Data System (ADS)

Lei, Lei; Carvajal, Teresa; Koslowski, Marisol

2012-04-01

We investigate the process of mechanically induced amorphization in small molecule organic crystals under extensive deformation. In this work, we develop a model that describes the amorphization of molecular crystals, in which the plastic response is calculated with a phase field dislocation dynamics theory in four materials: acetaminophen, sucrose, γ-indomethacin, and aspirin. The model is able to predict the fraction of amorphous material generated in single crystals for a given applied stress. Our results show that γ-indomethacin and sucrose demonstrate large volume fractions of amorphous material after sufficient plastic deformation, while smaller amorphous volume fractions are predicted in acetaminophen and aspirin, in agreement with experimental observation.

Numerical study of dynamic glottis and tidal breathing on respiratory sounds in a human upper airway model

PubMed Central

Wang, Zhaoxuan; Talaat, Khaled; Glide-Hurst, Carri; Dong, Haibo

2018-01-01

Background Human snores are caused by vibrating anatomical structures in the upper airway. The glottis is a highly variable structure and a critical organ regulating inhaled flows. However, the effects of the glottis motion on airflow and breathing sound are not well understood, while static glottises have been implemented in most previous in silico studies. The objective of this study is to develop a computational acoustic model of human airways with a dynamic glottis and quantify the effects of glottis motion and tidal breathing on airflow and sound generation. Methods Large eddy simulation and FW-H models were adopted to compute airflows and respiratory sounds in an image-based mouth-lung model. User-defined functions were developed that governed the glottis kinematics. Varying breathing scenarios (static vs. dynamic glottis; constant vs. sinusoidal inhalations) were simulated to understand the effects of glottis motion and inhalation pattern on sound generation. Pressure distributions were measured in airway casts with different glottal openings for model validation purpose. Results Significant flow fluctuations were predicted in the upper airways at peak inhalation rates or during glottal constriction. The inhalation speed through the glottis was the predominating factor in the sound generation while the transient effects were less important. For all frequencies considered (20–2500 Hz), the static glottis substantially underestimated the intensity of the generated sounds, which was most pronounced in the range of 100–500 Hz. Adopting an equivalent steady flow rather than a tidal breathing further underestimated the sound intensity. An increase of 25 dB in average was observed for the life condition (sine-dynamic) compared to the idealized condition (constant-rigid) for the broadband frequencies, with the largest increase of approximately 40 dB at the frequency around 250 Hz. Conclusion Results show that a severely narrowing glottis during inhalation, as well as flow fluctuations in the downstream trachea, can generate audible sound levels. PMID:29101633

Numerical study of dynamic glottis and tidal breathing on respiratory sounds in a human upper airway model.

PubMed

Xi, Jinxiang; Wang, Zhaoxuan; Talaat, Khaled; Glide-Hurst, Carri; Dong, Haibo

2018-05-01

Human snores are caused by vibrating anatomical structures in the upper airway. The glottis is a highly variable structure and a critical organ regulating inhaled flows. However, the effects of the glottis motion on airflow and breathing sound are not well understood, while static glottises have been implemented in most previous in silico studies. The objective of this study is to develop a computational acoustic model of human airways with a dynamic glottis and quantify the effects of glottis motion and tidal breathing on airflow and sound generation. Large eddy simulation and FW-H models were adopted to compute airflows and respiratory sounds in an image-based mouth-lung model. User-defined functions were developed that governed the glottis kinematics. Varying breathing scenarios (static vs. dynamic glottis; constant vs. sinusoidal inhalations) were simulated to understand the effects of glottis motion and inhalation pattern on sound generation. Pressure distributions were measured in airway casts with different glottal openings for model validation purpose. Significant flow fluctuations were predicted in the upper airways at peak inhalation rates or during glottal constriction. The inhalation speed through the glottis was the predominating factor in the sound generation while the transient effects were less important. For all frequencies considered (20-2500 Hz), the static glottis substantially underestimated the intensity of the generated sounds, which was most pronounced in the range of 100-500 Hz. Adopting an equivalent steady flow rather than a tidal breathing further underestimated the sound intensity. An increase of 25 dB in average was observed for the life condition (sine-dynamic) compared to the idealized condition (constant-rigid) for the broadband frequencies, with the largest increase of approximately 40 dB at the frequency around 250 Hz. Results show that a severely narrowing glottis during inhalation, as well as flow fluctuations in the downstream trachea, can generate audible sound levels.

Computational modeling for prediction of the shear stress of three-dimensional isotropic and aligned fiber networks.

PubMed

Park, Seungman

2017-09-01

Interstitial flow (IF) is a creeping flow through the interstitial space of the extracellular matrix (ECM). IF plays a key role in diverse biological functions, such as tissue homeostasis, cell function and behavior. Currently, most studies that have characterized IF have focused on the permeability of ECM or shear stress distribution on the cells, but less is known about the prediction of shear stress on the individual fibers or fiber networks despite its significance in the alignment of matrix fibers and cells observed in fibrotic or wound tissues. In this study, I developed a computational model to predict shear stress for different structured fibrous networks. To generate isotropic models, a random growth algorithm and a second-order orientation tensor were employed. Then, a three-dimensional (3D) solid model was created using computer-aided design (CAD) software for the aligned models (i.e., parallel, perpendicular and cubic models). Subsequently, a tetrahedral unstructured mesh was generated and flow solutions were calculated by solving equations for mass and momentum conservation for all models. Through the flow solutions, I estimated permeability using Darcy's law. Average shear stress (ASS) on the fibers was calculated by averaging the wall shear stress of the fibers. By using nonlinear surface fitting of permeability, viscosity, velocity, porosity and ASS, I devised new computational models. Overall, the developed models showed that higher porosity induced higher permeability, as previous empirical and theoretical models have shown. For comparison of the permeability, the present computational models were matched well with previous models, which justify our computational approach. ASS tended to increase linearly with respect to inlet velocity and dynamic viscosity, whereas permeability was almost the same. Finally, the developed model nicely predicted the ASS values that had been directly estimated from computational fluid dynamics (CFD). The present computational models will provide new tools for predicting accurate functional properties and designing fibrous porous materials, thereby significantly advancing tissue engineering. Copyright © 2017 Elsevier B.V. All rights reserved.

Forecasting climate change impacts on plant populations over large spatial extents

DOE PAGES

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; ...

2016-10-24

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less

Forecasting climate change impacts on plant populations over large spatial extents

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

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. Here, we overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates inmore » the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Finally, our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.« less

Forecasting climate change impacts on plant populations over large spatial extents

USGS Publications Warehouse

Tredennick, Andrew T.; Hooten, Mevin B.; Aldridge, Cameron L.; Homer, Collin G.; Kleinhesselink, Andrew R.; Adler, Peter B.

2016-01-01

Plant population models are powerful tools for predicting climate change impacts in one location, but are difficult to apply at landscape scales. We overcome this limitation by taking advantage of two recent advances: remotely sensed, species-specific estimates of plant cover and statistical models developed for spatiotemporal dynamics of animal populations. Using computationally efficient model reparameterizations, we fit a spatiotemporal population model to a 28-year time series of sagebrush (Artemisia spp.) percent cover over a 2.5 × 5 km landscape in southwestern Wyoming while formally accounting for spatial autocorrelation. We include interannual variation in precipitation and temperature as covariates in the model to investigate how climate affects the cover of sagebrush. We then use the model to forecast the future abundance of sagebrush at the landscape scale under projected climate change, generating spatially explicit estimates of sagebrush population trajectories that have, until now, been impossible to produce at this scale. Our broadscale and long-term predictions are rooted in small-scale and short-term population dynamics and provide an alternative to predictions offered by species distribution models that do not include population dynamics. Our approach, which combines several existing techniques in a novel way, demonstrates the use of remote sensing data to model population responses to environmental change that play out at spatial scales far greater than the traditional field study plot.

Coupled rotor/fuselage dynamic analysis of the AH-1G helicopter and correlation with flight vibrations data

NASA Technical Reports Server (NTRS)

Corrigan, J. C.; Cronkhite, J. D.; Dompka, R. V.; Perry, K. S.; Rogers, J. P.; Sadler, S. G.

1989-01-01

Under a research program designated Design Analysis Methods for VIBrationS (DAMVIBS), existing analytical methods are used for calculating coupled rotor-fuselage vibrations of the AH-1G helicopter for correlation with flight test data from an AH-1G Operational Load Survey (OLS) test program. The analytical representation of the fuselage structure is based on a NASTRAN finite element model (FEM), which has been developed, extensively documented, and correlated with ground vibration test. One procedure that was used for predicting coupled rotor-fuselage vibrations using the advanced Rotorcraft Flight Simulation Program C81 and NASTRAN is summarized. Detailed descriptions of the analytical formulation of rotor dynamics equations, fuselage dynamic equations, coupling between the rotor and fuselage, and solutions to the total system of equations in C81 are included. Analytical predictions of hub shears for main rotor harmonics 2p, 4p, and 6p generated by C81 are used in conjunction with 2p OLS measured control loads and a 2p lateral tail rotor gearbox force, representing downwash impingement on the vertical fin, to excite the NASTRAN model. NASTRAN is then used to correlate with measured OLS flight test vibrations. Blade load comparisons predicted by C81 showed good agreement. In general, the fuselage vibration correlations show good agreement between anslysis and test in vibration response through 15 to 20 Hz.

High-order harmonic generation by atoms in a few-cycle laser pulse: Carrier-envelope phase and many-electron effects

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

Frolov, M. V.; Manakov, N. L.; Silaev, A. A.

2011-02-15

Analytic formulas describing high-order harmonic generation (HHG) by atoms in a short laser pulse are obtained quantum mechanically in the tunneling limit. These results provide analytic expressions of the three-step HHG scenario, as well as of the returning electron wave packet, in a few-cycle pulse. Our results agree well with those of numerical solutions of the time-dependent Schroedinger equation for the H atom, while for Xe they predict many-electron atomic dynamics features in few-cycle HHG spectra and significant dependence of these features on the carrier-envelope phase of a laser pulse.

Physiological modules for generating discrete and rhythmic movements: action identification by a dynamic recurrent neural network.

PubMed

Bengoetxea, Ana; Leurs, Françoise; Hoellinger, Thomas; Cebolla, Ana M; Dan, Bernard; McIntyre, Joseph; Cheron, Guy

2014-01-01

In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.

Optimal Battery Utilization Over Lifetime for Parallel Hybrid Electric Vehicle to Maximize Fuel Economy

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

Patil, Chinmaya; Naghshtabrizi, Payam; Verma, Rajeev

This paper presents a control strategy to maximize fuel economy of a parallel hybrid electric vehicle over a target life of the battery. Many approaches to maximizing fuel economy of parallel hybrid electric vehicle do not consider the effect of control strategy on the life of the battery. This leads to an oversized and underutilized battery. There is a trade-off between how aggressively to use and 'consume' the battery versus to use the engine and consume fuel. The proposed approach addresses this trade-off by exploiting the differences in the fast dynamics of vehicle power management and slow dynamics of batterymore » aging. The control strategy is separated into two parts, (1) Predictive Battery Management (PBM), and (2) Predictive Power Management (PPM). PBM is the higher level control with slow update rate, e.g. once per month, responsible for generating optimal set points for PPM. The considered set points in this paper are the battery power limits and State Of Charge (SOC). The problem of finding the optimal set points over the target battery life that minimize engine fuel consumption is solved using dynamic programming. PPM is the lower level control with high update rate, e.g. a second, responsible for generating the optimal HEV energy management controls and is implemented using model predictive control approach. The PPM objective is to find the engine and battery power commands to achieve the best fuel economy given the battery power and SOC constraints imposed by PBM. Simulation results with a medium duty commercial hybrid electric vehicle and the proposed two-level hierarchical control strategy show that the HEV fuel economy is maximized while meeting a specified target battery life. On the other hand, the optimal unconstrained control strategy achieves marginally higher fuel economy, but fails to meet the target battery life.« less

A human ether-á-go-go-related (hERG) ion channel atomistic model generated by long supercomputer molecular dynamics simulations and its use in predicting drug cardiotoxicity.

PubMed

Anwar-Mohamed, Anwar; Barakat, Khaled H; Bhat, Rakesh; Noskov, Sergei Y; Tyrrell, D Lorne; Tuszynski, Jack A; Houghton, Michael

2014-11-04

Acquired cardiac long QT syndrome (LQTS) is a frequent drug-induced toxic event that is often caused through blocking of the human ether-á-go-go-related (hERG) K(+) ion channel. This has led to the removal of several major drugs post-approval and is a frequent cause of termination of clinical trials. We report here a computational atomistic model derived using long molecular dynamics that allows sensitive prediction of hERG blockage. It identified drug-mediated hERG blocking activity of a test panel of 18 compounds with high sensitivity and specificity and was experimentally validated using hERG binding assays and patch clamp electrophysiological assays. The model discriminates between potent, weak, and non-hERG blockers and is superior to previous computational methods. This computational model serves as a powerful new tool to predict hERG blocking thus rendering drug development safer and more efficient. As an example, we show that a drug that was halted recently in clinical development because of severe cardiotoxicity is a potent inhibitor of hERG in two different biological assays which could have been predicted using our new computational model. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Integration of nitrogen dynamics into the Noah-MP land surface model v1.1 for climate and environmental predictions

NASA Astrophysics Data System (ADS)

Cai, X.; Yang, Z.-L.; Fisher, J. B.; Zhang, X.; Barlage, M.; Chen, F.

2016-01-01

Climate and terrestrial biosphere models consider nitrogen an important factor in limiting plant carbon uptake, while operational environmental models view nitrogen as the leading pollutant causing eutrophication in water bodies. The community Noah land surface model with multi-parameterization options (Noah-MP) is unique in that it is the next-generation land surface model for the Weather Research and Forecasting meteorological model and for the operational weather/climate models in the National Centers for Environmental Prediction. In this study, we add a capability to Noah-MP to simulate nitrogen dynamics by coupling the Fixation and Uptake of Nitrogen (FUN) plant model and the Soil and Water Assessment Tool (SWAT) soil nitrogen dynamics. This model development incorporates FUN's state-of-the-art concept of carbon cost theory and SWAT's strength in representing the impacts of agricultural management on the nitrogen cycle. Parameterizations for direct root and mycorrhizal-associated nitrogen uptake, leaf retranslocation, and symbiotic biological nitrogen fixation are employed from FUN, while parameterizations for nitrogen mineralization, nitrification, immobilization, volatilization, atmospheric deposition, and leaching are based on SWAT. The coupled model is then evaluated at the Kellogg Biological Station - a Long Term Ecological Research site within the US Corn Belt. Results show that the model performs well in capturing the major nitrogen state/flux variables (e.g., soil nitrate and nitrate leaching). Furthermore, the addition of nitrogen dynamics improves the modeling of net primary productivity and evapotranspiration. The model improvement is expected to advance the capability of Noah-MP to simultaneously predict weather and water quality in fully coupled Earth system models.

Modelling soil-water dynamics in the rootzone of structured and water-repellent soils

NASA Astrophysics Data System (ADS)

Brown, Hamish; Carrick, Sam; Müller, Karin; Thomas, Steve; Sharp, Joanna; Cichota, Rogerio; Holzworth, Dean; Clothier, Brent

2018-04-01

In modelling the hydrology of Earth's critical zone, there are two major challenges. The first is to understand and model the processes of infiltration, runoff, redistribution and root-water uptake in structured soils that exhibit preferential flows through macropore networks. The other challenge is to parametrise and model the impact of ephemeral hydrophobicity of water-repellent soils. Here we have developed a soil-water model, which is based on physical principles, yet possesses simple functionality to enable easier parameterisation, so as to predict soil-water dynamics in structured soils displaying time-varying degrees of hydrophobicity. Our model, WEIRDO (Water Evapotranspiration Infiltration Redistribution Drainage runOff), has been developed in the APSIM Next Generation platform (Agricultural Production Systems sIMulation). The model operates on an hourly time-step. The repository for this open-source code is https://github.com/APSIMInitiative/ApsimX. We have carried out sensitivity tests to show how WEIRDO predicts infiltration, drainage, redistribution, transpiration and soil-water evaporation for three distinctly different soil textures displaying differing hydraulic properties. These three soils were drawn from the UNSODA (Unsaturated SOil hydraulic Database) soils database of the United States Department of Agriculture (USDA). We show how preferential flow process and hydrophobicity determine the spatio-temporal pattern of soil-water dynamics. Finally, we have validated WEIRDO by comparing its predictions against three years of soil-water content measurements made under an irrigated alfalfa (Medicago sativa L.) trial. The results provide validation of the model's ability to simulate soil-water dynamics in structured soils.

TADSim: Discrete Event-based Performance Prediction for Temperature Accelerated Dynamics

DOE PAGES

Mniszewski, Susan M.; Junghans, Christoph; Voter, Arthur F.; ...

2015-04-16

Next-generation high-performance computing will require more scalable and flexible performance prediction tools to evaluate software--hardware co-design choices relevant to scientific applications and hardware architectures. Here, we present a new class of tools called application simulators—parameterized fast-running proxies of large-scale scientific applications using parallel discrete event simulation. Parameterized choices for the algorithmic method and hardware options provide a rich space for design exploration and allow us to quickly find well-performing software--hardware combinations. We demonstrate our approach with a TADSim simulator that models the temperature-accelerated dynamics (TAD) method, an algorithmically complex and parameter-rich member of the accelerated molecular dynamics (AMD) family ofmore » molecular dynamics methods. The essence of the TAD application is captured without the computational expense and resource usage of the full code. We accomplish this by identifying the time-intensive elements, quantifying algorithm steps in terms of those elements, abstracting them out, and replacing them by the passage of time. We use TADSim to quickly characterize the runtime performance and algorithmic behavior for the otherwise long-running simulation code. We extend TADSim to model algorithm extensions, such as speculative spawning of the compute-bound stages, and predict performance improvements without having to implement such a method. Validation against the actual TAD code shows close agreement for the evolution of an example physical system, a silver surface. Finally, focused parameter scans have allowed us to study algorithm parameter choices over far more scenarios than would be possible with the actual simulation. This has led to interesting performance-related insights and suggested extensions.« less

Recipient-Biased Competition for an Intracellularly Generated Cross-Fed Nutrient Is Required for Coexistence of Microbial Mutualists

DOE PAGES

McCully, Alexandra L.; LaSarre, Breah; McKinlay, James B.; ...

2017-11-28

ABSTRACT Many mutualistic microbial relationships are based on nutrient cross-feeding. Traditionally, cross-feeding is viewed as being unidirectional, from the producer to the recipient. This is likely true when a producer’s waste, such as a fermentation product, has value only for a recipient. However, in some cases the cross-fed nutrient holds value for both the producer and the recipient. In such cases, there is potential for nutrient reacquisition by producer cells in a population, leading to competition against recipients. Here, we investigated the consequences of interpartner competition for cross-fed nutrients on mutualism dynamics by using an anaerobic coculture pairing fermentative Escherichiamore » coli and phototrophic Rhodopseudomonas palustris . In this coculture, E. coli excretes waste organic acids that provide a carbon source for R. palustris . In return, R. palustris cross-feeds E. coli ammonium (NH 4 + ), a compound that both species value. To explore the potential for interpartner competition, we first used a kinetic model to simulate cocultures with varied affinities for NH 4 + in each species. The model predicted that interpartner competition for NH 4 + could profoundly impact population dynamics. We then experimentally tested the predictions by culturing mutants lacking NH 4 + transporters in both NH 4 + competition assays and mutualistic cocultures. Both theoretical and experimental results indicated that the recipient must have a competitive advantage in acquiring cross-fed NH 4 + to sustain the mutualism. This recipient-biased competitive advantage is predicted to be crucial, particularly when the communally valuable nutrient is generated intracellularly. Thus, the very metabolites that form the basis for mutualistic cross-feeding can also be subject to competition between mutualistic partners. IMPORTANCE Mutualistic relationships, particularly those based on nutrient cross-feeding, promote stability of diverse ecosystems and drive global biogeochemical cycles. Cross-fed nutrients within these systems can be either waste products valued by only one partner or nutrients valued by both partners. Here, we explored how interpartner competition for a communally valuable cross-fed nutrient impacts mutualism dynamics. We discovered that mutualism stability necessitates that the recipient have a competitive advantage against the producer in obtaining the cross-fed nutrient, provided that the nutrient is generated intracellularly. We propose that the requirement for recipient-biased competition is a general rule for mutualistic coexistence based on the transfer of intracellularly generated, communally valuable resources.« less

Recipient-Biased Competition for an Intracellularly Generated Cross-Fed Nutrient Is Required for Coexistence of Microbial Mutualists

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

McCully, Alexandra L.; LaSarre, Breah; McKinlay, James B.

ABSTRACT Many mutualistic microbial relationships are based on nutrient cross-feeding. Traditionally, cross-feeding is viewed as being unidirectional, from the producer to the recipient. This is likely true when a producer’s waste, such as a fermentation product, has value only for a recipient. However, in some cases the cross-fed nutrient holds value for both the producer and the recipient. In such cases, there is potential for nutrient reacquisition by producer cells in a population, leading to competition against recipients. Here, we investigated the consequences of interpartner competition for cross-fed nutrients on mutualism dynamics by using an anaerobic coculture pairing fermentative Escherichiamore » coli and phototrophic Rhodopseudomonas palustris . In this coculture, E. coli excretes waste organic acids that provide a carbon source for R. palustris . In return, R. palustris cross-feeds E. coli ammonium (NH 4 + ), a compound that both species value. To explore the potential for interpartner competition, we first used a kinetic model to simulate cocultures with varied affinities for NH 4 + in each species. The model predicted that interpartner competition for NH 4 + could profoundly impact population dynamics. We then experimentally tested the predictions by culturing mutants lacking NH 4 + transporters in both NH 4 + competition assays and mutualistic cocultures. Both theoretical and experimental results indicated that the recipient must have a competitive advantage in acquiring cross-fed NH 4 + to sustain the mutualism. This recipient-biased competitive advantage is predicted to be crucial, particularly when the communally valuable nutrient is generated intracellularly. Thus, the very metabolites that form the basis for mutualistic cross-feeding can also be subject to competition between mutualistic partners. IMPORTANCE Mutualistic relationships, particularly those based on nutrient cross-feeding, promote stability of diverse ecosystems and drive global biogeochemical cycles. Cross-fed nutrients within these systems can be either waste products valued by only one partner or nutrients valued by both partners. Here, we explored how interpartner competition for a communally valuable cross-fed nutrient impacts mutualism dynamics. We discovered that mutualism stability necessitates that the recipient have a competitive advantage against the producer in obtaining the cross-fed nutrient, provided that the nutrient is generated intracellularly. We propose that the requirement for recipient-biased competition is a general rule for mutualistic coexistence based on the transfer of intracellularly generated, communally valuable resources.« less

Recipient-Biased Competition for an Intracellularly Generated Cross-Fed Nutrient Is Required for Coexistence of Microbial Mutualists.

PubMed

McCully, Alexandra L; LaSarre, Breah; McKinlay, James B

2017-11-28

Many mutualistic microbial relationships are based on nutrient cross-feeding. Traditionally, cross-feeding is viewed as being unidirectional, from the producer to the recipient. This is likely true when a producer's waste, such as a fermentation product, has value only for a recipient. However, in some cases the cross-fed nutrient holds value for both the producer and the recipient. In such cases, there is potential for nutrient reacquisition by producer cells in a population, leading to competition against recipients. Here, we investigated the consequences of interpartner competition for cross-fed nutrients on mutualism dynamics by using an anaerobic coculture pairing fermentative Escherichia coli and phototrophic Rhodopseudomonas palustris In this coculture, E. coli excretes waste organic acids that provide a carbon source for R. palustris In return, R. palustris cross-feeds E. coli ammonium (NH 4 + ), a compound that both species value. To explore the potential for interpartner competition, we first used a kinetic model to simulate cocultures with varied affinities for NH 4 + in each species. The model predicted that interpartner competition for NH 4 + could profoundly impact population dynamics. We then experimentally tested the predictions by culturing mutants lacking NH 4 + transporters in both NH 4 + competition assays and mutualistic cocultures. Both theoretical and experimental results indicated that the recipient must have a competitive advantage in acquiring cross-fed NH 4 + to sustain the mutualism. This recipient-biased competitive advantage is predicted to be crucial, particularly when the communally valuable nutrient is generated intracellularly. Thus, the very metabolites that form the basis for mutualistic cross-feeding can also be subject to competition between mutualistic partners. IMPORTANCE Mutualistic relationships, particularly those based on nutrient cross-feeding, promote stability of diverse ecosystems and drive global biogeochemical cycles. Cross-fed nutrients within these systems can be either waste products valued by only one partner or nutrients valued by both partners. Here, we explored how interpartner competition for a communally valuable cross-fed nutrient impacts mutualism dynamics. We discovered that mutualism stability necessitates that the recipient have a competitive advantage against the producer in obtaining the cross-fed nutrient, provided that the nutrient is generated intracellularly. We propose that the requirement for recipient-biased competition is a general rule for mutualistic coexistence based on the transfer of intracellularly generated, communally valuable resources. Copyright © 2017 McCully et al.

Spatiotemporal evolution of cavitation dynamics exhibited by flowing microbubbles during ultrasound exposure.

PubMed

Choi, James J; Coussios, Constantin-C

2012-11-01

Ultrasound and microbubble-based therapies utilize cavitation to generate bioeffects, yet cavitation dynamics during individual pulses and across consecutive pulses remain poorly understood under physiologically relevant flow conditions. SonoVue(®) microbubbles were made to flow (fluid velocity: 10-40 mm/s) through a vessel in a tissue-mimicking material and were exposed to ultrasound [frequency: 0.5 MHz, peak-rarefactional pressure (PRP): 150-1200 kPa, pulse length: 1-100,000 cycles, pulse repetition frequency (PRF): 1-50 Hz, number of pulses: 10-250]. Radiated emissions were captured on a linear array, and passive acoustic mapping was used to spatiotemporally resolve cavitation events. At low PRPs, stable cavitation was maintained throughout several pulses, thus generating a steady rise in energy with low upstream spatial bias within the focal volume. At high PRPs, inertial cavitation was concentrated in the first 6.3 ± 1.3 ms of a pulse, followed by an energy reduction and high upstream bias. Multiple pulses at PRFs below a flow-dependent critical rate (PRF(crit)) produced predictable and consistent cavitation dynamics. Above the PRF(crit), energy generated was unpredictable and spatially biased. In conclusion, key parameters in microbubble-seeded flow conditions were matched with specific types, magnitudes, distributions, and durations of cavitation; this may help in understanding empirically observed in vivo phenomena and guide future pulse sequence designs.

Power law versus exponential state transition dynamics: application to sleep-wake architecture.

PubMed

Chu-Shore, Jesse; Westover, M Brandon; Bianchi, Matt T

2010-12-02

Despite the common experience that interrupted sleep has a negative impact on waking function, the features of human sleep-wake architecture that best distinguish sleep continuity versus fragmentation remain elusive. In this regard, there is growing interest in characterizing sleep architecture using models of the temporal dynamics of sleep-wake stage transitions. In humans and other mammals, the state transitions defining sleep and wake bout durations have been described with exponential and power law models, respectively. However, sleep-wake stage distributions are often complex, and distinguishing between exponential and power law processes is not always straightforward. Although mono-exponential distributions are distinct from power law distributions, multi-exponential distributions may in fact resemble power laws by appearing linear on a log-log plot. To characterize the parameters that may allow these distributions to mimic one another, we systematically fitted multi-exponential-generated distributions with a power law model, and power law-generated distributions with multi-exponential models. We used the Kolmogorov-Smirnov method to investigate goodness of fit for the "incorrect" model over a range of parameters. The "zone of mimicry" of parameters that increased the risk of mistakenly accepting power law fitting resembled empiric time constants obtained in human sleep and wake bout distributions. Recognizing this uncertainty in model distinction impacts interpretation of transition dynamics (self-organizing versus probabilistic), and the generation of predictive models for clinical classification of normal and pathological sleep architecture.

Trajectory planning and optimal tracking for an industrial mobile robot

NASA Astrophysics Data System (ADS)

Hu, Huosheng; Brady, J. Michael; Probert, Penelope J.

1994-02-01

This paper introduces a unified approach to trajectory planning and tracking for an industrial mobile robot subject to non-holonomic constraints. We show (1) how a smooth trajectory is generated that takes into account the constraints from the dynamic environment and the robot kinematics; and (2) how a general predictive controller works to provide optimal tracking capability for nonlinear systems. The tracking performance of the proposed guidance system is analyzed by simulation.

Predicting and Controlling Complex Networks

DTIC Science & Technology

2015-06-22

vulnerability and to generate a global view of network security against attacks. By deploying network sensors at particular points in the Internet ...48006, 1-6 (2011). 2 13. L. Huang and Y.-C. Lai, “Cascading dynamics in complex quantum networks,” Chaos 21, 025107, 1-6 (2011). This work was selected...by July 2011 issue of Virtual Journal of Quantum Information (http://www.vjquantuminfo.org). 14. W.-X. Wang, Y.-C. Lai, and D. Armbruster, “Cascading

A flexible docking scheme to explore the binding selectivity of PDZ domains.

PubMed

Gerek, Z Nevin; Ozkan, S Banu

2010-05-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using ROSETTALIGAND, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 A. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately.

A flexible docking scheme to explore the binding selectivity of PDZ domains

PubMed Central

Gerek, Z Nevin; Ozkan, S Banu

2010-01-01

Modeling of protein binding site flexibility in molecular docking is still a challenging problem due to the large conformational space that needs sampling. Here, we propose a flexible receptor docking scheme: A dihedral restrained replica exchange molecular dynamics (REMD), where we incorporate the normal modes obtained by the Elastic Network Model (ENM) as dihedral restraints to speed up the search towards correct binding site conformations. To our knowledge, this is the first approach that uses ENM modes to bias REMD simulations towards binding induced fluctuations in docking studies. In our docking scheme, we first obtain the deformed structures of the unbound protein as initial conformations by moving along the binding fluctuation mode, and perform REMD using the ENM modes as dihedral restraints. Then, we generate an ensemble of multiple receptor conformations (MRCs) by clustering the lowest replica trajectory. Using RosettaLigand, we dock ligands to the clustered conformations to predict the binding pose and affinity. We apply this method to postsynaptic density-95/Dlg/ZO-1 (PDZ) domains; whose dynamics govern their binding specificity. Our approach produces the lowest energy bound complexes with an average ligand root mean square deviation of 0.36 Å. We further test our method on (i) homologs and (ii) mutant structures of PDZ where mutations alter the binding selectivity. In both cases, our approach succeeds to predict the correct pose and the affinity of binding peptides. Overall, with this approach, we generate an ensemble of MRCs that leads to predict the binding poses and specificities of a protein complex accurately. PMID:20196074

Human brain detects short-time nonlinear predictability in the temporal fine structure of deterministic chaotic sounds

NASA Astrophysics Data System (ADS)

Itoh, Kosuke; Nakada, Tsutomu

2013-04-01

Deterministic nonlinear dynamical processes are ubiquitous in nature. Chaotic sounds generated by such processes may appear irregular and random in waveform, but these sounds are mathematically distinguished from random stochastic sounds in that they contain deterministic short-time predictability in their temporal fine structures. We show that the human brain distinguishes deterministic chaotic sounds from spectrally matched stochastic sounds in neural processing and perception. Deterministic chaotic sounds, even without being attended to, elicited greater cerebral cortical responses than the surrogate control sounds after about 150 ms in latency after sound onset. Listeners also clearly discriminated these sounds in perception. The results support the hypothesis that the human auditory system is sensitive to the subtle short-time predictability embedded in the temporal fine structure of sounds.

Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana

PubMed Central

Fournier-Level, Alexandre; Perry, Emily O.; Wang, Jonathan A.; Braun, Peter T.; Migneault, Andrew; Cooper, Martha D.; Metcalf, C. Jessica E.; Schmitt, Johanna

2016-01-01

Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico “resurrection experiments” showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation. PMID:27140640

Predicting the evolutionary dynamics of seasonal adaptation to novel climates in Arabidopsis thaliana.

PubMed

Fournier-Level, Alexandre; Perry, Emily O; Wang, Jonathan A; Braun, Peter T; Migneault, Andrew; Cooper, Martha D; Metcalf, C Jessica E; Schmitt, Johanna

2016-05-17

Predicting whether and how populations will adapt to rapid climate change is a critical goal for evolutionary biology. To examine the genetic basis of fitness and predict adaptive evolution in novel climates with seasonal variation, we grew a diverse panel of the annual plant Arabidopsis thaliana (multiparent advanced generation intercross lines) in controlled conditions simulating four climates: a present-day reference climate, an increased-temperature climate, a winter-warming only climate, and a poleward-migration climate with increased photoperiod amplitude. In each climate, four successive seasonal cohorts experienced dynamic daily temperature and photoperiod variation over a year. We measured 12 traits and developed a genomic prediction model for fitness evolution in each seasonal environment. This model was used to simulate evolutionary trajectories of the base population over 50 y in each climate, as well as 100-y scenarios of gradual climate change following adaptation to a reference climate. Patterns of plastic and evolutionary fitness response varied across seasons and climates. The increased-temperature climate promoted genetic divergence of subpopulations across seasons, whereas in the winter-warming and poleward-migration climates, seasonal genetic differentiation was reduced. In silico "resurrection experiments" showed limited evolutionary rescue compared with the plastic response of fitness to seasonal climate change. The genetic basis of adaptation and, consequently, the dynamics of evolutionary change differed qualitatively among scenarios. Populations with fewer founding genotypes and populations with genetic diversity reduced by prior selection adapted less well to novel conditions, demonstrating that adaptation to rapid climate change requires the maintenance of sufficient standing variation.

Predictions for the $$\\bar{B}^{0}\\rightarrow \\bar{K}^{\\ast 0}$$ X(YZ) and $$\\bar{B}^{0}_{s}\\rightarrow\\phi$$ X(YZ) with X(4160), Y(3940), Z(3930)

DOE PAGES

Liang, Wei -Hong; Molina, R.; Xie, Ju -Jun; ...

2015-05-22

We investigate the decay ofmore » $$\\bar B^0 \\to \\bar K^{*0} R$$ and $$\\bar B^0_s \\to \\phi R$$ with $R$ being the $X(4160)$, $Y(3940)$, $Z(3930)$ resonances. Under the assumption that these states are dynamically generated from the vector-vector interaction, as has been concluded from several theoretical studies, we use a reaction mechanism of quark production at the elementary level, followed by hadronization of one final $$q \\bar q$$ pair into two vectors and posterior final state interaction of this pair of vector mesons to produce the resonances. With this procedure we are able to predict five ratios for these decays, which are closely linked to the dynamical nature of these states, and also predict the order of magnitude of the branching ratios which we find of the order of $$10^{-4}$$, well within the present measurable range. In order to further test the dynamical nature of these resonances we study the $$\\bar B^0_s \\to \\phi D^* \\bar D^*$$ and $$\\bar B^0_s \\to \\phi D_s^* \\bar D_s^*$$ decays close to the $$D^* \\bar D^*$$ and $$D_s^* \\bar D_s^*$$ thresholds and make predictions for the ratio of the mass distributions in these decays and the $$\\bar B^0_s \\to \\phi R$$ decay widths. In conclusion, the measurement of these decays rates can help unravel the nature of these resonances.« less

Mechanical Influences on Morphogenesis of the Knee Joint Revealed through Morphological, Molecular and Computational Analysis of Immobilised Embryos

PubMed Central

Roddy, Karen A.; Prendergast, Patrick J.; Murphy, Paula

2011-01-01

Very little is known about the regulation of morphogenesis in synovial joints. Mechanical forces generated from muscle contractions are required for normal development of several aspects of normal skeletogenesis. Here we show that biophysical stimuli generated by muscle contractions impact multiple events during chick knee joint morphogenesis influencing differential growth of the skeletal rudiment epiphyses and patterning of the emerging tissues in the joint interzone. Immobilisation of chick embryos was achieved through treatment with the neuromuscular blocking agent Decamethonium Bromide. The effects on development of the knee joint were examined using a combination of computational modelling to predict alterations in biophysical stimuli, detailed morphometric analysis of 3D digital representations, cell proliferation assays and in situ hybridisation to examine the expression of a selected panel of genes known to regulate joint development. This work revealed the precise changes to shape, particularly in the distal femur, that occur in an altered mechanical environment, corresponding to predicted changes in the spatial and dynamic patterns of mechanical stimuli and region specific changes in cell proliferation rates. In addition, we show altered patterning of the emerging tissues of the joint interzone with the loss of clearly defined and organised cell territories revealed by loss of characteristic interzone gene expression and abnormal expression of cartilage markers. This work shows that local dynamic patterns of biophysical stimuli generated from muscle contractions in the embryo act as a source of positional information guiding patterning and morphogenesis of the developing knee joint. PMID:21386908

FRAGSION: ultra-fast protein fragment library generation by IOHMM sampling.

PubMed

Bhattacharya, Debswapna; Adhikari, Badri; Li, Jilong; Cheng, Jianlin

2016-07-01

Speed, accuracy and robustness of building protein fragment library have important implications in de novo protein structure prediction since fragment-based methods are one of the most successful approaches in template-free modeling (FM). Majority of the existing fragment detection methods rely on database-driven search strategies to identify candidate fragments, which are inherently time-consuming and often hinder the possibility to locate longer fragments due to the limited sizes of databases. Also, it is difficult to alleviate the effect of noisy sequence-based predicted features such as secondary structures on the quality of fragment. Here, we present FRAGSION, a database-free method to efficiently generate protein fragment library by sampling from an Input-Output Hidden Markov Model. FRAGSION offers some unique features compared to existing approaches in that it (i) is lightning-fast, consuming only few seconds of CPU time to generate fragment library for a protein of typical length (300 residues); (ii) can generate dynamic-size fragments of any length (even for the whole protein sequence) and (iii) offers ways to handle noise in predicted secondary structure during fragment sampling. On a FM dataset from the most recent Critical Assessment of Structure Prediction, we demonstrate that FGRAGSION provides advantages over the state-of-the-art fragment picking protocol of ROSETTA suite by speeding up computation by several orders of magnitude while achieving comparable performance in fragment quality. Source code and executable versions of FRAGSION for Linux and MacOS is freely available to non-commercial users at http://sysbio.rnet.missouri.edu/FRAGSION/ It is bundled with a manual and example data. chengji@missouri.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Contribution of different generations of the brown shrimp Crangon crangon (L.) in the Dutch Wadden Sea to commercial fisheries: A dynamic energy budget approach

NASA Astrophysics Data System (ADS)

Campos, Joana; Van der Veer, Henk W.; Freitas, Vânia; Kooijman, Sebastiaan A. L. M.

2009-08-01

In this paper a contribution is made to the ongoing debate on which brown shrimp generation mostly sustains the autumn peak in coastal North Sea commercial fisheries: the generation born in summer, or the winter one. Since the two perspectives are based on different considerations on the growth timeframe from settlement till commercial size, the Dynamic Energy Budget (DEB) theory was applied to predict maximum possible growth under natural conditions. First, the parameters of the standard DEB model for Crangon crangon L. were estimated using available data sets. These were insufficient to allow a direct estimation, requiring a special protocol to achieve consistency between parameters. Next, the DEB model was validated by comparing simulations with published experimental data on shrimp growth in relation to water temperatures. Finally, the DEB model was applied to simulate growth under optimal food conditions using the prevailing water temperature conditions in the Wadden Sea. Results show clear differences between males and females whereby the fastest growth rates were observed in females. DEB model simulations of maximum growth in the Wadden Sea suggest that it is not the summer brood from the current year as Boddeke claimed, nor the previous winter generation as Kuipers and Dapper suggested, but more likely the summer generation from the previous year which contributes to the bulk of the fisheries recruits in autumn.

Human Guidance Behavior Decomposition and Modeling

NASA Astrophysics Data System (ADS)

Feit, Andrew James

Trained humans are capable of high performance, adaptable, and robust first-person dynamic motion guidance behavior. This behavior is exhibited in a wide variety of activities such as driving, piloting aircraft, skiing, biking, and many others. Human performance in such activities far exceeds the current capability of autonomous systems in terms of adaptability to new tasks, real-time motion planning, robustness, and trading safety for performance. The present work investigates the structure of human dynamic motion guidance that enables these performance qualities. This work uses a first-person experimental framework that presents a driving task to the subject, measuring control inputs, vehicle motion, and operator visual gaze movement. The resulting data is decomposed into subspace segment clusters that form primitive elements of action-perception interactive behavior. Subspace clusters are defined by both agent-environment system dynamic constraints and operator control strategies. A key contribution of this work is to define transitions between subspace cluster segments, or subgoals, as points where the set of active constraints, either system or operator defined, changes. This definition provides necessary conditions to determine transition points for a given task-environment scenario that allow a solution trajectory to be planned from known behavior elements. In addition, human gaze behavior during this task contains predictive behavior elements, indicating that the identified control modes are internally modeled. Based on these ideas, a generative, autonomous guidance framework is introduced that efficiently generates optimal dynamic motion behavior in new tasks. The new subgoal planning algorithm is shown to generate solutions to certain tasks more quickly than existing approaches currently used in robotics.

k-Nearest neighbour local linear prediction of scalp EEG activity during intermittent photic stimulation.

PubMed

Erla, Silvia; Faes, Luca; Tranquillini, Enzo; Orrico, Daniele; Nollo, Giandomenico

2011-05-01

The characterization of the EEG response to photic stimulation (PS) is an important issue with significant clinical relevance. This study aims to quantify and map the complexity of the EEG during PS, where complexity is measured as the degree of unpredictability resulting from local linear prediction. EEG activity was recorded with eyes closed (EC) and eyes open (EO) during resting and PS at 5, 10, and 15 Hz in a group of 30 healthy subjects and in a case-report of a patient suffering from cerebral ischemia. The mean squared prediction error (MSPE) resulting from k-nearest neighbour local linear prediction was calculated in each condition as an index of EEG unpredictability. The linear or nonlinear nature of the system underlying EEG activity was evaluated quantifying MSPE as a function of the neighbourhood size during local linear prediction, and by surrogate data analysis as well. Unpredictability maps were obtained for each subject interpolating MSPE values over a schematic head representation. Results on healthy subjects evidenced: (i) the prevalence of linear mechanisms in the generation of EEG dynamics, (ii) the lower predictability of EO EEG, (iii) the desynchronization of oscillatory mechanisms during PS leading to increased EEG complexity, (iv) the entrainment of alpha rhythm during EC obtained by 10 Hz PS, and (v) differences of EEG predictability among different scalp regions. Ischemic patient showed different MSPE values in healthy and damaged regions. The EEG predictability decreased moving from the early acute stage to a stage of partial recovery. These results suggest that nonlinear prediction can be a useful tool to characterize EEG dynamics during PS protocols, and may consequently constitute a complement of quantitative EEG analysis in clinical applications. Copyright © 2010 IPEM. Published by Elsevier Ltd. All rights reserved.

Chemically reacting fluid flow in exoplanet and brown dwarf atmospheres

NASA Astrophysics Data System (ADS)

Bordwell, Baylee; Brown, Benjamin P.; Oishi, Jeffrey S.

2016-11-01

In the past few decades, spectral observations of planets and brown dwarfs have demonstrated significant deviations from predictions in certain chemical abundances. Starting with Jupiter, these deviations were successfully explained to be the effect of fast dynamics on comparatively slow chemical reactions. These dynamical effects are treated using mixing length theory in what is known as the "quench" approximation. In these objects, however, both radiative and convective zones are present, and it is not clear that this approximation applies. To resolve this issue, we solve the fully compressible equations of fluid dynamics in a matched polytropic atmosphere using the state-of-the-art pseudospectral simulation framework Dedalus. Through the inclusion of passive tracers, we explore the transport properties of convective and radiative zones, and verify the classical eddy diffusion parameterization. With the addition of active tracers, we examine the interactions between dynamical and chemical processes using abstract chemical reactions. By locating the quench point (the point at which the dynamical and chemical timescales are the same) in different dynamical regimes, we test the quench approximation, and generate prescriptions for the exoplanet and brown dwarf communities.

Compression wave studies in Blair dolomite

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

Grady, D.E.; Hollenbach, R.E.; Schuler, K.W.

Dynamic compression wave studies have been conducted on Blair dolomite in the stress range of 0-7.0 GPa. Impact techniques were used to generate stress impulse input functions, and diffuse surface laser interferometry provided the dynamic instrumentation. Experimental particle velocity profiles obtained by this method were coupled with the conservation laws of mass and momentum to determine the stress-strain and stress-modulus constitutive properties of the material. Comparison between dynamic and quasistatic uniaxial stress-strain curves uncovered significant differences. Energy dissipated in a complete load and unload cycle differed by almost an order of magnitude and the longitudinal moduli differed by as muchmore » as a factor of two. Blair dolomite was observed to yield under dynamic loading at 2.5 GPa. Below 2.5 GPa the loading waves had a finite risetime and exhibited steady propagation. A finite linear viscoelastic constitutive model satisfactorily predicted the observed wave propagation. We speculate that dynamic properties of preexisting cracks provides a physical mechanism for both the rate dependent steady wave behavior and the difference between dynamic and quasistatic response.« less

The effect of physical parameterizations and initial data on the numerical prediction of the President's Day cyclone

NASA Technical Reports Server (NTRS)

Atlas, R.

1984-01-01

Results are presented from a series of forecast experiments which were conducted to assess the importance of large-scale dynamical processes, diabatic heating, and initial data to the prediction of the President's Day cyclone. The synoptic situation and NMC model forecasts for this case are summarized, and the analysis/forecast system and experiments are described. The GLAS Model forecast from the GLAS analysis at 0000 GMT 18 February is found to have correctly predicted intense coastal cyclogenesis and heavy precipitation. A forecast with surface heat and moisture fluxes eliminated failed to predict any cyclogenesis while a similar forecast with only the surface moisture flux excluded showed weak development. Diabatic heating resulting from oceanic fluxes significantly contributed to the generation of low-level cyclonic vorticity and the intensification and slow rate of movement of an upper level ridge over the western Atlantic.

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.

Dam Dynamics in the Colonial Northeast and Chesapeake: Hydrologic Implications

NASA Astrophysics Data System (ADS)

Bain, D. J.; Salant, N. L.; Brandt, S. L.

2008-12-01

Recent work has highlighted the widespread presence of low-head dams for power generation during the 19th century. However, this work largely depends on census numbers tabulated in the mid-1800s, over 200 years after European activity began in North America. In order to compare the hydrologic implications of colonial era low-head dam construction with the impacts of other simultaneous processes (e.g., expatriation of the beaver or forest clearance), we have compiled historical data on mills to reconstruct the temporal and spatial dynamics of low-head dam construction in the colonial northeastern United States (i.e., Virginia to Maine). This reconstruction, combined with the results of related work on beaver pond dynamics and deforestation, provides several insights into the distribution and impacts of human impoundments during this period. While the resulting hydrologic changes are large, the addition of human dams to the system seems to be minimally offset and less important than changes arising from the expatriation of the beaver or the removal of trees during this early period. In addition, the spatial patterns of dam construction are complex, making prediction of hydrologic and associated responses more difficult to predict.

Deformation and breakup of liquid-liquid threads, jets, and drops

NASA Astrophysics Data System (ADS)

Doshi, Pankaj

The formation and breakup of two-fluid jets and drops find application in various industrially important processes like microencapsulation, inkjet printing, dispersion and emulsion formation, micro fluidics. Two important aspects of these problems are studied in this thesis. The first regards the study of the dynamics of a two-fluid jet issuing out of a concentric nozzle and breaking into multiple liquid drops. The second aspect concerns the study of the dynamics of liquid-liquid interface rupture. Highly robust and accurate numerical algorithms based on the Galerkin finite element method (G/FEM) and elliptic mesh generation technique are developed. The most important results of this research are the prediction of compound drop formation and volume partitioning between primary drop and satellite drops, which are of critical importance for microencapsulation technology. Another equally important result is computational and experimental demonstration of a self-similar behavior for the rupture of liquid-liquid interface. The final focus is the study of the pinch-off dynamics of generalized-Newtonian fluids with deformation-rate-dependent rheology using asymptotic analysis and numerical computation. A significant result is the first ever prediction of self-similar pinch-off of liquid threads of generalized Newtonian fluids.

Molecular docking, 3D QSAR and dynamics simulation studies of imidazo-pyrrolopyridines as janus kinase 1 (JAK 1) inhibitors.

PubMed

Itteboina, Ramesh; Ballu, Srilata; Sivan, Sree Kanth; Manga, Vijjulatha

2016-10-01

Janus kinase 1 (JAK 1) plays a critical role in initiating responses to cytokines by the JAK-signal transducer and activator of transcription (JAK-STAT). This controls survival, proliferation and differentiation of a variety of cells. Docking, 3D quantitative structure activity relationship (3D-QSAR) and molecular dynamics (MD) studies were performed on a series of Imidazo-pyrrolopyridine derivatives reported as JAK 1 inhibitors. QSAR model was generated using 30 molecules in the training set; developed model showed good statistical reliability, which is evident from r 2 ncv and r 2 loo values. The predictive ability of this model was determined using a test set of 13 molecules that gave acceptable predictive correlation (r 2 Pred ) values. Finally, molecular dynamics simulation was performed to validate docking results and MM/GBSA calculations. This facilitated us to compare binding free energies of cocrystal ligand and newly designed molecule R1. The good concordance between the docking results and CoMFA/CoMSIA contour maps afforded obliging clues for the rational modification of molecules to design more potent JAK 1 inhibitors. Copyright © 2016 Elsevier Ltd. All rights reserved.

Molecular simulation study of cavity-generated instabilities in the superheated Lennard-Jones liquid

NASA Astrophysics Data System (ADS)

Torabi, Korosh; Corti, David S.

2010-10-01

Previous equilibrium-based density-functional theory (DFT) analyses of cavity formation in the pure component superheated Lennard-Jones (LJ) liquid [S. Punnathanam and D. S. Corti, J. Chem. Phys. 119, 10224 (2003); M. J. Uline and D. S. Corti, Phys. Rev. Lett. 99, 076102 (2007)] revealed that a thermodynamic limit of stability appears in which no liquidlike density profile can develop for cavity radii greater than some critical size (being a function of temperature and bulk density). The existence of these stability limits was also verified using isothermal-isobaric Monte Carlo (MC) simulations. To test the possible relevance of these limits of stability to a dynamically evolving system, one that may be important for homogeneous bubble nucleation, we perform isothermal-isobaric molecular dynamics (MD) simulations in which cavities of different sizes are placed within the superheated LJ liquid. When the impermeable boundary utilized to generate a cavity is removed, the MD simulations show that the cavity collapses and the overall density of the system remains liquidlike, i.e., the system is stable, when the initial cavity radius is below some certain value. On the other hand, when the initial radius is large enough, the cavity expands and the overall density of the system rapidly decreases toward vaporlike densities, i.e., the system is unstable. Unlike the DFT predictions, however, the transition between stability and instability is not infinitely sharp. The fraction of initial configurations that generate an instability (or a phase separation) increases from zero to unity as the initial cavity radius increases over a relatively narrow range of values, which spans the predicted stability limit obtained from equilibrium MC simulations. The simulation results presented here provide initial evidence that the equilibrium-based stability limits predicted in the previous DFT and MC simulation studies may play some role, yet to be fully determined, in the homogeneous nucleation and growth of embryos within metastable fluids.

Statistical properties of Charney-Hasegawa-Mima zonal flows

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

Anderson, Johan, E-mail: anderson.johan@gmail.com; Botha, G. J. J.

2015-05-15

A theoretical interpretation of numerically generated probability density functions (PDFs) of intermittent plasma transport events in unforced zonal flows is provided within the Charney-Hasegawa-Mima (CHM) model. The governing equation is solved numerically with various prescribed density gradients that are designed to produce different configurations of parallel and anti-parallel streams. Long-lasting vortices form whose flow is governed by the zonal streams. It is found that the numerically generated PDFs can be matched with analytical predictions of PDFs based on the instanton method by removing the autocorrelations from the time series. In many instances, the statistics generated by the CHM dynamics relaxesmore » to Gaussian distributions for both the electrostatic and vorticity perturbations, whereas in areas with strong nonlinear interactions it is found that the PDFs are exponentially distributed.« less

Simulation of Forward and Inverse X-ray Scattering From Shocked Materials

NASA Astrophysics Data System (ADS)

Barber, John; Marksteiner, Quinn; Barnes, Cris

2012-02-01

The next generation of high-intensity, coherent light sources should generate sufficient brilliance to perform in-situ coherent x-ray diffraction imaging (CXDI) of shocked materials. In this work, we present beginning-to-end simulations of this process. This includes the calculation of the partially-coherent intensity profiles of self-amplified stimulated emission (SASE) x-ray free electron lasers (XFELs), as well as the use of simulated, shocked molecular-dynamics-based samples to predict the evolution of the resulting diffraction patterns. In addition, we will explore the corresponding inverse problem by performing iterative phase retrieval to generate reconstructed images of the simulated sample. The development of these methods in the context of materials under extreme conditions should provide crucial insights into the design and capabilities of shocked in-situ imaging experiments.

Landslide Hazard from Coupled Inherent and Dynamic Probabilities

NASA Astrophysics Data System (ADS)

Strauch, R. L.; Istanbulluoglu, E.; Nudurupati, S. S.

2015-12-01

Landslide hazard research has typically been conducted independently from hydroclimate research. We sought to unify these two lines of research to provide regional scale landslide hazard information for risk assessments and resource management decision-making. Our approach couples an empirical inherent landslide probability, based on a frequency ratio analysis, with a numerical dynamic probability, generated by combining subsurface water recharge and surface runoff from the Variable Infiltration Capacity (VIC) macro-scale land surface hydrologic model with a finer resolution probabilistic slope stability model. Landslide hazard mapping is advanced by combining static and dynamic models of stability into a probabilistic measure of geohazard prediction in both space and time. This work will aid resource management decision-making in current and future landscape and climatic conditions. The approach is applied as a case study in North Cascade National Park Complex in northern Washington State.

Investigating the performances of a 1 MV high pulsed power linear transformer driver: from beam dynamics to x radiation

NASA Astrophysics Data System (ADS)

Maisonny, R.; Ribière, M.; Toury, M.; Plewa, J. M.; Caron, M.; Auriel, G.; d'Almeida, T.

2016-12-01

The performance of a 1 MV pulsed high-power linear transformer driver accelerator were extensively investigated based on a numerical approach which utilizes both electromagnetic and Monte Carlo simulations. Particle-in-cell calculations were employed to examine the beam dynamics throughout the magnetically insulated transmission line which governs the coupling between the generator and the electron diode. Based on the information provided by the study of the beam dynamics, and using Monte Carlo methods, the main properties of the resulting x radiation were predicted. Good agreement was found between these simulations and experimental results. This work provides a detailed understanding of mechanisms affecting the performances of this type of high current, high-voltage pulsed accelerator, which are very promising for a growing number of applications.

Exploring the formation pathways of donor-acceptor catenanes in aqueous dynamic combinatorial libraries.

PubMed

Cougnon, Fabien B L; Au-Yeung, Ho Yu; Pantoş, G Dan; Sanders, Jeremy K M

2011-03-09

The discovery through dynamic combinatorial chemistry (DCC) of a new generation of donor-acceptor [2]catenanes highlights the power of DCC to access unprecedented structures. While conventional thinking has limited the scope of donor-acceptor catenanes to strictly alternating stacks of donor (D) and acceptor (A) aromatic units, DCC is demonstrated in this paper to give access to unusual DAAD, DADD, and ADAA stacks. Each of these catenanes has specific structural requirements, allowing control of their formation. On the basis of these results, and on the observation that the catenanes represent kinetic bottlenecks in the reaction pathway, we propose a mechanism that explains and predicts the structures formed. Furthermore, the spontaneous assembly of catenanes in aqueous dynamic systems gives a fundamental insight into the role played by hydrophobic effect and donor-acceptor interactions when building such complex architectures.

Investigating the Transonic Flutter Boundary of the Benchmark Supercritical Wing

NASA Technical Reports Server (NTRS)

Heeg, Jennifer; Chwalowski, Pawel

2017-01-01

This paper builds on the computational aeroelastic results published previously and generated in support of the second Aeroelastic Prediction Workshop for the NASA Benchmark Supercritical Wing configuration. The computational results are obtained using FUN3D, an unstructured grid Reynolds-Averaged Navier-Stokes solver developed at the NASA Langley Research Center. The analysis results focus on understanding the dip in the transonic flutter boundary at a single Mach number (0.74), exploring an angle of attack range of ??1 to 8 and dynamic pressures from wind off to beyond flutter onset. The rigid analysis results are examined for insights into the behavior of the aeroelastic system. Both static and dynamic aeroelastic simulation results are also examined.

Modelling the spread of innovation in wild birds.

PubMed

Shultz, Thomas R; Montrey, Marcel; Aplin, Lucy M

2017-06-01

We apply three plausible algorithms in agent-based computer simulations to recent experiments on social learning in wild birds. Although some of the phenomena are simulated by all three learning algorithms, several manifestations of social conformity bias are simulated by only the approximate majority (AM) algorithm, which has roots in chemistry, molecular biology and theoretical computer science. The simulations generate testable predictions and provide several explanatory insights into the diffusion of innovation through a population. The AM algorithm's success raises the possibility of its usefulness in studying group dynamics more generally, in several different scientific domains. Our differential-equation model matches simulation results and provides mathematical insights into the dynamics of these algorithms. © 2017 The Author(s).

Elastic Multi-scale Mechanisms: Computation and Biological Evolution.

PubMed

Diaz Ochoa, Juan G

2018-01-01

Explanations based on low-level interacting elements are valuable and powerful since they contribute to identify the key mechanisms of biological functions. However, many dynamic systems based on low-level interacting elements with unambiguous, finite, and complete information of initial states generate future states that cannot be predicted, implying an increase of complexity and open-ended evolution. Such systems are like Turing machines, that overlap with dynamical systems that cannot halt. We argue that organisms find halting conditions by distorting these mechanisms, creating conditions for a constant creativity that drives evolution. We introduce a modulus of elasticity to measure the changes in these mechanisms in response to changes in the computed environment. We test this concept in a population of predators and predated cells with chemotactic mechanisms and demonstrate how the selection of a given mechanism depends on the entire population. We finally explore this concept in different frameworks and postulate that the identification of predictive mechanisms is only successful with small elasticity modulus.

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

Ye Jia; Lawrence Berkeley Laboratory, Berkeley, California 94720-8250; Li Youhong

Theoretical predictions indicate that ordered alloys can spontaneously develop a steady-state nanoscale microstructure when irradiated with energetic particles. This behavior derives from a dynamical competition between disordering in cascades and thermally activated reordering, which leads to self-organization of the chemical order parameter. We test this possibility by combining molecular dynamics (MD) and kinetic Monte Carlo (KMC) simulations. We first generate realistic distributions of disordered zones for Ni{sub 3}Al irradiated with 70 keV He and 1 MeV Kr ions using MD and then input this data into KMC to obtain predictions of steady state microstructures as a function of the irradiationmore » flux. Nanoscale patterning is observed for Kr ion irradiations but not for He ion irradiations. We illustrate, moreover, using image simulations of these KMC microstructures, that high-resolution transmission electron microscopy can be employed to identify nanoscale patterning. Finally, we indicate how this method could be used to synthesize functional thin films, with potential for magnetic applications.« less

Chaos emerging in soil failure patterns observed during tillage: Normalized deterministic nonlinear prediction (NDNP) and its application.

PubMed

Sakai, Kenshi; Upadhyaya, Shrinivasa K; Andrade-Sanchez, Pedro; Sviridova, Nina V

2017-03-01

Real-world processes are often combinations of deterministic and stochastic processes. Soil failure observed during farm tillage is one example of this phenomenon. In this paper, we investigated the nonlinear features of soil failure patterns in a farm tillage process. We demonstrate emerging determinism in soil failure patterns from stochastic processes under specific soil conditions. We normalized the deterministic nonlinear prediction considering autocorrelation and propose it as a robust way of extracting a nonlinear dynamical system from noise contaminated motion. Soil is a typical granular material. The results obtained here are expected to be applicable to granular materials in general. From a global scale to nano scale, the granular material is featured in seismology, geotechnology, soil mechanics, and particle technology. The results and discussions presented here are applicable in these wide research areas. The proposed method and our findings are useful with respect to the application of nonlinear dynamics to investigate complex motions generated from granular materials.

Neural Network Assisted Inverse Dynamic Guidance for Terminally Constrained Entry Flight

PubMed Central

Chen, Wanchun

2014-01-01

This paper presents a neural network assisted entry guidance law that is designed by applying Bézier approximation. It is shown that a fully constrained approximation of a reference trajectory can be made by using the Bézier curve. Applying this approximation, an inverse dynamic system for an entry flight is solved to generate guidance command. The guidance solution thus gotten ensures terminal constraints for position, flight path, and azimuth angle. In order to ensure terminal velocity constraint, a prediction of the terminal velocity is required, based on which, the approximated Bézier curve is adjusted. An artificial neural network is used for this prediction of the terminal velocity. The method enables faster implementation in achieving fully constrained entry flight. Results from simulations indicate improved performance of the neural network assisted method. The scheme is expected to have prospect for further research on automated onboard control of terminal velocity for both reentry and terminal guidance laws. PMID:24723821

Global reorganisation of cis-regulatory units upon lineage commitment of human embryonic stem cells

PubMed Central

Freire-Pritchett, Paula; Schoenfelder, Stefan; Várnai, Csilla; Wingett, Steven W; Cairns, Jonathan; Collier, Amanda J; García-Vílchez, Raquel; Furlan-Magaril, Mayra; Osborne, Cameron S; Fraser, Peter; Rugg-Gunn, Peter J; Spivakov, Mikhail

2017-01-01

Long-range cis-regulatory elements such as enhancers coordinate cell-specific transcriptional programmes by engaging in DNA looping interactions with target promoters. Deciphering the interplay between the promoter connectivity and activity of cis-regulatory elements during lineage commitment is crucial for understanding developmental transcriptional control. Here, we use Promoter Capture Hi-C to generate a high-resolution atlas of chromosomal interactions involving ~22,000 gene promoters in human pluripotent and lineage-committed cells, identifying putative target genes for known and predicted enhancer elements. We reveal extensive dynamics of cis-regulatory contacts upon lineage commitment, including the acquisition and loss of promoter interactions. This spatial rewiring occurs preferentially with predicted changes in the activity of cis-regulatory elements and is associated with changes in target gene expression. Our results provide a global and integrated view of promoter interactome dynamics during lineage commitment of human pluripotent cells. DOI: http://dx.doi.org/10.7554/eLife.21926.001 PMID:28332981

The inverse problem of using the information of historical data to estimate model errors is one of the science frontier research topics. In this study, we investigate such a problem using the classic Lorenz (1963) equation as a prediction model.

NASA Astrophysics Data System (ADS)

Wan, S.; He, W.

2016-12-01

The inverse problem of using the information of historical data to estimate model errors is one of the science frontier research topics. In this study, we investigate such a problem using the classic Lorenz (1963) equation as a prediction model and the Lorenz equation with a periodic evolutionary function as an accurate representation of reality to generate "observational data." On the basis of the intelligent features of evolutionary modeling (EM), including self-organization, self-adaptive and self-learning, the dynamic information contained in the historical data can be identified and extracted by computer automatically. Thereby, a new approach is proposed to estimate model errors based on EM in the present paper. Numerical tests demonstrate the ability of the new approach to correct model structural errors. In fact, it can actualize the combination of the statistics and dynamics to certain extent.

Near-trench slip potential of megaquakes evaluated from fault properties and conditions

PubMed Central

Hirono, Tetsuro; Tsuda, Kenichi; Tanikawa, Wataru; Ampuero, Jean-Paul; Shibazaki, Bunichiro; Kinoshita, Masataka; Mori, James J.

2016-01-01

Near-trench slip during large megathrust earthquakes (megaquakes) is an important factor in the generation of destructive tsunamis. We proposed a new approach to assessing the near-trench slip potential quantitatively by integrating laboratory-derived properties of fault materials and simulations of fault weakening and rupture propagation. Although the permeability of the sandy Nankai Trough materials are higher than that of the clayey materials from the Japan Trench, dynamic weakening by thermally pressurized fluid is greater at the Nankai Trough owing to higher friction, although initially overpressured fluid at the Nankai Trough restrains the fault weakening. Dynamic rupture simulations reproduced the large slip near the trench observed in the 2011 Tohoku-oki earthquake and predicted the possibility of a large slip of over 30 m for the impending megaquake at the Nankai Trough. Our integrative approach is applicable globally to subduction zones as a novel tool for the prediction of extreme tsunami-producing near-trench slip. PMID:27321861

Molecular modeling studies of structural properties of polyvinyl alcohol: a comparative study using INTERFACE force field.

PubMed

Radosinski, Lukasz; Labus, Karolina

2017-10-05

Polyvinyl alcohol (PVA) is a material with a variety of applications in separation, biotechnology, and biomedicine. Using combined Monte Carlo and molecular dynamics techniques, we present an extensive comparative study of second- and third-generation force fields Universal, COMPASS, COMPASS II, PCFF, and the newly developed INTERFACE, as applied to this system. In particular, we show that an INTERFACE force field provides a possibility of composing a reliable atomistic model to reproduce density change of PVA matrix in a narrow temperature range (298-348 K) and calculate a thermal expansion coefficient with reasonable accuracy. Thus, the INTERFACE force field may be used to predict mechanical properties of the PVA system, being a scaffold for hydrogels, with much greater accuracy than latter approaches. Graphical abstract Molecular Dynamics and Monte Carlo studies indicate that it is possible to predict properties of the PVA in narrow temperature range by using the INTERFACE force field.

Nonreactive mixing study of a scramjet swept-strut fuel injector

NASA Technical Reports Server (NTRS)

Mcclinton, C. R.; Torrence, M. G.; Gooderum, P. B.; Young, I. G.

1975-01-01

The results are presented of a cold-mixing investigation performed to supply combustor design information and to determine optimum normal fuel-injector configurations for a general scramjet swept-strut fuel injector. The experimental investigation was made with two swept struts in a closed duct at a Mach number of 4.4 and a nominal ratio of jet mass flow to air mass flow of 0.0295, with helium used to simulate hydrogen fuel. Four injector patterns were evaluated; they represented the range of hole spacing and the ratio of jet dynamic pressure to free-stream dynamic pressure. Helium concentration, pitot pressure, and static pressure in the downstream mixing region were measured to generate the contour plots needed to define the mixing-region flow field and the mixing parameters. Experimental results show that the fuel penetration from the struts was less than the predicted values based on flat-plate data; but the mixing rate was faster and produced a mixing length less than one-half that predicted.

Dynamic Radioisotope Power System Development for Space Explorations

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

Qualls, A L

Dynamic power conversion offers the potential to produce radioisotope power systems (RPS) that generate higher power outputs and utilize the Pu-238 radioisotope more efficiently than Radioisotope Thermoelectric Generators (RTG). Additionally, dynamic systems also offer the potential of producing generators with significantly reduced power degradation over the course of deep space missions so that more power will be available at the end of the mission when it is needed for both powering the science and transmitting the results. The development of dynamic generators involves addressing technical issues not typically associated with traditional thermoelectric generators. Developing long-life, robust and reliable dynamic conversionmore » technology is challenging yet essential to building a suitable generator. Considerations include working within existing handling infrastructure where possible so that development costs can be kept low and integrating dynamic generators into spacecraft, which may be more complex than integration of static systems. Methods of interfacing to and controlling a dynamic generator must be considered and new potential failure modes must be taken into account. This paper will address some of the key issues of dynamic RPS design, development and adaption.Dynamic power conversion offers the potential to produce Radioisotope Power Systems (RPS) that generate higher power outputs and utilize the available heat source plutonium fuel more efficiently than Radioisotope Thermoelectric Generators. Additionally, dynamic systems offer the potential of producing generators with significantly reduced power degradation over the course of deep space missions so that more power would be available at the end of the mission, when it is needed most for both powering science instruments and transmitting the resulting data. The development of dynamic generators involves addressing technical issues not typically associated with traditional thermoelectric generators. Developing long-life, robust, and reliable dynamic conversion technology is challenging yet essential to building a suitable flight-ready generator. Considerations include working within existing hardware-handling infrastructure, where possible, so that development costs can be kept low, and integrating dynamic generators into spacecraft, which may be more complex than integration of static thermoelectric systems. Methods of interfacing to and controlling a dynamic generator must also be considered, and new potential failure modes must be taken into account. This paper will address some of the key issues of dynamic RPS design, development, and adaption.« less

Dynamic modelling and simulation of CSP plant based on supercritical carbon dioxide closed Brayton cycle

NASA Astrophysics Data System (ADS)

Hakkarainen, Elina; Sihvonen, Teemu; Lappalainen, Jari

2017-06-01

Supercritical carbon dioxide (sCO2) has recently gained a lot of interest as a working fluid in different power generation applications. For concentrated solar power (CSP) applications, sCO2 provides especially interesting option if it could be used both as the heat transfer fluid (HTF) in the solar field and as the working fluid in the power conversion unit. This work presents development of a dynamic model of CSP plant concept, in which sCO2 is used for extracting the solar heat in Linear Fresnel collector field, and directly applied as the working fluid in the recuperative Brayton cycle; these both in a single flow loop. We consider the dynamic model is capable to predict the system behavior in typical operational transients in a physically plausible way. The novel concept was tested through simulation cases under different weather conditions. The results suggest that the concept can be successfully controlled and operated in the supercritical region to generate electric power during the daytime, and perform start-up and shut down procedures in order to stay overnight in sub-critical conditions. Besides the normal daily operation, the control system was demonstrated to manage disturbances due to sudden irradiance changes.

Transitions in Relationships With Older Parents: From Middle to Later Years

PubMed Central

Silverstein, Merril D.

2015-01-01

Objective. Although intergenerational relationships have been extensively examined, studies applying dynamic multidimensional treatments are rare. Employing the life course framework and the intergenerational solidarity and ambivalence paradigms, a typology of intergenerational relationships was derived and propositions about dynamics of intergenerational relationships were tested. Method. Using latent transition analysis, we modeled 4 waves of panel data spanning 18 years from the Longitudinal Study of Generations to examine how older parent–child relationships (N = 938) transitioned in and out of complex relational configurations. Results. We derived 5 relationship types roughly corresponding to those found in earlier research. Transitions in relationship type occurred mostly when both generations were relatively young, and along the lines of what attachment, ambivalence, and latent kinship theories would predict. When change did occur, it was primarily structured by factors affecting the availability of adult children, as well as circumstances that elevated the dependency of older parents and promoted both positive and negative reactivity in their adult children. Discussion. This study has demonstrated how typological analysis captures both the complexities and dynamics of intergenerational relationships in mature families. By including behavioral, emotional, and normative aspects of later life intergenerational relationships, we told a story that was more about continuity than change. PMID:24958693

Evaluation of Ochratoxin Recognition by Peptides Using Explicit Solvent Molecular Dynamics

PubMed Central

Thyparambil, Aby A.; Bazin, Ingrid; Guiseppi-Elie, Anthony

2017-01-01

Biosensing platforms based on peptide recognition provide a cost-effective and stable alternative to antibody-based capture and discrimination of ochratoxin-A (OTA) vs. ochratoxin-B (OTB) in monitoring bioassays. Attempts to engineer peptides with improved recognition efficacy require thorough structural and thermodynamic characterization of the binding-competent conformations. Classical molecular dynamics (MD) approaches alone do not provide a thorough assessment of a peptide’s recognition efficacy. In this study, in-solution binding properties of four different peptides, a hexamer (SNLHPK), an octamer (CSIVEDGK), NFO4 (VYMNRKYYKCCK), and a 13-mer (GPAGIDGPAGIRC), which were previously generated for OTA-specific recognition, were evaluated using an advanced MD simulation approach involving accelerated configurational search and predictive modeling. Peptide configurations relevant to ochratoxin binding were initially generated using biased exchange metadynamics and the dynamic properties associated with the in-solution peptide–ochratoxin binding were derived from Markov State Models. Among the various peptides, NFO4 shows superior in-solution OTA sensing and also shows superior selectivity for OTA vs. OTB due to the lower penalty associated with solvating its bound complex. Advanced MD approaches provide structural and energetic insights critical to the hapten-specific recognition to aid the engineering of peptides with better sensing efficacies. PMID:28505090

Design of a phased array for the generation of adaptive radiation force along a path surrounding a breast lesion for dynamic ultrasound elastography imaging.

PubMed

Ekeom, Didace; Hadj Henni, Anis; Cloutier, Guy

2013-03-01

This work demonstrates, with numerical simulations, the potential of an octagonal probe for the generation of radiation forces in a set of points following a path surrounding a breast lesion in the context of dynamic ultrasound elastography imaging. Because of the in-going wave adaptive focusing strategy, the proposed method is adapted to induce shear wave fronts to interact optimally with complex lesions. Transducer elements were based on 1-3 piezocomposite material. Three-dimensional simulations combining the finite element method and boundary element method with periodic boundary conditions in the elevation direction were used to predict acoustic wave radiation in a targeted region of interest. The coupling factor of the piezocomposite material and the radiated power of the transducer were optimized. The transducer's electrical impedance was targeted to 50 Ω. The probe was simulated by assembling the designed transducer elements to build an octagonal phased-array with 256 elements on each edge (for a total of 2048 elements). The central frequency is 4.54 MHz; simulated transducer elements are able to deliver enough power and can generate the radiation force with a relatively low level of voltage excitation. Using dynamic transmitter beamforming techniques, the radiation force along a path and resulting acoustic pattern in the breast were simulated assuming a linear isotropic medium. Magnitude and orientation of the acoustic intensity (radiation force) at any point of a generation path could be controlled for the case of an example representing a heterogeneous medium with an embedded soft mechanical inclusion.

Soil Water Balance and Vegetation Dynamics in two Water-limited Mediterranean Ecosystem on Sardinia under past and future climate change

NASA Astrophysics Data System (ADS)

Corona, R.; Montaldo, N.; Albertson, J. D.

2016-12-01

Water limited conditions strongly impacts soil and vegetation dynamics in Mediterranean regions, which are commonly heterogeneous ecosystems, characterized by inter-annual rainfall variability, topography variability and contrasting plant functional types (PFTs) competing for water use. Historical human influences (e.g., deforestation, urbanization) further altered these ecosystems. Sardinia island is a representative region of Mediterranean ecosystems. It is low urbanized except some plan areas close to the main cities where main agricultural activities are concentrated. Two contrasting case study sites are within the Flumendosa river basin (1700 km2). The first site is a typical grassland on an alluvial plan valley (soil depth > 2m) while the second is a patchy mixture of Mediterranean vegetation species (mainly wild olive trees and C3 herbaceous) that grow in a soil bounded from below by a rocky layer of basalt, partially fractured (soil depth 15 - 40 cm). In both sites land-surface fluxes and CO2 fluxes are estimated by the eddy correlation technique while soil moisture was continuously estimated with water content reflectometers, and periodically leaf area index (LAI) was estimated. The following objectives are addressed:1) pointing out the dynamics of land surface fluxes, soil moisture, CO2 and vegetation cover for two contrasting water-limited ecosystems; 2) assess the impact of the soil depth and type on the CO2 and water balance dynamics; 3) evaluate the impact of past and future climate change scenarios on the two contrasting ecosystems. For reaching the objectives an ecohydrologic model that couples a vegetation dynamic model (VDM), and a 3-component (bare soil, grass and woody vegetation) land surface model (LSM) has been used. Historical meteorological data are available from 1922 and hydro-meteorological scenarios are then generated using a weather generator. The VDM-LSM model predict soil water balance and vegetation dynamics for the generated hydrometeorological scenarios in the two contrasting ecosystems. Results demonstrate that vegetation dynamics are influenced by the inter-annual variability of atmospheric forcing, with vegetation density changing significantly according to seasonal rainfall amount. At the same time the vegetation dynamics affect the soil water balance.

Computer Simulation of Embryonic Systems: What can a ...

EPA Pesticide Factsheets

(1) Standard practice for assessing developmental toxicity is the observation of apical endpoints (intrauterine death, fetal growth retardation, structural malformations) in pregnant rats/rabbits following exposure during organogenesis. EPA’s computational toxicology research program (ToxCast) generated vast in vitro cellular and molecular effects data on >1858 chemicals in >600 high-throughput screening (HTS) assays. The diversity of assays has been increased for developmental toxicity with several HTS platforms, including the devTOX-quickPredict assay from Stemina Biomarker Discovery utilizing the human embryonic stem cell line (H9). Translating these HTS data into higher order-predictions of developmental toxicity is a significant challenge. Here, we address the application of computational systems models that recapitulate the kinematics of dynamical cell signaling networks (e.g., SHH, FGF, BMP, retinoids) in a CompuCell3D.org modeling environment. Examples include angiogenesis (angiodysplasia) and dysmorphogenesis. Being numerically responsive to perturbation, these models are amenable to data integration for systems Toxicology and Adverse Outcome Pathways (AOPs). The AOP simulation outputs predict potential phenotypes based on the in vitro HTS data ToxCast. A heuristic computational intelligence framework that recapitulates the kinematics of dynamical cell signaling networks in the embryo, together with the in vitro profiling data, produce quantitative pr

Computational Modeling and Simulation of Developmental ...

EPA Pesticide Factsheets

Standard practice for assessing developmental toxicity is the observation of apical endpoints (intrauterine death, fetal growth retardation, structural malformations) in pregnant rats/rabbits following exposure during organogenesis. EPA’s computational toxicology research program (ToxCast) generated vast in vitro cellular and molecular effects data on >1858 chemicals in >600 high-throughput screening (HTS) assays. The diversity of assays has been increased for developmental toxicity with several HTS platforms, including the devTOX-quickPredict assay from Stemina Biomarker Discovery utilizing the human embryonic stem cell line (H9). Translating these HTS data into higher order-predictions of developmental toxicity is a significant challenge. Here, we address the application of computational systems models that recapitulate the kinematics of dynamical cell signaling networks (e.g., SHH, FGF, BMP, retinoids) in a CompuCell3D.org modeling environment. Examples include angiogenesis (angiodysplasia) and dysmorphogenesis. Being numerically responsive to perturbation, these models are amenable to data integration for systems Toxicology and Adverse Outcome Pathways (AOPs). The AOP simulation outputs predict potential phenotypes based on the in vitro HTS data ToxCast. A heuristic computational intelligence framework that recapitulates the kinematics of dynamical cell signaling networks in the embryo, together with the in vitro profiling data, produce quantitative predic

Seamless Modeling for Research & Predictability of Severe Tropical Storms from Weather-to-Climate Timescales

NASA Astrophysics Data System (ADS)

Ramaswamy, V.; Chen, J. H.; Delworth, T. L.; Knutson, T. R.; Lin, S. J.; Murakami, H.; Vecchi, G. A.

2017-12-01

Damages from catastrophic tropical storms such as the 2017 destructive hurricanes compel an acceleration of scientific advancements to understand the genesis, underlying mechanisms, frequency, track, intensity, and landfall of these storms. The advances are crucial to provide improved early information for planners and responders. We discuss the development and utilization of a global modeling capability based on a novel atmospheric dynamical core ("Finite-Volume Cubed Sphere or FV3") which captures the realism of the recent tropical storms and is a part of the NOAA Next-Generation Global Prediction System. This capability is also part of an emerging seamless modeling system at NOAA/ Geophysical Fluid Dynamics Laboratory for simulating the frequency of storms on seasonal and longer timescales with high fidelity e.g., Atlantic hurricane frequency over the past decades. In addition, the same modeling system has also been employed to evaluate the nature of projected storms on the multi-decadal scales under the influence of anthropogenic factors such as greenhouse gases and aerosols. The seamless modeling system thus facilitates research into and the predictability of severe tropical storms across diverse timescales of practical interest to several societal sectors.

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

Wu, H.L.; Spronsen, G. van; Klaus, E.H.

A simulation model of the dynamics of a by-pass pig and related two-phase flow behavior along with field trials of the pig in a dry-gas pipeline have revealed significant gains in use of a by-pass pig in modifying gas and liquid production rates. The method can widen the possibility of applying two-phase flow pipeline transportation to cases in which separator or slug-catcher capacity is limited by practicality or cost. Pigging two-phase pipelines normally generates large liquid slug volumes in front of the pig. These require large separators or slug catchers. Using a high by-pass pig to disperse the liquid andmore » reduce the maximum liquid production rate before pig arrival has been investigated by Shell Exploration and Production companies. A simulation model of the dynamics of the pig and related two-phase flow behavior in the pipeline was used to predict the performance of by-pass pigs. Field trials in a dry-gas pipeline were carried out to provide friction data and to validate the model. The predicted mobility of the high by-pass pig in the pipeline and risers was verified and the beneficial effects due to the by-pass concept exceeded the prediction of the simplified model.« less

Towards Intelligent Control for Next Generation Aircraft

NASA Technical Reports Server (NTRS)

Acosta, Diana Michelle; KrishnaKumar, Kalmanje Srinvas; Frost, Susan Alane

2008-01-01

NASA Aeronautics Subsonic Fixed Wing Project is focused on mitigating the environmental and operation impacts expected as aviation operations triple by 2025. The approach is to extend technological capabilities and explore novel civil transport configurations that reduce noise, emissions, fuel consumption and field length. Two Next Generation (NextGen) aircraft have been identified to meet the Subsonic Fixed Wing Project goals - these are the Hybrid Wing-Body (HWB) and Cruise Efficient Short Take-Off and Landing (CESTOL) aircraft. The technologies and concepts developed for these aircraft complicate the vehicle s design and operation. In this paper, flight control challenges for NextGen aircraft are described. The objective of this paper is to examine the potential of state-of-the-art control architectures and algorithms to meet the challenges and needed performance metrics for NextGen flight control. A broad range of conventional and intelligent control approaches are considered, including dynamic inversion control, integrated flight-propulsion control, control allocation, adaptive dynamic inversion control, data-based predictive control and reinforcement learning control.

Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks

PubMed Central

2018-01-01

Much of the information the brain processes and stores is temporal in nature—a spoken word or a handwritten signature, for example, is defined by how it unfolds in time. However, it remains unclear how neural circuits encode complex time-varying patterns. We show that by tuning the weights of a recurrent neural network (RNN), it can recognize and then transcribe spoken digits. The model elucidates how neural dynamics in cortical networks may resolve three fundamental challenges: first, encode multiple time-varying sensory and motor patterns as stable neural trajectories; second, generalize across relevant spatial features; third, identify the same stimuli played at different speeds—we show that this temporal invariance emerges because the recurrent dynamics generate neural trajectories with appropriately modulated angular velocities. Together our results generate testable predictions as to how recurrent networks may use different mechanisms to generalize across the relevant spatial and temporal features of complex time-varying stimuli. PMID:29537963

Predictive process simulation of cryogenic implants for leading edge transistor design

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

Gossmann, Hans-Joachim; Zographos, Nikolas; Park, Hugh

2012-11-06

Two cryogenic implant TCAD-modules have been developed: (i) A continuum-based compact model targeted towards a TCAD production environment calibrated against an extensive data-set for all common dopants. Ion-specific calibration parameters related to damage generation and dynamic annealing were used and resulted in excellent fits to the calibration data-set. (ii) A Kinetic Monte Carlo (kMC) model including the full time dependence of ion-exposure that a particular spot on the wafer experiences, as well as the resulting temperature vs. time profile of this spot. It was calibrated by adjusting damage generation and dynamic annealing parameters. The kMC simulations clearly demonstrate the importancemore » of the time-structure of the beam for the amorphization process: Assuming an average dose-rate does not capture all of the physics and may lead to incorrect conclusions. The model enables optimization of the amorphization process through tool parameters such as scan speed or beam height.« less

Encoding sensory and motor patterns as time-invariant trajectories in recurrent neural networks.

PubMed

Goudar, Vishwa; Buonomano, Dean V

2018-03-14

Much of the information the brain processes and stores is temporal in nature-a spoken word or a handwritten signature, for example, is defined by how it unfolds in time. However, it remains unclear how neural circuits encode complex time-varying patterns. We show that by tuning the weights of a recurrent neural network (RNN), it can recognize and then transcribe spoken digits. The model elucidates how neural dynamics in cortical networks may resolve three fundamental challenges: first, encode multiple time-varying sensory and motor patterns as stable neural trajectories; second, generalize across relevant spatial features; third, identify the same stimuli played at different speeds-we show that this temporal invariance emerges because the recurrent dynamics generate neural trajectories with appropriately modulated angular velocities. Together our results generate testable predictions as to how recurrent networks may use different mechanisms to generalize across the relevant spatial and temporal features of complex time-varying stimuli. © 2018, Goudar et al.

Integrating Multibody Simulation and CFD: toward Complex Multidisciplinary Design Optimization

NASA Astrophysics Data System (ADS)

Pieri, Stefano; Poloni, Carlo; Mühlmeier, Martin

This paper describes the use of integrated multidisciplinary analysis and optimization of a race car model on a predefined circuit. The objective is the definition of the most efficient geometric configuration that can guarantee the lowest lap time. In order to carry out this study it has been necessary to interface the design optimization software modeFRONTIER with the following softwares: CATIA v5, a three dimensional CAD software, used for the definition of the parametric geometry; A.D.A.M.S./Motorsport, a multi-body dynamic simulation software; IcemCFD, a mesh generator, for the automatic generation of the CFD grid; CFX, a Navier-Stokes code, for the fluid-dynamic forces prediction. The process integration gives the possibility to compute, for each geometrical configuration, a set of aerodynamic coefficients that are then used in the multiboby simulation for the computation of the lap time. Finally an automatic optimization procedure is started and the lap-time minimized. The whole process is executed on a Linux cluster running CFD simulations in parallel.

Natural product-like virtual libraries: recursive atom-based enumeration.

PubMed

Yu, Melvin J

2011-03-28

A new molecular enumerator is described that allows chemically and architecturally diverse sets of natural product-like and drug-like structures to be generated from a core structure as simple as a single carbon atom or as complex as a polycyclic ring system. Integrated with a rudimentary machine-learning algorithm, the enumerator has the ability to assemble biased virtual libraries enriched in compounds predicted to meet target criteria. The ability to dynamically generate relatively small focused libraries in a recursive manner could reduce the computational time and infrastructure necessary to construct and manage extremely large static libraries. Depending on enumeration conditions, natural product-like structures can be produced with a wide range of heterocyclic and alicyclic ring assemblies. Because natural products represent a proven source of validated structures for identifying and designing new drug candidates, mimicking the structural and topological diversity found in nature with a dynamic set of virtual natural product-like compounds may facilitate the creation of new ideas for novel, biologically relevant lead structures in areas of uncharted chemical space.

Pros and cons of estimating the reproduction number from early epidemic growth rate of influenza A (H1N1) 2009.

PubMed

Nishiura, Hiroshi; Chowell, Gerardo; Safan, Muntaser; Castillo-Chavez, Carlos

2010-01-07

In many parts of the world, the exponential growth rate of infections during the initial epidemic phase has been used to make statistical inferences on the reproduction number, R, a summary measure of the transmission potential for the novel influenza A (H1N1) 2009. The growth rate at the initial stage of the epidemic in Japan led to estimates for R in the range 2.0 to 2.6, capturing the intensity of the initial outbreak among school-age children in May 2009. An updated estimate of R that takes into account the epidemic data from 29 May to 14 July is provided. An age-structured renewal process is employed to capture the age-dependent transmission dynamics, jointly estimating the reproduction number, the age-dependent susceptibility and the relative contribution of imported cases to secondary transmission. Pitfalls in estimating epidemic growth rates are identified and used for scrutinizing and re-assessing the results of our earlier estimate of R. Maximum likelihood estimates of R using the data from 29 May to 14 July ranged from 1.21 to 1.35. The next-generation matrix, based on our age-structured model, predicts that only 17.5% of the population will experience infection by the end of the first pandemic wave. Our earlier estimate of R did not fully capture the population-wide epidemic in quantifying the next-generation matrix from the estimated growth rate during the initial stage of the pandemic in Japan. In order to quantify R from the growth rate of cases, it is essential that the selected model captures the underlying transmission dynamics embedded in the data. Exploring additional epidemiological information will be useful for assessing the temporal dynamics. Although the simple concept of R is more easily grasped by the general public than that of the next-generation matrix, the matrix incorporating detailed information (e.g., age-specificity) is essential for reducing the levels of uncertainty in predictions and for assisting public health policymaking. Model-based prediction and policymaking are best described by sharing fundamental notions of heterogeneous risks of infection and death with non-experts to avoid potential confusion and/or possible misuse of modelling results.

Quiet High-Speed Fan

NASA Technical Reports Server (NTRS)

Lieber, Lysbeth; Repp, Russ; Weir, Donald S.

1996-01-01

A calibration of the acoustic and aerodynamic prediction methods was performed and a baseline fan definition was established and evaluated to support the quiet high speed fan program. A computational fluid dynamic analysis of the NASA QF-12 Fan rotor, using the DAWES flow simulation program was performed to demonstrate and verify the causes of the relatively poor aerodynamic performance observed during the fan test. In addition, the rotor flowfield characteristics were qualitatively compared to the acoustic measurements to identify the key acoustic characteristics of the flow. The V072 turbofan source noise prediction code was used to generate noise predictions for the TFE731-60 fan at three operating conditions and compared to experimental data. V072 results were also used in the Acoustic Radiation Code to generate far field noise for the TFE731-60 nacelle at three speed points for the blade passage tone. A full 3-D viscous flow simulation of the current production TFE731-60 fan rotor was performed with the DAWES flow analysis program. The DAWES analysis was used to estimate the onset of multiple pure tone noise, based on predictions of inlet shock position as a function of the rotor tip speed. Finally, the TFE731-60 fan rotor wake structure predicted by the DAWES program was used to define a redesigned stator with the leading edge configured to minimize the acoustic effects of rotor wake / stator interaction, without appreciably degrading performance.

CAD-Based Modeling of Advanced Rotary Wing Structures for Integrated 3-D Aeromechanics Analysis

NASA Astrophysics Data System (ADS)

Staruk, William

This dissertation describes the first comprehensive use of integrated 3-D aeromechanics modeling, defined as the coupling of 3-D solid finite element method (FEM) structural dynamics with 3-D computational fluid dynamics (CFD), for the analysis of a real helicopter rotor. The development of this new methodology (a departure from how rotor aeroelastic analysis has been performed for 40 years), its execution on a real rotor, and the fundamental understanding of aeromechanics gained from it, are the key contributions of this dissertation. This work also presents the first CFD/CSD analysis of a tiltrotor in edgewise flight, revealing many of its unique loading mechanisms. The use of 3-D FEM, integrated with a trim solver and aerodynamics modeling, has the potential to enhance the design of advanced rotors by overcoming fundamental limitations of current generation beam-based analysis tools and offering integrated internal dynamic stress and strain predictions for design. Two primary goals drove this research effort: 1) developing a methodology to create 3-D CAD-based brick finite element models of rotors including multibody joints, controls, and aerodynamic interfaces, and 2) refining X3D, the US Army's next generation rotor structural dynamics solver featuring 3-D FEM within a multibody formulation with integrated aerodynamics, to model a tiltrotor in the edgewise conversion flight regime, which drives critical proprotor structural loads. Prior tiltrotor analysis has primarily focused on hover aerodynamics with rigid blades or forward flight whirl-flutter stability with simplified aerodynamics. The first goal was met with the development of a detailed methodology for generating multibody 3-D structural models, starting from CAD geometry, continuing to higher-order hexahedral finite element meshing, to final assembly of the multibody model by creating joints, assigning material properties, and defining the aerodynamic interface. Several levels of verification and validation were carried out systematically, covering formulation, model accuracy, and accuracy of the physics of the problem and the many complex coupled aeromechanical phenomena that characterize the behavior of a tiltrotor in the conversion corridor. Compatibility of the new structural analysis models with X3D is demonstrated using analytical test cases, including 90° twisted beams and thick composite plates, and a notional bearingless rotor. Prediction of deformations and stresses in composite beams and plates is validated and verified against experimental measurements, theory, and state-of-the-art beam models. The second goal was met through integrated analysis of the Tilt Rotor Aeroacoustic Model (TRAM) proprotor using X3D coupled to Helios--the US Army's next generation CFD framework featuring a high fidelity Reynolds-average Navier-Stokes (RANS) structured/unstructured overset solver--as well as low order aerodynamic models. Although development of CFD was not part of this work, coupling X3D with Helios was, including establishing consistent interface definitions for blade deformations (for CFD mesh motion), aerodynamic interfaces (for loads transfer), and rotor control angles (for trim). It is expected that this method and solver will henceforth be an integral part of the Helios framework, providing an equal fidelity of representation for fluids and structures in the development of future advanced rotor systems. Structural dynamics analysis of the TRAM model show accurate prediction of the lower natural frequencies, demonstrating the ability to model advanced rotors from first principles using 3-D structural dynamics, and a study of how joint properties affect these frequencies reveals how X3D can be used as a detailed design tool. The CFD/CSD analysis reveals accurate prediction of rotor performance and airloads in edgewise flight when compared to wind tunnel test data. Structural blade loads trends are well predicted at low thrust, but a 3/rev component of flap and lag bending moment appearing in test data at high thrust remains a mystery. Efficiently simulating a gimbaled rotor is not trivial; a time-domain method with only a single blade model is proposed and tested. The internal stress in the blade, particularly at its root where the gimbal action has major influence, is carefully examined, revealing complex localized loading patterns.

Rossby and drift wave turbulence and zonal flows: The Charney-Hasegawa-Mima model and its extensions

NASA Astrophysics Data System (ADS)

Connaughton, Colm; Nazarenko, Sergey; Quinn, Brenda

2015-12-01

A detailed study of the Charney-Hasegawa-Mima model and its extensions is presented. These simple nonlinear partial differential equations suggested for both Rossby waves in the atmosphere and drift waves in a magnetically-confined plasma, exhibit some remarkable and nontrivial properties, which in their qualitative form, survive in more realistic and complicated models. As such, they form a conceptual basis for understanding the turbulence and zonal flow dynamics in real plasma and geophysical systems. Two idealised scenarios of generation of zonal flows by small-scale turbulence are explored: a modulational instability and turbulent cascades. A detailed study of the generation of zonal flows by the modulational instability reveals that the dynamics of this zonal flow generation mechanism differ widely depending on the initial degree of nonlinearity. The jets in the strongly nonlinear case further roll up into vortex streets and saturate, while for the weaker nonlinearities, the growth of the unstable mode reverses and the system oscillates between a dominant jet, which is slightly inclined to the zonal direction, and a dominant primary wave. A numerical proof is provided for the extra invariant in Rossby and drift wave turbulence-zonostrophy. While the theoretical derivations of this invariant stem from the wave kinetic equation which assumes weak wave amplitudes, it is shown to be relatively well-conserved for higher nonlinearities also. Together with the energy and enstrophy, these three invariants cascade into anisotropic sectors in the k-space as predicted by the Fjørtoft argument. The cascades are characterised by the zonostrophy pushing the energy to the zonal scales. A small scale instability forcing applied to the model has demonstrated the well-known drift wave-zonal flow feedback loop. The drift wave turbulence is generated from this primary instability. The zonal flows are then excited by either one of the generation mechanisms, extracting energy from the drift waves as they grow. Eventually the turbulence is completely suppressed and the zonal flows saturate. The turbulence spectrum is shown to diffuse in a manner which has been mathematically predicted. The insights gained from this simple model could provide a basis for equivalent studies in more sophisticated plasma and geophysical fluid dynamics models in an effort to fully understand the zonal flow generation, the turbulent transport suppression and the zonal flow saturation processes in both the plasma and geophysical contexts as well as other wave and turbulence systems where order evolves from chaos.

Seizure Prediction and its Applications

PubMed Central

Iasemidis, Leon D.

2011-01-01

Epilepsy is characterized by intermittent, paroxysmal, hypersynchronous electrical activity, that may remain localized and/or spread and severely disrupt the brain’s normal multi-task and multi-processing function. Epileptic seizures are the hallmarks of such activity and had been considered unpredictable. It is only recently that research on the dynamics of seizure generation by analysis of the brain’s electrographic activity (EEG) has shed ample light on the predictability of seizures, and illuminated the way to automatic, prospective, long-term prediction of seizures. The ability to issue warnings in real time of impending seizures (e.g., tens of minutes prior to seizure occurrence in the case of focal epilepsy), may lead to novel diagnostic tools and treatments for epilepsy. Applications may range from a simple warning to the patient, in order to avert seizure-associated injuries, to intervention by automatic timely administration of an appropriate stimulus, for example of a chemical nature like an anti-epileptic drug (AED), electromagnetic nature like vagus nerve stimulation (VNS), deep brain stimulation (DBS), transcranial direct current (TDC) or transcranial magnetic stimulation (TMS), and/or of another nature (e.g., ultrasonic, cryogenic, biofeedback operant conditioning). It is thus expected that seizure prediction could readily become an integral part of the treatment of epilepsy through neuromodulation, especially in the new generation of closed-loop seizure control systems. PMID:21939848

Differential roles of two delayed rectifier potassium currents in regulation of ventricular action potential duration and arrhythmia susceptibility.

PubMed

Devenyi, Ryan A; Ortega, Francis A; Groenendaal, Willemijn; Krogh-Madsen, Trine; Christini, David J; Sobie, Eric A

2017-04-01

Arrhythmias result from disruptions to cardiac electrical activity, although the factors that control cellular action potentials are incompletely understood. We combined mathematical modelling with experiments in heart cells from guinea pigs to determine how cellular electrical activity is regulated. A mismatch between modelling predictions and the experimental results allowed us to construct an improved, more predictive mathematical model. The balance between two particular potassium currents dictates how heart cells respond to perturbations and their susceptibility to arrhythmias. Imbalances of ionic currents can destabilize the cardiac action potential and potentially trigger lethal cardiac arrhythmias. In the present study, we combined mathematical modelling with information-rich dynamic clamp experiments to determine the regulation of action potential morphology in guinea pig ventricular myocytes. Parameter sensitivity analysis was used to predict how changes in ionic currents alter action potential duration, and these were tested experimentally using dynamic clamp, a technique that allows for multiple perturbations to be tested in each cell. Surprisingly, we found that a leading mathematical model, developed with traditional approaches, systematically underestimated experimental responses to dynamic clamp perturbations. We then re-parameterized the model using a genetic algorithm, which allowed us to estimate ionic current levels in each of the cells studied. This unbiased model adjustment consistently predicted an increase in the rapid delayed rectifier K + current and a drastic decrease in the slow delayed rectifier K + current, and this prediction was validated experimentally. Subsequent simulations with the adjusted model generated the clinically relevant prediction that the slow delayed rectifier is better able to stabilize the action potential and suppress pro-arrhythmic events than the rapid delayed rectifier. In summary, iterative coupling of simulations and experiments enabled novel insight into how the balance between cardiac K + currents influences ventricular arrhythmia susceptibility. © 2016 The Authors. The Journal of Physiology © 2016 The Physiological Society.

Predicting the effect of angular momentum on the dissociation dynamics of highly rotationally excited radical intermediates.

PubMed

Brynteson, Matthew D; Butler, Laurie J

2015-02-07

We present a model which accurately predicts the net speed distributions of products resulting from the unimolecular decomposition of rotationally excited radicals. The radicals are produced photolytically from a halogenated precursor under collision-free conditions so they are not in a thermal distribution of rotational states. The accuracy relies on the radical dissociating with negligible energetic barrier beyond the endoergicity. We test the model predictions using previous velocity map imaging and crossed laser-molecular beam scattering experiments that photolytically generated rotationally excited CD2CD2OH and C3H6OH radicals from brominated precursors; some of those radicals then undergo further dissociation to CD2CD2 + OH and C3H6 + OH, respectively. We model the rotational trajectories of these radicals, with high vibrational and rotational energy, first near their equilibrium geometry, and then by projecting each point during the rotation to the transition state (continuing the rotational dynamics at that geometry). This allows us to accurately predict the recoil velocity imparted in the subsequent dissociation of the radical by calculating the tangential velocities of the CD2CD2/C3H6 and OH fragments at the transition state. The model also gives a prediction for the distribution of angles between the dissociation fragments' velocity vectors and the initial radical's velocity vector. These results are used to generate fits to the previously measured time-of-flight distributions of the dissociation fragments; the fits are excellent. The results demonstrate the importance of considering the precession of the angular velocity vector for a rotating radical. We also show that if the initial angular momentum of the rotating radical lies nearly parallel to a principal axis, the very narrow range of tangential velocities predicted by this model must be convoluted with a J = 0 recoil velocity distribution to achieve a good result. The model relies on measuring the kinetic energy release when the halogenated precursor is photodissociated via a repulsive excited state but does not include any adjustable parameters. Even when different conformers of the photolytic precursor are populated, weighting the prediction by a thermal conformer population gives an accurate prediction for the relative velocity vectors of the fragments from the highly rotationally excited radical intermediates.

Dynamic response and transfer function of social systems: A neuro-inspired model of collective human activity patterns.

PubMed

Lymperopoulos, Ilias N

2017-10-01

The interaction of social networks with the external environment gives rise to non-stationary activity patterns reflecting the temporal structure and strength of exogenous influences that drive social dynamical processes far from an equilibrium state. Following a neuro-inspired approach, based on the dynamics of a passive neuronal membrane, and the firing rate dynamics of single neurons and neuronal populations, we build a state-of-the-art model of the collective social response to exogenous interventions. In this regard, we analyze online activity patterns with a view to determining the transfer function of social systems, that is, the dynamic relationship between external influences and the resulting activity. To this end, first we estimate the impulse response (Green's function) of collective activity, and then we show that the convolution of the impulse response with a time-varying external influence field accurately reproduces empirical activity patterns. To capture the dynamics of collective activity when the generating process is in a state of statistical equilibrium, we incorporate into the model a noisy input convolved with the impulse response function, thus precisely reproducing the fluctuations of stationary collective activity around a resting value. The outstanding goodness-of-fit of the model results to empirical observations, indicates that the model explains human activity patterns generated by time-dependent external influences in various socio-economic contexts. The proposed model can be used for inferring the temporal structure and strength of external influences, as well as the inertia of collective social activity. Furthermore, it can potentially predict social activity patterns. Copyright © 2017 Elsevier Ltd. All rights reserved.

Importance of vegetation distribution for future carbon balance

NASA Astrophysics Data System (ADS)

Ahlström, A.; Xia, J.; Arneth, A.; Luo, Y.; Smith, B.

2015-12-01

Projections of future terrestrial carbon uptake vary greatly between simulations. Net primary production (NPP), wild fires, vegetation dynamics (including biome shifts) and soil decomposition constitute the main processes governing the response of the terrestrial carbon cycle in a changing climate. While primary production and soil respiration are relatively well studied and implemented in all global ecosystem models used to project the future land sink of CO2, vegetation dynamics are less studied and not always represented in global models. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality and the associated turnover and proven skill in predicting vegetation distribution and succession. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the CMIP5 ensemble under RCP8.5 radiative forcing at year 2085. We exchanged carbon cycle processes between these 13 simulations and investigate the changes predicted by the emulator. This method allowed us to partition the entire ensemble carbon uptake uncertainty into individual processes. We found that NPP, vegetation dynamics (including biome shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33% respectively of uncertainties in modeled global C-uptake. Uncertainty due to vegetation dynamics was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by shifts in vegetation distribution, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

Phase Transitions in Geomorphology

NASA Astrophysics Data System (ADS)

Ortiz, C. P.; Jerolmack, D. J.

2015-12-01

Landscapes are patterns in a dynamic steady-state, due to competing processes that smooth or sharpen features over large distances and times. Geomorphic transport laws have been developed to model the mass-flux due to different processes, but are unreasonably effective at recovering the scaling relations of landscape features. Using a continuum approximation to compare experimental landscapes and the observed landscapes of the earth, one finds they share similar morphodynamics despite a breakdown of classical dynamical similarity between the two. We propose the origin of this effectiveness is a different kind of dynamic similarity in the statistics of initiation and cessation of motion of groups of grains, which is common to disordered systems of grains under external driving. We will show how the existing data of sediment transport points to common signatures with dynamical phase transitions between "mobile" and "immobile" phases in other disordered systems, particularly granular materials, colloids, and foams. Viewing landscape evolution from the lens of non-equilibrium statistical physics of disordered systems leads to predictions that the transition of bulk measurements such as particle flux is continuous from one phase to another, that the collective nature of the particle dynamics leads to very slow aging of bulk properties, and that the dynamics are history-dependent. Recent results from sediment transport experiments support these predictions, suggesting that existing geomorphic transport laws may need to be replaced by a new generation of stochastic models with ingredients based on the physics of disordered phase transitions. We discuss possible strategies for extracting the necessary information to develop these models from measurements of geomorphic transport noise by connecting particle-scale collective dynamics and space-time fluctuations over landscape features.

WIFIRE: A Scalable Data-Driven Monitoring, Dynamic Prediction and Resilience Cyberinfrastructure for Wildfires

NASA Astrophysics Data System (ADS)

Altintas, I.; Block, J.; Braun, H.; de Callafon, R. A.; Gollner, M. J.; Smarr, L.; Trouve, A.

2013-12-01

Recent studies confirm that climate change will cause wildfires to increase in frequency and severity in the coming decades especially for California and in much of the North American West. The most critical sustainability issue in the midst of these ever-changing dynamics is how to achieve a new social-ecological equilibrium of this fire ecology. Wildfire wind speeds and directions change in an instant, and first responders can only be effective when they take action as quickly as the conditions change. To deliver information needed for sustainable policy and management in this dynamically changing fire regime, we must capture these details to understand the environmental processes. We are building an end-to-end cyberinfrastructure (CI), called WIFIRE, for real-time and data-driven simulation, prediction and visualization of wildfire behavior. The WIFIRE integrated CI system supports social-ecological resilience to the changing fire ecology regime in the face of urban dynamics and climate change. Networked observations, e.g., heterogeneous satellite data and real-time remote sensor data is integrated with computational techniques in signal processing, visualization, modeling and data assimilation to provide a scalable, technological, and educational solution to monitor weather patterns to predict a wildfire's Rate of Spread. Our collaborative WIFIRE team of scientists, engineers, technologists, government policy managers, private industry, and firefighters architects implement CI pathways that enable joint innovation for wildfire management. Scientific workflows are used as an integrative distributed programming model and simplify the implementation of engineering modules for data-driven simulation, prediction and visualization while allowing integration with large-scale computing facilities. WIFIRE will be scalable to users with different skill-levels via specialized web interfaces and user-specified alerts for environmental events broadcasted to receivers before, during and after a wildfire. Scalability of the WIFIRE approach allows many sensors to be subjected to user-specified data processing algorithms to generate threshold alerts within seconds. Integration of this sensor data into both rapidly available fire image data and models will better enable situational awareness, responses and decision support at local, state, national, and international levels. The products of WIFIRE will be initially disseminated to our collaborators (SDG&E, CAL FIRE, USFS), covering academic, private, and government laboratories while generating values to emergency officials, and consequently to the general public. WIFIRE may be used by government agencies in the future to save lives and property during wildfire events, test the effectiveness of response and evacuation scenarios before they occur and assess the effectiveness of high-density sensor networks in improving fire and weather predictions. WIFIRE's high-density network, therefore, will serve as a testbed for future applications worldwide.

B-spline algebraic diagrammatic construction: Application to photoionization cross-sections and high-order harmonic generation

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

Ruberti, M.; Averbukh, V.; Decleva, P.

2014-10-28

We present the first implementation of the ab initio many-body Green's function method, algebraic diagrammatic construction (ADC), in the B-spline single-electron basis. B-spline versions of the first order [ADC(1)] and second order [ADC(2)] schemes for the polarization propagator are developed and applied to the ab initio calculation of static (photoionization cross-sections) and dynamic (high-order harmonic generation spectra) quantities. We show that the cross-section features that pose a challenge for the Gaussian basis calculations, such as Cooper minima and high-energy tails, are found to be reproduced by the B-spline ADC in a very good agreement with the experiment. We also presentmore » the first dynamic B-spline ADC results, showing that the effect of the Cooper minimum on the high-order harmonic generation spectrum of Ar is correctly predicted by the time-dependent ADC calculation in the B-spline basis. The present development paves the way for the application of the B-spline ADC to both energy- and time-resolved theoretical studies of many-electron phenomena in atoms, molecules, and clusters.« less

Laser-to-hot-electron conversion limitations in relativistic laser matter interactions due to multi-picosecond dynamics

NASA Astrophysics Data System (ADS)

Schollmeier, M.; Sefkow, A. B.; Geissel, M.; Arefiev, A. V.; Flippo, K. A.; Gaillard, S. A.; Johnson, R. P.; Kimmel, M. W.; Offermann, D. T.; Rambo, P. K.; Schwarz, J.; Shimada, T.

2015-04-01

High-energy short-pulse lasers are pushing the limits of plasma-based particle acceleration, x-ray generation, and high-harmonic generation by creating strong electromagnetic fields at the laser focus where electrons are being accelerated to relativistic velocities. Understanding the relativistic electron dynamics is key for an accurate interpretation of measurements. We present a unified and self-consistent modeling approach in quantitative agreement with measurements and differing trends across multiple target types acquired from two separate laser systems, which differ only in their nanosecond to picosecond-scale rising edge. Insights from high-fidelity modeling of laser-plasma interaction demonstrate that the ps-scale, orders of magnitude weaker rising edge of the main pulse measurably alters target evolution and relativistic electron generation compared to idealized pulse shapes. This can lead for instance to the experimentally observed difference between 45 MeV and 75 MeV maximum energy protons for two nominally identical laser shots, due to ps-scale prepulse variations. Our results show that the realistic inclusion of temporal laser pulse profiles in modeling efforts is required if predictive capability and extrapolation are sought for future target and laser designs or for other relativistic laser ion acceleration schemes.

Stability analysis in tachyonic potential chameleon cosmology

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

Farajollahi, H.; Salehi, A.; Tayebi, F.

2011-05-01

We study general properties of attractors for tachyonic potential chameleon scalar-field model which possess cosmological scaling solutions. An analytic formulation is given to obtain fixed points with a discussion on their stability. The model predicts a dynamical equation of state parameter with phantom crossing behavior for an accelerating universe. We constrain the parameters of the model by best fitting with the recent data-sets from supernovae and simulated data points for redshift drift experiment generated by Monte Carlo simulations.

Operational Implementation Design for the Earth System Prediction Capability (ESPC): A First-Look

DTIC Science & Technology

2014-02-20

Hybrid NAVDAS-AR data assimilation system assisting by providing dynamic estimates of the error in the background forecasts. 2.1.2 NAVDAS-AR – the...directly assimilates radiances from microwave radiometers and from interferometers and spectrometers in the infrared, and bending angle from Global...real-time analysis (at +3:00). Late in the 12-hr watch (around +8:00), a post-time NAVGEM/NAVDAS-AR run generates the background fields for the next

Chiral phases of fundamental and adjoint quarks

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

Natale, A. A.; Instituto de Física Teórica - UNESP Rua Dr. Bento T. Ferraz, 271, Bl.II - 01140-070, São Paulo, SP

2016-01-22

We consider a QCD chiral symmetry breaking model where the gap equation contains an effective confining propagator and a dressed gluon propagator with a dynamically generated mass. This model is able to explain the ratios between the chiral transition and deconfinement temperatures in the case of fundamental and adjoint quarks. It also predicts the recovery of the chiral symmetry for a large number of quarks (n{sub f} ≈ 11 – 13) in agreement with lattice data.

First-Principles Prediction of Densities of Amorphous Materials: The Case of Amorphous Silicon

NASA Astrophysics Data System (ADS)

Furukawa, Yoritaka; Matsushita, Yu-ichiro

2018-02-01

A novel approach to predict the atomic densities of amorphous materials is explored on the basis of Car-Parrinello molecular dynamics (CPMD) in density functional theory. Despite the determination of the atomic density of matter being crucial in understanding its physical properties, no first-principles method has ever been proposed for amorphous materials until now. We have extended the conventional method for crystalline materials in a natural manner and pointed out the importance of the canonical ensemble of the total energy in the determination of the atomic densities of amorphous materials. To take into account the canonical distribution of the total energy, we generate multiple amorphous structures with several different volumes by CPMD simulations and average the total energies at each volume. The density is then determined as the one that minimizes the averaged total energy. In this study, this approach is implemented for amorphous silicon (a-Si) to demonstrate its validity, and we have determined the density of a-Si to be 4.1% lower and its bulk modulus to be 28 GPa smaller than those of the crystal, which are in good agreement with experiments. We have also confirmed that generating samples through classical molecular dynamics simulations produces a comparable result. The findings suggest that the presented method is applicable to other amorphous systems, including those for which experimental knowledge is lacking.

Study of Topological Distributions of Inclusive Three- and Four-jet Events at the LHC

NASA Astrophysics Data System (ADS)

Gupta, Ruchi; CMS Collaboration

2016-04-01

A study of inclusive topological distributions of three- and four-jet events has been conducted by the CMS Collaboration at the LHC with a data sample corresponding to an integrated luminosity of 5.1 fb-1 at a centre of mass energy of 7 TeV. Kinematic and angular distributions in inclusive multijet final states serve as a natural probe of quantum chromodynamics and can reveal its inner dynamics. Comparisons are carried out with the data and predictions of leading order calculations and parton shower generators. The compared data results are corrected for detector effects and can be directly compared with other models or next-to-leading order theoretical predictions.

The e{sup +}e{sup -}{yields}J/{psi}DD-bar, J/{psi}DD-bar* reactions with dynamically generated resonances

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

Gamermann, D.; Oset, E.

2008-08-31

In two recent reactions by Belle producing DD-bar and DD-bar* meson pairs, peaks above threshold have been measured in the differential cross sections, possibly indicating new resonances in these channels. We want to study such reactions from the point of view that the D meson pairs are produced from already known or predicted resonances below threshold. Our study shows that the peak in the DD-bar* production is not likely to be caused by the X(3872) resonance, but the peak seen in DD-bar invariant mass can be well described if the DD-bar pair comes from the already predicted scalar X(3700) resonance.

Direct modeling parameter signature analysis and failure mode prediction of physical systems using hybrid computer optimization

NASA Technical Reports Server (NTRS)

Drake, R. L.; Duvoisin, P. F.; Asthana, A.; Mather, T. W.

1971-01-01

High speed automated identification and design of dynamic systems, both linear and nonlinear, are discussed. Special emphasis is placed on developing hardware and techniques which are applicable to practical problems. The basic modeling experiment and new results are described. Using the improvements developed successful identification of several systems, including a physical example as well as simulated systems, was obtained. The advantages of parameter signature analysis over signal signature analysis in go-no go testing of operational systems were demonstrated. The feasibility of using these ideas in failure mode prediction in operating systems was also investigated. An improved digital controlled nonlinear function generator was developed, de-bugged, and completely documented.

Operational Challenges In TDRS Post-Maneuver Orbit Determination

NASA Technical Reports Server (NTRS)

Laing, Jason; Myers, Jessica; Ward, Douglas; Lamb, Rivers

2015-01-01

The GSFC Flight Dynamics Facility (FDF) is responsible for daily and post maneuver orbit determination for the Tracking and Data Relay Satellite System (TDRSS). The most stringent requirement for this orbit determination is 75 meters total position accuracy (3-sigma) predicted over one day for Terra's onboard navigation system. To maintain an accurate solution onboard Terra, a solution is generated and provided by the FDF Four hours after a TDRS maneuver. A number of factors present challenges to this support, such as maneuver prediction uncertainty and potentially unreliable tracking from User satellities. Reliable support is provided by comparing an extended Kalman Filter (estimated using ODTK) against a Batch Least Squares system (estimated using GTDS).

Improved Rainfall Estimates and Predictions for 21st Century Drought Early Warning

NASA Technical Reports Server (NTRS)

Funk, Chris; Peterson, Pete; Shukla, Shraddhanand; Husak, Gregory; Landsfeld, Marty; Hoell, Andrew; Pedreros, Diego; Roberts, J. B.; Robertson, F. R.; Tadesse, Tsegae;

Theoretical Analysis of Penalized Maximum-Likelihood Patlak Parametric Image Reconstruction in Dynamic PET for Lesion Detection.

PubMed

Yang, Li; Wang, Guobao; Qi, Jinyi

2016-04-01

Detecting cancerous lesions is a major clinical application of emission tomography. In a previous work, we studied penalized maximum-likelihood (PML) image reconstruction for lesion detection in static PET. Here we extend our theoretical analysis of static PET reconstruction to dynamic PET. We study both the conventional indirect reconstruction and direct reconstruction for Patlak parametric image estimation. In indirect reconstruction, Patlak parametric images are generated by first reconstructing a sequence of dynamic PET images, and then performing Patlak analysis on the time activity curves (TACs) pixel-by-pixel. In direct reconstruction, Patlak parametric images are estimated directly from raw sinogram data by incorporating the Patlak model into the image reconstruction procedure. PML reconstruction is used in both the indirect and direct reconstruction methods. We use a channelized Hotelling observer (CHO) to assess lesion detectability in Patlak parametric images. Simplified expressions for evaluating the lesion detectability have been derived and applied to the selection of the regularization parameter value to maximize detection performance. The proposed method is validated using computer-based Monte Carlo simulations. Good agreements between the theoretical predictions and the Monte Carlo results are observed. Both theoretical predictions and Monte Carlo simulation results show the benefit of the indirect and direct methods under optimized regularization parameters in dynamic PET reconstruction for lesion detection, when compared with the conventional static PET reconstruction.

A dynamic bioenergetic model for coral-Symbiodinium symbioses and coral bleaching as an alternate stable state.

PubMed

Cunning, Ross; Muller, Erik B; Gates, Ruth D; Nisbet, Roger M

2017-10-27

Coral reef ecosystems owe their ecological success - and vulnerability to climate change - to the symbiotic metabolism of corals and Symbiodinium spp. The urgency to understand and predict the stability and breakdown of these symbioses (i.e., coral 'bleaching') demands the development and application of theoretical tools. Here, we develop a dynamic bioenergetic model of coral-Symbiodinium symbioses that demonstrates realistic steady-state patterns in coral growth and symbiont abundance across gradients of light, nutrients, and feeding. Furthermore, by including a mechanistic treatment of photo-oxidative stress, the model displays dynamics of bleaching and recovery that can be explained as transitions between alternate stable states. These dynamics reveal that "healthy" and "bleached" states correspond broadly to nitrogen- and carbon-limitation in the system, with transitions between them occurring as integrated responses to multiple environmental factors. Indeed, a suite of complex emergent behaviors reproduced by the model (e.g., bleaching is exacerbated by nutrients and attenuated by feeding) suggests it captures many important attributes of the system; meanwhile, its modular framework and open source R code are designed to facilitate further problem-specific development. We see significant potential for this modeling framework to generate testable hypotheses and predict integrated, mechanistic responses of corals to environmental change, with important implications for understanding the performance and maintenance of symbiotic systems. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Research on Generating Method of Embedded Software Test Document Based on Dynamic Model

NASA Astrophysics Data System (ADS)

Qu, MingCheng; Wu, XiangHu; Tao, YongChao; Liu, Ying

2018-03-01

This paper provides a dynamic model-based test document generation method for embedded software that provides automatic generation of two documents: test requirements specification documentation and configuration item test documentation. This method enables dynamic test requirements to be implemented in dynamic models, enabling dynamic test demand tracking to be easily generated; able to automatically generate standardized, standardized test requirements and test documentation, improved document-related content inconsistency and lack of integrity And other issues, improve the efficiency.

Top Quark Mass Calibration for Monte Carlo Event Generators

NASA Astrophysics Data System (ADS)

Butenschoen, Mathias; Dehnadi, Bahman; Hoang, André H.; Mateu, Vicent; Preisser, Moritz; Stewart, Iain W.

2016-12-01

The most precise top quark mass measurements use kinematic reconstruction methods, determining the top mass parameter of a Monte Carlo event generator mtMC. Because of hadronization and parton-shower dynamics, relating mtMC to a field theory mass is difficult. We present a calibration procedure to determine this relation using hadron level QCD predictions for observables with kinematic mass sensitivity. Fitting e+e- 2-jettiness calculations at next-to-leading-logarithmic and next-to-next-to-leading-logarithmic order to pythia 8.205, mtMC differs from the pole mass by 900 and 600 MeV, respectively, and agrees with the MSR mass within uncertainties, mtMC≃mt,1 GeV MSR .

Two Dimensional Mechanism for Insect Hovering

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

Jane Wang, Z.

2000-09-04

Resolved computation of two dimensional insect hovering shows for the first time that a two dimensional hovering motion can generate enough lift to support a typical insect weight. The computation reveals a two dimensional mechanism of creating a downward dipole jet of counterrotating vortices, which are formed from leading and trailing edge vortices. The vortex dynamics further elucidates the role of the phase relation between the wing translation and rotation in lift generation and explains why the instantaneous forces can reach a periodic state after only a few strokes. The model predicts the lower limits in Reynolds number and amplitudemore » above which the averaged forces are sufficient. (c) 2000 The American Physical Society.« less