Stability and Hopf bifurcation of a delayed ratio-dependent predator-prey system

NASA Astrophysics Data System (ADS)

Wang, Wan-Yong; Pei, Li-Jun

2011-04-01

Since the ratio-dependent theory reflects the fact that predators must share and compete for food, it is suitable for describing the relationship between predators and their preys and has recently become a very important theory put forward by biologists. In order to investigate the dynamical relationship between predators and their preys, a so-called Michaelis-Menten ratio-dependent predator-prey model is studied in this paper with gestation time delays of predators and preys taken into consideration. The stability of the positive equilibrium is investigated by the Nyquist criteria, and the existence of the local Hopf bifurcation is analyzed by employing the theory of Hopf bifurcation. By means of the center manifold and the normal form theories, explicit formulae are derived to determine the stability, direction and other properties of bifurcating periodic solutions. The above theoretical results are validated by numerical simulations with the help of dynamical software WinPP. The results show that if both the gestation delays are small enough, their sizes will keep stable in the long run, but if the gestation delays of predators are big enough, their sizes will periodically fluctuate in the long term. In order to reveal the effects of time delays on the ratio-dependent predator-prey model, a ratio-dependent predator-prey model without time delays is considered. By Hurwitz criteria, the local stability of positive equilibrium of this model is investigated. The conditions under which the positive equilibrium is locally asymptotically stable are obtained. By comparing the results with those of the model with time delays, it shows that the dynamical behaviors of ratio-dependent predator-prey model with time delays are more complicated. Under the same conditions, namely, with the same parameters, the stability of positive equilibrium of ratio-dependent predator-prey model would change due to the introduction of gestation time delays for predators and preys. Moreover, with the variation of time delays, the positive equilibrium of the ratio-dependent predator-prey model subjects to Hopf bifurcation.

Modeling ultrafast solvated electronic dynamics using time-dependent density functional theory and polarizable continuum model.

PubMed

Liang, Wenkel; Chapman, Craig T; Ding, Feizhi; Li, Xiaosong

2012-03-01

A first-principles solvated electronic dynamics method is introduced. Solvent electronic degrees of freedom are coupled to the time-dependent electronic density of a solute molecule by means of the implicit reaction field method, and the entire electronic system is propagated in time. This real-time time-dependent approach, incorporating the polarizable continuum solvation model, is shown to be very effective in describing the dynamical solvation effect in the charge transfer process and yields a consistent absorption spectrum in comparison to the conventional linear response results in solution. © 2012 American Chemical Society

An energy-balance model with multiply-periodic and quasi-chaotic free oscillations. [for climate forecasting

NASA Technical Reports Server (NTRS)

Bhattacharya, K.; Ghil, M.

1979-01-01

A slightly modified version of the one-dimensional time-dependent energy-balance climate model of Ghil and Bhattacharya (1978) is presented. The albedo-temperature parameterization has been reformulated and the smoothing of the temperature distribution in the tropics has been eliminated. The model albedo depends on time-lagged temperature in order to account for finite growth and decay time of continental ice sheets. Two distinct regimes of oscillatory behavior which depend on the value of the albedo-temperature time lag are considered.

Dependence of two-proton radioactivity on nuclear pairing models

NASA Astrophysics Data System (ADS)

Oishi, Tomohiro; Kortelainen, Markus; Pastore, Alessandro

2017-10-01

Sensitivity of two-proton emitting decay to nuclear pairing correlation is discussed within a time-dependent three-body model. We focus on the 6Be nucleus assuming α +p +p configuration, and its decay process is described as a time evolution of the three-body resonance state. For a proton-proton subsystem, a schematic density-dependent contact (SDDC) pairing model is employed. From the time-dependent calculation, we observed the exponential decay rule of a two-proton emission. It is shown that the density dependence does not play a major role in determining the decay width, which can be controlled only by the asymptotic strength of the pairing interaction. This asymptotic pairing sensitivity can be understood in terms of the dynamics of the wave function driven by the three-body Hamiltonian, by monitoring the time-dependent density distribution. With this simple SDDC pairing model, there remains an impossible trinity problem: it cannot simultaneously reproduce the empirical Q value, decay width, and the nucleon-nucleon scattering length. This problem suggests that a further sophistication of the theoretical pairing model is necessary, utilizing the two-proton radioactivity data as the reference quantities.

Birth-death models and coalescent point processes: the shape and probability of reconstructed phylogenies.

PubMed

Lambert, Amaury; Stadler, Tanja

2013-12-01

Forward-in-time models of diversification (i.e., speciation and extinction) produce phylogenetic trees that grow "vertically" as time goes by. Pruning the extinct lineages out of such trees leads to natural models for reconstructed trees (i.e., phylogenies of extant species). Alternatively, reconstructed trees can be modelled by coalescent point processes (CPPs), where trees grow "horizontally" by the sequential addition of vertical edges. Each new edge starts at some random speciation time and ends at the present time; speciation times are drawn from the same distribution independently. CPPs lead to extremely fast computation of tree likelihoods and simulation of reconstructed trees. Their topology always follows the uniform distribution on ranked tree shapes (URT). We characterize which forward-in-time models lead to URT reconstructed trees and among these, which lead to CPP reconstructed trees. We show that for any "asymmetric" diversification model in which speciation rates only depend on time and extinction rates only depend on time and on a non-heritable trait (e.g., age), the reconstructed tree is CPP, even if extant species are incompletely sampled. If rates additionally depend on the number of species, the reconstructed tree is (only) URT (but not CPP). We characterize the common distribution of speciation times in the CPP description, and discuss incomplete species sampling as well as three special model cases in detail: (1) the extinction rate does not depend on a trait; (2) rates do not depend on time; (3) mass extinctions may happen additionally at certain points in the past. Copyright © 2013 Elsevier Inc. All rights reserved.

A model of partial differential equations for HIV propagation in lymph nodes

NASA Astrophysics Data System (ADS)

Marinho, E. B. S.; Bacelar, F. S.; Andrade, R. F. S.

2012-01-01

A system of partial differential equations is used to model the dissemination of the Human Immunodeficiency Virus (HIV) in CD4+T cells within lymph nodes. Besides diffusion terms, the model also includes a time-delay dependence to describe the time lag required by the immunologic system to provide defenses to new virus strains. The resulting dynamics strongly depends on the properties of the invariant sets of the model, consisting of three fixed points related to the time independent and spatial homogeneous tissue configurations in healthy and infected states. A region in the parameter space is considered, for which the time dependence of the space averaged model variables follows the clinical pattern reported for infected patients: a short scale primary infection, followed by a long latency period of almost complete recovery and third phase characterized by damped oscillations around a value with large HIV counting. Depending on the value of the diffusion coefficient, the latency time increases with respect to that one obtained for the space homogeneous version of the model. It is found that same initial conditions lead to quite different spatial patterns, which depend strongly on the latency interval.

A comparison of time dependent Cox regression, pooled logistic regression and cross sectional pooling with simulations and an application to the Framingham Heart Study.

PubMed

Ngwa, Julius S; Cabral, Howard J; Cheng, Debbie M; Pencina, Michael J; Gagnon, David R; LaValley, Michael P; Cupples, L Adrienne

2016-11-03

Typical survival studies follow individuals to an event and measure explanatory variables for that event, sometimes repeatedly over the course of follow up. The Cox regression model has been used widely in the analyses of time to diagnosis or death from disease. The associations between the survival outcome and time dependent measures may be biased unless they are modeled appropriately. In this paper we explore the Time Dependent Cox Regression Model (TDCM), which quantifies the effect of repeated measures of covariates in the analysis of time to event data. This model is commonly used in biomedical research but sometimes does not explicitly adjust for the times at which time dependent explanatory variables are measured. This approach can yield different estimates of association compared to a model that adjusts for these times. In order to address the question of how different these estimates are from a statistical perspective, we compare the TDCM to Pooled Logistic Regression (PLR) and Cross Sectional Pooling (CSP), considering models that adjust and do not adjust for time in PLR and CSP. In a series of simulations we found that time adjusted CSP provided identical results to the TDCM while the PLR showed larger parameter estimates compared to the time adjusted CSP and the TDCM in scenarios with high event rates. We also observed upwardly biased estimates in the unadjusted CSP and unadjusted PLR methods. The time adjusted PLR had a positive bias in the time dependent Age effect with reduced bias when the event rate is low. The PLR methods showed a negative bias in the Sex effect, a subject level covariate, when compared to the other methods. The Cox models yielded reliable estimates for the Sex effect in all scenarios considered. We conclude that survival analyses that explicitly account in the statistical model for the times at which time dependent covariates are measured provide more reliable estimates compared to unadjusted analyses. We present results from the Framingham Heart Study in which lipid measurements and myocardial infarction data events were collected over a period of 26 years.

Dynamics of a Hogg-Huberman Model with Time Dependent Reevaluation Rates

NASA Astrophysics Data System (ADS)

Tanaka, Toshijiro; Kurihara, Tetsuya; Inoue, Masayoshi

2006-05-01

The dynamical behavior of the Hogg-Huberman model with time-dependent reevaluation rates is studied. The time dependence of the reevaluation rate that agents using one of resources decide to consider their resource choice is obtained in terms of states of the system. It is seen that the change of fraction of agents using one resource is suppressed to be smaller than that in the case of a fixed reevaluation rate and the chaos control in the system associated with time-dependent reevaluation rates can be performed by the system itself.

DEVELOPMENT AND PEER REVIEW OF TIME-TO-EFFECT MODELS FOR THE ANALYSIS OF NEUROTOXICITY AND OTHER TIME DEPENDENT DATA

EPA Science Inventory

Neurobehavioral studies pose unique challenges for dose-response modeling, including small sample size and relatively large intra-subject variation, repeated measurements over time, multiple endpoints with both continuous and ordinal scales, and time dependence of risk characteri...

Integrable Time-Dependent Quantum Hamiltonians

NASA Astrophysics Data System (ADS)

Sinitsyn, Nikolai A.; Yuzbashyan, Emil A.; Chernyak, Vladimir Y.; Patra, Aniket; Sun, Chen

2018-05-01

We formulate a set of conditions under which the nonstationary Schrödinger equation with a time-dependent Hamiltonian is exactly solvable analytically. The main requirement is the existence of a non-Abelian gauge field with zero curvature in the space of system parameters. Known solvable multistate Landau-Zener models satisfy these conditions. Our method provides a strategy to incorporate time dependence into various quantum integrable models while maintaining their integrability. We also validate some prior conjectures, including the solution of the driven generalized Tavis-Cummings model.

Model and observation comparison of the universal time and IMF by dependence of the ionospheric polar hole

NASA Technical Reports Server (NTRS)

Sojka, J. J.; Schunk, R. W.; Hoegy, W. R.; Grebowsky, J. M.

1991-01-01

The polar ionospheric F-region often exhibits regions of marked density depletion. These depletions have been observed by a variety of polar orbiting ionospheric satellites over a full range of solar cycle, season, magnetic activity, and universal time (UT). An empirical model of these observations has recently been developed to describe the polar depletion dependence on these parameters. Specifically, the dependence has been defined as a function of F10.7 (solar), summer or winter, Kp (magnetic), and UT. Polar cap depletions have also been predicted /1, 2/ and are, hence, present in physical models of the high latitude ionosphere. Using the Utah State University Time Dependent Ionospheric Model (TDIM) the predicted polar depletion characteristics are compared with those described by the above empirical model. In addition, the TDIM is used to predict the IMF By dependence of the polar hole feature.

Neutrino flavor instabilities in a time-dependent supernova model

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

Abbar, Sajad; Duan, Huaiyu

2015-10-19

In this study, a dense neutrino medium such as that inside a core-collapse supernova can experience collective flavor conversion or oscillations because of the neutral-current weak interaction among the neutrinos. This phenomenon has been studied in a restricted, stationary supernova model which possesses the (spatial) spherical symmetry about the center of the supernova and the (directional) axial symmetry around the radial direction. Recently it has been shown that these spatial and directional symmetries can be broken spontaneously by collective neutrino oscillations. In this letter we analyze the neutrino flavor instabilities in a time-dependent supernova model. Our results show that collectivemore » neutrino oscillations start at approximately the same radius in both the stationary and time-dependent supernova models unless there exist very rapid variations in local physical conditions on timescales of a few microseconds or shorter. Our results also suggest that collective neutrino oscillations can vary rapidly with time in the regimes where they do occur which need to be studied in time-dependent supernova models.« less

A time-dependent diffusion convection model for the long term modulation of cosmic rays

NASA Technical Reports Server (NTRS)

Gallagher, J. J.

1974-01-01

A model is developed which incorporates to first order the direct effects of the time dependent diffusive propagation of interstellar cosmic rays in a slowly changing interplanetary medium. The model provides a physical explanation for observed rigidity-dependent phase lags in modulated spectra (cosmic ray hysteresis). The average distance to the modulating boundary during the last solar cycle is estimated.

A method for diagnosing time dependent faults using model-based reasoning systems

NASA Technical Reports Server (NTRS)

Goodrich, Charles H.

1995-01-01

This paper explores techniques to apply model-based reasoning to equipment and systems which exhibit dynamic behavior (that which changes as a function of time). The model-based system of interest is KATE-C (Knowledge based Autonomous Test Engineer) which is a C++ based system designed to perform monitoring and diagnosis of Space Shuttle electro-mechanical systems. Methods of model-based monitoring and diagnosis are well known and have been thoroughly explored by others. A short example is given which illustrates the principle of model-based reasoning and reveals some limitations of static, non-time-dependent simulation. This example is then extended to demonstrate representation of time-dependent behavior and testing of fault hypotheses in that environment.

Low-energy fusion dynamics of weakly bound nuclei: A time dependent perspective

NASA Astrophysics Data System (ADS)

Diaz-Torres, A.; Boselli, M.

2016-05-01

Recent dynamical fusion models for weakly bound nuclei at low incident energies, based on a time-dependent perspective, are briefly presented. The main features of both the PLATYPUS model and a new quantum approach are highlighted. In contrast to existing timedependent quantum models, the present quantum approach separates the complete and incomplete fusion from the total fusion. Calculations performed within a toy model for 6Li + 209Bi at near-barrier energies show that converged excitation functions for total, complete and incomplete fusion can be determined with the time-dependent wavepacket dynamics.

Skeletal muscle tensile strain dependence: hyperviscoelastic nonlinearity

PubMed Central

Wheatley, Benjamin B; Morrow, Duane A; Odegard, Gregory M; Kaufman, Kenton R; Donahue, Tammy L Haut

2015-01-01

Introduction Computational modeling of skeletal muscle requires characterization at the tissue level. While most skeletal muscle studies focus on hyperelasticity, the goal of this study was to examine and model the nonlinear behavior of both time-independent and time-dependent properties of skeletal muscle as a function of strain. Materials and Methods Nine tibialis anterior muscles from New Zealand White rabbits were subject to five consecutive stress relaxation cycles of roughly 3% strain. Individual relaxation steps were fit with a three-term linear Prony series. Prony series coefficients and relaxation ratio were assessed for strain dependence using a general linear statistical model. A fully nonlinear constitutive model was employed to capture the strain dependence of both the viscoelastic and instantaneous components. Results Instantaneous modulus (p<0.0005) and mid-range relaxation (p<0.0005) increased significantly with strain level, while relaxation at longer time periods decreased with strain (p<0.0005). Time constants and overall relaxation ratio did not change with strain level (p>0.1). Additionally, the fully nonlinear hyperviscoelastic constitutive model provided an excellent fit to experimental data, while other models which included linear components failed to capture muscle function as accurately. Conclusions Material properties of skeletal muscle are strain-dependent at the tissue level. This strain dependence can be included in computational models of skeletal muscle performance with a fully nonlinear hyperviscoelastic model. PMID:26409235

Transit-time and age distributions for nonlinear time-dependent compartmental systems.

PubMed

Metzler, Holger; Müller, Markus; Sierra, Carlos A

2018-02-06

Many processes in nature are modeled using compartmental systems (reservoir/pool/box systems). Usually, they are expressed as a set of first-order differential equations describing the transfer of matter across a network of compartments. The concepts of age of matter in compartments and the time required for particles to transit the system are important diagnostics of these models with applications to a wide range of scientific questions. Until now, explicit formulas for transit-time and age distributions of nonlinear time-dependent compartmental systems were not available. We compute densities for these types of systems under the assumption of well-mixed compartments. Assuming that a solution of the nonlinear system is available at least numerically, we show how to construct a linear time-dependent system with the same solution trajectory. We demonstrate how to exploit this solution to compute transit-time and age distributions in dependence on given start values and initial age distributions. Furthermore, we derive equations for the time evolution of quantiles and moments of the age distributions. Our results generalize available density formulas for the linear time-independent case and mean-age formulas for the linear time-dependent case. As an example, we apply our formulas to a nonlinear and a linear version of a simple global carbon cycle model driven by a time-dependent input signal which represents fossil fuel additions. We derive time-dependent age distributions for all compartments and calculate the time it takes to remove fossil carbon in a business-as-usual scenario.

The Distribution of Chromosomal Aberrations in Human Cells Predicted by a Generalized Time-Dependent Model of Radiation-Induced Formation of Aberrations

NASA Technical Reports Server (NTRS)

Ponomarev, Artem L.; George, K.; Cucinotta, F. A.

2011-01-01

New experimental data show how chromosomal aberrations for low- and high-LET radiation are dependent on DSB repair deficiencies in wild-type, AT and NBS cells. We simulated the development of chromosomal aberrations in these cells lines in a stochastic track-structure-dependent model, in which different cells have different kinetics of DSB repair. We updated a previously formulated model of chromosomal aberrations, which was based on a stochastic Monte Carlo approach, to consider the time-dependence of DSB rejoining. The previous version of the model had an assumption that all DSBs would rejoin, and therefore we called it a time-independent model. The chromosomal-aberrations model takes into account the DNA and track structure for low- and high-LET radiations, and provides an explanation and prediction of the statistics of rare and more complex aberrations. We compared the program-simulated kinetics of DSB rejoining to the experimentally-derived bimodal exponential curves of the DSB kinetics. We scored the formation of translocations, dicentrics, acentric and centric rings, deletions, and inversions. The fraction of DSBs participating in aberrations was studied in relation to the rejoining time. Comparisons of simulated dose dependence for simple aberrations to the experimental dose-dependence for HF19, AT and NBS cells will be made.

A quantile regression model for failure-time data with time-dependent covariates

PubMed Central

Gorfine, Malka; Goldberg, Yair; Ritov, Ya’acov

2017-01-01

Summary Since survival data occur over time, often important covariates that we wish to consider also change over time. Such covariates are referred as time-dependent covariates. Quantile regression offers flexible modeling of survival data by allowing the covariates to vary with quantiles. This article provides a novel quantile regression model accommodating time-dependent covariates, for analyzing survival data subject to right censoring. Our simple estimation technique assumes the existence of instrumental variables. In addition, we present a doubly-robust estimator in the sense of Robins and Rotnitzky (1992, Recovery of information and adjustment for dependent censoring using surrogate markers. In: Jewell, N. P., Dietz, K. and Farewell, V. T. (editors), AIDS Epidemiology. Boston: Birkhaäuser, pp. 297–331.). The asymptotic properties of the estimators are rigorously studied. Finite-sample properties are demonstrated by a simulation study. The utility of the proposed methodology is demonstrated using the Stanford heart transplant dataset. PMID:27485534

Time-dependent behavior of passive skeletal muscle

NASA Astrophysics Data System (ADS)

Ahamed, T.; Rubin, M. B.; Trimmer, B. A.; Dorfmann, L.

2016-03-01

An isotropic three-dimensional nonlinear viscoelastic model is developed to simulate the time-dependent behavior of passive skeletal muscle. The development of the model is stimulated by experimental data that characterize the response during simple uniaxial stress cyclic loading and unloading. Of particular interest is the rate-dependent response, the recovery of muscle properties from the preconditioned to the unconditioned state and stress relaxation at constant stretch during loading and unloading. The model considers the material to be a composite of a nonlinear hyperelastic component in parallel with a nonlinear dissipative component. The strain energy and the corresponding stress measures are separated additively into hyperelastic and dissipative parts. In contrast to standard nonlinear inelastic models, here the dissipative component is modeled using an evolution equation that combines rate-independent and rate-dependent responses smoothly with no finite elastic range. Large deformation evolution equations for the distortional deformations in the elastic and in the dissipative component are presented. A robust, strongly objective numerical integration algorithm is used to model rate-dependent and rate-independent inelastic responses. The constitutive formulation is specialized to simulate the experimental data. The nonlinear viscoelastic model accurately represents the time-dependent passive response of skeletal muscle.

Dynamical initial-state model for relativistic heavy-ion collisions

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

Shen, Chun; Schenke, Bjorn

We present a fully three-dimensional model providing initial conditions for energy and net-baryon density distributions in heavy ion collisions at arbitrary collision energy. The model includes the dynamical deceleration of participating nucleons or valence quarks, depending on the implementation. The duration of the deceleration continues until the string spanned between colliding participants is assumed to thermalize, which is either after a fixed proper time, or a uctuating time depending on sampled final rapidities. Energy is deposited in space-time along the string, which in general will span a range of space-time rapidities and proper times. We study various observables obtained directlymore » from the initial state model, including net-baryon rapidity distributions, 2-particle rapidity correlations, as well as the rapidity decorrelation of the transverse geometry. Their dependence on the model implementation and parameter values is investigated. Here, we also present the implementation of the model with 3+1 dimensional hydrodynamics, which involves the addition of source terms that deposit energy and net-baryon densities produced by the initial state model at proper times greater than the initial time for the hydrodynamic simulation.« less

Dynamical initial-state model for relativistic heavy-ion collisions

NASA Astrophysics Data System (ADS)

Shen, Chun; Schenke, Björn

2018-02-01

We present a fully three-dimensional model providing initial conditions for energy and net-baryon density distributions in heavy-ion collisions at arbitrary collision energy. The model includes the dynamical deceleration of participating nucleons or valence quarks, depending on the implementation. The duration of the deceleration continues until the string spanned between colliding participants is assumed to thermalize, which is either after a fixed proper time, or a fluctuating time depending on sampled final rapidities. Energy is deposited in space time along the string, which in general will span a range of space-time rapidities and proper times. We study various observables obtained directly from the initial-state model, including net-baryon rapidity distributions, two-particle rapidity correlations, as well as the rapidity decorrelation of the transverse geometry. Their dependence on the model implementation and parameter values is investigated. We also present the implementation of the model with 3+1-dimensional hydrodynamics, which involves the addition of source terms that deposit energy and net-baryon densities produced by the initial-state model at proper times greater than the initial time for the hydrodynamic simulation.

Dynamical initial-state model for relativistic heavy-ion collisions

DOE PAGES

Shen, Chun; Schenke, Bjorn

2018-02-15

We present a fully three-dimensional model providing initial conditions for energy and net-baryon density distributions in heavy ion collisions at arbitrary collision energy. The model includes the dynamical deceleration of participating nucleons or valence quarks, depending on the implementation. The duration of the deceleration continues until the string spanned between colliding participants is assumed to thermalize, which is either after a fixed proper time, or a uctuating time depending on sampled final rapidities. Energy is deposited in space-time along the string, which in general will span a range of space-time rapidities and proper times. We study various observables obtained directlymore » from the initial state model, including net-baryon rapidity distributions, 2-particle rapidity correlations, as well as the rapidity decorrelation of the transverse geometry. Their dependence on the model implementation and parameter values is investigated. Here, we also present the implementation of the model with 3+1 dimensional hydrodynamics, which involves the addition of source terms that deposit energy and net-baryon densities produced by the initial state model at proper times greater than the initial time for the hydrodynamic simulation.« less

Single Machine Scheduling and Due Date Assignment with Past-Sequence-Dependent Setup Time and Position-Dependent Processing Time

PubMed Central

Zhao, Chuan-Li; Hsu, Hua-Feng

2014-01-01

This paper considers single machine scheduling and due date assignment with setup time. The setup time is proportional to the length of the already processed jobs; that is, the setup time is past-sequence-dependent (p-s-d). It is assumed that a job's processing time depends on its position in a sequence. The objective functions include total earliness, the weighted number of tardy jobs, and the cost of due date assignment. We analyze these problems with two different due date assignment methods. We first consider the model with job-dependent position effects. For each case, by converting the problem to a series of assignment problems, we proved that the problems can be solved in O(n 4) time. For the model with job-independent position effects, we proved that the problems can be solved in O(n 3) time by providing a dynamic programming algorithm. PMID:25258727

Single machine scheduling and due date assignment with past-sequence-dependent setup time and position-dependent processing time.

PubMed

Zhao, Chuan-Li; Hsu, Chou-Jung; Hsu, Hua-Feng

2014-01-01

This paper considers single machine scheduling and due date assignment with setup time. The setup time is proportional to the length of the already processed jobs; that is, the setup time is past-sequence-dependent (p-s-d). It is assumed that a job's processing time depends on its position in a sequence. The objective functions include total earliness, the weighted number of tardy jobs, and the cost of due date assignment. We analyze these problems with two different due date assignment methods. We first consider the model with job-dependent position effects. For each case, by converting the problem to a series of assignment problems, we proved that the problems can be solved in O(n(4)) time. For the model with job-independent position effects, we proved that the problems can be solved in O(n(3)) time by providing a dynamic programming algorithm.

Multi-objective and Perishable Fuzzy Inventory Models Having Weibull Life-time With Time Dependent Demand, Demand Dependent Production and Time Varying Holding Cost: A Possibility/Necessity Approach

NASA Astrophysics Data System (ADS)

Pathak, Savita; Mondal, Seema Sarkar

2010-10-01

A multi-objective inventory model of deteriorating item has been developed with Weibull rate of decay, time dependent demand, demand dependent production, time varying holding cost allowing shortages in fuzzy environments for non- integrated and integrated businesses. Here objective is to maximize the profit from different deteriorating items with space constraint. The impreciseness of inventory parameters and goals for non-integrated business has been expressed by linear membership functions. The compromised solutions are obtained by different fuzzy optimization methods. To incorporate the relative importance of the objectives, the different cardinal weights crisp/fuzzy have been assigned. The models are illustrated with numerical examples and results of models with crisp/fuzzy weights are compared. The result for the model assuming them to be integrated business is obtained by using Generalized Reduced Gradient Method (GRG). The fuzzy integrated model with imprecise inventory cost is formulated to optimize the possibility necessity measure of fuzzy goal of the objective function by using credibility measure of fuzzy event by taking fuzzy expectation. The results of crisp/fuzzy integrated model are illustrated with numerical examples and results are compared.

A Bimodal Hybrid Model for Time-Dependent Probabilistic Seismic Hazard Analysis

NASA Astrophysics Data System (ADS)

Yaghmaei-Sabegh, Saman; Shoaeifar, Nasser; Shoaeifar, Parva

2018-03-01

The evaluation of evidence provided by geological studies and historical catalogs indicates that in some seismic regions and faults, multiple large earthquakes occur in cluster. Then, the occurrences of large earthquakes confront with quiescence and only the small-to-moderate earthquakes take place. Clustering of large earthquakes is the most distinguishable departure from the assumption of constant hazard of random occurrence of earthquakes in conventional seismic hazard analysis. In the present study, a time-dependent recurrence model is proposed to consider a series of large earthquakes that occurs in clusters. The model is flexible enough to better reflect the quasi-periodic behavior of large earthquakes with long-term clustering, which can be used in time-dependent probabilistic seismic hazard analysis with engineering purposes. In this model, the time-dependent hazard results are estimated by a hazard function which comprises three parts. A decreasing hazard of last large earthquake cluster and an increasing hazard of the next large earthquake cluster, along with a constant hazard of random occurrence of small-to-moderate earthquakes. In the final part of the paper, the time-dependent seismic hazard of the New Madrid Seismic Zone at different time intervals has been calculated for illustrative purpose.

Evaluation of Time- and Concentration-dependent Toxic Effect Models for use in Aquatic Risk Assessments, Oral Presentation

EPA Science Inventory

Various models have been proposed for describing the time- and concentration-dependence of toxic effects to aquatic organisms, which would improve characterization of risks in natural systems. Selected models were evaluated using results from a study on the lethality of copper t...

The Polar Ionosphere and Interplanetary Field.

DTIC Science & Technology

1987-08-01

model for investigating time dependent behavior of the Polar F-region ionosphere in response to varying interplanetary magnetic field (IMF...conditions. The model has been used to illustrate ionospheric behavior during geomagnetic storms conditions. Future model applications may include...magnetosphere model for investigating time dependent behavior of the polar F-region ionosphere in response to varying interplanetary magnetic field

A Perishable Inventory Model with Return

NASA Astrophysics Data System (ADS)

Setiawan, S. W.; Lesmono, D.; Limansyah, T.

2018-04-01

In this paper, we develop a mathematical model for a perishable inventory with return by assuming deterministic demand and inventory dependent demand. By inventory dependent demand, it means that demand at certain time depends on the available inventory at that time with certain rate. In dealing with perishable items, we should consider deteriorating rate factor that corresponds to the decreasing quality of goods. There are also costs involved in this model such as purchasing, ordering, holding, shortage (backordering) and returning costs. These costs compose the total costs in the model that we want to minimize. In the model we seek for the optimal return time and order quantity. We assume that after some period of time, called return time, perishable items can be returned to the supplier at some returning costs. The supplier will then replace them in the next delivery. Some numerical experiments are given to illustrate our model and sensitivity analysis is performed as well. We found that as the deteriorating rate increases, returning time becomes shorter, the optimal order quantity and total cost increases. When considering the inventory-dependent demand factor, we found that as this factor increases, assuming a certain deteriorating rate, returning time becomes shorter, optimal order quantity becomes larger and the total cost increases.

3D inelastic analysis methods for hot section components

NASA Technical Reports Server (NTRS)

Dame, L. T.; Chen, P. C.; Hartle, M. S.; Huang, H. T.

1985-01-01

The objective is to develop analytical tools capable of economically evaluating the cyclic time dependent plasticity which occurs in hot section engine components in areas of strain concentration resulting from the combination of both mechanical and thermal stresses. Three models were developed. A simple model performs time dependent inelastic analysis using the power law creep equation. The second model is the classical model of Professors Walter Haisler and David Allen of Texas A and M University. The third model is the unified model of Bodner, Partom, et al. All models were customized for linear variation of loads and temperatures with all material properties and constitutive models being temperature dependent.

Uncertainty analysis in seismic tomography

NASA Astrophysics Data System (ADS)

Owoc, Bartosz; Majdański, Mariusz

2017-04-01

Velocity field from seismic travel time tomography depends on several factors like regularization, inversion path, model parameterization etc. The result also strongly depends on an initial velocity model and precision of travel times picking. In this research we test dependence on starting model in layered tomography and compare it with effect of picking precision. Moreover, in our analysis for manual travel times picking the uncertainty distribution is asymmetric. This effect is shifting the results toward faster velocities. For calculation we are using JIVE3D travel time tomographic code. We used data from geo-engineering and industrial scale investigations, which were collected by our team from IG PAS.

Parametric Study of a YAV-8B Harrier in Ground Effect Using Time-Dependent Navier-Stokes Computations

NASA Technical Reports Server (NTRS)

Shishir, Pandya; Chaderjian, Neal; Ahmad, Jsaim; Kwak, Dochan (Technical Monitor)

2001-01-01

Flow simulations using the time-dependent Navier-Stokes equations remain a challenge for several reasons. Principal among them are the difficulty to accurately model complex flows, and the time needed to perform the computations. A parametric study of such complex problems is not considered practical due to the large cost associated with computing many time-dependent solutions. The computation time for each solution must be reduced in order to make a parametric study possible. With successful reduction of computation time, the issue of accuracy, and appropriateness of turbulence models will become more tractable.

Creep and shrinkage effects on integral abutment bridges

NASA Astrophysics Data System (ADS)

Munuswamy, Sivakumar

Integral abutment bridges provide bridge engineers an economical design alternative to traditional bridges with expansion joints owing to the benefits, arising from elimination of expensive joints installation and reduced maintenance cost. The superstructure for integral abutment bridges is cast integrally with abutments. Time-dependent effects of creep, shrinkage of concrete, relaxation of prestressing steel, temperature gradient, restraints provided by abutment foundation and backfill and statical indeterminacy of the structure introduce time-dependent variations in the redundant forces. An analytical model and numerical procedure to predict instantaneous linear behavior and non-linear time dependent long-term behavior of continuous composite superstructure are developed in which the redundant forces in the integral abutment bridges are derived considering the time-dependent effects. The redistributions of moments due to time-dependent effects have been considered in the analysis. The analysis includes nonlinearity due to cracking of the concrete, as well as the time-dependent deformations. American Concrete Institute (ACI) and American Association of State Highway and Transportation Officials (AASHTO) models for creep and shrinkage are considered in modeling the time dependent material behavior. The variations in the material property of the cross-section corresponding to the constituent materials are incorporated and age-adjusted effective modulus method with relaxation procedure is followed to include the creep behavior of concrete. The partial restraint provided by the abutment-pile-soil system is modeled using discrete spring stiffness as translational and rotational degrees of freedom. Numerical simulation of the behavior is carried out on continuous composite integral abutment bridges and the deformations and stresses due to time-dependent effects due to typical sustained loads are computed. The results from the analytical model are compared with the published laboratory experimental and field data. The behavior of the laterally loaded piles supporting the integral abutments is evaluated and presented in terms of the lateral deflection, bending moment, shear force and stress along the pile depth.

Research on robust optimization of emergency logistics network considering the time dependence characteristic

NASA Astrophysics Data System (ADS)

WANG, Qingrong; ZHU, Changfeng; LI, Ying; ZHANG, Zhengkun

2017-06-01

Considering the time dependence of emergency logistic network and complexity of the environment that the network exists in, in this paper the time dependent network optimization theory and robust discrete optimization theory are combined, and the emergency logistics dynamic network optimization model with characteristics of robustness is built to maximize the timeliness of emergency logistics. On this basis, considering the complexity of dynamic network and the time dependence of edge weight, an improved ant colony algorithm is proposed to realize the coupling of the optimization algorithm and the network time dependence and robustness. Finally, a case study has been carried out in order to testify validity of this robustness optimization model and its algorithm, and the value of different regulation factors was analyzed considering the importance of the value of the control factor in solving the optimal path. Analysis results show that this model and its algorithm above-mentioned have good timeliness and strong robustness.

Statistical time-dependent model for the interstellar gas

NASA Technical Reports Server (NTRS)

Gerola, H.; Kafatos, M.; Mccray, R.

1974-01-01

We present models for temperature and ionization structure of low, uniform-density (approximately 0.3 per cu cm) interstellar gas in a galactic disk which is exposed to soft X rays from supernova outbursts occurring randomly in space and time. The structure was calculated by computing the time record of temperature and ionization at a given point by Monte Carlo simulation. The calculation yields probability distribution functions for ionized fraction, temperature, and their various observable moments. These time-dependent models predict a bimodal temperature distribution of the gas that agrees with various observations. Cold regions in the low-density gas may have the appearance of clouds in 21-cm absorption. The time-dependent model, in contrast to the steady-state model, predicts large fluctuations in ionization rate and the existence of cold (approximately 30 K), ionized (ionized fraction equal to about 0.1) regions.

A simple shear limited, single size, time dependent flocculation model

NASA Astrophysics Data System (ADS)

Kuprenas, R.; Tran, D. A.; Strom, K.

2017-12-01

This research focuses on the modeling of flocculation of cohesive sediment due to turbulent shear, specifically, investigating the dependency of flocculation on the concentration of cohesive sediment. Flocculation is important in larger sediment transport models as cohesive particles can create aggregates which are orders of magnitude larger than their unflocculated state. As the settling velocity of each particle is determined by the sediment size, density, and shape, accounting for this aggregation is important in determining where the sediment is deposited. This study provides a new formulation for flocculation of cohesive sediment by modifying the Winterwerp (1998) flocculation model (W98) so that it limits floc size to that of the Kolmogorov micro length scale. The W98 model is a simple approach that calculates the average floc size as a function of time. Because of its simplicity, the W98 model is ideal for implementing into larger sediment transport models; however, the model tends to over predict the dependency of the floc size on concentration. It was found that the modification of the coefficients within the original model did not allow for the model to capture the dependency on concentration. Therefore, a new term within the breakup kernel of the W98 formulation was added. The new formulation results is a single size, shear limited, and time dependent flocculation model that is able to effectively capture the dependency of the equilibrium size of flocs on both suspended sediment concentration and the time to equilibrium. The overall behavior of the new model is explored and showed align well with other studies on flocculation. Winterwerp, J. C. (1998). A simple model for turbulence induced flocculation of cohesive sediment. .Journal of Hydraulic Research, 36(3):309-326.

THE EFFECT OF A DYNAMIC INNER HELIOSHEATH THICKNESS ON COSMIC-RAY MODULATION

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

Manuel, R.; Ferreira, S. E. S.; Potgieter, M. S., E-mail: rexmanuel@live.com

2015-02-01

The time-dependent modulation of galactic cosmic rays in the heliosphere is studied over different polarity cycles by computing 2.5 GV proton intensities using a two-dimensional, time-dependent modulation model. By incorporating recent theoretical advances in the relevant transport parameters in the model, we showed in previous work that this approach gave realistic computed intensities over a solar cycle. New in this work is that a time dependence of the solar wind termination shock (TS) position is implemented in our model to study the effect of a dynamic inner heliosheath thickness (the region between the TS and heliopause) on the solar modulationmore » of galactic cosmic rays. The study reveals that changes in the inner heliosheath thickness, arising from a time-dependent shock position, does affect cosmic-ray intensities everywhere in the heliosphere over a solar cycle, with the smallest effect in the innermost heliosphere. A time-dependent TS position causes a phase difference between the solar activity periods and the corresponding intensity periods. The maximum intensities in response to a solar minimum activity period are found to be dependent on the time-dependent TS profile. It is found that changing the width of the inner heliosheath with time over a solar cycle can shift the time of when the maximum or minimum cosmic-ray intensities occur at various distances throughout the heliosphere, but more significantly in the outer heliosphere. The time-dependent extent of the inner heliosheath, as affected by solar activity conditions, is thus an additional time-dependent factor to be considered in the long-term modulation of cosmic rays.« less

Multi-scale simulations of droplets in generic time-dependent flows

NASA Astrophysics Data System (ADS)

Milan, Felix; Biferale, Luca; Sbragaglia, Mauro; Toschi, Federico

2017-11-01

We study the deformation and dynamics of droplets in time-dependent flows using a diffuse interface model for two immiscible fluids. The numerical simulations are at first benchmarked against analytical results of steady droplet deformation, and further extended to the more interesting case of time-dependent flows. The results of these time-dependent numerical simulations are compared against analytical models available in the literature, which assume the droplet shape to be an ellipsoid at all times, with time-dependent major and minor axis. In particular we investigate the time-dependent deformation of a confined droplet in an oscillating Couette flow for the entire capillary range until droplet break-up. In this way these multi component simulations prove to be a useful tool to establish from ``first principles'' the dynamics of droplets in complex flows involving multiple scales. European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie Grant Agreement No 642069. & European Research Council under the European Community's Seventh Framework Program, ERC Grant Agreement No 339032.

Suggestion of a Numerical Model for the Blood Glucose Adjustment with Ingesting a Food

NASA Astrophysics Data System (ADS)

Yamamoto, Naokatsu; Takai, Hiroshi

In this study, we present a numerical model of the time dependence of blood glucose value after ingesting a meal. Two numerical models are proposed in this paper to explain a digestion mechanism and an adjustment mechanism of blood glucose in the body, respectively. It is considered that models are exhibited by using simple equations with a transfer function and a block diagram. Additionally, the time dependence of blood glucose was measured, when subjects ingested a sucrose or a starch. As a result, it is clear that the calculated result of models using a computer can be fitted very well to the measured result of the time dependence of blood glucose. Therefore, it is considered that the digestion model and the adjustment model are useful models in order to estimate a blood glucose value after ingesting meals.

Intertime jump statistics of state-dependent Poisson processes.

PubMed

Daly, Edoardo; Porporato, Amilcare

2007-01-01

A method to obtain the probability distribution of the interarrival times of jump occurrences in systems driven by state-dependent Poisson noise is proposed. Such a method uses the survivor function obtained by a modified version of the master equation associated to the stochastic process under analysis. A model for the timing of human activities shows the capability of state-dependent Poisson noise to generate power-law distributions. The application of the method to a model for neuron dynamics and to a hydrological model accounting for land-atmosphere interaction elucidates the origin of characteristic recurrence intervals and possible persistence in state-dependent Poisson models.

Evaluation of Cox's model and logistic regression for matched case-control data with time-dependent covariates: a simulation study.

PubMed

Leffondré, Karen; Abrahamowicz, Michal; Siemiatycki, Jack

2003-12-30

Case-control studies are typically analysed using the conventional logistic model, which does not directly account for changes in the covariate values over time. Yet, many exposures may vary over time. The most natural alternative to handle such exposures would be to use the Cox model with time-dependent covariates. However, its application to case-control data opens the question of how to manipulate the risk sets. Through a simulation study, we investigate how the accuracy of the estimates of Cox's model depends on the operational definition of risk sets and/or on some aspects of the time-varying exposure. We also assess the estimates obtained from conventional logistic regression. The lifetime experience of a hypothetical population is first generated, and a matched case-control study is then simulated from this population. We control the frequency, the age at initiation, and the total duration of exposure, as well as the strengths of their effects. All models considered include a fixed-in-time covariate and one or two time-dependent covariate(s): the indicator of current exposure and/or the exposure duration. Simulation results show that none of the models always performs well. The discrepancies between the odds ratios yielded by logistic regression and the 'true' hazard ratio depend on both the type of the covariate and the strength of its effect. In addition, it seems that logistic regression has difficulty separating the effects of inter-correlated time-dependent covariates. By contrast, each of the two versions of Cox's model systematically induces either a serious under-estimation or a moderate over-estimation bias. The magnitude of the latter bias is proportional to the true effect, suggesting that an improved manipulation of the risk sets may eliminate, or at least reduce, the bias. Copyright 2003 JohnWiley & Sons, Ltd.

Time-dependent buoyant puff model for explosive sources

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

Kansa, E.J.

1997-01-01

Several models exist to predict the time dependent behavior of bouyant puffs that result from explosions. This paper presents a new model that is derived from the strong conservative form of the conservation partial differential equations that are integrated over space to yield a coupled system of time dependent nonlinear ordinary differential equations. This model permits the cloud to evolve from an intial spherical shape not an ellipsoidal shape. It ignores the Boussinesq approximation, and treats the turbulence that is generated by the puff itself and the ambient atmospheric tubulence as separate mechanisms in determining the puff history. The puffmore » cloud rise history was found to depend no only on the mass and initial temperature of the explosion, but also upon the stability conditions of the ambient atmosphere. This model was calibrated by comparison with the Roller Coaster experiments.« less

Social networks: Evolving graphs with memory dependent edges

NASA Astrophysics Data System (ADS)

Grindrod, Peter; Parsons, Mark

2011-10-01

The plethora of digital communication technologies, and their mass take up, has resulted in a wealth of interest in social network data collection and analysis in recent years. Within many such networks the interactions are transient: thus those networks evolve over time. In this paper we introduce a class of models for such networks using evolving graphs with memory dependent edges, which may appear and disappear according to their recent history. We consider time discrete and time continuous variants of the model. We consider the long term asymptotic behaviour as a function of parameters controlling the memory dependence. In particular we show that such networks may continue evolving forever, or else may quench and become static (containing immortal and/or extinct edges). This depends on the existence or otherwise of certain infinite products and series involving age dependent model parameters. We show how to differentiate between the alternatives based on a finite set of observations. To test these ideas we show how model parameters may be calibrated based on limited samples of time dependent data, and we apply these concepts to three real networks: summary data on mobile phone use from a developing region; online social-business network data from China; and disaggregated mobile phone communications data from a reality mining experiment in the US. In each case we show that there is evidence for memory dependent dynamics, such as that embodied within the class of models proposed here.

Modelling Faculty Replacement Strategies Using a Time-Dependent Finite Markov-Chain Process.

ERIC Educational Resources Information Center

Hackett, E. Raymond; Magg, Alexander A.; Carrigan, Sarah D.

1999-01-01

Describes the use of a time-dependent Markov-chain model to develop faculty-replacement strategies within a college at a research university. The study suggests that a stochastic modelling approach can provide valuable insight when planning for personnel needs in the immediate (five-to-ten year) future. (MSE)

Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies

PubMed Central

Inouye, David I.; Ravikumar, Pradeep; Dhillon, Inderjit S.

2016-01-01

We develop Square Root Graphical Models (SQR), a novel class of parametric graphical models that provides multivariate generalizations of univariate exponential family distributions. Previous multivariate graphical models (Yang et al., 2015) did not allow positive dependencies for the exponential and Poisson generalizations. However, in many real-world datasets, variables clearly have positive dependencies. For example, the airport delay time in New York—modeled as an exponential distribution—is positively related to the delay time in Boston. With this motivation, we give an example of our model class derived from the univariate exponential distribution that allows for almost arbitrary positive and negative dependencies with only a mild condition on the parameter matrix—a condition akin to the positive definiteness of the Gaussian covariance matrix. Our Poisson generalization allows for both positive and negative dependencies without any constraints on the parameter values. We also develop parameter estimation methods using node-wise regressions with ℓ1 regularization and likelihood approximation methods using sampling. Finally, we demonstrate our exponential generalization on a synthetic dataset and a real-world dataset of airport delay times. PMID:27563373

A Time Dependent Model of HD209458b

NASA Astrophysics Data System (ADS)

Iro, N.; Bézard, B.; Guillot, T.

2004-12-01

We developed a time-dependent radiative model for the atmosphere of HD209458b to investigate its thermal structure and chemical composition. Time-dependent temperature profiles were calculated, using a uniform zonal wind modelled as a solid body rotation. We predict day/night temperature variations of 600K around 0.1 bar, for a 1 km/s wind velocity, in good agreement with the predictions by Showman & Guillot (2002). On the night side, the low temperature allows the sodium to condense. Depletion of sodium in the morning limb may explain the lower than expected abundance found by Charbonneau et al. (2002).

Designing for time-dependent material response in spacecraft structures

NASA Technical Reports Server (NTRS)

Hyer, M. W.; Oleksuk, Lynda L. S.; Bowles, D. E.

1992-01-01

To study the influence on overall deformations of the time-dependent constitutive properties of fiber-reinforced polymeric matrix composite materials being considered for use in orbiting precision segmented reflectors, simple sandwich beam models are developed. The beam models include layers representing the face sheets, the core, and the adhesive bonding of the face sheets to the core. A three-layer model lumps the adhesive layers with the face sheets or core, while a five-layer model considers the adhesive layers explicitly. The deformation response of the three-layer and five-layer sandwich beam models to a midspan point load is studied. This elementary loading leads to a simple analysis, and it is easy to create this loading in the laboratory. Using the correspondence principle of viscoelasticity, the models representing the elastic behavior of the two beams are transformed into time-dependent models. Representative cases of time-dependent material behavior for the facesheet material, the core material, and the adhesive are used to evaluate the influence of these constituents being time-dependent on the deformations of the beam. As an example of the results presented, if it assumed that, as a worst case, the polymer-dominated shear properties of the core behave as a Maxwell fluid such that under constant shear stress the shear strain increases by a factor of 10 in 20 years, then it is shown that the beam deflection increases by a factor of 1.4 during that time. In addition to quantitative conclusions, several assumptions are discussed which simplify the analyses for use with more complicated material models. Finally, it is shown that the simpler three-layer model suffices in many situations.

An EOQ Model with Two-Parameter Weibull Distribution Deterioration and Price-Dependent Demand

ERIC Educational Resources Information Center

Mukhopadhyay, Sushanta; Mukherjee, R. N.; Chaudhuri, K. S.

2005-01-01

An inventory replenishment policy is developed for a deteriorating item and price-dependent demand. The rate of deterioration is taken to be time-proportional and the time to deterioration is assumed to follow a two-parameter Weibull distribution. A power law form of the price dependence of demand is considered. The model is solved analytically…

Comparing a marginal structural model with a Cox proportional hazard model to estimate the effect of time-dependent drug use in observational studies: statin use for primary prevention of cardiovascular disease as an example from the Rotterdam Study.

PubMed

de Keyser, Catherine E; Leening, Maarten J G; Romio, Silvana A; Jukema, J Wouter; Hofman, Albert; Ikram, M Arfan; Franco, Oscar H; Stijnen, Theo; Stricker, Bruno H

2014-11-01

When studying the causal effect of drug use in observational data, marginal structural modeling (MSM) can be used to adjust for time-dependent confounders that are affected by previous treatment. The objective of this study was to compare traditional Cox proportional hazard models (with and without time-dependent covariates) with MSM to study causal effects of time-dependent drug use. The example of primary prevention of cardiovascular disease (CVD) with statins was examined using up to 17.7 years of follow-up from 4,654 participants of the observational prospective population-based Rotterdam Study. In the MSM model, the weight was based on measurements of established cardiovascular risk factors and co-morbidity. In general, we could not demonstrate important differences in results from the Cox models and MSM. Results from analysis on duration of statin use suggested that substantial residual confounding by indication was not accounted for during the period shortly after statin initiation. In conclusion, although on theoretical grounds MSM is an elegant technique, lack of data on the precise time-dependent confounders, such as indication of treatment or other considerations of the prescribing physician jeopardizes the calculation of valid weights. Confounding remains a hurdle in observational effectiveness research on preventive drugs with a multitude of prescription determinants.

Fitting the Incidence Data from the City of Campinas, Brazil, Based on Dengue Transmission Modellings Considering Time-Dependent Entomological Parameters

PubMed Central

Yang, Hyun Mo; Boldrini, José Luiz; Fassoni, Artur César; Freitas, Luiz Fernando Souza; Gomez, Miller Ceron; de Lima, Karla Katerine Barboza; Andrade, Valmir Roberto; Freitas, André Ricardo Ribas

2016-01-01

Four time-dependent dengue transmission models are considered in order to fit the incidence data from the City of Campinas, Brazil, recorded from October 1st 1995 to September 30th 2012. The entomological parameters are allowed to depend on temperature and precipitation, while the carrying capacity and the hatching of eggs depend only on precipitation. The whole period of incidence of dengue is split into four periods, due to the fact that the model is formulated considering the circulation of only one serotype. Dengue transmission parameters from human to mosquito and mosquito to human are fitted for each one of the periods. The time varying partial and overall effective reproduction numbers are obtained to explain the incidence of dengue provided by the models. PMID:27010654

Dependability and performability analysis

NASA Technical Reports Server (NTRS)

Trivedi, Kishor S.; Ciardo, Gianfranco; Malhotra, Manish; Sahner, Robin A.

1993-01-01

Several practical issues regarding specifications and solution of dependability and performability models are discussed. Model types with and without rewards are compared. Continuous-time Markov chains (CTMC's) are compared with (continuous-time) Markov reward models (MRM's) and generalized stochastic Petri nets (GSPN's) are compared with stochastic reward nets (SRN's). It is shown that reward-based models could lead to more concise model specifications and solution of a variety of new measures. With respect to the solution of dependability and performability models, three practical issues were identified: largeness, stiffness, and non-exponentiality, and a variety of approaches are discussed to deal with them, including some of the latest research efforts.

Fast simulation of reconstructed phylogenies under global time-dependent birth-death processes.

PubMed

Höhna, Sebastian

2013-06-01

Diversification rates and patterns may be inferred from reconstructed phylogenies. Both the time-dependent and the diversity-dependent birth-death process can produce the same observed patterns of diversity over time. To develop and test new models describing the macro-evolutionary process of diversification, generic and fast algorithms to simulate under these models are necessary. Simulations are not only important for testing and developing models but play an influential role in the assessment of model fit. In the present article, I consider as the model a global time-dependent birth-death process where each species has the same rates but rates may vary over time. For this model, I derive the likelihood of the speciation times from a reconstructed phylogenetic tree and show that each speciation event is independent and identically distributed. This fact can be used to simulate efficiently reconstructed phylogenetic trees when conditioning on the number of species, the time of the process or both. I show the usability of the simulation by approximating the posterior predictive distribution of a birth-death process with decreasing diversification rates applied on a published bird phylogeny (family Cettiidae). The methods described in this manuscript are implemented in the R package TESS, available from the repository CRAN (http://cran.r-project.org/web/packages/TESS/). Supplementary data are available at Bioinformatics online.

Time-dependent probability density functions and information geometry in stochastic logistic and Gompertz models

NASA Astrophysics Data System (ADS)

Tenkès, Lucille-Marie; Hollerbach, Rainer; Kim, Eun-jin

2017-12-01

A probabilistic description is essential for understanding growth processes in non-stationary states. In this paper, we compute time-dependent probability density functions (PDFs) in order to investigate stochastic logistic and Gompertz models, which are two of the most popular growth models. We consider different types of short-correlated multiplicative and additive noise sources and compare the time-dependent PDFs in the two models, elucidating the effects of the additive and multiplicative noises on the form of PDFs. We demonstrate an interesting transition from a unimodal to a bimodal PDF as the multiplicative noise increases for a fixed value of the additive noise. A much weaker (leaky) attractor in the Gompertz model leads to a significant (singular) growth of the population of a very small size. We point out the limitation of using stationary PDFs, mean value and variance in understanding statistical properties of the growth in non-stationary states, highlighting the importance of time-dependent PDFs. We further compare these two models from the perspective of information change that occurs during the growth process. Specifically, we define an infinitesimal distance at any time by comparing two PDFs at times infinitesimally apart and sum these distances in time. The total distance along the trajectory quantifies the total number of different states that the system undergoes in time, and is called the information length. We show that the time-evolution of the two models become more similar when measured in units of the information length and point out the merit of using the information length in unifying and understanding the dynamic evolution of different growth processes.

Time-Dependent Behaviors of Granite: Loading-Rate Dependence, Creep, and Relaxation

NASA Astrophysics Data System (ADS)

Hashiba, K.; Fukui, K.

2016-07-01

To assess the long-term stability of underground structures, it is important to understand the time-dependent behaviors of rocks, such as their loading-rate dependence, creep, and relaxation. However, there have been fewer studies on crystalline rocks than on tuff, mudstone, and rock salt, because the high strength of crystalline rocks makes the detection of their time-dependent behaviors much more difficult. Moreover, studies on the relaxation, temporal change of stress and strain (TCSS) conditions, and relations between various time-dependent behaviors are scarce for not only granites, but also other rocks. In this study, previous reports on the time-dependent behaviors of granites were reviewed and various laboratory tests were conducted using Toki granite. These tests included an alternating-loading-rate test, creep test, relaxation test, and TCSS test. The results showed that the degree of time dependence of Toki granite is similar to other granites, and that the TCSS resembles the stress-relaxation curve and creep-strain curve. A viscoelastic constitutive model, proposed in a previous study, was modified to investigate the relations between the time-dependent behaviors in the pre- and post-peak regions. The modified model reproduced the stress-strain curve, creep, relaxation, and the results of the TCSS test. Based on a comparison of the results of the laboratory tests and numerical simulations, close relations between the time-dependent behaviors were revealed quantitatively.

AGRO-2014: A time dependent model for assessing the fate and food-web bioaccumulation of organic pesticides in farm ponds: Model testing and performance analysis.

PubMed

Gobas, Frank A P C; Lai, Hao-Feng; Mackay, Donald; Padilla, Lauren E; Goetz, Andy; Jackson, Scott H

2018-10-15

A time-dependent environmental fate and food-web bioaccumulation model is developed to improve the evaluation of the behaviour of non-ionic hydrophobic organic pesticides in farm ponds. The performance of the model was tested by simulating the behaviour of 3 hydrophobic organic pesticides, i.e., metaflumizone (CAS Number: 139968-49-3), kresoxim-methyl (CAS Number: 144167-04-4) and pyraclostrobin (CAS Number: 175013-18-0), in microcosm studies and a Bluegill bioconcentration study for metaflumizone. In general, model-calculated concentrations of the pesticides were in reasonable agreement with the observed concentrations. Also, calculated bioaccumulation metrics were in good agreement with observed values. The model's application to simulate concentrations of organic pesticides in water, sediment and biota of farm ponds after episodic pesticide applications is illustrated. It is further shown that the time dependent model has substantially better accuracy in simulating the concentrations of pesticides in farm ponds resulting from episodic pesticide application than corresponding steady-state models. The time dependent model is particularly useful in describing the behaviour of highly hydrophobic pesticides that have a potential to biomagnify in aquatic food-webs. Copyright © 2018 Elsevier B.V. All rights reserved.

Two-dimensional model of resonant electron collisions with diatomic molecules and molecular cations

NASA Astrophysics Data System (ADS)

Vana, Martin; Hvizdos, David; Houfek, Karel; Curik, Roman; Greene, Chris H.; Rescigno, Thomas N.; McCurdy, C. William

2016-05-01

A simple model for resonant collisions of electrons with diatomic molecules with one electronic and one nuclear degree of freedom (2D model) which was solved numerically exactly within the time-independent approach was used to probe the local complex potential approximation and nonlocal approximation to nuclear dynamics of these collisions. This model was reformulated in the time-dependent picture and extended to model also electron collisions with molecular cations, especially with H2+.This model enables an assessment of approximate methods, such as the boomerang model or the frame transformation theory. We will present both time-dependent and time-independent results and show how we can use the model to extract deeper insight into the dynamics of the resonant collisions.

Experimental verification of a real-time tuning method of a model-based controller by perturbations to its poles

NASA Astrophysics Data System (ADS)

Kajiwara, Itsuro; Furuya, Keiichiro; Ishizuka, Shinichi

2018-07-01

Model-based controllers with adaptive design variables are often used to control an object with time-dependent characteristics. However, the controller's performance is influenced by many factors such as modeling accuracy and fluctuations in the object's characteristics. One method to overcome these negative factors is to tune model-based controllers. Herein we propose an online tuning method to maintain control performance for an object that exhibits time-dependent variations. The proposed method employs the poles of the controller as design variables because the poles significantly impact performance. Specifically, we use the simultaneous perturbation stochastic approximation (SPSA) to optimize a model-based controller with multiple design variables. Moreover, a vibration control experiment of an object with time-dependent characteristics as the temperature is varied demonstrates that the proposed method allows adaptive control and stably maintains the closed-loop characteristics.

Integrable time-dependent Hamiltonians, solvable Landau-Zener models and Gaudin magnets

NASA Astrophysics Data System (ADS)

Yuzbashyan, Emil A.

2018-05-01

We solve the non-stationary Schrödinger equation for several time-dependent Hamiltonians, such as the BCS Hamiltonian with an interaction strength inversely proportional to time, periodically driven BCS and linearly driven inhomogeneous Dicke models as well as various multi-level Landau-Zener tunneling models. The latter are Demkov-Osherov, bow-tie, and generalized bow-tie models. We show that these Landau-Zener problems and their certain interacting many-body generalizations map to Gaudin magnets in a magnetic field. Moreover, we demonstrate that the time-dependent Schrödinger equation for the above models has a similar structure and is integrable with a similar technique as Knizhnik-Zamolodchikov equations. We also discuss applications of our results to the problem of molecular production in an atomic Fermi gas swept through a Feshbach resonance and to the evaluation of the Landau-Zener transition probabilities.

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

Znojil, Miloslav

For many quantum models an apparent non-Hermiticity of observables just corresponds to their hidden Hermiticity in another, physical Hilbert space. For these models we show that the existence of observables which are manifestly time-dependent may require the use of a manifestly time-dependent representation of the physical Hilbert space of states.

Can a simple lumped parameter model simulate complex transit time distributions? Benchmarking experiments in a virtual watershed.

NASA Astrophysics Data System (ADS)

Wilusz, D. C.; Maxwell, R. M.; Buda, A. R.; Ball, W. P.; Harman, C. J.

2016-12-01

The catchment transit-time distribution (TTD) is the time-varying, probabilistic distribution of water travel times through a watershed. The TTD is increasingly recognized as a useful descriptor of a catchment's flow and transport processes. However, TTDs are temporally complex and cannot be observed directly at watershed scale. Estimates of TTDs depend on available environmental tracers (such as stable water isotopes) and an assumed model whose parameters can be inverted from tracer data. All tracers have limitations though, such as (typically) short periods of observation or non-conservative behavior. As a result, models that faithfully simulate tracer observations may nonetheless yield TTD estimates with significant errors at certain times and water ages, conditioned on the tracer data available and the model structure. Recent advances have shown that time-varying catchment TTDs can be parsimoniously modeled by the lumped parameter rank StorAge Selection (rSAS) model, in which an rSAS function relates the distribution of water ages in outflows to the composition of age-ranked water in storage. Like other TTD models, rSAS is calibrated and evaluated against environmental tracer data, and the relative influence of tracer-dependent and model-dependent error on its TTD estimates is poorly understood. The purpose of this study is to benchmark the ability of different rSAS formulations to simulate TTDs in a complex, synthetic watershed where the lumped model can be calibrated and directly compared to a virtually "true" TTD. This experimental design allows for isolation of model-dependent error from tracer-dependent error. The integrated hydrologic model ParFlow with SLIM-FAST particle tracking code is used to simulate the watershed and its true TTD. To add field intelligence, the ParFlow model is populated with over forty years of hydrometric and physiographic data from the WE-38 subwatershed of the USDA's Mahantango Creek experimental catchment in PA, USA. The results are intended to give practical insight into tradeoffs between rSAS model structure and skill, and define a new performance benchmark to which other transit time models can be compared.

Better Modeling of Electrostatic Discharge in an Insulator

NASA Technical Reports Server (NTRS)

Pekov, Mihail

2010-01-01

An improved mathematical model has been developed of the time dependence of buildup or decay of electric charge in a high-resistivity (nominally insulating) material. The model is intended primarily for use in extracting the DC electrical resistivity of such a material from voltage -vs.- current measurements performed repeatedly on a sample of the material over a time comparable to the longest characteristic times (typically of the order of months) that govern the evolution of relevant properties of the material. This model is an alternative to a prior simplistic macroscopic model that yields results differing from the results of the time-dependent measurements by two to three orders of magnitude.

Neutron star dynamics under time dependent external torques

NASA Astrophysics Data System (ADS)

Alpar, M. A.; Gügercinoğlu, E.

2017-12-01

The two component model of neutron star dynamics describing the behaviour of the observed crust coupled to the superfluid interior has so far been applied to radio pulsars for which the external torques are constant on dynamical timescales. We recently solved this problem under arbitrary time dependent external torques. Our solutions pertain to internal torques that are linear in the rotation rates, as well as to the extremely non-linear internal torques of the vortex creep model. Two-component models with linear or nonlinear internal torques can now be applied to magnetars and to neutron stars in binary systems, with strong variability and timing noise. Time dependent external torques can be obtained from the observed spin-down (or spin-up) time series, \\dot Ω ≤ft( t \\right).

History-dependent friction and slow slip from time-dependent microscopic junction laws studied in a statistical framework

NASA Astrophysics Data System (ADS)

Thøgersen, Kjetil; Trømborg, Jørgen Kjoshagen; Sveinsson, Henrik Andersen; Malthe-Sørenssen, Anders; Scheibert, Julien

2014-05-01

To study how macroscopic friction phenomena originate from microscopic junction laws, we introduce a general statistical framework describing the collective behavior of a large number of individual microjunctions forming a macroscopic frictional interface. Each microjunction can switch in time between two states: a pinned state characterized by a displacement-dependent force and a slipping state characterized by a time-dependent force. Instead of tracking each microjunction individually, the state of the interface is described by two coupled distributions for (i) the stretching of pinned junctions and (ii) the time spent in the slipping state. This framework allows for a whole family of microjunction behavior laws, and we show how it represents an overarching structure for many existing models found in the friction literature. We then use this framework to pinpoint the effects of the time scale that controls the duration of the slipping state. First, we show that the model reproduces a series of friction phenomena already observed experimentally. The macroscopic steady-state friction force is velocity dependent, either monotonic (strengthening or weakening) or nonmonotonic (weakening-strengthening), depending on the microscopic behavior of individual junctions. In addition, slow slip, which has been reported in a wide variety of systems, spontaneously occurs in the model if the friction contribution from junctions in the slipping state is time weakening. Next, we show that the model predicts a nontrivial history dependence of the macroscopic static friction force. In particular, the static friction coefficient at the onset of sliding is shown to increase with increasing deceleration during the final phases of the preceding sliding event. We suggest that this form of history dependence of static friction should be investigated in experiments, and we provide the acceleration range in which this effect is expected to be experimentally observable.

History-dependent friction and slow slip from time-dependent microscopic junction laws studied in a statistical framework.

PubMed

Thøgersen, Kjetil; Trømborg, Jørgen Kjoshagen; Sveinsson, Henrik Andersen; Malthe-Sørenssen, Anders; Scheibert, Julien

2014-05-01

To study how macroscopic friction phenomena originate from microscopic junction laws, we introduce a general statistical framework describing the collective behavior of a large number of individual microjunctions forming a macroscopic frictional interface. Each microjunction can switch in time between two states: a pinned state characterized by a displacement-dependent force and a slipping state characterized by a time-dependent force. Instead of tracking each microjunction individually, the state of the interface is described by two coupled distributions for (i) the stretching of pinned junctions and (ii) the time spent in the slipping state. This framework allows for a whole family of microjunction behavior laws, and we show how it represents an overarching structure for many existing models found in the friction literature. We then use this framework to pinpoint the effects of the time scale that controls the duration of the slipping state. First, we show that the model reproduces a series of friction phenomena already observed experimentally. The macroscopic steady-state friction force is velocity dependent, either monotonic (strengthening or weakening) or nonmonotonic (weakening-strengthening), depending on the microscopic behavior of individual junctions. In addition, slow slip, which has been reported in a wide variety of systems, spontaneously occurs in the model if the friction contribution from junctions in the slipping state is time weakening. Next, we show that the model predicts a nontrivial history dependence of the macroscopic static friction force. In particular, the static friction coefficient at the onset of sliding is shown to increase with increasing deceleration during the final phases of the preceding sliding event. We suggest that this form of history dependence of static friction should be investigated in experiments, and we provide the acceleration range in which this effect is expected to be experimentally observable.

Time-dependent Data System (TDDS); an interactive program to assemble, manage, and appraise input data and numerical output of flow/transport simulation models

USGS Publications Warehouse

Regan, R.S.; Schaffranek, R.W.; Baltzer, R.A.

1996-01-01

A system of functional utilities and computer routines, collectively identified as the Time-Dependent Data System CI DDS), has been developed and documented by the U.S. Geological Survey. The TDDS is designed for processing time sequences of discrete, fixed-interval, time-varying geophysical data--in particular, hydrologic data. Such data include various, dependent variables and related parameters typically needed as input for execution of one-, two-, and three-dimensional hydrodynamic/transport and associated water-quality simulation models. Such data can also include time sequences of results generated by numerical simulation models. Specifically, TDDS provides the functional capabilities to process, store, retrieve, and compile data in a Time-Dependent Data Base (TDDB) in response to interactive user commands or pre-programmed directives. Thus, the TDDS, in conjunction with a companion TDDB, provides a ready means for processing, preparation, and assembly of time sequences of data for input to models; collection, categorization, and storage of simulation results from models; and intercomparison of field data and simulation results. The TDDS can be used to edit and verify prototype, time-dependent data to affirm that selected sequences of data are accurate, contiguous, and appropriate for numerical simulation modeling. It can be used to prepare time-varying data in a variety of formats, such as tabular lists, sequential files, arrays, graphical displays, as well as line-printer plots of single or multiparameter data sets. The TDDB is organized and maintained as a direct-access data base by the TDDS, thus providing simple, yet efficient, data management and access. A single, easily used, program interface that provides all access to and from a particular TDDB is available for use directly within models, other user-provided programs, and other data systems. This interface, together with each major functional utility of the TDDS, is described and documented in this report.

Regression analysis of sparse asynchronous longitudinal data.

PubMed

Cao, Hongyuan; Zeng, Donglin; Fine, Jason P

2015-09-01

We consider estimation of regression models for sparse asynchronous longitudinal observations, where time-dependent responses and covariates are observed intermittently within subjects. Unlike with synchronous data, where the response and covariates are observed at the same time point, with asynchronous data, the observation times are mismatched. Simple kernel-weighted estimating equations are proposed for generalized linear models with either time invariant or time-dependent coefficients under smoothness assumptions for the covariate processes which are similar to those for synchronous data. For models with either time invariant or time-dependent coefficients, the estimators are consistent and asymptotically normal but converge at slower rates than those achieved with synchronous data. Simulation studies evidence that the methods perform well with realistic sample sizes and may be superior to a naive application of methods for synchronous data based on an ad hoc last value carried forward approach. The practical utility of the methods is illustrated on data from a study on human immunodeficiency virus.

Gamma time-dependency in Blaxter's compartmental model.

NASA Technical Reports Server (NTRS)

Matis, J. H.

1972-01-01

A new two-compartment model for the passage of particles through the gastro-intestinal tract of ruminants is proposed. In this model, a gamma distribution of lifetimes is introduced in the first compartment; thereby, passage from that compartment becomes time-dependent. This modification is strongly suggested by the physical alteration which certain substances, e.g. hay particles, undergo in the digestive process. The proposed model is applied to experimental data.

Development of Co-Extrusion Technologies for Green Manufacture of Energetics

DTIC Science & Technology

2006-04-01

extrusion, Cc-extruded, ETPE, TPE, Energetic thermoplastic elastomer , PDMS, Polydimethyl siloxane, Fast core propellant, Co-layered, Wall slip, Shear...first opportunity possible, the steady FEM models of SIT will need to be converted into time dependent models to allow time dependent calculations to be

A temporal-spatial postprocessing model for probabilistic run-off forecast. With a case study from Ulla-Førre with five catchments and ten lead times

NASA Astrophysics Data System (ADS)

Engeland, K.; Steinsland, I.

2012-04-01

This work is driven by the needs of next generation short term optimization methodology for hydro power production. Stochastic optimization are about to be introduced; i.e. optimizing when available resources (water) and utility (prices) are uncertain. In this paper we focus on the available resources, i.e. water, where uncertainty mainly comes from uncertainty in future runoff. When optimizing a water system all catchments and several lead times have to be considered simultaneously. Depending on the system of hydropower reservoirs, it might be a set of headwater catchments, a system of upstream /downstream reservoirs where water used from one catchment /dam arrives in a lower catchment maybe days later, or a combination of both. The aim of this paper is therefore to construct a simultaneous probabilistic forecast for several catchments and lead times, i.e. to provide a predictive distribution for the forecasts. Stochastic optimization methods need samples/ensembles of run-off forecasts as input. Hence, it should also be possible to sample from our probabilistic forecast. A post-processing approach is taken, and an error model based on Box- Cox transformation, power transform and a temporal-spatial copula model is used. It accounts for both between catchment and between lead time dependencies. In operational use it is strait forward to sample run-off ensembles from this models that inherits the catchment and lead time dependencies. The methodology is tested and demonstrated in the Ulla-Førre river system, and simultaneous probabilistic forecasts for five catchments and ten lead times are constructed. The methodology has enough flexibility to model operationally important features in this case study such as hetroscadasety, lead-time varying temporal dependency and lead-time varying inter-catchment dependency. Our model is evaluated using CRPS for marginal predictive distributions and energy score for joint predictive distribution. It is tested against deterministic run-off forecast, climatology forecast and a persistent forecast, and is found to be the better probabilistic forecast for lead time grater then two. From an operational point of view the results are interesting as the between catchment dependency gets stronger with longer lead-times.

An EOQ model for weibull distribution deterioration with time-dependent cubic demand and backlogging

NASA Astrophysics Data System (ADS)

Santhi, G.; Karthikeyan, K.

2017-11-01

In this article we introduce an economic order quantity model with weibull deterioration and time dependent cubic demand rate where holding costs as a linear function of time. Shortages are allowed in the inventory system are partially and fully backlogging. The objective of this model is to minimize the total inventory cost by using the optimal order quantity and the cycle length. The proposed model is illustrated by numerical examples and the sensitivity analysis is performed to study the effect of changes in parameters on the optimum solutions.

Learning complex temporal patterns with resource-dependent spike timing-dependent plasticity.

PubMed

Hunzinger, Jason F; Chan, Victor H; Froemke, Robert C

2012-07-01

Studies of spike timing-dependent plasticity (STDP) have revealed that long-term changes in the strength of a synapse may be modulated substantially by temporal relationships between multiple presynaptic and postsynaptic spikes. Whereas long-term potentiation (LTP) and long-term depression (LTD) of synaptic strength have been modeled as distinct or separate functional mechanisms, here, we propose a new shared resource model. A functional consequence of our model is fast, stable, and diverse unsupervised learning of temporal multispike patterns with a biologically consistent spiking neural network. Due to interdependencies between LTP and LTD, dendritic delays, and proactive homeostatic aspects of the model, neurons are equipped to learn to decode temporally coded information within spike bursts. Moreover, neurons learn spike timing with few exposures in substantial noise and jitter. Surprisingly, despite having only one parameter, the model also accurately predicts in vitro observations of STDP in more complex multispike trains, as well as rate-dependent effects. We discuss candidate commonalities in natural long-term plasticity mechanisms.

Time dependent neural network models for detecting changes of state in complex processes: applications in earth sciences and astronomy.

PubMed

Valdés, Julio J; Bonham-Carter, Graeme

2006-03-01

A computational intelligence approach is used to explore the problem of detecting internal state changes in time dependent processes; described by heterogeneous, multivariate time series with imprecise data and missing values. Such processes are approximated by collections of time dependent non-linear autoregressive models represented by a special kind of neuro-fuzzy neural network. Grid and high throughput computing model mining procedures based on neuro-fuzzy networks and genetic algorithms, generate: (i) collections of models composed of sets of time lag terms from the time series, and (ii) prediction functions represented by neuro-fuzzy networks. The composition of the models and their prediction capabilities, allows the identification of changes in the internal structure of the process. These changes are associated with the alternation of steady and transient states, zones with abnormal behavior, instability, and other situations. This approach is general, and its sensitivity for detecting subtle changes of state is revealed by simulation experiments. Its potential in the study of complex processes in earth sciences and astrophysics is illustrated with applications using paleoclimate and solar data.

Latent Growth Modeling of nursing care dependency of acute neurological inpatients.

PubMed

Piredda, M; Ghezzi, V; De Marinis, M G; Palese, A

2015-01-01

Longitudinal three-time point study, addressing how neurological adult patient care dependency varies from the admission time to the 3rd day of acute hospitalization. Nursing care dependency was measured with the Care Dependency Scale (CDS) and a Latent Growth Modeling approach was used to analyse the CDS trend in 124 neurosurgical and stroke inpatients. Care dependence followed a decreasing linear trend. Results can help nurse-managers planning an appropriate amount of nursing care for acute neurological patients during their initial stage of hospitalization. Further studies are needed aimed at investigating the determinants of nursing care dependence during the entire in-hospital stay.

Implications of the earthquake cycle for inferring fault locking on the Cascadia megathrust

USGS Publications Warehouse

Pollitz, Fred; Evans, Eileen

2017-01-01

GPS velocity fields in the Western US have been interpreted with various physical models of the lithosphere-asthenosphere system: (1) time-independent block models; (2) time-dependent viscoelastic-cycle models, where deformation is driven by viscoelastic relaxation of the lower crust and upper mantle from past faulting events; (3) viscoelastic block models, a time-dependent variation of the block model. All three models are generally driven by a combination of loading on locked faults and (aseismic) fault creep. Here we construct viscoelastic block models and viscoelastic-cycle models for the Western US, focusing on the Pacific Northwest and the earthquake cycle on the Cascadia megathrust. In the viscoelastic block model, the western US is divided into blocks selected from an initial set of 137 microplates using the method of Total Variation Regularization, allowing potential trade-offs between faulting and megathrust coupling to be determined algorithmically from GPS observations. Fault geometry, slip rate, and locking rates (i.e. the locking fraction times the long term slip rate) are estimated simultaneously within the TVR block model. For a range of mantle asthenosphere viscosity (4.4 × 1018 to 3.6 × 1020 Pa s) we find that fault locking on the megathrust is concentrated in the uppermost 20 km in depth, and a locking rate contour line of 30 mm yr−1 extends deepest beneath the Olympic Peninsula, characteristics similar to previous time-independent block model results. These results are corroborated by viscoelastic-cycle modelling. The average locking rate required to fit the GPS velocity field depends on mantle viscosity, being higher the lower the viscosity. Moreover, for viscosity ≲ 1020 Pa s, the amount of inferred locking is higher than that obtained using a time-independent block model. This suggests that time-dependent models for a range of admissible viscosity structures could refine our knowledge of the locking distribution and its epistemic uncertainty.

A diffusive ink transport model for lipid dip-pen nanolithography

NASA Astrophysics Data System (ADS)

Urtizberea, A.; Hirtz, M.

2015-09-01

Despite diverse applications, phospholipid membrane stacks generated by dip-pen nanolithography (DPN) still lack a thorough and systematic characterization that elucidates the whole ink transport process from writing to surface spreading, with the aim of better controlling the resulting feature size and resolution. We report a quantitative analysis and modeling of the dependence of lipid DPN features (area, height and volume) on dwell time and relative humidity. The ink flow rate increases with humidity in agreement with meniscus size growth, determining the overall feature size. The observed time dependence indicates the existence of a balance between surface spreading and the ink flow rate that promotes differences in concentration at the meniscus/substrate interface. Feature shape is controlled by the substrate surface energy. The results are analyzed within a modified model for the ink transport of diffusive inks. At any humidity the dependence of the area spread on the dwell time shows two diffusion regimes: at short dwell times growth is controlled by meniscus diffusion while at long dwell times surface diffusion governs the process. The critical point for the switch of regime depends on the humidity.Despite diverse applications, phospholipid membrane stacks generated by dip-pen nanolithography (DPN) still lack a thorough and systematic characterization that elucidates the whole ink transport process from writing to surface spreading, with the aim of better controlling the resulting feature size and resolution. We report a quantitative analysis and modeling of the dependence of lipid DPN features (area, height and volume) on dwell time and relative humidity. The ink flow rate increases with humidity in agreement with meniscus size growth, determining the overall feature size. The observed time dependence indicates the existence of a balance between surface spreading and the ink flow rate that promotes differences in concentration at the meniscus/substrate interface. Feature shape is controlled by the substrate surface energy. The results are analyzed within a modified model for the ink transport of diffusive inks. At any humidity the dependence of the area spread on the dwell time shows two diffusion regimes: at short dwell times growth is controlled by meniscus diffusion while at long dwell times surface diffusion governs the process. The critical point for the switch of regime depends on the humidity. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr04352b

Comparison of parameterized nitric acid rainout rates using a coupled stochastic-photochemical tropospheric model

NASA Technical Reports Server (NTRS)

Stewart, Richard W.; Thompson, Anne M.; Owens, Melody A.; Herwehe, Jerold A.

1989-01-01

A major tropospheric loss of soluble species such as nitric acid results from scavenging by water droplets. Several theoretical formulations have been advanced which relate an effective time-independent loss rate for soluble species to statistical properties of precipitation such as the wet fraction and length of a precipitation cycle. In this paper, various 'effective' loss rates that have been proposed are compared with the results of detailed time-dependent model calculations carried out over a seasonal time scale. The model is a stochastic precipitation model coupled to a tropospheric photochemical model. The results of numerous time-dependent seasonal model runs are used to derive numerical values for the nitric acid residence time for several assumed sets of preciptation statistics. These values are then compared with the results obtained by utilizing theoretical 'effective' loss rates in time-independent models.

Time Dependent Models of Grain Formation Around Carbon Stars

NASA Technical Reports Server (NTRS)

Egan, M. P.; Shipman, R. F.

1996-01-01

Carbon-rich Asymptotic Giant Branch stars are sites of dust formation and undergo mass loss at rates ranging from 10(exp -7) to 10(exp -4) solar mass/yr. The state-of-the-art in modeling these processes is time-dependent models which simultaneously solve the grain formation and gas dynamics problem. We present results from such a model, which also includes an exact solution of the radiative transfer within the system.

Dynamics of entanglement and uncertainty relation in coupled harmonic oscillator system: exact results

NASA Astrophysics Data System (ADS)

Park, DaeKil

2018-06-01

The dynamics of entanglement and uncertainty relation is explored by solving the time-dependent Schrödinger equation for coupled harmonic oscillator system analytically when the angular frequencies and coupling constant are arbitrarily time dependent. We derive the spectral and Schmidt decompositions for vacuum solution. Using the decompositions, we derive the analytical expressions for von Neumann and Rényi entropies. Making use of Wigner distribution function defined in phase space, we derive the time dependence of position-momentum uncertainty relations. To show the dynamics of entanglement and uncertainty relation graphically, we introduce two toy models and one realistic quenched model. While the dynamics can be conjectured by simple consideration in the toy models, the dynamics in the realistic quenched model is somewhat different from that in the toy models. In particular, the dynamics of entanglement exhibits similar pattern to dynamics of uncertainty parameter in the realistic quenched model.

Spatially-Dependent Modelling of Pulsar Wind Nebula G0.9+0.1

NASA Astrophysics Data System (ADS)

van Rensburg, C.; Krüger, P. P.; Venter, C.

2018-03-01

We present results from a leptonic emission code that models the spectral energy distribution of a pulsar wind nebula by solving a Fokker-Planck-type transport equation and calculating inverse Compton and synchrotron emissivities. We have created this time-dependent, multi-zone model to investigate changes in the particle spectrum as they traverse the pulsar wind nebula, by considering a time and spatially-dependent B-field, spatially-dependent bulk particle speed implying convection and adiabatic losses, diffusion, as well as radiative losses. Our code predicts the radiation spectrum at different positions in the nebula, yielding the surface brightness versus radius and the nebular size as function of energy. We compare our new model against more basic models using the observed spectrum of pulsar wind nebula G0.9+0.1, incorporating data from H.E.S.S. as well as radio and X-ray experiments. We show that simultaneously fitting the spectral energy distribution and the energy-dependent source size leads to more stringent constraints on several model parameters.

Spatially dependent modelling of pulsar wind nebula G0.9+0.1

NASA Astrophysics Data System (ADS)

van Rensburg, C.; Krüger, P. P.; Venter, C.

2018-07-01

We present results from a leptonic emission code that models the spectral energy distribution of a pulsar wind nebula by solving a Fokker-Planck-type transport equation and calculating inverse Compton and synchrotron emissivities. We have created this time-dependent, multizone model to investigate changes in the particle spectrum as they traverse the pulsar wind nebula, by considering a time and spatially dependent B-field, spatially dependent bulk particle speed implying convection and adiabatic losses, diffusion, as well as radiative losses. Our code predicts the radiation spectrum at different positions in the nebula, yielding the surface brightness versus radius and the nebular size as function of energy. We compare our new model against more basic models using the observed spectrum of pulsar wind nebula G0.9+0.1, incorporating data from H.E.S.S. as well as radio and X-ray experiments. We show that simultaneously fitting the spectral energy distribution and the energy-dependent source size leads to more stringent constraints on several model parameters.

DaDyn-RS: a tool for the time-dependent simulation of damage, fluid pressure and long-term instability in alpine rock slopes

NASA Astrophysics Data System (ADS)

Riva, Federico; Agliardi, Federico; Amitrano, David; Crosta, Giovanni B.

2017-04-01

Large mountain slopes in alpine environments undergo a complex long-term evolution from glacial to postglacial environments, through a transient period of paraglacial readjustment. During and after this transition, the interplay among rock strength, topographic relief, and morpho-climatic drivers varying in space and time can lead to the development of different types of slope instability, from sudden catastrophic failures to large, slow, long-lasting yet potentially catastrophic rockslides. Understanding the long-term evolution of large rock slopes requires accounting for the time-dependence of deglaciation unloading, permeability and fluid pressure distribution, displacements and failure mechanisms. In turn, this is related to a convincing description of rock mass damage processes and to their transition from a sub-critical (progressive failure) to a critical (catastrophic failure) character. Although mechanisms of damage occurrence in rocks have been extensively studied in the laboratory, the description of time-dependent damage under gravitational load and variable external actions remains difficult. In this perspective, starting from a time-dependent model conceived for laboratory rock deformation, we developed Dadyn-RS, a tool to simulate the long-term evolution of real, large rock slopes. Dadyn-RS is a 2D, FEM model programmed in Matlab, which combines damage and time-to-failure laws to reproduce both diffused damage and strain localization meanwhile tracking long-term slope displacements from primary to tertiary creep stages. We implemented in the model the ability to account for rock mass heterogeneity and property upscaling, time-dependent deglaciation, as well as damage-dependent fluid pressure occurrence and stress corrosion. We first tested DaDyn-RS performance on synthetic case studies, to investigate the effect of the different model parameters on the mechanisms and timing of long-term slope behavior. The model reproduces complex interactions between topography, deglaciation rate, mechanical properties and fluid pressure occurrence, resulting in different kinematics, damage patterns and timing of slope instabilities. We assessed the role of groundwater on slope damage and deformation mechanisms by introducing time-dependent pressure cycling within simulations. Then, we applied DaDyn-RS to real slopes located in the Italian Central Alps, affected by an active rockslide and a Deep Seated Gravitational Slope Deformation, respectively. From Last Glacial Maximum to present conditions, our model allows reproducing in an explicitly time-dependent framework the progressive development of damage-induced permeability, strain localization and shear band differentiation at different times between the Lateglacial period and the Mid-Holocene climatic transition. Different mechanisms and timings characterize different styles of slope deformations, consistently with available dating constraints. DaDyn-RS is able to account for different long-term slope dynamics, from slow creep to the delayed transition to fast-moving rockslides.

Exposure time independent summary statistics for assessment of drug dependent cell line growth inhibition.

PubMed

Falgreen, Steffen; Laursen, Maria Bach; Bødker, Julie Støve; Kjeldsen, Malene Krag; Schmitz, Alexander; Nyegaard, Mette; Johnsen, Hans Erik; Dybkær, Karen; Bøgsted, Martin

2014-06-05

In vitro generated dose-response curves of human cancer cell lines are widely used to develop new therapeutics. The curves are summarised by simplified statistics that ignore the conventionally used dose-response curves' dependency on drug exposure time and growth kinetics. This may lead to suboptimal exploitation of data and biased conclusions on the potential of the drug in question. Therefore we set out to improve the dose-response assessments by eliminating the impact of time dependency. First, a mathematical model for drug induced cell growth inhibition was formulated and used to derive novel dose-response curves and improved summary statistics that are independent of time under the proposed model. Next, a statistical analysis workflow for estimating the improved statistics was suggested consisting of 1) nonlinear regression models for estimation of cell counts and doubling times, 2) isotonic regression for modelling the suggested dose-response curves, and 3) resampling based method for assessing variation of the novel summary statistics. We document that conventionally used summary statistics for dose-response experiments depend on time so that fast growing cell lines compared to slowly growing ones are considered overly sensitive. The adequacy of the mathematical model is tested for doxorubicin and found to fit real data to an acceptable degree. Dose-response data from the NCI60 drug screen were used to illustrate the time dependency and demonstrate an adjustment correcting for it. The applicability of the workflow was illustrated by simulation and application on a doxorubicin growth inhibition screen. The simulations show that under the proposed mathematical model the suggested statistical workflow results in unbiased estimates of the time independent summary statistics. Variance estimates of the novel summary statistics are used to conclude that the doxorubicin screen covers a significant diverse range of responses ensuring it is useful for biological interpretations. Time independent summary statistics may aid the understanding of drugs' action mechanism on tumour cells and potentially renew previous drug sensitivity evaluation studies.

Exposure time independent summary statistics for assessment of drug dependent cell line growth inhibition

PubMed Central

2014-01-01

Background In vitro generated dose-response curves of human cancer cell lines are widely used to develop new therapeutics. The curves are summarised by simplified statistics that ignore the conventionally used dose-response curves’ dependency on drug exposure time and growth kinetics. This may lead to suboptimal exploitation of data and biased conclusions on the potential of the drug in question. Therefore we set out to improve the dose-response assessments by eliminating the impact of time dependency. Results First, a mathematical model for drug induced cell growth inhibition was formulated and used to derive novel dose-response curves and improved summary statistics that are independent of time under the proposed model. Next, a statistical analysis workflow for estimating the improved statistics was suggested consisting of 1) nonlinear regression models for estimation of cell counts and doubling times, 2) isotonic regression for modelling the suggested dose-response curves, and 3) resampling based method for assessing variation of the novel summary statistics. We document that conventionally used summary statistics for dose-response experiments depend on time so that fast growing cell lines compared to slowly growing ones are considered overly sensitive. The adequacy of the mathematical model is tested for doxorubicin and found to fit real data to an acceptable degree. Dose-response data from the NCI60 drug screen were used to illustrate the time dependency and demonstrate an adjustment correcting for it. The applicability of the workflow was illustrated by simulation and application on a doxorubicin growth inhibition screen. The simulations show that under the proposed mathematical model the suggested statistical workflow results in unbiased estimates of the time independent summary statistics. Variance estimates of the novel summary statistics are used to conclude that the doxorubicin screen covers a significant diverse range of responses ensuring it is useful for biological interpretations. Conclusion Time independent summary statistics may aid the understanding of drugs’ action mechanism on tumour cells and potentially renew previous drug sensitivity evaluation studies. PMID:24902483

Time dependent reliability model incorporating continuum damage mechanics for high-temperature ceramics

NASA Technical Reports Server (NTRS)

Duffy, Stephen F.; Gyekenyesi, John P.

1989-01-01

Presently there are many opportunities for the application of ceramic materials at elevated temperatures. In the near future ceramic materials are expected to supplant high temperature metal alloys in a number of applications. It thus becomes essential to develop a capability to predict the time-dependent response of these materials. The creep rupture phenomenon is discussed, and a time-dependent reliability model is outlined that integrates continuum damage mechanics principles and Weibull analysis. Several features of the model are presented in a qualitative fashion, including predictions of both reliability and hazard rate. In addition, a comparison of the continuum and the microstructural kinetic equations highlights a strong resemblance in the two approaches.

Development and parameter identification of a visco-hyperelastic model for the periodontal ligament.

PubMed

Huang, Huixiang; Tang, Wencheng; Tan, Qiyan; Yan, Bin

2017-04-01

The present study developed and implemented a new visco-hyperelastic model that is capable of predicting the time-dependent biomechanical behavior of the periodontal ligament. The constitutive model has been implemented into the finite element package ABAQUS by means of a user-defined material subroutine (UMAT). The stress response is decomposed into two constitutive parts in parallel which are a hyperelastic and a time-dependent viscoelastic stress response. In order to identify the model parameters, the indentation equation based on V-W hyperelastic model and the indentation creep model are developed. Then the parameters are determined by fitting them to the corresponding nanoindentation experimental data of the PDL. The nanoindentation experiment was simulated by finite element analysis to validate the visco-hyperelastic model. The simulated results are in good agreement with the experimental data, which demonstrates that the visco-hyperelastic model developed is able to accurately predict the time-dependent mechanical behavior of the PDL. Copyright © 2017 Elsevier Ltd. All rights reserved.

Comparison of algorithms to generate event times conditional on time-dependent covariates.

PubMed

Sylvestre, Marie-Pierre; Abrahamowicz, Michal

2008-06-30

The Cox proportional hazards model with time-dependent covariates (TDC) is now a part of the standard statistical analysis toolbox in medical research. As new methods involving more complex modeling of time-dependent variables are developed, simulations could often be used to systematically assess the performance of these models. Yet, generating event times conditional on TDC requires well-designed and efficient algorithms. We compare two classes of such algorithms: permutational algorithms (PAs) and algorithms based on a binomial model. We also propose a modification of the PA to incorporate a rejection sampler. We performed a simulation study to assess the accuracy, stability, and speed of these algorithms in several scenarios. Both classes of algorithms generated data sets that, once analyzed, provided virtually unbiased estimates with comparable variances. In terms of computational efficiency, the PA with the rejection sampler reduced the time necessary to generate data by more than 50 per cent relative to alternative methods. The PAs also allowed more flexibility in the specification of the marginal distributions of event times and required less calibration.

Rating knowledge sharing in cross-domain collaborative filtering.

PubMed

Li, Bin; Zhu, Xingquan; Li, Ruijiang; Zhang, Chengqi

2015-05-01

Cross-domain collaborative filtering (CF) aims to share common rating knowledge across multiple related CF domains to boost the CF performance. In this paper, we view CF domains as a 2-D site-time coordinate system, on which multiple related domains, such as similar recommender sites or successive time-slices, can share group-level rating patterns. We propose a unified framework for cross-domain CF over the site-time coordinate system by sharing group-level rating patterns and imposing user/item dependence across domains. A generative model, say ratings over site-time (ROST), which can generate and predict ratings for multiple related CF domains, is developed as the basic model for the framework. We further introduce cross-domain user/item dependence into ROST and extend it to two real-world cross-domain CF scenarios: 1) ROST (sites) for alleviating rating sparsity in the target domain, where multiple similar sites are viewed as related CF domains and some items in the target domain depend on their correspondences in the related ones; and 2) ROST (time) for modeling user-interest drift over time, where a series of time-slices are viewed as related CF domains and a user at current time-slice depends on herself in the previous time-slice. All these ROST models are instances of the proposed unified framework. The experimental results show that ROST (sites) can effectively alleviate the sparsity problem to improve rating prediction performance and ROST (time) can clearly track and visualize user-interest drift over time.

Modeling Time-Dependent Association in Longitudinal Data: A Lag as Moderator Approach

ERIC Educational Resources Information Center

Selig, James P.; Preacher, Kristopher J.; Little, Todd D.

2012-01-01

We describe a straightforward, yet novel, approach to examine time-dependent association between variables. The approach relies on a measurement-lag research design in conjunction with statistical interaction models. We base arguments in favor of this approach on the potential for better understanding the associations between variables by…

About influence of input rate random part of nonstationary queue system on statistical estimates of its macroscopic indicators

NASA Astrophysics Data System (ADS)

Korelin, Ivan A.; Porshnev, Sergey V.

2018-05-01

A model of the non-stationary queuing system (NQS) is described. The input of this model receives a flow of requests with input rate λ = λdet (t) + λrnd (t), where λdet (t) is a deterministic function depending on time; λrnd (t) is a random function. The parameters of functions λdet (t), λrnd (t) were identified on the basis of statistical information on visitor flows collected from various Russian football stadiums. The statistical modeling of NQS is carried out and the average statistical dependences are obtained: the length of the queue of requests waiting for service, the average wait time for the service, the number of visitors entered to the stadium on the time. It is shown that these dependencies can be characterized by the following parameters: the number of visitors who entered at the time of the match; time required to service all incoming visitors; the maximum value; the argument value when the studied dependence reaches its maximum value. The dependences of these parameters on the energy ratio of the deterministic and random component of the input rate are investigated.

Viscoelastic modeling of deformation and gravity changes induced by pressurized magmatic sources

NASA Astrophysics Data System (ADS)

Currenti, Gilda

2018-05-01

Gravity and height changes, which reflect magma accumulation in subsurface chambers, are evaluated using analytical and numerical models in order to investigate their relationships and temporal evolutions. The analysis focuses mainly on the exploration of the time-dependent response of gravity and height changes to the pressurization of ellipsoidal magmatic chambers in viscoelastic media. Firstly, the validation of the numerical Finite Element results is performed by comparison with analytical solutions, which are devised for a simple spherical source embedded in a homogeneous viscoelastic half-space medium. Then, the effect of several model parameters on time-dependent height and gravity changes is investigated thanks to the flexibility of the numerical method in handling complex configurations. Both homogeneous and viscoelastic shell models reveal significantly different amplitudes in the ratio between gravity and height changes depending on geometry factors and medium rheology. The results show that these factors also influence the relaxation characteristic times of the investigated geophysical changes. Overall, these temporal patterns are compatible with time-dependent height and gravity changes observed on Etna volcano during the 1994-1997 inflation period. By modeling the viscoelastic response of a pressurized prolate magmatic source, a general agreement between computed and observed geophysical variations is achieved.

Mathematical analysis of a power-law form time dependent vector-borne disease transmission model.

PubMed

Sardar, Tridip; Saha, Bapi

2017-06-01

In the last few years, fractional order derivatives have been used in epidemiology to capture the memory phenomena. However, these models do not have proper biological justification in most of the cases and lack a derivation from a stochastic process. In this present manuscript, using theory of a stochastic process, we derived a general time dependent single strain vector borne disease model. It is shown that under certain choice of time dependent transmission kernel this model can be converted into the classical integer order system. When the time-dependent transmission follows a power law form, we showed that the model converted into a vector borne disease model with fractional order transmission. We explicitly derived the disease-free and endemic equilibrium of this new fractional order vector borne disease model. Using mathematical properties of nonlinear Volterra type integral equation it is shown that the unique disease-free state is globally asymptotically stable under certain condition. We define a threshold quantity which is epidemiologically known as the basic reproduction number (R 0 ). It is shown that if R 0 > 1, then the derived fractional order model has a unique endemic equilibrium. We analytically derived the condition for the local stability of the endemic equilibrium. To test the model capability to capture real epidemic, we calibrated our newly proposed model to weekly dengue incidence data of San Juan, Puerto Rico for the time period 30th April 1994 to 23rd April 1995. We estimated several parameters, including the order of the fractional derivative of the proposed model using aforesaid data. It is shown that our proposed fractional order model can nicely capture real epidemic. Copyright © 2017 Elsevier Inc. All rights reserved.

Evaluation of the effects of climate and man intervention on ground waters and their dependent ecosystems using time series analysis

NASA Astrophysics Data System (ADS)

Gemitzi, Alexandra; Stefanopoulos, Kyriakos

2011-06-01

SummaryGroundwaters and their dependent ecosystems are affected both by the meteorological conditions as well as from human interventions, mainly in the form of groundwater abstractions for irrigation needs. This work aims at investigating the quantitative effects of meteorological conditions and man intervention on groundwater resources and their dependent ecosystems. Various seasonal Auto-Regressive Integrated Moving Average (ARIMA) models with external predictor variables were used in order to model the influence of meteorological conditions and man intervention on the groundwater level time series. Initially, a seasonal ARIMA model that simulates the abstraction time series using as external predictor variable temperature ( T) was prepared. Thereafter, seasonal ARIMA models were developed in order to simulate groundwater level time series in 8 monitoring locations, using the appropriate predictor variables determined for each individual case. The spatial component was introduced through the use of Geographical Information Systems (GIS). Application of the proposed methodology took place in the Neon Sidirochorion alluvial aquifer (Northern Greece), for which a 7-year long time series (i.e., 2003-2010) of piezometric and groundwater abstraction data exists. According to the developed ARIMA models, three distinct groups of groundwater level time series exist; the first one proves to be dependent only on the meteorological parameters, the second group demonstrates a mixed dependence both on meteorological conditions and on human intervention, whereas the third group shows a clear influence from man intervention. Moreover, there is evidence that groundwater abstraction has affected an important protected ecosystem.

Time-local equation for exact time-dependent optimized effective potential in time-dependent density functional theory

NASA Astrophysics Data System (ADS)

Liao, Sheng-Lun; Ho, Tak-San; Rabitz, Herschel; Chu, Shih-I.

2017-04-01

Solving and analyzing the exact time-dependent optimized effective potential (TDOEP) integral equation has been a longstanding challenge due to its highly nonlinear and nonlocal nature. To meet the challenge, we derive an exact time-local TDOEP equation that admits a unique real-time solution in terms of time-dependent Kohn-Sham orbitals and effective memory orbitals. For illustration, the dipole evolution dynamics of a one-dimension-model chain of hydrogen atoms is numerically evaluated and examined to demonstrate the utility of the proposed time-local formulation. Importantly, it is shown that the zero-force theorem, violated by the time-dependent Krieger-Li-Iafrate approximation, is fulfilled in the current TDOEP framework. This work was partially supported by DOE.

A better understanding of long-range temporal dependence of traffic flow time series

NASA Astrophysics Data System (ADS)

Feng, Shuo; Wang, Xingmin; Sun, Haowei; Zhang, Yi; Li, Li

2018-02-01

Long-range temporal dependence is an important research perspective for modelling of traffic flow time series. Various methods have been proposed to depict the long-range temporal dependence, including autocorrelation function analysis, spectral analysis and fractal analysis. However, few researches have studied the daily temporal dependence (i.e. the similarity between different daily traffic flow time series), which can help us better understand the long-range temporal dependence, such as the origin of crossover phenomenon. Moreover, considering both types of dependence contributes to establishing more accurate model and depicting the properties of traffic flow time series. In this paper, we study the properties of daily temporal dependence by simple average method and Principal Component Analysis (PCA) based method. Meanwhile, we also study the long-range temporal dependence by Detrended Fluctuation Analysis (DFA) and Multifractal Detrended Fluctuation Analysis (MFDFA). The results show that both the daily and long-range temporal dependence exert considerable influence on the traffic flow series. The DFA results reveal that the daily temporal dependence creates crossover phenomenon when estimating the Hurst exponent which depicts the long-range temporal dependence. Furthermore, through the comparison of the DFA test, PCA-based method turns out to be a better method to extract the daily temporal dependence especially when the difference between days is significant.

Applying the relaxation model of interfacial heat transfer to calculate the liquid outflow with supercritical initial parameters

NASA Astrophysics Data System (ADS)

Alekseev, M. V.; Vozhakov, I. S.; Lezhnin, S. I.; Pribaturin, N. A.

2017-09-01

A comparative numerical simulation of the supercritical fluid outflow on the thermodynamic equilibrium and non-equilibrium relaxation models of phase transition for different times of relaxation has been performed. The model for the fixed relaxation time based on the experimentally determined radius of liquid droplets was compared with the model of dynamically changing relaxation time, calculated by the formula (7) and depending on local parameters. It is shown that the relaxation time varies significantly depending on the thermodynamic conditions of the two-phase medium in the course of outflowing. The application of the proposed model with dynamic relaxation time leads to qualitatively correct results. The model can be used for both vaporization and condensation processes. It is shown that the model can be improved on the basis of processing experimental data on the distribution of the droplet sizes formed during the breaking up of the liquid jet.

On absence of steady state in the Bouchaud-Mézard network model

NASA Astrophysics Data System (ADS)

Liu, Zhiyuan; Serota, R. A.

2018-02-01

In the limit of infinite number of nodes (agents), the Itô-reduced Bouchaud-Mézard network model of economic exchange has a time-independent mean and a steady-state inverse gamma distribution. We show that for a finite number of nodes the mean is actually distributed as a time-dependent lognormal and inverse gamma is quasi-stationary, with the time-dependent scale parameter.

Trap densities and transport properties of pentacene metal-oxide-semiconductor transistors. I. Analytical modeling of time-dependent characteristics

NASA Astrophysics Data System (ADS)

Basile, A. F.; Cramer, T.; Kyndiah, A.; Biscarini, F.; Fraboni, B.

2014-06-01

Metal-oxide-semiconductor (MOS) transistors fabricated with pentacene thin films were characterized by temperature-dependent current-voltage (I-V) characteristics, time-dependent current measurements, and admittance spectroscopy. The channel mobility shows almost linear variation with temperature, suggesting that only shallow traps are present in the semiconductor and at the oxide/semiconductor interface. The admittance spectra feature a broad peak, which can be modeled as the sum of a continuous distribution of relaxation times. The activation energy of this peak is comparable to the polaron binding energy in pentacene. The absence of trap signals in the admittance spectra confirmed that both the semiconductor and the oxide/semiconductor interface have negligible density of deep traps, likely owing to the passivation of SiO2 before pentacene growth. Nevertheless, current instabilities were observed in time-dependent current measurements following the application of gate-voltage pulses. The corresponding activation energy matches the energy of a hole trap in SiO2. We show that hole trapping in the oxide can explain both the temperature and the time dependences of the current instabilities observed in pentacene MOS transistors. The combination of these experimental techniques allows us to derive a comprehensive model for charge transport in hybrid architectures where trapping processes occur at various time and length scales.

Stability switches, Hopf bifurcation and chaos of a neuron model with delay-dependent parameters

NASA Astrophysics Data System (ADS)

Xu, X.; Hu, H. Y.; Wang, H. L.

2006-05-01

It is very common that neural network systems usually involve time delays since the transmission of information between neurons is not instantaneous. Because memory intensity of the biological neuron usually depends on time history, some of the parameters may be delay dependent. Yet, little attention has been paid to the dynamics of such systems. In this Letter, a detailed analysis on the stability switches, Hopf bifurcation and chaos of a neuron model with delay-dependent parameters is given. Moreover, the direction and the stability of the bifurcating periodic solutions are obtained by the normal form theory and the center manifold theorem. It shows that the dynamics of the neuron model with delay-dependent parameters is quite different from that of systems with delay-independent parameters only.

Regression analysis of sparse asynchronous longitudinal data

PubMed Central

Cao, Hongyuan; Zeng, Donglin; Fine, Jason P.

2015-01-01

Summary We consider estimation of regression models for sparse asynchronous longitudinal observations, where time-dependent responses and covariates are observed intermittently within subjects. Unlike with synchronous data, where the response and covariates are observed at the same time point, with asynchronous data, the observation times are mismatched. Simple kernel-weighted estimating equations are proposed for generalized linear models with either time invariant or time-dependent coefficients under smoothness assumptions for the covariate processes which are similar to those for synchronous data. For models with either time invariant or time-dependent coefficients, the estimators are consistent and asymptotically normal but converge at slower rates than those achieved with synchronous data. Simulation studies evidence that the methods perform well with realistic sample sizes and may be superior to a naive application of methods for synchronous data based on an ad hoc last value carried forward approach. The practical utility of the methods is illustrated on data from a study on human immunodeficiency virus. PMID:26568699

Effect of time dependence on probabilistic seismic-hazard maps and deaggregation for the central Apennines, Italy

USGS Publications Warehouse

Akinci, A.; Galadini, F.; Pantosti, D.; Petersen, M.; Malagnini, L.; Perkins, D.

2009-01-01

We produce probabilistic seismic-hazard assessments for the central Apennines, Italy, using time-dependent models that are characterized using a Brownian passage time recurrence model. Using aperiodicity parameters, ?? of 0.3, 0.5, and 0.7, we examine the sensitivity of the probabilistic ground motion and its deaggregation to these parameters. For the seismic source model we incorporate both smoothed historical seismicity over the area and geological information on faults. We use the maximum magnitude model for the fault sources together with a uniform probability of rupture along the fault (floating fault model) to model fictitious faults to account for earthquakes that cannot be correlated with known geologic structural segmentation.

Multiaxial Temperature- and Time-Dependent Failure Model

NASA Technical Reports Server (NTRS)

Richardson, David; McLennan, Michael; Anderson, Gregory; Macon, David; Batista-Rodriquez, Alicia

2003-01-01

A temperature- and time-dependent mathematical model predicts the conditions for failure of a material subjected to multiaxial stress. The model was initially applied to a filled epoxy below its glass-transition temperature, and is expected to be applicable to other materials, at least below their glass-transition temperatures. The model is justified simply by the fact that it closely approximates the experimentally observed failure behavior of this material: The multiaxiality of the model has been confirmed (see figure) and the model has been shown to be applicable at temperatures from -20 to 115 F (-29 to 46 C) and to predict tensile failures of constant-load and constant-load-rate specimens with failure times ranging from minutes to months..

Non-Gaussian lineshapes and dynamics of time-resolved linear and nonlinear (correlation) spectra.

PubMed

Dinpajooh, Mohammadhasan; Matyushov, Dmitry V

2014-07-17

Signatures of nonlinear and non-Gaussian dynamics in time-resolved linear and nonlinear (correlation) 2D spectra are analyzed in a model considering a linear plus quadratic dependence of the spectroscopic transition frequency on a Gaussian nuclear coordinate of the thermal bath (quadratic coupling). This new model is contrasted to the commonly assumed linear dependence of the transition frequency on the medium nuclear coordinates (linear coupling). The linear coupling model predicts equality between the Stokes shift and equilibrium correlation functions of the transition frequency and time-independent spectral width. Both predictions are often violated, and we are asking here the question of whether a nonlinear solvent response and/or non-Gaussian dynamics are required to explain these observations. We find that correlation functions of spectroscopic observables calculated in the quadratic coupling model depend on the chromophore's electronic state and the spectral width gains time dependence, all in violation of the predictions of the linear coupling models. Lineshape functions of 2D spectra are derived assuming Ornstein-Uhlenbeck dynamics of the bath nuclear modes. The model predicts asymmetry of 2D correlation plots and bending of the center line. The latter is often used to extract two-point correlation functions from 2D spectra. The dynamics of the transition frequency are non-Gaussian. However, the effect of non-Gaussian dynamics is limited to the third-order (skewness) time correlation function, without affecting the time correlation functions of higher order. The theory is tested against molecular dynamics simulations of a model polar-polarizable chromophore dissolved in a force field water.

Light propagation from fluorescent probes in biological tissues by coupled time-dependent parabolic simplified spherical harmonics equations

PubMed Central

Domínguez, Jorge Bouza; Bérubé-Lauzière, Yves

2011-01-01

We introduce a system of coupled time-dependent parabolic simplified spherical harmonic equations to model the propagation of both excitation and fluorescence light in biological tissues. We resort to a finite element approach to obtain the time-dependent profile of the excitation and the fluorescence light fields in the medium. We present results for cases involving two geometries in three-dimensions: a homogeneous cylinder with an embedded fluorescent inclusion and a realistically-shaped rodent with an embedded inclusion alike an organ filled with a fluorescent probe. For the cylindrical geometry, we show the differences in the time-dependent fluorescence response for a point-like, a spherical, and a spherically Gaussian distributed fluorescent inclusion. From our results, we conclude that the model is able to describe the time-dependent excitation and fluorescent light transfer in small geometries with high absorption coefficients and in nondiffusive domains, as may be found in small animal diffuse optical tomography (DOT) and fluorescence DOT imaging. PMID:21483606

Dissipative time-dependent quantum transport theory.

PubMed

Zhang, Yu; Yam, Chi Yung; Chen, GuanHua

2013-04-28

A dissipative time-dependent quantum transport theory is developed to treat the transient current through molecular or nanoscopic devices in presence of electron-phonon interaction. The dissipation via phonon is taken into account by introducing a self-energy for the electron-phonon coupling in addition to the self-energy caused by the electrodes. Based on this, a numerical method is proposed. For practical implementation, the lowest order expansion is employed for the weak electron-phonon coupling case and the wide-band limit approximation is adopted for device and electrodes coupling. The corresponding hierarchical equation of motion is derived, which leads to an efficient and accurate time-dependent treatment of inelastic effect on transport for the weak electron-phonon interaction. The resulting method is applied to a one-level model system and a gold wire described by tight-binding model to demonstrate its validity and the importance of electron-phonon interaction for the quantum transport. As it is based on the effective single-electron model, the method can be readily extended to time-dependent density functional theory.

Estimating the effect of a rare time-dependent treatment on the recurrent event rate.

PubMed

Smith, Abigail R; Zhu, Danting; Goodrich, Nathan P; Merion, Robert M; Schaubel, Douglas E

2018-05-30

In many observational studies, the objective is to estimate the effect of treatment or state-change on the recurrent event rate. If treatment is assigned after the start of follow-up, traditional methods (eg, adjustment for baseline-only covariates or fully conditional adjustment for time-dependent covariates) may give biased results. We propose a two-stage modeling approach using the method of sequential stratification to accurately estimate the effect of a time-dependent treatment on the recurrent event rate. At the first stage, we estimate the pretreatment recurrent event trajectory using a proportional rates model censored at the time of treatment. Prognostic scores are estimated from the linear predictor of this model and used to match treated patients to as yet untreated controls based on prognostic score at the time of treatment for the index patient. The final model is stratified on matched sets and compares the posttreatment recurrent event rate to the recurrent event rate of the matched controls. We demonstrate through simulation that bias due to dependent censoring is negligible, provided the treatment frequency is low, and we investigate a threshold at which correction for dependent censoring is needed. The method is applied to liver transplant (LT), where we estimate the effect of development of post-LT End Stage Renal Disease (ESRD) on rate of days hospitalized. Copyright © 2018 John Wiley & Sons, Ltd.

First-principles X-ray absorption dose calculation for time-dependent mass and optical density.

PubMed

Berejnov, Viatcheslav; Rubinstein, Boris; Melo, Lis G A; Hitchcock, Adam P

2018-05-01

A dose integral of time-dependent X-ray absorption under conditions of variable photon energy and changing sample mass is derived from first principles starting with the Beer-Lambert (BL) absorption model. For a given photon energy the BL dose integral D(e, t) reduces to the product of an effective time integral T(t) and a dose rate R(e). Two approximations of the time-dependent optical density, i.e. exponential A(t) = c + aexp(-bt) for first-order kinetics and hyperbolic A(t) = c + a/(b + t) for second-order kinetics, were considered for BL dose evaluation. For both models three methods of evaluating the effective time integral are considered: analytical integration, approximation by a function, and calculation of the asymptotic behaviour at large times. Data for poly(methyl methacrylate) and perfluorosulfonic acid polymers measured by scanning transmission soft X-ray microscopy were used to test the BL dose calculation. It was found that a previous method to calculate time-dependent dose underestimates the dose in mass loss situations, depending on the applied exposure time. All these methods here show that the BL dose is proportional to the exposure time D(e, t) ≃ K(e)t.

Towards an Analytical Age-Dependent Model of Contrast Sensitivity Functions for an Ageing Society

PubMed Central

Joulan, Karine; Brémond, Roland

2015-01-01

The Contrast Sensitivity Function (CSF) describes how the visibility of a grating depends on the stimulus spatial frequency. Many published CSF data have demonstrated that contrast sensitivity declines with age. However, an age-dependent analytical model of the CSF is not available to date. In this paper, we propose such an analytical CSF model based on visual mechanisms, taking into account the age factor. To this end, we have extended an existing model from Barten (1999), taking into account the dependencies of this model's optical and physiological parameters on age. Age-dependent models of the cones and ganglion cells densities, the optical and neural MTF, and optical and neural noise are proposed, based on published data. The proposed age-dependent CSF is finally tested against available experimental data, with fair results. Such an age-dependent model may be beneficial when designing real-time age-dependent image coding and display applications. PMID:26078994

Time-dependent Perpendicular Transport of Energetic Particles for Different Turbulence Configurations and Parallel Transport Models

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

Lasuik, J.; Shalchi, A., E-mail: andreasm4@yahoo.com

Recently, a new theory for the transport of energetic particles across a mean magnetic field was presented. Compared to other nonlinear theories the new approach has the advantage that it provides a full time-dependent description of the transport. Furthermore, a diffusion approximation is no longer part of that theory. The purpose of this paper is to combine this new approach with a time-dependent model for parallel transport and different turbulence configurations in order to explore the parameter regimes for which we get ballistic transport, compound subdiffusion, and normal Markovian diffusion.

Modeling the time-varying and level-dependent effects of the medial olivocochlear reflex in auditory nerve responses.

PubMed

Smalt, Christopher J; Heinz, Michael G; Strickland, Elizabeth A

2014-04-01

The medial olivocochlear reflex (MOCR) has been hypothesized to provide benefit for listening in noisy environments. This advantage can be attributed to a feedback mechanism that suppresses auditory nerve (AN) firing in continuous background noise, resulting in increased sensitivity to a tone or speech. MOC neurons synapse on outer hair cells (OHCs), and their activity effectively reduces cochlear gain. The computational model developed in this study implements the time-varying, characteristic frequency (CF) and level-dependent effects of the MOCR within the framework of a well-established model for normal and hearing-impaired AN responses. A second-order linear system was used to model the time-course of the MOCR using physiological data in humans. The stimulus-level-dependent parameters of the efferent pathway were estimated by fitting AN sensitivity derived from responses in decerebrate cats using a tone-in-noise paradigm. The resulting model uses a binaural, time-varying, CF-dependent, level-dependent OHC gain reduction for both ipsilateral and contralateral stimuli that improves detection of a tone in noise, similarly to recorded AN responses. The MOCR may be important for speech recognition in continuous background noise as well as for protection from acoustic trauma. Further study of this model and its efferent feedback loop may improve our understanding of the effects of sensorineural hearing loss in noisy situations, a condition in which hearing aids currently struggle to restore normal speech perception.

Emergence of Landauer transport from quantum dynamics: A model Hamiltonian approach

NASA Astrophysics Data System (ADS)

Pal, Partha Pratim; Ramakrishna, S.; Seideman, Tamar

2018-04-01

The Landauer expression for computing current-voltage characteristics in nanoscale devices is efficient but not suited to transient phenomena and a time-dependent current because it is applicable only when the charge carriers transition into a steady flux after an external perturbation. In this article, we construct a very general expression for time-dependent current in an electrode-molecule-electrode arrangement. Utilizing a model Hamiltonian (consisting of the subsystem energy levels and their electronic coupling terms), we propagate the Schrödinger wave function equation to numerically compute the time-dependent population in the individual subsystems. The current in each electrode (defined in terms of the rate of change of the corresponding population) has two components, one due to the charges originating from the same electrode and the other due to the charges initially residing at the other electrode. We derive an analytical expression for the first component and illustrate that it agrees reasonably with its numerical counterpart at early times. Exploiting the unitary evolution of a wavefunction, we construct a more general Landauer style formula and illustrate the emergence of Landauer transport from our simulations without the assumption of time-independent charge flow. Our generalized Landauer formula is valid at all times for models beyond the wide-band limit, non-uniform electrode density of states and for time and energy-dependent electronic coupling between the subsystems. Subsequently, we investigate the ingredients in our model that regulate the onset time scale of this steady state. We compare the performance of our general current expression with the Landauer current for time-dependent electronic coupling. Finally, we comment on the applicability of the Landauer formula to compute hot-electron current arising upon plasmon decoherence.

Emergence of Landauer transport from quantum dynamics: A model Hamiltonian approach.

PubMed

Pal, Partha Pratim; Ramakrishna, S; Seideman, Tamar

2018-04-14

The Landauer expression for computing current-voltage characteristics in nanoscale devices is efficient but not suited to transient phenomena and a time-dependent current because it is applicable only when the charge carriers transition into a steady flux after an external perturbation. In this article, we construct a very general expression for time-dependent current in an electrode-molecule-electrode arrangement. Utilizing a model Hamiltonian (consisting of the subsystem energy levels and their electronic coupling terms), we propagate the Schrödinger wave function equation to numerically compute the time-dependent population in the individual subsystems. The current in each electrode (defined in terms of the rate of change of the corresponding population) has two components, one due to the charges originating from the same electrode and the other due to the charges initially residing at the other electrode. We derive an analytical expression for the first component and illustrate that it agrees reasonably with its numerical counterpart at early times. Exploiting the unitary evolution of a wavefunction, we construct a more general Landauer style formula and illustrate the emergence of Landauer transport from our simulations without the assumption of time-independent charge flow. Our generalized Landauer formula is valid at all times for models beyond the wide-band limit, non-uniform electrode density of states and for time and energy-dependent electronic coupling between the subsystems. Subsequently, we investigate the ingredients in our model that regulate the onset time scale of this steady state. We compare the performance of our general current expression with the Landauer current for time-dependent electronic coupling. Finally, we comment on the applicability of the Landauer formula to compute hot-electron current arising upon plasmon decoherence.

Indentation mapping revealed poroelastic, but not viscoelastic, properties spanning native zonal articular cartilage.

PubMed

Wahlquist, Joseph A; DelRio, Frank W; Randolph, Mark A; Aziz, Aaron H; Heveran, Chelsea M; Bryant, Stephanie J; Neu, Corey P; Ferguson, Virginia L

2017-12-01

Osteoarthrosis is a debilitating disease affecting millions, yet engineering materials for cartilage regeneration has proven difficult because of the complex microstructure of this tissue. Articular cartilage, like many biological tissues, produces a time-dependent response to mechanical load that is critical to cell's physiological function in part due to solid and fluid phase interactions and property variations across multiple length scales. Recreating the time-dependent strain and fluid flow may be critical for successfully engineering replacement tissues but thus far has largely been neglected. Here, microindentation is used to accomplish three objectives: (1) quantify a material's time-dependent mechanical response, (2) map material properties at a cellular relevant length scale throughout zonal articular cartilage and (3) elucidate the underlying viscoelastic, poroelastic, and nonlinear poroelastic causes of deformation in articular cartilage. Untreated and trypsin-treated cartilage was sectioned perpendicular to the articular surface and indentation was used to evaluate properties throughout zonal cartilage on the cut surface. The experimental results demonstrated that within all cartilage zones, the mechanical response was well represented by a model assuming nonlinear biphasic behavior and did not follow conventional viscoelastic or linear poroelastic models. Additionally, 10% (w/w) agarose was tested and, as anticipated, behaved as a linear poroelastic material. The approach outlined here provides a method, applicable to many tissues and biomaterials, which reveals and quantifies the underlying causes of time-dependent deformation, elucidates key aspects of material structure and function, and that can be used to provide important inputs for computational models and targets for tissue engineering. Elucidating the time-dependent mechanical behavior of cartilage, and other biological materials, is critical to adequately recapitulate native mechanosensory cues for cells. We used microindentation to map the time-dependent properties of untreated and trypsin treated cartilage throughout each cartilage zone. Unlike conventional approaches that combine viscoelastic and poroelastic behaviors into a single framework, we deconvoluted the mechanical response into separate contributions to time-dependent behavior. Poroelastic effects in all cartilage zones dominated the time-dependent behavior of articular cartilage, and a model that incorporates tension-compression nonlinearity best represented cartilage mechanical behavior. These results can be used to assess the success of regeneration and repair approaches, as design targets for tissue engineering, and for development of accurate computational models. Copyright © 2017 Acta Materialia Inc. All rights reserved.

Predation and fragmentation portrayed in the statistical structure of prey time series

PubMed Central

Hendrichsen, Ditte K; Topping, Chris J; Forchhammer, Mads C

2009-01-01

Background Statistical autoregressive analyses of direct and delayed density dependence are widespread in ecological research. The models suggest that changes in ecological factors affecting density dependence, like predation and landscape heterogeneity are directly portrayed in the first and second order autoregressive parameters, and the models are therefore used to decipher complex biological patterns. However, independent tests of model predictions are complicated by the inherent variability of natural populations, where differences in landscape structure, climate or species composition prevent controlled repeated analyses. To circumvent this problem, we applied second-order autoregressive time series analyses to data generated by a realistic agent-based computer model. The model simulated life history decisions of individual field voles under controlled variations in predator pressure and landscape fragmentation. Analyses were made on three levels: comparisons between predated and non-predated populations, between populations exposed to different types of predators and between populations experiencing different degrees of habitat fragmentation. Results The results are unambiguous: Changes in landscape fragmentation and the numerical response of predators are clearly portrayed in the statistical time series structure as predicted by the autoregressive model. Populations without predators displayed significantly stronger negative direct density dependence than did those exposed to predators, where direct density dependence was only moderately negative. The effects of predation versus no predation had an even stronger effect on the delayed density dependence of the simulated prey populations. In non-predated prey populations, the coefficients of delayed density dependence were distinctly positive, whereas they were negative in predated populations. Similarly, increasing the degree of fragmentation of optimal habitat available to the prey was accompanied with a shift in the delayed density dependence, from strongly negative to gradually becoming less negative. Conclusion We conclude that statistical second-order autoregressive time series analyses are capable of deciphering interactions within and across trophic levels and their effect on direct and delayed density dependence. PMID:19419539

A diffusive ink transport model for lipid dip-pen nanolithography.

PubMed

Urtizberea, A; Hirtz, M

2015-10-14

Despite diverse applications, phospholipid membrane stacks generated by dip-pen nanolithography (DPN) still lack a thorough and systematic characterization that elucidates the whole ink transport process from writing to surface spreading, with the aim of better controlling the resulting feature size and resolution. We report a quantitative analysis and modeling of the dependence of lipid DPN features (area, height and volume) on dwell time and relative humidity. The ink flow rate increases with humidity in agreement with meniscus size growth, determining the overall feature size. The observed time dependence indicates the existence of a balance between surface spreading and the ink flow rate that promotes differences in concentration at the meniscus/substrate interface. Feature shape is controlled by the substrate surface energy. The results are analyzed within a modified model for the ink transport of diffusive inks. At any humidity the dependence of the area spread on the dwell time shows two diffusion regimes: at short dwell times growth is controlled by meniscus diffusion while at long dwell times surface diffusion governs the process. The critical point for the switch of regime depends on the humidity.

M≥7 Earthquake rupture forecast and time-dependent probability for the Sea of Marmara region, Turkey

USGS Publications Warehouse

Murru, Maura; Akinci, Aybige; Falcone, Guiseppe; Pucci, Stefano; Console, Rodolfo; Parsons, Thomas E.

2016-01-01

We forecast time-independent and time-dependent earthquake ruptures in the Marmara region of Turkey for the next 30 years using a new fault-segmentation model. We also augment time-dependent Brownian Passage Time (BPT) probability with static Coulomb stress changes (ΔCFF) from interacting faults. We calculate Mw > 6.5 probability from 26 individual fault sources in the Marmara region. We also consider a multisegment rupture model that allows higher-magnitude ruptures over some segments of the Northern branch of the North Anatolian Fault Zone (NNAF) beneath the Marmara Sea. A total of 10 different Mw=7.0 to Mw=8.0 multisegment ruptures are combined with the other regional faults at rates that balance the overall moment accumulation. We use Gaussian random distributions to treat parameter uncertainties (e.g., aperiodicity, maximum expected magnitude, slip rate, and consequently mean recurrence time) of the statistical distributions associated with each fault source. We then estimate uncertainties of the 30-year probability values for the next characteristic event obtained from three different models (Poisson, BPT, and BPT+ΔCFF) using a Monte Carlo procedure. The Gerede fault segment located at the eastern end of the Marmara region shows the highest 30-yr probability, with a Poisson value of 29%, and a time-dependent interaction probability of 48%. We find an aggregated 30-yr Poisson probability of M >7.3 earthquakes at Istanbul of 35%, which increases to 47% if time dependence and stress transfer are considered. We calculate a 2-fold probability gain (ratio time-dependent to time-independent) on the southern strands of the North Anatolian Fault Zone.

Time dependent emission line profiles in the radially streaming particle model of Seyfert galaxy nuclei and quasi-stellar objects

NASA Technical Reports Server (NTRS)

Hubbard, R.

1974-01-01

The radially-streaming particle model for broad quasar and Seyfert galaxy emission features is modified to include sources of time dependence. The results are suggestive of reported observations of multiple components, variability, and transient features in the wings of Seyfert and quasi-stellar emission lines.

Time-dependence of the electromechanical bending actuation observed in ionic-electroactive polymers

NASA Astrophysics Data System (ADS)

Bass, Patrick S.; Zhang, Lin; Cheng, Z.-Y.

The characteristics of the electromechanical response observed in an ionic-electroactive polymer (i-EAP) are represented by the time (t) dependence of its bending actuation (y). The electromechanical response of a typical i-EAP — poly(ethylene oxide) (PEO) doped with lithium perchlorate (LP) — is studied. The shortcomings of all existing models describing the electromechanical response obtained in i-EAPs are discussed. A more reasonable model: y=ymaxe-τ/t is introduced to characterize this time dependence for all i-EAPs. The advantages and correctness of this model are confirmed using results obtained in PEO-LP actuators with different LP contents and at different temperatures. The applicability and universality of this model are validated using the reported results obtained from two different i-EAPs: one is Flemion and the other is polypyrrole actuators.

SALSA3D: A Tomographic Model of Compressional Wave Slowness in the Earth’s Mantle for Improved Travel-Time Prediction and Travel-Time Prediction Uncertainty

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

Ballard, Sanford; Hipp, James R.; Begnaud, Michael L.

The task of monitoring the Earth for nuclear explosions relies heavily on seismic data to detect, locate, and characterize suspected nuclear tests. In this study, motivated by the need to locate suspected explosions as accurately and precisely as possible, we developed a tomographic model of the compressional wave slowness in the Earth’s mantle with primary focus on the accuracy and precision of travel-time predictions for P and Pn ray paths through the model. Path-dependent travel-time prediction uncertainties are obtained by computing the full 3D model covariance matrix and then integrating slowness variance and covariance along ray paths from source tomore » receiver. Path-dependent travel-time prediction uncertainties reflect the amount of seismic data that was used in tomography with very low values for paths represented by abundant data in the tomographic data set and very high values for paths through portions of the model that were poorly sampled by the tomography data set. The pattern of travel-time prediction uncertainty is a direct result of the off-diagonal terms of the model covariance matrix and underscores the importance of incorporating the full model covariance matrix in the determination of travel-time prediction uncertainty. In addition, the computed pattern of uncertainty differs significantly from that of 1D distance-dependent travel-time uncertainties computed using traditional methods, which are only appropriate for use with travel times computed through 1D velocity models.« less

SALSA3D: A Tomographic Model of Compressional Wave Slowness in the Earth’s Mantle for Improved Travel-Time Prediction and Travel-Time Prediction Uncertainty

DOE PAGES

Ballard, Sanford; Hipp, James R.; Begnaud, Michael L.; ...

2016-10-11

The task of monitoring the Earth for nuclear explosions relies heavily on seismic data to detect, locate, and characterize suspected nuclear tests. In this study, motivated by the need to locate suspected explosions as accurately and precisely as possible, we developed a tomographic model of the compressional wave slowness in the Earth’s mantle with primary focus on the accuracy and precision of travel-time predictions for P and Pn ray paths through the model. Path-dependent travel-time prediction uncertainties are obtained by computing the full 3D model covariance matrix and then integrating slowness variance and covariance along ray paths from source tomore » receiver. Path-dependent travel-time prediction uncertainties reflect the amount of seismic data that was used in tomography with very low values for paths represented by abundant data in the tomographic data set and very high values for paths through portions of the model that were poorly sampled by the tomography data set. The pattern of travel-time prediction uncertainty is a direct result of the off-diagonal terms of the model covariance matrix and underscores the importance of incorporating the full model covariance matrix in the determination of travel-time prediction uncertainty. In addition, the computed pattern of uncertainty differs significantly from that of 1D distance-dependent travel-time uncertainties computed using traditional methods, which are only appropriate for use with travel times computed through 1D velocity models.« less

Multi-state model for studying an intermediate event using time-dependent covariates: application to breast cancer.

PubMed

Meier-Hirmer, Carolina; Schumacher, Martin

2013-06-20

The aim of this article is to propose several methods that allow to investigate how and whether the shape of the hazard ratio after an intermediate event depends on the waiting time to occurrence of this event and/or the sojourn time in this state. A simple multi-state model, the illness-death model, is used as a framework to investigate the occurrence of this intermediate event. Several approaches are shown and their advantages and disadvantages are discussed. All these approaches are based on Cox regression. As different time-scales are used, these models go beyond Markov models. Different estimation methods for the transition hazards are presented. Additionally, time-varying covariates are included into the model using an approach based on fractional polynomials. The different methods of this article are then applied to a dataset consisting of four studies conducted by the German Breast Cancer Study Group (GBSG). The occurrence of the first isolated locoregional recurrence (ILRR) is studied. The results contribute to the debate on the role of the ILRR with respect to the course of the breast cancer disease and the resulting prognosis. We have investigated different modelling strategies for the transition hazard after ILRR or in general after an intermediate event. Including time-dependent structures altered the resulting hazard functions considerably and it was shown that this time-dependent structure has to be taken into account in the case of our breast cancer dataset. The results indicate that an early recurrence increases the risk of death. A late ILRR increases the hazard function much less and after the successful removal of the second tumour the risk of death is almost the same as before the recurrence. With respect to distant disease, the appearance of the ILRR only slightly increases the risk of death if the recurrence was treated successfully. It is important to realize that there are several modelling strategies for the intermediate event and that each of these strategies has restrictions and may lead to different results. Especially in the medical literature considering breast cancer development, the time-dependency is often neglected in the statistical analyses. We show that the time-varying variables cannot be neglected in the case of ILRR and that fractional polynomials are a useful tool for finding the functional form of these time-varying variables.

ALCHEMIC: Advanced time-dependent chemical kinetics

NASA Astrophysics Data System (ADS)

Semenov, Dmitry A.

2017-08-01

ALCHEMIC solves chemical kinetics problems, including gas-grain interactions, surface reactions, deuterium fractionization, and transport phenomena and can model the time-dependent chemical evolution of molecular clouds, hot cores, corinos, and protoplanetary disks.

Additive mixed effect model for recurrent gap time data.

PubMed

Ding, Jieli; Sun, Liuquan

2017-04-01

Gap times between recurrent events are often of primary interest in medical and observational studies. The additive hazards model, focusing on risk differences rather than risk ratios, has been widely used in practice. However, the marginal additive hazards model does not take the dependence among gap times into account. In this paper, we propose an additive mixed effect model to analyze gap time data, and the proposed model includes a subject-specific random effect to account for the dependence among the gap times. Estimating equation approaches are developed for parameter estimation, and the asymptotic properties of the resulting estimators are established. In addition, some graphical and numerical procedures are presented for model checking. The finite sample behavior of the proposed methods is evaluated through simulation studies, and an application to a data set from a clinic study on chronic granulomatous disease is provided.

Seismic hazard assessment over time: Modelling earthquakes in Taiwan

NASA Astrophysics Data System (ADS)

Chan, Chung-Han; Wang, Yu; Wang, Yu-Ju; Lee, Ya-Ting

2017-04-01

To assess the seismic hazard with temporal change in Taiwan, we develop a new approach, combining both the Brownian Passage Time (BPT) model and the Coulomb stress change, and implement the seismogenic source parameters by the Taiwan Earthquake Model (TEM). The BPT model was adopted to describe the rupture recurrence intervals of the specific fault sources, together with the time elapsed since the last fault-rupture to derive their long-term rupture probability. We also evaluate the short-term seismicity rate change based on the static Coulomb stress interaction between seismogenic sources. By considering above time-dependent factors, our new combined model suggests an increased long-term seismic hazard in the vicinity of active faults along the western Coastal Plain and the Longitudinal Valley, where active faults have short recurrence intervals and long elapsed time since their last ruptures, and/or short-term elevated hazard levels right after the occurrence of large earthquakes due to the stress triggering effect. The stress enhanced by the February 6th, 2016, Meinong ML 6.6 earthquake also significantly increased rupture probabilities of several neighbouring seismogenic sources in Southwestern Taiwan and raised hazard level in the near future. Our approach draws on the advantage of incorporating long- and short-term models, to provide time-dependent earthquake probability constraints. Our time-dependent model considers more detailed information than any other published models. It thus offers decision-makers and public officials an adequate basis for rapid evaluations of and response to future emergency scenarios such as victim relocation and sheltering.

Transcriptional dynamics with time-dependent reaction rates

NASA Astrophysics Data System (ADS)

Nandi, Shubhendu; Ghosh, Anandamohan

2015-02-01

Transcription is the first step in the process of gene regulation that controls cell response to varying environmental conditions. Transcription is a stochastic process, involving synthesis and degradation of mRNAs, that can be modeled as a birth-death process. We consider a generic stochastic model, where the fluctuating environment is encoded in the time-dependent reaction rates. We obtain an exact analytical expression for the mRNA probability distribution and are able to analyze the response for arbitrary time-dependent protocols. Our analytical results and stochastic simulations confirm that the transcriptional machinery primarily act as a low-pass filter. We also show that depending on the system parameters, the mRNA levels in a cell population can show synchronous/asynchronous fluctuations and can deviate from Poisson statistics.

Finite element simulation of location- and time-dependent mechanical behavior of chondrocytes in unconfined compression tests.

PubMed

Wu, J Z; Herzog, W

2000-03-01

Experimental evidence suggests that cells are extremely sensitive to their mechanical environment and react directly to mechanical stimuli. At present, it is technically difficult to measure fluid pressure, stress, and strain in cells, and to determine the time-dependent deformation of chondrocytes. For this reason, there are no data in the published literature that show the dynamic behavior of chondrocytes in articular cartilage. Similarly, the dynamic chondrocyte mechanics have not been calculated using theoretical models that account for the influence of cell volumetric fraction on cartilage mechanical properties. In the present investigation, the location- and time-dependent stress-strain state and fluid pressure distribution in chondrocytes in unconfined compression tests were simulated numerically using a finite element method. The technique involved two basic steps: first, cartilage was approximated as a macroscopically homogenized material and the mechanical behavior of cartilage was obtained using the homogenized model; second, the solution of the time-dependent displacements and fluid pressure fields of the homogenized model was used as the time-dependent boundary conditions for a microscopic submodel to obtain average location- and time-dependent mechanical behavior of cells. Cells and extracellular matrix were assumed to be biphasic materials composed of a fluid phase and a hyperelastic solid phase. The hydraulic permeability was assumed to be deformation dependent and the analysis was performed using a finite deformation approach. Numerical tests were made using configurations similar to those of experiments described in the literature. Our simulations show that the mechanical response of chondrocytes to cartilage loading depends on time, fluid boundary conditions, and the locations of the cells within the specimen. The present results are the first to suggest that chondrocyte deformation in a stress-relaxation type test may exceed the imposed system deformation by a factor of 3-4, that chondrocyte deformations are highly dynamic and do not reach a steady state within about 20 min of steady compression (in an unconfined test), and that cell deformations are very much location dependent.

Regression analysis using dependent Polya trees.

PubMed

Schörgendorfer, Angela; Branscum, Adam J

2013-11-30

Many commonly used models for linear regression analysis force overly simplistic shape and scale constraints on the residual structure of data. We propose a semiparametric Bayesian model for regression analysis that produces data-driven inference by using a new type of dependent Polya tree prior to model arbitrary residual distributions that are allowed to evolve across increasing levels of an ordinal covariate (e.g., time, in repeated measurement studies). By modeling residual distributions at consecutive covariate levels or time points using separate, but dependent Polya tree priors, distributional information is pooled while allowing for broad pliability to accommodate many types of changing residual distributions. We can use the proposed dependent residual structure in a wide range of regression settings, including fixed-effects and mixed-effects linear and nonlinear models for cross-sectional, prospective, and repeated measurement data. A simulation study illustrates the flexibility of our novel semiparametric regression model to accurately capture evolving residual distributions. In an application to immune development data on immunoglobulin G antibodies in children, our new model outperforms several contemporary semiparametric regression models based on a predictive model selection criterion. Copyright © 2013 John Wiley & Sons, Ltd.

Empirical analysis and modeling of manual turnpike tollbooths in China

NASA Astrophysics Data System (ADS)

Zhang, Hao

2017-03-01

To deal with low-level of service satisfaction at tollbooths of many turnpikes in China, we conduct an empirical study and use a queueing model to investigate performance measures. In this paper, we collect archived data from six tollbooths of a turnpike in China. Empirical analysis on vehicle's time-dependent arrival process and collector's time-dependent service time is conducted. It shows that the vehicle arrival process follows a non-homogeneous Poisson process while the collector service time follows a log-normal distribution. Further, we model the process of collecting tolls at tollbooths with MAP / PH / 1 / FCFS queue for mathematical tractability and present some numerical examples.

Time-Dependent Traveling Wave Tube Model for Intersymbol Interference Investigations

NASA Technical Reports Server (NTRS)

Kory, Carol L.; Andro, Monty; Downey, Alan (Technical Monitor)

2001-01-01

For the first time, a computational model has been used to provide a direct description of the effects of the traveling wave tube (TWT) on modulated digital signals. The TWT model comprehensively takes into account the effects of frequency dependent AM/AM and AM/PM conversion, gain and phase ripple; drive-induced oscillations; harmonic generation; intermodulation products; and backward waves. Thus, signal integrity can be investigated in the presence of these sources of potential distortion as a function of the physical geometry of the high power amplifier and the operational digital signal. This method promises superior predictive fidelity compared to methods using TWT models based on swept-amplitude and/or swept-frequency data. The fully three-dimensional (3D), time-dependent, TWT interaction model using the electromagnetic code MAFIA is presented. This model is used to investigate assumptions made in TWT black-box models used in communication system level simulations. In addition, digital signal performance, including intersymbol interference (ISI), is compared using direct data input into the MAFIA model and using the system level analysis tool, SPW.

Intersymbol Interference Investigations Using a 3D Time-Dependent Traveling Wave Tube Model

NASA Technical Reports Server (NTRS)

Kory, Carol L.; Andro, Monty; Downey, Alan (Technical Monitor)

2001-01-01

For the first time, a physics based computational model has been used to provide a direct description of the effects of the TWT (Traveling Wave Tube) on modulated digital signals. The TWT model comprehensively takes into account the effects of frequency dependent AM/AM and AM/PM conversion; gain and phase ripple; drive-induced oscillations; harmonic generation; intermodulation products; and backward waves. Thus, signal integrity can be investigated in the presence of these sources of potential distortion as a function of the physical geometry of the high power amplifier and the operational digital signal. This method promises superior predictive fidelity compared to methods using TWT models based on swept amplitude and/or swept frequency data. The fully three-dimensional (3D), time-dependent, TWT interaction model using the electromagnetic code MAFIA is presented. This model is used to investigate assumptions made in TWT black box models used in communication system level simulations. In addition, digital signal performance, including intersymbol interference (ISI), is compared using direct data input into the MAFIA model and using the system level analysis tool, SPW (Signal Processing Worksystem).

Measurement and modeling of diffusion time dependence of apparent diffusion coefficient and fractional anisotropy in prostate tissue ex vivo.

PubMed

Bourne, Roger; Liang, Sisi; Panagiotaki, Eleftheria; Bongers, Andre; Sved, Paul; Watson, Geoffrey

2017-10-01

The purpose of this study was to measure and model the diffusion time dependence of apparent diffusion coefficient (ADC) and fractional anisotropy (FA) derived from conventional prostate diffusion-weighted imaging methods as used in recommended multiparametric MRI protocols. Diffusion tensor imaging (DTI) was performed at 9.4 T with three radical prostatectomy specimens, with diffusion times in the range 10-120 ms and b-values 0-3000 s/mm 2 . ADC and FA were calculated from DTI measurements at b-values of 800 and 1600 s/mm 2 . Independently, a two-component model (restricted isotropic plus Gaussian anisotropic) was used to synthesize DTI data, from which ADC and FA were predicted and compared with the measured values. Measured ADC and FA exhibited a diffusion time dependence, which was closely predicted by the two-component model. ADC decreased by about 0.10-0.15 μm 2 /ms as diffusion time increased from 10 to 120 ms. FA increased with diffusion time at b-values of 800 and 1600 s/mm 2 but was predicted to be independent of diffusion time at b = 3000 s/mm 2 . Both ADC and FA exhibited diffusion time dependence that could be modeled as two unmixed water pools - one having isotropic restricted dynamics, and the other unrestricted anisotropic dynamics. These results highlight the importance of considering and reporting diffusion times in conventional ADC and FA calculations and protocol recommendations, and inform the development of improved diffusion methods for prostate cancer imaging. Copyright © 2017 John Wiley & Sons, Ltd.

Two-dimensional time-dependent modelling of fume formation in a pulsed gas metal arc welding process

NASA Astrophysics Data System (ADS)

Boselli, M.; Colombo, V.; Ghedini, E.; Gherardi, M.; Sanibondi, P.

2013-06-01

Fume formation in a pulsed gas metal arc welding (GMAW) process is investigated by coupling a time-dependent axi-symmetric two-dimensional model, which takes into account both droplet detachment and production of metal vapour, with a model for fume formation and transport based on the method of moments for the solution of the aerosol general dynamic equation. We report simulative results of a pulsed process (peak current = 350 A, background current 30 A, period = 9 ms) for a 1 mm diameter iron wire, with Ar shielding gas. Results showed that metal vapour production occurs mainly at the wire tip, whereas fume formation is concentrated in the fringes of the arc in the spatial region close to the workpiece, where metal vapours are transported by convection. The proposed modelling approach allows time-dependent tracking of fumes also in plasma processes where temperature-time variations occur faster than nanoparticle transport from the nucleation region to the surrounding atmosphere, as is the case for most pulsed GMAW processes.

Time-dependent quantum oscillator as attenuator and amplifier: noise and statistical evolutions

NASA Astrophysics Data System (ADS)

Portes, D.; Rodrigues, H.; Duarte, S. B.; Baseia, B.

2004-10-01

We revisit the quantum oscillator, modelled as a time-dependent LC-circuit. Nonclassical properties concerned with attenuation and amplification regions are considered, as well as time evolution of quantum noise and statistics, with emphasis on revivals of the statistical distribution.

Predicting the dynamics of bacterial growth inhibition by ribosome-targeting antibiotics

NASA Astrophysics Data System (ADS)

Greulich, Philip; Doležal, Jakub; Scott, Matthew; Evans, Martin R.; Allen, Rosalind J.

2017-12-01

Understanding how antibiotics inhibit bacteria can help to reduce antibiotic use and hence avoid antimicrobial resistance—yet few theoretical models exist for bacterial growth inhibition by a clinically relevant antibiotic treatment regimen. In particular, in the clinic, antibiotic treatment is time-dependent. Here, we use a theoretical model, previously applied to steady-state bacterial growth, to predict the dynamical response of a bacterial cell to a time-dependent dose of ribosome-targeting antibiotic. Our results depend strongly on whether the antibiotic shows reversible transport and/or low-affinity ribosome binding (‘low-affinity antibiotic’) or, in contrast, irreversible transport and/or high affinity ribosome binding (‘high-affinity antibiotic’). For low-affinity antibiotics, our model predicts that growth inhibition depends on the duration of the antibiotic pulse, and can show a transient period of very fast growth following removal of the antibiotic. For high-affinity antibiotics, growth inhibition depends on peak dosage rather than dose duration, and the model predicts a pronounced post-antibiotic effect, due to hysteresis, in which growth can be suppressed for long times after the antibiotic dose has ended. These predictions are experimentally testable and may be of clinical significance.

Predicting the dynamics of bacterial growth inhibition by ribosome-targeting antibiotics

PubMed Central

Greulich, Philip; Doležal, Jakub; Scott, Matthew; Evans, Martin R; Allen, Rosalind J

2017-01-01

Understanding how antibiotics inhibit bacteria can help to reduce antibiotic use and hence avoid antimicrobial resistance—yet few theoretical models exist for bacterial growth inhibition by a clinically relevant antibiotic treatment regimen. In particular, in the clinic, antibiotic treatment is time-dependent. Here, we use a theoretical model, previously applied to steady-state bacterial growth, to predict the dynamical response of a bacterial cell to a time-dependent dose of ribosome-targeting antibiotic. Our results depend strongly on whether the antibiotic shows reversible transport and/or low-affinity ribosome binding (‘low-affinity antibiotic’) or, in contrast, irreversible transport and/or high affinity ribosome binding (‘high-affinity antibiotic’). For low-affinity antibiotics, our model predicts that growth inhibition depends on the duration of the antibiotic pulse, and can show a transient period of very fast growth following removal of the antibiotic. For high-affinity antibiotics, growth inhibition depends on peak dosage rather than dose duration, and the model predicts a pronounced post-antibiotic effect, due to hysteresis, in which growth can be suppressed for long times after the antibiotic dose has ended. These predictions are experimentally testable and may be of clinical significance. PMID:28714461

User's manual for the time-dependent INERTIA code

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

Bailey, A.W.; Bennett, R.B.

1985-01-01

The time-dependent INERTIA code is described. This code models the effects of neutral beam momentum input in tokamaks as predicted by the time-dependent formulation of the Stacey-Sigmar formalism. The operation and architecture of the code are described, as are the supplementary plotting and impurity line radiation routines. A short description of the steady-state version of the INERTIA code is also provided.

Solvable two-dimensional time-dependent non-Hermitian quantum systems with infinite dimensional Hilbert space in the broken PT-regime

NASA Astrophysics Data System (ADS)

Fring, Andreas; Frith, Thomas

2018-06-01

We provide exact analytical solutions for a two-dimensional explicitly time-dependent non-Hermitian quantum system. While the time-independent variant of the model studied is in the broken PT-symmetric phase for the entire range of the model parameters, and has therefore a partially complex energy eigenspectrum, its time-dependent version has real energy expectation values at all times. In our solution procedure we compare the two equivalent approaches of directly solving the time-dependent Dyson equation with one employing the Lewis–Riesenfeld method of invariants. We conclude that the latter approach simplifies the solution procedure due to the fact that the invariants of the non-Hermitian and Hermitian system are related to each other in a pseudo-Hermitian fashion, which in turn does not hold for their corresponding time-dependent Hamiltonians. Thus constructing invariants and subsequently using the pseudo-Hermiticity relation between them allows to compute the Dyson map and to solve the Dyson equation indirectly. In this way one can bypass to solve nonlinear differential equations, such as the dissipative Ermakov–Pinney equation emerging in our and many other systems.

Temperature-Dependent Kinetic Prediction for Reactions Described by Isothermal Mathematics

DOE PAGES

Dinh, L. N.; Sun, T. C.; McLean, W.

2016-09-12

Most kinetic models are expressed in isothermal mathematics. In addition, this may lead unaware scientists either to the misconception that classical isothermal kinetic models cannot be used for any chemical process in an environment with a time-dependent temperature profile or, even worse, to a misuse of them. In reality, classical isothermal models can be employed to make kinetic predictions for reactions in environments with time-dependent temperature profiles, provided that there is a continuity/conservation in the reaction extent at every temperature–time step. In this article, fundamental analyses, illustrations, guiding tables, and examples are given to help the interested readers using eithermore » conventional isothermal reacted fraction curves or rate equations to make proper kinetic predictions for chemical reactions in environments with temperature profiles that vary, even arbitrarily, with time simply by the requirement of continuity/conservation of reaction extent whenever there is an external temperature change.« less

Three-dimensional fully-coupled electrical and thermal transport model of dynamic switching in oxide memristors

DOE PAGES

Gao, Xujiao; Mamaluy, Denis; Mickel, Patrick R.; ...

2015-09-08

In this paper, we present a fully-coupled electrical and thermal transport model for oxide memristors that solves simultaneously the time-dependent continuity equations for all relevant carriers, together with the time-dependent heat equation including Joule heating sources. The model captures all the important processes that drive memristive switching and is applicable to simulate switching behavior in a wide range of oxide memristors. The model is applied to simulate the ON switching in a 3D filamentary TaOx memristor. Simulation results show that, for uniform vacancy density in the OFF state, vacancies fill in the conduction filament till saturation, and then fill outmore » a gap formed in the Ta electrode during ON switching; furthermore, ON-switching time strongly depends on applied voltage and the ON-to-OFF current ratio is sensitive to the filament vacancy density in the OFF state.« less

The roles of time and displacement in velocity-dependent volumetric strain of fault zones

USGS Publications Warehouse

Beeler, N.M.; Tullis, T.E.

1997-01-01

The relationship between measured friction??A and volumetric strain during frictional sliding was determined using a rate and state variable dependent friction constitutive equation, a common work balance relating friction and volume change, and two types of experimental faults: initially bare surfaces of Westerly granite and rock surfaces separated by a 1 mm layer of < 90 ??m Westerly granite gouge. The constitutive equation is the sum of a constant term representing the nominal resistance to sliding and two smaller terms: a rate dependent term representing the shear viscosity of the fault surface (direct effect), and a term which represents variations in the area of contact (evolution effect). The work balance relationship requires that ??A differs from the frictional resistance that leads to shear heating by the derivative of fault normal displacement with respect shear displacement, d??n ld??s. An implication of this relationship is that the rate dependence of d??n ld??s contributes to the rate dependence of ??A. Experiments show changes in sliding velocity lead to changes in both fault strength and volume. Analysis of data with the rate and state equations combined with the work balance relationship preclude the conventional interpretation of the direct effect in the rate and state variable constitutive equations. Consideration of a model bare surface fault consisting of an undeformable indentor sliding on a deformable surface reveals a serious flaw in the work balance relationship if volume change is time-dependent. For the model, at zero slip rate indentation creep under the normal load leads to time-dependent strengthening of the fault surface but, according to the work balance relationship, no work is done because compaction or dilatancy can only be induced by shearing. Additional tests on initially bare surfaces and gouges show that fault normal strain in experiments is time-dependent, consistent with the model. This time-dependent fault normal strain, which is not accounted for in the work balance relationship, explains the inconsistency between the constitutive equations and the work balance. For initially bare surface faults, all rate dependence of volume change is due to time dependence. Similar results are found for gouge. We conclude that ??A reflects the frictional resistance that results in shear heating, and no correction needs to be made for the volume changes. The result that time-dependent volume changes do not contribute to ??A is a general result and extends beyond these experiments, the simple indentor model and particular constitutive equations used to illustrate the principle.

A two-dimensional, time-dependent model of suspended sediment transport and bed reworking for continental shelves

USGS Publications Warehouse

Harris, C.K.; Wiberg, P.L.

2001-01-01

A two-dimensional, time-dependent solution to the transport equation is formulated to account for advection and diffusion of sediment suspended in the bottom boundary layer of continental shelves. This model utilizes a semi-implicit, upwind-differencing scheme to solve the advection-diffusion equation across a two-dimensional transect that is configured so that one dimension is the vertical, and the other is a horizontal dimension usually aligned perpendicular to shelf bathymetry. The model calculates suspended sediment concentration and flux; and requires as input wave properties, current velocities, sediment size distributions, and hydrodynamic sediment properties. From the calculated two-dimensional suspended sediment fluxes, we quantify the redistribution of shelf sediment, bed erosion, and deposition for several sediment sizes during resuspension events. The two-dimensional, time-dependent approach directly accounts for cross-shelf gradients in bed shear stress and sediment properties, as well as transport that occurs before steady-state suspended sediment concentrations have been attained. By including the vertical dimension in the calculations, we avoid depth-averaging suspended sediment concentrations and fluxes, and directly account for differences in transport rates and directions for fine and coarse sediment in the bottom boundary layer. A flux condition is used as the bottom boundary condition for the transport equation in order to capture time-dependence of the suspended sediment field. Model calculations demonstrate the significance of both time-dependent and spatial terms on transport and depositional patterns on continental shelves. ?? 2001 Elsevier Science Ltd. All rights reserved.

High-resolution time-frequency representation of EEG data using multi-scale wavelets

NASA Astrophysics Data System (ADS)

Li, Yang; Cui, Wei-Gang; Luo, Mei-Lin; Li, Ke; Wang, Lina

2017-09-01

An efficient time-varying autoregressive (TVAR) modelling scheme that expands the time-varying parameters onto the multi-scale wavelet basis functions is presented for modelling nonstationary signals and with applications to time-frequency analysis (TFA) of electroencephalogram (EEG) signals. In the new parametric modelling framework, the time-dependent parameters of the TVAR model are locally represented by using a novel multi-scale wavelet decomposition scheme, which can allow the capability to capture the smooth trends as well as track the abrupt changes of time-varying parameters simultaneously. A forward orthogonal least square (FOLS) algorithm aided by mutual information criteria are then applied for sparse model term selection and parameter estimation. Two simulation examples illustrate that the performance of the proposed multi-scale wavelet basis functions outperforms the only single-scale wavelet basis functions or Kalman filter algorithm for many nonstationary processes. Furthermore, an application of the proposed method to a real EEG signal demonstrates the new approach can provide highly time-dependent spectral resolution capability.

MIMICKING COUNTERFACTUAL OUTCOMES TO ESTIMATE CAUSAL EFFECTS.

PubMed

Lok, Judith J

2017-04-01

In observational studies, treatment may be adapted to covariates at several times without a fixed protocol, in continuous time. Treatment influences covariates, which influence treatment, which influences covariates, and so on. Then even time-dependent Cox-models cannot be used to estimate the net treatment effect. Structural nested models have been applied in this setting. Structural nested models are based on counterfactuals: the outcome a person would have had had treatment been withheld after a certain time. Previous work on continuous-time structural nested models assumes that counterfactuals depend deterministically on observed data, while conjecturing that this assumption can be relaxed. This article proves that one can mimic counterfactuals by constructing random variables, solutions to a differential equation, that have the same distribution as the counterfactuals, even given past observed data. These "mimicking" variables can be used to estimate the parameters of structural nested models without assuming the treatment effect to be deterministic.

A constitutive material model for nonlinear finite element structural analysis using an iterative matrix approach

NASA Technical Reports Server (NTRS)

Koenig, Herbert A.; Chan, Kwai S.; Cassenti, Brice N.; Weber, Richard

1988-01-01

A unified numerical method for the integration of stiff time dependent constitutive equations is presented. The solution process is directly applied to a constitutive model proposed by Bodner. The theory confronts time dependent inelastic behavior coupled with both isotropic hardening and directional hardening behaviors. Predicted stress-strain responses from this model are compared to experimental data from cyclic tests on uniaxial specimens. An algorithm is developed for the efficient integration of the Bodner flow equation. A comparison is made with the Euler integration method. An analysis of computational time is presented for the three algorithms.

Missing Data Imputation versus Full Information Maximum Likelihood with Second-Level Dependencies

ERIC Educational Resources Information Center

Larsen, Ross

2011-01-01

Missing data in the presence of upper level dependencies in multilevel models have never been thoroughly examined. Whereas first-level subjects are independent over time, the second-level subjects might exhibit nonzero covariances over time. This study compares 2 missing data techniques in the presence of a second-level dependency: multiple…

Reply to the Discussion of Space-Time Modelling with Long-Memory Dependence: Assessing Ireland’s Wind Resource

DTIC Science & Technology

1988-10-01

meteorologists’ rule-of-thumb that climatic drift manifests itself in periods greater than 30 years. For a fractionally-differenced model with our...estimates in a univariate ARIMA (p, d, q) with I d I< 0.5 has been derived by Li and McLrjd (1986). The model used by I-Iaslett an Raftery can be viewed as...Reply to the Discussion of "Space-time Modelling with Long-mnmory cDependence: Assessing Ireland’s Wind Resource" cJohn Haslett Department of

Time-dependent magnetohydrodynamic simulations of the inner heliosphere

NASA Astrophysics Data System (ADS)

Merkin, V. G.; Lyon, J. G.; Lario, D.; Arge, C. N.; Henney, C. J.

2016-04-01

This paper presents results from a simulation study exploring heliospheric consequences of time-dependent changes at the Sun. We selected a 2 month period in the beginning of year 2008 that was characterized by very low solar activity. The heliosphere in the equatorial region was dominated by two coronal holes whose changing structure created temporal variations distorting the classical steady state picture of the heliosphere. We used the Air Force Data Assimilate Photospheric Flux Transport (ADAPT) model to obtain daily updated photospheric magnetograms and drive the Wang-Sheeley-Arge (WSA) model of the corona. This leads to a formulation of a time-dependent boundary condition for our three-dimensional (3-D) magnetohydrodynamic (MHD) model, LFM-helio, which is the heliospheric adaptation of the Lyon-Fedder-Mobarry MHD simulation code. The time-dependent coronal conditions were propagated throughout the inner heliosphere, and the simulation results were compared with the spacecraft located near 1 astronomical unit (AU) heliocentric distance: Advanced Composition Explorer (ACE), Solar Terrestrial Relations Observatory (STEREO-A and STEREO-B), and the MErcury Surface, Space ENvironment, GEochemistry, and Ranging (MESSENGER) spacecraft that was in cruise phase measuring the heliospheric magnetic field between 0.35 and 0.6 AU. In addition, during the selected interval MESSENGER and ACE aligned radially allowing minimization of the effects of temporal variation at the Sun versus radial evolution of structures. Our simulations show that time-dependent simulationsreproduce the gross-scale structure of the heliosphere with higher fidelity, while on smaller spatial and faster time scales (e.g., 1 day) they provide important insights for interpretation of the data. The simulations suggest that moving boundaries of slow-fast wind transitions at 0.1 AU may result in the formation of inverted magnetic fields near pseudostreamers which is an intrinsically time-dependent process. Finally, we show that heliospheric current sheet corrugation, which may result in multiple sector boundary crossings when observed by spacecraft, is caused by solar wind velocity shears. Overall, our simulations demonstrate that time-dependent heliosphere modeling is a promising direction of research both for space weather applications and fundamental physics of the heliosphere.

Extreme Unconditional Dependence Vs. Multivariate GARCH Effect in the Analysis of Dependence Between High Losses on Polish and German Stock Indexes

NASA Astrophysics Data System (ADS)

Rokita, Pawel

Classical portfolio diversification methods do not take account of any dependence between extreme returns (losses). Many researchers provide, however, some empirical evidence for various assets that extreme-losses co-occur. If the co-occurrence is frequent enough to be statistically significant, it may seriously influence portfolio risk. Such effects may result from a few different properties of financial time series, like for instance: (1) extreme dependence in a (long-term) unconditional distribution, (2) extreme dependence in subsequent conditional distributions, (3) time-varying conditional covariance, (4) time-varying (long-term) unconditional covariance, (5) market contagion. Moreover, a mix of these properties may be present in return time series. Modeling each of them requires different approaches. It seams reasonable to investigate whether distinguishing between the properties is highly significant for portfolio risk measurement. If it is, identifying the effect responsible for high loss co-occurrence would be of a great importance. If it is not, the best solution would be selecting the easiest-to-apply model. This article concentrates on two of the aforementioned properties: extreme dependence (in a long-term unconditional distribution) and time-varying conditional covariance.

Oscillating in synchrony with a metronome: serial dependence, limit cycle dynamics, and modeling.

PubMed

Torre, Kjerstin; Balasubramaniam, Ramesh; Delignières, Didier

2010-07-01

We analyzed serial dependencies in periods and asynchronies collected during oscillations performed in synchrony with a metronome. Results showed that asynchronies contain 1/f fluctuations, and the series of periods contain antipersistent dependence. The analysis of the phase portrait revealed a specific asymmetry induced by synchronization. We propose a hybrid limit cycle model including a cycle-dependent stiffness parameter provided with fractal properties, and a parametric driving function based on velocity. This model accounts for most experimentally evidenced statistical features, including serial dependence and limit cycle dynamics. We discuss the results and modeling choices within the framework of event-based and emergent timing.

A flexible cure rate model with dependent censoring and a known cure threshold.

PubMed

Bernhardt, Paul W

2016-11-10

We propose a flexible cure rate model that accommodates different censoring distributions for the cured and uncured groups and also allows for some individuals to be observed as cured when their survival time exceeds a known threshold. We model the survival times for the uncured group using an accelerated failure time model with errors distributed according to the seminonparametric distribution, potentially truncated at a known threshold. We suggest a straightforward extension of the usual expectation-maximization algorithm approach for obtaining estimates in cure rate models to accommodate the cure threshold and dependent censoring. We additionally suggest a likelihood ratio test for testing for the presence of dependent censoring in the proposed cure rate model. We show through numerical studies that our model has desirable properties and leads to approximately unbiased parameter estimates in a variety of scenarios. To demonstrate how our method performs in practice, we analyze data from a bone marrow transplantation study and a liver transplant study. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Physiologic volume of phosphorus during hemodialysis: predictions from a pseudo one-compartment model.

PubMed

Leypoldt, John K; Akonur, Alp; Agar, Baris U; Culleton, Bruce F

2012-10-01

The kinetics of plasma phosphorus concentrations during hemodialysis (HD) are complex and cannot be described by conventional one- or two-compartment kinetic models. It has recently been shown by others that the physiologic (or apparent distribution) volume for phosphorus (Vr-P) increases with increasing treatment time and shows a large variation among patients treated by thrice weekly and daily HD. Here, we describe the dependence of Vr-P on treatment time and predialysis plasma phosphorus concentration as predicted by a novel pseudo one-compartment model. The kinetics of plasma phosphorus during conventional and six times per week daily HD were simulated as a function of treatment time per session for various dialyzer phosphate clearances and patient-specific phosphorus mobilization clearances (K(M)). Vr-P normalized to extracellular volume from these simulations were reported and compared with previously published empirical findings. Simulated results were relatively independent of dialyzer phosphate clearance and treatment frequency. In contrast, Vr-P was strongly dependent on treatment time per session; the increase in Vr-P with treatment time was larger for higher values of K(M). Vr-P was inversely dependent on predialysis plasma phosphorus concentration. There was significant variation among predicted Vr-P values, depending largely on the value of K(M). We conclude that a pseudo one-compartment model can describe the empirical dependence of the physiologic volume of phosphorus on treatment time and predialysis plasma phosphorus concentration. Further, the variation in physiologic volume of phosphorus among HD patients is largely due to differences in patient-specific phosphorus mobilization clearance. © 2012 The Authors. Hemodialysis International © 2012 International Society for Hemodialysis.

A combined experimental atomic force microscopy-based nanoindentation and computational modeling approach to unravel the key contributors to the time-dependent mechanical behavior of single cells.

PubMed

Florea, Cristina; Tanska, Petri; Mononen, Mika E; Qu, Chengjuan; Lammi, Mikko J; Laasanen, Mikko S; Korhonen, Rami K

2017-02-01

Cellular responses to mechanical stimuli are influenced by the mechanical properties of cells and the surrounding tissue matrix. Cells exhibit viscoelastic behavior in response to an applied stress. This has been attributed to fluid flow-dependent and flow-independent mechanisms. However, the particular mechanism that controls the local time-dependent behavior of cells is unknown. Here, a combined approach of experimental AFM nanoindentation with computational modeling is proposed, taking into account complex material behavior. Three constitutive models (porohyperelastic, viscohyperelastic, poroviscohyperelastic) in tandem with optimization algorithms were employed to capture the experimental stress relaxation data of chondrocytes at 5 % strain. The poroviscohyperelastic models with and without fluid flow allowed through the cell membrane provided excellent description of the experimental time-dependent cell responses (normalized mean squared error (NMSE) of 0.003 between the model and experiments). The viscohyperelastic model without fluid could not follow the entire experimental data that well (NMSE = 0.005), while the porohyperelastic model could not capture it at all (NMSE = 0.383). We also show by parametric analysis that the fluid flow has a small, but essential effect on the loading phase and short-term cell relaxation response, while the solid viscoelasticity controls the longer-term responses. We suggest that the local time-dependent cell mechanical response is determined by the combined effects of intrinsic viscoelasticity of the cytoskeleton and fluid flow redistribution in the cells, although the contribution of fluid flow is smaller when using a nanosized probe and moderate indentation rate. The present approach provides new insights into viscoelastic responses of chondrocytes, important for further understanding cell mechanobiological mechanisms in health and disease.

Uniform California earthquake rupture forecast, version 2 (UCERF 2)

USGS Publications Warehouse

Field, E.H.; Dawson, T.E.; Felzer, K.R.; Frankel, A.D.; Gupta, V.; Jordan, T.H.; Parsons, T.; Petersen, M.D.; Stein, R.S.; Weldon, R.J.; Wills, C.J.

2009-01-01

The 2007 Working Group on California Earthquake Probabilities (WGCEP, 2007) presents the Uniform California Earthquake Rupture Forecast, Version 2 (UCERF 2). This model comprises a time-independent (Poisson-process) earthquake rate model, developed jointly with the National Seismic Hazard Mapping Program and a time-dependent earthquake-probability model, based on recent earthquake rates and stress-renewal statistics conditioned on the date of last event. The models were developed from updated statewide earthquake catalogs and fault deformation databases using a uniform methodology across all regions and implemented in the modular, extensible Open Seismic Hazard Analysis framework. The rate model satisfies integrating measures of deformation across the plate-boundary zone and is consistent with historical seismicity data. An overprediction of earthquake rates found at intermediate magnitudes (6.5 ??? M ???7.0) in previous models has been reduced to within the 95% confidence bounds of the historical earthquake catalog. A logic tree with 480 branches represents the epistemic uncertainties of the full time-dependent model. The mean UCERF 2 time-dependent probability of one or more M ???6.7 earthquakes in the California region during the next 30 yr is 99.7%; this probability decreases to 46% for M ???7.5 and to 4.5% for M ???8.0. These probabilities do not include the Cascadia subduction zone, largely north of California, for which the estimated 30 yr, M ???8.0 time-dependent probability is 10%. The M ???6.7 probabilities on major strike-slip faults are consistent with the WGCEP (2003) study in the San Francisco Bay Area and the WGCEP (1995) study in southern California, except for significantly lower estimates along the San Jacinto and Elsinore faults, owing to provisions for larger multisegment ruptures. Important model limitations are discussed.

Petri net-based dependability modeling methodology for reconfigurable field programmable gate arrays

NASA Astrophysics Data System (ADS)

Graczyk, Rafał; Orleański, Piotr; Poźniak, Krzysztof

2015-09-01

Dependability modeling is an important issue for aerospace and space equipment designers. From system level perspective, one has to choose from multitude of possible architectures, redundancy levels, component combinations in a way to meet desired properties and dependability and finally fit within required cost and time budgets. Modeling of such systems is getting harder as its levels of complexity grow together with demand for more functional and flexible, yet more available systems that govern more and more crucial parts of our civilization's infrastructure (aerospace transport systems, telecommunications, exploration probes). In this article promising method of modeling complex systems using Petri networks is introduced in context of qualitative and quantitative dependability analysis. This method, although with some limitation and drawback offer still convenient visual formal method of describing system behavior on different levels (functional, timing, random events) and offers straight correspondence to underlying mathematical engine, perfect for simulations and engineering support.

Modified creep and shrinkage prediction model B3 for serviceability limit state analysis of composite slabs

NASA Astrophysics Data System (ADS)

Gholamhoseini, Alireza

2016-03-01

Relatively little research has been reported on the time-dependent in-service behavior of composite concrete slabs with profiled steel decking as permanent formwork and little guidance is available for calculating long-term deflections. The drying shrinkage profile through the thickness of a composite slab is greatly affected by the impermeable steel deck at the slab soffit, and this has only recently been quantified. This paper presents the results of long-term laboratory tests on composite slabs subjected to both drying shrinkage and sustained loads. Based on laboratory measurements, a design model for the shrinkage strain profile through the thickness of a slab is proposed. The design model is based on some modifications to an existing creep and shrinkage prediction model B3. In addition, an analytical model is developed to calculate the time-dependent deflection of composite slabs taking into account the time-dependent effects of creep and shrinkage. The calculated deflections are shown to be in good agreement with the experimental measurements.

Revisiting gamma-ray burst afterglows with time-dependent parameters

NASA Astrophysics Data System (ADS)

Yang, Chao; Zou, Yuan-Chuan; Chen, Wei; Liao, Bin; Lei, Wei-Hua; Liu, Yu

2018-02-01

The relativistic external shock model of gamma-ray burst (GRB) afterglows has been established with five free parameters, i.e., the total kinetic energy E, the equipartition parameters for electrons {{ε }}{{e}} and for the magnetic field {{ε }}{{B}}, the number density of the environment n and the index of the power-law distribution of shocked electrons p. A lot of modified models have been constructed to consider the variety of GRB afterglows, such as: the wind medium environment by letting n change with radius, the energy injection model by letting kinetic energy change with time and so on. In this paper, by assuming all four parameters (except p) change with time, we obtain a set of formulas for the dynamics and radiation, which can be used as a reference for modeling GRB afterglows. Some interesting results are obtained. For example, in some spectral segments, the radiated flux density does not depend on the number density or the profile of the environment. As an application, through modeling the afterglow of GRB 060607A, we find that it can be interpreted in the framework of the time dependent parameter model within a reasonable range.

A multi-scale cardiovascular system model can account for the load-dependence of the end-systolic pressure-volume relationship

PubMed Central

2013-01-01

Background The end-systolic pressure-volume relationship is often considered as a load-independent property of the heart and, for this reason, is widely used as an index of ventricular contractility. However, many criticisms have been expressed against this index and the underlying time-varying elastance theory: first, it does not consider the phenomena underlying contraction and second, the end-systolic pressure volume relationship has been experimentally shown to be load-dependent. Methods In place of the time-varying elastance theory, a microscopic model of sarcomere contraction is used to infer the pressure generated by the contraction of the left ventricle, considered as a spherical assembling of sarcomere units. The left ventricle model is inserted into a closed-loop model of the cardiovascular system. Finally, parameters of the modified cardiovascular system model are identified to reproduce the hemodynamics of a normal dog. Results Experiments that have proven the limitations of the time-varying elastance theory are reproduced with our model: (1) preload reductions, (2) afterload increases, (3) the same experiments with increased ventricular contractility, (4) isovolumic contractions and (5) flow-clamps. All experiments simulated with the model generate different end-systolic pressure-volume relationships, showing that this relationship is actually load-dependent. Furthermore, we show that the results of our simulations are in good agreement with experiments. Conclusions We implemented a multi-scale model of the cardiovascular system, in which ventricular contraction is described by a detailed sarcomere model. Using this model, we successfully reproduced a number of experiments that have shown the failing points of the time-varying elastance theory. In particular, the developed multi-scale model of the cardiovascular system can capture the load-dependence of the end-systolic pressure-volume relationship. PMID:23363818

A new method for calculating time-dependent atomic level populations

NASA Technical Reports Server (NTRS)

Kastner, S. O.

1981-01-01

A method is described for reducing the number of levels to be dealt with in calculating time-dependent populations of atoms or ions in plasmas. The procedure effectively extends the collisional-radiative model to consecutive stages of ionization, treating ground and metastable levels explicitly and excited levels implicitly. Direct comparisons of full and simulated systems are carried out for five-level models.

Development of constitutive model for composites exhibiting time dependent properties

NASA Astrophysics Data System (ADS)

Pupure, L.; Joffe, R.; Varna, J.; Nyström, B.

2013-12-01

Regenerated cellulose fibres and their composites exhibit highly nonlinear behaviour. The mechanical response of these materials can be successfully described by the model developed by Schapery for time-dependent materials. However, this model requires input parameters that are experimentally determined via large number of time-consuming tests on the studied composite material. If, for example, the volume fraction of fibres is changed we have a different material and new series of experiments on this new material are required. Therefore the ultimate objective of our studies is to develop model which determines the composite behaviour based on behaviour of constituents of the composite. This paper gives an overview of problems and difficulties, associated with development, implementation and verification of such model.

A statistical analysis of the daily streamflow hydrograph

NASA Astrophysics Data System (ADS)

Kavvas, M. L.; Delleur, J. W.

1984-03-01

In this study a periodic statistical analysis of daily streamflow data in Indiana, U.S.A., was performed to gain some new insight into the stochastic structure which describes the daily streamflow process. This analysis was performed by the periodic mean and covariance functions of the daily streamflows, by the time and peak discharge -dependent recession limb of the daily streamflow hydrograph, by the time and discharge exceedance level (DEL) -dependent probability distribution of the hydrograph peak interarrival time, and by the time-dependent probability distribution of the time to peak discharge. Some new statistical estimators were developed and used in this study. In general features, this study has shown that: (a) the persistence properties of daily flows depend on the storage state of the basin at the specified time origin of the flow process; (b) the daily streamflow process is time irreversible; (c) the probability distribution of the daily hydrograph peak interarrival time depends both on the occurrence time of the peak from which the inter-arrival time originates and on the discharge exceedance level; and (d) if the daily streamflow process is modeled as the release from a linear watershed storage, this release should depend on the state of the storage and on the time of the release as the persistence properties and the recession limb decay rates were observed to change with the state of the watershed storage and time. Therefore, a time-varying reservoir system needs to be considered if the daily streamflow process is to be modeled as the release from a linear watershed storage.

A finite nonlinear hyper-viscoelastic model for soft biological tissues.

PubMed

Panda, Satish Kumar; Buist, Martin Lindsay

2018-03-01

Soft tissues exhibit highly nonlinear rate and time-dependent stress-strain behaviour. Strain and strain rate dependencies are often modelled using a hyperelastic model and a discrete (standard linear solid) or continuous spectrum (quasi-linear) viscoelastic model, respectively. However, these models are unable to properly capture the materials characteristics because hyperelastic models are unsuited for time-dependent events, whereas the common viscoelastic models are insufficient for the nonlinear and finite strain viscoelastic tissue responses. The convolution integral based models can demonstrate a finite viscoelastic response; however, their derivations are not consistent with the laws of thermodynamics. The aim of this work was to develop a three-dimensional finite hyper-viscoelastic model for soft tissues using a thermodynamically consistent approach. In addition, a nonlinear function, dependent on strain and strain rate, was adopted to capture the nonlinear variation of viscosity during a loading process. To demonstrate the efficacy and versatility of this approach, the model was used to recreate the experimental results performed on different types of soft tissues. In all the cases, the simulation results were well matched (R 2 ⩾0.99) with the experimental data. Copyright © 2018 Elsevier Ltd. All rights reserved.

Time dependent pre-treatment EPID dosimetry for standard and FFF VMAT.

PubMed

Podesta, Mark; Nijsten, Sebastiaan M J J G; Persoon, Lucas C G G; Scheib, Stefan G; Baltes, Christof; Verhaegen, Frank

2014-08-21

Methods to calibrate Megavoltage electronic portal imaging devices (EPIDs) for dosimetry have been previously documented for dynamic treatments such as intensity modulated radiotherapy (IMRT) using flattened beams and typically using integrated fields. While these methods verify the accumulated field shape and dose, the dose rate and differential fields remain unverified. The aim of this work is to provide an accurate calibration model for time dependent pre-treatment dose verification using amorphous silicon (a-Si) EPIDs in volumetric modulated arc therapy (VMAT) for both flattened and flattening filter free (FFF) beams. A general calibration model was created using a Varian TrueBeam accelerator, equipped with an aS1000 EPID, for each photon spectrum 6 MV, 10 MV, 6 MV-FFF, 10 MV-FFF. As planned VMAT treatments use control points (CPs) for optimization, measured images are separated into corresponding time intervals for direct comparison with predictions. The accuracy of the calibration model was determined for a range of treatment conditions. Measured and predicted CP dose images were compared using a time dependent gamma evaluation using criteria (3%, 3 mm, 0.5 sec). Time dependent pre-treatment dose verification is possible without an additional measurement device or phantom, using the on-board EPID. Sufficient data is present in trajectory log files and EPID frame headers to reliably synchronize and resample portal images. For the VMAT plans tested, significantly more deviation is observed when analysed in a time dependent manner for FFF and non-FFF plans than when analysed using only the integrated field. We show EPID-based pre-treatment dose verification can be performed on a CP basis for VMAT plans. This model can measure pre-treatment doses for both flattened and unflattened beams in a time dependent manner which highlights deviations that are missed in integrated field verifications.

Developing and Validating Path-Dependent Uncertainty Estimates for use with the Regional Seismic Travel Time (RSTT) Model

NASA Astrophysics Data System (ADS)

Begnaud, M. L.; Anderson, D. N.; Phillips, W. S.; Myers, S. C.; Ballard, S.

2016-12-01

The Regional Seismic Travel Time (RSTT) tomography model has been developed to improve travel time predictions for regional phases (Pn, Sn, Pg, Lg) in order to increase seismic location accuracy, especially for explosion monitoring. The RSTT model is specifically designed to exploit regional phases for location, especially when combined with teleseismic arrivals. The latest RSTT model (version 201404um) has been released (http://www.sandia.gov/rstt). Travel time uncertainty estimates for RSTT are determined using one-dimensional (1D), distance-dependent error models, that have the benefit of being very fast to use in standard location algorithms, but do not account for path-dependent variations in error, and structural inadequacy of the RSTTT model (e.g., model error). Although global in extent, the RSTT tomography model is only defined in areas where data exist. A simple 1D error model does not accurately model areas where RSTT has not been calibrated. We are developing and validating a new error model for RSTT phase arrivals by mathematically deriving this multivariate model directly from a unified model of RSTT embedded into a statistical random effects model that captures distance, path and model error effects. An initial method developed is a two-dimensional path-distributed method using residuals. The goals for any RSTT uncertainty method are for it to be both readily useful for the standard RSTT user as well as improve travel time uncertainty estimates for location. We have successfully tested using the new error model for Pn phases and will demonstrate the method and validation of the error model for Sn, Pg, and Lg phases.

KvN mechanics approach to the time-dependent frequency harmonic oscillator.

PubMed

Ramos-Prieto, Irán; Urzúa-Pineda, Alejandro R; Soto-Eguibar, Francisco; Moya-Cessa, Héctor M

2018-05-30

Using the Ermakov-Lewis invariants appearing in KvN mechanics, the time-dependent frequency harmonic oscillator is studied. The analysis builds upon the operational dynamical model, from which it is possible to infer quantum or classical dynamics; thus, the mathematical structure governing the evolution will be the same in both cases. The Liouville operator associated with the time-dependent frequency harmonic oscillator can be transformed using an Ermakov-Lewis invariant, which is also time dependent and commutes with itself at any time. Finally, because the solution of the Ermakov equation is involved in the evolution of the classical state vector, we explore some analytical and numerical solutions.

Rationale choosing interval of a piecewise-constant approximation of input rate of non-stationary queue system

NASA Astrophysics Data System (ADS)

Korelin, Ivan A.; Porshnev, Sergey V.

2018-01-01

The paper demonstrates the possibility of calculating the characteristics of the flow of visitors to objects carrying out mass events passing through checkpoints. The mathematical model is based on the non-stationary queuing system (NQS) where dependence of requests input rate from time is described by the function. This function was chosen in such way that its properties were similar to the real dependencies of speed of visitors arrival on football matches to the stadium. A piecewise-constant approximation of the function is used when statistical modeling of NQS performing. Authors calculated the dependencies of the queue length and waiting time for visitors to service (time in queue) on time for different laws. Time required to service the entire queue and the number of visitors entering the stadium at the beginning of the match were calculated too. We found the dependence for macroscopic quantitative characteristics of NQS from the number of averaging sections of the input rate.

IMPLEMENTATION OF THE IMPROVED QUASI-STATIC METHOD IN RATTLESNAKE/MOOSE FOR TIME-DEPENDENT RADIATION TRANSPORT MODELLING

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

Zachary M. Prince; Jean C. Ragusa; Yaqi Wang

Because of the recent interest in reactor transient modeling and the restart of the Transient Reactor (TREAT) Facility, there has been a need for more efficient, robust methods in computation frameworks. This is the impetus of implementing the Improved Quasi-Static method (IQS) in the RATTLESNAKE/MOOSE framework. IQS has implemented with CFEM diffusion by factorizing flux into time-dependent amplitude and spacial- and weakly time-dependent shape. The shape evaluation is very similar to a flux diffusion solve and is computed at large (macro) time steps. While the amplitude evaluation is a PRKE solve where the parameters are dependent on the shape andmore » is computed at small (micro) time steps. IQS has been tested with a custom one-dimensional example and the TWIGL ramp benchmark. These examples prove it to be a viable and effective method for highly transient cases. More complex cases are intended to be applied to further test the method and its implementation.« less

Ultrafast dynamic response of single-crystal β-HMX (octahydro-1,3,5,7-tetranitro-1,3,5,7-tetrazocine)

NASA Astrophysics Data System (ADS)

Zaug, Joseph M.; Austin, Ryan A.; Armstrong, Michael R.; Crowhurst, Jonathan C.; Goldman, Nir; Ferranti, Louis; Saw, Cheng K.; Swan, Raymond A.; Gross, Richard; Fried, Laurence E.

2018-05-01

We report experimental and computational studies of shock wave dynamics in single-crystal β-HMX on an ultrafast time scale. Here, a laser-based compression drive (˜1 ns in duration; stresses of up to ˜40 GPa) is used to propagate shock waves normal to the (110) and (010) lattice planes. Ultrafast time-domain interferometry measurements reveal distinct, time-dependent relationships between the shock wave velocity and particle velocity for each crystal orientation, which suggest evolving physical processes on a sub-nanosecond time scale. To help interpret the experimental data, elastic shock wave response was simulated using a finite-strain model of crystal thermoelasticity. At early propagation times (<500 ps), the model is in agreement with the data, which indicates that the mechanical response is dominated by thermoelastic deformation. The model agreement depends on the inclusion of nonlinear elastic effects in both the spherical and deviatoric stress-strain responses. This is achieved by employing an equation-of-state and a pressure-dependent stiffness tensor, which was computed via atomistic simulation. At later times (>500 ps), the crystal samples exhibit signatures of inelastic deformation, structural phase transformation, or chemical reaction, depending on the direction of wave propagation.

A Sandwich-Type Standard Error Estimator of SEM Models with Multivariate Time Series

ERIC Educational Resources Information Center

Zhang, Guangjian; Chow, Sy-Miin; Ong, Anthony D.

2011-01-01

Structural equation models are increasingly used as a modeling tool for multivariate time series data in the social and behavioral sciences. Standard error estimators of SEM models, originally developed for independent data, require modifications to accommodate the fact that time series data are inherently dependent. In this article, we extend a…

Multi-spacecraft testing of time-dependent interplanetary MHD models for operational forecasting of geomagnetic storms

NASA Technical Reports Server (NTRS)

Dryer, M.; Smith, Z. K.

1989-01-01

An MHD 2-1/2D, time-dependent model is used, together with observations of six solar flares during February 3-7, 1986, to demonstrate global, large-scale, compound disturbances in the solar wind over a wide range of heliolongitudes. This scenario is one that is likely to occur many times during the cruise, possibly even encounter, phases of the Multi-Comet Mission. It is suggested that a model such as this one should be tested with multi-spacecraft data (such as the MCM and earth-based probes) with several goals in view: (1) utility of the model for operational real-time forecasting of geomagnetic storms, and (2) scientific interpretation of certain forms of cometary activities and their possible association with solar-generated activity.

Cosmic Ray Hysteresis as Evidence for Time-dependent Diffusive Processes in the Long Term Solar Modulation

NASA Technical Reports Server (NTRS)

Ogallagher, J. J.

1973-01-01

A simple one-dimensional time-dependent diffusion-convection model for the modulation of cosmic rays is presented. This model predicts that the observed intensity at a given time is approximately equal to the intensity given by the time independent diffusion convection solution under interplanetary conditions which existed a time iota in the past, (U(t sub o) = U sub s(t sub o - tau)) where iota is the average time spent by a particle inside the modulating cavity. Delay times in excess of several hundred days are possible with reasonable modulation parameters. Interpretation of phase lags observed during the 1969 to 1970 solar maximum in terms of this model suggests that the modulating region is probably not less than 10 a.u. and maybe as much as 35 a.u. in extent.

Landau problem with time dependent mass in time dependent electric and harmonic background fields

NASA Astrophysics Data System (ADS)

Lawson, Latévi M.; Avossevou, Gabriel Y. H.

2018-04-01

The spectrum of a Hamiltonian describing the dynamics of a Landau particle with time-dependent mass and frequency undergoing the influence of a uniform time-dependent electric field is obtained. The configuration space wave function of the model is expressed in terms of the generalised Laguerre polynomials. To diagonalize the time-dependent Hamiltonian, we employ the Lewis-Riesenfeld method of invariants. To this end, we introduce a unitary transformation in the framework of the algebraic formalism to construct the invariant operator of the system and then to obtain the exact solution of the Hamiltonian. We recover the solutions of the ordinary Landau problem in the absence of the electric and harmonic fields for a constant particle mass.

Indoor Residence Times of Semivolatile Organic Compounds: Model Estimation and Field Evaluation

EPA Science Inventory

Indoor residence times of semivolatile organic compounds (SVOCs) are a major and mostly unavailable input for residential exposure assessment. We calculated residence times for a suite of SVOCs using a fugacity model applied to residential environments. Residence times depend on...

Time-dependent efficacy of longitudinal biomarker for clinical endpoint.

PubMed

Kolamunnage-Dona, Ruwanthi; Williamson, Paula R

2018-06-01

Joint modelling of longitudinal biomarker and event-time processes has gained its popularity in recent years as they yield more accurate and precise estimates. Considering this modelling framework, a new methodology for evaluating the time-dependent efficacy of a longitudinal biomarker for clinical endpoint is proposed in this article. In particular, the proposed model assesses how well longitudinally repeated measurements of a biomarker over various time periods (0,t) distinguish between individuals who developed the disease by time t and individuals who remain disease-free beyond time t. The receiver operating characteristic curve is used to provide the corresponding efficacy summaries at various t based on the association between longitudinal biomarker trajectory and risk of clinical endpoint prior to each time point. The model also allows detecting the time period over which a biomarker should be monitored for its best discriminatory value. The proposed approach is evaluated through simulation and illustrated on the motivating dataset from a prospective observational study of biomarkers to diagnose the onset of sepsis.

Black holes from large N singlet models

NASA Astrophysics Data System (ADS)

Amado, Irene; Sundborg, Bo; Thorlacius, Larus; Wintergerst, Nico

2018-03-01

The emergent nature of spacetime geometry and black holes can be directly probed in simple holographic duals of higher spin gravity and tensionless string theory. To this end, we study time dependent thermal correlation functions of gauge invariant observables in suitably chosen free large N gauge theories. At low temperature and on short time scales the correlation functions encode propagation through an approximate AdS spacetime while interesting departures emerge at high temperature and on longer time scales. This includes the existence of evanescent modes and the exponential decay of time dependent boundary correlations, both of which are well known indicators of bulk black holes in AdS/CFT. In addition, a new time scale emerges after which the correlation functions return to a bulk thermal AdS form up to an overall temperature dependent normalization. A corresponding length scale was seen in equal time correlation functions in the same models in our earlier work.

Scale Dependence of Statistics of Spatially Averaged Rain Rate Seen in TOGA COARE Comparison with Predictions from a Stochastic Model

NASA Technical Reports Server (NTRS)

Kundu, Prasun K.; Bell, T. L.; Lau, William K. M. (Technical Monitor)

2002-01-01

A characteristic feature of rainfall statistics is that they in general depend on the space and time scales over which rain data are averaged. As a part of an earlier effort to determine the sampling error of satellite rain averages, a space-time model of rainfall statistics was developed to describe the statistics of gridded rain observed in GATE. The model allows one to compute the second moment statistics of space- and time-averaged rain rate which can be fitted to satellite or rain gauge data to determine the four model parameters appearing in the precipitation spectrum - an overall strength parameter, a characteristic length separating the long and short wavelength regimes and a characteristic relaxation time for decay of the autocorrelation of the instantaneous local rain rate and a certain 'fractal' power law exponent. For area-averaged instantaneous rain rate, this exponent governs the power law dependence of these statistics on the averaging length scale $L$ predicted by the model in the limit of small $L$. In particular, the variance of rain rate averaged over an $L \\times L$ area exhibits a power law singularity as $L \\rightarrow 0$. In the present work the model is used to investigate how the statistics of area-averaged rain rate over the tropical Western Pacific measured with ship borne radar during TOGA COARE (Tropical Ocean Global Atmosphere Coupled Ocean Atmospheric Response Experiment) and gridded on a 2 km grid depends on the size of the spatial averaging scale. Good agreement is found between the data and predictions from the model over a wide range of averaging length scales.

Wave-vector and polarization dependent impedance model for a hexagonal periodic metasurface exemplified through finite-difference time-domain simulations.

PubMed

Ding, Yi S; He, Yang

2017-08-21

An isotropic impedance sheet model is proposed for a loop-type hexagonal periodic metasurface. Both frequency and wave-vector dispersion are considered near the resonance frequency. Therefore both the angle and polarization dependences of the metasurface impedance can be properly and simultaneously described in our model. The constitutive relation of this model is transformed into auxiliary differential equations which are integrated into the finite-difference time-domain algorithm. Finally, a finite large metasurface sample under oblique illumination is used to test the model and the algorithm. Our model and algorithm can significantly increase the accuracy of the homogenization methods for modeling periodic metasurfaces.

Halo Intrinsic Alignment: Dependence on Mass, Formation Time, and Environment

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

Xia, Qianli; Kang, Xi; Wang, Peng

In this paper we use high-resolution cosmological simulations to study halo intrinsic alignment and its dependence on mass, formation time, and large-scale environment. In agreement with previous studies using N -body simulations, it is found that massive halos have stronger alignment. For the first time, we find that for a given halo mass older halos have stronger alignment and halos in cluster regions also have stronger alignment than those in filaments. To model these dependencies, we extend the linear alignment model with inclusion of halo bias and find that the halo alignment with its mass and formation time dependence canmore » be explained by halo bias. However, the model cannot account for the environment dependence, as it is found that halo bias is lower in clusters and higher in filaments. Our results suggest that halo bias and environment are independent factors in determining halo alignment. We also study the halo alignment correlation function and find that halos are strongly clustered along their major axes and less clustered along the minor axes. The correlated halo alignment can extend to scales as large as 100 h {sup −1} Mpc, where its feature is mainly driven by the baryon acoustic oscillation effect.« less

Linearized blade row compression component model. Stability and frequency response analysis of a J85-3 compressor

NASA Technical Reports Server (NTRS)

Tesch, W. A.; Moszee, R. H.; Steenken, W. G.

1976-01-01

NASA developed stability and frequency response analysis techniques were applied to a dynamic blade row compression component stability model to provide a more economic approach to surge line and frequency response determination than that provided by time-dependent methods. This blade row model was linearized and the Jacobian matrix was formed. The clean-inlet-flow stability characteristics of the compressors of two J85-13 engines were predicted by applying the alternate Routh-Hurwitz stability criterion to the Jacobian matrix. The predicted surge line agreed with the clean-inlet-flow surge line predicted by the time-dependent method to a high degree except for one engine at 94% corrected speed. No satisfactory explanation of this discrepancy was found. The frequency response of the linearized system was determined by evaluating its Laplace transfer function. The results of the linearized-frequency-response analysis agree with the time-dependent results when the time-dependent inlet total-pressure and exit-flow function amplitude boundary conditions are less than 1 percent and 3 percent, respectively. The stability analysis technique was extended to a two-sector parallel compressor model with and without interstage crossflow and predictions were carried out for total-pressure distortion extents of 180 deg, 90 deg, 60 deg, and 30 deg.

A three-dimensional spin-diffusion model for micromagnetics

PubMed Central

Abert, Claas; Ruggeri, Michele; Bruckner, Florian; Vogler, Christoph; Hrkac, Gino; Praetorius, Dirk; Suess, Dieter

2015-01-01

We solve a time-dependent three-dimensional spin-diffusion model coupled to the Landau-Lifshitz-Gilbert equation numerically. The presented model is validated by comparison to two established spin-torque models: The model of Slonzewski that describes spin-torque in multi-layer structures in the presence of a fixed layer and the model of Zhang and Li that describes current driven domain-wall motion. It is shown that both models are incorporated by the spin-diffusion description, i.e., the nonlocal effects of the Slonzewski model are captured as well as the spin-accumulation due to magnetization gradients as described by the model of Zhang and Li. Moreover, the presented method is able to resolve the time dependency of the spin-accumulation. PMID:26442796

Time dependent behavior of a graphite/thermoplastic composite and the effects of stress and physical aging

NASA Technical Reports Server (NTRS)

Gates, Thomas S.; Feldman, Mark

1993-01-01

Two complimentary studies were performed to determine the effects of stress and physical aging on the matrix dominated time dependent properties of IM7/8320 composite. The first of these studies, experimental in nature, used isothermal tensile creep/aging test techniques developed for polymers and adapted them for testing of the composite material. From these tests, the time dependent transverse (S22) and shear (S66) compliance's for an orthotropic plate were found from short term creep compliance measurements at constant, sub-T(sub g) temperatures. These compliance terms were shown to be affected by physical aging. Aging time shift factors and shift rates were found to be a function of temperature and applied stress. The second part of the study relied upon isothermal uniaxial tension tests of IM7/8320 to determine the effects of physical aging on the nonlinear material behavior at elevated temperature. An elastic/viscoplastic constitutive model was used to quantify the effects of aging on the rate-independent plastic and rate-dependent viscoplastic response. Sensitivity of the material constants required by the model to aging time were determined for aging times up to 65 hours. Verification of the analytical model indicated that the effects of prior aging on the nonlinear stress/strain/time data of matrix dominated laminates can be predicted.

Nonadiabatic Dynamics for Electrons at Second-Order: Real-Time TDDFT and OSCF2.

PubMed

Nguyen, Triet S; Parkhill, John

2015-07-14

We develop a new model to simulate nonradiative relaxation and dephasing by combining real-time Hartree-Fock and density functional theory (DFT) with our recent open-systems theory of electronic dynamics. The approach has some key advantages: it has been systematically derived and properly relaxes noninteracting electrons to a Fermi-Dirac distribution. This paper combines the new dissipation theory with an atomistic, all-electron quantum chemistry code and an atom-centered model of the thermal environment. The environment is represented nonempirically and is dependent on molecular structure in a nonlocal way. A production quality, O(N(3)) closed-shell implementation of our theory applicable to realistic molecular systems is presented, including timing information. This scaling implies that the added cost of our nonadiabatic relaxation model, time-dependent open self-consistent field at second order (OSCF2), is computationally inexpensive, relative to adiabatic propagation of real-time time-dependent Hartree-Fock (TDHF) or time-dependent density functional theory (TDDFT). Details of the implementation and numerical algorithm, including factorization and efficiency, are discussed. We demonstrate that OSCF2 approaches the stationary self-consistent field (SCF) ground state when the gap is large relative to k(b)T. The code is used to calculate linear-response spectra including the effects of bath dynamics. Finally, we show how our theory of finite-temperature relaxation can be used to correct ground-state DFT calculations.

Estimating economic gains for landowners due to time-dependent changes in biotechnology

Treesearch

John E. Wagner; Thomas P. Holmes

1998-01-01

This paper presents a model for examining the economic value of biotechnological research given time-dependent changes in biotechnology. Previous papers examined this issue assuming a time-neutral change in biotechnology. However, when analyzing the genetic improvements of increasing a tree's resistance to a pathogen, this assumption is untenable. The authors...

Dynamic regimes of local homogeneous population model with time lag

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

Neverova, Galina; Frisman, Efim

We investigated Moran - Ricker model with time lag 1. It is made analytical and numerical study of the model. It is shown there is co-existence of various dynamic regimes under the same values of parameters. The model simultaneously possesses several different limit regimes: stable state, periodic fluctuations, and chaotic attractor. The research results show if present population size substantially depends on population number of previous year then it is observed quasi-periodic oscillations. Fluctuations with period 2 occur when the growth of population size is regulated by density dependence in the current year.

Thermal mathematical modeling of a multicell common pressure vessel nickel-hydrogen battery

NASA Technical Reports Server (NTRS)

Kim, Junbom; Nguyen, T. V.; White, R. E.

1992-01-01

A two-dimensional and time-dependent thermal model of a multicell common pressure vessel (CPV) nickel-hydrogen battery was developed. A finite element solver called PDE/Protran was used to solve this model. The model was used to investigate the effects of various design parameters on the temperature profile within the cell. The results were used to help find a design that will yield an acceptable temperature gradient inside a multicell CPV nickel-hydrogen battery. Steady-state and unsteady-state cases with a constant heat generation rate and a time-dependent heat generation rate were solved.

Scalar and vector Keldysh models in the time domain

NASA Astrophysics Data System (ADS)

Kiselev, M. N.; Kikoin, K. A.

2009-04-01

The exactly solvable Keldysh model of disordered electron system in a random scattering field with extremely long correlation length is converted to the time-dependent model with extremely long relaxation. The dynamical problem is solved for the ensemble of two-level systems (TLS) with fluctuating well depths having the discrete Z 2 symmetry. It is shown also that the symmetric TLS with fluctuating barrier transparency may be described in terms of the vector Keldysh model with dime-dependent random planar rotations in xy plane having continuous SO(2) symmetry. Application of this model to description of dynamic fluctuations in quantum dots and optical lattices is discussed.

Motoneuron membrane potentials follow a time inhomogeneous jump diffusion process.

PubMed

Jahn, Patrick; Berg, Rune W; Hounsgaard, Jørn; Ditlevsen, Susanne

2011-11-01

Stochastic leaky integrate-and-fire models are popular due to their simplicity and statistical tractability. They have been widely applied to gain understanding of the underlying mechanisms for spike timing in neurons, and have served as building blocks for more elaborate models. Especially the Ornstein-Uhlenbeck process is popular to describe the stochastic fluctuations in the membrane potential of a neuron, but also other models like the square-root model or models with a non-linear drift are sometimes applied. Data that can be described by such models have to be stationary and thus, the simple models can only be applied over short time windows. However, experimental data show varying time constants, state dependent noise, a graded firing threshold and time-inhomogeneous input. In the present study we build a jump diffusion model that incorporates these features, and introduce a firing mechanism with a state dependent intensity. In addition, we suggest statistical methods to estimate all unknown quantities and apply these to analyze turtle motoneuron membrane potentials. Finally, simulated and real data are compared and discussed. We find that a square-root diffusion describes the data much better than an Ornstein-Uhlenbeck process with constant diffusion coefficient. Further, the membrane time constant decreases with increasing depolarization, as expected from the increase in synaptic conductance. The network activity, which the neuron is exposed to, can be reasonably estimated to be a threshold version of the nerve output from the network. Moreover, the spiking characteristics are well described by a Poisson spike train with an intensity depending exponentially on the membrane potential.

Bayesian explorations of fault slip evolution over the earthquake cycle

NASA Astrophysics Data System (ADS)

Duputel, Z.; Jolivet, R.; Benoit, A.; Gombert, B.

2017-12-01

The ever-increasing amount of geophysical data continuously opens new perspectives on fundamental aspects of the seismogenic behavior of active faults. In this context, the recent fleet of SAR satellites including Sentinel-1 and COSMO-SkyMED permits the use of InSAR for time-dependent slip modeling with unprecedented resolution in time and space. However, existing time-dependent slip models rely on spatial smoothing regularization schemes, which can produce unrealistically smooth slip distributions. In addition, these models usually do not include uncertainty estimates thereby reducing the utility of such estimates. Here, we develop an entirely new approach to derive probabilistic time-dependent slip models. This Markov-Chain Monte Carlo method involves a series of transitional steps to predict and update posterior Probability Density Functions (PDFs) of slip as a function of time. We assess the viability of our approach using various slow-slip event scenarios. Using a dense set of SAR images, we also use this method to quantify the spatial distribution and temporal evolution of slip along a creeping segment of the North Anatolian Fault. This allows us to track a shallow aseismic slip transient lasting for about a month with a maximum slip of about 2 cm.

Profile local linear estimation of generalized semiparametric regression model for longitudinal data.

PubMed

Sun, Yanqing; Sun, Liuquan; Zhou, Jie

2013-07-01

This paper studies the generalized semiparametric regression model for longitudinal data where the covariate effects are constant for some and time-varying for others. Different link functions can be used to allow more flexible modelling of longitudinal data. The nonparametric components of the model are estimated using a local linear estimating equation and the parametric components are estimated through a profile estimating function. The method automatically adjusts for heterogeneity of sampling times, allowing the sampling strategy to depend on the past sampling history as well as possibly time-dependent covariates without specifically model such dependence. A [Formula: see text]-fold cross-validation bandwidth selection is proposed as a working tool for locating an appropriate bandwidth. A criteria for selecting the link function is proposed to provide better fit of the data. Large sample properties of the proposed estimators are investigated. Large sample pointwise and simultaneous confidence intervals for the regression coefficients are constructed. Formal hypothesis testing procedures are proposed to check for the covariate effects and whether the effects are time-varying. A simulation study is conducted to examine the finite sample performances of the proposed estimation and hypothesis testing procedures. The methods are illustrated with a data example.

Quantifying and Mitigating the Effect of Preferential Sampling on Phylodynamic Inference

PubMed Central

Karcher, Michael D.; Palacios, Julia A.; Bedford, Trevor; Suchard, Marc A.; Minin, Vladimir N.

2016-01-01

Phylodynamics seeks to estimate effective population size fluctuations from molecular sequences of individuals sampled from a population of interest. One way to accomplish this task formulates an observed sequence data likelihood exploiting a coalescent model for the sampled individuals’ genealogy and then integrating over all possible genealogies via Monte Carlo or, less efficiently, by conditioning on one genealogy estimated from the sequence data. However, when analyzing sequences sampled serially through time, current methods implicitly assume either that sampling times are fixed deterministically by the data collection protocol or that their distribution does not depend on the size of the population. Through simulation, we first show that, when sampling times do probabilistically depend on effective population size, estimation methods may be systematically biased. To correct for this deficiency, we propose a new model that explicitly accounts for preferential sampling by modeling the sampling times as an inhomogeneous Poisson process dependent on effective population size. We demonstrate that in the presence of preferential sampling our new model not only reduces bias, but also improves estimation precision. Finally, we compare the performance of the currently used phylodynamic methods with our proposed model through clinically-relevant, seasonal human influenza examples. PMID:26938243

Watching excitons move: the time-dependent transition density matrix

NASA Astrophysics Data System (ADS)

Ullrich, Carsten

2012-02-01

Time-dependent density-functional theory allows one to calculate excitation energies and the associated transition densities in principle exactly. The transition density matrix (TDM) provides additional information on electron-hole localization and coherence of specific excitations of the many-body system. We have extended the TDM concept into the real-time domain in order to visualize the excited-state dynamics in conjugated molecules. The time-dependent TDM is defined as an implicit density functional, and can be approximately obtained from the time-dependent Kohn-Sham orbitals. The quality of this approximation is assessed in simple model systems. A computational scheme for real molecular systems is presented: the time-dependent Kohn-Sham equations are solved with the OCTOPUS code and the time-dependent Kohn-Sham TDM is calculated using a spatial partitioning scheme. The method is applied to show in real time how locally created electron-hole pairs spread out over neighboring conjugated molecular chains. The coupling mechanism, electron-hole coherence, and the possibility of charge separation are discussed.

Constitutive Theory Developed for Monolithic Ceramic Materials

NASA Technical Reports Server (NTRS)

Janosik, Lesley A.

1998-01-01

With the increasing use of advanced ceramic materials in high-temperature structural applications such as advanced heat engine components, the need arises to accurately predict thermomechanical behavior that is inherently time-dependent and that is hereditary in the sense that the current behavior depends not only on current conditions but also on the material's thermomechanical history. Most current analytical life prediction methods for both subcritical crack growth and creep models use elastic stress fields to predict the time-dependent reliability response of components subjected to elevated service temperatures. Inelastic response at high temperatures has been well documented in the materials science literature for these material systems, but this issue has been ignored by the engineering design community. From a design engineer's perspective, it is imperative to emphasize that accurate predictions of time-dependent reliability demand accurate stress field information. Ceramic materials exhibit different time-dependent behavior in tension and compression. Thus, inelastic deformation models for ceramics must be constructed in a fashion that admits both sensitivity to hydrostatic stress and differing behavior in tension and compression. A number of constitutive theories for materials that exhibit sensitivity to the hydrostatic component of stress have been proposed that characterize deformation using time-independent classical plasticity as a foundation. However, none of these theories allow different behavior in tension and compression. In addition, these theories are somewhat lacking in that they are unable to capture the creep, relaxation, and rate-sensitive phenomena exhibited by ceramic materials at high temperatures. The objective of this effort at the NASA Lewis Research Center has been to formulate a macroscopic continuum theory that captures these time-dependent phenomena. Specifically, the effort has focused on inelastic deformation behavior associated with these service conditions by developing a multiaxial viscoplastic constitutive model that accounts for time-dependent hereditary material deformation (such as creep and stress relaxation) in monolithic structural ceramics. Using continuum principles of engineering mechanics, we derived the complete viscoplastic theory from a scalar dissipative potential function.

Erosion and refilling of the plasmasphere during a geomagnetic storm modeled by a neural network

NASA Astrophysics Data System (ADS)

Chu, X. N.; Bortnik, J.; Li, W.; Ma, Q.; Angelopoulos, V.; Thorne, R. M.

2017-07-01

We present a history-dependent model of the equatorial plasma density of the inner magnetosphere using a feedforward neural network with two hidden layers. As the model inputs, we take locations and time series of SYM-H, AL, and F10.7 indices. By considering not only the instantaneous values but also the past values of geomagnetic and solar indices, the model is history dependent on levels of geomagnetic and solar activity. The modeled electron density is continuous both spatially and temporally so that the evolution of the density can be studied (such as plasmaspheric refilling). The model is trained using the electron density inferred from the spacecraft potential from three THEMIS probes. The equatorial electron density is shown to be accurately reconstructed with a correlation coefficient of r 0.953 between data and model target. Since the model is history dependent, it succeeds in reconstructing various density features and dynamic behaviors, such as the quiet time plasmasphere, erosion and recovery of the plasmasphere, as well as the plume formation during a storm on 4 February 2011. Our model may provide unprecedented insight into the behavior of the equatorial density at any time and location; as an example we show the inferred refilling rate from our model and compare it to previous estimates.

Measurements of Time-Dependent CP Asymmetries in b->s Penguin Dominated Hadronic B Decays at BABAR

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

Biassoni, Pietro

2010-02-10

We report measurements of Time-Dependent CP asymmetries in several b->s penguin dominated hadronic B decays, where New Physics contributions may appear. We find no significant discrepancies with respect to the Standard Model expectations.

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

Tom Elicson; Bentley Harwood; Jim Bouchard

Over a 12 month period, a fire PRA was developed for a DOE facility using the NUREG/CR-6850 EPRI/NRC fire PRA methodology. The fire PRA modeling included calculation of fire severity factors (SFs) and fire non-suppression probabilities (PNS) for each safe shutdown (SSD) component considered in the fire PRA model. The SFs were developed by performing detailed fire modeling through a combination of CFAST fire zone model calculations and Latin Hypercube Sampling (LHS). Component damage times and automatic fire suppression system actuation times calculated in the CFAST LHS analyses were then input to a time-dependent model of fire non-suppression probability. Themore » fire non-suppression probability model is based on the modeling approach outlined in NUREG/CR-6850 and is supplemented with plant specific data. This paper presents the methodology used in the DOE facility fire PRA for modeling fire-induced SSD component failures and includes discussions of modeling techniques for: • Development of time-dependent fire heat release rate profiles (required as input to CFAST), • Calculation of fire severity factors based on CFAST detailed fire modeling, and • Calculation of fire non-suppression probabilities.« less

Covariance Function for Nearshore Wave Assimilation Systems

DTIC Science & Technology

2018-01-30

covariance can be modeled by a parameterized Gaussian function, for nearshore wave assimilation applications, the covariance function depends primarily on...case of missing values at the compiled time series, the gaps were filled by weighted interpolation. The weights depend on the number of the...averaging, in order to create the continuous time series, filters out the dependency on the instantaneous meteorological and oceanographic conditions

An economic order quantity model with nonlinear holding cost, partial backlogging and ramp-type demand

NASA Astrophysics Data System (ADS)

San-José, Luis A.; Sicilia, Joaquín; González-de-la-Rosa, Manuel; Febles-Acosta, Jaime

2018-07-01

In this article, a deterministic inventory model with a ramp-type demand depending on price and time is developed. The cumulative holding cost is assumed to be a nonlinear function of time. Shortages are allowed and are partially backlogged. Thus, the fraction of backlogged demand depends on the waiting time and on the stock-out period. The aim is to maximize the total profit per unit time. To do this, a procedure that determines the economic lot size, the optimal inventory cycle and the maximum profit is presented. The inventory system studied here extends diverse inventory models proposed in the literature. Finally, some numerical examples are provided to illustrate the theoretical results previously propounded.

Brownian motion of electrons in time-dependent magnetic fields.

NASA Technical Reports Server (NTRS)

Iverson, G. J.; Williams, R. M.

1973-01-01

The behavior of a weakly ionized plasma in slowly varying time-dependent magnetic fields is studied through an extension of Williamson's stochastic theory. In particular, attention is focused on the properties of electron diffusion in the plane perpendicular to the direction of the magnetic field, when the field strength is large. It is shown that, in the strong field limit, the classical 1/B-squared dependence of the perpendicular diffusion coefficient is obtained for two models in which the field B(t) is monotonic in t and for two models in which B(t) possesses at least one turning point.

The effect of the magnetic nanoparticle's size dependence of the relaxation time constant on the specific loss power of magnetic nanoparticle hyperthermia

NASA Astrophysics Data System (ADS)

Harabech, Mariem; Leliaert, Jonathan; Coene, Annelies; Crevecoeur, Guillaume; Van Roost, Dirk; Dupré, Luc

2017-03-01

Magnetic nanoparticle hyperthermia is a cancer treatment in which magnetic nanoparticles (MNPs) are subjected to an alternating magnetic field to induce heat in the tumor. The generated heat of MNPs is characterized by the specific loss power (SLP) due to relaxation phenomena of the MNP. Up to now, several models have been proposed to predict the SLP, one of which is the Linear Response Theory. One parameter in this model is the relaxation time constant. In this contribution, we employ a macrospin model based on the Landau-Lifshitz-Gilbert equation to investigate the relation between the Gilbert damping parameter and the relaxation time constant. This relaxation time has a pre-factor τ0 which is often taken as a fixed value ranging between 10-8 and 10-12 s. However, in reality it has small size dependence. Here, the influence of this size dependence on the calculation of the SLP is demonstrated, consequently improving the accuracy of this estimate.

Detecting and modelling delayed density-dependence in abundance time series of a small mammal (Didelphis aurita)

NASA Astrophysics Data System (ADS)

Brigatti, E.; Vieira, M. V.; Kajin, M.; Almeida, P. J. A. L.; de Menezes, M. A.; Cerqueira, R.

2016-02-01

We study the population size time series of a Neotropical small mammal with the intent of detecting and modelling population regulation processes generated by density-dependent factors and their possible delayed effects. The application of analysis tools based on principles of statistical generality are nowadays a common practice for describing these phenomena, but, in general, they are more capable of generating clear diagnosis rather than granting valuable modelling. For this reason, in our approach, we detect the principal temporal structures on the bases of different correlation measures, and from these results we build an ad-hoc minimalist autoregressive model that incorporates the main drivers of the dynamics. Surprisingly our model is capable of reproducing very well the time patterns of the empirical series and, for the first time, clearly outlines the importance of the time of attaining sexual maturity as a central temporal scale for the dynamics of this species. In fact, an important advantage of this analysis scheme is that all the model parameters are directly biologically interpretable and potentially measurable, allowing a consistency check between model outputs and independent measurements.

Versatile time-dependent spatial distribution model of sun glint for satellite-based ocean imaging

NASA Astrophysics Data System (ADS)

Zhou, Guanhua; Xu, Wujian; Niu, Chunyue; Zhang, Kai; Ma, Zhongqi; Wang, Jiwen; Zhang, Yue

2017-01-01

We propose a versatile model to describe the time-dependent spatial distribution of sun glint areas in satellite-based wave water imaging. This model can be used to identify whether the imaging is affected by sun glint and how strong the glint is. The observing geometry is calculated using an accurate orbit prediction method. The Cox-Munk model is used to analyze the bidirectional reflectance of wave water surface under various conditions. The effects of whitecaps and the reflectance emerging from the sea water have been considered. Using the moderate resolution atmospheric transmission radiative transfer model, we are able to effectively calculate the sun glint distribution at the top of the atmosphere. By comparing the modeled data with the medium resolution imaging spectrometer image and Feng Yun 2E (FY-2E) image, we have proven that the time-dependent spatial distribution of sun glint areas can be effectively predicted. In addition, the main factors in determining sun glint distribution and the temporal variation rules of sun glint have been discussed. Our model can be used to design satellite orbits and should also be valuable in either eliminating sun glint or making use of it.

Intersymbol Interference Investigations Using a 3D Time-Dependent Traveling Wave Tube Model

NASA Technical Reports Server (NTRS)

Kory, Carol L.; Andro, Monty

2002-01-01

For the first time, a time-dependent, physics-based computational model has been used to provide a direct description of the effects of the traveling wave tube amplifier (TWTA) on modulated digital signals. The TWT model comprehensively takes into account the effects of frequency dependent AM/AM and AM/PM conversion; gain and phase ripple; drive-induced oscillations; harmonic generation; intermodulation products; and backward waves. Thus, signal integrity can be investigated in the presence of these sources of potential distortion as a function of the physical geometry and operating characteristics of the high power amplifier and the operational digital signal. This method promises superior predictive fidelity compared to methods using TWT models based on swept- amplitude and/or swept-frequency data. First, the TWT model using the three dimensional (3D) electromagnetic code MAFIA is presented. Then, this comprehensive model is used to investigate approximations made in conventional TWT black-box models used in communication system level simulations. To quantitatively demonstrate the effects these approximations have on digital signal performance predictions, including intersymbol interference (ISI), the MAFIA results are compared to the system level analysis tool, Signal Processing Workstation (SPW), using high order modulation schemes including 16 and 64-QAM.

Linking plate reconstructions with deforming lithosphere to geodynamic models

NASA Astrophysics Data System (ADS)

Müller, R. D.; Gurnis, M.; Flament, N.; Seton, M.; Spasojevic, S.; Williams, S.; Zahirovic, S.

2011-12-01

While global computational models are rapidly advancing in terms of their capabilities, there is an increasing need for assimilating observations into these models and/or ground-truthing model outputs. The open-source and platform independent GPlates software fills this gap. It was originally conceived as a tool to interactively visualize and manipulate classical rigid plate reconstructions and represent them as time-dependent topological networks of editable plate boundaries. The user can export time-dependent plate velocity meshes that can be used either to define initial surface boundary conditions for geodynamic models or alternatively impose plate motions throughout a geodynamic model run. However, tectonic plates are not rigid, and neglecting plate deformation, especially that of the edges of overriding plates, can result in significant misplacing of plate boundaries through time. A new, substantially re-engineered version of GPlates is now being developed that allows an embedding of deforming plates into topological plate boundary networks. We use geophysical and geological data to define the limit between rigid and deforming areas, and the deformation history of non-rigid blocks. The velocity field predicted by these reconstructions can then be used as a time-dependent surface boundary condition in regional or global 3-D geodynamic models, or alternatively as an initial boundary condition for a particular plate configuration at a given time. For time-dependent models with imposed plate motions (e.g. using CitcomS) we incorporate the continental lithosphere by embedding compositionally distinct crust and continental lithosphere within the thermal lithosphere. We define three isostatic columns of different thickness and buoyancy based on the tectonothermal age of the continents: Archean, Proterozoic and Phanerozoic. In the fourth isostatic column, the oceans, the thickness of the thermal lithosphere is assimilated using a half-space cooling model. We also define the thickness of the thermal lithosphere for different continental types, with the exception of the deforming areas that are fully dynamic. Finally, we introduce a "slab assimilation" method in which the thermal structure of the slab, derived analytically, is progressively assimilated into the upper mantle through time. This method not only improves the continuity of slabs in forward models with imposed plate motions, but it also allows us to model flat slab segments that are particularly relevant for understanding dynamic surface topography. When it comes to post-processing and visualisation, GPlates allows the user to import time-dependent model output image stacks to visualise mantle properties (e.g. temperature) at a given depth through time, with plate boundaries and other data attached to plates overlain. This approach provides an avenue to simultaneously investigate the contributions of lithospheric deformation and mantle flow to surface topography. Currently GPlates is being used in conjunction with the codes CitcomS, Terra, BEMEarth and the adaptive mesh refinement code Rhea. A GPlates python plugin infrastructure makes it easy to extend interoperability with other geodynamic modelling codes.

Time-dependent jet flow and noise computations

NASA Technical Reports Server (NTRS)

Berman, C. H.; Ramos, J. I.; Karniadakis, G. E.; Orszag, S. A.

1990-01-01

Methods for computing jet turbulence noise based on the time-dependent solution of Lighthill's (1952) differential equation are demonstrated. A key element in this approach is a flow code for solving the time-dependent Navier-Stokes equations at relatively high Reynolds numbers. Jet flow results at Re = 10,000 are presented here. This code combines a computationally efficient spectral element technique and a new self-consistent turbulence subgrid model to supply values for Lighthill's turbulence noise source tensor.

Two-stage unified stretched-exponential model for time-dependence of threshold voltage shift under positive-bias-stresses in amorphous indium-gallium-zinc oxide thin-film transistors

NASA Astrophysics Data System (ADS)

Jeong, Chan-Yong; Kim, Hee-Joong; Hong, Sae-Young; Song, Sang-Hun; Kwon, Hyuck-In

2017-08-01

In this study, we show that the two-stage unified stretched-exponential model can more exactly describe the time-dependence of threshold voltage shift (ΔV TH) under long-term positive-bias-stresses compared to the traditional stretched-exponential model in amorphous indium-gallium-zinc oxide (a-IGZO) thin-film transistors (TFTs). ΔV TH is mainly dominated by electron trapping at short stress times, and the contribution of trap state generation becomes significant with an increase in the stress time. The two-stage unified stretched-exponential model can provide useful information not only for evaluating the long-term electrical stability and lifetime of the a-IGZO TFT but also for understanding the stress-induced degradation mechanism in a-IGZO TFTs.

Calculation of the Intensity of Physical Time Fluctuations Using the Standard Solar Model and its Comparison with the Results of Experimental Measurements

NASA Astrophysics Data System (ADS)

Morozov, A. N.

2017-11-01

The article reviews the possibility of describing physical time as a random Poisson process. An equation allowing the intensity of physical time fluctuations to be calculated depending on the entropy production density within irreversible natural processes has been proposed. Based on the standard solar model the work calculates the entropy production density inside the Sun and the dependence of the intensity of physical time fluctuations on the distance to the centre of the Sun. A free model parameter has been established, and the method of its evaluation has been suggested. The calculations of the entropy production density inside the Sun showed that it differs by 2-3 orders of magnitude in different parts of the Sun. The intensity of physical time fluctuations on the Earth's surface depending on the entropy production density during the sunlight-to-Earth's thermal radiation conversion has been theoretically predicted. A method of evaluation of the Kullback's measure of voltage fluctuations in small amounts of electrolyte has been proposed. Using a simple model of the Earth's surface heat transfer to the upper atmosphere, the effective Earth's thermal radiation temperature has been determined. A comparison between the theoretical values of the Kullback's measure derived from the fluctuating physical time model and the experimentally measured values of this measure for two independent electrolytic cells showed a good qualitative and quantitative concurrence of predictions of both theoretical model and experimental data.

A Pulsed Sphere Tutorial

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

Cullen, Dermott E.

2017-01-30

Here I attempt to explain what physically happens when we pulse an object with neutrons, specifically what we expect the time dependent behavior of the neutron population to look like. Emphasis is on the time dependent emission of both prompt and delayed neutrons. I also describe how the TART Monte Carlo transport code models this situation; see the appendix for a complete description of the model used by TART. I will also show that, as we expect, MCNP and MERCURY, produce similar results using the same delayed neutron model (again, see the appendix).

Solar Potential Analysis and Integration of the Time-Dependent Simulation Results for Semantic 3d City Models Using Dynamizers

NASA Astrophysics Data System (ADS)

Chaturvedi, K.; Willenborg, B.; Sindram, M.; Kolbe, T. H.

2017-10-01

Semantic 3D city models play an important role in solving complex real-world problems and are being adopted by many cities around the world. A wide range of application and simulation scenarios directly benefit from the adoption of international standards such as CityGML. However, most of the simulations involve properties, whose values vary with respect to time, and the current generation semantic 3D city models do not support time-dependent properties explicitly. In this paper, the details of solar potential simulations are provided operating on the CityGML standard, assessing and estimating solar energy production for the roofs and facades of the 3D building objects in different ways. Furthermore, the paper demonstrates how the time-dependent simulation results are better-represented inline within 3D city models utilizing the so-called Dynamizer concept. This concept not only allows representing the simulation results in standardized ways, but also delivers a method to enhance static city models by such dynamic property values making the city models truly dynamic. The dynamizer concept has been implemented as an Application Domain Extension of the CityGML standard within the OGC Future City Pilot Phase 1. The results are given in this paper.

Nonequilibrium itinerant-electron magnetism: A time-dependent mean-field theory

NASA Astrophysics Data System (ADS)

Secchi, A.; Lichtenstein, A. I.; Katsnelson, M. I.

2016-08-01

We study the dynamical magnetic susceptibility of a strongly correlated electronic system in the presence of a time-dependent hopping field, deriving a generalized Bethe-Salpeter equation that is valid also out of equilibrium. Focusing on the single-orbital Hubbard model within the time-dependent Hartree-Fock approximation, we solve the equation in the nonequilibrium adiabatic regime, obtaining a closed expression for the transverse magnetic susceptibility. From this, we provide a rigorous definition of nonequilibrium (time-dependent) magnon frequencies and exchange parameters, expressed in terms of nonequilibrium single-electron Green's functions and self-energies. In the particular case of equilibrium, we recover previously known results.

Equilibrium finite-frequency noise of an interacting mesoscopic capacitor studied in time-dependent density functional theory

NASA Astrophysics Data System (ADS)

Dittmann, Niklas; Splettstoesser, Janine; Helbig, Nicole

2018-03-01

We calculate the frequency-dependent equilibrium noise of a mesoscopic capacitor in time-dependent density functional theory (TDDFT). The capacitor is modeled as a single-level quantum dot with on-site Coulomb interaction and tunnel coupling to a nearby reservoir. The noise spectra are derived from linear-response conductances via the fluctuation-dissipation theorem. Thereby, we analyze the performance of a recently derived exchange-correlation potential with time-nonlocal density dependence in the finite-frequency linear-response regime. We compare our TDDFT noise spectra with real-time perturbation theory and find excellent agreement for noise frequencies below the reservoir temperature.

Neutron star dynamics under time-dependent external torques

NASA Astrophysics Data System (ADS)

Gügercinoǧlu, Erbil; Alpar, M. Ali

2017-11-01

The two-component model describes neutron star dynamics incorporating the response of the superfluid interior. Conventional solutions and applications involve constant external torques, as appropriate for radio pulsars on dynamical time-scales. We present the general solution of two-component dynamics under arbitrary time-dependent external torques, with internal torques that are linear in the rotation rates, or with the extremely non-linear internal torques due to vortex creep. The two-component model incorporating the response of linear or non-linear internal torques can now be applied not only to radio pulsars but also to magnetars and to neutron stars in binary systems, with strong observed variability and noise in the spin-down or spin-up rates. Our results allow the extraction of the time-dependent external torques from the observed spin-down (or spin-up) time series, \\dot{Ω }(t). Applications are discussed.

Modeling molecule-plasmon interactions using quantized radiation fields within time-dependent electronic structure theory

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

Nascimento, Daniel R.; DePrince, A. Eugene, E-mail: deprince@chem.fsu.edu

2015-12-07

We present a combined cavity quantum electrodynamics/ab initio electronic structure approach for simulating plasmon-molecule interactions in the time domain. The simple Jaynes-Cummings-type model Hamiltonian typically utilized in such simulations is replaced with one in which the molecular component of the coupled system is treated in a fully ab initio way, resulting in a computationally efficient description of general plasmon-molecule interactions. Mutual polarization effects are easily incorporated within a standard ground-state Hartree-Fock computation, and time-dependent simulations carry the same formal computational scaling as real-time time-dependent Hartree-Fock theory. As a proof of principle, we apply this generalized method to the emergence ofmore » a Fano-like resonance in coupled molecule-plasmon systems; this feature is quite sensitive to the nanoparticle-molecule separation and the orientation of the molecule relative to the polarization of the external electric field.« less

Exciton interference revealed by energy dependent exciton transfer rate for ring-structured molecular systems.

PubMed

Yan, Yun-An

2016-01-14

The quantum interference is an intrinsic phenomenon in quantum physics for photon and massive quantum particles. In principle, the quantum interference may also occur with quasi-particles, such as the exciton. In this study, we show how the exciton quantum interference can be significant in aggregates through theoretical simulations with hierarchical equations of motion. The systems under investigation are generalized donor-bridge-acceptor model aggregates with the donor consisting of six homogeneous sites assuming the nearest neighbor coupling. For the models with single-path bridge, the exciton transfer time only shows a weak excitation energy dependence. But models with double-path bridge have a new short transfer time scale and the excitation energy dependence of the exciton transfer time assumes clear peak structure which is detectable with today's nonlinear spectroscopy. This abnormality is attributed to the exciton quantum interference and the condition for a clear observation in experiment is also explored.

Empirical study of the dependence of the results of multivariable flexible survival analyses on model selection strategy.

PubMed

Binquet, C; Abrahamowicz, M; Mahboubi, A; Jooste, V; Faivre, J; Bonithon-Kopp, C; Quantin, C

2008-12-30

Flexible survival models, which avoid assumptions about hazards proportionality (PH) or linearity of continuous covariates effects, bring the issues of model selection to a new level of complexity. Each 'candidate covariate' requires inter-dependent decisions regarding (i) its inclusion in the model, and representation of its effects on the log hazard as (ii) either constant over time or time-dependent (TD) and, for continuous covariates, (iii) either loglinear or non-loglinear (NL). Moreover, 'optimal' decisions for one covariate depend on the decisions regarding others. Thus, some efficient model-building strategy is necessary.We carried out an empirical study of the impact of the model selection strategy on the estimates obtained in flexible multivariable survival analyses of prognostic factors for mortality in 273 gastric cancer patients. We used 10 different strategies to select alternative multivariable parametric as well as spline-based models, allowing flexible modeling of non-parametric (TD and/or NL) effects. We employed 5-fold cross-validation to compare the predictive ability of alternative models.All flexible models indicated significant non-linearity and changes over time in the effect of age at diagnosis. Conventional 'parametric' models suggested the lack of period effect, whereas more flexible strategies indicated a significant NL effect. Cross-validation confirmed that flexible models predicted better mortality. The resulting differences in the 'final model' selected by various strategies had also impact on the risk prediction for individual subjects.Overall, our analyses underline (a) the importance of accounting for significant non-parametric effects of covariates and (b) the need for developing accurate model selection strategies for flexible survival analyses. Copyright 2008 John Wiley & Sons, Ltd.

MIXOR: a computer program for mixed-effects ordinal regression analysis.

PubMed

Hedeker, D; Gibbons, R D

1996-03-01

MIXOR provides maximum marginal likelihood estimates for mixed-effects ordinal probit, logistic, and complementary log-log regression models. These models can be used for analysis of dichotomous and ordinal outcomes from either a clustered or longitudinal design. For clustered data, the mixed-effects model assumes that data within clusters are dependent. The degree of dependency is jointly estimated with the usual model parameters, thus adjusting for dependence resulting from clustering of the data. Similarly, for longitudinal data, the mixed-effects approach can allow for individual-varying intercepts and slopes across time, and can estimate the degree to which these time-related effects vary in the population of individuals. MIXOR uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring solution, the Cholesky factor of the random-effects variance-covariance matrix is estimated, along with the effects of model covariates. Examples illustrating usage and features of MIXOR are provided.

Finite element analysis of history-dependent damage in time-dependent fracture mechanics

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

Krishnaswamy, P.; Brust, F.W.; Ghadiali, N.D.

1993-11-01

The demands for structural systems to perform reliably under both severe and changing operating conditions continue to increase. Under these conditions time-dependent straining and history-dependent damage become extremely important. This work focuses on studying creep crack growth using finite element (FE) analysis. Two important issues, namely, (1) the use of history-dependent constitutive laws, and (2) the use of various fracture parameters in predicting creep crack growth, have both been addressed in this work. The constitutive model used here is the one developed by Murakami and Ohno and is based on the concept of a creep hardening surface. An implicit FEmore » algorithm for this model was first developed and verified for simple geometries and loading configurations. The numerical methodology developed here has been used to model stationary and growing cracks in CT specimens. Various fracture parameters such as the C[sub 1], C[sup *], T[sup *], J were used to compare the numerical predictions with experimental results available in the literature. A comparison of the values of these parameters as a function of time has been made for both stationary and growing cracks. The merit of using each of these parameters has also been discussed.« less

Soliton solutions, stability analysis and conservation laws for the brusselator reaction diffusion model with time- and constant-dependent coefficients

NASA Astrophysics Data System (ADS)

Inc, Mustafa; Yusuf, Abdullahi; Isa Aliyu, Aliyu; Hashemi, M. S.

2018-05-01

This paper studies the brusselator reaction diffusion model (BRDM) with time- and constant-dependent coefficients. The soliton solutions for BRDM with time-dependent coefficients are obtained via first integral (FIM), ansatz, and sine-Gordon expansion (SGEM) methods. Moreover, it is well known that stability analysis (SA), symmetry analysis and conservation laws (CLs) give several information for modelling a system of differential equations (SDE). This is because they can be used for investigating the internal properties, existence, uniqueness and integrability of different SDE. For this reason, we investigate the SA via linear stability technique, symmetry analysis and CLs for BRDM with constant-dependent coefficients in order to extract more physics and information on the governing equation. The constraint conditions for the existence of the solutions are also examined. The new solutions obtained in this paper can be useful for describing the concentrations of diffusion problems of the BRDM. It is shown that the examined dependent coefficients are some of the factors that are affecting the diffusion rate. So, the present paper provides much motivational information in comparison to the existing results in the literature.

A mathematical approach for evaluating Markov models in continuous time without discrete-event simulation.

PubMed

van Rosmalen, Joost; Toy, Mehlika; O'Mahony, James F

2013-08-01

Markov models are a simple and powerful tool for analyzing the health and economic effects of health care interventions. These models are usually evaluated in discrete time using cohort analysis. The use of discrete time assumes that changes in health states occur only at the end of a cycle period. Discrete-time Markov models only approximate the process of disease progression, as clinical events typically occur in continuous time. The approximation can yield biased cost-effectiveness estimates for Markov models with long cycle periods and if no half-cycle correction is made. The purpose of this article is to present an overview of methods for evaluating Markov models in continuous time. These methods use mathematical results from stochastic process theory and control theory. The methods are illustrated using an applied example on the cost-effectiveness of antiviral therapy for chronic hepatitis B. The main result is a mathematical solution for the expected time spent in each state in a continuous-time Markov model. It is shown how this solution can account for age-dependent transition rates and discounting of costs and health effects, and how the concept of tunnel states can be used to account for transition rates that depend on the time spent in a state. The applied example shows that the continuous-time model yields more accurate results than the discrete-time model but does not require much computation time and is easily implemented. In conclusion, continuous-time Markov models are a feasible alternative to cohort analysis and can offer several theoretical and practical advantages.

From spin noise to systematics: stochastic processes in the first International Pulsar Timing Array data release

NASA Astrophysics Data System (ADS)

Lentati, L.; Shannon, R. M.; Coles, W. A.; Verbiest, J. P. W.; van Haasteren, R.; Ellis, J. A.; Caballero, R. N.; Manchester, R. N.; Arzoumanian, Z.; Babak, S.; Bassa, C. G.; Bhat, N. D. R.; Brem, P.; Burgay, M.; Burke-Spolaor, S.; Champion, D.; Chatterjee, S.; Cognard, I.; Cordes, J. M.; Dai, S.; Demorest, P.; Desvignes, G.; Dolch, T.; Ferdman, R. D.; Fonseca, E.; Gair, J. R.; Gonzalez, M. E.; Graikou, E.; Guillemot, L.; Hessels, J. W. T.; Hobbs, G.; Janssen, G. H.; Jones, G.; Karuppusamy, R.; Keith, M.; Kerr, M.; Kramer, M.; Lam, M. T.; Lasky, P. D.; Lassus, A.; Lazarus, P.; Lazio, T. J. W.; Lee, K. J.; Levin, L.; Liu, K.; Lynch, R. S.; Madison, D. R.; McKee, J.; McLaughlin, M.; McWilliams, S. T.; Mingarelli, C. M. F.; Nice, D. J.; Osłowski, S.; Pennucci, T. T.; Perera, B. B. P.; Perrodin, D.; Petiteau, A.; Possenti, A.; Ransom, S. M.; Reardon, D.; Rosado, P. A.; Sanidas, S. A.; Sesana, A.; Shaifullah, G.; Siemens, X.; Smits, R.; Stairs, I.; Stappers, B.; Stinebring, D. R.; Stovall, K.; Swiggum, J.; Taylor, S. R.; Theureau, G.; Tiburzi, C.; Toomey, L.; Vallisneri, M.; van Straten, W.; Vecchio, A.; Wang, J.-B.; Wang, Y.; You, X. P.; Zhu, W. W.; Zhu, X.-J.

2016-05-01

We analyse the stochastic properties of the 49 pulsars that comprise the first International Pulsar Timing Array (IPTA) data release. We use Bayesian methodology, performing model selection to determine the optimal description of the stochastic signals present in each pulsar. In addition to spin-noise and dispersion-measure (DM) variations, these models can include timing noise unique to a single observing system, or frequency band. We show the improved radio-frequency coverage and presence of overlapping data from different observing systems in the IPTA data set enables us to separate both system and band-dependent effects with much greater efficacy than in the individual pulsar timing array (PTA) data sets. For example, we show that PSR J1643-1224 has, in addition to DM variations, significant band-dependent noise that is coherent between PTAs which we interpret as coming from time-variable scattering or refraction in the ionized interstellar medium. Failing to model these different contributions appropriately can dramatically alter the astrophysical interpretation of the stochastic signals observed in the residuals. In some cases, the spectral exponent of the spin-noise signal can vary from 1.6 to 4 depending upon the model, which has direct implications for the long-term sensitivity of the pulsar to a stochastic gravitational-wave (GW) background. By using a more appropriate model, however, we can greatly improve a pulsar's sensitivity to GWs. For example, including system and band-dependent signals in the PSR J0437-4715 data set improves the upper limit on a fiducial GW background by ˜60 per cent compared to a model that includes DM variations and spin-noise only.

1D-3D hybrid modeling-from multi-compartment models to full resolution models in space and time.

PubMed

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator-which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics.

Comparing Time-Dependent Geomagnetic and Atmospheric Effects on Cosmogenic Nuclide Production Rate Scaling

NASA Astrophysics Data System (ADS)

Lifton, N. A.

2014-12-01

A recently published cosmogenic nuclide production rate scaling model based on analytical fits to Monte Carlo simulations of atmospheric cosmic ray flux spectra (both of which agree well with measured spectra) (Lifton et al., 2014, Earth Planet. Sci. Lett. 386, 149-160: termed the LSD model) provides two main advantages over previous scaling models: identification and quantification of potential sources of bias in the earlier models, and the ability to generate nuclide-specific scaling factors easily for a wide range of input parameters. The new model also provides a flexible framework for exploring the implications of advances in model inputs. In this work, the scaling implications of two recent time-dependent spherical harmonic geomagnetic models spanning the Holocene will be explored. Korte and Constable (2011, Phys. Earth Planet. Int. 188, 247-259) and Korte et al. (2011, Earth Planet. Sci. Lett. 312, 497-505) recently updated earlier spherical harmonic paleomagnetic models used by Lifton et al. (2014) with paleomagnetic measurements from sediment cores in addition to archeomagnetic and volcanic data. These updated models offer improved accuracy over the previous versions, in part to due to increased temporal and spatial data coverage. With the new models as input, trajectory-traced estimates of effective vertical cutoff rigidity (RC- the standard method for ordering cosmic ray data) yield significantly different time-integrated scaling predictions when compared to the earlier models. These results will be compared to scaling predictions using another recent time-dependent spherical harmonic model of the Holocene geomagnetic field by Pavón-Carrasco et al. (2014, Earth Planet. Sci. Lett. 388, 98-109), based solely on archeomagnetic and volcanic paleomagnetic data, but extending to 14 ka. In addition, the potential effects of time-dependent atmospheric models on LSD scaling predictions will be presented. Given the typical dominance of altitudinal over latitudinal scaling effects on cosmogenic nuclide production, incorporating transient global simulations of atmospheric structure (e.g., Liu et al., 2009, Science 325, 310-314) into scaling frameworks may contribute to improved understanding of long-term production rate variations.

Skewness in large-scale structure and non-Gaussian initial conditions

NASA Technical Reports Server (NTRS)

Fry, J. N.; Scherrer, Robert J.

1994-01-01

We compute the skewness of the galaxy distribution arising from the nonlinear evolution of arbitrary non-Gaussian intial conditions to second order in perturbation theory including the effects of nonlinear biasing. The result contains a term identical to that for a Gaussian initial distribution plus terms which depend on the skewness and kurtosis of the initial conditions. The results are model dependent; we present calculations for several toy models. At late times, the leading contribution from the initial skewness decays away relative to the other terms and becomes increasingly unimportant, but the contribution from initial kurtosis, previously overlooked, has the same time dependence as the Gaussian terms. Observations of a linear dependence of the normalized skewness on the rms density fluctuation therefore do not necessarily rule out initially non-Gaussian models. We also show that with non-Gaussian initial conditions the first correction to linear theory for the mean square density fluctuation is larger than for Gaussian models.

Signatures of ecological processes in microbial community time series.

PubMed

Faust, Karoline; Bauchinger, Franziska; Laroche, Béatrice; de Buyl, Sophie; Lahti, Leo; Washburne, Alex D; Gonze, Didier; Widder, Stefanie

2018-06-28

Growth rates, interactions between community members, stochasticity, and immigration are important drivers of microbial community dynamics. In sequencing data analysis, such as network construction and community model parameterization, we make implicit assumptions about the nature of these drivers and thereby restrict model outcome. Despite apparent risk of methodological bias, the validity of the assumptions is rarely tested, as comprehensive procedures are lacking. Here, we propose a classification scheme to determine the processes that gave rise to the observed time series and to enable better model selection. We implemented a three-step classification scheme in R that first determines whether dependence between successive time steps (temporal structure) is present in the time series and then assesses with a recently developed neutrality test whether interactions between species are required for the dynamics. If the first and second tests confirm the presence of temporal structure and interactions, then parameters for interaction models are estimated. To quantify the importance of temporal structure, we compute the noise-type profile of the community, which ranges from black in case of strong dependency to white in the absence of any dependency. We applied this scheme to simulated time series generated with the Dirichlet-multinomial (DM) distribution, Hubbell's neutral model, the generalized Lotka-Volterra model and its discrete variant (the Ricker model), and a self-organized instability model, as well as to human stool microbiota time series. The noise-type profiles for all but DM data clearly indicated distinctive structures. The neutrality test correctly classified all but DM and neutral time series as non-neutral. The procedure reliably identified time series for which interaction inference was suitable. Both tests were required, as we demonstrated that all structured time series, including those generated with the neutral model, achieved a moderate to high goodness of fit to the Ricker model. We present a fast and robust scheme to classify community structure and to assess the prevalence of interactions directly from microbial time series data. The procedure not only serves to determine ecological drivers of microbial dynamics, but also to guide selection of appropriate community models for prediction and follow-up analysis.

A simple analytical model for dynamics of time-varying target leverage ratios

NASA Astrophysics Data System (ADS)

Lo, C. F.; Hui, C. H.

2012-03-01

In this paper we have formulated a simple theoretical model for the dynamics of the time-varying target leverage ratio of a firm under some assumptions based upon empirical observations. In our theoretical model the time evolution of the target leverage ratio of a firm can be derived self-consistently from a set of coupled Ito's stochastic differential equations governing the leverage ratios of an ensemble of firms by the nonlinear Fokker-Planck equation approach. The theoretically derived time paths of the target leverage ratio bear great resemblance to those used in the time-dependent stationary-leverage (TDSL) model [Hui et al., Int. Rev. Financ. Analy. 15, 220 (2006)]. Thus, our simple model is able to provide a theoretical foundation for the selected time paths of the target leverage ratio in the TDSL model. We also examine how the pace of the adjustment of a firm's target ratio, the volatility of the leverage ratio and the current leverage ratio affect the dynamics of the time-varying target leverage ratio. Hence, with the proposed dynamics of the time-dependent target leverage ratio, the TDSL model can be readily applied to generate the default probabilities of individual firms and to assess the default risk of the firms.

Voltage dependence of a stochastic model of activation of an alpha helical S4 sensor in a K channel membrane

NASA Astrophysics Data System (ADS)

Vaccaro, S. R.

2011-09-01

The voltage dependence of the ionic and gating currents of a K channel is dependent on the activation barriers of a voltage sensor with a potential function which may be derived from the principal electrostatic forces on an S4 segment in an inhomogeneous dielectric medium. By variation of the parameters of a voltage-sensing domain model, consistent with x-ray structures and biophysical data, the lowest frequency of the survival probability of each stationary state derived from a solution of the Smoluchowski equation provides a good fit to the voltage dependence of the slowest time constant of the ionic current in a depolarized membrane, and the gating current exhibits a rising phase that precedes an exponential relaxation. For each depolarizing potential, the calculated time dependence of the survival probabilities of the closed states of an alpha helical S4 sensor are in accord with an empirical model of the ionic and gating currents recorded during the activation process.

SDSS-IV MaNGA: modelling the metallicity gradients of gas and stars - radially dependent metal outflow versus IMF

NASA Astrophysics Data System (ADS)

Lian, Jianhui; Thomas, Daniel; Maraston, Claudia; Goddard, Daniel; Parikh, Taniya; Fernández-Trincado, J. G.; Roman-Lopes, Alexandre; Rong, Yu; Tang, Baitian; Yan, Renbin

2018-05-01

In our previous work, we found that only two scenarios are capable of reproducing the observed integrated mass-metallicity relations for the gas and stellar components of local star-forming galaxies simultaneously. One scenario invokes a time-dependent metal outflow loading factor with stronger outflows at early times. The other scenario uses a time-dependent initial mass function (IMF) slope with a steeper IMF at early times. In this work, we extend our study to investigate the radial profile of gas and stellar metallicity in local star-forming galaxies using spatially resolved spectroscopic data from the SDSS-IV MaNGA survey. We find that most galaxies show negative gradients in both gas and stellar metallicity with steeper gradients in stellar metallicity. The stellar metallicity gradients tend to be mass dependent with steeper gradients in more massive galaxies while no clear mass dependence is found for the gas metallicity gradient. Then we compare the observations with the predictions from a chemical evolution model of the radial profiles of gas and stellar metallicities. We confirm that the two scenarios proposed in our previous work are also required to explain the metallicity gradients. Based on these two scenarios, we successfully reproduce the radial profiles of gas metallicity, stellar metallicity, stellar mass surface density, and star formation rate surface density simultaneously. The origin of the negative gradient in stellar metallicity turns out to be driven by either radially dependent metal outflow or IMF slope. In contrast, the radial dependence of the gas metallicity is less constrained because of the degeneracy in model parameters.

A new technique for observationally derived boundary conditions for space weather

NASA Astrophysics Data System (ADS)

Pagano, Paolo; Mackay, Duncan Hendry; Yeates, Anthony Robinson

2018-04-01

Context. In recent years, space weather research has focused on developing modelling techniques to predict the arrival time and properties of coronal mass ejections (CMEs) at the Earth. The aim of this paper is to propose a new modelling technique suitable for the next generation of Space Weather predictive tools that is both efficient and accurate. The aim of the new approach is to provide interplanetary space weather forecasting models with accurate time dependent boundary conditions of erupting magnetic flux ropes in the upper solar corona. Methods: To produce boundary conditions, we couple two different modelling techniques, MHD simulations and a quasi-static non-potential evolution model. Both are applied on a spatial domain that covers the entire solar surface, although they extend over a different radial distance. The non-potential model uses a time series of observed synoptic magnetograms to drive the non-potential quasi-static evolution of the coronal magnetic field. This allows us to follow the formation and loss of equilibrium of magnetic flux ropes. Following this a MHD simulation captures the dynamic evolution of the erupting flux rope, when it is ejected into interplanetary space. Results.The present paper focuses on the MHD simulations that follow the ejection of magnetic flux ropes to 4 R⊙. We first propose a technique for specifying the pre-eruptive plasma properties in the corona. Next, time dependent MHD simulations describe the ejection of two magnetic flux ropes, that produce time dependent boundary conditions for the magnetic field and plasma at 4 R⊙ that in future may be applied to interplanetary space weather prediction models. Conclusions: In the present paper, we show that the dual use of quasi-static non-potential magnetic field simulations and full time dependent MHD simulations can produce realistic inhomogeneous boundary conditions for space weather forecasting tools. Before a fully operational model can be produced there are a number of technical and scientific challenges that still need to be addressed. Nevertheless, we illustrate that coupling quasi-static and MHD simulations in this way can significantly reduce the computational time required to produce realistic space weather boundary conditions.

Detecting Moving Targets by Use of Soliton Resonances

NASA Technical Reports Server (NTRS)

Zak, Michael; Kulikov, Igor

2003-01-01

A proposed method of detecting moving targets in scenes that include cluttered or noisy backgrounds is based on a soliton-resonance mathematical model. The model is derived from asymptotic solutions of the cubic Schroedinger equation for a one-dimensional system excited by a position-and-time-dependent externally applied potential. The cubic Schroedinger equation has general significance for time-dependent dispersive waves. It has been used to approximate several phenomena in classical as well as quantum physics, including modulated beams in nonlinear optics, and superfluids (in particular, Bose-Einstein condensates). In the proposed method, one would take advantage of resonant interactions between (1) a soliton excited by the position-and-time-dependent potential associated with a moving target and (2) eigen-solitons, which represent dispersive waves and are solutions of the cubic Schroedinger equation for a time-independent potential.

Finite horizon EOQ model for non-instantaneous deteriorating items with price and advertisement dependent demand and partial backlogging under inflation

NASA Astrophysics Data System (ADS)

Palanivel, M.; Uthayakumar, R.

2015-07-01

This paper deals with an economic order quantity (EOQ) model for non-instantaneous deteriorating items with price and advertisement dependent demand pattern under the effect of inflation and time value of money over a finite planning horizon. In this model, shortages are allowed and partially backlogged. The backlogging rate is dependent on the waiting time for the next replenishment. This paper aids the retailer in minimising the total inventory cost by finding the optimal interval and the optimal order quantity. An algorithm is designed to find the optimum solution of the proposed model. Numerical examples are given to demonstrate the results. Also, the effect of changes in the different parameters on the optimal total cost is graphically presented and the implications are discussed in detail.

Nonlinear stochastic exclusion financial dynamics modeling and time-dependent intrinsic detrended cross-correlation

NASA Astrophysics Data System (ADS)

Zhang, Wei; Wang, Jun

2017-09-01

In attempt to reproduce price dynamics of financial markets, a stochastic agent-based financial price model is proposed and investigated by stochastic exclusion process. The exclusion process, one of interacting particle systems, is usually thought of as modeling particle motion (with the conserved number of particles) in a continuous time Markov process. In this work, the process is utilized to imitate the trading interactions among the investing agents, in order to explain some stylized facts found in financial time series dynamics. To better understand the correlation behaviors of the proposed model, a new time-dependent intrinsic detrended cross-correlation (TDI-DCC) is introduced and performed, also, the autocorrelation analyses are applied in the empirical research. Furthermore, to verify the rationality of the financial price model, the actual return series are also considered to be comparatively studied with the simulation ones. The comparison results of return behaviors reveal that this financial price dynamics model can reproduce some correlation features of actual stock markets.

Robust inference in discrete hazard models for randomized clinical trials.

PubMed

Nguyen, Vinh Q; Gillen, Daniel L

2012-10-01

Time-to-event data in which failures are only assessed at discrete time points are common in many clinical trials. Examples include oncology studies where events are observed through periodic screenings such as radiographic scans. When the survival endpoint is acknowledged to be discrete, common methods for the analysis of observed failure times include the discrete hazard models (e.g., the discrete-time proportional hazards and the continuation ratio model) and the proportional odds model. In this manuscript, we consider estimation of a marginal treatment effect in discrete hazard models where the constant treatment effect assumption is violated. We demonstrate that the estimator resulting from these discrete hazard models is consistent for a parameter that depends on the underlying censoring distribution. An estimator that removes the dependence on the censoring mechanism is proposed and its asymptotic distribution is derived. Basing inference on the proposed estimator allows for statistical inference that is scientifically meaningful and reproducible. Simulation is used to assess the performance of the presented methodology in finite samples.

Method and device for predicting wavelength dependent radiation influences in thermal systems

DOEpatents

Kee, Robert J.; Ting, Aili

1996-01-01

A method and apparatus for predicting the spectral (wavelength-dependent) radiation transport in thermal systems including interaction by the radiation with partially transmitting medium. The predicted model of the thermal system is used to design and control the thermal system. The predictions are well suited to be implemented in design and control of rapid thermal processing (RTP) reactors. The method involves generating a spectral thermal radiation transport model of an RTP reactor. The method also involves specifying a desired wafer time dependent temperature profile. The method further involves calculating an inverse of the generated model using the desired wafer time dependent temperature to determine heating element parameters required to produce the desired profile. The method also involves controlling the heating elements of the RTP reactor in accordance with the heating element parameters to heat the wafer in accordance with the desired profile.

Modelling of Vortex-Induced Loading on a Single-Blade Installation Setup

NASA Astrophysics Data System (ADS)

Skrzypiński, Witold; Gaunaa, Mac; Heinz, Joachim

2016-09-01

Vortex-induced integral loading fluctuations on a single suspended blade at various inflow angles were modeled in the presents work by means of stochastic modelling methods. The reference time series were obtained by 3D DES CFD computations carried out on the DTU 10MW reference wind turbine blade. In the reference time series, the flapwise force component, Fx, showed both higher absolute values and variation than the chordwise force component, Fz, for every inflow angle considered. For this reason, the present paper focused on modelling of the Fx and not the Fz whereas Fz would be modelled using exactly the same procedure. The reference time series were significantly different, depending on the inflow angle. This made the modelling of all the time series with a single and relatively simple engineering model challenging. In order to find model parameters, optimizations were carried out, based on the root-mean-square error between the Single-Sided Amplitude Spectra of the reference and modelled time series. In order to model well defined frequency peaks present at certain inflow angles, optimized sine functions were superposed on the stochastically modelled time series. The results showed that the modelling accuracy varied depending on the inflow angle. None the less, the modelled and reference time series showed a satisfactory general agreement in terms of their visual and frequency characteristics. This indicated that the proposed method is suitable to model loading fluctuations on suspended blades.

Local dependence in random graph models: characterization, properties and statistical inference

PubMed Central

Schweinberger, Michael; Handcock, Mark S.

2015-01-01

Summary Dependent phenomena, such as relational, spatial and temporal phenomena, tend to be characterized by local dependence in the sense that units which are close in a well-defined sense are dependent. In contrast with spatial and temporal phenomena, though, relational phenomena tend to lack a natural neighbourhood structure in the sense that it is unknown which units are close and thus dependent. Owing to the challenge of characterizing local dependence and constructing random graph models with local dependence, many conventional exponential family random graph models induce strong dependence and are not amenable to statistical inference. We take first steps to characterize local dependence in random graph models, inspired by the notion of finite neighbourhoods in spatial statistics and M-dependence in time series, and we show that local dependence endows random graph models with desirable properties which make them amenable to statistical inference. We show that random graph models with local dependence satisfy a natural domain consistency condition which every model should satisfy, but conventional exponential family random graph models do not satisfy. In addition, we establish a central limit theorem for random graph models with local dependence, which suggests that random graph models with local dependence are amenable to statistical inference. We discuss how random graph models with local dependence can be constructed by exploiting either observed or unobserved neighbourhood structure. In the absence of observed neighbourhood structure, we take a Bayesian view and express the uncertainty about the neighbourhood structure by specifying a prior on a set of suitable neighbourhood structures. We present simulation results and applications to two real world networks with ‘ground truth’. PMID:26560142

Real-time plasma control in a dual-frequency, confined plasma etcher

NASA Astrophysics Data System (ADS)

Milosavljević, V.; Ellingboe, A. R.; Gaman, C.; Ringwood, J. V.

2008-04-01

The physics issues of developing model-based control of plasma etching are presented. A novel methodology for incorporating real-time model-based control of plasma processing systems is developed. The methodology is developed for control of two dependent variables (ion flux and chemical densities) by two independent controls (27 MHz power and O2 flow). A phenomenological physics model of the nonlinear coupling between the independent controls and the dependent variables of the plasma is presented. By using a design of experiment, the functional dependencies of the response surface are determined. In conjunction with the physical model, the dependencies are used to deconvolve the sensor signals onto the control inputs, allowing compensation of the interaction between control paths. The compensated sensor signals and compensated set-points are then used as inputs to proportional-integral-derivative controllers to adjust radio frequency power and oxygen flow to yield the desired ion flux and chemical density. To illustrate the methodology, model-based real-time control is realized in a commercial semiconductor dielectric etch chamber. The two radio frequency symmetric diode operates with typical commercial fluorocarbon feed-gas mixtures (Ar/O2/C4F8). Key parameters for dielectric etching are known to include ion flux to the surface and surface flux of oxygen containing species. Control is demonstrated using diagnostics of electrode-surface ion current, and chemical densities of O, O2, and CO measured by optical emission spectrometry and/or mass spectrometry. Using our model-based real-time control, the set-point tracking accuracy to changes in chemical species density and ion flux is enhanced.

Electronic field emission models beyond the Fowler-Nordheim one

NASA Astrophysics Data System (ADS)

Lepetit, Bruno

2017-12-01

We propose several quantum mechanical models to describe electronic field emission from first principles. These models allow us to correlate quantitatively the electronic emission current with the electrode surface details at the atomic scale. They all rely on electronic potential energy surfaces obtained from three dimensional density functional theory calculations. They differ by the various quantum mechanical methods (exact or perturbative, time dependent or time independent), which are used to describe tunneling through the electronic potential energy barrier. Comparison of these models between them and with the standard Fowler-Nordheim one in the context of one dimensional tunneling allows us to assess the impact on the accuracy of the computed current of the approximations made in each model. Among these methods, the time dependent perturbative one provides a well-balanced trade-off between accuracy and computational cost.

Comparison of Statistical Approaches Dealing with Time-dependent Confounding in Drug Effectiveness Studies

PubMed Central

Karim, Mohammad Ehsanul; Petkau, John; Gustafson, Paul; Platt, Robert W.; Tremlett, Helen

2017-01-01

In longitudinal studies, if the time-dependent covariates are affected by the past treatment, time-dependent confounding may be present. For a time-to-event response, marginal structural Cox models (MSCMs) are frequently used to deal with such confounding. To avoid some of the problems of fitting MSCM, the sequential Cox approach has been suggested as an alternative. Although the estimation mechanisms are different, both approaches claim to estimate the causal effect of treatment by appropriately adjusting for time-dependent confounding. We carry out simulation studies to assess the suitability of the sequential Cox approach for analyzing time-to-event data in the presence of a time-dependent covariate that may or may not be a time-dependent confounder. Results from these simulations revealed that the sequential Cox approach is not as effective as MSCM in addressing the time-dependent confounding. The sequential Cox approach was also found to be inadequate in the presence of a time-dependent covariate. We propose a modified version of the sequential Cox approach that correctly estimates the treatment effect in both of the above scenarios. All approaches are applied to investigate the impact of beta-interferon treatment in delaying disability progression in the British Columbia Multiple Sclerosis cohort (1995 – 2008). PMID:27659168

Measurements of Time-Dependent CP Asymmetries in b\\to s Penguin Dominated Hadronic B Decays at BaBar

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

Biassoni, Pietro; /Milan U. /INFN, Milan

2009-12-09

We report measurements of Time-Dependent CP asymmetries in several b {yields} s penguin dominated hadronic B decays, where New Physics contributions may appear. We find no significant discrepancies with respect to the Standard Model expectations.

1D-3D hybrid modeling—from multi-compartment models to full resolution models in space and time

PubMed Central

Grein, Stephan; Stepniewski, Martin; Reiter, Sebastian; Knodel, Markus M.; Queisser, Gillian

2014-01-01

Investigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell. For single cell or networks with relatively small numbers of neurons, general purpose simulators allow for space and time-dependent simulations of electrical signal processing, based on the cable equation theory. An emerging field in Computational Neuroscience encompasses a new level of detail by incorporating the full three-dimensional morphology of cells and organelles into three-dimensional, space and time-dependent, simulations. While every approach has its advantages and limitations, such as computational cost, integrated and methods-spanning simulation approaches, depending on the network size could establish new ways to investigate the brain. In this paper we present a hybrid simulation approach, that makes use of reduced 1D-models using e.g., the NEURON simulator—which couples to fully resolved models for simulating cellular and sub-cellular dynamics, including the detailed three-dimensional morphology of neurons and organelles. In order to couple 1D- and 3D-simulations, we present a geometry-, membrane potential- and intracellular concentration mapping framework, with which graph- based morphologies, e.g., in the swc- or hoc-format, are mapped to full surface and volume representations of the neuron and computational data from 1D-simulations can be used as boundary conditions for full 3D simulations and vice versa. Thus, established models and data, based on general purpose 1D-simulators, can be directly coupled to the emerging field of fully resolved, highly detailed 3D-modeling approaches. We present the developed general framework for 1D/3D hybrid modeling and apply it to investigate electrically active neurons and their intracellular spatio-temporal calcium dynamics. PMID:25120463

The time-dependent response of 3- and 5-layer sandwich beams

NASA Technical Reports Server (NTRS)

Hyer, M. W.; Oleksuk, L. S. S.; Bowles, D. E.

1992-01-01

Simple sandwich beam models have been developed to study the effect of the time-dependent constitutive properties of fiber-reinforced polymer matrix composites, considered for use in orbiting precision segmented reflectors, on the overall deformations. The 3- and 5-layer beam models include layers representing the face sheets, the core, and the adhesive. The static elastic deformation response of the sandwich beam models to a midspan point load is studied using the principle of stationary potential energy. In addition to quantitative conclusions, several assumptions are discussed which simplify the analysis for the case of more complicated material models. It is shown that the simple three-layer model is sufficient in many situations.

Intercept Centering and Time Coding in Latent Difference Score Models

ERIC Educational Resources Information Center

Grimm, Kevin J.

2012-01-01

Latent difference score (LDS) models combine benefits derived from autoregressive and latent growth curve models allowing for time-dependent influences and systematic change. The specification and descriptions of LDS models include an initial level of ability or trait plus an accumulation of changes. A limitation of this specification is that the…

Non steady-state descriptions of drug permeation through stratum corneum. I. The biphasic brick-and-mortar model.

PubMed

Heisig, M; Lieckfeldt, R; Wittum, G; Mazurkevich, G; Lee, G

1996-03-01

The diffusion equation should be solved for the non-steady-state problem of drug diffusion within a two-dimensional, biphasic stratum corneum membrane having homogeneous lipid and corneocyte phases. A numerical method was developed for a brick-and-mortar SC-geometry, enabling an explicit solution for time-dependent drug concentration within both phases. The lag time and permeability were calculated. It is shown how the barrier property of this model membrane depends on relative phase permeability, corneocyte alignment, and corneocyte-lipid partition coefficient. Additionally, the time-dependent drug concentration profiles within the membrane can be observed during the lag and steady-state phases. The model SC-membrane predicts, from purely morphological principles, lag times and permeabilities that are in good agreement with experimental values. The long lag times and very small permeabilities reported for human SC can only be predicted for a highly-staggered corneocyte geometry and corneocytes that are 1000 times less permeable than the lipid phase. Although the former conclusion is reasonable, the latter is questionable. The elongated, flattened corneocyte shape renders lag time and permeability insensitive to large changes in their alignment within the SC. Corneocyte/lipid partitioning is found to be fundamentally different to SC/donor partitioning, since increasing drug lipophilicity always reduces both lag time and permeability.

Analytical results for a stochastic model of gene expression with arbitrary partitioning of proteins

NASA Astrophysics Data System (ADS)

Tschirhart, Hugo; Platini, Thierry

2018-05-01

In biophysics, the search for analytical solutions of stochastic models of cellular processes is often a challenging task. In recent work on models of gene expression, it was shown that a mapping based on partitioning of Poisson arrivals (PPA-mapping) can lead to exact solutions for previously unsolved problems. While the approach can be used in general when the model involves Poisson processes corresponding to creation or degradation, current applications of the method and new results derived using it have been limited to date. In this paper, we present the exact solution of a variation of the two-stage model of gene expression (with time dependent transition rates) describing the arbitrary partitioning of proteins. The methodology proposed makes full use of the PPA-mapping by transforming the original problem into a new process describing the evolution of three biological switches. Based on a succession of transformations, the method leads to a hierarchy of reduced models. We give an integral expression of the time dependent generating function as well as explicit results for the mean, variance, and correlation function. Finally, we discuss how results for time dependent parameters can be extended to the three-stage model and used to make inferences about models with parameter fluctuations induced by hidden stochastic variables.

Low Variance Couplings for Stochastic Models of Intracellular Processes with Time-Dependent Rate Functions.

PubMed

Anderson, David F; Yuan, Chaojie

2018-04-18

A number of coupling strategies are presented for stochastically modeled biochemical processes with time-dependent parameters. In particular, the stacked coupling is introduced and is shown via a number of examples to provide an exceptionally low variance between the generated paths. This coupling will be useful in the numerical computation of parametric sensitivities and the fast estimation of expectations via multilevel Monte Carlo methods. We provide the requisite estimators in both cases.

Nonequilibrium dynamics of the O( N ) model on dS3 and AdS crunches

NASA Astrophysics Data System (ADS)

Kumar, S. Prem; Vaganov, Vladislav

2018-03-01

We study the nonperturbative quantum evolution of the interacting O( N ) vector model at large- N , formulated on a spatial two-sphere, with time dependent couplings which diverge at finite time. This model - the so-called "E-frame" theory, is related via a conformal transformation to the interacting O( N ) model in three dimensional global de Sitter spacetime with time independent couplings. We show that with a purely quartic, relevant deformation the quantum evolution of the E-frame model is regular even when the classical theory is rendered singular at the end of time by the diverging coupling. Time evolution drives the E-frame theory to the large- N Wilson-Fisher fixed point when the classical coupling diverges. We study the quantum evolution numerically for a variety of initial conditions and demonstrate the finiteness of the energy at the classical "end of time". With an additional (time dependent) mass deformation, quantum backreaction lowers the mass, with a putative smooth time evolution only possible in the limit of infinite quartic coupling. We discuss the relevance of these results for the resolution of crunch singularities in AdS geometries dual to E-frame theories with a classical gravity dual.

Superplastic Creep of Metal Nanowires From Rate-Dependent Plasticity Transition

DOE PAGES

Tao, Weiwei; Cao, Penghui; Park, Harold S.

2018-04-30

Understanding the time-dependent mechanical behavior of nanomaterials such as nanowires is essential to predict their reliability in nanomechanical devices. This understanding is typically obtained using creep tests, which are the most fundamental loading mechanism by which the time dependent deformation of materials is characterized. However, due to existing challenges facing both experimentalists and theorists, the time dependent mechanical response of nanowires is not well-understood. Here, we use atomistic simulations that can access experimental time scales to examine the creep of single-crystal face-centered cubic metal (Cu, Ag, Pt) nanowires. Here, we report that both Cu and Ag nanowires show significantly increasedmore » ductility and superplasticity under low creep stresses, where the superplasticity is driven by a rate-dependent transition in defect nucleation from twinning to trailing partial dislocations at the micro- or millisecond time scale. The transition in the deformation mechanism also governs a corresponding transition in the stress-dependent creep time at the microsecond (Ag) and millisecond (Cu) time scales. Overall, this work demonstrates the necessity of accessing time scales that far exceed those seen in conventional atomistic modeling for accurate insights into the time-dependent mechanical behavior and properties of nanomaterials.« less

Superplastic Creep of Metal Nanowires from Rate-Dependent Plasticity Transition.

PubMed

Tao, Weiwei; Cao, Penghui; Park, Harold S

2018-05-22

Understanding the time-dependent mechanical behavior of nanomaterials such as nanowires is essential to predict their reliability in nanomechanical devices. This understanding is typically obtained using creep tests, which are the most fundamental loading mechanism by which the time-dependent deformation of materials is characterized. However, due to existing challenges facing both experimentalists and theorists, the time-dependent mechanical response of nanowires is not well-understood. Here, we use atomistic simulations that can access experimental time scales to examine the creep of single-crystal face-centered cubic metal (Cu, Ag, Pt) nanowires. We report that both Cu and Ag nanowires show significantly increased ductility and superplasticity under low creep stresses, where the superplasticity is driven by a rate-dependent transition in defect nucleation from twinning to trailing partial dislocations at the micro- or millisecond time scale. The transition in the deformation mechanism also governs a corresponding transition in the stress-dependent creep time at the microsecond (Ag) and millisecond (Cu) time scales. Overall, this work demonstrates the necessity of accessing time scales that far exceed those seen in conventional atomistic modeling for accurate insights into the time-dependent mechanical behavior and properties of nanomaterials.

Superplastic Creep of Metal Nanowires From Rate-Dependent Plasticity Transition

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

Tao, Weiwei; Cao, Penghui; Park, Harold S.

Understanding the time-dependent mechanical behavior of nanomaterials such as nanowires is essential to predict their reliability in nanomechanical devices. This understanding is typically obtained using creep tests, which are the most fundamental loading mechanism by which the time dependent deformation of materials is characterized. However, due to existing challenges facing both experimentalists and theorists, the time dependent mechanical response of nanowires is not well-understood. Here, we use atomistic simulations that can access experimental time scales to examine the creep of single-crystal face-centered cubic metal (Cu, Ag, Pt) nanowires. Here, we report that both Cu and Ag nanowires show significantly increasedmore » ductility and superplasticity under low creep stresses, where the superplasticity is driven by a rate-dependent transition in defect nucleation from twinning to trailing partial dislocations at the micro- or millisecond time scale. The transition in the deformation mechanism also governs a corresponding transition in the stress-dependent creep time at the microsecond (Ag) and millisecond (Cu) time scales. Overall, this work demonstrates the necessity of accessing time scales that far exceed those seen in conventional atomistic modeling for accurate insights into the time-dependent mechanical behavior and properties of nanomaterials.« less

The performance of a reduced-order adaptive controller when used in multi-antenna hyperthermia treatments with nonlinear temperature-dependent perfusion.

PubMed

Cheng, Kung-Shan; Yuan, Yu; Li, Zhen; Stauffer, Paul R; Maccarini, Paolo; Joines, William T; Dewhirst, Mark W; Das, Shiva K

2009-04-07

In large multi-antenna systems, adaptive controllers can aid in steering the heat focus toward the tumor. However, the large number of sources can greatly increase the steering time. Additionally, controller performance can be degraded due to changes in tissue perfusion which vary non-linearly with temperature, as well as with time and spatial position. The current work investigates whether a reduced-order controller with the assumption of piecewise constant perfusion is robust to temperature-dependent perfusion and achieves steering in a shorter time than required by a full-order controller. The reduced-order controller assumes that the optimal heating setting lies in a subspace spanned by the best heating vectors (virtual sources) of an initial, approximate, patient model. An initial, approximate, reduced-order model is iteratively updated by the controller, using feedback thermal images, until convergence of the heat focus to the tumor. Numerical tests were conducted in a patient model with a right lower leg sarcoma, heated in a 10-antenna cylindrical mini-annual phased array applicator operating at 150 MHz. A half-Gaussian model was used to simulate temperature-dependent perfusion. Simulated magnetic resonance temperature images were used as feedback at each iteration step. Robustness was validated for the controller, starting from four approximate initial models: (1) a 'standard' constant perfusion lower leg model ('standard' implies a model that exactly models the patient with the exception that perfusion is considered constant, i.e., not temperature dependent), (2) a model with electrical and thermal tissue properties varied from 50% higher to 50% lower than the standard model, (3) a simplified constant perfusion pure-muscle lower leg model with +/-50% deviated properties and (4) a standard model with the tumor position in the leg shifted by 1.5 cm. Convergence to the desired focus of heating in the tumor was achieved for all four simulated models. The controller accomplished satisfactory therapeutic outcomes: approximately 80% of the tumor was heated to temperatures 43 degrees C and approximately 93% was maintained at temperatures <41 degrees C. Compared to the controller without model reduction, a approximately 9-25 fold reduction in convergence time was accomplished using approximately 2-3 orthonormal virtual sources. In the situations tested, the controller was robust to the presence of temperature-dependent perfusion. The results of this work can help to lay the foundation for real-time thermal control of multi-antenna hyperthermia systems in clinical situations where perfusion can change rapidly with temperature.

Three-factor models versus time series models: quantifying time-dependencies of interactions between stimuli in cell biology and psychobiology for short longitudinal data.

PubMed

Frank, Till D; Kiyatkin, Anatoly; Cheong, Alex; Kholodenko, Boris N

2017-06-01

Signal integration determines cell fate on the cellular level, affects cognitive processes and affective responses on the behavioural level, and is likely to be involved in psychoneurobiological processes underlying mood disorders. Interactions between stimuli may subjected to time effects. Time-dependencies of interactions between stimuli typically lead to complex cell responses and complex responses on the behavioural level. We show that both three-factor models and time series models can be used to uncover such time-dependencies. However, we argue that for short longitudinal data the three factor modelling approach is more suitable. In order to illustrate both approaches, we re-analysed previously published short longitudinal data sets. We found that in human embryonic kidney 293 cells cells the interaction effect in the regulation of extracellular signal-regulated kinase (ERK) 1 signalling activation by insulin and epidermal growth factor is subjected to a time effect and dramatically decays at peak values of ERK activation. In contrast, we found that the interaction effect induced by hypoxia and tumour necrosis factor-alpha for the transcriptional activity of the human cyclo-oxygenase-2 promoter in HEK293 cells is time invariant at least in the first 12-h time window after stimulation. Furthermore, we applied the three-factor model to previously reported animal studies. In these studies, memory storage was found to be subjected to an interaction effect of the beta-adrenoceptor agonist clenbuterol and certain antagonists acting on the alpha-1-adrenoceptor / glucocorticoid-receptor system. Our model-based analysis suggests that only if the antagonist drug is administer in a critical time window, then the interaction effect is relevant. © The authors 2016. Published by Oxford University Press on behalf of the Institute of Mathematics and its Applications. All rights reserved.

Fractional Models Simulating Non-Fickian Behavior in Four-Stage Single-Well Push-Pull Tests

NASA Astrophysics Data System (ADS)

Chen, Kewei; Zhan, Hongbin; Yang, Qiang

2017-11-01

Four-stage single-well push-pull (SWPP) tracer tests, including injection, chasing, resting, and pumping, were conducted in a fractured aquifer at Newark basin. An anomalous transport phenomenon observed in the SWPP tests is the linear decline of breakthrough curves (BTCs) at late time with slope of -1.8 in log-log plots. A time-dependent fractional model is developed to interpret the anomalous transport behavior. This model considers a time-dependent power law memory function and a time-dependent fractional advection-dispersion operator. The fractional advection-dispersion equations (fADE) are solved in a radial coordinate system using the implicit Euler method. A semi-analytical solution of the first-order rate-limited mobile-immobile model (FORMIM) is derived for comparison. It is found that both the nonlocal transport in time and space can produce the long-tailed BTC. A smaller time-fractional or space-fractional index leads to a lower peak concentration and a larger late-time slope. The mass distribution of the fractional-in-space (FS) model exhibits power law decline at the leading plume edge. Early breakthrough during pumping is not observed because the mobile mass at the start of pumping is nonzero and more concentrated near the wellbore. The capacity ratio is an important factor that affects the peak concentration. A larger capacity ratio leads to greater peak concentration. A smaller time-fractional index in the injection, chasing, or resting stage will move the BTC downward and the slope of the late time BTC is determined by the space-fractional index over all stages and the time-fractional index in the pumping stage. The capability of the existing models to recover the BTC of the SWPP test is discussed and some guidelines for how to choose the appropriate model to interpret the SWPP test data are proposed.

Ethylene regulates Apple (Malus x domestica) fruit softening through a dose x time-dependent mechanism and through differential sensitivities and dependencies of cell wall-modifying genes.

PubMed

Ireland, Hilary S; Gunaseelan, Kularajathevan; Muddumage, Ratnasiri; Tacken, Emma J; Putterill, Jo; Johnston, Jason W; Schaffer, Robert J

2014-05-01

In fleshy fruit species that have a strong requirement for ethylene to ripen, ethylene is synthesized autocatalytically, producing increasing concentrations as the fruits ripen. Apple fruit with the ACC OXIDASE 1 (ACO1) gene suppressed cannot produce ethylene autocatalytically at ripening. Using these apple lines, an ethylene sensitivity dependency model was previously proposed, with traits such as softening showing a high dependency for ethylene as well as low sensitivity. In this study, it is shown that the molecular control of fruit softening is a complex process, with different cell wall-related genes being independently regulated and exhibiting differential sensitivities to and dependencies on ethylene at the transcriptional level. This regulation is controlled through a dose × time mechanism, which results in a temporal transcriptional response that would allow for progressive cell wall disassembly and thus softening. This research builds on the sensitivity dependency model and shows that ethylene-dependent traits can progress over time to the same degree with lower levels of ethylene. This suggests that a developmental clock measuring cumulative ethylene controls the fruit ripening process.

Microstructural indicators of transition mechanisms in time-dependent fatigue crack growth in nickel base superalloys

NASA Astrophysics Data System (ADS)

Heeter, Ann E.

Gas turbine engines are an important part of power generation in modern society, especially in the field of aerospace. Aerospace engines are design to last approximately 30 years and the engine components must be designed to survive for the life of the engine or to be replaced at regular intervals to ensure consumer safety. Fatigue crack growth analysis is a vital component of design for an aerospace component. Crack growth modeling and design methods date back to an origin around 1950 with a high rate of accuracy. The new generation of aerospace engines is designed to be efficient as possible and require higher operating temperatures than ever seen before in previous generations. These higher temperatures place more stringent requirements on the material crack growth performance under creep and time dependent conditions. Typically the types of components which are subject to these requirements are rotating disk components which are made from advanced materials such as nickel base superalloys. Traditionally crack growth models have looked at high temperature crack growth purely as a function of temperature and assumed that all crack growth was either controlled by a cycle dependent or time dependent mechanism. This new analysis is trying to evaluate the transition between cycle-dependent and time-dependent mechanism and the microstructural markers that characterize this transitional behavior. The physical indications include both the fracture surface morphology as well as the shape of the crack front. The research will evaluate whether crack tunneling occurs and whether it consistently predicts a transition from cycle-dependent crack growth to time-dependent crack growth. The study is part of a larger research program trying to include the effects of geometry, mission profile and environmental effects, in addition to temperature effects, as a part of the overall crack growth system. The outcome will provide evidence for various transition types and correlate those physical attributes back to the material mechanisms to improve predictive modeling capability.

Calculating Path-Dependent Travel Time Prediction Variance and Covariance fro a Global Tomographic P-Velocity Model

NASA Astrophysics Data System (ADS)

Ballard, S.; Hipp, J. R.; Encarnacao, A.; Young, C. J.; Begnaud, M. L.; Phillips, W. S.

2012-12-01

Seismic event locations can be made more accurate and precise by computing predictions of seismic travel time through high fidelity 3D models of the wave speed in the Earth's interior. Given the variable data quality and uneven data sampling associated with this type of model, it is essential that there be a means to calculate high-quality estimates of the path-dependent variance and covariance associated with the predicted travel times of ray paths through the model. In this paper, we describe a methodology for accomplishing this by exploiting the full model covariance matrix and show examples of path-dependent travel time prediction uncertainty computed from SALSA3D, our global, seamless 3D tomographic P-velocity model. Typical global 3D models have on the order of 1/2 million nodes, so the challenge in calculating the covariance matrix is formidable: 0.9 TB storage for 1/2 of a symmetric matrix, necessitating an Out-Of-Core (OOC) blocked matrix solution technique. With our approach the tomography matrix (G which includes Tikhonov regularization terms) is multiplied by its transpose (GTG) and written in a blocked sub-matrix fashion. We employ a distributed parallel solution paradigm that solves for (GTG)-1 by assigning blocks to individual processing nodes for matrix decomposition update and scaling operations. We first find the Cholesky decomposition of GTG which is subsequently inverted. Next, we employ OOC matrix multiplication methods to calculate the model covariance matrix from (GTG)-1 and an assumed data covariance matrix. Given the model covariance matrix, we solve for the travel-time covariance associated with arbitrary ray-paths by summing the model covariance along both ray paths. Setting the paths equal and taking the square root yields the travel prediction uncertainty for the single path.

Development of a unified constitutive model for an isotropic nickel base superalloy Rene 80

NASA Technical Reports Server (NTRS)

Ramaswamy, V. G.; Vanstone, R. H.; Laflen, J. H.; Stouffer, D. C.

1988-01-01

Accurate analysis of stress-strain behavior is of critical importance in the evaluation of life capabilities of hot section turbine engine components such as turbine blades and vanes. The constitutive equations used in the finite element analysis of such components must be capable of modeling a variety of complex behavior exhibited at high temperatures by cast superalloys. The classical separation of plasticity and creep employed in most of the finite element codes in use today is known to be deficient in modeling elevated temperature time dependent phenomena. Rate dependent, unified constitutive theories can overcome many of these difficulties. A new unified constitutive theory was developed to model the high temperature, time dependent behavior of Rene' 80 which is a cast turbine blade and vane nickel base superalloy. Considerations in model development included the cyclic softening behavior of Rene' 80, rate independence at lower temperatures and the development of a new model for static recovery.

Computer Modeling of Non-Isothermal Crystallization

NASA Technical Reports Server (NTRS)

Kelton, K. F.; Narayan, K. Lakshmi; Levine, L. E.; Cull, T. C.; Ray, C. S.

1996-01-01

A realistic computer model for simulating isothermal and non-isothermal phase transformations proceeding by homogeneous and heterogeneous nucleation and interface-limited growth is presented. A new treatment for particle size effects on the crystallization kinetics is developed and is incorporated into the numerical model. Time-dependent nucleation rates, size-dependent growth rates, and surface crystallization are also included. Model predictions are compared with experimental measurements of DSC/DTA peak parameters for the crystallization of lithium disilicate glass as a function of particle size, Pt doping levels, and water content. The quantitative agreement that is demonstrated indicates that the numerical model can be used to extract key kinetic data from easily obtained calorimetric data. The model can also be used to probe nucleation and growth behavior in regimes that are otherwise inaccessible. Based on a fit to data, an earlier prediction that the time-dependent nucleation rate in a DSC/DTA scan can rise above the steady-state value at a temperature higher than the peak in the steady-state rate is demonstrated.

Static and Impulsive Models of Solar Active Regions

NASA Technical Reports Server (NTRS)

Patsourakos, S.; Klimchuk, James A.

2008-01-01

The physical modeling of active regions (ARs) and of the global coronal is receiving increasing interest lately. Recent attempts to model ARs using static equilibrium models were quite successful in reproducing AR images of hot soft X-ray (SXR) loops. They however failed to predict the bright EUV warm loops permeating ARs: the synthetic images were dominated by intense footpoint emission. We demonstrate that this failure is due to the very weak dependence of loop temperature on loop length which cannot simultaneously account for both hot and warm loops in the same AR. We then consider time-dependent AR models based on nanoflare heating. We demonstrate that such models can simultaneously reproduce EUV and SXR loops in ARs. Moreover, they predict radial intensity variations consistent with the localized core and extended emissions in SXR and EUV AR observations respectively. We finally show how the AR morphology can be used as a gauge of the properties (duration, energy, spatial dependence, repetition time) of the impulsive heating.

Maximum likelihood estimation for semiparametric transformation models with interval-censored data

PubMed Central

Mao, Lu; Lin, D. Y.

2016-01-01

Abstract Interval censoring arises frequently in clinical, epidemiological, financial and sociological studies, where the event or failure of interest is known only to occur within an interval induced by periodic monitoring. We formulate the effects of potentially time-dependent covariates on the interval-censored failure time through a broad class of semiparametric transformation models that encompasses proportional hazards and proportional odds models. We consider nonparametric maximum likelihood estimation for this class of models with an arbitrary number of monitoring times for each subject. We devise an EM-type algorithm that converges stably, even in the presence of time-dependent covariates, and show that the estimators for the regression parameters are consistent, asymptotically normal, and asymptotically efficient with an easily estimated covariance matrix. Finally, we demonstrate the performance of our procedures through simulation studies and application to an HIV/AIDS study conducted in Thailand. PMID:27279656

A global time-dependent model of thunderstorm electricity. I - Mathematical properties of the physical and numerical models

NASA Technical Reports Server (NTRS)

Browning, G. L.; Tzur, I.; Roble, R. G.

1987-01-01

A time-dependent model is introduced that can be used to simulate the interaction of a thunderstorm with its global electrical environment. The model solves the continuity equation of the Maxwell current, which is assumed to be composed of the conduction, displacement, and source currents. Boundary conditions which can be used in conjunction with the continuity equation to form a well-posed initial-boundary value problem are determined. Properties of various components of solutions of the initial-boundary value problem are analytically determined. The results indicate that the problem has two time scales, one determined by the background electrical conductivity and the other by the time variation of the source function. A numerical method for obtaining quantitative results is introduced, and its properties are studied. Some simulation results on the evolution of the displacement and conduction currents during the electrification of a storm are presented.

Reversible and Irreversible Time-Dependent Behavior of GRCop-84

NASA Technical Reports Server (NTRS)

Lerch, Bradley A.; Arnold, Steven M.; Ellis, David L.

2017-01-01

A series of mechanical tests were conducted on a high-conductivity copper alloy, GRCop-84, in order to understand the time dependent response of this material. Tensile, creep, and stress relaxation tests were performed over a wide range of temperatures, strain rates, and stress levels to excite various amounts of time-dependent behavior. At low applied stresses the deformation behavior was found to be fully reversible. Above a certain stress, termed the viscoelastic threshold, irreversible deformation was observed. At these higher stresses the deformation was observed to be viscoplastic. Both reversible and irreversible regions contained time dependent deformation. These experimental data are documented to enable characterization of constitutive models to aid in design of high temperature components.

Time-dependent clustering analysis of the second BATSE gamma-ray burst catalog

NASA Technical Reports Server (NTRS)

Brainerd, J. J.; Meegan, C. A.; Briggs, Michael S.; Pendleton, G. N.; Brock, M. N.

1995-01-01

A time-dependent two-point correlation-function analysis of the Burst and Transient Source Experiment (BATSE) 2B catalog finds no evidence of burst repetition. As part of this analysis, we discuss the effects of sky exposure on the observability of burst repetition and present the equation describing the signature of burst repetition in the data. For a model of all burst repetition from a source occurring in less than five days we derive upper limits on the number of bursts in the catalog from repeaters and model-dependent upper limits on the fraction of burst sources that produce multiple outbursts.

Time-Dependent Damage Investigation of Rock Mass in an In Situ Experimental Tunnel

PubMed Central

Jiang, Quan; Cui, Jie; Chen, Jing

2012-01-01

In underground tunnels or caverns, time-dependent deformation or failure of rock mass, such as extending cracks, gradual rock falls, etc., are a costly irritant and a major safety concern if the time-dependent damage of surrounding rock is serious. To understand the damage evolution of rock mass in underground engineering, an in situ experimental testing was carried out in a large belowground tunnel with a scale of 28.5 m in width, 21 m in height and 352 m in length. The time-dependent damage of rock mass was detected in succession by an ultrasonic wave test after excavation. The testing results showed that the time-dependent damage of rock mass could last a long time, i.e., nearly 30 days. Regression analysis of damage factors defined by wave velocity, resulted in the time-dependent evolutional damage equation of rock mass, which corresponded with logarithmic format. A damage viscoelastic-plastic model was developed to describe the exposed time-dependent deterioration of rock mass by field test, such as convergence of time-dependent damage, deterioration of elastic modules and logarithmic format of damage factor. Furthermore, the remedial measures for damaged surrounding rock were discussed based on the measured results and the conception of damage compensation, which provides new clues for underground engineering design.

Generalized Success-Breeds-Success Principle Leading to Time-Dependent Informetric Distributions.

ERIC Educational Resources Information Center

Egghe, Leo; Rousseau, Ronald

1995-01-01

Reformulates the success-breeds-success (SBS) principle in informetrics in order to generate a general theory of source-item relationships. Topics include a time-dependent probability, a new model for the expected probability that is compared with the SBS principle with exact combinatorial calculations, classical frequency distributions, and…

Size-dependent geometrically nonlinear free vibration analysis of fractional viscoelastic nanobeams based on the nonlocal elasticity theory

NASA Astrophysics Data System (ADS)

Ansari, R.; Faraji Oskouie, M.; Gholami, R.

2016-01-01

In recent decades, mathematical modeling and engineering applications of fractional-order calculus have been extensively utilized to provide efficient simulation tools in the field of solid mechanics. In this paper, a nonlinear fractional nonlocal Euler-Bernoulli beam model is established using the concept of fractional derivative and nonlocal elasticity theory to investigate the size-dependent geometrically nonlinear free vibration of fractional viscoelastic nanobeams. The non-classical fractional integro-differential Euler-Bernoulli beam model contains the nonlocal parameter, viscoelasticity coefficient and order of the fractional derivative to interpret the size effect, viscoelastic material and fractional behavior in the nanoscale fractional viscoelastic structures, respectively. In the solution procedure, the Galerkin method is employed to reduce the fractional integro-partial differential governing equation to a fractional ordinary differential equation in the time domain. Afterwards, the predictor-corrector method is used to solve the nonlinear fractional time-dependent equation. Finally, the influences of nonlocal parameter, order of fractional derivative and viscoelasticity coefficient on the nonlinear time response of fractional viscoelastic nanobeams are discussed in detail. Moreover, comparisons are made between the time responses of linear and nonlinear models.

Continuum modeling of rate-dependent granular flows in SPH

DOE PAGES

Hurley, Ryan C.; Andrade, José E.

2016-09-13

In this paper, we discuss a constitutive law for modeling rate-dependent granular flows that has been implemented in smoothed particle hydrodynamics (SPH). We model granular materials using a viscoplastic constitutive law that produces a Drucker–Prager-like yield condition in the limit of vanishing flow. A friction law for non-steady flows, incorporating rate-dependence and dilation, is derived and implemented within the constitutive law. We compare our SPH simulations with experimental data, demonstrating that they can capture both steady and non-steady dynamic flow behavior, notably including transient column collapse profiles. In conclusion, this technique may therefore be attractive for modeling the time-dependent evolutionmore » of natural and industrial flows.« less

Studies on energy transfer in dendrimer supermolecule using classical random walk model and Eyring model

NASA Astrophysics Data System (ADS)

Rana, Dipankar; Gangopadhyay, Gautam

2003-01-01

We have analyzed the energy transfer process in a dendrimer supermolecule using a classical random walk model and an Eyring model of membrane permeation. Here the energy transfer is considered as a multiple barrier crossing process by thermal hopping on the backbone of a cayley tree. It is shown that the mean residence time and mean first passage time, which involve explicit local escape rates, depend upon the temperature, size of the molecule, core branching, and the nature of the potential energy landscape along the cayley tree architecture. The effect of branching tries to create a uniform distribution of mean residence time over the generations and the distribution depends upon the interplay of funneling and local rates of transitions. The calculation of flux at the steady state from the Eyring model also gives a useful idea about the rate when the dendrimeric system is considered as an open system where the core is absorbing the transported energy like a photosynthetic reaction center and a continuous supply of external energy is maintained at the peripheral nodes. The effect of the above parameters of the system are shown to depend on the steady-state flux that has a qualitative resemblence with the result of the mean first passage time approach.

Rate of progression from first use to dependence on cocaine or opioids: a cross-substance examination of associated demographic, psychiatric, and childhood risk factors.

PubMed

Sartor, Carolyn E; Kranzler, Henry R; Gelernter, Joel

2014-02-01

A number of demographic factors, psychiatric disorders, and childhood risk factors have been associated with cocaine dependence (CD) and opioid dependence (OD), but little is known about their relevance to the rate at which dependence develops. Identification of the subpopulations at elevated risk for rapid development of dependence and the risk factors that accelerate the course of dependence is an important public health goal. Data were derived from cocaine dependent (n=6333) and opioid dependent (n=3513) participants in a multi-site study of substance dependence. Mean age was approximately 40 and 40% of participants were women; 51.9% of cocaine dependent participants and 29.5% of opioid dependent participants self-identified as Black/African-American. The time from first use to dependence was calculated for each substance and a range of demographic, psychiatric, and childhood risk factors were entered into ordinal logistic regression models to predict the (categorical) transition time to CD and OD. In both the cocaine and opioid models, conduct disorder and childhood physical abuse predicted rapid development of dependence and alcohol and nicotine dependence diagnoses were associated with slower progression to CD or OD. Blacks/African Americans were at greater risk than European Americans to progress rapidly to OD. Only a subset of factors known to be associated with CD and OD predicted the rate at which dependence developed. Nearly all were common to cocaine and opioids, suggesting that sources of influence on the timing of transitions to dependence are shared across the two substances. © 2013.

Factors influencing crime rates: an econometric analysis approach

NASA Astrophysics Data System (ADS)

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

2016-05-01

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

Recalculated probability of M ≥ 7 earthquakes beneath the Sea of Marmara, Turkey

USGS Publications Warehouse

Parsons, T.

2004-01-01

New earthquake probability calculations are made for the Sea of Marmara region and the city of Istanbul, providing a revised forecast and an evaluation of time-dependent interaction techniques. Calculations incorporate newly obtained bathymetric images of the North Anatolian fault beneath the Sea of Marmara [Le Pichon et al., 2001; Armijo et al., 2002]. Newly interpreted fault segmentation enables an improved regional A.D. 1500-2000 earthquake catalog and interevent model, which form the basis for time-dependent probability estimates. Calculations presented here also employ detailed models of coseismic and postseismic slip associated with the 17 August 1999 M = 7.4 Izmit earthquake to investigate effects of stress transfer on seismic hazard. Probability changes caused by the 1999 shock depend on Marmara Sea fault-stressing rates, which are calculated with a new finite element model. The combined 2004-2034 regional Poisson probability of M≥7 earthquakes is ~38%, the regional time-dependent probability is 44 ± 18%, and incorporation of stress transfer raises it to 53 ± 18%. The most important effect of adding time dependence and stress transfer to the calculations is an increase in the 30 year probability of a M ??? 7 earthquake affecting Istanbul. The 30 year Poisson probability at Istanbul is 21%, and the addition of time dependence and stress transfer raises it to 41 ± 14%. The ranges given on probability values are sensitivities of the calculations to input parameters determined by Monte Carlo analysis; 1000 calculations are made using parameters drawn at random from distributions. Sensitivities are large relative to mean probability values and enhancements caused by stress transfer, reflecting a poor understanding of large-earthquake aperiodicity.

Random walk in degree space and the time-dependent Watts-Strogatz model

NASA Astrophysics Data System (ADS)

Casa Grande, H. L.; Cotacallapa, M.; Hase, M. O.

2017-01-01

In this work, we propose a scheme that provides an analytical estimate for the time-dependent degree distribution of some networks. This scheme maps the problem into a random walk in degree space, and then we choose the paths that are responsible for the dominant contributions. The method is illustrated on the dynamical versions of the Erdős-Rényi and Watts-Strogatz graphs, which were introduced as static models in the original formulation. We have succeeded in obtaining an analytical form for the dynamics Watts-Strogatz model, which is asymptotically exact for some regimes.

Random walk in degree space and the time-dependent Watts-Strogatz model.

PubMed

Casa Grande, H L; Cotacallapa, M; Hase, M O

2017-01-01

In this work, we propose a scheme that provides an analytical estimate for the time-dependent degree distribution of some networks. This scheme maps the problem into a random walk in degree space, and then we choose the paths that are responsible for the dominant contributions. The method is illustrated on the dynamical versions of the Erdős-Rényi and Watts-Strogatz graphs, which were introduced as static models in the original formulation. We have succeeded in obtaining an analytical form for the dynamics Watts-Strogatz model, which is asymptotically exact for some regimes.

Measured Visual Motion Sensitivity at Fixed Contrast in the Periphery and Far Periphery

DTIC Science & Technology

2017-08-01

group Soldier performance. Soldier performance depends on visual detection of enemy personnel and materiel. Vision modeling in IWARS is neither...a highly time-critical and order- dependent activity, these unrealistic characterizations of target detection time and order severely limit the...recognize that MVTs should depend on target contrast, so we selected a target design different from that used in the Monaco et al. (2007) study. Based

Evidence for history-dependence of influenza pandemic emergence

NASA Astrophysics Data System (ADS)

Hill, Edward M.; Tildesley, Michael J.; House, Thomas

2017-03-01

Influenza A viruses have caused a number of global pandemics, with considerable mortality in humans. Here, we analyse the time periods between influenza pandemics since 1700 under different assumptions to determine whether the emergence of new pandemic strains is a memoryless or history-dependent process. Bayesian model selection between exponential and gamma distributions for these time periods gives support to the hypothesis of history-dependence under eight out of nine sets of modelling assumptions. Using the fitted parameters to make predictions shows a high level of variability in the modelled number of pandemics from 2010-2110. The approach we take here relies on limited data, so is uncertain, but it provides cheap, safe and direct evidence relating to pandemic emergence, a field where indirect measurements are often made at great risk and cost.

Effect of a Starting Model on the Solution of a Travel Time Seismic Tomography Problem

NASA Astrophysics Data System (ADS)

Yanovskaya, T. B.; Medvedev, S. V.; Gobarenko, V. S.

2018-03-01

In the problems of three-dimensional (3D) travel time seismic tomography where the data are travel times of diving waves and the starting model is a system of plane layers where the velocity is a function of depth alone, the solution turns out to strongly depend on the selection of the starting model. This is due to the fact that in the different starting models, the rays between the same points can intersect different layers, which makes the tomography problem fundamentally nonlinear. This effect is demonstrated by the model example. Based on the same example, it is shown how the starting model should be selected to ensure a solution close to the true velocity distribution. The starting model (the average dependence of the seismic velocity on depth) should be determined by the method of successive iterations at each step of which the horizontal velocity variations in the layers are determined by solving the two-dimensional tomography problem. An example illustrating the application of this technique to the P-wave travel time data in the region of the Black Sea basin is presented.

[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

PubMed

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

Combined risk assessment of nonstationary monthly water quality based on Markov chain and time-varying copula.

PubMed

Shi, Wei; Xia, Jun

2017-02-01

Water quality risk management is a global hot research linkage with the sustainable water resource development. Ammonium nitrogen (NH 3 -N) and permanganate index (COD Mn ) as the focus indicators in Huai River Basin, are selected to reveal their joint transition laws based on Markov theory. The time-varying moments model with either time or land cover index as explanatory variables is applied to build the time-varying marginal distributions of water quality time series. Time-varying copula model, which takes the non-stationarity in the marginal distribution and/or the time variation in dependence structure between water quality series into consideration, is constructed to describe a bivariate frequency analysis for NH 3 -N and COD Mn series at the same monitoring gauge. The larger first-order Markov joint transition probability indicates water quality state Class V w , Class IV and Class III will occur easily in the water body of Bengbu Sluice. Both marginal distribution and copula models are nonstationary, and the explanatory variable time yields better performance than land cover index in describing the non-stationarities in the marginal distributions. In modelling the dependence structure changes, time-varying copula has a better fitting performance than the copula with the constant or the time-trend dependence parameter. The largest synchronous encounter risk probability of NH 3 -N and COD Mn simultaneously reaching Class V is 50.61%, while the asynchronous encounter risk probability is largest when NH 3 -N and COD Mn is inferior to class V and class IV water quality standards, respectively.

A model-free characterization of recurrences in stationary time series

NASA Astrophysics Data System (ADS)

Chicheportiche, Rémy; Chakraborti, Anirban

2017-05-01

Study of recurrences in earthquakes, climate, financial time-series, etc. is crucial to better forecast disasters and limit their consequences. Most of the previous phenomenological studies of recurrences have involved only a long-ranged autocorrelation function, and ignored the multi-scaling properties induced by potential higher order dependencies. We argue that copulas is a natural model-free framework to study non-linear dependencies in time series and related concepts like recurrences. Consequently, we arrive at the facts that (i) non-linear dependences do impact both the statistics and dynamics of recurrence times, and (ii) the scaling arguments for the unconditional distribution may not be applicable. Hence, fitting and/or simulating the intertemporal distribution of recurrence intervals is very much system specific, and cannot actually benefit from universal features, in contrast to the previous claims. This has important implications in epilepsy prognosis and financial risk management applications.

Time-dependent MHD simulations of the solar wind outflow using interplanetary scintillation observations

DOE PAGES

Kim, Tae K.; Pogorelov, Nikolai V.; Borovikov, Sergey N.; ...

2012-11-20

Numerical modeling of the heliosphere is a critical component of space weather forecasting. The accuracy of heliospheric models can be improved by using realistic boundary conditions and confirming the results with in situ spacecraft measurements. To accurately reproduce the solar wind (SW) plasma flow near Earth, we need realistic, time-dependent boundary conditions at a fixed distance from the Sun. We may prepare such boundary conditions using SW speed and density determined from interplanetary scintillation (IPS) observations, magnetic field derived from photospheric magnetograms, and temperature estimated from its correlation with SW speed. In conclusion, we present here the time-dependent MHD simulationmore » results obtained by using the 2011 IPS data from the Solar-Terrestrial Environment Laboratory as time-varying inner boundary conditions and compare the simulated data at Earth with OMNI data (spacecraft-interspersed, near-Earth solar wind data).« less

Rate heterogeneity across Squamata, misleading ancestral state reconstruction and the importance of proper null model specification.

PubMed

Harrington, S; Reeder, T W

2017-02-01

The binary-state speciation and extinction (BiSSE) model has been used in many instances to identify state-dependent diversification and reconstruct ancestral states. However, recent studies have shown that the standard procedure of comparing the fit of the BiSSE model to constant-rate birth-death models often inappropriately favours the BiSSE model when diversification rates vary in a state-independent fashion. The newly developed HiSSE model enables researchers to identify state-dependent diversification rates while accounting for state-independent diversification at the same time. The HiSSE model also allows researchers to test state-dependent models against appropriate state-independent null models that have the same number of parameters as the state-dependent models being tested. We reanalyse two data sets that originally used BiSSE to reconstruct ancestral states within squamate reptiles and reached surprising conclusions regarding the evolution of toepads within Gekkota and viviparity across Squamata. We used this new method to demonstrate that there are many shifts in diversification rates across squamates. We then fit various HiSSE submodels and null models to the state and phylogenetic data and reconstructed states under these models. We found that there is no single, consistent signal for state-dependent diversification associated with toepads in gekkotans or viviparity across all squamates. Our reconstructions show limited support for the recently proposed hypotheses that toepads evolved multiple times independently in Gekkota and that transitions from viviparity to oviparity are common in Squamata. Our results highlight the importance of considering an adequate pool of models and null models when estimating diversification rate parameters and reconstructing ancestral states. © 2016 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2016 European Society For Evolutionary Biology.

Hysteresis in the Cell Response to Time-Dependent Substrate Stiffness

PubMed Central

Besser, Achim; Schwarz, Ulrich S.

2010-01-01

Abstract Mechanical cues like the rigidity of the substrate are main determinants for the decision-making of adherent cells. Here we use a mechano-chemical model to predict the cellular response to varying substrate stiffnesses. The model equations combine the mechanics of contractile actin filament bundles with a model for the Rho-signaling pathway triggered by forces at cell-matrix contacts. A bifurcation analysis of cellular contractility as a function of substrate stiffness reveals a bistable response, thus defining a lower threshold of stiffness, below which cells are not able to build up contractile forces, and an upper threshold of stiffness, above which cells are always in a strongly contracted state. Using the full dynamical model, we predict that rate-dependent hysteresis will occur in the cellular traction forces when cells are exposed to substrates of time-dependent stiffness. PMID:20655823

Two-state model of light induced activation and thermal bleaching of photochromic glasses: theory and experiments

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

Ferrari, Jose A.; Perciante, Cesar D

2008-07-10

The behavior of photochromic glasses during activation and bleaching is investigated. A two-state phenomenological model describing light-induced activation (darkening) and thermal bleaching is presented. The proposed model is based on first-order kinetics. We demonstrate that the time behavior in the activation process (acting simultaneously with the thermal fading) can be characterized by two relaxation times that depend on the intensity of the activating light. These characteristic times are lower than the decay times of the pure thermal bleaching process. We study the temporal evolution of the glass optical density and its dependence on the activating intensity. We also present amore » series of activation and bleaching experiments that validate the proposed model. Our approach may be used to gain more insight into the transmittance behavior of photosensitive glasses, which could be potentially relevant in a broad range of applications, e.g., real-time holography and reconfigurable optical memories.« less

Modeling the degradation mechanisms of C6/LiFePO4 batteries

NASA Astrophysics Data System (ADS)

Li, Dongjiang; Danilov, Dmitri L.; Zwikirsch, Barbara; Fichtner, Maximilian; Yang, Yong; Eichel, Rüdiger-A.; Notten, Peter H. L.

2018-01-01

A fundamental electrochemical model is developed, describing the capacity fade of C6/LiFePO4 batteries as a function of calendar time and cycling conditions. At moderate temperatures the capacity losses are mainly attributed to Li immobilization in Solid-Electrolyte-Interface (SEI) layers at the anode surface. The SEI formation model presumes the availability of an outer and inner SEI layers. Electron tunneling through the inner SEI layer is regarded as the rate-determining step. The model also includes high temperature degradation. At elevated temperatures, iron dissolution from the positive electrode and the subsequent metal sedimentation on the negative electrode influence the capacity loss. The SEI formation on the metal-covered graphite surface is faster than the conventional SEI formation. The model predicts that capacity fade during storage is lower than during cycling due to the generation of SEI cracks induced by the volumetric changes during (dis)charging. The model has been validated by cycling and calendar aging experiments and shows that the capacity loss during storage depends on the storage time, the State-of-Charge (SoC), and temperature. The capacity losses during cycling depend on the cycling current, cycling time, temperature and cycle number. All these dependencies can be explained by the single model presented in this paper.

Reconstruction of the action potential of ventricular myocardial fibres

PubMed Central

Beeler, G. W.; Reuter, H.

1977-01-01

1. A mathematical model of membrane action potentials of mammalian ventricular myocardial fibres is described. The reconstruction model is based as closely as possible on ionic currents which have been measured by the voltage-clamp method. 2. Four individual components of ionic current were formulated mathematically in terms of Hodgkin—Huxley type equations. The model incorporates two voltage- and time-dependent inward currents, the excitatory inward sodium current, iNa, and a secondary or slow inward current, is, primarily carried by calcium ions. A time-independent outward potassium current, iK1, exhibiting inward-going rectification, and a voltage- and time-dependent outward current, ix1, primarily carried by potassium ions, are further elements of the model. 3. The iNa is primarily responsible for the rapid upstroke of the action potential, while the other current components determine the configuration of the plateau of the action potential and the re-polarization phase. The relative importance of inactivation of is and of activation of ix1 for termination of the plateau is evaluated by the model. 4. Experimental phenomena like slow recovery of the sodium system from inactivation, frequency dependence of the action potential duration, all-or-nothing re-polarization, membrane oscillations are adequately described by the model. 5. Possible inadequacies and shortcomings of the model are discussed. PMID:874889

Computer simulation of earthquakes

NASA Technical Reports Server (NTRS)

Cohen, S. C.

1976-01-01

Two computer simulation models of earthquakes were studied for the dependence of the pattern of events on the model assumptions and input parameters. Both models represent the seismically active region by mechanical blocks which are connected to one another and to a driving plate. The blocks slide on a friction surface. In the first model elastic forces were employed and time independent friction to simulate main shock events. The size, length, and time and place of event occurrence were influenced strongly by the magnitude and degree of homogeniety in the elastic and friction parameters of the fault region. Periodically reoccurring similar events were frequently observed in simulations with near homogeneous parameters along the fault, whereas, seismic gaps were a common feature of simulations employing large variations in the fault parameters. The second model incorporated viscoelastic forces and time-dependent friction to account for aftershock sequences. The periods between aftershock events increased with time and the aftershock region was confined to that which moved in the main event.

Time-dependent i-DFT exchange-correlation potentials with memory: applications to the out-of-equilibrium Anderson model

NASA Astrophysics Data System (ADS)

Kurth, Stefan; Stefanucci, Gianluca

2018-06-01

We have recently put forward a steady-state density functional theory (i-DFT) to calculate the transport coefficients of quantum junctions. Within i-DFT it is possible to obtain the steady density on and the steady current through an interacting junction using a fictitious noninteracting junction subject to an effective gate and bias potential. In this work we extend i-DFT to the time domain for the single-impurity Anderson model. By a reverse engineering procedure we extract the exchange-correlation (xc) potential and xc bias at temperatures above the Kondo temperature T K. The derivation is based on a generalization of a recent paper by Dittmann et al. [N. Dittmann et al., Phys. Rev. Lett. 120, 157701 (2018)]. Interestingly the time-dependent (TD) i-DFT potentials depend on the system's history only through the first time-derivative of the density. We perform numerical simulations of the early transient current and investigate the role of the history dependence. We also empirically extend the history-dependent TD i-DFT potentials to temperatures below T K. For this purpose we use a recently proposed parametrization of the i-DFT potentials which yields highly accurate results in the steady state.

Rainfall disaggregation for urban hydrology: Effects of spatial consistence

NASA Astrophysics Data System (ADS)

Müller, Hannes; Haberlandt, Uwe

2015-04-01

For urban hydrology rainfall time series with a high temporal resolution are crucial. Observed time series of this kind are very short in most cases, so they cannot be used. On the contrary, time series with lower temporal resolution (daily measurements) exist for much longer periods. The objective is to derive time series with a long duration and a high resolution by disaggregating time series of the non-recording stations with information of time series of the recording stations. The multiplicative random cascade model is a well-known disaggregation model for daily time series. For urban hydrology it is often assumed, that a day consists of only 1280 minutes in total as starting point for the disaggregation process. We introduce a new variant for the cascade model, which is functional without this assumption and also outperforms the existing approach regarding time series characteristics like wet and dry spell duration, average intensity, fraction of dry intervals and extreme value representation. However, in both approaches rainfall time series of different stations are disaggregated without consideration of surrounding stations. This yields in unrealistic spatial patterns of rainfall. We apply a simulated annealing algorithm that has been used successfully for hourly values before. Relative diurnal cycles of the disaggregated time series are resampled to reproduce the spatial dependence of rainfall. To describe spatial dependence we use bivariate characteristics like probability of occurrence, continuity ratio and coefficient of correlation. Investigation area is a sewage system in Northern Germany. We show that the algorithm has the capability to improve spatial dependence. The influence of the chosen disaggregation routine and the spatial dependence on overflow occurrences and volumes of the sewage system will be analyzed.

Post-seismic and interseismic fault creep I: model description

NASA Astrophysics Data System (ADS)

Hetland, E. A.; Simons, M.; Dunham, E. M.

2010-04-01

We present a model of localized, aseismic fault creep during the full interseismic period, including both transient and steady fault creep, in response to a sequence of imposed coseismic slip events and tectonic loading. We consider the behaviour of models with linear viscous, non-linear viscous, rate-dependent friction, and rate- and state-dependent friction fault rheologies. Both the transient post-seismic creep and the pattern of steady interseismic creep rates surrounding asperities depend on recent coseismic slip and fault rheologies. In these models, post-seismic fault creep is manifest as pulses of elevated creep rates that propagate from the coseismic slip, these pulses feature sharper fronts and are longer lived in models with rate-state friction compared to other models. With small characteristic slip distances in rate-state friction models, interseismic creep is similar to that in models with rate-dependent friction faults, except for the earliest periods of post-seismic creep. Our model can be used to constrain fault rheologies from geodetic observations in cases where the coseismic slip history is relatively well known. When only considering surface deformation over a short period of time, there are strong trade-offs between fault rheology and the details of the imposed coseismic slip. Geodetic observations over longer times following an earthquake will reduce these trade-offs, while simultaneous modelling of interseismic and post-seismic observations provide the strongest constraints on fault rheologies.

Heterogeneity of human adipose blood flow

PubMed Central

Levitt, David G

2007-01-01

Background The long time pharmacokinetics of highly lipid soluble compounds is dominated by blood-adipose tissue exchange and depends on the magnitude and heterogeneity of adipose blood flow. Because the adipose tissue is an infinite sink at short times (hours), the kinetics must be followed for days in order to determine if the adipose perfusion is heterogeneous. The purpose of this paper is to quantitate human adipose blood flow heterogeneity and determine its importance for human pharmacokinetics. Methods The heterogeneity was determined using a physiologically based pharmacokinetic model (PBPK) to describe the 6 day volatile anesthetic data previously published by Yasuda et. al. The analysis uses the freely available software PKQuest and incorporates perfusion-ventilation mismatch and time dependent parameters that varied from the anesthetized to the ambulatory period. This heterogeneous adipose perfusion PBPK model was then tested by applying it to the previously published cannabidiol data of Ohlsson et. al. and the cannabinol data of Johansson et. al. Results The volatile anesthetic kinetics at early times have only a weak dependence on adipose blood flow while at long times the pharmacokinetics are dominated by the adipose flow and are independent of muscle blood flow. At least 2 adipose compartments with different perfusion rates (0.074 and 0.014 l/kg/min) were needed to describe the anesthetic data. This heterogeneous adipose PBPK model also provided a good fit to the cannabinol data. Conclusion Human adipose blood flow is markedly heterogeneous, varying by at least 5 fold. This heterogeneity significantly influences the long time pharmacokinetics of the volatile anesthetics and tetrahydrocannabinol. In contrast, using this same PBPK model it can be shown that the long time pharmacokinetics of the persistent lipophilic compounds (dioxins, PCBs) do not depend on adipose blood flow. The ability of the same PBPK model to describe both the anesthetic and cannabinol kinetics provides direct qualitative evidence that their kinetics are flow limited and that there is no significant adipose tissue diffusion limitation. PMID:17239252

Experimental evaluation criteria for constitutive models of time dependent cyclic plasticity

NASA Technical Reports Server (NTRS)

Martin, J. F.

1986-01-01

Notched members were tested at temperatures far above those recorded till now. Simulation of the notch root stress response was accomplished to establish notch stress-strain behavior. Cyclic stress-strain profiles across the net-section were recorded and on-line direct notch strain control was accomplished. Data are compared to three analysis techniques with good results. The objective of the study is to generate experimental data that can be used to evaluate the accuracy of constitutive models of time dependent cyclic plasticity.

Exact time-dependent solutions for a self-regulating gene.

PubMed

Ramos, A F; Innocentini, G C P; Hornos, J E M

2011-06-01

The exact time-dependent solution for the stochastic equations governing the behavior of a binary self-regulating gene is presented. Using the generating function technique to rephrase the master equations in terms of partial differential equations, we show that the model is totally integrable and the analytical solutions are the celebrated confluent Heun functions. Self-regulation plays a major role in the control of gene expression, and it is remarkable that such a microscopic model is completely integrable in terms of well-known complex functions.

A GIS-based time-dependent seismic source modeling of Northern Iran

NASA Astrophysics Data System (ADS)

Hashemi, Mahdi; Alesheikh, Ali Asghar; Zolfaghari, Mohammad Reza

2017-01-01

The first step in any seismic hazard study is the definition of seismogenic sources and the estimation of magnitude-frequency relationships for each source. There is as yet no standard methodology for source modeling and many researchers have worked on this topic. This study is an effort to define linear and area seismic sources for Northern Iran. The linear or fault sources are developed based on tectonic features and characteristic earthquakes while the area sources are developed based on spatial distribution of small to moderate earthquakes. Time-dependent recurrence relationships are developed for fault sources using renewal approach while time-independent frequency-magnitude relationships are proposed for area sources based on Poisson process. GIS functionalities are used in this study to introduce and incorporate spatial-temporal and geostatistical indices in delineating area seismic sources. The proposed methodology is used to model seismic sources for an area of about 500 by 400 square kilometers around Tehran. Previous researches and reports are studied to compile an earthquake/fault catalog that is as complete as possible. All events are transformed to uniform magnitude scale; duplicate events and dependent shocks are removed. Completeness and time distribution of the compiled catalog is taken into account. The proposed area and linear seismic sources in conjunction with defined recurrence relationships can be used to develop time-dependent probabilistic seismic hazard analysis of Northern Iran.

GPS Imaging of Time-Dependent Seasonal Strain in Central California

NASA Astrophysics Data System (ADS)

Kraner, M.; Hammond, W. C.; Kreemer, C.; Borsa, A. A.; Blewitt, G.

2016-12-01

Recently, studies are suggesting that crustal deformation can be time-dependent and nontectonic. Continuous global positioning system (cGPS) measurements are now showing how steady long-term deformation can be influenced by factors such as fluctuations in loading and temperature variations. Here we model the seasonal time-dependent dilatational and shear strain in Central California, specifically surrounding the Parkfield region and try to uncover the sources of these deformation patterns. We use 8 years of cGPS data (2008 - 2016) processed by the Nevada Geodetic Laboratory and carefully select the cGPS stations for our analysis based on the vertical position of cGPS time series during the drought period. In building our strain model, we first detrend the selected station time series using a set of velocities from the robust MIDAS trend estimator. This estimation algorithm is a robust approach that is insensitive to common problems such as step discontinuities, outliers, and seasonality. We use these detrended time series to estimate the median cGPS positions for each month of the 8-year period and filter displacement differences between these monthly median positions using a filtering technique called "GPS Imaging." This technique improves the overall robustness and spatial resolution of the input displacements for the strain model. We then model our dilatational and shear strain field for each month of time series. We also test a variety of a priori constraints, which controls the style of faulting within the strain model. Upon examining our strain maps, we find that a seasonal strain signal exists in Central California. We investigate how this signal compares to thermoelastic, hydrologic, and atmospheric loading models during the 8-year period. We additionally determine whether the drought played a role in influencing the seasonal signal.

Modeling the glass transition of amorphous networks for shape-memory behavior

NASA Astrophysics Data System (ADS)

Xiao, Rui; Choi, Jinwoo; Lakhera, Nishant; Yakacki, Christopher M.; Frick, Carl P.; Nguyen, Thao D.

2013-07-01

In this paper, a thermomechanical constitutive model was developed for the time-dependent behaviors of the glass transition of amorphous networks. The model used multiple discrete relaxation processes to describe the distribution of relaxation times for stress relaxation, structural relaxation, and stress-activated viscous flow. A non-equilibrium thermodynamic framework based on the fictive temperature was introduced to demonstrate the thermodynamic consistency of the constitutive theory. Experimental and theoretical methods were developed to determine the parameters describing the distribution of stress and structural relaxation times and the dependence of the relaxation times on temperature, structure, and driving stress. The model was applied to study the effects of deformation temperatures and physical aging on the shape-memory behavior of amorphous networks. The model was able to reproduce important features of the partially constrained recovery response observed in experiments. Specifically, the model demonstrated a strain-recovery overshoot for cases programmed below Tg and subjected to a constant mechanical load. This phenomenon was not observed for materials programmed above Tg. Physical aging, in which the material was annealed for an extended period of time below Tg, shifted the activation of strain recovery to higher temperatures and increased significantly the initial recovery rate. For fixed-strain recovery, the model showed a larger overshoot in the stress response for cases programmed below Tg, which was consistent with previous experimental observations. Altogether, this work demonstrates how an understanding of the time-dependent behaviors of the glass transition can be used to tailor the temperature and deformation history of the shape-memory programming process to achieve more complex shape recovery pathways, faster recovery responses, and larger activation stresses.

Temperature dependence of the hydrated electron's excited-state relaxation. I. Simulation predictions of resonance Raman and pump-probe transient absorption spectra of cavity and non-cavity models

NASA Astrophysics Data System (ADS)

Zho, Chen-Chen; Farr, Erik P.; Glover, William J.; Schwartz, Benjamin J.

2017-08-01

We use one-electron non-adiabatic mixed quantum/classical simulations to explore the temperature dependence of both the ground-state structure and the excited-state relaxation dynamics of the hydrated electron. We compare the results for both the traditional cavity picture and a more recent non-cavity model of the hydrated electron and make definite predictions for distinguishing between the different possible structural models in future experiments. We find that the traditional cavity model shows no temperature-dependent change in structure at constant density, leading to a predicted resonance Raman spectrum that is essentially temperature-independent. In contrast, the non-cavity model predicts a blue-shift in the hydrated electron's resonance Raman O-H stretch with increasing temperature. The lack of a temperature-dependent ground-state structural change of the cavity model also leads to a prediction of little change with temperature of both the excited-state lifetime and hot ground-state cooling time of the hydrated electron following photoexcitation. This is in sharp contrast to the predictions of the non-cavity model, where both the excited-state lifetime and hot ground-state cooling time are expected to decrease significantly with increasing temperature. These simulation-based predictions should be directly testable by the results of future time-resolved photoelectron spectroscopy experiments. Finally, the temperature-dependent differences in predicted excited-state lifetime and hot ground-state cooling time of the two models also lead to different predicted pump-probe transient absorption spectroscopy of the hydrated electron as a function of temperature. We perform such experiments and describe them in Paper II [E. P. Farr et al., J. Chem. Phys. 147, 074504 (2017)], and find changes in the excited-state lifetime and hot ground-state cooling time with temperature that match well with the predictions of the non-cavity model. In particular, the experiments reveal stimulated emission from the excited state with an amplitude and lifetime that decreases with increasing temperature, a result in contrast to the lack of stimulated emission predicted by the cavity model but in good agreement with the non-cavity model. Overall, until ab initio calculations describing the non-adiabatic excited-state dynamics of an excess electron with hundreds of water molecules at a variety of temperatures become computationally feasible, the simulations presented here provide a definitive route for connecting the predictions of cavity and non-cavity models of the hydrated electron with future experiments.

Disentangling density-dependent dynamics using full annual cycle models and Bayesian model weight updating

USGS Publications Warehouse

Robinson, Orin J.; McGowan, Conor P.; Devers, Patrick K.

2017-01-01

Density dependence regulates populations of many species across all taxonomic groups. Understanding density dependence is vital for predicting the effects of climate, habitat loss and/or management actions on wild populations. Migratory species likely experience seasonal changes in the relative influence of density dependence on population processes such as survival and recruitment throughout the annual cycle. These effects must be accounted for when characterizing migratory populations via population models.To evaluate effects of density on seasonal survival and recruitment of a migratory species, we used an existing full annual cycle model framework for American black ducks Anas rubripes, and tested different density effects (including no effects) on survival and recruitment. We then used a Bayesian model weight updating routine to determine which population model best fit observed breeding population survey data between 1990 and 2014.The models that best fit the survey data suggested that survival and recruitment were affected by density dependence and that density effects were stronger on adult survival during the breeding season than during the non-breeding season.Analysis also suggests that regulation of survival and recruitment by density varied over time. Our results showed that different characterizations of density regulations changed every 8–12 years (three times in the 25-year period) for our population.Synthesis and applications. Using a full annual cycle, modelling framework and model weighting routine will be helpful in evaluating density dependence for migratory species in both the short and long term. We used this method to disentangle the seasonal effects of density on the continental American black duck population which will allow managers to better evaluate the effects of habitat loss and potential habitat management actions throughout the annual cycle. The method here may allow researchers to hone in on the proper form and/or strength of density dependence for use in models for conservation recommendations.

A computationally simple model for determining the time dependent spectral neutron flux in a nuclear reactor core

NASA Astrophysics Data System (ADS)

Schneider, E. A.; Deinert, M. R.; Cady, K. B.

2006-10-01

The balance of isotopes in a nuclear reactor core is key to understanding the overall performance of a given fuel cycle. This balance is in turn most strongly affected by the time and energy-dependent neutron flux. While many large and involved computer packages exist for determining this spectrum, a simplified approach amenable to rapid computation is missing from the literature. We present such a model, which accepts as inputs the fuel element/moderator geometry and composition, reactor geometry, fuel residence time and target burnup and we compare it to OECD/NEA benchmarks for homogeneous MOX and UOX LWR cores. Collision probability approximations to the neutron transport equation are used to decouple the spatial and energy variables. The lethargy dependent neutron flux, governed by coupled integral equations for the fuel and moderator/coolant regions is treated by multigroup thermalization methods, and the transport of neutrons through space is modeled by fuel to moderator transport and escape probabilities. Reactivity control is achieved through use of a burnable poison or adjustable control medium. The model calculates the buildup of 24 actinides, as well as fission products, along with the lethargy dependent neutron flux and the results of several simulations are compared with benchmarked standards.

Fractional time-dependent apparent viscosity model for semisolid foodstuffs

NASA Astrophysics Data System (ADS)

Yang, Xu; Chen, Wen; Sun, HongGuang

2017-10-01

The difficulty in the description of thixotropic behaviors in semisolid foodstuffs is the time dependent nature of apparent viscosity under constant shear rate. In this study, we propose a novel theoretical model via fractional derivative to address the high demand by industries. The present model adopts the critical parameter of fractional derivative order α to describe the corresponding time-dependent thixotropic behavior. More interestingly, the parameter α provides a quantitative insight into discriminating foodstuffs. With the re-exploration of three groups of experimental data (tehineh, balangu, and natillas), the proposed methodology is validated in good applicability and efficiency. The results show that the present fractional apparent viscosity model performs successfully for tested foodstuffs in the shear rate range of 50-150 s^{ - 1}. The fractional order α decreases with the increase of temperature at low temperature, below 50 °C, but increases with growing shear rate. While the ideal initial viscosity k decreases with the increase of temperature, shear rate, and ingredient content. It is observed that the magnitude of α is capable of characterizing the thixotropy of semisolid foodstuffs.

Determination of efficiencies, loss mechanisms, and performance degradation factors in chopper controlled dc vehical motors. Section 2: The time dependent finite element modeling of the electromagnetic field in electrical machines: Methods and applications. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Hamilton, H. B.; Strangas, E.

1980-01-01

The time dependent solution of the magnetic field is introduced as a method for accounting for the variation, in time, of the machine parameters in predicting and analyzing the performance of the electrical machines. The method of time dependent finite element was used in combination with an also time dependent construction of a grid for the air gap region. The Maxwell stress tensor was used to calculate the airgap torque from the magnetic vector potential distribution. Incremental inductances were defined and calculated as functions of time, depending on eddy currents and saturation. The currents in all the machine circuits were calculated in the time domain based on these inductances, which were continuously updated. The method was applied to a chopper controlled DC series motor used for electric vehicle drive, and to a salient pole sychronous motor with damper bars. Simulation results were compared to experimentally obtained ones.

Online Robot Dead Reckoning Localization Using Maximum Relative Entropy Optimization With Model Constraints

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

Urniezius, Renaldas

2011-03-14

The principle of Maximum relative Entropy optimization was analyzed for dead reckoning localization of a rigid body when observation data of two attached accelerometers was collected. Model constraints were derived from the relationships between the sensors. The experiment's results confirmed that accelerometers each axis' noise can be successfully filtered utilizing dependency between channels and the dependency between time series data. Dependency between channels was used for a priori calculation, and a posteriori distribution was derived utilizing dependency between time series data. There was revisited data of autocalibration experiment by removing the initial assumption that instantaneous rotation axis of a rigidmore » body was known. Performance results confirmed that such an approach could be used for online dead reckoning localization.« less

Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula

NASA Astrophysics Data System (ADS)

Sarhadi, Ali; Burn, Donald H.; Concepción Ausín, María.; Wiper, Michael P.

2016-03-01

A time-varying risk analysis is proposed for an adaptive design framework in nonstationary conditions arising from climate change. A Bayesian, dynamic conditional copula is developed for modeling the time-varying dependence structure between mixed continuous and discrete multiattributes of multidimensional hydrometeorological phenomena. Joint Bayesian inference is carried out to fit the marginals and copula in an illustrative example using an adaptive, Gibbs Markov Chain Monte Carlo (MCMC) sampler. Posterior mean estimates and credible intervals are provided for the model parameters and the Deviance Information Criterion (DIC) is used to select the model that best captures different forms of nonstationarity over time. This study also introduces a fully Bayesian, time-varying joint return period for multivariate time-dependent risk analysis in nonstationary environments. The results demonstrate that the nature and the risk of extreme-climate multidimensional processes are changed over time under the impact of climate change, and accordingly the long-term decision making strategies should be updated based on the anomalies of the nonstationary environment.

Time distributions of solar energetic particle events: Are SEPEs really random?

NASA Astrophysics Data System (ADS)

Jiggens, P. T. A.; Gabriel, S. B.

2009-10-01

Solar energetic particle events (SEPEs) can exhibit flux increases of several orders of magnitude over background levels and have always been considered to be random in nature in statistical models with no dependence of any one event on the occurrence of previous events. We examine whether this assumption of randomness in time is correct. Engineering modeling of SEPEs is important to enable reliable and efficient design of both Earth-orbiting and interplanetary spacecraft and future manned missions to Mars and the Moon. All existing engineering models assume that the frequency of SEPEs follows a Poisson process. We present analysis of the event waiting times using alternative distributions described by Lévy and time-dependent Poisson processes and compared these with the usual Poisson distribution. The results show significant deviation from a Poisson process and indicate that the underlying physical processes might be more closely related to a Lévy-type process, suggesting that there is some inherent “memory” in the system. Inherent Poisson assumptions of stationarity and event independence are investigated, and it appears that they do not hold and can be dependent upon the event definition used. SEPEs appear to have some memory indicating that events are not completely random with activity levels varying even during solar active periods and are characterized by clusters of events. This could have significant ramifications for engineering models of the SEP environment, and it is recommended that current statistical engineering models of the SEP environment should be modified to incorporate long-term event dependency and short-term system memory.

Modeling hurricane evacuation traffic : development of a time-dependent hurricane evacuation demand model.

DOT National Transportation Integrated Search

2006-04-01

Little attention has been given to estimating dynamic travel demand in transportation planning in the past. However, when factors influencing travel are changing significantly over time such as with an approaching hurricane - dynamic demand and t...

Anisotropic diffusion and capture on surfaces: Time dependent modeling and visualization in 2 dimensions

NASA Astrophysics Data System (ADS)

Yang, Pu

Since the application of nanowires may lead to a new generation of electronic, optoelectronic and magnetic devices, there is much research on understanding the growth mechanism of various "self assembled" nanowires on semiconductor surfaces. The motivation of the present work is to use theoretical modeling to study the conditions required to form and grow elongated islands and nanowires. In this work, a modeling method is developed to study the time-dependent anisotropic diffusion and growth in two dimensions for an array of rectangular islands. This method uses discrete Fast Fourier Transformation (FFT) to solve the time-dependent diffusion equation on the surface. The ad-particles are captured and incorporated to the island edge to simulate island growth. Implemented in MATLABRTM programs, this model produces expected faceted shapes; the calculation runs very fast on a common personal computer. Time-dependent island growth and the evolving diffusion field have been visualized using simple MATLABRTM functions and can be made into MATLABRTM movies. This modeling method is applied to simulate elongated island and nanowire growth by incorporating anisotropic bonding at the island edge. When there is a full sink in one direction and partial sink in the other direction at the island edge, the model results in the growth of an elongated island with an aspect ratio that stabilizes after it reaches a certain value. This result agrees with experimental data on "endotaxial" nanowire growth. For the island edge with a full sink in one direction and no sink in the other direction, the island grows in length with constant width, which is comparable to experimental data on Bi nanoline and rare-earth metal nanowire growth.

A comment on Baker et al. 'The time dependence of an atom-vacancy encounter due to the vacancy mechanism of diffusion'

NASA Astrophysics Data System (ADS)

Dasenbrock-Gammon, Nathan; Zacate, Matthew O.

2017-05-01

Baker et al. derived time-dependent expressions for calculating average number of jumps per encounter and displacement probabilities for vacancy diffusion in crystal lattice systems with infinitesimal vacancy concentrations. As shown in this work, their formulation is readily expanded to include finite vacancy concentration, which allows calculation of concentration-dependent, time-averaged quantities. This is useful because it provides a computationally efficient method to express lineshapes of nuclear spectroscopic techniques through the use of stochastic fluctuation models.

A time-dependent model to determine the thermal conductivity of a nanofluid

NASA Astrophysics Data System (ADS)

Myers, T. G.; MacDevette, M. M.; Ribera, H.

2013-07-01

In this paper, we analyse the time-dependent heat equations over a finite domain to determine expressions for the thermal diffusivity and conductivity of a nanofluid (where a nanofluid is a fluid containing nanoparticles with average size below 100 nm). Due to the complexity of the standard mathematical analysis of this problem, we employ a well-known approximate solution technique known as the heat balance integral method. This allows us to derive simple analytical expressions for the thermal properties, which appear to depend primarily on the volume fraction and liquid properties. The model is shown to compare well with experimental data taken from the literature even up to relatively high concentrations and predicts significantly higher values than the Maxwell model for volume fractions approximately >1 %. The results suggest that the difficulty in reproducing the high values of conductivity observed experimentally may stem from the use of a static heat flow model applied over an infinite domain rather than applying a dynamic model over a finite domain.

Lattice dynamics approach to determine the dependence of the time-of-flight of transversal polarized acoustic waves on external stress

NASA Astrophysics Data System (ADS)

Tarar, K. S.; Pluta, M.; Amjad, U.; Grill, W.

2011-04-01

Based on the lattice dynamics approach the dependence of the time-of-flight (TOF) on stress has been modeled for transversal polarized acoustic waves. The relevant dispersion relation is derived from the appropriate mass-spring model together with the dependencies on the restoring forces including the effect of externally applied stress. The lattice dynamics approach can also be interpreted as a discrete and strictly periodic lumped circuit. In that case the modeling represents a finite element approach. In both cases the properties relevant for wavelengths large with respect to the periodic structure can be derived from the respective limit relating also to low frequencies. The model representing a linear chain with stiffness to shear and additional stiffness introduced by extensional stress is presented and compared to existing models, which so far represent each only one of the effects treated here in combination. For a string this effect is well known from musical instruments. The counteracting effects are discussed and compared to experimental results.

Scaling and efficiency determine the irreversible evolution of a market

PubMed Central

Baldovin, F.; Stella, A. L.

2007-01-01

In setting up a stochastic description of the time evolution of a financial index, the challenge consists in devising a model compatible with all stylized facts emerging from the analysis of financial time series and providing a reliable basis for simulating such series. Based on constraints imposed by market efficiency and on an inhomogeneous-time generalization of standard simple scaling, we propose an analytical model which accounts simultaneously for empirical results like the linear decorrelation of successive returns, the power law dependence on time of the volatility autocorrelation function, and the multiscaling associated to this dependence. In addition, our approach gives a justification and a quantitative assessment of the irreversible character of the index dynamics. This irreversibility enters as a key ingredient in a novel simulation strategy of index evolution which demonstrates the predictive potential of the model.

Aerodynamic Parameters of High Performance Aircraft Estimated from Wind Tunnel and Flight Test Data

NASA Technical Reports Server (NTRS)

Klein, Vladislav; Murphy, Patrick C.

1998-01-01

A concept of system identification applied to high performance aircraft is introduced followed by a discussion on the identification methodology. Special emphasis is given to model postulation using time invariant and time dependent aerodynamic parameters, model structure determination and parameter estimation using ordinary least squares an mixed estimation methods, At the same time problems of data collinearity detection and its assessment are discussed. These parts of methodology are demonstrated in examples using flight data of the X-29A and X-31A aircraft. In the third example wind tunnel oscillatory data of the F-16XL model are used. A strong dependence of these data on frequency led to the development of models with unsteady aerodynamic terms in the form of indicial functions. The paper is completed by concluding remarks.

Consistency of internal fluxes in a hydrological model running at multiple time steps

NASA Astrophysics Data System (ADS)

Ficchi, Andrea; Perrin, Charles; Andréassian, Vazken

2016-04-01

Improving hydrological models remains a difficult task and many ways can be explored, among which one can find the improvement of spatial representation, the search for more robust parametrization, the better formulation of some processes or the modification of model structures by trial-and-error procedure. Several past works indicate that model parameters and structure can be dependent on the modelling time step, and there is thus some rationale in investigating how a model behaves across various modelling time steps, to find solutions for improvements. Here we analyse the impact of data time step on the consistency of the internal fluxes of a rainfall-runoff model run at various time steps, by using a large data set of 240 catchments. To this end, fine time step hydro-climatic information at sub-hourly resolution is used as input of a parsimonious rainfall-runoff model (GR) that is run at eight different model time steps (from 6 minutes to one day). The initial structure of the tested model (i.e. the baseline) corresponds to the daily model GR4J (Perrin et al., 2003), adapted to be run at variable sub-daily time steps. The modelled fluxes considered are interception, actual evapotranspiration and intercatchment groundwater flows. Observations of these fluxes are not available, but the comparison of modelled fluxes at multiple time steps gives additional information for model identification. The joint analysis of flow simulation performance and consistency of internal fluxes at different time steps provides guidance to the identification of the model components that should be improved. Our analysis indicates that the baseline model structure is to be modified at sub-daily time steps to warrant the consistency and realism of the modelled fluxes. For the baseline model improvement, particular attention is devoted to the interception model component, whose output flux showed the strongest sensitivity to modelling time step. The dependency of the optimal model complexity on time step is also analysed. References: Perrin, C., Michel, C., Andréassian, V., 2003. Improvement of a parsimonious model for streamflow simulation. Journal of Hydrology, 279(1-4): 275-289. DOI:10.1016/S0022-1694(03)00225-7

Exciton interference revealed by energy dependent exciton transfer rate for ring-structured molecular systems

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

Yan, Yun-An, E-mail: yunan@gznc.edu.cn

2016-01-14

The quantum interference is an intrinsic phenomenon in quantum physics for photon and massive quantum particles. In principle, the quantum interference may also occur with quasi-particles, such as the exciton. In this study, we show how the exciton quantum interference can be significant in aggregates through theoretical simulations with hierarchical equations of motion. The systems under investigation are generalized donor-bridge-acceptor model aggregates with the donor consisting of six homogeneous sites assuming the nearest neighbor coupling. For the models with single-path bridge, the exciton transfer time only shows a weak excitation energy dependence. But models with double-path bridge have a newmore » short transfer time scale and the excitation energy dependence of the exciton transfer time assumes clear peak structure which is detectable with today’s nonlinear spectroscopy. This abnormality is attributed to the exciton quantum interference and the condition for a clear observation in experiment is also explored.« less

Time-Dependent ATR-FTIR Spectroscopic Studies on Fatty Acid Diffusion and the Formation of Metal Soaps in Oil Paint Model Systems.

PubMed

Baij, Lambert; Hermans, Joen J; Keune, Katrien; Iedema, Piet

2018-06-18

The formation of metal soaps (metal complexes of saturated fatty acids) is a serious problem affecting the appearance and structural integrity of many oil paintings. Tailored model systems for aged oil paint and time-dependent attenuated total reflection Fourier transform infrared (ATR-FTIR) spectroscopy were used to study the diffusion of palmitic acid and subsequent metal soap crystallization. The simultaneous presence of free saturated fatty acids and polymer-bound metal carboxylates leads to rapid metal soap crystallization, following a complex mechanism that involves both acid and metal diffusion. Solvent flow, water, and pigments all enhance metal soap crystallization in the model systems. These results contribute to the development of paint cleaning strategies, a better understanding of oil paint degradation, and highlight the potential of time-dependent ATR-FTIR spectroscopy for studying dynamic processes in polymer films. © 2018 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

Modulation of Galactic Cosmic Rays in the Inner Heliosphere, Comparing with PAMELA Measurements

NASA Astrophysics Data System (ADS)

Qin, G.; Shen, Z.-N.

2017-09-01

We develop a numerical model to study the time-dependent modulation of galactic cosmic rays in the inner heliosphere. In the model, a time-delayed modified Parker heliospheric magnetic field (HMF) and a new diffusion coefficient model, NLGCE-F, from Qin & Zhang, are adopted. In addition, the latitudinal dependence of magnetic turbulence magnitude is assumed to be ˜ (1+{\\sin }2θ )/2 from the observations of Ulysses, and the radial dependence is assumed to be ˜ {r}S, where we choose an expression of S as a function of the heliospheric current sheet tilt angle. We show that the analytical expression used to describe the spatial variation of HMF turbulence magnitude agrees well with the Ulysses, Voyager 1, and Voyager 2 observations. By numerically calculating the modulation code, we get the proton energy spectra as a function of time during the recent solar minimum, it is shown that the modulation results are consistent with the Payload for Antimatter-Matter Exploration and Light-nuclei Astrophysics measurements.

Equivalent source modeling of the main field using MAGSAT data

NASA Technical Reports Server (NTRS)

1980-01-01

The software was considerably enhanced to accommodate a more comprehensive examination of data available for field modeling using the equivalent sources method by (1) implementing a dynamic core allocation capability into the software system for the automatic dimensioning of the normal matrix; (2) implementing a time dependent model for the dipoles; (3) incorporating the capability to input specialized data formats in a fashion similar to models in spherical harmonics; and (4) implementing the optional ability to simultaneously estimate observatory anomaly biases where annual means data is utilized. The time dependence capability was demonstrated by estimating a component model of 21 deg resolution using the 14 day MAGSAT data set of Goddard's MGST (12/80). The equivalent source model reproduced both the constant and the secular variation found in MGST (12/80).

Coordinated Pulses of mRNA and of Protein Translation or Degradation Produce EGF-Induced Protein Bursts.

PubMed

Golan-Lavi, Roni; Giacomelli, Chiara; Fuks, Garold; Zeisel, Amit; Sonntag, Johanna; Sinha, Sanchari; Köstler, Wolfgang; Wiemann, Stefan; Korf, Ulrike; Yarden, Yosef; Domany, Eytan

2017-03-28

Protein responses to extracellular cues are governed by gene transcription, mRNA degradation and translation, and protein degradation. In order to understand how these time-dependent processes cooperate to generate dynamic responses, we analyzed the response of human mammary cells to the epidermal growth factor (EGF). Integrating time-dependent transcript and protein data into a mathematical model, we inferred for several proteins their pre-and post-stimulus translation and degradation coefficients and found that they exhibit complex, time-dependent variation. Specifically, we identified strategies of protein production and degradation acting in concert to generate rapid, transient protein bursts in response to EGF. Remarkably, for some proteins, for which the response necessitates rapidly decreased abundance, cells exhibit a transient increase in the corresponding degradation coefficient. Our model and analysis allow inference of the kinetics of mRNA translation and protein degradation, without perturbing cells, and open a way to understanding the fundamental processes governing time-dependent protein abundance profiles. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Modelling scale-dependent runoff generation in a small semi-arid watershed accounting for rainfall intensity and water depth

USDA-ARS?s Scientific Manuscript database

Observed scale effects of runoff and erosion on hillslopes and small watersheds pose one of the most intriguing challenges to modellers, because it results from complex interactions of time-dependent rainfall input with runoff, infiltration and macro- and microtopographic structures. A little studie...

Plasma flows in the heliosheath along the Voyager 1 and 2 trajectories due to effects of the 11 yr solar cycle

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

Provornikova, E.; Opher, M.; Izmodenov, V. V.

We investigate the role of the 11 yr solar cycle variations in the solar wind (SW) parameters on the flows in the heliosheath using a new three-dimensional time-dependent model of the interaction between the SW and the interstellar medium. For boundary conditions in the model we use realistic time and the latitudinal dependence of the SW parameters obtained from SOHO/SWAN and interplanetary scintillation data for the last two solar cycles (1990-2011). This data set generally agrees with the in situ Ulysses measurements from 1991 to 2009. For the first ∼30 AU of the heliosheath the time-dependent model predicts constant radialmore » flow speeds at Voyager 2 (V2), which is consistent with observations and different from the steady models that show a radial speed decrease of 30%. The model shows that V2 was immersed in SW with speeds of 500-550 km s{sup –1} upstream of the termination shock before 2009 and in wind with upstream speeds of 450-500 km s{sup –1} after 2009. The model also predicts that the radial velocity along the Voyager 1 (V1) trajectory is constant across the heliosheath, contrary to observations. This difference in observations implies that additional effects may be responsible for the different flows at V1 and V2. The model predicts meridional flows (VN) higher than those observed because of the strong bluntness of the heliosphere shape in the N direction in the model. The modeled tangential velocity component (VT) at V2 is smaller than observed. Both VN and VT essentially depend on the shape of the heliopause.« less

The Active Fault Parameters for Time-Dependent Earthquake Hazard Assessment in Taiwan

NASA Astrophysics Data System (ADS)

Lee, Y.; Cheng, C.; Lin, P.; Shao, K.; Wu, Y.; Shih, C.

2011-12-01

Taiwan is located at the boundary between the Philippine Sea Plate and the Eurasian Plate, with a convergence rate of ~ 80 mm/yr in a ~N118E direction. The plate motion is so active that earthquake is very frequent. In the Taiwan area, disaster-inducing earthquakes often result from active faults. For this reason, it's an important subject to understand the activity and hazard of active faults. The active faults in Taiwan are mainly located in the Western Foothills and the Eastern longitudinal valley. Active fault distribution map published by the Central Geological Survey (CGS) in 2010 shows that there are 31 active faults in the island of Taiwan and some of which are related to earthquake. Many researchers have investigated these active faults and continuously update new data and results, but few people have integrated them for time-dependent earthquake hazard assessment. In this study, we want to gather previous researches and field work results and then integrate these data as an active fault parameters table for time-dependent earthquake hazard assessment. We are going to gather the seismic profiles or earthquake relocation of a fault and then combine the fault trace on land to establish the 3D fault geometry model in GIS system. We collect the researches of fault source scaling in Taiwan and estimate the maximum magnitude from fault length or fault area. We use the characteristic earthquake model to evaluate the active fault earthquake recurrence interval. In the other parameters, we will collect previous studies or historical references and complete our parameter table of active faults in Taiwan. The WG08 have done the time-dependent earthquake hazard assessment of active faults in California. They established the fault models, deformation models, earthquake rate models, and probability models and then compute the probability of faults in California. Following these steps, we have the preliminary evaluated probability of earthquake-related hazards in certain faults in Taiwan. By accomplishing active fault parameters table in Taiwan, we would apply it in time-dependent earthquake hazard assessment. The result can also give engineers a reference for design. Furthermore, it can be applied in the seismic hazard map to mitigate disasters.

(U) Physics Validation of the RMI-Based Ejecta Source Model Implementation in FLAG: L2 Milestone #6035 Report

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

Tregillis, I. L.

The Los Alamos Physics and Engineering Models (PEM) program has developed a model for Richtmyer-Meshkov instability (RMI) based ejecta production from shock-melted surfaces, along with a prescription for a self-similar velocity distribution (SSVD) of the resulting ejecta particles. We have undertaken an effort to validate this source model using data from explosively driven tin coupon experiments. The model’s current formulation lacks a crucial piece of physics: a method for determining the duration of the ejecta production interval. Without a mechanism for terminating ejecta production, the model is not predictive. Furthermore, when the production interval is hand-tuned to match time-integrated massmore » data, the predicted time-dependent mass accumulation on a downstream sensor rises too sharply at early times and too slowly at late times because the SSVD overestimates the amount of mass stored in the fastest particles and underestimates the mass stored in the slowest particles. The functional form of the resulting m(t) is inconsistent with the available time-dependent data; numerical simulations and analytic studies agree on this point. Simulated mass tallies are highly sensitive to radial expansion of the ejecta cloud. It is not clear if the same effect is present in the experimental data but if so, depending on the degree, this may challenge the model’s compatibility with tin coupon data. The current implementation of the model in FLAG is sensitive to the detailed interaction between kinematics (hydrodynamic methods) and thermodynamics (material models); this sensitivity prohibits certain physics modeling choices. The appendices contain an extensive analytic study of piezoelectric ejecta mass measurements, along with test problems, excerpted from a longer work (LA-UR-17-21218).« less

Analysis of isothermal and cooling rate dependent immersion freezing by a unifying stochastic ice nucleation model

NASA Astrophysics Data System (ADS)

Alpert, P. A.; Knopf, D. A.

2015-05-01

Immersion freezing is an important ice nucleation pathway involved in the formation of cirrus and mixed-phase clouds. Laboratory immersion freezing experiments are necessary to determine the range in temperature (T) and relative humidity (RH) at which ice nucleation occurs and to quantify the associated nucleation kinetics. Typically, isothermal (applying a constant temperature) and cooling rate dependent immersion freezing experiments are conducted. In these experiments it is usually assumed that the droplets containing ice nuclei (IN) all have the same IN surface area (ISA), however the validity of this assumption or the impact it may have on analysis and interpretation of the experimental data is rarely questioned. A stochastic immersion freezing model based on first principles of statistics is presented, which accounts for variable ISA per droplet and uses physically observable parameters including the total number of droplets (Ntot) and the heterogeneous ice nucleation rate coefficient, Jhet(T). This model is applied to address if (i) a time and ISA dependent stochastic immersion freezing process can explain laboratory immersion freezing data for different experimental methods and (ii) the assumption that all droplets contain identical ISA is a valid conjecture with subsequent consequences for analysis and interpretation of immersion freezing. The simple stochastic model can reproduce the observed time and surface area dependence in immersion freezing experiments for a variety of methods such as: droplets on a cold-stage exposed to air or surrounded by an oil matrix, wind and acoustically levitated droplets, droplets in a continuous flow diffusion chamber (CFDC), the Leipzig aerosol cloud interaction simulator (LACIS), and the aerosol interaction and dynamics in the atmosphere (AIDA) cloud chamber. Observed time dependent isothermal frozen fractions exhibiting non-exponential behavior with time can be readily explained by this model considering varying ISA. An apparent cooling rate dependence ofJhet is explained by assuming identical ISA in each droplet. When accounting for ISA variability, the cooling rate dependence of ice nucleation kinetics vanishes as expected from classical nucleation theory. The model simulations allow for a quantitative experimental uncertainty analysis for parameters Ntot, T, RH, and the ISA variability. In an idealized cloud parcel model applying variability in ISAs for each droplet, the model predicts enhanced immersion freezing temperatures and greater ice crystal production compared to a case when ISAs are uniform in each droplet. The implications of our results for experimental analysis and interpretation of the immersion freezing process are discussed.

Network models of frequency modulated sweep detection.

PubMed

Skorheim, Steven; Razak, Khaleel; Bazhenov, Maxim

2014-01-01

Frequency modulated (FM) sweeps are common in species-specific vocalizations, including human speech. Auditory neurons selective for the direction and rate of frequency change in FM sweeps are present across species, but the synaptic mechanisms underlying such selectivity are only beginning to be understood. Even less is known about mechanisms of experience-dependent changes in FM sweep selectivity. We present three network models of synaptic mechanisms of FM sweep direction and rate selectivity that explains experimental data: (1) The 'facilitation' model contains frequency selective cells operating as coincidence detectors, summing up multiple excitatory inputs with different time delays. (2) The 'duration tuned' model depends on interactions between delayed excitation and early inhibition. The strength of delayed excitation determines the preferred duration. Inhibitory rebound can reinforce the delayed excitation. (3) The 'inhibitory sideband' model uses frequency selective inputs to a network of excitatory and inhibitory cells. The strength and asymmetry of these connections results in neurons responsive to sweeps in a single direction of sufficient sweep rate. Variations of these properties, can explain the diversity of rate-dependent direction selectivity seen across species. We show that the inhibitory sideband model can be trained using spike timing dependent plasticity (STDP) to develop direction selectivity from a non-selective network. These models provide a means to compare the proposed synaptic and spectrotemporal mechanisms of FM sweep processing and can be utilized to explore cellular mechanisms underlying experience- or training-dependent changes in spectrotemporal processing across animal models. Given the analogy between FM sweeps and visual motion, these models can serve a broader function in studying stimulus movement across sensory epithelia.

The two-mode multi-photon intensity-dependent Rabi model

NASA Astrophysics Data System (ADS)

Lo, C. F.

2014-06-01

We have investigated the energy eigen-spectrum of the two-mode k-photon intensity-dependent Rabi (IDR) model for k ≥ 2. Our analysis shows that the model does not have eigenstates in the Hilbert space spanned by the eigenstates of the two-mode k-photon intensity-dependent Jaynes-Cummings (IDJC) model, which is obtained by applying the rotating-wave approximation (RWA) to the two-mode k-photon IDR model. That is, the two-mode k-photon IDR model is ill-defined for k ≥ 2, and it is qualitatively different from the RWA counterpart which is valid for all values of k, implying that the counter-rotating term does drastically alter the nature of the RWA counterpart. Hence, the previous study of the effect of the counter-rotating term in the two-mode k-photon IDJC model via the time-dependent perturbation expansion is completely invalid.

Bayesian Techniques for Comparing Time-dependent GRMHD Simulations to Variable Event Horizon Telescope Observations

NASA Astrophysics Data System (ADS)

Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan; Medeiros, Lia; Özel, Feryal; Psaltis, Dimitrios

2016-12-01

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore the robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.

BAYESIAN TECHNIQUES FOR COMPARING TIME-DEPENDENT GRMHD SIMULATIONS TO VARIABLE EVENT HORIZON TELESCOPE OBSERVATIONS

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

Kim, Junhan; Marrone, Daniel P.; Chan, Chi-Kwan

2016-12-01

The Event Horizon Telescope (EHT) is a millimeter-wavelength, very-long-baseline interferometry (VLBI) experiment that is capable of observing black holes with horizon-scale resolution. Early observations have revealed variable horizon-scale emission in the Galactic Center black hole, Sagittarius A* (Sgr A*). Comparing such observations to time-dependent general relativistic magnetohydrodynamic (GRMHD) simulations requires statistical tools that explicitly consider the variability in both the data and the models. We develop here a Bayesian method to compare time-resolved simulation images to variable VLBI data, in order to infer model parameters and perform model comparisons. We use mock EHT data based on GRMHD simulations to explore themore » robustness of this Bayesian method and contrast it to approaches that do not consider the effects of variability. We find that time-independent models lead to offset values of the inferred parameters with artificially reduced uncertainties. Moreover, neglecting the variability in the data and the models often leads to erroneous model selections. We finally apply our method to the early EHT data on Sgr A*.« less

The Time-Dependent Chemistry of Cometary Debris in the Solar Corona

NASA Technical Reports Server (NTRS)

Pesnell, W. D.; Bryans, P.

2015-01-01

Recent improvements in solar observations have greatly progressed the study of sungrazing comets. They can now be imaged along the entirety of their perihelion passage through the solar atmosphere, revealing details of their composition and structure not measurable through previous observations in the less volatile region of the orbit further from the solar surface. Such comets are also unique probes of the solar atmosphere. The debris deposited by sungrazers is rapidly ionized and subsequently influenced by the ambient magnetic field. Measuring the spectral signature of the deposited material highlights the topology of the magnetic field and can reveal plasma parameters such as the electron temperature and density. Recovering these variables from the observable data requires a model of the interaction of the cometary species with the atmosphere through which they pass. The present paper offers such a model by considering the time-dependent chemistry of sublimated cometary species as they interact with the solar radiation field and coronal plasma. We expand on a previous simplified model by considering the fully time-dependent solutions of the emitting species' densities. To compare with observations, we consider a spherically symmetric expansion of the sublimated material into the corona and convert the time-dependent ion densities to radial profiles. Using emissivities from the CHIANTI database and plasma parameters derived from a magnetohydrodynamic simulation leads to a spatially dependent emission spectrum that can be directly compared with observations. We find our simulated spectra to be consistent with observation.

The Local Structure of Globalization. The Network Dynamics of Foreign Direct Investments in the International Electricity Industry

NASA Astrophysics Data System (ADS)

Koskinen, Johan; Lomi, Alessandro

2013-05-01

We study the evolution of the network of foreign direct investment (FDI) in the international electricity industry during the period 1994-2003. We assume that the ties in the network of investment relations between countries are created and deleted in continuous time, according to a conditional Gibbs distribution. This assumption allows us to take simultaneously into account the aggregate predictions of the well-established gravity model of international trade as well as local dependencies between network ties connecting the countries in our sample. According to the modified version of the gravity model that we specify, the probability of observing an investment tie between two countries depends on the mass of the economies involved, their physical distance, and the tendency of the network to self-organize into local configurations of network ties. While the limiting distribution of the data generating process is an exponential random graph model, we do not assume the system to be in equilibrium. We find evidence of the effects of the standard gravity model of international trade on evolution of the global FDI network. However, we also provide evidence of significant dyadic and extra-dyadic dependencies between investment ties that are typically ignored in available research. We show that local dependencies between national electricity industries are sufficient for explaining global properties of the network of foreign direct investments. We also show, however, that network dependencies vary significantly over time giving rise to a time-heterogeneous localized process of network evolution.

Mechanical Properties of Polymers.

ERIC Educational Resources Information Center

Aklonis, J. J.

1981-01-01

Mechanical properties (stress-strain relationships) of polymers are reviewed, taking into account both time and temperature factors. Topics include modulus-temperature behavior of polymers, time dependence, time-temperature correspondence, and mechanical models. (JN)

Time-dependent crack growth behavior of alloy 617 and alloy 230 at elevated temperatures

NASA Astrophysics Data System (ADS)

Roy, Shawoon Kumar

2011-12-01

Two Ni-base solid-solution-strengthened superalloys: INCONEL 617 and HAYNES 230 were studied to check sustained loading crack growth (SLCG) behavior at elevated temperatures appropriate for Next Generation Nuclear Plant (NGNP) applictaions with constant stress intensity factor (Kmax= 27.75 MPa✓m) in air. The results indicate a time-dependent rate controlling process which can be characterized by a linear elastic fracture mechanics (LEFM) parameter -- stress intensity factor (K). At elevated temperatures, the crack growth mechanism was best described using a damage zone concept. Based on results and study, SAGBOE (stress accelerated grain boundary oxidation embrittlement) is considered the primary reason for time-dependent SLCG. A thermodynamic equation was considered to correlate all the SLCG results to determine the thermal activation energy in the process. A phenomenological model based on a time-dependent factor was developed considering the previous researcher's time-dependent fatigue crack propagation (FCP) results and current SLCG results to relate cycle-dependent and time-dependent FCP for both alloys. Further study includes hold time (3+300s) fatigue testing and no hold (1s) fatigue testing with various load ratios (R) at 700°C with a Kmax of 27.75 MPa✓m. Study results suggest an interesting point: crack growth behavior is significantly affected with the change in R value in cycle-dependent process whereas in time-dependent process, change in R does not have any significant effect. Fractography study showed intergranular cracking mode for all time-dependent processes and transgranular cracking mode for cycle-dependent processes. In Alloy 230, SEM images display intergranular cracking with carbide particles, dense oxides and dimple mixed secondary cracks for time-dependent 3+300s FCP and SLCG test. In all cases, Alloy 230 shows better crack growth resistance compared to Alloy 617.

Challenges in reducing the computational time of QSTS simulations for distribution system analysis.

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

Deboever, Jeremiah; Zhang, Xiaochen; Reno, Matthew J.

The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modelling and impact analysis. Unlike conventional scenario - based studies , quasi - static time - series (QSTS) simulation s can realistically model time - dependent voltage controllers and the diversity of potential impacts that can occur at different times of year . However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1 - second resolution is often required , which could take conventional computers a computational time of 10more » to 120 hours when an actual unbalanced distribution feeder is modeled . This computational burden is a clear l imitation to the adoption of QSTS simulation s in interconnection studies and for determining optimal control solutions for utility operations . Our ongoing research to improve the speed of QSTS simulation has revealed many unique aspects of distribution system modelling and sequential power flow analysis that make fast QSTS a very difficult problem to solve. In this report , the most relevant challenges in reducing the computational time of QSTS simulations are presented: number of power flows to solve, circuit complexity, time dependence between time steps, multiple valid power flow solutions, controllable element interactions, and extensive accurate simulation analysis.« less

General Multimechanism Reversible-Irreversible Time-Dependent Constitutive Deformation Model Being Developed

NASA Technical Reports Server (NTRS)

Saleeb, A. F.; Arnold, Steven M.

2001-01-01

Since most advanced material systems (for example metallic-, polymer-, and ceramic-based systems) being currently researched and evaluated are for high-temperature airframe and propulsion system applications, the required constitutive models must account for both reversible and irreversible time-dependent deformations. Furthermore, since an integral part of continuum-based computational methodologies (be they microscale- or macroscale-based) is an accurate and computationally efficient constitutive model to describe the deformation behavior of the materials of interest, extensive research efforts have been made over the years on the phenomenological representations of constitutive material behavior in the inelastic analysis of structures. From a more recent and comprehensive perspective, the NASA Glenn Research Center in conjunction with the University of Akron has emphasized concurrently addressing three important and related areas: that is, 1) Mathematical formulation; 2) Algorithmic developments for updating (integrating) the external (e.g., stress) and internal state variables; 3) Parameter estimation for characterizing the model. This concurrent perspective to constitutive modeling has enabled the overcoming of the two major obstacles to fully utilizing these sophisticated time-dependent (hereditary) constitutive models in practical engineering analysis. These obstacles are: 1) Lack of efficient and robust integration algorithms; 2) Difficulties associated with characterizing the large number of required material parameters, particularly when many of these parameters lack obvious or direct physical interpretations.

Are Earthquake Clusters/Supercycles Real or Random?

NASA Astrophysics Data System (ADS)

Salditch, L.; Brooks, E. M.; Stein, S.; Spencer, B. D.

2016-12-01

Long records of earthquakes at plate boundaries such as the San Andreas or Cascadia often show that large earthquakes occur in temporal clusters, also termed supercycles, separated by less active intervals. These are intriguing because the boundary is presumably being loaded by steady plate motion. If so, earthquakes resulting from seismic cycles - in which their probability is small shortly after the past one, and then increases with time - should occur quasi-periodically rather than be more frequent in some intervals than others. We are exploring this issue with two approaches. One is to assess whether the clusters result purely by chance from a time-independent process that has no "memory." Thus a future earthquake is equally likely immediately after the past one and much later, so earthquakes can cluster in time. We analyze the agreement between such a model and inter-event times for Parkfield, Pallet Creek, and other records. A useful tool is transformation by the inverse cumulative distribution function, so the inter-event times have a uniform distribution when the memorylessness property holds. The second is via a time-variable model in which earthquake probability increases with time between earthquakes and decreases after an earthquake. The probability of an event increases with time until one happens, after which it decreases, but not to zero. Hence after a long period of quiescence, the probability of an earthquake can remain higher than the long-term average for several cycles. Thus the probability of another earthquake is path dependent, i.e. depends on the prior earthquake history over multiple cycles. Time histories resulting from simulations give clusters with properties similar to those observed. The sequences of earthquakes result from both the model parameters and chance, so two runs with the same parameters look different. The model parameters control the average time between events and the variation of the actual times around this average, so models can be strongly or weakly time-dependent.

Mapping temporal dynamics in social interactions with unified structural equation modeling: A description and demonstration revealing time-dependent sex differences in play behavior

PubMed Central

Beltz, Adriene M.; Beekman, Charles; Molenaar, Peter C. M.; Buss, Kristin A.

2013-01-01

Developmental science is rich with observations of social interactions, but few available methodological and statistical approaches take full advantage of the information provided by these data. The authors propose implementation of the unified structural equation model (uSEM), a network analysis technique, for observational data coded repeatedly across time; uSEM captures the temporal dynamics underlying changes in behavior at the individual level by revealing the ways in which a single person influences – concurrently and in the future – other people. To demonstrate the utility of uSEM, the authors applied it to ratings of positive affect and vigor of activity during children’s unstructured laboratory play with unfamiliar, same-sex peers. Results revealed the time-dependent nature of sex differences in play behavior. For girls more than boys, positive affect was dependent upon peers’ prior positive affect. For boys more than girls, vigor of activity was dependent upon peers’ current vigor of activity. PMID:24039386

Downscaling near-surface soil moisture from field to plot scale: A comparative analysis under different environmental conditions

NASA Astrophysics Data System (ADS)

Nasta, Paolo; Penna, Daniele; Brocca, Luca; Zuecco, Giulia; Romano, Nunzio

2018-02-01

Indirect measurements of field-scale (hectometer grid-size) spatial-average near-surface soil moisture are becoming increasingly available by exploiting new-generation ground-based and satellite sensors. Nonetheless, modeling applications for water resources management require knowledge of plot-scale (1-5 m grid-size) soil moisture by using measurements through spatially-distributed sensor network systems. Since efforts to fulfill such requirements are not always possible due to time and budget constraints, alternative approaches are desirable. In this study, we explore the feasibility of determining spatial-average soil moisture and soil moisture patterns given the knowledge of long-term records of climate forcing data and topographic attributes. A downscaling approach is proposed that couples two different models: the Eco-Hydrological Bucket and Equilibrium Moisture from Topography. This approach helps identify the relative importance of two compound topographic indexes in explaining the spatial variation of soil moisture patterns, indicating valley- and hillslope-dependence controlled by lateral flow and radiative processes, respectively. The integrated model also detects temporal instability if the dominant type of topographic dependence changes with spatial-average soil moisture. Model application was carried out at three sites in different parts of Italy, each characterized by different environmental conditions. Prior calibration was performed by using sparse and sporadic soil moisture values measured by portable time domain reflectometry devices. Cross-site comparisons offer different interpretations in the explained spatial variation of soil moisture patterns, with time-invariant valley-dependence (site in northern Italy) and hillslope-dependence (site in southern Italy). The sources of soil moisture spatial variation at the site in central Italy are time-variant within the year and the seasonal change of topographic dependence can be conveniently correlated to a climate indicator such as the aridity index.

Comparative study of the requantization of the time-dependent mean field for the dynamics of nuclear pairing

NASA Astrophysics Data System (ADS)

Ni, Fang; Nakatsukasa, Takashi

2018-04-01

To describe quantal collective phenomena, it is useful to requantize the time-dependent mean-field dynamics. We study the time-dependent Hartree-Fock-Bogoliubov (TDHFB) theory for the two-level pairing Hamiltonian, and compare results of different quantization methods. The one constructing microscopic wave functions, using the TDHFB trajectories fulfilling the Einstein-Brillouin-Keller quantization condition, turns out to be the most accurate. The method is based on the stationary-phase approximation to the path integral. We also examine the performance of the collective model which assumes that the pairing gap parameter is the collective coordinate. The applicability of the collective model is limited for the nuclear pairing with a small number of single-particle levels, because the pairing gap parameter represents only a half of the pairing collective space.

Atomic Dynamics in Simple Liquid: de Gennes Narrowing Revisited

NASA Astrophysics Data System (ADS)

Wu, Bin; Iwashita, Takuya; Egami, Takeshi

2018-03-01

The de Gennes narrowing phenomenon is frequently observed by neutron or x -ray scattering measurements of the dynamics of complex systems, such as liquids, proteins, colloids, and polymers. The characteristic slowing down of dynamics in the vicinity of the maximum of the total scattering intensity is commonly attributed to enhanced cooperativity. In this Letter, we present an alternative view on its origin through the examination of the time-dependent pair correlation function, the van Hove correlation function, for a model liquid in two, three, and four dimensions. We find that the relaxation time increases monotonically with distance and the dependence on distance varies with dimension. We propose a heuristic explanation of this dependence based on a simple geometrical model. This finding sheds new light on the interpretation of the de Gennes narrowing phenomenon and the α -relaxation time.

Dose-dependent model of caffeine effects on human vigilance during total sleep deprivation.

PubMed

Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Wesensten, Nancy J; Kamimori, Gary H; Balkin, Thomas J; Reifman, Jaques

2014-10-07

Caffeine is the most widely consumed stimulant to counter sleep-loss effects. While the pharmacokinetics of caffeine in the body is well-understood, its alertness-restoring effects are still not well characterized. In fact, mathematical models capable of predicting the effects of varying doses of caffeine on objective measures of vigilance are not available. In this paper, we describe a phenomenological model of the dose-dependent effects of caffeine on psychomotor vigilance task (PVT) performance of sleep-deprived subjects. We used the two-process model of sleep regulation to quantify performance during sleep loss in the absence of caffeine and a dose-dependent multiplier factor derived from the Hill equation to model the effects of single and repeated caffeine doses. We developed and validated the model fits and predictions on PVT lapse (number of reaction times exceeding 500 ms) data from two separate laboratory studies. At the population-average level, the model captured the effects of a range of caffeine doses (50-300 mg), yielding up to a 90% improvement over the two-process model. Individual-specific caffeine models, on average, predicted the effects up to 23% better than population-average caffeine models. The proposed model serves as a useful tool for predicting the dose-dependent effects of caffeine on the PVT performance of sleep-deprived subjects and, therefore, can be used for determining caffeine doses that optimize the timing and duration of peak performance. Published by Elsevier Ltd.

Topographic evolution of orogens: The long term perspective

NASA Astrophysics Data System (ADS)

Robl, Jörg; Hergarten, Stefan; Prasicek, Günther

2017-04-01

The landscape of mountain ranges reflects the competition of tectonics and climate, that build up and destroy topography, respectively. While there is a broad consensus on the acting processes, there is a vital debate whether the topography of individual orogens reflects stages of growth, steady-state or decay. This debate is fuelled by the million-year time scales hampering direct observations on landscape evolution in mountain ranges, the superposition of various process patterns and the complex interactions among different processes. In this presentation we focus on orogen-scale landscape evolution based on time-dependent numerical models and explore model time series to constrain the development of mountain range topography during an orogenic cycle. The erosional long term response of rivers and hillslopes to uplift can be mathematically formalised by the stream power and mass diffusion equations, respectively, which enables us to describe the time-dependent evolution of topography in orogens. Based on a simple one-dimensional model consisting of two rivers separated by a watershed we explain the influence of uplift rate and rock erodibility on steady-state channel profiles and show the time-dependent development of the channel - drainage divide system. The effect of dynamic drainage network reorganization adds additional complexity and its effect on topography is explored on the basis of two-dimensional models. Further complexity is introduced by coupling a mechanical model (thin viscous sheet approach) describing continental collision, crustal thickening and topography formation with a stream power-based landscape evolution model. Model time series show the impact of crustal deformation on drainage networks and consequently on the evolution of mountain range topography (Robl et al., in review). All model outcomes, from simple one-dimensional to coupled two dimensional models are presented as movies featuring a high spatial and temporal resolution. Robl, J., S. Hergarten, and G. Prasicek (in review), The topographic state of mountain ranges, Earth Science Reviews.

Atomic collisions in the presence of laser radiation - Time dependence and the asymptotic wave function

NASA Technical Reports Server (NTRS)

Devries, P. L.; George, T. F.

1982-01-01

A time-dependent, wave-packet description of atomic collisions in the presence of laser radiation is extracted from the more conventional time-independent, stationary-state description. This approach resolves certain difficulties of interpretation in the time-independent approach which arise in the case of asymptotic near resonance. In the two-state model investigated, the approach predicts the existence of three spherically scattered waves in this asymptotically near-resonant case.

Spatio-temporal analysis of the electron power absorption in electropositive capacitive RF plasmas based on moments of the Boltzmann equation

NASA Astrophysics Data System (ADS)

Schulze, J.; Donkó, Z.; Lafleur, T.; Wilczek, S.; Brinkmann, R. P.

2018-05-01

Power absorption by electrons from the space- and time-dependent electric field represents the basic sustaining mechanism of all radio-frequency driven plasmas. This complex phenomenon has attracted significant attention. However, most theories and models are, so far, only able to account for part of the relevant mechanisms. The aim of this work is to present an in-depth analysis of the power absorption by electrons, via the use of a moment analysis of the Boltzmann equation without any ad-hoc assumptions. This analysis, for which the input quantities are taken from kinetic, particle based simulations, allows the identification of all physical mechanisms involved and an accurate quantification of their contributions. The perfect agreement between the sum of these contributions and the simulation results verifies the completeness of the model. We study the relative importance of these mechanisms as a function of pressure, with high spatial and temporal resolution, in an electropositive argon discharge. In contrast to some widely accepted previous models we find that high space- and time-dependent ambipolar electric fields outside the sheaths play a key role for electron power absorption. This ambipolar field is time-dependent within the RF period and temporally asymmetric, i.e., the sheath expansion is not a ‘mirror image’ of the sheath collapse. We demonstrate that this time-dependence is mainly caused by a time modulation of the electron temperature resulting from the energy transfer to electrons by the ambipolar field itself during sheath expansion. We provide a theoretical proof that this ambipolar electron power absorption would vanish completely, if the electron temperature was constant in time. This mechanism of electron power absorption is based on a time modulated electron temperature, markedly different from the Hard Wall Model, of key importance for energy transfer to electrons on time average and, thus, essential for the generation of capacitively coupled plasmas.

Predicting Young’s Modulus of Glass/Ceramic Sealant for Solid Oxide Fuel Cell Considering the Combined Effects of Aging, Micro-Voids and Self-Healing

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

Liu, Wenning N.; Sun, Xin; Khaleel, Mohammad A.

We study the temperature dependent Young’s modulus for the glass/ceramic seal material used in Solid Oxide Fuel Cells (SOFCs). With longer heat treatment or aging time during operation, further devitrification may reduce the residual glass content in the seal material while boosting the ceramic crystalline content. In the meantime, micro-voids induced by the cooling process from the high operating temperature to room temperature can potentially degrade the mechanical properties of the glass/ceramic sealant. Upon reheating to the SOFC operating temperature, possible self-healing phenomenon may occur in the glass/ceramic sealant which can potentially restore some of its mechanical properties. A phenomenologicalmore » model is developed to model the temperature dependent Young’s modulus of glass/ceramic seal considering the combined effects of aging, micro-voids, and possible self-healing. An aging-time-dependent crystalline content model is first developed to describe the increase of the crystalline content due to the continuing devitrification under high operating temperature. A continuum damage mechanics (CDM) model is then adapted to model the effects of both cooling induced micro-voids and reheating induced self-healing. This model is applied to model the glass-ceramic G18, a candidate SOFC seal material previously developed at PNNL. Experimentally determined temperature dependent Young’s modulus is used to validate the model predictions« less

Semiparametric regression analysis of failure time data with dependent interval censoring.

PubMed

Chen, Chyong-Mei; Shen, Pao-Sheng

2017-09-20

Interval-censored failure-time data arise when subjects are examined or observed periodically such that the failure time of interest is not examined exactly but only known to be bracketed between two adjacent observation times. The commonly used approaches assume that the examination times and the failure time are independent or conditionally independent given covariates. In many practical applications, patients who are already in poor health or have a weak immune system before treatment usually tend to visit physicians more often after treatment than those with better health or immune system. In this situation, the visiting rate is positively correlated with the risk of failure due to the health status, which results in dependent interval-censored data. While some measurable factors affecting health status such as age, gender, and physical symptom can be included in the covariates, some health-related latent variables cannot be observed or measured. To deal with dependent interval censoring involving unobserved latent variable, we characterize the visiting/examination process as recurrent event process and propose a joint frailty model to account for the association of the failure time and visiting process. A shared gamma frailty is incorporated into the Cox model and proportional intensity model for the failure time and visiting process, respectively, in a multiplicative way. We propose a semiparametric maximum likelihood approach for estimating model parameters and show the asymptotic properties, including consistency and weak convergence. Extensive simulation studies are conducted and a data set of bladder cancer is analyzed for illustrative purposes. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Solvent effects in time-dependent self-consistent field methods. I. Optical response calculations

DOE PAGES

Bjorgaard, J. A.; Kuzmenko, V.; Velizhanin, K. A.; ...

2015-01-22

In this study, we implement and examine three excited state solvent models in time-dependent self-consistent field methods using a consistent formalism which unambiguously shows their relationship. These are the linear response, state specific, and vertical excitation solvent models. Their effects on energies calculated with the equivalent of COSMO/CIS/AM1 are given for a set of test molecules with varying excited state charge transfer character. The resulting solvent effects are explained qualitatively using a dipole approximation. It is shown that the fundamental differences between these solvent models are reflected by the character of the calculated excitations.

Supervised Learning Using Spike-Timing-Dependent Plasticity of Memristive Synapses.

PubMed

Nishitani, Yu; Kaneko, Yukihiro; Ueda, Michihito

2015-12-01

We propose a supervised learning model that enables error backpropagation for spiking neural network hardware. The method is modeled by modifying an existing model to suit the hardware implementation. An example of a network circuit for the model is also presented. In this circuit, a three-terminal ferroelectric memristor (3T-FeMEM), which is a field-effect transistor with a gate insulator composed of ferroelectric materials, is used as an electric synapse device to store the analog synaptic weight. Our model can be implemented by reflecting the network error to the write voltage of the 3T-FeMEMs and introducing a spike-timing-dependent learning function to the device. An XOR problem was successfully demonstrated as a benchmark learning by numerical simulations using the circuit properties to estimate the learning performance. In principle, the learning time per step of this supervised learning model and the circuit is independent of the number of neurons in each layer, promising a high-speed and low-power calculation in large-scale neural networks.

Modelling the time-dependent frequency content of low-frequency volcanic earthquakes

NASA Astrophysics Data System (ADS)

Jousset, Philippe; Neuberg, Jürgen; Sturton, Susan

2003-11-01

Low-frequency volcanic earthquakes and tremor have been observed on seismic networks at a number of volcanoes, including Soufrière Hills volcano on Montserrat. Single events have well known characteristics, including a long duration (several seconds) and harmonic spectral peaks (0.2-5 Hz). They are commonly observed in swarms, and can be highly repetitive both in waveforms and amplitude spectra. As the time delay between them decreases, they merge into tremor, often preceding critical volcanic events like dome collapses or explosions. Observed amplitude spectrograms of long-period volcanic earthquake swarms may display gliding lines which reflect a time dependence in the frequency content. Using a magma-filled dyke embedded in a solid homogeneous half-space as a simplified volcanic structure, we employ a 2D finite-difference method to compute the propagation of seismic waves in the conduit and its vicinity. We successfully replicate the seismic wave field of a single low-frequency event, as well as the occurrence of events in swarms, their highly repetitive characteristics, and the time dependence of their spectral content. We use our model to demonstrate that there are two modes of conduit resonance, leading to two types of interface waves which are recorded at the free surface as surface waves. We also demonstrate that reflections from the top and the bottom of a conduit act as secondary sources that are recorded at the surface as repetitive low-frequency events with similar waveforms. We further expand our modelling to account for gradients in physical properties across the magma-solid interface. We also expand it to account for time dependence of magma properties, which we implement by changing physical properties within the conduit during numerical computation of wave propagation. We use our expanded model to investigate the amplitude and time scales required for modelling gliding lines, and show that changes in magma properties, particularly changes in the bubble nucleation level, provide a plausible mechanism for the frequency variation in amplitude spectrograms.

Probabilistic seismic hazard in the San Francisco Bay area based on a simplified viscoelastic cycle model of fault interactions

USGS Publications Warehouse

Pollitz, F.F.; Schwartz, D.P.

2008-01-01

We construct a viscoelastic cycle model of plate boundary deformation that includes the effect of time-dependent interseismic strain accumulation, coseismic strain release, and viscoelastic relaxation of the substrate beneath the seismogenic crust. For a given fault system, time-averaged stress changes at any point (not on a fault) are constrained to zero; that is, kinematic consistency is enforced for the fault system. The dates of last rupture, mean recurrence times, and the slip distributions of the (assumed) repeating ruptures are key inputs into the viscoelastic cycle model. This simple formulation allows construction of stress evolution at all points in the plate boundary zone for purposes of probabilistic seismic hazard analysis (PSHA). Stress evolution is combined with a Coulomb failure stress threshold at representative points on the fault segments to estimate the times of their respective future ruptures. In our PSHA we consider uncertainties in a four-dimensional parameter space: the rupture peridocities, slip distributions, time of last earthquake (for prehistoric ruptures) and Coulomb failure stress thresholds. We apply this methodology to the San Francisco Bay region using a recently determined fault chronology of area faults. Assuming single-segment rupture scenarios, we find that fature rupture probabilities of area faults in the coming decades are the highest for the southern Hayward, Rodgers Creek, and northern Calaveras faults. This conclusion is qualitatively similar to that of Working Group on California Earthquake Probabilities, but the probabilities derived here are significantly higher. Given that fault rupture probabilities are highly model-dependent, no single model should be used to assess to time-dependent rupture probabilities. We suggest that several models, including the present one, be used in a comprehensive PSHA methodology, as was done by Working Group on California Earthquake Probabilities.

Crypto-Unitary Forms of Quantum Evolution Operators

NASA Astrophysics Data System (ADS)

Znojil, Miloslav

2013-06-01

The description of quantum evolution using unitary operator {u}(t)=exp(-i{h}t) requires that the underlying self-adjoint quantum Hamiltonian {h} remains time-independent. In a way extending the so called {PT}-symmetric quantum mechanics to the models with manifestly time-dependent "charge" {C}(t) we propose and describe an extension of such an exponential-operator approach to evolution to the manifestly time-dependent self-adjoint quantum Hamiltonians {h}(t).

Time-dependent deformation of polymer network in polymer-stabilized cholesteric liquid crystals (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lee, Kyung Min; Tondiglia, Vincent P.; Bunning, Timothy J.; White, Timothy J.

2017-02-01

Recently, we reported direct current (DC) field controllable electro-optic (EO) responses of negative dielectric anisotropy polymer stabilized cholesteric liquid crystals (PSCLCs). A potential mechanism is: Ions in the liquid crystal mixtures are trapped in/on the polymer network during the fast photopolymerization process, and the movement of ions by the application of the DC field distorts polymer network toward the negative electrode, inducing pitch variation through the cell thickness, i.e., pitch compression on the negative electrode side and pitch expansion on positive electrode side. As the DC voltage is directly applied to a target voltage, charged polymer network is deformed and the reflection band is tuned. Interestingly, the polymer network deforms further (red shift of reflection band) with time when constantly applied DC voltage, illustrating DC field induced time dependent deformation of polymer network (creep-like behavior). This time dependent reflection band changes in PSCLCs are investigated by varying the several factors, such as type and concentration of photoinitiators, liquid crystal monomer content, and curing condition (UV intensity and curing time). In addition, simple linear viscoelastic spring-dashpot models, such as 2-parameter Kelvin and 3-parameter linear models, are used to investigate the time-dependent viscoelastic behaviors of polymer networks in PSCLC.

Time-of-flight dependency on transducer separation distance in a reflective-path guided-wave ultrasonic flow meter at zero flow conditions.

PubMed

Aanes, Magne; Kippersund, Remi Andre; Lohne, Kjetil Daae; Frøysa, Kjell-Eivind; Lunde, Per

2017-08-01

Transit-time flow meters based on guided ultrasonic wave propagation in the pipe spool have several advantages compared to traditional inline ultrasonic flow metering. The extended interrogation field, obtained by continuous leakage from guided waves traveling in the pipe wall, increases robustness toward entrained particles or gas in the flow. In reflective-path guided-wave ultrasonic flow meters (GW-UFMs), the flow equations are derived from signals propagating solely in the pipe wall and from signals passing twice through the fluid. In addition to the time-of-flight (TOF) through the fluid, the fluid path experiences an additional time delay upon reflection at the opposite pipe wall due to specular and non-specular reflections. The present work investigates the influence of these reflections on the TOF in a reflective-path GW-UFM as a function of transducer separation distance at zero flow conditions. Two models are used to describe the signal propagation through the system: (i) a transient full-wave finite element model, and (ii) a combined plane-wave and ray-tracing model. The study shows that a range-dependent time delay is associated with the reflection of the fluid path, introducing transmitter-receiver distance dependence. Based on these results, the applicability of the flow equations derived using model (ii) is discussed.

Tour time in a two-route traffic system controlled by signals

NASA Astrophysics Data System (ADS)

Nagatani, Takashi; Naito, Yuichi

2011-11-01

We study the dynamic behavior of vehicular traffic in a two-route system with a series of signals (traffic lights) at low density where the number of signals on route A is different from that on route B. We investigate the dependence of the tour time on the route for some strategies of signal control. The nonlinear dynamic model of a two-route traffic system controlled by signals is presented by nonlinear maps. The vehicular traffic exhibits a very complex behavior, depending on the cycle time, the phase difference, and the irregularity. The dependence of the tour time on the route choice is clarified for the signal strategies.

Non-linear Min protein interactions generate harmonics that signal mid-cell division in Escherichia coli

PubMed Central

Walsh, James C.; Angstmann, Christopher N.; Duggin, Iain G.

2017-01-01

The Min protein system creates a dynamic spatial pattern in Escherichia coli cells where the proteins MinD and MinE oscillate from pole to pole. MinD positions MinC, an inhibitor of FtsZ ring formation, contributing to the mid-cell localization of cell division. In this paper, Fourier analysis is used to decompose experimental and model MinD spatial distributions into time-dependent harmonic components. In both experiment and model, the second harmonic component is responsible for producing a mid-cell minimum in MinD concentration. The features of this harmonic are robust in both experiment and model. Fourier analysis reveals a close correspondence between the time-dependent behaviour of the harmonic components in the experimental data and model. Given this, each molecular species in the model was analysed individually. This analysis revealed that membrane-bound MinD dimer shows the mid-cell minimum with the highest contrast when averaged over time, carrying the strongest signal for positioning the cell division ring. This concurs with previous data showing that the MinD dimer binds to MinC inhibiting FtsZ ring formation. These results show that non-linear interactions of Min proteins are essential for producing the mid-cell positioning signal via the generation of second-order harmonic components in the time-dependent spatial protein distribution. PMID:29040283

Average inactivity time model, associated orderings and reliability properties

NASA Astrophysics Data System (ADS)

Kayid, M.; Izadkhah, S.; Abouammoh, A. M.

2018-02-01

In this paper, we introduce and study a new model called 'average inactivity time model'. This new model is specifically applicable to handle the heterogeneity of the time of the failure of a system in which some inactive items exist. We provide some bounds for the mean average inactivity time of a lifespan unit. In addition, we discuss some dependence structures between the average variable and the mixing variable in the model when original random variable possesses some aging behaviors. Based on the conception of the new model, we introduce and study a new stochastic order. Finally, to illustrate the concept of the model, some interesting reliability problems are reserved.

Global empirical model of TEC response to geomagnetic activity

NASA Astrophysics Data System (ADS)

Mukhtarov, P.; Andonov, B.; Pancheva, D.

2013-10-01

global total electron content (TEC) model response to geomagnetic activity described by the Kp index is built by using the Center for Orbit Determination of Europe (CODE) TEC data for a full 13 years, January 1999 to December 2011. The model describes the most probable spatial distribution and temporal variability of the geomagnetically forced TEC anomalies assuming that these anomalies at a given modified dip latitude depend mainly on the Kp index, local time (LT), and longitude. The geomagnetic anomalies are expressed by the relative deviation of TEC from its 15 day median and are denoted as rTEC. The rTEC response to the geomagnetic activity is presented by a sum of two responses with different time delay constants and different signs of the cross-correlation function. It has been found that the mean dependence of rTEC on Kp index can be expressed by a cubic function. The LT dependence of rTEC is described by Fourier time series which includes the contribution of four diurnal components with periods 24, 12, 8, and 6 h. The rTEC dependence on longitude is presented by Fourier series which includes the contribution of zonal waves with zonal wave numbers up to 6. In order to demonstrate how the model is able to reproduce the rTEC response to geomagnetic activity, three geomagnetic storms at different seasons and solar activity conditions are presented. The model residuals clearly reveal two types of the model deviation from the data: some underestimation of the largest TEC response to the geomagnetic activity and randomly distributed errors which are the data noise or anomalies generated by other sources. The presented TEC model fits to the CODE TEC input data with small negative bias of -0.204, root mean squares error RMSE = 4.592, and standard deviation error STDE = 4.588. The model offers TEC maps which depend on geographic coordinates (5° × 5° in latitude and longitude) and universal time (UT) at given geomagnetic activity and day of the year. It could be used for both science and possible service (nowcasting and short-term prediction); for the latter, a detailed validation of the model at different geophysical conditions has to be performed in order to clarify the model predicting quality.

Validation of methods to control for immortal time bias in a pharmacoepidemiologic analysis of renin-angiotensin system inhibitors in type 2 diabetes.

PubMed

Yang, Xilin; Kong, Alice Ps; Luk, Andrea Oy; Ozaki, Risa; Ko, Gary Tc; Ma, Ronald Cw; Chan, Juliana Cn; So, Wing Yee

2014-01-01

Pharmacoepidemiologic analysis can confirm whether drug efficacy in a randomized controlled trial (RCT) translates to effectiveness in real settings. We examined methods used to control for immortal time bias in an analysis of renin-angiotensin system (RAS) inhibitors as the reference cardioprotective drug. We analyzed data from 3928 patients with type 2 diabetes who were recruited into the Hong Kong Diabetes Registry between 1996 and 2005 and followed up to July 30, 2005. Different Cox models were used to obtain hazard ratios (HRs) for cardiovascular disease (CVD) associated with RAS inhibitors. These HRs were then compared to the HR of 0.92 reported in a recent meta-analysis of RCTs. During a median follow-up period of 5.45 years, 7.23% (n = 284) patients developed CVD and 38.7% (n = 1519) were started on RAS inhibitors, with 39.1% of immortal time among the users. In multivariable analysis, time-dependent drug-exposure Cox models and Cox models that moved immortal time from users to nonusers both severely inflated the HR, and time-fixed models that included immortal time deflated the HR. Use of time-fixed Cox models that excluded immortal time resulted in a HR of only 0.89 (95% CI, 0.68-1.17) for CVD associated with RAS inhibitors, which is closer to the values reported in RCTs. In pharmacoepidemiologic analysis, time-dependent drug exposure models and models that move immortal time from users to nonusers may introduce substantial bias in investigations of the effects of RAS inhibitors on CVD in type 2 diabetes.

Error modeling for surrogates of dynamical systems using machine learning: Machine-learning-based error model for surrogates of dynamical systems

DOE PAGES

Trehan, Sumeet; Carlberg, Kevin T.; Durlofsky, Louis J.

2017-07-14

A machine learning–based framework for modeling the error introduced by surrogate models of parameterized dynamical systems is proposed. The framework entails the use of high-dimensional regression techniques (eg, random forests, and LASSO) to map a large set of inexpensively computed “error indicators” (ie, features) produced by the surrogate model at a given time instance to a prediction of the surrogate-model error in a quantity of interest (QoI). This eliminates the need for the user to hand-select a small number of informative features. The methodology requires a training set of parameter instances at which the time-dependent surrogate-model error is computed bymore » simulating both the high-fidelity and surrogate models. Using these training data, the method first determines regression-model locality (via classification or clustering) and subsequently constructs a “local” regression model to predict the time-instantaneous error within each identified region of feature space. We consider 2 uses for the resulting error model: (1) as a correction to the surrogate-model QoI prediction at each time instance and (2) as a way to statistically model arbitrary functions of the time-dependent surrogate-model error (eg, time-integrated errors). We then apply the proposed framework to model errors in reduced-order models of nonlinear oil-water subsurface flow simulations, with time-varying well-control (bottom-hole pressure) parameters. The reduced-order models used in this work entail application of trajectory piecewise linearization in conjunction with proper orthogonal decomposition. Moreover, when the first use of the method is considered, numerical experiments demonstrate consistent improvement in accuracy in the time-instantaneous QoI prediction relative to the original surrogate model, across a large number of test cases. When the second use is considered, results show that the proposed method provides accurate statistical predictions of the time- and well-averaged errors.« less

Error modeling for surrogates of dynamical systems using machine learning: Machine-learning-based error model for surrogates of dynamical systems

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

Trehan, Sumeet; Carlberg, Kevin T.; Durlofsky, Louis J.

A machine learning–based framework for modeling the error introduced by surrogate models of parameterized dynamical systems is proposed. The framework entails the use of high-dimensional regression techniques (eg, random forests, and LASSO) to map a large set of inexpensively computed “error indicators” (ie, features) produced by the surrogate model at a given time instance to a prediction of the surrogate-model error in a quantity of interest (QoI). This eliminates the need for the user to hand-select a small number of informative features. The methodology requires a training set of parameter instances at which the time-dependent surrogate-model error is computed bymore » simulating both the high-fidelity and surrogate models. Using these training data, the method first determines regression-model locality (via classification or clustering) and subsequently constructs a “local” regression model to predict the time-instantaneous error within each identified region of feature space. We consider 2 uses for the resulting error model: (1) as a correction to the surrogate-model QoI prediction at each time instance and (2) as a way to statistically model arbitrary functions of the time-dependent surrogate-model error (eg, time-integrated errors). We then apply the proposed framework to model errors in reduced-order models of nonlinear oil-water subsurface flow simulations, with time-varying well-control (bottom-hole pressure) parameters. The reduced-order models used in this work entail application of trajectory piecewise linearization in conjunction with proper orthogonal decomposition. Moreover, when the first use of the method is considered, numerical experiments demonstrate consistent improvement in accuracy in the time-instantaneous QoI prediction relative to the original surrogate model, across a large number of test cases. When the second use is considered, results show that the proposed method provides accurate statistical predictions of the time- and well-averaged errors.« less

Time-dependent sorption of two novel fungicides in soils within a regulatory framework.

PubMed

Gulkowska, Anna; Buerge, Ignaz J; Poiger, Thomas; Kasteel, Roy

2016-12-01

Convincing experimental evidence suggests increased sorption of pesticides on soil over time, which, so far, has not been considered in the regulatory assessment of leaching to groundwater. Recently, Beulke and van Beinum (2012) proposed a guidance on how to conduct, analyse and use time-dependent sorption studies in pesticide registration. The applicability of the recommended experimental set-up and fitting procedure was examined for two fungicides, penflufen and fluxapyroxad, in four soils during a 170 day incubation experiment. The apparent distribution coefficient increased by a factor of 2.5-4.5 for penflufen and by a factor of 2.5-2.8 for fluxapyroxad. The recommended two-site, one-rate sorption model adequately described measurements of total mass and liquid phase concentration in the calcium chloride suspension and the calculated apparent distribution coefficient, passing all prescribed quality criteria for model fit and parameter reliability. The guidance is technically mature regarding the experimental set-up and parameterisation of the sorption model for the two moderately mobile and relatively persistent fungicides under investigation. These parameters can be used for transport modelling in soil, thereby recognising the existence of the experimentally observed, but in the regulatory leaching assessment of pesticides not yet routinely considered phenomenon of time-dependent sorption. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Boundary versus bulk behavior of time-dependent correlation functions in one-dimensional quantum systems

NASA Astrophysics Data System (ADS)

Eliëns, I. S.; Ramos, F. B.; Xavier, J. C.; Pereira, R. G.

2016-05-01

We study the influence of reflective boundaries on time-dependent responses of one-dimensional quantum fluids at zero temperature beyond the low-energy approximation. Our analysis is based on an extension of effective mobile impurity models for nonlinear Luttinger liquids to the case of open boundary conditions. For integrable models, we show that boundary autocorrelations oscillate as a function of time with the same frequency as the corresponding bulk autocorrelations. This frequency can be identified as the band edge of elementary excitations. The amplitude of the oscillations decays as a power law with distinct exponents at the boundary and in the bulk, but boundary and bulk exponents are determined by the same coupling constant in the mobile impurity model. For nonintegrable models, we argue that the power-law decay of the oscillations is generic for autocorrelations in the bulk, but turns into an exponential decay at the boundary. Moreover, there is in general a nonuniversal shift of the boundary frequency in comparison with the band edge of bulk excitations. The predictions of our effective field theory are compared with numerical results obtained by time-dependent density matrix renormalization group (tDMRG) for both integrable and nonintegrable critical spin-S chains with S =1 /2 , 1, and 3 /2 .

Global convergence in leaf respiration from estimates of thermal acclimation across time and space.

PubMed

Vanderwel, Mark C; Slot, Martijn; Lichstein, Jeremy W; Reich, Peter B; Kattge, Jens; Atkin, Owen K; Bloomfield, Keith J; Tjoelker, Mark G; Kitajima, Kaoru

2015-09-01

Recent compilations of experimental and observational data have documented global temperature-dependent patterns of variation in leaf dark respiration (R), but it remains unclear whether local adjustments in respiration over time (through thermal acclimation) are consistent with the patterns in R found across geographical temperature gradients. We integrated results from two global empirical syntheses into a simple temperature-dependent respiration framework to compare the measured effects of respiration acclimation-over-time and variation-across-space to one another, and to a null model in which acclimation is ignored. Using these models, we projected the influence of thermal acclimation on: seasonal variation in R; spatial variation in mean annual R across a global temperature gradient; and future increases in R under climate change. The measured strength of acclimation-over-time produces differences in annual R across spatial temperature gradients that agree well with global variation-across-space. Our models further project that acclimation effects could potentially halve increases in R (compared with the null model) as the climate warms over the 21st Century. Convergence in global temperature-dependent patterns of R indicates that physiological adjustments arising from thermal acclimation are capable of explaining observed variation in leaf respiration at ambient growth temperatures across the globe. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

3DFEMWATER: A three-dimensional finite element model of water flow through saturated-unsaturated media

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

Yeh, G.T.

1987-08-01

The 3DFEMWATER model is designed to treat heterogeneous and anisotropic media consisting of as many geologic formations as desired, consider both distributed and point sources/sinks that are spatially and temporally dependent, accept the prescribed initial conditions or obtain them by simulating a steady state version of the system under consideration, deal with a transient head distributed over the Dirichlet boundary, handle time-dependent fluxes due to pressure gradient varying along the Neumann boundary, treat time-dependent total fluxes distributed over the Cauchy boundary, automatically determine variable boundary conditions of evaporation, infiltration, or seepage on the soil-air interface, include the off-diagonal hydraulic conductivitymore » components in the modified Richards equation for dealing with cases when the coordinate system does not coincide with the principal directions of the hydraulic conductivity tensor, give three options for estimating the nonlinear matrix, include two options (successive subregion block iterations and successive point interactions) for solving the linearized matrix equations, automatically reset time step size when boundary conditions or source/sinks change abruptly, and check the mass balance computation over the entire region for every time step. The model is verified with analytical solutions or other numerical models for three examples.« less

Study on reservoir time-varying design flood of inflow based on Poisson process with time-dependent parameters

NASA Astrophysics Data System (ADS)

Li, Jiqing; Huang, Jing; Li, Jianchang

2018-06-01

The time-varying design flood can make full use of the measured data, which can provide the reservoir with the basis of both flood control and operation scheduling. This paper adopts peak over threshold method for flood sampling in unit periods and Poisson process with time-dependent parameters model for simulation of reservoirs time-varying design flood. Considering the relationship between the model parameters and hypothesis, this paper presents the over-threshold intensity, the fitting degree of Poisson distribution and the design flood parameters are the time-varying design flood unit period and threshold discriminant basis, deduced Longyangxia reservoir time-varying design flood process at 9 kinds of design frequencies. The time-varying design flood of inflow is closer to the reservoir actual inflow conditions, which can be used to adjust the operating water level in flood season and make plans for resource utilization of flood in the basin.

Time-dependent importance sampling in semiclassical initial value representation calculations for time correlation functions.

PubMed

Tao, Guohua; Miller, William H

2011-07-14

An efficient time-dependent importance sampling method is developed for the Monte Carlo calculation of time correlation functions via the initial value representation (IVR) of semiclassical (SC) theory. A prefactor-free time-dependent sampling function weights the importance of a trajectory based on the magnitude of its contribution to the time correlation function, and global trial moves are used to facilitate the efficient sampling the phase space of initial conditions. The method can be generally applied to sampling rare events efficiently while avoiding being trapped in a local region of the phase space. Results presented in the paper for two system-bath models demonstrate the efficiency of this new importance sampling method for full SC-IVR calculations.

Path-Dependent Travel Time Prediction Variance and Covariance for a Global Tomographic P- and S-Velocity Model

NASA Astrophysics Data System (ADS)

Hipp, J. R.; Ballard, S.; Begnaud, M. L.; Encarnacao, A. V.; Young, C. J.; Phillips, W. S.

2015-12-01

Recently our combined SNL-LANL research team has succeeded in developing a global, seamless 3D tomographic P- and S-velocity model (SALSA3D) that provides superior first P and first S travel time predictions at both regional and teleseismic distances. However, given the variable data quality and uneven data sampling associated with this type of model, it is essential that there be a means to calculate high-quality estimates of the path-dependent variance and covariance associated with the predicted travel times of ray paths through the model. In this paper, we describe a methodology for accomplishing this by exploiting the full model covariance matrix and show examples of path-dependent travel time prediction uncertainty computed from our latest tomographic model. Typical global 3D SALSA3D models have on the order of 1/2 million nodes, so the challenge in calculating the covariance matrix is formidable: 0.9 TB storage for 1/2 of a symmetric matrix, necessitating an Out-Of-Core (OOC) blocked matrix solution technique. With our approach the tomography matrix (G which includes a prior model covariance constraint) is multiplied by its transpose (GTG) and written in a blocked sub-matrix fashion. We employ a distributed parallel solution paradigm that solves for (GTG)-1 by assigning blocks to individual processing nodes for matrix decomposition update and scaling operations. We first find the Cholesky decomposition of GTG which is subsequently inverted. Next, we employ OOC matrix multiplication methods to calculate the model covariance matrix from (GTG)-1 and an assumed data covariance matrix. Given the model covariance matrix, we solve for the travel-time covariance associated with arbitrary ray-paths by summing the model covariance along both ray paths. Setting the paths equal and taking the square root yields the travel prediction uncertainty for the single path.

Stroke Onset Time Determination Using MRI Relaxation Times without Non-Ischaemic Reference in A Rat Stroke Model

PubMed Central

Knight, Michael J.; McGarry, Bryony M.; Jokivarsi, Kimmo T.; Gröhn, Olli H.J.; Kauppinen, Risto A.

2017-01-01

Background Objective timing of stroke in emergency departments is expected to improve patient stratification. Magnetic resonance imaging (MRI) relaxations times, T2 and T1ρ, in abnormal diffusion delineated ischaemic tissue were used as proxies of stroke time in a rat model. Methods Both ‘non-ischaemic reference’-dependent and -independent estimators were generated. Apparent diffusion coefficient (ADC), T2 and T1ρ, were sequentially quantified for up to 6 hours of stroke in rats (n = 8) at 4.7T. The ischaemic lesion was identified as a contiguous collection of voxels with low ADC. T2 and T1ρ in the ischaemic lesion and in the contralateral non-ischaemic brain tissue were determined. Differences in mean MRI relaxation times between ischaemic and non-ischaemic volumes were used to create reference-dependent estimator. For the reference-independent procedure, only the parameters associated with log-logistic fits to the T2 and T1ρ distributions within the ADC-delineated lesions were used for the onset time estimation. Result The reference-independent estimators from T2 and T1ρ data provided stroke onset time with precisions of ±32 and ±27 minutes, respectively. The reference-dependent estimators yielded respective precisions of ±47 and ±54 minutes. Conclusions A ‘non-ischaemic anatomical reference’-independent estimator for stroke onset time from relaxometric MRI data is shown to yield greater timing precision than previously obtained through reference-dependent procedures. PMID:28685128

Memory-dependent derivatives for photothermal semiconducting medium in generalized thermoelasticity with two-temperature

NASA Astrophysics Data System (ADS)

Lotfy, K.; Sarkar, N.

2017-11-01

In this work, a novel generalized model of photothermal theory with two-temperature thermoelasticity theory based on memory-dependent derivative (MDD) theory is performed. A one-dimensional problem for an elastic semiconductor material with isotropic and homogeneous properties has been considered. The problem is solved with a new model (MDD) under the influence of a mechanical force with a photothermal excitation. The Laplace transform technique is used to remove the time-dependent terms in the governing equations. Moreover, the general solutions of some physical fields are obtained. The surface taken into consideration is free of traction and subjected to a time-dependent thermal shock. The numerical Laplace inversion is used to obtain the numerical results of the physical quantities of the problem. Finally, the obtained results are presented and discussed graphically.

Relaxation limit of a compressible gas-liquid model with well-reservoir interaction

NASA Astrophysics Data System (ADS)

Solem, Susanne; Evje, Steinar

2017-02-01

This paper deals with the relaxation limit of a two-phase compressible gas-liquid model which contains a pressure-dependent well-reservoir interaction term of the form q (P_r - P) where q>0 is the rate of the pressure-dependent influx/efflux of gas, P is the (unknown) wellbore pressure, and P_r is the (known) surrounding reservoir pressure. The model can be used to study gas-kick flow scenarios relevant for various wellbore operations. One extreme case is when the wellbore pressure P is largely dictated by the surrounding reservoir pressure P_r. Formally, this model is obtained by deriving the limiting system as the relaxation parameter q in the full model tends to infinity. The main purpose of this work is to understand to what extent this case can be represented by a well-defined mathematical model for a fixed global time T>0. Well-posedness of the full model has been obtained in Evje (SIAM J Math Anal 45(2):518-546, 2013). However, as the estimates for the full model are dependent on the relaxation parameter q, new estimates must be obtained for the equilibrium model to ensure existence of solutions. By means of appropriate a priori assumptions and some restrictions on the model parameters, necessary estimates (low order and higher order) are obtained. These estimates that depend on the global time T together with smallness assumptions on the initial data are then used to obtain existence of solutions in suitable Sobolev spaces.

Evaluation of Mass Filtered, Time Dilated, Time-of-Flight Mass Spectrometry

DTIC Science & Technology

2010-01-01

Figure 4.4: Mass resolution dependence on field for selected actinides and surrogates...45 Figure 4.7: Mass resolution dependence on field for selected actinides and actinide surrogates, modeled with no initial...system. A somewhat better mass resolution would need to be achieved in order to separate hydride molecules in the actinide region. However, the

A hazard rate analysis of fertility using duration data from Malaysia.

PubMed

Chang, C

1988-01-01

Data from the Malaysia Fertility and Family Planning Survey (MFLS) of 1974 were used to investigate the effects of biological and socioeconomic variables on fertility based on the hazard rate model. Another study objective was to investigate the robustness of the findings of Trussell et al. (1985) by comparing the findings of this study with theirs. The hazard rate of conception for the jth fecundable spell of the ith woman, hij, is determined by duration dependence, tij, measured by the waiting time to conception; unmeasured heterogeneity (HETi; the time-invariant variables, Yi (race, cohort, education, age at marriage); and time-varying variables, Xij (age, parity, opportunity cost, income, child mortality, child sex composition). In this study, all the time-varying variables were constant over a spell. An asymptotic X2 test for the equality of constant hazard rates across birth orders, allowing time-invariant variables and heterogeneity, showed the importance of time-varying variables and duration dependence. Under the assumption of fixed effects heterogeneity and the Weibull distribution for the duration of waiting time to conception, the empirical results revealed a negative parity effect, a negative impact from male children, and a positive effect from child mortality on the hazard rate of conception. The estimates of step functions for the hazard rate of conception showed parity-dependent fertility control, evidence of heterogeneity, and the possibility of nonmonotonic duration dependence. In a hazard rate model with piecewise-linear-segment duration dependence, the socioeconomic variables such as cohort, child mortality, income, and race had significant effects, after controlling for the length of the preceding birth. The duration dependence was consistant with the common finding, i.e., first increasing and then decreasing at a slow rate. The effects of education and opportunity cost on fertility were insignificant.

Time-dependent diffusion MRI in cancer: tissue modeling and applications

NASA Astrophysics Data System (ADS)

Reynaud, Olivier

2017-11-01

In diffusion weighted imaging (DWI), the apparent diffusion coefficient has been recognized as a useful and sensitive surrogate for cell density, paving the way for non-invasive tumor staging, and characterization of treatment efficacy in cancer. However, microstructural parameters, such as cell size, density and/or compartmental diffusivities affect diffusion in various fashions, making of conventional DWI a sensitive but non-specific probe into changes happening at cellular level. Alternatively, tissue complexity can be probed and quantified using the time dependence of diffusion metrics, sometimes also referred to as temporal diffusion spectroscopy when only using oscillating diffusion gradients. Time-dependent diffusion (TDD) is emerging as a strong candidate for specific and non-invasive tumor characterization. Despite the lack of a general analytical solution for all diffusion times / frequencies, TDD can be probed in various regimes where systems simplify in order to extract relevant information about tissue microstructure. The fundamentals of TDD are first reviewed (a) in the short time regime, disentangling structural and diffusive tissue properties, and (b) near the tortuosity limit, assuming weakly heterogeneous media near infinitely long diffusion times. Focusing on cell bodies (as opposed to neuronal tracts), a simple but realistic model for intracellular diffusion can offer precious insight on diffusion inside biological systems, at all times. Based on this approach, the main three geometrical models implemented so far (IMPULSED, POMACE, VERDICT) are reviewed. Their suitability to quantify cell size, intra- and extracellular spaces (ICS and ECS) and diffusivities are assessed. The proper modeling of tissue membrane permeability – hardly a newcomer in the field, but lacking applications - and its impact on microstructural estimates are also considered. After discussing general issues with tissue modeling and microstructural parameter estimation (i.e. fitting), potential solutions are detailed. The in vivo applications of this new, non-invasive, specific approach in cancer are reviewed, ranging from the characterization of gliomas in rodent brains and observation of time-dependence in breast tissue lesions and prostate cancer, to the recent preclinical evaluation of new treatments efficacy. It is expected that clinical applications of TDD will strongly benefit the community in terms of non-invasive cancer screening.

The time dependence of rock healing as a universal relaxation process, a tutorial

NASA Astrophysics Data System (ADS)

Snieder, Roel; Sens-Schönfelder, Christoph; Wu, Renjie

2017-01-01

The material properties of earth materials often change after the material has been perturbed (slow dynamics). For example, the seismic velocity of subsurface materials changes after earthquakes, and granular materials compact after being shaken. Such relaxation processes are associated by observables that change logarithmically with time. Since the logarithm diverges for short and long times, the relaxation can, strictly speaking, not have a log-time dependence. We present a self-contained description of a relaxation function that consists of a superposition of decaying exponentials that has log-time behaviour for intermediate times, but converges to zero for long times, and is finite for t = 0. The relaxation function depends on two parameters, the minimum and maximum relaxation time. These parameters can, in principle, be extracted from the observed relaxation. As an example, we present a crude model of a fracture that is closing under an external stress. Although the fracture model violates some of the assumptions on which the relaxation function is based, it follows the relaxation function well. We provide qualitative arguments that the relaxation process, just like the Gutenberg-Richter law, is applicable to a wide range of systems and has universal properties.

Deterministic Local Sensitivity Analysis of Augmented Systems - II: Applications to the QUENCH-04 Experiment Using the RELAP5/MOD3.2 Code System

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

Ionescu-Bujor, Mihaela; Jin Xuezhou; Cacuci, Dan G.

2005-09-15

The adjoint sensitivity analysis procedure for augmented systems for application to the RELAP5/MOD3.2 code system is illustrated. Specifically, the adjoint sensitivity model corresponding to the heat structure models in RELAP5/MOD3.2 is derived and subsequently augmented to the two-fluid adjoint sensitivity model (ASM-REL/TF). The end product, called ASM-REL/TFH, comprises the complete adjoint sensitivity model for the coupled fluid dynamics/heat structure packages of the large-scale simulation code RELAP5/MOD3.2. The ASM-REL/TFH model is validated by computing sensitivities to the initial conditions for various time-dependent temperatures in the test bundle of the Quench-04 reactor safety experiment. This experiment simulates the reflooding with water ofmore » uncovered, degraded fuel rods, clad with material (Zircaloy-4) that has the same composition and size as that used in typical pressurized water reactors. The most important response for the Quench-04 experiment is the time evolution of the cladding temperature of heated fuel rods. The ASM-REL/TFH model is subsequently used to perform an illustrative sensitivity analysis of this and other time-dependent temperatures within the bundle. The results computed by using the augmented adjoint sensitivity system, ASM-REL/TFH, highlight the reliability, efficiency, and usefulness of the adjoint sensitivity analysis procedure for computing time-dependent sensitivities.« less

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

PubMed Central

Hübel, Niklas; Dahlem, Markus A.

2014-01-01

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

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

Dehart, Mark; Mausolff, Zander; Goluoglu, Sedat

This report summarizes university research activities performed in support of TREAT modeling and simulation research. It is a compilation of annual research reports from four universities: University of Florida, Texas A&M University, Massachusetts Institute of Technology and Oregon State University. The general research topics are, respectively, (1) 3-D time-dependent transport with TDKENO/KENO-VI, (2) implementation of the Improved Quasi-Static method in Rattlesnake/MOOSE for time-dependent radiation transport approximations, (3) improved treatment of neutron physics representations within TREAT using OpenMC, and (4) steady state modeling of the minimum critical core of the Transient Reactor Test Facility (TREAT).

Distributional behavior of diffusion coefficients obtained by single trajectories in annealed transit time model

NASA Astrophysics Data System (ADS)

Akimoto, Takuma; Yamamoto, Eiji

2016-12-01

Local diffusion coefficients in disordered systems such as spin glass systems and living cells are highly heterogeneous and may change over time. Such a time-dependent and spatially heterogeneous environment results in irreproducibility of single-particle-tracking measurements. Irreproducibility of time-averaged observables has been theoretically studied in the context of weak ergodicity breaking in stochastic processes. Here, we provide rigorous descriptions of equilibrium and non-equilibrium diffusion processes for the annealed transit time model, which is a heterogeneous diffusion model in living cells. We give analytical solutions for the mean square displacement (MSD) and the relative standard deviation of the time-averaged MSD for equilibrium and non-equilibrium situations. We find that the time-averaged MSD grows linearly with time and that the time-averaged diffusion coefficients are intrinsically random (irreproducible) even in the long-time measurements in non-equilibrium situations. Furthermore, the distribution of the time-averaged diffusion coefficients converges to a universal distribution in the sense that it does not depend on initial conditions. Our findings pave the way for a theoretical understanding of distributional behavior of the time-averaged diffusion coefficients in disordered systems.

Dynamic circadian modulation in a biomathematical model for the effects of sleep and sleep loss on waking neurobehavioral performance.

PubMed

McCauley, Peter; Kalachev, Leonid V; Mollicone, Daniel J; Banks, Siobhan; Dinges, David F; Van Dongen, Hans P A

2013-12-01

Recent experimental observations and theoretical advances have indicated that the homeostatic equilibrium for sleep/wake regulation--and thereby sensitivity to neurobehavioral impairment from sleep loss--is modulated by prior sleep/wake history. This phenomenon was predicted by a biomathematical model developed to explain changes in neurobehavioral performance across days in laboratory studies of total sleep deprivation and sustained sleep restriction. The present paper focuses on the dynamics of neurobehavioral performance within days in this biomathematical model of fatigue. Without increasing the number of model parameters, the model was updated by incorporating time-dependence in the amplitude of the circadian modulation of performance. The updated model was calibrated using a large dataset from three laboratory experiments on psychomotor vigilance test (PVT) performance, under conditions of sleep loss and circadian misalignment; and validated using another large dataset from three different laboratory experiments. The time-dependence of circadian amplitude resulted in improved goodness-of-fit in night shift schedules, nap sleep scenarios, and recovery from prior sleep loss. The updated model predicts that the homeostatic equilibrium for sleep/wake regulation--and thus sensitivity to sleep loss--depends not only on the duration but also on the circadian timing of prior sleep. This novel theoretical insight has important implications for predicting operator alertness during work schedules involving circadian misalignment such as night shift work.

Limitations to the use of two-dimensional thermal modeling of a nuclear waste repository

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

Davis, B.W.

1979-01-04

Thermal modeling of a nuclear waste repository is basic to most waste management predictive models. It is important that the modeling techniques accurately determine the time-dependent temperature distribution of the waste emplacement media. Recent modeling studies show that the time-dependent temperature distribution can be accurately modeled in the far-field using a 2-dimensional (2-D) planar numerical model; however, the near-field cannot be modeled accurately enough by either 2-D axisymmetric or 2-D planar numerical models for repositories in salt. The accuracy limits of 2-D modeling were defined by comparing results from 3-dimensional (3-D) TRUMP modeling with results from both 2-D axisymmetric andmore » 2-D planar. Both TRUMP and ADINAT were employed as modeling tools. Two-dimensional results from the finite element code, ADINAT were compared with 2-D results from the finite difference code, TRUMP; they showed almost perfect correspondence in the far-field. This result adds substantially to confidence in future use of ADINAT and its companion stress code ADINA for thermal stress analysis. ADINAT was found to be somewhat sensitive to time step and mesh aspect ratio. 13 figures, 4 tables.« less

Evolution model with a cumulative feedback coupling

NASA Astrophysics Data System (ADS)

Trimper, Steffen; Zabrocki, Knud; Schulz, Michael

2002-05-01

The paper is concerned with a toy model that generalizes the standard Lotka-Volterra equation for a certain population by introducing a competition between instantaneous and accumulative, history-dependent nonlinear feedback the origin of which could be a contribution from any kind of mismanagement in the past. The results depend on the sign of that additional cumulative loss or gain term of strength λ. In case of a positive coupling the system offers a maximum gain achieved after a finite time but the population will die out in the long time limit. In this case the instantaneous loss term of strength u is irrelevant and the model exhibits an exact solution. In the opposite case λ<0 the time evolution of the system is terminated in a crash after ts provided u=0. This singularity after a finite time can be avoided if u≠0. The approach may well be of relevance for the qualitative understanding of more realistic descriptions.

The fractional derivative Kelvin–Voigt model of viscoelasticity with and without volumetric relaxation

NASA Astrophysics Data System (ADS)

Rossikhin, Yu A.; Shitikova, M. V.

2018-04-01

The fractional derivative Kelvin–Voigt model of viscoelasticity involving the time-dependent Poisson’s operator has been studied not only for the case of a time-independent bulk modulus, but also when the volumetric relaxation is taken into account. It has been shown that such a model could describe the features of auxetic materials.

Multi-Step Time Series Forecasting with an Ensemble of Varied Length Mixture Models.

PubMed

Ouyang, Yicun; Yin, Hujun

2018-05-01

Many real-world problems require modeling and forecasting of time series, such as weather temperature, electricity demand, stock prices and foreign exchange (FX) rates. Often, the tasks involve predicting over a long-term period, e.g. several weeks or months. Most existing time series models are inheritably for one-step prediction, that is, predicting one time point ahead. Multi-step or long-term prediction is difficult and challenging due to the lack of information and uncertainty or error accumulation. The main existing approaches, iterative and independent, either use one-step model recursively or treat the multi-step task as an independent model. They generally perform poorly in practical applications. In this paper, as an extension of the self-organizing mixture autoregressive (AR) model, the varied length mixture (VLM) models are proposed to model and forecast time series over multi-steps. The key idea is to preserve the dependencies between the time points within the prediction horizon. Training data are segmented to various lengths corresponding to various forecasting horizons, and the VLM models are trained in a self-organizing fashion on these segments to capture these dependencies in its component AR models of various predicting horizons. The VLM models form a probabilistic mixture of these varied length models. A combination of short and long VLM models and an ensemble of them are proposed to further enhance the prediction performance. The effectiveness of the proposed methods and their marked improvements over the existing methods are demonstrated through a number of experiments on synthetic data, real-world FX rates and weather temperatures.

Cardiac transient outward potassium current: a pulse chemistry model of frequency-dependent properties.

PubMed

Liu, L; Krinsky, V I; Grant, A O; Starmer, C F

1996-01-01

Recent voltage-clamp studies of isolated myocytes have demonstrated widespread occurrence of a transient outward current (I(to)) carried by potassium ions. In the canine ventricle, this current is well developed in epicardial cells but not in endocardial cells. The resultant spatial dispersion of refractoriness is potentially proarrhythmic and may be amplified by channel blockade. The inactivation and recovery time constants of this channel are in excess of several hundred milliseconds, and consequently channel availability is frequency dependent at physiological stimulation rates. When the time constants associated with transitions between different channel conformations are rapid relative to drug binding kinetics, the interactions between drugs and an ion channel can be approximated by a sequence of first-order reactions, in which binding occurs in pulses in response to pulse train stimulation (pulse chemistry). When channel conformation transition time constants do not meet this constraint, analytical characterizations of the drug-channel interaction must then be modified to reflect the channel time-dependent properties. Here we report that the rate and steady-state amount of frequency-dependent inactivation of I(to) are consistent with a generalization of the channel blockade model: channel availability is reduced in a pulsatile exponential pattern as the stimulation frequency is increased, and the rate of reduction is a linear function of the pulse train depolarizing and recovery intervals. I(to) was reduced in the presence of quinidine. After accounting for the use-dependent availability of I(to) channels, we found little evidence of an additional use-dependent component of block after exposure to quinidine, suggesting that quinidine reacts with both open and closed I(to) channels as though the binding site is continuously accessible. The model provides a useful tool for assessing drug-channel interactions when the reaction cannot be continuously monitored.

Disease-induced mortality in density-dependent discrete-time S-I-S epidemic models.

PubMed

Franke, John E; Yakubu, Abdul-Aziz

2008-12-01

The dynamics of simple discrete-time epidemic models without disease-induced mortality are typically characterized by global transcritical bifurcation. We prove that in corresponding models with disease-induced mortality a tiny number of infectious individuals can drive an otherwise persistent population to extinction. Our model with disease-induced mortality supports multiple attractors. In addition, we use a Ricker recruitment function in an SIS model and obtained a three component discrete Hopf (Neimark-Sacker) cycle attractor coexisting with a fixed point attractor. The basin boundaries of the coexisting attractors are fractal in nature, and the example exhibits sensitive dependence of the long-term disease dynamics on initial conditions. Furthermore, we show that in contrast to corresponding models without disease-induced mortality, the disease-free state dynamics do not drive the disease dynamics.

When can a single-species, density-dependent model capture the dynamics of a consumer-resource system?

PubMed

Reynolds, Sara A; Brassil, Chad E

2013-12-21

Single-species population models often include density-dependence phenomenologically in order to approximate higher order mechanisms. Here we consider the common scenario in which density-dependence acts via depletion of a renewed resource. When the response of the resource is very quick relative to that of the consumer, the consumer dynamics can be captured by a single-species, density-dependent model. Time scale separation is used to show analytically how the shape of the density-dependent relationship depends on the type of resource and the form of the functional response. Resource types of abiotic, biotic, and biotic with migration are considered, in combination with linear and saturating functional responses. In some cases, we derive familiar forms of single-species models, adding to the justification for their use. In other scenarios novel forms of density-dependence are derived, for example an abiotic resource and a saturating functional response can result in a nonlinear density-dependent relationship in the associated single-species model of the consumer. In this case, the per capita relationship has both concave-up and concave-down sections. © 2013 Published by Elsevier Ltd. All rights reserved.

Tear film dynamics with evaporation, wetting, and time-dependent flux boundary condition on an eye-shaped domain

PubMed Central

Li, Longfei; Braun, R. J.; Maki, K. L.; Henshaw, W. D.; King-Smith, P. E.

2014-01-01

We study tear film dynamics with evaporation on a wettable eye-shaped ocular surface using a lubrication model. The mathematical model has a time-dependent flux boundary condition that models the cycles of tear fluid supply and drainage; it mimics blinks on a stationary eye-shaped domain. We generate computational grids and solve the nonlinear governing equations using the OVERTURE computational framework. In vivo experimental results using fluorescent imaging are used to visualize the influx and redistribution of tears for an open eye. Results from the numerical simulations are compared with the experiment. The model captures the flow around the meniscus and other dynamic features of human tear film observed in vivo. PMID:24926191

Hemispheric Asymmetries of Magnetosphere-Ionosphere-Thermosphere Dynamics

NASA Astrophysics Data System (ADS)

Perlongo, Nicholas James

The geospace environment, comprised of the magnetosphere-ionosphere-thermosphere system, is a highly variable and non-linearly coupled region. The dynamics of the system are driven primarily by electromagnetic and particle radiation emanating from the Sun that occasionally intensify into what are known as solar storms. Understanding the interaction of these storms with the near Earth space environment is essential for predicting and mitigating the risks associated with space weather that can irreparably damage spacecraft, harm astronauts, disrupt radio and GPS communications, and even cause widespread power outages. The geo-effectiveness of solar storms has hemispheric, seasonal, local time, universal time, and latitudinal dependencies. This dissertation investigates those dependencies through a series of four concentrated modeling efforts. The first study focuses on how variations in the solar wind electric field impact the thermosphere at different times of the day. Idealized simulations using the Global Ionosphere Thermosphere Model (GITM) revealed that perturbations in thermospheric temperature and density were greater when the universal time of storm onset was such that the geomagnetic pole was pointed more towards the sun. This universal time effect was greater in the southern hemisphere where the offset of the geomagnetic pole is larger. The second study presents a model validation effort using GITM and the Thermosphere Ionosphere Electrodynamics General Circulation Model (TIE-GCM) compared to GPS Total Electron Content (TEC) observations. The results were divided into seasonal, regional, and local time bins finding that the models performed best near the poles and on the dayside. Diffuse aurora created by electron loss in the inner magnetosphere is an important input to GITM that has primarily been modeled using empirical relationships. In the third study, this was addressed by developing the Hot Election Ion Drift Integrator (HEIDI) ring current model to include a self-consistent description of the aurora and electric field. The model was then coupled to GITM, allowing for a more physical aurora. Using this new configuration in the fourth study, the ill-constrained electron scattering rate was shown to have a large impact on auroral results. This model was applied to simulate a geomagnetic storm during each solstice. The hemispheric asymmetry and seasonal dependence of the storm-time TEC was investigated, finding that northern hemisphere winter storms are most geo-effective when the North American sector is on the dayside. Overall, the research presented in this thesis strives to accomplish two major goals. First, it describes an advancement of a numerical model of the ring current that can be further developed and used to improve our understanding of the interactions between the ionosphere and magnetosphere. Second, the time and spatial dependencies of the geospace response to solar forcing were discovered through a series of modeling efforts. Despite these advancements, there are still numerous open questions, which are also discussed.

A two-column formalism for time-dependent modelling of stellar convection. I. Description of the method

NASA Astrophysics Data System (ADS)

Stökl, A.

2008-11-01

Context: In spite of all the advances in multi-dimensional hydrodynamics, investigations of stellar evolution and stellar pulsations still depend on one-dimensional computations. This paper devises an alternative to the mixing-length theory or turbulence models usually adopted in modelling convective transport in such studies. Aims: The present work attempts to develop a time-dependent description of convection, which reflects the essential physics of convection and that is only moderately dependent on numerical parameters and far less time consuming than existing multi-dimensional hydrodynamics computations. Methods: Assuming that the most extensive convective patterns generate the majority of convective transport, the convective velocity field is described using two parallel, radial columns to represent up- and downstream flows. Horizontal exchange, in the form of fluid flow and radiation, over their connecting interface couples the two columns and allows a simple circulating motion. The main parameters of this convective description have straightforward geometrical meanings, namely the diameter of the columns (corresponding to the size of the convective cells) and the ratio of the cross-section between up- and downdrafts. For this geometrical setup, the time-dependent solution of the equations of radiation hydrodynamics is computed from an implicit scheme that has the advantage of being unaffected by the Courant-Friedrichs-Lewy time-step limit. This implementation is part of the TAPIR-Code (short for The adaptive, implicit RHD-Code). Results: To demonstrate the approach, results for convection zones in Cepheids are presented. The convective energy transport and convective velocities agree with expectations for Cepheids and the scheme reproduces both the kinetic energy flux and convective overshoot. A study of the parameter influence shows that the type of solution derived for these stars is in fact fairly robust with respect to the constitutive numerical parameters.

Collisional Processes Probed by using Resonant Four-Wave Mixing Spectroscopy

NASA Astrophysics Data System (ADS)

McCormack, E. F.; Stampanoni, A.; Hemmerling, B.

2000-06-01

Collisionally-induced decay processes in excited-state nitric oxide (NO) have been measured by using time-resolved two-color, resonant four-wave mixing (TC-RFWM) spectroscopy and polarization spectroscopy (PS). Markedly different time dependencies were observed in the data obtained by using TC-RFWM when compared to PS. Oscillations in the PS signal as a function of delay between the pump and probe laser pulses were observed and it was determined that their characteristics depend very sensitively on laser polarization. Analysis reveals that the oscillations in the decay curves are due to coherent excitation of unresolved hyperfine structure in the A state of NO. A comparison of beat frequencies obtained by taking Fourier transforms of the time data to the predicted hyperfine structure of the A state support this explanation. Further, based on a time-dependent model of PS as a FWM process, the signal’s dependence as a function of time on polarization configuration and excitation scheme can be predicted. By using the beat frequency values, fits of the model results to experimental decay curves for different pressures allows a study of the quenching rate in the A state due to collisional processes. A comparison of the PS data to laser-induced fluorescence decay measurements reveals different decay rates which suggests that the PS signal decay depends on the orientation and alignment of the excited molecules. The different behavior of the decay curves obtained by using TC-RFWM and PS can be understood in terms of the various contributions to the decay as described by the model and this has a direct bearing on which technique is preferable for a given set of experimental parameters.

Angular radiation temperature simulation for time-dependent capsule drive prediction in inertial confinement fusion

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

Jing, Longfei; Yang, Dong; Li, Hang

2015-02-15

The x-ray drive on a capsule in an inertial confinement fusion setup is crucial for ignition. Unfortunately, a direct measurement has not been possible so far. We propose an angular radiation temperature simulation to predict the time-dependent drive on the capsule. A simple model, based on the view-factor method for the simulation of the radiation temperature, is presented and compared with the experimental data obtained using the OMEGA laser facility and the simulation results acquired with VISRAD code. We found a good agreement between the time-dependent measurements and the simulation results obtained using this model. The validated model was thenmore » used to analyze the experimental results from the Shenguang-III prototype laser facility. More specifically, the variations of the peak radiation temperatures at different view angles with the albedo of the hohlraum, the motion of the laser spots, the closure of the laser entrance holes, and the deviation of the laser power were investigated. Furthermore, the time-dependent radiation temperature at different orientations and the drive history on the capsule were calculated. The results indicate that the radiation temperature from “U20W112” (named according to the diagnostic hole ID on the target chamber) can be used to approximately predict the drive temperature on the capsule. In addition, the influence of the capsule on the peak radiation temperature is also presented.« less

Modeling ecological traps for the control of feral pigs

PubMed Central

Dexter, Nick; McLeod, Steven R

2015-01-01

Ecological traps are habitat sinks that are preferred by dispersing animals but have higher mortality or reduced fecundity compared to source habitats. Theory suggests that if mortality rates are sufficiently high, then ecological traps can result in extinction. An ecological trap may be created when pest animals are controlled in one area, but not in another area of equal habitat quality, and when there is density-dependent immigration from the high-density uncontrolled area to the low-density controlled area. We used a logistic population model to explore how varying the proportion of habitat controlled, control mortality rate, and strength of density-dependent immigration for feral pigs could affect the long-term population abundance and time to extinction. Increasing control mortality, the proportion of habitat controlled and the strength of density-dependent immigration decreased abundance both within and outside the area controlled. At higher levels of these parameters, extinction was achieved for feral pigs. We extended the analysis with a more complex stochastic, interactive model of feral pig dynamics in the Australian rangelands to examine how the same variables as the logistic model affected long-term abundance in the controlled and uncontrolled area and time to extinction. Compared to the logistic model of feral pig dynamics, the stochastic interactive model predicted lower abundances and extinction at lower control mortalities and proportions of habitat controlled. To improve the realism of the stochastic interactive model, we substituted fixed mortality rates with a density-dependent control mortality function, empirically derived from helicopter shooting exercises in Australia. Compared to the stochastic interactive model with fixed mortality rates, the model with the density-dependent control mortality function did not predict as substantial decline in abundance in controlled or uncontrolled areas or extinction for any combination of variables. These models demonstrate that pest eradication is theoretically possible without the pest being controlled throughout its range because of density-dependent immigration into the area controlled. The stronger the density-dependent immigration, the better the overall control in controlled and uncontrolled habitat combined. However, the stronger the density-dependent immigration, the poorer the control in the area controlled. For feral pigs, incorporating environmental stochasticity improves the prospects for eradication, but adding a realistic density-dependent control function eliminates these prospects. PMID:26045954

Time-dependent corona models - Scaling laws

NASA Technical Reports Server (NTRS)

Korevaar, P.; Martens, P. C. H.

1989-01-01

Scaling laws are derived for the one-dimensional time-dependent Euler equations that describe the evolution of a spherically symmetric stellar atmosphere. With these scaling laws the results of the time-dependent calculations by Korevaar (1989) obtained for one star are applicable over the whole Hertzsprung-Russell diagram and even to elliptic galaxies. The scaling is exact for stars with the same M/R-ratio and a good approximation for stars with a different M/R-ratio. The global relaxation oscillation found by Korevaar (1989) is scaled to main sequence stars, a solar coronal hole, cool giants and elliptic galaxies.

Subordinated continuous-time AR processes and their application to modeling behavior of mechanical system

NASA Astrophysics Data System (ADS)

Gajda, Janusz; Wyłomańska, Agnieszka; Zimroz, Radosław

2016-12-01

Many real data exhibit behavior adequate to subdiffusion processes. Very often it is manifested by so-called ;trapping events;. The visible evidence of subdiffusion we observe not only in financial time series but also in technical data. In this paper we propose a model which can be used for description of such kind of data. The model is based on the continuous time autoregressive time series with stable noise delayed by the infinitely divisible inverse subordinator. The proposed system can be applied to real datasets with short-time dependence, visible jumps and mentioned periods of stagnation. In this paper we extend the theoretical considerations in analysis of subordinated processes and propose a new model that exhibits mentioned properties. We concentrate on the main characteristics of the examined subordinated process expressed mainly in the language of the measures of dependence which are main tools used in statistical investigation of real data. We present also the simulation procedure of the considered system and indicate how to estimate its parameters. The theoretical results we illustrate by the analysis of real technical data.

Generalized semiparametric varying-coefficient models for longitudinal data

NASA Astrophysics Data System (ADS)

Qi, Li

In this dissertation, we investigate the generalized semiparametric varying-coefficient models for longitudinal data that can flexibly model three types of covariate effects: time-constant effects, time-varying effects, and covariate-varying effects, i.e., the covariate effects that depend on other possibly time-dependent exposure variables. First, we consider the model that assumes the time-varying effects are unspecified functions of time while the covariate-varying effects are parametric functions of an exposure variable specified up to a finite number of unknown parameters. The estimation procedures are developed using multivariate local linear smoothing and generalized weighted least squares estimation techniques. The asymptotic properties of the proposed estimators are established. The simulation studies show that the proposed methods have satisfactory finite sample performance. ACTG 244 clinical trial of HIV infected patients are applied to examine the effects of antiretroviral treatment switching before and after HIV developing the 215-mutation. Our analysis shows benefit of treatment switching before developing the 215-mutation. The proposed methods are also applied to the STEP study with MITT cases showing that they have broad applications in medical research.

Transitioning NWChem to the Next Generation of Manycore Machines

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

Bylaska, Eric J.; Apra, E; Kowalski, Karol

The NorthWest chemistry (NWChem) modeling software is a popular molecular chemistry simulation software that was designed from the start to work on massively parallel processing supercomputers [1-3]. It contains an umbrella of modules that today includes self-consistent eld (SCF), second order Møller-Plesset perturbation theory (MP2), coupled cluster (CC), multiconguration self-consistent eld (MCSCF), selected conguration interaction (CI), tensor contraction engine (TCE) many body methods, density functional theory (DFT), time-dependent density functional theory (TDDFT), real-time time-dependent density functional theory, pseudopotential plane-wave density functional theory (PSPW), band structure (BAND), ab initio molecular dynamics (AIMD), Car-Parrinello molecular dynamics (MD), classical MD, hybrid quantum mechanicsmore » molecular mechanics (QM/MM), hybrid ab initio molecular dynamics molecular mechanics (AIMD/MM), gauge independent atomic orbital nuclear magnetic resonance (GIAO NMR), conductor like screening solvation model (COSMO), conductor-like screening solvation model based on density (COSMO-SMD), and reference interaction site model (RISM) solvation models, free energy simulations, reaction path optimization, parallel in time, among other capabilities [4]. Moreover, new capabilities continue to be added with each new release.« less

Targeted Maximum Likelihood Estimation for Dynamic and Static Longitudinal Marginal Structural Working Models

PubMed Central

Schwab, Joshua; Gruber, Susan; Blaser, Nello; Schomaker, Michael; van der Laan, Mark

2015-01-01

This paper describes a targeted maximum likelihood estimator (TMLE) for the parameters of longitudinal static and dynamic marginal structural models. We consider a longitudinal data structure consisting of baseline covariates, time-dependent intervention nodes, intermediate time-dependent covariates, and a possibly time-dependent outcome. The intervention nodes at each time point can include a binary treatment as well as a right-censoring indicator. Given a class of dynamic or static interventions, a marginal structural model is used to model the mean of the intervention-specific counterfactual outcome as a function of the intervention, time point, and possibly a subset of baseline covariates. Because the true shape of this function is rarely known, the marginal structural model is used as a working model. The causal quantity of interest is defined as the projection of the true function onto this working model. Iterated conditional expectation double robust estimators for marginal structural model parameters were previously proposed by Robins (2000, 2002) and Bang and Robins (2005). Here we build on this work and present a pooled TMLE for the parameters of marginal structural working models. We compare this pooled estimator to a stratified TMLE (Schnitzer et al. 2014) that is based on estimating the intervention-specific mean separately for each intervention of interest. The performance of the pooled TMLE is compared to the performance of the stratified TMLE and the performance of inverse probability weighted (IPW) estimators using simulations. Concepts are illustrated using an example in which the aim is to estimate the causal effect of delayed switch following immunological failure of first line antiretroviral therapy among HIV-infected patients. Data from the International Epidemiological Databases to Evaluate AIDS, Southern Africa are analyzed to investigate this question using both TML and IPW estimators. Our results demonstrate practical advantages of the pooled TMLE over an IPW estimator for working marginal structural models for survival, as well as cases in which the pooled TMLE is superior to its stratified counterpart. PMID:25909047

Time Dependent Dielectric Breakdown in Copper Low-k Interconnects: Mechanisms and Reliability Models

PubMed Central

Wong, Terence K.S.

2012-01-01

The time dependent dielectric breakdown phenomenon in copper low-k damascene interconnects for ultra large-scale integration is reviewed. The loss of insulation between neighboring interconnects represents an emerging back end-of-the-line reliability issue that is not fully understood. After describing the main dielectric leakage mechanisms in low-k materials (Poole-Frenkel and Schottky emission), the major dielectric reliability models that had appeared in the literature are discussed, namely: the Lloyd model, 1/E model, thermochemical E model, E1/2 models, E2 model and the Haase model. These models can be broadly categorized into those that consider only intrinsic breakdown (Lloyd, 1/E, E and Haase) and those that take into account copper migration in low-k materials (E1/2, E2). For each model, the physical assumptions and the proposed breakdown mechanism will be discussed, together with the quantitative relationship predicting the time to breakdown and supporting experimental data. Experimental attempts on validation of dielectric reliability models using data obtained from low field stressing are briefly discussed. The phenomenon of soft breakdown, which often precedes hard breakdown in porous ultra low-k materials, is highlighted for future research.

Three-dimensional particle-particle simulations: Dependence of relaxation time on plasma parameter

NASA Astrophysics Data System (ADS)

Zhao, Yinjian

2018-05-01

A particle-particle simulation model is applied to investigate the dependence of the relaxation time on the plasma parameter in a three-dimensional unmagnetized plasma. It is found that the relaxation time increases linearly as the plasma parameter increases within the range of the plasma parameter from 2 to 10; when the plasma parameter equals 2, the relaxation time is independent of the total number of particles, but when the plasma parameter equals 10, the relaxation time slightly increases as the total number of particles increases, which indicates the transition of a plasma from collisional to collisionless. In addition, ions with initial Maxwell-Boltzmann (MB) distribution are found to stay in the MB distribution during the whole simulation time, and the mass of ions does not significantly affect the relaxation time of electrons. This work also shows the feasibility of the particle-particle model when using GPU parallel computing techniques.

Generation of real-time mode high-resolution water vapor fields from GPS observations

NASA Astrophysics Data System (ADS)

Yu, Chen; Penna, Nigel T.; Li, Zhenhong

2017-02-01

Pointwise GPS measurements of tropospheric zenith total delay can be interpolated to provide high-resolution water vapor maps which may be used for correcting synthetic aperture radar images, for numeral weather prediction, and for correcting Network Real-time Kinematic GPS observations. Several previous studies have addressed the importance of the elevation dependency of water vapor, but it is often a challenge to separate elevation-dependent tropospheric delays from turbulent components. In this paper, we present an iterative tropospheric decomposition interpolation model that decouples the elevation and turbulent tropospheric delay components. For a 150 km × 150 km California study region, we estimate real-time mode zenith total delays at 41 GPS stations over 1 year by using the precise point positioning technique and demonstrate that the decoupled interpolation model generates improved high-resolution tropospheric delay maps compared with previous tropospheric turbulence- and elevation-dependent models. Cross validation of the GPS zenith total delays yields an RMS error of 4.6 mm with the decoupled interpolation model, compared with 8.4 mm with the previous model. On converting the GPS zenith wet delays to precipitable water vapor and interpolating to 1 km grid cells across the region, validations with the Moderate Resolution Imaging Spectroradiometer near-IR water vapor product show 1.7 mm RMS differences by using the decoupled model, compared with 2.0 mm for the previous interpolation model. Such results are obtained without differencing the tropospheric delays or water vapor estimates in time or space, while the errors are similar over flat and mountainous terrains, as well as for both inland and coastal areas.

Reconciling Time, Space and Function: A New Dorsal-Ventral Stream Model of Sentence Comprehension

ERIC Educational Resources Information Center

Bornkessel-Schlesewsky, Ina; Schlesewsky, Matthias

2013-01-01

We present a new dorsal-ventral stream framework for language comprehension which unifies basic neurobiological assumptions (Rauschecker & Scott, 2009) with a cross-linguistic neurocognitive sentence comprehension model (eADM; Bornkessel & Schlesewsky, 2006). The dissociation between (time-dependent) syntactic structure-building and…

Rotational dynamics in supercooled water from nuclear spin relaxation and molecular simulations.

PubMed

Qvist, Johan; Mattea, Carlos; Sunde, Erik P; Halle, Bertil

2012-05-28

Structural dynamics in liquid water slow down dramatically in the supercooled regime. To shed further light on the origin of this super-Arrhenius temperature dependence, we report high-precision (17)O and (2)H NMR relaxation data for H(2)O and D(2)O, respectively, down to 37 K below the equilibrium freezing point. With the aid of molecular dynamics (MD) simulations, we provide a detailed analysis of the rotational motions probed by the NMR experiments. The NMR-derived rotational correlation time τ(R) is the integral of a time correlation function (TCF) that, after a subpicosecond librational decay, can be described as a sum of two exponentials. Using a coarse-graining algorithm to map the MD trajectory on a continuous-time random walk (CTRW) in angular space, we show that the slowest TCF component can be attributed to large-angle molecular jumps. The mean jump angle is ∼48° at all temperatures and the waiting time distribution is non-exponential, implying dynamical heterogeneity. We have previously used an analogous CTRW model to analyze quasielastic neutron scattering data from supercooled water. Although the translational and rotational waiting times are of similar magnitude, most translational jumps are not synchronized with a rotational jump of the same molecule. The rotational waiting time has a stronger temperature dependence than the translation one, consistent with the strong increase of the experimentally derived product τ(R) D(T) at low temperatures. The present CTRW jump model is related to, but differs in essential ways from the extended jump model proposed by Laage and co-workers. Our analysis traces the super-Arrhenius temperature dependence of τ(R) to the rotational waiting time. We present arguments against interpreting this temperature dependence in terms of mode-coupling theory or in terms of mixture models of water structure.

From Geometry Optimization to Time Dependent Molecular Structure Modeling: Method Developments, ab initio Theories and Applications

NASA Astrophysics Data System (ADS)

Liang, Wenkel

This dissertation consists of two general parts: (I) developments of optimization algorithms (both nuclear and electronic degrees of freedom) for time-independent molecules and (II) novel methods, first-principle theories and applications in time dependent molecular structure modeling. In the first part, we discuss in specific two new algorithms for static geometry optimization, the eigenspace update (ESU) method in nonredundant internal coordinate that exhibits an enhanced performace with up to a factor of 3 savings in computational cost for large-sized molecular systems; the Car-Parrinello density matrix search (CP-DMS) method that enables direct minimization of the SCF energy as an effective alternative to conventional diagonalization approach. For the second part, we consider the time dependence and first presents two nonadiabatic dynamic studies that model laser controlled molecular photo-dissociation for qualitative understandings of intense laser-molecule interaction, using ab initio direct Ehrenfest dynamics scheme implemented with real-time time-dependent density functional theory (RT-TDDFT) approach developed in our group. Furthermore, we place our special interest on the nonadiabatic electronic dynamics in the ultrafast time scale, and presents (1) a novel technique that can not only obtain energies but also the electron densities of doubly excited states within a single determinant framework, by combining methods of CP-DMS with RT-TDDFT; (2) a solvated first-principles electronic dynamics method by incorporating the polarizable continuum solvation model (PCM) to RT-TDDFT, which is found to be very effective in describing the dynamical solvation effect in the charge transfer process and yields a consistent absorption spectrum in comparison to the conventional linear response results in solution. (3) applications of the PCM-RT-TDDFT method to study the intramolecular charge-transfer (CT) dynamics in a C60 derivative. Such work provides insights into the characteristics of ultrafast dynamics in photoexcited fullerene derivatives, and aids in the rational design for pre-dissociative exciton in the intramolecular CT process in organic solar cells.

Modeling of Internet Influence on Group Emotion

NASA Astrophysics Data System (ADS)

Czaplicka, Agnieszka; Hołyst, Janusz A.

Long-range interactions are introduced to a two-dimensional model of agents with time-dependent internal variables ei = 0, ±1 corresponding to valencies of agent emotions. Effects of spontaneous emotion emergence and emotional relaxation processes are taken into account. The valence of agent i depends on valencies of its four nearest neighbors but it is also influenced by long-range interactions corresponding to social relations developed for example by Internet contacts to a randomly chosen community. Two types of such interactions are considered. In the first model the community emotional influence depends only on the sign of its temporary emotion. When the coupling parameter approaches a critical value a phase transition takes place and as result for larger coupling constants the mean group emotion of all agents is nonzero over long time periods. In the second model the community influence is proportional to magnitude of community average emotion. The ordered emotional phase was here observed for a narrow set of system parameters.

A Joint Model for Vitamin K-Dependent Clotting Factors and Anticoagulation Proteins.

PubMed

Ooi, Qing Xi; Wright, Daniel F B; Tait, R Campbell; Isbister, Geoffrey K; Duffull, Stephen B

2017-12-01

Warfarin acts by inhibiting the reduction of vitamin K (VK) to its active form, thereby decreasing the production of VK-dependent coagulation proteins. The aim of this research is to develop a joint model for the VK-dependent clotting factors II, VII, IX and X, and the anticoagulation proteins, proteins C and S, during warfarin initiation. Data from 18 patients with atrial fibrillation who had warfarin therapy initiated were available for analysis. Nine blood samples were collected from each subject at baseline, and at 1-5, 8, 15 and 29 days after warfarin initiation and assayed for factors II, VII, IX and X, and proteins C and S. Warfarin concentration-time data were not available. The coagulation proteins data were modelled in a stepwise manner using NONMEM ® Version 7.2. In the first stage, each of the coagulation proteins was modelled independently using a kinetic-pharmacodynamic model. In the subsequent step, the six kinetic-pharmacodynamic models were combined into a single joint model. One patient was administered VK and was excluded from the analysis. Each kinetic-pharmacodynamic model consisted of two parts: (1) a common one-compartment pharmacokinetic model with first-order absorption and elimination for warfarin; and (2) an inhibitory E max model linked to a turnover model for coagulation proteins. In the joint model, an unexpected pharmacodynamic lag was identified and the estimated degradation half-life of VK-dependent coagulation proteins were in agreement with previously published values. The model provided an adequate fit to the observed data. The joint model represents the first work to quantify the influence of warfarin on all six VK-dependent coagulation proteins simultaneously. Future work will expand the model to predict the influence of exogenously administered VK on the time course of clotting factor concentrations after warfarin overdose and during perioperative warfarin reversal procedures.

Out-of-equilibrium relaxation of the thermal Casimir effect in a model polarizable material

NASA Astrophysics Data System (ADS)

Dean, David S.; Démery, Vincent; Parsegian, V. Adrian; Podgornik, Rudolf

2012-03-01

Relaxation of the thermal Casimir or van der Waals force (the high temperature limit of the Casimir force) for a model dielectric medium is investigated. We start with a model of interacting polarization fields with a dynamics that leads to a frequency dependent dielectric constant of the Debye form. In the static limit, the usual zero frequency Matsubara mode component of the Casimir force is recovered. We then consider the out-of-equilibrium relaxation of the van der Waals force to its equilibrium value when two initially uncorrelated dielectric bodies are brought into sudden proximity. For the interaction between dielectric slabs, it is found that the spatial dependence of the out-of-equilibrium force is the same as the equilibrium one, but it has a time dependent amplitude, or Hamaker coefficient, which increases in time to its equilibrium value. The final relaxation of the force to its equilibrium value is exponential in systems with a single or finite number of polarization field relaxation times. However, in systems, such as those described by the Havriliak-Negami dielectric constant with a broad distribution of relaxation times, we observe a much slower power law decay to the equilibrium value.

One-dimensional time-dependent fluid model of a very high density low-pressure inductively coupled plasma

NASA Astrophysics Data System (ADS)

Chaplin, Vernon H.; Bellan, Paul M.

2015-12-01

A time-dependent two-fluid model has been developed to understand axial variations in the plasma parameters in a very high density (peak ne≳ 5 ×1019 m-3 ) argon inductively coupled discharge in a long 1.1 cm radius tube. The model equations are written in 1D with radial losses to the tube walls accounted for by the inclusion of effective particle and energy sink terms. The ambipolar diffusion equation and electron energy equation are solved to find the electron density ne(z ,t ) and temperature Te(z ,t ) , and the populations of the neutral argon 4s metastable, 4s resonant, and 4p excited state manifolds are calculated to determine the stepwise ionization rate and calculate radiative energy losses. The model has been validated through comparisons with Langmuir probe ion saturation current measurements; close agreement between the simulated and measured axial plasma density profiles and the initial density rise rate at each location was obtained at pA r=30 -60 mTorr . We present detailed results from calculations at 60 mTorr, including the time-dependent electron temperature, excited state populations, and energy budget within and downstream of the radiofrequency antenna.

A Time-dependant atmospheric model of HD209458b

NASA Astrophysics Data System (ADS)

Iro, N.; Bézard, B.; Guillot, T.

2004-11-01

Charbonneau et al. (2002) conducted HST spectroscopic observations of HD209458 centered on the sodium doublet at 589.3 nm. An absorption feature was found, interpreted as an absorption from the sodium in the planet's atmosphere. However, this feature is weaker than predicted by static radiative equilibrium atmospheric models of HD209458b. We present a time-dependent radiative model of the atmosphere of HD209458b and investigate its thermal structure and chemical composition. Time-dependent temperature profiles are calculated, assuming a constant-with-height zonal wind, modelled as a solid body rotation. We predict day-night variations of the effective temperature of ˜600 K, for an equatorial rotation rate of 1 km s-1, in good agreement with the predictions by Showman & Guillot, 2002. At high altitudes (mbar pressures or less), the night temperatures are low enough to allow sodium to condense into Na2S. Synthetic transit spectra of the visible Na doublet show a much weaker sodium absorption on the morning limb than on the evening limb. The calculated dimming of the sodium feature during a planetary transit agrees with the value reported by Charbonneau et al. (2002).

Transport and Reactive Flow Modelling Using A Particle Tracking Method Based on Continuous Time Random Walks

NASA Astrophysics Data System (ADS)

Oliveira, R.; Bijeljic, B.; Blunt, M. J.; Colbourne, A.; Sederman, A. J.; Mantle, M. D.; Gladden, L. F.

2017-12-01

Mixing and reactive processes have a large impact on the viability of enhanced oil and gas recovery projects that involve acid stimulation and CO2 injection. To achieve a successful design of the injection schemes an accurate understanding of the interplay between pore structure, flow and reactive transport is necessary. Dependent on transport and reactive conditions, this complex coupling can also be dependent on initial rock heterogeneity across a variety of scales. To address these issues, we devise a new method to study transport and reactive flow in porous media at multiple scales. The transport model is based on an efficient Particle Tracking Method based on Continuous Time Random Walks (CTRW-PTM) on a lattice. Transport is modelled using an algorithm described in Rhodes and Blunt (2006) and Srinivasan et al. (2010); this model is expanded to enable for reactive flow predictions in subsurface rock undergoing a first-order fluid/solid chemical reaction. The reaction-induced alteration in fluid/solid interface is accommodated in the model through changes in porosity and flow field, leading to time dependent transport characteristics in the form of transit time distributions which account for rock heterogeneity change. This also enables the study of concentration profiles at the scale of interest. Firstly, we validate transport model by comparing the probability of molecular displacement (propagators) measured by Nuclear Magnetic Resonance (NMR) with our modelled predictions for concentration profiles. The experimental propagators for three different porous media of increasing complexity, a beadpack, a Bentheimer sandstone and a Portland carbonate, show a good agreement with the model. Next, we capture the time evolution of the propagators distribution in a reactive flow experiment, where hydrochloric acid is injected into a limestone rock. We analyse the time-evolving non-Fickian signatures for the transport during reactive flow and observe an increase in transport heterogeneity at latter times, representing the increase in rock heterogeneity. Evolution of transit time distribution is associated with the evolution of concentration profiles, thus highlighting the impact of initial rock structure on the reactive transport for a range of Pe and Da numbers.

Further results on open-loop compensation of rate-dependent hysteresis in a magnetostrictive actuator with the Prandtl-Ishlinskii model

NASA Astrophysics Data System (ADS)

Al Janaideh, Mohammad; Aljanaideh, Omar

2018-05-01

Apart from the output-input hysteresis loops, the magnetostrictive actuators also exhibit asymmetry and saturation, particularly under moderate to large magnitude inputs and at relatively higher frequencies. Such nonlinear input-output characteristics could be effectively characterized by a rate-dependent Prandtl-Ishlinskii model in conjunction with a function of deadband operators. In this study, an inverse model is formulated to seek real-time compensation of rate-dependent and asymmetric hysteresis nonlinearities of a Terfenol-D magnetostrictive actuator. The inverse model is formulated with the inverse of the rate-dependent Prandtl-Ishlinskii model, satisfying the threshold dilation condition, with the inverse of the deadband function. The inverse model was subsequently applied to the hysteresis model as a feedforward compensator. The proposed compensator is applied as a feedforward compensator to the actuator hardware to study its potential for rate-dependent and asymmetric hysteresis loops. The experimental results are obtained under harmonic and complex harmonic inputs further revealed that the inverse compensator can substantially suppress the hysteresis and output asymmetry nonlinearities in the entire frequency range considered in the study.

Measurement and simulation of unmyelinated nerve electrostimulation: Lumbricus terrestris experiment and numerical model

NASA Astrophysics Data System (ADS)

Šarolić, A.; Živković, Z.; Reilly, J. P.

2016-06-01

The electrostimulation excitation threshold of a nerve depends on temporal and frequency parameters of the stimulus. These dependences were investigated in terms of: (1) strength-duration (SD) curve for a single monophasic rectangular pulse, and (2) frequency dependence of the excitation threshold for a continuous sinusoidal current. Experiments were performed on the single-axon measurement setup based on Lumbricus terrestris having unmyelinated nerve fibers. The simulations were performed using the well-established SENN model for a myelinated nerve. Although the unmyelinated experimental model differs from the myelinated simulation model, both refer to a single axon. Thus we hypothesized that the dependence on temporal and frequency parameters should be very similar. The comparison was made possible by normalizing each set of results to the SD time constant and the rheobase current of each model, yielding the curves that show the temporal and frequency dependencies regardless of the model differences. The results reasonably agree, suggesting that this experimental setup and method of comparison with SENN model can be used for further studies of waveform effect on nerve excitability, including unmyelinated neurons.

Measurement and simulation of unmyelinated nerve electrostimulation: Lumbricus terrestris experiment and numerical model.

PubMed

Šarolić, A; Živković, Z; Reilly, J P

2016-06-21

The electrostimulation excitation threshold of a nerve depends on temporal and frequency parameters of the stimulus. These dependences were investigated in terms of: (1) strength-duration (SD) curve for a single monophasic rectangular pulse, and (2) frequency dependence of the excitation threshold for a continuous sinusoidal current. Experiments were performed on the single-axon measurement setup based on Lumbricus terrestris having unmyelinated nerve fibers. The simulations were performed using the well-established SENN model for a myelinated nerve. Although the unmyelinated experimental model differs from the myelinated simulation model, both refer to a single axon. Thus we hypothesized that the dependence on temporal and frequency parameters should be very similar. The comparison was made possible by normalizing each set of results to the SD time constant and the rheobase current of each model, yielding the curves that show the temporal and frequency dependencies regardless of the model differences. The results reasonably agree, suggesting that this experimental setup and method of comparison with SENN model can be used for further studies of waveform effect on nerve excitability, including unmyelinated neurons.

Models and analysis for multivariate failure time data

NASA Astrophysics Data System (ADS)

Shih, Joanna Huang

The goal of this research is to develop and investigate models and analytic methods for multivariate failure time data. We compare models in terms of direct modeling of the margins, flexibility of dependency structure, local vs. global measures of association, and ease of implementation. In particular, we study copula models, and models produced by right neutral cumulative hazard functions and right neutral hazard functions. We examine the changes of association over time for families of bivariate distributions induced from these models by displaying their density contour plots, conditional density plots, correlation curves of Doksum et al, and local cross ratios of Oakes. We know that bivariate distributions with same margins might exhibit quite different dependency structures. In addition to modeling, we study estimation procedures. For copula models, we investigate three estimation procedures. the first procedure is full maximum likelihood. The second procedure is two-stage maximum likelihood. At stage 1, we estimate the parameters in the margins by maximizing the marginal likelihood. At stage 2, we estimate the dependency structure by fixing the margins at the estimated ones. The third procedure is two-stage partially parametric maximum likelihood. It is similar to the second procedure, but we estimate the margins by the Kaplan-Meier estimate. We derive asymptotic properties for these three estimation procedures and compare their efficiency by Monte-Carlo simulations and direct computations. For models produced by right neutral cumulative hazards and right neutral hazards, we derive the likelihood and investigate the properties of the maximum likelihood estimates. Finally, we develop goodness of fit tests for the dependency structure in the copula models. We derive a test statistic and its asymptotic properties based on the test of homogeneity of Zelterman and Chen (1988), and a graphical diagnostic procedure based on the empirical Bayes approach. We study the performance of these two methods using actual and computer generated data.

Dynamic sensitivity analysis of biological systems

PubMed Central

Wu, Wu Hsiung; Wang, Feng Sheng; Chang, Maw Shang

2008-01-01

Background A mathematical model to understand, predict, control, or even design a real biological system is a central theme in systems biology. A dynamic biological system is always modeled as a nonlinear ordinary differential equation (ODE) system. How to simulate the dynamic behavior and dynamic parameter sensitivities of systems described by ODEs efficiently and accurately is a critical job. In many practical applications, e.g., the fed-batch fermentation systems, the system admissible input (corresponding to independent variables of the system) can be time-dependent. The main difficulty for investigating the dynamic log gains of these systems is the infinite dimension due to the time-dependent input. The classical dynamic sensitivity analysis does not take into account this case for the dynamic log gains. Results We present an algorithm with an adaptive step size control that can be used for computing the solution and dynamic sensitivities of an autonomous ODE system simultaneously. Although our algorithm is one of the decouple direct methods in computing dynamic sensitivities of an ODE system, the step size determined by model equations can be used on the computations of the time profile and dynamic sensitivities with moderate accuracy even when sensitivity equations are more stiff than model equations. To show this algorithm can perform the dynamic sensitivity analysis on very stiff ODE systems with moderate accuracy, it is implemented and applied to two sets of chemical reactions: pyrolysis of ethane and oxidation of formaldehyde. The accuracy of this algorithm is demonstrated by comparing the dynamic parameter sensitivities obtained from this new algorithm and from the direct method with Rosenbrock stiff integrator based on the indirect method. The same dynamic sensitivity analysis was performed on an ethanol fed-batch fermentation system with a time-varying feed rate to evaluate the applicability of the algorithm to realistic models with time-dependent admissible input. Conclusion By combining the accuracy we show with the efficiency of being a decouple direct method, our algorithm is an excellent method for computing dynamic parameter sensitivities in stiff problems. We extend the scope of classical dynamic sensitivity analysis to the investigation of dynamic log gains of models with time-dependent admissible input. PMID:19091016

Comparison of Statistical Approaches for Dealing With Immortal Time Bias in Drug Effectiveness Studies

PubMed Central

Karim, Mohammad Ehsanul; Gustafson, Paul; Petkau, John; Tremlett, Helen

2016-01-01

In time-to-event analyses of observational studies of drug effectiveness, incorrect handling of the period between cohort entry and first treatment exposure during follow-up may result in immortal time bias. This bias can be eliminated by acknowledging a change in treatment exposure status with time-dependent analyses, such as fitting a time-dependent Cox model. The prescription time-distribution matching (PTDM) method has been proposed as a simpler approach for controlling immortal time bias. Using simulation studies and theoretical quantification of bias, we compared the performance of the PTDM approach with that of the time-dependent Cox model in the presence of immortal time. Both assessments revealed that the PTDM approach did not adequately address immortal time bias. Based on our simulation results, another recently proposed observational data analysis technique, the sequential Cox approach, was found to be more useful than the PTDM approach (Cox: bias = −0.002, mean squared error = 0.025; PTDM: bias = −1.411, mean squared error = 2.011). We applied these approaches to investigate the association of β-interferon treatment with delaying disability progression in a multiple sclerosis cohort in British Columbia, Canada (Long-Term Benefits and Adverse Effects of Beta-Interferon for Multiple Sclerosis (BeAMS) Study, 1995–2008). PMID:27455963

Co Modeling and Co Synthesis of Safety Critical Multi threaded Embedded Software for Multi Core Embedded Platforms

DTIC Science & Technology

2017-03-20

computation, Prime Implicates, Boolean Abstraction, real- time embedded software, software synthesis, correct by construction software design , model...types for time -dependent data-flow networks". J.-P. Talpin, P. Jouvelot, S. Shukla. ACM-IEEE Conference on Methods and Models for System Design ...information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing   data sources, gathering and

Nonadiabatic Dynamics in Single-Electron Tunneling Devices with Time-Dependent Density-Functional Theory

NASA Astrophysics Data System (ADS)

Dittmann, Niklas; Splettstoesser, Janine; Helbig, Nicole

2018-04-01

We simulate the dynamics of a single-electron source, modeled as a quantum dot with on-site Coulomb interaction and tunnel coupling to an adjacent lead in time-dependent density-functional theory. Based on this system, we develop a time-nonlocal exchange-correlation potential by exploiting analogies with quantum-transport theory. The time nonlocality manifests itself in a dynamical potential step. We explicitly link the time evolution of the dynamical step to physical relaxation timescales of the electron dynamics. Finally, we discuss prospects for simulations of larger mesoscopic systems.

Nonadiabatic Dynamics in Single-Electron Tunneling Devices with Time-Dependent Density-Functional Theory.

PubMed

Dittmann, Niklas; Splettstoesser, Janine; Helbig, Nicole

2018-04-13

We simulate the dynamics of a single-electron source, modeled as a quantum dot with on-site Coulomb interaction and tunnel coupling to an adjacent lead in time-dependent density-functional theory. Based on this system, we develop a time-nonlocal exchange-correlation potential by exploiting analogies with quantum-transport theory. The time nonlocality manifests itself in a dynamical potential step. We explicitly link the time evolution of the dynamical step to physical relaxation timescales of the electron dynamics. Finally, we discuss prospects for simulations of larger mesoscopic systems.

Atomic Dynamics in Simple Liquid: de Gennes Narrowing Revisited

DOE PAGES

Wu, Bin; Iwashita, Takuya; Egami, Takeshi

2018-03-27

The de Gennes narrowing phenomenon is frequently observed by neutron or x-ray scattering measurements of the dynamics of complex systems, such as liquids, proteins, colloids, and polymers. The characteristic slowing down of dynamics in the vicinity of the maximum of the total scattering intensity is commonly attributed to enhanced cooperativity. In this Letter, we present an alternative view on its origin through the examination of the time-dependent pair correlation function, the van Hove correlation function, for a model liquid in two, three, and four dimensions. We find that the relaxation time increases monotonically with distance and the dependence on distancemore » varies with dimension. We propose a heuristic explanation of this dependence based on a simple geometrical model. Furthermore, this finding sheds new light on the interpretation of the de Gennes narrowing phenomenon and the α-relaxation time.« less

Atomic Dynamics in Simple Liquid: de Gennes Narrowing Revisited

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

Wu, Bin; Iwashita, Takuya; Egami, Takeshi

The de Gennes narrowing phenomenon is frequently observed by neutron or x-ray scattering measurements of the dynamics of complex systems, such as liquids, proteins, colloids, and polymers. The characteristic slowing down of dynamics in the vicinity of the maximum of the total scattering intensity is commonly attributed to enhanced cooperativity. In this Letter, we present an alternative view on its origin through the examination of the time-dependent pair correlation function, the van Hove correlation function, for a model liquid in two, three, and four dimensions. We find that the relaxation time increases monotonically with distance and the dependence on distancemore » varies with dimension. We propose a heuristic explanation of this dependence based on a simple geometrical model. Furthermore, this finding sheds new light on the interpretation of the de Gennes narrowing phenomenon and the α-relaxation time.« less

Automatic detection of key innovations, rate shifts, and diversity-dependence on phylogenetic trees.

PubMed

Rabosky, Daniel L

2014-01-01

A number of methods have been developed to infer differential rates of species diversification through time and among clades using time-calibrated phylogenetic trees. However, we lack a general framework that can delineate and quantify heterogeneous mixtures of dynamic processes within single phylogenies. I developed a method that can identify arbitrary numbers of time-varying diversification processes on phylogenies without specifying their locations in advance. The method uses reversible-jump Markov Chain Monte Carlo to move between model subspaces that vary in the number of distinct diversification regimes. The model assumes that changes in evolutionary regimes occur across the branches of phylogenetic trees under a compound Poisson process and explicitly accounts for rate variation through time and among lineages. Using simulated datasets, I demonstrate that the method can be used to quantify complex mixtures of time-dependent, diversity-dependent, and constant-rate diversification processes. I compared the performance of the method to the MEDUSA model of rate variation among lineages. As an empirical example, I analyzed the history of speciation and extinction during the radiation of modern whales. The method described here will greatly facilitate the exploration of macroevolutionary dynamics across large phylogenetic trees, which may have been shaped by heterogeneous mixtures of distinct evolutionary processes.

Automatic Detection of Key Innovations, Rate Shifts, and Diversity-Dependence on Phylogenetic Trees

PubMed Central

Rabosky, Daniel L.

2014-01-01

A number of methods have been developed to infer differential rates of species diversification through time and among clades using time-calibrated phylogenetic trees. However, we lack a general framework that can delineate and quantify heterogeneous mixtures of dynamic processes within single phylogenies. I developed a method that can identify arbitrary numbers of time-varying diversification processes on phylogenies without specifying their locations in advance. The method uses reversible-jump Markov Chain Monte Carlo to move between model subspaces that vary in the number of distinct diversification regimes. The model assumes that changes in evolutionary regimes occur across the branches of phylogenetic trees under a compound Poisson process and explicitly accounts for rate variation through time and among lineages. Using simulated datasets, I demonstrate that the method can be used to quantify complex mixtures of time-dependent, diversity-dependent, and constant-rate diversification processes. I compared the performance of the method to the MEDUSA model of rate variation among lineages. As an empirical example, I analyzed the history of speciation and extinction during the radiation of modern whales. The method described here will greatly facilitate the exploration of macroevolutionary dynamics across large phylogenetic trees, which may have been shaped by heterogeneous mixtures of distinct evolutionary processes. PMID:24586858

Biomechanics of fundamental frequency regulation: Constitutive modeling of the vocal fold lamina propria.

PubMed

Chan, Roger W; Siegmund, Thomas; Zhang, Kai

2009-12-01

Accurate characterization of biomechanical characteristics of the vocal fold is critical for understanding the regulation of vocal fundamental frequency (F(0)), which depends on the active control of the intrinsic laryngeal muscles as well as the passive biomechanical response of the vocal fold lamina propria. Specifically, the tissue stress-strain response and viscoelastic properties under cyclic tensile deformation are relevant, when the vocal folds are subjected to length and tension changes due to posturing. This paper describes a constitutive modeling approach quantifying the relationship between vocal fold stress and strain (or stretch), and establishes predictions of F(0) with the string model of phonation based on the constitutive parameters. Results indicated that transient and time-dependent changes in F(0), including global declinations in declarative sentences, as well as local F(0) overshoots and undershoots, can be partially attributed to the time-dependent viscoplastic response of the vocal fold cover.

A Rigorous Temperature-Dependent Stochastic Modelling and Testing for MEMS-Based Inertial Sensor Errors.

PubMed

El-Diasty, Mohammed; Pagiatakis, Spiros

2009-01-01

In this paper, we examine the effect of changing the temperature points on MEMS-based inertial sensor random error. We collect static data under different temperature points using a MEMS-based inertial sensor mounted inside a thermal chamber. Rigorous stochastic models, namely Autoregressive-based Gauss-Markov (AR-based GM) models are developed to describe the random error behaviour. The proposed AR-based GM model is initially applied to short stationary inertial data to develop the stochastic model parameters (correlation times). It is shown that the stochastic model parameters of a MEMS-based inertial unit, namely the ADIS16364, are temperature dependent. In addition, field kinematic test data collected at about 17 °C are used to test the performance of the stochastic models at different temperature points in the filtering stage using Unscented Kalman Filter (UKF). It is shown that the stochastic model developed at 20 °C provides a more accurate inertial navigation solution than the ones obtained from the stochastic models developed at -40 °C, -20 °C, 0 °C, +40 °C, and +60 °C. The temperature dependence of the stochastic model is significant and should be considered at all times to obtain optimal navigation solution for MEMS-based INS/GPS integration.

A Study of Time-dependent and Anisotropic Effects on the Deformation Response of Two Flywheel Designs

NASA Technical Reports Server (NTRS)

Saleeb, Atef F.; Arnold, Steven M.; Al-Zoubi, Nasser R.

2003-01-01

The influence of material time dependency and anisotropy in the context of two specific flywheel designs-preload and multi-directional composite (MDC)--is investigated. In particular, we focus on the following aspects: 1) geometric constraints, 2) material constraints, 3) loading type, and 4) the fundamental character of the time-dependent response, i.e., reversible or irreversible. The bulk of the results presented were obtained using a composite (PMC IM7/8552 at 135 C) material system. The material was characterized using a general multimechanism hereditary (viscoelastoplastic) model. As a general conclusion, the results have clearly shown that both the preload and the MDC rotor designs are significantly affected by time-dependent material behavior, which may impact the state of rotor balance and potentially reduce its operating life. In view of the results of the parametric studies and predictions made in the present study, the need for actual experimentation focusing on the time-dependent behavior of full-scale flywheel rotors is self-evident.

The effect of area size and predation on the time to extinction of prairie vole populations. simulation studies via SERDYCA: a Spatially-Explicit Individual-Based Model of Rodent Dynamics

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

Kostova, T; Carlsen, T

2003-11-21

We present a spatially-explicit individual-based computational model of rodent dynamics, customized for the prairie vole species, M. Ochrogaster. The model is based on trophic relationships and represents important features such as territorial competition, mating behavior, density-dependent predation and dispersal out of the modeled spatial region. Vegetation growth and vole fecundity are dependent on climatic components. The results of simulations show that the model correctly predicts the overall temporal dynamics of the population density. Time-series analysis shows a very good match between the periods corresponding to the peak population density frequencies predicted by the model and the ones reported in themore » literature. The model is used to study the relation between persistence, landscape area and predation. We introduce the notions of average time to extinction (ATE) and persistence frequency to quantify persistence. While the ATE decreases with decrease of area, it is a bell-shaped function of the predation level: increasing for 'small' and decreasing for 'large' predation levels.« less

A neural computational model for animal's time-to-collision estimation.

PubMed

Wang, Ling; Yao, Dezhong

2013-04-17

The time-to-collision (TTC) is the time elapsed before a looming object hits the subject. An accurate estimation of TTC plays a critical role in the survival of animals in nature and acts as an important factor in artificial intelligence systems that depend on judging and avoiding potential dangers. The theoretic formula for TTC is 1/τ≈θ'/sin θ, where θ and θ' are the visual angle and its variation, respectively, and the widely used approximation computational model is θ'/θ. However, both of these measures are too complex to be implemented by a biological neuronal model. We propose a new simple computational model: 1/τ≈Mθ-P/(θ+Q)+N, where M, P, Q, and N are constants that depend on a predefined visual angle. This model, weighted summation of visual angle model (WSVAM), can achieve perfect implementation through a widely accepted biological neuronal model. WSVAM has additional merits, including a natural minimum consumption and simplicity. Thus, it yields a precise and neuronal-implemented estimation for TTC, which provides a simple and convenient implementation for artificial vision, and represents a potential visual brain mechanism.

Robust analysis of semiparametric renewal process models

PubMed Central

Lin, Feng-Chang; Truong, Young K.; Fine, Jason P.

2013-01-01

Summary A rate model is proposed for a modulated renewal process comprising a single long sequence, where the covariate process may not capture the dependencies in the sequence as in standard intensity models. We consider partial likelihood-based inferences under a semiparametric multiplicative rate model, which has been widely studied in the context of independent and identical data. Under an intensity model, gap times in a single long sequence may be used naively in the partial likelihood with variance estimation utilizing the observed information matrix. Under a rate model, the gap times cannot be treated as independent and studying the partial likelihood is much more challenging. We employ a mixing condition in the application of limit theory for stationary sequences to obtain consistency and asymptotic normality. The estimator's variance is quite complicated owing to the unknown gap times dependence structure. We adapt block bootstrapping and cluster variance estimators to the partial likelihood. Simulation studies and an analysis of a semiparametric extension of a popular model for neural spike train data demonstrate the practical utility of the rate approach in comparison with the intensity approach. PMID:24550568

Reactive Radial Diffusion Model for the Aging/Sequestration Process

NASA Astrophysics Data System (ADS)

Ginn, T. R.; Basagaoglu, H.; McCoy, B. J.; Scow, K. M.

2001-12-01

A radial diffusion model has been formulated to simulate age-dependent bioavailability of chemical compounds to micro-organisms residing outside (and/or inside) the porous soil particles. Experimental findings in the literature indicate that the sequestration and reduction in bioavailability of contaminants are controlled presumably by the diffusion-limited sorption kinetics and the time-variant desorption process. Here we combine radial-diffusion mass transfer modeling with the exposure-time concept to generate mass-balance equations for the intra- and extra-particle concentrations. The model accomodates reversible sorption kinetics involving sorption time-dependence of the rate coefficients, distinct intra- and extra-particle biodegradation rates; and a dynamic mass interaction between the intra- and extra-particle concentrations arising from the radial diffusion concept. The model explicitly treats multiple particle classes distributed in size and chemical properties in a bulk aquifer or soil volume, which allows the simulation of the sequestration and bioavailability of contaminants in different particle size classes that have distinct diffusion, reaction, and aging properties.

Hawkes process model with a time-dependent background rate and its application to high-frequency financial data.

PubMed

Omi, Takahiro; Hirata, Yoshito; Aihara, Kazuyuki

2017-07-01

A Hawkes process model with a time-varying background rate is developed for analyzing the high-frequency financial data. In our model, the logarithm of the background rate is modeled by a linear model with a relatively large number of variable-width basis functions, and the parameters are estimated by a Bayesian method. Our model can capture not only the slow time variation, such as in the intraday seasonality, but also the rapid one, which follows a macroeconomic news announcement. By analyzing the tick data of the Nikkei 225 mini, we find that (i) our model is better fitted to the data than the Hawkes models with a constant background rate or a slowly varying background rate, which have been commonly used in the field of quantitative finance; (ii) the improvement in the goodness-of-fit to the data by our model is significant especially for sessions where considerable fluctuation of the background rate is present; and (iii) our model is statistically consistent with the data. The branching ratio, which quantifies the level of the endogeneity of markets, estimated by our model is 0.41, suggesting the relative importance of exogenous factors in the market dynamics. We also demonstrate that it is critically important to appropriately model the time-dependent background rate for the branching ratio estimation.

Hawkes process model with a time-dependent background rate and its application to high-frequency financial data

NASA Astrophysics Data System (ADS)

Omi, Takahiro; Hirata, Yoshito; Aihara, Kazuyuki

2017-07-01

A Hawkes process model with a time-varying background rate is developed for analyzing the high-frequency financial data. In our model, the logarithm of the background rate is modeled by a linear model with a relatively large number of variable-width basis functions, and the parameters are estimated by a Bayesian method. Our model can capture not only the slow time variation, such as in the intraday seasonality, but also the rapid one, which follows a macroeconomic news announcement. By analyzing the tick data of the Nikkei 225 mini, we find that (i) our model is better fitted to the data than the Hawkes models with a constant background rate or a slowly varying background rate, which have been commonly used in the field of quantitative finance; (ii) the improvement in the goodness-of-fit to the data by our model is significant especially for sessions where considerable fluctuation of the background rate is present; and (iii) our model is statistically consistent with the data. The branching ratio, which quantifies the level of the endogeneity of markets, estimated by our model is 0.41, suggesting the relative importance of exogenous factors in the market dynamics. We also demonstrate that it is critically important to appropriately model the time-dependent background rate for the branching ratio estimation.

A Nonparametric Approach For Representing Interannual Dependence In Monthly Streamflow Sequences

NASA Astrophysics Data System (ADS)

Sharma, A.; Oneill, R.

The estimation of risks associated with water management plans requires generation of synthetic streamflow sequences. The mathematical algorithms used to generate these sequences at monthly time scales are found lacking in two main respects: inability in preserving dependence attributes particularly at large (seasonal to interannual) time lags; and, a poor representation of observed distributional characteristics, in partic- ular, representation of strong assymetry or multimodality in the probability density function. Proposed here is an alternative that naturally incorporates both observed de- pendence and distributional attributes in the generated sequences. Use of a nonpara- metric framework provides an effective means for representing the observed proba- bility distribution, while the use of a Svariable kernelT ensures accurate modeling of & cedil;streamflow data sets that contain a substantial number of zero flow values. A careful selection of prior flows imparts the appropriate short-term memory, while use of an SaggregateT flow variable allows representation of interannual dependence. The non- & cedil;parametric simulation model is applied to monthly flows from the Beaver River near Beaver, Utah, USA, and the Burrendong dam inflows, New South Wales, Australia. Results indicate that while the use of traditional simulation approaches leads to an inaccurate representation of dependence at long (annual and interannual) time scales, the proposed model can simulate both short and long-term dependence. As a result, the proposed model ensures a significantly improved representation of reservoir storage statistics, particularly for systems influenced by long droughts. It is important to note that the proposed method offers a simpler and better alternative to conventional dis- aggregation models as: (a) a separate annual flow series is not required, (b) stringent assumptions relating annual and monthly flows are not needed, and (c) the method does not require the specification of a "water year", instead ensuring that the sum of any sequence of flows lasting twelve months will result in the type of dependence that is observed in the historical annual flow series.

Real-time individualization of the unified model of performance.

PubMed

Liu, Jianbo; Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Balkin, Thomas J; Reifman, Jaques

2017-12-01

Existing mathematical models for predicting neurobehavioural performance are not suited for mobile computing platforms because they cannot adapt model parameters automatically in real time to reflect individual differences in the effects of sleep loss. We used an extended Kalman filter to develop a computationally efficient algorithm that continually adapts the parameters of the recently developed Unified Model of Performance (UMP) to an individual. The algorithm accomplishes this in real time as new performance data for the individual become available. We assessed the algorithm's performance by simulating real-time model individualization for 18 subjects subjected to 64 h of total sleep deprivation (TSD) and 7 days of chronic sleep restriction (CSR) with 3 h of time in bed per night, using psychomotor vigilance task (PVT) data collected every 2 h during wakefulness. This UMP individualization process produced parameter estimates that progressively approached the solution produced by a post-hoc fitting of model parameters using all data. The minimum number of PVT measurements needed to individualize the model parameters depended upon the type of sleep-loss challenge, with ~30 required for TSD and ~70 for CSR. However, model individualization depended upon the overall duration of data collection, yielding increasingly accurate model parameters with greater number of days. Interestingly, reducing the PVT sampling frequency by a factor of two did not notably hamper model individualization. The proposed algorithm facilitates real-time learning of an individual's trait-like responses to sleep loss and enables the development of individualized performance prediction models for use in a mobile computing platform. © 2017 European Sleep Research Society.

Time-dependent interstellar chemistry

NASA Technical Reports Server (NTRS)

Glassgold, A. E.

1985-01-01

Some current problems in interstellar chemistry are considered in the context of time-dependent calculations. The limitations of steady-state models of interstellar gas-phase chemistry are discussed, and attempts to chemically date interstellar clouds are reviewed. The importance of studying the physical and chemical properties of interstellar dust is emphasized. Finally, the results of a series of studies of collapsing clouds are described.

Effects of self-esteem on state and trait components of interpersonal dependency and depression in the workplace.

PubMed

Takagishi, Yukihiro; Sakata, Masatsugu; Kitamura, Toshinori

2011-09-01

This longitudinal study was undertaken to clarify the relationships among self-esteem, interpersonal dependency, and depression, focusing on a trait and state component of interpersonal dependency and depression. In a sample of 466 working people, self-esteem, interpersonal dependency, job stressor, and depression were assessed at 2 points of time. A structural equation model (SEM) was created to differentiate the trait component of interpersonal dependency, depression and the state component of interpersonal dependency, depression. The model revealed that self-esteem influenced trait interpersonal dependency and trait depression but not state interpersonal dependency or depression. Setting a latent variable as a trait component to differentiate trait and state in interpersonal dependency and depression in SEM was found to be effective both statistically and clinically. © 2011 Wiley Periodicals, Inc.

A MODELLING FRAMEWORK FOR MERCURY CYCLING IN LAKE MICHIGAN

EPA Science Inventory

A time-dependent mercury model was developed to describe mercury cycling in Lake Michigan. The model addresses dynamic relationships between net mercury loadings and the resulting concentrations of mercury species in the water and sediment. The simplified predictive modeling fram...

Recharge characteristics of an unconfined aquifer from the rainfall-water table relationship

NASA Astrophysics Data System (ADS)

Viswanathan, M. N.

1984-02-01

The determination of recharge levels of unconfined aquifers, recharged entirely by rainfall, is done by developing a model for the aquifer that estimates the water-table levels from the history of rainfall observations and past water-table levels. In the present analysis, the model parameters that influence the recharge were not only assumed to be time dependent but also to have varying dependence rates for various parameters. Such a model is solved by the use of a recursive least-squares method. The variable-rate parameter variation is incorporated using a random walk model. From the field tests conducted at Tomago Sandbeds, Newcastle, Australia, it was observed that the assumption of variable rates of time dependency of recharge parameters produced better estimates of water-table levels compared to that with constant-recharge parameters. It was observed that considerable recharge due to rainfall occurred on the very same day of rainfall. The increase in water-table level was insignificant for subsequent days of rainfall. The level of recharge very much depends upon the intensity and history of rainfall. Isolated rainfalls, even of the order of 25 mm day -1, had no significant effect on the water-table levels.

Computationally efficient approach for solving time dependent diffusion equation with discrete temporal convolution applied to granular particles of battery electrodes

NASA Astrophysics Data System (ADS)

Senegačnik, Jure; Tavčar, Gregor; Katrašnik, Tomaž

2015-03-01

The paper presents a computationally efficient method for solving the time dependent diffusion equation in a granule of the Li-ion battery's granular solid electrode. The method, called Discrete Temporal Convolution method (DTC), is based on a discrete temporal convolution of the analytical solution of the step function boundary value problem. This approach enables modelling concentration distribution in the granular particles for arbitrary time dependent exchange fluxes that do not need to be known a priori. It is demonstrated in the paper that the proposed method features faster computational times than finite volume/difference methods and Padé approximation at the same accuracy of the results. It is also demonstrated that all three addressed methods feature higher accuracy compared to the quasi-steady polynomial approaches when applied to simulate the current densities variations typical for mobile/automotive applications. The proposed approach can thus be considered as one of the key innovative methods enabling real-time capability of the multi particle electrochemical battery models featuring spatial and temporal resolved particle concentration profiles.

Single-particle stochastic heat engine.

PubMed

Rana, Shubhashis; Pal, P S; Saha, Arnab; Jayannavar, A M

2014-10-01

We have performed an extensive analysis of a single-particle stochastic heat engine constructed by manipulating a Brownian particle in a time-dependent harmonic potential. The cycle consists of two isothermal steps at different temperatures and two adiabatic steps similar to that of a Carnot engine. The engine shows qualitative differences in inertial and overdamped regimes. All the thermodynamic quantities, including efficiency, exhibit strong fluctuations in a time periodic steady state. The fluctuations of stochastic efficiency dominate over the mean values even in the quasistatic regime. Interestingly, our system acts as an engine provided the temperature difference between the two reservoirs is greater than a finite critical value which in turn depends on the cycle time and other system parameters. This is supported by our analytical results carried out in the quasistatic regime. Our system works more reliably as an engine for large cycle times. By studying various model systems, we observe that the operational characteristics are model dependent. Our results clearly rule out any universal relation between efficiency at maximum power and temperature of the baths. We have also verified fluctuation relations for heat engines in time periodic steady state.

Real-time forecasting of an epidemic using a discrete time stochastic model: a case study of pandemic influenza (H1N1-2009).

PubMed

Nishiura, Hiroshi

2011-02-16

Real-time forecasting of epidemics, especially those based on a likelihood-based approach, is understudied. This study aimed to develop a simple method that can be used for the real-time epidemic forecasting. A discrete time stochastic model, accounting for demographic stochasticity and conditional measurement, was developed and applied as a case study to the weekly incidence of pandemic influenza (H1N1-2009) in Japan. By imposing a branching process approximation and by assuming the linear growth of cases within each reporting interval, the epidemic curve is predicted using only two parameters. The uncertainty bounds of the forecasts are computed using chains of conditional offspring distributions. The quality of the forecasts made before the epidemic peak appears largely to depend on obtaining valid parameter estimates. The forecasts of both weekly incidence and final epidemic size greatly improved at and after the epidemic peak with all the observed data points falling within the uncertainty bounds. Real-time forecasting using the discrete time stochastic model with its simple computation of the uncertainty bounds was successful. Because of the simplistic model structure, the proposed model has the potential to additionally account for various types of heterogeneity, time-dependent transmission dynamics and epidemiological details. The impact of such complexities on forecasting should be explored when the data become available as part of the disease surveillance.

A Global Picture of the Gamma-Ricker Map: A Flexible Discrete-Time Model with Factors of Positive and Negative Density Dependence.

PubMed

Liz, Eduardo

2018-02-01

The gamma-Ricker model is one of the more flexible and general discrete-time population models. It is defined on the basis of the Ricker model, introducing an additional parameter [Formula: see text]. For some values of this parameter ([Formula: see text], population is overcompensatory, and the introduction of an additional parameter gives more flexibility to fit the stock-recruitment curve to field data. For other parameter values ([Formula: see text]), the gamma-Ricker model represents populations whose per-capita growth rate combines both negative density dependence and positive density dependence. The former can lead to overcompensation and dynamic instability, and the latter can lead to a strong Allee effect. We study the impact of the cooperation factor in the dynamics and provide rigorous conditions under which increasing the Allee effect strength stabilizes or destabilizes population dynamics, promotes or prevents population extinction, and increases or decreases population size. Our theoretical results also include new global stability criteria and a description of the possible bifurcations.

Strategies for sperm chemotaxis in the siphonophores and ascidians: a numerical simulation study.

PubMed

Ishikawa, Makiko; Tsutsui, Hidekazu; Cosson, Jacky; Oka, Yoshitaka; Morisawa, Masaaki

2004-04-01

Chemotactic swimming behaviors of spermatozoa toward an egg have been reported in various species. The strategies underlying these behaviors, however, are poorly understood. We focused on two types of chemotaxis, one in the siphonophores and the second in the ascidians, and then proposed two models based on experimental data. Both models assumed that the radius of the path curvature of a swimming spermatozoon depends on [Ca(2+)](i), the intracellular calcium concentration. The chemotaxis in the siphonophores could be simulated in a model that assumes that [Ca(2+)](i) depends on the local concentration of the attractant in the vicinity of the spermatozoon and that a substantial time period is required for the clearance of transient high [Ca(2+)](i). In the case of ascidians, trajectories similar to those in experiments could be adequately simulated by a variant of this model that assumes that [Ca(2+)](i) depends on the time derivative of the attractant concentration. The properties of these strategies and future problems are discussed in relation to these models.

Characterizing the Developmental Trajectory of Sirolimus Clearance in Neonates and Infants

PubMed Central

Emoto, C; Mizuno, T; Schniedewind, B; Christians, Uwe; Adams, DM; Vinks, AA

2016-01-01

Sirolimus is increasingly being used in neonates and infants, but the mechanistic basis of age‐dependent changes in sirolimus disposition has not been fully addressed yet. In order to characterize the age‐dependent changes, serial sirolimus clearance (CL) estimates in individual young pediatric patients were collected and analyzed by population modeling analysis. In addition, sirolimus metabolite formation was also investigated to further substantiate the corresponding age‐dependent change in CYP3A activity. The increasing pattern over time of allometrically size‐normalized sirolimus CL estimates vs. age was well described by a sigmoidal Emax model. This age‐dependent increase was also observed within each individual patient over a 4‐year study period. CYP3A‐dependent sirolimus metabolite formation changed in a similar fashion. This study clearly demonstrates the rapid increase of sirolimus CL over time in neonates and infants, indicating the developmental change. This developmental pattern can be explained by a parallel increase in CYP3A metabolic activity. PMID:27501453

Other satellite atmospheres: Their nature and planetary interactions

NASA Technical Reports Server (NTRS)

Smyth, W. H.

1982-01-01

The Io sodium cloud model was successfully generated to include the time and spatial dependent lifetime sink produced by electron impact ionization as the plasma torus oscillates about the satellite plane, while simultaneously including the additional time dependence introduced by the action of solar radiation pressure on the cloud. Very preliminary model results are discussed and continuing progress in analysis of the peculiar directional features of the sodium cloud is also reported. Significant progress was made in developing a model for the Io potassium cloud and differences anticipated between the potassium and sodium cloud are described. An effort to understand the hydrogen atmosphere associated with Saturn's rings was initiated and preliminary results of a very and study are summarized.

Integrated Structural/Acoustic Modeling of Heterogeneous Panels

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett, A.; Aboudi, Jacob; Arnold, Steven, M.; Pennline, James, A.

2012-01-01

A model for the dynamic response of heterogeneous media is presented. A given medium is discretized into a number of subvolumes, each of which may contain an elastic anisotropic material, void, or fluid, and time-dependent boundary conditions are applied to simulate impact or incident pressure waves. The full time-dependent displacement and stress response throughout the medium is then determined via an explicit solution procedure. The model is applied to simulate the coupled structural/acoustic response of foam core sandwich panels as well as aluminum panels with foam inserts. Emphasis is placed on the acoustic absorption performance of the panels versus weight and the effects of the arrangement of the materials and incident wave frequency.

Consequence of reputation in the Sznajd consensus model

NASA Astrophysics Data System (ADS)

Crokidakis, Nuno; Forgerini, Fabricio L.

2010-07-01

In this work we study a modified version of the Sznajd sociophysics model. In particular we introduce reputation, a mechanism that limits the capacity of persuasion of the agents. The reputation is introduced as a score which is time-dependent, and its introduction avoid dictatorship (all spins parallel) for a wide range of parameters. The relaxation time follows a log-normal-like distribution. In addition, we show that the usual phase transition also occurs, as in the standard model, and it depends on the initial concentration of individuals following an opinion, occurring at a initial density of up spins greater than 1/2. The transition point is determined by means of a finite-size scaling analysis.

A complex permittivity model for field estimation of soil water contents using time domain reflectometry

USDA-ARS?s Scientific Manuscript database

Accurate electromagnetic sensing of soil water contents (') under field conditions is complicated by the dependence of permittivity on specific surface area, temperature, and apparent electrical conductivity, all which may vary across space or time. We present a physically-based mixing model to pred...

The development and validation of a numerical integration method for non-linear viscoelastic modeling

PubMed Central

Ramo, Nicole L.; Puttlitz, Christian M.

2018-01-01

Compelling evidence that many biological soft tissues display both strain- and time-dependent behavior has led to the development of fully non-linear viscoelastic modeling techniques to represent the tissue’s mechanical response under dynamic conditions. Since the current stress state of a viscoelastic material is dependent on all previous loading events, numerical analyses are complicated by the requirement of computing and storing the stress at each step throughout the load history. This requirement quickly becomes computationally expensive, and in some cases intractable, for finite element models. Therefore, we have developed a strain-dependent numerical integration approach for capturing non-linear viscoelasticity that enables calculation of the current stress from a strain-dependent history state variable stored from the preceding time step only, which improves both fitting efficiency and computational tractability. This methodology was validated based on its ability to recover non-linear viscoelastic coefficients from simulated stress-relaxation (six strain levels) and dynamic cyclic (three frequencies) experimental stress-strain data. The model successfully fit each data set with average errors in recovered coefficients of 0.3% for stress-relaxation fits and 0.1% for cyclic. The results support the use of the presented methodology to develop linear or non-linear viscoelastic models from stress-relaxation or cyclic experimental data of biological soft tissues. PMID:29293558

Position-dependent radiative transfer as a tool for studying Anderson localization: Delay time, time-reversal and coherent backscattering

NASA Astrophysics Data System (ADS)

van Tiggelen, B. A.; Skipetrov, S. E.; Page, J. H.

2017-05-01

Previous work has established that the localized regime of wave transport in open media is characterized by a position-dependent diffusion coefficient. In this work we study how the concept of position-dependent diffusion affects the delay time, the transverse confinement, the coherent backscattering, and the time reversal of waves. Definitions of energy transport velocity of localized waves are proposed. We start with a phenomenological model of radiative transfer and then present a novel perturbational approach based on the self-consistent theory of localization. The latter allows us to obtain results relevant for realistic experiments in disordered quasi-1D wave guides and 3D slabs.

Conditional Dependence between Response Time and Accuracy: An Overview of its Possible Sources and Directions for Distinguishing between Them

PubMed Central

Bolsinova, Maria; Tijmstra, Jesper; Molenaar, Dylan; De Boeck, Paul

2017-01-01

With the widespread use of computerized tests in educational measurement and cognitive psychology, registration of response times has become feasible in many applications. Considering these response times helps provide a more complete picture of the performance and characteristics of persons beyond what is available based on response accuracy alone. Statistical models such as the hierarchical model (van der Linden, 2007) have been proposed that jointly model response time and accuracy. However, these models make restrictive assumptions about the response processes (RPs) that may not be realistic in practice, such as the assumption that the association between response time and accuracy is fully explained by taking speed and ability into account (conditional independence). Assuming conditional independence forces one to ignore that many relevant individual differences may play a role in the RPs beyond overall speed and ability. In this paper, we critically consider the assumption of conditional independence and the important ways in which it may be violated in practice from a substantive perspective. We consider both conditional dependences that may arise when all persons attempt to solve the items in similar ways (homogeneous RPs) and those that may be due to persons differing in fundamental ways in how they deal with the items (heterogeneous processes). The paper provides an overview of what we can learn from observed conditional dependences. We argue that explaining and modeling these differences in the RPs is crucial to increase both the validity of measurement and our understanding of the relevant RPs. PMID:28261136

Modeling Stepped Leaders Using a Time Dependent Multi-dipole Model and High-speed Video Data

NASA Astrophysics Data System (ADS)

Karunarathne, S.; Marshall, T.; Stolzenburg, M.; Warner, T. A.; Orville, R. E.

2012-12-01

In summer of 2011, we collected lightning data with 10 stations of electric field change meters (bandwidth of 0.16 Hz - 2.6 MHz) on and around NASA/Kennedy Space Center (KSC) covering nearly 70 km × 100 km area. We also had a high-speed video (HSV) camera recording 50,000 images per second collocated with one of the electric field change meters. In this presentation we describe our use of these data to model the electric field change caused by stepped leaders. Stepped leaders of a cloud to ground lightning flash typically create the initial path for the first return stroke (RS). Most of the time, stepped leaders have multiple complex branches, and one of these branches will create the ground connection for the RS to start. HSV data acquired with a short focal length lens at ranges of 5-25 km from the flash are useful for obtaining the 2-D location of these multiple branches developing at the same time. Using HSV data along with data from the KSC Lightning Detection and Ranging (LDAR2) system and the Cloud to Ground Lightning Surveillance System (CGLSS), the 3D path of a leader may be estimated. Once the path of a stepped leader is obtained, the time dependent multi-dipole model [ Lu, Winn,and Sonnenfeld, JGR 2011] can be used to match the electric field change at various sensor locations. Based on this model, we will present the time-dependent charge distribution along a leader channel and the total charge transfer during the stepped leader phase.

A single-vendor and a single-buyer integrated inventory model with ordering cost reduction dependent on lead time

NASA Astrophysics Data System (ADS)

Vijayashree, M.; Uthayakumar, R.

2017-09-01

Lead time is one of the major limits that affect planning at every stage of the supply chain system. In this paper, we study a continuous review inventory model. This paper investigates the ordering cost reductions are dependent on lead time. This study addressed two-echelon supply chain problem consisting of a single vendor and a single buyer. The main contribution of this study is that the integrated total cost of the single vendor and the single buyer integrated system is analyzed by adopting two different (linear and logarithmic) types ordering cost reductions act dependent on lead time. In both cases, we develop effective solution procedures for finding the optimal solution and then illustrative numerical examples are given to illustrate the results. The solution procedure is to determine the optimal solutions of order quantity, ordering cost, lead time and the number of deliveries from the single vendor and the single buyer in one production run, so that the integrated total cost incurred has the minimum value. Ordering cost reduction is the main aspect of the proposed model. A numerical example is given to validate the model. Numerical example solved by using Matlab software. The mathematical model is solved analytically by minimizing the integrated total cost. Furthermore, the sensitivity analysis is included and the numerical examples are given to illustrate the results. The results obtained in this paper are illustrated with the help of numerical examples. The sensitivity of the proposed model has been checked with respect to the various major parameters of the system. Results reveal that the proposed integrated inventory model is more applicable for the supply chain manufacturing system. For each case, an algorithm procedure of finding the optimal solution is developed. Finally, the graphical representation is presented to illustrate the proposed model and also include the computer flowchart in each model.

A Conditional Joint Modeling Approach for Locally Dependent Item Responses and Response Times

ERIC Educational Resources Information Center

Meng, Xiang-Bin; Tao, Jian; Chang, Hua-Hua

2015-01-01

The assumption of conditional independence between the responses and the response times (RTs) for a given person is common in RT modeling. However, when the speed of a test taker is not constant, this assumption will be violated. In this article we propose a conditional joint model for item responses and RTs, which incorporates a covariance…

Thermalization and light cones in a model with weak integrability breaking

DOE PAGES

Bertini, Bruno; Essler, Fabian H. L.; Groha, Stefan; ...

2016-12-09

Here, we employ equation-of-motion techniques to study the nonequilibrium dynamics in a lattice model of weakly interacting spinless fermions. Our model provides a simple setting for analyzing the effects of weak integrability-breaking perturbations on the time evolution after a quantum quench. We establish the accuracy of the method by comparing results at short and intermediate times to time-dependent density matrix renormalization group computations. For sufficiently weak integrability-breaking interactions we always observe prethermalization plateaus, where local observables relax to nonthermal values at intermediate time scales. At later times a crossover towards thermal behavior sets in. We determine the associated time scale,more » which depends on the initial state, the band structure of the noninteracting theory, and the strength of the integrability-breaking perturbation. Our method allows us to analyze in some detail the spreading of correlations and in particular the structure of the associated light cones in our model. We find that the interior and exterior of the light cone are separated by an intermediate region, the temporal width of which appears to scale with a universal power law t 1/3.« less

An ensemble survival model for estimating relative residual longevity following stroke: Application to mortality data in the chronic dialysis population

PubMed Central

Phadnis, Milind A; Wetmore, James B; Shireman, Theresa I; Ellerbeck, Edward F; Mahnken, Jonathan D

2016-01-01

Time-dependent covariates can be modeled within the Cox regression framework and can allow both proportional and nonproportional hazards for the risk factor of research interest. However, in many areas of health services research, interest centers on being able to estimate residual longevity after the occurrence of a particular event such as stroke. The survival trajectory of patients experiencing a stroke can be potentially influenced by stroke type (hemorrhagic or ischemic), time of the stroke (relative to time zero), time since the stroke occurred, or a combination of these factors. In such situations, researchers are more interested in estimating lifetime lost due to stroke rather than merely estimating the relative hazard due to stroke. To achieve this, we propose an ensemble approach using the generalized gamma distribution by means of a semi-Markov type model with an additive hazards extension. Our modeling framework allows stroke as a time-dependent covariate to affect all three parameters (location, scale, and shape) of the generalized gamma distribution. Using the concept of relative times, we answer the research question by estimating residual life lost due to ischemic and hemorrhagic stroke in the chronic dialysis population. PMID:26403934

An ensemble survival model for estimating relative residual longevity following stroke: Application to mortality data in the chronic dialysis population.

PubMed

Phadnis, Milind A; Wetmore, James B; Shireman, Theresa I; Ellerbeck, Edward F; Mahnken, Jonathan D

2017-12-01

Time-dependent covariates can be modeled within the Cox regression framework and can allow both proportional and nonproportional hazards for the risk factor of research interest. However, in many areas of health services research, interest centers on being able to estimate residual longevity after the occurrence of a particular event such as stroke. The survival trajectory of patients experiencing a stroke can be potentially influenced by stroke type (hemorrhagic or ischemic), time of the stroke (relative to time zero), time since the stroke occurred, or a combination of these factors. In such situations, researchers are more interested in estimating lifetime lost due to stroke rather than merely estimating the relative hazard due to stroke. To achieve this, we propose an ensemble approach using the generalized gamma distribution by means of a semi-Markov type model with an additive hazards extension. Our modeling framework allows stroke as a time-dependent covariate to affect all three parameters (location, scale, and shape) of the generalized gamma distribution. Using the concept of relative times, we answer the research question by estimating residual life lost due to ischemic and hemorrhagic stroke in the chronic dialysis population.

Support time-dependent transformations for surveying and GIS : current status and upcoming challenges

NASA Astrophysics Data System (ADS)

Mahmoudabadi, H.; Lercier, D.; Vielliard, S.; Mein, N.; Briggs, G.

2016-12-01

The support of time-dependent transformations for surveying and GIS is becoming a critical issue. We need to convert positions from the realizations of the International Terrestrial Reference Frame to any national reference frame. This problem is easy to solve when all of the required information is available. But it becomes really complicated in a worldwide context. We propose an overview of the current ITRF-aligned reference frames and we describe a global solution to support time-dependent transformations between them and the International Terrestrial Reference Frame. We focus on the uncertainties of station velocities used. In a first approximation, we use a global tectonic plate model to calculate point velocities. We show the impact of the velocity model on the coordinate accuracies. Several countries, particularly in active regions, are developing semi-dynamic reference frames. These frames include local displacement models updated regularly and/or after major events (such as earthquakes). Their integration into surveying or GIS applications is an upcoming challenge. We want to encourage the geodetic community to develop and use standard formats.

Triphasic spike-timing-dependent plasticity organizes networks to produce robust sequences of neural activity

PubMed Central

Waddington, Amelia; Appleby, Peter A.; De Kamps, Marc; Cohen, Netta

2012-01-01

Synfire chains have long been proposed to generate precisely timed sequences of neural activity. Such activity has been linked to numerous neural functions including sensory encoding, cognitive and motor responses. In particular, it has been argued that synfire chains underlie the precise spatiotemporal firing patterns that control song production in a variety of songbirds. Previous studies have suggested that the development of synfire chains requires either initial sparse connectivity or strong topological constraints, in addition to any synaptic learning rules. Here, we show that this necessity can be removed by using a previously reported but hitherto unconsidered spike-timing-dependent plasticity (STDP) rule and activity-dependent excitability. Under this rule the network develops stable synfire chains that possess a non-trivial, scalable multi-layer structure, in which relative layer sizes appear to follow a universal function. Using computational modeling and a coarse grained random walk model, we demonstrate the role of the STDP rule in growing, molding and stabilizing the chain, and link model parameters to the resulting structure. PMID:23162457

Reinforcement Learning Using a Continuous Time Actor-Critic Framework with Spiking Neurons

PubMed Central

Frémaux, Nicolas; Sprekeler, Henning; Gerstner, Wulfram

2013-01-01

Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity. PMID:23592970

Reinforcement learning using a continuous time actor-critic framework with spiking neurons.

PubMed

Frémaux, Nicolas; Sprekeler, Henning; Gerstner, Wulfram

2013-04-01

Animals repeat rewarded behaviors, but the physiological basis of reward-based learning has only been partially elucidated. On one hand, experimental evidence shows that the neuromodulator dopamine carries information about rewards and affects synaptic plasticity. On the other hand, the theory of reinforcement learning provides a framework for reward-based learning. Recent models of reward-modulated spike-timing-dependent plasticity have made first steps towards bridging the gap between the two approaches, but faced two problems. First, reinforcement learning is typically formulated in a discrete framework, ill-adapted to the description of natural situations. Second, biologically plausible models of reward-modulated spike-timing-dependent plasticity require precise calculation of the reward prediction error, yet it remains to be shown how this can be computed by neurons. Here we propose a solution to these problems by extending the continuous temporal difference (TD) learning of Doya (2000) to the case of spiking neurons in an actor-critic network operating in continuous time, and with continuous state and action representations. In our model, the critic learns to predict expected future rewards in real time. Its activity, together with actual rewards, conditions the delivery of a neuromodulatory TD signal to itself and to the actor, which is responsible for action choice. In simulations, we show that such an architecture can solve a Morris water-maze-like navigation task, in a number of trials consistent with reported animal performance. We also use our model to solve the acrobot and the cartpole problems, two complex motor control tasks. Our model provides a plausible way of computing reward prediction error in the brain. Moreover, the analytically derived learning rule is consistent with experimental evidence for dopamine-modulated spike-timing-dependent plasticity.

Understanding Pitch Perception as a Hierarchical Process with Top-Down Modulation

PubMed Central

Balaguer-Ballester, Emili; Clark, Nicholas R.; Coath, Martin; Krumbholz, Katrin; Denham, Susan L.

2009-01-01

Pitch is one of the most important features of natural sounds, underlying the perception of melody in music and prosody in speech. However, the temporal dynamics of pitch processing are still poorly understood. Previous studies suggest that the auditory system uses a wide range of time scales to integrate pitch-related information and that the effective integration time is both task- and stimulus-dependent. None of the existing models of pitch processing can account for such task- and stimulus-dependent variations in processing time scales. This study presents an idealized neurocomputational model, which provides a unified account of the multiple time scales observed in pitch perception. The model is evaluated using a range of perceptual studies, which have not previously been accounted for by a single model, and new results from a neurophysiological experiment. In contrast to other approaches, the current model contains a hierarchy of integration stages and uses feedback to adapt the effective time scales of processing at each stage in response to changes in the input stimulus. The model has features in common with a hierarchical generative process and suggests a key role for efferent connections from central to sub-cortical areas in controlling the temporal dynamics of pitch processing. PMID:19266015

The stochastic system approach for estimating dynamic treatments effect.

PubMed

Commenges, Daniel; Gégout-Petit, Anne

2015-10-01

The problem of assessing the effect of a treatment on a marker in observational studies raises the difficulty that attribution of the treatment may depend on the observed marker values. As an example, we focus on the analysis of the effect of a HAART on CD4 counts, where attribution of the treatment may depend on the observed marker values. This problem has been treated using marginal structural models relying on the counterfactual/potential response formalism. Another approach to causality is based on dynamical models, and causal influence has been formalized in the framework of the Doob-Meyer decomposition of stochastic processes. Causal inference however needs assumptions that we detail in this paper and we call this approach to causality the "stochastic system" approach. First we treat this problem in discrete time, then in continuous time. This approach allows incorporating biological knowledge naturally. When working in continuous time, the mechanistic approach involves distinguishing the model for the system and the model for the observations. Indeed, biological systems live in continuous time, and mechanisms can be expressed in the form of a system of differential equations, while observations are taken at discrete times. Inference in mechanistic models is challenging, particularly from a numerical point of view, but these models can yield much richer and reliable results.

Frequency-dependent selection predicts patterns of radiations and biodiversity.

PubMed

Melián, Carlos J; Alonso, David; Vázquez, Diego P; Regetz, James; Allesina, Stefano

2010-08-26

Most empirical studies support a decline in speciation rates through time, although evidence for constant speciation rates also exists. Declining rates have been explained by invoking pre-existing niches, whereas constant rates have been attributed to non-adaptive processes such as sexual selection and mutation. Trends in speciation rate and the processes underlying it remain unclear, representing a critical information gap in understanding patterns of global diversity. Here we show that the temporal trend in the speciation rate can also be explained by frequency-dependent selection. We construct a frequency-dependent and DNA sequence-based model of speciation. We compare our model to empirical diversity patterns observed for cichlid fish and Darwin's finches, two classic systems for which speciation rates and richness data exist. Negative frequency-dependent selection predicts well both the declining speciation rate found in cichlid fish and explains their species richness. For groups like the Darwin's finches, in which speciation rates are constant and diversity is lower, speciation rate is better explained by a model without frequency-dependent selection. Our analysis shows that differences in diversity may be driven by incipient species abundance with frequency-dependent selection. Our results demonstrate that genetic-distance-based speciation and frequency-dependent selection are sufficient to explain the high diversity observed in natural systems and, importantly, predict decay through time in speciation rate in the absence of pre-existing niches.

Real-Time Measurements of Aft Dome Insulation Erosion on Space Shuttle Reusable Solid Rocket Motor

NASA Technical Reports Server (NTRS)

McWhorter, Bruce; Ewing, Mark; Albrechtsen, Kevin; Noble, Todd; Longaker, Matt

2004-01-01

Real-time erosion of aft dome internal insulation was measured with internal instrumentation on a static test of a lengthened version of the Space Shuffle Reusable Solid Rocket Motor (RSRM). This effort marks the first time that real-time aft dome insulation erosion (Le., erosion due to the combined effects of thermochemical ablation and mechanical abrasion) was measured in this kind of large motor static test [designated as Engineering Test Motor number 3 (ETM3)I. This paper presents data plots of the erosion depth versus time. The data indicates general erosion versus time behavior that is in contrast to what would be expected from earlier analyses. Engineers have long known that the thermal environment in the aft dome is severe and that the resulting aft dome insulation erosion is significant. Models of aft dome erosion involve a two-step process of computational fluid dynamics (CFD) modeling and material ablation modeling. This modeling effort is complex. The time- dependent effects are difficult to verify with only prefire and postfire insulation measurements. Nozzle vectoring, slag accumulation, and changing boundary conditions will affect the time dependence of aft dome erosion. Further study of this data and continued measurements on future motors will increase our understanding of the aft dome flow and erosion environment.

Dynamic modulation of spike timing-dependent calcium influx during corticostriatal upstates

PubMed Central

Evans, R. C.; Maniar, Y. M.

2013-01-01

The striatum of the basal ganglia demonstrates distinctive upstate and downstate membrane potential oscillations during slow-wave sleep and under anesthetic. The upstates generate calcium transients in the dendrites, and the amplitude of these calcium transients depends strongly on the timing of the action potential (AP) within the upstate. Calcium is essential for synaptic plasticity in the striatum, and these large calcium transients during the upstates may control which synapses undergo plastic changes. To investigate the mechanisms that underlie the relationship between calcium and AP timing, we have developed a realistic biophysical model of a medium spiny neuron (MSN). We have implemented sophisticated calcium dynamics including calcium diffusion, buffering, and pump extrusion, which accurately replicate published data. Using this model, we found that either the slow inactivation of dendritic sodium channels (NaSI) or the calcium inactivation of voltage-gated calcium channels (CDI) can cause high calcium corresponding to early APs and lower calcium corresponding to later APs. We found that only CDI can account for the experimental observation that sensitivity to AP timing is dependent on NMDA receptors. Additional simulations demonstrated a mechanism by which MSNs can dynamically modulate their sensitivity to AP timing and show that sensitivity to specifically timed pre- and postsynaptic pairings (as in spike timing-dependent plasticity protocols) is altered by the timing of the pairing within the upstate. These findings have implications for synaptic plasticity in vivo during sleep when the upstate-downstate pattern is prominent in the striatum. PMID:23843436

Evaluation of a Multi-Axial, Temperature, and Time Dependent (MATT) Failure Model

NASA Technical Reports Server (NTRS)

Richardson, D. E.; Anderson, G. L.; Macon, D. J.; Rudolphi, Michael (Technical Monitor)

2002-01-01

To obtain a better understanding the response of the structural adhesives used in the Space Shuttle's Reusable Solid Rocket Motor (RSRM) nozzle, an extensive effort has been conducted to characterize in detail the failure properties of these adhesives. This effort involved the development of a failure model that includes the effects of multi-axial loading, temperature, and time. An understanding of the effects of these parameters on the failure of the adhesive is crucial to the understanding and prediction of the safety of the RSRM nozzle. This paper documents the use of this newly developed multi-axial, temperature, and time (MATT) dependent failure model for modeling failure for the adhesives TIGA 321, EA913NA, and EA946. The development of the mathematical failure model using constant load rate normal and shear test data is presented. Verification of the accuracy of the failure model is shown through comparisons between predictions and measured creep and multi-axial failure data. The verification indicates that the failure model performs well for a wide range of conditions (loading, temperature, and time) for the three adhesives. The failure criterion is shown to be accurate through the glass transition for the adhesive EA946. Though this failure model has been developed and evaluated with adhesives, the concepts are applicable for other isotropic materials.

Prediction of hemoglobin in blood donors using a latent class mixed-effects transition model.

PubMed

Nasserinejad, Kazem; van Rosmalen, Joost; de Kort, Wim; Rizopoulos, Dimitris; Lesaffre, Emmanuel

2016-02-20

Blood donors experience a temporary reduction in their hemoglobin (Hb) value after donation. At each visit, the Hb value is measured, and a too low Hb value leads to a deferral for donation. Because of the recovery process after each donation as well as state dependence and unobserved heterogeneity, longitudinal data of Hb values of blood donors provide unique statistical challenges. To estimate the shape and duration of the recovery process and to predict future Hb values, we employed three models for the Hb value: (i) a mixed-effects models; (ii) a latent-class mixed-effects model; and (iii) a latent-class mixed-effects transition model. In each model, a flexible function was used to model the recovery process after donation. The latent classes identify groups of donors with fast or slow recovery times and donors whose recovery time increases with the number of donations. The transition effect accounts for possible state dependence in the observed data. All models were estimated in a Bayesian way, using data of new entrant donors from the Donor InSight study. Informative priors were used for parameters of the recovery process that were not identified using the observed data, based on results from the clinical literature. The results show that the latent-class mixed-effects transition model fits the data best, which illustrates the importance of modeling state dependence, unobserved heterogeneity, and the recovery process after donation. The estimated recovery time is much longer than the current minimum interval between donations, suggesting that an increase of this interval may be warranted. Copyright © 2015 John Wiley & Sons, Ltd.

Validation of Methods to Control for Immortal Time Bias in a Pharmacoepidemiologic Analysis of Renin–Angiotensin System Inhibitors in Type 2 Diabetes

PubMed Central

Yang, Xilin; Kong, Alice PS; Luk, Andrea OY; Ozaki, Risa; Ko, Gary TC; Ma, Ronald CW; Chan, Juliana CN; So, Wing Yee

2014-01-01

Background Pharmacoepidemiologic analysis can confirm whether drug efficacy in a randomized controlled trial (RCT) translates to effectiveness in real settings. We examined methods used to control for immortal time bias in an analysis of renin–angiotensin system (RAS) inhibitors as the reference cardioprotective drug. Methods We analyzed data from 3928 patients with type 2 diabetes who were recruited into the Hong Kong Diabetes Registry between 1996 and 2005 and followed up to July 30, 2005. Different Cox models were used to obtain hazard ratios (HRs) for cardiovascular disease (CVD) associated with RAS inhibitors. These HRs were then compared to the HR of 0.92 reported in a recent meta-analysis of RCTs. Results During a median follow-up period of 5.45 years, 7.23% (n = 284) patients developed CVD and 38.7% (n = 1519) were started on RAS inhibitors, with 39.1% of immortal time among the users. In multivariable analysis, time-dependent drug-exposure Cox models and Cox models that moved immortal time from users to nonusers both severely inflated the HR, and time-fixed models that included immortal time deflated the HR. Use of time-fixed Cox models that excluded immortal time resulted in a HR of only 0.89 (95% CI, 0.68–1.17) for CVD associated with RAS inhibitors, which is closer to the values reported in RCTs. Conclusions In pharmacoepidemiologic analysis, time-dependent drug exposure models and models that move immortal time from users to nonusers may introduce substantial bias in investigations of the effects of RAS inhibitors on CVD in type 2 diabetes. PMID:24747198

Conditional, Time-Dependent Probabilities for Segmented Type-A Faults in the WGCEP UCERF 2

USGS Publications Warehouse

Field, Edward H.; Gupta, Vipin

2008-01-01

This appendix presents elastic-rebound-theory (ERT) motivated time-dependent probabilities, conditioned on the date of last earthquake, for the segmented type-A fault models of the 2007 Working Group on California Earthquake Probabilities (WGCEP). These probabilities are included as one option in the WGCEP?s Uniform California Earthquake Rupture Forecast 2 (UCERF 2), with the other options being time-independent Poisson probabilities and an ?Empirical? model based on observed seismicity rate changes. A more general discussion of the pros and cons of all methods for computing time-dependent probabilities, as well as the justification of those chosen for UCERF 2, are given in the main body of this report (and the 'Empirical' model is also discussed in Appendix M). What this appendix addresses is the computation of conditional, time-dependent probabilities when both single- and multi-segment ruptures are included in the model. Computing conditional probabilities is relatively straightforward when a fault is assumed to obey strict segmentation in the sense that no multi-segment ruptures occur (e.g., WGCEP (1988, 1990) or see Field (2007) for a review of all previous WGCEPs; from here we assume basic familiarity with conditional probability calculations). However, and as we?ll see below, the calculation is not straightforward when multi-segment ruptures are included, in essence because we are attempting to apply a point-process model to a non point process. The next section gives a review and evaluation of the single- and multi-segment rupture probability-calculation methods used in the most recent statewide forecast for California (WGCEP UCERF 1; Petersen et al., 2007). We then present results for the methodology adopted here for UCERF 2. We finish with a discussion of issues and possible alternative approaches that could be explored and perhaps applied in the future. A fault-by-fault comparison of UCERF 2 probabilities with those of previous studies is given in the main part of this report.

The delayed rectifier potassium conductance in the sarcolemma and the transverse tubular system membranes of mammalian skeletal muscle fibers

PubMed Central

DiFranco, Marino; Quinonez, Marbella

2012-01-01

A two-microelectrode voltage clamp and optical measurements of membrane potential changes at the transverse tubular system (TTS) were used to characterize delayed rectifier K currents (IKV) in murine muscle fibers stained with the potentiometric dye di-8-ANEPPS. In intact fibers, IKV displays the canonical hallmarks of KV channels: voltage-dependent delayed activation and decay in time. The voltage dependence of the peak conductance (gKV) was only accounted for by double Boltzmann fits, suggesting at least two channel contributions to IKV. Osmotically treated fibers showed significant disconnection of the TTS and displayed smaller IKV, but with similar voltage dependence and time decays to intact fibers. This suggests that inactivation may be responsible for most of the decay in IKV records. A two-channel model that faithfully simulates IKV records in osmotically treated fibers comprises a low threshold and steeply voltage-dependent channel (channel A), which contributes ∼31% of gKV, and a more abundant high threshold channel (channel B), with shallower voltage dependence. Significant expression of the IKV1.4 and IKV3.4 channels was demonstrated by immunoblotting. Rectangular depolarizing pulses elicited step-like di-8-ANEPPS transients in intact fibers rendered electrically passive. In contrast, activation of IKV resulted in time- and voltage-dependent attenuations in optical transients that coincided in time with the peaks of IKV records. Normalized peak attenuations showed the same voltage dependence as peak IKV plots. A radial cable model including channels A and B and K diffusion in the TTS was used to simulate IKV and average TTS voltage changes. Model predictions and experimental data were compared to determine what fraction of gKV in the TTS accounted simultaneously for the electrical and optical data. Best predictions suggest that KV channels are approximately equally distributed in the sarcolemma and TTS membranes; under these conditions, >70% of IKV arises from the TTS. PMID:22851675

Transient triggering of near and distant earthquakes

USGS Publications Warehouse

Gomberg, J.; Blanpied, M.L.; Beeler, N.M.

1997-01-01

We demonstrate qualitatively that frictional instability theory provides a context for understanding how earthquakes may be triggered by transient loads associated with seismic waves from near and distance earthquakes. We assume that earthquake triggering is a stick-slip process and test two hypotheses about the effect of transients on the timing of instabilities using a simple spring-slider model and a rate- and state-dependent friction constitutive law. A critical triggering threshold is implicit in such a model formulation. Our first hypothesis is that transient loads lead to clock advances; i.e., transients hasten the time of earthquakes that would have happened eventually due to constant background loading alone. Modeling results demonstrate that transient loads do lead to clock advances and that the triggered instabilities may occur after the transient has ceased (i.e., triggering may be delayed). These simple "clock-advance" models predict complex relationships between the triggering delay, the clock advance, and the transient characteristics. The triggering delay and the degree of clock advance both depend nonlinearly on when in the earthquake cycle the transient load is applied. This implies that the stress required to bring about failure does not depend linearly on loading time, even when the fault is loaded at a constant rate. The timing of instability also depends nonlinearly on the transient loading rate, faster rates more rapidly hastening instability. This implies that higher-frequency and/or longer-duration seismic waves should increase the amount of clock advance. These modeling results and simple calculations suggest that near (tens of kilometers) small/moderate earthquakes and remote (thousands of kilometers) earthquakes with magnitudes 2 to 3 units larger may be equally effective at triggering seismicity. Our second hypothesis is that some triggered seismicity represents earthquakes that would not have happened without the transient load (i.e., accumulated strain energy would have been relieved via other mechanisms). We test this using two "new-seismicity" models that (1) are inherently unstable but slide at steady-state conditions under the background load and (2) are conditionally stable such that instability occurs only for sufficiently large perturbations. For the new-seismicity models, very small-amplitude transients trigger instability relative to the clock-advance models. The unstable steady-state models predict that the triggering delay depends inversely and nonlinearly on the transient amplitude (as in the clock-advance models). We were unable to generate delayed triggering with conditionally stable models. For both new-seismicity models, the potential for triggering is independent of when the transient load is applied or, equivalently, of the prestress (unlike in the clock-advance models). In these models, a critical triggering threshold appears to be inversely proportional to frequency. Further advancement of our understanding will require more sophisticated, quantitative models and observations that distinguish between our qualitative, yet distinctly different, model predictions.

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-01-01

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

Modeling hard clinical end-point data in economic analyses.

PubMed

Kansal, Anuraag R; Zheng, Ying; Palencia, Roberto; Ruffolo, Antonio; Hass, Bastian; Sorensen, Sonja V

2013-11-01

The availability of hard clinical end-point data, such as that on cardiovascular (CV) events among patients with type 2 diabetes mellitus, is increasing, and as a result there is growing interest in using hard end-point data of this type in economic analyses. This study investigated published approaches for modeling hard end-points from clinical trials and evaluated their applicability in health economic models with different disease features. A review of cost-effectiveness models of interventions in clinically significant therapeutic areas (CV diseases, cancer, and chronic lower respiratory diseases) was conducted in PubMed and Embase using a defined search strategy. Only studies integrating hard end-point data from randomized clinical trials were considered. For each study included, clinical input characteristics and modeling approach were summarized and evaluated. A total of 33 articles (23 CV, eight cancer, two respiratory) were accepted for detailed analysis. Decision trees, Markov models, discrete event simulations, and hybrids were used. Event rates were incorporated either as constant rates, time-dependent risks, or risk equations based on patient characteristics. Risks dependent on time and/or patient characteristics were used where major event rates were >1%/year in models with fewer health states (<7). Models of infrequent events or with numerous health states generally preferred constant event rates. The detailed modeling information and terminology varied, sometimes requiring interpretation. Key considerations for cost-effectiveness models incorporating hard end-point data include the frequency and characteristics of the relevant clinical events and how the trial data is reported. When event risk is low, simplification of both the model structure and event rate modeling is recommended. When event risk is common, such as in high risk populations, more detailed modeling approaches, including individual simulations or explicitly time-dependent event rates, are more appropriate to accurately reflect the trial data.

Intelligent sensor-model automated control of PMR-15 autoclave processing

NASA Technical Reports Server (NTRS)

Hart, S.; Kranbuehl, D.; Loos, A.; Hinds, B.; Koury, J.

1992-01-01

An intelligent sensor model system has been built and used for automated control of the PMR-15 cure process in the autoclave. The system uses frequency-dependent FM sensing (FDEMS), the Loos processing model, and the Air Force QPAL intelligent software shell. The Loos model is used to predict and optimize the cure process including the time-temperature dependence of the extent of reaction, flow, and part consolidation. The FDEMS sensing system in turn monitors, in situ, the removal of solvent, changes in the viscosity, reaction advancement and cure completion in the mold continuously throughout the processing cycle. The sensor information is compared with the optimum processing conditions from the model. The QPAL composite cure control system allows comparison of the sensor monitoring with the model predictions to be broken down into a series of discrete steps and provides a language for making decisions on what to do next regarding time-temperature and pressure.

Dynamo action with wave motion.

PubMed

Tilgner, A

2008-03-28

It is shown that time dependent velocity fields in a fluid conductor can act as dynamos even when the same velocity fields frozen in at any particular time cannot. This effect is observed in propagating waves in which the time dependence is simply a steady drift of a fixed velocity pattern. The effect contributes to magnetic field generation in numerical models of planetary dynamos and relies on the property that eigenmodes of the induction equation are not all orthogonal to each other.

When can time-dependent currents be reproduced by the Landauer steady-state approximation?

NASA Astrophysics Data System (ADS)

Carey, Rachel; Chen, Liping; Gu, Bing; Franco, Ignacio

2017-05-01

We establish well-defined limits in which the time-dependent electronic currents across a molecular junction subject to a fluctuating environment can be quantitatively captured via the Landauer steady-state approximation. For this, we calculate the exact time-dependent non-equilibrium Green's function (TD-NEGF) current along a model two-site molecular junction, in which the site energies are subject to correlated noise, and contrast it with that obtained from the Landauer approach. The ability of the steady-state approximation to capture the TD-NEGF behavior at each instant of time is quantified via the same-time correlation function of the currents obtained from the two methods, while their global agreement is quantified by examining differences in the average currents. The Landauer steady-state approach is found to be a useful approximation when (i) the fluctuations do not disrupt the degree of delocalization of the molecular eigenstates responsible for transport and (ii) the characteristic time for charge exchange between the molecule and leads is fast with respect to the molecular correlation time. For resonant transport, when these conditions are satisfied, the Landauer approach is found to accurately describe the current, both on average and at each instant of time. For non-resonant transport, we find that while the steady-state approach fails to capture the time-dependent transport at each instant of time, it still provides a good approximation to the average currents. These criteria can be employed to adopt effective modeling strategies for transport through molecular junctions in interaction with a fluctuating environment, as is necessary to describe experiments.

Some consequences of shear on galactic dynamos with helicity fluxes

NASA Astrophysics Data System (ADS)

Zhou, Hongzhe; Blackman, Eric G.

2017-08-01

Galactic dynamo models sustained by supernova (SN) driven turbulence and differential rotation have revealed that the sustenance of large-scale fields requires a flux of small-scale magnetic helicity to be viable. Here we generalize a minimalist analytic version of such galactic dynamos to explore some heretofore unincluded contributions from shear on the total turbulent energy and turbulent correlation time, with the helicity fluxes maintained by either winds, diffusion or magnetic buoyancy. We construct an analytic framework for modelling the turbulent energy and correlation time as a function of SN rate and shear. We compare our prescription with previous approaches that include only rotation. The solutions depend separately on the rotation period and the eddy turnover time and not just on their ratio (the Rossby number). We consider models in which these two time-scales are allowed to be independent and also a case in which they are mutually dependent on radius when a radial-dependent SN rate model is invoked. For the case of a fixed rotation period (or a fixed radius), we show that the influence of shear is dramatic for low Rossby numbers, reducing the correlation time of the turbulence, which, in turn, strongly reduces the saturation value of the dynamo compared to the case when the shear is ignored. We also show that even in the absence of winds or diffusive fluxes, magnetic buoyancy may be able to sustain sufficient helicity fluxes to avoid quenching.

Time-dependent summary receiver operating characteristics for meta-analysis of prognostic studies.

PubMed

Hattori, Satoshi; Zhou, Xiao-Hua

2016-11-20

Prognostic studies are widely conducted to examine whether biomarkers are associated with patient's prognoses and play important roles in medical decisions. Because findings from one prognostic study may be very limited, meta-analyses may be useful to obtain sound evidence. However, prognostic studies are often analyzed by relying on a study-specific cut-off value, which can lead to difficulty in applying the standard meta-analysis techniques. In this paper, we propose two methods to estimate a time-dependent version of the summary receiver operating characteristics curve for meta-analyses of prognostic studies with a right-censored time-to-event outcome. We introduce a bivariate normal model for the pair of time-dependent sensitivity and specificity and propose a method to form inferences based on summary statistics reported in published papers. This method provides a valid inference asymptotically. In addition, we consider a bivariate binomial model. To draw inferences from this bivariate binomial model, we introduce a multiple imputation method. The multiple imputation is found to be approximately proper multiple imputation, and thus the standard Rubin's variance formula is justified from a Bayesian view point. Our simulation study and application to a real dataset revealed that both methods work well with a moderate or large number of studies and the bivariate binomial model coupled with the multiple imputation outperforms the bivariate normal model with a small number of studies. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A nonlinear dynamical analogue model of geomagnetic activity

NASA Technical Reports Server (NTRS)

Klimas, A. J.; Baker, D. N.; Roberts, D. A.; Fairfield, D. H.; Buechner, J.

1992-01-01

Consideration is given to the solar wind-magnetosphere interaction within the framework of deterministic nonlinear dynamics. An earlier dripping faucet analog model of the low-dimensional solar wind-magnetosphere system is reviewed, and a plasma physical counterpart to that model is constructed. A Faraday loop in the magnetotail is considered, and the relationship of electric potentials on the loop to changes in the magnetic flux threading the loop is developed. This approach leads to a model of geomagnetic activity which is similar to the earlier mechanical model but described in terms of the geometry and plasma contents of the magnetotail. The model is characterized as an elementary time-dependent global convection model. The convection evolves within a magnetotail shape that varies in a prescribed manner in response to the dynamical evolution of the convection. The result is a nonlinear model capable of exhibiting a transition from regular to chaotic loading and unloading. The model's behavior under steady loading and also some elementary forms of time-dependent loading is discussed.

On numerical integration and computer implementation of viscoplastic models

NASA Technical Reports Server (NTRS)

Chang, T. Y.; Chang, J. P.; Thompson, R. L.

1985-01-01

Due to the stringent design requirement for aerospace or nuclear structural components, considerable research interests have been generated on the development of constitutive models for representing the inelastic behavior of metals at elevated temperatures. In particular, a class of unified theories (or viscoplastic constitutive models) have been proposed to simulate material responses such as cyclic plasticity, rate sensitivity, creep deformations, strain hardening or softening, etc. This approach differs from the conventional creep and plasticity theory in that both the creep and plastic deformations are treated as unified time-dependent quantities. Although most of viscoplastic models give better material behavior representation, the associated constitutive differential equations have stiff regimes which present numerical difficulties in time-dependent analysis. In this connection, appropriate solution algorithm must be developed for viscoplastic analysis via finite element method.

Time‐dependent renewal‐model probabilities when date of last earthquake is unknown

USGS Publications Warehouse

Field, Edward H.; Jordan, Thomas H.

2015-01-01

We derive time-dependent, renewal-model earthquake probabilities for the case in which the date of the last event is completely unknown, and compare these with the time-independent Poisson probabilities that are customarily used as an approximation in this situation. For typical parameter values, the renewal-model probabilities exceed Poisson results by more than 10% when the forecast duration exceeds ~20% of the mean recurrence interval. We also derive probabilities for the case in which the last event is further constrained to have occurred before historical record keeping began (the historic open interval), which can only serve to increase earthquake probabilities for typically applied renewal models.We conclude that accounting for the historic open interval can improve long-term earthquake rupture forecasts for California and elsewhere.

A time dependent anatomically detailed model of cardiac conduction

NASA Technical Reports Server (NTRS)

Saxberg, B. E.; Grumbach, M. P.; Cohen, R. J.

1985-01-01

In order to understand the determinants of transitions in cardiac electrical activity from normal patterns to dysrhythmias such as ventricular fibrillation, we are constructing an anatomically and physiologically detailed finite element simulation of myocardial electrical propagation. A healthy human heart embedded in paraffin was sectioned to provide a detailed anatomical substrate for model calculations. The simulation of propagation includes anisotropy in conduction velocity due to fiber orientation as well as gradients in conduction velocities, absolute and relative refractory periods, action potential duration and electrotonic influence of nearest neighbors. The model also includes changes in the behaviour of myocardial tissue as a function of the past local activity. With this model, we can examine the significance of fiber orientation and time dependence of local propagation parameters on dysrhythmogenesis.

Long-range dependence in earthquake-moment release and implications for earthquake occurrence probability.

PubMed

Barani, Simone; Mascandola, Claudia; Riccomagno, Eva; Spallarossa, Daniele; Albarello, Dario; Ferretti, Gabriele; Scafidi, Davide; Augliera, Paolo; Massa, Marco

2018-03-28

Since the beginning of the 1980s, when Mandelbrot observed that earthquakes occur on 'fractal' self-similar sets, many studies have investigated the dynamical mechanisms that lead to self-similarities in the earthquake process. Interpreting seismicity as a self-similar process is undoubtedly convenient to bypass the physical complexities related to the actual process. Self-similar processes are indeed invariant under suitable scaling of space and time. In this study, we show that long-range dependence is an inherent feature of the seismic process, and is universal. Examination of series of cumulative seismic moment both in Italy and worldwide through Hurst's rescaled range analysis shows that seismicity is a memory process with a Hurst exponent H ≈ 0.87. We observe that H is substantially space- and time-invariant, except in cases of catalog incompleteness. This has implications for earthquake forecasting. Hence, we have developed a probability model for earthquake occurrence that allows for long-range dependence in the seismic process. Unlike the Poisson model, dependent events are allowed. This model can be easily transferred to other disciplines that deal with self-similar processes.

Brownian motion model with stochastic parameters for asset prices

NASA Astrophysics Data System (ADS)

Ching, Soo Huei; Hin, Pooi Ah

2013-09-01

The Brownian motion model may not be a completely realistic model for asset prices because in real asset prices the drift μ and volatility σ may change over time. Presently we consider a model in which the parameter x = (μ,σ) is such that its value x (t + Δt) at a short time Δt ahead of the present time t depends on the value of the asset price at time t + Δt as well as the present parameter value x(t) and m-1 other parameter values before time t via a conditional distribution. The Malaysian stock prices are used to compare the performance of the Brownian motion model with fixed parameter with that of the model with stochastic parameter.

Recent progress in empirical modeling of ion composition in the topside ionosphere

NASA Astrophysics Data System (ADS)

Truhlik, Vladimir; Triskova, Ludmila; Bilitza, Dieter; Kotov, Dmytro; Bogomaz, Oleksandr; Domnin, Igor

2016-07-01

The last deep and prolonged solar minimum revealed shortcomings of existing empirical models, especially of parameter models that depend strongly on solar activity, such as the IRI (International Reference Ionosphere) ion composition model, and that are based on data sets from previous solar cycles. We have improved the TTS-03 ion composition model (Triskova et al., 2003) which is included in IRI since version 2007. The new model called AEIKion-13 employs an improved description of the dependence of ion composition on solar activity. We have also developed new global models of the upper transition height based on large data sets of vertical electron density profiles from ISIS, Alouette and COSMIC. The upper transition height is used as an anchor point for adjustment of the AEIKion-13 ion composition model. Additionally, we show also progress on improvements of the altitudinal dependence of the ion composition in the AEIKion-13 model. Results of the improved model are compared with data from other types of measurements including data from the Atmosphere Explorer C and E and C/NOFS satellites, and the Kharkiv and Arecibo incoherent scatter radars. Possible real time updating of the model by the upper transition height from the real time COSMIC vertical profiles is discussed. Triskova, L.,Truhlik,V., Smilauer, J.,2003. An empirical model of ion composition in the outer ionosphere. Adv. Space Res. 31(3), 653-663.

Estimation of Recurrence of Colorectal Adenomas with Dependent Censoring Using Weighted Logistic Regression

PubMed Central

Hsu, Chiu-Hsieh; Li, Yisheng; Long, Qi; Zhao, Qiuhong; Lance, Peter

2011-01-01

In colorectal polyp prevention trials, estimation of the rate of recurrence of adenomas at the end of the trial may be complicated by dependent censoring, that is, time to follow-up colonoscopy and dropout may be dependent on time to recurrence. Assuming that the auxiliary variables capture the dependence between recurrence and censoring times, we propose to fit two working models with the auxiliary variables as covariates to define risk groups and then extend an existing weighted logistic regression method for independent censoring to each risk group to accommodate potential dependent censoring. In a simulation study, we show that the proposed method results in both a gain in efficiency and reduction in bias for estimating the recurrence rate. We illustrate the methodology by analyzing a recurrent adenoma dataset from a colorectal polyp prevention trial. PMID:22065985