Impact of the time scale of model sensitivity response on coupled model parameter estimation

NASA Astrophysics Data System (ADS)

Liu, Chang; Zhang, Shaoqing; Li, Shan; Liu, Zhengyu

2017-11-01

That a model has sensitivity responses to parameter uncertainties is a key concept in implementing model parameter estimation using filtering theory and methodology. Depending on the nature of associated physics and characteristic variability of the fluid in a coupled system, the response time scales of a model to parameters can be different, from hourly to decadal. Unlike state estimation, where the update frequency is usually linked with observational frequency, the update frequency for parameter estimation must be associated with the time scale of the model sensitivity response to the parameter being estimated. Here, with a simple coupled model, the impact of model sensitivity response time scales on coupled model parameter estimation is studied. The model includes characteristic synoptic to decadal scales by coupling a long-term varying deep ocean with a slow-varying upper ocean forced by a chaotic atmosphere. Results show that, using the update frequency determined by the model sensitivity response time scale, both the reliability and quality of parameter estimation can be improved significantly, and thus the estimated parameters make the model more consistent with the observation. These simple model results provide a guideline for when real observations are used to optimize the parameters in a coupled general circulation model for improving climate analysis and prediction initialization.

Temperature Responses to Spectral Solar Variability on Decadal Time Scales

NASA Technical Reports Server (NTRS)

Cahalan, Robert F.; Wen, Guoyong; Harder, Jerald W.; Pilewskie, Peter

2010-01-01

Two scenarios of spectral solar forcing, namely Spectral Irradiance Monitor (SIM)-based out-of-phase variations and conventional in-phase variations, are input to a time-dependent radiative-convective model (RCM), and to the GISS modelE. Both scenarios and models give maximum temperature responses in the upper stratosphere, decreasing to the surface. Upper stratospheric peak-to-peak responses to out-of-phase forcing are approx.0.6 K and approx.0.9 K in RCM and modelE, approx.5 times larger than responses to in-phase forcing. Stratospheric responses are in-phase with TSI and UV variations, and resemble HALOE observed 11-year temperature variations. For in-phase forcing, ocean mixed layer response lags surface air response by approx.2 years, and is approx.0.06 K compared to approx.0.14 K for atmosphere. For out-of-phase forcing, lags are similar, but surface responses are significantly smaller. For both scenarios, modelE surface responses are less than 0.1 K in the tropics, and display similar patterns over oceanic regions, but complex responses over land.

The determinants of response time in a repeated constant-sum game: A robust Bayesian hierarchical dual-process model.

PubMed

Spiliopoulos, Leonidas

2018-03-01

The investigation of response time and behavior has a long tradition in cognitive psychology, particularly for non-strategic decision-making. Recently, experimental economists have also studied response time in strategic interactions, but with an emphasis on either one-shot games or repeated social-dilemmas. I investigate the determinants of response time in a repeated (pure-conflict) game, admitting a unique mixed strategy Nash equilibrium, with fixed partner matching. Response times depend upon the interaction of two decision models embedded in a dual-process framework (Achtziger and Alós-Ferrer, 2014; Alós-Ferrer, 2016). The first decision model is the commonly used win-stay/lose-shift heuristic and the second the pattern-detecting reinforcement learning model in Spiliopoulos (2013b). The former is less complex and can be executed more quickly than the latter. As predicted, conflict between these two models (i.e., each one recommending a different course of action) led to longer response times than cases without conflict. The dual-process framework makes other qualitative response time predictions arising from the interaction between the existence (or not) of conflict and which one of the two decision models the chosen action is consistent with-these were broadly verified by the data. Other determinants of RT were hypothesized on the basis of existing theory and tested empirically. Response times were strongly dependent on the actions chosen by both players in the previous rounds and the resulting outcomes. Specifically, response time was shortest after a win in the previous round where the maximum possible payoff was obtained; response time after losses was significantly longer. Strongly auto-correlated behavior (regardless of its sign) was also associated with longer response times. I conclude that, similar to other tasks, there is a strong coupling in repeated games between behavior and RT, which can be exploited to further our understanding of decision making. Copyright © 2017 Elsevier B.V. All rights reserved.

A simple two-stage model predicts response time distributions.

PubMed

Carpenter, R H S; Reddi, B A J; Anderson, A J

2009-08-15

The neural mechanisms underlying reaction times have previously been modelled in two distinct ways. When stimuli are hard to detect, response time tends to follow a random-walk model that integrates noisy sensory signals. But studies investigating the influence of higher-level factors such as prior probability and response urgency typically use highly detectable targets, and response times then usually correspond to a linear rise-to-threshold mechanism. Here we show that a model incorporating both types of element in series - a detector integrating noisy afferent signals, followed by a linear rise-to-threshold performing decision - successfully predicts not only mean response times but, much more stringently, the observed distribution of these times and the rate of decision errors over a wide range of stimulus detectability. By reconciling what previously may have seemed to be conflicting theories, we are now closer to having a complete description of reaction time and the decision processes that underlie it.

A Semiparametric Model for Jointly Analyzing Response Times and Accuracy in Computerized Testing

ERIC Educational Resources Information Center

Wang, Chun; Fan, Zhewen; Chang, Hua-Hua; Douglas, Jeffrey A.

2013-01-01

The item response times (RTs) collected from computerized testing represent an underutilized type of information about items and examinees. In addition to knowing the examinees' responses to each item, we can investigate the amount of time examinees spend on each item. Current models for RTs mainly focus on parametric models, which have the…

Structural Equation Model Approach to the Use of Response Times for Improving Estimation in Item Response Models

ERIC Educational Resources Information Center

Sen, Rohini

2012-01-01

In the last five decades, research on the uses of response time has extended into the field of psychometrics (Schnikpe & Scrams, 1999; van der Linden, 2006; van der Linden, 2007), where interest has centered around the usefulness of response time information in item calibration and person measurement within an item response theory. framework.…

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…

Reducing ambulance response times using discrete event simulation.

PubMed

Wei Lam, Sean Shao; Zhang, Zhong Cheng; Oh, Hong Choon; Ng, Yih Ying; Wah, Win; Hock Ong, Marcus Eng

2014-01-01

The objectives of this study are to develop a discrete-event simulation (DES) model for the Singapore Emergency Medical Services (EMS), and to demonstrate the utility of this DES model for the evaluation of different policy alternatives to improve ambulance response times. A DES model was developed based on retrospective emergency call data over a continuous 6-month period in Singapore. The main outcome measure is the distribution of response times. The secondary outcome measure is ambulance utilization levels based on unit hour utilization (UHU) ratios. The DES model was used to evaluate different policy options in order to improve the response times, while maintaining reasonable fleet utilization. Three policy alternatives looking at the reallocation of ambulances, the addition of new ambulances, and alternative dispatch policies were evaluated. Modifications of dispatch policy combined with the reallocation of existing ambulances were able to achieve response time performance equivalent to that of adding 10 ambulances. The median (90th percentile) response time was 7.08 minutes (12.69 minutes). Overall, this combined strategy managed to narrow the gap between the ideal and existing response time distribution by 11-13%. Furthermore, the median UHU under this combined strategy was 0.324 with an interquartile range (IQR) of 0.047 versus a median utilization of 0.285 (IQR of 0.051) resulting from the introduction of additional ambulances. Response times were shown to be improved via a more effective reallocation of ambulances and dispatch policy. More importantly, the response time improvements were achieved without a reduction in the utilization levels and additional costs associated with the addition of ambulances. We demonstrated the effective use of DES as a versatile platform to model the dynamic system complexities of Singapore's national EMS systems for the evaluation of operational strategies to improve ambulance response times.

Person-Fit Statistics for Joint Models for Accuracy and Speed

ERIC Educational Resources Information Center

Fox, Jean-Paul; Marianti, Sukaesi

2017-01-01

Response accuracy and response time data can be analyzed with a joint model to measure ability and speed of working, while accounting for relationships between item and person characteristics. In this study, person-fit statistics are proposed for joint models to detect aberrant response accuracy and/or response time patterns. The person-fit tests…

Grade of Membership Response Time Model for Detecting Guessing Behaviors

ERIC Educational Resources Information Center

Pokropek, Artur

2016-01-01

A response model that is able to detect guessing behaviors and produce unbiased estimates in low-stake conditions using timing information is proposed. The model is a special case of the grade of membership model in which responses are modeled as partial members of a class that is affected by motivation and a class that responds only according to…

A Bivariate Generalized Linear Item Response Theory Modeling Framework to the Analysis of Responses and Response Times.

PubMed

Molenaar, Dylan; Tuerlinckx, Francis; van der Maas, Han L J

2015-01-01

A generalized linear modeling framework to the analysis of responses and response times is outlined. In this framework, referred to as bivariate generalized linear item response theory (B-GLIRT), separate generalized linear measurement models are specified for the responses and the response times that are subsequently linked by cross-relations. The cross-relations can take various forms. Here, we focus on cross-relations with a linear or interaction term for ability tests, and cross-relations with a curvilinear term for personality tests. In addition, we discuss how popular existing models from the psychometric literature are special cases in the B-GLIRT framework depending on restrictions in the cross-relation. This allows us to compare existing models conceptually and empirically. We discuss various extensions of the traditional models motivated by practical problems. We also illustrate the applicability of our approach using various real data examples, including data on personality and cognitive ability.

Sensitivity analysis of machine-learning models of hydrologic time series

NASA Astrophysics Data System (ADS)

O'Reilly, A. M.

2017-12-01

Sensitivity analysis traditionally has been applied to assessing model response to perturbations in model parameters, where the parameters are those model input variables adjusted during calibration. Unlike physics-based models where parameters represent real phenomena, the equivalent of parameters for machine-learning models are simply mathematical "knobs" that are automatically adjusted during training/testing/verification procedures. Thus the challenge of extracting knowledge of hydrologic system functionality from machine-learning models lies in their very nature, leading to the label "black box." Sensitivity analysis of the forcing-response behavior of machine-learning models, however, can provide understanding of how the physical phenomena represented by model inputs affect the physical phenomena represented by model outputs.As part of a previous study, hybrid spectral-decomposition artificial neural network (ANN) models were developed to simulate the observed behavior of hydrologic response contained in multidecadal datasets of lake water level, groundwater level, and spring flow. Model inputs used moving window averages (MWA) to represent various frequencies and frequency-band components of time series of rainfall and groundwater use. Using these forcing time series, the MWA-ANN models were trained to predict time series of lake water level, groundwater level, and spring flow at 51 sites in central Florida, USA. A time series of sensitivities for each MWA-ANN model was produced by perturbing forcing time-series and computing the change in response time-series per unit change in perturbation. Variations in forcing-response sensitivities are evident between types (lake, groundwater level, or spring), spatially (among sites of the same type), and temporally. Two generally common characteristics among sites are more uniform sensitivities to rainfall over time and notable increases in sensitivities to groundwater usage during significant drought periods.

Crossfit analysis: a novel method to characterize the dynamics of induced plant responses.

PubMed

Jansen, Jeroen J; van Dam, Nicole M; Hoefsloot, Huub C J; Smilde, Age K

2009-12-16

Many plant species show induced responses that protect them against exogenous attacks. These responses involve the production of many different bioactive compounds. Plant species belonging to the Brassicaceae family produce defensive glucosinolates, which may greatly influence their favorable nutritional properties for humans. Each responding compound may have its own dynamic profile and metabolic relationships with other compounds. The chemical background of the induced response is therefore highly complex and may therefore not reveal all the properties of the response in any single model. This study therefore aims to describe the dynamics of the glucosinolate response, measured at three time points after induction in a feral Brassica, by a three-faceted approach, based on Principal Component Analysis. First the large-scale aspects of the response are described in a 'global model' and then each time-point in the experiment is individually described in 'local models' that focus on phenomena that occur at specific moments in time. Although each local model describes the variation among the plants at one time-point as well as possible, the response dynamics are lost. Therefore a novel method called the 'Crossfit' is described that links the local models of different time-points to each other. Each element of the described analysis approach reveals different aspects of the response. The crossfit shows that smaller dynamic changes may occur in the response that are overlooked by global models, as illustrated by the analysis of a metabolic profiling dataset of the same samples.

Crossfit analysis: a novel method to characterize the dynamics of induced plant responses

PubMed Central

2009-01-01

Background Many plant species show induced responses that protect them against exogenous attacks. These responses involve the production of many different bioactive compounds. Plant species belonging to the Brassicaceae family produce defensive glucosinolates, which may greatly influence their favorable nutritional properties for humans. Each responding compound may have its own dynamic profile and metabolic relationships with other compounds. The chemical background of the induced response is therefore highly complex and may therefore not reveal all the properties of the response in any single model. Results This study therefore aims to describe the dynamics of the glucosinolate response, measured at three time points after induction in a feral Brassica, by a three-faceted approach, based on Principal Component Analysis. First the large-scale aspects of the response are described in a 'global model' and then each time-point in the experiment is individually described in 'local models' that focus on phenomena that occur at specific moments in time. Although each local model describes the variation among the plants at one time-point as well as possible, the response dynamics are lost. Therefore a novel method called the 'Crossfit' is described that links the local models of different time-points to each other. Conclusions Each element of the described analysis approach reveals different aspects of the response. The crossfit shows that smaller dynamic changes may occur in the response that are overlooked by global models, as illustrated by the analysis of a metabolic profiling dataset of the same samples. PMID:20015363

Modeling Information Accumulation in Psychological Tests Using Item Response Times

ERIC Educational Resources Information Center

Ranger, Jochen; Kuhn, Jörg-Tobias

2015-01-01

In this article, a latent trait model is proposed for the response times in psychological tests. The latent trait model is based on the linear transformation model and subsumes popular models from survival analysis, like the proportional hazards model and the proportional odds model. Core of the model is the assumption that an unspecified monotone…

A bivariate model for analyzing recurrent multi-type automobile failures

NASA Astrophysics Data System (ADS)

Sunethra, A. A.; Sooriyarachchi, M. R.

2017-09-01

The failure mechanism in an automobile can be defined as a system of multi-type recurrent failures where failures can occur due to various multi-type failure modes and these failures are repetitive such that more than one failure can occur from each failure mode. In analysing such automobile failures, both the time and type of the failure serve as response variables. However, these two response variables are highly correlated with each other since the timing of failures has an association with the mode of the failure. When there are more than one correlated response variables, the fitting of a multivariate model is more preferable than separate univariate models. Therefore, a bivariate model of time and type of failure becomes appealing for such automobile failure data. When there are multiple failure observations pertaining to a single automobile, such data cannot be treated as independent data because failure instances of a single automobile are correlated with each other while failures among different automobiles can be treated as independent. Therefore, this study proposes a bivariate model consisting time and type of failure as responses adjusted for correlated data. The proposed model was formulated following the approaches of shared parameter models and random effects models for joining the responses and for representing the correlated data respectively. The proposed model is applied to a sample of automobile failures with three types of failure modes and up to five failure recurrences. The parametric distributions that were suitable for the two responses of time to failure and type of failure were Weibull distribution and multinomial distribution respectively. The proposed bivariate model was programmed in SAS Procedure Proc NLMIXED by user programming appropriate likelihood functions. The performance of the bivariate model was compared with separate univariate models fitted for the two responses and it was identified that better performance is secured by the bivariate model. The proposed model can be used to determine the time and type of failure that would occur in the automobiles considered here.

Controls on terrestrial carbon feedbacks by productivity versus turnover in the CMIP5 Earth System Models

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

Koven, C. D.; Chambers, J. Q.; Georgiou, K.

To better understand sources of uncertainty in projections of terrestrial carbon cycle feedbacks, we present an approach to separate the controls on modeled carbon changes. We separate carbon changes into four categories using a linearized, equilibrium approach: those arising from changed inputs (productivity-driven changes), and outputs (turnover-driven changes), of both the live and dead carbon pools. Using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations for five models, we find that changes to the live pools are primarily explained by productivity-driven changes, with only one model showing large compensating changes to live carbon turnover times. For dead carbon pools, themore » situation is more complex as all models predict a large reduction in turnover times in response to increases in productivity. This response arises from the common representation of a broad spectrum of decomposition turnover times via a multi-pool approach, in which flux-weighted turnover times are faster than mass-weighted turnover times. This leads to a shift in the distribution of carbon among dead pools in response to changes in inputs, and therefore a transient but long-lived reduction in turnover times. Since this behavior, a reduction in inferred turnover times resulting from an increase in inputs, is superficially similar to priming processes, but occurring without the mechanisms responsible for priming, we call the phenomenon "false priming", and show that it masks much of the intrinsic changes to dead carbon turnover times as a result of changing climate. These patterns hold across the fully coupled, biogeochemically coupled, and radiatively coupled 1 % yr −1 increasing CO 2 experiments. We disaggregate inter-model uncertainty in the globally integrated equilibrium carbon responses to initial turnover times, initial productivity, fractional changes in turnover, and fractional changes in productivity. For both the live and dead carbon pools, inter-model spread in carbon changes arising from initial conditions is dominated by model disagreement on turnover times, whereas inter-model spread in carbon changes from fractional changes to these terms is dominated by model disagreement on changes to productivity in response to both warming and CO 2 fertilization. However, the lack of changing turnover time control on carbon responses, for both live and dead carbon pools, in response to the imposed forcings may arise from a common lack of process representation behind changing turnover times (e.g., allocation and mortality for live carbon; permafrost, microbial dynamics, and mineral stabilization for dead carbon), rather than a true estimate of the importance of these processes.« less

Controls on terrestrial carbon feedbacks by productivity versus turnover in the CMIP5 Earth System Models

DOE PAGES

Koven, C. D.; Chambers, J. Q.; Georgiou, K.; ...

2015-09-07

To better understand sources of uncertainty in projections of terrestrial carbon cycle feedbacks, we present an approach to separate the controls on modeled carbon changes. We separate carbon changes into four categories using a linearized, equilibrium approach: those arising from changed inputs (productivity-driven changes), and outputs (turnover-driven changes), of both the live and dead carbon pools. Using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations for five models, we find that changes to the live pools are primarily explained by productivity-driven changes, with only one model showing large compensating changes to live carbon turnover times. For dead carbon pools, themore » situation is more complex as all models predict a large reduction in turnover times in response to increases in productivity. This response arises from the common representation of a broad spectrum of decomposition turnover times via a multi-pool approach, in which flux-weighted turnover times are faster than mass-weighted turnover times. This leads to a shift in the distribution of carbon among dead pools in response to changes in inputs, and therefore a transient but long-lived reduction in turnover times. Since this behavior, a reduction in inferred turnover times resulting from an increase in inputs, is superficially similar to priming processes, but occurring without the mechanisms responsible for priming, we call the phenomenon "false priming", and show that it masks much of the intrinsic changes to dead carbon turnover times as a result of changing climate. These patterns hold across the fully coupled, biogeochemically coupled, and radiatively coupled 1 % yr −1 increasing CO 2 experiments. We disaggregate inter-model uncertainty in the globally integrated equilibrium carbon responses to initial turnover times, initial productivity, fractional changes in turnover, and fractional changes in productivity. For both the live and dead carbon pools, inter-model spread in carbon changes arising from initial conditions is dominated by model disagreement on turnover times, whereas inter-model spread in carbon changes from fractional changes to these terms is dominated by model disagreement on changes to productivity in response to both warming and CO 2 fertilization. However, the lack of changing turnover time control on carbon responses, for both live and dead carbon pools, in response to the imposed forcings may arise from a common lack of process representation behind changing turnover times (e.g., allocation and mortality for live carbon; permafrost, microbial dynamics, and mineral stabilization for dead carbon), rather than a true estimate of the importance of these processes.« less

Development of a nonlinear model for the prediction of response times of glucose affinity sensors using concanavalin A and dextran and the development of a differential osmotic glucose affinity sensor

NASA Astrophysics Data System (ADS)

Reis, Louis G.

With the increasing prevalence of diabetes in the United States and worldwide, blood glucose monitoring must be accurate and reliable. Current enzymatic sensors have numerous disadvantages that make them unreliable and unfavorable among patients. Recent research in glucose affinity sensors correct some of the problems that enzymatic sensors experience. Dextran and concanavalin A are two of the more common components used in glucose affinity sensors. When these sensors were first explored, a model was derived to predict the response time of a glucose affinity sensor using concanavalin A and dextran. However, the model assumed the system was linear and fell short of calculating times representative of the response times determined through experimental tests with the sensors. In this work, a new model that uses the Stokes-Einstein Equation to demonstrate the nonlinear behavior of the glucose affinity assay was developed to predict the response times of similar glucose affinity sensors. In addition to the device tested by the original linear model, additional devices were identified and tested with the proposed model. The nonlinear model was designed to accommodate the many different variations between systems. The proposed model was able to accurately calculate response times for sensors using the concanavalin A-dextran affinity assay with respect to the experimentally reported times by the independent research groups. Parameter studies using the nonlinear model were able to identify possible setbacks that could compromise the response of thesystem. Specifically, the model showed that the improper use of asymmetrical membranes could increase the response time by as little as 20% or more as the device is miniaturized. The model also demonstrated that systems using the concanavalin Adextran assay would experience higher response times in the hypoglycemic range. This work attempted to replicate and improve an osmotic glucose affinity sensor. The system was designed to negate additional effects that could cause artifacts or irregular readings such as external osmotic differences and external pressure differences. However, the experimental setup and execution faced numerous setbacks that highlighted the additional difficulty that sensors using asymmetrical ceramic membranes and the concanavalin A-dextran affinity assay may experience.

The Behavioral Economics of Choice and Interval Timing

ERIC Educational Resources Information Center

Jozefowiez, J.; Staddon, J. E. R.; Cerutti, D. T.

2009-01-01

The authors propose a simple behavioral economic model (BEM) describing how reinforcement and interval timing interact. The model assumes a Weber-law-compliant logarithmic representation of time. Associated with each represented time value are the payoffs that have been obtained for each possible response. At a given real time, the response with…

A Study of Bayesian Estimation and Comparison of Response Time Models in Item Response Theory

ERIC Educational Resources Information Center

Suh, Hongwook

2010-01-01

Response time has been regarded as an important source for investigating the relationship between human performance and response speed. It is important to examine the relationship between response time and item characteristics, especially in the perspective of the relationship between response time and various factors that affect examinee's…

Modeling Climate Responses to Spectral Solar Forcing on Centennial and Decadal Time Scales

NASA Technical Reports Server (NTRS)

Wen, G.; Cahalan, R.; Rind, D.; Jonas, J.; Pilewskie, P.; Harder, J.

2012-01-01

We report a series of experiments to explore clima responses to two types of solar spectral forcing on decadal and centennial time scales - one based on prior reconstructions, and another implied by recent observations from the SORCE (Solar Radiation and Climate Experiment) SIM (Spectral 1rradiance Monitor). We apply these forcings to the Goddard Institute for Space Studies (GISS) Global/Middle Atmosphere Model (GCMAM). that couples atmosphere with ocean, and has a model top near the mesopause, allowing us to examine the full response to the two solar forcing scenarios. We show different climate responses to the two solar forCing scenarios on decadal time scales and also trends on centennial time scales. Differences between solar maximum and solar minimum conditions are highlighted, including impacts of the time lagged reSponse of the lower atmosphere and ocean. This contrasts with studies that assume separate equilibrium conditions at solar maximum and minimum. We discuss model feedback mechanisms involved in the solar forced climate variations.

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

Using Response Times to Assess Learning Progress: A Joint Model for Responses and Response Times

ERIC Educational Resources Information Center

Wang, Shiyu; Zhang, Susu; Douglas, Jeff; Culpepper, Steven

2018-01-01

Analyzing students' growth remains an important topic in educational research. Most recently, Diagnostic Classification Models (DCMs) have been used to track skill acquisition in a longitudinal fashion, with the purpose to provide an estimate of students' learning trajectories in terms of the change of fine-grained skills overtime. Response time…

Grid Modeling Tools | Grid Modernization | NREL

Science.gov Websites

integrates primary frequency response (turbine governor control) with secondary frequency response (automatic generation control). It simulates the power system dynamic response in full time spectrum with variable time control model places special emphasis on electric power systems with high penetrations of renewable

An Immuno-epidemiological Model of Paratuberculosis

NASA Astrophysics Data System (ADS)

Martcheva, M.

2011-11-01

The primary objective of this article is to introduce an immuno-epidemiological model of paratuberculosis (Johne's disease). To develop the immuno-epidemiological model, we first develop an immunological model and an epidemiological model. Then, we link the two models through time-since-infection structure and parameters of the epidemiological model. We use the nested approach to compose the immuno-epidemiological model. Our immunological model captures the switch between the T-cell immune response and the antibody response in Johne's disease. The epidemiological model is a time-since-infection model and captures the variability of transmission rate and the vertical transmission of the disease. We compute the immune-response-dependent epidemiological reproduction number. Our immuno-epidemiological model can be used for investigation of the impact of the immune response on the epidemiology of Johne's disease.

Time-dependent dose-response relation for absence of vaginal elasticity after gynecological radiation therapy.

PubMed

Alevronta, Eleftheria; Åvall-Lundqvist, Elisabeth; Al-Abany, Massoud; Nyberg, Tommy; Lind, Helena; Waldenström, Ann-Charlotte; Olsson, Caroline; Dunberger, Gail; Bergmark, Karin; Steineck, Gunnar; Lind, Bengt K

2016-09-01

To investigate the dose-response relation between the dose to the vagina and the patient-reported symptom 'absence of vaginal elasticity' and how time to follow-up influences this relation. The study included 78 long-term gynecological cancer survivors treated between 1991 and 2003 with external beam radiation therapy. Of those, 24 experienced absence of vaginal elasticity. A normal tissue complication model is introduced that takes into account the influence of time to follow-up on the dose-response relation and the patient's age. The best estimates of the dose-response parameters were calculated using Probit, Probit-Relative Seriality (RS) and Probit-time models. Log likelihood (LL) values and the Akaike Information Criterion (AIC) were used to evaluate the model fit. The dose-response parameters for 'absence of vaginal elasticity' according to the Probit and Probit-time models with the 68% Confidence Intervals (CI) were: LL=-39.8, D 50 =49.7 (47.2-52.4) Gy, γ 50 =1.40 (1.12-1.70) and LL=-37.4, D 50 =46.9 (43.5-50.9) Gy, γ 50 =1.81 (1.17-2.51) respectively. The proposed model, which describes the influence of time to follow-up on the dose-response relation, fits our data best. Our data indicate that the steepness of the dose-response curve of the dose to the vagina and the symptom 'absence of vaginal elasticity' increases with time to follow-up, while D 50 decreases. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

A sequential sampling account of response bias and speed-accuracy tradeoffs in a conflict detection task.

PubMed

Vuckovic, Anita; Kwantes, Peter J; Humphreys, Michael; Neal, Andrew

2014-03-01

Signal Detection Theory (SDT; Green & Swets, 1966) is a popular tool for understanding decision making. However, it does not account for the time taken to make a decision, nor why response bias might change over time. Sequential sampling models provide a way of accounting for speed-accuracy trade-offs and response bias shifts. In this study, we test the validity of a sequential sampling model of conflict detection in a simulated air traffic control task by assessing whether two of its key parameters respond to experimental manipulations in a theoretically consistent way. Through experimental instructions, we manipulated participants' response bias and the relative speed or accuracy of their responses. The sequential sampling model was able to replicate the trends in the conflict responses as well as response time across all conditions. Consistent with our predictions, manipulating response bias was associated primarily with changes in the model's Criterion parameter, whereas manipulating speed-accuracy instructions was associated with changes in the Threshold parameter. The success of the model in replicating the human data suggests we can use the parameters of the model to gain an insight into the underlying response bias and speed-accuracy preferences common to dynamic decision-making tasks. © 2013 American Psychological Association

Cognitive diagnosis modelling incorporating item response times.

PubMed

Zhan, Peida; Jiao, Hong; Liao, Dandan

2018-05-01

To provide more refined diagnostic feedback with collateral information in item response times (RTs), this study proposed joint modelling of attributes and response speed using item responses and RTs simultaneously for cognitive diagnosis. For illustration, an extended deterministic input, noisy 'and' gate (DINA) model was proposed for joint modelling of responses and RTs. Model parameter estimation was explored using the Bayesian Markov chain Monte Carlo (MCMC) method. The PISA 2012 computer-based mathematics data were analysed first. These real data estimates were treated as true values in a subsequent simulation study. A follow-up simulation study with ideal testing conditions was conducted as well to further evaluate model parameter recovery. The results indicated that model parameters could be well recovered using the MCMC approach. Further, incorporating RTs into the DINA model would improve attribute and profile correct classification rates and result in more accurate and precise estimation of the model parameters. © 2017 The British Psychological Society.

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

Logical-Rule Models of Classification Response Times: A Synthesis of Mental-Architecture, Random-Walk, and Decision-Bound Approaches

ERIC Educational Resources Information Center

Fific, Mario; Little, Daniel R.; Nosofsky, Robert M.

2010-01-01

We formalize and provide tests of a set of logical-rule models for predicting perceptual classification response times (RTs) and choice probabilities. The models are developed by synthesizing mental-architecture, random-walk, and decision-bound approaches. According to the models, people make independent decisions about the locations of stimuli…

Evaluating Cognitive Theory: A Joint Modeling Approach Using Responses and Response Times

ERIC Educational Resources Information Center

Klein Entink, Rinke H.; Kuhn, Jorg-Tobias; Hornke, Lutz F.; Fox, Jean-Paul

2009-01-01

In current psychological research, the analysis of data from computer-based assessments or experiments is often confined to accuracy scores. Response times, although being an important source of additional information, are either neglected or analyzed separately. In this article, a new model is developed that allows the simultaneous analysis of…

Response-Time Tests of Logical-Rule Models of Categorization

ERIC Educational Resources Information Center

Little, Daniel R.; Nosofsky, Robert M.; Denton, Stephen E.

2011-01-01

A recent resurgence in logical-rule theories of categorization has motivated the development of a class of models that predict not only choice probabilities but also categorization response times (RTs; Fific, Little, & Nosofsky, 2010). The new models combine mental-architecture and random-walk approaches within an integrated framework and…

Simulating Silicon Photomultiplier Response to Scintillation Light

PubMed Central

Jha, Abhinav K.; van Dam, Herman T.; Kupinski, Matthew A.; Clarkson, Eric

2015-01-01

The response of a Silicon Photomultiplier (SiPM) to optical signals is affected by many factors including photon-detection efficiency, recovery time, gain, optical crosstalk, afterpulsing, dark count, and detector dead time. Many of these parameters vary with overvoltage and temperature. When used to detect scintillation light, there is a complicated non-linear relationship between the incident light and the response of the SiPM. In this paper, we propose a combined discrete-time discrete-event Monte Carlo (MC) model to simulate SiPM response to scintillation light pulses. Our MC model accounts for all relevant aspects of the SiPM response, some of which were not accounted for in the previous models. We also derive and validate analytic expressions for the single-photoelectron response of the SiPM and the voltage drop across the quenching resistance in the SiPM microcell. These analytic expressions consider the effect of all the circuit elements in the SiPM and accurately simulate the time-variation in overvoltage across the microcells of the SiPM. Consequently, our MC model is able to incorporate the variation of the different SiPM parameters with varying overvoltage. The MC model is compared with measurements on SiPM-based scintillation detectors and with some cases for which the response is known a priori. The model is also used to study the variation in SiPM behavior with SiPM-circuit parameter variations and to predict the response of a SiPM-based detector to various scintillators. PMID:26236040

Large-scale geomorphology: Classical concepts reconciled and integrated with contemporary ideas via a surface processes model

NASA Astrophysics Data System (ADS)

Kooi, Henk; Beaumont, Christopher

1996-02-01

Linear systems analysis is used to investigate the response of a surface processes model (SPM) to tectonic forcing. The SPM calculates subcontinental scale denudational landscape evolution on geological timescales (1 to hundreds of million years) as the result of simultaneous hillslope transport, modeled by diffusion, and fluvial transport, modeled by advection and reaction. The tectonically forced SPM accommodates the large-scale behavior envisaged in classical and contemporary conceptual geomorphic models and provides a framework for their integration and unification. The following three model scales are considered: micro-, meso-, and macroscale. The concepts of dynamic equilibrium and grade are quantified at the microscale for segments of uniform gradient subject to tectonic uplift. At the larger meso- and macroscales (which represent individual interfluves and landscapes including a number of drainage basins, respectively) the system response to tectonic forcing is linear for uplift geometries that are symmetric with respect to baselevel and which impose a fully integrated drainage to baselevel. For these linear models the response time and the transfer function as a function of scale characterize the model behavior. Numerical experiments show that the styles of landscape evolution depend critically on the timescales of the tectonic processes in relation to the response time of the landscape. When tectonic timescales are much longer than the landscape response time, the resulting dynamic equilibrium landscapes correspond to those envisaged by Hack (1960). When tectonic timescales are of the same order as the landscape response time and when tectonic variations take the form of pulses (much shorter than the response time), evolving landscapes conform to the Penck type (1972) and to the Davis (1889, 1899) and King (1953, 1962) type frameworks, respectively. The behavior of the SPM highlights the importance of phase shifts or delays of the landform response and sediment yield in relation to the tectonic forcing. Finally, nonlinear behavior resulting from more general uplift geometries is discussed. A number of model experiments illustrate the importance of "fundamental form," which is an expression of the conformity of antecedent topography with the current tectonic regime. Lack of conformity leads to models that exhibit internal thresholds and a complex response.

Spatial analysis of ambulance response times related to prehospital cardiac arrests in the city-state of Singapore.

PubMed

Earnest, Arul; Hock Ong, Marcus Eng; Shahidah, Nur; Min Ng, Wen; Foo, Chuanyang; Nott, David John

2012-01-01

The main objective of this study was to establish the spatial variation in ambulance response times for out-of-hospital cardiac arrests (OHCAs) in the city-state of Singapore. The secondary objective involved studying the relationships between various covariates, such as traffic condition and time and day of collapse, and ambulance response times. The study design was observational and ecological in nature. Data on OHCAs were collected from a nationally representative database for the period October 2001 to October 2004. We used the conditional autoregressive (CAR) model to analyze the data. Within the Bayesian framework of analysis, we used a Weibull regression model that took into account spatial random effects. The regression model was used to study the independent effects of each covariate. Our results showed that there was spatial heterogeneity in the ambulance response times in Singapore. Generally, areas in the far outskirts (suburbs), such as Boon Lay (in the west) and Sembawang (in the north), fared badly in terms of ambulance response times. This improved when adjusted for key covariates, including distance from the nearest fire station. Ambulance response time was also associated with better traffic conditions, weekend OHCAs, distance from the nearest fire station, and OHCAs occurring during nonpeak driving hours. For instance, the hazard ratio for good ambulance response time was 2.35 (95% credible interval [CI] 1.97-2.81) when traffic conditions were light and 1.72 (95% CI 1.51-1.97) when traffic conditions were moderate, as compared with heavy traffic. We found a clear spatial gradient for ambulance response times, with far-outlying areas' exhibiting poorer response times. Our study highlights the utility of this novel approach, which may be helpful for planning emergency medical services and public emergency responses.

Scalable and responsive event processing in the cloud

PubMed Central

Suresh, Visalakshmi; Ezhilchelvan, Paul; Watson, Paul

2013-01-01

Event processing involves continuous evaluation of queries over streams of events. Response-time optimization is traditionally done over a fixed set of nodes and/or by using metrics measured at query-operator levels. Cloud computing makes it easy to acquire and release computing nodes as required. Leveraging this flexibility, we propose a novel, queueing-theory-based approach for meeting specified response-time targets against fluctuating event arrival rates by drawing only the necessary amount of computing resources from a cloud platform. In the proposed approach, the entire processing engine of a distinct query is modelled as an atomic unit for predicting response times. Several such units hosted on a single node are modelled as a multiple class M/G/1 system. These aspects eliminate intrusive, low-level performance measurements at run-time, and also offer portability and scalability. Using model-based predictions, cloud resources are efficiently used to meet response-time targets. The efficacy of the approach is demonstrated through cloud-based experiments. PMID:23230164

Space-for-Time Substitution Works in Everglades Ecological Forecasting Models

PubMed Central

Banet, Amanda I.; Trexler, Joel C.

2013-01-01

Space-for-time substitution is often used in predictive models because long-term time-series data are not available. Critics of this method suggest factors other than the target driver may affect ecosystem response and could vary spatially, producing misleading results. Monitoring data from the Florida Everglades were used to test whether spatial data can be substituted for temporal data in forecasting models. Spatial models that predicted bluefin killifish (Lucania goodei) population response to a drying event performed comparably and sometimes better than temporal models. Models worked best when results were not extrapolated beyond the range of variation encompassed by the original dataset. These results were compared to other studies to determine whether ecosystem features influence whether space-for-time substitution is feasible. Taken in the context of other studies, these results suggest space-for-time substitution may work best in ecosystems with low beta-diversity, high connectivity between sites, and small lag in organismal response to the driver variable. PMID:24278368

An entropic barriers diffusion theory of decision-making in multiple alternative tasks

PubMed Central

Sigman, Mariano; Cecchi, Guillermo A.

2018-01-01

We present a theory of decision-making in the presence of multiple choices that departs from traditional approaches by explicitly incorporating entropic barriers in a stochastic search process. We analyze response time data from an on-line repository of 15 million blitz chess games, and show that our model fits not just the mean and variance, but the entire response time distribution (over several response-time orders of magnitude) at every stage of the game. We apply the model to show that (a) higher cognitive expertise corresponds to the exploration of more complex solution spaces, and (b) reaction times of users at an on-line buying website can be similarly explained. Our model can be seen as a synergy between diffusion models used to model simple two-choice decision-making and planning agents in complex problem solving. PMID:29499036

A Multivariate Multilevel Approach to the Modeling of Accuracy and Speed of Test Takers

ERIC Educational Resources Information Center

Klein Entink, R. H.; Fox, J. P.; van der Linden, W. J.

2009-01-01

Response times on test items are easily collected in modern computerized testing. When collecting both (binary) responses and (continuous) response times on test items, it is possible to measure the accuracy and speed of test takers. To study the relationships between these two constructs, the model is extended with a multivariate multilevel…

Testing the Race Model Inequality in Redundant Stimuli with Variable Onset Asynchrony

ERIC Educational Resources Information Center

Gondan, Matthias

2009-01-01

In speeded response tasks with redundant signals, parallel processing of the signals is tested by the race model inequality. This inequality states that given a race of two signals, the cumulative distribution of response times for redundant stimuli never exceeds the sum of the cumulative distributions of response times for the single-modality…

Modelling fourier regression for time series data- a case study: modelling inflation in foods sector in Indonesia

NASA Astrophysics Data System (ADS)

Prahutama, Alan; Suparti; Wahyu Utami, Tiani

2018-03-01

Regression analysis is an analysis to model the relationship between response variables and predictor variables. The parametric approach to the regression model is very strict with the assumption, but nonparametric regression model isn’t need assumption of model. Time series data is the data of a variable that is observed based on a certain time, so if the time series data wanted to be modeled by regression, then we should determined the response and predictor variables first. Determination of the response variable in time series is variable in t-th (yt), while the predictor variable is a significant lag. In nonparametric regression modeling, one developing approach is to use the Fourier series approach. One of the advantages of nonparametric regression approach using Fourier series is able to overcome data having trigonometric distribution. In modeling using Fourier series needs parameter of K. To determine the number of K can be used Generalized Cross Validation method. In inflation modeling for the transportation sector, communication and financial services using Fourier series yields an optimal K of 120 parameters with R-square 99%. Whereas if it was modeled by multiple linear regression yield R-square 90%.

Decision-Tree Models of Categorization Response Times, Choice Proportions, and Typicality Judgments

ERIC Educational Resources Information Center

Lafond, Daniel; Lacouture, Yves; Cohen, Andrew L.

2009-01-01

The authors present 3 decision-tree models of categorization adapted from T. Trabasso, H. Rollins, and E. Shaughnessy (1971) and use them to provide a quantitative account of categorization response times, choice proportions, and typicality judgments at the individual-participant level. In Experiment 1, the decision-tree models were fit to…

Separability of Item and Person Parameters in Response Time Models.

ERIC Educational Resources Information Center

Van Breukelen, Gerard J. P.

1997-01-01

Discusses two forms of separability of item and person parameters in the context of response time models. The first is "separate sufficiency," and the second is "ranking independence." For each form a theorem stating sufficient conditions is proved. The two forms are shown to include several cases of models from psychometric…

Aircraft Fault Detection Using Real-Time Frequency Response Estimation

NASA Technical Reports Server (NTRS)

Grauer, Jared A.

2016-01-01

A real-time method for estimating time-varying aircraft frequency responses from input and output measurements was demonstrated. The Bat-4 subscale airplane was used with NASA Langley Research Center's AirSTAR unmanned aerial flight test facility to conduct flight tests and collect data for dynamic modeling. Orthogonal phase-optimized multisine inputs, summed with pilot stick and pedal inputs, were used to excite the responses. The aircraft was tested in its normal configuration and with emulated failures, which included a stuck left ruddervator and an increased command path latency. No prior knowledge of a dynamic model was used or available for the estimation. The longitudinal short period dynamics were investigated in this work. Time-varying frequency responses and stability margins were tracked well using a 20 second sliding window of data, as compared to a post-flight analysis using output error parameter estimation and a low-order equivalent system model. This method could be used in a real-time fault detection system, or for other applications of dynamic modeling such as real-time verification of stability margins during envelope expansion tests.

Patterns of Response Times and Response Choices to Science Questions: The Influence of Relative Processing Time

ERIC Educational Resources Information Center

Heckler, Andrew F.; Scaife, Thomas M.

2015-01-01

We report on five experiments investigating response choices and response times to simple science questions that evoke student "misconceptions," and we construct a simple model to explain the patterns of response choices. Physics students were asked to compare a physical quantity represented by the slope, such as speed, on simple physics…

Functional response and capture timing in an individual-based model: predation by northern squawfish (Ptychocheilus oregonensis) on juvenile salmonids in the Columbia River

USGS Publications Warehouse

Petersen, James H.; DeAngelis, Donald L.

1992-01-01

The behavior of individual northern squawfish (Ptychocheilus oregonensis) preying on juvenile salmonids was modeled to address questions about capture rate and the timing of prey captures (random versus contagious). Prey density, predator weight, prey weight, temperature, and diel feeding pattern were first incorporated into predation equations analogous to Holling Type 2 and Type 3 functional response models. Type 2 and Type 3 equations fit field data from the Columbia River equally well, and both models predicted predation rates on five of seven independent dates. Selecting a functional response type may be complicated by variable predation rates, analytical methods, and assumptions of the model equations. Using the Type 2 functional response, random versus contagious timing of prey capture was tested using two related models. ln the simpler model, salmon captures were assumed to be controlled by a Poisson renewal process; in the second model, several salmon captures were assumed to occur during brief "feeding bouts", modeled with a compound Poisson process. Salmon captures by individual northern squawfish were clustered through time, rather than random, based on comparison of model simulations and field data. The contagious-feeding result suggests that salmonids may be encountered as patches or schools in the river.

Linguistic Models of FO Use, Physiological Models of FO Control, and the Issue of "Mean Response Time."

ERIC Educational Resources Information Center

Herman, Rebecca; Beckman, Mary; Honda, Kiyoshi

1999-01-01

Evaluates "mean response time" (MRT), a method used in previous studies to relate physiological evidence (recordings of electromyographic activity in the cricothyroid and sternohyoid) to acoustic evidence (fundamental frequency). (Author/VWL)

Corrective response times in a coordinated eye-head-arm countermanding task.

PubMed

Tao, Gordon; Khan, Aarlenne Z; Blohm, Gunnar

2018-06-01

Inhibition of motor responses has been described as a race between two competing decision processes of motor initiation and inhibition, which manifest as the reaction time (RT) and the stop signal reaction time (SSRT); in the case where motor initiation wins out over inhibition, an erroneous movement occurs that usually needs to be corrected, leading to corrective response times (CRTs). Here we used a combined eye-head-arm movement countermanding task to investigate the mechanisms governing multiple effector coordination and the timing of corrective responses. We found a high degree of correlation between effector response times for RT, SSRT, and CRT, suggesting that decision processes are strongly dependent across effectors. To gain further insight into the mechanisms underlying CRTs, we tested multiple models to describe the distribution of RTs, SSRTs, and CRTs. The best-ranked model (according to 3 information criteria) extends the LATER race model governing RTs and SSRTs, whereby a second motor initiation process triggers the corrective response (CRT) only after the inhibition process completes in an expedited fashion. Our model suggests that the neural processing underpinning a failed decision has a residual effect on subsequent actions. NEW & NOTEWORTHY Failure to inhibit erroneous movements typically results in corrective movements. For coordinated eye-head-hand movements we show that corrective movements are only initiated after the erroneous movement cancellation signal has reached a decision threshold in an accelerated fashion.

Bounded influence function based inference in joint modelling of ordinal partial linear model and accelerated failure time model.

PubMed

Chakraborty, Arindom

2016-12-01

A common objective in longitudinal studies is to characterize the relationship between a longitudinal response process and a time-to-event data. Ordinal nature of the response and possible missing information on covariates add complications to the joint model. In such circumstances, some influential observations often present in the data may upset the analysis. In this paper, a joint model based on ordinal partial mixed model and an accelerated failure time model is used, to account for the repeated ordered response and time-to-event data, respectively. Here, we propose an influence function-based robust estimation method. Monte Carlo expectation maximization method-based algorithm is used for parameter estimation. A detailed simulation study has been done to evaluate the performance of the proposed method. As an application, a data on muscular dystrophy among children is used. Robust estimates are then compared with classical maximum likelihood estimates. © The Author(s) 2014.

Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions.

PubMed

Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick

2018-01-01

When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. Copyright © 2017 The Authors. Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.

A Response-Time Approach to Comparing Generalized Rational and Take-the-Best Models of Decision Making

ERIC Educational Resources Information Center

Bergert, F. Bryan; Nosofsky, Robert M.

2007-01-01

The authors develop and test generalized versions of take-the-best (TTB) and rational (RAT) models of multiattribute paired-comparison inference. The generalized models make allowances for subjective attribute weighting, probabilistic orders of attribute inspection, and noisy decision making. A key new test involves a response-time (RT)…

Response latencies are alive and well for identifying fakers on a self-report personality inventory: A reconsideration of van Hooft and Born (2012).

PubMed

Holden, Ronald R; Lambert, Christine E

2015-12-01

Van Hooft and Born (Journal of Applied Psychology 97:301-316, 2012) presented data challenging both the correctness of a congruence model of faking on personality test items and the relative merit (i.e., effect size) of response latencies for identifying fakers. We suggest that their analysis of response times was suboptimal, and that it followed neither from a congruence model of faking nor from published protocols on appropriately filtering the noise in personality test item answering times. Using new data and following recommended analytic procedures, we confirmed the relative utility of response times for identifying personality test fakers, and our obtained results, again, reinforce a congruence model of faking.

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.

A generalized linear factor model approach to the hierarchical framework for responses and response times.

PubMed

Molenaar, Dylan; Tuerlinckx, Francis; van der Maas, Han L J

2015-05-01

We show how the hierarchical model for responses and response times as developed by van der Linden (2007), Fox, Klein Entink, and van der Linden (2007), Klein Entink, Fox, and van der Linden (2009), and Glas and van der Linden (2010) can be simplified to a generalized linear factor model with only the mild restriction that there is no hierarchical model at the item side. This result is valuable as it enables all well-developed modelling tools and extensions that come with these methods. We show that the restriction we impose on the hierarchical model does not influence parameter recovery under realistic circumstances. In addition, we present two illustrative real data analyses to demonstrate the practical benefits of our approach. © 2014 The British Psychological Society.

Using perceptual cues for brake response to a lead vehicle: Comparing threshold and accumulator models of visual looming.

PubMed

Xue, Qingwan; Markkula, Gustav; Yan, Xuedong; Merat, Natasha

2018-06-18

Previous studies have shown the effect of a lead vehicle's speed, deceleration rate and headway distance on drivers' brake response times. However, how drivers perceive this information and use it to determine when to apply braking is still not quite clear. To better understand the underlying mechanisms, a driving simulator experiment was performed where each participant experienced nine deceleration scenarios. Previously reported effects of the lead vehicle's speed, deceleration rate and headway distance on brake response time were firstly verified in this paper, using a multilevel model. Then, as an alternative to measures of speed, deceleration rate and distance, two visual looming-based metrics (angular expansion rate θ˙ of the lead vehicle on the driver's retina, and inverse tau τ -1 , the ratio between θ˙ and the optical size θ), considered to be more in line with typical human psycho-perceptual responses, were adopted to quantify situation urgency. These metrics were used in two previously proposed mechanistic models predicting brake onset: either when looming surpasses a threshold, or when the accumulated evidence (looming and other cues) reaches a threshold. Results showed that the looming threshold model did not capture the distribution of brake response time. However, regardless of looming metric, the accumulator models fitted the distribution of brake response times better than the pure threshold models. Accumulator models, including brake lights, provided a better model fit than looming-only versions. For all versions of the mechanistic models, models using τ -1 as the measure of looming fitted better than those using θ˙, indicating that the visual cues drivers used during rear-end collision avoidance may be more close to τ -1 . Copyright © 2018 Elsevier Ltd. All rights reserved.

Individual differences in attention influence perceptual decision making.

PubMed

Nunez, Michael D; Srinivasan, Ramesh; Vandekerckhove, Joachim

2015-01-01

Sequential sampling decision-making models have been successful in accounting for reaction time (RT) and accuracy data in two-alternative forced choice tasks. These models have been used to describe the behavior of populations of participants, and explanatory structures have been proposed to account for between individual variability in model parameters. In this study we show that individual differences in behavior from a novel perceptual decision making task can be attributed to (1) differences in evidence accumulation rates, (2) differences in variability of evidence accumulation within trials, and (3) differences in non-decision times across individuals. Using electroencephalography (EEG), we demonstrate that these differences in cognitive variables, in turn, can be explained by attentional differences as measured by phase-locking of steady-state visual evoked potential (SSVEP) responses to the signal and noise components of the visual stimulus. Parameters of a cognitive model (a diffusion model) were obtained from accuracy and RT distributions and related to phase-locking indices (PLIs) of SSVEPs with a single step in a hierarchical Bayesian framework. Participants who were able to suppress the SSVEP response to visual noise in high frequency bands were able to accumulate correct evidence faster and had shorter non-decision times (preprocessing or motor response times), leading to more accurate responses and faster response times. We show that the combination of cognitive modeling and neural data in a hierarchical Bayesian framework relates physiological processes to the cognitive processes of participants, and that a model with a new (out-of-sample) participant's neural data can predict that participant's behavior more accurately than models without physiological data.

Using a discrete-event simulation to balance ambulance availability and demand in static deployment systems.

PubMed

Wu, Ching-Han; Hwang, Kevin P

2009-12-01

To improve ambulance response time, matching ambulance availability with the emergency demand is crucial. To maintain the standard of 90% of response times within 9 minutes, the authors introduce a discrete-event simulation method to estimate the threshold for expanding the ambulance fleet when demand increases and to find the optimal dispatching strategies when provisional events create temporary decreases in ambulance availability. The simulation model was developed with information from the literature. Although the development was theoretical, the model was validated on the emergency medical services (EMS) system of Tainan City. The data are divided: one part is for model development, and the other for validation. For increasing demand, the effect was modeled on response time when call arrival rates increased. For temporary availability decreases, the authors simulated all possible alternatives of ambulance deployment in accordance with the number of out-of-routine-duty ambulances and the durations of three types of mass gatherings: marathon races (06:00-10:00 hr), rock concerts (18:00-22:00 hr), and New Year's Eve parties (20:00-01:00 hr). Statistical analysis confirmed that the model reasonably represented the actual Tainan EMS system. The response-time standard could not be reached when the incremental ratio of call arrivals exceeded 56%, which is the threshold for the Tainan EMS system to expand its ambulance fleet. When provisional events created temporary availability decreases, the Tainan EMS system could spare at most two ambulances from the standard configuration, except between 20:00 and 01:00, when it could spare three. The model also demonstrated that the current Tainan EMS has two excess ambulances that could be dropped. The authors suggest dispatching strategies to minimize the response times in routine daily emergencies. Strategies of capacity management based on this model improved response times. The more ambulances that are out of routine duty, the better the performance of the optimal strategies that are based on this model.

The matrix exponential in transient structural analysis

NASA Technical Reports Server (NTRS)

Minnetyan, Levon

1987-01-01

The primary usefulness of the presented theory is in the ability to represent the effects of high frequency linear response with accuracy, without requiring very small time steps in the analysis of dynamic response. The matrix exponential contains a series approximation to the dynamic model. However, unlike the usual analysis procedure which truncates the high frequency response, the approximation in the exponential matrix solution is in the time domain. By truncating the series solution to the matrix exponential short, the solution is made inaccurate after a certain time. Yet, up to that time the solution is extremely accurate, including all high frequency effects. By taking finite time increments, the exponential matrix solution can compute the response very accurately. Use of the exponential matrix in structural dynamics is demonstrated by simulating the free vibration response of multi degree of freedom models of cantilever beams.

Modal identification of structures from the responses and random decrement signatures

NASA Technical Reports Server (NTRS)

Brahim, S. R.; Goglia, G. L.

1977-01-01

The theory and application of a method which utilizes the free response of a structure to determine its vibration parameters is described. The time-domain free response is digitized and used in a digital computer program to determine the number of modes excited, the natural frequencies, the damping factors, and the modal vectors. The technique is applied to a complex generalized payload model previously tested using sine sweep method and analyzed by NASTRAN. Ten modes of the payload model are identified. In case free decay response is not readily available, an algorithm is developed to obtain the free responses of a structure from its random responses, due to some unknown or known random input or inputs, using the random decrement technique without changing time correlation between signals. The algorithm is tested using random responses from a generalized payload model and from the space shuttle model.

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

Reaction times to weak test lights. [psychophysics biological model

NASA Technical Reports Server (NTRS)

Wandell, B. A.; Ahumada, P.; Welsh, D.

1984-01-01

Maloney and Wandell (1984) describe a model of the response of a single visual channel to weak test lights. The initial channel response is a linearly filtered version of the stimulus. The filter output is randomly sampled over time. Each time a sample occurs there is some probability increasing with the magnitude of the sampled response - that a discrete detection event is generated. Maloney and Wandell derive the statistics of the detection events. In this paper a test is conducted of the hypothesis that the reaction time responses to the presence of a weak test light are initiated at the first detection event. This makes it possible to extend the application of the model to lights that are slightly above threshold, but still within the linear operating range of the visual system. A parameter-free prediction of the model proposed by Maloney and Wandell for lights detected by this statistic is tested. The data are in agreement with the prediction.

Improving the Reliability of Student Scores from Speeded Assessments: An Illustration of Conditional Item Response Theory Using a Computer-Administered Measure of Vocabulary.

PubMed

Petscher, Yaacov; Mitchell, Alison M; Foorman, Barbara R

2015-01-01

A growing body of literature suggests that response latency, the amount of time it takes an individual to respond to an item, may be an important factor to consider when using assessment data to estimate the ability of an individual. Considering that tests of passage and list fluency are being adapted to a computer administration format, it is possible that accounting for individual differences in response times may be an increasingly feasible option to strengthen the precision of individual scores. The present research evaluated the differential reliability of scores when using classical test theory and item response theory as compared to a conditional item response model which includes response time as an item parameter. Results indicated that the precision of student ability scores increased by an average of 5 % when using the conditional item response model, with greater improvements for those who were average or high ability. Implications for measurement models of speeded assessments are discussed.

Improving the Reliability of Student Scores from Speeded Assessments: An Illustration of Conditional Item Response Theory Using a Computer-Administered Measure of Vocabulary

PubMed Central

Petscher, Yaacov; Mitchell, Alison M.; Foorman, Barbara R.

2016-01-01

A growing body of literature suggests that response latency, the amount of time it takes an individual to respond to an item, may be an important factor to consider when using assessment data to estimate the ability of an individual. Considering that tests of passage and list fluency are being adapted to a computer administration format, it is possible that accounting for individual differences in response times may be an increasingly feasible option to strengthen the precision of individual scores. The present research evaluated the differential reliability of scores when using classical test theory and item response theory as compared to a conditional item response model which includes response time as an item parameter. Results indicated that the precision of student ability scores increased by an average of 5 % when using the conditional item response model, with greater improvements for those who were average or high ability. Implications for measurement models of speeded assessments are discussed. PMID:27721568

Quantifying the Regional Extent and Magnitude of Interbasin Groundwater Flow and Its Role in Climatic Perturbations in Northern New Mexico, USA

NASA Astrophysics Data System (ADS)

Stewart-Maddox, Noah

Interbasin groundwater flow (IGF) occurs when water that is recharged in one watershed or basin discharges into an adjacent watershed or basin. This contributes additional water and solute mass to the receiving watershed complicating water and solute mass-balance estimates. Additionally, IGF can alter the response time of a watershed in two primary ways, where response time is defined as the amount of time it takes for a watershed to respond to some perturbation that causes a change in recharge. First, changes that occur outside the watershed in the contributing watershed can impact process behavior in the receiving watershed. Secondly, the response time of these external perturbations will be longer than the response time of perturbations that occur solely inside the watershed since the flowpath lengths of IGF are much greater than the flowpaths originating solely inside the watershed, thus an integrated response time arises between the watersheds. Changes in land-use and climate are causing changes in groundwater systems throughout the world, especially with respect to groundwater recharge. Understanding the timing and magnitude of these changes is critically important for future management strategies, sustainability, and adaptation. While progress has been made in identifying IGF in the field, it remains extremely difficult to determine the regional (spatial) extent of IGF. Typically, extensive sampling over a large spatial and temporal scale is required to conclusively determine the extent and magnitude of IGF. Unfortunately, high spatial-resolution datasets are not always available in ungauged or mountainous basins. In this thesis, I examine new methods to determine the extent of IGF, and develop a conceptual model that describes the effect of IGF on watershed response times. First, I present a new methodology using mixing models constrained by inverse geochemical modeling to determine the extent and magnitude of IGF in three watersheds (Canjilon, El Rito, and Vallecitos) draining the Tusas Mountains of northern New Mexico, USA (sites where IGF has been shown to occur). Secondly, I show the construction of a 3D geological model of the Tusas Mountains, which will be used in future work to look at the effects of IGF on watershed response times. Finally, response times are approximated under different IGF conditions to provide a conceptual framework describing the effects of IGF on response time. These results show that IGF can have a dramatic effect on increasing the response time of watersheds, which has important implications moving into the future. I find that the IGF connection from Canjilon to El Rito is large, as supported by previous research. However, the IGF connection from El Rito to Vallecitos is weak to non-existent. The maximum possible IGF contribution from El Rito to Vallecitos occurs during snowmelt when IGF contributes as much as 20% of the solute mass to Vallecitos. During summer and fall months, the IGF contribution to solute mass decreases to less than 5%. Due to the longer flowpath of this IGF connection, the response times along the IGF flowpaths in El Rito and Vallecitos are approximately double the response times of local flowpaths. This means that the amount of IGF that is occurring has a very strong influence on the integrated response time of a given watershed. I end my thesis by presenting a geological model, which will be used in the future to develop a hydrogeological model to more fully answer this question.

Exploratory analysis of real personal emergency response call conversations: considerations for personal emergency response spoken dialogue systems.

PubMed

Young, Victoria; Rochon, Elizabeth; Mihailidis, Alex

2016-11-14

The purpose of this study was to derive data from real, recorded, personal emergency response call conversations to help improve the artificial intelligence and decision making capability of a spoken dialogue system in a smart personal emergency response system. The main study objectives were to: develop a model of personal emergency response; determine categories for the model's features; identify and calculate measures from call conversations (verbal ability, conversational structure, timing); and examine conversational patterns and relationships between measures and model features applicable for improving the system's ability to automatically identify call model categories and predict a target response. This study was exploratory and used mixed methods. Personal emergency response calls were pre-classified according to call model categories identified qualitatively from response call transcripts. The relationships between six verbal ability measures, three conversational structure measures, two timing measures and three independent factors: caller type, risk level, and speaker type, were examined statistically. Emergency medical response services were the preferred response for the majority of medium and high risk calls for both caller types. Older adult callers mainly requested non-emergency medical service responders during medium risk situations. By measuring the number of spoken words-per-minute and turn-length-in-words for the first spoken utterance of a call, older adult and care provider callers could be identified with moderate accuracy. Average call taker response time was calculated using the number-of-speaker-turns and time-in-seconds measures. Care providers and older adults used different conversational strategies when responding to call takers. The words 'ambulance' and 'paramedic' may hold different latent connotations for different callers. The data derived from the real personal emergency response recordings may help a spoken dialogue system classify incoming calls by caller type with moderate probability shortly after the initial caller utterance. Knowing the caller type, the target response for the call may be predicted with some degree of probability and the output dialogue could be tailored to this caller type. The average call taker response time measured from real calls may be used to limit the conversation length in a spoken dialogue system before defaulting to a live call taker.

Modeling in Real Time During the Ebola Response.

PubMed

Meltzer, Martin I; Santibanez, Scott; Fischer, Leah S; Merlin, Toby L; Adhikari, Bishwa B; Atkins, Charisma Y; Campbell, Caresse; Fung, Isaac Chun-Hai; Gambhir, Manoj; Gift, Thomas; Greening, Bradford; Gu, Weidong; Jacobson, Evin U; Kahn, Emily B; Carias, Cristina; Nerlander, Lina; Rainisch, Gabriel; Shankar, Manjunath; Wong, Karen; Washington, Michael L

2016-07-08

To aid decision-making during CDC's response to the 2014-2016 Ebola virus disease (Ebola) epidemic in West Africa, CDC activated a Modeling Task Force to generate estimates on various topics related to the response in West Africa and the risk for importation of cases into the United States. Analysis of eight Ebola response modeling projects conducted during August 2014-July 2015 provided insight into the types of questions addressed by modeling, the impact of the estimates generated, and the difficulties encountered during the modeling. This time frame was selected to cover the three phases of the West African epidemic curve. Questions posed to the Modeling Task Force changed as the epidemic progressed. Initially, the task force was asked to estimate the number of cases that might occur if no interventions were implemented compared with cases that might occur if interventions were implemented; however, at the peak of the epidemic, the focus shifted to estimating resource needs for Ebola treatment units. Then, as the epidemic decelerated, requests for modeling changed to generating estimates of the potential number of sexually transmitted Ebola cases. Modeling to provide information for decision-making during the CDC Ebola response involved limited data, a short turnaround time, and difficulty communicating the modeling process, including assumptions and interpretation of results. Despite these challenges, modeling yielded estimates and projections that public health officials used to make key decisions regarding response strategy and resources required. The impact of modeling during the Ebola response demonstrates the usefulness of modeling in future responses, particularly in the early stages and when data are scarce. Future modeling can be enhanced by planning ahead for data needs and data sharing, and by open communication among modelers, scientists, and others to ensure that modeling and its limitations are more clearly understood. The activities summarized in this report would not have been possible without collaboration with many U.S. and international partners (http://www.cdc.gov/vhf/ebola/outbreaks/2014-west-africa/partners.html).

Impact of Future Climate on Radial Growth of Four Major Boreal Tree Species in the Eastern Canadian Boreal Forest

PubMed Central

Huang, Jian-Guo; Bergeron, Yves; Berninger, Frank; Zhai, Lihong; Tardif, Jacques C.; Denneler, Bernhard

2013-01-01

Immediate phenotypic variation and the lagged effect of evolutionary adaptation to climate change appear to be two key processes in tree responses to climate warming. This study examines these components in two types of growth models for predicting the 2010–2099 diameter growth change of four major boreal species Betula papyrifera, Pinus banksiana, Picea mariana, and Populus tremuloides along a broad latitudinal gradient in eastern Canada under future climate projections. Climate-growth response models for 34 stands over nine latitudes were calibrated and cross-validated. An adaptive response model (A-model), in which the climate-growth relationship varies over time, and a fixed response model (F-model), in which the relationship is constant over time, were constructed to predict future growth. For the former, we examined how future growth of stands in northern latitudes could be forecasted using growth-climate equations derived from stands currently growing in southern latitudes assuming that current climate in southern locations provide an analogue for future conditions in the north. For the latter, we tested if future growth of stands would be maximally predicted using the growth-climate equation obtained from the given local stand assuming a lagged response to climate due to genetic constraints. Both models predicted a large growth increase in northern stands due to more benign temperatures, whereas there was a minimal growth change in southern stands due to potentially warm-temperature induced drought-stress. The A-model demonstrates a changing environment whereas the F-model highlights a constant growth response to future warming. As time elapses we can predict a gradual transition between a response to climate associated with the current conditions (F-model) to a more adapted response to future climate (A-model). Our modeling approach provides a template to predict tree growth response to climate warming at mid-high latitudes of the Northern Hemisphere. PMID:23468879

Impact of future climate on radial growth of four major boreal tree species in the Eastern Canadian boreal forest.

PubMed

Huang, Jian-Guo; Bergeron, Yves; Berninger, Frank; Zhai, Lihong; Tardif, Jacques C; Denneler, Bernhard

2013-01-01

Immediate phenotypic variation and the lagged effect of evolutionary adaptation to climate change appear to be two key processes in tree responses to climate warming. This study examines these components in two types of growth models for predicting the 2010-2099 diameter growth change of four major boreal species Betula papyrifera, Pinus banksiana, Picea mariana, and Populus tremuloides along a broad latitudinal gradient in eastern Canada under future climate projections. Climate-growth response models for 34 stands over nine latitudes were calibrated and cross-validated. An adaptive response model (A-model), in which the climate-growth relationship varies over time, and a fixed response model (F-model), in which the relationship is constant over time, were constructed to predict future growth. For the former, we examined how future growth of stands in northern latitudes could be forecasted using growth-climate equations derived from stands currently growing in southern latitudes assuming that current climate in southern locations provide an analogue for future conditions in the north. For the latter, we tested if future growth of stands would be maximally predicted using the growth-climate equation obtained from the given local stand assuming a lagged response to climate due to genetic constraints. Both models predicted a large growth increase in northern stands due to more benign temperatures, whereas there was a minimal growth change in southern stands due to potentially warm-temperature induced drought-stress. The A-model demonstrates a changing environment whereas the F-model highlights a constant growth response to future warming. As time elapses we can predict a gradual transition between a response to climate associated with the current conditions (F-model) to a more adapted response to future climate (A-model). Our modeling approach provides a template to predict tree growth response to climate warming at mid-high latitudes of the Northern Hemisphere.

The dorsal medial frontal cortex is sensitive to time on task, not response conflict or error likelihood.

PubMed

Grinband, Jack; Savitskaya, Judith; Wager, Tor D; Teichert, Tobias; Ferrera, Vincent P; Hirsch, Joy

2011-07-15

The dorsal medial frontal cortex (dMFC) is highly active during choice behavior. Though many models have been proposed to explain dMFC function, the conflict monitoring model is the most influential. It posits that dMFC is primarily involved in detecting interference between competing responses thus signaling the need for control. It accurately predicts increased neural activity and response time (RT) for incompatible (high-interference) vs. compatible (low-interference) decisions. However, it has been shown that neural activity can increase with time on task, even when no decisions are made. Thus, the greater dMFC activity on incompatible trials may stem from longer RTs rather than response conflict. This study shows that (1) the conflict monitoring model fails to predict the relationship between error likelihood and RT, and (2) the dMFC activity is not sensitive to congruency, error likelihood, or response conflict, but is monotonically related to time on task. Copyright © 2010 Elsevier Inc. All rights reserved.

Modeling Fan Effects on the Time Course of Associative Recognition

PubMed Central

Schneider, Darryl W.; Anderson, John R.

2011-01-01

We investigated the time course of associative recognition using the response signal procedure, whereby a stimulus is presented and followed after a variable lag by a signal indicating that an immediate response is required. More specifically, we examined the effects of associative fan (the number of associations that an item has with other items in memory) on speed–accuracy tradeoff functions obtained in a previous response signal experiment involving briefly studied materials and in a new experiment involving well-learned materials. High fan lowered asymptotic accuracy or the rate of rise in accuracy across lags, or both. We developed an Adaptive Control of Thought–Rational (ACT-R) model for the response signal procedure to explain these effects. The model assumes that high fan results in weak associative activation that slows memory retrieval, thereby decreasing the probability that retrieval finishes in time and producing a speed–accuracy tradeoff function. The ACT-R model provided an excellent account of the data, yielding quantitative fits that were as good as those of the best descriptive model for response signal data. PMID:22197797

A novel trauma leadership model reflective of changing times.

PubMed

DʼHuyvetter, Cecile; Cogbill, Thomas H

2014-01-01

As a result of generational changes in the health care workforce, we sought to evaluate our current Trauma Medical Director Leadership model. We assessed the responsibilities, accountability, time requirements, cost, and provider satisfaction with the current leadership model. Three new providers who had recently completed fellowship training were hired, each with unique professional desires, skill sets, and experience. Our goal was to establish a comprehensive, cost-effective, accountable leadership model that enabled provider satisfaction and equalized leadership responsibilities. A 3-pronged team model was established with a Medical Director title and responsibilities rotating per the American College of Surgeons verification cycle to develop leadership skills and lessen hierarchical differences.

Development of Aeroservoelastic Analytical Models and Gust Load Alleviation Control Laws of a SensorCraft Wind-Tunnel Model Using Measured Data

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Vartio, Eric; Shimko, Anthony; Kvaternik, Raymond G.; Eure, Kenneth W.; Scott,Robert C.

2007-01-01

Aeroservoelastic (ASE) analytical models of a SensorCraft wind-tunnel model are generated using measured data. The data was acquired during the ASE wind-tunnel test of the HiLDA (High Lift-to-Drag Active) Wing model, tested in the NASA Langley Transonic Dynamics Tunnel (TDT) in late 2004. Two time-domain system identification techniques are applied to the development of the ASE analytical models: impulse response (IR) method and the Generalized Predictive Control (GPC) method. Using measured control surface inputs (frequency sweeps) and associated sensor responses, the IR method is used to extract corresponding input/output impulse response pairs. These impulse responses are then transformed into state-space models for use in ASE analyses. Similarly, the GPC method transforms measured random control surface inputs and associated sensor responses into an AutoRegressive with eXogenous input (ARX) model. The ARX model is then used to develop the gust load alleviation (GLA) control law. For the IR method, comparison of measured with simulated responses are presented to investigate the accuracy of the ASE analytical models developed. For the GPC method, comparison of simulated open-loop and closed-loop (GLA) time histories are presented.

Development of Aeroservoelastic Analytical Models and Gust Load Alleviation Control Laws of a SensorCraft Wind-Tunnel Model Using Measured Data

NASA Technical Reports Server (NTRS)

Silva, Walter A.; Shimko, Anthony; Kvaternik, Raymond G.; Eure, Kenneth W.; Scott, Robert C.

2006-01-01

Aeroservoelastic (ASE) analytical models of a SensorCraft wind-tunnel model are generated using measured data. The data was acquired during the ASE wind-tunnel test of the HiLDA (High Lift-to-Drag Active) Wing model, tested in the NASA Langley Transonic Dynamics Tunnel (TDT) in late 2004. Two time-domain system identification techniques are applied to the development of the ASE analytical models: impulse response (IR) method and the Generalized Predictive Control (GPC) method. Using measured control surface inputs (frequency sweeps) and associated sensor responses, the IR method is used to extract corresponding input/output impulse response pairs. These impulse responses are then transformed into state-space models for use in ASE analyses. Similarly, the GPC method transforms measured random control surface inputs and associated sensor responses into an AutoRegressive with eXogenous input (ARX) model. The ARX model is then used to develop the gust load alleviation (GLA) control law. For the IR method, comparison of measured with simulated responses are presented to investigate the accuracy of the ASE analytical models developed. For the GPC method, comparison of simulated open-loop and closed-loop (GLA) time histories are presented.

Monte Carlo study on pulse response of underwater optical channel

NASA Astrophysics Data System (ADS)

Li, Jing; Ma, Yong; Zhou, Qunqun; Zhou, Bo; Wang, Hongyuan

2012-06-01

Pulse response of the underwater wireless optical channel is significant for the analysis of channel capacity and error probability. Traditional vector radiative transfer theory (VRT) is not able to deal with the effect of receiving aperture. On the other hand, general water tank experiments cannot acquire an accurate pulse response due to the limited time resolution of the photo-electronic detector. We present a Monte Carlo simulation model to extract the time-domain pulse response undersea. In comparison with the VRT model, a more accurate pulse response for practical ocean communications could be achieved through statistical analysis of the received photons. The proposed model is more reasonable for the study of the underwater optical channel.

Modeling Confidence Judgments, Response Times, and Multiple Choices in Decision Making: Recognition Memory and Motion Discrimination

PubMed Central

Ratcliff, Roger; Starns, Jeffrey J.

2014-01-01

Confidence in judgments is a fundamental aspect of decision making, and tasks that collect confidence judgments are an instantiation of multiple-choice decision making. We present a model for confidence judgments in recognition memory tasks that uses a multiple-choice diffusion decision process with separate accumulators of evidence for the different confidence choices. The accumulator that first reaches its decision boundary determines which choice is made. Five algorithms for accumulating evidence were compared, and one of them produced proportions of responses for each of the choices and full response time distributions for each choice that closely matched empirical data. With this algorithm, an increase in the evidence in one accumulator is accompanied by a decrease in the others so that the total amount of evidence in the system is constant. Application of the model to the data from an earlier experiment (Ratcliff, McKoon, & Tindall, 1994) uncovered a relationship between the shapes of z-transformed receiver operating characteristics and the behavior of response time distributions. Both are explained in the model by the behavior of the decision boundaries. For generality, we also applied the decision model to a 3-choice motion discrimination task and found it accounted for data better than a competing class of models. The confidence model presents a coherent account of confidence judgments and response time that cannot be explained with currently popular signal detection theory analyses or dual-process models of recognition. PMID:23915088

Predicted persistence and response times of linear and cyclic volatile methylsiloxanes in global and local environments.

PubMed

Kim, Jaeshin; Mackay, Donald; Whelan, Michael John

2018-03-01

We investigated the response times of eight volatile methylsiloxanes (VMSs) in environmental systems at different scales from local to global, with a particular focus on overall loss rates after cessation of emissions. In part, this is driven by proposals to restrict the use of some of these compounds in certain products in Europe. The GloboPOP model estimated low absolute Arctic Contamination Potentials for all VMSs and rapid response times in all media except sediment. VMSs are predicted to be distributed predominantly in air where they react with OH radicals, leading to short response times. After cessation of emissions VMSs concentrations in the environment are expected to decrease rapidly from current levels. Response times in specific water and sediment systems were evaluated using a dynamic QWASI model. Response times were sensitive to both physico-chemical properties and environmental characteristics. Degradation was predicted to play the most important role in determining response times in water and sediment. In the case of the lowest molecular weight VMSs such as L2 and D3, response times were essentially independent of environmental characteristics due to fast hydrolysis in water and sediment. However, response times for the other VMSs are system-specific. They are relatively short in shallow water bodies but increase with depth due to the diminishing role of volatilization on concentration change as volume to surface area ratio increases. In sediment, degradation and resuspension rates also contribute most to the response times. The estimated response times for local environments are useful for planning future monitoring programs. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Numerical results for near surface time domain electromagnetic exploration: a full waveform approach

NASA Astrophysics Data System (ADS)

Sun, H.; Li, K.; Li, X., Sr.; Liu, Y., Sr.; Wen, J., Sr.

2015-12-01

Time domain or Transient electromagnetic (TEM) survey including types with airborne, semi-airborne and ground play important roles in applicants such as geological surveys, ground water/aquifer assess [Meju et al., 2000; Cox et al., 2010], metal ore exploration [Yang and Oldenburg, 2012], prediction of water bearing structures in tunnels [Xue et al., 2007; Sun et al., 2012], UXO exploration [Pasion et al., 2007; Gasperikova et al., 2009] etc. The common practice is introducing a current into a transmitting (Tx) loop and acquire the induced electromagnetic field after the current is cut off [Zhdanov and Keller, 1994]. The current waveforms are different depending on instruments. Rectangle is the most widely used excitation current source especially in ground TEM. Triangle and half sine are commonly used in airborne and semi-airborne TEM investigation. In most instruments, only the off time responses are acquired and used in later analysis and data inversion. Very few airborne instruments acquire the on time and off time responses together. Although these systems acquire the on time data, they usually do not use them in the interpretation.This abstract shows a novel full waveform time domain electromagnetic method and our recent modeling results. The benefits comes from our new algorithm in modeling full waveform time domain electromagnetic problems. We introduced the current density into the Maxwell's equation as the transmitting source. This approach allows arbitrary waveforms, such as triangle, half-sine, trapezoidal waves or scatter record from equipment, being used in modeling. Here, we simulate the establishing and induced diffusion process of the electromagnetic field in the earth. The traditional time domain electromagnetic with pure secondary fields can also be extracted from our modeling results. The real time responses excited by a loop source can be calculated using the algorithm. We analyze the full time gates responses of homogeneous half space and two layered models with half sine current waveform as examples. We find the on time responses are quite sensitive to resistivity or depth changes. The results show the potential use of full waveform responses in time domain electromagnetic surveys.

Posterior Predictive Checks for Conditional Independence between Response Time and Accuracy

ERIC Educational Resources Information Center

Bolsinova, Maria; Tijmstra, Jesper

2016-01-01

Conditional independence (CI) between response time and response accuracy is a fundamental assumption of many joint models for time and accuracy used in educational measurement. In this study, posterior predictive checks (PPCs) are proposed for testing this assumption. These PPCs are based on three discrepancy measures reflecting different…

Prediction, time variance, and classification of hydraulic response to recharge in two karst aquifers

USGS Publications Warehouse

Long, Andrew J.; Mahler, Barbara J.

2013-01-01

Many karst aquifers are rapidly filled and depleted and therefore are likely to be susceptible to changes in short-term climate variability. Here we explore methods that could be applied to model site-specific hydraulic responses, with the intent of simulating these responses to different climate scenarios from high-resolution climate models. We compare hydraulic responses (spring flow, groundwater level, stream base flow, and cave drip) at several sites in two karst aquifers: the Edwards aquifer (Texas, USA) and the Madison aquifer (South Dakota, USA). A lumped-parameter model simulates nonlinear soil moisture changes for estimation of recharge, and a time-variant convolution model simulates the aquifer response to this recharge. Model fit to data is 2.4% better for calibration periods than for validation periods according to the Nash–Sutcliffe coefficient of efficiency, which ranges from 0.53 to 0.94 for validation periods. We use metrics that describe the shapes of the impulse-response functions (IRFs) obtained from convolution modeling to make comparisons in the distribution of response times among sites and between aquifers. Time-variant IRFs were applied to 62% of the sites. Principal component analysis (PCA) of metrics describing the shapes of the IRFs indicates three principal components that together account for 84% of the variability in IRF shape: the first is related to IRF skewness and temporal spread and accounts for 51% of the variability; the second and third largely are related to time-variant properties and together account for 33% of the variability. Sites with IRFs that dominantly comprise exponential curves are separated geographically from those dominantly comprising lognormal curves in both aquifers as a result of spatial heterogeneity. The use of multiple IRF metrics in PCA is a novel method to characterize, compare, and classify the way in which different sites and aquifers respond to recharge. As convolution models are developed for additional aquifers, they could contribute to an IRF database and a general classification system for karst aquifers.

Using Response-Time Constraints in Item Selection To Control for Differential Speededness in Computerized Adaptive Testing. LSAC Research Report Series.

ERIC Educational Resources Information Center

van der Linden, Wim J.; Scrams, David J.; Schnipke, Deborah L.

This paper proposes an item selection algorithm that can be used to neutralize the effect of time limits in computer adaptive testing. The method is based on a statistical model for the response-time distributions of the test takers on the items in the pool that is updated each time a new item has been administered. Predictions from the model are…

Modeling aging effects on two-choice tasks: response signal and response time data.

PubMed

Ratcliff, Roger

2008-12-01

In the response signal paradigm, a test stimulus is presented, and then at one of a number of experimenter-determined times, a signal to respond is presented. Response signal, standard response time (RT), and accuracy data were collected from 19 college-age and 19 60- to 75-year-old participants in a numerosity discrimination task. The data were fit with 2 versions of the diffusion model. Response signal data were modeled by assuming a mixture of processes, those that have terminated before the signal and those that have not terminated; in the latter case, decisions are based on either partial information or guessing. The effects of aging on performance in the regular RT task were explained the same way in the models, with a 70- to 100-ms increase in the nondecision component of processing, more conservative decision criteria, and more variability across trials in drift and the nondecision component of processing, but little difference in drift rate (evidence). In the response signal task, the primary reason for a slower rise in the response signal functions for older participants was variability in the nondecision component of processing. Overall, the results were consistent with earlier fits of the diffusion model to the standard RT task for college-age participants and to the data from aging studies using this task in the standard RT procedure. Copyright (c) 2009 APA, all rights reserved.

Modeling Aging Effects on Two-Choice Tasks: Response Signal and Response Time Data

PubMed Central

Ratcliff, Roger

2009-01-01

In the response signal paradigm, a test stimulus is presented, and then at one of a number of experimenter-determined times, a signal to respond is presented. Response signal, standard response time (RT), and accuracy data were collected from 19 college-age and 19 60- to 75-year-old participants in a numerosity discrimination task. The data were fit with 2 versions of the diffusion model. Response signal data were modeled by assuming a mixture of processes, those that have terminated before the signal and those that have not terminated; in the latter case, decisions are based on either partial information or guessing. The effects of aging on performance in the regular RT task were explained the same way in the models, with a 70- to 100-ms increase in the nondecision component of processing, more conservative decision criteria, and more variability across trials in drift and the nondecision component of processing, but little difference in drift rate (evidence). In the response signal task, the primary reason for a slower rise in the response signal functions for older participants was variability in the nondecision component of processing. Overall, the results were consistent with earlier fits of the diffusion model to the standard RT task for college-age participants and to the data from aging studies using this task in the standard RT procedure. PMID:19140659

Evaluating perceptual integration: uniting response-time- and accuracy-based methodologies.

PubMed

Eidels, Ami; Townsend, James T; Hughes, Howard C; Perry, Lacey A

2015-02-01

This investigation brings together a response-time system identification methodology (e.g., Townsend & Wenger Psychonomic Bulletin & Review 11, 391-418, 2004a) and an accuracy methodology, intended to assess models of integration across stimulus dimensions (features, modalities, etc.) that were proposed by Shaw and colleagues (e.g., Mulligan & Shaw Perception & Psychophysics 28, 471-478, 1980). The goal was to theoretically examine these separate strategies and to apply them conjointly to the same set of participants. The empirical phases were carried out within an extension of an established experimental design called the double factorial paradigm (e.g., Townsend & Nozawa Journal of Mathematical Psychology 39, 321-359, 1995). That paradigm, based on response times, permits assessments of architecture (parallel vs. serial processing), stopping rule (exhaustive vs. minimum time), and workload capacity, all within the same blocks of trials. The paradigm introduced by Shaw and colleagues uses a statistic formally analogous to that of the double factorial paradigm, but based on accuracy rather than response times. We demonstrate that the accuracy measure cannot discriminate between parallel and serial processing. Nonetheless, the class of models supported by the accuracy data possesses a suitable interpretation within the same set of models supported by the response-time data. The supported model, consistent across individuals, is parallel and has limited capacity, with the participants employing the appropriate stopping rule for the experimental setting.

A model of interval timing by neural integration.

PubMed

Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

2011-06-22

We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.

Logical-rule models of classification response times: a synthesis of mental-architecture, random-walk, and decision-bound approaches.

PubMed

Fific, Mario; Little, Daniel R; Nosofsky, Robert M

2010-04-01

We formalize and provide tests of a set of logical-rule models for predicting perceptual classification response times (RTs) and choice probabilities. The models are developed by synthesizing mental-architecture, random-walk, and decision-bound approaches. According to the models, people make independent decisions about the locations of stimuli along a set of component dimensions. Those independent decisions are then combined via logical rules to determine the overall categorization response. The time course of the independent decisions is modeled via random-walk processes operating along individual dimensions. Alternative mental architectures are used as mechanisms for combining the independent decisions to implement the logical rules. We derive fundamental qualitative contrasts for distinguishing among the predictions of the rule models and major alternative models of classification RT. We also use the models to predict detailed RT-distribution data associated with individual stimuli in tasks of speeded perceptual classification. PsycINFO Database Record (c) 2010 APA, all rights reserved.

June 13, 2013 U.S. East Coast Meteotsunami: Comparing a Numerical Model With Observations

NASA Astrophysics Data System (ADS)

Wang, D.; Becker, N. C.; Weinstein, S.; Whitmore, P.; Knight, W.; Kim, Y.; Bouchard, R. H.; Grissom, K.

2013-12-01

On June 13, 2013, a tsunami struck the U.S. East Coast and caused several reported injuries. This tsunami occurred after a derecho moved offshore from North America into the Atlantic Ocean. The presence of this storm, the lack of a seismic source, and the fact that tsunami arrival times at tide stations and deep ocean-bottom pressure sensors cannot be attributed to a 'point-source' suggest this tsunami was caused by atmospheric forces, i.e., a meteotsunami. In this study we attempt to reproduce the observed phenomenon using a numerical model with idealized atmospheric pressure forcing resembling the propagation of the observed barometric anomaly. The numerical model was able to capture some observed features of the tsunami at some tide stations, including the time-lag between the time of pressure jump and the time of tsunami arrival. The model also captures the response at a deep ocean-bottom pressure gauge (DART 44402), including the primary wave and the reflected wave. There are two components of the oceanic response to the propagating pressure anomaly, inverted barometer response and dynamic response. We find that the dynamic response over the deep ocean to be much smaller than the inverted barometer response. The time lag between the pressure jump and tsunami arrival at tide stations is due to the dynamic response: waves generated and/or reflected at the shelf-break propagate shoreward and amplify due to the shoaling effect. The evolution of the derecho over the deep ocean (propagation direction and intensity) is not well defined, however, because of the lack of data so the forcing used for this study is somewhat speculative. Better definition of the pressure anomaly through increased observation or high resolution atmospheric models would improve meteotsunami forecast capabilities.

Extinction time of a stochastic predator-prey model by the generalized cell mapping method

NASA Astrophysics Data System (ADS)

Han, Qun; Xu, Wei; Hu, Bing; Huang, Dongmei; Sun, Jian-Qiao

2018-03-01

The stochastic response and extinction time of a predator-prey model with Gaussian white noise excitations are studied by the generalized cell mapping (GCM) method based on the short-time Gaussian approximation (STGA). The methods for stochastic response probability density functions (PDFs) and extinction time statistics are developed. The Taylor expansion is used to deal with non-polynomial nonlinear terms of the model for deriving the moment equations with Gaussian closure, which are needed for the STGA in order to compute the one-step transition probabilities. The work is validated with direct Monte Carlo simulations. We have presented the transient responses showing the evolution from a Gaussian initial distribution to a non-Gaussian steady-state one. The effects of the model parameter and noise intensities on the steady-state PDFs are discussed. It is also found that the effects of noise intensities on the extinction time statistics are opposite to the effects on the limit probability distributions of the survival species.

Dynamic response analysis of structure under time-variant interval process model

NASA Astrophysics Data System (ADS)

Xia, Baizhan; Qin, Yuan; Yu, Dejie; Jiang, Chao

2016-10-01

Due to the aggressiveness of the environmental factor, the variation of the dynamic load, the degeneration of the material property and the wear of the machine surface, parameters related with the structure are distinctly time-variant. Typical model for time-variant uncertainties is the random process model which is constructed on the basis of a large number of samples. In this work, we propose a time-variant interval process model which can be effectively used to deal with time-variant uncertainties with limit information. And then two methods are presented for the dynamic response analysis of the structure under the time-variant interval process model. The first one is the direct Monte Carlo method (DMCM) whose computational burden is relative high. The second one is the Monte Carlo method based on the Chebyshev polynomial expansion (MCM-CPE) whose computational efficiency is high. In MCM-CPE, the dynamic response of the structure is approximated by the Chebyshev polynomials which can be efficiently calculated, and then the variational range of the dynamic response is estimated according to the samples yielded by the Monte Carlo method. To solve the dependency phenomenon of the interval operation, the affine arithmetic is integrated into the Chebyshev polynomial expansion. The computational effectiveness and efficiency of MCM-CPE is verified by two numerical examples, including a spring-mass-damper system and a shell structure.

Assessing dose–response effects of national essential medicine policy in China: comparison of two methods for handling data with a stepped wedge-like design and hierarchical structure

PubMed Central

Ren, Yan; Yang, Min; Li, Qian; Pan, Jay; Chen, Fei; Li, Xiaosong; Meng, Qun

2017-01-01

Objectives To introduce multilevel repeated measures (RM) models and compare them with multilevel difference-in-differences (DID) models in assessing the linear relationship between the length of the policy intervention period and healthcare outcomes (dose–response effect) for data from a stepped-wedge design with a hierarchical structure. Design The implementation of national essential medicine policy (NEMP) in China was a stepped-wedge-like design of five time points with a hierarchical structure. Using one key healthcare outcome from the national NEMP surveillance data as an example, we illustrate how a series of multilevel DID models and one multilevel RM model can be fitted to answer some research questions on policy effects. Setting Routinely and annually collected national data on China from 2008 to 2012. Participants 34 506 primary healthcare facilities in 2675 counties of 31 provinces. Outcome measures Agreement and differences in estimates of dose–response effect and variation in such effect between the two methods on the logarithm-transformed total number of outpatient visits per facility per year (LG-OPV). Results The estimated dose–response effect was approximately 0.015 according to four multilevel DID models and precisely 0.012 from one multilevel RM model. Both types of model estimated an increase in LG-OPV by 2.55 times from 2009 to 2012, but 2–4.3 times larger SEs of those estimates were found by the multilevel DID models. Similar estimates of mean effects of covariates and random effects of the average LG-OPV among all levels in the example dataset were obtained by both types of model. Significant variances in the dose–response among provinces, counties and facilities were estimated, and the ‘lowest’ or ‘highest’ units by their dose–response effects were pinpointed only by the multilevel RM model. Conclusions For examining dose–response effect based on data from multiple time points with hierarchical structure and the stepped wedge-like designs, multilevel RM models are more efficient, convenient and informative than the multilevel DID models. PMID:28399510

Real-Time Decision Making and Aggressive Behavior in Youth: A Heuristic Model of Response Evaluation and Decision (RED)

PubMed Central

Fontaine, Reid Griffith; Dodge, Kenneth A.

2009-01-01

Considerable scientific and intervention attention has been paid to judgment and decision-making systems associated with aggressive behavior in youth. However, most empirical studies have investigated social-cognitive correlates of stable child and adolescent aggressiveness, and less is known about real-time decision making to engage in aggressive behavior. A model of real-time decision making must incorporate both impulsive actions and rational thought. The present paper advances a process model (response evaluation and decision; RED) of real-time behavioral judgments and decision making in aggressive youths with mathematic representations that may be used to quantify response strength. These components are a heuristic to describe decision making, though it is doubtful that individuals always mentally complete these steps. RED represents an organization of social–cognitive operations believed to be active during the response decision step of social information processing. The model posits that RED processes can be circumvented through impulsive responding. This article provides a description and integration of thoughtful, rational decision making and nonrational impulsivity in aggressive behavioral interactions. PMID:20802851

Real-Time Decision Making and Aggressive Behavior in Youth: A Heuristic Model of Response Evaluation and Decision (RED).

PubMed

Fontaine, Reid Griffith; Dodge, Kenneth A

2006-11-01

Considerable scientific and intervention attention has been paid to judgment and decision-making systems associated with aggressive behavior in youth. However, most empirical studies have investigated social-cognitive correlates of stable child and adolescent aggressiveness, and less is known about real-time decision making to engage in aggressive behavior. A model of real-time decision making must incorporate both impulsive actions and rational thought. The present paper advances a process model (response evaluation and decision; RED) of real-time behavioral judgments and decision making in aggressive youths with mathematic representations that may be used to quantify response strength. These components are a heuristic to describe decision making, though it is doubtful that individuals always mentally complete these steps. RED represents an organization of social-cognitive operations believed to be active during the response decision step of social information processing. The model posits that RED processes can be circumvented through impulsive responding. This article provides a description and integration of thoughtful, rational decision making and nonrational impulsivity in aggressive behavioral interactions.

A Maximum Likelihood Approach to Functional Mapping of Longitudinal Binary Traits

PubMed Central

Wang, Chenguang; Li, Hongying; Wang, Zhong; Wang, Yaqun; Wang, Ningtao; Wang, Zuoheng; Wu, Rongling

2013-01-01

Despite their importance in biology and biomedicine, genetic mapping of binary traits that change over time has not been well explored. In this article, we develop a statistical model for mapping quantitative trait loci (QTLs) that govern longitudinal responses of binary traits. The model is constructed within the maximum likelihood framework by which the association between binary responses is modeled in terms of conditional log odds-ratios. With this parameterization, the maximum likelihood estimates (MLEs) of marginal mean parameters are robust to the misspecification of time dependence. We implement an iterative procedures to obtain the MLEs of QTL genotype-specific parameters that define longitudinal binary responses. The usefulness of the model was validated by analyzing a real example in rice. Simulation studies were performed to investigate the statistical properties of the model, showing that the model has power to identify and map specific QTLs responsible for the temporal pattern of binary traits. PMID:23183762

Response Errors Explain the Failure of Independent-Channels Models of Perception of Temporal Order

PubMed Central

García-Pérez, Miguel A.; Alcalá-Quintana, Rocío

2012-01-01

Independent-channels models of perception of temporal order (also referred to as threshold models or perceptual latency models) have been ruled out because two formal properties of these models (monotonicity and parallelism) are not borne out by data from ternary tasks in which observers must judge whether stimulus A was presented before, after, or simultaneously with stimulus B. These models generally assume that observed responses are authentic indicators of unobservable judgments, but blinks, lapses of attention, or errors in pressing the response keys (maybe, but not only, motivated by time pressure when reaction times are being recorded) may make observers misreport their judgments or simply guess a response. We present an extension of independent-channels models that considers response errors and we show that the model produces psychometric functions that do not satisfy monotonicity and parallelism. The model is illustrated by fitting it to data from a published study in which the ternary task was used. The fitted functions describe very accurately the absence of monotonicity and parallelism shown by the data. These characteristics of empirical data are thus consistent with independent-channels models when response errors are taken into consideration. The implications of these results for the analysis and interpretation of temporal order judgment data are discussed. PMID:22493586

New model performance index for engineering design of control systems

NASA Technical Reports Server (NTRS)

1970-01-01

Performance index includes a model representing linear control-system design specifications. Based on a geometric criterion for approximation of the model by the actual system, the index can be interpreted directly in terms of the desired system response model without actually having the model's time response.

Hydrograph separation for karst watersheds using a two-domain rainfall-discharge model

USGS Publications Warehouse

Long, Andrew J.

2009-01-01

Highly parameterized, physically based models may be no more effective at simulating the relations between rainfall and outflow from karst watersheds than are simpler models. Here an antecedent rainfall and convolution model was used to separate a karst watershed hydrograph into two outflow components: one originating from focused recharge in conduits and one originating from slow flow in a porous annex system. In convolution, parameters of a complex system are lumped together in the impulse-response function (IRF), which describes the response of the system to an impulse of effective precipitation. Two parametric functions in superposition approximate the two-domain IRF. The outflow hydrograph can be separated into flow components by forward modeling with isolated IRF components, which provides an objective criterion for separation. As an example, the model was applied to a karst watershed in the Madison aquifer, South Dakota, USA. Simulation results indicate that this watershed is characterized by a flashy response to storms, with a peak response time of 1 day, but that 89% of the flow results from the slow-flow domain, with a peak response time of more than 1 year. This long response time may be the result of perched areas that store water above the main water table. Simulation results indicated that some aspects of the system are stationary but that nonlinearities also exist.

Bladder pain in an LL-37 interstitial cystitis and painful bladder syndrome model.

PubMed

Jia, Wanjian; Schults, Austin J; Jensen, Mark Martin; Ye, Xiangyang; Alt, Jeremiah A; Prestwich, Glenn D; Oottamasathien, Siam

2017-01-01

Our goal was to evaluate the pain response in an LL-37 induced murine model for interstitial cystitis/painful bladder syndrome (IC/PBS). In particular, we sought to characterize the dose dependence, time-course, and relationship of LL-37 induced bladder inflammation and pain. The IC/PBS model was induced in C57Bl/6 mice by instilling 50 μL of LL-37, an immunomodulatory human cathelicidin (anti-microbial peptide), in the bladder for 1 hr. Pain responses were measured using von Frey filaments (0.04 gm to 4.0 gm) before and after LL-37 instillation. Inflammation was evaluated using tissue myeloperoxidase (MPO) assay, gross inspection, and microscopic histologic examination. The dose response experiment demonstrated a graded pain response, with higher concentrations of LL-37 challenge yielding higher pain responses across all stimuli tested. Statistical significance was seen when comparing 1.0 gm von Frey filament results at 320 μM (68 ± 8% response) vs. 0 μM (38 ± 6% response). Interestingly, pain responses did not attenuate across time but increased significantly after 5 (p=0.0012) and 7 days (p=0.0096). Comparison with MPO data suggested that pain responses could be independent of inflammation. We demonstrated within our LL-37 induced IC/PBS model pain occurs in a dose-dependent fashion, pain responses persist beyond the initial point of insult, and our dose response and time course experiments demonstrated that pain was independent of inflammation.

A model for discriminating reinforcers in time and space.

PubMed

Cowie, Sarah; Davison, Michael; Elliffe, Douglas

2016-06-01

Both the response-reinforcer and stimulus-reinforcer relation are important in discrimination learning; differential responding requires a minimum of two discriminably-different stimuli and two discriminably-different associated contingencies of reinforcement. When elapsed time is a discriminative stimulus for the likely availability of a reinforcer, choice over time may be modeled by an extension of the Davison and Nevin (1999) model that assumes that local choice strictly matches the effective local reinforcer ratio. The effective local reinforcer ratio may differ from the obtained local reinforcer ratio for two reasons: Because the animal inaccurately estimates times associated with obtained reinforcers, and thus incorrectly discriminates the stimulus-reinforcer relation across time; and because of error in discriminating the response-reinforcer relation. In choice-based timing tasks, the two responses are usually highly discriminable, and so the larger contributor to differences between the effective and obtained reinforcer ratio is error in discriminating the stimulus-reinforcer relation. Such error may be modeled either by redistributing the numbers of reinforcers obtained at each time across surrounding times, or by redistributing the ratio of reinforcers obtained at each time in the same way. We assessed the extent to which these two approaches to modeling discrimination of the stimulus-reinforcer relation could account for choice in a range of temporal-discrimination procedures. The version of the model that redistributed numbers of reinforcers accounted for more variance in the data. Further, this version provides an explanation for shifts in the point of subjective equality that occur as a result of changes in the local reinforcer rate. The inclusion of a parameter reflecting error in discriminating the response-reinforcer relation enhanced the ability of each version of the model to describe data. The ability of this class of model to account for a range of data suggests that timing, like other conditional discriminations, is choice under the joint discriminative control of elapsed time and differential reinforcement. Understanding the role of differential reinforcement is therefore critical to understanding control by elapsed time. Copyright © 2016 Elsevier B.V. All rights reserved.

Time-lag effects of global vegetation responses to climate change.

PubMed

Wu, Donghai; Zhao, Xiang; Liang, Shunlin; Zhou, Tao; Huang, Kaicheng; Tang, Bijian; Zhao, Wenqian

2015-09-01

Climate conditions significantly affect vegetation growth in terrestrial ecosystems. Due to the spatial heterogeneity of ecosystems, the vegetation responses to climate vary considerably with the diverse spatial patterns and the time-lag effects, which are the most important mechanism of climate-vegetation interactive effects. Extensive studies focused on large-scale vegetation-climate interactions use the simultaneous meteorological and vegetation indicators to develop models; however, the time-lag effects are less considered, which tends to increase uncertainty. In this study, we aim to quantitatively determine the time-lag effects of global vegetation responses to different climatic factors using the GIMMS3g NDVI time series and the CRU temperature, precipitation, and solar radiation datasets. First, this study analyzed the time-lag effects of global vegetation responses to different climatic factors. Then, a multiple linear regression model and partial correlation model were established to statistically analyze the roles of different climatic factors on vegetation responses, from which the primary climate-driving factors for different vegetation types were determined. The results showed that (i) both the time-lag effects of the vegetation responses and the major climate-driving factors that significantly affect vegetation growth varied significantly at the global scale, which was related to the diverse vegetation and climate characteristics; (ii) regarding the time-lag effects, the climatic factors explained 64% variation of the global vegetation growth, which was 11% relatively higher than the model ignoring the time-lag effects; (iii) for the area with a significant change trend (for the period 1982-2008) in the global GIMMS3g NDVI (P < 0.05), the primary driving factor was temperature; and (iv) at the regional scale, the variation in vegetation growth was also related to human activities and natural disturbances. Considering the time-lag effects is quite important for better predicting and evaluating the vegetation dynamics under the background of global climate change. © 2015 John Wiley & Sons Ltd.

Sensitivity of Antarctic sea ice to the Southern Annular Mode in coupled climate models

NASA Astrophysics Data System (ADS)

Holland, Marika M.; Landrum, Laura; Kostov, Yavor; Marshall, John

2017-09-01

We assess the sea ice response to Southern Annular Mode (SAM) anomalies for pre-industrial control simulations from the Coupled Model Intercomparison Project (CMIP5). Consistent with work by Ferreira et al. (J Clim 28:1206-1226, 2015. doi: 10.1175/JCLI-D-14-00313.1), the models generally simulate a two-timescale response to positive SAM anomalies, with an initial increase in ice followed by an eventual sea ice decline. However, the models differ in the cross-over time at which the change in ice response occurs, in the overall magnitude of the response, and in the spatial distribution of the response. Late twentieth century Antarctic sea ice trends in CMIP5 simulations are related in part to different modeled responses to SAM variability acting on different time-varying transient SAM conditions. This explains a significant fraction of the spread in simulated late twentieth century southern hemisphere sea ice extent trends across the model simulations. Applying the modeled sea ice response to SAM variability but driven by the observed record of SAM suggests that variations in the austral summer SAM, which has exhibited a significant positive trend, have driven a modest sea ice decrease. However, additional work is needed to narrow the considerable model uncertainty in the climate response to SAM variability and its implications for 20th-21st century trends.

Uncertainty analysis of accident notification time and emergency medical service response time in work zone traffic accidents.

PubMed

Meng, Qiang; Weng, Jinxian

2013-01-01

Taking into account the uncertainty caused by exogenous factors, the accident notification time (ANT) and emergency medical service (EMS) response time were modeled as 2 random variables following the lognormal distribution. Their mean values and standard deviations were respectively formulated as the functions of environmental variables including crash time, road type, weekend, holiday, light condition, weather, and work zone type. Work zone traffic accident data from the Fatality Analysis Report System between 2002 and 2009 were utilized to determine the distributions of the ANT and the EMS arrival time in the United States. A mixed logistic regression model, taking into account the uncertainty associated with the ANT and the EMS response time, was developed to estimate the risk of death. The results showed that the uncertainty of the ANT was primarily influenced by crash time and road type, whereas the uncertainty of EMS response time is greatly affected by road type, weather, and light conditions. In addition, work zone accidents occurring during a holiday and in poor light conditions were found to be statistically associated with a longer mean ANT and longer EMS response time. The results also show that shortening the ANT was a more effective approach in reducing the risk of death than the EMS response time in work zones. To shorten the ANT and the EMS response time, work zone activities are suggested to be undertaken during non-holidays, during the daytime, and in good weather and light conditions.

Evidence for impulsivity in the Spontaneously Hypertensive Rat drawn from complementary response-withholding tasks

PubMed Central

Sanabria, Federico; Killeen, Peter R

2008-01-01

Background The inability to inhibit reinforced responses is a defining feature of ADHD associated with impulsivity. The Spontaneously Hypertensive Rat (SHR) has been extolled as an animal model of ADHD, but there is no clear experimental evidence of inhibition deficits in SHR. Attempts to demonstrate these deficits may have suffered from methodological and analytical limitations. Methods We provide a rationale for using two complementary response-withholding tasks to doubly dissociate impulsivity from motivational and motor processes. In the lever-holding task (LHT), continual lever depression was required for a minimum interval. Under a differential reinforcement of low rates schedule (DRL), a minimum interval was required between lever presses. Both tasks were studied using SHR and two normotensive control strains, Wistar-Kyoto (WKY) and Long Evans (LE), over an overlapping range of intervals (1 – 5 s for LHT and 5 – 60 s for DRL). Lever-holding and DRL performance was characterized as the output of a mixture of two processes, timing and iterative random responding; we call this account of response inhibition the Temporal Regulation (TR) model. In the context of TR, impulsivity was defined as a bias toward premature termination of the timed intervals. Results The TR model provided an accurate description of LHT and DRL performance. On the basis of TR parameter estimates, SHRs were more impulsive than LE rats across tasks and target times. WKY rats produced substantially shorter timed responses in the lever-holding task than in DRL, suggesting a motivational or motor deficit. The precision of timing by SHR, as measured by the variance of their timed intervals, was excellent, flouting expectations from ADHD research. Conclusion This research validates the TR model of response inhibition and supports SHR as an animal model of ADHD-related impulsivity. It indicates, however, that SHR's impulse-control deficit is not caused by imprecise timing. The use of ad hoc impulsivity metrics and of WKY as control strain for SHR impulsivity are called into question. PMID:18261220

RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.11)

NASA Astrophysics Data System (ADS)

Long, A. J.

2014-09-01

The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, springflow, groundwater level, solute transport, or cave drip for a measurement point in response to a system input of precipitation, recharge, or solute injection. The RRAWFLOW open-source code is written in the R language and is included in the Supplement to this article along with an example model of springflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution; i.e., the unit hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Other options include the use of user-defined IRFs and different methods to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications. RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

Dynamic ambulance reallocation for the reduction of ambulance response times using system status management.

PubMed

Lam, Sean Shao Wei; Zhang, Ji; Zhang, Zhong Cheng; Oh, Hong Choon; Overton, Jerry; Ng, Yih Yng; Ong, Marcus Eng Hock

2015-02-01

Dynamically reassigning ambulance deployment locations throughout a day to balance ambulance availability and demands can be effective in reducing response times. The objectives of this study were to model dynamic ambulance allocation plans in Singapore based on the system status management (SSM) strategy and to evaluate the dynamic deployment plans using a discrete event simulation (DES) model. The geographical information system-based analysis and mathematical programming were used to develop the dynamic ambulance deployment plans for SSM based on ambulance calls data from January 1, 2011, to June 30, 2011. A DES model that incorporated these plans was used to compare the performance of the dynamic SSM strategy against static reallocation policies under various demands and travel time uncertainties. When the deployment plans based on the SSM strategy were followed strictly, the DES model showed that the geographical information system-based plans resulted in approximately 13-second reduction in the median response times compared to the static reallocation policy, whereas the mathematical programming-based plans resulted in approximately a 44-second reduction. The response times and coverage performances were still better than the static policy when reallocations happened for only 60% of all the recommended moves. Dynamically reassigning ambulance deployment locations based on the SSM strategy can result in superior response times and coverage performance compared to static reallocation policies even when the dynamic plans were not followed strictly. Copyright © 2014 Elsevier Inc. All rights reserved.

The Value of Response Times in Item Response Modeling

ERIC Educational Resources Information Center

Molenaar, Dylan

2015-01-01

A new and very interesting approach to the analysis of responses and response times is proposed by Goldhammer (this issue). In his approach, differences in the speed-ability compromise within respondents are considered to confound the differences in ability between respondents. These confounding effects of speed on the inferences about ability can…

Testing for Aberrant Behavior in Response Time Modeling

ERIC Educational Resources Information Center

Marianti, Sukaesi; Fox, Jean-Paul; Avetisyan, Marianna; Veldkamp, Bernard P.; Tijmstra, Jesper

2014-01-01

Many standardized tests are now administered via computer rather than paper-and-pencil format. In a computer-based testing environment, it is possible to record not only the test taker's response to each question (item) but also the amount of time spent by the test taker in considering and answering each item. Response times (RTs) provide…

Task Inhibition and Response Inhibition in Older vs. Younger Adults: A Diffusion Model Analysis

PubMed Central

Schuch, Stefanie

2016-01-01

Differences in inhibitory ability between older (64–79 years, N = 24) and younger adults (18–26 years, N = 24) were investigated using a diffusion model analysis. Participants performed a task-switching paradigm that allows assessing n−2 task repetition costs, reflecting inhibitory control on the level of tasks, as well as n−1 response-repetition costs, reflecting inhibitory control on the level of responses. N−2 task repetition costs were of similar size in both age groups. Diffusion model analysis revealed that for both younger and older adults, drift rate parameters were smaller in the inhibition condition relative to the control condition, consistent with the idea that persisting task inhibition slows down response selection. Moreover, there was preliminary evidence for task inhibition effects in threshold separation and non-decision time in the older, but not the younger adults, suggesting that older adults might apply different strategies when dealing with persisting task inhibition. N−1 response-repetition costs in mean RT were larger in older than younger adults, but in mean error rates tended to be larger in younger than older adults. Diffusion-model analysis revealed longer non-decision times in response repetitions than response switches in both age groups, consistent with the idea that motor processes take longer in response repetitions than response switches due to persisting response inhibition of a previously executed response. The data also revealed age-related differences in overall performance: Older adults responded more slowly and more accurately than young adults, which was reflected by a higher threshold separation parameter in diffusion model analysis. Moreover, older adults showed larger non-decision times and higher variability in non-decision time than young adults, possibly reflecting slower and more variable motor processes. In contrast, overall drift rate did not differ between older and younger adults. Taken together, diffusion model analysis revealed differences in overall performance between the age groups, as well as preliminary evidence for age differences in dealing with task inhibition, but no evidence for an inhibitory deficit in older age. PMID:27895599

Modeling Nonignorable Missing Data in Speeded Tests

ERIC Educational Resources Information Center

Glas, Cees A. W.; Pimentel, Jonald L.

2008-01-01

In tests with time limits, items at the end are often not reached. Usually, the pattern of missing responses depends on the ability level of the respondents; therefore, missing data are not ignorable in statistical inference. This study models data using a combination of two item response theory (IRT) models: one for the observed response data and…

A swinging seesaw as a novel model mechanism for time-dependent hormesis under dose-dependent stimulatory and inhibitory effects: A case study on the toxicity of antibacterial chemicals to Aliivibrio fischeri.

PubMed

Sun, Haoyu; Calabrese, Edward J; Zheng, Min; Wang, Dali; Pan, Yongzheng; Lin, Zhifen; Liu, Ying

2018-08-01

Hormesis occurs frequently in broadly ranging biological areas (e.g. plant biology, microbiology, biogerontology), toxicology, pharmacology and medicine. While numerous mechanisms (e.g. receptor and pathway mediated pathway responses) account for stimulatory and inhibitory features of hormetic dose responses, the vast majority emphasizes the inclusion of many doses but only one timepoint or use of a single optimized dose that is assessed over a broad range of timepoints. In this paper, a toxicity study was designed using a large number of properly spaced doses with responses determined over a large number of timepoints, which could help us reveal the underlying mechanism of hormesis. We present the results of a dose-time-response study on hormesis using five antibacterial chemicals on the bioluminescence of Aliivibrio fischeri, measuring expression of protein mRNA based on quorum sensing, simulating bioluminescent reaction and analyzing toxic actions of test chemicals. The findings show dose-time-dependent responses conforming to the hormetic dose-response model, while revealing unique response dynamics between agent induced stimulatory and inhibitory effects within bacterial growth phase dynamics. These dynamic dose-time features reveal a type of biological seesaw model that integrates stimulatory and inhibitory responses within unique growth phase, dose and time features, which has faultlessly explained the time-dependent hormetic phenomenon induced by five antibacterial chemicals (characterized by low-dose stimulation and high-dose inhibition). This study offers advances in understanding cellular dynamics, the biological integration of diverse and opposing responses and their role in evolutionary adaptive strategies to chemicals, which can provide new insight into the mechanistic investigation of hormesis. Copyright © 2018 Elsevier Ltd. All rights reserved.

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.

A model of interval timing by neural integration

PubMed Central

Simen, Patrick; Balci, Fuat; deSouza, Laura; Cohen, Jonathan D.; Holmes, Philip

2011-01-01

We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes; that correlations among them can be largely cancelled by balancing excitation and inhibition; that neural populations can act as integrators; and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule’s predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior. PMID:21697374

A Ballistic Model of Choice Response Time

ERIC Educational Resources Information Center

Brown, Scott; Heathcote, Andrew

2005-01-01

Almost all models of response time (RT) use a stochastic accumulation process. To account for the benchmark RT phenomena, researchers have found it necessary to include between-trial variability in the starting point and/or the rate of accumulation, both in linear (R. Ratcliff & J. N. Rouder, 1998) and nonlinear (M. Usher & J. L. McClelland, 2001)…

Mathematical modeling improves EC50 estimations from classical dose-response curves.

PubMed

Nyman, Elin; Lindgren, Isa; Lövfors, William; Lundengård, Karin; Cervin, Ida; Sjöström, Theresia Arbring; Altimiras, Jordi; Cedersund, Gunnar

2015-03-01

The β-adrenergic response is impaired in failing hearts. When studying β-adrenergic function in vitro, the half-maximal effective concentration (EC50 ) is an important measure of ligand response. We previously measured the in vitro contraction force response of chicken heart tissue to increasing concentrations of adrenaline, and observed a decreasing response at high concentrations. The classical interpretation of such data is to assume a maximal response before the decrease, and to fit a sigmoid curve to the remaining data to determine EC50 . Instead, we have applied a mathematical modeling approach to interpret the full dose-response curve in a new way. The developed model predicts a non-steady-state caused by a short resting time between increased concentrations of agonist, which affect the dose-response characterization. Therefore, an improved estimate of EC50 may be calculated using steady-state simulations of the model. The model-based estimation of EC50 is further refined using additional time-resolved data to decrease the uncertainty of the prediction. The resulting model-based EC50 (180-525 nm) is higher than the classically interpreted EC50 (46-191 nm). Mathematical modeling thus makes it possible to re-interpret previously obtained datasets, and to make accurate estimates of EC50 even when steady-state measurements are not experimentally feasible. The mathematical models described here have been submitted to the JWS Online Cellular Systems Modelling Database, and may be accessed at http://jjj.bio.vu.nl/database/nyman. © 2015 FEBS.

Dynamic calibration approach for determining catechins and gallic acid in green tea using LC-ESI/MS.

PubMed

Bedner, Mary; Duewer, David L

2011-08-15

Catechins and gallic acid are antioxidant constituents of Camellia sinensis, or green tea. Liquid chromatography with both ultraviolet (UV) absorbance and electrospray ionization mass spectrometric (ESI/MS) detection was used to determine catechins and gallic acid in three green tea matrix materials that are commonly used as dietary supplements. The results from both detection modes were evaluated with 14 quantitation models, all of which were based on the analyte response relative to an internal standard. Half of the models were static, where quantitation was achieved with calibration factors that were constant over an analysis set. The other half were dynamic, with calibration factors calculated from interpolated response factor data at each time a sample was injected to correct for potential variations in analyte response over time. For all analytes, the relatively nonselective UV responses were found to be very stable over time and independent of the calibrant concentration; comparable results with low variability were obtained regardless of the quantitation model used. Conversely, the highly selective MS responses were found to vary both with time and as a function of the calibrant concentration. A dynamic quantitation model based on polynomial data-fitting was used to reduce the variability in the quantitative results using the MS data.

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.

Modelling the firing pattern of bullfrog vestibular neurons responding to naturalistic stimuli

NASA Technical Reports Server (NTRS)

Paulin, M. G.; Hoffman, L. F.

1999-01-01

We have developed a neural system identification method for fitting models to stimulus-response data, where the response is a spike train. The method involves using a general nonlinear optimisation procedure to fit models in the time domain. We have applied the method to model bullfrog semicircular canal afferent neuron responses during naturalistic, broad-band head rotations. These neurons respond in diverse ways, but a simple four parameter class of models elegantly accounts for the various types of responses observed. c1999 Elsevier Science B.V. All rights reserved.

Nowcast model for hazardous material spill prevention and response, San Francisco Bay, California

USGS Publications Warehouse

Cheng, Ralph T.; Wilmot, Wayne L.; Galt, Jerry A.

1997-01-01

The National Oceanic and Atmospheric Administration (NOAA) installed the Physical Oceanographic Real-time System (PORTS) in San Francisco Bay, California, to provide real-time observations of tides, tidal currents, and meteorological conditions to, among other purposes, guide hazardous material spill prevention and response. Integrated with nowcast modeling techniques and dissemination of real-time data and the nowcasting results through the Internet on the World Wide Web, emerging technologies used in PORTS for real-time data collection forms a nowcast modeling system. Users can download tides and tidal current distribution in San Francisco Bay for their specific applications and/or for further analysis.

Applying Kaplan-Meier to Item Response Data

ERIC Educational Resources Information Center

McNeish, Daniel

2018-01-01

Some IRT models can be equivalently modeled in alternative frameworks such as logistic regression. Logistic regression can also model time-to-event data, which concerns the probability of an event occurring over time. Using the relation between time-to-event models and logistic regression and the relation between logistic regression and IRT, this…

Two mechanisms of rephasal of circadian rhythms in response to a 180 deg phase shift /simulated 12-hr time zone change/

NASA Technical Reports Server (NTRS)

Deroshia, C. W.; Winget, C. M.; Bond, G. H.

1976-01-01

A model developed by Wever (1966) is considered. The model describes the behavior of circadian rhythms in response to photoperiod phase shifts simulating time zone changes, as a function of endogenous periodicity, light intensity, and direction of phase shift. A description is given of an investigation conducted to test the model upon the deep body temperature rhythm in unrestrained subhuman primates. An evaluation is conducted regarding the applicability of the model in predicting the type and duration of desynchronization induced by simulated time zone changes as a function of endogenous periodicity.

Multi-time-scale heat transfer modeling of turbid tissues exposed to short-pulsed irradiations.

PubMed

Kim, Kyunghan; Guo, Zhixiong

2007-05-01

A combined hyperbolic radiation and conduction heat transfer model is developed to simulate multi-time-scale heat transfer in turbid tissues exposed to short-pulsed irradiations. An initial temperature response of a tissue to an ultrashort pulse irradiation is analyzed by the volume-average method in combination with the transient discrete ordinates method for modeling the ultrafast radiation heat transfer. This response is found to reach pseudo steady state within 1 ns for the considered tissues. The single pulse result is then utilized to obtain the temperature response to pulse train irradiation at the microsecond/millisecond time scales. After that, the temperature field is predicted by the hyperbolic heat conduction model which is solved by the MacCormack's scheme with error terms correction. Finally, the hyperbolic conduction is compared with the traditional parabolic heat diffusion model. It is found that the maximum local temperatures are larger in the hyperbolic prediction than the parabolic prediction. In the modeled dermis tissue, a 7% non-dimensional temperature increase is found. After about 10 thermal relaxation times, thermal waves fade away and the predictions between the hyperbolic and parabolic models are consistent.

Modeling Cyber Conflicts Using an Extended Petri Net Formalism

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

Zakrzewska, Anita N; Ferragut, Erik M

2011-01-01

When threatened by automated attacks, critical systems that require human-controlled responses have difficulty making optimal responses and adapting protections in real- time and may therefore be overwhelmed. Consequently, experts have called for the development of automatic real-time reaction capabilities. However, a technical gap exists in the modeling and analysis of cyber conflicts to automatically understand the repercussions of responses. There is a need for modeling cyber assets that accounts for concurrent behavior, incomplete information, and payoff functions. Furthermore, we address this need by extending the Petri net formalism to allow real-time cyber conflicts to be modeled in a way thatmore » is expressive and concise. This formalism includes transitions controlled by players as well as firing rates attached to transitions. This allows us to model both player actions and factors that are beyond the control of players in real-time. We show that our formalism is able to represent situational aware- ness, concurrent actions, incomplete information and objective functions. These factors make it well-suited to modeling cyber conflicts in a way that allows for useful analysis. MITRE has compiled the Common Attack Pattern Enumera- tion and Classification (CAPEC), an extensive list of cyber attacks at various levels of abstraction. CAPEC includes factors such as attack prerequisites, possible countermeasures, and attack goals. These elements are vital to understanding cyber attacks and to generating the corresponding real-time responses. We demonstrate that the formalism can be used to extract precise models of cyber attacks from CAPEC. Several case studies show that our Petri net formalism is more expressive than other models, such as attack graphs, for modeling cyber conflicts and that it is amenable to exploring cyber strategies.« less

A Two-Timescale Response to Ozone Depletion: Importance of the Background State

NASA Astrophysics Data System (ADS)

Seviour, W.; Waugh, D.; Gnanadesikan, A.

2015-12-01

It has been recently suggested that the response of Southern Ocean sea-ice extent to stratospheric ozone depletion is time-dependent; that the ocean surface initially cools due to enhanced northward Ekman drift caused by a poleward shift in the eddy-driven jet, and then warms after some time due to upwelling of warm waters from below the mixed layer. It is therefore possible that ozone depletion could act to favor a short-term increase in sea-ice extent. However, many uncertainties remain in understanding this mechanism, with different models showing widely differing time-scales and magnitudes of the response. Here, we analyze an ensemble of coupled model simulations with a step-function ozone perturbation. The two-timescale response is present with an approximately 30 year initial cooling period. The response is further shown to be highly dependent upon the background ocean temperature and salinity stratification, which is influenced by both natural internal variability and the isopycnal eddy mixing parameterization. It is suggested that the majority of inter-model differences in the Southern Ocean response to ozone depletion is caused by differences in stratification.

Flood Nowcasting With Linear Catchment Models, Radar and Kalman Filters

NASA Astrophysics Data System (ADS)

Pegram, Geoff; Sinclair, Scott

A pilot study using real time rainfall data as input to a parsimonious linear distributed flood forecasting model is presented. The aim of the study is to deliver an operational system capable of producing flood forecasts, in real time, for the Mgeni and Mlazi catchments near the city of Durban in South Africa. The forecasts can be made at time steps which are of the order of a fraction of the catchment response time. To this end, the model is formulated in Finite Difference form in an equation similar to an Auto Regressive Moving Average (ARMA) model; it is this formulation which provides the required computational efficiency. The ARMA equation is a discretely coincident form of the State-Space equations that govern the response of an arrangement of linear reservoirs. This results in a functional relationship between the reservoir response con- stants and the ARMA coefficients, which guarantees stationarity of the ARMA model. Input to the model is a combined "Best Estimate" spatial rainfall field, derived from a combination of weather RADAR and Satellite rainfield estimates with point rain- fall given by a network of telemetering raingauges. Several strategies are employed to overcome the uncertainties associated with forecasting. Principle among these are the use of optimal (double Kalman) filtering techniques to update the model states and parameters in response to current streamflow observations and the application of short term forecasting techniques to provide future estimates of the rainfield as input to the model.

Emergencies planning and response: Coupling an exposure model with different atmospheric dispersion models

NASA Astrophysics Data System (ADS)

Sanchez, E. Y.; Colman Lerner, J. E.; Porta, A.; Jacovkis, P. M.

2013-11-01

Information on spatial and time dependent concentration patterns of hazardous substances, as well as on the potential effects on population, is necessary to assist in chemical emergency planning and response. To that end, some models predict transport and dispersion of hazardous substances, and others estimate potential effects upon exposed population. Taken together, both groups constitute a powerful tool to estimate vulnerable regions and to evaluate environmental impact upon affected populations. The development of methodologies and models with direct application to the context in which we live allows us to draft a more clear representation of the risk scenario and, hence, to obtain the adequate tools for an optimal response. By means of the recently developed DDC (Damage Differential Coupling) exposure model, it was possible to optimize, from both the qualitative and the quantitative points of view, the estimation of the population affected by a toxic cloud, because the DDC model has a very good capacity to couple with different atmospheric dispersion models able to provide data over time. In this way, DDC analyzes the different concentration profiles (output from the transport model) associating them with some reference concentration to identify risk zones. In this work we present a disaster scenario in Chicago (USA), by coupling DDC with two transport models of different complexity, showing the close relationship between a representative result and the run time of the models. In the same way, it becomes evident that knowing the time evolution of the toxic cloud and of the affected regions significantly improves the probability of taking the correct decisions on planning and response facing the emergency.

Time-varying SMART design and data analysis methods for evaluating adaptive intervention effects.

PubMed

Dai, Tianjiao; Shete, Sanjay

2016-08-30

In a standard two-stage SMART design, the intermediate response to the first-stage intervention is measured at a fixed time point for all participants. Subsequently, responders and non-responders are re-randomized and the final outcome of interest is measured at the end of the study. To reduce the side effects and costs associated with first-stage interventions in a SMART design, we proposed a novel time-varying SMART design in which individuals are re-randomized to the second-stage interventions as soon as a pre-fixed intermediate response is observed. With this strategy, the duration of the first-stage intervention will vary. We developed a time-varying mixed effects model and a joint model that allows for modeling the outcomes of interest (intermediate and final) and the random durations of the first-stage interventions simultaneously. The joint model borrows strength from the survival sub-model in which the duration of the first-stage intervention (i.e., time to response to the first-stage intervention) is modeled. We performed a simulation study to evaluate the statistical properties of these models. Our simulation results showed that the two modeling approaches were both able to provide good estimations of the means of the final outcomes of all the embedded interventions in a SMART. However, the joint modeling approach was more accurate for estimating the coefficients of first-stage interventions and time of the intervention. We conclude that the joint modeling approach provides more accurate parameter estimates and a higher estimated coverage probability than the single time-varying mixed effects model, and we recommend the joint model for analyzing data generated from time-varying SMART designs. In addition, we showed that the proposed time-varying SMART design is cost-efficient and equally effective in selecting the optimal embedded adaptive intervention as the standard SMART design.

The effect of stimulus strength on the speed and accuracy of a perceptual decision.

PubMed

Palmer, John; Huk, Alexander C; Shadlen, Michael N

2005-05-02

Both the speed and the accuracy of a perceptual judgment depend on the strength of the sensory stimulation. When stimulus strength is high, accuracy is high and response time is fast; when stimulus strength is low, accuracy is low and response time is slow. Although the psychometric function is well established as a tool for analyzing the relationship between accuracy and stimulus strength, the corresponding chronometric function for the relationship between response time and stimulus strength has not received as much consideration. In this article, we describe a theory of perceptual decision making based on a diffusion model. In it, a decision is based on the additive accumulation of sensory evidence over time to a bound. Combined with simple scaling assumptions, the proportional-rate and power-rate diffusion models predict simple analytic expressions for both the chronometric and psychometric functions. In a series of psychophysical experiments, we show that this theory accounts for response time and accuracy as a function of both stimulus strength and speed-accuracy instructions. In particular, the results demonstrate a close coupling between response time and accuracy. The theory is also shown to subsume the predictions of Piéron's Law, a power function dependence of response time on stimulus strength. The theory's analytic chronometric function allows one to extend theories of accuracy to response time.

Response surface modeling for hot, humid air decontamination of materials contaminated with Bacillus anthracis ∆Sterne and Bacillus thuringiensis Al Hakam spores

PubMed Central

2014-01-01

Response surface methodology using a face-centered cube design was used to describe and predict spore inactivation of Bacillus anthracis ∆Sterne and Bacillus thuringiensis Al Hakam spores after exposure of six spore-contaminated materials to hot, humid air. For each strain/material pair, an attempt was made to fit a first or second order model. All three independent predictor variables (temperature, relative humidity, and time) were significant in the models except that time was not significant for B. thuringiensis Al Hakam on nylon. Modeling was unsuccessful for wiring insulation and wet spores because there was complete spore inactivation in the majority of the experimental space. In cases where a predictive equation could be fit, response surface plots with time set to four days were generated. The survival of highly purified Bacillus spores can be predicted for most materials tested when given the settings for temperature, relative humidity, and time. These predictions were cross-checked with spore inactivation measurements. PMID:24949256

Dynamic responses of railroad car models to vertical and lateral rail inputs

NASA Technical Reports Server (NTRS)

Sewall, J. L.; Parrish, R. V.; Durling, B. J.

1971-01-01

Simplified dynamic models were applied in a study of vibration in a high-speed railroad car. The mathematical models used were a four-degree-of-freedom model for vertical responses to vertical rail inputs and a ten-degree-of-freedom model for lateral response to lateral or rolling (cross-level) inputs from the rails. Elastic properties of the passenger car body were represented by bending and torsion of a uniform beam. Rail-to-car (truck) suspensions were modeled as spring-mass-dashpot oscillators. Lateral spring nonlinearities approximating certain complicated truck mechanisms were introduced. The models were excited by displacement and, in some cases, velocity inputs from the rails by both deterministic (including sinusoidal) and random input functions. Results were obtained both in the frequency and time domains. Solutions in the time domain for the lateral model were obtained for a wide variety of transient and random inputs generated on-line by an analog computer. Variations in one of the damping properties of the lateral car suspension gave large fluctuations in response over a range of car speeds for a given input. This damping coefficient was significant in reducing lateral car responses that were higher for nonlinear springs for three different inputs.

On the validity of measuring change over time in routine clinical assessment: a close examination of item-level response shifts in psychosomatic inpatients.

PubMed

Nolte, S; Mierke, A; Fischer, H F; Rose, M

2016-06-01

Significant life events such as severe health status changes or intensive medical treatment often trigger response shifts in individuals that may hamper the comparison of measurements over time. Drawing from the Oort model, this study aims at detecting response shift at the item level in psychosomatic inpatients and evaluating its impact on the validity of comparing repeated measurements. Complete pretest and posttest data were available from 1188 patients who had filled out the ICD-10 Symptom Rating (ISR) scale at admission and discharge, on average 24 days after intake. Reconceptualization, reprioritization, and recalibration response shifts were explored applying tests of measurement invariance. In the item-level approach, all model parameters were constrained to be equal between pretest and posttest. If non-invariance was detected, these were linked to the different types of response shift. When constraining across-occasion model parameters, model fit worsened as indicated by a significant Satorra-Bentler Chi-square difference test suggesting potential presence of response shifts. A close examination revealed presence of two types of response shift, i.e., (non)uniform recalibration and both higher- and lower-level reconceptualization response shifts leading to four model adjustments. Our analyses suggest that psychosomatic inpatients experienced some response shifts during their hospital stay. According to the hierarchy of measurement invariance, however, only one of the detected non-invariances is critical for unbiased mean comparisons over time, which did not have a substantial impact on estimating change. Hence, the use of the ISR can be recommended for outcomes assessment in clinical routine, as change score estimates do not seem hampered by response shift effects.

Technical Note: Response time evolution of XR-QA2 GafChromic™ film models.

PubMed

Aldelaijan, Saad; Tomic, Nada; Papaconstadopoulos, Pavlos; Schneider, James; Seuntjens, Jan; Shih, Shelley; Lewis, David; Devic, Slobodan

2018-01-01

To evaluate the response of the newest XR-QA2 GafChromic™ film model in terms of postexposure signal growth and energy response in comparison with the older XR-QA (Version 2) model. Pieces of film were irradiated to air kerma in air values up to 12 cGy with several beam qualities (5.3-8.25 mm Al) commonly used for CT scanning. Film response was scored in terms of net reflectance from scanned film images at various points in time postirradiation ranging from 1 to 7 days and 5 months postexposure. To reconstruct the measurement signal changes with postirradiation delay, we irradiated one film piece and then scanned it at different point times starting from 2" min and up to 3 days postexposure. For all beam qualities and dose range investigated, it appears that the XR-QA2 film signal completely saturated after 15 h. Compared to 15 h postirradiation scanning time, the observed variation in net reflectance were 3%, 2%, and 1% for film scanned 2" min, 20 min, and 3 h after exposure, respectively, which is well within the measurement uncertainty of the XR-QA2 based reference radiochromic film dosimetry system. A comparison between the XR-QA (Version 2) and the XR-QA2 film response after several months (relative to their responses after 24 h) show differences in up to 8% and 1% for each film model respectively. The replacement of cesium bromide in the older XR-QA (Version 2) film model with bismuth oxide in the newer XR-QA2 film, while keeping the same single sensitive layer structure, lead to a significantly more stable postexposure response. © 2017 American Association of Physicists in Medicine.

Development of the Complex General Linear Model in the Fourier Domain: Application to fMRI Multiple Input-Output Evoked Responses for Single Subjects

PubMed Central

Rio, Daniel E.; Rawlings, Robert R.; Woltz, Lawrence A.; Gilman, Jodi; Hommer, Daniel W.

2013-01-01

A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI) blood-oxygen level-dependent (BOLD) multivariate data. This methodology was originally developed to analyze multiple stimulus input evoked response BOLD data. However, to analyze clinical data generated using a repeated measures experimental design, the model has been extended to handle multivariate time series data and demonstrated on control and alcoholic subjects taken from data previously analyzed in the temporal domain. Analysis of BOLD data is typically carried out in the time domain where the data has a high temporal correlation. These analyses generally employ parametric models of the hemodynamic response function (HRF) where prewhitening of the data is attempted using autoregressive (AR) models for the noise. However, this data can be analyzed in the Fourier domain. Here, assumptions made on the noise structure are less restrictive, and hypothesis tests can be constructed based on voxel-specific nonparametric estimates of the hemodynamic transfer function (HRF in the Fourier domain). This is especially important for experimental designs involving multiple states (either stimulus or drug induced) that may alter the form of the response function. PMID:23840281

Development of the complex general linear model in the Fourier domain: application to fMRI multiple input-output evoked responses for single subjects.

PubMed

Rio, Daniel E; Rawlings, Robert R; Woltz, Lawrence A; Gilman, Jodi; Hommer, Daniel W

2013-01-01

A linear time-invariant model based on statistical time series analysis in the Fourier domain for single subjects is further developed and applied to functional MRI (fMRI) blood-oxygen level-dependent (BOLD) multivariate data. This methodology was originally developed to analyze multiple stimulus input evoked response BOLD data. However, to analyze clinical data generated using a repeated measures experimental design, the model has been extended to handle multivariate time series data and demonstrated on control and alcoholic subjects taken from data previously analyzed in the temporal domain. Analysis of BOLD data is typically carried out in the time domain where the data has a high temporal correlation. These analyses generally employ parametric models of the hemodynamic response function (HRF) where prewhitening of the data is attempted using autoregressive (AR) models for the noise. However, this data can be analyzed in the Fourier domain. Here, assumptions made on the noise structure are less restrictive, and hypothesis tests can be constructed based on voxel-specific nonparametric estimates of the hemodynamic transfer function (HRF in the Fourier domain). This is especially important for experimental designs involving multiple states (either stimulus or drug induced) that may alter the form of the response function.

Preference as a Function of Active Interresponse Times: A Test of the Active Time Model

ERIC Educational Resources Information Center

Misak, Paul; Cleaveland, J. Mark

2011-01-01

In this article, we describe a test of the active time model for concurrent variable interval (VI) choice. The active time model (ATM) suggests that the time since the most recent response is one of the variables controlling choice in concurrent VI VI schedules of reinforcement. In our experiment, pigeons were trained in a multiple concurrent…

A distributed lag approach to fitting non-linear dose-response models in particulate matter air pollution time series investigations.

PubMed

Roberts, Steven; Martin, Michael A

2007-06-01

The majority of studies that have investigated the relationship between particulate matter (PM) air pollution and mortality have assumed a linear dose-response relationship and have used either a single-day's PM or a 2- or 3-day moving average of PM as the measure of PM exposure. Both of these modeling choices have come under scrutiny in the literature, the linear assumption because it does not allow for non-linearities in the dose-response relationship, and the use of the single- or multi-day moving average PM measure because it does not allow for differential PM-mortality effects spread over time. These two problems have been dealt with on a piecemeal basis with non-linear dose-response models used in some studies and distributed lag models (DLMs) used in others. In this paper, we propose a method for investigating the shape of the PM-mortality dose-response relationship that combines a non-linear dose-response model with a DLM. This combined model will be shown to produce satisfactory estimates of the PM-mortality dose-response relationship in situations where non-linear dose response models and DLMs alone do not; that is, the combined model did not systemically underestimate or overestimate the effect of PM on mortality. The combined model is applied to ten cities in the US and a pooled dose-response model formed. When fitted with a change-point value of 60 microg/m(3), the pooled model provides evidence for a positive association between PM and mortality. The combined model produced larger estimates for the effect of PM on mortality than when using a non-linear dose-response model or a DLM in isolation. For the combined model, the estimated percentage increase in mortality for PM concentrations of 25 and 75 microg/m(3) were 3.3% and 5.4%, respectively. In contrast, the corresponding values from a DLM used in isolation were 1.2% and 3.5%, respectively.

High Resolution Flash Flood Forecasting Using a Wireless Sensor Network in the Dallas-Fort Worth Metroplex

NASA Astrophysics Data System (ADS)

Bartos, M. D.; Kerkez, B.; Noh, S.; Seo, D. J.

2017-12-01

In this study, we develop and evaluate a high resolution urban flash flood monitoring system using a wireless sensor network (WSN), a real-time rainfall-runoff model, and spatially-explicit radar rainfall predictions. Flooding is the leading cause of natural disaster fatalities in the US, with flash flooding in particular responsible for a majority of flooding deaths. While many riverine flood models have been operationalized into early warning systems, there is currently no model that is capable of reliably predicting flash floods in urban areas. Urban flash floods are particularly difficult to model due to a lack of rainfall and runoff data at appropriate scales. To address this problem, we develop a wide-area flood-monitoring wireless sensor network for the Dallas-Fort Worth metroplex, and use this network to characterize rainfall-runoff response over multiple heterogeneous catchments. First, we deploy a network of 22 wireless sensor nodes to collect real-time stream stage measurements over catchments ranging from 2-80 km2 in size. Next, we characterize the rainfall-runoff response of each catchment by combining stream stage data with gage and radar-based precipitation measurements. Finally, we demonstrate the potential for real-time flash flood prediction by joining the derived rainfall-runoff models with real-time radar rainfall predictions. We find that runoff response is highly heterogeneous among catchments, with large variabilities in runoff response detected even among nearby gages. However, when spatially-explicit rainfall fields are included, spatial variability in runoff response is largely captured. This result highlights the importance of increased spatial coverage for flash flood prediction.

Optimization of the High-speed On-off Valve of an Automatic Transmission

NASA Astrophysics Data System (ADS)

Li-mei, ZHAO; Huai-chao, WU; Lei, ZHAO; Yun-xiang, LONG; Guo-qiao, LI; Shi-hao, TANG

2018-03-01

The response time of the high-speed on-off solenoid valve has a great influence on the performance of the automatic transmission. In order to reduce the response time of the high-speed on-off valve, the simulation model of the valve was built by use of AMESim and Ansoft Maxwell softwares. To reduce the response time, an objective function based on ITAE criterion was built and the Genetic Algorithms was used to optimize five parameters including circle number, working air gap, et al. The comparison between experiment and simulation shows that the model is verified. After optimization, the response time of the valve is reduced by 38.16%, the valve can meet the demands of the automatic transmission well. The results can provide theoretical reference for the improvement of automatic transmission performance.

Investigations on response time of magnetorheological elastomer under compression mode

NASA Astrophysics Data System (ADS)

Zhu, Mi; Yu, Miao; Qi, Song; Fu, Jie

2018-05-01

For efficient fast control of vibration system with magnetorheological elastomer (MRE)-based smart device, the response time of MRE material is the key parameter which directly affects the control performance of the vibration system. For a step coil current excitation, this paper proposed a Maxwell behavior model with time constant λ to describe the normal force response of MRE, and the response time of MRE was extracted through the separation of coil response time. Besides, the transient responses of MRE under compression mode were experimentally investigated, and the effects of (i) applied current, (ii) particle distribution and (iii) compressive strain on the response time of MRE were addressed. The results revealed that the three factors can affect the response characteristic of MRE quite significantly. Besides the intrinsic importance for contributing to the response evaluation and effective design of MRE device, this study may conduce to the optimal design of controller for MRE control system.

A Diffusion Model Analysis of the Effects of Aging on Recognition Memory

ERIC Educational Resources Information Center

Ratcliff, Roger; Thapar, Anjali; McKoon, Gail

2004-01-01

The effects of aging on response time were examined in a recognition memory experiment with young, college age subjects and older, 60-75 year old subjects. The older subjects were slower than the young subjects but almost as accurate. Ratcliff's (1978) diffusion model was fit to the data and it provided a good account of response times, their…

Time series modeling of live-cell shape dynamics for image-based phenotypic profiling.

PubMed

Gordonov, Simon; Hwang, Mun Kyung; Wells, Alan; Gertler, Frank B; Lauffenburger, Douglas A; Bathe, Mark

2016-01-01

Live-cell imaging can be used to capture spatio-temporal aspects of cellular responses that are not accessible to fixed-cell imaging. As the use of live-cell imaging continues to increase, new computational procedures are needed to characterize and classify the temporal dynamics of individual cells. For this purpose, here we present the general experimental-computational framework SAPHIRE (Stochastic Annotation of Phenotypic Individual-cell Responses) to characterize phenotypic cellular responses from time series imaging datasets. Hidden Markov modeling is used to infer and annotate morphological state and state-switching properties from image-derived cell shape measurements. Time series modeling is performed on each cell individually, making the approach broadly useful for analyzing asynchronous cell populations. Two-color fluorescent cells simultaneously expressing actin and nuclear reporters enabled us to profile temporal changes in cell shape following pharmacological inhibition of cytoskeleton-regulatory signaling pathways. Results are compared with existing approaches conventionally applied to fixed-cell imaging datasets, and indicate that time series modeling captures heterogeneous dynamic cellular responses that can improve drug classification and offer additional important insight into mechanisms of drug action. The software is available at http://saphire-hcs.org.

Wetting and drying of soil in response to precipitation: Data analysis, modeling, and forecasting

USGS Publications Warehouse

Basak, Aniruddha; Kulkarni, Chinmay; Schmidt, Kevin M.; Mengshoel, Ole

2016-01-01

This paper investigates methods to analyze and forecast soil moisture time series. We extend an existing Antecedent Water Index (AWI) model, which expresses soil moisture as a function of time and rainfall. Unfortunately, the existing AWI model does not forecast effectively for time periods beyond a few hours. To overcome this limitation, we develop a novel AWI-based model. Our model accumulates rainfall over a time interval and can fit a diverse range of wetting and drying curves. In addition, parameters in our model reflect hydrologic redistribution processes of gravity and suction.We validate our models using experimental soil moisture and rainfall time series data collected from steep gradient post-wildfire sites in Southern California, where rapid landscape change was observed in response to small to moderate rain storms. We found that our novel model fits the data for three distinct soil textures, occurring at different depths below the ground surface (5, 15, and 30 cm). Our model also successfully forecasts soil moisture trends, such as drying and wetting rate.

Evaluation of the Comet Assay for Assessing the Dose-Response Relationship of DNA Damage Induced by Ionizing Radiation

PubMed Central

Wang, Yan; Xu, Chang; Du, Li Qing; Cao, Jia; Liu, Jian Xiang; Su, Xu; Zhao, Hui; Fan, Fei-Yue; Wang, Bing; Katsube, Takanori; Fan, Sai Jun; Liu, Qiang

2013-01-01

Dose- and time-response curves were combined to assess the potential of the comet assay in radiation biodosimetry. The neutral comet assay was used to detect DNA double-strand breaks in lymphocytes caused by γ-ray irradiation. A clear dose-response relationship with DNA double-strand breaks using the comet assay was found at different times after irradiation (p < 0.001). A time-response relationship was also found within 72 h after irradiation (p < 0.001). The curves for DNA double-strand breaks and DNA repair in vitro of human lymphocytes presented a nice model, and a smooth, three-dimensional plane model was obtained when the two curves were combined. PMID:24240807

Plant ecosystem responses to rising atmospheric CO2: applying a "two-timing" approach to assess alternative hypotheses for mechanisms of nutrient limitation

NASA Astrophysics Data System (ADS)

Medlyn, B.; Jiang, M.; Zaehle, S.

2017-12-01

There is now ample experimental evidence that the response of terrestrial vegetation to rising atmospheric CO2 concentration is modified by soil nutrient availability. How to represent nutrient cycling processes is thus a key consideration for vegetation models. We have previously used model intercomparison to demonstrate that models incorporating different assumptions predict very different responses at Free-Air CO2 Enrichment experiments. Careful examination of model outputs has provided some insight into the reasons for the different model outcomes, but it is difficult to attribute outcomes to specific assumptions. Here we investigate the impact of individual assumptions in a generic plant carbon-nutrient cycling model. The G'DAY (Generic Decomposition And Yield) model is modified to incorporate alternative hypotheses for nutrient cycling. We analyse the impact of these assumptions in the model using a simple analytical approach known as "two-timing". This analysis identifies the quasi-equilibrium behaviour of the model at the time scales of the component pools. The analysis provides a useful mathematical framework for probing model behaviour and identifying the most critical assumptions for experimental study.

Modelling and tuning for a time-delayed vibration absorber with friction

NASA Astrophysics Data System (ADS)

Zhang, Xiaoxu; Xu, Jian; Ji, Jinchen

2018-06-01

This paper presents an integrated analytical and experimental study to the modelling and tuning of a time-delayed vibration absorber (TDVA) with friction. In system modelling, this paper firstly applies the method of averaging to obtain the frequency response function (FRF), and then uses the derived FRF to evaluate the fitness of different friction models. After the determination of the system model, this paper employs the obtained FRF to evaluate the vibration absorption performance with respect to tunable parameters. A significant feature of the TDVA with friction is that its stability is dependent on the excitation parameters. To ensure the stability of the time-delayed control, this paper defines a sufficient condition for stability estimation. Experimental measurements show that the dynamic response of the TDVA with friction can be accurately predicted and the time-delayed control can be precisely achieved by using the modelling and tuning technique provided in this paper.

Response of an eddy-permitting ocean model to the assimilation of sparse in situ data

NASA Astrophysics Data System (ADS)

Li, Jian-Guo; Killworth, Peter D.; Smeed, David A.

2003-04-01

The response of an eddy-permitting ocean model to changes introduced by data assimilation is studied when the available in situ data are sparse in both space and time (typical for the majority of the ocean). Temperature and salinity (T&S) profiles from the WOCE upper ocean thermal data set were assimilated into a primitive equation ocean model over the North Atlantic, using a simple nudging scheme with a time window of about 2 days and a horizontal spatial radius of about 1°. When data are sparse the model returns to its unassimilated behavior, locally "forgetting" or rejecting the assimilation, on timescales determined by the local advection and diffusion. Increasing the spatial weighting radius effectively reduces both processes and hence lengthens the model restoring time (and with it, the impact of assimilation). Increasing the nudging factor enhances the assimilation effect but has little effect on the model restoring time.

The linear transformation model with frailties for the analysis of item response times.

PubMed

Wang, Chun; Chang, Hua-Hua; Douglas, Jeffrey A

2013-02-01

The item response times (RTs) collected from computerized testing represent an underutilized source of information about items and examinees. In addition to knowing the examinees' responses to each item, we can investigate the amount of time examinees spend on each item. In this paper, we propose a semi-parametric model for RTs, the linear transformation model with a latent speed covariate, which combines the flexibility of non-parametric modelling and the brevity as well as interpretability of parametric modelling. In this new model, the RTs, after some non-parametric monotone transformation, become a linear model with latent speed as covariate plus an error term. The distribution of the error term implicitly defines the relationship between the RT and examinees' latent speeds; whereas the non-parametric transformation is able to describe various shapes of RT distributions. The linear transformation model represents a rich family of models that includes the Cox proportional hazards model, the Box-Cox normal model, and many other models as special cases. This new model is embedded in a hierarchical framework so that both RTs and responses are modelled simultaneously. A two-stage estimation method is proposed. In the first stage, the Markov chain Monte Carlo method is employed to estimate the parametric part of the model. In the second stage, an estimating equation method with a recursive algorithm is adopted to estimate the non-parametric transformation. Applicability of the new model is demonstrated with a simulation study and a real data application. Finally, methods to evaluate the model fit are suggested. © 2012 The British Psychological Society.

Aberrant connections between climbing fibres and Purkinje cells induce alterations in the timing of an instrumental response in the rat.

PubMed

Gaytán-Tocavén, Lorena; López-Vázquez, Miguel Ángel; Guevara, Miguel Ángel; Olvera-Cortés, María Esther

2017-09-01

Cerebellar participation in timing and sensory-motor sequences has been supported by several experimental and clinical studies. A relevant role of the cerebellum in timing of conditioned responses in the range of milliseconds has been demonstrated, but less is known regarding the role of the cerebellum in supra-second timing of operant responses. A dissociated role of the cerebellum and striatum in timing in the millisecond and second range had been reported, respectively. The climbing fibre-Purkinje cell synapse is crucial in timing models; thus, the aberrant connection between these cellular elements is a suitable model for evaluating the contribution of the cerebellum in timing in the supra-second range. The aberrant connection between climbing fibres and Purkinje cells was induced by administration of the antagonist of NMDA receptors MK-801 to Sprague-Dawley rats at postnatal days 7-14. The timing of an operant response with two fixed intervals (5 and 8 s) and egocentric sequential learning was evaluated in 60-day-old adult rats. The aberrant connections caused a reduced accuracy in the timing of the instrumental response that was more evident in the 8-s interval and a reduced number of successive correct responses (responses emitted in the correct second without any other response between them) in the 8-s interval. In addition, an inability to incorporate new information in a sequence previously learned in egocentric-based sequence learning was apparent in rats with aberrant CF-PC synapses. These results support a relevant role for the cerebellum in the fine-tuning of the timing of operant responses in the supra-second range.

Improving linear accelerator service response with a real- time electronic event reporting system.

PubMed

Hoisak, Jeremy D P; Pawlicki, Todd; Kim, Gwe-Ya; Fletcher, Richard; Moore, Kevin L

2014-09-08

To track linear accelerator performance issues, an online event recording system was developed in-house for use by therapists and physicists to log the details of technical problems arising on our institution's four linear accelerators. In use since October 2010, the system was designed so that all clinical physicists would receive email notification when an event was logged. Starting in October 2012, we initiated a pilot project in collaboration with our linear accelerator vendor to explore a new model of service and support, in which event notifications were also sent electronically directly to dedicated engineers at the vendor's technical help desk, who then initiated a response to technical issues. Previously, technical issues were reported by telephone to the vendor's call center, which then disseminated information and coordinated a response with the Technical Support help desk and local service engineers. The purpose of this work was to investigate the improvements to clinical operations resulting from this new service model. The new and old service models were quantitatively compared by reviewing event logs and the oncology information system database in the nine months prior to and after initiation of the project. Here, we focus on events that resulted in an inoperative linear accelerator ("down" machine). Machine downtime, vendor response time, treatment cancellations, and event resolution were evaluated and compared over two equivalent time periods. In 389 clinical days, there were 119 machine-down events: 59 events before and 60 after introduction of the new model. In the new model, median time to service response decreased from 45 to 8 min, service engineer dispatch time decreased 44%, downtime per event decreased from 45 to 20 min, and treatment cancellations decreased 68%. The decreased vendor response time and reduced number of on-site visits by a service engineer resulted in decreased downtime and decreased patient treatment cancellations.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

A new framework for climate sensitivity and prediction: a modelling perspective

NASA Astrophysics Data System (ADS)

Ragone, Francesco; Lucarini, Valerio; Lunkeit, Frank

2016-03-01

The sensitivity of climate models to increasing CO2 concentration and the climate response at decadal time-scales are still major factors of uncertainty for the assessment of the long and short term effects of anthropogenic climate change. While the relative slow progress on these issues is partly due to the inherent inaccuracies of numerical climate models, this also hints at the need for stronger theoretical foundations to the problem of studying climate sensitivity and performing climate change predictions with numerical models. Here we demonstrate that it is possible to use Ruelle's response theory to predict the impact of an arbitrary CO2 forcing scenario on the global surface temperature of a general circulation model. Response theory puts the concept of climate sensitivity on firm theoretical grounds, and addresses rigorously the problem of predictability at different time-scales. Conceptually, these results show that performing climate change experiments with general circulation models is a well defined problem from a physical and mathematical point of view. Practically, these results show that considering one single CO2 forcing scenario is enough to construct operators able to predict the response of climatic observables to any other CO2 forcing scenario, without the need to perform additional numerical simulations. We also introduce a general relationship between climate sensitivity and climate response at different time scales, thus providing an explicit definition of the inertia of the system at different time scales. This technique allows also for studying systematically, for a large variety of forcing scenarios, the time horizon at which the climate change signal (in an ensemble sense) becomes statistically significant. While what we report here refers to the linear response, the general theory allows for treating nonlinear effects as well. These results pave the way for redesigning and interpreting climate change experiments from a radically new perspective.

Assessing dose-response effects of national essential medicine policy in China: comparison of two methods for handling data with a stepped wedge-like design and hierarchical structure.

PubMed

Ren, Yan; Yang, Min; Li, Qian; Pan, Jay; Chen, Fei; Li, Xiaosong; Meng, Qun

2017-02-22

To introduce multilevel repeated measures (RM) models and compare them with multilevel difference-in-differences (DID) models in assessing the linear relationship between the length of the policy intervention period and healthcare outcomes (dose-response effect) for data from a stepped-wedge design with a hierarchical structure. The implementation of national essential medicine policy (NEMP) in China was a stepped-wedge-like design of five time points with a hierarchical structure. Using one key healthcare outcome from the national NEMP surveillance data as an example, we illustrate how a series of multilevel DID models and one multilevel RM model can be fitted to answer some research questions on policy effects. Routinely and annually collected national data on China from 2008 to 2012. 34 506 primary healthcare facilities in 2675 counties of 31 provinces. Agreement and differences in estimates of dose-response effect and variation in such effect between the two methods on the logarithm-transformed total number of outpatient visits per facility per year (LG-OPV). The estimated dose-response effect was approximately 0.015 according to four multilevel DID models and precisely 0.012 from one multilevel RM model. Both types of model estimated an increase in LG-OPV by 2.55 times from 2009 to 2012, but 2-4.3 times larger SEs of those estimates were found by the multilevel DID models. Similar estimates of mean effects of covariates and random effects of the average LG-OPV among all levels in the example dataset were obtained by both types of model. Significant variances in the dose-response among provinces, counties and facilities were estimated, and the 'lowest' or 'highest' units by their dose-response effects were pinpointed only by the multilevel RM model. For examining dose-response effect based on data from multiple time points with hierarchical structure and the stepped wedge-like designs, multilevel RM models are more efficient, convenient and informative than the multilevel DID models. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

A local circuit model of learned striatal and dopamine cell responses under probabilistic schedules of reward.

PubMed

Tan, Can Ozan; Bullock, Daniel

2008-10-01

Recently, dopamine (DA) neurons of the substantia nigra pars compacta (SNc) were found to exhibit sustained responses related to reward uncertainty, in addition to the phasic responses related to reward-prediction errors (RPEs). Thus, cue-dependent anticipations of the timing, magnitude, and uncertainty of rewards are learned and reflected in components of DA signals. Here we simulate a local circuit model to show how learned uncertainty responses are generated, along with phasic RPE responses, on single trials. Both types of simulated DA responses exhibit the empirically observed dependencies on conditional probability, expected value of reward, and time since onset of the reward-predicting cue. The model's three major pathways compute expected values of cues, timed predictions of reward magnitudes, and uncertainties associated with these predictions. The first two pathways' computations refine those modeled by Brown et al. (1999). The third, newly modeled, pathway involves medium spiny projection neurons (MSPNs) of the striatal matrix, whose axons corelease GABA and substance P, both at synapses with GABAergic neurons in the substantia nigra pars reticulata (SNr) and with distal dendrites (in SNr) of DA neurons whose somas are located in ventral SNc. Corelease enables efficient computation of uncertainty responses that are a nonmonotonic function of the conditional probability of reward, and variability in striatal cholinergic transmission can explain observed individual differences in the amplitudes of uncertainty responses. The involvement of matricial MSPNs and cholinergic transmission within the striatum implies a relation between uncertainty in cue-reward contingencies and action-selection functions of the basal ganglia.

Modelling the spatio-temporal modulation response of ganglion cells with difference-of-Gaussians receptive fields: relation to photoreceptor response kinetics.

PubMed

Donner, K; Hemilä, S

1996-01-01

Difference-of-Gaussians (DOG) models for the receptive fields of retinal ganglion cells accurately predict linear responses to both periodic stimuli (typically moving sinusoidal gratings) and aperiodic stimuli (typically circular fields presented as square-wave pulses). While the relation of spatial organization to retinal anatomy has received considerable attention, temporal characteristics have been only loosely connected to retinal physiology. Here we integrate realistic photoreceptor response waveforms into the DOG model to clarify how far a single set of physiological parameters predict temporal aspects of linear responses to both periodic and aperiodic stimuli. Traditional filter-cascade models provide a useful first-order approximation of the single-photon response in photoreceptors. The absolute time scale of these, plus a time for retinal transmission, here construed as a fixed delay, are obtained from flash/step data. Using these values, we find that the DOG model predicts the main features of both the amplitude and phase response of linear cat ganglion cells to sinusoidal flicker. Where the simplest model formulation fails, it serves to reveal additional mechanisms. Unforeseen facts are the attenuation of low temporal frequencies even in pure center-type responses, and the phase advance of the response relative to the stimulus at low frequencies. Neither can be explained by any experimentally documented cone response waveform, but both would be explained by signal differentiation, e.g. in the retinal transmission pathway, as demonstrated at least in turtle retina.

Recovery and Resilience After a Nuclear Power Plant Disaster: A Medical Decision model for Managing an Effective, Timely, and Balanced Response

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

Coleman, C. Norman; Blumenthal, Daniel J.

2013-05-01

Based on experiences in Tokyo responding to the Fukushima Daiichi nuclear power plant crisis, a real-time, medical decision model is presented by which to make key health-related decisions given the central role of health and medical issues in such disasters. Focus is on response and recovery activities that are safe, timely, effective, and well-organized. This approach empowers on-site decision makers to make interim decisions without undue delay using readily available and high-level scientific, medical, communication, and policy expertise. Key features of this approach include ongoing assessment, consultation, information, and adaption to the changing conditions. This medical decision model presented ismore » compatible with the existing US National Response Framework structure.« less

Single- versus dual-process models of lexical decision performance: insights from response time distributional analysis.

PubMed

Yap, Melvin J; Balota, David A; Cortese, Michael J; Watson, Jason M

2006-12-01

This article evaluates 2 competing models that address the decision-making processes mediating word recognition and lexical decision performance: a hybrid 2-stage model of lexical decision performance and a random-walk model. In 2 experiments, nonword type and word frequency were manipulated across 2 contrasts (pseudohomophone-legal nonword and legal-illegal nonword). When nonwords became more wordlike (i.e., BRNTA vs. BRANT vs. BRANE), response latencies to nonwords were slowed and the word frequency effect increased. More important, distributional analyses revealed that the Nonword Type = Word Frequency interaction was modulated by different components of the response time distribution, depending on the specific nonword contrast. A single-process random-walk model was able to account for this particular set of findings more successfully than the hybrid 2-stage model. (c) 2006 APA, all rights reserved.

RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15)

USGS Publications Warehouse

Long, Andrew J.

2015-01-01

The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, spring flow, groundwater level, or solute transport for a measurement point in response to a system input of precipitation, recharge, or solute injection. I introduce the first version of RRAWFLOW available for download and public use and describe additional options. The open-source code is written in the R language and is available at http://sd.water.usgs.gov/projects/RRAWFLOW/RRAWFLOW.html along with an example model of streamflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution, i.e., the unit-hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Several options are included to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications (e.g., estimating missing periods in a hydrologic record). RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

Modeling and design of challenge tests: Inflammatory and metabolic biomarker study examples.

PubMed

Gabrielsson, Johan; Hjorth, Stephan; Vogg, Barbara; Harlfinger, Stephanie; Gutierrez, Pablo Morentin; Peletier, Lambertus; Pehrson, Rikard; Davidsson, Pia

2015-01-25

Given the complexity of pharmacological challenge experiments, it is perhaps not surprising that design and analysis, and in turn interpretation and communication of results from a quantitative point of view, is often suboptimal. Here we report an inventory of common designs sampled from anti-inflammatory, respiratory and metabolic disease drug discovery studies, all of which are based on animal models of disease involving pharmacological and/or patho/physiological interaction challenges. The corresponding data are modeled and analyzed quantitatively, the merits of the respective approach discussed and inferences made with respect to future design improvements. Although our analysis is limited to these disease model examples, the challenge approach is generally applicable to the vast majority of pharmacological intervention studies. In the present five Case Studies results from pharmacodynamic effect models from different therapeutic areas were explored and analyzed according to five typical designs. Plasma exposures of test compounds were assayed by either liquid chromatography/mass spectrometry or ligand binding assays. To describe how drug intervention can regulate diverse processes, turnover models of test compound-challenger interaction, transduction processes, and biophase time courses were applied for biomarker response in eosinophil count, IL6 response, paw-swelling, TNFα response and glucose turnover in vivo. Case Study 1 shows results from intratracheal administration of Sephadex, which is a glucocorticoid-sensitive model of airway inflammation in rats. Eosinophils in bronchoalveolar fluid were obtained at different time points via destructive sampling and then regressed by the mixed-effects modeling. A biophase function of the Sephadex time course was inferred from the modeled eosinophil time courses. In Case Study 2, a mouse model showed that the time course of cytokine-induced IL1β challenge was altered with or without drug intervention. Anakinra reversed the IL1β induced cytokine IL6 response in a dose-dependent manner. This Case Study contained time courses of test compound (drug), challenger (IL1β) and cytokine response (IL6), which resulted in high parameter precision. Case Study 3 illustrates collagen-induced arthritis progression in the rat. Swelling scores (based on severity of hind paw swelling) were used to describe arthritis progression after the challenge and the inhibitory effect of two doses of an orally administered test compound. In Case Study 4, a cynomolgus monkey model for lipopolysaccharide LPS-induced TNFα synthesis and/or release was investigated. This model provides integrated information on pharmacokinetics and in vivo potency of the test compounds. Case Study 5 contains data from an oral glucose tolerance test in rats, where the challenger is the same as the pharmacodynamic response biomarker (glucose). It is therefore convenient to model the extra input of glucose simultaneously with baseline data and during intervention of a glucose-lowering compound at different dose levels. Typically time-series analyses of challenger- and biomarker-time data are necessary if an accurate and precise estimate of the pharmacodynamic properties of a test compound is sought. Erosion of data, resulting in the single-point assessment of drug action after a challenge test, should generally be avoided. This is particularly relevant for situations where one expects time-curve shifts, tolerance/rebound, impact of disease, or hormetic concentration-response relationships to occur. Copyright © 2014 Elsevier B.V. All rights reserved.

A new modelling and identification scheme for time-delay systems with experimental investigation: a relay feedback approach

NASA Astrophysics Data System (ADS)

Pandey, Saurabh; Majhi, Somanath; Ghorai, Prasenjit

2017-07-01

In this paper, the conventional relay feedback test has been modified for modelling and identification of a class of real-time dynamical systems in terms of linear transfer function models with time-delay. An ideal relay and unknown systems are connected through a negative feedback loop to bring the sustained oscillatory output around the non-zero setpoint. Thereafter, the obtained limit cycle information is substituted in the derived mathematical equations for accurate identification of unknown plants in terms of overdamped, underdamped, critically damped second-order plus dead time and stable first-order plus dead time transfer function models. Typical examples from the literature are included for the validation of the proposed identification scheme through computer simulations. Subsequently, the comparisons between estimated model and true system are drawn through integral absolute error criterion and frequency response plots. Finally, the obtained output responses through simulations are verified experimentally on real-time liquid level control system using Yokogawa Distributed Control System CENTUM CS3000 set up.

Modelling pH evolution and lactic acid production in the growth medium of a lactic acid bacterium: application to set a biological TTI.

PubMed

Ellouze, M; Pichaud, M; Bonaiti, C; Coroller, L; Couvert, O; Thuault, D; Vaillant, R

2008-11-30

Time temperature integrators or indicators (TTIs) are effective tools making the continuous monitoring of the time temperature history of chilled products possible throughout the cold chain. Their correct setting is of critical importance to ensure food quality. The objective of this study was to develop a model to facilitate accurate settings of the CRYOLOG biological TTI, TRACEO. Experimental designs were used to investigate and model the effects of the temperature, the TTI inoculum size, pH, and water activity on its response time. The modelling process went through several steps addressing growth, acidification and inhibition phenomena in dynamic conditions. The model showed satisfactory results and validations in industrial conditions gave clear evidence that such a model is a valuable tool, not only to predict accurate response times of TRACEO, but also to propose precise settings to manufacture the appropriate TTI to trace a particular food according to a given time temperature scenario.

A meta-analysis of response-time tests of the sequential two-systems model of moral judgment.

PubMed

Baron, Jonathan; Gürçay, Burcu

2017-05-01

The (generalized) sequential two-system ("default interventionist") model of utilitarian moral judgment predicts that utilitarian responses often arise from a system-two correction of system-one deontological intuitions. Response-time (RT) results that seem to support this model are usually explained by the fact that low-probability responses have longer RTs. Following earlier results, we predicted response probability from each subject's tendency to make utilitarian responses (A, "Ability") and each dilemma's tendency to elicit deontological responses (D, "Difficulty"), estimated from a Rasch model. At the point where A = D, the two responses are equally likely, so probability effects cannot account for any RT differences between them. The sequential two-system model still predicts that many of the utilitarian responses made at this point will result from system-two corrections of system-one intuitions, hence should take longer. However, when A = D, RT for the two responses was the same, contradicting the sequential model. Here we report a meta-analysis of 26 data sets, which replicated the earlier results of no RT difference overall at the point where A = D. The data sets used three different kinds of moral judgment items, and the RT equality at the point where A = D held for all three. In addition, we found that RT increased with A-D. This result holds for subjects (characterized by Ability) but not for items (characterized by Difficulty). We explain the main features of this unanticipated effect, and of the main results, with a drift-diffusion model.

Frequency Preference Response to Oscillatory Inputs in Two-dimensional Neural Models: A Geometric Approach to Subthreshold Amplitude and Phase Resonance.

PubMed

Rotstein, Horacio G

2014-01-01

We investigate the dynamic mechanisms of generation of subthreshold and phase resonance in two-dimensional linear and linearized biophysical (conductance-based) models, and we extend our analysis to account for the effect of simple, but not necessarily weak, types of nonlinearities. Subthreshold resonance refers to the ability of neurons to exhibit a peak in their voltage amplitude response to oscillatory input currents at a preferred non-zero (resonant) frequency. Phase-resonance refers to the ability of neurons to exhibit a zero-phase (or zero-phase-shift) response to oscillatory input currents at a non-zero (phase-resonant) frequency. We adapt the classical phase-plane analysis approach to account for the dynamic effects of oscillatory inputs and develop a tool, the envelope-plane diagrams, that captures the role that conductances and time scales play in amplifying the voltage response at the resonant frequency band as compared to smaller and larger frequencies. We use envelope-plane diagrams in our analysis. We explain why the resonance phenomena do not necessarily arise from the presence of imaginary eigenvalues at rest, but rather they emerge from the interplay of the intrinsic and input time scales. We further explain why an increase in the time-scale separation causes an amplification of the voltage response in addition to shifting the resonant and phase-resonant frequencies. This is of fundamental importance for neural models since neurons typically exhibit a strong separation of time scales. We extend this approach to explain the effects of nonlinearities on both resonance and phase-resonance. We demonstrate that nonlinearities in the voltage equation cause amplifications of the voltage response and shifts in the resonant and phase-resonant frequencies that are not predicted by the corresponding linearized model. The differences between the nonlinear response and the linear prediction increase with increasing levels of the time scale separation between the voltage and the gating variable, and they almost disappear when both equations evolve at comparable rates. In contrast, voltage responses are almost insensitive to nonlinearities located in the gating variable equation. The method we develop provides a framework for the investigation of the preferred frequency responses in three-dimensional and nonlinear neuronal models as well as simple models of coupled neurons.

Translation of Real-Time Infectious Disease Modeling into Routine Public Health Practice

PubMed Central

Chughtai, Abrar A.; Heywood, Anita; Gardner, Lauren M.; Heslop, David J.; MacIntyre, C. Raina

2017-01-01

Infectious disease dynamic modeling can support outbreak emergency responses. We conducted a workshop to canvas the needs of stakeholders in Australia for practical, real-time modeling tools for infectious disease emergencies. The workshop was attended by 29 participants who represented government, defense, general practice, and academia stakeholders. We found that modeling is underused in Australia and its potential is poorly understood by practitioners involved in epidemic responses. The development of better modeling tools is desired. Ideal modeling tools for operational use would be easy to use, clearly indicate underlying parameterization and assumptions, and assist with policy and decision making. PMID:28418309

Theoretical Modeling and Electromagnetic Response of Complex Metamaterials

DTIC Science & Technology

2017-03-06

AFRL-AFOSR-VA-TR-2017-0042 Theoretical Modeling and Electromagnetic Response of Complex Metamaterials Andrea Alu UNIVERSITY OF TEXAS AT AUSTIN Final...Nov 2016 4. TITLE AND SUBTITLE Theoretical Modeling and Electromagnetic Response of Complex Metamaterials 5a.  CONTRACT NUMBER 5b.  GRANT NUMBER...based on parity-time symmetric metasurfaces, and various advances in electromagnetic and acoustic theory and applications. Our findings have opened

Rise time and response measurements on a LiSOCl2 cell

NASA Technical Reports Server (NTRS)

Bastien, Caroline; Lecomte, Eric J.

1992-01-01

Dynamic impedance tests were performed on a 180 Ah LiSOCl2 cell in the frame of a short term work contract awarded by Aerospatiale as part of the Hermes Space Plane development work. These tests consisted of rise time and response measurements. The rise time test was performed to show the ability to deliver 4 KW, in the nominal voltage range (75-115 V), within less than 100 microseconds, and after a period at rest of 13 days. The response measurements test consisted of step response and frequency response tests. The frequency response test was performed to characterize the response of the LiSOCl2 cell to a positive or negative load step of 10 A starting from various currents. The test was performed for various depths of discharge and various temperatures. The test results were used to build a mathematical, electrical model of the LiSOCl2 cell which are also presented. The test description, test results, electrical modelization description, and conclusions are presented.

Aerial Refueling Simulator Validation Using Operational Experimentation and Response Surface Methods with Time Series Responses

DTIC Science & Technology

2013-03-21

10 2.3 Time Series Response Data ................................................................................. 12 2.4 Comparison of Response...to 12 evaluating the efficiency of the parameter estimates. In the past, the most popular form of response surface design used the D-optimality...as well. A model can refer to almost anything in math , statistics, or computer science. It can be any “physical, mathematical, or logical

Time and outcome framing in intertemporal tradeoffs.

PubMed

Scholten, Marc; Read, Daniel

2013-07-01

A robust anomaly in intertemporal choice is the delay-speedup asymmetry: Receipts are discounted more, and payments are discounted less, when delayed than when expedited over the same interval. We developed 2 versions of the tradeoff model (Scholten & Read, 2010) to address such situations, in which an outcome is expected at a given time but then its timing is changed. The outcome framing model generalizes the approach taken by the hyperbolic discounting model (Loewenstein & Prelec, 1992): Not obtaining a positive outcome when expected is a worse than expected state, to which people are over-responsive, or hypersensitive, and not incurring a negative outcome when expected is a better than expected state, to which people are under-responsive, or hyposensitive. The time framing model takes a new approach: Delaying a positive outcome or speeding up a negative one involves a loss of time to which people are hypersensitive, and speeding up a positive outcome or delaying a negative one involves a gain of time to which people are hyposensitive. We compare the models on their quantitative predictions of indifference data from matching and preference data from choice. The time framing model systematically outperforms the outcome framing model. PsycINFO Database Record (c) 2013 APA, all rights reserved.

REAL-TIME MEASUREMENT OF AIRWAY RESPONSES TO SULOFUR DIOXIDE (SO2) IN AN INTACT, AWAKE GUINEA PIG MODEL

EPA Science Inventory

Real-time measurment of airway responses to Sulfur Dioxide (SO2) in an intact, awake guinea pig model. J Stanek1,2, Q Krantz2, J Nolan2, D Winsett2, W Watkinson2, and D Costa2. 1College of Veterinary Medicine, NCSU, Raleigh, NC, USA; 2Pulmonary Toxicology Branch, ETD, NHEERL, US...

The impact of short term synaptic depression and stochastic vesicle dynamics on neuronal variability

PubMed Central

Reich, Steven

2014-01-01

Neuronal variability plays a central role in neural coding and impacts the dynamics of neuronal networks. Unreliability of synaptic transmission is a major source of neural variability: synaptic neurotransmitter vesicles are released probabilistically in response to presynaptic action potentials and are recovered stochastically in time. The dynamics of this process of vesicle release and recovery interacts with variability in the arrival times of presynaptic spikes to shape the variability of the postsynaptic response. We use continuous time Markov chain methods to analyze a model of short term synaptic depression with stochastic vesicle dynamics coupled with three different models of presynaptic spiking: one model in which the timing of presynaptic action potentials are modeled as a Poisson process, one in which action potentials occur more regularly than a Poisson process (sub-Poisson) and one in which action potentials occur more irregularly (super-Poisson). We use this analysis to investigate how variability in a presynaptic spike train is transformed by short term depression and stochastic vesicle dynamics to determine the variability of the postsynaptic response. We find that sub-Poisson presynaptic spiking increases the average rate at which vesicles are released, that the number of vesicles released over a time window is more variable for smaller time windows than larger time windows and that fast presynaptic spiking gives rise to Poisson-like variability of the postsynaptic response even when presynaptic spike times are non-Poisson. Our results complement and extend previously reported theoretical results and provide possible explanations for some trends observed in recorded data. PMID:23354693

MATHEMATICAL MODEL OF STERIODOGENESIS TO PREDICT DYNAMIC RESPONSE TO ENDOCRINE DISRUPTORS

EPA Science Inventory

WE ARE DEVELOPING A MECHANISTIC MATHEMATICAL MODEL OF THE INTRATESTICULAR AND INTRAOVARIAN METABOLIC NETWORK THAT MEDIATES STEROID SYNTHESIS, AND THE KINETICS FOR ENZYME INHIBITION BY EDCs TO PREDICT THE TIME AND DOSE-RESPONSE.

Firing-rate response of linear and nonlinear integrate-and-fire neurons to modulated current-based and conductance-based synaptic drive.

PubMed

Richardson, Magnus J E

2007-08-01

Integrate-and-fire models are mainstays of the study of single-neuron response properties and emergent states of recurrent networks of spiking neurons. They also provide an analytical base for perturbative approaches that treat important biological details, such as synaptic filtering, synaptic conductance increase, and voltage-activated currents. Steady-state firing rates of both linear and nonlinear integrate-and-fire models, receiving fluctuating synaptic drive, can be calculated from the time-independent Fokker-Planck equation. The dynamic firing-rate response is less easy to extract, even at the first-order level of a weak modulation of the model parameters, but is an important determinant of neuronal response and network stability. For the linear integrate-and-fire model the response to modulations of current-based synaptic drive can be written in terms of hypergeometric functions. For the nonlinear exponential and quadratic models no such analytical forms for the response are available. Here it is demonstrated that a rather simple numerical method can be used to obtain the steady-state and dynamic response for both linear and nonlinear models to parameter modulation in the presence of current-based or conductance-based synaptic fluctuations. To complement the full numerical solution, generalized analytical forms for the high-frequency response are provided. A special case is also identified--time-constant modulation--for which the response to an arbitrarily strong modulation can be calculated exactly.

Response of the human vestibulo-ocular reflex system to constant angular acceleration. I. Theoretical study.

PubMed

Boumans, L J; Rodenburg, M; Maas, A J

1983-01-01

The response of the human vestibulo-ocular reflex system to a constant angular acceleration is calculated using a second order model with an adaptation term. After first reaching a maximum the peracceleratory response declines. When the stimulus duration is long the decay is mainly governed by the adaptation time constant Ta, which enables to reliably estimate this time constant. In the postacceleratory period of constant velocity there is a reversal in response. The magnitude and the time course of the per- and postacceleratory response are calculated for various values of the cupular time constant T1, the adaptation time constant Ta, and the stimulus duration, thus enabling their influence to be assessed.

Aggregate modeling of fast-acting demand response and control under real-time pricing

DOE PAGES

Chassin, David P.; Rondeau, Daniel

2016-08-24

This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop amore » more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. Finally, the results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.« less

Aggregate modeling of fast-acting demand response and control under real-time pricing

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

Chassin, David P.; Rondeau, Daniel

This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop amore » more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. Finally, the results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.« less

Aggregate modeling of fast-acting demand response and control under real-time pricing

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

Chassin, David P.; Rondeau, Daniel

This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop amore » more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. The results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.« less

A Composite Likelihood Inference in Latent Variable Models for Ordinal Longitudinal Responses

ERIC Educational Resources Information Center

Vasdekis, Vassilis G. S.; Cagnone, Silvia; Moustaki, Irini

2012-01-01

The paper proposes a composite likelihood estimation approach that uses bivariate instead of multivariate marginal probabilities for ordinal longitudinal responses using a latent variable model. The model considers time-dependent latent variables and item-specific random effects to be accountable for the interdependencies of the multivariate…

The question of nonlinearity in the dose-response relation between particulate matter air pollution and mortality: can Akaike's Information Criterion be trusted to take the right turn?

PubMed

Roberts, Steven; Martin, Michael A

2006-12-15

The shape of the dose-response relation between particulate matter air pollution and mortality is crucial for public health assessment, and departures of this relation from linearity could have important regulatory consequences. A number of investigators have studied the shape of the particulate matter-mortality dose-response relation and concluded that the relation could be adequately described by a linear model. Some of these researchers examined the hypothesis of linearity by comparing Akaike's Information Criterion (AIC) values obtained under linear, piecewise linear, and spline alternative models. However, at the current time, the efficacy of the AIC in this context has not been assessed. The authors investigated AIC as a means of comparing competing dose-response models, using data from Cook County, Illinois, for the period 1987-2000. They found that if nonlinearities exist, the AIC is not always successful in detecting them. In a number of the scenarios considered, AIC was equivocal, picking the correct simulated dose-response model about half of the time. These findings suggest that further research into the shape of the dose-response relation using alternative model selection criteria may be warranted.

The development of personal models of diabetes in the first 2 years after diagnosis: a prospective longitudinal study.

PubMed

Lawson, V L; Bundy, C; Harvey, J N

2008-04-01

Personal models of diabetes comprise beliefs about symptoms, treatment effectiveness, consequences and emotional responses to possible future complications. They are associated with, and influence, self-care behaviour. Little work has examined potential influences on the development and maintenance of personal models. The aims of this study were: (i) to assess changes in personal models over 2 years from diagnosis of diabetes; and (ii) to examine the relative contributions of health threat communication (at diagnosis, since diagnosis, during follow-up care) and personality to personal models of diabetes 2 years post-diagnosis. Newly diagnosed patients were interviewed at diagnosis (< 3 months; time 1) and 6 months (time 2), 1 year (time 3) and 2 years (time 4) after diagnosis. Data were available for 158 patients at time 1 (32 Type 1 patients and 126 Type 2 patients), 147 at time 2, 142 at time 3 and 138 at time 4. Perceptions of symptoms, consequences, course and control of diabetes remained stable over time. Emotional responses decreased and illness coherence (perceived understanding) increased over time. Health threat communication was a stronger predictor of personal models than personality. Emotional responses to diabetes 2 years after diagnosis were predicted by perceptions of a threatening health message (at diagnosis 18%, at follow-up 5%). Health threat communication predicted perceptions of serious consequences (at diagnosis 5%, at follow-up 9%). Perceptions of a reassuring message during follow-up were related to beliefs of treatment effectiveness (26%). The communication of information and the way it is perceived is an important determinant of the patient's view of their diabetes. The initial effects of the education process at diagnosis persisted 2 years after diagnosis.

First passage time: Connecting random walks to functional responses in heterogeneous environments (Invited)

NASA Astrophysics Data System (ADS)

Lewis, M. A.; McKenzie, H.; Merrill, E.

2010-12-01

In this talk I will outline first passage time analysis for animals undertaking complex movement patterns, and will demonstrate how first passage time can be used to derive functional responses in predator prey systems. The result is a new approach to understanding type III functional responses based on a random walk model. I will extend the analysis to heterogeneous environments to assess the effects of linear features on functional responses in wolves and elk using GPS tracking data.

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.

Conflict Resolution as Near-Threshold Decision-Making: A Spiking Neural Circuit Model with Two-Stage Competition for Antisaccadic Task

PubMed Central

Wang, Xiao-Jing

2016-01-01

Automatic responses enable us to react quickly and effortlessly, but they often need to be inhibited so that an alternative, voluntary action can take place. To investigate the brain mechanism of controlled behavior, we investigated a biologically-based network model of spiking neurons for inhibitory control. In contrast to a simple race between pro- versus anti-response, our model incorporates a sensorimotor remapping module, and an action-selection module endowed with a “Stop” process through tonic inhibition. Both are under the modulation of rule-dependent control. We tested the model by applying it to the well known antisaccade task in which one must suppress the urge to look toward a visual target that suddenly appears, and shift the gaze diametrically away from the target instead. We found that the two-stage competition is crucial for reproducing the complex behavior and neuronal activity observed in the antisaccade task across multiple brain regions. Notably, our model demonstrates two types of errors: fast and slow. Fast errors result from failing to inhibit the quick automatic responses and therefore exhibit very short response times. Slow errors, in contrast, are due to incorrect decisions in the remapping process and exhibit long response times comparable to those of correct antisaccade responses. The model thus reveals a circuit mechanism for the empirically observed slow errors and broad distributions of erroneous response times in antisaccade. Our work suggests that selecting between competing automatic and voluntary actions in behavioral control can be understood in terms of near-threshold decision-making, sharing a common recurrent (attractor) neural circuit mechanism with discrimination in perception. PMID:27551824

Conflict Resolution as Near-Threshold Decision-Making: A Spiking Neural Circuit Model with Two-Stage Competition for Antisaccadic Task.

PubMed

Lo, Chung-Chuan; Wang, Xiao-Jing

2016-08-01

Automatic responses enable us to react quickly and effortlessly, but they often need to be inhibited so that an alternative, voluntary action can take place. To investigate the brain mechanism of controlled behavior, we investigated a biologically-based network model of spiking neurons for inhibitory control. In contrast to a simple race between pro- versus anti-response, our model incorporates a sensorimotor remapping module, and an action-selection module endowed with a "Stop" process through tonic inhibition. Both are under the modulation of rule-dependent control. We tested the model by applying it to the well known antisaccade task in which one must suppress the urge to look toward a visual target that suddenly appears, and shift the gaze diametrically away from the target instead. We found that the two-stage competition is crucial for reproducing the complex behavior and neuronal activity observed in the antisaccade task across multiple brain regions. Notably, our model demonstrates two types of errors: fast and slow. Fast errors result from failing to inhibit the quick automatic responses and therefore exhibit very short response times. Slow errors, in contrast, are due to incorrect decisions in the remapping process and exhibit long response times comparable to those of correct antisaccade responses. The model thus reveals a circuit mechanism for the empirically observed slow errors and broad distributions of erroneous response times in antisaccade. Our work suggests that selecting between competing automatic and voluntary actions in behavioral control can be understood in terms of near-threshold decision-making, sharing a common recurrent (attractor) neural circuit mechanism with discrimination in perception.

Leveraging First Response Time into the Knowledge Tracing Model

ERIC Educational Resources Information Center

Wang, Yutao; Heffernan, Neil T.

2012-01-01

The field of educational data mining has been using the Knowledge Tracing model, which only look at the correctness of student first response, for tracking student knowledge. Recently, lots of other features are studied to extend the Knowledge Tracing model to better model student knowledge. The goal of this paper is to analyze whether or not the…

Global response of the ionosphere to atmospheric tides forced from below: Comparison between COSMIC measurements and simulations by atmosphere-ionosphere coupled model GAIA

NASA Astrophysics Data System (ADS)

Pancheva, D.; Miyoshi, Y.; Mukhtarov, P.; Jin, H.; Shinagawa, H.; Fujiwara, H.

2012-07-01

This paper for the first time presents a detailed comparison between simulated and observed global electron density responses to different atmospheric tides forced from below. The recently developed Earth's whole atmospheric model from the troposphere to the ionosphere, called GAIA, has been used for the simulation of the electron density tidal responses. They have been compared with the extracted from the COSMIC electron density data tidal responses for the period of time October 2007 to March 2009. Particular attention has been paid to the nonmigrating DE3/DE2 and migrating DW1, SW2 and TW3 electron density responses. The GAIA model reproduced quite well the COSMIC DE3/DE2 responses. Both simulations and observations revealed three altitude regions of enhanced electron density responses: (1) an upper level response, above 300 km height, apparently shaped mainly by the “fountain effect” (2) a response located near altitudes of ˜200-270 km, and (3) a lower thermospheric response situated near 120-150 km height. A possible mechanism is suggested for explaining the two lower level responses. For the first time the GAIA model simulations supported the observational evidence found in the COSMIC measurements that the ionospheric WN4 (WN3) longitude structure is not generated only by the DE3 (DE2) tide as it has been often assumed. As regards the comparison of the migrating DW1, SW2 and TW3 responses the obtained results clearly demonstrate that the GAIA model reproduce very well of the SW2 and TW3 COSMIC electron density responses. The only main discrepancy is seen in the migrating DW1 response; the observation does not support the splitting of the simulated response at both sides of the equator. This is due mainly to the difference between the SABER and GAIA SW2 tide in the lower thermosphere as it turned out that the DW1 electron density response strongly depends on the mean features of the lower thermospheric SW2 tide.

Fast logic?: Examining the time course assumption of dual process theory.

PubMed

Bago, Bence; De Neys, Wim

2017-01-01

Influential dual process models of human thinking posit that reasoners typically produce a fast, intuitive heuristic (i.e., Type-1) response which might subsequently be overridden and corrected by slower, deliberative processing (i.e., Type-2). In this study we directly tested this time course assumption. We used a two response paradigm in which participants have to give an immediate answer and afterwards are allowed extra time before giving a final response. In four experiments we used a range of procedures (e.g., challenging response deadline, concurrent load) to knock out Type 2 processing and make sure that the initial response was intuitive in nature. Our key finding is that we frequently observe correct, logical responses as the first, immediate response. Response confidence and latency analyses indicate that these initial correct responses are given fast, with high confidence, and in the face of conflicting heuristic responses. Findings suggest that fast and automatic Type 1 processing also cues a correct logical response from the start. We sketch a revised dual process model in which the relative strength of different types of intuitions determines reasoning performance. Copyright © 2016 Elsevier B.V. All rights reserved.

A Two-Timescale Response of the Southern Ocean to Ozone Depletion: Importance of the Background State

NASA Astrophysics Data System (ADS)

Seviour, W.; Waugh, D.; Gnanadesikan, A.

2016-02-01

It has been recently suggested that the response of Southern Ocean sea-ice extent to stratospheric ozone depletion is time-dependent; that the ocean surface initially cools due to enhanced northward Ekman drift caused by a poleward shift in the eddy-driven jet, and then warms after some time due to upwelling of warm waters from below the mixed layer. It is therefore possible that ozone depletion could act to favor a short-term increase in sea-ice extent. However, many uncertainties remain in understanding this mechanism, with different models showing widely differing time-scales and magnitudes of the response. Here, we analyze an ensemble of coupled model simulations with a step-function ozone perturbation. The two-timescale response is present with an approximately 30 year initial cooling period. The response is further shown to be highly dependent upon the background ocean temperature and salinity stratification, which is influenced by both natural internal variability and the isopycnal eddy mixing parameterization. It is suggested that the majority of inter-model differences in the Southern Ocean response to ozone depletion are caused by differences in stratification.

A validation of ground ambulance pre-hospital times modeled using geographic information systems.

PubMed

Patel, Alka B; Waters, Nigel M; Blanchard, Ian E; Doig, Christopher J; Ghali, William A

2012-10-03

Evaluating geographic access to health services often requires determining the patient travel time to a specified service. For urgent care, many research studies have modeled patient pre-hospital time by ground emergency medical services (EMS) using geographic information systems (GIS). The purpose of this study was to determine if the modeling assumptions proposed through prior United States (US) studies are valid in a non-US context, and to use the resulting information to provide revised recommendations for modeling travel time using GIS in the absence of actual EMS trip data. The study sample contained all emergency adult patient trips within the Calgary area for 2006. Each record included four components of pre-hospital time (activation, response, on-scene and transport interval). The actual activation and on-scene intervals were compared with those used in published models. The transport interval was calculated within GIS using the Network Analyst extension of Esri ArcGIS 10.0 and the response interval was derived using previously established methods. These GIS derived transport and response intervals were compared with the actual times using descriptive methods. We used the information acquired through the analysis of the EMS trip data to create an updated model that could be used to estimate travel time in the absence of actual EMS trip records. There were 29,765 complete EMS records for scene locations inside the city and 529 outside. The actual median on-scene intervals were longer than the average previously reported by 7-8 minutes. Actual EMS pre-hospital times across our study area were significantly higher than the estimated times modeled using GIS and the original travel time assumptions. Our updated model, although still underestimating the total pre-hospital time, more accurately represents the true pre-hospital time in our study area. The widespread use of generalized EMS pre-hospital time assumptions based on US data may not be appropriate in a non-US context. The preference for researchers should be to use actual EMS trip records from the proposed research study area. In the absence of EMS trip data researchers should determine which modeling assumptions more accurately reflect the EMS protocols across their study area.

A Repeated Trajectory Class Model for Intensive Longitudinal Categorical Outcome

PubMed Central

Lin, Haiqun; Han, Ling; Peduzzi, Peter N.; Murphy, Terrence E.; Gill, Thomas M.; Allore, Heather G.

2014-01-01

This paper presents a novel repeated latent class model for a longitudinal response that is frequently measured as in our prospective study of older adults with monthly data on activities of daily living (ADL) for more than ten years. The proposed method is especially useful when the longitudinal response is measured much more frequently than other relevant covariates. The repeated trajectory classes represent distinct temporal patterns of the longitudinal response wherein an individual’s membership in the trajectory classes may renew or change over time. Within a trajectory class, the longitudinal response is modeled by a class-specific generalized linear mixed model. Effectively, an individual may remain in a trajectory class or switch to another as the class membership predictors are updated periodically over time. The identification of a common set of trajectory classes allows changes among the temporal patterns to be distinguished from local fluctuations in the response. An informative event such as death is jointly modeled by class-specific probability of the event through shared random effects. We do not impose the conditional independence assumption given the classes. The method is illustrated by analyzing the change over time in ADL trajectory class among 754 older adults with 70500 person-months of follow-up in the Precipitating Events Project. We also investigate the impact of jointly modeling the class-specific probability of the event on the parameter estimates in a simulation study. The primary contribution of our paper is the periodic updating of trajectory classes for a longitudinal categorical response without assuming conditional independence. PMID:24519416

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...

One-day offset in daily hydrologic modeling: An exploration of the issue in automatic model calibration

USDA-ARS?s Scientific Manuscript database

The literature of daily hydrologic modelling illustrates that daily simulation models are incapable of accurately representing hydrograph timing due to relationships between precipitation and watershed hydrologic response. For watersheds with a time of concentration less than 24 hrs and a late day p...

Adaptive Automation Design and Implementation

DTIC Science & Technology

2015-09-17

Study : Space Navigator This section demonstrates the player modeling paradigm, focusing specifically on the response generation section of the player ...human-machine system, a real-time player modeling framework for imitating a specific person’s task performance, and the Adaptive Automation System...Model . . . . . . . . . . . . . . . . . . . . . . . 13 Clustering-Based Real-Time Player Modeling . . . . . . . . . . . . . . . . . . . . . . 15 An

The diffusion decision model: theory and data for two-choice decision tasks.

PubMed

Ratcliff, Roger; McKoon, Gail

2008-04-01

The diffusion decision model allows detailed explanations of behavior in two-choice discrimination tasks. In this article, the model is reviewed to show how it translates behavioral data-accuracy, mean response times, and response time distributions-into components of cognitive processing. Three experiments are used to illustrate experimental manipulations of three components: stimulus difficulty affects the quality of information on which a decision is based; instructions emphasizing either speed or accuracy affect the criterial amounts of information that a subject requires before initiating a response; and the relative proportions of the two stimuli affect biases in drift rate and starting point. The experiments also illustrate the strong constraints that ensure the model is empirically testable and potentially falsifiable. The broad range of applications of the model is also reviewed, including research in the domains of aging and neurophysiology.

Nonlinear finite element model updating for damage identification of civil structures using batch Bayesian estimation

NASA Astrophysics Data System (ADS)

Ebrahimian, Hamed; Astroza, Rodrigo; Conte, Joel P.; de Callafon, Raymond A.

2017-02-01

This paper presents a framework for structural health monitoring (SHM) and damage identification of civil structures. This framework integrates advanced mechanics-based nonlinear finite element (FE) modeling and analysis techniques with a batch Bayesian estimation approach to estimate time-invariant model parameters used in the FE model of the structure of interest. The framework uses input excitation and dynamic response of the structure and updates a nonlinear FE model of the structure to minimize the discrepancies between predicted and measured response time histories. The updated FE model can then be interrogated to detect, localize, classify, and quantify the state of damage and predict the remaining useful life of the structure. As opposed to recursive estimation methods, in the batch Bayesian estimation approach, the entire time history of the input excitation and output response of the structure are used as a batch of data to estimate the FE model parameters through a number of iterations. In the case of non-informative prior, the batch Bayesian method leads to an extended maximum likelihood (ML) estimation method to estimate jointly time-invariant model parameters and the measurement noise amplitude. The extended ML estimation problem is solved efficiently using a gradient-based interior-point optimization algorithm. Gradient-based optimization algorithms require the FE response sensitivities with respect to the model parameters to be identified. The FE response sensitivities are computed accurately and efficiently using the direct differentiation method (DDM). The estimation uncertainties are evaluated based on the Cramer-Rao lower bound (CRLB) theorem by computing the exact Fisher Information matrix using the FE response sensitivities with respect to the model parameters. The accuracy of the proposed uncertainty quantification approach is verified using a sampling approach based on the unscented transformation. Two validation studies, based on realistic structural FE models of a bridge pier and a moment resisting steel frame, are performed to validate the performance and accuracy of the presented nonlinear FE model updating approach and demonstrate its application to SHM. These validation studies show the excellent performance of the proposed framework for SHM and damage identification even in the presence of high measurement noise and/or way-out initial estimates of the model parameters. Furthermore, the detrimental effects of the input measurement noise on the performance of the proposed framework are illustrated and quantified through one of the validation studies.

A model of the formation of illusory conjunctions in the time domain.

PubMed

Botella, J; Suero, M; Barriopedro, M I

2001-12-01

The authors present a model to account for the miscombination of features when stimuli are presented using the rapid serial visual presentation (RSVP) technique (illusory conjunctions in the time domain). It explains the distributions of responses through a mixture of trial outcomes. In some trials, attention is successfully focused on the target, whereas in others, the responses are based on partial information. Two experiments are presented that manipulated the mean processing time of the target-defining dimension and of the to-be-reported dimension, respectively. As predicted, the average origin of the responses is delayed when lengthening the target-defining dimension, whereas it is earlier when lengthening the to-be-reported dimension; in the first case the number of correct responses is dramatically reduced, whereas in the second it does not change. The results, a review of other research, and simulations carried out with a formal version of the model are all in close accordance with the predictions.

The episodic random utility model unifies time trade-off and discrete choice approaches in health state valuation

PubMed Central

Craig, Benjamin M; Busschbach, Jan JV

2009-01-01

Background To present an episodic random utility model that unifies time trade-off and discrete choice approaches in health state valuation. Methods First, we introduce two alternative random utility models (RUMs) for health preferences: the episodic RUM and the more common instant RUM. For the interpretation of time trade-off (TTO) responses, we show that the episodic model implies a coefficient estimator, and the instant model implies a mean slope estimator. Secondly, we demonstrate these estimators and the differences between the estimates for 42 health states using TTO responses from the seminal Measurement and Valuation in Health (MVH) study conducted in the United Kingdom. Mean slopes are estimates with and without Dolan's transformation of worse-than-death (WTD) responses. Finally, we demonstrate an exploded probit estimator, an extension of the coefficient estimator for discrete choice data that accommodates both TTO and rank responses. Results By construction, mean slopes are less than or equal to coefficients, because slopes are fractions and, therefore, magnify downward errors in WTD responses. The Dolan transformation of WTD responses causes mean slopes to increase in similarity to coefficient estimates, yet they are not equivalent (i.e., absolute mean difference = 0.179). Unlike mean slopes, coefficient estimates demonstrate strong concordance with rank-based predictions (Lin's rho = 0.91). Combining TTO and rank responses under the exploded probit model improves the identification of health state values, decreasing the average width of confidence intervals from 0.057 to 0.041 compared to TTO only results. Conclusion The episodic RUM expands upon the theoretical framework underlying health state valuation and contributes to health econometrics by motivating the selection of coefficient and exploded probit estimators for the analysis of TTO and rank responses. In future MVH surveys, sample size requirements may be reduced through the incorporation of multiple responses under a single estimator. PMID:19144115

The stochastic dance of early HIV infection

NASA Astrophysics Data System (ADS)

Merrill, Stephen J.

2005-12-01

The stochastic nature of early HIV infection is described in a series of models, each of which captures aspects of the dance of HIV during the early stages of infection. It is to this highly variable target that the immune response must respond. The adaptability of the various components of the immune response is an important aspect of the system's operation, as the nature of the pathogens that the response will be required to respond to and the order in which those responses must be made cannot be known beforehand. As HIV infection has direct influence over cells responsible for the immune response, the dance predicts that the immune response will be also in a variable state of readiness and capability for this task of adaptation. The description of the stochastic dance of HIV here will use the tools of stochastic models, and for the most part, simulation. The justification for this approach is that the early stages and the development of HIV diversity require that the model to be able to describe both individual sample path and patient-to-patient variability. In addition, as early viral dynamics are best described using branching processes, the explosive growth of these models both predicts high variability and rapid response of HIV to changes in system parameters.In this paper, a basic viral growth model based on a time dependent continuous-time branching process is used to describe the growth of HIV infected cells in the macrophage and lymphocyte populations. Immigration from the reservoir population is added to the basic model to describe the incubation time distribution. This distribution is deduced directly from the modeling assumptions and the model of viral growth. A system of two branching processes, one in the infected macrophage population and one in the infected lymphocyte population is used to provide a description of the relationship between the development of HIV diversity as it relates to tropism (host cell preference). The role of the immune response to HIV and HIV infected cells is used to describe the movement of the infection from a few infected macrophages to a disease of infected CD4+ T lymphocytes.

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.

A model-free method for mass spectrometer response correction. [for oxygen consumption and cardiac output calculation

NASA Technical Reports Server (NTRS)

Shykoff, Barbara E.; Swanson, Harvey T.

1987-01-01

A new method for correction of mass spectrometer output signals is described. Response-time distortion is reduced independently of any model of mass spectrometer behavior. The delay of the system is found first from the cross-correlation function of a step change and its response. A two-sided time-domain digital correction filter (deconvolution filter) is generated next from the same step response data using a regression procedure. Other data are corrected using the filter and delay. The mean squared error between a step response and a step is reduced considerably more after the use of a deconvolution filter than after the application of a second-order model correction. O2 consumption and CO2 production values calculated from data corrupted by a simulated dynamic process return to near the uncorrupted values after correction. Although a clean step response or the ensemble average of several responses contaminated with noise is needed for the generation of the filter, random noise of magnitude not above 0.5 percent added to the response to be corrected does not impair the correction severely.

Performance Dependences of Multiplication Layer Thickness for InP/InGaAs Avalanche Photodiodes Based on Time Domain Modeling

NASA Technical Reports Server (NTRS)

Xiao, Yegao; Bhat, Ishwara; Abedin, M. Nurul

2005-01-01

InP/InGaAs avalanche photodiodes (APDs) are being widely utilized in optical receivers for modern long haul and high bit-rate optical fiber communication systems. The separate absorption, grading, charge, and multiplication (SAGCM) structure is an important design consideration for APDs with high performance characteristics. Time domain modeling techniques have been previously developed to provide better understanding and optimize design issues by saving time and cost for the APD research and development. In this work, performance dependences on multiplication layer thickness have been investigated by time domain modeling. These performance characteristics include breakdown field and breakdown voltage, multiplication gain, excess noise factor, frequency response and bandwidth etc. The simulations are performed versus various multiplication layer thicknesses with certain fixed values for the areal charge sheet density whereas the values for the other structure and material parameters are kept unchanged. The frequency response is obtained from the impulse response by fast Fourier transformation. The modeling results are presented and discussed, and design considerations, especially for high speed operation at 10 Gbit/s, are further analyzed.

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.

Stochastic Car-Following Model for Explaining Nonlinear Traffic Phenomena

NASA Astrophysics Data System (ADS)

Meng, Jianping; Song, Tao; Dong, Liyun; Dai, Shiqiang

There is a common time parameter for representing the sensitivity or the lag (response) time of drivers in many car-following models. In the viewpoint of traffic psychology, this parameter could be considered as the perception-response time (PRT). Generally, this parameter is set to be a constant in previous models. However, PRT is actually not a constant but a random variable described by the lognormal distribution. Thus the probability can be naturally introduced into car-following models by recovering the probability of PRT. For demonstrating this idea, a specific stochastic model is constructed based on the optimal velocity model. By conducting simulations under periodic boundary conditions, it is found that some important traffic phenomena, such as the hysteresis and phantom traffic jams phenomena, can be reproduced more realistically. Especially, an interesting experimental feature of traffic jams, i.e., two moving jams propagating in parallel with constant speed stably and sustainably, is successfully captured by the present model.

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.

The influence of physical and cognitive factors on reactive agility performance in men basketball players.

PubMed

Scanlan, Aaron; Humphries, Brendan; Tucker, Patrick S; Dalbo, Vincent

2014-01-01

This study explored the influence of physical and cognitive measures on reactive agility performance in basketball players. Twelve men basketball players performed multiple sprint, Change of Direction Speed Test, and Reactive Agility Test trials. Pearson's correlation analyses were used to determine relationships between the predictor variables (stature, mass, body composition, 5-m, 10-m and 20-m sprint times, peak speed, closed-skill agility time, response time and decision-making time) and reactive agility time (response variable). Simple and stepwise regression analyses determined the individual influence of each predictor variable and the best predictor model for reactive agility time. Morphological (r = -0.45 to 0.19), sprint (r = -0.40 to 0.41) and change-of-direction speed measures (r = 0.43) had small to moderate correlations with reactive agility time. Response time (r = 0.76, P = 0.004) and decision-making time (r = 0.58, P = 0.049) had large to very large relationships with reactive agility time. Response time was identified as the sole predictor variable for reactive agility time in the stepwise model (R(2) = 0.58, P = 0.004). In conclusion, cognitive measures had the greatest influence on reactive agility performance in men basketball players. These findings suggest reaction and decision-making drills should be incorporated in basketball training programmes.

Fast Electrically Driven Capillary Rise Using Overdrive Voltage.

PubMed

Hong, Sung Jin; Hong, Jiwoo; Seo, Hee Won; Lee, Sang Joon; Chung, Sang Kug

2015-12-29

Enhancement of response speed (or reduction of response time) is crucial for the commercialization of devices based on electrowetting (EW), such as liquid lenses and reflective displays, and presents one of the main challenges in EW research studies. We demonstrate here that an overdrive EW actuation gives rise to a faster rise of a liquid column between parallel electrodes, compared to a DC EW actuation. Here, DC actuation is actually a simple applied step function, and overdrive is an applied step followed by reduction to a lower voltage. Transient behaviors and response time (i.e., the time required to reach the equilibrium height) of the rising liquid column are explored under different DC and overdrive EW actuations. When the liquid column rises up to a target height by means of an overdrive EW, the response time is reduced to as low as 1/6 of the response time using DC EW. We develop a theoretical model to simulate the EW-driven capillary rise by combining the kinetic equation of capillary flow (i.e., Lucas-Washburn equation) and the dynamic contact angle model considering contact line friction, contact angle hysteresis, contact angle saturation, and the EW effect. This theoretical model accurately predicts the outcome to within a ± 5% error in regard to the rising behaviors of the liquid column with a low viscosity, under both DC EW and overdrive actuation conditions, except for the early stage (

Effect of space flight on interferon production - mechanistic studies

NASA Technical Reports Server (NTRS)

Sonnenfeld, Gerald

1991-01-01

Ground-based models were studied for the effects of space flight on immune responses. Most time was spent on the model for the antiorthostatic, hypokinetic, hypodynamic suspension model for rats. Results indicate that suspension is useful for modeling the effects of spaceflight on functional immune responses, such as interferon and interleukin production. It does not appear to be useful for modeling shifts in leukocyte sub-populations. Calcium and 1,25-dihydroxyvitamin D sub 3 appear to play a pivitol role in regulating shifts in immune responses due to suspension. The macrophage appears to be an important target cell for the effects of suspension on immune responses.

RRAWFLOW: Rainfall-Response Aquifer and Watershed Flow Model (v1.15)

NASA Astrophysics Data System (ADS)

Long, A. J.

2015-03-01

The Rainfall-Response Aquifer and Watershed Flow Model (RRAWFLOW) is a lumped-parameter model that simulates streamflow, spring flow, groundwater level, or solute transport for a measurement point in response to a system input of precipitation, recharge, or solute injection. I introduce the first version of RRAWFLOW available for download and public use and describe additional options. The open-source code is written in the R language and is available at http://sd.water.usgs.gov/projects/RRAWFLOW/RRAWFLOW.html along with an example model of streamflow. RRAWFLOW includes a time-series process to estimate recharge from precipitation and simulates the response to recharge by convolution, i.e., the unit-hydrograph approach. Gamma functions are used for estimation of parametric impulse-response functions (IRFs); a combination of two gamma functions results in a double-peaked IRF. A spline fit to a set of control points is introduced as a new method for estimation of nonparametric IRFs. Several options are included to simulate time-variant systems. For many applications, lumped models simulate the system response with equal accuracy to that of distributed models, but moreover, the ease of model construction and calibration of lumped models makes them a good choice for many applications (e.g., estimating missing periods in a hydrologic record). RRAWFLOW provides professional hydrologists and students with an accessible and versatile tool for lumped-parameter modeling.

Finite-time hybrid projective synchronization of the drive-response complex networks with distributed-delay via adaptive intermittent control

NASA Astrophysics Data System (ADS)

Cheng, Lin; Yang, Yongqing; Li, Li; Sui, Xin

2018-06-01

This paper studies the finite-time hybrid projective synchronization of the drive-response complex networks. In the model, general transmission delays and distributed delays are also considered. By designing the adaptive intermittent controllers, the response network can achieve hybrid projective synchronization with the drive system in finite time. Based on finite-time stability theory and several differential inequalities, some simple finite-time hybrid projective synchronization criteria are derived. Two numerical examples are given to illustrate the effectiveness of the proposed method.

LIMO EEG: a toolbox for hierarchical LInear MOdeling of ElectroEncephaloGraphic data.

PubMed

Pernet, Cyril R; Chauveau, Nicolas; Gaspar, Carl; Rousselet, Guillaume A

2011-01-01

Magnetic- and electric-evoked brain responses have traditionally been analyzed by comparing the peaks or mean amplitudes of signals from selected channels and averaged across trials. More recently, tools have been developed to investigate single trial response variability (e.g., EEGLAB) and to test differences between averaged evoked responses over the entire scalp and time dimensions (e.g., SPM, Fieldtrip). LIMO EEG is a Matlab toolbox (EEGLAB compatible) to analyse evoked responses over all space and time dimensions, while accounting for single trial variability using a simple hierarchical linear modelling of the data. In addition, LIMO EEG provides robust parametric tests, therefore providing a new and complementary tool in the analysis of neural evoked responses.

LIMO EEG: A Toolbox for Hierarchical LInear MOdeling of ElectroEncephaloGraphic Data

PubMed Central

Pernet, Cyril R.; Chauveau, Nicolas; Gaspar, Carl; Rousselet, Guillaume A.

2011-01-01

Magnetic- and electric-evoked brain responses have traditionally been analyzed by comparing the peaks or mean amplitudes of signals from selected channels and averaged across trials. More recently, tools have been developed to investigate single trial response variability (e.g., EEGLAB) and to test differences between averaged evoked responses over the entire scalp and time dimensions (e.g., SPM, Fieldtrip). LIMO EEG is a Matlab toolbox (EEGLAB compatible) to analyse evoked responses over all space and time dimensions, while accounting for single trial variability using a simple hierarchical linear modelling of the data. In addition, LIMO EEG provides robust parametric tests, therefore providing a new and complementary tool in the analysis of neural evoked responses. PMID:21403915

3D time-domain airborne EM modeling for an arbitrarily anisotropic earth

NASA Astrophysics Data System (ADS)

Yin, Changchun; Qi, Yanfu; Liu, Yunhe

2016-08-01

Time-domain airborne EM data is currently interpreted based on an isotropic model. Sometimes, it can be problematic when working in the region with distinct dipping stratifications. In this paper, we simulate the 3D time-domain airborne EM responses over an arbitrarily anisotropic earth with topography by edge-based finite-element method. Tetrahedral meshes are used to describe the abnormal bodies with complicated shapes. We further adopt the Backward Euler scheme to discretize the time-domain diffusion equation for electric field, obtaining an unconditionally stable linear equations system. We verify the accuracy of our 3D algorithm by comparing with 1D solutions for an anisotropic half-space. Then, we switch attentions to effects of anisotropic media on the strengths and the diffusion patterns of time-domain airborne EM responses. For numerical experiments, we adopt three typical anisotropic models: 1) an anisotropic anomalous body embedded in an isotropic half-space; 2) an isotropic anomalous body embedded in an anisotropic half-space; 3) an anisotropic half-space with topography. The modeling results show that the electric anisotropy of the subsurface media has big effects on both the strengths and the distribution patterns of time-domain airborne EM responses; this effect needs to be taken into account when interpreting ATEM data in areas with distinct anisotropy.

Hierarchical Bayes Models for Response Time Data

ERIC Educational Resources Information Center

Craigmile, Peter F.; Peruggia, Mario; Van Zandt, Trisha

2010-01-01

Human response time (RT) data are widely used in experimental psychology to evaluate theories of mental processing. Typically, the data constitute the times taken by a subject to react to a succession of stimuli under varying experimental conditions. Because of the sequential nature of the experiments there are trends (due to learning, fatigue,…

Time- and Space-Order Effects in Timed Discrimination of Brightness and Size of Paired Visual Stimuli

ERIC Educational Resources Information Center

Patching, Geoffrey R.; Englund, Mats P.; Hellstrom, Ake

2012-01-01

Despite the importance of both response probability and response time for testing models of choice, there is a dearth of chronometric studies examining systematic asymmetries that occur over time- and space-orders in the method of paired comparisons. In this study, systematic asymmetries in discriminating the magnitude of paired visual stimuli are…

Theory, Solution Methods, and Implementation of the HERMES Model

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

Reaugh, John E.; White, Bradley W.; Curtis, John P.

The HERMES (high explosive response to mechanical stimulus) model was developed over the past decade to enable computer simulation of the mechanical and subsequent energetic response of explosives and propellants to mechanical insults such as impacts, perforations, drops, and falls. The model is embedded in computer simulation programs that solve the non-linear, large deformation equations of compressible solid and fluid flow in space and time. It is implemented as a user-defined model, which returns the updated stress tensor and composition that result from the simulation supplied strain tensor change. Although it is multi-phase, in that gas and solid species aremore » present, it is single-velocity, in that the gas does not flow through the porous solid. More than 70 time-dependent variables are made available for additional analyses and plotting. The model encompasses a broad range of possible responses: mechanical damage with no energetic response, and a continuous spectrum of degrees of violence including delayed and prompt detonation. This paper describes the basic workings of the model.« less

A semi-parametric within-subject mixture approach to the analyses of responses and response times.

PubMed

Molenaar, Dylan; Bolsinova, Maria; Vermunt, Jeroen K

2018-05-01

In item response theory, modelling the item response times in addition to the item responses may improve the detection of possible between- and within-subject differences in the process that resulted in the responses. For instance, if respondents rely on rapid guessing on some items but not on all, the joint distribution of the responses and response times will be a multivariate within-subject mixture distribution. Suitable parametric methods to detect these within-subject differences have been proposed. In these approaches, a distribution needs to be assumed for the within-class response times. In this paper, it is demonstrated that these parametric within-subject approaches may produce false positives and biased parameter estimates if the assumption concerning the response time distribution is violated. A semi-parametric approach is proposed which resorts to categorized response times. This approach is shown to hardly produce false positives and parameter bias. In addition, the semi-parametric approach results in approximately the same power as the parametric approach. © 2017 The British Psychological Society.

An organizational metamodel for hospital emergency departments.

PubMed

Kaptan, Kubilay

2014-10-01

I introduce an organizational model describing the response of the hospital emergency department. The hybrid simulation/analytical model (called a "metamodel") can estimate a hospital's capacity and dynamic response in real time and incorporate the influence of damage to structural and nonstructural components on the organizational ones. The waiting time is the main parameter of response and is used to evaluate the disaster resilience of health care facilities. Waiting time behavior is described by using a double exponential function and its parameters are calibrated based on simulated data. The metamodel covers a large range of hospital configurations and takes into account hospital resources in terms of staff and infrastructures, operational efficiency, and the possible existence of an emergency plan; maximum capacity; and behavior both in saturated and overcapacitated conditions. The sensitivity of the model to different arrival rates, hospital configurations, and capacities and the technical and organizational policies applied during and before a disaster were investigated. This model becomes an important tool in the decision process either for the engineering profession or for policy makers.

Nonlinear Maps for Design of Discrete-Time Models of Neuronal Network Dynamics

DTIC Science & Technology

2016-03-31

2016 Performance/Technic~ 03-01-2016- 03-31-2016 4. TITLE AND SUBTITLE Sa. CONTRACT NUMBER Nonlinear Maps for Design of Discrete -Time Models of...simulations is to design a neuronal model in the form of difference equations that generates neuronal states in discrete moments of time. In this...responsive tiring patterns. We propose to use modern DSP ideas to develop new efficient approaches to the design of such discrete -time models for

Qualitative analysis of a stochastic epidemic model with specific functional response and temporary immunity

NASA Astrophysics Data System (ADS)

Hattaf, Khalid; Mahrouf, Marouane; Adnani, Jihad; Yousfi, Noura

2018-01-01

In this paper, we propose a stochastic delayed epidemic model with specific functional response. The time delay represents temporary immunity period, i.e., time from recovery to becoming susceptible again. We first show that the proposed model is mathematically and biologically well-posed. Moreover, the extinction of the disease and the persistence in the mean are established in the terms of a threshold value R0S which is smaller than the basic reproduction number R0 of the corresponding deterministic system.

Numerical modelling of landscape and sediment flux response to precipitation rate change

NASA Astrophysics Data System (ADS)

Armitage, John J.; Whittaker, Alexander C.; Zakari, Mustapha; Campforts, Benjamin

2018-02-01

Laboratory-scale experiments of erosion have demonstrated that landscapes have a natural (or intrinsic) response time to a change in precipitation rate. In the last few decades there has been growth in the development of numerical models that attempt to capture landscape evolution over long timescales. However, there is still an uncertainty regarding the validity of the basic assumptions of mass transport that are made in deriving these models. In this contribution we therefore return to a principal assumption of sediment transport within the mass balance for surface processes; we explore the sensitivity of the classic end-member landscape evolution models and the sediment fluxes they produce to a change in precipitation rates. One end-member model takes the mathematical form of a kinetic wave equation and is known as the stream power model, in which sediment is assumed to be transported immediately out of the model domain. The second end-member model is the transport model and it takes the form of a diffusion equation, assuming that the sediment flux is a function of the water flux and slope. We find that both of these end-member models have a response time that has a proportionality to the precipitation rate that follows a negative power law. However, for the stream power model the exponent on the water flux term must be less than one, and for the transport model the exponent must be greater than one, in order to match the observed concavity of natural systems. This difference in exponent means that the transport model generally responds more rapidly to an increase in precipitation rates, on the order of 105 years for post-perturbation sediment fluxes to return to within 50 % of their initial values, for theoretical landscapes with a scale of 100×100 km. Additionally from the same starting conditions, the amplitude of the sediment flux perturbation in the transport model is greater, with much larger sensitivity to catchment size. An important finding is that both models respond more quickly to a wetting event than a drying event, and we argue that this asymmetry in response time has significant implications for depositional stratigraphies. Finally, we evaluate the extent to which these constraints on response times and sediment fluxes from simple models help us understand the geological record of landscape response to rapid environmental changes in the past, such as the Paleocene-Eocene thermal maximum (PETM). In the Spanish Pyrenees, for instance, a relatively rapid (10 to 50 kyr) duration of the deposition of gravel is observed for a climatic shift that is thought to be towards increased precipitation rates. We suggest that the rapid response observed is more easily explained through a diffusive transport model because (1) the model has a faster response time, which is consistent with the documented stratigraphic data, (2) there is a high-amplitude spike in sediment flux, and (3) the assumption of instantaneous transport is difficult to justify for the transport of large grain sizes as an alluvial bedload. Consequently, while these end-member models do not reproduce all the complexity of processes seen in real landscapes, we argue that variations in long-term erosional dynamics within source catchments can fundamentally control when, how, and where sedimentary archives can record past environmental change.

Submillisecond-response and scattering-free infrared liquid crystal phase modulators.

PubMed

Sun, Jie; Chen, Yuan; Wu, Shin-Tson

2012-08-27

We demonstrate a submillisecond-response and scattering-free infrared phase modulator using a polymer network liquid crystal (PNLC). The required voltage for achieving 2π phase change at λ = 1.06 µm is 70V (or 5.8 V/μm) and the measured response time is ~200 µs at 25°C and 30 µs at 70°C. Opposite to our conventional understanding, a high viscosity LC helps to achieve small domain size during polymerization process, which in turn reduces the response time and light scattering. We use Rayleigh-Gans-Debye scattering model to analyze the voltage-on state transmission spectra. When the domain size is comparable to the wavelength, the model fits with experimental results well. But when the domain size is smaller than the wavelength, the simple Rayleigh model works well.

Modeling Pacing Behavior and Test Speededness Using Latent Growth Curve Models

ERIC Educational Resources Information Center

Kahraman, Nilufer; Cuddy, Monica M.; Clauser, Brian E.

2013-01-01

This research explores the usefulness of latent growth curve modeling in the study of pacing behavior and test speededness. Examinee response times from a high-stakes, computerized examination, collected before and after the examination was subjected to a timing change, were analyzed using a series of latent growth curve models to detect…

Comparing model-based adaptive LMS filters and a model-free hysteresis loop analysis method for structural health monitoring

NASA Astrophysics Data System (ADS)

Zhou, Cong; Chase, J. Geoffrey; Rodgers, Geoffrey W.; Xu, Chao

2017-02-01

The model-free hysteresis loop analysis (HLA) method for structural health monitoring (SHM) has significant advantages over the traditional model-based SHM methods that require a suitable baseline model to represent the actual system response. This paper provides a unique validation against both an experimental reinforced concrete (RC) building and a calibrated numerical model to delineate the capability of the model-free HLA method and the adaptive least mean squares (LMS) model-based method in detecting, localizing and quantifying damage that may not be visible, observable in overall structural response. Results clearly show the model-free HLA method is capable of adapting to changes in how structures transfer load or demand across structural elements over time and multiple events of different size. However, the adaptive LMS model-based method presented an image of greater spread of lesser damage over time and story when the baseline model is not well defined. Finally, the two algorithms are tested over a simpler hysteretic behaviour typical steel structure to quantify the impact of model mismatch between the baseline model used for identification and the actual response. The overall results highlight the need for model-based methods to have an appropriate model that can capture the observed response, in order to yield accurate results, even in small events where the structure remains linear.

Numerical analysis of multicomponent responses of surface-hole transient electromagnetic method

NASA Astrophysics Data System (ADS)

Meng, Qing-Xin; Hu, Xiang-Yun; Pan, He-Ping; Zhou, Feng

2017-03-01

We calculate the multicomponent responses of surface-hole transient electromagnetic method. The methods and models are unsuitable as geoelectric models of conductive surrounding rocks because they are based on regular local targets. We also propose a calculation and analysis scheme based on numerical simulations of the subsurface transient electromagnetic fields. In the modeling of the electromagnetic fields, the forward modeling simulations are performed by using the finite-difference time-domain method and the discrete image method, which combines the Gaver-Stehfest inverse Laplace transform with the Prony method to solve the initial electromagnetic fields. The precision in the iterative computations is ensured by using the transmission boundary conditions. For the response analysis, we customize geoelectric models consisting of near-borehole targets and conductive wall rocks and implement forward modeling simulations. The observed electric fields are converted into induced electromotive force responses using multicomponent observation devices. By comparing the transient electric fields and multicomponent responses under different conditions, we suggest that the multicomponent-induced electromotive force responses are related to the horizontal and vertical gradient variations of the transient electric field at different times. The characteristics of the response are determined by the varying the subsurface transient electromagnetic fields, i.e., diffusion, attenuation and distortion, under different conditions as well as the electromagnetic fields at the observation positions. The calculation and analysis scheme of the response consider the surrounding rocks and the anomalous field of the local targets. It therefore can account for the geological data better than conventional transient field response analysis of local targets.

The Effect of Ongoing Exposure Dynamics in Dose Response Relationships

PubMed Central

Pujol, Josep M.; Eisenberg, Joseph E.; Haas, Charles N.; Koopman, James S.

2009-01-01

Characterizing infectivity as a function of pathogen dose is integral to microbial risk assessment. Dose-response experiments usually administer doses to subjects at one time. Phenomenological models of the resulting data, such as the exponential and the Beta-Poisson models, ignore dose timing and assume independent risks from each pathogen. Real world exposure to pathogens, however, is a sequence of discrete events where concurrent or prior pathogen arrival affects the capacity of immune effectors to engage and kill newly arriving pathogens. We model immune effector and pathogen interactions during the period before infection becomes established in order to capture the dynamics generating dose timing effects. Model analysis reveals an inverse relationship between the time over which exposures accumulate and the risk of infection. Data from one time dose experiments will thus overestimate per pathogen infection risks of real world exposures. For instance, fitting our model to one time dosing data reveals a risk of 0.66 from 313 Cryptosporidium parvum pathogens. When the temporal exposure window is increased 100-fold using the same parameters fitted by our model to the one time dose data, the risk of infection is reduced to 0.09. Confirmation of this risk prediction requires data from experiments administering doses with different timings. Our model demonstrates that dose timing could markedly alter the risks generated by airborne versus fomite transmitted pathogens. PMID:19503605

The Behavioral Economics of Choice and Interval Timing

PubMed Central

Jozefowiez, J.; Staddon, J. E. R.; Cerutti, D. T.

2009-01-01

We propose a simple behavioral economic model (BEM) describing how reinforcement and interval timing interact. The model assumes a Weber-law-compliant logarithmic representation of time. Associated with each represented time value are the payoffs that have been obtained for each possible response. At a given real time, the response with the highest payoff is emitted. The model accounts for a wide range of data from procedures such as simple bisection, metacognition in animals, economic effects in free-operant psychophysical procedures and paradoxical choice in double-bisection procedures. Although it assumes logarithmic time representation, it can also account for data from the time-left procedure usually cited in support of linear time representation. It encounters some difficulties in complex free-operant choice procedures, such as concurrent mixed fixed-interval schedules as well as some of the data on double bisection, that may involve additional processes. Overall, BEM provides a theoretical framework for understanding how reinforcement and interval timing work together to determine choice between temporally differentiated reinforcers. PMID:19618985

Research on the effect of noise at different times of day: Models, methods and findings

NASA Technical Reports Server (NTRS)

Fields, J. M.

1985-01-01

Social surveys of residents' responses to noise at different times of day are reviewed. Some of the discrepancies in published reports about the importance of noise at different times of day are reduced when the research findings are classified according to the type of time of day reaction model, the type of time of day weight calculated and the method which is used to estimate the weight. When the estimates of nighttime weights from 12 studies are normalized, it is found that they still disagree, but do not support stronger nighttime weights than those used in existing noise indices. Challenges to common assumptions in nighttime response models are evaluated. Two of these challenges receive enough support to warrant further investigation: the impact of changes in numbers of noise events may be less at night than in the day and nighttime annoyance may be affected by noise levels in other periods. All existing social survey results in which averages of nighttime responses were plotted by nighttime noise levels are reproduced.

A High-Order, Time Invariant, Linearized Model for Application to HHCIAFCS Interaction Studies

NASA Technical Reports Server (NTRS)

Cheng, Rendy P.; Tischler, Mark B.; Celi, Roberto

2003-01-01

This paper describes a methodology for the extraction of a linear time invariant model from a nonlinear helicopter model, and followed by an examination of the interactions of the Higher Harmonic Control (HHC) and the Automatic Flight Control System (AFCS). This new method includes an embedded harmonic analyzer inside a linear time invariant model, which allows the periodicity of the helicopter response to be captured. The: coupled high-order model provides the needed level of dynamic fidelity to permit an analysis and optimization of the AFCS and HHC loops. Results of this study indicate that the closed-loop HHC system has little influence on the AFCS or on the vehicle handling qualities, which indicates that the AFCS does not need modification to work with the HHC system. The results also show that the vibration response to maneuvers must be considered during the HHC design process, which leads to much higher required HHC loop crossover frequencies. This research also demonstrates that the transient vibration response during maneuvers can be reduced by optimizing the closed-loop higher harmonic control laws using conventional control system analyses.

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.

Modeling operators' emergency response time for chemical processing operations.

PubMed

Murray, Susan L; Harputlu, Emrah; Mentzer, Ray A; Mannan, M Sam

2014-01-01

Operators have a crucial role during emergencies at a variety of facilities such as chemical processing plants. When an abnormality occurs in the production process, the operator often has limited time to either take corrective actions or evacuate before the situation becomes deadly. It is crucial that system designers and safety professionals can estimate the time required for a response before procedures and facilities are designed and operations are initiated. There are existing industrial engineering techniques to establish time standards for tasks performed at a normal working pace. However, it is reasonable to expect the time required to take action in emergency situations will be different than working at a normal production pace. It is possible that in an emergency, operators will act faster compared to a normal pace. It would be useful for system designers to be able to establish a time range for operators' response times for emergency situations. This article develops a modeling approach to estimate the time standard range for operators taking corrective actions or following evacuation procedures in emergency situations. This will aid engineers and managers in establishing time requirements for operators in emergency situations. The methodology used for this study combines a well-established industrial engineering technique for determining time requirements (predetermined time standard system) and adjustment coefficients for emergency situations developed by the authors. Numerous videos of workers performing well-established tasks at a maximum pace were studied. As an example, one of the tasks analyzed was pit crew workers changing tires as quickly as they could during a race. The operations in these videos were decomposed into basic, fundamental motions (such as walking, reaching for a tool, and bending over) by studying the videos frame by frame. A comparison analysis was then performed between the emergency pace and the normal working pace operations to determine performance coefficients. These coefficients represent the decrease in time required for various basic motions in emergency situations and were used to model an emergency response. This approach will make hazardous operations requiring operator response, alarm management, and evacuation processes easier to design and predict. An application of this methodology is included in the article. The time required for an emergency response was roughly a one-third faster than for a normal response time.

Ionospheric E-Region Response to Solar-Geomagnetic Storms Observed by TIMED/SABER and Application to IRI Storm-Model Development

NASA Technical Reports Server (NTRS)

Mertens, Christopher J.; Mast, Jeffrey C.; Winick, Jeremy R.; Russell, James M., III; Mlynczak, Martin G.; Evans, David S.

2007-01-01

The large thermospheric infrared radiance enhancements observed from the TIMED/SABER experiment during recent solar storms provide an exciting opportunity to study the influence of solar-geomagnetic disturbances on the upper atmosphere and ionosphere. In particular, nighttime enhancements of 4.3 um emission, due to vibrational excitation and radiative emission by NO+, provide an excellent proxy to study and analyze the response of the ionospheric E-region to auroral electron dosing and storm-time enhancements to the E-region electron density. In this paper we give a status report of on-going work on model and data analysis methodologies of deriving NO+ 4.3 um volume emission rates, a proxy for the storm-time E-region response, and the approach for deriving an empirical storm-time correction to International Reference Ionosphere (IRI) E-region NO+ and electron densities.

Estimation of automobile-driver describing function from highway tests using the double steering wheel

NASA Technical Reports Server (NTRS)

Delp, P.; Crossman, E. R. F. W.; Szostak, H.

1972-01-01

The automobile-driver describing function for lateral position control was estimated for three subjects from frequency response analysis of straight road test results. The measurement procedure employed an instrumented full size sedan with known steering response characteristics, and equipped with a lateral lane position measuring device based on video detection of white stripe lane markings. Forcing functions were inserted through a servo driven double steering wheel coupling the driver to the steering system proper. Random appearing, Gaussian, and transient time functions were used. The quasi-linear models fitted to the random appearing input frequency response characterized the driver as compensating for lateral position error in a proportional, derivative, and integral manner. Similar parameters were fitted to the Gabor transformed frequency response of the driver to transient functions. A fourth term corresponding to response to lateral acceleration was determined by matching the time response histories of the model to the experimental results. The time histories show evidence of pulse-like nonlinear behavior during extended response to step transients which appear as high frequency remnant power.

A deterministic and stochastic model for the system dynamics of tumor-immune responses to chemotherapy

NASA Astrophysics Data System (ADS)

Liu, Xiangdong; Li, Qingze; Pan, Jianxin

2018-06-01

Modern medical studies show that chemotherapy can help most cancer patients, especially for those diagnosed early, to stabilize their disease conditions from months to years, which means the population of tumor cells remained nearly unchanged in quite a long time after fighting against immune system and drugs. In order to better understand the dynamics of tumor-immune responses under chemotherapy, deterministic and stochastic differential equation models are constructed to characterize the dynamical change of tumor cells and immune cells in this paper. The basic dynamical properties, such as boundedness, existence and stability of equilibrium points, are investigated in the deterministic model. Extended stochastic models include stochastic differential equations (SDEs) model and continuous-time Markov chain (CTMC) model, which accounts for the variability in cellular reproduction, growth and death, interspecific competitions, and immune response to chemotherapy. The CTMC model is harnessed to estimate the extinction probability of tumor cells. Numerical simulations are performed, which confirms the obtained theoretical results.

Operational atmospheric modeling system CARIS for effective emergency response associated with hazardous chemical releases in Korea.

PubMed

Kim, Cheol-Hee; Park, Jin-Ho; Park, Cheol-Jin; Na, Jin-Gyun

2004-03-01

The Chemical Accidents Response Information System (CARIS) was developed at the Center for Chemical Safety Management in South Korea in order to track and predict the dispersion of hazardous chemicals in the case of an accident or terrorist attack involving chemical companies. The main objective of CARIS is to facilitate an efficient emergency response to hazardous chemical accidents by rapidly providing key information in the decision-making process. In particular, the atmospheric modeling system implemented in CARIS, which is composed of a real-time numerical weather forecasting model and an air pollution dispersion model, can be used as a tool to forecast concentrations and to provide a wide range of assessments associated with various hazardous chemicals in real time. This article introduces the components of CARIS and describes its operational modeling system. Some examples of the operational modeling system and its use for emergency preparedness are presented and discussed. Finally, this article evaluates the current numerical weather prediction model for Korea.

Jointly modeling longitudinal proportional data and survival times with an application to the quality of life data in a breast cancer trial.

PubMed

Song, Hui; Peng, Yingwei; Tu, Dongsheng

2017-04-01

Motivated by the joint analysis of longitudinal quality of life data and recurrence free survival times from a cancer clinical trial, we present in this paper two approaches to jointly model the longitudinal proportional measurements, which are confined in a finite interval, and survival data. Both approaches assume a proportional hazards model for the survival times. For the longitudinal component, the first approach applies the classical linear mixed model to logit transformed responses, while the second approach directly models the responses using a simplex distribution. A semiparametric method based on a penalized joint likelihood generated by the Laplace approximation is derived to fit the joint model defined by the second approach. The proposed procedures are evaluated in a simulation study and applied to the analysis of breast cancer data motivated this research.

Kinetic operational models of agonism for G-protein-coupled receptors.

PubMed

Hoare, Samuel R J; Pierre, Nicolas; Moya, Arturo Gonzalez; Larson, Brad

2018-06-07

The application of kinetics to research and therapeutic development of G-protein-coupled receptors has become increasingly valuable. Pharmacological models provide the foundation of pharmacology, providing concepts and measurable parameters such as efficacy and potency that have underlain decades of successful drug discovery. Currently there are few pharmacological models that incorporate kinetic activity in such a way as to yield experimentally-accessible drug parameters. In this study, a kinetic model of pharmacological response was developed that provides a kinetic descriptor of efficacy (the transduction rate constant, k τ ) and allows measurement of receptor-ligand binding kinetics from functional data. The model assumes: (1) receptor interacts with a precursor of the response ("Transduction potential") and converts it to the response. (2) The response can decay. Familiar response vs time plots emerge, depending on whether transduction potential is depleted and/or response decays. These are the straight line, the "association" exponential curve, and the rise-and-fall curve. Convenient, familiar methods are described for measuring the model parameters and files are provided for the curve-fitting program Prism (GraphPad Software) that can be used as a guide. The efficacy parameter k τ is straightforward to measure and accounts for receptor reserve; all that is required is measurement of response over time at a maximally-stimulating concentration of agonist. The modular nature of the model framework allows it to be extended. Here this is done to incorporate antagonist-receptor binding kinetics and slow agonist-receptor equilibration. In principle, the modular framework can incorporate other cellular processes, such as receptor desensitization. The kinetic response model described here can be applied to measure kinetic pharmacological parameters than can be used to advance the understanding of GPCR pharmacology and optimize new and improved therapeutics. Copyright © 2018 Elsevier Ltd. All rights reserved.

Adaptive Response in Female Modeling of the Hypothalamic-pituitary-gonadal Axis

EPA Science Inventory

Exposure to endocrine disrupting chemicals can affect reproduction and development in both humans and wildlife. We are developing a mechanistic computational model of the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows to predict dose-response and time-course ...

Queueing analysis of a canonical model of real-time multiprocessors

NASA Technical Reports Server (NTRS)

Krishna, C. M.; Shin, K. G.

1983-01-01

A logical classification of multiprocessor structures from the point of view of control applications is presented. A computation of the response time distribution for a canonical model of a real time multiprocessor is presented. The multiprocessor is approximated by a blocking model. Two separate models are derived: one created from the system's point of view, and the other from the point of view of an incoming task.

Dynamic Sensorimotor Planning during Long-Term Sequence Learning: The Role of Variability, Response Chunking and Planning Errors

PubMed Central

Verstynen, Timothy; Phillips, Jeff; Braun, Emily; Workman, Brett; Schunn, Christian; Schneider, Walter

2012-01-01

Many everyday skills are learned by binding otherwise independent actions into a unified sequence of responses across days or weeks of practice. Here we looked at how the dynamics of action planning and response binding change across such long timescales. Subjects (N = 23) were trained on a bimanual version of the serial reaction time task (32-item sequence) for two weeks (10 days total). Response times and accuracy both showed improvement with time, but appeared to be learned at different rates. Changes in response speed across training were associated with dynamic changes in response time variability, with faster learners expanding their variability during the early training days and then contracting response variability late in training. Using a novel measure of response chunking, we found that individual responses became temporally correlated across trials and asymptoted to set sizes of approximately 7 bound responses at the end of the first week of training. Finally, we used a state-space model of the response planning process to look at how predictive (i.e., response anticipation) and error-corrective (i.e., post-error slowing) processes correlated with learning rates for speed, accuracy and chunking. This analysis yielded non-monotonic association patterns between the state-space model parameters and learning rates, suggesting that different parts of the response planning process are relevant at different stages of long-term learning. These findings highlight the dynamic modulation of response speed, variability, accuracy and chunking as multiple movements become bound together into a larger set of responses during sequence learning. PMID:23056630

On cell resistance and immune response time lag in a model for the HIV infection

NASA Astrophysics Data System (ADS)

Solovey, Guillermo; Peruani, Fernando; Ponce Dawson, Silvina; Maria Zorzenon dos Santos, Rita

2004-11-01

Recently, a cellular automata model has been introduced (Phys. Rev. Lett. 87 (2001) 168102) to describe the spread of the HIV infection among target cells in lymphoid tissues. The model reproduces qualitatively the entire course of the infection displaying, in particular, the two time scales that characterize its dynamics. In this work, we investigate the robustness of the model against changes in three of its parameters. Two of them are related to the resistance of the cells to get infected. The other one describes the time interval necessary to mount specific immune responses. We have observed that an increase of the cell resistance, at any stage of the infection, leads to a reduction of the latency period, i.e., of the time interval between the primary infection and the onset of AIDS. However, during the early stages of the infection, when the cell resistance increase is combined with an increase in the initial concentration of infected cells, the original behavior is recovered. Therefore we find a long and a short latency regime (eight and one year long, respectively) depending on the value of the cell resistance. We have obtained, on the other hand, that changes on the parameter that describes the immune system time lag affects the time interval during which the primary infection occurs. Using different extended versions of the model, we also discuss how the two-time scale dynamics is affected when we include inhomogeneities on the cells properties, as for instance, on the cell resistance or on the time interval to mount specific immune responses.

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.

Dynamic Alignment Models for Neural Coding

PubMed Central

Kollmorgen, Sepp; Hahnloser, Richard H. R.

2014-01-01

Recently, there have been remarkable advances in modeling the relationships between the sensory environment, neuronal responses, and behavior. However, most models cannot encompass variable stimulus-response relationships such as varying response latencies and state or context dependence of the neural code. Here, we consider response modeling as a dynamic alignment problem and model stimulus and response jointly by a mixed pair hidden Markov model (MPH). In MPHs, multiple stimulus-response relationships (e.g., receptive fields) are represented by different states or groups of states in a Markov chain. Each stimulus-response relationship features temporal flexibility, allowing modeling of variable response latencies, including noisy ones. We derive algorithms for learning of MPH parameters and for inference of spike response probabilities. We show that some linear-nonlinear Poisson cascade (LNP) models are a special case of MPHs. We demonstrate the efficiency and usefulness of MPHs in simulations of both jittered and switching spike responses to white noise and natural stimuli. Furthermore, we apply MPHs to extracellular single and multi-unit data recorded in cortical brain areas of singing birds to showcase a novel method for estimating response lag distributions. MPHs allow simultaneous estimation of receptive fields, latency statistics, and hidden state dynamics and so can help to uncover complex stimulus response relationships that are subject to variable timing and involve diverse neural codes. PMID:24625448

Synthesis of a control model for a liquid nitrogen cooled, closed circuit, cryogenic nitrogen wind tunnel and its validation

NASA Technical Reports Server (NTRS)

Balakrishna, S.; Goglia, G. L.

1979-01-01

The details of the efforts to synthesize a control-compatible multivariable model of a liquid nitrogen cooled, gaseous nitrogen operated, closed circuit, cryogenic pressure tunnel are presented. The synthesized model was transformed into a real-time cryogenic tunnel simulator, and this model is validated by comparing the model responses to the actual tunnel responses of the 0.3 m transonic cryogenic tunnel, using the quasi-steady-state and the transient responses of the model and the tunnel. The global nature of the simple, explicit, lumped multivariable model of a closed circuit cryogenic tunnel is demonstrated.

Metabolomics biomarkers to predict acamprosate treatment response in alcohol-dependent subjects.

PubMed

Hinton, David J; Vázquez, Marely Santiago; Geske, Jennifer R; Hitschfeld, Mario J; Ho, Ada M C; Karpyak, Victor M; Biernacka, Joanna M; Choi, Doo-Sup

2017-05-31

Precision medicine for alcohol use disorder (AUD) allows optimal treatment of the right patient with the right drug at the right time. Here, we generated multivariable models incorporating clinical information and serum metabolite levels to predict acamprosate treatment response. The sample of 120 patients was randomly split into a training set (n = 80) and test set (n = 40) five independent times. Treatment response was defined as complete abstinence (no alcohol consumption during 3 months of acamprosate treatment) while nonresponse was defined as any alcohol consumption during this period. In each of the five training sets, we built a predictive model using a least absolute shrinkage and section operator (LASSO) penalized selection method and then evaluated the predictive performance of each model in the corresponding test set. The models predicted acamprosate treatment response with a mean sensitivity and specificity in the test sets of 0.83 and 0.31, respectively, suggesting our model performed well at predicting responders, but not non-responders (i.e. many non-responders were predicted to respond). Studies with larger sample sizes and additional biomarkers will expand the clinical utility of predictive algorithms for pharmaceutical response in AUD.

The dynamics of learning about a climate threshold

NASA Astrophysics Data System (ADS)

Keller, Klaus; McInerney, David

2008-02-01

Anthropogenic greenhouse gas emissions may trigger threshold responses of the climate system. One relevant example of such a potential threshold response is a shutdown of the North Atlantic meridional overturning circulation (MOC). Numerous studies have analyzed the problem of early MOC change detection (i.e., detection before the forcing has committed the system to a threshold response). Here we analyze the early MOC prediction problem. To this end, we virtually deploy an MOC observation system into a simple model that mimics potential future MOC responses and analyze the timing of confident detection and prediction. Our analysis suggests that a confident prediction of a potential threshold response can require century time scales, considerably longer that the time required for confident detection. The signal enabling early prediction of an approaching MOC threshold in our model study is associated with the rate at which the MOC intensity decreases for a given forcing. A faster MOC weakening implies a higher MOC sensitivity to forcing. An MOC sensitivity exceeding a critical level results in a threshold response. Determining whether an observed MOC trend in our model differs in a statistically significant way from an unforced scenario (the detection problem) imposes lower requirements on an observation system than the determination whether the MOC will shut down in the future (the prediction problem). As a result, the virtual observation systems designed in our model for early detection of MOC changes might well fail at the task of early and confident prediction. Transferring this conclusion to the real world requires a considerably refined MOC model, as well as a more complete consideration of relevant observational constraints.

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.

Modeling Systems-Level Regulation of Host Immune Responses

PubMed Central

Thakar, Juilee; Pilione, Mylisa; Kirimanjeswara, Girish; Harvill, Eric T; Albert, Réka

2007-01-01

Many pathogens are able to manipulate the signaling pathways responsible for the generation of host immune responses. Here we examine and model a respiratory infection system in which disruption of host immune functions or of bacterial factors changes the dynamics of the infection. We synthesize the network of interactions between host immune components and two closely related bacteria in the genus Bordetellae. We incorporate existing experimental information on the timing of immune regulatory events into a discrete dynamic model, and verify the model by comparing the effects of simulated disruptions to the experimental outcome of knockout mutations. Our model indicates that the infection time course of both Bordetellae can be separated into three distinct phases based on the most active immune processes. We compare and discuss the effect of the species-specific virulence factors on disrupting the immune response during their infection of naive, antibody-treated, diseased, or convalescent hosts. Our model offers predictions regarding cytokine regulation, key immune components, and clearance of secondary infections; we experimentally validate two of these predictions. This type of modeling provides new insights into the virulence, pathogenesis, and host adaptation of disease-causing microorganisms and allows systems-level analysis that is not always possible using traditional methods. PMID:17559300

An experimental manipulation of responsibility in children: a test of the inflated responsibility model of obsessive-compulsive disorder.

PubMed

Reeves, J; Reynolds, S; Coker, S; Wilson, C

2010-09-01

The objective of this study was to investigate whether Salkovskis (1985) inflated responsibility model of obsessive-compulsive disorder (OCD) applied to children. In an experimental design, 81 children aged 9-12 years were randomly allocated to three conditions: an inflated responsibility group, a moderate responsibility group, and a reduced responsibility group. In all groups children were asked to sort sweets according to whether or not they contained nuts. At baseline the groups did not differ on children's self reported anxiety, depression, obsessive-compulsive symptoms or on inflated responsibility beliefs. The experimental manipulation successfully changed children's perceptions of responsibility. During the sorting task time taken to complete the task, checking behaviours, hesitations, and anxiety were recorded. There was a significant effect of responsibility level on the behavioural variables of time taken, hesitations and check; as perceived responsibility increased children took longer to complete the task and checked and hesitated more often. There was no between-group difference in children's self reported state anxiety. The results offer preliminary support for the link between inflated responsibility and increased checking behaviours in children and add to the small but growing literature suggesting that cognitive models of OCD may apply to children. (c) 2010 Elsevier Ltd. All rights reserved.

Improvement of Varioptic's liquid lens based on electrowetting: how to obtain a short response time and its application in the design of a high resolution iris biometric system

NASA Astrophysics Data System (ADS)

Burger, Benjamin; Meimon, Serge C.; Petit, Cyril; Nguyen, Minh Chau

2015-02-01

This communication presents the results obtained for decreasing the response time of electrowetting-based real time focus correctors (liquid lenses). In order to provide a compact iris biometric system demonstrator, we have achieved a response time at 90% of 7.5 ms for a change in focalization from 0 diopter to 10 diopter with a liquid lens having an aperture of 1.9 mm. We have used a hydrodynamic fluid reorganization model to predict the features of these fast liquid lenses and evaluated the sensivity of the response time to the different conception parameters.

How time delay and network design shape response patterns in biochemical negative feedback systems.

PubMed

Börsch, Anastasiya; Schaber, Jörg

2016-08-24

Negative feedback in combination with time delay can bring about both sustained oscillations and adaptive behaviour in cellular networks. Here, we study which design features of systems with delayed negative feedback shape characteristic response patterns with special emphasis on the role of time delay. To this end, we analyse generic two-dimensional delay differential equations describing the dynamics of biochemical signal-response networks. We investigate the influence of several design features on the stability of the model equilibrium, i.e., presence of auto-inhibition and/or mass conservation and the kind and/or strength of the delayed negative feedback. We show that auto-inhibition and mass conservation have a stabilizing effect, whereas increasing abruptness and decreasing feedback threshold have a de-stabilizing effect on the model equilibrium. Moreover, applying our theoretical analysis to the mammalian p53 system we show that an auto-inhibitory feedback can decouple period and amplitude of an oscillatory response, whereas the delayed feedback can not. Our theoretical framework provides insight into how time delay and design features of biochemical networks act together to elicit specific characteristic response patterns. Such insight is useful for constructing synthetic networks and controlling their behaviour in response to external stimulation.

Human Dose-Response Data for Francisella tularensis and a Dose- and Time-Dependent Mathematical Model of Early-Phase Fever Associated with Tularemia After Inhalation Exposure.

PubMed

McClellan, Gene; Coleman, Margaret; Crary, David; Thurman, Alec; Thran, Brandolyn

2018-04-25

Military health risk assessors, medical planners, operational planners, and defense system developers require knowledge of human responses to doses of biothreat agents to support force health protection and chemical, biological, radiological, nuclear (CBRN) defense missions. This article reviews extensive data from 118 human volunteers administered aerosols of the bacterial agent Francisella tularensis, strain Schu S4, which causes tularemia. The data set includes incidence of early-phase febrile illness following administration of well-characterized inhaled doses of F. tularensis. Supplemental data on human body temperature profiles over time available from de-identified case reports is also presented. A unified, logically consistent model of early-phase febrile illness is described as a lognormal dose-response function for febrile illness linked with a stochastic time profile of fever. Three parameters are estimated from the human data to describe the time profile: incubation period or onset time for fever; rise time of fever; and near-maximum body temperature. Inhaled dose-dependence and variability are characterized for each of the three parameters. These parameters enable a stochastic model for the response of an exposed population through incorporation of individual-by-individual variability by drawing random samples from the statistical distributions of these three parameters for each individual. This model provides risk assessors and medical decisionmakers reliable representations of the predicted health impacts of early-phase febrile illness for as long as one week after aerosol exposures of human populations to F. tularensis. © 2018 Society for Risk Analysis.

Modelling and optimization of semi-solid processing of 7075 Al alloy

NASA Astrophysics Data System (ADS)

Binesh, B.; Aghaie-Khafri, M.

2017-09-01

The new modified strain-induced melt activation (SIMA) process presented by Binesh and Aghaie-Khafri was optimized using a response surface methodology to improve the thixotropic characteristics of semi-solid 7075 alloy. The responses, namely the average grain size and the shape factor, were considered as functions of three independent input variables: effective strain, isothermal holding temperature and time. Mathematical models for the responses were developed using the regression analysis technique, and the adequacy of the models was validated by the analysis of variance method. The calculated results correlated fairly well with the experiments. It was found that all the first- and second-order terms of the independent parameters and the interactive terms of the effective strain and holding time were statistically significant for the responses. In order to simultaneously optimize the responses, the desirable values for the effective strain, holding temperature and time were predicted to be 5.1, 609 °C and 14 min, respectively, when employing the desirability function approach. Based on the optimization results, a significant improvement in the average grain size and shape factor of the semi-solid slurry prepared by the new modified SIMA process was observed.

A mathematical model relating response durations to amount of subclinical resistant disease.

PubMed

Gregory, W M; Richards, M A; Slevin, M L; Souhami, R L

1991-02-15

A mathematical model is presented which seeks to determine, from examination of the response durations of a group of patients with malignant disease, the mean and distribution of the resistant tumor volume. The mean tumor-doubling time and distribution of doubling times are also estimated. The model assumes that in a group of patients there is a log-normal distribution both of resistant disease and of tumor-doubling times and implies that the shapes of certain parts of an actuarial response-duration curve are related to these two factors. The model has been applied to data from two reported acute leukemia trials: (a) a recent acute myelogenous leukemia trial was examined. Close fits were obtained for both the first and second remission-duration curves. The model results suggested that patients with long first remissions had less resistant disease and had tumors with slower growth rates following second line treatment; (b) an historical study of maintenance therapy for acute lymphoblastic leukemia was used to estimate the mean cell-kill (approximately 10(4) cells) achieved with single agent, 6-mercaptopurine. Application of the model may have clinical relevance, for example, in identifying groups of patients likely to benefit from further intensification of treatment.

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.

Identification of Linear and Nonlinear Aerodynamic Impulse Responses Using Digital Filter Techniques

NASA Technical Reports Server (NTRS)

Silva, Walter A.

1997-01-01

This paper discusses the mathematical existence and the numerically-correct identification of linear and nonlinear aerodynamic impulse response functions. Differences between continuous-time and discrete-time system theories, which permit the identification and efficient use of these functions, will be detailed. Important input/output definitions and the concept of linear and nonlinear systems with memory will also be discussed. It will be shown that indicial (step or steady) responses (such as Wagner's function), forced harmonic responses (such as Theodorsen's function or those from doublet lattice theory), and responses to random inputs (such as gusts) can all be obtained from an aerodynamic impulse response function. This paper establishes the aerodynamic impulse response function as the most fundamental, and, therefore, the most computationally efficient, aerodynamic function that can be extracted from any given discrete-time, aerodynamic system. The results presented in this paper help to unify the understanding of classical two-dimensional continuous-time theories with modern three-dimensional, discrete-time theories. First, the method is applied to the nonlinear viscous Burger's equation as an example. Next the method is applied to a three-dimensional aeroelastic model using the CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code and then to a two-dimensional model using the CFL3D Navier-Stokes code. Comparisons of accuracy and computational cost savings are presented. Because of its mathematical generality, an important attribute of this methodology is that it is applicable to a wide range of nonlinear, discrete-time problems.

Identification of Linear and Nonlinear Aerodynamic Impulse Responses Using Digital Filter Techniques

NASA Technical Reports Server (NTRS)

Silva, Walter A.

1997-01-01

This paper discusses the mathematical existence and the numerically-correct identification of linear and nonlinear aerodynamic impulse response functions. Differences between continuous-time and discrete-time system theories, which permit the identification and efficient use of these functions, will be detailed. Important input/output definitions and the concept of linear and nonlinear systems with memory will also be discussed. It will be shown that indicial (step or steady) responses (such as Wagner's function), forced harmonic responses (such as Tbeodorsen's function or those from doublet lattice theory), and responses to random inputs (such as gusts) can all be obtained from an aerodynamic impulse response function. This paper establishes the aerodynamic impulse response function as the most fundamental, and, therefore, the most computationally efficient, aerodynamic function that can be extracted from any given discrete-time, aerodynamic system. The results presented in this paper help to unify the understanding of classical two-dimensional continuous-time theories with modem three-dimensional, discrete-time theories. First, the method is applied to the nonlinear viscous Burger's equation as an example. Next the method is applied to a three-dimensional aeroelastic model using the CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code and then to a two-dimensional model using the CFL3D Navier-Stokes code. Comparisons of accuracy and computational cost savings are presented. Because of its mathematical generality, an important attribute of this methodology is that it is applicable to a wide range of nonlinear, discrete-time problems.

Theory, Guidance, and Flight Control for High Maneuverability Projectiles

DTIC Science & Technology

2014-01-01

estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources, gathering and maintaining...2.8 Linear System Modeling with Time Delay ...................................................................22 2.9 Linear System Modeling Without... Time Delay .............................................................23 3. Guidance and Flight Control 24 3.1 Proportional Navigation Guidance Law

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.

Stochastic optimization for modeling physiological time series: application to the heart rate response to exercise

NASA Astrophysics Data System (ADS)

Zakynthinaki, M. S.; Stirling, J. R.

2007-01-01

Stochastic optimization is applied to the problem of optimizing the fit of a model to the time series of raw physiological (heart rate) data. The physiological response to exercise has been recently modeled as a dynamical system. Fitting the model to a set of raw physiological time series data is, however, not a trivial task. For this reason and in order to calculate the optimal values of the parameters of the model, the present study implements the powerful stochastic optimization method ALOPEX IV, an algorithm that has been proven to be fast, effective and easy to implement. The optimal parameters of the model, calculated by the optimization method for the particular athlete, are very important as they characterize the athlete's current condition. The present study applies the ALOPEX IV stochastic optimization to the modeling of a set of heart rate time series data corresponding to different exercises of constant intensity. An analysis of the optimization algorithm, together with an analytic proof of its convergence (in the absence of noise), is also presented.

A model for predicting aortic dynamic response to -G sub z impact acceleration.

NASA Technical Reports Server (NTRS)

Advani, S. H.; Tarnay, T. J.; Byars, E. F.; Love, J. S.

1972-01-01

A steady state dynamic response model for the radial motion of the aorta is developed from in vivo pressure-displacement and nerve stimulation experiments on canines. The model represented by a modified Van der Pol wave motion oscillator closely predicts steady state and perturbed response results. The applicability of the steady state canine aortic model to tailward acting impact forces is studied by means of the perturbed phase plane of the oscillator. The backflow through the aortic arch resulting from a specified acceleration-time profile is computed and an analysis for predicting the forced motion aortic response is presented.

Adapting cultural mixture modeling for continuous measures of knowledge and memory fluency.

PubMed

Tan, Yin-Yin Sarah; Mueller, Shane T

2016-09-01

Previous research (e.g., cultural consensus theory (Romney, Weller, & Batchelder, American Anthropologist, 88, 313-338, 1986); cultural mixture modeling (Mueller & Veinott, 2008)) has used overt response patterns (i.e., responses to questionnaires and surveys) to identify whether a group shares a single coherent attitude or belief set. Yet many domains in social science have focused on implicit attitudes that are not apparent in overt responses but still may be detected via response time patterns. We propose a method for modeling response times as a mixture of Gaussians, adapting the strong-consensus model of cultural mixture modeling to model this implicit measure of knowledge strength. We report the results of two behavioral experiments and one simulation experiment that establish the usefulness of the approach, as well as some of the boundary conditions under which distinct groups of shared agreement might be recovered, even when the group identity is not known. The results reveal that the ability to recover and identify shared-belief groups depends on (1) the level of noise in the measurement, (2) the differential signals for strong versus weak attitudes, and (3) the similarity between group attitudes. Consequently, the method shows promise for identifying latent groups among a population whose overt attitudes do not differ, but whose implicit or covert attitudes or knowledge may differ.

Empirical STORM-E Model. [I. Theoretical and Observational Basis

NASA Technical Reports Server (NTRS)

Mertens, Christopher J.; Xu, Xiaojing; Bilitza, Dieter; Mlynczak, Martin G.; Russell, James M., III

2013-01-01

Auroral nighttime infrared emission observed by the Sounding of the Atmosphere using Broadband Emission Radiometry (SABER) instrument onboard the Thermosphere-Ionosphere-Mesosphere Energetics and Dynamics (TIMED) satellite is used to develop an empirical model of geomagnetic storm enhancements to E-region peak electron densities. The empirical model is called STORM-E and will be incorporated into the 2012 release of the International Reference Ionosphere (IRI). The proxy for characterizing the E-region response to geomagnetic forcing is NO+(v) volume emission rates (VER) derived from the TIMED/SABER 4.3 lm channel limb radiance measurements. The storm-time response of the NO+(v) 4.3 lm VER is sensitive to auroral particle precipitation. A statistical database of storm-time to climatological quiet-time ratios of SABER-observed NO+(v) 4.3 lm VER are fit to widely available geomagnetic indices using the theoretical framework of linear impulse-response theory. The STORM-E model provides a dynamic storm-time correction factor to adjust a known quiescent E-region electron density peak concentration for geomagnetic enhancements due to auroral particle precipitation. Part II of this series describes the explicit development of the empirical storm-time correction factor for E-region peak electron densities, and shows comparisons of E-region electron densities between STORM-E predictions and incoherent scatter radar measurements. In this paper, Part I of the series, the efficacy of using SABER-derived NO+(v) VER as a proxy for the E-region response to solar-geomagnetic disturbances is presented. Furthermore, a detailed description of the algorithms and methodologies used to derive NO+(v) VER from SABER 4.3 lm limb emission measurements is given. Finally, an assessment of key uncertainties in retrieving NO+(v) VER is presented

Single molecule force spectroscopy at high data acquisition: A Bayesian nonparametric analysis

NASA Astrophysics Data System (ADS)

Sgouralis, Ioannis; Whitmore, Miles; Lapidus, Lisa; Comstock, Matthew J.; Pressé, Steve

2018-03-01

Bayesian nonparametrics (BNPs) are poised to have a deep impact in the analysis of single molecule data as they provide posterior probabilities over entire models consistent with the supplied data, not just model parameters of one preferred model. Thus they provide an elegant and rigorous solution to the difficult problem encountered when selecting an appropriate candidate model. Nevertheless, BNPs' flexibility to learn models and their associated parameters from experimental data is a double-edged sword. Most importantly, BNPs are prone to increasing the complexity of the estimated models due to artifactual features present in time traces. Thus, because of experimental challenges unique to single molecule methods, naive application of available BNP tools is not possible. Here we consider traces with time correlations and, as a specific example, we deal with force spectroscopy traces collected at high acquisition rates. While high acquisition rates are required in order to capture dwells in short-lived molecular states, in this setup, a slow response of the optical trap instrumentation (i.e., trapped beads, ambient fluid, and tethering handles) distorts the molecular signals introducing time correlations into the data that may be misinterpreted as true states by naive BNPs. Our adaptation of BNP tools explicitly takes into consideration these response dynamics, in addition to drift and noise, and makes unsupervised time series analysis of correlated single molecule force spectroscopy measurements possible, even at acquisition rates similar to or below the trap's response times.

A simple model of mechanotransduction in primate glabrous skin

PubMed Central

Dong, Yi; Mihalas, Stefan; Kim, Sung Soo; Yoshioka, Takashi; Niebur, Ernst

2013-01-01

Tactile stimulation of the hand evokes highly precise and repeatable patterns of activity in mechanoreceptive afferents; the strength (i.e., firing rate) and timing of these responses have been shown to convey stimulus information. To achieve an understanding of the mechanisms underlying the representation of tactile stimuli in the nerve, we developed a two-stage computational model consisting of a nonlinear mechanical transduction stage followed by a generalized integrate-and-fire mechanism. The model improves upon a recently published counterpart in two important ways. First, complexity is dramatically reduced (at least one order of magnitude fewer parameters). Second, the model comprises a saturating nonlinearity and therefore can be applied to a much wider range of stimuli. We show that both the rate and timing of afferent responses are predicted with remarkable precision and that observed adaptation patterns and threshold behavior are well captured. We conclude that the responses of mechanoreceptive afferents can be understood using a very parsimonious mechanistic model, which can then be used to accurately simulate the responses of afferent populations. PMID:23236001

Blast Loading of Epoxy Panels Using a Shock Tube

NASA Technical Reports Server (NTRS)

Pankow, Mark; Waas, Anthony M.; Bednarcyk, Brett

2010-01-01

The high strain rate mechanical response of thin polymer plates has been studied using a modified shock tube. Diagnostics include the pressure-time history of the incident and reflected pulses and the use of digital image correlation (DIC) techniques to extract the time-history of the out-of-plane displacement distribution. Additionally, finite element models have been developed to understand the plate response and to validate and modify plate material constitutive models that have been proposed.

NOTE: Implementation of angular response function modeling in SPECT simulations with GATE

NASA Astrophysics Data System (ADS)

Descourt, P.; Carlier, T.; Du, Y.; Song, X.; Buvat, I.; Frey, E. C.; Bardies, M.; Tsui, B. M. W.; Visvikis, D.

2010-05-01

Among Monte Carlo simulation codes in medical imaging, the GATE simulation platform is widely used today given its flexibility and accuracy, despite long run times, which in SPECT simulations are mostly spent in tracking photons through the collimators. In this work, a tabulated model of the collimator/detector response was implemented within the GATE framework to significantly reduce the simulation times in SPECT. This implementation uses the angular response function (ARF) model. The performance of the implemented ARF approach has been compared to standard SPECT GATE simulations in terms of the ARF tables' accuracy, overall SPECT system performance and run times. Considering the simulation of the Siemens Symbia T SPECT system using high-energy collimators, differences of less than 1% were measured between the ARF-based and the standard GATE-based simulations, while considering the same noise level in the projections, acceleration factors of up to 180 were obtained when simulating a planar 364 keV source seen with the same SPECT system. The ARF-based and the standard GATE simulation results also agreed very well when considering a four-head SPECT simulation of a realistic Jaszczak phantom filled with iodine-131, with a resulting acceleration factor of 100. In conclusion, the implementation of an ARF-based model of collimator/detector response for SPECT simulations within GATE significantly reduces the simulation run times without compromising accuracy.

The cerebellum in action: a simulation and robotics study.

PubMed

Hofstötter, Constanze; Mintz, Matti; Verschure, Paul F M J

2002-10-01

The control or prediction of the precise timing of events are central aspects of the many tasks assigned to the cerebellum. Despite much detailed knowledge of its physiology and anatomy, it remains unclear how the cerebellar circuitry can achieve such an adaptive timing function. We present a computational model pursuing this question for one extensively studied type of cerebellar-mediated learning: the classical conditioning of discrete motor responses. This model combines multiple current assumptions on the function of the cerebellar circuitry and was used to investigate whether plasticity in the cerebellar cortex alone can mediate adaptive conditioned response timing. In particular, we studied the effect of changes in the strength of the synapses formed between parallel fibres and Purkinje cells under the control of a negative feedback loop formed between inferior olive, cerebellar cortex and cerebellar deep nuclei. The learning performance of the model was evaluated at the circuit level in simulated conditioning experiments as well as at the behavioural level using a mobile robot. We demonstrate that the model supports adaptively timed responses under real-world conditions. Thus, in contrast to many other models that have focused on cerebellar-mediated conditioning, we investigated whether and how the suggested underlying mechanisms could give rise to behavioural phenomena.

Modeling non-linear growth responses to temperature and hydrology in wetland trees

NASA Astrophysics Data System (ADS)

Keim, R.; Allen, S. T.

2016-12-01

Growth responses of wetland trees to flooding and climate variations are difficult to model because they depend on multiple, apparently interacting factors, but are a critical link in hydrological control of wetland carbon budgets. To more generally understand tree growth to hydrological forcing, we modeled non-linear responses of tree ring growth to flooding and climate at sub-annual time steps, using Vaganov-Shashkin response functions. We calibrated the model to six baldcypress tree-ring chronologies from two hydrologically distinct sites in southern Louisiana, and tested several hypotheses of plasticity in wetlands tree responses to interacting environmental variables. The model outperformed traditional multiple linear regression. More importantly, optimized response parameters were generally similar among sites with varying hydrological conditions, suggesting generality to the functions. Model forms that included interacting responses to multiple forcing factors were more effective than were single response functions, indicating the principle of a single limiting factor is not correct in wetlands and both climatic and hydrological variables must be considered in predicting responses to hydrological or climate change.

Measuring temperature dependence of soil respiration: importance of incubation time, soil type, moisture content and model fits

NASA Astrophysics Data System (ADS)

Schipper, L. A.; Robinson, J.; O'Neill, T.; Ryburn, J.; Arcus, V. L.

2015-12-01

Developing robust models of the temperature response and sensitivity of soil respiration is critical for determining changes carbon cycling in response to climate change and at daily to annual time scales. Currently, approaches for measuring temperature dependence of soil respiration generally use long incubation times (days to weeks and months) at a limited number of incubation temperatures. Long incubation times likely allow thermal adaptation by the microbial population so that results are poorly representative of in situ soil responses. Additionally, too few incubation temperatures allows for the fit and justification of many different predictive equations, which can lead to inaccuracies when used for carbon budgeting purposes. We have developed a method to rapidly determine the response of soil respiration rate to wide range of temperatures. An aluminium block with 44 sample slots is heated at one end and cooled at the other to give a temperature gradient from 0 to 55°C at about one degree increments. Soil respiration is measured within 5 hours to minimise the possibility of thermal adaptation. We have used this method to demonstrate the similarity of temperature sensitivity of respiration for different soils from the same location across seasons. We are currently testing whether long-term (weeks to months) incubation alter temperature response and sensitivity that occurs in situ responses. This method is also well suited for determining the most appropriate models of temperature dependence and sensitivity of soil respiration (including macromolecular rate theory MMRT). With additional testing, this method is expected to be a more reliable method of measuring soil respiration rate for soil quality and modelling of soil carbon processes.

New approach to analyzing soil-building systems

USGS Publications Warehouse

Safak, E.

1998-01-01

A new method of analyzing seismic response of soil-building systems is introduced. The method is based on the discrete-time formulation of wave propagation in layered media for vertically propagating plane shear waves. Buildings are modeled as an extension of the layered soil media by assuming that each story in the building is another layer. The seismic response is expressed in terms of wave travel times between the layers, and the wave reflection and transmission coefficients at layer interfaces. The calculation of the response is reduced to a pair of simple finite-difference equations for each layer, which are solved recursively starting from the bedrock. Compared with commonly used vibration formulation, the wave propagation formulation provides several advantages, including the ability to incorporate soil layers, simplicity of the calculations, improved accuracy in modeling the mass and damping, and better tools for system identification and damage detection.A new method of analyzing seismic response of soil-building systems is introduced. The method is based on the discrete-time formulation of wave propagation in layered media for vertically propagating plane shear waves. Buildings are modeled as an extension of the layered soil media by assuming that each story in the building is another layer. The seismic response is expressed in terms of wave travel times between the layers, and the wave reflection and transmission coefficients at layer interfaces. The calculation of the response is reduced to a pair of simple finite-difference equations for each layer, which are solved recursively starting from the bedrock. Compared with commonly used vibration formulation, the wave propagation formulation provides several advantages, including the ability to incorporate soil layers, simplicity of the calculations, improved accuracy in modeling the mass and damping, and better tools for system identification and damage detection.

Dayside and nightside magnetic field responses at 780 km altitude to dayside reconnection.

NASA Astrophysics Data System (ADS)

Snekvik, Kristian; Østgaard, Nikolai; Tenfjord, Paul; Petter Reistad, Jone; Magnus Laundal, Karl; Milan, Stephen E.; Haaland, Stein E.

2017-04-01

During southward IMF, dayside reconnection will drive the Dungey cycle in the Earth's magnetosphere, which is manifested as a two cell convection pattern in the ionosphere. We address the response of the ionospheric convection to changes in the dayside reconnection rate. Previous studies have reported two apparently contradicting results. The first is that the ionospheric convection responds within one minute both near noon and near midnight. The second is that the response is 10-20 minutes delayed near midnight compared to near noon. To test these apparently contradicting scenarios, we have performed a statistical investigation of the response by examining the magnetic field perturbations at 780 km altitude due to dayside reconnection. The AMPERE data products derived from the Iridium constellation provide global maps of the disturbance magnetic field. The time development of the convection is modelled as the sum of an accelerating force and a decelerating force. Furthermore, the accelerating force is parametrised as a linear sum of past reconnection rates, while the decelerating force is proportional to the convection itself. This results in an asymptotic model which gradually reaches a steady-state value. By fitting the data to the model, we confirm previous reports of an almost immediate response both near noon and near midnight combined with a 10-20 minutes reconfiguration time of the two cell convection pattern. The e-folding time of the asymptotic model was found to be about 40 minutes. We present a new explanation of the response and reconfiguration times based on how MHD waves propagate in the magnetospheric lobes when newly reconnected open flux tubes are added to the lobes, and the magnetopause flaring angle increases.

Integrated defense system overlaps as a disease model: with examples for multiple chemical sensitivity.

PubMed Central

Rowat, S C

1998-01-01

The central nervous, immune, and endocrine systems communicate through multiple common messengers. Over evolutionary time, what may be termed integrated defense system(s) (IDS) have developed to coordinate these communications for specific contexts; these include the stress response, acute-phase response, nonspecific immune response, immune response to antigen, kindling, tolerance, time-dependent sensitization, neurogenic switching, and traumatic dissociation (TD). These IDSs are described and their overlap is examined. Three models of disease production are generated: damage, in which IDSs function incorrectly; inadequate/inappropriate, in which IDS response is outstripped by a changing context; and evolving/learning, in which the IDS learned response to a context is deemed pathologic. Mechanisms of multiple chemical sensitivity (MCS) are developed from several IDS disease models. Model 1A is pesticide damage to the central nervous system, overlapping with body chemical burdens, TD, and chronic zinc deficiency; model 1B is benzene disruption of interleukin-1, overlapping with childhood developmental windows and hapten-antigenic spreading; and model 1C is autoimmunity to immunoglobulin-G (IgG), overlapping with spreading to other IgG-inducers, sudden spreading of inciters, and food-contaminating chemicals. Model 2A is chemical and stress overload, including comparison with the susceptibility/sensitization/triggering/spreading model; model 2B is genetic mercury allergy, overlapping with: heavy metals/zinc displacement and childhood/gestational mercury exposures; and model 3 is MCS as evolution and learning. Remarks are offered on current MCS research. Problems with clinical measurement are suggested on the basis of IDS models. Large-sample patient self-report epidemiology is described as an alternative or addition to clinical biomarker and animal testing. Images Figure 1 Figure 2 Figure 3 Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 PMID:9539008

Calculating Nozzle Side Loads using Acceleration Measurements of Test-Based Models

NASA Technical Reports Server (NTRS)

Brown, Andrew M.; Ruf, Joe

2007-01-01

As part of a NASA/MSFC research program to evaluate the effect of different nozzle contours on the well-known but poorly characterized "side load" phenomena, we attempt to back out the net force on a sub-scale nozzle during cold-flow testing using acceleration measurements. Because modeling the test facility dynamics is problematic, new techniques for creating a "pseudo-model" of the facility and nozzle directly from modal test results are applied. Extensive verification procedures were undertaken, resulting in a loading scale factor necessary for agreement between test and model based frequency response functions. Side loads are then obtained by applying a wide-band random load onto the system model, obtaining nozzle response PSD's, and iterating both the amplitude and frequency of the input until a good comparison of the response with the measured response PSD for a specific time point is obtained. The final calculated loading can be used to compare different nozzle profiles for assessment during rocket engine nozzle development and as a basis for accurate design of the nozzle and engine structure to withstand these loads. The techniques applied within this procedure have extensive applicability to timely and accurate characterization of all test fixtures used for modal test.A viewgraph presentation on a model-test based pseudo-model used to calculate side loads on rocket engine nozzles is included. The topics include: 1) Side Loads in Rocket Nozzles; 2) Present Side Loads Research at NASA/MSFC; 3) Structural Dynamic Model Generation; 4) Pseudo-Model Generation; 5) Implementation; 6) Calibration of Pseudo-Model Response; 7) Pseudo-Model Response Verification; 8) Inverse Force Determination; 9) Results; and 10) Recent Work.

Step responses of a torsional system with multiple clearances: Study of vibro-impact phenomenon using experimental and computational methods

NASA Astrophysics Data System (ADS)

Oruganti, Pradeep Sharma; Krak, Michael D.; Singh, Rajendra

2018-01-01

Recently Krak and Singh (2017) proposed a scientific experiment that examined vibro-impacts in a torsional system under a step down excitation and provided preliminary measurements and limited non-linear model studies. A major goal of this article is to extend the prior work with a focus on the examination of vibro-impact phenomena observed under step responses in a torsional system with one, two or three controlled clearances. First, new measurements are made at several locations with a higher sampling frequency. Measured angular accelerations are examined in both time and time-frequency domains. Minimal order non-linear models of the experiment are successfully constructed, using piecewise linear stiffness and Coulomb friction elements; eight cases of the generic system are examined though only three are experimentally studied. Measured and predicted responses for single and dual clearance configurations exhibit double sided impacts and time varying periods suggest softening trends under the step down torque. Non-linear models are experimentally validated by comparing results with new measurements and with those previously reported. Several metrics are utilized to quantify and compare the measured and predicted responses (including peak to peak accelerations). Eigensolutions and step responses of the corresponding linearized models are utilized to better understand the nature of the non-linear dynamic system. Finally, the effect of step amplitude on the non-linear responses is examined for several configurations, and hardening trends are observed in the torsional system with three clearances.

Ultrasound-Assisted Extraction of Cannabinoids from Cannabis Sativa L. Optimized by Response Surface Methodology.

PubMed

Agarwal, Charu; Máthé, Katalin; Hofmann, Tamás; Csóka, Levente

2018-03-01

Ultrasonication was used to extract bioactive compounds from Cannabis sativa L. such as polyphenols, flavonoids, and cannabinoids. The influence of 3 independent factors (time, input power, and methanol concentration) was evaluated on the extraction of total phenols (TPC), flavonoids (TF), ferric reducing ability of plasma (FRAP) and the overall yield. A face-centered central composite design was used for statistical modelling of the response data, followed by regression and analysis of variance in order to determine the significance of the model and factors. Both the solvent composition and the time significantly affected the extraction while the sonication power had no significant impact on the responses. The response predictions obtained at optimum extraction conditions of 15 min time, 130 W power, and 80% methanol were 314.822 mg GAE/g DW of TPC, 28.173 mg QE/g DW of TF, 18.79 mM AAE/g DW of FRAP, and 10.86% of yield. A good correlation was observed between the predicted and experimental values of the responses, which validated the mathematical model. On comparing the ultrasonic process with the control extraction, noticeably higher values were obtained for each of the responses. Additionally, ultrasound considerably improved the extraction of cannabinoids present in Cannabis. Low frequency ultrasound was employed to extract bioactive compounds from the inflorescence part of Cannabis. The responses evaluated were-total phenols, flavonoids, ferric reducing assay and yield. The solvent composition and time significantly influenced the extraction process. Appreciably higher extraction of cannabinoids was achieved on sonication against control. © 2018 Institute of Food Technologists®.

A modal analysis of flexible aircraft dynamics with handling qualities implications

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1983-01-01

A multivariable modal analysis technique is presented for evaluating flexible aircraft dynamics, focusing on meaningful vehicle responses to pilot inputs and atmospheric turbulence. Although modal analysis is the tool, vehicle time response is emphasized, and the analysis is performed on the linear, time-domain vehicle model. In evaluating previously obtained experimental pitch tracking data for a family of vehicle dynamic models, it is shown that flexible aeroelastic effects can significantly affect pitch attitude handling qualities. Consideration of the eigenvalues alone, of both rigid-body and aeroelastic modes, does not explain the simulation results. Modal analysis revealed, however, that although the lowest aeroelastic mode frequency was still three times greater than the short-period frequency, the rigid-body attitude response was dominated by this aeroelastic mode. This dominance was defined in terms of the relative magnitudes of the modal residues in selected vehicle responses.

A validation of ground ambulance pre-hospital times modeled using geographic information systems

PubMed Central

2012-01-01

Background Evaluating geographic access to health services often requires determining the patient travel time to a specified service. For urgent care, many research studies have modeled patient pre-hospital time by ground emergency medical services (EMS) using geographic information systems (GIS). The purpose of this study was to determine if the modeling assumptions proposed through prior United States (US) studies are valid in a non-US context, and to use the resulting information to provide revised recommendations for modeling travel time using GIS in the absence of actual EMS trip data. Methods The study sample contained all emergency adult patient trips within the Calgary area for 2006. Each record included four components of pre-hospital time (activation, response, on-scene and transport interval). The actual activation and on-scene intervals were compared with those used in published models. The transport interval was calculated within GIS using the Network Analyst extension of Esri ArcGIS 10.0 and the response interval was derived using previously established methods. These GIS derived transport and response intervals were compared with the actual times using descriptive methods. We used the information acquired through the analysis of the EMS trip data to create an updated model that could be used to estimate travel time in the absence of actual EMS trip records. Results There were 29,765 complete EMS records for scene locations inside the city and 529 outside. The actual median on-scene intervals were longer than the average previously reported by 7–8 minutes. Actual EMS pre-hospital times across our study area were significantly higher than the estimated times modeled using GIS and the original travel time assumptions. Our updated model, although still underestimating the total pre-hospital time, more accurately represents the true pre-hospital time in our study area. Conclusions The widespread use of generalized EMS pre-hospital time assumptions based on US data may not be appropriate in a non-US context. The preference for researchers should be to use actual EMS trip records from the proposed research study area. In the absence of EMS trip data researchers should determine which modeling assumptions more accurately reflect the EMS protocols across their study area. PMID:23033894

Identifying Variability in Mental Models Within and Between Disciplines Caring for the Cardiac Surgical Patient.

PubMed

Brown, Evans K H; Harder, Kathleen A; Apostolidou, Ioanna; Wahr, Joyce A; Shook, Douglas C; Farivar, R Saeid; Perry, Tjorvi E; Konia, Mojca R

2017-07-01

The cardiac operating room is a complex environment requiring efficient and effective communication between multiple disciplines. The objectives of this study were to identify and rank critical time points during the perioperative care of cardiac surgical patients, and to assess variability in responses, as a correlate of a shared mental model, regarding the importance of these time points between and within disciplines. Using Delphi technique methodology, panelists from 3 institutions were tasked with developing a list of critical time points, which were subsequently assigned to pause point (PP) categories. Panelists then rated these PPs on a 100-point visual analog scale. Descriptive statistics were expressed as percentages, medians, and interquartile ranges (IQRs). We defined low response variability between panelists as an IQR ≤ 20, moderate response variability as an IQR > 20 and ≤ 40, and high response variability as an IQR > 40. Panelists identified a total of 12 PPs. The PPs identified by the highest number of panelists were (1) before surgical incision, (2) before aortic cannulation, (3) before cardiopulmonary bypass (CPB) initiation, (4) before CPB separation, and (5) at time of transfer of care from operating room (OR) to intensive care unit (ICU) staff. There was low variability among panelists' ratings of the PP "before surgical incision," moderate response variability for the PPs "before separation from CPB," "before transfer from OR table to bed," and "at time of transfer of care from OR to ICU staff," and high response variability for the remaining 8 PPs. In addition, the perceived importance of each of these PPs varies between disciplines and between institutions. Cardiac surgical providers recognize distinct critical time points during cardiac surgery. However, there is a high degree of variability within and between disciplines as to the importance of these times, suggesting an absence of a shared mental model among disciplines caring for cardiac surgical patients during the perioperative period. A lack of a shared mental model could be one of the factors contributing to preventable errors in cardiac operating rooms.

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.

Predicting the threshold of pulse-train electrical stimuli using a stochastic auditory nerve model: the effects of stimulus noise.

PubMed

Xu, Yifang; Collins, Leslie M

2004-04-01

The incorporation of low levels of noise into an electrical stimulus has been shown to improve auditory thresholds in some human subjects (Zeng et al., 2000). In this paper, thresholds for noise-modulated pulse-train stimuli are predicted utilizing a stochastic neural-behavioral model of ensemble fiber responses to bi-phasic stimuli. The neural refractory effect is described using a Markov model for a noise-free pulse-train stimulus and a closed-form solution for the steady-state neural response is provided. For noise-modulated pulse-train stimuli, a recursive method using the conditional probability is utilized to track the neural responses to each successive pulse. A neural spike count rule has been presented for both threshold and intensity discrimination under the assumption that auditory perception occurs via integration over a relatively long time period (Bruce et al., 1999). An alternative approach originates from the hypothesis of the multilook model (Viemeister and Wakefield, 1991), which argues that auditory perception is based on several shorter time integrations and may suggest an NofM model for prediction of pulse-train threshold. This motivates analyzing the neural response to each individual pulse within a pulse train, which is considered to be the brief look. A logarithmic rule is hypothesized for pulse-train threshold. Predictions from the multilook model are shown to match trends in psychophysical data for noise-free stimuli that are not always matched by the long-time integration rule. Theoretical predictions indicate that threshold decreases as noise variance increases. Theoretical models of the neural response to pulse-train stimuli not only reduce calculational overhead but also facilitate utilization of signal detection theory and are easily extended to multichannel psychophysical tasks.

Time-scale Dependence of Response of an Estuarine Water Quality Model to Nutrient Loading

EPA Science Inventory

We describe calibration and evaluation of a water quality model being implemented for Narragansett Bay to quantify the response of concentrations of nutrients, phytoplankton chlorophyll a and dissolved oxygen in the Bay to loading rates of nutrients and other boundary conditions....

[Construction of the Time Management Scale and examination of the influence of time management on psychological stress response].

PubMed

Imura, Tomoya; Takamura, Masahiro; Okazaki, Yoshihiro; Tokunaga, Satoko

2016-10-01

We developed a scale to measure time management and assessed its reliability and validity. We then used this scale to examine the impact of time management on psychological stress response. In Study 1-1, we developed the scale and assessed its internal consistency and criterion-related validity. Findings from a factor analysis revealed three elements of time management, “time estimation,” “time utilization,” and “taking each moment as it comes.” In Study 1-2, we assessed the scale’s test-retest reliability. In Study 1-3, we assessed the validity of the constructed scale. The results indicate that the time management scale has good reliability and validity. In Study 2, we performed a covariance structural analysis to verify our model that hypothesized that time management influences perceived control of time and psychological stress response, and perceived control of time influences psychological stress response. The results showed that time estimation increases the perceived control of time, which in turn decreases stress response. However, we also found that taking each moment as it comes reduces perceived control of time, which in turn increases stress response.

Fourier functional analysis for unsteady aerodynamic modeling

NASA Technical Reports Server (NTRS)

Lan, C. Edward; Chin, Suei

1991-01-01

A method based on Fourier analysis is developed to analyze the force and moment data obtained in large amplitude forced oscillation tests at high angles of attack. The aerodynamic models for normal force, lift, drag, and pitching moment coefficients are built up from a set of aerodynamic responses to harmonic motions at different frequencies. Based on the aerodynamic models of harmonic data, the indicial responses are formed. The final expressions for the models involve time integrals of the indicial type advocated by Tobak and Schiff. Results from linear two- and three-dimensional unsteady aerodynamic theories as well as test data for a 70-degree delta wing are used to verify the models. It is shown that the present modeling method is accurate in producing the aerodynamic responses to harmonic motions and the ramp type motions. The model also produces correct trend for a 70-degree delta wing in harmonic motion with different mean angles-of-attack. However, the current model cannot be used to extrapolate data to higher angles-of-attack than that of the harmonic motions which form the aerodynamic model. For linear ramp motions, a special method is used to calculate the corresponding frequency and phase angle at a given time. The calculated results from modeling show a higher lift peak for linear ramp motion than for harmonic ramp motion. The current model also shows reasonably good results for the lift responses at different angles of attack.

Clinical Predictive Modeling Development and Deployment through FHIR Web Services.

PubMed

Khalilia, Mohammed; Choi, Myung; Henderson, Amelia; Iyengar, Sneha; Braunstein, Mark; Sun, Jimeng

2015-01-01

Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction.

Clinical Predictive Modeling Development and Deployment through FHIR Web Services

PubMed Central

Khalilia, Mohammed; Choi, Myung; Henderson, Amelia; Iyengar, Sneha; Braunstein, Mark; Sun, Jimeng

2015-01-01

Clinical predictive modeling involves two challenging tasks: model development and model deployment. In this paper we demonstrate a software architecture for developing and deploying clinical predictive models using web services via the Health Level 7 (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The services enable model development using electronic health records (EHRs) stored in OMOP CDM databases and model deployment for scoring individual patients through FHIR resources. The MIMIC2 ICU dataset and a synthetic outpatient dataset were transformed into OMOP CDM databases for predictive model development. The resulting predictive models are deployed as FHIR resources, which receive requests of patient information, perform prediction against the deployed predictive model and respond with prediction scores. To assess the practicality of this approach we evaluated the response and prediction time of the FHIR modeling web services. We found the system to be reasonably fast with one second total response time per patient prediction. PMID:26958207

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

Time-domain approach for the transient responses in stratified viscoelastic Earth models

NASA Technical Reports Server (NTRS)

Hanyk, L.; Moser, J.; Yuen, D. A.; Matyska, C.

1995-01-01

We have developed the numerical algorithm for the computation of transient viscoelastic responses in the time domain for a radially stratified Earth model. Stratifications in both the elastic parameters and the viscosity profile have been considered. The particular viscosity profile employed has a viscosity maximum with a constrast of O(100) in the mid lower mantle. The distribution of relaxation times reveals the presence of a continuous spectrum situated between O(100) and O(exp 4) years. The principal mode is embedded within this continuous spectrum. From this initial-value approach we have found that for the low degree harmonics the non-modal contributions are comparable to the modal contributions. For this viscosity model the differences between the time-domain and normal-mode results are found to decrease strongly with increasing angular order. These calculations also show that a time-dependent effective relaxation time can be defined, which can be bounded by the relaxation times of the principal modes.

Identification of time-varying structural dynamic systems - An artificial intelligence approach

NASA Technical Reports Server (NTRS)

Glass, B. J.; Hanagud, S.

1992-01-01

An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.

The El Nino-Southern Oscillation in the second Hadley Centre coupled model and its response to greenhouse warming

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

Collins, M.

This paper describes El Nino-Southern Oscillation (ENSO) interannual variability simulated in the second Handley Centre coupled model under control and greenhouse warming scenarios. The model produces a very reasonable simulation of ENSO in the control experiment--reproducing the amplitude, spectral characteristics, and phase locking to the annual cycle that are observed in nature. The mechanism for the model ENSO is shown to be a mixed SST-ocean dynamics mode that can be interpreted in terms of the ocean recharge paradigm of Jin. In experiments with increased levels of greenhouse gases, no statistically significant changes in ENSO are seen until these levels approachmore » four times preindustrial values. In these experiments, the model ENSO has an approximately 20% larger amplitude, a frequency that is approximately double that of the current ENSO (implying more frequent El Ninos and La Ninas), and phase locks to the annual cycle at a different time of year. It is shown that the increase in the vertical gradient of temperature in the thermocline region, associated with the model's response to increased greenhouse gases, is responsible for the increase in the amplitude of ENSO, while the increase in meridional temperature gradients on either side of the equator, again associated with the models response to increasing greenhouse gases, is responsible for the increased frequency of ENSO events.« less

A physiologically based nonhomogeneous Poisson counter model of visual identification.

PubMed

Christensen, Jeppe H; Markussen, Bo; Bundesen, Claus; Kyllingsbæk, Søren

2018-04-30

A physiologically based nonhomogeneous Poisson counter model of visual identification is presented. The model was developed in the framework of a Theory of Visual Attention (Bundesen, 1990; Kyllingsbæk, Markussen, & Bundesen, 2012) and meant for modeling visual identification of objects that are mutually confusable and hard to see. The model assumes that the visual system's initial sensory response consists in tentative visual categorizations, which are accumulated by leaky integration of both transient and sustained components comparable with those found in spike density patterns of early sensory neurons. The sensory response (tentative categorizations) feeds independent Poisson counters, each of which accumulates tentative object categorizations of a particular type to guide overt identification performance. We tested the model's ability to predict the effect of stimulus duration on observed distributions of responses in a nonspeeded (pure accuracy) identification task with eight response alternatives. The time courses of correct and erroneous categorizations were well accounted for when the event-rates of competing Poisson counters were allowed to vary independently over time in a way that mimicked the dynamics of receptive field selectivity as found in neurophysiological studies. Furthermore, the initial sensory response yielded theoretical hazard rate functions that closely resembled empirically estimated ones. Finally, supplied with a Naka-Rushton type contrast gain control, the model provided an explanation for Bloch's law. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Examining responses of ecosystem carbon exchange to environmental changes using particle filtering mathod

NASA Astrophysics Data System (ADS)

Yokozawa, M.

2017-12-01

Attention has been paid to the agricultural field that could regulate ecosystem carbon exchange by water management and residual treatments. However, there have been less known about the dynamic responses of the ecosystem to environmental changes. In this study, focussing on paddy field, where CO2 emissions due to microbial decomposition of organic matter are suppressed and alternatively CH4 emitted under flooding condition during rice growth season and subsequently CO2 emission following the fallow season after harvest, the responses of ecosystem carbon exchange were examined. We conducted model data fusion analysis for examining the response of cropland-atmosphere carbon exchange to environmental variation. The used model consists of two sub models, paddy rice growth sub-model and soil decomposition sub-model. The crop growth sub-model mimics the rice plant growth processes including formation of reproductive organs as well as leaf expansion. The soil decomposition sub-model simulates the decomposition process of soil organic carbon. Assimilating the data on the time changes in CO2 flux measured by eddy covariance method, rice plant biomass, LAI and the final yield with the model, the parameters were calibrated using a stochastic optimization algorithm with a particle filter method. The particle filter method, which is one of the Monte Carlo filters, enable us to evaluating time changes in parameters based on the observed data until the time and to make prediction of the system. Iterative filtering and prediction with changing parameters and/or boundary condition enable us to obtain time changes in parameters governing the crop production as well as carbon exchange. In this study, we focused on the parameters related to crop production as well as soil carbon storage. As the results, the calibrated model with estimated parameters could accurately predict the NEE flux in the subsequent years. The temperature sensitivity, denoted by Q10s in the decomposition rate of soil organic carbon (SOC) were obtained as 1.4 for no cultivation period and 2.9 for cultivation period (submerged soil condition in flooding season). It suggests that the response of ecosystem carbon exchange differs due to SOC decomposition process which is sensitive to environmental variation during paddy rice cultivation period.

An Analytic Form for the Interresponse Time Analysis of Shull, Gaynor, and Grimes with Applications and Extensions

ERIC Educational Resources Information Center

Kessel, Robert; Lucke, Robert L.

2008-01-01

Shull, Gaynor and Grimes advanced a model for interresponse time distribution using probabilistic cycling between a higher-rate and a lower-rate response process. Both response processes are assumed to be random in time with a constant rate. The cycling between the two processes is assumed to have a constant transition probability that is…

Identification of the dominant runoff pathways from data-based mechanistic modelling of nested catchments in temperate UK

NASA Astrophysics Data System (ADS)

Ockenden, M. C.; Chappell, N. A.

2011-05-01

SummaryUnderstanding hydrological flow pathways is important for modelling stream response, in order to address a range of environmental problems such as flood prediction, prediction of chemical loads and identification of contaminant pathways for subsequent remediation. This paper describes the use of parametrically efficient, low order models to identify the dominant modes of stream response for catchments within the Upper Eden, UK. A first order linear model adequately identified the dominant mode in all but one of the sub-catchments. A consistent pattern of time constants and pure time delays between catchments was observed over different periods of data. In the nested catchments, time constants increased as the catchment size increased from 1.1 km 2 at Gais Gill (2-7 h) to 69.4 km 2 at Kirkby Stephen (5-10 h) to 223.4 km 2 at Great Musgrave (7-16 h) to 616.4 km 2 at Temple Sowerby (11-22 h), but Blind Beck (a small catchment 8.8 km 2, time constants 11-21 h) had time constants most similar to Temple Sowerby. This was attributed to a combination of the storage role of permeable rock strata, where present, and the effect of scale on sub-surface and channel routing. A first order model could not be identified for the 1.0 km 2 Low Hall catchment, which comprises permeable sandstone overlain by Quaternary sediments. A second-order model of Low Hall stream showed a higher proportion of water taking a slower pathway (76% via a slow pathway; time constant 252 h) than a model with the same structure for the 8.8 km 2 Blind Beck (46% via slow pathway; time constant 60 h), where only 38% of the basin was underlain by the same permeable sandstone. This highlights the need to quantify the role of deep pathways through permeable rock, where present, in addition to the effect of catchment size on response times.

Characterizing the physics of plant root gravitropism: A systems modeling approach

NASA Astrophysics Data System (ADS)

Yoder, Thomas Lynn

Root gravitropism is divided into three mechanisms; the gravity sensor, transduction, and differential growth. The gravitropic response has been imitated with various mathematical constructs, but a coherent model based on systems engineering concepts does not exist. The goal of this research is to create models of the gravitropic sensor and differential growth response that are consistent with actual physical characteristics of these mechanisms. The study initially establishes that the amyloplasts within the central columella cells of maize are feasible gravity sensors; statoliths. Video-microscopy studies of live root cap sections are used to quantify the dynamics of the statoliths. Extensive MATLAB analysis of amyloplast sedimentation indicates that an actin network interferes with the free sedimentation of the statoliths. This interference is most significant in the central region of the cell and less significant near the periphery. This obstruction of actin creates a channeling behavior in amyloplasts sedimenting through the cell's central region. The amyloplasts also appear to exhibit cross-correlated motions. Cytochalasin D mediates both the channeling and correlated behaviors, confirming that the obstructive influence is actin-based. The video analysis produced a refined value for maize cytoplasmic viscosity. Efforts to model the differential growth mechanism examined historical growth data from numerous researchers. RELEL (relative elemental elongation) growth data applied to a model set analogous to bi-metallic bending is used. Testing and analysis of the model highlights an extremely high sensitivity of curvature to all RELEL parameters. This sensitivity appears to be the reason for the significant differences between gravitropic responses within like species. Newly observed gravitropic responses, along with historical data, are used to explore the gravitropic time response specifications as opposed to averaging individual time-curvature data into single responses. This approach highlights the significant disadvantages of time-averaging, low sampling rates, and a lack of frequency components being incorporated into the response. A single feedback "black box" model is created so that, along with the sensor and differential growth models, some inferences could be made about the elusive transduction mechanism. Numerous pieces of circumstantial evidence are found that indicate that the gravitropic mechanism is not a single-pathway system.

Response Surface Modeling Using Multivariate Orthogonal Functions

NASA Technical Reports Server (NTRS)

Morelli, Eugene A.; DeLoach, Richard

2001-01-01

A nonlinear modeling technique was used to characterize response surfaces for non-dimensional longitudinal aerodynamic force and moment coefficients, based on wind tunnel data from a commercial jet transport model. Data were collected using two experimental procedures - one based on modem design of experiments (MDOE), and one using a classical one factor at a time (OFAT) approach. The nonlinear modeling technique used multivariate orthogonal functions generated from the independent variable data as modeling functions in a least squares context to characterize the response surfaces. Model terms were selected automatically using a prediction error metric. Prediction error bounds computed from the modeling data alone were found to be- a good measure of actual prediction error for prediction points within the inference space. Root-mean-square model fit error and prediction error were less than 4 percent of the mean response value in all cases. Efficacy and prediction performance of the response surface models identified from both MDOE and OFAT experiments were investigated.

Study of the thermospheric and ionospheric response to the 2009 sudden stratospheric warming using TIME-GCM and GSM TIP models: First results

NASA Astrophysics Data System (ADS)

Klimenko, M. V.; Klimenko, V. V.; Bessarab, F. S.; Korenkov, Yu N.; Liu, Hanli; Goncharenko, L. P.; Tolstikov, M. V.

2015-09-01

This paper presents a study of mesosphere and low thermosphere influence on ionospheric disturbances during 2009 major sudden stratospheric warming (SSW) event. This period was characterized by extremely low solar and geomagnetic activity. The study was performed using two first principal models: thermosphere-ionosphere-mesosphere electrodynamics general circulation model (TIME-GCM) and global self-consistent model of thermosphere, ionosphere, and protonosphere (GSM TIP). The stratospheric anomalies during SSW event were modeled by specifying the temperature and density perturbations at the lower boundary of the TIME-GCM (30 km altitude) according to data from European Centre for Medium-Range Weather Forecasts. Then TIME-GCM output at 80 km was used as lower boundary conditions for driving GSM TIP model runs. We compare models' results with ground-based ionospheric data at low latitudes obtained by GPS receivers in the American longitudinal sector. GSM TIP simulation predicts the occurrence of the quasi-wave vertical structure in neutral temperature disturbances at 80-200 km altitude, and the positive and negative disturbances in total electron content at low latitude during the 2009 SSW event. According to our model results the formation mechanisms of the low-latitude ionospheric response are the disturbances in the n(O)/n(N2) ratio and thermospheric wind. The change in zonal electric field is key mechanism driving the ionospheric response at low latitudes, but our model results do not completely reproduce the variability in zonal electric fields (vertical plasma drift) at low latitudes.

Short-Term Memory Scanning Viewed as Exemplar-Based Categorization

ERIC Educational Resources Information Center

Nosofsky, Robert M.; Little, Daniel R.; Donkin, Christopher; Fific, Mario

2011-01-01

Exemplar-similarity models such as the exemplar-based random walk (EBRW) model (Nosofsky & Palmeri, 1997b) were designed to provide a formal account of multidimensional classification choice probabilities and response times (RTs). At the same time, a recurring theme has been to use exemplar models to account for old-new item recognition and to…

Predicting landscape vegetation dynamics using state-and-transition simulation models

Treesearch

Colin J. Daniel; Leonardo Frid

2012-01-01

This paper outlines how state-and-transition simulation models (STSMs) can be used to project changes in vegetation over time across a landscape. STSMs are stochastic, empirical simulation models that use an adapted Markov chain approach to predict how vegetation will transition between states over time, typically in response to interactions between succession,...

Modeling 100,000-year climate fluctuations in pre-Pleistocene time series

NASA Technical Reports Server (NTRS)

Crowley, Thomas J.; Kim, Kwang-Yul; Mengel, John G.; Short, David A.

1992-01-01

A number of pre-Pleistocene climate records exhibit significant fluctuations at the 100,000-year (100-ky) eccentricity period, before the time of such fluctuations in global ice volume. The origin of these fluctuations has been obscure. Results reported here from a modeling study suggest that such a response can occur over low-altitude land areas involved in monsoon fluctuations. The twice yearly passage of the sun across the equator and the seasonal timing of perihelion interact to increase both 100-ky and 400-ky power in the modeled temperature field. The magnitude of the temperature response is sufficiently large to leave an imprint on the geologic record, and simulated fluctuations resemble those found in records of Triassic lake levels.

A model for incomplete longitudinal multivariate ordinal data.

PubMed

Liu, Li C

2008-12-30

In studies where multiple outcome items are repeatedly measured over time, missing data often occur. A longitudinal item response theory model is proposed for analysis of multivariate ordinal outcomes that are repeatedly measured. Under the MAR assumption, this model accommodates missing data at any level (missing item at any time point and/or missing time point). It allows for multiple random subject effects and the estimation of item discrimination parameters for the multiple outcome items. The covariates in the model can be at any level. Assuming either a probit or logistic response function, maximum marginal likelihood estimation is described utilizing multidimensional Gauss-Hermite quadrature for integration of the random effects. An iterative Fisher-scoring solution, which provides standard errors for all model parameters, is used. A data set from a longitudinal prevention study is used to motivate the application of the proposed model. In this study, multiple ordinal items of health behavior are repeatedly measured over time. Because of a planned missing design, subjects answered only two-third of all items at a given point. Copyright 2008 John Wiley & Sons, Ltd.

Time and Moral Judgment

ERIC Educational Resources Information Center

Suter, Renata S.; Hertwig, Ralph

2011-01-01

Do moral judgments hinge on the time available to render them? According to a recent dual-process model of moral judgment, moral dilemmas that engage emotional processes are likely to result in fast deontological gut reactions. In contrast, consequentialist responses that tot up lives saved and lost in response to such dilemmas would require…

Implementation of a weather responsive traffic estimation and prediction system (TrEPS) for signal timing at Utah DOT.

DOT National Transportation Integrated Search

2014-07-01

The overall goal of this project is to integrate and operationalize weather-sensitive TrEPS models calibrated for the Salt Lake City region to support weather-responsive traffic signal timing implementation and evaluation in the Riverdale corridor in...

Linear system identification via backward-time observer models

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Phan, Minh

1993-01-01

This paper presents an algorithm to identify a state-space model of a linear system using a backward-time approach. The procedure consists of three basic steps. First, the Markov parameters of a backward-time observer are computed from experimental input-output data. Second, the backward-time observer Markov parameters are decomposed to obtain the backward-time system Markov parameters (backward-time pulse response samples) from which a backward-time state-space model is realized using the Eigensystem Realization Algorithm. Third, the obtained backward-time state space model is converted to the usual forward-time representation. Stochastic properties of this approach will be discussed. Experimental results are given to illustrate when and to what extent this concept works.

Developing Predictive Approaches to Characterize Adaptive Responses of the Reproductive Endocrine Axis to Aromatase Inhibition: Computational Modeling

EPA Science Inventory

Exposure to endocrine disrupting chemicals can affect reproduction and development in both humans and wildlife. We developed a mechanistic mathematical model of the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows to predict dose-response and time-course (DRTC)...

Predicting Adaptive Response to Fadrozole Exposure: Computational Model of the Fathead Minnow Hypothalamic-Pituitary-Gonadal Axis

EPA Science Inventory

Exposure to endocrine disrupting chemicals can affect reproduction and development in both humans and wildlife. We are developing a mechanistic mathematical model of the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows to predict dose-response and time-course (...

Adaptive Response in Female Fathead Minnows Exposed to an Aromatase Inhibitor: Computational Modeling of the Hypothalamic-Pituitary-Gonadal Axis

EPA Science Inventory

Exposure to endocrine disrupting chemicals can affect reproduction and development in both humans and wildlife. We are developing a mechanistic computational model of the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows to predict dose-response and time-course ...

Finite-Element Methods for Real-Time Simulation of Surgery

NASA Technical Reports Server (NTRS)

Basdogan, Cagatay

2003-01-01

Two finite-element methods have been developed for mathematical modeling of the time-dependent behaviors of deformable objects and, more specifically, the mechanical responses of soft tissues and organs in contact with surgical tools. These methods may afford the computational efficiency needed to satisfy the requirement to obtain computational results in real time for simulating surgical procedures as described in Simulation System for Training in Laparoscopic Surgery (NPO-21192) on page 31 in this issue of NASA Tech Briefs. Simulation of the behavior of soft tissue in real time is a challenging problem because of the complexity of soft-tissue mechanics. The responses of soft tissues are characterized by nonlinearities and by spatial inhomogeneities and rate and time dependences of material properties. Finite-element methods seem promising for integrating these characteristics of tissues into computational models of organs, but they demand much central-processing-unit (CPU) time and memory, and the demand increases with the number of nodes and degrees of freedom in a given finite-element model. Hence, as finite-element models become more realistic, it becomes more difficult to compute solutions in real time. In both of the present methods, one uses approximate mathematical models trading some accuracy for computational efficiency and thereby increasing the feasibility of attaining real-time up36 NASA Tech Briefs, October 2003 date rates. The first of these methods is based on modal analysis. In this method, one reduces the number of differential equations by selecting only the most significant vibration modes of an object (typically, a suitable number of the lowest-frequency modes) for computing deformations of the object in response to applied forces.

Constitutive Models Based on Compressible Plastic Flows

NASA Technical Reports Server (NTRS)

Rajendran, A. M.

1983-01-01

The need for describing materials under time or cycle dependent loading conditions has been emphasized in recent years by several investigators. In response to the need, various constitutive models describing the nonlinear behavior of materials under creep, fatigue, or other complex loading conditions were developed. The developed models for describing the fully dense (non-porous) materials were mostly based on uncoupled plasticity theory. The improved characterization of materials provides a better understanding of the structual response under complex loading conditions. The pesent studies demonstrate that the rate or time dependency of the response of a porous aggregate can be incorporated into the nonlinear constitutive behavior of a porous solid by appropriately modeling the incompressible matrix behavior. It is also sown that the yield function which wads determined by a continuum mechanics approach must be verified by appropriate experiments on void containing sintered materials in order to obtain meaningful numbers for the constants that appear in the yield function.

Modeling the effect of boost timing in murine irradiated sporozoite prime-boost vaccines

PubMed Central

Zhang, Min; Herrero, Miguel A.; Acosta, Francisco J.; Tsuji, Moriya

2018-01-01

Vaccination with radiation-attenuated sporozoites has been shown to induce CD8+ T cell-mediated protection against pre-erythrocytic stages of malaria. Empirical evidence suggests that successive inoculations often improve the efficacy of this type of vaccines. An initial dose (prime) triggers a specific cellular response, and subsequent inoculations (boost) amplify this response to create a robust CD8+ T cell memory. In this work we propose a model to analyze the effect of T cell dynamics on the performance of prime-boost vaccines. This model suggests that boost doses and timings should be selected according to the T cell response elicited by priming. Specifically, boosting during late stages of clonal contraction would maximize T cell memory production for vaccines using lower doses of irradiated sporozoites. In contrast, single-dose inoculations would be indicated for higher vaccine doses. Experimental data have been obtained that support theoretical predictions of the model. PMID:29329308

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

Evaluation of Different Dose-Response Models for High Hydrostatic Pressure Inactivation of Microorganisms

PubMed Central

2017-01-01

Modeling of microbial inactivation by high hydrostatic pressure (HHP) requires a plot of the log microbial count or survival ratio versus time data under a constant pressure and temperature. However, at low pressure and temperature values, very long holding times are needed to obtain measurable inactivation. Since the time has a significant effect on the cost of HHP processing it may be reasonable to fix the time at an appropriate value and quantify the inactivation with respect to pressure. Such a plot is called dose-response curve and it may be more beneficial than the traditional inactivation modeling since short holding times with different pressure values can be selected and used for the modeling of HHP inactivation. For this purpose, 49 dose-response curves (with at least 4 log10 reduction and ≥5 data points including the atmospheric pressure value (P = 0.1 MPa), and with holding time ≤10 min) for HHP inactivation of microorganisms obtained from published studies were fitted with four different models, namely the Discrete model, Shoulder model, Fermi equation, and Weibull model, and the pressure value needed for 5 log10 (P5) inactivation was calculated for all the models above. The Shoulder model and Fermi equation produced exactly the same parameter and P5 values, while the Discrete model produced similar or sometimes the exact same parameter values as the Fermi equation. The Weibull model produced the worst fit (had the lowest adjusted determination coefficient (R2adj) and highest mean square error (MSE) values), while the Fermi equation had the best fit (the highest R2adj and lowest MSE values). Parameters of the models and also P5 values of each model can be useful for the further experimental design of HHP processing and also for the comparison of the pressure resistance of different microorganisms. Further experiments can be done to verify the P5 values at given conditions. The procedure given in this study can also be extended for enzyme inactivation by HHP. PMID:28880255

Recovery and resilience after a nuclear power plant disaster: a medical decision model for managing an effective, timely, and balanced response.

PubMed

Coleman, C Norman; Blumenthal, Daniel J; Casto, Charles A; Alfant, Michael; Simon, Steven L; Remick, Alan L; Gepford, Heather J; Bowman, Thomas; Telfer, Jana L; Blumenthal, Pamela M; Noska, Michael A

2013-04-01

Resilience after a nuclear power plant or other radiation emergency requires response and recovery activities that are appropriately safe, timely, effective, and well organized. Timely informed decisions must be made, and the logic behind them communicated during the evolution of the incident before the final outcome is known. Based on our experiences in Tokyo responding to the Fukushima Daiichi nuclear power plant crisis, we propose a real-time, medical decision model by which to make key health-related decisions that are central drivers to the overall incident management. Using this approach, on-site decision makers empowered to make interim decisions can act without undue delay using readily available and high-level scientific, medical, communication, and policy expertise. Ongoing assessment, consultation, and adaption to the changing conditions and additional information are additional key features. Given the central role of health and medical issues in all disasters, we propose that this medical decision model, which is compatible with the existing US National Response Framework structure, be considered for effective management of complex, large-scale, and large-consequence incidents.

A competitive binding model predicts the response of mammalian olfactory receptors to mixtures

NASA Astrophysics Data System (ADS)

Singh, Vijay; Murphy, Nicolle; Mainland, Joel; Balasubramanian, Vijay

Most natural odors are complex mixtures of many odorants, but due to the large number of possible mixtures only a small fraction can be studied experimentally. To get a realistic understanding of the olfactory system we need methods to predict responses to complex mixtures from single odorant responses. Focusing on mammalian olfactory receptors (ORs in mouse and human), we propose a simple biophysical model for odor-receptor interactions where only one odor molecule can bind to a receptor at a time. The resulting competition for occupancy of the receptor accounts for the experimentally observed nonlinear mixture responses. We first fit a dose-response relationship to individual odor responses and then use those parameters in a competitive binding model to predict mixture responses. With no additional parameters, the model predicts responses of 15 (of 18 tested) receptors to within 10 - 30 % of the observed values, for mixtures with 2, 3 and 12 odorants chosen from a panel of 30. Extensions of our basic model with odorant interactions lead to additional nonlinearities observed in mixture response like suppression, cooperativity, and overshadowing. Our model provides a systematic framework for characterizing and parameterizing such mixing nonlinearities from mixture response data.

Parenting Predictors of Delay Inhibition in Socioeconomically Disadvantaged Preschoolers

PubMed Central

Merz, Emily C.; Landry, Susan H.; Zucker, Tricia A.; Barnes, Marcia A.; Assel, Michael; Taylor, Heather B.; Lonigan, Christopher J.; Phillips, Beth M.; Clancy-Menchetti, Jeanine; Eisenberg, Nancy; Spinrad, Tracy L.; Valiente, Carlos; de Villiers, Jill; Consortium, the School Readiness Research

2016-01-01

This study examined longitudinal associations between specific parenting factors and delay inhibition in socioeconomically disadvantaged preschoolers. At Time 1, parents and 2- to 4-year-old children (mean age = 3.21 years; N = 247) participated in a videotaped parent-child free play session, and children completed delay inhibition tasks (gift delay-wrap, gift delay-bow, and snack delay tasks). Three months later, at Time 2, children completed the same set of tasks. Parental responsiveness was coded from the parent-child free play sessions, and parental directive language was coded from transcripts of a subset of 127 of these sessions. Structural equation modeling was used, and covariates included age, gender, language skills, parental education, and Time 1 delay inhibition. Results indicated that in separate models, Time 1 parental directive language was significantly negatively associated with Time 2 delay inhibition, and Time 1 parental responsiveness was significantly positively associated with Time 2 delay inhibition. When these parenting factors were entered simultaneously, Time 1 parental directive language significantly predicted Time 2 delay inhibition whereas Time 1 parental responsiveness was no longer significant. Findings suggest that parental language that modulates the amount of autonomy allotted the child may be an important predictor of early delay inhibition skills. PMID:27833461

Electrocoagulation and nanofiltration integrated process application in purification of bilge water using response surface methodology.

PubMed

Akarsu, Ceyhun; Ozay, Yasin; Dizge, Nadir; Elif Gulsen, H; Ates, Hasan; Gozmen, Belgin; Turabik, Meral

Marine pollution has been considered an increasing problem because of the increase in sea transportation day by day. Therefore, a large volume of bilge water which contains petroleum, oil and hydrocarbons in high concentrations is generated from all types of ships. In this study, treatment of bilge water by electrocoagulation/electroflotation and nanofiltration integrated process is investigated as a function of voltage, time, and initial pH with aluminum electrode as both anode and cathode. Moreover, a commercial NF270 flat-sheet membrane was also used for further purification. Box-Behnken design combined with response surface methodology was used to study the response pattern and determine the optimum conditions for maximum chemical oxygen demand (COD) removal and minimum metal ion contents of bilge water. Three independent variables, namely voltage (5-15 V), initial pH (4.5-8.0) and time (30-90 min) were transformed to coded values. The COD removal percent, UV absorbance at 254 nm, pH value (after treatment), and concentration of metal ions (Ti, As, Cu, Cr, Zn, Sr, Mo) were obtained as responses. Analysis of variance results showed that all the models were significant except for Zn (P > 0.05), because the calculated F values for these models were less than the critical F value for the considered probability (P = 0.05). The obtained R(2) and Radj(2) values signified the correlation between the experimental data and predicted responses: except for the model of Zn concentration after treatment, the high R(2) values showed the goodness of fit of the model. While the increase in the applied voltage showed negative effects, the increases in time and pH showed a positive effect on COD removal efficiency; also the most effective linear term was found as time. A positive sign of the interactive coefficients of the voltage-time and pH-time systems indicated synergistic effect on COD removal efficiency, whereas interaction between voltage and pH showed an antagonistic effect.

A simple model for strong ground motions and response spectra

USGS Publications Warehouse

Safak, Erdal; Mueller, Charles; Boatwright, John

1988-01-01

A simple model for the description of strong ground motions is introduced. The model shows that response spectra can be estimated by using only four parameters of the ground motion, the RMS acceleration, effective duration and two corner frequencies that characterize the effective frequency band of the motion. The model is windowed band-limited white noise, and is developed by studying the properties of two functions, cumulative squared acceleration in the time domain, and cumulative squared amplitude spectrum in the frequency domain. Applying the methods of random vibration theory, the model leads to a simple analytical expression for the response spectra. The accuracy of the model is checked by using the ground motion recordings from the aftershock sequences of two different earthquakes and simulated accelerograms. The results show that the model gives a satisfactory estimate of the response spectra.

Viscoelastic dynamic arterial response.

PubMed

Charalambous, Haralambia P; Roussis, Panayiotis C; Giannakopoulos, Antonios E

2017-10-01

Arteries undergo large deformations under applied intraluminal pressure and may exhibit small hysteresis due to creep or relaxation process. The mechanical response of arteries depends, among others, on their topology along the arterial tree. Viscoelasticity of arterial tissues, which is the topic investigated in this study, is mainly a characteristic mechanical response of arteries that are located away from the heart and have increased smooth muscle cells content. The arterial wall viscosity is simulated by adopting a generalized Maxwell model and the method of internal variables, as proposed by Bonet and Holzapfel et al. The total stresses consist of elastic long-term stresses and viscoelastic stresses, requiring an iterative procedure for their calculation. The cross-section of the artery is modeled as a circular ring, consisting of a single homogenized layer, under a time-varying blood pressure. Two different loading approximations for the aortic pressure vs time are considered. A novel numerical method is developed in order to solve the controlling integro-differential equation. A large number of numerical investigations are performed and typical response time-profiles are presented in pictorial form. Results suggest that the viscoelastic arterial response is mainly affected by the ratio of the relaxation time to the characteristic time of the response and by the pressure-time approximation. Numerical examples, based on data available in the literature, are conducted. The investigation presented in this study reveals the effect of each material parameter on the viscoelastic arterial response. Thus, a better understanding of the behavior of viscoelastic arteries is achieved. Copyright © 2017 Elsevier Ltd. All rights reserved.

Incorporating the gas analyzer response time in gas exchange computations.

PubMed

Mitchell, R R

1979-11-01

A simple method for including the gas analyzer response time in the breath-by-breath computation of gas exchange rates is described. The method uses a difference equation form of a model for the gas analyzer in the computation of oxygen uptake and carbon dioxide production and avoids a numerical differentiation required to correct the gas fraction wave forms. The effect of not accounting for analyzer response time is shown to be a 20% underestimation in gas exchange rate. The present method accurately measures gas exchange rate, is relatively insensitive to measurement errors in the analyzer time constant, and does not significantly increase the computation time.

Landscape structure and climate influences on hydrologic response

NASA Astrophysics Data System (ADS)

Nippgen, Fabian; McGlynn, Brian L.; Marshall, Lucy A.; Emanuel, Ryan E.

2011-12-01

Climate variability and catchment structure (topography, geology, vegetation) have a significant influence on the timing and quantity of water discharged from mountainous catchments. How these factors combine to influence runoff dynamics is poorly understood. In this study we linked differences in hydrologic response across catchments and across years to metrics of landscape structure and climate using a simple transfer function rainfall-runoff modeling approach. A transfer function represents the internal catchment properties that convert a measured input (rainfall/snowmelt) into an output (streamflow). We examined modeled mean response time, defined as the average time that it takes for a water input to leave the catchment outlet from the moment it reaches the ground surface. We combined 12 years of precipitation and streamflow data from seven catchments in the Tenderfoot Creek Experimental Forest (Little Belt Mountains, southwestern Montana) with landscape analyses to quantify the first-order controls on mean response times. Differences between responses across the seven catchments were related to the spatial variability in catchment structure (e.g., slope, flowpath lengths, tree height). Annual variability was largely a function of maximum snow water equivalent. Catchment averaged runoff ratios exhibited strong correlations with mean response time while annually averaged runoff ratios were not related to climatic metrics. These results suggest that runoff ratios in snowmelt dominated systems are mainly controlled by topography and not by climatic variability. This approach provides a simple tool for assessing differences in hydrologic response across diverse watersheds and climate conditions.

Modeling the Time-Course of Responses for the Border Ownership Selectivity Based on the Integration of Feedforward Signals and Visual Cortical Interactions

PubMed Central

Wagatsuma, Nobuhiko; Sakai, Ko

2017-01-01

Border ownership (BO) indicates which side of a contour owns a border, and it plays a fundamental role in figure-ground segregation. The majority of neurons in V2 and V4 areas of monkeys exhibit BO selectivity. A physiological work reported that the responses of BO-selective cells show a rapid transition when a presented square is flipped along its classical receptive field (CRF) so that the opposite BO is presented, whereas the transition is significantly slower when a square with a clear BO is replaced by an ambiguous edge, e.g., when the square is enlarged greatly. The rapid transition seemed to reflect the influence of feedforward processing on BO selectivity. Herein, we investigated the role of feedforward signals and cortical interactions for time-courses in BO-selective cells by modeling a visual cortical network comprising V1, V2, and posterior parietal (PP) modules. In our computational model, the recurrent pathways among these modules gradually established the visual progress and the BO assignments. Feedforward inputs mainly determined the activities of these modules. Surrounding suppression/facilitation of early-level areas modulates the activities of V2 cells to provide BO signals. Weak feedback signals from the PP module enhanced the contrast gain extracted in V1, which underlies the attentional modulation of BO signals. Model simulations exhibited time-courses depending on the BO ambiguity, which were caused by the integration delay of V1 and V2 cells and the local inhibition therein given the difference in input stimulus. However, our model did not fully explain the characteristics of crucially slow transition: the responses of BO-selective physiological cells indicated the persistent activation several times longer than that of our model after the replacement with the ambiguous edge. Furthermore, the time-course of BO-selective model cells replicated the attentional modulation of response time in human psychophysical experiments. These attentional modulations for time-courses were induced by selective enhancement of early-level features due to interactions between V1 and PP. Our proposed model suggests fundamental roles of surrounding suppression/facilitation based on feedforward inputs as well as the interactions between early and parietal visual areas with respect to the ambiguity dependence of the neural dynamics in intermediate-level vision. PMID:28163688

Modeling the Time-Course of Responses for the Border Ownership Selectivity Based on the Integration of Feedforward Signals and Visual Cortical Interactions.

PubMed

Wagatsuma, Nobuhiko; Sakai, Ko

2016-01-01

Border ownership (BO) indicates which side of a contour owns a border, and it plays a fundamental role in figure-ground segregation. The majority of neurons in V2 and V4 areas of monkeys exhibit BO selectivity. A physiological work reported that the responses of BO-selective cells show a rapid transition when a presented square is flipped along its classical receptive field (CRF) so that the opposite BO is presented, whereas the transition is significantly slower when a square with a clear BO is replaced by an ambiguous edge, e.g., when the square is enlarged greatly. The rapid transition seemed to reflect the influence of feedforward processing on BO selectivity. Herein, we investigated the role of feedforward signals and cortical interactions for time-courses in BO-selective cells by modeling a visual cortical network comprising V1, V2, and posterior parietal (PP) modules. In our computational model, the recurrent pathways among these modules gradually established the visual progress and the BO assignments. Feedforward inputs mainly determined the activities of these modules. Surrounding suppression/facilitation of early-level areas modulates the activities of V2 cells to provide BO signals. Weak feedback signals from the PP module enhanced the contrast gain extracted in V1, which underlies the attentional modulation of BO signals. Model simulations exhibited time-courses depending on the BO ambiguity, which were caused by the integration delay of V1 and V2 cells and the local inhibition therein given the difference in input stimulus. However, our model did not fully explain the characteristics of crucially slow transition: the responses of BO-selective physiological cells indicated the persistent activation several times longer than that of our model after the replacement with the ambiguous edge. Furthermore, the time-course of BO-selective model cells replicated the attentional modulation of response time in human psychophysical experiments. These attentional modulations for time-courses were induced by selective enhancement of early-level features due to interactions between V1 and PP. Our proposed model suggests fundamental roles of surrounding suppression/facilitation based on feedforward inputs as well as the interactions between early and parietal visual areas with respect to the ambiguity dependence of the neural dynamics in intermediate-level vision.

[Application of three compartment model and response surface model to clinical anesthesia using Microsoft Excel].

PubMed

Abe, Eiji; Abe, Mari

2011-08-01

With the spread of total intravenous anesthesia, clinical pharmacology has become more important. We report Microsoft Excel file applying three compartment model and response surface model to clinical anesthesia. On the Microsoft Excel sheet, propofol, remifentanil and fentanyl effect-site concentrations are predicted (three compartment model), and probabilities of no response to prodding, shaking, surrogates of painful stimuli and laryngoscopy are calculated using predicted effect-site drug concentration. Time-dependent changes in these calculated values are shown graphically. Recent development in anesthetic drug interaction studies are remarkable, and its application to clinical anesthesia with this Excel file is simple and helpful for clinical anesthesia.

A Probabilistic, Dynamic, and Attribute-wise Model of Intertemporal Choice

PubMed Central

Dai, Junyi; Busemeyer, Jerome R.

2014-01-01

Most theoretical and empirical research on intertemporal choice assumes a deterministic and static perspective, leading to the widely adopted delay discounting models. As a form of preferential choice, however, intertemporal choice may be generated by a stochastic process that requires some deliberation time to reach a decision. We conducted three experiments to investigate how choice and decision time varied as a function of manipulations designed to examine the delay duration effect, the common difference effect, and the magnitude effect in intertemporal choice. The results, especially those associated with the delay duration effect, challenged the traditional deterministic and static view and called for alternative approaches. Consequently, various static or dynamic stochastic choice models were explored and fit to the choice data, including alternative-wise models derived from the traditional exponential or hyperbolic discount function and attribute-wise models built upon comparisons of direct or relative differences in money and delay. Furthermore, for the first time, dynamic diffusion models, such as those based on decision field theory, were also fit to the choice and response time data simultaneously. The results revealed that the attribute-wise diffusion model with direct differences, power transformations of objective value and time, and varied diffusion parameter performed the best and could account for all three intertemporal effects. In addition, the empirical relationship between choice proportions and response times was consistent with the prediction of diffusion models and thus favored a stochastic choice process for intertemporal choice that requires some deliberation time to make a decision. PMID:24635188

Titrating decision processes in the mental rotation task.

PubMed

Provost, Alexander; Heathcote, Andrew

2015-10-01

Shepard and Metzler's (1971) seminal mental-rotation task-which requires participants to decide if 1 object is a rotated version of another or its mirror image-has played a central role in the study of spatial cognition. We provide the first quantitative model of behavior in this task that is comprehensive in the sense of simultaneously providing an account of both error rates and the full distribution of response times. We used Brown and Heathcote's (2008) model of choice processing to separate out the contributions of mental rotation and decision stages. This model-based titration process was applied to data from a paradigm where converging evidence supported performance being based on rotation rather than other strategies. Stimuli were similar to Shepard and Metzler's block figures except a long major axis made rotation angle well defined for mirror stimuli, enabling comprehensive modeling of both mirror and normal responses. Results supported a mental rotation stage based on Larsen's (2014) model, where rotation takes a variable amount of time with a mean and variance that increase linearly with rotation angle. Differences in response threshold differences were largely responsible for mirror responses being slowed, and for errors increasing with rotation angle for some participants. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

Model of the transient neurovascular response based on prompt arterial dilation

PubMed Central

Kim, Jung Hwan; Khan, Reswanul; Thompson, Jeffrey K; Ress, David

2013-01-01

Brief neural stimulation results in a stereotypical pattern of vascular and metabolic response that is the basis for popular brain-imaging methods such as functional magnetic resonance imagine. However, the mechanisms of transient oxygen transport and its coupling to cerebral blood flow (CBF) and oxygen metabolism (CMRO2) are poorly understood. Recent experiments show that brief stimulation produces prompt arterial vasodilation rather than venous vasodilation. This work provides a neurovascular response model for brief stimulation based on transient arterial effects using one-dimensional convection–diffusion transport. Hemoglobin oxygen dissociation is included to enable predictions of absolute oxygen concentrations. Arterial CBF response is modeled using a lumped linear flow model, and CMRO2 response is modeled using a gamma function. Using six parameters, the model successfully fit 161/166 measured extravascular oxygen time courses obtained for brief visual stimulation in cat cerebral cortex. Results show how CBF and CMRO2 responses compete to produce the observed features of the hemodynamic response: initial dip, hyperoxic peak, undershoot, and ringing. Predicted CBF and CMRO2 response amplitudes are consistent with experimental measurements. This model provides a powerful framework to quantitatively interpret oxygen transport in the brain; in particular, its intravascular oxygen concentration predictions provide a new model for fMRI responses. PMID:23756690

An efficient energy response model for liquid scintillator detectors

NASA Astrophysics Data System (ADS)

Lebanowski, Logan; Wan, Linyan; Ji, Xiangpan; Wang, Zhe; Chen, Shaomin

2018-05-01

Liquid scintillator detectors are playing an increasingly important role in low-energy neutrino experiments. In this article, we describe a generic energy response model of liquid scintillator detectors that provides energy estimations of sub-percent accuracy. This model fits a minimal set of physically-motivated parameters that capture the essential characteristics of scintillator response and that can naturally account for changes in scintillator over time, helping to avoid associated biases or systematic uncertainties. The model employs a one-step calculation and look-up tables, yielding an immediate estimation of energy and an efficient framework for quantifying systematic uncertainties and correlations.

Incorporating Midbrain Adaptation to Mean Sound Level Improves Models of Auditory Cortical Processing

PubMed Central

Schoppe, Oliver; King, Andrew J.; Schnupp, Jan W.H.; Harper, Nicol S.

2016-01-01

Adaptation to stimulus statistics, such as the mean level and contrast of recently heard sounds, has been demonstrated at various levels of the auditory pathway. It allows the nervous system to operate over the wide range of intensities and contrasts found in the natural world. Yet current standard models of the response properties of auditory neurons do not incorporate such adaptation. Here we present a model of neural responses in the ferret auditory cortex (the IC Adaptation model), which takes into account adaptation to mean sound level at a lower level of processing: the inferior colliculus (IC). The model performs high-pass filtering with frequency-dependent time constants on the sound spectrogram, followed by half-wave rectification, and passes the output to a standard linear–nonlinear (LN) model. We find that the IC Adaptation model consistently predicts cortical responses better than the standard LN model for a range of synthetic and natural stimuli. The IC Adaptation model introduces no extra free parameters, so it improves predictions without sacrificing parsimony. Furthermore, the time constants of adaptation in the IC appear to be matched to the statistics of natural sounds, suggesting that neurons in the auditory midbrain predict the mean level of future sounds and adapt their responses appropriately. SIGNIFICANCE STATEMENT An ability to accurately predict how sensory neurons respond to novel stimuli is critical if we are to fully characterize their response properties. Attempts to model these responses have had a distinguished history, but it has proven difficult to improve their predictive power significantly beyond that of simple, mostly linear receptive field models. Here we show that auditory cortex receptive field models benefit from a nonlinear preprocessing stage that replicates known adaptation properties of the auditory midbrain. This improves their predictive power across a wide range of stimuli but keeps model complexity low as it introduces no new free parameters. Incorporating the adaptive coding properties of neurons will likely improve receptive field models in other sensory modalities too. PMID:26758822

Model for the dynamic responses of taste receptor cells to salty stimuli. I. Function of lipid bilayer membranes.

PubMed Central

Naito, M; Fuchikami, N; Sasaki, N; Kambara, T

1991-01-01

The dynamic response of the lipid bilayer membrane is studied theoretically using a microscopic model of the membrane. The time courses of membrane potential variations due to monovalent salt stimulation are calculated explicitly under various conditions. A set of equations describing the time evolution of membrane surface potential and diffusion potential is derived and solved numerically. It is shown that a rather simple membrane such as lipid bilayer has functions capable of reproducing the following properties of dynamic response observed in gustatory receptor potential. Initial transient depolarization does not occur under Ringer adaptation but does under water. It appears only for comparatively rapid flows of stimuli, the peak height of transient response is expressed by a power function of the flow rate, and the membrane potential gradually decreases after reaching its peak under long and strong stimulation. The dynamic responses in the present model arise from the differences between the time dependences in the surface potential phi s and the diffusion potential phi d across a membrane. Under salt stimulation phi d cannot immediately follow the variation in phi s because of the delay due to the charging up of membrane capacitance. It is suggested that lipid bilayer in the apical membrane is the most probable agency producing the initial phasic response to the stimulation. PMID:1873461

Response of a tethered aerostat to simulated turbulence

NASA Astrophysics Data System (ADS)

Stanney, Keith A.; Rahn, Christopher D.

2006-09-01

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

A coupled aero-structural model of a HAWT blade for dynamic load and response prediction in time-domain for health monitoring applications

NASA Astrophysics Data System (ADS)

Sauder, Heather Scot

To reach the high standards set for renewable energy production in the US and around the globe, wind turbines with taller towers and longer blades are being designed for onshore and offshore wind developments to capture more energy from higher winds aloft and a larger rotor diameter. However, amongst all the wind turbine components wind turbine blades are still the most prone to damage. Given that wind turbine blades experience dynamic loads from multiple sources, there is a need to be able to predict the real-time load, stress distribution and response of the blade in a given wind environment for damage, flutter and fatigue life predictions. Current methods of wind-induced response analysis for wind turbine blades use approximations that are not suitable for wind turbine blade airfoils which are thick, and therefore lead to inaccurate life predictions. Additionally, a time-domain formulation can prove to be especially advantageous for predicting aerodynamic loads on wind turbine blades since they operate in a turbulent atmospheric boundary layer. This will help to analyze the blades on wind turbines that operate individually or in a farm setting where they experience high turbulence in the wake of another wind turbine. A time-domain formulation is also useful for examining the effects of gusty winds that are transient in nature like in gust fronts, thunderstorms or extreme events such as hurricanes, microbursts, and tornadoes. Time-domain methods present the opportunity for real-time health monitoring strategies that can easily be used with finite element methods for prediction of fatigue life or onset of flutter instability. The purpose of the proposed work is to develop a robust computational model to predict the loads, stresses and response of a wind turbine blade in operating and extreme wind conditions. The model can be used to inform health monitoring strategies for preventative maintenance and provide a realistic number of stress cycles that the blade will experience for fatigue life prediction procedures. To fill in the gaps in the existing knowledge and meet the overall goal of the proposed research, the following objectives were accomplished: (a) improve the existing aeroelastic (motion- and turbulence-induced) load models to predict the response of wind turbine blade airfoils to understand its behavior in turbulent wind, (b) understand, model and predict the response of wind turbine blades in transient or gusty wind, boundary-layer wind and incoherent wind over the span of the blade, (c) understand the effects of aero-structural coupling between the along-wind, cross-wind and torsional vibrations, and finally (d) develop a computational tool using the improved time-domain load model to predict the real-time load, stress distribution and response of a given wind turbine blade during operating and parked conditions subject to a specific wind environment both in a short and long term for damage, flutter and fatigue life predictions.

Feedback control design for non-inductively sustained scenarios in NSTX-U using TRANSP

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

Boyer, M. D.; Andre, R. G.; Gates, D. A.

This paper examines a method for real-time control of non-inductively sustained scenarios in NSTX-U by using TRANSP, a time-dependent integrated modeling code for prediction and interpretive analysis of tokamak experimental data, as a simulator. The actuators considered for control in this work are the six neutral beam sources and the plasma boundary shape. To understand the response of the plasma current, stored energy, and central safety factor to these actuators and to enable systematic design of control algorithms, simulations were run in which the actuators were modulated and a linearized dynamic response model was generated. A multi-variable model-based control schememore » that accounts for the coupling and slow dynamics of the system while mitigating the effect of actuator limitations was designed and simulated. Simulations show that modest changes in the outer gap and heating power can improve the response time of the system, reject perturbations, and track target values of the controlled values.« less

Feedback control design for non-inductively sustained scenarios in NSTX-U using TRANSP

DOE PAGES

Boyer, M. D.; Andre, R. G.; Gates, D. A.; ...

2017-04-24

This paper examines a method for real-time control of non-inductively sustained scenarios in NSTX-U by using TRANSP, a time-dependent integrated modeling code for prediction and interpretive analysis of tokamak experimental data, as a simulator. The actuators considered for control in this work are the six neutral beam sources and the plasma boundary shape. To understand the response of the plasma current, stored energy, and central safety factor to these actuators and to enable systematic design of control algorithms, simulations were run in which the actuators were modulated and a linearized dynamic response model was generated. A multi-variable model-based control schememore » that accounts for the coupling and slow dynamics of the system while mitigating the effect of actuator limitations was designed and simulated. Simulations show that modest changes in the outer gap and heating power can improve the response time of the system, reject perturbations, and track target values of the controlled values.« less

Feedback control design for non-inductively sustained scenarios in NSTX-U using TRANSP

NASA Astrophysics Data System (ADS)

Boyer, M. D.; Andre, R. G.; Gates, D. A.; Gerhardt, S. P.; Menard, J. E.; Poli, F. M.

2017-06-01

This paper examines a method for real-time control of non-inductively sustained scenarios in NSTX-U by using TRANSP, a time-dependent integrated modeling code for prediction and interpretive analysis of tokamak experimental data, as a simulator. The actuators considered for control in this work are the six neutral beam sources and the plasma boundary shape. To understand the response of the plasma current, stored energy, and central safety factor to these actuators and to enable systematic design of control algorithms, simulations were run in which the actuators were modulated and a linearized dynamic response model was generated. A multi-variable model-based control scheme that accounts for the coupling and slow dynamics of the system while mitigating the effect of actuator limitations was designed and simulated. Simulations show that modest changes in the outer gap and heating power can improve the response time of the system, reject perturbations, and track target values of the controlled values.

Searching for serial refreshing in working memory: Using response times to track the content of the focus of attention over time.

PubMed

Vergauwe, Evie; Hardman, Kyle O; Rouder, Jeffrey N; Roemer, Emily; McAllaster, Sara; Cowan, Nelson

2016-12-01

One popular idea is that, to support the maintenance of a set of elements over brief periods of time, the focus of attention rotates among the different elements, thereby serially refreshing the content of working memory (WM). In the research reported here, probe letters were presented between to-be-remembered letters, and response times to these probes were used to infer the status of the different items in WM. If the focus of attention cycles from one item to the next, its content should be different at different points in time, and this should be reflected in a change in the response time patterns over time. Across a set of four experiments, we demonstrated a striking pattern of invariance in the response time patterns over time, suggesting either that the content of the focus of attention did not change over time or that response times cannot be used to infer the content of the focus of attention. We discuss how this pattern constrains models of WM, attention, and human information processing.

Hardware Model of a Shipboard Generator

DTIC Science & Technology

2009-05-19

controller output PM motor power RM motor resistance Td derivative time constant Tf1 fuel valve time constant Tg1 governor time constant Tg2 governor...in speed, sending a response signal to the fuel valve that regulates gas turbine power. At this point, there is an inherent variation between the...basic response analysis [5]. 29 Electrical Power Rotor Inertia Amplifiers Fuel Valve Turbine Dynamics Rotational Friction and Windage

Identification of Synchronous Machine Stability - Parameters: AN On-Line Time-Domain Approach.

NASA Astrophysics Data System (ADS)

Le, Loc Xuan

1987-09-01

A time-domain modeling approach is described which enables the stability-study parameters of the synchronous machine to be determined directly from input-output data measured at the terminals of the machine operating under normal conditions. The transient responses due to system perturbations are used to identify the parameters of the equivalent circuit models. The described models are verified by comparing their responses with the machine responses generated from the transient stability models of a small three-generator multi-bus power system and of a single -machine infinite-bus power network. The least-squares method is used for the solution of the model parameters. As a precaution against ill-conditioned problems, the singular value decomposition (SVD) is employed for its inherent numerical stability. In order to identify the equivalent-circuit parameters uniquely, the solution of a linear optimization problem with non-linear constraints is required. Here, the SVD appears to offer a simple solution to this otherwise difficult problem. Furthermore, the SVD yields solutions with small bias and, therefore, physically meaningful parameters even in the presence of noise in the data. The question concerning the need for a more advanced model of the synchronous machine which describes subtransient and even sub-subtransient behavior is dealt with sensibly by the concept of condition number. The concept provides a quantitative measure for determining whether such an advanced model is indeed necessary. Finally, the recursive SVD algorithm is described for real-time parameter identification and tracking of slowly time-variant parameters. The algorithm is applied to identify the dynamic equivalent power system model.

Phenomenology and Signal Processing for UXO/Clutter Discrimination

DTIC Science & Technology

2009-08-01

29 Figure 25. (a) Pasion -Oldenburg model fit to the EMI response of a 4.2 inch mortar aligned transverse to the primary field...b) Comparison between the two-component and Pasion - Oldenburg model fits to the 4.2 inch mortar response...30 Figure 26. Pasion -Oldenburg exponent γ compared to the magnetic crossover time τM for model fits to EMI data collected

A two-phase flow model for submarine granular flows: With an application to collapse of deeply-submerged granular columns

NASA Astrophysics Data System (ADS)

Lee, Cheng-Hsien; Huang, Zhenhua

2018-05-01

The collapse process of a submerged granular column is strongly affected by its initial packing. Previous models for particle response time, which is used to quantify the drag force between the solid and liquid phases in rheology-based two-phase flow models, have difficulty in simulating the collapse process of granular columns with different initial concentrations (initial packing conditions). This study introduces a new model for particle response time, which enables us to satisfactorily model the drag force between the two phases for a wide range of volume concentration. The present model can give satisfactory results for both loose and dense packing conditions. The numerical results have shown that (i) the initial packing affects the occurrence of contractancy/diltancy behavior during the collapse process, (ii) the general buoyancy and drag force are strongly affected by the initial packing through contractancy and diltancy, and (iii) the general buoyancy and drag force can destabilize the granular material in loose packing condition but stabilize the granular material in dense packing condition. The results have shown that the collapse process of a densely-packed granular column is more sensitive to particle response time than that of a loosely-packed granular column.

Puget Sound Operational Forecast System - A Real-time Predictive Tool for Marine Resource Management and Emergency Responses

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

Yang, Zhaoqing; Khangaonkar, Tarang; Chase, Jared M.

2009-12-01

To support marine ecological resource management and emergency response and to enhance scientific understanding of physical and biogeochemical processes in Puget Sound, a real-time Puget Sound Operational Forecast System (PS-OFS) was developed by the Coastal Ocean Dynamics & Ecosystem Modeling group (CODEM) of Pacific Northwest National Laboratory (PNNL). PS-OFS employs the state-of-the-art three-dimensional coastal ocean model and closely follows the standards and procedures established by National Oceanic and Atmospheric Administration (NOAA) National Ocean Service (NOS). PS-OFS consists of four key components supporting the Puget Sound Circulation and Transport Model (PS-CTM): data acquisition, model execution and product archive, model skill assessment,more » and model results dissemination. This paper provides an overview of PS-OFS and its ability to provide vital real-time oceanographic information to the Puget Sound community. PS-OFS supports pacific northwest region’s growing need for a predictive tool to assist water quality management, fish stock recovery efforts, maritime emergency response, nearshore land-use planning, and the challenge of climate change and sea level rise impacts. The structure of PS-OFS and examples of the system inputs and outputs, forecast results are presented in details.« less

Critical scales to explain urban hydrological response: an application in Cranbrook, London

NASA Astrophysics Data System (ADS)

Cristiano, Elena; ten Veldhuis, Marie-Claire; Gaitan, Santiago; Ochoa Rodriguez, Susana; van de Giesen, Nick

2018-04-01

Rainfall variability in space and time, in relation to catchment characteristics and model complexity, plays an important role in explaining the sensitivity of hydrological response in urban areas. In this work we present a new approach to classify rainfall variability in space and time and we use this classification to investigate rainfall aggregation effects on urban hydrological response. Nine rainfall events, measured with a dual polarimetric X-Band radar instrument at the CAESAR site (Cabauw Experimental Site for Atmospheric Research, NL), were aggregated in time and space in order to obtain different resolution combinations. The aim of this work was to investigate the influence that rainfall and catchment scales have on hydrological response in urban areas. Three dimensionless scaling factors were introduced to investigate the interactions between rainfall and catchment scale and rainfall input resolution in relation to the performance of the model. Results showed that (1) rainfall classification based on cluster identification well represents the storm core, (2) aggregation effects are stronger for rainfall than flow, (3) model complexity does not have a strong influence compared to catchment and rainfall scales for this case study, and (4) scaling factors allow the adequate rainfall resolution to be selected to obtain a given level of accuracy in the calculation of hydrological response.

Thermosphere Global Time Response to Geomagnetic Storms Caused by Coronal Mass Ejections

NASA Astrophysics Data System (ADS)

Oliveira, D. M.; Zesta, E.; Schuck, P. W.; Sutton, E. K.

2017-10-01

We investigate, for the first time with a spatial superposed epoch analysis study, the thermosphere global time response to 159 geomagnetic storms caused by coronal mass ejections (CMEs) observed in the solar wind at Earth's orbit during the period of September 2001 to September 2011. The thermosphere neutral mass density is obtained from the CHAMP (CHAllenge Mini-Satellite Payload) and GRACE (Gravity Recovery Climate Experiment) spacecraft. All density measurements are intercalibrated against densities computed by the Jacchia-Bowman 2008 empirical model under the regime of very low geomagnetic activity. We explore both the effects of the pre-CME shock impact on the thermosphere and of the storm main phase onset by taking their times of occurrence as zero epoch times (CME impact and interplanetary magnetic field Bz southward turning) for each storm. We find that the shock impact produces quick and transient responses at the two high-latitude regions with minimal propagation toward lower latitudes. In both cases, thermosphere is heated in very high latitude regions within several minutes. The Bz southward turning of the storm onset has a fast heating manifestation at the two high-latitude regions, and it takes approximately 3 h for that heating to propagate down to equatorial latitudes and to globalize in the thermosphere. This heating propagation is presumably accomplished, at least in part, with traveling atmospheric disturbances and complex meridional wind structures. Current models use longer lag times in computing thermosphere density dynamics during storms. Our results suggest that the thermosphere response time scales are shorter and should be accordingly adjusted in thermospheric empirical models.

How does the predicted geomagnetic main field variation alter the thermosphere-ionosphere storm-time response?

NASA Astrophysics Data System (ADS)

Maute, A. I.; Lu, G.; Richmond, A. D.

2017-12-01

Earth's magnetic main field plays an important role in the thermosphere-ionosphere (TI) system, as well as its coupling to Earth's magnetosphere. The ionosphere consists of a weakly ionized plasma strongly influenced by the main field and embedded in the thermosphere. Therefore, ion-neutral coupling and ionospheric electrodynamics can influence the plasma distribution and neutral dynamics. There are strong longitude variations of the TI storm response. At high latitude magnetosphere-ionosphere coupling is organized by the geomagnetic main field, leading in general to stronger northern middle latitude storm time response in the American sector due to the geomagnetic dipole location. In addition, the weak geomagnetic main field in the American sector leads to larger local ExB drift and can alter the plasma densities. During geomagnetic storms the intense energy input into the high latitude region is redistributed globally, leading to thermospheric heating, wind circulation changes and alterations of the ionospheric electrodynamics. The storm time changes are measurable in the plasma density, ion drift, temperature, neutral composition, and other parameters. All these changes depend, to some degree, on the geomagnetic main field which changes on decadal time scales. In this study, we employ a forecast model of the geomagnetic main field based on data assimilation and geodynamo modeling [Aubert et al., 2015]. The main field model predicts that in 50 years the South Atlantic Anomaly is further weakened by 2 mT and drifts westward by approximately 10o. The dipole axis moves northward and westward by 2o and 6o, respectively. Simulating the March 2015 geomagnetic storm with the Thermosphere-Ionosphere Electrodynamics General Circulation Model (TIE-GCM) driven by the Assimilative Mapping of Ionospheric Electrodynamics (AMIE), we evaluate the thermosphere-ionosphere response using the geomagnetic main field of 2015, 2065, and 2115. We compare the TI response for 2015 with available satellite data, e.g. Swarm and COSMIC, and discuss the changes in the TI response due to the predicted main field changes to identify regions of potential increase and decrease in the storm time response. Aubert, J., Geophys. J. Int. 203, 1738-1751, 2015, doi: 10.1093/gji/ggv394 .

A zebrafish larval model reveals early tissue-specific innate immune responses to Mucor circinelloides.

PubMed

Voelz, Kerstin; Gratacap, Remi L; Wheeler, Robert T

2015-11-01

Mucormycosis is an emerging fungal infection that is clinically difficult to manage, with increasing incidence and extremely high mortality rates. Individuals with diabetes, suppressed immunity or traumatic injury are at increased risk of developing disease. These individuals often present with defects in phagocytic effector cell function. Research using mammalian models and phagocytic effector cell lines has attempted to decipher the importance of the innate immune system in host defence against mucormycosis. However, these model systems have not been satisfactory for direct analysis of the interaction between innate immune effector cells and infectious sporangiospores in vivo. Here, we report the first real-time in vivo analysis of the early innate immune response to mucormycete infection using a whole-animal zebrafish larval model system. We identified differential host susceptibility, dependent on the site of infection (hindbrain ventricle and swim bladder), as well as differential functions of the two major phagocyte effector cell types in response to viable and non-viable spores. Larval susceptibility to mucormycete spore infection was increased upon immunosuppressant treatment. We showed for the first time that macrophages and neutrophils were readily recruited in vivo to the site of infection in an intact host and that spore phagocytosis can be observed in real-time in vivo. While exploring innate immune effector recruitment dynamics, we discovered the formation of phagocyte clusters in response to fungal spores that potentially play a role in fungal spore dissemination. Spores failed to activate pro-inflammatory gene expression by 6 h post-infection in both infection models. After 24 h, induction of a pro-inflammatory response was observed only in hindbrain ventricle infections. Only a weak pro-inflammatory response was initiated after spore injection into the swim bladder during the same time frame. In the future, the zebrafish larva as a live whole-animal model system will contribute greatly to the study of molecular mechanisms involved in the interaction of the host innate immune system with fungal spores during mucormycosis. © 2015. Published by The Company of Biologists Ltd.

Real-time simulation of the nonlinear visco-elastic deformations of soft tissues.

PubMed

Basafa, Ehsan; Farahmand, Farzam

2011-05-01

Mass-spring-damper (MSD) models are often used for real-time surgery simulation due to their fast response and fairly realistic deformation replication. An improved real time simulation model of soft tissue deformation due to a laparoscopic surgical indenter was developed and tested. The mechanical realization of conventional MSD models was improved using nonlinear springs and nodal dampers, while their high computational efficiency was maintained using an adapted implicit integration algorithm. New practical algorithms for model parameter tuning, collision detection, and simulation were incorporated. The model was able to replicate complex biological soft tissue mechanical properties under large deformations, i.e., the nonlinear and viscoelastic behaviors. The simulated response of the model after tuning of its parameters to the experimental data of a deer liver sample, closely tracked the reference data with high correlation and maximum relative differences of less than 5 and 10%, for the tuning and testing data sets respectively. Finally, implementation of the proposed model and algorithms in a graphical environment resulted in a real-time simulation with update rates of 150 Hz for interactive deformation and haptic manipulation, and 30 Hz for visual rendering. The proposed real time simulation model of soft tissue deformation due to a laparoscopic surgical indenter was efficient, realistic, and accurate in ex vivo testing. This model is a suitable candidate for testing in vivo during laparoscopic surgery.

Time-Domain Full-Wave Modeling of Nonlinear Air Breakdown in High-Power Microwave Devices and Systems

DTIC Science & Technology

2017-09-30

AFRL-RD-PS- AFRL-RD-PS- TR-2017-0047 TR-2017-0047 TIME -DOMAIN FULL-WAVE MODELING OF NONLINEAR AIR BREAKDOWN IN HIGH-POWER MICROWAVE...Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions...TITLE AND SUBTITLE Time -Domain Full-Wave Modeling of Nonlinear Air Breakdown in High-Power Microwave Devices and Systems 5a. CONTRACT NUMBER 5b

Parsimonious Hydrologic and Nitrate Response Models For Silver Springs, Florida

NASA Astrophysics Data System (ADS)

Klammler, Harald; Yaquian-Luna, Jose Antonio; Jawitz, James W.; Annable, Michael D.; Hatfield, Kirk

2014-05-01

Silver Springs with an approximate discharge of 25 m3/sec is one of Florida's first magnitude springs and among the largest springs worldwide. Its 2500-km2 springshed overlies the mostly unconfined Upper Floridan Aquifer. The aquifer is approximately 100 m thick and predominantly consists of porous, fractured and cavernous limestone, which leads to excellent surface drainage properties (no major stream network other than Silver Springs run) and complex groundwater flow patterns through both rock matrix and fast conduits. Over the past few decades, discharge from Silver Springs has been observed to slowly but continuously decline, while nitrate concentrations in the spring water have enormously increased from a background level of 0.05 mg/l to over 1 mg/l. In combination with concurrent increases in algae growth and turbidity, for example, and despite an otherwise relatively stable water quality, this has given rise to concerns about the ecological equilibrium in and near the spring run as well as possible impacts on tourism. The purpose of the present work is to elaborate parsimonious lumped parameter models that may be used by resource managers for evaluating the springshed's hydrologic and nitrate transport responses. Instead of attempting to explicitly consider the complex hydrogeologic features of the aquifer in a typically numerical and / or stochastic approach, we use a transfer function approach wherein input signals (i.e., time series of groundwater recharge and nitrate loading) are transformed into output signals (i.e., time series of spring discharge and spring nitrate concentrations) by some linear and time-invariant law. The dynamic response types and parameters are inferred from comparing input and output time series in frequency domain (e.g., after Fourier transformation). Results are converted into impulse (or step) response functions, which describe at what time and to what magnitude a unitary change in input manifests at the output. For the hydrologic response model, frequency spectra of groundwater recharge and spring discharge suggest an exponential response model, which may explain a significant portion of spring discharge variability with only two fitting parameters (mean response time 2.4 years). For the transport model, direct use of nitrate data is confounded by inconsistent data and a strong trend. Instead, chloride concentrations in rainfall and at the spring are investigated as a surrogate candidate. Preliminary results indicate that the transport response function of the springshed as a whole may be of the gamma type, which possesses both a larger initial peak as well as a longer tail than the exponential response function. This is consistent with the large range of travel times to be expected between input directly into fast conduits connected to the spring (e.g., though sinkholes) and input or back-diffusion from the rock matrix. The result implies that reductions in nitrate input, especially at remote and hydraulically not well connected locations, will only manifest in a rather delayed and smoothed out form in concentration observed at the spring.

Impulse response of a two-dimensional rough surface overlying an inhomogeneous, nondispersive medium: A hybrid model

NASA Astrophysics Data System (ADS)

Keiffer, Richard; Novarini, Jorge; Norton, Guy

2002-11-01

A numerical model to calculate the impulse response of a two-dimensional, impenetrable, rough surface directly in the time domain has been recently introduced [R. S. Keiffer and J. C. Novarini, J. Acoust. Soc. Am. 107, 27-39 (2000)]. This model is based on wedge diffraction theory and assumes the half-space containing the source and receiver is homogeneous. In this work, the model is extended to handle media where the index of refraction varies with depth by merging the scattering model with a ray-based propagation model. The resulting hybrid model is tested against a finite-difference time-domain (FDTD) method for backscattering from a corrugated surface in the presence of a refractive layer. This new model can be applied, for example, to calculate acoustic reverberation from the sea surface in cases where the water mass is inhomogeneous and dispersion is negligible. [Work supported by ONR/NRL (PE 61153N-32) and by grants of computer time DoD HPC Shared Resource Center at Stennis Space Center, MS.

Using Micro-computed Tomography for the Assessment of Tumor Development and Follow-up of Response to Treatment in a Mouse Model of Lung Cancer.

PubMed

Hegab, Ahmed E; Kameyama, Naofumi; Kuroda, Aoi; Kagawa, Shizuko; Yin, Yongjun; Ornitz, David; Betsuyaku, Tomoko

2016-05-20

Lung cancer is the most lethal cancer in the world. Intensive research is ongoing worldwide to identify new therapies for lung cancer. Several mouse models of lung cancer are being used to study the mechanism of cancer development and to experiment with various therapeutic strategies. However, the absence of a real-time technique to identify the development of tumor nodules in mice lungs and to monitor the changes in their size in response to various experimental and therapeutic interventions hampers the ability to obtain an accurate description of the course of the disease and its timely response to treatments. In this study, a method using a micro-computed tomography (CT) scanner for the detection of the development of lung tumors in a mouse model of lung adenocarcinoma is described. Next, we show that monthly follow-up with micro-CT can identify dynamic changes in the lung tumor, such as the appearance of additional nodules, increase in the size of previously detected nodules, and decrease in the size or complete resolution of nodules in response to treatment. Finally, the accuracy of this real-time assessment method was confirmed with end-point histological quantification. This technique paves the way for planning and conducting more complex experiments on lung cancer animal models, and it enables us to better understand the mechanisms of carcinogenesis and the effects of different treatment modalities while saving time and resources.

A Second-Order Conditionally Linear Mixed Effects Model with Observed and Latent Variable Covariates

ERIC Educational Resources Information Center

Harring, Jeffrey R.; Kohli, Nidhi; Silverman, Rebecca D.; Speece, Deborah L.

2012-01-01

A conditionally linear mixed effects model is an appropriate framework for investigating nonlinear change in a continuous latent variable that is repeatedly measured over time. The efficacy of the model is that it allows parameters that enter the specified nonlinear time-response function to be stochastic, whereas those parameters that enter in a…

Economic value of big game habitat production from natural and prescribed fire

Treesearch

Armando Gonzalez-Caban; John B. Loomis; Dana Griffin; Elen Wu; Daniel McCollum; Jane McKeever; Diane Freeman

2003-01-01

A macro time-series model and a micro GIS model were used to estimate a production function relating deer harvest response to prescribed fire, holding constant other environmental variables. The macro time-series model showed a marginal increase in deer harvested of 33 for an increase of 1,100 acres of prescribed burn. The marginal deer increase for the micro GIS model...

Lawsuit lead time prediction: Comparison of data mining techniques based on categorical response variable.

PubMed

Gruginskie, Lúcia Adriana Dos Santos; Vaccaro, Guilherme Luís Roehe

2018-01-01

The quality of the judicial system of a country can be verified by the overall length time of lawsuits, or the lead time. When the lead time is excessive, a country's economy can be affected, leading to the adoption of measures such as the creation of the Saturn Center in Europe. Although there are performance indicators to measure the lead time of lawsuits, the analysis and the fit of prediction models are still underdeveloped themes in the literature. To contribute to this subject, this article compares different prediction models according to their accuracy, sensitivity, specificity, precision, and F1 measure. The database used was from TRF4-the Tribunal Regional Federal da 4a Região-a federal court in southern Brazil, corresponding to the 2nd Instance civil lawsuits completed in 2016. The models were fitted using support vector machine, naive Bayes, random forests, and neural network approaches with categorical predictor variables. The lead time of the 2nd Instance judgment was selected as the response variable measured in days and categorized in bands. The comparison among the models showed that the support vector machine and random forest approaches produced measurements that were superior to those of the other models. The evaluation of the models was made using k-fold cross-validation similar to that applied to the test models.

A biophysical model examining the role of low-voltage-activated potassium currents in shaping the responses of vestibular ganglion neurons.

PubMed

Hight, Ariel E; Kalluri, Radha

2016-08-01

The vestibular nerve is characterized by two broad groups of neurons that differ in the timing of their interspike intervals; some fire at highly regular intervals, whereas others fire at highly irregular intervals. Heterogeneity in ion channel properties has been proposed as shaping these firing patterns (Highstein SM, Politoff AL. Brain Res 150: 182-187, 1978; Smith CE, Goldberg JM. Biol Cybern 54: 41-51, 1986). Kalluri et al. (J Neurophysiol 104: 2034-2051, 2010) proposed that regularity is controlled by the density of low-voltage-activated potassium currents (IKL). To examine the impact of IKL on spike timing regularity, we implemented a single-compartment model with three conductances known to be present in the vestibular ganglion: transient sodium (gNa), low-voltage-activated potassium (gKL), and high-voltage-activated potassium (gKH). Consistent with in vitro observations, removing gKL depolarized resting potential, increased input resistance and membrane time constant, and converted current step-evoked firing patterns from transient (1 spike at current onset) to sustained (many spikes). Modeled neurons were driven with a time-varying synaptic conductance that captured the random arrival times and amplitudes of glutamate-driven synaptic events. In the presence of gKL, spiking occurred only in response to large events with fast onsets. Models without gKL exhibited greater integration by responding to the superposition of rapidly arriving events. Three synaptic conductance were modeled, each with different kinetics to represent a variety of different synaptic processes. In response to all three types of synaptic conductance, models containing gKL produced spike trains with irregular interspike intervals. Only models lacking gKL when driven by rapidly arriving small excitatory postsynaptic currents were capable of generating regular spiking. Copyright © 2016 the American Physiological Society.

Simple Climate Model Evaluation Using Impulse Response Tests

NASA Astrophysics Data System (ADS)

Schwarber, A.; Hartin, C.; Smith, S. J.

2017-12-01

Simple climate models (SCMs) are central tools used to incorporate climate responses into human-Earth system modeling. SCMs are computationally inexpensive, making them an ideal tool for a variety of analyses, including consideration of uncertainty. Despite their wide use, many SCMs lack rigorous testing of their fundamental responses to perturbations. Here, following recommendations of a recent National Academy of Sciences report, we compare several SCMs (Hector-deoclim, MAGICC 5.3, MAGICC 6.0, and the IPCC AR5 impulse response function) to diagnose model behavior and understand the fundamental system responses within each model. We conduct stylized perturbations (emissions and forcing/concentration) of three different chemical species: CO2, CH4, and BC. We find that all 4 models respond similarly in terms of overall shape, however, there are important differences in the timing and magnitude of the responses. For example, the response to a BC pulse differs over the first 20 years after the pulse among the models, a finding that is due to differences in model structure. Such perturbation experiments are difficult to conduct in complex models due to internal model noise, making a direct comparison with simple models challenging. We can, however, compare the simplified model response from a 4xCO2 step experiment to the same stylized experiment carried out by CMIP5 models, thereby testing the ability of SCMs to emulate complex model results. This work allows an assessment of how well current understanding of Earth system responses are incorporated into multi-model frameworks by way of simple climate models.

Input-output relationship in social communications characterized by spike train analysis

NASA Astrophysics Data System (ADS)

Aoki, Takaaki; Takaguchi, Taro; Kobayashi, Ryota; Lambiotte, Renaud

2016-10-01

We study the dynamical properties of human communication through different channels, i.e., short messages, phone calls, and emails, adopting techniques from neuronal spike train analysis in order to characterize the temporal fluctuations of successive interevent times. We first measure the so-called local variation (LV) of incoming and outgoing event sequences of users and find that these in- and out-LV values are positively correlated for short messages and uncorrelated for phone calls and emails. Second, we analyze the response-time distribution after receiving a message to focus on the input-output relationship in each of these channels. We find that the time scales and amplitudes of response differ between the three channels. To understand the effects of the response-time distribution on the correlations between the LV values, we develop a point process model whose activity rate is modulated by incoming and outgoing events. Numerical simulations of the model indicate that a quick response to incoming events and a refractory effect after outgoing events are key factors to reproduce the positive LV correlations.

Evaluating Curriculum-Based Measurement from a Behavioral Assessment Perspective

ERIC Educational Resources Information Center

Ardoin, Scott P.; Roof, Claire M.; Klubnick, Cynthia; Carfolite, Jessica

2008-01-01

Curriculum-based measurement Reading (CBM-R) is an assessment procedure used to evaluate students' relative performance compared to peers and to evaluate their growth in reading. Within the response to intervention (RtI) model, CBM-R data are plotted in time series fashion as a means modeling individual students' response to varying levels of…

Gradual Growth versus Shape Invariance in Perceptual Decision Making

ERIC Educational Resources Information Center

Rouder, Jeffrey N.; Yue, Yu; Speckman, Paul L.; Pratte, Michael S.; Province, Jordan M.

2010-01-01

A dominant theme in modeling human perceptual judgments is that sensory neural activity is summed or integrated until a critical bound is reached. Such models predict that, in general, the shape of response time distributions change across conditions, although in practice, this shape change may be subtle. An alternative view is that response time…

Computational Modeling of Hypothalamic-Pituitary-Gonadal Axis to Predict Adaptive Responses in Female Fathead Minnows Exposed to an Aromatase Inhibitor

EPA Science Inventory

Exposure to endocrine disrupting chemicals can affect reproduction and development in both humans and wildlife. We are developing a mechanistic computational model of the hypothalamic-pituitary-gonadal (HPG) axis in female fathead minnows to predict dose response and time-course...

V/STOL tilt rotor aircraft study mathematical model for a real time simulation of a tilt rotor aircraft (Boeing Vertol Model 222), volume 8

NASA Technical Reports Server (NTRS)

Rosenstein, H.; Mcveigh, M. A.; Mollenkof, P. A.

1973-01-01

A mathematical model for a real time simulation of a tilt rotor aircraft was developed. The mathematical model is used for evaluating aircraft performance and handling qualities. The model is based on an eleven degree of freedom total force representation. The rotor is treated as a point source of forces and moments with appropriate response time lags and actuator dynamics. The aerodynamics of the wing, tail, rotors, landing gear, and fuselage are included.

TimeXNet Web: Identifying cellular response networks from diverse omics time-course data.

PubMed

Tan, Phit Ling; López, Yosvany; Nakai, Kenta; Patil, Ashwini

2018-05-14

Condition-specific time-course omics profiles are frequently used to study cellular response to stimuli and identify associated signaling pathways. However, few online tools allow users to analyze multiple types of high-throughput time-course data. TimeXNet Web is a web server that extracts a time-dependent gene/protein response network from time-course transcriptomic, proteomic or phospho-proteomic data, and an input interaction network. It classifies the given genes/proteins into time-dependent groups based on the time of their highest activity and identifies the most probable paths connecting genes/proteins in consecutive groups. The response sub-network is enriched in activated genes/proteins and contains novel regulators that do not show any observable change in the input data. Users can view the resultant response network and analyze it for functional enrichment. TimeXNet Web supports the analysis of high-throughput data from multiple species by providing high quality, weighted protein-protein interaction networks for 12 model organisms. http://txnet.hgc.jp/. ashwini@hgc.jp. Supplementary data are available at Bioinformatics online.

Gaps in knowledge and data driving uncertainty in models of photosynthesis.

PubMed

Dietze, Michael C

2014-02-01

Regional and global models of the terrestrial biosphere depend critically on models of photosynthesis when predicting impacts of global change. This paper focuses on identifying the primary data needs of these models, what scales drive uncertainty, and how to improve measurements. Overall, there is a need for an open, cross-discipline database on leaf-level photosynthesis in general, and response curves in particular. The parameters in photosynthetic models are not constant through time, space, or canopy position but there is a need for a better understanding of whether relationships with drivers, such as leaf nitrogen, are themselves scale dependent. Across time scales, as ecosystem models become more sophisticated in their representations of succession they needs to be able to approximate sunfleck responses to capture understory growth and survival. At both high and low latitudes, photosynthetic data are inadequate in general and there is a particular need to better understand thermal acclimation. Simple models of acclimation suggest that shifts in optimal temperature are important. However, there is little advantage to synoptic-scale responses and circadian rhythms may be more beneficial than acclimation over shorter timescales. At high latitudes, there is a need for a better understanding of low-temperature photosynthetic limits, while at low latitudes the need is for a better understanding of phosphorus limitations on photosynthesis. In terms of sampling, measuring multivariate photosynthetic response surfaces are potentially more efficient and more accurate than traditional univariate response curves. Finally, there is a need for greater community involvement in model validation and model-data synthesis.

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.

Delay time correction of the gas analyzer in the calculation of anatomical dead space of the lung.

PubMed

Okubo, T; Shibata, H; Takishima, T

1983-07-01

By means of a mathematical model, we have studied a way to correct the delay time of the gas analyzer in order to calculate the anatomical dead space using Fowler's graphical method. The mathematical model was constructed of ten tubes of equal diameter but unequal length, so that the amount of dead space varied from tube to tube; the tubes were emptied sequentially. The gas analyzer responds with a time lag from the input of the gas signal to the beginning of the response, followed by an exponential response output. The single breath expired volume-concentration relationship was examined with three types of expired flow patterns of which were constant, exponential and sinusoidal. The results indicate that the time correction by the lag time plus time constant of the exponential response of the gas analyzer gives an accurate estimation of anatomical dead space. Time correction less inclusive than this, e.g. lag time only or lag time plus 50% response time, gives an overestimation, and a correction larger than this results in underestimation. The magnitude of error is dependent on the flow pattern and flow rate. The time correction in this study is only for the calculation of dead space, as the corrected volume-concentration curves does not coincide with the true curve. Such correction of the output of the gas analyzer is extremely important when one needs to compare the dead spaces of different gas species at a rather faster flow rate.

Developing an Accurate CFD Based Gust Model for the Truss Braced Wing Aircraft

NASA Technical Reports Server (NTRS)

Bartels, Robert E.

2013-01-01

The increased flexibility of long endurance aircraft having high aspect ratio wings necessitates attention to gust response and perhaps the incorporation of gust load alleviation. The design of civil transport aircraft with a strut or truss-braced high aspect ratio wing furthermore requires gust response analysis in the transonic cruise range. This requirement motivates the use of high fidelity nonlinear computational fluid dynamics (CFD) for gust response analysis. This paper presents the development of a CFD based gust model for the truss braced wing aircraft. A sharp-edged gust provides the gust system identification. The result of the system identification is several thousand time steps of instantaneous pressure coefficients over the entire vehicle. This data is filtered and downsampled to provide the snapshot data set from which a reduced order model is developed. A stochastic singular value decomposition algorithm is used to obtain a proper orthogonal decomposition (POD). The POD model is combined with a convolution integral to predict the time varying pressure coefficient distribution due to a novel gust profile. Finally the unsteady surface pressure response of the truss braced wing vehicle to a one-minus-cosine gust, simulated using the reduced order model, is compared with the full CFD.

Generalized Processing Tree Models: Jointly Modeling Discrete and Continuous Variables.

PubMed

Heck, Daniel W; Erdfelder, Edgar; Kieslich, Pascal J

2018-05-24

Multinomial processing tree models assume that discrete cognitive states determine observed response frequencies. Generalized processing tree (GPT) models extend this conceptual framework to continuous variables such as response times, process-tracing measures, or neurophysiological variables. GPT models assume finite-mixture distributions, with weights determined by a processing tree structure, and continuous components modeled by parameterized distributions such as Gaussians with separate or shared parameters across states. We discuss identifiability, parameter estimation, model testing, a modeling syntax, and the improved precision of GPT estimates. Finally, a GPT version of the feature comparison model of semantic categorization is applied to computer-mouse trajectories.

Mixed-effects Gaussian process functional regression models with application to dose-response curve prediction.

PubMed

Shi, J Q; Wang, B; Will, E J; West, R M

2012-11-20

We propose a new semiparametric model for functional regression analysis, combining a parametric mixed-effects model with a nonparametric Gaussian process regression model, namely a mixed-effects Gaussian process functional regression model. The parametric component can provide explanatory information between the response and the covariates, whereas the nonparametric component can add nonlinearity. We can model the mean and covariance structures simultaneously, combining the information borrowed from other subjects with the information collected from each individual subject. We apply the model to dose-response curves that describe changes in the responses of subjects for differing levels of the dose of a drug or agent and have a wide application in many areas. We illustrate the method for the management of renal anaemia. An individual dose-response curve is improved when more information is included by this mechanism from the subject/patient over time, enabling a patient-specific treatment regime. Copyright © 2012 John Wiley & Sons, Ltd.

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

Dynamic Price Vector Formation Model-Based Automatic Demand Response Strategy for PV-Assisted EV Charging Stations

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

Chen, Qifang; Wang, Fei; Hodge, Bri-Mathias

A real-time price (RTP)-based automatic demand response (ADR) strategy for PV-assisted electric vehicle (EV) Charging Station (PVCS) without vehicle to grid is proposed. The charging process is modeled as a dynamic linear program instead of the normal day-ahead and real-time regulation strategy, to capture the advantages of both global and real-time optimization. Different from conventional price forecasting algorithms, a dynamic price vector formation model is proposed based on a clustering algorithm to form an RTP vector for a particular day. A dynamic feasible energy demand region (DFEDR) model considering grid voltage profiles is designed to calculate the lower and uppermore » bounds. A deduction method is proposed to deal with the unknown information of future intervals, such as the actual stochastic arrival and departure times of EVs, which make the DFEDR model suitable for global optimization. Finally, both the comparative cases articulate the advantages of the developed methods and the validity in reducing electricity costs, mitigating peak charging demand, and improving PV self-consumption of the proposed strategy are verified through simulation scenarios.« less

A shock absorber model for structure-borne noise analyses

NASA Astrophysics Data System (ADS)

Benaziz, Marouane; Nacivet, Samuel; Thouverez, Fabrice

2015-08-01

Shock absorbers are often responsible for undesirable structure-borne noise in cars. The early numerical prediction of this noise in the automobile development process can save time and money and yet remains a challenge for industry. In this paper, a new approach to predicting shock absorber structure-borne noise is proposed; it consists in modelling the shock absorber and including the main nonlinear phenomena responsible for discontinuities in the response. The model set forth herein features: compressible fluid behaviour, nonlinear flow rate-pressure relations, valve mechanical equations and rubber mounts. The piston, base valve and complete shock absorber model are compared with experimental results. Sensitivity of the shock absorber response is evaluated and the most important parameters are classified. The response envelope is also computed. This shock absorber model is able to accurately reproduce local nonlinear phenomena and improves our state of knowledge on potential noise sources within the shock absorber.

Low and High Frequency Models of Response Statistics of a Cylindrical Orthogrid Vehicle Panel to Acoustic Excitation

NASA Technical Reports Server (NTRS)

Smith, Andrew; LaVerde, Bruce; Teague, David; Gardner, Bryce; Cotoni, Vincent

2010-01-01

This presentation further develops the orthogrid vehicle panel work. Employed Hybrid Module capabilities to assess both low/mid frequency and high frequency models in the VA One simulation environment. The response estimates from three modeling approaches are compared to ground test measurements. Detailed Finite Element Model of the Test Article -Expect to capture both the global panel modes and the local pocket mode response, but at a considerable analysis expense (time & resources). A Composite Layered Construction equivalent global stiffness approximation using SEA -Expect to capture response of the global panel modes only. An SEA approximation using the Periodic Subsystem Formulation. A finite element model of a single periodic cell is used to derive the vibroacoustic properties of the entire periodic structure (modal density, radiation efficiency, etc. Expect to capture response at various locations on the panel (on the skin and on the ribs) with less analysis expense

Stimulus probability effects in absolute identification.

PubMed

Kent, Christopher; Lamberts, Koen

2016-05-01

This study investigated the effect of stimulus presentation probability on accuracy and response times in an absolute identification task. Three schedules of presentation were used to investigate the interaction between presentation probability and stimulus position within the set. Data from individual participants indicated strong effects of presentation probability on both proportion correct and response times. The effects were moderated by the ubiquitous stimulus position effect. The accuracy and response time data were predicted by an exemplar-based model of perceptual cognition (Kent & Lamberts, 2005). The bow in discriminability was also attenuated when presentation probability for middle items was relatively high, an effect that will constrain future model development. The study provides evidence for item-specific learning in absolute identification. Implications for other theories of absolute identification are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

[Optimal extraction of effective constituents from Aralia elata by central composite design and response surface methodology].

PubMed

Lv, Shao-Wa; Liu, Dong; Hu, Pan-Pan; Ye, Xu-Yan; Xiao, Hong-Bin; Kuang, Hai-Xue

2010-03-01

To optimize the process of extracting effective constituents from Aralia elata by response surface methodology. The independent variables were ethanol concentration, reflux time and solvent fold, the dependent variable was extraction rate of total saponins in Aralia elata. Linear or no-linear mathematic models were used to estimate the relationship between independent and dependent variables. Response surface methodology was used to optimize the process of extraction. The prediction was carried out through comparing the observed and predicted values. Regression coefficient of binomial fitting complex model was as high as 0.9617, the optimum conditions of extraction process were 70% ethanol, 2.5 hours for reflux, 20-fold solvent and 3 times for extraction. The bias between observed and predicted values was -2.41%. It shows the optimum model is highly predictive.

Effects of dwell time of excitation waveform on meniscus movements for a tubular piezoelectric print-head: experiments and model

NASA Astrophysics Data System (ADS)

Chang, Jiaqing; Liu, Yaxin; Huang, Bo

2017-07-01

In inkjet applications, it is normal to search for an optimal drive waveform when dispensing a fresh fluid or adjusting a newly fabricated print-head. To test trial waveforms with different dwell times, a camera and a strobe light were used to image the protruding or retracting liquid tongues without ejecting any droplets. An edge detection method was used to calculate the lengths of the liquid tongues to draw the meniscus movement curves. The meniscus movement is determined by the time-domain response of the acoustic pressure at the nozzle of the print-head. Starting at the inverse piezoelectric effect, a mathematical model which considers the liquid viscosity in acoustic propagation is constructed to study the acoustic pressure response at the nozzle of the print-head. The liquid viscosity retards the propagation speed and dampens the harmonic amplitude. The pressure response, which is the combined effect of the acoustic pressures generated during the rising time and the falling time and after their propagations and reflections, explains the meniscus movements well. Finally, the optimal dwell time for droplet ejections is discussed.

Prediction and control of neural responses to pulsatile electrical stimulation

NASA Astrophysics Data System (ADS)

Campbell, Luke J.; Sly, David James; O'Leary, Stephen John

2012-04-01

This paper aims to predict and control the probability of firing of a neuron in response to pulsatile electrical stimulation of the type delivered by neural prostheses such as the cochlear implant, bionic eye or in deep brain stimulation. Using the cochlear implant as a model, we developed an efficient computational model that predicts the responses of auditory nerve fibers to electrical stimulation and evaluated the model's accuracy by comparing the model output with pooled responses from a group of guinea pig auditory nerve fibers. It was found that the model accurately predicted the changes in neural firing probability over time to constant and variable amplitude electrical pulse trains, including speech-derived signals, delivered at rates up to 889 pulses s-1. A simplified version of the model that did not incorporate adaptation was used to adaptively predict, within its limitations, the pulsatile electrical stimulus required to cause a desired response from neurons up to 250 pulses s-1. Future stimulation strategies for cochlear implants and other neural prostheses may be enhanced using similar models that account for the way that neural responses are altered by previous stimulation.

Implementation of polarization processes in a charge transport model applied on poly(ethylene naphthalate) films

NASA Astrophysics Data System (ADS)

Hoang, M.-Q.; Le Roy, S.; Boudou, L.; Teyssedre, G.

2016-06-01

One of the difficulties in unravelling transport processes in electrically insulating materials is the fact that the response, notably charging current transients, can have mixed contributions from orientation polarization and from space charge processes. This work aims at identifying and characterizing the polarization processes in a polar polymer in the time and frequency-domains and to implement the contribution of the polarization into a charge transport model. To do so, Alternate Polarization Current (APC) and Dielectric Spectroscopy measurements have been performed on poly(ethylene naphthalene 2,6-dicarboxylate) (PEN), an aromatic polar polymer, providing information on polarization mechanisms in the time- and frequency-domain, respectively. In the frequency-domain, PEN exhibits 3 relaxation processes termed β, β* (sub-glass transitions), and α relaxations (glass transition) in increasing order of temperature. Conduction was also detected at high temperatures. Dielectric responses were treated using a simplified version of the Havriliak-Negami model (Cole-Cole (CC) model), using 3 parameters per relaxation process, these parameters being temperature dependent. The time dependent polarization obtained from the CC model is then added to a charge transport model. Simulated currents issued from the transport model implemented with the polarization are compared with the measured APCs, showing a good consistency between experiments and simulations in a situation where the response comes essentially from dipolar processes.

New Insights to Compare and Choose TKTD Models for Survival Based on an Interlaboratory Study for Lymnaea stagnalis Exposed to Cd.

PubMed

Baudrot, Virgile; Preux, Sara; Ducrot, Virginie; Pave, Alain; Charles, Sandrine

2018-02-06

Toxicokinetic-toxicodynamic (TKTD) models, as the General Unified Threshold model of Survival (GUTS), provide a consistent process-based framework compared to classical dose-response models to analyze both time and concentration-dependent data sets. However, the extent to which GUTS models (Stochastic Death (SD) and Individual Tolerance (IT)) lead to a better fitting than classical dose-response model at a given target time (TT) has poorly been investigated. Our paper highlights that GUTS estimates are generally more conservative and have a reduced uncertainty through smaller credible intervals for the studied data sets than classical TT approaches. Also, GUTS models enable estimating any x% lethal concentration at any time (LC x,t ), and provide biological information on the internal processes occurring during the experiments. While both GUTS-SD and GUTS-IT models outcompete classical TT approaches, choosing one preferentially to the other is still challenging. Indeed, the estimates of survival rate over time and LC x,t are very close between both models, but our study also points out that the joint posterior distributions of SD model parameters are sometimes bimodal, while two parameters of the IT model seems strongly correlated. Therefore, the selection between these two models has to be supported by the experimental design and the biological objectives, and this paper provides some insights to drive this choice.

An Empirical Correction Method for Improving off-Axes Response Prediction in Component Type Flight Mechanics Helicopter Models

NASA Technical Reports Server (NTRS)

Mansur, M. Hossein; Tischler, Mark B.

1997-01-01

Historically, component-type flight mechanics simulation models of helicopters have been unable to satisfactorily predict the roll response to pitch stick input and the pitch response to roll stick input off-axes responses. In the study presented here, simple first-order low-pass filtering of the elemental lift and drag forces was considered as a means of improving the correlation. The method was applied to a blade-element model of the AH-64 APache, and responses of the modified model were compared with flight data in hover and forward flight. Results indicate that significant improvement in the off-axes responses can be achieved in hover. In forward flight, however, the best correlation in the longitudinal and lateral off-axes responses required different values of the filter time constant for each axis. A compromise value was selected and was shown to result in good overall improvement in the off-axes responses. The paper describes both the method and the model used for its implementation, and presents results obtained at hover and in forward flight.

Using Remote Sensing Mapping and Growth Response to Environmental Variability to Aide Aquatic Invasive Plant Management

NASA Technical Reports Server (NTRS)

Bubenheim, David L.; Schlick, Greg; Genovese, Vanessa; Wilson, Kenneth D.

2018-01-01

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for floating and submerged aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used map (area coverage and biomass density), direct operations, and assess management impacts on plant communities. Archived satellite records enable review of results following previous climate and management events and aide in developing long-term strategies. Examples of remote sensing aiding effectiveness of aquatic weed management will be discussed as well as areas for potential technological improvement. Modeling at local and watershed scales using the SWAT modeling tool provides insight into land-use effects on water quality (described by Zhang in same Symposium). Controlled environment growth studies have been conducted to quantify the growth response of invasive aquatic plants to water quality and other environmental factors. Environmental variability occurs across a range of time scales from long-term climate and seasonal trends to short-term water flow mediated variations. Response time for invasive species response are examined at time scales of weeks, day, and hours using a combination of study duration and growth assessment techniques to assess water quality, temperature (air and water), nitrogen, phosphorus, and light effects. These provide response parameters for plant growth models in response to the variation and interact with management and economic models associated with aquatic weed management. Plant growth models are to be informed by remote sensing and applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments and phenology. Initial utilization of remote sensing tools developed for mapping of aquatic invasive plants improved operational efficiency in management practices. These assessment methods provide a comprehensive and quantitative view of aquatic invasive plants communities in the California Delta.

Salmonella Fecal Shedding and Immune Responses are Dose- and Serotype- Dependent in Pigs

PubMed Central

Ivanek, Renata; Österberg, Julia; Gautam, Raju; Sternberg Lewerin, Susanna

2012-01-01

Despite the public health importance of Salmonella infection in pigs, little is known about the associated dynamics of fecal shedding and immunity. In this study, we investigated the transitions of pigs through the states of Salmonella fecal shedding and immune response post-Salmonella inoculation as affected by the challenge dose and serotype. Continuous-time multistate Markov models were developed using published experimental data. The model for shedding had four transient states, of which two were shedding (continuous and intermittent shedding) and two non-shedding (latency and intermittent non-shedding), and one absorbing state representing permanent cessation of shedding. The immune response model had two transient states representing responses below and above the seroconversion level. The effects of two doses [low (0.65×106 CFU/pig) and high (0.65×109 CFU/pig)] and four serotypes (Salmonella Yoruba, Salmonella Cubana, Salmonella Typhimurium, and Salmonella Derby) on the models' transition intensities were evaluated using a proportional intensities model. Results indicated statistically significant effects of the challenge dose and serotype on the dynamics of shedding and immune response. The time spent in the specific states was also estimated. Continuous shedding was on average 10–26 days longer, while intermittent non-shedding was 2–4 days shorter, in pigs challenged with the high compared to low dose. Interestingly, among pigs challenged with the high dose, the continuous and intermittent shedding states were on average up to 10–17 and 3–4 days longer, respectively, in pigs infected with S. Cubana compared to the other three serotypes. Pigs challenged with the high dose of S. Typhimurium or S. Derby seroconverted on average up to 8–11 days faster compared to the low dose. These findings highlight that Salmonella fecal shedding and immune response following Salmonella challenge are dose- and serotype-dependent and that the detection of specific Salmonella strains and immune responses in pigs are time-sensitive. PMID:22523553

Assessment of hemoglobin responsiveness to epoetin alfa in patients on hemodialysis using a population pharmacokinetic pharmacodynamic model.

PubMed

Wu, Liviawati; Mould, Diane R; Perez Ruixo, Juan Jose; Doshi, Sameer

2015-10-01

A population pharmacokinetic pharmacodynamic (PK/PD) model describing the effect of epoetin alfa on hemoglobin (Hb) response in hemodialysis patients was developed. Epoetin alfa pharmacokinetics was described using a linear 2-compartment model. PK parameter estimates were similar to previously reported values. A maturation-structured cytokinetic model consisting of 5 compartments linked in a catenary fashion by first-order cell transfer rates following a zero-order input process described the Hb time course. The PD model described 2 subpopulations, one whose Hb response reflected epoetin alfa dosing and a second whose response was unrelated to epoetin alfa dosing. Parameter estimates from the PK/PD model were physiologically reasonable and consistent with published reports. Numerical and visual predictive checks using data from 2 studies were performed. The PK and PD of epoetin alfa were well described by the model. © 2015, The American College of Clinical Pharmacology.

Assessment of Anthropometric Trends and the Effects on Thermal Regulatory Models: Females Versus Males

DTIC Science & Technology

2007-08-01

primary somatotypes , which were identified by multivariate analysis, had no significant effect on the simulated thermo-physiological responses ...population. Anthropometric values for each somatotype applied to a thermal regulatory model resulted into physiological response comparisons of Figure 2 and...Public report ing burden for this collect ion of information is est imated to average 1 hour per response , including the time for review ing instruct ions

Immune Response to Electromagnetic Fields through Cybernetic Modeling

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

Godina-Nava, J. J.; Segura, M. A. Rodriguez; Cadena, S. Reyes

We study the optimality of the humoral immune response through a mathematical model, which involves the effect of electromagnetic fields over the large lymphocytes proliferation. Are used the so called cybernetic variables in the context of the matching law of microeconomics or mathematical psychology, to measure the large lymphocytes population and to maximize the instantaneous antibody production rate in time during the immunologic response in order to most efficiently inactivate the antigen.

Immune Response to Electromagnetic Fields through Cybernetic Modeling

NASA Astrophysics Data System (ADS)

Godina-Nava, J. J.; Segura, M. A. Rodríguez; Cadena, S. Reyes; Sierra, L. C. Gaitán

2008-08-01

We study the optimality of the humoral immune response through a mathematical model, which involves the effect of electromagnetic fields over the large lymphocytes proliferation. Are used the so called cybernetic variables in the context of the matching law of microeconomics or mathematical psychology, to measure the large lymphocytes population and to maximize the instantaneous antibody production rate in time during the immunologic response in order to most efficiently inactivate the antigen.

Uncertainty Analysis of Decomposing Polyurethane Foam

NASA Technical Reports Server (NTRS)

Hobbs, Michael L.; Romero, Vicente J.

2000-01-01

Sensitivity/uncertainty analyses are necessary to determine where to allocate resources for improved predictions in support of our nation's nuclear safety mission. Yet, sensitivity/uncertainty analyses are not commonly performed on complex combustion models because the calculations are time consuming, CPU intensive, nontrivial exercises that can lead to deceptive results. To illustrate these ideas, a variety of sensitivity/uncertainty analyses were used to determine the uncertainty associated with thermal decomposition of polyurethane foam exposed to high radiative flux boundary conditions. The polyurethane used in this study is a rigid closed-cell foam used as an encapsulant. Related polyurethane binders such as Estane are used in many energetic materials of interest to the JANNAF community. The complex, finite element foam decomposition model used in this study has 25 input parameters that include chemistry, polymer structure, and thermophysical properties. The response variable was selected as the steady-state decomposition front velocity calculated as the derivative of the decomposition front location versus time. An analytical mean value sensitivity/uncertainty (MV) analysis was used to determine the standard deviation by taking numerical derivatives of the response variable with respect to each of the 25 input parameters. Since the response variable is also a derivative, the standard deviation was essentially determined from a second derivative that was extremely sensitive to numerical noise. To minimize the numerical noise, 50-micrometer element dimensions and approximately 1-msec time steps were required to obtain stable uncertainty results. As an alternative method to determine the uncertainty and sensitivity in the decomposition front velocity, surrogate response surfaces were generated for use with a constrained Latin Hypercube Sampling (LHS) technique. Two surrogate response surfaces were investigated: 1) a linear surrogate response surface (LIN) and 2) a quadratic response surface (QUAD). The LHS techniques do not require derivatives of the response variable and are subsequently relatively insensitive to numerical noise. To compare the LIN and QUAD methods to the MV method, a direct LHS analysis (DLHS) was performed using the full grid and timestep resolved finite element model. The surrogate response models (LIN and QUAD) are shown to give acceptable values of the mean and standard deviation when compared to the fully converged DLHS model.

A MODEL OF ESTUARY RESPONSE TO NITROGEN LOADING AND FRESHWATER RESIDENCE TIME

EPA Science Inventory

We have developed a deterministic model that relates average annual nitrogen loading rate and water residence time in an estuary to in-estuary nitrogen concentrations and loss rates (e.g. denitrification and incorporation in sediments), and to rates of nitrogen export across the ...

Modeling exposure–lag–response associations with distributed lag non-linear models

PubMed Central

Gasparrini, Antonio

2014-01-01

In biomedical research, a health effect is frequently associated with protracted exposures of varying intensity sustained in the past. The main complexity of modeling and interpreting such phenomena lies in the additional temporal dimension needed to express the association, as the risk depends on both intensity and timing of past exposures. This type of dependency is defined here as exposure–lag–response association. In this contribution, I illustrate a general statistical framework for such associations, established through the extension of distributed lag non-linear models, originally developed in time series analysis. This modeling class is based on the definition of a cross-basis, obtained by the combination of two functions to flexibly model linear or nonlinear exposure-responses and the lag structure of the relationship, respectively. The methodology is illustrated with an example application to cohort data and validated through a simulation study. This modeling framework generalizes to various study designs and regression models, and can be applied to study the health effects of protracted exposures to environmental factors, drugs or carcinogenic agents, among others. © 2013 The Authors. Statistics in Medicine published by John Wiley & Sons, Ltd. PMID:24027094

'Real-life' study of imatinib therapy in chronic phase-chronic myeloid leukemia: A novel retrospective observational longitudinal analysis.

PubMed

Merante, Serena; Ferretti, Virginia; Elena, Chiara; Calvello, Celeste; Rocca, Barbara; Zappatore, Rita; Cavigliano, Paola; Orlandi, Ester

2017-01-01

Imatinib is a cornerstone of treatment of chronic myeloid leukemia. It remains unclear whether transient treatment discontinuation or dose changes affect outcome and this approach has not yet been approved for use outside clinical trials. We conducted a retrospective single-institution observational study to evaluate factors affecting response in 'real-life' clinical practice in 138 chronic myeloid leukemia patients in chronic phase treated with imatinib. We used a novel longitudinal data analytical model, with a generalized estimating equation model, to study BCR-ABL variation according to continuous standard dose, change in dose or discontinuation; BCR-ABL transcript levels were recorded. Treatment history was subdivided into time periods for which treatment was given at constant dosage (total 483 time periods). Molecular and cytogenetic complete response was observed after 154 (32%) and 358 (74%) time periods, respectively. After adjusting for length of time period, no association between dose and cytogenetic complete response rate was observed. There was a significantly lower molecular complete response rate after time periods at a high imatinib dosage. This statistical approach can identify individual patient variation in longitudinal data collected over time and suggests that changes in dose or discontinuation of therapy could be considered in patients with appropriate biological characteristics.

Real-time pricing strategy of micro-grid energy centre considering price-based demand response

NASA Astrophysics Data System (ADS)

Xu, Zhiheng; Zhang, Yongjun; Wang, Gan

2017-07-01

With the development of energy conversion technology such as power to gas (P2G), fuel cell and so on, the coupling between energy sources becomes more and more closely. Centralized dispatch among electricity, natural gas and heat will become a trend. With the goal of maximizing the system revenue, this paper establishes the model of micro-grid energy centre based on energy hub. According to the proposed model, the real-time pricing strategy taking into account price-based demand response of load is developed. And the influence of real-time pricing strategy on the peak load shifting is discussed. In addition, the impact of wind power predicted inaccuracy on real-time pricing strategy is analysed.

Time-dependent compressibility of poly (methyl methacrylate) (PMMA) : an experimental and molecular dynamics investigation

NASA Astrophysics Data System (ADS)

Sane, Sandeep Bhalchandra

This thesis contains three chapters, which describe different aspects of an investigation of the bulk response of Poly(Methyl Methacrylate) (PMMA). The first chapter describes the physical measurements by means of a Belcher/McKinney-type apparatus. Used earlier for the measurement of the bulk response of Poly(Vinyl Acetate), it was now adapted for making measurements at higher temperatures commensurate with the glass transition temperature of PMMA. The dynamic bulk compliance of PMMA was measured at atmospheric pressure over a wide range of temperatures and frequencies, from which the master curves for the bulk compliance were generated by means of the time-temperature superposition principle. It was found that the extent of the transition ranges for the bulk and shear response were comparable. Comparison of the shift factors for bulk and shear responses supports the idea that different molecular mechanisms contribute to shear and bulk deformations. The second chapter delineates molecular dynamics computations for the bulk response for a range of pressures and temperatures. The model(s) consisted of 2256 atoms formed into three polymer chains with fifty monomer units per chain per unit cell. The time scales accessed were limited to tens of pico seconds. It was found that, in addition to the typical energy minimization and temperature annealing cycles for establishing equilibrium models, it is advantageous to subject the model samples to a cycle of relatively large pressures (GPa-range) for improving the equilibrium state. On comparing the computations with the experimentally determined "glassy" behavior, one finds that, although the computations were limited to small samples in a physical sense, the primary limitation rests in the very short times (pico seconds). The molecular dynamics computations do not model the physically observed temperature sensitivity of PMMA, even if one employs a hypothetical time-temperature shift to account for the large difference in time scales between experiment and computation. The values computed by the molecular dynamics method do agree with the values measured at the coldest temperature and at the highest frequency of one kiloHertz. The third chapter draws on measurements of uniaxial, shear and Poisson response conducted previously in our laboratory. With the availability of four time or frequency-dependent material functions for the same material, the process of interconversion between different material functions was investigated. Computed material functions were evaluated against the direct experimental measurements and the limitations imposed on successful interconversion due to the experimental errors in the underlying physical data were explored. Differences were observed that are larger than the experimental errors would suggest.

Testing the Utility of a Bio-Neuropsychosocial Model for Predicting Medical Adherence and Responsibility During Early Adolescence in Youth With Spina Bifida.

PubMed

Psihogios, Alexandra M; Murray, Caitlin; Zebracki, Kathy; Acevedo, Laura; Holmbeck, Grayson N

2017-10-01

The present longitudinal, multi-method, and multi-informant study examined biological, neuropsychological, and social predictors of medical adherence and responsibility among early adolescents with spina bifida (SB). Youth with SB (M age = 11.40 at Time 1) and their parents and teachers completed surveys, and families and peers completed observational assessments, at two biennial data collection time points (n = 112 for both time points). Multinomial logistic regressions tested predictors of group membership (adherent vs. nonadherent and child responsible vs. not responsible with SB medical tasks). Consistent with the bio-neuropsychosocial model, several risk factors emerged for SB management. Impaired gross motor classification and low IQ were barriers to obtaining medical responsibility, and high family stress and executive dysfunction were barriers to adherence and responsibility. This study offered intervention targets to promote self-management and adherence for youth with SB and their families, including parent stress-management and family problem-solving. © The Author 2016. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process

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

Song, Hyun-Seob; Thomas, Dennis G.; Stegen, James C.

In a recent study of denitrification dynamics in hyporheic zone sediments, we observed a significant time lag (up to several days) in enzymatic response to the changes in substrate concentration. To explore an underlying mechanism and understand the interactive dynamics between enzymes and nutrients, we developed a trait-based model that associates a community’s traits with functional enzymes, instead of typically used species guilds (or functional guilds). This enzyme-based formulation allows to collectively describe biogeochemical functions of microbial communities without directly parameterizing the dynamics of species guilds, therefore being scalable to complex communities. As a key component of modeling, we accountedmore » for microbial regulation occurring through transcriptional and translational processes, the dynamics of which was parameterized based on the temporal profiles of enzyme concentrations measured using a new signature peptide-based method. The simulation results using the resulting model showed several days of a time lag in enzymatic responses as observed in experiments. Further, the model showed that the delayed enzymatic reactions could be primarily controlled by transcriptional responses and that the dynamics of transcripts and enzymes are closely correlated. The developed model can serve as a useful tool for predicting biogeochemical processes in natural environments, either independently or through integration with hydrologic flow simulators.« less

Conditional responding is impaired in chronic alcoholics.

PubMed

Hildebrandt, Helmut; Brokate, B; Hoffmann, E; Kröger, B; Eling, P

2006-07-01

Bechara (2003) describes a model for disturbances in executive functions related to addiction. This model involves deficits in decision-making and in suppressing pre-potent representations or response patterns. We tested this model in 29 individuals with long-term heavy alcohol dependency and compared their performance with that of 20 control subjects. Only individuals without memory impairment, with normal intelligence and normal visual response times were included. We examined word fluency, object alternation, spatial stimulus-response incompatibility, extra-dimensional shift learning and decision-making using the Gambling task. We subtracted the performance in a control condition from that of the executive condition, in order to focus specifically on the executive component of each task. Only the object alternation and incompatibility tasks revealed significant differences between the group of alcoholics and the control group. Moreover, response times in the object alternation task correlated with duration of alcohol dependency. The results do not argue in favor of a specific deficit in decision-making or in shifting between relevant representations. We conclude that long-term alcohol abuse leads to an impairment in conditional responding, provided the response depends on former reactions or the inhibition of pre-potent response patterns.

Multi scale modeling of 2450MHz electric field effects on microtubule mechanical properties.

PubMed

Setayandeh, S S; Lohrasebi, A

2016-11-01

Microtubule (MT) rigidity and response to 2450MHz electric fields were investigated, via multi scale modeling approach. For this purpose, six systems were designed and simulated to consider all types of feasible interactions between α and β monomers in MT, by using all atom molecular dynamics method. Subsequently, coarse grain modeling was used to design different lengths of MT. Investigation of effects of external 2450MHz electric field on MT showed MT less rigidity in the presence of such field, which may perturb its functions. Moreover, an additional computational setup was designed to study effects of 2450MHz field on MT response to AFM tip. It was found, more tip velocity led to MT faster transformation and less time was required to change MT elastic response to plastic one, applying constant radius. Moreover it was observed smaller tip caused to increase required time to change MT elastic response to plastic one, considering constant velocity. Furthermore, exposing MT to 2450MHz field led to no significant changes in MT response to AFM tip, but quick change in MT elastic response to plastic one. Copyright © 2016 Elsevier Inc. All rights reserved.

How parasitism affects critical patch-size in a host-parasitoid model: application to the forest tent caterpillar.

PubMed

Cobbold, C A; Lewis, M A; Lutscher, F; Roland, J

2005-03-01

Habitat structure has broad impacts on many biological systems. In particular, habitat fragmentation can increase the probability of species extinction and on the other hand it can lead to population outbreaks in response to a decline in natural enemies. An extreme consequence of fragmentation is the isolation of small regions of suitable habitat surrounded by a large region of hostile matrix. This scenario can be interpreted as a critical patch-size problem, well studied in a continuous time framework, but relatively new to discrete time models. In this paper we present an integrodifference host-parasitoid model, discrete in time and continuous in space, to study how the critical habitat-size necessary for parasitoid survival changes in response to parasitoid life history traits, such as emergence time. We show that early emerging parasitoids may be able to persist in smaller habitats than late emerging species. The model predicts that these early emerging parasitoids lead to more severe host outbreaks. We hypothesise that promoting efficient late emerging parasitoids may be key in reducing outbreak severity, an approach requiring large continuous regions of suitable habitat. We parameterise the model for the host species of the forest tent caterpillar Malacosoma disstria Hbn., a pest insect for which fragmented landscape increases the severity of outbreaks. This host is known to have several parasitoids, due to paucity of data and as a first step in the modelling we consider a single generic parasitoid. The model findings are related to observations of the forest tent caterpillar offering insight into this host-parasitoid response to habitat structure.

The BCD of response time analysis in experimental economics.

PubMed

Spiliopoulos, Leonidas; Ortmann, Andreas

2018-01-01

For decisions in the wild, time is of the essence. Available decision time is often cut short through natural or artificial constraints, or is impinged upon by the opportunity cost of time. Experimental economists have only recently begun to conduct experiments with time constraints and to analyze response time (RT) data, in contrast to experimental psychologists. RT analysis has proven valuable for the identification of individual and strategic decision processes including identification of social preferences in the latter case, model comparison/selection, and the investigation of heuristics that combine speed and performance by exploiting environmental regularities. Here we focus on the benefits, challenges, and desiderata of RT analysis in strategic decision making. We argue that unlocking the potential of RT analysis requires the adoption of process-based models instead of outcome-based models, and discuss how RT in the wild can be captured by time-constrained experiments in the lab. We conclude that RT analysis holds considerable potential for experimental economics, deserves greater attention as a methodological tool, and promises important insights on strategic decision making in naturally occurring environments.

Simulating Descent and Landing of a Spacecraft

NASA Technical Reports Server (NTRS)

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

2005-01-01

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

A dynamic dual process model of risky decision making.

PubMed

Diederich, Adele; Trueblood, Jennifer S

2018-03-01

Many phenomena in judgment and decision making are often attributed to the interaction of 2 systems of reasoning. Although these so-called dual process theories can explain many types of behavior, they are rarely formalized as mathematical or computational models. Rather, dual process models are typically verbal theories, which are difficult to conclusively evaluate or test. In the cases in which formal (i.e., mathematical) dual process models have been proposed, they have not been quantitatively fit to experimental data and are often silent when it comes to the timing of the 2 systems. In the current article, we present a dynamic dual process model framework of risky decision making that provides an account of the timing and interaction of the 2 systems and can explain both choice and response-time data. We outline several predictions of the model, including how changes in the timing of the 2 systems as well as time pressure can influence behavior. The framework also allows us to explore different assumptions about how preferences are constructed by the 2 systems as well as the dynamic interaction of the 2 systems. In particular, we examine 3 different possible functional forms of the 2 systems and 2 possible ways the systems can interact (simultaneously or serially). We compare these dual process models with 2 single process models using risky decision making data from Guo, Trueblood, and Diederich (2017). Using this data, we find that 1 of the dual process models significantly outperforms the other models in accounting for both choices and response times. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

A Model for Real-Time Data Reputation Via Cyber Telemetry

DTIC Science & Technology

2016-06-01

TIME DATA REPUTATION VIA CYBER TELEMETRY by Beau M. Houser June 2016 Thesis Advisor: Dorothy E. Denning Co-Advisor: Phyllis Schneck...information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and...Master’s Thesis 4. TITLE AND SUBTITLE A MODEL FOR REAL- TIME DATA REPUTATION VIA CYBER TELEMETRY 5. FUNDING NUMBERS 6. AUTHOR(S) Beau M

A Model-Based Approach to Trial-By-Trial P300 Amplitude Fluctuations

PubMed Central

Kolossa, Antonio; Fingscheidt, Tim; Wessel, Karl; Kopp, Bruno

2013-01-01

It has long been recognized that the amplitude of the P300 component of event-related brain potentials is sensitive to the degree to which eliciting stimuli are surprising to the observers (Donchin, 1981). While Squires et al. (1976) showed and modeled dependencies of P300 amplitudes from observed stimuli on various time scales, Mars et al. (2008) proposed a computational model keeping track of stimulus probabilities on a long-term time scale. We suggest here a computational model which integrates prior information with short-term, long-term, and alternation-based experiential influences on P300 amplitude fluctuations. To evaluate the new model, we measured trial-by-trial P300 amplitude fluctuations in a simple two-choice response time task, and tested the computational models of trial-by-trial P300 amplitudes using Bayesian model evaluation. The results reveal that the new digital filtering (DIF) model provides a superior account of the trial-by-trial P300 amplitudes when compared to both Squires et al.’s (1976) model, and Mars et al.’s (2008) model. We show that the P300-generating system can be described as two parallel first-order infinite impulse response (IIR) low-pass filters and an additional fourth-order finite impulse response (FIR) high-pass filter. Implications of the acquired data are discussed with regard to the neurobiological distinction between short-term, long-term, and working memory as well as from the point of view of predictive coding models and Bayesian learning theories of cortical function. PMID:23404628

Forced and intrinsic variability in the response to increased wind stress of an idealized Southern Ocean

NASA Astrophysics Data System (ADS)

Wilson, Chris; Hughes, Chris W.; Blundell, Jeffrey R.

2015-01-01

use ensemble runs of a three layer, quasi-geostrophic idealized Southern Ocean model to explore the roles of forced and intrinsic variability in response to a linear increase of wind stress imposed over a 30 year period. We find no increase of eastward circumpolar volume transport in response to the increased wind stress. A large part of the resulting time series can be explained by a response in which the eddy kinetic energy is linearly proportional to the wind stress with a possible time lag, but no statistically significant lag is found. However, this simple relationship is not the whole story: several intrinsic time scales also influence the response. We find an e-folding time scale for growth of small perturbations of 1-2 weeks. The energy budget for intrinsic variability at periods shorter than a year is dominated by exchange between kinetic and potential energy. At longer time scales, we find an intrinsic mode with period in the region of 15 years, which is dominated by changes in potential energy and frictional dissipation in a manner consistent with that seen by Hogg and Blundell (2006). A similar mode influences the response to changing wind stress. This influence, robust to perturbations, is different from the supposed linear relationship between wind stress and eddy kinetic energy, and persists for 5-10 years in this model, suggestive of a forced oscillatory mode with period of around 15 years. If present in the real ocean, such a mode would imply a degree of predictability of Southern Ocean dynamics on multiyear time scales.

A connectionist modeling study of the neural mechanisms underlying pain's ability to reorient attention.

PubMed

Dowman, Robert; Ritz, Benjamin; Fowler, Kathleen

2016-08-01

Connectionist modeling was used to investigate the brain mechanisms responsible for pain's ability to shift attention away from another stimulus modality and toward itself. Different connectionist model architectures were used to simulate the different possible brain mechanisms underlying this attentional bias, where nodes in the model simulated the brain areas thought to mediate the attentional bias, and the connections between the nodes simulated the interactions between the brain areas. Mathematical optimization techniques were used to find the model parameters, such as connection strengths, that produced the best quantitative fits of reaction time and event-related potential data obtained in our previous work. Of the several architectures tested, two produced excellent quantitative fits of the experimental data. One involved an unexpected pain stimulus activating somatic threat detectors in the dorsal posterior insula. This threat detector activity was monitored by the medial prefrontal cortex, which in turn evoked a phasic response in the locus coeruleus. The locus coeruleus phasic response resulted in a facilitation of the cortical areas involved in decision and response processes time-locked to the painful stimulus. The second architecture involved the presence of pain causing an increase in general arousal. The increase in arousal was mediated by locus coeruleus tonic activity, which facilitated responses in the cortical areas mediating the sensory, decision, and response processes involved in the task. These two neural network architectures generated competing predictions that can be tested in future studies.

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

NASA Astrophysics Data System (ADS)

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

2018-07-01

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

A Two-Stage Process Model of Sensory Discrimination: An Alternative to Drift-Diffusion

PubMed Central

Landy, Michael S.

2016-01-01

Discrimination of the direction of motion of a noisy stimulus is an example of sensory discrimination under uncertainty. For stimuli that are extended in time, reaction time is quicker for larger signal values (e.g., discrimination of opposite directions of motion compared with neighboring orientations) and larger signal strength (e.g., stimuli with higher contrast or motion coherence, that is, lower noise). The standard model of neural responses (e.g., in lateral intraparietal cortex) and reaction time for discrimination is drift-diffusion. This model makes two clear predictions. (1) The effects of signal strength and value on reaction time should interact multiplicatively because the diffusion process depends on the signal-to-noise ratio. (2) If the diffusion process is interrupted, as in a cued-response task, the time to decision after the cue should be independent of the strength of accumulated sensory evidence. In two experiments with human participants, we show that neither prediction holds. A simple alternative model is developed that is consistent with the results. In this estimate-then-decide model, evidence is accumulated until estimation precision reaches a threshold value. Then, a decision is made with duration that depends on the signal-to-noise ratio achieved by the first stage. SIGNIFICANCE STATEMENT Sensory decision-making under uncertainty is usually modeled as the slow accumulation of noisy sensory evidence until a threshold amount of evidence supporting one of the possible decision outcomes is reached. Furthermore, it has been suggested that this accumulation process is reflected in neural responses, e.g., in lateral intraparietal cortex. We derive two behavioral predictions of this model and show that neither prediction holds. We introduce a simple alternative model in which evidence is accumulated until a sufficiently precise estimate of the stimulus is achieved, and then that estimate is used to guide the discrimination decision. This model is consistent with the behavioral data. PMID:27807167

A Two-Stage Process Model of Sensory Discrimination: An Alternative to Drift-Diffusion.

PubMed

Sun, Peng; Landy, Michael S

2016-11-02

Discrimination of the direction of motion of a noisy stimulus is an example of sensory discrimination under uncertainty. For stimuli that are extended in time, reaction time is quicker for larger signal values (e.g., discrimination of opposite directions of motion compared with neighboring orientations) and larger signal strength (e.g., stimuli with higher contrast or motion coherence, that is, lower noise). The standard model of neural responses (e.g., in lateral intraparietal cortex) and reaction time for discrimination is drift-diffusion. This model makes two clear predictions. (1) The effects of signal strength and value on reaction time should interact multiplicatively because the diffusion process depends on the signal-to-noise ratio. (2) If the diffusion process is interrupted, as in a cued-response task, the time to decision after the cue should be independent of the strength of accumulated sensory evidence. In two experiments with human participants, we show that neither prediction holds. A simple alternative model is developed that is consistent with the results. In this estimate-then-decide model, evidence is accumulated until estimation precision reaches a threshold value. Then, a decision is made with duration that depends on the signal-to-noise ratio achieved by the first stage. Sensory decision-making under uncertainty is usually modeled as the slow accumulation of noisy sensory evidence until a threshold amount of evidence supporting one of the possible decision outcomes is reached. Furthermore, it has been suggested that this accumulation process is reflected in neural responses, e.g., in lateral intraparietal cortex. We derive two behavioral predictions of this model and show that neither prediction holds. We introduce a simple alternative model in which evidence is accumulated until a sufficiently precise estimate of the stimulus is achieved, and then that estimate is used to guide the discrimination decision. This model is consistent with the behavioral data. Copyright © 2016 the authors 0270-6474/16/3611259-16$15.00/0.

Dealing with the health state 'dead' when using discrete choice experiments to obtain values for EQ-5D-5L heath states.

PubMed

Ramos-Goñi, Juan Manuel; Rivero-Arias, Oliver; Errea, María; Stolk, Elly A; Herdman, Michael; Cabasés, Juan Manuel

2013-07-01

To evaluate two different methods to obtain a dead (0)--full health (1) scale for EQ-5D-5L valuation studies when using discrete choice (DC) modeling. The study was carried out among 400 respondents from Barcelona who were representative of the Spanish population in terms of age, sex, and level of education. The DC design included 50 pairs of health states in five blocks. Participants were forced to choose between two EQ-5D-5L states (A and B). Two extra questions concerned whether A and B were considered worse than dead. Each participant performed ten choice exercises. In addition, values were collected using lead-time trade-off (lead-time TTO), for which 100 states in ten blocks were selected. Each participant performed five lead-time TTO exercises. These consisted of DC models offering the health state 'dead' as one of the choices--for which all participants' responses were used (DCdead)--and a model that included only the responses of participants who chose at least one state as worse than dead (WTD) (DCWTD). The study also estimated DC models rescaled with lead-time TTO data and a lead-time TTO linear model. The DC(dead) and DCWTD models produced relatively similar results, although the coefficients in the DCdead model were slightly lower. The DC model rescaled with lead-time TTO data produced higher utility decrements. Lead-time TTO produced the highest utility decrements. The incorporation of the state 'dead' in the DC models produces results in concordance with DC models that do not include 'dead'.

Context Effects in Multi-Alternative Decision Making: Empirical Data and a Bayesian Model

ERIC Educational Resources Information Center

Hawkins, Guy; Brown, Scott D.; Steyvers, Mark; Wagenmakers, Eric-Jan

2012-01-01

For decisions between many alternatives, the benchmark result is Hick's Law: that response time increases log-linearly with the number of choice alternatives. Even when Hick's Law is observed for response times, divergent results have been observed for error rates--sometimes error rates increase with the number of choice alternatives, and…

Modeling Fan Effects on the Time Course of Associative Recognition

ERIC Educational Resources Information Center

Schneider, Darryl W.; Anderson, John R.

2012-01-01

We investigated the time course of associative recognition using the response signal procedure, whereby a stimulus is presented and followed after a variable lag by a signal indicating that an immediate response is required. More specifically, we examined the effects of associative fan (the number of associations that an item has with other items…

Serial and Parallel Attentive Visual Searches: Evidence from Cumulative Distribution Functions of Response Times

ERIC Educational Resources Information Center

Sung, Kyongje

2008-01-01

Participants searched a visual display for a target among distractors. Each of 3 experiments tested a condition proposed to require attention and for which certain models propose a serial search. Serial versus parallel processing was tested by examining effects on response time means and cumulative distribution functions. In 2 conditions, the…

Analytic Support of Emergency Response and Recovery for the Wide-Area Recovery & Resiliency Program (WARRP) Task 1: Medical Countermeasures Response

DTIC Science & Technology

2012-02-23

time Detect and Characterize Event Multiple Materiel No integration between national biosurveillance systems Could receive disparate signals and the...is very limited in its applicability at this time only being deployable in one city and in the process of being implemented in four more Push models

Space-time modeling of timber prices

Treesearch

Mo Zhou; Joseph Buongriorno

2006-01-01

A space-time econometric model was developed for pine sawtimber timber prices of 21 geographically contiguous regions in the southern United States. The correlations between prices in neighboring regions helped predict future prices. The impulse response analysis showed that although southern pine sawtimber markets were not globally integrated, local supply and demand...

Modeling Student Test-Taking Motivation in the Context of an Adaptive Achievement Test

ERIC Educational Resources Information Center

Wise, Steven L.; Kingsbury, G. Gage

2016-01-01

This study examined the utility of response time-based analyses in understanding the behavior of unmotivated test takers. For the data from an adaptive achievement test, patterns of observed rapid-guessing behavior and item response accuracy were compared to the behavior expected under several types of models that have been proposed to represent…

Quantitative Nuclease Protection Assays (qNPA) as Windows into Chemical-Induced Adaptive Response in Cultures of Primary Human Hepatocytes (Concentration and Time-Response)

EPA Science Inventory

Cultures of primary human hepatocytes have been shown to be dynamic in vitro model systems that retain liver-like functionality (e.g. metabolism, transport, induction). We have utilized these culture models to interrogate 309 ToxCast chemicals. The study design characterized both...

The Consequences of Ignoring Item Parameter Drift in Longitudinal Item Response Models

ERIC Educational Resources Information Center

Lee, Wooyeol; Cho, Sun-Joo

2017-01-01

Utilizing a longitudinal item response model, this study investigated the effect of item parameter drift (IPD) on item parameters and person scores via a Monte Carlo study. Item parameter recovery was investigated for various IPD patterns in terms of bias and root mean-square error (RMSE), and percentage of time the 95% confidence interval covered…

Linking Outcomes from Peabody Picture Vocabulary Test Forms Using Item Response Models

ERIC Educational Resources Information Center

Hoffman, Lesa; Templin, Jonathan; Rice, Mabel L.

2012-01-01

Purpose: The present work describes how vocabulary ability as assessed by 3 different forms of the Peabody Picture Vocabulary Test (PPVT; Dunn & Dunn, 1997) can be placed on a common latent metric through item response theory (IRT) modeling, by which valid comparisons of ability between samples or over time can then be made. Method: Responses…

Atmospheric and Oceanic Response to Southern Ocean Deep Convection Oscillations on Decadal to Centennial Time Scales in Climate Models

NASA Astrophysics Data System (ADS)

Martin, T.; Reintges, A.; Park, W.; Latif, M.

2014-12-01

Many current coupled global climate models simulate open ocean deep convection in the Southern Ocean as a recurring event with time scales ranging from a few years to centennial (de Lavergne et al., 2014, Nat. Clim. Ch.). The only observation of such event, however, was the occurrence of the Weddell Polynya in the mid-1970s, an open water area of 350 000 km2 within the Antarctic sea ice in three consecutive winters. Both the wide range of modeled frequency of occurrence and the absence of deep convection in the Weddell Sea highlights the lack of understanding concerning the phenomenon. Nevertheless, simulations indicate that atmospheric and oceanic responses to the cessation of deep convection in the Southern Ocean include a strengthening of the low-level atmospheric circulation over the Southern Ocean (increasing SAM index) and a reduction in the export of Antarctic Bottom Water (AABW), potentially masking the regional effects of global warming (Latif et al., 2013, J. Clim.; Martin et al., 2014, Deep Sea Res. II). It is thus of great importance to enhance our understanding of Southern Ocean deep convection and clarify the associated time scales. In two multi-millennial simulations with the Kiel Climate Model (KCM, ECHAM5 T31 atmosphere & NEMO-LIM2 ~2˚ ocean) we showed that the deep convection is driven by strong oceanic warming at mid-depth periodically overriding the stabilizing effects of precipitation and ice melt (Martin et al., 2013, Clim. Dyn.). Sea ice thickness also affects location and duration of the deep convection. A new control simulation, in which, amongst others, the atmosphere grid resolution is changed to T42 (~2.8˚), yields a faster deep convection flip-flop with a period of 80-100 years and a weaker but still significant global climate response similar to CMIP5 simulations. While model physics seem to affect the time scale and intensity of the phenomenon, the driving mechanism is a rather robust feature. Finally, we compare the atmospheric and oceanic responses among CMIP5 models. Since open ocean convection is the dominant mode of AABW formation in these models, the northward extent and strength of the AABW cell in the Atlantic correlates with the deep convection intensity but varies between models. Likewise, atmospheric response patterns outside the Southern Ocean region are not consistent among models.

Comparison of in vivo and ex vivo viscoelastic behavior of the spinal cord.

PubMed

Ramo, Nicole L; Shetye, Snehal S; Streijger, Femke; Lee, Jae H T; Troyer, Kevin L; Kwon, Brian K; Cripton, Peter; Puttlitz, Christian M

2018-03-01

Despite efforts to simulate the in vivo environment, post-mortem degradation and lack of blood perfusion complicate the use of ex vivo derived material models in computational studies of spinal cord injury. In order to quantify the mechanical changes that manifest ex vivo, the viscoelastic behavior of in vivo and ex vivo porcine spinal cord samples were compared. Stress-relaxation data from each condition were fit to a non-linear viscoelastic model using a novel characterization technique called the direct fit method. To validate the presented material models, the parameters obtained for each condition were used to predict the respective dynamic cyclic response. Both ex vivo and in vivo samples displayed non-linear viscoelastic behavior with a significant increase in relaxation with applied strain. However, at all three strain magnitudes compared, ex vivo samples experienced a higher stress and greater relaxation than in vivo samples. Significant differences between model parameters also showed distinct relaxation behaviors, especially in non-linear relaxation modulus components associated with the short-term response (0.1-1 s). The results of this study underscore the necessity of utilizing material models developed from in vivo experimental data for studies of spinal cord injury, where the time-dependent properties are critical. The ability of each material model to accurately predict the dynamic cyclic response validates the presented methodology and supports the use of the in vivo model in future high-resolution finite element modeling efforts. Neural tissues (such as the brain and spinal cord) display time-dependent, or viscoelastic, mechanical behavior making it difficult to model how they respond to various loading conditions, including injury. Methods that aim to characterize the behavior of the spinal cord almost exclusively use ex vivo cadaveric or animal samples, despite evidence that time after death affects the behavior compared to that in a living animal (in vivo response). Therefore, this study directly compared the mechanical response of ex vivo and in vivo samples to quantify these differences for the first time. This will allow researchers to draw more accurate conclusions about spinal cord injuries based on ex vivo data (which are easier to obtain) and emphasizes the importance of future in vivo experimental animal work. Copyright © 2017 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Time and moral judgment.

PubMed

Suter, Renata S; Hertwig, Ralph

2011-06-01

Do moral judgments hinge on the time available to render them? According to a recent dual-process model of moral judgment, moral dilemmas that engage emotional processes are likely to result in fast deontological gut reactions. In contrast, consequentialist responses that tot up lives saved and lost in response to such dilemmas would require cognitive control to override the initial response. Cognitive control, however, takes time. In two experiments, we manipulated the time available to arrive at moral judgments in two ways: by allotting a fixed short or large amount of time, and by nudging people to answer swiftly or to deliberate thoroughly. We found that faster responses indeed lead to more deontological responses among those moral dilemmas in which the killing of one to save many necessitates manhandling an innocent person and in which this action is depicted as a means to an end. Thus, our results are the first demonstration that inhibiting cognitive control through manipulations of time alters moral judgments. Copyright © 2011 Elsevier B.V. All rights reserved.

Dynamical Adaptation in Photoreceptors

PubMed Central

Clark, Damon A.; Benichou, Raphael; Meister, Markus; Azeredo da Silveira, Rava

2013-01-01

Adaptation is at the heart of sensation and nowhere is it more salient than in early visual processing. Light adaptation in photoreceptors is doubly dynamical: it depends upon the temporal structure of the input and it affects the temporal structure of the response. We introduce a non-linear dynamical adaptation model of photoreceptors. It is simple enough that it can be solved exactly and simulated with ease; analytical and numerical approaches combined provide both intuition on the behavior of dynamical adaptation and quantitative results to be compared with data. Yet the model is rich enough to capture intricate phenomenology. First, we show that it reproduces the known phenomenology of light response and short-term adaptation. Second, we present new recordings and demonstrate that the model reproduces cone response with great precision. Third, we derive a number of predictions on the response of photoreceptors to sophisticated stimuli such as periodic inputs, various forms of flickering inputs, and natural inputs. In particular, we demonstrate that photoreceptors undergo rapid adaptation of response gain and time scale, over ∼ 300 ms—i. e., over the time scale of the response itself—and we confirm this prediction with data. For natural inputs, this fast adaptation can modulate the response gain more than tenfold and is hence physiologically relevant. PMID:24244119

Optimal design of clinical trials with biologics using dose-time-response models.

PubMed

Lange, Markus R; Schmidli, Heinz

2014-12-30

Biologics, in particular monoclonal antibodies, are important therapies in serious diseases such as cancer, psoriasis, multiple sclerosis, or rheumatoid arthritis. While most conventional drugs are given daily, the effect of monoclonal antibodies often lasts for months, and hence, these biologics require less frequent dosing. A good understanding of the time-changing effect of the biologic for different doses is needed to determine both an adequate dose and an appropriate time-interval between doses. Clinical trials provide data to estimate the dose-time-response relationship with semi-mechanistic nonlinear regression models. We investigate how to best choose the doses and corresponding sample size allocations in such clinical trials, so that the nonlinear dose-time-response model can be precisely estimated. We consider both local and conservative Bayesian D-optimality criteria for the design of clinical trials with biologics. For determining the optimal designs, computer-intensive numerical methods are needed, and we focus here on the particle swarm optimization algorithm. This metaheuristic optimizer has been successfully used in various areas but has only recently been applied in the optimal design context. The equivalence theorem is used to verify the optimality of the designs. The methodology is illustrated based on results from a clinical study in patients with gout, treated by a monoclonal antibody. Copyright © 2014 John Wiley & Sons, Ltd.

Description of Aspergillus flavus growth under the influence of different factors (water activity, incubation temperature, protein and fat concentration, pH, and cinnamon essential oil concentration) by kinetic, probability of growth, and time-to-detection models.

PubMed

Kosegarten, Carlos E; Ramírez-Corona, Nelly; Mani-López, Emma; Palou, Enrique; López-Malo, Aurelio

2017-01-02

A Box-Behnken design was used to determine the effect of protein concentration (0, 5, or 10g of casein/100g), fat (0, 3, or 6g of corn oil/100g), a w (0.900, 0.945, or 0.990), pH (3.5, 5.0, or 6.5), concentration of cinnamon essential oil (CEO, 0, 200, or 400μL/kg) and incubation temperature (15, 25, or 35°C) on the growth of Aspergillus flavus during 50days of incubation. Mold response under the evaluated conditions was modeled by the modified Gompertz equation, logistic regression, and time-to-detection model. The obtained polynomial regression models allow the significant coefficients (p<0.05) for linear, quadratic and interaction effects for the Gompertz equation's parameters to be identified, which adequately described (R 2 >0.967) the studied mold responses. After 50days of incubation, every tested model system was classified according to the observed response as 1 (growth) or 0 (no growth), then a binary logistic regression was utilized to model A. flavus growth interface, allowing to predict the probability of mold growth under selected combinations of tested factors. The time-to-detection model was utilized to estimate the time at which A. flavus visible growth begins. Water activity, temperature, and CEO concentration were the most important factors affecting fungal growth. It was observed that there is a range of possible combinations that may induce growth, such that incubation conditions and the amount of essential oil necessary for fungal growth inhibition strongly depend on protein and fat concentrations as well as on the pH of studied model systems. The probabilistic model and the time-to-detection models constitute another option to determine appropriate storage/processing conditions and accurately predict the probability and/or the time at which A. flavus growth occurs. Copyright © 2016 Elsevier B.V. All rights reserved.

Lake transparency: a window into decadal variations in dissolved organic carbon concentrations in Lakes of Acadia National Park, Maine

USGS Publications Warehouse

Roesler, Collin S.; Culbertson, Charles W.

2016-01-01

A forty year time series of Secchi depth observations from approximately 25 lakes in Acadia National Park, Maine, USA, evidences large variations in transparency between lakes but relatively little seasonal cycle within lakes. However, there are coherent patterns over the time series, suggesting large scale processes are responsible. It has been suggested that variations in colored dissolved organic matter (CDOM) are primarily responsible for the variations in transparency, both between lakes and over time and further that CDOM is a robust optical proxy for dissolved organic carbon (DOC). Here we present a forward model of Secchi depth as a function of DOC based upon first principles and bio-optical relationships. Inverting the model to estimate DOC concentration from Secchi depth observations compared well with the measured DOC concentrations collected since 1995 (RMS error < 1.3 mg C l-1). This inverse model allows the time series of DOC to be extended back to the mid 1970s when only Secchi depth observations were collected, and thus provides a means for investigating lake response to climate forcing, changing atmospheric chemistry and watershed characteristics, including land cover and land use.

A Computational Approach for Probabilistic Analysis of LS-DYNA Water Impact Simulations

NASA Technical Reports Server (NTRS)

Horta, Lucas G.; Mason, Brian H.; Lyle, Karen H.

2010-01-01

NASA s development of new concepts for the Crew Exploration Vehicle Orion presents many similar challenges to those worked in the sixties during the Apollo program. However, with improved modeling capabilities, new challenges arise. For example, the use of the commercial code LS-DYNA, although widely used and accepted in the technical community, often involves high-dimensional, time consuming, and computationally intensive simulations. Because of the computational cost, these tools are often used to evaluate specific conditions and rarely used for statistical analysis. The challenge is to capture what is learned from a limited number of LS-DYNA simulations to develop models that allow users to conduct interpolation of solutions at a fraction of the computational time. For this problem, response surface models are used to predict the system time responses to a water landing as a function of capsule speed, direction, attitude, water speed, and water direction. Furthermore, these models can also be used to ascertain the adequacy of the design in terms of probability measures. This paper presents a description of the LS-DYNA model, a brief summary of the response surface techniques, the analysis of variance approach used in the sensitivity studies, equations used to estimate impact parameters, results showing conditions that might cause injuries, and concluding remarks.

Characterization of tissue response to radiofrequency ablation using 3D model-based analysis of interventional MR images

NASA Astrophysics Data System (ADS)

Weinberg, Brent D.; Lazebnik, Roee S.; Breen, Michael S.; Lewin, Jonathan S.; Wilson, David L.

2003-05-01

Using magnetic resonance imaging (MRI), real-time guidance is feasible for radiofrequency (RF) current ablation of pathologic tissue. Lesions have a characteristic two-zone appearance: an inner core (Zone I) surrounded by a hyper-intense rim (Zone II). A better understanding of both the immediate (hyper-acute) and delayed (sub-acute) physiological response of the target tissue will aid development of minimally invasive tumor treatment strategies. We performed in vivo RF ablations in a rabbit thigh model and characterized the tissue response to treatment through contrast enhanced (CE) T1 and T2 weighted MR images at two time points. We measured zonal grayscale changes as well as zone volume changes using a 3D computationally fitted globally deformable parametric model. Comparison over time demonstrated an increase in the volume of both the inner necrotic core (mean 56.5% increase) and outer rim (mean 16.8% increase) of the lesion. Additionally, T2 images of the lesion exhibited contrast greater than or equal to CE T1 (mean 35% improvement). This work establishes a foundation for the clinical use of T2 MR images coupled with a geometric model of the ablation for noninvasive lesion monitoring and characterization.

Accounting for inter-annual and seasonal variability in regionalization of hydrologic response in the Great Lakes basin

NASA Astrophysics Data System (ADS)

Kult, J. M.; Fry, L. M.; Gronewold, A. D.

2012-12-01

Methods for predicting streamflow in areas with limited or nonexistent measures of hydrologic response typically invoke the concept of regionalization, whereby knowledge pertaining to gauged catchments is transferred to ungauged catchments. In this study, we identify watershed physical characteristics acting as primary drivers of hydrologic response throughout the US portion of the Great Lakes basin. Relationships between watershed physical characteristics and hydrologic response are generated from 166 catchments spanning a variety of climate, soil, land cover, and land form regimes through regression tree analysis, leading to a grouping of watersheds exhibiting similar hydrologic response characteristics. These groupings are then used to predict response in ungauged watersheds in an uncertainty framework. Results from this method are assessed alongside one historical regionalization approach which, while simple, has served as a cornerstone of Great Lakes regional hydrologic research for several decades. Our approach expands upon previous research by considering multiple temporal characterizations of hydrologic response. Due to the substantial inter-annual and seasonal variability in hydrologic response observed over the Great Lakes basin, results from the regression tree analysis differ considerably depending on the level of temporal aggregation used to define the response. Specifically, higher levels of temporal aggregation for the response metric (for example, indices derived from long-term means of climate and streamflow observations) lead to improved watershed groupings with lower within-group variance. However, this perceived improvement in model skill occurs at the cost of understated uncertainty when applying the regression to time series simulations or as a basis for model calibration. In such cases, our results indicate that predictions based on long-term characterizations of hydrologic response can produce misleading conclusions when applied at shorter time steps. This study suggests that measures of hydrologic response quantified at these shorter time steps may provide a more robust basis for making predictions in applications of water resource management, model calibration and simulations, and human health and safety.

Climate warming due to increasing atmospheric CO2 - Simulations with a multilayer coupled atmosphere-ocean seasonal energy balance model

NASA Technical Reports Server (NTRS)

Li, Peng; Chou, Ming-Dah; Arking, Albert

1987-01-01

The transient response of the climate to increasing CO2 is studied using a modified version of the multilayer energy balance model of Peng et al. (1982). The main characteristics of the model are described. Latitudinal and seasonal distributions of planetary albedo, latitude-time distributions of zonal mean temperatures, and latitudinal distributions of evaporation, water vapor transport, and snow cover generated from the model and derived from actual observations are analyzed and compared. It is observed that in response to an atmospheric doubling of CO2, the model reaches within 1/e of the equilibrium response of global mean surface temperature in 9-35 years for the probable range of vertical heat diffusivity in the ocean. For CO2 increases projected by the National Research Council (1983), the model's transient response in annually and globally averaged surface temperatures is 60-75 percent of the corresponding equilibrium response, and the disequilibrium increases with increasing heat diffusivity of the ocean.

A model of survival following pre-hospital cardiac arrest based on the Victorian Ambulance Cardiac Arrest Register.

PubMed

Fridman, Masha; Barnes, Vanessa; Whyman, Andrew; Currell, Alex; Bernard, Stephen; Walker, Tony; Smith, Karen L

2007-11-01

This study describes the epidemiology of sudden cardiac arrest patients in Victoria, Australia, as captured via the Victorian Ambulance Cardiac Arrest Register (VACAR). We used the VACAR data to construct a new model of out-of-hospital cardiac arrest (OHCA), which was specified in accordance with observed trends. All cases of cardiac arrest in Victoria that were attended by Victorian ambulance services during the period of 2002-2005. Overall survival to hospital discharge was 3.8% among 18,827 cases of OHCA. Survival was 15.7% among 1726 bystander witnessed, adult cardiac arrests of presumed cardiac aetiology, presenting in ventricular fibrillation or ventricular tachycardia (VF/VT), where resuscitation was attempted. In multivariate logistic regression analysis, bystander CPR, cardiac arrest (CA) location, response time, age and sex were predictors of VF/VT, which, in turn, was a strong predictor of survival. The same factors that affected VF/VT made an additional contribution to survival. However, for bystander CPR, CA location and response time this additional contribution was limited to VF/VT patients only. There was no detectable association between survival and age younger than 60 years or response time over 15min. The new model accounts for relationships among predictors of survival. These relationships indicate that interventions such as reduced response times and bystander CPR act in multiple ways to improve survival.

Response inhibition predicts poor antidepressant treatment response in very old depressed patients.

PubMed

Sneed, Joel R; Roose, Steven P; Keilp, John G; Krishnan, K Ranga Rama; Alexopoulos, George S; Sackeim, Harold A

2007-07-01

There have been mixed findings regarding the prognostic significance of age of onset, executive dysfunction, and hyperintensity burden on treatment outcome in late-life depression. Growth curve models were fit to data from the only 8-week, double-blind, placebo controlled trial of citalopram (20-40 mg/day) in patients aged 75 years and older with unipolar depression. Baseline assessment included Structured Clinical Interview for Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) (to determine age at onset), Stroop Color-Word Test (to assess the response inhibition component of execution dysfunction), and structural magnetic resonance imaging (to determine hyperintensity burden). In the citalopram condition, patients with response inhibition (most impaired quartile) scored higher at endpoint than those without response inhibition. There were no effects for age of onset or hyperintensity load on response in the citalopram condition. In the placebo condition, patients with early-onset depression had higher depression scores at endpoint than patients with late-onset depression. Only response inhibition, a fundamental executive function, predicted poor treatment response to antidepressant medication. Although patients with response inhibition also showed deficits in reaction time, adjusting for reaction time in our final response inhibition model did not substantively change the findings.

Neuropathogenesis of Zika Virus in a Highly Susceptible Immunocompetent Mouse Model after Antibody Blockade of Type I Interferon (Open Access Publisher’s Version)

DTIC Science & Technology

2017-01-09

death, astrogliosis, microgliosis, scattered necrotic cellular debris, and inflammatory cell infiltrates. This model of ZIKV pathogenesis will be...these models is they utilize immunodeficient knockout mice lacking key compo- nents of the innate antiviral response. We describe the use of a lethal...murine model for ZIKV where the innate response of immunocompetent mice is suppressed only at the time of infection. We show that the mice develop

On universal procrastination

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2017-09-01

This paper presents a general stochastic model for procrastination with respect to a deadline. The model establishes a universal procrastination pattern that follows an inverse power-law: if the time remaining to the deadline is r then the response is 1/rε , where ɛ is a positive exponent. The model further establishes that the exponent value ε =1 , which yields the harmonic response 1/r , stands out as special and distinguishable. The theoretical results of the model are shown to be in perfect accord with recent empirical findings.

Fast and slow responses of Southern Ocean sea surface temperature to SAM in coupled climate models

NASA Astrophysics Data System (ADS)

Kostov, Yavor; Marshall, John; Hausmann, Ute; Armour, Kyle C.; Ferreira, David; Holland, Marika M.

2017-03-01

We investigate how sea surface temperatures (SSTs) around Antarctica respond to the Southern Annular Mode (SAM) on multiple timescales. To that end we examine the relationship between SAM and SST within unperturbed preindustrial control simulations of coupled general circulation models (GCMs) included in the Climate Modeling Intercomparison Project phase 5 (CMIP5). We develop a technique to extract the response of the Southern Ocean SST (55°S-70°S) to a hypothetical step increase in the SAM index. We demonstrate that in many GCMs, the expected SST step response function is nonmonotonic in time. Following a shift to a positive SAM anomaly, an initial cooling regime can transition into surface warming around Antarctica. However, there are large differences across the CMIP5 ensemble. In some models the step response function never changes sign and cooling persists, while in other GCMs the SST anomaly crosses over from negative to positive values only 3 years after a step increase in the SAM. This intermodel diversity can be related to differences in the models' climatological thermal ocean stratification in the region of seasonal sea ice around Antarctica. Exploiting this relationship, we use observational data for the time-mean meridional and vertical temperature gradients to constrain the real Southern Ocean response to SAM on fast and slow timescales.

Helical wire stress analysis of unbonded flexible riser under irregular response

NASA Astrophysics Data System (ADS)

Wang, Kunpeng; Ji, Chunyan

2017-06-01

A helical wire is a critical component of an unbonded flexible riser prone to fatigue failure. The helical wire has been the focus of much research work in recent years because of the complex multilayer construction of the flexible riser. The present study establishes an analytical model for the axisymmetric and bending analyses of an unbonded flexible riser. The interlayer contact under axisymmetric loads in this model is modeled by setting radial dummy springs between adjacent layers. The contact pressure is constant during the bending response and applied to determine the slipping friction force per unit helical wire. The model tracks the axial stress around the angular position at each time step to calculate the axial force gradient, then compares the axial force gradient with the slipping friction force to judge the helical wire slipping region, which would be applied to determine the bending stiffness for the next time step. The proposed model is verified against the experimental data in the literature. The bending moment-curvature relationship under irregular response is also qualitatively discussed. The stress at the critical point of the helical wire is investigated based on the model by considering the local flexure. The results indicate that the present model can well simulate the bending stiffness variation during irregular response, which has significant effect on the stress of helical wire.

A basic mathematical model of the immune response

NASA Astrophysics Data System (ADS)

Mayer, H.; Zaenker, K. S.; an der Heiden, U.

1995-03-01

Interaction of the immune system with a target population of, e.g., bacteria, viruses, antigens, or tumor cells must be considered as a dynamic process. We describe this process by a system of two ordinary differential equations. Although the model is strongly idealized it demonstrates how the combination of a few proposed nonlinear interaction rules between the immune system and its targets are able to generate a considerable variety of different kinds of immune responses, many of which are observed both experimentally and clinically. In particular, solutions of the model equations correspond to states described by immunologists as ``virgin state,'' ``immune state'' and ``state of tolerance.'' The model successfully replicates the so-called primary and secondary response. Moreover, it predicts the existence of a threshold level for the amount of pathogen germs or of transplanted tumor cells below which the host is able to eliminate the infectious organism or to reject the tumor graft. We also find a long time coexistence of targets and immune competent cells including damped and undamped oscillations of both. Plausibly the model explains that if the number of transformed cells or pathogens exeeds definable values (poor antigenicity, high reproduction rate) the immune system fails to keep the disease under control. On the other hand, the model predicts apparently paradoxical situations including an increased chance of target survival despite enhanced immune activity or therapeutically achieved target reduction. A further obviously paradoxical behavior consists of a positive effect for the patient up to a complete cure by adding an additional target challenge where the benefit of the additional targets depends strongly on the time point and on their amount. Under periodically pulsed stimulation the model may show a chaotic time behavior of both target growth and immune response.

Helicopter flight dynamics simulation with a time-accurate free-vortex wake model

NASA Astrophysics Data System (ADS)

Ribera, Maria

This dissertation describes the implementation and validation of a coupled rotor-fuselage simulation model with a time-accurate free-vortex wake model capable of capturing the response to maneuvers of arbitrary amplitude. The resulting model has been used to analyze different flight conditions, including both steady and transient maneuvers. The flight dynamics model is based on a system of coupled nonlinear rotor-fuselage differential equations in first-order, state-space form. The rotor model includes flexible blades, with coupled flap-lag-torsion dynamics and swept tips; the rigid body dynamics are modeled with the non-linear Euler equations. The free wake models the rotor flow field by tracking the vortices released at the blade tips. Their behavior is described by the equations of vorticity transport, which is approximated using finite differences, and solved using a time-accurate numerical scheme. The flight dynamics model can be solved as a system of non-linear algebraic trim equations to determine the steady state solution, or integrated in time in response to pilot-applied controls. This study also implements new approaches to reduce the prohibitive computational costs associated with such complex models without losing accuracy. The mathematical model was validated for trim conditions in level flight, turns, climbs and descents. The results obtained correlate well with flight test data, both in level flight as well as turning and climbing and descending flight. The swept tip model was also found to improve the trim predictions, particularly at high speed. The behavior of the rigid body and the rotor blade dynamics were also studied and related to the aerodynamic load distributions obtained with the free wake induced velocities. The model was also validated in a lateral maneuver from hover. The results show improvements in the on-axis prediction, and indicate a possible relation between the off-axis prediction and the lack of rotor-body interaction aerodynamics. The swept blade model improves both the on-axis and off-axis response. An axial descent though the vortex ring state was simulated. As theǒrtex ring" goes through the rotor, the unsteady loads produce large attitude changes, unsteady flapping, fluctuating thrust and an increase in power required. A roll reversal maneuver was found useful in understanding the cross-couplings effects found in rotorcraft, specifically the effect of the aerodynamic loading on the rotor orientation and the off-axis response.

Experimental and computational results on exciton/free-carrier ratio, hot/thermalized carrier diffusion, and linear/nonlinear rate constants affecting scintillator proportionality

NASA Astrophysics Data System (ADS)

Williams, R. T.; Grim, Joel Q.; Li, Qi; Ucer, K. B.; Bizarri, G. A.; Kerisit, S.; Gao, Fei; Bhattacharya, P.; Tupitsyn, E.; Rowe, E.; Buliga, V. M.; Burger, A.

2013-09-01

Models of nonproportional response in scintillators have highlighted the importance of parameters such as branching ratios, carrier thermalization times, diffusion, kinetic order of quenching, associated rate constants, and radius of the electron track. For example, the fraction ηeh of excitations that are free carriers versus excitons was shown by Payne and coworkers to have strong correlation with the shape of electron energy response curves from Compton-coincidence studies. Rate constants for nonlinear quenching are implicit in almost all models of nonproportionality, and some assumption about track radius must invariably be made if one is to relate linear energy deposition dE/dx to volume-based excitation density n (eh/cm3) in terms of which the rates are defined. Diffusion, affecting time-dependent track radius and thus density of excitations, has been implicated as an important factor in nonlinear light yield. Several groups have recently highlighted diffusion of hot electrons in addition to thermalized carriers and excitons in scintillators. However, experimental determination of many of these parameters in the insulating crystals used as scintillators has seemed difficult. Subpicosecond laser techniques including interband z scan light yield, fluence-dependent decay time, and transient optical absorption are now yielding experimental values for some of the missing rates and ratios needed for modeling scintillator response. First principles calculations and Monte Carlo simulations can fill in additional parameters still unavailable from experiment. As a result, quantitative modeling of scintillator electron energy response from independently determined material parameters is becoming possible on an increasingly firmer data base. This paper describes recent laser experiments, calculations, and numerical modeling of scintillator response.

Experimental and computational results on exciton/free-carrier ratio, hot/thermalized carrier diffusion, and linear/nonlinear rate constants affecting scintillator proportionality

DOE PAGES

Williams, R. T.; Grim, Joel Q.; Li, Qi; ...

2013-09-26

Models of nonproportional response in scintillators have highlighted the importance of parameters such as branching ratios, carrier thermalization times, diffusion, kinetic order of quenching, associated rate constants, and radius of the electron track. For example, the fraction ηeh of excitations that are free carriers versus excitons was shown by Payne and coworkers to have strong correlation with the shape of electron energy response curves from Compton-coincidence studies. Rate constants for nonlinear quenching are implicit in almost all models of nonproportionality, and some assumption about track radius must invariably be made if one is to relate linear energy deposition dE/dx tomore » volume-based excitation density n (eh/cm 3) in terms of which the rates are defined. Diffusion, affecting time-dependent track radius and thus density of excitations, has been implicated as an important factor in nonlinear light yield. Several groups have recently highlighted diffusion of hot electrons in addition to thermalized carriers and excitons in scintillators. However, experimental determination of many of these parameters in the insulating crystals used as scintillators has seemed difficult. Subpicosecond laser techniques including interband z scan light yield, fluence-dependent decay time, and transient optical absorption are now yielding experimental values for some of the missing rates and ratios needed for modeling scintillator response. First principles calculations and Monte Carlo simulations can fill in additional parameters still unavailable from experiment. As a result, quantitative modeling of scintillator electron energy response from independently determined material parameters is becoming possible on an increasingly firmer data base. This study describes recent laser experiments, calculations, and numerical modeling of scintillator response.« less

Examining the time course of genital and subjective sexual responses in women and men with concurrent plethysmography and thermography.

PubMed

Huberman, Jackie S; Dawson, Samantha J; Chivers, Meredith L

2017-10-01

Sexual response is a dynamic process, though there is limited knowledge of the time course and relationships among its psychological and physiological components. To address this gap, we concurrently assessed self-reported sexual arousal, genital temperature (with thermography), and genital vasocongestion (with vaginal photoplethysmography [VPP] or penile plethysmography [PPG]) during sexual and nonsexual films in 28 androphilic women (attracted to men) and 27 gynephilic men (attracted to women). Men and women had similarly strong agreement between subjective and genital responses (sexual concordance) with thermography, but this agreement was stronger in men than women with PPG/VPP. The time course of changes in self-reported arousal was most similar to changes in genital temperature (i.e., time to onset and peak response). Time-lagged correlations and multilevel modeling revealed changes in the strength of relationships between aspects of sexual response over time. Results highlight the dynamic nature of sexual response and drawbacks of relying on zero-order correlations to characterize sexual concordance. Copyright © 2017 Elsevier B.V. All rights reserved.

An Improved Dynamic Model for the Respiratory Response to Exercise

PubMed Central

Serna, Leidy Y.; Mañanas, Miguel A.; Hernández, Alher M.; Rabinovich, Roberto A.

2018-01-01

Respiratory system modeling has been extensively studied in steady-state conditions to simulate sleep disorders, to predict its behavior under ventilatory diseases or stimuli and to simulate its interaction with mechanical ventilation. Nevertheless, the studies focused on the instantaneous response are limited, which restricts its application in clinical practice. The aim of this study is double: firstly, to analyze both dynamic and static responses of two known respiratory models under exercise stimuli by using an incremental exercise stimulus sequence (to analyze the model responses when step inputs are applied) and experimental data (to assess prediction capability of each model). Secondly, to propose changes in the models' structures to improve their transient and stationary responses. The versatility of the resulting model vs. the other two is shown according to the ability to simulate ventilatory stimuli, like exercise, with a proper regulation of the arterial blood gases, suitable constant times and a better adjustment to experimental data. The proposed model adjusts the breathing pattern every respiratory cycle using an optimization criterion based on minimization of work of breathing through regulation of respiratory frequency. PMID:29467674

Relating the variability of tone-burst otoacoustic emission and auditory brainstem response latencies to the underlying cochlear mechanics

NASA Astrophysics Data System (ADS)

Verhulst, Sarah; Shera, Christopher A.

2015-12-01

Forward and reverse cochlear latency and its relation to the frequency tuning of the auditory filters can be assessed using tone bursts (TBs). Otoacoustic emissions (TBOAEs) estimate the cochlear roundtrip time, while auditory brainstem responses (ABRs) to the same stimuli aim at measuring the auditory filter buildup time. Latency ratios are generally close to two and controversy exists about the relationship of this ratio to cochlear mechanics. We explored why the two methods provide different estimates of filter buildup time, and ratios with large inter-subject variability, using a time-domain model for OAEs and ABRs. We compared latencies for twenty models, in which all parameters but the cochlear irregularities responsible for reflection-source OAEs were identical, and found that TBOAE latencies were much more variable than ABR latencies. Multiple reflection-sources generated within the evoking stimulus bandwidth were found to shape the TBOAE envelope and complicate the interpretation of TBOAE latency and TBOAE/ABR ratios in terms of auditory filter tuning.

Modeling the Scheduling of Eye Movements and Manual Responses in Performing a Sequence of Discrete Tasks

NASA Technical Reports Server (NTRS)

Wu, Shu-Chieh; Remington, Roger W.; Lewis, Richard

2006-01-01

Common tasks in daily life are often accomplished by a sequence of actions that interleave information acquisition through the eyes and action execution by the hands. How are eye movements coordinated with the release of manual responses and how may their coordination be represented at the level of component mental operations? We have previously presented data from a typing-like task requiring separate choice responses to a series of five stimuli. We found a consistent pattern of results in both motor and ocular timing, and hypothesized possible relationships among underlying components. Here we report a model of that task, which demonstrates how the observed timing of eye movements to successive stimuli could be accounted for by assuming systems: an open-loop system generating saccades at a periodic rate, and a closed-loop system commanding a saccade based on stimulus processing. We relate this model to models of reading and discuss the motivation for dual control.

A micro-epidemic model for primary dengue infection

NASA Astrophysics Data System (ADS)

Mishra, Arti; Gakkhar, Sunita

2017-06-01

In this paper, a micro-epidemic non-linear dynamical model has been proposed and analyzed for primary dengue infection. The model incorporates the effects of T cells immune response as well as humoral response during pathogenesis of dengue infection. The time delay has been accounted for production of antibodies from B cells. The basic reproduction number (R0) has been computed. Three equilibrium states are obtained. The existence and stability conditions for infection-free and ineffective cellular immune response state have been discussed. The conditions for existence of endemic state have been obtained. Further, the parametric region is obtained where system exhibits complex behavior. The threshold value of time delay has been computed which is critical for change in stability of endemic state. A threshold level for antibodies production rate has been obtained over which the infection will die out even though R0 > 1. The model is in line with the clinical observation that viral load decreases within 7-14 days from the onset of primary infection.

Numerical study on response time of a parallel plate capacitive polyimide humidity sensor based on microhole upper electrode

NASA Astrophysics Data System (ADS)

Zhou, Wenhe; He, Xuan; Wu, Jianyun; Wang, Liangbi; Wang, Liangcheng

2017-07-01

The parallel plate capacitive humidity sensor based on the grid upper electrode is considered to be a promising one in some fields which require a humidity sensor with better dynamic characteristics. To strengthen the structure and balance the electric charge of the grid upper electrode, a strip is needed. However, it is the strip that keeps the dynamic characteristics of the sensor from being further improved. The numerical method is time- and cost-saving, but the numerical study on the response time of the sensor is just of bits and pieces. The numerical models presented by these studies did not consider the porosity effect of the polymer film on the dynamic characteristics. To overcome the defect of the grid upper electrode, a new structure of the upper electrode is provided by this paper first, and then a model considering the porosity effects of the polymer film on the dynamic characteristics is presented and validated. Finally, with the help of software FLUENT, parameter effects on the response time of the humidity sensor based on the microhole upper electrode are studied by the numerical method. The numerical results show that the response time of the microhole upper electrode sensor is 86% better than that of the grid upper electrode sensor, the response time of humidity sensor can be improved by reducing the hole spacing, increasing the aperture, reducing film thickness, and reasonably enlarging the porosity of the film.

Low-Dose Involved-Field Radiation in the Treatment of Non-Hodgkin Lymphoma: Predictors of Response and Treatment Failure

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

Russo, Andrea L., E-mail: alrusso@partners.org; Chen, Yu-Hui; Martin, Neil E.

Purpose: To investigate clinical and pathologic factors significant in predicting local response and time to further treatment after low-dose involved-field radiation therapy (LD-IFRT) for non-Hodgkin lymphoma (NHL). Methods and Materials: Records of NHL patients treated at a single institution between April 2004 and September 2011 were retrospectively reviewed. Low-dose involved-field radiation therapy was given as 4 Gy in 2 fractions over 2 consecutive days. Treatment response and disease control were determined by radiographic studies and/or physical examination. A generalized estimating equation model was used to assess the effect of tumor and patient characteristics on disease response. A Cox proportional hazardsmore » regression model was used to assess time to further treatment. Results: We treated a total of 187 sites in 127 patients with LD-IFRT. Histologies included 66% follicular, 9% chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma, 10% marginal zone, 6% mantle cell lymphoma (MCL), and 8% other. Median follow-up time was 23.4 months (range, 0.03-92.2 months). The complete response, partial response, and overall response rates were 57%, 25%, and 82%, respectively. A CLL histology was associated with a lower response rate (odds ratio 0.2, 95% confidence interval 0.1-0.5, P=.02). Tumor size, site, age at diagnosis, and prior systemic therapy were not associated with response. The median time to first recurrence was 13.6 months. Those with CLL and age ≤50 years at diagnosis had a shorter time to further treatment for local failures (hazard ratio [HR] 3.63, P=.01 and HR 5.50, P=.02, respectively). Those with CLL and MCL had a shorter time to further treatment for distant failures (HR 11.1 and 16.3, respectively, P<.0001). Conclusions: High local response rates were achieved with LD-IFRT across most histologies. Chronic lymphocytic leukemia and MCL histologies and age ≤50 years at diagnosis had a shorter time to further treatment after LD-IFRT.« less

Development of model infectious disease protocols for fire and EMS personnel.

PubMed

Miller, Nancy L; Gudmestad, Tom; Eisenberg, Mickey S

2005-01-01

To develop model infectious disease exposure plans for emergency medical services agencies in King County, Washington. All fire departments in King County, Washington, were surveyed to determine their pathogen exposure policies. After these agencies were surveyed, model response plans were developed for both bloodborne and airborne pathogen exposure. Twenty-four of the 35 fire departments in King County submitted infectious disease exposure policies. There was diversity among the plans, and not all were deemed able to provide prophylaxis in a timely fashion. Based on this lack of uniformity among response plans, model response plans were developed for bloodborne and airborne infectious disease pathogens. Great variety was present throughout the exposure plans currently in use throughout King County, Washington. Model plans would likely universalize response to pathogen exposure and help to ensure prompt and appropriate postexposure prophylaxis.

Transient responses of phosphoric acid fuel cell power plant system. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Lu, Cheng-Yi

1983-01-01

An analytical and computerized study of the steady state and transient response of a phosphoric acid fuel cell (PAFC) system was completed. Parametric studies and sensitivity analyses of the PAFC system's operation were accomplished. Four non-linear dynamic models of the fuel cell stack, reformer, shift converters, and heat exchangers were developed based on nonhomogeneous non-linear partial differential equations, which include the material, component, energy balance, and electrochemical kinetic features. Due to a lack of experimental data for the dynamic response of the components only the steady state results were compared with data from other sources, indicating reasonably good agreement. A steady state simulation of the entire system was developed using, nonlinear ordinary differential equations. The finite difference method and trial-and-error procedures were used to obtain a solution. Using the model, a PAFC system, that was developed under NASA Grant, NCC3-17, was improved through the optimization of the heat exchanger network. Three types of cooling configurations for cell plates were evaluated to obtain the best current density and temperature distributions. The steady state solutions were used as the initial conditions in the dynamic model. The transient response of a simplified PAFC system, which included all of the major components, subjected to a load change was obtained. Due to the length of the computation time for the transient response calculations, analysis on a real-time computer was not possible. A simulation of the real-time calculations was developed on a batch type computer. The transient response characteristics are needed for the optimization of the design and control of the whole PAFC system. All of the models, procedures and simulations were programmed in Fortran and run on IBM 370 computers at Cleveland State University and the NASA Lewis Research Center.

Time-resolved spectroscopy at surfaces and adsorbate dynamics:insights from a model-system approach

NASA Astrophysics Data System (ADS)

Boström, Emil; Mikkelsen, Anders; Verdozzi, Claudio

We introduce a finite-system, model description of the initial stages of femtosecond laser induced desorption at surfaces. Using the exact many-body time evolution and also results from a novel time-dependent DFT description for electron-nuclear systems, we analyse the competition between several surface-response mechanisms and electronic correlations in the transient and longer time dynamics under the influence of dipole-coupled fields. Our model allows us to explore how coherent multiple-pulse protocols impact desorption in a variety of prototypical experiments.

Semi-empirical study of ortho-cresol photo degradation in manganese-doped zinc oxide nanoparticles suspensions

PubMed Central

2012-01-01

The optimization processes of photo degradation are complicated and expensive when it is performed with traditional methods such as one variable at a time. In this research, the condition of ortho-cresol (o-cresol) photo degradation was optimized by using a semi empirical method. First of all, the experiments were designed with four effective factors including irradiation time, pH, photo catalyst’s amount, o-cresol concentration and photo degradation % as response by response surface methodology (RSM). The RSM used central composite design (CCD) method consists of 30 runs to obtain the actual responses. The actual responses were fitted with the second order algebraic polynomial equation to select a model (suggested model). The suggested model was validated by a few numbers of excellent statistical evidences in analysis of variance (ANOVA). The used evidences include high F-value (143.12), very low P-value (<0.0001), non-significant lack of fit, the determination coefficient (R2 = 0.99) and the adequate precision (47.067). To visualize the optimum, the validated model simulated the condition of variables and response (photo degradation %) be using a few number of three dimensional plots (3D). To confirm the model, the optimums were performed in laboratory. The results of performed experiments were quite close to the predicted values. In conclusion, the study indicated that the model is successful to simulate the optimum condition of o-cresol photo degradation under visible-light irradiation by manganese doped ZnO nanoparticles. PMID:22909072

Recent topographic evolution and erosion of the deglaciated Washington Cascades inferred from a stochastic landscape evolution model

NASA Astrophysics Data System (ADS)

Moon, Seulgi; Shelef, Eitan; Hilley, George E.

2015-05-01

In this study, we model postglacial surface processes and examine the evolution of the topography and denudation rates within the deglaciated Washington Cascades to understand the controls on and time scales of landscape response to changes in the surface process regime after deglaciation. The postglacial adjustment of this landscape is modeled using a geomorphic-transport-law-based numerical model that includes processes of river incision, hillslope diffusion, and stochastic landslides. The surface lowering due to landslides is parameterized using a physically based slope stability model coupled to a stochastic model of the generation of landslides. The model parameters of river incision and stochastic landslides are calibrated based on the rates and distribution of thousand-year-time scale denudation rates measured from cosmogenic 10Be isotopes. The probability distributions of those model parameters calculated based on a Bayesian inversion scheme show comparable ranges from previous studies in similar rock types and climatic conditions. The magnitude of landslide denudation rates is determined by failure density (similar to landslide frequency), whereas precipitation and slopes affect the spatial variation in landslide denudation rates. Simulation results show that postglacial denudation rates decay over time and take longer than 100 kyr to reach time-invariant rates. Over time, the landslides in the model consume the steep slopes characteristic of deglaciated landscapes. This response time scale is on the order of or longer than glacial/interglacial cycles, suggesting that frequent climatic perturbations during the Quaternary may produce a significant and prolonged impact on denudation and topography.

Understanding the Asian summer monsoon response to greenhouse warming: the relative roles of direct radiative forcing and sea surface temperature change

NASA Astrophysics Data System (ADS)

Li, Xiaoqiong; Ting, Mingfang

2017-10-01

Future hydroclimate projections from state-of-the-art climate models show large uncertainty and model spread, particularly in the tropics and over the monsoon regions. The precipitation and circulation responses to rising greenhouse gases involve a fast component associated with direct radiative forcing and a slow component associated with sea surface temperature (SST) warming; the relative importance of the two may contribute to model discrepancies. In this study, regional hydroclimate responses to greenhouse warming are assessed using output from coupled general circulation models in the Coupled Model Intercomparison Project-Phase 5 (CMIP5) and idealized atmospheric general circulation model experiments from the Atmosphere Model Intercomparison Project. The thermodynamic and dynamic mechanisms causing the rainfall changes are examined using moisture budget analysis. Results show that direct radiative forcing and SST change exert significantly different responses both over land and ocean. For most part of the Asian monsoon region, the summertime rainfall changes are dominated by the direct CO2 radiative effect through enhanced monsoon circulation. The response to SST warming shows a larger model spread compared to direct radiative forcing, possibly due to the cancellation between the thermodynamical and dynamical components. While the thermodynamical response of the Asian monsoon is robust across the models, there is a lack of consensus for the dynamical response among the models and weak multi-model mean responses in the CMIP5 ensemble, which may be related to the multiple physical processes evolving on different time scales.

A new short-term forecasting model for the total electron content storm time disturbances

NASA Astrophysics Data System (ADS)

Tsagouri, Ioanna; Koutroumbas, Konstantinos; Elias, Panagiotis

2018-06-01

This paper aims to introduce a new model for the short-term forecast of the vertical Total Electron Content (vTEC). The basic idea of the proposed model lies on the concept of the Solar Wind driven autoregressive model for Ionospheric short-term Forecast (SWIF). In its original version, the model is operationally implemented in the DIAS system (http://dias.space.noa.gr) and provides alerts and warnings for upcoming ionospheric disturbances, as well as single site and regional forecasts of the foF2 critical frequency over Europe up to 24 h in advance. The forecasts are driven by the real time assessment of the solar wind conditions at ACE location. The comparative analysis of the variations in foF2 and vTEC during eleven geomagnetic storm events that occurred in the present solar cycle 24 reveals similarities but also differences in the storm-time response of the two characteristics with respect to the local time and the latitude of the observation point. Since the aforementioned dependences drive the storm-time forecasts of the SWIF model, the results obtained here support the upgrade of the SWIF's modeling technique in forecasting the storm-time vTEC variation from its onset to full development and recovery. According to the proposed approach, the vTEC storm-time response can be forecasted from 1 to 12-13 h before its onset, depending on the local time of the observation point at storm onset at L1. Preliminary results on the assessment of the performance of the proposed model and further considerations on its potential implementation in operational mode are also discussed.

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

Water and Solute Flux Simulation Using Hydropedology Survey Data in South African Catchments

NASA Astrophysics Data System (ADS)

Lorentz, Simon; van Tol, Johan; le Roux, Pieter

2017-04-01

Hydropedology surveys include linking soil profile information in hillslope transects in order to define dominant subsurface flow mechanisms and pathways. This information is useful for deriving hillslope response functions, which aid storage and travel time estimates of water and solute movement in the sub-surface. In this way, the "soft" data of the hydropedological survey can be included in simple hydrological models, where detailed modelling of processes and pathways is prohibitive. Hydropedology surveys were conducted in two catchments and the information used to improve the prediction of water and solute responses. Typical hillslope response functions are then derived using a 2-D finite element model of the hydropedological features. Similar response types are mapped. These mapped response units are invoked in a simple SCS based, hydrological and solute transport model to yield water and solute fluxes at the catchment outlets. The first catchment (1.6 km2) comprises commercial forestry in a sedimentary geology of sandstone and mudstone formation while the second catchment (6.1 km2) includes mine waste impoundments in a granitic geology. In this paper, we demonstrate the method of combining hydropedological interpretation with catchment hydrology and solute transport simulation. The forested catchment, with three dominant hillslope response types, have solute response times in excess of 90 days, whereas the granitic responses occur within 10 days. The use of the hydropedological data improves the solute distribution response and storage simulation, compared to simulations without the hydropedology interpretation. The hydrological responses are similar, with and without the use of the hydropedology data, but the simulated distribution of water in the catchment is improved using the techniques demonstrated.

Using genetic algorithms to optimise current and future health planning--the example of ambulance locations.

PubMed

Sasaki, Satoshi; Comber, Alexis J; Suzuki, Hiroshi; Brunsdon, Chris

2010-01-28

Ambulance response time is a crucial factor in patient survival. The number of emergency cases (EMS cases) requiring an ambulance is increasing due to changes in population demographics. This is decreasing ambulance response times to the emergency scene. This paper predicts EMS cases for 5-year intervals from 2020, to 2050 by correlating current EMS cases with demographic factors at the level of the census area and predicted population changes. It then applies a modified grouping genetic algorithm to compare current and future optimal locations and numbers of ambulances. Sets of potential locations were evaluated in terms of the (current and predicted) EMS case distances to those locations. Future EMS demands were predicted to increase by 2030 using the model (R2 = 0.71). The optimal locations of ambulances based on future EMS cases were compared with current locations and with optimal locations modelled on current EMS case data. Optimising the location of ambulance stations locations reduced the average response times by 57 seconds. Current and predicted future EMS demand at modelled locations were calculated and compared. The reallocation of ambulances to optimal locations improved response times and could contribute to higher survival rates from life-threatening medical events. Modelling EMS case 'demand' over census areas allows the data to be correlated to population characteristics and optimal 'supply' locations to be identified. Comparing current and future optimal scenarios allows more nuanced planning decisions to be made. This is a generic methodology that could be used to provide evidence in support of public health planning and decision making.

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time.

PubMed

Limongi, Roberto; Silva, Angélica M

2016-11-01

The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production - where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

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 High-Order, Linear Time-Invariant Model for Application to Higher Harmonic Control and Flight Control System Interaction

NASA Technical Reports Server (NTRS)

Cheng, Rendy P.; Tischler, Mark B.; Celi, Roberto

2006-01-01

This research describes a new methodology for the extraction of a high-order, linear time invariant model, which allows the periodicity of the helicopter response to be accurately captured. This model provides the needed level of dynamic fidelity to permit an analysis and optimization of the AFCS and HHC algorithms. The key results of this study indicate that the closed-loop HHC system has little influence on the AFCS or on the vehicle handling qualities, which indicates that the AFCS does not need modification to work with the HHC system. However, the results show that the vibration response to maneuvers must be considered during the HHC design process, and this leads to much higher required HHC loop crossover frequencies. This research also demonstrates that the transient vibration responses during maneuvers can be reduced by optimizing the closed-loop higher harmonic control algorithm using conventional control system analyses.

Characterization of time-resolved fluorescence response measurements for distributed optical-fiber sensing.

PubMed

Sinchenko, Elena; Gibbs, W E Keith; Davis, Claire E; Stoddart, Paul R

2010-11-20

A distributed optical-fiber sensing system based on pulsed excitation and time-gated photon counting has been used to locate a fluorescent region along the fiber. The complex Alq3 and the infrared dye IR-125 were examined with 405 and 780 nm excitation, respectively. A model to characterize the response of the distributed fluorescence sensor to a Gaussian input pulse was developed and tested. Analysis of the Alq3 fluorescent response confirmed the validity of the model and enabled the fluorescence lifetime to be determined. The intrinsic lifetime obtained (18.2±0.9 ns) is in good agreement with published data. The decay rate was found to be proportional to concentration, which is indicative of collisional deactivation. The model allows the spatial resolution of a distributed sensing system to be improved for fluorophores with lifetimes that are longer than the resolution of the sensing system.

The overconstraint of response time models: rethinking the scaling problem.

PubMed

Donkin, Chris; Brown, Scott D; Heathcote, Andrew

2009-12-01

Theories of choice response time (RT) provide insight into the psychological underpinnings of simple decisions. Evidence accumulation (or sequential sampling) models are the most successful theories of choice RT. These models all have the same "scaling" property--that a subset of their parameters can be multiplied by the same amount without changing their predictions. This property means that a single parameter must be fixed to allow the estimation of the remaining parameters. In the present article, we show that the traditional solution to this problem has overconstrained these models, unnecessarily restricting their ability to account for data and making implicit--and therefore unexamined--psychological assumptions. We show that versions of these models that address the scaling problem in a minimal way can provide a better description of data than can their overconstrained counterparts, even when increased model complexity is taken into account.

System Identification and Verification of Rotorcraft UAVs

NASA Astrophysics Data System (ADS)

Carlton, Zachary M.

The task of a controls engineer is to design and implement control logic. To complete this task, it helps tremendously to have an accurate model of the system to be controlled. Obtaining a very accurate system model is not a trivial one, as much time and money is usually associated with the development of such a model. A typical physics based approach can require hundreds of hours of flight time. In an iterative process the model is tuned in such a way that it accurately models the physical system's response. This process becomes even more complicated for unstable and highly non-linear systems such as the dynamics of rotorcraft. An alternate approach to solving this problem is to extract an accurate model by analyzing the frequency response of the system. This process involves recording the system's responses for a frequency range of input excitations. From this data, an accurate system model can then be deduced. Furthermore, it has been shown that with use of the software package CIFER® (Comprehensive Identification from FrEquency Responses), this process can both greatly reduce the cost of modeling a dynamic system and produce very accurate results. The topic of this thesis is to apply CIFER® to a quadcopter to extract a system model for the flight condition of hover. The quadcopter itself is comprised of off-the-shelf components with a Pixhack flight controller board running open source Ardupilot controller logic. In this thesis, both the closed and open loop systems are identified. The model is next compared to dissimilar flight data and verified in the time domain. Additionally, the ESC (Electronic Speed Controller) motor/rotor subsystem, which is comprised of all the vehicle's actuators, is also identified. This process required the development of a test bench environment, which included a GUI (Graphical User Interface), data pre and post processing, as well as the augmentation of the flight controller source code. This augmentation of code allowed for proper data logging rates of all needed parameters.

Modelling and simulation of biased agonism dynamics at a G protein-coupled receptor.

PubMed

Bridge, L J; Mead, J; Frattini, E; Winfield, I; Ladds, G

2018-04-07

Theoretical models of G protein-coupled receptor (GPCR) concentration-response relationships often assume an agonist producing a single functional response via a single active state of the receptor. These models have largely been analysed assuming steady-state conditions. There is now much experimental evidence to suggest that many GPCRs can exist in multiple receptor conformations and elicit numerous functional responses, with ligands having the potential to activate different signalling pathways to varying extents-a concept referred to as biased agonism, functional selectivity or pluri-dimensional efficacy. Moreover, recent experimental results indicate a clear possibility for time-dependent bias, whereby an agonist's bias with respect to different pathways may vary dynamically. Efforts towards understanding the implications of temporal bias by characterising and quantifying ligand effects on multiple pathways will clearly be aided by extending current equilibrium binding and biased activation models to include G protein activation dynamics. Here, we present a new model of time-dependent biased agonism, based on ordinary differential equations for multiple cubic ternary complex activation models with G protein cycle dynamics. This model allows simulation and analysis of multi-pathway activation bias dynamics at a single receptor for the first time, at the level of active G protein (α GTP ), towards the analysis of dynamic functional responses. The model is generally applicable to systems with N G G proteins and N* active receptor states. Numerical simulations for N G =N * =2 reveal new insights into the effects of system parameters (including cooperativities, and ligand and receptor concentrations) on bias dynamics, highlighting new phenomena including the dynamic inter-conversion of bias direction. Further, we fit this model to 'wet' experimental data for two competing G proteins (G i and G s ) that become activated upon stimulation of the adenosine A 1 receptor with adenosine derivative compounds. Finally, we show that our model can qualitatively describe the temporal dynamics of this competing G protein activation. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

The BUMP model of response planning: intermittent predictive control accounts for 10 Hz physiological tremor.

PubMed

Bye, Robin T; Neilson, Peter D

2010-10-01

Physiological tremor during movement is characterized by ∼10 Hz oscillation observed both in the electromyogram activity and in the velocity profile. We propose that this particular rhythm occurs as the direct consequence of a movement response planning system that acts as an intermittent predictive controller operating at discrete intervals of ∼100 ms. The BUMP model of response planning describes such a system. It forms the kernel of Adaptive Model Theory which defines, in computational terms, a basic unit of motor production or BUMP. Each BUMP consists of three processes: (1) analyzing sensory information, (2) planning a desired optimal response, and (3) execution of that response. These processes operate in parallel across successive sequential BUMPs. The response planning process requires a discrete-time interval in which to generate a minimum acceleration trajectory to connect the actual response with the predicted future state of the target and compensate for executional error. We have shown previously that a response planning time of 100 ms accounts for the intermittency observed experimentally in visual tracking studies and for the psychological refractory period observed in double stimulation reaction time studies. We have also shown that simulations of aimed movement, using this same planning interval, reproduce experimentally observed speed-accuracy tradeoffs and movement velocity profiles. Here we show, by means of a simulation study of constant velocity tracking movements, that employing a 100 ms planning interval closely reproduces the measurement discontinuities and power spectra of electromyograms, joint-angles, and angular velocities of physiological tremor reported experimentally. We conclude that intermittent predictive control through sequential operation of BUMPs is a fundamental mechanism of 10 Hz physiological tremor in movement. Copyright © 2010 Elsevier B.V. All rights reserved.

Interval timing under a behavioral microscope: Dissociating motivational and timing processes in fixed-interval performance.

PubMed

Daniels, Carter W; Sanabria, Federico

2017-03-01

The distribution of latencies and interresponse times (IRTs) of rats was compared between two fixed-interval (FI) schedules of food reinforcement (FI 30 s and FI 90 s), and between two levels of food deprivation. Computational modeling revealed that latencies and IRTs were well described by mixture probability distributions embodying two-state Markov chains. Analysis of these models revealed that only a subset of latencies is sensitive to the periodicity of reinforcement, and prefeeding only reduces the size of this subset. The distribution of IRTs suggests that behavior in FI schedules is organized in bouts that lengthen and ramp up in frequency with proximity to reinforcement. Prefeeding slowed down the lengthening of bouts and increased the time between bouts. When concatenated, latency and IRT models adequately reproduced sigmoidal FI response functions. These findings suggest that behavior in FI schedules fluctuates in and out of schedule control; an account of such fluctuation suggests that timing and motivation are dissociable components of FI performance. These mixture-distribution models also provide novel insights on the motivational, associative, and timing processes expressed in FI performance. These processes may be obscured, however, when performance in timing tasks is analyzed in terms of mean response rates.

Effects of lesions to the left lateral prefrontal cortex on task-specific top-down biases and response strategies in blocked-cyclic naming.

PubMed

Belke, Eva

Anders, Riès, van Maanen and Alario put forward evidence accumulation modelling of object naming times as an alternative to neural network models of lexical retrieval. The authors exemplify their approach using data from the blocked-cyclic naming paradigm, requiring speakers to repeatedly name small sets of related or unrelated objects. The effects observed with this paradigm are understood reasonably well within the tradition of neural network modelling. However, implemented neural network models do not specify interfaces for task-specific top-down influences and response strategies that are likely to play a role in the blocked-cyclic naming paradigm, distinguishing it from continuous, non-cyclic manipulations of the naming context. I argue that the evidence accumulation approach falls short on this account as well, as it does not specify the potential contribution of task-specific top-down processes and strategic facilitation effects to the response time distributions. Future endeavours to model or fit data from blocked-cyclic naming experiments should strive to do so by simultaneously considering data from continuous context manipulations.

Structural-Vibration-Response Data Analysis

NASA Technical Reports Server (NTRS)

Smith, W. R.; Hechenlaible, R. N.; Perez, R. C.

1983-01-01

Computer program developed as structural-vibration-response data analysis tool for use in dynamic testing of Space Shuttle. Program provides fast and efficient time-domain least-squares curve-fitting procedure for reducing transient response data to obtain structural model frequencies and dampings from free-decay records. Procedure simultaneously identifies frequencies, damping values, and participation factors for noisy multiple-response records.

Thermo-mechanical concepts applied to modeling liquid propellant rocket engine stability

NASA Astrophysics Data System (ADS)

Kassoy, David R.; Norris, Adam

2016-11-01

The response of a gas to transient, spatially distributed energy addition can be quantified mathematically using thermo-mechanical concepts available in the literature. The modeling demonstrates that the ratio of the energy addition time scale to the acoustic time scale of the affected volume, and the quantity of energy added to that volume during the former determine the whether the responses to heating can be described as occurring at nearly constant volume, fully compressible or nearly constant pressure. Each of these categories is characterized by significantly different mechanical responses. Application to idealized configurations of liquid propellant rocket engines provides an opportunity to identify physical conditions compatible with gasdynamic disturbances that are sources of engine instability. Air Force Office of Scientific Research.

Developing AN Emergency Response Model for Offshore Oil Spill Disaster Management Using Spatial Decision Support System (sdss)

NASA Astrophysics Data System (ADS)

Balogun, Abdul-Lateef; Matori, Abdul-Nasir; Wong Toh Kiak, Kelvin

2018-04-01

Environmental resources face severe risks during offshore oil spill disasters and Geographic Information System (GIS) Environmental Sensitivity Index (ESI) maps are increasingly being used as response tools to minimize the huge impacts of these spills. However, ESI maps are generally unable to independently harmonize the diverse preferences of the multiple stakeholders' involved in the response process, causing rancour and delay in response time. This paper's Spatial Decision Support System (SDSS) utilizes the Analytic Hierarchy Process (AHP) model to perform tradeoffs in determining the most significant resources to be secured considering the limited resources and time available to perform the response operation. The AHP approach is used to aggregate the diverse preferences of the stakeholders and reach a consensus. These preferences, represented as priority weights, are incorporated in a GIS platform to generate Environmental sensitivity risk (ESR) maps. The ESR maps provide a common operational platform and consistent situational awareness for the multiple parties involved in the emergency response operation thereby minimizing discord among the response teams and saving the most valuable resources.

Step-off, vertical electromagnetic responses of a deep resistivity layer buried in marine sediments

NASA Astrophysics Data System (ADS)

Jang, Hangilro; Jang, Hannuree; Lee, Ki Ha; Kim, Hee Joon

2013-04-01

A frequency-domain, marine controlled-source electromagnetic (CSEM) method has been applied successfully in deep water areas for detecting hydrocarbon (HC) reservoirs. However, a typical technique with horizontal transmitters and receivers requires large source-receiver separations with respect to the target depth. A time-domain EM system with vertical transmitters and receivers can be an alternative because vertical electric fields are sensitive to deep resistive layers. In this paper, a time-domain modelling code, with multiple source and receiver dipoles that are finite in length, has been written to investigate transient EM problems. With the use of this code, we calculate step-off responses for one-dimensional HC reservoir models. Although the vertical electric field has much smaller amplitude of signal than the horizontal field, vertical currents resulting from a vertical transmitter are sensitive to resistive layers. The modelling shows a significant difference between step-off responses of HC- and water-filled reservoirs, and the contrast can be recognized at late times at relatively short offsets. A maximum contrast occurs at more than 4 s, being delayed with the depth of the HC layer.

The Use of Piecewise Growth Models to Estimate Learning Trajectories and RtI Instructional Effects in a Comparative Interrupted Time-Series Design

ERIC Educational Resources Information Center

Zvoch, Keith

2016-01-01

Piecewise growth models (PGMs) were used to estimate and model changes in the preliteracy skill development of kindergartners in a moderately sized school district in the Pacific Northwest. PGMs were applied to interrupted time-series (ITS) data that arose within the context of a response-to-intervention (RtI) instructional framework. During the…

Modeling human vestibular responses during eccentric rotation and off vertical axis rotation

NASA Technical Reports Server (NTRS)

Merfeld, D. M.; Paloski, W. H. (Principal Investigator)

1995-01-01

A mathematical model has been developed to help explain human multi-sensory interactions. The most important constituent of the model is the hypothesis that the nervous system incorporates knowledge of sensory dynamics into an "internal model" of these dynamics. This internal model allows the nervous system to integrate the sensory information from many different sensors into a coherent estimate of self-motion. The essence of the model is unchanged from a previously published model of monkey eye movement responses; only a few variables have been adjusted to yield the prediction of human responses. During eccentric rotation, the model predicts that the axis of eye rotation shifts slightly toward alignment with gravito-inertial force. The model also predicts that the time course of the perception of tilt following the acceleration phase of eccentric rotation is much slower than that during deceleration. During off vertical axis rotation (OVAR) the model predicts a small horizontal bias along with small horizontal, vertical, and torsional oscillations. Following OVAR stimulation, when stopped right- or left-side down, a small vertical component is predicted that decays with the horizontal post-rotatory response. All of the predictions are consistent with measurements of human responses.

Simulating the Thermal Response of High Explosives on Time Scales of Days to Microseconds

NASA Astrophysics Data System (ADS)

Yoh, Jack J.; McClelland, Matthew A.

2004-07-01

We present an overview of computational techniques for simulating the thermal cookoff of high explosives using a multi-physics hydrodynamics code, ALE3D. Recent improvements to the code have aided our computational capability in modeling the response of energetic materials systems exposed to extreme thermal environments, such as fires. We consider an idealized model process for a confined explosive involving the transition from slow heating to rapid deflagration in which the time scale changes from days to hundreds of microseconds. The heating stage involves thermal expansion and decomposition according to an Arrhenius kinetics model while a pressure-dependent burn model is employed during the explosive phase. We describe and demonstrate the numerical strategies employed to make the transition from slow to fast dynamics.

Modulation of Temporal Precision in Thalamic Population Responses to Natural Visual Stimuli

PubMed Central

Desbordes, Gaëlle; Jin, Jianzhong; Alonso, Jose-Manuel; Stanley, Garrett B.

2010-01-01

Natural visual stimuli have highly structured spatial and temporal properties which influence the way visual information is encoded in the visual pathway. In response to natural scene stimuli, neurons in the lateral geniculate nucleus (LGN) are temporally precise – on a time scale of 10–25 ms – both within single cells and across cells within a population. This time scale, established by non stimulus-driven elements of neuronal firing, is significantly shorter than that of natural scenes, yet is critical for the neural representation of the spatial and temporal structure of the scene. Here, a generalized linear model (GLM) that combines stimulus-driven elements with spike-history dependence associated with intrinsic cellular dynamics is shown to predict the fine timing precision of LGN responses to natural scene stimuli, the corresponding correlation structure across nearby neurons in the population, and the continuous modulation of spike timing precision and latency across neurons. A single model captured the experimentally observed neural response, across different levels of contrasts and different classes of visual stimuli, through interactions between the stimulus correlation structure and the nonlinearity in spike generation and spike history dependence. Given the sensitivity of the thalamocortical synapse to closely timed spikes and the importance of fine timing precision for the faithful representation of natural scenes, the modulation of thalamic population timing over these time scales is likely important for cortical representations of the dynamic natural visual environment. PMID:21151356

Spatially distributed storm runoff modeling using remote sensing and geographic information systems

NASA Astrophysics Data System (ADS)

Melesse, Assefa Mekonnen

Advances in scientific knowledge and new techniques of remote sensing permit a better understanding of the physical land features governing hydrologic processes, and make possible efficient, large-scale hydrologic modeling. The need for land-cover and hydrologic response change detection at a larger scale and at times of the year when hydrologic studies are critical makes satellite imagery the most cost effective, efficient and reliable source of data. The use of a Geographic Information System (GIS) to store, manipulate and visualize these data, and ultimately to estimate runoff from watersheds, has gained increasing attention in recent years. In this work, remotely-sensed data and GIS tools were used to estimate the changes in land-cover, and to estimate runoff response, for three watersheds (Etonia, Econlockhatchee, and S-65A sub-basins) in Florida. Land-use information from Digital Orthophoto Quarter Quadrangles (DOQQ), Landsat Thematic Mapper (TM), and Enhanced Thematic Mapper Plus (ETM+) were analyzed for the years 1973, 1984, 1990, 1995, and 2000. Spatial distribution of land-cover was assessed over time. The corresponding infiltration excess runoff response of the study areas due to these changes was estimated using the United States Department of Agriculture, Natural Resources Conservation Service Curve Number (USDA-NRCS-CN) method. A Digital Elevation Model (DEM)-GIS technique was developed to predict stream response to runoff events based on the travel time from each grid cell to the watershed outlet. The method was tested on a representative watershed (Simms Creek) in the Etonia sub-basin. Simulated and observed runoff volume and hydrographs were compared for 17 storm events. Isolated storms, with volumes of not less than 12.75 mm (0.5 inch) were selected. This is the minimum amount of rainfall volume recommended for the NRCS-CN method. Results show that the model predicts the runoff response of the study area with an average efficiency of 57%. Comparison of the runoff prediction to Snyder's synthetic Unit hydrograph method and TOPMODEL shows the spatially distributed infiltration excess travel time model performs better than both the Snyder's method and TOPMODEL. The model is applicable to ungaged watersheds and useful for predicting runoff hydrographs resulting from changes in the land-cover.

Designing seasonal initial attack resource deployment and dispatch rules using a two-stage stochastic programming procedure

Treesearch

Yu Wei; Michael Bevers; Erin J. Belval

2015-01-01

Initial attack dispatch rules can help shorten fire suppression response times by providing easy-to-follow recommendations based on fire weather, discovery time, location, and other factors that may influence fire behavior and the appropriate response. A new procedure is combined with a stochastic programming model and tested in this study for designing initial attack...

Adolescent RSA Responses during an Anger Discussion Task: Relations to Emotion Regulation and Adjustment

PubMed Central

Cui, Lixian; Morris, Amanda Sheffield; Harrist, Amanda W.; Larzelere, Robert E.; Criss, Michael M.; Houltberg, Benjamin J.

2015-01-01

The current study examined associations between adolescent respiratory sinus arrhythmia (RSA) during an angry event discussion task and adolescents’ emotion regulation and adjustment. Data were collected from 206 adolescents (10–18 years old, M age = 13.37). Electrocardiogram (ECG) and respiration data were collected from adolescents, and RSA values and respiration rates were computed. Adolescents reported on their own emotion regulation, prosocial behavior, and aggressive behavior. Multi-level latent growth modeling was employed to capture RSA responses across time (i.e., linear and quadratic changes; time course approach), and adolescent emotion regulation and adjustment variables were included in the model to test their links to RSA responses. Results indicated that high RSA baseline was associated with more adolescent prosocial behavior. A pattern of initial RSA decreases (RSA suppression) in response to angry event recall and subsequent RSA increases (RSA rebound) were related to better anger and sadness regulation and more prosocial behavior. However, RSA was not significantly linked to adolescent aggressive behavior. We also compared the time course approach with the conventional linear approach and found that the time course approach provided more meaningful and rich information. The implications of adaptive RSA change patterns are discussed. PMID:25642723

Predicting vertically-nonsequential wetting patterns with a source-responsive model

USGS Publications Warehouse

Nimmo, John R.; Mitchell, Lara

2013-01-01

Water infiltrating into soil of natural structure often causes wetting patterns that do not develop in an orderly sequence. Because traditional unsaturated flow models represent a water advance that proceeds sequentially, they fail to predict irregular development of water distribution. In the source-responsive model, a diffuse domain (D) represents flow within soil matrix material following traditional formulations, and a source-responsive domain (S), characterized in terms of the capacity for preferential flow and its degree of activation, represents preferential flow as it responds to changing water-source conditions. In this paper we assume water undergoing rapid source-responsive transport at any particular time is of negligibly small volume; it becomes sensible at the time and depth where domain transfer occurs. A first-order transfer term represents abstraction from the S to the D domain which renders the water sensible. In tests with lab and field data, for some cases the model shows good quantitative agreement, and in all cases it captures the characteristic patterns of wetting that proceed nonsequentially in the vertical direction. In these tests we determined the values of the essential characterizing functions by inverse modeling. These functions relate directly to observable soil characteristics, rendering them amenable to evaluation and improvement through hydropedologic development.

Item Response Theory Models for Performance Decline during Testing

ERIC Educational Resources Information Center

Jin, Kuan-Yu; Wang, Wen-Chung

2014-01-01

Sometimes, test-takers may not be able to attempt all items to the best of their ability (with full effort) due to personal factors (e.g., low motivation) or testing conditions (e.g., time limit), resulting in poor performances on certain items, especially those located toward the end of a test. Standard item response theory (IRT) models fail to…

Children Are Not like Older Adults: A Diffusion Model Analysis of Developmental Changes in Speeded Responses

ERIC Educational Resources Information Center

Ratcliff, Roger; Love, Jessica; Thompson, Clarissa A.; Opfer, John E.

2012-01-01

Children (n = 130; M[subscript age] = 8.51-15.68 years) and college-aged adults (n = 72; M[subscript age] = 20.50 years) completed numerosity discrimination and lexical decision tasks. Children produced longer response times (RTs) than adults. R. Ratcliff's (1978) diffusion model, which divides processing into components (e.g., quality of…

Groundwater dynamics mediate low-flow response to global warming in snow-dominated alpine regions

Treesearch

Christina Tague; Gordon E. Grant

2009-01-01

In mountain environments, spatial and temporal patterns of snow accumulation and melt are dominant controls on hydrologic responses to climate change. In this paper, we develop a simple conceptual model that links the timing of peak snowmelt with geologically mediated differences in rate of streamflow recession. This model demonstrates that within the western United...

Screening of the aerodynamic and biophysical properties of barley malt

NASA Astrophysics Data System (ADS)

Ghodsvali, Alireza; Farzaneh, Vahid; Bakhshabadi, Hamid; Zare, Zahra; Karami, Zahra; Mokhtarian, Mohsen; Carvalho, Isabel. S.

2016-10-01

An understanding of the aerodynamic and biophysical properties of barley malt is necessary for the appropriate design of equipment for the handling, shipping, dehydration, grading, sorting and warehousing of this strategic crop. Malting is a complex biotechnological process that includes steeping; germination and finally, the dehydration of cereal grains under controlled temperature and humidity conditions. In this investigation, the biophysical properties of barley malt were predicted using two models of artificial neural networks as well as response surface methodology. Stepping time and germination time were selected as the independent variables and 1 000 kernel weight, kernel density and terminal velocity were selected as the dependent variables (responses). The obtained outcomes showed that the artificial neural network model, with a logarithmic sigmoid activation function, presents more precise results than the response surface model in the prediction of the aerodynamic and biophysical properties of produced barley malt. This model presented the best result with 8 nodes in the hidden layer and significant correlation coefficient values of 0.783, 0.767 and 0.991 were obtained for responses one thousand kernel weight, kernel density, and terminal velocity, respectively. The outcomes indicated that this novel technique could be successfully applied in quantitative and qualitative monitoring within the malting process.

Model under-representation of decadal Pacific trade wind trends and its link to tropical Atlantic bias

NASA Astrophysics Data System (ADS)

Kajtar, Jules B.; Santoso, Agus; McGregor, Shayne; England, Matthew H.; Baillie, Zak

2018-02-01

The strengthening of the Pacific trade winds in recent decades has been unmatched in the observational record stretching back to the early twentieth century. This wind strengthening has been connected with numerous climate-related phenomena, including accelerated sea-level rise in the western Pacific, alterations to Indo-Pacific ocean currents, increased ocean heat uptake, and a slow-down in the rate of global-mean surface warming. Here we show that models in the Coupled Model Intercomparison Project phase 5 underestimate the observed range of decadal trends in the Pacific trade winds, despite capturing the range in decadal sea surface temperature (SST) variability. Analysis of observational data suggests that tropical Atlantic SST contributes considerably to the Pacific trade wind trends, whereas the Atlantic feedback in coupled models is muted. Atmosphere-only simulations forced by observed SST are capable of recovering the time-variation and the magnitude of the trade wind trends. Hence, we explore whether it is the biases in the mean or in the anomalous SST patterns that are responsible for the under-representation in fully coupled models. Over interannual time-scales, we find that model biases in the patterns of Atlantic SST anomalies are the strongest source of error in the precipitation and atmospheric circulation response. In contrast, on decadal time-scales, the magnitude of the model biases in Atlantic mean SST are directly linked with the trade wind variability response.

HOW TO MODEL HYDRODYNAMICS AND RESIDENCE TIMES OF 27 ESTUARIES IN 4 MONTHS

EPA Science Inventory

The hydrodynamics and residence times of 27 embayments were modeled during the first year of a project whose goal is to define the relation between nitrogen loadings and ecological responses of 44 systems that range from small to the size of Narragansett Bay and Buzzards Bay. The...

EFFECT OF RESIDENCE TIME ON ANNUAL EXPORT AND DENITRIFICATION OF NITROGEN IN ESTUARIES: A MODEL ANALYSIS

EPA Science Inventory

A simple model of annual average response of an estuary to mean nitrogen loading rate and freshwater residence time was developed and tested. It uses nitrogen inputs from land, deposition from the atmosphere, and first-order calculations of internal loss rate and export to perfor...

A Rescorla-Wagner drift-diffusion model of conditioning and timing

PubMed Central

Alonso, Eduardo

2017-01-01

Computational models of classical conditioning have made significant contributions to the theoretic understanding of associative learning, yet they still struggle when the temporal aspects of conditioning are taken into account. Interval timing models have contributed a rich variety of time representations and provided accurate predictions for the timing of responses, but they usually have little to say about associative learning. In this article we present a unified model of conditioning and timing that is based on the influential Rescorla-Wagner conditioning model and the more recently developed Timing Drift-Diffusion model. We test the model by simulating 10 experimental phenomena and show that it can provide an adequate account for 8, and a partial account for the other 2. We argue that the model can account for more phenomena in the chosen set than these other similar in scope models: CSC-TD, MS-TD, Learning to Time and Modular Theory. A comparison and analysis of the mechanisms in these models is provided, with a focus on the types of time representation and associative learning rule used. PMID:29095819

Terrestrial Ecosystem Science 2017 ECRP Annual Report: Tropical Forest Response to a Drier Future: Turnover Times of Soil Organic Matter, Roots, Respired CO 2, and CH 4 Across Moisture Gradients in Time and Space

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

McFarlane, Karis J.

The overall goal of my Early Career research is to constrain belowground carbon turnover times for tropical forests across a broad range in moisture regimes. My group is using 14C analysis and modeling to address two major objectives: quantify age and belowground carbon turnover times across tropical forests spanning a moisture gradient from wetlands to dry forest; and identify specific areas for focused model improvement and data needs through site-specific model-data comparison and belowground carbon modeling for tropic forests.